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There is great interest in the dynamics of health behaviors in social networks and how they affect collective public health outcomes , but measuring population health behaviors over time and space requires substantial resources . Here , we use publicly available data from 101 , 853 users of online social media collected over a time period of almost six months to measure the spatio-temporal sentiment towards a new vaccine . We validated our approach by identifying a strong correlation between sentiments expressed online and CDC-estimated vaccination rates by region . Analysis of the network of opinionated users showed that information flows more often between users who share the same sentiments - and less often between users who do not share the same sentiments - than expected by chance alone . We also found that most communities are dominated by either positive or negative sentiments towards the novel vaccine . Simulations of infectious disease transmission show that if clusters of negative vaccine sentiments lead to clusters of unprotected individuals , the likelihood of disease outbreaks is greatly increased . Online social media provide unprecedented access to data allowing for inexpensive and efficient tools to identify target areas for intervention efforts and to evaluate their effectiveness .
Outbreaks of vaccine preventable diseases are a major public health issue . Outbreaks are more likely to occur if either overall vaccination rates decline [1] , or if communities with very low vaccination rates increase in frequency or size [2] , [3] . As individual health behaviors appear to be modulated by social networks [4] , [5] , there is great interest in the dynamics of health behaviors in social networks [6] . Furthermore , measuring health behaviors - such as vaccination - in populations over time and space is essential to identify target areas for interventions and evaluate their effectiveness , but it is generally labor-intensive and expensive when based on traditional survey methodologies [7] . The rise of online social media in the past few years has created new possibilities of measuring health behavior . Such services are used by hundreds of millions of people who are publicly sharing various aspects about their daily lives , including those related to health behavior[8] , [9] . Using such data to gauge health behaviors in populations represents a fundamental shift in measurement methodology because the study population is not responding to a survey , but rather shares data in a survey-free context , often in real time . The power of using web data to track events in real time in the context of public health has recently been demonstrated for influenza surveillance [10] , [11] , but assessing health behavior has so far remained elusive . Here , we used publicly available short text messages collected from an online social service ( Twitter ) from August 2009 to January 2010 in the United States . During this time , pandemic influenza A ( H1N1 ) was spreading nationwide but a vaccine became widely available only very late in the year . We collected practically all publicly available text messages on Twitter ( so called “tweets” ) containing English keywords relating to vaccination as well as location information provided by the authors of text messages ( if available ) . We also collected information on who followed whom among the authors , which allowed us to recreate a directed network of information flow . A subset of the collected tweets was manually evaluated as expressing a negative , positive or neutral sentiment towards influenza A ( H1N1 ) vaccination . We then trained a machine learning algorithm on the manually rated tweets , and then used the resulting classifier to automatically predict sentiments for the remaining unrated text messages . The fully classified data set allowed us to calculate a temporal , localized influenza A ( H1N1 ) vaccination sentiment score and to generate a network of information flow which allowed us to study its properties with respect to the distribution of sentiments . Finally , by extrapolating the findings to empirical contact networks relevant for infectious disease spread , we investigate the effect of non-random vaccination distributions on the likelihood of disease outbreaks .
Overall , of the 477 , 768 collected tweets , 318 , 379 were classified as relevant to the influenza A ( H1N1 ) vaccine . Of those , 255 , 828 were classified as neutral , 26 , 667 as negative , and 35 , 884 as positive . Starting from late August 2009 , we observed a steady increase in the number of relevant tweets in the United States until early November 2009 , after which the number of tweets dropped back to previous levels . Figure 1A shows the absolute numbers of positive ( n+ ) , negative ( n- ) and neutral ( n0 ) tweets per day in the United States . The overall influenza A ( H1N1 ) vaccine sentiment score , measured as the relative difference of positive and negative tweets ( ( n+-n- ) / ( n++ n- + n0 ) ) , started at a negative value in late Summer 2009 and showed relatively large short term fluctuations . The 14 day - moving average turned positive in mid October ( as the vaccine became available ) and remained positive for the rest of the year ( Figure 1B ) . For vaccination sentiments measured online to be meaningful , they need to be compared to empirical data for validation . A positive correlation between the influenza A ( H1N1 ) vaccination sentiment score and estimated vaccination coverage would be relevant to public health efforts because it would allow for the identification of target areas for communication interventions . To test for such a correlation , we used estimated influenza A ( H1N1 ) vaccination rates up to January 2010 as provided by the CDC [12] . These estimates are based on results from the Behavioral Risk Factor Surveillance System ( BRFSS ) and the National 2009 H1N1 Flu Survey ( NHFS ) . We found a very strong correlation on the level of HHS regions ( weighted r = 0 . 78 , p = 0 . 017; regions as defined by the US Department of Health & Human Services ) using the estimated vaccination coverages for all persons older than 6 months ( Figure 1C ) , and a strong correlation at the level of state ( weighted r = 0 . 52 , p = 0 . 0046 ) . All reported correlation values are Pearson product-moment correlation coefficients because the variables considered for analysis are normally distributed ( Shapiro-Wilk test and Anderson-Darling test ) , weighted by the total number of tweets ( n+ + n- + n0 ) per region . Using data on who followed whom among users in the dataset allows us to generate a directed network of information flow whose structure ( with respect to the distribution of opinions on vaccination ) can provide insight into how sentiments are distributed ( see Methods ) . In order to investigate if users preferentially seek information from other users who share their opinion , we measured assortative mixing of users with a qualitatively similar opinion on vaccination ( homophily ) by calculating the assortativity coefficient r which is defined [13] as where and eij is the fraction of edges in the network that connect a node of type i to one of type j ( in the direction of i to j ) . A positive value of r ( with maximum value 1 ) is found in a network where nodes are predominantly connected to nodes of the same type . A value of r = 0 would indicate a randomly mixed network , and a negative value ≤ -1 would indicate a disassortative network where nodes of one type are predominantly connected to nodes of the other type ( for the technical reasons why the minimum value of r is not always -1 see ref . [13] ) . In the network of 39 , 284 users who had a non-zero sentiment score ( from now on referred to as the opinionated network , i . e . containing only users who expressed predominantly either positive or negative opinions ) , we find r = 0 . 144 . In order to assess the significance of this value , we randomized the opinions on the network ( bootstrap with replacement ) 10 , 000 times and found the maximum value for r among these randomized networks to be 0 . 0056 , more than an order of magnitude lower than in the original network ( mean: -3*10-4 , 95% CI: -0 . 0032 , 0 . 0027 ) . We also calculated for each node ( user ) the fraction f of incoming edges from nodes with the same qualitative sentiment , then randomized the opinions and compared the new distribution of f to the original distribution . For 10 , 000 randomized networks we found that in all cases the mean of the original distribution ( 0 . 601 ) was significantly larger than the mean of the distribution of the randomized networks ( p<10-95 for all tests using paired Wilcoxon signed rank test , max . mean: 0 . 548 , mean of means: 0 . 531 , 95% CI: 0 . 52 , 0 . 541 ) . These results demonstrate that there is significantly more information flow between users who share the same sentiments than expected based on the distribution of sentiments . Social networks often naturally divide into communities , i . e groups of people who share common interests , beliefs and opinions . In a network of opinionated users , the question of community structure naturally arises , i . e . are there communities within the network where positive or negative attitudes towards the novel vaccine dominate ? In order to tackle this question , we separated the giant component of the opinionated network ( 34 , 025 users ) into communities of users that are densely connected compared to the rest of the network using the spin glass community detection algorithm [14] . We then calculated the proportion of users with negative attitudes p ( - ) and compared it to the average in the giant component , p ( - ) = 0 . 396 . With the exception of a single community , all communities ( containing at least 1% of the users in the entire network ) were significantly more positive or negative than expected ( Figure 2; Fisher's exact test , 10-279<p<10-6 ) , ranging from p ( - ) = 0 . 764 in the most negative community ( 2 , 453 users ) to p ( - ) = 0 . 266 in the most positive community ( 2 , 517 users ) . Non-random distributions of opinions on vaccines can have a profound effect on the likelihood of disease outbreaks if this distribution leads to a clustered distribution of vaccination status in the population [2] . Communities with very low vaccination rates are not protected by herd immunity even if the overall vaccination rate in the population is high . To quantify this effect , we used a recently collected high-resolution contact network relevant for infectious disease transmission [15] to simulate the spread of influenza A ( H1N1 ) . We performed simulations as described previously [15] with a constant vaccination rate but varying levels of assortativity ( see Methods ) . Figure 2B shows that the probability of large outbreaks is greatly increased when susceptibility to disease is positively assorted . The probability of an outbreak that infects >5% of the population , for example , can be increased more than 10-fold at r>0 . 14 ( as observed in the Twitter network ) relative to the random distribution where r ∼0 ( Figure 2C ) .
Immunization is generally considered one of the greatest public health achievements in human history [16] . Globally , vaccines have dramatically reduced morbidity and mortality caused by infectious diseases , and vaccines continue to prevent or mitigate the spread of infectious diseases . Despite these resounding successes , however , maintaining sufficiently high vaccination coverages has become very challenging in recent years [1] , [3] . Unsubstantiated concerns over the safety of vaccines , the rise of the internet and its effect on how fast rumors and misinformation can spread , and a general sense of security from infectious diseases have all contributed to a situation where individual concerns about potential negative side effects often outweigh the benefits of immunization [17] . We've shown here that in a network of almost 40 , 000 opinionated users of an online social media service , there was significantly more information flow between users who shared the same sentiments than expected if the sentiments were randomly distributed . We also found that most communities were dominated by either positive or negative sentiments towards the novel vaccine . Our data do not allow us to say whether links of information flow were created because of similar vaccination sentiments , or whether other factors , including those that strongly correlate with vaccination sentiments , were responsible for link creation in the first place . Either way , however , the significantly positive assortativity of negative and positive sentiments provide evidence that online social media can act as an “echo chamber” where personal opinions that affect individual medical decisions are predominately reaffirmed by others . We've also shown that if network clusters of similar sentiments towards vaccination lead to network clusters in the distribution of vaccination , the probability of large outbreaks is greatly increased . Importantly , this effect is strongest when the levels of vaccination coverage are near the levels of required herd immunity under the assumption of a random distribution [2] , [18] . We do not assume that online social networks strongly overlap with contact networks relevant to infectious disease in the real world , but the extent of homophily may very well be quite similar in both networks ( or even lower in online networks such as Twitter where links need not be reciprocated ) . Indeed , there is increasing evidence from multiple studies that there is significant geographic and social clustering of non-medical vaccination exemptions , resulting in increases in local risk of vaccine-preventable disease outbreaks [3] , [19]-[21] . Communication strategies that aim to decrease the positively assorted distribution of vaccination might thus be an efficient way - in addition to existing efforts to increase general vaccination rates in the population - to decrease the risk of disease outbreaks . Currently , empirical data on assortativity in vaccination status is lacking , but collecting such data would be desirable in order to identify the communities which are at highest risk . While data from online social media offers great potential to measure health behaviors , and even measure human behavior more generally , a number of caveats need to be mentioned . First , because of the observational nature of the study , we cannot exclude that other confounding factors ( e . g . vaccine supply ) might have influenced the results . Second , extracting information from short online text messages for the purpose of assessing health behaviors presents a number of challenges . Users of online social media might not be a representative sample of the population; text messages may be interpreted differently by different users , and sentiment analysis is not 100% accurate ( see also Methods ) . However , the large volume of data - and the large number of users - substantially reduce the extent to which such limitations affect the overall results . Furthermore , data from online social media have a number of advantages that other data cannot provide . The fact that social media provide network data - i . e . the data do not only contain what is being broadcast , but also to whom - allows us to study processes such as the spread of information , behaviors , opinions , etc . as well as the social structure on which these processes occur . A particular benefit of Twitter data is that they are publicly available - tweets are by default public messages , unlike messages exchanged on other social media services that are generally private by default . This is important because the potential of computational social sciences to understand the dynamics of human societies cannot be fully explored if all data are private and owned by companies and governments [22] . Publicly available data from online social media provide unprecedented opportunities , especially in the realm of public health , e . g . by allowing for inexpensive and efficient tools for the public health community to identify regional areas that would most benefit from intensified communication about the safety and benefit of vaccines . Given the explosive growth of online social media in the past few years , we believe the approach presented here can be applied more generally to study the spread of various health behaviors , a topic of great importance as health behaviors are a leading cause of morbidity and mortality [23] .
Starting on August 25th 2009 , we collected all tweets in English containing at least one of the following search strings: vaccination OR vaccine OR vaccinated OR vaccinate OR vaccinating OR immunized OR immunize OR immunization OR immunizing . Along with the tweet text , we downloaded the date and time when the tweet was published , and the location of the user ( if provided ) . We also downloaded the user id , follower ids , and friends ids . The followers of a user A are those users who will receive messages from user A . The friends of a user A are those users from whom user A receives messages . Thus , information flows from a user to his followers . Until January 19th 2010 , we collected tweets every day in real time . Barring occasional short term disruptions due to technical issues , the data set represents the set of tweets meeting the keyword conditions mentioned above in that timeframe . Each tweet in the dataset needed to be classified into one of four sentiment polarities: positive , negative , neutral and irrelevant ( see below ) . Since the dataset of 477 , 768 tweets was too large to classify manually in a reasonable time frame , we used a machine learning approach to identifying the sentiments expressed in the tweets . This process involved choosing a machine learning algorithm , selecting features of the input and considering other strategies for maximizing the accuracy of the sentiment analysis . We evaluated various classifiers and experimented with different feature sets in order to select the most accurate combination . We compared three standard classification algorithms: Naive Bayes , Maximum Entropy and a Dynamic Language Model classifier ( using process character n-gram models ) . The Naive Bayes classifier was implemented using the Natural Language Toolkit ( NLTK ) [24] . The Maximum Entropy classifier was accessed using NLTK , but used the MegaM ( http://www . cs . utah . edu/~hal/megam/ ) implementation . The Language Model classifier was implemented using LingPipe ( http://www . alias-i . com/lingpipe/ ) and is recommended in the LingPipe documentation for sentiment analysis . Supervised machine learning approaches , regardless of algorithm used , all require a training dataset . In order to create a training dataset , we needed people to assign sentiment polarities to a random subset of tweets from our database . Study participants ( “students” from now on ) were recruited from two undergraduate classes at the Pennsylvania State University to rate tweets with the help of a simple web-based rating application . Students were asked to rate tweets based on the following question: what sentiment does the tweeting person ( the author ) have regarding the influenza A ( H1N1 ) vaccine ? They were presented with four options: 1 . positive: A positive sentiment means the author is likely to get the influenza A ( H1N1 ) vaccine . Example tweet that was rated as positive: off to get swine flu vaccinated before work . 2 . negative: A negative sentiment means the author is unlikely to get the influenza A ( H1N1 ) vaccine . Example tweet that was rated as negative: What Can You Do To Resist The U . S . H1N1 "Vaccination" Program ? Help Get Word Out . The H1N1 "Vaccine" Is DIRTY . DontGetIt . 3 . neutral: No clear sentiment can be detected . Example tweet that was rated as neutral: The Health Department will be offering the seasonal flu vaccine for children 6 months - 19 yrs . of age starting on Monday , Nov . 16 . 4 . irrelevant: The tweet is not clearly about the influenza A ( H1N1 ) vaccine . Example tweet that was rated as irrelevant: Filipino discovers new vaccine against malaria that 'treats' the mosquitoes , too ! The web-based rating application was set up such that every other tweet rated by a student was one that was also rated by all the other students . All other tweets were randomly selected . A student could not rate any tweet more than once , but we did not prevent multiple students from rating the same randomly selected tweet . 64 students volunteered for the task , and submitted 88 , 237 ratings . Students were assigned to rate at least 1400 tweets , and 44 students complied with this request ( and received extra course credit - the other 20 students rated less than 1400 tweets ) . In total , students evaluated 47 , 143 unique tweets . To evaluate the best classifier , we divided the feature sets extracted from the manually rated tweets into a training set and a test set . The classifiers were evaluated by looking at the percentage of tweets from the test set that classifiers could rate accurately . A tweet was considered accurately rated if the sentiment polarity predicted by the classifier matched majority opinion as assigned by the students . In order to build a high confidence test set , we took all tweets with at least 44 ratings , and then eliminated tweets where both of the following were true: a ) the percentage of the majority sentiment polarity was not higher than 50% , i . e . an absolute majority could not be established , and b ) we ( i . e . MS and SK ) disagreed with the majority sentiment polarity . This left us with a high confidence test set of 630 tweets . The training set ( 46 , 442 tweets ) consisted of all the tweets that had less than 44 ratings . For our sentiment classification , we used an ensemble method combining the Naive Bayes and the Maximum Entropy classifiers . We used the Naive Bayes classifier to determine the positive and negative tweets , and the Maximum Entropy classifier to determine the neutral and irrelevant tweets ( leveraging the classifiers' respective strengths ) . In case of a conflict , the Maximum Entropy classifier's decision was final . The accuracy of this ensemble classifier was 84 . 29% . Feature selection is the process of choosing the most informative subset of all the possible features of the training data . Choosing the right features to extract from a tweet is a process of trial and error . We achieved the highest accuracy ( for both classifiers ) by choosing the set of words constructed from the tweets after filtering out stop words defined by Apache Lucerne's list of stop words ( http://lucene . apache . org/ - stop words from: org . apache . lucene . analysis . StopAnalyzer ) except “no” and “not” . We further filtered out all punctuation except for ‘ ! ’ from the tweet text since exclamation marks are often used to indicate a stronger sentiment . Finally , adding stemming improved the accuracy of the classifier . The challenge of trying to classify tweets is that each tweet is at maximum only 140 characters . This limitation encourages non-standard abbreviations , slang and otherwise poorly written phrases within the body of a tweet . The general lack of context in a single tweet combined with poorly expressed sentiment means that it is unreasonable to expect a 100% accuracy out of the automated classifiers or even 100% agreement among students . To get a sense of how our automated classifier was performing , we compared it to the accuracy of individual students . Among students that rated at least 1400 tweets , the average accuracy of the students was 64% . Only 7 students had a higher accuracy than the ensemble classifier , the highest being 90% . To ensure the highest quality during classification of tweets not rated by students , we implemented the following strategy . Tweets that were part of the test set didn't need to be evaluated by the classifier since we were confident about the assigned polarities . For all other tweets , we let the classifier predict the sentiment . If the classifier disagreed with the majority , we treated the classifier as a manual rater , and simply took the polarity assigned by the rater ( i . e . users and classifier ) with the highest accuracy . Twitter allows a tweeter's location to be manually entered into his or her profile . The profile's location field is free form , and accepts any entry; including ones that do not specify any location . A tweeter's position can also be updated by their GPS enabled mobile device , providing an accurate location specified by a pair of latitude and longitude co-ordinates ( this feature was not yet widely used in 2009 ) . For this location data to be useful to us , we needed to resolve these location strings into informative locations . Our goal for this study was to resolve within the United States to the state level . Since we downloaded tweets over a period of several months , there are often multiple tweets from the same tweeter . The location of the tweeter was downloaded with each tweet . In most cases , the tweeter's static location was duplicated multiple times throughout the data set . However , in some cases , over time , tweeters reported different locations . For each tweeter , we resolved all unique locations by using the Yahoo ! PlaceFinder web service ( http://developer . yahoo . com/geo/placefinder/ ) . Using the PlaceFinder API , we sent the location string to the service which , if it recognized the location , returned state and country level information . Of the 155 , 676 locations , there were 9 , 231 location strings that could not be accurately resolved using the PlaceFinder web service . In order to deal with those , we again created a web application and asked students to resolve the location manually if possible . Once all locations were resolved , tweeters with locations in multiple states were excluded from the analysis . In order to generate a network of Twitter users that captures information flow about opinions on the influenza A ( H1N1 ) vaccine , we used the following algorithm ( recall that information flows from users to their followers ) : Note that this algorithm treats the network as static , rather than as dynamic . The number of followers and friends might change over time ( both generally increase ) . Thus , the network is essentially a snapshot of the network as seen on the last day of data collection ( i . e . January 19th , 2010 ) . For extremely large counts of followers and friends , the data collection process did only collect the first 5 , 000 friends and/or followers that Twitter returned - this problem was only recognized late in the project . However , our algorithm deals effectively with this artificial cut off because it searches for edges both in the followers and friends lists . To see why this is the case , assume that a very popular user has more than 5 , 000 followers . It can be safely assumed that almost all of the followers of this user have a friend count of less than 5 , 000 users ( because accounts with more than 5 , 000 friends are extremely rare ) . Thus , even though we might not find an existing edge while looking at the followers of this popular user , we will find the edge while looking at the friends list of the followers . With regard to the cutoff of 5 , 000 friends ( extremely rare ) , it is unlikely that a person can cognitively follow the message stream of more than 5 , 000 users , and thus even if we would miss some data , the effect is negligible . Finally , we remove all users from the network that do not have a positive or negative influenza A ( H1N1 ) vaccine sentiment score . The overall influenza A ( H1N1 ) vaccine sentiment score is defined as the difference of positive and negative tweets divided by the sum of all relevant tweets ( n+-n- ) / ( n++n-+n0 ) . This results in a network of 39 , 284 nodes ( i . e . opinionated users ) and 685 , 719 edges ( i . e . tweets ) which has one giant component consisting of 34 , 025 nodes and 685 , 390 edges ( i . e . 99 . 95% of the edges of the network are also in the giant component ) . We simulate the spread of an influenza A ( H1N1 ) -like infectious disease on an empirical network collected with wireless sensor network technology[15] . We could have chosen any network , but decided to use this network collected at a high school for its high accuracy and coverage , but the results are applicable to any network ( indeed we've previously run infectious disease simulations on artificial networks with qualitatively similar results[2] ) . The disease simulation has been described in detail in [15] , but briefly , we use an SEIR simulation model parameterized with data from influenza outbreaks [25] , [26] . Transmission occurs exclusively along the measured contacts with a minimum duration of 30 minutes throughout the day of the graph collected in ref . [15] . Each individual ( i . e . , node of the network ) is in one of four classes: susceptible , exposed , infectious , and recovered . All individuals are initially susceptible with the exception of the vaccinated individuals who are always in the recovered class . On the first day of the week , a random susceptible individual is chosen as the index case , i . e . its status is set to exposed . A simulation is stopped after the number of both exposed and infectious individuals has gone back to 0 ( i . e . , all infected individuals have recovered ) . Each time step represents 12 hours and is divided into day and night . Transmission can occur only during the day and only on weekdays ( because this is a network collected at a high school and we do not consider any transmission outside of the school; although this assumption will not hold in reality , it allows us to analyze the spread of a disease starting from a single infected case ) . Transmission of disease from an infectious to a susceptible individual occurs with a probability of 1 − ( 1 − 0 . 00767 ) w , where w is the weight of the contact edge ( in intervals of 20 seconds - the values were chosen so that the the minimum transmission rate [i . e where w = 90] is 0 . 5 - this resulted in an R0 of 2 . 03 for all outbreaks with at least one secondary infection ) . After infection , an individual will move into the exposed class ( infected but not infectious ) . After an incubation period , modeled by a right-shifted Weibull distribution with a fixed offset of half a day [power parameter = 2 . 21 , scale parameter = 1 . 10 [25]] , an exposed individual will become symptomatic and move into the infectious class . As in [15] , we assume that on the half day that the individual becomes infectious , the duration of all contacts of the infectious individual is reduced by 75% . This reduction ensures that if an individual becomes symptomatic and starts to feel ill during a school day , social contacts are reduced and the individual leaves the school or is dismissed from school after a few hours . In the following days , all contacts are reduced by 100% until recovery ( i . e . , the individual stays at home ) . Once an individual is infectious , recovery occurs with a probability of 1 − 0 . 95t per time step , where t represents the number of time steps spent in the infectious state [in line with data from an outbreak of influenza A ( H1N1 ) at a New York City school[26]] . After 12 days in the infectious class , an individual will recover if recovery has not occurred before that time . We assume that all exposed individuals developed symptoms ( see [15] for a justification of this assumption ) . Vaccination occurs by picking individuals randomly and vaccinate them to achieve a vaccination coverage of 0 . 624 , reflecting the proportion of positive sentiments in the Twitter network as described above . Such a random process will result in an assortativity index r∼0 . In order to understand the effect of increased homophily on disease outbreaks , we redistribute the vaccination statuses such that the vaccination coverage remains constant , but r increases . We use a simple algorithm to do this , given a desired r value: This simple algorithm allows us to use the same network structure with a constant vaccination coverage while at the same time generate variable values of r . For each minimum value of r , starting from 0 up to 0 . 145 in increments of 0 . 005 , we generated 100 , 000 redistributions of vaccinations and ran a simulation per redistribution , as described above . This resulted in a total of 3 , 000 , 000 simulation runs on a network with constant structure and constant vaccination coverage , but with different values for the assortativity index r .
|
Sentiments about vaccination can strongly affect individual vaccination decisions . Measuring such sentiments - and how they are distributed in a population - is typically a difficult and resource-intensive endeavor . We use publicly available data from Twitter , a popular online social media service , to measure the evolution and distribution of sentiments towards the novel influenza A ( H1N1 ) vaccine during the second half of 2009 , i . e . the fall wave of the H1N1 ( swine flu ) pandemic . We find that projected vaccination rates based on sentiments expressed on Twitter are in very good agreement with vaccination rates estimated by the CDC with traditional phone surveys . Looking at the online social network , we find that both negative and positive opinions are clustered , and that an equivalent level of clustering of vaccinations in a population would strongly increase disease outbreak risks .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Methods"
] |
[
"text",
"mining",
"natural",
"language",
"processing",
"social",
"and",
"behavioral",
"sciences",
"population",
"modeling",
"social",
"networks",
"sociology",
"biology",
"computational",
"biology",
"infectious",
"disease",
"modeling"
] |
2011
|
Assessing Vaccination Sentiments with Online Social Media: Implications for Infectious Disease Dynamics and Control
|
The flagellar regulon controls Salmonella biofilm formation , virulence gene expression and the production of the major surface antigen present on the cell surface: flagellin . At the top of a flagellar regulatory hierarchy is the master operon , flhDC , which encodes the FlhD4C2 transcriptional complex required for the expression of flagellar , chemotaxis and Salmonella pathogenicity island 1 ( Spi1 ) genes . Of six potential transcriptional start-sites within the flhDC promoter region , only two , P1flhDC and P5flhDC , were functional in a wild-type background , while P6flhDC was functional in the absence of CRP . These promoters are transcribed differentially to control either flagellar or Spi1 virulent gene expression at different stages of cell growth . Transcription from P1flhDC initiates flagellar assembly and a negative autoregulatory loop through FlhD4C2-dependent transcription of the rflM gene , which encodes a repressor of flhDC transcription . Transcription from P1flhDC also initiates transcription of the Spi1 regulatory gene , hilD , whose product , in addition to activating Spi1 genes , also activates transcription of the flhDC P5 promoter later in the cell growth phase . The regulators of flhDC transcription ( RcsB , LrhA , RflM , HilD , SlyA and RtsB ) also exert their control at different stages of the cell growth phase and are also subjected to cell growth phase control . This dynamic of flhDC transcription separates the roles of FlhD4C2 transcriptional activation into an early cell growth phase role for flagellar production from a late cell growth phase role in virulence gene expression .
Tens of millions of human cases of Salmonellosis , a foodborne gastroenteritis caused by Salmonella enterica , occur worldwide every year killing more than a hundred thousand people annually ( World Health Organization Fact sheet N°139 , August 2013 ) . Typhoid fever caused by Salmonella Typhi kills an equivalent number of people each year . A prominent player in Salmonella pathogenesis is the bacterial flagellum . The bacterial flagellum is an ion-powered , complex motor organelle that endows bacterial cells , such as Escherichia coli and Salmonella enterica , with the ability to propel themselves through liquid medium and across hydrated surfaces [1] . Motility also plays an important role in biofilm formation and in the ability of many pathogens to reach their sites of infection and establish disease [2] , [3] . Early work on the discovery of Salmonella virulence genes identified a transposon insertion in the flagellar filament cap gene , fliD , as defective for survival of cells in macrophages [4] . However , fliD is in an operon with the fliT gene whose product is a regulator of the flagellar and Spi1 virulence genes master regulatory complex FlhD4C2 [5] , [6] . The transposon insertion in fliD was polar on fliT gene expression and thus identified regulation of FlhD4C2 activity as critical for Salmonella virulence . The two proteins that make up the FlhD4C2 transcriptional regulatory complex are co-expressed from the flhDC operon , class 1 promoter , which is at the top of a complex transcriptional hierarchy for both flagellar and Spi1 virulence genes expression . The decision whether or not to produce flagella is regulated at the levels of flhDC transcription , translation , FlhD4C2 assembly and stability [7] . Positive regulators of flhDC operon transcription include cAMP-CRP , Fis , Fur , H-NS and QseB [8]–[14] . A large number of regulatory factors are also reported to inhibit flhDC transcription . These factors include , LrhA , RcsB , RtsB , SlyA , DskA , PefI-SrgD , FimZ , HdfR , OmpR and RflM [15]–[20] . The FlhD4C2 activity generates an auto-regulatory loop by activating transcription of the rflM gene encoding a LysR-type DNA binding protein RflM , which in turn inhibits the transcription of flhDC [21] . The post-transcriptional factors regulating flhDC include , CsrA [22] , [23] , Hsp70 chaperone DnaK [24] and ClpXP protease [25] . Recently an FlhD4C2 repressed gene , ydiV [26] , was shown to code for a protein ( YdiV ) that will bind to FlhD4C2 , in its free or DNA-bound form , remove FlhD4C2 from DNA and serves as an adapter that targets FlhD4C2 for ClpXP-dependent degradation [27] , [28] . In Salmonella , an initial characterization of the flhDC promoter region identified six transcriptional start sites ( TSSs ) [13] . In a recent study , only four of the original six TSSs were detected [29] . The presence of six TSSs in the Salmonella flhDC regulatory region combined with the presence of DNA binding sites of CRP , LrhA , RtsB , HilD , RcsB , HNS and others indicated a complex level of the flhDC transcriptional regulation . Salmonella enterica is an intracellular facultative pathogen causing a range of diseases in a variety of hosts [30] . Important virulence factors required for Salmonella invasion of epithelial cells and development of Salmonellosis are encoded within the Salmonella pathogenicity island 1 ( Spi1 ) genes . Spi1 encodes a virulence-associated type III secretion system ( T3SS ) as part of an injectisome structure required for the secretion and injection of multiple effector proteins into the cytoplasm of host cells [31]–[36] . Expression of Spi1 genes is controlled in response to specific combinations of environmental signals in a complex hierarchical process with multiple transcriptional regulators . These include , HilA , a member of the OmpR/ToxR family of transcriptional regulators , which promotes transcription of genes encoding the necessary components for a functional Spi1 injectisome system [32] , [35] , [37] , [38] . Also included are the hilC and hilD genes whose products are members of the Ara/XylS family of transcriptional regulators that control hilA gene transcription . HilD is at the top of the regulatory network controlling Spi1 expression because most regulators controlling hilA transcription appears to be HilD-dependent [39] , [40] . It is noteworthy to mention that many protein components of the Spi1 and flagella T3SS exhibit a significant degree of amino acid identity , leading to the production of remarkably similar T3SS structures [16] , [33] , [34] , [41] , [42] . Furthermore , many of the transcriptional and posttranslational regulatory factors of flhDC also target the main transcriptional regulators of Spi1 , such as HilA and HilD [11] , [43]–[52] . In addition , the ATP-dependent Lon protease was shown to degrade both FlhD4C2 and HilD [24] , [25] . Coordinated expression of Spi1 and flagellar genes has been recently demonstrated [53] . In Salmonella , expression of Spi1 genes is activated by FliZ [54]–[57] , which is encoded within the flagellar fliAZY operon . FilZ activates the hilD gene expression at the posttranslational level and HilD in turn promotes transcription of the rtsAB operon , which encodes a pathogenesis-related DNA-binding regulatory proteins . RtsA and RtsB reciprocally regulate both the Spi1 and flagellar genes [17] . The direct binding of RtsB to the flhDC promoter region inhibits flhDC transcription and motility [17] . We decided to investigate how input from different regulatory factors might integrate multiple environmental or cell cycle signals into the control of flhDC expression in Salmonella enterica . We explored how and when positive and negative regulators affect flhDC expression throughout the cell growth cycle . We measured the effect of RcsB , LrhA , RflM , SlyA , RtsB and HilD regulatory factors on flhDC operon transcription at different cell growth phases . We characterized the specific TSSs within the flhDC promoter region and their involvement in the positive and negative control of flhDC cell-cycle dependent transcription . Finally , we examined how the individual TSSs and protein regulatory factors controlled the interconnection between the flagellar and Spi1 regulons .
To investigate flhDC operon transcription at different phases of the cell growth , we constructed a transcriptional fusion of the flhDC promoter region to the luciferase operon of Photorhabdus luminescence ( luxCDBAE operon ) . Because the flhDC operon is autoregulated negatively by RflM and positively by HilD , we designed strains harboring an intact copy of the flhDC operon under the control of its native promoter ( PflhDC ) and an in-frame fusion of a second copy of the promoter region of flhDC ( through the first 272 nucleotides of flhD coding sequence ) to the luciferase operon: DUP[ ( PwtflhDC-luxCDBAE ) *Km* ( PwtflhDC-flhD+C+ ) ] ( Figure 1A ) . Thus , individual PflhDC promoter regions transcribe both the luminescence operon reporter and the flhDC operon . This results in a strain with luminescence readout for the level of transcriptional activation of flhDC under conditions that also preserves the wild-type expression of the flagellar regulon including flhDC autoregulation through FlhD4C2-dependent expression of rflM and hilD genes . For simplicity , we will refer to the DUP[ ( PwtflhDC-luxCDBAE ) *Km* ( PwtflhDC-flhD+C+ ) ] construct as PwtflhDC . Following batch inoculation of an overnight culture of the PwtflhDC strain into fresh media with shaking at 30°C , transcription of the flhDC genes declined 4-fold during the initial lag phase transition to log phase growth to a minimal value ( Figure 1B ) . This observation is consistent with that reported in an earlier study [11] . After the transition to log phase growth , transcription of flhDC increased more than 10-fold between OD 0 . 3 and 1 . 2 , followed by a decline in flhDC transcription as cells enter late log and stationary phase growth ( Figure 1B ) . In Salmonella enterica , flagellar regulon transcription is highest during the exponential phase of growth and decays in late stationary phase [58] . Transcription of the flagellar master regulatory operon , flhDC , is under both negative and positive control by multiple regulatory factors . Null mutations in any one of the rcsB , rflM , lrhA , slyA , and rtsB genes result in increased transcription of the flhDC operon , which is consistent with an inhibitory activity on flhDC expression . HilD is an activator of flhDC transcription such that over-expression of the hilD gene increases flhDC expression ( Singer et al . submitted ) . The diversity of transcription factors controlling expression of flhDC reflects the complexity of flhDC transcriptional regulation and suggests that flhDC transcription is controlled when Salmonella cells are experiencing different metabolic or environmental states , or different growth conditions under which these transcriptional factors are active . We examined both the timing and magnitude of individual regulatory proteins on flhDC transcriptional control throughout the cell's growth phase . We tested flhDC transcriptional levels as a function of the cell's growth phase in strains missing the individual negative regulators RcsB , LrhA , RflM , RtsB , SlyA and the positive regulator HilD ( Figures 1C & D ) . As was presented above for the wild-type strain , this was done by growing PwtflhDC cells in liquid culture at 30°C using luciferase as the reporter for flhDC transcription levels . Luciferase levels were determined at specific optical densities shown in Figure 1 . As expected , removal of individual inhibitors resulted in an increase in flhDC transcription levels while removal of HilD decreased flhDC transcription . Importantly , our assay revealed a growth phase-dependent hierarchy of the effect of these regulators . At OD 0 . 3 , basal flhDC transcription was elevated in the absence of LrhA and RcsB , while removal of RflM , RtsB , SlyA or HilD exhibited the same basal level of transcription as wild type ( Figures 1C & 1D ) . This suggests that RcsB and LrhA act earlier , during lag phase , to inhibit flhDC transcription . This effect could also represent a carry-over of repression from stationary phase that keep flhDC transcription low during the transition to log growth . In the absence of RflM we observed an earlier transition to flhDC activation than in the other mutant strains . Since FlhD4C2 transcribes the rflM gene and RflM protein inhibits flhDC transcription ( flhDC auto-inhibition ) , this result suggests that flhDC auto-inhibition through RflM occurs during early exponential phase to control when full FlhD4C2-dependent gene expression occurs at log phase . The negative effect of RtsB and SlyA on flhDC transcription was detected as cells enter early stationary phase . We also observed that the maximum flhDC transcription level peaked earlier for both the hilD and rflM mutants at OD 1 , while the wild type and mutants in rcsB , lrhA , slyA and rtsB peaked around OD 1 . 2 . The data presented in Figure 1C demonstrate that initial flhDC transcription is kept low by a combination of repressors including at least RcsB and LrhA . Initial FlhD4C2 expression during the stationary to log phase transition produces enough RflM to maintain a low level of flhDC transcription until an OD of ∼0 . 3 is reached . After OD 0 . 3 , flhDC transcription increased significantly , but RflM , RcsB and LrhA reduce the overall level . Interestingly , the wild-type level is balanced by the presence of the HilD activator of flhDC transcription , the hilD-activated inhibitor of flhDC transcription RtsB and by the virulence associated factor SlyA ( Figure 1D ) . In order to obtain more detailed information relating the effect of specific regulatory proteins on flhDC transcription as a function of the cell's growth phase , we determined luciferase levels for the PwtflhDC grown in liquid culture at 30°C in 96 well plates with a microplate reader . Using this assay system , we could measure the activity of flhDC transcription at shorter times intervals ( 6 min ) with continuous shaking at 150 rpm . We observed the same trend of regulation of the flhDC operon as seen in batch cultures for lrhA , rcsB ( Figure 2A ) , rflM ( Figure 2B ) , slyA and rtsB ( Figure 2C ) , and hilD mutants ( Figure 2D ) . However , the pattern observed in 96 well plates was somewhat different compared to the batch growth . We observed that activation of flhDC transcription took place earlier at OD∼0 . 2 rather than OD∼0 . 3 . Consistent with this observation , the differences between the activity of flhDC in wild-type versus mutant strains also occurred at an earlier OD measurement in microtiter plate growth compared to growth in batch culture . The cells in 96 well plates reached maximum expression at OD∼0 . 6 compared to OD∼1 . 2 in the batch culture . We attribute these differences to the mode of growth in 96 well plates ( 150 rpm ) where bacterial cells are grown in much lower volumes and likely to be subjected to different oxygen levels in the medium compared to batch cultures . It has been shown that activation of flgA , a gene under the control of flhDC , under static conditions ( no shaking of 96 well plates ) occurred immediately after dilution of an overnight culture into LB-1% Salt [53] . When we tested the activation of flhDC operon in standing batch culture in LB , we observed that flhDC transcription increased at OD∼0 . 12 ( Figure S1 ) , which is earlier compared to what we observed either in batch shaking ( OD∼0 . 3 ) or 96 well grown cultures ( OD∼0 . 2 ) . Moreover , the shutdown of flhDC transcription observed in standing cultures took place after cells reach an OD∼0 . 6 compared to shaking batch culture where the shutdown started at an OD∼1 . 2 . Because flhDC transcription is differentially regulated by different transcription factors in a growth phase dependent manner , we hypothesized that the effect of each of these regulators is observed at the time when they are produced during the cell growth cycle . To investigate this possibility we placed the luxCDBAE operon reporter under control of the promoters of the six regulatory genes lrhA , rcsB , rflM , slyA , rtsB and hilD , whose products have been demonstrated to bind directly to the flhDC promoter region and monitored their expression profile at different optical densities ( binding of RflM or SlyA to the flhDC promoter region has not been reported ) . We monitored the activities of these constructs in 96 well plates over time . We observed that the transcription of the autoregulated gene lrhA is immediately activated following dilution from an overnight culture , and before the activation of flhDC ( Figure S2 . A ) . Transcription of rcsD ( which is the first gene of the rcsDB operon transcribed from the rcsD promoter ) also initiated before flhDC ( Figure S2 . B ) , whereas transcription of rflM overlapped with that of flhDC ( Figure S2 . B ) . Since rflM transcription is dependent on FlhD4C2 , these results suggest that low basal levels of FlhD4C2 are sufficient to promote rflM gene transcription . In addition , transcription of rflM reached a maximum at OD∼0 . 35 and decayed very quickly ( Figure S2 . B ) compared to the rest of the regulators tested in this study . The transcription of hilD gene is under positive autoregulatory control by HilD itself [59] and by HilD-activated RtsA [17] . In addition , the product of an flhDC activated gene , FliZ controls HilD at a posttranslational level [54] , [57] . We observed that transcription of hilD increased at OD of ∼0 . 4 ( Figure S2 . C ) , at the same time when HilD promoted transcription of flhDC ( Figure 2D ) . The expression of the HilD-activated rtsA gene ( the first gene of the rtsAB operon ) appeared to be activated at the same time as hilD ( Figure S2 . C ) . Transcription of the slyA gene was activated just after flhDC transcription started and before initiation of hilD and rtsA transcription , with a peak of expression at entry into stationary phase ( Figure S2 . D ) . These results suggest that there is a hierarchy of transcription of the factors regulating flhDC transcription that mirrors their effect on the transcriptional regulation of the flhDC operon . We next asked if the protein levels of the regulatory factors controlling flhDC transcription were also growth phase dependent . We performed Western blot analysis of whole cell lysates of Salmonella strains ( LrhA-HA , RcsB-3×Flag , RflM-HA , SlyA-HA , RtsB-HA and HilD-Flag ) at different optical densities ( Figure 3A ) . We established that LrhA is present at an early time point during cell growth ( OD∼0 . 2 ) with maximum expression at OD∼0 . 6 followed by a decay at late stationary phase ( note that both the N-terminal and C-terminal HA-tag fusion to LrhA are made but not functional and therefore there is no positive feedback regulation of lrhA transcription by LrhA protein [18] ) . The level of RcsB protein , the transcriptional regulator of the phosphorelay system RcsDBC , also appeared to be growth phase dependent because RcsB protein was detected early in the growth phase ( OD∼0 . 2 ) and increased at the stationary phase of cell growth . The FlhD4C2 activated RflM , was produced early in the growth phase ( OD∼0 . 2 ) , and increased at OD∼0 . 4 followed by a quick decay during the rest of the cell's growth phase . HilD protein , the positive activator of flhDC transcription , was detected at OD∼0 . 4 and increased at stationary phase ( Figure 3A ) . RtsB , whose gene is under the transcriptional control by HilD , was not detected early in the growth phase and was present at OD∼1 . 3 . The absence of RtsB at an early time point in the blot might be due to the detection limits for low protein levels in our experiment ( See CHIP , Figure 3B , where RtsB was already associated with the promoter of flhDC at OD∼1 ) . In contrast , the negative regulator SlyA was produced during all the phases of cell growth , with a sharp increase at OD∼1 . These results demonstrate a hierarchy at the level of expression of flhDC regulators that specifically mimics the differential dynamics of flhDC operon transcription . We examined the in vivo binding dynamics within the flhDC promoter region by these regulatory factors . At different optical densities ( 0 . 4 to 1 . 4 ) , chromatin immunoprecipitations ( ChIP ) were conducted using strains with individually tagged transcriptional factors , RcsB , RflM , HilD , RtsB , LrhA and SlyA ( Figure 3B ) . Expression of RcsB and binding of RscB to its target DNA at the flhDC promoter was detected throughout the entire growth phase . However , RcsB bound levels increased as cells progressed to exponential phase ( OD 0 . 4 to 0 . 6 ) followed by decreased binding at latter stages of growth . The transcriptional regulator RflM binding to DNA was detected at OD∼0 . 4 with maximal binding at OD∼0 . 6 , but was no longer bound the flhDC promoter region beyond OD∼0 . 6 . HilD , a transcriptional activator of flhDC , was bound to the flhDC promoter region at OD∼0 . 4 increasing to a maximum bound level at OD∼0 . 8 and followed by absence of bound HilD at OD∼1 . SlyA was not physically associated with the flhDC promoter at OD∼0 . 4 and ∼0 . 6 , but was bound to the flhDC promoter region at OD∼0 . 8 . There was no binding of RtsB to the flhDC promoter at an early time point of cell growth OD∼0 . 4 to 0 . 6 . Binding by RtsB had initiated by OD 0 . 8 and increased through OD 1 . 4 . We were unable to immunoprecipitate LrhA tagged protein because C-terminal or N-terminal tagged LrhA behaved like lrhA null mutant ( Figure S5; ) . These results highlight the binding dynamics of different regulators to the flhDC promoter region resulting in a dynamic of flhDC operon transcription . Six transcriptional start sites , designated P1flhDC , P2flhDC , P3flhDC , P4flhDC , P5flhDC and P6flhDC , within Salmonella flhDC promoter region were obtained by primer extension [13] . However only P1flhDC , P3flhDC , P4flhDC and P5flhDC were detected by RNA-Seq based approach [29] . Each of these TSSs was preceded by a hexamer motif ( −10 box ) with the consensus invariant residues adenine at position 2 ( A2 ) and thymine at position 6 ( T6 ) , except for P4 ( Figure 4A ) . To investigate the authenticity of these TSSs , we made alterations of the −10 sequences targeting the conserved residues A2 and T6 by changing them to a cytosine residue ( C ) and also by totally changing the −10 box to a GTTGGT sequence ( Figure 4B ) . As controls , additional mutations were made in each −10 box , in a nucleotide other than A2 or T6 ( Figures 4B & S3A ) that supposedly should not alter significantly the effect of RNAP on transcription [60] . Because flhDC is subjected to negative and positive transcriptional feedback , mutations of the promoters responsible for transcription of flhDC operon in the wild-type strain might affect the positive and negative auto-regulation of flhDC transcription . We thus monitored the activities of the promoters mutants fused to luciferase operon in an flhD+C+ background ( described above ) . Mutations of wild-type sequence P1flhDC ( TATAGT ) to GTTGGT ( P1− . 1flhDC ) ; TCTAGC ( P1− . 2flhDC ) or TCTAGT ( P1− . 3flhDC ) but not TACAGT ( P1− . 4flhDC ) were associated with a significant reduction of flhDC transcription ( Figure 4C ) . Mutations of the wild-type P5flhDC ( TATGCT ) to TCTGCC ( P5− . 2flhDC ) or TCTGCT ( P5− . 3flhDC ) but not to TACGCT ( P5− . 4flhDC ) reduced significantly the transcription of flhDC to the same extent as the mutation of −10 to GTTGGT ( P5− . 1flhDC ) ( Figure 4D ) . These results indicated that P1flhDC and P5flhDC are bona-fide promoters . Analysis of mutations of −10 sequences of the P2flhDC and P6flhDC ( overlapping with the CRP binding site which is required for the transcription of flhDC from P1flhDC promoter ) and P3flhDC ( overlapping with the LrhA binding site ) and P4flhDC were not conclusive ( Supplementary Text S1 & Figure S3 ) . We further investigated the authenticity of the six putative TSSs of the flhDC operon , by engineering strains with combined mutations in the promoter region of flhDC leaving only one wild-type −10 sequence from the six described promoters . Thus , P1+ designates a strain that has only a functional P1 promoter , etc . We also constructed a control strain with combined mutations in all the six promoters , AP−flhDC ( All Promoters mutated ) . We established that P1+flhDC and P5+flhDC were able to promote flhDC operon transcription but to a lesser extent to what is observed in the wild-type strain ( Figure 4E ) . The transcription of flhDC was totally abolished in strains harboring P2+flhDC , P3+flhDC , P6+flhDC and APs−flhDC , while P4+flhDC mutants showed very low level of flhDC transcription ( 1 . 8% relative to the wild-type strain ) ( Figure 4E ) . These results suggested that in the wild-type background P1flhDC and P5flhDC are the main promoters driving flhDC operon transcription with a marginal activity from the P4flhDC promoter . Yanagihara et al . , 1999; have demonstrated that P6flhDC is only active in the absence of CRP , we confirmed that P6+flhDC ( only P6 is functional ) is inhibited by CRP , because in a crp null mutant there was an increase of transcription of P6+flhDC compared to wild-type ( Figure S3H ) . Since only mutations in P1flhDC and P5flhDC promoters significantly affected the expression of flhDC , we would expect the level of transcription of flhDC operon in the absence of both P1 and P5 promoters to be similar to the level of transcription of flhDC operon in the absence of all flhDC promoters ( P1 through P6 ) . To investigate this hypothesis , we measured the luciferase activity in a strain with combined mutations in P1flhDC and P5flhDC promoters ( P1−P5−flhDC ) and compared it to the luciferase activity of a wild-type strain and to a strain with all six promoters mutated ( strain AP's ) . We observed that transcription of flhDC operon in strain P1−P5−flhDC was totally abolished to the same levels observed in a strain with all flhDC promoters mutated ( Figure 4F ) . These results demonstrated that in a wild-type background P1flhDC and P5flhDC are the major promoters driving transcription of flhDC operon . We concluded that transcription of the flhDC operon in strain P1−flhDC ( harboring mutations of the −10 box of P1flhDC ) is driven from the P5flhDC promoter and that transcription of the flhDC operon in strain P5−flhDC ( harboring mutations of −10 box of P5flhDC ) is driven from P1flhDC . Once we established that P1flhDC and P5flhDC are the main promoters driving transcription of the flhDC operon , we monitored the expression of the P1flhDC and P5flhDC promoters at different optical densities using PwtflhDC , P1−flhDC and P5−flhDC constructs ( Figure 5A ) . The transcription profile of flhDC operon in strains P1−flhDC ( P5-expressed ) and P5−flhDC ( P1-expressed ) demonstrated that both promoters are required for transcription of flhDC because the expression of flhDC operon in constructs P1−flhDC ( P5-expressed ) and P5−flhDC ( P1-expressed ) did not reach the expression levels of the wild-type strain , PwtflhDC ( both P1 and P5 are expressed ) ( Figure 5A ) . Moreover , transcription of flhDC operon from P1flhDC is activated earlier than P5flhDC because ( i ) the transcription profile of the flhDC operon in construct P5−flhDC ( P1-expressed ) overlapped with that of the wild-type strain from OD 0 . 1 to OD 0 . 4 , ( Figure 5A ) and ( ii ) there was a delay in the transcription of flhDC operon in construct P1−flhDC ( P5-expressed ) where the transcription started taking place at OD∼0 . 35 ( Figure 5A ) compared to the wild-type PwtflhDC and P5−flhDC ( P1-expressed ) strains ( OD∼0 . 2 ) . The same hierarchy of expression of P1 and P5 was observed in batch culture ( Figure 6A & B ) . The transcription of flhDC operon in P5−flhDC ( P1-expressed ) started declining at OD∼0 . 4–0 . 5 , meanwhile , transcription of flhDC operon in strain P1−flhDC ( P5-expressed ) was more pronounced at a later growth stage accounting for ∼60% relative to the wild-type at OD∼0 . 6 ( Figure 5A ) . It is apparent from the dynamic profile of flhDC operon transcription , that P5flhDC promoter transcription occurs concomitantly with a cessation or decline in the transcription from P1flhDC ( Figure 5A ) . These results indicate that P1flhDC is an early promoter , whose activation drives the transcription of flhDC operon synthesis at early growth phase followed by a cessation or decline once P5flhDC promoter is activated . We have demonstrated that HilD is a positive regulator of flhDC transcription ( Figure 1D & 2D ) . As shown ( Figure 2D ) , when cells are grown in the 96 well plate format , the effect of HilD on the transcription of flhDC takes place starting at OD∼0 . 4 . In order to determine which of the two promoters , P1flhDC or P5flhDC , is the target of the positive regulation by HilD , we compared the dynamic profile of flhDC transcription in PwtflhDC , P1−flhDC and P5−flhDC constructs in a wild-type and its isogenic strain hilD null mutant ( Figures 5B & C ) . We established that , relative to the wild-type strain background , a deletion of hilD ( i ) reduced PwtflhDC promoter transcription; ( ii ) abolished the transcription of flhDC operon in construct P1−flhDC ( P5-expressed ) ( Figure 5B ) and ( iii ) did not affect the transcription of flhDC operon in construct P5−flhDC ( P1-expressed ) ( Figure 5C ) . These results indicate that HilD promotes transcription from P5flhDC and has no apparent effect on P1flhDC promoter transcription . Transcription of the flhDC operon is subjected to negative feedback by RflM , which is activated at the transcriptional level by FlhD4C2 [21] . To further study the effect of the negative autoregulation on flhDC operon transcription kinetics , we monitored the transcription profile , over time , in the three strains PwtflhDC , P1−flhDC and P5−flhDC in the absence and presence of RflM . We established that there was an increase in the transcription from PwtflhDC in the absence of RflM ( Figure 2B ) . We demonstrated that the P1flhDC promoter is under negative autoregulation by RflM because the expression of flhDC operon in strain P1−flhDC ( P5-expressed ) was similar between the wild-type and its isogenic rflM null mutant ( Figure 5D ) . Additionally , we found that RflM did not appear to regulate P5flhDC because flhDC transcription in strain P5−flhDC ( P1-expressed ) increased in the absence of RflM ( Figure 5E ) . These results demonstrated that in the wild-type background the P1flhDC promoter is subjected to negative autoregulation through RflM , while transcription from P5flhDC appeared to be RflM independent . We employed an alternative approach to confirm which of the flhDC promoters is specifically inhibited by the transcriptional factor RflM . We monitored the transcription of flhDC in a strain that overproduces RflM under control of the arabinose promoter , ParaBAD::rflM+ . In the presence of arabinose , used to induce overexpression of rflM , we observed an inhibition of transcription of flhDC operon in the three strains tested , PwtflhDC , P1−flhDC and P5−flhDC ( Figure 5F ) . These results suggest that RflM is able to inhibit transcription of flhDC operon from both promoters , P1 and P5 , which is in contradiction to the specific inhibition of the P1flhDC but not the P5flhDC promoter by RflM observed in Figures 5D & E . RflM protein production or stability appears to decline in function of cell growth cycle ( Figure 3A ) , suggested that continuous production of RflM might affect indirectly the expression of P5flhDC . Because HilD is an activator of the P5flhDC promoter , we hypothesized that overexpression of RflM inhibits transcription of hilD gene . In order to test this hypothesis , we monitored the activity of a luciferase transcriptional fusion of the hilD promoter , PhilD , in two genetic backgrounds: ( i ) ParaBAD::FCF ( ii ) ParaBAD::rflM+ . We observed that under conditions that overproduce RflM , presence of arabinose , there was an inhibition of transcription of the autoregulated gene hilD ( Figure 6 , compare column 1 to column 2 ) . Note that the strains used to determine luciferase activity are all flhD+C+ , and overexpression of RflM inhibits flhDC transcription required for production of the posttranslational regulator of HilD . Thus , the effect of RflM , on hilD transcription could be indirect through inhibiting flhDC . To test if the effect of RflM on hilD , is direct or indirect we used two additional strains ( i ) ParaBAD::FCF PflhDC::T-POP and ( ii ) ParaBAD::rflM+ PflhDC::T-POP . For the PflhDC::T-POP backgrounds the flhDC operon is transcribed from the tetracycline ( Tc ) -inducible tetA promoter , and as such are flhDC− in the absence of tetracycline and flhDC+ in the presence of tetracycline . First , we observed that flhDC controlled transcription of the hilD gene , because in the absence of Tc , there was a 2-fold decrease in the PhilD transcription level in the PflhDC::TPOP strain background ( Figure 6D , compare column 3 to column 5 ) . Moreover , we demonstrated that under condition of RflM overexpression , there was a higher level of inhibition of hilD transcription compared to the reduction observed in the PflhDC::T-POP background ( Figure 6D , compare column 5 to column 6 ) . The overproduction effect of RflM was not rescued by addition of Tc to induce flhDC transcription , an activator of hilD transcription ( Figure 6D , compare column 6 to column 8 ) . These results demonstrated that RflM could inhibit transcription of the hilD gene in an flhDC independent manner . Thus flhDC and rflM have opposite effects on the transcription of hilD , where flhDC is an indirect positive regulator of HilD , yet high levels of RflM inhibit hilD transcription . Since HilD is an activator of P5flhDC transcription , we conclude that the negative effect of RflM overproduction on transcription of P5flhDC is indirect and through inhibition of hilD gene transcription , The presence of two principal TSSs within the flhDC operon promoter region combined with the hierarchical regulation by different transcriptional factors , suggests that there is differential regulation at the promoter by different transcriptional regulators at different cell growth phases . We investigated which of the specific regulators: RcsB , LrhA , SlyA and RtsB control transcription of flhDC through the P1flhDC and P5flhDC promoters start-sites . There appears to be five stages of flhDC transcription that are controlled by three clusters of response regulators . Deletion of either , rcsB , lrhA or rflM resulted in increased motility compared to the wild-type strain [18] , [19] , [62] . We observed that null mutations in any of the late regulators: hilD , rtsB or slyA , did not affect motility ( Figure 7A ) . Based on the expression profiles of the flhDC operon in these mutant strains , these results establish that Salmonella wild-type motility will only need to reach a threshold of flhDC expression for motility , while increased flhDC expression later in the growth phase has no further effect on motility . It is noteworthy to mention that factors that affected the early transcription of the P1flhDC promoter: LrhA , RcsB ( Figure 6A ) and RflM ( Figure 5E ) affected motility while transcriptional factors , HilD and SlyA , that regulate P5flhDC promoter late in the growth phase ( Figure 5B & 6B ) did not affect motility ( Figure 7A ) . Moreover , RtsB , by inhibiting transcription from P1flhDC at later stages of growth ( Figure 6B ) , did not inhibit motility suggesting that the growth phase combined with activation of flhDC promoters is important for motility ( Figure 7A ) . It is noteworthy to mention that the factors that affected transcription of P5 flhDC but not motility are bona fide virulence factors . We decided to study the effect of the flhDC promoter mutations on the motility of Salmonella . We constructed strains harboring single mutation in each of the promoters separately . Thus P1− refers to a strain that has a mutation in P1 promoter , etc . Note that these strains in contrast to strains harboring the luciferase constructs do not harbor a duplication of the flhDC operon . We demonstrated that strains defective in P1flhDC start-site transcription ( only P1 is mutated ) were non-motile while P5flhDC defective strains ( only P5 is mutated ) exhibited no apparent reduction of motility ( Figure 7B ) . There was a motility defect of the strains P2− and P6− that is related to the effect of CRP ( as discussed earlier and in Supplementary material ) . The motility of P3− and P4− were not significantly different from the wild-type strain . These results confirmed that in the wild-type background transcription from P1flhDC is a prerequisite for motility while P5flhDC is not required for motility . These results also suggested that the right timing of expression of flhDC is essential for motility . If this hypothesis is correct , we could expect that if flhDC is expressed from P5flhDC promoter at an early time point it should confer a motility phenotype . To test this hypothesis we used the non-motile strain P5+ ( only P5 is functional and the other promoters are mutated ) ( Figure 7C ) to isolate suppressors of motility inhibition . This strain was used in order to limit isolating mutations in the other promoters of flhDC that would otherwise suppress motility [16] . We isolated a spontaneous suppressor that restores motility to the P5+ strain ( Figure 7C ) and mapped the mutation to the promoter region of hilD gene ( addition of a thymine residue at position −51 from the start codon of HilD and resulting in higher expression of hilD ( labeled hilDup ) ) . The isolation of this mutation confirmed that HilD regulates the P5flhDC promoter . If the hypothesis that the timing of expression of flhDC as a prerequisite for motility is correct , then a hilD-up mutation should promote transcription of flhDC operon from P5 promoter at early growth phase . To test this hypothesis we used a transcriptional lac fusion to fliL , a class 2 promoter that is positively regulated by FlhD4C2 , as readout to determine the expression of the P5 promoter transcription . The transcription of fliL indicates the presence of FlhD4C2-dependent transcription . Transcription of fliL in the P5+ strain was very low during early growth phases and increased when cells reached an OD of 1 . 4 ( Figure 7D ) . These results suggest that P5+ cells are able to express flagellar genes at later stage of cell's growth phase yet they are not motile . Interestingly , overexpression of hilD , hilDup mutant resulted in a premature activation of P5flhDC , leading to the transcription of fliL at early growth phase and similar to the timing and levels of the wild-type strain ( Figure 7D ) . These results suggested that the timing of FlhD4C2 production during an early growth phase is critical for motility .
The pre-log steady state transcription of flhDC regulation is controlled by two transcription factors , RcsB and LrhA . Null mutation in any of these transcriptional regulators , promoted flhDC transcription early in the growth phase and this inhibition was maintained throughout the rest of the growth phase ( exponential and stationary ) . We found that the effect of LrhA and RcsB was coincident with activation of transcription of their respective genes . As cell densities reached an OD of 0 . 2–0 . 3 , transcription of flhDC increased . The increased flhDC transcription resulted in transcription of rflM , which in turn resulted in the feedback inhibition of flhDC transcription . This effect was consistent with the concurrent transcriptional activation of flhDC and rflM , where a surge of transcription of rflM mimicked that of flhDC and decayed quickly compared to the rest of the regulators controlling flhDC transcription . At the protein level , RflM appeared to follow the same early production and a quick decay as observed at the transcriptional level . We conclude that RflM limits flhDC transcription perhaps to efficiently control the kinetic expression of the middle and late flagellar class genes to facilitate flagellum assembly . Class 2 promoters respond differently to FlhD4C2 levels allowing the cell to control the timing of an individual class 2 operon transcription with respect to the other class 2 operons . Auto-repression at the transcriptional level has been shown to reduce relative variance and duration of fluctuations , and consequently limits noise in downstream expression [65] , [66] . Expression of fliC , encoding the filament component of the flagellum , has been demonstrated to be bistable [67] , [68] . We suggest that RflM would fulfill the noise reduction of flagellar class 2 and class 3 promoters transcription during exponential growth phase , by controlling class 1 flhDC operon transcription . In support of this hypothesis , a null mutation of rflM gene has been shown to increase heterogeneity of fliC expression in a cell population when compared to wild-type [21] . Once bacteria reach mid-exponential phase growth , there is a second layer of control on flhDC operon transcription . This control is positive , and is brought on by the effect of a virulence-associated transcription factor , HilD . There was a delay in the positive effect of HilD compared to the negative control exerted by RcsB , LrhA and RflM . This delayed HilD effect on flhDC operon transcription was due to the time required to activate HilD expression through FlhD4C2-dependent FliZ production . FlhD4C2 activates fliZ gene transcription from a flagellar class 2 promoter and FliZ , in turn , activates hilD expression at the post-translational level [57] . Finally , a third layer of flhDC transcription takes place and , unexpectedly , is also controlled by HilD . HilD activates the transcription of two regulatory factor genes , rtsB [17] and slyA ( data not shown ) . RtsB and SlyA are two DNA binding regulators , which then act to inhibit flhDC transcription . There is no doubt that flagellar motility provides a significant survival advantage over non-motile bacteria in many environmental situations . Furthermore , the link between production of flagella and other regulatory networks [69]–[72] would be affected if an unchecked production of flagella occurs . The overexpression of the flagellar regulon also attenuates Salmonella virulence [73] . These observations could explain the array of negative regulators controlling transcription of flhDC operon and keeping a check on the flagellar synthesis as well as FlhD4C2 production . While the literature reports the presence of either four or six transcription start-sites in the flhDC promoter region [13] , [29] , our work suggests that only the P1flhDC and P5flhDC promoters are functional in a wild-type strain under laboratory growth conditions . First , we demonstrated that there was a reduction in flhDC operon transcription in the absence of P1flhDC or P5flhDC compared to the wild-type strain ( Figure 4C & D ) . Second , we showed that flhDC operon transcription was totally abolished in P1−P5−flhDC double mutant ( Figure 4F ) . We confirmed that the P6flhDC promoter is active only in the absence of CRP [13] . Moreover , there was no apparent effect of P4flhDC , P3flhDC and P2flhDC promoters on flhDC transcription . In E . coli , CsrA , a carbon storage global regulator , activates flhDC expression in an RNaseE-dependent manner through protection of 5′end cleavage [23] . The 5′-UTR of the P5flhDC start-site transcript is 534 bases in length . We suspect that the presumed P3flhDC and P2flhDC start-sites resulted from RNAseE-dependent RNA-processing and/or degradation of the P5flhDC transcript . The P4flhDC start-site might also result from RNA processing; however , the isolation of mutants in the −10 region of P4flhDC that result in increased flhDC transcription suggests there might be unknown conditions where transcription from P4flhDC occurs [16] . Genes with multiple transcription start-sites combined with auto-regulatory networks have been described in other systems . These include , Salmonella phoP , Bordetela pertussis bvgA , E . coli rrnA , and Salmonella fliAZ operon [27] , [74]–[78] . These four cases bear similarity with flhDC operon transcription from P1flhDC and P5flhDC promoters . However , the case of flhDC is more elaborate , where two disparate pathways are used as feedback control . First , we demonstrated a sequential activation of P1flhDC and P5flhD transcripts that are growth phase dependent ( Figure 5A ) . The P1flhDC promoter activating two regulatory pathways resulting in both a negative and a positive regulatory loop and each of these loops has a specific effect on the flhDC operon promoters . The negative loop starts with P1flhDC , leading to the production of FlhD4C2 that activates rflM , which in turn feedback inhibits the P1flhDC promoter ( Figure 5E ) . The positive feedback loop is also generated from P1flhDC , where transcription of flhDC operon from P1flhDC leads to fliZ gene transcription followed by FliZ activation of hilD . HilD then activates the second flhDC transcriptional cycle from P5flhDC ( Figure 5B ) . Paradoxically , HilD controls transcription of rtsB and slyA genes , whose products binds to the flhDC promoter region ( Figure 3B ) and inhibit transcription , from P1flhDC and P5flhDC , respectively ( Figures 6A & B ) . The three promoter classes of the flagellar regulon , class 1 , class 2 and class 3; are expressed in a temporal cascade that coincides with flagellum assembly [79] . The control of flagella production is ultimately determined through the production of FlhD4C2 . However , when flhDC is highly over-expressed the cells are not motile for reasons that are not understood . Thus , an intricate temporal control of gene expression and specific quantities of a functional FlhD4C2 master regulator are essential for motility . For example , the activator of type I fimbriae gene expression , FimZ , represses flhDC transcription suggesting that adherence is impeded in the presence of functional flagella . Neither deletion of flhDC nor over-expression of flhDC affect type I fimbriae gene expression suggesting that the presence of fimbriae ( at wild-type levels ) does not impede swimming . FlhD4C2 activity is also required in other cell processes such as Spi1 gene expression and other genes less characterized such as the srfABC operon [80] , which is implicated in surfactin production and the modABC operon [80] , which is involved an anaerobic respiration . This leads us to speculate that P1flhDC is required for flagella production and P5flhDC is required for growth in various environmental conditions such as in biofilms or in host cells . One possibility is that the activation of flhDC transcription from P5flhDC might represent a mechanism of protein amplification by a surge of transcription , when it is necessary to turn on the Spi1 regulatory network , even under conditions where flagella synthesis is inhibited at the level of fliA and fliC . This scenario can be very useful after infection when the bacteria requires expression of virulence factors to survive the physical and immune clearance of the eukaryotic host . Flagella appear to be required for reaching and selecting point of entry of bacteria into host cells [81] . The low pH of the stomach will cause flagella already present to depolymerize [82] . In the intestine , the early transcription of flhDC operon from the P1 promoter provides the transcription factor , FlhD4C2 for expression of functional flagellar machinery to reassemble filaments and allow bacterial cells to swim to selected points of entry into epithelia cells . At the time of invasion , expression of both T3SS1 and flagella has been shown to be required . Thus , in the second step , the already expressed flhDC from P1flhDC promoter activates transcription of fliZ , the posttranslational regulator of HilD . In turn , HilD promotes transcription of Spi1 genes , leading to invasion . Thus P1-expressed flhDC fulfills two functions: driving the cells near the point of entry and also boosting the expression of Spi1 , necessary for invasion , through its effect on HilD . It is noteworthy to mention that invasion of epithelial cells is a rapid process occurring within 10 to 15 minutes after introduction of S . typhimurium into the intestinal lumen [83] . Translocation of bacteria across the epithelial barrier and into the underlying tissue is observed within 2 hours after infection of ligated ileal loops [83] , [84] . Interestingly Salmonella can replicate within two distinct intracellular environments: intravacuolar and cytosolic [85] . Once inside the host , the expression of both flagella and Spi1 appear to be downregulated but not abolished with most of the cytosolic population expressing both flagella and Spi1 at latter stage of infection . In addition , only a subset of T3SS1-induced cytosolic bacteria was motile [85] . We speculate that once bacteria invade epithelial cells , HilD activates P5flhDC and down-regulates the transcription of P1flhDC in an RtsB-dependent manner . The transcription from P5flhDC is bistable leading to two populations of cells , one is flagellated and the other is not ( ∼10% of cells being flagellated ) . This bistable expression of P5flhDC is reminiscent with the bistable expression of Spi1 . We suggest that the presence of two populations inside epithelial cells could be explained by the bistability from P5flhDC promoter and the consequent downregulation of P1flhDC might represent a mechanism to limit the number of flagellated cells . The cytosolic growth of Salmonella leads to the extrusion of epithelial cells as a host defense mechanism [85] . The consequent release of the invasion-prone flagellated cells bacteria back into the mucus rich and inflamed gut endows Salmonella with a fitness advantage to use the energy-taxis mechanism to benefit from inflammation [86] . We speculate that the different timing of expression of flagellar promoters P1 and P5 and the bistable expression of P5flhDC represent a mechanism by which bacteria can disseminate and increase transmission by fecal shedding . These hypotheses are under investigation . An additional scenario is that the transcription from P5flhDC has no effect on the synthesis of flagella but rather leads to the production of single subunits of the active transcriptional complex FlhD4C2 . It has been shown that the inhibition of FlhD4C2-dependent transcription inside host cells is due to the effect of YdiV-mediated ClpXP degradation of the FlhD4C2 complex . The expression from P5flhDC late during cell growth will not allow for motility because the activation of the ClpXP leads to the degradation of the complex . However , ClpXP in addition to degrading the FlhD4C2complex also degrades the FlhC single subunit but not FlhD . This leads to the hypothesis that single FlhD or FlhC subunits might activate transcription of other genes required for virulence [87] Our finding can be rationalized in terms of a model ( Figure 8 ) . Two regulatory factors , LrhA and RcsB regulate flhDC by inhibiting transcription from P1flhDC and P5flhDC . The effect of RcsB is more dominant on P1flhDC then on P5flhDC , whereas LrhA represses more strongly P5flhDC than P1flhDC . Transcription activation of P1flhDC by CRP leads to a rapid transcription of rflM , which in turn reduces transcription of P1flhDC , and limits a rapid class 2 and class 3 genes expression . The FlhD4C2 complex , already produced , allows motility to proceed and also promotes activation of HilD at the posttranslational level through FliZ , ultimately leading to activation of transcription from the P5flhDC promoter . This positive autoregulation also generates a subsequent inhibition of flhDC operon transcription , of both P1flhDC and P5flhDC promoters , by two HilD-induced regulatory factors SlyA and RtsB , themselves regulated by different environmental cues . The activation of transcription from P5flhDC would lead to higher expression of FlhD4C2 . Though not necessary for motility , it could affect expression of HilD . Because , HilD is required for Salmonella survival inside host cells , this positive circle of activation might be well suited for virulence .
Bacterial strains and primers used in this study are listed in Table S1 and Table S2 , respectively ( Supplementary Information ) . Bacterial cells were routinely grown in Luria-Bertani ( LB ) broth and , when necessary , supplemented with appropriate antibiotics at the following concentrations: Kanamycin ( 5–10 µg/ml ) , tetracycline ( 15 µg/ml ) in agar plates and for induction of T-POP 3 . 5 µg/ml ) . L-arabinose was used at 0 . 2% ( w/v ) when needed . Motility agar plates were prepared as described earlier [62] . The generalized transducing phage of S . typhimurium P22HT105/1 int-201 was used in all transductional crosses [88] For the construction of strain TH18684 DUP[ ( PwtflhDC8093-luxCDBAE ) *Km* ( PwtflhDC-flhD+C+ ) ] primers 5104 and 5103 [designed to delete the replication origin and tetracycline resistance ( TcR ) cassette of the plasmid pRG38 [89]] were used to amplify the kanamycin cassette of pKD3 . The PCR product was electroporated into TH18710 ( LT2/pKD46/pRG38 ) followed by selection for kanamycin resistance ( KmR ) . KmR colonies were pooled and infected with P22 to produce a transducing lysate . This lysate was used to transduce LT2 selecting KmR . The KmR transductants were replica-plated in LB+Km and LB+Tc . Tc-sensitive ( TcS ) and KmR colonies should have resulted from integration of PflhDC-luxCDBAE into the chromosome generating a duplication of the promoter region of the flhDC operon . To check the integration of a single copy of PflhDC-luxCDBAE-Km and to screen for the presence of any duplication of the luxCDBAE upon integration , a set of primers [1401 ( reverse for luxC ) - 3091 ( forward in upstream of PwtflhDC promoter region not present in the plasmid pRG38 ) ] demonstrated the correct integration of the plasmid at the flhDC promoter region . A second PCR reaction using [Primers 267 ( Km ) and 1403 ( luxE ) ] demonstrated the correct placement of Km cassette after the luciferase operon . Amplification with primers , 1403 and 1401 , indicated a single copy integration of the plasmid without its origin of replication . Five candidates were obtained having a single integration of PwtflhDC-luciferase into the chromosome . One of the five candidates was sequenced and used in this study ( TH18684 ) . The Duplication of PflhDC was maintained in the presence of 5–10 µg/ml Km . Mutations in the promoter region of PflhDC-lux were constructed using the λ-Red recombinase system , as reported previously [90] , using the primers listed in Table S2 . All transcriptional fusion constructs using the luciferase operon reporter used the strain TH18727: ( DUP[ ( PflhDC8093::tetRA-luxCDBAE*Km* ( PflhDCflhD+flhC+ ) ]/pKD46 ) as the electroporation recipient . Individual fusion constructs with specific promoter regions were designed as follows: the rcsB promoter region included 400 bp upstream of the start codon through 230 bp of coding region , the rcsD promoter region included 466 bp upstream of the start codon through 260 bp of coding region , the slyA promoter region included 258 bp upstream of the start codon and 290 bp of the coding region , the hilD promoter region included 300 bp upstream of the start codon through 240 bp of coding region , the rtsA promoter region included 264 bp upstream of the start codon through 290 bp of coding region , the lrhA promoter region included 880 bp upstream of the start codon through 200 bp of coding region and the rflM promoter region included 460 bp upstream of the start codon through 284 bp of coding region . The promoter regions defined above were amplified by PCR using the respective primers listed in Table S2 , and electroporated into strain TH18727 , using the Lambda-Red recombinase system selecting for replacement of tetRA element with a PCR-amplified DNA fragment [90] . Chromosomal FLAG-tagged HilD , RcsB and chromosomal HA-tagged RtsB , SlyA , RflM , HilD and LrhA were generated by the Lambda-Red recombinase system , as described previously [91] using gene-specific primer pairs , as shown in Table S2 . All strains were verified by PCR amplification and DNA sequence analysis . LB+Km medium containing 1% tryptone , 0 . 5% yeast extract , and 0 . 5% NaCl was used for growth of all bacterial cultures to determine the transcription activities of luciferase . Overnight cultures in LB+Km cultures were adjusted to the same OD 595 nm , then , 8-ml glass tubes containing 2 ml of LB+Km were inoculated with a 500-fold dilution of the bacterial suspensions and incubated at 30°C in a water bath with shaking at 250 rpm . For determination of luciferase activity in batch cultures , samples ( 200 µl ) were taken at different time point and the light production along with the OD595 were measured in 96 well plates in a microplate reader ( PolarStar Optima ) . For the determination of luciferase activity in 96 well plates , adjusted OD595 of overnight bacterial cultures at 37°C were diluted 500-fold in LB+Km and 200 µl of diluted bacteria were added to 96 well dark plates ( Greiner ) . The plates were sealed with breathe easy membrane ( to minimize evaporation and to allow growth in semi-aerobic conditions ) and incubated in a chamber/shaker of a PolarStar Optima microplate reader ( BMG labtech ) set at 30°C . The conditions of the plate reader to determine the light production and OD 595 nm were as follow: orbital Shaking for 300 s at 150 rpm , 5 s stop and 95 s for luciferase light reading of the wells . For normalization of results a 0 . 1 s integration time was used . The OD 595 nm and light production ( luciferase ) was measured over time using a PolarStar Optima microplate reader ( BMG labtech ) . For the background , we took the average measurements of the strain ( TH18402 ) harboring mutations in all the promoters of flhDC . After background correction , relative light units ( Arbitrary Units ) were calculated by dividing the lights reading with its corresponding OD 595 nm . The OD 595 nm in our setting of the PolarStar Optima reader corresponds to ∼1 . 69 factor of the OD 595 nm read with 1 ml spectrophotometer . Whole-cell extracts were prepared from samples of cultures grown in LB . 500-ml flasks containing 100 ml of LB were inoculated with a 500-fold dilution of the bacterial suspensions and incubated at 30°C in an orbital shaker at 150 rpm . Cells were collected at different optical densities ( 0 . 25 , 0 . 4 , 0 . 6 , 0 . 8 , 1 and 1 . 3 ) and washed twice with ice cold PBS . Pellets were lysed , at room temperature for 15 minutes , using B-PER reagent ( Fisher , product #78243 ) with freshly added lysozyme ( 1 mg/ml ) and protease inhibitors ( Roche ) . The lysates were clarified by centrifugation at 4°C for 10 minutes . Supernatants were transferred to new eppendorfs and the extracted proteins were quantified using the BSA assay ( BioRad ) . Samples , containing 50 µg of total protein per lane , were electrophoresed onto 12% to 14% Tris/SDS gels . To detect RtsA-HA a 15% Tricine-SDS gel was used as described [92] . Following transfer onto a 0 . 45 µm pore size polyvinylidene difluoride ( PDVF ) membrane ( Immobilon P , Millipore ) using a semidry transfer apparatus ( Bio-Rad ) , membrane were blocked for 1 hour at room temperature with freshly prepared non-fat dry milk ( 5% w/v ) in PBS . For detection of HA-tagged or Flag-tagged proteins , membrane blots were incubated overnight at 4°C with anti-HA ( Covance ) or anti-Flag M2 ( Sigma ) mouse monoclonal antibodies at 1∶1 , 000 and 1∶2 , 000 dilutions respectively . DnaK was detected using Anti-DnaK ( Covance ) diluted 1∶10 , 000 . The blots were washed three times with PBS-T ( PBS+0 . 1% tween ) and incubated protected from light with green or red infrared dye-conjugated secondary antibody in non-fat dry milk ( 3% w/v ) in PBS-T for 45 minutes at room temperature . Following three washes in PBS-T and one wash in PBS . Labeled proteins bands were detected using the Odyssey Infrared Imaging System ( Li-COR Biosciences , Lincoln , NE , USA ) . CHIP was performed as in [93] with modifications . Bacterial batch cultures were grown at 30°C to different ODs , at which point formaldehyde ( final concentration of 1% ) was added to cells . After 20 min at room temperature in an orbital shaker , cross-linking was quenched by the addition of glycine ( 500 mM ) for 10 minutes . Samples were then placed on ice for an additional 10 minutes to complete quenching . Cells were collected by centrifugation , and washed twice with cold phosphate-buffer saline ( pH 7 . 5 ) . Cells pellets were resuspended in 1 ml of lysis buffer ( 10 mM Tris , pH 8 . 0 , 20% sucrose , 50 mM NaCl , 10 mM EDTA , 10 µg/ml of lysozyme ) and incubated at 37°C for 30 min . Following lysis , 1 ml of immunoprecipitation buffer ( 50 mM HEPES-KOH , pH 7 . 5 , 150 mM NaCl , 10 mM EDTA , 1% Triton X-100 , 0 . 1% sodium deoxycholate , 0 . 1% sodium dodecyl sulfate ) and phenylmethylsulfonyl fluoride ( final concentration of 1 mM ) were added . To shear cellular DNA to an average size of 500 to 1 , 000 bp , the cell extracts were sonicated on ice using Misonix Sonicator 3000 with a microtip at power 2 for three 10 s pulses , with 30 s rests on ice between pulses . The lysates were clarified by centrifugation and the supernatant were treated with 5 µl RNaseA ( 10 µg/ml ) at 37°C for 30 minutes . The treated supernatant was retained for use as the input sample in the immunoprecipitation experiments . Aliquots of sheared samples were uncross-linked by incubation for 2 h at 42°C and 6 h at 65°C in 0 . 5× elution buffer containing freshly added 0 . 8 mg/ml of Proteinase K . DNA was purified using a PCR purification Kit ( Bioline ) . An aliquot of purified DNA was run in a 1 . 25% agarose gel to confirm the shearing of DNA to 500–1000 bp fragments and DNA was quantified using Nanodrop spectrophotometer . An Aliquot of the input sample ( 2 µg ) was used for each immunoprecipitation experiment . The sample was incubated with 50 µl of proteinPlus A/G beads ( Santa Cruz ) and 4 µl of HA monoclonal antibody ( Covance ) or Flag M2 antibody ( Sigma ) for 90 min at room temperature on a rotating wheel . An immunoprecipitation experiment without antibody was also set up as a negative control . The beads were collected by centrifugation and subsequently washed three time with immunoprecipitation buffer and once with immunoprecipitation buffer plus 300 mM NaCl , once with wash buffer ( 10 mM Tris-HCl , pH 8 . 0 , 250 mM LiCl , 1 mM EDTA , 0 . 5% Nonidet-P40 , 0 . 5% sodium deoxycholate ) and finally with PBS buffer ( pH 7 . 5 ) . Immunoprecipitated complexes were then removed from the beads by treatment with elution buffer ( 50 mM Tris-HCl [pH 7 . 5] , 10 mM EDTA , 1% SDS ) . Crosslinking of immunoprecipitated samples was reversed by incubation for 2 h at 42°C and 6 h at 65°C in 0 . 5× elution buffer with 0 . 8 mg/ml of Pronase ( Roche ) . Prior to analysis , DNA was purified from the immunoprecipitate by using a PCR purification kit ( Bioline ) and resuspended in 30 µl of TE and quantified using a Nanodrop spectrophotometer . Two micrograms of the fragmented DNA , isolated from DNA-protein complexes , was used as the input in all ChIP assays . Following purification , Real-time PCRs were run on a C1000 thermal cycler ( BioRad ) to analyze immunoprecipitated DNA . DNA samples were used in a 20 µl reaction mix containing a 1 µM concentration of each oligonucleotide and 10 µl of 2× SYBR-Green Reaction mix . Two pairs of primers , 3569-3477 and 3753-3090 covering the promoter region of flhDC were used ( Table S2 ) . PCR conditions were as follow: Initial denaturation at 95°C for 3 min , and 40 cycles of 95°C for 15 s and 60°C for 1 min , followed by the default melting curve program of the PCR machine . Fold-enrichments were determined by the 2−ΔCT method described in SA Biosciences User manual . To account for chromatin sample preparation differences , CHIP DNA fractions Ct values ( Mean threshold cycles ) were normalized ( ΔCt ( normalized ChIP ) to the Input DNA fraction Ct values by substracting the Ct-values of the sample from the corresponding no antibody control . The percentage input of each ChIP fraction was calculated using 2 ( −ΔCt ( normalized ChIP ) and adjusted to the normalized background ( No antibody ) using the following formula: ΔΔCt ( Chip ) = ΔCt ( normalized ChIP ) −ΔCt ( normalized NoAb ) . The IP fold enrichment was then calculated using 2 ( −ΔΔCt ( ChIP/NAC ) ) to evaluate the fold amount of starting material of the sample applied in the real-time PCR .
|
Flagellar-mediated motility is fundamental to Salmonella pathogenesis , which takes the lives of hundreds of thousands of people each year . The genes of the Salmonella pathogenicity island 1 and those of the flagellar regulon are part of the same transcriptional hierarchy . We report the novel finding where the key control of this network takes place at the flhDC promoter region . We followed the transcription from the two “live” flhDC promoters as a function of the cell growth phase . P1 comes on early in the cell cycle , while P5 comes on late . Transcription of P5 is HilD dependent , which represents a totally new finding and Salmonella specific: there is no HilD in E . coli flhDC control , no P5 transcription . P1 & P5 can express flhDC to equivalent levels , yet only P1- dependent expression produces motility UNLESS we artificially induce P5 EARLY in the cell cycle . This work is the foundation for the cell cycle stages a Salmonella bacterium experiences during host infection . This is a significant conceptual advance in Salmonella pathogenesis: one can no longer consider gene regulation at 37°C and OD 0 . 6 as a reflection of the Salmonella infection cycle; the whole cell growth cycle must be considered in understanding this complex biological processes .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"biology",
"microbiology"
] |
2014
|
The Effect of Cell Growth Phase on the Regulatory Cross-Talk between Flagellar and Spi1 Virulence Gene Expression
|
Schistosomes express a family of integral membrane proteins , called tetraspanins ( TSPs ) , in the outer surface membranes of the tegument . Two of these tetraspanins , Sm-TSP-1 and Sm-TSP-2 , confer protection as vaccines in mice , and individuals who are naturally resistant to S . mansoni infection mount a strong IgG response to Sm-TSP-2 . To determine their functions in the tegument of S . mansoni we used RNA interference to silence expression of Sm-tsp-1 and Sm-tsp-2 mRNAs . Soaking of parasites in Sm-tsp dsRNAs resulted in 61% ( p = 0 . 009 ) and 74% ( p = 0 . 009 ) reductions in Sm-tsp-1 and Sm-tsp-2 transcription levels , respectively , in adult worms , and 67%–75% ( p = 0 . 011 ) and 69%–89% ( p = 0 . 004 ) reductions in Sm-tsp-1 and Sm-tsp-2 transcription levels , respectively , in schistosomula compared to worms treated with irrelevant control ( luciferase ) dsRNA . Ultrastructural morphology of adult worms treated in vitro with Sm-tsp-2 dsRNA displayed a distinctly vacuolated and thinner tegument compared with controls . Schistosomula exposed in vitro to Sm-tsp-2 dsRNA had a significantly thinner and more vacuolated tegument , and morphology consistent with a failure of tegumentary invaginations to close . Injection of mice with schistosomula that had been electroporated with Sm-tsp-1 and Sm-tsp-2 dsRNAs resulted in 61% ( p = 0 . 005 ) and 83% ( p = 0 . 002 ) reductions in the numbers of parasites recovered from the mesenteries four weeks later when compared to dsRNA-treated controls . These results imply that tetraspanins play important structural roles impacting tegument development , maturation or stability .
Schistosomes are parasitic trematodes that cause chronic infection in over 207 million people in 76 developing tropical countries . Schistosomiasis is generally associated with poverty , poor water supply and inadequate sanitation [1] . Infection rates and intensities are high in early childhood , peak around 8 to 15 years and decrease in adulthood [2] . Despite effective and inexpensive widespread treatment with the anthelmintic drug praziquantel for over 20 years , this parasitic disease still causes more than 250 , 000 deaths per year and accounts for 1 . 7 to 4 . 5 million disability-adjusted life years ( DALYs ) lost annually [3] . Humans become infected with schistosomes when they are exposed to free-living cercariae in fresh water . Cercariae penetrate the skin , shed their tails and transform into schistosomula , which reside in the dermis of the skin before entering the blood capillaries to migrate through the vasculature to the portal venous system where they mature into adult worms [4] . The outer surface of schistosomula and adult worms , the tegument , is a multinucleated syncitium that contains tegumental cell bodies situated below the muscular layers . During transformation from cercaria to schistosomula , the outer surface of the tegument ( the interface with the host ) is remodeled from a single membrane with a prominent glycocalyx into an unusual double membrane ( or “heptalaminate” ) structure [5] . This double membrane is widely believed to play an essential role in the ability of schistosomes to evade the host immune system , a characteristic that allows them to live for years within their hosts [6] . The outer of the two surface membranes also has the ability to adsorb host blood molecules , masking its non-self status thereby contributing to immune evasion and prolonged survival [7] . We believe that tegumental proteins are ideal targets for immunological and pharmacological intervention [8] . The generation of a large number of S . mansoni expressed sequence tags [9] and the recently completed genome sequence [10] , in combination with advances in characterizing the tegument proteome has led to the discovery of many tegument specific proteins [11] . Among them are a group of membrane proteins called tetraspanins , which are highly expressed in the outer tegument membrane of adult schistosomes [12] , [13] . To date , five tetraspanin cDNAs have been described from S . mansoni , namely Sm-23 [12] , Sm-tsp-1 and Sm-tsp-2 [13] , Sm-tetraspanin-B and Sm-tetraspanin-C [14] . Tetraspanins are a large superfamily of surface-associated membrane proteins characterized by the conserved structure of four hydrophobic transmembrane domains , a small and large extracellular loop , an interconnecting intracellular loop , and cytoplasmic amino- and carboxyl- termini [15] . Tetraspanins undergo post-translational modification in which palmitate is bound to the membrane proximal cysteine residues and associates with cholesterol-rich domains [16] . This process enables tetraspanins to play key roles in molecular organization of cell membranes , interacting with one another and also specific partner proteins such as integrins , MHC and co-stimulatory molecules to form large signal transducing complexes termed tetraspanin-enriched microdomains ( TEMs ) [17] . Tetraspanins are widely distributed in many cell types but their physiological roles are mostly unknown . Several lines of evidence have implicated tetraspanins in the regulation of cell adhesion , differentiation , motility , aggregation , cell signaling and sperm-egg fusion [18] , [19] , [20] , [21] . They have been linked to various pathological processes including lymphocyte activation [19] , cancer [22] , fertilization [23] , [24] , and interactions between pathogens and host cells such as HIV [25] , HCV [26] and Plasmodium [27] . We previously identified two cDNAs , Sm-tsp-1 ( Sm01494 ) and Sm-tsp-2 ( Sm12366 ) , in adult S . mansoni using signal sequence trapping [13] , and showed that both of these tetraspanins were expressed in the tegument of the adult parasite [28] . Other authors confirmed the surface expression of these tetraspanins using various mass spectrometric approaches to characterize the schistosome surface [11] , [29] , [30] . We expressed the large extracellular loop of Sm-TSP-1 and Sm-TSP-2 in E . coli and used the soluble recombinant proteins to immunize mice and then challenged them with cercariae . Mice vaccinated with recombinant Sm-TSP-1 and Sm-TSP-2 had significantly reduced adult worm , liver egg and fecal egg burdens [28] . Moreover , strong IgG1 and IgG3 antibody responses against Sm-TSP-2 were detected in sera of individuals deemed putatively resistant ( PR ) to S . mansoni in comparison to sera from chronically infected individuals [28] . Despite their promise as vaccines against schistosomiasis , the functions of Sm-TSP-1 and Sm-TSP-2 have not yet been elucidated . We therefore employed RNA interference ( RNAi ) to explore the roles of Sm-tsp-1 and tsp-2 in larval and adult S . mansoni . RNAi has been utilized with S . mansoni to suppress endogenous gene expression in schistosomula [31] , adult worms [32] , eggs [33] and sporocysts [34] . Here , we show that RNAi results in reductions in expression of Sm-tsp-1 and tsp-2 mRNAs in schistosomula and adult worms , and malformation of the tegument in worms cultured in vitro . Moreover , silencing of tsp-1 and tsp-2 expression in schistosomula results in up to 90% fewer worms maturing to adulthood when introduced into mice compared with parasites exposed to control dsRNAs , highlighting their essential roles in tegument biogenesis and maintenance and further supporting the development of novel therapies targeting these genes and their protein products .
Expression of Sm-tsp-1 and Sm-tsp-2 mRNAs in different stages of the S . mansoni life cycle was determined relative to control Sm-α-tubilin mRNA using qRT-PCR . Sm-tsp-1 and Sm-tsp-2 mRNAs were detected in all stages of the schistosome life cycle with higher levels identified in eggs , miracidia and cercariae than in 5-day old schistosomula , males and female worms for tsp-1; a similar expression profile was observed for tsp-2 but gene expression was notably reduced in cercariae ( Figure 1 ) . Interestingly , the highest level of Sm-tsp-1 expression was detected in cercariae whereas Sm-tsp-2 expression was lowest in cercariae . We previously demonstrated that Sm-TSP-1 and Sm-TSP-2 are expressed on the tegument surface membrane of adult worms [28] . The tegument is fully formed by 3h after cercarial transformation [35] , so to determine whether these TSPs are expressed in the tegument at this early stage after host entry and whether they are accessible to antibodies on live parasites , we probed live newly transformed schistosomula with antibodies against both proteins . Both Sm-TSP-1 and Sm-TSP-2 were detected over the entire surface tegument of live schistosomula when probed with mouse anti-TSP-1 or -TSP-2 sera followed by FITC-labelled anti-mouse IgG ( Figure 2 ) . Adult worms soaked for 7 days in Sm-tsp-1 dsRNA had a 61% ( p = 0 . 009 ) reduction in Sm-tsp-1 mRNA expression compared to parasites soaked in control dsRNA ( Figure 3A ) . A 74% ( p = 0 . 009 ) reduction in Sm-tsp-2 mRNA levels was detected in worms that were cultured in media containing Sm-tsp-2 dsRNA compared to parasites soaked in luciferase dsRNA ( Figure 3B ) . Parasites were visually monitored for motility on a daily basis but no differences were detected between groups ( not shown ) . Soaking of 3 h old schistosomula in Sm-tsp-1 dsRNA for 7 , 14 and 21 days caused 75% ( p<0 . 001 ) , 67% ( p = 0 . 019 ) and 69% ( p = 0 . 021 ) decreases in Sm-tsp-1 mRNA expression in comparison to the control group ( Figure 4A ) . Larval parasites incubated with Sm-tsp-2 dsRNA for 7 days exhibited an 88% ( p<0 . 001 ) decrease in Sm-tsp-2 transcript levels compared to luciferase dsRNA treated schistosomula ( Figure 4B ) . RNAi knockdown was maintained with reductions of 82% ( p = 0 . 004 ) and 69% ( p = 0 . 021 ) at days 14 and 21 , respectively , compared to the control group . As observed in adult worms , suppression of Sm-tsp RNAs resulted in no obvious phenotypic differences compared to the luciferase dsRNA-treated control group when examined by light microscopy . Cultures were visually inspected using a light microscope on a daily basis and no differences in early growth and development of schistosomula ( development of intestinal ceca or size of schistosomula ) [36] were apparent between test and control dsRNA treated groups . To determine whether knockdown of Sm-tsp-2 RNA was evident at the protein level , we performed Western blot analysis on dsRNA treated adult ( Figure 5A ) and larval ( Figure 5B ) parasites . Parasites were treated with Sm-tsp-2 or luciferase dsRNAs , lysed in 1% Triton X-100 and immunoblotted with anti-Sm-TSP-2 or anti-Sm-Pmy antibodies which target a sub-tegumental muscle protein , paramyosin [37] . Sm-TSP-2 protein expression was decreased in adult worms treated with Sm-tsp-2 dsRNA compared to worms treated with luciferase dsRNA for the four concentrations ( 2 . 0 , 1 . 0 , 0 . 5 and 0 . 25 µg ) tested . In contrast , the Sm-Pmy protein expression levels did not change in both test and control groups . The experiment was repeated three times with similar results and a representative image is shown ( Figure 5A ) . Densitometry analysis was performed on each band and the ratio of Sm-TSP-2 to Sm-Pmy at each concentration was calculated . Analysis of whole worm lysates ( 0 . 25 µg ) by densitometry ( not shown ) revealed an average of 61% ( p = 0 . 027 ) reduction in Sm-TSP-2 expression in adult worms treated with Sm-tsp-2 dsRNA compared to the control luciferase group . For RNAi treated schistosomula , the amount of Sm-TSP-2 protein expressed by schistosomula after 7 days in culture with Sm-tsp-2 dsRNA was reduced compared to parasites soaked in luciferase dsRNA ( Figure 5B ) . Densitometry analysis of lysates ( 2 µg , 1 µg and 0 . 5 µg ) showed an average decline of 36% ( data not shown ) . This decrease was lower than expected since suppression of Sm-tsp-2 mRNA was more pronounced in schistosomula than in adult parasites . Adult and larval parasites soaked in Sm-tsp-1 dsRNA demonstrated no obvious differences in protein expression to luciferase dsRNA control worms by Western blotting analysis ( data not shown ) . Adult parasites and schistosomula treated with Sm-tsp-2 dsRNA in vitro displayed modified tegument structure when visualized with transmission electron microscopy ( TEM ) compared with luciferase dsRNA treated controls ( Figure 6 ) . The tegument of adult worms incubated in vitro in Sm-tsp-2 dsRNA ( Figure 6C , E ) was more highly vacuolated than luciferase dsRNA controls ( Figure 6A ) , with extensive and enlarged vacuoles throughout the surface layer . The tegument of these parasites had less apparent cytoplasm and hence fewer cytoplasmic inclusions and was frequently much thinner than that of controls ( Figure 6C , E ) . Schistosomula transformed and cultured in vitro presented a tegument that resembled that of larvae from natural or experimental infection ( Figure 6B ) [38] . The tegument in Sm-tsp-2 dsRNA treated schistosomula ( Figure 6D , F ) was consistently thinner than those of luciferase controls ( P<0 . 001 ) , measuring on average 0 . 3784±0 . 016 µm compared with 0 . 5842±0 . 323 µm for luciferase controls ( Figure 6G ) . Volume density measures for invaginations and clear vesicular compartments of the tegument showed higher volumes for these compartments in Sm-tsp-2 treated schistosomula ( p = 0 . 014; Figure 6F ) . The morphology of the schistosomula tegument was consistent with a failure to close invaginations of the surface ( Figure 6D , F ) . Adult worms and schistosomula soaked in Sm-tsp-1 dsRNA showed no obvious differences to luciferase dsRNA control worms when examined by transmission electron microscopy ( data not shown ) . In the mammalian host , larval schistosomes migrate from the skin through the lungs to the liver and then mature in the mesenteric veins [4] . In an effort to mimic in vivo conditions , 3 h schistosomula were electroporated with 100 µg/ml of Sm-tsp-1 , Sm-tsp-2 or luciferase dsRNA and then injected intramuscularly into female C57BL/6 mice . Four weeks later mice were perfused to determine the number of parasites that reached maturity in the mesenteries . Significantly fewer parasites were recovered from the mesenteric veins compared to the luciferase control group ( see Figure 7A for results of three experiments ) . Mice injected with schistosomula that were electroporated with Sm-tsp-1 dsRNA yielded 48% ( p = 0 . 045 ) , 60% ( p = 0 . 009 ) and 67% ( p = 0 . 019 ) reduction in the number of parasites recovered for Experiments 1 , 2 and 3 , respectively in comparison to the luciferase control group . Schistosomula pretreated with Sm-tsp-2 dsRNA and then injected into mice resulted in 70% ( p = 0 . 039 ) , 91% ( p = 0 . 009 ) and 78% ( p = 0 . 018 ) decreases in parasite survival for Experiments 1 , 2 and 3 , respectively when compared to the luciferase dsRNA group . The numbers of mature worms harvested from the luciferase control group were very low , with recovery ranging from 0 . 5-1 . 5% , however the data was consistent between three experiments , with a reproducible and significant reduction in worm recovery rates between tsp and luciferase dsRNA treated parasites . RNA was extracted from surviving worms that were perfused from mice and transcript levels were analyzed by qRT-PCR . Sm-tsp-1 expression was only slightly lower ( 17% ) in worms recovered from mice that were infected with Sm-tsp-1 dsRNA-treated schistosomula compared to the control group . Likewise , Sm-tsp-2 expression was slightly reduced ( 15% ) in worms recovered from mice that were infected with Sm-tsp-2 dsRNA treated worms compared to the luciferase control group ( Figure 7B ) . However , when the same batch of dsRNA electroporated schistosomula were cultured in vitro for the same period of time ( 4 weeks ) , as opposed to being injected into mice , significant knockdown of Sm-tsp-1 and Sm-tsp-2 transcripts by 58% and 87% , respectively ( Figure 7C ) , was observed . These results illustrate that silencing of Sm-tsp-1 and Sm-tsp-2 by either soaking or electroporation leads to suppression of tetraspanin genes in schistosomes , and suppression is maintained for at least 4 weeks in culture . The data also implies one of three possible outcomes for Sm-tsp dsRNA treated schistosomula that survived to adulthood after being transferred into mice; ( 1 ) RNAi was not as effective in those individual schistosomula that survived in mice as opposed to those that perished; ( 2 ) some of the RNAi treated parasites received ( or took up ) less dsRNA , and therefore the efficacy of gene suppression was variable between individuals in a single electroporated batch; ( 3 ) it is also possible that host developmental cues stimulate transcription .
Schistosomes express a family of tetraspanins in their tegument . Sm23 was the first tetraspanin identified in S . mansoni [12] , and is of interest as a DNA vaccine antigen against schistosomiasis [39] . Its orthologue from S . japonicum , Sj23 , protects water buffaloes against challenge infection when administered as a DNA vaccine [39] . We identified two additional tetraspanins , Sm-tsp-1 and Sm-tsp-2 , which showed high levels of protection when administered to mice as recombinant protein vaccines against S . mansoni [13] , [28] . However , despite the protective efficacy that these tetraspanins afford , their functions in the parasite are unknown . To understand the roles that these proteins play in the schistosome tegument , we herein explored the effects of silencing the expression of Sm-tsp-1 and Sm-tsp-2 mRNAs in adult and larval S . mansoni . RNAi has been used to suppress a number of schistosome genes in an effort to determine their functions [40] , [41] . Soaking of S . mansoni with dsRNA encoding the intestinal protease cathepsin B ( SmCB1 ) , resulted in greater than 10-fold decrease in SmCB1 mRNA levels and significant growth inhibition compared to parasites treated with control dsRNA [42] . Suppression of the mRNA encoding another intestinal protease , S . mansoni cathepsin D ( SmCD ) , in schistosomula by electroporation with dsRNA led to reduction in RNA transcript levels , growth retardation in vitro and in vivo , and decreased cathepsin D enzymatic activity [43] . Silencing of the SmAQP gene encoding a water channel protein by electroporating schistosomula with short interfering RNAs suppressed mRNA and protein expression in the tegument , and treated parasites cultured in vitro exhibited stunted growth and lower viability [44] . RNAi has been used to determine the functional importance of tetraspanins in other organisms [45] . Suppression of tetraspanin-15 mRNA by feeding C . elegans with dsRNA resulted in dissociation of the cuticle and degeneration of the hypodermis , compromising epidermal integrity [46] . RNAi has also been used to determine the function of human tetraspanins in various cell types [45] . For example , the CD151 tetraspanin interacts with membrane proteins including the laminin-binding integrin α3β1; when lung adenocarcinoma cells were cultured on laminin-511 and then treated with CD151 siRNA , abnormal membrane protrusions on laminin-511 were apparent and tyrosine phosphorylation dependent signalling was reduced [47] . These findings indicate a role for tetraspanins in the maintenance of cell membrane biogenesis and structural integrity , and support our observations on the compromised tegument membrane formation in S . mansoni when tsp mRNA expression is suppressed . Numerous reports have documented molecular interactions between tetraspanins and MHC , and involvement of human tetraspanins in regulating T cell co-stimulation and peptide/MHC presentation [48] , [49] , [50] , indicating additional , non-structural roles . Schistosomes acquire host MHC onto their surfaces [51] , presenting the intriguing possibility that they function as a receptor for host MHC . However , the majority of mammalian tetraspanin binding partners identified to date are membrane proteins rather than extracellular ligands [45]; moreover , our data presented here implies that schistosome tetraspanins are pivotal for proper tegument formation , even during in vitro culture in the absence of immune cells , supporting a structural role in the establishment and maintenance of the tegument . Indeed , the tetraspanin CD9 complexes with numerous proteins including Ig-containing proteins [52] , a family of proteins which are also present in the S . mansoni tegument membrane [30] . Various authors have described the contribution of tetraspanins , such as CD9 and CD151 , with members of the integrin family in promoting cell-cell interactions and migration [53] , [54] , [55] . Mass spectrometric analysis of the S . mansoni tegument revealed a β-integrin subunit in the sub-tegumental layer [29] . Suppression of tetraspanin mRNA expression in schistosomes may affect lateral interactions with integrins in the tegument , and the parasite's ability to migrate through the lungs to the liver and mesenteries where they would mature . The binding partner ( s ) associated with Sm-TSP-1 or Sm-TSP-2 , or any of the other three S . mansoni tegument tetraspanins , have yet to be identified . We have produced monoclonal antibodies to Sm-TSP-2 and these antibodies are being used to immunoprecipitate Sm-TSP-2 and its binding partners in an effort to unravel the tegumental tetraspanin web . To assess the viability of dsRNA treated parasites in vivo , we injected tsp or luciferase dsRNA treated parasites into mice via the intramuscular route [56] . Recovery of adult worms from the mesenteries 4 weeks later was very low but was in agreement with other reports where newly transformed schistosomula were electroporated with dsRNAs prior to intramuscular injection into mice and subsequent recovery of adult worms from the mesenteries [41] . The natural route of S . mansoni infection is through percutaneous penetration of cercariae; exposure of laboratory mice to cercariae is generally performed via the abdomen or tail . Intramuscular injection of mice with schistosomula is not the natural infection route and consequently may have contributed to the low recovery rates . Despite the low recovery of adult parasites , we consistently over three experiments recovered significantly fewer worms from the mice injected with tsp dsRNA treated parasites . Moreover , tsp mRNA levels in those parasites that were recovered from mice were higher than levels in parasites cultured in vitro for the same time period after electroporation with dsRNAs , indicating that the parasites that survived in vivo had not succumbed to the effects of RNAi . We envisage that interruption of Sm-TSP-1 and TSP-2 protein expression in the tegument of maturing schistosomula results in impaired turnover of the tegument apical membrane complex . Our observations from adults and schistosomula treated with Sm-tsp-2 dsRNA would indicate that a likely role for Sm-tsp-2 is in invagination and internalization of the surface membrane , and perhaps the closure and internalization of surface invaginations . This postulate is consistent with the suggestion that TSP-2 binds other parasite sub-surface and surface molecules in the tegument . The vaccine efficacy of TSP-2 may thus result from impairment of the surface recycling mechanisms in developing and adult schistosomes . While this impaired surface turnover was not deleterious to in vitro cultivated adult worms and schistosomula , the effect was particularly marked in treated schistosomula transferred into the host . In addition , schistosomes have the capacity to adsorb host blood molecules that mask antigenic epitopes from the host's immune system [7] . By affecting surface tegument development and turnover , suppression of tsp expression ( and potential disruption of TEMs ) may render the organism susceptible to immune recognition and clearance .
All animals were maintained in accordance with the guidelines of the Animal Ethics Committee ( AEC ) of Queensland Institute of Medical Research and the Institutional Animal Care and Use Committee ( IACUC ) of The University of Pennsylvania . All studies and procedures were reviewed and approved by the AEC and IACUC of Queensland Institute of Medical Research and The University of Pennsylvania respectively . The Puerto Rican strain of S . mansoni and Biomphalaria glabrata snails were provided by the National Institutes of Allergy and Infectious Diseases Schistosomiasis Resource Centre at the Biomedical Research Institute ( Rockville , Maryland , USA ) . B . glabrata infected with miracidia were exposed to incandescent light for 1h to obtain cercariae which were used to percutaneously infect 6–8 week old C57BL/6 female mice ( www . jax . org ) . After 8 weeks , adult parasites were recovered by hepatic-portal perfusion and then washed three times with wash medium containing RPMI 1640 , 1% antibiotic/antimycotic and 10 mM Hepes ( www . invitrogen . com ) before experimentation . To obtain schistosomula , cercariae were passed through a 22-gauge emulsifying needle 25 times to mechanically shear the cercarial tails from the bodies [57] . The resulting schistosomula were isolated from free tails by centrifugation through a 60% percoll gradient [58] , washed three times with washing medium and incubated at 37°C under 5% CO2 atmosphere before experimentation . Three hour schistosomula ( n = 500 ) were blocked in blocking buffer containing 1% goat serum in Dulbecco's Phosphate Buffered Saline ( DPBS ) containing MgCl2 and CaCl2 ( www . invitrogen . com ) . Schistosomula were labelled with sera against recombinant Sm-TSP-1 , Sm-TSP-2 or control pre-vaccination sera [28] diluted to 1∶50 in blocking buffer for 1 h . Secondary goat anti-mouse Ig-FITC ( www . chemicon . com ) was then introduced at 1∶100 dilution in blocking buffer for 1 h followed by 4% paraformaldehyde to fix the parasites . Incubations were carried out at 4°C and parasites were washed in DPBS between incubations . Approximately 200 schistosomula were examined using a Leica MRIRB microscope and DC500 camera ( www . leica . com ) . dsRNAs were prepared from DNA templates that were amplified by PCR from S . mansoni paired adult worm cDNA using primers flanked with T7 RNA polymerase promoter sequence ( underlined ) at the 5′ ends . A 523 bp fragment of the Sm-tsp-1 coding DNA was generated using primers ( forward: 5′-TAATACGACTCACTATAGGGACTTGCTTCGGGACAACAAC-3′ , reverse: 5′-TAATACGACTCACTATAGGGTTCGAAAGCTGCAATAGAAACA-3′ ) and a 565 bp fragment of the Sm-tsp-2 coding DNA was produced using primers ( forward: 5′-TAATACGACTCACTATAGGGTGATTGTGGTTGGTGCACTT-3′ , reverse: 5′-TAATACGACTCACTATAGGGGACCAATGCGAACAGAAACA-3′ ) . The GenBank accession numbers for Sm-tsp-1 and Sm-tsp-2 are AF521093 and AF521091 , respectively . The PCR products were then utilized as templates for synthesis of dsRNAs using the T7 Megascript kit ( www . ambion . com ) , following the manufacturer's instructions . An irrelevant negative control , firefly luciferase dsRNA derived from pGL3-basic ( www . promega . com ) , was prepared as described previously [31] . Adult schistosomes were cultured in vitro in Medium 199 ( www . invitrogen . com ) supplemented with 10% fetal calf serum ( www . gembio . com ) , 1% antibiotic/antimycotic and 10 mM Hepes at 37°C under 5% CO2 atmosphere . Five pairs of adult worms were soaked in the presence of Sm-tsp-1 , Sm-tsp-2 or luciferase dsRNAs at 1 µg/ml for 7 days with changes of media and dsRNAs every second day . Schistosomula were maintained at 37°C with 5% CO2 in Medium 169 [36] supplemented with 10% human AB serum ( www . gembio . com ) and mouse whole blood . Larval parasites ( 3 h old ) were soaked in 1 µg/ml of Sm-tsp-1 , Sm-tsp-2 or luciferase dsRNAs and cultured in vitro at 37°C under 5% CO2 atmosphere for 7 , 14 and 21 days , with fresh changes of media , blood and dsRNAs every second day . Adult and larval parasites were washed in wash medium prior to RNA or protein extraction . Newly transformed schistosomula were incubated in wash medium at 37°C with 5% CO2 for 3 h . Parasites were then resuspended in 50 µl of wash medium with 100 µg/ml of Sm-tsp-1 , Sm-tsp-2 or luciferase dsRNAs and electroporated in a 4 mm cuvette at 125 V for 20 ms using a square-wave BTX ECM 830 electroporator ( www . btxonline . com ) . After three washes in wash medium , schistosomula were counted and 2000 were injected intramuscularly into each C57BL/6 female mouse ( 3 mice per group ) using a 23-gauge needle . Adult worms were perfused 28 days later to assess the number of worms that had matured and reached the mesenteries . RNA was isolated from parasites using RNeasy Mini kit ( www . qiagen . com ) and then treated with Turbo DNA-free endonuclease ( www . ambion . com ) to remove contaminating genomic DNA . The quantity of RNA was measured on a Nanodrop Spectrophotometer ( www . nanodrop . com ) and 250 ng of total RNA , SuperScript II reverse transcriptase ( www . invitrogen . com ) and oligo dT15 primer ( www . promega . com ) were used to synthesize first strand cDNA . The following primers were designed for real-time qRT-PCR; Sm-TSP-1 ( forward: 5′-TGGTTGTGCTTATTGGGTTG-3′ and reverse: 5′-TGATGTCTTGTGCCTCTGGT-3′ ) ; Sm-TSP-2 ( forward: 5′-CGAAATTGAACCCCCACTAC-3′ and revere: 5′-CATGCTCCAAACATCCCTAAA-3′ ) ; Sm-Paramyosin ( forward: 5′-CGTGAAGGTCGTCGTATGGT-3′ and reverse 5′-GACGTTCAAATTTACGTGCTTG-3′ ) and Sm-α-tubilin ( forward: 5′-CCAGCAAAATCAGATGGTGAA-3′ and reverse: 5′-TTGACATCCTTGGGGACAAC-3′ ) . qRT-PCR was conducted in triplicate and each reaction underwent 40 amplification cycles using an Applied Biosystems 7500 real-time PCR system ( www . appliedbiosystems . com ) with cDNA equivalent to 20 ng of total RNA , 50 nM of primers and SYBR green PCR Master Mix ( www . appliedbiosystems . com ) . Dissociation curves were generated for each sample to verify the amplification of a single PCR product . Sm-tsp transcript levels were calculated relative to Sm-paramyosin in test and irrelevant dsRNA treated parasites using the 2−ΔΔCt method [59] , and data was expressed as percent differences . For relative endogenous expression of tsp mRNAs in schistosome life cycle stages , Sm-α-tubulin was used as the endogenous standard . Sm-paramyosin was used as the housekeeping gene for analyzing Sm-tsp expression in RNAi experiments . RNAi-treated adult parasites and schistosomula were harvested after 7 days and then lysed with 1% Triton X-100 in Tris buffered saline supplemented with complete protease inhibitor cocktail EASYpacks ( www . roche . com ) . Protein concentrations of lysates were determined using a BCA protein assay kit ( www . pierce . com ) , and lysates were electrophoresed in 12% SDS-PAGE gels at concentrations of 2 , 1 , 0 . 5 and 0 . 25 µg total protein per well . Proteins were transferred to nitrocellulose membrane ( Hybond-ECL , www . gehealthcare . com ) and then probed with either anti-Sm-TSP-2 ( 3H5/2 ) monoclonal antibody supernatants ( L . Cooper , M . Tran and A . Loukas , unpublished ) diluted 1∶1 , 000 followed by anti-mouse Ig-HRP ( www . chemicon . com ) diluted 1∶5 , 000 . Reactive proteins were detected by ECL ( www . gehealthcare . com ) as per the manufacturer's instructions . To assess equal protein loading , nitrocellulose membranes were stripped after reacting with anti-TSP-2 antibodies and then re-probed with anti-paramyosin ( Sm4B1 ) monoclonal antibody supernatants [60] diluted at 1∶1 , 000 followed by anti-mouse Ig-HRP . Experiments were repeated three times and protein quantities in gel bands were determined using Syngene Tools and software ( www . syngene . com ) . Adult parasites and schistosomula were soaked in 1 µg/ml of Sm-tsp or luciferase dsRNAs for 7 days at 37°C under 5% CO2 atmosphere , washed three times in wash medium and then fixed in 3% glutaradehyde in 0 . 1M phosphate buffer at pH 7 . 4 , followed by fixation in potassium ferricyanide-reduced osmium tetroxide . After fixation , parasites were dehydrated in acetone and embedded in Epon Resin ( ProSciTech ) . Ultrathin sections were mounted onto copper grids , contrasted in uranyl acetate and lead citrate and examined and photographed using a JEM 1011 transmission electron microscope operated at 80 kV and equipped with a digital camera . A morphometric approach was employed to quantify possible changes to tegument structure in schistosomula treated with Sm-tsp-2 relative to those treated with luciferase dsRNA . Point counting stereology [61] , [62] was used to measure the volume of tegument occupied by vacuolar compartments or tegument invaginations in the tegument . Such regions were evident as clear spaces in TEM sections . Twenty individual schistosomula were selected at low magnification in the TEM . For each parasite , the first region of tegument observed that fulfilled the two criteria below was photographed at ×10 , 000 magnification . Criteria for selection were , firstly , that the region photographed was from the lateral aspect of a parasite that was clearly longer than wide and in which internal organs were present , and secondly , that the region was not excessively spinous . Volume density of vacuolar compartments of tegument were estimated using grids generated by Image J analysis software ( NIH Besthesda ) , and were calculated as the number of points on the grid intersecting a vacuolar space divided by the number of points intersecting the tegument . This was measured across the entire profile of the tegument in each electron micrograph , so that only one measure was obtained for each schistosomulum . In addition to the volume density measure , the thickness of the tegument was measured at 10 different points using the line tool in Image J . For each measure , a line was drawn digitally on each micrograph from the basal membrane of the tegument to the apical membrane . Regions where the tegument was excessively invaginated , and those containing isolated spines and sensory receptors were not measured . The 10 thickness measurements were averaged for each schistosomulum . All data are presented as the mean±standard error . Differences between groups were assessed for statistical significance using Student t-test ( GraphPad Prism Software , www . graphpad . com ) . A statistically significant difference for a particular comparison was defined as p<0 . 050 .
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Schistosomes , or blood flukes , reside in the blood vessels surrounding the liver and bowel of their human hosts . They infect 200 million people and kill many thousands each year in developing countries . The parasites cover themselves in a unique series of cell membranes called the tegument . Molecules in the tegument membranes are a major target for the development of new drugs and vaccines against the parasite . Here we show that at least one member of a family of tegument membrane proteins called tetraspanins , Sm-TSP-2 , is integral to the proper formation of the tegument and subsequent survival of the parasite in its human host , providing a potential mechanism by which a vaccine based on Sm-TSP-2 protects immunized hosts .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"infectious",
"diseases/helminth",
"infections"
] |
2010
|
Suppression of mRNAs Encoding Tegument Tetraspanins from Schistosoma mansoni Results in Impaired Tegument Turnover
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Glyceraldehyde-3-phosphate dehydrogenase ( GAPDH ) is an important enzyme in energy metabolism with diverse cellular regulatory roles in vertebrates , but few reports have investigated the importance of plant GAPDH isoforms outside of their role in glycolysis . While animals possess one GAPDH isoform , plants possess multiple isoforms . In this study , cell biological and genetic approaches were used to investigate the role of GAPDHs during plant immune responses . Individual Arabidopsis GAPDH knockouts ( KO lines ) exhibited enhanced disease resistance phenotypes upon inoculation with the bacterial plant pathogen Pseudomonas syringae pv . tomato . KO lines exhibited accelerated programmed cell death and increased electrolyte leakage in response to effector triggered immunity . Furthermore , KO lines displayed increased basal ROS accumulation as visualized using the fluorescent probe H2DCFDA . The gapa1-2 and gapc1 KOs exhibited constitutive autophagy phenotypes in the absence of nutrient starvation . Due to the high sequence conservation between vertebrate and plant cytosolic GAPDH , our experiments focused on cytosolic GAPC1 cellular dynamics using a complemented GAPC1-GFP line . Confocal imaging coupled with an endocytic membrane marker ( FM4-64 ) and endosomal trafficking inhibitors ( BFA , Wortmannin ) demonstrated cytosolic GAPC1 is localized to the plasma membrane and the endomembrane system , in addition to the cytosol and nucleus . After perception of bacterial flagellin , GAPC1 dynamically responded with a significant increase in size of fluorescent puncta and enhanced nuclear accumulation . Taken together , these results indicate that plant GAPDHs can affect multiple aspects of plant immunity in diverse sub-cellular compartments .
Innate immunity is the most ancient and evolutionarily conserved system mediating pathogen perception in animals , fungi and plants [1] . Although plants lack an adaptive immune system , germ line encoded plant immune receptors recognize pathogen derived molecules or proteins and mount a successful defense response [2] . Commonly , extracellular domains of plant immune receptors recognize conserved microbe associated molecular patterns and subsequently activate pattern triggered immunity ( PTI ) . Primarily intracellular immune receptors recognize pathogen effectors delivered into host cells during infection resulting in effector triggered immunity ( ETI ) [2 , 3] . Both PTI and ETI result in dramatic cellular changes including the production of reactive oxygen species ( ROS ) , Ca2+ influx , MAP kinase signaling , and transcriptional reprogramming [4] . Despite significant overlap in defense markers , ETI is generally viewed as a stronger response and typically culminates in a form of localized programmed cell death termed the hypersensitive response ( HR ) at the site of infection [5] . Consequently , constitutive activation of immune signaling can lead to seedling lethality or cell death , while insufficient activation results in enhanced susceptibility to infection [6 , 7] . Thus , plants have fine-tuned the duration and amplitude of immune responses at the level of the receptor and beyond to properly orchestrate plant defense responses . Robust regulation of immune responses relies on several housekeeping proteins , including heat shock protein 90 and the ubiquitin ligase-associated protein suppressor of the G2 allele of skp1 ( SGT1 ) [8 , 9] . Pathogens can also target and co-opt the use of housekeeping proteins , further highlighting their importance in immune regulation [10 , 11] . In animals , the glycolytic housekeeping protein glyceraldehyde 3-phosphate dehydrogenase ( GAPDH ) contributes moonlighting activities to various alternative processes such as DNA repair , RNA binding , membrane fusion and transport , cytoskeletal dynamics , autophagy and cell death [12–14] . Due to the strong impact of GAPDHs on metabolic homeostasis and its diverse moonlighting activities , GAPDHs may be attractive targets for pathogen effectors . One example is the NleB effector , conserved in E . coli and Citrobacter rodentium , which O-GlcNAcylates GAPDH and disrupts GAPDH-mediated activation of transcription factors involved in regulation of innate immunity [15] . The role of metabolic checkpoints in cellular immune responses and cell death is beginning to be unraveled , revealing complex regulation by housekeeping enzymes and organelle function [16 , 17] . GAPDH is found in organisms from all kingdoms of life , with a high degree of sequence conservation . As a housekeeping protein GAPDH is known for its role in glycolysis , where it catalyzes the reversible conversion of glyceraldehyde 3-phosphate to 1 , 3-bisphosphoglycerate [18] . Animal cells contain only one isoform of GAPDH , and many moonlighting activities as well as changes in sub-cellular localization are influenced by redox dependent post-translational modifications of GAPDH on a number of highly conserved residues [19 , 20] . Whether GAPDH sequence conservation carries over to regulation of its diverse functions in plants has yet to be determined . As a result of gene duplication events and diversification , plants possess multiple GAPDH isoforms [21] . Arabidopsis contains four distinct isoforms comprised of seven phosphorylating and one non-phosphorylating GAPDH . These include: chloroplastic photosynthetic GAPDHs ( GAPA1 , GAPA2 , and GAPB ) , cytosolic glycolytic GAPDHs ( GAPC1 and GAPC2 ) , plastidic glycolytic GAPDHs ( GAPCp1 and GAPCp2 ) , and the NADP-dependent non-phosphorylating cytosolic GAPDH ( NP-GAPDH ) [18] . The substrate conversion by glycolytic GAPDHs catalyzes a concomitant reduction of NAD+ to NADH [22] . Arabidopsis GAPA1/2 and GAPB use NADPH to generate NADP+ , which buffers free radical formation from the electron chain transport by dissipating the proton gradient at the thylakoid membrane [23 , 24] . Therefore , by contributing to the maintenance of the NAD ( P ) + / NAD ( P ) H ratio of the cell , plant GAPDHs can influence both cellular redox as well as general metabolism . All phosphorylating GAPDHs share a similar structure including a highly reactive catalytic cysteine that can undergo multiple redox-induced post-translational modifications in response to ROS and reactive nitrogen species [18] . GAPC1's catalytic cysteine residue was determined to be S-nitrosylated in Arabidopsis during ETI in two independent large-scale proteomic studies [25 , 26] . Hydrogen peroxide also inhibits the traditional enzymatic activity of recombinant GAPC1 and GAPA1 proteins [27–29] . In Arabidopsis , treatment with hydrogen peroxide leads to increased binding of GAPC1 with Phospholipase Dδ resulting in enhanced enzyme activity of Phospholipase Dδ [30] . Overexpression of GAPA1 in yeast and Arabidopsis protoplasts inhibited ROS generation and programmed cell death induced by the apoptosis regulator BAX [31] . Treatment with cadmium or other chemicals inducing cytoplasmic oxidation leads to enhanced nuclear accumulation of Arabidopsis GAPC1 in root tip cells [32] . Thus , ROS or oxidative treatments can induce GAPDH post-translational modifications and are likely to facilitate new GAPDH protein associations , influence subcellular localization , and regulate activity in plants . In this manuscript , we focused on the role of individual GAPDH proteins in regulating plant innate immunity using the interaction between the bacterial pathogen Pseudomonas syringae pv . tomato ( Pst ) and its plant host , Arabidopsis thaliana [33] . All tested individual GAPDH KO lines exhibited enhanced disease resistance phenotypes to both virulent and avirulent Pst , limiting bacterial growth and accelerating the HR . Protoplasts made from KO lines displayed increased intracellular ROS . Experiments focused on GAPC1 , using a gapc1 KO complemented with GAPC1-GFP driven by its native promoter . In addition to the cytosol and occasionally the nucleus , GAPC1 associated with endomembrane compartments . Perception of bacterial flagellin lead to an increase in nuclear accumulation of GAPC1-GFP as well as an increase in size of GAPC1-GFP labeled vesicles . Collectively , these data highlight plant GAPDH's involvement in diverse processes and impact on the plant innate immune response .
To determine whether individual Arabidopsis GAPDH isoforms play a role during infection with Pst DC3000 , we screened T-DNA insertion lines for knockout ( KO ) lines in distinct isoforms . KO lines were obtained for the following GAPDH isoforms: gapa1 ( At3g26650 , SALK_138657 and SALK_145802 ) , gapc1 ( At3g04120 , SALK_010839 ) , gapc2 ( At1g13440 , SALK_016539 ) , gapCp1 ( At1g79530 , SAIL_390_G10 and SALK_052938 ) , and gapCp2 ( At1g16300 , SALK_137288 and SALK_008979 ) . The SALK T-DNA KO lines for gapa1 have not been previously published , and RT-PCR validation is provided in S1 Fig KO lines in the plastidic glycolytic GAPDHs , gapCp1and gapCp2 were previously published [34] , as were the cytosolic GAPDHs [22] . RT-PCR validation of gapCp1 and gapCp2 KOs is provided in S1 Fig Homozygous T-DNA KO lines for GAPA2 and GAPB were not identified and there were no available T-DNA insertions in exons . A screen of two separate T-DNA insertion lines ( SALK_023971 and SALK_067204 ) within the promoter of GAPA2 yielded homozygosity for the insertion without altering gene expression . The general morphology and plant size of individual KO lines during vegetative growth resembled Col-0 . After successfully identifying homozygous GAPDH KO lines , we subjected them to a variety of disease assays to determine their relative contribution during infection with Pseudomonas syringae pv . tomato ( Pst ) strain DC3000 . KO lines and the Col-0 control were dip inoculated with Pst DC3000 and bacterial titers were determined four days post-inoculation . All of the GAPDH KO lines exhibited enhanced disease resistance , with a 10 fold reduction in bacterial titers compared to the Col-0 control when inoculated with virulent bacteria ( Fig 1A and 1B ) . Lower bacterial titers correlated with a similar reduction in disease symptoms ( Fig 1C ) . Due to the high degree of sequence conservation between human GAPDH with Arabidopsis GAPC1 ( 68% amino acid similarity ) , we were particularly interested in the role of GAPC1 in the innate immune response . The gapc1 KO line was complemented with GAPC1-GFP under control of its endogenous promoter ( npro::GAPC1-GFP ) . Two independent , single insertion T3 homozygous lines were identified expressing GAPC1-GFP ( S2 Fig ) and bacterial growth was analyzed . Both npro::GAPC1-GFP lines 3–4 and 9–6 complemented the gapc1 KO and exhibited similar bacterial growth and disease symptoms as wild-type Col-0 ( Fig 1D and 1E ) . We did not observe any morphological defects in the npro::GAPC1-GFP lines ( Fig 1E ) . Localized programmed cell death is a hallmark of ETI and is termed the hypersensitive response ( HR ) . The HR can be visualized macroscopically when avirulent bacteria are syringe infiltrated into leaves at high concentrations ( 4×107 CFU mL-1 ) . Pst DC3000 expressing the AvrRpt2 effector , which is recognized by the Arabidopsis RPS2 immune receptor [35] , was used to investigate HR responses in individual GAPDH KO lines . The progression of cell death was quantified by measuring electrolyte leakage using a conductivity meter . All KO lines exhibited an accelerated HR and enhanced electrolyte leakage compared to the wild-type Col-0 control , indicating a more rapid cell death progression in the KO lines ( Fig 2A ) . Macroscopic HR was evaluated as well , and KO lines displayed more rapid tissue collapse starting at 10h post-infiltration while Col-0 collapsed at 12h post-infiltration ( Fig 2B ) . An enhanced disease resistance phenotype was also found after inoculation with avirulent Pst DC3000 expressing AvrRpt2 ( S3 Fig ) . Although all KO lines tested exhibit enhanced disease resistance to Pst DC3000 , the magnitude of responses varied between individual lines . The gapCps exhibited the highest resistance to virulent bacterial growth and displayed very few chlorotic symptoms , followed by gapc1 in overall symptom reduction and bacterial growth ( Fig 1A , 1B , and 1C ) . We used quantitative PCR to determine if the cause of enhanced disease resistance in the GAPDH KOs was due to transcriptional “priming” for a defense response . Pathogenesis-related 1 ( PR1 ) is a commonly used defense marker gene whose expression is induced in response to pathogen perception and salicylic acid [36] . In unchallenged GAPDH KO lines , basal PR1 expression was constitutively up-regulated compared to Col-0 ( Fig 1F ) . This indicates that GAPDH KO lines may be primed for pathogen defense responses in the absence of an elicitor , leading to accelerated defense responses upon pathogen inoculation . Taken together , these results indicate that multiple GAPDH isoforms act as negative regulators of plant immune responses . Plant GAPDH isoforms arose through multiple gene duplication events [21] . Phylogenetic analyses of the seven Arabidopsis GAPDH isoforms in addition to human and E . coli GAPDH reveals a high degree of sequence conservation ( Fig 3A ) [37] . Gene duplication can lead to diversification of biochemical functions and expression patterns . However , duplicated genes may also carry out similar or overlapping functions making genetic analyses challenging . Previously , it was reported that a KO in the non-phosphorylating GAPDH induced higher level expression of GAPC1 [38] . In order to investigate if single GAPDH KOs induce differential regulation of additional isoforms , we performed quantitative real-time PCR ( qPCR ) analyses to investigate basal expression of GAPDHs on four-week-old plants . Both GAPCp1 and GAPCp2 were expressed at a very low level and were excluded from the analyses based on their high Cq values ( Cq = 34 ) . qPCR analyses of the individual KO lines revealed complex transcriptional regulation of some GAPDH family members relative to wild-type Col-0 ( Fig 3B–3F ) . GAPA1 and GAPA2 were down-regulated in all the GAPDH KOs , while GAPB expression was unchanged in the majority of lines ( Fig 3B , 3C , and 3D ) . Both GAPC1 and GAPC2 were down-regulated in gapa1-2 ( Fig 3E and 3F ) . GAPC2 expression was up-regulated in the gapc1 line , presumably to help compensate for the loss of GAPC1; however , GAPC1 expression was not significantly different from Col-0 in the gapc2 line . Overall , GAPA1 , GAPA2 and GAPC1 had the most significant alterations in expression levels in the GAPDH KO lines . Thus , GAPDH family members appear to be under complex regulation , with epistatic interactions occurring between GAPA1 and the cytosolic isoforms . To assess Arabidopsis GAPDH enzymatic activity in individual KO lines , whole-leaf homogenates were used to analyze rates of glycolysis and the Calvin cycle . While cytosolic GAPC1 and GAPC2 have conserved sequence and glycolytic function with their animal and yeast counterparts , plants have evolved chloroplastic GAPDHs that function in the Calvin cycle . The basic biochemical reaction performed by GAPDH isoforms in glycolysis and the Calvin cycle is the same , with the direction of the reaction being reversed . The direction being assayed can be controlled for in vitro by utilizing a two-step enzymatic assay starting with reagents that preferentially drive substrate production in either direction . We used aldolase and fructose 1 , 6-bisphosphate or 3-phosphoglycerate ( with endogenous phosphoglycerate kinase ) to assess GAPDH enzymatic activity in the direction of either glycolysis ( Fig 3G ) or the Calvin cycle ( Fig 3H ) , respectively . Only gapa1-2 exhibited significantly impaired activity in both directions . This could be explained by the decreased transcript abundance of the cytosolic GAPDH isoforms ( GAPC1 and GAPC2 ) in addition to chloroplastic GAPA2 in gapa1-2 . Both gapc1 and gapc2 exhibited significantly reduced activity in the glycolytic direction . The gapCp lines were not altered in activity as compared to Col-0 . It is possible that GAPDH activity is reduced in plastids of gapCp KO lines , but this decrease is below the level of detection using a whole leaf assay . Chloroplasts play a role in the initiation and propagation of the HR , the generation of ROS involved in transcriptional reprogramming of defense-related genes , and limiting cell death [39 , 40] . Therefore , changes in plastid GAPDH activity may alter chloroplast contributions to immunity . GAPDH enzymatically catalyzes the only reductive step in glycolysis and the Calvin cycle , and has been linked to programmed cell death in animal systems [14 , 41] . Since changes in GAPDH activity have been linked to cell death phenotypes in other organisms , we examined changes in GAPDH enzymatic activity during innate immune responses . Plant immune responses were evaluated after activation of Arabidopsis FLAGELLIN SENSING2 ( FLS2 ) , a pattern-triggered immune receptor which detects a 22 amino acid epitope of bacterial flagellin termed flg22 [42] . Four-week-old Arabidopsis plants were infiltrated with either 5μM flg22 or 10mM MgCl2 . Glycolytic GAPDH activity was evaluated in samples harvested at 25min , 1h and 3h post-infiltration . Enzymatic activity significantly increased in flg22 infiltrated samples taken at 1h ( p < 0 . 05 ) and 3h ( p < 0 . 01 ) compared with MgCl2 infiltrated samples ( Fig 4A ) . To determine whether transcriptional regulation of GAPDHs occurs during PTI , we performed qPCR analyses using five of the seven phosphorylating GAPDH genes in the Arabidopsis Col-0 ecotype . Four-week-old Col-0 plants were infiltrated with either 5μM flg22 or water and leaf tissue was harvested 3h post infiltration . At 3h post infiltration GAPA1 , GAPA2 and GAPB transcripts were slightly down-regulated to less than half the control , while GAPC1 transcript levels increased by more than two-fold ( Fig 4C and 4D ) . These results demonstrate contrasting regulation of photosynthetic and glycolytic GAPDHs during PTI . GAPDH enzymatic activity increased in the glycolytic direction during PTI ( Fig 4A ) , consistent with an increase in transcription of GAPC1 . In order to evaluate alterations in glycolytic GAPDH enzymatic activity during ETI responses , four-week-old Col-0 plants were infiltrated with 10mM MgCl2 or a bacterial suspension of Pst DC3000 carrying empty vector or AvrRpt2 . Tissue was harvested at the first signs of the HR when vein silvering was initially visible ( ~8h post-infiltration ) . GAPDH activity was significantly increased in leaves infiltrated with Pst DC3000 empty vector compared to MgCl2 , as well as in leaves undergoing ETI responses ( Fig 4B ) . We were unable to detect a gross change in total GAPDH protein levels during bacterial infection or flg22 elicited immune responses using anti-GAPDH western blotting ( S4 Fig ) . However , the sensitivity of western blotting is antibody dependent [43] . Therefore , our antibody may not be sensitive enough to detect minor changes in protein abundance . All GAPDH KO lines exhibited enhanced disease resistance to virulent and avirulent Pst DC3000 . One potent set of anti-microbial molecules produced by plant cells during the innate immune response are reactive oxygen species ( ROS ) . It is well documented that the role of extracellular ROS production mediated by the NADPH oxidase respiratory burst oxidase-D ( RBOHD ) is critical to mounting an effective defense response to bacterial pathogens [44] . A luminol-based extracellular ROS assay using flg22 as an elicitor was not able to cause a significant alteration in extracellular ROS production for gapc1 and gapc2 mutant lines compared to Col-0 . Interestingly , when all ROS data was analyzed together , gapa1-2 had a significantly reduced burst compared to Col-0 ( S5 Fig ) . GAPA1 is localized to the chloroplasts , a site of significant intracellular ROS production [40] . It is possible that loss of GAPA1 alters redox homeostasis , dampening the ROS burst produced by the NADPH oxidase RBOHD . GAPDHs can directly impact cellular redox potential through their involvement in the reducing step of either glycolysis or the Calvin cycle [18 , 24] . Therefore , the basal intracellular ROS levels of GAPDH KO lines were analyzed . Protoplasts were isolated from four-week-old Col-0 , gapa1-2 , gapc1 , gapc2 , gapCp1-2 and gapCp2-2 plants and incubated under bright light for 1h since chloroplastic isoforms are light activated enzymes [21 , 23] . Following incubation in the light , the intracellular ROS probe H2DCFDA was added and protoplasts were kept in the dark for 15 min prior to imaging ( Fig 5A ) . The extent of H2DCFDA fluorescence was quantified from the pixel intensity for each genotype ( Fig 5B , 5C , and 5D ) . Although all GAPDH KO lines exhibited significantly enhanced basal intracellular ROS ( p<0 . 01 ) , the magnitude of enhanced ROS varied between lines ( Fig 5A–5D ) . The accelerated cell death observed across GAPDH KO lines during the HR may be explained by increased intracellular ROS production in response to bright light stimulation , as HR development depends on light and plants are placed under a light bank after inoculation [45] . Previous reports indicated that recombinant GAPA1 , GAPC1 and GAPC2 are sensitive to hydrogen peroxide treatment , supporting a hypothesis for GAPDHs as cellular redox sensors [27–29] . In order to investigate if all phosphorylating GAPDH proteins are sensitive to hydrogen peroxide , recombinant proteins were purified from E . coli and their enzymatic activity assessed before and after incubation with hydrogen peroxide ( S5B Fig ) . As previously shown , GAPC1 and GAPC2 activity was decreased after incubation with hydrogen peroxide ( S5B Fig , [28 , 29] ) . Furthermore , GAPCp1 and GAPCp2 activity was also inhibited upon treatment with hydrogen peroxide ( S5B Fig ) . At lower concentrations , ROS have been described as acting as inter- and intracellular signaling molecules which may condition cells for accelerated responses to stimuli [46] . If GAPDHs are acting as cellular redox buffers , loss of one of these isoforms may allow for greater ROS accumulation . We chose to investigate GAPC1 localization in detail due to its highly conserved amino acid sequence similarity to GAPDHs in other organisms ( Fig 3A ) . In addition to cytosolic and nuclear localizations , animal systems have linked GAPDH to endosomal movement and membrane fusion [47–49] . Signaling platforms at the plasma membrane and endomembrane are proving to be crucial in defense signaling of Arabidopsis as well as animal systems [50] . Arabidopsis GAPC1 has been reported to be primarily cytosolic , with some nuclear re-localization events in cells stressed by cadmium [32] , but no endomembrane localization has been described . Our results indicating a change in glycolytic activity led us to hypothesize that GAPC1 undergoes dynamic partitioning during the immune response potentially mediated by subcellular re-localization . We investigated GAPC1 localization by confocal microscopy using the npro::GAPC1-GFP line 3–4 . Plasmolysis using 1M NaCl revealed GAPC1-GFP localized to Hechtian strands , indicating partial plasma membrane localization ( Fig 6A , 6B , and 6C ) . Western blotting after membrane fractionation in wild-type Col-0 using α-GAPDH shows endogenous GAPDH is present in nuclear , cytoplasmic and membrane fractions ( S6 Fig ) . Thus , GAPC1 exhibits diverse subcellular localizations in the absence of stress conditions . In order to further probe the relationship between GAPC1 and cellular membranes , we treated the first true leaves of three-week-old plants grown in soil with either 30μM Brefeldin A ( BFA ) or 33μM Wortmannin and examined them by confocal microscopy . BFA is known to inhibit ARF-GEFs and block the Golgi dependent secretion pathway resulting in the characteristic formation of “BFA bodies” , while Wortmannin is an inhibitor of phosphatidyl-inositol 3-kinase , and interferes with endocytosis and vacuolar sorting [50–52] . In the presence of BFA , characteristic BFA bodies stained with FM4-64 co-localized with GAPC1-GFP , indicating that GAPC1-GFP localization is BFA-sensitive ( Fig 6D , 6E , and 6F ) . FM4-64 is an amphiphilic styryl dye that fluoresces in hydrophobic environments such as lipid membranes and is commonly used as an endocytic marker [53] . In animal systems BFA induces the ADP-ribosylation of two proteins: GAPDH and CtBP3/BARS [54 , 55] . However , subcellular localization of GAPDH in response to BFA treatment has not been previously visualized in either plants or animals . In the Wortmannin treated seedlings , an increase in the size of endosomes occurred ( Fig 6G and 6H ) . These data indicate that GAPC1-GFP localization is sensitive to the inhibition of Golgi-mediated and late endocytic trafficking pathways . Furthermore , these results highlight the diverse sub-cellular localization of GAPC1 . During the plant innate immune response , several proteins dynamically re-localize to different sub-cellular compartments [3] . FLS2 , the well characterized flagellin receptor , is an example of a protein that is dynamically re-localized after immune activation . FLS2 is localized to the plasma membrane and is intimately connected with the endomembrane system . In the absence of flagellin perception , resting state FLS2 is recycled through the trans-Golgi network and early endosomal pathway [50] . When activated , FLS2 is endocytosed , traffics through the endocytic pathway to late endosomes and reaches the multi-vesicular body , presumably for sorting and degradation [50 , 56] . Thus , flg22 is an excellent probe for cellular re-localization responses during PTI . We detected a change in total GAPDH activity during innate immune responses ( Fig 4B and 4C ) and an association of GAPC1 with diverse compartments in Arabidopsis ( Fig 6 , [57] ) . Therefore , GAPC1-GFP localization was examined after elicitation with flg22 . Leaves of four-week-old plants were infiltrated with 10mM MgCl2 or 5μM flg22 diluted in 10mM MgCl2 and imaged 30 min post-infiltration by confocal microscopy . Leaves infiltrated with MgCl2 alone exhibited GAPC1-GFP labeled fluorescent puncta that were on average half the size of those in leaves treated with flg22 ( Fig 7A , 7B , and 7C ) . In order to statistically quantify the size change of GAPC1-GFP puncta after flg22 treatment , images from both treatments were pooled and blindly processed for average size . Flg22 treatment was found to induce a significant increase in puncta area ( p< 0 . 01 ) . Arabidopsis GAPC1 and animal GAPDH have also been described as dynamically re-localizing to the nucleus in response to cellular stress [32 , 58] . Quantification of fluorescently-labeled nuclei from confocal z-stack slices revealed an increase in nuclear-localized GAPC1-GFP after flg22 treatment ( Fig 7D , 7E , and 7F ) . Isolation of nuclei from seedlings treated with water or 5μM flg22 supports enhanced accumulation of GAPC1-GFP in the nucleus after flg22 treatment ( Fig 7G ) . Together , these data indicate a dynamic re-distribution of GAPC1-GFP to the endomembrane system and nucleus during innate immune signaling . Autophagy is a highly conserved cellular recycling mechanism , involved in degrading unnecessary or damaged materials and organelles during normal growth and development [59] . Although autophagy is an active process in growth and development , few autophagy bodies are present in wild-type plants under normal basal growth conditions [60] . During specific cellular-stresses such as exposure to ROS , endoplasmic reticulum stress or nutrient starvation , autophagy is induced and can lead to programmed cell death [61] . Given that GAPDHs are involved in glucose metabolism and the individual KO lines exhibit enhanced disease resistance , accelerated HR , and enhanced intracellular ROS accumulation , we sought to examine alterations in autophagy responses . In Arabidopsis , autophagy can be induced by nitrogen starvation elicited by growing seedlings on nitrogen-limiting media [60] . For our experiments , two-week-old seedlings were grown first on full strength MS agarose media then transferred to liquid MS or liquid MS lacking nitrogen to induce autophagy for a period of 4–5 days . Monodansylcadaverine ( MDC ) , a fluorescent dye that specifically binds autophagosomes [60 , 62] , was used to visualize autophagy induction by confocal microscopy . Concanamycin A , an inhibitor of vacuolar H+-ATPases , was used to de-acidify the vacuole and allow for visualization of autophagosome accumulation in the vacuole . When grown on full MS media , Col-0 exhibits very few to no autophagy bodies ( Fig 8A ) . Interestingly , gapa1-2 and gapc1 seedlings grown on full nutrient media exhibited an enhanced accumulation of autophagosomes in the vacuole as compared to Col-0 ( Fig 8B and 8C ) . Quantification of MDC-labeled puncta within 30 μm2 sections revealed a significantly higher number of MDC-labeled autophagosomes in gapa1-2 and gapc1 seedlings than Col-0 ( Fig 8G ) . However , there was no gross difference observed between Col-0 and the gapdh KO lines in the number of autophagy bodies present under nitrogen starvation ( S7 Fig ) . These data suggest a role for GAPA1 and GAPC1 in the negative regulation of basal autophagy , as the induced autophagy response is phenotypically normal . To confirm the autophagy phenotype observed with MDC , seedlings were transiently transfected with tRFP-ATG8a and autophagosomes visualized by microscopy . Autophagy is regulated by a set of autophagy-related genes ( Atgs ) that are highly conserved across eukaryotes [63] . When autophagy is initiated , the ubiquitin-like Atg8 protein can be used as a marker to label cytosolic autophagosomes [60 , 63] . Autophagosomes labeled with tRFP-Atg8a were present in the cytoplasm of Col-0 , gapa1-2 , and gapc1 seedlings ( Fig 8D , 8E , and 8F ) . Similar to the MDC-labeling , quantification of the number of fluorescently-labeled puncta in 30 μm2 image sections revealed a significantly higher number of autophagosomes present in gapa1-2 and gapc1 seedlings compared to Col-0 ( Fig 8H ) . Autophagy is a diversely regulated process and is intricately connected to cellular glucose metabolism [61] . Not only does glucose availability directly impact glycolysis , but it also impacts glycosylation modifications in the endoplasmic reticulum ( ER ) [61] . Under nutrient stress a disruption of protein glycosylation in the ER can lead to the unfolded protein response ( UPR ) and trigger autophagy [61] . To investigate UPR-triggered autophagy , we examined the UPR marker bZIP60 [64] . During the UPR in plants , IRE1A and IRE1B are activated and cause the cleavage of the mRNA bZIP60 , which can be visualized by the presence of a doublet after RT-PCR using primers spanning the cleavage site [64 , 65] . Col-0 treated with 2mM DTT was used as a positive control for induction of the UPR and confirmed the generation of a doublet PCR product ( Fig 8I ) using previously published primers that span the alternate splicing site [64] . No cleavage of bZIP60 mRNA was observed in the gapa1 or gapc1 KO lines with or without elicitation by flg22 ( Fig 8I ) . Without cleavage of bZIP60 mRNA , canonical UPR activation should not be responsible for the induction of autophagy .
In this manuscript , we genetically investigated the importance of five of the seven phosphorylating GAPDHs , revealing enhanced defense responses in individual KO lines . GAPDHs are differentially regulated by a variety of post-translational modifications , some of which have been linked to transcriptional reprogramming and endosomal trafficking in animals [12 , 18] . Our data provide evidence that plant GAPDHs serve roles outside of glycolysis and the Calvin cycle . The sub-cellular localization of GAPC1-GFP fluorescent puncta and their subsequent change in size after flg22 treatment indicates a response consistent with either ROS-induced protein aggregation or fusion of GAPC1-GFP associated endosomal compartments [66 , 67] . Additionally , we see a change in GAPDH glycolytic activity during immune signaling . Impacts on plant immunity imparted by individual isoforms are likely influenced by complex genetic regulation . Our analyses of GAPDH KO lines revealed that individual KOs affected immune responses . Individual KO lines exhibited enhanced disease resistance to virulent and avirulent Pst DC3000 , accelerated cell death in response to avirulent Pst DC3000 , enhanced basal expression of the defense marker gene PR1 , and enhanced intracellular ROS accumulation . Furthermore , the gapc1 and gapa1 possessed an increased basal autophagy phenotype . These effects may be linked as downstream consequences of the heightened basal ROS detected in each KO . Exogenous ROS application has been shown to enhance PR1 gene expression , autophagy flux , and protein aggregation [66–70] . Although individual GAPDH KO lines exhibited similar phenotypic effects , their magnitude varied . qRT-PCR analyses revealed expression of individual GAPDH isoforms were regulated in a complex manner across single KO lines . In most instances , there was a compounding effect where mutation of a single GAPDH resulted in the down-regulation of multiple GAPDH isoforms . For example , GAPA1 and GAPA2 were significantly down-regulated across all single KO lines , mimicking transcriptional responses observed during PTI ( Figs 3B , 3C , and 4C ) . During PTI in wild-type plants , GAPC1 mRNA was significantly up-regulated four-fold compared to controls 3h post-flg22 treatment , while transcription of photosynthetic GAPDHs was down-regulated at this time point . GAPDH is frequently used as a control to normalize gene expression during qPCR . Our data highlight that GAPDH expression dynamically changes upon flg22 perception . Therefore , GAPDH expression should be interrogated before use or alternative marker genes should be used to normalize gene expression [71] . Total glycolytic GAPDH enzymatic activity increased during infection with virulent or avirulent Pst DC3000 as well as after perception of flg22 . Enhanced glycolytic activity has been linked to promotion of cell survival [14 , 72] . Additionally , a primary output of glycolysis is pyruvate , a direct scavenger of cellular ROS [73] . Thus , in wild-type plants undergoing immune responses , enhancing glycolysis may be important for providing elevated levels of the ROS scavenger pyruvate . Furthermore , plant defense signaling is an energetic process , highlighted by the well-known tradeoff between growth and defense [74] . Glycolysis generates ATP . Thus , an increase in glycolytic GAPDH activity during pathogen perception could provide additional energy required for global cellular reprogramming towards defense . In mammals , GAPDH is required for glycolytic ATP-driven rapid vesicular transport [75] . We also observed GAPC1-GFP associating with vesicles ( Figs 6 and 7 ) , which could provide energy enabling vesicular movement . Using the ROS sensitive probe H2DCFDA , we found all tested GAPDH KO lines exhibited enhanced intracellular ROS accumulation . GAPA1 , GAPA2 , and GAPB catalyze the reductive step in the Calvin cycle with concomitant oxidation of NADPH to NADP+ [76] . Interestingly , GAPA1 and GAPA2 mRNA expression levels were significantly lower in all KO lines . NADP+ is important as an electron acceptor for protons accumulating at the thylakoid membrane generated during photosynthesis . A reduction of NADP+ can lead to an increase in ROS production at the thylakoid membrane due to excess proton accumulation [24] . In addition to Calvin-cycle mediated regulation of intracellular ROS production , GAPDH proteins are also sensitive to regulation by ROS themselves . Our results in combination with previous experiments demonstrated that hydrogen peroxide treatment inactivated GAPA1 , GAPC1 , GAPC2 , and GAPCp1/2 enzymatic activity in vitro [27–29] . Large scale proteomic studies have identified S-Nitrosylation of Arabidopsis GAPDHs during infection with avirulent Pst DC3000 and in response to treatment with nitric oxide [25 , 26 , 77] . It will be important to determine if the oxidative state of GAPDH is monitored and if GAPDHs directly contribute to ROS quenching in plants . Depending on the pathogen and recognized effector , autophagy can promote cell death or survival [16] . Autophagy is required to limit the spread of ETI induced cell death after infection of Nicotiana benthamiana with Tobacco Mosaic Virus [78] . A pro-death role for autophagy has also been described in the case of ETI triggered by Pst DC3000 AvrRps4 in Arabidopsis Ws-0 [79] . Although autophagy was required for wild-type HR triggered by AvrRps4 , it was not required for normal HR responses to Pst DC3000 effectors AvrRpt2 or AvrRpm1 [79] . Therefore , the accelerated HR we observed in response to Pst DC3000 AvrRpt2 infiltration is likely due to enhanced defense priming in the GAPDH KO lines . ROS have also been shown to be essential for the formation of autophagosomes in mammalian cells and Arabidopsis [69 , 70] . We see enhanced ROS and PR1 expression in the GAPDH KOs , indicating autophagy may be induced as a pro-survival mechanism against accumulating ROS . Previous studies have demonstrated primarily cytoplasmic localization for GAPC1 , with occasional nuclear accumulation [32 , 73 , 80] . Our npro::GAPC1-GFP complemented lines also exhibited a similar localization pattern . Overexpression of GAPC1 in protoplasts enables enhanced nuclear accumulation as well as association with mitochondria and the actin cytoskeleton [32 , 81] . However , these subcellular localizations were not detected in stable native promoter GAPC1-YFP lines [32] . In animal cells as well as plant roots , GAPDH can dynamically re-localize to the nucleus upon oxidative or cold stress [20 , 32 , 80] . We also detected enhanced nuclear localization and a significant alteration in the size of GAPC1-GFP fluorescent puncta during PTI . In its monomeric form , human nuclear GAPDH is active as a uracil-DNA-glycosylase [82] . Plant chloroplast isoform GAPB was demonstrated to have nuclear uracil-DNA-glycosylase activity [57 , 83] . This moonlighting GAPDH activity may be an important component of monitoring DNA damage . We also detected GAPC1-GFP as plasma membrane associated and in small mobile puncta . We demonstrate that GAPC1-GFP is sensitive to the PI3K inhibitor Wortmannin which is a chemical inhibitor of autophagy . Recently , GAPC1 and GAPC2 were reported to bind membrane-localized Phospholipase D ( PLD ) and its downstream product Phosphatidic Acid [30 , 84] . Furthermore , the oxidized form of GAPCs significantly enhanced PLD enzymatic activity [30] . The association of GAPC1 with PLD under oxidizing conditions could account for an increase in the size of vesicles associated with GAPC1-GFP after perception of flg22 ( Fig 7B ) . Here , we provide evidence that GAPDHs can influence plant immune responses and GAPC1 exhibits diverse and dynamic cellular localization upon flagellin perception . Phenotypes observed in the KOs such as the accumulation of reactive oxygen species and induction of basal autophagy support GAPDH mediated regulation of metabolic checkpoints . Future research investigating the role of nuclear GAPC1 will determine if plant GAPDHs , like their animal counterparts , are involved in transcriptional reprogramming during times of cellular stress . We have provided evidence supporting GAPDHs as pro-survival molecules in plants , negatively regulating cell death in response to pathogen challenge . Due to a lack of gross morphological phenotypes in single gapdh KOs , individual members may be promising targets for genome editing to enhance crop disease resistance .
T-DNA insertion lines for GAPA1 ( SALK_138567 and SALK_145802; gapa1-1 and gapa1-2 respectively ) , GAPC1 ( SALK_010839 ) , and GAPC2 ( SALK_016935 ) were obtained from the SALK institute , genotyped , and homozygous KO lines were verified by RT-PCR . Homozygous seed for GAPCp1 ( SAIL_390_G10 and SALK_052938; gapCp1-1 and gapCp1-2 respectively ) and GAPCp2 ( SALK_137288 , SALK_008979; gapCp2-1 and gapCp2-2 respectively ) were previously described [34] . Plants were grown in a controlled environmental chamber at 23°C with a 10-h light/14-h dark photoperiod under a light intensity of 85 μE/m2/s . For all the experiments , 4–5 week old plants were used . Transgenic npro::GAPC1-GFP lines were generated using the floral dip method [85] , in order to complement the gapc1 KO . The length of native promoter we used was 811bp , and it was PCR amplified and cloned as an in-frame fusion to genomic GAPC1 in pENTR ( Invitrogen ) . Next , the GAPC1 construct was transferred into the binary vector pGWB4 using gateway technology to generate a C-terminal GFP tag [86] . Transgenic plants were selected on 50μg/mL hygromycin . T3 homozygous lines were used for all experiments . All PCR primers used for genotyping and cloning are listed in S1 Table . Pst DC3000 and Pst DC3000 ( AvrRpt2 ) , were grown on nutrient yeast-glycerol ( NYG ) plates for 30 h , then cultured at 28°C in NYG media for 48 h . Pst DC3000 ( AvrRpt2 ) expressed AvrRpt2 from the broad-host range vector pDSK519 [87] . Antibiotics were used for plate selection at the following concentrations: 25 μg/ml kanamycin , 100 μg/ml rifampicin , and 35 μg/ml chloramphenicol . For dip inoculation , Arabidopsis plants were grown in a mesh covered pot to facilitate submergence for 30 sec of the aerial portion into bacterial suspension containing 1×109 CFU/ml bacteria in 10 mM MgCl2with 0 . 02% silwet L-77 . Inoculated plants were left covered with a plastic dome for 3h . At 4 days post inoculation , leaves were surface sterilized for 30 sec in 70% ethanol and bacterial populations were determined as described by Kim and colleagues [88] . All experiments were repeated at least three times , with a minimum of six biological replicates per time point . For both HR and electrolyte leakage , Arabidopsis Col-0 and GAPDH KO leaves were infiltrated using a needleless syringe with 4×107 CFU/ml of Pst DC3000 and Pst DC3000 ( AvrRpt2 ) . After infiltration , plants were placed under a light bank ( 100 μE/m2/s ) and HR was scored at 10 h post inoculation . For electrolyte leakage , two leaves per plant were infiltrated across four biological replicates per genotype . Total tissue was harvested using a cork borer to generate 1 . 5 cm2 of leaf discs ( six total leaf discs ) . Leaf discs were placed in distilled water ( 20mL in a 50mL conical tube ) for 1h and individual biological replicates kept separate . Leaf discs were transferred to a 12-well tissue culture plate ( Corning ) containing 4mL of distilled water per well and placed under the light bank . Conductivity was measured using the Orion 3 Star conductivity meter ( Thermo Scientific ) . All experiments were repeated at least three times . MEGA6 was used to perform phylogenetic analysis on GAPDH amino acid sequences and draw the un-rooted tree [37] . A maximum-likelihood tree construction was used based on the JTT matrix-based model with bootstraps . Total RNA was extracted using the TRI zol Reagent ( Invitrogen ) according to manufacturer’s instructions , and subsequently incubated with RNase-free DNase I ( Invitrogen ) to remove genomic DNA contamination . RNA was extracted from three biological replicates per treatment . Each biological sample comprised two leaves from a single plant , and the pooled 2μg of RNA was used as a template for reverse transcription with Promega M-MLV reverse transcriptase in the presence of 0 . 5μg/μl oligo ( dT ) primers . Equal amounts of first-strand cDNAs were used as templates for RT-PCR amplification using the primers listed in supplemental S1 Table . Semi-quantitative RT-PCR was run for 30 cycles for gapa1-2 lines and 35 cycles for gapCp lines . Quantitative real-time PCR reactions used Bio-Rad SsoFast EvaGreen Supermix according to manufacturer’s directions using a CFX96 Touch ( Bio-Rad ) . Thermocyling parameters began with a first step at 95°C for 30 sec and 39 cycles afterwards alternating between 5 sec at 95°C and 15 sec at 60°C . A melting curve followed the final cycle and ran 5s at 65°C and 5 s at 95°C . Gene expression was normalized against the Arabidopsis ELONGATION FACTOR 1-ALPHA ( At5g60390 ) . Protoplasts were prepared enzymatically according to previously described methods [86] . After isolation , protoplasts were re-suspended in W1 solution ( 0 . 5 M mannitol , 4 mM MES , pH 5 . 7 , 20 mM KCl ) after the rinse steps with W5 ( 154 mM NaCl , 125 mM CaCl2 , 5 mM KCl , 2 mM MES , pH 5 . 7 ) and allowed to sit and recover for 5h before treatment . After resting , protoplasts were quantified with a hemacytometer and aliquoted into a 24 well Corning Costar cell culture plate where they were diluted with W1 to 1 x 105 cells/ 200μL . The cell culture plate was moved to a light bank where the protoplasts were left under bright light for 1h . Prior to imaging , 750nM 2' , 7'-dichlorodihydrofluorescein diacetate ( H2DCFDA , CalBioChem ) was added and cells incubated in the dark for 12–15 min . Images used for quantification of gapa1 and Col-0 ( Fig 5 ) were obtained using a Leica DM 5000B epifluorescent microscope with a GFP cube ( excitation 470/40 , emission 525/50 ) . All other genotypes were imaged using the Axio Imager M2 microscope ( Zeiss , Germany ) using a 40X objective ( EC Plan-NEOFLUAR 40X/ 0 . 75 , Zeiss ) . Fluorescence was quantified using ImageJ from a minimum of 25 protoplasts across 10 or more images per genotype . SDS-PAGE and subsequent immunoblotting were performed according to standard procedures [89] . GAPC1-GFP immunoblots were performed with Anti-GFP ( ab290 , Abcam ) rabbit polyclonal antibody at a dilution of 1:8 , 000 . Anti-cF6BP immunoblots were performed using rabbit polyclonal antibody at a dilution of 1: 5 , 000 ( Agrisera ) . Anti-RIN4 immunoblotting used affinity purified antisera from rabbit at 1:3 , 000 . Rabbit polyclonal antibodies anti-Histone 3 ( ab1791 , Abcam ) and anti-psbO ( ab65563 , Abcam ) were used at 1:1 , 000 and 1:3 , 000 , respectively . Secondary goat anti-rabbit IgG-HRP conjugate ( Biorad ) was used at a dilution of 1:3 , 000 for detection via enhanced chemiluminescence ( Pierce ) . GAPDH immunoblots were performed using anti-GAPDH ( GenScript ) goat polyclonal antibody at a dilution of 1:500 . Secondary bovine anti-goat IgG-HRP ( Santa Cruz Biotechnology ) was used at a dilution of 1:3 , 000 for detection via enhanced chemiluminescence ( Pierce ) . Plasmids containing the seven phosphorylating GAPDH cDNAs in a pET28a backbone were transfected into E . coli . Recombinant protein was purified on Ni-NTA Agarose beads ( Qiagen ) and used for Western blotting . Leaves from 4–5 week old rosette leaves were ground in liquid nitrogen by mortar and pestle . Each sample contained pooled leaves from 3–4 plants . Homogenates were otherwise prepared as described [22] . To the frozen , ground tissue , 600 μl of buffer containing 50mM Tris-HCl , pH 8 . 0 , 5mM EDTA , 1mM phenylmethylsulfonyl fluoride , and 2mM 2-mercaptoethanol was added . The homogenate was transferred to an eppendorf tube and centrifuged at 12 , 000 g for 20 min at 4°C . The supernatant was collected and protein content quantified by Pierce 660 protein assay ( Thermo Scientific ) and normalized across all samples and 30μg of total leaf protein was used for all activity assays . Cytosolic GAPDH activity was assayed spectrophotometrically using a Spectramax Plus384 spectrophotometer ( Molecular Devices ) at 340nm by the reduction of NAD+ , as described [22] . Photosynthetic GAPDH activity was also assayed as described previously with minor modifications [76] . 3-phosphoglycerate kinase was omitted in the photosynthetic GAPDH activity assay since it is present and abundant in the leaf extract [90] . Experiments were repeated a minimum of three times , and data was normalized to the control and all runs combined for statistical analysis . In the recombinant GAPDH activity assays , 1 . 5 μg of total protein was used . Hydrogen peroxide at specified concentrations was added just prior to the initiation of the assay . All confocal microscopy was performed using a Zeiss LSM710 confocal microscope equipped with a LDC-apochromat 40×/1 . 1W Korr M27 water-immersion objective ( NA 1 . 1 ) . GFP was excited at 488nm , emission collected at 500–550nm for all experiments except MDC treatments . After treatment with 50 μM MDC , GFP emission was collected at 510–560nm . Leaves incubated with 1 μM FM464 ( Invitrogen ) were excited at 488nm and emission collected at 620–660nm . MDC was visualized using UV laser and emission of 467–510nm . For flg22 treatment , leaves of four-week-old plants were infiltrated using a needleless syringe with 5μM flg22 ( GenScript , 80 . 1% purity ) or water and imaged after 30 min . Images were randomized and aggregate size was blindly quantified using ImageJ . Brefeldin A ( BFA , Sigma ) bodies and endosomal networks were imaged using three-week-old seedlings submerged in 1μM FM4-64 for 3h with or without addition of 30μM BFA 1 . 5h prior to imaging . Autophagy was examined according to [60] , with slight modifications . Seeds were sown on full MS agarose plates and grown for 10 days in 16h light/ 8h dark at 23°C . Seedlings were then transferred to liquid media containing MS or nitrogen-free MS ( PhytoTechnology Laboratories ) for 4–5 more days under the same growth conditions . The night before imaging , 1μM Concanamycin A ( Sigma ) or equivalent volume of DMSO was added to each well . Three hours before imaging , 50μM MDC was added and plates were wrapped in foil and kept in the dark . Transient expression of 2x35S::tRFP-Atg8a was as previously described [91] , with some modifications . After a four day co-cultivation period with Agrobacterium GV3101 the co-cultivation media was removed and seedlings were washed three times with distilled water . Seedlings were then re-suspended in full MS media and imaged by confocal microscopy . All image analysis was performed using a combination of software tools , Zen 2012 software ( Carl Zeiss ) , ImageJ ( http://rsbweb . nih . gov/ij/ ) and Image Pro Plus ( Media Cybernetics , Rockville , MD ) . Isolation of Arabidopsis nuclei was carried out as previously described with some modifications [92] . Two week old seedlings were transferred to a six-well culture plate and treated ± 5 μM flg22 for 30 min . One gram of seedlings from each treatment was frozen in liquid nitrogen for nuclear isolation . Seedlings were ground in liquid nitrogen and re-suspended in 5mL Extraction Buffer ( 2 M hexylene glycol , 20 mM PIPES-KOH ( pH 7 . 0 ) , 10 mM MgCl2 , 1 mM Spermidine , 1 mM Spermine , 1 mM 2-Mercaptoethanol , 1% Triton X-100 ) . The suspension was stirred at 4°C for 10 minutes and then filtered through two layers of cheesecloth stacked with two layers of Miracloth ( EMD Millipore ) . Percoll suspensions of 30% and 80% Percoll were prepared in Gradient Buffer ( 0 . 5M hexylene glycol , 5 mM PIPES-KOH ( pH 7 . 0 ) , 10mM MgCl2 , 1 mM 2-Mercaptoethanol , 1% Triton X-100 ) . Three mL of 30% Percoll were added to a 15 mL conical tube and under-laid with 3 mL of 80% Percoll . The plant extract was pipetted on top and the sample was centrifuged at 1000g for 30 minutes at 4°C . Nuclei were extracted from the interface between the 30% and 80% Percoll layers into a 2 mL tube . The nuclear fraction was brought to 0 . 5 mL volume with Gradient buffer and under-laid with 30% Percoll and centrifuged at 2000g for 10 minutes at 4°C . After the supernatent was completely removed and the pellet was re-suspended in 0 . 5 mL gradient buffer , 0 . 5 mL of 30% Percoll was again under-laid and the 2000g centrifugation repeated . The pellet was then re-suspended in Laemmli buffer , quantified for equal loading using Pierce 660 protein assay ( Thermo Scientific ) , and diluted to 1 μg/ 10 μl for SDS-PAGE gel analysis .
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Plants can be infected by all pathogen classes , significantly impacting crop production and food security . Innate immune responses are critical to plant survival but must be tightly regulated in order to avoid negative impacts on growth and development . Here , we investigated the role of glyceraldehyde 3-phosphate dehydrogenase ( GAPDH ) proteins in the model plant Arabidopsis thaliana , a mustard relative . Animals have one GAPDH isoform , which has been intensely investigated and shown to exhibit diverse moonlighting , or non-traditional , activities . Plants possess multiple GAPDH isoforms that reside in distinct sub-cellular compartments . Using a combination of genetic investigation of specific GAPDH knockouts coupled with microscopy , we found that GAPDHs regulate accumulation of reactive oxygen species and cell death in response to inoculation with the bacterial pathogen Pseudomonas syringae . The GAPC1 isoform exhibits diverse sub-cellular localizations and dynamically responds to perception of bacterial flagellin . The GAPC1 and GAPA1 isoforms also negatively regulate autophagy , which is an important component of plant immune responses . Taken together , our results demonstrate that multiple GAPDH isoforms act to negatively regulate plant defense responses . Negative regulators are important for precisely regulating the duration and amplitude of immune responses .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[] |
2015
|
Beyond Glycolysis: GAPDHs Are Multi-functional Enzymes Involved in Regulation of ROS, Autophagy, and Plant Immune Responses
|
Using a model for the dynamics of the full somatic nervous system of the nematode C . elegans , we address how biological network architectures and their functionality are degraded in the presence of focal axonal swellings ( FAS ) arising from neurodegenerative disease and/or traumatic brain injury . Using biophysically measured FAS distributions and swelling sizes , we are able to simulate the effects of injuries on the neural dynamics of C . elegans , showing how damaging the network degrades its low-dimensional dynamical responses . We visualize these injured neural dynamics by mapping them onto the worm’s low-dimensional postures , i . e . eigenworm modes . We show that a diversity of functional deficits arise from the same level of injury on a connectomic network . Functional deficits are quantified using a statistical shape analysis , a procrustes analysis , for deformations of the limit cycles that characterize key behaviors such as forward crawling . This procrustes metric carries information on the functional outcome of injuries in the model . Furthermore , we apply classification trees to relate injury structure to the behavioral outcome . This makes testable predictions for the structure of an injury given a defined functional deficit . More critically , this study demonstrates the potential role of computational simulation studies in understanding how neuronal networks process biological signals , and how this processing is impacted by network injury .
Understanding networked and dynamic systems is of growing importance across the engineering , physical and biological sciences . Such systems are often composed of a diverse set of dynamic elements whose connectivity are prescribed by sparse and/or dense connections that are local and/or long-range in nature . Indeed , for many systems of interest , the diversity in connectivity and dynamics make it extremely challenging to characterize dynamics on a macroscopic network level . Of great interest in biological settings is the fact that such complex networks often produce robust and low-dimensional functional responses to dynamic inputs . Indeed , the structure of their large connectivity graph can determine how the system operates as a whole [1 , 2] . Neuronal networks , in particular , may encode key behavioral responses with low-dimensional patterns of activity , or population codes , as they generate functionality [3–8] . Unfortunately , all biological networks are susceptible to pathological and/or traumatic events that might compromise their performance . In neuronal settings , this may be induced by neurodegenerative diseases [9–11] , concussions , traumatic brain injuries ( TBI ) [12–14] or aging . In this work , we extend a computational model to investigate behavioral impairments in the nematode C . elegans when the underlying neuronal network is damaged . Specifically , we consider how the low-dimensional population codes are compromised under the impact of an injury . Characterizing the resulting cognitive and behavioral deficits is a critical step in understanding the role of network architecture in producing robust functionality . A hallmark feature of damaged neuronal networks is the extensive presence of Focal Axonal Swellings ( FAS ) . FAS has been implicated in cognitive deficits arising from TBI and a variety of leading neurological disorders and neurodegenerative diseases . For instance , FAS is extensively observed in Alzheimer’s disease [10 , 11] , Creutzfeldt-Jakob’s disease [15] , HIV dementia [16] , Multiple Sclerosis [17 , 18] and Parkinson’s disease [19] . Most concussions and traumatic brain injuries also lead to FAS or other morphological changes in axons [20–25] . Such dramatic changes in axon geometry may disrupt axonal transport [26 , 27] , and can potentially hinder the information encoded in neural spike train activity [28–30] . Injured axons thus provide an important diagnostic marker for the overwhelming variety of cognitive and behavioral deficits [9 , 28 , 31] , in animals and humans [23 , 32–34] . The massive size of human neuronal networks and their complex activity patterns make it difficult to directly relate neuronal network damage to specific behavioral deficits . C . elegans , in contrast , has only 302 neurons , and its stereotyped connectivity ( i . e . the worm’s “Connectome” ) is known [35] . This relatively small neuronal network generates a limited and tractable set of functional behaviors ( see Table 1 of [36] ) , with much of its locomotion/crawling behavior approximately confined to five observable motor states related to forward and backward crawling , omega turns , head sweeps and brief pause states . Furthermore , these behaviors are well described as a superposition of only a few principal component body-shape modes [37] . The combination of a fully-resolved neuronal network and a tractable low-dimensional output space makes C . elegans an ideal model organism for studying the impact of network damage on behavioral deficits . Indeed , it is the only such neuronal network model currently available allowing for such a direct translational study of network damage ( injury ) to behavioral responses . More precisely , computational models of C . elegans nervous system dynamics for the full or partial connectome successfully generate motorneuron outputs that can be related to behavior [38] , allowing for interpretable outputs even without accounting for muscular , mechanical or environmental factors , e . g . [39] . We consider the model in [39] , which applies a single-compartment membrane model to the full somatic connectome; neurons are approximated as passive linear units connected by linear gap junctions and nonlinear chemical synapses . Synaptic activation depends sigmoidally upon pre-synaptic voltage in equilibrium , and approaches this equilibrium value linearly in time . All neurons are approximated as identical , with order-of-magnitude parameter assignments , except for their connectivity data . Fig 1 ( a ) demonstrates a simulation of the putative forward crawling behavior identified in [39] within this model of C . elegans neural dynamics along with its projection onto principal component body-shape modes [37] . In this perspective , we understand forward crawling as corresponding to a limit cycle ( i . e . a closed periodic trajectory ) in the principal component space of simulated neural recordings . Extending this framework to damaged networks as in Fig 1 ( c ) allow us to explore how axonal pathologies lead to impaired functionality and behavioral deficits . Even in our idealized injury simulations , the network’s impaired activity displayed significant variability . This highlights one of the most challenging aspects of the field: the need for effective metrics to distinguish different types of behavioral deficits . We propose such a criterium by using techniques borrowed from statistical shape analysis to quantify distortions in the main features of dynamical activity . This metric is shown to be related to the functional outcome of an injury . We further apply classification trees to our results to relate functional deficits to specific patterns of FAS . This leads to experimentally-testable predictions about the effects of neuronal network-damage to the crawling motion of C . elegans and potentially new avenues for clinical diagnostics . Indeed , our studies show that network damage leads to a diversity of dynamical/behavioral deficits .
We investigate how network distributed FAS as illustrated in Fig 1 ( c ) may affect its ability to generate desired responses to an input . Network features associated with behavioral outcomes are best understood in model organisms such as the C . elegans since it has a limited repertoire of functional responses that include forward and backward crawling , omega turns , head sweeps and brief pause states . Our focus in these studies will be on the behavior of forward crawling since a variety of experimental ablation studies have identified key neurons associated this functionality . For instance , stimulation of PLM neurons excites densely-connected interneurons , which in turn , activate motorneurons responsible for forward body motion [40] . Experimentally , optogenetic stimulation of the PLM neurons directly induces a forward motion response [41 , 42] . Details of the underlying neurocircuitry were found by a series of ablation studies , where the functional role of a neuron is evaluated by disconnecting it from the network and observing behavioral deficits [39 , 43] . The coordinated body motion of a crawling worm is well documented in videos and its postural dynamics were revealed by principal component analysis to consist of only a few dominant modes [37] . Specifically , the sinusoidal body-shape undulations which describe the worm’s forward motion is well-described by circular trajectories ( limit cycles ) on the phase-space of its first two principal components . An analogous mathematical form is present in the collective motorneuron dynamics following PLM stimulation [39] . This commonality suggests that observed behaviors do retain fundamental signatures of the underlying network dynamics . We show such a trajectory for ( simulated ) motorneuron responses to PLM excitation in Fig 1 ( a ) . This low-dimensional representation captures 99 . 3% of the total energy of the system , and can be artificially mapped to crawling body-shape modes . Although this mapping is still far from a mechanistic description of the worm’s coordinated body movement , we believe it captures important aspects of the crawling behavior . See the Methods section for details . Importantly , functional deficits of the C . elegans dynamics are understood as excursions/perturbations from the ideal limit cycle trajectory . Damaged networks will be shown to fail to produce the low-dimensional output codes necessary for generating the optimal forward crawling limit cycle . The robustness of the dynamical signatures ( population codes ) associated with behavior are investigated in injured neuronal networks . Our injury statistics and FAS models are drawn from state-of-the-art biophysical experiments and observations of the distribution and size of FAS . Fig 2 shows prototypical FAS injuries from stretching [26] and TBI in the optic nerve of mice [25] . Fig 2 ( d ) shows a histogram of the probability of injury and size of the FAS . These are used in our computational model [39] . In a simulated injury , we assign to each affected neuron an axonal swelling from the distribution in Fig 1 ( b ) . Values are scaled by an ( overall ) injury intensity parameter μ , such that 1 + μ ∝ E swollen axon area healthy axon area ( 1 ) Fig 1 ( c ) exemplifies different injury settings: μ = 0 reproduces the original ( uninjured ) network , and lower/higher values of μ correspond to mild/severe injuries . The presence of axonal swellings ultimately distorts the forward-motion limit cycle dynamics . Fig 3 shows dynamical anomalies for different connectome injuries . Notice how they induce qualitatively different changes to the closed orbit regarding location , size and shape . Fig 3 ( c ) reproduces the specific simulated ablations from [39] , leading again to different dynamical effects . A much larger ensemble of simulations ( 1 , 447 randomly-chosen injuries , as well as the code necessary to generate more ) and their corresponding effects to fundamental low-dimensional structures are included in the Supporting Materials . Increasing values of μ typically shrink and shift the limit cycles within the plane . In all simulations , there was always a sufficiently high injury level in which μ * = {injured limit cycle collapses into a stable fixed point } ( 2 ) This occurs for instance , in Fig 3 ( b ) when μ = 3 . 80 . Recent blast injury studies on C . elegans show that many of the nematodes display temporary paralysis before recovering to crawling behaviors [45] . We would suggest that during the peak of the FAS , the injury levels on many of the nematodes are above μ* , thus leading to a collapse of a limit cycle to a fixed point where no motion is possible , i . e . it is in a paralyzed state . Despite their common statistical distribution , randomly drawn injuries induce qualitatively different changes in the shape of the limit cycle . Additional distorted sets are shown in the rows of Fig 4 ( along with 1 , 447 random-injury simulation sets in the Supporting Materials ) . Thus , random injuries of equitable strength can lead to significantly different behavioral deficits . Importantly , the deformation of the two-dimensional limit cycle can be used to characterize such functional differences . To distinguish dynamical signatures of potentially different functional deficits , we evaluate the Procrustes Distance ( PD ) between healthy and injured limit cycles . The PD is an important tool from statistical shape analysis to measure the similarity between two shapes after discounting effects due to translation , uniform scaling , or rotation . Fig 4 depicts PD values for pairs of healthy/injured limit cycles as a function of injury level μ . All curves are plotted until the injured limit cycle collapses into a fixed point ( μ = μ* ) , and the colored dots in the rightmost plots correspond to the same-colored limit cycles on the left plots . Recent experimental work which induced mild TBI in C . elegans found that increasing the number of shock waves to which the worm was exposed reduced the worm’s average speed and , in many cases , led to temporary paralysis [45] . The results of our simulations can be compared to these results: In Fig 5 we plot the location of the fixed points into which limit cycles collapse ( the “endpoints” , occurring at injury level μ = μ* ) . We consider the following question: does the location of this endpoint ( and thus the behavioral outcome of the injury ) relate to the PD curve , and does it relate to the structure of the injury itself ? Towards this end , we construct two simple classes of behavioral outcomes: endpoints which end in either the “upper” or “lower” part of the distribution ( for which we label the endpoints as red and green , respectively ) . Panel ( b ) of Fig 5 shows the average PD curve for the two classes . They are qualitatively different: the average PD curve of “upper” endpoints is smoothly rising , whereas the average PD curve of “lower” endpoints has an extended declining region . Shown also are the average scaling factor and translation distance of the distorted cycles . Unlike the average PD curves , these change monotonically and are not distinct between classes . This suggests that the shape of the PD curve carries information about the functional outcome of the injury . We quantify this by fitting a classification tree to predict the endpoint class from the shape of the PD curve: this was found to predict endpoint class with a cross-validation error of 22 . 0% . By comparison , randomly shuffling the labels leads to nearly double the cross-validation error , with an average of ( 44 . 6 ± 1 . 4 ) % . Of even greater interest is any possible relationship between injury structure and behavioral output which could , given a specific pattern of distorted dynamics , make predictions about the class of neural injury . To this end , we fit a classification tree to predict the endpoint class from the injury . Fig 6 shows a classification tree which predicts endpoint class with a cross-validation error of only 14 . 6% . This is much less than the error from a random class , suggesting that we can meaningfully relate the structure of a specific injury to a specific behavioral outcome . Classification trees provide a highly interpretable and predictive method for making this connection , and make specific experimental predictions for the injuries corresponding to functional deficits .
The dynamic model for the C . elegans connectome simulates its neuronal responses to stimuli with a number of simplifications aimed at keeping the number of parameters at a minimum: we use a fairly standard and simple single-compartment membrane equation , and treat all neurons as identical save for their connectivity . Many neurons in the network are nearly isopotential [46 , 47] , and it is a common and reasonable simplification to model neurons via single-compartment membrane equations , with membrane voltages as the state variables for each neuron . Given this , Wicks et al . constructed a single-compartment membrane model for neuron dynamics [48] , which we later extended to incorporate connection data for the full somatic connectome [39] . We assume that the membrane voltage dynamics of neuron i is governed by: C V i ˙ = - G c ( V i - E c e l l ) - I i G a p ( V → ) - I i S y n ( V → ) + I i E x t ( 3 ) The parameter C represents the whole-cell membrane capacitance , Gc the membrane leakage conductance and Ecell the leakage potential of neuron i . The external input current is given by I i E x t . Note that this is , essentially , a fairly standard single-compartment membrane equation [49] , and its governing equations are formally identical to that used by Wicks et al . [48] except for our use of the full somatic connectome , our simplifying parameter assumptions , and minor differences in the treatment of synaptic dynamics taken from [50] . In all simulations within this paper , we set I i E x t to be constant for the PLM neuron pair and zero for all other neurons . This assures that densely connected interneurons will stimulate the motorneuron subcircuits responsible for forward crawling behavior . Neural interaction via gap junctions and synapses are modeled by the input currents I i G a p ( V → ) ( gap ) and I i S y n ( V → ) ( synaptic ) . Their equations are given by: I i G a p = ∑ j G i j g ( V i - V j ) ( 4 ) I i S y n = ∑ j G i j s s j ( V i - E j ) ( 5 ) We treat gap junctions between neurons i and j as ohmic resistances with total conductivity G i j g . We assume that I i S y n is also modulated by a synaptic activity variable si , which represents the conductivity of synapses from neuron i as a fraction of their maximum conductivity . This is governed by: s i ˙ = a r ϕ ( v i ; β , V t h ) ( 1 - s i ) - a d s i ( 6 ) Here ar and ad correspond to rise and decay time , and ϕ is the sigmoid function ϕ ( vi; β , Vth ) = 1/ ( 1 + exp ( −β ( Vi − Vth ) ) ) . This form of sigmoidal activation is taken from [50] . Note that it can be shown ( by setting s ˙ = 0 ) that , as in [48] , the equilibrium value of si depends sigmoidally upon Vi . We keep all parameter values from [39] ( see Table 1 . The Connectome data , consisting of the number of gap junctions N i j g and number of synaptic connections N i j s , are taken from Varshney et al . [35] ( as available on WormAtlas [51] ) . As in that study , we consider only the 279 somatic neurons which make synaptic connections ( excluding 20 pharyngeal neurons , and 3 neurons which make no synaptic connections ) . Each individual synapse and gap junction is assigned an equal conductivity of g = 100pS ( such that G i j g = g · N i j g and G i j s = g · N i j s ) . The values of cell membrane conductance and capacitance are affected by injuries , but in the uninjured case are set as equal for all neurons with values of Gc = 10pS and C = 1pF . Note that in uninjured simulations , all neurons are modeled as identical except for their connectivity and the assignment of them as excitatory or inhibitory ( where Ej will have one of two values corresponding to these classes ) . The model is valuable because it generates a low-dimensional neural proxy for behavioral responses . Specifically , constant stimulation of the tail-touch mechanosensory pair PLM creates a two-mode oscillatory limit cycle in the forward motion motorneurons [39] . This same dynamical signature was revealed in video analysis of the body-shape of the crawling worm [37] . Thus the model is consistent with the observed biophysics . Specifically , we calculate this plane by first simulating the forward-motion motorneuron membrane voltages ( class DB , VB , DD , VD ) in response to a PLM Input of IPLML , IPLMR = 2 × 104 Arb . Units for the uninjured model . We take time snapshots these membrane voltages V → M ( t ) , collect them into a matrix V , and take that matrix’s singular value decomposition . That is: V = [ V → M ( t 0 ) , V → M ( t 1 ) … ] = P · Σ · Q T ( 7 ) where P and Q are unitary and Σ is diagonal . The columns of P are the principal orthogonal modes . As in [39] , the first two of these modes ( the first two columns of P ) almost entirely capture the dynamics of the system within this subspace under constant PLM stimulation . Projection of the full-system dynamics onto this plane consists of projecting the system’s motorneuron dynamics onto these modes . Note that the single-compartment model which we employ ignores the spatial extent of neurons and specific location of each connection . Our simplified injury model therefore must treat injury as a whole-cell effect . Focal Axonal Swellings ( FAS ) increase the volume of an axon , which in turn , should alter the cell’s capacitance and leakage conductance within our model . If we approximate a neuron by a single cable of length l and constant cross-section a , we may assume that the circuit parameters will scale with the axonal volume , i . e . , C ∝ a · l ( 8a ) G c ∝ a · l ( 8b ) When an axon swells , its healthy cross-sectional area aH will increase to some swollen value ai > aH . Thus we assume that the healthy values for capacitance C and conductance Gc will also change according to C i = C · ( a i / a H ) = C · ( 1 + μ · m i ) ( 9a ) G i c = G c · ( a i / a H ) = G c · ( 1 + μ · m i ) ( 9b ) We define the individual damage mi to neuron i as proportional to the relative excess area from swelling , i . e . , mi ∝ ( ai − aH ) /aH . Values of mi are computed from the experimentally derived distributions in Fig 2 . Specifically , we construct FAS from the axonal swelling data of Wang et al . [25] , which used confocal microscopy to measure injury-induced swellings in the optic nerve of Thy1-YFP-16 mice . Taken together , these define an “injury vector” m → , which we then normalize to | | m → | | 2 = 1 . After normalizing , the injury vector is then scaled by a global injury intensity defined as follows: μ = ⟨ a i / a H ⟩ - 1 ⟨ m i ⟩ ( 10 ) Mild traumatic brain injuries yield small values of μ indicating that the average area of swollen axons is small . Severe brain injuries yield high values of μ , indicating that large swellings are more common . We leave the PLM pair of neurons receiving input uninjured . All other neurons have their mi values assigned from the experimental statistical distributions . The governing equation for an injured neuron is now C V i ˙ = - G c ( V i - E c e l l ) - ( I i G a p ( V → ) + I i S y n ( V → ) ) / ( 1 + μ · m i ) ( 11 ) We can readily interpret the limiting cases: when μ ⋅ mi = 0 , the original governing equation is recovered , and thus μ = 0 corresponds to the healthy case . When μ ⋅ mi is large , gap junction and synaptic currents have no effect . The neuron’s voltage decays exponentially to its leakage potential , effectively isolating it from the network . Note that our random assignment of swelling values neglects any spatial structure of the injury . This could be easily modified by using a distribution which depends on the spatial location of the neuron . Furthermore , this is a very simple model for neuronal swelling , in keeping with our simple model for neurons . It necessarily neglects the actual geometry of swelling . The use of a multi-compartment model would enable this in future studies . Ultimately , there is currently limited biophysical evidence for making more sophisticated models . As such , we have tried to capitalize on as many biophysical observations as possible so as to make a model that is consistent with many of the key experimental observations . We use MATLAB ( version R2013a ) to solve the system of neuronal dynamical equations via Euler’s method , using a timestep of 10−4s . We consider an ensemble of 1 , 447 different types of injury ( set of targeted neurons ) , for which the global intensity μ may vary from 0 ( uninjured ) to a critical value μ* . When the intensity exceeds μ* ( found by a bisection algorithm ) , the limit cycle collapses to a fixed point . To obtain intermediate values , we perform five simulations linearly spaced throughout ( 0 , 0 . 9μ* ) and ten additional simulations throughout ( 0 . 9μ* , μ* ) . We classify the resulting injured trajectories as a Fixed Point or a Periodic Orbit according to the following criteria: Note that these criteria classify very small periodic orbits as fixed points , since their behaviors are very similar . The method may also classify sufficiently slow , long-timescale oscillatory transients as periodic . These tests ignore the first 5 seconds of simulation time ( 50 , 000 timesteps ) , chosen heuristically as a typical timescale of transient decay . After this initial wait , we check the criteria at the end of each subsequent 5 seconds of simulation time until convergence is detected . The results were not observed to be sensitive to the length of this interval . Stephens et al . [37] found that the forward crawling motion of C . elegans is well described by two principal component body-shape modes called eigenworm modes . When moving forward , the modes alternate within its phase space forming a limit cycle . Kunert et al . [39] also found a two-dimensional limit cycle , but for the collective motorneuron activity after PLM stimulation . They interpret this similar dynamical signature as a neuronal analog to the observed behavioral pattern . To interpret the distorted neural activity caused by our simulated injuries , we construct a map from the neuronal activity plane onto the eigenworm plane . The body-shape modes were extracted from Figure 2 ( c ) of [37] . We first calculate the optimal linear mapping of the healthy trajectory onto a circle ( see Fig 3a ) . We then use this calibration for all other trajectories . This artificially translates anomalous neuronal responses to anomalous body motions . Our procedure has a number of limitations , for which we list a few: The lack of direct neuronal analogs for injured network modes limits our ability to interpret arbitrary impaired behavioral responses . Further computational work could also find neuronal proxies for additional behavioral modes so as to enable a more complete mapping . Recent work on blast injuries of worms [45] could potentially help extend the analysis by providing injured eigenworm mode projections . Procrustes Distance ( PD ) measures the dissimilarity between shapes , and in our context , we wish to compare the shape of the trajectories of the healthy neural responses ( circular orbits in the phase plane ) with the distorted ones produced after simulated injuries . For that , we use the function procrustes . m from MATLAB’s Statistics and Machine Learning Toolbox . We collect N data points from each trajectory and annotate their ( x , y ) coordinates in a ( 2 × N ) shape matrix S . The PD between two distinct shapes SA and SB is given by P D = min b , R , c ∥ S B - b · S A · R + c → ∥ 2 ( 12 ) In other words , it finds the optimal ( 2D ) rotation matrix R , scaling factor b > 0 , and translation vector c → to minimize the sum of the squares of the distances between all points . Intuitively , it compares shapes discounting translation , rotation , or scaling . To calculate the PD curves as in Fig 4 , we use the uninjured ( μ = 0 ) limit cycle as our first shape SA . The second shape SB is the limit cycle calculated for each injury at the indicated value of μ . We pre-process the trajectories to extract data points only within a single period . Since injuries usually distort the trajectory length , we use MATLAB’s spline . m function to interpolate them and collect the same number of data points . Both limit cycles must also be phase-aligned , which we achieve by finding the phase that minimizes the Procrustes Distance . We hypothesize that both the injury itself and the PD curves contain meaningful signatures of behavioral outcomes of a given injury . For example , there is always a critical injury level μ = μ* in which the injured response collapses into a fixed point . Our artificial map suggests that this endpoint location corresponds to the shape of a paralyzed worm . We thus wish to relate endpoint location to ( 1 ) the shape of the PD curve , and to ( 2 ) the injury vector m → . For these purposes , we classified the endpoints simply by dividing the endpoint distribution along its major axis . Specifically , we take the distribution of endpoints in Fig 5 , calculate the leading principal orthogonal mode ( via taking the Singular Value Decomposition , as mentioned earlier ) , and classify the points by the value of their projection onto this mode ( where we arbitrarily classify projection values ≥ −0 . 01 as the “upper plane” and < −0 . 01 as the “lower” plane ) . Given this definition , 63 . 2% of the points lie within the upper plane , and 36 . 8% lie in the lower plane . Note that all of the forthcoming analysis could be equally well applied to any other output feature , and so we choose this classification for its relative simplicity . We calculate the average PD curve within each class . Since the PD curves may have a different number of points , we first pre-process them . Specifically , we normalize the maximum μ and Procrustes Distance to 1 for all curves , and then interpolate them using MATLAB’s spline . m such that all curves have the same number of points . We then simply take the average and standard deviation to obtain the average curves shown within Fig 5 . This figure also plots the average scaling and translation curves as a function of injury level , for each class . Scaling factors ( i . e . the factor by which the size of the distorted limit cycle has decreased from the original cycle ) are given as an output of MATLAB’s procrustes . m as used above . Translation distance is found by calculating the location of the mean of each distorted cycle , and then calculating the distance by which this mean is displaced from the origin . These curves are then normalized , interpolated and averaged , yielding the average curves in Fig 5 . Note that , unlike the PD curves , translation and scaling are monotonic and not distinct between classes , and thus they do not carry the same information about the functional outcome of the injury . We use the ClassificationTree class from MATLAB’s Statistics Toolbox ( version R2013a ) . Fitting and cross-validation are performed using the included methods ClassificationTree . fit and kfoldLoss with default settings ( 10 folds ) . The minimum leaf size was set by calculating cross-validation error over a range of minimum leaf sizes ( see Fig 6b ) . For both PD curves and Injuries , cross-validation errors are optimal at a minimum leaf size of around 40 . We use this minimum leaf size for all fits . The classification tree that uses normalized PD Curve Shapes to predict the endpoint class yield a cross-validation error of 22 . 0% . We can compare this to the random case ( i . e . the case where PD Curve Shape has no relationship to the class ) by repeating this analysis with randomly shuffled class labels . For 100 trials with randomly-shuffled labels , the observed cross-validation error was 43 . 8 ± 1 . 4% . Injury vectors were also used to fit classification trees for predicting endpoint classes ( see Fig 6 ) . The cross-validation error of 14 . 6% was significantly lower in this case , while the randomly-shuffled labels analysis returned a error of 44 . 6 ± 1 . 3% ( consistent with the random error above ) . In both cases we observe that the cross-validation error is far below what we would expect if the data had no relation to the classes . Thus we can predict ( with cross-validated accuracy exceeding 85% ) the region into which the endpoint will fall given a specific injury . Moreover , the classification tree in Fig 6 is very simple to interpret and depends on only three neurons: ALML , AVM and SDQL . As per WormAtlas [51] , all three of these neurons have sensory functions ( ALML and AVM are mechanosensory; SDQL is an interneuron but is oxygen-sensing ) .
Simulated injuries distort dynamical signatures in the network’s activity , such as limit cycles . Our Procrustes Distance metric quantifies how much the shape of the limit cycle is distorted , compared to the healthy cycle . Our results indicate that as different injuries evolve , this metric follows qualitatively different trends ( as in Fig 4 ) . In all trials , a sufficiently high injury level μ = μ* collapses the limit cycle into a stable fixed point . The shape of the PD curve helps inform the location of this fixed point ( as in Fig 5 ) . This suggests that the shape of the PD curve , as the injury evolves , may help predict the eventual behavioral outcome ( e . g . , the body shape the worm will assume during temporary paralysis ) . Thus we have prescribed a method to monitor the dynamics of the injured worm and the implications of the injury as it evolves . Finally , our classification trees divides neural injuries into two distinct classes of functional outcomes ( i . e . endpoints in the “lower” or “upper” portions of the distribution ) . Its cross-validation predictive accuracy is over 85% and implicates only three specific neurons ( ALML , AVM , and SDQL ) . This relationship between injury structure and behavioral outcome is simple , interpretable and testable . Such trees can be fit for arbitrary injured behaviors and could be used more broadly for any given model of injured full-Connectome dynamics . The metrics and methods described in this work can potentially be used to construct diagnostic tools capable of identifying a variety of cognitive deficits . Moreover , the severity of a TBI injury and/or neurodegenerative disease can be quantified by measuring its metric distance from the normal/healthy performance . Our work gives clear mathematical tools capable of formulating such diagnostic tools for assessing injuries and functional deficits . The present study has many limitations , many due to the lack of biophysical evidence required to build better models . For example , though we treat all neurons as identical passive , linear units , it is known experimentally that different neurons appear to exhibit different behaviors ( for example , some neurons appear to be functionally bistable [55] and could be modeled as such , as in [56] ) . We predict the results of injuries only on the two “forward-motion” motorneuron modes , ignoring other modes potentially associated with impaired behaviors . Furthermore , the exact mapping of our motorneuron voltage modes onto these body-shape modes is ambiguous . The model lacks muscles and body features of the worm which limits our ability to make more general predictions . We also neglect external feedback mechanisms required for sustained and spontaneous forward motion , and assume that tail-touch neurons are constantly stimulated . It is uncertain how such feedback mechanisms would alter the trajectory . The order-of-magnitude parameter estimates of our model parameters also make direct quantitative comparisons difficult . We believe the merit of this study lies not so much on the specific results presented , but on the new directions and methodologies it opens for future work . In fact , computational and experimental studies on the effects of network injury are still at their infancy for C . elegans and other models . Many limitations of this work could be overcome with a more detailed model for the C . elegans neuronal network both before and after injury . Coupling this with an external , mechanical model would allow for more general predictions . This could be accomplished with simplified mechanical models for locomotion ( such as in [56] ) or with more complete , future “in-silica” models such as OpenWorm [57] . The development of such models , which do not ignore the spatial extent and shape of neurons , would allow for the study of the effects of injuring individual connections , or the effect of injuring individual neurons non-homogeneously . This study suggests that such modeling work should also consider how to model neural injuries , after which our analysis techniques could be applied directly . Experimental studies would not only test our model , but also in , in conjunction with our work , provide a new testbed for models of injured connectomic dynamics . Our Procrustes Distance metric , shown here to carry information about the eventual outcome of an injury , may also be useful in the real-time analysis of injury progression . Thus our study provides a way forward in monitoring behavioral outcomes of injured networks . Ultimately at present , limitations in biophysical measurements and neural recordings make it extremely difficult to identify more sophisticated underlying mechanisms responsible for dysfunctions in neural networks , especially when circuits display intrinsically complex behavior and functional activity . We believe the rapid advancement of recording technologies in neuroscience will significantly help refine the model presented here . Given that the modeling of neuronal networks is one of the most vibrant fields of computational neuroscience [49 , 58 , 59] , our contribution provides a comprehensive study of how the effects attributed to FAS jeopardize the network functionality , opening new possibilities and objectives for the study of network architectures .
|
Neurodegenerative diseases such as Alzheimer’s disease , Creutzfeldt-Jakob’s disease , HIV dementia , Multiple Sclerosis and Parkinson’s disease are leading causes of cognitive impairment and death worldwide . Similarly , traumatic brain injury , the signature injury of the Iraq and Afghanistan wars , affects an estimated 57 million people . All of these conditions are characterized by the presence of focal axonal swellings ( FAS ) throughout the brain . On a network level , however , the effects of FAS remain unexplored . With the emergence of models which simulate an organism’s full neuronal network , we are poised to address how neuronal network performance is degraded by FAS-related damage . Using a model for the full-brain dynamics of the nematode Caenorhabditis elegans , we are able to explore the loss of network functionality as a function of increased neuronal swelling . The relatively small neuronal network generates a limited and tractable set of functional behaviors , and we develop metrics which characterize how these behaviors are impaired by network injuries . These metrics quantify the severity of TBI and/or neurodegenerative disease , and could potentially be used to construct diagnostic tools capable of identifying various cognitive deficits . Additionally , we apply classification trees to our results to make predictions about the structure of an injury from specific cognitive deficits .
|
[
"Abstract",
"Introduction",
"Results",
"Methods",
"Discussion"
] |
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2017
|
Functionality and Robustness of Injured Connectomic Dynamics in C. elegans: Linking Behavioral Deficits to Neural Circuit Damage
|
TNF-related apoptosis inducing ligand ( TRAIL ) death receptors ( DR ) regulate apoptosis and inflammation , but their role in antiviral defense is poorly understood . Cytomegaloviruses ( CMV ) encode many immune-modulatory genes that shape host immunity , and they utilize multiple strategies to target the TNF-family cytokines . Here we show that the m166 open reading frame ( orf ) of mouse CMV ( MCMV ) is strictly required to inhibit expression of TRAIL-DR in infected cells . An MCMV mutant lacking m166 expression ( m166stop ) is severely compromised for replication in vivo , most notably in the liver , and depleting natural killer ( NK ) cells , or infecting TRAIL-DR−/− mice , restored MCMV-m166stop replication completely . These results highlight the critical importance for CMV to have evolved a strategy to inhibit TRAIL-DR signaling to thwart NK-mediated defenses .
Tumor necrosis factor ( TNF ) -family cytokines regulate multiple aspects of host antiviral immunity , in part through their abilities to promote cell death and survival [1] . In many cases , this involves both the direct killing of virally infected cells , as well as assisting in terminating the host effector response after infection is controlled in order to limit tissue damage and restore homeostasis . Herpesviruses induce robust host defenses upon infection , including many mediated by TNF-family cytokines , but nevertheless successfully establish a lifelong infection . This is due in large part because they encode an enormous number of immune-modulatory proteins , a fact epitomized by cytomegalovirus ( CMV , the prototypic β-herpesvirus ) [2] , [3] , the largest of the human herpesviruses that expresses >700 protein-encoding transcripts [4] derived from its >230 kb genome . As CMV , as well as other herpesviruses , encode multiple strategies targeting the TNF-family [1] , [5] , this strongly suggests their importance in defense to these persistent viruses and the necessity for the evolution of viral counterstrategies targeting them . Human CMV ( HCMV/HHV5 ) infects the majority of people worldwide , with incidence increasing with age and varying by race , geography and socioeconomic standing [6] . Primary infection is usually asymptomatic in healthy individuals , however in people with suppressed or naive immune systems it can result in serious disease , and the high incidence of congenital infection is a driving force for vaccine development [7] . Natural killer ( NK ) cells are critical for controlling HCMV infection and disease [8] , [9] , and recent data indicate the virus preferentially impacts NK subsets expressing the NKG2C activating receptor [10] , [11] . In turn , HCMV utilizes multiple strategies to dampen NK-mediated defenses in order to promote its replication and dissemination [12] . As CMV replication is highly species specific , mouse CMV ( MCMV; a natural mouse pathogen ) has proved to be an invaluable model for studying CMV infection and immunity . MCMV has provided many key insights into mechanisms of NK-mediated antiviral immunity through both direct recognition of infected cells ( e . g . m157-Ly49H interaction ) [13] , [14] and cytokine-induced activation ( e . g . IL-12 and type I interferon ( IFN-I ) ) [15] . TNF-related apoptosis inducing ligand ( TRAIL/TNFSF10 ) binds multiple receptors in humans and mice , including both death ( DR ) and ‘decoy’ receptors [16] , [17] . While humans encode two DRs for TRAIL ( TRAIL-R1/DR4 and TRAIL-R2/DR5 ) , mice encode only one , which shows modestly higher homology to TRAIL-R2 [17] . TRAIL is expressed by a wide range of hematopoietic and stromal cells , and is strongly induced by IFNs [18] . NK cells can produce high levels of TRAIL [18] , [19] , utilizing it as an effector molecule to kill tumor cells [20] , [21] . Although TRAIL's role in regulating anti-tumor immunity is well established , its importance in anti-pathogen defense is only just emerging [22] , [23] . Several studies suggest a multi-faceted role for TRAIL in antiviral immunity , where it can be both protective and pathogenic , depending upon virus- and tissue-specific factors [18] , [23] , [24] , [25] . We have recently demonstrated that the HCMV glycoprotein UL141 can bind and suppress cell surface expression of the human TRAIL-DRs [26] , expanding upon its previously known role in restricting expression of the NK cell activating ligands CD155 and CD112 [27] , [28] . We now show that inhibition of TRAIL-DR signaling is conserved across the CMVs , with the m166 protein of MCMV performing a similar function as UL141 despite showing no overt sequence similarity , and is critical to thwart TRAIL-mediated NK defenses in vivo . M166 completely neutralizes host defenses mediated by TRAIL-DR signaling in vivo , with no alterations in the replication of wild-type MCMV seen in TRAIL-DR−/− mice , highlighting how key insights into operable host defenses can be uncovered by studying viral immune modulatory strategies .
CMV utilizes multiple strategies to block both extrinsic and intrinsic apoptotic pathways [29] , [30] , and recent data has shown that human CMV directly inhibits TRAIL-DR expression [26] , [31] . To test whether mouse CMV might utilize a similar strategy , infected fibroblasts were analyzed for TRAIL-DR expression by flow cytometry ( Fig . 1A ) , revealing that MCMV also inhibits cell surface levels of this DR . MCMV inactivated with UV light was unable to inhibit TRAIL-DR expression ( data not shown ) , strongly suggesting that a virally-encoded protein performed this function . To attempt and identify the responsible MCMV open reading frame ( orf ) , a panel of relatively large deletion mutants generated in the BAC cloned MCMV genome ( Smith strain ) was initially utilized [32] . TRAIL-DR surface expression was monitored after infection of 3T3 cells with these mutants , revealing a putative responsible orf ( s ) to be located between m159 and m170 ( Fig . 1B ) . Additional smaller deletion mutants ( Δm159-m161 , Δm162-m166 , Δ167-m170 ) were then utilized to identify the m162-m166 region as required for TRAIL-DR inhibition ( data not shown ) . Subsequently , individual mutant viruses were generated disrupting these five individual orfs , revealing that an intact m166 orf appeared to be required for inhibition of TRAIL-DR cell surface expression ( Fig . 1C ) . Similar to HCMV [4] , recent analysis of the MCMV transcriptome has revealed the presence of numerous , previously unrecognized transcripts arising largely from differential splicing [33] . Our initial approach inserting a kanamycin resistance cassette to identify the MCMV genomic loci that encoded the orf ( s ) responsible for restricting TRAIL-DR expression , although effective , has high potential to impact expression of neighboring or transcriptionally overlapping orfs . Therefore , in order to verify the predicted m166 orf-encoded protein was truly required for inhibiting TRAIL-DR expression , a stop codon was inserted in the m166 orf by ‘traceless’ mutagenesis in the BAC-cloned K181 strain of MCMV ( referred to as m166stop hereafter ) , which should be minimally disruptive to the overall locus transcription . MCMV-m166stop was unable to restrict TRAIL-DR cell surface expression ( Fig . 1D ) , indicating that the predicted m166 orf is required for TRAIL-DR inhibition . Detailed expression analysis of m166 has not been performed to date , which is common for many of the predicted MCMV orfs . RACE analysis of transcripts emanating from the m166 locus revealed only one major mRNA initiating from the predicted start codon ( Fig . 2A ) , consistent with a recently published result [33] . M166 mRNA expression was detectable by 30 minutes post infection , closely paralleling expression of the immediate early-1 ( ie1 ) mRNA ( Fig . 2B ) . For analysis of m166 protein expression , a recombinant MCMV was generated with a C-terminal HA epitope tag ( MCMV-m166HA ) . MCMV-m166HA inhibited TRAIL-DR expression similarly to WT MCMV ( Fig . 2C ) , and m166 protein was detectable by 2 hours post infection , robustly expressed by 4 hours and remained high at 24 hours ( Fig . 2D ) . The downregulation of TRAIL-DR cell surface levels followed a similar kinetic , with reduced expression beginning at 4–8 hours and increasing by 24 hours ( Fig . S1 ) . The expression of m166 was inhibited by cycloheximide and actinomycin D , whereas it was not blocked by addition of foscarnet , indicating m166 is an early gene product ( Fig . 2E ) . M166 was localized largely to the endoplasmic reticulum ( ER ) ( co-localized with GRP94 , ER marker ) in MCMV-m166HA infected 3T3 cells at early times ( 6 h ) , while at later times ( 20 h ) it was also detectable in the Golgi apparatus ( co-localized with GM130 , cis-golgi marker ) ( Fig . 2F ) . Endogenous TRAIL-DR could be detected in 3T3 cells only after treatment with the proteasome inhibitor MG132 , but under these conditions no co-localization was observed with m166 ( Fig . S2A ) . When TRAIL-DR was overexpressed , a modest level of co-localization with m166 was observed in the ER ( Fig . S2B ) . At these same times when m166 was expressed largely intracellular and TRAIL-DR cell surface levels were markedly decreased , TRAIL-DR mRNA levels remained similar to uninfected cells , indicating inhibition by m166 occurs at a post-transcriptional step ( Fig . 2G ) . Finally , transfection of a m166-GFP expression plasmid into 3T3 cells resulted in downregulation of TRAIL-DR cell surface expression , indicating that m166 is both necessary and sufficient to restrict its cell surface expression ( Fig . 2H ) . As expected , based on our observations of several Smith-based BAC mutants that lacked m166 expression , replication of MCMV K181 m166stop was similar to WT in cultured fibroblasts ( Fig . S3 ) . However , to examine whether restriction of TRAIL-DR by m166 might contribute to in vivo virulence , BALB/c mice were infected with MCMV WT and m166stop , and replication levels were determined four days later . Mice infected with MCMV-m166stop showed no detectable virus production in liver ( Fig . 3A ) and markedly reduced replication ( ∼15 fold ) in spleen ( Fig . 3B ) with two different doses of MCMV ( Fig . S4A , B ) . Significantly reduced replication of m166stop was also observed in both the lung and heart at day 4 ( Fig . S4C , D ) . Our recent results indicate that the ‘first burst’ of MCMV production in vivo occurs at ∼32 hours in the spleen and liver after systemic infection , and that innate control at this early time is dependent upon stromal cell-mediated defenses and independent of toll-like receptors [34] , [35] . Interestingly , m166stop replication was also compromised ( ∼5–10 fold ) in the liver at 32 hours post infection ( Fig . 3C ) . This result indicates that in addition to the absolute requirement for m166-mediated inhibition of TRAIL-DR to sustain replication of MCMV in this organ until day 4 , it is also critical to thwart innate defenses at the very earliest times of infection . NK cells exert innate defense to MCMV infection in the spleen and liver , with the degree varying depending upon the specific inbred mouse strain [14] , [36] , [37] . Infection with MCMV WT and m166stop resulted in equivalent numbers of resident/recruited NK cells in the liver at day 4 ( Fig . 4A ) . Next , to ascertain whether MCMV-m166stop was more subject to NK-mediated antiviral defenses , these cells were depleted prior to infection . NK-depletion resulted in the complete restoration of MCMV-m166stop replication to WT levels in both the liver and spleen ( Fig . 4B , C ) . Notably , depleting NK cells did not enhance the replication of WT MCMV in either spleen or liver of BALB/c mice ( Fig . 4B , C ) , which was not entirely unexpected based on previous results [38] , [39] . NK cells can express TRAIL in response to virus-induced innate cytokines , so this was analyzed during MCMV infection . Tissue-resident NK cells exist in naïve , C57BL/6 ( B6 ) mice at various stages of maturation identified by their differential expression of CD11b , DX5 and CD27 , with ‘immature’ cells ( CD11blo ) in the liver constitutively expressing cell-surface TRAIL and making up a low proportion of the total pool ( <30% ) [40] , [41] . Similar subsets of mature and immature NK cells could be identified in naïve BALB/c mice ( Fig . S5A ) , with many being CD11blo ( >60% ) and expressing high levels of surface TRAIL ( Fig . 5A ) . TRAIL was undetectable on mature liver NK cells ( CD11bhi ) , and no splenic NK cell subsets expressed detectable TRAIL in naïve mice ( Fig . 5B ) . Following infection with MCMV , surface TRAIL was induced to much higher levels on approximately half of the CD11bl°CD27− and a small percentage of CD11bl°CD27+ NK cells in the liver ( 5–6 fold increase in MFI in both subsets ) , while only very modest TRAIL induction ( <2 fold ) was seen on mature NK cells in this organ ( Fig . 5C ) . In contrast , all NK subsets in the spleen showed very modest induction of TRAIL following MCMV infection ( <2 fold over naïve ) , with immature subsets expressing slightly more than mature ( Fig . 5D ) . In addition , TRAIL mRNA levels in FACS-purified , liver NK cell subsets paralleled its cell surface expression ( Fig . S5B ) , indicating mature NK cell subsets are not likely to express high levels of secreted/soluble TRAIL compared to their immature counterparts . Importantly , NK cell numbers ( Fig . 4A ) , subset proportions and TRAIL expression were not grossly different upon infection with MCMV WT and m166stop ( Fig . S5C , D ) , although a slight increase in the proportion of mature NK cells was observed in m166stop MCMV infected livers ( WT vs . m166stop = 59 . 8% vs 68% ) , indicating this mutant does not induce a ‘globally different’ response . Taken together , these results show that distinct subsets of tissue resident NK cells differentially express TRAIL upon MCMV infection , and likely have distinct capacities to mediate TRAIL-dependent immune control . In addition , high levels of TRAIL expression by liver-resident NK cells correlates with the enhanced control of the m166stop mutant in that organ compared to the spleen . The HCMV UL141 protein restricts expression of several cell surface molecules that regulate NK activation and/or effector function in addition to the human TRAIL-DRs ( e . g . CD155 and CD112 ) [26] , [27] , [28] . Consequently , it is possible that m166 may also target additional host proteins , and was therefore critical to determine whether inhibition of TRAIL-DR expression was responsible for the attenuated replication of m166stop . Therefore , TRAIL-DR−/− BALB/c mice were infected with MCMV WT and m166stop , and viral replication was measured in liver and spleen four days later . Exactly paralleling the data obtained in NK-depleted mice , m166stop replication was restored to WT levels in the liver and spleen of TRAIL-DR−/− mice ( Fig . 6 ) . Notably , no differences in the replication of WT MCMV was observed in spleens or livers of TRAIL-DR−/− mice , supporting the notion that m166 completely neutralizes any potential antiviral defenses mediated by this DR in vivo . Naïve TRAIL-DR−/− mice have similar NK subset proportions and TRAIL expression to WT BALB/c mice , and equivalent numbers of TRAIL-expressing NK cells were present in the liver of TRAIL-DR−/− upon infection with both MCMV WT and m166stop ( Fig . S6 ) . In summary , these results prove that the dominant function of m166 is to promote resistance to TRAIL-DR dependent , NK-mediated innate defense during MCMV infection .
Here we have identified the m166 protein of MCMV to be critical for viral inhibition of NK cell-mediated innate defense through its inhibition of TRAIL-DR cell surface expression . This is the first function ascribed to m166 , and the first report that this natural mouse pathogen specifically targets this death receptor . M166 promotes early MCMV replication in an organ-specific manner , with the m166stop mutant being essentially ‘dead’ in the liver while still replicating to some degree in the spleen ( ∼15 fold reduction ) . A key message from this study is that: In order to fully understand the operable host immune mechanisms activated upon infection that have antiviral potential , we must consider both the virus and host sides of the equation . Our results in TRAIL-DR−/− mice show that replication of WT MCMV is unaltered , which at first glance might suggest that signaling by this TNFR has no potential to impact defenses to this β-herpesvirus . Instead , we have revealed that TRAIL-DR signaling is extremely effective at limiting MCMV replication/spread if it is not neutralized by m166 function . These results exemplify the crucial role that signaling by TNF-family cytokines plays in regulating the ‘push-and-pull’ between virus and host , exemplified by the herpesviruses , which establish lifelong persistence and employ a variety of strategies to target them . The mouse model is commonly used to attempt and elucidate operable host immune mechanisms that may control CMV infection of humans . These two CMVs show many similarities in both their course of infection and their lasting impact on host immunity ( e . g . CMV-specific T cells commonly make up >10% of the entire pool in humans and mice ) . However , the primary sequences of many orfs have ‘drifted’ during the >10 million years of independent evolution in their hosts [42] , and it is common for immune modulatory genes encoded by primate CMVs to have no obvious sequence orthologue in their rodent counterparts . HCMV antagonizes the TRAIL/TRAIL-DR pathway through use of the UL141 glycoprotein . UL141 binds directly to human TRAIL-R2 , ‘trapping’ it in the endoplasmic reticulum , reducing its cell surface levels and desensitizing cells to TRAIL-mediated killing [26] . Detection of mouse TRAIL-DR by immunofluorescence is challenging with currently available reagents . Treatment with the proteasome inhibitor MG132 induced high cellular levels and facilitated its detection in fibroblasts , and MG132 also enhances human TRAIL-R2 expression [43] , but under these conditions no co-localization was observed with m166 ( Fig . S2 ) . Overexpression of both TRAIL-DR and m166 resulted in some ER co-localization , suggesting a potential for these two proteins to interact directly in a subcellular membrane compartment . However , we have observed no binding between purified m166:Fc and TRAIL-DR:Fc proteins ( done by ELISA , data not shown ) , suggesting that direct binding may be low affinity , or that additional protein ( s ) ‘bridge’ this interaction . Additionally , m166 shows no overt primary sequence homology to UL141 , and does not encode a readily identifiable Ig-domain like its functional HCMV counterpart [31] . Taken together , the data indicates that m166 and UL141 may use different mechanisms to restrict expression of TRAIL-DRs in their respective species , but suggests a strong evolutionary pressure for the convergent evolution of these two CMV genes targeting the TRAIL-DRs . This is the first report detailing the expression and function of the MCMV m166 protein . However , previous work has suggested that m166 was likely to be important for in vivo fitness of MCMV [44] . In that study , the MCMV Smith strain was subjected to random insertion of an ∼3 . 6 kb transposon , with subsequent screening for viruses that could replicate normally in cultured cells but showed altered in vivo virulence . Notably , the Δm166-transposon mutant was attenuated to a higher degree in the spleen than in the liver , differing from our results . This may be ascribable to the m166stop mutant having a more modest effect on expression of neighboring orfs . Additionally , the Δm166-transposon mutant was generated in the non BAC-cloned , less virulent Smith strain , which may contributes to this difference . Nevertheless , the past work validates the approach of performing random mutagenesis of the MCMV genome and screening for in vivo replication defects to identify gene ( s ) involved in subverting host immune defenses . Several MCMV gene products ( m138 , m145 , m152 and m155 ) can inhibit expression of NKG2D-activating ligands in infected cells ( e . g . RAE-1 , MULT-1 and H60 ) [39] , [45] , and MCMV mutants lacking these genes are compromised to varying degrees in BALB/c mice due to enhanced NK cell control . MCMV also encodes multiple proteins with the potential , or proven capacity , to block extrinsic apoptotic signaling pathways ( e . g . the caspase and Bak/Bax inhibitors m36 , m38 . 5 and m41/41 . 1 ) [30] , [46] . Consequently , the m166stop mutant maintains several additional , and potentially overlapping or redundant , strategies to block NK and TRAIL-dependent immune control . However , this mutant virus is dramatically attenuated in vivo , highlighting the critical importance of inhibiting TRAIL-DR expression for MCMV to thwart host defenses . This strongly suggests that TRAIL- and NKG2D-dependent NK effector functions operate in a mutually exclusive and non-redundant fashion in MCMV defense . Interestingly , immature human NK cells derived from cord blood preferentially utilize TRAIL-dependent killing mechanisms , as opposed to perforin/granzyme which require degranulation and involve NKG2D activation , supporting the notion that specific NK subsets utilize distinct effector mechanisms to kill target cells [47] . Perhaps because NKG2D ligands are expressed at very low levels in uninfected cells , while TRAIL-DR is expressed constitutively , m166 inhibition of TRAIL-DR has evolved to facilitate the very earliest phase of replication [35] , an idea supported by our data that m166stop has a lower ‘first burst’ of replication in the liver at 32 hours . Also in this vein , why is m36-mediated inhibition of caspase-8 activation , or viral inhibition of Bak/Bax , not able to compensate for the lack of m166 function ? This suggests that TRAIL-induced cell death in the context of viral infection may be more complex than currently appreciated . This complexity is also likely to vary based on the infected cell type , as in the spleen where MCMV infects marginal zone stromal cells [35] the requirement for m166 is not absolute , whereas in liver hepatocytes and/or endothelial cells it is crucial . Developing robust in vitro assays for assessing TRAIL-mediated killing by mouse NK cells has been a challenge for the field . Our preliminary studies indicate that m166stop infected L929 cells show increased caspase activation after exposure cell-expressed mTRAIL ( Fig . S7 ) . Experiments aimed at determining whether purified mouse NK cells operate in a similar TRAIL-dependent manner are currently underway . Strikingly , MCMV is able to completely neutralize NK-mediated defenses in BALB/c mice . Depleting NK cells in BALB/c infected with WT MCMV did not enhance replication in the spleen or liver , with similar results being reported by the groups of Jonjic and Vidal . This is not the case in all mouse strains , most notably in B6 mice , where the MCMV m157 protein expressed on the surface of infected cells binds the Ly49H receptor , robustly activating NK cells and restricting early MCMV replication [48] , [49] . Previous work with MCMV mutants unable to block NKG2D ligands revealed that the m157-Ly49H interaction ‘trumps’ the role of NKG2D inhibition in B6 mice , where these mutants show similar replication to WT virus if m157 expression is intact [45] . In general however , it is believed that the dramatic NK-dependent resistance mediated by m157-Ly49H in B6 mice is not representative of the situation in outbred mice or ‘wild’ strains of MCMV , where Ly49H is oftentimes not expressed or m157 has evolved not to bind this activating receptor [50] . Interestingly , MCMV Smith strain ( non BAC-cloned ) was reported to replicate to lower levels in B6 TRAIL-DR−/− mice [51] , something we did not observe in BALB/c mice with the K181 strain , suggesting that in the context of an extremely robust NK cell response differential roles for TRAIL-DR signaling may exist . This point is highlighted by recent data suggesting that other immune cell types expressing TRAIL , such as neutrophils , have potential to impact MCMV replication in B6 mice where NK responses are very robust [52] . CMV-induced soluble , innate cytokines also play a key role in NK activation ( e . g . IFN-I , IL-12 and IL-18 ) [14] . IFN-I promotes TRAIL expression and NK cell cytolytic activity in both mice and humans , while IL-12/18 induces IFNγ production . The vast majority of primary human NK cells present in peripheral blood are CD56dim and have no/low levels of TRAIL expression , but the ∼5% of CD56bright NK cells do express TRAIL constitutively [26] . These CD56bright NK are often classified as ‘immature’ , perhaps paralleling the CD11blo NK subset in mice , and are present at much higher levels in tissue compared to blood [53] . Ex vivo treatment of human blood NK cells with IFN-I induces TRAIL strongly in all subsets [26] , whereas in mice the CD11blo subset in the liver selectively induces TRAIL during MCMV infection . Whether these differences in the constitutive and inducible expression of TRAIL in various NK cell subsets are due to species or tissue specific reasons remains an open question . However , the fact that the m166stop mutant virus is markedly more sensitive to TRAIL-DR signaling in the liver where many more NK cells express TRAIL highly , strongly suggests a key role for this extrinsic death pathway in that organ . Interestingly , TRAIL expressing CD11blo immature NK cells are present at much higher levels in fetal liver [40] , and TRAIL is induced to high levels by IFN-I in HCMV infected placental cells [54] , suggesting that subversion of TRAIL-DR signaling by CMV may facilitate fetal infection . Taken together , we have shown that a viral gene product specifically inhibiting TRAIL-DR expression is critical to promote replication in vivo . Several other viruses restrict this pathway via direct or indirect targeting of receptor-ligand interactions and/or downstream signaling [1] , but to this point few of these have been tested in vivo , and none have been shown to specifically promote replication by inhibiting the TRAIL-DR . Notably , as HCMV utilizes UL141 to perform a similar function as m166 [26] , this strongly supports the notion that restricting the TRAIL/TRAIL-DR pathway is crucial for CMV replication in many hosts .
This study was carried out in strict accordance with the recommendations in the Guide for the Care and Use of Laboratory Animals of the animal Welfare Act and the National Institutes of Health . All animal protocols were approved by the Institutional Animal Care and Use Committee ( IACUC ) of the La Jolla Institute for Allergy and Immunology , San Diego ( OLAW Assurance # A3779-01 ) . NIH-3T3 ( 3T3 ) cells were from the ATCC ( CRL1658 ) and 1° mouse embryo fibroblasts ( MEF ) were isolated from day E13 . 5 C57BL/6 embryos ( used from passage 1–4 ) . MEF were cultured in Dulbecco's modified Eagles medium supplemented with 10% fetal bovine serum , Pen/Strep and L-glutamine ( GIBCO ) . 3T3 were cultured similarly , but in newborn calf serum ( Omega Scientific ) . All cell cultures were verified to be mycoplasma free . The MCMV-GFP BAC ( pSM3FR-GFP , Smith ) was provided by Dr . M . Messerle . Deletions and insertions in the MCMV-GFP BAC was performed in Escherichia coli by ET mutagenesis and characterized as described previously [32] . WT and MCMV mutants generated on Smith BAC were used for the in vitro experiments performed in figures 1 and 2 . The K181 MCMV-m166stop mutant was generated by inserting two stop codons after the 44th amino acid through ‘traceless mutagenesis’ , as described [55] . The K181 BAC derived WT and m166stop mutant MCMV were used for all in vivo experiments shown in figures 3 through 6 . Primer sequences are provided in the Table S1 . Mutant BAC-DNAs were characterized by sequencing . MCMV virus stocks were generated by electroporating BAC DNA into 3T3 cells [56] , subsequent expansion in 1° MEFs , and were quantified by standard plaque assay in 3T3 cells . BALB/c mice were purchased from The Jackson Laboratory ( Bar Harbor , ME ) and subsequently bred in house . TRAIL-DR−/− B6 mice ( provided by S . Schoenberger , LIAI , with kind permission from A . Winoto , UC Berkley ) were backcrossed on BALB/c for 9 generations in house , and subsequently bred as heterozygotes to use +/+ and −/− littermate controls for experiments ( 8–12 week old , sex matched ) . Mice were infected intraperitoneally ( i . p . ) with 1×106 pfu of MCMV , and pfu from infected organs were determined by plaque assay in 3T3 cells . Mice were bred under specific pathogen-free conditions in the Department of Laboratory Animal Care at the La Jolla Institute for Allergy and Immunology ( LIAI ) , with all experiments performed in accordance with the guidelines by the Association for assessment and Accreditation of laboratory Animal Care . Total cellular RNA was isolated at indicated time points after spin infection with TRIzol ( Roche ) followed by an RNeasy mini kit ( Qiagen , Hilden , Germany ) . To assess mRNA expression in FACS sort purified NK cells from MCMV infected mice , RNA was isolated using the RNeasy micro kit ( Qiagen , Hilden , Germany ) . Complementary DNA was generated using the iScript cDNA synthesis kit ( Bio-Rad ) and real-time qPCR was performed as described [57] . All mRNA levels were normalized to L32 mRNA , with primers: L32 ( + ) 5′-ggatctggcccttgaacctt-3′ , L32 ( − ) 5′-gaaactggcggaaaccca-3′; MCMV ie1 ( + ) 5′-agctgttggtggtgtcactcaa-3′ , MCMV ie1 ( − ) 5′-ggctgggactcatcttcttcag-3′; MCMV m166 ( + ) 5′-tgcgttgggaacaactcc-3′ , MCMV m166 ( − ) 5′-catcgtgcactgcagacat-3′; TRAIL ( + ) 5′-ctaagtactcctcccttgccca-3′ , TRAIL ( − ) 5′-tccgagtgatcccagtaatgtg-3′; CD11b ( + ) 5′-caatagccagcctcagtgc-3′ , CD11b ( − ) 5′-gagcccaggggagaagtg-3′; NKG2D ( + ) 5′-gatggctcctctctctcatacaa-3′ and NKG2D ( − ) 5′-tgagccatagacagcacagg-3′ . For RACE analysis , amplification of 5′ and 3′ ends was performed using the 5′/3′ RACE kit , 2nd generation ( Roche ) according to manufacturer's instructions . Primers: MCMV m166 5′end 5′RACEm166-2 . for ( 5′-atgggctcgggacgcggacgc-3′ ) , second amplification step cDNAm166-4 ( + ) ( 5′-gtttgctacagtctacgagcg-3′ ) . MCMV m166 3′end cDNAm166-4 ( − ) ( 5′-cgctcgtagactgtagcaaac-3′ ) . cDNAm166-4 ( + ) and ( − ) are reverse complementary , allowing for seamless alignment of sequencing products . The amplified products were purified by agarose gel and sequenced . Anti-TRAIL ( N2B2 ) and anti-CD27 ( LG-3A10 ) antibodies were purchased from Biolegend; anti CD49b ( pan NK , DX5 ) , anti-CD3ε ( 17A2 ) , anti CD11b ( M1/70 ) , anti-CD122 ( TM-b1 ) , anti TRAIL-R2 ( MD5-1 ) , and anti-IFNγ ( XMG1 . 2 ) were purchased from eBioscience . Antibodies were conjugated to Biotin , FITC , PE , APC , PECy7 , PerCP-Cy5 . 5 , Alexa Fluor 700 and eFluor 450 . To deplete NK cells , mice were injected i . p . with 50 µl of anti-asialo GM1 antibody ( Wako ) in 200 µl PBS 24 hours before infection . NK cell depletion was monitored in peripheral blood and spleen by FACS ( >97% depletion ) . For detection of cell surface TRAIL-R2 levels , 3T3 cells were seeded in 6-well dishes and next day spin-infected with MCMV ( 1500 rpm for 5 min , turn plate and repeat ) . At indicated times , cells were detached with trypsin ( verified not to alter TRAIL-R2 levels when compared to detachment with PBS/EDTA ) , washed 2× in PBS , resuspended in staining buffer ( PBS +2% FCS +0 . 05% sodium azide ) containing biotinylated anti-TRAIL-R2 antibody for 30 min on ice , washed 2× and incubated with Streptavidin-APC for 30 min ( BD Pharmingen ) before FACS analysis . For detection of surface TRAIL by liver NK cells , livers were perfused with PBS , minced between frosted ends of glass slides , washed and pelleted . Cell slurries were resuspended in 33 . 75% Percoll solution ( in 1× PBS ) and centrifuged at room temperature for 12 min ( 680 g ) to pellet the mononuclear cells , washed and counted prior to use . Cells were incubated with anti-CD122 , CD3 , DX5 , CD11b and CD27 to delineate different NK cell subsets . Liver mononuclear cells were gated for NK cells using CD122 and CD3 antibodies and further delineated into four subsets using CD27 and CD11b antibodies . TRAIL expression was detected with biotin anti-TRAIL antibody followed by streptavidin PE . Spleens were processed through a 70 µM cell strainer as described previously [35] and similarly analyzed for TRAIL expression by NK cells . Data were collected on a LSRII or FACSCalibur flow cytometer ( BD Biosciences ) and analyzed using FlowJo software ( Tree Star ) . To sort purify NK cells for mRNA analysis , liver cells from MCMV infected and naïve mice were processed and stained for surface markers as described above . The four NK subsets were sorted on FACSAria and RNA isolated from sorted cells for mRNA analysis . 3T3 cells were infected with MCMV-m166HA . To selectively analyze immediate-early protein expression , cycloheximide ( 100 µg/ml; Sigma ) was added to 3T3 cells 30 min prior to infection and was let sit on cells for up to 3 h post infection . At this time , cycloheximide media was washed away and actinomycin D ( 2 . 5 µg/ml; Sigma ) was added to cells for another 3 h . To block late protein expression , Foscarnet ( 250 µg/ml; Sigma ) was added just prior to infection and was present throughout . At 48 h after infection , cell pellets were scarped and lysed in protein sample buffer ( 3% SDS , 2% β-mercaptoethanol , 200 mM Tris [pH 8 . 8] , 0 . 5M sucrose , 5 mM EDTA ) , boiled for 5 min , separated by SDS-PAGE ( 10% gel ) and transferred to nitrocellulose filters . Filters were probed with anti-HA ( H6908; Sigma ) at 2 µg/ml followed by detection with donkey anti-rabbit HRP ( GE healthcare ) . Signals were detected with the ECL detection kit ( Amersham ) . 3T3 cells were seeded in 8 well Lab-Tek II Chambered Coverglass #1 . 5 Borosilicate Sterile ( Nalge-Nunc ) at ∼40% confluency and infected with MCMV-GFPm166HA for 6 h or 20 h . Cells were fixed in 4% paraformaldehyde/PBS for 10 min and permeabilized in PBS-0 . 2% Triton-X-100 for 5 min at room temperature . Rat anti-HA antibody ( 3F10 , 1 µg/ml , Bio-Rad ) plus anti-GM130 ( 35/GM130 , 1∶300 , BD Biosciences ) incubations in staining buffer ( 1% BSA/PBS ) were done overnight at 4°C , followed by incubation with Cy5 anti-rat IgG antibody ( 1∶300 , Jackson Labs ) plus PE anti-mouse IgG ( 1∶300 , SouthernBiotech ) for 1 h at room temperature . For HA + GRP94 co-stains , cells were incubated with mouse anti-HA antibody ( HA . 11 , 1∶500 , Covance ) plus anti-GRP94 antibody ( 9G10 , 1∶300 , Abcam ) at 4°C overnight , followed by 1 h incubation at room temperature with APC conjugated anti-mouse IgG ( 1∶300 , Jackson Labs ) plus PE anti-rat IgG ( 1∶300 , eBioscience ) . Imaging was done with a Marianas inverted microscope with SlideBook software ( Intelligent Imaging Innovations , Denver ) ( 63× magnification ) and analyzed using ImageJ software ( National Institute of Mental Health , Bethesda , MD ) . The m166-GFP expression plasmid was generated by PCR amplification of the m166 orf from the K181 genome and cloning into the CT-GFP fusion TOPO vector ( Invitrogen ) . 3T3 cells were seeded in a 24-well plate at 50 , 000 cells per well , 0 . 5 µg of m166-GFP plasmid DNA was incubated with 50 µL jetPRIME buffer ( Polyplus ) and 1 . 5 µL jetPRIME reagent for 10 minutes at room temperature before addition to the 3T3 cells in normal growth media . Seventy-two hours post transfection cells were analyzed by flow cytometry for TRAIL-R expression in GFP+ and GFP- cells as described . Statistical significance was analyzed by unpaired Student's t test . Unless otherwise indicated , data represent the mean ± SEM and * indicates p<0 . 05 and ** p<0 . 005 .
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TRAIL death receptors regulate apoptosis and inflammation , and growing evidence suggests their importance in promoting antiviral defenses . Many viruses encode strategies to modulate signaling by TNF family cytokines in order to shape host defenses . Cytomegaloviruses encode many immune modulatory genes , many of which target the TNF family , highlighting their critical role in host antiviral immunity . Here we show that the mouse cytomegalovirus ( MCMV ) m166 protein restricts cell surface expression of the TRAIL death receptor in infected cells , thus protecting them from TRAIL mediated apoptosis . An MCMV mutant lacking m166 gene expression ( MCMV-m166stop ) is severely attenuated for replication in vivo , especially in the liver , where a population of immature natural killer ( NK ) cells resides that express very high levels of TRAIL . These TRAIL-expressing NK cells are critical for antiviral defense , as their depletion restores replication of MCMV-m166stop to wildtype levels . In addition , replication of MCMV-m166stop is normal in TRAIL-DR deficient mice , definitively demonstrating the importance for m166-mediated inhibition of this TNFR in promoting viral replication and subverting host innate defenses .
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2014
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Inhibition of the TRAIL Death Receptor by CMV Reveals Its Importance in NK Cell-Mediated Antiviral Defense
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Robust oscillatory behaviors are common features of circadian and cell cycle rhythms . These cyclic processes , however , behave distinctively in terms of their periods and phases in response to external influences such as light , temperature , nutrients , etc . Nevertheless , several links have been found between these two oscillators . Cell division cycles gated by the circadian clock have been observed since the late 1950s . On the other hand , ionizing radiation ( IR ) treatments cause cells to undergo a DNA damage response , which leads to phase shifts ( mostly advances ) in circadian rhythms . Circadian gating of the cell cycle can be attributed to the cell cycle inhibitor kinase Wee1 ( which is regulated by the heterodimeric circadian clock transcription factor , BMAL1/CLK ) , and possibly in conjunction with other cell cycle components that are known to be regulated by the circadian clock ( i . e . , c-Myc and cyclin D1 ) . It has also been shown that DNA damage-induced activation of the cell cycle regulator , Chk2 , leads to phosphorylation and destruction of a circadian clock component ( i . e . , PER1 in Mus or FRQ in Neurospora crassa ) . However , the molecular mechanism underlying how DNA damage causes predominantly phase advances in the circadian clock remains unknown . In order to address this question , we employ mathematical modeling to simulate different phase response curves ( PRCs ) from either dexamethasone ( Dex ) or IR treatment experiments . Dex is known to synchronize circadian rhythms in cell culture and may generate both phase advances and delays . We observe unique phase responses with minimum delays of the circadian clock upon DNA damage when two criteria are met: ( 1 ) existence of an autocatalytic positive feedback mechanism in addition to the time-delayed negative feedback loop in the clock system and ( 2 ) Chk2-dependent phosphorylation and degradation of PERs that are not bound to BMAL1/CLK .
Circadian rhythms are periodic physiological events that recur about every 24 hours . The importance of circadian rhythms is well recognized in many different organisms' survival as well as in human physiology . Misregulations in circadian rhythms may lead to different conditions such as depression , familial advanced sleep phase syndrome ( FASPS ) , delayed sleep phase syndrome ( DSPS ) , or insomnia , which largely impact our society [1] , [2] . Recent studies indicate higher incidents of cancer in clock defective individuals [3] , [4] and chronic jet-lag is associated with higher mortality rate in aged mice as well as faster growth of tumor [5] , [6] The molecular mechanism of circadian rhythms began to become clear beginning with the discovery of the period ( per ) gene in Drosophila melanogaster in 1971 [7] , and the frequency ( frq ) gene in Neurospora crassa in 1973 [8] . Through analysis of the genetic variants of these genes , pieces of the clock's mechanism could be described . The consensus idea is that it involves interlocked feedback loops largely based on a transcription-translation related time-delayed negative feedback loop [9] . Most of the genes encoding proteins involved in the mechanism of circadian rhythms have been found simply by screens aimed at cataloging the components or by analysis of the regulation of the components . Several studies of mathematical modeling and systems approaches helped further understanding of circadian rhythms in various organisms [10]–[14] . One of the defining properties of circadian rhythms is the ability to phase shift upon a stimulus from external cues . This property allows organisms to adapt efficiently to the external environment . For example , a person traveling east to Europe from the U . S . will experience a jet-lag in the process to adapt advanced phase . Even a brief pulse of light may cause phase advances or delays depending on the timing and influence of the pulse [15] . It is intuitive to assume that a phase shifting agent will create both phase advances and delays depending on the timing and strength of the pulse by uniformly affecting molecular pathways in the circadian system [16] . It has been observed that 2 h treatments of Rat-1 fibroblasts with dexamethasone ( Dex ) result in large advances and delays ( Type 0 resetting of the phase ) , possibly by inducing transcription of both rPer1 and rPer2 [17] , [18] . This Dex-dependent PRC is also observed in the NIH3T3-Bmal1-Luc-1 cells [19] . If the Dex-dependent induction of Per transcripts causes both phase advances and delays , we would also predict that DNA damage-dependent phosphorylation and degradation of PERs by Chk2 [20] , [21] would result in similar PRCs . Recent findings indicate that this prediction is wrong [18] , [21] . Upon experiencing DNA damage , the cell cycle machinery influences the circadian clock in such a way that creates predominantly phase advances in Rat-1 fibroblasts and mice [18] , as well as in Neurospora crassa [21] . These data strongly suggest that there is a conserved pathway across different species that affects the phase of the clock after DNA damage , and involves physical interactions of ATM and/or Chk2 with a core clock component ( i . e . PER1 or FRQ ) [18] , [20] , [21] . This interaction leads to phosphorylation of PER1 and FRQ [21] , [22] . The molecular mechanism for this unique phenomenon , however , remains unexplained . In this paper , we explore the minimum criteria in the molecular network of circadian rhythms that simulate the above PRCs with tools of computational modeling . Theoretically , a time-delayed negative feedback is sufficient to create robust oscillations . Both cell cycle and circadian rhythms , however , contain both negative and positive feedbacks in their wiring networks . Positive feedback mechanisms are essential for proper eukaryotic cell divisions [23] whereas their roles in circadian rhythms remain elusive . Recently , Tsai and colleagues indicated that a general function of positive feedbacks in different networks is to create tunable robustness in the system [24] . In our study , we address two questions 1 ) what is a molecular mechanism that accounts for Chk2-dependent PRC in circadian rhythms ? , and 2 ) is the positive feedback mechanism necessary for the observed PRC ? In the conditions that we have tested , we discovered that we can only simulate the Chk2-dependent PRC with predominantly phase advances when Chk2 only affects PERs that are not bound to BMAL1/CLK in the presence of an autocatalytic positive feedback mechanism . Both conditions are required for proper simulations . Our study is the only in silico experiment to indicate the necessity of an autocatalytic positive feedback mechanism in simulating specific phenotype in the circadian system .
We explored our simple mammalian circadian clock model ( Fig . 1 ) from our previous work [25] to investigate whether we can simulate different PRCs from the Dex and IR treatment experiments [17] , [18] . Note that an autocatalytic positive feedback mechanism is already embedded in our model [12] , [26] . Based on the experimental data , we added the following in our previous model: 1 ) Dex increases the transcripts of Per but not Bmal1 [18] , and 2 ) Chk2 phosphorylates PERs and facilitates their degradation upon DNA damage [20] , [21] . Our simulations show that the Dex-dependent increase of Per messages creates both Type 0 ( as shown in the experiment , strong resetting of the phase ) and Type 1 PRCs ( weak resetting of the phase ) depending on the strength ( concentration ) of the Dex treatments ( Fig . 2A ) . It is , however , not trivial to simulate a PRC with mostly phase advances reproducing the phenotype from the IR treatment experiments [18] . We observe a PRC with large advances and delays if we follow the simplest possible assumption that DNA damage induces Chk2-dependent phosphorylation and degradation of all forms of PER ( monomer , dimer , and complex with BMAL1/CLK ) ( Fig 1 and Fig 2B ) . Through in silico experiments , however , we observe minimum phase delays as seen in experiments [18] , [21] only when Chk2 does not affect the PER that is in a complex with BMAL1/CLK ( i . e . due to conformational changes of PER upon complex formation ) ( Fig . 2B ) . In other words , Chk2 prematurely degrades PERs that are not bound to BMAL1/CLK to advance the clock , while allowing continued repression of BMAL1/CLK by not degrading the PERs that are in complex with BMAL1/CLK ( Fig . 2C ) . This prolonged repression on BMAL1/CLK creates small delays when Chk2 affects PERs around their minima as observed in experiments [18] , [21] . It is interesting to note that an inhibition of CKIε , another kinase that is known to phosphorylate PER , generates a PRC with only delays [27] . This PRC is qualitatively different than the PRC after DNA damage as there are no advances . We can simulate a mirror image of the PRC with mostly advances , which creates mostly delays , by reducing the rates for Chk2-dependent phosphorylations ( not shown ) . Our data , however , is qualitatively different as we do see small advances whereas Badura and colleagues did not observe any advances [27] . This difference are possibly due to the following reasons: 1 ) Badura et al . administered a CKIε inhibitor not as a pulse ( there was no removal of the drug after administration ) , and 2 ) it is possible that Chk2 and CKIε results in different types of phosphorylations which can lead to different consequences . We plan to further investigate this with an extended version of circadian clock module . Our simple model is adapted from Tyson and colleagues' earlier paper where both negative and positive feedbacks play essential roles in creating a robust oscillator [12] , [26] . The autocatalytic positive feedback mechanism in the model arises from different stabilities between PER monomers vs . PER complexes . Based on molecular data from Drosophila system [28]–[31] , we assume that PER monomers are more susceptible to degradation than PER in complexes ( i . e . PER/PER , PER/CRY , etc . ) . This creates autocatalytic PER dynamics as PER stabilizes itself by forming complexes . To date , this is the only circadian rhythm model that employs an essential positive feedback mechanism that is necessary to maintain a robust oscillator [32] . Hence , we wondered whether the incorporated essential positive feedback is required ( or disposable ) in simulating the unique PRCs upon DNA damage . In order to test our hypothesis , we removed the autocatalysis in the model by assuming no stability differences between PER monomers and complexes . Then , we re-parameterized the system to rescue oscillations ( see materials and methods ) . Note that we had to use a Hill-coefficient = 4 for highly cooperative negative feedback in order to rescue oscillations in our four-variable model in the absence of the autocatalytic positive feedback mechanism . To our surprise , we were not able to generate the unique PRC with predominantly phase advances upon DNA damage even by assuming differential phosphorylation and degradation of PER monomers vs . PER complexes with BMAL1/CLK ( lane 2 , Table 1 ) . We wondered whether above conclusions from our simple model can be generalized to a more comprehensive model with distinct wiring network . Hence , we tested Leloup and Goldbeter's mammalian model [33] , [34] . They used four sets of parameters in order to investigate possible functions of multiple feedback loops in the circadian system . For our purposes , we concentrated in parameter sets 1 and 3 . In the parameter set 1 , robust oscillations of their model can arise from two different time-delayed negative feedback loops: PER-driven and PER/CRY-independent BMAL1/CLK-driven negative feedback loops . For this parameter set , they can generate an oscillator based on BMAL1/CLK-driven negative feedback loop in the absence of the PER-driven negative feedback loop . In the parameter set 3 , they disabled the BMAL1/CLK-driven negative feedback loop making the system a PER/CRY-dependent single negative feedback oscillator . We did not explore parameter sets 2 and 4 because PER is not required for oscillations in parameter sets 2 and 4 . The wiring network of Leloup and Goldbeter's model is significantly different from our model which consists of an intertwined dynamics between an essential autocatalytic positive feedback and time-delayed negative feedback [12] , [32] . We incorporated Chk2-induced degradation of PER molecules that are not bound to BMAL1/CLK in the Leloup and Goldbeter's model . Then , we tested Chk-2-dependent differential degradation of PER as in our simple model . Our simulations indicate that we see both TYPE 1 and TYPE 0 PRC depending on the strength of Chk2 , but we do not observe asymmetric PRCs with mostly advances ( lane 3 and 4 , Table 1 ) . These results show that the differential effect of Chk2-dependent degradation of PER complexes is not enough to create the observed DNA-damage induced PRCs with the innate wiring of the Leloup and Goldbeter's model . Our next step was to introduce an autocatalytic positive feedback mechanism in the Leloup and Goldbeter's model and investigate its role in reproducing the asymmetric PRC upon DNA-damage . First , we added an autocatalytic positive feedback in the parameter set 1 of Leloup and Goldbeter's model in a similar way as in our simple model . PER complexes are assumed to be more stable than PER monomers . To our surprise , we were not able to generate the PRCs with predominantly phase advances with differential degradations of PER complexes by Chk2 even with an added autocatalytic positive feedback mechanism ( lane 5 , Table 1 ) . We wondered whether this was due to the PER-independent BMAL1/CLK-driven negative feedback loop which is built in the parameter set 1 . Hence , we tested the parameter set 3 which consists of the PER-driven single negative feedback . Interestingly , we were able to simulate the observed asymmetric PRC with predominantly phase advances as we have observed in our simple model only when both the autocatalytic positive feedback and the differential effect of Chk2 on PERs were implemented in the absence of BMAL1/CLK-driven negative feedback loop ( lane 6 , Table 1 ) . This suggests that there exists an important dynamical relationship between negative feedback loops and an autocatalytic positive feedback mechanism .
What are the implications of DNA damage-induced phase responses of the circadian clock to the cell cycle ? We hypothesize that cells utilize various pathways for different timing events in response to DNA damage . The Chk2 kinase directly inhibits the progress of the cell cycle by phosphorylating and removing Cdc25C ( a phosphatase that is antagonistic to Wee1 which activates cell proliferation ) from the nucleus [35] . Moreover , the cell cycle machinery also employs Chk2 in order to provide an additional mechanism that helps to delay the cell cycle progress for extended time by indirectly increasing the level of Wee1 via the circadian network . We believe that the above sequential roles of Chk2 maximize the efficiency of DNA damage-induced delay . With our model , we show that premature degradation of PER , resulting in phase advances , causes early activation of BMAL1 ( Fig 2C ) . This creates an early transcriptional activation of the Wee1 ( G2 inhibitor of the cell cycle ) during the upcoming circadian cycle , which delays the cell cycle in the G2 phase . If the DNA damage-response induces large phase delays , it will generate a short-lived , transient increase of BMAL1 , but a long delay in the activation of Wee1 by BMAL1/CLK for the upcoming circadian cycle . This late activation of Wee1 is probably not a desired result for an efficient DNA damage response . Our model is simple and intuitive , and yet predicts a molecular mechanism that is responsible for the observed PRC . Our in silico experiments elucidate a molecular mechanism that accounts for Chk2-dependent phase advances and minimum delays of the circadian clock upon DNA damage . It seems counterintuitive to assume that Chk2 does not affect the PER that is in a complex with BMAL1/CLK . This may appear to prolong the repression on BMAL1 , which will delay the activation of Wee1 . However , due to the cyclic nature of the circadian clock , our simulations suggest that these unique Chk2-dependent phase responses are the best strategy for inducing large and prolonged induction of Wee1 by BMAL1/CLK , allowing extended time for the cell cycle to repair problems upon DNA damage . We propose that the cell cycle network is ingeniously wired with the circadian clock for an optimal response upon DNA damage . Previously , experimentalists showed that the functional circadian clock is important for optimum response to the chemotherapeutic agent cyclophosphamide or γ radiation [4] , [36] . For example , reduced apoptosis is observed in mPer2 deficient mice compared to wild-type mice upon γ radiation , which resulted in tumorigenesis [4] . Based on these works , it can be assumed that DNA damage response is more efficient when the circadian clock is intact . We do not know , however , how the efficiency of DNA damage response is affected by the circadian clock . Hence , we suggest testing the efficiency of DNA damage response in the presence and absence of the circadian clock in both in cell culture ( i . e . wild-type vs . cryko ) as well as in vivo . Another intriguing finding is the importance of the autocatalytic positive feedback mechanism in simulating the observed PRC upon DNA damage . Our simple model is adapted from Tyson and colleagues which implemented both negative and positive feedback mechanisms [12] , [32] . DNA damage-induced PRCs with predominantly advances are lost upon removal of the positive feedback even with the differential degradation of PERs by Chk2 . This observation is extended to the Leloup and Goldbeter's model [33] , [34] . We tested four different combinations of positive and negative feedback loops with two different sets of parameters ( Table 1 ) . Our findings confirm that the autocatalytic positive feedback mechanism is required to simulate DNA damage-induced PRCs . Our results elucidate three important points: ( 1 ) the role of the autocatalytic positive mechanism in the circadian system , ( 2 ) the wiring of different negative feedback loops , and ( 3 ) the interplay between positive and negative feedbacks in response to DNA damage . We acknowledge that there are multiple feedback loops in the circadian system [9] . Therefore , it is essential to develop a more comprehensive model accounting detailed dynamics of different negative feedback loops in the clock network . Furthermore , it is important to experimentally verify autocatalytic positive feedback mechanisms in the context of circadian rhythms , the nonlinearity of negative feedback loops , and the possible interplay between the positive and negative feedback loops in the circadian clock .
Our objective is to create a simple mammalian circadian clock model that accounts for different phase response curves ( PRCs ) observed from various experiments [17] , [18] , [21] . For simplicity of the model , we only deal with PER protein and treat PER1 , PER2 , and PER3 as same proteins . CRY proteins ( CRY1 and CRY2 ) are also part of core clock components that negatively regulate BMAL1/CLK . We do not consider , however , CRY proteins in this model for two reasons: ( 1 ) simplicity of the model , and ( 2 ) it is not yet known whether Chk2 phosphorylates and triggers degradation of CRY proteins as mPER1 . We will include the function of CRY proteins in our future work . We assume that PERs exist in monomers ( Clock Protein , CP ) , dimers ( Clock Protein , CP2 ) , and complex with the BMAL1/CLK ( Transcription Factor , TF ) . We imagine that the BMAL1/CLK is inactive when bound to PER ( Inactive Complex , IC ) creating a negative feedback . We treat CLK as a parameter in the system since it does not cycle [37] . We also assume that the CP2 is more stable than the CP , which introduces a positive feedback in the system [12] . Dex induces the transcription of Per message ( Message , M ) [18] , and DNA damage-activated Chk2 promotes phosphorylation and degradation of PERs [20] , [21] . We use same equations and parameter values from our previous publication [25] other than the newly added effects of Dex or Chk2 . Messenger RNA of the clock proteins ( Per mRNA ) : ( 1 ) Monomer clock proteins ( PER ) : ( 2 ) Dimer form of clock proteins ( PER/PER ) : ( 3 ) Transcription factor ( BMAL1/CLK ) : ( 4 ) Inactive complex of clock dimers and transcription factor: ( 5 ) Total amount of clock proteins ( PER on Fig . 2 ) : ( 6 ) Rate constants ( h−1 ) :Dimensionless constants: All protein concentrations in the model are expressed in arbitrary units ( au ) because , for the most part , we do not know the actual concentrations of most circadian proteins in the cell . All rate constants capture only the timescales of processes ( rate constant units are in h−1 ) . Various parameters of the model of Zámborszky et al . [25] have been changed in order to remove the originally existing positive feedback from the system . The equations are the same as presented above . Many parameters were changed to create a robust circadian rhythm with approx 24 h period . Changed parameters: Rate constants ( h-1 ) : kms = 0 . 5 , kmd = 0 . 045 , kcps = 10 , kcpd = 0 . 0001 , ka = 100 , kd = 0 . 001 , kcp2d = 0 . 0001 , kicd = 0 . 001 , kica = 4 , kp1 = 1 . 97 , kp2 = 1 . 97 . Dimensionless constants: TFtot = 1 , Jp = 0 . 05 , J = 0 . 4 , n = 4 . The Chk2 induces degradation of PER monomers and PER-CRY dimers but not PER proteins that are in complex with BMAL1/CLK . To achieve this we replaced the original Vphos term by ( Vphos+VChk2 ) in the original Leloup and Goldbeter models [33] , [34] . In simulations we used VChk2 = 1 to simulate the effect of IR pulse treatment . We increased the nonspecific degradation rate constant for destruction of nonphosphorylated PER monomers in the cytosol from 0 . 01 to 0 . 3 , while keeping the background degradation rates of PER/PER dimers and PER/CRY complexes at the original 0 . 01 level . In this way PER has a positive influence on itself by forming complexes . This creates a similar autocatalytic positive feedback mechanism as the one we used in Zámborszky et al . [25] . We used XPP-AUT computer program [38] of G . Bard Ermentrout ( freely available at http://www . math . pitt . edu/~bard/xpp/xpp . html ) for simulations and analysis of our model . The ODE file of our model is available as online supplementary material of this article ( see Text S1 ) . The SBML version of the model is also downloadable from the BioModels Database ( http://www . ebi . ac . uk/biomodels-main/ ) [39] , as MODEL7984093336 . For each simulation , we calculated the phase differences between unperturbed and perturbed systems after 10 days ( 10 circadian cycles ) . Treatments were induced at each circadian hour .
|
Molecular components and mechanisms that connect cell cycle and circadian rhythms are important for the well-being of an organism . Cell cycle machinery regulates the progress of cell growth and division while the circadian rhythm network generates an ∼24 h time-keeping mechanism that regulates the daily processes of an organism ( i . e . metabolism , bowel movements , body temperature , etc . ) . It is observed that cell divisions usually occur during a certain time window of a day , which indicated that there are circadian-gated cell divisions . Moreover , it's been shown that mice are more prone to develop cancer when certain clock genes are mutated resulting in an arrhythmic clock . Recently , a cell cycle checkpoint regulator , Chk2 , was identified as a component that influences a core clock component and creates mostly phase advances ( i . e . , jet lags due to traveling east ) in circadian rhythms upon DNA damage . This phase response with minimum delays is an unexpected result , and the molecular mechanism behind this phenomenon remains unknown . Our computational analyses of a mathematical model reveal two molecular criteria that account for the experimentally observed phase responses of the circadian clock upon DNA damage . These results demonstrate how circadian clock regulation by cell cycle checkpoint controllers provides another layer of complexity for efficient DNA damage responses .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"cell",
"biology/cell",
"signaling",
"cell",
"biology/cell",
"growth",
"and",
"division",
"computational",
"biology/signaling",
"networks",
"computational",
"biology/systems",
"biology",
"molecular",
"biology/dna",
"repair"
] |
2009
|
Minimum Criteria for DNA Damage-Induced Phase Advances in Circadian Rhythms
|
The phenomenon of antibody dependent enhancement as a major determinant that exacerbates disease severity in DENV infections is well accepted . While the detailed mechanism of antibody enhanced disease severity is unclear , evidence suggests that it is associated with both increased DENV infectivity and suppression of the type I IFN and pro-inflammatory cytokine responses . Therefore , it is imperative for us to understand the intracellular mechanisms altered during ADE infection to decipher the mechanism of severe pathogenesis . In this present work , qRT-PCR , immunoblotting and gene array analysis were conducted to determine whether DENV-antibody complex infection exerts a suppressive effect on the expression and/or function of the pathogen recognition patterns , focusing on the TLR-signaling pathway . We show here that FcγRI and FcγRIIa synergistically facilitated entry of DENV-antibody complexes into monocytic THP-1 cells . Ligation between DENV-antibody complexes and FcR not only down regulated TLRs gene expression but also up regulated SARM , TANK , and negative regulators of the NF-κB pathway , resulting in suppression of innate responses but increased viral production . These results were confirmed by blocking with anti-FcγRI or anti-FcγRIIa antibodies which reduced viral production , up-regulated IFN-β synthesis , and increased gene expression in the TLR-dependent signaling pathway . The negative impact of DENV-ADE infection on the TLR-dependent pathway was strongly supported by gene array screening which revealed that both MyD88-dependent and –independent signaling molecules were down regulated during DENV-ADE infection . Importantly , the same phenomenon was seen in PBMC of secondary DHF/DSS patients but not in PBMC of DF patients . Our present work demonstrates the mechanism by which DENV uses pre-existing immune mediators to defeat the principal activating pathway of innate defense resulting in suppression of an array of innate immune responses . Interestingly , this phenomenon specifically occurred during the severe form of DENV infection but not in the mild form of disease .
Dengue is the most prevalent vector-borne disease occurring in tropical and subtropical regions with an estimated 50 to 100 million people infected each year . This includes 500 , 000 cases of life-threatening disease which are dengue hemorrhagic fever ( DHF ) and dengue shock syndrome ( DSS ) [1] , [2] . Dengue viruses , members of family Flaviviridae , are a group of four genetically distinct serotypes known as DEN-1 to -4 . The genome of these viruses is a single-stranded positive sense RNA which is approximately 11 kb in length and encodes for three structural ( C , prM , E ) and seven non-structural ( NS1 , NS2A , NS2B , NS3 , NS4A , NS4B , NS5 ) proteins [3] . Infection with dengue virus ( DENV ) causes two clinically distinct syndromes which are dengue fever , a mild form of the disease and DHF/DSS , a life-threatening disease . The pathophysiology of DHF/DSS development is of interest among researchers since the incidence of DHF/DSS is 25–80 times higher in people previously exposed to DENV than in DENV-naïve individuals , indicating the significance of pre-existing immune mediators such as aberrant T cells , cytokine storms and the enhancing activity of the subneutralizing antibodies [4] , [5] , [6] . Among these mediators , the presence of enhancing antibodies stand out the most because it is the only risk factor that can explain DHF/DSS development in primary infected infants due to the finding that the peak incidence of DHF/DSS development in infected infants correlates with the decline of maternally derived protective antibodies to non-protective or subneutralizing levels . Moreover , these infants do not experience DHF/DSS accompanying a primary dengue virus infection after the maternally derived antibodies have completely disappeared [7] , [8] , [9] , [10] . This epidemiological data is supported by in vitro enhancement infection experiments in which neat plasma from healthy infants born to dengue-immune mothers enhances dengue virus infection in a manner that correlates with the age-related DHF/DSS development in infants [11] , [12] . To further support the role of subneutralizing antibodies , investigators have been able to mimic this phenomenon in a mouse model and in rhesus monkeys [13] , [14] . The role of enhancing antibodies in exacerbating disease severity has been reported in other types of infection . For example , Leishmania is known to exploit host IgGs facilitating the entry of Leishmania amastigotes into macrophages . The entry of amastigotes-antibody complexes via Fcγ receptor ligation does not only allow the numerous parasites to penetrate into macrophages but also suppress the development of cell-mediated immunity resulting in progressive non-healing leishmaniasis in mice [15] , [16] . The mechanism by which enhancing antibodies exacerbate dengue disease severity has not been fully established . However , severe dengue is associated with high levels of circulating DENV , and enhancing antibodies have been proposed to facilitate DENV production by at least two mechanisms . Firstly , enhancing antibodies function as a bridge between infectious DENV particles and FcR on cell surfaces resulting in an increased number of infected cells [17] , [18] . Interestingly , Rodenhuis-Zybert et al . recently demonstrated that enhancing antibodies not only promote entry of the mature DENV but also assists entry of non-infectious virions or immature DENV particles into FcγR bearing cells [19] . Once inside the target cells , these immature viruses replicate effectively . This phenomenon , if occurring in natural dengue virus infections , could significantly contribute to disease severity . The second mechanism proposed is one in which infection via Fc and FcR ligation switches the intracellular response from an antiviral mode into an immune suppressive mode [20] . This suppression mediates the severity of the secondary dengue virus infection . Thus , to gain more information on the intrinsic role of enhancing antibodies , we further investigated the mechanism of immune evasion induced by DENV-ADE infection . Once attacked by viruses , host cells immediately recognize the invaders using several types of sensing systems [21] . One of these systems is the Toll-like receptors or TLRs pathway , and six TLRs have been reported to recognize viral invaders . For example , the extracellular TLR-2 and TLR-4 detect viral particles/viral proteins on the cell surface , while the endosomal TLRs recognize viral nucleic acid components such as dsRNA , ssRNA and unmethylated DNA with a CpG motif [22] . Upon ligation to the invader , TLRs trigger a signaling cascade through the recruitment of a set of TIR-domain-containing adaptors including MyD88 , TIRAP ( MAL ) , TRIF ( TICAM ) and TRAM ( TICAM2 ) . Based on the MyD88 molecule , the TLR signaling cascade can be divided into two principle pathways , the MyD88-dependent and MyD88-independent ( or TRIF-dependent pathway ) signaling pathways . While most TLRs trigger the MyD88-dependent signaling pathway via the TIR-containing cytosolic adaptor MyD88 , TLR-3 and TLR-4 initiate their signals through TRIF activation [23] . Both MyD88-dependent and TRIF-dependent signaling pathways can activate type I IFN and inflammatory cytokines via NF-κB and the IRFs family [24] , [25] . Activation of the TLRs signaling pathway in response to viral infection has been intensively studied [26] , [27] , [28] , [29] . For example , the response against hepatitis C virus infection is mediated by the TLR2 and TLR3 signaling [30] , [31] , while West Nile Virus ( WNV ) can be recognized by TLR-3 , eliciting an antiviral response shaping innate as well as adaptive immunity in in vivo experiments [32] , [33] . TLR-3 and TLR-7 have been reported to play important roles in inhibiting dengue virus infection in U937 and HEK293 cells , respectively [34] , [35] . The present study investigated the effect of DENV-antibody complex infection on TLR-dependent signaling in a monocytic cell line . The experiments were conducted in vitro and ex vivo , meaning that infected THP-1 cells and PBMCs from infected patients were used , respectively . This is the first study to show the negative effect of enhancing antibodies on the expression and function of the antigen recognition pathway in human monocytic cells . Results showed that preexisting subneutralizing antibodies were able to ligate infectious DENV particles to both FcγRI and FcγRIIa . Upon ligation , activation of TLR-negative regulators and down-regulation of membrane as well as cytoplasmic TLRs was pronounced , resulting in suppression of TLR-dependent immune activation . These results were also found in secondary DHF PMBC but not in secondary infection DF PBMC .
The protocol for patient enrollment and sample collection is approved by The Committee on Human Rights Related to Human Experimentation , Mahidol University , Bangkok , Thailand . Dengue-infected patients , which hospitalized at Queen Sirikit National Institute of Child Health , Bangkok , Thailand , were enrolled to the study after the parents/guardians have giving written informed consent . All clinical investigation must have been conducted according to the principles expressed in the Declaration of Helsinki . The enrolled patients were 5–10 years of age . Blood samples were obtained twice , once on the day of admission ( fever day ) and the other on 30 days after admission ( convalescence day ) . Plasma and PBMCs were separated immediately and were kept frozen at −80°C until required . The patient's disease severity was graded as DF or DHF according to WHO criteria . All enrolled cases were classified as secondary infection by haemagglutination inhibition ( HI ) titre and IgM ELISA assay [36] . Convalescent serum from a patient infected with DENV serotype 3 ( DENV-3 ) at a 1∶ 10 , 000 dilution was used in all DENV-ADE infection experiments [38] . Antibody-dependent enhanced infection of DENV-2 16681 into THP-1 cells was conducted as described [38] . Briefly , THP-1 cells were infected with a complex between DENV-2 16681 and the enhancing antibodies at the MOI of 0 . 01 pfu/cell . After an hour of incubation at 37°C , cells were washed and were further cultured in growth medium . The infected cells and supernatants were harvested at 3 , 6 , 12 , 18 , 24 hours and every 24 h for 3 consecutive days . In this experiment , sets of control were performed which were THP-1 cultures infected with DENV at the MOI of 5 . 0 and 10 . 0 pfu/cell , THP-1 cells infected with UV-treated-DENV-Ab complexes and the mock-infected THP-1 cells . THP-1 cells were pre-incubated at 37°C for 90 minutes with either an anti-human FcγRI MAb or an anti-human FcγRIIa MAb ( R&D System , Inc . , Minneaspolis , MN ) or both antibodies , at a concentration of 5 µg/ml of each antibody . After incubation , cells were washed with IMDM before being infected with DENV or DENV-antibody complexes . RNA was extracted from supernatants using TRIZOL ( Invitrogen , CA , USA ) . The purified viral RNA was then monitored by real time RT-PCR using QuantiTect Probe RT-PCR ( Qiagen , Germany ) as described by Houng et al [39] . Real time RT-PCR amplification , data collection and analysis were performed using a Roter-Gene™ 3000 ( Corbett Research , Sydney , Australia ) . The RNA copy number was calculated using dengue serotype-specific copy standards . Total RNA was extracted from infected cells using the QIAgen RNAeasy Kit ( QIAgen , Germany ) . Biotin-UTP labeled cRNA probes were synthesized using 3 µg of cDNA amplified from the total RNA template ( Superarray Inc . , Frederrick , MD , USA ) . The labeled cRNA ( 6 µg ) from each sample was then incubated with Oligo GEArray Human Toll-Like Receptor Signaling pathway ( OHS-018 . 2 ) membranes containing 113 TLR-related genes . The hybridized membranes were washed and hybridization signals were detected using a chemiluminescent system according to the manufacturer's instruction . The intensity of hybridization was determined by ImageMaster TotalLab version 2 . 00 ( Amersham Pharmacia , England ) and was acquired in TIFF format . The digital TIFF image files were then analyzed by ClonTech AtlasImage software , version 2 . 7 ( CloneTech , CA , USA ) . The background was automatically subtracted and standardization of all the signals was performed by normalizing the raw data with β2-microglobulin ( β2-m ) and Glyceraldehyde 3-phosphate dehydrogenase ( GADPH ) . The correlation between two data sets was tested using Pearson's correlation with P-value<0 . 05 . Two-fold and 0 . 5 fold difference in expression between normalized gene intensities compared between control , DENV , and DENV-ADE samples were considered as significant up-regulation and down-regulation , respectively . The qRT-PCR was used to investigate levels of gene expression . In brief , RNA was extracted from harvested cells using the QIAgen RNAeasy Kit ( QIAgen , Germany ) and then subjected to first-strand cDNA synthesis before amplification by qRT-PCR using specific primers . The primer sets for TLR-3 , TLR-4 , TLR-7 , TRIF , TRAF-6 , TRAM , IRAK-4 , and ACTIN are : TLR-3: forward , 5′-AGG AAC TCC TTT GCC TTG GT-3′ ; reverse , 5′ – TTT CCA GAG CCG TGC TAA GT- 3′; TLR-4: forward , 5′ –TGG ATA CGT TTC CTT ATA AG- 3′ ; reverse , 5′ –CAA GTA CAA GCA AAG TCA TTC- 3′ ; TLR-7: forward , 5′ –CCT GGA AAC TTT GGA CCT CA- 3′ ; reverse , 5′-CCA CCA GAC AAA CCA CAC AG- 3′ ; TRIF: forward , 5′ – CCC TGT GGA CAG TGG AAG AT- 3′ ; reverse , 5′ –CAA GAC CCT TCA CCC AGA AA- 3′; TRAF-6: forward , 5′-GTT GCT GAA ATC GAA GCA CA- 3′; reverse , 5′ –CGG GTT TGC CAG TGT AGA AT- 3′ ; TRAM: forward , 5′ – GGG TGA TGT TCG TGT CTG TG- 3′ ; reverse , 5′ –ACT GAG GCG CTG AGG TAA AA- 3′ ; IRAK-4: forward , 5′ –CCT TTG CCT TCC ATT GTG AT- 3′ ; reverse , 5′ –GTT TTG GCT TAC GGT TCT GC- 3′; SARM: forward , 5′ –TTG CCA AGC AGC AAT GTT AG- 3′ ; reverse , 5′ –TCT CCT CCC AAC CAG AAA TG- 3′; TANK: forward , 5′ –CAG GCA TGC ATG GAT AGA GA- 3′ ; reverse , 5′ –TTC AAG CAG AGG AAC ACA GC- 3′; Beta-actin: forward , 5′- CCT GGC ACC CAG CAC AAT-3′ ; reverse , 5′GGG CCG GAC TCG TCA TAC- 3′ The qRT-PCR was carried out using the SYBR system ( Invitrogen , Oregon , USA ) , using actin as a control . Levels of SARM , TRAF6 , IRAK4 , TLR7 , IKK-α , and Rel-A protein production were semi-quantitated using immunoblotting . The intensity of each specific protein was detected using monoclonal antibodies as previously described [38] . Level of IFN-β production was quantitated using a PBL Medical Laboratories Kit ( Piscataway , New Jersey , USA ) according to the manufacturer's protocol . Values were expressed as mean ± standard deviation ( SD ) of at least three independent observations . Statistical significance was tested by Student's t-test , One-way ANOVA , as indicated in the legend of figure . P-values<0 . 05 were considered significant .
Two types of FcR , FcγRI ( CD64 ) and FcγRIIa ( CD32 ) , have been reported by several investigators to participate in the entry of DENV-antibody complexes in in vitro systems [17] , [40] , [41] , [42] . In the present study , the synergistic role of FcγRI and FcγRIIa in DENV-ADE infection in THP-1 cells was investigated . THP-1 cells were pretreated with either anti-FcγRI or anti-FcγRIIa antibodies or both before being infected with either DENV or DENV- enhancing antibody complexes . The level of viral production was monitored by assaying RNA copy number and the number of infectious virions using real-time RT-PCR and plaque assay , respectively . As demonstrated in Fig . 1a–b , blocking of FcγRI or FcγRIIa significantly suppressed viral production in DENV-ADE infection of THP-1 cells . The largest reduction in viral production was found in cells pre-treated with both anti-FcγRI and anti-FcγRIIa antibodies , suggesting that FcγRI and FcγRIIa synergistically mediate the entry of DENV-enhancing antibody complexes into THP-1 cells . Our previous report demonstrated that DENV-ADE infection significantly suppresses IFN-β production in THP-1 cells ( 20 ) . Therefore , the level of IFN-β production was used as a marker to test the synergistic role of FcγRI and FcγRIIa on DENV-ADE infection . THP-1 cells were pretreated with anti-FcγRI and anti-FcγRIIa before being infected with DENV-enhancing antibody complexes , and the production of IFN-β was assayed at 24 hr of infection using ELISA . As shown in Fig . 1c , blocking of ADE-infection via FcγRI and FcγRIIa completely restored IFN-β production . Taken together , these results show that DENV-enhancing antibody complexes use both FcγRI and FcγRIIa for entry . We previously reported that one of the intrinsic roles of ADE-infection is suppression of type I interferon via the RIG-I/MDA-5 signaling pathway [20] . Since type I interferon production is also activated via the TLR pathogen recognition pathway [43] , we therefore investigated whether DENV-ADE infection has any effect on TLR expression and/or the TLR-dependent signaling pathway . To answer this question , THP-1 cells were infected with either DENV alone or infected with DENV- enhancing antibody complexes . The expression of a surface membrane TLR ( TLR-4 ) , endosomal TLRs ( TLR-3 , TLR-7 ) and TLR-signaling molecules ( TRIF , TRAF-6 and IRAK4 ) were monitored using qRT-PCR and immunoblotting . As illustrated in Fig . 2 , THP-1 cells infected with DENV-2 significantly stimulated TLR-3 , TLR-4 , TLR-7 , TRIF and TRAF-6 expression . This data correlated with the level of IFN-β production as shown in Fig . 1c . In contrast , DENV- enhancing antibody complex infection significantly suppressed TLR and TLR-signaling molecules in comparison to infection by DENV alone . This data is supported by anti-FcγRI and anti-FcγRIIa treatment in which blocking of DENV-ADE infection via these two receptors restored the expression of TLR ( s ) and TLR-signaling molecules . This data is also supported by the increased IFN-β production as shown in Fig . 1c . Collectively , DENV-ADE infection could interfere with TLR-dependent signaling via FcγRI and FcγRIIa ligation which corresponded to the reduction of IFN-β production . In addition , pre-treatment with anti-FcγRIIa antibodies restored a higher level of TLRs and TLR-signaling molecules than pretreatment with FcγRI ( Fig . 2 ) . To ensure that phenomenon found in this study is not due to the effect of higher level of viruses produced during ADE-infection mode , control experiments were preformed . THP-1 cultures were infected with DENV at the MOI of 5 . 0 and 10 . 0 pfu/cell , or with UV-treated-DENV-enhancing Ab complexes , or were mock infected . THP-1 cultures infected with the MOI of 10 . 0 replicated DENV to the same level as ADE-infected mode . In contrast , infection by higher MOI of DENV activates stronger TLR-3 and -4 expressions ( Figure S1 ) . THP-1 cells infected with UV-DENV-Ab complexes revealed no suppressive effect on IFN-β production ( data not shown ) . Taken together , this information indicated that suppression of TLRs and TLR signaling pathway demonstrated in our study is due to the infectious immune complexes infection . Suppression of the TLR-dependent signaling pathway may due to down-regulation of TLR synthesis and/or blocking of TLR-signals . Unfortunately , negative regulators of TLR synthesis have not yet been identified . Thus we investigated whether or not down-regulation of the TLR-dependent signaling pathway is due to DENV-ADE infection activating negative regulators of TLRs signaling such as SARM and TANK and so the levels of SARM and TANK gene expression were investigated . As shown in Fig . 3 , expression levels of SARM and TANK were significantly increased at 3 hr post DENV-ADE infection , but not in DENV infection . Since THP-1 is a monocytic cell line it may not be an ideal physiological model of the natural response during DENV infection . Therefore , to confirm the phenomenon found in THP-1 cells , expression levels of TLR-3 , TLR-4 , TLR-7 and TRAF-6 in PBMCs obtained from secondary DF and secondary DHF patients , on fever and convalescent days were determined by qRT-PCR . Interestingly , expression of these genes was significantly down-regulated in secondary DHF patients but not in DF patients ( Fig . 4 ) , suggesting that the TLR-dependent signaling pathway is activated during the mild form of DENV-infection but not in the severe form of the infection . To further elucidate the impact of ADE-infection on TLR-dependent signaling , a TLR-specific oligonucleotide array analysis was conducted to differentiate responses between DENV infection and infection by DENV-enhancing antibody complexes . As shown in Table 1 , the expression of 27 out of 113 TLR-related genes was significantly altered during DENV-ADE infection . These genes were categorized on the basis of their functions as TLR , TIR containing adaptor molecules , effector molecules , NF-κB associated molecules , JNK/p38 pathway , IRF pathway , IFN-inducible genes and others . Among these 27 genes , 21 and 6 genes were down- and up-regulated during DENV-ADE infection , respectively . Most of the down-regulated genes are associated with both the MyD88-dependent and -independent signaling pathways such as TLR-4 , TIRAP , IRAK-2 , IRAK-4 , TRIF ( TICAM1 ) and TRAM ( TICAM2 ) . This data indicates that both MyD88-dependent and -independent pathways were suppressed . The expression of TLR-3 and -7 were not included in this table since their expression were suppression less than two folds , 1 . 7 and 1 . 6 folds , respectively . Expression of the other types of TLR was undetectable in our array analysis . The suppressive effect was also strongly seen in the NF-κB signaling pathway , in which genes required for IκB degradation and NF-κB activation such as MAP3K7IP1 ( TAB1 ) , MAP3K7IP2 ( TAB2 ) , TRAF-6 , UBE2N and MAP3K7 were down-regulated . This observation was confirmed by the reduction of NF-κB signaling molecules including the REL complex , NF-κB2 , CHUK ( IKK-α ) and MAP4K4 while NF-κBIE , an inhibitor of NF-κB , was up-regulated . In addition , suppression of the IRF pathway and IFN-inducible genes was also pronounced during ADE-infection . In addition , the expression of SARM gene was 1 . 5 folds increased while the activation of TANK gene was undetectable during ADE-infection . Taken together , these data imply that DENV-ADE infection may activate host negative regulators which in turn down regulate the MyD88-dependent , MyD88–independent and NF-κB signaling pathway , supporting the in vitro and ex vivo experiments described above . To validate data obtained from the oligonucleotide array analysis , qRT-PCR was used to monitor the expression of 3 genes including of TICAM2 , TIRAP and IRAK-4 at 3 , 6 , 12 , 18 , 24 hours post inoculation . The observed copy numbers of these representative genes are shown in Fig . 5a–c . The levels of expression of these genes were significantly down-regulated in THP-1 cells infected with DENV-ADE infection meaning that data from qRT-PCR confirmed the cDNA analysis . In addition , the protein levels of IKK-α and Rel-A were determined using specific monoclonal antibodies . As shown in fig 5 d–e , degradation of phosphorylated IKK-α and suppression of Rel-A production was significant in DENV-ADE infection mode suggesting that immune complexes infection suppesses NF-κB pathway .
Even though the presence of antibodies that enhance dengue viral infectivity has been known since 1977 [44] , the mechanism ( s ) as to how these antibodies increases viral infectivity and exacerbate disease severity is only just being understood . Our reports and others show that enhancing antibodies is not only facilitating virus entry , but also alter the intracellular responses and that the synergism between the extrinsic and the intrinsic roles of enhancing antibodies significantly increases viral burst size and the total virus yield . The first mechanism by which antibodies enhance DENV infectivity occurs at the plasma membrane . In this process , enhancing antibodies facilitate the interaction between virus particles and the FcR on target cells . This event gives rise to a higher chance of virus penetration resulting in a greater number of infected cells . The significance of Fc and FcR ligation on ADE-infection has been confirmed using genetically engineered antibody variants which can not bind to FcR [45] . These engineered antibodies abrogate ADE-infection and protect mice from ADE-induced lethal challenge . The types of FcR involved in DENV-antibody complex infection have been investigated intensively by several groups of investigators as well as by our group and all agree that both FcγRI and FcγRIIa facilitate ADE-infection in natural DENV target cells and in DENV susceptible cell lines [12] , [16] , [20] , [41] . Moreover , we observed that FcγRIIa enhanced the infectivity in THP-1 cells more efficiently than FcγRI did ( Fig 1a and Fig . 2 ) . Our finding is supported by the previous report using FcγR transfected COS-7 cells in which FcγRIIa enhances dengue virus immune complex infectivity more efficient than FcγRI . This difference may due to mode of virus-immune complex internalization mediated by these two types of FcR [42] . In the other experimental system , engatement of immune-complexes to FcγRI signals through γ-chain to initiate proinflammatory cytokines production and to transport the complexes to MHC-II mediated antigen presentation while interaction between immune-complexes and FcγRIIa impaires proinflammatory cytokine production and antigen presentation [46] . Whether this phenomenon can be applied to DENV-immune complex infection remains unclear . Investigation of the intrinsic role of enhancing antibodies has pointed toward suppression of the innate immune response in which type I interferon and proinflammatory cytokine production are revealed as the main targets [38] and the mechanism of suppression is partly due to ADE infection up regulating negative regulators of the RIG-I/MDA5 signaling pathway [20] . In the present work , we expanded our investigation horizontally to another type I interferon stimulating pathway , the TLR-signaling pathway . Toll-like receptors , some of the most important pattern recognition receptors , are abundant on monocytes/macrophages and dendritic cells , the main in vivo target cells for DENV , and TLRs are key players in priming innate responses upon viral infection . They detect invaders and trigger antiviral defenses , interferon and pro-inflammatory cytokines . Interferon then exerts an antiviral activity through activating the JAK/STAT signaling pathway resulting in the activation of interferon stimulated genes which subsequently inhibit viruses by a non-cytolytic mechanism . In turn , invaders can circumvent the interferon response to be able to propagate in the host cell . DNA viruses including hepatitis B virus ( HBV ) use their envelop and non-envelope proteins to suppress TLRs expression as well as to inhibit responses elicited by TLRs stimulation [47] , [48] , [49] . The vaccinia virus uses the A46R and A52R proteins to inhibit TLR-signaling molecules such as TRIF , TRAM and IRAK-2 resulting in ablation of type I IFN production [50] , [51] . Respiratory syncytial virus ( RSV ) strain A2 and Measles virus ( MeV ) , a member of the Paramyxoviridae family , can antagonize TLR-7 and TLR-9 induced type I IFN and proinflammatory cytokine production in epithelial cells , hematopoietic cells ( T lymphocytes , B lymphocytes , monocytes ) and pDC [52] . Similar to A46R and A52R of the vaccinia virus , the NS3-4A heterodimer of Hepatitis C virus inhibits the TLR-3 mediated antiviral response by degrading TRIF while NS5A has been reported to bind directly to MyD88 leading to inhibition of the MyD88-dependent signaling pathway [53] , [54] . Moreover , the entire genome of hepatitis C virus has also been found to suppress TLR-3 , -4 and -7 in HepG-2 cells [55] . Similar events are also reported during DENV infection . DENV use nonstructural proteins to block phosphorylation and to down-regulate expression of major components of the JAK/STAT pathway causing reduced activation of IFNα/β stimulating genes [56] , [57] . All of the antagonists mentioned above are viruses or viral products . However , high-jacking of pre-existing host immune factors by viruses to interfere with the TLR-dependent signaling pathway has not been reported . We are the first group that has been able to show that DENV exploits pre-existing subneutralizing antibodies to defeat the TLRs system . Upon engagement between FcR and DENV-antibody complexes or entry of DENV into monocytic cells via FcR , expression of TLR-3 , -4 , -7 and TLR signaling molecules were dramatically decreased in parallel to the decreased production of IFN-β . This observation was further confirmed in experiments that showed that production of IFN-β and expression of TLRs were restored when ADE-infected cells were pretreated with anti-FcR antibodies . This data indicates that entry of DENV via FcR preferentially switches off the TLR-dependent IFN stimulating pathway . The switch off mechanism was mediated at the TLRs gene expression level and through activation of the negative signaling regulators , TANK and SARM ( Fig . 6 ) . Unfortunately , the events occurring upstream of TLRs expression and of SARM and TANK activation are unknown , and therefore require further investigation . However , Kurane and colleagues have demonstrated that functional ITAM is essential for ADE infection [58] . The events shown in Fig . 6 are well supported by the array analysis in which ADE-infection suppressed TLR gene expression and down-regulated the TLR-signaling cascade while several negative regulators of TLR-cascade were up-regulated . Importantly , this phenomenon was also found in natural DENV infection in which TLRs ( TLR-3 , -4 , and -7 ) and TRAF6 were strongly suppressed in PBMC from secondary DHF patients but not in PBMC of mild disease , secondary DF patients . Taken together , the data obtained from in vitro as well as ex vivo studies indicate a significant collapse of the TLR-dependent signaling pathway during DENV-enhancing antibody complex infection . In conclusion , the present study and our previous report on the suppression of TLR-signaling during DENV-ADE infection of THP-1 human monocytic cells clearly show that initiation of infection by DENV-enhancing antibody complexes defeats the major pathogen recognition pattern pathway resulting in suppression of innate antiviral responses . How dengue immune complexes can have such broad effects on cells is not clear . FcRs are well known in their roles in regulating a multitude of innate and adaptive immune responses . After crosslinking by immune complexes , ITAM initiates either negative or positive signals through several types of adaptor molecules such as Syk/ZAP family PTKs , Src family kinase and SHIP-1 , SHP-1 etc . [59] , [60] . The inhibitory activities of SHIP-1 , SHP-1 and Lyn/P13k can be can be seen on multiple signaling pathways including TLRs [61] , [62] . Even though direct role of these adaptors on RIGI/MDA5 remain unclear but TLRa and RIGI/MDA5 pathways crosstalk at several steps , thus , the negative effect against TLRs possibly block RIGI/MDA5 pathway . Finally , DENV immune complexes formed with neutralizing or partially neutralizing antibodies fail to suppress innate immunity but permit limited infection of monocyte/macrophage resulting in mild disease is crucial problem requiring further study .
|
Dengue is the most common vector-borne viral disease in humans , with 50–100 million infections per year . The severity of dengue ranges from an acute febrile illness , DF , to a life-threatening vascular leakage syndrome with or without shock , DHF/DSS . Determinants of these syndromes are mainly host factors including non protective but cross reactive antibodies which are known as preexisting enhancing antibodies . These antibodies enhance disease severity through increasing the virus infected cell mass and facilitating intracellular virus replication . Here we demonstrate that DENV exploits preexisting subneutralizing antibodies to defeat the pathogen recognition system and to down regulate the TLR signaling pathway resulting in suppression of an array of innate immune responses . Furthermore , we also show that this phenomenon specifically occurs in the severe form of dengue but not in the mild form of disease .
|
[
"Abstract",
"Introduction",
"Methods",
"Results",
"Discussion"
] |
[
"infectious",
"diseases/viral",
"infections"
] |
2010
|
Subversion of Innate Defenses by the Interplay between DENV and Pre-Existing Enhancing Antibodies: TLRs Signaling Collapse
|
Although the vertebrate limb bud has been studied for decades as a model system for spatial pattern formation and cell specification , the cellular basis of its distally oriented elongation has been a relatively neglected topic by comparison . The conventional view is that a gradient of isotropic proliferation exists along the limb , with high proliferation rates at the distal tip and lower rates towards the body , and that this gradient is the driving force behind outgrowth . Here we test this hypothesis by combining quantitative empirical data sets with computer modelling to assess the potential role of spatially controlled proliferation rates in the process of directional limb bud outgrowth . In particular , we generate two new empirical data sets for the mouse hind limb—a numerical description of shape change and a quantitative 3D map of cell cycle times—and combine these with a new 3D finite element model of tissue growth . By developing a parameter optimization approach ( which explores spatial patterns of tissue growth ) our computer simulations reveal that the observed distribution of proliferation rates plays no significant role in controlling the distally extending limb shape , and suggests that directional cell activities are likely to be the driving force behind limb bud outgrowth . This theoretical prediction prompted us to search for evidence of directional cell orientations in the limb bud mesenchyme , and we thus discovered a striking highly branched and extended cell shape composed of dynamically extending and retracting filopodia , a distally oriented bias in Golgi position , and also a bias in the orientation of cell division . We therefore provide both theoretical and empirical evidence that limb bud elongation is achieved by directional cell activities , rather than a PD gradient of proliferation rates .
Vertebrate limb development is a classical model system which has contributed to some of the key concepts in the developmental field [1] , [2] . Over a period of 1–2 d a roughly homogeneous mass of undifferentiated mesenchymal cells develops into a complex collection of different cell types ( including cartilage , bone , tendons , and dermis ) which are spatially organized to create a functional organ . In the mouse and chick , the limb bud starts as a small bulge from the lateral flank of the embryo . It possesses a very simple structure , composed of a central mass of mesenchymal cells covered by a single-cell ectodermal epithelium . Very early in development the ectoderm develops a thickened ridge ( the apical ectodermal ridge , or AER ) which runs along the antero-posterior ( AP ) axis and marks the anatomical boundary between dorsal and ventral ectoderm ( Figure 1A ) . Subsequent growth of the bud shows a preferential orientation—extension in the distal direction ( away from the body ) is dramatic , while by comparison the increase in width and height is much slower . Although great strides have been made in understanding the molecular basis of patterning and cell specification [3] , [4] , [5] , [6] , [7] , the cellular basis of distally oriented limb bud outgrowth remains unclear . The oldest and still the most prominent hypothesis to explain the physical morphogenesis of limb bud outgrowth is the “proliferation gradient” model ( Figure 1B ) , first described by Ede and Law in 1969 [8] . This idea states that a diffusible signal from the AER acts primarily as a mitogen [9] which “…signals the mesenchyme immediately underlying it , termed the progress or proliferative zone , to proliferate , resulting in directed proximo-distal outgrowth” [10] . Much evidence appears to support this hypothesis , in particular a graded distribution of proliferation rates along the proximo-distal axis has been reported for both mouse and chick limb buds ( as observed by mitotic index counting [11] , BrdU incorporation [12] , [3H]thymidine labelling [9] , and cell-cycle specific antibody labelling [13] ) . During the 1990s concrete evidence was presented for the molecules responsible for this mitogenic effect—FGF4 and FGF8 were shown to be expressed specifically in the AER , to be able to diffuse away from the source cells [14] and to have mitogenic influence in cell culture and various organ systems [10] , [15] , [16] . A few other hypotheses have been proposed to explain limb bud morphogenesis . Oriented cell divisions are known to be involved in other morphogenetic processes like vertebrate gastrulation [17] or Drosophila wing disc development [18] , however no evidence for a preferred direction of cell division has been shown during limb bud extension [11] or subsequently been reported . Programmed cell death is known to occur in a few localized regions of the developing bud [13] , but it cannot explain the distally directed extension of the limb . More importantly , Li and Muneoka [19] performed an elegant experiment demonstrating that at least some of the mesenchymal cells in the chick wing bud can move towards an ectopic source of FGF4 implanted in the centre of the bud . This raised the intriguing possibility that mesenchymal cells might treat the FGF gradient as a chemoattractant rather than a mitogen , and respond by active migration towards the AER . Finally , it was speculated in 1970 [11] that the ectoderm might play a mechanical role in shaping the growing limb bud , however it has been demonstrated that limb development can proceed quite normally in the absence of significant regions of dorsal ectoderm [20] , [21] . Despite these suggested alternatives , the “proliferation gradient” model has remained the dominant hypothesis for the last 40 years [22] , [23] , [24] . Although the concept was first articulated by Ede and Law [8] , it was their own pioneering computer simulation ( from the late 1960s ) which first questioned the model . However , the strength of their conclusions rested on a rather abstract 2D cellular automaton approach , and more recent computer simulations have adopted the idea . In 1999 Dillon and Othmer [22] created the first realistic 2D finite element model ( FEM ) of limb development , and although their simulation was not aimed at exploring the cellular basis of directional outgrowth , they nevertheless directly incorporated the proliferation gradient hypothesis into their model by allowing growth rates to be controlled by a molecule diffusing from the distal tip . In contrast to Dillon and Othmer , more recent computer simulations have specifically aimed to explore the proliferation gradient model and concluded that the hypothesis can indeed explain limb outgrowth . Poplawski et al . incorporated the gradient hypothesis within a Cellular Potts framework to show that distally restricted growth could produce bud elongation [25] , while Morishita and Iwasa employed a cell-based 2D spring lattice [23] to demonstrate a similar result . This last study renames the concept with the more explicit term “growth-based morphogenesis , ” emphasizing that although the global shape changes are directional , they result from local cell behaviours which are non-directional [23] . This highlights our key question to be addressed here: Are the important cell activities for outgrowth directional or isotropic ? All active cell behaviours can be classified into these two categories . Processes such as migration and intercalation are directional—they depend on cells having a sense of orientation ( for example by sensing gradients or using the PCP system ) . By contrast , behaviours such as cell death are not oriented ( i . e . they are isotropic ) , and therefore cause contraction of tissue equally in all directions . Cell proliferation can fall into either of these two categories: in some cases the orientation of cell division is known to be carefully controlled ( like Drosophila wing disc development [18] ) , but in other cases there appears to be no control of orientation , for example in the developing limb bud it is believed that cells divide randomly in any orientation [11] . The popular notion of growth-based morphogenesis ( which is equivalent to the established proliferation gradient model ) states that controlling the rates of isotropic proliferation is enough [23] , and that cells do not require directional information . Here we develop a new interdisciplinary approach to address this question . Rather than explore a range of different hypotheses , our goal is to focus on the most popular one—growth-based morphogenesis [23]—and to rigorously test its sufficiency as an explanation of limb bud outgrowth . In other words , we explore whether non-directional ( isotropic ) cell behaviours can explain limb bud elongation . Firstly , we develop novel data-capture and processing techniques to generate empirical quantitative data-sets for two distinct aspects of the developing mouse limb bud: ( i ) accurate 3D geometry of the shape changes and ( ii ) a quantitative map of cell cycle times . Secondly , to our knowledge , we create the first dynamic 3D computer simulation of limb outgrowth , which is directly based on these data . By developing a novel 3D parameter-optimisation approach we demonstrate that the observed spatial control of proliferation rates has little impact on morphogenesis and cannot explain distally directed limb bud outgrowth . We conclude that isotropic cell behaviours in general , such as non-oriented cell proliferation and programmed cell death , provide little or no contribution to the major observed shape changes . The main role of proliferation must be simply to provide enough progenitor cells for the organ . We predict that shape generation ( elongation ) must instead be driven by directional cell activities , such as active migration or cell intercalation . Prompted by this theoretical prediction , we go back to the real system to examine cell shape and markers of cell orientation in the developing chick limb bud . We find that most mesenchymal cells have a striking highly branched and extended cell shape composed of dynamically extending and retracting filopodia , a distally oriented bias in Golgi position , and also a bias in the orientation of cell division . The discovery of this collection of oriented cellular activities opens a new area of enquiry into how active mesenchymal behaviours ( such as migration and intercalation ) contribute to morphogenesis of the limb , which has only been addressed by one pioneering study so far [19] .
To build a data-driven computer model we wished to have an accurate representation of the changing shape of the growing mouse limb bud . A numerical simulation requires a defined spatial domain , and previous studies have employed 2D abstract approximations of the growing limb bud shapes . In this study we have improved on previous work in two ways: Firstly , the simulation ( and therefore the shape information ) is 3D instead of 2D . This is important as we aim to model mechanical forces which cannot be correctly captured in a 2D abstraction ( for example the 2D simulation of Dillon and Othmer [22] required virtual springs to be added from the dorsal ectoderm to the ventral ectoderm , to compensate for the lack of the full 3D structure ) . Secondly , rather than a simple mathematically defined “bulging” shape , we wished to use real empirical shape features to define the spatial domain of our simulation . We therefore employed state-of-the-art 3D imaging technology to generate accurate quantitative shape information of real embryonic mouse limb buds ( Figure 2 ) . For each embryo examined , detailed 3D shape information was generated using optical projection tomography ( OPT ) —an imaging technology ideally suited for scanning mesoscopic biological specimens [26] . Using an OPT scanner we captured 400 projection images of the autofluorescence from the embryo , rotating it by 0 . 9° between images . A filtered back-projection algorithm [27] was then used to reconstruct a voxel dataset from the raw projections , and from this a 3D intensity iso-surface was generated for the embryo ( this is a 3D contour which encloses all regions above a certain threshold intensity , Figure 2C ) . From these static 3D representations , the right hind limb was then virtually dissected away from the rest of the embryo for further analysis ( Figure 2D , 2E ) . We selected two limb buds of different developmental ages for 3D scanning: an earlier stage with shape denoted by St0 representing the initial condition for the simulation and a later stage St1 which defines the target shape that real limb development achieves . These shapes are given by the isosurfaces extracted from the empirical OPT data , as described in the previous paragraph . The general strategy followed is to simulate the growth of the limb starting with initial shape St0 and then to compare the shapes predicted by the simulation ( predicted = pSt1 ) with the real target shape St1 . Three criteria were important in choosing suitable developmental stages for St0 and St1 . The shape change must be significant enough to distinguish between good and bad results of the simulation , but the time-interval should also be short enough to be computationally efficient . Also , for the purposes of building the computer model we wish to assume uniform physical properties for the mesenchyme , and we therefore require a developmental stage when internal mesenchymal condensations have not yet formed . Based on these criteria we selected two limb buds ( E11 . 0 and E11 . 25 ) which are 6 h apart in normal development ( see Figure 2A , B ) . The shapes of six embryos at each stage were examined to ensure that the shape change due to growth was much greater than the shape variability between embryos of the same stage ( Figure S1 ) . Mesenchymal cell density was also checked at different positions of the older limb bud ( E11 . 25 ) , and despite the expression of early skeletal markers such as Sox9 and Noggin , localised regions of higher density ( mesenchymal condensations ) have not yet formed ( Figure S2 ) . Staging was performed by comparison to a collection of 200 embryos harvested at precise time-points between E10 . 5 and E12 . 5 . The resulting isosurface St0 could then be used to create the full 3D tetrahedral mesh required for subsequent modelling ( Figure 2G; this was done using the program NetGen [28] ) . We have therefore created for the first time a numerical ( geometric ) representation of the mouse limb bud shape change in 3D . Using this resource we can assess the limb bud length ( PD ) of St0 and St1 ( 1 , 020 µm and 1 , 450 µm , respectively ) and calculate an average extension rate of 75 microns/h , or a total extension of 43% over 6 h ( note that the scales in Figures 2A–E are not the same ) . In contrast , the extension along the DV and AP axis is much less: ∼1% and 12% , respectively . The volumes for the two time-points are 0 . 551 mm3 and 0 . 914 mm3 , respectively . The second dataset required for our study is a quantitative 3D map of cell proliferation rates in the limb . Common approaches for measuring cell proliferation include mitotic index counting , BrdU , and anti-pH3 staining . In 1970 Hornbruch and Wolpert [11] used haematoxylin and eosin staining to analyze the mitotic index of mesenchymal cells in the chick limb and identified a gradient of high proliferation at the distal tip and lower proliferation proximally at stages HH23–27 . More recently Fernández-Terán et al . [13] studied the cell proliferation activity in the mouse and chick limbs using anti-pH3 immunohistochemistry and found a similar general pattern . However , single labelling techniques like these have an important limitation . Determining the number of cells in one cell cycle phase as a fraction of the total number of cells ( for example the proportion of BrdU-labelled cells in S-phase ) is a relative measurement and cannot provide information on how long that phase lasts in minutes or hours . This limitation applies to all single-labelling approaches , whether using BrdU , pH3 , Ki67 , PCNA , or tritiated-thymidine . Previous studies have therefore provided information on the relative rates across different regions of the limb , but have never quantified these spatial patterns in terms of cell cycle time . Pulse-chase experiments overcome this limitation through the use of two or more labels administered to the living cells at different times [29]; however , this has typically been done on dissociated cell populations , thereby losing all spatial information . To overcome this problem we adapted a double-labelling technique successfully used by Martynoga et al . [30] to quantify proliferation rates on 2D sections of the developing telencephalon ( adapted from Shibui et al . [31] ) . This approach allows measurement of the average cell cycle time of a population of cells by sequentially labelling them with two different markers at a known time interval ( Figure 3A ) . Pregnant females are injected first with IddU and then after time interval Ti are injected again with BrdU . Embryos harvested 30 min later are fixed , embedded , sectioned , and then analysed using two different fluorescent secondary antibodies plus DAPI staining , which allows the identification of three cell populations: unlabelled ( blue ) , single-labelled ( blue and green ) , and double-labelled . In effect this creates a new artificial phase of the cell cycle whose exact duration is known: single-labelled cells are those which left S-phase during time Ti ( called leaving cells , the number of which is Lcells [29] ) . Since the cell population is dividing asynchronously , then the different phases of the cell cycle will be sampled equally ( Figure 3A ) . The ratio of the total number of cells to Lcells therefore equals the ratio of the total cell cycle , Tc , to Ti: ( 1 ) Tc can therefore easily be calculated for each local population of labelled cells: ( 2 ) To create our quantitative 3D map of cell proliferation rates a limb bud was chosen ( having an age in between those of St0 and St1 ) and was cut into sections 7 µm thick ( Figure 3B , C ) . After fluorescent immunohistochemistry we analysed how smoothly the Tc values vary across the sections and subsequently selected 30 areas to capture this spatial distribution . For each of these areas the differently labelled cells in a circular region with a diameter of 215 µm were manually counted and the cell-cycle time calculated ( Figure 3B ) . A 3D mapping between the 30 areas and St0 was created ( Figure 3D ) . This gave a sparse representation of proliferation rates for the limb . These values were then interpolated across the remaining vertices of the tetrahedral mesh corresponding to St0 ( from Figure 2G ) using a radial basis function ( RBF , see Materials and Methods ) , creating a full map of Tc values which vary smoothly across the 3D space of the limb bud . We have thus created the first quantitative 3D map of proliferation rates for a growing vertebrate limb bud . The qualitative pattern agrees with previous studies ( with higher proliferation rates in distal regions and closer to the ridge , and lower rates at the proximal end ) [13] , however a map of absolute Tc values across the tissue has not previously been achieved . We performed this analysis for a few limb buds at different ages and revealed that over the 6 h period from E11 . 0 to E11 . 25 the changes in proliferation rate are insignificant . This makes sense when one considers that the fastest cell cycle time was itself ∼10 h . We therefore consider this 3D map to be a suitable representation of the average rates during the 6 h period of the simulation . The next aspect of this study was to define a suitable method for integrating the data into a dynamic model of growth . Three components are required: a method to represent the growing 3D spatial domain of the simulation , a choice of model/equations to represent the growing limb bud tissue and a numerical method to solve the equations over time . Previous models ( which have all been 2D ) have included a variety of approaches , either considering a space larger than the limb bud itself ( using the immersed-boundary method to represent the limb within the larger space [22] ) or representing the 2D shape of the limb bud itself with an irregular triangular mesh , which can be used as the framework for a finite element method [32] or a spring-lattice method [23] . For our 3D model we used a tetrahedralised mesh to approximate the geometric domain . We used NetGen [28] to transform the closed 3D iso-surface St0 into a fully tetrahedralised mesh suitable for the FEM simulation ( Figure 2G ) . A variety of meshes were generated with different spatial resolution ( defining how fine or coarse the mesh is ) , and from these we chose a 3D mesh with approximately 6 , 000 vertices and 27 , 000 tetrahedrons , as a balance between computational expense and accuracy . Philips et al . reported that vertebrate mesenchymal tissue behaves like an elastic solid over very short time scales but displays a liquid-like characteristic in response to stress in long-term culture [33] . The first FEM of limb development ( 2D ) therefore employed the Navier-Stokes equations to represent the mesenchyme as a viscous incompressible fluid whose volume increases corresponding to a distributed source term , s , which represents the patterns of cell division [22] . Due to the small size of the limb bud , and the extremely low velocities involved ( ∼75 µm/h , described above ) we chose a modified version of the Navier-Stokes equation to describe the movement of mesenchyme in our 3D model , in agreement with other cases where convection is negligible [32] , [34] , [35] . This also agrees with the recent lattice model proposed by Morishita [23] . We have also performed comparative simulations with and without convection to demonstrate that it has no significant effect on the results ( unpublished data ) . We used the following equations which describe the balance of forces acting at any given region of the fluid as follows: ( 3 ) ( 4 ) where , v is velocity , p is pressure , and Re is the Reynolds number . Equation ( 4 ) describes fluid continuity , which usually represents the conservation of mass . In our case ( following Dillon and Othmer [22] and Murea and Hentschel [32] ) we alter this equation to allow a distributed material source term s which can vary arbitrarily across space and time: ( 5 ) In this way , the s field ( tissue growth ) can drive the velocity ( tissue movements ) of the system . Positive s values result in tissue growth at the position x , y , z at time t . In fact , s represents the proportional volumetric growth per unit time ( otherwise known as the growth constant k , or the growth-frequency ) , so a value of 0 . 1 h−1 means that the volume expands by 10% in 1 h . An important question is how to relate s to real cellular activities . We consider cell density ( ) to be the number of cells ( ) per unit volume ( ) : ( 6 ) The volumetric growth rate ( ) for a given region of tissue can therefore be completely defined as a function of two variables: the rate of cell number change ( ) and the rate of cell density change ( ) . At some stages of development these two factors effectively cancel out; for example the first few rounds of zygotic cell division simply divide the existing cellular material into a larger number of smaller regions ( cells ) . In other words , as the cell number increases , so does the cell density such that overall volume remains unchanged . By contrast , in limb development cell density does not change much during our 6 h time interval , such that growth is mostly driven by cell proliferation . It is also known that programmed cell death only occurs in three small well-defined regions in the limb buds of both mouse and chick [13] . For simplicity , we will start by assuming that d is constant . In this case is proportional to , and s is equal to sp , which we define as the proportional growth rate due to proliferation alone . Constant sp describes exponential growth , and in general then , the number of cells Nt at a time point t can therefore be calculated from the number of cells at an earlier timepoint N0 by the following equation: ( 7 ) When t equals the cell doubling time ( Tc ) , then Nt1 must be double the value of Nto; therefore sp can be calculated from Tc for each region of tissue as follows: ( 8 ) It can be seen from this equation the intuitive fact that sp is inversely proportional to Tc—as the cell cycle becomes longer ( slower ) , then growth rate decreases . Using equation ( 8 ) we can therefore approximate a 3D field of sp values that represents tissue growth . If we use hours as the unit of time , a cell cycle time of 10 h translates into an sp value of 0 . 07 h−1 . We next wished to check whether cell density changes significantly during the 6 h period between t0 and t1 . Analysis of nuclear-stained sections from four stages of limb bud development showed that although there are no spatial variations in cell density ( mesenchymal condensations have not yet formed ) there is a small but clear increase in the uniform cell density over time ( Figure S2 ) . From E11 . 0 to E11 . 25 the cell density increases at ∼1 . 7% per hour , which can therefore be represented by sd = 0 . 017 ( the proportional rate of volumetric change due to cell density changes ) . An increase in cell density means that the cells are packed closer together ( either due to a reduction in secretion of extra-cellular matrix ( ECM ) , or a reduction in average cell size ) , and this therefore leads to a decrease in volume . The overall proportional volumetric growth rate is therefore defined as follows: ( 9 ) In other words , if the proliferation causes volumetric expansion of 10% per hour , and density increase causes volumetric shrinkage of 1% per hour , the net growth will be 9% per hour . We used the commercial software package FastFlo to solve these equations [36] and employed the artificial compressibility method to derive a solvable equation for pressure [37] . The suitability of this approach was tested using simple geometric figures ( spheres ) with a variety of source terms to confirm that the correct result was computed . The domain was implemented as a Lagrangian mesh—in other words the 3D mesh grows in unison with the growth of the limb bud . Each tetrahedron therefore represents a given piece of growing tissue within the bud . Although each of these tissue regions increases in size over the 6 h , we assume that the s value for each region is constant during the 6 h period ( as justified above ) and is thus carried along with the vertices of the mesh . After generating the two sets of quantitative 3D data on shape St0 and St1 and constructing the FEM of tissue growth we could start exploring the “growth-based morphogenesis” hypothesis . The 3D distribution of the source term s was directly calculated from our atlas of cell cycle times ( using equations 8 and 9 ) , and from St0 the simulation was run forwards over a period of 6 h to determine the new predicted limb bud shape pSt1 . Solving the equations requires a value for the Reynold's number , and previous studies have chosen a single value ( equivalent to the viscosity of water ) to explore limb growth dynamics [22] . However , the real effective viscosity of mesenchymal tissue is not known , and we therefore chose to explore a wide range of values , to ensure that our conclusions would not be dependent on this unknown parameter . We performed 6 simulations , covering 5 orders of magnitude from 10−1down to 10−6 ( a viscosity similar to honey ) . Results of these simulations revealed that viscosity had only a minor impact on the final shape ( Figure S3 ) . Over the 5 orders of magnitude in range of Re explored , limb bud elongation varied by just 9% points . The real limb shows an outgrowth of 43% whereas the simulations showed an increase in PD length of between 3% and 12% . Thus , we conclude that the exact value of the viscosity used in these simulations is not a critical parameter . The predicted shapes are all similar to each other ( Figure S3 ) , and none of them match the empirically measured St1 . A detailed analysis of one of these simulations ( Re = 10−2 ) is highlighted in Figure 4A–D . Rather than a distally oriented outgrowth , the virtual limb bud shows fairly uniform growth in all directions ( green arrows in Figure 4B ) resulting in a predicted shape ( green surface in Figure 4C , D ) which is unlike the real measured shape ( blue surface in Figure 4D ) . In order to confirm the general importance of this conclusion for limb bud development , we also repeated the entire analysis for a younger stage of hindlimb: 3D imaging by OPT , BrdU/IddU analysis , cell density counting , and finite element modelling was performed for an earlier limb bud shape ( E10 . 5 growing to E10 . 75 ) . As before , the proliferation pattern shows a slight gradient of values along the PD axis ( Figure 4E ) which in principle could agree with the “growth-based morphogenesis” hypothesis . However , the simulations using these empirical values confirmed again that the correct shape cannot be achieved using this model ( Figure 4F–H ) . In both simulations the final predicted volume of the limb bud is smaller than the real volume ( a 15% and 21% deficit for the younger and older simulations , respectively ) . This is most likely explained by the fact that some cells are still entering the limb bud from the main body flank during early developmental stages . Although we are confident of the estimate of Tc values , we also wished to double-check that a hypothetical error in our Tc calculation method could not account for the failure of elongation . We therefore performed an extra pair of simulations in which the estimated s values were uniformly scaled up such that the final volume equalled the real volume . This required average Tc values of 8 . 1 h and 9 . 5 h , respectively , for the younger and older simulations . Both of these “volume-corrected” simulations show the same result as before—a general increase in limb bud size in all directions , rather than distal-specific elongation ( Figure S4 ) . Additionally , we performed one final test , in which the average measured Tc value was distributed uniformly across the limb bud . The resulting shape was visually indistinguishable from the simulation using the measured gradient of Tc values , highlighting that this observed proliferation gradient has no significant effect compared to a flat distribution . One way that a general isotropic increase in volume could be converted into a distal elongation is if the mesenchyme was “squeezed” by the ectoderm , and this idea has been proposed a few times [11] , [22] , [38] . This concept predicts that the mesenchyme exerts an outward force , which is mechanically resisted by the ectoderm . The strongest evidence against this idea was first described in the classical work of Saunders [20] , in which he showed that removal of large segments of the dorsal ectoderm ( up to three-fourths of the dorsal surface ) did not interfere with relatively normal limb development—in particular that the mesenchymal tissue did not spill out through the ectodermal hole . This was later re-confirmed by Martin and Lewis [21] in experiments which specifically destroyed the dorsal ectoderm of the chick limb bud with UV radiation , while leaving the AER intact . We have also made similar observations in mouse limb buds grown in in vitro culture ( Figure S5 ) , and we therefore rule out the possibility that distal elongation is the product of an isotropic mesenchymal expansion being squeezed and restricted by an external ectodermal force . Taken together our simulation results strongly suggest that in the absence of any directional cell behaviours the empirically measured proliferation pattern cannot produce the correct limb bud shape . Although this spatial pattern is apparently controlled quite precisely [13] , with lower rates proximally and higher rates distally and near the ectoderm ( Figure 3F ) , nevertheless this spatial gradient does not appear to be important for limb elongation . Our data-driven simulations strongly suggest that isotropic growth can be ruled out as the main force for distally directed limb bud elongation . However , despite our confidence that these are the most accurate empirical data sets generated for the limb bud so far ( on 3D shape change and cell cycle times ) , nevertheless the possibility for some numerical errors remains . As our simulations depend heavily on the numerical details of these data sets , it is therefore essential to perform a systematic exploration of the parameters of the model: Within which bounds will our conclusions hold true ? In other words , could a different set of isotropic growth rates be consistent with growth-based morphogenesis ? Are there in fact multiple growth patterns that could be compatible ? If so , how different would these proliferation rates be to our measured data ? To answer these questions we formulated our model as an inverse question . Rather than starting with the initial shape St0 and the growth data TC and asking what shape pSt1 they predict ( as done in the previous section ) , we start with the initial and final shapes ( St0 and St1 ) and ask the computer to search for a theoretical growth pattern which could produce this result . The inverse approach has previously been used for other complex developmental questions , such as deducing gene network design from the resulting expression patterns in Drosophila [39] , [40] . The approach requires three components: ( i ) a parameterisation of the problem , ( ii ) a fitness function , and ( iii ) a method to find optimal solutions to the problem . In general , two classes of optimization methods are distinguished: local and global ( recently reviewed in Ashyraliyev et al . [41] ) . Global search methods are necessary when the search space is likely to have many fitness optima ( known as a rugged landscape ) , making it hard to locate the true global best result . They mostly employ stochastic functions to avoid getting trapped in local optima ( for example Simulated Annealing [42] ) . Local optimization methods by contrast can be used for either low dimensional or constrained problems ( known as a correlated fitness landscape ) . Local methods start from a specific initial set of parameter values ( i . e . an initial position in the landscape ) and assume that a continuous “uphill” path leads to the global optimum . Theoretical considerations suggested that our choice of parameterization ( defining an independent growth value for each region of tissue ) would create a smooth , correlated landscape . We therefore explored the use of a local search method . ( This choice is verified in the next section . ) Due to the rather slow running time of a single simulation ( 5–8 min ) we chose the Hooke and Jeeves direct search method ( rather than a gradient-based method ) [43] . At each iteration of the optimization , all 525 parameters are tested individually to assess whether a small local increase or decrease in the growth rate improves the solution . At the end of each iteration a new candidate solution is constructed by combining all the individual improvements ( thereby implementing a diagonal move in parameter space ) . The magnitude of the increments/decrements is reduced during the course of the optimization process to allow finer adjustments as the solution improves ( similar to the cooling schedule employed in Simulated Annealing [42] ) . Once developed , we used this optimization strategy to ask if a 3D proliferation pattern could be found that would give us a shape similar to the empirical measured St1—in other words , is it at all possible that a 3D distribution of purely isotropic behaviours can explain normal limb bud development ? We restricted the optimized s term to be positive , so that despite the belief that some cells enter into the limb bud from the flank , it is nevertheless reasonable to compare the optimized s values to the results from our BrdU/IddU double-labelling experiments . Other possible influences like cell death were thus intentionally neglected . After 75 iterations of optimization a shape was produced which showed a significantly higher similarity to the St1 shape than our previous result ( using the empirical BrdU/IddU data Figure 4 ) , although the DV and AP growth was still greater than the real St1 ( Figure 5B–E ) . This improved shape change was explained by a dramatic difference in proliferation pattern . This optimized pattern shows a much stronger spatial gradient along the PD axis—with s ranging from just above zero in much of the bud to 0 . 47 h−1 in the distal-most regions ( Figure 5B ) . This contrasts with the empirical cell cycle data which range from s = 0 . 03 h−1 to just 0 . 07 h−1 ( Figure 4B ) . Since the resulting simulated shape still did not match the empirical St1 we next asked a more general question . Rather than restricting the exploration of s to positive values—which could correspond specifically to proliferation ( equation 7 ) —we extended the possible range of s into negative values , thereby allowing active tissue shrinkage to also play a role , which in principle could occur by programmed cell death or local increases in cell density . In practice this allows s to represent the combined effect of any isotropic cell behaviours . Adding this change and rerunning the optimization achieved a large improvement in the match between the shapes of pSt1 and St1 ( Video S2 ) . However , before analyzing this result in detail we wished to confirm that our choice of a local search method was suitable for this problem—in other words to determine whether this optimization process would become trapped on local optima rather than finding a genuine global result . A common strategy to address this question is to start the simulation at multiple different initial conditions ( i . e . different positions in the landscape ) and explore whether it always converges to similar solutions . In addition to the two previous optimisations ( which were started with all s values set to zero ) we chose five additional initial conditions—two different linear gradients of proliferation in different directions , two radial gradients ( either increasing or decreasing from the centre ) and one pattern with a random distribution of values . These initial patterns were chosen to represent a collection of extreme alternative spatial distributions ( Figure S6 ) , thereby covering a wide region of parameter space . These tests all resulted in a very similar final optimized distribution within about 25 iterations . Plotting the shape difference over iterations of the optimisation process shows all five cases converging rapidly to a good fit ( blue lines in Figure 6A ) . Interestingly , they converged faster than the previous case ( when s values could not go below zero ) , which required 75 iterations before stabilizing ( red line in Figure 6A ) . Examination of the final patterns showed that despite some small variations , they had all converged on the same solution ( see also Figure S6 ) , strongly suggesting that the fitness landscape for this problem contains one global optimum , which is reachable along a continuous path of incremental fitness improvements from many different starting positions . To further verify this conclusion we monitored the change in s values during the optimization process at four specific positions within the limb bud: distal , central , dorsal , and ventral . In the first example all s values started at zero ( Figure 6B ) . During optimization the s values for distal tissue increased up to around 0 . 4 h−1 , central values increased a small amount , and dorsal/ventral values decreased to negative values . In the second example , the initial pattern of s values displayed a variety of different values for different regions—distal tissue started with low values , and central tissue with high values . During optimization , these values “crossed over” to converge on a final pattern similar to the previous case ( with high distal values around 0 . 4 h−1 , medium central values of around 0 . 15 h−1 , and again negative values for dorsal/ventral tissue ) . These results strengthen the conclusion that one global optimal solution exists which is repeatedly found , irrespective of the starting values . One of these optimization results is shown in more detail in Figure 6D–G . The much closer correspondence of the limb bud shapes can be seen by the more complex intersection between the green and blue surfaces in Figure 6G ( representing the predicted and real shapes , respectively ) , as compared to Figures 4D and 5E . More specifically , the shape comparison is ∼70% better than the shape produced by the real BrdU/IddU data ( blue graphs compared to green line in Figure 6A ) . This is only achieved by having very high proliferation in a very narrow distal region and negative values in much of the mesenchyme . In fact 22 . 5% of the volume of the mesenchymal tissue adopts a negative s value ( all the blue regions in Figure 6D ) , suggesting that if cells only perform isotropic activities , significant tissue shrinkage would be necessary to achieve the correct shape ( more than 10% shrinkage per hour in large regions of the bud ) . The primary motivation for this parameter exploration was to determine whether numerical errors in our cell cycle data could account for the model's inability to generate the correct limb bud shape . The optimization experiments produced two main results . ( 1 ) The concept of growth-based morphogenesis is theoretically possible—a pattern exists ( Figure 6D ) which can indeed produce the observed shape changes . ( 2 ) However , this pattern is dramatically different from our measured BrdU/IddU data ( Figure 4B ) , both quantitatively and qualitatively . For example , in the optimised result , the volumetric growth in the distal region must be as high as >0 . 5 h−1 . Since cell density does not significantly change over these developmental stages ( described above ) , the major source of volumetric growth is indeed cell division , and the model would require a cell cycle time of less than 1 . 5 h , which has never been observed in the growing mouse limb bud . Additionally , the predicted regions of strong tissue shrinkage cannot be explained by programmed cell death , as this is well known to occur in just three small regions [13] , rather than the large predicted 22% volume of the limb bud . At a more general level we have shown that purely isotropic cell behaviours ( such as cell proliferation , cell death , and change in cell density ) can be ruled out as the driving force for limb bud outgrowth . Our computer modelling makes the prediction that correct limb bud morphogenesis requires some kind of directional cellular activities . To verify this prediction we went back to the limb bud , to search for evidence of oriented cellular structure within the mesenchyme . Determining the shape of individual cells can be facilitated in two ways: ( a ) Membrane-specific labels dramatically increase the chance of visualizing the fine-structure of the cell outline . Cytosolic labels by comparison tend to produce an intense signal from the main cell body that outshines fine details of the membrane . ( b ) However , labelling too many adjacent cells can make it impossible to delineate each one clearly , and so membrane dyes such as bodipyceramide are unhelpful . The ideal approach labels the membranes of just a small subset of cells within an unlabelled tissue , thereby allowing each cell shape to be highlighted precisely . We therefore chose to electroporate a membrane-targeted GFP construct into the lateral plate mesoderm of HH15 chick embryos in ovo , to achieve stochastic cell labelling in the limb bud mesenchyme 24 h later ( HH21 ) . Confocal microscopy of labelled cells revealed a striking morphology . The vast majority of mesenchymal cells have very complex 3D shapes , exhibiting long filopodial processes which branch extensively and extend up to 3 cell diameters away ( Figure 7A–C ) . These shapes do not strongly resemble the “classical” 2D migrating cell morphology with a broad leading edge and narrow trailing edge , although this could be due to the genuinely 3D nature of the mesenchymal environment—indeed for some cells the Golgi-side appears to have more filopodia than the opposite side ( Figure 7C–E ) . Although an unambiguous orientation is not clear for individual cells , when many adjacent cells are labelled a gross orientation of the cellular processes can be discerned ( double-headed arrow in Figure 7B ) . This rough orientation is towards the nearby ectoderm and therefore perpendicular to the main PD axis , rather than towards the AER , possibly suggesting a cell intercalatory mechanism rather than a simple distal-wards migration . Apart from the extensive filopodia , we failed to detect another type of cellular process that has previously been described for limb bud mesenchymal cells: cytonemes , which are long processes ( up to 700 µm ) which are much thinner than typical filopodia and with a constant cross-sectional profile approximately 0 . 2 µm across . Since the complex 3D distribution of filopodia could be the driving force behind cell migration or intercalation , we performed time-lapse imaging of the electroporated limb buds in ovo , to determine how active they are . This imaging revealed a highly dynamic nature of the filopodial protrusions—contracting and re-extending in a manner reminiscent to migrating fibroblasts ( Figure 7F ) . Considering that almost all labelled mesenchymal cells display this complex array of dynamic filopodia , these observations considerably alter the classical view of the limb bud mesenchyme which has been repeatedly modelled as if cell divisions and cell growth represented the main source of force-generation [22] , [23] , [25] , [32] . As before , a single preferential direction for filopodial activity was not evident , arguing against a simple model of chemotactic migration towards the AER . To further explore the possible orientation of these cells we labelled the Golgi apparatus , because in many actively migrating cells it displays a biased position between the nucleus and the leading edge [44] . Golgi orientation in the developing limb bud mesenchyme has previously been explored with respect to the ectoderm [45] and the developing mesenchymal condensations [46] , [47] . Interestingly , whereas a slight bias towards the ectoderm was previously reported at later stages of limb development ( >E12 . 5 in the mouse or HH24 in chick ) , we already see a clear bias at HH21 ( Figure 8A , B ) . In more than 70% of cells the Golgi is positioned on the distal side of the cell ( n = 565 ) . Interestingly , although Golgi orientation shows more of a distal bias than the general cell shape , it is also not aligned strictly towards the AER—it appears to be influenced both by the AER and by the nearby ectoderm . In other words despite a general distal-wards bias , we do not find a precise alignment between Golgi position and the direction of limb elongation . If cell orientation is an important aspect of normal morphogenesis , then it is possible that the presence of cells pointing in the opposite direction is the consequence of cell divisions , during which the daughter cells must at least temporarily have their Golgi on opposite sides of the cell ( due to the movements of spindle formation and chromosome segregation ) . This would effectively reduce the strength of the measurable orientation bias . Although a previous study had reported a lack of bias in the orientation of cell division [11] , our interest in possible directional cell behaviours prompted us to re-evaluate this question . By measuring the angle of the relative positions of daughter chromatids at telophase ( n = 187 ) we revealed that there is indeed a clear bias in the cell division orientation in different regions of the limb bud ( Figure 8C–G ) . In regions close to the ectoderm this bias is similar to the bias for Golgi positions ( partly distal and partly ectodermal ) . Indeed as mentioned above , these two observations could be linked by the fact that during cell division Golgi positions will be determined by the positions of the daughter cells . However , in the central region of mesenchyme furthest from the ectoderm , this correlation is not seen—Golgi bias is clearly distally oriented , while the cell division shows a slight bias perpendicular to this ( i . e . along the DV axis ) . We also found a bias in cell division orientation of mouse limb bud mesenchymal cells , by tracking the angles of cytokenesis in time-lapse confocal movies of mouse limb buds cultured in vitro ( Figure S7 , and methods in Text S1 ) .
The cells in a developing organ can perform a wide range of active behaviours and movements—for example cell division , cell death , secretion of ECM , changes in cell size , active migration , intercalation , and convergent extension . A central difficulty for biologists is to pinpoint which behaviours are responsible for tissue-level movements . With state-of-the-art time-lapse microscopy it is increasingly possible to watch these behaviours directly , but observing a behaviour does not prove that it has a role in generating the tissue-level forces . For example , cell intercalation can either be the driving force behind convergent extension [48] or can alternatively be the by-product of tissue movements driven by other external forces . While a few previous studies on the limb have sought to uncover which cell behaviours might contribute to limb bud outgrowth [11] , [19] , here we have chosen a very different approach—to focus on the most popular concept , growth-based morphogenesis , and to rigorously test its sufficiency as a mechanistic explanation . The concept of growth-based morphogenesis is both an intuitive and popular explanation for limb bud outgrowth [9] , [10] , [23] . Even studies which revealed a possible alternative force for outgrowth still refer to the need for high proliferation localized specifically in the progress zone , stimulated by the mitogenic effects of FGFs secreted from the AER [19] . Similarly , studies which revealed the proliferative influence of ectodermal WNTs across the whole limb bud still also claimed a need for higher proliferation in the progress zone due to the combined effects of general ectodermal signals ( WNTs ) and specific AER signals ( FGFs ) [24] . The idea has twice been translated into a formal computer model [22] , [23] , however in both cases the idea was only explored at a conceptual level . Both models operated in 2D rather than 3D and did not attempt to integrate empirical growth data . By contrast , through novel image processing techniques we have measured the variables most relevant for the concept ( 3D shape changes and proliferation rates ) and directly tested whether the theory is compatible with reality . In particular , this was achieved by introducing a novel approach for parameter optimization—rather than optimizing a low-dimensional space of global parameters , we efficiently explored a 525-dimensional parameter space of local growth values , thereby creating quantitative predictions about how the growth-based morphogenesis concept could be theoretically possible ( Figure S9 ) . Interestingly , our data-driven growth model is effectively an extension of a 1D model produced over 30 years ago by Lewis [49] , in which he compiled the values of mitotic index along the PD axis and performed a similar growth calculation for the goal of creating a mathematical linear fate-map of the growing chick wing bud . It is the use of new data-capture techniques and finite-element modelling which has enabled us to overcome the challenge of extending his approach into 3D . An intriguing finding is that there is indeed a reproducible way in which the theory can produce the correct 3D shape . The successful growth pattern displays a very specific spatial distribution , and furthermore , this optimized pattern directly reflects the general assumptions behind growth-based morphogenesis—that mesenchymal proliferation rates are highest close to the AER . The correspondence between the predicted stripe of high proliferation ( red regions of limb buds in Figure 7A and Figure S6 ) and the location of the AER is striking , because no information about the ridge was included in the model . In principle , this result provides general confirmation that the underlying concept of growth-based morphogenesis is theoretically possible , as shown previously in 2D [22] , [23] . However , because our model is 3D and includes accurate information about the real shape of the limb , we can go a step further and compare the values of parameters in the model with real life measurements . It thus becomes clear that the growth pattern required to make the model work ( extremely high proliferation just under the ridge , and negative values ( tissue shrinkage ) in a large proportion of the mesenchyme ) is not reflected either in the quantification of real cell cycle times nor in the known small zones of programmed cell death [13] . Figure 9 highlights this comparison through the use of two different colour maps . Figure 8A shows the spatial pattern of real proliferation rates in two orthogonal cross-sections through the limb bud , with a colour map normalized with respect to the fastest and slowest dividing cells ( a cell cycle time of 11 h ( red ) and 25 h ( blue ) , respectively ) . Panel B shows the same information ( the real cell cycle times ) , but with a colour map which has been normalized with respect to the fully optimised result from Figure 6D , which is shown in panel C . To achieve growth-based morphogenesis the proliferation rates must adopt extreme values—ranging from −0 . 1 h−1 to 0 . 6 h−1 . If the real cell cycle times are displayed with the same colour map ( panel B ) they constitute a very narrow range between these extremes—hardly any variation is seen . This is reflected in the observation that this real but shallow gradient of cell cycle times ( from 11 to 25 h ) has no significant impact on limb bud shape but only provides an increase in overall size ( Figure 4D ) . We therefore suggest that the major role of cell proliferation is simply to provide enough progenitor cells for the ongoing development of the limb and that the spatial pattern of proliferative rates is likely to reflect other constraints , such as the gradual condensation of skeletal elements in the core of the bud , which is known to correlate with reduced proliferation rates [50] . This study started with real laboratory measurements ( on shape change and cell cycle times ) , combined them into a computational model , and then ruled out isotropic cell behaviours as a possible explanation for limb bud outgrowth . It thus makes a prediction which brings us full-circle , back into the lab in search for biological evidence of oriented cell activities . Our search has been fruitful in uncovering clear evidence for a variety of oriented cell behaviours ( Figures 7 and 8 ) . The complex , extensive , and dynamic cell protrusions have not been previously described in the limb and raise a number of fascinating questions . The cell shapes themselves , plus the dynamic extension and retraction of filopodia , are indicative of active cells which could perform migration or active intercalation . The biased orientation of filopodia , Golgi , and cell divisions is not strictly distal but does display some distal bias . As a proof-of-concept we created a final simulation in which a hypothetical distal “migratory” force was added to the outward force generated by the isotropic growth pattern , creating a hybrid force field which is partly distal and partly towards the ectoderm ( reflecting our observations above ) . This resulting hybrid growth orientation was indeed able to generate a shape which resembles the real shape change ( Figure S8 ) . Cell migration has typically been studied in 2D contexts , so one possibility is that migrating cells are present but hard to identify because the genuinely 3D environment obscures any obvious leading edge and trailing edge . However an alternative ( which is not mutually exclusive ) is that the ectodermal orientation of these processes reflects an intercalatory mechanism producing a convergent-extension mode of tissue movement . In this scenario cells would be selectively pulling against their neighbours in a plane perpendicular to the PD axis ( convergence ) , and the resultant squeezing together would push cells out along the PD axis ( extension ) . Unlike classical cases of convergent-extension [48] , the convergence would be balanced by cell proliferation , such that the limb bud does not become narrower over time . The vertebrate limb may thus provide a new paradigm for understanding 3D collective cell movements which involves a complex balance of oriented cell activities . Another intriguing question is how cell mixing and/or migration can occur without the extended cellular processes becoming entangled . Interestingly , Figure 7B shows that a few cells in the field-of-view have rounded up into a spherical shape , in a manner suggestive of cell division . If cells retract their cellular processes every time they divide , as has been observed in many other systems , then this could resolve the problem of entanglement . In conclusion , we provide both theoretical and empirical evidence suggesting that distal elongation is driven by directional cell behaviours , rather than the proliferation gradient hypothesis ( or growth-based morphogenesis ) . Oriented cell activities are often controlled by the PCP system , and our prediction may therefore help explain the phenotype of Wnt5a mutants . WNT signalling is known to orient the PCP system in mesenchymal cells undergoing convergent-extension [51] , and intriguingly the phenotype of Wnt5a knock-out mouse embryos includes reduced limb bud elongation [52] .
First the tissue is washed 3 times in PBS , for 10 min each time , to wash out excess fixative . It was then embedded in 1% LMP agarose made with sterile dH2O . When set , the agarose block was trimmed with a surgical blade , ensuring adequate agarose was left surrounding the tissue , and glued to a cylindrical metal mount in the desired orientation for scanning . The samples were then placed into a clean glass container ( height 5 . 5 cm ) and tissue dehydrated at room temperature overnight by the careful addition of 100% MeOH to cover the sample . The following day , three 10 min washes are performed using MeOH , which was then replaced with BABB ( 1 part Benzyl Alcohol ( Sigma ) to 2 parts Benzyl Benzoate ( Sigma ) ) . With the lid removed , the bijou bottle is allowed to stand overnight at room temperature in a fume hood , to allow any remaining MeOH to evaporate . Samples were usually kept in BABB overnight and scanned the following day . Pregnant mice were administered IddU followed by BrdU by sequential interperitoneal injections after a defined inter-injection interval ( Ti ) of 150 min . Embryos were harvested and fixed 30 min later , as this is known to be long enough for BrdU to reach the mesenchymal cells from the maternal blood stream and incorporate into the replicating DNA [30] , [53] . Information about basic 3D image processing for OPT can be found in supplementary methods Text S1 .
|
Although the vertebrate limb bud has been studied for decades as a classical model system for the spatial control of cell fates , the question of how the limb bud physically elongates has been much less studied . One particular hypothesis has been dominant in the field , known either as the proliferation gradient hypothesis or growth-based morphogenesis . This states that elongation is achieved by distal cells ( furthest from the body ) being stimulated to divide faster than proximal cells . Importantly , this hypothesis does not propose any kind of oriented or directional cell behaviours—high distal rates of non-oriented proliferation are considered to be sufficient—and indeed several 2D computer simulations have reproduced this concept in silico . However , thus far quantitative data from the limb bud has not been incorporated into these models . Here , we extended computer simulations into 3D and incorporated quantitative data on both shape changes and proliferation rates . These new simulations demonstrated that gradients of non-oriented proliferation are unable to explain limb bud elongation . We thus experimentally tested for evidence of oriented cell behaviours and indeed found that the cell shape , Golgi orientation , and cell divisions all display a non-random bias during limb bud outgrowth . Our data run contrary to the proliferation gradient hypothesis , indicating instead that oriented cell behaviours are important for driving elongation .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Material",
"and",
"Methods"
] |
[
"computational",
"biology/systems",
"biology",
"developmental",
"biology/morphogenesis",
"and",
"cell",
"biology"
] |
2010
|
The Role of Spatially Controlled Cell Proliferation in Limb Bud Morphogenesis
|
The simian malaria parasite Plasmodium knowlesi is emerging as a public health problem in Southeast Asia , particularly in Malaysian Borneo where it now accounts for the greatest burden of malaria cases and deaths . Control is hindered by limited understanding of the ecology of potential vector species . We conducted a one year longitudinal study of P . knowlesi vectors in three sites within an endemic area of Sabah , Malaysia . All mosquitoes were captured using human landing catch . Anopheles mosquitoes were dissected to determine , oocyst , sporozoites and parous rate . Anopheles balabacensis is confirmed as the primary vector of . P . knowlesi ( using nested PCR ) in Sabah for the first time . Vector densities were significantly higher and more seasonally variable in the village than forest or small scale farming site . However An . balabacensis survival and P . knowlesi infection rates were highest in forest and small scale farm sites . Anopheles balabacensis mostly bites humans outdoors in the early evening between 1800 to 2000hrs . This study indicates transmission is unlikely to be prevented by bednets . This combined with its high vectorial capacity poses a threat to malaria elimination programmes within the region .
Significant progress has been made fighting malaria in the last decade , decreasing the incidence of cases and mortality by 30% and 47% respectively on a global scale [1] and reducing cases by 76% in Asia Pacific countries [2] . The development and use of better tools for diagnostics and treatment [3] coupled with substantial increases in the coverage of vector control methods such as Long Lasting Insecticide Treated bednets ( LLINs ) and Indoor Residual Spraying [4] have contributed to these successes . An additional challenge to malaria elimination is the existence of a zoonotic reservoir of malaria . The primate malaria Plasmodium knowlesi has recently been documented as causing human infections in multiple countries in Southeast Asia [5–11] , and is a serious public health problem within Malaysia [12–19] . In the Malaysian state of Sabah , this parasite is now responsible for the greatest number of malaria cases with 815 and 996 cases reported respectively in 2012 and 2013 [20] . This growing burden of P . knowlesi presents a notable obstacle to malaria elimination in Malaysia where historically , most transmission has been due to human-specific parasite species [17] . Since 2011 , Malaysia has made great progress towards the elimination of these human malaria species , leading to a target for complete elimination by 2020 [21] . Whether existing elimination targets can be met in the face of increasing P . knowlesi cases with this Plasmodium now causing 38% of human malaria cases in Malaysia in 2012 remains to be seen . Two features of P . knowlesi make it particularly difficult to control by conventional methods: ( 1 ) it has a sizeable zoonotic reservoir in macaques , which means that even if infections are eliminated from humans there remains a risk of future spillover , and ( 2 ) current evidence indicates that previously incriminated mosquito vectors of P . knowlesi in Malaysia bite and rest outdoors where control methods such as LLINs and IRS will not be effective [19 , 22 , 23] . Incrimination of vector species responsible of P . knowlesi transmission is a crucial first step for planning control but limited data is available on vectors of simian malaria in this region . Mosquitoes belonging to the Anopheles leucosphyrus group are thought to be responsible for P . knowlesi transmission . Anopheles hackeri was the first species to be incriminated as a vector , in the coastal area of Selangor [24] , followed by An . latens in Kapit , Sarawak [22 , 25] , An . cracens in Kuala Lipis [14 , 23] and An . introlatus in Hulu Selangor [19] . In Vietnam An . dirus , was incriminated as the P . knowlesi vector [26 , 27] . The considerable spatial variation in P . knowlesi vector species both within and beyond Malaysia reinforces the need for detailed studies of vector ecology in a localized context to guide appropriate control strategy . Anopheles balabacensis is hypothesized to be the primary vector of P . knowlesi within the current , extensive transmission foci of P . knowlesi in Sabah . Based on extensive studies carried out in the region in the 1980s [28–31] An . balabacensis was incriminated as a vector of human malaria , and laboratory studies that showed that An . balabacensis can be experimentally infected with P . knowlesi [32] . Since this early work , there has been significant ecological change occurring throughout Sabah due to conversion of forest to palm oil plantations [33–35] . How these changes have impacted the abundance , diversity and transmission potential of P . knowlesi vectors needs to be investigated . Control of P . knowlesi in Sabah requires confirmation that An . balabacensis remains the most likely vector , and characterization of its dynamics within a range of habitats that reflect current land use patterns . For that purpose , we conducted a 12 month longitudinal study within the large , ongoing focus of P . knowlesi transmission in Kudat and Banggi Island ( Kudat District ) in Sabah , aiming to characterize the abundance and biting behavior of potential vector species and incriminate vector species . These findings will be of importance to guide the development of local vector control programmes to eliminate malaria transmission .
Studies were conducted in three sites: Timbang Dayang ( TD ) ( 117°102’92”E , 7°155’85”N ) and Limbuak Laut ( LL ) 117°065’75”E , 7°215’84”N ) on Banggi island , and Kampung Paradason ( KP ) ( 116°786’35”E , 6°768’37”N on mainland Kudat ( Fig 1 ) . These sites were selected to reflect the range of ecotypes broadly representative of the study area in Northern Sabah: small scale farming ( TD ) , secondary forest ( LL ) and a village settlement ( KP ) . Sightings of macaques and recent human cases of P . knowlesi were reported near all sites . Timbang Dayang is a village with a population of 180 people . It is situated in a hilly landscape where houses are surrounded by small farming areas ~200 meters from the edge of secondary forest . These small farms ( >1 hectare ) contain mixed agriculture primarily for household consumption , including maize , banana and fruit trees . The mosquito collection site was near the edge of farm approximately 150 meters from the group of houses . Limbuak Laut ( LL ) is a village consisting of 144 people , with houses situated on a road bordering closed canopy secondary forest . Mosquito sampling was conducted at a point situated within the secondary forest , at a distance of approximately 500 meters from the edge of the forest . Paradason in Kudat is a village of 160 people situated in a heavily cultivated area , characterized by swidden farming and small plantations of rubber and palm oil . The area is undergoing a high rate of environmental change , including frequent burning and clearing of land . Little intact secondary forest remains in this area . The local community lives in both individual houses and a traditional communal longhouse shared between six households . Here mosquitoes were sampled at a point near the longhouse ( 100m ) , and in an associated garden area 75m away from the first collecting point . Mosquitoes were collected by human landing collections ( HLC ) which were carried out monthly at all sampling sites from August 2013 to July 2014 ( three nights per month at TD and LL and two nights in KP ) . Two men per team carried out collections at each site from 1800 to 0600 hrs . Mosquitoes landing on the legs of catchers were captured individually in vials which were then plugged with cotton wool and labelled by hour and collection sites . A supervisor visited the team hourly to ensure collections were being carried out . In TD and LL , collections were conducted by one team each night , whereas two teams ( situated ~75 m apart ) worked each night in Kudat . Thus a total of six individual human landing catches were performed each month in TD and LL , and eight per month at KP . In the laboratory Anopheles mosquitoes were identified using the keys of Reid ( 1968 ) and Sallum ( 2005 ) . Specimens morphologically identified as An . balabacensis were further confirmed by PCR and sequencing analysis of ITS2 and CO1 genes [19] . Anopheles mosquitoes were dissected to extract their ovaries , midguts and salivary glands to determine parity , oocyst and sporozoites respectively . All positive midguts and salivary glands , and the corresponding head and thorax of these positive specimens were transferred into individual microcentrifuge tubes containing 95% ethanol for subsequent molecular analysis . Ethanol was allowed to evaporate completely from specimen tubes by placing them in a Thermomixer ( Eppendorf , Germany ) at 70°C . Genomic DNA was extracted from the guts and glands using the DNeasy tissue kit ( Qiagen , Germany ) according to the manufacturer’s protocol . The eluted DNA was kept at -20°C until required . A nested PCR was performed to detect and identify human specific malaria parasites ( Plasmodium falciparum , P . vivax , P . malariae and P . ovale ) and P . knowlesi found in mosquitoes using primers based on the Plasmodium small subunit ribosomal RNA ( ssurRNA ) [12 , 36] . Primers and protocol used for human malaria and P . knowlesi detection were as developed by Singh et al [12] and Lee et al [37] for other simian malaria . Positive and negative controls were also included for each batch of assays . Statistical analysis was conducted using PASW Statistics 18 and R programming language for statistical analysis ( version 3 . 2 . 0 ) . Generalised linear mixed models ( GLMM ) were constructed to analyse the following parameters of interest: the abundance of An . balabacensis , their time of biting , and the proportion of vectors that were ( i ) infected with oocysts , ( ii ) infected with sporozoites , and ( iii ) that were parous . In all analyses , locality ( TD , LL or KP ) was fit as a fixed effect . Month was fit alternatively as a fixed ( to predict monthly values ) or random effect ( to test for differences between localities while controlling for seasonal variation ) . Poisson and negative binomial distributions were used separately in the analysis of mosquito abundance , while a binomial distribution was assumed in all analysis of proportion data ( parity and infection rates ) . Zero inflation in count data ( mosquito abundance ) was assessed . Models testing associations between response variables ( vector abundance , parity and infection rates ) explanatory variables ( locality and month ) and random effects of sampling night were assessed through comparison on the basis of having higher log-likelihood and lower Akaike information criterion ( AIC ) values , as well as the result of analysis of variance ( ANOVA ) of nested models ) . Tukey post hoc contrasts were used to differentiate the nature of statistical differences between localities . Graphs were produced using GraphPad Prism 6 . 0 . This project was approved by the NMRR Ministry of Health Malaysia ( NMRR-12-786-13048 ) . All volunteers who carried out mosquito collections signed informed consent forms and were provided with antimalarial prophylaxis during participation .
A total of 1884 Anopheles belonging to ten different species was obtained of which An . balabacensis predominated ( 95 . 1% of total , Table 1 ) in all sites . Other species of Anopheles were found in very low numbers and present in one or two localities only . Anopheles balabacensis was the only species from the Leucosphyrus group caught . A total of 379 Culicines were obtained but were not identified to species . The number of An . balabacensis collected in HLC ranged from ~2–28 per man night , but did not show any clear , consistent trend in seasonality ( Fig 2 ) . The pattern of seasonal fluctuation differed between sites ( Fig 2 ) . In the forest site ( Fig 2A ) , An . balabacensis abundance was relatively low ( <15 per night ) and constant across months . In the small farming site , An . balabaensis varied more than 10-fold over the course of a year , with a high in August and November , and low from February-to May and July 2014 . Anopheles balabacensis abundance was more variable in the village settlement ( Fig 2C ) . Here the highest monthly density was observed in January ( 27 per night ) with values <1 per night in October and November . Analysis using GLMM models indicated that the Poisson distribution was generally a better representation of An . balabacensis abundance data than the negative binomial . On the basis of statistical models assuming a Poisson distribution , the Tukey post hoc test indicated that An . balabancensis abundance was significantly higher in the village settlement ( KP ) than in the two other localities , ( KP and LL: ( p = 0 . 04; KP and TD: p = 0 . 02;Table 2 ) . Controlling for variation across months , An . balabancensis abundance in the village site was estimated to be ~15–20% higher than in the other localities . As shown in Fig 3 An . balabacensis started to bite as early as 1800 hours and continued to bite throughout the night until early hours of the morning . The peak biting time occurred between 1800 to 2000hrs in both LL and KP ( Fig 3A and 3C ) , accounting for 38% of the total night catch . In TD , biting rates were relatively similar between 1800-2400hrs , then began to fall with a second small peak in the early part of the morning ( 0300-0400hrs , Fig 3B ) . The parous rate of An . balabacensis was more than 50% on most collections , in all sites ( Fig 4 ) . The mean parous rate varied between 58 to 65% , with little fluctuation ( Fig 4 , Table 3 ) . Statistical analysis indicated no evidence of significant variation in parity rates between all 3 sites ( p>0 . 05 , Table 2 ) . On the basis of the parous rate , a daily survival rate [38] , life expectancy [39] and vectorial capacity values were calculated [40] for An . balabacensis at each site . Estimates of An . balabacensis survival and vectorial capacity were predicted to be higher in LL and TD compared to KP ( Table 3 ) . In LL and TD respectively , 24% and 22% of An . balabacensis would be expected to live the 10 days necessary for P . knowlesi to develop into transmission-stage sporozoites , contrasting with only 16% in KP . Those surviving the 10 days would have a further life expectancy of 7 and 6 . 7 days in LL and TD respectively , compared to 5 . 4 days in KP . Vectorial capacity was predicted to be highest in LL with an estimated value of 3 . 85 . Forty five ( 3% ) An . balabacensis out of the 1482 dissected were found to be positive for Plasmodium infection in terms of either sporozoites ( 14 ) , oocysts ( 18 ) or both ( 13 ) by microscopy . Of these only 10 salivary glands and three midguts were positive for P . knowlesi by PCR . Besides P . knowlesi other simian malaria parasites were also present as shown in Table 4 . This shows that in addition to P . knowlesi , An . balabacensis is also a vector to other simian Plasmodium species as well . Due complexity of infection the subsequent discussion refers to all Plasmodia . There was no consistent seasonal pattern of mosquito infection rates across sites ( Fig 5 ) . In LL sporozoite rates were highest from December to February ( 4–16 . 67% ) . In the TD , sporozoite rates were high in December ( 5 . 00% ) and in June to July ( 7 . 69–12 . 50% ) . In March , only three mosquitoes at TD were dissected of which two were found to be positive; one for sporozoites and one for oocyst . Thus , sporozoite rates appear to be extremely high at this time , but it is likely an artifact of low sample size . In KP the highest sporozoite rate was obtained in May 2014 ( 2 . 86% ) . The highest entomological inoculation rate ( EIR ) was 0 . 6 in TD in June . Tukey post hoc tests performed on the results of statistical models of An . balabancensis infection rates indicated there was variation between sites . Specificially , sporozoites rates were lower in KP compared to LL ( p = 0 . 04 ) , and oocyst rates were lower in KP than in TD ( p = 0 . 035 ) ( Table 2 ) . Sporozoite rates were estimated to be approximately 2 and 3 times higher in the LL and TD respectively than in KP ( Table 2 ) .
Our study provides the first evidence to confirm that An . balabacensis is the vector of the zoonotic malaria P . knowlesi within the substantial foci of human infection in Sabah . It was the predominant species found in all sites with mean biting rates ranging from 6 . 8 to 8 . 8 . A substantial proportion of An . balabacensis ( 32 . 8% ) were captured biting outdoors in the early part of the evening ( 1800–2000 ) , a time when humans would not be expected to be using LLINs , which is the current front line malaria control strategy in Malaysia . In this study all collections were made outdoors , as previous studies have found that this is where the majority of An . balabacensis ( ~76% ) host seek [28 , 41] . However , we note that total amount of human exposure to infectious bites from An . balabacensis may be even higher than indicated here if the additional contribution of limited indoor exposure were to be incorporated . In comparing the density and bionomics of An . balabancensis populations between three sites , we found evidence of geographical variation in both their abundance and sporozoite infection rate . Vector abundance was highest in the village site , whereas sporozoite rates were higher in the forest and small farming site than in the village site . However , it is unknown whether these differences are truly the result of habitat-dependent transmission efficiencies , as only one site from each ecotype was sampled . However these findings reinforces the hypothesis that spatial heterogeneity in P . knowlesi exposure risk may be driven by variation in mosquito vector demography in addition to the presence of the reservoir macaque host . Although it has been postulated that P . knowlesi was present in macaques before the arrival of humans in Southeast Asia [42] , and a large number of P . knowlesi malaria cases has been reported from Sabah [20] , the identity of the vector remained elusive . Whilst it has been demonstrated by Chin et al [43] that An . balabacensis can transmit P . knowlesi from monkey to man , man to monkey and man to man under experimental conditions , this study is the first to confirm that it acts as a vector under natural conditions . Anopheles balabacensis was also incriminated as the primary vector of human malaria in Sabah in the 1950s [44 , 45]; a role that was further supported with extensive studies in the 1980s which confirmed its role as the main vector for human malaria infections [28 , 46] . Given An . balabacensis is the likely vector of other primate malaria species in this area , it could also be the conduit for other zoonotic malaria spillovers to humans . This indicates that these Plasmodia species are not partitioned amongst different vector species , and emphasizes that An . balabacensis should be the primary target for all malaria control efforts in the area . We observed a significant difference in the Anopheles species composition found here relative to previous studies in Sabah . Currently An . balabacensis and An . donaldi constituted > 95% and 1 . 3% of all Anopheles recorded on Bangii island respectively , while studies in this area in the 1980s estimated the relative proportion of these species to 13 . 6% , and 39% of Anopheles respectively [29] . In the central region of Sabah An . donaldi was incriminated as the dominant vector for human malaria parasites in studies carried out in 2001–2002 [41] . We did not document infection in An . donaldi within this study , but this may because too few were collected ( n = 25 ) for reliable detection . Thus , we cannot dismiss the possibility that An . donaldi remains in other areas of Sabah where it is most abundant . The cause of this apparent shift in malaria vector species composition over the past 40 years in Banggi Island is uncertain although it coincides with a period of extensive deforestation in Sabah [33 , 34] . One possibility is that this is just an artefact of sampling , as here we did not conduct sampling in the exact same locations as historical studies , but instead targeted sites of known human P . knowlesi infection . These sites may have inherently higher densities of An . balabancensis ( thus triggering P . knowlesi infection ) than other locations within the area . However , there is grounds to hypothesize this could be evidence of long-term shift in species composition in response to the rapid deforestation or prolonged use of interventions such as LLINs or IRS as has been documented elsewhere [47] . In previous work within the Kinabatangan area of Sabah , we have also documented a shift from a high proportion of An . balabacensis to dominance of An . donaldi within the same sites over the period 1980s to 2000 [29 , 41] . Regardless of the explanation for the dominance of An . balabacensis within this study the relatively high survival and sporozoite rates in this vector coupled with the potentially increased contact of human-vector-macaques have likely made major contributions to the increase in P . knowlesi cases in the area . Although Sabah has reported a large number of P . knowlesi cases in the past few years especially in Kudat district , it is hypothesized that people are only getting infected when they visit forested areas . Within our current study sites , the number of malaria cases occurring over the sampling period ranged from 1 . 9 to 2 . 5 cases per 100 people [48] . As positive An . balabacensis were present in most months of the year and most of the infective mosquitoes ( 40% ) were captured biting in the early part of the evening between1800 to 2000 , people could be exposed when they return from work in or around forested areas . Our preliminary studies now and previously have demonstrated that the Anopheles mosquitoes start biting only after 1800 hrs . The average biting rate reported for An . balabacensis here is much higher than in previous studies conducted in the 1980s ( eg . 6 . 8 to 8 . 8/night compared to 0 . 75 to 4 . 44 ) [28] . These biting rates are also considerably higher than has been reported for An . latens ( 0 . 95 to 4 . 71 bites per night ) in Sarawak [22] . The high density of An . balabacensis in this area combined with its relatively high sporozoite rates with all simian malaria ( 1 . 82% ) and P . knowlesi in particular ( 0 . 67% ) indicate it is most likely responsible for the majority of transmission in this area . In this study all mosquitoes were collected using human bait , thus results are only directly informative for estimating potential human exposure and not transmission between macaques . Ideally parallel collections of mosquitoes attracted towards macaques would have been conducted but this was not possible due to logistical constraints and ethics regulations for working with macaques . Previous work [22 , 23] showed that the P . knowlesi vectors in other areas namely An . latens and An . cracens were attracted to both humans and macaques . Furthermore in Palawan Island , Philippines , An . balabacensis was more attracted to a monkey baited trap than traps baited with water buffalo or humans and individuals host seeking on macaques had oocyst and sporozoites ( although malaria species unconfirmed ) [49] . Thus , although data for mosquitoes biting macaques are not available here , we could expect , that transmission between macaques to be at least as high or much greater than predicted for humans here . To further resolve the transmission dynamics of P . knowlesi in primates , these studies should be expanded to incorporate assessment of the host preference and choice of An . balabacensis and other potential vectors most directly through analysis of the blood meals in randomly sampled resting females [50] . However , collection of recently blood fed mosquitoes resting outdoors has proved challenging . To overcome this limitation ongoing work is also investigating the use of new sampling methods to increase feasibility of such data collection in the future . The high rate of parity , survival and sporozoite infections in this mosquito indicates that An . balabcensis is a highly competent vector . With a very high vectorial capacity and life expectancy , An . balabacensis will continue to pose a risk of human infection . As Malaysia moves towards malaria elimination , breaking transmission under these conditions will be extremely challenging , further complicated by the presence of a sizeable macaque reservoir . Current frontline malaria control measures in this area are insecticide treated bednets and indoor residual spraying but more innovative control methods that specifically target outdoor biting mosquitoes such as the use of repellents or attractive toxic sugar baits will be essential .
|
The first natural infection of Plasmodium knowlesi was reported 40 years ago . At that time it was perceived that the infection would not affect humans . However , now P . knowlesi is the predominant malaria species ( 38% of the cases ) infecting people in Malaysia and is a notable obstacle to malaria elimination in the country . Plasmodium knowlesi has also been reported from all countries in Southeast Asia with the exception of Lao PDR and Timor Leste . In Sabah , Malaysian Borneo cases of human P . knowlesi are increasing . Thus , a comprehensive understanding of the bionomics of the vectors is required so as to enable proper control strategies . Here , we conducted a longitudinal study in Kudat district , Sabah , to determine and characterize the vectors of P . knowlesi within this transmission foci . Anopheles balabacensis was the predominant mosquito in all study sites and is confirmed as vector for P . knowlesi and other simian malaria parasites . The peak biting time was in the early part of the evening between1800 to 2000 . Thus , breaking the chain of transmission is an extremely challenging task for the malaria elimination programme .
|
[
"Abstract",
"Introduction",
"Methods",
"Results",
"Discussion"
] |
[] |
2015
|
Seasonal and Spatial Dynamics of the Primary Vector of Plasmodium knowlesi within a Major Transmission Focus in Sabah, Malaysia
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In Drosophila , dosage compensation augments X chromosome-linked transcription in males relative to females . This process is achieved by the Dosage Compensation Complex ( DCC ) , which associates specifically with the male X chromosome . We previously found that the morphology of this chromosome is sensitive to the amounts of the heterochromatin-associated protein SU ( VAR ) 3-7 . In this study , we examine the impact of change in levels of SU ( VAR ) 3-7 on dosage compensation . We first demonstrate that the DCC makes the X chromosome a preferential target for heterochromatic markers . In addition , reduced or increased amounts of SU ( VAR ) 3-7 result in redistribution of the DCC proteins MSL1 and MSL2 , and of Histone 4 acetylation of lysine 16 , indicating that a wild-type dose of SU ( VAR ) 3-7 is required for X-restricted DCC targeting . SU ( VAR ) 3-7 is also involved in the dosage compensated expression of the X-linked white gene . Finally , we show that absence of maternally provided SU ( VAR ) 3-7 renders dosage compensation toxic in males , and that global amounts of heterochromatin affect viability of ectopic MSL2-expressing females . Taken together , these results bring to light a link between heterochromatin and dosage compensation .
Drosophila melanogaster uses two systems of whole chromosome regulation: dosage compensation mediating the two fold up-regulation of male X-linked genes and the Painting of Fourth , POF , regulating the mainly heterochromatic fourth chromosome . Binding of POF to the fourth chromosome is dependent on the heterochromatic protein HP1 [1] . POF and HP1 colocalize on fourth chromosome-linked genes and both are involved in the global regulation of the fourth chromosome [1] , [2] . Johansson et al . ( 2007 ) proposed that POF stimulates and HP1 represses genes expression and that the interdependent binding of these two proteins precisely tunes output from the fourth chromosome . Dosage compensation targets the male X chromosome to correct the unbalance between the unique X chromosome of males and the two X chromosomes of females . To compensate for the resulting disparity in X chromosome-linked gene expression , most X-linked genes in males are hyperactivated . The Dosage Compensation Complex ( DCC ) consists of five proteins called the MSLs for Male Specific Lethal ( MSL1 , MSL2 , MSL3 , MLE and MOF ) as well as two non-coding RNAs , roX1 and roX2 ( reviewed in [3] , [4] , [5] , [6] ) . In males , the expression of MSL2 mediates the stabilization of the other proteins and the assembly of the DCC specifically on the X chromosome [7] . This results in an enrichment of acetylation of histone H4 at lysine 16 ( H4K16ac ) on the male X chromosome , due to the MOF protein of the complex [8] , [9] . The histone mark could in part explain the subsequent hypertranscription of X-linked genes in males [10] , [11] . In females , the Sex-lethal gene turns off the dosage compensation system by repressing the Msl2 translation [12] , [13] . One of the most intriguing issues of dosage compensation is the specific recognition of the male X chromosome by the DCC . Searches for X chromosomal DNA sequences determining DCC binding failed to identify a consensus sequence [14] , [15] , [16] . Global mapping of MSL proteins on the X chromosome has demonstrated that the DCC associates primarily with genes rather than intergenic regions , displays a 3′- bias and correlates with transcription [14] , [16] , [17] . Moreover , the MSL complex is attracted to genes marked by H3K36 trimethylation , a mark of active transcription [18] . Furthermore , the levels of DCC proteins MSL1 and MSL2 are critical for correct targeting to the X chromosome [19] . Over-expression of both msl1 and msl2 results in inappropriate MSLs binding to the chromocenter and chromosome 4 [19] , [20] . MSL2 , deleted of its C-terminal part , binds as a complex with MSL1 to the heterochromatic chromocenter [21] . roX RNAs are also key components for X chromosome targeting since roX1roX2 mutants cause relocation of MSLs complex to autosomal regions and the chromocenter [22] , [23] . These data reveal an unpredicted physical association between the MSL complex and heterochromatic regions . H4K16 acetylation is not the only chromatin mark distinguishing the Drosophila male X chromosome from the autosomes . Phosphorylation of H3 at serine 10 , catalyzed by JIL-1 , is a histone modification highly enriched on the male X chromosome [24] . The JIL-1 kinase interacts with the DCC and is involved in dosage compensation of X-linked genes [25] , [26] . Interestingly , Jil-1 mutant alleles affect both condensation of the male X chromosome and expansion of heterochromatic domains , providing evidence for a dynamic balance between heterochromatin and euchromatin [27] , [28] . Other general modulators of chromatin state , as ISWI or NURF , are also required for normal X chromosome morphology in males [29] , [30] , [31] . The NURF complex and MSL proteins have opposite effects on X chromosome morphology and on roX transcription [32] . We have discovered previously an intriguing genetic interaction between the heterochromatic proteins SU ( VAR ) 3-7 and HP1 , and dosage compensation [33] . Su ( var ) 3-7 encodes a protein mainly associated with pericentromeric heterochromatin and telomeres , but also with a few euchromatic sites [34] , [35] , [36] . Specific binding to pericentric heterochromatin requires the heterochromatic protein HP1 [33] . HP1 localizes to heterochromatin through an interaction with methylated K9 of histone H3 ( H3K9me2 ) , a heterochromatic mark mainly generated by the histone methyltransferase SU ( VAR ) 3-9 [37] , [38] , [39] . SU ( VAR ) 3-7 interacts genetically and physically with HP1 [35] , [36] and with SU ( VAR ) 3-9 [38] , [40] . Su ( var ) 3-7 , Su ( var ) 2-5 encoding HP1 and Su ( var ) 3-9 are modifiers of position effect variegation ( PEV ) , the phenomenon of gene silencing induced by heterochromatin [34] , [41] , [42] ( reviewed in [43] , [44] ) . These three genes enhance or suppress the PEV depending on their doses and thus are considered as encoding structural components of heterochromatin [45] . Strikingly , the amounts of SU ( VAR ) 3-7 and HP1 affect male X chromosome morphology more dramatically than other chromosomes . Reduced doses of SU ( VAR ) 3-7 or HP1 result in bloating of the X chromosome specifically in males [33] . Increased doses of SU ( VAR ) 3-7 cause the opposite phenotype , a spectacular condensation of the X chromosome associated with recruitment of other heterochromatin markers [40] . Some unique feature of the male X chromosome makes it particularly sensitive to change in SU ( VAR ) 3-7 amounts . In addition , knock-down of Su ( var ) 3-7 results in reduced male viability leading to a 0 . 7 male/female ratio in the progeny of Su ( var ) 3-7 homozygous mutant mothers [40] . The possibility of interaction between activating and repressive chromatin factors on the male X chromosome led us to analyze the impact of SU ( VAR ) 3-7 on dosage compensation . In this study we show that wild-type levels of SU ( VAR ) 3-7 are required for male X chromosome morphology , X chromosome-restricted DCC targeting , expression of P ( white ) transgenes in males and for coping with increased MSL1 and MSL2 levels . We provide evidence for interplay between heterochromatin and dosage compensation in Drosophila .
An excess of SU ( VAR ) 3-7 induces male and female lethality and causes spectacular changes in the morphology of polytene chromosomes [40] . The male X chromosome is always the most affected chromosome: it becomes highly condensed and shortened and its characteristic banding pattern is modified . To test whether the Dosage Compensation Complex is required for the male X chromosome phenotypes , we over-expressed Su ( var ) 3-7 in a mutant for the DCC and we examined the morphology of the X chromosome ( Figure 1 ) . Homozygous mutants in mle , the gene encoding the RNA helicase component of the DCC , do not compensate for dose and die at the third-instar larval stage , late enough to permit examination of polytene chromosomes [46] , [47] . The combination of mle1 with a transgene over-expressing Su ( var ) 3-7 ( P[HA: SuvarFL4D] [48] ) , results in an almost normal male X chromosome morphology whereas brothers in the same progeny heterozygous for the mle1 mutation still display strong condensation of the X chromosome ( Figure 1A ) . Thus , the condensation process of the male X chromosome in presence of an excess of SU ( VAR ) 3-7 requires the Dosage Compensation Complex . We had shown previously that the male X chromosome condensation coincided with association of SU ( VAR ) 3-7 all along the X chromosome and recruitment of the heterochromatic proteins HP1 and H3K9me2 [40] . To test whether the enrichment of heterochromatic markers on the male X chromosome requires the presence of the DCC , we performed immunostaining on male larvae expressing the Su ( var ) 3-7 transgene together with the mle1 mutation . In homozygous mle1 larvae over-expressing Su ( var ) 3-7 , SU ( VAR ) 3-7 , HP1 and H3K9me2 enrichment on the male X chromosome is lost in contrast to the heterozygous mle brothers of the same cross ( not shown , and Figure 1B ) . We conclude that association of the DCC on the X chromosome is required to make the X chromosome a preferential target for heterochromatic markers in a context of high levels of SU ( VAR ) 3-7 . Then , to test whether the DCC is not only necessary but also sufficient for the altered morphology of the X chromosome , we examined X polytene chromosomes of females expressing the Su ( var ) 3-7 transgene and the DCC ( Figure 2 ) . Dosage compensation in females was artificially induced by a transgene expressing MSL2 under the control of the hsp83 promoter [7] . The expression of msl-2 in females over-expressing Su ( var ) 3-7 causes the X chromosomes to condense as typically seen only in males over-expressing Su ( var ) 3-7 ( Figure 2A ) . Furthermore , assembly of the DCC on the X chromosomes in these females leads to an enrichment of SU ( VAR ) 3-7 binding on the X chromosomes , but also of HP1 and H3K9me2: the heterochromatic markers enrichment on the X chromosomes is more or less abundant according to the strength of the heat-shock inducing expression of Su ( var ) 3-7 ( Figure 2 B , 2C , and not shown ) . This X chromosomes coating by heterochromatic markers is never observed in wild type females ( not shown and [40] ) . The Dosage Compensation Complex is therefore not only necessary but also sufficient to allow the massive recruitment of heterochromatic proteins on the X chromosomes induced by high levels of SU ( VAR ) 3-7 . On the condensed male or female X chromosomes , MSL2 does not colocalize with the heterochromatic proteins: some regions of the X chromosome enriched for SU ( VAR ) 3-7 and HP1 are almost devoid of MSLs and inversely ( Figure 2D ) . The dosage compensation complex renders the X chromosomes especially attractive to the SU ( VAR ) 3-7/HP1 complex , when in large amounts , but its binding pattern differs from that of MSLs . To test whether SU ( VAR ) 3-7 is recruited by the DCC , we examined whether a P[w+GMroX1] transgene , known to recruit the DCC when inserted on an autosome [49] , is able to attract SU ( VAR ) 3-7 and HP1 at its insertion site . Three P[w+GMroX1] insertions ( at 85D , 69C , 79B [50] ) were tested by immunostaining on males salivary gland polytene chromosomes , with antibodies against MSL2 as a control for efficient DCC assembling at the insertion site and against SU ( VAR ) 3-7 and HP1 for the creation of a new binding site at these locations . Although strong MSL2 staining was detected at the autosomal site of the three lines , neither SU ( VAR ) 3-7 nor HP1 were detected at these cytological locations ( not shown ) . We conclude that the DCC binding to the roX1 transgene does not recruit detectable amounts of SU ( VAR ) 3-7 and HP1 proteins . In addition , we crossed the transgenic P[w+GMroX1] males with wild type females , or females homozygous mutants for Su ( var ) 3-7 , in order to test whether reduced SU ( VAR ) 3-7 amounts modify the extent of MSLs spreading around the insertion [49] . We did not observe significant changes of the local MSL spreading in the absence of maternal SU ( VAR ) 3-7 ( not shown ) . However , we were surprised to note that the expression of the white gene , a reporter gene within the transgene , was modified by the absence of maternal SU ( VAR ) 3-7 product in the three lines ( Figure 3 and not shown ) . The well-known X-linked white gene and its truncated version mini-white retain full dosage compensation on the X and partial dosage compensation when transposed to autosomes [51] . Our observation that white expression is specifically reduced in males in the crosses that lack maternal SU ( VAR ) 3-7 leads us to conclude that SU ( VAR ) 3-7 specifically regulates white expression in males . This suggests an implication of SU ( VAR ) 3-7 in dosage compensation . We wondered then whether the wild type dose of SU ( VAR ) 3-7 is required for correct MSLs localization . We have shown that in hypomorphic Su ( var ) 3-7 mutants , MSLs staining appears globally unmodified on the bloated X chromosome ( [33] and Figure 4 ) ; MSL1 , MSL2 and H4K16ac are still present at hundreds of sites on the male X chromosome and at very few sites on autosomes . Interestingly , in more severe Su ( var ) 3-7 mutant conditions , we did detect changes in MSLs localization: in Su ( var ) 3-7R2a8 or in Su ( var ) 3-79 homozygous mutant larvae raised at 29°C , MSL1 and MSL2 proteins are clearly visible at the chromocenter in proportions that are never observed in wild-type males raised in the same condition ( Figure 4 and Figure S1 ) . The enrichment at pericentromeric heterochromatin is also visible for H4K16ac in Su ( var ) 3-7 mutant larvae , meaning that the MSL complex delocalized at heterochromatin is enzymatically active ( Figures 4 and Figure S1 ) . These results show that reducing the amounts of SU ( VAR ) 3-7 delocalizes the MSLs towards heterochromatin . Next , we compared MSLs staining in presence of increased levels of SU ( VAR ) 3-7 . In wild-type males , the MSL1 protein accumulates at hundreds of sites on the X chromosome and is associated with 5 +/− 1 sites on autosomes ( Figure 5 ) . The number of autosomal sites increases to thirty on polytene chromosomes from heat-shocked larvae containing one copy of the Su ( var ) 3-7 transgene . With two copies of the transgene , the number of autosomal sites reaches a hundred , and MSL1 exhibits a decreased affinity for the X chromosome ( Figure 5 ) . Similar delocalization on autosomes is visible for MSL2 and H4K16ac ( not shown and Figure 5 ) . This indicates that the complex is still enzymatically active on autosomes . Staining by MSL1 , MSL2 or H4K16ac of the chromocenter and of chromosome 4 is not detected . For the three proteins , the delocalization on autosomal sites is proportional to the dose of SU ( VAR ) 3-7 . As controls , absence of heat-shock in the Su ( var ) 3-7 homozygous transgenic line and heat shock in wild-type did not cause MSLs nor H4K16ac delocalization ( Figure 5 and not shown ) . In sum , high levels of SU ( VAR ) 3-7 in males lead to recruitment of heterochromatic proteins on the X chromosome and concomitantly to delocalization of the MSLs on autosomes , suggesting an antagonism between heterochromatin and the DCC . We conclude that wild-type levels of SU ( VAR ) 3-7 are required for X chromosome-restricted binding of the MSLs . Phenotypes of MSLs relocation on autosomes or at chromocenter due to changes in SU ( VAR ) 3-7 levels resemble those due to changes in levels of the MSLs [19] , [20] . Su ( var ) 3-7 mutations could therefore lead to the production of an altered DCC by modifying expression of genes encoding components of the complex . We first compared MSL1 and H4K16ac levels in wild-type and Su ( var ) 3-7 mutant third instar larvae by Western blot analysis . We did not detect changes ( not shown ) . We have also tested by quantitative reverse-PCR the level of transcription of msl1 , msl2 , msl3 , mof , mle , roX1 and roX2 genes in wild-type and Su ( var ) 3-7 male mutant larvae . We did not detect either significant changes in the levels of transcription of any of these genes ( Figure 6 ) . This indicates that SU ( VAR ) 3-7 does not regulate directly the expression of dosage compensation genes , but rather acts at the level of the X chromosome chromatin conformation . We then addressed the question of whether the striking displacement of the DCC on autosomes in presence of an excess of SU ( VAR ) 3-7 modifies the level of expression of the dosage-compensated white gene when located either on the X chromosome or on autosomes . The white gene harboured by P transgenes can indeed easily be moved to different places in the genome while conserving its dosage compensated expression [51] . white expression was monitored by the levels of eye pigments . Females homozygous for a P ( mini-white ) transgene ( described in Materials and Methods ) were crossed either to wild type males or to males harbouring the heat-shock transgene over-expressing Su ( var ) 3-7 . F1 progeny from both crosses was submitted to daily heat-shocks at 35°C from third instar larval stage to adulthood . We tested 12 lines harbouring the P ( mini-white ) transgene: six out of twelve contain a transgene on the X chromosome , and in the six others the transgene is on an autosome . Interestingly , for none of the six lines containing the P ( mini-white ) on autosomes was eye colour modified in male or female by increased Su ( var ) 3-7 expression compared to wild type dose of SU ( VAR ) 3-7 ( an example is given in Figure 7 ) . In contrast , for five out of six lines harbouring the P ( mini-white ) on the X chromosome , F1 males displayed lighter eyes in presence of over-expressed Su ( var ) 3-7 than in wild-type context . On the other hand , female eye colour from these crosses did not change with the dose of SU ( VAR ) 3-7 ( Figure 7 ) . As control , we verified that repression of white gene never occurs in not heat-shocked crosses nor in crosses with wild-type dose of SU ( VAR ) 3-7 submitted to daily heat-shocks ( not shown and Figure 7 ) . As for the sixth P ( mini-white ) line on the X , overproduction of SU ( VAR ) 3-7 in this line killed the males , whereas females were perfectly viable . This unexplained male lethality prevented us to conclude on the effect of over-expressing Su ( var ) 3-7 on male eye colour . In sum , these data show that an increased dose of SU ( VAR ) 3-7 reduces specifically in males the level of expression of the dosage compensated white gene , when and only when this gene is on the X chromosome . The remarkable effect of SU ( VAR ) 3-7 on the dosage compensated white gene led us to wonder whether SU ( VAR ) 3-7 is required for dosage compensation of other X-linked genes . Expression of seven X-linked genes and two autosomal genes were analyzed by quantitative RT-PCR in third instar larvae of wild type and Su ( var ) 3-7 null mutant male . We analyzed transcripts levels of the seven dosage-compensated genes arm , BR-C , CG14804 , dspt6 , Gs2 , Pgd , mRpL16 and of two autosomal genes , RNApolII and tubulin α . The levels of transcripts were normalized to efg1 and gapdh autosomal genes as internal standard . We did not detect significant modifications of expression of these X-linked genes in Su ( var ) 3-7 mutant males larvae compared to autosomal genes ( Figure S2 ) . These results indicate that the lack of SU ( VAR ) 3-7 does not significantly modify the transcription level of a set of X-linked genes . To investigate further the implication of SU ( VAR ) 3-7 on dosage compensation , we wondered whether the amounts of SU ( VAR ) 3-7 have an impact on male viability . Indeed , knock-down of Su ( var ) 3-7 results in significantly more lethality in males than in females [52] . It is however difficult to compare male and female viability as they differ by many factors as sex differentiation , dosage compensation , heterochromatin amounts , etc . We therefore examined viability among males with modified DCC activities . In a Su ( var ) 3-7 mutant background , we compared the viability of males in presence of different amounts of MSLs proteins by using transgenes expressing MSL1 and MSL2 under the control of the hsp83 promoter [7] , [53]: The transgenes do not affect the viability of otherwise wild-type males ( Table 1 ) . But the absence of maternal SU ( VAR ) 3-7 kills the males harbouring the transgenes: homozygous Su ( var ) 3-7R2a8 females crossed with transgenic ( H83MSL1-H83MSL2 ) males produce only 6% of male adult progeny harbouring the transgenes compared to 48% if the mothers are heterozygous for a Su ( var ) 3-7 mutation . However , with mothers homozygous mutant for another heterochromatic component , the SU ( VAR ) 3-9 histone-methyl-transferase , we found no effect on the viability of males . The absence of maternal SU ( VAR ) 3-7 product specifically renders increased MSL1 and MSL2 expression toxic to males . In Drosophila , the Y chromosome is 20 Mbases long and is made almost entirely of heterochromatin [54] . To test whether the global amount of heterochromatin has an influence on the DCC activity , we crossed either wild-type females or females engineered to expressing msl2 by carrying the msl2 transgene ( H83MSL2 [7] ) to males bearing a compound X-Y chromosome ( C ( 1:Y ) yw ) . These crosses produce males lacking the Y chromosome ( X/0 ) and females containing a Y chromosome ( XXY ) . Details of the crosses and of their offspring are given in Materials and Methods and in Supporting Information Table S1 . In the control crosses , female viability is slightly modified by the presence of a Y chromosome ( female/male ratio: 0 . 72 ) and viability of XX females is not altered by the presence of the msl2 expressing transgene thanks to a mutation into the endogenous msl1 gene ( female/male ratio 0 . 96 ) . However the combination of the msl2 transgene and additional heterochromatin provided by the extra Y chromosome affects severely the viability of females ( female/male ratio 0 . 26 ) . The effect on viability lends weight to a model whereby dosage compensation is sensitive to heterochromatin .
Reduced levels of SU ( VAR ) 3-7 induce bloating of the male X chromosome , whereas increased levels cause condensation of the male X chromosome [33] , [40] . Moreover , at high dose , SU ( VAR ) 3-7 , normally restricted to heterochromatin , invades preferentially the male X chromosome and , to a lesser extent , the autosomes [40] . These observations led us to investigate the features rendering the male X chromosome particularly sensitive to SU ( VAR ) 3-7 . In this paper we have examined the genetic interaction between a gene essential for dosage compensation , mle , and Su ( var ) 3-7 on the morphology of the male X chromosome . Bloating and shrinking of the X chromosome both require the presence of the DCC , and assembly of the DCC in females is sufficient to make their X chromosomes preferential targets for SU ( VAR ) 3-7 , when in excess ( Figures 1 and 2 ) . The dosage compensation system is thus responsible for the sensitivity of the male X chromosome to changes in SU ( VAR ) 3-7 amounts . One explanation for the X chromosome sensitivity is that increased levels of H4K16 acetylation induced by the DCC render chromatin of the male X chromosome more accessible to chromatin factors and more sensitive to disturbances than other chromosomes [3] , [4] , [55] . We cannot exclude the possibility that SU ( VAR ) 3-7-induced X chromosome defects are indicators of a more general effect of the protein on all chromosomes as described for ISWI: Null mutations in the gene encoding ISWI cause aberrant morphology of the male X chromosome but not of autosomes and females X chromosomes [29] , but expression of a very strong dominant negative form of ISWI in vivo leads indeed to decondensation of all chromosomes in both sexes [56] . Nevertheless other data in our work discussed later favour the hypothesis whereby X chromosome defects result from a specific interaction between SU ( VAR ) 3-7 and dosage compensation . Male X chromosome sensitivity to SU ( VAR ) 3-7 was rather unexpected , as in a wild-type context , in contrast to over-expression conditions , we did not detect preferential binding of SU ( VAR ) 3-7 to the male X chromosome . The absence of detectable SU ( VAR ) 3-7 enrichment on the male X polytene chromosome from third instar larvae may be due either to lack of sensitivity of the immunostaining procedure or to observations made in inappropriate tissues or development stages . Similar puzzling observations have been made for HP1 , which is not preferentially seen on the male X polytene chromosomes , although reduced HP1 induces bloating of the male X chromosome [33] , [57] , [58] , [59] . In cultured cells however , a moderate HP1 enrichment was detected with the DamID technique on the male X chromosome and not on the female X chromosomes [60] , suggesting that HP1 participates in the structure of the male X chromosome . A striking and novel result of this study is that precise wild-type amounts of the heterochromatic protein SU ( VAR ) 3-7 are required to restrict MSLs binding to the X chromosome . In Su ( var ) 3-7 mutants , we have observed that the MSL proteins are recruited to the chromocenter ( Figure 4 and Figure S1 ) . Furthermore , when SU ( VAR ) 3-7 is present in excess , MSLs are massively delocalized from the X chromosome to many sites on autosomes ( Figure 5 ) . We propose two hypotheses . First , the effect of SU ( VAR ) 3-7 on the MSLs distribution is indirect and due to the regulation of the expression of a component of the DCC . Indeed , increased amounts of MSL1 and MSL2 lead to MSLs binding on autosomes and at chromocenter [19] , [20] , [61] , and MSLs delocalization from the X chromosome to autosomes and chromocenter is detectable in roX1roX double mutants [22] , [23] . A careful regulation of MSLs and roX RNAs concentration is therefore important to restrict DCC activity to appropriate targets . In addition , increased levels of MSL2 , or of both MSL2 and MSL1 , result in a diffuse morphology of the X chromosome [7] , [20] , [53] . This phenotype resembles the bloated X chromosome of Su ( var ) 3-7 and Su ( var ) 2-5 mutants , suggesting that the amounts of MSL2 and MSL1 are downregulated by the heterochromatic proteins . Expression of many euchromatic genes are under the control of the HP1 protein [62] , [63] , [64] , [65] , leading us to test whether changes in SU ( VAR ) 3-7 amounts modify the expression of roXs , msl1 and msl2 or the stability of MSL1 and MSL2 . Quantitative RTPCR ( Figure 6 ) and Western blots did not detect significant changes in the amounts of DCC components . In HP1 mutant msl1 transcription is also not affected [66] . These results speak against the hypothesis of regulation of expression of a DCC component by a SU ( VAR ) 3-7/HP1 complex . The second hypothesis is that SU ( VAR ) 3-7 modifies the MSLs distribution by changing the chromatin state of the X chromosome and of the pericentric heterochromatin . Changes in chromatin conformation or epigenetic marks could modify affinity of the DCC for entry sites [15] , [67] . Demakova et al . [19] and Dahlsveen et al . [15] have described numerous entry sites on the X chromosome , and have suggested a hierarchy of entry sites with different affinities for the DCC . Even cryptic binding sites on autosomes and at the chromocenter are recognized by the DCC in certain conditions . We propose that increasing SU ( VAR ) 3-7 amounts on the X chromosome results in an enrichment of HP1 and H3K9 dimethylation [40] , and leads to a more compact heterochromatic-like structure of the X chromosome which then blocks access to the high-affinity entry sites . The free DCC , chased from the X chromosome sites turns toward low-affinity sites present on autosomes , but not toward those embedded into the chromocenter . Indeed , cryptic chromocenter sites become more inaccessible by heterochromatin compaction [40] , a phenomenon also responsible for the enhancement of variegation by increased SU ( VAR ) 3-7 levels [40] . Inversely , the absence of SU ( VAR ) 3-7 induces a more relaxed chromatin state at the chromocenter [33] , thus increasing affinity of the entry sites embedded into heterochromatin , and allowing MSLs binding at the chromocenter . Similar recruitments of MSLs at heterochromatin have been described in the literature in three situations: in roX1roX2 mutants [22] , [23] , in presence of excess of MSL2 [19] and in C-terminal truncated MSL2 mutants [21] . This means that cryptic entry sites present in heterochromatin become more accessible to the MSLs either in a Su ( var ) 3-7 mutants or if DCC composition is modified . The explanation of heterochromatin affinity for the MSLs remains obscure . On the X chromosome , the Su ( var ) 3-7 mutation induces the bloated morphology resembling that described as a result of decreased levels of silencing factors as HP1 , ISWI and NURF [29] , [30] , [33] , or of increased MSLs levels [20] . Our study and others suggest that male X chromosome morphology depends on the balance between silencing and activating complexes [2] , [27] , [28] , [32] . The simultaneous existence of the repressive SU ( VAR ) 3-7/HP1 proteins and the MSLs complex may provide a set of potential interactions that cumulatively regulate dosage compensation [6] . Several arguments support a role for SU ( VAR ) 3-7 in dosage compensation . Reduced male viability in the progeny of Su ( var ) 3-7 homozygous females is a first argument for a function played by the protein specifically in males [52] . Our results also show that wild-type amounts of SU ( VAR ) 3-7 are required to cope with increased MSL1 and MSL2 levels . In absence of maternal SU ( VAR ) 3-7 product , the transgenes expressing MSL1 and MSL2 become toxic to males , whereas no lethality is observed with wild-type or half amounts of SU ( VAR ) 3-7 ( Table 1 ) . This suggests that SU ( VAR ) 3-7 is required very early in development to counteract an excess of MSL1 or MSL2 activity . Corroborating this effect , we determined that the global amount of heterochromatin affects the viability of females engineered to expressing msl2 . The presence of the highly heterochromatic Y chromosome kills half of the females expressing msl2 . As proposed by Weiler and Wakimoto [68] , [69] , the Y chromosome functions as a sink for heterochromatic factors as SU ( VAR ) 3-7 and HP1 [68] , [69] . A Y chromosome added to XX females could sequester heterochromatic proteins , and induce lethality in a context of female dosage compensation . All these data lead to the conclusion that SU ( VAR ) 3-7 is required for the viability of dosage-compensated flies . We propose two explanations: Either SU ( VAR ) 3-7 is required to restrict DCC on the X chromosome , and the lethality induced by the lack of SU ( VAR ) 3-7 is due to the MSLs ectopic activity outside of the X chromosome ( at heterochromatin ) , or SU ( VAR ) 3-7 is required on the dosage compensated X chromosome and , in this case , the Su ( var ) 3-7 mutant lethality results from malfunctioning of the DCC on the X . To discriminate between these two hypothesis , we examined expression of X-linked genes in Su ( var ) 3-7 mutants ( Figure S2 ) . Although small changes are visible , the RT-PCR analysis did not allow us to conclude that the lack of SU ( VAR ) 3-7 affects significantly the levels of transcripts of seven X-linked genes . If they exist , changes were indeed expected to be very small . For MSLs mutations , the magnitude of the decrease is very modest considering the severe failure of dosage compensation ( around 1 . 5 [10] , [11] ) . Taking into account that the Su ( var ) 3-7 mutation induces only 30% lethality among males , expected changes in transcript accumulation are predicted to be even smaller . Moreover , transcripts analysis was done in male larvae and some slight biological variations between our three samples cannot be avoided though great care was taken on samples homogeneity . Finally , normalizing to internal autosomal genes RNA could also introduce a bias [6] . We believe that in our case , quantitative RT-PCR experiment was not the appropriate method to detect very small changes of expression . In consequence , we have used an alternative system to test the implication of SU ( VAR ) 3-7 on dosage compensation . We have determined the effect of increased or decreased Su ( var ) 3-7 expression on the dosage compensated expression of the white gene carried by P transgenes . Strikingly , we observed that lack and excess of SU ( VAR ) 3-7 decreases the white expression specifically in males , and never in females ( Figures 3 and 7 ) . This is a strong indication that the wild type dose of SU ( VAR ) 3-7 is required for correct dosage compensated expression of the white gene . Interestingly , Su ( var ) 3-7 over-expression affects white expression when the gene is localized on the X chromosome and not on autosomes , although white is still partially dosage compensated on autosomes [51] . This may result from the combination of two phenomena: On the X chromosome , excess of SU ( VAR ) 3-7 induces preferential enrichment of heterochromatic silencing proteins and partial loss of MSLs . On autosomes , heterochromatic proteins recruitment is less visible and , in addition , the MSLs are massively present [40] ( Figure 5 ) . Consequently the dosage compensation of a P ( white ) transgene linked to the X chromosome is more likely to be perturbed by excess of SU ( VAR ) 3-7 than an autosomal insertion . In sum , we have revealed in this study a role for SU ( VAR ) 3-7 on global X chromosome morphology with an impact on the distribution of MSLs proteins , thus highlighting the contribution of SU ( VAR ) 3-7 to the intriguing issue of X specific DCC targeting . It appears also that SU ( VAR ) 3-7 is required for the viability of dosage compensated flies and the expression of a dosage compensated X-linked gene , suggesting a puzzling interplay between heterochromatin and the DCC . SU ( VAR ) 3-7 plays a subtle role on dosage compensation: Flies need SU ( VAR ) 3-7 , especially the maternal protein , for correct dosage compensation but , at the same time , excess of SU ( VAR ) 3-7 has a negative effect on dosage compensation . Our future interest will focus on the fascinating issue of the molecular nature of heterochromatin/DCC intersection .
Su ( var ) 3-7 over-expression: heat-shocks were carried out on Drosophila melanogaster lines containing the inducible Su ( var ) 3-7 transgene P ( HA:SuvarFL ) ( lines 1A and 4D [48] ) and on the yw67 control line . Egg laying was at 25°C for 24 hours , and larvae were incubated at 30°C for two days . Three heat-shocks of 30 minutes at 35°C were then performed each day until adulthood . Su ( var ) 3-7 mutants: we used the null mutant Su ( var ) 3-7R2a8 [33] raised at 25°C and the hypomorphic Su ( var ) 3-79 mutant [52] raised at 29°C . P ( mini-white ) stocks were kindly provided by D . Pauli . Flies harbour one P ( UASt mini-white ) transgene localized at different locations on the X or on autosomes [70] . The P ( UASt mini-white ) transgenes harbor different cDNA sequences that are not expressed due to the lack of GAL4 drivers . - To test whether reduced SU ( VAR ) 3-7 amounts modify the extent of MSLs spreading around a P[w+GMroX1] transgene insertion [49] , we crossed ten transgenic ywroX1ex6/Y;P[w+GMroX1] males ( from three lines with insertion at 85D , 69C or 79B kindly provided by R . Kelley [49] ) to ten wild type ( w1118 ) females or w1118; Su ( var ) 3-7R2a8 homozygous females . Male larvae were collected for immunostaining and male adults were kept to examine the effect of the lack of maternal SU ( VAR ) 3-7 on white expression . Eyes of adult flies from several crosses replica were examined five days after hatching . - To test the effects of increased SU ( VAR ) 3-7 amounts on white expression of P ( mini-white ) transgenes , ten P ( mini-white ) homozygous females were crossed at 25°C either to wild-type males or to males harbouring the transgene that over-expresses Su ( var ) 3-7 by heat-shock induction [48] . Progeny from both crosses was submitted to daily heat-shocks at 35°C from the third instar larval stage to adulthood or were kept at 25°C for all development . Eyes of adult flies from several crosses replica were examined five days after hatching . - The genetic crosses shown in Table 1 were realized as follows: Fifteen w1118; Su ( var ) 3-7R2a8 homozygous or heterozygous females were crossed at 25°C with fifteen w/Y; msl2 cn; H83MSL1-H83MSL2/+ males . Progeny w; msl2 cn/+; Su ( var ) 3-7R2a8/+ with ( red eyes ) or without ( white eyes ) the H83MSL1-H83MSL2 transgenes was counted . Dramatic difference in males viability was observed depending upon whether or not the mother supplied wild type SU ( VAR ) 3-7 protein in the egg . Similar crosses were done with wild-type and Su ( var ) 3-917 homozygous females . - To test the effect of an additional Y chromosome in females that ectopically express MSL2 [7] , fifteen wild type ( w1118 ) females or yw; msl1/Cyo; P ( w+H83-MSL2 ) 6I/P ( w+H83-MSL2 ) 6I females were crossed at 25°C either to males bearing a compound X-Y chromosome ( C ( 1;Y ) yw ) or to w1118 males . In the F1 , all the females and males were counted without discriminating the presence of the CyO balancer or of the chromosome II with the endogenous msl1 mutation . In fact 95% the F1 females carry the endogenous msl1 mutation that supports their survival . Crosses were done several times and the percentage of males and females obtained in each cross is given in Supporting Information Table S1 . Orcein stainings of polytene chromosomes were done as in [33] . Procedures for immunostaining were those of Platero et al . , [71] with the following modifications: fixation and squashing were done in 4% formaldehyde . Primary antibodies were used at the following dilutions: 1∶10 for anti-SU ( VAR ) 3-7 [35] , 1∶400 for anti-HP1 ( a gift of Lori Wallrath ) and 1∶200 for anti-MSL2 and anti-MSL1 ( gifts of M . Kuroda ) , and for anti-H4K16ac ( a gift of Brian Turner ) . For immunostaining experiments , two independent Hs-Su ( var ) 3-7 transgene insertions and two independent Su ( var ) 3-7 mutants have been studied to avoid genetic background effect . For each staining , mutant and wild-type larvae were always treated together; salivary glands were squashed in the same conditions , incubated with the same antibodies preparation , and analyzed in same exposure conditions . Each experiment was done several times . RNA was isolated from 30 male third instar larvae using Trizol ( Invitrogen ) . After DNase treatment ( Ambion DNA free™ ) , one µg of total RNA was used to make cDNA using random hexamers and the Supercript II reverse transcriptase ( Invitrogen ) . Linear real time PCR was performed using Power SYBR Green Master Mix ( Applied Biosystems ) , on a SDS 7900 HT instrument ( Applied Biosystems ) with the following parameters: 50°C for two minutes , 95°C for ten minutes , and 45 cycles of 95°C 15 secondes−60°C one minute . Each gene was tested with specific primers designed using the program Primer Express v 2 . 0 ( Applied Biosystems ) with default parameters . Oligonucleotides sequences will be provided on request . Triplicates of samples and triplicates of PCR were performed and the results obtained for each tested genes were normalized with two or four control genes treated in parallel ( tubulin α , RP49 , RNA pol II , EFG1 ) . Raw Ct values obtained with SDS 2 . 2 ( Applied Biosystems ) were imported in Excel and normalisation factor and fold changes were calculated using the GeNorm method [72] . Real-time PCR and data analysis were performed at the Genomics Platform , NCCR “Frontiers in Genetics” ( http://www . frontiers-in-genetics . org/genomics . htm ) . Brains of 20 third instar larvae were dissected in Ringer and resuspended in SDS lysis buffer ( 1% SDS , 10 mM EDTA , 50 mM Tris-HCl , pH 8 ) [73] . Proteins in samples were dosed using the BCA™ Protein Assay Kit ( Pierce ) . Samples ( 5 µg or 10 µg of proteins ) were separated on SDS PAGE and transferred on a PVDF membrane ( Millipore ) . Membranes were blocked in TBS , 0 . 1% tween , 5% dry milk or BSA with α-MSL-1 ( 1/500 ) α-tubulin ( 1/2000 ) ( Sigma T 9026 ) , α-H4K16ac ( 1/50 ) , α-H3 ( 1/5000 ) ( Abcam 1791 ) . Membranes were washed with TBS , 0 . 1% Tween , incubated with secondary antibodies coupled to HRP and revealed by chemiluminescence .
|
In Drosophila , females have two X chromosomes and males only one . The difference in the dose of X-associated genes is compensated by male-specific protein machinery , the Dosage Compensation Complex ( DCC ) , which augments the activity of genes of the single male X . We report that the specific targeting of the DCC on the male X chromosome depends critically on the correct dose of the SU ( VAR ) 3-7 protein . This protein was previously known to associate with condensed and silenced regions of the chromosomes called heterochromatin by contrast with the active form of chromatin called euchromatin . Loss of SU ( VAR ) 3-7 in males causes displacement of the DCC to heterochromatin and bloating of the X chromosome . In contrast , excess of SU ( VAR ) 3-7 leads to a delocalization of the DCC to other chromosomes and to massive shrinking of the X chromosome . We show that SU ( VAR ) 3-7 is involved in the dosage compensated expression of the X-linked white gene and in the viability of dosage compensated flies . Altogether , these results bring to light a link between silencing mechanisms of heterochromatin and mechanisms controlling the balance of sex-chromosome activity ( dosage compensation ) . This opens new perspectives on how complexes that control the global chromosome organisation impact the fine tuning of gene expression .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"genetics",
"and",
"genomics/gene",
"expression",
"genetics",
"and",
"genomics/nuclear",
"structure",
"and",
"function",
"genetics",
"and",
"genomics/chromosome",
"biology",
"genetics",
"and",
"genomics/gene",
"function",
"genetics",
"and",
"genomics/epigenetics"
] |
2008
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SU(VAR)3-7 Links Heterochromatin and Dosage Compensation in Drosophila
|
Neural circuits reliably encode and transmit signals despite the presence of noise at multiple stages of processing . The efficient coding hypothesis , a guiding principle in computational neuroscience , suggests that a neuron or population of neurons allocates its limited range of responses as efficiently as possible to best encode inputs while mitigating the effects of noise . Previous work on this question relies on specific assumptions about where noise enters a circuit , limiting the generality of the resulting conclusions . Here we systematically investigate how noise introduced at different stages of neural processing impacts optimal coding strategies . Using simulations and a flexible analytical approach , we show how these strategies depend on the strength of each noise source , revealing under what conditions the different noise sources have competing or complementary effects . We draw two primary conclusions: ( 1 ) differences in encoding strategies between sensory systems—or even adaptational changes in encoding properties within a given system—may be produced by changes in the structure or location of neural noise , and ( 2 ) characterization of both circuit nonlinearities as well as noise are necessary to evaluate whether a circuit is performing efficiently .
Our sensory systems encode information about the external environment and transmit this information to higher brain areas with remarkable fidelity , despite a number of sources of noise that corrupt the incoming signal . Noise—variability in neural responses that masks the relevant signal—can arise from the external inputs to the nervous system ( e . g . , in stochastic arrival of photons at the retina , which follow Poisson statistics ) and from properties intrinsic to the nervous system , such as variability in channel gating , vesicle release , and neurotransmitter diffusion ( reviewed in [1] ) . This noise places fundamental limits on the accuracy with which information can be encoded by a cell or population [2–5] . An equally important consideration , however , is that noise dictates which processing strategies adopted by the nervous system will be most effective in transmitting signal relative to noise . Efficient coding theory has been an important principle in the study of neuroscience for over half a century , and a number of studies have found that neural circuits can encode and transmit as much useful information as possible given physical and physiological constraints [6–13] . Foundational work by Laughlin successfully predicted the function by which an interneuron in the blowfly eye transformed its inputs [7] . This and other early work prompted a myriad of studies that considered how neurons could make the most efficient use of their output range in a variety of systems and stimulus conditions [14–19] . Efficient coding theory has played an important role in how we interpret biological systems . However , one cannot know how efficiently a neuron or population is encoding its inputs without understanding the sources of noise present in the system . Several previous studies have recognized noise as an important factor in determining optimal computations [8 , 11 , 12 , 20 , 21] . These and related studies of efficient coding often make strong assumptions about the location of noise in the system in question , and these assumptions are typically not based on direct measurements of the underlying noise sources . For example , noise is often assumed to arise at the output stage and follow Poisson statistics . Yet experimental evidence has shown that spike generation itself is near-deterministic , implying that most noise observed in a neuron’s responses is inherited from earlier processing stages [22–24] . Indeed , several different sources of noise may contribute to response variability , and the relative contributions of these noise sources can change under different environmental and stimulus conditions [25–27] . Importantly , the results of efficient coding analyses depend on the assumptions made about the locations of noise in the system in question , but there has been to date no systematic study of the implications that different noise sources have for efficient coding strategies . In particular , identifying failures of efficient coding theory—i . e . , neural computations that do not optimally transform inputs—necessitates a broad understanding of how different sources of noise alter efficient coding predictions . Here , we consider how the optimal encoding strategies of neurons depend on the location of noise in a neural circuit . We focus on the coding strategies of single neurons or pairs of neurons in feedforward circuits as simple cases with physiologically relevant applications . Indeed , early sensory systems often encode stimuli in a small number of parallel channels , including in vision [28–30] , audition [31] , chemosensation [32] , thermosensation [33] , and somatosensation [34] . We build a model that incorporates several different sources of noise , relaxing many of the assumptions of previously studied models , including the shape of the function by which a neuron transforms its inputs to outputs . We determine the varied , and often competing , effects that different noise sources have on efficient coding strategies and how these strategies depend on the location , magnitude , and correlations of noise across neurons . Much of the efficient coding literature is impacted by these results . For example , Laughlin’s predictions assume that downstream noise is identical for all responses; when this is not true , a different processing strategy will be optimal . Other recent work , considering such questions as when it is advantageous to have diverse encoding properties in a population and when sparse firing is beneficial , bears reinterpretation in light of these results [21 , 35] . Our work demonstrates that understanding the sources of noise in a neural circuit is critical to interpreting circuit function .
The model is schematized in Fig 1 , and is detailed below . We constructed this model with retinal circuitry in mind , though the model could be reinterpreted to represent other primarily feedforward early sensory systems , or even small segments of cortical circuitry . We begin with a simple feature of neural circuits that captures a ubiquitous encoding transformation: a nonlinear conversion of inputs to outputs . Nonlinear processing arises from several biological processes , such as dendritic integration , vesicle release at the synapse , and spike generation [36 , 37] . Such nonlinearities appear in most neural coding models ( such as the commonly used linear-nonlinear-poisson ( LNP ) models or generalized linear models [38–40] ) . Although there are likely several sites with some level of nonlinear processing in the retinal circuitry , there is a single dominant nonlinearity at most light levels which can be localized to the output synapse of the bipolar cells [41] . Our goal is to determine the shape of the nonlinearity in this model that most faithfully encodes a distribution of inputs—i . e . , the optimal encoding strategy . Indeed , in the retina , the shape of this nonlinearity has been shown to adapt under different stimulus conditions , suggesting that this adaptation might serve to improve encoding of visual stimuli as environmental conditions ( and hence noise ) change [18 , 42] . The pathway receives an input signal or stimulus s , which is drawn from the standard normal distribution . Generally , an individual value of s can represent any deviation from the mean stimulus value , and the full distribution of s represents the set of inputs that might be encountered over some time window in which the circuit is able to adapt . In the context of the retinal circuitry , s can be understood as the contrast of a small region , or pixel , of the visual stimulus . The contrast in this pixel might be positive or negative relative to the ambient illumination level . The full distribution of s would then represent the distribution of contrasts encountered by this bipolar cell as the eye explores a particular scene . ( We use Gaussian distributions here for simplicity in analytical computations , though similar results are obtained in simulations with skewed stimulus distributions , similar to the distributions of pixel contrast of natural scenes [43] . ) We assume the distribution of s is fixed in time . If properties of the signal distribution varied randomly in time ( for example , if the variance of possible signals the circuit receives fluctuates between integration times ) , over long times the circuit would see an effectively broader distribution due to this extra variability . Conversely , if the particular visual scene being viewed or other environmental conditions change suddenly , the input distribution as a whole ( for example , the range of contrasts , corresponding to the width of the input distribution ) also changes suddenly . Therefore we expect the shape of the optimal nonlinearity to adapt to this new set of signal and noise distributions . We do not model the adaptation process itself; our results for the optimal nonlinearity correspond to the end result of the adaptation process in this interpretation . We incorporate three independent sources of noise , located before , during , and after the nonlinear processing stage ( Fig 1A and 1B ) . The input stimulus is first corrupted by upstream noise η . This noise source represents various forms of sensory noise that corrupt signals entering the circuit . This might include noise in the incoming stimulus itself or noise in photoreceptors . The strength of this noise source is governed by its variance , σ up 2 . The signal plus noise ( Fig 1B , purple ) is then passed through a nonlinearity f ( ⋅ ) , which sets the mean of a scaled Poisson process with a quantal size κ . The magnitude of κ determines the contribution of this noise source , with large values of κ corresponding to high noise . This noise source captures quantal variations in response , such as synaptic vesicle release , which can be a significant source of noise at the bipolar cell to ganglion cell synapse [26] . Finally , the scaled Poisson response is corrupted by downstream noise ζ ( with variance σ down 2 ) to obtain the output response ( Fig 1B , green ) . This source of noise captures any variability introduced after the nonlinearity , such as noise in a postsynaptic target . In the retina , this downstream noise captures noise intrinsic to a retinal ganglion cell , and the final output of the model is the current recorded in a ganglion cell . If the sources of upstream and downstream noise are independent ( e . g . , photoreceptor noise and retinal ganglion cell channel noise , respectively ) , then the two kinds of noise will be uncorrelated in a feedforward circuit like we model here . Lateral input from other channels , which we do not consider , could potentially introduce dependence between upstream and downstream noise . Feedback connections operating on timescales within a single-integration window could also potentially introduce correlations between additive upstream and downstream noises . However , while such connections could be important in cortical circuits , they are not significant in the sensory circuits that inspired this model , so we assume independent upstream and downstream noise in this work . For further biological interpretation of the model , see Discussion . We begin by studying a model of a single pathway . We then consider how two pathways operating in parallel ought to divide the stimulus space to most efficiently code inputs . These models are constructed of two parallel pathways of the single pathway motif ( Fig 1C ) , with the addition that noise may be correlated across both pathways . The study of two parallel channels is motivated by the fact that a particular area of visual space is typically encoded by paired ON and OFF channels with otherwise similar functional properties , but similar parallel processing occurs throughout early sensory systems and in some cortical areas [29 , 31 , 32] . We will return to further discussion of parallel pathways in the second half of the Results . We begin with the case of a single pathway . For simplicity , we start with cases in which one of the three noise sources dominates over the others . Considering cases in which a single noise source dominates isolates the distinct effects of each noise source on the optimal nonlinearity . We then show that these same effects govern how the three noise sources compete in setting the optimal nonlinearity when they are all of comparable magnitude . Information in many sensory systems is encoded in parallel pathways . In vision , for example , inputs are encoded by both ON cells and OFF cells . In audition , an incoming stimulus is encoded in many parallel channels , each encoding a particular frequency band . Allowing for multiple parallel channels raises fundamental questions about how these resources should be allocated: should multiple channels have the same or different response polarities ? Should an input be encoded in multiple channels redundantly , or should different channels specialize in encoding a particular range of inputs ? To understand these tradeoffs , we solved our model for the optimal nonlinearities for a pair of parallel pathways , the simplest case in which these questions can be investigated . Indeed , in many cases , a small number of sensory neurons are responsible for carrying the relevant signal [46–49] . Our circuit model for multiple pathways comprises parallel copies of the single pathway model ( Fig 1C ) , with the additional detail that both upstream and downstream noise may be correlated across pathways . We show below that the sign and strength of these correlations can strongly affect optimal encoding strategies . To focus on the effects of noise on optimal encoding strategies , we added complexity to the noise structure , while making significant simplifications in the stimulus structure . In particular , we assume that both channels receive the same stimulus . Correlated but non-identical stimuli in the two channels would likely affect optimal encoding strategies , but we did not explore this possibility and leave it as a direction for future inquiry . We discuss the parallel pathway results in the following order: first , we discuss the possible pairs of nonlinearities , which are richer than the single-pathway case . We then discuss the functional effects that each of the parameters , or in some cases combinations of parameters , has on the shapes of the nonlinearities , with a focus on which parameter regimes favor highly overlapping versus minimally overlapping encoding of inputs ( hereafter referred to as “overlapping” and “non-overlapping” ) . Finally , we discuss factors that determine whether a circuit should encode inputs with channels of opposite polarity versus channels of the same polarity .
Noise in neural circuits arises from a variety of sources , both internal and external to the nervous system ( reviewed in [1] ) . Noise is present in sensory inputs , such as fluctuations in photon arrival rate at the retina , which follow Poisson statistics , or variability in odorant molecule arrival at olfactory receptors due to random diffusion and the turbulent nature of odor plumes . Noise also arises within the nervous system due to several biophysical processes , such as sensory transduction cascades , channel opening , synaptic vesicle release , and neurotransmitter diffusion . Past work has focused on two complementary , but distinct aspects of neural coding: 1 ) how noise limits coding fidelity , and 2 ) how circuits should efficiently encode inputs in the presence of such noise . Much of the work to date has focused on the first aspect , investigating how noise places fundamental limits on information transfer and coding fidelity for fixed neural coding strategies ( e . g . , tuning curves ) [2–5] . Examples include studying how noise correlations lead to ambiguous separation of neural responses [2] and which correlation structures maximally inhibit coding performance [5] . The second perspective dates back to the pioneering work of [6] and [7] . These early works primarily considered how efficient codes are affected by constraints on neural responses , such as limited dynamic range . Recent studies have built upon these foundational studies , investigating further questions such as how circuit architecture shapes optimal neural codes [20 , 21 , 35 , 56–58] . However , this body of work has not systematically studied how efficient coding strategies depend on assumptions made about the nature of noise in a circuit . Previous work has shown that the amount of noise in a circuit can qualitatively change optimal coding strategies [8 , 59] . We also find that noise strength can be an important factor in determining efficient coding strategies . A 5- to 10-fold decrease in the signal-to-noise ratio produces dramatic qualitative changes in the optimal nonlinearities ( Fig 2 ) , and those changes depend on noise location . The SNR values used in our study correspond to a range of SNR values commonly observed in responses of neurons in early sensory systems [60 , 61] , suggesting that this result could be observed in biological circuits . Our analysis goes beyond considerations of noise strength to reveal how efficient coding strategies change depending on where noise arises in a circuit , showing that different noise sources often having competing effects . Other work in the context of decision making has similarly shown that the location of noise can impact the optimal architecture of a network , thus demonstrating that noise location in a circuit is important not only for signal transmission but also for computation [62] . Knowledge of both noise strength and where noise arises is therefore crucial for determining whether a neural circuit is encoding efficiently or not . Notably , even when the SNR of the circuit outputs is the same , the optimal nonlinearity can be very different depending on the location of the dominant noise source . The locations of different noise sources have perhaps been most clearly elucidated in the retina . Several studies have investigated noise within the photoreceptors , and in some cases have even implicated certain elements within the transduction cascade [61 , 63 , 64] . Additional noise arises at the photoreceptor to bipolar cell synapse , where stochastic fluctuations in vesicle release obscure the signal [45 , 65–67] . It has also been suggested that noise downstream of this synapse contributes a significant amount of the total noise observed in the ganglion cells , with some studies pointing to the bipolar cell to ganglion cell synapse specifically [26 , 67] . Several pieces of evidence show that the relative contributions of different noise sources can change under different conditions as a circuit adapts . For example , in starlight or similar conditions , external noise due to variability in photon arrival dominates noise in rod photoreceptors and the downstream retinal circuitry [61 , 68–70] . As light levels increase , noise in the circuits reading out the photoreceptor signals—particularly at the synapse between cone bipolar cells and ganglion cells—can play a more prominent role [26 , 67] . Moreover , even in cases where the magnitude of a given noise source remains unchanged , adaptation can engage different nonlinearities throughout the circuit , shifting the location of the dominant nonlinearity and thereby effectively changing the location of the noise sources relative to the circuit nonlinearity . The fact that noise strength and nonlinearity location in neural circuits is subject to change under different conditions underscores the importance of understanding how these circuit features shape optimal encoding strategies . In the retina , it has been observed that the nonlinearity at the cone bipolar to ganglion cell synapse can change dramatically depending on ambient illumination . Under daylight viewing conditions , this synapse exhibits strong rectification . Yet under dimmer viewing conditions , this synapse is nearly linear [42] . The functional role of this change is unclear , though the fact that noise sources are known to change under different levels of illumination points to a possible answer . If the dominant source of noise shifts from external sources to sources within downstream circuitry with increasing light level , as suggested by the evidence in [42] , our results indicate that the circuit indeed ought to operate more nonlinearly at higher light levels . Furthermore , it is known that the strength of correlations not only varies between different types of retinal ganglion cells [71] , but these correlations may be stimulus dependent [72 , 73] . Based on our results for paired nonlinearities , we predict that types of neurons that receive highly correlated input will have nonlinearities with small overlap , while cells that receive uncorrelated input will have highly overlapping nonlinearities . Fully understanding this adaptation , and adaptations in other systems , will require further elucidation of the noise sources in the circuit . Understanding how different aspects of circuit architecture shape efficient coding strategies has been a recent area of interest [20 , 21 , 35 , 56–58] . However , a systematic study of the effects of noise was not the goal of these works , and so the properties of the noise in these studies has been limited , bound by specific assumptions on noise strength and location , and the allowed shapes of nonlinearities . As a result , while there is some overlap in the conclusions of these studies , the differences in assumptions about the noise and nonlinearities also lead to some apparent disagreement . Fortunately , we can investigate many similar questions within our model , and thereby complement the results of these previous studies and enrich our understanding of the role of circuit architecture and function . We briefly discuss the connections that other published studies have to the work presented here , focusing on studies with questions that can be most directly investigated as special cases of our model . Early work by Laughlin suggested a simple solution for how a single neuron can maximize the amount of information transmitted: a neuron should utilize all response levels with equal frequency , thereby maximizing the response entropy [7] . Laughlin found that an interneuron in the compound eye of the blowfly transforms its inputs according to this principle . More recent work investigated nonlinearities in salamander and macaque retinal ganglion cells , predicting that optimal nonlinearities should be steep with moderate thresholds [35] . Experimental measurements of nonlinearities in ganglion cells were found to be near-optimal based on these predictions . Although both of these studies ( along with many others ) predict that neurons are efficiently encoding their inputs , assumptions about noise are not well-constrained by experiment . ( In one case , the model assumes very low noise of equal magnitude for all output levels , while in the other all noise is at the level of the nonlinearity output . ) As our work shows , one can arrive at different—even opposite—conclusions depending on where noise is assumed to enter the circuit . Without experimentally determining the sources of noise in each circuit , it is impossible to determine whether that circuit is performing optimally . Going beyond single neurons or pathways , several recent studies have investigated the benefits of using multiple channels to encode stimuli and assigning different roles to each of those channels depending on circuit inputs . For example , Gjorgjieva and colleagues investigated when it is beneficial to encode inputs with multiple neurons of the same polarity versus encoding inputs with neurons of different polarity [56] . They conclude that ON-ON and ON-OFF circuits generally produce the same amount of mutual information , with ON-OFF circuits doing so more efficiently per spike . Our results provide a broader context in which we can interpret their findings , showing that when additive downstream noise ( which was not included in their model ) is anti-correlated , encoding with same polarity neurons can become a more favorable solution . Another recent study investigated under what conditions it is beneficial for multiple neurons of the same polarity to have the same threshold and when it is beneficial to split thresholds [21] . In particular , [21] find that nonlinearities split when the strength of upstream noise is weak . Our results are consistent with this finding and again broaden our understanding of why this splitting occurs: by incorporating correlations , we show that it is not simply the amount of noise that determines splitting , but the combination of noise strength and noise correlations . This identifies additional possibilities for testing these efficient coding predictions , by looking not just for cells that receive noisy input with similar magnitudes , but by looking for types of cells that receive correlated versus uncorrelated input and determining the degree of overlap of their nonlinearities . We find that even in relatively simple circuit models , assumptions about the location and strength of multiple noise sources in neural circuits strongly impact conclusions about optimal encoding . In particular , different relative strengths of noise upstream , downstream , or associated with nonlinear processing of signals yield different optimal coding strategies , even if the overall signal-to-noise ratio is the same . Furthermore , correlations between noise sources across multiple channels alter the degree to which optimal channels encode overlapping portions of the signal distribution , as well as the overall polarity of the channels . On the other hand , different combinations of noise sources can also yield very similar nonlinearities . Consequently , measurements of noise at various locations in neural circuits are necessary to verify or refute ideas about efficient coding and to more broadly understand the strategies by which neurons mitigate the effects of unwanted variability in neural computations .
Our model is schematized in Fig 1 . Biophysical interpretation is discussed in detail in the Results and Discussion . We model the input to the circuit as a signal or stimulus s that comes from a distribution of possible inputs within a short integration time window , and hence is a random variable in our model . Before this input can be encoded by the circuit , it is corrupted by noise η , which we also take to be a random variable . The circuit then encodes total signal s + η by nonlinearly transforming it , f ( s + η ) . This transformed signal sets the mean of a variable circuit response . That is , the circuit does not respond deterministically , but stochastically . We do not take this stochastic response to be spiking , due to the fact that spike generation has been shown to be repeatable , attributing variability in spiking to other sources [22–24] . Instead , inspired by quantal neurotransmitter release , which results in post-synaptic potentials of integer multiples of a fixed minimum size , we model the stochastic response as a scaled Poisson distribution: responses come in integer multiples of a minimum non-zero response size κ , with an overall mean response f ( s + η ) , conditioned on the total input , s + η . This stochastic response is then corrupted by downstream noise ζ , which we also take to be a random variable . The total response r of a single-path circuit is thus r = κ m + ζ , ( 2 ) where m is a Poisson-distributed random variable with mean κ − 1 f ( s + η ) , such that the mean of κm is f ( s + η ) . Our circuit model thus has three sources of intrinsic variability: the additive noise sources ( η and ζ ) and the stochastic scaled-Poisson response . We assume the statistics of the signal and noise are held fixed over a time window long enough that the circuit can adapt its nonlinearity to the full distribution of signal and noise . That is , in a small integration time window Δt , the channel receives a draw from the signal and noise distributions to produce a response . Thus , we model the signal s and noises η , ζ , and the scaled Poisson responses as random variables rather than stochastic processes . In this work , we assume the distribution of possible inputs to be Gaussian with fixed variance σ s 2; without loss of generality we can take the mean to be zero ( i . e . , the signal represents variations relative to a mean background ) . We assume the upstream and downstream noise to be Gaussian with mean 0 and variances σ up 2 and σ down 2 , respectively . The assumption of Gaussian distributions for the input and noise is not a restriction of the model , but a choice we make to simplify our analyses and because we expect physiologically relevant noise sources to share many of the properties of a Gaussian distribution . Even in cases where the input distribution is not Gaussian , pre-processing of inputs can remove heavy tails and lead to more Gaussian-like input distributions . It has been shown that stimulus filtering in the retina indeed has this effect [74] . An additional scenario to consider is the possibility that the signal properties , such as the variances , could themselves be random . We might then wonder how this would impact the predicted nonlinearities . As a “trial” of our model is a single draw from the stimulus and noise distributions , there is no well-defined variance on a single trial . A changing variance on every trial would be equivalent to starting with a broader noise distribution of fixed variance . We can thus interpret the stimulus distribution we use in the study to be the effective distribution after trial-by-trial variations in variance have already been taken into account . The results for a signal of constant variance can thus be adapted , qualitatively , to the case of random trial-by-trial variance by increasing the stimulus variance in order to mimic the impact that trial-by-trial changes in variance have on the shape of the nonlinearity . In order to understand how noise properties and location impact efficient coding strategies , we seek the nonlinearity that best encoded the input distribution for a variety of noise conditions . We primarily consider the mean squared error ( MSE ) of a linear estimator of the stimulus , as outlined below , as our criterion of optimality . This is not the only possible optimality criterion , so to check the effects that other criteria might have , we also consider maximizing the mutual information ( MI ) between stimulus and response . MI provides a measure of coding fidelity that is free from assumptions about how information is read out from responses . However , MI is difficult to evaluate analytically for all but the simplest models . Indeed , for our model , deriving exact analytic equations for the optimal nonlinearities using MI is intractable . We turn to simulations in this case . We determine the nonlinearities obtained by minimizing the MSE using two complementary methods . First , we take variational derivatives of the MSE with respect to the nonlinearities themselves to derive a set of exact equations for the optimal nonlinearities , free from any assumptions about their shape or functional form , as described below . The only constraints we apply are that the nonlinearity must be non-negative and saturate at a value of 1 . ( The choice of saturation level is arbitrary and does not affect the results . ) Applying such constraints are non-trivial—in most variational problems constraints enforce an equality , but in our method we are enforcing an inequality , discussed in the next section . Using this analytic approach , we minimize the assumptions we make about the nonlinearities and obtain insights into the behavior of the model that are otherwise inaccessible . Second , we parametrize the nonlinearities as sigmoidal or piecewise linear curves with two parameters that control the slope and offset . We simulate the model , sweeping over the slope and offset parameters ( Fig 8A ) until we find the parameter set that minimizes the MSE of the linear readout . This parametric approach makes strong assumptions about the form of the nonlinearity but also has distinct advantages . Simulations allow us to test to what extent our conclusions about the shape ( i . e . , slope and offset ) of the optimal nonlinearity depend on its specific functional form . For example , we find from our analytical calculations that optimal nonlinearities are roughly piecewise linear ( Fig 8C ) , but one might expect biophysical constraints to restrict neurons to having smooth nonlinearities . For this reason , we also test sigmoidal shaped nonlinearities , a smooth approximation of the piecewise linear solutions that emerge from the nonparametric analytical approach , and use simulations to find the optimal parameters . We find the results with sigmoidal nonlinearities qualitatively very similar to the analytical solution ( Fig 8C ) . Parametric simulations have the additional advantage of allowing tests of more complex criteria for optimality than the MSE , such as maximizing the mutual information ( MI ) between the stimulus and responses , which we cannot compute analytically . Using simulations with parametrized nonlinearities , we are able to find the nonlinearity that maximizes MI ( Fig 8B ) . We have verified that optimal nonlinearities found by maximizing MI are qualitatively similar to those found by minimizing the MSE of a linear readout ( Fig 8C shows one example ) . For simplicity , throughout the main text of this paper we focus on results for minimizing MSE , but present results from maximizing MI in a few cases for comparison . Analytic calculations allow us to exactly determine the nonlinearities that minimize the MSE of a linear readout , without making any assumptions about the shape of the nonlinearity . However , it is possible that certain physiological properties might constrain the shape of the nonlinearity ( to be smooth , for example ) . It is also possible that another criterion for optimality ( instead of minimizing MSE of a linear readout ) might yield different results . To test these possibilities , we turned to simulations . For all results , the stimulus is drawn from the standard normal distribution , and nonlinearity outputs are constrained to fall between 0 and 1 . For the simulations presented in this work , we swept over the parameters listed in Table 1 . We chose a lower value of σdown = 0 . 1 rather than 0 to limit the number of parameter sets for which all noise sources in the model were zero , as these sets frequently do not converge within a reasonable amount of time . Because our code is written in terms of the unrescaled nonlinearities , we swept over ρeff by fixing σs = 1 and σup = 2 and sweeping over the upstream noise correlation coefficient ρup = {− 0 . 25 , 0 . 0625 , 0 . 3750 , 0 . 6875 , 1 . 0} . We swept over a much finer range of ρup between 0 . 875 and 1 to resolve the splitting seen in Fig 6 . For these cases , we only used one initial seed to speed up computation . The upstream noise variance must be larger than the stimulus variance in order to achieve ρeff = 0 . As the rescaled nonlinearities only depend on the ρeff , κ , σdown and ρdown , this choice only affects the absolute values of the MSE , which do depend on the ratio between σs and σup . Despite the dependence of the MSE on σs and σup , changing these parameters does not change which solutions are optimal for a fixed set of ρeff , κ , σdown and ρdown . This is because , for the optimal nonlinearities , the MSE works out to ( in terms of the rescaled nonlinearities and decoding weights ) χ 2 = σ s 2 1 - σ 2 σ s 2 + σ up 2 D ˜ 1 ⟨yf ˜ 1 ⟩ + D ˜ 2 ⟨ y f ˜ 2 ⟩ . The term D ˜ 1 〈 y f ˜ 1 〉 + D ˜ 2 〈 y f ˜ 2 〉 is always positive because the decoding weights and averages always have the same sign . For fixed parameter values , it is only this term that varies between ON-OFF and ON-ON pairs . As the rescaled quantities only depend on ρ eff , κ , σ down 2 , and ρdown ( for equal noise variances in each pathway ) , the exact values of σ s 2 and σ up 2 do not determine which class of solutions is optimal except through ρeff . However , because the values of σ s 2 and σ up 2 do affect the overall MSE , the optimal solution may not perform significantly better than “nearby” sub-optimal nonlinearities; e . g . , there may be a wide range of nonlinearities that give MSE within 1–5% of the optimal nonlinearity when the upstream noise variance is large . See Figs 2 and 5 in Results . Similarly , the percentage difference in MSE between ON-OFF versus ON-ON strategies can vary depending on the size of σs and σup . Fig 7 shows differences of up to 20% for σs = 1 . 0 and σup = 1 . 0 ( we use a smaller value of σup here to show that the percent differences in MSE can be significiant; the default value of σup = 2 . 0 yields percent differences in MSE of up to about 5% ) . For Fig 8 ( comparison of methods for determining the optimal nonlinearity ) , the parameters used were: σup = 0 . 2 , κ = 10-3 , and σdown = 0 . 2 . For Fig 2 ( single pathway optimal nonlinearities ) the parameters are listed in Table 2; parameters for Fig 3 ( comparison of optimal and suboptimal nonlinearities ) are listed in Table 3; parameters for Fig 5 ( parallel pathway optimal nonlinearities ) are listed in Table 4 .
|
For decades the efficient coding hypothesis has been a guiding principle in determining how neural systems can most efficiently represent their inputs . However , conclusions about whether neural circuits are performing optimally depend on assumptions about the noise sources encountered by neural signals as they are transmitted . Here , we provide a coherent picture of how optimal encoding strategies depend on noise strength , type , location , and correlations . Our results reveal that nonlinearities that are efficient if noise enters the circuit in one location may be inefficient if noise actually enters in a different location . This offers new explanations for why different sensory circuits , or even a given circuit under different environmental conditions , might have different encoding properties .
|
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"Abstract",
"Introduction",
"Results",
"Discussion",
"Methods"
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2016
|
How Do Efficient Coding Strategies Depend on Origins of Noise in Neural Circuits?
|
The emerging resistance to quinine jeopardizes the efficacy of a drug that has been used in the treatment of malaria for several centuries . To identify factors contributing to differential quinine responses in the human malaria parasite Plasmodium falciparum , we have conducted comparative quantitative trait locus analyses on the susceptibility to quinine and also its stereoisomer quinidine , and on the initial and steady-state intracellular drug accumulation levels in the F1 progeny of a genetic cross . These data , together with genetic screens of field isolates and laboratory strains associated differential quinine and quinidine responses with mutated pfcrt , a segment on chromosome 13 , and a novel candidate gene , termed MAL7P1 . 19 ( encoding a HECT ubiquitin ligase ) . Despite a strong likelihood of association , episomal transfections demonstrated a role for the HECT ubiquitin-protein ligase in quinine and quinidine sensitivity in only a subset of genetic backgrounds , and here the changes in IC50 values were moderate ( approximately 2-fold ) . These data show that quinine responsiveness is a complex genetic trait with multiple alleles playing a role and that more experiments are needed to unravel the role of the contributing factors .
Quinine , an active ingredient of cinchona bark , is an important drug in the pharmacopoeia against malaria , an infectious disease that causes an estimated 219 million clinical cases and 0 . 66 million deaths annually [1] . Quinine is used , together with partner drugs , as a second line treatment of uncomplicated malaria and as a first line treatment of malaria in the first trimester of pregnancy [2] . Severe cases of malaria are also frequently treated with quinine , although currently there are better treatment options [2] . Unfortunately , a progressive loss in responsiveness of the human malaria parasite Plasmodium falciparum to quinine has been observed , particularly in Southeast Asia [3]–[5] where cases of quinine treatment failure regularly occur , but also in Latin American and Africa [6]–[9] . In spite of quinine's pharmaceutical importance , very little is known about its antimalarial mode of action or the mechanism of resistance . The lack of information , particularly the paucity of genetic markers predictive of quinine resistance , complicates the molecular surveillance of quinine resistant P . falciparum strains and jeopardizes efforts to preserve the efficacy of this very valuable drug . The search for genetic markers of quinine resistance has been complicated by the pleiotropic nature of quinine's mode of action and the complexity of the resistance phenotype . Quinine seems to target endogenous heme detoxification pathways in the parasite's digestive vacuole [10] , [11] and it may further block the activity of PfMDR1 [12] , [13] , a multi-drug resistance transporter predominantly residing at the parasite's digestive vacuolar membrane [14] , although the full scope of quinine's molecular targets has yet to be defined . Reflecting the pleitropic mode of action , resistance to quinine seems to be multifactorial . Genetic markers that have been implicated in altered in vitro quinine responsiveness include pfcrt ( chloroquine resistance transporter gene ) , pfmdr1 ( multi-drug resistance gene ) , pfnhe ( sodium/hydrogen ion exchanger gene ) and PFD0610w ( putative phosphopantothenoylcysteine synthetase gene ) [12] , [15]–[24] . However , the data linking these genes to altered quinine responsiveness are conflicting and there is evidence suggesting that the genetic background plays an important , hitherto unexplained , role for the ability of any of these genes to confer quinine response variations . For example , a genetic analysis and some , but not all , epidemiological studies found a correlation between the K76T polymorphism in pfcrt ( a mutation indicative of chloroquine resistance in P . falciparum ) with reduced quinine responsiveness [15] , [16] , [25] , [26] , whereas an allelic exchange experiment observed the reverse - an increase in quinine susceptibility when the wild type pfcrt allele was replaced by the mutated allele in the P . falciparum clone GC03 [27]–[29] . Similarly , the genetic background seems to determine whether mutations within pfmdr1 and pfnhe bring about changes in the susceptibility to quinine [18] , [30] , [31] . To identify novel factors contributing to reduced quinine responsiveness , we have conducted comparative quantitative trait loci analyses on the susceptibility to quinine and its stereoisomer quinidine and on the initial and steady-state intracellular drug accumulation levels in the F1 progeny of the genetic cross between the P . falciparum strains HB3 and Dd2 . This approach follows up on the idea of a possible correlation between quinine resistance and reduced intracellular quinine accumulation , as suggested by the fact that pfcrt , pfmdr1 and pfnhe , all encode transporters that are thought to contribute to quinine resistance by reducing digestive vacuolar drug concentrations below toxic levels [12] , [13] , [19] , [21] , [22] , [32]–[34] . Here we describe a novel putative quinine response gene , termed MAL7P1 . 19 ( PF3D7_0704600 ) . MAL7P1 . 19 encodes a HECT ubiquitin-protein ligase that shares homologies with UFD4 [35] , a factor implicated in the ubiquitin fusion degradation pathway and in the Arg/N rule pathway , as shown in Saccharomyces cerevisiae [36]
In a previous study we have shown that the P . falciparum clone HB3 accumulated with time significantly more [3H]-quinine and [3H]-quinidine from external concentrations of 40 nM than did the P . falciparum clone Dd2 [21] . Time courses of intracellular drug accumulation performed concurrently confirmed this result ( supplementary Figure S1 ) . The level of quinine and quinidine accumulation reciprocally correlated with the in vitro susceptibility of the two strains to these two drugs , with Dd2 having half maximal inhibitory concentrations ( IC50 values ) for quinine and quinidine three- and four-fold higher than those of HB3 [15] ( supplementary Table S1 ) . To identify factors contributing to quinine and quinidine response variations , we performed quantitative trait loci ( QTL ) analyses on the amounts of quinine and quinidine accumulation at the 5 min ( initial uptake phase; Figures 1A and 2A ) and 25 min ( steady state phase; supplementary Figures S2A and S3A ) time points in the published 34 F1 progeny of the HB3 x Dd2 cross and the two parental clones [37] ( supplementary Table S1 ) . In addition , we determined the quinidine growth inhibitory concentrations ( IC50 values ) for the F1 progeny and the parental clones ( Figure 2A and supplementary Table S1 ) and analyzed these data by QTL mapping . We further reanalyzed the previously published quinine IC90 values and the corresponding IC50 values [15] ( Figure 1B and supplementary Figure S2A ) . The QTL analyses , depicted in the form of the computed LOD scores against the previously described genetic linkage maps of all 14 P . falciparum chromosomes [38] , identified for both drugs , both assays ( accumulation and proliferation assay ) , both time points , and both IC50 and IC90 values , a bifurcated peak on chromosome 7 where one finger corresponded to pfcrt ( 20 . 2 cM ) and another , well-separated finger , centered around the marker B5M12 ( 5 . 8 cM ) ( Figures 1B , 1C , 2B , and 2C , supplementary Figures S2B , S2C , S3B , and S3C ) . The bifurcated peak on chromosome 7 accounted for 59% ( 64% ) and 31% ( 43% ) of the total variance in the quinine ( quinidine ) accumulation ratios and in the quinine ( quinidine ) susceptibilities , respectively . As exemplified by the QTL analysis on quinine susceptibility , the contribution of both chromosome 7 peaks was sensitive to verapamil ( Figure 1C , thin line ) , a chemosensitzer and an established inhibitor of PfCRT [20] , [22] , [39] . The pfcrt and the B5M12 peaks are supported by 8 and 17 independent markers , respectively . The bottom of the valley between both peaks is defined by 9 markers and five independent recombination events , in the progeny , between the B5M12 and the pfcrt locus ( supplementary Table S2 ) . Markers generated as part of this study are listed in supplementary Table S3 . Supplementary Figure S4 shows an overview of the B5M12 locus . The statistical procedure we used for the QTL analysis ( see Material and Methods ) recorded also the sign of the correlation coefficients between the response variation and the polymorphisms at each genetic locus . For both chromosome 7 peaks , the correlation coefficients were negative for drug accumulation and positive for drug susceptibility ( Supplementary Table S4 ) indicating that it is the presence of the Dd2-inherited loci that is associated with a reduction in quinine and quinidine accumulation and an increase in resistance . Moreover , there is a statistically significant interaction between the pfcrt locus and the B5M12 locus ( two way ANOVA; P = 0 . 035 for quinine; P = 0 . 006 for quinidine ) , suggesting that the Dd2-inherited B5M12 and pfcrt loci co-act in bringing about significant quinine and quinidine response variations . The QTL analyses further identified a bifurcated peak on chromosome 13 ( defined by the markers VAPA and C13M73 ) that is associated with altered quinine and quinidine susceptibility , but not with altered drug accumulation ( Figures 1B and 2B , supplementary Figures S2B , and S3B , and Supplementary Table S4 ) . The bifurcated peak on chromosome 13 explains 35% and 27% of the total variance in quinine and quinidine susceptibility observed in the F1 progeny . It needs to be of Dd2 origin to confer an increase in resistance . In addition to the QTLs on chromosomes 7 and 13 , no further QTLs rose above the confidence line in the genetic scans using the quinine and quinidine IC50 or IC90 values or the quinine accumulation data ( p<0 . 01 , Figures 1B and 2B and supplementary Figure S2B ) . For the quinidine accumulation data , two additional QTLs were observed: PF12 on chromosome 6 ( 51 . 7 cM ) and Poly3 on chromosome 13 ( 107 . 3 cM ) ( Figure 2B , supplementary Figure S3B , and Supplementary Table S4 ) . In secondary scans , we separately analyzed the progeny that carried the wild type pfcrt allele and the progeny that carried the mutated pfcrt allele , thereby eliminating the contribution of pfcrt to drug response variations [40] . The secondary scans again identified the B5M12 locus with both drugs and for both time points at which drug accumulation levels were determined ( Supplementary Table S4 ) . In addition , the secondary scans revealed additional minor QTLs; some were shared between quinine and quinidine , including pfmdr1 ( 69 . 2 cM ) , B5M86 ( 60 . 2 cM ) and C5M2 ( 2 . 6 cM ) on chromosome 5 and MEF1 ( 32 . 6 cM ) and Poly3 ( 107 . 3 cM ) on chromosome 13 . The loci pfmdr1 , B5M86 and C5M2 contributed to increased quinine and quinidine accumulation , whereas the other three loci were associated with reduced drug accumulation , when inherited from Dd2 ( Supplementary Table S4 ) . Other QTLs were specific for quinidine , including C9M43 on chromosome 9 ( 0 cM ) and TPI and C14M75 on chromosome 14 ( 123 . 4 cM and 9 . 6 cM ) . Secondary scans performed on the IC50 values revealed additional QTLs that contributed to both altered quinine and quinidine susceptibility , including BM75 and BM103 ( 31 . 7 cM and 100 . 5 cM ) on chromosome 6 . Other minor QTLs seem to confer stereoisomeric responses , such as B5M4 ( 23 . 1 cM ) on chromosome 6 and C13M73 ( 178 . 8 cM ) on chromosome 13 , which are specific for quinine , and B7M14 ( 51 . 6 cM ) on chromosome 10 and AG15 ( 60 . 3 cM ) on chromosome 11 , which are specific for quinidine ( Supplementary Table S4 ) . Minor QTLs and QTLs identified in secondary scans were not investigated further . The segment of chromosome 13 that is associated with differential quinine and quinidine susceptibility , but not with altered drug accumulation levels , contains pfnhe , a gene that some , but not all , studies have implicated in altered quinine responsiveness and which is thought to affect intracellular quinine partitioning [15] , [16] , [25] , [29] . In a recent study , it has been shown that genetically-engineered pfnhe mutants with down-regulated pfnhe expression levels displayed decreased quinine IC50-values , dependent upon the genetic background of the strain [18] . The two pfnhe mutants that revealed increased quinine susceptibility were M-11BB5 and M-13BA6 , whereas M-1GC06 did not show this phenotype [18] . For each of the three pfnhe mutants and their corresponding unmutated progenitor lines , we measured the accumulation of quinine and quinidine at the 5 min time point ( Figures 3A and B ) . In none of the cases was there a statistically significant difference in drug accumulation as between the wild type and down-regulated pfnhe mutant under the conditions employed in this study . To further examine the contribution of the B5M12 locus to differential quinine and quinidine responses , we selected three progeny ( GC03 , CH3-116 and C188 ) that harbor the wild type pfcrt allele but which differ with regard to the B5M12 locus . GC03 contains the wild type HB3 B5M12 variant , whereas CH3-116 and C188 inherited the B5M12 locus from Dd2 ( Table 1 ) . The three progeny and the two parental clones HB3 and Dd2 were transfected with a vector expressing the Dd2 pfcrt variant fused in frame with the coding sequence of the green fluorescence protein ( GFP ) . The vectors were maintained at approximately 40 copies per haploid genome , with no significant differences between the transfectants ( Figure 4A ) . In all cases , the PfCRT/GFP fusion protein was expressed and localized at the membrane of the parasite's digestive vacuole , as determined by live cell fluorescence microscopy ( Figure 4A ) . Western analyses using an antiserum specific to PfCRT confirmed the expression of the 75 . 6 kDa PfCRT/GFP fusion protein in the transfectants ( Figure 4B ) . However , the amount of protein was lower than that of the endogenous PfCRT ( 48 . 7 kDa , Figure 4B ) . We then determined the responses of the transfectants to quinine , quinidine , and chloroquine - the latter drug serving as a control . In all transfected lines , with the exception of the transfected Dd2 line , there was a significant increase in chloroquine IC50 values and , associated therewith , a substantial reduction in chloroquine accumulation ratios , as compared to the corresponding parental strains ( P<0 . 01; Figure 4C ) . This finding indicates that the episomally expressed Dd2 pfcrt variant is functional and confers a dominant positive phenotype with regard to chloroquine resistance , although the degree of resistance fell short of that of Dd2 , possibly due to the low expression level of the episomally encoded pfcrt gene [41] and/or because of a weakened chloroquine transport activity of the GFP-extended PfCRT protein . In comparison to chloroquine where all the pfcrt transfectants , except for that of Dd2 , differentially responded to the drug , the response variations observed for quinine and quinidine were multifarious . A reduction in quinine accumulation levels was only found in CH3-116 and C188 , the two progeny harboring the B5M12 locus from Dd2 , and not in GC03 or HB3 that both possess the wild type HB3 B5M12 locus ( Figure 4C; Table 1 ) . This finding is consistent with the QTL analysis that identified the B5M12 and the pfcrt locus as the two principal and co-acting contributors to differential quinine accumulation ratios in the HB3 x Dd2 cross . Interestingly , the reduction in quinine accumulation ratios did not correlate with an increase in quinine IC50 values as one would have expected by analogy with chloroquine . Instead , CH3-116 and C188 became significantly more quinine and also more quinidine-sensitive when episomally expressing the Dd2 pfcrt variant , with the IC50 values dropping to 54–60% of those of the corresponding parental strains ( Figures 4D and C ) . No changes in susceptibility to the two enantiomers were observed in the HB3 , GC03 , and Dd2 background . In this context it should be noted that the B5M12 and the pfcrt locus jointly contribute only a third to the total variance in quinine and quinidine susceptibility in the HB3 x Dd2 cross . Another third is attributed to the bifurcated peak on chromosome 13 ( see above ) and a final third to various minor QTLs . Both CH3-116 and C188 inherited the respective chromosome 13 domains from HB3 ( Table 1 ) suggesting that , while the presence of both the B5M12 and the pfcrt locus from Dd2 is sufficient to reduce intracellular quinine accumulation , this does not suffice to increase the level of resistance without additional other QTLs being also of the Dd2 type , such as the two chromosome 13 loci . That expression of the mutant pfcrt gene in certain genetic backgrounds results in increased , and not in reduced , susceptibility to quinine and quinidine has also recently been observed [27] , [42] . It is explained by the PfCRT-mediated drug transport enhancing the encounter of the drug with targets outside the digestive vacuole [42] . The contributing genes in the chromosome 13 QTLs might be such targets ( see discussion ) . Transfecting the strains with a vector expressing the wild type pfcrt fused to GFP had no effect on chloroquine or quinine responses ( supplementary Figure S5 ) . The B5M12 locus consists of 33 annotated genes of which four are for t-RNAs ( Supplementary Figure S4 ) . We undertook a search among the remaining 29 annotated gene sequences to identify polymorphisms that might correlate with the changes in quinine and quinidine responses . To this end , we analyzed available genome sequence databases for HB3 and Dd2 and , in addition , amplified and sequenced the respective open reading frames from both parental clones . For 7 of these annotated genes , we could find no polymorphic differences between HB3 and Dd2 . For 4 of them , we failed to obtain sequence information . Those annotated genes for which we found polymorphisms ( either as codon replacements or as length polymorphisms ) are listed in supplementary Table S5 . In total we identified 109 polymorphisms in the B5M12 locus between HB3 and Dd2 . We selected 92 polymorphisms in 20 genes for further analysis . Six genes harboring a single conservative amino acid replacement were not followed through . A study by Mu et al ( 2003 ) has recorded the IC50 values for quinine and chloroquine for a large number of field isolates and laboratory strains of P . falciparum from different geographic origin [43] . From this collation we selected 26 strains from Southeast Asia , 12 strains from Africa , 10 strains from Latin America , one strain from Papua New Guinea and one strain of unknown origin . In DNA extracted from these 50 strains , we identified the specific polymorphism in the annotated genes selected within the B5M12 locus , as well as in pfcrt and pfmdr1 ( supplementary Table S5 ) . Ten of the strains had a wild type pfcrt and 40 of the strains had a mutated pfcrt allele ( as defined by the K76T polymorphism ) . The polymorphisms in a strain were then correlated with the IC50 values for quinine or chloroquine . A score was obtained equivalent to a LOD score over the whole set of polymorphisms . In the LOD score presentations , shown as the histogram of Figure 5A , the bars indicate the peak LOD score at each annotated gene . A horizontal line at height zero indicates no polymorphism at this locus , while a gap indicates a gene that escaped analysis or was not selected for further analysis . Two genes were associated with a major peak in LOD score for the quinine IC50 values . The left hand ( upstream ) peak is at a single gene locus identified as MAL7P1 . 19 ( PF3D7_0704600 ) , a gene encoding a putative HECT ubiquitin-protein ligase ( originally annotated as a putative ubiquitin transferase ) [35] and , henceforth termed pfut . Particularly , a set of five amino acid replacements at positions 1375 ( N to S ) , 1387 ( Y to F ) , 1401 ( E to D ) , 1406 ( G to C ) , and 1407 ( E to D ) were significantly associated with altered quinine responsiveness . The right hand ( downstream ) peak corresponds to the RAMA gene ( Rhoptry Associated Membrane Antigen; MAP7P1 . 208 ) . We repeated the analysis , omitting a random five of the 50 strains and obtained a very similar LOD score profile with the same major peaks at the pfut gene and at RAMA . We repeated the 5 of 50 random omissions procedure another four times and , in each case , received much the same profile ( data not shown ) . To assess which of the two genes , pfut or RAMA , determines reduced quinine susceptibility , we grouped the strains according to their haplotypes with regard to pfcrt and pfut or pfcrt and RAMA . We considered all pfut genes encoding a Y1387F substitution and all RAMA encoding a M321F substitution as mutant . A correlative box plot analysis of these groups with the IC50 values for quinine and chloroquine revealed clear distinctions between the two drugs ( Figure 5 ) . For quinine , pfcrt and pfut must both be present in the mutated form to obtain a significant increase in the IC50 value ( Figure 5B ) , whereas for chloroquine it is sufficient that only pfcrt is present as the mutant , while further mutation at the pfut gene does not increase the IC50 value significantly ( Figure 5C ) . The segment on chromosome 13 was not considered in this analysis . For the RAMA gene , there is no strain that has a mutant copy of this gene together with a wild type pfcrt gene , so that a full statistically valid grouping analysis , similar to that performed for the pfut gene , could not be done . Nevertheless , it is clear that , in contrast to the case for the pfut gene , there is not a significant increase in quinine IC50 value ( p = 0 . 10 ) when , in the background of mutant pfcrt , the wild type ( HB3 ) form of RAMA is replaced by the mutant form ( compare columns 3 and 4 of Figure 5D ) . Similarly , RAMA had no statistically valid effect on chloroquine IC50 values ( Figure 5E ) . These data would suggest that RAMA does not contribute to reduced quinine responsiveness . A secondary scan among strains containing a mutant pfcrt revealed a non-significant association of reduced quinine susceptibility with pfmdr1 ( data not shown ) . Previous studies have identified a region around pfcrt on chromosome 7 that is conserved in many chloroquine resistant field isolates and laboratory strains and which co-segregates with pfcrt [44]–[46] . To assess whether the genes of the B5M12 locus segregate independently of , or together with pfcrt , we correlated , in the 50 P . falciparum strains , the presence of mutated pfcrt with the polymorphic markers identified in the B5M12 locus and in genes flanking this chromosomal domain . The putative pfut gene , RAMA and the genes downstream of the B5M12 locus , towards the pfcrt locus ( including PF07_0026 and PF07_0029 ) , were significantly associated with mutated pfcrt , but this is not the case for the 22 genes in the B5M12 locus that lie between the putative pfut gene and RAMA ( Figure 6 ) . This finding suggests that the putative pfut gene is co-selected with pfcrt and does not co-segregate with pfcrt due to physical linkage . This cannot be said of RAMA . RAMA seems to be part of the low variability region that is conserved in many P . falciparum strains harboring a mutant pfcrt and which co-segregates with pfcrt . Co-selection of pfut with pfcrt is further supported by the presence of conserved polymorphisms within the HECT ubiquitin ligase in P . falciparum strains that carry different mutant pfcrt haplotypes . Including the tyrosine to phenylalanine replacement at position 1387 , we identified 19 single amino acid polymorphisms and 4 length polymorphisms within PfUT ( Figure 7A and supplementary Table S5 ) . Grouping the 50 field isolates and laboratory strains according to their geographic origin and their quinine IC50 values , revealed conserved polymorphisms in the pfut gene , which are present in strains from Latin America , Africa , and Southeast Asian with quinine IC50 values exceeding 100 nM ( Figure 7B ) . Note that the strains from Latin America and from Asia have experienced different drug selection histories and , accordingly , possess distinct pfcrt haplotypes [38] , [42] . The gene pfut encodes a protein of 3893 amino acids that is predicted to have four transmembrane domains and to belong to a subfamily of enzymatically active ubiquitin-protein ligases that contain an N-terminal armadillo-like fold implicated in substrate binding and a C-terminal HECT domain ( homologous to the E6-AP carboxyl terminus ) ( Figure 7A ) [35] . As shown in other systems , the HECT domain catalyzes ubiquitination . It accepts ubiquitin from a charged E2 conjugating enzyme via a cysteine thioester intermediate and subsequently transfers the ubiquitin to a substrate protein or to the growing end of a multiubiquitin chain [47] . The ability to bind ubiquitin distinguishes HECT domain ubiquitin ligases from other types of E3 ligases that do not form a transient intermediate with ubiquitin and , instead , facilitate the reaction between E2 and the substrate protein by bringing both in close proximity [47] . Antibodies raised against the N- and the C-terminal domain of PfUT identified a high molecular protein complex of >1 MDa in extracts prepared from isolated parasites solubilized with increasing concentrations of Triton X-100 ( Figure 8A ) . Under reducing and denaturing conditions , a protein of 460 kDa was identified in total membrane fractions extracted with Triton X-114 ( Figure 8B ) , consistent with the predicted molecular weight of this protein . Immunofluorescence microscopy partially co-localized PfUT with the ER marker BiP and the Golgi marker ERD2 , but not with PfCRT ( Figure 8C ) . Quantitative immunoelectron microscopy confirmed a predominant localization of PfUT at the ER/Golgi complex ( Figure 8D and E ) . The large size of the pfut gene and the position of the key mutations precluded us from using allelic exchange transfection strategies to validate the function of this gene in conferring altered quinine and quinidine responses . We , therefore , pursued an alternative strategy by overexpressing the HECT domain of the pfut gene in genetically different P . falciparum strains . We reasoned that the polymorphisms in PfUT might affect the activity or substrate specificity of this enzyme and that overexpressing the HECT domain in the cytoplasm might create a dominant negative or positive quinine and quinidine response phenotype in a manner depend on the genetic profile of the recipient strain with regard to pfcrt , pfut , and the two chromosome 13 QTLs . This approach was inspired by studies conducted in other systems revealing that isolated HECT domains can be enzymatically active [48] . To test this strategy we selected the two parental lines HB3 and Dd2 and five progeny ( GC03 , CH3-116 , TC05 , D43 , and 7C111 ) , displaying different permutations of the relevant loci ( Table 1 ) , and transfected them with a vector expressing a minimal HECT domain fused to GFP . The minimal HECT domain ( from amino acids 3652 to 3875 ) contained all predicted E2 interaction sites and the catalytic cleft including the catalytically active cysteine at position 3860 , but lacked parts of the N- and C-terminal lobes that can enhance catalytic activity , as shown in other systems [49] . Cytoplasmic expression of the fusion protein was confirmed by fluorescence microscopy ( Figure 9A ) . The transfected strains maintained the vector at comparable copy numbers per haploid genome of approximately 30 , with no significant differences between the transfectants ( Figure 9A ) . Two of the transfected strains , namely 7C111UT and TC05UT , revealed a significant reduction in intracellular quinine accumulation and an almost doubling of the quinine and quinidine IC50 values , compared with the corresponding parental stains ( P<0 . 01 , Figures 9B and C ) . These strains harbor , as genomic copies , the pfut locus from HB3 and the pfcrt locus and the relevant chromosome 13 QTLs from Dd2 ( Table 1 ) . A third strain , namely D43UT , revealed only a significant reduction in the amount of quinine accumulation ( P<0 . 01 , Figure 9B ) , but no differences in quinine and quinidine resistance ( Figure 9C ) . Although D43UT contains the genomic HB3 pfut locus and the genomic Dd2 pfcrt locus , it lacks the chromosome 13 QTLs from Dd2 ( Table 1 ) that , as already observed in the QTL analyses and in the pfcrt transfectants , contribute to reduced quinine and quindine susceptibility . Overexpression of the HECT domain in HB3 , CH3-116 , or GC03 , which all carry the pfcrt locus from HB3 ( but different alleles of the pfut locus and the chromosome 13 QTLs ) , had no significant effect on quinine accumulation ratios or quinine and quinidine IC50 values , nor was there any effect in Dd2 ( Figure 9B and C ) . The chloroquine responses were unaffected by overexpression of the PfUT HECT domain ( Figure 9B and C ) . Thus , cytoplasmic overexpression of the PfUT HECT domain affected quinine and quinidine response parameters , but only in predisposed genetic backgrounds , with changes in intracellular drug accumulation depending on the presence of the pfcrt locus from Dd2 and changes in IC50 values depending on the additional presence of the Dd2 chromosome 13 QTLs . To verify the enzymatic activity of the HECT domain/GFP fusion protein , we isolated the 110 kDa protein from the transfected Dd2 strain by affinity chromatography using an antibody against GFP . We subsequently tested the enriched protein in in vitro ubiqutination assays reconstituted with commercially available human recombinant components including ubiquitin , the E1 activating enzyme UBA , and the E2 conjugating enzymes UBCH5a or UBCH13 . The two E2 conjugating enzymes were chosen because they were found to be suitable partners for a P . falciparum RING E3 ubiquitin ligase in previous in vitro studies [50] . The enzymatic reactions were performed in a buffer containing an ATP regeneration system and examined by Western analysis . An antibody against ubiquitin detected high molecular weight ubiquitinated products only in the reaction containing the PfUT HECT domain and that only when reconstituted with the E2 conjugating enzyme UBCH5a ( Figure 10A; supplementary Figure S6A ) . Reactions that did not contain the PfUT HECT domain or in which UBCH13 replaced UBCH5a were catalytically inactive ( Figure 10A; supplementary Figure S6A ) . High molecular weight ubiqutinated products in the absence of a substrate protein are characteristic of some HECT ubiquitin ligases and are explained by spontaneous self polyubiquitination of internal lysines , following formation of the thioester adduct [48] , [51] . No enzymatic activity was observed when , instead of the HECT domain/GFP fusion protein , GFP only was tested . GFP was isolated from a transgenic Dd2 line following the protocol established for the HECT domain/GFP fusion ( supplementary Figure S6B ) . Next we added enriched PfCRT/GFP as a putative substrate to the active reaction . PfCRT/GFP was isolated from transfected Dd2 parasites by affinity chromatography using an antiserum against GFP . The antibody against ubiquitin detected the PfCRT/GFP fusion protein and the immunoglobulin heavy ( 53 kDa ) and light chains ( 25 kDa ) ( the conditions required to elute PfCRT/GFP from the column also eluted immunoglobulins ) but only in reactions containing the PfUT HECT domain and not in the control ( Figure 10B ) . Reprobing the membrane with an antiserum against PfUT confirmed the presence of the PfUT HECT domain/GFP fusion protein of 110 kDa in the enzymatically active reaction , whereas the negative control did not contain the protein ( Figure 10B ) . The PfCRT/GFP fusion protein of 75 . 6 kDa was present in both reactions ( Figure 10B ) . Apparently , the PfUT HECT domain catalyzed the ubiquitination of the PfCRT/GFP fusion protein and of immunoglobulins . These data suggest that the HECT domain/GFP fusion expressed in the various P . falciparum transfectants is enzymatically active .
Although quinine has been used in the treatment of malaria since the 17th century , it remains a fairly effective drug with cure rates generally exceeding 90% . High failure rates of ≥20% have been reported only from Venezuela and Cambodia [52] . There is , however , a general progressive decline in the sensitivity of P . falciparum strains to quinine across all malaria endemic areas [52]–[55] , which increasingly threatens the clinical efficacy of this important antimalarial drug . The very slow genesis of quinine resistance argues for a highly complex underpinning mechanism , one that out-matches that of the structurally related antimalarial drug chloroquine . In comparison , chloroquine resistance emerged in as few as 12 years after the drug was introduced in the field . It primarily results from multiple mutations in the pfcrt gene [56] . A previous study has mapped altered quinine responsiveness in the HB3 x Dd2 cross as a Mendelian trait to segments on chromosomes 5 , 7 and 13 , containing the polymorphic genes pfcrt , pfmdr1 , and pfnhe , respectively [15] . Our re-analysis of quinine responses in the HB3 x Dd2 cross has revealed a more refined picture . We confirmed the association with pfcrt and pfmdr1 and , in addition , identified a novel candidate gene , termed MAL7P1 . 19 ( or pfut ) encoding a HECT ubiquitin-protein ligase [35] . Our data further shed new light on the role of the pfnhe containing segment on chromosome 13 . This segment shows an interesting dichotomy . It contributes to reduced quinine and quinidine susceptibility , but not to differential drug accumulation . This is a surprising finding . Previous studies have suggested that the contributing gene within the chromosome 13 segment is pfnhe [15] and that polymorphisms in , and/or altered expression levels of , pfnhe might affect intracellular pH homeostasis [19] , which in turn might impact on drug partitioning , particularly if the drug has acidotropic properties as do quinine and quinidine . However , we did not find such an effect . Differential intracellular quinine and quinidine accumulation was independent of the pfnhe expression level , as shown by investigating mutants with partially knocked-down pfnhe expression , and it was independent of polymorphisms in PfNHE even though PfNHE of HB3 and Dd2 differ by several amino acid substitutions and length polymorphisms . This raises the possibility of factors other than pfnhe contributing to altered quinine and quinidine susceptibility [57] , [58] . This possibility is further nurtured by pfnhe residing in a valley of what might be a doublet QTL , defined by the markers VAPA and C13M73 , although the evidence for a doublet QTL is only circumspect . The defining property of the chromosome 13 segment , that it decreased quinine and quinidine susceptibility while having no noticeable effect on quinine and quinidine accumulation ( Figures 1 and 2 ) , might suggest that it encodes factors that are targeted by quinine and quinidine . The pfut gene remained unnoticed in the initial study by Ferdig et al . ( 2004 ) [15] , probably because the relevant LOD scores ( B5M12 linkage group ) , derived from cell proliferation assays , only just reached significance in the analysis of the quinine IC50 and IC90 values . In contrast , the LOD scores derived from our accumulation studies were four to five magnitudes higher , providing sufficient statistical power to link the pfut locus with quinine response variants . Furthermore , unlike Ferdig et al . ( 2004 ) , we have based our genetic linkage analysis on not just one assay but on two independent assays ( the standard cell proliferation assay and the drug accumulation assay ) and have independently confirmed the results with the related drug quinidine . Thereby our results achieved a high degree of confidence . Both pfut and pfcrt reside on chromosome 7 in genetic linkage groups that are 14 . 4 cM or , alternatively , 97 kb apart ( supplementary Table S2 ) . Although both loci are physically linked , they are , in genetic terms , sufficiently apart to unequivocally separate them from one another in the QTL analyses of the HB3 x Dd2 cross . The reported average recombination distance of ∼15 kb per cM in this cross allows loci to be mapped within segments of 15–50 kb [37] . Further aiding in the parsing of the pfut and pfcrt loci , there is a saturating number of independent recombination events in the part of chromosome 7 surrounding pfcrt because of previous efforts to resolve the chloroquine resistance locus , which eventually led to the discovery of pfcrt [37] , [56] . Of the 34 progeny , five carry distinct recombination events in the interjacent chromosomal domain between pfut and pfcrt , allowing us to parse both loci with high statistical power ( P = 0 . 0008 ) . In comparison , in another genetic cross , between the P . falciparum strains 7G8 and GB4 , none of the progeny harbor a recombination event between the pfut and pfcrt loci [38] . Accordingly , both markers form a single genetic linkage group in this cross . This explains why a recent study associated altered quinine and quinidine responses in the 7G8 x GB4 cross with a single QTL on chromosome 7 , and not two , despite 7G8 and GB4 carrying distinct pfut and pfcrt haplotypes [42] . The association studies on polymorphic markers in 50 field isolates and strains revealed that pfut is not part of the chromosomal domain of restricted genetic diversity that surrounds pfcrt in chloroquine resistant P . falciparum strains [44]–[46] . There are at least twelve polymorphic genes immediately downstream of pfut towards pfcrt , none of which were associated with mutant pfcrt . In comparison , RAMA , which is one of the genes closest to pfcrt in the B5M12 locus , seems to be part of the low diversity pfcrt linkage disequilibrium block . RAMA and the genes following it on the chromosome in the direction towards pfcrt are all highly associated with mutant pfcrt , suggesting that they have been passed on from one parasite generation to the next as part of a conserved chromosomal domain . pfut seems to contribute to quinine and quinidine response variations only when paired with other traits , particularly with pfcrt and a segment on chromosome 13 . A possible functional association between pfut and pfcrt is supported by the drug accumulation assays performed with the progeny of the HB3 x Dd2 cross ( Figures 1B and 2B ) and with the pfcrt and PfUT HECT domain transfectants ( Figures 4D; Figure 9B ) where mutant pfcrt could only bring about a significant reduction in drug accumulation levels when partnered with the variant form of pfut or an overexpressed PfUT HECT domain . However , the pfcrt and pfut associated reduction in intracellular drug levels did not necessarily result in reduced susceptibility as defined by an IC50 or IC90 value . In two of the five genetic backgrounds investigated there was a reciprocal correlation between drug accumulation and resistance , but in three other genetic backgrounds the combined effect of the pfcrt and pfut genes was neutral or even resulted in increased drug sensitivity ( compare transfectants and corresponding parental strains in Figures 4 and 9 ) . The explanation offered by the QTL analysis is that these strains lack the chromosome 13 QTL ( s ) that , as discussed above , might encode targets of quinine and quinidine . Indeed , all the transfectants in which pfcrt and pfut conferred increased quinine and quinidine resistance also harbored the relevant chromosome 13 segment from Dd2 . Those transfectants that lacked the Dd2 chromosome 13 segment revealed no changes in susceptibility or became even more susceptible , despite the expression of the variant form of pfcrt and the variant or overexpressed form of pfut . The absence of a reciprocal correlation between PfCRT-mediated drug efflux from the digestive vacuole , as defined by a reduced net intracellular drug accumulation ratio , and drug susceptibility has recently also been noted and is explained by the altered drug flux enhancing the encounter of the drug with targets outside the digestive vacuole [42] . The complex , multifactorial nature of quinine resistance explains allelic exchange experiments in which polymorphic pfcrt alleles were introduced into the genetic background of the P . falciparum clone GC03 ( a progeny from the HB3 x Dd2 cross ) [27] . These mutants were highly susceptible to quinine and quinidine . We explain this puzzling result by the fact that these mutants carry the wild-type HB3-like pfut gene and the wild type chromosome 13 QTLs , thus lacking essential factors required for reduced quinine responsiveness . Similarly , the lack of a correlation between mutant pfcrt and quinine resistance in some field isolates may be because these strains are wild-type in the relevant other loci . Unexpectedly , low quinine responding strains ( as defined by an IC50 value >100 nM ) from Latin America and Southeast Asia and also the two African strains investigated share a conserved set of polymorphisms within PfUT ( Figure 7B ) , despite distinct regional histories of drug use and drug selection , as evidenced by their different pfcrt variants [38] , [42] . This conservation has to be considered in the context of the overall highly polymorphic nature of pfut . We noted at least 19 non-synonymous mutations and several length polymorphisms in this gene between HB3 and Dd2 . Apparently , the conserved set of polymorphisms within pfut has independently emerged in Latin America and in Southeast Asia , suggesting that pfut is under a strong positive selective pressure [23] , possibly from the use of quinine , although previous genome wide association studies failed to establish a link between pfut and quinine response variations [23] , [24] . The conserved polymorphic residues reside in a domain of PfUT that reveals a high degree of phylogenetic diversity among orthologs in other Plasmodia . Whether pfut contributes to drug response variations other than quinine and quinidine is still under investigation . pfut does not seem to contribute to resistance to amodiaquine or its active metabolite desethyl amodiaquine [38] , [42] , compounds that shares the quinolone scaffold with quinine and chloroquine , or to artemisinin [59] . There is , however , evidence implicating the pfut-carrying B5M12 locus in altered responses to diphemanil and , possibly , chloroquine [40] , [60] . An effect of the B5M12 locus on altered chloroquine responsiveness in the HB3 x Dd2 cross , however , is controversial and only supported by the QTL analysis on the chloroquine IC50 values reported by Patel et al . ( 2010 ) , but not by the Sa et al . ( 2009 ) or our own data sets [38] , [40] , [42] . How PfUT affects quinine responses is currently unclear . PfUT localizes to the parasite's ER/Golgi complex where it seems to form high molecular weight complexes of >1 MDa , as shown in a native blue gel , possibly by associating with factors of the proteasome [61] . However , PfUT does not seem to be part of the ER-associated degradation pathway that mediates proteolysis of misfolded proteins [62] . PfUT shares sequence homologies with the Saccharomyces cerevisiae UFD4 HECT ubiquitin-protein ligase [35] . UFD4 was initially identified as a component of the ubiquitin fusion degradation pathway that recognizes an N-terminal ubiquitin moiety and which targets these ubiquitin fusion proteins for polyubiquitination and degradation [63] . Later it was found that UFD4 is also involved in the Arg/N-end rule pathway , by augmenting the processivity of polyubiquitination of Arg/N-end rule substrates [36] . Thus , PfUT might play a role in proteasome-mediated degradation . A yeast-two-hybrid screen has revealed an interaction of PfUT with several proteins [61] that might be substrates of PfUT . This includes the chloroquine resistance marker protein ( CRMP ) , a putative nuclear target of chloroquine [64] . There are several examples in the literature where mutations in an ubiquitin ligase or a deubiquitination enzyme affect drug susceptibilities , frequently by regulating the stability of a resistance-mediating drug transporter [65]–[67] . An example from a malaria parasite is a deubiquitination enzyme that is associated with increased resistance to artemisinin and chloroquine in Plasmodium chabaudi [68] . Since both PfUT and PfCRT spatially and temporally overlap , as PfCRT traffics to the parasite's digestive vacuole via the parasite's ER/Golgi complex [69] , it is tempting to speculate that PfUT acts on PfCRT and that mutational changes in , or overexpression of , PfUT affect PfCRT's trafficking , final conformation , longevity , and/or activity . Although the isolated PfUT HECT domain ubiquitinated a PfCRT/GFP fusion protein in an in vitro reconstituted ubiquitination assay ( Figure 10B ) , further experiments are needed to validate this finding and demonstrate ubiquitination of native PfCRT in the parasite . A previous proteomic analysis of PfCRT purified from the parasite revealed phosphorylation at serine 33 , serine 411 , and threonine 416 , with the last posttranslational modification being a defining signal for trafficking of PfCRT to the digestive vacuole [69] . Ubiquitination of PfCRT was not detected in this study , possible because the N-terminal domain of PfCRT , which is the likely site of action of PfUT , was not covered in this study . In general , coverage was poor in regions other than the C-terminal cytoplasmic domain . In summary , our study presents several independent lines of evidence suggestive of pfut playing a role in altered quinine and quinidine responses in certain genetic backgrounds . Definitive proof , however , would await allelic exchange experiments and extended surveys of clinical isolates to validate the association of polymorphisms in pfut with reduced quinine susceptibility .
P . falciparum was cultured as previously described [70] and synchronized using the sorbitol method [71] . The F1 progeny from the HB3 x Dd2 cross have been described [37] and were obtained from MR4 . The identity of all progeny was verified by PCR using eight highly polymorphic microsatellite markers as described [42] . The transfection vector expressing pfcrt tagged in frame with the coding sequence of the green fluorescence protein has recently been described [69] . Briefly , the pfcrt coding sequence from the chloroquine resistant P . falciparum strain Dd2 or the wild type sequence from the chloroquine sensitive strain HB3 was cloned into the XhoI and AvrII restricted pARL1a+ transfection vector [72] in a manner that allowed pfcrt expression to be controlled by its own promoter . The GFP coding sequences was subsequently cloned into AvrII and XmaI restricted pARL1a+ vector containing the pfcrt coding sequence to create a C terminal PfCRT/GFP fusion . The catalytic domain of PfUT encompassing the amino acids 3653 to 3877 were cloned in frame with the coding sequences of the conditional aggregation domain [73] and GFP into XhoI and AvrII restricted pARL1a+ . Parasites were transfected using 100 µg plasmid DNA , and transfectants were selected using 5 nM WR99210 , as previously described [74] . Transfectants were detected in blood smears 14–21 days post transfection . Transfectants were grown in the presence of 5 nM WR99210 until two days before analysis when the drug pressure was removed to avoid interference of WR99210 with the drug accumulation assay or the growth inhibition assay . Live cell imaging of P . falciparum-infected erythrocytes were performed as described [69] . Radiolabeled quinoline antimalarial drugs were obtained from the following vendors: [3H]-chloroquine ( 18 . 8 Ci/mmol ) , GE Healthcare; [3H]-quinine ( 20 Ci/mmol ) and [3H]-quinidine ( 20 Ci/mmol ) , American Radiolabeled Chemicals , Inc . The drug accumulation assay has been fully described [21] , [75] . Briefly , P . falciparum-infected erythrocytes were purified using a strong magnet ( VarioMACS , Miltenyi Biotec ) , as described [75] . This yielded a purity of trophozoite-infected erythrocytes of 95–100% as determined by light microscopic examination of Giemsa-stained blood smears . The cells were resuspended in prewarmed RPMI 1640 containing 11 mM glucose , 25 mM HEPES , and 2 mM glutamine ( pH 7 . 3 at 37°C ) at an haematocrit of 25000 cells/µl . The haematocrit was determined using an automated cell counter ( Z1-Coulter Particle Counter , Beckman Coulter Inc . ) . Cells were then incubated at 37°C in the presence of 40 nM of the respective drug and the amount of label accumulated over time was monitored . The cellular drug accumulation ratio was determined as described [75] . Throughout the study , trophozoite-infected erythrocytes ( 20–28 hrs post invasion ) were examined . The accumulation ratios to quinine , quinidine and chloroquine were determined in parallel assays . Cell proliferation assays in the presence of different concentrations of chloroquine , quinine , and quinidine , were performed as described [15] . For the pfcrt and pfut HECT domain transfectant parasite lines , the IC50 values to these drugs were determined in parallel assays over a period of four months . The quinine IC90 values in the presence and absence of 0 . 89 µM verapamil have been described for the HB3 x Dd2 cross [15] . The corresponding quinine IC50 values for the HB3 x Dd2 cross were derived from these original data and are compiled in supplementary Table S1 . The quinine and chloroquine IC50 values for the 50 field isolates and laboratory strains were taken from Mu et al . ( 2003 ) [43] . QTL analysis was performed as described [76] and validated using R/QTL . The percent contribution of individual QTLs to the total variance in a response parameter was calculated using R/QTL . The genetic maps have been published [38] . The QTL analysis for the field strains was performed in a similar fashion . The quinine susceptibility of a strain was correlated with the presence or absence of a certain polymorphism , yielding the Pearson coefficient and from this , the probability , as the P value . The appropriate LOD score for a locus was computed as the logarithm of the probability P at that locus divided by the mean of the P values taken over all the loci . LOD scores above 2 ( a P value one-hundredth that of the mean ) were deemed significant . Data were analysed using one or two way ANOVA test ( Holm-Sidak test ) , or the Student's t-test , where appropriate . Statistical calculations were done using SigmaPlot 12 . 5 . Appropriate regions of the HB3 and Dd2 genomes were downloaded from the Broad Institute MIT database and analyzed using the BLAST algorithm to identify putative polymorphisms . Novel SNPs , indels , and microsatellite markers have been reported to Genbank . Rabbit and mouse antisera were generated against the N-terminal ( residues 473 to 712 ) , the C-terminal domain of PfUT ( residues 3654 to 3875 ) and against two combined peptides ( DYNIKEDDESGSSN and LDDGVRPEKRKT ) . Immunofluorescence was carried out on magnet purified trophozoites [42] fixed with 4% EM-grade paraformaldehyde ( EMS ) and 0 . 0075% EM-grade glutaraldehyde ( Merck ) in PBS for 30 min [77] . Primary antisera were diluted as follows: rabbit α-PfBiP 1∶1000; rat α-PfERD2 1∶500; rabbit N-terminal PfUT 1∶3000; rabbit C-terminal PfUT 1∶3000; mouse N-terminal PfUT 1∶2000 . Corresponding secondary antibodies were used at a dilution of 1∶1000 . Slides were viewed using a LSM510 laser scanning confocal microscope ( Carl Zeiss ) . Immuno electron microscopy was performed as described [78] , using the rabbit antisera against the N-terminal domain of PfUT ( 1∶100 ) coupled to 10 nm protein A colloidal gold . For Western analysis , the following antisera were used: guinea pig anti-PfCRT ( dilution 1∶1000 ) [79] and as secondary antibody donkey anti guinea pig antibodies conjugated with horseradish peroxidase ( POD ) ( 1∶10000 , Dianova ) ; monoclonal mouse anti-GFP ( dilution 1∶1000 , Roche Diagnostics ) and as secondary antibody goat anti mouse POD ( 1∶10000 , Dianova ) ; rabbit anti the C-terminal domain of PfUT ( residues 3652 to 3875 ) ( 1∶5000 ) and as secondary antibody goat anti rabbit POD ( 1∶10000 , Dianova ) ; monoclonal-mouse anti-ubiquitin ( 1∶2000 , Santa Cruz Biotechnology ) and as secondary antibody goat anti mouse POD ( 1∶10000 , Dianova ) . POD activity was detected using the BM Chemiluminescence Blotting Substrate Kit ( Roche Diagnostics ) . For the analysis of native proteins and protein complexes , magnet purified trophozoites were saponin-lysed ( 0 . 07% in PBS ) , washed two times in PBS , and subsequently solubilized using increasing concentrations of Triton X-100 ranging from 0 . 125% to 1% with mixing at 4°C for 30 min . All solutions were supplemented with protease inhibitors ( 1 mM PMSF , 50 µg/ml aprotinin , 20 µg/ml leupeptin ) . Insoluble material was pelleted ( 14 , 000 g for 30 min at 4°C ) , and supernatant fractions were collected . Samples were subsequently analyzed using a native blue gel as described [80] . For the analysis of membrane proteins , a Triton X-114 phase separation protocol was used [81] . Briefly , saponin-lysed magnet purified trophozoites were incubated in a Triton X-114 buffer ( 1% Triton X-114 , 150 mM NaCl , 10 mM Tris-Cl pH 7 . 4 ) for 3 min at 30°C before centrifuged at 300 g . The supernatant was removed and subject to a second round of extraction ( 0 . 5% final concentration of Triton X-114 ) . The lower detergent phase was analyzed by SDS-PAGE on a 3–8% gradient gel followed by Western analysis . The DNA from approximately 2×108 parasites was isolated using the DNeasy Blood & Tissue Kit from Qiagen . Copies of pARL plasmids were subsequently determinate by quantitative real time PCR as described [82] , using primers to the bla gene . The reaction was performed using the LigthCycler DNA Master SYBR Green I reaction mix and the Biorad CFX96 Real-Time System . In parallel reactions , the amount of genomic DNA was determined by quantitative real time PCR , using primers to the P . falciparum β-tubulin gene , as described [83] . The normalized number of plasmid copies per haploid genome was then obtained . The high copy numbers reported in this study are consistent with episomal maintenance of the transfection vector , although occasional genomic integration cannot be excluded . The GFP fusion proteins PfCRT/GFP and PfUT HECT domain/GFP were isolated from the respective transfectant Dd2 lines as described [69] . Briefly , following synchronisation with 5% sorbitol [71] , infected erythrocytes at the trophozoite stage were purified from 600 ml parasite culture ( 5% haematocrit and 8% parasitemia ) using the Super Macs magnet ( Miltenyi Biotech ) and the D column . Infected erythrocytes were subsequently treated with 0 . 07% saponin in PBS . Immunoprecipitation was performed as described [73] . Briefly , proteins were extracted using the RIPA buffer for PfCRT ( 1% NP-40 , 1% sodium deoxycholate , 0 . 1% SDS , 150 mM NaCl , 10 mM Na-Phosphate buffer pH 7 , 1 mM EDTA ) and an TNE buffer for PfUT ( 20 mM Tris-HCl pH 7 . 5 , 137 mM NaCl , 1% NP40 , 2 mM EDTA , plus protease inhibitors: leupeptin 20 µg/ml , aprotinin 50 µg/ml , PMSF 1 mM ) . The lysate was then diluted with 9 volumes of NETT buffer ( 10 mM Na-Phosphate buffer pH 7 , 150 mM NaCl , 0 . 1% NP-40 , and 1 mM EDTA ) . Prior to immuno-precipitation , lysates were cleared using goat IgGs . For immunoprecipitation , the ProFound™ Co-Immunoprecipitation Kit ( Pierce ) was used according to the manufacturer's instructions , using goat anti-GFP antiserum ( Rockland ) . Immuno-precipitated material was washed in buffers with increasing NaCl concentrations ranging from 250 to 350 mM and one additional wash with 50 mM Tris HCl pH 7 . 5 . All buffers used were supplemented with a cocktail of protease and phosphatase inhibitors ( 50 µg/ml aprotinin , 20 µg/ml leupeptin , 1 mM PMSF ) . In vitro ubiqitination assays were performed as described [50] and examined by Western analysis . The following reagents purchased from Boston Biochem were used in the ubiquitination assay: 70 µM human recombinant ubiquitin , 200 nM human recombinant ubiquitin activating enzyme UBA , 5 µM human recombinant ubiquitin conjugating enzyme UbcH5a or UbcH13 , and 1 x energy regeneration solution . The reactions were size-fractionated by non-reducing SDS PAGE on a 4–12% gradient gel , transferred to polyvinylidene difluoride membranes , and analyzed using the antisera indicated ( see also above ) .
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Quinine , a natural product from cinchona bark , has been used in the treatment of malaria for centuries . Unfortunately , a progressive loss in responsiveness of the human malaria parasite Plasmodium falciparum to quinine has been observed , particularly in Southeast Asia , where cases of quinine treatment failure regularly occur . To better understand how P . falciparum defends itself against the cytotoxic activity of quinine , we have conducted comparative linkage analyses in the F1 progeny of a genetic cross where we assessed the susceptibility and the amount of intracellular accumulation of quinine and of its stereoisomer quinidine . These data identified a novel candidate gene encoding a HECT ubiquitin-protein ligase that might contribute to altered quinine responsiveness . The identification of this novel gene might improve the surveillance of quinine-resistant malaria parasites in the field and aid the preservation of this valuable antimalarial drug .
|
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"Methods"
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2014
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A HECT Ubiquitin-Protein Ligase as a Novel Candidate Gene for Altered Quinine and Quinidine Responses in Plasmodium falciparum
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For homeostasis , lingual taste papilla organs require regulation of epithelial cell survival and renewal , with sustained innervation and stromal interactions . To investigate a role for Hedgehog/GLI signaling in adult taste organs we used a panel of conditional mouse models to manipulate GLI activity within epithelial cells of the fungiform and circumvallate papillae . Hedgehog signaling suppression rapidly led to taste bud loss , papilla disruption , and decreased proliferation in domains of papilla epithelium that contribute to taste cells . Hedgehog responding cells were eliminated from the epithelium but retained in the papilla stromal core . Despite papilla disruption and loss of taste buds that are a major source of Hedgehog ligand , innervation to taste papillae was maintained , and not misdirected , even after prolonged GLI blockade . Further , vimentin-positive fibroblasts remained in the papilla core . However , retained innervation and stromal cells were not sufficient to maintain taste bud cells in the context of compromised epithelial Hedgehog signaling . Importantly taste organ disruption after GLI blockade was reversible in papillae that retained some taste bud cell remnants where reactivation of Hedgehog signaling led to regeneration of papilla epithelium and taste buds . Therefore , taste bud progenitors were either retained during epithelial GLI blockade or readily repopulated during recovery , and were poised to regenerate taste buds once Hedgehog signaling was restored , with innervation and papilla connective tissue elements in place . Our data argue that Hedgehog signaling is essential for adult tongue tissue maintenance and that taste papilla epithelial cells represent the key targets for physiologic Hedgehog-dependent regulation of taste organ homeostasis . Because disruption of GLI transcriptional activity in taste papilla epithelium is sufficient to drive taste organ loss , similar to pharmacologic Hedgehog pathway inhibition , the findings suggest that taste alterations in cancer patients using systemic Hedgehog pathway inhibitors result principally from interruption of signaling activity in taste papillae .
Hedgehog ( HH ) signaling plays complex regulatory roles in adult organ and tissue maintenance [1] . From regulation in epithelia that turn over slowly and normally are ‘quiescent’ [2] to skin that regularly renews [3] , roles for HH activity are temporally- and niche-specific , and rely on interactions with nerves [4] and stromal cells [5 , 6] . Delineating the context-dependent functions of HH signaling in different tissues is thus a high priority for better understanding the normal regulation of organ homeostasis , regeneration and disease . Taste papillae are constantly renewing , complex , multimodal sensory organs that subserve lingual taste , touch and temperature , and have varied and essential roles in eating [7] . The specialized taste bud cells turn over every 3 to 20-plus days , with an average life span of about 10 days [8–11] . The stratified squamous epithelium of the papilla organs also continuously turns over [12 , 13] and is seated on a basal lamina that envelopes a connective tissue core of stromal fibroblasts , blood vessel endothelial cells , nerve fibers and ensheathing Schwann cells , and extracellular matrix . Despite constant taste bud and epithelial cell renewal and replacement , and dynamic connective tissues , the lingual taste organs maintain structural and functional sensory integrity . The precise regulation that orchestrates the biology of such diverse cell types to sustain taste papilla organs and lingual sensory homeostasis is not well understood . We have approached study of taste organ maintenance and renewal with multiple genetic mouse models to focus on regulation by Hedgehog/GLI ( HH/GLI ) signaling . Hedgehog ( HH ) signaling initiates when secreted HH ligands bind to Patched1 ( PTCH1 ) and to the co-receptors GAS1 , CDON and BOC [14] , resulting in de-repression of Smoothened ( SMO ) which transduces the HH signal intracellularly via a series of cytoplasmic intermediaries [15 , 16] . Subsequent modulation of the GLI transcription factors ( GLI1 , GLI2 , GLI3 ) leads to differential protein processing , including a shift from transcriptional repressor to activator forms , and transcription of HH target genes that include Ptch1 and Gli1 [17] . GLI1 functions strictly as a transcriptional activator but is dispensable for embryonic and postnatal development [18 , 19] . GLI2 is the major activator of HH-driven transcriptional responses in vivo [20] , whereas GLI3 operates primarily as a repressor [21] . The HH pathway is a principal regulator of taste organ development although other pathways are involved [22 , 23] . There are well characterized effects of the HH pathway in taste papilla induction and patterning , and proposed roles in taste bud progenitor differentiation [24– 26] . Significantly , recent studies point to a requirement for properly regulated HH signaling in adult taste organ maintenance . Expression of an oncogenic form of GLI2 in tongue epithelia leads to altered fungiform papilla number , structure , taste buds , and epithelial proliferation [27] . In contrast , overexpression of SHH results in the formation of ectopic , non-innervated taste bud-like structures in suprabasal lingual epithelium outside of the fungiform papillae [28] . In cancer patients , treatment with drugs to inhibit the HH pathway is associated with profound alterations in taste [29 , 30] , and use of these drugs to block HH signaling in rodents results in aberrant fungiform papillae , loss of taste buds and severely disrupted taste sensation [31] . Fungiform papilla ( FP ) epithelia contain stem or progenitor cells that replenish taste bud cells during tissue homeostasis [8 , 32 , 33] , and with genetic-inducible fate mapping , we showed that Gli1-positive , HH-responding cells in the basal layer of fungiform papillae and in perigemmal cells contribute both to taste bud cells and to taste papilla epithelium [27] . Putative stem cells also have been reported within taste buds themselves [34] , and SHH-positive progenitor cells within taste buds can give rise to all taste bud cell types [35] . Additionally , forced activation of Wnt signaling in SHH-expressing cells promotes FP taste cell differentiation [36] . In the circumvallate papilla ( CV ) on the posterior tongue , also , taste and papilla cells are in constant turnover and Lgr5 is a proposed stem cell marker [34] . HH pathway regulation has been suggested in taste bud cell proliferation and differentiation [37] . SHH is detected in taste bud basal cells and Ptch1-expressing cells are included in highly proliferative epithelial cells around taste buds , but reportedly not in the underlying stroma [9 , 38] . The patterns in FP and CV suggest a paracrine mode of signaling from SHH-expressing taste bud cells to neighboring epithelial and stromal cell populations [27 , 37] . However , to date , a requirement for HH signaling activity in specific cell populations of adult taste organs has not been rigorously examined with genetic HH pathway blockade . To gain a better understanding of how HH signaling contributes to taste organ maintenance , we genetically manipulated GLI transcription factor activity selectively in epithelial cells using either a doxycycline-regulated dominant-negative Gli repressor , GliR , allele , or by conditional deletion of epithelial Gli2 either on a wild-type or Gli1 null background . We have characterized rapid and profound effects of epithelium-specific HH/GLI blockade on FP and CV papilla integrity and taste bud loss , and a relative sparing of neural and stromal elements . Strikingly , the FP , CV and taste bud phenotypes were rescued when GLI inhibition was stopped , demonstrating a remarkable plasticity in these tissues; although in a subset of fungiform papillae there was no recovery . Overall we show that HH signaling is an essential regulator of papilla taste organ integrity , principally with epithelial effects that respond rapidly both to signal repression and release . Our findings argue that taste alterations in patients treated with systemic HH pathway inhibitors can be explained by interruption of HH/GLI signaling activity in HH-responsive epithelial cells of taste papilla organs .
To assess effectiveness of signaling blockade in our models we stained for lacZ positive cells in mice carrying a Gli1lacZ allele , which serves as a sensitive and specific reporter for HH pathway activity [18] . In Control mice , HH-responding cells were detected in the basal cell layer of the FP epithelial walls , in perigemmal epithelial cells around the TB , and in stromal cells of the connective tissue core ( Fig 3 Control Gli1lacZ ) . As early as 5 days after transgene activation in epiGliR mice , HH-responding cells were no longer detected in the fungiform papilla walls and perigemmal epithelial cells but were retained in the FP connective tissue core ( Fig 3 , epiGliR Day 5 , Day 11 ) , confirming repression of HH signaling selectively in the targeted cell populations . Similar results were obtained in K5GliR , Gli2cKO and Gli2cKO;Gli1KO mice ( S2A Fig ) . Having established effective blockade of epithelial HH/GLI signaling activity we examined expression of SHH , which in the FP is typically restricted to a subset of taste bud cells [27] that express the taste bud cell marker Keratin 8 ( K8 ) [43] . After only 5 days of transgene expression/GLI blockade in epiGliR mice , taste bud cells were fewer in number , did not span the full thickness of the epithelium , and apical taste pores were missing ( Fig 3 , SHH/K8 Control and Day 5 ) . By 11 days ( epiGliR ) or 35 days ( K5GliR ) of transgene expression , discernible taste bud cell collections were detected only occasionally and they were localized to the lower third of lingual epithelium ( Fig 3 , Day 11 and inset; S2B Fig , Day 35 K5GliR ) . Overall , within the TB remnants at various stages of “deterioration” associated with HH signaling repression , there were some SHH expressing cells in the TB base as is typical in adult FP/TB ( Fig 3 , Day 5 , Day 11 and inset; S2B Fig , Day 35 K5GliR ) . The residual SHH in some FPs may be capable of signaling to HH-responsive stromal cells retained in the FP after HH repression and could potentially participate in maintaining epithelial integrity and/or FP structure . There are , however , TYPE III FP/No TB in all models ( Figs 1 and 2 ) and because these have no TBs they have no SHH in the FP . The effects of HH signaling on proliferation in different cell types within tissues are highly context-dependent . Whereas HH signaling drives proliferation in several settings [1] , in others the HH pathway maintains quiescence [2] . Altered proliferative activity in papilla organs could contribute to the profound morphological alterations we detected following GLI blockade . Using antibodies to the basal layer marker , p63 , the proliferation marker , Ki67 , and EdU labeling to detect cells in S phase , we confirmed previously identified domains of high proliferation at the base of the FP and in perigemmal cells ( 27 ) in Control tongues ( Fig 4A–4E ) . The marker p63 was expressed uniformly within basal cells of the FP walls and perigemmal cells ( Fig 4A; S3A and S3B Fig ) whereas the intensity of Ki67 immunostaining was typically reduced in basal cells as they ‘ascended’ the papilla wall toward the apex ( Fig 4D ) . To quantify proliferation we counted Ki67-positive cells in three epithelial compartments: the apical and basal halves of the fungiform papillae walls , and the perigemmal compartment surrounding the taste bud ( Fig 4F ) . In the basal papilla domain of epiGliR mice , after 5 days there was a 66% reduction in Ki67-positive cells and a trend toward reduction in the apical domain that did not reach significance ( Fig 4G APICAL , BASAL ) . In Gli2cKO tongues , after 16 days , there was again a non-significant trend toward fewer Ki67+ cells in the apical FP but there was no difference in the basal papilla ( Fig 4H APICAL , BASAL ) . The difference in basal papilla proliferation in epiGliR compared to Gli2cKO FP could relate to the more profound effects on papilla structure in the epiGliR model ( see Fig 1 ) . Strikingly , GLI blockade led to a reduction in Ki67-positive perigemmal FP cells both in epiGliR and Gli2cKO mice ( Fig 4G epiGliR PERI; H Gli2cKO PERI ) . This reflects the fact that the number of perigemmal cells in the region that neighbors taste bud ‘remnants’ is radically reduced in GLI-inhibited tongues , arguing in favor of a pivotal role for the HH pathway in maintaining this epithelial cell population . This concept was further examined by immunostaining for the HH target Cyclin D1 . We quantified Cyclin D1-positive cells in apical and basal papilla walls and in perigemmal cells , as we did for Ki67 expression ( Fig 4H ) . In the Gli2cKO tongue , there was a trend to a reduced number of cells in the apical FP wall and in perigemmal cells . Cyclin D1-positive cells in apical and perigemmal regions were reduced by about 20% from Control ( S3C , S3D and S3E Fig ) . Overall the data are similar to results with Ki67+ cell counts , but do not reach statistical significance . Thus , GLI blockade leads to fewer proliferating cells in epithelial compartments that contribute to taste cells during homeostasis [27 , 32] , suggesting that the loss of taste buds following HH pathway blockade is due at least in part to a deficiency in taste cell renewal . In an effort to gain insight into the mechanism of cell loss after HH blockade , we examined apoptosis in tongues from Control and GLI-inhibited mice . Immunostaining for cleaved caspase 3 did not reveal differences from Controls in any of our models ( S3F and S3G Fig ) and cell labeling was infrequent as predicted from other studies in taste bud [44 , 45] . TUNEL-positive cells are occasionally seen in epidermis and they are up-regulated after UV-irradiation [46] and also in tongue after X-ray irradiation [47] . We used H&E sections in Control and Gli2cKO tongues ( S3H , S3I and S3J Fig ) to directly compare with TUNEL reactions . There were multiple TUNEL-positive cells in Control and Gli2cKO FP epithelium ( S3K , S3L and S3M Fig ) , with an accumulation of positive cells in more apical layers of Gli2cKO TYPE II and in TYPE III FP that had taste bud cell loss and acquisition of a conical , filiform-like cap ( S3L and S3M Fig ) . Accumulated TUNEL-positive cells in the FP apex in GLI-inhibited models resembled those in filiform papillae in Control mice ( S3H Fig FILI ) . These are unlikely to represent classical apoptotic cells because we did not detect cells expressing cleaved caspase 3; moreover , it is known that cell death in keratinocyte differentiation does not follow classic apoptotic pathways [48 , 49 , 50] . Overall , increased apoptotic cell death is not likely to be a principal factor in taste organ alterations during HH/GLI blockade . We demonstrated that FP and TB are disrupted or lost with HH/GLI blockade , and with fewer taste cells , SHH expression is much reduced in taste bud remnants . Further , proliferation was reduced in the TB perigemmal cells . Given the requirement for innervation in taste organ homeostasis [51] , we examined innervation to the tongue and to taste buds specifically in Gli2 repressor ( K5GliR , epiGliR ) and Gli2cKO mice . Innervation to the tongue ( combined chorda tympani/lingual nerve ) and to taste buds specifically ( chorda tympani only ) was studied ( Fig 5 ) . The connective tissue core of the FP typically contains neurofilament ( NF ) -positive fibers of the combined chorda tympani/lingual nerve that distribute to the taste bud and lateral wall regions of the papilla core ( Fig 5A , Chorda/Lingual Control ) . A distinctive ‘basket’ of fibers encircles the basal lamina region just under taste bud cells . After 5 days of transgene activation in lingual epithelium of K5GliR or epiGliR mice , despite taste bud disruption ( Fig 1C ) , there is a robust innervation within papillae as seen with NF label ( Fig 5C , K5GliR Day 5 ) . NF-positive nerve fibers are also detected in epiGliR mice despite severe disruption of taste buds and papillae ( Fig 5E ) , and in Gli2cKO mice ( Fig 5G ) . FP innervation from the chorda tympani nerve to taste buds specifically , and not to the papilla walls , can be identified with immunostaining for P2X3 ( Fig 5B , arrow , Chorda tympani , Control ) . P2X3 is strongly expressed in peripheral sensory , including gustatory neurons [52 , 53] . In contrast to NF , P2X3 immunostaining therefore detects chorda tympani nerve and also some fibers within the taste bud , with cells that co-express K8 ( Fig 5B ) . Taste specific P2X3-positive innervation is retained in the papilla core of K5GliR mice and into the apical papilla epithelium and taste bud cell remnants ( Fig 5D , K5GliR , Day 5 , arrow ) . In day 11 epiGliR mice , P2X3-positive fibers are detected even though most K8-positive taste bud cells are lost ( Fig 5F arrows ) . In FP of Gli2cKO tongues over a prolonged period of 28 days of doxycycline administration , taste nerves remain although FPs are disrupted and few retain intact TB remnants ( Fig 5H arrow ) . Importantly , we did not observe any re-patterning or displacement of lingual innervation from the FP to aberrant sites; that is , fibers remained directed to the appropriate ‘target’ region in K5GliR , epiGliR and Gli2cKO mouse tongues . In tongue , NF-positive fibers typically course within the reticular lamina propria under the epithelium ( S4A Fig , Control arrows ) and turn to innervate FPs ( S4B Fig , Control ) . A similar pattern of nerves under the epithelium is retained in K5GliR and epiGliR tongues ( S4C and S4E Fig arrows ) and is in a directed course to densely innervate the FP ( S4D and S4F Fig ) . Significantly , innervation is retained in FPs without K8-positive taste bud cells at a comparable extent to FPs with taste buds ( S4B , S4D and S4F Fig ) . The NF-positive bundles of the chorda/lingual nerve in the tongue body and coursing into the FP are surrounded by lacZ-positive , HH-responding cells ( S4G , S4H and S4I Fig ) . Furthermore , S100-positive immunohistochemistry , to mark nerve Schwann cells , demonstrates a close association with HH-responding cells in the FP core ( S4J Fig ) . Thus , any sources of SHH ligand from taste bud cell remnants or from other cell elements in the FP tissue core have direct access to nerve-associated HH-responding cells . Our data demonstrate that overall there is no gross elimination or misdirection of innervation in tongue , FP and/or TB cells with HH pathway suppression over long periods and profound target organ disruption . Although taste buds and papillae are severely disrupted or lost in the K5GliR , epiGliR and Gli2cKO mouse tongues , FP-like structures can be identified that retain a somewhat rectangular shape , albeit more pointed apically , with epithelial down-growths ( Figs 1 and 2 ) . Also , HH-responding , Gli1lacZ-positive cells remain within the FP connective tissue ( Fig 3 ) . Because HH interacts with connective tissue cells and can be chemotactic [2 , 54] , we used antibodies against vimentin , the principal intermediate filament of stromal fibroblast cells and a pan-fibroblast marker , to test for potential effects of HH suppression on FP stromal cells . In Control FP , vimentin-positive cells are: 1 ) in the central stromal core; 2 ) distributed along the papilla walls; 3 ) in the neurofilament-positive ‘basket’ niche just under the taste bud cells; and , 4 ) in cells that send filopodia extensions to contact the basal lamina ( Fig 6A , 6B and 6C ) . In Gli2cKO tongues vimentin-positive stroma cells are not disrupted or redistributed but are retained in the basket region at the FP apex and have filopodia extending into the basal lamina ( Fig 6D , 6E and 6F ) . Vimentin-positive cells were not observed within the taste bud in Control or Gli2cKO tongues; a few cells were observed in the epithelium . Overall there was no evidence for deregulated stromal cell activity in HH repression . Other stromal cell types were labeled with antibodies for the macrophage marker , F4/80 , and for smooth muscle actin ( α-SMA ) . Labeled macrophages were in relatively small numbers in the FP core ( S5A , S5B and S5C Fig ) and there was no evidence of extensive macrophage infiltration associated with HH suppression . SMA-positive stromal cells were distributed in reticular lamina propria under the epithelium , within the filiform papilla core and the FP central core ( S5D and S5E Fig ) and were not numerous compared to vimentin-positive cells . The data demonstrate that following epithelial repression of HH signaling and loss of taste organ integrity , major cell types in the papilla core are retained . Whereas anterior tongue FPs have an ectodermal embryonic origin , the posterior tongue tissues and large circumvallate papilla ( CV ) have endodermal derivation [55 , 56] and could be affected differently by HH/GLI suppression . In contrast to the single TB in rodent FP , the CV contains a few hundred taste buds in dense physical juxtaposition in walls of the papilla trenches [57] . In Control and Gli2cKO mice , the general structure of the CV was similar ( Fig 7A and 7C ) . To assess size of the CV we quantified length of CV walls ( Fig 7A , bars on left wall ) and computed depth of the CV from the number of dorsal to ventral serial sections . In Gli2cKO tongues these papilla measurements were not different from Control tongues across 5 to 35 days of gene deletion ( Fig 7E ) . However , in contrast to the maintained overall CV structure , the numbers of TB profiles/remnants , or complete TBs with a taste pore , were markedly reduced compared to Control ( Fig 7B , 7D and 7F ) . After 16 days of epithelial Gli2 deletion , TB profiles were reduced by about 60% and full TBs ( with pores ) were almost eliminated ( Fig 7F ) . ( ANOVA data and posthoc analyses are presented in S1E and S1F Fig ) As in FP , NF-positive innervation to the CV , via the glossopharyngeal nerve , was not eliminated after epithelial gene deletion for 28 days which led to profound taste bud reduction ( S6A and S6B Fig ) . Furthermore , comparable to results for FP , proliferating Ki67+ cells in the CV basal epithelium were substantially reduced after HH/GLI suppression ( S6C and S6D Fig ) . To determine whether cell death was a major contributor to TB cell loss in the CV after HH inhibition , we performed TUNEL staining and did not discern a difference from Control tongue ( S6E and S6F Fig ) . Again this is similar to the FP . Similar to Gli2cKO mice ( Fig 7F ) , in K5GliR tongues after 35 days of HH/GLI blockade , the number of CV taste pores was reduced to a mean of 10 compared to the control mean of 50 ( S6G Fig ) . An even more profound effect on CV taste buds was observed in epiGliR mice: taste bud remnants and/or complete taste buds were essentially eliminated after 5 days ( S7A , S7B , S7C and S7D Fig ) , and the CV shape was altered , with increased keratinization after 11 days ( S7E and S7F Fig ) . In Control mice carrying a Gli1lacZ allele , X-Gal-positive HH-responding cells were detected in basal epithelial and perigemmal cells in the CV and in the stroma around taste bud-bearing CV walls ( Fig 8A and 8B Control ) . However , in Gli2cKO mice , there was a sustained loss of HH-responding X-Gal-positive epithelial cells in the CV , as early as 5 days after gene deletion , with variable numbers of X-Gal-positive cells remaining in the surrounding stroma particularly near taste bud remnants ( Fig 8C and 8D Day 5; Fig 8E and 8F Day 35 ) . In Control CV , SHH expression is clustered in the basal cell region of taste buds ( Fig 8G and 8H ) . Associated with the loss of taste bud cells seen as early as Day 5 after gene deletion , there was a reduction in SHH expression within the taste buds of the CV ( Fig 8I and 8J Day 5 ) . With taste bud profiles or remnants some SHH-expressing cells remained , shown at Day 35 ( Fig 8K and 8L Day 35 ) . In summary , the CV papilla epithelium was severely disrupted after HH/GLI blockade and was unable to sustain a full complement of TBs with pores , although papilla innervation remained . In association with taste bud cell loss , Ki67-positive basal epithelial cells were decreased , and epithelial HH-responding cells and SHH expression were reduced . These data indicate that both ectoderm-derived FP and endoderm-derived CV papillae require epithelial HH signaling for proper tissue maintenance . To determine whether effects of epithelial HH/GLI blockade on papillae and taste buds were reversible , we induced transgene expression in K5GliR mice by treating with doxycycline for 16 days , and then withdrew doxycycline for a subsequent 7 , 14 or 30 days . At 16 days of transgene expression , K5GliR FP were disrupted and taste bud cells were reduced or lost ( Fig 9A and 9B ) . TYPE I FP/TB were reduced to about 25% of Control values and TYPE III Atypical FP/No TB papillae were about double those in Control , or 40% of all FP ( Fig 9D ) . When doxycycline treatment was stopped to shutdown transgene expression , 7 days were not sufficient to induce recovery of FP/TB organs ( Fig 9D ) . However , after treatment withdrawal for 14 days , epithelial integrity was restored ( Fig 9C ) and TYPE I Typical FP/TBs were recovered to about 80% of Control ( Fig 9D ) . TYPE III Atypical FP/No TB papillae , on the other hand , also remained at a substantial proportion or about 40% of FP over 7–30 day recovery periods ( Fig 9D ) , without apparent recovery . ( All ANOVA data are provided in S8A Fig ) . After 7–14 days recovery from 16 days of HH repression , X-Gal-positive , HH responding cells were again detected in perigemmal and basal epithelial cells in regenerated TYPE I Typical FP/TB ( S9A , S9B and S9C Fig ) but were only in the connective tissue stroma of TYPE III Atypical FP/No TB taste organs ( S9G , S9H and S9I Fig ) . In 32% of TYPE II Atypical FP/Atypical TB after 7 days recovery there were some X-Gal-positive cells already appearing in the papilla epithelium ( S9F Fig ) . Note that after 7 days recovery from HH repression , 25% of TYPE I Typical FP/TB have a distribution of lacZ-positive cells in FP epithelial walls and the stromal core ( S9C Fig ) , whereas Type III Atypical FP/No TB have no lacZ-positive cells in the epithelium ( S9I Fig ) . To probe for recovery of proliferating cells we examined Ki67 expression in apical , basal and perigemmal cell regions of the FP . In tongues from Controls and mice with K5GliR transgene expression for 16 days , the results replicated those shown in Fig 4H for cell proliferation in Gli2cKO mice . In tongues from 16 day-induced K5GliR mice followed by 30 days treatment withdrawal , there was recovery of Ki67+ cell numbers in apical and perigemmal regions ( S8G , S8H , S8I and S8J Fig ) . The extent of this recovery , significant in perigemmal cells , directly matched that for recovery of Type I FP/TB after treatment withdrawal ( S8K Fig ) . Similarly , CV papillae and taste buds also recovered after release of HH/GLI blockade . Sixteen days after GLI repression in K5GliR mice , the CV retained structural integrity compared to Control mice ( Fig 9E , 9F and 9H ) . However , there was a clear and substantial loss of CV taste buds ( Fig 9I , 9J and 9L ) , comparable to that seen in Gli2cKO mice ( Fig 7 ) . The CV taste bud profiles in K5GliR tongues were reduced to about 50% and pores were reduced to about 20% of Control values ( Fig 9L ) . After 14 days off doxycycline treatment , the CV structure was still intact ( Fig 9G and 9H ) and taste bud profiles recovered to about 66% of Control values and to about 95% after 30 days ( Fig 9K and 9L ) . Taste pores recovered to more than 80% of Control values after 14 or 30 days ( Fig 9L ) . Compared to loss of HH-responding cells in the epithelium around the taste buds after HH repression ( Fig 8 ) , after 14 days recovery from treatment , X-Gal-positive cells were in the CV stroma and surrounding the taste buds ( S10 Fig ) . ( All ANOVA data are in S8B and S8C Fig ) With a shorter HH/GLI suppression period of 5 days , there was full recovery of TYPE I Typical FP/TBs , and of TB profiles and pores in the CV , within 14 days . Therefore with a shorter period of suppression and less extensive taste organ effects , recovery was complete ( S8D , S8E and S8F Fig ) . Thus , even after a prolonged period of HH/GLI repression , there was recovery of taste organ integrity in over half of FP papillae , and FP and CV taste buds , after only two weeks of doxycycline withdrawal . Therefore , during the period of epithelial HH/GLI blockade , progenitor cells that could reconstitute the papilla epithelium and taste buds upon reversal from HH/GLI repression survived or were rapidly re-formed . In TYPE III Atypical FP/No TB recovery was not detected , suggesting that with elimination of TB cells and therefore epithelium-derived HH ligand , progenitors for intact papillae and taste buds were irreversibly eliminated . The data suggest that HH-expressing taste bud cells are necessary for epithelial recovery from HH/GLI blockade .
Our data demonstrate effects of HH signaling block in K5-expressing cells in two very different gustatory papillae: the FP with a single taste bud in the apex and the CV with a few hundred taste buds that are dense and in physical juxtaposition in walls of the papilla trenches [57] . On withdrawal of doxycycline to stop transgene expression in K5GliR mice , a large proportion of FP and CV epithelia and taste buds recover . In FP perigemmal cells , the Ki67 cell expression that is reduced after HH/GLI suppression also recovers . Therefore TB progeny are not eliminated in HH signaling repression in the epithelium of these papillae but are poised to regenerate TBs , with innervation and papilla organ connective tissue core elements already in place , once HH/GLI signaling is restored . SHH-positive cells within TBs are proposed as a possible obligate stage in differentiation of all TB cell types , as post-mitotic precursors not stem cells [35] . However , we find that a subset or about 40% of TYPE III Atypical FP/No TB taste organs do not recover after HH/GLI blockade . Because these FPs lack TBs , they lack SHH ligand in the epithelium and do not attain reconstitution of HH-responding cells in the papilla epithelium . Therefore we suggest that epithelium-derived HH is essential to maintain and re-activate TB cell progenitors which may reside within TBs . We note that after 14–30 days to restore HH/GLI signaling after HH repression , the recovery of Typical FP/TB and CV taste buds is substantial but incomplete in the FP/TB . Notably , in a pharmacological block of systemic HH signaling with the HH pathway inhibitor drug LDE225 , there also is substantial loss of Typical FP and taste buds after 16 days [31] . These experiments uncovered the likely mechanisms underlying taste loss in cancer patients treated with systemic HH pathway inhibition [29 , 30] . Although with LDE225 pathway inhibition the taste buds and associated SHH were lost , a robust innervation remained within aberrant fungiform papillae . As in our genetic models to block epithelial HH signaling , there also is recovery after 14 days without the inhibitor drug , of about 50% of Typical FP/TB [60]; and these typical organs demonstrate a full complement of X-Gal-positive , HH responding cells in papilla epithelial walls and perigemmal cells . However , in LDE225 HH inhibition , and all genetic models , about 40% of taste organs are Atypical FP/No TB , and in these papillae HH-responding cells are only in the papilla core . We are studying the nature of the FP/TB that apparently are incapable of regeneration . Whereas we do not rule out a possible decrease in nerve fibers , at the light microscopic level there is no general elimination or misdirection of innervation in anterior tongue , FP and/or TB cells even after epithelial HH pathway suppression over long periods . Also , innervation remains robust in the CV in Gli2 repressor and cKO mice . Because SHH is much reduced in the taste bud , in parallel with the loss of SHH-expressing taste bud cells , the retained innervation indicates that SHH is not a major , taste bud , target-derived maintenance factor for innervation to the papilla and TB . Further , because P2X3 fibers remain in FP in Gli2 mutant and deletion tongues there is apparently not a major destruction of geniculate ganglion neurons that project via the chorda tympani to taste buds . In a pharmacologic block of HH signaling with the HH pathway inhibitor drug LDE225 we also demonstrated that although taste buds were lost , thus reducing available taste bud-derived SHH , a robust innervation remained to taste bud cell remnants and aberrant fungiform papillae [31] . However , we have localized HH-responding , Gli1lacZ-positive cells adjacent to nerve bundles and S100-labeled Schwann cells within the FP . Furthermore , within the body of the tongue Gli1lacZ-positive cells are seen along the perimeter of large bundles of the chorda tympani/lingual nerve . Overall our data put Gli1lacZ-positive cells in contiguity with nerve fibers and nerve-associated Schwann cells , possibly even in cells of the perineurium [61] . We propose that in addition to SHH in taste bud cells , there are possible sources of SHH from the geniculate ganglion and trigeminal ganglion , and via innervating nerve fibers could potentially provide local SHH ligand to Gli1lacZ-positive HH-responding cells in the taste papilla organ . SHH has been reported in trigeminal ganglion neurons in studies of pulp innervation [62] . If sensory nerve endings are a source of HH ligand from trigeminal or geniculate ganglia these could activate HH signaling in stromal cells of the FP core , as seen in hair follicle innervation [3] . There is , then , ligand from SHH released from taste buds in epithelium , much reduced with HH suppression; and , potentially from trigeminal and geniculate ganglia at nerve endings within the FP . Thus , HH-responding cells in multiple domains of the papilla organ could have access to ligand from at least two sources . Not only do we find that SHH in taste bud cells is apparently not a major target-derived support factor for FP/TB lingual innervation but also , even the sustained lingual and FP innervation is not sufficient to maintain or regenerate intact taste buds in the face of epithelial HH-repression . Innervation is necessary to maintain taste buds but on anterior tongue of mouse with combined chorda tympani and lingual nerve cut a number of taste buds remain [51] . Therefore whereas nerves are essential to transmit taste responses to the CNS and to maintain taste buds , there apparently is not a complete or sole sensory , chorda tympani nerve dependence of all adult FP taste bud cells . In mice with SHH over-expression , K8-positive , taste bud-like cells can form in lingual epithelium outside of FPs but these are not innervated and therefore are not able to transmit taste sensation [28]; this indicates a taste bud cell-like phenotype in the absence of taste innervation and chemosensory function . Therefore , the sensory nerve dependence of taste bud cells is complex [63] . The importance of stromal cells in the papilla core , adjacent to taste bud cells and their supporting epithelium , has been essentially ignored in the taste field . Stromal fibroblasts with the intermediate filament vimentin are important in cell adhesion , migration and signaling [64] and SHH can be chemotactic and interact with fibroblasts in SHH trafficking [54] . There also is ample evidence that HH signaling regulates fibroblast activity , e . g . , in kidney interstitium [65] , in lung [2 , 5] and during pancreas tumorigenesis [6] . However , despite the profound alterations in taste organs that arise after blockade of HH/GLI signaling in epithelial cells , immunostaining for fibroblasts did not reveal appreciable differences compared to Control mice . This is in contrast to mesenchymal cell proliferation when HH signaling is downregulated after injury in adult lung epithelial cells [2] . Nor did we observe a massive influx of macrophages in the papilla core . The retention of multiple cell populations , and nerve endings , in the papilla core , despite disruption of overall papilla structure , may provide a crucial microenvironment needed for recovery of taste organs after HH/GLI blockade . Sensory homeostasis demands balanced cell physiology , and physiological adjustments in major signaling pathways can alter taste function and create risk for diet selection , toxin avoidance and proper nutrition . We showed that HH/GLI signaling is essential to preserve homeostasis in taste papillae and resident TBs; this pathway operating in peripheral taste organs is , therefore , crucial for taste sensation and nutrient regulation . Our findings contribute to understanding the biological basis of taste alterations in patients who take HH Pathway Inhibitors ( HPIs ) for treatment of basal cell carcinoma [29 , 30] . The responses to genetic HH/GLI repression that we observed in FP have a similar time course to FP/TB alterations in mouse tongue after HPI administration [31] . HH repression in the lingual epithelium leads to profound loss of taste buds but nerves and connective tissue cells are maintained within taste papilla organs . Therefore , taste bud progenitor cells are strictly dependent on epithelial HH signaling , and can function to regenerate taste buds when HH signaling is restored as long as some residual TB cells remain . However , if HH and HH-responding cells are eliminated from the fungiform papilla epithelium through taste bud loss , papillae and taste buds do not recover from HH suppression . This suggests that HH in taste bud cells , acting through paracrine signaling to responding cells , is in a principal role for taste bud and papilla maintenance and restoration . To keep taste bud cell homeostasis at a necessary steady state for sensory function , epithelial HH/GLI signaling is required .
Maintenance of mice and all experimental procedures were conducted in accordance with NIH guidelines and were approved by the University of Michigan Institutional Animal Care and Use Committee ( protocols: PRO00006464 , BLA; PRO00006657 , AAD; PRO00005851 , CMM ) . Gli1lacZ/+: mice were used to indicate cells responding to HH/expressing the target gene Gli1 . Mice were maintained on mixed backgrounds . K5-rtTA;tetO-Gli2ΔC4;Gli1lacZ/+ ( K5GliR ) : doxycycline-inducible , reversible , dominant-negative inhibition of Hh/Gli target genes in K5 expressing , basal epithelial cells ( littermates negative for K5rtTA and/or tetO- Gli2ΔC4 were used as controls ) . K5-Cre;R26-LSL-rtTA;tetO-Gli2ΔC4;Gli1lacZ/+ ( epiGliR ) : doxycycline-inducible , dominant-negative inhibition of Hh/Gli target genes in K5 expressing cells and their progeny ( littermates negative for K5rtTA and/or tetO- Gli2ΔC4 and/or R26-LSL-rtTA were used as controls ) . K5-rtTA;tetO-Cre;Gli2fl/fl;Gli1lacZ/lacZ and K5-rtTA;tetO-Cre;Gli2fl/fl;Gli1lacZ/+ ( Gli2cKO ) : doxycycline-dependent , Cre-driven deletion of Gli2 in K5-expressing cells , heterozygous or null for Gli1 ( littermates negative for K5rtTA and/or tetO-Cre were used as controls ) . K5-rtTA;tetO-Cre;Gli2fl/fl;Gli1lacZ/lacZ ( Gli2cKO;Gli1KO ) : a Gli2/Gli1 double deletion in K5-expressing cells ( littermates negative for K5rtTA and/or tetO-Cre with Gli1+/+ were used as controls ) . K5-rtTA mice [66] were obtained from Adam Glick ( Pennsylvania State University ) . Each of the following strains was obtained from Jackson Labs: Gli1lacZ/lacZ ( Stock No: 008211 ) [18]; Gli2fl/fl ( Stock No: 007926 ) [67]; tetO-Cre ( Stock No: 006224 ) [68] . tetO-Gli2ΔC4 mice were generated using a mouse Gli2ΔC4 cDNA [4 , 40] inserted into pTet-Splice using standard molecular cloning techniques ( Ermilov et al in preparation ) . Doxycycline was administered in chow at 1 g or 6g doxycycline/kg chow ( Bio-Serv ) , for specified periods . Once started , doxycycline treatment for conditional , epithelium-specific gene deletion studies was continuous throughout the treatment period . For recovery studies using K5GliR mice , doxycycline administration was stopped to extinguish Gli2 expression . Animals were maintained on normal chow to monitor recovery from HH/GLI blockade . For each experiment and time point , observations were made in at least 3 experimental and 3 littermate control mice , with noted exceptions for very long experimental periods . Actual animal numbers are included in all graphs . The terminal deoxynucleotidyl transferase dUTP nick ending labeling assay ( TUNEL; Millipore Kit S7165 ) was used with manufacturer protocol to detect apoptotic cell nuclei . We studied TUNEL-positive cells in FP in one experimental and one control tongue from Gli2cKO mice at 28 days after deletion; and for CV in two experimental and two control tongues from Gli2cKO mice at 16 days after deletion and assessed distribution patterns in papilla and surrounding epithelium . We studied Cleaved Caspase 3 in FP in one experimental and one control tongue each for the K5GliR model after 5 days and for the epiGliR model after 11 days induction . Cleaved Caspase 3 in the CV was studied in one Control tongue and one Gli2cKO at 16 days after deletion . Papilla innervation was analyzed in immunoreactions with antibodies to Neurofilament Heavy ( NF200 ) and for specific chemosensory innervation with an antibody to P2X3 . We studied 1–2 experimental and one control tongue each for K5GliR and epiGliR models across 3 time points , one control and one experimental tongue from Gli2cKO mice at 28 days post induction . Innervation patterns were analyzed qualitatively to identify nerve fibers in the “basket” region just under the taste bud region ( using NF ) or within the taste bud ( using P2X3 ) and fibers directed through the middle of the papilla core . To identify fibroblasts within the FP core and discern how these cells are associated with the epithelium or with basal lamina we used double immunoreactions for vimentin and heparan sulfate proteoglycan ( HSPG ) to delineate the basal lamina . We studied 8 FP each in Gli2cKO tongues , one experimental and one control , at 28 days post induction . For each of the FP we captured images of four serial sections ( or 8 X 4 sections per tongue ) . We counted FP stromal cells that were in basal lamina contact , that is , contiguous to/touching or crossing/within the basal lamina in each tongue . In these same sections we counted vimentin-positive cells that were in the core of the papilla , that is , in the stroma not in basal lamina contact . We also counted all Vimentin-positive cells within the epithelium for each FP . To ensure that vimentin-positive cells were not macrophages or smooth muscle actin-positive cells we used immunoreactions for F4/80 or αSMA respectively . All data in figures are presented as means and standard errors . For analysis of FP types and CV measures , across time periods , we used One Way Analysis of Variance ( ANOVA ) for each papilla type , with the Least Significant Difference posthoc test , and a significance level of p<0 . 05 . Numbers of tongues/FPs are in graphs . In Supplemental Figs 1 and 9 , complete F and p values are presented for FP and CV quantification data/graphs . For all ANOVA , we pooled data from Control mice for the comparison group against Experimental time points . For Gli2cKO;Gli1KO FP analysis , to overcome small sample sizes at some time points , we compared pooled Control ( n = 6 ) with pooled data from doxy-treated Day 16 , 28 ( n = 4 ) and from Day 35 , 45 tongues ( n = 4 ) but all time points are shown in figures . In analysis of cell proliferation and stromal cells numbers , the independent samples t test , with Levene’s test for equality of variance , was used to compare differences between treatments ( significance level = p ≤ 0 . 05 ) .
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Taste papillae are small organs visible on the surface of the tongue that contain taste buds , which are connected to nerves that transmit signals for taste sensation to the brain . To function properly , taste papilla and taste bud cells need to be continuously replenished . We are studying how collections of proteins , called signaling pathways , ensure that the sense of taste is maintained . We show that one specific signaling pathway , the Hedgehog pathway , is absolutely essential for proper function of taste organs . When we block the Hedgehog pathway , nearly all taste papillae dramatically change shape and taste buds disappear . This response occurs because specific taste cell populations in the taste papillae can no longer function properly , even though taste organ nerves are still present . When we release the blockade of Hedgehog signaling , many taste papillae and taste buds are regenerated . Our findings identify a critical requirement for the Hedgehog signaling pathway in maintaining taste papillae and taste buds , help explain why cancer patients treated with Hedgehog pathway inhibitors lose their ability to taste , and suggest that changes in this pathway could be responsible for other conditions associated with taste disturbance .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Methods"
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] |
2016
|
Maintenance of Taste Organs Is Strictly Dependent on Epithelial Hedgehog/GLI Signaling
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Facial cleanliness and sanitation are postulated to reduce trachoma transmission , but there are no previous data on community-level herd protection thresholds . We characterize associations between active trachoma , access to improved sanitation facilities , and access to improved water sources for the purpose of face washing , with the aim of estimating community-level or herd protection thresholds . We used cluster-sampled Global Trachoma Mapping Project data on 884 , 850 children aged 1–9 years from 354 , 990 households in 13 countries . We employed multivariable mixed-effects modified Poisson regression models to assess the relationships between water and sanitation coverage and trachomatous inflammation—follicular ( TF ) . We observed lower TF prevalence among those with household-level access to improved sanitation ( prevalence ratio , PR = 0 . 87; 95%CI: 0 . 83–0 . 91 ) , and household-level access to an improved washing water source in the residence/yard ( PR = 0 . 81; 95%CI: 0 . 75–0 . 88 ) . Controlling for household-level water and latrine access , we found evidence of community-level protection against TF for children living in communities with high sanitation coverage ( PR80–90% = 0 . 87; 95%CI: 0 . 73–1 . 02; PR90–100% = 0 . 76; 95%CI: 0 . 67–0 . 85 ) . Community sanitation coverage levels greater than 80% were associated with herd protection against TF ( PR = 0 . 77; 95%CI: 0 . 62–0 . 97 ) —that is , lower TF in individuals whose households lacked individual sanitation but who lived in communities with high sanitation coverage . For community-level water coverage , there was no apparent threshold , although we observed lower TF among several of the higher deciles of community-level water coverage . Our study provides insights into the community water and sanitation coverage levels that might be required to best control trachoma . Our results suggest access to adequate water and sanitation can be important components in working towards the 2020 target of eliminating trachoma as a public health problem .
Trachoma is the leading infectious cause of blindness [1] . An estimated 450 , 000 people suffer from trachoma-related blindness with another 1 . 4 million suffering from trachoma-related moderate to severe visual impairment globally [2] . Trachoma is a public health problem in 42 countries , where 200 million people live in endemic areas [3] . Repeated conjunctival Chlamydia trachomatis infection , transmitted via synanthropic flies or person-to-person contact , causes scarring , and eventually ( in some people ) makes the eyelashes curl inwards , scraping the cornea , causing physical pain and leading to impaired vision [4] . Repeated infections are also associated with broader consequences such as poverty and social exclusion . [5 , 6] WHO recommends the SAFE strategy to eliminate trachoma [7]: Surgery to reposition in-turned eyelashes; Antibiotics , given via annual mass treatment; Facial cleanliness to reduce transmission; and Environmental improvement , particularly access to water and sanitation , which facilitates facial cleanliness and reduces fly-breeding sites , respectively [8] . F and E are primary preventive interventions , and A and S are secondary and tertiary preventive interventions , respectively . S and A have a solid evidence base [9 , 10] . For F and E , observational studies support implementation through associations between trachoma , poor sanitation and inadequate facial cleanliness , though evidence from individual intervention studies has been mixed [11] . Previous association studies have primarily assessed household-level exposures , ignoring potential community-level protection from water and sanitation coverage in neighboring houses . Sanitation is a public good , and ignoring community-level coverage may lead to underestimates of the importance of these exposures [12] . There is biological plausibility that increased community-level coverage of facial cleanliness and/or sanitation could reduce trachoma transmission , even to non-face washers or to those without access to sanitation . There is evidence to suggest that sanitation confers community-level or herd protection on some other health outcomes , such as anthropometric nutritional outcomes [12–15] , diarrhea [16 , 17] , and infant mortality [18] . A cluster-randomized trial in Ethiopia demonstrated a protection effect against ocular C . trachomatis infection in untreated older individuals when 1–10-year-olds were given antibiotics [19] . Some community-based studies have assessed the impact of sanitation [20] or face washing promotion [21] on trachoma , but only one study that we know of has assessed if sanitation confers herd/community-level protection on trachoma . [22] In this study , Oswald et al . found that higher community coverage levels of sanitation were associated with lower prevalence of active trachoma in Ethiopia . We aren’t aware of any studies assessing impacts of community-level facewashing on trachoma . In this study , we used data from 13 countries that participated in the Global Trachoma Mapping Project ( GTMP ) [23 , 24] . We explore community-level coverage thresholds of sanitation and of water for face washing , seeking evidence for community-level protection ( i . e . , protection due to high community-level coverage ) and for herd protection ( i . e . , protection due to high community coverage that specifically benefits those without individual access to latrines or water ) . We hypothesized we would observe indications of community or herd protection among individuals living in communities with high coverage of sanitation or high coverage of water for face washing .
All 29 GTMP-participating countries were eligible for inclusion in this study [23 , 24] . All countries were sent emails requesting participation , and those interested signed agreements to collaborate and share data . Of the Ministries of Health that responded , 13 countries had adequate WASH data and were included in the final dataset . The GTMP was generally administered at national level of participating countries , and consisted of common data collection methodologies implemented by uniformly trained fieldworkers who had been certified in diagnosing TF; this training and certification is discussed in great detail elsewhere [25] . Our dataset consisted of 2 , 176 , 563 residents from 13 countries: Côte d'Ivoire , Egypt , Guinea , Malawi , Yemen , Nigeria , Vanuatu , Ethiopia , Lao People's Democratic Republic , Solomon Islands , Democratic Republic of the Congo , Mozambique , and Benin ( Fig 1 ) . We excluded 157 , 478 individuals: 116 , 316 were absent , 21 , 996 refused participation , 749 had mental or physical impairments that prevented participation , 16 , 080 could not be examined ( because , e . g . , they kept eyes shut tight ) , and 2 , 337 had missing data on water and sanitation exposures . In analyses assessing all ages , therefore , we used data from 2 , 019 , 085 participants from 451 , 207 households in 13 , 454 clusters . However , our primary focus was on 1–9-year-olds , the standard active trachoma indicator group [8] . Of retained participants , 1 , 134 , 235 were aged ≥10 years , so the primary outcomes dataset included 884 , 850 1–9-year-olds from 354 , 990 households in 13 , 451 clusters . Data were collected between December 2012 and January 2016 by health ministry staff who had been trained and certified by the GTMP [23] . Households were sampled using two-stage or multi-stage cluster sampling , employing , as far as was practical , equal-probability sampling approaches [25] . In each selected household , information was collected from the household head on the type of water source used in the dry season for drinking water , the time taken to collect water from that source , the type of water source used in the dry season for washing faces , the time taken to collect water from that source , and the usual place of defecation for household adults . Teams then visited the household’s latrine or toilet , and recorded whether hand-washing facilities , hand-washing water , and soap were present . Survey forms are provided as supplementary materials ( S1 and S2 Texts ) . Both eyes of all household members aged ≥1-year were examined for trachoma . All data were entered directly into smartphones via a custom-built Android app [25] . Other aspects of data collection , including country-specific details , are described elsewhere [3 , 23 , 25–40] . Presence or absence of trachomatous inflammation—follicular ( TF ) and trachomatous inflammation—intense ( TI ) were each assessed in the right and left eyes . Presence of either sign is diagnostic of “active trachoma” using WHO’s simplified grading scheme [41] . Our primary outcome was TF in ( either or both eyes of ) 1–9-year-olds . Our primary outcome , assessing TF only , was chosen because tests for TF had a higher positive predictive value than for TI , and inter-grader agreement exercises for trainee graders used TF . Furthermore , we used TF , rather than TI ( or TF and/or TI ) , because it is the index recommended by WHO for determining the needs for the A , F , and E interventions against trachoma . We performed a sensitivity analysis with the outcome as TF and/or TI in either the right or left eye or both . We also performed a secondary analysis to assess the association between TF in all-ages ( rather than just 1–9-year-olds ) and our exposure variables . Our household-level exposures of interest were: binary household-level access to improved sanitation ( i . e . , improved vs . not ) , and binary household-level access to an improved source of water for face-washing located in the residence/yard ( i . e . , improved and on site vs . not ) . Each households’ sanitation facilities were observed by an enumerator who recorded the latrine/toilet type . We categorized sanitation facilities and water sources as improved or unimproved using WHO-UNICEF Joint Monitoring Program ( JMP ) for Water Supply and Sanitation definitions [42] . The main type of water source used for face washing during the dry season was reported to the enumerator by the head of household . We first categorized the water source as either improved or unimproved , as per the JMP definition [42] . The head of household also reported the distance to this water source , and because water use behaviors probably depend on distance to source [43] , we constrained the definition of “improved” water sources to those located in the residence/yard . For brevity , throughout this paper we use “household sanitation” to mean binary household-level access to improved sanitation , and the term “household water” to mean binary household-level access to an improved face washing water source in the residence/yard . Our two community-level exposure variables of interest were: the proportion of sampled households in the cluster with improved sanitation , and the proportion of sampled households in the cluster with an improved face washing water source in the residence/yard . For each individual , we estimated the surrounding prevalence of water/sanitation by aggregating household-level water/sanitation variables across the cluster , excluding that individual’s household . Including only neighboring households better represents the indirect exposure we wished to measure , and avoids forced correlation between household-level and cluster-level variables . These continuous cluster-level washing water/sanitation variables were later categorized with cut-points at each 10th percentile of coverage . Many GTMP-supported surveys used compact segment sampling , and our cluster-level coverage estimates in those cases are representative of true cluster-level prevalences . For brevity , we use herein the terms “sanitation coverage , ” and “water coverage” to describe our two community-level exposures of interest . We incorporated the following potential confounders in the models: participant’s age and sex , cluster-level TF prevalence , and country ( indicator variables included for each country ) . With infectious disease outcomes it is common to control for baseline or cluster-level prevalence of the outcome , as this variable may affect the probability of transmission to unaffected individuals [44 , 45] . We employed interaction terms to jointly characterize impact of community-level and household-level water/sanitation . Our analysis code is available by request to the corresponding author . All analyses were carried out in STATA , version 14 ( StataCorp , College Station , TX ) . To explore relationships between continuous water coverage and TF and between continuous sanitation coverage and TF , we used a log-linear binomial model and a simple linear spline with knots at each centile of water/sanitation coverage . We experimented with different placement of knots , and placed knots at each centile because it allowed us to look for deviations from nonlinearity while maintaining adequate sample size and precision within groups . For the fully adjusted models , we employed mixed-effects modified Poisson regression; log-linear binomial models were first attempted but did not converge [46] . We produced adjusted prevalence ratios ( PRs ) comparing various sanitation and water exposures and presence or absence of TF . Our first model assessed the relationship between TF and household- and community-level water variables , and household- and community-level sanitation variables . For community-level variables , we used indicator variables to denote water and sanitation coverage deciles within each cluster . We also used this model to explore the “total effect” of the community- and household-level variables together: we compared the TF prevalence for individuals living in the highest coverage decile who also had household latrines to the TF prevalence of individuals living in the lowest coverage decile who did not have household latrines . This fully adjusted model resembled the form: log ( μij ) =α+β0HHsanitationij+β1HHwaterij+∑p=2P=10βpsanitationcoveragej+∑q=2Q=10βqwatercoveragej+∑r=1Rγrconfoundersij+uj where μij represents the expected probability of the outcome in the ith participant from the jth cluster; β represents sanitation and water coefficients , and γ represents confounder coefficients . The subscript p indexes each sanitation coverage decile ( omitting the reference group ) , q indexes each washing water coverage decile ( omitting the reference group ) , and r indexes each confounder variable . A random intercept , uj , is included to account for clustering within the jth community . To assess for linearity between water/sanitation coverage and TF , we used a similar model , but instead of including ten separate indicator variables , we included a ten-level ordinal variable . To jointly characterize the interaction between community- and household-level water/sanitation variables , we created a second model . This interaction model allowed us to explore a possible “indirect effect” [15] of community-level coverage among those lacking household-level access . The fully adjusted interaction model resembled the form: log ( μij ) =α+β0HHsanitationij+β1HHwaterij+∑p=2P=10βpsanitationcoveragej+∑q=2Q=10βqwatercoveragej+∑r=1Rγrconfoundersij+∑p=2P=10δpsanitationcoveragej×HHsanitationij+∑q=2Q=10δpwatercoveragej×HHwaterij+uj Interaction coefficients in the above are represented by δ . The “Sanitation coverage × HH sanitation” term captures interactions between the pth sanitation coverage decile and the household sanitation variable . Similarly , the “Water coveragej × HH waterij” terms capture interactions between the qth washing water coverage decile and the household water variable . We performed a sensitivity analysis to assess the association between any sanitation use ( rather than improved sanitation ) and TF . We also performed a sensitivity analysis to assess the association between any washing water located in the residence/yard ( rather than improved and located in the residence/yard ) and TF . Finally , we performed a sensitivity analysis to assess the association between having a washing water source within 30 minutes compared to ≥30 minutes and TF . For each of these sensitivity analyses , the household sanitation and water variables were aggregated to create a community-level variable ( analogous to our creation of coverage variables for the primary analyses ) . Each model was similar to the first model described above , substituting the new variable of interest . Our main analyses used data from all 13 countries with the goal to improve generalizability . However , we also did some additional analyses on specific sub-populations to further asses internal validity . Musca sorbens is not known in Vanuatu , Lao , or the Solomon Islands , so we performed a sensitivity analysis to assess our sanitation findings , without including these three countries . Another reason for using data from all 13 countries , is that the models require lots of observations . Nigeria contributed enough data ( and had enough variability in their data ) to run a model specific to Nigeria only , and we present a sensitivity analysis using this country only . It was determined by the Emory IRB that no IRB review was required for our secondary analyses on de-identified data ( IRB00091226 ) .
The final dataset consisted of 884 , 850 1–9-year-olds from 354 , 990 households from 13 countries ( Table 1 ) . Of these 884 , 850 1–9-year-olds , 8 . 2% ( SE = 0 . 1% ) had TF . TF prevalence was lower when including participants of all ages ( prevalence = 4 . 4%; SE = 0 . 1%; S1 Table ) . The intra-cluster correlation coefficient for TF was 0 . 54 . Of 354 , 990 included households , 18 . 1% ( SE = 0 . 3% ) had household sanitation , and 11 . 5% ( SE = 0 . 2% ) had household water ( Table 1 ) . Prevalences of TF , household sanitation , and household water varied across countries . Unadjusted analyses showed that communities in the lowest water and sanitation coverage decile had the highest TF prevalence ( Fig 2 ) . As sanitation coverage increased from 0% to 100% , the TF prevalence generally decreased ( Fig 2 ( A ) ) . As water coverage increased from 0% to 10% , there was a steep decrease in TF prevalence , after which the TF prevalence remained relatively flat in the 20–100% coverage range ( Fig 2 ( B ) ) . The high TF prevalence in the first deciles of water and sanitation coverage were heavily driven by data from Ethiopia , which contributed 174 , 628 1–9-year-olds with high TF prevalence ( 22 . 6% ) , and very low household water ( 1 . 9% ) and sanitation ( 5 . 6% ) . Our first model assessed the relationship between TF and household- and community-level water variables , and household- and community-level sanitation variables . TF prevalence was lower among those with household sanitation ( prevalence ratio [PR] = 0 . 87; 95% CI: 0 . 83 , 0 . 91; Table 2 ) , compared to those without . A lower TF prevalence was also found among those with household water ( PR = 0 . 81; 95% CI: 0 . 75 , 0 . 88 ) compared to those without . When considering community-level sanitation coverage , we observed lower levels of TF for participants living in communities with at least 90% sanitation coverage ( PR90–100% = 0 . 76; 95% CI: 0 . 67 , 0 . 85 ) compared to those living in communities with 0–10% coverage . We also observed lower TF levels , although marginally insignificant ( p = 0 . 09 ) , for participants living in communities with 80–90% latrine coverage ( PR80–90% = 0 . 87; 95% CI: 0 . 73 , 1 . 02 ) . As for washing water coverage , several of the estimates comparing higher coverage deciles to the lowest coverage decile had lower prevalences of TF ( Table 2; Fig 3 ) . To assess for linearity between water/sanitation coverage and TF , we used a similar model , but instead of including ten separate indicator variables , we included a ten-level ordinal variable . There was a linear trend between sanitation coverage and TF ( p-trend = 0 . 008; Table 2 ) ; however , this trend was driven largely by decreases in TF prevalence only at coverage >80% ( Fig 3 ) . There was a linear trend ( p-trend = 0 . 038; Table 2 ) between water coverage and TF; however , the graphical representation of this relationship is more V-shaped than linear ( Fig 3 ) . We also use parameters from the first model to characterize the “total effect” of the community- and household-level variables together . The PRs due to having sanitation both at home and across the community compared to not having sanitation in either place were highly significant ( PR80–90%+home = 0 . 75; 95% CI: 0 . 64 , 0 . 88; PR90–100%+home = 0 . 65; 95% CI: 0 . 58 , 0 . 74; Fig 4 ) . The PRs contrasting the “total effect” due to having water both at home and across the community compared to not having water in either place were all significant ( Fig 4 ) . To jointly characterize the interaction between community- and household-level water/sanitation variables , we used the model with interaction terms . Our results indicated evidence for “herd protection” at sanitation coverage ≥80% ( PR = 0 . 77; 95% CI: 0 . 62 , 0 . 97; Fig 5 ) . There was no clear relationship between water coverage and TF ( Fig 5 ) . Using deciles instead of quintiles with these interaction terms led to many estimates having wide confidence intervals ( S1 Fig ) , so our preferred analysis was that which used quintiles ( Fig 5 ) . Our sensitivity analysis to assess the association between TF and our exposure variables in all-ages ( rather than just 1–9-year-olds ) showed a nearly identical relationship between water and sanitation coverages and TF ( S2 Table; S2 Fig ) . Our sensitivity analysis to assess the association between any sanitation use ( rather than improved sanitation ) and TF showed no evidence of lower TF with increasing sanitation coverage ( S3 Table; S3 Fig ) . The sensitivity analysis to assess the association between any washing water located in the residence/yard ( rather than improved and located in the residence/yard ) and TF showed evidence of lower TF in the upper two water coverage deciles ( S4 Table; S4 Fig ) . The sensitivity analysis to assess the association between having a washing water source within 30 minutes compared to ≥30 minutes and TF showed no evidence of lower TF ( and perhaps an increase ) with increasing community-level water coverage ( S5 Table; S5 Fig ) . The sensitivity analysis with the outcome as TF and/or TI produced results that were nearly identical to those from the main analysis assessing TF only ( S6 Table; S6 Fig ) . In the sensitivity analysis in which we dropped those countries where Musca sorbens is not known , the sanitation results were very similar to those results from all countries ( S7 Fig ) . Finally , in the sensitivity analysis where we analyzed the Nigeria data alone , we observed associations that indicate community-level protection against TF due to high coverage of sanitation , but also protection due to high coverage of water ( S8 Fig ) .
Our results are congruent with the belief that water , sanitation and hygiene are important for accelerating efforts towards global trachoma elimination as a public health problem [3 , 56] . Our findings are also in support of Sustainable Development Goal 6 , which calls for availability and sustainable management of water and sanitation for all [57] . We provide some evidence of the importance of reaching high water and sanitation coverage levels in order to confer health benefits . While we observed the lowest TF prevalences among people living in the highest sanitation coverage deciles , actually attaining these high sanitation coverage levels may take significant effort , as non-adopters tend to be of lower SES , more marginalized , less educated , and often living in more difficult-to-reach locations [58 , 59] . A systematic review assessing the impact of sanitation interventions suggested that only 7 of 27 interventions would achieve sanitation coverage of >80% [60] , the level that our data suggests might be required to confer community-level or herd protection against trachoma . Achieving higher sanitation among lower SES groups might be particularly beneficial , in that trachoma is more likely to affect such populations [47 , 48] . Our findings indicate that even if communities are initially unable to attain the high community-wide sanitation prevalences that might be required to attain community-level or herd protection , there may still be direct benefits of individual households having access to both sanitation and washing water .
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Trachoma is the leading infectious cause of blindness . Previous association studies have primarily assessed household-level exposures , ignoring potential community-level protection from water and sanitation coverage in neighboring houses . There is biological plausibility that increased community-level coverage of facial cleanliness and/or sanitation could reduce trachoma transmission , even to non-face washers or to those without access to sanitation . Our study investigates relationships between active trachoma and community-level coverage of sanitation and water , is novel in concept and unprecedented in scale , including data from trachoma-endemic areas of 13 countries . Our findings support the plausibility of community-level or herd protection from trachoma with increasing water and sanitation coverage . We also observed lower TF prevalence among those with household-level access to sanitation and water . Our results suggest access to adequate water and sanitation can be important components in working towards the 2020 target of eliminating trachoma as a public health problem .
|
[
"Abstract",
"Introduction",
"Methods",
"Results",
"Discussion"
] |
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"medicine",
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2018
|
Sanitation and water supply coverage thresholds associated with active trachoma: Modeling cross-sectional data from 13 countries
|
Sleep , a reversible quiescent state found in both invertebrate and vertebrate animals , disconnects animals from their environment and is highly regulated for coordination with wakeful activities , such as reproduction . The fruit fly , Drosophila melanogaster , has proven to be a valuable model for studying the regulation of sleep by circadian clock and homeostatic mechanisms . Here , we demonstrate that the sex peptide receptor ( SPR ) of Drosophila , known for its role in female reproduction , is also important in stabilizing sleep in both males and females . Mutants lacking either the SPR or its central ligand , myoinhibitory peptide ( MIP ) , fall asleep normally , but have difficulty in maintaining a sleep-like state . Our analyses have mapped the SPR sleep function to pigment dispersing factor ( pdf ) neurons , an arousal center in the insect brain . MIP downregulates intracellular cAMP levels in pdf neurons through the SPR . MIP is released centrally before and during night-time sleep , when the sleep drive is elevated . Sleep deprivation during the night facilitates MIP secretion from specific brain neurons innervating pdf neurons . Moreover , flies lacking either SPR or MIP cannot recover sleep after the night-time sleep deprivation . These results delineate a central neuropeptide circuit that stabilizes the sleep state by feeding a slow-acting inhibitory input into the arousal system and plays an important role in sleep homeostasis .
Sleep is an evolutionarily conserved physiological state marked by sustained and reversible quiescence during which animals display reduced responsiveness to external stimuli [1] . Sleep is important for diverse biological processes , such as immune responses , metabolism , obesity , longevity , and learning and memory , and reduction in the quality and quantity of sleep in humans , can give rise to sleep disorders and increased morbidity [2] , [3] . Despite its medical importance and wide occurrence across animal phylogeny , the evolutionary and functional origins of sleep remain poorly understood [4] . Recently , the fruit fly Drosophila melanogaster has become an important invertebrate model for sleep research [5] , [6] . This genetically amenable organism has a simpler central nervous system ( CNS ) and shares defining characteristics of mammalian sleep , such as reduced sensory responsiveness , dual circadian and homeostatic regulation , and reduced brain activity [7]–[10] . Genetic studies on Drosophila have identified many molecules and pathways important for sleep control , many of which have conserved roles in regulating mammalian sleep [1] , [5] . As in mammals , GABAergic signaling promotes sleep in Drosophila mainly by suppressing activities of the arousal systems [4] , [11] , [12] . Studies on a GABAA receptor mutant revealed that sleep onset and sleep maintenance are genetically dissociable [2] , [3] , [13] . However , how sleep initiation and maintenance are differentially regulated is not known . Sleep is governed mainly by two regulatory systems: circadian and homeostatic drive . The molecular model that explains circadian control of the wake-sleep cycle is well established ( for a review , [5] ) . In contrast , no coherent mechanism for sleep homeostasis is yet available . Sleep is also shaped by other competing or complementary behaviors , such as ones associated with learning , feeding , and reproduction [5] , [6] , [14] . Mating was shown to induce female Drosophila to sleep less , particularly during the daytime [15] . Sex peptide ( SP ) , a male seminal protein transferred to the female during copulation [16] , [17] , was implicated in the post-mating reduction of siesta sleep , because females that copulated with males lacking SP did not lose sleep . Sex peptide receptor ( SPR ) , a G-protein coupled receptor ( GPCR ) mediates many of the actions of SP on female reproductive behavior [18] . On transfer to the female , SP activates SPR in a small number of uterine neurons and triggers post-mating behavioral responses ( PMR ) , characterized by ( but not restricted to ) suppression of mating receptivity and initiation of egg laying [19] , [20] . For the PMR induction , SPR is required only in a small number of female-specific internal sensory neurons . However , SPR expression in the CNS is broad , and shows little sexual difference , suggesting it has additional roles in both males and females [18] . Recently , the brain-gut myoinhibitory peptides ( MIPs ) ( also known as allatostatin-B or prothoracicostatic peptides ) , have been shown to also activate SPR when expressed heterologously in mammalian cells [21]–[23] . Unlike SP , however , MIP , which is expressed in the central interneurons with little sexual dimorphism [24] , is unable to induce the PMR in Drosophila females [21] . Thus , the biological function of MIP-SPR signaling in Drosophila remains elusive . Here , we demonstrate that mutants lacking either SPR or its ligand , MIP , slept less regardless of sex and mating status , primarily because of difficulty in maintaining sleep . By combining genetic analyses and optical activity imaging , we found that SPR mediates MIP actions to modulate neural activities of a fly arousal system involving pigment dispersing factor ( pdf ) neurons . The brain MIP neurons release MIP before and during night-time sleep . Sleep deprivation facilitates MIP secretion from a small subset of brain neurons , axonal processes of which innervate dendritic fields of pdf neurons . Mutants lacking either SPR or MIP failed to show normal sleep homeostasis . We conclude that the MIP-SPR signaling pathway functions as a sleep homeostat that senses the need for sleep and stabilizes sleep by providing a slow-acting inhibitory input to an arousal center .
To determine whether SPR was necessary for the SP-induced daytime sleep loss , we examined the sleep profile of the SPR-deficient mutants ( SPR−/− ) that carry a micro-deletion of the genomic region containing SPR and a few neighboring genes . The SPR−/− females fail to switch reproductive behaviors upon mating or SP injection [18] . To control for possible genetic background differences , we compared wild-type Canton-S ( CS ) flies with SPR-deficient mutants backcrossed with CS for six generations . We examined the sleep profiles of virgin females , mated females and males separately . Strikingly , the SPR-deficient mutants slept less than the isogenic wild-type counterparts regardless of sex and mating status ( virgin versus mated ) ( Figure 1A–1K ) . However , virgin and mated females demonstrated almost equal levels of daily sleep in any given genotype ( Figures 1B and S1 ) . In CS females , the mating effects on siesta sleep are temporary and do not last more than three days after mating ( RE Isaac , unpublished data ) . Because we examined the sleep profile of females at least 5 days after mating , this observation may explain the absence of a mating effect on sleep in our experiments . Nevertheless , lack of SPR expression suppressed both day- and night-time sleep duration by approximately 48% and 77% , respectively , compared to CS virgin females ( Figure 1A and 1B ) . This observation contrasts with the daytime sleep loss reported previously for mated females , suggesting that SPR has a role in sleep regulation independent of mating status . In terms of waking activity , however , SPR-deficient mutants did not differ from CS , indicating that the sleep loss observed in mutants is not attributable to nonspecific hyperactivity ( Figure 1C and 1H ) . We also measured the number of sleep bouts and the average length of each sleep bout , which indicates sleep initiation and sleep maintenance abilities , respectively . The SPR-deficient mutant had almost the same number of sleep bouts , but markedly shorter average sleep-bout length compared to wild-type flies ( Figure 1D , 1E , 1I , and 1J ) . Since environmental light was shown to affect sleep in Drosophila [25] , we examined the baseline sleep of the SPR deficient mutant in light-dark ( LD ) and dark-dark ( DD ) environments . In both conditions , the SPR mutant displayed significant reductions in daytime and night-time sleep ( Figures 1F , 1K , S2A , and S2B ) . To test whether SPR expression in the nervous system is sufficient for normal sleep behavior , we introduced elav-Gal4 and upstream activation sequence ( UAS ) -Drosophila SPR ( DrmSPR ) into the SPR-deficient mutant lines . In these flies , we observed complete rescue of the sleep phenotype in both sexes ( Figure 1L and 1M ) . Subsequently , we tested whether the sleep phenotype was rescued by expressing SPR in pickpocket ( ppk ) neurons , in which SPR expression is essential for the SP-induced PMR [19] , [20] . Unlike PMR , sleep was not restored by SPR expression in ppk neurons , indicating that the sleep-regulating SPR circuit can be separated from the PMR-regulating SPR circuit ( Figure 1L ) . On the basis of these results , we conclude that SPR is essential for baseline sleep maintenance in both males and females . To map the SPR neurons responsible for sleep regulation , we suppressed SPR expression in the major sleep circuits using SPR-RNAi . First , we confirmed SPR-RNAi efficacy on the sleep phenotype by examining pan-neural SPR-RNAi ( elav-Gal4/UAS-SPR-IR1 ) ( Figure S3 ) . Like SPR-deficient mutants , pan-neural SPR-RNAi flies slept considerably less than controls , regardless of sex and mating status , and their total sleep loss was attributable mainly to reduced sleep-bout duration ( Figure S3 ) . Next , we ran the SPR-RNAi screen with 15 Gal4 drivers , targeting either the sex-behavior circuit or known sleep-control circuits , including ellipsoid body , mushroom body , fan-shaped body , monoaminergic , and circadian clock neurons ( Figure 2A ) . Knockdown of SPR expression in fruitlessGal4 neurons [26] , [27] did not produce the sleep phenotype , but it did result in defects in the female PMR [18] . Again , this result dissociates the SPR circuit regulating sleep from the circuit regulating sexual behavior . In this screen , we identified three circadian clock-specific Gal4 neural populations in which SPR expression is required for wild-type levels of sleep ( Figure 2A ) : cry-Gal4 [28] , C929-Gal4 [29] , and pdf-Gal4 [30] . SPR knockdown resulted in significant sleep loss with all three Gal4 lines . To test whether SPR expression in these Gal4 neurons was sufficient for wild-type sleep levels , we combined each of these Gal4 drivers with UAS-DrmSPR in SPR-deficient mutants . When SPR expression was restored in cry-Gal4 , C929-Gal4 , or pdf-Gal4 neurons , the sleep phenotype was completely rescued ( Figure 2B ) . However , expression of Tribolium castaneum SPR ( TrcSPR ) , which is insensitive to both SP and MIP ( see Materials and Methods ) , did not rescue . Overexpression of DrmSPR or Aedes aegypti SPR ( AeaSPR ) in control background using the pan-neural elav-Gal4 did not elevate sleep levels ( Figure S4 ) . Among three Gal4 neuron populations in which SPR expression was essential for sleep function , pdf-Gal4 had the most restricted expression pattern . Thus , we investigated whether pdf neurons express SPR by staining brains in which pdf neurons produce enhanced green fluorescent protein ( EGFP ) with anti-SPR antibody . The pdf-Gal4 neurons are largely divided into two groups: the large and small lateral ventral neurons ( l-LNvs and s-LNvs ) . We detected anti-SPR staining in both groups of pdf neurons , as well as many other CNS cells ( Figure 2C ) . As expected , pdf neurons in brains of SPR-deficient mutants did not stain with the SPR antibody ( Figure 2C ) . Previously , Rosbash and colleagues used microarray technology to identify 1 , 000 to 2 , 000 mRNAs enriched in either l-LNvs or s-LNvs as compared to the population of neurons labeled by the pan-neuronal driver elav-Gal4 [31] . We were able to verify from their results that SPR is significantly enriched in l-LNvs , but not in s-LNvs . It should be noted that lack of enrichment does not mean absence of expression . Recently , it was reported that s-LNvs release the inhibitory short neuropeptide F ( sNPF ) , which stabilizes night-time sleep by acting on l-LNvs [32] . Since this result implicated differential roles of l-LNvs and s-LNvs in sleep regulation , we examined day- and night-time sleep separately in SPR-RNAi targeting either pdf-Gal4 neurons , including both l-LNvs and s-LNvs , or C929-Gal4 , including l-LNvs and other peptidergic secretory neurons , but not s-LNvs . Knockdown of SPR expression in l-LNvs with C929-Gal4 reduced night-time sleep , but not daytime sleep ( Figure S5A–S5C ) , and sleep-bout duration was only reduced during night-time ( Figure S5D and S5E ) . In addition , knockdown of SPR in both l- and s-LNvs with pdf-Gal4 reduced day- and night-time sleep and average sleep-bout duration together ( Figure S5F–S5J ) , suggesting that SPR in s-LNvs regulates sleep in daytime . Together , these results suggest that SPR modulates functions of s-LNvs and l-LNvs , resulting in stabilization of daytime and night-time sleep , respectively . SPR has two unrelated peptide ligands , SP and MIP . Unlike SP , MIP is expressed in central neurons of both males and females [21] , [33] . Because we observed a sleep phenotype in both sexes of SPR-deficient mutants , we suspected that MIP rather than SP is the sleep-regulating ligand of SPR . To test this hypothesis , we examined the sleep profile upon knockdown of MIP expression in the nervous system ( elav-Gal4 , UAS-MIP-IR; henceforth referred to as MIP-RNAi ) . To control for potential off-target effects , two independent RNAi lines ( UAS-MIP-IR1 and UAS-MIP-IR2 ) were tested in parallel ( Figures 3 and S6 ) . Anti-MIP staining in the CNS confirmed the knockdown of MIP in two RNAi lines ( Figure S7 ) . Both sexes of MIP-RNAi flies slept less than controls . Sleep loss was evident both day and night and was due to shortened sleep-bout duration , but not changes in the number of sleep bouts . Moreover , like the SPR deficient mutant , MIP-RNAi flies sleep less in both LD and DD conditions ( Figures 3 , S2C , and S2D ) . These sleep phenotypes are strikingly similar to those observed in SPR-RNAi and SPR-deficient mutants , further indicating that MIPs are the sleep-regulating ligands for SPR . Some insect SPRs are highly sensitive to Drosophila MIP , but much less so to Drosophila SP [18] , [21]–[23] . For example , DrmSPR is highly sensitive to MIP ( EC50 , 0 . 5 nM ) and SP ( EC50 , 4 . 3 nM ) , whereas AeaSPR is sensitive to MIP ( EC50 , 0 . 5 nM ) but less so to SP ( EC50 , 167 nM ) . Likewise , Bombyx mori SPR ( BomSPR ) is highly sensitive to MIP ( EC50 , 7 . 6 nM ) , but shows modest sensitivity to SP ( EC50 , 67 nM ) . Hence , we asked whether DrmSPR that is sensitive to both MIP and SP could be functionally substituted by AeaSPR and BomSPR , both of which are sensitive to MIP but not to SP . Pan-neural expression of these SPRs rescued the sleep phenotype of SPR-deficient mutants completely , but expression of TrcSPR , which is insensitive to both SP and MIP , did not ( Figure S8 ) . Together , these results provide additional support for MIP as both a pharmacologically and behaviorally relevant ligand for the SPR . To control indirect developmental effects of SPR or MIP knockdown on sleep , we adopted the RU486-activated gene switch ( GS ) -Gal4 system [34] and tested whether adult-restricted knockdown of SPR or MIP also produces the short sleep phenotype . SPR-RNAi adults carrying pdf-GS-Gal4 were fed with RU486 or vehicle-containing food for two days prior to the sleep measurement ( Figure S9A ) . Compared with vehicle-treated controls , RU486-treated adults showed significant reductions in daytime and night-time sleep ( Figure S9B and S9C ) , underscoring the adult-specific function of SPR in baseline sleep regulation . In parallel experiments , we examined MIP-RNAi combined with elav-GS-Gal4 . Like SPR-RNAi , adult-restricted MIP-RNAi also reduced sleep levels significantly in daytime and night-time ( Figure S9D and S9E ) . With these results , we conclude that adult-specific expression of SPR and MIP is important for maintaining normal baseline sleep . Having shown that both SPR , and its ligand MIP , are essential for sleep maintenance and that wake-promoting pdf neurons are key SPR neurons , we next investigated whether MIP modulates the activity of pdf neurons through SPR . In the isolated brain , pdf neurons respond to bath-applied peptides , such as PDF and diuretic hormone 31 , by upregulating intracellular cAMP [35] . As a GPCR , SPR can signal through two trimeric G protein pathways , Gα-i and Gα-o [18] , [19] , both of which downregulate intracellular cAMP upon activation . Therefore , we monitored MIP-induced cAMP dynamics in pdf neurons using Epac1-camps , a fluorescence resonance energy transfer ( FRET ) -based cAMP sensor [35] , [36] . Upon binding to cAMP Epac1-camps undergoes a conformational change to increase inverse YFP/CFP FRET signal . Using pdf-Gal4/UAS-Epac1-camps females , we asked if the l-LNvs are responsive to synthetic MIP peptide . Bath perfusions of MIP at 10–100 µM resulted in significant reductions in inverse Epac1-camps FRET ( henceforth , reduction of cAMP ) in l-LNvs , compared to vehicle control ( Figure 4A and 4B ) . Perfusions of MIP at 1 and 3 µM concentrations yielded inhibitory trends , but a comparison of maximal loss of inverse FRET did not reveal a statistically significant difference from vehicle controls . We also examined s-LNvs in the explanted brain . Like l-LNvs , s-LNvs also displayed inhibitory trends in response to MIP at concentrations higher than 10 µM; however , these were of lower magnitude and more variable compared to the responses of the l-LNvs ( Figure S10 ) . Next , we asked whether MIP action on the l-LNvs occurs through SPR by examining MIP-induced cAMP dynamics in the l-LNvs of SPR-deficient mutants ( SPR−/−; pdf-Gal4/UAS-Epac1-camps ) . Unlike wild-type neurons , mutant neurons did not display obvious reduction in cAMP in response to 50 µM MIP ( Figure 4C ) . When SPR expression was rescued in SPR−/− mutant l-LNvs , these neurons now responded to 50 µM MIP with a reduction in the cAMP ( Figure 4C ) . These results support the hypothesis that MIP acts directly to reduce cAMP levels in pdf neurons through SPR . In our ex vivo cAMP monitoring experiments , the minimum MIP concentration required to elicit statistically significant maximum Epac1-camps inverse FRET changes in l-LNvs neurons was ∼10 µM . This is substantially higher than the MIP concentration required for SPR expressed in cultured cells to start responding , which is around 1 nM . Because we did not remove neurolemma , a blood-brain barrier that separates bathing saline and the brain neurons , it was expected that much higher doses of peptides would be necessary to elicit a response detectable with live brain imaging . Similarly , pdf neurons expressing PDF receptor ( PDFR ) start to respond to micromolar concentrations of bath-applied PDF in the explanted brain [35] , whereas PDFR in cultured cells can respond to PDF at a concentration as low as 0 . 1 nM [37] , [38] . Furthermore , low doses of cAMP function mainly via the cAMP-dependent protein kinase A ( PKA ) , whereas higher cAMP concentrations exert additional effects through Epac [39] . Indeed , in some case the Epac1-camps sensor failed to report low levels of cAMP , which a PKA-based cAMP sensor could reliably detect [40] . Thus , it is also possible that low concentrations of MIP modulate pdf neurons by reducing PKA activity without causing measurable FRET changes in the Epac1-camps cAMP sensor . Since MIP appears to display some inhibitory effects on the s-LNvs , key pacemaker cells controlling the circadian rhythm [41] , [42] , we examined the circadian rhythm of flies lacking either SPR or MIP , but detected no obvious defect ( Figure S11; Table S1 ) . In addition , they also displayed intact morning anticipations both in LD and DD conditions , suggesting that the rather weak and variable SPR-MIP signaling within the s-LNvs is dispensable for pacemaker functions ( Figure S11 ) . Our results show that MIP is a sleep-promoting factor , which presumably reduces the excitability of wake-promoting pdf neurons by decreasing their intracellular cAMP levels . As a sleep regulator , MIP would be released prior to or during sleep . Thus , we used an anti-MIP antibody to measure MIP levels during normal sleep-wake cycles . Remarkably , the intensity of anti-MIP activity in the brain oscillates throughout the cycle . The oscillation is synchronized in most brain MIP neurons and processes ( Figure 5A and 5B ) . The brain anti-MIP level increases early in the morning ( zeitgeber time [ZT] 0 ) and stays elevated during daytime ( ZT 0–8 ) . Then , it drops markedly at ZT 12 , prior to onset of the night-time sleep phase , and remains low during the night . The strongest reduction was detected at ZT 20 h , when the sleep stabilizing drive is most required ( Figure 5B ) . Unlike the brain , the ventral nerve cord ( VNC ) showed no sign of anti-MIP oscillation ( Figure 5B ) . Next , we examined MIP mRNA levels in the brain using in situ hybridization . Unlike anti-MIP activities , the MIP transcript level does not oscillate and remains stable during the wake-sleep cycle ( Figure 5C ) . This result was also confirmed by quantitative reverse transcription PCR experiments , which showed that MIP mRNA in the head remains constant throughout the day ( Figure 5D ) . In contrast , the transcript levels of a central clock gene period changed during the cycle , and revealed the peak level at ZT 8 and 12 . Because neuropeptides are packaged in large dense-core vesicles and transported to distal axon terminals slowly [43] , it takes at least several hours to replenish the peptide vesicle pools after depletion [44] . Thus , the strong reduction of anti-MIP staining without measurable changes in transcript levels reflects massive secretory activity of the brain MIP neurons . To verify that the loss of anti-MIP staining is a consequence of prolonged neural activation , we used the Drosophila transient receptor potential A1 ( dTrpA1 ) , a warmth-activated cation channel , to confirm that thermal activation of MIP neurons depletes anti-MIP staining , almost completely ( Figure S12 ) . All together , these results strongly suggest that MIP neurons in the brain become active between ZT 8 and ZT 20 , and secrete their peptidergic contents constitutively and synchronously , during which time the sleep drive is greater than any other time of the day . The marked reduction of the brain anti-MIP levels during sleep cycle is consistent with the release of MIP to promote sleep in vivo . To further explore this hypothesis , we asked whether sleep deprivation changes MIP levels in the brain . Since MIP works as a sleep-promoting factor and its level decreases during the sleep state , sleep deprivation should drive flies to release MIP continuously , and in consequence result in considerable loss of anti-MIP staining . Indeed , 12 h-long mechanical sleep deprivation significantly reduced anti-MIP labeling ( Figure 6A–6C ) . The loss of anti-MIP labeling was particularly evident in axons of the lateral MIP-immunoreactive optic lobe ( LMIo ) neurons innervating the optic lobe medulla ( Figure 6C ) , but less pronounced in axons of other MIP neurons arborizing the median lateral protocerebrum ( MLP ) , dorso-lateral protocerebrum ( DLP ) , and suboesophageal ganglion ( SOG ) ( Figure 6C and 6D ) . A strong reduction of anti-MIP labeling in LMIo indicates massive secretion of MIP from this site during sleep deprivation . We noted that anti-MIP staining in MLP was elevated moderately after sleep deprivation . The processes arborizing MLP come from inferior contralateral interneurons ( ICLI ) , a pair of neurons that express natalisin ( NTL ) , a tachykinin-like neuropeptide implicated in sexual activities of both sexes , as well as MIP ( Figure S13A and S13B ) [45] . Thus , we examined sleep functions of ICLI by suppressing MIP expression using NTL-Gal4 driver , and found that ICLI-specific knockdown of MIP did not affect the baseline sleep architecture ( Figure S13C and S13D ) . Nevertheless , the observation that sleep deprivation suppresses secretory activities of ICLI that are important for sexual behavior raises an intriguing possibility that ICLI may serve as a link between sleep and sexual activity . Sleep is under the control of two regulatory systems , circadian and homeostatic , which define sleep timing and duration , respectively [46] . Since MIP-LMIo neurons deplete their contents in response to sleep deprivation , we suspected that MIP-SPR pathway may play a role in maintaining sleep homeostasis . To test this , the SPR deficient mutant and its isogenic control were subjected to 12 h-long mechanical sleep deprivation during the night ( ZT 12–24 ) , and allowed to recover the sleep loss in the following morning ( Figure 7A ) . With this protocol , control flies showed a significant amount of sleep rebound ( ∼20% of lost sleep ) after sleep deprivation . In contrast , the SPR deficient mutant showed no sleep rebound ( Figure 7B ) . In parallel , we also observed lack of sleep rebound in pdf neuron-specific SPR-RNAi ( pdf-Gal4/UAS-SPR-IR1 ) , indicating that SPR expression particularly in pdf neurons is required for the normal sleep homeostasis ( Figure 7C ) . Next , we investigated sleep rebound of pan-neuronal MIP-RNAi flies . Compared to controls , elav-Gal4/UAS-MIP-IR1 showed a significant reduction in sleep rebound when measured for 12 h , but not for 6 h ( Figure 7D ) . The lack of phenotype in the 6 h rebound could be due to insufficient knockdown of MIP expression in this particular genotype . Thus , we adopted a stronger elavC155-Gal4 driver , and confirmed that elavC155-Gal4/UAS-MIP-IR1 flies had greatly attenuated sleep rebound for both the 6 and 12 h periods after sleep deprivation ( Figure 7E ) . With these data , we conclude that MIP-SPR signaling pathway is important for the Drosophila sleep homeostasis . Marked reduction of anti-MIP labeling in the medulla of sleep-deprived flies suggests that LMIo neurons are linked to sleep regulation . Furthermore , SPR-positive pdf neurons also arborize on the entire distal surface of the medulla ( Figure 8A ) . To determine whether the dendritic field of pdf neurons contacts axonal processes of LMIo neurons , we prepared flies expressing a dendrite marker [47] in pdf neurons ( pdf-Gal4/UAS-DenMark ) and simultaneously visualized both the dendrite marker and MIP ( Figure 8B ) . The dendrites of the pdf neurons are distributed around the base of the medulla and in a few locations closely apposed to MIP-positive processes of LMIo neurons ( arrowheads and arrows in Figure 8B′ ) . Overall , however , the staining pattern of pdf neuron dendrites and MIP-positive axonal varicosities in the medulla suggest that they are unlikely to make synaptic contacts ( Figure 8B″ ) . We propose , therefore , that MIP may act like many other neuromodulators via volume transmission [48] . In other words , it diffuses to activate SPR on the dendrites and somas of l-LNvs and s-LNvs .
Here we report the discovery of a peptidergic modulatory pathway particularly important in stabilizing sleep and maintaining sleep homeostasis in Drosophila . The key molecules in this novel sleep-regulating pathway are SPR and its peptide ligand MIP . SPR was first identified as a receptor that triggers PMR by mediating actions of the seminal protein SP in females [18] . Although previous biochemical studies demonstrated that SPR could interact with MIP as well as SP , there was no evidence that the interaction between MIP and SPR is biologically relevant in Drosophila [21] . By combining genetic analyses and optical activity imaging , we provide several independent lines of evidence demonstrating that MIP consolidates sleep state and maintain sleep homeostasis by acting through SPR expressed in arousal-promoting pdf neurons . First , flies lacking either SPR or MIP have a highly similar sleep phenotype . Second , sleep phenotypes of MIP or SPR mutant are manifested regardless of sex , consistent with previous accounts that unlike SP , MIP and SPR expression in the brain show little sexual difference [18] , [33] . Third , ex vivo optical activity imaging revealed that exogenous application of MIP downregulates cAMP levels in SPR-expressing pdf neurons , but not in SPR-deficient mutant neurons . Fourth , the sleep phenotypes of SPR-deficient mutants are rescued by restoring SPR expression with insect SPRs that are highly sensitive to MIP , but less sensitive to SP . Hence , SPR interacts with two evolutionarily unrelated sets of ligands , each of which controls completely different behaviors: SP for reproductive behaviors and MIP for sleep behavior . For sleep behaviors , all phenotypes observed in the SPR deficient mutant were also observed in MIP-RNAi . Thus , there is no reason to assume additional ligand ( s ) for SPR besides SP and MIP at this moment . Nevertheless , our finding that a peptide GPCR can mediate actions of multiple , unrelated groups of ligands should be taken into consideration in searching for peptides and/or other types of ligands for GPCRs . Our genetic analyses demonstrated that the expression of SPR in three Gal4 neural populations ( cry-Gal4 , C929-Gal4 , and pdf-Gal4 ) is required and sufficient for wild-type levels of sleep maintenance . Furthermore , anti-SPR staining confirmed the SPR expression in two major subsets of pdf neurons , l-LNvs and s-LNvs . In particular , l-LNvs are common to all three Gal4 populations [28] , [30] , [49] . Thus , the most parsimonious explanation of our results is that SPR in l-LNvs mediates a sleep-related MIP function . This rationale is also supported by previous reports . Firstly , l-LNvs respond to light and other modulatory cues and promote arousal by releasing PDF [25] , [49] , a major wake-promoting factor functionally analogous to vertebrate orexin/hypocretin [5] , [11] . Secondly , excitation of l-LNvs suppresses night-time sleep [11] , [50] . Third , l-LNvs are major targets of inhibitory GABA-GABAA signaling , which promotes sleep both in flies and mammals [11] , [12] . Fourth , blocking sNPF-mediated inhibitory input to l-LNvs impairs sleep stability particularly in night-time [32] . Finally , MIP signaling through SPR can down-regulate cAMP levels in l-LNvs . Together , these and our genetic data provide cogent support for a role for MIP signaling in stabilizing the sleep state by modulating l-LNvs activities through the SPR ( Figure 9 ) . Another group of pdf neurons , s-LNvs are critical in timing the onset of morning behavior and are the key pacemaker cells controlling the circadian locomotor rhythm [41] , [42] . Although the precise role of s-LNvs in sleep regulation remains less clear , previous reports implicated that s-LNvs regulate sleep mainly by relaying information from l-LNvs . In response to light and modulatory substances , such as dopamine and octopamine , l-LNvs secrete PDF , which in turn elevates cAMP levels in s-LNvs by activating the PDFR [49] . Consistent with the role of s-LNvs in sleep regulation , knockdown of PDFR in pdf neurons ( presumably affecting the s-LNvs and not the l-LNvs ) elevates total sleep [11] . Recently , it was shown that s-LNvs produce sNPF , which modulates l-LNvs and stabilizes sleep , particularly in night-time [32] . Here , we also report that SPR expression in s-LNvs is important for maintaining daily sleep architecture . Knockdown of SPR in s-LNvs reduced daytime sleep and its average bout duration , whereas knockdown of SPR in l-LNvs reduced night-time sleep and its average bout duration . Together with previous results , our observations suggest that s-LNvs are involved in sleep regulation , and that MIP-SPR signaling stabilizes sleep by modulating the activity of s-LNvs directly and indirectly through l-LNvs ( Figure 9 ) . Our genetic and cAMP imaging results indicate that MIP regulates sleep as a ligand for SPR . Thus , it is also important to know whether MIP is secreted at biologically relevant times . The monitoring of levels of MIP peptide and mRNA at various time points in a day suggested that almost all brain MIP neurons release their contents synchronously from dusk to dawn , when the majority of flies fall and stay asleep . The rhythmic secretory activity of MIP neurons is likely to be under the control of the circadian clock rather than environmental light , because initiation and termination of the MIP secretion occurs prior to the light-off ( ZT 12 ) and the light-on time ( ZT 24 ) , respectively . Since MIP neurons are not part of the circadian clock network [33] , it would be interesting to see in the future to elucidate how they interact with the neuronal circadian clock network . Our results indicate that MIP release in most brain neurons appears synchronized , and MIP neurons in the brain arborize in many areas of the brain , including the olfactory glomeruli , the SOG , the lateral ventral protocerebrum , mushroom body , and so on ( for further evidence , see [24] , [33] , [45] ) . Considering SPR is expressed broadly in large numbers of the brain neurons [18] , massively secreted MIP in these sites probably modulates not only neurons important for locomotor activities and but also many others involved in diverse biological processes , such as olfactory , feeding , sexual activity , learning , and memory . Like in the human situation , sleep in Drosophila is also affected by other behavioral aspects , such as stress , social interactions , learning , diet , feeding , and reproduction [14] . In females , mating suppresses daytime sleep , and male-derived SP is responsible for this sleep modulation [15] . On the other hand , SP also plays key roles in eliciting the PMR , such as reduced receptivity to further mating and increased egg-laying [18] . In this study , we clearly demonstrated that the sleep-relevant SPR circuits ( l-LNvs and s-LNvs ) are distinct from the PMR-relevant SPR circuit ( ppk+ fru+ neurons ) . Intriguingly , however , SP circulates in the haemolymph of mated females [51] , [52] , raising the possibility that the haemolymph-born SP activates SPR in the sleep circuit and modulates sleep . This is certainly a plausible scenario , considering that SP is a potent agonist for the SPR [18] , and bath-applied SPR agonist ( in this case , MIP ) can affect cAMP levels in s-LNvs . In theory , however , the SPR activation in the sleep circuit either by haemolymph-born SP or centrally released MIP should promote sleep , rather than suppress it . Thus , we suspect that the daytime sleep loss observed in the mated female is not due to direct modulation of the SPR-sleep circuit by SP . Rather , SP actions on the PMR circuit elevate reproductive drives in mated females , which in consequence makes them spend more time during the day searching for food and egg-laying sites , and less time in falling asleep . Nevertheless , we cannot formally exclude the possibility that SP modulates female sleep . In theory , SP circulating in haemolymph of the mated female can promote sleep drive and counter wakefulness driven by reproductive motivations . Thus , we speculate that SPR may serve as a molecular integrator that computes reproductive-state coding signal ( SP ) and sleep-pressure coding signal ( MIP ) and therefore contribute to shaping daily sleep architecture . Multiple lines of evidence indicate that MIP-SPR signaling is a part of the homeostatic control system . First , mutants lacking either MIP or SPR show significant reduction in total amount of sleep , which is an indicator of homeostatic regulation [5] . Second , sleep deprivation drives MIP-LMIo , a subset of brain MIP neurons to release MIP into the optic lobe medulla where pdf neurons innervate . We propose that MIP-LMIo senses sleep pressure and modulates MIP secretion to maintain optimum sleep duration . Lastly and most importantly , mutants lacking either MIP or SPR show no sleep rebound after sleep deprivation . Together , these observations suggest that the activity of MIP neurons is controlled by two separable pathways; one associated with the circadian clock network ( see above ) , and the other associated with a sleep homeostat . It has been proposed in mammals that activity-dependent metabolites , such as adenosine , GABA , prostaglandins , and cytokines , are involved in sleep homeostasis , particularly the sleep initiation phase [53] . The role of GABA signaling in sleep is conserved both in mammals and flies [5] . In Drosophila , GABA regulates both sleep initiation and maintenance because silencing GABAergic neurons results in a significant decrease of sleep latency from lights-off as well as mean sleep-bout duration [11] , [13] . At the beginning of the night , GABA initiates sleep by inhibiting the activities of wake-promoting pdf neurons through the GABAA receptor , a ligand-gated Cl− channel [11] , [12] . After animals fall asleep , at least three modulatory pathways stabilize the sleep state and sustain it throughout the night ( Figure 9 ) : sNPF-sNPF receptor [32] , GABA-GABAB receptor 2 [54] , and MIP-SPR ( this study ) . All three pathways feed inhibitory modulation into l-LNvs , and in consequence keep these neurons from releasing PDF during the night ( Figure 9 ) . Unlike the other two pathways , MIP-SPR signaling is also important for stabilizing daytime sleep . Our model predicts that in the morning , shortly before light-on , s-LNvs release less sNPF than PDF . This probably is due to faster depletion of sNPF pool in s-LNvs during the night , as suggested by the fact that sNPF mRNA levels in s-LNvs are 30-fold higher in the morning ( ZT 0 ) than in the evening ( ZT 12 ) [31] . Then , subsequent to light-on l-LNvs are stimulated to release PDF [55] , which in turn modulates the motor control centers either directly or indirectly through s-LNvs [11] , [50] , and in consequence promotes wakefulness . Later , as sleep pressure builds up during the day , MIP-LMIos sense the sleep pressure and release MIP , allowing sleep to ensue in the middle of the day . MIP is expected to act via volume transmission , meaning that once released , it can access both l-LNvs as well as s-LNvs . In daytime , however the inhibitory actions of MIP on l-LNvs are fully countered by excitatory inputs from environmental light via dopamine and octopamine signaling , partly because MIP secretion is weaker at this time of day than at night-time . For siesta sleep , therefore SPR activation in s-LNvs is more important than that in l-LNvs ( Figure 9 ) . Several lines of evidence indicate that MIP , not SP , is the ancestral ligand of SPR [21] , [23] . MIP can activate SPRs from diverse species including the sea slug Aplysia , whereas SP can only activate SPRs from Drosophila species at physiological levels . MIPs are also more potent than SP as SPR agonists . Furthermore , orthologs of SPR and MIP are clearly detectable in most ( but not all ) sequenced genomes from Lophotrochozoa and Ecdysozoa . By contrast , SP has been found only in the genomes of a few closely related Drosophila species , indicative of their recent origin . Together , these observations suggest that the SPR-MIP signaling axis is evolutionarily ancestral , whereas the SPR-SP signaling axis arose only recently in Drosophila evolution , concomitantly with the emergence of SP . Our discovery that sleep regulation is a possible ancestral SPR function is a critical step forward in understanding how the SPR evolved functional multiplicity by recruiting a newly emerging ligand .
Flies were reared on standard food containing dextrose , cornmeal , and yeast at room temperature . UAS-AeaSPR , UAS-BomSPR , and UAS-TrcSPR were generated as described previously [18] . When expressed in CHO cells , the TrcSPR was insensitive to both SP and MIP , tested at 10 µM ( not shown ) . Each receptor coding sequence was cloned into the pPT13 vector ( a custom-designed vector modified from a standard UAS vector ) and inserted into a specific second chromosome site ( defined here as VIE-72a ) using the ΦC31 system [56] . Mutants and transgenic lines described previously are as follow: CS , Df ( 1 ) Exel6234 ( SPR−/− ) , UAS-SPR-IR1 and UAS-DrmSPR [18] , UAS-MIP-IR1 and UAS-MIP-IR2 [21] , elav-Gal4 ( III ) [57] , UAS-Dicer2 [58] , cry-Gal4 [28] , pdf-Gal4 [30] , C929-Gal4 [29] , fruGal4 [26] , tdc-Gal4 [59] , th-Gal4 [60] , ort-Gal4 [61] , C232-Gal4 , C161-Gal4 and 189Y-Gal4 [62] , 201Y-Gal4 [63] , 1471-Gal4 [64] , C309-Gal4 [63] , OK348-Gal4 [65] , and UAS-DenMark [47] . The elavC155-Gal4 ( I ) and elav-Gal4 ( II ) was obtained from the Bloomington Drosophila Stock Center ( Bloomington stock number , 8760 and 8765 ) . The elav-Gal4 ( III ) carrying a UAS-Dicer2 on the X chromosome was used for all pan-neural RNAi experiments , unless stated otherwise . Virgin females and males were collected at eclosion , and aged for 5 days in groups of 10–15 before assay . Mated females were prepared by combining 2–3-day-old virgin females with males for at least 2 days . Five-day-old flies were loaded in 65 mm×5 mm glass tubes containing 4% sucrose and 2% agar , and their 1 min-bin locomotor activity was collected with DAM System monitors ( Trikinetics ) in an incubator at 25°C and 60% humidity . Flies were monitored for 6 days under a 12 h light∶dark ( LD ) cycle . To compute sleep parameters , the data from days 5 and 6 were analysed with custom-built software . An uninterrupted inactivity lasting at least 5 min was counted as a sleep bout [7] . Flies with no activity in the final day of analysis were removed . The measurement of relative cAMP levels within single neuron cell bodies during bath application of MIP was done as previously described [35] with minor modifications . Flies for imaging experiments were reared at 25°C under a 12∶12 light-dark cycle . Living brains expressing the cAMP sensor Epac1-camps in neurons of interest were dissected from 3- to 5-day-old flies into room temperature hemolymph-like saline ( HL3 ) consisting of ( in mM ) : 70 NaCl , 5 KCl , 1 . 5 CaCl2 , 20 MgCl2 , 10 NaHCO3 , 5 trehalose , 115 sucrose , 5 HEPES; pH 7 . 1 [66] and stuck to the bottom of 35×10 mm Falcon Petri Dishes containing a petri dish perfusion insert containing 360 µl HL3 ( Bioscience Tools ) . Dissections were always performed between 6 and 11 hours after lights-on . Brains were allowed to settle and adhere to the bottom of the dish for 10 minutes before imaging . Epac1-camps imaging of relative cAMP levels was conducted as previously described [67] . Briefly , frames containing LNv cell bodies were scanned as single optical sections once every five seconds . After 30 s of initial scanning , 40 µl of MIP peptide ( at 10× the target concentration in 1% DMSO ) was gently added into the perfusion insert by hand with a micropipette to yield the target MIP concentration and 0 . 1% DMSO . cAMP responses of neurons of interest were monitored for a total of 5 min with an Olympus Fluoview 1000 confocal microscope equipped with the Fluoview software ( Olympus ) . Post-imaging analysis of Epac1-camps responses was done as previously described [68] . HPLC-purified synthetic MIP4 ( EPTWNNLKGMW-amide ) was obtained from AnyGen . For sleep deprivation , 3-day-old flies were individually loaded into 65-mm×5-mm glass tubes containing food , and entrained to a 12 h LD cycle . After 3 days of entrainment , flies were subjected to the sleep deprivation protocol described [69] previously during the dark cycle ( ZT 12–24 ) at day 4 . For the behavioral sleep homeostasis assay , flies were subjected to the SNAP-based sleep deprivation described previously [70] and allowed to recover the sleep loss in the following morning ( day 7 ) [71] . For SPR staining , the brains were dissected under ice-cold PBS ( pH 7 . 4 ) and fixed in PBS containing 4% paraformaldehyde at 4°C . Note that it was crucial to fix the tissue for more than 24 h for the successful anti-SPR staining [18] . After washing and blocking , the brain tissues were incubated in an anti-SPR antibody ( 1∶500 ) for 48 h at 4°C and then with an HRP-conjugated goat anti-rabbit antibody ( 1∶100; Invitrogen catalogue number T20924 ) for 1 h at RT . Then , the brain was stained with Tyramide signal amplification kit ( Invitrogen ) according to the manufacturer's instruction , and mounted in Vectashield ( Vector Labs ) . For MIP and DenMark labelling , brains were processed similarly , but fixed for 30 min at RT . Mouse monoclonal anti-MIP antibody 1A4 ( 1∶1 , 000 ) [72] and an Alexa-488 goat anti-mouse ( 1∶1 , 000; Invitrogen catalogue number A11001 ) were used as primary and secondary antibodies , respectively . To visualize DenMark , an anti-RFP antibody ( 1∶2 , 000; Invitrogen catalogue number R10367 ) and an Alexa-568 goat anti-rabbit antibody ( 1∶2 , 000; Invitrogen catalogue number A11011 ) were used . Images were acquired with a Zeiss LSM700/Axioscope laser scanning microscope and processed using ImageJ [73] . For quantification of anti-MIP labeling , labeling intensity was measured as the corrected total fluorescence ( CTF ) , calculated by subtracting the integrated fluorescence of an area of interest with its background fluorescence . Because MIP-immunoreactivity in the subesophageal ganglion ( SOG ) area were not different between treatments , CTF of each brain area were normalized by dividing CTF of the SOG . In situ hybridization was performed as described [72] . Dissected brains were fixed in 4% paraformaldehyde for overnight at 4°C , stored in 70% ethanol , washed with PBS with Tween-20 , treated with proteinase K and glycine , and hybridized with a digoxygenin ( DIG ) -labeled single-stranded DNA probe for overnight at 48°C . Blocked with 1% BSA , the brains were incubated with anti-DIG antibody conjugated with alkaline phosphatase ( Roche ) for overnight at 4°C , and stained with NBT-BCIP ( Roche ) . Primers used to generate MIP probe was a forward primer ( 5′-CTGATGGTGCTCCTCATCCT-3′ ) and a reverse primer ( 5′-CTGTGCTACGGCGATTCTCT-3′ ) . Images were taken in a bright field microscope ( Olympus BX53 ) .
|
Sleep is a common trait in animals , from insects to mammals , and it needs to be coordinated with other critical activities such as feeding and reproduction . However , the mechanisms by which this is achieved are not fully understood . The fruit fly Drosophila melanogaster has become a key model organism for sleep research and it has been shown that reproduction is one of the factors that can modulate sleep in these animals . Researchers have observed that mating reduces the daytime sleep of female flies and shown that the seminal fluid protein Sex Peptide ( SP ) , a ligand of the Sex Peptide Receptor ( SPR ) that is transferred to females during copulation , is responsible for this reduction of siesta sleep . Here , we investigated further the role of SPR in sleep regulation in Drosophila . We show that SPR is required for sleep stabilization in both sexes and that in mutant flies lacking SPR or its ligand myoinhibitory peptide ( MIP ) sleep is fragmented independently of reproduction . Unlike SP , MIP is expressed in the brain of both sexes and acts on SPR to silence specific neurons that keep flies awake , stabilizing sleep . Hence , our results reveal that SPR interacts with two distinct ligands to control different behaviors: SP for reproduction and MIP for sleep .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"biochemistry",
"physiological",
"processes",
"behavioral",
"neuroscience",
"neurochemistry",
"neuromodulation",
"animal",
"behavior",
"neurochemicals",
"physiology",
"sleep",
"hormones",
"biology",
"and",
"life",
"sciences",
"neuropeptides",
"evolutionary",
"biology",
"zoology",
"neuroscience",
"peptide",
"hormones"
] |
2014
|
A Homeostatic Sleep-Stabilizing Pathway in Drosophila Composed of the Sex Peptide Receptor and Its Ligand, the Myoinhibitory Peptide
|
Human onchocerciasis , caused by the filarial nematode Onchocerca volvulus , is controlled almost exclusively by the drug ivermectin , which prevents pathology by targeting the microfilariae . However , this reliance on a single control tool has led to interest in vaccination as a potentially complementary strategy . Here , we describe the results of a trial in West Africa to evaluate a multivalent , subunit vaccine for onchocerciasis in the naturally evolved host-parasite relationship of Onchocerca ochengi in cattle . Naïve calves , reared in fly-proof accommodation , were immunised with eight recombinant antigens of O . ochengi , administered separately with either Freund's adjuvant or alum . The selected antigens were orthologues of O . volvulus recombinant proteins that had previously been shown to confer protection against filarial larvae in rodent models and , in some cases , were recognised by serum antibodies from putatively immune humans . The vaccine was highly immunogenic , eliciting a mixed IgG isotype response . Four weeks after the final immunisation , vaccinated and adjuvant-treated control calves were exposed to natural parasite transmission by the blackfly vectors in an area of Cameroon hyperendemic for O . ochengi . After 22 months , all the control animals had patent infections ( i . e . , microfilaridermia ) , compared with only 58% of vaccinated cattle ( P = 0 . 015 ) . This study indicates that vaccination to prevent patent infection may be an achievable goal in onchocerciasis , reducing both the pathology and transmissibility of the infection . The cattle model has also demonstrated its utility for preclinical vaccine discovery , although much research will be required to achieve the requisite target product profile of a clinical candidate .
Onchocerciasis ( ‘River Blindness’ ) is recognised as one of the world's most important neglected tropical diseases [1] . The first-stage larva ( microfilaria , Mf ) of the nematode Onchocerca volvulus causes debilitating lesions of the eyes and skin [2] , with >99% of the global burden confined to sub-Saharan Africa [3] . Recent rapid epidemiological mapping of onchocerciasis in central Africa has determined that the prevalence is 37 million [3] , more than double that estimated in 1995 [4] . Initially , the main tool for onchocerciasis control was the targeting of riverine breeding sites of the blackfly vector ( Simulium spp . ) with larvicides [5] . However , when the anthelminthic drug ivermectin was donated for human use in 1987 , it supplemented vector control in the original Onchocerciasis Control Programme ( which ceased operations in 2002 ) and is now the single tool used for the vast majority of regions covered by the current African Programme for Onchocerciasis Control and the Onchocerciasis Elimination Program for the Americas [6] . Indubitably , ivermectin has been extremely successful in controlling onchocerciasis as a public health problem through annual or semi-annual mass treatments [7]; however , it also has a number of limitations . Firstly , ivermectin is a microfilaricidal drug that is not lethal to the adult worms ( i . e . , macrofilaricidal ) [8]; hence , repeated treatments are required as the adults can persist in the human host for over 10 years [9] . Secondly , ivermectin is contraindicated in areas of central Africa that are hyperendemic for another filarial infection , loiasis , because it can induce a severe post-treatment encephalopathy [10] . Thirdly , ivermectin does not always abrogate transmission , and maintenance of drug distribution for decades is constrained by economic and logistical hurdles , particularly in regions of civil unrest [11] . Finally , there is mounting clinical [12] and molecular [13] evidence that resistance to ivermectin may be emerging in certain foci . Potential complementary control options for onchocerciasis include a macrofilaricidal drug or a vaccine . The targeting of the Wolbachia endosymbionts found within worm tissues with antibiotics has been shown to be macrofilaricidal in Onchocerca infections [14] , [15] and there has been extensive research into this approach [16] . However , antibiotic chemotherapy is currently not suitable for mass administration since macrofilaricidal activity requires 4–6 weeks of continuous treatment [15]; shorter regimens are not effective [17] , [18] . The ambitious objective of vaccine development was the focus of the Edna McConnell Clark Foundation's ‘Oncho Task Force’ network , which facilitated the development of animal models for onchocerciasis , as well as characterisation and production of recombinant antigens and investigations of mammalian immune responses to the parasite [19] . With the recent renewed determination to reduce the global burden of neglected tropical diseases , there has come awareness that even vaccines with only partial efficacy could have a major impact in endemic countries if combined with existing chemotherapeutics [20] , [21] . Proof-of-principle for vaccination against onchocerciasis in natural host-parasite relationships has been demonstrated against O . lienalis in cattle using sonicated Mf [22] and against O . ochengi , also in cattle , using irradiated infective larvae ( L3 ) [23] . The latter species is the closest extant relative of O . volvulus [24] and is transmitted by the same complex of blackfly vectors ( S . damnosum sensu lato ) in west and central Africa [25] . Moreover , O . volvulus and O . ochengi exhibit extensive antigenic cross-reactivity , as evidenced by the serological recognition of O . volvulus recombinant antigens by cattle infected with O . ochengi [26] , and can generate cross-protective responses both experimentally [27] and naturally [25] . Therefore , the bovine O . ochengi system was utilised to evaluate a recombinant vaccine in a field trial in a hyperendemic area . The vaccine comprised 8 antigens ( table 1 ) , originally identified in O . volvulus , that were expressed as O . ochengi orthologues . These proteins were selected on the basis of extensive research by laboratories within the Oncho Task Force , which used two main criteria: efficacy against filariae in animal models and/or recognition by ‘putatively immune’ sera , obtained from humans who remained apparently uninfected despite intensive natural exposure to O . volvulus transmission .
Pregnant cows ( Bos indicus , Gudali breed ) were recruited from the Adamawa Plateau region of Cameroon , and their calves were reared from birth in fly-proof accommodation at the Institut de Recherche Agricole pour le Développement ( IRAD ) , Regional Centre of Wakwa , near Ngaoundéré . The calves were divided into two groups that were matched for age , weight and O . ochengi infection status of the dam , as determined by presence or absence of Mf in skin biopsies ( table 2 ) . For natural exposure to infection , animals were grazed on pasture bordering the River Vina du Sud for 22 months as previously described [23] . This is a hyperendemic area for O . ochengi , where the annual transmission potential has been estimated at 74 , 000 L3 per animal [25] . All procedures performed on animals in Cameroon were equivalent to those authorised by a Home Office Project Licence ( Animals [Scientific Procedures] Act 1986 ) for related work on cattle in the UK . The study was approved by the Ethics Committee of the Regional Centre of Wakwa , IRAD , and authorised by the Regional Programmes Committee of IRAD before experimental work began . The eight O . volvulus antigens selected for the vaccine trial were identified in an O . ochengi L3-stage Lambda ZAP Express ( Stratagene ) cDNA library using a standard plaque screening technique ( ECL Probe-Amp Kit , Amersham Pharmacia Biotech ) . Briefly , probes were PCR-labelled with fluorescein using the O . volvulus cDNA clones as template . The O . ochengi λ-phage plaques were hybridized with the labelled probe to identify the orthologous O . ochengi cDNA phage clones , which were then isolated and amplified by PCR . Sequences were verified using a dRhodamine Terminator Cycle Sequencing Kit ( Applied Biosystems ) on a 310 Genetic Analyzer instrument ( Applied Biosystems ) . The PCR products were sub-cloned ( in the appropriate reading frame ) into an expression vector incorporating a N-terminal polyhistidine tag ( pRSET [Invitrogen] or pJC40 [ATCC] ) , and the purified plasmids were transformed into BL21 ( DE3 ) Escherichia coli cells ( Invitrogen ) for recombinant protein expression . Following analysis by SDS-PAGE , 25 mg of each recombinant fusion protein was purified by metal chelation chromatography ( His·Bind Purification Kit , Novagen ) according to the manufacturer's instructions . The purified recombinant proteins were dialyzed against 1× phosphate-buffered saline ( PBS ) and quantified using a bicinchoninic acid protein assay ( Pierce ) . Each calf in the vaccinated group received all 8 recombinant antigens as separate injections ( a primary immunisation followed by two boosters at 4-week intervals; table 3 ) in the respective optimal adjuvant ( table 1 ) . The proteins were solubilised in sterile PBS , combined with an equal volume of either alum ( Imject , Pierce ) or Freund's complete adjuvant ( Sigma; primary vaccination ) followed by Freund's incomplete adjuvant ( Sigma; first booster ) then PBS only ( second booster ) , and mixed for 10 min until emulsified . To reduce the risk of antigenic competition , each protein was delivered ( 50% i . m . and 50% s . c . ) in a unique muscular site adjacent to a draining lymph node ( left or right omotransversarius , triceps , tensor fasciae latae or semitendinosus ) , and injections in different adjuvants were staggered by two weeks to minimise potential interactions ( table 3 ) . At predetermined intervals , blood was collected by jugular venepuncture and serum was stored at −20°C prior to transport to the UK on refrigerant gel . To reduce non-specific background signals , sera ( 10% [vol/vol] ) were pre-absorbed against E . coli extract ( 2 mg/ml protein , Promega ) in blocking solution ( 20% [vol/vol] soya milk , 10 mM Tris-hydrochloride , pH 8 . 5; 150 mM sodium chloride , 0 . 1% [vol/vol] ‘Tween’-20 ) for 2 h at ambient temperature , followed by overnight incubation at 4°C . Each stage of the assays was optimised independently by checkerboard titration using positive and negative sera pools , obtained from Gudali cattle with patent O . ochengi infection ( n = 9 ) or 13-week-old Gudali calves reared from birth in fly-proof accommodation ( n = 6 ) , respectively . Microtitre plates ( MaxiSorp , Nunc ) were coated with recombinant antigen in carbonate buffer ( 15 mM sodium carbonate , 35 mM sodium bicarbonate , pH 9 . 6 ) for 24 h ( 4°C ) , blocked overnight ( 4°C ) and incubated for 2 h ( ambient ) with sera diluted in blocking solution . Horseradish peroxidase-conjugated , sheep anti-bovine IgG1 or IgG2 ( both obtained from Serotec ) was diluted to 0 . 2 µg/ml in wash buffer ( i . e . , blocking solution without soya milk ) and applied for 2 h ( ambient ) followed by addition of substrate-chromogen ( 0 . 3 mg/ml diammonium 2 , 2′-azino-bis[3-ethylbenzothiazoline-6-sulphonate] and 0 . 1% [vol/vol] hydrogen peroxide in 50 mM sodium citrate buffer , pH 4 . 0 ) . All washes were performed using a SkanWasher-400 automated instrument ( Molecular Devices ) and OD was measured at 405 nm on an MRX microplate reader ( Dynex Technologies ) . Plates were only accepted if OD405 nm for positive control sera lay within 10% of a predetermined standard , and sample readings were corrected by subtraction of negative control values prior to analysis . To validate comparisons between IgG1 and IgG2 levels , a commercial bovine immunoglobulin reference serum ( Bethyl Laboratories ) was used to coat microtitre plates with known concentrations of IgG1 and IgG2 ( 0 . 006-12 µg/ml ) . Over this range , equivalent IgG concentrations produced OD405 nm with a divergence of <25% . Thus , OD405 nm was indicative of the relative concentrations of IgG1 and IgG2 and did not simply reflect differential avidity of the specific conjugates . At quarterly intervals from 6 months post-exposure ( mpe ) , animals were assessed by palpation for intradermal nodules ( containing adult worms ) ; the positions of which were marked in situ with tattoo ink and recorded on a ‘hide map’ . Triplicate skin biopsies were obtained at the same time-points and Mf densities were determined by microscopy as previously described [28] . At the termination of the experiment , palpation for nodules was performed by an individual blinded to the treatment groups . All nodules were removed under local anaesthesia over a period of several weeks ( for welfare reasons ) and dissected in PBS to release adult male worms from the female mass . The males were counted and their lengths measured , and the female was examined microscopically for developing embryos or Mf in the uteri ( gravidity ) . All analyses were performed using SPSS software ( v . 15 . 0; SPSS Inc . ) , and P< . 05 was the critical threshold unless otherwise specified . For parasitological data , frequencies were compared using relative risk estimates and Fisher's exact tests in the crosstabs procedure , and medians were analysed by Mann-Whitney U tests with exact significance . For serological data , animals were categorised as highly , poorly , or non-immunoresponsive according to cut-offs of >1 . 0 , 0 . 1–1 . 0 , or <0 . 1 OD405 nm units ( respectively ) for sera collected immediately before natural exposure to infection . If a treatment group's responses to an antigen were in a single category , further discrimination was achieved using a cut-off at the 50th percentile . To identify potential interactions between antibody responses to the recombinant antigens in individual vaccinated animals , scatter-plots of OD405 nm for antigen-pairs were inspected visually . An apparent association between responsiveness categories was analysed by Fisher's exact test . The medians of total area-under-curve for antibody responses were compared using Mann-Whitney U tests with exact significance , and as 16 individual tests were conducted , the Bonferroni adjustment for multiple comparisons was applied .
At 22 mpe , the prevalence of dermal Mf in vaccinated animals was significantly lower ( by 42%; P = . 015 , Fisher's exact test ) than that observed in adjuvant-control animals ( table 4 ) . In contrast , vaccination had no significant effect on adult worm burdens , as measured by nodule load , total worm recovery , number of males , or number of gravid females ( table 4 ) . Moreover , the length of male worms was not affected significantly by vaccination ( data not shown ) . Despite the reduced prevalence of Mf in vaccinated cattle , median microfilarial density was equivalent to that for adjuvant-control animals ( table 4 ) . There was no statistically significant relationship between positive skin biopsies in calves at the termination of the experiment and positive status of dams ( table 2 ) for Mf before calving ( relative risk , 0 . 98; 95% C . I . , 0 . 64–1 . 52 ) . All vaccinated animals responded with both IgG isotypes to all 8 antigens ( defined as an OD405 nm value >0 . 1 units above the negative control baseline ) immediately prior to field exposure ( table 1 ) , a time-point that corresponded to 4 weeks after the final immunisations ( table 3 ) . For IgG1 , all vaccinated animals were highly immunoresponsive ( OD405 nm>1 . 0 ) to all antigens except OoB8 , which was strongly recognised by only two-thirds of immunised calves ( table 1 ) . Animals with poor IgG1 responses to OoB8 tended to exhibit higher IgG1 levels for OoFBA , but this association was not statistically significant ( P = . 061 , Fisher's exact test ) . In all cases , IgG2 levels were lower than for IgG1 , although >90% of vaccinated animals showed strong recognition of OoRAL2 , OoFAR1 and OoFBA with this isotype ( table 1 ) . The majority of adjuvant-control animals did not recognise any of the antigens , with the notable exception of IgG1 responses to OoTMY1 ( 54% high responders , table 1 ) . Strong IgG1 responses to OoFBA were observed in approximately one-third of control animals , whereas high IgG2 levels in this group were restricted to 1–2 animals recognising OoTMY1 and OoRAL2 ( table 1 ) . The total area-under-curve was calculated for IgG1 and IgG2 responses at 0 , 4 and 21 mpe , and plotted separately for adjuvant-control animals , vaccinated cattle that became patent , and vaccinated animals that were protected from patent infection ( figure 1 ) . In general , antibody levels in the vaccinated group peaked at 0–4 mpe; moreover , there was very little ( if any ) response above baseline to any of the antigens in adjuvant-control cattle following exposure ( data not shown ) . The only marked difference in area-under-curve between patent and non-patent vaccinated animals was observed with the IgG2 response to OoTMY1 ( figure 1 ) , with a higher median level exhibited by protected cattle ( Mann-Whitney U test , P = . 048 ) . However , this was not statistically significant after Bonferroni adjustment for 16 comparisons ( corrected critical P = . 003 ) .
This study represents the first field trial of a recombinant antigen vaccine against onchocerciasis , and builds upon our preceding evaluation of an irradiated L3 vaccine against O . ochengi that induced significant protection against natural field challenge [23] . With the recombinant vaccine in the current study , the prevalence of microfilaridermia ( i . e . , patent infection ) was 42% lower than in control animals , whereas the irradiated vaccine induced 67% protection against patency and also significantly reduced the number of gravid female worms and microfilarial density in vaccinated cattle [23] . In addition , immunisations using sonicated O . lienalis Mf conferred 97% protection against experimental challenge with homologous Mf in cattle that did not harbour adult parasites [22] . However , a vaccine composed of native parasite material is very unlikely to be produced for human use because of the quantities required , the necessity for cryogenic storage and the infectious risks associated with biological material recovered directly from the host . The observed protective efficacy against Mf in the current experiment , with no significant effect on the adult stage , is noteworthy . It is possible that the reduction in patent infections in vaccinated animals was secondary to sub-lethal effects on reproduction of the adult parasites [29] , although this seems unlikely as there was no apparent abrogation of embryogenesis in female worms . However , since five of the vaccine antigens are expressed in Mf ( table 1 ) , the direct targeting of this stage by the immune response is entirely plausible and appears to have occurred without demonstrable vaccine-mediated inhibition of L3 development . A vaccine against Mf might not only be less technically challenging to develop than a prophylactic vaccine directed against L3 , but could be almost as beneficial to the affected population if pathology was ameliorated and transmission to the vector prevented . Conversely , an anti-Mf vaccine might be associated with a greater risk of inducing immunopathology , particularly as hyper-reactive onchocerciasis ( Sowda ) is characterised by an aggressive immune response against Mf [30] . This is a hypothetical consideration , but one that would need to be addressed rigorously during clinical testing of any vaccine candidate in onchocerciasis . Whilst Sowda is relatively uncommon in most endemic foci , individuals at increased risk of developing hyper-reactivity to Mf could be identified by genetic screening , since this condition is associated with particular polymorphisms [31] , [32] . Moreover , the innate immune responses to Wolbachia endobacteria that trigger dermal and ocular pathology in generalised onchocerciasis are a result of the death of Mf in significant numbers [30]; this could be prevented if a vaccine blocked the migration of Mf into the skin and eyes . The logistic challenges associated with use of a large animal model under tropical field conditions , and the long duration of natural exposure required to test protection ( ∼2 years ) , necessitated a multivalent approach in which all vaccinated animals were inoculated with all of the most promising candidate antigens identified in previous studies . Careful design was implemented to diminish competitive inhibition between immune responses by separating the inoculations both anatomically and temporally; consequently , the immunised animals exhibited good immunoresponsiveness to the eight antigens at the levels of IgG1 , IgG2 , or both isotypes , with little evidence of significant antigen competition . In most cases , specificity of the bovine serological responses was high , although a large proportion of adjuvant-control animals recognised OoTMY1 and OoFBA . Both tropomyosin [33] and fructose-1 , 6-bisphosphate aldolase [34] are highly conserved proteins , and cross-reactive antibodies could have been generated by co-infections with gastrointestinal nematodes such as Haemonchus placei , Cooperia spp . and Strongyloides papillosus . Indeed , even in housed cattle in the UK , total IgG responses to recombinant O . volvulus aldolase were almost indistinguishable between animals experimentally infected with O . ochengi and uninfected controls [26] . The disparity between the very high levels of protection afforded by irradiated parasites and some crude antigen extracts , as compared with the recombinant antigens in the current study , could be due to a number of factors . In common with other eukaryotic proteins , the expression of recombinant nematode proteins in E . coli can lead to the production of molecules that exhibit aberrant secondary or tertiary structures , or which lack important post-translational modifications . For instance , the Ancylostoma secreted proteins have to be expressed in a eukaryotic system ( Pichia pastoris ) in order to attain the conformational epitopes and catalytic activity of the native protein , and these characteristics are critical for the immunogenicity of hookworm vaccines under development [35] . However , all the antigens used in the current field trial had induced significant protection against filarial challenge in other models when expressed as recombinant proteins in E . coli ( table 1 ) . Perhaps a more relevant limitation to our multivalent approach is the possibility that one or more of the antigens reduced the protective efficacy of the others by the induction of immunoregulatory pathways . Indeed , the O . volvulus orthologue of one of the antigens used in the vaccine , OoCPI , can induce hyporesponsiveness in T-cells [36] . There was no compelling association between the serological response to any single antigen and protection against patent infection . However , there was a negative trend ( non-significant after Bonferroni correction for multiple comparisons; a highly conservative statistical adjustment [37] ) between levels of IgG2 against OoTMY1 and detectable Mf . As the orthologous tropomyosin moiety from O . volvulus has been shown to induce protection against O . lienalis Mf in a mouse model [38] , and anti-tropomyosin antibodies are inversely correlated with Mf density in infected humans [33] , this antigen warrants further investigation as a key component of a potential anti-Mf vaccine . This does not necessarily imply that IgG antibodies are the key effectors of vaccine-mediated immunity , but levels of IGg1 and IgG2 were assayed in the current study simply to demonstrate recognition of individual antigens in the immunised animals . Indeed , a previous study of bovine antibody responses to recombinant O . volvulus antigens ( in Gudali cattle naturally infected with O . ochengi at the same field site ) reported that neither IgG1 nor IgG2 levels were clearly associated ( positively or negatively ) with parasite burden [39] . Further insights into the role of OoTMY1 and the other antigens might have been revealed by complementary analyses of IgE levels , lymphoproliferation and eosinophilia [40] , [41] . It should be noted that OoTMY1 was delivered in Freund's adjuvant because this had been used in a prior vaccination experiment in jirds , which demonstrated significant protection against a challenge infection with Acanthocheilonema viteae [38] . As Freund's adjuvant is not licensed for human use , future trials should consider the inclusion of an alternative adjuvant that could facilitate Th1-like responses , such as CpG oligodeoxynucleotides [42] , which may be close to regulatory approval . In conclusion , we have demonstrated for the first time under field conditions that in a natural host-Onchocerca relationship , it is possible to significantly reduce the frequency of infections that attain full patency using a recombinant vaccine . The next phase of vaccine design for onchocerciasis will require the separate evaluation of individual vaccine candidates ( particularly tropomyosin ) to determine whether the multivalent approach is necessary to achieve protection . The cattle model , although logistically challenging and relatively costly , is far less complex and expensive than are clinical trials in humans . In this field trial and others [14] , [17] , [23] , the O . ochengi system has filled a critical niche between laboratory studies in rodent models ( that are unnatural hosts of Onchocerca parasites ) and field evaluation of onchocerciasis control in human populations . Our study opens up the prospect of specifically targeting the Mf stage by vaccination , which in conjunction with currently available chemotherapy , could ensure that the impressive achievements of onchocerciasis control are sustained and extended for the decades to come .
|
River blindness , or onchocerciasis , is caused by a parasitic worm ( Onchocerca volvulus ) that is transmitted by blood-feeding blackflies , which breed in fast-flowing rivers . More than 37 million people are infected and may experience visual impairment and/or severe dermatitis . Control of onchocerciasis is largely dependent on a single drug , ivermectin . Whilst this is extremely effective at killing the worms' offspring ( microfilariae ) and preventing symptoms , ivermectin does not eliminate the long-lived adult parasites or always stop transmission . Consequently , treatments must be repeated for many years , and drug resistance may be emerging . Against this background , a vaccine against onchocerciasis would provide an important additional tool to sustain effective control . In this study , we evaluated eight worm antigens as vaccine components in cattle , which are often parasitized by O . ochengi ( the closest relative of O . volvulus ) in West Africa . Twelve uninfected animals received all eight antigens and were exposed to natural transmission of O . ochengi alongside 13 unvaccinated cattle . After almost two years , 92% of vaccinated animals had acquired adult worms , but only 58% were positive for microfilariae; whereas 100% of unvaccinated animals harboured both parasite stages . This suggests that a vaccine against microfilariae to prevent development of disease in humans may be achievable .
|
[
"Abstract",
"Introduction",
"Methods",
"Results",
"Discussion"
] |
[
"infectious",
"diseases/helminth",
"infections",
"immunology/immunity",
"to",
"infections",
"immunology/immune",
"response",
"infectious",
"diseases/neglected",
"tropical",
"diseases"
] |
2009
|
Immunisation with a Multivalent, Subunit Vaccine Reduces Patent Infection in a Natural Bovine Model of Onchocerciasis during Intense Field Exposure
|
Most reductionist theories of muscle attribute a fiber's mechanical properties to the scaled behavior of a single half-sarcomere . Mathematical models of this type can explain many of the known mechanical properties of muscle but have to incorporate a passive mechanical component that becomes ∼300% stiffer in activating conditions to reproduce the force response elicited by stretching a fast mammalian muscle fiber . The available experimental data suggests that titin filaments , which are the mostly likely source of the passive component , become at most ∼30% stiffer in saturating Ca2+ solutions . The work described in this manuscript used computer modeling to test an alternative systems theory that attributes the stretch response of a mammalian fiber to the composite behavior of a collection of half-sarcomeres . The principal finding was that the stretch response of a chemically permeabilized rabbit psoas fiber could be reproduced with a framework consisting of 300 half-sarcomeres arranged in 6 parallel myofibrils without requiring titin filaments to stiffen in activating solutions . Ablation of inter-myofibrillar links in the computer simulations lowered isometric force values and lowered energy absorption during a stretch . This computed behavior mimics effects previously observed in experiments using muscles from desmin-deficient mice in which the connections between Z-disks in adjacent myofibrils are presumably compromised . The current simulations suggest that muscle fibers exhibit emergent properties that reflect interactions between half-sarcomeres and are not properties of a single half-sarcomere in isolation . It is therefore likely that full quantitative understanding of a fiber's mechanical properties requires detailed analysis of a complete fiber system and cannot be achieved by focusing solely on the properties of a single half-sarcomere .
Many biological systems are irreducible meaning that they have more complicated properties than the structures of which they are composed . Detailed understanding of a complete system therefore requires knowledge both about how its individual components function and about how those components interact . A property of the complete system is described as emergent if it arises because of interactions between components and is not a property of a single component in isolation . Studying the emergence of new properties is an important aspect of modern systems biology and the approach has produced important new insights into many living systems [1] . Although systems-based models of muscle are now being developed [2] , alternative reductionist models have dominated quantitative muscle biophysics for the last 60 years . The main strategy has been to try and explain the properties of an entire muscle fiber as the scaled behavior of a single half-sarcomere . This technique was pioneered by A . F . Huxley in 1957 [3] and it has been outstandingly successful . For example , reductionist half-sarcomere theories can explain virtually all of the mechanical effects that occur immediately after a muscle fiber is subjected to a very rapid length or tension perturbation [4] , [5] . Muscle fibers do however exhibit some mechanical properties that are not immediately consistent with the expected behavior of a single half-sarcomere . The goal of the present work was to determine whether one specific experimental effect might be an emergent property of a group of half-sarcomeres as opposed to an inherent property of a single one . The analysis focused on the tension responses produced by stretching a chemically permeabilized rabbit psoas muscle fiber . If this type of preparation is stretched when it is inactive , the force response is relatively small and probably largely attributable to the elongation of titin molecules [6] . When the preparation is activated and then lengthened , the stretch response contains an additional , larger , component reflecting the displacement of populations of attached cross-bridges away from the distributions that they adopted during the isometric phase of the contraction . If the filaments keep moving at the same rate for a sufficiently long time , the standard mathematical theories ( for example , [3] ) predict that cross-bridge populations will reach new steady-state distributions dictated by the strain-dependence of the myosin rate transitions and the velocity of the imposed length change [7] . If steady-state is indeed achieved , the cross-bridge population distributions will remain stable and the force due to attached cross-bridges will therefore remain constant . This simple analysis implies that titin molecules are the only molecular structures inside the half-sarcomere that can produce a force that increases during the latter stages of an imposed stretch . If titin behaves as an elastic spring that is independent of the level of Ca2+ activation the rate at which force rises late in an imposed stretch should therefore be the same in maximally-activated fibers as it is in relaxed fibers . In fact force rises >3-fold faster in activated rabbit psoas fibers than it does in the same fibers when they are inactive [7] . One possible explanation for this effect is that the properties of molecules within each half-sarcomere change when a muscle is stretched while it is activated . For example , titin filaments could become stiffer , or the cross-bridge populations could fail to reach steady-state during a prolonged movement . Both of these effects could potentially reflect force-dependent protein-protein interactions [8] . A second possible explanation is that the half-sarcomeres continue to operate as they did before the stretch and that the measured experimental behavior is an emergent property of a collection of heterogeneous half-sarcomeres . These explanations are not mutually exclusive so it is also possible that both effects contribute to the activation dependence of the latter stages of the stretch response . An argument against variable titin properties being the sole explanation is that the magnitude of the Ca2+-dependent stiffening required to explain the behavior observed in psoas fibers ( ∼300% increase in titin stiffness ) is much larger than that ( ∼30% increase in stiffness ) observed in experiments that have specifically investigated titin's Ca2+-sensitivity [9] . The idea that the activation-dependence of the latter stages of the stretch response could reflect emergent behavior of a collection of half-sarcomeres might be inferred from a number of previous reports [10]–[12] but it does not seem to have been explicitly stated or analyzed in quantitative detail before . This paper presents a mathematical model that was developed to investigate the potential emergence of new mechanical behavior in a system composed of multiple half-sarcomeres . Detailed computer simulations show that the model can reproduce the activation dependence of the latter stages of the stretch response without requiring that titin filaments stiffen when the Ca2+ concentration rises . The stretch response of a fast mammalian muscle fiber may therefore be an irreducible property of the complete cell .
Fig 1 shows experimental force records for a chemically permeabilized rabbit psoas fiber subjected to a ramp lengthening followed by a ramp shortening in four different pCa solutions . The rate at which force rose during the latter stages of the stretch increased with the level of Ca2+ activation . Data from 5 fibers showed that the slope ( estimated by linear regression ) of the tension response during the last one-third of the stretch was 3 . 26±0 . 87 ( SD ) times greater ( t-test for value greater than unity , p<0 . 001 ) in pCa ( = −log10[Ca2+] ) 4 . 5 solution ( maximal Ca2+ activation ) than it was in pCa 9 . 0 solution ( minimal Ca2+ activation ) . As discussed in the Introduction , the increased slope in the pCa 4 . 5 condition is not consistent with the expected behavior of a single population of cycling cross-bridges arranged in parallel with an elastic component that has properties that are independent of the level of activation . Computer simulations were performed to test the hypothesis that the activation dependence of the latter stages of the force response may be an emergent property of a collection of half-sarcomeres . The model is summarized in Fig 2 and explained in detail in Materials and Methods . Parameters defining the passive mechanical properties of the half-sarcomeres ( Table 1 , Column 3 ) were determined by fitting Eq 8 to an experimental record measured in pCa 9 . 0 solution . Multidimensional optimization procedures were then used to adjust the other parameters defining the model's behavior in an attempt to fit the simulated force response to the experimental record measured in pCa 4 . 5 solution . The best-fitting force response obtained in this manner is shown in red in the top panel in Fig 3 . The corresponding model parameters are listed in Table 2 ( Column 3 ) . The blue lines in the top panel in Fig 3 show the force responses produced by a single half-sarcomere framework with the same model parameters . The simulated force records for the single and multi-half-sarcomere frameworks are the same for the pCa 9 . 0 condition ( where there are no attached cross-bridges ) but different for the pCa 4 . 5 condition . Note in particular that the multi-half-sarcomere framework predicts a smaller short-range force response and a tension that rises more steeply during the latter stages of the stretch . This progressively increasing tension is not a property of a single activated half-sarcomere in these simulations and therefore reflects interactions that occur between half-sarcomeres; it is an emergent property of the multi-half-sarcomere framework . The red lines in the bottom panel in Fig 3 show the length traces for the 300 half-sarcomeres in the larger framework superposed . ( The traces are shown in more detail in Supporting Information Figure S1 . ) Although individual half-sarcomeres followed length trajectories defined by Eq 2 the behavior of the overall system is chaotic . During the stretch , for example , some half-sarcomeres are lengthening , some are shortening , and some remain nearly isometric . The behavior of each pair of half-sarcomeres on the other hand is more orderly . Indeed , at any given time-point in the simulation , all the full sarcomeres had virtually the same length . This is because the inter-myofibrillar links ( Fig 2 ) were sufficiently stiff to keep the Z-disks in register during the activation . The effect is demonstrated in Fig 4B where the computer-rendered striation patterns show that the Z-disks ( drawn in magenta ) are always aligned whereas the M-lines ( drawn in yellow ) are frequently displaced from the middle of the sarcomere . Z-disk alignment is no longer maintained in the simulations if the inter-myofibrillar links are ablated in silico by setting kim equal to zero ( Fig 4C ) . In this situation , mean sarcomere length averaged perpendicular to the filaments for the different half-sarcomere pairs ( green lines in Fig 4A ) is no longer constant although mean sarcomere length averaged parallel to the filaments is always the same in the different myofibrils . ( This has to be the case because all the myofibrils have the same length and contain the same number of sarcomeres . ) A movie showing how the computer-generated striation patterns change during the length perturbations is provided as Supporting Information Video S1 . Interestingly , the predicted isometric force value is lower for the simulations with kim equal to zero . The area under an xy-plot of force against length during the stretch ( not shown ) is also lower indicating that the framework simulated without inter-myofibrillar links would absorb less energy during an eccentric contraction . This mimics experimental results obtained by Sam et al . [13] using muscles from desmin-null mice . Fig 5 shows the effects of changing the size of the model framework and the numerical value of a key model parameter . All simulations were performed with the parameters listed in the third columns of Tables 1 and 2 except for Fig 5C where α ( Eq 7 ) was varied as shown . Increasing nhs ( the number of half-sarcomeres in each myofibril ) from 1 to 10 in a framework with 6 myofibrils markedly improved the fit to the experimental record . The additional improvement gained by further increasing nhs to 50 was more modest . When there were already 50 half-sarcomeres in each myofibril , increasing the number of myofibrils did not dramatically improve the fit during the stretch response ( Fig 5B ) but it did help to stabilize isometric force before the stretch . This is at least partly because the presence of inter-myofibrillar links stabilized sarcomere ( but not half-sarcomere ) lengths ( Fig 4B and C ) . The effects of varying α to alter the amount of half-sarcomere heterogeneity in the largest framework are summarized in Fig 5C . Note that increasing α beyond 0 . 1 did not substantially change the fit to the experimental data and that the simulated response for the framework with 300 half-sarcomeres and α equal to zero was not different from that of the single half-sarcomere framework with the same model parameters . This second point demonstrates that a fiber system does not exhibit emergent properties if the half-sarcomeres of which it is composed are all identical . This informal sensitivity analysis suggests that the activation dependence of the latter stages of the stretch response is more likely to reflect inhomogeneity between half-sarcomeres along a myofibril than inhomogeneity between different myofibrils . This prediction is based on the computed results shown in Fig 5A and B . Increasing the number of half-sarcomeres from 1 to 50 in a framework with 6 myofibrils markedly changed the slope of the force response during the second half of the stretch ( Fig 5A ) . In contrast , increasing the number of myofibrils in a framework with 50 half-sarcomeres ( Fig 5B ) reduced the magnitude of oscillations in the computed force records but did not substantially alter the underlying trend of the responses . The value of the parameters defining Fpas ( Table 1 , Column 3 ) were determined by fitting Eq 8 to force records measured for a fiber in pCa 9 . 0 solution during small dynamic stretches ( 4% muscle length ) imposed from a starting sarcomere length of ∼2600 nm . It is therefore possible that the calculated parameters overestimate the isometric passive tension that would have been measured if the half-sarcomeres were stretched more than 4% . ( The passive length tension relationship was not measured in the original experiments [7] so the relevant experimental data were not available for comparison . ) To eliminate any possibility that the tension response during the latter stages of an imposed stretch is only activation-dependent in the current simulations because the titin filaments are unrealistically stiff at long lengths , additional calculations were performed with a linear passive component . The parameters defining Fpas in this case ( Table 1 , Column 4 ) were determined by fitting Eq 9 to the same pCa 9 . 0 force record . Passive force calculated in this way did not reach the maximal Ca2+-activated value until the sarcomeres were stretched beyond 3500 nm . The best-fitting force simulations deduced by multi-dimensional optimization with the linear titin component are shown in red in Fig 6A . While the simulation of the active fiber does not match the experimental data as well as the simulations ( Fig 3 ) performed with the non-linear titin component ( r2 = 0 . 93 as opposed to r2 = 0 . 98 ) it does reproduce the activation-dependence of the slope of the force response during the latter stages of the stretch . Rat soleus fibers exhibit a stretch response that is qualitatively different from that produced by rabbit psoas fibers [14] . Instead of force rising during the latter stages of the movement , force tends to peak and then fall slightly to a plateau that is maintained as long as the stretch persists . ( A similar plateau is observed when frog tibialis anterior fibers are stretched [15] ) . Although the shape of the response seems to imply that passive titin properties are less important in rat soleus fibers than they are in rabbit psoas fibers , Campbell & Moss [14] showed that a single half-sarcomere model produced the best-fit to the real Ca2+-activated data when the cross-bridges were arranged in parallel with a titin spring that was ∼3 times stiffer than that measured experimentally in pCa 9 . 0 solution . The behavior of the soleus fibers was thus very similar to that described here for psoas preparations . This suggests that simulations performed with a multi-half-sarcomere framework might also produce a better fit to the mechanical data from soleus fibers than a model based on a single half-sarcomere . Fig 6B shows the results of calculations performed to test this hypothesis . Parameter values for the simulations are listed in Tables 1 and 2 ( Column 5 in both cases ) . The predictions for the multi-half-sarcomere framework fit the experimental data well ( r2 = 0 . 97 ) and , as in the case of the simulations of psoas fiber data , predict a lower isometric force and a less prominent short-range response than the simulations performed with a single half-sarcomere framework and otherwise identical model parameters .
This work provides important new insights and introduces novel simulation techniques but the idea that the mechanical properties of a muscle fiber might be influenced by individual half-sarcomeres behaving in different ways is not new [15] , [20]–[22] . One of the controversies in the field is whether sarcomeres ‘pop’ , that is , extend rapidly to beyond filament overlap [12] . This behavior can be predicted from an analysis of the steady-state active and passive length tension relationships but it has not been observed in some experiments that have specifically investigated the issue in small myofibrillar preparations [23] , [24] . Other data [25] suggest that some sarcomeres in a sub-maximally activated myofibril ‘yield’ and others ‘resist’ during a stretch . The present simulations suggest that there are at least two mechanisms that may reduce the likelihood of ( but perhaps not entirely eliminate ) popping under normal physiological conditions . First , attached cross-bridges in half-sarcomeres that are starting to elongate will be stretched thereby producing increased force . If the total length of the muscle fiber is fixed , other half-sarcomeres in the same myofibril will have to shorten and force will therefore drop in these structures . The changes in the forces produced by cross-bridges in the half-sarcomeres that moved are transient because they will dissipate as the myosin heads progress through their normal cycle . However , while they exist , they act in such a way as to reduce the development of additional heterogeneity . In vivo , this effect could be enough to prevent the cell from being structurally damaged before it relaxes at the end of the contraction and passive mechanical properties are able to restore the fiber's prior arrangement . Second , forces in molecules that link half-sarcomeres will help to preserve sarcomere length uniformity . In the current simulations , some of these molecules are represented mathematically by linear springs that connect Z-disks in adjacent myofibrils . It was particularly interesting to discover that the in silico ‘knock-out’ of inter-myofibrillar connections ( kim = 0 , Fig 4 ) reproduced the functional effects observed in mice from desmin-null mice - lower isometric force and decreased energy absorption during imposed stretches [13] . One of the many interesting features of the second phase of the stretch response of activated muscle fibers is that it can be quite variable . Fig 6 , for example , shows that it is markedly different in fast and slow mammalian fibers under very similar experimental conditions . Getz et al . [11] observed that differences can also be observed within fast fibers from rabbit psoas muscle . Their manuscript notes that the “continued force rise after the critical stretch was sometimes but not always present in our data” . ( It is important to note that the stretches used by Getz et al . were up to 25 times faster than the ones simulated in the present work . A slow rise in force during the latter stages of the stretch was always observed in the experiments with psoas fibers that are simulated here [7] . ) Getz et al . suggested that the variable nature of their measured responses might reflect different amounts of half-sarcomere heterogeneity in their preparations . Their conclusion is supported by the present simulations . Half-sarcomere heterogeneity has also been suggested as a potential explanation for residual force enhancement - the augmented force that persists long after a stretch and hold imposed during a maximal contraction [26] . The current simulations support this hypothesis too because Edman & Tsuchiya [10] showed that the size of the enhancement correlates with the magnitude of the second phase of the force response in the stretch that produces it . However , half-sarcomere heterogeneity may not be the only mechanism responsible for residual force enhancement because Edman & Tsuchiya [10] also showed that there could be a small residual enhancement when the conditioning stretch didn't produce a measurable second phase force response . Precise measurements of the mechanical properties of single muscle fibers are often performed using a technique known as sarcomere length control [27] , [28] . This is an important experimental approach but it should be made clear that the technique does not eliminate the potential emergence of new properties due to the collective behavior of half-sarcomeres . This is because sarcomere length control dictates the mean sarcomere length in a selected region of the muscle fiber rather than the lengths of the individual half-sarcomeres . It is thus the in vitro equivalent of the computer simulations discussed in this work in which xT , the total length of a defined group of half-sarcomeres , is the controlled variable . Many biologists probably regard it as axiomatic that the properties of a muscle fiber vary along its length . After all , organelles , such as nuclei and mitochondria , are localized structures that are not uniformly ‘smeared’ throughout the cell . There are , of course , other sorts of non-uniformity in muscle cells as well . There is good evidence to suggest , for example , that eye muscle fibers express different myosin isoforms along their length [29] and that sarcomeres near the end of a fiber are shorter than those near the middle [30] . Many quantitative models of muscle on the other hand overlook variability within muscle fibers and attribute the mechanical properties of an experimental preparation to the scaled behavior of a single population of cycling cross-bridge that is sometimes arranged in parallel with a passive mechanical component . These reductionist theories have been outstandingly successful at explaining the behavior observed in some specific experiments [31] but the simulations presented in this work suggest that more realistic multi-scale modeling may be required to fully reproduce the behavior of whole muscle fibers . Multi-scale modeling may be particularly helpful in studies of muscle disease . It is well known , for example , that muscle function is compromised in muscular dystrophy where the primary defect occurs in a large structural protein [32] . Defects in such proteins will affect the way that forces are transmitted between and around myofibrils which , as shown in Fig 4 , may significantly alter a muscle's mechanical behavior . This concept is also supported by experimental data . Shimamoto et al . [25] recently showed , for example , that modifying Z-disk structure with antibodies can influence the emergent properties of a myofibrillar preparation by altering the way that half-sarcomeres interact . Finally , the simulations shown in Fig 5C demonstrate that the relatively small amount of half-sarcomere heterogeneity produced by increasing α from 0 . 0 to 0 . 1 dramatically alters the mechanical properties of the muscle framework . Further increases in α produce more half-sarcomere heterogeneity but do not substantially alter the predicted force response . This is a very interesting finding because it implies that the mechanical properties of a muscle that was originally perfectly uniform would change markedly if localized structural and/or proteomic abnormalities developed as a result of a disease process and/or unusual mechanical stress . The mechanical properties of a muscle cell that was already slightly heterogeneous on the other hand would not be substantially altered by additional irregularities . This could be a significant advantage for a living cell that is continually repairing itself and which is potentially subject to damaging stimuli and large external forces . Muscle cells may have evolved to become fault-tolerant systems . The mathematical modeling presented in this work suggests that muscle fibers may exhibit emergent mechanical properties that reflect interactions between half-sarcomeres . If this is indeed the case , systems-level approaches will tbe required to explain how known proteomic and structural heterogeneities influence function in normal and diseased tissue .
Animal use was approved by the University of Wisconsin-Madison Institutional Animal Care and Use Committee . All of the experimental records shown in this work were collected by the author in Dr . Richard Moss's laboratory at the University of Wisconsin-Madison . Full details of the experimental procedures and some of the records have already been published [7] , [14] . Animal use was approved by the relevant Institutional Animal Care and Use Committee . The structural framework studied in this work ( Fig 2 ) consisted of nm parallel chains of myofibrils , each of which was itself composed of nhs half-sarcomeres arranged in series . Every second Z-line was linked to the corresponding Z-line in each of the other myofibrils by a linear elastic spring of stiffness kim . These connections simulated the mechanical effects of proteins such as desmin that connect myofibrils at Z-disks [33] . The force within each half-sarcomere ( Fhs ) was the sum of Fpas , a ‘passive’ elastic force due to the mechanical elongation of structural molecules such as titin , and Fact , an ‘active’ force produced by ATP-dependent cross-bridge cycling [34] , [35] . ( 1 ) Fpas was a single-valued function of the length ( xhs ) of each half-sarcomere . Fact was more complicated and depended on the half-sarcomere's preceding motion . Both force components are described in more detail below . The mechanical behavior of the multi-half-sarcomere framework was simulated by assuming that ( 1 ) the force in a given myofibril was the same at every point along its length and ( 2 ) the sum of the lengths of the half-sarcomeres in each myofibril was equal to the total muscle length . These assumptions lead to a set of functions ( 2 ) where Fhs , i , j and xhs , i , j respectively describe the force developed by and the length of half-sarcomere i in myofibril j , Fm , j is the force in myofibril j and xT is the total length of the framework ( Fig 2 ) . These functions can be solved using a root-finding method ( see Numerical Methods section below ) to yield the lengths of each half-sarcomere and thus the mechanical state of the framework . Fact values for each half-sarcomere in the framework were calculated using techniques previously described for a single half-sarcomere model by Campbell & Moss [7] . Myosin heads were assumed to cycle through the 3-state kinetic scheme shown in Fig 7 . The proportion p ( xhs ) of cross-bridges participating in the kinetic scheme in each half-sarcomere was set to zero for all xhs during simulations of passive muscle ( pCa 9 . 0 conditions ) . In simulations of activate muscle ( pCa 4 . 5 conditions ) , p ( xhs ) was assumed to scale with the number of myosin heads overlapping the thin filament ( Fig 8A ) so that ( 3 ) where xoverlap is lthin+lthick−xhs , xmaxoverlap is lthick−lbare , and lthin , lthick , and lbare are the lengths of the thin filaments ( 1120 nm ) , thick filaments ( 815 nm ) and thick filament bare zone ( 80 nm ) respectively and λfalloff is a model parameter arbitrarily set to 0 . 005 nm−1 . The rate constants defining the probability of a cross-bridge moving to a different biochemical state depended on the length x of the cross-bridge link and twelve model parameters ( Table 2 ) that were determined by fitting the simulated force values to representative data records using multidimensional optimization techniques ( see below ) . The spring constant kcb for an individual cross-bridge link was defined as 0 . 0016 N m−1 in close agreement with recent experimental estimates for this parameter [36] , [37] . Energies for the cross-bridge states ( Fig 8B ) were defined as ( 4 ) where x is the length of the cross-bridge link , xps is the length of the force-generating power-stroke and A1 , base and A2 , base define the minimum energy of cross-bridge links bound in the A1 and A2 states respectively . The energy difference between the ED and ED′ states ( Fig 8B ) was 25 kBT where kB is Boltzmann's constant ( 1 . 381×10−23 J K−1 ) and T was 288 K . ( The original experiments were performed at 15°C [7] , [37] ) . Strain-dependent rate functions f12 ( x ) , f23 ( x ) and f31 ( x ) for the forward transitions ( Fig 7 ) were defined as ( 5 ) Reverse rate functions g21 ( x ) , g32 ( x ) and g13 ( x ) were defined in terms of the forward rate functions and the energy difference between the relevant states [38] as ( 6 ) Panels B , C and D in Fig 8 show the strain-dependence of the free energy diagram for the cross-bridge scheme , the forward rate functions and the reverse rate functions used in the simulations shown in Fig 3 . The numerical values of the relevant parameters are listed in the third column in Table 2 . The number of myosin heads per unit cross-sectional area in a single half-sarcomere framework was always N0 ( defined in this work as 1 . 15×1017 m−2 [36] ) . Half-sarcomere heterogeneity was incorporated into the simulations of multiple half-sarcomere frameworks by assuming that the number of myosin heads per half-sarcomere was a normally distributed variable . Thus the actual number ( Ni ) of myosin heads participating in the cross-bridge cycle in half-sarcomere i at half-sarcomere length xhs was equal to ( 7 ) where Gi ( α ) was a variable randomly selected from a Gaussian distribution with mean of unity and a variance of α . The passive force Fpas increased in a non-linear manner as ( 8 ) where σ , xoffset and L were determined by curve-fitting [7] , [14] , with the exception of one set of simulations . Fig 6A shows force records simulated with a passive force that increased linearly with half-sarcomere length as ( 9 ) where kpas defines the stiffness of the passive elastic spring and xslack is the half-sarcomere length at which the spring falls slack . Filament compliance effects [39] , [40] were incorporated by assuming that if a half-sarcomere changed length by Δxhs in a given time-step each cross-bridge link in the half-sarcomere changed length by ½Δxhs [11] . This over-simplifies the realignment of actin binding sites and myosin heads that occurs in real muscle fibers but the finite availability of computing power means that it is not yet practical to implement more realistic simulations of filament compliance effects [41]–[44] with a framework containing 300 half-sarcomeres . The mathematical model was implemented as a multi-threaded console application ( Visual Studio 2005 , Microsoft , Redmond , WA ) written in C++ . Equation 2 was solved using the newt ( ) function described by Press et al . [45] which invokes Newton's method to solve non-linear sets of functions . Δx for cross-bridge populations [7] was set to 0 . 5 nm . The time-step was set to 1 ms . Reducing these parameters by 50% did not materially change the results of the calculations . Calculated rate constants ( Eqs 5 and 6 ) were constrained to a maximum value of 500 s−1 . Rate constants were set to zero if the calculated value was less than 0 . 01 s−1 . This simplified the numerical procedures used to solve the evolution of the cross-bridge populations . Randomly-distributed double-precision numbers were generated using the Mersenne Twister Algorithm [46] . Post-processing of simulation output files and subsequent figure development was performed using custom-written MATLAB ( The Mathworks , Nattick , MA ) software . Particle swarm optimization routines [47] were used to fit the force traces predicted by the simulations to selected experimental records . This was done by searching for the lowest attainable value of an error function defined as ( 10 ) where Fexpt , i is the experimentally-recorded force value at time-point i and F ( Φ ) predict , i is the corresponding prediction for parameter set Φ . Solving Eq 2 for a framework with nm = 6 and nhs = 50 took ∼0 . 25 s on a quad-core 2 . 5 GHz personal computer . Each simulated force response ( of order 103 time-steps with 1 ms resolution ) therefore required ∼5 minutes to compute . To reduce the wall-time required for the parameter estimation procedures , the calculations were performed using spare screen-saver processing time on ∼30 computers running DEngine ( for Distributed computing ENGINE ) software developed by the author ( http://www . dengine . org ) . This arrangement allowed typical optimization tasks to be completed using a particle swarm algorithm [47] in ∼2 days ( ∼10 times faster than if the task was performed using a single representative machine ) .
|
Quantitative muscle biophysics has been dominated for the last 60 years by reductionist theories that try to explain the mechanical properties of an entire muscle fiber as the scaled behavior of a single half-sarcomere ( typical muscle fibers contain ∼106 such structures ) . This work tests the hypothesis that a fiber's mechanical properties are irreducible , meaning that the fiber exhibits more complex behavior than the half-sarcomeres do . The key finding is that a system composed of many interacting half-sarcomeres has mechanical properties that are very different from that of a single half-sarcomere . This conclusion is based on the results of extensive computer modeling that reproduces the mechanical behavior of a fast mammalian muscle fiber during an imposed stretch without requiring that titin filaments become more than 3-fold stiffer in an activated muscle . This work is significant because it shows that it is probably not sufficient to attribute functional properties of whole muscle fibers solely to the behavior of a single half-sarcomere . Systems-level approaches are therefore likely to be required to explain how known structural and biochemical heterogeneities influence function in normal and diseased muscle tissue .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"mathematics",
"physiology/muscle",
"and",
"connective",
"tissue",
"biophysics/theory",
"and",
"simulation",
"physiology/motor",
"systems",
"computational",
"biology/systems",
"biology"
] |
2009
|
Interactions between Connected Half-Sarcomeres Produce Emergent Mechanical Behavior in a Mathematical Model of Muscle
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This study aims to estimate the age-specific risks of clinical dengue attack ( i . e . , the risk of symptomatic dengue among the total number of dengue virus ( DENV ) infections ) during primary and secondary infections . We analyzed two pieces of epidemiological information in Binh Thuan province , southern Vietnam , i . e . , age-specific seroprevalence and a community-wide longitudinal study of clinical dengue attack . The latter data set stratified febrile patients with DENV infection by age as well as infection parity . A simple modeling approach was employed to estimate the age-specific risks of clinical dengue attack during primary and secondary infections . Using the seroprevalence data , the force of infection was estimated to be 11 . 7% ( 95% confidence intervals ( CI ) : 10 . 8–12 . 7 ) per year . Median age ( and the 25–75 percentiles ) of dengue fever patients during primary and secondary infections were 12 ( 9–20 ) and 20 ( 14–31 ) years , respectively . The estimated age-specific risk of clinical dengue increases as a function of age for both primary and secondary infections; the estimated proportion of symptomatic patients among the total number of infected individuals was estimated to be <7% for those aged <10 years for both primary and secondary infections , but increased as patients become older , reaching to 8–11% by the age of 20 years . For both primary and secondary infections , higher age at DENV infection was shown to result in higher risk of clinical attack . Age as an important modulator of clinical dengue explains recent increase in dengue notifications in ageing countries in Southeast Asia , and moreover , poses a paradoxical problem of an increase in adult patients resulting from a decline in the force of infection , which may be caused by various factors including time-dependent variations in epidemiological , ecological and demographic dynamics .
Dengue ranks among the most important infectious diseases with a major impact on public health in many countries in the tropics and subtropics . Estimates showed that approximately 3 . 5 billion people , ∼55% of the world's population live in countries at risk for dengue [1] . The global incidence has increased steadily over the last six decades , simultaneously with an increase in geographic distribution and a transition from epidemic-type dengue with long interepidemic intervals to endemic-type with seasonal fluctuation [2]–[4] . Dengue virus ( DENV ) transmission primarily takes place through bites by the principal mosquito vectors , Aedes aegypti , which feed preferentially on human blood , and are often found in and around human dwellings [5] , [6] . Infection with any of the four dengue serotypes results in either asymptomatic infection , or a spectrum of clinically apparent disease ranging from mild undifferentiated febrile illness to severe dengue of which dengue shock syndrome ( DSS ) is the most common life threatening syndrome in children [7] . The mechanisms for the variable clinical outcome are not completely elucidated , but genetic factors , race , maternal antibody , circulating serotype and infection with multiple serotypes are believed to play an important role in determining the disease severity [8] . When it comes to the disease severity , a well-established epidemiological risk factor is the age at infection [9]–[12] . It is known that differences in clinically apparent dengue vary by age; pre-school children and infants have rather more often undifferentiated febrile illnesses while pre-adolescent children often develop fever [13] , and moreover younger children with dengue hemorrhagic fever ( DHF ) are known to experience more severe clinical outcome ( e . g . higher case fatality ratio ) than adults [12] . Dengue is a pediatric disease in Southeast Asia except for Singapore . A rigorous vector control program has substantially reduced the transmission in Singapore and , as a consequence , dengue patients are predominantly seen in adults . Nevertheless , with the elevation in patients' age , the outcome of DENV infection may be more favorable since most adult dengue patients present with dengue fever ( DF ) instead of with DHF [14] . Apart from age , infection parity is known to be a critical factor of disease severity; primary infection with any of the four serotypes is believed to elicit lifelong immunity against that serotype , but confers partial or transient immunity against other serotypes [15] , [16] . Cross-reactive , but sub-neutralizing DENV-reactive IgG , acquired by a previous heterotypic serotype infection may enhance DENV infectivity which may result in higher viral burden and contribute to induced disease severity . Heterologous secondary infections have been associated with large , clinical outbreaks of DHF/DSS where severe dengue occurs most frequently in children [12] . In some rigorous observations , the age group with highest susceptibility to contracting DSS was that of children with a modal age of 8 to 11 years [17] , [18] . Although age at infection and infection parity are the representative key modulators of clinical dengue and disease severity , their relationship has yet to be established and explicitly quantified . A previous study investigated the relationship between age at primary infection in Brazil and the risk of febrile illness , suggesting that adults are more likely than children to have clinical dengue [19] . This result should ideally be validated in the Southeast Asian settings . Moreover , we have yet to understand the age-specific risk of symptomatic disease during secondary infection . This present study tackles these issues by analyzing epidemiological data sets in southern Vietnam , focusing specifically on the age-specific risk of symptomatic dengue given infection . That is , we do not consider age-specific severity of clinical dengue , and rather , focusing only on the conditional probability of illness given infection . Because of high transmission potential with co-circulating multiple serotypes , dengue has been mainly a pediatric disease in Vietnam , and ironically , this provides us with an opportunity to investigate the age-specific risks of clinical attack both during primary and secondary infections . The present study aims to characterize a fundamental relationship between age at DENV infection and the risk of developing clinical attack .
The protocols for recruitment , testing and follow-up were approved by the Review Board of the Cho Ray Hospital , Ho Chi Minh City , Provincial Health Services and the community stations . The study was explained and discussed in meetings ( e . g . with the People's Committee of the communities , the PHC-staff and school teachers ) . All patients ( or , for children , the parents or guardian ) gave written informed consent . Our study rests on empirical observations in Binh Thuan province which is located along the south-eastern coast of Vietnam , 150 km northeast of Ho Chi Minh City , wedged between the Truong Son forested mountains ( alt . 1100–1642 m ) in the west and the South Chinese Sea in the east . It covers 7 , 828 km2 and the estimated population was 1 , 140 , 429 inhabitants in 2004 . The majority of the population lives in rural areas , with approximately 187 , 042 people in and around the capital , Phan Thiet City . Healthcare is provided by a provincial hospital in Phan Thiet city , nine district hospitals and 115 community posts for primary healthcare ( PHC ) and disease control . We examined two pieces of epidemiological information , ( i ) age-specific seroprevalence and ( ii ) age-specific frequency of clinical attack of dengue during primary and secondary infections , as determined by serological confirmation , in order to estimate the age-specific risk of clinical dengue attack . Figure S1 shows the participating PHCs and the villages in which the serosurvey were conducted . The mean distance between the source of seroprevalence data and all PHCs was 40 . 5 km ( range 3–87 km ) . The former data set included age stratified seroprevalence data from a cross-sectional survey among primary school children in two communities ( Ham Kiem and Ham Hiep ) . This survey was conducted among 961 children , aged from 7 to 14 years , in 2003 . The detailed results are given elsewhere [20] , [21] . Approximately 1 ml of blood was collected by finger puncture in plain vials ( Greiner , Minicollect ) , left to clot at ambient temperature , centrifuged at 1000 rpm for 15 minutes and serum was transferred to a sterile vial for storage at −20°C until testing . All samples were tested for the presence of dengue specific serum antibodies against dengue virus using a commercial available indirect IgG enzyme-linked immunosorbent assay ( ELISA ) . The indirect IgG ELISA was performed according to the manufactures instructions ( Focus Technologies Inc . , Cypress , CA , USA ) [22] . Optical density ( OD ) values were measured at 450 nm with 620 nm as a reference with a Benchmark microplate reader ( Bio-Rad Laboratories , Inc . , Hercules , CA , USA ) . Results were expressed as the ratio between the sample OD value and the OD value of the kit calibration serum ( ODR ) , both after subtraction of the OD of an enclosed blank specimen . ODR values >1 were considered positive . Seroprevalence ( i . e . proportion positive ) was stratified by age group . Second , age-specific frequencies of clinical attack were derived from a prospective longitudinal observational study at 12 PHCs across Binh Thuan province and at the provincial malaria control center in Phan Thiet City . That study examined the etiology of acute undifferentiated fever ( AUF ) from March 2001 to March 2006 [23]–[27] . All patients presenting with AUF were included . AUF was defined as any febrile illness of duration less than 14 days , confirmed by an axillary temperature of ≥38 . 0°C , without any clinical indication for either severe systemic or organ specific disease . Malaria was excluded by microscopic examination of a thick blood smear . A standardized questionnaire was employed to collect demographic and clinical information . Serum samples were collected from patients with a febrile illness by venous puncture on presentation ( acute sample; t0 ) and after 3 weeks ( convalescence sample; t3 ) . Serum samples were stored at −20°C at the study sites until monthly transfer to Cho Ray hospital ( Ho Chi Minh City , Vietnam ) , where they were stored at −70°C . Complete sets of acute and convalescence samples were selected for dengue serology . In 2001 all collected serum pairs were tested with dengue ELISA; afterwards paired samples were randomly selected as two patients per PHC and per month from the total data set [23] . Paired serum samples were tested for dengue with direct IgG ELISA and IgM-Capture ELISA ( Focus Technologies Inc . , Cypress , CA , USA ) . It should be noted that these serological tests did not distinguish between an infection with DENV from that with Japanese Encephalitis virus ( JEV ) . Cross-reactivity with JEV antibodies may have occurred , potentially involving a small proportion of samples [21] . Details regarding the ELISA and the interpretation of results were described previously [28] . In brief , a fourfold increase of antibody concentrations between t0 and t3 was considered significant . The IgM concentration on t3 , relative to the IgG concentration on t3 was also used as a criterion . Acute primary DENV infection was defined as positive IgM on t3 with an IgM/IgG ratio on t3 greater than one . A positive IgM on t3 with an IgM/IgG ratio on t3 less than one , or a negative IgM reaction on t3 but with a positive IgG t3 and a fourfold molar increase of IgG between t0 to t3 were classified as acute secondary dengue . A negative IgM reaction on t3 , a positive IgG on t3 but without a fourfold increase between t0 and t3 was classified as “not acute dengue but past infection” , and a subject of both negative IgM and IgG on t3 was classified as “no dengue” . It could well be possible that patients with an immune response to secondary dengue infection have had a tertiary or even dengue infection with a fourth serotype . Because the immune response between sequential dengue infections was not explicitly distinguished by using this ELISA , we grouped all individuals with serological indicative of a repeated infection and defined these as the secondary dengue infections in the present study . The epidemiological , virological and clinical features have been described elsewhere [29] . All four serotypes have been circulating during the study period with a potential shift of the dominant DENV serotype over time . Whereas DENV-4 was the dominant serotype in 2001–2002 , DENV-1 and DENV-2 later came to be most frequently isolated .
The age-specific population size of Binh Thuan province is shown in Figure 2A . Mean and median ages ( and the 25–75 percentiles ) were 24 . 7 and 20 ( 9–35 ) years , respectively . Employing an exponential approximation , the natural death rate ( μ ) was estimated to be 4 . 05×10−2 ( 95% confidence interval ( CI ) : 4 . 04×10−2–4 . 05×10−2 ) per year . Figure 2B shows the observed and predicted age-dependent seroprevalence . The force of infection of the total of α serotypes , αλ , was estimated as 11 . 7% ( 95% CI: 10 . 8–12 . 7 ) per year . A total of 14595 febrile patients were included in our longitudinal survey . Eighty-three patients were excluded as the inclusion criteria for AUF were not met . That is , eleven patients were afebrile ( i . e . <38°C ) , axillary temperatures of 19 patients were not documented , and 53 patients were diagnosed with an organ specific disease ( e . g . pharyngitis ) at presentation . Paired sera were collected from 8268 febrile patients; 1938 ( 23 . 4% ) serum pairs were tested with dengue IgM- and IgG-ELISA . Of these , DENV infection was serologically confirmed in 382 patients ( 19 . 7% ) . Primary infection accounted for 76 confirmed patients ( 19 . 9% ) , and secondary infection for 306 patients . Their age-specific frequencies are shown in Figures 2C and 2D , respectively . Median age ( and the 25–75 percentiles ) of dengue fever patients during primary and secondary infections were 12 ( 9–20 ) and 20 ( 14–31 ) years , respectively , revealing that secondary infection occurs at significantly older ages ( p<0 . 01 , Wilcoxon test ) . None of confirmed dengue infections were suggestive of severe clinical forms of dengue , DHF or DSS . Using the maximum likelihood estimate of αλ = 0 . 117 and the default values of α and δ , age-specific frequencies of primary , secondary and tertiary infections are shown in Figure 3A . As indicated by 1/αλ , the mean age at primary infection is 8 . 5 years , and secondary and tertiary infections occur at older ages . Figure 3B shows the estimated risks of symptomatic dengue during primary and secondary infections for Weibull and exponential assumptions ( results with logit model is not shown as it yielded the similar qualitative pattern to Weibull ) . The conditional risks of clinical attack were shown to increase as a function of age during both primary and secondary infections . The estimated proportion of symptomatic subjects among the total number of infected individuals was below 7% for those aged younger than 10 years of age for both primary and secondary infections , but increased as patients become older , reaching to 8–11% by the age of 20 years . Within the age-band examined ( <60 years ) , both assumptions indicate that the risk of symptomatic dengue during secondary infection is higher than that during primary infection for all ages . The Weibull distributed age-specific risk of clinical dengue during primary and secondary infections plateau around the ages of 15 and 19 years , respectively . Figures 3C and 3D compares the observed and predicted age-specific numbers of symptomatic subjects during primary and secondary infections , respectively . Using default values of α and δ , the AIC values were estimated to be 1461 , 1460 and 1470 for logit , Weibull and exponential assumptions , respectively . The preference of Weibull assumption did not change when we varied α from 2 . 5 to 4 . 0 and δ from 10 days to 12 months . Figures 4A and 4B examine the univariate sensitivity of r2 ( a ) to α for Weibull and exponential assumptions , respectively . The age-specific risk of clinical attack was the highest for all ages with α = 3 , but the overall difference in the conditional risk from those with other α remained within 5% for Weibull assumption . The Weibull assumption was always preferred in terms of AIC , but the difference in AIC between the logit and Weibull models remained <3 for the range of α that we examined . Similarly , Figures 4C and 4D show the univariate sensitivity of r2 ( a ) to δ for the Weibull and exponential assumptions , respectively . The age-specific risk of symptomatic secondary dengue infection with default δ ( 1 month ) yielded the smallest estimates , but again the difference in the estimated risks of clinical attack remained within 5% for Weibull assumption . Again , AIC values indicated Weibull model as the best , but the differences in AIC values between logit and Weibull models remained <3 for the whole range of δ . Since our prospective study involved only 29 and 36 children aged 10 years or younger during primary and secondary infections , respectively , we also examined the effect of sample size on the age-specific conditional risk of illness given infection . Even when the absolute numbers of children ≤10 years was doubled , the qualitative patterns of risks ( i . e . age-specific increase in the risk of disease , and higher risk during secondary infection than primary infection ) remained the same . However , the age at which the risk of symptomatic dengue is saturated with logit and Weibull assumptions , was shifted to the left , approximately by 3–4 years younger as compared to the baseline . The AIC values were estimated to be 1664 , 1664 and 1686 for logit , Weibull and exponential assumptions , respectively . These increases perhaps reflect a mismatch of the estimated force of infection with the incidence data .
We estimated the age-specific risks of clinical dengue attack by combining two epidemiological data sets , ( i ) age-specific seroprevalence and ( ii ) age-specific frequency of symptomatic dengue during primary and secondary infections . The former data set was used to reconstruct the age-specific frequencies of primary and secondary infections ( including those with and without symptoms ) , and subsequently , by taking the age-specific ratio of the latter data set to the reconstructed infection frequency with an aid of modeling method , the age-specific conditional probability of disease given infection was estimated . Although our model required a number of simplifying assumptions , we have shown unambiguously that the conditional risks of clinical attack increased as a function of age for both primary and secondary infections . Thus , higher age-groups , e . g . , adolescents and young adults are more likely to develop symptomatic dengue than younger individuals , e . g . , primary school children . Moreover , Weibull model indicates that the age-specific risks of symptomatic disease in adults both during primary and secondary infection remain almost independent of age , perhaps reflecting greater variations in age-specific susceptibility to symptomatic disease among children and adolescents . To our knowledge , the present study is the first to characterize the age-specific risk of developing clinical attack during both primary and secondary dengue infection by means of epidemiological modeling method . Whereas the risk of severe complications given clinically apparent dengue ( e . g . , the risk of hospitalization and the case fatality ratio ) in children is higher than in adults [12] , the age-specific risk of disease itself is the other way around and increases with age . Although pathogenesis of DENV infection and its severe complications involves many unanswered questions , and despite their multifactoral nature , our study emphasizes a critical importance of age as a key modulating factor of the risks of clinical attack during primary and secondary infections . Two important practical implications can be drawn from our results . First , as was shown in a study in Thailand , a rapid demographic transition has taken place in many Southeast Asian countries where swift ageing , i . e . , the shift of the age distribution of human population toward older ages , has been observed [37] . Our results support the notion of Cummings et al . [37] in that the ageing society is truly at risk of increase in dengue incidence . Indeed , Binh Thuan province yielded an average age at infection of 8 . 5 years , which is slightly greater than a previous published estimate ( e . g . 5 . 2–6 . 1 years in Rayong , Thailand , 1980 [31] ) , indicating that the transmission is less intensive in Binh Thuan province in the 21st century than in Thailand , 1980 . Second , while the incidence in Southeast Asian countries has been increasing [38]–[42] , there has been a decline in the force of infection , resulting in a shift in the age distribution of DHF toward older age groups [33] , [37] . In addition to ageing , the decline might have reflected various factors including time-dependent variations in epidemiological , ecological and demographic dynamics , e . g natural decline in the transmission , successful control of vectors and human migration . Our exercise suggests that such a decline in the force of infection could nevertheless result in an increase in older symptomatic individuals , thereby resulting in a paradoxical increase in the total number of symptomatic dengue patients ( and thus , the incidence of symptomatic dengue individuals for the entire population ) . Although clinical outcome of severe DENV infection in adults may be more favorable than in children , in terms of prognosis of clinically apparent dengue [12] , [14] , the incidence of symptomatic cases may not decrease with a slight decline in the force of infection . Clarification on the population impact of age-specific risks of clinical attack on the total number of severe forms of dengue is the subject of our future studies . Despite our successful estimation of the age-specific risk of clinical dengue attack , two limitations of the present study should be noted . First , the majority of DENV infections remain asymptomatic , and a very small amount of symptomatic patients ( ∼5% ) results in severe disease [9] . Our longitudinal survey data did not capture sub-clinical infections or very mild symptomatic patients , implying that our estimate of the risk of clinical attack may have been potentially underestimated . Nevertheless , our survey did not select for specific signs and symptoms of dengue , examining only AUF patients by laboratory testing , and thus , we believe that the age distributions ( Figures 2C and 2D ) reflected unbiased age-specific frequencies of all the symptomatic subjects during primary and secondary infections . Second , we assumed that the force of infection is time- and age-independent and the transmission potential is identical among all co-circulating serotypes . Ignorance on these realisms , e . g . , seasonality , age-dependency and decline in λ over a long period of time , forces us to accentuate the lack of precision in our estimates of r1 ( a ) and r2 ( a ) . For example , the lack of age-dependency may have led to slight underestimation in r1 ( a ) among small children and potentially an overestimation for both r1 ( a ) and r2 ( a ) among adults . Besides , whereas modeling approach such as ours certainly requires a number of unrealistic assumptions , we believe that our conclusion on the qualitative pattern , i . e . , an increase in the risk of clinical attack with age , remains intact . Of course , various other pre-infection factors other than age and infection parity contribute to the risk of disease severity , including cross-protective immunity between serotypes , the number of co-circulating serotypes and their pathogenicity [40] , [43]–[49] . Indeed , our incidence data did not include any DHF patients among a total of 306 symptomatic patients during secondary infection . Although no direct comparison can be made , this 0% is significantly smaller than that estimated in a prospective study in Thailand [9] . Possible explanations are that ( a ) our prospective study focused on the etiology of AUF , and the fraction of patients with severe dengue manifestations ( e . g . who may not have presented at the PHCs or have sought care directly at higher medical level ) might have been potentially disregarded , ( b ) the average age at infection in Binh Thuan province is higher than that in Bangkok during 1980s , and secondary infection at higher age can reduce the absolute number of DHF patients , and ( c ) not only serotype but also different strains could yield differential virulence given symptomatic infection . Moreover , molecular epidemiological studies have demonstrated that long-term expansion of dengue epidemic is regulated by selection-driven adaptive evolution of DENV strains [50]–[52] . Since the absolute risk of symptomatic infection is vulnerable to the virus ( strain ) -specific virulence as well as our reliance on symptoms of patients and help seeking behavior , the estimate of absolute risk could potentially vary from one region to another . In that sense , our simple approach is regarded as a first step to characterize the epidemiological determinants of dengue in a rudimentary fashion , and our study at least confirmed age-specific increase in the risk of clinical dengue given infection , offering practically important implications . Modeling with sequential infection assumption still remains to be a common strategy to capture the serotypic sequential infection mechanisms [31]–[33] , [49] , and future incorporation of strain-specificity needs to account for strain specific virulence as well as host-response ( including cross immunity ) to each strain [53] , which will be far more complex than the simplistic sequential approach . In conclusion , we examined the age-specific risks of clinical attack during primary and secondary DENV infections in Vietnam , showing that those at higher age-group are more likely to develop symptomatic disease than younger individuals . Age as an important modulator of clinical dengue attack explains recent epidemiological shift in dengue notification in ageing countries in Southeast Asia , and moreover , poses a paradoxical problem of an increase in adult patients resulting from a decline in the force of infection which may be caused by various factors including time-dependent variations in epidemiological , ecological and demographic dynamics .
|
Although age at dengue virus ( DENV ) infection is recognized as playing a key role in characterizing the risks of clinical attack and disease severity , the contributions of age to disease development have yet to be quantified in detail . We estimated the age-specific risk of clinical attack ( i . e . , the risk of symptomatic dengue among the total number of DENV infections ) during primary and secondary DENV infections in Vietnam , by employing a simple epidemiological modeling approach in which two pieces of epidemiological data sets were used , i . e . , ( i ) age-specific seroprevalence and ( ii ) age-specific frequency of clinical attack of dengue during primary and secondary infections . We showed that those at higher age are more likely to develop symptomatic dengue than younger individuals for both primary and secondary infections; the estimated proportion of symptomatic patients among the total number of infected individuals was below 7% for those aged younger than 10 years of age for both primary and secondary infections , but was shown to be elevated as the patients become older , reaching to 8–11% by the age of 20 years . Age as an important modulator of clinical dengue attack explains recent increase in dengue notifications in ageing countries in Southeast Asia , and moreover , poses a paradoxical problem of an increase in adult patients resulting from a decline in the force of infection , which may be caused by various factors including time-dependent variations in epidemiological , ecological and demographic dynamics .
|
[
"Abstract",
"Introduction",
"Methods",
"Results",
"Discussion"
] |
[
"medicine",
"public",
"health",
"and",
"epidemiology",
"mathematical",
"computing",
"mathematics",
"epidemiology",
"infectious",
"disease",
"epidemiology"
] |
2011
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Age-Specificity of Clinical Dengue during Primary and Secondary Infections
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The unique ability of the tuberculosis ( TB ) bacillus , Mycobacterium tuberculosis , to persist for long periods of time in lung hypoxic lesions chiefly contributes to the global burden of latent TB . We and others previously reported that the M . tuberculosis ancestor underwent massive episodes of horizontal gene transfer ( HGT ) , mostly from environmental species . Here , we sought to explore whether such ancient HGT played a part in M . tuberculosis evolution towards pathogenicity . We were interested by a HGT-acquired M . tuberculosis-specific gene set , namely moaA1-D1 , which is involved in the biosynthesis of the molybdenum cofactor . Horizontal acquisition of this gene set was striking because homologues of these moa genes are present all across the Mycobacterium genus , including in M . tuberculosis . Here , we discovered that , unlike their paralogues , the moaA1-D1 genes are strongly induced under hypoxia . In vitro , a M . tuberculosis moaA1-D1-null mutant has an impaired ability to respire nitrate , to enter dormancy and to survive in oxygen-limiting conditions . Conversely , heterologous expression of moaA1-D1 in the phylogenetically closest non-TB mycobacterium , Mycobacterium kansasii , which lacks these genes , improves its capacity to respire nitrate and grants it with a marked ability to survive oxygen depletion . In vivo , the M . tuberculosis moaA1-D1-null mutant shows impaired survival in hypoxic granulomas in C3HeB/FeJ mice , but not in normoxic lesions in C57BL/6 animals . Collectively , our results identify a novel pathway required for M . tuberculosis resistance to host-imposed stress , namely hypoxia , and provide evidence that ancient HGT bolstered M . tuberculosis evolution from an environmental species towards a pervasive human-adapted pathogen .
Mycobacterium tuberculosis ( Mtb ) is an obligate , strictly human-adapted pathogen of major public health importance [1] . One of the most striking features of this microorganism is its ability to persist in lung lesions , the granulomas , for years and even decades in a so-called “dormant” state , before it eventually reactivates and causes tuberculosis ( TB ) disease . Up to one fourth of the global population is thought to carry such latent Mtb infection [2] . The human granuloma is an acidic , nutrient-poor and highly hypoxic environment [3] . To survive such hostile conditions , Mtb is thought to have evolved multiple metabolic mechanisms , including the use of fatty acids as carbon and energy sources for example [4] . How these mechanisms were acquired remains largely unknown . Horizontal gene transfer ( HGT ) is a primary driving force in evolution of prokaryotes [5] . By enabling the sudden acquisition of novel metabolic functions , HGT can shift the overall ecology of bacterial recipients , granting them with the ability to colonize new environments , including new living hosts , in a pathogenic or non-pathogenic ( i . e . symbiotic or commensal ) manner [6 , 7] . The recent evolution of Mtb and related species of the so-called Mtb complex ( MTBC ) , which cause TB in human and other mammals , is considered mostly clonal , with few if any HGT events detected within the complex or between the complex and other species [8] . However comparative genomics and other in silico studies have revealed important episodes of HGT in early steps after the divergence of non-tuberculous mycobacterial species , including in branches of TB bacilli represented by Mycobacterium canettii ( also known as smooth tubercle bacilli , STB ) that preceded the emergence of the MTBC ancestor [8–14] . Many of these exogenously acquired genes are clustered into genomic islands , and the use of parametric methods allowed us to assign phylogenetic origins to most of them . Strikingly , a large fraction of these genes were acquired from environmental species , belonging to the genera Rhizobiales , Pseudomonadales , Burkholderiales , and Bifidobacteriales [9 , 10] , supporting the previous assumption that the MTBC ancestor was most likely an environmental species [15] . Here , we explored whether these ancient episodes of HGT played a role in the acquisition of virulence mechanisms during Mtb evolution , rather than reflecting natural gene flow . We were particularly interested by a 15-kb genomic island , rv3108-26c [15] , hereinafter named Moco-1 , which contains genes , namely moaA1-D1 , organized into an operon and predicted to encode enzymes involved in the early steps of the molybdenum cofactor ( Moco ) biosynthesis pathway [16 , 17] . In all living organisms , Moco and related Mo-containing cofactors are required for the proper function of various oxidoreductases , including the canonical prokaryotic nitrate reductase ( NR ) NarGHI [16 , 18] , which fulfills both nitrate assimilatory and anaerobic respiratory functions in Mtb [19–22] . The moaA1-D1 gene set was previously reported to be required for NR-mediated nitrate assimilation by Mtb when bacteria are grown on nitrate as sole nitrogen source under aerobic conditions [23] . Whether these genes are required for nitrate respiration under hypoxia has not been investigated . The exclusive presence of Moco-1 in genomes of TB-causing mycobacteria strikingly contrasts with the universal distribution of homologues of these genes , namely moaA2-D2 , among Mtb and all other mycobacteria [17] . Thus we wondered whether acquisition of the supplemental moaA1-D1 gene set influenced Mtb pathoadaptation . In this article , we show that the horizontally acquired moaA1-D1 genes , but not their vertically transmitted moaA2-D2 homologues , are up-regulated by the hypoxia-inducible transcriptional regulator MoaR1 , which also belongs to the Moco-1 genomic island . Our data show that hypoxia-specific induction of the moaA1-D1 locus sustains Mtb nitrate respiration and persistence in the absence of oxygen in vitro and in vivo . Altogether , our study identifies a novel pathway required for Mtb resistance to hypoxia , and uncovers a key contribution of ancient HGT to the evolutionary success of this major pathogen .
The organization of the moa and related genes involved in the Moco biosynthesis pathway ( S1 Fig ) is very complex in Mtb , with essentially three sets of genes numbered as one to three [15 , 23] . The moaA1-D1 genes , which are involved in the early steps of the Moco biosynthesis pathway ( S1 Fig ) , are embedded in a ~15-kb genome fragment , corresponding to the rv3108-26c genes and hereinafter named Moco-1 . We and others previously identified Moco-1 as a genomic island acquired through HGT after the divergence from the phylogenetically closest non-tuberculous mycobacterial species , Mycobacterium marinum and Mycobacterium kansasii [9 , 11 , 12] . In particular , the genomic signature pattern , i . e . the tetranucleotide frequency [24] , of the first ~4-kb fragment of Moco-1 , i . e . rv3108-13 , which includes the moaA1-D1 genes , is incongruent with that of the Mtb genome as a whole ( Fig 1A–1C ) . This suggests that i/ Moco-1 is a mosaic resulting from two or more HGT events , or that ii/ Moco-1 was acquired in a single HGT event followed by compositional amelioration/erosion of the rest of the island , i . e . rv3114-26c ( Fig 1A ) . A genomic signature-based phylogenetic analysis using the Genomic Origin of Horizontal Transfers and Metagenomics ( GOHTAM ) program [25] indicated that the rv3108-13 locus clusters with plasmids of the β-proteobacterium species Burkholderia vietnamiensis ( Fig 1A–1C ) , suggesting a possible origin for Moco-1 . The Moco-1 region was examined in M . canettii isolates , obtained from human TB cases but thought to represent earlier stages of pathoadaptive evolution relative to the MTBC ( 8 , 14 , 45 , 46 ) . Strikingly , the Moco-1 region was detected as a complete genomic island only in some M . canettii strains , including representatives of the genomically most divergent lineages from the MTBC ( i . e . STB-K , -J , and -I; S2 Fig ) , suggesting that the Moco-1 region was already acquired by the common progenitor of M . canettii . In other M . canettii strains , such as STB-A , -D , -E , -H and -L , a sequence block from the rv3112 to rv3125c orthologues is missing , resulting in the truncation of the rv3111 ( moaC1 ) and rv3126c orthologues on both flanks , with an identical junction sequence among the strains ( S2 Fig ) . The latter observation suggests that the Moco-1 region was partially deleted in a single event at a common node during subsequent divergence of some M . canettii lineages . However , it is also possible that the region was first acquired and/or partially deleted in individual lineages , and then shuttled to other lineages by intra-species recombination . Indeed , we inferred traces of such shuttling between M . canettii strains from the observation of an almost perfect sequence match between gene blocks from at least rv3105c to rv3117 orthologues of STB-I and STB-G , contrasting with the much higher SNP density detected in neighboring regions between both strains ( S3 Fig ) . A second moa gene cluster , namely moaA3-moaB3-moaC3-moaX ( in which moaX results from a moaD-E gene fusion [23] ) , is also present both in M . canettii and MTBC genomes but not in other mycobacteria ( Fig 1D , S4 Fig ) , and was thus proposed to also result from ancient HGT into a common ancestor of the TB bacilli [11] . The close sequence similarity between these genes and the moaA1-D1 genes ( S4 Fig ) suggests that they originate from duplication from the moaA1-D1 locus . However , they have been subject to partial gene loss at least in Mtb H37Rv , where part of moaB3 and the entire moaA3 genes are absent due to an IS6110-mediated deletion [26] . Finally , Mtb contains a third set of moa genes , namely moaA2-D2 , which are present in all fast- and slow-growing Mycobacterium species that we examined , indicating vertical transmission from a distant , common mycobacterial ancestor ( S4 Fig , Fig 1D ) . This latter gene cluster encompasses the unique adenylyltransferase-encoding gene mog ( rv0865 ) , which is needed for MoCo biosynthesis ( S1 Fig ) [16] . Thus , it appears that , relative to non-tuberculous mycobacteria , the architecture of the moa gene sets is original and quite plastic in the MTBC and in M . canettii strains , consisting of a complex combination of horizontally acquired ( moaA1-D1 ) , vertically transmitted ( moaA2-D2 ) , and duplicated and diversified ( moaA3-X ) gene clusters . Some of them show post-HGT modifications such as partial gene loss , e . g . the absence of moaA3 and moaB3 from Mtb H37Rv or the absence of selected genes in the Moco-1 region from some M . canettii strains , as well as traces of gene fusion events , e . g . moaX in the MTBC . This led us to ask which had been the selective advantage , if any , of the horizontal acquisition of supplemental sets of moa genes by the TB bacilli during evolution . To address this question , we used the Mtb H37Rv strain , which contains only one set of HGT-acquired moa genes , i . e . moaA1-D1 , but not the complete moaA3-X cluster , in addition to vertically transmitted moa genes , i . e . moaA2-D2 . The moaA1-D1 locus is known to be involved in nitrate assimilation when nitrate is provided as sole nitrogen source [23] . Here we asked whether this locus is required for nitrate respiration , i . e . to use nitrate as terminal electron acceptor , in the absence of oxygen . We generated a Mtb H37Rv mutant deleted of the rv3109-15 locus ( Δrv3109-15 ) , which encompasses the moaA1-D1 operon , using the recombineering technology [27] and its corresponding complemented variant . In normoxic conditions ( 21% O2 ) , the Δrv3109-15 mutant did not show any defect in nitrate reduction compared to the wild type and complemented strains , as measured by nitrite production in the culture medium ( Fig 2A ) , and in line with previous findings [23] . In contrast , the Δrv3109-15 mutant was impaired in nitrate respiration under hypoxic conditions ( <1% O2 ) , and this phenotype was reversed by genetic complementation using an integrating cosmid carrying a genomic insert from Mtb H37Rv that over-spans the deleted region and flanking sections and provides gene expression from their natural promoters ( Fig 2B ) . Similarly , transformation of the Δrv3109-15 mutant with an integrative plasmid expressing the moaA1-D1 genes from a strong , constitutive promoter also led to a complemented phenotype ( S5 Fig ) , This latter finding confirmed the importance of moaA1-D1 for sustaining nitrate respiration under hypoxia and validated results obtained by the cosmid-complemented construct . For the remaining experiments in this study , the cosmid-complemented construct was used . As a control , a mutant deleted in the mog gene ( Δmog ) , in which Moco biosynthesis is supposed to be abolished ( S1 Fig ) , was totally impaired in its ability to reduce nitrate in hypoxic conditions , which was also reversed after genetic complementation ( Fig 2B ) . In order to extend our finding to other parts of the Moco-1 genomic island , we generated a mutant deleted of the rv3115-19 locus ( Δrv3115-19 ) , which contains the moeB2 and moaE1 genes . This mutant did not show any defect in nitrate reduction , neither in normoxic nor in hypoxic conditions ( Fig 2A and 2B ) . These results demonstrate that within Moco-1 , the moaA1-D1 locus plays a key part in proper function of the Mtb NR , at least in hypoxic conditions; under these conditions , the moeB2 and moaE1 genes are dispensable , either because they are not functional or because their function is redundant with that of their moeB1 and moaE2 homologues . In a reverse evolution experiment , we also found that heterologous overexpression of moaA1-D1 in M . kansasii , a species close to the MTBC but which does not harbor the moaA1-D1 locus , resulted in an enhanced ability of this bacterium to reduce nitrate ( Fig 2C ) , further strengthening our conclusion on the role of moaA1-D1 in nitrate reduction . Because nitrate reduction sustains Mtb persistence under hypoxia in vitro [19] , we asked whether the impaired ability of the Mtb Δrv3109-15 mutant to reduce nitrate had any consequences on its capacity to survive hypoxic stress . In two models of rapid and slow ( the “Wayne model” [28] , which allows studying later events during hypoxia and dormancy ) O2 depletion , the Δrv3109-15 mutant showed a defect in surviving hypoxic stress by 3- and 2-orders of magnitude , respectively , which was reversed upon genetic complementation ( Fig 2D and 2E ) . Interestingly , genetic deletion of the 3’-fragment of the Moco-1 island in the Δrv3115-19 mutant did not affect the ability of Mtb to survive slow or fast hypoxic stress ( Fig 2D and 2E ) . Importantly and in line with our results in Mtb , heterologous expression of moaA1-D1 in M . kansasii enabled this bacterium to survive hypoxia , while wild-type M . kansasii progressively dies in this condition ( Fig 2F ) . Altogether , these data show that although moaA1-D1 is dispensable for nitrate reduction in normoxic conditions , this locus is required for nitrate respiration and persistence under hypoxic conditions . Moreover , the results obtained in M . kansasii suggest that the acquisition of moaA1-D1 represented a key step during the course of evolution of the MTBC ancestor in becoming adapted to hypoxia . Because early adaptation to hypoxia is a key step in mycobacterial entry into dormancy , we next asked whether the moaA1-D1 locus played a part in this process . We measured expression of three dormancy-related genes of the so-called DosR regulon [29 , 30] , namely tgs1 , hspX/acr and rv1738 , in the wild type and Δrv3109-15 mutant at early ( 6 h ) or late ( 4 days ) stages after O2 depletion . At both stages induction of the DosR-regulated genes was impaired in the mutant strain ( Fig 3A ) . As a consequence of impaired induction of tgs1 , accumulation of triacylglycerol ( TAG ) , which is a hallmark of mycobacterial dormancy [31] , was also found impaired in the Δrv3109-15 mutant and restored in the complemented strain ( Fig 3B–3D , S6 Fig ) . Mycobacterial entry into dormancy is associated with a modification in the redox status of the cell , which is accompanied by modifications in ATP turnover . In our model , incubation of the Δrv3109-15 mutant in hypoxic conditions resulted in a diminished generation of reduced NAD ( Fig 3E ) and an increased production of ATP ( Fig 3F ) , compared to the wild type and complemented strains . As controls , the wild type strain cultivated in the absence of nitrate or a Mtb mutant inactivated in narG [32] ( ΔnarG ) , which encodes the catalytic subunit of the membrane-bound NR NarGHI , were both unable to produce reduced NAD , and over-produced ATP in the same conditions ( Fig 3E and 3F ) . Altogether , these findings indicate that the moaA1-D1 inactivation partially phenocopies narG deletion , and that the moaA1-D1 locus is involved in Mtb adaptation and proper entry into dormancy . Because the Mtb H37Rv genome harbors paralogues of moaA1-D1 genes , namely moaA2-D2 and moaC3 , we wondered whether hypoxia could act as a triggering signal for expression of all or a subset of these genes . Strikingly , we found that while expression of moaA1-D1 was strongly upregulated by hypoxia , expression of all their homologues but moaB2 was irresponsive to hypoxia ( Fig 4A ) . At a first glance , these data are different to results of previous studies , in which hypoxic stress was not associated with induction of the moaA1-D1 locus [29 , 33] . However in these previous studies , bacteria were cultivated in a rich medium ( i . e . 7H9/ADC ) . In our hands also , hypoxic stress in this rich medium barely induced moaA1-D1 expression ( S7A Fig ) . This indicates that the moaA1-D1 locus is hypoxia-responsive when bacteria are cultivated in minimal medium only , which mimics the nutrient-poor conditions found in granulomas in vivo . At an early stage during the transition to hypoxia , we also found that expression of the nitrate transporter NarK2- , and the NR catalytic subunit NarG-encoding genes was induced ( Fig 4B ) . This confirms previous findings obtained for NarK2 [21] . Regarding NarG , our findings are reminiscent of the results of a recent study in which narG expression was induced after addition of nitrate in hypoxic conditions [34] . The MoaR1 ( Rv3124 ) transcriptional regulator , which is encoded by a gene in the Moco-1 genomic island , was shown to activate moaA1-D1 gene expression in recombinant Rv3124-overexpressing Mtb and Mycobacterium bovis bacillus Calmette Guérin ( BCG ) strains [35] . Here , we found that moaR1 expression was also induced by hypoxia ( Fig 4C ) . Again , such induction was only observed when bacteria were cultivated in minimal medium , and not in rich medium ( S7B Fig ) . Strikingly , hypoxic induction of moaA1-D1 was abolished in a Mtb mutant strain deleted of the moaR1 gene ( Δrv3124 mutant ) , at both early ( 6 h ) and late ( 4 days ) stages after transition to hypoxia ( Fig 4D ) . As observed in the Δrv3109-15 mutant , the moaR1-deleted mutant was likewise impaired in induction of the dormancy genes tgs1 , hspX/acr , rv1738 ( Fig 4E ) , reflecting an altered entry into dormancy . Similarly , the Δrv3124 mutant was impaired in nitrate reduction and TAG accumulation in hypoxic , but not normoxic conditions ( Fig 4F–4H ) . Finally , heterologous overexpression of moaR1/rv3124 in a moaA1-D1-complemented recombinant M . kansasii strain , whose genome does not contain a moaR1 homologue , resulted in increased nitrate reduction ( Fig 4I ) , and further enabled this bacterium to survive hypoxia ( Fig 4J ) . Altogether , these data show that MoaR1 is a hypoxia-responsive transcriptional activator that drives moaA1-D1 expression and sustains Mtb nitrate reduction and entry into dormancy in hypoxic and nutrient-scarce conditions .
Our results highlight an important piece in the complex process of Mtb adaptation to hypoxia [42] . In this pathogen , early ( <2 h ) response to O2 depletion mostly relies on the DosR transcriptional regulator that is activated by its cognate redox- and O2- sensor histidine kinases , DosS and DosT . During prolonged hypoxic stress , the DosR-independent , so-called enduring hypoxic response ( EHR ) allows sustained bacterial survival in the absence of O2 and non-replicating persistence [43] . A recent system-level analysis revealed a complex network of transcriptional regulators involved in gene expression rewiring during Mtb transition into hypoxia or reaeration [44] . This network is centered on the transcription factor Rv0081 that connects the early ( DosR ) and late ( EHR ) responses to various metabolic switches that occur during mycobacterial adaptation to O2 depletion . Where does the MoaR1 regulation of the moaA1-D1 locus stand in this network ? Analyses of the global transcriptional effects of overexpression of >200 transcription factors [45] indicate that in addition to moaA1-D1 , MoaR1 strongly activates expression of rv3113 , rv3114 , rv3121 ( cyp141 ) and rv3125c ( ppe49 ) , but is unlikely to modulate expression of any other genes in the Mtb genome . This suggests that MoaR1 is a Moco-1-specific regulator . The same study indicates that moaR1 expression is slightly induced by other transcription factors , namely the hypoxia regulatory hub Rv0081 [44] , the cell division-associated regulator Rv3260c/WhiB2 , and the starvation-induced regulator Rv3291c . Moreover , in addition to MoaR1 , the moaA1-D1 locus can be activated by Rv0081 , by Rv0324 , a regulator involved in the HER [43] , by Rv3286c/SigF , and by the histone-like protein Rv3597c/Lsr2 . Although these data must be taken with caution as they were obtained using recombinant over-expressing systems , they nevertheless suggest that genes of the Moco-1 genomic island might also be under the control of one or more transcriptional regulators of the Mtb core genome ( e . g . Rv0081 ) , either directly or , more likely , after early induction of MoaR1; indeed our data show that genetic inactivation of MoaR1 completely abrogates hypoxia-mediated induction of the moaA1-D1 locus . This complex regulatory network of Moco-1 gene expression during hypoxic stress will need to be further deciphered . In normoxia , basal expression of moa genes might be sufficient for proper Moco synthesis and normal function of the NR and other Moco-dependent enzymes [17] , as has been shown for moaD2 and the moaD-E hybrid gene moaX [23] . The differential responses of the various moa homologues presumably reflect Mtb adaptation to various oxygen-limited microenvironments encountered during the course of infection . Importantly , our study was conducted in the genetic background of the Mtb H37Rv strain in which the moa3 locus has been partially deleted . The phenotype of a rv3109-12-deleted mutant might be different in a background with an intact moa3 locus , such as M . bovis , which will need further investigation . Our findings also bring new insights into the mechanisms that favored the emergence of Mtb as an extremely “successful” and widespread pathogen , and on the contribution of ancient HGT events to this process , which has long been disregarded . The presence of the Moco-1 locus , either in full or partially deleted , in M . canettii strains representing very early branching lineages of the tubercle bacilli [14] , indicates that this region was acquired at an early time point in the evolution of Mtb , after the divergence from non-tuberculous mycobacteria but before clonal expansion of the MTBC . The presence of Moco-1 in the M . canettii genomes also offers a plausible explanation for the putative environmental origin of this region inferred from our genomic signature analysis . While the MTBC represents obligate mammalian-adapted pathogens , several lines of evidence suggest that M . canettii is less adapted to mammalian hosts and might have an environmental reservoir [8 , 14 , 46 , 47] . The observed interruption of the moaA1-D1 gene set in some M . canettii strains , might explain , at least in part , why these bacteria are less adapted to mammalian hosts than Mtb . Such a reservoir might have favored direct contacts and hence HGT between the ancestral M . canettii-like pool and environmental bacteria , such as Burkholderia spp . or other close species . Our results evoke that lateral acquisition of the moaA1-D1 locus and the MoaR1 transcriptional regulator by such ( an ) ancestor ( s ) improved its/their potential to rapidly adapt its/their metabolism to nitrate respiration under hypoxia , which is a hallmark of most TB granulomas . This scenario is also strongly supported by our findings that introduction and overexpression of moaA1-D1 in the environmental mycobacterium M . kansasii , representing the phylogenetically closest non-tuberculosis mycobacterial species , enabled the latter recombinant strain to both greatly improve its nitrate respiration and readily survive upon oxygen depletion . Thus , several lines of evidence suggest that the unique ancestral acquisition of this locus represented a significant evolutionary shift towards improved metabolic adaptation of an environmental mycobacterial recipient species to stringent hypoxic conditions . Yet , the role of the moaA1-D1 gene set in species of the MTBC that harbor a complete version of the moaA3-X paralogue locus , such as Mycobacterium bovis , remains to be explored . More generally , our findings raise intriguing questions about which of the up to 9% of the Mtb genes plausibly acquired by exogenous HGT [9 , 11 , 12] might have supported Mtb evolution towards pathogenicity . Taken together , our results thus suggest an evolutionary scenario in which the MTBC ancestor has progressively “learned” to become a most successful pathogen in part by gain of critical functions , through natural selection following exogenous HGT from its environmental neighbors , and by gene or gene allele shuttling within an ancestral M . canettii-like strain pools . Our recent data indicate that this adaptation was supplemented by parallel loss-of-function such as that affecting the pks5 locus , which resulted in bacterial surface remodeling and increased virulence during the transition from a generalist M . canettii-like ancestor to the obligate pathogens of the MTBC [48] . On a more practical aspect , deciphering such critical steps in early Mtb pathoevolution may provide clues for identifying yet unknown vulnerable targets of the tubercle bacillus , as outlined in this study , which might be of interest for the development of novel therapeutic intervention against TB . In line with this , an inhibitor of MoeW , another horizontally acquired enzyme involved in Moco biosynthesis [9] , was reported to improve Mtb killing [49] . A broader exploration of the potential of the many Mtb Moco biosynthesis enzymes , and those of the Moco-1 island in particular , as drug targets probably holds great promise for tackling TB , including latent infection .
Mycobacteria were grown at 37°C in Middlebrook 7H9 medium ( Difco ) supplemented with 10% albumin-dextrose-catalase ( ADC , Difco ) and 0 . 05% Tyloxapol ( Sigma ) , or on Middlebrook 7H11 agar medium ( Difco ) supplemented with 10% oleic acid-albumin-dextrose-catalase ( OADC , Difco ) . When required , kanamycin , hygromycin or streptomycin were added to the culture media . In the Wayne model , bacteria were grown in Dubos medium ( Difco ) supplemented with 10% Dubos medium albumin ( Difco ) and 0 . 05% Tween 80 ( Sigma ) in glass tubes tightly closed with screwed caps and tight rubber caps , and incubated at 37°C , as previously described [28] . In experiments using nitrate as sole nitrogen source ( fast hypoxia model ) , bacteria were first grown in Sauton’s modified medium containing 0 . 05% Tyloxapol , 0 . 5 g/L KH2PO4 , 0 . 5 g/L MgSO4 , 2 g/L citric acid , 10 g/L glycerol and 5g/L asparagine prepared in tap water and neutralized to pH 7 . 0 with NaOH . Before switching to hypoxia , bacteria were washed with PBS and asparagine was replaced with NaNO3 ( 10 mM ) . Anaerobic conditions were generated in an anaerobic jar containing a GasPak EZ anaerobe container system ( Fisher scientific ) . Nitrite production in culture media was measured using the Griess reagent assay ( Sigma ) . For measurement of intracellular [NADH , H+] , bacteria were lysed at 65°C for 20 minutes and NADH , H+ was quantified with a NAD/NADH Quantitation Kit ( Sigma ) . Total protein concentration was determined using the Micro BCA Protein Assay Kit ( Thermo Scientific ) . Intracellular [ATP] was quantified after lysis of the bacteria for 10 minutes at 100°C using the BacTiter-Glo Microbial Cell Viability Assay ( Promega ) . All mutant strains of Mtb were constructed by allelic exchange using the recombineering method [27] . Briefly , allelic exchange substrates for the Δrv3109-3115 , Δrv3115-3119 and Δmog mutants , were prepared by amplifying from Mtb H37Rv genomic DNA two 1‐kb DNA fragments flanking the regions to be deleted that were inserted on each side of a kanamycin resistance cassette , into a pGem5Z plasmid . The recombination substrate was recovered by enzymatic digestion and purified from agarose gels . For the Δrv3124 strain , a DNA fragment of 1311 bp ( with rv3124 in position 442-1311bp ) was amplified by PCR , cloned into pGem5Z and a kanamycin resistance cassette was inserted at position 388 bp of rv3124 . Linearized constructs were introduced by electroporation in Mtb competent cells carrying pJV53H , a hygromycin resistant pJV53-derived plasmid expressing recombineering proteins . H37Rv::pJV53H was grown in 7H9-ADC-Tween 80 in the presence of hygromycin ( 50 μg/ml ) until mid-log phase and expression of recombineering enzymes was induced by 0 . 2% acetamide ( Sigma ) overnight at 37°C . After induction , electrocompetent bacteria were prepared and electroporation performed with 100 ng of the linearized fragments . After 48 h incubation at 37°C in 7H9-ADC-Tween 80 without antibiotic , bacteria were plated onto 7H11-OADC agar medium in the presence of kanamycin ( 50 μg/ml ) . Kanamycin resistant clones were harvested , grown in 7H9-ADC-Tween 80 in the presence of kanamycin and verified to carry the expected allele replacement by PCR . The pJV53H plasmid was then lost by serial rounds of culture without antibiotic . For complementation of the Δrv3109-3115 strain , we used the pYUB412-derived integrative cosmid I528 [50] . I528 confers resistance to hygromycin and harbors a DNA fragment encompassing the region 3 , 454 to 3 , 485 kbp in the Mtb H37Rv genome . For complementation of the Δrv3115-3119 and Δrv3124 strains , we used the pYUB412-derived integrative cosmid IE240 , which harbors a genomic fragment from Mtb Erdman corresponding to the genomic region 3 , 479 to 3 , 516 kbp of Mtb H37Rv . The description of the cosmids used in the study , together with that of the deleted regions in the mutants , are provided in S8 Fig . The Δmog complemented strain was obtained after transformation with a pVV16mog vector with mog gene expression under the control of the constitutive hsp60 promoter . The ΔnarG mutant and its complemented strain were described earlier [19] . Primers used for PCR are listed in S1 Table . For constitutive expression of moaA1-D1 in M . kansasii , the rv3109-rv3112 region was amplified by PCR from Mtb H37Rv genomic DNA and a plasmid containing this region under the control of a constitutive promoter ( P1 ) was constructed by multisite gateway recombination using the procedures detailed by Schnappinger et al . [51] . The resulting vector was transformed into M . kansasii for a stable integration at the att site of the L5 mycobacteriophage . The same approach was used for the generation of a plasmid constitutively expressing rv3124 . This latter construct was used for the transformation of a strain of M . kansasii previously transformed with the pYUB412-derived integrative cosmid I528 ( described above ) . Primers used for PCR are listed in S1 Table . A reporter strain of Mtb was constructed by transformation of wt Mtb strain with a reporter plasmid constructed by multisite gateway recombination using the procedures detailed by Schnappinger et al . [51] . The construct contains three different modules: the first one is the orf encoding the RFP under the control of a constitutive promoter ( P1 ) , the second one is a 1 kb region spanning from -900 to +100 bp of the start codon of rv3109 and the third module is an orf encoding the GFP . In this construct , GFP is expressed under the control of the rv3109 promoter , as previously defined by Mendoza Lopez et al . [35] . When transformed in Mtb , the construct is stably integrated in single copy at the att site of the L5 mycobacteriophage . Strains were adapted in culture medium containing NaNO3 ( 10 mM ) one week before they were incubated in hypoxic conditions . Total RNA was extracted from cultures grown to logarithmic phase ( OD600 between 0 . 5 and 0 . 6 ) using the RNeasy kit ( Qiagen ) following manufacturer’s instructions with slight modifications . Briefly , 5 mL of culture were centrifuged for 10 min at 1 , 800xg , the pellet was resuspended in 700 μL of 0 . 1% β-mercaptoethanol-containing RLT lysis buffer , and 0 . 1 μm-diameter glass beads were added to the tubes . Cells were lysed by two 120-second pulses at full speed in a bead-beater device . The samples were centrifuged for 30 sec at 20 , 200xg . One volume of absolute ethanol was added to the filtrate , and total RNA purified with an RNeasy column following the manufacturer’s procedure . RNA samples were treated for 30 min with 2U of Turbo DNase ( Turbo DNA free kit , Ambion ) . The amount and purity of RNA were quantified using a NanoDrop ND-1000 apparatus ( Thermo Scientific ) by measuring absorbance at 260/280 nm . Double-stranded cDNA was reverse-transcribed using the superscript III Reverse Trancriptase kit ( Invitrogen ) , according to the manufacturer’s protocol . For real-time qPCR , specific primers ( S1 Table ) were designed using the QuantPrime software[52] and PCR reactions were performed using SYBR Green Premix Ex Taq ( Ozyme ) , according to the manufacturer’s protocol . All real-time qPCR reactions were carried out using a 7500 Real-Time PCR System and data were analyzed using the 7500 Software version 2 . 3 ( Applied Biosystems ) . PCR array data were calculated by the comparative cycle threshold method , normalized with rpoB housekeeping gene , and expressed as mean fold change in experimental samples relative to initial time . Primers used for Rt-qPCR are shown in S2 Table . In order to visualize TAG accumulation , bacteria were cultivated for 30 days in Dubos-Tween-Albumin broth complemented with 50 μM of 1-pyrenedecanoic acid ( PDA , Molecular Probes ) . Bacteria were harvested by centrifugation , fixed for 2 h with 4% paraformaldehyde ( PFA ) at room temperature , and examined by confocal laser scanning microscopy . Images were acquired with an LSM 710 microscope and recorded using the Zen software ( Carl Zeiss , Inc . ) with a λexc = 360 nm and a λem between 400-500nm . Images were analyzed using the ImageJ software . For thin layer chromatography analysis of lipid content , total lipids were extracted with CHCl3/MeOH ( 1/1 ) and separation was done on silica plates using a CHCl3/MeOH/H20 60/16/2 mix as mobile phase . Fluorescence emission was recorded under UV illumination at λexc = 365 nm . Quantification of lipid droplets positive bacteria was performed in the same culture conditions; after PFA fixation , bacteria were analyzed by flow cytometry ( λexc = 450 nm ) using a LSR II flow cytometer ( Becton Dickinson ) . All animal experiments were performed in animal facilities that meet all legal requirements in France and by qualified personnel in such a way to minimize discomfort for the animals . All procedures including animal studies were conducted in strict accordance with French laws and regulations in compliance with the European community council directive 68/609/EEC guidelines and its implementation in France . All protocols were reviewed and approved by the Comité d’Ethique Midi-Pyrénées ( reference MP/03/07/04/09 ) . Six- to eight-week-old female mice ( C3HeB/FeJ , Jackson laboratory , or C57BL/6J , Charles River ) were anesthetized with a cocktail of ketamine ( 60 mg/kg , Merial ) and xylasine ( 10 mg/kg , Bayer ) and infected intranasally with ≈200 CFUs of mycobacteria in 25 μL of PBS-0 . 01% Tween 80 . At 21 and 98 days post-infection , mice were sacrificed , and lungs and spleen homogenates were plated onto 7H11 agar for CFU scoring . For histological analysis , mice were infected intranasally with ≈200 CFUs of the RFP- Prv3109-GFP reporter strain . Mice were sacrificed after 98 days infection and lungs and spleen were fixed for 24 hours at 4°C in Periodate-Lysine-Paraformaldehyde ( PLP ) prior freezing in Optimal cutting temperature compound ( OCT ) . Ten μm-sections were realized using a cryostat before labelling with TOPRO-3 ( Molecular Probes ) and examination by confocal laser scanning microscopy . Data were analyzed using the Student’s t-test ( two-tailed ) . The moa gene and protein sequences from Mtb ( H37Rv ) , M . bovis ( AF2122/97 ) , M . marinum ( M ) , M . fortuitum ( ATCC 6841 ) , M . smegmatis ( MC2155 ) , M . avium ( 104 ) , M . vaccae ( ATCC 25954 ) , M . abscessus ( ATCC 19977 ) , M . gilvum ( PYR-GCK ) , M . kansasii ( ATCC 12478 ) and M . gordonae were retrieved and analyzed using the Ensembl Genomes interface [53] . Horizontal gene transfers were identified either based on the genomic signature and a Kullback-Leibler divergence [9 , 24] , or from atypical codon usage [54] . Local Jensen-Shannon divergence in tetranucleotide frequency was calculated between sliding windows ( 5-kb in length , 100-bp step ) over the Mtb genome and either itself or the pBVIE01 plasmid . HGT donor candidates were screened using GOHTAM [25] , which includes the signatures profiles , i . e . tetranucleotide frequencies , of all the species present in GenBank . The hit found for rv3108-13 suggests that the most likely donor is closely related to the Burkholderia vietnamiensis G4 plasmids . Further investigations showed that the B . vietnamiensis plasmid pBVIE01 exhibits the closest genomic signature to that of the rv3108-13 cluster . This hit exhibited a quality score of 4/5 , from an Euclidean distance of 0 . 012 , and a confidence score of 4/5 given the respective length of the sequences compared . The genomic signature tree was built using GOHTAM by neighbor joining the pairwise comparison matrix of the 4-nucleotide word frequencies of all-versus-all taxa with an Euclidean distance [55] . The resulting distances and scale are subsequently converted into arbitrary units . Taxa are represented by either their whole chromosomal or whole specific plasmid sequence . Similarity matrixes between homologous proteins were built from pairwise alignments with BLASTP ( v 2 . 2 . 31+ ) [56] without sequence filters . The lower matrixes in orange depict the coverage of the alignment defined as the smallest aligned fraction of either the query or the subject sequence . The upper matrix depicts in blue-white-red the percentage of identity of the aligned fraction . Self-alignment of genes ( diagonals ) were not considered . Alignments of the moa gene sequences and flanking regions were performed for M . canettii strains STB-A ( CIPT 140010059 ) , -D , -E , -G , -H , -I , -J , and -K and Mtb H37Rv , M . bovis AF2122/97 , and M . africanum GM041182 , using corresponding genome sequences as retrieved under Magnifying Genome ( MaGe ) server ( https://www . genoscope . cns . fr/agc/microscope/home/index . php ) . Comparative alignments were performed based on analysis of gene synteny and BLAST searches , using a custom Multiple Annotation of Genomes and Differential Analysis ( MAGDA ) software , developed in the Plague and Yersinia pestis laboratory ( Centre for Infection and Immunity of Lille/University of Lille ) . ACT comparison files were generated using MAUVE version 2 . 3 . 1 software to visualize the SNP densities in the moa gene sequences and flanking regions between STB-G and STB-I [57 , 58] .
|
Mycobacterium tuberculosis , the etiological agent of tuberculosis ( TB ) , can persist for years and even decades in the lungs of its human host . Here we report that a unique M . tuberculosis gene cluster involved in the synthesis of the molybdenum cofactor , a cofactor for several oxidoreductases including the nitrate reductase , allows this major pathogen to respire nitrate and to persist in a dormant state under hypoxia , a stress condition encountered in lung TB lesions . Strikingly the M . tuberculosis ancestor , which most likely was an environmental harmless bacterium , acquired this gene cluster , together with its hypoxia-responsive transcriptional regulator , horizontally from neighboring bacteria . Our results uncover a key step in M . tuberculosis evolution towards pathogenicity .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"methods"
] |
[
"horizontal",
"gene",
"transfer",
"chemical",
"compounds",
"gene",
"transfer",
"nitrates",
"fungal",
"evolution",
"hypoxia",
"bacteria",
"research",
"and",
"analysis",
"methods",
"sequence",
"analysis",
"mycology",
"sequence",
"alignment",
"bioinformatics",
"gene",
"expression",
"chemistry",
"actinobacteria",
"genetic",
"loci",
"cell",
"biology",
"mycobacterium",
"tuberculosis",
"database",
"and",
"informatics",
"methods",
"genetics",
"biology",
"and",
"life",
"sciences",
"physical",
"sciences",
"evolutionary",
"biology",
"evolutionary",
"processes",
"organisms"
] |
2017
|
Horizontal acquisition of a hypoxia-responsive molybdenum cofactor biosynthesis pathway contributed to Mycobacterium tuberculosis pathoadaptation
|
The 2014–6 West African Ebola epidemic highlights the need for rigorous , rapid clinical trial methods for vaccines . A challenge for trial design is making sample size calculations based on incidence within the trial , total vaccine effect , and intracluster correlation , when these parameters are uncertain in the presence of indirect effects of vaccination . We present a stochastic , compartmental model for a ring vaccination trial . After identification of an index case , a ring of contacts is recruited and either vaccinated immediately or after 21 days . The primary outcome of the trial is total vaccine effect , counting cases only from a pre-specified window in which the immediate arm is assumed to be fully protected and the delayed arm is not protected . Simulation results are used to calculate necessary sample size and estimated vaccine effect . Under baseline assumptions about vaccine properties , monthly incidence in unvaccinated rings and trial design , a standard sample-size calculation neglecting dynamic effects estimated that 7 , 100 participants would be needed to achieve 80% power to detect a difference in attack rate between arms , while incorporating dynamic considerations in the model increased the estimate to 8 , 900 . This approach replaces assumptions about parameters at the ring level with assumptions about disease dynamics and vaccine characteristics at the individual level , so within this framework we were able to describe the sensitivity of the trial power and estimated effect to various parameters . We found that both of these quantities are sensitive to properties of the vaccine , to setting-specific parameters over which investigators have little control , and to parameters that are determined by the study design . Incorporating simulation into the trial design process can improve robustness of sample size calculations . For this specific trial design , vaccine effectiveness depends on properties of the ring vaccination design and on the measurement window , as well as the epidemiologic setting .
The West African Ebola epidemic highlighted the need to identify a range of trial designs to evaluate vaccine effects rapidly , efficiently and rigorously during emerging disease outbreaks . The ring-vaccination trial approach employed in the Ebola ça suffit trial in Guinea is one innovative approach [1] , which produced valuable evidence that the vaccine could prevent Ebola infection [2] . Other approaches considered include individual randomization and a stepped-wedge design [3 , 4] . In such trials it is difficult to estimate the likely effect of an infectious disease intervention because of indirect effects , and this issue is compounded by complex trial design . Sample size calculations are based on group-level quantities such as intervention effect and are therefore potentially inaccurate . By creating a transmission dynamic model for a ring vaccination trial , we show that we can make sample size calculations based on disease characteristics and individual intervention efficacy . With this framework in place we are then able to examine the estimated vaccine effect and sample size under a range of assumptions about the properties of the vaccine , the trial , and the study population . Although the only implementation of the ring trial design has been in Guinea during the Ebola epidemic , lessons can be learned and extended to other diseases and contexts . Here , we examine the tail end of an epidemic of a disease with a latent and asymptomatic phase with effective contact tracing to illustrate a more widely-applicable set of findings . In particular , we use baseline parameters values consistent with Ebola in West Africa in 2014–6 , but we vary several assumptions over broader ranges than those occurring in the Ebola ça suffit trial , with the aim of being relevant to a range of potential future situations .
The simulation is based on a stochastic , susceptible-exposed-infectious-detected-removed-vaccinated ( SEIDRV ) model for individual disease events , and it represents progression of the disease in a small cluster ( henceforth ‘ring’ ) with homogeneous mixing . The ring represents both contacts and contacts of contacts so the assumption of homogeneous mixing is a simplifying assumption , which we can relax by modelling ‘contacts’ and ‘contacts of contacts’ as separate compartments with the highest transmission among the contacts . New cases arise through direct contact between an infectious individual and a susceptible individual within the ring , and through external infectious pressure , denoted by F , which is constant and fixed for all members of the ring . Members of the ring undergo surveillance by the study team , meaning that infectious individuals are detected and isolated with a daily probability pH , ending their infectious period . We assume in the baseline scenario that detection rate in the trial is equivalent to routine surveillance , reflecting the fact that the trial doesn’t interrupt or enhance disease control efforts . If infectiousness ends naturally , individuals can no longer be detected . A ring is enrolled into the trial when a case is detected through routine surveillance . This first detected case is defined as the index case for the purposes of the trial , but may or may not be the true index case of the outbreak in the ring . Once a ring enters the trial all its members are randomly assigned to immediate vaccination ( on day 1 ) or delayed vaccination ( on day 22 ) . In the baseline scenario we assume no ineligibility or non-consent , so that all susceptible and exposed individuals in the ring are vaccinated , and that there is no heterogeneity or administrative delay affecting the day of vaccination . The mechanism of the vaccine in an individual is as follows: multiplicative leaky efficacy [5] increases linearly from 0 to VE ( set at baseline to be 0 . 7 ) over a period of Dramp days following vaccination , after which there is no change in efficacy over the study period [6] . Statistical analysis of the trial is based on cumulative incidence in the rings by end of follow-up and a 95% confidence interval is calculated and reported [7] . The required sample size to test a vaccine effect with 80% power is based on a difference in cumulative incidence [8] , using parameters output by a simulated trial with 15 , 000 rings . We chose this analysis method because of the existence of simple closed-form sample size and vaccine efficacy formulae . Because both arms receive the vaccine , cases that contribute towards the cumulative incidence in each arm are only counted during a window in which the immediate arm is presumed to be protected by the vaccine , and the delayed arm is not protected . The window length is set to 21 days , equal to the vaccination delay between the arms . Because the disease has an asymptomatic phase and the vaccine has a ramp-up period during which it is not fully efficacious , the window starts at 16 days , the sum of the average asymptomatic period length and Dramp , in an attempt to exclude cases in the immediate arm who were infected before they were fully protected by the vaccine . We did not explicitly implement clustering in the simulation , instead assuming that transmission dynamics in all rings are independent . However , clustering of cases within rings arises naturally due to dependent happenings . We measure this clustering using the intracluster correlation coefficient ( ICC ) , calculated as per Shoukri et al [9] , adjusting for the covariate of trial arm and accounting for variable ring size where appropriate . In conducting the statistical analysis we assume full knowledge of the vaccine mechanism , and that cases are only included if they are detected before their infectious period ends , and their symptoms appeared during the window . For additional details on the disease transmission model , ring initiation , and analysis of the trial see the supplementary appendix . Table 1 shows the parameters used in the model , their meanings , values under baseline assumptions , and references or justifications . In order to align this model with the presumed context of the Ebola ça suffit trial , we modelled an entirely susceptible study population at the end of an epidemic , so that Reff has fallen to below one due to behaviour change . To calibrate the model , we set Reff to reproduce a monthly detected attack rate of 2% when starting from one infected individual in a ring of 50 unvaccinated susceptible individuals , in the presence of case detection at a rate pBH .
Under baseline parameters in this model , the median total vaccine effect calculated from performing 100 trials with 89 rings in each arm was 70% . This value should include direct and indirect effects , so we would expect it to exceed the direct effect of 70% . However , while direct effects begin immediately , indirect effects are only important in the second generation of preventable cases onwards . There are cases in this generation that occur in the case-counting window because Reff is small and the window duration is not much longer than a typical disease generation ( 17 days ) , so the indirect effects are small . Fig 1 shows the effect of six variables on the point estimate of vaccine effect: daily probability of detection , true individual vaccine efficacy , proportion of infections from outside the ring , baseline attack rate in the unvaccinated population , administrative delay in vaccination , and start day of case-counting window . Firstly , if there is enhanced surveillance in both arms of the trial leading to more rapid isolation of infectious cases ( pH>pBH ) , this will modestly reduce effectiveness estimates ( Fig 1A ) . Secondly , as individual vaccine efficacy properties increase the estimated vaccine effect increases ( Figs 1B and S1 ) . Thirdly , the percentage of infections from within the ring shows a weak negative association with the estimate of vaccine effect ( Fig 1C ) . While the magnitude of indirect effects is modest as discussed above , they are almost negligible when most infections are from outside the ring , because preventing infections within the ring does not confer as much protection to susceptible individuals . The increase in vaccine effect with higher attack rate seen in Fig 1D is driven by the increase in indirect vaccine effects in the immediate arm . Finally , delay between ring formation and vaccination means that by the beginning of the time window the vaccine has had less time to prevent cases in the immediate arm . Thus the reduction in incidence in the immediate arm does not reflect the true effect of the vaccine and the vaccine effect estimate is reduced ( Fig 1E ) . A major determinant of the effect estimate is the choice of time window in which to count cases , as seen in Fig 1F . Not surprisingly , starting the window too early reduces the estimated effects because it includes a period of time during which the vaccine cannot affect the incidence of cases becoming symptomatic–many cases becoming symptomatic on day 8 , for example , will have been infected by the index case prior to isolation , or will have been infected by a contact on ( say ) day 3 , before the vaccine had time to induce protection . Starting the window later than the baseline of 16 days allows the trial to capture later generations in the chain of transmission , from a vaccinated person to another vaccinated person . This increases the vaccine effect estimate as it includes indirect effects . One might expect to see that starting the window too late would reduce effect estimates because it would include a period when the delayed group was also protected by the vaccine . This does not appear to be the case , at least up to a start time of 35 days ( Fig 1F ) –see the supplementary material for an explanation of this phenomenon . Fig 2 shows the effect of the same six variables on the required sample size: baseline attack rate in unvaccinated population , start day of case-counting window , daily probability of detection , true individual vaccine efficacy , administrative delay in vaccination , and force of external infection . The effect of each parameter on the sample size can be understood through its effect on one or more of the three factors that determine the power of this trial: the number of events , how they are distributed between the two arms , and the level of clustering of cases within rings . Respectively these factors are represented by the attack rate in the controls , the cumulative incidence difference between the arms , and the intracluster correlation coefficient ( ICC ) [8] . Variables that decrease the incidence rate in the controls and cases will decrease the power because for the same sample size the trial will observe fewer events . The baseline detected attack rate among unvaccinated individuals is a simple example of such a parameter ( Fig 2A ) . Two other parameters act on the overall incidence in the trial . Firstly , making the start of the case-counting window later decreases incidence in both arms because with Reff<1 the incidence is on average declining , so across all rings in the trial the number of cases decreases over the follow-up period ( Fig 2B ) . Secondly , the case detection decreases detected incidence rate at both extremes ( Fig 2C ) . When case detection is high , transmission chains are interrupted by case isolation and the true incidence decreases . When case detection is low , many cases die or recover before they can be detected and consequently the detected incidence decreases . Variables that make the two arms of the trial appear more different will increase the power of the trial as the ability to differentiate between them is increased , and Fig 1 identifies such variables . Vaccine characteristics , in particular vaccine efficacy ( Fig 2D ) , are simple examples of such a parameter , since the immediate arm receives greater protection against disease compared to the delayed arm . Changes to two other parameters increase the incidence difference in this way , as explained above: reducing the delay between ring formation and vaccination ( Fig 2E ) and starting the case-counting window earlier ( Fig 2B ) . The effect of the timing of starting to count cases thus reflects two opposing forces on the sample size: it decreases sample size by increasing the incidence difference , and it increases sample size by decreasing the overall incidence . When the window is early , the former of these effects dominates as seen by the increase in sample size for early time windows in Fig 2B . When the window is late , the latter effect dominates , as seen by the increase in sample size for late time windows in the same figure . Finally , the level of clustering within rings inflates the sample size , because more clustering means that each individual case provides less information . It is often not intuitive to predict the direction in which a parameter will cause the ICC to change , and in many cases the ICC is not sensitive to the parameter . One exception is the infection from outside the ring ( Fig 2F ) . The most significant effect of introducing external infection and reducing within-ring transmission is to make infection probability for one individual within a ring independent from the infection prevalence within the same ring . This reduces clustering in incidence ( making it more Poisson-like ) , thus reducing the ICC and the necessary sample size . The width of the confidence intervals is affected in the same way by the three variables described above . In particular , low incidence in either arm , high ICC and a small incidence difference between the arms all lead to a wider confidence interval . The formula for the confidence interval is different from the formula used to make the power calculation , so the trends do not completely align because the size of the effect of each of the three factors is different for the confidence interval and the sample size . For an investigation of the sensitivity of the total vaccine effect estimate and sample size to other parameters in the model , see the supplementary material . For an interactive tool to explore the sensitivity of the trial parameters , see https://matthitchings . shinyapps . io/ShinyApps/ .
The ring-vaccination , cluster-randomized design has two key strengths that make it a good candidate when disease transmission exhibits spatiotemporal variation . Firstly , by including members of the study population who are contacts of cases , the trial preferentially selects those at higher risk of disease acquisition , leading to an increase in efficiency while preserving false-positive rate through randomization . Indeed , when a vaccine with 0% efficacy was tested in our simulations the false positive rate was maintained at 5% . Secondly , even those study subjects who are randomized to delayed vaccination are theoretically in close contact with the study team meaning that individuals from the source population who are at the highest risk are followed closely and benefit from the trial even in the absence of vaccination [12] . In addition , vaccination of clusters when they arise allows for gradual inclusion , meaning that this design is appropriate when logistical constraints make immediate vaccination of all participants impossible or inappropriate . In this respect it is similar to a stepped-wedge cluster trial , in which prespecified clusters within the study population are vaccinated in a random order . Although we have not made a direct comparison in this study , Bellan et al [13] showed that the stepped-wedge design is underpowered when the incidence is declining because it cannot prioritize the vaccine for those at highest risk . The ring vaccination design , on the other hand , is inherently risk-prioritized because all study participants should be at higher risk than the general population . All trials should be correctly powered in order to avoid erroneous rejection of an efficacious vaccine . For a trial design with several complexities such as the one presented here , a sophisticated approach to sample size calculation is merited . A standard approach to sample size calculation for this trial would involve specifying the attack rate among the controls , the desired effect of the vaccine on the population level , and the ICC . In the context of a serious epidemic , these parameters are unlikely to be estimated with certainty; for example , the ICC requires cluster-level data to be estimated accurately . The ICC is an important parameter in designing cluster-randomized trials , yet in the absence of data it is often assumed to be 0 . 05 . In our simulations the range of ICCs observed was 0 . 01–0 . 04 , suggesting that the value of this uncertain parameter should not always be assumed to be fixed at 0 . 05 . Therefore , the modelling approach replaces assumptions about these cluster-level quantities with assumptions about population-level parameters and disease characteristics , which are more likely to be available through analysis of data from the outbreak . A second advantage of the modelling approach is that , based as it is on a simulating the transmission of disease within a trial , it is possible to explore the impact of parameters describing the design of the trial and the properties of the disease . The added detail gained from specifying the disease model allowed us in this study to identify some key issues with the design that are worth considering . Firstly , as seen in Fig 2C , increasing case-finding efficiency above background rate has a negative impact on power , as fast isolation of cases in both arms leads to an overall decrease in cases observed by the trial . In future trials it is worth considering if there are alternative or composite endpoints , if the disease in question permits , that can be used to allow for efficacy estimates while maintaining close follow-up . Secondly , a key design consideration in the delayed-arm ring-vaccination trial is when to count cases . An intuitively appealing approach is to place the window so that the immediate arm is receiving full protection and the delayed arm none . This should in theory minimize bias caused by misclassification of unvaccinated individuals as vaccinated and vice-versa . While this placement achieves nearly maximal power , it does not maximize the VE estimate . Indirect effects that are important later in time increase the VE estimate for later time windows , while at the same time declining incidence within each ring decreases power for later time windows . Finally , the above point draws attention to the fact that caution is required when interpreting the VE estimate produced by the trial . As seen in Fig 1 , many parameters that are not characteristics of the vaccine can influence the estimated effect . Whether this is due to misclassification ( for example , when the time window is too early ) or due to indirect effects ( for example , when the attack rate is high enough to cause long transmission chains ) , the context of the trial should be taken into account when interpreting the VE estimate . While in the baseline scenario the trial appears to correctly estimate the individual efficacy , this is the result of misclassification and indirect effects cancelling each other out . This claim is supported by the fact that the median VE estimate falls below the individual-level vaccine efficacy when most or all infections are from outside the ring ( Fig 1C ) and indirect effects are negligible . The focus of this model was to explore parameters within each ring and understand how they affect the quality of data coming from the trial . As a result , we did not consider the wider context of the population disease dynamics , and in particular how and when the rings arise . For example , we calibrated Reff to a secondary attack rate in a cluster was 2% , which is not necessarily comparable to the monthly cumulative incidence in the population . If transmission takes place mainly in clusters then population cumulative incidence could be somewhat lower than cluster secondary attack rate , increasing the efficiency of a ring-vaccination trial relative to a stepped-wedge cluster trial or individual RCT . Linking this model to a model of disease within the general population would allow us to make direct comparisons to other trial designs such as the stepped-wedge cluster trial and the individually-randomized trial investigated elsewhere [13 , 14] , but it would require detailed information about the nature of clustering of the disease in this context , and for simplicity we focused on the within-ring dynamics only . As with every model , there are limitations to these simulation results . The strength of the modelling approach compared with a standard approach is that it better estimates the parameters on which the sample size depends . However , some of the model parameters might still be uncertain in a situation in which such a model might be useful . For example , we may have limited information about the characteristics of a disease , in particular its latent and incubation period , and its Reff . The simulation results are dependent on these assumptions , and so they cannot be used at the very outset of epidemic , or else they risk being highly inaccurate . Even at the end of the West African Ebola epidemic , there were no more than four or five reliable estimates of the latent and infectious periods of EVD , and indeed there is perhaps evidence that our understanding of the natural history of the disease remains limited [15] . In addition , we have considered only the simplest method of analysis for the trial–a comparison of attack rates between the two arms after correction for clustering of cases within rings . More sophisticated methods , including time-to-event analyses incorporating ring-level random effects , as performed in the Ebola ça suffit trial , would have somewhat different sample size requirements . However , we believe that the trends seen here would be similar for other methods , because the VE estimates returned by various methods will be similar for a rare outcome [5] . In building the model we made some simplifying assumptions , and although we tested the robustness of the results to these assumptions ( see supplementary material ) it is possible that a more sophisticated model would provide more accurate results , particularly if superspreading events are not rare in this study population . For a vaccine trial in an epidemic , when the level of indirect effects is hard to predict , power calculations can be sensitive to parameters about which very little is known . Simulations such as these can be important aids in understanding a range of values for these parameters before a trial is carried out , and thus ensuring that the trial has sufficient power to detect an efficacious vaccine . In this trial , a finding significantly different from the null likely indicates one or more types of vaccine efficacy at the individual level , but the magnitude of the effect and the power to detect the effect will vary across settings .
|
The urgency , as well as the logistical and sometimes ethical challenges of clinical trials for interventions during epidemics of emerging diseases prompts the need for novel designs and analytic strategies . The successful use of a novel cluster-randomized ring-vaccination trial to test an Ebola vaccine in Guinea raises the general question of what circumstances would favour the use of trials of similar design and how the properties of the population , the vaccine and the trial would influence the necessary sample size and the expected results . We present a generalized transmission dynamic model for a ring vaccination trial to address these questions . This work is an example of the general phenomenon that mechanistic , transmission-dynamic simulations can aid in the design and interpretation of intervention trials for infectious diseases , when the trial itself can have non-obvious effects on transmission dynamics that may not be fully captured by effect- and sample-size calculations for noncommunicable diseases .
|
[
"Abstract",
"Introduction",
"Methods",
"Results",
"Discussion"
] |
[
"medicine",
"and",
"health",
"sciences",
"infectious",
"disease",
"epidemiology",
"immunology",
"tropical",
"diseases",
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2017
|
Using simulation to aid trial design: Ring-vaccination trials
|
Aberrant protein modifications play an important role in the pathophysiology of many human diseases , in terms of both dysfunction of physiological modifications and the formation of pathological modifications by reaction of proteins with endogenous electrophiles . Recent studies have identified a chemical homolog of lysine acetylation , N6-formyllysine , as an abundant modification of histone and chromatin proteins , one possible source of which is the reaction of lysine with 3′-formylphosphate residues from DNA oxidation . Using a new liquid chromatography-coupled to tandem mass spectrometry method to quantify all N6-methyl- , -acetyl- and -formyl-lysine modifications , we now report that endogenous formaldehyde is a major source of N6-formyllysine and that this adduct is widespread among cellular proteins in all compartments . N6-formyllysine was evenly distributed among different classes of histone proteins from human TK6 cells at 1–4 modifications per 104 lysines , which contrasted strongly with lysine acetylation and mono- , di- , and tri-methylation levels of 1 . 5-380 , 5-870 , 0-1400 , and 0-390 per 104 lysines , respectively . While isotope labeling studies revealed that lysine demethylation is not a source of N6-formyllysine in histones , formaldehyde exposure was observed to cause a dose-dependent increase in N6-formyllysine , with use of [13C , 2H2]-formaldehyde revealing unchanged levels of adducts derived from endogenous sources . Inhibitors of class I and class II histone deacetylases did not affect the levels of N6-formyllysine in TK6 cells , and the class III histone deacetylase , SIRT1 , had minimal activity ( <10% ) with a peptide substrate containing the formyl adduct . These data suggest that N6-formyllysine is refractory to removal by histone deacetylases , which supports the idea that this abundant protein modification could interfere with normal regulation of gene expression if it arises at conserved sites of physiological protein secondary modification .
In addition to physiological secondary modifications , proteins are subjected to reactions with endogenous electrophiles generated by oxidative stress , inflammation , and normal cell metabolic processes [1]–[5] . These adventitious or pathological modifications typically arise by reaction of the nucleophilic side chains of lysine , histidine , and cysteine with reactive electrophiles such as malondialdehyde , 4-hydroxynonenal ( HNE ) , and glyoxal generated by oxidation of polyunsaturated fatty acids and carbohydrates , among other biomolecules [2]–[4] , [6] , [7] . The resulting adducts , which can alter protein function and lead to protein degradation , are associated with a variety of pathological processes and human diseases [1]–[5] , [8] . Among these pathological adducts , N6-formylation of lysine has recently emerged as an abundant protein modification [5] , [9]–[11] . While originally described in chromatin proteins [9]–[11] , it has since been identified as an adduct arising in proteins subjected to nitrosative and oxidative stresses [5] . In chromatin proteins , N6-formyllysine has the potential to interfere with the functions of other post-translational modifications that perform signaling functions [12]–[15] , such as acetylation , methylation , phosphorylation , ubiquitylation , and ADP ribosylation , with some locations modified in more than one way ( e . g . , refs . [16]–[18] ) . The chemical similarities of N6-formyllysine and N6-acetyllysine suggest a disruptive role for the former in signaling by histone acetylation . Indeed , N6-formyllysine has been detected at conserved sites of lysine acetylation and methylation in histones [10] , [11] . While N6-formyllysine adducts are now well recognized as abundant protein modifications in cells , the source of these pathological adducts remains unclear . We recently showed that some portion of N6-formyllysine arises in chromatin proteins by reaction of lysine side chains with the 3′-formylphosphate residue derived from 5′-oxidation of 2-deoxyribose in DNA in cells ( Figure 1 ) [9] . However , the observation of this adduct in proteins treated with the biological oxidant , peroxynitrite , suggests other sources for the formyl species [5] . Considering that formaldehyde reacts with amines to give a carbinolamine intermediate that is only one oxidation state away from a formamide functional group ( Figure 1 ) , we hypothesized that endogenous formaldehyde could serve as a source of N6-formyllysine residues in histone and other proteins . In addition to environmental and occupational sources [19]–[21] , formaldehyde arises from cellular processes such as oxidative demethylation of nucleic acid and histone proteins , as well as biosynthesis of purines , thymidine , and some amino acids [20] , [22] , [23] , making it a relatively abundant metabolite at concentrations ranging from 13 to 97 µM in human plasma [20] . To test this hypothesis and to clarify the cellular locations and quantities of N6-formyllysine relative to other major histone modifications , we developed a novel liquid chromatography-coupled electrospray tandem mass spectrometry ( LC-MS/MS ) method to quantify all N6-methyl- , -acetyl- , and -formyl-lysine modifications . Application of this method reveals that endogenous formaldehyde is a major source of N6-formyllysine , that this adduct is widespread among proteins in all cellular compartments , and that , in chromatin proteins , it is refractory to removal by histone deacetylases .
Our previous method for quantifying N6-formyllysine in proteins involved proteinase K-mediated hydrolysis of proteins , derivatization of the resulting amino acids with phenylisothiocyanate ( PITC ) , HPLC pre-purification of amino acid derivatives , and final LC-MS/MS analysis of the derivatized amino acids [9] . This method proved to be relatively insensitive and biased as a result of using proteinase K , which produced only partial hydrolysis of some proteins when used in small quantities to minimize background autolysis . To resolve these problems , we used Streptomyces griseus protease at ratio of 1 µg enzyme per 10 µg proteins , which resulted in efficient and complete digestion of all proteins as judged by comparing the measured amount of lysine released per µg of purified histone proteins to the theoretical lysine content of the proteins . In addition , the method was optimized to eliminate HPLC pre-purification step , and the need for PITC derivatization to achieve chromatographic resolution of amino acids was obviated by use of aqueous normal phase HPLC with a diamond-hydride column . This chromatographic system resolved N6-acetyllysine , mono- , di- , and tri-N6-methyllysines , as well as N6-formyllysine and lysine , as shown in Figure 2 . With isotopically labeled internal standards added prior to protease digestion , identification and quantification of amino acids were accomplished by HPLC-coupled to tandem quadrupole mass spectrometry in positive ion mode , using multiple reaction monitoring ( MRM ) transitions . With a 2% precision for technical replicates , the limits of detection were found to be 1 fmol for N6-formyl- and N6-acetyllysine , 10 fmol for lysine , and 50 fmol for each of N6-mono- , di- , and tri-methyl lysine . Data for the various lysine modifications are expressed here as proportions of the total number of lysines in the sample . To validate the new analytical method for lysine modifications , we compared the frequency of N6-formyllysine among different classes of histone proteins extracted from TK6 cells and resolved by reversed-phase HPLC . As shown in Figure S1A , all of the major histone classes were separated , with further resolution of variant forms of histones H1 and H3 ( SDS-PAGE verification in Figure S1B ) , which is consistent with previous observations in cultured human cells [10] . N6-Formyllysine was detected in all histone classes at a frequency of 1–4 modifications per 104 lysines . This 3- to 4-fold variation among histone classes stands in contrast to the 10- to 100-fold variation in the frequency of other modifications ( Table 1 ) . The data in Table 1 represent the first absolute quantification of the various lysine acetyl and methyl modifications in histone proteins , and are consistent with published studies of relative quantities of histone modifications using immunologic and radiolabeling techniques [10] , [24]–[26] . Histone modification-based signaling involves the location and number of specific modification targets within a histone protein , as well as the frequency of modification of a target among all copies of a particular histone protein . Our data provide some insight into this issue . For example , we observed low-level acetylation and methylation in histone H1 , which is consistent with studies using radiolabeled acetate [24] , while this low level of modification maps to specific sites in the globular domain and N-terminal tail of histone H1 [10] . This low-level of acetylation and methylation in histone H1 stands in contrast to the high level of acetylation of H2 , H3 and H4 ( Table 1 ) , which is again supported by studies using radiolabeled acetate [24] . The new analytical method was next applied to quantify N6-formyllysine in non-histone proteins . We had previously observed N6-formyllysine mainly in histone proteins [9] , perhaps as a result of biased proteolysis or subsequent steps in the technique . However , using the new method , we are now able to detect N6-formyllysine modifications in a variety of different proteins , as shown in Table 2 . Further , an analysis of proteins in nuclear , cytosolic , and membrane compartments in bovine liver revealed the presence of N6-formyllysine in all three locations ( Table 2 ) . These observations are consistent with a source for N6-formyllysine other than the 3′-formylphosphate residues of DNA oxidation previously identified for histone proteins [9] . One alternative to 3′-formylphosphate residues as a source of N6-formyllysine is oxidation of the carbinolamine intermediate in the reaction of formaldehyde with side chain amine of lysine ( Figure 1; N6- ( hydroxymethyl ) -lysine ) . To test this hypothesis , we performed a series of experiments , starting with an in vitro reaction of L-lysine with different concentrations of formaldehyde and quantification of N6-formyllysine . As shown in Figure 3A , there was a concentration-dependent formation of N6-formyllysine in reactions with formaldehyde , presumably as a result of oxidation of the carbinolamine adduct by the background of reactive oxygen species generated by trace metals and dissolved oxygen in the solution . The oxygen dependence of formaldehyde-induced N6-formyllysine was verified by bubbling 100% oxygen ( 4 h ) into the solution of 1 mM lysine and 10 mM formaldehyde , which caused a 2 . 2 ( ±0 . 4 ) -fold increase in the level of N6-formyllysine after 12 h of incubation at 37°C . The dose-response relationship for formaldehyde-induced N6-formyllysine formation was also observed in histone proteins extracted from TK6 cells exposed to formaldehyde for 2 h at 37°C ( Figure 3B ) , with 10 mM formaldehyde producing roughly the same fold-change of N6-formyllysine in both in vitro and cellular studies . The relatively high endogenous levels of N6-formyllysine in histone and other proteins ( Table 1 and Table 2 ) raised the question of the contribution of exogenous formaldehyde exposures to the total load of N6-formyllysine in the cells . To address this issue , we exposed TK6 cells to [13C , 2H2]-labeled formaldehyde , which led to the formation of N6-[13C , 2H]-formyllysine that is 2 mass units heavier than the endogenous adducts ( Figure 4A ) . Following extraction of the histone proteins from formaldehyde-treated TK6 cells ( 2 h , 37°C ) , both endogenous and exogenous N6-formyllysine were quantified by monitoring the transitions m/z 175→112 and m/z 177→114 , respectively ( Figure 4A ) , with a third transition ( m/z 179→116 ) for the 4 , 4 , 5 , 5-[2H]-N6-formyllysine internal standard . As shown in Figure 4B , levels of endogenous ( unlabeled ) N6-formyllysine remained constant at all concentrations of [13C , 2H2]-formaldehyde , while N6-[13C , 2H]-formyllysine increased as a function of the concentration of labeled formaldehyde . The enzymatic demethylation of N6-methyllysine modifications represents another possible source of N6-formyllysine in histone proteins , given both the carbinolamine intermediate known to form during the process of lysine demethylation and the ultimate release of the methyl group as formaldehyde [23] . Adventitious oxidation of the carbinolamine intermediate or secondary reaction of the released formaldehyde could result in the formation of N6-formyllysine locally . To test these hypotheses , TK6 cells were grown in customized RPMI medium containing L-methionine with a [13C , 2H3]-methyl group for 20 days to label all methyl groups in N6-methyllysine species , and histone proteins were extracted for analysis every 2 days . If N6-formyllysine is a product of disrupted lysine demethylation in histones and is formed via oxidation of the carbinolamine intermediate known to form during the process of lysine demethylation [23] , or by reaction of lysine with the formaldehyde released at the last step of successful lysine demethylation [23] , then one would expect to see an increase of 2 mass units corresponding to formation of N6-[13C , 2H]-formyllysine ( m/z 177→114 transition ) . In order to increase the signal-to-noise ratio for N6-[13C , 2H]-formyllysine , N6-formyllysine was HPLC-pre-purified in all samples before LC-MS/MS analysis . Figure 5 depicts an example of the analysis using the day 6 sample . As shown in Figure 5 , N6-mono-methyllysine and N6-di-methyllysine are predominately labeled ( >90% ) with heavy isotope methyl groups ( i . e . , [13C , 2H3]-methyl ) . In contrast to methyllysines , the level of N6-[13C , 2H]-formyllysine did not increase beyond the natural isotope abundance level of ∼0 . 7% for the [M+2] ion of N6-formyllysine ( Figure 5C and Figure S2 ) . Note that the HPLC gradient was changed here to fully resolve a contaminant signal from the TK6 cells ( identified as the [M+1] ion of citrulline ) that otherwise co-eluted with N6-formyllysine and produced an m/z value similar to the [M+2] isotopomer of N6-formyllysine . The chemical similarity of N6-formyllysine and N6-acetyllysine suggested that the former might be subject to removal by lysine deacetylases that recognize and remove N6-acetyllysine from histone and other proteins [16] , [27]–[30] . Lysine deacetylases fall into several classes , including classes I and II that share a common hydrolytic mechanism and are all inhibited by suberoylanilidehydroxamic acid ( SAHA ) , and the class III enzymes ( i . e . , sirtuins ) that are NAD+-dependent deacetylases [31] , [32] . In order to assess the activity of lysine deacetylases with N6-formyllysine substrates , TK6 cells were treated with SAHA and the levels of N6-acetyllysine and N6-formyllysine were quantified . The results shown in Figure 6A reveal that , while SAHA caused a 3-fold increase in the level of N6-acetyllysine ( 4 to 14 per 103 lysines ) , lysine formylation was not affected . To assess sirtuin activity against N6-formyllysine , we performed in vitro reactions of SIRT1 with a consensus peptide ( GGAKRHR ) containing N6-formyllysine or N6-acetyllysine , and the quantities of the modified and unmodified peptides were analyzed by LC-MS/MS . As shown in Figure 6B , SIRT1 removed the acetyl modification completely to generate the unmodified peptide , while only ∼10% ( ±4% ) of N6-formyllysine was removed .
N6-Formyllysine was first reported in 1985 in reactions of lysine with formaldehyde in vitro [33] and , more recently , it was shown to form during in vitro silver-staining procedures that involve the use of formaldehyde [34] . The recent discovery of N6-formyllysine as a relatively abundant endogenous posttranslational modification of histones and other nuclear proteins in cells [9]–[11] has raised questions about its mechanism of formation and its potential for interfering with the regulatory function of lysine N6-acetylation . With respect to formation , we previously presented evidence that N6-formyllysine in histones could arise from reactions with 3′-formylphosphate residues derived from DNA oxidation [9] . However , formaldehyde emerged as an alternative source given the high reactivity of formaldehyde toward primary amines , such as the side chain of lysine , and the potential for endogenous oxidation to convert a formaldehyde-derived carbinolamine to a stable formamide ( Figure 1 ) . We have now demonstrated in vitro and in cells that formaldehyde exposure leads to formation of N6-formyllysine residues in proteins . The fact that this modification arises in proteins other than chromatin proteins and in cellular compartments other than the nucleus ( Table 2 ) suggests that 3′-formylphosphate residues in oxidized DNA do not account for all N6-formyllysine adducts . This is consistent with recent studies in which N6-formyllysine was detected in a protein oxidized with peroxynitrite in vitro [5] . The absence of detectable N6-formyllysine arising from demethylation of N6-methyllysine species ( Figure 5C and Figure S2 ) suggests that interruption of histone demethylation reactions to form the carbinolamine precursor of N6-formyllysine occurs at low frequency , or that the formaldehyde produced by complete lysine demethylation [23] does not occur at concentrations high enough to drive formylation of lysine or cause substantial changes in N6-formyllysine levels detected by our current analytical method . Furthermore , there is the possibility that the formaldehyde released during lysine demethylation may be scavenged before it could react with lysines in histones . A recent study reports that lysine-specific demethylase 1 ( LSD1 ) is a folate binding protein [35] , which led the authors to hypothesize that the biological function of folate is to trap the formaldehyde that is generated during lysine demethylation [35] . In addition , the observation that the formaldehyde equivalent derived from histone demethylation might not account for a significant portion of formyllysine residues is not surprising in light of the abundance of formaldehyde from other cellular processes , such as nucleic acid demethylation and biosynthesis of purines , thymidine and some amino acids [20] , [22] , [23] . This is clear from the high steady-state concentrations of formaldehyde in human plasma ( 13–97 µM ) [20] , though the contribution of long-term , low-level exposure from environmental sources of formaldehyde cannot be ruled out . The relative abundance of N6-formyllysine in histone and other proteins ( Table 1 and Table 2 ) [9]–[11] and the persistence of these adducts in histone proteins provides insights into both their source and their potential effects on cell function . The N6-formyllysine residues are relatively evenly distributed among different classes of histone proteins ( Table 1 ) , while the other functional modifications show very biased distributions over a large frequency range , which is consistent with the known function and conserved locations for lysine methylation and acetylation [16]–[18] . This random distribution of formyllysine adducts in histone proteins suggests that they are adventitious and not physiological . The fact that N6-formyllysine levels are similar in histone and non-nuclear proteins and in all cell compartments also suggests that the sources of this protein modification are equally balanced in the various compartments and proteins , or that there is a single dominant source that distributes uniformly throughout the cell . With regard to its persistence in cells , there is still no evidence supporting the enzymatic removal of N6-formyllysine . Our investigation reveals that N6-formyllysine adducts appear to be refractory to removal by histone deacetylase enzymes , which suggests that they will persist throughout the lifetime of individual histone proteins . Although our results are consistent with lysine N6-formylation as a stable protein modification , we cannot rule out the possibility of an enzyme that removes this modification from selected conserved lysine sites in histone proteins , resulting in small changes in the population level of formyllysine that are not detectable by our current analytical method . Figure 7 summarizes our findings presented here on N6-formyllysine adducts . The high abundance of lysine N6-formylation in histone proteins ( Table 1 ) as well as its occurrence at many of the known conserved functional locations for lysine acetylation and methylation in histones [10] , [11] suggests that N6-formyllysine could interfere with signaling processes associated with physiological histone modifications [16] , [27] . Mann and co-workers found formylation of core and linker histones at multiple lysines in both the N- and C-terminal tails and in the globular domains [10] , which is consistent with our observation of a random distribution of N6-formyllysines among the different histone classes . Several of the formylated lysines occurred at functionally important sites . For example , the observed N6-formylation of lysine 12 in histone H4 could interfere with BRD2 bromodomain-dependent transcriptional activation that occurs when the lysine is acetylated [10] . Furthermore , formylation was observed at several lysines known to make contact with the DNA backbone in nucleosomes , which could interfere with nucleosome organization given the conserved acetylation and methylation at these sites [10] . Our observation that N6-formyllysine is refractory to removal by several histone deacetylases suggests that the adducts could interfere with the epigenetic regulatory processes mediated by acetylation and methylation . While this potential epigenetic mechanism of disruption of cell function may contribute to the toxicity and carcinogenicity associated with formaldehyde [20] , [36]–[40] , the association of N6-formyllysine with a variety of different cell and organismal processes , including metabolism and the oxidative and nitrosative stresses of inflammation [5] , [9] , suggests that this adduct may play a role in many pathophysiological processes in humans .
Unlabeled and [13C , 2H2]-labeled formaldehyde were purchased as 37% and 20% aqueous solutions from Amresco ( Solon , OH ) and Isotec ( Miamisburg , OH ) , respectively . 4 , 4 , 5 , 5-[2H]-Lysine was purchased from Cambridge Isotope Laboratories ( Andover , MA ) . 4 , 4 , 5 , 5-[2H]-N6-Formyllysine was synthesized from 4 , 4 , 5 , 5-[2H]-lysine according to Jiang et al . [9] . 3 , 3 , 4 , 4 , 5 , 5 , 6 , 6-[2H]-N6-Acetyllysine were obtained from CDN Isotopes ( Pointe-Claire , Quebec , Canada ) . L-Methionine- ( [13C , 2H3]-methyl ) was obtained from Isotec ( Miamisburg , OH ) . L-Lysine , N6-formyllysine , N6-acetyllysine , bovine serum albumin , human recombinant HMG-1 , human IgG , Streptomyces griseus protease , and protease inhibitor cocktail ( for use with mammalian cell and tissue extracts ) were obtained from Sigma-Aldrich ( St . Louis , MO ) . N6-Mono-methyllysine , N6-di-methyllysine , and N6-tri-methyllysine were purchased from Bachem Bioscience Inc . ( King of Prussia , PA ) . Nonidet P-40 was from Roche Diagnostic Corporation ( Indianapolis , IN ) . Suberoylanilidehydroxamic acid ( SAHA ) and SIRT1 ( human recombinant ) enzyme were purchased from Cayman chemical ( Ann Arbor , MI ) . Peptide substrates for SIRT1 ( GGAKRHR and its lysine-acetylated and -formylated forms ) were synthesized at Massachusetts Institute of Technology Biopolymers Laboratory . The human lymphoblastoid TK6 cell line was a generous gift of Prof . Gerald Wogan ( Massachusetts Institute of Technology ) . TK6 cells were cultured in RPMI 1640 medium ( Cellgro , Manassas , VA ) supplemented with 10% heat-inactivated horse serum ( Atlanta Biologicals , Lawrenceville , GA ) , 10 , 000 U penicillin/ml and 10 , 000 µg streptomycin/ml ( Lonza , Walkersville , MD ) , and 2 mM L-glutamine ( Lonza , Walkersville , MD ) at 37°C in a 5% CO2 atmosphere . For formaldehyde exposure studies , TK6 cells were pelleted , washed , and resuspended in RPMI 1640 medium without any supplements , prior to addition of formaldehyde to the medium . Following addition of formaldehyde , cells were incubated at 37°C for 2 h with occasional mixing prior to extracting chromatin proteins . Histones were extracted from ∼107 cells after exposure and the quantity of formyllysine , as a percentage of total lysine , was measured as described below . For lysine demethylation studies , TK6 cells were grown in a customized RPMI-1640 medium identical to the traditional medium ( e . g . , supplemented with horse serum , antibiotics , and L-glutamine ) , except for the presence of labeled methionine ( L-methionine- ( [13C , 2H3]-methyl ) ) instead of non-labeled methionine . Histones ( from ∼107 cells ) were extracted every 2 d for 20 d in order to investigate the formation of N6-[13C , 2H]-formyllysine . For histone deacetylase studies , TK6 cells were incubated with the histone deacetylase inhibitor , suberoylanilidehydroxamic acid ( SAHA ) , for 20 h at 37°C in a 5% CO2 atmosphere prior to histone extraction . SAHA was dissolved in a 50∶50 solution of DMSO∶PBS prior to addition to cell media . Control cells ( ∼107 ) were treated with the DMSO∶PBS vehicle . Extraction of histones was performed according to Boyne et al . [41] , with modifications . Cells ( ∼107 per sample ) were pelleted by centrifugation at 1000× g for 5 min at 4°C and the pellet was washed once with PBS . Cell pellets were then lysed by resuspension in ice-cold lysis buffer ( 15 mM Tris-HCl , pH 7 . 5 , 15 mM NaCl , 60 mM KCl , 1 mM CaCl2 , 5 mM MgCl2 , 250 mM sucrose , 1 mM dithiothreitol , 10 mM sodium butyrate ) containing a 100∶1 v∶v dilution of protease inhibitor cocktail in the presence of 0 . 03% Nonidet P-40 and incubation on ice for 5 min with occasional gentle mixing . Nuclei were pelleted by centrifugation at 600× g for 5 min at 4°C , and the pellet was washed twice with ice-cold lysis buffer without Nonidet P-40 . Histones were extracted by addition of ice-cold 0 . 4 N H2SO4 and incubation overnight on ice . The solution was centrifuged at 3000× g for 5 min and proteins in supernatant were precipitated by addition of 20% v/v trichloroacetic acid and overnight incubation at 4°C . Samples were then centrifuged at 14000× g for 10 min at 4°C , washed once with ice-cold acetone containing 0 . 1% HCl , and once with ice-cold acetone . The extracts were air-dried and stored at −20°C until use . For collecting membrane , cytosolic , and nuclear fractions , 20 mg of bovine liver tissue was cut into small pieces and washed with PBS , and proteins were fractionated using the Subcellular Protein Fractionation Kit from Thermo Scientific ( Waltham , MA ) and a Kontes all-glass Dounce homogenizer ( 10 strokes with a type B pestle ) . Proteins in subcellular extracts were precipitated by addition of 20% v/v trichloroacetic acid and overnight incubation at 4°C . Samples were then centrifuged at 14000× g for 10 min at 4°C , washed once with ice-cold acetone containing 0 . 1% HCl , and once with ice-cold acetone . The extracts were air-dried and stored at −20°C until use . HPLC purification of total histones was performed according to Boyne et al . [41] with modifications . Total histones ( ≤50 µg ) were dissolved in 0 . 1% trifluoroacetic acid ( TFA ) in water and fractionated by HPLC on an Agilent 1100 series instrument ( Agilent Technologies , Santa Clara , CA ) , using a Source 5RPC C18 reversed-phase column ( 4 . 6×150 mm , 5 µm particles; GE Healthcare Life Sciences ) . The mobile phase flow rate was 1 mL/min and the solvent system was 0 . 1% TFA in water ( A ) and 0 . 094% TFA in acetonitrile ( B ) with the elution starting at 0% B , linearly increasing to 28% B over 28 min , reaching 37% B at 70 min , 38% B at 100 min , 60% B at 150 min , and finally 100% B at 151 min , before the column was re-equilibrated to 0% B for 10 min . Protein elution was monitored by UV absorbance at 214 nm and histones in each fraction were tentatively identified by resolution on a 13% SDS-PAGE gel with Coomassie Blue staining ( see Figure S1 ) . Histones extracted from TK6 cells and other protein samples were dissolved in 50 µL of 100 mM ammonium bicarbonate buffer ( pH 8 . 5 ) , 4 , 4 , 5 , 5-[2H]-lysine ( 2 nmol ) , 4 , 4 , 5 , 5-[2H]-N6-formyllysine ( 1 pmol ) , and 3 , 3 , 4 , 4 , 5 , 5 , 6 , 6-[2H]-N6-acetyl lysine ( 10 pmol ) were added as internal standards , and the proteins hydrolyzed by addition of S . griseus protease ( freshly prepared solution each time ) with incubation at 37°C for ≥16 h . Streptomyces griseus was used at a ratio of 1 µg of enzyme per 10 µg of protein . Samples were then dried under vacuum and resuspended in 50 µL of water before mass spectrometry analysis . N6-Formyllysine and other amino acids were quantified as a percentage of the total quantity of lysine , by liquid chromatography-coupled mass spectrometry ( LC-MS/MS ) . HPLC was performed with an Agilent 1100 series instrument . Adducts of interest in the resuspended protein hydrolysates were separated using an aqueous normal phase Cogent diamond hydride column ( 2 . 1×150 mm , 4 µm ) from MicroSolv Technology Corporation ( Eatontown , NJ ) . The mobile phase flow rate was 400 µL/min , and the column temperature was maintained at 20°C . The solvent system was 0 . 1% acetic acid in water ( A ) and 0 . 1% acetic acid in acetonitrile ( B ) , with the elution starting at 100% B , the gradient linearly decreased to 25% B over 30 min , stayed at 25% B for 3 additional min before the column was re-equilibrated at 100% B for 7 min . In order to separate a co-eluting contaminant from pre-purified lysine demethylation study samples , an extended chromatography run time was used , with the elution starting at 100% B , the gradient linearly decreased to 75% B over 75 min , further decreased to 25% B over the next 3 min , reached 15% by 83 min before the column was re-equilibrated at 100% B for 7 min . The species of interest were then analyzed using Agilent 6410 triple quadrupole mass spectrometer ( MS/MS ) equipped with an electrospray ionization ( ESI ) source operated in positive ion mode . The operating parameters were as follows: ESI capillary voltage , 4000 V; gas temperature , 350°C; drying gas flow , 12 L/min; and nebulizer pressure , 30 psi . Selected reaction monitoring ( SRM ) transitions are summarized in Table 3 . Note that in addition to chromatographic separation ( Figure 2 ) and presence of internal standards , the unique product ions of 112 m/z and 126 m/z for formyl and acetyl lysines , respectively , distinguish them from their isobaric compounds di- and tri-methyl lysines . The fragmentor voltage and collision energy were optimized in order to maximize the signal of each product ion monitored ( see Figure S3 ) and are summarized in Table 3 . 4 , 4 , 5 , 5-[2H]-Lysine , 4 , 4 , 5 , 5-[2H]-N6-formyllysine , and 3 , 3 , 4 , 4 , 5 , 5 , 6 , 6-[2H]-N6-acetyl lysine were used as internal standards . Calibration curves for the labeled and unlabeled forms of these analytes were constructed by plotting the ratios of the areas of the MS signals for the labeled and unlabeled forms against their corresponding concentration ratios ( Figure S4 ) . N6-Methylated lysine species were quantified using the deuterated acetyl lysine internal standard signal ( Figure S4 ) . SIRT1 peptide substrates ( GGAKRHR , GGAKacetylRHR , and GGAKformylRHR ) were HPLC purified on an Agilent 1100 series instrument using Vydac 218TP52 C18 reverse-phase column ( 2 . 1×250 mm , 5 µm ) from Grace Vydac ( Hesperia , CA ) . The mobile phase flow rate was 200 µL/min , and the column temperature was maintained at 30°C . The solvent system was 0 . 05% trifluoroacetic acid in water ( A ) and 0 . 05% trifluoroacetic acid in 80% acetonitrile ( B ) , with the isocratic elution of 5% B for the first 5 min , then a linear increase to 42% B over 25 min , reaching 100% B at 31 min followed by column re-equilibration at 5% B for 10 min . Each purified SIRT1 peptide substrate ( 100 pmol ) were incubated overnight ( 12 h ) at 25°C with 1 µg SIRT1 , in 50 mM Tris-HCl ( pH 8 ) buffer containing 137 mM NaCl , 2 . 7 mM KCl , 1 mM MgCl2 , and 6 mM NAD+ . The removal of acetyl and formyl groups from SIRT1 peptide substrates was determined using liquid chromatography-coupled mass spectrometry . HPLC was performed on an Agilent 1100 series instrument using Agilent Exclipse XDB C18 reverse-phase column ( 4 . 6×150 mm , 5 µm ) . The mobile phase flow rate was 200 µL/min , and the column temperature was maintained at 40°C . The solvent system was 0 . 1% acetic acid in water ( A ) and 0 . 1% acetic acid in acetonitrile ( B ) , with the elution starting at 20% B , the gradient linearly increased to 50% B over 5 min , reached 100% B at 6 min , and kept at 100% B for 9 minutes before the column was re-equilibrated at 20% B for 10 min . The species of interest were then analyzed using the Agilent 6410 MS/MS system equipped with an electrospray ionization ( ESI ) source operated in positive ion mode . The operating parameters were as follows: ESI capillary voltage , 3500 V; gas temperature , 345°C; drying gas flow , 8 L/min; and nebulizer pressure , 30 psi . Multiple reaction monitoring ( MRM ) transitions were as follow: GGAKRHR peptide , m/z 781 . 1→625 . 2; GGAKformylRHR peptide , m/z 809 . 4→516 . 3; and GGAKacetylRHR peptide , m/z 823 . 4→530 . 4 . The fragmentor voltage and collision energy were 200 V and 40 V for GGAKRHR peptide , respectively; 100 V and 46 V for GGAKformylRHR peptide; and 100 V and 52 V for GGAKacetylRHR peptide .
|
Oxidative stress and inflammation lead to the generation of a multitude of electrophiles in cells that in turn react with nucleophilic macromolecules such as DNA , RNA , polyunsaturated fatty acids , and proteins , leading to progression of a variety of disorders and diseases . Emerging evidence points to widespread modification of cellular proteins by N6-formylation of lysine as a result of adventitious reactions with endogenous electrophiles . N6-Formyllysine is a chemical homolog of the biologically important N6-acetyllysine and thus may interfere with acetylation signaling in cells . While N6-formyllysine adducts are now well recognized as abundant protein modifications in cells , the source of these pathological adducts remains unclear . Our previous study proposed N6-formylation of lysine in histone proteins occurred by reaction of lysine with 3′-formylphosphate residues arising from DNA oxidation . Here , we investigate additional sources as well as the fate of this abundant pathological protein modification . Our results reveal that endogenous formaldehyde is a major source of N6-formyllysine and that this adduct is widely distributed among proteins in all cell compartments . We also demonstrate for the first time that N6-formyllysine modifications do not undergo appreciable removal by histone deacetylases , which suggests that they persist in proteins and possibly interfere with the signaling functions at conserved lysine positions in histone proteins .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"biochemistry",
"analytical",
"chemistry",
"molecular",
"cell",
"biology",
"gene",
"expression",
"genetics",
"chemical",
"biology",
"epigenetics",
"biology",
"chemistry",
"molecular",
"biology",
"genetics",
"and",
"genomics",
"histone",
"modification"
] |
2013
|
Quantitative Analysis of Histone Modifications: Formaldehyde Is a Source of Pathological N6-Formyllysine That Is Refractory to Histone Deacetylases
|
It is well understood that apicomplexan parasites , such as the malaria pathogen Plasmodium , are descended from free-living algae , and maintain a vestigial chloroplast that has secondarily lost all genes of photosynthetic function . Recently , two fully photosynthetic relatives of parasitic apicomplexans have been identified , the ‘chromerid’ algae Chromera velia and Vitrella brassicaformis , which retain photosynthesis genes within their chloroplasts . Elucidating the processes governing gene expression in chromerid chloroplasts might provide valuable insights into the origins of parasitism in the apicomplexans . We have characterised chloroplast transcript processing pathways in C . velia , V . brassicaformis and P . falciparum with a focus on the addition of an unusual , 3′ poly ( U ) tail . We demonstrate that poly ( U ) tails in chromerids are preferentially added to transcripts that encode proteins that are directly involved in photosynthetic electron transfer , over transcripts for proteins that are not involved in photosynthesis . To our knowledge , this represents the first chloroplast transcript processing pathway to be associated with a particular functional category of genes . In contrast , Plasmodium chloroplast transcripts are not polyuridylylated . We additionally present evidence that poly ( U ) tail addition in chromerids is involved in the alternative processing of polycistronic precursors covering multiple photosynthesis genes , and appears to be associated with high levels of transcript abundance . We propose that changes to the chloroplast transcript processing machinery were an important step in the loss of photosynthesis in ancestors of parasitic apicomplexans .
The transition from a photosynthetic to a parasitic lifestyle has occurred a multitude of times across the eukaryotes [1] . Parasitism , concomitant with either the complete loss or a severe reduction in dependence on photosynthesis , has been documented in members of the land plants and the green , red , and brown algae [1]–[4] . Typically , parasitic organisms descended from photosynthetic ancestors retain chloroplasts with their own genome , but these genomes are vastly reduced in content . Various hypotheses have been suggested for why certain genes are retained in the chloroplast , and others are transferred to the nucleus , such as the greater relative frequency of mutations in chloroplast genes , the higher energetic cost associated with synthesis and import of cytoplasmic proteins , and the direct regulation of chloroplast-encoded genes in response to changes in chloroplast redox state , or other biochemical parameters [5]–[7] . However , the reasons why , and when , chloroplast genes are lost during the transition from photosynthesis to parasitism remain comparatively underexplored . Perhaps the most dramatic example of the transition from photosynthesis to parasitism occurs in the apicomplexans , a group containing several pathogens of major humanitarian importance , including the malaria parasite Plasmodium , and Toxoplasma and Cryptosporidium , causative agents respectively of toxoplasmosis and cryptosporidiosis , both potentially fatal to immuno-compromised patients [1] . Apicomplexans are descended from photosynthetic algae , and the majority - apart from Cryptosporidium - retain a vestigial , non-photosynthetic , chloroplast-derived organelle , termed the ‘apicoplast’ , which is involved in a number of metabolic pathways fundamental to parasite viability and pathology [8] , [9] . The apicoplast contains its own genome that is conventionally organised , but has lost all genes for proteins that function directly in photosynthetic electron transfer , which we will henceforth term ‘photosynthesis genes’ , and only retains genes of non-photosynthetic function [10] . Although the evolutionary origin of the apicoplast has been the subject of debate , recent studies firmly place it as being of secondary , red algal derivation , and sharing a common ancestry with the chloroplasts found in a closely related group of algae , the peridinin dinoflagellates [10]–[12] . Peridinin dinoflagellates possess an extremely unusual chloroplast genome , which is organised on small , plasmid-like elements termed ‘minicircles’ , and has a highly reduced coding content . The chloroplast genomes of peridinin dinoflagellates contain only a few photosynthesis genes , genes for ribosomal and transfer RNAs , and in some species other open reading frames that lack an identified function , or recognisable homologues to other lineages [1] , [13] . Dinoflagellate chloroplasts use abnormal RNA metabolism pathways including rolling circle transcription , and extensive post-transcriptional editing occurs in certain species [14] , [15] . Most dramatically , a 3′ terminal poly ( U ) tail is added during the processing of transcripts of protein-coding genes [16] . While similar transcript polyuridylylation events have been reported in various nuclear and mitochondrial lineages , they do not occur in plant or other algal chloroplasts . Transcript polyuridylylation has likewise not been found in the apicoplast , although , to our knowledge , this has not been shown systematically and the only information available comes indirectly from EST libraries and next generation sequencing reads [12] , [17] , [18] . In the past decade , two fully photosynthetic close relatives of apicomplexan parasites have been identified , jointly referred to as the ‘chromerid’ algae [1] , [19] . Chromera velia is a small , single-celled alga with coccoid and motile forms , whereas Vitrella brassicaformis ( e . g . CCMP3155 ) is a much larger , pseudocolonial alga , with a complex life cycle [19] , [20] . Both species form symbiotic associations with zooxanthellate corals [19]–[21] , and recent studies suggest that many more as yet uncultured chromerids are present in coralline environments [22] , [23] . Phylogenetic analyses robustly place C . velia and V . brassicaformis as separate sister groups to apicomplexans [11] , [19] to the exclusion of peridinin dinoflagellates . The exact dates at which the chromerid lineages diverged from the parasitic apicomplexans remain a matter of debate , although these have been estimated to be anywhere between 350 and 700 million years before the present , and were probably well after the divergence of the common ancestor of apicomplexans and chromerids from the dinoflagellates [24]–[26] . Some of the metabolic pathways associated with the chloroplasts of C . velia , at least , are more similar to those occurring in the chloroplasts of other free-living algae than to those of apicomplexans , whereas the opposite is true for others [27]–[31] . A more detailed understanding of the processes governing the expression of photosynthesis versus non-photosynthesis genes in the chloroplasts of chromerid algae might provide insights into the evolution of parasitism in early apicomplexans . The chloroplast genomes of both C . velia and V . brassicaformis have been sequenced and are of the same endosymbiotic derivation as those of apicomplexans and peridinin dinoflagellates . The V . brassicaformis chloroplast genome consists of one single circular chromosome , similar to that of apicomplexans , while the C . velia chloroplast genome is believed to comprise a single , long linear chromosome , unlike that of either dinoflagellates or apicomplexans [11] , [32] . However , both chromerid chloroplast genomes are larger than those of either the apicomplexan or peridinin dinoflagellate lineages , retaining 55 ( Chromera ) and 71 ( Vitrella ) non-redundant annotated protein-coding genes , of both photosynthetic and non-photosynthetic function , as well as a small number of open reading frames of unannotated function , and specific to either species [11] . It has previously been shown that , similar to the situation in dinoflagellates , poly ( U ) tails are added to at least three chloroplast transcripts ( psaA , psbB , psbC ) in C . velia [11] , [32] . However , it is not known to which other transcripts in C . velia chloroplasts poly ( U ) tails are added , or whether similar poly ( U ) addition occurs in V . brassicaformis [32] . More broadly , the precise functional role of transcript poly ( U ) addition in chromerid algae remains uncharacterised . Here , we present an in-depth study of transcript poly ( U ) addition in C . velia and V . brassicaformis . We demonstrate that in both species poly ( U ) tails are principally added to transcripts encoding functional components of the photosynthetic electron transfer chain . Conversely , transcripts that do not encode products that directly function in photosynthesis tend not to be polyuridylylated in either C . velia or V . brassicaformis . This is to our knowledge the first example of a chloroplast transcript processing pathway that differentially recognises a particular functional category of genes . We additionally demonstrate that poly ( U ) addition occurs early in transcript processing in C . velia , and may influence other processing events on photosynthesis gene transcripts . Finally , we confirm that poly ( U ) addition does not occur in the apicomplexan Plasmodium falciparum . As the poly ( U ) machinery in chromerid algae is involved in the differential recognition of photosynthesis and non-photosynthesis genes , its loss may have played an important role in the transition of early apicomplexans from photosynthesis to obligate parasitism .
To test for the presence of polyuridylylated transcripts in C . velia and V . brassicaformis , we generated cDNA using an oligo-d ( A ) primer , which anneals to transcript poly ( U ) tails [12] , [33] . The oligo-d ( A ) primed cDNA was used as a template for a series of PCR reactions using the same oligo-d ( A ) primer , and a series of forward primers specific to different chloroplast genes from each species ( Table S1 ) . Figure 1 shows the results from two representative photosynthesis genes where RT-PCR products were obtained , consistent with the presence of polyuridylylated transcripts ( fig . 1: C . velia psbA , atpB-2 , panel A , lanes 1–2; V . brassicaformis psbA , atpB , panel A , lanes 7–8 ) . The identity of each transcript obtained via PCR was confirmed by direct sequencing , using the PCR forward primer as the sequencing primer . Similar products were observed with a control transcript from a dinoflagellate chloroplast ( Amphidinium carterae psbA ) that is known to be polyuridylylated ( fig . 1 , panel B , lane 1 ) [33] . In contrast , analogous RT-PCRs against representative chloroplast genes that do not encode products directly involved in photosynthesis from both species ( rps11 and rrs ) failed to resolve clear products , even after two successive rounds of PCR amplification ( fig . 1 , panel A , lanes 3–4 , 9–10 ) . We could detect RT-PCR products generated using gene-specific primers ( fig . 1 , panel A lanes 5–6 , 11–12 , Table S2 ) , implying that transcripts of each gene are present , but do not receive a poly ( U ) tail . Similar products were observed for a control nuclear transcript ( C . velia Hsp90 ) as well as a transcript from a diatom chloroplast ( Phaeodactylum tricornutum psbA ) which has previously been shown not to receive a poly ( U ) tail ( fig . 1 , panel B lanes 3–6 ) [12] . To determine whether poly ( U ) tail addition is significantly biased towards photosynthesis genes in chromerid algae , we performed oligo-d ( A ) RT-PCRs against every annotated gene and open reading frame in the C . velia chloroplast genome ( n = 78 ) , and over half the genes in the V . brassicaformis chloroplast genome ( n = 43 , out of 74 total ) ( Table S2 ) . In both species , transcript poly ( U ) addition was significantly biased towards photosynthesis genes ( chi-squared: C . velia P<0 . 005; V . brassicaformis P<0 . 05 ) . While we could identify some genes that contradicted general patterns - i . e . transcripts of photosynthesis genes that do not receive a poly ( U ) tail or polyuridylylated transcripts that encode non-photosynthesis proteins , or novel open reading frames – most of these exceptions were specific to one species . Only two non-photosynthesis genes ( rpl3 and rps18 ) were found to possess poly ( U ) sites in both species , and none of the non-polyuridylylated photosynthesis genes was conserved between C . velia and V . brassicaformis ( fig . 2 ) . None of the poly ( U ) sites identified was predicted to lie within poly ( T ) tracts of more than 6 bp in either genomic sequence , suggesting that the poly ( U ) tails are not genome-encoded [11] . Consistent with other studies [32] , we could not detect any evidence of post-transcriptional editing in any transcripts in either species . We wished to determine whether poly ( U ) sites were associated with specific regions of chromerid chloroplast genomes . Comparison of RT-PCR products with genomic sequences showed that , other than a preferential association with photosynthesis gene 3′ UTRs , poly ( U ) sites are broadly distributed across chromerid chloroplast genomes . We could identify poly ( U ) sites on genes located at the 5′ end ( C . velia petG ) , in the interior ( C . velia atpB-2 ) and 3′ end ( C . velia psbA ) of clusters of related function , as well as on photosynthesis genes that are located within clusters containing genes of otherwise non-photosynthetic function ( e . g . C . velia atpI , which is positioned downstream of rps14 and upstream of rpl11 ) [11] . We tested whether poly ( U ) sites were enriched at the start or end of potential operons in C . velia , defining operons as uninterrupted clusters of genes in the genomic sequence that are in the same transcriptional orientation [11] , and could not find any significant association ( Table S3 , chi-squared: P>0 . 35 ) . Plant chloroplasts utilise two different RNA polymerases: a nuclear-encoded polymerase related to the phage-type polymerase of mitochondria , which principally transcribes non-photosynthesis genes , and a bacterial-type , plastid-encoded polymerase , principally involved in the expression of photosynthesis genes [34]–[36] . Modulation of the activity of each polymerase may underpin developmental and physiological changes in chloroplast gene expression [37]–[39] . While there is no evidence for the presence of a phage-type plastid polymerase outside the land plant lineage [40] , [41] , subunits of a bacterial-type polymerase are encoded in the chloroplast genomes of C . velia and V . brassicaformis [11] . To test whether this polymerase preferentially transcribes genes that either contain or lack an associated poly ( U ) site , we searched for predicted bacterial-type promoters across the 5′ UTR of every gene in the C . velia chloroplast using a Neural Network Promoter Prediction server [42] . Similar to what has been reported in plants [35] , [36] , we found evidence for large numbers of candidate promoters in the C . velia chloroplast at a wide range of positions , including upstream of photosynthesis and non-photosynthesis genes ( Table S3 ) . Across the entire genome , bacterial promoters appeared to be weakly enriched upstream of genes that possess poly ( U ) sites ( chi-squared: P<0 . 05 ) . However , this was almost entirely due to the fact that bacterial promoters were generally not found upstream of ORFs of unknown function , which are also less likely to possess poly ( U ) sites than photosynthesis genes . Considering genes of recognisable function , there was no direct association between the presence of predicted bacterial promoters and poly ( U ) sites ( chi-squared: P>0 . 2 ) . It therefore appears that- at least in the case of a bacterial polymerase- there is not a convincing association between the presence of a candidate promoter and poly ( U ) site on specific genes . We additionally analysed the position of poly ( U ) sites relative to the 3′ end of coding sequences . The position of poly ( U ) sites relative to the 3′ end of each gene is certainly highly variable , although certain trends were present in each species . Typically , poly ( U ) sites in V . brassicaformis were positioned close to the stop codon , with an average 3′ UTR of 55 nt , although in one case ( petG ) a 3′ UTR of 277 nt was recorded ( Table S2 ) . In contrast , poly ( U ) sites in C . velia were positioned further downstream of the stop codon , with an average 3′UTR of 145 nt , and extending up to 584 nt for one poly ( U ) site found downstream of psbH ( Table S2 ) . In one case , the C . velia ORF264 gene , we could identify a poly ( U ) site that was positioned within the coding sequence itself , 50 bp upstream of the stop codon . This was the only poly ( U ) site to be found immediately upstream of a predicted termination codon . Oligo-d ( A ) RT-PCR using a gene specific forward primer , positioned immediately downstream of this poly ( U ) site , revealed the presence of a second ORF264 poly ( U ) site , positioned 281 nt into the 3′ UTR ( Tables S1 , S2 ) . The sequence covered by the ORF264 gene does not contain any other sizeable open-reading frames that terminate upstream of the poly ( U ) site , and it is therefore likely that the addition of a poly ( U ) tail at the internal site disrupts translation of the ORF264 transcript . Several other C . velia chloroplast genes appeared to possess multiple potential poly ( U ) sites , as with ORF264 . In some instances , oligo-d ( A ) RT-PCR reactions for C . velia produced multiple bands visible after gel electrophoresis ( e . g . atpB-2; fig . 1 , panel A , lane 2; Table S2 ) , which could correspond to multiple alternative poly ( U ) sites within the 3′ UTR . We assessed variation in poly ( U ) site position by cloning and sequencing individual RT-PCR products for transcripts from three genes that produced multiple products by oligo-d ( A ) RT-PCR ( C . velia psaC , atpB-2 , atpI; Table S4 ) . To identify whether poly ( U ) sites vary even in genes where no obvious heterogeneity in position could be inferred purely from gel electrophoresis , we cloned and sequenced individual RT-PCR products for petD and psbA from both C . velia and V . brassicaformis , each of which produced only a single visible gel band . We found substantial variability in 3′ UTR length for many of the transcripts tested , even if only one band was distinguishable by agarose gel electrophoresis . In one particularly extreme case ( atpB-2 ) we observed eleven different poly ( U ) sites , ranging from 60 to 467 nt into the 3′ UTR ( fig . S1 , Table S4 ) , which broadly corresponded to the different band sizes visible on oligo-d ( A ) RT-PCR ( fig . 1 , panel A , lane 3 ) . In contrast , little variability was seen with V . brassicaformis petD and psbA , which had consistent tail lengths and only a single nucleotide variability in the 3′UTR prior to the poly ( U ) tail . Consistent with this variability , we were unable to identify any conserved sequence motifs located either upstream or downstream of the poly ( U ) sites in either species . Nor could we identify any consistent changes in GC or purine content , or any predicted secondary structures that were universally associated with poly ( U ) sites in either species , suggesting that different poly ( U ) sites might be defined in different ways by the transcript processing machinery . However , ten of the twenty-four poly ( U ) sites in V . brassicaformis , including four sites associated with non-photosynthesis genes ( ccs1 , chlN , rps4 , rps16 ) were immediately adjacent to the 5′ end of predicted tRNAs ( Table S2 , fig . S2 ) . Although we could identify poly ( U ) sites that were independent of tRNAs , we could not identify any genes immediately upstream of tRNA genes whose transcripts did not receive poly ( U ) tails ( Table S2 ) . This suggests that some of the poly ( U ) sites in V . brassicaformis are generated by the cleavage of downstream tRNAs from precursor transcripts . It has previously been suggested that the poly ( U ) tails found in dinoflagellate chloroplasts may facilitate gene expression , either by protecting transcripts from 3′ end degradation [33] , or by enabling other transcript processing events , such as editing , that facilitate translation [12] , [43] . A recent next generation sequencing study of the Chromera velia chloroplast transcriptome , by Janouškovec et al . , recovered substantially higher read coverage for transcripts of photosynthesis genes than for transcripts of genes that are not directly involved in photosynthesis , or other open reading frames , suggesting that photosynthesis gene transcripts are highly abundant in the C . velia chloroplast [32] . Substantial variation was recorded in transcript abundance within individual operons , indicating that this is at least in part dependent on differences in transcript processing over different genes [32] . We considered whether the presence of a poly ( U ) tail might be associated with high transcript abundance in chromerid chloroplasts . Calculating from the quantitative read coverage data obtained by Janouškovec et al . [32] , genes that possess poly ( U ) sites are significantly more highly expressed than those that do not ( Table S3 , Mann-Whitney test , P<E-04 ) . While there may be a general association between polyuridylylation and high levels of expression , other gene-specific factors are also likely to influence transcript abundance , and it is therefore not justifiable to attribute differences in transcript level between different genes solely to the presence of a poly ( U ) tail . In plant chloroplasts , photosynthesis genes are generally more highly expressed than genes of non-photosynthesis function [44] , [45] , and the higher transcript abundance associated here with polyuridylylated transcripts , which predominantly function in photosynthesis , could similarly be due to the function of the protein , as opposed to the presence or absence of a poly ( U ) tail . To gain a more accurate understanding of whether transcript poly ( U ) tails affect transcript abundance , we considered the expression levels of three photosynthesis genes that are present in the C . velia chloroplast genome as multiple copies or fragments . The psaA gene is split into two functional units , which encode separate parts of the mature photosystem I reaction centre protein [11] , [32] . The two psaA transcripts are not trans-spliced together , and are separately translated to form distinct but presumably functionally cooperative proteins [32] . Transcripts of each of the psaA genes are highly expressed , and both have been shown to receive a poly ( U ) tail ( [32] , fig . 3 , panel A , lanes 1–2 ) . A similar situation is true for the atpB gene , encoding the chloroplast ATP synthase β subunit , which is likewise split into two functionally autonomous , and highly expressed gene fragments . As with psaA , we could detect poly ( U ) tails on both atpB transcripts ( fig . 3 , panel A , lanes 3–4 ) . In contrast to the atpB and psaA genes , the atpH gene is present in two paralogous copies on the C . velia with very different expression patterns . Transcripts of atpH-1 encode a complete copy of the ATP synthase c subunit , and are highly abundant in chromerid chloroplasts [32] . Transcripts of atpH-2 encode not only a complete c subunit , but in addition encode a novel 89 aa C-terminal extension not found in protein sequences from other chloroplast lineages ( fig . S3 , panel A ) . The atpH-2 transcripts are nearly one hundredfold lower in abundance than those of atpH-1 , are the least abundant photosynthesis gene transcripts within the C . velia chloroplast , and are only marginally more abundant than rpl36 , the least abundant transcript of recognisable protein-coding function . This suggests that the atpH-2 gene is a pseudogene ( [32] , fig . 3 , panel B ) . The 5′ end and 5′ UTR of the atpH-2 gene are almost identical to the atpH-1 gene ( 93% nucleotide similarity; fig . S3 , panel B ) , suggesting that the difference in transcript abundance is due to sequences within the 3′ extension or 3′ UTR of atpH-2 . We found that while transcripts of atpH-1 receive a poly ( U ) tail , transcripts of atpH-2 do not ( fig . 3 , lanes 5–8 ) . The loss of a poly ( U ) site from the atpH-2 gene , associated with a much lower level of expression than any other analogous gene in the C . velia chloroplast , very strongly indicates that the presence of a poly ( U ) tail is associated with high levels of gene expression in chromerid chloroplasts . Given that poly ( U ) tails appear to be associated with high transcript levels in chromerids , we wished to investigate the precise role of the poly ( U ) tail in transcript processing . In particular , we wished to determine what proportion of transcripts for individual photosynthesis genes contain poly ( U ) tails , and whether alternative , poly ( U ) -independent processing pathways may be present . We accordingly performed RT-PCRs on circularised RNA for a range of chloroplast transcripts in Chromera velia using an internal , gene-specific cDNA synthesis primer , an outward-directed PCR reverse primer that annealed just within the 5′ end of coding sequence ( CDS ) , and a PCR forward primer that annealed to the 3′ end of the CDS ( Table S1 ) . We tested six genes known to possess poly ( U ) sites; five photosynthesis genes , of varying levels of transcript abundance ( in descending order: psbA , petB , psbH , atpB ( 2 ) , and atpI ) , and rps18 , one of only two non-photosynthesis genes found to possess a poly ( U ) site in both C . velia and Vitrella brassicaformis . In addition , we tested two genes that lacked an associated poly ( U ) site: rps14 , located directly upstream of atpI , and atpH-2 , directly upstream of psbA . We identified homopolymeric poly ( U ) tails on C . velia psbA , atpB-2 , atpI , petB and psbH transcripts , consistent with the oligo-d ( A ) RT-PCR data ( fig . 4 , Table S5 , panels A–D ) . Only two of the polyuridylylated transcripts identified by circular RT-PCR , out of a total of 27 sequenced , contained any nucleotides other than uridine within the 3′ tail , indicating that heteropolymeric tails are extremely rare in chromerid chloroplasts . For each gene , we could additionally identify non-polyuridylylated transcripts , similar to what has been found in dinoflagellates [12] , [33] , but in almost every case these transcripts terminated either within the CDS or significantly upstream of the poly ( U ) site in the 3′ UTR of the gene , which may suggest that they are the 3′ degradation products of previously polyuridylylated transcripts ( fig . 4 ) . Within the five polyuridylylated photosynthesis genes , we could identify only three transcripts ( one transcript each for psbA , petB , and atpI ) that terminated at or extended past the corresponding poly ( U ) sites . Overall , our data are consistent with poly ( U ) tail addition being the only 3′ maturation pathway acting on photosynthesis gene transcripts . We could identify transcripts for both atpH-2 and rps14 that extended into the 3′ UTR , but could not detect poly ( U ) tails or any other form of terminal modifications on transcripts of either gene ( Table S5 , panels A , C ) . This indicates that transcripts from genes that lack poly ( U ) sites are not subject to any alternative 3′ modification events . Surprisingly , a circular RT-PCR using primers internal to the rps18 gene failed to identify any polyuridylylated transcripts ( although their existence was indicated by the oligo-d ( A ) linear RT-PCR experiments ) , but instead recovered large numbers of transcripts that terminated within the 3′ UTR , upstream of the previously identified consensus poly ( U ) site ( Table S5 , panel E ) . We could retrieve polyuridylylated rps18 transcripts only by using a PCR forward primer that annealed directly upstream of the rps18 poly ( U ) site , thus biasing the PCR for transcripts that extended at least as far as the poly ( U ) site . However , in this case we also identified equal numbers of transcripts that extended past the consensus poly ( U ) site ( fig . 4 , Table S5 , panel E ) . This suggests that the effective concentration of polyuridylylated rps18 transcripts was very low . Therefore , while rps18 and some other non-photosynthesis genes may possess poly ( U ) sites that are detectable by oligo-d ( A ) RT-PCR , the majority of the corresponding non-photosynthesis gene transcripts do not receive a poly ( U ) tail during transcript processing . This confirms that the poly ( U ) tail is principally functionally involved in the processing of photosynthesis gene transcripts in chromerid chloroplasts . Similar to the variation we observed for transcript 3′ ends , we found that different transcripts identified for a particular gene by circular RT-PCR had different 5′ terminus positions ( Table S5 ) . For a few genes , transcripts appeared to terminate preferentially at a certain position within the 5′ UTR: for example , 7 out of 8 atpH-2 transcripts sequenced terminated 35 nt upstream of the atpH-2 gene . However , for other genes , we could identify transcripts that terminated at different positions in the 5′ UTR , or terminated at the 5′ end within the CDS ( Table S5 ) , suggesting heterogeneous processing of the 5′ end . It has long been known that chloroplast genes are cotranscribed [46]–[49] . Recently , it has been demonstrated that poly ( U ) tails are added to polycistronic transcripts in dinoflagellates , indicating that poly ( U ) tail addition may occur relatively early in transcript processing [15] , [33] . We found extensive evidence for polycistronic transcripts in both chromerid species from oligo-d ( A ) RT-PCR . For some genes for which we could not identify a monocistronic polyuridylylated transcript , polycistronic polyuridylylated products were recovered , with the poly ( U ) site in the 3′ UTR of the gene furthest downstream . These polycistronic polyuridylylated products extended over two genes ( e . g . C . velia psbK-psbV ) and in one case , even over four genes ( V . brassicaformis rps14-psbV-ccsA-psbK ) , ( Table S2 ) . At three other selected loci ( C . velia , atpH2-psbA , ORF207-atpB2 , and rps14-atpI ) , we could specifically amplify transcripts that extended over both genes from oligo-d ( A ) primed cDNA , using PCR primers that would amplify a region between the 5′ end of the upstream gene and the 3′ end of the downstream gene ( fig . S4 ) . To determine whether these polycistronic transcripts are subject to similar 5′ end-processing events as monocistronic transcripts , or uniquely represent primary transcripts , we performed circular RT-PCRs using a primer combination specific to dicistronic rps14-atpI transcripts ( Table S1 , S5 ) . As the T4 RNA ligase used for RNA ligation can only act on transcripts with 5′ monophosphate groups , any products consistent with polycistronic transcripts would indicate that these transcripts had undergone 5′ processing [15] , [33] . We could detect a polyuridylylated transcript that extended from the 5′ end of rps14 to the atpI poly ( U ) site ( Table S5 , panel B ) . In total , our data suggest that the chromerid chloroplast transcript pool consists of a mixture of monocistronic , dicistronic and potentially even larger polycistronic transcripts , ( U ) sites ( psbA , atpB-2 , atpI; fig . 5 , panels A–C ) , many of which may have undergone 5′ and 3′ end processing . Given the heterogeneous composition of the chromerid chloroplast transcript pool , we wished to determine how significant a fraction of the C . velia chloroplast transcriptome polycistronic transcripts represented . We accordingly analysed northern blots of C . velia RNA using probes specific to transcripts of genes that possess poly ( U ) sites ( psbA , atpI , and atpB-2 ) , and of genes that do not ( atpH-2 , rps14 ) ( Table S6 ) . For each of the genes that possess poly ( U ) sites , we could identify bands consistent with monocistronic transcripts . For psbA , we observed a single band corresponding to an 1100 nt transcript , while for atpI we observed a band corresponding to about 950 nt ( fig . 5 , panels A , B ) . These agree with expected sizes ( from circular RT-PCR results ) of monocistronic transcripts ( 5′ UTR , gene , 3′ UTR and a poly ( U ) tail ) ( Table S5 ) . Although we cannot exclude that non-polyuridylylated psbA or atpI transcripts were also present , we did not identify ( by circular RT-PCR ) any non-polyuridylylated transcripts , of either gene , of a length that would comigrate with the bands visible in the northern blots ( Table S5 ) . For atpB-2 , we identified multiple bands . The two high intensity bands at 1600 and 1800 nt correspond to the monocistronic , polyuridylylated transcripts obtained by circular RT-PCR ( fig . 5 , panel C; Table S5 ) . We additionally identified a higher molecular weight band of 2000 nt , and while we could not identify any transcripts by circular RT-PCR of a similar length , this band could plausibly represent monocistronic transcripts that extend to the most distant poly ( U ) site associated with atpB-2 , positioned 467 nt into the 3′ UTR ( Table S4 ) . No non-polyuridylylated atpB-2 transcripts of 1500 nt length or greater were identified by circular RT-PCR . However , circular RT-PCR ( Table S5 ) did reveal the presence of non-polyuridylylated atpB-2 transcripts , with 3′ ends internal to the atpB-2 CDS , which might correspond to a faint 1300 nt band detected in the northern blot ( fig . 5 , panel C; Table S5 ) . In contrast to the high abundance of monocistronic transcripts , we could not identify any higher molecular weight bands of a size consistent with polycistronic transcripts , for either psbA or atpB-2 ( fig . 5 , panel A ) . We could identify a faint band in the atpI northern blot at 1400 nt that might correspond to a polycistronic precursor , but this band was of much lower intensity than the band corresponding to the monocistronic transcript ( fig . 5 , panel D ) . Overall , our data indicate that while polycistronic transcripts may be present in chromerid chloroplasts , the transcripts of at least some photosynthesis genes are predominantly present as monocistronic mRNAs , many of which are likely to possess poly ( U ) tails . It is possible that the presence of a poly ( U ) tail might be associated with the processing of polycistronic precursors to monocistronic transcripts . To test this , we probed northern blots for atpH-2 and rps14 , which are not polyuridylylated , to determine whether they are processed as efficiently as transcripts of genes that possess poly ( U ) sites . The atpH-2 probe sequence was designed against the C-terminal extension unique to the C . velia atpH-2 gene , and therefore was not expected to cross-hybridise with transcripts of atpH-1 ( Table S6 ) . Surprisingly , a northern blot probed for atpH-2 recovered several high intensity , high molecular weight bands ( fig . 5; panel D ) . The 900 and 1500 nt bands correspond in size to polycistronic atpH-2 transcripts obtained by circular RT-PCR that extended well into the psbA CDS ( Table S5 ) . A lower intensity band at 500 nt was of similar size to degraded transcripts observed in circular RT-PCR that terminated within the atpH-2 CDS ( fig . 5 , panel D; Table S5 ) . We could not identify a band of corresponding size ( 600 nt ) to monocistronic atpH-2 , even though such transcripts were identified using circular RT-PCR . This suggests that monocistronic atpH-2 transcripts are not present at physiologically significant concentrations ( fig . 5 , panel D; Table S5 ) . Similarly , in the case of the rps14 , which lacks an associated poly ( U ) site , only bands at 1700 and 2000 nt could be observed , far larger than the c . 500 nt monocistronic transcripts obtained by circular RT-PCR ( fig . 5 , panel E ) . The dominant populations of rps14 transcripts must at least possess a lengthy 3′ UTR , as similar bands were also recovered by a probe that spanned the non-coding region downstream of rps14 and upstream of the adjacent atpI gene ( fig . 5; panel F ) . This implies that , at least at certain loci , transcripts of genes that lack associated poly ( U ) sites may be subject to limited 3′ end-maturation events , and are instead retained on higher molecular weight precursors . For several of the oligo-d ( A ) RT-PCR products sequenced ( e . g . C . velia atpI , V . brassicaformis rps18 ) , the poly ( U ) site associated with a particular gene is positioned within the 5′ end of the downstream coding sequence . If these polyuridylylated transcripts are generated from the cleavage of longer , polycistronic precursors , the poly ( U ) sites would indicate that transcripts are generated by alternative 3′ processing , in that the generation of a mature mRNA from a polycistronic precursor transcript would prevent the generation of an mRNA of the downstream gene from the same precursor . Such alternative processing is similar to what has been previously identified in other chloroplast lineages [33] , [47] . To determine whether alternative processing can occur in chromerid chloroplasts , we investigated transcript processing at the C . velia petG-petB-psbH-atpA locus ( fig . S5 ) . We identified polyuridylylated dicistronic petG-petB and petB-psbH transcripts , using similar RT-PCRs as before ( fig . S5 ) , demonstrating that polyuridylylated polycistronic transcripts are present over this locus . The poly ( U ) site associated with petB is located 27 nt within the 5′ end of psbH , and the psbH poly ( U ) site is located up to 584 nt into atpA ( Table S2 ) , hence it would be impossible to generate complete psbH transcripts from a precursor that had already yielded a polyuridylylated petB transcript , or atpA transcripts from a precursor that yielded psbH . We could additionally identify polyuridylylated monocistronic petB , monocistronic psbH , and dicistronic petB-psbH transcripts by circular RT-PCR ( Table S5 , panel D ) . This indicates that transcripts at this locus do undergo some degree of 5′ cleavage , and that monocistronic transcripts could plausibly be cleaved from polycistronic precursors . It is possible that , instead of being generated by the processing of common , polycistronic precursors , mRNAs in chromerid chloroplasts that have overlapping terminus regions might be separately transcribed from different promoter sites in the 5′UTR of each gene , and accumulate as independent populations of transcripts . Although we cannot exclude the possibility that some psbH transcripts are independently transcribed from promoter sequences promoter elements positioned between the petB and psbH genes , we could identify psbH transcripts from circular RT-PCR that extend at the 5′ end into the petB CDS by up to 261 nt ( Table S5 , panel D ) , which clearly must have been initiated from elements further upstream . While it is possible that psbH transcripts are generated from a promoter internal to the petB CDS , internal promoter sites are uncommon at least for protein-coding genes in plant chloroplasts , and generally appear to give rise only to very low levels of transcripts [35] , [36] , [50] , so it is unlikely that the transcriptional products of an internal promoter sequence would be detectable by circular RT-PCR . Taken together , our data therefore indicates that petB and psbH transcripts are most likely to be cotranscribed from a common promoter element upstream of the petB 5′ end . In at least some cases , mature , monocistronic petB and psbH mRNAs are generated by the alternative 5′ and 3′ cleavage of a common polycistronic precursor , which may be the dicistronic petB-psbH transcripts obtained by circular RT-PCR ( fig . 6 , panel A ) . Finally , we wished to determine whether alternatively processed transcripts comprise a significant proportion of the chromerid chloroplast transcript pool . We investigated the relative abundance of different processing intermediates over the petB-psbH locus , by analysing northern blots with probes for the C . velia petB and psbH genes ( fig . 6 ) . The psbH probe was positioned downstream of the petB poly ( U ) site , and the petB probe was positioned so that there was minimal overlap with the 5′ end of psbH transcripts ( Table S1 , S5 , S6 ) . Monocistronic transcripts should therefore only be detectable in either the petB or psbH blots , whereas common polycistronic precursors should be detectable in both . We observed 1600 and 1800 nt bands in both the petB and psbH blots ( fig . 6 , panel B ) . The 1600 nt band was of an equivalent size to polyuridylylated , dicistronic petB-psbH transcripts obtained by circular RT-PCR ( Table S5 , panel D ) , indicating that polycistronic transcripts are abundant over this locus . We could not identify any other high molecular weight bands of high intensity in either blot . However , we also observed lower molecular weight bands that were specific to either the petB or the psbH blots ( fig . 6 , panel B ) . The 1100 nt band seen when probed for petB is similar in size to a monocistronic transcript , which terminates at the 5′ end in the intergenic region between petG and petB , and at the 3′ end in the psbH CDS , as obtained by circular RT-PCR ( fig . 6 , panel B; Table S5 , panel D ) . Similarly , the 700 nt band seen when probed for psbH is similar in size to the circular RT-PCR sequence of a monocistronic transcript that terminates at the 5′ end in the petB CDS , and at the 3′ end in the atpA CDS ( fig . 6 , panel B; Table S5 , panel D ) . This indicates that monocistronic petB and psbH mRNAs , generated by alternative processing , do accumulate to a detectable level in C . velia chloroplasts . If poly ( U ) tails are added to transcripts prior to 5′ processing , the selection of a specific poly ( U ) site may even be involved in specifying which 5′ end maturation pathway occurs . As transcripts from non-photosynthesis genes in chromerid chloroplasts are generally not polyuridylylated , we wished to determine whether poly ( U ) tails were added to apicoplast transcripts , since proteins encoded in the apicoplast genome do not function in photosynthesis . We accordingly performed oligo-d ( A ) RT-PCRs as before , using RNA from Plasmodium falciparum , and PCR forward primers specific to all thirty protein-coding genes in the apicoplast . Oligo-d ( A ) RT-PCRs against apicoplast genes typically did not yield distinct bands ( Fig . 7 , lanes 1–3 ) . In some cases , we could observe faint bands on gel electrophoresis of oligo-d ( A ) RT-PCR products , which could potentially represent polyuridylylated transcripts . However , when sequenced , no product corresponded to apicoplast sequences . In contrast , we could identify non-polyuridylylated transcripts for apicoplast genes by amplification of cDNA generated using gene-specific primers ( fig . 7 , lanes 4–6 ) . We therefore conclude that only non-polyuridylylated transcripts are present in the P . falciparum apicoplast .
We have characterised the distribution and function of poly ( U ) sites across the chloroplast genomes of the chromerid algae Chromera velia and Vitrella brassicaformis , and have shown that Plasmodium falciparum transcripts do not undergo polyuridylylation . The poly ( U ) sites found on chromerid chloroplast transcripts share some degree of similarity with those of dinoflagellates . Variable or alternative poly ( U ) sites , which appear to be particularly widespread in C . velia , have also been observed in several dinoflagellate species [12] , [16] , [33] , [51] . Furthermore , the association between poly ( U ) sites and tRNA cleavage in V . brassicaformis has previously been suggested for the dinoflagellate Heterocapsa triquetra [43] , [51] . However , unlike in dinoflagellates , polyuridylylation occurs only on specific transcripts in chromerid chloroplasts . To date , only one protein-coding gene that lacks an associated poly ( U ) site has been identified in a peridinin dinoflagellate chloroplast - petD in Amphidinium carterae [15] . Conversely , large numbers of protein-coding genes in both the C . velia and V . brassicaformis chloroplasts lack an associated poly ( U ) site , and these principally encode products that do not directly function in photosynthetic electron transfer . While we could identify a small number of photosynthesis genes in either C . velia or V . brassicaformis that lacked poly ( U ) sites , or transcripts of non-photosynthesis genes that were polyuridylylated ( Table S2 , fig . 2 ) , very few of these exceptions were conserved between both species , and our rps18 circular RT-PCR data suggest that at least some of the poly ( U ) sites associated with non-photosynthesis genes may not be physiologically significant ( Table S5 , panel E ) . Thus , the polyuridylylation of chromerid chloroplast transcripts appears to largely be dependent on a photosynthetic function of the translation product . With this in mind , the function of transcript polyuridylylation in chromerid chloroplasts is particularly intriguing . The high expression level of photosynthesis gene transcripts , which has been suggested to help enable rapid photo-physiological adaptation to changing light conditions [27] , [32] , may suggest that the poly ( U ) tail facilitates transcript accumulation in chromerid chloroplasts . Transcript processing complexes are known to be involved in negative regulation of non-coding transcripts in other organelle lineages [4] , [52] . The presence or absence of a poly ( U ) site might similarly be involved in discriminating between functional and non-functional photosynthesis gene transcripts , such as those of the functional atpH-1 gene and the non-functional atpH-2 gene , and might potentially determine the levels to which they accumulate in chromerid chloroplasts ( fig . 3 ) . Notably , the atpH-2 CDS itself does not contain in-frame premature termination codons , or any other features that would directly prevent its expression . Thus , the loss of a poly ( U ) site on the atpH-2 transcript , and consequent reduction in transcript abundance [32] , could minimise expression of atpH-2 without inactivation of the underlying gene sequence . It remains to be determined whether atpH-2 protein accumulates to a significant level in C . velia chloroplasts , but our data as a whole certainly suggest that poly ( U ) tails may facilitate expression of functional copies of photosynthesis genes in chromerid chloroplasts . One possible means by which the poly ( U ) tail could facilitate gene expression is by coordinating other chloroplast transcript processing events . As polyuridylylated polycistronic transcripts are present in chromerid chloroplasts , poly ( U ) tails might be added relatively early in transcript processing . For certain genes that possess poly ( U ) sites ( petB , psbH ) , polycistronic transcripts accumulate to concentrations detectable in northern blots , but in these and other genes ( e . g . psbA , atpB-2 , atpI ) , monocistronic mRNAs , which have presumably been cleaved from polycistronic precursors , are abundant ( fig . 5 , panels A–C , fig . 6 ) . Similar patterns of transcript abundance have recently been reported for other photosynthesis genes in C . velia by Janouškovec et al . [32] . In contrast to the high levels of transcript processing observed for polyuridylylated genes , transcripts from the rps14 and atpH-2 genes ( which do not contain associated poly ( U ) sites ) are predominantly present as high molecular-weight precursors ( fig . 5 , panels D–F ) , indicating that transcripts are subject to very limited 3′ end processing in the absence of a poly ( U ) tail , and the presence of a poly ( U ) site could be associated with the cleavage of polycistronic transcripts to monocistronic mRNAs . At loci such as C . velia petG-petB-psbH that contain multiple possible poly ( U ) sites , the selection of a poly ( U ) site may define which products are generated . Alternative processing of precursors containing multiple potential photosynthesis gene transcripts has previously been suggested to occur in dinoflagellates [15] , [33] , and is similar to alternative 3′ polyadenylylation sites previously observed in nuclear genomes , which may substantially alter the coding capacity and regulatory properties of nuclear transcripts [53] , [54] . It will be interesting to test how the presence of a poly ( U ) tail may influence the accumulation and expression of polyuridylylated transcripts . For example , polyuridylylated transcripts might be more stable than non-polyuridylylated transcripts following the inhibition of chloroplast transcription , or be more frequently associated with polysomal fractions in chromerid chloroplasts . . The distribution and function of the poly ( U ) machinery in chromerid chloroplasts may underline key events in the evolution of the non-photosynthetic apicoplast found in apicomplexans . The most parsimonious scenario is that transcript polyuridylylation arose in a photosynthetic common ancestor of chromerids , dinoflagellates , and apicomplexans ( fig . 8 , point A ) . It is not possible to determine whether poly ( U ) tails in this common ancestor were added only to photosynthesis transcripts , or were initially applied to all chloroplast transcripts with specificity arising later , as the chloroplasts of peridinin dinoflagellates do not retain any recognisable genes of non-photosynthetic function , which instead have been almost entirely relocated to the nucleus [13] , [55] , [56] ( fig . 8 , point B ) . However , in the common ancestor of chromerids and apicomplexans , the polyuridylylation machinery exclusively targeted transcripts of photosynthesis genes ( fig . 8 , point C ) , with specific exceptions and counterexamples having arisen subsequently in each lineage since their divergence . In each chromerid species , poly ( U ) sites have been lost from a small number of photosynthesis genes , and gained by a few non-photosynthesis genes . In contrast , within parasitic apicomplexans , all of the photosynthesis genes have been lost from the apicoplast , presumably concomitantly with the loss of the associated polyuridylylation machinery ( fig . 8 , point D ) [10] . It is possible that an early ancestor of apicomplexans changed from a photosynthetic to a non-photosynthetic lifestyle , and the poly ( U ) machinery was subsequently lost due to a lack of selective pressure for its retention . Equally , if the presence of a poly ( U ) pathway were essential for the correct processing of photosynthesis gene transcripts , then the loss of the protein ( s ) involved in polyuridylylation might have been a key step in the transition from a photosynthetic to a parasitic lifestyle . Examples are known from parasitic plants where the loss of a consensus transcript processing site appears to precede inactivation of a chloroplast gene , and presumably its eventual loss of the chloroplast genome [4] , [57] . Further analysis of the gene expression machinery of chromerids may provide important insights into the evolutionary steps required to convert a photosynthetic alga into a non-photosynthetic parasite such as Plasmodium .
All work involving human blood was carried out in accordance with the UK Human Tissue Act ( 2004 ) , and we thank our anonymous donors for their blood . Liquid cultures of Chromera velia CCMP2878 were grown in f/2 medium at 18°C , under 30 µE illumination on a 16∶8 h L∶D cycle . Cultures were harvested at 18 days post-inoculation ( mid-log phase ) for RT-PCR , and at 30 days ( early stationary phase ) for northern blotting . C . velia cells were predominantly in coccoid form at all time points harvested . Vitrella brassicaformis CCMP3155 were grown under the same conditions in f/2 medium supplemented with 100 µg/l ampicillin , and 20 µg/l each kanamycin and spectinomycin . Cultures were harvested at approximately two to three months post-inoculation , at which point pigmented colonies of vegetative cells were visible in the culture flask . Amphidinium carterae CCMP 1314 and Phaeodactylum tricornutum CCAP 1055/2 were grown under the same conditions in f/2 medium as previously described [12] , and harvested at 25 days post-inoculation ( mid-log phase ) . Plasmodium falciparum was cultured in donated red blood cells according to a method previously described [58] . Mature cultures of C . velia and V . brassicaformis were pelleted , washed twice with sterile artificial seawater , and resuspended in 1 ml Trizol reagent ( Invitrogen ) /30 mg cells . Each resuspension was ground to a powder in liquid nitrogen in a clean pestle and mortar that had been prewashed in 10% hydrogen peroxide to remove RNase . The powdered cells were resuspended in an additional 1 ml Trizol/30 mg cells , and Trizol phase extraction , DNase treatment and RNA cleanup was performed as previously described [12] , [33] . Each RNA sample was confirmed to be DNA-free through two rounds of direct PCR . Total RNA was harvested from asynchronous P . falciparum culture using Trizol ( Invitrogen ) as previously described [59] . RNA for use in RT-PCR reactions was stored at −80°C in diethylpyrocarbonate-treated water . RNA for use in northern blots was not subjected to DNase treatment , but resuspended immediately following precipitation in formamide , and stored at −80°C . Genomic DNA was harvested from C . velia as has previously been described [11] . Oligo-d ( A ) and gene-specific RT-PCRs were performed for C . velia and V . brassicaformis as previously described [12] . Due to the extreme AT-richness of the genome , P . falciparum PCR reactions were carried out for 30 elongation cycles , with an annealing temperature of 50°C and an extension temperature of 60°C . RNA of C . velia was circularised , and circular RT-PCRs were performed using previously described methods [12] , [33] . Primers for each RT-PCR reaction are tabulated in Table S4 . PCR products were purified using the MinElute PCR cleanup kit ( Qiagen ) . Cloned products were ligated into pGEM-T Easy vector ( Promega ) , transformed into competent Escherichia coli DH5α , and purified with either a GeneJET miniprep kit ( Fermentas ) or a Qiagen miniprep kit prior to sequencing . Products were sequenced using an Applied Biosystems 3730xl DNA Analyzer . Sequences were aligned against the C . velia and V . brassicaformis chloroplast genome using MAFFT ( http://mafft . cbrc . jp/alignment/software/ ) . To identify putative bacterial promoters in the C . velia chloroplast , we extracted the 5′ UTR sequence of each gene , and searched for promoter sequences using the Neural Network Promoter Prediction server [42] ( http://www . fruitfly . org/seq_tools/promoter . html ) . A pilot experiment was performed using the barley chloroplast genome , for which promoters have been extensively characterised [36] , and a cut-off value of 0 . 8 was selected as identifying the highest number of promoters with a minimal false positive rate . To identify putative sequences associated with poly ( U ) sites , alignments of every 3′ UTR sequence , and the 100 bp of genomic sequence downstream of each poly ( U ) site , were constructed . To search for sequences with conserved patterns of purines and pyrimidines , sequences were manually recoded using RY IUPAC nomenclature , as has previously been described [60] . Conserved primary sequences were searched by visual inspection of alignments , by reciprocal BLASTing of each sequence against each other sequence within the alignment , and with three online motif search programs: Bioprospector ( http://robotics . stanford . edu/~xsliu/BioProspector/ ) , Improbizer ( http://users . soe . ucsc . edu/~kent/improbizer/improbizer . html ) , and PhyloGibbs ( http://www . phylogibbs . unibas . ch/cgi-bin/phylogibbs . pl ) . GC contents were plotted using the crude alignments and GeneIOUS Pro ( http://www . geneious . com/ ) . Conserved secondary structures were searched using the locARNA ( http://www . bioinf . uni-freiburg . de/Software/LocARNA/ ) and Carnac web servers ( http://bioinfo . lifl . fr/carnac/ ) . Oligo-d ( A ) RT-PCR products were deposited in GenBank ( Accession numbers KC618536-KC618583 ) . Northern blots were performed using a DIG northern starter kit ( Roche ) . For each blot , 3 µg total cellular RNA was diluted to 20 µl in formamide , melted at 65°C for 5 minutes , snap frozen , and separated by electrophoresis at 100 V on a 1% TBE-agarose gel , containing 500 mg/l guanidine thiocyanate , for 90 minutes . 4 µl DIG-labelled RNA ladder I ( Roche ) , again diluted to 20 µl in formamide , melted and snap frozen , run alongside as a size marker , and a formamide-only lane was run as a negative control . The northern transfer was set up overnight per the manufacturer's instructions , using a positively charged nitrocellulose membrane ( Roche ) . To confirm RNA integrity during electrophoresis , an additional lane of total cellular RNA was run out , stained post-hoc in ethidium bromide , and visualised with UV . The residual gel slices left following compression were likewise stained and visualised to confirm RNA integrity during transfer . Blots were hybridised overnight at 65°C against complementary RNA probes , generated by in vitro transcription of a template sequence , using T7 RNA polymerase and digoxigenin-labelled nucleotides . Template sequences were generated by ligating PCR products against desired regions of the C . velia chloroplast genome into pGEM-T Easy vector sequence ( Promega ) , and amplifying the ligation products using a T7 primer and a PCR forward primer , to generate products containing the short , 49 bp T7 arm of the vector sequence fused to an antisense orientation insert . Probe sequences are tabulated in Table S1 . Hybridisation products were visualised using an anti-digoxigenin/CPD-star system ( Roche ) , per the manufacturer's instructions .
|
Chloroplasts contain their own genomes , containing two broad functional types of gene: genes encoding proteins directly involved in photosynthesis , and genes with a non-photosynthesis function , such as cofactor biosynthesis , assembly of protein complexes , or expression of the chloroplast genome . Thus far , to our knowledge , no chloroplast gene expression pathways in any lineage have been found to target one functional category of gene specifically . Here , we show that a chloroplast RNA processing pathway – the addition of a 3′ poly ( U ) tail – is specifically associated with photosynthesis genes in two species of algae , the ‘chromerids’ Chromera and Vitrella . The addition of the poly ( U ) tail enables the precise processing of mature photosynthesis gene transcripts from precursor RNA , and is likely to be essential for expression of the chromerid photosynthesis machinery . The chromerid algae are the closest photosynthetic relatives of a parasitic group of eukaryotes , the apicomplexans , which include the malaria pathogen Plasmodium . Apicomplexans are descended from algae , and retain a reduced chloroplast , which contains genes only of non-photosynthesis function . We have confirmed that 3′ poly ( U ) tails are not added to Plasmodium chloroplast transcripts . The expression pathways associated with photosynthesis genes have therefore been lost in the evolution of the apicomplexan chloroplast , and this loss could potentially have driven the transition from photosynthesis to parasitism .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"evolutionary",
"biology",
"parasite",
"evolution",
"plant",
"cell",
"biology",
"microbiology",
"marine",
"biology",
"parasitology",
"chloroplast",
"plant",
"science",
"plants",
"divergent",
"evolution",
"forms",
"of",
"evolution",
"phycology",
"biology",
"algae",
"rna",
"rna",
"processing",
"nucleic",
"acids",
"plant",
"evolution",
"molecular",
"cell",
"biology",
"genomic",
"evolution"
] |
2014
|
Evolution of Chloroplast Transcript Processing in Plasmodium and Its Chromerid Algal Relatives
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Development of eye tissue is initiated by a conserved set of transcription factors termed retinal determination network ( RDN ) . In the fruit fly Drosophila melanogaster , the zinc-finger transcription factor Glass acts directly downstream of the RDN to control identity of photoreceptor as well as non-photoreceptor cells . Tight control of spatial and temporal gene expression is a critical feature during development , cell-fate determination as well as maintenance of differentiated tissues . The molecular mechanisms that control expression of glass , however , remain largely unknown . We here identify complex regulatory mechanisms controlling expression of the glass locus . All information to recapitulate glass expression are contained in a compact 5 . 2 kb cis-acting genomic element by combining different cell-type specific and general enhancers with repressor elements . Moreover , the immature RNA of the locus contains an alternative small open reading frame ( smORF ) upstream of the actual glass translation start , resulting in a small peptide instead of the three possible Glass protein isoforms . CRISPR/Cas9-based mutagenesis shows that the smORF is not required for the formation of functioning photoreceptors , but is able to attenuate effects of glass misexpression . Furthermore , editing the genome to generate glass loci eliminating either one or two isoforms shows that only one of the three proteins is critical for formation of functioning photoreceptors , while removing the two other isoforms did not cause defects in developmental or photoreceptor function . Our results show that eye development and function is largely unaffected by targeted manipulations of critical features of the glass transcript , suggesting a strong selection pressure to allow the formation of a functioning eye .
While genes of the retinal determination network ( RDN ) are necessary and sufficient for inducing eye tissue in the imaginal-disc , distinct transcription factors are subsequently involved in promoting the developmental program of cell fate determination as well as terminal differentiation . The zinc-finger transcription factor Glass provides a critical link between the RDN and terminal differentiation . Glass is required during eye development for the differentiation of photoreceptor neurons , patterning of the ommatidia , as well as for the differentiation of cone- and pigment-cells [1–4] . glass mutants were first discovered by H . J . Muller in 1918 and O . L . Mohr in 1919 , and were named after their smaller eyes with smooth , glassy surface and altered pigmentation [5] . While it was initially assumed that photoreceptor precursors undergo apoptosis in glass mutants , we recently showed that these cells adopt a neuronal cell fate , extend axons and form synapses , but fail to express rhodopsins as well as phototransduction genes . For the determination of photoreceptor identity , glass promotes the terminal differentiation gene hazy [1 , 6] . Interestingly glass acts in conjunction with distinct transcription factors to coordinate different cell fates during eye formation . For the specification of cone cells glass acts together with dPax2 , eyes absent and lozenge , while for the formation of pigment cells it requires escargot [4] . Thus , dependent on the cellular context Glass is likely to control distinct developmental programs . However , mechanisms that act to control expression of glass remain largely unknown . We here provide insight into surprisingly diverse regulatory mechanisms acting to regulate the glass locus . By further dissecting a previously identified 5 . 2 kb genomic element we identified a set of regulatory core elements , including a general promotor , two pan-photoreceptor enhancer elements , a reciprocal enhancer element for non-photoreceptor cells , an element driving expression in a subset of photoreceptors as well as an ocelli-specific enhancer element . By analysing a GFP reporter including the 5’UTR we identified an alternative small open reading frame ( smORF ) upstream of the actual Glass translation start , resulting in a small peptide instead of the Glass protein . Interestingly , editing the corresponding genomic sequences to mutate the smORF did not cause any developmental defect nor photoattraction behaviour . However , when misexpressing Glass in a transcript including the smORF it attenuates developmental deficits , suggesting that while evolutionarily conserved within drosophilids the smORF is not essential for eye development , but may act to buffer Glass expression level . Moreover , we assessed the requirement and functionality of the three Glass protein isoforms by CRISPR-mediated genome editing introducing deletions into the glass locus resulting in the loss of one or two of the three isoforms . We analysed these isoform mutants for the morphology of their eyes , the expression of photoreceptor markers that depend on Glass function , photoreceptor activity , and light preference behaviour . We found that the short Glass PB isoform is not able to confer normal eye development and function resulting in a glass mutant phenotype , while the Glass PA isoform alone is fully functional . Our results suggest that the expression of glass is tightly regulated as the development of a functional tissue surprisingly does not result in detectable change in the physiological response or alteration in photoattraction behaviour upon deletion of the smORF . Similarly , only one of the isoforms is critical for eye development . Since sequence comparison to closely related species show conservation of these features , such mechanisms may function to fine-tune gene expression .
In the developing eye , expression of glass is initiated at the morphogenetic furrow in the eye-imaginal disc of third instar larvae and is detectable in the nuclei of all cells posterior to the morphogenetic furrow [7] . The same expression pattern is obtained with a reporter construct containing a 5 . 2 kb DNA fragment upstream of glass [8] , spanning from -4190 bp to the AUG at +960 ( Fig 1A ) [8] . Surprisingly , using this 5 . 2 kb upstream genomic sequence to drive a GFP reporter we observed that GFP expression was barely detectable in the eye imaginal discs ( Fig 1B and 1B” ) . By increasing the gain at the confocal microscope , we were able to detect a weak GFP signal posterior to the morphogenetic furrow , barely above background level ( Fig 1B”’ and 1B”” ) . A closer inspection of our reporter construct revealed the presence of two potential start codons in the 5’UTR of glass , that were also present in the GFP reporter construct , one at position +889 relative to the predicted transcription start , the other at position +955 . Translation from the first start codon , if functional , may compete with the GFP start codon thus generating a protein that overlaps , but is not in frame , with the GFP coding sequence , resulting in the production of a 316 amino acid long protein ( Fig 1B’ ) . To test whether translation of GFP in our reporter construct was affected by the presence of the upstream start codon ( s ) , we generated two additional reporter constructs: one , in which the potential upstream start codons were deleted ( Fig 1C’ ) , and another , in which the GFP start codon was deleted and the GFP coding sequence was brought into frame with the upstream start codons ( Fig 1D’ ) . Both GFP reporter variants resulted in strong GFP expression posterior of the morphogenetic furrow ( Fig 1C , 1C” , 1D and 1D” ) . Thus , the reduced GFP expression observed in the original reporter construct was caused by the translation of the reporter construct in a different reading frame due to the presence of additional start codons upstream of the GFP coding sequence . Since the GFP reporter we used does not contain a nuclear localization signal , GFP produced from its own start codon , as in construct C’ , is mainly localized in the cytoplasm ( Fig 1C”’ and 1C”” ) . However , when GFP was fused in frame with the smORF , it showed strong nuclear localization ( Fig 1D”’ and 1D”” ) , suggesting that the first 24 amino acids added to the GFP coding sequence contain a nuclear localization signal . Indeed , amino acids 2 to 20 of this fusion protein are predicted to affect nuclear localization [9] . Thus , the translation of this fusion protein starts at the first AUG codon at position +889 . In order to understand the cis-regulatory logic of glass expression we further dissected this genomic region in the construct that does not contain the two upstream start codons ( Fig 1C’ ) . Using a number of restriction sites located in the upstream regulatory sequence , we generated truncations of our GFP reporter , similar to those used by Liu et al . [8] , and also tested some deletions within this upstream sequence ( Fig 2A ) . After deleting half of the 5 . 2 kb fragment ( construct B: -1885 to +886 ) , GFP expression is still restricted to the region posterior of the morphogenetic furrow ( Fig 2B ) . Further deletion of a small fragment between the BamHI and EcoRI sites ( construct C: -1598 to +886 ) shows patchy GFP expression in the developing photoreceptor precursors ( Fig 2C ) . While construct B is expressed in all cell types forming the presumptive eye , the expression of construct C is restricted to presumptive photoreceptor cells with variable expression levels ( S1A Fig ) , suggesting that the fragment from -1885 to -1598 might contain some non-photoreceptor specific enhancer . A fragment truncated at the XbaI site ( construct D: -703 to +886 ) is expressed in all the photoreceptor precursors posterior of the morphogenetic furrow with the highest levels directly after the furrow and reduced levels towards the posterior end ( Fig 2D ) . This construct also shows ectopic expression in a stripe anterior of the furrow ( Fig 2D’ arrowhead ) . This misexpression of GFP is spreading over the entire eye-antenna-disc in a construct starting at the XhoI site ( construct E: -239 to +886 , Fig 2E ) , suggesting that this fragment contains a minimal promoter whose activation is independent of eye specific enhancers . We used this minimal promoter region in combination with other fragments of the enhancer to analyse the expression patterns conferred by the 5’ enhancer elements . We tested the 287 bp fragment between the BamHI and EcoRI sites that we suspected to drive expression specifically in non-photoreceptor cells based on the different expression patterns between constructs B and C . We found that this small fragment in combination with the minimal promoter ( construct F: -1885 to -1598 / -239 to +886 ) can restrict GFP expression to the region posterior to the morphogenetic furrow ( Fig 2F ) . With this enhancer fragment , the GFP signal is absent in the presumptive photoreceptor cells and restricted to the cells surrounding the photoreceptor precursors ( Fig 2F”’ , S1B Fig ) . A complementary construct lacking only this small region ( construct G: -4301 to -1906 / -1598 to +886 ) , shows a reciprocal expression pattern posterior of the furrow with expression restricted to presumptive photoreceptors ( Fig 2G ) . The 1 . 2 kb region located at the 5’ end of the glass enhancer fragment in combination with the minimal promoter ( construct H: -4301 to -3123 / -239 to +886 ) , also restricts GFP expression to cells posterior of the morphogenetic furrow ( Fig 2H ) . In this case GFP is only expressed in three of the eight presumptive photoreceptors ( Fig 2H”’ ) . We identified these as R2 , R5 , and R8 using defined markers [10] ( S1C Fig ) . In addition , this part of the glass enhancer is required for expression in the ocelli anlage ( Fig 2G and 2H arrows ) . Finally , the fragment between the two BamHI sites ( construct I: -3123 to -1906 / -239 to +886 ) drives GFP expression in all presumptive photoreceptors ( Fig 2I and 2I’ , S1D Fig ) , similar to construct D , but with lower expression levels directly after the furrow and increasing GFP levels towards the posterior end . Taken together , the 5 . 2 kb glass regulatory region contains a general promoter region ( -239 to +886 ) , an ocelli enhancer region ( -4301 to -3123 ) , that also drives expression in a subset of photoreceptor precursors , a non-photoreceptor enhancer element ( -1886 to -1598 ) , two general photoreceptor enhancer elements ( -3123 to -1906 and -1598 to -239 ) , and a repressor region ( -1598 to -703 ) ( S2A Fig ) . glass expression is directly regulated by Sine oculis , a member of the retina determination network [1] . The 5 . 2 kb enhancer region contains 31 potential Sine oculis binding sites ( altogether 10 sites with a perfect AGATAC consensus sequence [11] and 22 sites with a more degenerate version YGATAY [12] , S2A Fig ) . Expression of a reporter gene driven by the non-photoreceptor enhancer fragment ( -1886 to -1598 ) is lost if the three Sine oculis binding sites present in this fragment are mutated [1] . Thus , Sine oculis might act as a general activator of glass expression by binding to all enhancer elements , while other transcription factors might be binding more specifically to an individual enhancer element conferring expression in only a subset of the cells . We performed an in silico analysis looking for additional transcription factor binding sites in the entire 5 . 2 kb region . We found potential binding sites for 263 different transcription factors including factors that are known to regulate eye development ( p . e . Pph13 , Optix , Otd , Hth , Ey , Dr , Kr , Ato ) ( S2B Fig , S1 Table ) . There are also several potential binding sites for Glass within the photoreceptor enhancer regions suggesting an auto-regulatory function . Our identification of the different enhancer regions will allow more specific testing of the role of these transcription factors in the cell-specific regulation of glass . The upstream start codons in the 5’UTR of glass strongly reduced the expression of our original GFP reporter construct , presumably due to interference with GFP translation and production of a 316 amino acid long protein encoded in the 3rd frame of the eGFP sequence used here . In the glass transcript , translation from the upstream start codon might also interfere with Glass translation producing a 34 amino acid long peptide encoded by the smORF that overlapps with the Glass coding sequence ( Fig 3A ( b ) ) . Interestingly , the 4 nucleotide sequence preceding the upstream start codon ( CAAG ) is more similar to the Drosophila consensus Kozak sequence ( MAAM , whereby M stands for either A or C ) [13] than the sequence upstream of the actual Glass start codon ( TGTC ) ( Fig 3A ) . Sequence comparison with glass genes from other Diptera revealed that upstream start codons are present in all glass 5’UTRs of Drosophilidae as well as in Lucilia , Musca , and Glossina , possibly producing peptides that overlap with the Glass coding sequence ( S3A Fig ) . Although the length of these peptides differs slightly due to insertion and deletion of nucleotide triplets , the frameshift relative to Glass and the amino acid sequence are conserved within the Drosophilidae , suggesting that the encoded peptide itself might have a conserved function ( S3B Fig ) . Interestingly , the N-terminal half of the peptide contains mainly basic residues that can provide a nuclear localization signal , as revealed in the GFP reporter construct that was cloned in frame with the upstream start codon ( Fig 1D ) . The central part of the peptide sequence is more variable and truncated in D . grimshawi , D . virilis , and D . mojavensis , while it is extended in D . wilistoni , L . cuprina , M . domestica , and G . morsitans ( S3B Fig ) . Not surprisingly , conservation is also high in the C-terminal part overlapping the Glass coding sequence . The N-termini of the Glass orthologs of other insects , including mosquitoes , are not conserved , and there are no upstream overlapping open reading frames in these transcripts . Since the 34 amino acid long peptide is encoded by the glass mRNA , it might have a function in eye development . We used the CRISPR/Cas9 technique to introduce small deletions in the peptide coding sequence that will result in a frameshift of the peptide without affecting the Glass coding sequence . We named the resulting smORF alleles “brainy smurf” ( brs ) after the smurf with the glasses . We introduced a double strand break 6 nucleotides downstream of the start codon of the peptide and provided a template for repair that contained a single nucleotide change as well as a single nucleotide deletion ( brs-1nt ) ( Fig 3A ( c ) ) . Glass transcript levels were not significantly altered in these brs-1nt mutants in comparison to the original nos-Cas9 line ( S4B Fig ) . In addition to the single nucleotide deletion provided by the template , we also found several lines that had small indels in the region of the CRISPR site used ( Fig 3A ( d-f ) ) . Although after injection of the gRNA and crossing the G0 flies with a deficiency line that uncovers the glass locus we had selected F1 flies that showed a subtle rough eye phenotype , after establishing stable lines the eyes did not show any morphological defects ( Fig 3B–3F ) . We therefore stained for the expression of different photoreceptor markers . We used w1118 flies as controls , since our brs- lines were in a w- background due to crossing the G0 flies with w;; Df ( 3R ) Exel6178 and the F1 flies with w;; Dr e/TM3 . w1118 control flies have big round compound eyes expressing the phototransduction proteins Rhodopsin1 ( Rh1 ) , No receptor potential A ( NorpA ) , Transient receptor potential ( Trp ) , and Transient receptor potential-like ( Trpl ) ( Fig 3B ) . Adult flies are attracted to light in phototaxis experiments [6] . This is also the case for white eyed mutants ( Fig 3B ) . brs-1nt homozygous flies have normal eyes , expressing all tested markers and show light preference comparable to wildtype flies ( Fig 3C ) . We observed the same phototaxis behaviour and marker gene expression in the randomly generated brs mutations ( Fig 3D–3F ) . The GFP reporter constructs demonstrated that the presence of the upstream start codon can interfere with translation from the actual start codon . To test if this is also the case for the translation of Glass , we introduced a 5 nucleotide deletion at the Glass start codon , putting it into frame with the upstream start codon ( brs-5nt::Glass ) ( Fig 3A ( g ) ) . Again , no changes in glass transcript levels were observed in this line in comparison to nos-Cas9 flies ( S4B Fig ) . From these transcripts , Glass translation starts at the upstream start codon that has the “better” Kozak sequence and fuses the nuclear localization signal encoded by the N-terminus of Brs to the Glass protein . We considered that this could result in higher levels of Glass activity that might interfere with eye development . However , we did not observe any changes in eye morphology , marker gene expression , photoreceptor shape , or light preference ( Fig 3G ) . Thus , the potential increase of Glass protein either does not interfere with its function or is compensated by other mechanisms . To test our hypothesis that the upstream start codon might interfere with Glass translation , we used an over-expression assay . Driving UAS-glass-PA expression with a strong eyeless-Gal4 enhancer results in lethality of the pharate flies ( Fig 3H , Table 1 ) . The flies have severe head defects that prevent them from eclosing with only a small number of escapers ( 0 . 4% ) ( Fig 3I ) . Overexpression of a UAS-brs construct did not affect viability of the flies or their eye shape ( Fig 3J , Table 1 ) , indicating that the small peptide produced does not interfere with eye development . Co-expression of UAS-glass-PA and UAS-brs inserted on different chromosomes showed a similar level of lethality as UAS-glass-PA alone ( 0 , 3% survival rate ) , indicating that the peptide itself does not interfere with Glass function . However , in a construct that contains the peptide coding sequence upstream and overlapping with the Glass PA coding sequence as in the endogenous transcript , the lethality caused by the over-expression of Glass protein was reduced , resulting in a 20 . 3% survival rate , where the adult escapers had normal or smaller eyes ( Fig 3K ) . Therefore , the presence of the Brs peptide itself does not reduce Glass levels . brs only interferes with Glass translation , when directly placed as an upstream overlapping open reading frame in the glass mRNA . glass encodes a 604 amino acid protein containing a transcriptional activation domain and a DNA-binding domain that consists of five zinc-fingers of which the three C-terminal zinc-fingers were shown to be necessary and sufficient for DNA binding [7 , 14] . However , according to FlyBase ( flybase . org ) , the glass gene encodes three different protein isoforms ( Fig 1A ) . The PA isoform contains a complete set of 5 zinc-fingers providing sequence specific DNA binding to the target genes of Glass [3 , 15] . In addition to the Glass PA isoform , two other isoforms are predicted to exist based on expressed sequence tags and sequence conservation [16 , 17] . Failure to splice out the last intron of the mRNA transcript , results in the production of a truncated 557 amino acid Glass PB isoform lacking the second half of the fifth zinc-finger . This version of Glass cannot bind specifically to its target sequence in vitro [14] . Of the 19 cDNA clones whose sequences are available on FlyBase ( flybase . org ) , seven are covering the last and/or the second-last exon , and all seven still contain the last intron , suggesting that this intron is frequently retained in the transcript . The position of the last intron ( intron 4 in Drosophila ) including the stop codon immediately following the exon-intron junction is only present in the glass orthologs of Diptera and Lepidoptera ( S5A Fig ) . In the postman butterfly ( Heliconius melipone ) the stop codon is not located immediately after the exon intron junction but 17 basepairs into the intron . Other arthropods do not have an intron at this position . An extended 679 amino acid long Glass PC isoform , containing all 5 zinc-fingers followed by additional 75 amino acids , is produced by a readthrough of the Glass PA stop codon . The prediction of this longer isoform is based on sequence conservation 3’ of the regular stop codon [18] and was confirmed using the Coding Potential Assessment Tool ( CPAT ) that calculates the coding probability of a DNA sequence using Drosophila statistics [19] . A comparison of the sequence following the Glass stop codon within the higher Diptera shows conservation on the amino acid level suggesting that the extended protein is produced by a direct misinterpretation of the stop codon without shifting the reading frame ( S5B and S5C Fig ) [20 , 21] . The amino acid sequences of the extended Glass proteins from different higher Diptera are highly conserved at their N- and C-termini , but have a central region that is rich in histidine residues of very variable length . Particularly , the Musca and Lucilia Glass PC versions contain a high number of additional amino acids in this central part . The PC sequence is not conserved in other insects including mosquitoes . To test the requirement and function of the three different Glass isoforms in vivo , we introduced specific changes in the endogenous glass locus by CRISPR/Cas9- mediated genome editing , eliminating either one or two of the Glass isoforms ( Fig 4A ) . We used w1118 flies as controls , since our glass deletion lines were in a w- background due to crossing the G0 flies with w;; Df ( 3R ) Exel6178 and the F1 flies with w;; Dr e/TM3 ( Fig 4B ) . Flies expressing only the Glass PA+PC isoforms due to a deletion of the last intron had normal , functional eyes expressing phototransduction proteins like control flies ( Fig 4C ) . In contrast , a deletion that allowed only the production of the truncated PB isoform phenocopied glass amorphic mutations , in which photoreceptors failed to differentiate as revealed by the loss of phototransduction proteins ( Fig 4D ) [1] . We also prevented the production of the PC isoform by adding two additional stop codons at the end of the Glass PA sequence ( PA+PB ) . This had no effect on eye shape or on photoreceptor marker gene expression ( Fig 4E ) . By deleting the last intron and adding stop codons at the end of the Glass PA sequence we generated flies that can only express the PA isoform . These flies also have normal functional eyes expressing all tested markers ( Fig 4F ) . In addition to marker gene expression , we also measured photoreceptor activity by recording electroretinograms ( ERGs ) . We found that all isoform mutants that had normal eye shape and were expressing phototransduction proteins , showed normal ERG responses [22] , while the flies expressing only the Glass PB isoform did not produce any ERG signal in response to light ( Fig 4G ) . When we tested the light preference of our different Glass isoform mutants , we found that all variations expressing the Glass PA isoform showed light preference comparable to wildtype flies ( Fig 4H ) . In contrast , the flies expressing only the Glass PB isoform were photoneutral , with a light preference index that is not significantly different from chance , but significantly different from that of control flies and similar to that of glass mutants , which fail to detect light [6] . Glass is also required for the development of other light sensing organs in Drosophila . In addition to their compound eyes , adult fruitflies have three ocelli on top of their heads expressing Rhodopsin 2 ( S6A Fig ) [23 , 24] , and four photoreceptor cells on each side of the head forming the eyelet , that is located underneath the retina and required for regulation of the circadian rhythm ( S6B Fig ) [24 , 25] . During larval stages 12 photoreceptor cells on each side of the head form the larval eyes ( Bolwig organs ) , with four photoreceptor cells expressing Rhodopsin 5 and the other eight expressing Rhodopsin 6 ( S6C Fig ) [26] . All these visual organs are present in the flies expressing the Glass PA+PC isoforms ( S6D–S6F Fig ) . These photoreceptors are also fully developed in flies expressing the Glass PA+PB isoforms ( S6G–S6I Fig ) and in flies expressing only the Glass PA isoform ( S6J–S6L Fig ) . In contrast , flies expressing only the truncated Glass PB isoform not only show a glass mutant phenotype in their compound eyes , but also don’t have ocelli . We were not able to identify fully differentiated photoreceptors of the Bolwig organ , the eyelet , or the ocelli based on their expression of Rhodopsins or Chaoptin . Therefore , we stained for Krüppel and Spalt , two transcription factors that are already expressed in the Bolwig organ precursors at embryonic stage 12 ( S6M Fig ) , whose expression is maintained at larval stages in wildtype flies ( S6N Fig ) . Krüppel is expressed in all twelve cells , while Spalt is only expressed in the four primary precursors that will later express Rhodopsin 5 ( S6O Fig ) . In stage 12 embryos containing only the Glass PB isoform the Bolwig organ precursors are specified and two cells even express Spalt and Krüppel ( S6P Fig ) . However , at larval stage neither these cell type specific transcription factors nor the rhodopsins are detectable suggesting that the cells lost their identity and probably never reached their final position ( S6Q and S6R Fig ) . To see if the expression of only one or two of the Glass isoforms would affect glass transcript levels , we performed qPCR on the different isoform mutant lines . We used nos-Cas9 flies for comparison since the genomic changes had been introduced in this line using CRISPR . We used a forward primer located in exon 4 in combination with a reverse primer located in exon 5 to quantify the amount of spliced transcript and the same forward primer in combination with a reverse primer located in intron 4 to quantify the amount of unspliced transcript . Since the glPB line has a deletion of the part of exon5 that is bound by the reverse primer , we only tested unspliced transcript levels in this line . Similarly , since intron 4 was deleted in the gl PA+PC and the glPA lines , we only tested spliced transcript levels in these lines . The glass transcript levels in the glPA+PC and in the glPA lines did not differ significantly from control flies ( S4A and S4B Fig ) . We found a slight but significant increase of transcript levels in the glPA+PB line for the spliced as well as the unspliced version . This might be due to higher mRNA stability as result of the loss of translation of the PC isoform or due to higher transcription levels as response to the failure to produce the extended version of the protein . Finally , we found that in the glPB line the amount of unspliced transcript is significantly increased in comparison to the rather small amount found in wildtype flies and reaches a level in the same range as the spliced transcript found in wildtype flies , although due to the different reverse primers used , the expression levels cannot be directly compared . Thus , in the line that shows a glass mutant phenotype due to the loss of production of a functional protein , glass expression is not heavily upregulated . A glass mutant phenotype was also observed in flies in which , after CRISPR-induced DNA double strand break , the DNA repair occurred in form of non-homologous end joining , either deleting the exon-intron junction and the stop codon located in the last intron , or introducing a frameshift at the beginning of the last exon ( S7A Fig ) . Like flies expressing the truncated Glass PB isoform , these flies also have small eyes with a glassy surface . They do not express any of the tested photoreceptor makers , have no ERG response and do not show phototaxis behaviour ( S7B–S7G Fig ) . Thus , although conserved , the extended version of Glass is dispensable in photoreceptors . In contrast , the truncated PB version alone cannot fulfil Glass function , while its absence does not interfere with Glass function in the eye .
The 5 . 2 kb region upstream of the glass start codon had previously been identified as the minimal sequence required for normal Glass expression [8] . The lacZ-reporter construct used in this paper also contained the upstream start codon located in intron 2 . Due to the enzymatic activity of the β-galactosidase , sufficient signal was produced to detect reporter gene activity posterior of the morphogenetic furrow . However , further truncations of the upstream sequence only yielded transgenic lines with weak or variable expression or lines that did not show expression at all . Similarly , our original GFP-reporter construct showed only very weak expression levels even with the same 5 . 2 kb enhancer fragment . After removal of the upstream start codon , expression of our GFP-reporter construct was strongly enhanced allowing us to perform a classical enhancer bashing approach to further dissect the upstream region of glass . We were able to identify different enhancer regions that conferred reporter gene expression in cells posterior to the morphogenetic furrow . The retinal determination network consisting of several transcription factors , specifies the position of the eye field in many different organisms [27] . Sine oculis , a member of the retinal determination network , regulates glass expression by directly binding to sites in the enhancer sequence [1] . Given that all enhancer fragments we tested , showed GFP expression posterior to the morphogenetic furrow , we propose that Sine oculis binds to multiple sites in the 5 . 2 kb enhancer to activate glass expression . In addition to this general reporter gene activation we identified specific enhancer regions driving expression in distinct cell types . For example , the 5’-end of the enhancer that leads to expression in the ocelli anlage and in a subset of the photoreceptors , or the BamHI-EcoRI region that activates expression in non-photoreceptor cells . Thus , other transcription factors binding more specifically to these enhancer elements , might regulate glass expression in a cell-type dependent manner . Stop codon readthrough is relatively abundant in Drosophila [28] . Especially genes expressed in the nervous system are putative candidates for this process [29] . Glass has also been listed as a candidate for this protein extension mechanism based on several criteria [18]: Sequence comparison of the amino acids following the regular stop codon shows a higher conservation within higher Diptera than what is found in the 3’UTR of non-readthrough transcripts . The pattern of nucleotide substitutions also suggests that there is no alteration of the reading frame as it might occur in the case of alternative splicing or ribosome hopping . The most frequent stop codon readthrough context ( UGAC ) [18] , is also found at the Glass PA stop codon . Upon readthrough of a UGA stop codon either arginine , cysteine , serine , or tryptophan can be inserted by a near-cognate tRNA at this position [30] . In our isoform deletion experiments we did not test the conditions at which the stop codon is deleted or replaced by another codon ( Glass PC and Glass PB+PC ) because the function of the resulting protein might be affected by the type of alteration we introduce . Our results from the mutants expressing only the Glass PA isoform suggest , that under laboratory conditions , stop codon readthrough and production of the extended Glass PC version is not required for eye development and photoreceptor function . The Glass PB isoform alone is not functional . Our deletion mutants that can only express this truncated version as well as our other deletions that affect splicing and result in proteins terminating in intron 4 , have a glass mutant eye phenotype , that is: they lack the expression of photoreceptor markers , show no photoreceptor activity and are photoneutral [1 , 6 , 31] . This corroborates previous results that showed that the last three zinc-fingers are essential for sequence specific DNA-binding and that a Glass protein lacking the C-terminal end shows no transcriptional activity [14] . The intron that is retained in the Glass RB transcript , is only found in Diptera and Lepidoptera , suggesting that it originated in the last common ancestor of flies and butterflies . Intron retention can be a means of regulating protein levels since they are usually degraded by nonsense-mediated decay [32] . One of the first examples for cell-type specific intron retention was the Drosophila P-element [33] . In germ cells intron 3 is spliced out resulting in functional transposase production . In contrast , in somatic cells intron 3 is retained resulting in a truncated protein that antagonizes the full-length protein . Intron retention can also generate new protein isoforms like the Drosophila Noble protein [34] . In addition , intron-retaining mRNA transcripts can remain in the nucleus and be spliced upon requirement providing a source of transcript that could be faster activated than by de novo transcription [35] . Recent RNAseq data suggests that intron 4 is not retained in the glass mRNA [4] . The authors found that expression of either the glass RA+RC or the glass RB transcript from transgenic constructs resulted in production of functional Glass protein , suggesting that in their ectopic expression experiments , intron 4 of the RB transcript was spliced out to produce full-length Glass PA ( and PC ) protein . Thus , we would consider the glass RB transcript as an intermediate stage that has been accumulated during cDNA preparation but that can be further processed to encode functional Glass protein . As we show here , the absence of intron 4 in the glass gene allowing only the production of the Glass PA ( and PC ) protein does not affect eye development and function . According to the scanning model of translation initiation [36] , the 40S ribosomal subunit scans the mRNA from the 5’end until it encounters the first AUG codon . Translation will start at this codon , which in the case of glass mRNA would mean that only the Brs protein should be produced . However , under certain conditions , translation can also start at a later AUG codon [37] . One of these mechanisms , called leaky scanning , applies for an upstream AUG with a weak context , were the codon with the weak context is skipped by some ribosomes starting translation further downstream . However , this cannot be the case for Glass translation , since there are two AUG codons upstream of the Glass start codon within exon 2 and both have a better Kozak sequence than the actual Glass AUG . Another mechanism would be reinitiation , where after translation of a small upstream open reading frame , the ribosome can move on and re-acquire a Met-tRNA allowing it to reinitiate translation at the next AUG codon . However , since ribosomes cannot backup , the overlapping open reading frame should profoundly inhibit Glass translation [38 , 39] . It was shown that overlapping upstream open reading frames; and particularly those that have an optimal AUG context , are efficiently removed from the Drosophila genome [40] , suggesting that those that can be found and that are even conserved outside of the most closely related species , have been selected due to a specific function . In the case of Glass , we found evidence that translation from the upstream start codon strongly reduces GFP translation and also interferes with Glass translation when overexpressed . However , this suggests that the endogenous Glass protein would be expressed at very low levels . One possible way to overcome this problem , would be by splicing out exon 2 so that the two upstream AUGs and the Glass AUG would be removed from the transcript . In this case translation would start from an AUG codon in exon 3 ( amino acid 26 of the predicted full-length protein ) . However , there is no evidence , that exon 2 is spliced out of the transcript to produce a truncated Glass version . Another hypothesis would be that Glass translation starts by reinitiation at the AUG codon in exon 3 after translation of Brs . In fact , the Glass proteins of Anopheles darlingi and of Culex quinquefasciatus are predicted to start at this position ( with a conserved motif: MYISC ) , while Anopheles gambiae Glass is predicted to start in an exon located further upstream of the start codons of the other two mosquito species , but with an N-terminal sequence that is not related to that found in Drosophila and other higher Diptera . Also , other insects’ Glass proteins start further downstream than in the Diptera . It could be possible that for most insects the actual Glass translation start has not yet been identified due to higher sequence divergence at the N-termini . This would suggest , that the first 25 amino acids mostly encoded by exon 2 of the Drosophila transcripts are dispensable for Glass function , or that they are only required in higher Diptera . In addition to regulating Glass protein levels by directly interfering with translation efficiency , the Brs peptide could have other functions in the developing eye , where it is expressed along with Glass . Small peptides can have important roles such as hormones , pheromones , transcriptional regulators , antibacterial peptides , etc . [41] . However , we could neither identify such a role for Brs by mutating it , nor by overexpressing it , suggesting that its main role is the regulation of Glass translation . In summary , our results suggest that the removal of intron 4 , which was added in the common ancestor of flies and butterflies , is essential for the production of a functional Glass protein . Stop codon readthrough resulting in an extension of the Glass protein that is conserved in higher Diptera seems to be dispensable for Glass function in photoreceptor development . The addition of an exon containing several AUGs upstream of the Glass start codon found in mosquitoes , can interfere with Glass translation . Nevertheless , conservation of the upstream start codon and sequence conservation of the Brs peptide suggest that higher Diptera have found a way to overcome this interference and that Brs might even have adopted a beneficial function .
Flies were reared at 25°C on a cornmeal medium containing agar , fructose , molasses , and yeast . Strains for site directed integration ( 25709 , 25710 ) , w1118 mutants ( 3605 ) , deficiency lines ( 4431 , 7657 ) [42] , balancer lines ( 36305 , 8379 ) , and nos-Cas9 expressing flies ( 54591 ) [43] were obtained from the Bloomington Drosophila Stock Center . ey-Gal4 expressing flies were a kind gift from R . Stocker . All oligos used for cloning and all sequencing reactions were purchased from microsynth . The following primer sequences show the annealing sequence part in capitals and any additional sequence in small letters . Restriction sites are underlined . A 5257 basepair long PCR fragment was amplified from genomic DNA of CantonS flies using primers “glass -4301 Asc fw” ( 5´-ggcgcgccTAACCCGATACAAATGGAGAGG-3´ ) and glass 5’UTR Not re” ( 5´-gcggccgcGACATGACTCCACTTCTGGAAC-3´ ) . The fragment was inserted into pCR-Blunt II-TOPO vector ( Invitrogen ) . From there it was excised using the restriction enzymes AscI and NotI and cloned into a GFP reporter vector ( pDVattBR , kind gift from Jens Rister ) to generate the basic glass-GFP reporter construct ( Fig 1A and 1B’ ) . The plasmid was injected into y , w; attP2 embryos to produce transgenic flies ( Genetic services Inc . ) . To delete the two upstream start codons , a 1483 bp PCR product was amplified from the original glass-GFP reporter plasmid using primers “glass -597 fw” ( 5’-TAAAAACTACTGAAAACTGCTGCCGATG-3’ ) and “glass exon2 noAUG Pme re” ( 5’-gcgtttaaacGATGCGTTAATTTCCAACTGCAAGGC-3’ ) , TOPO cloned into pCRII , sequenced , digested XhoI-PmeI , and transferred into the original plasmid also cut with XhoI-PmeI , thereby removing the 104 basepairs encoding the N-terminus of Brs , and part of the multiple cloning site of the vector ( Fig 1C’ ) . To put the GFP coding sequence in frame with the upstream start codon , the GFP coding sequence was amplified by PCR using the primers “GFP noStart Not fw” ( 5’-tcgcggccgcgGGTGAGCAAGGGCGAGG-3’ ) putting a NotI site in front of GFP ( starting with the 3rd nucleotide of GFP ) and “GFP down Fse re” ( 5’-GATTATGATCTAGAGTCGCGGCCG-3’ ) covering an FseI and an XbaI site in the plasmid . The PCR product was cloned NotI-XbaI into pBluescript , sequenced , and transferred NotI-FseI into the original glass-GFP reporter plasmid deleting most of the multiple cloning site and the GFP start codon ( Fig 1D’ ) . For the enhancer analysis , the construct lacking the upstream start codons was digested with different combinations of restriction enzymes and religated . For construct B the plasmid was digested with BglII cutting in the multiple cloning site at the 5’-end of the enhancer and with BamHI cutting at position -3123 . A second BamHI site at position -1885 was not in the database sequence but is present in the fragment amplified from the CantonS flies . Therefore , religation of the plasmid after BglII-BamHI digestion ( the two enzymes producing compatible sticky ends ) resulted in an enhancer fragment ranging from position -1885 to +886 . For construct C the plasmid was digested with EcoRI cutting at the multiple cloning site at the 5’-end of the enhancer and at positions -1598 and -2040 in the enhancer . Religation resulted in an enhancer fragment ranging from position -1598 to +886 . For construct D the plasmid was digested with XbaI cutting in the multiple cloning site at the 5’-end of the enhancer and at position -703 . Religation resulted in an enhancer fragment ranging from -703 to +886 . For construct E , construct C was digested with XbaI cutting in the multiple cloning site at the 5’-end and at position -703 in the enhancer as well as with XhoI cutting at position -239 in the enhancer . The two ends were filled using Klenow polymerase and religated resulting in an enhancer fragment ranging from position -239 to +886 . For construct F , construct B was digested with EcoRI cutting at position -1598 and XhoI cutting at position -239 . The two ends were filled using Klenow polymerase and religated resulting in an enhancer fragment ranging from position -1885 to -1598 fused to the minimal promoter fragment from position -239 to +886 . For construct G , the original -4301 to +886 plasmid was digested with NheI cutting at positions -1910 , -1903 , and -682 , the site at position -2179 is missing in our enhancer fragment amplified from CantonS flies . In another reaction the original plasmid was digested with EcoRI cutting at positions -1598 and -2040 . Both reactions were filled using Klenow polymerase , digested with BglII , and then the BglII-NheIfilled fragment was ligated into the BglII-EcoRIfilled fragment fusing the enhancer region from -4301 to -1910 to the region from -1598 to +886 . For construct H , the original plasmid was digested BamHI-XhoI . The two ends were filled using Klenow polymerase and religated to fuse the fragment from -4301 to -3123 to the fragment from -239 to +886 . For construct I , the original plasmid was digested with NheI and in an independent reaction with XhoI . Both digestion reactions were filled with Klenow polymerase . The NheIfilled reaction was further digested with BamHI and the XhoIfilled reaction was further digested with BglII . Then the BamHI-NheIfilled fragment was ligated into the BglII-XhoIfilled plasmid resulting in a fusion of an enhancer fragment ranging from -3123 to -1910 to the minimal promoter ranging from -239 to +886 . All constructs were injected into nos-ΦC31;; attP2 flies for site directed integration . The G0 flies were crossed individually to w1118 flies to screen for w+ offspring . w+ F1 flies were crossed individually to 3rd chromosome balancer flies ( w;; Dr e/TM3 ) and their balanced offspring was crossed inter se to produce stable lines . For the UAS constructs we used the glass cDNA plasmid GH20219 as starting point . This cDNA still contains intron 4 due to incomplete splicing resulting in the RB transcript isoform . To remove the intron , two PCR reactions were set up . One with primers “glass 5’UTR BamHI fw” ( 5’-gaggatCCTCGCCAAAAGTCGCTTCTTG-3’ ) and “glass exon4 re” ( 5’-ccccgactgcgaaaatCTGAGCAGGCAGAGCTTGCAC-3’ ) resulting in a fragment ranging from the 5’-end of the 5’UTR to the end of exon 4 , with the sequence given in small letters of the reverse primer overlapping with the beginning of exon 5 . The other PCR reaction was done with primers “glass exon5 fw” ( 5’-gctctgcctgctCAGATTTTCGCAGTCGGGGAACTTG-3’ ) and “gl Stop Xho re” ( 5’-ggctcgaGTCATGTGAGCAGGCTGTTGCC-3’ ) , resulting in a fragment ranging from the beginning of exon 5 to the PA stop codon , with the sequence given in small letters of the forward primer overlapping with the end of exon 4 . Both PCR products were mixed together to provide the template for another PCR reaction with primers “gl 5’UTR BamHI fw” and “gl Stop Xho re” . The resulting PCR product ranging from the 5’UTR to the PA stop codon without intron 4 was digested with BamHI-XhoI and cloned into pBluescript . After sequencing , different fragments were PCR amplified . The Glass PA coding sequence was amplified with primers “gl Start+Kozak attB1 fw” ( 5’-ggggacaagtttgtacaaaaaagcaggcttcaaCATGGGATTGTTATATAAGGGTTCCAAACT-3’ ) and “gl Stop attB2 re” ( 5’-ggggaccactttgtacaagaaagctgggtcgTCATGTGAGCAGGCTGTTGCC-3’ ) . The brs sequence was amplified with primers “glass+Smurf attB1 fw” ( 5’-ggggacaagtttgtacaaaaaagcaggcttcCGCATCAAGATGAAGCGTAGGAAAAGC-3’ ) and “glass Smurf Stop attB2 re” ( 5’-ggggaccactttgtacaagaaagctgggtcTCAGGAGTTTGGAACCCTTATATAACAATCCC-3’ ) . The brs-glass-PA sequence was amplified with primers “glass+Smurf attB1 fw” and “gl Stop attB2 re” . The primer sequence in small letters are the attB parts used for gateway cloning . The PCR products were gateway cloned into pENTRY201 , sequences , and transferred into the vector pUASg . attB for injection ( Genetic Services Inc . ) . UAS-glass-PA and UAS-brs-Glass-PA were injected into nos-ΦC31; attP40 flies , while the UAS-brs plasmid was injected into nos-ΦC31;; attP2 flies . After balancing the transgenic flies , UAS-glass-RAattP40 and UAS-brsattP2 were combined in a single line: w; UAS-GlassRAattP40; UAS-BrsattP2 . The different UAS-construct bearing flies were crossed to ey-Gal4/CyO flies , and the number of offspring with Cy+ versus the number of offspring with CyO wings was determined . For calculation of the survival rate the number of Cy+ flies was divided by the number of CyO flies ( Table 1 ) . For the alterations of the endogenous glass locus by CRISPR/Cas9 genome editing , we assembled the different templates in pBluescript . For the Glass PA+PC variant , we needed to remove intron 4 from the genomic DNA without changing the sequence at the Glass PA stop codon . Since there were no useful restriction sites between the intron 4 / exon 5 junction and the Glass PA stop codon , we decided to introduce an NdeI site in this sequence by altering a single nucleotide in the third position of the codon for the first histidine residue of the last zinc-finger ( histidine 567 of Glass PA: CAC to CAT ) . We PCR amplified a 932 bp fragment from the genomic DNA of nos-Cas9 flies using primers “glass ex5 R1 Nde fw” ( 5’-gagaattcatatgCGCGTCCACGGCAAC-3’ ) and “glass 3’UTR re” ( 5’-GATCAAAGCACCTGTCTTACATCTACGTCTAG-3’ ) , and a 1529 bp fragment from the intronless glass version assembled in pBluescript for generation of the UAS-glass-PA construct using primers “glass ex4 R1 fw” ( 5’-cggaattcAAGAGTGCGCCGCTTCC-3’ ) and “glass ex5 Nde re” ( 5’-CGCATatgCCGATTCAAGTTCCCCGAC-3’ ) . Both PCR products were combined in pBluescript vector by digesting the one covering the C-terminus from the NdeI site introduced in exon 5 to an endogenous HindIII site in the 5’UTR with NdeI-HindIII , and the one covering exon 4 and part of exon 5 with EcoRI-NdeI ( due to an endogenous NdeI site in the middle of exon4 this part was cloned in two steps ) . The sequence of the resulting fragment ranging from the beginning of exon 4 to the 5’UTR and lacking intron 4 was confirmed . For the Glass PB variant , we introduced a deletion ranging from the end of intron 4 to the middle of the sequence added in the extended Glass PC protein version ( Fig 4A ) . We amplified two PCR products from the genomic DNA of nos-Cas9 flies . A 1866 bp fragment spanning exon 4 and most of intron 4 was amplified with primers “glass ex4 R1 fw” and “glass int4 Xho re” ( 5’-AActcgagGTATAACGTTCCAGGACTGCTC-3’ ) , and a 1287 bp fragment ranging from the middle of the Glass PC encoding sequence to a place located around 500 bp downstream of the glass gene was amplified with primers “glass 3’UTR Xho fw” ( 5’-aactcgagCATCGGCGATTATACTCCACC-3’ ) and “glass down Kpn re” ( 5’-agggtaccTTTATGGTGGCCTCCCAGG-3’ ) . Both fragments were subcloned , sequenced and combined in pBluescript by digesting the one covering exon 4 and intron 4 with EcoRI-XhoI , and the one covering part of the PC coding region , the 3’UTR and donwnstream genomic sequence with XhoI-Acc65I . For the Glass PA+PB variant , we introduced two additional stop codons at the end of the Glass PA encoding part and deleted 29 of the nucleotides following the stop codon . We PCR amplified two PCR products from the genomic DNA of nos-Cas9 flies . A 2034 bp fragment spanning exon 4 , intron 4 , and the PA encoding part of exon 5 was amplified with primers “glass ex4 fw” and “glass RA 3xStop Xho re” ( 5’-ctctcgagctattatcaTGTGAGCAGGCTGTTGCCAC-3’ ) . A 1365 bp fragment spanning most of the Glass RC specific sequence , the 3’UTR and around 500 nucleotides of downstream genomic sequence was amplified using primers “glass RC Xho fw” ( 5’- ttctcgAGCATTACCACCCCCCGC-3’ ) and “glass down Kpn re” . Both fragments were subcloned , sequenced , and combined in pBluescript by digesting the one covering exon 4 , intron 4 , and the Glass PA encoding part plus stop codons with EcoRI-XhoI , and the one covering the Glass PC region , 3’UTR , and downstream genomic sequence XhoI-Acc65I . For the Glass PA variant , we performed a PCR amplification of exon 4 and the 5’-end of exon 5 with the same first primer pair as for the Glass PA+PB template , but using the intronless glass version assembled in pBluescript for generation of the UAS-glass-PA construct as a template . We subcloned this 1638 bp fragment EcoRI-XhoI , sequenced it , and combined it with the 1365 bp fragment spanning most of the Glass RC specific sequence , the 3’UTR and around 500 nucleotides of downstream genomic sequence . For expression of the CRISPR guideRNAs , sense and antisense oligos with overhangs fitting the sticky ends of the BbsI digested vector were annealed and ligated into pU6-BbsI-chiRNA plasmid ( a gift from Melissa Harrison & Kate O’Connor-Giles & Jill Wildonger , Addgene plasmid # 45946 [44] ) . Site 1 ( ctgctcaggtgagtccg/gga ) is located at the junction between exon 4 and intron 4 . Site 2 ( gtccacagattttcgca/gtc ) is located at the junction between intron 4 and exon 5 . Site 3 ( agg/agtgcaggaggtttcca ) guides Cas9 to cut 12 bp downstream of the Glass PA stop codon . Site 4 ( aca/tgggtaactacgactac ) is located in the middle of the Glass PC encoding region ( Fig 4A ) . CRISPR sites were selected based on their position in the glass genomic sequence using a CRISPR site prediction program ( http://tools . flycrispr . molbio . wisc . edu/targetFinder/ [45] ) . The templates for the different Glass isoform variants were co-injected with sgRNA expression plasmids into embryos of nos-Cas9 flies . The Glass PA+PC variant was co-injected with the sgRNA plasmids for sites 1 and 2 . The template for the Glass PB variant was co-injected with sgRNA plasmids for sites 2 and 4 . The template for the Glass PA+PB variant was co-injected with the sgRNA plasmid for site 3 . The template for the Glass PA variant was co-injected with the sgRNA plasmids for sites 1 and 3 . The resulting G0 flies were crossed individually with deficiency lines uncovering the glass locus . Some of the offspring resulting from Cas9 cutting at CRISPR site 1 ( and 3 ) showed a glass mutant phenotype due to CRISPR induced non-homologous end joining ( S7 Fig ) . Irrespective of the eye phenotype the offspring was crossed individually with third chromosome balancer flies ( w;; Dr , e/TM3 ) and analyzed by PCR for the introduced deletions and sequence alterations . The glass genes of those lines that showed changes in the PCR analyses , were sequenced to confirm the introduced changes and identify other alterations that resulted in glass mutant phenotypes . For the deletions in the brs sequence , template sequences were assembled in pBluescript . For the 1nt deletion two PCR products were amplified . A 2759 bp fragment ranging from position -1863 in the glass enhancer region to position +896 in the brs coding sequence was amplified using primers “glass -2700 Kpn fw” ( 5’-tgggtaccGGCAGCAGAGACAGGCTC-3’ ) and “smurf -1nt H3 re” ( 5’-ccaagcttCATCTTGATGCGTTAATTTCCAACTGC-3’ ) . The resulting PCR product was cloned Acc65I-HindIII into pBluescript and sequenced . A 2493 bp fragment ranging from position +899 in the brs coding sequence to position +3392 at the end of exon 4 was amplified from nos-Cas9 genomic DNA using primers “smurf -1nt H3 fw” ( 5’-gaaagcttGGAAAAGCAGGAACAAATGCGCG-3’ ) and “glass exon4 Pst re” ( 5’-ctctgcagGCAGAGCTTGCACTGG-3’ ) . The resulting PCR product was cloned HindIII-PstI into pBluescript , sequenced , and combined with the 5’-fragment . For the 5 nt deletion fusing Brs with Glass , A 2821 bp fragment ranging from position -1863 to +953 in the brs coding sequence just before the second AUG codon was amplified from nos-Cas9 genomic DNA using primers “glass -2700 Kpn fw” and “smurf -5nt BamH Nco re” ( 5’-ccggatcccatggCTCCACTTCTGGAACGTTTGGGC-3’ ) . The resulting PCR product was cloned Acc65I-BamHI into pBluescript and sequenced . A 1632 bp fragment ranging from position +959 just before the Glass start codon to position +2591 in exon 4 was amplified from nos-Cas9 genomic DNA using primers “smurf -5nt Nco fw” ( 5’-ctccatggGATTGTTATATAAGGGTTCCAAACTCCTG-3’ ) and “glass ex4 Not re” ( 5’-aagcggccgcatggtgcatggtcatgttcatgc-3’ ) , cloned NcoIfilled-NotI into pBluescript BamHIfilled-NotI , sequenced , and combined KpnI-NcoI with the 5’-fragment . For expression of the CRISPR guideRNAs , sense and antisense oligos with overhangs fitting the sticky ends of the BbsI digested vector were annealed and ligated into the BbsI digested pCDF4-U6:1_U6:3tandemgRNAs plasmid ( gift from Simon Bullock , addgene plasmid # 49411 ) . The site for the -1nt deletion ( aacgcatcaagatgaag/cgt ) is located at the upstream start codon , the site for the -5nt deletion ( ccagaagtggagtcatg/tca ) is located at the Glass start codon ( Fig 3A ) . The templates for the brs mutations were co-injected with the corresponding sgRNA expression plasmid into embryos of nos-Cas9 flies . The resulting G0 flies were crossed individually with deficiency lines uncovering the glass locus . Some of the F1 flies had a very subtle rough eye phenotype over the glass deficiency–but also over the TM6b balancer . The F1 flies were crossed individually with 3rd chromosome balancer flies to establish stocks , and tested by PCR and restriction digest with either HindIII or NcoI for presence of the introduced changes . Genomic DNA of the glass locus from homozygous candidates was PCR amplified and sent for sequencing . Additional sequence changes due to non-homologous end joining were also identified ( Fig 3A ( d-f ) ) . We used FIMO from the meme suite version 4 . 9 . 1 [46 , 47] with the standard parameter . Drosophila only Position Weight Matrices ( PWMs ) were collected and carefully curated from flyfactorsurvey [48] , Jaspar [49] and Transfac [50] . Eye-antennal-discs were dissected from 25–30 larvae per genotype and experiment . Total RNA was extracted using Trizol ( QIAzol , QIAGEN ) and chloroform . After precipitation the RNA pellets were resuspeded in nuclease-free water and the RNA content determined using NanoDrop ( Thermo Fisher Scientific ) . cDNA was generated using the GoScript reverse transcription system ( Promega ) with oligo ( dT ) primers . qPCR was performed on a Rotor Gene Q cycler ( QIAGEN ) using the KAPA SYBR FAST qPCR Kit ( KAPA biosystems ) . The following primer combinations were used: qPCR Primers were synthetized and HPLC purified at microsynth . All qPCR reactions were set up as duplicates and three biological replicates were performed for each genotype . The thresholds were set manually and the resulting Ct values were analysed using Microsoft Excel to calculate average , standard deviation and statistical significance ( student’s t-test ) . The light preference assays were prepared and performed under red light conditions during the subjective day . Drosophila melanogaster adults of both sexes were used . Given that light perception in Drosophila is affected by age [6] , for consistency , we used <1 day old flies in all our experiments . Without anaesthesia 20–40 flies were taken from food vials and loaded into the elevator chamber of a T-maze . The elevator chamber was descended , and flies were allowed to move freely between the elevator chamber and two plastic tubes for 2 min . A white LED was placed at one end of one testing tube . Thus , only one testing tube was illuminated . After 2 min the elevator chamber was ascended , and flies were not able to move between testing tubes and elevator chamber . We determined the number of flies in the illuminated testing tube ( L ) and the number of flies in the dark testing tube ( D ) as well as the number of flies in the elevator chamber ( E ) . We calculated a preference index as follows: Preferenceindex= ( L−D ) / ( L+D+E ) Light intensity was measured from the distance of the elevator chamber to the LED . The light intensity was 1338 μW/cm2 with a first maximum intensity peak of 16 . 6 μW/cm2/nm at 443 nm with half-widths of around 11 nm and a second maximum intensity peak of 6 . 8 μW/cm2/nm at 545 nm with half-widths of around 62 nm . ERG recordings were obtained as previously described [51] . Briefly , we mounted living flies inside a pipette tip , leaving their heads outside , and immobilised them with a mixture of bee wax and colophony 3:1 , which worked as a glue . We placed the flies inside a dark chamber and applied two electrodes: a ground electrode was positioned inside the head of the fly , and a recording electrode was introduced into the retina . In our stimulation protocol , we illuminated the compound eye with orange light for 5 seconds to transform all metarhodopsin to rhodopsin , switched off the light for 10 seconds , and illuminated again a second time with orange light for another 5 seconds . We recorded the response of photoreceptors to the second stimulus . Eye imaginal discs were dissected from third instar larvae and fixed in 3 . 7% formaldehyde dissolved in phosphate buffer ( PB ) for 20 minutes . Bolwig organs from third instar larvae and ocelli and eyelets in the adult brain were dissected in PB and fixed in 3 . 7% formaldehyde prepared in PB for 25 minutes . For cryosections , we dissected the heads of the flies and fixed them for 20 minutes with 3 . 7% formaldehyde dissolved PB , as previously described [1] . We washed these samples by using phosphate buffer with Triton 0 . 3% ( PBT ) and incubated them overnight in cryoprotected solution ( 25% sucrose in PB ) . Then , we embedded the heads in OCT , froze them , and took 14 μm sections by using a cryostat . All tissue samples ( eye imaginal discs , bolwig organs , adult brains with ocelli , eyelets and cryosections ) were washed with PBT at least 3–4 times and incubated sequentially in primary and secondary antibodies ( each antibody incubation step was performed overnight , washing with PBT ( 3–4 times ) between and in the end of these steps ) . We used Vectashield as a mounting medium . As primary antibodies , we used rabbit anti-GFP ( 1:1000 , Molecular probes , A-6455 ) , rabbit anti-Rh2 ( 1:100 ) [24] , rabbit anti-Rh6 ( 1:10 , 000 ) [52] , rabbit anti-Sal ( 1:500 ) [53] , guinea pig anti-Kr ( 1:200 , a gift from J . Jaeger ) , mouse anti-Rh5 ( 1:50 ) [54] and guinea pig anti-Sens ( 1:800 , courtesy of H . Bellen [55] ) . To stain against phototransduction proteins we used antibodies generated in C . Zuker’s lab: anti-NorpA ( 1:100 ) , rabbit anti-Trpl ( 1:100 ) , both of which were kindly provided by N . Colley . The following antibodies were obtained from Developmental Studies Hybridoma Bank ( DSHB ) at The University of Iowa: mouse anti-Rh1 ( 1:20 , 4C5 ) , mouse anti-Trp ( 1:20 , MAb83F6 ) , mouse anti-FasII ( 1:20 , No . 1D4 ) , mouse anti-Chp ( 1:20 , No . 24B10 ) and rat anti-Elav ( 1:30 , No . 7E8A10 ) . Secondary antibodies were obtained from Molecular probes , and we used the conjugated with the following Alexa fluor proteins: 488 , 568 , and 647 . In addition , we also used Hoechst 33258 ( 1:100 , Sigma , No . 94403 ) .
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Changes of the genomic context can have a profound influence on gene expression . Addition or deletion of transcription factor binding sites can influence when and where a gene is transcribed . Changes in exon/intron structure can affect protein length and composition . Stop codon readtrough results in the production of an elongated version of the protein . Such changes can also reduce the protein levels or even alter protein function . As a consequence , they are usually quickly removed from the genome . Thus , conservation of such traits over more than the most closely related species indicates that they are neutral or even beneficial . In the fruitfly Drosophila melanogaster , the glass gene , which is an important regulator of eye development , combines such features in its transcript , making it a good candidate to investigate these phenomena . In this study we analysed the role of the different Glass isoforms generated by intron retention and stop codon readthrough . We identified several cell- and tissue-specific enhancer elements in the glass regulatory sequence , and found a small open reading frame that interferes with Glass translation . Conservation of these features in other fly species suggests that their potential effects on Glass levels does not interfere with eye development .
|
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2019
|
Multilevel regulation of the glass locus during Drosophila eye development
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Speciation is a continuous process and analysis of species pairs at different stages of divergence provides insight into how it unfolds . Previous genomic studies on young species pairs have revealed peaks of divergence and heterogeneous genomic differentiation . Yet less known is how localised peaks of differentiation progress to genome-wide divergence during the later stages of speciation in the presence of persistent gene flow . Spanning the speciation continuum , stickleback species pairs are ideal for investigating how genomic divergence builds up during speciation . However , attention has largely focused on young postglacial species pairs , with little knowledge of the genomic signatures of divergence and introgression in older stickleback systems . The Japanese stickleback species pair , composed of the Pacific Ocean three-spined stickleback ( Gasterosteus aculeatus ) and the Japan Sea stickleback ( G . nipponicus ) , which co-occur in the Japanese islands , is at a late stage of speciation . Divergence likely started well before the end of the last glacial period and crosses between Japan Sea females and Pacific Ocean males result in hybrid male sterility . Here we use coalescent analyses and Approximate Bayesian Computation to show that the two species split approximately 0 . 68–1 million years ago but that they have continued to exchange genes at a low rate throughout divergence . Population genomic data revealed that , despite gene flow , a high level of genomic differentiation is maintained across the majority of the genome . However , we identified multiple , small regions of introgression , occurring mainly in areas of low recombination rate . Our results demonstrate that a high level of genome-wide divergence can establish in the face of persistent introgression and that gene flow can be localized to small genomic regions at the later stages of speciation with gene flow .
Speciation is a continuous process through which reproductive isolation is established [1–3] . According to the genic view of speciation [4] , when populations are in contact , gene flow is initially restricted at barrier loci ( i . e . loci underlying reproductive isolation ) , leading to the emergence of peaks of genetic differentiation surrounding such barriers; i . e . heterogeneous genomic differentiation [5 , 6] . As speciation progresses , this localised build-up of reproductive isolation spreads to nearby regions due to linkage disequilibrium [4 , 5 , 7] . Once a critical amount of differentiation at multiple barrier loci has accumulated , reduction of the genome-wide effective migration rate will eventually lead to divergence across the entire genome [5 , 7] . This final step of genome-wide congealing may be a rapid and non-linear phase transition under certain conditions , such as when isolating barriers have a polygenic basis or a few strong barrier loci arise [8–10] . Recent empirical genomic studies have revealed regions of high and low differentiation dispersed throughout the genome at early stages of speciation [7 , 11 , 12] . This empirical data has lent strong support to the genic perspective of the speciation process [4] . To-date however , the majority of speciation genomic studies demonstrating heterogeneous genetic differentiation have come from young species or population pairs with low divergence [7 , 11 , 12] . Several thorough genomic studies on old sympatric species pairs exist , including European rabbits [13] , Drosophila species [14] , sunflowers [15] , whitefishes [16] , flycatchers [17 , 18] , wild mice [19] , Mimulus [20] and stick insects [9]; however except in a few cases , such as with Heliconius [21 , 22] , divergence is thought to have occurred during periods of geographical isolation . Distinction between primary and secondary divergence is important for interpreting the patterns of genomic differentiation [12 , 17] . This is because high genome-wide differentiation may have evolved via genetic drift and local adaptation during allopatric isolation , rather than due to divergence with gene flow . Following secondary contact after geographical isolation , heterogeneous genomic differentiation may arise due to introgression . Without a picture of the demographic history , this scenario may be indistinguishable from primary divergence [23] . Despite the fact that the expected pattern of genomic differentiation during speciation is influenced by the timing and duration of geographical isolation [7] , testing different demographic histories has been somewhat neglected by the field [7 , 23] , although this is now changing [17 , 24] . Other factors besides the demographic history of a species pair can also confound patterns of heterogeneous genomic differentiation . For example , variation in recombination rate influences the patterns of genomic differentiation , because local adaptation or background selection in genomic regions where recombination is reduced can elevate differentiation measures and be mistaken for barrier loci [18 , 25 , 26] . Mutation rate variation also influences the patterns of absolute divergence [27] . Regions of low differentiation may be caused by shared ancestral polymorphism rather than gene flow [25 , 28] . Distinction between gene flow and shared ancestral polymorphism is likely easier in more divergent species pairs [27 , 29 , 30] . Furthermore , the use of multiple classical and recently developed methods , such as detection of recent hybrid progeny , ABBA-BABA tests [21 , 31] , model-based inference [32] , and comparisons between allopatric and sympatric pairs [21 , 26] provide a means to distinguish signatures of gene flow from alternative explanations . It is therefore essential to account for factors such as demographic history , recombination rate variation , and shared ancestral polymorphism that can confound the interpretation of genome scan data [7 , 12] . Three-spined stickleback species pairs ( genus Gasterosteus ) span the speciation continuum at varying stages of divergence , making them a model system for speciation research [33 , 34] . To-date genomic research on speciation with gene flow in the stickleback complex has largely focused on weakly divergent species pairs , such as lake-stream ecotypes [35–37] . Such studies have shown that the genomic landscape of differentiation between these recently diverged sympatric or parapatric species pairs is heterogeneous and interspersed with multiple peaks of high differentiation [35 , 37 , 38] . The emerging pattern is consistent with predictions under the genic concept of speciation–i . e . that reproductive isolation is localized in the genome at early stages of divergence [4 , 39] . However , it remains unclear whether such localized differentiation will eventually progress toward genome-wide differentiation in the face of gene flow [40] . Toward the end of the stickleback speciation continuum is a marine species pair in Japan [41 , 42] . The Japan Sea stickleback ( G . nipponicus ) is sympatric with the Pacific Ocean lineage of three-spined stickleback ( G . aculeatus ) ( Fig 1A ) in the waters surrounding the Japanese archipelago ( Fig 1C ) [41 , 43] . Divergence time between the two marine species has been estimated to be 1 . 5–2 million years based on allozyme and microsatellite data [42 , 44] , making it much older than postglacial stickleback species pairs . Divergence between the species may have occurred as a result of the repeated isolation of the Sea of Japan during the Pleistocene , but this divergence scenario remains to be explicitly tested [42 , 44] . A unique feature of the G . nipponicus and G . aculeatus system , relative to postglacial stickleback species pairs , is that a neo-sex chromosome has arisen due to a fusion between a Y chromosome and a previously autosomal chromosome IX ( chrIX ) in the G . nipponicus lineage [41 , 45] . Furthermore , crosses between Japan Sea females and Pacific Ocean males show hybrid male sterility [42] . Previous quantitative trait locus ( QTL ) mapping identified QTL for courtship behaviour on the neo-X and hybrid male sterility on the ancestral-X . However , there are other isolating barriers , such as eco-geographical isolation , temporal isolation , and ecological selection against migrants [42 , 46 , 47] . The combination of these multiple barriers most likely contributes to the strong reproductive isolation in this system [41 , 48] . However , despite such strong divergence , hybrids have been observed where the two species co-occur in Northern Japan [41] and phylogenetic discordance between nuclear and mitochondrial loci suggests some history of introgression during speciation [49 , 50] . Although the Japanese species pair represents one of the furthest points of divergence within the stickleback species complex , speciation remains incomplete . The evolutionary history and genome-wide patterns of genetic differentiation and introgression of this strongly divergent species pair therefore remains an open question . The aim of our study was to address this gap in our knowledge; i . e . to quantify the patterns of genomic differentiation and introgression at a later stage of the stickleback speciation continuum . To this end , we used previously published whole-genome sequences and newly acquired Restriction-site Associated DNA sequencing ( RAD-seq ) data from the Japanese stickleback species pair to determine their evolutionary history and characterise patterns of gene flow between them . Our first aim was to establish how and when divergence took place between G . nipponicus and G . aculeatus . Using thousands of genomic loci and a coalescent modelling approach on the resequence data , we tested a range of divergence scenarios and estimated the timing and duration of isolation , the extent of gene flow and fluctuations in population size . After identifying that the two species have indeed diverged in the face of gene flow , we first used our RAD-seq dataset to investigate patterns of population structure and introgression between the Japanese stickleback species pairs . We then used a comparative genome scan approach with the resequence data , adding G . aculeatus lineage from the Atlantic Ocean [51] as an allopatric control ( Fig 1A , S1 Fig ) . After establishing that gene flow has occurred but that a high level of genomic differentiation has remained , we used two independent measures of gene flow to identify where in the genome introgression has left its mark . We tested whether introgression occurs more frequently in regions of high recombination and whether it occurs in regions with functionally important genes . Our findings suggest a high level of genome-wide divergence can be maintained in the face of gene flow , as introgression is restricted to small , localized genomic regions .
Phylogenetic analysis on 35 , 666 10 kb non-overlapping genome windows on autosomes ( i . e . , excluding chrIX and chrXIX ) using whole genome resequence data on 26 individuals supports a deep split between G . aculeatus ( both Pacific and Atlantic Ocean lineages ) and G . nipponicus ( Japan Sea stickleback ) ( Fig 1A ) . Of all windows , 98 . 8% support the split between species , while only 0 . 51% indicate clustering of fish occurring in Japan ( the Japanese Pacific Ocean G . aculeatus and the Japan Sea G . nipponicus; S1 Table and Fig 1A ) . We calculated genealogical sorting index ( gsi ) [52] on maximum likelihood phylogenies estimated from non-overlapping sliding windows of 10 kb across the autosomes . High gsi indicates monophyly , while low gsi indicates mixed ancestry [52] . Genome-wide averages ( ± SD ) of gsi were high , but not complete , for all three Gasterosteus lineages with that of the Japan Sea stickleback being the highest ( Atlantic gsi = 0 . 45 ± 0 . 10 , Pacific gsi = 0 . 57 ± 0 . 09 , Japan Sea gsi = 0 . 72 ± 0 . 06 ) . This is in stark contrast to the mitogenome phylogeny where sticklebacks from both species occurring in Japan fall into a single clade separate from the clade occurring in the Western Pacific and Atlantic ( Fig 1B , S2 Fig ) . A lack of mitogenome divergence between G . aculeatus and G . nipponicus from the Japanese archipelago suggests mitochondrial introgression might occur where these lineages overlap ( Fig 1C ) . Since the consensus autosomal phylogeny suggests a more recent split between the Japanese Pacific and Atlantic G . aculeatus lineages than the split in the mitochondrial phylogeny , the two mitogenome clades may represent the split between G . aculeatus and G . nipponicus lineages with mitochondrial introgression likely having occurred from the Japan Sea G . nipponicus into the Pacific Ocean G . aculeatus in sympatry . Divergence time estimates between the mitogenome clades are thus informative for dating the divergence time between G . aculeatus and G . nipponicus lineages . Bayesian coalescent analysis using a strict clock model in Bayesian Evolutionary Analysis by Sampling Trees ( BEAST ) suggests a median split date of 1 . 30 million years ( 0 . 15–2 . 41; 95% Highest Posterior Density [HPD] intervals; S2 Table ) for the two major mitogenome clades ( S2 Fig ) , consistent with previous estimates [49] . Divergence between Eastern Pacific and Atlantic haplotypes is more recent at 0 . 39 million years ( 0 . 03–0 . 74; 95% HPD ) but is older than the Most Recent Common Ancestor ( MRCA ) of all haplotypes occurring in Japan ( Fig 1B , S2 Fig ) , suggesting mitochondrial gene flow from G . nipponicus to G . aculeatus may have occurred within the last 0 . 39 million years . To investigate the demographic history of G . aculeatus and G . nipponicus , we first used pairwise sequential Markov coalescent ( PSMC ) on all 26 Atlantic Ocean , Japan Sea and Pacific Ocean resequenced stickleback genomes to examine fluctuations in effective population size . Strikingly , G . nipponicus experienced a severe bottleneck around 0 . 15–0 . 3 million years before present ( BP ) ( Fig 1D ) ; mean Ne fell to 26 , 422 ± 1 , 191 at its lowest point . Subsequently after 0 . 1 million years BP , G . nipponicus underwent a dramatic effective population size expansion ( Fig 1D ) : mean Ne rose to 195 , 974 ± 28 , 832 ( i . e . ~7 . 5 times increase from the bottleneck ) during the late Pleistocene . In contrast , the effective population size of the Japanese Pacific Ocean G . aculeatus has remained relatively stable throughout its history ( mean Ne ± SD = 118 , 150 ± 4 , 330; Fig 1D , see S3 Fig for bootstrap support ) . Although the Atlantic ( Fig 1D ) and Western Pacific lineages of G . aculeatus ( S4 Fig ) also experienced some growth during the late Pleistocene , their effective population sizes remained smaller than that of G . nipponicus . Cryptic population structure in G . nipponicus might explain the disparity in Ne between lineages; however our RAD-sequence dataset confirms substructure is not present in this species ( see below for more details on RAD-seq dataset; S5 Fig and S6 Fig ) . Furthermore , genome-wide averages of Tajima’s D also support a recent demographic expansion for G . nipponicus ( mean ± SD of Tajima’s D = -0 . 82±0 . 45 ) and stable effective population size in the Pacific Ocean ( mean ± SD of Tajima’s D = -0 . 04 ± 0 . 63 ) . To explicitly test whether divergence between G . aculeatus and G . nipponicus occurred in the presence of gene flow , we used an Approximate Bayesian Computation ( ABC ) approach with 1 , 874 2 kb loci randomly sampled from across autosomes . We tested five divergence scenarios–isolation ( I ) , isolation with migration ( IM ) , isolation-with-ancient-migration ( IAM ) , isolation-with-recent-migration ( IRM ) and isolation-with-ancient-and-recent-migration ( IARM ) –i . e . two discrete periods of contact . Since the results of our PSMC analyses indicate Ne has varied throughout divergence ( Fig 1D ) , we performed a hierarchical ABC analysis , first selecting the most appropriate population growth model ( i . e . constant size , population growth and a Japan Sea bottleneck ) within each divergence scenario and then performing final model selection amongst the best supported divergence/growth model scenarios ( see S1 Text for full specification of models , priors , parameters and extensive sensitivity testing ) . Using 20 summary statistics ( see S1 Text for a full list of statistics used ) and a neural-network rejection method with 1% tolerance of simulated datasets , the best-supported divergence scenario was a model of IM with a bottleneck occurring only in the Japan Sea species ( Fig 2A , Table 1 ) . An IARM model was the second best supported model . The use of a standard ABC rejection method gave rise to the qualitatively similar results and we found no evidence of an overrepresentation of introgressed regions in the loci used as the observed data for this analysis ( S1 Text ) . An independent maximum likelihood based demographic analysis using the joint G . aculeatus and G . nipponicus site frequency spectrum ( SFS ) derived from RAD-seq data showed high support for an IARM model ( see S1 Text ) . Parameter estimates from the ABC IM model suggest divergence between G . aculeatus and G . nipponicus occurred 0 . 68 million years ago ( median estimate , 0 . 18–4 . 17 million years , lower & upper 95% HPD; Fig 2B ) . A Japan Sea bottleneck occurred 0 . 3 million years ago ( 0 . 03–2 . 21 million years 95% HPD ) , reducing Ne to about 20% of the contemporary estimate ( Fig 2C , S3 Table ) . Mean migration rates between the two species were low , and migration rate ( expressed as mij−i . e proportion of population i that are migrants from j per generation ) from the Pacific Ocean lineage into the Japan Sea lineage ( m12: median = 1 . 3 x 10−6 , 95% HPD = 8 . 61 x 10−8–5 . 32 x 10−6 ) was slightly greater than in the opposite direction ( m21: median = 1 . 05 x 10−6 , 95% HPD = 4 . 91 x 10−8–6 . 39 x 10−6 , N . B . migration rates are backwards in time; see also Fig 2D & S3 Table ) . In addition to this , the distribution of the migration rate hyperprior suggested that a large number of loci showed some level of gene flow ( S1 Text ) . Contemporary Ne of the Japan Sea lineage is larger than that of the Pacific Ocean , although the Ne estimates differed in magnitude from those estimated by PSMC ( Figs 1D and 2C , S3 Table ) . Given this difference in effective population size , the scaled migration rates , the expected number of migrants per generation , ( 2Nimij ) are higher from Pacific Ocean lineage into the Japan Sea than the alternative ( PO to JS = 0 . 18; JS to PO = 0 . 04 ) in contemporary populations , although still very low . Scaled migration rates were likely more similar during the Japan Sea bottleneck , because lower effective population size of the Japan Sea population ( 1 . 22 x 104 ) at this stage reduces the expected number of migrants from the Pacific Ocean to the Japan Sea ( 0 . 031 ) . Identifying admixture and the presence of backcrossed individuals between species where they co-occur provides strong evidence of on-going introgression [7 , 12] . To address this , we used a RAD-sequencing dataset with a larger sample size of 245 individuals from the Atlantic , Pacific and Japan Sea lineages , including previously published data from Pacific-derived populations in North America [53] . Principal component analysis ( PCA ) of allele frequencies at 3 , 744 high-quality bi-allelic SNPs pruned to remove loci in linkage disequilibrium showed that , consistent with our whole genome data , the main axis explaining 20% of the variance was between G . aculeatus and G . nipponicus ( S5 Fig ) . The secondary axis explaining 9 . 49% of the variance was mainly between the Atlantic and Pacific populations ( S5 Fig ) . Importantly , PCA showed a single individual was intermediate between the Pacific and Japan Sea populations occurring in Akkeshi , the sympatric site in Hokkaido , Japan where our whole genome-sequenced samples were collected ( Fig 1C ) . A separate Bayesian analysis for admixture using STRUCTURE [54 , 55] found greatest support for K = 2 among stickleback populations and also identified the putative F1 hybrid plus individuals with possible recent admixture in Akkeshi ( S6 Fig ) . To further investigate variation in individual ancestry , we identified 5 , 967 ancestry-informative loci i . e . autosomal SNPs with an allele frequency difference of >0 . 8 between the Japan Sea and Pacific Ocean lineages . Using a genomic cline approach , we estimated interspecific heterozygosity ( i . e . , proportion of loci with alleles from both species ) and hybrid index ( i . e . , proportion of alleles from one species ) on simulated hybrid genotypes . This indicates the marker set has high power to detect hybrid ancestry ( S7 Fig ) . Analyses on the observed data suggest the RAD-seq dataset includes one F1 hybrid and several individuals with likely hybrid ancestry in the last few generations ( S7 Fig ) . Taken together , these data indicate that divergence between the Japanese G . aculeatus and G . nipponicus is much older and greater compared to commonly studied postglacial stickleback species pairs . Despite the great extent of divergence between Japanese stickleback species , parameter estimates and observational data suggest that gene flow between them is on-going . Genome-wide differentiation was strikingly high between G . nipponicus and G . aculeatus regardless of their geographical overlap ( Fig 3A & 3B and Fig 4 , and S8 Fig and S9 Fig ) . The genome-wide average of FST between the sympatric species was 0 . 628; this is higher than FST in all other studied stickleback species pairs , which is typically less than 0 . 3 [35–37 , 56] ( see Fig 3C ) . The genome-wide average of absolute divergence ( dXY ) was 0 . 012; which is also high compared to previously calculated dXY values , i . e . less than 0 . 005 , between postglacial parapatric and sympatric stickleback ecotypes [35 , 57 , 58] . Despite consistently high divergence , both FST and dXY values were significantly lower where the two species occur in contact ( Table 2 , Figs 3 & , 4 , S8 Fig and S9 Fig; 10 , 000 replicate permutation tests on 10 kb windows: P < 2 . 2 x 10−16 for both statistics ) , consistent with the presence of gene flow in sympatry . A more fine-scale analysis of genome-wide divergence based on 10 kb non-overlapping windows revealed that the high baseline divergence between G . nipponicus and G . aculeatus is interspersed by regions of low differentiation in both FST and dXY genome scans ( Fig 4 top two panels , S8 Fig and S9 Fig ) , possibly indicating introgression . To identify genomic regions of recent introgression , we calculated two independent measures . The first of these was GMIN , the ratio of the minimum dXY to the average dXY [30] . Under strict isolation , minimum dXY relates to the upper bound of divergence time between two populations , whereas when introgression occurs , minimum dXY reflects the timing of the most recent migration event [30] . The second measure was fd , an estimate of the proportion of introgressed sites in a genome window , calculated using a four population ABBA-BABA test [59] . GMIN is more effective at identifying recent , low level gene flow than either FST or dXY but by definition it is unable to detect genomic regions where complete introgression has occurred [30] , which can however be detected using fd . Importantly , both measures are robust to variation in recombination rate [30 , 59] . Combining these two statistics therefore allows us to identify both low-level ( GMIN ) and strong introgression ( fd ) . Focusing on between species comparisons , mean ( ± SD ) GMIN measured from 10 kb non-overlapping windows was greater in allopatry than sympatry ( Japan Sea vs . Atlantic: 0 . 876 ± 0 . 071; Japan Sea vs . Pacific: 0 . 857±0 . 103; randomization test P < 2 . 2x10-16; Fig 4 ) . Mean fd was also greater when the species overlapped ( JS vs . AT: -0 . 0031 ± 0 . 0540; JS vs . PO: 0 . 0039±0 . 0328; P < 2 . 2x10-16; Fig 4 ) , and both statistics are more strongly negatively correlated in sympatry ( S10 Fig ) supporting gene flow between G . nipponicus and Japanese populations of G . aculeatus . Genomic regions of low GMIN ( i . e . GMIN valleys ) may indicate recent introgression . We identified genome windows with low GMIN values using a Hidden-Markov classification model [60] ( S11 Fig ) . We then clustered 10 kb outlier windows occurring within 30 kb of one another into putative GMIN valleys . GMIN in particular may be susceptible to false positives as a result of shared ancestral polymorphism . However , lower dXY and higher fd in sympatric GMIN valley windows compared to the genomic background suggests shared ancestral polymorphism alone does not explain the patterns observed here ( S12 Fig; randomization test , P < 2 . 2 x 10−16 in both cases ) . These regions of introgression were more common in the genome when the two species overlapped , with 637 valleys in sympatry ( JS-PO comparison ) compared to 337 in allopatry ( JS-AT comparison ) ( randomization test , t = 5 . 35 , P < 2 . 2 x 10−16 ) and a greater number of valleys per chromosome ( Fig 5A ) , although mean valley size did not differ significantly ( 77 . 6 kb and 75 . 4 kb in sympatry and allopatry respectively , P = 0 . 82 ) . Interestingly , 225 valleys were shared between JS-PO and JS-AT comparisons ( Fig 4 ) . These shared valleys may indicate shared ancestral polymorphism but they may also reflect introgression from Pacific Ocean to Japan Sea , where one or a few Japan Sea individuals carry haplotypes derived from Pacific Ocean and therefore are also similar to Atlantic Ocean haplotypes too . However , a larger number of valleys ( 412 valleys ) were unique to the JS-PO comparison , where introgression might occur from Japan Sea to Pacific Ocean . A similar geographical comparison of peaks of fd between species was not possible , due to the fact that fd is much closer to 0 in the comparison between G . nipponicus and the Atlantic G . aculeatus and very few peaks were present ( Fig 4 ) . Nonetheless , Hidden-Markov classification identified 823 fd peaks occurring between G . nipponicus and Pacific G . aculeatus ( S13 Fig ) . If the fd peaks mainly indicate introgression from Pacific Ocean to Japan Sea , dXY between Japan Sea and Atlantic Ocean is expected to be lower in these regions compared to the genome background , as Japan Sea fish carry haplotypes derived from the Pacific Ocean , which in turn are similar to the Atlantic Ocean haplotypes . While JS-AT dXY was lower in fd peaks compared to the genome background ( JS-AT mean dXY ± SD , fd peaks: 0 . 0121±0 . 0035 , genome-background: 0 . 0127±0 . 0026; one-tailed permutation test , P < 2 . 2 x 10−16 ) , this difference was not very clear ( S14 Fig ) . In contrast , if introgression occurred mainly from Japan Sea to Pacific Ocean , dXY in the PO-AT comparison should increase in fd peaks relative to the genome background , as Pacific Ocean fish carry Japan Sea-derived haplotypes , which are divergent from the Atlantic Ocean haplotypes . We clearly observed this pattern ( PO-AT mean dXY ± SD , fd peaks: 0 . 0065±0 . 0035 , genome-background: 0 . 0038±0 . 00182; P < 2 . 2 x 10−16; S14 Fig ) ; suggesting that introgression from Japan Sea to Pacific Ocean may be more predominant than the opposite direction . Importantly , our findings using GMIN , dXY and fd are robust to different missing data thresholds and did not change when phased vs . unphased data is used ( S1 Text ) . To further investigate the direction of gene flow , we used partitioned D statistics ( an extension of the four population test–see S15 Fig ) , which tests the excess of shared derived alleles using five , rather than four populations [61] . To this end , we added an allopatric Japan Sea population ( collected from Lake Shinji , a brackish lake at the Japan Sea coast of southern Honshu ) . A positive D12 statistic is proposed to indicate the predominance of introgression from P3 to P2 ( S15 Fig ) [61] . When P3 was set to Japan Sea ( where P31 is sympatric and P32 is allopatric with the Pacific Ocean ) and P2 to Pacific Ocean ( see S14 Fig ) , D12 was significantly positive in fd peaks ( one-tailed permutation test , P < 2 . 2 x 10−16 ) . In contrast , when we rotated the populations at the tips–i . e . setting P2 to sympatric Japan Sea , P31 to Pacific Ocean , and P32 to Atlantic Ocean ( see S15 Fig ) , D12 was not positive , consistent with the suggestion that introgression is occurring mainly from Japan Sea to Pacific Ocean . However , the resolution of partitioned D statistics has been criticized [62]; positive D12 can also be caused by introgression from the Pacific Ocean ( P2 ) to the common ancestor of the sympatric and allopatric Japan Sea populations ( P31 & P32 ) . To overcome this issue , we calculated DFOIL , which also uses a five-population test but accounts for all possible introgression events [62] . When P1 = sympatric Japan Sea , P2 = allopatric Japan Sea , P3 = Pacific Ocean , and P4 = Atlantic Ocean ( S16 Fig ) , DFOIL clearly indicated the presence of ancestral introgression ( 239 out of 4 , 236 100 kb-windows ) between the Japan Sea ancestor ( P12 ) and the Pacific Ocean ( P3 ) ( see S15 Fig ) . However , we found only a few windows showing unidirectional introgression ( 6 in total ) , meaning we cannot determine the direction of introgression using this analysis ( S16 Fig ) . This low sensitivity may be due to the fact that structuring in the Japan Sea lineage is very low ( S6 Fig ) [63]–i . e . recent divergence time between the sympatric and allopatric Japan Sea populations or high intraspecific gene flow within the Japan Sea species . To investigate whether introgression co-varies with recombination rate , we used a previously published recombination map from an Atlantic G . aculeatus cross [64] to interpolate genome-wide recombination rate variation ( see Methods ) . We detected a negative correlation between recombination rate and GMIN and a positive correlation with fd ( Pearson’s correlation , GMIN: r = -0 . 17 , P < 2 . 2 x 10−16; fd: r = 0 . 08 , P < 2 . 2 x 10−16 , S17 Fig ) . Accordingly , mean recombination rate for putatively introgressed regions was over two times higher than the genome background ( GMIN: valley = 8 . 98 cM/Mb , non-valley = 3 . 99 cM/Mb; fd: peak = 9 . 64 cM/Mb , non-peak = 4 . 16 cM/Mb; randomization test P < 2 . 2 x 10−16 in both cases; Fig 5B ) . Sex chromosomes likely played an important role in speciation between G . aculeatus and G . nipponicus [41 , 45] . A fusion between Y and chrIX means that chrIX segregates as a neo-sex chromosome in G . nipponicus but not G . aculeatus which only carries the ancestral and shared sex chromosome , chrXIX [41 , 45] . The divergent XY ( G . aculeatus ) and X1X2Y ( G . nipponicus ) systems means that recombination is reduced for chrIX and chrXIX in hybrids carrying the neo-Y [45] . Given this recombination rate reduction and previously identified QTL for traits involved in reproductive isolation that map to chrIX and chrXIX [41 , 45] , we tested whether recent introgression ( i . e . measured using GMIN ) was reduced in this part of the genome relative to the autosome . For this , we repeated our analyses using females only ( 5 Japan Sea and 6 Pacific Ocean ) . The number and density of valleys was lowest on the neo-sex chromosome , chrIX ( 16 valleys or 0 . 8 valleys per Mb ) but not on the ancestral sex chromosome ( chrXIX , see S4 Table ) . Finally , we investigated the nature of introgression between the two species . We first asked whether introgression occurs more frequently in genic or non-genic regions . We identified 3 , 261 genes occurring in GMIN valleys and 2 , 958 genes from fd peaks between sympatric G . aculeatus and G . nipponicus; 60% of genes identified were found in both types of introgressed window , whereas 23% occurred only in GMIN valleys and 15% only in fd peaks ( S18 Fig ) . Irrespective of the method used to detect putatively introgressed regions , the number of genes identified was greater than the number expected by chance ( P < 0 . 0001 based on a null distribution generated from 1 , 000 random samples of the genome ) . Mean recombination rate was higher in the genomic windows where genes are present compared to the genomic background ( gene windows = 4 . 92 cM/Mb , genome-background = 4 . 24 cM/Mb; permutation test: P < 2 . 2 x 10−16 ) . This suggests that introgression may be more likely in genic regions of the genome than non-genic regions , which can be partly explained by higher recombination rates in genic regions . To further investigate the functional enrichment of the genes occurring in regions of introgression , we performed gene ontology ( GO ) analysis on 2 , 310 GMIN valley and 2 , 217 fd peak genes with orthologs in the human genome . Enriched GO terms for fd peaks included immune response , metabolic processes and chromatin assembly , while enriched GO terms for GMIN valleys included major histocompatibility complex ( MHC ) protein and metabolic processes ( S5 Table & S6 Table ) .
Determining the demographic and evolutionary history of species pairs is an important first step for understanding how speciation has unfolded in any system [7 , 12] . Our present study has produced several lines of evidence indicating that divergence between the Japanese sticklebacks has occurred in the presence of gene flow . Firstly , our ABC analysis supported a model of isolation with migration . Previously , it has been speculated that the Japan Sea stickleback diverged largely as a result of geographical isolation in the Sea of Japan caused by sea level fluctuation during the early Pleistocene [42 , 44] . Using ABC , we were able to explicitly test several divergence hypotheses in a statistical framework [65]; our findings suggest that gene flow has likely occurred throughout majority of the divergence history . It should be noted that ABC and most established demographic inference methods perform poorly when resolving the timing of gene flow between lineages [66 , 67] . Therefore , one caveat to the interpretation of our ABC results is that we cannot rule out the possibility that the two species diverged in repeated cycles of contact ( i . e . akin to our IARM model which had the second highest level of support; Table 1 ) , but these periods of contact were simply too close in time . Our independent SFS-based demographic analysis using RAD-seq data also suggested higher support for an IARM model than for an IM model . Nonetheless , the posterior probabilities from models with migration in the ABC analysis overwhelmingly support a scenario of divergence with a period of gene flow irrespective of the timing or nature of the actual speciation event . The presence of extant recent hybrids in sympatry also strongly indicates that introgression is still on-going . In several cases of sympatric pairs of highly diverged species [68–70] , hybrids beyond F1 are found and provide strong evidence for on-going gene flow . We observed a probable F1 hybrid in the wild and several other individuals with evidence of recent hybrid ancestry in our RAD-seq dataset , consistent with previous studies that observed wild caught hybrids [41 , 71] . This provides direct observation of admixture in the wild . Lower levels of genome-wide divergence ( both FST and dXY ) between sympatric pairs compared to allopatric pairs also indicate the presence of gene flow . Our GMIN and fd genome scans showed a higher number of putatively introgressed regions between G . nipponicus and Japanese Pacific G . aculeatus than between G . nipponicus and Atlantic G . aculeatus , suggesting that introgression has been occurring even after the Atlantic and Pacific stickleback populations diverged approximately 390 , 000 years BP . Our partitioned D statistics demonstrated that gene flow from G . nipponicus into Japanese Pacific G . aculeatus may be more predominant than the opposite direction in sympatry . Contrasting mitochondrial and nuclear genome phylogenies are also consistent with the presence of gene flow . Mitochondrial introgression has likely occurred from G . nipponicus into G . aculeatus at some point in the last 0 . 39 million years . Our mitogenome phylogeny confirmed previous findings that there is no mitochondrial structure that distinguishes between the G . nipponicus and Japanese populations of G . aculeatus [49 , 50] . This is in contrast to our nuclear autosomal phylogeny which showed that majority of the genome supports a clear split between G . nipponicus and G . aculeatus occurring in Japan and that the latter shares a more recent common ancestor with Atlantic European G . aculeatus populations . In short , mitogenome data clusters the Gasterosteus lineages by geography , while the nuclear data clusters them by species . Disparities in effective population size between lineages are a common cause of unidirectional mitonuclear introgression with introgression likely occurring from a larger to a smaller population [72] . Our reconstruction of temporal variation in effective population size using PSMC showed a rapid population expansion of G . nipponicus during the late Pleistocene that created a large demographic disparity with the G . aculeatus Pacific Ocean lineage . Although it should be noted that admixture and cryptic population structure can increase effective population size estimates when using PSMC [73 , 74] , we found no evidence of clear population structure in the Japan Sea lineage ( S6 Fig ) . Furthermore , both Japan Sea and Pacific Ocean individuals were sequenced to very high mean coverage ( 80X ) , therefore differences in depth of coverage are very unlikely to explain the PSMC results [75] or introduce bias into our ABC analysis . Unidirectional mitochondrial introgression might also be caused by female mate choice [76] . Our previous behavioural studies indicate that Japan Sea females often mate with Pacific Ocean males , while Pacific Ocean females rarely mate with Japan Sea males [41 , 42] . Hybrid females from Japan Sea female and Pacific Ocean male crosses are fertile [42] and will carry Japan Sea mitochondrial DNA . Backcrossing of these hybrids to Pacific Ocean males would result in unidirectional mitochondrial introgression from the Japan Sea to Pacific Ocean . Compared to young species pairs , less is known about the patterns of genomic differentiation at more advanced stages of speciation with gene flow . Our ABC analyses placed the estimated divergence time of G . aculeatus and G . nipponicus at 0 . 68 million years BP . Similarly , our Bayesian coalescent analysis of mitogenome divergence revealed a 1 . 3 million year split between the Japanese and Atlantic-Pacific Gasterosteus mitochondrial clades . Both mitochondrial and nuclear split estimates suggest that divergence between G . aculeatus and G . nipponicus occurred well before the end of the last glacial period . Therefore the Japanese stickleback system is older than all other previously examined postglacial sympatric or parapatric species pairs , which have typically diverged within the last 20 , 000 years [33] . The Japanese stickleback system also has a mean genome-wide FST and dXY values higher than any other sympatric or parapatric stickleback species pair studied so far such as lake-stream or freshwater-anadromous pairs ( Fig 3C ) [36 , 38 , 57]; placing this pair at the furthest end of the speciation continuum . The primary explanation for the observed elevated divergence is most likely the more ancient divergence time of the Japan Sea-Pacific Ocean species pair compared to postglacial species pairs [38 , 77] . However , the results of our demographic analyses indicate that high divergence is not due to a long period of allopatric isolation without gene flow , contrary to what has previously been suggested [42 , 44] . This is important , as failing to account for variation in evolutionary history among species pairs placed on a continuum will obscure the processes leading to higher differentiation as speciation progresses . A further explanation for the high genomic divergence is the presence of strong isolating barriers between the Japan Sea and Pacific Ocean sticklebacks . Total reproductive isolation ( 0 . 970 ) is greater than in all postglacial species pairs ( 0 . 716–0 . 895 ) [48] and arises from a combination of habitat [46 , 47] , temporal [78] and sexual isolation , and hybrid sterility [41 , 42] . Recent theoretical studies have shown that selection on many barrier loci in the face of gene flow may result in a transition from low to high differentiation as a result of ‘genome-wide congealing’ [10 , 79] . It is important to note however that we lack evidence that such a transition might explain the high differentiation we see here relative to the rest of the stickleback continuum ( Fig 3C ) . Our study has also demonstrated two important signatures of introgression in the Japanese sympatric stickleback pair . Firstly , levels of background genome differentiation between G . aculeatus and G . nipponicus estimated by FST were lower in sympatry compared to allopatry . We note that this pattern was observed both in our whole genome and RAD-seq datasets . The higher overall genetic differentiation between G . nipponicus and Atlantic G . aculeatus is likely due to genetic drift and local adaptation and the fact that these two lineages have never overlapped geographically . Secondly and strikingly , using resequencing data , we identified small regions of localised introgression dispersed throughout the genome when G . nipponicus and G . aculeatus co-occur in sympatry . These introgression regions were measured using GMIN , the ratio of minimum dXY to mean dXY [30] , and fd , the proportion of introgressed sites in a genome window [59] . Several methodological issues might influence these measures of introgression . Firstly , there is a coverage disparity between resequenced individuals sampled in Japan and those from the Atlantic ( mean 61X and 12X coverage respectively ) , but both sample sets are sequenced to a depth suitable for accurate genotyping . Furthermore , Atlantic Ocean individuals with relatively lower depth are not included in the analysis of ABC and only serve as a comparison for genome-wide patterns of differentiation , divergence or introgression between the sympatric Japanese species . Secondly , both GMIN and fd are sensitive to sample size; fewer individuals will mean rare haplotypes have a lower sampling probability . However , by re-conducting our analyses using only females , a much smaller sample size than our main analysis , we still identified clear signals of introgression . Thirdly , GMIN will be biased downwards if a recently backcrossed individual is included in the dataset . All Japanese G . aculeatus and G . nipponicus used in the study were identified as ‘pure’ individuals with genotyping at multiple microsatellite loci prior to resequencing [41 , 45] . To further ensure that a single backcrossed individual was not biasing our findings , we examined the two haplotypes producing the lowest value of dXY in each GMIN valley to confirm that the majority were not always from the same individuals ( doi:10 . 5061/dryad . 104g3d0 ) . Finally , shared ancestral polymorphism cannot explain why more GMIN valleys occur in sympatry ( Fig 5A ) ( S9 Fig & S13 Fig ) . What then underlies the localised pattern of introgression we observe ? One possible explanation is the fact that many isolating barriers are involved in reproductive isolation [41 , 48] . Although the genomic basis of these isolating barriers remains unknown , it is likely that barrier loci occur throughout the genome; pervasive selection at multiple loci is expected to limit the extent of introgression at this scale [80] . We found significant positive relationships between recombination rates and introgression . The strength and extent of negative selection against an allele at a barrier locus and genomic regions linked to it is inversely proportional to recombination rate [80] . Recombination determines effective migration rate [81]; when recombination is high , neutral and adaptive loci linked to the target of negative selection in the recipient population have a greater probability of escaping removal and so their probability of introgression is greater [3] . Selection has a higher efficiency in these high recombination rate regions due to increased effective population size–therefore deleterious introgression is also more likely to be removed . The expectation then is that signatures of introgressed neutral or adaptive alleles are most likely to persist in regions of the genome where recombination rate is sufficiently high enough , and indeed , the positive association between introgressed regions and recombination rate we observed supports this ( Fig 5B , S15 Fig ) . Introgression is typically lower on sex chromosomes relative to autosomes in multiple taxa due to the effects of reduced recombination and greater exposure to selection in the hemizygous sex [82] . The sex chromosomes play an important role in the Japanese stickleback system , harbouring QTL for hybrid sterility and behavioural isolation [41] . Consistent with this , we observed lower introgression on the neo-sex chromosome ( Fig 5E & 5F ) , although we cannot exclude the possibility that the fusion occurred more recently than the speciation event , so the opportunity for introgression on the neo-sex chromosomes was simply low relative to the rest of the genome . Taken together , our findings suggest that strong divergent selection and recombination rate variation may determine the localised signature of introgression in the genome . The nature of gene flow in the Japanese stickleback system may also give some clues as to why we observe such highly localised introgression . One possibility is that a proportion of the introgression we detected is adaptive; i . e . it is maintained because of either directional or balancing selection . Adaptive introgression has been detected in a wide range of taxa [83] , including humans [84] . However , the expected signatures of the process remain unclear–especially when introgression is widespread in the genome , as is possibly the case here . Our GO analyses suggest an enrichment of immune response genes , including MHC genes , and metabolism genes in introgressed regions . Immune genes have been identified as being under balancing selection in hybridising taxa , particularly plants [85] and birds [86] . Several genes involved in metabolism are also reported to be under balancing selection in humans [87] . Furthermore , recent analysis suggests that negative frequency dependent selection might result in introgression of rare MHC alleles between divergent stickleback ecotypes [88] . Further research is necessary to directly test whether this process might explain introgression in the Japanese stickleback system . Much of our knowledge of how genomic differentiation builds along the speciation continuum is drawn from studies focusing on young , allopatric or completely reproductively isolated species pairs . Very few examples of species pairs at a later stage of divergence with on-going gene flow have been investigated . Here , we have shown that the Japan Sea and Pacific Ocean species pair exemplifies this under-represented stage of speciation and is situated at the further end of the stickleback species continuum . The high genomic differentiation between the species may be due to a more ancient divergence time than previously studied postglacial species pairs , selection on multiple isolating barriers or a combination of the two . Despite high differentiation , gene flow is on-going between the species and we identified localized signatures of introgression throughout the genome . Although the localized nature of the introgression remains unclear , selection–either directional or balancing–may play some role in promoting it . Overall , our study demonstrates that high levels of genomic divergence can be established and maintained in the presence of gene flow . Further genomic studies on more species pairs at late stages of speciation with gene flow will help to understand the generality of the patterns seen here .
All animal experiments were approved by the institutional animal care and use committee of the National Institute of Genetics ( 23–15 , 24–15 , 25–18 ) .
|
When species evolve , reproductive isolation leads to a build-up of differentiation in the genome where genes involved in the process occur . Spanning the speciation continuum , stickleback species pairs are ideal for investigating how genomic divergence accumulates during speciation . However , much of our understanding of stickleback speciation comes from early stage divergence , with relatively few examples from more divergent species pairs that still exchange genes . To address this , we focused on Pacific Ocean and Japan Sea sticklebacks , which co-occur in the Japanese islands . We established that they are the oldest and most divergent known stickleback species pair , that they evolved in the face of gene flow and that this gene flow is still on going . We found introgression is confined to small , localised genomic regions where recombination rate is high . Our results show high divergence can be maintained between species , despite extensive gene flow .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"methods"
] |
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"taxonomy",
"fish",
"atlantic",
"ocean",
"japan",
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"locations",
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"vertebrates",
"animals",
"osteichthyes",
"phylogenetics",
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2018
|
The genomic landscape at a late stage of stickleback speciation: High genomic divergence interspersed by small localized regions of introgression
|
Chikungunya is a viral disease transmitted by Aedes aegypti and Ae . albopictus mosquitoes . In late 2013 , chikungunya virus ( CHIKV ) was introduced into the Caribbean island of St . Martin . Since then , approximately 2 million chikungunya cases have been reported by the Pan American Health Organization , and most countries in the Americas report autochthonous transmission of CHIKV . In Nicaragua , the first imported case was described in July 2014 and the first autochthonous case in September 2014 . Here , we conducted two studies to analyze the seroprevalence of anti-CHIKV antibodies after the first chikungunya epidemic in a community-based cohort study ( ages 2–14 years ) and in a cross-sectional survey of persons aged ≥15 years in the same area of Managua , Nicaragua . Routine annual serum samples collected from 3 , 362 cohort participants in March/April 2014 and 2015 , and 848 age-stratified samples collected from persons ≥15 years old at the end of May-beginning of June 2015 were used to estimate the seroprevalence of anti-CHIKV antibodies after the first epidemic ( October 2014 to February 2015 in the study population ) . Using an Inhibition ELISA assay that measures total anti-CHIKV antibodies , the seroprevalence was significantly higher in those aged ≥15 ( 13 . 1% ( 95%CI: 10 . 9 , 15 . 5 ) ) than in the pediatric population ( 6 . 1% ( 95%CI: 5 . 3 , 6 . 9 ) ) . The proportion of inapparent infections was 58 . 3% ( 95%CI: 51 . 5 , 65 . 1 ) in children and 64 . 9% ( 95%CI: 55 . 2 , 73 . 7 ) in the ≥15 study population . We identified age , water availability , household size , and socioeconomic status as factors associated with the presence of anti-CHIKV antibodies . Overall , this is the first report of CHIKV seropositivity in continental Latin America and provides useful information for public health authorities in the region .
Chikungunya virus ( CHIKV ) is an alphavirus belonging to the Togaviridae family and is primarily transmitted by Aedes ( Ae . ) aegypti and Ae . albopictus mosquitos [1] . The main epidemic cycle consists of human-mosquito-human transmission , although a natural reservoir of CHIKV in non-human primates serves as part of a sylvatic cycle in Africa , which maintains virus circulation during inter-epidemic periods [2 , 3] . A bite from an infected mosquito transmits CHIKV , causing chikungunya , an acute viral illness characterized by high fever , arthalgia , myalgia and skin rash [4] . In the chronic stage of the disease , persistent or re-occurring arthralgia is common and may last for years [4 , 5] . Historically , mortality due to chikungunya was thought to be unusual and only observed in the very young , old or immunocompromised; however , the during the outbreak in La Reunion Island in 2005–6 , a case fatality rate of 1/1 , 000 was observed [6] . Even though the mortality rate remains in question , high attack rates are often seen throughout different epidemics [7] . Since the isolation of CHIKV after a 1952–1953 epidemic in present-day Tanzania [8] , it has been endemic in parts of Africa and Asia; however , within the last decade it has reemerged as a major threat to human health globally , causing massive outbreaks in endemic areas , as well as in new regions [2] . After over 30 years of small , limited outbreaks , CHIKV resurfaced in Kenya and the Indian Ocean in 2004–5 [7 , 9–11] . A combination of increased global travel and trade , wide distribution of the mosquito vectors , and lack of herd immunity contributes to the introduction and rapid spread of CHIKV in naïve populations . This was the case in parts of Europe , Asia and the Indian Ocean that reported locally transmitted cases of CHIKV for the first time [10 , 12] , as well as the recent introduction of CHIKV into the Americas [13] . In the Americas , autochthonous CHIKV transmission was first reported in the Caribbean on the island of St . Martin in December 2013 [13 , 14] . Regional dissemination into Central/South/North America has affected more than 45 countries or regions , with approximately 2 million suspected cases , as reported by the Pan American Health Organization [15] . Nicaragua reported its first imported chikungunya case in July 2014 [16] . In Managua , the capital city , the first imported case was identified in August 2014 and the first locally transmitted case in September 2014 ( A . Balmaseda , personal communication ) . In this study , we performed a cross-sectional seroprevalence study of anti-CHIKV antibodies in District II of Managua in children aged 2–14 years enrolled in the Pediatric Dengue Cohort Study [17 , 18] and in individuals aged ≥15 years recruited door-to-door specifically for this study . In both study populations , total anti-CHIKV antibodies were detected via Inhibition Enzyme Linked Immunosorbant Assay ( ELISA ) , and factors associated with CHIKV seropositivity were evaluated using the same questionnaire . The objective of this study was to determine the seroprevalence of anti-CHIKV antibodies during the first chikungunya outbreak in Managua , correlate potential risk factors with CHIKV seropositivity , and show the spatial distribution of CHIKV seroprevalence in District II of Managua . Altogether , this study indicates the level of protective immunity the population has developed , identifies susceptible populations and factors associated with seropositivity , and can help government institutions develop intervention and mitigation strategies .
The protocol for the Pediatric Dengue Cohort Study ( PDCS ) was reviewed and approved by the Institutional Review Boards ( IRB ) of the University of California , Berkeley , the University of Michigan , and the Nicaraguan Ministry of Health . Parents or legal guardians of all subjects provided written informed consent , and subjects 6 years of age and older provided oral assent . An amendment to add CHIKV infection screening to the PDCS , including specific consent/assent from the parent/guardian and the participant , was also approved by the IRBs reviewing the study . The protocol for the cross-sectional study of persons aged ≥15 years was reviewed and approved by the IRB of the Nicaraguan Ministry of Health and the Pan American Health Organization's Ethics Review Committee . Participants 18 years of age and older provided written informed consent . For participants aged 15–17 , parents or legal guardians provided written informed consent and participants provided written assent . This study examined the seroprevalence of anti-CHIKV antibodies in two study populations , 2–14 years and ≥15 years of age , residing in the catchment area of the Health Center Sócrates Flores Vivas ( HCSFV ) in District II of Managua , Nicaragua . The total population served by HCSFV is ~62 , 000 , with a population density of ~6 , 700 habitants/km2 . The population aged 2–14 and ≥15 was estimated in 2015 at 14 , 240 and 45 , 312 , respectively ( G . Kuan , personal communication ) . The 15 neighborhoods of the study area are low- to mid-socioeconomic status; the illiteracy rate is 7% . The majority of homes , ranging from residential to shanty dwellings , are owner-occupied; close to 95% of the area has access to water and sewage infrastructure , and 88% has garbage collection services . Samples from participants 2–14 years old were obtained through the ongoing PDCS , originally established in 2004 to study dengue and dengue virus infections in Nicaragua [17 , 18] and expanded to include CHIKV infection in children in September 2014 [16] . The PDCS consists of approximately 3 , 500 children aged 2–14 years , and children are provided with all of their primary health care through the study at the HCSFV . Acute and convalescent blood samples are collected from participants meeting the case definition of dengue and/or chikungunya or presenting with undifferentiated fever [16] . Additionally , a routine blood sample is collected annually in March/April from the children when they are healthy . During the annual sampling , the parents/guardians also complete a socioeconomic and household risk factor questionnaire . Participants who are sick when presenting for the annual sample collection , in particular those who had a fever within the previous week , are referred to a study physician and asked to return for sampling when healthy . Participants are enrolled and withdrawn throughout the year according to age criteria; thus , not all participants had routine annual samples collected in both 2014 and 2015 . This study was restricted to those with paired 2014 and 2015 samples ( n = 3 , 362 , Table 1 ) . Participants aged ≥15 were recruited as part of a community-based cross-sectional study conducted at the end of May/beginning of June 2015 in the same area as the cohort study . Age and residency were the only inclusion criteria . To be consistent with the PDCS , individuals who had experienced fever within the seven days prior to sampling were excluded from the study . To avoid clustering , a maximum of two people per household were allowed to participate . Sample size was estimated to determine the seroprevalence with a +/- 10% precision using the following parameters: estimated seroprevalence rate of 20% , type I error of 0 . 05 , and power of 0 . 8 . The estimated sample size was 502 participants . In order to adjust for clustering by household ( enrollment of up to 2 persons per household ) , a correlation coefficient of 0 . 6 to 0 . 9 was used , yielding a final sample size of 604 to 904 participants . The study area in Managua was composed of 15 neighborhoods , and the sample size of each neighborhood was proportional to its total population . Each neighborhood is divided into blocks . The sample size of the neighborhood was distributed uniformly among blocks . Within a block , houses to be visited were randomly selected by study personnel . Within each household , potential participants were approached randomly . The target enrollment per household was 2 participants; however , in some households only one person consented to study participation . Approximately 150 individuals per ten-year age group ( 15–24 , 25–34 , 35–44 , 45–54 , 55–64 , 65+ ) were sampled . Each participant was asked to complete a survey , which included information about the participant’s demographics , household , socioeconomic status and potential risk factors . Surveillance of symptomatic chikungunya cases conducted in the cohort study indicated that , in this area of Managua , the first epidemic of chikungunya lasted from September 2014 until February 2015 [16] , and the second epidemic began in June 2015 and lasted through February 2016 . Therefore , by utilizing samples from pediatric and ≥15 year-old study populations , we were able to analyze the seroprevalence of anti-CHIKV antibodies during the first outbreak of chikungunya in Managua . The same demographic and household survey was used in the two study populations . Demographic data collected included sex , age and education , and the household questionnaire included questions on appliance ownership and conditions of the home . In addition , participants aged ≥15 were asked to recall any self or clinical diagnosis of chikungunya ( including symptoms and disease severity ) and to describe their knowledge and attitudes towards chikungunya . In both studies , the survey was administered orally and answers were recorded by HCSFV interviewers on a mobile device ( smart phone or tablet computer ) using a custom-built application . Global positioning system ( GPS ) latitude and longitude coordinates were taken using the GPS capabilities of the mobile devices . To characterize the socio-economic status ( SES ) of each household , a wealth index was constructed using the following variables from the household survey: crowding ( ratio of the number of people in the household divided by the number of bedrooms ) , number of fans , TVs , refrigerators , motor cycles , and/or cars owned , materials used to build the ceiling and the floor , and whether the family cooked with firewood . The wealth index was then analyzed using principal component analysis ( PCA ) [19] . PCA analyses were run separately for both study populations . As the number of households in the ≥15 years study population was relatively low , the households were divided into two halves , “poor” and “not poor” , according to their SES . To be consistent , the same approach was used for the pediatric study population . Individual participants were assigned the SES of their household . An in-house single-dilution inhibition Enzyme Linked Immunosorbent Assay ( ELISA ) was used to detect total CHIKV-specific antibodies in the serum of the participants ( Saborio et al , submitted for publication ) . In this assay , CHIKV antigen produced in C6/36 cells is captured onto polystyrene plates using the anti-CHIKV monoclonal antibody ( mAb ) 187 ( obtained from Dr . Michael S . Diamond , Washington University in St . Louis ) [20] . CHIKV-specific antibodies that might be present in the participants’ samples then compete for binding to the CHIKV antigen with horseradish peroxidase ( HRP ) -conjugated anti-CHIKV mAb 152 ( obtained from Dr . Michael S . Diamond ) [20] . Using tetramethylbenzidine HRP substrate , bound mAb 152 is quantified by measuring the optical density ( OD ) at 450 nm on an ELISA reader . Samples with an OD lower than 50% of the negative controls' mean OD were considered seropositive . The sensitivity of this assay was measured using paired healthy annual samples collected in March/April 2014 and March/April 2015 in cohort participants who had experienced a laboratory-confirmed acute CHIKV infection in the period between the annual sample collections . The assay had a sensitivity of 92 . 4% ( 95%CI 86 . 9 , 97 . 8 ) , such that of the 92 chikungunya cases , 85 seroconverted ( i . e . , the sample was negative in 2014 and positive in 2015 ) . Data were analyzed using STATA Software ( STATA Corp , College Station TX ) . Relative and absolute frequencies are reported for categorical variables , and mean and standard deviation are reported for quantitative variables . A binomial distribution was used to calculate 95% confidence intervals ( CIs ) for seroprevalence and proportion of inapparent infections . The seroprevalence estimate was post-stratified using the 2015 age structure ( G . Kuan , personal communication ) and the 2005 gender structure [21] of the study area population . We used generalized linear models assuming a Poisson distribution in order to calculate prevalence ratios ( PR ) . Crude and adjusted PR were calculated using univariate and multivariate analysis , respectively . Two multivariate models were constructed . One included all variables listed in Table 2 except the number of persons per household and one included all variables except SES . This was done as the number of persons per household was also used to determine the participant's SES . A mixed-effects Poisson regression was used to test the hypothesis that at least one neighborhood had a seroprevalence different to the seroprevalence of the entire study area . In the mixed-effects Poisson regression , the fixed effects were sex , age group , SES , and daily hours without water , and the random effect was the neighborhood . To identify neighborhoods with a seroprevalence different than the seroprevalence of the study area , random effects for the variable neighborhood and their 95%CIs were visually inspected for overlap ( caterpillar plot ) .
A total of 3 , 362 paired annual samples from the pediatric cohort were collected in March/April 2014 and 2015 and analyzed in this study ( Table 1 ) . Of these , 1 , 685 ( 50 . 1% ) were from females and 1 , 677 ( 49 . 9% ) were from males , approximately a 1:1 ratio . Age was uniformly distributed in the pediatric cohort; one-year age groups 2 to 14 years old had in average 259 participants ( range: 231–281 ) . A total of 1 , 078 persons aged ≥15 were approached for participation in the community-based cross-sectional study . Of those , 848 ( 79 . 6% ) consented to participate . The approval rate was significantly higher in females ( 84 . 1% ) than in males ( 67 . 2% ) ( p<0 . 0001 ) . This , combined with the fact that more women were at home when the study was conducted , resulted in female-to-male ratio of 2 . 6:1 among the 848 participants ( Table 1 ) . Participants were distributed across all ages , with the 15–29 year age group having the highest number of participants ( 240; 28 . 3% ) and the 65+ group having the lowest number of participants ( 192 , 22 . 6% ) . The socioeconomic status ( SES ) distribution was similar in both studies; 58 . 8% and 59 . 7% of the participants lived in a household categorized as poor for participants aged 2–14 and ≥15 , respectively ( Table 1 ) . The amount of time without water per household was determined based on self-reporting . A similar distribution was recorded among the households in both studies , with the majority of the households reporting access to water 24 hours per day ( Table 1; 72 . 3% for pediatric and 75 . 1% for ≥15 year-old participants ) . The seropositivity in both study populations was determined via Inhibition ELISA . In the pediatric cohort study , paired samples were collected in March/April 2014 , before the introduction of CHIKV into Nicaragua , and in March/April 2015 , at the end of the first chikungunya epidemic and before the onset of the second epidemic , which began in mid-June 2015 . As expected , no sample collected in 2014 was seropositive for anti-CHIKV antibodies ( n = 3 , 362 ) . In 2015 , 204 children were seropositive for CHIKV , for a seroprevalence of 6 . 1% ( 95% Confidence Interval ( CI ) : 5 . 3 , 6 . 9 ) ( Table 2 ) . In the cross-sectional study of persons aged ≥15 years , single samples were collected at the end of May/beginning of June 2015 . In this population , 13 . 1% ( 95%CI: 10 . 9 , 15 . 4 ) of the 848 participants were seropositive for CHIKV ( Table 3 ) . Comparing the two populations , the seroprevalence in children aged 2–14 was 7 . 0 ( 95%CI: 4 . 6 , 9 . 4 ) percentage points lower than those ≥15 ( p<0 . 001 ) ( Fig 1A ) . The post-stratified estimate of the seroprevalence for the population aged ≥2 years in the study area was 11 . 6% ( 95%CI: 9 . 7 , 13 . 7 ) . In the pediatric cohort study , symptomatic chikungunya cases were captured through enhanced passive surveillance at the HCSFV since the introduction of CHIKV in the study population . Participants presenting with suspected chikungunya and/or dengue , as well as those with undifferentiated fever , were tested for acute CHIKV infection by real-time RT-PCR [16] . Participants positive for anti-CHIKV antibodies who did not present with an episode of laboratory-confirmed chikungunya were considered to have experienced an inapparent infection . In the study population aged ≥15 , self-report was used to infer symptomatic and inapparent CHIKV infections . The proportion of inapparent infections among all participants with anti-CHIKV antibodies was 58 . 3% ( 95%CI: 51 . 5 , 65 . 1 ) in the cohort population and 64 . 9% ( 95%CI: 55 . 2 , 73 . 7 ) in the study population aged ≥15 years old . Potential factors associated with CHIKV seropositivity were explored separately in both study populations . Gender was not associated with increased seroprevalence of anti-CHIKV antibodies in either population ( Tables 2 and 3 ) , but age was . In the pediatric population , there was a statistical association between increasing seropositivity and increasing age ( Table 2 ) . The oldest children in the cohort study , ages 10–14 , had the highest seroprevalence of anti-CHIKV antibodies: 8 . 9% ( 95%CI: 7 . 4 , 10 . 7 ) . The adjusted prevalence ratio ( aPR ) for this age group compared to the 2–4 year-old group was 1 . 85 ( 95%CI: 1 . 50 , 2 . 29 ) . Seroprevalence was then calculated for each one-year age group ( Fig 1B ) . Seroprevalence was consistently lower in one-year age groups from 2 to 9 years than in groups from 10 to 14 . Accordingly , the aPR for children aged 10–14 was 2 . 00 ( 95%CI: 1 . 70 , 2 . 35 ) when compared to those aged 2–9 ( p<0 . 001 ) . When analyzing only the participants aged ≥15 , age was not demonstrated to be statistically associated with seropositivity ( Table 3 ) . However , when combining all participants in this study , participants with ages 2–14 displayed a lower seroprevalence than those ≥15 years old ( p<0 . 001 ) . SES and household factors were evaluated as potential factors associated with seroprevalence of anti-CHIKV antibodies . Children characterized with a low SES ( “poor" ) , based on the questionnaire parents/guardians answered , had a statistically higher seroprevalence ( aPR: 1 . 33; 95%CI: 1 . 11 , 1 . 58 ) than those in the higher SES “not poor” category ( Table 2 ) . Similarly , participants ≥15 years old with a low SES had a higher overall seroprevalence ( aPR 1 . 11; 95%CI 0 . 82 , 1 . 51 ) ; however , this difference was not statistically significant ( Table 3 ) . Another household factor that was examined was water availability . A statistically significant positive association between number of hours without water and anti-CHIKV seroprevalence was observed in pediatric study population , with the highest seroprevalence in the ≥8-hour group ( Table 2 ) ; however , there was no significant association between hours without water and seroprevalence in the ≥15 year-old study population ( Table 3 ) . Household size ( number of people per household ) was statistically associated as a protective factor in both study populations ( Tables 2 and 3 ) . Utilizing study household GPS coordinates , we visualized the spatial distribution of seroprevalence of anti-CHIKV antibodies by neighborhood . This study was conducted in a relatively small area of ~9 square kilometers . The seroprevalence in each neighborhood was calculated combining the participants from both studies . Seroprevalence varied 10-fold across neighborhoods: from 1 . 8% ( 95%CI: 0 . 05 , 9 . 7 ) in San Antonio to 17 . 5% ( 95%CI: 7 . 3 , 32 . 8 ) in William Díaz ( Fig 2 ) . Two neighborhoods had a seroprevalence significantly higher than the mean seroprevalence of the study area ( p<0 . 001 ) : Bóer and Santa Ana Sur . Moreover , 7 of the 15 neighborhoods consist of mixed commercial and residential areas , while the rest are mainly residential . Interestingly , 6 of 7 neighborhoods with commercial activity corresponded to the neighborhoods with the highest seroprevalence . The survey administered to ≥15 year-old participants included questions that addressed knowledge about chikungunya . The majority of the participants ( 93 . 5% ) considered themselves informed about chikungunya ( S1 Table ) . The major source of information was television ( 77 . 3% ) , followed by radio ( 11 . 7% ) . Other sources included community health workers , talks at the health centers/posts and newspapers . Knowledge about how chikungunya is transmitted was also evaluated . A total of 766 ( 90 . 3% ) correctly identified mosquitoes as the disease vector . Participants were also asked about practices of chikungunya prevention implemented in their household . Of all participants , 758 ( 89 . 4% ) implemented at least one measure ( S1 Table ) . Knowledge or practices did not impact seroprevalence rates ( S1 Table ) .
This study is the first to report seroprevalence and factors associated with CHIKV seropositivity in continental Latin America . The seroprevalence of anti-CHIKV antibodies were measured in two studies conducted in the same area of Managua , Nicaragua: an ongoing pediatric ( 2–14 years old ) cohort study [17 , 18] and a cross-sectional study in participants aged ≥15 years . The seroprevalence in the pediatric study was 6 . 1% ( 95%CI: 5 . 3 , 6 . 9 ) , while it was 13 . 1% ( 95%CI: 10 . 9 , 15 . 5 ) in the ≥15 year-old study population . Moreover , older children had a higher seroprevalence than younger children . Increased number of hours without water in the household , lower socioeconomic status and lower number of people per household resulted in an increased risk for CHIKV infection . The proportion of inapparent infections among all infections was 58 . 3% ( 95%CI: 51 . 5 , 65 . 1 ) in children and 64 . 9% ( 95%CI: 55 . 2 , 73 . 7 ) in participants ≥15 years . The seroprevalence within the study area varied spatially , with neighborhood seroprevalence ranging from 1 . 8 to 17 . 5% . In comparison to other seroprevalence studies , the seropositivity in our study is similar to Northern Italy , 10 . 2% [22] , and St . Martin’s Island , 16 . 9% [23] . However , other studies performed in Asia , Africa and the Indian Ocean report higher seroprevalence , ranging from 25% to 75% [24–29] . The differences in seroprevalence between studies could be due to multiple factors . First , the strength of the outbreak/epidemic , indicated by the number of cases reported , could differ . Also , studies that measure anti-CHIKV IgG antibodies in endemic regions are likely detecting cumulative anti-CHIKV antibodies from previous CHIKV outbreaks [25 , 28] , whereas this study reflects the first introduction of CHIKV into Nicaragua . Mosquito distribution differs in different countries , and transmission of CHIKV can be affected by the vector species , due to adaptive mutations in CHIKV that expand its vector competence [30] . Furthermore , some studies [10 , 24 , 26] were conducted in areas where circulating CHIKV strains were different from the Asian genotype strains identified in Nicaragua [31] . Strains imported into Nicaragua in August 2015 had E1 gene sequences that were 100% identical to the first strain sequenced in the Americas , BritishVirginIslands/99659/KJ451624/2014 [31] . Although no seroprevalence studies of anti-CHIKV antibodies in continental Latin America have been published to date , clinical attack rates in certain countries during the 2014–2015 epidemic were reported as very high ( e . g . , up to 81% in some areas of the Dominican Republic ) [32 , 33] . Several factors could contribute to the lower rate in Nicaragua . First , the country experienced a drought in 2014 that resulted in a delayed rainy season with less rainfall [34] , which could have reduced entomological indices . Notably , Breteau indices in the study area were lower in 2014 than in 2011–2013 ( G . Kuan , personal communication ) . However , the low seroprevalence after the first chikungunya epidemic indicates that the majority of the population remains susceptible to CHIKV infection and herd immunity has not yet been achieved . Consistent with this , the second chikungunya epidemic , which began in June 2015 and lasted until February 2016 , was much larger than the first epidemic described in this report ( September 2014 to February 2015 ) . We plan on documenting the increase in seroprevalence by examining the same pediatric and ≥15 year-old participants in March-May of 2016 . The proportion of inapparent infections observed in this study was high , 58 . 3% ( 95%CI: 51 . 5 , 65 . 1 ) in children and 64 . 9% ( 95%CI: 55 . 2 , 73 . 7 ) in ≥15 year-old participants . The majority of seroprevalence studies have been conducted in areas where the East/Central/South African ( ECSA ) genotype of CHIKV had circulated [2] . These studies report proportions of inapparent infections ranging from 3 . 8% to 47 . 1% [10 , 22–28 , 35] and only two report proportions higher than 40% [28 , 35] . Two studies were carried out in areas where the same CHIKV genotype as the one present in Nicaragua circulated but outside of the Americas: a small study conducted in Malaysia in 2007 ( 17 . 5% inapparent infections ) [25] and a cohort study in the Philippines in 2012–2013 ( 82 . 1% inapparent infections ) [36] . Finally , a study conducted on the island of St . Martin , the point of introduction of CHIKV in the Americas [23] , recently reported a proportion of inapparent infections of 39 . 0% . Taken together , these studies and this report appear to point towards a higher proportion of inapparent CHIKV infections during outbreaks/epidemics caused by the Asian genotype . In this study , factors associated with CHIKV seropositivity were age , water availability , household size , and SES . Seroprevalence increased with age in the pediatric population . Moreover , ≥15 years old participants had a seroprevalence of anti-CHIKV antibodies two times higher than participants aged 2–14 . This observation is consistent with other outbreaks , which report lower seroprevalence in children [22 , 24 , 25 , 27 , 28] . In this study , gender was not associated with CHIKV seropositivity . Some previous seroprevalence studies report women having a higher seroprevalence [26 , 29] , while others report the contrary [22 , 24 , 27] , and one study reports no gender difference [28] . Socioeconomic level was analyzed in this study using a wealth index . Lower SES correlated with increased CHIKV seropositivity . However , this increase was statistically significant only in the 2–14 year-old population , likely as a result of the larger sample size in this population compared to the ≥15-year-old study population . Similarly , an increase in the number of hours without water supply was correlated with an increased seroprevalence , but only reached significance in the 2–14 years population . Water availability can be a potential risk factor associated with CHIKV seroprevalence since Ae . aegypti mosquitoes that transmit the virus breed in clean water in and around people’s homes . We hypothesize that a greater number of hours without water represents a higher chance that the household will store water , thus increasing the number and volume of mosquito breeding containers . In contrast , household size was a protective factor in both study populations . A higher number of people in a household might decrease the likelihood of each individual getting bitten by an infected mosquito , and a lower vector-to-person ratio could be protective at the individual level . Although this study was conducted in a limited geographic area , seroprevalence varied 10-fold across neighborhoods . As reported in a seroprevalence study conducted in Bagan Pashor , Malaysia [25] , neighborhoods with higher commercial activity in Managua showed higher seroprevalence . This study has certain limitations . Both the pediatric and ≥15 year-old seroprevalence levels were lower than expected , and because of this , the sample size for the ≥15 study was underestimated . As a result , some factors demonstrated trends , rather than statistically significant associations . The majority of the people available during recruitment of the ≥15 year-old study population were females because men in the study area are less likely to be at home during the day . In addition , males who were approached were less likely to participate in the study than females . Another point is that symptomatic cases in the ≥15-year-old study population were self-reported , which might bias the estimate of the proportion of symptomatic infections in this population . However , the proportion of inapparent infections in the ≥15 year-old study population ( 64 . 9% ) was quite similar to that in children ( 58 . 3% ) , where symptomatic cases were laboratory-confirmed acute cases in the cohort study [16] . Finally , the Inhibition ELISA used to detect anti-CHIKV antibodies had a sensitivity of 92 . 4% . Given the 95% CI of the assay sensitivity , the seroprevalence can be estimated at 6 . 2–7 . 0% and 13 . 4–15 . 1% in the pediatric and ≥15 year-old study populations , respectively . Overall , we report seroprevalence of anti-CHIKV antibodies after the first epidemic in Managua , Nicaragua , and analyze factors associated with CHIKV seropositivity . In this newly exposed population , a low seroprevalence was documented , and we expected ( and observed ) an elevated seroprevalence in the second epidemic because the vast majority of the population was still susceptible after the first chikungunya epidemic . These data help the Ministry of Health in Nicaragua plan appropriate vector control and new mitigation strategies to confront the current CHIKV epidemics and provide useful information about the epidemic of chikungunya in the Americas .
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Chikungunya is a viral disease primarily characterized by high fever and joint pain . Chikungunya virus ( CHIKV ) is transmitted by infected Aedes aegypti and Ae . albopictus mosquitos . Although chikungunya was first described in 1952 and CHIKV has circulated in parts of Africa and Asia , since then , it was not introduced into the Americas until late 2013 . Chikungunya poses a threat in tropical countries where the vector mosquitoes reside and in particular in CHIKV-naïve populations . In this study , we aimed to explore the dissemination of CHIKV through the first epidemic in Nicaragua and evaluate possible factors associated with infection . By analyzing the sera of two study populations , pediatric ( 2–14 years old ) and ≥15 years participants , for anti-CHIKV antibodies , we determined who was infected during the first outbreak in Nicaragua . The seroprevalence of anti-CHIKV antibodies in the pediatric and ≥15 year-old study populations was 6 . 1% and 13 . 1% , respectively . Furthermore , using a demographic/household survey , we found that age , water availability , household size , and socioeconomic status were associated with CHIKV seropositivity . In conclusion , this study indicates the level of protective immunity the population has developed and can help government institutions develop intervention strategies .
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2016
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Seroprevalence of Anti-Chikungunya Virus Antibodies in Children and Adults in Managua, Nicaragua, After the First Chikungunya Epidemic, 2014-2015
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The neglected parasitic infection Chagas disease is rapidly becoming a globalised public health issue due to migration . There are only two anti-parasitic drugs available to treat this disease , benznidazole and nifurtimox . Thus it is important to identify and validate new drug targets in Trypanosoma cruzi , the causative agent . T . cruzi expresses an ER-localised ascorbate-dependent peroxidase ( TcAPx ) . This parasite-specific enzyme has attracted interest from the perspective of targeted chemotherapy . To assess the importance of TcAPx in protecting T . cruzi from oxidative stress and to determine if it is essential for virulence , we generated null mutants by targeted gene disruption . Loss of activity was associated with increased sensitivity to exogenous hydrogen peroxide , but had no effect on susceptibility to the front-line Chagas disease drug benznidazole . This suggests that increased oxidative stress in the ER does not play a significant role in its mechanism of action . Homozygous knockouts could proceed through the entire life-cycle in vitro , although they exhibited a significant decrease in their ability to infect mammalian cells . To investigate virulence , we exploited a highly sensitive bioluminescence imaging system which allows parasites to be monitored in real-time in the chronic stage of murine infections . This showed that depletion of enzyme activity had no effect on T . cruzi replication , dissemination or tissue tropism in vivo . TcAPx is not essential for parasite viability within the mammalian host , does not have a significant role in establishment or maintenance of chronic infections , and should therefore not be considered a priority for drug design .
The protozoan parasite Trypanosoma cruzi is the causative agent of Chagas disease . In Latin America , 8–10 million people are infected , with many more at risk . In addition , as a result of migration , the disease is becoming a public health issue in non-endemic regions , such as Europe and the US [1–3] . Infection with T . cruzi is usually life-long , and up to 30% of individuals develop chronic Chagas disease , with symptoms that include cardiomyopathy and/or digestive megasyndromes . Treatment of T . cruzi infection is dependent on two drugs first introduced in the 1970s , benznidazole and nifurtimox . Both of these nitroheterocyclic compounds can have toxic side effects and do not consistently result in sterile cure , particularly in adults . Whilst benznidazole is curative in the acute stage of the disease [4] , its efficacy in the chronic phase remains controversial , despite much research effort [5 , 6] . A further problem which impacts on the widespread use of benznidazole and nifurtimox is the potential for cross-resistance . Both compounds are pro-drugs and are activated within the parasite by the same mitochondrial nitroreductase ( TcNTR ) . Activation of benznidazole results in depletion of the cellular thiol pool , likely leading to a reduced ability to deal with oxidative stress [7] . Loss of , or mutations within TcNTR , can result in resistance to both of the front-line drugs [8–10] . Consequently , there is an urgent need for new chemotherapeutic agents . Many aspects of trypanosome biochemistry are distinct from their mammalian hosts , and as such , have been proposed as targets for drug design . One example is the T . cruzi vitamin C dependent hemoperoxidase TcAPx , an enzyme belonging to Class 1 of the peroxidase–catalase superfamily [11] . This group of enzymes , which are absent from mammals , has been reclassified to separate true ascorbate peroxidases ( APx ) and cytochrome c peroxidases ( CcP ) from the hybrid type A and B APx-CcP groups , which show characteristics of both [12] . TcAPx falls into the hybrid type A group , which includes APx from the closely related Euglena gracilis , and from algae and oomycetes . The function of APx enzymes is to reduce H2O2 to H2O using ascorbate as an electron donor , thereby minimising the production of highly reactive hydroxyl radicals . APxs are particularly important in photosynthetic plants which contain isoforms targeted to each cellular compartment where reactive oxygen species ( ROS ) are formed . For example , plastid targeted isoforms protect the plant from H2O2 generated during photosynthesis [13] . In trypanosomatids there is only one APx isoform , which in T . cruzi is targeted to the endoplasmic reticulum ( ER ) [11] . The major source of H2O2 in the ER is oxidative protein folding , a process mediated by enzymes such as the flavoprotein ER oxidoreductin ( Ero1 ) . Ero1 uses molecular oxygen to oxidise protein disulphide isomerase , the enzyme required for disulphide bridge formation in the ER . For each disulphide bond generated , a molecule of H2O2 is formed , and this process can therefore generate high levels of oxidative stress . In the ER , TcAPx has the capacity to prevent this by reducing the resulting H2O2 before it builds to toxic levels . APx is also found in the related parasite Leishmania , where it is a mitochondrial enzyme [14] , and in several other kinetoplastids , but it is absent from the African trypanosomes , Trypanosoma brucei , Trypanosoma congolense and Trypanosoma vivax [15] . The importance of TcAPx to the viability and infection potential of T . cruzi is unknown . Proteomic studies have suggested that there is increased expression in the infectious metacyclic trypomastigote forms [16] . However , it has also been shown that TcAPx expression levels are not related to virulence or metacyclogenesis in a panel of ten parasite strains , whereas expression of other antioxidant enzymes ( the mitochondrial and cytosolic peroxiredoxins ) does correlate with infectivity [17] . Here , we describe a series of experiments designed to determine whether the parasite-specific TcAPx enzyme has a crucial role in the infection process .
T . cruzi epimastigotes ( strain Sylvio X10/6 ) were maintained in RPMI-1640 supplemented as previously described [18] at 27°C . L6 rat myoblast and Vero cells were cultured in the same medium but without hemin and trypticase , at 37°C in 5% CO2 . Metacyclic parasites were obtained from stationary phase epimastigote cultures as previously reported [9] . Mammalian cell monolayers were infected by addition of metacyclic trypomastigotes at a ratio of 5:1 ( parasites:host cells ) . Parasite transfection was carried out using an Amaxa Nucleofector II device with human T-cell buffer ( Lonza ) . 5 x107 epimastigotes were transformed with 5–10 μg of construct DNA . Drug selection was carried out at 10 μg ml-1 blasticidin , 5 μg ml-1 puromycin , 100 μg ml-1 G418 and 150 μg ml-1 hygromycin , as appropriate ( InVivoGen ) . Parasite cloning was carried out by diluting the parasite suspension to a concentration of 2 cells ml-1 and plating in 96-well microtitre plates at 100 μl per well . Plates were maintained at 27°C in 5% ( v/v ) CO2 with humidity . Recombinant his-tagged TcAPx was purified as described [11] . The protein was electrophoresed on 10% ( w/v ) SDS-PAGE gels and the TcAPx band excised . This was frozen in liquid nitrogen , ground to a fine powder , mixed with Freund’s complete adjuvant , and injected into mice . A pre-immunisation serum sample was obtained prior to injection . Antibodies were tested by western blotting against recombinant TcAPx and trypanosome lysates . Membranes were probed with mouse anti-TcAPx ( 1:1000 ) , followed by goat anti-mouse HRP conjugate ( BioRad ) , and developed using ECL+ kit ( GE Healthcare ) . Protein concentrations were assayed using the BCA method ( Pierce ) . For gene disruption constructs , the TcAPx ORF ( TcCLB . 506193 . 60 ) was amplified from T . cruzi genomic DNA and cloned into pGEM-T easy ( Promega ) using primers 5’-CAGGCAAGGTACCGTTTTCTTCAT and 5’-TTTTGACTCTGCTGGGAGAG . The TcAPx insert was then isolated with Sac I and Sph I and sub-cloned into Sac I/Sph I digested pUC19 to create pUC-TcAPx-2 . The plasmid pUC-TcAPx-2 was cut with Nae I and Apa I resulting in the deletion of the central 284 bp from TcAPx . Drug resistance cassettes for puromycin and blasticidin were ligated into this gap to produce the disruption constructs pTcAPx-Δ284-PAC and pTcAPx-Δ284-BLA . The resistance cassettes used RNA processing signals from T . brucei tubulin . The gene deletion construct pTcAPx-KO-BLA was constructed as follows . The 5’ flank encompassing the 3’ end of the CLPTM1 gene ( TcCLB . 506193 . 20 ) and the intergenic sequence up to centre of the TcAPx ORF , was amplified from genomic DNA using primers 5’-AATCCATCGTCTCTTGAAT and 5’-CTTGAGCGATTCCAGCGCA . The template DNA was isolated from the TcAPx+/- cell line to ensure that the amplicon was specific to the second intact TcAPx allele to allow efficient targeting . The 3’ end encompassing the STOP codon of TcAPx , the downstream intergenic sequence and the 5’ end of the G6PDH gene ( TcCLB . 506193 . 70 ) was amplified using primers 5’-TGACGCGTCCAGGTGCAG and 5’-TTGCACCGAGTACCACGAT . The 3’ flank was cloned into pGEM-T to produce pTcAPx-3’flank . The BLA drug resistance cassette was cloned as a Not I /blunted Apa I fragment into Not I/SmaTM I cut pTcAPx-3’flank to produce pBLA-3’KO . The 5’ flank was cloned into pGEM-T then isolated as a Not I/Bam HI fragment , which was cloned into Not I/Bam HI cut pBLA-3’KO to produce pTcAPx-KO-BLA . For transfection the fragment was isolated following Not I/Apa I digestion . Construction of the episomal expression vector pTEX-APx is described elsewhere [11] . The luciferase reporter construct pTRIX2-RE9h [19] was modified for bioluminescent tagging of null mutants by removal of the NeoR gene and its replacement with a HygR gene to generate pTRIX2-RE9h-Hyg . Parasites in the logarithmic phase of growth were diluted back to 5 x 105 ml-1 in 96-well plates . The appropriate concentration of drug was added and the plates were incubated at 27°C . Each drug concentration was tested against each cell line in quadruplicate . Resazurin ( Sigma ) was added after 5 days and the plates incubated for a further 4 days . 0 . 1% SDS was added to each well to lyse the parasites and the plates then read in a Spectramax M3 Microplate reader . Results were analysed using GraphPad Prism . L6 rat myoblasts or Vero cells were plated in chamber slides . They were allowed to settle for 16 hours and then infected with metacyclic trypomastigotes at a ratio of 5 trypanosomes per cell . The infection was incubated for 48 hours at 37°C , then extracellular trypanosomes removed by extensive washing in serum-free medium . After washing , slides were fixed in 100% methanol at room temperature for 15 minutes . The chamber walls were removed and the cells stained with Giemsa . The proportion of cells carrying intracellular parasites was calculated as a measure of infectivity . Seven replicates were performed per infection . Parasites from an exponentially growing culture were counted , pelleted and washed in PBS . They were lysed in Cell Culture Lysis Reagent ( CCLR , Promega ) . Luciferase activity was measured using the luciferase assay system ( Promega ) according to manufacturer’s instructions . Cell extracts were diluted as necessary in CCLR supplemented with 100 μg ml-1 bovine serum albumin . Each assay was performed on two individual extracts per cell line and in duplicate per extract . Luminescence was monitored on a SpectraMax M3 Microplate Reader ( Molecular Devices GmbH ) . All animal work was carried out under UK Home Office project licence ( PPL 70/6997 ) and was approved by the London School of Hygiene and Tropical Medicine Animal Welfare and Ethical Review Body . All protocols and procedures were conducted in accordance with the UK Animals ( Scientific Procedures ) Act 1986 ( ASPA ) . Animals were maintained under specific pathogen-free conditions in individually ventilated cages . They experienced a 12 hour light/dark cycle and had access to food and water ad libitum . Female BALB/c mice aged 8–12 weeks ( Charles River UK ) were infected by intra-peritoneal injection with 2 x 105 culture-derived trypomastigotes . The course of infection was monitored by bioluminescent imaging as detailed elsewhere [19] . Briefly , 10 minutes prior to imaging , mice were injected i . p . with 150 mg kg-1 d-luciferin in Dulbecco’s modified PBS . They were anaesthetised with 2 . 5% ( v/v ) isoflurane in oxygen , then placed in the IVIS Illumina II system ( Caliper Life Sciences ) . Images were acquired using Living Image 4 . 3 software with an exposure time of up to 5 minutes . After imaging , mice were weighed and revived , then placed back into their cages . For ex-vivo imaging , mice were injected with d-luciferin as above , then terminally anaesthetised with Euthatal ( Merial ) and sacrificed by exsanguination . Mice were perfused with 10 ml 0 . 3 mg ml−1 d-luciferin in Dulbecco’s modified PBS via the heart . Organs were removed , placed on a Petri dish and soaked in 0 . 3 mg ml−1 d-luciferin , then imaged as previously described [19] . All imaging data were analysed with Living ImageTM 4 . 3 software ( Caliper Life Sciences ) , using uninfected animals to set the base line for background luminescence . Statistical analysis of differences between groups or values was carried out using Student’s t-test , the F-test or one-way ANOVA depending on the experiment . Figure legends indicate the test used in each experiment . All analysis was processed using GraphPad Prism software .
The TcAPx loci are found on chromosome 36 of the T . cruzi genome reference strain CL-Brener ( TcVI group ) . In this hybrid lineage , there are considerable organisational differences in the structure of the loci between the Esmeraldo-like ( EL , TcII derived ) and non-Esmeraldo-like ( NEL , TcIII derived ) haplotypes ( S1 Fig ) , indicative of extensive rearrangement . For gene deletion studies , we therefore selected the Sylvio X10/6 strain ( TcI group ) , where the organisation of these loci is conserved between chromosome homologues . Consecutive rounds of targeted gene disruption were undertaken to test the feasibility of generating TcAPx null mutants ( Fig 1A , Methods ) . We could readily disrupt a single allele , but it was not possible to ablate both copies of the gene , despite multiple attempts . Either a third allele was detected after selection , the second construct recombined with the modified allele , or the drug resistance cassette formed episomes made up of head-to-tail tandemly repeated copies ( S2 Fig ) . Failure to achieve sequential disruption of both gene copies is often considered as evidence that the encoded protein has an essential function . To explore this further , we attempted to delete the second copy of the gene in epimastigotes which had been modified to express TcAPx from an episome ( Fig 1B and 1C , pTEX-APx described in [11] ) . Transformants were obtained following transfection with the integrative vector and the absence of the second endogenous TcAPx allele confirmed by Southern blotting . By implication , failure to generate null mutants in the absence of an ectopic copy did not arise from off-target effects of the gene inactivation process . To determine if TcAPx is an essential gene , we cultured two individually derived populations of the complemented , homozygous deletion mutants in the absence of G418 , the selective drug required for maintenance of the episome . In T . cruzi , episomes undergo random segregation . Therefore , in cells where both chromosomal copies of TcAPx had been disrupted , loss or retention of pTEX-APx , in the absence of selective drug pressure should reveal if the gene is essential . A similar technique has been developed for testing essentiality in Leishmania [20] . Analysis of parasite DNA prepared after the removal of drug selection revealed that the episome was lost from the population with similar kinetics to wild type cells transformed with pTEX-APx episome ( Fig 1C ) . Using the NeoR gene as a probe , it was apparent that the copy number had fallen by >90% within 60 generations ( approximately 60 days ) and to undetectable levels after 90 . Western blotting confirmed that the TcAPx protein was no longer present at detectable levels ( Fig 1D ) . For phenotypic analysis , clonal lines were derived from each of these populations ( Methods ) . These were negative for both the endogenous and ectopic copies of TcAPx ( Fig 1E , the 3 . 1 kb Cla I hybridising band present in the null mutant lanes corresponds to the disrupted copy of the gene as shown by hybridisation with the PAC probe; see map Fig 1A ) and did not express the protein ( Fig 1F ) . The null mutants showed no obvious growth phenotype when cultured as epimastigotes ( Fig 2A ) and could differentiate into metacyclic trypomastigotes in stationary phase cultures . These metacyclic trypomastigotes were able to infect L6 cells , a rat myoblast line , and Vero cells , albeit at a somewhat reduced level ( Fig 2C and 2D ) . Once inside the host cell , they were able to differentiate into amastigotes ( Fig 2B ) . The amastigotes differentiated to bloodstream trypomastigotes and lysed the cells as normal . The released trypomastigotes were fully capable of differentiating back into epimastigotes or re-infecting naïve cells . Thus , the null mutants could complete the entire life-cycle in vitro . Parasites which over-express TcAPx are more resistant to exogenous H2O2 than wild type ( Wilkinson et al . , 2002a ) , implying that cells lacking this enzyme might be hypersensitive . This proved to be the case , with the null mutants showing a significant fall in their EC50 values ( Fig 3A ) ( P<0 . 0001 ) . Reintroduction of an ectopic copy of the gene decreased H2O2 susceptibility to a level above that exhibited by wild type parasites , indicating that the sensitivity phenotype was due to the loss of TcAPx . It can be inferred that the higher EC50 value displayed by the complemented cell line results from the enhanced TcAPx expression level in epimastigotes containing a multicopy episome , as demonstrated previously in a wild type background [11] . The front line drug used to treat Chagas disease was also tested against the null mutants ( Fig 3B ) . Benznidazole is activated in the trypanosome mitochondrion by the action of a type I nitroreductase to produce toxic metabolites [21] . The compartment ( s ) in which these metabolites mediate their trypanocidal effect ( s ) are unknown , as is their final target ( s ) /mode of action . Metabolomic studies have suggested that benznidazole biotransformation has a major effect on thiol biochemistry within the parasite , leading to significant depletion of the major low molecular weight thiol , trypanothione [7] . Trypanothione is a key mediator of electron transfer to components of the antioxidant defence system , including TcAPx [22] . Previous work has also suggested that overexpression of Fe-superoxide dismutase increased susceptibility to benznidazole in T . cruzi [23] . Thus , one possibility is that benznidazole-mediated toxicity could result from depletion of antioxidant defences after activation by TcNTR . However , when we examined drug-sensitivity , there was no statistically significant difference between the EC50 values for wild type and TcAPx null mutants with benznidazole ( Fig 3B ) . Thus ablation of TcAPx activity does not increase susceptibility to benznidazole or its metabolites . This is consistent with a previous observation which reported that increased TcAPx expression does not confer benznidazole resistance [11] . Therefore , if redox stress has any role in the activity of this drug , it is unlikely that generation of H2O2 within the ER is a significant component . The null mutants retained an ability to progress through the life cycle in vitro but did display a slightly decreased ability to infect cultured mammalian cells and an increased sensitivity to H2O2 . We therefore investigated whether these deleterious phenotypes had any effect on their ability to establish a chronic infection in a murine model . The Sylvio X10/6 strain used in this study is not highly virulent . In most murine models , parasites are rarely detected in the bloodstream by microscopy , even during the acute stage of infection . This has been noted with other clones in the Sylvio X10 series [24] . We therefore exploited a highly sensitive T . cruzi bioluminescence imaging model developed in our laboratory , which allows chronic infections to be monitored in real time [19] . In this model , there is a linear relationship between parasite burden and bioluminescence , and a robust correlation with qPCR . Both wild type and TcΔAPx null mutant parasites were transformed with the pTRIX2-RE9h-Hyg vector ( Methods ) , which facilitates the targeting of a red-shifted luciferase gene [25] into the RRNA array , such that expression is under the control of a strong RNA polymerase I dependent promoter . The growth rate of the bioluminescent transfectants was assayed in vitro to determine whether expression of the luciferase gene had any effect . The doubling time was not significantly different between the wild type pTRIX2-Re9h-Hyg transformants and the TcAPX null mutants expressing luciferase ( S3 Fig ) . The bioluminescent lines were also assayed for luciferase activity to ensure that the clones used in infection studies expressed similar levels of bioluminescence . The luciferase activity for each of the cell lines is shown in S4 Fig . BALB/c mice were inoculated with bioluminescent trypanosomes ( Methods ) and the course of infection followed over 56–60 days . Six mice were infected with each parasite line . Both null mutant clones showed a similar pattern of infection to the bioluminescent wild type cells ( Fig 4A ) . There was an initial dispersal of parasites from the intra-peritoneal injection site , with dissemination throughout the mice during the 14 days leading to the peak of the acute stage of the wild type infection . With the Sylvio X10/6 strain the wild type does not produce a symptomatic , patent acute phase and trypomastigotes are not observed in blood smears . This has also been demonstrated with the Sylvio X10/4 strain [24] . The null mutants showed a similar pattern of dispersal throughout the mouse , although total body flux peaked between day 7 and 14 rather than at day 14 ( Fig 4B ) . By day 28 all three cell lines were behaving comparably , and a more focal pattern of infection , characteristic of the chronic stage , was observed ( Fig 4A ) . The total body flux suggested very similar levels of parasite burden after day 28 ( Fig 4B ) , regardless of the presence or absence of TcAPx This infection profile matches that seen with the CL-Brener strain [19] . Ex vivo imaging of selected tissues and organs from necropsies of infected mice immediately post-mortem ( Methods ) showed that the gastro-intestinal tract ( stomach and/or colon ) was the major site of parasite persistence following establishment of chronic stage infection . Sporadic bioluminescent foci were observed associated with other sites in some animals , including the gut mesenteries , heart and lungs , but there was no pattern with respect to experimental groups ( Fig 5 ) . Thus , there were no significant differences in tissue-specific distribution observed between the wild type parasites and the null mutants . This profile of persistence in the GI tract and sporadic infection of other sites is also observed with the CL-Brener strain at a similar stage of infection [19] . Taken together , these results therefore indicate that TcAPx is not essential for the establishment of an acute infection , dispersal of parasites throughout the host , or for their persistence in their gastro-intestinal niche during the chronic stage .
In this study , we have shown that the T . cruzi ascorbate peroxidase protects the parasite from H2O2 exposure , but it is dispensable during each life-cycle stage in vitro and is not required to give rise to chronic infections in a mouse model . Initially , we had found that sequential targeted disruption of both TcAPx alleles could not be achieved , except in the presence of an episomal copy . However , further experimentation demonstrated that this ectopic copy itself was not maintained in the absence of selective ( G418 ) pressure , and that null mutants were then obtained . It is reasonable to assume that total loss of TcAPx activity must have detrimental consequences to the parasite under the conditions pertaining during the selection process , and that this is sufficient to prevent the outgrowth of homozygote knockouts . The subsequent ability of null mutants to survive the gradual loss of the ectopic copies could reflect differences in the culture environment in the two situations , and/or a metabolic adaptation over time which accommodates the loss of ascorbate peroxidase activity . This outcome highlights the fact that the inability to generate T . cruzi null mutants by conventional methods should not , of itself , be taken as evidence that a gene is essential . Our data imply that TcAPx activity is not required for any of the fundamental processes governing parasite replication , development and virulence . The enzyme is localised to the endoplasmic reticulum and , unlike other trypanosomatid peroxidases , it has a substrate specificity that is limited to H2O2 [11 , 26] . In the ER , H2O2 is produced as part of the reaction cycle of Ero1 , a luminal membrane associated flavoprotein that mediates disulphide bond formation in client proteins , with one molecule of H2O2 produced each time Ero1 reduces protein disulphide isomerase [27 , 28] . In mammalian cells which lack APx , the ER resident glutathione peroxidases 7 ( GPx7 ) and 8 ( GPx8 ) are utilised to remove H2O2 generated during this process [29 , 30] . Trypanosomatids do not have selenium-dependent glutathione peroxidases such as GPxs 7 and 8 . It is likely therefore , that a major role of TcAPx in T . cruzi is to eliminate peroxide molecules produced by the Ero1 reaction . In T . brucei and Leishmania , which lack an ER-localised APx , this function may be performed by other ER associated peroxidases [31] , or the H2O2 may itself be utilised as an oxidant in protein folding as has been shown in mammalian cells [30 , 32] . The membrane-permeable properties of H2O2 allow it to penetrate all compartments of the cell , including the ER . This is evidenced by our observation that overexpression of TcAPx confers protection against exogenous H2O2 exposure , whereas depletion results in enhanced sensitivity . Thus , our results suggest that in the null mutants , there are no effective alternative mechanisms for clearing high levels of H2O2 from the ER , and that this leads to cell death at lower exogenous concentrations than in wild type parasites . As Ero1 is localised in the ER , it could be that membrane phospholipids are the primary target of the H2O2 generated by this protein . T . cruzi also expresses an ER resident non-selenium glutathione dependent peroxidase ( TcGPX II ) which catalyses the reduction of lipid hydroperoxides [26] . This activity may compensate to an extent for depletion of TcAPx by protecting the ER membrane from oxidative damage . ER resident ascorbate itself may also have an additional antioxidant effect , even in the absence of TcAPx . The susceptibility of null mutants to benznidazole was the same as wild type parasites . This is consistent with previous data which showed that overexpression of TcAPx has no effect on susceptibility to this nitroheterocyclic agent [11] . Benznidazole treatment does have a major effect on thiol biochemistry within the parasite , and leads to depletion of trypanothione [7] . Because of the central antioxidant role of this major low molecular weight thiol , benznidazole treatment may render T . cruzi more susceptible to oxidative stress . However , it is implicit that this enhanced susceptibility cannot be mediated via a build up of H2O2 within the ER , as depletion or overexpression of TcAPx has no effect on benznidazole sensitivity . The TcAPx null mutants were able to establish a chronic infection in mice , despite a reduced infection capacity in vitro . Although they appeared to produce a slightly shorter acute phase , they displayed similar tissue tropism to wild type parasites , with persistence in the gastro-intestinal tract ( particularly in the stomach and the colon ) after immune-mediated clearance from most other sites . We have observed a similar pattern in chronic murine infections with the CL-Brener strain of T . cruzi [19] . It can be implied that TcAPx is not essential for immune evasion and that an oxidative burst that generates high exogenous levels of H2O2 is not a significant component of the response to this parasite . Deletion of the Leishmania major orthologue of TcAPx ( LmAPx ) also results in a hypersensitivity to exogenous H2O2 [33] . However , in that case the null mutants exhibited an enhanced virulence phenotype in the mouse footpad model for cutaneous leishmaniasis . These authors suggest that this may be due to an increased number of “apoptotic” parasites in the null mutant population . The LmAPx protein occurs in the mitochondrion rather than the endoplasmic reticulum and therefore plays a different biological role in Leishmania compared to T . cruzi [14] . Secondly , invasion of Leishmania is restricted to professional phagocytic cells where the parasite replicates in the phagolysosome , whereas T . cruzi can infect both phagocytic and non-phagocytic cell types , and replicates in the host-cell cytoplasm . These factors could account for the differential effects on virulence . In summary , the data presented here clearly demonstrate that TcAPx is not a suitable target for drug development , since inhibition of its activity would not have a significant effect on parasite virulence or infectivity .
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The single-cell parasite Trypanosoma cruzi causes Chagas disease , one of the major neglected tropical infections . Throughout Latin America , this disease is an important cause of premature death due to heart failure , and it is currently an emerging public health problem in the US , Europe and across the world . There are only two drugs available to treat the infection , benznidazole and nifurtimox . Both have significant side effects and resistance/treatment failures are increasing . The T . cruzi vitamin-C dependent peroxidase ( TcAPx ) is an anti-oxidant enzyme which is absent from the mammalian host , and has been proposed as a potential drug target . Using genetic manipulation , we have deleted the genes for this enzyme from T . cruzi . The resulting null mutants were hypersensitive to hydrogen peroxide but displayed normal sensitivity to benznidazole . Using a bioluminescent model of infection , we could demonstrate that the null mutants were able to establish a similar infection to that of wild type parasites . Our results show that TcAPx should not be pursued as a target for drug design .
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[
"Abstract",
"Introduction",
"Methods",
"Results",
"Discussion"
] |
[] |
2015
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The Trypanosoma cruzi Vitamin C Dependent Peroxidase Confers Protection against Oxidative Stress but Is Not a Determinant of Virulence
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Many neurons are unable to regenerate after damage . The ability to regenerate after an insult depends on life stage , neuronal subtype , intrinsic and extrinsic factors . C . elegans is a powerful model to test the genetic and environmental factors that affect axonal regeneration after damage , since its axons can regenerate after neuronal insult . Here we demonstrate that diapause promotes the complete morphological regeneration of truncated touch receptor neuron ( TRN ) axons expressing a neurotoxic MEC-4 ( d ) DEG/ENaC channel . Truncated axons of different lengths were repaired during diapause and we observed potent axonal regrowth from somas alone . Complete morphological regeneration depends on DLK-1 but neuronal sprouting and outgrowth is DLK-1 independent . We show that TRN regeneration is fully functional since animals regain their ability to respond to mechanical stimulation . Thus , diapause induced regeneration provides a simple model of complete axonal regeneration which will greatly facilitate the study of environmental and genetic factors affecting the rate at which neurons die .
Animals that enter diapause or hibernate not only survive for long periods of time without eating , but also preserve their nervous systems [1– 3] . This protection has been proposed to be a result of a high capacity for detoxification and maintenance of low oxidative stress [1– 4] . The bacterivore nematode Caenorhabditis elegans exits development and enters diapause under environmental stresses such as food deprivation , crowding , high temperatures , and exposure to pathogenic bacteria [5– 7] . Animals that enter diapause undergo a profound restructuring of physiology , morphology , metabolism and gene expression to accommodate lack of caloric intake . C . elegans animals that enter diapause become dauer larvae that live off fat reserves , which are tightly rationed by AMPK phosphorylation of lipase ATGL-1 [8] . In the absence of environmental stress , C . elegans undergo reproductive development and progress from embryos through four larval stages ( L1–L4 ) to the adult stage . In contrast , dauers arrest progenitor cell lineages at a late-L2 like state which at the exit of quiescence , resume post dauer L3 fate [9] . Like L1-L2 larvae , dauers most likely use the glyoxylate cycle to generate gluconeogenic intermediaries from acetyl CoA [10] . We previously showed that in models of neuronal degeneration , neurons were completely protected in dauers . In this work , we use a simple model of axonal degeneration comprising a single neuron with a long process , a genetically encoded pro-degenerative stimulus and a simple behavioral test that assesses the function of a neuron , to study the environmental and genetic factors affecting axonal regrowth . Our model differs from axotomy in that the expression of hyperactive degenerins constitutes a chronic injury as opposed to the discrete damage produced by laser axotomy in multiple animals including C . elegans [11– 13] , Drosophila melanogaster ( fruit flies ) [14 , 15] , Danio rerio ( zebrafish ) [16] , and mammals [17] . We find that diapause strongly promotes the morphological and functional regeneration of mechanosensory axons that were broken by a genetically encoded trigger of chronic injury . Additionally , we show that wild-type dauers regenerate mechanosensory axons after a discrete injury conferred by laser axotomy . We further show that complete morphological and functional regeneration but not sprouting depends on the function of DLK-1 .
The expression of constitutively active degenerins such as mec-4d ( e1611 ) and deg-1 ( u38 ) in C . elegans sensory neurons causes the necrotic death of those neurons [18– 21] . The mec-4d mutation , results in the expression of a dysfunctional MEC-4 pore-forming unit in the touch receptor neurons ( TRNs ) [22] . MEC-4d expression causes the unregulated entry of cations to the cell , provoking cell swelling , activation of proteases and the energetic collapse of the neurons [23 , 24] . Embryonic TRNs , the Anterior Lateral Microtubule ( ALM ) and the Posterior Lateral Microtubule ( PLM ) neurons of the touch circuit arise between 400 to 500 minutes after the first zygote division in embryonic development [25] . In mec-4d mutants , embryonic TRNs have already died at the time of hatching , with somas of ALMs , PLMs and the Posterior Ventral Microtubule ( PVM ) vacuolated in early L1s [3 , 24] ( S1 Fig ) . The PVM neuron is also born at 12 hours after hatching in wild type animals . However , development of the PVM is difficult to analyze in the mec-4d background because only 3% and 4% of truncated axons are seen 48 and 72 hours after hatching , respectively , S1 Fig ) . The AVM ( Anterior Ventral Microtubule ) neuron is born 12 hours after hatching , and in mec-4d animals , degenerates in a time dependent manner and with a stereotyped change in morphology ( Fig 1A and 1B , detailed description in Materials and Methods ) . First , the distal end of the axon breaks and small fragments of the severed axon degenerate ( Axon Long , AxL ) . Subsequently , larger fragments of axon degenerate ( Axonal Truncation , AxT ) , followed by the disappearance of all fragmented processes ( Fig 1A and 1B and reference [3] ) . To understand how AVM morphology correlates with function , we analyzed axon morphology of mec-4d L4 larvae using fluorescence microscopy and tested their ability to respond to touch [26] . The presence of wild-type and long AVM axons ( AxW and AxL ) was strongly correlated with function , while animals with truncated axons ( AxT ) , without axons ( either with ( AxØ-S ) or without a soma ( AxØ ) were largely touch insensitive ( Fig 1D ) . While the number of functional axons ( AxW and AxL ) decreased with time , there was a brief increase in the number of animals with short axons ( AxT ) during the L2 stage ( Fig 1E ) . The time-dependent decline of wild-type axons observed in Fig 1C during development and adulthood is no longer observed if animals arrest as dauers in the late L2 larval stage , approximately 24–36 hours after hatching . After a week in the dauer stage , a large number of animals displayed wild-type axonal morphology that lasted for the duration of diapause ( Fig 1F ) . Degeneration resumed immediately after dauer recovery ( Fig 1G ) , suggesting that optimal conditions for neuroprotection and/or inhibition of degeneration that occur during diapause are lost as soon as animals feed ad libitum . Since the fraction of wild-type axons after 7 days in diapause ( Fig 1F ) was much higher than those present at 12 or 24 hours in normal development ( Fig 1B and 1C ) , it is likely that during diapause , regrowth of axons may be the underlying reason for the observed protection . To test whether axons were able to regenerate during diapause , we assessed the morphological and functional changes of the mec-4d AVM neuron immediately after the formation of dauer larvae ( first day of dauer , definition in Materials and Methods ) , and compared it to animals that had been in dauer for one week , 30 , 60 , or 90 days ( Fig 2A , detailed description in Materials and Methods ) . To determine if the axonal morphology of the dauer mec-4d AVM correlated with function , we analyzed the animals’ ability to respond to touch to the anterior part of the body of dauer animals [3] and individually scored their AVM morphology . 90% of animals with wild-type axons ( AxW ) or axons with a process that extends to the nerve ring ( AxL ) were touch sensitive , while those with short axons ( AxT ) or without axons ( AxØ-S or AxØ ) were largely touch insensitive ( Fig 2B ) . This shows that the ability to respond to gentle touch of a given morphological category is similar in dauers and developing larvae . The wild-type touch response of dauer mec-4d mutants suggests that MEC-4d channels are active during diapause [3] . The first day of dauer , 30 . 2% of animals had wild-type axons while on the seventh day of dauer this number increased to 71 . 4% , strongly suggesting that broken axons can regrow when animals are in diapause . The fraction of wild-type axons increased significantly after one month in diapause ( to 78 . 5% , p = 0 . 002 ) and remained unchanged until 60 days in diapause ( Fig 2C ) . The fraction of truncated neurons ( AxL and AxT ) decreased with time while the number of neurons with only a soma decreased at the 7th day in diapause . At 90 days ( 3 months ) in diapause , the number of wild-type axons decreased to 48 . 4% . This coincides with the limits of the lifespan of dauer animals . To test whether the decline of neuronal integrity in diapause was related to the expiration of dauer animals , we measured the lifespan of mec-4d dauer animals using N2 animals as controls . Only 10% of mec-4d dauer animals were still alive at day 90 ( 50% of wild type dauer animals were alive at day 90 , S2 Fig ) . This may suggest that AVMs resume degeneration as a consequence of dauer animals reaching the end of their energy availability , which impacts on systemic and touch receptor neuron ( TRN ) ion homeostasis . Can diapause entry stimulate regeneration of other axons ? In mec-4d mutants the embryonic TRNs , ALM and PLM , died at the time of hatching [3 , 24] , and are therefore impractical for testing dauer regrowth . We previously observed that neurodegeneration of the TRNs was slower at 25°C compared to 20°C [3] , providing an experimental setting to test the regrowth of embryonic neurons in diapause . To examine the ability of embryonic touch cells to regenerate during diapause after mec-4d induced injury , we starved animals that had hatched at 25°C , a temperature at which approximately 50% of day 1 dauers had either truncated or wild type appearing ALM or PLMs ( Fig 2F and 2G ) . We scored the neuronal integrity of dauer ALMs and PLMs at days 1 , 7 and 30 of diapause . The observed increase in morphologically wild-type axons between the first and seventh day of diapause indicates that the ALMs and PLMs are capable of regenerating during diapause ( Fig 2F and 2G ) . Specifically , 54% of animals had wild-type axons on the first day of diapause , while at 7 days this number significantly increased to 76% , and was maintained at 30 days . To confirm the ability of ALM axons to regenerate during diapause , we severed wild type ALM axons with a pulsed laser and measured regeneration 18–24 hours later . We found that like ALM axons chronically injured by mec-4d expression , ALM axons regenerated after being severed during diapause ( Fig 2H ) . Next , we tested whether diapause induced the functional regeneration of the PVC interneurons expressing the deg-1 prodegenerative stimulus [18] . deg-1 animals progressively lose the ability to respond to posterior touch due to the time dependent degeneration of the PVC interneuron [18] . We scored the ability of synchronized populations of deg-1 animals ( L2/L3 larvae , young adults and one-week dauers ) to respond to posterior touch . While 18% and 7% of L2/L3 and adult animals , respectively , responded to tail touch , 53% of dauer animals responded to tail touch ( Fig 2I ) , demonstrating functional regeneration of the PVC neuron . Our findings indicate that diapause strongly stimulates regeneration in two different sets of degenerating neurons . To further examine the AVM changes that occurred during the first seven days in diapause , we assessed AVM morphology and the ability to respond to gentle touch in populations of synchronized dauer animals every 24 hours ( see Materials and Methods for details ) . The first significant change in the number of wild-type axons occurred on the third day of diapause compared to animals in the first day of diapause ( 41 . 4% vs 30 . 1% , respectively ) , reaching 60% on the seventh day of diapause ( Fig 3A and 3B ) . The number of short truncated axons ( AxT ) decreased between days 1 and 4 , and long axons ( AxL ) disappeared at day 7 . Interestingly , the number of AVMs with only a soma ( AxØ-S ) decreased between day 1 and day 7 , likely due to regrowth of their axon , while the number of animals with fully degenerated AVMs ( no soma or axon present , AxØ ) , did not change in time ( Fig 3A and 3C ) . This suggests that AVM neurons cannot arise de novo if their somas have degenerated , but that surviving AVM somas can regenerate an axon after mec-4d induced degeneration . Importantly , the number of touch sensitive mec-4d animals increased during the first week of diapause ( Fig 3D ) , which correlates with the increase in number of wild-type axons during the first week of diapause ( Fig 3E ) . Wild-type ( N2 ) dauer animals were touch sensitive showing that TRNs function normally during diapause , while mec-4 ( u253 ) loss-of-function mutants were completely insensitive . This demonstrates that the MEC-4 channel is required for mechanical response to gentle touch in diapause and it is therefore unlikely that other channels are contributing to the touch response in mec-4d dauer animals . We analyzed the distribution of MEC-4 channels along the TRN axons by measuring the number of MEC-4::GFP puncta in the PLM neuron . L2 animals exhibit an average of 22 puncta in 120 μm , while animals in dauer and at dauer exit had an average of 19 puncta per 120 μm ( Fig 3F ) . This small yet significant difference does not diminish the degree of the touch response of animals ( Fig 3D and 3F and S3 Fig ) . To understand whether the initial morphology of axons impacts their ability to regenerate , we analyzed 71 individual dauers at the first and third day after diapause entry ( details in Materials and Methods ) . The third day was the earliest time point when a significant increase in wild-type AVM morphology was observed in the population-based experiments ( Fig 3B ) . When dauers resume development , they exit as L3/L4 larvae , which have larger pharynx than dauer animals . To ensure that animals remained at the dauer stage in our experiments we measured the pharyngeal width of mec-4d dauer animals , L3 animals and L4 animals ( S4 Fig ) . The average pharyngeal width of dauer animals was 10 . 2 μm , while the average pharyngeal width of L3 and L4 animals was 20 . 6 and 24 . 3 μm respectively . Pharyngeal widths confirmed that animals followed longitudinally remained as dauers after three days . Average values for the width of the mec-4d animals’ pharynxes did not change between day 1 and day 3 of diapause and were approximately 11 μm ( S2 Table ) , similar to the values for dauer animals ( S4 Fig ) . On the third day , 65% of animals had regenerated their AVM axons ( S1 Table ) , and 35% had not ( S3 Table , pharyngeal measures in S4 Table ) . Importantly , the number of animals with wild-type axons examined longitudinally ( 40 . 8% ) was similar to the 41 . 4% observed in the population-based studies ( Fig 3B ) . Neurons with a soma but without an axon ( AxØ-S ) on the first day of diapause displayed the highest growth after three days , both in length ( μm ) and percentage of growth ( Fig 3G and 3H ) . Fig 3I shows images of individual dauer animals with growing axons , starting at day 1 with only somas ( AxØ-S ) or truncated axons ( AxT ) and reaching wild-type length on the third day . Conversely , animals that entered diapause without neurons ( 30 individual AxØ animals ) did not regrow a soma or axon ( Fig 3H and S5 Table ) , which cannot be attributed to accidental exit from diapause ( animals maintained a typical dauer morphology and narrow pharynx , S6 Table ) . Therefore , although dauer animals are capable of regenerating axons from a mechanosensory soma , they are not able to replace degenerated mechanosensory somas . Is the regenerative capacity of dauers comparable with that of developing animals , especially young larvae , which have a high capacity to regenerate [27] ? Because mec-4d is a chronic prodegenerative stimulus and diapause entry is protective , the comparison between development and diapause required an acute stimulus , where degeneration was slowed or stopped after damage . A stimulus that decreases degeneration is growing mec-4d animals at 25°C . At 25°C the ALM and PLMs did not degenerate during embryogenesis and are present after hatching and for several hours afterwards ( Fig 2D and 2E ) . At 25°C , the AVMs also developed normally until 48–72 hours after hatching ( S4 Fig and reference [3] ) . This allows the efficiency of regeneration of dauer animals to be compared to that of animals in development . Possible reasons for the protection of axons in mec-4d animals at 25°C include reduced MEC-4 channel expression , diminished function , and that a process required for degeneration downstream of channel activation is affected at higher temperatures . To test whether the expression of MEC-4 channels is affected at 25°C we measured the number of puncta in the PLMs of animals expressing MEC-4::GFP ( see above and Materials and Methods ) at 20ºC and 25ºC in L2 , 1-day and 1-week dauer animals and at in animals that had exited the dauer stage ( representative images of neurons at both temperatures are shown in S3 Fig ) . The number of MEC-4 channels in the TRN axons at each stage was similar at both temperatures , therefore expression of MEC-4 is not affected by temperature either in development or diapause ( Fig 4A ) . To assess mechanosensation at 25°C , we quantified the number of responses of developing animals to 10 anterior and posterior touches [26] . We found that wild-type animals responded to 100% of touches at 15°C and 20°C however animals responded 50% less frequently at 25°C ( Fig 4B ) . This suggests animals raised at lower temperatures might habituate faster to mechanical stimulation than those raised at 25°C . We next asked whether the decrease in the touch response observed at 25°C was due to transient or persistent molecular , cellular or biochemical change , which might include altered gene expression , protein localization , and protein modification . We grew animals at 15°C and 25°C until the L4 stage and performed touch tests immediately , 4 hours , and 24 hours after a temperature shift to 25°C or 15°C . After the temperature shift , animals responded with the same frequency that they had responded at the temperature they were raised ( Fig 4C ) , suggesting that temperature induces a change that lasts for at least 24 hours . Taken together these results suggest that 25°C causes a long-lasting change that affects either the function of the MEC-4 channel itself or an intracellular process downstream of the MEC-4 channel . To compare the growth of damaged axons during diapause with that of normal animal development , we chose the ALM and PLM touch receptor neurons . Unlike the AVM , the ALM and PLM complete development before hatching; therefore , axon regeneration can be evaluated independently of developmental axon outgrowth in the ALM and PLM . We compared the dynamics of mec-4d-dependent ALM and PLM axon degeneration in populations of worms ( Fig 4D and 4E ) and in individual worms ( Fig 4F and 4G , and S7 and S8 Tables ) , during development and in diapause , at 25°C . We started with animals that had a soma with or without an axon ( AxT , AxL , AxØ-S ) , excluding the AxØ category . In both the population and individual studies , the ALM and PLM axons degenerated during development , yet regrew in dauer animals ( classification in Figure Legend ) , indicating diapause is a strong inductor of regeneration in the mec-4d degenerin model of degeneration . We next asked whether the molecular mechanisms that regulate dauer formation also regulate axon degeneration and repair in mec-4d axons . Dauer formation is accompanied by recognizable molecular changes such as the downregulation of the Insulin Receptor DAF-2 and the nuclear translocation of DAF-16/FOXO [28] . Not only does daf-2 regulate dauer formation , it has also been shown to regulate axon regeneration after laser-induced injury [29– 31] . To determine whether loss of daf-2 affects mec-4d induced changes in axon morphology in dauer animals , we performed a population-based time course analysis of axonal morphology of daf-2ts; mec-4d dauers every 24 hours for 1 week . The daf-2ts allele is a temperature sensitive mutation that reduces daf-2 function at 25°C . Fig 5A shows that daf-2ts; mec-4d animals have significantly more wild-type axons at 20°C than mec-4d animals throughout the first week in diapause , except in days 3 and 4 . A possible reason is that 20°C is semi-permissive for DAF-2 function and even though there are more wild-type axons in daf-2; mec-4d , they are not statistically different from mec-4d . At 25°C where DAF-2 is completely nonfunctional , both strains behaved similarly ( Fig 5B ) . This suggests that at 25°C DAF-2 disfunction provided by dauer entry and the non-permissive temperature are inseparable . This , together with the hypofunction of MEC-4d ( Fig 4B ) render a highly protective environment . In an effort to further separate the global state of diapause from DAF-2 downregulation , we evaluated the neuronal integrity of AVMs and ALMs in dauers raised at 25°C and temperature shifted to 15°C or 20°C . Temperature shift of daf-2ts; mec-4d dauers but not mec-4d from the non-permissive ( 25°C ) to the permissive ( 15°C ) temperature significantly reduced the number of AVM and ALM wild-type axons during diapause ( Fig 5C and 5E ) . Temperature shifts to 20°C , a semi-permissive temperature for insulin signaling , did not diminish dauer protection ( Fig 5D and 5F ) . Importantly , shifting the temperature from 25°C to 15°C during diapause did not cause animals to exit the dauer state . Together , these results show that inactivation of DAF-2 regulates axonal maintenance in dauer animals . To test whether DAF-2 hypoactivity induced regrowth of the touch receptor neurons independently of dauer formation , daf-2ts; mec-4d animals hatched at 20°C were shifted to 15°C or 25°C as L1 larvae . To control for the protective effect of higher temperatures on the mec-4d induced degeneration ( reference [3] and S5 Fig ) we used mec-4d animals for comparison . daf-2ts; mec-4d animals shifted at birth to 25°C started with less wild-type axons at 24 hours than mec-4d mutants , but had a significantly larger number of AxW axons at 48 and 72 hours ( Fig 6A ) . Axons in daf-2ts; mec-4d animals shifted to 15°C , where DAF-2 is fully functional , were indistinguishable from those in mec-4d mutants . These results suggest that DAF-2 downregulation contributes to neuronal protection [3] and potentially to axonal regrowth of mec-4d damaged axons . To directly test whether DAF-2 downregulation promoted regrowth of axons , we performed temperature shifts at later stages of development when AVM was already born and had various degrees of degeneration . daf-2ts; mec-4d and mec-4d animals born at 20°C were kept for 24 hours at the permissive temperature of 15°C . After 24 hours at 15°C , animals were shifted to 25°C and their morphology was scored 24 and 48 hours later ( Fig 6B ) . While in mec-4d animals the change in wild-type axons was not significantly different , daf-2ts; mec-4d animals regrew their AVM neurons 48 hours after the shift from 15°C to 25°C ( 72 hours after hatching , Fig 6B ) . This result suggests that DAF-2 downregulation promotes regrowth of axons in non-dauer mec-4d animals . DAF-16 activation is a key downstream factor in the inhibition of regeneration caused by DAF-2 [29] . To test the role of daf-16 in the degeneration of the TRN we compared the time course of degeneration in mec-4d animals to daf-16; mec-4d mutants . daf-16 mutation caused a rapid degeneration of the mec-4d AVM , starting from 12 hours post hatching ( Fig 6C and 6D ) . Conversely , transgenic overexpression of DAF-16 conferred significant protection to the integrity of the AVM ( Fig 6E ) and its function ( Fig 6F ) . These results show that DAF-16 plays a crucial role in the protection of mec-4d axons conferred by DAF-2 downregulation . The mitogen-activated protein kinase kinase kinase DLK-1 is essential for axon regeneration in models of axonal damage in C . elegans [13 , 32] , Drosophila [33] , and mice [34–36] and has been implicated in neuronal development and degeneration in diverse organisms [37– 40] . We asked whether mec-4d-induced TRN degeneration and later diapause-induced regeneration in C . elegans require DLK-1 function . To answer the first question , we scored AVM morphology during normal development and in diapause in dlk-1 ( km12 ) loss-of-function mutants , in a wild-type or mec-4d background . During normal development of mec-4d; dlk-1 animals , only 11 . 1% of the animals had wild-type AVM neurons at 24 hours , similar to the number of wild-type AVM neurons to mec-4d animal at 24 hours . However , unlike mec-4d animals , the number of wild-type axons in mec-4d; dlk-1 animals did not change in adulthood and for several days after fertility ( Fig 7A ) . This suggests that DLK-1 is needed for degeneration of the TRNs as shown for Drosophila and mice [37] . Fig 7B shows the number of AVM neurons remaining ( the sum of all neurons with axons , regardless of category ) for mec-4d and dlk-1; mec-4d animals during the course of development and adulthood . While mec-4d animals completely degenerated their axons , dlk-1 loss impaired the normal course of degeneration . Most truncated ( AxT ) neurons in dlk-1; mec-4d mutants displayed neurite defects during development that increased as animals aged . Fig 7C shows the number of animals with defective AVM ( neurons with posterior processes , double axons and random sprouting from cell soma and axon ) within the AxT category in a temporal course . These defects were only visible in dlk-1; mec-4d animals , because dlk-1 mutants did not display abnormalities in AVM development ( dlk-1; Pmec-17mec-17gfp in Fig 7D ) or in touch response ( Fig 7E ) . We also observed that dlk-1 mRNA expression in mec-4d mutants is higher than in wild-type animals both in development ( Fig 7F ) and diapause ( Fig 7G ) . Together , this shows that DLK-1 plays an important role in TRNs upon neuronal damage . To understand the role of DLK-1 in axon regeneration observed in diapause animals , we performed a population-based time course analysis of axonal growth in dlk-1; mec-4d dauer animals . Like non-dauer dlk-1; mec-4d animals a number of dauer animals also displayed neurite defects ( Fig 8A ) . The number of wild-type axons ( AxW ) did not vary significantly between the first and seventh day , indicating that DLK-1 is needed for growth of axons in diapause ( Fig 8B ) . Analysis of longer times into diapause showed that axonal categories remain mostly unchanged in dlk-1; mec-4d animals . Especially wild-type axons were not significantly different throughout the 35 days ( Fig 8C ) . Given that loss of dlk-1 rendered axons largely static; we wondered whether neurons that were technically capable of responding ( AxL and AxW ) did so . Touch tests were performed on dlk-1; mec-4d dauers that were subsequently mounted on agar pads for observation . AxW and AxL AVM neurons were non-functional in dlk-1; mec-4d mutants ( Fig 8D ) , suggesting that even when their morphology is intact , the function of these neurons is impaired . To further study the AVM dynamics of dlk-1; mec-4d animals , we analyzed and measured individual axons in a 3-day time course . S6 Table shows that animals stayed in diapause for the length of the experiment , as measured by the width of the pharynx . Even though dlk-1; mec-4d dauers were not capable of fully regenerating , some neurons extended small processes ( S9 Table ) . The growth observed ( 18 . 2% ) was primarily from axons that started as Ax∅ or AxT the first day of dauer and reached AxT or AxL . Importantly , 50% of the growth was erratic , with additional axonal sprouts from the cell body , double processes and neurites oriented posteriorly ( Fig 8A and S9 Table ) . This shows that there is a small DLK-1 independent outgrowth of neurites in mec-4d axons , but full-length regeneration requires DLK-1 during diapause .
Dormancy in the form of diapause and hibernation allows the preservation of tissues and organs for long periods of time in complete absence of food intake . A common feature of different types of dormancy is the decrease in metabolic rate and gene expression [41– 45] . The nervous system is a remarkable example of tissue preservation during restoration of blood flow in hibernation [1 , 2] and protection from injury during diapause [3] . In this work , we show that C . elegans undergoing diapause are capable of fully regenerating damaged touch receptor neurons expressing a constitutively active degenerin , MEC-4d . Neuronal growth in mec-4d-expressing animals is in most cases complete as 36% more axons have a wild-type morphology by the seventh day of diapause compared to the first day of diapause and 72% of axons are functional on the seventh day of diapause ( Fig 3D ) . This protection is long lasting , as 86% of AVM neurons are functional after 2 months in diapause ( Fig 2C ) . Strikingly , elongation of mec-4d AVM axons during diapause is morphologically indistinguishable from developmental outgrowth of wild-type AVM axons , as most axons reach the maximum length of the developmental neurons ( Fig 3I ) . The finding that the number of morphologically wild-type axons increases with time in diapause , while the number of truncated axons ( whose distal axon segments have already degenerated ) decreases , suggests repair of these truncated axons is unlikely to be caused by the fusion of severed distal and proximal axons that has been observed in other models of axon repair [46– 48] . Together , our data indicate AVM axons in mec-4d dauer animals are capable of complete morphological regeneration and full restoration of mechanosensation . The ALM and PLM mechanoreceptors expressing the mec-4d degenerin ( Fig 2F ) , as well as the PVC interneuron expressing the deg-1 degenerin ( Fig 2I ) , the ALM after axotomy ( Fig 2H ) , and the ASJ sensory axons after injury [49] all regenerate in dauer animals , suggesting that diapause may promote regrowth of a broad number of neuronal types in response to various forms of injury . Beyond neuronal tissues , it will be important to study whether diapause can also promote the regeneration of other structures given that changes during dormancy are systemic . Interestingly , in the Colorado potato beetle the completely degenerated wing muscles fully regenerate during diapause [50] . Factors that may play an important role in diapause-induced regeneration are low metabolic rate , increased function of pro-regenerative genes , and decreased function of genes that inhibit regeneration . A hallmark of dauers , non-ageing larvae , is the downregulation of the DAF-2 insulin receptor . Interestingly , axonal regeneration in aging motor neurons is inhibited by DAF-2 , through regulation of the intrinsic neuronal activity of the DAF-16/FOXO transcription factor [29] . Congruently , our experiments show that daf-2; mec-4d mutant animals significantly regenerate the AVM neuron in non-dauer animals ( Fig 6B ) . The protective and regenerative effects of DAF-2 downregulation in mec-4d dauers is likely mediated by DAF-16 . We show that DAF-16 overexpression maintains neuronal integrity ( Fig 6E ) , while daf-16 mutation enhance degeneration of mec-4d neurons ( Fig 6D ) . Importantly , turning DAF-2 on in dauers decreases the number of animals with wild-type AVM and ALM axons ( Fig 5C ) . This suggests that DAF-2 downregulation in diapause is upstream of several changes in protein activity and gene expression underlying axonal regeneration , likely triggered by the activation of DAF-16 among other changes . DAF-16 has a large number of evolutionarily conserved transcriptional targets , including genes involved in cellular stress-response , antimicrobial and metabolic genes [51– 53] . Importantly , expression of DLK-1 , a key regulator of regeneration , is regulated by DAF-16 in neurons and downregulated by insulin/IGF1 signaling [29] . The extent of axon regeneration in dauers is larger than the extent of axon regeneration observed in daf-2 ( ts ) mutants during normal development ( Figs 2C and 6B ) . The increased regenerative ability could be a consequence of the incomplete downregulation of DAF-2 in the temperature sensitive mutant or due to the influence of other gene expression changes that occur independently of insulin pathway function . Once AVM axons have regenerated , the wild-type morphology is maintained until day 60 of diapause ( Fig 2C ) . Likely , diapause creates a systemic and cellular environment that , in addition to enhancing axon regeneration , also protects neurons from degeneration even when the mec-4d prodegenerative stimulus is active . This protection is in part explained by the activation of DAF-16 and downstream transcriptional targets such as catalases and superoxide dismutase enzymes [54] , which confer a high antioxidant capacity to dauer larva , and collectively inhibit neuronal degeneration [3] . Other relevant factors that contribute to the protection of mec-4d axons in diapause remain to be discovered . It will be important to study the electrophysiological properties of the MEC-4d channel in dauer quiescence to better understand the cause of the lack of degeneration . The ability of dauer animals to respond to mechanical stimulation suggests the channel may be functional ( Fig 3D and 3E ) . Additionally , the amount of MEC-4 expression in diapause and in non-dauer larvae is very similar [3] , suggesting that diapausing neurons have a strong ability to maintain cellular homeostasis . Individual analysis of mec-4d AVM regeneration showed that neurons with only a soma at dauer entry display the highest regenerative capacity ( 94 μm in average ) compared to neurons with truncated axons ( 47 μm , Fig 3H ) . This de novo growth of axons offers a new paradigm to study neuronal regeneration . Dauer somas and their extracellular matrix may resemble a stem cell like environment where the extension of an axon occurs anew . Interestingly , a number of anti-regenerative genes are downregulated in dauers . For example , lin-12/Notch , which limits neurite extension during development [55] and impairs regeneration [56] , is down-regulated 1 . 9-fold in dauers ( see S1 Table in [57] ) . The smallest amount of growth was observed when axons are long at diapause entry ( 30 μm of average growth ) , especially in axons connected to the nerve ring . This is consistent with the finding of Wu et al . [12] where the synaptic branch inhibits regrowth of ALM and PLM touch receptor neurons . Animals whose neurons did not regenerate were those whose soma degenerated entirely before dauer entry . These animals did not display de novo AVM neurogenesis ( S4 Table ) . The most favorable outcome of axonal repair is to regenerate circuits and to restore nervous system function . Few models of regeneration in invertebrates and mammals are able to attribute recovery of function to a specific regenerated axon . Examples in C . elegans are the recovery of movement observed after the injury induced in the D-type motor neurons [11 , 56 , 58] , and the recovery of the posterior touch response after axonal fusion of injured fragments of PLM [31 , 59] . In this work we used the term functional regeneration for those neurons that were capable of providing a response to anterior gentle touch after regrowth . The ALM , AVM , and PLM mechanosensory neurons sense touch to the body and provide input to the command neurons via both synaptic connections and gap junctions [60] . The anterior ALM and AVM touch cells are connected by a gap junction , which creates an anterior touch cell network . AVM neurons also function independently of the ALM neurons , presumably via the gap junctions with AVD and the synaptic connections with AVB [61] . The AVM neuron alone is capable of providing one or two responses out of ten to anterior touch [3 , 60] . Combining the response to one anterior touch as a measure of AVM function with visualization of AVM morphology ( MEC-17::GFP ) , we found dauer animals are capable of functional and morphological regeneration of the touch circuit ( Fig 3E ) . DLK-1 is widely required for regeneration of axons in worm , mice and fly models of axon damage [32–35] . Additionally , though seemingly contradictory , DLK-1 has been shown to have a role in the degeneration of axons in mice and flies [37 , 38] . Here we show that after damage caused by hyperactive degenerins , DLK-1 is necessary for both degeneration when animals feed ad libitum and for complete morphological regeneration of the axons during diapause ( Fig 8D ) . DLK-1 responds to axonal damage participating in at least two processes . The first includes the stabilization of the CEBP-1 BZip transcription factor and upregulation of genes required for axon regeneration such as poly-ADP ribose glycohydrolases [13 , 36 , 58 , 62] . The second is a regulation of microtubule dynamics in C . elegans [13 , 63 , 64] that includes downregulation of the microtubule depolymerase KLP-7 and upregulation of the cytosolic carboxypeptidase CCPP-6 , which promotes microtubule growth and axon regeneration [65] . Whether DLK-1 regulates protection and regeneration of mec-4d axons in diapause through similar mechanisms is an interesting avenue of future investigation . We did observe weak DLK-1 independent regeneration at dauer entry and during the first 3 days in diapause . Upon individual examination , a 19 . 6% increase in growth at the third day was observed mostly when AVM neurons entered diapause with only a soma . This growth was always incomplete , and half of the time erratic ( Fig 8A and S9 Table ) . This is consistent with the finding of DLK-1 independent outgrowth of the ASJ sensory neurons [49] , and dendrite regeneration in Drosophila dendritic arborization neurons [66] . A possible explanation for the observed outgrowth , could be the action of the MAPKKK MLK-1 ( Jnk pathway ) , which is essential for axonal regeneration [32 , 67] . MEK-1 , downstream of MLK-1 can activate PMK-3 , and consequently generate a DLK-1-like activation [67] , bypassing the need for DLK-1 . These data suggest that even in the case that DLK-1 is inactive , there are other ways by which the mec-4d neurons can activate axonal outgrowth , but DLK-1 is necessary to achieve extended axon regeneration . In this work we use a degenerin model to study neuronal regeneration during diapause . Even though mec-4d is a chronic insult , we show that the degree of damage can be modulated by temperature . This degenerin model has previously been demonstrated to be molecularly similar to mammalian Wallerian degeneration because it shares at least three molecular characteristics: it depends on intracellular Ca2+ increase , it is delayed by blocking the mitochondrial transition pore ( mPTP ) and reduced by overexpression of nmat-2 , the C . elegans NMNAT-2 protein [3] . The relevance of this work is two-fold . First , we report that dauer quiescence is capable of functionally regenerating damaged axons . The changes that animals undergo are similar to other forms of suspended animation such as hibernation in mammals [68] . Diapause is capable of inducing full regeneration of neurons starting from a soma alone , and this regrowth is more extensive than from truncated axons . This implies that repairing a broken axon is more difficult for the cellular machinery then creating one anew . It will be interesting to explore what metabolic and molecular determinants of diapause underlie this powerful ability to regenerate neurons . Second , diapause-triggered regeneration is genetically encoded , avoiding laborious interventions to damage axons . Furthermore , diapause induction can be performed by food depletion in order to obtain large numbers of injured animals . Finally , a behavioral test can easily be used to test the functionality of the neuron . Functional regeneration but not neuronal outgrowth in diapause depends on DLK-1 , creating a broad platform for gene discovery both dlk-1-dependent and independent . This model also offers the possibility of electrophysiological examination of the MEC-4d channel in vivo , to understand its gating properties , ion selectivity under degenerative conditions , and mechanical stimulation . It will be important to investigate the metabolic changes that define a protective environment as well as the metabolic profile of neurons during diapause to better understand cell autonomous and systemic conditions that create an ideal environment for neuronal repair .
C . elegans wild type ( N2 ) and mutants TU2773 [uIs31 ( Pmec-17mec-17::gfp ) ;mec-4d ( e1611 ) X] , TU253 [mec-4 ( u253 ) X] , QW1314 [dlk-1 ( km12 ) ; uIs31 ( Pmec-17mec-17::gfp ) ; mec-4d ( e1611 ) X] , KU12 [dlk-1 ( km12 ) ] , QW1314 [dlk-1 ( km12 ) ; uIs31 ( Pmec-17mec-17::gfp ) ] , WCH34 [daf-2 ( e1368ts ) III; uIs31 ( Pmec-17gfp ) ; mec-4d ( e1611 ) X] , TU38 [ ( deg-1 ( u38 ) ] and TU3755 [uIs58 ( Pmec-4mec-4::gfp ) ] , WCH36 ( [zIs356 ( daf-16p::daf-16a/b::GFP; rol-6 ( su1006 ) ]; uIs31 ( Pmec-17mec-17::gfp ) , mec-4d ( e1611 ) X ) , and WCH39 [daf-16 ( m27 ) , uIs31 ( Pmec-17mec-17::gfp ) , mec-4d ( e1611 ) X] were maintained at 20°C in Nematode Growth Media ( NGM ) agar plates , inoculated with E . coli OP50 [69] . The expression pattern given by Pmec-17mec-17::gfp is referred in the text as mec-17::gfp and that of Pmec-4mec-4::gfp , as mec-4::gfp . E . coli OP50 was grown fresh from a -80°C glycerol stock , and streaked onto a Luria Bertani ( LB ) plate containing Streptomycin 25 mg/ml at 37°C . Next morning , a chunk of the lawn was allowed to grow for 6 hours in liquid LB with Streptomycin 25 mg/ml . 300 μl of the culture was seeded onto NGM plates and allowed to dry for 18–24 hours before use . Large amounts of gravid adults were washed off plates with M9 buffer , collected in Eppendorf tubes and centrifuged for 2 minutes at 2500 rpm . Supernatant was discarded and the pellet resuspended in 1 ml of alkaline hypochlorite solution ( 20 ml of 1M NaOH , 30 ml NaClO and 50 ml H2O in 100 ml of solution ) . Tubes were kept at mild agitation and every 30 seconds an aliquot was removed for observation . Once only embryos remained ( within 5 minutes from hypochlorite addition ) , tubes were centrifuged for 2 min at 2500 rpm and the supernatant discarded . The pellet was washed twice with M9 buffer . Plates with large amounts of laid eggs were washed with M9 to eliminate all larvae and adults . Within the next two hours , newly hatched L1 animals were collected with a mouth pipette and transferred to the desired experimental plates . Synchronized L1 larvae were placed in plates with food using a mouth pipette . The integrity of AVM axons at 12 , 24 , 48 and 72 hours post hatching was observed and scored . The same experiments at 25°C also included ALM and PLM neurons . For experiments at 25°C without temperature shifts , parentals of animals examined were kept at the same temperature starting as L4s . Animals were scored until 168 hours at intervals of 24 hours ( Fig 1B ) . For each evaluation three plates with 30 worms were used . Dauer and non-dauer animals were placed on 2% agarose pads on glass slides , immobilized with 1 mM or 20 mM levamisole respectively . The preparation was covered with glass coverslips and subsequently observed under a 40x or 60x oil objective in an upright Nikon Eclipse Ni-U fluorescent microscope . For high resolution images in Figs 3I and 4G , we used a Leica TCS SP5X microscope . All images were taken with a Canon EOS Rebel T3i camera , attached to the Nikon Eclipse Ni-U microscope . Fluorescence photographs were taken with 1/10 sec exposure time , and ISO 3200 . Nomarski ( DIC ) images were taken with 1/5 sec of exposure time and ISO 200 . NGM plates were seeded with 300 μl of an E . coli OP50 culture and allowed to dry for 18–24 hours . To kill bacteria , plate and lid were placed upside down on a UV-transilluminator ( LabNet International , 100-240V , 50–60 Hz ) for 5 minutes . To confirm that bacteria were dead , a portion of the lawn was streaked on an LB plate and allowed to grow overnight at 37°C . Dauers were isolated by 1% SDS treatment of animals in starved plates [5] . Plates were washed with 2 ml of 1% SDS , and transferred to an Eppendorf tube . The tube was agitated manually every 2 minutes for 15 minutes total . Finally , the tube was centrifuged for 2 min at 2500 rpm , the supernatant eliminated and the dauer pellet seeded on a plate without bacteria . To further isolate dauers from worm carcasses , live animals were allowed to crawl off the pellet for 30 to 60 minutes . The portion of the plate with the remaining pellet was excised from the plate with a scalpel and dauers collected either by pipette or a filtered pipette tip using sterile M9 with . This was performed at 20 and 25°C . To directly observe the regenerative effect of diapause entry , individual dauers were followed in a time dependent manner . Two factors were critical in this protocol: 1 ) avoiding contamination in order to keep worms in dauer , and 2 ) obtaining animals in the first day of dauer . To avoid contamination , a ) collected dauers were descendant of parental embryos from hypochlorite treatment , fed on previously UV killed E . coli OP50 ( see above ) ; b ) SDS 1% was supplemented with carbenicillin 25 mg/ml ( Santa Cruz Biotechnology ) and 250 mg/ml of Amphotericin B ( fungizone , Gibco/Thermofisher ) . One-day dauers were obtained by SDS 1% treatment . The pellet was washed twice with H2O containing the same antibiotics mentioned before , under agitation for another 10 minutes ( 5 minutes with each wash ) . The total pellet was placed on the center of an empty NGM plate , and dauers were allowed to crawl outside the pellet for collection . The fraction of the plate that contained the carcasses and the total pellet was cut out using a scalpel or stainless laboratory spatula . Dauers that were on the remaining agar , were collected with H2O , centrifuged and seeded on a new NGM plate without food . Animals were individually collected with a mouth pipette and placed on an agarose pad with 20μM levamisole for observation . This protocol was performed at 20 and 25°C . To be considered for individual evaluation , dauers had to have a degree of axonal truncation on the first day , including incomplete AxW ( second image in Fig 2A ) and animals with only a soma AxØ-S or no visible neuron ( AxØ ) . Each animal was mounted on 2% agarose pad using a mouth pipette and levamisole 20 μM . If animals fulfilled the above morphological criteria , they were photographed under fluorescence and Nomarski ( DIC ) in the same position , in order to collect information from the first day and compare it to the following days . After image collection , animals were taken from the agarose pad . Using a scalpel , the coverslip was separated from the agarose bed , avoiding breaking or losing the worm as a consequence of detaching the glass . After this , using a mouth pipette and a mix of autoclaved distilled H2O supplemented with Carbenicillin ( 25 mg/ml ) and Amphotericin B ( 250 mg/ml ) , animals were collected from the pad and placed on individual wells in a 24-well plate . Each well contained 200 μl of H2O plus Carbenicillin ( 25 mg/ml ) and Amphotericin B ( 250 mg/ml ) and 30 wild type ( N2 ) dauers ( see explanation below ) . These dauers were obtained using plates of N2 , which were starved for at least two weeks , being the main criterion the presence of large quantity of dauers . 24-well plates were sealed with parafilm ( Bemis , Parafilm M ) and incubated at 20 and 25°C without agitation until the second evaluation 2 days later ( day 3 of dauers ) . On day 3 , the content of the well was collected with filtered tips on an Eppendorf tube . Animals that remained on the edges of the well were collected with a mouth pipette . Tubes were centrifuged for 4 min at 2500 rpm . Most supernatant was carefully discarded and the remaining pellet was placed on an agarose pad . With a mouth pipette any drop left on the Eppendorf tube was extracted . Finally , 20 μM levamisole were added to paralyze all dauers . To avoid dispersion caused by covering the preparation , the coverslip was placed once the liquid was absorbed . gfp expressing animals were located among all dauers and registered as described before . Explanation for mixing each mec-4d dauer with wild type dauers: Maintaining individual dauers was challenging . When growing them on plates after 24 hours , they either escaped or were lost under the agar . In liquid , individual dauers tended to enlarge the pharynx and started pumping , and displayed morphological changes proper of dauer recovery , even though they were unable to resume development for the lack of food . We reasoned that mixing the mec-4d dauer with a population of other dauers would prevent them from dauer recovery ( for the hormonal effect ) . To distinguish them , N2 dauers without any visible marker were added to each mec-4d animal express gfp in the AVM cell . mec-4d eggs , obtained from hypochlorite treatment , were grown at 20°C until the L4 larval stage . Plates were then moved to 25°C , where the F1 hatched and develop . Once bacteria were consumed , the plate was observed for the appearance of first day dauers . If one dauer was found , plates were treated with SDS 1% as explained above . To evaluate the effects of DAF-2 downregulation on dauer animals , we used the strains WCH34 ( daf-2ts ( e1368 ) ; uIs31 ( Pmec-17mec -17::gfp ) ; mec-4d ( e1611 ) and TU2773 [uIs31 ( Pmec-17mec-17::gfp ) ;mec-4d ( e1611 ) X] as a control . Embryos from both strains obtained from hypochlorite treatment , were placed on plates at 25°C until diapause entry by starvation . SDS 1% treatment and dauer scoring was performed as described for one-week dauers above . 30–50 dauers were used to record the morphology in the first day as dauer at 25°C . Then , animals were divided into three plates and shifted to 15°C and 20°C . Morphology of AVM and ALM was scored 2 , 4 and 6 days after the temperature shift . One-week old dauers that derived from the same plate were obtained by SDS 1% treatment . The first evaluation was done with 30 dauers directly from SDS 1% treatment to establish the hour zero of dauer recovery . 30 to 50 dauers were placed on 3 plates with E . coli OP50 and examined every 24 hours until 96 hours post-dauer . To measure the lifespan of wild type and mec-4d animals in diapause , large amounts of dauers were isolated using the same criteria for the synchronization of dauer explained above ( More than one-month dauers ) . Minimally 30 dauers we placed in each well of a 24-well plate , filled with distilled water , antibiotics and antifungal as mention above . The media of each well was changed with new liquid every two weeks . The quantification of dauers was done using three wells ( with at least 30 dauers each ) per week per strain for a total of 16 weeks . Each well was labeled with the number corresponding to the week its examination was scheduled . To evaluate the number of live dauers , animals were collected from each well and placed on a 60mm NGM plate with E . coli OP50 food . Total dauers were immediately counted to record the initial number of individuals . 24 hours later , the number of live non-dauer animals was counted again . For each time point the percent of live animals was calculated using the initial dauer count . Each point in the graph is the average of three replicas . To directly observe the regeneration of the embryonic neurons in developing animals at 25°C , individual animals were followed during the initial 24 to 48 hours of development . Animals were selected based on the criteria of having truncated axons , according to the morphological categories described above for ALM and PLM neurons . Newly hatched L1s were collected with a mouth pipette and mounted on agarose pads immobilized with 1 μM levamisole . Worms were observed and photographed in the microscope under 60x objective to keep a registry of the morphology of the ALM/PLM neurons at every time point . Then , animals were rapidly passed to a new plate with E . coli OP50 food . 24 and 48 hours later the same protocols were repeated . Animals were maintained at 25° at all times . To evaluate the functionality of the AVM mechanoreceptor neuron , the ability of dauer animals to respond to gentle touch was tested [26] . Animals were touched at 20 and 25°C . To correlate AVM morphology with the ability of animals to respond to the anterior touch , touch tests were first performed to dauer animals synchronized as explained above and immediately mounted on agarose pads for observation in the microscope and scoring of the AVM morphology . This protocol was performed at 20 and 25°C . To quantify the number of MEC-4 channels in the TRN axons , the strain TU3755 containing the uIs58 ( Pmec-4mec-4::gfp ) transgene was used . MEC-4 channels appear as puncta along the axon and can easily be counted [70] Specifically , the PLM neuron was used to measure the number of puncta in synchronized L2 , day 1 and day 7 dauers and 24 hours after dauer recovery , at 20 and 25°C . Once the animals were in the required state , each animal was mounted on an agarose pad and immobilized using 1μM levamisole . Then , animals were photographed focusing on the PLM neuron taking different focal planes of the axon , to obtain the best representation of the MEC-4 channels . From each state , 20 animals were scored . Pictures were analyzed with ImageJ , using the Neubauer chamber to calibrate the equivalency on microns of the images in the program . All photos were formatted to a resolution of 5184 x 3456 pixels . To normalize the measurements and consider the same size in all animals , PLM soma was taken as initial point and from this 120 μm was measured . The quantity of channel found in this axonal size was quantified and taken as value for each animal . This procedure was repeated for each animal in all state evaluated . To synchronized dauer we performed the same protocol mention above . To evaluate the effect of DAF-2 hypofunction on the regeneration of the AVM neuron , we used the WCH34 strain [daf-2ts ( e1368 ) ; uIs31 ( Pmec-17mec -17::gfp ) ; mec-4d ( e1611 ) ] . L1 were synchronized by mouth pipetting from plates at 20°C ( 0–2 hours post hatching ) and transferred to 15 different new plates at 15°C or 25°C ( 30 plates total , 30 L1 per plate minimally ) and allowed to grow for 24 hours . Animals from 3 plates at each temperature ( shifted to 15°C or 25°C ) were used for morphological assessment at 48 and 72 hours post hatching which are 24 and 48 hours after the shift respectively . To evaluate the effect of DAF-16 overexpression in the degeneration of the AVM mechanoreceptor , a mec-4d strain expressing the zIs356 transgene [daf-16p::DAF-16A/B::GFP; rol-6 ( su1006 ) ] was created ( WCH36 ) Due to the high intensity and diffuse expression pattern of the zIs356 transgene , usual observation of AVM axons as integrity assessment was not possible . To circumvent this , we used two different approaches . Functionality of the AVM neuron was assessed by a behavioral touch test [26] in both TU2773 and WCH36 strains . Secondly , animals were scored in an Epi-Fluorescence Stereoscope ( AZ-100 , NIKON ) for the presence of neuronal somas as a readout of neuronal protection . Axotomy experiments were carried out as previously described [71] . Post axotomy images were acquired with an Olympus DSU mounted on an Olympus BX61 microscope , Andor Neo sCMOS camera , and Lumen light source . Animals were scored 18–24 hours after axotomy . Total RNA was isolated using TRIzol ( Invitrogen ) from N2 and mec-4d animals , in L2 and dauer stage . 100 μM of RNA were used for each reverse transcription reaction to using Superscript IV reverse transcriptase ( Thermofisher Scientific ) . To determine the quantity of both isoforms of dlk-1 transcripts , a semi-quantitative PCR was performed using ama-1 as reference of constitutive expression . Cycle number was standardized to remain in the exponential phase of amplification . Amplification was performed using KAPA Hifi HotStart ready mix PCR ( KAPA Biosystems ) . 100ng of DNA were used for each sample as template for all conditions . Primers used were for dlk-1a , forward 5’ , CTTGGTCACACCAACATCAG 3’ and reverse 5’ , GTGTCACAAGCTCCGACC 3’; for ama-1 , forward 5’ GTGGATGCGGTCATCAACCATC 3’ and reverse 5’ TTCTTTTCCTTTCAGTCGCTGCTTG 3’ . 25 μL and 10μL of reactions were used to run on a 3% agarose gel for dlk-1 and ama-1 samples respectively . Quantification of band intensity was done using ImageJ , taking ama-1 as control of a constitutively expressed gene . Each experiment was performed in three technical triplicates and at least three biological replicates . Biological replicates were defined as experiments made in different days , containing triplicates of each condition , and a technical replicate as a triplicate of the same condition on the same day . The average of the three reads of each triplicate was considered as one count of a minimum of three for each point of a curve . In other words , the data is collected and processed as a single technical replicate ( the average of three counts of the same plate ) , and its mean is used as a single biological replicate . Each figure contains at least three experiments ( biological replicates ) . Exceptions of that number per figure are: ( 1F ) 653 , ( 2B ) 208 , ( 2C ) 918 , ( 2G ) 184 , ( 3F ) 160 , ( 3G ) 41 , ( 4A ) 240 , ( 4F ) 60 , ( 6E ) 120 , ( 7D ) 205 . Entire experiments were excluded when there was contamination with unwanted bacteria or fungi . Statistical evaluation was performed using one or two way-ANOVA , with post-hoc tests , and Chi square test when indicated . Results of all tests are detailed in Supporting Information ( S2 File ) .
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Diapause entry and hibernation have the striking ability to protect the nervous system from diverse types of damage . Here we show that the diapausing dauer larvae of C . elegans regenerate broken mechanosensory neurons that were damaged by the hyperactivation of degenerins ( MEC-4d ) or by axotomy during diapause . This regeneration is complete and functional , rendering neurons capable of responding to touch after three days in diapause . Genetic inactivation of the insulin receptor DAF-2 promotes regeneration of mec-4d axons in non-dauer animals . Overexpression of the downstream transcription factor DAF-16 promotes neuronal protection in mec-4d neurons while loss of daf-16 accelerates mec-4d induced degeneration . Temperature sensitive activation of DAF-2 during diapause induces the loss of axonal integrity . This indicates that the insulin signaling pathway is an important underlying factor in regeneration . Additionally , we show that complete morphological regeneration depends on DLK-1 , a conserved protein required for axonal repair . In this work we introduce a simple model of complete axonal regeneration , which will greatly facilitate the study of environmental and genetic factors affecting neurodegeneration and constitute an advantage in studying axonal regrowth .
|
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"Abstract",
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2019
|
Diapause induces functional axonal regeneration after necrotic insult in C. elegans
|
Evasion of host immune responses is a prerequisite for chronic bacterial diseases; however , the underlying mechanisms are not fully understood . Here , we show that the persistent intracellular pathogen Brucella abortus prevents immune activation of macrophages by inducing CD4+CD25+ T cells to produce the anti-inflammatory cytokine interleukin-10 ( IL-10 ) early during infection . IL-10 receptor ( IL-10R ) blockage in macrophages resulted in significantly higher NF-kB activation as well as decreased bacterial intracellular survival associated with an inability of B . abortus to escape the late endosome compartment in vitro . Moreover , either a lack of IL-10 production by T cells or a lack of macrophage responsiveness to this cytokine resulted in an increased ability of mice to control B . abortus infection , while inducing elevated production of pro-inflammatory cytokines , which led to severe pathology in liver and spleen of infected mice . Collectively , our results suggest that early IL-10 production by CD25+CD4+ T cells modulates macrophage function and contributes to an initial balance between pro-inflammatory and anti-inflammatory cytokines that is beneficial to the pathogen , thereby promoting enhanced bacterial survival and persistent infection .
Persistent bacterial infections have a significant impact on public health [1] . While evasion of host immune responses is a prerequisite for these chronic infections , the underlying mechanisms are not fully understood . Human brucellosis , caused by the intracellular gram-negative coccobacilli Brucella spp . , is considered one of the most important zoonotic diseases worldwide , with more than 500 , 000 new human cases reported annually [2] . The disease is characterized by a long incubation period that leads to a chronic , sometimes lifelong , debilitating infection with serious clinical manifestations such as fever , arthritis , hepatomegaly , and splenomegaly [3] , [4] . Human and animal brucellosis share many similarities , such as persistence in tissues of the mononuclear phagocyte system , including spleen , liver , lymph nodes , and bone marrow [4] . Therefore , the use of animal models such as mice has been an important tool to better characterize the immune response to Brucella infection that leads to long-term bacterial persistence and chronic disease . There is general agreement that the initial interferon gamma ( IFN-γ ) mediated Th1 immune response is crucial for the control of Brucella infection , since absence of IFN-γ results in decreased control of bacterial growth [5] , [6] and IFN-γ-deficient C57BL/6 mice succumb to overwhelming disease [7] . However , the inflammatory response induced by Brucella spp . in vivo is much milder than that observed with pyogenic infections such as salmonellosis , suggesting the stealth of Brucella as a possible reason for the absence of early proinflammatory responses [8] , [9] . Recent studies have shown that Brucella spp . use both passive and active mechanisms to evade initial innate immune recognition through toll-like receptors ( TLRs ) [10] . Although avoidance of TLR recognition is a key factor in the lack of initial inflammation during Brucella infection , how subsequent interactions of Brucella with the host immune system result in chronic disease is poorly understood . Interleukin-10 ( IL-10 ) is an immunoregulatory cytokine produced by most T cell subsets , B cells , neutrophils , macrophages , and some dendritic cell subsets [11] . It is suggested that by acting on antigen-presenting cells such as macrophages , IL-10 can inhibit the development of Th1 type responses [12] . In the context of infectious diseases , it is believed that the host uses IL-10 to control over-exuberant immune responses to pathogenic microorganisms in order to limit tissue damage [11] . Interestingly , studies using chronic pathogens such as Leishmania major [13] , human cytomegalovirus [14] , or Mycobacterium tuberculosis ( reviewed in [15] ) have demonstrated that the absence of IL-10 leads to a better clearance of these pathogens , with variable degrees of immunopathology . These studies suggest that pathogens have developed mechanisms to take advantage of the host immune-regulation in order to persist for longer periods and establish chronic infection . Similar to other chronic pathogens , B . abortus infection induces IL-10 production [5] , [6] , [16] . Moreover , IL-10 gene polymorphisms have been associated with increased susceptibility to human brucellosis [17] . However , questions regarding the impact of IL-10 in B . abortus persistence and establishment of chronic infection , as well as the cell types responsible for this cytokine production remain to be answered . Therefore , we used IL-10 deficient mice to determine the role of IL-10 in modulating the initial immune response to Brucella infection . Furthermore , using cell-specific knock-out mice , we elucidated the immunological mechanisms underlying IL-10 induced immune-regulation during Brucellosis .
IL-10 has an important role in controlling the immune response induced by different inflammatory processes [15] . Moreover , Brucella infection has been shown to induce IL-10 production by splenocytes in vitro [5] and during intravenous in vivo infection [6] , [16] . To determine the time-course of IL-10 production during B . abortus infection , C57BL/6 mice were infected intraperitoneally ( IP ) with 5×105 CFU of the virulent B . abortus strain 2308 and IL-10 production was determined at 3 , 9 , 15 , and 21 days post-infection ( d . p . i . ) . Infected mice exhibited significantly higher levels of IL-10 in the serum ( Fig . 1A ) , which was associated with increased IL-10 transcript levels in the spleen ( Fig . 1B ) and liver ( Fig . 1C ) as early as 3 d . p . i . Importantly , significantly increased levels of IL-10 in serum and infected organs was only detected until 15 d . p . i . , suggesting a possible regulatory function for this cytokine during acute Brucella infection . To further investigate if IL-10 plays a role in modulating the inflammatory response during acute brucellosis , C57BL/6 wild-type and Il10-deficient mice ( IL-10−/− ) were infected IP with 5×105 CFU of B . abortus 2308 and responses were evaluated at 9 d . p . i . Interestingly , IL-10−/− mice had significantly lower bacterial survival in both the spleen ( Fig . 2A ) and the liver ( Fig . 2B ) . IL-10−/− mice also exhibited increased induction of pro-inflammatory cytokines such as IFN-γ , interleukin-6 ( IL-6 ) and tumor necrosis factor alpha ( TNF-α ) in infected organs ( Fig . 2C ) and in serum from infected mice ( Fig . 2D ) . The typical tissue response to Brucella infection is granulomatous inflammation [4] . However , in the spleen and liver of IL-10−/− mice B . abortus infection resulted in development of an acute inflammatory response characterized by vasculitis and thrombosis , necrosis , and influx of neutrophils ( Fig . 2E and 2F ) . Collectively , these data demonstrate a critical role for IL-10 in modulating the initial inflammation and pathology in response to B . abortus infection , which in turn benefits the pathogen due to enhanced bacterial survival . IL-10 can be produced by different T cell subsets , as well as by B cells , neutrophils , macrophages , and some DC subsets [18] . To determine the cell types responsible for IL-10 production during early B . abortus infection , Il10-GFP reporter mice [19] were infected IP with 5×105 CFU of B . abortus and IL-10 producing cells were identified at 3 and 9 d . p . i . by flow cytometry . A significant increase in the number of IL-10 producing T cells was observed in infected mice at 3 and 9 days post infection , whereas macrophages presented increased production of IL-10 only at 3 d . p . i . Moreover , the number of IL-10 producing B cells , neutrophils , and dendritic cells did not change significantly when compared to uninfected mice ( Fig . 3A and 3B , and data not shown ) . Importantly , even though a significant increase in the number of IL-10 producing CD8+ T cells was observed ( Fig . 3C ) , a tenfold higher number of IL-10 producing T cells was observed in the CD4+ T cell population ( Fig . 3C ) . No IL-10 production by γδ T cells was observed ( data not shown ) . Various IL-10 producing CD4+ T cells have been described , including the CD4+CD25+ subset [20] . Interestingly , an expansion of the CD4+CD25+ T cell population was observed in the spleen of B . abortus infected mice at 9 d . p . i . ( Fig . S1 ) . Moreover , a 5-fold greater number of IL-10 producing CD4+CD25+ T cells was detected at 9 d . p . i . , compared to IL-10 producing CD4+CD25− T cells ( Fig . 3D and 3E ) , suggesting that the CD4+CD25+ T cell subset is the major population responsible for IL-10 production during acute brucellosis in the mouse . Our previous data suggested that T cells and possibly macrophages would be the main cell types producing IL-10 during early Brucella infection . Therefore , to further investigate the importance of macrophage derived IL-10 during Brucella infection , we generated Il-10flox/floxLysMCre+/− ( IL-10flox/LysMCre ) mice , which have macrophages and neutrophils that are unable to produce IL-10 . IL-10flox/LysMCre mice and littermate Il-10flox/floxLysMCre−/− controls were infected IP with 5×105 CFU of B . abortus 2308 , and at 3 , 9 and 21 d . p . i . disease progression was evaluated . Interestingly , IL-10flox/LysMCre infected mice exhibited decreased levels of IL-10 in the serum ( Fig . 4A ) when compared to control animals only at 3 d . p . i . , Moreover , IL-10flox/LysMCre mice exhibited increased ability to control B . abortus infection in both spleen ( Fig . 4B ) and liver ( Fig . 4C ) , only at initial stages of infection . This increased host resistance was accompanied by significantly higher levels of the pro-inflammatory cytokines IL-6 , TNF-α and IFN-γ in serum ( Fig . 4D ) , spleen ( Fig . 4E ) and liver ( data not shown ) as well as increased histopathological lesions in infected organs ( Fig . S2 ) of IL-10flox/LysMCre mice when compared to littermate controls ( Fig . 4D , 4E and data not shown ) . Collectively , this data suggests that macrophage derived IL-10 plays a limited role in development of the chronic disease caused by B . abortus and raises the possibility that T-cells could , indeed , be the main cell type responsible for IL-10 production during early Brucellosis . Therefore , to further investigate the importance of T-cell derived IL-10 during Brucella infection , we used Il-10flox/floxCd4Cre+/− ( IL-10flox/CD4Cre ) mice , which have T cells that are unable to produce IL-10 [21] . IL-10flox/CD4Cre and littermate Il-10flox/floxCd4Cre−/− control mice were infected IP with 5×105 CFU of B . abortus 2308 , and at 3 , 9 , 21 and 42 d . p . i . , disease progression was evaluated . Remarkably , IL-10flox/CD4Cre infected mice exhibited lower levels of IL-10 in serum ( Fig . S3A ) , and spleen ( Fig . S3B ) when compared to control animals at 9 d . p . i . , providing compelling support for the hypothesis that T-cells are a major source of IL-10 production during early B . abortus infection . Previous results using IL-10−/− and IL-10flox/LysMCre mice ( Fig . 2 and 4 ) suggested that IL-10 was important for initial B . abortus persistence in the host . Therefore , we investigated whether the lack of T cell-derived IL-10 would affect bacterial persistence . Indeed , IL-10flox/CD4Cre mice exhibited significantly improved control of B . abortus infection in the spleen and liver at 9 , 21 and 42 d . p . i . ( Fig . 5A and 5B ) . Controlling B . abortus replication could be beneficial to the host , since the ability to survive for longer periods is a key mechanism for chronic pathogens to thrive . However , loss of IL-10 driven immune modulation has been shown to cause severe and sometimes lethal inflammatory responses in different infectious disease models [15] . To determine the disease progression , weight changes in IL-10flox/CD4Cre and control mice were followed at 3 , 9 , 15 , 21 , 28 , 35 and 42 d . p . i . ( Fig . 5C ) . To ensure that any detectable change in weight was the result of B . abortus infection , uninfected IL-10flox/CD4Cre and littermate control mice were also used ( data not shown ) . IL-10flox/CD4Ce mice exhibited significantly decreased weight gain during early infection and , by 21 days post-infection , they started to behave like control animals . IL-10flox/CD4Cre uninfected mice did not exhibit any slower weight gain and behaved like uninfected control mice ( data not shown ) . Moreover , increased levels of the pro-inflammatory cytokines IFN-γ , IL-6 , and TNF-α were observed in serum ( Fig . 5D ) spleen ( Fig . 5E ) and liver ( Fig . S3C ) of IL-10flox/CD4Cre at 3 , 9 days and , to a lesser extent , at 21 d . p . i . To determine if the significantly reduced weight gain and higher induction of pro-inflammatory cytokines were associated with a detrimental inflammatory response , spleen and liver sections from IL-10flox/CD4Cre and control mice were blindly evaluated by veterinary pathologists ( MNX and TMS ) . Interestingly , IL-10flox/CD4Cre mice exhibited increased pathology , characterized by marked influx of neutrophils and histiocytes in the spleen ( Fig . 6A and 6C ) , as well as tissue necrosis and multifocal neutrophilic vasculitis and thrombosis in the liver ( Fig . 6B and 6C ) at 3 and 9 d . p . i . , suggesting an acute inflammatory response . Importantly , a hallmark of B . abortus infection is a mild initial pro-inflammatory response , which leads to a chronic infection characterized by formation of granulomas in infected organs [4] , [22] . However , by 21 d . p . i . , IL-10flox/CD4Cre mice exhibited decreased granuloma formation in the spleen ( Fig . 6A and 6C ) when compared to littermate control mice . Taken together , these data demonstrate that T cell-derived IL-10 production during early B . abortus infection is crucial for the development of the chronic disease and morbidity caused by B . abortus , and limits the production of the pro-inflammatory response necessary to control the infection . However , the cell types affected by the IL-10 production during Brucella infection remained unclear . Since Brucella spp . are known to invade and survive inside phagocytic cells such as macrophages [23] , we hypothesized that macrophages could be the cell type affected by IL-10 during Brucella infection . To determine the effect of IL-10 on B . abortus survival during macrophage infection in vitro , bone marrow derived macrophages ( BMDM ) from C57BL/6 and IL-10−/− mice were infected with B . abortus 2308 ( MOI = 100 ) and the bacterial survival was measured at 1 , 8 , and 24 h post-infection ( h . p . i . ) ( Fig . 7A ) . B . abortus infected wild-type BMDM produced significant amounts of IL-10 ( Fig . S4A ) . B . abortus exhibited a significantly decreased ability to survive inside BMDM from IL-10−/− mice at 8 and 24 h . p . i . when compared to BMDM from wild-type mice . Importantly , B . abortus infected IL-10−/− BMDM did not exhibit increased cell death , determined by LDH assay ( data not shown ) . Moreover , to ensure that the observed effect resulted from an absence of IL-10 production , recombinant IL-10 ( rIL-10 ) was added to the IL-10−/− BMDM media during infection ( Fig . 7A ) . As expected , the addition of rIL-10 restored B . abortus survival inside macrophages . Results similar to those described above ( Fig . 7A ) were also observed in IFNγ-activated BMDM ( data not shown ) . The ability of Brucella spp . to persist and replicate within macrophages involves a temporary fusion of Brucella-containing vacuole with the late endosome/lysosome during the initial hours post-infection , and subsequent exclusion of the endosomal/lysosomal proteins from the Brucella-containing vacuole [24] . To determine if B . abortus inability to persist inside macrophages was due to changes in the pathogen's intracellular trafficking , we infected wild-type and IL-10−/− BMDM with B . abortus expressing mCherry ( MOI = 100 ) and bacterial co-localization with the late endosome marker LAMP1 was determined at 24 h . p . i . by confocal microscopy . Interestingly , while the majority of B . abortus was found to lack LAMP1 in wild type BMDM , the opposite was found in BMDM derived from IL-10−/− mice , in which over 80% of bacteria were co-localized with LAMP1 ( Fig . 7B and 7C ) . This phenotype was IL-10-dependent , since addition of rIL-10 to the IL-10−/− BMDM restored the ability of the pathogen to escape the late endosome ( Fig . 7B and 7C ) . Results similar to those described ( Fig . 7B and Fig . 7C ) were also observed in IFNγ activated BMDM ( data not shown ) . It has been demonstrated that IL-10 can inhibit a protective immune response , possibly by blocking NF-κB activation [25] and downstream production of pro-inflammatory cytokines by antigen-presenting cells such as macrophages [15] , [26] . To investigate if IL-10 production would have an effect on NF-κB activation in Brucella infected macrophages , we used an NF-κB reporter RAW murine macrophage cell line ( RAW-Blue cells ) . RAW-Blue cells were infected with B . abortus 2308 ( MOI = 100 ) in the presence of IL-10 receptor blocking antibody ( IL-10R Ab ) or rIL-10 , and NF-κB activation was measured at 8 and 24 h . p . i . Brucella infected RAW-Blue macrophages produced significant amounts of IL-10 ( Fig . S4B ) . Blockage of IL-10R resulted in decreased B . abortus intracellular survival inside RAW-Blue macrophages when compared to untreated controls at 24 h . p . i . , as previously observed in IL-10−/− BMDM ( data not shown ) . B . abortus infection did not result in significant NF-κB activation by any of the treatment groups at 8 h . p . i . ( Fig . 8A ) . The use of IL-10R Ab to block the response of B . abortus infected RAW-Blue macrophages to IL-10 resulted in a significant increase in NF-κB activation at 24 h . p . i . when compared to untreated infected macrophages . Conversely , addition of exogenous rIL-10 resulted in a significant inhibition of NF-κB activation in B . abortus infected cells ( Fig . 8A ) . The results above described were also observed in IFNγ activated RAW blue cells ( data not shown ) . To confirm that IL-10 affects pro-inflammatory cytokine production by infected macrophages , bone marrow-derived macrophages ( BMDM ) from C57BL/6 and IL-10−/− mice were infected with B . abortus 2308 ( MOI = 100 ) and cytokine expression was measured at 24 h . p . i . by ELISA and quantitative real-time PCR . Significantly , an absence of IL-10 resulted in higher expression levels of the pro-inflammatory cytokines IL-6 and TNFα by infected macrophages ( Fig . 8B and 8C ) . Moreover , the phenotype observed was shown to be IL-10 dependent , since the addition of rIL-10 to IL-10−/− infected BMDM restored IL-6 and TNF-α expression to wild-type levels . Results similar to those described in Fig . 8B and Fig . 8C were also observed in IFN-γ activated BMDM ( data not shown ) . Our results demonstrate that IL-10 production during B . abortus infection in vitro affects macrophage function by modulating NF-κB activation and the production of pro-inflammatory cytokines by infected cells . To further investigate the possibility that macrophages are the cell type responding to the IL-10 produced during B . abortus infection , we used Il-10Rflox/floxLysMCre+/− ( IL-10Rflox/LysMCre ) mice , which are unable to express the IL-10 receptor 1 chain ( IL-10R1 ) specifically in monocytes/macrophages and/or neutrophils [27] . IL-10Rflox/LysMCre and Il-10Rflox/floxLysMCre−/− control mice were infected intraperitoneally with 5×105 CFU of B . abortus 2308 for 3 , 9 , 21 and 42 days and bacterial survival in infected organs was evaluated . Our results from in vitro infection suggested that IL-10 affects the ability of B . abortus to survive inside macrophages . Remarkably , IL-10Rflox/LysMCre mice showed lower CFU counts in both spleen ( Fig . 9A ) and liver ( Fig . 9B ) at 9 , 21 and 42 d . p . i . when compared to littermate control mice . This data provided strong support for the idea that macrophage responsiveness to IL-10 is necessary for optimal initial B . abortus colonization of the host as well as long-term persistence . The results shown above ( Fig . 5 ) demonstrated that a lack of IL-10 production by T cells during B . abortus in vivo infection resulted in increased pro-inflammatory responses and evident clinical signs of disease in mice . Moreover , our in vitro results suggested that blockage of IL-10R played a role in the control of NF-κB activation and pro-inflammatory cytokine production by B . abortus-infected macrophages . Therefore , we sought to determine the effect of macrophage responsiveness to IL-10 in the early host response to B . abortus infection . B . abortus-infected IL-10R/LysMCre mice exhibited decreased weight gain at 9 , 15 , and 21 d . p . i . when compared to wild-type infected mice ( Fig . 9C ) . Furthermore , levels of IFN-γ , IL-6 and TNF-α were significantly increased in serum ( Fig . 9D ) spleens ( Fig . 9E ) and livers ( Fig . S5 ) of IL-10R/LysMCre at 3 , 9 d . p . i . and , to a lesser extent , at 21 d . p . i . To determine if macrophage non-responsiveness to IL-10 would result in detrimental pathologic changes , spleen and liver sections from infected IL-10Rflox/LysMCre and control mice were blindly evaluated by veterinary pathologists ( MNX and TMS ) . As expected , IL-10Rflox/LysMCre showed severe acute lesions characterized by influx of neutrophils and histiocytes , as well as tissue necrosis and multifocal neutrophilic vasculitis and thrombosis in the spleen at 9 d . p . i . ( Fig . 10A and 10C ) and in the liver ( Fig . 10B and 10C ) at 9 and 21 d . p . i . However , at 21 and 42 days post-infection , IL-10Rflox/LysMCre mice exhibited decreased granuloma formation in spleen ( Fig . 10A and 10C ) when compared to littermate control mice , suggesting that macrophage responsiveness to IL-10 is important for development of chronic pathological lesions in spleens of infected animals . These data provide the direct support for the idea that induction of IL-10 during B . abortus in vivo infection plays a key role in modulation of macrophage function , which , in turn , provides the ideal initial immunological environment for bacterial colonization and development of chronic infection .
The balance between pro-inflammatory and anti-inflammatory cytokine production appears to be crucial for the ability of the host to eradicate an infection , as well as for the clinical presentation and/or pathology resulting from the infection . This balance appears to shift in the case of persistent pathogens such as Brucella spp . , which are able to evade TLR signaling during the early stages of infection , thereby preventing development of an immune response that is appropriate to clear the infection [28] . It is known that during the acute phase of B . abortus infection in mice , neutralization of IL-10 reduces bacterial colonization [5] . Here , we provide support to the idea that during this phase of B . abortus infection , early production of IL-10 by T cells is key to promoting persistent intracellular infection . In a number of infectious disease models , several cell types , including T cell subsets , B cells , neutrophils , macrophages and some DC subsets have been shown to be able to produce IL-10 [18] . Even though B . abortus infected macrophages are capable of producing IL-10 in vitro , only B cells have been implicated as a potential source of IL-10 during in vivo infection [29] . In this study , however , we have demonstrated that macrophages play a limited role in IL10 production during early acute B . abortus infection . Additionally , we identified T cells , more specifically CD4+CD25+ T cells , as the major source of this cytokine during acute brucellosis . Indeed , Svetić and collaborators [1] have suggested a possible role for CD4+ T cells in IL-10 production during acute murine Brucellosis . Interestingly , previous studies have demonstrated elevated numbers of CD4+CD25+ T cells in PBMCs from human patients with acute brucellosis [30] as well as in draining lymph nodes from B . melitensis infected sheep [28] . Moreover , Pasquali and collaborators demonstrated that depletion of CD4+CD25+ T cells resulted in increased control of B . abortus infection due to elevated activation of effector T cells and higher production of pro-inflammatory cytokines such as IFN-γ by infected mice [31] . Most likely , the effects seen in this latter study were an indirect effect of the decreased IL-10 production by T cells , resulting in elevated macrophage activation in CD25-depleted mice upon B . abortus infection . Taken together , these results point to CD4+CD25+ T cells as important players in modulating the early immune response to B . abortus in vivo . There is a general agreement that macrophages represent a critical niche for Brucella persistence in the host [4] . Importantly , they have been described as one of the cell types responding to IL-10 production in other infection models [11] , [27] . Here we have demonstrated that macrophages are a main cell type responding to the immunomodulatory functions of IL-10 during both in vitro and in vivo Brucella infection . Moreover , IL-10 signaling had a significant impact on the ability of B . abortus-infected macrophages to produce pro-inflammatory cytokines and to permit intracellular growth of B . abortus . Interestingly , O'Leary and collaborators have demonstrated that IL-10 production by immune cells can affect the ability of M . tuberculosis to escape the LAMP1+ late endosomal compartment and to establish infection in human macrophages in vitro [32] . In agreement with this previous study , we have demonstrated that the capacity of macrophages to respond to IL-10 impacts intracellular survival of Brucella by decreasing the pathogen's ability to escape the LAMP1+ late endosome , a prerequisite for replication in an endoplasmic reticulum-associated compartment . It is important to note that the LysM promoter used to drive Cre expression in IL10Rflox mice is expressed in both neutrophils and macrophages [27] . Although our understanding of the role of neutrophils during brucellosis is still evolving [8] , [33] , we and others have described recruitment of these cells to both spleens and livers of B . abortus-infected mice during the acute infection phase ( [33] , Fig . 6 and Fig . 9 ) . Moreover , the neutrophil recruitment was more evident in the absence of IL-10 ( Fig . 2 , Fig . 6 and Fig . 9 ) . Therefore , although Brucella resistance to neutrophil killing has been well described [34] , it is possible that the increased cytokine expression and pathology observed in IL10Rflox/LysMCre mice could also be due in part to a failure of neutrophils recruited to the site of infection to respond to IL-10 . It should be pointed out that , although IL-10 contributes to persistence of B . abortus in vivo , abrogation of IL-10 production ( Fig . 2 ) or neutralization of IL-10 in vivo [5] did not result in eradication of B . abortus from tissues , contrary to what has been shown for Leishmania [13] . Therefore , factors in addition to IL-10 production must also contribute to chronic persistence of B . abortus . Although TGF-β has been shown to be produced by B cells and macrophages in BALB/c mice [29] , consistent with this report , we did not observe any increase in circulating TGF-β1 , TGF-β2 , or TGF-β3 at 21 or 42 days post infection of C57BL/6 mice ( data not shown ) . However , these results do not rule out a role for local activation of TGF-β in promoting chronic infection . An important factor in persistence of Brucella is the transient nature of IFNγ production in infected mice , which subsides by 21 d post infection in mice [35] , therefore our observed lack of a role of IL-10 later in infection could suggest that its role is to antagonize the activity of IFNγ at earlier stages of infection . Finally , the possibility should be considered that during chronic infection , B . abortus may reside in a cell type that has inherently low microbicidal activity , as has been found for M . tuberculosis [36] and B . melitensis [37] . At first glance , our data suggest that inhibition of IL-10 signaling would be beneficial to the host , since IL-10−/− , IL-10flox/CD4Cre and IL-10Rflox/LysMcre showed increased ability to control B . abortus infection at both acute and chronic stages of infection . Moreover , both IL-10flox/CD4Cre and IL-10Rflox/LysMcre exhibited reduced formation of granulomas , a potential niche for B . abortus persistence [4] , during the chronic stage of infection . However , in spite of the increased bacterial clearance , we demonstrated that lack of IL-10 during Brucella infection could potentially be detrimental to the host , since B . abortus infected IL-10 deficient mice presented evident signs of acute disease , characterized by changes in weight gain and marked histopathological lesions in both spleen and liver . Indeed , studies on other chronic pathogens such as Leishmania major [38] , human cytomegalovirus [14] , and M . tuberculosis ( reviewed in [15] ) have demonstrated that even though absence of IL-10 leads to better clearance of these pathogens , it can also result in severe and sometimes lethal pathologic changes . Therefore , although modulation of the IL-10 signaling pathway could be a potential target to avoid the establishment of chronic infection , more studies are needed to elucidate the optimal activation of the immune system necessary to improve clearance of chronic pathogens without a great cost to the host .
Bacterial strains used in this study were the virulent strain Brucella abortus 2308 and its isogenic mutant strain MX2 which has an insertion of pKSoriT-bla-kan-PsojA-mCherry plasmid [37] . For strain MX2 , positive clones were kanamycin resistant and fluorescent , as previously described [37] . Strains were cultured on tryptic soy agar ( Difco/Becton-Dickinson , Sparks , MD ) or tryptic soy broth at 37°C on a rotary shaker . Bacterial inocula for mouse infection were cultured on tryptic soy agar plus 5% blood for 3 days [39] . For cultures of strain MX2 , kanamycin ( Km ) was added to the culture medium at 100 µg/mL . All work with B . abortus cells was performed at biosafety level 3 . Bone marrow-derived macrophages were differentiated from bone marrow precursors from femora and tibiae of female , 6 to 8 weeks old , C57BL/6J and IL-10−/− mice obtained from The Jackson Laboratory ( Bar Harbor ) following a previously published procedure [40] . For BMDM experiments , 24-well microtiter plates were seeded with macrophages at concentration of 5×105 cells/well in 0 . 5 mL of RPMI media ( Invitrogen , Grand Island , NY ) supplemented with 10% FBS and 10 mM L-glutamine ( RPMI supl ) incubated for 48 h at 37°C in 5% CO2 . Preparation of the inoculum and BMDM infection was performed as previously described [40] . Briefly , for inoculum preparation , B . abortus 2308 was grown for 24 h and then diluted in RPMI supl , and about 5×107 bacteria in 0 . 5 mL of RPMI supl were added to each well of BMDM , reaching multiplicity of infection ( MOI ) of 100 . Microtiter plates were centrifuged at 210× g for 5 min at room temperature in order to synchronize infection . Cells were incubated for 20 min at 37°C in 5% CO2 , free bacteria were removed by three washes with phosphate-buffered saline ( PBS ) , and the zero-time-point sample was taken as described below . After the PBS wash , RMPI supl plus 50 mg gentamicin per mL was added to the wells , and the cells were incubated at 37°C in 5% CO2 . For cytokine production assays , supernatants from each well were sampled at 0 , 8 , 24 , or 48 h after infection , depending on the experiment performed . In order to determine bacterial survival , the medium was aspirated at the time points described above , and the BMDM were lysed with 0 . 5 mL of 0 . 5% Tween 20 , followed by rinsing of each well with 0 . 5 mL of PBS . Viable bacteria were quantified by serial dilution in sterile PBS and plating on TSA . For gene expression assays , BMDM were resuspended in 0 . 5 mL of TRI-reagent ( Molecular Research Center , Cincinnati ) at the time-points described above and kept at −80°C until further use . When necessary , 1 ng/mL of mouse rIL-10 ( eBioscience , San Diego , CA ) or 1 ng/mL of mouse rIFN-γ ( BD Bioscience , San Jose , CA ) was added to the wells and kept throughout the experiments . All experiments were performed independently in triplicate at least three times and the standard error for each time point calculated . RAW-Blue cells ( Invivogen , San Diego , CA ) were derived from RAW-264 . 7 macrophages with chromosomal integration of a SEAP reporter construct inducible by NF-κB and AP-1 . RAW-Blue cells were maintained in Zeocin ( Invivogen , San Diego , CA ) selective medium . For RAW-Blue experiments , 24-well microtiter plates were seeded with macrophages at concentration of 2×105 cells/well in 0 . 5 mL of DMEM media ( Invitrogen , Grand Island , NY ) supplemented with 10% FBS and 10 mM L-glutamine ( DMEM supl ) . Preparation of the inoculum and RAW-Blue infection was performed as previously described [40] , using MOI = 100 . For NF-κB activation assays , supernatant from each well was sampled at 8 h and 24 h after infection and secretion of the substrate SEAP was detected and measured in a spectrophotometer at 650 nm with QUANTI-Blue ( Invivogen , San Diego , CA ) according to manufacturer's instructions . When necessary , 1 ng/mL of mouse rIL-10 ( eBioscience , San Diego , CA ) , 1 ng/mL of mouse rIFN-γ ( BD Bioscience , San Jose , CA ) , 1 µg/mL of anti-mouse IL-10R antibody ( R&D Systems , Minneapolis , MN ) or anti-mouse IgG isotype antibody control ( R&D Systems , Minneapolis , MN ) were added to the wells and kept throughout the experiments . All experiments were performed independently in triplicate at least three times and the standard error for each time point calculated . Experiments with mice were carried out in strict accordance with the recommendations in the Guide for Care and Use of Laboratory Animals of the National Institute of Health and were approved by the Institutional Animal Care and Use Committees at the University of California at Davis ( protocol number: 16468 ) . Female C57BL/6J wild-type mice , B6 . 129P2-Il10tm1Cgn/J; ( IL-10−/− ) mice [29] and Il-10 GFP reporter mice [19] , aged 6–8 weeks , were obtained from The Jackson Laboratory ( Bar Harbor ) . Female and male Il10flox/floxCd4cre+/− ( IL-10flox/CD4Cre ) , and Il10Rflox/floxLysmcre+/− ( IL-10Rflox/LysMCre ) aged 6–8 weeks , were reported previously [27] , [31] . Female and male IL10flox/floxLysMCre+/− ( IL-10flox/LysMCre ) were generated at UC Davis . For the strains IL-10 flox/CD4Cre , IL-10Rflox/LysMCre and IL-10flox/LysMCre , littermate Il10flox/floxCd4cre−/− , Il10Rflox/floxLysmcre−/− , and IL10flox/floxLysMCre−/− mice were used as control , respectively . Mice were held in microisolator cages with sterile bedding and irradiated feed in a biosafety level 3 laboratory . Groups of 3 to 5 mice were inoculated intraperitoneally ( i . p . ) with 0 . 2 mL of phosphate-buffered saline ( PBS ) containing 5×105 CFU of B . abortus 2308 as previously described [41] . At 3 , 9 , 15 , 21 and/or 42 days after infection , depending on the experiment performed , the mice were euthanized by CO2 asphyxiation and their serum , livers and spleens were collected aseptically at necropsy . The livers and spleens were homogenized in 2 mL of PBS , and serial dilutions of the homogenate were plated on TSA for enumeration of CFU . Samples of liver and spleen tissue were also collected for gene expression and histopathology analysis as described below . The presence of IL-10 , IL-6 and TNF-α in BMDM supernatant and in serum samples from C57BL/6 , IL-10flox/CD4Cre , IL-10flox/LysMCre and littermate control mice infected with B . abortus 2308 was determined by indirect enzyme-linked immunosorbent assay ( ELISA ) ( eBioscience , San Diego , CA ) according to the manufacturer's instructions . The ELISA test was read at 450 nm with an ELISA microplate reader ( MR5000; Dynatech ) . The sensitivity of the ELISA used was 7 . 8 pg/mL . Data points are the averages of duplicate dilutions , with each measurement being performed twice . Eukaryotic gene expression was determined by real-time PCR as previously described [40] . Briefly , eukaryotic RNA was isolated using TRI reagent ( Molecular Research Center , Cincinnati ) according to the manufacturer's instructions . A Reverse transcriptase reaction was performed to prepare complementary DNA ( cDNA ) using TaqMan reverse transcription reagents ( Applied Biosystems , Carlsbad ) . A volume of 4 µL of cDNA was used as template for each real-time PCR reaction in a total reaction volume of 25 µL . Real-time PCR was performed using SYBR-Green ( Applied Biosystems ) along with the primers listed in Table S1 in Text S1 . Data were analyzed using the comparative Ct method ( Applied Biosystems , Carlsbad ) . Transcript levels of Il10 , Il6 , Ifng and Tnfa were normalized to mRNA levels of the housekeeping gene βactin . Formalin fixed spleen and liver tissue sections were stained with hematoxylin and eosin , and two veterinary pathologists ( MX and TS ) performed a blinded evaluation using criteria described in Table S2 in Text S1 . Representative images were obtained using an Olympus BX41 microscope and the brightness adjusted ( Adobe Photoshop CS2 ) . Flow cytometric analysis of IL-10 producing cells was performed in splenocytes from IL-10 GFP reporter mice infected for 3 and 9 days with B . abortus 2308 . Briefly , after passing the spleen cells through a 100-µm cell strainer and treating the samples with ACK buffer ( 0 . 15 M NH4Cl , 1 . 0 mM KHCO3 , 0 . 1 mM Na2EDTA [pH 7 . 2] ) to lyse red blood cells , splenocytes were washed with PBS ( Gibco ) containing 1% bovine serum albumin ( fluorescence-activated cell sorter [FACS] buffer ) . After cell counting , 4×106 cells/mouse were re-suspended in PBS and stained with Aqua Live/Dead cell discriminator ( Invitrogen , Grand Island , NY ) according to the manufacturer's protocol . After Live/Dead staining , splenocytes were resuspended in 50 µL of FACS buffer and cells were stained with a cocktail of anti-B220 Brilliant Violet 421 ( Biolegend , San Diego , CA ) , anti-CD3 PE ( BD Pharmingen , San Jose , CA ) , anti-CD11b APC . Cy7 ( Biolegend , San Diego , CA ) , anti-F4/80 Pe . Cy7 ( Biolegend , San Diego , CA ) , anti-Cd11c APC ( Biolegend , San Diego , CA ) . To determine the T cell subset responsible for IL-10 production , cells were stained with a cocktail of anti-CD3 APC . Cy7 ( eBioscience , San Diego , CA ) , anti-CD8 AF700 ( BD Pharmigen , San Jose , CA ) , anti-TCRγδ PE ( BD Pharmigen , San Jose , CA ) , anti-CD4 eFluor 450 ( eBioscience , San Diego , CA ) , anti-CD25 Pe . Cy7 ( eBioscience , San Diego , CA ) . The cells were washed with FACS buffer and fixed with 4% formaldehyde for 30 min at 4°C , and resuspended in FACS buffer prior to analysis . Flow cytometry analysis was performed using an LSRII apparatus ( Becton Dickinson , San Diego , CA ) , and data were collected for 5×105 cells/mouse . Resulting data were analyzed using Flowjo software ( Treestar , inc . Ashland , OR ) . Gates were based on Fluorescence-Minus-One ( FMO ) controls . Immunofluorescence of Brucella infected BMDM was performed as previously described [24] . Briefly , B . abortus MX2 infected BMDM were grown on 12-mm glass coverslips in 24-well plates were washed three times with PBS , fixed with 3% paraformaldehyde , pH 7 . 4 , at 37°C for 20 min , washed three times with PBS and then incubated for 10 min in 50 mm NH4Cl in PBS in order to quench free aldehyde groups . Samples were blocked and permeabilized in 10% goat serum and 0 . 1% saponin in PBS for 30 min at room temperature . Cells were labeled by inverting coverslips onto drops of primary antibodies diluted in 10% horse serum and 0 . 1% saponin in PBS and incubating for 45 min at room temperature . The primary antibody used was rat anti-mouse LAMP-1 ( BD Pharmigen , San Jose , CA ) . Bound antibodies were detected by incubation with 1∶500 dilution of Alexa Fluor 488 donkey anti-rat ( Invitrogen , Grand Island , NY ) for 45 min at room temperature . Cells were washed twice with 0 . 1% saponin in PBS , once in PBS , once in H2O and then mounted in Mowiol 4-88 mounting medium ( Calbiochem ) . Samples were observed on a Carl Zeiss LSM 510 confocal laser scanning microscope for image acquisition ( Carl Zeiss Micro Imaging ) . Confocal images of 1024×1024 pixels were acquired as projections of three consecutive slices with a 0 . 38-µm step and assembled using Adobe Photoshop CS2 ( Adobe Systems ) . For quantification of Brucella MX2 and Lamp1+ compartment colocalization , at least 100 bacteria/sample were counted . All experiments were performed independently in quadruplicate at least two times . Fold changes of ratios ( bacterial numbers or mRNA levels ) and percentages ( flow cytometry and fluorescent microscopy ) were transformed logarithmically prior to statistical analysis . An unpaired Student's t-test was performed on the transformed data to determine whether differences in fold changes between groups were statistically significant ( P<0 . 05 ) . Significance of differences in histopathology scores was determined by a one-tailed non-parametric test ( Mann-Whitney ) .
|
Brucella spp . are pathogens causing chronic intracellular infections that evade detection by pattern recognition receptors of the innate immune system . In this work , we tested the hypothesis that , in addition to eliciting a weak proinflammatory response during infection , induction of an immunoregulatory environment early during infection could promote persistent infection . Our results show that IL-10 produced at early time points is important for blunting inflammatory responses to B . abortus in infected tissues . CD4+ T cells are an important source of this cytokine , since mice lacking T cell-derived IL-10 exhibited increased inflammatory pathology and also were better able to control B . abortus infection . A target of this CD4 T cell-derived IL-10 is macrophages , since treatment of these cells with IL-10 in vitro supported intracellular replication of B . abortus , while blocking IL-10 restricted the ability of B . abortus to exit the phagolysosomal compartment and replicate intracellularly . Further , mice conditionally deficient for IL-10 receptor on macrophages were better able to control infection with B . abortus . Taken together , our results support a model in which IL-10 production by T cells promotes chronic infection by rendering macrophages more permissive for intracellular replication of B . abortus .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"medicine",
"bacterial",
"diseases",
"infectious",
"diseases",
"zoonoses",
"immune",
"cells",
"monocytes",
"immunity",
"t",
"cells",
"microbial",
"control",
"immunology",
"host-pathogen",
"interaction",
"biology",
"immunoregulation",
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"pathogens",
"immune",
"response"
] |
2013
|
CD4+ T Cell-derived IL-10 Promotes Brucella abortus Persistence via Modulation of Macrophage Function
|
Leishmaniasis is a disease caused by the protozoan parasite , Leishmania . The disease remains a global threat to public health requiring effective chemotherapy for control and treatment . In this study , the effect of some selected phenolic compounds on Leishmania donovani was investigated . The compounds were screened for their anti-leishmanial activities against promastigote and intracellular amastigote forms of Leishmania donovani . The dose dependent effect and cytotoxicity of the compounds were determined by the MTT assay . Flow cytometry was used to determine the effect of the compounds on the cell cycle . Parasite morphological analysis was done by microscopy and growth kinetic studies were conducted by culturing cells and counting at 24 hours intervals over 120 hours . The cellular levels of iron in promastigotes treated with compounds was determined by atomic absorption spectroscopy and the effect of compounds on the expression of iron dependent enzymes was investigated using RT-qPCR . The IC50 of the compounds ranged from 16 . 34 μM to 198 μM compared to amphotericin B and deferoxamine controls . Rosmarinic acid and apigenin were the most effective against the promastigote and the intracellular amastigote forms . Selectivity indexes ( SI ) of rosmarinic acid and apigenin were 15 . 03 and 10 . 45 respectively for promastigotes while the SI of 12 . 70 and 5 . 21 respectively was obtained for intracellular amastigotes . Morphologically , 70% of rosmarinic acid treated promastigotes showed rounded morphology similar to the deferoxamine control . About 30% of cells treated with apigenin showed distorted cell membrane . Rosmarinic acid and apigenin induced cell arrest in the G0/G1 phase in promastigotes . Elevated intracellular iron levels were observed in promastigotes when parasites were treated with rosmarinic acid and this correlated with the level of expression of iron dependent genes . The data suggests that rosmarinic acid exerts its anti-leishmanial effect via iron chelation resulting in variable morphological changes and cell cycle arrest .
Leishmaniasis is caused by the parasitic , single-cell eukaryotic organism called Leishmania . It is transmitted to man and animals ( e . g . rodents , hydrax , canids ) via a blood meal feed of the female sand-fly [1] . Currently , there are about 18 different Leishmania species including Leishmania donovani that have been discovered to be pathogenic to humans [2 , 3] . L . donovani amongst other species of the parasite causes visceral leishmaniasis ( VL ) . VL is the most intense and fatal clinical manifestation of the disease compared to the other form of leishmaniasis known as cutaneous leishmaniasis . The reported global annual mortality caused by VL infection is about 20 , 000 [3 , 4] . It is the next cause of parasite-related death after malaria [1] and is thought to be underreported mainly due to subclinical forms , socioeconomic constraints and other barriers such as diagnosis and detection of the parasite . The disease remains a global threat that requires effective chemotherapy since not much progress has been made in the development of a potent vaccine . The available drugs used in the treatment of leishmaniasis include first line treatment drugs such as pentavalent antimonials and second line drugs ( amphotericin B , pentamidine , paromomycin and miltefosine ) , for the treatment of resistant cases [5] . A new drug , sitamaquine is currently under development for the potential treatment of visceral leishmaniasis ( VL ) . The use of some of these drugs for the treatment of leishmaniasis are affected by factors such as emergence of drug resistance , especially with the pentavalent antimonials [6–11] and challenges of toxicity , short half-life and high cost of drugs , as well as failure of patient to comply with treatment [5 , 12 , 13] . Phenolic compounds , which are secondary plant metabolites found in diet , have been reported amongst other natural compounds to have inhibitory effects against protozoan parasites [14 , 15] . The potential of phenolic compounds as leishmanicidal agents have been reported in a number of studies [16–19] . They have been reported to mainly function as antioxidants by chelation of metal ions [20] and removal of free radicals [19] . The metal chelation property of phenolic compounds is mainly by the presence of the ortho-dihydroxy ( catechol and galloyl groups ) and flavan moiety that exists within the compounds [21] . These moieties , the number and orientation of OH groups and the negative charge density present in some of these phenolic compounds are known iron binding elements [22–25] . Studies have also shown that these compounds can induce apoptotic cell death in Leishmania via other pathways other than iron chelation [26 , 27] . Iron metabolism is an essential pathway that is important for Leishmania parasite survival and replication in the phagolysosomes of macrophages [28–30] . Within the parasitophorous vacuole of macrophages , the parasites have the ability to utilize various iron sources such as heme [31] , transferrin [32] , lactoferrin [33 , 34] and hemoglobin [35] . Iron serves as an internal precursor of Fe-S clusters and Fe-dependent enzymes serving as a cofactor of several enzymes like iron superoxide dismutase ( FeSOD ) and constituent element of ribonucleotide reductase [30 , 36] , thus supporting essential cellular functions . Therefore , the selective removal of iron by chelation would probably result in reduction in the accessibility of iron to the parasite which would likely impair growth and eventually cause death of parasites . In this study , we investigated the effect of ten phenolic compounds on promastigotes and intracellular amastigotes of Leishmania donovani and suggest a mechanism of their action against the parasite .
Stock solutions with concentration between 100–730 μM of the phenolic compounds ( protocatechuic acid , gallic acid , caffeic acid , vanillic acid , ferulic acid , p-Coumaric acid , apigenin , chlorogenic acid , rosmarinic acid , salicylic acid ) ( Fig 1 ) and deferoxamine ( Sigma Aldrich , USA ) were prepared by dissolving in dimethyl sulfoxide ( DMSO ) at room temperature and stored at 4°C . The final concentration of DMSO used was 1% . Amphotericin B ( Sigma Aldrich , USA ) was prepared in double distilled water . Deferoxamine , a known iron chelator and Amphotericin B , a drug used for the treatment of leishmaniasis , were used as controls . Leishmania donovani promastigotes ( MHOM/SD/62/1S strain ) were kindly provided by Dr . Yamthe Lauve ( Bei Resources NIAID , NIH ) . The promastigotes were cultured and maintained at 25°C in M-199 medium containing 100 mg/L L-glutamine , 100 μ/ml penicillin-G , 100 μg/mL streptomycin and complemented with 10% heat inactivated fetal bovine serum ( FBS ) . RAW 264 . 7 ( RIKEN BioResource Centre Cell Bank , Japan ) cells were kindly provided by Professor Regina Appiah-Opong of the Clinical Pathology Department , Noguchi Memorial Institute for Medical Research , Ghana . The MTT assay was done as previously described [37] . Briefly , promastigotes ( 2 x 105 cells ) were cultured in freshly prepared M-199 medium supplemented with 10% heat inactivated fetal bovine serum in the presence or absence of varying concentrations of the phenolic compounds ( 0–50 μg/mL ) for 72 hours at 25°C . Amphotericin B ( 0–50 μg/mL ) and deferoxamine ( 0–50 μg/mL ) were used as positive controls . After incubation , 5 mg/mL MTT solution was added to the promastigotes in each well and incubated for 3 hours at 25°C . In this assay , the yellow tetrazolium MTT dye was reduced to insoluble formazan crystals ( purple color ) in living cells using NADH as their reducing agent . Formazan crystals formed after incubation were solubilized with acidified isopropanol and incubated at 37°C for 30 min . The change in color from yellow to purple was read at an absorbance of 570 nm using Thermo Scientific Varioskan LUX . The cell viability and IC50 were determined from the concentration response curve generated using GraphPad Prism 6 . 0 Software . The dose dependent inhibition of phenolic compounds on promastigotes was determined by culturing promastigotes ( 2 x 105 cells ) in freshly prepared M199 medium in the presence and absence of varying concentration of the test compounds , apigenin ( IC50 , 2x IC50 , 4x IC50 ) , rosmarinic acid ( IC50 , 2x IC50 , 4x IC50 ) , amphotericin B ( 1/2 IC50 , IC50 ) and deferoxamine ( IC50 , 2x IC50 , 4x IC50 ) , for 120 hours . The number of parasites was determined by staining with trypan blue every 24 hours . Quantification of the viable parasites was determined by counting the parasites with the clear cytoplasm ( non-stained ) using a Neubauer hemocytometer with a cover slip . Three independent experiments were performed , and data expressed as mean ± standard deviation . Promastigotes ( 2 x 106 cells ) were incubated with appropriate concentrations of apigenin ( 2x IC50 ) , rosmarinic acid ( 2x IC50 ) , amphotericin B ( 1/2 IC50 ) and deferoxamine ( 2x IC50 ) for 24 hours at 25°C , harvested by low-speed centrifugation at 239 x g for 10 min , washed once with Voorheis Modified Phosphate Buffered Saline ( vPBS ) , fixed in 8% paraformaldehyde ( PFA ) , lysed with 10% v/v Triton X-100 and incubated for 10 min . The cell pellets were then washed twice and resuspended in 1x PBS . The cells were then allowed to settle on poly-L-lysine coated slides and then rinsed with 1x PBS . Tris-HCl ( 100 mM ) pH 7 . 5 in 1x PBS was used to block the PFA for 10 minutes . DAPI stain ( 0 . 1μg/mL ) was added followed by one wash in 1x PBS . Coverslips were mounted onto the slides using Vectashield mounting media and observed under the Olympus fluorescent microscope to detect any phenotypic changes in L . donovani promastigotes . The total number of parasites was determined by direct counting of parasites per field , using ImageJ Software . The frequency of parasites was visually determined by counting parasites that had any abnormalities in their structure compared to the untreated control . Cell cycle analysis of treated and untreated L . donovani promastigotes was performed using flow cytometry . After treatment of promastigotes ( 2 x 106 cells ) with the appropriate concentrations of the compounds [apigenin ( 2x IC50 ) , rosmarinic acid ( 2x IC50 ) , amphotericin B ( 1/2 IC50 ) and deferoxamine ( 2x IC50 ) ] for 24 hours , the cells were harvested and fixed in 70% ethanol ( diluted in 1x PBS ) for 1 hour . The fixed cells were harvested , resuspended in 1x PBS for 1 min and washed twice in 1x PBS . Staining solution ( Guava cell cycle reagent ) was added and incubated at room temperature for 30 min . The percentage cell count in G0 , G1 , S , G2 and M phases of the cell cycle were determined with BD LSR Fortessa™ . X-20 analyzer ( BD Biosciences ) and data was analyzed with FlowJo software . Promastigotes ( 4 x 106 cells ) were treated with apigenin ( 2x IC50 ) , rosmarinic acid ( 2x IC50 ) , amphotericin B ( 1/2 IC50 ) and deferoxamine ( 2x IC50 ) ] and then incubated for 24 hours at 25°C . After incubation , the promastigotes were harvested and resuspended in serum-free M199/1%BSA . MitoTracker Red CMXROS ( a cationic fluorescent dye that labels the mitochondria within live cells ) at 100 nM was added and incubated for 30 min . Parasites were washed once with serum-free M199/1% BSA , pelleted by centrifugation at 1500 rpm for 10 min , resuspended in 1x vPBS and 6% paraformaldehyde and incubated at 4°C for 1 hour . The promastigote pellets were washed twice and resuspended in 1xPBS . The parasites were then allowed to settle on poly-L-lysine coated slides and DAPI stain ( 0 . 1μg/mL ) was added followed by one wash in 1x PBS . Coverslips were mounted onto the slides using Vectashield mounting media and observed under the Olympus fluorescent microscope to detect any abnormalities in the structure of the mitochondria . The total number of parasites was determined by direct counting of parasites per field , using ImageJ Software . Parasites with distorted mitochondria were visually determined by counting parasites that had any abnormalities in the structure of the mitochondria compared to the untreated control . Intracellular iron content of Leishmania donovani was estimated by treating promastigotes ( 2 x 107 cells ) with rosmarinic acid ( 4x IC50 ) and apigenin ( 4x IC50 ) , and amphotericin B ( IC50 ) , deferoxamine ( 4x IC50 ) and incubated at 25°C for 24 hours . The parasites were then washed twice with 1x PBS and resuspended in 50 μl deionized water . An aliquot ( 10 μl ) of the parasite suspension was used for protein content determination as described by [38] . The remaining parasite sample ( 40 μl ) was digested with HNO3 for 1 hour at 80°C and overnight at 20°C . Cell digestions were stopped by the addition of 30% H2O2 and topped up to 1 . 5 ml with deionized water . Iron content in digested samples , spent and unused media were measured by atomic absorption spectroscopy using a Perkin Elmer Analyst 300 spectrometer . Promastigotes ( 1 x 107 cells ) were separately treated with rosmarinic acid , apigenin , amphotericin B and deferoxamine , harvested after 24 hours incubation at 25°C . The parasites were then pelleted by centrifugation at 239 × g for 10 min and the pellet was re-suspended in 1 mL TRIzol . Samples were incubated overnight at -80°C and total RNA was extracted as described by the manufacturer’s protocol using Quick-RNA MiniPrep Plus ( Zymo Research , USA ) . Purity of total RNA was determined to be approximately 2 . 0 using a Nanodrop . The oligonucleotide primers for the amplification of the iron dependent enzymes—ribonucleotide reductase ( RNR ) ( 3’TACGACACGCTGAAGGAGTG and 5’CAACAACTTCTGCGCATCG ) , iron superoxide dismutase A ( FeSOD ) ( 3’GCTCGGCTTCAACTACAAGG and 5’GTCCGTGAAGGTCTTCTTCC ) and Leishmania iron transporter 1 ( LIT1 ) ( 3’CCTACTCACTTGGCCTGCAT and 5’ TAGCAGCTGTGTCTGTCGTC ) were designed using sequences of Leishmania reference genome from tritrypdb . org ( http://tritrypdb . org/tritrypdb/ ) and Primer 3 software . The oligonucleotide primers used in amplifying the housekeeping gene Histone 2A were ( 3’ CGCGAAATGTGGTCTGATCT and 5’TCTTCGCTCGACTACAGCAG ) . The RT-qPCR reaction was conducted as described by manufacturer’s protocol with final concentrations of oligonucleotide primers as 0 . 4 μM , 1x Luna Universal One-Step Reaction mix , 1x Luna WarmStart RT Enzyme Mix and template RNA ≤ 1 μg . All the RT-PCR products were standardized with respect to the endogenous control , Histone 2A . The levels of the mRNA transcripts were obtained using the QuantStudio 5 Real-Time PCR System ( Applied Biosystems ) . The data represent three independent experiments done in triplicate and a fold change in gene expression of >2 was considered significant . Raw 264 . 7 cells were seeded into 96-well plates at ( 1 x 106 cells ) in DMEM supplemented with 10% FBS , 100 μg/mL streptomycin , 100 u/mL penicillin-G , 2g/L NaHCO3 and incubated at 37°C for 24 hours in 5% CO2 . The cells were treated with 0–50 μg/mL concentrations of the phenolic compounds for 48 hours at 37°C in 5% CO2 . Deferoxamine and amphotericin B at 0–50 μg/mL concentrations were used as positive controls . Cell viability was estimated by measuring the mitochondria oxidative activity by MTT assay and absorbance was read at 570 nm using Thermo Scientific Varioskan LUX . Selectivity index ( SI ) was calculated as the ratio of the CC50 to IC50 values . Amastigote cultures were prepared as reported by Jain and colleagues [39] . Briefly , Raw 264 . 7 cells ( 4 x 107 cells ) were seeded in 4 chamber slides and 1 x 107 cells in 96 well plates and incubated for 24 hours at 37°C in 5% CO2 . The RAW 264 . 7 cells were infected with metacyclic promastigotes ( 1 x 108 cells ) at an infection ratio of 1:10 macrophage: parasites and incubated for 24 hours at 37°C in 5% CO2 . The overlying medium was removed , and the monolayer intracellular amastigotes were carefully washed four times with serum free M199 to remove free parasites . Freshly prepared M199 containing 10% FBS and the test compounds at concentrations ranging from 0–50 μg/mL were added to the infected cells and incubated for 48 hours at 37°C in 5% CO2 . Triplicate incubations were performed in all the experiments . The chamber slides were washed thrice after incubation with M199 without FBS . The slides were then fixed in absolute methanol for 30 sec , rehydrated in 1x PBS for 5 min and stained with DAPI for 15 min . The slides were viewed by fluorescence microscopy and the number of infected macrophages counted using ImageJ Software to determine the infectivity index and IC50 values for amastigotes . The infected RAW 264 . 7 cells in the 96 wells microtiter plates were also incubated for 48 hours and washed thrice as above . Sodium dodecyl sulfate ( SDS ) of concentration 0 . 05% was added to the wells for 30 sec for controlled lysis with M199 and 10% FBS . After the 30 sec , M199 with 10% FBS was added and the plates incubated at 25°C for 72 hours for the differentiation of the rescued amastigotes to promastigotes . Following incubation , the amastigotes were subjected to MTT assay and the absorbance obtained were used to estimate IC50 values of the compounds against the amastigote forms . All results obtained were represented as mean±standard deviation ( SD ) from three independent experiments . GraphPad Prism 6 . 0 Software was used in the analysis of the data . The in vitro leishmanicidal activity , indicated as IC50 , was derived from non-linear regression analysis . Statistically significant differences for the different groups were determined by Student’s t test and Dunnett’s multiple comparisons test , p-value ≤ 0 . 05 were considered significant . Cell cycle data was analysed with FlowJo Version 10 and GraphPad Prism 6 . 0 Software . The RT-PCR was done in triplicate and statistical analysis was done using the student t test and the Dunnett’s multiple comparisons test , p-value ≤ 0 . 05 were considered significant .
To investigate the effects of the phenolic compounds on cell viability , 2 x 105 promastigotes were incubated with varying concentrations ( 0–50 μg/mL ) of the phenolic compounds . The phenolic compounds that elicited significant anti-leishmanial activity were rosmarinic acid and apigenin . Treatment with rosmarinic acid and apigenin affected parasites’ growth in a dose- and time-dependent manner with IC50 values of 16 . 34 ± 0 . 1 μM and 22 . 77 ± 0 . 01 μM respectively . Amphotericin B and deferoxamine had IC50 values of 6 . 56 ± 0 . 06 μM and 10 . 35 ± 0 . 01 μM respectively ( Table 1 ) . In order to evaluate the effects of rosmarinic acid and apigenin on parasite replication , promastigotes were cultured in the presence or absence of the compounds . Cell density was measured every 24 hours over the 120 hours of culturing by staining with trypan blue and counting in a hemocytometer chamber . Treatment with increasing concentrations of apigenin and rosmarinic acid , and the control compounds , amphotericin B and deferoxamine , resulted in drastic reduction in promastigote replication ( Fig 2 ) . An exponential growth was observed for untreated cells , while a reduction in cell growth was evident at 48 hours after treatment with rosmarinic acid , apigenin and deferoxamine and at 24h in amphotericin B treated-parasites . At 48 hours there was a 50% decrease in the number of promastigotes when cultured in the presence of IC50 concentrations of rosmarinic acid ( p value = 0 . 011 ) , apigenin ( p value = 0 . 024 ) and deferoxamine ( p value = 0 . 030 ) . The number of parasites reduced significantly by 90% at 24 hours in the presence of IC50 concentrations amphotericin B ( p value = 0 . 004 ) ( Fig 2 ) . The cytotoxic effect of compounds on Raw 264 . 7 cells was assessed using the MTT assay . The phenolic compounds had cytotoxic concentration ( CC50 ) values and selectivity indexes ( SI ) between 13–520 μM and 0 . 2–15 respectively . Rosmarinic acid and apigenin which had high anti-leishmanial activity gave SI values of 15 . 03 and 10 . 45 against the promastigotes , compared with 2 . 27 and 2 . 60 SI values of amphotericin B and deferoxamine respectively . Against the intracellular amastigotes , rosmarinic acid , apigenin , deferoxamine and amphotericin B showed SI values of 12 . 70 , 5 . 21 , 0 . 73 and 2 . 40 respectively ( Tables 1 and 2 ) . Morphological changes were assessed after 24 hours in promastigotes treated with 2x IC50 values of rosmarinic acid , apigenin and deferoxamine , as well as half the IC50 of amphotericin B . Abnormalities in the size and shape of promastigotes relative to the untreated control were observed in the micrographs . About 90% of untreated parasites appeared thin and elongated with long flagellum and smooth cell membrane . The kinetoplast and nuclear DNA also remained intact when observed using the DAPI stain . Upon treatment with rosmarinic acid , 70% ( p value = 0 . 007 ) of the parasites appeared rounded with associated cytoplasmic condensation and the kinetoplast and nuclear DNA appeared aggregated . Treatment with amphotericin B had 90% ( p value = 0 . 004 ) of parasites showing irregular shape , severe distortion in the cell membrane with a loss of the kinetoplast DNA , 30% ( p value = 0 . 021 ) of parasites treated with apigenin appeared ruptured and 90% ( p value = 0 . 005 ) of promastigotes treated with deferoxamine had rounded morphology with aggregated kinetoplast and nuclear DNA , similar to that observed for rosmarinic acid ( Fig 3 ) . We further investigated the effect of rosmarinic acid and apigenin on the structure of the mitochondria by incubating the promastigotes in the presence or absence of the compounds for 24 hours . The parasites stained with mitotracker red and DAPI revealed that about 98% of the untreated parasites had a well-defined mitochondrion within the cell body of the parasite . When parasites were treated with rosmarinic acid , apigenin , deferoxamine and amphotericin B , 70% ( p value = 0 . 037 ) , 75 . 8% ( p value = 0 . 039 ) , 81% ( p value = 0 . 004 ) and 99% ( p value = 0 . 0036 ) respectively of promastigotes had the mitotracker dye accumulating in the cytoplasm with bright red aggregation ( Fig 4 ) . The normal well-defined shape of the mitochondrion was distorted in treated promastigotes . To investigate the effect of phenolic compounds on the cell cycle of the parasite , the DNA content of treated and untreated cells incubated for 24 hours were analysed using propidium iodide and the cell cycle progression determined by flow cytometry ( Fig 5 ) . The untreated parasites had 34 . 6% of cells at G0/G1 while significant differences were observed in the number of parasites for all the compounds tested . There was an increase in the G0/G1 cells when parasites were treated with apigenin and rosmarinic acid ( apigenin 8% increase , p value = 0 . 008 and rosmarinic acid 7 . 1% increase , p value = 0 . 006 ) ( Fig 5B and 5C ) . We observed a similar increase in deferoxamine and amphotericin B treated parasites ( deferoxamine 7% increase , p value = 0 . 040 and amphotericin B 13 . 1% increase , p value = 0 . 0004 ) . Only amphotericin B showed a significant increase in the number of parasites at the S phase . There was no significant change in the number of parasites at the G2 phase for all compounds tested . However , there was a significant decrease in the number of parasites at the M phase for all treatments compared to the untreated ( apigenin 6 . 8% decrease , p value = 0 . 0062; rosmarinic acid = 8 . 0% decrease , p value = 0 . 011; deferoxamine 7 . 7% decrease , p value = 0 . 012 and amphotericin B = 13 . 8% , p value = 0 . 003 ) ( Fig 5F ) . In order to assess whether apigenin and rosmarinic acid were acting as iron chelators , the iron concentration in cell digest , unused and spent culture medium was determined with an atomic absorption spectrophotometer as described by Dragset and colleagues [40] . Protein content for the parasites was determined to be 40 . 5 μg/mL . Promastigotes treated with deferoxamine and rosmarinic acid showed elevated intracellular iron levels relative to the untreated cells ( deferoxamine 0 . 36 mg/L , p value = 0 . 040 and rosmarinic acid 0 . 30 mg/L , p value = 0 . 020 ) . Amphotericin B ( 0 . 15 mg/L , p value = 0 . 120 ) did not show any significant change in intracellular iron levels , whereas apigenin showed significant decrease 0 . 1 mg/L , p value = 0 . 020 compared to the untreated parasites ( Fig 6A ) . However , the concentration of iron in the spent media was significantly decreased by about three-fold in treated parasites compared to the unused ( apigenin 0 . 11 mg/L , p value = 0 . 002; rosmarinic acid 0 . 09 mg/L , p value = 0 . 002; deferoxamine 0 . 08 mg/L , p value = 0 . 002; amphotericin B 0 . 07 mg/L , p value = 0 . 002 ) ( Fig 6B ) . The effect of the test compounds on the mRNA of iron dependent proteins in promastigotes was investigated by determining the mRNA expression levels using quantitative RT PCR . The change in the levels of mRNA expression was determined by comparing with the untreated control . There were varying degrees of expressions of the iron dependent proteins in the presence of the compounds . LIT1 and FeSOD were significantly over expressed in deferoxamine treated parasites compared to the untreated parasites ( LIT1 = 125-fold and FeSOD = 5-fold ) ( Fig 7A and 7B ) . LIT1 level was also significantly upregulated in amphotericin B ( 5-fold ) and rosmarinic acid ( 3-fold ) treated parasites while there was no observed change in apigenin treated parasites ( Fig 7A ) . The FeSOD levels however did not significantly change in amphotericin B , apigenin and rosmarinic acid treated parasites ( Fig 7B ) . There was an increased expression of RNR in amphotericin B ( 3-fold ) and apigenin ( 3-fold ) treated cells and a decrease in the expression of RNR in deferoxamine ( 80% reduction , p value < 0 . 0001 ) and rosmarinic acid treated parasites ( 90% reduction , p value < 0 . 0001 ) ( Fig 7C ) . To assess the effects of the phenolic compounds on amastigotes , infected macrophages were treated with increasing concentration of the compounds ( 3 . 12–50 μg/mL ) . Rosmarinic acid and apigenin showed significant inhibitory effect against the amastigotes with IC50 values of 19 . 21±0 . 01 μM and 45 . 66±0 . 01 μM respectively . The IC50 values observed for amphotericin B and deferoxamine were 6 . 491±0 . 03 μM and 36 . 74±0 . 01 μM respectively ( Table 2 ) . When the infected macrophages were treated with increasing concentrations of rosmarinic acid , apigenin , deferoxamine and amphotericin B , there was a decrease in the number of infected cells . Treatment with amphotericin B at a low concentration ( 3 . 12 μg/mL ) gave the lowest infectivity index of 56 ( p value = 0 . 0005 ) compared to the untreated infected macrophages ( Fig 8 ) . The infectivity values for rosmarinic acid , apigenin and deferoxamine were lower ( rosmarinic acid 140 , p value = 0 . 003; apigenin 152 . 2 , p value = 0 . 005 and deferoxamine 177 , p value = 0 . 006 ) compared to the untreated infected macrophages ( Fig 8 ) . Surprisingly , there was no visible morphological changes in the amastigotes after drug treatment .
The ability of phenolic compounds known to have effects against certain protozoan parasites [26 , 41 , 42] was investigated to understand their mechanism of action against Leishmania donovani . All the phenolic compounds used were found to be active in the concentration range of 16–198 μM , with rosmarinic acid and apigenin having a high inhibitory effect on both forms of the parasite , with selectivity values higher than amphotericin B , an anti-leishmanial drug and deferoxamine , an iron chelator . The differences in the leishmanicidal activities observed against the parasite between the selected phenolic compounds , and the amphotericin B and deferoxamine control could be explained by the structural variations in these phenolic compounds . Rosmarinic acid has been shown to inhibit the cellular replication of L . amazonensis , an activity that has been reported to be due to the iron chelating ability of the catechol groups it contains [18] . Caffeic acid , a catechol compound and a component of rosmarinic acid , had a lower inhibitory effect against the parasite compared to rosmarinic acid . The conjugation of caffeic acid with 3- ( 3 , 4-dihydroxyphenyl ) lactic acid resulting in two iron chelating catechol groups as found in rosmarinic acid could account for its ability to better scavenge iron from the parasite and hence the more pronounced growth inhibitory effect . Apigenin has no catechol functionality in its structure but it has been suggested that the 2–3 double bond and three hydroxyl groups of apigenin might be involved in the generation of reactive oxygen species which inhibited the growth of L . amazonensis [27 , 43 , 44] . These groups have also been shown to influence the metal scavenging activity of apigenin [45] . Deferoxamine had a higher inhibitory effect on the parasite compared to the phenolic compounds and has also been shown to have a higher affinity for iron [46 , 47] . Its mechanism of scavenging iron from the parasite could result in the inhibitory effect observed . Rosmarinic acid and apigenin showed significant effects on the morphology of the parasite . The rounding and cytoplasmic condensation of cells treated with rosmarinic acid and the associated aggregation of the kinetoplast and nuclear DNA , could be the way the compound exert its inhibitory effects . Similar morphological changes were observed for deferoxamine treated cells . The observations suggest that rosmarinic acid and deferoxamine probably chelate the free iron within the medium , creating an iron poor environment that affects the stability of the iron acquisition mRNA transcripts leading to their transformation into axenic amastigotes [48] , which appear rounded . Other studies have also shown that , certain conditions such as pH , temperature and iron deficient culture media mimic the intracellular environment of the host cell and cause the transformation of thin elongated promastigotes to rounded forms of axenic amastigotes [49 , 50] . The morphological changes induced by deferoxamine and rosmarinic acid could cause programmed cell death as suggested by Islamuddin and others [51] . Cells treated with apigenin appeared lysed with the loss of kinetoplast and nuclear DNA . The lytic action observed could be attributed to apigenin’s ability to lyse certain cell organelles , such as the mitochondria and Golgi apparatus [43] . The distortion of the parasite’s cell membrane by treatment with amphotericin B could be due to its binding to ergosterol in the parasite membrane . This could lead to the formation of pores within the cell membrane , which alter the ion balance , causing cell lysis and death of the parasite [52] . Mitochondria integrity which defines the functionality of the cell was also compromised in the presence of the compounds . The effect of apigenin and rosmarinic acid on the mitochondria membrane potential supports findings of several studies that reported their involvement in inducing apoptotic death of cells through the production of ROS . These studies have shown that alteration in the morphology of the mitochondria can lead to the loss of cell viability [43 , 53 , 54] . Accumulation of amphotericin B within the parasite has also been shown to auto-oxidize and generate ROS within L . donovani [55 , 56] this could cause a loss in the integrity of the mitochondria membrane . The effect of deferoxamine on the parasites supports a study which reported that iron chelating compounds result in the depletion of iron and affect the ability of FeSODA located in the parasite’s mitochondria to mop up the reactive oxygen species [48] . This removal of iron , an essential cofactor , from FeSODA affects the activity and structure of the mitochondria [57] . The parasites that survived treatment with higher concentration of compounds could either be resistant parasites or parasites that have some dysfunction in their mitochondria but are still viable . The accumulation of cells in GO/GI phase observed when promastigotes were treated with rosmarinic acid , apigenin and deferoxamine suggests that the compounds could be inducing cell cycle arrest by affecting certain cell cycle regulatory proteins . Iron chelation has been reported to decrease the level of expression of cyclin and cdk genes and an increase in cyclin dependent inhibitors [58] . The accumulation of cells in the GO/G1 phase observed for rosmarinic acid treated parasites maybe as a result of inhibition of the replication of cells , halt DNA synthesis and the activity of some cell cycle proteins [59] . It is most likely that , apigenin alters the cell cycle regulatory system by decreasing the expression of cyclins and cdks [60] hence the accumulation of cells in the G0/G1 phase . Microarray analysis of deferoxamine treated HL-60 leukaemia cells resulted in a significant decrease in the mRNA expressions of cyclin genes and RNR [61 , 62] . Amphotericin B has been shown to cause an increase in the G1 and S phases , and a decrease in the M phases in cells [63] . The susceptibility of the parasites to amphotericin B has been attributed to the synthesis of sterols initiated in the G1 and S phases of the parasite’s cell cycle [64] . In this study , we observed elevated intracellular iron content of parasites treated with rosmarinic acid and deferoxamine . The presence of pyrozolopyrimidinine ( PZP ) , an iron chelator , caused the accumulation of iron within Mycobacteria smegmatis; an obligate intracellular organism like Leishmania , indicating that iron chelating compounds could induce an accumulation of iron within cells [40] . Iron depletion from the culture medium and the parasite’s ability to sense iron deprivation could lead to the upregulation of LIT1 and FeSOD and downregulation of RNR for survival and virulence [30] . Rosmarinic acid and deferoxamine might have created an iron depleted environment in the parasite which could have led to the differential expression of these iron acquisition genes in the Leishmania . Trypanosomes have been shown to upregulate the transferrin receptor to cope in an iron depleted environment [65] . We observed a 3-fold increase in the expression of Leishmania iron transporter 1 ( LIT1 ) in parasites treated with rosmarinic acid compared to the earlier reported six-fold upregulation of the gene in an iron depleted environment [48] . The upregulation of RNR observed for amphotericin B and apigenin treated cells suggest that these two compounds do not prevent the incorporation of cellular iron into newly synthesized iron dependent proteins . Amongst the phenolic compounds investigated in this study , rosmarinic acid and apigenin had selectivity indexes greater than 10 suggesting that their effects were on the parasite and not on the host cells [66 , 67] . This supports other studies reporting the low toxicity levels of rosmarinic acid and apigenin against host cells [18 , 44] . It was also observed that amongst the phenolic compounds , rosmarinic acid and apigenin that had pronounced inhibition against the promastigotes were also potent against the intracellular amastigotes . Their effectiveness was shown by the low level of infectivity compared to the untreated infected-macrophages and their IC50 values . This suggests that , the compounds might transverse the host cell but are degraded rapidly [68] . Infected cells treated with deferoxamine , had some cells still infected with promastigotes even at the highest concentration . This limitation of deferoxamine could be attributed to its lipophobic nature causing it not to be able to transverse the cell membrane of the host cell to elicit its effect [69] . It was also observed that , the IC50 values of rosmarinic acid and apigenin against the promastigotes were lower compared to the intracellular amastigotes , suggesting that , the compounds have relatively easier access to the promastigotes growing freely in the culture medium but , the presence of the host cell reduces their interaction with the intracellular parasite [18] . The present study showed an anti-leishmanial activity of rosmarinic acid and apigenin against L . donovani promastigotes and intracellular amastigotes and resulted in changes in the mitochondria integrity and morphology of the cells . Rosmarinic acid and apigenin induced cell cycle arrest in the G0/G1 phase . Elevated intracellular iron levels observed in promastigotes treated with rosmarinic acid correlated with differential expression levels of iron dependent genes which could have led to a decrease in the activity of crucial iron-regulated enzymes . The findings suggest that rosmarinic acid could be exerting its inhibitory effect against the parasite via iron chelation which results in changes in cell morphology and the arrest of the cell cycle while apigenin may exert its inhibitory effects by other mechanisms . These findings present useful chemotherapeutic potential of phenolic compounds in Leishmaniasis . Further studies that include the use of a combination of the most active phenolic compounds and the currently used anti-leishmanial drugs will provide information on any synergistic effects of the compounds . Also , further in vivo studies are essential to evaluate the leishmanicidal activity of rosmarinic acid and apigenin against Leishmania .
|
The available drugs used in treatment of leishmaniasis , a disease caused by the Leishmania parasite , include pentavalent antimonials and amphotericin B . The cost and associated toxicity of the drugs , side effects and the emergence of drug resistance parasites , as well as the discomfort in drug administration suggests the need for new and better chemotherapeutic interventions . Iron is involved in several biological processes in the Leishmania parasite and it’s important for its growth and survival . The effects of using iron chelators to deprive parasite of iron was investigated in this study . Treatment of L . donovani with rosmarinic acid and apigenin inhibited the growth of promastigotes and intracellular amastigotes in a dose dependent manner . Morphologically , the compounds induced alterations in the parasites upon treatments . Rosmarinic acid was observed to cause the dysfunction of the mitochondria and alter the expression of iron dependent enzymes . Rosmarinic acid ability to chelate iron could be responsible for the changes in cell morphology and cell cycle observed .
|
[
"Abstract",
"Introduction",
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"Results",
"Discussion"
] |
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2019
|
In vitro activity and mode of action of phenolic compounds on Leishmania donovani
|
Organ-selector transcription factors control simultaneously cell differentiation and proliferation , ensuring the development of functional organs and their homeostasis . How this is achieved at the molecular level is still unclear . Here we have investigated how the transcriptional pulse of string/cdc25 ( stg ) , the universal mitotic trigger , is regulated during Drosophila retina development as an example of coordinated deployment of differentiation and proliferation programs . We identify the eye specific stg enhancer , stg-FMW , and show that Pax6 selector genes , in cooperation with Eya and So , two members of the retinal determination network , activate stg-FMW , establishing a positive feed-forward loop . This loop is negatively modulated by the Meis1 protein , Hth . This regulatory logic is reminiscent of that controlling the expression of differentiation transcription factors . Our work shows that subjecting transcription factors and key cell cycle regulators to the same regulatory logic ensures the coupling between differentiation and proliferation programs during organ development .
Selector genes are transcription factors that instruct the development of organs . The processes under the control of selector genes include the assignation of cell fates and their organ-specific responses to extracellular signals [1] . But organ development also requires the faithful execution of proliferation programs to ensure the expansion of progenitor cells and their coordinated exit from the cell cycle prior to the onset of differentiation . This coordinated cell cycle exit is critical to regulate organ size during development and to ensure tissue homeostasis during adult life . The power of selector genes to control the differentiation state of cells and their proliferation regimes explains why abnormal expression of these transcription factors is often associated to cancer [reviewed in 2 , 3] . However , how selector genes carry out the coordination between proliferation and differentiation programs is still unclear . Structures of the nervous system , such as the retina , in which complex arrays of different cell types need to be assembled from multipotent proliferative progenitors , are especially sensitive to impairments of proliferation control mechanisms [reviewed in 4 , 5] . It is therefore likely that selector genes coordinate cell cycle exit with the processes of differentiation and patterning by co-regulating the transcription of cell cycle and patterning genes . However , this control may be direct or mediated by intermediate transcription factors . The eye selector function is exerted by a network of transcription factors and signaling pathways , with many of the network genes shared by invertebrates and vertebrates . The Pax6 selector genes are on top of the retinal determination ( RD ) gene network in both animal groups [6] . Pax6 mutations are responsible for aniridia [7 , 8] , while Pax6 overexpression is associated with retinoblastoma cancer progression through promotion of proliferation and cell survival [9–11] . In Drosophila , the RD gene network comprises a number of transcription factors and nuclear proteins , that includes members of conserved gene families: The Pax6 paralogues eyeless ( ey ) and twin of eyeless ( toy ) ; the Six family genes Optix ( Six3 ) and sine-oculis ( so; Six1 , 2 ) ; So’s partner , eyes absent ( eya ) ; dachshund ( dac ) ; and the Meis1 homologue homothorax ( hth ) . These genes are not only connected through transcriptional cross-regulation , but also have been found to engage in protein complexes [reviewed in 12 , 13] . Research during the past years is yielding an increasingly clearer picture of how the process of eye specification and retinal patterning in Drosophila is controlled [reviewed in 13 , 14] . The eye primordium ( also called “eye disc” ) derives from the So-expressing embryonic cephalic neuroectoderm [15] . Within this domain , toy activates ey expression during late embryogenesis , which results in the specification of the eye-progenitor cells [16] . During larval life , ey-expressing progenitors are maintained proliferative and multipotent as long as they express hth [17–19] . Repression of hth starts during the third and last larval stage ( L3 ) , mediated by Decapentaplegic ( Dpp a BMP2/4-like molecule ) and Hedgehog ( Hh ) signals produced at a moving signaling center , called “morphogenetic furrow” ( MF ) . hth repression is key , as it allows the upregulation of so , eya and dac [17 , 19] . Coinciding with hth repression , the expression of string ( stg ) -the Drosophila cdc25 phosphatase homologue [20–22]- is upregulated and this drives cells through a few consecutive mitotic rounds ( the first mitotic wave , FMW ) , resulting in G1-synchronized ey-so-eya-dac-expressing cells ( retinal precursors ) [17 , 19 , 20] . The expression of ey , so and eya turns on the expression of the bHLH gene atonal ( ato ) , the fly homologue of ath5/atoh7 , which is necessary for the differentiation of precursor cells into photoreceptors , lens and pigment cells of the retina [23–26] . The information processing devices in networks such as the RD gene network are cis-regulatory elements ( CREs ) , DNA sequences that allow binding of specific combinations of transcription factors , which in turn regulate transcription of the CRE target genes [27] . Therefore , CREs are key to understand the logic that drives the developmental processes directed by a gene network . In the Drosophila RD gene network , CREs from ey [28 , 29] , so [30 , 31] , eya [32] , dac [33]; optix [34] and ato [24–26 , 35] have been isolated and studied in molecular detail . Not surprisingly , all rely on direct Pax6 input and at least so , dac and ato CREs also integrate direct regulation by the So:Eya complex [24–26 , 31 , 33] . But all of these genes are transcription factors , not effector genes . Is the logic acting upon transcription factors the same as that controlling specific outputs of the network’s function—such as cell cycle control ? In this paper we have addressed this issue by investigating the direct regulatory logic acting upon the eye-specific stg CRE . During Drosophila retina development , a transcriptional burst of stg is associated to the transition from proliferative progenitors to cell cycle quiescent precursors [19 , 20 , 22] . This peak of stg drives progenitors , which are mostly in the G2 phase of their cell cycle , through the FMW , leading to their G1 synchronization [19 , 36] . This synchronicity is essential: In stghwy mutants , which lack specifically this peak of stg expression , precursors are specified but do not become G1-synchronized . As a result , the patterning of the retina is aberrant [22] . Therefore , the study of stg transcriptional regulation in the eye offers an ideal model to understand how organ specific cell cycle and patterning programs are coupled during development . We identified a distal 5′stg CRE , which we named stg-FMW ( First Mitotic Wave ) enhancer . When stg expression was driven by stg-FMW enhancer , it rescued the eye defects of stghwy mutants , indicating that stg-FMW contains most , if not all the regulatory information required for the accurate spatial-temporal expression of stg at the progenitor-precursor transition . Within this element , we characterized two positive inputs: one from both Pax6 proteins , Ey and Toy , and one from So:Eya . Interaction with these transcription factors occurs through two binding sites . We also identified one negative input: Hth . In agreement , assays in vivo suggested that Hth hampers Ey activation of stg-FMW . This fact could explain mechanistically the negative action of Hth on stg transcription . The picture that emerges is of a coherent feed-forward loop in which Ey and Toy play partially redundant activating roles , together with So:Eya , on stg transcription . Moreover , this activation is modulated by the negative input of the meis1 gene , hth .
As an entry point into the molecular mechanisms by which selector transcription factors activate organ-specific programs of cell division , we searched for an eye specific regulatory element of stg . Lehman and co-workers had scanned 38 Kb of the stg locus ( from-35 to +3 relative to the transcription start site ) and uncovered several CREs [21 and Fig . 1A] . These included CREs active in embryos and imaginal discs , but none of the fragments studied recapitulated the strong stripe of stg expression anterior to the MF ( Fig . 1B ) . We re-analyzed a similar interval of 38 . 7 Kb ( from the stg transcription start site [Chr3R: 25 . 081 . 410] to CG14506 [Chr3R: 25 . 120 . 100] , the gene located immediately upstream of stg ) by generating a new set of tiled reporter transgenes with an average fragments length of 5 Kb . Contiguous fragments overlap each other an average length of 1 , 5 Kb ( Fig . 1A ) . This approach was selected to avoid splitting blocks of conserved sequence , as sequence conservation is often a landmark of CREs [37] . Again , none of the fragments from this interval revealed an expression pattern reminiscent of stg in the eye disc . Together with the Lehman study , our results suggested that the eye-specific CREs should be located further upstream [21] . To try to define the expected limit of the stg regulatory landscape we used several landmarks . First , the analysis of an extended genomic region revealed the existence of two class I insulator binding sites [38 , 39] , one immediately downstream of the stg transcript ( Chr3R: 25077239 ) and another downstream of Cnx99A ( Chr3R: 25138877 ) , delimiting a region of 61 , 6 Kb ( Fig . 1A ) . Binding of class I insulators helps to establish chromatin boundaries between genes [39 , 40] . Therefore , we considered that this region might comprise the stg regulatory landscape and should include unidentified stg CREs . This interval includes CG14506 as well . However , this transcript is not conserved in all Drosophila species sequenced , although the adjacent sequences are highly conserved , suggesting that CG14506 is a bystander gene within the stg locus . Second , a regulatory mutation in the stg gene , highway ( stghwy ) , had been shown to be associated to an insertion of an uncharacterized DNA sequence at around 30 Kb upstream of the stg transcription start site . The stghwy is a viable allele that results in slightly reduced , roughened eyes [22] . In stghwy mutant eye discs the peak of stg expression at the progenitor-precursor transition is lost ( Fig . 1B , C ) . As a consequence , cells fail to undergo G1 arrest , and accumulate in G2 , with high levels of mitotic cyclins , such as cyclin B [Fig . 1G , H and 22] . Since stghwy is an eye-specific regulatory allele of stg , we reasoned that the stghwy insertion might be affecting the CRE we were looking after , perhaps having landed in its vicinity . A primer walking strategy was next employed to identify the nature of the DNA element and the exact insertion point in stghwy . Molecularly , we defined the mutation associated with stghwy as an insertion of a gypsy transposable element between positions Chr3R: 25115094 and Chr3R: 25115097 ( Fig . 1A and S1A Fig . ) . Gypsy transposable elements are known to block enhancer-promoter interactions when located in between them [reviewed in 41] . This finding suggested that the insertion in stghwy was likely impairing the contacts between the eye-specific CRE and the stg promoter . Further , it predicted that the eye CREs should lie between the genes CG14506 and Cnx99A . When we extended our reporter transgene study to this region , we identified a fragment of 4 . 8 Kb , located distal to CG14506 and 52 Kb away from the stg promoter . This fragment was sufficient to drive expression of the reporter gene ( destabilized Green Fluorescent Protein , ( dGFP ) ) in eye discs , both in a stripe anterior to the MF as well as in cells posterior to it ( Fig . 1A and S1B Fig . ) . In addition , this fragment showed enhancer activity in the dorsal anterior region of the eye disc , where the prospective ocellar region resides , and in the lamina region of the optic lobes . We named it stg-VisualSystem ( stg-VS ) . We next subdivided stg-VS into smaller overlapping fragments . This allowed the identification of two enhancer elements , of 539bp and 690bp respectively , that drive expression in different cell populations of the eye disc ( Fig . 1A , D , E ) . The remaining sub-fragments of stg-VS failed to drive expression in the visual system or elsewhere . The 539bp enhancer drives strong dGFP expression in the FMW domain and precursor cells and recapitulates stg expression in the eye field after differentiation onset ( S2 Fig . ) . Accordingly , the 539bp enhancer was called stg-First Mitotic Wave ( stg-FMW ) ( Fig . 1D ) . The 690bp element drives expression in the ocellar domain , and in a subset of cells posterior to the MF . This fragment was named stg-EyeOcelli ( stg-EO ) ( Fig . 1E ) . stg-FMW and stg-EO are expressed in adjacent , non-overlapping domains ( Fig . 1F , F’ ) and together reconstitute the eye disc-specific pattern of stg transcription . Anteriorly , expression driven by stg-FMW abuts the Hth expression domain ( Fig . 1F , F’ ) , as was previously shown for stg mRNA [19] . Expression of stg-EO in the eye field overlaps the so-called second mitotic wave [SMW , 42] . To test that stg-FMW is a functional stg enhancer , we attempted to rescue the stghwy phenotype , by driving stg expression using a stg-FMW-GAL4 driver in stghwy homozygous individuals . stg-FMW-GAL4>UAS-stg rescued the adult eye phenotype and the pattern of cyclin B accumulation in L3 eye discs of stghwy mutants ( Fig . 1G-I ) . This result supports the idea that stg-FMW is a functional , eye-specific stg CRE and , together with the data on enhancer activity throughout the stg locus , suggests that it may be the sole CRE responsible for stg expression at the FMW . The stg-FMW sequence shows a high degree of conservation ( Fig . 2A ) . Using JASPAR and TRANSFAC models [43 , 44] we predicted the existence of putative transcription factor binding sites for components of the RD network . For the identification of Ey binding sites we generated our own position weight matrix from a set of published binding sites [24 , 30 , 34 , 45] ( Fig . 2B and S3 Fig . ) . Evolutionarily conserved Ey binding sites in the genome of 12 Drosophila species were filtered using the CBS platform [46] . Two highly conserved regions were identified , which we refer to as Binding Site 1 ( BS1 ) and BS2 ( Fig . 2A , C ) . BS1 contains partially overlapping putative binding sites for Ey/Pax6 and So ( Fig . 2C ) . BS2 contains one Ey/Pax6 conserved binding site , and a highly conserved consensus site for Hth lies adjacent to it ( Fig . 2A , C ) . To test the in vivo relevance of BS1 and BS2 , we mutated the bases fitting the Ey/Pax6 consensus at each site . Transgenic lines carrying mutant versions of the stg-FMW enhancer harboring mutations in BS1 ( stg*BS1 ) , in BS2 ( stg*BS2 ) or in both sites ( stg *BS1+*BS2 ) were analyzed ( Fig . 2D-G ) . Neither the stg*BS1 nor the stg*BS2 single mutants showed altered temporal or spatial expression ( Fig . 2E , F ) , suggesting that the remaining site suffices for enhancer activity during eye development . However , when the two sites were simultaneously mutated ( stg*BS1+*BS2 ) , enhancer activity was lost ( Fig . 2G ) . This shows that both sites are redundant for enhancer activity in vivo . Since mutation of both Ey/Pax6 consensus-binding sites abolished enhancer activity , we next assayed whether Ey was required for stg-FMW activity . The expression of stg-FMW remains unaffected in clones where ey expression has been knocked-down using RNAi ( Fig . 2H ) . As toy , a second Pax6 gene , is expressed coextensively with ey in the eye primordium [16] , we tested if Toy was required for regulation of stg-FMW . As observed with ey , toy downregulation through RNAi did not affect enhancer activity ( Fig . 2I ) . Since Ey and Toy have similar expression patterns and binding site preferences [16 , 31 , 47] , we next tested a potential redundant function of Ey and Toy in stg-FMW regulation . For this , we generated clones of cells in which both genes were simultaneously knocked-down by co-expression of ey-RNAi and toy-RNAi . In these cells the activity of stg-FMW was abolished in a cell-autonomous way ( Fig . 2J ) . This result shows that both Ey and Toy redundantly activate the stg-FMW enhancer . A redundant function between Ey and Toy was further supported by the finding that in ey2 homozygous imaginal discs , where toy expression is maintained [16] , the pattern and levels of expression of stg mRNA or stg-FMW were not affected ( S4A-G Fig . ) . To explore a potential “division of labor” between the two sites , with each of them specializing in only one of the two Pax6 , we generated clones of ey-RNAi and toy-RNAi in the presence of stg-FMW mutated versions ( stg*BS1 and stg*BS2 ) ( S4H-K Fig . ) Upon mutation of BS1 or BS2 , downregulation of Ey did not abolish enhancer activity ( S4F , G Fig . ) . Downregulation of Toy did not impact on the activity of the single-mutant versions of stg-FMW either ( S4J , K Fig . ) . These results show that one Ey/Pax6 binding site suffices for enhancer activity , and that Ey and Toy do not have preferential binding in vivo . Region BS1 also contains a putative binding site for So ( Fig . 2C ) . So is known to physically interact with the transcriptional co-activator Eya to regulate downstream genes [48] . We next tested the role of So and its transcriptional co-activator Eya in the regulation of stg-FMW . Both genes lay downstream of Ey in the RD gene network [reviewed in 14 , 49] and stg has been previously identified as a transcriptional target of the Eya:So complex [50] . Loss of function of Eya ( S5A Fig . ) or its downregulation by means of RNAi ( Fig . 3A ) in cell clones resulted in a cell-autonomous loss of enhancer activity in the precursor domain . A similar result was obtained when So expression was knocked down using RNAi ( S5B Fig . ) . This loss of enhancer activity coincided with the maintenance of high levels of Hth expression ( Fig . 3A” and S5B Fig . ) . We had previously shown that Hth could act as a repressor of stg transcription [19] . Additionally , Eya:So are negative regulators of Hth expression during eye development [17] . Therefore , the observed loss of stg-FMW enhancer activity could result from either the loss of Hth repression , or alternatively reflect a positive requirement of Eya:So for stg-FMW activation . To discriminate between these two hypotheses , we first checked whether ectopic expression of Hth could repress stg-FMW . In Hth-expressing clones stg-FMW activation was delayed , but not repressed ( Fig . 4A ) . These findings were qualitatively different from the ones obtained upon RNAi-mediated eya knock-down , where loss of enhancer activity was always observed , irrespective of the position of the clones within the precursor cell domain . This suggested that indeed Eya:So acted as stg-FMW activators . To test this issue avoiding any interference by Hth , we generated clones of cells simultaneously mutant for eya ( eya null ) and hth ( hth RNAi ) , using the MARCM system ( Fig . 3B ) [51] . In eya- hth- cells , stg-FMW activity was always lost in a cell-autonomous manner . However , in these eya- hth- double mutant cells expression of Ey was maintained ( S5C Fig . ) . Therefore , these results show that Eya:So are required as stg-FMW activators independently of their role as hth transcriptional repressors . Since the RD nuclear protein Dac has also been found as part of the Eya/So complex [52] we tested if Dac also played a role in stg transcriptional regulation . In clones of a dac-null allele ( dac3 ) the expression of stg-FMW remained unaltered ( S5D Fig . ) , indicating that Dac is not a partner of Eya:So in the regulation of stg-FMW enhancer . This finding further indicates that different Eya:So targets may rely on the formation of different protein complexes . Previous results suggested that Hth was a transcriptional repressor of stg [19] . However , as we described before , ectopic expression of Hth delayed the onset of stg-FMW activation , but did not block it ( Fig . 4A ) , suggesting that hth could be involved in the precise timing of stg-FMW expression rather than in repressing it . To test this idea , we generated hth-mutant clones of a strong allele ( hthP2 ) [53] . Since hth-clones grow poorly [18 , 19 , 54] , we gave them a growth advantage by using the Minute technique [55] . In hth- M+ clones the anterior border of stg-FMW expression was shifted anteriorly ( Fig . 4B ) . Therefore hth is required for the precise spatio-temporal activation of stg-FMW , delaying its initiation . Hth is a transcription factor and its action could be mediated through direct interaction with the stg-FMW enhancer . In fact , we identified a potential Hth BS in the stg-FMW sequence ( Fig . 2C ) . However , mutation of this site ( stg*hth ) did not result in changes in stg-FMW expression ( Fig . 4C and S6C Fig . ) . Although this result does not rule out a direct Hth-DNA interaction through a non-canonical site on the stg-FMW enhancer , it points to an indirect effect . In fact , it has been previously shown that Hth and Ey can form a protein complex in vivo [17] . The possibility that Hth affects stg-FMW through Ey is explored below . Our results show that during eye development Ey/ Toy and So plus Eya are all necessary to activate stg-FMW , although in the eye neither the Pax6 genes Ey/Toy or Eya/So are sufficient to do so . Molecularly , mutational analysis of the Pax6 binding sites suggested that Ey and Toy could exert their function through direct binding to BS1 and BS2 . To test this hypothesis directly and grasp the molecular interactions underlying stg-FMW activity , we performed chromatin immunoprecipitation followed by quantitative real-time PCR ( ChIP-qPCR ) experiments . We used ectopic gene expression in wing discs as they can be used as a “blank slate” where to assess the functional consequences of expressing RD genes , including Ey . In addition , since in the wing disc Hth expression is restricted to the hinge , we bypass the potential repressor effect of Hth on Ey activity in most of the disc . To drive gene expression we used the dpp-GAL4 line , which is expressed in a stripe that bisects the wing disc along its anterior-posterior ( A/P ) axis ( Fig . 5A ) . dpp-GAL4-driven Ey expression ( dpp>ey ) was sufficient to promote activation of the enhancer throughout the Dpp expression domain ( Fig . 5B and S7 Fig . ) , in agreement with the potent eye-inducing ability of Ey [56 , 57] . In contrast , Toy was only able to induce expression from stg-FMW in a small subset of cells in the ventral hinge region ( Fig . 5C ) . This suggests that although in the eye imaginal disc both Ey and Toy have the ability to promote enhancer activity , Ey is a stronger regulator of stg-FMW than Toy . We next analyzed the in vivo binding of Ey to stg-FMW by ChIP-qPCR in dpp>ey wing discs . We designed primers so that we could detect binding to region 1 ( stg-BS1 ) or region 2 ( stg-BS2 ) . As positive control we used a region in the ato-3′ enhancer known to be bound by Ey [24] ( Fig . 5I ) . As expected , we detected a high enrichment of Ey at ato-3’ relative to our negative control ( Fig . 5I ) . ChIP-qPCR analysis showed that Ey binds to both BS1 and BS2 , reinforcing the results described above showing that both sites are used in vivo . We consistently recovered higher amounts of chromatin from BS2 than from BS1 , suggesting that Ey’s binding affinity towards BS2 region is higher ( Fig . 5I ) , and that this site might be preferentially used by Ey in vivo . Our previous experiments showed a requirement for the Eya:So complex in stg-FMW activation , and identified a putative So binding site on region BS1 . Ectopic assays in the wing showed that co-expression of Eya and So ( dpp>Eya , So ) was able to activate the enhancer in a subset of hinge cells located along the A/P boundary ( Fig . 5D and S7 Fig . ) . However , ectopic expression of So , alone or together with Dac , was not sufficient to activate stg-FMW . This observation supports the existence of an Eya:So complex within the precursor domain , whose targets are distinct and independent of the Dac:Eya:So complex . Eya and So can act as transcriptional regulators of Ey [29 , 49] and it could be argued that the observed stg-FMW activity might be indirect and due to Ey up-regulation . To test this point , we checked if ectopic expression of Eya:So in the Dpp domain induced Ey expression . Although ectopic Ey expression was easily detected in the antennal imaginal disc , we systematically failed to detect Ey expression in the wing or leg imaginal discs of dpp>Eya , So larvae ( S7D , G Fig . ) . These results are in agreement with previous observations [16 , 48 , 58] . Nevertheless , and to rule out the possibility that undetectable levels of Ey might contribute to the activation of stg-FMW upon ectopic Eya:So expression ( Fig . 5D ) , we used an RNAi to knock ey expression down when co-expressing Eya and So ( dpp>eyRNAi , Eya , So; Fig . 5E ) . In these conditions , ectopic stg-FMW was induced in the same subset of cells as when induced by Eya and So alone ( Fig . 5D , E ) . This shows that , in ectopic assays , the Eya:So complex has the capacity to promote transcription from the enhancer independently of Ey . This finding allowed us to test if BS1 , which contains a putative So binding site , was indeed required for the activation of stg-FMW by Eya+So . In case this hypothesis were true , mutation of BS1 should preclude stg-FMW activation . To test this point , we checked Eya:So’s ability to activate the enhancer upon mutation of BS1 or BS2 , when Ey expression was simultaneously attenuated ( dpp>eyRNAi , Eya , So ) . In this background , mutation of BS1 ( stg*BS1 ) prevented Eya+So from activating the enhancer ( Fig . 5F ) . In contrast , when stg*BS2 was used , the pattern and expression levels of the reporter gene upon Eya+So expression were similar to those of wild-type stg-FMW ( Fig . 5G ) . These results suggest that Eya:So complex most likely regulates stg-FMW activity through binding to stg-BS1 . To test this hypothesis we performed ChIP-qPCR experiments using an HA-tagged Eya protein ( Eya:HA ) . As Eya lacks a DNA binding domain , its association with DNA would only occur if forming a complex with its DNA-binding partner So [59] . Thus , Eya ChIP can be used as a read-out of Eya:So target DNA binding . In dpp>Eya:HA wing discs , anti-HA ChIP-qPCR showed enrichment of stg-BS1 and stg-BS2 , although only that for BS2 was statistically significant . ato-3’ , which was again used as positive control , showed also a significant enrichment , as so did the banA enhancer ( also included as control; see below ) , although to a lower extent ( S7H Fig . ) . Taken together , our results show that the Eya:So complex is able to bind BS2 ( and likely also BS1 ) . However , Eya:So regulation of stg-FMW relies mostly on BS1 . In addition to the positive regulators Toy , Ey , Eya and So , our experiments indicate that Hth contributes to the precision of the onset of stg-FMW expression , delaying its activation . The fact that a mutation that eliminates the single canonical Hth binding site does not affect the enhancer’s expression suggested that Hth’s action could be indirect , perhaps mediated through its known interaction with Ey [17] . To test this point , we evaluated the ability of Ey to activate stg-FMW in the presence of ectopic Hth ( Fig . 5H ) . In the wing imaginal disc , ectopic expression of Hth strongly reduces the ability of Ey to activate transcription of the reporter gene , which can only be detected in spots in hinge cells ( compare Fig . 5H with 5B ) . To address if Hth counteracts Ey positive role on stg transcription by preventing Ey’s binding to chromatin , we performed ChIP-qPCR assays in wing discs upon simultaneous expression of an HA-tagged Ey plus Hth ( dpp>HA:Ey , Hth ) ( Fig . 5I , red bars ) . The amount of Ey bound to chromatin regions stg-BS1 and stg-BS2 in dpp>HA:Ey , Hth was slightly reduced compared to dpp>HA:Ey ( Fig . 5I , blue bars ) . A stronger reduction was observed for ato-3′ , the activity of which is known to be directly regulated by Ey binding [24 , 25] . These results show that Hth only moderately hampers Ey binding to its target DNA sites , something that could be happening through a direct Hth:Ey interaction . Additionally , we noted that banA , a CRE from the bantam gene , a known direct Hth target in the eye is also bound by Ey ( Fig . 5I ) [18] . In contrast to stg and ato sequences , we observe a 2-fold enrichment of the banA sequence upon ectopic co-expression of Hth and Ey . This is in agreement with the known binding of Hth to banA and likely reflects the previously described ability of Hth to interact with Ey [17 , 18] .
Selector genes lie atop organ-specific gene regulatory networks ( GRNs ) , but it is still unclear what is the depth of their connectivity—i . e . whether selectors regulate a first layer of transcription factors that then relay their information , through consecutive layers down onto specific effector genes ( those that determine the actual properties of the cells ) , or if they regulate the expression at all levels of those GRNs , connecting both to transcription factors and effector genes . This control , in any case , is established by their binding to specific CREs and still , in most organogenetic processes , our knowledge of the molecular logic used by selector genes in GRNs to control gene expression is fragmentary . The Drosophila RD gene network is a good example of this . Despite the vast knowledge of its main components and their contribution to eye development , there is not much evidence about the molecular mechanisms that underlie their function . In particular , how interactions among the different RD gene network components take place and contribute to retina development , by acting not only on other components of the network ( all transcription factors or nuclear co-factors ) but also on effector genes . In this study we have addressed this question by investigating the mechanisms that regulate stg transcription in the developing eye . stg codes for the universal phosphatase that triggers the G2-M transition [60] . Upregulation of stg expression during L3 is essential for the synchronous exit from mitosis of retinal progenitors , while simultaneously ensures their amplification at the FMW in order to produce a sufficient number of retinal precursors . It therefore works as an effector gene during the progenitor-precursor cell state transition . We identified the eye-specific stg CRE and showed that it contains two conserved Pax6 binding sites . Drosophila has two Pax6 paralogues , toy and ey [16] . The expression of toy starts during early embryogenesis and is required for the activation of ey transcription in the eye primordium during late embryogenesis . During larval development , both toy and ey are coexpressed in the undifferentiated cells of the developing eye primordium [16] . However , while loss of ey function during larval stages results in smaller or absent eyes [61 , 62] , no function in the eye had been attributed to the larval expression of toy . Here we show that both ey and toy act as positive regulators of the stg-FMW CRE , and that in the absence of ey , toy suffices to maintain stg-FMW CRE activity . However , ectopic experiments in the wing show that their activating capacity differs , with Ey proving to be a more efficient activator of stg CRE than Toy . This is consistent with a less powerful eye-inducing ability of Toy compared to Ey [16 , 56 , 57] . The discrepancy between the functional equivalence of Ey and Toy in the eye and their different eye-inducing ability in ectopic assays could be explained if Ey expression could facilitate the accessibility of Toy to ( at least some ) Ey targets . This would happen in the eye ( where toy activates ey very early in the development of the eye primordium ) but not in the wing , where none of the two Pax6 genes are normally expressed . Our work shows that Ey is able to bind both BS1 and BS2 , but shows higher affinity towards BS2 in vivo ( Fig . 5I ) , suggesting that this site might play a key role in the enhancer activity . In agreement , we found that mutation of BS2 , although not affecting stg-FMW pattern , causes a significant reduction in its expression levels ( S6 Fig . ) . On the other hand , the transcriptional complex Eya:So is able to bind to BS1 and BS2 with similar affinities , but genetic analysis suggests that interaction with BS1 is critical for stg-FMW activity ( Fig . 5E-G ) . However , while this analysis derives from wing disc assays , the mechanism of action in the eye disc might be more complex . While in the wing disc Ey shows a superior stg-FMW induction , in the eye removing Eya:So results in loss of enhancer’s activity , despite the fact that Ey and Toy expression remain . This suggests a model in which Toy/Ey and Eya:So cooperate to activate stg-FMW enhancer . A similar cooperation between Ey and So has been recently described for the activation of ato CREs [24 , 25] , which are also active anterior to the MF with a pattern similar to that of stg-FMW [24–26] . The picture that emerges is that of a feed-forward loop , in which Pax6 genes activate Eya and So expression and then Pax6 and Eya:So control stg-FMW through direct binding . The engagement of Ey/Pax6 and Eya:So in a positive feed-forward loop has also been reported for the activation of dac , even though in this case two separate enhancer elements are involved [33] . Therefore , a similar gene regulatory motif involving Ey and Eya:So operates to control the expression of transcription factors and stg , this latter an effector gene . This may be a general feature of the gene networks where Pax6 proteins participate . For example , during the development of the vertebrate eye lens , Pax6 and c-Maf are similarly engaged in a positive feed-forward loop to activate the expression of crystallin genes [63] . This suggests that synergistic interactions among transcription factors within the same GRN determine the specificity of their recruitment to cell type-specific CREs . A key step towards the activation of stg-FMW is the repression of Hth , which is mediated by Dpp and Hh [19] . Hth interferes with the coherent feed-forward loop formed by Ey and Eya:So ( Fig . 6 ) at two points: First , Hth moderately hampers Ey binding to stg-CRE , something that could contribute to the temporal shifts that this enhancer suffers upon manipulating hth function ( this work ) . This could happen through a direct Hth-Ey physical interaction [17] . And second , Hth also acts as a transcriptional repressor of Eya [17] . The resulting GRN allows integration of extracellular signals with tissue specification resulting in a short pulse of stg transcription as soon as MF-produced Dpp represses Hth . This pulse is thus made coincidental with the transition from progenitors into precursors ( Fig . 6 ) . The need of both Ey and Eya/So inputs for the enhancer’s activation acts as a molecular coincidence detector that ensures that the enhancer will only be active when the regulatory state of the cell is “correct” , avoiding spurious stg activation . Our results also point to a role for hth regulation as a precision mechanism , acting to guarantee a sudden , rather than gradual , activation of stg . It is through hth regulation that the system integrates the extracellular cues with the activity of the selector genes . This mechanism ensures coupling of growth with tissue specification . That hth and its vertebrate homologues may play a similar role in Ey/Pax6-regulated processes than the one we have described for stg CRE is a tantalizing hypothesis that needs to be investigated . Interestingly , loss of function of Hth does not suffice for enhancer activation in all cells of the anterior domain ( Fig . 4 ) . This seems to indicate that additional factors or signaling inputs contribute to stg-FMW activation . Dpp and Hh signaling are the obvious candidates . However , ectopic activation of either pathway does not change stg-FMW activity in progenitor cells ( S8 Fig . ) Altogether our data suggests the existence of still unknown anterior factors/signaling inputs that contribute to the regulation of stg-FMW expression onset . The role of Pax6 genes in cancer development appears to be linked with their function during organ development . They act as oncogenes in organs where their expression correlates with the maintenance of the progenitor state , as is the case of the retina and pancreas [reviewed in 2] . In both organs , the maintenance of Pax6 expression during adult stages associates with a failure to undergo differentiation and to tumor development . In contrast , cdc25 is commonly up-regulated in tumors , as expected from a mitotic gene , but this up-regulation is not tumor type-specific [60] . Our results raise the possibility that Pax6 genes may regulate cell cycle genes in collaboration with Eya/Six proteins also during vertebrate organogenesis , something that might be linked with their oncogenic potential .
The following fly stocks were used: w1118 , stghwy [22] , w; FRT82BhthP2/TM6B [64] , w; dac3 FRT40A/ CyO [65] , w; eyaE8 FRT40 [66 , 67] , UAS-Toy [16] , UAS-eya , UAS-so [24] , UAS-so , UAS-dac ( kindly provided by F . Pignoni ) , UAS-soRNAi ( VDRC 8950 ) ; UAS-eyaRNAi ( VDRC 43911 ) ; UAS-hthRNAi ( VDRC 12764 ) ; UAS-eyRNAi ( VDRC 42845 ) and UAS-toyRNAi ( VDRC 15919 ) , ey2 ( Bloomington Stock Center ) [61] . Standard genetic techniques were used to introduce stg-FMW reporters in the different genetic backgrounds . All crosses were kept at 25°C unless otherwise stated . Cells mutant for hthP2 were recovered using the Minute technique [55] . The fly strain yw , hsFLP; FRT82BhsCD2 , y+M/TM2 was used . Mutant tissue was identified by the absence of CD2 staining . Clones were induced between 24 and 48 h or 48 and 72 h after egg laying ( AEL ) by a 45′ heat-shock ( hs ) at 37°C . The Flip-Out method [68] was used to induce gain of function clones . The line yw , hsFLP , act>hsCD2>Gal4 was used . Clones were generated at 36–60 h AEL , by a 20′ hs at 35 . 5°C . Flies were kept at 25°C , except when UAS-RNAi lines were used , in which case they were transferred to 29°C after hs . Dpp-Gal4/TM6B ( FBti0002123 ) and Dpp-Gal4 , UAS-GFP/ MKRS ( kindly provided by M . Dominguez ) were used to ectopically express RD genes in the wing imaginal disc . The FlyC31 system was used to generate all transgenic lines used in this study . Transgenes were inserted in either 2L ( 22A ) or 3R ( 86FA ) attP sites [69] . Insertions on either landing site yielded similar results . Two reporter vectors were used for assaying enhancer activity: pRVV54 that uses nuclear lacZ as reporter [70] , and pBPUwdGFP which uses destabilized GFP as reporter [71] . stg-FMW was cloned into pBPGUw [72] vector to generate stgFMW-Gal4 line . Overlapping DNA fragments , covering >60 Kb of stg locus were amplified by PCR and introduced into either pBPUwdGFP or pRVV54 using the Gateway System . Mutant versions of stg-FMW were cloned into pBPUwdGFP and inserted in 2L ( 22A ) and 3R ( 86A ) sites , as wild-type versions of the enhancer . The megaprimer method was used to generate mutations on putative Ey and Hth binding sites [73] . Primers delimiting stg-FMW enhancer sequence and used for enhancer mutagenesis are listed in S1 Table . Imaginal discs were dissected and fixed according to standard protocols . Primary antibodies used were guinea-pig anti-Hth [74] , rabbit anti-PH3 ( Sigma ) , rabbit anti β-galactosidase ( Cappel ) , mouse anti β-galactosidase ( Sigma ) , mouse anti-CD2 ( Serotec ) , rabbit anti-GFP ( Molecular Probes ) , mouse anti-Ey ( Clements et al . , 2008 ) and rabbit anti-cyclin B [75] . Mouse anti-Eya , rat anti-ELAV ( 7E8A10 ) , and mouse anti-cyclin B were from Developmental Studies Hybridoma Bank ( Iowa University ) . Fluorescently labeled secondary antibodies were from Molecular Probes . Anti-mouse-HRP ( Sigma ) was used for immunoperoxidase staining . Digoxigenin labelled stg RNA probe was produced from cDNA clone LD47579 ( BDGP ) . ImageJ was used to quantify pixel intensities ( http://imagej . nih . gov/ij/ ) . A PCR based approach was used to map and characterize , at the molecular level , the nature of stghwy allele . Several primer combinations spanning the genomic region Chr3R: 25 . 081 . 410 to Chr3R: 25 . 141 . 369 ( Drosophila Genome Release 5 ) were used to amplify fragments of approximately 5 Kb of DNA from control ( w1118 ) and stghwy flies . An insertion was detected between genomic coordinates Chr3R: 25114731 and ChR3R: 25115810 . Primers flanking and within this region were employed to amplify and sequence stghwy DNA . Wing imaginal discs from wandering L3 larvae of the following genotypes , dpp>Ey-HA , GFP; dpp> Ey-HA , Hth-GFP and dpp> Eya:HA , GFP were used for Chip-qPCR analysis . Chromatin was prepared essentially as described in Estella et al . [76] . 30 μg of soluble chromatin , with a size average of 200 bp , was incubated with 3 μg of rabbit anti-HA antibody ( AbCam ) . Ey:HA and Eya:HA bound chromatin complexes were pulled down with protein G magnetic beads ( Invitrogen ) according to Sandmann et al . [77] . Chromatin was eluted with 100 mM NaHCO3 . To reverse crosslinking , samples were incubated overnight at 65°C after the addition of 160 mM NaCl . DNA was purified via phenol-chloroform extraction and ethanol precipitation . The PCRs were performed on 1:50 dilutions of the ChIP and input samples . Primers were designed to specifically amplify regions BS1 and BS2 , which are 100 bps apart . Primers on ato-3’ enhancer were used as positive control [24] . Primers used are described in S1 Table .
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Organs develop from groups of undifferentiated cells that proliferate and differentiate into specific cell types . During development , the coupling between proliferation and differentiation programs ensures that enough cells of the different cell types are generated . This is critical for proper organ formation and function . Here , we use the developing Drosophila eye to examine how the coupling between these two programs is achieved . During eye development , progenitors are amplified before they exit the cell cycle and enter the differentiation program . This amplification step depends on an expression burst of the mitotic trigger string/cdc25 , which , by forcing cells into mitosis , synchronizes cells in G1 just before differentiation onset . Thus string regulation acts as a hub where differentiation and proliferation programs are integrated . We identify a DNA element that controls the burst of string expression prior to differentiation , and show that it is regulated by the same gene network that triggers eye development . The transcription factor Pax6/Eyeless is a key regulator in this network . Eyeless acts cooperatively with Sine oculis and Eyes absent to regulate string , through a positive feed-forward loop . This loop is negatively modulated by the progenitor-specific transcription factor Homothorax/Meis1 . This work shows that transcription factors that instruct cells to acquire an eye fate also control their proliferation regime , thus guaranteeing the coupling between proliferation and differentiation .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[] |
2015
|
Eye Selector Logic for a Coordinated Cell Cycle Exit
|
The Janus Kinase 2 ( JAK2 ) plays essential roles in transmitting signals from multiple cytokine receptors , and constitutive activation of JAK2 results in hematopoietic disorders and oncogenesis . JAK2 kinase activity is negatively regulated by its pseudokinase domain ( JH2 ) , where the gain-of-function mutation V617F that causes myeloproliferative neoplasms resides . In the absence of a crystal structure of full-length JAK2 , how JH2 inhibits the kinase domain ( JH1 ) , and how V617F hyperactivates JAK2 remain elusive . We modeled the JAK2 JH1–JH2 complex structure using a novel informatics-guided protein-protein docking strategy . A detailed JAK2 JH2-mediated auto-inhibition mechanism is proposed , where JH2 traps the activation loop of JH1 in an inactive conformation and blocks the movement of kinase αC helix through critical hydrophobic contacts and extensive electrostatic interactions . These stabilizing interactions are less favorable in JAK2-V617F . Notably , several predicted binding interfacial residues in JH2 were confirmed to hyperactivate JAK2 kinase activity in site-directed mutagenesis and BaF3/EpoR cell transformation studies . Although there may exist other JH2-mediated mechanisms to control JH1 , our JH1–JH2 structural model represents a verifiable working hypothesis for further experimental studies to elucidate the role of JH2 in regulating JAK2 in both normal and pathological settings .
Janus tyrosine kinase 2 ( JAK2 ) belongs to the JAK family of intracellular non-receptor tyrosine kinases , which mediates signaling from a plethora of cytokine receptors [1] . Like other JAK members , JAK2 is kept inactive in the basal state . Dimerization/oligomerization of cytokine receptors upon cytokine engagement triggers trans-phosphorylation of JAK2 proteins bound to the receptor cytosolic domain , activating JAK2 kinase activity . Activated JAK2 in turn phosphorylates the cytokine receptor cytoplasmic domains to create sites of interaction for downstream signaling molecules such as the STAT ( signal transduction and transcription ) family of transcription factors . Constitutive activation of JAK2 either by chromosomal translocation or by gain-of-function mutations results in hematological malignancies including leukemias and myeloproliferative neoplasms ( MPN ) [2]–[5] . Constitutive activation of the JAK2/STAT3 pathway was also shown to be essential for the growth of human solid tumor xenografts [6] . As a consequence , JAK2 has emerged as a promising target for anti-cancer therapy . However , mechanisms underlying how JAK2 kinase activity is kept off in the basal state and turned on under normal or pathological conditions are not fully understood . Strong evidence suggests that the C-terminal kinase domain ( JH1 , standing for JAK homology domain 1 ) of JAK2 is allosterically regulated by other JAK2 domains , namely a N-terminal FERM ( band 4 . 1 , ezrin , radixin , moesin ) domain which associates with cytokine receptors , a Src homology-2 ( SH2 ) domain whose function remains unclear , and a pseudokinase domain ( JH2 , standing for JAK homology domain 2 ) ( Figure 1 ) . JH2 , originally thought of as a “pseudo kinase” that has a kinase fold but is devoid of kinase activity , plays particularly important roles in regulating JAK2 kinase activity . First , JH2 is essential to inhibit JH1 in the basal state . JH2 can bind to and inhibit JH1 in trans , and deletion of JH2 increases basal JAK2 kinase activity [7]–[9] . Recent studies also demonstrated that JH2 actually possesses low catalytic activity and autophosphorylates two negative regulatory sites in the SH2-JH2 domain linker and in JH2 to maintain basal auto-inhibition [10] . Functional importance of JH2-mediated auto-inhibition is underscored by the existence of a hyperactivating JAK2 mutation therein in MPN patients . This hyperactivating mutation , V617F , is found in almost all MPN patients with polycythemia vera and is sufficient to cause a similar disease in mice [11] , [12] . The V617F mutation is also frequently found in essential thrombocythemia and primary myelofibrosis , two other kinds of MPN . Second , we and others have shown that JH2 also positively regulates JAK2 kinase activity as it is essential for cytokine-induced JAK2 activation . Deletion or mutations in JH2 resulted in JAK2 variants that showed elevated basal activity but cannot be further stimulated by cytokine , and that the elevated activity is below that of cytokine-stimulated wild-type JAK2 ( JAK2-WT ) [8] , [12] . In addition , we showed that the JAK2-V617F mutant has a lower Km for substrates compared to JAK2-WT , indicating that JH2 can also promote substrate binding to JH1 [13] . Understanding the exact molecular mechanisms underlying how JH2 both positively and negatively regulates JH1 calls for a structure of the full-length JAK2 . Unfortunately , despite many years of efforts in the field , such a structure is not yet available . Computational modeling thus represents an important technique in bridging the gap to explore the relationship between structure and function . The two hypotheses that JH2 negatively regulates JAK2 kinase activity , either by binding and inhibiting JH1 directly or via the two negative regulatory phosphorylation sites , are not mutually exclusive . In addition , the latter hypothesis may be more complex to involve other JAK2 domains . We thus chose to start our interrogation of JH2-mediated regulation of JAK2 kinase activity from modeling the JH1–JH2 complex . As both JH1 and JH2 adopt a kinase fold , one practical strategy is to model the JH1–JH2 complex using dimeric kinase forms indicated by crystal structures of kinase complexes or by assembly derived from crystal packing [14] . For EGFR [15] and PKR [16] , [17] , the dimeric unit implicated by crystal packing helped to reveal novel dimerization and activation mechanisms . A structure model of JAK2 , based on the dimeric form of FGFR1 kinase implicated by crystal packing [18] , was built by Kroemer and coworkers [19] , [20] . In this model , two interfaces between JH1 and JH2 were proposed: one dominated by interactions between the two paralleled αC helices , and the other between the JH1 activation loop and a loop in JH2 that includes V617 . The V617F mutation was proposed to destabilize the latter interface to relieve auto-inhibition [21] . Subsequently , Lee and coworkers performed molecular dynamics ( MD ) simulations on this model to explore the hypothesized conformational changes at the atomic level and found a strong π-π stacking interaction between V617F and F595 [22] . The importance of this interaction in the ability of V617F to constitutively activate JAK2 was later validated experimentally [23] , [24] . Protein kinases adopt at least two distinct conformational states: a structurally-conserved “on” state that is active and a less-structurally-conserved “off” state that has minimal activity [25] . The plethora of kinase crystal structures to date have provided a structural basis for kinase regulatory mechanisms , where conformational changes in the αC helix and in the activation loop are the common features [25] . For example , the fibroblast growth factor receptor 2 ( FGFR2 ) has an autoinhibitory “molecular brake” involving movements of the activation loop , the αC helix and the kinase hinge region [26] . The autoinhibitory domain of AMP-activated protein kinase ( AMPK ) constrains the mobility of αC helix and results in much lower kinase activity [27] . In Kroemer's model , both JH1 and JH2 domains were built in an inactive conformation . In addition , this model was minimally refined , and conformational stability was not evaluated . In light of recent findings that the JAK2 JH2 domain actually possesses kinase activity and phosphorylates two negative regulatory sites , a revised model is warranted . We thus developed a novel step-wise computational strategy to build a new model ab initio , with JH2 in an active conformation and JH1 in an inactive conformation . In this paper we describe a hierarchical protein-protein docking and refinement protocol ( Figure 2 ) and report the most energetically favorable and structurally stable model of the JAK2 JH1–JH2 complex . In our model , JH2 stabilizes the inactive conformation of JH1 through extensive hydrophobic contacts and electrostatic interactions . Importantly , we experimentally assessed and validated critical interfacial residues predicted from our model , which would not have been envisioned from previous models . Although we cannot rule out the possibility that dimerization and autophosphorylation of JH2 might be the predominant mechanism to inhibit JH1 , our JH1–JH2 model represents a verifiable working hypothesis for further experimental studies , with the ultimate goal to understand how JH2 regulates JAK2 in both normal and pathological settings .
Two strategies were employed to build an initial model of the complex between the inactive conformation of JH1 and the active conformation of JH2 ( Figure 3 ) . In the first strategy , models were constructed based on the hypothesis that the JH1–JH2 complex interface connects allosteric sites of JH1 and JH2 . Allosteric sites in JH1 and JH2 were identified by MutInf ( mutual information-based analysis of MD simulations ) , a novel method previously developed to identify allosteric sites in an unbiased , statistically robust manner [28] . In the second strategy , models were constructed based on available kinase dimeric forms similar to those in the study by Kroemer and coworkers [19] , [20] . As detailed in the Methods section , a total of four diverse JAK2 JH1–JH2 complex structures were modeled according to the dimer structures of FGFR1 [18] , FGFR2 [26] , BRAF [29] and RNA-dependent protein kinase PKR [16] . We first used MutInf ( details in the Methods ) to identify allosteric sites in the crystal structure of JH1 in the active conformation ( PDB ID: 2B7A ) to validate our method . Consistent with conventional kinase regulatory mechanisms , dynamical couplings from the activation loop and the hinge region to the αC helix were observed . Direct coupling between the αC helix and activation loop occurs via a polar network; for example , residues R897 in the αC helix and K1011 in the activation loop coordinating the phosphorylated Y1008 . The strongest correlated residues in the pairwise matrix were mapped on to the structure ( Figure S1 ) . We next modeled JH1 in the inactive conformation based on the inactive conformation of EGFR ( PDB ID: 2GS7 ) and examined the pattern of correlated motions using MutInf ( Figures 4A–B , and S2A–B ) . Notably , a more robust communication between the αC helix and the activation loop was observed in the inactive form than in the active form . Unlike the polar network found in active JH1 , a hydrophobic network in the inactive JH1 connects the greasy surfaces formed by the αC helix and the activation loop . In particular , a cluster of hydrophobic residues , namely L997 , V1000 and L1001 in the activation loop , are coupled to the following residues: L884 in β3 sheet , L925 in β4 sheet , V916 and Y918 in the β5 sheet , and L892 in the αC helix . Other correlated residues , such as E890 , H891 , R893 , D894 and E900 are also located in the aC helix . Therefore , conformational changes of the αC helix are highly coupled to the activation loop in JH1 in both the active and inactive states , despite the nature of the network differs . We also modeled JH2 in the active conformation and applied MutInf analysis ( Figures 4C–D , and S2C–D ) . Surprisingly , no significant couplings were identified for residues in the αC helix , in contrast to results from JH1 . Instead , we identified two novel coupling sites: one consists of residues L681 , L682 , E684 and G690 in the β7–β8 sheet near the hinge region and the other is close to the catalytic loop ( residues L669 and I670 ) and activation loop ( S703 , I704 , K709 , I711 , Q713 and E714 ) . It is likely that these two correlated sites in JH2 are involved in stabilizing JH1 in an inactive conformation . Six initial models ( Figure 4 ) , four from modeling kinase dimers and two from MutInf predicted interfaces were refined by a hierarchical protein-protein docking and refinement procedure to systematically improve the quality of these complex models . Among the six models , Model 2 ( derived from the MutInf approach ) was the most structurally stable and energetically favorable structure throughout the entire 10 ns MD simulation ( Table 1 ) , as assessed by averaged root-mean-square fluctuation of JH2 ( PK_RMSF 1 . 8 Å ) , averaged interaction energy ( −217 . 1±26 . 5 kcal/mol ) , averaged charged and hydrophobic contacts ( 7 and 16 respectively ) , and averaged BSA ( ∼1300 Å2 ) . Internal motions of JH2 and JH1 themselves were relatively small , with RMSF values ( Cα ) around 1∼2 Å among all models ( data not shown ) . Therefore , Model 2 likely represents the near-native conformation of the JAK2 JH1–JH2 complex in an auto-inhibited state . In addition , fluctuations of the αC helix were measured to assess whether the predicted protein-protein interface in model 2 would block the mobility of αC helix ( Table 1 ) . Indeed , the motion of αC helix in Model 2 is the lowest of all models due to strong interfacial interactions between JH2 and JH1 . We explored the auto-inhibition mechanism of JAK2-WT and the constitutive activation mechanism of the JAK2-V617F mutant based on model 2 . We carried out an additional 30 ns unbiased MD simulations for both JAK2-WT and JAK2-V617F structures after the addition of two linkers between JH2 and JH1 , and between the SH2 domain and JH2 , respectively . A strong π-π stacking interaction with the neighboring residue F595 was proposed to be important for the V617F mutation to constitutively activate JAK2 [22]–[24] . Consistent with this notion , the centroid distance between residues 595 and 617 was stable across the entire 30 ns simulation in the JAK2-V617F model ( Figures 5A and 5B ) , with the average centroid distance of 5 . 8 Å , which is within the range generally accepted for a π-π stacking interaction ( 4 . 5∼7 . 0 Å ) [30] . In contrast , in the JAK2-WT model , the distance between F595 and V617 increased , accompanied by a large conformational change of the β4/β5 region after 18 ns ( Figures 5A and 5C ) . Interestingly , we observed that a model lacking the SH2-JH2 linker also lost this π-π stacking interaction after 22 ns simulation ( Figure S3 ) , indicating that the SH2-JH2 linker may regulate JAK2 kinase activity . These results are in line with the fact that activating mutations in this linker ( exon 12 mutations ) are found in MPN patients [12] , [31] . We also examined the structural and energetic consequences introduced by the V617F mutation . In contrast to JAK2-WT , JAK2-V617F clearly lost the favorable interactions between JH1 and JH2 and showed greater conformational changes in the 30 ns MD simulation , as measured by average RMSD ( 3 . 8±0 . 6 Å in WT and 4 . 4±0 . 8 Å in V617F ) and averaged interaction energy ( −279 . 4±22 . 1 kcal/mol in WT and −235 . 4±18 . 2 kcal/mol in V617F ) ( Figures S4A–B ) . In particular , the V617F mutation led to a dramatic conformational rearrangement of the activation loop in JH1 , changing from the initially modeled inactive conformation ( largely buried ) toward a more active conformation ( more opened ) . In JAK2-WT , the activation loop's motions were less pronounced ( Figures 6A–B ) , consistent with previous simulation results based on Kroemer's model [22] . In addition , the fluctuation of the αC helix in JH2 was blocked in JAK2-V617F ( Figure S4C ) , and the V617 mutation rigidifies αC helix in JH2 in the simulation of crystal structure of JH2 [32] . Notably , a favorable salt bridge interaction , involving R588 in the αC helix of JH2 and E1028 in JH1 , was broken in JAK2-V617F but remained stable in JAK2-WT ( Figure S4D ) , suggesting that the V617F mutation releases steric constraints with the activation loop in JH1 via trapping the movement of αC helix in JH2 . The V617F mutant did not convert the inactive conformational state of JH1 to an active one during our 30 ns MD simulation ( Figures 6 ) . For example , the fluctuation of the αC helix in JH1 , a key region for regulating kinase activity , was blocked in both JAK2-V617F and JAK2-WT ( Figures 6C–D ) . In addition , important interfacial contacts between JH1 and JH2 , such as V706 and V1033 , and L707 and I973 , still remained intact in JAK2-V617F ( data not shown ) . Previously , we showed that V617F is only able to hyperactivate full-length JAK2 , and a mutant JAK2 lacking the N-terminal FERM domain had similar activities with or without the existence of the V617F mutation [13] . It is likely that our simulation of V617F in the JH1–JH2 complex only represents an early step of hyperactivation , while other JAK2 domains are required for V617F to fully activate JAK2 . Our JH1–JH2 model presents unique structural features ( Figure 7 ) that are different from Kroemer's model ( Figure S5 ) . Our model is in an anti-symmetric-like and face-to-face domain arrangement , with extensive interactions spanning the αC helix and the αEF/αF loop of both JH2 and JH1 . This new dimeric form results in extensive electrostatic ( interface 1 ) and tightly packed hydrophobic interactions ( interface 2 ) . Interface 1 is dominated by two inter-domain salt bridge interactions , formed by R588 and E592 in the αC helix of JH2 , and E1028 and K1030 in the αEF/αF loop of JH1 , respectively . Interface 2 is dominated by strong hydrophobic contacts between V706 and L707 in the activation loop region of JH2 with I973 and V1033 in JH1 . Importantly , our model predicts the critical role of residues V706 and L707 in JH2 in stabilizing the inactive conformation of JH1 , which could not have been identified in Kroemer's model ( Figure S5 ) . In addition , our model indicates that R588 in JH2 forms strong salt bridge interaction with E1028 in JH1 while it interacts with E890 in Kroemer's model , and E592 in JH2 interacts with K1030 in JH1 while it contacts with R893 in Kroemer's model . To assess our model , we performed computational alanine scanning of the JH1–JH2 interface ( Table S1 ) [33]–[35] , and selected corresponding residues for mutagenesis studies . For interface 1 , we engineered R588A and E592A in JH2 , and the corresponding E1028A and K1030A in JH1 to examine the predicted inter-domain salt bridge interactions . We also made compensatory mutants R588E/E1028R and E592K/K1030E . For interface 2 , we engineered V706A and L707A in JH2 , and I901A , R971A , I973A and V1033A in JH1 to examine the predicted hydrophobic contacts . We hypothesized that these mutations will directly interrupt favorable interactions between JH2 and JH1 , releasing auto-inhibition to activate JH1 kinase activity . We first examined the effects on JAK2 auto-phosphorylation in HEK293T cells transiently expressing hemaglutinnin ( HA ) -tagged wild-type or mutated JAK2 . As shown in Figure 8A , R588A , E592A , V706A , and L707A were hyperactive compared to JAK2-WT as measured by an antibody specifically recognizing the phosphorylated active form of JAK2 . To corroborate these studies , we also examined the ability of these JAK2 mutants to phosphorylate downstream substrate STAT5 . Hyperactivation of STAT5 can be observed using antibodies recognizing phosphorylated active form of STAT5 via flow cytometry ( Figure 8B ) . Moreover , we investigated the in vivo effect of JAK2 mutants in BaF3/EpoR cells . BaF3/EpoR cells depend on JAK2 activity to proliferate , and expression of JAK2-V617F transforms these cells into factor-independent growth . Consistent with their hyperactivity , R588A , E592A , V706A transformed BaF3/EpoR cells into factor-independent growth , although to a lesser extent than V617F ( Figure 8C ) . L707A was not able to transform BaF3/EpoR cells , despite its hyperactivation . This may be due to the fact that transformation of BaF3/EpoR cells relies on signaling originated from the EpoR-JAK2 complex instead of JAK2 in isolation . L707A may affect the conformation of JAK2 such that although it is hyperactivated , it is less efficient in phosphorylating substrates in the context of a EpoR-JAK2 complex to transform BaF3/EpoR cells . Interestingly , all mutations in the kinase domain ( I901A , R971A , I973A , E1028A , K1030A , and V1033A ) reduced basal JAK2 kinase activity ( Figure 8D ) . These residues may function in a more complex manner in that they are important both for inhibitory interaction with JH2 and for regulating kinase activity of JH1 .
JAK2 plays essential roles in transmitting signals from multiple cytokine receptors , and has emerged as a prominent drug target in hematological malignancies . JAK2 kinase activity is negatively regulated by its JH2 domain , in which a gain-of-function mutation is found in the majority of patients with myeloproliferative neoplasms . Understanding of how the JH2 domain regulates JAK2 kinase activity ( JH1 ) thus is urgently needed . In the absence of full-length JAK2 structures , we developed a model of the JAK2 JH1–JH2 complex using computational modeling . We assessed this model by mutating critical residues in the predicted complex interface in JH2 and showed that they indeed hyperactivated JAK2 kinase activity . Our model requires further experimental validation . Nevertheless , it represents a verifiable working hypothesis that facilitates structure-function interrogation of mechanisms underlying JAK2 signaling . Importantly , our model was built by a novel strategy based on allosteric sites on interacting partners . This step-wise computational strategy we devised may be easily adopted for studying novel protein-protein interactions in a general manner . Several important lessons were learned from our study . First , our study provides “proof-of-principle” evidence that information on allosteric sites of each interacting partner can be used to guide the generation of protein complex structures . In addition to four models constructed based on available kinase dimeric interfaces , we applied the MutInf algorithm to identify sites exhibited correlated torsional motions in JH1 and JH2 to guide protein-protein docking . The MutInf method applies equilibrium molecular dynamics simulations to identify correlated motions between spatially unrelated residues , so that novel allosteric sites might be identified in an unbiased , statistically robust manner [28] . Detailed analysis of MD simulation trajectories clearly indicates that Model 2 , derived from MutInf , was the most energetically favorable and structurally stable model among the six models built . This work represents the first application of using MutInf in a prospective prediction of sites on two protein domains involved in a protein-protein interface . Second , a priori knowledge of the starting conformation for JH1 and JH2 is important for model generation . In contrast to Kroemer's model in which JH2 was built in the inactive conformation , our initial JH1–JH2 model was built such that JH1 is in the inactive conformation and JH2 in the active conformation . This is based on the latest findings that JH2 possesses kinase activity and auto-phosphorylates two JAK2 residues to maintain basal auto-inhibition . In our model , the active conformation of JH2 traps JH1 in an inactive conformation via direct interfacial contacts . Our experimental data that mutating the important interfacial residues V706 and L707 in the JH2 activation loop hyperactivated JAK2 strongly support our model . The importance of V706 and L707 would not have been noticed if JH2 were built in an inactive conformation . It should be noted that although it is hard to argue that JH2 is not in an active conformation as it phosphorylates negative regulatory JAK2 sites in the basal state , the exact conformation of JH2 and JH1 would have to await a crystal structure of full-length JAK2 . Third , the presence of linker loops between JH1 and JH2 , and between SH2 and JH2 play a critical role in model construction . We modeled the loops after we determined the best packing mode between JH1 and JH2 – a necessary step in refining the final complex structure . The JH1–JH2 loop reduced the spatial sampling needed in protein-protein docking and restrained the inter-domain arrangement although it remains challenging of loop prediction for those longer than 12 residues [36] . In addition , we also found that the SH2-JH2 linker loop can stabilize the π stacking interaction between residues F617 and F595 in JAK2-V617F . Consistent with our results , mutations in the SH2-JH2 linker loop ( the exon 12 mutations ) , similar to V617F , hyperactivate JAK2 and are found in patients with myeloproliferative neoplasms [12] , [31] . Mutating critical interfacial residues in JH2 hyperactivated JAK2 kinase activity , lending strong support to our model . Among these critical residues , R588 was previously identified in our random mutagenesis screen of residues essential for JAK2 auto-inhibition . E592 is adjacent to residue S591 , where a S591L mutation was identified in the same random screen [12] . Differ from Kroemer's model , our model predicts that R588 in JH2 forms strong salt bridge interaction with E1028 in JH1 instead of E890 ( Figure S5 ) . Importantly , our model predicts the critical role of residues V706 and L707 in JH2 in stabilizing the inactive conformation of JH1 , which could not have been identified in Kroemer's model ( Figure S5 ) . Surprisingly , mutating the corresponding interfacial residues in JH1 , instead of hyperactivating JAK2 , resulted in reduced basal JAK2 kinase activity . Among these residues , none are conserved within the kinase family except for I973 ( Table S2 ) . These residues thus are not likely to disrupt the kinase fold or directly reduce enzymatic activity . We envision that they serve dual roles in regulating JAK2 kinase activity . First , they interact with JH2 to trap JH1 in an inactive conformation in the basal state . Second , they regulate JH1 activity upon release from JH2 . These JH1 residues may control its conformational transition from an inactive to an active state . Alternatively , they may interact with other JAK2 domains such as the FERM domain to activate JH1 activity . Therefore , mutating these residues , although relieves the inhibitory JH1–JH2 interaction , also hinders JH1 kinase activity . Another hypothesis put forth was that dimerization and autophosphorylation of JH2 might be the predominant mechanism to inhibit JH1 [10] , [32] . However , how JH2 phosphorylation of negative regulatory sites results in JH1 inhibition remains elusive . Our results and the contribution of the different mechanisms in JH2-mediated JAK2 regulation await confirmation by experimental structures and further experiments . During the revision of this manuscript , the Hubbard group reported the X-ray structure of the JAK2 JH2 domain [32] . Superimposition of the crystal structure with our modeled complex structure showed that the two structures are well aligned except in the predicted interfacial regions including the αC helix and the activation loop ( Figure S6 ) . Both regions are highly flexible in our simulations and in simulation results reported by Hubbard's group . Importantly , our predicted JH1–JH2 interfaces can still be identified , especially for residues E592 and V706 , which lends further support to our model . In addition , the JH2 activation loop is less open compared to our modeled structure . Future work will utilize this new crystal structure of JH2 to further refine our JH1–JH2 complex model . In summary , we hypothesized that the JH1–JH2 interface involves sites on each partner with a high degree of correlated motions with other sites ( i . e . potential allosteric sites ) , and tested this working hypothesis using a hierarchical protein-protein docking and refinement protocol . Our JH1–JH2 model generated from this approach is more energetically favorable compared to those generated in parallel based on available kinase dimeric forms . We then tested our model with prospective mutational analyses . We note that our approach – predicting potential allosteric sites on each partner using MutInf and subsequently adding restraints between these sites to guide protein-protein docking – is particularly novel , and should be useful in predicting interface regions involved in other protein-protein complexes . We expect that our JAK2 JH1–JH2 structure model may facilitate the further exploration of the atomic events of regulatory mechanisms in JAK protein family ( structure models available at http://www . huanglab . org . cn/JAK2_MODEL ) . We also believe that the computational approach we used here will be applicable in predicting novel protein-protein interactions in other systems in general .
The JAK2 JH1 domain was crystallized in the active conformation . We modeled the JAK2 kinase domain in the inactive conformation ( residues 840–1132 ) using its active conformation structure as a template ( PDB id: 2B7A ) [37] , with the αC helix ( residues 882–928 ) and activation loop ( residues 992–1018 ) modeled from the inactive conformation of EGFR ( PDB id: 2GS7 ) [15] . The sequence alignment is shown in Figure S7A . The sequences were aligned using ClustalW ( version 2 . 0 . 5 ) with protein fast pair-wise alignment using default parameters [38] . The final sequence alignment used in homology modeling was slightly adjusted based on superimposed structures . Homology model was built using the program MODELLER ( version 9v7 ) [39] , [40] . The model with top DPOE assessment scores in MODELLER was selected and validated with PROCHECK with an overall G-factor of −0 . 15 [41] . Ramachandran plot analysis [42] showed that conformations for 87 . 4% of residues are located in the most favored regions . Because no structure was available at the time of our study , we generated a homology model for JH2 . The sequence of JH2 ( residues 545–816 ) was aligned with all available human kinase domains in the PDB , where its DPG motif was manually aligned with the conserved DFG motif in kinases ( Figure S7B ) . The sequence identity is about 25% on average , while the highest identify is with the kinase domain of PYK2 ( 28% ) and JAK2 ( 26% ) . JH1 can interact with JH2 , and also phosphorylates the other JH1 in the dimerized receptor complex in trans . These results imply conservation of binding characteristics between these two domains . Thus , the crystal structure of the JAK2 kinase domain ( PDB id: 2B7A ) [37] was chosen as a template to build the homology model of JH2 . The Ramachandran plot analysis showed that conformations for more than 87 . 2% of the residues are located in the most favored regions . In addition , the linker between JH2 and JH1 ( residues 817–839 ) was modeled by employing the loop modeling in MODELLER . The SH2-Pseudokinase linker region ( residues 523–544 ) was built based on the inactive c-Abl tyrosine kinase structure [43] ( Figure S7C ) . Both linkers were generated after the construction of the JH1–JH2 complex structure . We employed two independent strategies to identify binding interfaces between JH2 and JH1 . One is based on predicted allosteric sites of JH2 and JH1 , and the other on available kinase dimeric forms . In the first strategy , we hypothesized that the near-native JH1–JH2 complex interface should connect allosteric sites of the partners identified by a mutual information-based analysis of MD simulations ( MutInf ) [28] . This method analyzes MD simulation trajectories to calculate the mutual information between pairs of residues's conformations using the distributions of the φ , ψ , and ω torsion angles of the protein backbone and the χ torsion angles of the amino acid side-chains from the MD simulations and then applies tests of significance and statistical corrections to remove noise . We identified candidate allosteric sites for both JH1 and JH2 following the same protocol we previously published [28] . MD simulations were carried out for five parallel systems with different random seeds to improve the conformational sampling . Each copy was minimized in explicit solvent , followed by equilibration at 300 K using constant volume for 10 ps and using a constant pressure [44] of 1 atm for 5 ns . Production simulation was run for 10 ns , with snapshots of the atomic coordinates recorded every 1 ps . A hierarchical clustering protocol using “heatmap” function and a force-directed network diagram [45] in R package ( http://www . r-project . org/ ) was used to cluster the matrix of mutual information between residues to identify groups of residues showing similar patterns of correlations . These highly correlated residues were grouped to identify candidate allosteric sites . Finally , JH1 and JH2 were manually joined at surface regions where their statistically correlated sites could be coupled together to form functional interactions . A similar strategy that predicts allosteric sites using statistical coupling analysis [46] was used to engineer proteins with regulatory activity . In the second strategy , we constructed JH1–JH2 complex models based on available kinase dimeric forms similar to those in the study performed by Kroemer and coworkers [19] , [20] . A total of four diverse JH1–JH2 complex structures were modeled according to the dimer structures of FGFR1 [18] , FGFR2 [26] , BRAF [29] and RNA-dependent protein kinase PKR [16] . To eliminate the physically unrealistic interactions produced by manual superposition and to explore the localized potential energy surface efficiently , a local protein-protein docking perturbation was performed using RosettaDock program ( Rosetta 2 . 3 ) [47] , [48] . The Rosetta sidechain packing algorithm was applied to allow sidechain flexibility during docking [48] . The docking poses of the JH1–JH2 complex were sampled by spanning a Gaussian random angle of 8° around the axis of the centers and by tilting 8° from the axis after translating JH2 by Gaussian-distributed random distances with a 3 Å standard deviation along the line connecting protein centers and an 8 Å standard deviation in the two perpendicular directions [47] . A total of 10 , 000 poses were generated for each predetermined dimer configuration . Subsequently , all the generated docking poses were filtered by the length of the linker between JH2 and JH1 domains ( cutoff value of 60 Å ) . The remaining poses ( within 1000 ) were clustered using NMRCLUST program [49] by computing the root-mean-squared distance ( RMSD ) of Cα atoms of JH2 after superimposing JH1 . Each representative pose from the top 5 clusters was selected for further MD simulation refinement . The JH1–JH2 complex structure was prepared using Maestro ( Schrödinger LLC , New York NY ) . Molecular dynamics was performed by employing the program Desmond 2 . 2 . 7 . 3 . 0 [50] with OPLS 2005 force field [51] in 0 . 15 M NaCl [52] and TIP3P explicit water model [53] . The cubic boundary condition was selected and no protein atom was within 10 Å of the edge . The whole system contains about 89 , 000 atoms and is 98×98×98 Å3 in size . The equilibration of solvated system was performed with 2 , 000 steps of steep descent minimization followed by 3 , 000 steps of L-BGFS minimization , with 50 kcal·mol−1 ·Å−2 harmonic position restraints applied to heavy atoms of the solute . The production run was performed in MTK NPT ( 1 bar , 300 K ) ensemble for 10 ns . The cutoffs of short-range electrostatic and Lennard-Jones interactions were 10 Å . Long-range electrostatic interactions were computed by the Particle Mesh Ewald method [54] using 64×64×64 grid with σ = 2 . 18 Å . The M-SHAKE algorithm [55] was used to constrain all bonds involving hydrogen atoms with the integration step size of 2 fs . The 10 ns MD simulation was analyzed by root-mean-squared fluctuations of JH2 Cα atoms after superimposing onto the kinase domain ( PK_RMSF ) , buried surface areas ( BSA ) measured by the program MSMS [56] , and hydrophobic contacts and ionic interactions ( H/I interactions ) in the binding interface calculated by the PIC server [57] . The interaction energy was calculated by subtracting the energies of pseudokinase and kinase domains from the energy of complex ( Ebind = Ecomplex−EJH1−EJH2 ) using the Protein Local Optimization Program ( PLOP ) [58]–[60] . The interaction energy was simplified by accounting the sum of electrostatic ( Eele ) and van der Waals ( Evdw ) interaction terms . Finally , a 30 ns extended MD simulation was performed to further refine the selected near-native JH1–JH2 complex structure after modeling the linkers between JH2 and JH1 , and between SH2 and JH2 , respectively . The computational alanine scanning of the JH1–JH2 interface was conducted on the Robetta server [33]–[35] using the refined JH1–JH2 complex structure . The conservation analysis of mutating residues in the kinase domain was carried out on the ConSurf server [61] , [62] by collecting 150 JAK2 homologue sequences . HA-tagged JAK2 and JAK2 mutants were expressed in the pcDNA3 . 1 vector . HEK293T cells transiently expressing wild-type or JAK2 mutants were lysed in 1% NP-40 lysis buffer ( 50 mM Tris/HCl ( pH 7 . 4 ) , 150 mM NaCl and 1% Nonidet P40 ) with phosphatase and protease inhibitors . The lysates were immunoblotted with antibodies recognizing activated JAK2 ( anti-phospho-JAK2 , EMD Millipore #07-606 , 1∶1000 ) or HA ( Covance #MMS-101P , 1∶1000 ) [12] . Wild-type or mutants JAK2 were stably expressed in the MSCV-IRES-CD4 vector in BaF3/EpoR cells . The expression levels of wild-type or mutant JAK2 were similar based on expression of CD4 via flow cytometry ( Figure S8 ) . To examine factor-independent growth , cells were washed extensively in RPMI medium with 1% BSA and then grown in RPMI medium with 10% fetal bovine serum without IL-3 as previously described [12] . Cell numbers were determined at days indicated by MTT assay . Cells were seeded in triplicate ( 10 , 000/well in 100 µl ) in 96-well plates . 15 µl of 3- ( 4 , 5-dimethylthiazole-2-yl ) -2 , 5-diphenyl tetrazolium bromide ( MTT; Promega , Madison , WI ) was then added to each well to determine live cell numbers according to the manufacturer's instruction . HEK293T cells were co-transfected with plasmids expressing STAT5 and wild-type or mutant JAK2 . 48 hrs post transfection , cells were fixed with 1 . 6% paraformaldehyde , permeabilized with acetone , washed with staining buffer ( PBS with 1% BSA ) , and stained with Alexa647-conjugated phospho-STAT5 antibodies ( BD Biosciences #612599 , 1∶50 ) . Fluorescence was determined by flow cytometry on a FACS Calibur ( BD Biosciences ) and median fluorescence from 10 , 000 cells was analyzed by FlowJo software [63] .
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Protein-protein interactions ( PPIs ) are essential to cellular signal transduction , and structural information about PPIs is crucial for understanding of how cellular machinery functions at the atomistic level . However , both experimental structural determination and computational prediction of PPI are challenging . In the cytoplasmic tyrosine kinase JAK2 , a pseudokinase domain ( JH2 ) negatively regulates kinase activity of its adjacent catalytic kinase domain ( JH1 ) . A gain-of-function mutation within JH2 is found in the majority of patients with myeloproliferative neoplasms , and is sufficient to cause similar diseases in murine models . Here we combined an informatics-guided protein-protein docking method with molecular dynamics simulation to construct and refine the JAK2 JH1–JH2 complex , and validated our model with mutational studies . Our modeled structure suggests that JH2 auto-inhibits JAK2 kinase activities by blocking the movements of the activation loop and the αC helix of JH1 , but awaits further validation by a detailed structure of the full-length JAK2 protein .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Methods"
] |
[
"physics",
"biochemistry",
"computer",
"science",
"computational",
"chemistry",
"classical",
"mechanics",
"statistical",
"mechanics",
"chemistry",
"biology",
"computational",
"biology",
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2013
|
Ab Initio Modeling and Experimental Assessment of Janus Kinase 2 (JAK2) Kinase-Pseudokinase Complex Structure
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Protein phosphorylation plays a central role in creating a highly dynamic network of interacting proteins that reads and responds to signals from growth factors in the cellular microenvironment . Cells of the neural crest employ multiple signaling mechanisms to control migration and differentiation during development . It is known that defects in these mechanisms cause neuroblastoma , but how multiple signaling pathways interact to govern cell behavior is unknown . In a phosphoproteomic study of neuroblastoma cell lines and cell fractions , including endosomes and detergent-resistant membranes , 1622 phosphorylated proteins were detected , including more than half of the receptor tyrosine kinases in the human genome . Data were analyzed using a combination of graph theory and pattern recognition techniques that resolve data structure into networks that incorporate statistical relationships and protein-protein interaction data . Clusters of proteins in these networks are indicative of functional signaling pathways . The analysis indicates that receptor tyrosine kinases are functionally compartmentalized into distinct collaborative groups distinguished by activation and intracellular localization of SRC-family kinases , especially FYN and LYN . Changes in intracellular localization of activated FYN and LYN were observed in response to stimulation of the receptor tyrosine kinases , ALK and KIT . The results suggest a mechanism to distinguish signaling responses to activation of different receptors , or combinations of receptors , that govern the behavior of the neural crest , which gives rise to neuroblastoma .
Neuroblastoma arises from cells of the neural crest , a population of multipotent , migrating cells that differentiate into neurons in the peripheral nervous system , melanocytes , and structural cells [1] . Neuroblastoma represents 7–10% of childhood cancers and about half of all infant cancers . Positive prognosis ranges from 95% to 10% depending on age , markers expressed in tumor cells , and stage of progression . 70% of neuroblastomas are already metastatic at diagnosis . There is compelling evidence that stalled or incomplete cell differentiation is the primary defect that gives rise to this cancer [2–6] . Neural crest cells appear to restrict their range of cell fate choices in sequential steps [7 , 8] , and the profound heterogeneity in neuroblastoma is caused by a failure to differentiate at different stages . Neuroblastoma tumors and cell lines thus represent a snapshot of failed differentiation at different stages in the neural crest sympathoadrenal lineage [2 , 4 , 7 , 8] . Anaplastic lymphoma kinase ( ALK ) , a receptor tyrosine kinase ( RTK ) , is frequently mutated and activated in both familial and spontaneous neuroblastomas , suggesting that this receptor can prevent a key differentiation step in neural crest cells [9–15] . Incompletely differentiated cells may give rise to a proliferating population when mutations occur that allow checkpoints in the cell division cycle and mechanisms of programmed cell death to be bypassed . The tragic outcome is too often a metastatic cancer with poor prognosis . To address this clinically challenging problem , a greater understanding of the signaling mechanisms that are active in neural crest and neuroblastoma is required . Tyrosine kinase signaling networks play a major role in governing cell differentiation , including in neuroblastoma [16] . There are 90 tyrosine kinases in the human genome; 58 of these are receptor tyrosine kinases [17 , 18] , many of which have unknown functions . Src Homology 2 ( SH2 ) domains ( and one-fifth of phosphotyrosine-binding or PTB domains ) mediate selective protein–protein interactions with proteins phosphorylated on tyrosine residues , and thus mediate assembly of phosphotyrosine signaling networks [19] . The metazoan evolution of multicellular organisms coincided with expansion of tyrosine kinases , protein tyrosine phosphatases , and SH2 domains , which suggests that tyrosine kinase signaling mechanisms play a major role in cell differentiation [20–22] . Unfortunately , the system isn’t foolproof , and cancer results when the dynamic assembly of signaling complexes goes awry [23] . Thus , the complexity of kinase-substrate and other protein-protein interactions in tyrosine kinase signaling pathways is important to understand because these pathways govern the choice between differentiation and cancer . Tyrosine kinase signaling mechanisms are intimately intertwined with mechanisms that govern protein interactions in endocytosis . Src Homology 3 ( SH3 ) domains are among the most abundant protein domain modules encoded by eukaryotic genomes; over 300 SH3 domains are found in 213 human proteins [24 , 25] . SH3 domain-containing proteins , which typically bind to proline-rich motifs [26] , are functionally linked to both endocytosis and tyrosine kinase signaling pathways [24] . SH3-domain-containing proteins play a role in endocytosis that is conserved in yeast , worms , and humans [26 , 27] . SH3 proteins may also contain other domains ( e . g . , kinase , phosphatase , GTP exchange , GTPase activating ) to perform conserved functions in endocytosis and cytoskeletal dynamics , and , in metazoans , RTK signaling [28 , 29] . 36 human proteins contain one SH2 domain and one or more SH3 domain ( s ) ( SH2-SH3 proteins ) [25] . Most SH2-SH3 proteins are phosphorylated on multiple sites on tyrosine as well as serine and/or threonine residues . Half of them also have tyrosine kinase domains , e . g . , the SRC-family kinases ( SFKs ) . Interactions between proteins that contain SH2 and SH3 domains indicate that tyrosine kinase signaling and endocytosis are linked , and there is good evidence that endocytosis and signal transduction in general are integrated [30 , 31] . To identify patterns in tyrosine phosphorylation in neuroblastoma , we acquired phosphoproteomic data from 21 neuroblastoma cell lines and cell fractions including endosomes and detergent-resistant lipid rafts as previously characterized [32 , 33] . New approaches were devised to analyze these data . We previously experimented with different dimensionality reduction and clustering techniques and validated methods that effectively resolve clusters from lung cancer phosphoproteomic data [34] . An important first step is to represent missing values as “data not available” instead of zero in spectrometry data . By combining pattern recognition techniques with gene ontology ( GO ) and protein-protein interaction ( PPI ) data , we learned that clusters that contain interacting proteins are likely to indicate functional signaling pathways [34–40] . Here , we extend methods that employ graph theory and pattern recognition algorithms to introduce techniques to visualize data structure , namely a cluster-filtered network ( CFN ) and co-cluster correlation network ( CCCN ) . We focussed primarily on proteins containing tyrosine kinase , tyrosine phosphatase , SH2 and SH3 domains , which collectively we call phosphotyrosine network control proteins ( PNCPs ) .
To identify patterns in tyrosine phosphorylation in neuroblastoma , we analyzed tyrosine phosphoproteomic data acquired from 21 neuroblastoma cell lines using immunoprecipitation of tyrosine phosphorylated peptides as previously described [41 , 42] . Four cell lines [SH-SY5Y , LAN-6 , SMS-KCN , and SK-N-BE ( 2 ) ] were selected for further studies because of their different point mutations in ALK , p53 status , RTK expression , morphology , and growth patterns . These cells were fractionated to isolate endosomes and detergent-resistant lipid rafts [32 , 33] , and analyzed under different conditions that changed the state of their signaling pathways . Quantification of immunoprecipitated phosphopeptides was obtained from the peak intensity of each peptide ( from the MS1 spectrum of the intact peptide before fragmentation for MS/MS analysis ) [41 , 42] . We experimented with different ways to analyze the mass spectrometry data ( described in detail in Materials and Methods ) . For the first analysis described below , phosphopeptide amounts were summed for each protein in each sample , with the exception of the SRC-family kinases ( SFKs ) , where the C-terminal inhibitory phosphorylation was summed separately and given the names SRC_i; LYN_i; FYN_i; and YES1_i . This provided an overview of which proteins were present and phosphorylated together in the same samples . For the second analysis , phosphopeptides were summed into individual phosphorylation sites , which were then clustered . Clustering data were obtained by treating all samples mathematically as different states in the neuroblastoma system . We describe analysis of the whole dataset first , then subsets of the data , focusing on signaling proteins in endosomes and detergent-resistant membranes . 1622 phosphorylated proteins were identified in all neuroblastoma samples ( S1 Fig; S3 Dataset ) . 1203 of these were tyrosine phosphorylated , identified from peptides immunoprecipitated using an anti-phosphotyrosine antibody . 557 proteins were identified from phospho-AKT substrate immunoprecipitation; of these 419 were unique , and 138 were dually phosphorylated proteins also found in the phosphotyrosine data . Due to limits in mass spectrometric detection of peptides [43–47] , these data were not an exhaustive determination of all phosphorylated proteins in all samples . To ask whether these data were complete enough for analysis of signaling pathways , we employed graph theory , which describes the properties of networks [35 , 38] . S1 Fig shows a network constructed using proteins identified in neuroblastoma phosphoproteomic data as nodes , and protein-protein interaction ( PPI ) edges merged as described [34] . We found that the entire neuroblastoma phosphoproteomic network of 1622 proteins and 18728 interactions is dense enough to have the structure and properties expected of biological networks , including clusters that can be usefully interpreted ( S2 Fig ) . PPI databases are biased towards proteins best studied in the scientific literature [36–38] , and not all protein-protein interactions in PPI databases may occur in neuroblastoma cells . Nevertheless , PPI network analysis indicates that the phosphoproteomic data are complete enough to examine further to gain insight into signal transduction pathways that are active in neuroblastoma ( S2 Fig ) . We hypothesize that proteins containing tyrosine kinase , tyrosine phosphatase , SH2 and SH3 domains ( PNCPs ) will collectively initiate and control phosphotyrosine signaling pathways [19 , 24] . In neuroblastoma phosphoproteomic data , we detected 31 phosphorylated RTKs out of 58 in the human genome ( S3 Fig ) ; 41 of 110 SH2-domain-containing proteins; 12 out of 38 ( or 107 possible , based on open reading frames in the human genome ) proteins containing the tyrosine phosphatase ( PTPc ) domain; and 61 out of the 216 human SH3-domain containing proteins . There are 36 proteins in the human genome that contain both SH2 and SH3 domains and 17 of these were detected in neuroblastoma phosphoproteomic data . These data indicate that neuroblastoma cell lines express and phosphorylate a large fraction of the PNCPs in the human genome . This remarkable diversity in phosphotyrosine signaling pathways likely represents a snapshot of signaling pathways activated in the sympathoadrenal lineage of neural crest that gives rise to neuroblastoma at different stages of development [2–6] . The robust expression of RTK pathways that are known to function in neural crest differentiation suggests the hypothesis that neuroblastoma cells might be multipotent despite being selected for proliferation in culture . To test this hypothesis we transplanted neuroblastoma cells in to the developing neural tube of live chick embryos and indeed found that they were capable of both migration and terminal differentiation ( S4 Fig ) . Notably , four different transplanted human neuroblastoma cell lines [LAN6 , SK-N-BE ( 2 ) , SMS-KCN , and SH-SY5Y] migrated to neural crest target sites , incorporated into the developing ganglia , and expressed neuronal markers specific to mature afferents ( S4 Fig ) . The potential to migrate along the stereotypical neural crest migration pathways , and differentiate into most neural-crest-derived cell types , suggests that many of the RTK signaling pathways that control differentiation and migration were generally functional in these neuroblastoma cell lines . Thus , our phosphoproteomic data has relevance to pathways active in neural crest from which neuroblastoma is derived , and warrants detailed analysis . We developed new methods to analyze proteomic data based on the hypothesis that data structure can be described using a combination of graph theory and pattern recognition techniques . The first key step was to recognize that missing data , which are common in mass spectrometry data due to stochastic variation in phosphopeptide detection , should not have a value of zero [34] . The next key step was to represent different statistical relationships by proximity on two- or three-dimensional graphs using an effective dimension reduction , or embedding , technique , t-distributed stochastic neighbor embedding ( t-SNE ) [48 , 49] . Clusters were identified by proximity on resulting three-dimensional data structures ( embeddings ) using a minimum spanning tree , single linkage method [34 , 50] . 75–80 clusters were identified from each embedding based on dissimilarity calculated in different ways ( S1 Movie; S1 Dataset ) . Clusters were evaluated internally , based on the primary data , and externally , using PPI and gene ontology ( GO ) databases ( S5 Fig ) . These evaluations confirm that these methods effectively resolve meaningful clusters as previously described [34] . We experimented with different approaches to use these clusters to define signaling pathways active in neuroblastoma . One approach was to apply a “hard” filter , or exclusive approach to identify groups of proteins that co-cluster from two or more dissimilarity representations . This exclusive approach separates groups of proteins that are most likely to define core units of signaling pathways [34] . Alternatively , an inclusive approach treats clusters derived from different embeddings as equally valid and therefore allows overlap between cluster membership . This inclusive approach recognizes that signaling pathways use common effectors . We show results from each of these approaches in turn . For the first , exclusive cluster analysis , we focused on PNCPs and proteins whose phosphorylation pattern was statistically most similar determined by both Euclidean distance and Spearman correlation ( Figs 1 and S6 ) . Heat maps ( Fig 1 and S6 , right ) indicate that the phosphorylation patterns in the primary data are reasonably consistent within each cluster . The RTK , ALK , clustered with two other RTKs ( FGFR1 , PDGFRA ) , activated FYN , and LYN phosphorylated on the C-terminal inhibitory site ( LYN_i; Fig 1A ) . The tyrosine kinase , FAK ( PTK2 ) , and the adaptor molecules BCAR1 , SHC1 and CBLB were included in this group of PNCPs . We also noted other clusters that suggest interactions among phosphorylated tyrosine kinases: IGF1R with LYN , FER , the phosphatase PTPN11/SHP-2 , and the tyrosine kinase TNK2 , whose interactions with other proteins in this group have not been previously characterized ( Fig 1B ) . In addition , we found that EGFR and EPHB3 clustered with inhibited FYN and SRC as well as the SH3 , SH2 containing tyrosine kinase , ABL1 , and MPP5 , a protein with PDZ , SH3 , and guanylate kinase domains whose interactions are not characterized ( Fig 1C ) . Examples of other clusters identified using this hard filter are shown in S6 Fig . These clusters define phosphorylated proteins most commonly phosphorylated together in the same samples in this data set , which suggests possible interactions among signaling proteins that were previously unknown . Assignment of proteins to one cluster should not be viewed as evidence for excluding it from participating in a signaling pathway identified in another cluster , however [34] . An alternative , inclusive approach is to recognize possible relationships defined by different measures of statistical similarity . Clusters derived from t-SNE applied to Spearman , Euclidean , and hybrid Spearman-Euclidean ( SED ) embeddings were typically overlapping but not identical , yet reasonably close in their ability to resolve meaningful clusters as determined by external and internal evaluations ( S5 Fig; [34] ) . This suggests that statistical relationships independently defined by Euclidean distance or Spearman correlation are equally valid . Using this inclusive method that recognizes clusters derived from different embeddings had the advantage that it allows overlap between cluster membership , which makes sense biologically for these data because signaling pathways overlap and converge . We employed the inclusive clustering strategy to filter protein interaction edges to obtain the cluster-filtered network ( CFN ) shown in Fig 2 . In this graph , only edges among proteins that co-clustered based on Spearman , Euclidean , or hybrid Spearman-Euclidean ( SED ) dissimilarity are shown . This CFN data structure is useful because graph layouts that treat edges like springs ( edge-weighted , spring embedded; force-directed ) aggregate proteins that share a statistical relationship and interact with one another , so nearest neighbors are likely to represent functional groups ( regions highlighted in Fig 2 ) . An alternative visualization of data structure is a co-cluster correlation network ( CCCN; S7 Fig ) . In this graph , edges represent positive ( yellow ) or negative ( blue ) correlation , filtered to show only edges among proteins that clustered together and have a Spearman correlation coefficient greater than the absolute value of 0 . 5 . The networks in Figs 2 and S7 are complementary because they apply a different filter to clustering results . Proteins that interact with one another may not tightly correlate , and co-clustered proteins that do tightly correlate may not have been studied previously for evidence of interactions . These filtered networks thus prune cluster members that have no evidence for interaction and do not tightly correlate with others in the group , yet allow potential interactions among pathways to be studied because overlapping cluster membership is defined by different embeddings . Exploration of these networks reveals potential functional interactions among signaling proteins defined by the structure of neuroblastoma phosphoproteomic data . We noted two groups of highly phosphorylated RTKs that clustered together ( Fig 3 ) . Networks in Fig 3 show only positive correlation ( yellow ) and PPI ( grey ) edges between RTKs and co-clustered effector proteins , with proteins that link to three or more receptors grouped in the center of the graphs ( Fig 3 ) . The similarity in phosphorylation patterns for proteins in these groups can be seen in heat maps of the primary data ( S8 Fig ) . Co-clustering of ALK with PDGFRA , FGFR1 , and IGF1R ( through co-clustering with FGFR1 ) is indicative of a collaborative relationship ( Fig 3A ) . Similarly , EGFR co-clusters with PDGFRB , EPHA2 , EPHB3 , and DDR2 ( Fig 3B ) , indicating that these RTKs form a separate collaborative group . While different RTKs within these collaborative groups share a number of co-clustering downstream proteins in common , the only effector proteins in common between these two collaborative groups are PIK3R2 , FYN , and the SFK scaffold protein , PAG1 [51] . The following general conclusions can be made from these analyses so far . Clusters that contain proteins that interact with one another , identified using statistical relationships from phosphoproteomic data , likely indicate functional signaling pathways . New potential interactions are suggested when strong clustering is observed among proteins whose physical interactions have not been previously characterized ( e . g . , TNK2 and MPP5 in Fig 1 ) . Common patterns of phosphorylation in neuroblastoma samples suggests collaboration among RTKs within functional groups ( Fig 3 ) . Since activation of different RTKs was associated with different states of activation and inhibition of different SFKs , particularly FYN and LYN ( Figs 1 and 3 ) , we next examined how stimulation or inhibition of RTKs affected phosphorylation of other tyrosine kinases . RTK activation affects other RTKs , SFKs , and other tyrosine kinases . To examine the effects of RTK stimulation on other tyrosine kinases , we compared phosphoproteomic data from cells treated to influence RTK activity , or not treated , in the same experiment . Fig 4A shows tyrosine kinases whose total phosphorylation changed more than two-fold under experimental conditions where RTKs were stimulated by ligand or ALK was inhibited . For example , NGF treatment caused a more than twofold increase in total phosphorylation of DDR2 , and more than fivefold decrease in phosphorylation of PDGFRA in both LAN-6 and SH-SY5Y cells . EGF treatment of SK-N-BE ( 2 ) cells activated EGFR and stimulated EPHA3 phosphorylation about 3-fold ( Fig 4A ) . These data indicate that stimulation of one RTK affects the phosphorylation state of other RTKs in neuroblastoma cell lines . Changes in inhibitory phosphorylation of LYN and SRC were also observed ( Fig 4A , LYN_i; SRC_i ) , so individual phosphorylation sites on SFKs and other kinases were examined further . Phosphopeptides were assigned to phosphorylation sites based on peptide sequence homology ( see Materials and Methods ) . The data revealed that both activating ( SFK Y411-426 ) and inhibitory ( SFK Y508-531 ) phosphorylation sites on the SFKs LYN , FYN , YES1 , and SRC were significantly affected in different ways by treatments that influence RTK activity ( Fig 4B ) . For example , the LYN inhibitory phosphorylation ( LYN 508 ) was reduced by NGF treatment and increased by EGF treatment . In contrast , FYN inhibitory phosphorylation ( FYN 531 ) was increased by NGF in two cell lines ( Fig 4B ) . These data suggest the hypothesis that activation and inhibition of LYN and FYN distinguishes responses to different RTKs ( Figs 1 and 3 ) . Tyrosine phosphorylation of RTKs is generally thought to be a measure of activation , but differences in different RTK phosphorylation sites were seen in these experiments . For example , NGF treatment both increased and decreased phosphorylation on different sites on EGFR , RET , IGF1R , ALK , and other RTKs in LAN-6 and SH-SY5Y cells ( S9A Fig ) . Some variations in individual phosphorylation site responses to treatments were also observed for other tyrosine kinases ( S9B Fig ) , but they were not as dramatic as those of SFKs ( Fig 4B ) . These data indicate that different RTKs initiate signaling mechanisms to cause distinct phosphorylation patterns on other tyrosine kinases , including RTKs and SFKs . Combined with the clustering patterns shown in Figs 1 and 3 , the data suggest the hypothesis that SFKs , particularly FYN and LYN , discern and integrate signals from different RTKs . We hypothesized that functional interactions among these signaling proteins may occur in specific intracellular locations , namely endosomes and lipid rafts , and therefore we performed phosphoproteomic analyses on these fractions . We asked whether particular signaling proteins were enriched in endosomes and detergent-resistant membranes ( DRMs ) . RTKs are present in endosomes that can be distinguished from other types of receptors by size and density ( S10 Fig ) [32] . Phosphoproteomic analysis was also performed on detergent-resistant and-sensitive fractions distinguished by extraction with non-ionic detergent ( S10 Fig ) [33 , 52] . Endosomes from three neuroblastoma cell lines were characterized by phosphoproteomic analysis . In all endosome fractions from three cell lines ( LAN-6 , SMS-KCN , SK-N-BE ( 2 ) ) , 908 proteins were detected , including 22 RTKs , 10 tyrosine phosphatases; 30 SH2- and 44 SH3-domain-containing proteins . The most highly phosphorylated RTKs in neuroblastoma were those identified in Fig 5A by large yellow nodes that indicates large amounts detected in endosome fractions ( e . g . , DDR2 , ALK , KIT , RET , EGFR , PDGFA , FGFR1 ) . FYN and LYN containing both activating and inhibiting phosphorylations were also prominent in endosomes , along with PAG1 , inhibited SRC ( SRC_i ) , the SH3 adaptor protein BCAR1 , several other adaptor proteins , two tyrosine phosphatases ( PTPN11/SHP-2 and PTPRN ) , and PLCG1/PLCγ1 , which was found previously in endosomes in PC12 cells [53] . Notably , 26 out of the 55 SH3-domain-containing proteins in the human genome that were predicted to have a function in endocytosis based on orthologous interactions in C . elegans were found in neuroblastoma endosome fractions , and 2 of the 55 were detected in lysosome fractions [24] . We asked whether particular phosphorylated proteins were enriched in endosomes and DRMs by calculating the ratio between amounts in those fractions compared to proteins in all other samples from the same cell line . ALK , FGFR1 , RET , PDGFRA , DDR2 , EGFR , and IGF1R were enriched in endosomes from two or more neuroblastoma cell lines , but there were profound differences among cell lines ( Fig 5B ) . In Fig 6 , enrichment was graphed in PPI networks as big yellow nodes for positive enrichment and small blue nodes for de-enrichment ( defined as lower amounts in that fraction compared to elsewhere ) . In LAN-6 cells , most RTKs were enriched in endosomes , except EPHA2 and ROR1 , which were enriched in DRMs ( Fig 6A and 6B ) . In SK-N-BE ( 2 ) cells made to over-express NTRK1/TrkA , this receptor was enriched in endosomes and de-enriched in DRMs , whereas its related receptor , NTRK2/TrkB , had the opposite pattern , being enriched in DRMs and de-enriched in endosomes ( Fig 6C and 6D ) . The SFKs , FYN and LYN were localized differently , with LYN ( and LYN_i ) being enriched in DRMs in LAN-6 and SK-N-BE ( 2 ) cells , and FYN ( and FYN_i ) being enriched in endosomes in LAN-6 cells , but not in SK-N-BE ( 2 ) cells ( Fig 6 ) . PAG1 was enriched in endosomes in LAN-6 cells ( Fig 6A ) and , in contrast , in DRMs in SK-N-BE ( 2 ) cells ( Fig 6D ) . We noted differences in distribution of SFK and PAG1 phosphorylation on individual phosphorylation sites between the two cell lines ( Fig 5C ) . For example , PAG1 81 was consistently phosphorylated in endosomes , and PAG1 317 was consistently phosphorylated in DRMs in both cell lines , yet PAG 359 and other sites were highly phosphorylated in LAN-6 , but not SK-N-BE ( 2 ) endosomes ( Fig 5C ) . These data suggest a relationship between SFK and PAG1 phosphorylation on specific sites and intracellular localization . These data suggest the hypothesis that stimulation of different RTKs should affect the activity and intracellular localization of FYN and LYN . We used a cell fractionation approach to assay intracellular localization after stimulation of ALK with PTN and KIT with SCF ( Fig 7 ) . Amounts of FYN and LYN increased with PTN and SCF treatment in organelles whose migration on velocity sedimentation gradients overlaps with Rab7 and acid phosphatase [32] , markers for late endosomes and lysosomes ( Fig 7A–7D , fractions 4–7 ) . SCF also induced increases mainly in FYN localization to fractions 8–11 ( Fig 7B and 7D ) , which contain endosomes marked by Rab4 and Rab5 [32] . LYN and FYN also increased in fractions 16–22 in response to both ligands ( Fig 7A–7D ) . These fractions contain soluble , cytoplasmic proteins , and signaling particles , which were previously resolved on gradients centrifuged with greater force [52] . FYN and LYN were robustly associated with membranes that floated to the density of endosomes on floatation equilibrium gradients , and amounts increased in organelles of higher sedimentation velocity ( E1 ) after PTN treatment ( Fig 7E ) . Both FYN and LYN were predominantly phosphorylated on their activating sites in these membranes ( Fig 7F ) . Differences between FYN and LYN localization to detergent-resistant and-soluble fractions were also observed . FYN’s response to PTN ( enhanced DRM and diminished P1M association; Fig 7G ) was different from that to SCF ( reduced DRM , enhanced P1M association ) . In contrast , LYN’s response to both ligands was similar ( reduced DRM , increased P1M association; Fig 7G ) . The magnitude of ligand-induced changes in FYN and LYN in organelle fractions were distinct in response to PTN and SCF ( Fig 7H ) . Increased FYN and LYN in faster sedimenting organelles ( lys and E1 fractions ) likely reflects migration to multivesicular bodies , late endosomes , and possibly lysosomes [32] . These data are consistent with the hypothesis that RTK activation regulates FYN and LYN localization and activity in neuroblastoma cells in a manner that distinguishes responses to individual RTKs . These data motivated further higher resolution interrogation of the relationships between individual protein phosphorylation events . We investigated the relationships among phosphorylation sites by clustering phosphorylation sites ( summed from homologous phosphopeptides ) and visualizing data structure as a co-cluster correlation network ( CCCN ) . The edge-weighted , spring-embedded layout of this network showed several distinct groups of sites with statistical relationships to other groups ( S11 Fig ) . The data were interrogated with a focus on the most highly phosphorylated sites on RTKs , SFKs , and PAG1 to ask if phosphorylation sites cluster together . Two distinct clusters are shown in Fig 8 . ALK was detected in 22 distinct phosphopeptides in neuroblastoma samples , which could be collapsed into 13 distinct phosphorylation sites based on sequence homology . Fig 8A shows that the ALK phosphorylation site , ALK 1507 , which was most frequently seen in neuroblastoma samples , was associated with inhibited LYN ( LYN 508 ) , and activated FYN ( FYN 420; LCK 394; SRC 419; YES1 426; this site was assigned to FYN in total phosphorylation calculations because other FYN phosphopeptides were detected in the same samples; see Materials and Methods ) . Co-clustered phosphorylation sites on several other proteins in this cluster resemble the cluster in Fig 1A . Fig 8B shows that other ALK phosphorylation sites ( ALK 1096 and 1604 ) clustered with the most prominently detected phosphorylation site on DDR2 ( DDR2 481 ) , along with activated LYN ( LYN 411 ) , and inhibited FYN and SRC ( FYN 531; YES1 537 and SRC 530 ) . Also co-clustered with the group in Fig 8B were phosphorylation sites from other RTKs represented in the cluster in Fig 1B . Strikingly , a number of phosphorylation sites on PAG1 were detected , but none were statistically clustered with activated FYN and inhibited LYN ( Fig 8A ) , while the most prominent PAG1 phosphorylation sites clustered with activated LYN and inhibited FYN and SRC ( Fig 8B ) . The data suggest a mutually antagonistic relationship between different SFKs , particularly LYN and FYN , so that when one is activated , the other is inhibited . Phosphorylation of PAG1 , which recruits SFKs and their inhibitory kinase , CSK , to bind to it [51] , appears to be associated with the state where LYN is activated , and FYN and other SFKs are inhibited ( Fig 8B ) . The data suggest that RTK phosphorylation does not occur on all sites at once under all conditions , resulting in different phosphorylation sites on ALK and other RTKs clustering separately from one another . RTKs phosphorylated on different sites also fractionated to endosomes and DRMs selectively ( S12 Fig ) . For example , some ALK and KIT phosphorylation sites were enriched in endosomes , while others were enriched in DRMs , with differences between the two cell lines examined ( S12 Fig ) . In contrast , all EGFR and RET phosphopeptides were consistently enriched in endosomes . Phosphorylation on selected sites would be consistent with RTKs acting as effectors as well as initiators of signal transduction . Phosphorylation by other tyrosine kinases , such as other RTKs or SFKs , may favor particular sites , and thus influence intracellular location , providing different contexts for signaling pathways to influence cell responses .
There is considerable interest in tyrosine kinase signaling mechanisms because of their roles in tumor initiation and metastasis . Tyrosine kinase signaling mechanisms arose during evolution when multicellular organisms evolved [19 , 54] , and many RTKs are known to be involved in governing cell behaviors such as cell division , cell death , differentiation , and migration . Acquisition of phosphoproteomic data from a migratory , multipotent tumor cell type was motivated by these considerations . The complexity of the data forced us to develop new approaches to understand signaling mechanisms that involve tyrosine phosphorylation . Indeed , modeling dynamic complex systems and their interacting macromolecules remains a general challenge that lags far behind large-scale acquisition of biological data [35 , 55] . To make progress , we found it useful to apply techniques from the fields of pattern recognition and graph ( network ) theory and combine them with external PPI and GO data [34] , thus extending the concept of using a variety of statistical techniques for exploratory data analysis [56] . Exploratory data analysis is inherently descriptive in its initial stages , but allows generation of hypotheses which then motivates more directed data interrogation and subsequent experiments . In this way , initial phosphoproteomic analysis of neuroblastoma cell lines motivated further experiments where cells were treated to perturb signaling pathways and subjected to organelle fractionation . Several technical hurdles had to be overcome when analyzing these data . 1 ) Phosphoproteomic data , like any mass spectrometry data , has missing values because many peptides are not analyzed by the detector , and using a “data not available” marker ( NA ) instead of zero facilitated calculation of statistical relationships based only on observed data [34] . 2 ) Employing an effective embedding technique [48 , 49] prior to clustering allowed resolution of patterns that were difficult to discern otherwise [34] . 3 ) The analysis treated all samples mathematically as different states in the total neuroblastoma signaling system . Embeddings were first performed on data from cell lysates from 21 neuroblastoma cell lines grown in culture without treatments . Preliminary analysis led to emerging trends in clustering that resembled the more robustly defined clusters derived when all samples were included , including different cell lines , cells treated in ways to perturb signaling pathways , and cell fractions . In fact , we noted different phosphoproteomic results from the same cell lines cultured under nominally similar conditions when grown by different investigators or at different times . This heterogeneity could be due to differences in serum batches , selection pressure by passaging , or other factors . Mathematically , any heterogeneity is useful for statistical analyses because different phosphorylation patterns help distinguish signaling pathways . 4 ) Visualizing data as networks was informative in several ways . Initially , networks that included all PPI edges allowed us to determine that the dataset was complete enough for further analysis ( S1 and S2 Figs ) . However the multitude of known interactions among signaling proteins was too complex to be informative , and not specific to neuroblastoma . Importantly , to visualize data structure in a new and informative way , we developed an innovation that may be generally useful , namely to filter edges to show interactions only between co-clustered components ( CFN , Fig 3; CCCN , S7 and S11 Figs ) . Including clusters from different ( equally valid ) embeddings recognizes that tyrosine kinase signaling pathways are highly interconnected by conveniently allowing overlap in cluster membership . Applying this approach to individual phosphorylation sites ( S11 Fig ) elucidated phosphorylation patterns and relationships among signaling pathways with high resolution . These graphs allowed exploration of data structure using network analysis in a visually accessible graph . We focussed here on PNCPs ( proteins with tyrosine kinase , tyrosine phosphatase , SH2 and SH3 domains ) . Cytoscape-accessible files of these graphs are provided online for investigators interested in exploring the data further S2 Dataset . The observation that neuroblastoma cell lines expressed more than half of the RTKs in the human genome ( S3 Fig ) , and responded to signals from growth factors in the embryonic microenvironment to migrate and differentiate into a number of neural crest target sites ( S4 Fig ) , suggests that neuroblastoma , and neural crest from which it is derived , takes full advantage of RTK signaling mechanisms to govern cell fate decisions . We found functional compartmentalization of tyrosine kinase signaling pathways in neuroblastoma cells from different tumor origins , with different sets of RTKs forming collaborative groups that interact with each other and common downstream effectors ( Fig 3 ) . There was also physical compartmentalization of signaling components within neuroblastoma cells . By combining cell fractionation with phosphoproteomics , we found that there was non-uniform distribution of signaling components , and moreover non-uniform distribution of phosphorylated residues on individual proteins ( Figs 5 , 6 and S12 Fig ) . Compartmentalization of signal-initiating receptors and downstream effectors may be employed to distinguish extracellular instructions that determine cell fate . Many receptors signal from endosomes to amplify signals , activate different effectors than those activated at the plasma membrane , or convey signals to different intracellular locations [30 , 57–61] . In fact , there is evidence that endosomal signaling from a number of different receptors affects cell fate decisions during development [62–66] . Different RTKs elicit different cellular responses , yet all appear to activate the canonical RAS/ERK , PLC-γ , SFK , and PI3K/AKT pathways . Differential responses may be obtained by affecting the duration of downstream effector activation [67] , or by modulating the relative strength of downstream pathway signaling , as has been elegantly shown for the ratio of activation of AKT and ERK pathways that distinguishes the proliferation and neurite-outgrowth ( differentiation ) response in PC12 cells [68] . Our data suggest that SFKs , especially FYN and LYN , function as signal integrating devices—central hubs in the tyrosine kinase signaling network—to distinguish RTK signal transduction pathways , in part by activating distinct mechanisms specifically in endosomes and lipid rafts . FYN and LYN were highly phosphorylated in endosomes and detergent resistant membranes , and their activity and localization was affected by cell type ( Figs 5 and 6 ) and changed in different ways in response to receptor activation ( Fig 7 ) . FYN and LYN appear to have a partially antagonistic relationship because when one is activated , the other is frequently phosphorylated on its C-terminal inhibitory site ( Figs 1 and 8 ) . How localized activation of FYN and LYN may in turn affect the relative strength and duration of effector pathways , or the ratio of activation of AKT and ERK , remains to be determined . Previous work supports the hypothesis that SFKs function to affect signal integration and protein localization . SFK family members are differentially palmitoylated , which affects their localization on endosomes and the plasma membrane [69 , 70] . SFKs have been implicated in the regulation of endocytosis by a variety of mechanisms . These include phosphorylation of clathrin [71] , modification of Rho proteins and actin assembly [69 , 72] , and regulation of the Cbl family of ubiquitin ligases [51 , 73 , 74] , which control RTK sorting in endosomes [75 , 76] . The localization of SFKs to lipid rafts is thought to be important for their signaling function [77] . For example , it has been shown that FYN plays a role in localizing NTRK2/TrkB to lipid rafts [78] , and LYN , which is enriched in lipid rafts ( Fig 6 ) is a key effector of NTRK1/TrkA for terminal differentiation [79] . The transmembrane SFK scaffold protein PAG1 ( Cbp/PAG ) has been previously described to associate with lipid rafts [80] . Consistent with this , we found PAG1 in DRMs ( Figs 5 and 6 ) . PAG1 was also one of the most highly phosphorylated proteins in endosomes ( Figs 5 and 6 ) . PAG1 binds several different SFK family members , and can bind to more than one at a time , as well as to the kinase that phosphorylates the inhibitory site on them , CSK [51] . In fact , PAG1 can form a complex with a number of SFK regulatory proteins in addition to CSK: the phosphatase , PEP , PTPN22 and SOCS1 , which catalyses SFK ubiqutination [51] . PAG1 also binds PLCG1/PLCγ1 and PI 3-kinase; and PLCG1 and PIK3R1/2 were detected in endosome fractions in this study . The phosphatase , PTPN11/SHP-2 , which was also prominently detected in neuroblastoma endosomes ( Fig 5A ) may also be part of this complex [81] . Different patterns of PAG1 and PTPN11 phosphorylation in leukemia and prostate cancer are associated with different activation states of SFKs and other signaling effectors [82 , 83] . This array of proteins bound to the PAG1 scaffold may either positively or negatively regulate SFK activity as well as other effectors , depending on context . Interestingly , we found phosphorylated PAG1 to be clustered with activated LYN and inhibited FYN ( and SRC ) , but not activated FYN and inhibited LYN ( Fig 8 ) . The collaborative groups that emerged from these data ( Fig 3 ) suggest the hypothesis that receptors within these groups might be likely to cause transactivation of other RTKs within the same group . IGFR1 1161 phosphorylation was decreased by the ALK inhibitor on a similar scale to ALK 1507 and 1509 ( S9 Fig ) , which is consistent with the hypothesis that ALK and IGFR1 activities are linked ( Fig 3A ) . The data show substantial variability on different RTK phosphorylation sites , however . When we performed clustering on individual phosphorylation sites ( S1 Fig ) , different phosphorylation sites on ALK and other RTKs clustered separately from one another . For example , ALK 1507 was associated with the group of sites shown in Fig 8A , while ALK 1096 and 1604 was associated with the group in Fig 8B . These phosphorylation patterns may be due to selective phosphorylation or dephosphorylation . Phosphorylation on selected sites would be consistent with RTKs acting as effectors as well as initiators of signal transduction; other tyrosine kinases , such as other RTKs or SFKs , may favor phosphorylation on particular sites . One mechanism of RTK transactivation could involve heterodimerization of different RTKs or multiprotein receptor clusters . Heterodimers have been inferred from co-immunoprecipitation between MET , EGFR , and ERBB3/Her3 [84]; PDGFR and EGFR [85]; AXL and EGFR [86]; and among similar EGFR and FGFR family members [87] . SFKs may also play a role in RTK transactivation [87] . SFK SH2 domains bind to phosphorylated tyrosine residues on RTKs , and can phosphorylate RTKs directly , in some cases mimicking those sites phosphorylated during ligand-induced receptor activation [74] . SFKs associate with RTKs in protein complexes and play a direct role in transducing their signals [74 , 88] . It has been shown that transactivation between PDGFR and EGFR depends on SFKs [85] , and SRC is recruited to PDGFRB and the GPCR , MBTPS1/S1P1 , which form a complex that is endocytosed as a unit [89] . In addition , phosphatases may favor particular sites . For example , the phosphatase , PTPN6/SHP-1 , acts on NTRK1/TrkA , mainly at Y674 and Y675 [90] , and association of PTPN6/SHP-1 with lipid rafts suggests localized dephosphorylation of NTRK1/TrkA [33] . Point mutations in the RTK , ALK , are the primary cause of familial neuroblastoma and account for 8–12% of sporadic neuroblastomas [15] . ALK is expressed earlier than Trks ( NTRK1-3 ) in neural crest development [91] , highly expressed in paravertebral sympathetic ganglia [92] , and co-expressed with NTRK1/TrkA and RET in a subtype of dorsal root ganglia neurons during development [93] . Overexpression of full-length ALK in PC12 cells causes increased phosphorylation of PTPN11/SHP-2 and STAT3 [94] . We found PTPN11 clustered with ALK and IGF1R ( Figs 1B and 3A ) , and localized in endosomes ( Fig 5A ) . STAT3 co-clustered with ALK , IGF1R and PDGFRA as part of the same collaborative group ( Fig 3A ) . That phosphorylated ALK was present in many neuroblastoma cell lines is consistent with its role as an important marker , or driver , of neuroblastoma . Like ALK , KIT is an emerging marker for aggressive neuroblastoma that leads to poor prognosis [95] . We found KIT in a subset of neuroblastoma cell lines , and enriched in endosomes in SK-N-BE ( 2 ) cells ( Figs 6 and S6C ) . Activation of either ALK or KIT caused increased association of FYN and LYN with endosomes ( Fig 7 ) . Both ALK and KIT are expressed early in neural crest , giving rise to the hypothesis that cells derived from an earlier stage of the neural crest sympathoadrenal lineage are more likely to give rise to more aggressive tumors and poor clinical outcome . Sox10+/Kit+ , but not Sox10+/Kit- cells , remain multipotent even after reaching their final target tissue [96 , 97] . Neuroblastoma cells that express high levels of KIT can induce tumors ninefold more efficiently than those with low KIT expression [95] . Interestingly , KIT clustered with ROR1 ( S6C Fig ) , which is also expressed early in development and is a marker for cell migration and invasiveness in neuroblastoma and other cancers [98] . The data suggest that both KIT and ALK may be active early in neural crest development and their activity signifies , or causes , incomplete differentiation . Neurotrophin receptors are of interest in neuroblastoma because they are markers for clinical prognosis . NTRK1/TrkA is a marker for neuroblastoma tumors that spontaneously undergo apoptosis and regression , while NTRK2/TrkB is often expressed with its ligand , ( BDNF ) , forming an autocrine loop that predicts poor prognosis [99–101] . The pan-neurotrophin receptor , p75NTR enhances sensitivity to low neurotrophin levels , which affects response and outcome in NTRK1/2-expressing cells [102] . Overexpression of NTRK1/TrkA in LAN-6 cells caused apoptosis , but was tolerated in SK-N-BE ( 2 ) neuroblastoma cells that express non-functional p53 , in agreement with previous work [103] . The differential localization of NTRK1/TrkA , which preferred endosomes , and NTRK2/TrkB , which was enriched in DRMs ( Fig 6C and 6D ) may provide a clue as to how these two similar receptors have such profoundly different effects in neuroblastoma . Neurotrophin receptors signaling from lipid rafts vs . endosomes may account for the selectivity of their transduced signals and the resulting effects on cell behavior [33 , 104 , 105] . Neuroblastoma cell lines offer insight into neural crest signaling pathways that is difficult to obtain directly from migrating immature neural crest cells . While signaling pathways activated by oncogenic mechanisms and cell culture conditions no doubt contribute to the phosphorylation patterns we identified here , the fact that these cells retained the capacity to migrate and differentiate ( S4 Fig ) indicates that neuroblastoma cell lines retain signaling pathways activated in immature , multipotent neural crest [2 , 4 , 7 , 8] . That neuroblastoma cells express so many RTKs suggests that mechanisms to discern and integrate different receptors’ signals must play a role in cell fate decisions in neural crest and neuroblastoma [106–108] . SFKs , which contain a tyrosine kinase domain , a SH2 domain that recognizes phosphorylated tyrosine , and a SH3 domain that plays a conserved role in endocytosis ( and other ) mechanisms , appear to be constructed for signal integration . The activation and dynamic intracellular location of LYN and FYN , and a scaffold protein ( PAG1 ) that binds to them , suggest that these SFKs function to discern and integrate signals from different RTKs . Discovery of new pathways activated in neuroblastoma cells provides potentially new therapeutic approaches [109] . Co-activation of two or more RTKs , which is not uncommon in cancer , leads to therapeutic challenges that compel consideration of treatment with multiple inhibitors [110–113] . The data and analysis presented here suggest , for example , that ALK-driven tumors might also present activated IGF1R , FGF1R , and/or PDGFRA . When challenged by ALK inhibitor therapy , these receptors could take over as drivers to activate similar signaling pathways ( Fig 3A ) . The data also suggest that there are different routes to cell proliferation in neuroblastoma , such as the distinct mechanisms activated by the EGFR group ( Fig 3B ) , or KIT ( Figs S6C and 7 ) . In the future , it will be important to compare our results to pathways activated in neuroblastoma primary tumors in different microenvironments . This study , and other large-scale gene expression or proteomic studies that include network and pathway analysis [82 , 83 , 114] and gene ontology [115] , will help determine likely control points for cell growth , migration , and differentiation in individual tumors .
21 neuroblastoma cell lines were obtained by Cell Signaling Technology ( Danvers , MA ) from American Type Culture Collection ( ATCC; Manassas , VA ) ; Leibniz Institute DSMZ-German Collection of Microorganisms and Cell Cultures ( DSMZ; Braunschweig Germany ) ; Coriell Institute for Medical Research ( Camden , NJ ) ; and Interlab Cell Line Collection ( ICLC; Genova , Italy ) . SMS-KCN , LAN6 , SK-N-BE ( 2 ) , and SH-SY5Y , were obtained by M . G . from Children’s Hospital of Los Angeles , CA , except for SH-SY5Y cells , which were provided by Dr . Mark Israel ( University of California , San Francisco , CA ) . Neuroblastoma cells were grown in RPMI 1640 medium ( Thermo Scientific HyClone , U . S . ) supplemented with NaHCO3 ( Sigma , U . S . ) and 10% fetal bovine serum ( Thermo Scientific HyClone , U . S . ) . Tyrosine phosphoproteomic data for 21 neuroblastoma cell lines were initially acquired at Cell Signaling Technology using techniques described previously [41 , 42] . Cells were incubated overnight in media without serum prior to harvesting for mass spectrometry . Four cell lines [SH-SY5Y , LAN-6 , SMS-KCN , and SK-N-BE ( 2 ) ] were selected for further studies because of different point mutations in ALK , p53 status , RTK expression , morphology , and growth characteristics . A sub-line of adherent SMS-KCN cells , named SMS-KCN-A , was selected by culturing SMS-KCN cells on collagen coated plates and removing floating cell spheres . SMS-KCN-A cells required trypsin for passage and retained their adherent phenotype after passaging . SK-N-BE ( 2 ) cells were made to overexpress Rat TrkA with CFP insert at amino acid 587 ( in the cytoplasmic tail ) using a γ-retroviral expression vector ( a gift from Mary Beth Eiden , NIH [116] ) . The construct was made using transposon-mediated insertion [117] , and shown to be functional as assayed by NGF-induced tyrosine phosphorylation and neurite outgrowth in PC12nnr5 cells ( in which endogenous TrkA is non-functional ) . The γ-retroviral genomic vector plasmid ( pRT43 . 2TrkCFP ) , helper plasmids ( pIK6 . 1 . gagpol+ATG and pLP-VSVG ) were transfected into HEK293T cells using calcium phosphate . Cell culture media ( Dulbecco’s Modified Eagle Medium/10% FBS ) was changed approximately 16 hours post-transfection . Supernatant containing viral particles was harvested at 48 and 72 hours post-transfection and pooled together . Cell lines were treated ( or left untreated , control ) with ligands or the ALK inhibitor TAE684 as indicated in Table 1 . For organelle fractionation phosphoproteomics , cell lines were treated with ligands ( LAN-6 and TrkA-CFP-expressing SK-N-BE ( 2 ) : NGF , SMS-KCN:BDNF ) for 10 min at 37°C . For cell fractionation experiments after ALK and KIT stimulation ( Fig 7 ) , LAN-6 cells were serum-starved for 2hr , then treated with 50 nM PTN or 5 nM SCF ( R & D Systems ) . Ligands were bound to cells at 4°C for 1 hr , then cells were warmed to 37°C for 10 min or 1 hr . Organelles were isolated from mechanically permeabilized cells using velocity sedimentation only ( Fig 7A–7D ) or velocity sedimentation followed by flotation equilibrium centrifugation as described [32] . Phosphoproteomic analysis was performed on two endosome ( E1 , E2 ) and lysosome ( Lys ) fractions as shown in S10 Fig mass-density plots . In addition , E3 and cytosol ( cyt ) fractions collected from velocity gradients as indicated in Fig 7C were methanol/chloroform precipitated for gel electrophoresis and western blot analysis . Detergent-resistant ( DRM ) and-soluble ( P1M ) fractions were prepared as described [33] except that flotation of detergent-resistant membranes was not performed for mass spectrometry experiments or gel electrophoresis and western blotting . Antibodies used in Fig 7 were from Cell Signaling Technologies ( Danvers , MA ) : anti-LYN ( #2796 ) ;-FYN ( #4023 ) ;-pSRC ( Y416; #2101 ) ;-non-pSRC ( Y416; #2102 ) . HRP-linked secondary antibodies were from GE Healthcare UK Limted: anti-Rabbit HRP ( # NA934V ) ; anti-Mouse HRP ( #NA931V ) . Ligands were from R & D Systems: PTN ( #252-PL ) ; SCF ( #255-SC ) . Quantification of immunoprecipitated phosphopeptides was obtained from the peak intensity of each peptide ( from the MS1 spectrum of the intact peptide before fragmentation for MS/MS analysis ) [41 , 42] . Data were processed using R [118 , 119] . Gene names were mapped and converted to unique gene identifier names ( according to genenames . org ) . In cases where conserved peptide sequences identified multiple proteins , if a protein was identified by a different peptide in the sample , the peptide was assigned to that protein , otherwise the first name was used ( this is referred to as exclusively summed ) . Where phosphorylation sites were known to have inhibitory effect on protein activity ( Regulatory_sites . gz ) , peak intensity values were converted to negative values ( this allows graphing network nodes as blue , as in Fig 1 ) . Peak intensity was summed for each protein in each sample ( i . e . , cell line ) using functions written in R [34] , except in the case of SRC-family kinases ( SFKs ) , where peptides phosphorylated on C-terminal inhibitory sites were tracked separately ( denoted FYN_i , LYN_i , SRC_i , YES1_i , FRK_i ) . Due to limits in mass spectrometry detection , data were not expected to be complete; for example SMS-KCN cells express NTRK2 ( TrkB ) , but NTRK2 peptides were masked; and NTRK1 was not always detected in cell lines known to express it . Therefore , missing values were treated as NA ( data not available ) for statistical calculations [34] . In cases where duplicate mass spectrometry analyses were conducted on the same cell line , under the same conditions within a short time frame ( e . g . , duplicate runs of the same experiment ) , data were merged to include the average of the two runs , ignoring missing values . Otherwise , each experiment was treated as an independent sample for data analysis . Summarized data are available online as Supplemental Data ( S3 Dataset ) . Primary phosphoproteomics data are available from PhosphoSitePlus ( http://www . phosphosite . org/browseDiseaseResultAction . do ? id=66&type=true ) using curation set ( CS ) numbers 1119 , 1121 , 1148 , 1154 , 1157 , 1206 , 1448 , 1613 , 1762 , 1763 , 1764 , 1886 , 1887 , 1888 , 2042 , 2043 , 2044 , 3492 , 3493 , 3495 , 4010 , 4011 , 5180 , 5181 , 5182 , 5269 , 5270 , 5271 , 5272 , 6121 , 6122 , 6123 , 6124 , 6125 , 6151 , 6152 , 6153 , 6154 , 6155 , 9206 , 9208 , 9942 , 9943 , 9944 , 9946 , 10553 , 10554 , 10555 , and 10557 . Supplementary data , and links to spectra and other important experimental parameters from this submission will be also made available via the ‘Reprints , References , Supplemental Tables’ page http://www . phosphosite . org/staticSupp . do . Duplicate MS runs on the same samples in the same experiment were LAN6 . Control ( CS 5269 , 5270 ) ; LAN6 . NGF ( CS 5271 , 5272 ) ; SMSKCN . Control ( CS 3492 , 3493 ) ; SMSKCN . NGF ( CS 3494 , 3495 ) ; SMSKCN . Control ( CS 3549 , 3550 ) ; SMSKCN . BDNF ( CS 3551 , 3552 ) . 1203 tyrosine phosphorylated and 557 AKT-substrate ( using RxRxxS/T consensus sequence antibodies ) proteins were identified in all samples; 138 were in common between phosphotyrosine and phospho-AKT substrate data . For analysis of proteins , the total amount of phosphorylation of each protein was determined by summing peak intensity signals from all peptides for each protein in each sample . In cases where conserved sequences did not allow unambiguous assignment to a particular protein , peptides were assigned to proteins that were detected by other phosphopeptides in the same sample or the first name was used . We thus obtained a data matrix in which each row corresponds to a protein and each column corresponds to a neuroblastoma cell line or organelle fraction ( i . e . a sample; Fig 1 ) . The elements of the data matrix contain the total peak intensity signals . All samples were treated as different states in the neuroblastoma system . To ensure that all samples were weighted equally in statistical calculations , data were normalized by scaling by sample standard deviations without centering . The statistical similarity of any two proteins was determined by the extent to which they were detected in similar amounts in each sample . This relationship was represented in different ways . First , the Euclidean distance between the row vectors corresponding to the two proteins was stored in a distance matrix . A dissimilarity matrix ( also called dissimilarity representation or feature vector ) is similar to a distance matrix except the values do not necessarily specify Euclidean distance [120 , 121] . For the second method , dissimilarity was represented by one minus the absolute value of the Spearman correlation of each protein with every other protein . A third method employed combining equally scaled Euclidean distance and Spearman dissimilarity as a dissimilarity matrix , referred to as Spearman-Euclidean dissimilarity , or SED [34 , 122] . The dimension-reduction ( embedding ) technique , t-distributed stochastic neighbor embedding ( t-SNE ) was employed to visualize the proteins in a scatter plot based on the distance or dissimilarity matrices [34 , 48 , 123] . This machine learning technique aims to represent each protein by a two- ( or three- ) dimensional point , arranging the points in such a way that nearby points in the scatter plot correspond to proteins with statistical similarity and distant points to dissimilar proteins . Proteins close to one another in this data structure were identified as clusters by the minimum spanning tree , single linkage method [50] . Three dimensional embeddings of data structure were visualized with PyMOL and Cytoscape , the latter using RCytoscape and three dimensional manipulation functions from the R package , rgl ( S1 Movie ) . Filters were applied to focus on proteins containing tyrosine kinase , tyrosine phosphatase , SH2 , and SH3 domains ( PNCPs ) , or to focus on proteins that clustered together using both Spearman and Euclidean dissimilarity embeddings [34] . Clusters were evaluated by several quantitative measures . For comparison , 70 non-overlapping random clusters were generated containing gene names from the data set; the number of members was also randomized to mimic the number of genes identified in clusters defined by t-SNE embedding and minimum spanning tree methods . Evaluations based on examining the primary data ( internal evaluations ) were performed as described [34] . A quantitative index was used to evaluate the density of data ( percent NA or missing values ) and the conformity to the pattern in the group , weighted by the total phosphopeptide signal ( S5A and S5B Fig ) . External evaluations with data from PPI ( S5C and S5D Fig ) and GO ( S5E and S5F Fig ) databases were also compared to 20 random clusters [34] . PPI edges from String ( string . embl . de/ ) [124] , GeneMANIA ( genemania . org/ ) [125] , and the kinase-substrate interactions from PhosphoSitePlus ( phosphosite . org ) [126] were merged as described [34] . Network modules or highly interconnected regions of the neuroblastoma phosphoproteomic network ( S2B Fig ) were determined using Cytoscape plugins MCODE and NeMo . Gene Ontology ( GO ) was determined as described [34] . Enriched gene function annotations , or GO terms for gene groups determined by clustering methods , and for the randomly selected genes as described above , were retrieved using Bioconductor libraries “GO . db , ” “GOstats , ” and “org . Hs . eg . db” ( [127] bioconductor . org/ ) using a p-value <0 . 01 . If there was enrichment , at least two genes in the cluster should have the same GO term , so terms with single genes were discarded . The enriched GO terms per gene was compared to the average background for randomly selected genes from the dataset; this background was about one enriched GO term for every three genes [34] . When the number of enriched GO terms is more than five fold over background , this is strong evidence for enrichment [34] . For phosphorylation site analyses , peptide peak intensity values were summed based on sequence homology and phosphorylation site , independent of the presence or absence of oxidized methionine . In cases where conserved sequences did not allow unambiguous assignment to a particular protein , the peptide name either retained multiple names , for example “FYN 420; LCK 394; SRC 419; YES1 426 , ” or were merged into all possible larger peptides , for example MAPKs and C-terminal inhibitory phosphorylations on SRC , FYN , and YES1 ( referred to as inclusively summed ) . Four neuroblastoma cell lines ( LAN6 , SK-N-BE ( 2 ) , SMS-KCN , and SY5Y ) were cultured in 25 μL hanging drops containing approximately 5 , 000 neuroblastoma cells . Cells were transplanted into the neural crest of developing chick embryos to determine if these cells could survive transplantation and subsequently integrate into the migration pathways of the chick neural crest cells . Of the 14 embryos that were injected , 10 survived the transplantation process: three of these were injected with LAN6 cells , two with SK-N-BE ( 2 ) cells , three with SMS-KCN cells , and two with SY5Y cells . Fluorescent imaging of embryo sections showed that all four cell lines were successfully transplanted and could be located within various areas of the embryo with the use of GFP infection with adeno-associated virus that expresses GFP ( AAV-GFP , a gift from Dr . D . Poulsen , University of Montana ) , anti-GFP ( Rockland , Gilbertsville , PA ) , anti-ERGIC ( Alexis Biochemicals , U . S . ) , and fluorescent secondary antibodies ( Alexa Fluor 514 goat anti-mouse and Alexa Fluor 488 chicken anti-rabbit from Invitrogen Molecular Probes , U . S . ) . Further details of embro transplantation methods are provided in S1 Text .
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Neuroblastoma is a childhood cancer for which therapeutic progress has been slow . We analyzed a large number phosphorylated proteins in neuroblastoma cells to discern patterns that indicate functional signal transduction pathways . To analyze the data , we developed novel techniques that resolve data structure and visualize that structure as networks that represent both protein interactions and statistical relationships . We also fractionated neuroblastoma cells to examine the location of signaling proteins in different membrane fractions and organelles . The analysis revealed that signaling pathways are functionally and physically compartmentalized into distinct collaborative groups distinguished by phosphorylation patterns and intracellular localization . We found that two related proteins ( FYN and LYN ) act like central hubs in the tyrosine kinase signaling network that change intracellular localization and activity in response to activation of different receptors .
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[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[] |
2015
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Neuroblastoma Tyrosine Kinase Signaling Networks Involve FYN and LYN in Endosomes and Lipid Rafts
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Thioester-containing protein 1 ( TEP1 ) is a key immune factor that determines mosquito resistance to a wide range of pathogens , including malaria parasites . Here we report a new allele-specific function of TEP1 in male fertility . We demonstrate that during spermatogenesis TEP1 binds to and removes damaged cells through the same complement-like cascade that kills malaria parasites in the mosquito midgut . Further , higher fertility rates are mediated by an allele that renders the mosquito susceptible to Plasmodium . By elucidating the molecular and genetic mechanisms underlying TEP1 function in spermatogenesis , our study suggests that pleiotropic antagonism between reproduction and immunity may shape resistance of mosquito populations to malaria parasites .
Anopheles gambiae mosquitoes are the most efficient vectors of human malaria . Mosquitoes actively respond to Plasmodium infections by mounting immune responses that destroy the majority of invading parasites . These responses are largely mediated by thioester-containing protein 1 ( TEP1 ) [1–4] , a homologue of the mammalian complement factor C3 . TEP1 is synthesized in the mosquito blood cells and is secreted into the blood or hemolymph , where a protein cascade called “mosquito complement-like system” tightly controls its activity . A series of studies on TEP1-mediated killing of Plasmodium parasites demonstrated that a complex of two leucine-rich repeat proteins , leucine-rich immune protein 1 ( LRIM1 ) and Anopheles Plasmodium-responsive leucine-rich protein 1C ( APL1C ) , prevents precocious activation of TEP1 [5 , 6] , whereas heme peroxidase 2 ( HPX2 ) and NADPH oxidase 5 ( NOX5 ) oxidases direct TEP1 binding to Plasmodium by modifying ookinete surfaces [7] . Elimination of any of these factors does not affect TEP1 expression but abolishes its binding to parasites and increases mosquito susceptibility to infections [2 , 7–9] . However , TEP1 function was only examined in the immune responses of females , which are responsible for malaria transmission . Here we report a new function of TEP1 in male fertility . We demonstrate that TEP1 and other members of the complement-like cascade are present in the testes and uncover an allele-specific TEP1 contribution to clearance of apoptotic cells during spermatogenesis . We also show that TEP1 binding to defective sperm cells is regulated by the same complement-like cascade that kills malaria parasites in the mosquito midgut . In spite of these similarities , our results demonstrate that male fertility is promoted by the TEP1*S2 allele , which renders mosquitoes susceptible to Plasmodium infections . By elucidating the molecular and genetic mechanisms underlying TEP1 function in reproduction , our study reveals an example of pleiotropic antagonism between alleles that may impact the genetic makeup of the mosquito resistance to Plasmodium .
Using polyclonal antibodies and confocal microscopy of dissected whole mount testes , we observed TEP1 signal in the spermatogenic compartments of A . gambiae . The mosquito spermatogenic compartments are distinguished by the shape of the sperm nuclei [10] and by the expression pattern of β-tubulin [11] . The apical side of the testes contains a ring of hub cells , the niche of the germline stem cells ( GSC ) and somatic stem cells ( SSC ) . Upon division , GSCs differentiate into the primary spermatogonia . These compartments do not express the β-tubulin gene whose expression begins in the spermatocytes . All sperm cells from the hub to the spermatocytes display rounded nuclei , whereas the nuclei of the spermatids and spermatozoa adopt their mature elongated shape . To facilitate mapping of TEP1-positive cells in the testes , we made use of the DSX transgenic line in which β-tubulin gene promoter directed the expression of green fluorescent protein ( GFP ) reporter in spermatocytes , spermatids , and spermatozoa ( Fig 1A and 1B ) [12] . TEP1 signal was detected on spermatogonia ( round nuclei , no expression of β-tubulin::eGFP , Fig 1C ) and on spermatozoa ( elongated nuclei , expression of β-tubulin::eGFP , Fig 1D and 1E ) . Given this surprising localization , we tested whether TEP1 expression correlates with spermatogonial development , which in mosquitoes is initiated at the larval stages and is completed a couple of days after the emergence of adults [10 , 13] . In Anopheles males , copulation triggers a new wave of spermatogenesis to replenish the ejaculated spermatozoa [10] . Therefore , we monitored the occurrence of TEP1 signal in the testes of virgin males during the first 2 wk after adult emergence and after mating . The percentage of testes with TEP1-positive spermatogonia decreased during the first week after male emergence and correlated with the termination of spermatogenesis ( Fig 1F ) . Consistent with the onset of sperm production , the proportion of testes with TEP1-positive spermatogonia increased after mating ( Fig 1G ) . In contrast , spermatogenesis did not promote the occurrence of TEP1-positive spermatozoa , whose numbers were increasing with time after adult emergence . These data suggest that TEP1 occurrence in the testes correlates with spermatogenic development . As spermatogenesis is accompanied by waves of apoptosis [14 , 15] , we asked whether TEP1 was recruited to defective spermatogonia . To this end , massive sperm damage was experimentally induced in DSX pupae by radiation [10 , 16] . We first gauged the impact of radiation on male fertility and confirmed that it drastically decreased hatching rates of the progeny ( Fig 2A and 2B ) . A significant reduction in egg laying was only observed in females mated with the DSX males irradiated with the highest dose ( 100 Gray [Gy] ) . Further , we observed a significant increase in the proportion of testes with TEP1-positive spermatogonia , which correlated with the reduction in the size of the spermatogonial compartment in 3-d-old irradiated DSX males ( Fig 2C–2E , S1 Fig ) , suggestive of TEP1 recruitment to defective cells . Indeed , radiation significantly increased the number of damaged cells , as measured by TdT-mediated dUTP nick-end labeling ( TUNEL ) , which marks DNA breaks associated with cell death . Interestingly , all TEP1-positive cells in the testes of control and irradiated males were TUNEL positive , but not all TUNEL-positive cells were also stained with the anti-TEP1 antibody ( Fig 2F ) . Moreover , radiation-induced cell damage and TEP1 signal were also detected in the GFP-negative germ-line compartment ( Fig 2G ) . These results suggest that TEP1 is recruited to damaged cells . The specificity of the detected TEP1 signal was confirmed by two independent approaches . First , we used a mosquito transgenic line ( 7b ) in which TEP1 expression is constitutively repressed by a dominant transgene-mediated silencing ( S2 Fig ) . Second , we injected irradiated DSX males with double-stranded RNA ( dsRNA ) against TEP1 1 d after emergence . TEP1 signal was not detected in the testes of irradiated males in both TEP1 depletion methods , confirming signal specificity ( Fig 2H , S2 Fig ) . We next examined whether other members of the complement-like cascade were present in the testes , using polyclonal antibodies against LRIM1 and HPX2 and confocal microscopy . Neither LRIM1 nor HPX2 signals associated with the sperm cells , but they were detected in the cells attached to the testes ( S3 Fig ) . Since elimination of any of these factors does not affect TEP1 expression but abolishes TEP1 binding to parasites [2 , 7–9] , we exploited their silencing to discriminate whether TEP1 is expressed in or bound to the sperm cells . Depletion of either protein abolished TEP1 signal on spermatogonia but did not affect TEP1 expression , as evidenced by a clear TEP1 signal detected by immunoblotting in the hemolymph extracts of males ( Fig 2H , S4 Fig ) , supporting the hypothesis that the observed signal resulted from TEP1 binding to spermatogonia . Taken together , these results demonstrate that the complement-like cascade regulates TEP1 binding to defective sperm . In mammals , complement contributes to the removal of apoptotic cells [17] . Therefore , we examined whether TEP1 binding mediated clearance of defective spermatogonia by comparing the number of TUNEL-positive cells in the testes of control and TEP1-depleted males in a similar genetic background of the F1 progeny of a reciprocal cross between DSX and 7b ( S5 Fig ) . Significantly higher numbers of TUNEL-positive cells were detected in the absence of TEP1 in the testes of freshly emerged males ( Fig 2I , day 1 ) . Furthermore , while irradiation increased the number of damaged cells in all samples , their numbers decreased with time in controls but remained high in TEP1-depleted mosquitoes ( Fig 2I , day 3 ) . These results suggest that TEP1 binding to the spermatogonia correlates with removal of defective cells during spermatogenesis . Based on these results , we proposed that TEP1 marks damaged spermatogonia for removal . Accumulation of dead cells degrades sperm quality [18] . Therefore , we hypothesized that TEP1 deficiency should decrease male fertility after irradiation . Indeed , radiation significantly decreased larval hatching rates ( Fig 3A ) . Importantly , a larger decrease was observed in the progeny of TEP1-depleted males as compared to controls , suggesting that TEP1 partially rescues radiation-induced male sterility . TEP1 is a highly polymorphic gene with four major alleles that differ in their capacity to kill or to resist malaria parasites—namely , the resistance-associated alleles R1 and R2 and the susceptibility-associated alleles S1 and S2 [19–22] . Resistance alleles are believed to offer selective advantages to the mosquitoes infected with Plasmodium; however , the fitness costs of these alleles have not been experimentally tested . To explore the impact of TEP1 polymorphism on the fertility of irradiated males , we generated three S1/S1 , S2/S2 , and R1/R1 homozygous lines from the TEP1-heterozygous T4 line of A . gambiae obtained from Imperial College , London ( S6 Fig ) . Indeed , TEP1 genotyping of this line identified the following frequencies of TEP1 alleles: R1 ( 14% ) , S1 ( 67% ) , and S2 ( 19% ) . To obtain TEP1 homozygous lines , the legs of virgin females and males were used for nested PCR-restriction fragment length polymorphism ( RFLP ) genotyping , and the reciprocal crosses were set up between the selected individuals . Once the TEP1 homozygosity of the established lines was confirmed , male pupae from each line were irradiated , and the testes of the resulting males were dissected , stained , and microscopically examined . Lower numbers of TUNEL-positive cells were observed in the testes of S2/S2 as compared to S1/S1 and R1/R1 males ( Fig 3B ) . Moreover , the progeny of S2/S2 males had higher hatching rates than S1/S1 and R1/R1 irradiated males ( Fig 3C ) . Importantly , no differences were observed between these lines in the absence of radiation . These results suggest that the TEP1*S2 allele efficiently protects against radiation-induced male sterility . To exclude the possibility that the observed differences were caused by variation at an unrelated locus , we generated heterozygous S1 , S2 , and R1 males depleted for TEP1 by crossing TEP1 homozygous males from each of the three lines with 7b females ( S6 Fig ) . Pupae of the resulting progeny were irradiated , and the obtained TEP1-depleted 3-d-old males were crossed with TEP1*S1-homozygous females . Similar sizes of egg batches and egg-hatching rates indicated that TEP1 depletion abrogated fertility advantages of the S2 allele ( Fig 3D ) . Taken together , our results indicate the allele-specific contribution of TEP1 to higher male fertility rates in stressful conditions induced by radiation . We next evaluated whether TEP1 regulated male fertility under normal conditions . The radiation experiments described above were performed with young males ( 3-d-old ) . However , age plays a critical role in male mating behavior and insemination success . Although 3-d-old males are sexually competent , mosquito males show the highest levels of mating activity and form mating swarms several days later ( 7 to 9 d after emergence ) [23 , 24] . Therefore , we compared the fertility of young ( 3-d-old ) and mature ( 9-d-old ) control and TEP1-depleted males . Moderate but significantly lower hatching rates were observed in the progeny of mature but not young TEP1-depleted males as compared to same-age controls ( Fig 4A ) , demonstrating that TEP1 regulates male fertility in the absence of radiation . To make sure that the observed phenotype was due to clearance of damaged sperm cells and not a consequence of microbial infections in TEP1-depleted mosquitoes , we examined bacterial loads in the testes and male accessory glands ( MAGs ) of control and TEP1-depleted 1- and 13-d-old mosquitoes by quantitative PCR of the conserved bacterial 16S rRNA gene . No significant differences between the two groups were detected ( S7 Fig ) , indicating that TEP1 depletion did not cause significant changes in microbiota proliferation in male reproductive tissues that could explain the observed impact of TEP1 depletion on male sterility . To validate the specific contribution of the TEP1*S2 allele to male fertility , we compared the fertility rates of mature males of the TEP1 S1/S1 , S2/S2 , or R1/R1 homozygous lines described above . As in the radiation experiments , significantly higher hatching rates were detected in the progeny of S2/S2 males ( Fig 4B ) . The causative effect of the TEP1 polymorphism was further validated by reciprocal allele-specific RNA interference , which interrogates the effects of allele-specific silencing in an identical genetic background [21] . To this end , we performed reciprocal crosses between R1/R1 and S2/S2 homozygous lines and used males of F1 progeny heterozygous for TEP1 ( S2/R1 ) for injections with allele-specific dsRNAs targeting S2 ( dsS ) or R1 ( dsR ) . Injections of dsLacZ and dsTEP1 served as negative and positive controls , respectively . A significant reduction in the expression of targeted alleles was confirmed by quantitative PCR ( Fig 4C ) . A moderate but significant decrease in hatching rates was detected in the progeny of dsS- and dsTEP1-depleted males ( Fig 4D ) , thereby confirming the role of the S2 allele in male fertility . We noted that the progeny of dsR-injected males displayed reduced hatching rates as compared to control dsLacZ , pointing towards epistatic interactions between TEP1 alleles . Taken together , these data demonstrate the contribution of TEP1*S2 allele to male fertility , thereby raising a possibility of a fitness trade-off between TEP1 alleles in reproduction and immunity .
We discovered a new function of the complement-like cascade in spermatogenesis that impacts male fertility in the malaria mosquito . We demonstrate that depletion of the complement-like factor TEP1 results in accumulation of defective sperm and decreases male fertility . Our study extends the role of the mosquito complement-like cascade from immunity to the removal of defective sperm during spermatogenesis and , thereby , to male fertility and reproduction . We also show that TEP1 function in spermatogenesis is regulated by the same HPX2-LRIM1 axis that controls killing of Plasmodium parasites in the midgut . We propose that activation of the TEP1/LRIM1/APL1C complex is induced by an unknown mechanism in the proximity of the damaged sperm cells . It appears that the surface modification mediated by HPX2 is required for TEP1 binding to the damaged sperm , suggesting that the same signals are used by the mosquitoes to label defective cells and invading pathogens ( S8 Fig ) . This conserved requirement for reactive nitrogen species in the activation of the mosquito complement-like system in immunity and reproduction suggests that nitration through oxidation of cell surface proteins may be a general mechanism of complement activation , which may be relevant for the activation of the alternative complement pathway in mammals ( S8 Fig ) . The role of the complement factor C3 , a mammalian homologue of TEP1 , in the clearance of apoptotic bodies is well documented [17 , 25] . However , C3 deficient mice are fully fertile , and sperm quality is kept in check by a complement-independent mechanism , probably to prevent a deleterious complement activation on self surfaces and gamete damage [26] . Future studies should examine the mechanism ( s ) that mediate ( s ) removal of damaged cells and of invading parasites . In Drosophila , electron microscopy detected traces of the abnormal sperm in the neighboring cells but also inside the macrophage-like cells present in the testis tissues [27] . Although phagocytosis may contribute to the removal of the damaged sperm cells , this process is irrelevant for parasite clearance in the midgut , as no phagocytic cells have been detected by electron microscopy [28] . Previous reports demonstrated the causative role of the R1 allele in mosquito resistance to infections with Plasmodium berghei and with some isolates of P . falciparum [21 , 22 , 29 , 30] . However , low rates of infected mosquitoes in natural populations question the impact of Plasmodium on TEP1 evolution . Given the broad function of TEP1 in immune responses to bacteria and fungi [19 , 31–33] , local microbial pressures on the larval stages may drive its exceptional variability across Africa [22] , a hypothesis that has never been experimentally proven . Here we show that TEP1 affects reproduction at the age when males actively engage in mating , suggesting that our findings are relevant for male fitness in natural mosquito populations . Moreover , we report that in contrast to resistance to Plasmodium , a distinct “susceptible” S2 allele mediates higher male fertility rates . At the structural level , the S2 form of TEP1 is mostly similar to the S1 form , except for a β-hairpin loop , shared with R1 and R2 and located on the convex surface of the thioester domain [34] . The exposed position of this loop is suggestive of its role in protein–protein interactions . Although interactions with distinct partners may define a critical role of S2 form in cell removal , further studies are needed to examine biochemical bases of TEP1 pleiotropism . A recent report demonstrated the role of the mosquito heme peroxidase 15 ( HPX15 ) in long-term female fertility by protecting sperm from oxidative damage during storage in spermathecae [35] . The results presented here uncover the role of the HPX2/TEP1/LRIM1 complement-like cascade in the removal of defective sperm cells in the testes , the process that promotes male fertility rates . As strong selective pressures apply to genes involved in reproduction [36] and male fitness [37] , even the moderate contribution of S2 to male fertility revealed in our experiments may have important consequences for mosquito field populations , as enrichment in S2 alleles may render mosquito populations more susceptible to Plasmodium infections . Taken together , we propose that pleiotropic antagonism may drive the evolution of the TEP1 locus and shape the genetic makeup of resistance to Plasmodium in a major malaria vector .
All work in this study was performed in agreement with national animal work authorization E 67-484-2 issued by the Department of Veterinary Services , Prefecture du Bas-Rhin , France . A . gambiae sensu stricto strain G3 and TEP1 homozygous and transgenic lines originating from it were used throughout the study . Mosquitoes were reared in the insectary at 28 ± 2°C and 80 ± 5% humidity with a 12/12 h dark/light cycle . Larvae were fed with grinded fish food ( Tetra ) , and adults received a 10% sugar solution ( w/v ) . All work in this study was performed in agreement with national animal work authorization E 67-482-2 issued by the Department of Veterinary Services , Prefecture du Bas-Rhin , France . F1 progenies of the reciprocal crosses between DSX and 7b lines were used for experiments with 7b; DSX and wt; DSX males . To obtain 7b/S1 , 7b/S2 , and 7b/R1 heterozygous males , F1 progenies of crosses between 7b females and TEP1*S1/S1 , *S2/S2 , and *R1/R1 homozygous males were used . Males heterozygous for TEP1*S2/R1 were from the F1 progeny of a cross between TEP1*R1/R1 females and TEP1*S2/S2 males . The COPAS instrument ( Union Biometrica ) was used for sexing of the early larval stages [39] . Females and males of DSX , TEP1-homozygous , and 7b lines were raised separately , and 100 males and 50 females were mated in each cross . To identify TEP1 alleles in the mosquito lines used in this study , we used a nested PCR-RFLP . DNA was extracted from one mosquito leg in 40 μl of grinding buffer ( 10 mM Tris-HCl pH 8 . 2; 1 mM EDTA; 25 mM NaCl ) mixed with 0 . 4 μl of 100x Proteinase K ( Sigma ) and incubated for 45 min at 37°C . A first PCR was conducted using VB3 5ʹ-ATGTGGTGAGCAGAATATGG-3ʹ and VB4 5ʹ-ACATCAATTTGCTCCGAGTT-3ʹ primers , followed by a second PCR performed on 2 μl of the resulting product with AG1656 5ʹ-ATCTAATCGACAAAGCTACGAATTT-3ʹ and AG1653 5ʹ-CTTCAGTTGAACGGTGTAGTCGTT-3ʹ primers , producing a final fragment of 764 bp . Both PCR reactions were subjected to 95°C for 2 min , 30 cycles with 15 s at 95°C , 15 s at 55°C , and 45 s at 72°C , and a final step at 72°C for 5 min , using GO Tag Green Master mix ( Promega ) . PCR products were digested by Bam HI , Hind III , or Bse NI ( Fermentas ) and analyzed on 1 . 5% agarose gels . Expected restriction patterns are provided in S1 Table . Genotyping was conducted on 96 males and 96 females from T4 , DSX , 7b , and on each of the TEP1-homozygous and TEP1-heterozygous lines . Verification of TEP1 sequences from homozygous lines was obtained by amplicon sequencing as described [21] using DNA extracts of five different mosquitoes for each line . DNA was extracted using the DNeasy kit ( QIAGEN ) . Sequencing revealed that TEP1*S1 corresponded to the TEP1*S4 allele initially identified in the VKper line , TEP1*S2 to the TEP1*S6 allele from the Ngousso , and TEP1*R1 to the TEP1*R1 from the L3-5 refractory line [21 , 29] . To examine the presence of TEP1 , HPX2 , and LRIM1 , the testes were dissected in 1x PBS , fixed with 2% PFA in 1x PBS for 1 h; permeabilized with 0 . 5% Triton in 1x PBS for 20 min; blocked with 0 . 5% Triton , 1% BSA , in 1x PBS for 30 min; incubated overnight at 4°C with anti-TEP1 ( 1/300 ) [41] , the anti-HPX2 [7] , or anti-LRIM1 [5] polyclonal rabbit antibodies in the blocking solution and then washed with 0 . 5% Triton , 1% BSA , in 1x PBS; and incubated for 2 h with a secondary fluorescence-labeled Cy3 or Cy5 anti-rabbit IgG antibody ( 1/1 , 000 ) ( Jackson Laboratory ) and DAPI ( 1/5 , 000 ) ( Vector Laboratories ) in the blocking solution for 15 min . To reveal DNA damage , the TUNEL assay was performed on TEP1-stained testes dehydrated for 3 h on SuperFrost/Plus slides ( Menzel-Glazer ) using the ApopTag Red In Situ kit ( Millipore ) . To determine TEP1 occurrence in the testes after mating , 2-d-old virgin males were added to a cage containing virgin females , and couples were collected in copula within the first hour . Males were then kept in a separate cage for 2 d . The testes were dissected and assessed for TEP1 presence using anti-TEP1 polyclonal antibodies and immunofluorescence . All samples were mounted in Vectashield medium ( Vector Laboratories ) , examined using a LSM700 laser confocal microscope ( Zeiss ) , and analyzed using Image J open source software [42] with the Figure J package [43] . To determine the presence of TEP1 , LRIM1 , or HPX2 in the hemolymph or the testes , hemolymph samples from ten mosquitoes were collected by proboscis clipping , and the testes extracts were obtained by grinding 20 dissected testes in 10 μl of Laemmli buffer ( Tris-HCl 0 . 35 M; 10 . 3% SDS; 36% glycerol; 5% β-mercaptoethanol; 0 . 012% bromophenol blue ) . Extracts were separated by precast 4%–20% gradient SDS-PAGE ( Bio-Rad ) . Protein membrane transfer , antibody incubations , and detection were carried out , as previously described [41] , using anti-TEP1 [41] ( 1/1 , 000 ) and anti-LRIM1 [5] antibodies ( 1/300 ) , with anti-prophenoloxidase 2 ( PPO2 ) ( 1/15 , 000 ) or anti-α-actin antibody ( 1/1 , 000 ) ( Chemicon ) as loading controls . Immunoblotting of HPX2 was conducted in native conditions as described [7] . Bound antibodies were detected by an anti-rabbit or anti-mouse IgG conjugated to horseradish peroxidase ( 1/30 , 000 ) ( Promega ) using Super Signal West Pico Chemiluminescent Substrate ( Thermo Scientific ) . To deplete TEP1 , LRIM1 , TEP1*S , or TEP1*R , dsRNAs for TEP1 , LRIM1 , LacZ , TEP1*S ( dsS ) , and TEP1*R ( dsR ) were produced from plasmids containing the dsRNA-target sequence flanked by two T7 promoters [5 , 21 , 44] . To deplete HPX2 , dsRNA for HPX2 was produced from PCR-amplified fragments flanked with two T7 promoters as described [7] . RNA synthesis and purification were performed using MegaScript and MegaClear kits ( Ambion ) . RNA concentrations were measured by Nanodrop ( Thermo Scientific ) before annealing 3 μg/μl of sense and anti-sense RNAs by boiling . DsRNAs were injected ( 69 nl ) into the thorax of CO2-immobilized 1-d-old mosquitoes using a glass capillary mounted onto a Nanoject II injector ( Drummond ) . To quantify the mRNA level for TEP1 , LRIM1 , and HPX2 , total RNA was extracted from ten mosquitoes using the RNeasy extraction kit ( QIAGEN ) or RNAzol ( Sigma-Aldrich ) and reverse-transcribed by the M-MuLV Reverse Transcription kit ( Thermo Scientific ) . Gene expression was quantified using primers and probes detailed in S2 Table by quantitative PCR with Fast SybrGreen chemistry for LRIM1 and HPX2 and TaqMan chemistry for TEP1 and RPL19 , using the ABI 7500 Fast Real-Time PCR machine . Expression of RPL19 , the gene encoding housekeeping ribosomal protein L19 , was used for normalization . To induce sperm damage , pupae were subjected to radiation within the first 12 h after pupation using a Biobeam 8000 ( Gamma-Service Medical Research ) . To estimate the impact of TEP1 presence or the TEP1 allele on male fertility , female and male larvae were sexed by the COPAS instrument and raised separately [39] . On day 3 after emergence , 25 virgin females were mixed with 50 virgin males in a cubic 17 cm cage . Females were fed on a mouse 5 d later , and unfed females were removed from the cage . On day 7 , individual females were placed into plastic vials containing 1–2 ml of water and closed with cotton pads . On days 9–10 , the deposited eggs and larvae were counted in each vial . We confirmed that females that did not lay eggs had no sperm in their spermathecae , as previously reported [45] . For fertility assays with mature males , males were kept virgin , and on day 9 after emergence , they were mated to 3-d-old females and assessed as above . Experiments were repeated four times: two independent experiments with two different cages . To examine the effect of TEP1 depletion on bacterial loads in the male sexual organs , control ( T4 ) and TEP1-depleted ( 7b ) larvae were reared in the same water to ensure equal exposure to the environmental microbes . The adults were separated after eclosion based on expression of fluorescent markers . On days 1 and 13 after emergence , the testes and MAGs were dissected from five adults per group , and DNA was extracted using the DNeasy kit ( QIAGEN ) . Bacterial loads were gauged by quantitative PCR of the highly conserved 16S rRNA gene ( S2 Table ) [46] . Three independent biological experiments were conducted . Normalization of the distribution and the homogeneity of variances was evaluated by Shapiro’s and Bartlett’s tests , respectively . To fit normal distribution and homogeneity of variances , larval hatching rates were arcsin square root-transformed before analysis . Statistical analyses were conducted using SYSTAT 12 . 0 ( SYSTAT software ) and R ( http://www . R-project . org ) software .
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While Anopheline mosquitoes are the most efficient vectors of human malaria , they do have protective mechanisms directed against the causative parasite , Plasmodium falciparum . Their immune system targets the invading parasites through activation of the mosquito complement-like system . A central component of this system , thioester-containing protein 1 ( TEP1 ) , is a highly polymorphic gene with four allelic classes . Although one class , called R1 , mediates efficient parasite elimination , the other classes render the mosquitoes susceptible to Plasmodium infections . Until now , it was not clear how or why any of these susceptible TEP1 alleles were maintained in the population . Here we discover a new role of TEP1 in male fertility . We demonstrate that mosquitoes use the same mechanism—nitration of target surfaces—to flag both damaged sperm and Plasmodium cells . Binding of TEP1 to , and removal of , the aberrant sperm is critical to preserve high fertility rates . In the absence of TEP1 , accumulation of damaged sperm degrades male fertility . Surprisingly , in spite of the common mechanism of TEP1 activation , distinct alleles of TEP1 mediate efficient removal of defective sperm and killing of malaria parasites . Our results suggest that pleiotropic function in immunity and reproduction is one of the mechanisms that maintain TEP1 polymorphism in mosquito populations .
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[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Methods"
] |
[] |
2015
|
A New Role of the Mosquito Complement-like Cascade in Male Fertility in Anopheles gambiae
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The visceral endoderm ( VE ) is a simple epithelium that forms the outer layer of the egg-cylinder stage mouse embryo . The anterior visceral endoderm ( AVE ) , a specialised subset of VE cells , is responsible for specifying anterior pattern . AVE cells show a stereotypic migratory behaviour within the VE , which is responsible for correctly orientating the anterior-posterior axis . The epithelial integrity of the VE is maintained during the course of AVE migration , which takes place by intercalation of AVE and other VE cells . Though a continuous epithelial sheet , the VE is characterised by two regions of dramatically different behaviour , one showing robust cell movement and intercalation ( in which the AVE migrates ) and one that is static , with relatively little cell movement and mixing . Little is known about the cellular rearrangements that accommodate and influence the sustained directional movement of subsets of cells ( such as the AVE ) within epithelia like the VE . This study uses an interdisciplinary approach to further our understanding of cell movement in epithelia . Using both wild-type embryos as well as mutants in which AVE migration is abnormal or arrested , we show that AVE migration is specifically linked to changes in cell packing in the VE and an increase in multi-cellular rosette arrangements ( five or more cells meeting at a point ) . To probe the role of rosettes during AVE migration , we develop a mathematical model of cell movement in the VE . To do this , we use a vertex-based model , implemented on an ellipsoidal surface to represent a realistic geometry for the mouse egg-cylinder . The potential for rosette formation is included , along with various junctional rearrangements . Simulations suggest that while rosettes are not essential for AVE migration , they are crucial for the orderliness of this migration observed in embryos . Our simulations are similar to results from transgenic embryos in which Planar Cell Polarity ( PCP ) signalling is disrupted . Such embryos have significantly reduced rosette numbers , altered epithelial packing , and show abnormalities in AVE migration . Our results show that the formation of multi-cellular rosettes in the mouse VE is dependent on normal PCP signalling . Taken together , our model and experimental observations suggest that rosettes in the VE epithelium do not form passively in response to AVE migration . Instead , they are a PCP-dependent arrangement of cells that acts to buffer the disequilibrium in cell packing generated in the VE by AVE migration , enabling AVE cells to migrate in an orderly manner .
Epithelia have structural and functional roles throughout embryonic development and adult life . Their organised , cohesive nature makes them ideal for lining structures and acting as selective barriers . Epithelia show distinct apical-basolateral polarity , with the apical domain characterised by junctional complexes that form tight junctions serving as a barrier to the flow of substances between cells . In addition , adherens junctions extend in a continuous belt around cells and provide structural integrity to epithelia . Many functions associated with epithelia during development , growth , disease , and repair require them to be highly dynamic whilst at the same time maintaining robust structural integrity . Most morphogenetic processes during development therefore involve extensive remodelling of epithelial tissues: branching morphogenesis in the developing kidneys , lungs , and mammary glands; development of sensory organs and ganglia from epithelial placodes; and the formation of the neural tube , to give just a few examples ( reviewed in [1]–[5] ) . The mouse visceral endoderm ( VE ) is an example of a simple epithelium with a critical developmental role . It covers the epiblast and extraembryonic ectoderm ( ExE ) of the egg-cylinder stage mouse embryo . Though the foetus is derived predominantly from the epiblast , it is cells of the VE that are responsible for specifying anterior pattern in the epiblast . The anterior visceral endoderm ( AVE ) , a specialised subset of cells in the VE , is responsible for the correct orientation of the anterior-posterior axis in the mouse embryo ( reviewed in [6]–[9] ) . At around 5½ days post coitum ( dpc ) , cells at the distal tip of the VE differentiate to form the distinct subpopulation of the AVE , characterised by the expression of genetic markers such as Hex , Lefty1 , and Cer-1 [10]–[12] . The AVE migrates proximally in a unidirectional manner and then comes to an abrupt stop at the junction between the epiblast and ExE [13] . From this position , the AVE induces anterior pattern in the underlying epiblast by restricting expression of posterior markers to the opposite side of the epiblast cup [6] , [14] . In mutants such as NodalΔ600/LacZ and Cripto−/− , the AVE is correctly induced at the distal tip of the egg-cylinder but fails to migrate , leading consequently to posterior markers in the epiblast being incorrectly localised . Such embryos show severe gastrulation defects and fail to develop further [15] , [16] . The driving force for AVE migration remains unclear . Dkk1 , a secreted inhibitor of Wnt signalling , is expressed just ahead of migrating AVE cells and has been shown to act as a guidance cue for the AVE [17] . A relatively higher level of cell proliferation in the posterior VE has been suggested to provide the initial displacement of AVE cells towards the anterior and possibly drive their directional migration [12] , however more recent results suggest that the proliferation rate in the posterior VE is not higher than that in other regions of the VE and therefore unlikely to be involved in the movement of AVE cells [18] . Time-lapse microscopy of embryos carrying a Hex-GFP transgene that marks AVE cells shows that they actively migrate over a period of 4–5 h and are extremely dynamic , showing robust protrusive activity in the direction of motion [13] . Once AVE cells reach the border of the ExE , they abruptly cease proximal movement and instead start moving laterally along the boundary , as if in response to a barrier to migration . During this lateral movement , AVE cells show fewer or no protrusions [13] , [19] . Recent reports have shown that the VE retains epithelial integrity during AVE migration [19] , [20] . The tight and adherens junction markers ZO-1 and E-cadherin are present continuously along all cell borders of the entire VE at all stages of migration . In addition , AVE cells must migrate within the plane of the epithelium , rather than on top of other VE cells , because the VE remains a simple epithelium only one cell layer in thickness [13] . It would therefore seem necessary for AVE cells to negotiate their way through the VE without breaking epithelial integrity . This has been verified by time-lapse studies that show that AVE cell migration involves cell intercalation [19] , [20] . Our time-lapse studies of the non-AVE cells of the VE show that the cells just ahead of ( more proximal to ) the migrating AVE show neighbour exchange during AVE migration [20] . Moreover , like the AVE , these cells too are unable to move beyond the boundary with the ExE . VE cells overlying the ExE ( ExE-VE ) show dramatically different behaviour in comparison to VE cells overlying the epiblast ( Epi-VE ) . While the Epi-VE shows robust cell movement and intercalation , the ExE-VE in contrast is relatively static and shows very little cell mixing [20] . The barrier to AVE migration therefore appears to be a region of VE ( the ExE-VE ) that is non-permissive of the cell rearrangements required for AVE migration . These two regions of the VE also show differences in localisation of the molecular motors F-actin and Myosin IIA , and the Planar Cell Polarity ( PCP ) signalling molecules Dishevelled-2 ( Dvl-2 ) and Vangl2 [20] . PCP signalling coordinates cell polarisation and rearrangement across fields of cells in many different contexts , such as the compound-eye and wings of Drosophila , and the mammalian neural tube ( reviewed in [21]–[23] ) . Morphogenetic cell movements in an epithelial context have been extensively studied in the Drosophila wing-disc and germband . Convergent extension movements in the germ band are brought about by junctional remodelling that results in T1-neighbour exchanges [24] and the formation and resolution of multi-cellular rosettes ( five or more cells meeting at a point , Box 1 ) [25] . Germband extension is also characterised by an increase in the anisotropy of cells , initially regularly packed cells becoming increasingly disordered in their packing and shape [26] . Epithelial tissues , including the mouse visceral endoderm , resemble two-dimensional networks of polygons [27] , [28] . Vertex models , in which each cell is represented by a polygon with a limited set of properties , are therefore often used to simulate the tissue-level effects of forces and important cellular processes , such as growth , proliferation , and junctional rearrangements . Rauzi et al . , for example , used a vertex model to show that tissue elongation can be driven by an anisotropy of cortical tension in combination with simple junctional rearrangements [29] . Aegerter-Wilmsen et al . meanwhile found that they were able to reproduce polygonal distributions in the Drosophila imaginal wing disc by including mechanical feedback as a regulator for cellular growth [30] . Several other authors have used vertex models to gain key insights into other biological phenomena [31]–[34] . Using a combination of mathematical modelling and experimental observations , we probe how the broader cell intercalation movements observed in the Epi-VE might influence AVE migration . By examining embryos at various stages of AVE migration and mutant embryos in which migration fails to take place , we show that AVE migration is specifically linked with changes in cell packing in the VE and an increase in multi-cellular rosette arrangements . To explore the role of rosettes during AVE migration , we have developed a mathematical model that simulates cell movements in the VE . This model extends previous vertex models by implementing an ellipsoidal surface to represent a realistic geometry for the mouse embryo . We also include a new type of junctional rearrangement , by allowing close vertices to join together , thus mimicking rosette formation . Simulations in which rosettes are allowed to form closely mimic experimentally observed AVE migratory behaviour . However , simulations in which rosettes are not allowed to form show abnormally disordered AVE migration ( Box 1 ) , suggesting that , while rosettes may not be essential for AVE migration , they are essential for the orderliness to this migration observed in actual embryos . These simulations closely recapitulate results from mutant embryos in which PCP signalling is disrupted and which have significantly reduced rosette numbers . AVE cells are still able to migrate to the anterior in these mutants , but do so in an abnormally dispersed , disordered manner . Our model and experimental observations together lead us to suggest that in the mouse VE , multi-cellular rosettes do not drive cell migration but rather buffer the disruption in cell packing arising from AVE migration , thereby enabling the AVE to migrate in an orderly manner .
To characterise in greater detail the changes in cellular packing in the VE that accompany and possibly influence AVE migration , we visualised apical boundaries of VE cells by staining fixed embryos for the tight junction marker ZO-1 . We captured 3-D confocal image volumes of entire embryos and then opacity-rendered the image stacks . This provided volume renderings of entire embryos , so that the shape of individual cells of the surface VE and the junctions formed between them could be examined in the context of the cylindrical embryo as a whole . These experiments were performed with Hex-GFP transgenic embryos [35] , in which the AVE is marked by GFP fluorescence . In embryos in which the AVE had not yet commenced migration , cells were mostly regular in outline throughout the VE . In contrast , in embryos in which the AVE had migrated anteriorly , Epi-VE cells showed a great variety of shapes and irregular packing , though ExE-VE cells remained relatively regular in shape and packing ( Figure 1A ) . This suggested the observed irregularities in cell shape might be related to the cell rearrangements in the Epi-VE that accompany AVE migration . To quantify the differences in cell shape in the Epi-VE and ExE-VE at different stages of AVE migration , we counted the neighbours for each of the cells of the VE as a measure of the number of sides or polygon number of the cell [30] . Using the opacity renderings of fixed embryos , we manually identified each VE cell , noted whether it was located in the Epi-VE or ExE-VE and the number of cells that shared an edge with it . A hexagonal arrangement of cells ( mean polygon number close to six ) is considered to be the preferred or equilibrium packing of cells in an epithelium , and deviations from this are indicative of increased disequilibrium ( Box 1 ) [26] , [28] . We grouped embryos into four different stages of AVE migration using Hex-GFP fluorescence to determine whether the AVE had been induced and to what degree it had migrated . “Pre-AVE” embryos were those in which the AVE had not yet been induced . “Distal” embryos had the AVE induced at the distal tip , but it had not yet started migrating . In “migrating” embryos , the AVE was in the process of migrating , and in “anterior” embryos the AVE had reached the boundary of the ExE-VE ( the proximal limit to migration ) and was starting to spread laterally . We compared polygon numbers in the ExE-VE and Epi-VE within each stage and found that in “pre-AVE” and “distal” embryos , the difference between mean polygon numbers in these two regions was not significant ( p>0 . 07 , Student's t test ) . However , in “migrating” and “anterior” embryos , the mean polygon number in the Epi-VE was significantly lower than that in the respective ExE-VE ( p<0 . 002 , Student's t test ) ( Figure 1B ) . We compared polygon numbers across the different stages , and found no significant difference in the mean in the ExE-VE of the four stages ( p = 0 . 25 , ANOVA ) . However , there was a significant difference in the mean polygon numbers among the Epi-VE of the four stages ( p = 0 . 0007 , ANOVA ) . In pair-wise comparisons , the mean polygon number of the Epi-VE of “migrating” and “anterior” embryos were both significantly lower than that of the Epi-VE of “distal” embryos ( p = 0 . 02 , Student's t test ) ( Figure 1B′ ) . We next determined the frequency of the different polygon numbers in the Epi-VE and ExE-VE at the four stages in development . As with the mean polygon number , in “pre-AVE” and “distal” embryos , the distribution of polygon numbers in the Epi-VE was not significantly different from that in the respective ExE-VE ( p>0 . 4 , Kolmogorov-Smirnov test ) ( Figure S1A and B ) . By contrast , in “migrating” and “anterior” embryos , the distribution of polygon numbers in the Epi-VE was significantly different to that in the respective ExE-VE ( p<0 . 02 , Kolmogorov-Smirnov test ) , with a relatively higher proportion of four-sided cells ( Figure S1C and D ) . We compared polygon number frequencies in the Epi-VE across the four stages and found that it was not significantly different between “pre-AVE” and “distal” embryos ( p = 0 . 5 , Kolmogorov-Smirnov test ) ( Figure S2A ) . However , as with the mean polygon number , the frequencies of polygon numbers in the Epi-VE of both “migrating” and “anterior” embryos was significantly different from that in the Epi-VE of “distal” embryos ( p<0 . 05 , Kolmogorov-Smirnov test ) ( Figure S2B , C , and H ) . The Epi-VE of “migrating” and “anterior” embryos showed an increase in the proportion of four-sided cells at the expense of five- and six-sided cells as compared to “distal” embryos ( Figure S2H ) , which would explain the significant reduction in mean polygon number in the Epi-VE of these stages . The change we see in cell packing in the VE is localised to the region to which AVE migration is restricted ( the Epi-VE ) and to the stages during which AVE cells migrate ( “migrating” and “anterior” ) . To verify if the change in packing of Epi-VE cells is linked specifically to AVE migration ( as opposed , for instance , to the developmental stage of embryos ) , we examined NodalΔ600/lacZ and Cripto−/− embryos , two mutants in which the AVE is correctly specified but fails to migrate . Embryos comparable to “anterior” stage wild-type embryos in size ( p = 0 . 41 , ANOVA ) and shape ( Figure S3 ) were dissected at 5 . 75 dpc and their polygon numbers determined . We found that VE cell packing in both NodalΔ600/lacZ and Cripto−/− embryos was more similar to that in “distal” embryos than to that in “anterior” embryos . In contrast to “anterior” embryos ( but similar to “distal” embryos ) , neither NodalΔ600/lacZ nor Cripto−/− embryos showed a significant difference in mean polygon number between their Epi-VE and respective ExE-VE ( p>0 . 18 , Student's t test ) ( Figure 1B ) . The frequencies of polygon numbers in the two regions were also similar ( p>0 . 21 , Kolmogorov-Smirnov test ) ( Figure S1E and F ) . Furthermore , when compared to the Epi-VE of “distal” embryos the Epi-VE of NodalΔ600/lacZ and Cripto−/− embryos did not show a significant difference in mean polygon number ( p>0 . 34 , Student's t test ) ( Figure 1B′ ) or frequencies of polygon numbers ( p>0 . 38 , Kolmogorov-Smirnov test ) ( Figure S2D , E , and H ) . When compared to the Epi-VE of “anterior” embryos , the Epi-VE of stage-matched NodalΔ600/lacZ and Cripto−/− embryos did show a significant difference in mean polygon number ( p<0 . 02 , Student's t test ) ( Figure 1B′ ) and frequencies of polygon numbers ( p<0 . 03 , Kolmogorov-Smirnov test ) ( Figure S2F , G , and H ) . Both mutants had a lower proportion of four-sided cells and higher proportion of six-sided cells as compared to “migrating” and “anterior” embryos ( Figure S2H ) . These data all point to a specific link between AVE migration and changes in cell packing in the Epi-VE . To confirm this is indeed the case , we determined the polygon number of VE cells in living embryos undergoing AVE migration . We visualised cell outlines in the VE of cultured embryos by differential interference contrast ( DIC ) time-lapse microscopy . Embryos were transgenic for Hex-GFP , enabling us to monitor AVE migration . We captured images from five focal planes at each time-point so cell outlines could be visualised unambiguously . We imaged embryos every 15 minutes to achieve sufficient time-resolution to follow individual cells from one time-point to the next . Due to the strong curvature of the surface of the embryo , only a relatively small portion of the surface VE could be viewed in focus . We analysed five embryos , in which we tracked a total of 31 Epi-VE and 28 ExE-VE cells during AVE migration , over an average period of 4 hours . We then compared the mean polygon number of these cells at the start of the experiment ( when the AVE was at the distal tip of the embryo ) with the mean polygon number of the same cells at the end of the experiment ( when the AVE was in the process of migrating ) . The mean polygon number of the tracked Epi-VE cells was significantly lower during AVE migration compared to before the AVE had started migrating ( p = 0 . 036 , Student's t test on paired samples ) ( Figure 1C ) . The change in the mean polygon number of the “control” ExE-VE cells tracked during this same period was not significant ( p = 0 . 238 , Student's t test on paired samples ) . These results , together with the results from fixed wild-type and mutant embryos , strongly suggest migration of AVE cells is specifically accompanied by a reduction in mean polygon number in the Epi-VE and a shift away from the equilibrium cell packing arrangement . Renderings of the VE surface revealed a variety of junctions between cells . In addition to junctions where three cells meet at a point ( typical of idealised hexagonal arrays of cells ) , we also frequently observed four-cell junctions and five or more VE cells meeting at a central point to form rosette arrangements ( Figure 2A ) . Rosettes typically comprised between five and seven cells , occasionally with one or two cells contributing to two distinct rosettes ( Figure 2B ) . The majority of cells involved in rosettes were non-Hex-GFP expressing , though 8% of rosettes also included Hex-GFP cells ( n = 51 rosettes ) . Examination of confocal sections and segmentation of rosettes to separately render individual cells in the context of the surrounding VE confirmed that rosettes are comprised of a single layer of cells , with all cells of the rosettes in contact with the epiblast ( Movie S1 ) . Multi-cellular rosettes are characteristic intermediaries of long-range coordinated cell rearrangements during germband extension in Drosophila [25] . Together with the fundamental mechanism of T1 neighbour exchange [24] , they are understood to drive convergent extension movements in the germband . To determine what role rosettes might play in the context of the mouse VE where no such convergent extension movements have been reported , we quantified rosette numbers in fixed embryos . As with our analysis of polygon numbers , we categorised embryos into four groups: “pre-AVE , ” in which the AVE had not yet been induced; “distal , ” in which the VE was at the distal tip , prior to migration; “migrating , ” where the AVE was in the process of migration; and “anterior , ” in which the AVE had reached the endpoint to proximal migration and had started moving laterally . We manually scored multi-cellular rosettes in opacity renderings of ZO-1 stained embryos for each category . To correct for any differences in the number of cells in the VE present and able to contribute to rosette formation , we divided the number of rosettes by the total number of VE cells for that embryo . We refer to this value as the rosette “density . ” The average rosette density was then calculated for each group . Average rosette density was significantly different across the four groups ( p = 0 . 025 , ANOVA ) . We found a progressive increase in rosette density from “pre-AVE” to “distal” to “migrating” stages ( Figure 3A ) . “Migrating” embryos had a significantly higher rosette density than “distal” and “pre-AVE” embryos ( p<0 . 05 , Student's t test ) . Rosettes' density decreased slightly from “migrating” to “anterior” stages , but not in a significant manner ( p = 0 . 14 , Student's t test ) . The significant increase in rosette density during AVE migration suggests that rosette formation might be linked specifically to AVE migration . To confirm that this is indeed the case , we assessed rosette numbers in a double blind manner in NodalΔ600/lacZ and Cripto−/− embryos , two mutants in which the AVE is correctly specified but fails to migrate [15] , [16] . Embryos were dissected at 5 . 75 dpc , comparable to “anterior” stage wild-type embryos in size ( Figure 3A′ , p = 0 . 90 , ANOVA ) and shape ( Figure S3 ) and rosette numbers determined . Mutants of both lines showed a significant reduction in rosette density when compared to both “anterior” and “migrating” stage embryos ( Figure 3A ) ( p<0 . 01 , Student's t test ) . Both mutants had a significant reduction in the average number of rosettes ( Figure 3A′ ) , leading to the observed reduction in rosette density . To determine if rosettes are restricted to any one region of the VE , we plotted their distribution with respect to the future anterior and the boundary between the epiblast and ExE . Rosettes showed a strong bias in distribution with respect to the boundary between the epiblast and ExE , being located almost exclusively in the Epi-VE , the region to which AVE cell migration is restricted . Within the Epi-VE , they did not show any bias in distribution with respect to the presumptive anterior ( Figure 3B ) . Rosette numbers increase during AVE migration ( Figure 3A′ ) , suggesting they are not static features of the VE . They are found predominantly in the Epi-VE , which is characterised by cell mixing [20] . To determine if rosettes in the mouse VE form by cell movement ( as opposed , for example , to stereotypic patterns of cell division , or apoptosis of one cell drawing surrounding cells into a central point ) , we visualised cell outlines in the VE of cultured Hex-GFP embryos by DIC time-lapse microscopy . As before , we captured images from five focal planes at each time-point so cell outlines could be visualised unambiguously , and with a 15-minute time-lapse to achieve sufficient time-resolution to follow individual cells from one time-point to the next . Again , due to the strong curvature of the surface of the embryo , only a relatively small portion of the surface VE could be viewed in focus . In five embryos that remained in focus and in the field of view continuously for between 2 and 7 hours , we recorded a total of five rosettes forming—one rosette in each of three embryos and two rosettes in a fourth embryo . All these rosettes formed as a result of VE cells intercalating so that five or more cells met at a single central point to form a rosette . We did not observe apoptosis or cell division leading to rosette formation in any of these embryos . Cell tracking confirmed that in forming rosettes , cells that initially were not in contact with one another became neighbours ( Figure 4 and Movies S2 and S3 ) . Consistent with the distribution of rosettes in fixed embryos , we observed rosettes forming only in the Epi-VE . We did not observe any rosettes resolving in our time-lapse recordings , suggesting that if they do resolve , it is on much longer time scales to their formation . We quantified rosettes in opacity renderings of ZO-1 stained 6 . 5 dpc embryos , approximately 20 hours after AVE migration , and found that while overall rosette density was significantly lower compared to “anterior” embryos , the average number of rosettes per embryo was significantly higher ( Figure S4 ) . Our experimental observations show that AVE migration is accompanied by a decrease in mean polygon number in the Epi-VE and an increase in the number of rosettes . To explore possible roles for rosettes , we created a mathematical model that represents AVE migration within the mouse VE . A critical feature of the model is the ability to adjust the number of rosettes that form during migration simulations by changing a single parameter . We are thus able to observe how varying rosette numbers affects the emergent migration behaviour , whilst keeping all other parameters constant . Such computational experiments were intended to demonstrate whether rosettes are an important part of the migration process , or merely coincidental . We have recently described a 2-D version of such a model [36] . In our model , the apical surfaces of cells of the VE are represented by polygons lying on the surface of an ellipsoid . The polygonal representation is an abstraction of the cell shapes observed in vivo and captures key features such as edge- and neighbour-numbers . This framework is one of a class of cell-based models , including , for example , the cellular Potts model [37] and the cell-centre model [38] . Of these models , the vertex representation is the most appropriate in the context of AVE migration as it permits the explicit modelling of junctional rearrangements including rosette formation . The numerous forces acting on each cell in vivo are encapsulated by tension and pressure forces acting on the vertices of the polygonal cells . The directions in which these forces act in two-dimensions are shown in Figure 5A . To extrapolate to a three-dimensional ellipsoid , the forces act tangentially to the surface at each vertex ( Figure 5B ) . Each cell also has a volume that is able to change over time . The cell's height along the apical-basal axis can be inferred by dividing the volume by apical surface area . The equation for the tension force acting on a vertex due to one of the cells to which it belongs is given by:where CL and CP are constants , lc and la are the lengths of the clockwise and anti-clockwise edges , respectively , and p is the length of the cell perimeter ( Figure 5B , C ) . The pressure force equation , meanwhile , is given by:where CA , CH , and CD are constants , a is the cell area , at is a target area , H is the height-to-area ratio , θ is the average internal angle of the cell ( θ = π ( s−2 ) /s for an s-sided polygon ) , is the internal angle at the current vertex ( see Figure 5A ) , and n1 . and n2 are integers . We note that the exact form of the force equations does not affect the qualitative behaviour of our simulations . More information about the tension and pressure force equations can be found in Text S1 . By summing the contributions to the total force from each cell , an equation of motion for each vertex can be formulated . In this type of biological system , viscous forces dominate , and we therefore make the simplifying assumption that inertial forces can be neglected . The only additional parameter in the equations of motions is thus a viscosity parameter . The equation of motion for a vertex i is given by:where μi is the viscous coefficient , xi is the vertex position , and Fi is the sum of all forces acting on the vertex . The equations are solved iteratively , with vertices free to move anywhere in 3-D space . In vivo the cells of the VE adhere to the epiblast and extra-embryonic ectoderm below , maintaining the shape of the embryo . To simulate this restoring force , vertices are therefore projected back to the ellipsoid during each iteration ( Figure 5D ) . The time-step in our simulations is kept sufficiently small so that this projection is small relative to the movement of the vertices . In vivo , cells in the Epi-VE are highly labile relative to those of the ExE-VE [20] . To simulate this fact , we adjust the relative viscosity of the vertices in each half of the ellipsoid . A higher viscosity μ in the ExE-VE ensures that movement is more restricted in the proximal half of the embryo . In this way we are able to simulate the barrier to migration that occurs at the junction between the Epi-VE and ExE-VE . Alongside the standard vertex movements driven by the forces described above , two types of junctional rearrangement have been observed experimentally , and are therefore included in the model . The first is a T1 transition , which has been used in many previous vertex models ( e . g . Weliky and Oster [31] , Farhadifar [32] ) . Secondly , an edge whose length falls below a certain threshold is allowed to contract to a single point , with the vertices at the ends of the edge joining together . Rosettes of various sizes occur when several neighbouring edges contract in succession . This is a key process in the model , allowing the effect of rosettes on migration to be investigated . The number of rosettes can be controlled by adjusting the threshold length at which vertices join together . Increasing the threshold leads to more rearrangements , while decreasing it leads to fewer rearrangements . During AVE migration in vivo , cells grow in volume and proliferate , and the size of the embryo increases . In order for our model to be realistic it is important to include these processes . Each cell is assigned an initial volume , which grows logistically over time . Cell division is implemented stochastically , based on the ratio of cell volume to some target ( see Text S1 for details ) . To simulate the concurrent increase in embryo size , the ellipsoid itself is allowed to grow over time . This requires an adjustment of the equations for the projection of vertices back to the ellipsoid surface ( see Text S1 for details ) . The radius of the ellipsoid grows linearly , and over the course of migration increases by approximately 10% , in agreement with experimental observations . We designate a subset of cells at the distal tip of our ellipsoid to be the AVE and induce them to migrate by adjusting the forces acting on their vertices ( Figure 5D ) . This is achieved in practice by increasing the pressure force at one or more of the proximal-most vertices of each migrating cell . Increasing this force causes those vertices to move , which in turn affects the properties of the cell and results in the whole cell moving proximally . In reality migrating cells show protrusions in the direction of cell movement that can be several cell diameters long [13] , [19] . Our migration force can therefore be thought of as the reaction of the main body of the cell to the directional cues provided by the protrusions . We initially simulated AVE migration with the vertex-joining threshold set at a level that allowed rosettes to form at a similar density to that observed experimentally . The AVE cells migrated in a manner similar to that seen in embryos , as an orderly , coherent group of cells . It was also found that cells ahead of the AVE were pushed against the ExE-VE forming a “crescent” shape very similar to that observed in embryos ( Figure 6A , C and Movie S4 ) . To further test if our simulations were reasonable representations of experimental observations , we quantified polygon numbers both early and late in simulation ( roughly equivalent to “distal” and “anterior” embryos , respectively ) . As in cultured wild-type embryos , during simulations the Epi-VE underwent a significant reduction in mean polygon number ( p<0 . 001 , Student's t test ) ( Figure 5E ) . We also compared the frequency of different polygon numbers in the simulations . Similar to our observations in embryos , there was a significant shift in the frequencies of polygon numbers in the Epi-VE late in simulation as compared to early in simulations ( p<0 . 001 , Kolmogorov-Smirnov test ) ( Figure 5F ) , with a marked increase in the proportion of four-sided cells at the expense of six-sided cells . Simulations were then run with a small vertex-joining threshold distance , thereby reducing the number of rosettes that form . All other parameters were kept constant . In this case AVE cells were able to migrate round the surface of the ellipsoid to the boundary with the ExE-VE , but in a dispersed manner not normally observed in embryos ( Figure 6B and Movie S4 ) . In these simulations the AVE breaks up into several clumps of cells with non-AVE cells between them , rather than maintaining its structure as a single coherent group . The simulations suggest that the formation of rosette arrangements in the VE during AVE migration is required for the normal , orderly migration of AVE cells . PCP signalling coordinates cell polarisation and rearrangement across fields of cells in a variety of contexts . PCP signalling is disrupted in the ROSA26Lyn-Celsr1 mouse line [20] . To determine if rosette formation is perturbed in these mutants , we quantified them in mutant embryos dissected at 5 . 75 dpc , a stage comparable to the wild-type “anterior” group . Mutants had a significantly reduced rosette density when compared to “anterior” embryos ( p<0 . 05 , Student's t test ) ( Figure 7A ) . ROSA26Lyn-Celsr1 embryos are similar in size to “anterior” embryos and the reduction in rosette density is the result of a significant reduction in the average number of rosettes per embryo ( p<0 . 001 , Student's t test ) ( Figure 7A′ ) . The AVE migrates in ROSA26Lyn-Celsr1 mutants , but in the majority of cases ( six out of eight embryos ) was abnormally dispersed , in a manner reminiscent of simulations in our model when rosettes were not allowed to form ( Figures 7B–C and 6B ) . These mutants also show a variety of other AVE migration abnormalities such as unilateral whorls or migration into the ExE-VE [20] . We determined the polygon numbers of VE cells in ROSA26Lyn-Celsr1embryos . As with wild-type “anterior” embryos , the mean polygon number was significantly lower in the Epi-VE compared to the ExE-VE ( p<0 . 001 , Student's t test ) ( Figure 7D ) . Similarly , the frequency of polygon numbers in the ExE-VE and Epi-VE was found to be significantly different ( p≤0 . 001 , Kolmogorov-Smirnov test ) ( Figure S1G ) . Interestingly , when compared to the Epi-VE of wild-type “anterior” embryos , the polygon number in the Epi-VE of ROSA26Lyn-Celsr1 embryos was significantly lower ( p<0 . 05 , Student's t test ) ( Figure 7D ) , suggesting that there was increased disequilibrium in Epi-VE cell packing in the absence of rosettes .
Prior to AVE migration , the distribution of cell polygon number is comparable in the Epi-VE and ExE-VE , with a peak between five and six sides . This distribution is different from the equilibrium distribution reported by Gibson et al . for a variety of metazoan epithelia that have a distinct peak at six-sided cells [28] . One possible explanation for this difference is that while the epithelia considered by Gibson et al . are all relatively flat ( Drosophila wing imaginal disc , Xenopus tail epidermis , and Hydra external epidermis ) , the mouse VE is very highly curved with an average of fewer than 20 cells around a circumference of about 300 microns . This is likely to impose different constraints on the packing of cells in the VE when compared to other epithelia . During AVE migration stages , mean polygon number drops and polygon distribution shifts towards three- and four-sided cells , but only in the Epi-VE ( Figure 1B , B′ , and Figure S2H ) . The ExE-VE in contrast does not show so marked a reduction in mean polygon number . This is consistent with time-lapse data which show that the Epi-VE and ExE-VE are distinct in their behaviour , the former undergoing a great deal of cell mixing with cells continuously changing shape , while the latter is relatively static [20] . A specific link between AVE migration and changes in epithelial topology is reinforced by NodalΔ600/lacZ and Cripto−/− embryos in which the AVE fails to migrate and in which the mean polygon number in the Epi-VE remains close to that in wild-type embryos in which the AVE has not yet started migrating ( Figure 1B and B′ ) . A reduction in mean polygon number is also observed in the Epi-VE of cultured embryos , where the same set of VE cells is monitored during AVE migration . This indicates that the reduction in mean polygon number is due at least in part to dynamic changes in the packing of existing VE cells taking place on the time scale of 4 hours rather than , for example , new cells with fewer cell edges arising through division . Again , the change in polygon number is restricted to Epi-VE cells , consistent with this being the region that is behaviourally labile and to which AVE cell migration is restricted [20] . These findings suggest that during AVE migration the Epi-VE is in a state of increased disequilibrium with respect to cell packing . We observe multi-cellular rosettes in the Epi-VE , a striking conformation of cells that deviates greatly from the hexagonal packing considered to be the equilibrium arrangement of cells in epithelia . In the Drosophila germband , rosettes have been shown to be transient intermediaries of the long-range coordinated cell movements of convergent-extension [25] . There are , however , no convergent-extension movements in the mouse VE and rosettes appear to play a different role in this context . The significant increase in rosettes during AVE migration in wild-type embryos and the reduction in rosettes in mutants with a failure of AVE migration point to a specific role for rosettes in AVE migration ( Figure 3A ) . This is further supported by the observation that rosettes are predominantly found in the Epi-VE , the region of the VE to which AVE migration is restricted . However , rosettes are not restricted to the anterior region of the Epi-VE but more or less evenly distributed throughout the Epi-VE ( Figure 3B ) , with only a minority of rosettes ( 8% ) including any Hex-GFP positive AVE cells . This suggests that rosettes are not involved specifically in driving AVE cell movement or determining the direction in which they migrate , but play a more general role in the Epi-VE during AVE migration . Our mathematical model predicts that rosettes are essential for ordered migration , in which the AVE cells migrate as a coherent group . When simulations are run with fewer rosettes , AVE migration still takes place , but in an abnormally dispersed manner . It is only when rosettes are allowed to form that AVE migration is much more orderly and closely resembles that seen in actual embryos . This is confirmed by experiments using ROSA26Lyn-Celsr1 mutant embryos in which PCP signalling is disrupted [20] and significantly fewer rosettes are formed . Such embryos exhibit AVE migration but in an abnormally disordered fashion . Rosettes in the mouse VE are therefore not essential to drive AVE migration ( in the sense they are understood to contribute to convergent extension in the Drosophila germ band ) , but appear to have the subtler role of modulating AVE migration so that it occurs in a stereotypic , orderly manner . AVE cells have been shown to migrate in response to a directional cue from Dkk1 [17] . AVE cells migrate within an intact epithelial sheet by cell intercalation [19] , [20] . It is not only AVE cells that show this intercalatory behaviour , but also other surrounding cells in the Epi-VE [20] . This suggests that intercalation among AVE and non-AVE cells in the Epi-VE needs to be coordinated , to allow AVE cells to “negotiate” their way through a field of Epi-VE cells to arrive at the prospective anterior . Our time-lapse experiments show that rosettes form as a result of cell intercalation and that the majority of cells participating in rosettes , though in the Epi-VE , are not AVE cells . PCP signalling is active in the Epi-VE and influences AVE migration [20] . When PCP signalling is disrupted , there are significantly fewer rosettes though the AVE still migrates ( albeit abnormally ) , suggesting that rosette formation is not a passive response to AVE migration but is actively dependent on PCP signalling . We interpret these results to suggest the following working model of AVE migration . Though AVE cells migrate in response to an extrinsic guidance cue , since they have to migrate through an intact epithelium , this movement has to be achieved through cell intercalation that has to be coordinated between the migrating AVE cells and surrounding non-AVE cells . We suggest that the role of PCP signalling in the Epi-VE is to coordinate this intercalation , at least in part via the formation of rosettes . We suggest rosettes facilitate orderly AVE migration by buffering the increased disequilibrium in cell packing in the Epi-VE accompanying the directional movement of AVE cells . Consistent with this view , after AVE migration the mean polygon number in embryos with disrupted PCP signalling is significantly lower than that in the Epi-VE of equivalent stage wild-type embryos , indicative of increased epithelial disequilibrium in the absence of rosettes . How might rosette formation buffer the disequilibrium of cell packing in the Epi-VE ? One possibility is that it allows non-AVE cells to group together and behave as a single unit , which in some way makes it easier for AVE cells to migrate through the VE epithelium . Though we observe several rosettes forming in time-lapse experiments , we do not observe any rosettes resolving . This suggests either that once formed they are relatively static features or that they resolve over different time-scales than those over which they form . Rosette density in 6 . 5 dpc embryos ( approximately 20 hours after AVE migration ) is significantly lower than that in “anterior” embryos , but this is due to the significant increase in size of embryos between these two stages rather than to a reduction in the number of rosettes . A total of 6 . 5 dpc embryos have a significantly higher average number of rosettes per embryo as compared to “anterior” embryos ( Figure S4 ) , consistent with the notion that rosettes formed during AVE migration might accumulate over time rather than resolve . A detailed study of the dynamics of rosettes will help address how precisely rosettes aid in the orderly migration of AVE cells , the mechanistic basis for their formation , and clarify whether they resolve . Recent developments in high resolution , low photo-damaging imaging technology such as light sheet microscopy [39] , [40] now make it feasible to monitor cell movements on the surface of the cylindrical embryo over extended time-scales and will help resolve these issues . In contrast to convergent-extension movements where all cells undergo a coordinated medio-lateral intercalation leading to tissue elongation , during AVE migration a subset of cells migrates directionally within a larger field of cells that undergoes cell rearrangement without extensive changes to the overall shape of the epithelium . Since the VE is arranged as a cylinder , it provides an appropriate model for the study of cell movements in other epithelia on elongated curved surfaces , such as lung buds , ureteric buds , or developing intestinal villi . Our mathematical model of cell movements in the VE , in combination with experimental intervention , provides a powerful tool for the study of directed cell movements within epithelia . It is built on simple assumptions , incorporating forces acting upon cells , cell division , directional movement of a subset of cells , a behavioural “barrier” to migration , and the ability of cells to rearrange to form rosettes . Although the cells in our model have volume and height , they are not fully 3-D , in the sense that forces act only on apical surfaces , and there is no consideration of the fact that neighbouring cells might be at different heights . As further biological data are obtained , 3-D vertex models such as that of Honda et al . [41] may become desirable in exploring the cellular dynamics of epithelia such as the VE . However , representing the tissue as a 2-D sheet as we have currently done has proved informative in exploring the role of rosettes . From just the starting conditions of our model , behaviour emerges in simulations similar to that observed experimentally—for example , the formation of a “crescent” where cells ahead of the AVE are pushed against the ExE-VE , the reduction in mean polygon number during migration , and the abnormally broad and disordered migration of AVE cells when rosettes are not allowed to form . This emergent behaviour reinforces the potential of our model as a tool in probing cell migration in the VE and other epithelia .
Genetically modified mice were maintained on a mixed C57Bl/6 CBA/J background . The Hex-GFP line was bred into the various mutant backgrounds to enable the AVE to be followed . Embryos carrying the Hex-GFP transgene were obtained by crossing homozygous Hex-GFP studs with CD1 females ( Charles River ) . All mice were maintained on a 12 hour light , 12 hour dark cycle . Noon on the day of finding a vaginal plug was designated 0 . 5 dpc . Embryos of the appropriate stage were dissected in M2 medium ( Sigma ) with fine forceps and tungsten needles . Secondary only controls were done to verify the specificity of secondary antibodies . Embryos were fixed in 4% PFA in PBS at 4°C for 30 minutes; washed at room-temperature thrice for 5 minutes each in 0 . 1% Triton-X100 in PBS ( PBT ) ; incubated in 0 . 25% Triton-X100 in PBS for 15 minutes; washed thrice in PBT; blocked with 2 . 5% donkey serum , 2 . 5% goat serum , and 3% Bovine Serum Albumin ( BSA ) in PBT for 1 hour; incubated overnight at 4°C in primary antibodies diluted in 100 µl PBT; washed five times in PBT for 5 minutes each , with a final additional wash for 20 minutes; incubated at room temperature in the appropriate secondary diluted in 100 µl PBT for 2 hours or overnight; washed in PBT five times for 5 minutes and once for 15 minutes; and finally mounted with Vectashield mounting media containing DAPI ( Vector Labs H-1200 ) . Antibodies used were: Rabbit anti-ZO-1 ( Zymed laboratories 61-7300 ) 1∶100 and Alexa Fluor 555 donkey anti-rabbit IgG ( Invitrogen A-31572 ) . Fixed samples were imaged on Zeiss LSM 510META and Zeiss LSM 710 confocal microscopes using 20×/0 . 75NA or 40×/1 . 2NA lenses as appropriate . DAPI was excited at 405 nm , EGFP at 488 nm , and Alexa Fluor 555 at 543 nm . Z-stacks of entire embryos were acquired at a 0 . 8 µm interval using non-saturating scan parameters . Z-stacks of embryos were opacity rendered as 3-D volumes using Volocity Software ( Improvision , UK ) . Figures were prepared with Adobe CS2 Photoshop and Illustrator ( Adobe Inc ) . Opacity rendered views of embryos were rotated through 360° , printed out , and the polygon number of each cell determined manually as the number of neighbours it had . Each cell was given a unique reference number to avoid being counted twice . Data were tabulated in Microsoft Excel and Apple Numbers 2009 . Statistical analysis was performed using SPSS Statistics 17 . 0 and Apple Numbers 2009 . Culture media consisted of 50% home-made heat-inactivated mouse serum and 50% CMRL ( Invitrogen ) supplemented with L-glutamine , equilibrated at 37°C and 5% CO2 for at least 2 hours prior to imaging . Embryos were transferred into the pre-equilibrated media in Lab-TekII Coverglass bottomed eight-well rectangular chambers ( Nalge Nunc International ) and imaged for up to 8 hours on an inverted Zeiss 710 confocal microscope equipped with an environmental chamber to maintain conditions of 37°C and 5% CO2 . Embryos were imaged with a water immersion 40×/1 . 2 NA objective every 15 minutes . At every time point , a Z-stack of five focal planes separated by 10 . 78 µm was captured . EGFP marking AVE cells was excited at 488 nm and DIC images were acquired with the confocal's transmitted light PMT . Antibody stained confocal imaged embryos were recovered from slides; washed in syringe filtered PBT thrice for 5 minutes; washed in lysis buffer ( 50 mM Tris HCl pH 8–8 . 5 , 1 mM EDTA , 0 . 5% Tween-20 ) for 5 minutes; transferred into PCR strips containing lysis buffer ( 16 µl for 5 . 5 dpc embryos ) and Proteinase K ( 1 µl 20 mg/ml PK per 25 µl of embryo lysis buffer ) ; lysed at 55°C for 1 hour; and the Proteinase K inactivated by incubating at 95°C for 10 minutes . PCR genotyping was performed using 3 µl of lysed embryo as template , the appropriate primers , and Illustra PuReTaq Ready-To-Go PCR Beads ( GE Healthcare Catalogue No . 27-9557-01 ( 0 . 2 ml tubes/plate 96 ) ) . Cripto mutants were identified by their failure of AVE migration phenotype . Primers for ROSA26Lyn-Celsr1: R1: 5′AAAGTCGCTCTGAGTTGTTAT3′; R2: 5′GCGAAGAGTTTGTCCTCAACC3′; R3: 5′GGAGCGGGAGAAATGGATATG3′ . Bands expected: 250 bp mutant ( R1+R2 ) and 500 bp ( R1+R3 ) . Primers for NodallacZ: LacZ-5: 5′CCGCGCTGTACTGGAGGCTGAAG3′; LacZ-3: 5′ATACTGCACCGGGCGGGAAGGAT3′; A: 5′ATGTGGACGTGACCGGACAGAACT3′; B: 5′CTGGATGTAGGCATGGTTGGTAGGAT3′ . Bands expected: 750 bp mutant and 700 bp . Primers for NodalΔ600: Δ600-5: 5′GCTAGTGGCGCGATCGGAATGGA3′; Δ600-6: 5′AAGGGAAGTGAACTGGAAAGGTATGT3′ . Bands expected: 350 bp mutant and 950 bp .
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The mouse visceral endoderm ( VE ) is a simple epithelium in the egg cylinder stage mouse embryo . Many functions associated with epithelia require them to undergo extensive remodelling through changes in the shape and relative positions of constituent cells , a process about which we understand relatively little . The anterior visceral endoderm ( AVE ) is a specialized group of cells in the simple epithelium of the VE , and their stereotypic migratory behaviour is essential for establishing the orientation of the anterior-posterior axis in the early mouse embryo . We show that AVE migration is linked to changes in cell packing in the VE and an increase in “rosettes , ” which are striking collections of five or more cells meeting at a central point . To probe the role of rosettes during AVE migration , we have developed a mathematical model of cell movement in the VE . Simulations suggest that rosettes are not essential for AVE migration , but are crucial for the orderliness of this migration . We also explored the role of Planar Cell Polarity ( PCP ) signalling , which is known to coordinate cell polarization and rearrangement in many different tissues . We find that mutants in which PCP signalling is disrupted have fewer rosettes , altered epithelial packing , and abnormal AVE migration . We suggest that rosettes in the mouse VE are a PCP-dependent arrangement of cells that act to buffer the disturbances in cell packing generated by AVE migration , thereby enabling AVE cells to migrate in an orderly manner .
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[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"animal",
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"developmental",
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2012
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Multi-Cellular Rosettes in the Mouse Visceral Endoderm Facilitate the Ordered Migration of Anterior Visceral Endoderm Cells
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As Arabidopsis thaliana is increasingly employed in evolutionary and ecological studies , it is essential to understand patterns of natural genetic variation and the forces that shape them . Previous work focusing mostly on global and regional scales has demonstrated the importance of historical events such as long-distance migration and colonization . Far less is known about the role of contemporary factors or environmental heterogeneity in generating diversity patterns at local scales . We sampled 1 , 005 individuals from 77 closely spaced stands in diverse settings around Tübingen , Germany . A set of 436 SNP markers was used to characterize genome-wide patterns of relatedness and recombination . Neighboring genotypes often shared mosaic blocks of alternating marker identity and divergence . We detected recent outcrossing as well as stretches of residual heterozygosity in largely homozygous recombinants . As has been observed for several other selfing species , there was considerable heterogeneity among sites in diversity and outcrossing , with rural stands exhibiting greater diversity and heterozygosity than urban stands . Fine-scale spatial structure was evident as well . Within stands , spatial structure correlated negatively with observed heterozygosity , suggesting that the high homozygosity of natural A . thaliana may be partially attributable to nearest-neighbor mating of related individuals . The large number of markers and extensive local sampling employed here afforded unusual power to characterize local genetic patterns . Contemporary processes such as ongoing outcrossing play an important role in determining distribution of genetic diversity at this scale . Local “outcrossing hotspots” appear to reshuffle genetic information at surprising rates , while other stands contribute comparatively little . Our findings have important implications for sampling and interpreting diversity among A . thaliana accessions .
Gaining a detailed understanding of Arabidopsis thaliana in its native context is becoming especially important as this species is increasingly employed as a model in studies of adaptation and evolution [1] , [2] . Arabidopsis thaliana is an annual herb that exists in the wild in fragmented populations throughout much of the northern hemisphere . It is self-compatible and wild populations are highly homozygous – average outcrossing rates have been estimated in the range of 0 . 3 to 2 . 5% [e . g . , [3]–[6]] . A large body of literature on the population genetics of self-fertilizing plants established already decades ago that self-fertilizing species often exhibit strong local differentiation of individual stands and that stands are often not genetically homogeneous [e . g . , [7]–[15]] . Numerous studies published since have also demonstrated a tendency for high heterogeneity in measures of genetic diversity and heterozygosity among stands [9] , [16] . This pattern has been observed many times and is generally stronger in self-fertilizing than outcrossing species [16] . Differences in diversity or heterozygosity that correlated with specific habitat characteristics have been documented in several systems , one example being higher outcrossing in mesic than xeric sites [e . g . , [7] , [8] , [15]] . Genetic variation in A . thaliana follows the same basic patterns as other self-fertilizing species , but the molecular resources and extensive sampling available in A . thaliana have allowed a much more fine-grained analysis of these patterns . Like other selfers , A . thaliana does not exist exclusively in monotypic stands , and it is not completely selfing in the wild [e . g . , [6] , [17]–[20]] . Nevertheless , even neighboring stands are often strongly differentiated , suggesting low inter-population migration rates and limited dispersal distances [e . g . , [4] , [21] , [22]] . Several studies have uncovered considerable variability among stands in genetic diversity and/or heterozygosity [e . g . , [19] , [21]–[23]] . The observation that at least some wild A . thaliana stands may be quite transient supports the idea that rapid turnover could contribute to patterns of strong local differentiation and high prevalence of genetically depauperate stands [21] . However , this would be complicated by the presence of a seed bank , which could buffer the effects of population turnover [24] . Population genetic patterns of A . thaliana have been investigated at varying geographic scales [25] . Several recent studies have provided evidence of range-wide population structure [e . g . , [18] , [26]–[28]] , indicative of historical processes such as recolonization from different ice-age refugia , or opportunities that appeared with the spread of human agriculture [26] , [28] . These results are also consistent with the view that contemporary gene flow and migration are sufficiently low , at least at large geographic scales , to give rise to an overall pattern of isolation by distance [18] , [27] , [29] , [30] . Nevertheless , linkage disequilibrium ( LD ) in A . thaliana is generally quite low , indicating that recombination , even if rare , is sufficient to break nonrandom allele associations at a species-wide level [31] , [32] . A similar trend has been observed in wild barley [33] . Extensive chromosomal stretches of haplotype identity in some pairwise comparisons within regions indicate that outcrossing among local types generates genetic novelty in A . thaliana by recombining pre-existing haplotypes [18] . Local populations can be strongly differentiated even when they are geographically close [4] , [21] , [22] and variability in diversity has been found among stands [5] , [6] , [20] , [22] . Despite considerable advances in knowledge of local populations , few studies have sampled extensively from adjacent sites , and none of the previous studies has included a network of numerous local stands to specifically examine micro-geographic genetic structure . Compared to our understanding of larger-scale patterns , we know much less about how contemporary processes such as outcrossing impact local population structure in A . thaliana . Furthermore , few studies have addressed how heterogeneous environments might affect genetic patterns at a fine geographic scale in this species . Such information is a crucial prerequisite for studies of local adaptation , and it is particularly important in view of the resources that are being invested in using A . thaliana for genome-wide association studies [31] and large-scale sequencing efforts [34] . We examined local-scale population genetic patterns in 77 A . thaliana stands distributed in a restricted region around Tübingen , in Southwestern Germany . We sampled over one thousand individuals from stands varying in size and ecological setting , and genotyped progeny with 436 intermediate-frequency single nucleotide polymorphism ( SNP ) markers distributed across the genome [35] . This large number of markers and extensive local sampling provided a uniquely detailed picture of patterns of relatedness and heterozygosity , and the scale at which these patterns are evident in the landscape . Finally , we revisited several stands one year later , to address how replicable the sampling would be and whether similar genotypes persist within local stands over multiple years , or whether migration or germination from seed banks might infuse novel variation .
From April to June 2007 , we sampled A . thaliana within an area comprising approximately 460 square kilometers in the Neckar river valley around the town of Tübingen in Southwestern Germany ( Figure 1 , Table S1 ) . We collected seeds from 1 , 005 individuals from 77 stands . We defined a stand as a single cluster of plants separated from other groups by at least 35 meters . This threshold was used because it was the lowest distance that we observed between clearly distinct groups without any intervening plants . Though it is possible in some cases for pollen of selfing plants to travel further than this distance [e . g . , [36]] , we observed very strong differentiation among most neighboring stands , even when they were very closely spaced , and thus kept them separate in further analyses . We refer to the physical locations of stands as “sites . ” Across the entire region , pairwise physical distance between sampled stands ranged from 35 m to 40 km , with the most isolated stand being 16 km from its closest sampled neighbor . The average distance of stands to their closest sampled neighbor was 1 . 7 km . Stands varied considerably in size , from one or a few individuals to thousands of plants . Where stands consisted of fewer than 20 individuals , we sampled all plants present . For stands larger than 20 , we sampled 20 to 30 individuals . The individual collection sites had a range of different physical characteristics , and covered examples with high human impact in urban settings , as well as sites in rural environments in meadows and field borders with less ongoing human influence . In meadow sites , the presence of A . thaliana plants was often associated with vole or mole activity , suggesting that the small mounds of upheaved or cleared earth produced by these animals provide sufficient disturbed ground to support A . thaliana in otherwise highly competitive meadow environments . Stands varied considerably in the number of genotypes found . Twenty-three of the 77 stands ( 30% ) were monotypic , that is all individuals sampled were identical at all 436 markers . The remaining 56 stands each contained two or more distinct types . While there was a general trend for stands with only a single genotype to be smaller than stands with two or more genotypes ( average 12 . 2 vs . 17 . 3 individuals; p = 0 . 047 ) , some larger stands were also monotypic and many small stands contained multiple genotypes ( Table S1 ) . Among stands with ten or more individuals , 18% were monotypic , and of those with 20 or more plants , 15% were monotypic . Stands with multiple genotypes differed along a continuum in the prevalence of each of the distinct types: at the extremes , some stands were dominated by one or a few common genotypes , while others were made up of many rare genotypes ( Table S1 , Table S2 ) . Consistent with this , there was considerable variation among sites for genetic diversity ( see below ) . Overall , we identified 324 unique multi-locus genotypes , of which 247 were fully homozygous . Since naturally occurring A . thaliana stands varied considerably in size , we asked whether this might affect genetic diversity or observed heterozygosity . Unsurprisingly , the number of plants sampled in a stand correlated significantly with the number of distinct genotypes identified ( correlation = 0 . 46 , p = 0 . 0002 , r2 = 0 . 21 ) . However , several other parameters were not strongly correlated with stand size , including genetic diversity measured as He ( r = 0 . 166 , p = 0 . 21 ) or 1-Q ( r = 0 . 044 , p = 0 . 74 ) . Even correlation with observed heterozygosity was weak ( r = −0 . 26 , p = 0 . 085 ) . Any trends were primarily due to smaller stands: For 39 stands containing ten or more individuals , the relationship between stand size and He ( r = 0 . 026 , p = 0 . 870 ) , 1-Q ( r = 0 . 04 , p = 0 . 822 ) , and observed heterozygosity ( r = −0 . 14 , p = 0 . 424 ) were very weak . Therefore , for further analyses of stand diversity and heterozygosity , we used only this subset . Despite the lack of strong correlations between stand size and population parameters , we could not exclude that sample size differences could affect estimates of diversity and heterozygosity [37] . Thus , in order to make genetic parameters of populations more directly comparable and to compensate for variation in sample sizes , we employed a sub-sampling approach ( see Materials and Methods; Table S3 ) . Both He and the inbreeding statistic FIS were variable among populations . He ranged from 0 for monotypic stands to 0 . 318 for He ( Table S3 , Figure S1 ) . Average FIS across the whole dataset was 0 . 969 ( ±0 . 0001 ) indicating an overall effective outcrossing rate of 1 . 6% for the entire Tübingen area . This is well within the range of previous estimates , which ranged from 0 . 3 to 2 . 5% [e . g . , [3] , [4] , [6]] . The average value obscures considerable heterogeneity among stands . Most stands in our dataset ( 64% ) had no evidence of outcrossing , whereas others had estimated effective outcrossing rates considerably higher than what has been previously reported for A . thaliana ( Table S3 , Figure S1 ) . The TuHO stand had a particularly low FIS ( 0 . 69 ) but this was due to a single outcrossed individual in a stand that had otherwise almost no diversity ( Table S3 ) . The lowest FIS among the remaining stands was 0 . 75 , which reflects considerable heterozygosity compared with most other stands , and translates to an estimated effective outcrossing rate of 14 . 5% ( Table S3 ) . High variation in diversity and heterozygosity as we observed here is consistent with what has been reported for other self-compatible species [e . g . , [10] , [13]] . Variation in genetic diversity has also been reported in other studies of A . thaliana [e . g . , [19] , [21]–[23]] . Since marker heterozygosity indicated recent outcrossing , we examined the distribution of SNP differences and heterozygosity across the genome in more detail , to obtain direct evidence of recombination among resident genotypes . Our high marker density , with on average one marker per 250 kb , gave us good power to uncover footprints of past or ongoing recombination . When comparing SNP genotypes of two unrelated individuals , or related genotypes individuals descended from a common ancestor without recombination ( diverging purely by mutation ) , allele differences should be randomly distributed across the genome . In the majority of pairwise comparisons of genotypes between stands in our dataset , this was indeed what we observed ( data not shown ) . This was also often true of pairwise comparisons of distinct types within stands , particularly in genetically simple stands with a small number of predominant homozygous genotypes . However , pairwise comparisons of genotypes in some stands revealed patterns of allele sharing in mosaic blocks of identical and diverged sequence ( Figure S2 ) . This pattern is suggestive of a history of outcrossing and recombination followed by self-fertilization . Indeed , in two stands , Ey and Obn , all of the numerous distinct genotypes detected at each locale could be attributed to different combinations of only two ancestral genotypes ( Figure S2A ) . Hence , these stands were effectively natural recombinant inbred lines . Some continued gene exchange among recombined types within each stand was evident in varying degrees of heterozygosity in individuals . The existence of distinct fully homozygous recombinant genotypes suggests that these stands have been stable for numerous generations and that the descendants of ancestral outcrossing events continue to populate these sites . In addition to historical recombination and introgression events , in some stands we observed extended stretches of linked heterozygous SNPs . We found 77 such individuals ( 7 . 7% of our entire sample ) , which were unevenly distributed among stands . Forty-nine stands ( 64% ) had no heterozygotes at all , while some of the remaining 28 stands had numerous heterozygotes , and others had just one or two ( Table S1 ) . In some cases putative parental genotypes were identified in the same stand , and patterns of relatedness and heterozygosity indicated both historic and ongoing genetic exchange in these stands ( Figure 2 ) . There was some evidence of pollen flow among stands: In some cases we could not identify the pollen parent of a particular heterozygote within a sample , and in one instance we found a plant in the TüPK stand that had been pollinated by a type not detected in TüPK , but identical to one that dominated the TüV stand 75 meters away . Emphasizing the power afforded by the large number of SNPs we used , some outcrossing events would almost certainly have gone unnoticed with a smaller marker set: For example , two distinct genotypes found in the Müh stand were nearly identical , differing at only four out of the 436 SNPs , yet we found in this stand an outcrossed individual that was heterozygous for all four of these SNPs . In some stands we found indications that spatial structure might affect the patterns of observed heterozygosity . The Erg stand , which we sampled at roughly one-meter intervals along an approximately 30 meter transect , was dominated on each side by a distinct genotype . Where the two genotype clusters met , we identified two individual progeny that were heterozygous for all SNPs differentiating the two dominant homozygous types ( Figure 2 , Figure S3 ) . A similar pattern occurred in the Bai stand ( Figure S3 ) . Bai and Erg represent what may be comparatively young stands , and may be examples of an early stage in the formation of more diverse stands with mixed haplotype blocks of the sort we observed elsewhere ( Figure S2 ) . Because in both Erg and Bai genotypes seemed to be non-randomly distributed , we examined ten other stands where samples had been collected in order . Several were spatially structured . Stands with fewer genotypes tended to show stronger clustering of identical genotypes , but even in genetically diverse stands , identical genotypes were preferentially found in close proximity to one another ( Figure S3 ) . The degree of genotype clustering , particularly the proportion of individuals flanked by two identical neighbors , was correlated with FIS , ( r = 0 . 48; p = 0 . 098; Figure S3B ) . Though the relationship was not statistically significant at ∝ = 0 . 05 , this trend nevertheless suggests that spatial structure within stands may impact observed heterozygosity in natural stands of A . thaliana ( e . g . , the Wahlund effect [38] ) . Overall , even closely spaced stands were very strongly differentiated . In only one instance were neighboring stands genetically identical: TüNR consisted of two small stands that were 120 meters apart , but together contained only a single genotype . Otherwise , very few genotypes were shared among stands: In only 15 cases did we find genotypes identical at all 436 markers in different stands ( Table S4 ) . This is compatible with low migration rates and/or failure of single multi-locus genotypes to persist for extended times . Eleven of the shared genotype pairs ( 73% ) originated from stands that were near one another ( 50 meters to 1 . 2 kilometers apart ) . For example , TüKB and TüV , 220 meters apart , differed in only one rare genotype unique to the TüV stand . TüV and TüPK , 75 meters apart , shared one multi-locus genotype out of the eight present in these two stands together . The remaining four cases of individuals with identical multilocus genotypes shared between stands were found further apart , from seven to 21 kilometers , suggesting that on rare occasions longer distance dispersal occurs . Among these four cases , two involve stands ( Erg and GE ) located on sites with recent road construction activity , hinting at a possible human element in movement of genotypes . Though formally possible , the likelihood that identical combinations of such a large number of intermediate-frequency markers distributed across all five chromosomes could arise by processes other than maintenance of ancestral types or migration of contemporary types is extremely unlikely . Similar haplotypes that could independently form identical genotypes through anything but a very large number of recombination events were not found in this dataset . Thus we conclude that identical genotypes almost certainly arose from dispersal or from persistence of ancient types . Many closely spaced stands , some as little as 35 meters apart , shared no identical genotypes , suggesting that despite their proximity , these sites were probably independently colonized and have experienced little or no gene flow . For example , the stands Tü-SB25/Tü-SB30 ( 55 meters apart ) , HaP , HaP2 and Ha3 ( 35 to 150 meters apart ) , Fell2/Fell3 and KBG1/KBG2 ( each 110 meters apart ) and Bach1/Bach2 ( 260 meters apart ) did not share any multi-locus genotype . The few neighboring stands that did share whole-genome genotypes were all located in urban areas where dispersal by forces such as wind or tracking by humans may be more common than in more heavily vegetated rural areas . Genetic differentiation between stands can be quantified by the fixation index , FST . Within the Tübingen region , pairwise FST values among single stands of A . thaliana were very high , suggesting strong stand subdivision , with an average FST of 0 . 61 . Though smaller stands were more likely to consist of single genotypes , high pairwise FST values were not solely attributable to inclusion of these sites . In a subset of 25 stands that had at least three distinct multi-locus genotypes and consisted of 10 or more sampled individuals , pairwise FST values still averaged 0 . 60 . A subset of 13 populations having more than 25 individuals each had an average pairwise FST of 0 . 52 . Thus even large stands with many genotypes were strongly differentiated . There was no evidence of an overall pattern of isolation by distance in the Tübingen area as indicated by a Mantel test [39] ( p = 0 . 76 ) . We also tested for spatial autocorrelation [e . g . , [40] , [41]] . In an analysis of either 10 ( each 3 . 8 km ) or 30 ( each 0 . 5 km ) geographic distance classes , Moran's I [41]–[43] indicated significantly positive autocorrelation for the shortest distance classes ( 0–3 . 8 km; Figure S4A ) . Genetic distance , DG [44] , showed a similar trend ( Figure S4B ) . With distance bins of 0 . 5 km the first seven bins ( up to 3 . 5 km ) showed significant autocorrelation with Moran's I ( data not shown ) . Not surprisingly , Ripley's aggregation index R [41] indicated that the sample overall represented a significantly clumped distribution of genotypes ( 0 . 10 ) . This pattern of strong autocorrelation in the smallest distance classes is seen in the majority of plant species and this trend is particularly strong in self-fertilizing herbaceous species with gravity-dispersed seeds [45] . To examine whether distinct genotypes from the same population were more similar to each other than to those from other populations , we calculated pairwise genetic distance ( SNP differentiation ) for our whole dataset and divided the list into within- and between-stand comparisons . For between-stand comparisons , there was a roughly normal distribution of values centered on a mean of 0 . 58±0 . 09 ( Figure S5 ) . Within stands , however , the distribution of pairwise comparisons looked quite different: 4 , 500 out of 10 , 066 comparisons had a genetic distance of 0 ( identical genotypes ) . The mean distance within populations was 0 . 20±0 . 2 , or 0 . 35±0 . 2 , if identical genotypes were excluded . Non-identical genotypes found within the same stand were thus on average much more similar to each other than genotypes sampled from different stands ( Mann-Whitney U-test , p<0 . 0001; Figure S5 ) . A nonparametric clustering analysis , which does not rely on assumptions such as free out-crossing , revealed a tendency for genotypes from nearby stands , as well as distinct genotypes within stands , to group together ( Figure 3A ) , though clusters from different sub-regions within the Tübingen area were often intercalated . This pattern is in agreement with previous phylogenetic analyses of local populations , where the tips of the phylogeny were clustered according to geography , but deeper nodes were not [21] . Gap statistics [46] , [47] suggested two or five clusters in the Tübingen region ( Figure S6A; dotted lines in Figure 3A ) . The distribution of genotypes belonging to each of these clusters broadly correlated with the East-West orientation that the stands followed along the Neckar river valley ( Figure 3B and 3C ) . A major boundary was located around Tübingen , with the Eastern-most area , Walddorf ( Figure 1 ) , largely separated from the rest of the region ( Figure 3 ) . This could reflect a difference in colonization history , or that the Walddorf area is more isolated by the surrounding Schönbuch forest . Indeed , we have not found A . thaliana in forests around Tübingen despite repeated attempts ( K . B . and L . Y . , unpublished observations ) . Nearly all heterozygous or obviously recombinant genotypes we observed originated from sites in rural settings , such as meadows or field borders . This prompted us to investigate more closely the relationship between site type and population genetic parameters . We classified the sites of origin as “rural” if the stands were found in meadows , near agricultural fields , or in grassy rural roadsides , and “urban” if they were in towns , where we found plants in parking areas , vacant lots , gardens , or in cracks between paving stones . To correct for sample size variation , we used only He and FIS values calculated using a sub-sampling approach to compare stands . Urban stands often consisted of only a single or a few genome-wide genotype ( s ) while rural sites only rarely contained just a single genotype ( Table S1 ) . Urban sites had lower average genetic diversity than rural sites: Mean urban site diversity ( He ) was 0 . 10 ( 95% confidence interval 0–0 . 26; median 0 . 07 ) while rural sites averaged 0 . 18 ( 95% confidence interval 0–0 . 36; median 0 . 18 ) ( Figure 4 , Table S3 ) , a statistically significant difference ( Mann-Whitney U-test , p<0 . 009 ) . When multiple genotypes were present in urban stands , SNP differences tended to be randomly distributed across the genome , suggesting the absence of a history of local recombination events ( data not shown ) . Rural stands , in contrast , often showed evidence of clustering of SNP differences in pairwise genotype comparisons suggestive of historical recombination events ( Figure S2 ) . This could have resulted from differences in the prevalence of outcrossing: rural sites had significantly lower FIS than urban sites ( Mann-Whitney U-test , p<0 . 01 ) . Rural sites had a mean and median FIS of 0 . 92 and 0 . 93 , respectively , while urban sites had a mean and median of 0 . 96 and 1 . 0 , respectively . The mean FIS translates to effective outcrossing of 4 . 1% in rural and 1 . 9% in urban stands , or 3 . 5% and 0% based on median FIS ( Figure 4 ) . In summary , rural sites had on average higher genetic diversity as well as a higher degree of heterozygosity . In the spring of 2008 , we returned to a subset of 21 sites that had had medium to large stands in 2007 . In all of them we again found A . thaliana plants . We genotyped individual progeny of 369 plants with a subset of 149 markers [35] , of which 133 were informative , to determine whether identical genotypes were recovered . In stands that were monotypic or genetically simple in 2007 , we found mostly identical genotypes in 2008 . While this is perhaps unsurprising , it does suggest that factors such as a latent genetically diverse seed bank or high migration are not contributing extensive variability from year to year at these sites . From more genetically complex stands , however , fewer identical genotypes were recovered ( Table S5 ) . In moderately diverse stands , we recovered some identical and some distinct genotypes , while in large , genetically complex meadow stands , we detected little or no genotype identity between 2007 and 2008 . This suggests that these stands contained so many genotypes that our level of sampling in subsequent years was small relative to the diversity present in the entire stand . Alternatively , immigration or germination from seed banks was contributing to variation from year to year . To examine whether samples in different years were effectively samples from the same larger set of genotypes , we calculated pairwise FST values for each site across the two years . Since sample sizes in the two years were different , we again employed a sub-sampling strategy to estimate sample differentiation among years ( see Materials and Methods ) . Excluding stands where only a single identical genotype was found in both years , the comparisons between years gave FST values ranging from 0 . 03 to 0 . 13 ( Table S5 ) . That relative to between-population comparisons , FST values were low , but not zero , indicated that genotypes sampled in successive years were distinct , but still more closely related that genotypes sampled from different sites . This is most easily interpreted as subsamples drawn from a larger diverse population . This conclusion also supported by a cluster analysis on the 2007 and 2008 genotypes: distinct genotypes found across years tended to group together ( Figure 5 ) .
In the Tübingen area , multi-locus genotypes showed some tendency to be more closely related to their nearest neighbors . Groups from different sub-regions were nevertheless intercalated in cluster analyses . This is consistent with previous observations of microgeographical clustering of related genotypes that does not extend to larger scales , for example in studies of local A . thaliana accessions from North America [21] and China [48] . These findings support the previous conclusion that individual A . thaliana stands are loosely connected parts of meta-populations , with some level of genetic exchange among stands occurring at local scales [e . g . , [49]] . Gene flow among nearby stands and recombination within stands , even if rare , apparently suffice to cause proximal accessions to be on average more closely related than those that are further apart . Together with conclusions from other surveys [e . g . , [6] , [18] , [26]] , this points to A . thaliana genotypes having a discernable “local stamp” when sampled at different geographical scales , from tens of meters to thousands of kilometers . Together these results imply that local contemporary processes – such as recombination and short-range migration – and historical colonization patterns are both important factors in generating the complex spatial patterns of genetic structure observed at different scales in A . thaliana . Within single contiguous stands of plants we sometimes saw evidence of extensive genetic exchange and patterns of haplotype sharing suggestive of historical recombination , in agreement with previous reports that individuals within stands are genetically closer than ones from different populations or regions [5] . In our 2007 sample , 8% of individuals were heterozygous for linked markers across parts or all of the genome , and we also found many instances of clearly recombinant , but largely or fully homozygous types . In many cases , the putative parental genotypes were also found within the same stand . Estimated effective outcrossing for the whole sample set averaged less than 2% , but varied strikingly among stands , and could be as high as 14 . 5% . Outcrossing of A . thaliana has generally been estimated to be around 1% or less [e . g . , [3]–[5]] , with some exceptional individual stands that had estimated rates of up to 7 . 5% [25] . Since A . thaliana has been thought to be nearly exclusively selfing , observed heterozygosity at microsatellite markers was sometimes attributed to de novo mutation rather than outcrossing [e . g . , [4] , [5]] . We employed genome-wide biallelic SNP markers for which this concern does not apply , since the single base mutation rate [50] is negligible compared to even a very low outcrossing rate . Furthermore , we observed heterozygosity – when present – at numerous linked markers in an individual . We are therefore confident that heterozygosity in our sample arose from outcrossing rather than de novo mutation . Outcrossing rates calculated from FIS values , while informative for comparisons , should be treated with caution and not necessarily be seen as reflecting the actual outcrossing rate . Other factors may also affect heterozygosity . The presence of fine-scale spatial structure together with nearest-neighbor mating can inflate homozygosity , known as the Wahlund effect [38] . Indeed , simulations have shown that the increased homozygosity , patch structure and microgeographic differentiation typical of selfing species can be generated by nearest-neighbor mating [51] . Sampled heterozygosity can also be affected by selection , when heterozygous allele combinations are advantageous . This has been observed in several self-pollinated plant species [e . g . , [12] , [14] , [15]] . Hence in discussing outcrossing rates estimated from FIS , we can think of the calculated outcrossing as measuring “effective outcrossing” – that is , the rate of generation of heterozygous genotypes , regardless of the actual outcrossing rate of the stand in question . This borrows terminology used by Ritland where “effective selfing” is defined as “the probability that an allele chosen at random from an individual's mate is identical by descent with either allele at the same locus in that individual” [52] . Effective selfing accounts for mating with relatives due to near-neighbor mating , population structure , short dispersal distances and selection . In our sample , at least some stands were strongly internally structured and this correlated to some degree with observed homozygosity , suggesting that the Wahlund effect [38] can contribute to homozygosity in A . thaliana . This implies that actual outcrossing in wild stands may exceed estimates based on marker heterozygosity . The relationship between actual outcrossing and observed heterozygosity in A . thaliana awaits more thorough quantification , for example by progeny array analysis of unstructured stands [e . g . , [8] , [53]] . In non-uniformly distributed species , self-fertilization is often associated with increased spatial genetic structure [54] , but whether it is a cause or consequence of selfing is not always entirely clear . For example , species such as A . thaliana that require some degree of disturbance to compete successfully may exist in patchy populations because of the transience of their niche . In such situations , selfing may be selectively favored to provide reproductive assurance and mitigate the effects of small population size and unavailability of crossing partners [55] . In A . lyrata , an outcrossing relative of A . thaliana that is often patchily distributed , self-compatibility has spontaneously arisen in several populations [56] , [57] . Thus , though it is clearly plausible that selfing in A . thaliana promotes the observed population structure , it is also conceivable that A . thaliana was initially patchily distributed , and selfing was selectively advantageous as a result . It is not unusual that the genetic diversity of self-fertilizing species strongly varies among stands [e . g . , [16]] , and A . thaliana is no exception [e . g . , [4] , [5] , [25]] . We observed A . thaliana growing at many different sites: some in cracks between paving stones in urban environments , others at the edges of urban gardens , along rural roadsides or in railway ballast , in grassy field borders , or in species-rich rural meadow sites . This in itself is not new: other studies have described wild A . thaliana stands in a range of settings [e . g . , [3] , [25]] . However , the correlation between site type and genetic characteristics of stands that we found , though previously hinted at [23] , has not been examined and documented in detail for A . thaliana . In our collection , urban stands were often small and either monotypic or contained only a few common multi-locus genotypes with little or no evidence of historical recombination among them and little or no heterozygosity . This suggests that lineages propagate in urban sites predominantly by self-fertilization or by crossing with genetically identical neighbors , and that rare migration events are likely the primary force for generating diversity in these stands . Selfing species such as A . thaliana can also have reduced within-population genetic diversity because of high local extinction and recolonization rates [e . g . , [58]] . In the case of A . thaliana , whether urban stands tend to be genetically simple and homozygous because they are particularly short-lived , or because migration is so low that stands remain monotypic for extended periods , remains unknown . However , rapid local extinction has been observed in some natural A . thaliana populations [e . g . , [21]] . Indeed , when we revisited stands that we had identified in 2007 , we found A . thaliana grew at most sites again in 2008 . However , several smaller stands , such as HaS , TüHG , TüWa and TüSB25 , had disappeared . Rural stands in our sample , in contrast to urban ones , contained many distinct , though often related genotypes . Rural stands showed stronger evidence for ancestral recombination , with extended chromosomal stretches of allele sharing in pairwise genotype comparisons , as well as extensive heterozygosity . The latter not only indicated recent outcrossing , but also likely reflected the fact that rural stands were in general less spatially structured than urban ones . These patterns suggest that rural sites may have greater long-term stability than urban ones . Many genotypes obtained from such stands were complex mosaics of SNP identity and divergence in pairwise comparisons , while other stands were composed entirely of recombinants of just two ancestral genotypes . The intricate patterns of relatedness in these stands suggest extensive sharing of genetic information , both in the past and ongoing . This is consistent with what was observed in a smaller survey of eight stands in England , where those with low levels of human interference also had higher heterozygosity and genetic diversity than those with higher human impact [23] . A study of A . thaliana site ecology in Norway did not find a significant correlation between species richness and genetic diversity [25] , but the stands with high diversity and some heterozygosity were also described as being from “species-rich” sites [25] . Multiple factors may contribute to the differences in observed heterozygosity between rural and urban sites . The high diversity and patterns of recombination could be an indication that rural sites are less transient than urban sites , allowing the signature of ancestral outcrossing events to survive within stands . Rural sites may also enjoy higher pollinator prevalence . Numerous pollinators , including thrips and larger flying insects such as solitary bees and dipterans , have been reported to visit flowers of A . thaliana in central Germany [59] , and A . thaliana flowers may actively encourage some level of pollinator-mediated outcrossing by emitting volatiles that could serve as pollinator attractants [60] . The physical environment might affect outcrossing as well . In several self-fertilizing grasses , stands in mesic conditions showed more outcrossing than stands in xeric environments [e . g . , [7] , [8] , [15]] . Outcrossing rates may also vary from season to season , sometimes correlating with average temperature and rainfall [e . g . , [61] , [62]] . We did not assay whether rural sites were in general more mesic or cooler than urban ones , but given that many rural stands were found in heavily vegetated drainage ditches , or in meadows where grasses may protect soil from drying out or shade A . thaliana plants , it is possible that such differences impact outcrossing . Some rural stands with a large number of distinct genotypes were nevertheless genetically simple , with all observed types attributable to hybridization and subsequent recombination between two or three ancestral genotypes . We found such stands especially in more species-poor rural sites such as an abandoned railway platform ( Ey ) , or an exposed slope by a rural roadside ( Obn ) . A few other rural stands consisted of only two to three distinct haplotypes , with first-generation heterozygotes among the dominant types ( Erg and Bai ) . We suspect that these stands were recently colonized or only recently became polymorphic due to ingress of migrants . Consistent with this , these stands were in areas disturbed by road construction activity the year prior to our collection . By sampling in consecutive years , we found that from genetically simple sites , identical genotypes were usually recovered in the second year . For genetically more complex stands , we found numerous additional genotypes in the second year , sometimes without recovering genotypes identical to those found in the previous year . However , in many cases these distinct genotypes were closely related and clustered together with those from the previous year in the same stand . This suggests that even where additional sampling over multiple years uncovers distinct genotypes , they are for the most part drawn from a similar population sample and do not represent a completely novel array of genotypes . Some diversity could originate from persistence of seeds in the soil over several growing seasons: A . thaliana seeds are known to occur in soil seed banks [63] , [64] where they can retain the ability to germinate for at least 30 months [65] , [66] . Migration may also be a factor . Wind could distribute seeds , as could inadvertent human-mediated transport . Arabidopsis thaliana seeds have even been shown to germinate from rabbit dung , suggesting these animals may act as a dispersal agent [67] . In some cases the differences across years could also be due to small sample sizes relative to the actual population size and the amount of genetic diversity present in these stands . In aggregate , our data suggest that rural stands are likely to be the primary generators of recombined genomes in A . thaliana , an important source of diversity via novel allele combinations . Perhaps the patterns observed in rural stands are more representative of the ancestral situation for A . thaliana . An ability to invade human-generated low-competition habitats may have provided open niches and new opportunities , but with the trade-off that it precipitated a shift toward higher degrees of inbreeding and reduced genetic diversity within stands . We have presented evidence that local-scale genotype distribution patterns in A . thaliana are influenced by contemporary forces such as outcrossing and site ecology , which has important implications for designing studies of natural variation and adaptation . The strong spatial differentiation and heterogeneity of local stands observed here are consistent with previous studies of A . thaliana [e . g . , [4] , [21] , [22]] and of other self-fertilizing plants [e . g . , [7]–[15]] . In addition , our work complements a recent study of over 5 , 700 plants drawn from the world-wide range of A . thaliana and genotyped with 139 markers [30] . Although it employed a different sampling scheme , with less detailed investigation of individual populations from the Eurasian continent , its conclusions are in broad agreement with our work . Together with previous reports , our data suggest that patterns of isolation by distance observed at larger scales [e . g . , [6] , [18] , [26] , [27] , [30]] may be generated at the local level by a combination of historical colonization and contemporary recombination among closely-spaced genotypes . Outcrossing and recombination within stands can be extensive , while gene flow between stands appears to be rare . Site type characteristics correlated with genetic patterns , and we observed enormous variation among stands in estimated outcrossing rates – from none to as high as 20% . Rural stands in species-rich meadow sites had considerably higher genetic diversity and heterozygosity than stands in more urban or species-poor sites . Rural stands are thus likely hotspots for the generation of novel allele combinations . Effective recombination rates are sufficiently high , and effective population size sufficiently large , to break down allele associations [31] , [32] . Historical recombination has been suggested as a cause for breakdown of LD in Norwegian populations [25] , and may explain limited LD in other self-fertilizing species [33] . While the species-wide LD patterns are good news for genome-wide association mapping [1] , an interesting opportunity is offered by the collections of naturally formed recombinant inbred lines we have identified in several stands . Recombinant inbred lines generated in the laboratory have played a major role in the analysis of natural genetic variation in A . thaliana [2] , [68] . The recombinant genotypes we have found have survived in the wild for successive generations and thus provide a rare platform to study the ability of distinct genotypes to establish themselves in diverse habitats . With sufficiently large samples from such stands , one could monitor genotype frequencies throughout the genome in studies over multiple years to ask whether certain alleles or allele combinations are under- or overrepresented , or whether frequencies fluctuate over time as biotic and abiotic conditions change in successive years .
Seeds from individual plants were collected from 77 wild stands around Tübingen from late April to early June in 2007 , and again from a subset of 21 of these stands in 2008 . Seeds were germinated in growth chambers , and a single descendent individual was selected for DNA extraction . DNA was extracted from leaf tissue that had been frozen at −80°C using a Biosprint 96 DNA plant kit on a Biosprint 96 robotic workstation ( Qiagen ) . SNP assays were designed as described by Warthmann and colleagues [35] . We genotyped single progeny of all 1 , 005 plants using 551 genome-wide single nucleotide polymorphism ( SNP ) markers . These included a set of 149 markers selected to optimize common variants among worldwide A . thaliana accessions [35] , which were used on both the 2007 and 2008 samples . The 2007 samples were genotyped in addition with 402 SNP markers designed to be maximally informative between 20 world-wide accessions analyzed in a previous high-resolution SNP discovery study [69] . We culled markers with very high heterozygous call rates ( suggestive of copy number variation ) or high failure rates , leaving in the 2007 set a total of 436 markers , of which 431 were informative , and 133 markers in the 2008 set . Population gene diversity was calculated as expected heterozygosity ( He ) and as 1-Qinterindividual , the latter was calculated in GENEPOP v . 4 . 0 [70] . Qinterindividual is the probability of identity of two alleles among individuals within a stand , estimated based on observed SNP identities . This is calculated for each marker individually , and then averaged across the genome [70] . FST was also calculated in GENEPOP v . 4 . 0 , which follows the methods of Weir and Cockerham [71] . For stands of ten or more individuals , we calculated He and FIS using a subsampling approach to account for variation in sample size and to allow comparisons among stands , for example among rural versus urban sites . Subsampling was performed in R [47] ( scripts available on request ) as follows: We took a random sample of ten individuals from each sample greater than ten and calculated He and FIS for each marker . This was reiterated 100 times and average values were calculated for each marker , and then averaged across the genome to obtain the mean value for the stand . 95% confidence intervals were calculated using 1 , 000 iterations of Weir's bootstrapping algorithm [72] . We tested for differences between rural and urban sites with the Mann-Whitney U-test implemented in R [47] on the stand mean values for He and FIS calculated from the subsampling procedure . FST values for 2007 versus 2008 samples from 14 stands were similarly corrected for sampling differences using a sub-sampling approach . For each sample pair from the same site , we subsampled from the larger sample the same number of individuals as are in the smaller sample . FST was calculated for each sub-sample compared to the smaller sample , and this was reiterated 100 times to calculate a mean FST for each comparison . Confidence intervals were calculated using bootstrapping as described above . Mantel tests for isolation by distance were performed in GENEPOP v . 4 . 0 [70] . Autocorrelation analyses [40] were performed in SGS [73] calculating a correlogram for Moran's I [42] , [43] and a distogram for genetic distance DG [44] with pairwise comparisons grouped into 10 or 30 distance classes , with sizes 3 . 84 km and 0 . 5 km respectively . With ten distance classes , each class had 1 , 000 or more comparisons , while with 30 classes , each had 100 or more pairwise comparisons . 95% confidence intervals around expected mean values were calculated with 500 permutations of the data . Pairwise genetic distance between individuals and between stands was calculated using the Maximum Likelihood procedure in MEGA 4 . 0 [74] . Additional statistical analyses were performed and plots and histograms generated in Kaleidagraph v . 4 . 0 . 3 ( Synergy Software ) . We scanned genotypes manually for chromosomal stretches of heterozygosity and allele identity indicative of outcrossing or historical recombination events . Outcrossing ( OC ) was estimated from FIS using the standard equation: OC = 1 - ( ( FIS x 2 ) / ( 1+FIS ) ) . We performed nonparametric clustering of the SNP data , since A . thaliana violates common assumptions such as free outcrossing . Nonparametric clustering was performed using nonredundant genotypes in AWClust , implemented in R [47] . AWclust was also used to calculate gap statistics to estimate cluster numbers [46] , [47] .
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The popular model plant Arabidopsis thaliana is increasingly used to investigate questions in evolution and ecology . Thus it is important to understand the dynamics of wild populations at a scale relevant to single plants . We analyzed over 1 , 000 individuals from 77 ecologically diverse stands near Tübingen in Southwestern Germany . By assaying hundreds of independent markers in their genomes , we generated an unprecedentedly detailed view of local relatedness and recombination patterns . As has been observed previously for Arabidopsis thaliana and other self-compatible plants , even closely neighboring stands were strongly differentiated . Nevertheless , individuals tended to be most closely related to near neighbors , and footprints of recent recombination events were apparent . Structure was evident within stands , suggesting short dispersal ranges and the potential for nearest neighbor mating to reduce heterozygosity . We also observed differences between stands in rural and urban settings: stands in species-rich rural sites had higher average genetic diversity and presented more evidence of past and ongoing outcrossing than their species-poor urban counterparts . Thus novel combinations of genes may primarily arise in a subset of stands that act as “outcrossing hotspots , ” while others contribute little to increasing genetic diversity .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"evolutionary",
"biology/plant",
"genetics",
"and",
"gene",
"expression",
"evolutionary",
"biology/evolutionary",
"ecology"
] |
2010
|
Local-Scale Patterns of Genetic Variability, Outcrossing, and Spatial Structure in Natural Stands of Arabidopsis thaliana
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Manganese ( Mn ) is an essential micronutrient that is not readily available to pathogens during infection due to an active host defense mechanism known as nutritional immunity . To overcome this nutrient restriction , bacteria utilize high-affinity transporters that allow them to compete with host metal-binding proteins . Despite the established role of Mn in bacterial pathogenesis , little is known about the relevance of Mn in the pathophysiology of E . faecalis . Here , we identified and characterized the major Mn acquisition systems of E . faecalis . We discovered that the ABC-type permease EfaCBA and two Nramp-type transporters , named MntH1 and MntH2 , work collectively to promote cell growth under Mn-restricted conditions . The simultaneous inactivation of EfaCBA , MntH1 and MntH2 ( ΔefaΔmntH1ΔmntH2 strain ) led to drastic reductions ( >95% ) in cellular Mn content , severe growth defects in body fluids ( serum and urine ) ex vivo , significant loss of virulence in Galleria mellonella , and virtually complete loss of virulence in rabbit endocarditis and murine catheter-associated urinary tract infection ( CAUTI ) models . Despite the functional redundancy of EfaCBA , MntH1 and MntH2 under in vitro or ex vivo conditions and in the invertebrate model , dual inactivation of efaCBA and mntH2 ( ΔefaΔmntH2 strain ) was sufficient to prompt maximal sensitivity to calprotectin , a Mn- and Zn-chelating host antimicrobial protein , and for the loss of virulence in mammalian models . Interestingly , EfaCBA appears to play a prominent role during systemic infection , whereas MntH2 was more important during CAUTI . The different roles of EfaCBA and MntH2 in these sites could be attributed , at least in part , to the differential expression of efaA and mntH2 in cells isolated from hearts or from bladders . Collectively , this study demonstrates that Mn acquisition is essential for the pathogenesis of E . faecalis and validates Mn uptake systems as promising targets for the development of new antimicrobials .
While normal residents of the gastrointestinal ( GI ) tract of animals and humans , enterococci are also the third most frequent cause of hospital-acquired infections and a major threat to public health due to the alarming rise of multidrug-resistant isolates [1] . Enterococcal infections in humans are mainly caused by Enterococcus faecalis and Enterococcus faecium , with the great majority of infections ( ~70% ) caused by E . faecalis . Collectively , enterococci rank as the third leading etiological agent in infective endocarditis ( IE ) [2] , second in complicated urinary tract infections ( UTI ) [3] , and one of the leading causes of device-associated infections and bacteremia [1] . Despite the recent introduction of new antibiotics active against both E . faecalis and E . faecium ( i . e . daptomycin , linezolid , tigecycline ) , the indiscriminate use of antibiotics and the rise in elderly and severely ill populations susceptible to infection continues to contribute to a worldwide increase in enterococcal infections [4 , 5] . The pathogenic potential of E . faecalis , and more generally , of all enterococci , has been largely attributed to their harsh and extremely durable nature , which includes intrinsic tolerance to commonly-used antibiotics ( such as cephalosporins ) , chlorine , alcohol-based detergents , and an ability to survive extreme fluctuations in temperature , pH , oxygen tension , humidity and nutrient availability [1] . We recently showed that virulence-related phenotypes of a strain unable to synthesize the nutritional alarmone ( p ) ppGpp , known as ( p ) ppGpp0 strain , were directly linked to manganese ( Mn ) homeostasis , as important phenotypes of the ( p ) ppGpp0 strain could be reverted by addition of Mn to laboratory growth medium or serum [6] . Mn is an essential micronutrient for bacterial pathogens and hosts alike [7] . In lactic acid bacteria such as E . faecalis , Mn is the co-factor of enzymes of central metabolic pathways , such as energy generation and DNA biosynthesis , and has been shown to play an important role in oxidative stress responses [6 , 8] . Similarly , vertebrates require Mn for a variety of cellular pathways such as lipid , protein , and carbohydrate metabolism [9 , 10] and , depending on the tissue , Mn levels range from 0 . 3 to 2 . 9 μg per gram of tissue [11 , 12] . While the lowest range concentration found in tissues is more than enough to promote bacterial growth , the mammalian host restricts the availability of essential metals such as Mn and iron ( Fe ) to invading pathogens by producing small molecules and proteins that tightly bind to metals , an active process termed nutritional immunity [13] . For example , Fe-binding proteins such as transferrin ( TF ) and lactoferrin ( LF ) are utilized by the host to chelate Fe in serum ( TF ) and mucose ( LF ) , thereby restricting its bioavailability to invading pathogens [14] . The bioavailability of Mn and zinc ( Zn ) in the host is restricted , at least in part , by calprotectin , a Mn/Zn-sequestering protein of the S100 family that accounts for more than 40% of the total protein content of neutrophils [15] . In addition , macrophages express an Nramp ( Natural Resistance-Associated Macrophage Protein ) -type Fe/Mn transporter that starves phagocytosed bacteria to promote clearance in the phagolysosome [7] . Notably , mice defective of calprotectin or the Nramp-type macrophage transporter are significantly more susceptible to bacterial infections [16 , 17] . To overcome host-imposed Mn restriction , bacteria produce their own high-affinity Mn transporters . Presently , three classes of Mn transporters are known in bacteria: i ) ABC-type permeases , ii ) Nramp-type H+/Mn transporters , and iii ) the less common P-type transporters [7] . Not surprisingly , Mn uptake systems have been identified as major virulence factors for several gram-negative and gram-positive pathogens [7 , 8 , 18] . For instance , in Salmonella enterica serovar Typhimurium , deletion of the ABC transporter sitABCD alone or in combination with the Nramp transporter mntH led to virulence attenuation in a murine systemic infection model [19] . Similarly , in Staphylococcus aureus , combined inactivation of the ABC-type transporter mntABC and the Nramp-type transporter mntH reduced staphylococcal virulence in murine skin abscess [20] and systemic infection models [17] . In streptococci , which are more closely related to the enterococci , deletion of the ABC-type Mn transporter attenuated virulence of Streptococcus mutans , S . parasanguinis and S . sanguinis in rat or rabbit models of IE as well as of Streptococcus pyogenes in a murine model of skin infection [21–25] . Remarkably , deletion of the ABC-type Mn transporter psaBCA rendered Streptococcus pneumoniae completely avirulent in at least three different animal models [26] . The significance of Mn homeostasis and specifically Mn acquisition systems to E . faecalis pathogenesis has not been explored in detail . In silico analysis indicates that the core genome of E . faecalis encodes three putative Mn transporters: the ABC-type transporter EfaCBA and two Nramp-type transporters designated MntH1 and MntH2 [27 , 28] . Previous global transcriptional ( microarray ) analysis revealed that transcription of these genes , particularly efaCBA and mntH2 , is strongly induced in blood or in urine ex vivo as well as in a murine peritonitis model [29–31] . In addition , transcription of efaCBA , mntH2 and to a much lesser extent mntH1 is induced in Mn-depleted laboratory medium while repressed in Mn-rich medium [6 , 32–34] . Notably , an earlier study identified EfaA ( the lipoprotein component of the EfaCBA complex ) as a prominent antigen in enterococcal IE that can be used as an immunodiagnostic tool to discriminate E . faecalis from other IE-causing bacteria [35 , 36] . Finally , virulence of a strain lacking efaA was slightly attenuated in the murine peritonitis model [36] . To determine the significance of Mn homeostasis in the pathophysiology of E . faecalis , we generated a panel of single ( Δefa , ΔmntH1 , ΔmntH2 ) , double ( ΔefaΔmntH1 , ΔefaΔmntH2 , ΔmntH1ΔmntH2 ) and triple ( ΔefaΔmntH1ΔmntH2 ) deletion mutants in strain OG1RF and tested their ability to grow under metal-restricted conditions and to cause infection in three different animal models . We found that production of only one of the three Mn transporters is sufficient to support growth of E . faecalis in Mn-depleted media , a finding that is supported by the drastic reduction in cellular Mn levels in the triple ΔefaΔmntH1ΔmntH2 mutant but not in single or double mutant strains . Loss of efaCBA alone impaired growth in serum or in the presence of calprotectin in vitro . In most cases , inactivation of mntH2 exacerbated the phenotypes of the Δefa mutant , suggesting that EfaCBA and MntH2 are the primary high-affinity Mn transporters of E . faecalis . While only ΔefaΔmntH1ΔmntH2 showed virulence attenuation in the Galleria mellonella invertebrate model , both ΔefaΔmntH2 double and ΔefaΔmntH1ΔmntH2 triple mutant strains were virtually avirulent in the two mammalian models tested ( i . e . , rabbit IE and murine catheter-associated UTI ) . Collectively , this investigation highlights the essentiality of Mn acquisition to E . faecalis pathogenesis , suggesting that pathways associated with Mn homeostasis are promising targets for the development of new antimicrobials .
The annotations of EF2074-2076 ( OG1RF11677-11679 ) , EF1901 ( OG1RF11567 ) and EF1057 ( OG1RF10838 ) as efaCBA , mntH1 and mntH2 , respectively , have been inferred based on their similarities to previously characterized Mn transport systems and their Mn-dependent transcriptional profiles [32–34] . To uncover the role of these systems in metal uptake , single ( Δefa , ΔmntH1 , ΔmntH2 ) , double ( ΔefaΔmntH1 , ΔefaΔmntH2 , ΔmntH1ΔmntH2 ) and triple ( ΔefaΔmntH1ΔmntH2 ) deletion strains were generated using a markerless system [37] . Brain Heart Infusion ( BHI ) broth has been previously reported to contain relatively low levels of Mn when compared to other laboratory media , such as the chemically-defined FMC medium [6 , 25] . Using inductively coupled plasma-optical emission spectrometry ( ICP-OES ) , we confirmed this to also be the case for BHI prepared in our laboratory—Mn , Fe and Zn concentrations were ~ 1 . 1 μM ( Mn ) , ~ 3 . 9 μM ( Fe ) and ~ 11 . 3 μM ( Zn ) ( Fig 1A ) . With those values in mind , all mutant strains were isolated on BHI plates supplemented with 150 μM MnSO4 . Upon genetic confirmation that all gene deletions occurred as planned , we tested the capacity of all mutant strains to grow on unsupplemented BHI . While single and double mutant strains grew well on plain BHI plates , the triple ΔefaΔmntH1ΔmntH2 mutant could only grow on Mn-supplemented BHI ( Fig 1B ) . To confirm this initial observation , growth of the parent OG1RF and mutant strains was monitored in the chemically-defined FMC medium depleted of Mn ( Mn < 90 nM ) [6] . Growth of all mutant strains ( singles , doubles and triple mutant strains ) in complete FMC ( Mn-replete ) was indistinguishable from growth of the parent strain ( Fig 1C and 1E ) . Single Δefa , ΔmntH1 , and ΔmntH2 , as well as double ΔefaΔmntH1 and ΔmntH1ΔmntH2 behaved similarly to the parent strain when Mn was depleted from the medium ( Fig 1D and 1F ) . In contrast , the ΔefaΔmntH2 double mutant strain displayed an extended lag phase and slightly reduced final growth yields in Mn-depleted FMC ( Fig 1F ) . Most notably , both growth rate and final growth yields were severely impaired in the triple mutant strain under these conditions ( Fig 1F ) . Ectopic expression of any one of the three Mn transporters from a plasmid ( pTG-efa , pTG-mntH1 or pTG-mntH2 ) partially rescued the growth defect of the triple mutant on unsupplemented BHI agar and restored growth in Mn-depleted FMC ( Fig 1G and 1H ) . Collectively , these results strongly support that EfaCBA , MntH1 and MntH2 are bona fide , functionally redundant , Mn transporters . Next , we used ICP-OES to quantify cellular Mn content in the different Mn transport mutants . In agreement with the results shown in Fig 1 , single deletions of efaCBA , mntH1 or mntH2 did not affect cellular Mn content ( Fig 2A ) . However , combined deletion of mntH2 with either efaCBA or mntH1 ( ΔefaΔmntH2 and ΔmntH1ΔmntH2 ) caused a significant reduction ( ~ 40% ) in intracellular Mn pools ( Fig 2B ) . Most notably , Mn pools were below detection limit in the triple mutant strain , thereby providing unequivocal evidence of the cooperative nature of EfaCBA , MntH1 and MntH2 in Mn acquisition . Taking into account that a balanced Mn/Fe ratio is essential for cellular homeostasis , and that bacterial systems homologous to EfaCBA have been shown to also transport Fe [7 , 38] , we used ICP-OES to also determine the cellular Fe content in our panel of mutant strains . While Fe pools were not affected in single and double mutants of Nramp-type transporters ( ΔmntH1 , ΔmntH2 and ΔmntH1ΔmntH2 ) , loss of EfaCBA , either alone or in combination with MntH1 and MntH2 , led to ~ 40% reduction in cellular Fe content ( Fig 2 ) , indicating that , similar to streptococci , EfaCBA is a dual Mn/Fe transporter [7 , 25] . To rule out that loss of mntH1 , mntH2 or both can lead to further reductions in intracellular Fe in the Δefa background strain , we repeated the ICP-OES analysis of Δefa , ΔefaΔmntH1 , ΔefaΔmntH2 , and ΔefaΔmntH1ΔmntH2 strains in the same experiment . Inactivation of mntH2 ( or mntH1 ) in the Δefa background did not result in further reductions in Fe content ( S1 Fig , panel A ) . Considering that EfaCBA participates in Fe uptake , we evaluated whether Fe supplementation ( 150 μM FeSO4 ) could restore growth of the ΔefaΔmntH1ΔmntH2 triple mutant strain on BHI plates . We found that , different than Mn ( Fig 1 ) , Fe supplementation does not restore growth of the triple mutant in BHI agar ( S1 Fig , panel B ) . We also monitored growth of the different mutant strains in FMC depleted of Fe ( FMC ↓ Fe ) , or both Fe and Mn ( FMC ↓ Mn ↓ Fe ) ( S1 Fig , panels C-F ) . While the single Δefa strain displayed a moderate growth defect during Fe limitation , the double and triple mutant strains were indistinguishable from the parent strain . When Fe and Mn were simultaneously depleted from the medium , the ΔefaΔmntH2 and ΔefaΔmntH1ΔmntH2 mutants displayed an exacerbated growth defect when compared to growth in Mn-depleted medium ( FMC ↓ Mn ) ( Fig 1 , panel F ) , supporting the notion that Fe and Mn can act as interchangeable co-factors in E . faecalis [6] . Collectively , these results indicate that the growth defect of the ΔefaΔmntH1ΔmntH2 strain can be primarily associated to its inability to acquire Mn . Metal sequestration is an ancient infection defense mechanism that spans various kingdoms of life [39] . Insects , such as G . mellonella , produce Fe-chelating proteins homologous to mammalian TF and ferritin and could theoretically use similar strategies to chelate Mn [40–42] . To probe the significance of Mn transport in E . faecalis virulence , we first used the G . mellonella larvae model of systemic infection . All single and double mutants killed G . mellonella at rates that were comparable to the parent OG1RF strain ( S2 Fig ) , with similar averages of larvae survival ( ~ 27% ) 72 hours post-infection ( Fig 3 ) . However , virulence of the triple ΔefaΔmntH1ΔmntH2 mutant was dramatically impaired with ~ 87% larvae survival after 72 hours ( Fig 3 , S2 Fig ) . The Mn- and Zn-binding calprotectin is a major protein used by vertebrates to restrict the availability of these two transition metals to microbes during infection [15] . Normally found in circulating blood and tissues at relatively low levels , calprotectin rapidly accumulates to concentrations of up to 1mg ml-1 in response to inflammation and infection [15] , thereby depleting Zn and Mn from the infected site . Of note , previous studies indicated that the antimicrobial activity of calprotectin against E . faecalis is , at least in part , due to Mn sequestration [15] . Here , we assessed the ability of the Mn transport mutants to grow in the presence of a sub-inhibitory concentration of purified calprotectin . At the selected concentration , addition of calprotectin delayed growth of the parent OG1RF strain at the initial time-points , but did not impact final growth yields after 24 hours of incubation when compared to untreated cells ( S3 Fig ) . Of note , growth of the ΔefaΔmntH1ΔmntH2 triple mutant strain was impaired even in the absence of calprotectin , most likely due to the low Mn levels present in this medium ( S3 Fig ) . Loss of mntH1 ( ΔmntH1 ) did not affect enterococcal tolerance to calprotectin when compared to the parent strain . However , inactivation of mntH2 , either by itself ( ΔmntH2 ) or combined with mntH1 ( ΔmntH1ΔmntH2 ) , moderately impaired growth of E . faecalis in the presence of calprotectin ( Fig 4 and S3 Fig ) . Interestingly , growth rates and growth yields of any one of the efaCBA mutants was severely impaired by calprotectin . As expected , double inactivation of efaCBA and mntH2 ( ΔefaΔmntH2 ) rendered E . faecalis even more susceptible to the inhibitory effects of calprotectin . These results revealed that EfaCBA , closely followed by MntH2 , is the primary Mn transporter used by E . faecalis to overcome the inhibitory effects of calprotectin . A member of the S100 family , calprotectin forms a S100A8/S100A9 heterodimer with two distinct metal-binding sites: a high-affinity Zn-binding site and a dual high-affinity Zn/Mn-binding site . To confirm that the increased sensitivity of Δefa strains to calprotectin was due to Mn sequestration and not to Zn sequestration , we tested the sensitivity of wild-type and selected mutant strains against a calprotectin variant ( ΔMn Tail calprotectin ) that retains the ability to chelate Zn but is unable to chelate Mn due to amino acid substitutions of key histidine residues ( His103 and His105 ) in the C-terminal tail of calprotectin [15] . The inability to chelate Mn by the calprotectin ΔMn Tail variant restored final growth yields of all mutant strains tested to wild-type levels ( Fig 4 , and S4 Fig , panel A ) , strongly suggesting that EfaCBA , and to a lesser extent MntH2 , promote tolerance to calprotectin in a Mn-dependent manner . In line with this finding , the antimicrobial activity of native calprotectin could be fully overcome by Mn supplementation ( 10 μM MnSO4 ) ( S4 Fig ) . Because calprotectin has been shown to also scavenge Fe in vitro [43] , we also tested whether Fe supplementation ( 10 μM FeSO4 ) could rescue calprotectin tolerance in E . faecalis . Addition of Fe rendered the wild-type and ΔmntH2 strains even more sensitive to calprotectin , while partially restoring growth of the Δefa single mutant ( S4 Fig ) . More importantly , Fe did not rescue calprotectin tolerance of the double ΔefaΔmntH2 strain . Collectively these results indicate that EfaCBA and MntH2 mediate calprotectin tolerance by primarily facilitating Mn uptake . Next , we monitored growth and survival of the Mn transport mutants in pooled human serum at 37°C—serum was used instead of whole blood to avoid free metal contamination released by lysing erythrocytes . While inactivation of mntH1 and mntH2 , alone or in combination , did not affect the ability of E . faecalis to grow and survive in serum , loss of efaCBA led to a significant decrease in survival after 48 hours incubation when compared to the parent strain ( ~1 . 3 log Δefa , ~1 . 5 log ΔefaΔmntH1 , ~2 . 3 log ΔefaΔmntH2 , ~1 . 8 log , ΔefaΔmntH1ΔmntH2 ) ( Fig 5A and 5B ) . To determine if the survival defect of Δefa strains was due to an inability to scavenge Mn or Fe from the environment , we supplemented serum with 1 mM MnSO4 or 1 mM FeSO4 . Of note , the metal stocks chosen for supplementation were 99% pure to minimize the presence of other transition metals . The addition of either Mn or Fe restored serum growth and survival of Δefa strains to wild-type OG1RF levels ( Fig 5C ) . Moreover , Mn or Fe supplementation increased final growth yields of all strains , including the parent strain , confirming that both metals are growth-limiting factors in the human serum . Collectively , these results indicate that the EfaCBA system plays a primary role in promoting E . faecalis serum survival , likely because of its dual capacity to function as a Mn and Fe transporter . Patients with enterococcal IE are known to generate specific antibodies against EfaA , the substrate-binding lipoprotein component of the EfaCBA system [32 , 35] . While an efaA single mutant was previously shown to be slightly attenuated in a mouse peritonitis model [36] , the contribution of EfaCBA , or the other Mn transport systems MntH1 and MntH2 , in enterococcal IE has not been explored . Here , we used a catheterized rabbit IE model [44] to determine the ability of selected Mn transport mutants to colonize a previously-formed sterile heart vegetation and , then , systemically spread to different organs by using spleen homogenates as a readout . In the first experimental set , the parent OG1RF strain was co-inoculated systemically ( via ear vein injection ) with single Δefa and triple ΔefaΔmntH1ΔmntH2 strains . Forty-eight hours post-infection , an average of 7 . 5 ( +/- 0 . 7 SD ) and 4 . 1 ( +/- 0 . 9 SD ) log10 CFU E . faecalis were recovered from hearts and spleens , respectively , confirming that E . faecalis can efficiently colonize the injured heart endothelium and spread systemically in this model . PCR was used to screen E . faecalis colonies ( 50 to 100 per animal and organ ) to distinguish between the three strains based on the different amplification products obtained using efaCBA and mntH2 flanking primers . Of the total colonies screened from heart vegetations , ~ 55% corresponded to the parent OG1RF and ~ 45% to the Δefa single mutant strain ( Fig 6A ) . While the average recovery rates of OG1RF and Δefa were not statistically significant ( p>0 . 05 ) , there was a great variation from animal to animal , with the parent OG1RF corresponding to the large majority ( >90% ) of colonies recovered in two animals and Δefa predominating at ~ 80% in the remaining three animals ( Fig 6A ) . Similar trends were observed in the corresponding spleens of the individual animals ( ~ 49% OG1RF and ~ 51% Δefa , p>0 . 05 ) ( Fig 6B ) , indicating that systemic dissemination is likely a direct consequence of bacterial seeding from the heart vegetation . Most importantly , none of the screened colonies in this experiment corresponded to the triple mutant strain in either heart vegetations or spleens ( Fig 6A and 6B ) . Based on the strong growth defect of the double ΔefaΔmntH2 in the presence of calprotectin and in serum ( Figs 4 and 5 ) , we next tested the ability of the parent OG1RF , ΔmntH2 and ΔefaΔmntH2 strains to colonize the heart vegetations in a triple co-infection experiment . In this second set of experiments , the average numbers of OG1RF and ΔmntH2 recovered from heart vegetations and spleens were not significantly different ( ~ 40% OG1RF , ~ 60% ΔmntH2 , p>0 . 05 ) ( Fig 6C and 6D ) . Interestingly , the double ΔefaΔmntH2 mutant phenocopied the triple mutant strain , as none of the colonies screened from each animal corresponded to the ΔefaΔmntH2 strain . Of note , none of the mutant strains tested displayed a growth/fitness defect in vitro when co-cultured in BHI supplemented with 150 μM MnSO4 ( S5 Fig ) . Collectively , these results strongly support that EfaCBA and MntH2 are the primary Mn transporters of E . faecalis during infection and further underscore the functional redundancy shared by these two Mn transporters in vivo . Previous studies have shown that transcription of efaCBA and mntH2 is induced when E . faecalis is grown in urine , indicating that Mn is also a growth-limiting nutrient in the bladder environment [30 , 45] . We used ICP-OES to determine the Mn content in pooled human urine obtained from healthy donors and found this batch to be low in Mn ( ~ 0 . 7 μM ) , which is within the normal clinical range described elsewhere [10] . Copper ( Cu ) ( ~ 0 . 2 μM ) and Fe ( ~ 0 . 7 μM ) levels were also low in pooled urine , whereas Zn levels ( ~ 9 . 2 μM ) were comparatively much higher . Nevertheless , it should be noted that these values represent total metal concentrations present in urine not taking into account their bioavailability . Next , we tested the ability of the mutant strains to grow in human urine supplemented with bovine serum albumin ( BSA ) at 37°C—BSA was used to supplement urine to mimic protein infiltration during catheter-associated urinary tract infections ( CAUTI ) , a condition shown to promote growth of E . faecalis in the bladder environment [46 , 47] . We found that both the double ΔefaΔmntH2 and triple ΔefaΔmntH1ΔmntH2 mutant strains displayed a significant growth defect after 24 hours of incubation ( Fig 7A ) . While the parent , single and double mutant strains entered stationary phase and maintained the same growth yields for up to 48 hours , the ΔefaΔmntH1ΔmntH2 triple mutant also displayed a survival defect after 48 hours ( ~ 1 log10 reduction in CFU ml-1 , p < 0 . 05 ) when compared to the other strains ( S6 Fig ) . Importantly , MnSO4 supplementation ( 1 mM ) fully restored growth of the triple mutant strain in urine , while addition of FeSO4 ( 1 mM ) only partially rescued the defective phenotype ( Fig 7B ) . To determine whether Mn acquisition is also relevant to enterococcal UTI , we tested the parent OG1RF and each individual mutant strain in a murine CAUTI model [48] . Twenty-four hours post-infection , the OG1RF , Δefa and ΔmntH1 strains were recovered in similar numbers from the bladders of infected animals , whereas the ΔmntH2 strain had a ~ 1 . 5 log10 CFU reduction ( p<0 . 05 ) in total bacteria recovered ( Fig 8A ) . Inactivation of mntH1 did not exacerbate the phenotype of the mntH2 single gene inactivation ( ΔmntH1ΔmntH2 ) but simultaneous inactivation of efaCBA and mntH1 ( ΔefaΔmntH1 ) resulted in ~ 1 log10 CFU reduction in bacteria recovered from the bladder ( p<0 . 05 ) . In agreement with the mounting evidence supporting that EfaCBA and MntH2 are the primary systems for Mn acquisition , combined deletion of efaCBA and mntH2 ( ΔefaΔmntH2 ) or all three Mn transporters ( ΔefaΔmntH1ΔmntH2 ) further reduced bacterial loads recovered from the bladder to below or near the detection limit ( Fig 8A ) . The exact same trends found in the bladder were observed for bacteria recovered from biofilms formed on the surface of the implanted catheters , i . e . significantly lower bacterial burden for strains lacking mntH2 and very little to no bacterial cells recovered from strains lacking both efaCBA and mntH2 ( Fig 8B ) . Interestingly , the bacterial counts of strains with an attenuated phenotype were lower on catheters than in the bladders , suggesting that Mn uptake is especially critical for biofilm formation on urinary catheters . Moreover , while the parent OG1RF was able to ascend to the kidneys in 55% of the mice and disseminate to spleen and heart in ~ 30% of the animals infected , the Mn transport mutants were rarely recovered from kidneys and were almost never isolated from more distant organs such as spleen and heart ( S7 Fig ) . The overall impaired systemic dissemination of Mn transport mutants is in line with the importance of Mn acquisition systems for enterococcal survival in serum ( Fig 5 ) and for infection in the rabbit IE model ( Fig 6 ) . Biofilm formation of E . faecalis on urinary catheters is a critical step in UTI and is primarily mediated by the enterococcal surface adhesin EbpA [47 , 49] . Notably , the metal ion-dependent adhesion site ( MIDAS ) of EbpA is required for biofilm formation in urine and for virulence in the experimental CAUTI model [47 , 50] . While the identity of the metal bound to the tip of EbpA remains elusive , we wondered if the colonization defect of strains lacking one or more Mn transporters could relate to impaired biofilm formation and/or defects in EbpA production . First , we tested the ability of the parent and mutant strains to form biofilms on the surfaces of tissue culture plate wells and plastic catheters that were pre-coated with fibrinogen to promote biofilm formation in an EbpA-dependent manner [47] . After 24 hours of incubation in urine supplemented with BSA , the single Δefa , double ΔefaΔmntH2 and triple ΔefaΔmntH1ΔmntH2 mutant strains formed significantly less biofilm as measured by either crystal violet staining of tissue culture plates ( Fig 9A ) or catheter immunostaining ( Fig 9B ) . In agreement with these findings , the double ΔefaΔmntH2 and triple ΔefaΔmntH1ΔmntH2 mutant strains displayed a ~ 1 log10 CFU reduction in catheter-associated bacteria when compared to the parent strain ( Fig 9C ) . While compatible with the slight reduction in biofilm formation ( Fig 9A and 9B ) , the ~ 0 . 5 log10 CFU reduction observed with the Δefa single mutant on the catheter surface was not statistically significant ( Fig 9C ) . Finally , we used ELISA to quantify the surface expression levels of EbpA in the different strains grown under the same conditions used in the biofilm assay , i . e . urine supplemented with BSA . Despite defects in biofilm formation of Δefa , ΔefaΔmntH2 and ΔefaΔmntH1ΔmntH2 strains on fibrinogen-coated surfaces , there were no apparent differences in EbpA levels between parent and mutant strains ( Fig 9D ) , suggesting that the defective biofilm phenotype is not EbpA-dependent . The results described above suggest that EfaCBA is the chief Mn transporter in bloodstream infections while MntH2 appears to play a more prominent role in CAUTI . Given the functional redundancy of these Mn transporters , we wondered if efaCBA and mntH2 were differentially expressed when E . faecalis is in the bloodstream or in urine , thereby providing an explanation for the different phenotypic behaviors of Δefa and ΔmntH2 strains in different sites of infection . To address this possibility , we used quantitative reverse transcription-PCR ( qPCR ) to determine efaA , mntH1 and mntH2 transcription levels in vivo . When compared to cells grown in trypsinized beef heart medium , we found that efaA transcription was strongly induced in cells isolated from rabbit heart valves ( ~ 15-fold after two days and ~ 100-fold after three-four days ) ( Fig 10A ) . On the other hand , transcription of mntH1 was moderately repressed after infection ( 7-fold and 3-fold repression after two and three-four days , respectively ) , whereas mntH2 transcription remained largely unaltered over time ( Fig 10A ) . Strikingly , mntH2 was the only gene up-regulated ( ~ 10-fold induction ) in cells recovered from the bladders of mice 24 hours post-infection , while efaA and mntH1 transcription was not significantly altered ( Fig 10B ) . Since Mn plays a crucial role in promoting oxidative stress tolerance in lactic acid bacteria [6] , in part by acting as the co-factor of superoxide dismutase ( sodA ) , we also determined the transcription levels of sodA ( EF0463 , OG1RF10348 ) as a readout for oxidative stress in IE and CAUTI . Surprisingly , sodA transcription was downregulated ( ~ 15-fold ) at the early stage of endocarditis infection ( two days ) and did not differ from the inoculum condition at the later stage of infection ( three-four days ) ( Fig 10A ) . Similarly unexpected , cells recovered from the bladders of infected mice displayed a ~ 25-fold reduction in sodA one day post-infection ( Fig 10B ) .
In this study we confirm previous in silico predictions that the E . faecalis core genome encodes three bona fide Mn transporters: one ABC-type ( EfaCBA ) and two Nramp-type transporters ( MntH1 and MntH2 ) [27] . Early studies showed that the virulence of an E . faecalis efaA mutant was slightly delayed in a mouse peritonitis model despite the fact that the strain failed to display noticeable phenotypes in vitro [33 , 36] . Here , we provide an explanation for such findings by showing that only the simultaneous inactivation of two or all three transporters can drastically impair Mn homeostasis under laboratory as well as in vivo conditions . Specifically , the ΔefaΔmntH1ΔmntH2 triple mutant strain was unable to grow ( or grew very poorly ) in Mn-restricted environments—a condition commonly encountered in human tissues—and was unable to robustly infect vertebrate and invertebrate animal hosts . To our knowledge , this is the first description of an E . faecalis mutant strain being virtually avirulent in multiple animal infection models . Moreover , this is also the first demonstration that the ability to acquire Mn using high affinity transporters within the urinary tract environment was shown to be an important aspect for the development of bacterial UTI . While EfaCBA , MntH1 and MntH2 appear to be functionally redundant , simultaneous inactivation of efaCBA and mntH2 often phenocopied the triple mutant strain . Specifically , the double ΔefaΔmntH2 mutant strain was highly sensitive to calprotectin , displayed a biofilm formation defect in human urine and was virtually avirulent in the IE and CAUTI models . None of these phenotypes were further exacerbated in the triple mutant strain that also lacked mntH1 . Considering that mntH1 transcription is not as strongly affected by in vitro Mn fluctuations as efaCBA and mntH2 [6 , 34] , it is tempting to speculate that EfaCBA and MntH2 are the primary high-affinity Mn transporters of E . faecalis responsible for maintaining Mn homeostasis in Mn-restricted environments . In contrast , MntH1 may serve as a housekeeping transporter , possibly with lower affinity for Mn than EfaCBA and MntH2 , under Mn-replete conditions . The specificity and affinity ( high/low ) of each transport system for Mn , as well as other important transition metals such as Cu , Fe and Zn , will be determined in future studies . Lactic acid bacteria like enterococci and streptococci are notoriously Mn-centric organisms , having a much higher nutritional demand for Mn than other bacterial groups [38] . This metabolic particularity might explain why the striking loss of virulence observed here contrasts with the moderate virulence attenuation of Mn transport mutants in gram-negative and other gram-positive pathogens [7 , 8 , 17] . Indeed , the complete loss of virulence of ΔefaΔmntH2 and ΔefaΔmntH1ΔmntH2 strains shown here is only comparable to the virulence defects of streptococcal strains lacking EfaCBA orthologs [25 , 51 , 52] . Interestingly , the observation that E . faecalis produces three highly conserved Mn transporters instead of two , such as most streptococci [53] , may be an indication that this opportunistic pathogen is better equipped to acquire Mn from the host environment than some of the closely-related pathogenic species such as S . pyogenes and S . pneumoniae . Alternatively , it is possible that E . faecalis may simply have a higher cellular demand for Mn than streptococci , having to rely on multiple Mn transporters to meet such high demand . This would resemble Lactobacillus plantarum , a non-pathogenic organism with five annotated Mn transporters ( one P-type , one ABC-type , and three Nramp-type transporters ) that has one of the highest cellular requirements for Mn among gram-positive and gram-negative bacteria [38 , 54] . While Mn is the co-factor of several growth-promoting bacterial enzymes , Mn is thought to mediate bacterial virulence mainly by protecting cells from host-derived reactive oxygen species ( ROS ) [7 , 8 , 18 , 44 , 53 , 55] . Previous studies have shown that Mn contributes to elimination of damaging ROS via three distinct mechanisms: ( i ) by direct non-enzymatic scavenging of superoxide radicals , ( ii ) by serving as the co-factor of the Mn-dependent superoxide dismutase ( SOD ) enzyme , and ( iii ) by replacing Fe as an enzymatic co-factor thereby protecting Fe-binding proteins from Fenton chemistry damage [8 , 38 , 56] . Not surprisingly , Mn transport mutants of different bacterial species display enhanced sensitivity to oxidative stresses in vitro and reduced macrophage survival [18 , 19 , 53 , 57] . We were previously able to show that Mn availability is critical for enterococcal tolerance to hydrogen peroxide [6] . Here , we demonstrate that similar to S . aureus and Neisseria gonorrhoeae [20 , 58] , inability to acquire Mn with high affinity increases the sensitivity of the E . faecalis ΔefaΔmntH2 strain to paraquat , a superoxide generator ( S8 Fig ) . Addition of Mn to the medium fully restored paraquat tolerance of the mutant strain to wild-type levels , indicating that EfaCBA and MntH2 contribute to superoxide tolerance only in Mn restricted environments . Global transcriptional analyses of E . faecalis grown in whole blood or urine ex vivo or isolated from a murine peritonitis model showed that transcription of several genes associated with ROS detoxification , including sodA , is induced when compared to cells grown in laboratory medium , indicating that bacterial cells have to cope with ROS stress during invasive infections [29–31] . Unexpectedly , we found that transcription of sodA was downregulated in the early stages of IE and CAUTI infection ( Fig 10 ) . While further studies are needed to determine if E . faecalis does not encounter oxidative stress during these infections , it is possible that the downshift in sodA is a response mechanism to lower the cellular Mn requirement when this nutrient is already restricted . In support of this possibility , sodA transcription has been previously shown to be repressed in E . faecalis during Mn limitation in vitro and in cells recovered from a rabbit subdermal abscess model 8 hours post-infection [6 , 59] . Nevertheless , the discrepant transcriptional induction of sodA in different studies remains to be resolved . One possibility is that , during infection , oxidative stress fluctuates according to the dynamic and temporal immune responses mounted by the host . By obtaining the transcriptional profile of efaA , mntH1 and mntH2 during IE and CAUTI , we found that the transcriptional responses of each system to different environmental cues in vivo can greatly differ . This was particularly noticeable for efaA and mntH2 , since efaA was strongly induced in cells recovered from heart valves whereas mntH2 was induced in CAUTI ( Fig 10 ) . In contrast , transcription of mntH1 was repressed in heart valves while remaining largely unaltered in CAUTI . Considering that efaCBA , mntH1 and mntH2 have been previously shown to be regulated by EfaR [33] , a metalloregulator from the DtxR family , the different transcriptional profiles of these genes were somewhat unexpected . However , the same study proposed that , similar to Bacillus subtilis and S . enterica , there could be other factors regulating transcription of Mn transport genes in E . faecalis [8 , 33 , 60 , 61] . In fact , in silico analysis of the E . faecalis OG1RF genome identified two Fur-binding consensus sequences upstream efaC , the first gene in the efaCBA operon , indicating that this dual Fe/Mn transporter may also be regulated in response to Fe availability , oxidative stress or both . Future studies are warranted to identify the environmental cues present in blood and urine that trigger the different transcriptional responses of efaCBA and mntH2 , as well as the potential cis and trans-acting elements regulating these responses . In addition to differences in expression and , possibly , metal-binding affinity , the distinct behaviors of efaCBA and mntH2 mutants in the context of IE and CAUTI may have additional explanations . For instance , EfaA homologs of S . sanguinis ( SsaB ) , S . parasanguinis ( FimA ) and S . pneumoniae ( PsaA ) have been proposed to act as adhesins to a variety of relevant surfaces [53] . While the role of Mn ABC transport permeases as moonlighting proteins that participate in cell adhesion is a subject of debate [53] , the possibility that EfaA can also function as a surface adhesin should not be completely excluded at this point . Alternatively , considering that the availability of free Mn and Fe is greatly restricted in the bloodstream , it is possible that the dual ability of EfaCBA to import both metals , as suggested by cellular metal quantifications of efa mutants in this and other studies [62] , is physiologically relevant during bloodstream infections but not during UTI . In support of this possibility , both Fe and Mn are growth-limiting factors for E . faecalis in serum ( Fig 5 ) [6] , while only Mn could fully rescue the growth defect of the triple Mn transport mutant in urine ( Fig 7 ) . Importantly , the biological significance of Fe to bacterial infection is highlighted by the high incidence of opportunistic infections in individuals with elevated levels of circulating free Fe due to hemochromatosis [14] . Similarly , elevated tissue levels of Mn were recently show to promote staphylococcal abscess formation in the murine heart [55] , collectively supporting the notion that Fe and Mn availability facilitates bloodstream infections . At this time , the dominant role of MntH2 in CAUTI is less clear . Recent work in Streptococcus agalactiae showed that the Nramp-type MntH is induced at low pH and facilitates macrophage and acid stress survival [63] . It is thus possible that the transcriptional induction of mntH2 in the urinary tract is attributed to a low pH response . Alternatively , we hypothesized that MntH2 might contribute to Cu detoxification during CAUTI . Specifically , Cu and ceruloplasmin—the major mammalian Cu-binding protein—were recently found to accumulate during bacterial UTI and uropathogenic Escherichia coli ( UPEC ) has been shown to up-regulate Cu efflux systems during clinical UTI to avoid Cu toxicity [64 , 65] . Thus , we tested the ability of parent and ΔmntH2 strains to grow in human urine supplemented with Cu . However , both strains were completely resistant to physiological concentrations of Cu ( up to 0 . 5 μm ) and showed identical levels of Cu sensitivity at supra-physiological concentrations ( S9 Fig ) . While in need of further study , it appears that the prominent role of MntH2 in CAUTI could be simply attributed to its higher expression levels in the bladder environment when compared to EfaCBA . In summary , here we show that maintenance of Mn homeostasis is an essential trait enabling E . faecalis to fully exert its full pathogenic potential . Specifically , simultaneous inactivation of efaCBA and mntH2 renders E . faecalis avirulent in two mammalian infection models while only a triple ΔefaΔmntH1ΔmntH2 mutant strain was attenuated in the G . mellonella invertebrate model . These results expand the knowledge that bacterial Mn transport systems are promising targets for the development of novel antimicrobial therapies , which should be particularly effective to combat E . faecalis infections [66] . Work will soon be underway to uncover the significance of dietary Mn in the pathophysiology of E . faecalis , to elucidate the organ-dependent differential transcriptional regulation of each Mn transporter , and to understand the contribution of Mn-dependent responses to oxidative stress survival in the context of infection .
Bacterial strains and plasmids used in this study are listed in Table 1 . All E . faecalis strains were routinely grown overnight at 37°C in BHI supplemented with 150 μM MnSO4 . When required , 10 μg ml-1 erythromycin was added to the growth medium for stable maintenance of plasmids in the complemented strains . The primary antibodies used in the study were rabbit anti-Streptococcus group D antigen ( anti-E . faecalis lipoteichoic acid ) [67] and mouse anti-EbpAFull [47] . Horseradish peroxidase ( HRP ) -conjugated goat anti-mouse and goat anti-rabbit antisera from KPL and IRDye 680LT goat anti-rabbit from LI-COR Biosciences were used as secondary antibodies . Deletion of efaCBA , mntH1 , and mntH2 from the E . faecalis OG1RF strain was carried out using the pCJK47 markerless genetic exchange system [37] . Briefly , ~ 1 kb PCR products flanking the efaCBA , mntH1 , or mntH2 coding sequences were amplified with the primers listed in S1 Table . The amplicons included the first and last residues of the coding DNA to avoid unanticipated polar effects . Cloning of amplicons into the pCJK47 vector , electroporation and conjugation into E . faecalis strains and final isolation of single mutant strains were carried out as previously described [37] . Double mutants were obtained by conjugating the different pCJK constructs accordingly into Δefa , ΔmntH1 or ΔmntH2 single mutants . A triple mutant was obtained by conjugating the pCJK-mntH2 plasmid into the ΔefaΔmntH1 double mutant . All gene deletions were confirmed by PCR sequencing of the insertion site and flanking sequences in single , double and triple mutants . BHI agar was supplemented with 150 μM MnSO4 to enable isolation of the triple mutant strain . The shuttle vector pTG001 , a modified version of the nisin-inducible pMSP3535 plasmid [69] with an optimized RBS and additional restriction cloning sites ( a gift from Dr . Anthony Gaca , Harvard Medical School ) , was used to complement the ΔefaΔmntH1ΔmntH2 triple mutant strain . Briefly , the coding sequence of efaCBA , mntH1 , or mntH2 was amplified from OG1RF ( efaCBA , mntH1 , mntH2 ) using the primers listed in S1 Table , digested with the appropriate restriction enzymes and ligated into pTG001 digested with compatible restriction enzymes to yield plasmids pTG-efa , pTG-mntH1 and pTG-mntH2 . Upon propagation in E . coli DH10B , pTG001 ( empty plasmid ) and the complementation vectors were electroporated into OG1RF wild-type or ΔefaΔmntH1ΔmntH2 strains using a standard protocol [70] modified such that electroporated cells were immediately recovered in BHI supplemented with 0 . 4 M sorbitol . Presence of plasmids were confirmed via PCR amplification of the DNA insert region using plasmid-specific primers . In vitro growth of strains in metal-depleted medium was performed using the chemically-defined FMC medium [71] depleted for Mn , Fe , or Mn and Fe as previously described [6] . When indicated , the Mn and Fe concentrations were depleted from ~ 110 μM ( Mn ) and ~ 75 μM ( Fe ) in metal-replete FMC to < 90 nM in Mn- and/or Fe-depleted FMC . Overnight cultures were diluted 1:40 in complete FMC ( metal-replete ) and grown aerobically at 37°C to an OD600 of 0 . 25 ( early exponential phase ) . Then , cultures were diluted 1:100 into fresh FMC depleted for Mn , Fe , or Mn and Fe , and cell growth was monitored using the Bioscreen growth reader monitor ( Oy Growth Curves AB Ltd . ) . To assess colony formation on BHI plates , overnight cultures were washed once in sterile PBS containing 0 . 1 mM EDTA to chelate extracellular divalent cations , followed by a second PBS wash to remove EDTA . Washed cells were diluted 1:100 in PBS , and 5 μl aliquots were spotted on plain BHI agar plates or BHI plates containing 150 μM MnSO4 , or 150 μM FeSO4 . Plates were incubated overnight at 37°C before growth was recorded . For growth assessment of E . faecalis strains in the presence of 35 mM paraquat , overnight cultures were first diluted 1:40 in BHI and grown to an OD600 of ~ 0 . 25 prior to inoculation ( 1:100 ) into fresh BHI with or without 150 μM MnSO4 and 35 mM paraquat . Growth was monitored using the Bioscreen growth reader monitor over a 24 hours period . Growth in the presence of purified calprotectin and the His ( 103–105 ) —Asn calprotectin variant ( a gift from Dr . Walter Chazin and Dr . Eric Skaar , University of Vanderbilt ) was adapted from previous reports [15 , 72 , 73] . Briefly , overnight cultures were diluted 1:50 in fresh BHI broth and incubated 1 hour at 37°C . Then , cultures were diluted 1:100 into calprotectin medium , consisting of 38% BHI and 62% CP buffer [20 mM Tris pH 7 . 5 , 100 mM NaCl , 3 mM CaCl2 , 5 mM β-mercaptoethanol] . Native calprotectin and its variant unable to bind Mn [15] were added at a sub-inhibitory concentration ( 120 μg ml-1 ) , and growth at 37°C was recorded at 30 min intervals for up to 24 hours . When indicated , 10 μM MnSO4 , ZnSO4 , or FeSO4 , were added to the medium to test for growth rescue . Total metal concentration in BHI , human urine and within bacterial cells was determined as previously described by inductively coupled plasma—optical emission spectrometry ( ICP-OES ) at the University of Florida Institute of Food and Agricultural Sciences Analytical Services Laboratories [6] . Briefly , for quantification of metals in liquids , 18 ml BHI or urine were digested with 2 ml trace-metal grade 35% HNO3 prior to analysis . For quantification of the cellular metal content of bacterial cells , overnight cultures were washed twice with BHI and subsequently used to inoculate fresh BHI ( 1:20 ) and incubated statically at 37°C . After reaching an OD600 ~ 0 . 5 , cells were harvested by centrifugation , washed twice in ice-cold PBS supplemented with 0 . 5 mM EDTA to chelate extracellular divalent cations , and aliquots were collected for metal analysis . Bacterial pellets were resuspended in 1 ml 35% HNO3 and digested at 90°C for 1 hour in a high-density polyethylene scintillation vial ( Fisher Scientific ) . Digested bacteria were diluted 1:10 in reagent-grade H2O prior to ICP-OES metal analysis . Metal composition was quantified using a 5300DV ICP Atomic Emission Spectrometer ( Perkin Elmer ) , and concentrations were determined by comparison with a standard curve . Metal concentrations were normalized to total protein content determined by the bicinchoninic acid ( BCA ) assay . Larvae of G . mellonella was used to assess virulence of OG1RF and its derivatives as described elsewhere [74] . Briefly , overnight cultures were washed to reduce Mn carryover . Groups of 15 larvae ( 200–300 mg in weight ) were injected with 5 μl of bacterial inoculum containing ~ 5x105 CFU . Larvae injected with heat-inactivated E . faecalis OG1RF ( 30 min at 100°C ) were used as negative control . After injection , larvae were kept at 37°C and G . mellonella survival was recorded at selected intervals for up to 72 hours . Experiments were performed independently at least six times with similar results . Survival of strains in pooled human serum and pooled human urine ( Lee Biosolutions ) was monitored as previously described [6] . Briefly , overnight cultures grown in BHI+Mn were washed in sterile PBS as indicated above to remove excess Mn and inoculated 1:200 in human serum or urine . Cultures were incubated aerobically at 37°C and , at selected time points , aliquots were serially diluted and plated on Mn-supplemented BHI plates for colony-forming unit ( CFU ) determination . For determination of growth in human urine , overnight cultures were normalized to an OD600 of 1 . 0 in BHI+Mn . Cells were washed 3 times with 1X PBS followed by 1:1000 dilution into undiluted pooled female urine supplemented with 20 mg ml-1 of BSA and incubated at 37°C . Bacterial growth was monitored by quantifying CFU as described above . When indicated , serum and urine were supplemented with a final concentration of 1 mM FeSO4 ( 99% , Sigma ) , 1 mM MnSO4 ( 99% , Sigma ) or with increasing concentrations ( 0 . 5 μM , 0 . 5 mM or 1 mM ) of CuSO4 ( 99% , Acros Organics ) . Urine was pooled from 3 healthy female donors , clarified by centrifugation , filter-sterilized , and adjusted to pH 6 . 5 prior to use . All urine samples were collected after obtaining written consent as per the study approval from the Washington University School of Medicine Internal Review Board ( approval ID #201207143 ) . Male and female specific pathogen-free New Zealand White rabbits ( 2–4 kg; RSI Biotechnology ) were utilized in an endocarditis model to assess virulence as previously described [25] . Prior to surgery , the rabbits were sedated and anesthetized with a cocktail of ketamine , xylazine and buprenorphine . A 19-gauge catheter was inserted into the aortic valve by way of the right carotid artery to induce minor damage . Each catheter was trimmed and sutured in place and the incision was closed with staples . Later the same day , duplicate inoculum preparation began by inoculating all strains into BHI for overnight growth in 6% O2 . For the ΔefaΔmntH1ΔmntH2 strain only , BHI medium was supplemented with 100 μM Mn . The next morning , cultures were diluted 1:10 in fresh BHI with Mn supplementation and incubated with lids tight at 37°C until an OD600 of ~0 . 8 was obtained . The cells were then washed twice with 7 ml Chelex-treated ( Bio-Rad ) PBS containing 0 . 1mM EDTA . As determined in previous pilot experiments , a portion of the duplicate resuspended cells was removed and diluted to achieve equal strain representation and a total inoculum of ~107 CFU/ml . From each sample , 1 ml was removed , sonicated and plated for enumeration , while 0 . 5 ml were injected into the peripheral ear vein of each of three rabbits per inoculum . A total of six animals were used for each set of experiments . However , one animal per group had to be euthanized before the set time point and was not included in the final analysis . Forty-eight hours after inoculation , rabbits were euthanized via intravenous injection of Euthasol ( Med-Pharmex Inc . ) . Catheter placement was verified upon necropsy . Harvested cardiac vegetations and spleens were placed into PBS , homogenized and plated on Mn-supplemented BHI agar plates . Resulting colonies were picked and patched onto a new BHI plate supplemented with Mn as appropriate . PCR screens were used to determine the frequency with which each strain was recovered from heart vegetations and spleens . Thus , 50 to 100 colonies per organ and animal were randomly chosen and screened by colony PCR ( primers listed in table S1 ) for their efaCBA and mntH2 status ( either wild-type or deleted gene ) . To verify that the ΔefaΔmntH2 and the ΔefaΔmntH1ΔmntH2 strains are not growth inhibited in vitro when co-cultured with the parent OG1RF and their respective single mutant strains ( Δefa or ΔmntH2 ) , overnight cultures were diluted in PBS to an initial inoculum of ~ 2 x 103 CFU of each strain . Then , we co-cultured OG1RF with Δefa and ΔefaΔmntH1ΔmntH2 , or with ΔmntH2 and ΔefaΔmntH2 strains in BHI supplemented with 150 μM MnSO4 . After 9 hours of incubation , PCR screens were used to determine the frequency with which each individual strain was recovered from the medium as described above . The mice used in this study were 6-week-old female wild-type C57BL/6Ncr mice purchased from Charles River Laboratories . Mice were subjected to transurethral implantation and inoculated as previously described [48] . Mice were anesthetized by inhalation of isoflurane and implanted with a 5-mm length platinum-cured silicone catheter . When indicated , mice were infected immediately following catheter implantation with 50 μl of ~2 × 107 CFU of bacteria in PBS introduced into the bladder lumen by transurethral inoculation as previously described [48] . To harvest the catheters and organs , mice were euthanized 24 hours post-infection by cervical dislocation after anesthesia inhalation , and bladder , kidneys , spleen and heart were aseptically harvested . Subsequently , the silicone implant was retrieved from the bladder . Silicone catheters ( 1 cm , Nalgene 50 silicone tubing , Brand Products ) or 96-well polystyrene plates ( Grenier CellSTAR ) were coated overnight at 4°C with 100 μg ml-1 human fibrinogen free of plasminogen and von Willebrand Factor ( Enzyme Research Laboratory ) . The next day , E . faecalis overnight cultures were diluted to an optical density ( OD600 ) of 0 . 2 in BHI broth . The diluted cultures were centrifuged , washed three times with 1x PBS , and diluted 1:100 in urine supplemented with 20 mg ml-1 BSA . Bacterial cells were allowed to attach to the fibrinogen-coated silicone catheters or 96-well polystyrene plates for 24 hours at 37°C under static conditions . After bacterial incubation , catheters and microplates were washed with PBS to remove unbound bacteria . Half of the catheters were vortexed for 30 sec , sonicated for 5 min , and vortexed again for 30 sec to retrieve bacteria in the biofilm for CFU quantification . The other half of catheters were used to visualize biofilms . Briefly , catheters were fixed with formalin for 20 min and then washed three times with PBS . Catheters were blocked at 4°C with 5% dry skin milk PBS , followed by three washes with PBS-T . After the washes , plates were incubated for an hour at room temperature with rabbit anti-Streptococcus group D antigen antisera ( 1:500 ) in dilution buffer . Plates were washed with PBS-T , incubated with the Odyssey secondary antibody ( goat anti-rabbit IRDye 680LT , diluted 1:10 , 000 ) for 45 min at room temperature and washed three times with PBS-T . As a final step , plates were scanned for infrared signal using the Odyssey Imaging System ( LI-COR Biosciences ) . Fibrinogen coated-catheters were used as a control for any auto-fluorescence . For assessment of biofilm formation on fibrinogen-coated 96-well polystyrene plates , microplates were stained with 0 . 5% crystal violet for 10 min at room temperature . Excess dye was removed by rinsing with sterile water and then plates were allowed to dry at room temperature . Biofilms were resuspended with 200 μl of 33% acetic acid and the absorbance at 595 nm was measured on a microplate reader ( Molecular Devices ) . Experiments were performed independently in triplicate per condition and per experiment . Surface expression of EbpA by E . faecalis OG1RF parent and Mn transporter mutants was determined by ELISA as previously described [75] Bacterial strains were grown for 18 hours in urine supplemented with 20 mg ml-1 of BSA . Then , cells were washed three times with PBS , normalized to an OD600 of 0 . 5 , resuspended in 50 mM carbonate buffer ( pH 9 . 6 ) containing 0 . 1% sodium azide and used to coat ( 100 μl aliquots ) Immulon 4HBX microtiter plates overnight at 4°C . The next day , plates were washed three times with PBS-T ( PBS containing 0 . 05% Tween 20 ) to remove unbound bacteria and blocked for 2 hours with 1 . 5% BSA–0 . 1% sodium azide–PBS ( BB ) followed by three washes in PBS-T . EbpA surface expression was detected using mouse anti-EbpAFull antisera , which was diluted 1:100 in PBS dilution buffer ( PBS with 0 . 05% Tween 20 , 0 . 1% BSA , and 0 . 5% methyl α-d-mannopyronoside ) before serial dilutions were performed . A 100-μl volume was added to the plate , and the reaction mixture was incubated for additional 2 hours . Subsequently , plates were washed three times with PBS-T , incubated for 1 hour with HRP-conjugated goat anti-rabbit antisera ( 1:2 , 000 ) , and washed again three times with PBS-T . Detection was performed using a TMB substrate reagent set ( BD ) . The reaction mixtures were incubated for 5 min to allow color to develop , then the reactions were stopped by the addition of 1 . 0 M sulfuric acid . The absorbance was determined at 450 nm . Titers were defined as the last dilution with an A450 of at least 0 . 2 . As an additional control , rabbit anti-Streptococcus group D antiserum was used to verify that whole cells of all strains were bound to the microtiter plates at similar levels . EbpA expression titers were normalized against the bacterial titers at the same dilution . The aortic valve homogenate RNAs used for these experiments were collected and analyzed in another study from rabbits infected with E . faecalis OG1RF in an experimental model of IE [76] . Gene expression was studied in RNA samples collected from animals infected for two days ( early infection , n = 5 rabbits ) or three to four days ( advanced infection , n = 8 rabbits ) . For transcript quantifications during CAUTI , OG1RF cells were recovered from bladders of three infected mice , pooled and immediately placed in RNAlater solution ( in triplicate , total n = 9 animals ) . RNA extraction , reverse transcription and real-time PCR were carried out following standard protocols [6 , 77] . Data were analyzed using GraphPad Prism 6 . 0 software unless otherwise stated . Differences in cellular metal uptake , final growth in Mn-depleted FMC or human urine , the percentage of strains recovered from the rabbit IE experimental model , and the log10-transformed CFU values recovered from in vitro catheter biofilms were determined via ordinary one-way ANOVA followed by post-test comparisons . Log10-transformed CFU values from serum survival and calprotectin growth experiments were analyzed via a two-way ANOVA followed by comparison post-tests . While differences in the G . mellonella killing rate of mutant strains was assessed with the Mantel-Cox log-rank test , final 72 hour survival of larvae were similarly compared via ordinary one-way ANOVA with Dunnett’s multiple comparison post-test . Of note , two outliers ( one for a ΔmntH1 replicate , another for a ΔefaΔmntH1ΔmntH2 replicate ) were identified using the ROUT method ( Q = 1% ) and removed from the final analysis . For CAUTI experiments , biofilm assays and EbpA expression , data from multiple experiments were pooled and Two-tailed Mann-Whitney U tests were performed . To determine statistical significance in fold-change transcription of selected genes , fold-change values for each gene were plotted as geometric mean with the corresponding 95% confidence interval ( error bars ) . A line at y = 1 denotes equal transcripts in inoculum control vs in vivo condition . 95% confidence intervals that did not cross y = 1 were significantly different ( * p<0 . 05 ) from the inoculum control . Urine samples for growth curves were collected after obtaining informed written consent for all subjects enrolled in the study as per the study approval from the Washington University School of Medicine Internal Review Board ( approval ID #201207143 ) . Populations generally classified as vulnerable , including children under the age of 18 , were not enrolled in the study . Only subjects 18 years of age or older at the time of consent were eligible for the study . No group or persons were excluded from the study due to race , ethnicity or gender . Case subjects were enrolled solely based on the eligibility criteria . Animal procedures for rabbit IE were approved by the Institutional Animal Care and Use Committee of the Virginia Commonwealth University as part of protocol number AM10030 as well as the University of Minnesota Institutional Animal Care and Use Committee as part of protocol number 0910A73332 . The Washington University Animal Studies Committee approved all mouse infections and procedures as part of protocol number 20150226 . All animal care was consistent with the Guide for the Care and Use of Laboratory Animals from the National Research Council and the USDA Animal Care Resource Guide .
|
Enterococcus faecalis is a leading cause of hospital-acquired infections that are often difficult to treat due to their exceptional multidrug resistance . Manganese ( Mn ) is an essential micronutrient for bacterial pathogens during infection . To prevent infection , the host limits Mn bioavailability to invading bacteria in an active process known as nutritional immunity . To overcome this limitation , bacteria produce high-affinity Mn uptake systems to scavenge Mn from host tissues . Here , we identified the main Mn transporters of E . faecalis and show that , by working collectively , they are essential for growth of this opportunistic pathogen in Mn-restricted environments . Notably , the inability to acquire Mn during infection rendered E . faecalis virtually avirulent in different animal models , thereby revealing the essentiality of Mn acquisition to enterococcal pathogenesis . The results reported here highlight that bacterial Mn transport systems are promising targets for the development of novel antimicrobial therapies , which are expected to be particularly powerful to combat enterococcal infections .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"methods"
] |
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"biotechnology",
"medicine",
"and",
"health",
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"pathology",
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"laboratory",
"medicine",
"manganese",
"enterococcus",
"infections",
"pathogens",
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"microbiology",
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"animals",
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] |
2018
|
Manganese acquisition is essential for virulence of Enterococcus faecalis
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Chagas disease is a vector-borne parasitic disease of major public health importance . Current prevention efforts are based on triatomine vector control to reduce transmission to humans . Success of vector control interventions depends on their acceptability and value to affected communities . We aimed to identify opportunities for and barriers to improved vector control strategies in the Yucatan peninsula , Mexico . We employed a sequence of qualitative and quantitative research methods to investigate knowledge , attitudes and practices surrounding Chagas disease , triatomines and vector control in three rural communities . Our combined data show that community members are well aware of triatomines and are knowledgeable about their habits . However , most have a limited understanding of the transmission dynamics and clinical manifestations of Chagas disease . While triatomine control is not a priority for community members , they frequently use domestic insecticide products including insecticide spray , mosquito coils and plug-in repellents . Families spend about $32 US per year on these products . Alternative methods such as yard cleaning and window screens are perceived as desirable and potentially more effective . Screens are nonetheless described as unaffordable , in spite of a cost comparable to the average annual spending on insecticide products . Further education campaigns and possibly financing schemes may lead families to redirect their current vector control spending from insecticide products to window screens . Also , synergism with mosquito control efforts should be further explored to motivate community involvement and ensure sustainability of Chagas disease vector control .
Chagas disease is a vector-borne parasitic disease endemic in the Americas , where it is of major public health importance , affecting up to 8–9 million people [1] . Recent estimates also illustrate the very high disease burden it causes [2] . Chagas disease is present in Mexico , but its importance is poorly documented and controversial . While the Ministry of Health officially reports a few hundred cases [3] , one study estimated the number of people infected to be nearly 6 million [4] . The only nationwide studies are from the late 1980s and indicate a national seroprevalence of 1–2% , with an important heterogeneity among regions and states [5]–[7] . In Yucatan , seroprevalence ranges from 1% in urban areas up to 5% in rural villages [8] , [9] . Despite these data , there is no national vector control program to reduce transmission , nor are there education campaigns to raise awareness of the disease in Mexico . The Mexican health care system is divided into the Instituto Mexicano de Seguro Social ( IMSS ) , which covers workers in the private sector , and the Instituto de Seguridad y Servicios Sociales de los Trabajadores ( ISSSTE ) , which covers workers in the public sector . The Seguro Popular de Salud , launched in 2004 , aims at covering the 48 million the lowest income quintile left uninsured by IMSS and ISSSTE programs [10] . These programs provide basic health care and medicine to patients , and some health education . Vector control activities , mostly focused on the prevention of dengue , and to a lesser extent on malaria , are conducted directly by the Secretaria de Salud . The current national guidelines [11] recommend the cleaning of the house in case of triatomine infestation , followed by insecticide spraying in case of recurrent infestation or if a human case is detected , and are applied on a case by case basis . Most vectorial transmission to humans is associated with domiciliated triatomines species well adapted to human housing . However , several autochtonous triatomine species can transiently invade houses and present different degrees of adaptation to human housing . In these conditions , conventional indoor insecticide spraying is of limited efficacy for vector control , and it is thus necessary to design novel vector control interventions that are tailored to vector behavior and ecology for better efficacy [12]–[15] . Communities' knowledge , attitudes and practices related to vector-borne diseases vary depending on the vector and may moderate acceptance of and participation in vector control activities [16]–[19] . For example , while conventional insecticide spraying of domiciles for triatomine control was well-accepted by communities in Honduras , an alternative based on insecticidal paint had a low level of acceptance from both the communities and vector control personnel because it was perceived as less effective and had a strong odor [20] . As success of vector control interventions depends on their acceptability and value to affected communities , an understanding of sociocultural factors is needed to inform development of control strategies [21] . Communities affected by Chagas disease often have biological and ecological knowledge of triatomine vectors , while understanding of parasite transmission and the disease itself is more limited [22]–[27] . Community members' knowledge and perceptions can however be quite variable , depending on the epidemiological importance of Chagas disease in the area , and the intensity of previous vector control and education activities [23] , [24] , [26] , [28] , [29] . Common community practices and public health interventions to control triatomine house infestation also vary , from a heavy reliance on insecticide spraying in Honduras [23] , to a focus on improved hygiene and housing improvement in Minais Gerais , Brazil [24] and Bolivia [25] . In the Yucatan peninsula , Mexico , Triatoma dimidiata is the main vector and infests houses on a seasonal basis [30]–[38] . Some risk factors for house infestation have been identified [34] , [39] , [40] and may be targeted for improved control . Integrated vector control interventions have been evaluated [14] , [15] , [41] , however , no information is available on how communities perceive the disease and T . dimidiata vectors . In the present study , we investigated community knowledge , attitudes and practices surrounding Chagas disease , triatomines and vector control to identify opportunities for and barriers to improved vector control strategies , as well as needs for tailored Chagas disease education .
The study was carried out in the villages of Bokoba ( 21 . 01°N , 89 . 07°W ) , Teya ( 21 . 05°N , 89 . 07°W ) and Sudzal ( 20 . 87°N , 88 . 98°W ) , located about 15–20 km apart in the central part of Yucatan , Mexico ( Figure 1 ) . There are a total of 570 , 702 and 416 houses in Bokoba , Teya and Sudzal , respectively , all of which have been georeferenced [34] . The respective populations are of about 2 , 000 inhabitants in both Bokoba and Teya and 1 , 600 in Sudzal , with about 40% of the population below 14 years of age [39] . Most of the population ( over 90% ) are native Mayan speakers ( most are also native Spanish speakers ) . Most heads of households are subsistence farmers ( 38% ) , and a few work in construction or manufacture ( 14% ) ; a minority have a regular work contract ( 22% ) [39] . The majority ( 63% ) have limited income and receive social welfare benefits ( “Oportunidades” program ) [39] . The average educational level is completion of primary school [39] . Triatomine surveys and Chagas disease-related research activities have been carried out in these communities since 2006 , including a pilot vector control intervention [14] and a serological survey , as well as basic Chagas disease education and awareness . A sequence of qualitative and quantitative research methods was employed to investigate community members' knowledge , attitudes and practices surrounding Chagas disease , triatomines and vector control in each of the study communities . Freelisting , the first method , provided us with appropriate terminology and an entry point to engaging in further research in the communities [42] . It also allowed us to evaluate triatomines and Chagas disease in reference to other biting insects and vector-borne diseases to gain greater perspective on participant priorities and evaluate the potential for synergistic , multi-disease vector control interventions . Results from freelisting were used to develop the content of ranking exercises , which in turn informed development of the focus group discussion guide . We explored threat perception , as defined in the Health Belief Model as perceived severity and susceptibility , by asking about dangerousness of biting insects and biting frequency [43] . Results from all previous methods were used to design a survey to quantify and further explore previous results . All fieldwork was performed by experienced social scientists . This mixed methods approach allowed us to leverage the comparative strengths of qualitative and quantitative approaches and to use complementary data to triangulate findings and corroborate conclusions [44] . The protocol and all activities were reviewed and approved by both the World Health Organization and the Autonomous University of Yucatan institutional bioethics committees . All participants provided written informed consent before engaging in any research activities .
We present here a first assessment of community knowledge , perceptions and practices related to Chagas disease and triatomine vectors in Yucatan , Mexico , evaluated through mixed qualitative and quantitative approaches . This study provides key data for the design of culturally acceptable vector control interventions and identifies specific needs for Chagas disease education . Our data demonstrate that community members are aware of triatomines , knowledgeable about their habits , and frequently come into contact with them in their houses . Community members' identification of pictures of adult triatomines , but not nymphs , and their descriptions of bugs flying in through windows at night matches our previous observations and description of the seasonal infestation by adult T . dimidiata and its limited colonization of houses [31] , [33] , [35]–[37] . Community members are also well aware of some specific aspects of triatomine behavior , such as their presence in the bushes surrounding villages , and their habit of hiding in rock piles , which have been identified as risk factors for house infestation [34] , [35] , [39] , [40] . This well-developed knowledge of triatomines is similar to that observed in other communities from endemic regions [22]–[29] . The elevated proportion of households reporting seeing triatomines inside their homes is in agreement with the high infestation by T . dimidiata that has been described in the Yucatan peninsula and further illustrates the risk of Chagas disease in the region . While triatomines are considered “dangerous , ” this seems to be due to the actual bite wound rather than a complete understanding of Chagas disease . A few participants did know that a chronic condition can develop over time , but most had a limited understanding of Chagas disease transmission , its relationship with triatomines and the specific health consequences . Again , this appears similar to what has been observed in other countries and communities [23]–[29] . Even those who mentioned a chronic disease always expressed some level of skepticism ( e . g . ‘I've been told that…’ ) , indicating that the threat of Chagas disease has not truly been appropriated in these communities and remains theoretical . This lack of knowledge and awareness of Chagas disease and its relationship with triatomines can be considered a major barrier for vector control , as it likely results in communities having limited interest in and motivation for eliminating triatomines . There is thus an important need for education on these aspects . The health centers of these communities appear to be appropriate settings for information dissemination , although multiple sources and improved educational materials may allow for more extensive and effective diffusion . Indeed , most of the inhabitants referred to talks and pamphlets provided by our research group through the health center over the past years as their main source of information . Although it was not the focus of our study , community members spontaneously and frequently spoke of mosquitoes and dengue fever , and seemed to have a good knowledge of this disease and its prevention , suggesting that dengue vector control and education activities , together with the high visibility of dengue fever ( incidence of 280/100 , 000 inhabitants in the state of Yucatan ) may have been effective in raising awareness of dengue fever [50] and could serve as models for Chagas disease interventions . However , the high visibility of dengue fever compared to Chagas disease may partially explain higher community awareness and threat perception . Focus group discussion findings indicate that participants do not have personal experience with Chagas disease . However , many had friends or relatives that had had dengue fever , and were able to discuss the effects of the disease . Insect control , and more specifically mosquito control , is a concern for a majority of community members , though prevention of triatomine infestation is not a priority . They frequently use a number of domestic insecticide products , including insecticide spray , mosquito coils , and plug-in repellents , even though they are aware of their limited effectiveness . Many spend around one $ US each week to purchase these products , leading to a cumulative spending of about 32 $ US annually and per household . Given that the average income of these households is limited ( 63% of households benefit from the social welfare program “Oportunidades , ” [39] which targets families with an estimated income below a poverty threshold established at 600–1300 $US/person/year ) , this spending supports the importance of vector control for community members . Based on motivation to control insects in general and mosquitoes in particular , it is likely that many households would engage in further vector control efforts directed against triatomines if they recognized them as severe threats . Interventions aimed at preventing triatomine infestation , but that also protect against other insects such as mosquitoes , are likely to be adopted by communities . Importantly , the studied communities perceive some strategies to be potentially more effective than insecticide products . For example , they stressed the importance of having a clean yard to avoid insects and associate triatomine infestation with a dirty yard . This is in agreement with modeling and field studies which indicate that a clean yard can result in a 50–60% reduction in house infestation by triatomines [14] , [41] . Nonetheless , time and effort may remain barriers to yard cleaning . Many yards are infested and even colonized by T . dimidiata [36] , [38] . Another issue is that yard cleaning is perceived as requiring a collective effort to be effective , and many participants mentioned that their efforts in maintaining a clean yard were ineffective if neighbors did not also maintain their yards appropriately . Because yard cleaning also contributes to mosquito vector control , education messages may be designed to synergize efforts against dengue fever and Chagas disease vectors . Window insect screens were also perceived as effective , as previously demonstrated by modeling and field studies [14] , [15] , [41] , and desirable by community members . The main obstacle to wider use is cost , as screens are perceived as unaffordable for many households ( F9: “Either we put mosquito screens or we eat . ” ) . However , the annual cumulative spending on insecticide products of a typical household is comparable to the price of screens . Indeed , we reported in a previous pilot study a cost of 40–50 $US/house for the manufacture and installation of screens [14] . Appropriate funding schemes might make it possible for households to redirect their current vector control spending from mosquito coils , insecticide spray and plug-in repellent , which have little or no effect on triatomine infestation [39] , to more effective insect screens , [14] , [15] , [41] and thus benefit from better vector control . Such funding or microcredit schemes , together with specific Chagas disease education , may be included as part of the Seguro Popular health insurance program , which targets many community members . Again , the effectiveness of insect screens in preventing all vector-borne diseases should be emphasized . Indeed , multi-disease and integrated vector control interventions are believed to be more cost-effective , as well as more effective and sustainable than single disease-centered interventions [51] , [52] . Finally , women are mostly responsible for insect prevention in the home , including measures taken in the peridomestic area , and should be engaged in the design and implementation of interventions , as observed in other communities [53] . They are motivated to protect children especially; the benefit of avoiding acute Chagas disease in children should be emphasized in future educational efforts . Though they were not included in the current analysis , we found children to be interested in and enthusiastic about study activities , such as yard cleaning . Involving them in prevention activities might also increase community participation [24] , [54] . This study is a formative , descriptive analysis of the knowledge , attitudes and practices of communities related to triatomine vector control and Chagas disease that relies on participant response . Possible limitations include response bias ( all methods ) and social desirability bias ( focus group discussions ) . In order to minimize response bias , investigators trained in an anthropological approach to qualitative data collection conducted freelisting and ranking exercises as well as focus group discussions . Also , investigators purposefully positioned themselves as non-experts and redirected participant questions about biting insects , insect prevention , and insect-related disease back to participants . Social desirability bias may have caused participants to over report frequency or intensity of insect prevention practices , as these were said to be important for child health and therefore indicative of good parenting . Recall bias may have affected responses to some survey questions , in particular those that asked respondents to quantify prevention method use and price . Finally , the communities in which we worked may be more familiar with triatomines and Chagas disease than surrounding communities because of education sessions in relation to past research , but this only strengthens our conclusion that Chagas disease , though present , is not well understood by communities at risk for infection . In conclusion , the studied communities in Yucatan , Mexico appear very knowledgeable about triatomine vectors , but there is a clear need for education on Chagas disease to increase awareness of and interest in controlling this disease . Mosquitoes rather than triatomines are a concern for most households , who dedicate a significant proportion of their limited income to the purchase of products of limited effectiveness against triatomines . Alternatively , yard cleaning and window screens are perceived as effective and desirable by community members . These two methods of vector control , which could prevent both triatomines and mosquitoes from entering houses and biting inhabitants , should be promoted . The cost of insect screens , however , is a barrier that should be addressed , potentially through financing schemes . Importantly , synergism with dengue vector control efforts should be leveraged to increase community involvement and ensure sustainability of Chagas disease control .
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Chagas disease is an important parasitic disease transmitted by triatomine bugs . Current prevention efforts are based on eliminating triatomines from homes to reduce disease transmission to humans . However , the success of these control interventions depends on their acceptability and value to affected communities . We aimed to identify opportunities for and barriers to triatomine control strategies in the Yucatan peninsula , Mexico . We used a sequence of group discussion , interviews , and a survey to investigate the perception and knowledge of communities on Chagas disease and triatomines in three villages from the Yucatan peninsula , Mexico . Inhabitants are rather familiar with triatomine bugs , but do not associate well these bugs with Chagas disease and its clinical manifestations . Mosquito rather than triatomine control is a common preoccupation , and households frequently use insecticide spray , mosquito coils and plug-in repellents , spending about $32 US per year on these products . Alternative methods such as yard cleaning and window screens are perceived as desirable and potentially more effective . Screens are nonetheless described as unaffordable . The promotion of education campaigns and possibly financing schemes could help families to redirect their current spending from insecticide products to window screens . Also , synergism with mosquito control efforts should be further explored to motivate community involvement and ensure sustainability of Chagas disease vector control .
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2014
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Opportunities for Improved Chagas Disease Vector Control Based on Knowledge, Attitudes and Practices of Communities in the Yucatan Peninsula, Mexico
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Despite the central importance of transcriptional regulation in biology , it has proven difficult to determine the regulatory mechanisms of individual genes , let alone entire gene networks . It is particularly difficult to decipher the biophysical mechanisms of transcriptional regulation in living cells and determine the energetic properties of binding sites for transcription factors and RNA polymerase . In this work , we present a strategy for dissecting transcriptional regulatory sequences using in vivo methods ( massively parallel reporter assays ) to formulate quantitative models that map a transcription factor binding site’s DNA sequence to transcription factor-DNA binding energy . We use these models to predict the binding energies of transcription factor binding sites to within 1 kBT of their measured values . We further explore how such a sequence-energy mapping relates to the mechanisms of trancriptional regulation in various promoter contexts . Specifically , we show that our models can be used to design specific induction responses , analyze the effects of amino acid mutations on DNA sequence preference , and determine how regulatory context affects a transcription factor’s sequence specificity .
High-throughput sequencing allows us to sequence the genome of nearly any species at will . The amount of genomic data available is already enormous and will only continue to grow . However , this mass of data is largely uninformative without appropriate methods of analyzing it . Despite decades of research , much genomic data still defies our efforts to interpret it . It is particularly challenging to interpret non-coding DNA such as intergenic regulatory regions . We can infer the locations of some transcription start sites and transcription factor binding sites , but these inferences tell us little about the functional role of these putative sites . In order to better interpret these types of sequences , we need a better understanding of how sequence elements control gene expression . A deep understanding of the relationship between DNA sequence and gene expression would enable one to a ) predict the binding strengths of novel transcription factor binding sites and b ) design regulatory sequences de novo for synthetic biology applications . An important avenue for developing this level of understanding is to propose models that map sequence to function and to perform experiments that test these models . One challenge that has made it difficult to develop quantitative sequence-function mappings is the fact that an extremely small portion of known regulatory sequences are understood on a quantitative biophysical level . Over half of the genes in Escherichia coli , which is arguably the best-understood model organism , lack any regulatory annotation ( see RegulonDB [1] ) . Those operons whose regulation is well described ( e . g . the lac , rel , and mar operons [2–4] ) required decades of study involving laborious genetic and biochemical experiments [5] . A wide variety of new techniques have been proposed and implemented to simplify the process of determining how a gene is regulated . Chromatin immunoprecipitation ( ChIP ) based methods such as ChIP-chip and ChIP-seq make it possible to determine the genome-wide binding locations of individual transcription factors of interest . Massively parallel reporter assays ( MPRAs ) have made it possible to read out transcription factor binding position and occupancy in vivo with base-pair resolution , and provide a means for analyzing additional features such as “insulator” sequences [6–8] . In vitro methods based on protein-binding microarrays [9] , SELEX [10–12] , MITOMI [13–15] , and binding assays performed in high-throughput sequencing flow cells [16 , 17] have made it possible to measure transcription factor affinity to a broad array of possible binding sites and can also account for features such as flanking sequences [15 , 18 , 19] . However , in vitro methods cannot fully account for the in vivo consequences of binding site context and interactions with other proteins . Current in vivo methods for measuring transcription factor binding affinities , such as bacterial one-hybrid [20 , 21] , require a restructuring of the promoter so that it no longer resembles its genomic counterpart . Additionally , efforts to computationally ascertain the locations of transcription factor binding sites frequently produce false positives [22 , 23] . Furthermore , a common assumption underlying many of these methods is that transcription factor occupancy in the vicinity of a promoter implies regulation , but it has been shown that occupancy cannot always accurately predict the effect of a transcription factor on gene regulation [24 , 25] . As these examples show , it remains challenging to integrate multiple aspects of transcription factor binding into a cohesive understanding of gene regulation that would allow for predictive models that map sequence to function . In previous work we showed how an MPRA called Sort-Seq can be used on virgin promoters to identify regulatory architectures [26] . The current work takes the logical and critical next step of rigorously examining how reliable the Sort-Seq results are as a foundation for predicting and controlling transcription with single-nucleotide resolution . In Ref . [27] , we showed that the MPRA Sort-Seq [28] , combined with a simple linear model for protein-DNA binding specificity , can be used to accurately predict the binding energies of multiple RNAP binding site mutants , serving as a jumping off point for the use of such models as a quantitative tool in synthetic biology . Here we apply this technique to transcription factor binding sites in an effort to better understand how transcription factors interact with regulatory DNA under different conditions . Specifically , we use Sort-Seq to map sequence to binding energy for a repressor-operator interaction , and we rigorously characterize the variables that must be considered in order to obtain an accurate mapping between DNA sequence and binding energy . We then use our sequence-energy mapping to design a series of operators with a hierarchy of controlled binding energies measured in absolute energy units ( kBT ) . To demonstrate our control over these operators and their associated regulatory logic , we use these characterized binding sites to design a wide range of induction responses with different phenotypic properties such as leakiness , dynamic range and [EC50] . Next , we focus our attention on the synergy between mutations in the amino acid sequence of transcription factors and their corresponding binding sites . Finally , we show the broader reach of these results by exploring how binding site position and regulatory context can change the DNA-protein sequence specificity for multiple different transcription factors .
A major goal of this study was to show that one can use Sort-Seq to precisely map DNA sequence to binding energy for a transcription factor binding site , thus making it possible to predict and manipulate transcriptional activity in vivo . While numerous in vitro studies have successfully mapped sequence to affinity [9–17 , 29 , 30] , and some in vivo studies have used methods such as bacterial one-hybrid to provide such mappings as well [20 , 21] , these studies are limited because they do not reflect the actual wild-type arrangement of regulatory elements , thus potentially missing vital regulatory information . Moreover , while position-weight matrices ( PWMs ) derived from genomic data have traditionally been used to ascertain in vivo sequence specificities , it can be difficult to convert these specificities into quantitative binding energy mappings due to the relatively small number of sequences that are used to generate these PWMs . Sort-Seq has previously been shown to be a promising technique for mapping protein binding sequences to binding energies . In Ref . [27] , binding energy predictions for RNAP were made from an energy matrix generated in Ref . [28] that used the wild-type lac promoter as a reference sequence ( i . e . the sequence that was mutated to perform Sort-Seq ) . Here , we design experiments that use the Sort-Seq technique described in [28] with the specific intent of creating energy matrices with maximum predictive power ( see Fig 1 ) , and we test the predictions from these matrices against measured binding energies . We show that such predictive matrices can be produced for multiple transcription factors ( e . g . XylR , PurR , and LacI ) implicated in an array of regulatory architectures . To thoroughly test the accuracy of our predictive matrices , we begin with promoters that employ “simple repression , ” in which a repressor binds to an operator such that it occludes RNAP binding , thereby preventing transcription and repressing the gene [31] . As a model for how sequence-energy mappings might be used for transcription factor binding sites in simple repression architectures , we interrogate the binding specificity of the lac repressor ( LacI ) . LacI was chosen for this role because it is well-characterized and has known binding sites in only one operon within the genome , making it an ideal choice for this kind of systematic and rigorous analysis . We create three distinct energy matrices in which each of the natural lac operators ( O1 , O2 , or O3 [2] ) acts as the reference sequence . S1 Fig lists the wild-type sequences for these simple repression constructs . As described in Fig 1 , to perform Sort-Seq we start by mutating the promoter at a rate of ∼ 10% . Here we mutate both the RNAP binding site and the operator , starting with either O1 , O2 , or O3 for the operator sequence . While our analysis focuses on the operators themselves , mutating the RNAP site as well aids in model-fitting as described in S1 Text . We place the promoters upstream of a fluorescent reporter gene and create a plasmid library of these constructs . We transform this plasmid library into a population of E . coli in which lacI and lacZYA have been deleted , but lacI has been reintroduced to the genome with a synthetic RBS that allows us to precisely control the LacI copy number within the cell , as described in Ref . [32] . We require at least 106 transformants for each plasmid library to ensure sufficient library diversity . Then , we use fluorescence-activated cell sorting ( FACS ) to sort E . coli containing these plasmids into four bins based on their expression levels . We perform high-throughput sequencing on the libraries from each bin . For the majority of our analysis , we split the sequencing results into three separate “replicates . ” As discussed in S1 Text , this provides a level of variation that is comparable to multi-day biological replicates . Once we have a set of promoter sequences with corresponding expression levels , we use these data to infer an energy matrix for the transcription factor binding site that assigns energy values ( in arbitrary units ) to each base at each sequence position . We use Markov Chain Monte Carlo ( MCMC ) with a Metropolis-Hastings algorithm to infer a set of energy matrix values that maximizes the mutual information between the predicted binding energies of our sequences and their corresponding expression bins . Briefly , this algorithm proceeds as follows: 1 ) a set of energy matrix parameters is proposed for each base at each operator position , 2 ) the proposed matrix is used to calculate the binding energies ( in arbitrary units ) of the set of binding site sequences , and 3 ) this set of energy parameters is accepted or rejected with some probability . If it is rejected , a new set of energy parameters is proposed , some distance away from the previous parameter set . As discussed in detail in Ref . [33] , the probability of accepting a proposal is derived from the probability distribution p ( data|model ) ∝ 2NI ( ε ( σ ) ;μ ) , where N is the number of data points and I ( ε ( σ ) ; μ ) represents the mutual information between the energy prediction ε ( σ ) for the promoter sequence σ and the expression bin μ . In other words , the set of proposed values is accepted or rejected according to how well the associated binding energy predictions explain the observed distribution of sequences in expression bins . After this algorithm has been iterated 30000 times ( after 10000 repeats for a “burn-in” period ) , the energy matrix values are then determined by calculating the sample mean of the parameter values that were accepted . Once an energy matrix has been inferred , the matrix is fixed such that the matrix elements corresponding to the reference sequence are set at 0 , and the other matrix elements at each sequence position are calculated relative to this reference element . The reference sequence is the operator sequence that serves as the “wild-type” in each Sort-Seq experiment–that is , the sequence away from which the library sequences are mutated . For more details on this procedure , see S1 Text . The energy matrices that result from the procedure described above are given in arbitrary energy units . To convert these arbitrary units into absolute energy units , we also perform Bayesian parameter estimation using MCMC to determine the scaling factor that should be applied to the energy matrix to convert each position into kBT energy units ( we note that 1 kBT ≈ 0 . 62 kcal/mol at T = 37°C ) . This inference procedure is highly similar to the procedure outlined above , but where before we maximized the mutual information between predicted binding energies and expression bin for a full set of energy matrix parameters , here we maximize the mutual information between predicted expression and expression bin for a single parameter , which is the scaling factor that converts a matrix into absolute energy units . This scaling factor is a “diffeomorphic mode” of the model that cannot be inferred by direct mutual information maximization , but can be inferred when incorporated into a more complex model in which other sequence elements are also varied [34] . We make use of the assumption that gene expression will be proportional to the probability that RNAP is bound to the promoter , pbound , which is given by p b o u n d = P N N S e - β Δ ε P 1 + P N N S e - β Δ ε P + 2 R N N S e - β Δ ε R , ( 1 ) where P is the number of RNAP in the cell , ΔεP is the RNAP binding energy , R is the repressor copy number , NNS is the number of nonspecific binding sites in the genome , and ΔεR is the repressor binding energy . As noted in S1 Text , our inference procedure also requires that we infer an energy matrix and scaling factor for the RNAP binding site . We do not note these values in this work , as our focus is on sequence-energy mappings for transcription factor binding sites . We note also that we can write the repressor binding energy as ΔεR = αεmat + Δεwt , where εmat is the energy value obtained by summing the matrix elements associated with a sequence , Δεwt is the binding energy associated with the reference sequence , and α is the desired scaling factor that converts the matrix values into kBT units . To obtain a value for α , an MCMC algorithm is used where we maximize the mutual information I ( pbound , μ ) between the values of pbound calculated for each binding site sequence and the expression bin into which that sequence was sorted . For more information on this process , see S1 Text . See S2 Text for a comparison to other methods for obtaining the scaling factor . A reference sequence refers to the sequence which serves as the “wild-type” for each experiment . For each library , the promoter is mutated relative to its reference sequence . Additionally , when assigning binding energies to an energy matrix , all binding energies are calculated relative to the reference sequence . One might assume that Sort-Seq experiments should reveal the same binding specificity regardless of the reference sequence used to produce the library , provided that the transcription factor does not change . To test this possibility , we generated energy matrices using three different reference sequences , all of which are binding sites for LacI . For our reference sequences we use the three natural E . coli lac operators ( O1 = AATTGTGAGCGGATAACAATT , O2 = AAATGTGAGCGAGTAACAACC , and O3 = GGCAGTGAGCGCAACGCAATT ) . For our primary analysis we use single-point energy matrix models . These models assume that each nucleotide position within a binding site contributes independently to the binding energy ( see S3 Text for predictions using higher-order models ) . Each operator has a distinct LacI binding energy , with O1 being the strongest at -15 . 3 kBT , O2 being the second strongest at -13 . 9 kBT , and O3 being the weakest at -9 . 7 kBT [32] . The operator sequences are rather dissimilar to each other , with O2 having 5 mutations relative to O1 and O3 having 8 mutations relative to O1 ( and 11 mutations relative to O2 ) . For each library , the average operator sequence has only 2 mutations relative to the reference sequence . As a result , a library generated with O1 as the reference sequence is unlikely to share any mutant sequences with a library generated with O2 or O3 as the reference sequence . Here we assess whether dissimilar mutant libraries generated from different reference sequences produce similar energy matrices and sequence logos from their respective Sort-Seq data sets . We obtain energy matrix models by following the Sort-Seq procedure outlined above , splitting our Sort-Seq data into three separate groups of nonoverlapping sequences to produce matrix replicates , as discussed in S1 Text . We then infer an energy matrix for each replicate . In Fig 2 we show energy matrices composed of the mean energy value at each matrix position , and the corresponding sequence logos . As shown in Fig 2A , the three operators each produce qualitatively similar energy matrices , with the left side of the binding site showing greater sequence dependence than the right side , as evidenced by the larger magnitude of the binding energies assigned to each matrix position . Note that we set the binding energy of the reference sequence to 0 kBT for these energy matrices , so that the binding energies assigned to each possible mutation are calculated relative to the reference sequence . For all energy matrices , positions 4-10 show the greatest sequence preference . This preference is reflected in the natural lac operator sequences themselves , as the bases from 4-10 are conserved in each of the operators . Notably , the majority of mutations available to O1 incur a penalty to binding energy , while many of the mutations available to O3 enhance the binding energy . This is consistent with the observation that O1 has a strong binding energy while O3 has a weak binding energy . When the energy matrices are used to produce sequence logos as in Fig 2B ( see Ref . [35] for an explanation of the mathematics used to relate binding energies to base-pair frequencies , and Ref . [36] for a discussion of sequence logos themselves ) , we see a consistent preference for a slightly asymmetric binding site , reflecting the fact that LacI is known to bind asymmetrically to its operators [37] . Additionally , clear differences arise for the different operators . While the sequence logos derived from O1 and O2 indicate very similar sequence preferences , the preferred sequence suggested by the O3 sequence logo differs in some prominent positions . In S4 Text we note that weaker binding sites exhibit a greater variation in the quality of their sequence logos; thus it may be that the O3 binding site is simply too weak to provide an informative sequence logo . In Fig 2C–2E we plot the energy values from each matrix against one another to show how the energy matrices compare to one another quantitatively . For ease of comparison , here the energy values are fixed so that the mean energy value at each sequence position is 0 kBT . We see that replicates of energy matrices with an O1 reference sequence are highly similar to each other with a Pearson’s correlation coefficient of r = 0 . 95 , as calculated from the mean energy matrix values ( Fig 2C ) . However , this similarity deteriorates somewhat as the reference sequence diverges from O1 , with a value of r = 0 . 85 for an O2-derived matrix ( Fig 2D ) and r = 0 . 48 for an O3-derived matrix ( Fig 2E ) . Thus , while energy matrices derived from different reference sequences may be qualitatively similar , there are notable quantitative dissimilarities between these matrices . In S2 Fig we also represent each matrix as an energy logo as introduced in Ref . [38] and used in Ref . [30] to represent the sequence specificity of LacI determined from in vitro experiments . In S3 Fig we show how energy matrix values inferred for O1 in this work compare with the energy matrix values inferred for O1 using an in vitro technique in Ref . [30] . We find that the values from these two studies generally agree , particularly for lower energy values . Any differences may be due to the different experimental procedures used in these studies . The energy matrices obtained via Sort-Seq should allow us to map sequence to phenotype . The relevant phenotype for simple repression constructs is the degree to which the system is repressed , which can be measured using the fold-change . We define fold-change as the ratio of expression in a repressed system to expression in a system with no repressors , as described by the equation fold-change = expression ( R ) expression ( R=0 ) . ( 2 ) where R is the repressor copy number . As discussed in further detail elsewhere [31 , 32] , the fold-change can also be computed using a thermodynamic model given by fold-change = 1 1 + 2 R N N S e - β Δ ε R , ( 3 ) where the factor of 2 in “2R” indicates that for the case of LacI , each LacI tetramer has two heads and can essentially be counted as two repressors . NNS is the number of nonspecific binding sites available in the genome ( ∼ 4 . 6 × 106 in E . coli ) and ΔεR is the operator binding energy . We note that this model makes the simplifying assumption that the RNAP binds weakly to the promoter . We find that for the lacUV5 promoter , this assumption holds for RNAP copy number P ≲ 1000 . From Ref . [39] we know that the relevant sigma factor , RpoD , has a copy number of 650 ± 100 in the growth condition used here ( M9 + 0 . 5% glucose at 37°C ) . In principle , the energy matrix models shown in Fig 2 can be used to predict the binding energy of an operator mutant . To explore the ability of energy matrices to predict the effects of mutations on operator binding strength , we designed a number of mutant operators with 1 , 2 , or 3 mutations relative to the O1 operator . Experimentally-determined values for the binding energies of these mutants could then be compared against values predicted by our LacI energy matrices . To obtain experimental values for mutant binding energies we start with chromosomally-integrated simple repression constructs for each mutant , which were incorporated into strains with LacI tetramer copy numbers of R = 11 ± 1 , 30 ± 10 , 62 ± 15 , 130 ± 20 , 610 ± 80 , and 870 ± 170 . These copy numbers were inferred from quantitative Western blot measurements in Ref . [32] , and the error in these copy numbers denotes the standard deviation of at least three Western blot replicates . We determined the fold-change by measuring the YFP fluorescence levels of each strain by flow cytometry and substituting them into Eq 2 . We determine each mutant’s binding energy , ΔεR , by performing a single-parameter fit of Eq 3 to the resulting data via nonlinear regression . Fig 3A shows several fold-change values for 1 bp , 2 bp , and 3 bp mutants overlaid with these fitted curves ( the remaining fold-change data are shown in S2–S4 Figs ) . The energy matrices derived from Sort-Seq can be used to predict the value of ΔεR associated with a given operator mutant , as discussed in detail in S1 Text . To make these predictions , we use energy matrices produced using Sort-Seq data where O1 is the reference sequence and repressor copy number R = 130 . As before , we split the Sort-Seq data into three groups to produce three replicate energy matrices . We make our predictions using each of these replicate matrices in order to obtain a mean value and standard deviation for the predicted ΔεR for each operator mutant . We note that any error in the predictions can be caused by error in the energy matrices themselves or in the inferred scaling factors . Fig 3B shows how binding energy values measured by fitting to repressor titration data compare to values predicted using energy matrices that were produced using O1 as a reference sequence . For single base pair mutations most predictions perform well and are accurate to within 1 kBT , with many predictions differing from the measured values by less than 0 . 5 kBT . Predictions are less accurate for 2 bp or 3 bp mutations , although the majority of these predictions are still within 1 . 5 kBT of the measured value . To give a sense of the consequences of an incorrect energy prediction , a prediction error of ±1 kBT can alter the expected fold-change of a simple repression architecture by a magnitude of approximately 0 − 0 . 25 , depending on the binding site’s binding energy and the repressor copy number R . The quality of matrix predictions appears to degrade as mutants deviate farther from the wild-type sequence used to generate the energy matrix . To evaluate predictions for a broader range of deviations from the energy matrix , we made predictions from two energy matrices: the mean energy matrix using O1 as a reference sequence with repressor copy number R = 130 , and the mean energy matrix using O2 as a reference sequence with R = 130 . This allowed us to access predictions for operators that are mutated by several base pairs relative to the matrix . In Fig 3C we show how prediction error , defined as the discrepancy in kBT between a predicted and measured energy value , varies depending on the number of mutations relative to the wild-type binding site sequence . We find that predictions remain relatively accurate for mutants that differ by up to 4 bp relative to the wild-type sequence , with median deviations of ∼ 1 . 0 kBT or less from the measured binding energy . Other studies have noted that energy matrix models that don’t account for epistatic interactions fail to accurately predict binding energies for mutants with multiple mutations relative to the reference sequence [29 , 40] . Thus we find that the relatively low errors depicted in Fig 3C exceed expectations for what a single-point energy matrix model can achieve . We note that energy matrix quality , as measured by the accuracy of its predictions , may be affected by factors such as repressor copy number or wild-type transcription factor binding energy . Changes in growth state can be expected to affect the number of transcription factors present in the cell ( although transcription factors appear to be less sensitive to growth state than the general proteome [39] ) , so it is important to determine how sensitive our approach is to changes in repressor copy number . Additionally , we expect that at some repressor copy numbers and binding site strengths , the binding site may be either fully saturated with repressor or entirely unbound by repressor , which may also affect energy matrix quality . In S4 Text , we assess whether energy matrix quality is affected by the LacI copy number of the background strain , and find that it has little effect on matrix quality . We also compare predictions made from energy matrices with different reference sequences ( i . e . O1 , O2 , or O3 ) , and find that using O1 as a reference sequence produces the most accurate energy matrices , while using O3 produces energy matrices that are almost entirely non-predictive . In S5 Text , we consider whether better energy matrices are made using libraries in which the entire promoter is mutated or only the operator is mutated . We find that mutating the operator alone can provide more accurate energy matrices , though one must fit energy matrix predictions to binding energy measurements in order to convert these matrices into kBT units . Our predictive energy matrices suggest a promising strategy for addressing the challenge of genetic circuit design , which has typically relied on trial and error to achieve specific outputs [41 , 42] . By contrast , previous studies have shown how thermodynamic models can be used to predict gene outputs given a set of inputs [31 , 32] , which can suggest appropriate inputs to produce a desired output . For example , the key inputs for the fold-change Eq 3 are repressor copy number R and repressor-operator binding energy ΔεR , and one can use Eq 3 to determine a set of R and ΔεR values that can be used to target a desired fold-change response . Energy matrix predictions can be used to design operator sequences with a particular value of ΔεR , thereby making it possible to tune genetic circuits and target specific phenotypes . As shown in Fig 3B , mutating an operator by as little as one base pair can provide a broad range of ΔεR values that can be predicted accurately . One particularly useful class of simple genetic circuit , which can be layered with other genetic components to create complex logic [43] , is inducible simple repression [44–47] . In such a system , an allosteric repressor can switch between an active form , which binds to an operator with high affinity , and an inactive form , which has a low affinity to the operator . An inducer may bind to the repressor and stabilize the repressor’s inactive form , thereby reducing the probability that the repressor will bind to the operator and increasing the probability that RNAP will bind and initiate transcription . The result is that an inducible system can access a broad range of fold-change values simply by tuning the concentration of inducer . As discussed in Ref . [48] , the fold-change of an inducible simple repression circuit can be described by the equation fold-change ( c ) = ( 1 + ( 1 + c K A ) n ( 1 + c K A ) n + e - β Δ ε A I ( 1 + c K I ) n 2 R N N S e - β Δ ε R ) - 1 , ( 4 ) where c is the concentration of inducer , n is the number of inducer binding sites on the repressor , KA and KI are the dissociation constants of the inducer and repressor when the repressor is in its active or inactive state , respectively , and ΔεAI is the difference in free energy between the repressor’s active and inactive states . In Ref . [48] we determined that these values are K A = 139 - 22 + 29 μ M , K I = 0 . 53 - 0 . 04 + 0 . 04 μ M , and ΔεAI = 4 . 5 kBT for LacI with the inducer IPTG . Where noted , superscripts and subscripts indicate the upper and lower bounds for the 95th percentile of the parameter value distributions . There are n = 2 inducer binding sites on each LacI dimer . We note that while we use Eq 4 here to represent induction of LacI by IPTG , this equation is general and can be used for any inducible system that utilizes simple repression . We can use these parameter values for the lac-based system considered here to explore how tuning the operator-repressor binding energy ΔεR can alter the induction response when an effector ( i . e . IPTG ) is introduced to the system . Importantly , our sequence-energy mapping provides a straightforward avenue for tuning ΔεR by altering the binding sequence rather than mutating the repressor itself , which is much more difficult to characterize . We note that an induction response can be described by a number of key phenotypic parameters . The leakiness is the minimum fold-change when no inducer is present , given by fold- change ( c → 0 ) ( Eq 1 in S6 Text ) . The saturation is the maximum fold-change when inducer is present at saturating concentrations , given by fold- change ( c → ∞ ) ( Eq 2 in S6 Text ) . The dynamic range is the difference between the saturation and leakiness , and represents the magnitude of the induction response ( Eq 4 in S6 Text ) . The [EC50] is the inducer concentration at which the fold-change is equal to the midpoint of the induction response ( Eq 6 in S6 Text ) . Full expressions for these parameters are shown in S6 Text . Fig 4A and 4B show how these phenotypic parameters vary with ΔεR given the values of KA , KI , and ΔεAI listed above and the repressor copy number R = 130 . We can see that there are inherent trade-offs between phenotypic parameter values . For instance , in this particular system one cannot tune ΔεR to obtain a small dynamic range ( e . g . a dynamic range of 0 . 1 ) while also having an intermediate leakiness value ( e . g . a leakiness of 0 . 4 ) . Rather , one must design an induction response by choosing from the available phenotypes , or else alter the system by tuning additional parameters such as KA and KI , which requires mutating the protein itself or using a different transcription factor altogether as in Ref . [41] . To show how energy matrices can be used to design specific induction responses , we chose six of our single base-pair mutants with a range of predicted binding energies , which we could expect to exhibit a range of phenotypic properties as shown in Fig 4A and 4B . Induction responses for each of these mutants were measured by growing cultures in the presence of varying IPTG concentrations and measuring the fold-change at each concentration . Fig 4C–4H shows how the induction data compare against theory curves plotted using the mean ΔεR values predicted from the energy matrices derived from Sort-Seq data with the O1 reference sequence and repressor copy number R = 130 . In general the predicted induction curves match well with the data , though the predicted induction curves in Fig 4C and 4H are noticeably dissimilar to the data . Theory curves plotted using the measured binding energy ( rather than the predicted binding energy ) describe the data well , indicating that any mis-match between the data and the predicted theory curve is due to error in the predicted binding energy , which may arise from errors in the matrices themselves or the inferred scaling factor . Predictive energy matrices offer a simple way of analyzing direct interactions between amino acids and nucleotides . Mutating individual amino acids in the repressor’s DNA-binding domain and then observing changes in the energy matrix makes it possible to determine how changing the amino acid composition of the DNA-binding domain alters sequence preference . If sequence specificity is altered only for specific base pairs when an amino acid is mutated , this may indicate that the amino acid interacts directly with those base pairs . While it is possible to obtain such information using binding assays [49] or labor-intensive structural biology approaches , Sort-Seq makes it possible to efficiently sample protein-DNA interactions . To analyze the effects of amino acid mutations on sequence specificity , we chose mutations which had previously been found to alter LacI-DNA binding properties without entirely disrupting the repressor’s ability to bind DNA [49 , 50] . We performed Sort-Seq using strains containing one of three LacI mutants , Y20I , Q21A , or Q21M , where the first letter indicates the wild-type amino acid , the number indicates the amino acid position , and the last letter indicates the identity of the mutated amino acid . Here we used matrices derived from libraries in which only the operator was mutated; each matrix was scaled such that the average mutation carried a binding penalty equal to the average binding penalty for wild-type LacI , measured in kBT energy units . Sequence logos derived from the mean energy matrices for each LacI mutant are shown in Fig 5 , along with the wild-type sequence logo for comparison . As with the wild-type repressor , for each of the mutant repressors we find that the left half-site of the sequence logo has a stronger sequence preference . For both Y20I and Q21M , the same sequence is preferred in the left half-site as for the wild-type LacI . This contrasts with the results from Ref . [49] , in which it was found that Y20I prefers an adenine at sequence position 6 , rather than the guanine preferred at this position by the wild-type repressor . As in Ref . [49] , we find that an adenine is preferred at sequence position 6 for the Q21A mutant . Additionally , when comparing the left and right half-sites of each energy matrix , we find that for each mutant the preferred sequence is not entirely symmetric . This is especially notable at positions 8 and 12 , in which symmetry is broken in each of the sequence logos shown in Fig 5 . For wild-type LacI , we see that G is preferred at position 8 with a probability of 0 . 75 ± 0 . 05 , where the error represents the standard deviation of probabilities derived from each replicate matrix . At position 12 , A is preferred with a probability of 0 . 49 ± 0 . 06 . We see this trend repeated for Y20I , where G is 0 . 79 ± 0 . 09 probable at position 8 and T is 0 . 63 ± 0 . 10 probable at position 12 , Q21A where G is 0 . 86 ± 0 . 06 probable at position 8 and A is 0 . 63 ± 0 . 05 probable at position 12 , and Q21M where G is 0 . 61 ± 0 . 07 probable at position 8 and A is 0 . 50 ± 0 . 11 probable at position 12 . For each mutant , these sites are found to prefer asymmetrical bases with p-value < 0 . 05 . Thus we see that the lac repressor’s notable preference for a pseudo-symmetric operator is preserved in each of the mutants we tested [29 , 30 , 37] . In this work we have used the lac system to demonstrate how Sort-Seq can be used to map binding site sequence to binding energy , and we used these mappings to rationally design novel genetic circuit elements and identify the effects of amino acid mutations on LacI’s sequence specificity . Importantly , this approach is not specific to the lac system and can be applied to any system in which transcription factors alter gene expression by binding to DNA within the promoter region . In Ref . [26] we showed how Sort-Seq could be used alongside mass spectrometry to determine the locations of transcription factor binding sites in a promoter of interest and identify which transcription factors bind to these sites . We generated energy matrices for a number of transcription factors ( e . g . RelBE , MarA , PurR , XylR , and others ) . Here we analyze selected energy matrices from Ref . [26] to show how energy matrices can be used to understand transcriptional activity in promoters with varied architectures beyond simple repression . One of the questions we wish to answer is to what extent altering the context of a binding site within a regulatory architecture will alter sequence specificity . One hypothesis is that a transcription factor’s preferred binding sequence will remain the same regardless of how its binding site is positioned within the regulatory architecture . However , it is known that factors beyond the core operator sequence , such as flanking sequences and DNA shape , can affect sequence specificity [19 , 51 , 52] . Additionally , interactions with other proteins may alter the way a transcription factor contacts the DNA , which could affect sequence specificity as well [53] . It is important to know whether a transcription factor’s specificity is sensitive to the context of the binding site within the promoter architecture , as this determines the extent to which an energy matrix can be used to analyze binding sites throughout the genome . Additionally , observing how sequence specificities change with binding site context may alert us to changes in regulatory mechanisms as the operator is moved to different positions in the promoter . In Ref . [26] , we used Sort-Seq to obtain energy matrices and sequence logos for the transcription factors XylR and PurR in the context of the natural promoters for xylE and purT , respectively . The xylE promoter has two XylR binding sites directly adjacent to one another , allowing us to compare these two energy matrices against each other . In this context , we find that XylR appears to act as an activator in tandem with a CRP binding site . Sequence logos for the two XylR binding sites are shown in Fig 6A , obtained from mean energy matrix values for each site . The energy matrices and sequence logos for these binding sites have some significant dissimilarities . Dissimilarities are particularly notable at positions 6-8 , where the left-hand site prefers “TTT” with probabilities 0 . 89 ± 0 . 03 , 0 . 54 ± 0 . 01 , and 0 . 65 ± 0 . 03 respectively , and the right-hand site prefers “AAA” with probabilities 0 . 58 ± 0 . 01 , 0 . 79 ± 0 . 01 , and 0 . 47 ± 0 . 01 . We can say that the sequence preferences at each of these positions differ between the two binding sites with p-value < 0 . 0001 . These changes in sequence specificity may be due to interactions with neighboring DNA-binding proteins . We note that in the xylE promoter the left-hand XylR site is adjacent to a CRP site , while the right-hand XylR site is adjacent to the RNAP site . The close proximity of these binding sites suggests that there may be direct interactions between proteins . Such interactions could constrain the binding conformations of each XylR copy and thus alter how each XylR interacts with its DNA binding site . The Pearson’s correlation coefficient r between the mean values of the two energy matrices is r = 0 . 73 . In Ref . [26] we find that PurR acts as a repressor in the purT promoter , with a single binding site between the -10 and -35 sites . In order to compare the associated energy matrix with a PurR energy matrix from a different regulatory context , here we create a synthetic promoter in which the PurR binding site has been moved directly downstream of the RNAP site . This should continue to be a simple repression architecture in which repressor binding occludes RNAP binding , but the change in operator position may alter the repressor’s interaction with the DNA . Sequence logos for both PurR binding sites are shown in Fig 6B . The two PurR sequence logos are very similar to one another , indicating no significant changes in the interactions between the repressor and the DNA . We calculate the Pearson’s correlation coefficient between the two energy matrices to be r = 0 . 90 , which is significantly higher than the value calculated for the two XylR energy matrices . We additionally performed Sort-Seq on a LacI simple repression construct in which the lac operator was placed upstream of the RNAP binding site rather than downstream . In Ref . [27] it is shown that LacI binding to an upstream operator still represses , but whereas a downstream operator represses by preventing RNAP from binding , an upstream operator appears to directly contact a bound RNAP and prevent it from escaping the promoter . Moreover , an upstream operator’s binding strength does not directly correspond with the level of repression associated with the promoter . These factors make repression by an upstream lac operator an interesting architecture to compare with repression by a downstream lac operator . Sequence logos for the upstream and downstream LacI binding sites are shown in Fig 6C . These logos are very similar to one another , despite the fact that the repression mechanisms and protein interactions differ for these two architectures . The Pearson’s correlation coefficient between the two matrices is r = 0 . 96 . For the above analysis we note that the energy matrices used to make these sequence logos were scaled using a theoretical “average” binding penalty derived from a statistical mechanical analysis of transcriptional regulation ( see S2 Text ) . This is because a number of the necessary parameters for some of these architectures , such as repressor copy number or wild-type binding energies , still remain poorly characterized . In order to confidently infer scaling factors for transcription factor binding sites , it is necessary to have a thermodynamic model that is known to accurately describe the architecture and contains a minimum of unknown parameter values . For the example of simple lac repression , our thermodynamic model has been shown repeatedly to accurately describe the key mechanisms of simple repression architectures [24 , 32 , 48 , 54 , 55] . We have performed our Sort-Seq experiments in strains which are known to lack any additional LacI binding sites in the chromosome , in which we know the repressor copy number R , and which we know do not contain any known inducers of LacI . These factors allow us to confidently infer energy matrix scaling factors . If we consider the case of simple repression by PurR , we know that the promoter is under co-repression through concerted binding of the ligand hypoxanthine to PurR [56] . While Eq ( 4 ) provides a rational model for a simple allosteric architecture of this type , the allosteric parameters KA , KI , and εAI are uncharacterized; moreover , the concentration of inducer in the system is uncharacterized . While the PurR repressor copy number has been measured to be about 400 dimers per cell under the growth conditions considered here [39] , attempting to fit the remaining parameters with our Sort-Seq expression data is not possible due to significant degeneracy in the parameter space [48] . Note that in the case of the XylR architecture , we are hesitant to suggest a new thermodynamic model for pbound without further work to understand the specific mechanism of regulation and identify all of the relevant parameters . For example , it is unclear whether a single bound copy of XylR is capable of activating the promoter , or whether it must bind in a complex with another copy of XylR . Additionally , there are likely to be physical interactions between CRP , the two copies of XylR , and RNAP that would be represented by effective interaction energy parameters . This would add a significant number of parameters to the thermodynamic model , all with unknown values , which would make it difficult to make accurate estimates of any parameter value in the model . This prevents us from inferring scaling factors for the XylR binding sites using MCMC .
In this work , we apply quantitative modeling to in vivo experimental data to analyze interactions between transcription factors and their binding sites under multiple conditions . As an example of how our approach might be used to analyze a transcription factor’s sequence-specific binding energy , we used Sort-Seq to create energy matrices that map DNA sequence to binding energy for the lac repressor ( Fig 2 ) . We performed this work in the context of a simple repression architecture , which is widespread among bacterial promoters [57] and is frequently used in synthetic biology [47 , 58 , 59] . We test our model’s predictions against binding energies inferred from fold-change measurements of roughly 30 lac operator mutants ( Fig 3 ) . These predictions proved to be accurate to within ∼ 1 . 0 kBT for binding sites with up to four mutations relative to the reference sequence . We note , however , that our energy matrices cannot be used to predict the binding energies of operator mutants containing insertions or deletions , such as the synthetic operator Oid . Because we are able to accurately predict operator binding energies , our sequence-energy mappings can be used to design specific regulatory responses , which is of great utility to synthetic biology . We combine energy matrices with a thermodynamic model of inducible simple repression to design induction curves , as demonstrated in Fig 4 [48] . We note that in spite of the overall success of our predictions , there remain some predictions that are significantly different from the measured values ( see the outliers in Fig 3C ) . Such inaccuracies are particularly problematic when using energy matrices for design applications , as discrepancies between a system’s expected and actual response may render a designed system unsuitable for its intended application . We can see examples of this in Fig 4F–4H , where inaccuracies in binding energy predictions are reflected in the predicted titration curves . Two of the six prediction curves do not accurately describe the data , with the data exhibiting mis-matches in either saturation or leakiness . If the saturation or leakiness are vital parameters in the designed system , then such a mis-match could cause the system to fail . Importantly , the error associated with binding energy predictions varies depending on the method used to obtain a scaling factor to convert the energy matrix to absolute energy units . As discussed in S2 Text , inferring the scaling factor using MCMC , as we do for our predictions in the main text , introduces a source of error related to uncertainties in the inference procedure . Error can be reduced by using an alternative scaling procedure such as fitting to sequences with known binding energies . We also explore how sequence specificity is altered when transcription factor amino acids are mutated . To do this , we repeat our Sort-Seq experiments in bacterial strains expressing LacI mutants in which the DNA-binding domain has been altered ( Fig 5 ) . Because all nucleotides in the binding site are mutated with some frequency in Sort-Seq experiments , we are able to identify changes in specificity throughout the entire binding site . Other methods for analyzing the sequence preference of transcription factor mutants tend to be more laborious and less fine-grained , often focusing on a small set of nucleotides within the binding site . These include binding experiments between DNA mutants and protein mutants [49] , gene expression experiments using chimeric transcription factor proteins [60] , and comparative genomics [61] . We further explore how regulatory context alters sequence specificity . We generate sequence logos from energy matrices obtained for the transcription factors XylR , PurR , and LacI in different regulatory contexts , as shown in Fig 6 . We find that the two adjacent XylR binding sites exhibit significantly different binding specificities , possibly due to interactions between transcription factors . In contrast , the simple repression constructs analyzed for PurR and LacI have nearly identical sequence specificities . By itself , our method is unable to determine the causes of context-dependent changes in sequence specificity , though it is known that DNA shape or binding to cofactors can alter a transcription factor’s specificity [51–53] . Rather , our approach can be used to determine whether a given binding site’s sequence preferences diverge from the “standard” sequence specificity for the relevant transcription factor , and further experiments ( such as SELEX-seq in the presence of a transcription factor and possible cofactors [53] ) can be performed to determine the cause of the change in sequence specificity . A major advantage of our in vivo approach is that it allows us to analyze transcription factors in their natural context , in the presence of interacting proteins , small molecules , and DNA shape effects . This is especially important when analyzing regulatory regions that have not been previously annotated , as was the case for the XylR and PurR matrices obtained in Ref . [26] . However , a clear advantage of in vitro approaches is that they can accurately measure low-affinity binding sites [12 , 13 , 15] . When using our in vivo approach , weaker reference sequences produce energy matrices with variable quality and are more likely to make poor predictions ( see S4 Text ) . However , accuracy may be improved by investigating ways to reduce the experimental noise associated with in vivo systems , for instance by incorporating promoter constructs as single copies in the chromosome rather than multiple copies on plasmid , for example using the “landing pad” technique described in Ref . [62] . We further note that the primary methodology used here , in which an energy matrix scaling factor is inferred via MCMC , offers an indirect readout of transcription factor binding energies that relies on the assumption that transcription will always be initiated ( at some rate ) if the promoter is occupied by RNAP . While this assumption often provides a valid approximation of the mechanisms of transcription , previous work has shown that this is not always an appropriate model [24 , 25] . More detailed models of transcription would be required in order to apply this methodology to systems in which RNAP occupancy does not reliably predict transcription initiation . When such models are not available , energy matrix scaling factors can be inferred using a theoretical binding energy penalty for mutations as detailed in S2 Text . This work provides a foundation for further studies that would benefit from sequence-energy mappings . For example , our analysis of three LacI amino acid mutants could be expanded to include a full array of LacI DNA-binding mutants , which would allow one to make inferences regarding repressor-operator coevolution . Additionally , while we make extensive use of LacI in the present work , similar analyses could be performed with any transcription factor , making it possible to improve upon the genomically-inferred sequence logos presently available for many transcription factors . We demonstrate this capability in Fig 6 , where we identify the sequence specificities of two additional transcription factors , XylR and PurR . The data shown in Fig 6 further demonstrate that we can assess effects on sequence specificity that result from factors such as binding site positioning or protein-protein interactions . Thus , for cases in which it is known that sequence specificity is affected by DNA shape , flanking sequences , cofactor binding , or other factors outside of the operator binding sequence , our approach can be used to obtain a base-pair resolution map of the effects on sequence specificity . Finally , we note that one of the primary strengths of our approach is that it can be used to elucidate the transcriptional regulation of a gene with a previously-unknown regulatory architecture . As shown in Ref . [26] , Sort-Seq can be combined with mass spectrometry to identify transcription factor binding sites and those sites’ regulatory roles for any gene of interest . Here we show that data sets obtained in this manner can also be used to map sequence to binding energy , thus showing that a single experiment can be used to characterize multiple aspects of a previously-unannotated regulatory sequence . Currently , we convert our energy matrices to absolute energy units using a theoretical scaling factor for cases where thermodynamic models for the regulatory architecture are unknown , but future work may improve our ability to identify thermodynamic models and thus infer more accurate scaling factors . Furthermore , our approach does not rely specifically on the Sort-Seq technique used here , but can be adapted to multiple experimental designs , such as RNA-seq based MPRAs that have been demonstrated in multiple model systems [7 , 63–65] . Over time , we envision incorporating high-throughput synthesis and analysis techniques to adapt our approach for genome-wide studies in both prokaryotes and eukaryotes .
To generate promoter libraries for Sort-Seq , mutagenized oligonucleotide pools were purchased from Integrated DNA Technologies ( Coralville , IA ) . These consisted of single-stranded DNA containing the lacUV5 promoter and LacI operator plus 20 bp on each end for PCR amplification and Gibson Assembly . Either both the lacUV5 promoter and LacI binding site or only the LacI binding site was mutated with a ten percent mutation rate per nucleotide . These oligonucleotides were amplified by PCR and inserted back into a pUA66-operator-GFP construct using Gibson Assembly . To achieve high transformation efficiency , reaction buffer components from the Gibson Assembly reaction were removed by drop dialysis for 90 minutes and cells were transformed by electroporation of freshly prepared electrocompetent cells . Following an initial outgrowth in SOC media , cells were diluted with 50 mL LB media and grown overnight under kanamycin selection . Transformation typically yielded 106 − 107 transformants as assessed by plating 100 μL of cells diluted 1:104 onto an LB plate containing kanamycin and counting the resulting colonies . Simple repression motifs used in fold-change measurements were adapted from those in Garcia et al . [32] . Briefly , a simple repression construct with the O1 operator sequence was cloned into a pZS25 plasmid background directly downstream of a lacUV5 promoter , driving expression of a YFP gene when the operator is not bound by LacI . This plasmid contains a kanamycin resistance gene for selection . Mutant LacI operator constructs ( listed in Table 1 ) were generated by PCR amplification of the lacUV5 O1-YFP plasmid using primers containing the point mutations as well as sufficient overlap for re-circularizing the amplified DNA by one-piece Gibson Assembly . A second construct was generated to express LacI at a specified copy number . Specifically , lacI was cloned into a pZS3*1 background that provides constitutive expression of LacI from a PLtetO−1 promoter [66] . This plasmid contains a chloramphenicol resistance gene for selection . The LacI copy number is controlled by mutating the ribosomal binding site ( RBS ) for the lacI gene as described in [67] using site-directed mutagenesis ( Quickchange II; Stratagene , San Diego , CA ) and further detailed in [32] . Here , we mutated the RBS such that it would produce a LacI copy number of ∼130 tetramers once the construct had been integrated into the chromosome . Once the plasmids had been generated , the promoter and lacI constructs were each amplified by PCR and integrated into the chromosome by lambda-red recombineering using the pSIM6 expression plasmid [68] . The promoter construct and YFP gene were inserted into the galK locus in the E . coli genome and the lacI construct was inserted into the ybcN locus . As previously mentioned , wild-type lacI was cloned into a pZS3*1 background providing constitutive expression of LacI , with the LacI copy number mediated by a mutated RBS . We used the RBS corresponding to a LacI tetramer copy number of ∼130 for each mutant . To create DNA-binding mutants for LacI we used site-directed mutagenesis ( Quickchange II; Stratagene , San Diego , CA ) using the mutagenesis primers listed in Table 2 . We mutated the amino acid Y to I at position 20 and Q to A or M at position 21 . We chose these mutations based on data from previous studies [49 , 50] , though we note that our amino acid numbering system is shifted by +3 relative to the mutants in these previous studies since we use a slightly different version of lacI . As with the wild-type lacI , we integrate the mutants into the genome at the ybcN locus by lambda-red recombineering using the pSIM6 expression plasmid . E . coli strains used in this work were derived from K12 MG1655 . To generate strains with different LacI copy number , the lacI constructs were integrated into a strain that additionally has the entire lacI and lacZYA operons removed from the chromosome . These constructs were integrated at the ybcN chromosomal location . This resulted in strains containing mean LacI tetramer copy numbers of R = 11 ± 2 , 30 ± 10 , 62 ± 15 , 130 ± 20 , 610 ± 80 , and 870 ± 170 , where the error denotes the standard deviation of at least three replicates as measured by quantitative western blots in Ref . [32] . For Sort-Seq experiments , plasmid promoter libraries were constructed as described above and then transformed into the strains with R = 30 , 62 , 130 or 610 . For fold-change measurements , each O1 operator mutant was integrated into strains containing each of the listed LacI copy numbers . These simple repression constructs were chromosomally integrated at the galK chromosomal location via lambda red recombineering . Generation of the final strains containing a simple repression motif and a specific LacI copy number was achieved by P1 transduction . For each LacI titration experiment , we also generated a strain in which the operator-YFP construct had been integrated , but the lacI and lacZYA operons had been removed entirely . This provided us with a fluorescence expression measurement corresponding to R = 0 , which is necessary for calculation of fold-change . For each Sort-Seq experiment , cells were grown to saturation in lysogeny broth ( LB ) and then diluted 1:10 , 000 into minimal M9 + 0 . 5% glucose for overnight growth . Once these cultures reached an OD of 0 . 2-0 . 3 the cells were washed three times with PBS by centrifugation at 4000 rpm for 10 minutes at 4°C . They were then diluted two-fold with PBS to reach an approximate OD of 0 . 1-0 . 15 . These cells were then passed through a 40 μm cell strainer to eliminate any large clumps of cells . A Beckman Coulter MoFlo XDP cell sorter was used to obtain initial fluorescence histograms of 500 , 000 events per library in the FL1 fluorescence channel with a PMT voltage of 800 V and a gain of 10 . The histograms were used to set four binning gates that each covered ∼ 15% of the histogram . 500 , 000 cells were collected into each of the four bins . Finally , sorted cells were regrown overnight in 10 mL of LB media , under kanamycin selection . Overnight cultures from each sorted bin were miniprepped ( Qiagen , Germany ) , and PCR was used to amplify the mutated region from each plasmid for Illumina sequencing . The primers contained Illumina adapter sequences as well as barcode sequences that were unique to each fluorescence bin , enabling pooling of the sorted samples . Sequencing was performed by either the Millard and Muriel Jacobs Genetics and Genomics Laboratory at Caltech or NGX Bio ( San Fransisco , CA ) . Single-end 100bp or paired-end 150bp flow cells were used , with about 500 , 000 non-unique sequences collected per library bin . After performing a quality check and filtering for sequences whose PHRED score was greater than 20 for each base pair , the total number of useful reads per bin was approximately 300 , 000 to 500 , 000 per million reads requested . Energy weight matrices for binding by LacI and RNAP were inferred using Bayesian parameter estimation with a error-model-averaged likelihood as previously described [28 , 69] and further detailed in S1 Text . Unless otherwise specified , replicates were formed by randomly splitting the Sort-Seq data sets into three groups containing equal numbers of sequences . Each of these groups was used to create a separate energy matrix . These matrices were either used to create a “mean” energy matrix , as when a matrix heat-map or sequence logo is displayed , or were used individually to create replicate binding energy predictions . Where p-values are noted for sequence preference , the probabilities of each base at a given position were first calculated for each replicate matrix using the equation prob N = e - ε N e - ε A + e - ε C + e - ε G + e - ε T , ( 5 ) where N represents a given base , and εN is the binding energy associated with that base at the given sequence position . With these probabilities in hand , we used a one-way Welch’s ANOVA test implemented in R to determine if there was a statistically significant difference in mean probability values . If a statistical difference ( p-value < 0 . 01 ) was found between the means , we confirmed that the most probable base was statistically distinct from all other bases using a Games-Howell post-hoc analysis implemented in R . Fold-change measurements were collected as previously described in Ref . [48] on a MACSquant Analyzer 10 Flow Cytometer ( Miltenyi Biotec , Germany ) . Briefly , YFP fluorescence measurements were collected using 488nm laser excitation , with a 525/50 nm emission filter . Settings in the instrument panel for the laser were as follows: trigger on FSC ( linear , 423V ) , SSC ( linear , 537 V ) , and B1 laser ( hlog , 790V ) . Before each experiment the MACSquant was calibrated using MACSQuant Calibration Beads ( Miltenyi Biotec , CAT NO . 130-093-607 ) . Cells were grown to OD 0 . 2-0 . 3 and then diluted tenfold into ice-cold minimal M9 + 0 . 5% glucose . Cells were then automatically sampled from a 96-well plate kept at approximately 4°–10°C using a MACS Chill 96 Rack ( Miltenyi Biotec , CAT NO . 130-094-459 ) at a flow rate of 2 , 000–6 , 000 measurements per second . For those measurements that were taken for IPTG induction curves , cells were grown as above with the addition of an appropriate concentration of IPTG ( Isopropyl β-D-1 thiogalactopyranoside Dioxane Free , Research Products International ) . For each IPTG concentration , a stock of 100-fold concentrated IPTG in MilliQ-purified water was prepared and partitioned into 100 μL aliquots . The same parent stock was used for all induction experiments described in this work . The fold-change in gene expression was calculated by taking the ratio of the mean YFP expression of the population of cells in the presence of LacI to that in the absence of LacI . Since the measured fluorescence intensity of each cell also includes autofluorescence which is present even in the absence of YFP , we account for this background by computing the fold change as fold-change = ⟨ I R > 0 ⟩ - ⟨ I auto ⟩ ⟨ I R = 0 ⟩ - ⟨ I auto ⟩ , ( 6 ) where 〈IR>0〉 is the average cell YFP intensity in the presence of repressor , 〈IR=0〉 is the average cell YFP intensity in the absence of repressor , and 〈Iauto〉 is the average cell autofluorescence intensity as determined by measuring the fluorescence of cells in which R = 0 and there is no fluorescent reporter .
|
It has been said that we live in the “genomic era , ” a time where we can readily sequence full genomes at will . However , it remains difficult to interpret much of the information within a genome . This is especially true of non-coding sequences such as promoters , which contain a number of features such as transcription factor binding sites that determine how genes are regulated . There is no straightforward regulatory “code” that tells us how transcription factor binding sites are organized within a promoter . In this work we examine how DNA sequence determines one of the most important features of a promoter , the strength with which a transcription factor binds to its DNA binding site . We discuss an approach to modeling DNA sequence-specific transcription factor binding energies in vivo using a massively parellel reporter assay . We develop models that allow us to predict the binding energy between a transcription factor and a mutated version of its binding site . We then show that this modeling technique can be used to address a number of scientific and design questions , such as engineering the behavior of genetic circuit elements or examining how transcription factors and their binding sites co-evolve .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Methods"
] |
[
"chemical",
"characterization",
"gene",
"regulation",
"regulatory",
"proteins",
"dna-binding",
"proteins",
"dna",
"transcription",
"transcription",
"factors",
"sequence",
"motif",
"analysis",
"research",
"and",
"analysis",
"methods",
"sequence",
"analysis",
"transcriptional",
"control",
"bioinformatics",
"proteins",
"gene",
"expression",
"binding",
"analysis",
"biochemistry",
"dna",
"sequence",
"analysis",
"database",
"and",
"informatics",
"methods",
"genetics",
"biology",
"and",
"life",
"sciences"
] |
2019
|
Mapping DNA sequence to transcription factor binding energy in vivo
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Venezuelan equine encephalitis virus ( VEEV ) is responsible for VEE epidemics that occur in South and Central America and the U . S . The VEEV envelope contains two glycoproteins E1 ( mediates cell membrane fusion ) and E2 ( binds receptor and elicits virus neutralizing antibodies ) . Previously we constructed E1 and E2 epitope maps using murine monoclonal antibodies ( mMAbs ) . Six E2 epitopes ( E2c , d , e , f , g , h ) bound VEEV-neutralizing antibody and mapped to amino acids ( aa ) 182–207 . Nothing is known about the human antibody repertoire to VEEV or epitopes that engage human virus-neutralizing antibodies . There is no specific treatment for VEE; however virus-neutralizing mMAbs are potent protective and therapeutic agents for mice challenged with VEEV by either peripheral or aerosol routes . Therefore , fully human MAbs ( hMAbs ) with virus-neutralizing activity should be useful for prevention or clinical treatment of human VEE . We used phage-display to isolate VEEV-specific hFabs from human bone marrow donors . These hFabs were characterized by sequencing , specificity testing , VEEV subtype cross-reactivity using indirect ELISA , and in vitro virus neutralization capacity . One E2-specific neutralizing hFAb , F5n , was converted into IgG , and its binding site was identified using competitive ELISA with mMAbs and by preparing and sequencing antibody neutralization-escape variants . Using 11 VEEV-reactive hFabs we constructed the first human epitope map for the alphaviral surface proteins E1 and E2 . We identified an important neutralization-associated epitope unique to the human immune response , E2 aa115–119 . Using a 9 Å resolution cryo-electron microscopy map of the Sindbis virus E2 protein , we showed the probable surface location of this human VEEV epitope . The VEEV-neutralizing capacity of the hMAb F5 nIgG is similar to that exhibited by the humanized mMAb Hy4 IgG . The Hy4 IgG has been shown to limit VEEV infection in mice both prophylactically and therapeutically . Administration of a cocktail of F5n and Hy4 IgGs , which bind to different E2 epitopes , could provide enhanced prophylaxis or immunotherapy for VEEV , while reducing the possibility of generating possibly harmful virus neutralization-escape variants in vivo .
Venezuelan equine encephalitis virus ( VEEV ) is a member of the Alphavirus genus in the family Togaviridae and is maintained in a natural enzootic cycle between mosquitoes and rodent hosts , although equines and humans may also be infected in an epizootic cycle [1] . While VEEV causes high-titered viremia in equines , resulting in encephalitis with a mortality rate between 30 to 90% , disease in humans is usually self-limited and consists of fever , chills , malaise , and severe headaches , with 1 to 4% progressing to severe encephalitis [2] . Outbreaks of epizootic VEEV ( subtypes 1AB and 1C ) occur periodically in South and Central America , even spreading to south Texas , and therefore it is considered an emerging pathogen [3] . While the last major transcontinental outbreak of epizootic VEEV occurred in 1969–1971 , smaller South and Central American outbreaks of VEEV 1C have occurred since , such as the one in Colombia and Venezuela in 1995–1996 [4] , [5] . In the mid to late 1990's outbreaks caused by the usually enzootic subtype VEEVs occurred in Peru and Panama ( VEEV-1D ) , and in the Mexican states of Chiapas and Oaxaca ( VEEV-1E ) [6]–[9] . VEEV has potential as a bioweapon , principally because of its low human infective dose , easy production , and capability for effective transmission by aerosolization [10] , [11] , and it is listed as a NIAID Category B priority pathogen . Experimental vaccines ( TC-83 , C-84 ) have been used to protect laboratory personnel and military troops , but are not licensed for general use [12]–[14] . A new , live-attenuated vaccine , V3526 , developed from a virulent VEEV infectious clone by site-directed mutagenesis [15] , proved effective in animal studies [16]–[18] , but was associated with adverse events in phase 1 clinical trials and subsequently abandoned [19] , [20] . Alphaviruses have a positive-sense , single-stranded RNA genome of approximately 11 . 45 kb enclosed within an icosahedral nucleocapsid surrounded by a lipid bilayer derived from the infected cell's plasma membrane . Two integral membrane glycoproteins , E1 and E2 , are embedded in the lipid envelope and are assembled as heterodimers into 80 trimeric spikes on the virus surface [21]–[25] . Although the crystal structures of the E1 and capsid proteins of several alphaviruses have been solved , no well-diffracting crystals of either E2 or virus particles have been obtained [26]–[28] . However , cryo-electron microscopy ( cryoEM ) reconstructions of several alphaviruses have been reported and have provided insights into probable E1/E2 structure-function relationships [25] , [29]–[32] . The E1 glycoprotein is responsible for cell membrane fusion , while E2 is primarily involved in receptor binding and cell entry as well as eliciting VEEV-specific neutralizing antibodies . We have previously analyzed the antigenic structure of both the VEEV E1 and E2 glycoproteins using murine ( m ) monoclonal antibodies ( MAbs ) and defined six E2 epitopes ( E2c , d , e , f , g , h ) involved in VEEV neutralization [33]–[35] . These epitopes clustered in a “critical VEEV E2 neutralization site , ” and were mapped to E2 amino acids ( aa ) 182–207 by sequencing the RNA of MAb neutralization-escape VEEV variants [36] . Similar E2 neutralization sites have been identified for both Sindbis virus ( SV ) ( E2 aa170–220 ) and Ross River virus ( RRV ) ( E2 aa216–251 ) using mMAbs [37]–[39] . The VEEV epitopes E2c and E2h are the most conserved on the E2 glycoproteins of heterologous VEEVs [33] , [40] . Specific treatment for VEEV infections is not available; however , MAbs reacting with the critical neutralization site demonstrate potent protective activity in a murine model following either peripheral or aerosol challenge with virulent VEEV [12] , [35] , [41] , [42] . Moreover , anti-E2c mMAb 1A4A-1 and anti-E2g mMAb 1A3A-9 , as well as the humanized anti-E2c mMAb Hy4 IgG , have been shown to provide post-exposure protection when administered within 24 hr after virus inoculation [12] , [43] . Fully human ( h ) MAbs would be the best choice for clinical treatment of human infections; however , little is known about the immunologic specificities of the human antibody repertoire to VEEV , and no protective hMAbs have yet been isolated , characterized , or implemented . In this report we have presented a map of the human VEEV antibody response and determined the human immunodominant epitopes on the VEEV E1 and E2 proteins . We used phage-display technology to isolate VEEV-specific hFabs from bone marrow donors known to have circulating antibodies for VEEV [44]–[47] . We have characterized a panel of 11 hFabs for VEEV surface protein specificity , subtype cross-reactivity , and in vitro virus-neutralizing capacity . Two anti-E2 hFabs , H6 and F5 , one of which ( F5 ) exhibited potent neutralizing activity , were converted to fully human IgG1 molecules . Two F5 hMAb neutralization-escape VEEV variants were isolated . Sequencing of the E1 and E2 protein genes of these variant viruses identified a unique human VEEV neutralization domain as the likely binding site of the F5 hMAb . Alphavirus cryoEM maps , with associated markers , support proposing a probable surface-accessible location on VEEV E2 for the F5 native ( n ) IgG binding site .
The VEE complex viruses used in this study were Trinidad donkey ( TrD , subtype 1 , variety AB ) , vaccine strain TC-83 ( 1-AB ) , P676 ( 1-C ) , 3880 ( 1-D ) , Mena II ( 1-E ) , Everglades ( EVE ) ( 2 ) , Mucambo ( MUC ) ( 3-A ) , Pixuna ( PIX ) ( 4 ) , Cabassou ( CAB ) ( 5 ) , and AG80-663 ( Rio Negro ) ( 6 ) , which were obtained from the Division of Vector-Borne Infectious Diseases ( DVBID ) , Centers for Disease Control ( CDC ) , Fort Collins , CO . Viruses grown in Vero cells were purified by equilibrium density-gradient centrifugation [48] . Purified VEEV TC-83 used for panning phage display libraries was inactivated with 0 . 05% or 0 . 3% β-propiolactone ( BPL ) in 0 . 1M Tris base , pH 9 , for 48 h at 4°C . Virus inactivation was verified by inoculation of Vero cells , which were monitored for cytopathic effects ( CPE ) . Inactivated virus was evaluated by ELISA for preservation of important epitopes reactive with neutralizing mMAbs [33] . Anti-VEEV neutralizing mMAbs ( 3B4C-4 , 1A4D-1 , 1A3A-9 , 1A3B-7 , and 3B2A-9 ) and their respective neutralization-escape variant viruses used in the characterization of hMAb F5 nIgG have been well-documented [33] , [34] , [36] . Total RNA was obtained from bone marrow and blood samples supplied by two military donors ( 951 , 1037 ) using Tri-reagent BD ( Molecular Research Center , Inc . , Cincinnati , OH ) according to the manufacturer's instructions . Blood utilized in this project was obtained under protocol 01-124 approved by Scripps Clinic , IRB#00001283 , Assurance Number FWA00000467 . Bone marrow samples were obtained from a commercial source . Donor sera ELISA titers to VEEV TC-83 were 1∶500–3000 . Messenger RNA was isolated using Oligotex spin columns ( Qiagen , Valencia , CA ) following the manufacturer's protocol . To amplify mRNA , first strand cDNA was synthesized using SuperScript II reverse transcriptase ( Invitrogen , Carlsbad , CA ) according to the manufacturer's protocol . Second strand cDNA was synthesized according to the method fully described in the patent WO2005/060641A2 [49] . The cDNA was purified with a PCR purification kit ( Qiagen ) and single primer amplification was performed according to the method fully described in the patent . The amplified products were digested with Xba I/Sac I for the kappa light chains ( LCs ) , Xba I/Kas I for the lambda LCs , and Xho I/Age I ( Pin AI ) for the heavy chains ( HCs ) , and cloned into Fab expression phagemid vectors PAX243hGK and PAX243hGL . Two Fab libraries were generated for each donor , one expressing kappa LCs and one , lambda LCs , and both utilizing gamma HCs . Fab-bearing phage from all libraries were panned through one to four rounds of enrichment against inactivated VEEV TC-83 coated in 96-well plates overnight at 4°C . Wells were washed with water and blocked 1 h at 37°C with 3% bovine serum albumin ( BSA ) in phosphate-buffered saline ( PBS ) . The phage library was added to the wells and incubated at 37°C for 2 h . Wells were washed 10 times with PBS containing 0 . 05% Tween-20 ( PBS-T ) . The bound Fab-phage were eluted with 2M glycine , pH 2 . 2 , neutralized with 2M Tris base , used to infect log phase E . coli cells , strain ER 2738 , and amplified by adding helper phage , strain VCSM13 , to the infected bacteria for each round of panning . Individual colonies were produced by plating infected bacteria . Screening by ELISA on inactivated VEEV TC-83 virus was performed in high throughput mode using a Tecan robot ( Tecan Systems Inc . , San Jose , CA ) for large numbers of colonies ( >1000 ) picked using a Q-pix instrument ( Genetix Inc . , Boston , MA ) . Individual colonies were grown overnight in deep-well microtiter dishes in a Hi-Gro high-speed incubator-shaker ( GeneMachines , San Carlos , CA ) . Aliquots were removed and stored as stocks containing 15% glycerol or 10% DMSO . After centrifugation of the deep-well dishes , Fab-containing supernatants were collected for ELISA screening . Alkaline phosphatase ( AP ) -labeled goat anti-human Fab ( Pierce Protein-Thermo Fisher Scientific , Rockford , IL ) was used to detect expressed Fab bound to antigen . Miniprep DNA ( Qiagen ) from positive colonies was sequenced across the light and heavy chains using standard primers for the phagemid expression vectors . Sequences were analyzed using DNAstar software ( DNAstar Inc . , Madison , WI ) to identify and classify unique candidates . For soluble Fab expression and purification , the gene III fusion region of the phagemid was removed from positive , unique candidates by subcloning . At this stage it was possible to insert an oligonucleotide that encoded a combination epitope tag consisting of an influenza virus hemagglutinin ( HA tag ) and 6 histidine residues ( His tag ) for detection and purification with anti-HA and/or Ni-NTA [50] . Panning and screening of additional libraries were done on inactivated VEEV TC-83 , either with or without epitope masking by non-neutralizing hMAbs F2 engineered ( e ) IgG and H6 eIgG to increase the chances of isolating Fabs with neutralizing capability . For panning with epitope masking , wells coated with VEEV TC-83 were incubated with F2 eIgG ( 50 µg/ml ) and H6 eIgG ( 10 µg/ml ) in 1% BSA-PBS at 37°C for 30 min followed by addition of library phage and incubation at 37°C for 1 . 5 h . Fabs selected for characterization were cloned into a Fab expression vector , PAEV1 , using Eco RI/Spe I restriction sites available in the vector ( Figure S1A ) . Two Fabs , K1B11 and K1H3 , which had Eco RI sites in their LCs were cloned into a PAEV1 vector containing Fab L1A7 LCs and HCs by using the Xba I/Age I sites ( Figure S1B ) . The selected Fabs were produced in BL21 E . coli cells with induction by isopropyl-β-D-thiogalactopyranoside and purified on a goat anti-human IgG F ( ab′ ) 2 affinity column . Purified F5 Fab for use as a positive control in ELISA was prepared from F5 eIgG by papain digestion using an ImmunoPure Fab Preparation Kit ( Pierce ) according to the manufacturer's instructions . Four hFabs ( F2 , F5 , G1 and H6 ) were converted to full-length IgG1s in a two-step cloning process ( Figure S2 ) . The region between LC and HC ( Not I to Xho sites ) was replaced with mammalian control elements , including a poly A signal for the end of the LC , a human cytomegalovirus promoter to direct expression of the HC , and an HC mammalian leader sequence . This intermediate was inserted via restriction sites Sfi I and Age I into a mammalian expression vector containing additional control elements and IgG1 HC constant domains . The resulting “engineered” IgG1 differed from the n sequence due to the few non-n aa codons at three restriction sites ( Xba I , Sac I , and Xho I ) present at the N-terminus of both LC and HC . F5 eIgG was then converted to IgG containing n sequences in three steps using site-specific mutation and overlap PCR ( Figure S3 ) . The sequences of all constructs were verified . HMAbs were produced by transfecting 120 ml of 293-EBNA cells ( 3 . 75×105 cells/ml ) with 64 µg of MAb expression vector DNA using Effectene ( Qiagen ) according to the manufacturer's protocol . The culture supernatant was harvested 5–7 days after transfection and each MAb was purified on a protein A column using FPLC . Stable cell lines producing F5 nIgG were established by selecting transfected 293-EBNA cells with puromycin ( 10µg/ml ) . The transfected cells were initially grown in 24-well plates and medium was screened by ELISA using a goat anti-human IgG F ( ab′ ) 2 antibody-AP conjugate ( Jackson ImmunoResearch , West Grove , PA ) for detection . The 2 wells with the highest antibody expression were chosen for single cell selection in four 96-well plates . Wells containing single-cell colonies were tested by ELISA and the best producers were chosen for expansion . One of these clones , IE9 , was grown in 1 . 5 L and 6 L cultures that produced 25 mg and 50 mg MAb , respectively , after protein A column purification . The purified antibody showed specific binding to inactivated VEEV TC-83 that was comparable to that of F5 nIgG prepared from transient transfection of 293-EBNA cells . The GenBank accession numbers for the F5 nIgG light and heavy chain variable region sequences are HM047070 and HM047071 , respectively . Indirect ELISAs were used to verify VEEV binding by purified hFabs and to determine the cross-reactivity of selected hFabs and hMAbs to six VEEV subtypes and four varieties of subtype 1 . ELISAs were performed essentially as previously described [43] , [51] . Fab or MAb binding to purified virus was detected by goat anti-human IgG F ( ab′ ) 2- or Fc-specific-AP conjugates ( Jackson ImmunoResearch ) . An absorbance ratio ( A405 test sample/A405 negative control ) >2 was considered to be positive . Competitive binding assays ( CBAs ) were used to determine the ability of F5 nIgG to block the binding of anti-VEEV neutralizing mMAb-horseradish peroxidase ( HRP ) conjugates , and , conversely , the ability of purified mMAbs or hFabs to block the binding of F5 nIgG-HRP to virus . A dilution of each unconjugated mMAb , hMAb , or hFab that resulted in approximately 70% binding to VEEV TC-83 was determined by titration in an indirect ELISA , using either AP-conjugated goat anti-mouse IgG ( Fc-specific ) or goat anti-human IgG [F ( ab′ ) 2-specific] as a detector and Sigma 104 phosphatase substrate . Reactions were read at 405 nm . Dilutions of MAb conjugates that resulted in an A405 of approximately 1 . 0 were also determined for use in CBAs . For competitions using MAb-HRP conjugates , wells were coated with 1 µg VEEV TC-83 overnight and then blocked with 3% goat serum in PBS for 1 h at 37°C . MAb or Fab competitors were added at predetermined dilutions , serially diluted 1∶2 in PBS-T , and incubated at room temperature for 30 min . A previously determined constant dilution of MAb-HRP in blocking buffer was added to each serially-diluted competitor and incubated for 1 h at 37°C . One hundred µl premixed tetramethyl benzidine substrate ( Neogen Corp . , Lexington , KY ) was added to each well , the reaction was stopped in 15–30 min with 50 µl 1N H2SO4 , and plates were read at 450 nm . Viral protein specificity of each antibody was determined by immunoblot using precast 8% Tris-glycine gels ( Invitrogen ) for fractionation of purified VEEV TC-83 , 1 or 2 µg per lane , under both reducing and non-reducing conditions for 110 min at 125 volts . Electroblotting onto 0 . 2 µm nitrocellulose membranes using a Novex XCell blotting apparatus ( Invitrogen ) was done according to the manufacturer's protocol . Membranes were blocked with StartingBlock buffer ( Pierce ) at 4°C to prevent nonspecific binding . Membrane strips were incubated with the purified hMAbs and hFabs as well as protein E1- and E2-specific mMAbs for 2 h at room temperature , followed by incubation with either AP-conjugated goat anti-human IgG F ( ab′ ) 2 or goat anti-mouse IgG ( Jackson ImmunoResearch ) for 1 h , and then visualized with 5-bromo-4-chloro-3-indolyl-phosphate/nitroblue tetrazolium phosphatase substrate ( Kirkegaard and Perry Laboratories , Gaithersburg , MD ) . The PRNT for IgG or Fab antibody fragments was performed essentially as previously described [43] . Neutralization-escape variant viruses were selected with F5 nIgG using an infectious clone of VEEV TC-83 , pVE/IC-92 , in a manner similar to that used previously to select escape variant viruses for neutralizing mMAbs [36] , [52] . In this case , different amounts of purified MAb F5 nIgG ( 6 replicates each of 50 µg , 5 µg , and 0 . 5 µg ) were incubated with approximately 100 pfu of virus for 1 h at 37°C and then plated on Vero cell monolayers in 6-well plates . Well-isolated plaques were cored , eluted overnight at 4°C , and 0 . 5 ml of the eluted virus from each sample was incubated with 25 µg ( 5 ml ) of F5 nIgG for 1 h at 37°C . Each sample was then adsorbed to Vero cells containing 50 µg MAb/ml in the culture medium and monitored for CPE . Supernatant was collected from this second selection cycle from wells showing CPE and the virus seed was passed once in Vero cells without addition of F5 nIgG . Two variant viruses were isolated and RNA was extracted from 140-µl aliquots of seed virus from the variant and parent viruses using the QIAamp viral RNA Kit ( Qiagen ) following the manufacturer's instructions . RNA was eluted in 30–40 µl of nuclease-free water and stored at −80°C . Amplimers for sequencing the glycoprotein-coding region of pVE/IC-92 and the two variant viruses were generated by standard RT-PCR performed with either 5 or 10 µl of template RNA and 20 pmol of each primer ( Table S1 ) in a 50 µl-reaction using the Titan RT-PCR Kit ( Roche Molecular Biochemicals , Indianapolis , IN ) , following the manufacturer's protocol . Initial RT was performed at 50°C for 30 min , followed by denaturation at 96°C for 2 min . PCR included 10 cycles of 96°C for 20 sec , 52°C for 30 sec , 68°C for 2 . 5 min; 25 cycles of 96°C for 20 sec , 52°C for 30 sec , 68°C for 2 . 5–6 . 7min; and a final extension at 68°C for 7 min in a DNA Engine Thermocycler ( BioRad , Hercules , CA ) . The resulting amplimers were gel purified using a QIAquick Gel Extraction Kit ( Qiagen ) , essentially following the manufacturer's protocol . Approximately 20–30 ng of each amplimer was used for direct sequencing using a 9800 Fast Thermocycler , a Big Dye automated DNA sequencing kit , and a 3130×l Genetic Analyzer ( Applied Biosystems , Foster City , CA ) .
Bone marrow specimens with matched sera donated by VEEV seropositive , active service military personnel were provided to Alexion Antibody Technologies ( AAT ) , San Diego , CA , from a commercial source . The human donor sera were tested against inactivated VEEV TC-83 using an indirect ELISA . Only inactivated VEEV was used at AAT; both native and inactivated VEEV were used at DVBID , CDC , and Colorado State University , Fort Collins , CO . Two donor bone marrows , 951 and 1037 , were selected for use in constructing phage display libraries . Large libraries , 2 . 6–5 . 7×109 phage particles per ml , were obtained and panned through four rounds on inactivated VEEV TC-83 . A panel of hFab clones from panning rounds three and four for each of four libraries ( 951κ , 951λ , 1037κ , and 1037λ ) was screened on VEEV TC-83 as well as 1% BSA ( negative control ) . Three hFab clones with the highest ELISA signals from each of the four libraries were selected for sequence analysis . The sequencing results ( not shown ) showed that all three 951κ clones were identical . Ten of the 12 clones had the same variable HC region , but the majority of those Fabs had different LC sequences . In all , there were 10 unique clones in three separate HC groupings . Four hFab clones , P3F2 , P3F5 , P3H6 , and P3G1 , were expressed as soluble molecules and purified by Ni-NTA column chromatography for use in serological assays . These four clones were also converted to full-length IgG1 molecules ( Figure S2 ) . Because the P3F5 clone had significant VEEV-neutralizing ability , a stable cell line expressing F5 nIgG was generated in 293-EBNA cells . An attempt was made to identify additional anti-VEEV hFabs using libraries from donors 951 and 1037 . In this case the VEEV TC-83 used for panning and screening was inactivated with 0 . 05% BPL; previously the virus used for these procedures was inactivated with 0 . 3% BPL , a concentration subsequently shown to reduce the binding of F5 eIgG and F5 nIgG ( Table S2 ) . Panning was done with and without epitope masking with non-neutralizing hMAbs F2 eIgG and H6 eIgG in order to increase the probability of isolating Fabs with neutralizing ability . Nine new hFabs were isolated , four using the epitope masking protocol ( K1B11 , K1H3 , L1A7 , and K2E2 ) and five without masking ( LR3H11 , KR2A3 , KR2B12 , KR2C2 , and 951-D3 ) . HMAbs were titrated on VEEV TC-83 by ELISA ( Figure S4 ) . The three hMAbs and mMAb 3B4C-4 had similar binding affinities for TC-83 , with titers of approximately 3 ng/ml . All the hFabs had endpoint titers of 5–20 ng/ml with the exception of L1A7 which had a titer of approximately 0 . 5 µg/ml ( Fig . S5 ) . The viral protein specificities of the hMAbs and hFabs were determined by immunoblot using purified VEEV TC-83 separated by PAGE under both reducing and non-reducing conditions . Seven of 11 antibodies were specific for the E2 glycoprotein and four for E1 . All the E2-specific antibodies recognized both reduced and non-reduced protein , whereas the E1-specific antibodies lost reactivity after proteins were subjected to reducing conditions ( exposure to 2-mercaptoethanol ) ( Table 1 ) . The human antibodies were evaluated by ELISA to determine cross-reactivity with nine VEEVs , representing four subtype 1 varieties as well as subtypes 2–6 ( Table 1 ) . HMAb epitope designations were based on the number and specificity of the VEEV subtypes and varieties recognized by each antibody in ELISA and the sequence data for MAb and Fab HC and LC complementary determining region 3 ( HCDR3 , LCDR3 ) ( Tables 1 , 2 ) . The cross-reactivity analysis is also presented in graphica10 . 1371/journal . pntd . 0000739 . t001Table 1 Characterization of human MAbs and Fabs for Venezuelan equine encephalitis virus ( VEEV ) . Epitope µg MAb MAbA 1ABB 1C 1D 1E 2 3 4 5 6 PRNTC ImmunoblotD hE2a1 1 H6 eIgG ++ ++ ++ ++ ++ ++ − ++ ++ >10 +/not tested hE2a2 1 LR3H11 ++ ++ ++ ++ ++ + − + + >100 +/+ hE2b 1 KR2A3 ++ ++ ++ + ++ + − + + >100 +/+ hE2b 1 KR2B12 ++ ++ ++ + ++ + − + + >100 +/+ hE2b 1 KR2C2 ++ ++ ++ ++ ++ + − + + >100 +/+ hE2c 1 F5 nIgG ++ ++ ++ ++ ++ ++ − − ++ 0 . 01 +/+ hE2d 10 951 D3 ++ + + ++ − − − − − >100 +/+ mE2c 100 Hy4 IgG ++ ++ + − ++ − − − − < . 004 +/+ hE1a 1 K1B11E ++ ++ ++ ++ ++ ++ + ++ ++ >100 +/− hE1a 1 K1H3E ++ ++ ++ ++ ++ ++ + ++ ++ >100 +/− hE1b 10 L1A7E ++ ++ ++ − + ++ − + − 2–3 . 1 +/− hE1c 1 K2E2E ++ ++ ++ − ++ ++ ++ ++ ++ >100 +/− AMAb tested as full antibody ( H6 , F5 , and Hy4 ) or Fab . Hy4 IgG is a humanized mouse ( m ) MAb; all other antibodies are human ( h ) . BCross-reactivity reported as percent of each MAb's reactivity with subtype 1AB ( VEEV TC-83 ) ; ++ ( >50% ) , + ( 25–50% ) and − ( <25% ) . Viruses used for each subtype: 1C ( P676 ) , 1D ( 3880 ) , 1E ( Mena II ) , 2 ( Everglades ) , 3 ( Mucambo ) , 4 ( Pixuna ) , 5 ( Cabassou ) , and 6 ( AG80-663 ) . CAntibody endpoint concentration ( µg/ml ) in a 70% plaque-reduction neutralization test ( PRNT ) with VEEV TC-83 . DAntibody reactivity by immunoblot on nonreduced/reduced VEEV TC-83 antigens . EFabs isolated using epitope masking with anti-E2 hMAbs F2 eIgG and H6 eIgG during the panning process . l form since antibodies with similar cross-reactivities had unique titration curves when antibody concentration was plotted versus absorbance at 405 nm ( Figures 1 , 2 ) . Sufficient amounts of MAbs F2 eIgG and G1 eIgG were not available to determine ELISA cross-reactivity but each was shown to be specific for E2 by immunoblot and to have PRNT endpoints of ≥10µg/ml ( data not shown ) . H6 eIgG , assigned to epitope hE2a1 , was the most cross-reactive of the anti-E2 MAbs characterized , reacting with all the VEEV subtypes and varieties tested except subtype 4 ( Table 1 , Figure 1 ) . MAbs F2 , G1 , and H6 had the same HCDR3 aa sequence , but different LCDR3 sequences , which might indicate that these MAbs bind to different , but overlapping epitopes ( Table 2 ) . Fab LR3H11 was assigned to epitope hE2a2 based on the similarities of its ELISA titration curve to that for the anti-hE2a1 MAb ( Figure 1 ) and its cross-reactivity ( Table 1 ) , and on differences in HCDR3 and LCDR3 sequences ( Table 2 ) . LR3H11 had a generally lower level of reactivity to all the VEEV subtypes ( especially subtypes 3 , 5 , and 6 ) , compared to H6 eIgG . The higher reactivity level of H6 eIgG compared to Fab LR3H11 could be due to the fact that H6 is a complete IgG molecule . Although the HCDR3 sequence is the same for LR3H11 and the anti-hE2b Fabs , the LCDR3 sequences are completely different ( Table 2 ) . The three anti-hE2b Fabs , KR2A3 , KR2B12 , and KR2C2 , have identical HCDR3 sequences and the LCDR3 sequences are 44 to 100% similar ( Table 2 ) . Fabs KR2A3 and KR2B12 have the same sequence throughout except for one aa change in framework region 2 ( Lys to Arg ) . In addition , this group of Fabs had a distinct reactivity profile consisting of three reactivity groups ( curves ) which included the following subtypes and varieties: ( 1 ) 1AB , 1C , 1D , 2; ( 2 ) 1E , 3 , 5 , 6; and ( 3 ) 4 ( Figure 1 ) . MAb F5 nIgG had a unique cross-reactivity pattern and unique HCDR3/LCDR3 sequences as well as potent viral neutralizing activity , and was assigned to epitope hE2c ( Tables 1 , 2; Figure 1 ) . Fab 951 D3 , which was isolated from a different bone marrow donor , also had unique HCDR3/LCDR3 sequences and a unique cross-reactivity pattern , and was assigned to epitope hE2d ( Tables 1 , 2; Figure 1 ) . The E1-specific hFabs were isolated using epitope blocking during the panning process . Blocking with two E2-specific , non-neutralizing MAbs ( F2 and H6 ) did not have the desired effect of increasing the isolation of neutralizing Fabs; instead this blocking seemed to have inhibited binding of E2-specific Fabs since only E1-specific Fabs were isolated . L1A7 had very limited neutralizing ability , typical for an E1-specific MAb ( Table 1 ) . Fabs K1H3 and K1B11 had identical HCDR3 sequences and very similar LCDR3 sequences ( two aa differences ) ; these Fabs were assigned to epitope hE1a ( Tables 1 , 2; Figure 2 ) . Anti-hE1a Fabs were the most cross-reactive antibodies identified , showing good reactivity with all the VEEV subtypes tested . Fabs L1A7 and K2E2 had unique HCDR3 and LCDR3 sequences as well as cross-reactivity patterns , and were assigned to epitopes hE1b and hE1c , respectively ( Tables 1 , 2; Figure 2 ) . CBAs were performed by ELISA , using VEEV TC-83 as the antigen , to determine if there was spatial overlap between epitope hE2c , defined by the neutralizing hMAb F5 nIgG , and the epitopes defined by the other hFabs . Only the homologous F5 Fab or F5 nIgG was able to compete with F5 nIgG , unconjugated or conjugated to HRP ( Table 3 ) . None of the anti-hE2a2 , -hE2b , -hE2d , -hE1a , -hE1b , or -hE1c Fabs showed >50% competition with F5 nIgG . CBAs between mMAbs and hMAb F5 were also used to evaluate the spatial similarity of the hE2c epitope defined by MAb F5 nIgG to the previously characterized VEEV E2 epitopes defined by mMAbs which comprise the major E2 neutralization domain ( E2 aa182–207 ) [33] , [34]; competition values >50% were considered significant ( Table 4 ) . The results showed that epitope hE2c is most spatially aligned with mMAb-defined epitopes E2d and E2f; antibodies defining these epitopes showed reciprocal or two-way competition . One-way competitions included F5 nIgG competing with anti-mE2a-HRP and anti-mE2e-HRP ( 59% and 56% , respectively ) ; however , neither anti-mE2a nor anti-mE2e could compete with F5-HRP . Murine and humanized anti-E2c MAbs 1A4A-1 and Hy4-IgG [43] competed with F5-HRP ( 92% and 95% , respectively ) , but F5 did not significantly block the virus binding of anti-E2c 1A4A-1-HRP ( 20% ) . Additionally , there was no competition between F5 and anti-E2g or anti-E2h mMAbs . These analyses indicate that F5 nIgG does not bind to an epitope within the major neutralization domain on the VEEV E2 glycoprotein defined by mMAbs [33] . Anti-VEEV mMAb neutralization-escape variants with mutations in epitopes E2c , E2f , E2g , or E2h were evaluated for reactivity with F5 nIgG [36] . If the epitope recognized by F5 were the same as , or near , any of the changed aa residues ( E2-182 , 183 , 199 , and 207 ) in the neutralization-escape variant viruses , then F5 would be unable to neutralize that variant . Results indicated that F5 was able to neutralize all the variant viruses , including v3B2A-9 which is specific for an E1 epitope ( Table 5 ) . F5 nIgG PRNT endpoints were equivalent for all the variant viruses as well as the parent VEEV TC-83 . MAb F5 nIgG was used to select neutralization-escape variants of the VEEV TC-83 infectious clone , pVE/IC-92 , in order to more accurately map the binding site of this potent neutralizing antibody . Two variant ( v ) viruses were isolated , vF5 nIgG-3 ( vF5-3 ) and vF5 nIgG-5 ( vF5-5 ) , which required either 500- or 2000-fold more F5 nIgG for neutralization than that needed for neutralization of parental VEEV TC-83 ( Table 6 ) . Neutralization of these variants was also evaluated with the humanized Hy4 IgG which is known to bind to the mE2c epitope ( E2 aa182 ) [36] . The vF5-5 virus required ≥4000-fold more Hy4 IgG than the parent virus for neutralization , and thus was neutralization-resistant for both F5 nIgG and Hy4 IgG . Although the vF5-3 virus resisted neutralization with F5 nIgG , Hy4 neutralized this variant as well as it neutralized VEEV TC-83 . Genomes of the variant and parental VE/IC-92 viruses were sequenced from nucleotide 8195 to 11421 , which includes genetic information for viral structural proteins E1 , E2 , E3 , 6K and a portion of the capsid . Mutations in the variant viruses were found only in the E2 glycoprotein between aa 115–119 ( Table 7 ) . The vF5-3 virus had a transition from A to G at nucleotide 8906 , resulting in a non-conservative amino acid change from Lys to Glu at E2 aa115 . There was also a deletion of nucleotides 8918–8923 , coding for Val ( E2 aa119 ) , in the parent virus . The vF5-5 virus had a silent G to A change at nucleotide 8908 , followed by a deletion of nucleotides 8909–8911 , which code for Lys ( E2 aa116 ) . The sequence change at E2 aa115 and deletions at E2 aa116 and 119 in these neutralization-escape variant viruses indicate that F5 binds at this site in the E2 glycoprotein . F5 nIgG neutralizing activity was somewhat more reduced with vF5-5 virus than with vF5-3 , suggesting that the deletion of Lys is more disruptive for F5 binding than the Lys to Glu substitution coupled with the Val deletion found in the vF5-3 virus .
The humoral immune response to VEEV infection in mice has been well characterized and anti-VEEV mMAbs have played an essential role in identifying the important antigenic domains of the virus glycoproteins [33]–[35] . Although non-human primate models have been used to evaluate vaccine efficacy of candidate VEEVs , the antibody repertoires in these primates and humans have not been well characterized [16] , [17] , [53] . Use of phage antibody libraries generated from immune or nonimmune donors has proved to be an efficient method for obtaining a diverse set of non-human primate or human antibodies for a wide variety of viruses: VEEV [54] , human papillomavirus [55] , Sin Nombre virus [56] , West Nile virus [57] , yellow fever virus ( YFV ) [58] , rabies virus [59] , SARS-coronavirus [60] , hepatitis A virus ( HAV ) [61] , dengue 4 virus ( DENV4 ) [62] , rotavirus [63] , Hantaan virus [64] , measles virus [65] , and HIV [66] . In this study we have characterized 11 unique hFabs and hMAbs for viral protein specificity , VEEV subtype cross-reactivity , and virus neutralization capacity and constructed the first human epitope map for the E1 and E2 proteins of an alphavirus . In addition we have mapped the potential E2 binding site of the potent neutralizing hMAb F5 nIgG using CBAs with the other hFabs as well as anti-VEEV mMAbs , and isolated and sequenced the RNA coding for E1 and E2 glycoproteins of F5 neutralization-escape variant viruses . The antibody clones selected for characterization showed good ELISA binding to VEEV TC-83 and had unique complete gene sequences; seven hMAbs were specific for the E2 glycoprotein and four for E1 . Only two neutralizing hFabs , F5 and L1A7 , were isolated , despite the use of a blocking strategy during panning to favor selection of such antibodies . A similar strategy was used , without much success , in an attempt to favor selection of West Nile virus hMAbs specific for domain III of the envelope glycoprotein [57] . The anti-E2 specific F5 nIgG had a 70% PRNT endpoint of 10 ng/ml , equivalent to that described for the most effective neutralizing anti-VEEV E2 mMAbs ( Table 1 ) [33] , [34] . Poorer neutralization titers for human or chimpanzee Fabs or MAbs specific for YFV , DENV4 or HAV have been reported: 0 . 1–3 µg/ml , 0 . 2–0 . 6 µg/ml , and 0 . 5 µg/ml , respectively [58] , [61] , [62] . The E1-specific hFab L1A7 had a PRNT endpoint of 3 µg/ml , 300-fold lower than F5 . The titer might be higher for a complete IgG antibody , but typically neutralization titers for anti-E1 mMAbs are less than anti-E2 mMAbs [34] . A high degree of cross-reactivity for the various VEEV subtypes and varieties was found for the E2-specific hMAbs and hFabs compared to the spectrum of type-specific to subgroup-reactive reactivities shown by the well-characterized mMAbs ( Table 1 ) [33] , [34] , [67] . In fact , no VEEV type-specific hMAbs were isolated . The methodology for generating the mMAbs was different from that used in this study , but in all studies screening was done on plate-bound , purified virus and clones were selected that had the highest level of binding by ELISA . The virus used for panning in this study was inactivated with either 0 . 3% or 0 . 05% BPL , while live virus was used in ELISAs to select mMAbs . However , the BPL-treated virus was reactive with neutralizing mMAbs in ELISA and it was assumed that neutralizing hMAbs would also bind this antigen . HMAb F5 nIgG was originally selected using 0 . 3% BPL-treated virus , but it was later discovered that its binding to live virus was 50–75% greater ( Table S2 ) ; therefore , the amount of BPL used was decreased to 0 . 05% , which improved F5 binding ( data not shown ) . The fact that the binding of mMAbs was not affected by treating virus with 0 . 3% BPL , but binding of hMAb F5 was affected , suggests that epitopes recognized by the VEEV neutralizing mMAbs and hMAb F5 may not be the same . The ELISA binding affinity of the three human IgG antibodies , F5 , H6 , and G1 , for VEEV TC-83 was equivalent to that of mMAb 3B4C-4 ( Figure S4 ) . Both F5 nIgG and 3B4C-4 are potent neutralizing MAbs while neither H6 eIgG nor G1eIgG have biological activity , so in this case high affinity was not necessarily correlated with neutralization capacity . CBA analysis indicated that the hE2c epitope defined by F5 nIgG does not spatially overlap any of the other epitopes defined by the panel of hFabs ( Table 3 ) . The cross-reactivity profile of this hMAb was also unique ( Table 1 , Figure 1 ) . CBA results comparing F5 and a panel of mMAbs important in defining a major VEEV E2 neutralization domain suggested that epitopes mE2d and mE2f were spatially near epitope hE2c based on reciprocal competition patterns ( Table 4 ) . The mE2f epitope has been mapped to residue E2-183 , but mE2d has not yet been mapped [36] . However , in the original description of this neutralization domain defined by mMAbs , there was no direct competition between mE2d and mE2f [33] . Further analysis revealed that F5 neutralized all four mMAb neutralization-escape variant viruses to the same degree as the parent VEEV TC-83 , indicating that binding of F5 was not affected by an aa change at either E2-182 , -183 , -199 or -207 , providing important evidence that F5 recognized a different E2 epitope than any of the four neutralizing mMAbs used to generate the variant viruses ( Table 5 ) . We isolated two neutralization-escape variant viruses of F5 nIgG , vF5-3 and vF5-5 , and sequenced their structural protein genes to locate the theoretical binding site of this hMAb . Based on the aa changes in the variant viruses , F5 binding was mapped to aa residues E2-115 to 119 ( Table 7 ) . The aa deletions and substitution in vF5-5 and vF5-3 viruses alter the net charge or degree of hydrophilicity in this E2 region , possibly affecting the accessibility of this epitope for antibody binding . Variant virus vF5-5 was more resistant than vF5-3 to neutralization with F5 , although both variant viruses required significantly more MAb for neutralization than required for VEEV TC-83 ( Table 6 ) . We also tested whether or not the humanized mMAb Hy4 IgG , specific for the mE2c epitope , could neutralize these two variant viruses . If the binding sites for F5 and Hy4 are different , it would be expected that Hy4 would neutralize both F5 variant viruses . However , only vF5-3 was neutralized , and vF5-5 was as resistant to neutralization by Hy4 as it was to F5 . This rather puzzling result , in addition to the reciprocal competition between F5 and the anti-E2f mMAb , might suggest some type of interaction or induced conformational change between the neutralization domains located at E2 aa182–207 and E2 aa115–119 . Of course the possibility cannot be excluded that the detected mutations are not the contact residues for F5 , but that these amino acid substitutions or deletions induce distant conformational changes that affect MAb binding . The identification of a novel neutralization domain on the VEEV E2 glycoprotein is analogous to the identification of a second neutralization domain on SV , identified using anti-E2c MAbs R6 and R13 neutralization-escape variant viruses that contained a coding change at either E2 aa62 , 96 , or 159 [68] . It was proposed that these E2 residues that formed an alternative neutralization site could be folded to form a binding site with the surface dimensions of approximately 600–750 Å , measurements similar to those determined for the interaction of lysozyme–anti-lysozyme immune complexes [69] . Transposon-insertion mutagenesis of SV resulted in a virus with an insertion at E2-119 that was less efficiently neutralized by SV mMAbs 202 ( anti-E2ab ) and 209 ( anti-E2c ) [70] . Similarly , a variant of RRV , attenuated in mice , had five E2 aa differences compared to wild-type at positions 3 , 67 , 119 , 251 , and 302 [39] . Residue 251 lies in the major neutralization domain , whereas residues 67 and 119 were proposed to influence neutralization efficiency in the variant virus . Examination of VEEV E2 mutations that affect virus binding to heparan sulfate led to a proposal that E2 residues 76 and 116 may form a conformational , surface-accessible epitope , but its involvement with virus neutralization is unknown [71] . Although the crystal structure of the alphavirus E2 glycoprotein has not been solved , cryoEM reconstructions of E2 have been reported [25] , [30] , [72] . The 9Å resolution cryoEM map of the SV E2 presented by Mukhopadhyay et al . [72] was annotated with markers representing locations of glycosylation sites , the protein N-terminus , and a neutralizing Fab binding site . We have adapted their figure to show the probable surface-accessible location of the hMAb F5 nIgG binding site ( E2 aa115–119 ) and its relationship with other markers ( Figure 3A , B ) . Mapping of this epitope to a unique E2 neutralization site was based on the data presented in this study: ( 1 ) epitope binding by hMAb F5 nIgG was more sensitive to 0 . 3% BPL treatment than epitopes recognized by neutralizing mMAbs , ( 2 ) hMAb F5 was able to neutralize all anti-VEEV mMAb neutralization escape variant viruses and therefore did not bind to E2 residues 182–207 , defined as the “critical” neutralization domain , and ( 3 ) hMAb F5 neutralization escape variant viruses vF5-3 and vF5-5 defined a neutralization epitope involving E2 aa115–119 . Results from studies in mice using VEEV E2 synthetic peptides as vaccines have been included in the proposed map of the E2 ectodomain to complement the placement of the hE2c epitope ( Figure 3B ) . Previously , we identified two peptide vaccines , VE2pep01 ( E2 aa1–25 ) and VE2pep13 ( E2 aa241–265 ) that protected mice from virulent VEEV challenge [73]–[75] . We also isolated an anti-peptide MAb , 1A2B-10 , specific for E2 aa1–19 , which passively protected mice challenged with VEEV varieties 1AB , 1C , and 1D [76] . None of the anti-peptide antibodies , either polyclonal or monoclonal , had virus-neutralizing activity , indicating that their cognate peptides were not likely to be surface-accessible or lacked the appropriate conformation . The proposed configuration of the E2 molecule shown in Fig . 3B places the hE2c epitope ( E2 aa115–119 ) on the surface of the spike above the more cryptic locations of the E2 N-terminus ( VE2pep01 ) and aa 241–265 ( VE2pep13 ) . Such an arrangement would be in agreement with the current knowledge of the structure of the E2 glycoprotein , the location of specific markers , and functional attributes of specified epitopes . We are now in collaboration to obtain structural data on Fab-virion complexes to determine actual binding sites of F5 nIgG and other human and murine MAbs . The VEEV neutralizing ability of the hMAb F5 nIgG is similar to that exhibited by the humanized mMAb Hy4 IgG . When administered prophylactically , as little as 100 ng of Hy4 was able to protect 90% of mice challenged intraperitoneally with virulent VEEV [43] . In addition , Hy4 given one or 24 h after VEEV infection cured 90% or 75% of infected mice , respectively . F5 nIgG would be expected to be as effective an immunotherapeutic as Hy4 IgG . Administration of a cocktail of the two MAbs , which bind to different epitopes , could provide increased protection against generating virulent VEEV neutralization-escape variants in vivo .
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Although the murine immune response to Venezuelan equine encephalitis virus ( VEEV ) is well-characterized , little is known about the human antibody response to VEEV . In this study we used phage display technology to isolate a panel of 11 VEEV-specfic Fabs from two human donors . Seven E2-specific and four E1-specific Fabs were identified and mapped to five E2 epitopes and three E1 epitopes . Two neutralizing Fabs were isolated , E2-specific F5 and E1-specific L1A7 , although the neutralizing capacity of L1A7 was 300-fold lower than F5 . F5 Fab was expressed as a complete IgG1 molecule , F5 native ( n ) IgG . Neutralization-escape VEEV variants for F5 nIgG were isolated and their structural genes were sequenced to determine the theoretical binding site of F5 . Based on this sequence analysis as well as the ability of F5 to neutralize four neutralization-escape variants of anti-VEEV murine monoclonal antibodies ( mapped to E2 amino acids 182–207 ) , a unique neutralization domain on E2 was identified and mapped to E2 amino acids 115–119 .
|
[
"Abstract",
"Introduction",
"Methods",
"Results",
"Discussion"
] |
[
"microbiology/immunity",
"to",
"infections",
"neurological",
"disorders/infectious",
"diseases",
"of",
"the",
"nervous",
"system",
"immunology/immune",
"response",
"virology/emerging",
"viral",
"diseases",
"immunology/immunity",
"to",
"infections",
"virology/host",
"antiviral",
"responses"
] |
2010
|
The First Human Epitope Map of the Alphaviral E1 and E2 Proteins Reveals a New E2 Epitope with Significant Virus Neutralizing Activity
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Components of bacteria have been shown to induce innate antiviral immunity via Toll-like receptors ( TLRs ) . We have recently shown that FimH , the adhesin portion of type 1 fimbria , can induce the innate immune system via TLR4 . Here we report that FimH induces potent in vitro and in vivo innate antimicrobial responses . FimH induced an innate antiviral state in murine macrophage and primary MEFs which was correlated with IFN-β production . Moreover , FimH induced the innate antiviral responses in cells from wild type , but not from MyD88−/− , Trif−/− , IFN−α/βR−/− or IRF3−/− mice . Vaginal delivery of FimH , but not LPS , completely protected wild type , but not MyD88−/− , IFN-α/βR−/− , IRF3−/− or TLR4−/− mice from subsequent genital HSV-2 challenge . The FimH-induced innate antiviral immunity correlated with the production of IFN-β , but not IFN-α or IFN-γ . To examine whether FimH plays a role in innate immune induction in the context of a natural infection , the innate immune responses to wild type uropathogenic E . coli ( UPEC ) and a FimH null mutant were examined in the urinary tract of C57Bl/6 ( B6 ) mice and TLR4-deficient mice . While UPEC expressing FimH induced a robust polymorphonuclear response in B6 , but not TLR4−/− mice , mutant bacteria lacking FimH did not . In addition , the presence of TLR4 was essential for innate control of and protection against UPEC . Our results demonstrate that FimH is a potent inducer of innate antimicrobial responses and signals differently , from that of LPS , via TLR4 at mucosal surfaces . Our studies suggest that FimH can potentially be used as an innate microbicide against mucosal pathogens .
The innate immune system plays a crucial role in the early defence against microbial infections [1] , [2] , [3] , [4] , [5] , [6] . A key aspect of the innate immune response is the synthesis and secretion of type I interferons ( IFN ) such as IFN-α and IFN-β . The innate immune system detects infections through germ-line encoded pattern recognition receptors [7] , such as Toll-like receptors ( TLRs ) . TLRs recognize conserved structures present in large groups of microorganisms , but not found in the host , called pathogen-associated molecular patterns ( PAMPs ) [8] , [9] , [10] , [11] , [12] . Thus far , 10 TLRs have been identified in mice and humans [13] , [14] , [15] , [16] , with each receptor recognizing a unique set of PAMPs [17] , [18] . Examples of PAMPs include lipopolysaccharide ( LPS , a ligand for TLR4 ) , flagellin ( a ligand for TLR5 ) , double-stranded RNA ( dsRNA , a ligand for TLR3 ) , bacterial CpG DNA ( a ligand for TLR9 ) and profillin ( a ligand for TLR11 ) . Upon ligand binding , TLRs initiate intracellular signalling through their cytoplasmic Toll/IL-1 ( TIR ) domain . These signalling pathways can be divided into common ( MyD88-dependent ) and specific ( MyD88-independent ) categories . TLR2 , 5 , 7–9 and 11 signalling is mainly MyD88-dependent , while TLR3 and 4 signalling is mediated through either MyD88 or Trif . Recently , we and others have reported that CpG ODN/TLR9 signalling leads to the induction of potent innate protection against herpes simplex virus ( HSV-2 ) infection both in vivo and in vitro [3] , [19] , [20] , [21] , [22] , [23] . Local intravaginal ( IVAG ) delivery of CpG ODN or Poly I:C resulted in rapid proliferation and thickening of the vaginal epithelium and induction of a innate antiviral state that did not block virus entry but inhibited viral replication in vaginal epithelial cells . This TLR ligand-induced innate protection correlated with production of IFN-β , but not IFN-α , IFN-γ or TNF-α . Treatment of mice lacking the IFN-α/βR with CpG or Poly I:C did not provide innate antiviral protection against genital HSV-2 challenge compared to control mice . More recently , it has been shown that DC-derived IFNs are crucial for the innate antiviral activity of CpG in the genital tract [24] . Several PAMPs of bacterial origin including LPS , flagellin , peptidoglycan and bacterial DNA can activate the innate immune system via TLRs [18] . FimH , the adhesion portion of type 1 fimbriae produced by most Enterobacteriaceae including uropathogenic E . coli , is a conserved protein involved in bacterial attachment to mucosal epithelial cells [25] , [26] , [27] . Type I fimbriae have long been implicated in bacterial urinary tract infections in humans [25] , [28] , [29] , [30] , [31] , [32] , [33] and have been the focus of many attempts to generate a vaccine against pathogenic Gram-negative bacteria [26] , [29] , [34] , [35] , [36] . We have recently shown that recombinant FimH protein can activate the innate immune system through MyD88 and TLR4 in primary murine cells ( [37] and un-published data ) . Little is known about the antiviral or antibacterial activity of FimH . Here we report that FimH is a potent inducer of innate antimicrobial responses . Our in vitro and in vivo experiments clearly show that FimH-induced innate antiviral immunity is associated with IFN-β production and requires MyD88 , Trif , TLR4 , IRF-3 and type I IFN signalling .
We have previously reported that bacterial LPS and CpG DNA as well as Poly I:C can induce innate antiviral responses in RAW264 . 7 cells . More recently , we have shown that FimH can stimulate these cells and induce the production of TNF-α ( [37] and un-published data ) . Here we first examined if FimH-mediated signalling resulted in antiviral activity . RAW264 . 7 cells treated with FimH had significantly lower HSV-2 titers compared to cells treated with PBS ( Fig . 1A&B ) . This innate protection correlated with the production of IFN-β , but not IFN-α or IFN-γ ( Fig . 1C ) . It is well documented that FimH binds to alpha-D-mannosides [38] , [39] , [40] , [41] . We then examined if the mannose binding domain of FimH is involved in the signaling . Incubation of FimH with D-mannose had no effect on FimH-induced innate antiviral response ( Fig . 1D ) . Recently we have shown that FimH signalling required TLR4 and MyD88 pathway in murine macrophages [37] . It is well documented that Poly I:C induces strong antiviral responses in mouse embryonic fibroblasts ( MEFs ) as measured by a standard VSV plaque reduction assay . We first examined whether FimH could induce the production of type 1 IFNs , resulting in an innate antiviral state in B6 MEFs . Interestingly , FimH induced similar levels of IFN-β , but not IFN-α , in B6 MEFs compared to those treated with Poly I:C ( Fig . 2A ) and provided complete protection against VSV challenge ( Fig . 2B& 3 ) . B6 MEFs treated with FimH also showed little or no VSV-GFP replication , as detected by GFP fluorescence , when compared to untreated MEFs ( Fig . 3A ) . We then examined whether FimH-induced innate antiviral responses were MyD88 , Trif and/or type I IFN dependent . FimH failed to provide protection against VSV challenge in MEFs deficient in either the MyD88 or Trif adaptors , whereas Poly I:C provided complete protection in MEFs lacking MyD88 and partial protection in MEFs lacking Trif ( Fig . 2B , 3B , C ) . To further investigate whether type 1 IFNs , particularly IFN-β , were involved in FimH-induced innate antiviral immunity , MEFs from IFN-α/βR−/− or IRF-3−/− mice were treated with FimH or Poly I:C and then challenged with VSV . FimH failed to induce an innate antiviral state in the absence of either IRF-3 or type 1 IFN signalling ( Fig . 2B , 3D , E ) . Poly I:C induced only moderate protection at 30 nM or 15 nM , but no significant differences in VSV-GFP fluorescence was observed in MEFs at lower concentrations compared to untreated MEFs ( Fig . 2A , B , 3D , E ) . We have reported that the mucosal delivery of some TLR ligands/agonists can induce an innate antiviral state and provide complete protection against subsequent IVAG HSV-2 challenge [3] , [19] , [22] . To examine if local delivery of FimH can provide innate protection against subsequent IVAG HSV-2 challenge , FimH was administered intravaginally to mice and then mice were challenged with lethal doses of HSV-2 24 hours following this treatment . FimH provided 100% protection against IVAG HSV-2 challenge compared to control mice ( Fig . 4A ) . Moreover , HSV-2 virus particles were not present in the vaginal washes from FimH-treated mice compared to control mice ( Fig . 4B ) . To further verify that the innate antiviral protection in FimH-treated mice was due to the direct effects of FimH protein , but not LPS or other bacterial contaminants , we performed three experiments: 1 ) mice were treated with 5000 ng of LPS and then challenged with HSV-2; 2 ) mice were treated with protease-digested FimH ( complete digestion was confirmed by gel electrophoresis ) and then challenged with HSV-2; 3 ) mice were treated with either FimH or another component of bacterial pilin ( PapG ) , which were expressed , purified and prepared in the same manner . As shown in Figure 5A neither LPS nor digested FimH protected mice against subsequent challenge with IVAG HSV-2 . Mice treated with PapG were also not protected against IVAG HSV-2 challenge ( Fig . 5B ) . However , both FimH and PapG were prepared identically and the preparations had similar levels of LPS . Interestingly , FimH , but not LPS , induced dramatic morphological changes in the genital mucosa , including thickening of the vaginal epithelium and recruitment of polymorphonuclear cells ( PMNs ) ( Fig . 5C ) . Our in vitro observations show that FimH signalling requires TLR4 , MyD88 and type 1 IFN signalling to induce innate antiviral activity . Thus , we examined whether vaginal delivery of FimH could protect mice lacking these innate factors against genital HSV-2 infection . While FimH provided nearly complete protection in B6 mice , there was no protection against IVAG HSV-2 challenge in FimH-treated MyD88−/− mice ( Fig . 6A ) . We also examined if type I IFNs , particularly IFN-β , were involved in the FimH-induced innate antiviral immunity in vivo . Vaginal delivery of FimH and Poly I:C to IFN-α/βR−/− and IRF-3−/− mice failed to protect them against IVAG HSV-2 challenge compared to control mice ( Fig . 6A ) . This innate protection strongly correlated with the production of IFN-β , but not IFN-α , levels in the vaginal washes ( Fig . 6B ) . To ensure that the ELISA kit could detect naturally produced IFN-α , we used supernatants from BM-DCs treated with Poly I:C or CpG ODN and were able to detect high levels of mIFN-α ( Figure S1 ) . Finally , to confirm that FimH signals via TLR4 , B6 and TLR4−/− mice were treated with FimH and then challenged with IVAG HSV-2 . FimH failed to protect TLR4−/− mice but completely protected B6 mice against genital HSV-2 challenge ( Fig . 6C ) . FimH plays an important role in the pathogenicity of uropathogenic E . coli ( UPEC ) [26] . To examine whether FimH plays a role in innate immune induction in the context of a natural infection , we measured PMN leukocyte recruitment to the urinary tract in B6 mice and TLR4-deficient mice following infection with wild type UPEC and a fimH null mutant . In B6 mice , UPEC expressing FimH induced a rapid PMN response whereas mutant bacteria lacking FimH did not ( Fig . 7A ) . This FimH-induced PMN influx required TLR4 , since the cellular influx was blocked in TLR4-deficient mice ( Fig . 7B ) . The bacterial load was enumerated in the bladder 24 h after infection . TLR4 was required for control of infection in the bladder , as TLR4−/− mice had ∼1 . 5-log more wild type bacteria in the bladder at 24 h compared to B6 mice ( Fig . 7C ) , which correlated with a loss of PMN recruitment in the TLR4−/− mice . Deletion of fimH resulted in decreased colonization of the bladder but this decrease was not overcome in a TLR4−/− background , confirming that while FimH is important for UPEC colonization of the bladder [33] , FimH-independent signaling through TLR4 is not likely a major contributor to infection control in B6 mice .
We have demonstrated here that FimH can induce a potent innate antiviral state , both in vitro and in vivo . Pre-treatment of MEFs from B6 mice , but not MyD88−/− , Trif−/− , IRF-3−/− or IFN-α/βR−/− mice , with FimH conferred protective antiviral responses . Mucosal delivery of FimH , but not LPS , provided complete protection against IVAG HSV-2 challenge in B6 mice while it failed to provide any protection in MyD88−/− mice . Moreover , the FimH-induced innate antiviral immunity was associated with the induction of IFN-β in the genital tract and required TLR4 and IRF-3 . To evaluate the biological significance of FimH in host pathogen interaction , we have examined the host innate response in FimH knockout uropathogenic E . coli in the presence and absence of TLR4 . TLR4 was required for the induction of innate immune responses against UPEC . We have shown that FimH requires TLR4 and MyD88 to activate murine primary macrophages . In addition we have also reported that dsRNA and CpG ODN confer protection against HSV-2 , both in vitro and in vivo [3] , [19] , [22] . Similar to Poly I:C and CpG , the FimH-induced innate antiviral state correlates with IFN-β , but not IFN-α or IFN-γ production . Although we have observed high levels of TNF-α , it is unlikely that the FimH induced innate antiviral activity is mediated via TNF-α . Previous work showed that treatment of RAW264 . 7 cells with TNF-α cannot protect them against HSV-2 infection [42] . FimH also induces significant levels of NO production . Both IFN-β and NO are able to block HSV-2 replication [1] , [2] , [43] , [44] , [45] . We have observed induction of a strong innate antiviral state by FimH that correlated with the production of IFN-β , and required TLR4 . It was first important to establish whether , in addition to TLR4 , FimH binding to its natural receptor , mannose , is essential for induction of innate antiviral activity . It is well documented that FimH adhesin of uropathogenic E . coli type 1 fimbriae bind to mannose on epithelial cells . Blocking the mannose-binding portion of FimH with D-mannose had no effect on the FimH-induced innate antiviral activity . This suggested that FimH may bind to TLR4 independent of mannose to induce antiviral responses . We were unable to detect any IFN-α from FimH treated RAW264 . 7 or B6 MEFS by ELISA . This suggested that IFN-β is the key factor in the FimH-induced innate antiviral state . Given the importance of the transcription factor IRF3 in the production of IFN-β in fibroblast and epithelial cells , FimH also failed to induce IFN-β production from IRF-3−/− MEFs and did not protect these cells against VSV . Taken together , these data indicate that FimH signals through IRF3 in the induction of an innate antiviral response . We and others have shown that mucosal delivery of TLR ligands protect mice against subsequent IVAG HSV-2 challenge [3] , [19] , [20] , [21] , [22] , [46] . More recently , we have found that the TLR ligand-induced innate antiviral responses against IVAG HSV-2 strongly correlate with the production of IFN-β , but not IFN-α [47] . Our data show that FimH activity of FimH against genital HSV-2 challenge requires MyD88−/− , IRF-3−/− IFN-α/βR−/− and TLR4−/− mice did not provide any protection against subsequent IVAG HSV-2 challenge compared to B6 control . FimH also induced significantly lower levels of IFN-β in MyD88−/− mice while IFN-β was not detectable in IRF-3−/− mice compared to B6 control mice . This clearly suggested that FimH-induced innate antiviral activity against IVAG HSV-2 is mediated via TLR4 , MyD88 and type 1 IFNs , particularly IFN-β . Since we purified recombinant FimH from bacteria , it was essential to confirm that the antiviral activity seen with the purified FimH was not due to LPS contamination and/or other possible minor proteins . Our in vitro and in vivo data clearly showed that the antiviral activity of FimH was not due to contamination with LPS . We have used all possible controls to confirm that FimH was responsible for the innate antiviral responses . First , control samples from bacteria that contained empty vector and processed in exactly the same manner as FimH had no antiviral activity assuring that the antiviral response seen with FimH is not due to low levels of LPS contamination . Second , both enzymatic digestion and heat inactivation of FimH protein significantly abrogated the activity of FimH protein in vitro and in vivo . To also confirm that FimH , but not LPS , is responsible for in vivo innate antiviral responses , we performed several experiments . First; local delivery of LPS or digested/heat-inactivated FimH protein gave no protection against subsequent IVAG HSV-2 challenge in B6 mice compared to treatment with intact FimH protein . Second; local delivery of recombinant PapG protein , another adhesin of fimbriated bacteria which was prepared exactly with the same protocol as FimH , gave no protection against subsequent IVAG HSV-2 challenge in B6 mice compared to FimH . However , PapG protein had the same levels of LPS compared to FimH . In addition , our in vitro experiments clearly showed that low levels of LPS present in our samples cannot provide any protection against viral infections . In addition we have shown that FimH can directly bind TLR4 ( [37] and un-published data ) . Furthermore , while FimH induced dramatic changes in genital mucosa , there was no difference in the histomorphology of the genital mucosa from LPS- or PBS-treated mice . More importantly , our recent data indicates that FimH signals in cells unresponsive to LPS ( [37] and un-published data ) . It is well known that FimH play an import role in attachment of bacteria to epithelial cells and contributes to pathogenecity of UPEC . Our data show that TLR4 is involved in FimH signalling with epithelial cells . FimH-expressing UPEC were able to induce recruitment of PMNs to the urinary tract of wild type mice , while isogenic bacteria lacking FimH did not . Interestingly , this response is controlled by TLR4 expression and is abolished when we used FimH− UPEC , even in the presence of TLR4 . These data are similar to the PMN response seen following infection with a type I fimbriated derivative of non-adhesive E . coli [48] . Because these UPEC strains share expression of another TLR4-activating PAMP ( LPS ) , these data suggest that the dominant innate immune-activating PAMP on uropathogengic E . coli may in fact be FimH . In support of this , deletion of fimH resulted in decreased colonization of the bladder as reported previously [33] but the level of colonization by fimH− UPEC was similar in a B6 and TLR4−/− background . These data suggest that FimH-independent signaling through TLR4 is not likely a major contributor to infection control in B6 mice . This is the first report to show that FimH has potent innate antiviral activity which also requires TLR4 , MyD88 , Trif , IRF-3 and type 1 IFNs , particularly IFN-β . So far , TLR ligands such as dsRNA , ssRNA , and CpG DNA have been associated with the induction of innate antiviral immunity . Protein ligands of TLRs have not been associated with the induction of innate antiviral immunity . Here , however , we demonstrate that FimH , but not LPS , mediates innate antiviral activity at the genital mucosa . It is of particular interest that both TLR5 and TLR11 ligands signal via MyD88 , whereas FimH protein signals through both MyD88 and Trif , leading to activation of the IRF-3 pathway . Results from this study may provide the basis for a novel mucosal innate microbicide for a vast variety of mucosal viral infections such as HSV-2 , HIV-1 or other sexually transmitted infections .
Female C57BL/6 , 129SVPasCrl mice , 8–12 weeks old , were purchased from Charles River Laboratory ( Quebec , Canada ) . TLR4−/− mice were purchased from Jackson laboratory ( Bar Harbor , USA ) . Breeding pairs of IFNα/βR−/− were kindly provided by Rolf M . Zinkernagel ( Zürich , Switzerland ) . Breeding pairs of IRF-3−/− , MyD88−/− and Trif−/− mice were kindly provided by Dr . T . Taniguchi ( via Dr . T . Moran ) , Dr . S . Akira ( via Dr . D . Golenbock ) and Dr . B . Beutler , respectively . All mice were housed in level B rooms which followed a 12 hour day and 12 hour night schedule , and were maintained under standard temperature controlled conditions . RAW264 . 7 , HEL fibroblasts and BJ fibroblasts cells were purchased from ATCC . B6 , IRF-3−/− , MyD88−/− , Trif−/− and IFNα/βR−/− murine embryonic fibroblasts ( MEFs ) were prepared from gestation day 13 . 5 in α-MEM with 20% FBS and weaned then grown in 10% α-MEM for experiments . 293 , 293-hTLR4 and 293-hTLR4-CD14/MD2 cells were purchased from InvivoGen and maintained in 10% DMEM supplemented with 10ug/mL blasticidin ( 293-hTLR4 ) or 10ug/mL blasticidin and 50ug/mL HygroGold ( 293-hTLR4-CD14/MD2 ) . HSV-2 strain 333 was grown and titred as previously described [49] . VSV expressing GFP was kindly provided by Dr . Brian Lichty ( McMaster University , Hamilton , ON ) . GM-CSF was purchased from R&D . α-D-manosidase , LPS ( L26-54 ) and Poly I:C were purchased from Sigma ( Oakville , ON , Canada ) . Depo-Provera was purchased from Upjohn ( Don Mills , ON , Canada ) . The fimH gene from avian pathogenic E . coli strain EC99 ( O78 ) was cloned into pQE-30 and expressed in BL-21 competent E . coli . FimH expression and purification were performed as previously described [50] . Briefly , Protein expression was induced by adding 1M IPTG to a final concentration of 1 mM and induction continued for a period of 5 hours . Bacterial pellets were lysed and protein isolation continued under denaturing conditions utilizing Ni-NTA affinity chromatography . Isolated protein fractions were then dialyzed in a 10-kDa Slidlyzer dialysis cassette against PBS . The LPS contraction in the purified FimH protein was determined using Limulus Amebocyte Lysate LPS detection kit according to the manufacturer's protocol . RAW264 . 7 cells were treated with FimH ( 10 µg/ml ) , Poly I:C ( 10 µg/ml ) or left un-treated . Twenty-four hours post treatment the supernatants were collected and stored at -20°C for further study . The cells were then infected with HSV-2 , MOI of 0 . 1 . Twenty to twenty-two hours post infection the cells and supernatants were collected for HSV-2 titration on Vero cells . Passage 3 MEFs from B6 , IRF-3−/− , MyD88−/− , Trif−/− and IFNα/βR−/− mice were split into 12-well plates and then treated with various concentrations of FimH , Poly I:C or LPS or left un-treated . Twenty-four hours post treatment , MEFs were infected with VSV-GFP . Levels of GFP fluorescence were visualized and quantified using a Typhoon™ scanner ( GE Healthcare ) 24 hours post-infection . B6 , TLR4−/− , IRF-3−/− , MyD88−/− and IFNα/βR−/− mice , 6–8 weeks old , were subcutaneously ( sc ) injected with 2 mg of progesterone/mouse ( Depo-Provera ) . Four days later the mice were anaesthetized and treated vaginally with FimH ( 40 µg/mouse ) or Poly I:C ( 100 µg/mouse ) . Twenty-four hours after treatment the mice were anesthetised , placed on their backs , and infected IVAG with a lethal dose of HSV-2 in 10 µl of PBS for at least 45 min while being maintained under anaesthesia . Vaginal washes were collected daily after infection ( days 1–3 ) by pipetting 2×30 µL of PBS into and out of the vagina 6–8 times . Viral titers in IVAG washes were determined by plaque assay on monolayers of Vero cells as previously described [49] . Treated mice were also monitored daily for genital pathology and survival for up to 4 weeks . Pathology was scored on a five point scale . Zero indicated no infection; 1 , slight redness of external vagina; 2 , swelling and redness of external vagina; 3 , severe swelling of external vagina and hair loss in the surrounding area; 4 , ulceration of vaginal tissue , redness and swelling; 5 , continued ulceration , redness , swelling and sometimes paralysis in back legs , at which point the mice were euthanized . To study the effects of FimH or LPS on vaginal tissue morphology , progesterone-treated mice received FimH ( 40 µg/mouse ) or LPS ( 5 µg/mouse ) . After 24 h , vaginal tissue was removed , fixed in 4% paraformaldehyde , embedded in paraffin , and sectioned at 5 µm for hematoxylin and eosin staining . IFN-α , IFN-β , IFN-γ and IL-8 ELISAs were conducted using Quantikine Murine Kits from R&D Systems ( Minneapolis , MN , USA ) according to the manufacturer's instructions . IFN-α and IFN-β ELISAs were conducted using PBL Biomedical kits from PBL ( Piscataway , NJ , USA ) . The IFN-α ELISA kit detects mouse IFN-αA , IFN-α1 , IFN-α4 , IFN-α5 , IFN-α6 , and IFN-α9 , with a detection limit of 10 pg/ml . A human cystitis isolate of uropathogenic Escherichia coli was used for experimental urinary tract infection of mice . E . coli NU14-1 , which does not express FimH due to a disruption of the fimH gene , and E . coli NU14 , which is the isogenic wild type parent strain , were kindly provided by Dr . Scott Hultgren ( Washington University , St . Louis , MO ) . E . coli were cultured in LB broth with streptomycin at 50 µg ml . For mouse infection studies , bacteria were grown overnight in LB broth , washed in 0 . 85% saline , and resuspended in saline to a concentration of ∼109 colony forming units ( cfu ) per ml . B6 mice and TLR4−/− were infected with 0 . 1 ml ( 108 cfu ) of bacterial suspension . A soft catheter ( 0 . 7 mm ) placed in the urethra of anaesthetized mice and the bacterial were delivered into balder . Urine was collected 0 , 2 , 6 and 24 hours post-infection and polymorphonuclear leukocytes were quantified using a haemocytometer . Twenty-four hours after infection , the bladders were removed , homogenized and the bacterial load was enumerated . Statistical differences among the viral titers were determined by analysis of variance followed by Tukey's test . The statistical significances of the survival rates and the percentage of GFP expressing cells were determined by the χ2 test . A P value of <0 . 05 was considered statistically significant . An unpaired t test was used to determine significant differences in cytokine production .
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The innate immune system is an evolutionarily conserved defence mechanism that protects the host from infection by microbes such as viruses , bacteria and fungi . Incoming pathogens are recognized by a set of evolutionary conserved receptors , including the Toll-like receptors ( TLRs ) , that can be found on the surface of epithelial cells at the mucosal surface . We recently found that FimH , a specific adhesin located at the tip of type 1 fimbriae in uropathogenic E . coli , binds directly to TLR4 . Here , we demonstrate the biological significance of this interaction . In the context of a natural infection , recognition of FimH by TLR4 is important for the host to mount an innate immune response against uropathogenic E . coli . Furthermore , we show that purified FimH protein induces a potent innate antiviral response , both in tissue culture and in animal models . This response is mediated predominantly by the production of type I interferon . Our results suggest that FimH is an excellent candidate for development as a microbicide against pathogen infection .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
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"microbiology/immunity",
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"infections",
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"microbiology/innate",
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2008
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FimH Adhesin of Type 1 Fimbriae Is a Potent Inducer of Innate Antimicrobial Responses Which Requires TLR4 and Type 1 Interferon Signalling
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Nuclear hormone receptors ( NHRs ) are ligand-gated transcription factors that control adaptive host responses following recognition of specific endogenous or exogenous ligands . Although NHRs have expanded dramatically in C . elegans compared to other metazoans , the biological function of only a few of these genes has been characterized in detail . Here , we demonstrate that an NHR can activate an anti-pathogen transcriptional program . Using genetic epistasis experiments , transcriptome profiling analyses and chromatin immunoprecipitation-sequencing , we show that , in the presence of an immunostimulatory small molecule , NHR-86 binds to the promoters of immune effectors to activate their transcription . NHR-86 is not required for resistance to the bacterial pathogen Pseudomonas aeruginosa at baseline , but activation of NHR-86 by this compound drives a transcriptional program that provides protection against this pathogen . Interestingly , NHR-86 targets immune effectors whose basal regulation requires the canonical p38 MAPK PMK-1 immune pathway . However , NHR-86 functions independently of PMK-1 and modulates the transcription of these infection response genes directly . These findings characterize a new transcriptional regulator in C . elegans that can induce a protective host response towards a bacterial pathogen .
Nuclear hormone receptors ( NHRs ) are transcription factors that regulate a number of key biological processes following recognition of specific exogenous or endogenous ligands . Interestingly , the genomes of Caenorhabditis species contain a large number of NHRs compared to other metazoans [1] . 284 NHRs are present in C . elegans , whereas Drosophila and humans have only 21 and 48 , respectively [2] . The marked expansion of NHRs suggests that these proteins play particularly important roles in nematode physiology [2 , 3]; however , only a very small minority of C . elegans NHRs have been characterized in detail [2] . Like other metazoans , C . elegans rely on inducible host defense mechanisms during infection with bacterial pathogens [4–7] . The mechanisms that engage these immune defenses are not completely understood . Considering their roles as intracellular sensors of specific ligands , we hypothesized that NHRs function in innate immune activation in C . elegans . However , forward genetic screens did not previously identify an NHR that is necessary for pathogen resistance [8 , 9] . We , therefore , designed a genetic screen to determine if an NHR could activate protective immune defenses in C . elegans . Utilizing a potent immunostimulatory small molecule as a chemical probe , we identified NHR-86 and showed that it drives a transcriptional response that protects C . elegans from infection with the bacterial pathogen Pseudomonas aeruginosa . NHR-86 is a homolog of mammalian hepatocyte nuclear factor 4 ( HNF4 ) , an NHR that has been implicated in the pathogenesis of inflammatory bowel disease [10–13] . We show that , in the presence of an immunostimulatory small molecule , NHR-86 induces innate immune defenses by binding to the promoters of immune effectors , in a manner that does not require the canonical p38 MAPK PMK-1 pathway . In this context , PMK-1 sets the basal expression of innate immune response genes , but is dispensable for their induction by NHR-86 . These data demonstrate a new mechanism by which immune defenses are engaged to protect the worm and raise the possibility that the expansion of the NHR family in C . elegans may have been fueled , at least in part , by the roles of these proteins in the activation of host defense responses .
To determine if an NHR can induce protective immune responses , 258 of the 284 NHR genes in the C . elegans genome were screened by RNAi [14] using the C . elegans Pirg-4 ( F08G5 . 6 ) ::GFP transcriptional immune reporter and the immunostimulatory xenobiotic R24 . R24 ( also referred to as RPW-24 ) was originally identified in a screen of 37 , 214 small molecules for new anti-infective compounds [15] . This molecule robustly activates innate immune defenses and protects nematodes infected with bacterial pathogens [7 , 16–18] . For this screen , the Pirg-4::GFP transcriptional reporter was chosen as a convenient readout of immune activation . IRG-4 ( infection response gene-4 ) contains a CUB-like domain , a group of secreted proteins that are postulated to play a role in host defense [19] . Basal levels of irg-4 transcription are controlled by the p38 MAPK PMK-1 pathway [19] . This gene is induced during infection by multiple bacterial pathogens , including P . aeruginosa [19–23] , and by the small molecule R24 [16–18] . RNAi-mediated knockdown of ten NHRs partially affected the R24-mediated induction of Pirg-4::GFP by R24 ( S1 Table ) , but only one NHR ( nhr-86 ) completely abrogated the upregulation of this immune reporter ( Fig 1A ) . We confirmed the results of the nhr-86 ( RNAi ) experiment using several approaches . The previously characterized null allele nhr-86 ( tm2590 ) [3] , which contains a 172 bp deletion that removes 33 bp in exon 4 of nhr-86 , suppressed Pirg-4::GFP induction by R24 ( Fig 1A and 1C ) . CRISPR-Cas9 was used to generate a clean deletion of nhr-86 [nhr-86 ( ums12 ) ] ( Fig 1B ) . ums12 is a 5 . 5 kb deletion that removes nearly all of the nhr-86 coding region , which caused a marked reduction in the nhr-86 transcript ( S1A Fig ) . The nhr-86 ( ums12 ) mutation fully suppressed the induction of Pirg-4::GFP by R24 ( Fig 1A and 1C ) . In addition to irg-4 , nhr-86 is required for the R24-dependent transcriptional upregulation of two additional immune effectors that contain CUB-like domains , irg-5 ( F35E12 . 5 ) and irg-6 ( C32H11 . 1 ) ( Figs 1 and S1B ) . Like irg-4 , irg-5 and irg-6 are induced by several different bacterial pathogens , require the p38 MAPK PMK-1 pathway for their basal transcriptional levels , and are induced in accordance with the virulence potential of the pathogen [17 , 19–24] . R24-mediated induction of the Pirg-5::GFP transgene was abrogated by nhr-86 ( RNAi ) and in the nhr-86 ( tm2590 ) background ( Fig 1A ) . In addition , qRT-PCR of irg-5 and irg-6 showed that nhr-86 loss-of-function mutations suppress induction by R24 ( Figs 1C and S1B ) . Interestingly , RNAi-mediated knockdown of irg-4 renders worms hypersusceptible to killing by P . aeruginosa [25 , 26] . Importantly , irg-4 knockdown does not shorten the lifespan of nematodes growing on E . coli OP50 , the normal laboratory food source , nor does its knockdown cause susceptibility to other stressors [25 , 26] . We confirmed these observations and also found that irg-5 ( RNAi ) and irg-6 ( RNAi ) animals are more susceptible to killing by P . aeruginosa ( S1C Fig ) . As with irg-4 ( RNAi ) , knockdown of irg-5 or irg-6 did not shorten the lifespan of C . elegans growing on E . coli OP50 ( S1D Fig ) . Thus , nhr-86 drives the induction of at least three innate immune effectors that confer resistance to P . aeruginosa infection . To define the genes that are dependent on nhr-86 for their transcription , we performed mRNA-sequencing . We compared the mRNA expression profiles of wild-type animals and two different nhr-86 loss-of-function alleles ( tm2590 and ums12 ) , each exposed to the immunostimulatory molecule R24 or mock treatment . Exposure to R24 caused the induction of 391 genes , which ( as in previous studies ) were enriched for innate immune response and xenobiotic detoxification genes [16–18] . The upregulation of 147 of these genes in the nhr-86 ( tm2590 ) mutants and 205 genes in the nhr-86 ( ums12 ) mutants were significantly attenuated ( Fig 2A ) . Importantly , the mRNA expression patterns of both nhr-86 loss-of-function mutants were tightly correlated ( Fig 2B ) with 142 misregulated genes in common between these two datasets ( S2 Table ) . Analysis of these 142 nhr-86-dependent genes revealed a significant enrichment of innate immune genes and those involved in the defense response to bacterial pathogens ( Fig 2A and 2C ) . Included among these nhr-86-dependent genes are the representative immune effectors irg-4 , irg-5 , irg-6 , mul-1 ( F49F1 . 6 ) and drd-50 ( F49F1 . 1 ) ( Fig 2A ) . mul-1 and drd-50 are induced during infection with multiple bacterial pathogens , including P . aeruginosa [17 , 19–24] . To confirm the results of our mRNA-seq data , we used a NanoString codeset to examine the expression of 118 innate immune and stress response genes in biological replicate RNA samples from wild-type and nhr-86 ( tm2590 ) animals ( Fig 2D ) . From the NanoString codeset , we identified 28 genes induced by R24 , 23 of which were pathogen-response genes . Of the 23 pathogen-response genes , we identified 22 that are dependent on nhr-86 for their induction . The NanoString experiment also confirmed the observation in the mRNA-seq experiment that nhr-86 is not required for the induction of all R24-induced genes ( Fig 2A and 2D ) . Interestingly , many of these genes that are upregulated by R24 in a manner independent of nhr-86 are cytochrome P450s , which are involved in the detoxification of xenobiotics ( Fig 2D and S2 Table ) . Thus , nhr-86 is required for the upregulation of only a specific subset of the R24-induced genes , a group that is strongly enriched for innate immune effectors ( Fig 2C ) . Interestingly , examination of the mRNA-seq profiles of C . elegans that were not exposed to compound ( i . e . , normal growth conditions or basal expression ) revealed that the expression of 302 genes were significantly lower in the nhr-86 loss-of-function mutants compared to wild-type animals ( >2-fold change , PPEE<0 . 05 ) and only 11 of these genes were differentially regulated more than 4-fold ( PPEE<0 . 05 ) . Only 6 of these genes were among the 142 genes that required nhr-86 for their induction by R24 . Comparison of the basal expression of irg-4 , irg-5 and irg-6 in the two nhr-86 loss-of-function alleles with wild-type animals by qRT-PCR confirmed this observation ( Fig 1C and S1B Fig ) . Thus , while nhr-86 is necessary for the transcriptional induction of genes and innate immune effectors in particular , it is largely dispensable for their basal regulation . To determine the direct targets of NHR-86 during R24 exposure , we performed chromatin immunoprecipitation-sequencing ( ChIP-seq ) . Of the 142 genes that are induced by R24 in an nhr-86-dependent manner , NHR-86 bound to the promoters of 32 of these genes following treatment with R24 compared to control ( Fig 3A and S3 Table ) . All but one of these 32 genes are induced during infection with at least one bacterial pathogen , including 14 genes that are upregulated during infection with P . aeruginosa ( S3 Table ) . Among the immune effectors whose transcription is directly regulated by NHR-86 are irg-4 ( Fig 3B ) , irg-5 ( Fig 3C ) , mul-1 ( Fig 3D ) , drd-50 ( Fig 3E ) and irg-6 ( S3 Table ) . The ChIP-seq experiment was performed with a strain containing a GFP-tagged NHR-86 protein ( NHR-86::GFP ) that has been previously characterized [3] . The induction of irg-4 by R24 was restored in nhr-86 ( tm2590 ) mutants , which contained this NHR-86::GFP construct ( S2A Fig ) . ChIP followed by qPCR ( ChIP-qPCR ) was used to confirm that NHR-86 binds to the promoters of innate immune effectors following R24 treatment . Promoter regions associated with irg-4 ( Fig 3B ) , irg-5 ( Fig 3C ) , mul-1 ( Fig 3D ) and drd-50 ( Fig 3E ) were significantly enriched following R24 treatment , but not in samples exposed to the solvent control . In addition , these promoter regions were not enriched in either control or R24-exposed wild-type animals , which do not express NHR-86::GFP that was used to immunoprecipitate promoter fragments . Binding of NHR-86 to the promoters of immune response genes upon R24 treatment was associated with a corresponding increase in mRNA transcript levels of these genes , which was entirely abrogated in both nhr-86 loss-of-function mutants ( Fig 3B–3E ) . Importantly , a control region within the irg-5 promoter ( Fig 3C ) and a random intergenic region on chromosome VI ( Fig 3F ) were not enriched in the ChIP-qPCR or ChIP-seq experiments . In addition , 110 genes were induced by R24 in an nhr-86-dependent manner , but NHR-86 did not bind to their promoters . Of note , NHR-86 is expressed in the nuclei of C . elegans intestinal epithelial cells [3] and promotes the induction of the innate immune effectors irg-4::GFP and irg-5::GFP in the intestine ( Fig 1A ) , the tissue that directly interfaces with ingested pathogens . A motif analysis was performed on the promoters bound by NHR-86::GFP to identify putative regulatory sequences . A single 15 bp sequence was strongly enriched in these promoters ( E-value: 1 . 7e-003 , S2C Fig ) . 15 of the 32 genes whose transcription were directly regulated by NHR-86 in the presence of R24 contain this 15 bp element in their promoters , including irg-4 , irg-5 and mul-1 ( S3 Table ) . However , only 3 of 172 genes that are induced by R24 independent of NHR-86 contain this 15 bp element . These data suggest that this 15 bp sequence may be a potential binding site for NHR-86 . Together , the mRNA-seq and ChIP-seq data demonstrate that , in the presence of an immunostimulatory molecule , NHR-86 engages the promoters of innate immune effector genes to drive their transcription . Under normal growth conditions , nhr-86 does not bind to the promoters of immune effectors ( e . g . , irg-4 , irg-5 , mul-1 and drd-50 ) and does not affect their basal expression . These data are the first demonstration of direct immune effector regulation by a nuclear hormone receptor in C . elegans . To determine if nhr-86 induces a physiologically-relevant transcriptional response , we compared the susceptibility of the nhr-86 loss-of-function mutants to P . aeruginosa infection following exposure to R24 . R24 protects wild-type C . elegans during P . aeruginosa infection [16–18] . Consistent with the key role of nhr-86 in driving the induction of innate immune defenses , nhr-86 loss-of-function mutants ( tm2590 and ums12 ) significantly suppressed the pathogen-resistance phenotype of R24-exposed wild-type worms ( Fig 4A ) . Together , these data demonstrate that the defense response induced by nhr-86 promotes host resistance to bacterial infection . An alternate method of examining the physiological relevance of immune effector induction in C . elegans involves studying the effect of induced transcriptional responses on stress in the endoplasmic reticulum ( ER ) . The induction of host immune effectors in C . elegans requires compensatory activation of the unfolded protein response ( UPR ) in the ER , presumably to handle the increase in proteins trafficking through this organelle [27 , 28] . Accordingly , R24 exposure caused the induction of Phsp-4::GFP , a transcriptional reporter for the BiP/GRP78 homolog in C . elegans , which indicates UPR activation ( Fig 4B ) . hsp-4 transcription is regulated by the transcription factor XBP-1 , which is activated by the ER-transmembrane protein IRE-1 when unfolded proteins accumulate in the ER . IRE-1 has RNase activity , which upon activation , cleaves xbp-1 mRNA to change its reading frame and encode the active XBP-1 protein [29] . We found that exposure to R24 increased the active , spliced form of xbp-1 ( Fig 4C ) . Total xbp-1 mRNA was also increased following R24 treatment ( Fig 4C ) . Interestingly , knockdown of nhr-86 suppressed Phsp-4::GFP induction ( Fig 4B ) and the accumulation of active xbp-1 ( Fig 4C ) following exposure to the xenobiotic R24 . In addition , animals deficient in nsy-1 , the MAPKKK upstream of the p38 MAPK pmk-1 ( Fig 4B ) , and pmk-1 ( S3A Fig ) , failed to induce the Phsp-4::GFP following exposure to R24 . pmk-1 ( km25 ) mutants abrogated the cleaving of xbp-1 into its active form ( Fig 4C ) . Thus , R24-mediated immune induction activates the UPR , in a manner dependent on nhr-86 and the p38 MAP pmk-1 pathway . We considered the possibility that R24 is a direct poison of the ER . However , tunicamycin , a potent inducer of ER stress and the UPR , did not activate the immune reporter Pirg-4::GFP ( S3B Fig ) . In addition , RNAi-mediated knockdown of nhr-86 did not suppress Phsp-4::GFP induction by tunicamycin ( S3C Fig ) . Thus , ER stress itself does not lead to the induction of nhr-86-dependent innate immune responses , but rather occurs as a consequence of mobilizing this protective host response . These data are consistent with prior reports , which demonstrate that activation of the p38 MAPK pmk-1 pathway is not dependent on IRE-1/XBP-1 [27 , 28] . Together , these data demonstrate that the immune response induced by nhr-86 following exposure to R24 is a physiologically-relevant source of ER stress and provide further support for the conclusion that nhr-86 activates a pathogen-defense response involving secreted proteins . In the absence of R24 , C . elegans nhr-86 mutants are not more susceptible to P . aeruginosa infection than wild-type animals ( Fig 4A ) . In addition , the induction of the innate immune effectors irg-5 , irg-6 and irg-1 during P . aeruginosa infection is not attenuated in the nhr-86 ( ums12 ) mutant; however , the induction of irg-4 is significantly lower ( S4 Fig ) . Given the marked expansion of the NHR family in C . elegans , NHRs , or potentially another mechanism , may function redundantly with NHR-86 to activate host defense genes during P . aeruginosa infection . It is also possible that P . aeruginosa does not produce the ligand sensed by NHR-86 . The immunostimulatory molecule R24 upregulates innate immune effectors whose basal expression requires the p38 MAPK pmk-1 [16] , a key signaling mediator in a pathway that is critically important for host defense against bacterial pathogens [8 , 19] . To determine if nhr-86 and pmk-1 function in the same or distinct pathways in the transcriptional modulation of innate immune effector genes , we compared gene expression ( Figs 5A and S5A ) and pathogen resistance ( Fig 5B ) phenotypes of the pmk-1 ( km25 ) and nhr-86 ( tm2590 ) single mutants with the pmk-1 ( km25 ) ; nhr-86 ( tm2590 ) double mutant . We previously observed that R24 can extend the lifespan of pmk-1 ( km25 ) mutant animals that are infected with P . aeruginosa [[16] and Fig 5B] . In addition , we found that pmk-1 is dispensable for the induction of a group of innate immune effectors , including irg-4 , irg-5 , mul-1 and drd-50 [[16] , see also Figs 5A and S5A] . However , because the basal level of expression of these four effectors is decreased in the pmk-1 ( km25 ) mutant , the absolute level of immune effector expression following exposure to R24 is markedly lower compared to controls ( Figs 5A and S5A ) . The deficiency in the basal regulation of immune effectors in the pmk-1 ( km25 ) mutant contributes to the enhanced susceptibility of this mutant to P . aeruginosa infection in both naive and R24-treated animals [8 , 19] ( Fig 5B ) . These data indicate that R24 drives the induction of a protective immune response independent of pmk-1 . Consistent with this observation , exposure to R24 does not cause an increase in the percentage of active ( phosphorylated ) PMK-1 relative to total PMK-1 in wild-type or nhr-86 ( ums12 ) animals ( Fig 5C and 5D ) . The susceptibility of the pmk-1 ( km25 ) ; nhr-86 ( tm2590 ) double mutant to P . aeruginosa infection in the absence of R24 is identical to the pmk-1 ( km25 ) mutant , further suggesting that NHR-86 functions in an R24-dependent manner ( Fig 5B ) . Importantly , the nhr-86 ( tm2590 ) allele suppressed the R24-mediated enhanced longevity in the pmk-1 ( km25 ) background ( Fig 5B ) . Accordingly , the basal expression of irg-4 , irg-5 , mul-1 , drd-50 and irg-6 is reduced in the pmk-1 ( km25 ) ; nhr-86 ( tm2590 ) double mutant to the same level as the pmk-1 ( km25 ) mutant ( Figs 5A and S5A ) . Importantly , the R24-mediated induction of these immune effectors in the pmk-1 ( km25 ) background is blocked by the nhr-86 ( tm2590 ) mutation ( Figs 5A and S5A ) . Of note , the induction of at least two cytochrome P450 xenobiotic detoxification genes by R24 is not dependent on either nhr-86 or pmk-1 ( S5B Fig ) . These data further support that nhr-86 is required for only a specific subset of the R24-induced genes ( Fig 2 ) . In summary , these genetic epistasis experiments support the model that , upon activation , NHR-86 traffics to the promoters of immune effectors to mount a protective immune response in a manner independent of the p38 MAPK pmk-1 pathway ( Fig 6 ) . In this context , a principal role of the p38 MAPK pmk-1 is to ensure basal resistance to pathogens by controlling the tonic expression of innate immune effectors , such as irg-4 , irg-5 , mul-1 and drd-50 .
This study extends the known functions of C . elegans NHRs to include the activation of anti-pathogen transcriptional responses . Following treatment with an immunostimulatory small molecule , NHR-86 directly activates innate immune effector transcription in a manner that promotes resistance to bacterial infection . ChIP-seq and mRNA-seq revealed an enrichment for innate immune effectors among the transcriptional targets of NHR-86 , including at least three genes , irg-4 , irg-5 and irg-6 , that are each required for normal resistance to P . aeruginosa infection . Consistent with this model , the induction of protective immune defenses by NHR-86 occurs independently of the p38 MAPK pmk-1 . In addition , in the absence of an immunostimulatory molecule , NHR-86 is not required for the basal regulation and is not at the promoters of immune effectors . Arda et al . proposed that NHRs , and NHR-86 in particular , organize modular gene regulatory networks to facilitate the rapid coordination of adaptive responses to intracellular ligands [3] . Our data show that an anti-pathogen transcriptional response is one such adaptive response . We previously demonstrated that a conserved component of the Mediator transcriptional regulatory complex , MDT-15/MED15 , links detoxification and innate immune defenses in C . elegans [17] . The Mediator complex is conserved from yeasts to humans and regulates transcription by physically interacting with both transcriptional regulators and RNA polymerase II [30 , 31] . Individual mediator subunits , particularly those like MDT-15 , which are in the tail region of the complex , dictate the physical interactions with transcriptional regulators and play important roles in modulating specific transcriptional outputs [30–34] . Like nhr-86 , mdt-15 is required for the induction of immune effectors whose basal expression is dependent on the p38 MAPK PMK-1 pathway [17] . In addition , MDT-15 functions downstream of the PMK-1 cascade to control the expression of immune effectors [17] . Notably , a subset of the immune effectors in mdt-15-deficient animals , including irg-4 , irg-5 , and drd-50 have reduced basal levels of expression [as in pmk-1 ( km25 ) mutants] and cannot be induced by the small molecule R24 ( as in nhr-86 loss-of-function mutants ) . Importantly , NHR-86 is known to physically interact with MDT-15 [3] . Thus , we hypothesize that MDT-15 and NHR-86 function together to drive the transcription of immune response genes , such as irg-4 , irg-5 and drd-50 . The ligand that activates NHR-86 is not known . Indeed , it is possible that R24 or a metabolite derived from this compound is an activating ligand of NHR-86 . However , it is important to note that not all R24-induced genes are dependent on nhr-86 for their upregulation . Alternatively , NHR-86 may detect a host-derived ligand that is associated with the toxic effects of R24 on nematode cells . R24 induces xenobiotic detoxification genes and shortens the lifespan of nematodes growing in standard laboratory conditions [16] . C . elegans activates immune defenses following toxin-mediated disruption of cellular homeostasis [35] . Thus , NHR-86 may function as part of a similar cellular surveillance mechanism , although this is not known . Notably , nhr-86 loss-of-function mutants are not more susceptible to P . aeruginosa infection at baseline . While nhr-86 is required for the induction of the immune effectors irg-5 and irg-6 by the immunostimulatory xenobiotic R24 , it is dispensable for their induction during P . aeruginosa infection . Thus , it is possible that P . aeruginosa infection does not produce a ligand that is sensed by NHR-86 or there are redundant mechanisms engaged to activate C . elegans defenses during pseudomonal infection . In either case , our data demonstrate that a C . elegans NHR can drive a protective transcriptional response towards a bacterial pathogen . These findings raise the possibility that NHRs provide a facile and evolutionarily adaptable mechanism to activate protective immune defenses in response to diverse ligands .
C . elegans strains were maintained on standard nematode growth media plates with E . coli OP50 as a food source , as described [36] . The previously published C . elegans strains used in this study were: N2 Bristol [36] , KU25 pmk-1 ( km25 ) [8] , AU306 agIs44 [Pirg-4::GFP::unc-54-3’UTR; Pmyo-2::mCherry] [17] , AY101 acIs101 [pDB09 . 1 ( Pirg-5::gfp ) ; pRF4 ( rol-6 ( su1006 ) ) ] [21] , SJ405 zcIs4 ( Phsp-4::gfp ) [37] , VL491 nhr-86 ( tm2590 ) [3] , and VL648 unc-119 ( ed3 ) ; wwIs22 [Pnhr-86::nhr-86ORF::GFP unc-119 ( + ) ] [3] . The strains developed in this study were: RPW137 nhr-86 ( ums12 ) , RPW119 pmk-1 ( km25 ) ;nhr-86 ( tm2590 ) , RPW99 nhr-86 ( tm2590 ) ; agIs44 , RPW106 nhr-86 ( tm2590 ) ; acIs101 , and RPW165 nhr-86 ( ums12 ) ; agIs44 . Pseudomonas aeruginosa strain PA14 was used for all studies [38] . CRISPR/Cas9 was used to generate nhr-86 ( ums12 ) as described [39] . Target sequences were selected on exons 1 and 6 of nhr-86 . Forward and reverse oligonucleotides were designed to contain the target sequence and overhangs compatible with BsaI sites in plasmid pPP13 , a modified version of pRB1017 [39 , 40] . Forward and reverse oligonucleotides were annealed and ligated into pPP13 cut with BsaI to create the gRNA plasmids . Plasmids were confirmed by sequencing . A DNA mixture of pDD162 ( 50 ng/L ) , the gRNA plasmids ( 25 ng/L each ) , pJA58 ( 50 ng/L ) and the ssODN repair template for dpy-10 ( cn64 ) ( 20 ng/L ) was prepared in injection buffer ( 20 mM potassium phosphate , 3 mM potassium citrate , 2% PEG , pH 7 . 5 ) and injected into N2 worms . Mutations in the dpy-10 gene were used as a CRISPR co-conversion marker . The F1 progeny were screened for Rol and Dpy phenotypes 3–4 days after injection and then for deletions in the nhr-86 coding region using PCR . The nhr-86 ( ums12 ) mutant contains a 5539 bp deletion that spans from 17 bp upstream of the ATG to 30 bp before the stop codon with an insertion of 6 bp at the breakpoint . Primer sequences used for genotyping are listed in S5 Table . A previously-described library containing RNAi clones corresponding to 258 of the 284 NHRs in the C . elegans genome was used for this study [14] . These genes were screened for their ability to abrogate the induction of agIs44 by 70 μM R24 , as described [17] . “Slow killing” P . aeruginosa infection experiments were performed as previously described [18 , 41] . In all of these assays , the final concentration of DMSO was 1% and 70 μM R24 was used . Wild-type is either N2 or agIs44 . All pathogenesis and lifespan assays are representative of three biological replicates . Sample sizes , mean lifespan , % lifespan extension conferred by R24 treatment in each background ( where applicable ) and p values for all trials are shown in S4 Table . Synchronized , L1 stage , hermaphrodites C . elegans of the indicated genotypes were grown to the L4/ young adult stage , transferred to assay plates , and incubated at 20°C overnight . 70 μM R24 or solvent control ( DMSO , 1% final concentration ) assay plates were prepared as described [16–18] . RNA was isolated using TriReagent ( Sigma-Aldrich ) , purified on a column ( Qiagen ) , and analyzed by mRNA-seq using the BGISEQ-500 platform ( BGI Americas Corp ) . mRNA-seq data analysis was performed by BGI Americas Corp . Biological replicate RNA samples were analyzed using NanoString nCounter Gene Expression Analysis ( NanoString Technologies ) with a “codeset” designed by NanoString that contained probes for 118 C . elegans genes . The codeset has been described previously [17 , 18] . Probe hybridization , data acquisition and analysis were performed according to instructions from NanoString with each RNA sample normalized to the control genes snb-1 , ama-1 and act-1 . For the qRT-PCR studies , RNA was reverse transcribed to cDNA using the RETROscript Kit ( Life Technologies ) and analyzed using a CFX1000 machine ( Bio-Rad ) . The sequences of primers that were designed for this study are presented in S5 Table . Other primers were previously published [19 , 27 , 33 , 42] . All values were normalized against the control gene snb-1 . Fold change was calculated using the Pfaffl method [43] . C . elegans were prepared as described above to ensure that stage-matched , hermaphrodite animals at the young L4 larval stage were studied in each condition . Protein lysates were prepared as previously described [17] and probed with a 1:1000 dilution of an antibody that recognizes the doubly-phosphorylated TGY motif of PMK-1 ( Promega Corporation ) . Monoclonal anti-α-tubulin antibody was used at a dilution of 1:1 , 000 ( Sigma-Aldrich ) . A polyclonal antibody against the total PMK-1 protein was raised using the peptide DFQKNVAFADEEEDEEKMES ( PMK-1 amino acids 358 to 377 ) in a rabbit ( Thermo Scientific Pierce Custom Antibody Services ) and used at a dilution of 1:1000 . We confirmed that the total PMK-1 antibody detects total , but not active ( phosphorylated ) PMK-1 ( Fig 5C ) . Horseradish peroxidase ( HRP ) -conjugated anti-rabbit ( Cell Signaling Technology ) and anti-mouse IgG secondary antibodies ( Abcam ) were diluted 1:10 , 000 and used to detect the primary antibodies following the addition of ECL reagents ( Thermo Fisher Scientific , Inc . ) , which were visualized using a BioRad ChemiDoc MP Imaging System . The band intensities were quantified using BioRad Image Lab software version 5 . 2 . 1 , and the ratio of active phosphorylated PMK-1 to total PMK-1 was calculated with all samples normalized to the ratio of wild-type control animals . Chromatin immunoprecipitation was performed with a strain containing a GFP-tagged NHR-86 protein ( NHR-86::GFP ) that has been previously characterized [3] . nhr-86 transcript levels are 2 . 7-fold elevated in the NHR-86::GFP strain compared to wild-type ( S2B Fig ) . ChIP was performed as previously described [44 , 45] with modifications . Briefly , L4 synchronized , hermaphrodite C . elegans ( wild-type and transgenic NHR-86::GFP animals ) were exposed to “slow killing” plates [41] containing either DMSO ( 1% ) or 70 μM R24 for approximately 18 hours . Animals were then collected and washed with 4°C M9 and phosphate-buffered saline to remove bacteria . Cross-linking of protein and DNA was performed in 2% formaldehyde for 30 minutes at room temperature . Cross-linking was quenched with 100 mM glycine , animals were washed in M9 , resuspended in lysis buffer ( 50 mM Hepes–KOH pH 7 . 5 , 300 mM NaCl , 1 mM EDTA , 1% ( v/v ) Triton X-100 , 0 . 1% ( w/v ) sodium deoxycholate , 0 . 5% ( v/v ) N-Lauroylsarcosine , and protease inhibitors ) and lysed with a Teflon homogenizer . Lysates were then sonicated using a Bioruptor UCD-200 for 10 cycles ( 30 s on , 30 s off ) to obtain 500–1000 bp DNA fragments . Sonicated lysates ( 2 mg ) were pre-cleared with protein G Dynabeads ( Invitrogen ) , 10% of lysate removed for input , and incubated with 5 μg anti-GFP antibody ( Roche ) overnight . Immune complexes were collected with protein G Dynabeads , washed , and eluted from beads . Cross-links were reversed at 65°C overnight and DNA fragments were purified with PCR purification columns ( Qiagen ) . qPCR was performed on input and immunoprecipitated samples using primers designed around the transcription start site . All ChIP data are presented as percent input normalized to a random intragenic region on chromosome four . Primer sequences are available in S5 Table . ChIP-seq was performed by BGI Americas Corp . The raw sequencing data were first clipped for adaptor sequences and then mapped to the C . elegans genome ( ce10 , UC Santa Cruz ) by the Burrows-Wheeler Aligner algorithm ( BWA MEM , BWA version 0 . 7 . 15 ) . The output SAM files were processed and sorted with the Picard tools . The output mapping files ( BAM files ) were filtered with SAMtools to remove any read that had a mapping quality less than 10 ( SAMtools view–b–q 10 input . bam > output . bam ) . Peaks were determined using MACS version 2 . 1 with the no-model parameter . The final set of peaks were called if the difference in intensity values of samples had a significance level of p-value < 0 . 025 . To identify candidate motifs for NHR-86 binding , ChIP peaks that were located in promoter regions of genes were examined using the MEME motif analysis platform [Parameters: minw = 8 , maxw = 25 , in two modes ( zoops & anr ) , significance threshold ( E-value > = 1e-01 ) , http://meme . sdsc . edu] . A background model is used by MEME to calculate the log likelihood ratio and statistical significance of the motif . We set the following requirements: the most significant motif should exist in 50% of input sequences , and the genes containing the motif should have the largest overlap between ChIP-Seq and RNA-seq datasets . A single 15 bp motif was identified that met these criteria ( E-value: 1 . 7e-003 , S2C Fig ) . 66 sites of 101 input sequences had this motif , including 15 of the 32 genes that overlapped in the ChIP-Seq and RNA-seq datasets . Nematodes were mounted onto agar pads , paralyzed with 10 mM levamisole ( Sigma ) and photographed using a Zeiss AXIO Imager Z2 microscope with a Zeiss Axiocam 506mono camera and Zen 2 . 3 ( Zeiss ) software . Differences in survival of C . elegans in the P . aeruginosa pathogenesis assays were determined with the log-rank test using OASIS 2 as previously described [46] . Data from one experiment that is representative of the replicates is shown . Other statistical tests , indicated in the figure legends , were performed using Prism 7 ( GraphPad Software ) .
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The family of nuclear hormone receptors ( NHRs ) has expanded in the nematode C . elegans . NHRs are intracellular sensors that control adaptive host responses following recognition of specific endogenous or exogenous ligands . These proteins are therefore well positioned to function in pathogen sensing and innate immune activation . The C . elegans genome contains 284 NHRs , whereas humans and Drosophila have only 48 and 21 , respectively . However , the biological function of the great majority of the NHRs in C . elegans is not known . We designed a genetic screen to determine if an NHR functions in immune activation , and identified NHR-86 , a homolog of human hepatocyte nuclear factor 4 ( HNF4 ) . We show that NHR-86 drives a transcriptional response that provides protection against the bacterial pathogen Pseudomonas aeruginosa .
|
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2019
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The nuclear hormone receptor NHR-86 controls anti-pathogen responses in C. elegans
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Group A Rotavirus ( RVA ) is the leading cause of severe diarrhea in children . The aims of the present study were to determine the neutralizing activity of VP6-specific llama-derived single domain nanoantibodies ( VHH nanoAbs ) against different RVA strains in vitro and to evaluate the ability of G6P[1] VP6-specific llama-derived single domain nanoantibodies ( VHH ) to protect against human rotavirus in gnotobiotic ( Gn ) piglets experimentally inoculated with virulent Wa G1P[8] rotavirus . Supplementation of the daily milk diet with 3B2 VHH clone produced using a baculovirus vector expression system ( final ELISA antibody -Ab- titer of 4096; virus neutralization -VN- titer of 256 ) for 9 days conferred full protection against rotavirus associated diarrhea and significantly reduced virus shedding . The administration of comparable levels of porcine IgG Abs only protected 4 out of 6 of the animals from human RVA diarrhea but significantly reduced virus shedding . In contrast , G6P[1]-VP6 rotavirus-specific IgY Abs purified from eggs of hyperimmunized hens failed to protect piglets against human RVA-induced diarrhea or virus shedding when administering similar quantities of Abs . The oral administration of VHH nanoAb neither interfered with the host's isotype profiles of the Ab secreting cell responses to rotavirus , nor induced detectable host Ab responses to the treatment in serum or intestinal contents . This study shows that the oral administration of rotavirus VP6-VHH nanoAb is a broadly reactive and effective treatment against rotavirus-induced diarrhea in neonatal pigs . Our findings highlight the potential value of a broad neutralizing VP6-specific VHH nanoAb as a treatment that can complement or be used as an alternative to the current strain-specific RVA vaccines . Nanobodies could also be scaled-up to develop pediatric medication or functional food like infant milk formulas that might help treat RVA diarrhea .
Diarrhea is the second most common cause of childhood mortality worldwide , causing 1 . 3 million deaths among children younger than 5 years of age [1] . Group A rotavirus ( RVA ) is the leading cause of severe diarrhea in children worldwide and is responsible for approximately 29% of all diarrheal deaths , causing 453 , 000 deaths per year [2]–[5] . Human rotaviruses ( Group A , B and C ) have also been implicated as causative agents of diarrheal outbreaks occurring in nursing homes [6] , among travelers [7] , in day-care centers [8] , and in patients suffering from a variety of immunodeficiency conditions [9] , [10] . Rotaviruses have a genome consisting of 11 segments of double-stranded RNA . Most segments encode a single polypeptide , allowing the virus to express six structural proteins ( VPs ) and five non-structural proteins ( NSPs ) [11] . Twenty-seven G-types and 35 P-types that independently elicit virus-neutralizing antibodies ( Abs ) have been identified based on the RVA outer capsid proteins VP7 ( G-type ) and VP4 ( P-type ) [12] . Of these , G-types G1 to G4 and G9 combined with P-types P[4] , P[6] and P[8] account for most of the G-P combinations of human RVA detected globally . They are responsible for approximately 90% of all RVA infections worldwide , showing different relative proportions by year and region [13]–[15] . Other genotypes such as G5 , G8 , G10 and G12 in combination with P[7] , P[8] and P[9] were recently reported infecting children from South America , the Caribbean , Africa and Asia with lower incidences [15]–[21] . Currently , diarrhea caused by RVA can be prevented through vaccination but treatment strategies are non-specific , largely symptom-based , and involve fluid , electrolyte replacement and maintenance of nutrition [22] . Live-attenuated oral RVA vaccines have variable degrees of efficacy and a high cost [23] , [24] . Recent clinical trials showed that RVA vaccines have significantly lower efficacy in countries with limited infrastructure and resources , usually the countries with the highest RVA burdens [24] . Moreover , vaccine-acquired human RVA infection and diarrhea has been previously reported in children suffering from severe combined immunodeficiency , which led the Centers for Disease Control to issue a recommendation against their use in this population [25] . On the other hand , rotavirus-specific treatments such as passive immunotherapy using antibodies ( Abs ) are associated with various degrees of success against infectious diseases of different etiologies , such as viral , bacterial , fungal and protozoal origin in both humans and animals [10] , [22] , [26]–[35] . Therefore , we investigated llama-derived single-chain antibody fragments ( VHH ) against rotavirus VP6 protein as preventive therapy and a potential treatment option . VHHs are the smallest molecules with antigen-binding capacity and present distinctive properties that differentiate them from conventional antibodies , such as the ability to remain intact in the gastrointestinal tract during oral administration . The RVA VP6 inner capsid protein is highly immunogenic and constitutes the target antigen of most immunodiagnostic tests [36] , [37] . Based on its nucleotide ( nt ) variability ( 85% nt identity among VP6 of the same group ) , at least 17 VP6 I ( for intermediate capsid shell ) genotypes have been described , I1 and I2 being the most frequently found in human RVA strains [38] , [39] . Most studies show that conventional Abs to VP6 lack extracellular neutralizing activity in vitro [40]–[43] . Tosser et al . developed a monoclonal Ab to VP6 ( RV-133 ) that interacted with both double- and triple-layer particles and induced partial decapsidation but failed to neutralize RVA in vitro [40] . Burns et al . reported two IgA monoclonal Abs to VP6 ( clones 7D9 and 10C10 ) that did not present detectable neutralizing activity in vitro but inhibited viral transcription and completely protected against infection in vivo [44] , [45] . However , conflicting results regarding the effectiveness of VP6 Abs mediating passive protection in neonatal mice have been reported [44] , [46] . Some studies showed that VP6-specific maternal Abs did not provide passive protection against RVA-associated diarrhea in neonatal mice [47] , [48] while others reported partial protection in neonatal mice born to dams immunized with recombinant VP6 derived from C486 RVA ( G6P[1]I ? ) that did not develop virus neutralizing Abs [41] . Similar studies that used passive IgA monoclonal Abs to VP6 suggested that protection in vivo is in fact mediated by the binding of VP6 IgA Ab to RVA , which protects by intracellular neutralization during transcytosis in the mouse gut [44] , [48]–[50] . In any case , it is well known that the continuous presence of high titers of passive RVA Abs in the gut lumen ( naturally produced or artificially added to the milk ) fully protects against diarrhea and significantly reduces virus shedding [43] , [51]–[53] . We have previously developed VHH against VP6 from bovine RVA strain C486 ( G6P[1]I ? ) . These VHH nanoAbs neutralized RVA in vitro , independently of the serotype . This result was further confirmed in vivo by partial protection of VHH clones 3B2 and 2KD1 against RVA challenge in a neonatal mouse model , demonstrating for the first time the broad neutralization activity of VP6 specific VHH nanoAbs in vitro and in vivo [54] , [55] . Neutralizing VHH nanoAbs directed to VP6 may provide a new strategy for the prevention and treatment of RVA diarrhea . However , being a heterologous source of Abs , the host immune response to the passive treatment must be considered , especially in view of plans to use llama VHH nanoAbs prophylactically and/or therapeutically in humans . We chose for this study the Improved Baculovirus Expression System ( IBES technology ) , which uses baculovirus expression vectors in combination with Trichoplusia ni larvae as living biofactories . The benefits of this platform have been largely proven for other recombinant proteins as a cost-efficient production platform for a number of recombinant proteins [55]–[58] . The optimal production of high yields of fully functional VP6-specific VHH derived from larvae has been published recently , wherein the protective effect of this VHH nanoAb in mice was reported [55] , confirming previous results obtained with VHH derived from Escherichia coli [54] . To test the VP6-specific VHH antibody against human RVA gastroenteritis we chose the neonatal gnotobiotic ( Gn ) pig model . The Gn piglets are a widely known animal model susceptible to human RVA infection and disease and the pathogenicity of RVA in Gn piglets mimics that after natural RVA infection of infants . Furthermore their gastrointestinal physiology and mucosal immune system resemble that of human infants [59]–[61] . Here , we assess the broad neutralizing activity of 3B2 VHH to different genotypes of RVA circulating in humans; and evaluate the passive protection conferred by oral administration of VP6-specific VHH clone 3B2 against RVA-induced diarrhea in neonatal Gn piglets experimentally inoculated with one of the most prevalent strains of human RVA , Wa G1P[8]I1 .
The aim of the present experiment was to evaluate the protection of orally administered G6P[1] VP6-specific VHH against human RVA associated diarrhea in Gn piglets experimentally inoculated with virulent Wa G1P[8]I1 RVA , one of the most prevalent RVA strains circulating in human infants worldwide [15]–[21] . The experimental design included five groups of Gn pigs receiving milk supplemented with one of the following: 3B2 VHH nanoAbs ( VHH produced against G6P[1] ) , Wa G1P[8]I1 human RVA-specific porcine IgG Abs ( IgG ) , G6P[1] VP6-specific chicken IgY Abs ( IgY ) , control larvae ( CL ) or Ab-free milk ( No Treatment , NT ) . The results for VN and ELISA isotype-specific Ab titers to Wa human RVA in the supplemented milk are depicted in Table 1 . As shown , VP6-specific VHH nanoAbs had a final Wa human RVA ELISA Ab titer of 4096 and a VN titer of 256 in the supplemented milk , similar to the Ab titers obtained in porcine anti-Wa human RVA IgG supplemented milk used as a positive homologous control treatment . Milk containing chicken IgY polyclonal Abs purified from eggs of VP6-vaccinated hens with a final Wa human RVA ELISA Ab titer of 4096 and a VN titer to Wa human RVA of 64 was considered as a control for heterologous conventional Abs to VP6 . As expected , no Abs against Wa human RVA were detected for CL supplemented milk and Ab free milk -NT , consisting of sterile commercial bovine milk- ( Table 1 ) . Table 2 shows the presence of diarrhea and the amount of virus shedding detected . Supplementation of the milk diet with VP6-specific VHH nanoAbs for 9 days conferred full protection ( 5 of 5 animals protected ) against Wa Human RVA diarrhea in Gn pigs . The positive control group , pigs treated with the same ELISA and VN titer of homologous IgG Abs to Wa human RVA , were partially protected , as 4 out of 6 animals did not develop diarrhea after virus inoculation . In the 2 piglets from this group that developed diarrhea , there was a delay in the onset ( post inoculation day -PID-4; p = 0 . 0214 ) and a reduction in the mean duration ( 0 . 7 days; p<0 . 0001 ) and in the mean cumulative diarrhea score ( 4 . 0; p<0 . 0001 ) , all of which differed significantly compared to animals that did not receive any treatment ( NT group; no animals protected; mean onset: PID 2 . 2; mean duration: 6 . 8 days; mean cumulative diarrhea score: 15 . 6 ) . Finally , animals in the IgY and CL groups developed diarrhea with statistically comparable protection parameters ( in terms of percentage of animals with diarrhea , mean onset , duration and mean cumulative diarrhea score ) to that of the NT group of pigs ( Table 2 ) . Virus shedding was detected in all animals in the VHH group ( 5 out of 5 infected animals ) . Although the mean onset of virus shedding was similar in all groups of pigs , in the VHH group , the mean duration ( 3 . 0 days; p = 0 . 0012 ) and the AUC ( 6 . 1×104 FFU/ml*day; p = 0 . 0055 ) were significantly lower than the ones in the NT group ( mean duration: 5 . 6 days , AUC: 1 . 8×106 FFU/ml*day ) . Mean peak titer and mean titer of virus shed showed a trend toward lower values than in the NT group , but not significantly so . For the IgG group , 5 of the 6 animals had only a short duration and low amounts of virus shedding ( mean onset: PID 3 . 0; mean duration: 1 . 6 days; AUC: 1 . 9×104 FFU/ml*day ) . The mean peak titer ( 103 . 4 FFU/ml; p = 0 . 014 ) and mean titer of virus shed ( 100 . 5 FFU/ml; p = 0 . 0012 ) for this group of pigs were significantly lower than pigs in NT group ( 105 . 7 FFU/ml and 101 . 2 FFU7ml respectively ) . The IgY and CL groups were intermediate between the positive control group ( IgG group ) and the NT pigs regarding mean duration , AUC , mean peak titer and mean titer of virus shed . There were no statistically significant differences in the onset of virus shedding ( IgY = CL = PID 1 . 8 ) and the percentage of animals infected ( IgY = CL = all the animals infected ) compared to the NT group ( Table 2 ) . The profiles of individual infectious virus shedding as determined by CCIF assay are depicted in Figure 1 . Pigs in the VHH group showed a variable pattern of virus shedding , with some pigs shedding RVA for only one day and other pigs shedding virus for up to seven days . Only two pigs shed virus for one day after the end of the treatment , but in low titers . No diarrhea was observed in this group of pigs , indicative of asymptomatic virus shedding . In the IgG group , five pigs shed virus for up to three days during the administration of the treatment and there was no virus shedding after the end of the treatment . Although all the pigs in the CL group developed diarrhea and shed virus , one animal shed infectious virus after the treatment ended , but without diarrhea . The patterns of virus shedding in IgY , CL and NT groups were similar , with high titers of RVA particles shed for several days despite the administration of IgY or CL treatments ( Figure 1 and Table 2 ) . The presence of porcine coproAbs to Wa human RVA was evaluated daily in all the groups of pigs by isotype-specific ELISA ( Figure 2 ) . The IgM Abs were first detected at variable time points depending on the group of pigs and its presence was associated with virus clearance ( Figure 1 ) . The IgM response was always followed by IgA Ab responses . All the Ab titers detected were low and this may be explained by the fact that samples were diluted rectal swab fluids and not feces . In particular , IgA was the main isotype detected in rectal swab fluids and intestinal contents . We further evaluated the persistence of the VHH , IgY and IgG Abs in rectal swab fluids after the treatments ( Figure 2 ) . The VHH nanoAbs administered were detected in rectal swab fluids from treated piglets by ELISA until up to two days after the end of the milk supplementation ( PID 9 ) , but always in low titers . The VP6-specific IgY Abs were also detected in rectal swab fluids , but only at the beginning of the milk diet supplementation . Although the supplemented Abs are indistinguishable from the host's immune response , no swine IgG Abs to RVA Wa were detected in rectal swab fluids from the IgG group of pigs during the treatment ( Figure 2 ) suggesting that the treatment is being degraded in the intestinal tract . The porcine serum Ab isotype responses to Wa RVA are depicted in Figure 3 . At PID 7 , IgM was the main Ab isotype detected in pigs' sera and titers coincided with the VN activity detected . For all the experimental groups of pigs , except for the IgG group , these results were also in agreement with the coproAb responses previously described ( Figure 2 ) . Pigs in groups VHH , IgY and CL showed statistically higher titers of IgM Abs in serum at PID 7 ( p = 0 . 0015 ) and PID 14 ( p = 0 . 0033 ) than the IgG group; the NT group had intermediate titers at this experimental time point ( PID 7 ) . No other significant differences in porcine Ab titers to Wa RVA were detected in sera . There was a progressive increase in VN Ab titers over time during the experiment in animals from all groups , with the highest titers detected at PID 21 , together with the presence of IgA and IgG Abs to Wa RVA ( Figure 3 ) . No heterologous Abs derived from the treatments ( Abs to VHH and IgY ) were detected in serum samples from treated piglets at PID 0 , 7 , 14 and 21 by ELISA ( data not shown ) . The Ab Secreting Cell ( ASC ) responses to RVA in systemic lymphoid tissues and gastrointestinal lymphoid tissues ( GALT ) at PID 21 were evaluated by ELISPOT assay and ( Figures 4 and 5 , respectively ) . Results for IgM ASCs in tissues at PID 21 are not shown since few of them were detected . There were statistically higher IgG ASC numbers in blood from the VHH group compared with the IgG group , while the CL , IgY and NT groups showed intermediate numbers ( p = 0 . 003 ) ( Figure 4 ) . The numbers of IgA ASC were significantly higher in mesenteric lymph nodes ( MLN ) from the NT group than in the groups receiving human RVA-specific Abs as treatments ( VHH , IgY and IgG groups ) ( p = 0 . 026 ) . No further significant differences were observed in ASC numbers in systemic lymphoid tissues and MLN between groups ( Figure 4 ) . Different numbers of ASC to Wa RVA at PID 21 in the GALT were detected in all the intestinal tissues studied ( Figure 5 ) . At PID 21 , IgA was the main ASC isotype detected in the GALT from all groups of pigs , followed by IgG . The ASC numbers were statistically similar among groups . However , the IgA ASC numbers from jejunum were significantly lower in the VHH group compared with all other groups of pigs ( p = 0 . 019 ) . A trend towards lower numbers of ASC was observed in the VHH group compared with the NT group , but no other significant differences were detected ( Figure 5 ) . The presence of a nanobody-specific immune response in VHH and IgY treated animals was determined by ELISA in sera and intestinal contents of treated piglets ( Figure 6 ) . The IgG Ab levels were determined in serum samples weekly . In the intestinal contents , IgA Ab responses were determined together with IgG Abs to VHH nanoAbs at PID 21 . In spite of the presence of low titers of orally administered VHH nanoAbs in rectal swab fluids from the VHH group , the treated piglets did not develop specific Ab responses to the VHH nanoAbs neither in serum nor in the intestinal contents by PID 21 ( Figure 6 ) . Further analysis of rectal swab fluids also failed to detect porcine Abs to the VHH nanoAb ( data not shown ) . In contrast , piglets fed with milk supplemented with IgY Abs to VP6 developed a humoral Ab response to the IgY Ab , ( Figure 6 ) . Piglets in the IgY group developed serum IgG Abs to IgY at PID 7 ( 9 days after starting the treatment ) , with a peak at PID 14 . The IgA and IgG Abs to chicken IgY were also observed in the intestinal contents at PID 21 ( Figure 6 ) , but not in rectal swab fluids ( data not shown ) . As expected for the piglets that did not receive heterologous immunoglobulins , no IgG/IgA Abs to IgY or VHH were detected in CL , IgG and NT piglets in serum , rectal swab fluids or intestinal contents ( Figure 6 and data not shown ) . Swine Abs to porcine IgG were not tested , as an immune response of the host to homologous Abs is not expected . To further characterize the ability of VHH nanoAbs to neutralize RVA , a virus neutralization assay was performed using several RVA strains . The RVA strains were selected considering their G- , P- and I-genotypes in order to include as many genotypes circulating in humans as possible ( Table 3 ) . VHH nanoAb 3B2 was able to neutralize all the RVA strains tested at different concentrations , ranging from 15 . 63 µg VHH/ml for SA11 strain to 0 . 06 µg VHH/ml for Wa and F45 strains . As a control , non-related VHH nanoAb was not reactive against any of the RVA strains tested ( Table 3 ) .
The VP6 constitutes the inner capsid of rotavirus and it is the most abundant and immunodominant viral protein . The Abs directed to VP6 are highly cross-reactive among RVA so VP6 immunization could potentially provide heterotypic protection [62] . The main objective of the present study was to determine the efficacy of the oral administration of G6P[1] VP6-specific VHH nanoAbs against Wa G1P[8]I1 human RVA-induced diarrhea in a Gn pig model of infection and disease . The 3B2 VHH clone protected all treated animals from RVA-induced diarrhea when administered daily as milk supplement at a final Wa RVA ELISA Ab titer of 4096 ( VN titer of 256 ) during nine consecutive days . The protection observed was comparable to that in pigs treated with porcine IgG Abs to Wa RVA at the same ELISA and VN titers . This latter group of pigs was considered the positive control group , simulating the protection conferred by homologous Abs [63] , [64] . The presence of diarrhea in 2 out of 4 animals from the IgG group suggests that this passive treatment with homologous Abs is not completely capable of preventing RVA-induced diarrhea against the challenge dose administered . However , the homologous treatment still conferred a great degree of protection , highlighting the importance of passive maternal Abs in newborns . These results reinforce the importance of the use of RVA vaccines ( to induce active immunity ) but also state the precedent that additional RVA-specific strategies might be useful to control and prevent RVA diarrhea in human infants . Passive or active protection against RVA diarrhea is the most desirable outcome of any treatment or vaccination and can be achieved even when continued viral shedding is detected in stools . Moreover , the asymptomatic infection allows development of active immunity ( as noted in our study ) to prevent subsequent natural RVA infections . In our study , passive treatment with homologous porcine IgG Abs also provided a high degree of protection against virus shedding . However , the production of large amounts of polyclonal human IgG Abs specific to RVA needed for children would be difficult to implement and Abs would be mostly RVA strain-specific . We investigated a more universal treatment against a wide range of RVA strains applicable for neonatal humans or animals , based on VHH technology , which is easy to scale up and presents distinctive advantageous properties over traditional antibodies . The 3B2 VHH clone expressed in E . coli was previously characterized and showed a broad neutralizing activity against RVA in vitro , independently of the RVA serotype [54] . Remarkably , this VHH was developed against the VP6 of bovine C486 ( G6P[1]I ? ) RVA strain , but it showed broad neutralization activity in vitro against RVA of heterologous serotypes and species of origin including Wa HRV [54] . Furthermore , this result was confirmed by in vivo partial passive protection against bovine RVA strain C486 and murine RVA strain ECW ( G16P[16]I7 ) at 48 h post challenge in a neonatal mouse model using 1 mg/ml ( 22 , 2 mg/kg/day ) of recombinant VHH administered once a day for 5 consecutive days [54] . The 3B2 VHH clone expressed in insect cell cultures had the same therapeutic properties as the one expressed in E . coli in the neonatal mouse model [55] . In the present study , 3B2 VHH neutralized virus infection in vitro from several RVA strains and this seemed to be independent of the G- , P- and I-genotypes of RVA strains tested . The results obtained in vitro demonstrate that the 3B2 VHH nanoAb inhibits infection by relevant RVA strains circulating in humans worldwide , including not only Wa ( G1P[8]I1 ) , but also DS1 ( G2P[4]I2 ) , 69M ( G8P[10]I2 ) , F45 ( G9P[8]I ? ) and Arg720 ( G12P[9]I ? ) among others ( Table 3 ) . In addition , a high in vivo protection rate was observed in this study against VirWa human RVA inoculation in Gn pigs fed with 22 mg of VHH nanoAbs per 210 ml of milk ( 0 . 1 mg/ml of milk , 44 mg/pig/day or 20–40 mg/kg/day ) . VHH nanoAbs protected against RVA-induced diarrhea in all the animals tested , even when all the animals shed virus infective particles . Since VHHs are recombinant monoclonal Abs , the possibility of VP6 escape mutant selection should be considered . Further studies are underway to determine if VHH nanoAbs promote VP6 escape mutants in vitro and in vivo . This information will help us better understand how the VHH nanoAbs inhibit RVA infection . Chicken egg yolk IgY Abs to G6P[1] VP6 were also used as a control for treatment with heterologous conventional Abs . This treatment was not protective against RVA diarrhea or virus shedding in Gn pigs . These results obtained in gn pigs , an animal model that closely resembles RVA pathogenicity in human infants , are in agreement with the lack of protection observed in a mice model using other conventional Abs directed to VP6 protein [47] , [48] . Of note , the avian IgY Abs were obtained from VP6-vaccinated hens with pre-existing VN activity to Wa RVA . Avian rotavirus is endemic in hens [11] and it has been reported that mammalian and avian RVAs have a low degree of nucleotide sequence identity for all eleven genome segments [39] , [65] . This may explain the presence of only low pre-existing VN activity to RVA in the chickens due to cross reactivity . Serum , coproAbs , and ASC responses were tested to assess the development of the pigs' immune responses to Wa RVA . The highest ASC responses to Wa RVA were in the GALT at PID 21 , with lower ASC numbers in systemic lymphoid tissues . Our results indicate that pigs receiving passive Ab treatments ( IgG , IgY or VHH ) had the same isotype profile of IgA ASC but of lower magnitude than piglets in NT group , suggesting some interference effect . A short delay in the development of the immune response and a lower number of ASC were also evident in the group of pigs treated with VHH ( in particular , reduced IgA ASC in jejunum ) . However , the magnitude of the Ab responses developed was potent enough to prevent Wa RVA diarrhea after a second exposure to the virus , in agreement with previous reports [66] . However , it is unclear if the passive treatment with VHH nanoAbs affected the development of the pigs' immune response to RVA infection . The absence of diarrhea , and thus a lower level of viral replication , probably affects the development of a stronger immune response . The administration of control larvae as passive treatment ( CL ) failed to prevent RVA-associated diarrhea and did not significantly modify piglets' immune responses to Wa human RVA , but showed a trend toward less severe diarrhea , virus shedding and lower number of ASC compared to the NT group . An explanation for this phenomenon is not clear and may be related to biological factors in the harvested T . ni larvae that may have an adjuvant or immunopotentiating effect on innate immunity in the Gn pigs . It has been described that baculovirus could elicit antiviral activity in mammalian cells , both in vitro and in vivo , but this hypotheses should be further explored [67] . However , the control larvae group trend to reduce virus shedding was not enough to statistically modify the diarrhea-associated parameters , as it was not significantly different from NT control group . A critical point to be considered is the host's immune response to the passive treatment with heterologous Abs , as it has serious health implications such as the development of allergy and other hypersensitivity reactions . In this study , a heterologous neutralizing VHH nanoAb was examined as a prevention strategy against human RVA in an animal model that closely mimics the intestinal physiology of human infants . VHH-treated piglets did not develop detectable humoral Ab responses against the passive VHH treatment ( in serum , rectal swab fluids , or intestinal contents ) by the methodology used . In contrast , piglets treated with IgY Abs to VP6 developed a humoral Ab response to the passive IgY treatment , characterized by the presence of IgG Abs to IgY in serum and both IgG and IgA Abs to IgY in the intestinal contents . Equally important , no heterologous Abs derived from the VHH or IgY passive treatment were detected in sera of treated animals , which suggests that there was no transmission of VHH or IgY Abs from the gut lumen to the blood . It is well documented that under physiological , non-inflamed conditions , dendritic cells migrate from mucosa to present antigens in the lymph nodes [68] . As a result , dietary antigens are presented in association with signals that drive a suppressive immune response . It has been reported that IgY is highly immunogenic as it has been used as a model antigen for testing mucosal adjuvants , which might explain the presence of IgG anti IgY in sera of treated animals [69] , [70] . On the contrary , the oral administration of VHH nanoAbs might induce a tolerant state , preventing the host from eliciting an anti-VHH immune response , but further studies must be conducted to confirm this statement . It has been previously reported that passive VHH nanoAbs to VP6 with similar VN activity were protective against RVA in vivo in mice [71]–[75] . Briefly , Van der Vaart et al . produced VHH nanoAbs to a G3 Rhesus-monkey RV ( RRV ) strain in yeast . Daily oral administration of 50–100 µg/pup ( 20–40 mg/kg/day ) during five days reduced the morbidity of RRV-induced diarrhea in mice , but it was unclear whether the VHH nanoAbs were effective against other rotavirus strains [73] . Pant et al . also produced VHH nanoAbs to G3 RRV in Lactobacillus paracasei , in both secreted and cell surface–anchored forms . Lactobacilli expressing membrane anchored nanoAbs showed neutralizing activity in vitro . The prophylactic use of those VHH nanoAb during 5 days reduced the frequency , duration and severity of diarrhea in mouse pups after oral inoculation with RRV [72] , [75] . Recently , Aladin et al . further characterized the same VHH clones ( ARP1 and ARP3 ) and reported in vitro neutralizing activity against several RVA strains including human RVA strains Wa , DS1 , 69M , F45 and ST3 , but failed to neutralize SA11 and one of the RRV strains tested . Although these VHH nanoAbs were developed against complete RRV , ARP1 and ARP3 are also directed to VP6 as evidenced by western blot analysis . [71] In contrast , ARP1 and ARP3 recognize a lineal epitope of VP6 unlike 3B2 VHH that is directed to a conformational epitope [54] , [71] . Collectively , the evidence obtained from Aladin et al . together with our results suggest that the ability of VHH nanoAbs to inhibit in vitro virus replication does not correlate with a specific VP6 genotype as several RVA strains with different G- , P- and I-genotypes were neutralized by VHHs . However , 3B2 VHH appears to be much more efficient in inhibiting strain-specific RVA replication than ARP1 and ARP2 VHHs [71] , as lower amounts of 3B2 VHH were needed to neutralize Wa , DS1 , ST3 , F45 and 69M RVA infection in vitro . This assumption should be confirmed testing the VHH nanoAbs ( 3B2 , ARP1 and ARP3 ) under the same conditions . The VHH nanoAbs were the first Abs to demonstrate extracellular neutralizing activity . The mechanism by which VHH nanoAbs inhibit virus replication is still unclear and several studies are in progress in our laboratory to elucidate it . With this in mind , Feng et al . showed that the attachment of a VP6-specific IgA monoclonal Ab to VP6 introduced a conformational change in the VP6 trimer , rendering the particle transcriptionally incompetent and preventing the elongation of initiated transcripts [45] . Since monoclonal Abs to VP6 are capable of inhibiting RVA transcription [76] , it reinforces the idea that VP6 IgA Abs confer protection in vivo by inhibiting viral transcription at the start of the intracellular phase of the viral replication cycle . It is widely known that the VP6 protein plays a key role in the organization of the virion , because it is in direct contact with the inner and the outer protein shells . Likewise , VP6 is the physical adaptor between two biological functions critical for RVA: cell entry ( related to the virus outer layer ) and genomic RNA packaging ( related to the inner layer ) [11] , [77] . Although the VP6 protein is only exposed in double-layered particles , VHH nanoAbs of smaller size than conventional Abs , could penetrate the outer shell , bind VP6 , and block decapsidation , inhibiting the early steps of virus replication . An improved structural understanding of the common features of the different RVA strains neutralized by VHH nanoAbs will shed light into this mechanism . Finally , our results indicate that the VHH clone 3B2 is a recombinant monoclonal nanoAb that should be further explored as a potential treatment of RVA-associated diarrhea , as it showed 100% efficacy against Wa G1P[8]I1 RVA-induced diarrhea in vivo , and a broad neutralizing activity against several RVA strains circulating in humans worldwide in vitro [54] . This VHH nanoAb would also have the advantage of producing and administering a single antibody in contrast to a cocktail of different conventional Abs directed to the common G-P RVA strains circulating in human populations . Additionally , it could be scaled-up to develop pediatric medications or functional foods like infant milk formulas to control RVA diarrhea . Producing VHHs using an expression system with high production efficiency or downstream processing is crucial , since the commercial application of this treatment will greatly depend on the VHH nanoAb production costs . Additional studies will be needed to determine the safety and efficacy of VHHs against different RVA wild type strains as well as the stability and administration regime of a treatment . In summary , our findings show the potential value of broad neutralizing VP6-specific VHH nanoAbs as a treatment that could complement ( but not replace ) the use of serotype-specific RVA vaccines . This study represents a proof of principle of the efficacy of VHH oral therapy to prevent RVA diarrhea . This type of treatment has great potential to be implemented in developing countries , where RVA mortality is high and current vaccines seem less efficacious , and also to be administered to prematurely born or immunodeficient children worldwide [25] , [78] .
This study was carried out in strict accordance with the recommendations by the Public Health Service Policy , United States Department of Agriculture Regulations , the National Research Council's Guide for the Care and Use of Laboratory Animals , and the Federation of Animal Science Societies' Guide for the Care and Use of Agricultural Animals in Agricultural Research and Teaching , and all relevant institutional , state , and federal regulations and policies regarding animal care and use at The Ohio State University . The study protocol was approved by the Committee on the Ethics of Animal Experiments of The Ohio State University ( Protocol Number: 2010A00000088 ) . All the pigs were maintained , samples collected , and then euthanized , and all efforts were made to minimize the suffering of animals . Oral inoculation of neonatal pigs with Wa RVA caused transient diarrhea of variable severity from which piglets recovered spontaneously within a few days . The euthanasia was performed by electrocution following anesthesia . For this particular study , we used the lowest number of pigs previously shown to permit detection of statistical significances among treatments considering welfare principles . A statistician verified the minimum number of pigs required per treatment group before starting the experiments . The intestinal contents of RVA Wa G1 , P1A [8] infected Gn pigs were diluted in minimal essential medium ( MEM; Invitrogen , Carlsbad , USA ) , and used for virus inoculation as described [64] . Attenuated Wa HRV ( cell culture adapted ) was propagated in monkey kidney ( MA-104 ) cells for use in sow hyperimmunization , enzyme-linked immunospot assay ( ELISPOT ) , ELISA and VN assays . The RVA strains DS1 ( G2P[4]I2 ) , SA11 ( G3P[1]I2 ) , Gottfried ( G4P[6]I1 ) , ST3 ( G4P[6]I1 ) , H1 ( G5P[7]I5 ) , 69M ( G8P[10]I2 ) , F45 ( G9P[8]I ? ) and Arg720 ( G12P[9]I ? ) were propagated in monkey kidney ( MA-104 ) cells for use in VN assays . The MA-104 cell line of fetal rhesus monkey kidney cells ( passage 36 ) was originally purchased from Microbiological Associates ( now BioWhittaker , Radnor , USA ) . The Sf9 cell line , a clonal isolate derived from Spodoptera frugiperda ( Fall Armyworm ) , was obtained from Invitrogen and cultured in Grace's insect media ( GIBCO , Carlsbad , USA ) supplemented with 10% fetal bovine serum ( FBS , GIBCO ) , 3% non-essential amino acids ( Invitrogen ) , 1% nystatin , streptomycin and penicillin and 20 µg/ml gentamycin ( Invitrogen ) . Sf9 cells were grown at 27°C and MA-104 cells at 37°C in a 5% CO2 –air atmosphere . Human Wa RVA shedding was detected in rectal swab fluids using an antigen capture ELISA as described previously [63] , [64] , [87] . Virus infectious titer was assessed by CCIF assay as described previously [52] . Fluorescent cells were counted using a fluorescence microscope and titers were expressed as the number of fluorescent focus forming units per ml ( FFU/ml ) . The area under the virus shedding ( FFU/ml by CCIF ) curve through time ( PID ) ( AUC ) was calculated using statistical software and expressed as FFU/ml*day . First , the AUC for each piglet was determined and then the average AUC was calculated for the group . The VHH nanoAb titers to Wa RVA were quantified in the VP6-specific VHH nanoAb pool , supplemented milk , pig sera , rectal swab fluids , LIC and SIC . Briefly , 96 well ELISA plates ( Maxisorp , NUNC , Roskilde , Denmark ) were coated with 1∶10 , 000 dilution of RVA-specific guinea pig polyclonal serum at 37°C during 1 h and then incubated with 10% nonfat milk in PBS-Tween 0 . 05% for blocking of non-specific activity . The supernatants of semi-purified attenuated ( Att ) Wa RVA-infected ( 105 FFU/ml ) MA-104 cell culture lysates or mock infected MA-104 cell lysates were then added , followed by serial four-fold dilutions of the samples . VHH were detected using a rabbit polyclonal anti-VHH serum ( 1∶7 , 000 dilution ) . This rabbit antiserum was made in house , vaccinating the animal with a cocktail of several VHH nanoAbs . The plates were later incubated with commercial HRP-labeled goat polyclonal Abs to rabbit IgG at a 1∶2 , 000 dilution ( KPL , Kirkegaard & Perry Laboratories Inc . , Gaithersburg , USA ) at 37°C for 1 h . Hydrogen peroxide and 2 , 2′-azino-bis ( 3-ethylbenzothiazoline-6-sulphonic acid ( ABTS ) were used as substrate/chromogen system ( KPL , Kirkegaard & Perry Laboratories Inc . ) . The cut off point for the assay was established as the mean plus three standard deviations of the optical density measured in virus-coated PBS wells ( blank ) . The IgY Ab titers to Wa RVA were determined in hen sera , crude egg yolks , purified IgY pools , supplemented milks , pig sera , rectal swabs , LIC , and SIC by an indirect ELISA as described elsewhere [53] . The cut off point for the assay was established as the mean plus three standard deviations of the optical density measured in virus-coated PBS wells ( blank ) . The IgM , IgA and IgG Ab titers to Wa RVA were quantified in the Wa RVA porcine IgG Ab pool , pig sera , rectal swab fluids , LIC , and SIC . Specific Abs to Wa RVA were detected by an indirect ELISA using the reagents and protocol described previously [63] , [64] , [82] . The cut off point for the assay was established as mean plus three standard deviations of the optical density measured in virus-coated PBS wells ( blank ) . The IgG Ab titers to recombinant VHH were quantified in the pig sera , rectal swab contents , LIC , and SIC . The IgA Ab titers to recombinant VHH were quantified only in rectal swab contents , LIC , and SIC . Briefly , 96 well ELISA plates ( Maxisorp , NUNC ) were coated with 1 µg per well of purified bivalent VHH nanoAbs ( provided by Algenex S . L . , Madrid , Spain ) and then incubated with 10% nonfat milk in PBS-Tween 0 . 05% for blocking of non-specific activity . Serial four-fold dilutions of porcine serum , rectal swab contents or intestinal content samples were incubated for 1 h at 37°C . The plates were later incubated with commercial HRP-labeled goat polyclonal Abs to porcine IgA at 1∶3000 dilution ( AbD Serotec Inc . , Raleigh , USA ) or with commercial biotin-labeled goat polyclonal Abs to porcine IgG at a 1∶20 , 000 dilution ( KPL , Kirkegaard & Perry Laboratories Inc . ) for 1 h at 37°C . The wells that contained commercial anti-pig IgG Ab were later incubated with commercial HRP-labeled streptavidin ( 1∶10 , 000 ) ( Sigma-Aldrich , Munich , Germany ) for 1 h at 37°C . Hydrogen peroxide and ABTS were used as substrate/chromogen system ( KPL , Kirkegaard & Perry Laboratories Inc . ) . This ELISA was also performed using a second set of reagents ( HRP-labeled commercial anti-pig IgG Ab from KPL , Kirkegaard & Perry Laboratories Inc . ) to confirm the results obtained . The cut off point for the assay was established as the mean plus three standard deviations of the optical density measured in virus-coated PBS wells ( blank ) . The ELISA used to detect porcine Abs against VHH nanoAbs in the present study was analytically validated against positive control sera from animals systemically immunized with a pool of VHH nanoAbs . This assay was able to detect the presence of VHH -specific Abs in this samples that were then considered positive controls for each assay performed . The IgG Ab titers to chicken IgY were quantified in the pig sera , LIC , and SIC . The IgA Ab titers to IgY Ab were quantified only in LIC and SIC . Specific Abs to IgY Ab treatment were detected by an indirect ELISA using the reagents and protocol described previously [53] . The ELISA used in the present study to detect porcine Abs against IgY Ab was analytically validated against positive control sera from animals systemically immunized with IgY Abs . This assay was able to detect the presence of IgY-specific Abs in this samples that were then considered positive controls for each assay performed . The VN Ab titers to Wa RVA in passive treatment pools , egg yolks , supplemented milks , and pig sera were determined by fluorescent focus neutralization ( FFN ) test as previously described [63] . For in vitro RVA fluorescent focus reduction assay using different RVA strains , a fourfold dilution of each VHH clone ( 3B2 or a non-related clone ) was mixed with an equal volume of RVA containing 100 DICT . The VN titer was expressed as the reciprocal of the highest sample dilution that resulted in >80% reduction in the number of fluorescent foci . The 80% reduction criterion was selected in order to be more stringent than in protocols considering only 50% reduction . Tissue samples of duodenum , jejunum , and ileum lamina propria were collected . The MLNs were collected and processed separately . The MNCs from blood and spleen were extracted to evaluate ASC responses in systemic lymphoid tissues . All the MNC suspensions were obtained as previously described for pig tissues and blood [82] and the purified cells from all tissues and blood were resuspended to a final concentration of 5×106 MNC/ml in RPMI-1640 ( GIBCO ) supplemented with 10% FBS , 20 mM HEPES , 2 mM Glutamine , 1 mM sodium pyruvate , 0 . 1 mM non-essential amino acids , 100 IU/ml penicillin , 67 mg/ml streptomycin and 50 mg/ml gentamycin ( E-RPMI ) . The cell viability of each MNC suspension was assessed by Trypan blue exclusion ( in all cases it was >90% ) . An ELISPOT assay for quantification of Wa RVA specific IgM , IgA , IgG ASC was conducted to evaluate effector B-cell responses from all piglets at PID 21 , as previously described [53] , [63] , [64] , [82] . The spots were developed with a tetramethylbenzidine peroxidase substrate system ( TMB , KPL , Kirkegaard & Perry Laboratories , Inc . ) . Fisher's exact test was used to compare proportions of animals with diarrhea and virus shedding among groups . The Kruskall-Wallis rank sum test ( non-parametric ) was used to compare days of onset and duration of diarrhea and virus shedding , cumulative diarrhea scores and cumulative titers of virus shed ( area under the curve , AUC ) among groups that were recorded from PID 0 to 21 . Negative samples at a dilution of 1∶4 were assigned an arbitrary Ab titer of 2 for the calculation of geometric mean titers ( GMTs ) . Neutralizing and isotype-specific Ab titers were log10-transformed prior to statistical analysis . Differences in Ab titers among groups were evaluated by comparison of means at four different time-points post virus inoculation ( PID 0 , 7 , 14 , 21 ) . Multiple comparison test of repeated measures throughout time was done following Akaike criteria for the selection of covariance matrices [88] , [89] . In further comparisons of treatments and post virus inoculation time-points , Šidák's correction was applied [90] . At PID 21 , the ASC numbers were compared among groups using the Kruskall-Wallis rank sum test . Statistical significance was assessed at p<0 . 05 for all comparisons . Statistical analyses were conducted using Infostat statistical software and MedCalc version 11 . 1 . 1 . 0 statistical software . Statistical analysis is available upon request .
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Group A rotavirus ( RVA ) is the most common cause of severe diarrhea in human infants worldwide . Live-attenuated rotavirus vaccines are available to prevent rotavirus diarrhea in children , although their efficacy in impoverished areas has been questioned , in addition to not being suitable for children suffering from immune deficiencies . Since no rotavirus-specific treatments are available as an alternative , we investigated llama-derived single-chain antibody fragments ( VHH ) as preventive therapy and a potential treatment option . Gnotobiotic piglets were chosen as an animal model because their gastrointestinal physiology and mucosal immune system resemble that of human infants . We evaluated the broad neutralizing activity of a VHH clone ( 3B2 ) to different genotypes of RVA circulating in humans , and tested the efficacy of oral administration of 3B2 VHH as a functional milk to prevent the diarrhea induced by one of the most prevalent human RVA strains ( G1P[8] ) . Supplementation of the milk diet with 3B2 twice a day for 9 days conferred full protection against rotavirus-associated diarrhea and significantly reduced virus shedding in gnotobiotic piglets experimentally inoculated with a human RVA . This study demonstrates the potential application of VHH to prevent rotavirus-induced diarrhea , and suggests that VHHs should be further investigated as a suitable treatment for gastroenteritis .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"medicine",
"infectious",
"diseases",
"viral",
"diseases",
"rotavirus",
"infection"
] |
2013
|
Recombinant Monovalent Llama-Derived Antibody Fragments (VHH) to Rotavirus VP6 Protect Neonatal Gnotobiotic Piglets against Human Rotavirus-Induced Diarrhea
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New interventions tools are a priority for schistosomiasis control and elimination , as the disease is still highly prevalent . The identification of proteins associated with active infection and protective immune response may constitute the basis for the development of a successful vaccine and could also indicate new diagnostic candidates . In this context , post-genomic technologies have been progressing , resulting in a more rational discovery of new biomarkers of resistance and antigens for diagnosis . Two-dimensional electrophoresed Schistosoma mansoni adult worm protein extracts were probed with pooled sera of infected and non-infected ( naturally resistant ) individuals from a S . mansoni endemic area . A total of 47 different immunoreactive proteins were identified by mass spectrometry . Although the different pooled sera shared most of the immunoreactive protein spots , nine protein spots reacted exclusively with the serum pool of infected individuals , which correspond to annexin , major egg antigen , troponin T , filamin , disulphide-isomerase ER-60 precursor , actin and reticulocalbin . One protein spot , corresponding to eukaryotic translation elongation factor , reacted exclusively with the pooled sera of non-infected individuals living in the endemic area . Western blotting of two selected recombinant proteins , major egg antigen and hemoglobinase , showed a similar recognition pattern of that of the native protein . Using a serological proteome analysis , a group of antigens related to the different infection status of the endemic area residents was identified and may be related to susceptibility or resistance to infection .
Schistosomiasis is one of the most important parasitic diseases , being prevalent in 76 countries [1] . Despite many control efforts , mainly after the introduction of a chemotherapeutic treatment in 1980s , the disease is still highly prevalent [2] . The control of the main medically important species Schistosoma mansoni , Schistosoma japonicum and Schistosoma haematobium is based on the use of praziquantel , the only drug available for chemotherapy [3] . The use of the chemotherapy has a clear effect on morbidity [4] , [5] . However , repeated mass drug administration has exerted selective pressure on parasite population and resistance to praziquantel is being described by different investigators [6] . The development of long-term protection based on vaccination would be of significant benefit for disease control [7] . Despite a large body of research in this area and one ongoing clinical trial [8] , there is no effective vaccine against schistosomiasis . Together with the fact that mass drug administration has been applied widely and the increasing drug pressure on the parasite population , it becomes more evident the need to find alternative methods of schistosomiasis control/elimination . In this context development of an effective vaccine is a plausible alternative . The lack of understanding of the protective immunological mechanisms , and the difficulty in identifying antigens which stimulate such a response , remain the major barriers towards the development of anti-schistosome vaccines [9] . Many single antigens with potential use as a vaccine have been proposed , but most have showed disappointing results even with different immunization schemes and experimental models [10] , [11] . Nevertheless , distinct observations in animals and humans indicate that it is feasible to achieve protection against infection . Significant levels of protection were obtained in experiments with irradiated cercariae [12] and with some recombinant antigens [13]–[16] . Furthermore , several reports from our group and others have suggested that resistance to infection is acquired naturally or drug induced [17]–[21] . In our studies specifically , we have shown that resistance may develop naturally in endemic areas , describing a group of individuals , that live in areas where transmission is active but do not get infected , called Endemic Normals [22] . These individuals were defined using specific criteria such as being S . mansoni egg-negative over 5 years despite continuous exposure to contaminated water , no previous treatment with anthelmintic drugs and having vigorous cellular and humoral immune response to crude schistosome antigen preparations [23] , [24] . The immune response of individuals with natural resistance to schistosomiasis differs significantly from that of post-treatment resistant and infected individuals [17] . The immunological mechanisms that prevent the infection in drug-induced and naturally resistant individuals living in endemic areas for schistosomiasis may constitute the basis for the development of a successful vaccine [7] , [25] , [26] . Therefore , we believe that using the most recent technology to identify antigens reactive to antibodies from resistant individuals , both natural and drug induced , we will be able to screen at a much faster pace for putative protective antigens . Schistosomiasis control will benefit from a vaccine , but a new generation of diagnostic tools is as much a part of any control and eradication strategy . Available tools , especially fecal exams , encounter limitations in low parasitic load and low infection rates settings and in the follow-up to treatment [27] , [28] . The next generation of assays needs to be simple , inexpensive , fast , sensitive , specific and capable of distinguishing active from prior infection [28] , [29] . The empirical science used in the last decades is strikingly changing with the use of high throughput global approaches to a less biased , and more encompassing development for the proposition of new biomarkers to the discovery of vaccine candidates , drug and diagnostic targets [24] , [25] , [30] . Significant progress has been made in S . mansoni and S . japonicum proteomic studies , mainly with the description of proteins differentially expressed in the different life cycle stages of the parasite [31]–[33] , between male and female worms [34] and irradiated and normal cercariae [35] . Furthermore , proteomic studies have concentrated mainly on the studies of proteins exposed on the parasite surface and readily accessible to the host , i . e . identification of tegumental proteins [36]–[42] or secreted/excreted proteins [38] , [43]–[49] . A combination of proteomic and serological analyses has been used as a promising experimental approach for screening new biomarkers candidates to different diseases , identifying proteins useful for diagnosis , therapy and vaccine design [50]–[54] . A limited number of studies have performed serological-proteomic analysis using schistosome proteins . Serum of experimentally infected animals was used to screen antigens of S . japonicum in two-dimensional electrophoresis ( 2-DE ) in an attempt to identify suitable antigens for diagnostic purposes , identifying four proteins out of 30 immunoreactive protein spots [30] . Comparative proteomic and immunological analysis of S . haematobium , S . bovis and Echinostoma caproni revealed some common cross-species antigens and species-specific targets [55] . Additional studies using S . mansoni immunoprecipitated proteins from protective and non-protective rat serum analyzed by 2-DE showed four spots specifically reactive with the protective rat serum [56] . High and low worm burden serum from infected Rhesus macaques were used to probe S . mansoni gut secretions and tegument surface proteins in 2-DE . The study identified gut digestive enzymes , tegument surface hydrolases and antioxidant enzymes as IgG targets of the IgG high titer serum of low burden animals [57] . The use of infected human serum was conducted only for S . haematobium , where a total of 71 immunoreactive protein spots were identified as 26 different proteins [58]–[60] . Although important observations have been made in relation to schistosome antigen identification , a human schistosomiasis mansoni coherent screening for new antigens is still necessary . In the present study we used , for the first time , serum antibodies of infected and naturally resistant individuals from a S . mansoni endemic area to compare the recognition profiles of adult worm antigens by these serum antibodies using two-dimensional Western blotting . We identified a total of 47 S . mansoni antigenic proteins . We also observed that some of the antigens were differentially recognized by antibodies of infected and naturally resistant individuals . This panel of antigens may constitute an informative source for the improvement of diagnostic tools and vaccine development to schistosomiasis .
This research was approved by the Ethics Committee for Human Research of CPqRR – FIOCRUZ ( CAAE: 1 . 0 . 245 . 000-08 ) . Written informed consent was obtained from all participants at the time of the stool collection . All procedures involving animals were conducted in compliance with the Manual for the Use of Animals/FIOCRUZ and approved by the Ethics Committee on the Use of Experimental Animal ( CEUA – FIOCRUZ ) license number LW-17/09 . BALB/c mice were infected by the subcutaneous route with 100 S . mansoni cercariae of the LE strain . After 45 days , adult worms were recovered by perfusion of the portal mesenteric system , as described by Pellegrino and Siqueira [61] . The adult worms were washed three times in RPMI medium ( SIGMA ) , snap frozen in liquid nitrogen and stored at −70°C until use . S . mansoni adult worm total protein extract ( AW-TOT ) was obtained from direct lysis of the parasites in lysis buffer [8 M Urea , 2 M Thiourea , 4% 3-3-Cholamidopropyl-dimethylammonio-propane-sulfonate ( CHAPS ) , 50 mM dithiothreitol ( DTT ) , 20 mM Tris and Complete Mini Protease Inhibitor Cocktail Tablets ( Roche ) ] . After homogenization under continuous agitation for 2 hours at room temperature , followed by 10 repeated passages through a 30-gauge hypodermic needle , the homogenate was centrifuged at 20 , 000×g for 30 min at 25°C and the supernatant was collected and stored at −70°C until use . S . mansoni adult worm tegument protein extract ( AW-TEG ) was obtained by freeze/thaw/vortex method in Tris Buffered Saline ( TBS ) supplemented with Complete Mini Protease Inhibitor Cocktail Tablets , according to Roberts and co-workers [62] with some modifications . Briefly , after thawing on ice , the outer tegumental membrane complex was removed by ten 1 second vortex pulses at maximum speed . All the supernatant content , obtained after decanting the stripped worms , was passed through a 30-gauge hypodermic needle 10 times and then concentrated using a 3 kDa cutoff centrifuge filter ( Millipore ) . Next , acetone precipitation was performed and the pellet was solubilized in SBI buffer [7 M Urea , 2 M Thiourea , 15 mM 1 , 2-diheptanoyl-sn-glycero-3-phosphatidylcholine ( DHPC ) , 0 . 5% Triton X-100 , 20 mM DTT and Complete Mini Protease Inhibitor Cocktail Tablets] , as described by Babu and co-workers [63] , and stored at −70°C until use . Protein concentration of both protein extracts was measured by the Bradford method [64] and the quality of the extracts was verified by SDS-PAGE 12% [65] . The human serum samples were obtained from a rural population of the Virgem das Graças village ( VDG ) . This is a hyperendemic area for schistosomiasis located in the Jequitinhonha Valley in northern Minas Gerais State , Brazil . In VDG there is no treated water or basic sanitation and water contact was determined by direct observation and translated to Total Body Minutes ( TBM ) . Stool samples were processed by the Kato-Katz method to detect eggs of S . mansoni and other intestinal helminthes . Two slides from each stool sample collected in three consecutive days were used for quantification of number of eggs/gram of stool [66] . In the present study , the serum samples were chosen according to the following criteria: individuals not infected by other helminthes ( Ascaris lumbricoides , Trichuris trichiura and Ancylostoma ) , between 20–50 years of age , man or non-pregnant women . Individuals positive for S . mansoni eggs at the start of the study in 2001 were called Infected Individuals ( INF ) , and those who were egg negative in the three years of the study ( 2001 , 2002 and 2006 ) were identified as Non-Infected Individuals from Endemic Area ( NE ) . All the serum samples used in this study were obtained at the initiation of the study in January 2001 , before mass chemotherapy with praziquantel was administered . Serum samples of 13 INF , who had 8 to 304 eggs/gram of stool , and 9 NE were used ( Table 1 ) . Sera of Non-Infected volunteers from non-endemic sites ( NI ) were also used in this study , 7 from USA or 2 from UK sites . For each two-dimensional-polyacrylamide-gel-electrophoresis ( 2D-PAGE ) , 100 µg of proteins from AW-TOT or AW-TEG extracts were used . The AW-TOT proteins were solubilized in IEF rehydration buffer [8 M Urea , 2 M Thiourea , 4% CHAPS , 0 . 0025% bromophenol blue , 65 mM DTT and 1% BioLyte 3–10 buffer 100× ( Bio-Rad ) ] and the AW-TEG proteins in SBI buffer supplemented with 0 . 0025% bromophenol blue and 0 . 4% BioLyte 3–10 buffer 100× ( Bio-Rad ) [63] , both to 125 µl final volume . After homogenization under continuous agitation for 1 hour at room temperature , the samples were centrifuged at 16 , 000×g for 30 min . The supernatants were loaded onto 7 cm IPG strip 3–10 , 3–10NL or 5–8 pH ranges ( Bio-Rad ) by in-gel sample rehydration . Isoelectric focusing was carried out in a Protean IEF Cell ( Bio-Rad ) at 20°C and 50 µA/strip . Passive rehydration was performed for 4 hours , followed by active rehydration at 50 V for 12 hours , and focalization at 500 V for 30 min , followed by 1 , 000 V for 30 min , 4 , 000 V for 1 hour and 4 , 000 V up to 16 , 000 V/h . The IPG strips were equilibrated in reducing buffer ( 6 M Urea , 30% glycerol , 2% SDS , 50 mM Tris-HCl pH 8 . 8 , 0 . 001% bromophenol blue and 130 mM DTT ) for 10 min , and in alkylating buffer containing 135 mM iodoacetamide for a further 10 min . The IPG strips and molecular weight standard were placed on top of 12% SDS-PAGE gels and sealed with 0 . 5% agarose . The second dimension electrophoretic protein separation was carried out using a Mini-Protean III ( Bio-Rad ) under 60 V constant voltage for 10 min , and then under 100 V until the dye front reached the bottom of the gel . For each 2-DE experiment , at least two 2D-PAGEs were performed in parallel , one to be used in a Western blotting experiment and another corresponding 2D-PAGE to be stained by Colloidal Coomassie Blue G-250 for spot excision and protein identification . The 2D-PAGEs were immediately transferred to a PVDF-based membrane ( Immuno-blot 0 . 2 µm , Bio-Rad ) using a Trans-Blot Electrophoretic Transfer Cell ( Bio-Rad ) at 100 V ( 2–3 mA cm2 ) for 120 min with transfer buffer ( 25 mM Tris-Base , 192 mM glycine , 20% methanol ) . The membranes were washed in water and air-dried . Before proceeding with Western blotting , the membranes were re-activated in 100% methanol and blocked for 16 hours in TBS ( 20 mM Tris-HCl , 500 mM NaCl , pH 7 . 5 ) containing 0 . 05% Tween-20 and 3% BSA ( TBS-T/3% BSA ) at room temperature . Each membrane was incubated separately for 2 hours with each pool of INF , NE or NI ( from USA volunteers ) sera diluted 1∶500 in TBS-T/1% BSA . After 2×30 min washes in TBS-T/1% BSA , the membranes were incubated with goat anti-human Ig's polyvalent antibody , HRPO conjugated ( Caltag Laboratories ) , diluted 1∶100 , 000 in TBS-T/1% BSA . After 2×30 min washes in TBS-T and 1×15 min wash in TBS , the immunoreactive proteins were developed using ECL Plus Western Blotting Detection System ( GE Healthcare ) and the membranes were exposed for 16 hours to X-Ray film . All the 2D-WB experiments were performed in triplicate . The X-Ray films and its corresponding Colloidal Coomassie Blue stained 2D-PAGE were overlapped . The antigenic protein spots were manually and individually excised from the corresponding 2D-PAGE for mass spectrometry identification . First , spots were washed in Milli-Q water , and then destained 2×15 min in 50% acetronitrile ( ACN ) /25 mM ammonium bicarbonate ( AB ) pH 8 . 0 until clear of blue stain . The gel fragments were dried in 100% ACN for 5 min , followed by rehydration in 100 mM AB for 5 min and addition of same volume of 100% ACN . The solution was removed and 100% ACN was added again . After removing the ACN , the spots were completely dried in a Speed Vac Concentrator Plus ( Eppendorf ) for 20 min . The final dried spots were re-swollen in 10 µl of 20 µg/ml Sequencing Grade Modified Trypsin ( Promega ) in 25 mM AB for 10 min and then , additional 10 µl of 25 mM AB were added . Protein digestion was conducted at 37°C for 16 hours . After the incubation , the supernatant was transferred to a clean tube and 30 µl of 5% formic acid ( FA ) /60% ACN were added to gel spots for the extraction of the tryptic peptides . This procedure was performed 2×30 min under constant agitation . The supernatant was pooled to the respective tube containing the initial peptide solution . This solution was dried in a Speed Vac and the peptides were resuspended in 8 µl of 0 . 1% FA . The peptides were desalted in reverse phase micro-columns Zip Tip C18 ( Millipore ) , according to manufacture instructions . Peptides were dried again and resuspended in 1 µl of 50% ACN/0 . 1% trifluoracetic acid ( TFA ) solution . MALDI-ToF-ToF analysis was performed on the 4700 Proteomics Analyzer ( Applied Biosystems ) . Briefly , 0 . 5 µl of the micro-column eluate was mixed with 0 . 2 µl of alpha-cyano-4-hydroxycinnamic acid matrix ( 20 mg/ml in 30% ACN/0 . 3% TFA ) . Samples were spotted onto the ABI 192-targed MALDI plate by co-crystallization and mass spectrometry data were acquired in positive and reflectron mode , mass range 900–4 , 000 Da , using a neodymium-doped yttrium aluminum garnet ( Nd: YAG ) laser with a 200-Hz repetition rate . Typically , the analyses were conducted using 2 , 000 shots of MS and 4 , 000 shots of MS/MS to the 10 most abundant ions . External calibration was performed using a mixture of four peptides: des-Arg1-bradykinin ( m/z = 904 . 47 ) , angiotensin I ( m/z = 1296 . 69 ) , Glu1-fibrinopeptide B ( m/z = 1570 . 68 ) and adrenocorticotropic hormone ( 18–39 ) ( m/z = 2465 . 20 ) ( mass standards kit for the 4700 Proteomics Analyzer ) . The list of peptide and fragment mass values generated by the mass spectrometer for each spot were submitted to a MS/MS ion search using MASCOT ( Matrix Science , Boston , MA ) to search in the NCBInr database . The parameters used were: allowance of two tryptic miss cleavages , peptide error tolerance of ±0 . 6 Da , MS/MS error tolerance of ±0 . 2 Da , peptide charge +1 and variable modifications of methionine ( oxidation ) , cysteine ( carbamidomethylation and propionamidation ) . To avoid random matches , only ions with individual score above of the indicated by the MASCOT to identity or extensive homology ( p<0 . 05 ) were considered for protein identification . To those protein matches obtained from NCBInr search that did not retrieve a Smp number , a blastp search was conducted using the SchistoDB database Version 2 . 0 ( www . schistodb . net ) [67] . Hierarchical clustering was performed with the identified immunoreactive proteins according to similarities in recognition profile with each pool of serum used in this study , in three two-dimensional Western blotting assays . Recognition profile similarity was measured by the Euclidean distance , with complete-linkage among samples , using the Hierarchical Clustering ( HC ) algorithm available at the GenePattern Platform [68] . The S . mansoni hemoglobinase precursor ( Smp_075800 ) and major egg antigen ( Smp_049300 . 3 ) were expressed using a wheat germ cell-free expression system ( TNT SP6 High-Yield Wheat Germ Protein Expression System , Promega ) by coupled in vitro transcription-translation . The coding region of the corresponding genes were obtained by PCR amplification using a previously constructed S . mansoni adult worm cDNA library as template . Primers were designed using the Flexi Vector Primer Designer Tool ( Promega ) , adding an extra C-terminal histidine tag . The primers used to amplify the coding region of major egg antigen and hemoglobinase genes were as follow: forward ( 5′-GGCTGCGATCGCCATGTCTGGTGGGAAACAACATA-3′ ) and reverse ( 5′-TGATGTTTAAACGTGGTGGTGGTGGTGGTGAGTAATTGCATGTTGCTT-3′ ) , and , forward ( 5′-CCTGGCGATCGCCATGGTATCCGATGAAACTGTTAGTGA-3′ ) and reverse ( 5′- TGATGTTTAAACGTGGTGGTGGTGGTGGTGACCGCAAATTTTTATGATTGCT-3′ ) , respectively . PCR reactions were composed of 25 µl JumpStart REDTaq ReadyMix Reaction Mix ( Sigma-Aldrich ) , 2 . 5 µl of each gene specific forward and reverse primer ( 10 µM ) , 2 µl of S . mansoni adult worm cDNA library in 50 µl final volume . The purified PCR products were inserted into pF3A WG ( BYDV ) Flexi Vector ( Promega ) using the Flexi Vector System ( Promega ) and the plasmids were transformed into electrocompetent DH5α Escherichia coli cells by electroporation . Colonies were selected and grown in LB-Amp broth . Plasmids were purified using QIAprep Spin Miniprep Kit ( Qiagen ) and verified by DNA sequencing using the SP6 and T7 terminator primers ( Source Bioscience , Nottingham , UK ) . Protein synthesis was initiated by adding the DNA plasmids as template according to the instructions described in the TNT SP6 High-Yield Wheat Germ Protein Expression System protocol . Protein expression was analyzed by the incorporation of labeled lysine residues ( FluoroTect GreenLys , Promega ) loading 5 µl of the reaction in 4–20% Mini-PROTEAN TGX Precast Gel ( Bio-Rad ) and detecting with a laser-based fluorescent gel scanner ( Fujifilm LAS-4000 Imaging System ) . For Western blotting analyzes , 3 µl of the protein synthesis reaction were blotted onto 0 . 45 µm nitrocellulose membranes after electrophoresis . The membranes were blocked for 16 hours in TBS-T/3% nonfat dry milk and then incubated separately for 2 hours with each pool of INF , NE or NI ( from UK volunteers ) sera diluted 1∶500 in a pre-adsorbed solution . These serum pools were pre-adsorbed for 16 hours in TBS-T/3% nonfat dry milk and 5% wheat germ protein extract . After 2×30 min washes in TBS-T/1% nonfat dry milk , membranes were incubated with rabbit anti-human IgG antibody ( Sigma ) diluted 1∶10 , 000 in TBS-T/1% nonfat dry milk for 1 hour and with anti-rabbit IgG HRP conjugated ( ECL Plus Western Blotting Reagent Pack , GE Healthcare ) in the same conditions , with 2×30 min washes between antibodies incubations . The membranes were revealed using ECL Plus-Western Blotting Detection System ( GE Healthcare ) and the proteins were visualized by chemiluminescence detection using a Fujifilm LAS-4000 Imaging System .
S . mansoni adult worm total and tegumental protein extracts were used initially in 2D-WB in order to evaluate the antigenicity of proteins using total immunoglobulins in pooled sera of S . mansoni infected individuals . Firstly , Colloidal Coomassie Blue stained 2D-PAGEs were conducted using different IPG strip pH ranges ( 3–10 , 3–10NL and 5–8 ) in order to visualize the separation pattern of the AW-TOT protein extract . All the different IPG strip pH ranges used showed good resolution of the spots and minimal streaking . Protein spots were reproducibly resolved in a broad pH range and molecular weight ( Figure 1A ) . Corresponding 2D-WB using each of the IPG strip pH ranges were performed to determine which pH range would better separate the immunoreactive protein spots when using pool of INF serum against AW-TOT protein extract . The use of IPG strip 3–10 , 3–10NL and 5–8 pH ranges showed that distinct antigenic spots were evidenced when resolved by different IPG strip pH ranges ( Figure 1B ) . Although most of the antigenic proteins were common among all the IPG strip pH range used , some proteins were exclusively identified in specific IPG strip pH range , contributing to increase the total number of identified immunoreactive proteins ( Table 2 ) . AW-TEG protein extract was also used in an attempt to enrich the analysis with immunologically exposed parasite proteins . The AW-TEG protein extract was separated in pH 3–10 IPG strip and it was observed a distinct 2D-PAGE and 2D-WB pattern to the AW-TOT protein extract , although there are some common immunoreactive protein spots in both extracts ( Figure 1 ) . When the 2D-WB X-Ray films and the corresponding Colloidal Coomassie Blue stained 2D-PAGEs were overlapped it was observed that there was no direct correlation between the amount of protein in the AW-TOT and AW-TEG protein extracts and its antigenicity level . Although the most of immunoreactive spots recognized by the INF serum were visible in its corresponding 2D-PAGE , there were some strongly stained protein spots that showed weak or no immunoreactivity ( dashed circles in Figures 1A and 1B ) . Conversely , there were some barely visible protein spots in the 2D-PAGE that were highly immunoreactive ( circles in Figures 1A and 1B ) . Most of the immunoreactive protein spots show a pI above 6 . 5 and molecular weight above 25 kDa . Immunoreactive spots visualized in each of the pH ranges were excised from the corresponding Colloidal Coomassie stained 2D-PAGE for proteins identification by mass spectrometry ( MS/MS ) . A total of 37 immunoreactive spots were excised from the 2D-PAGE using AW-TOT protein extract and pH 3–10 IPG strip . Additional 37 and 39 spots were excised from the 2D-PAGE using the pH 3–10NL IPG strip and the pH 5–8 IPG strip , respectively . From the 2D-PAGE using AW-TEG protein extract , 36 immunoreactive spots were excised . Some of the protein spots could not be identified by MS/MS . Using AW-TOT protein extract and pH 3–10 and pH 5–8 IPG strips , 7 and 14 immunoreactive spots were not MS/MS identified , respectively . Two immunoreactive spots from the 2D-PAGE using AW-TEG protein extract were also not identified ( gray circles in Figure 1C ) . A total of 47 different S . mansoni immunoreactive proteins were identified . Using AW-TOT protein extract 22 , 29 and 18 proteins were identified from 2D-PAGE of pH 3–10 , pH 3–10NL and pH 5–8 , respectively . AW-TEG protein extract yielded 25 proteins identified from 2D-PAGE of pH 3–10 . Most proteins were identified in more than one pH range , but others were exclusive . Additionally , 9 immunoreactive proteins were identified only in AW-TEG protein extract ( Figure 2 ) . All proteins identified by mass spectrometry in at least one 2D-WB experiment were included ( Table 2 ) . In some cases , as the result of post-translational modifications , splice variants or paralogue genes , for example , the same protein description was identified for different immunoreactive spots , but a representative gene ID was used . In order to identify antigens differentially recognized by antibodies from pooled sera of S . mansoni infected ( INF ) and non-infected ( NE ) individuals from the endemic area , 2D-WB experiments were performed using both serum pools . A serum pool of non-infected individuals from a non-endemic area ( NI ) was also used . AW-TOT and AW-TEG protein extracts were focused using pH 3–10 IPG strips . Four 2D-PAGEs were electrophoresed simultaneously . Three of them were used in the 2D-WB with the three serum pools separately ( INF , NE , NI ) . The fourth gel was stained with Colloidal Coomassie for spot excision and MS/MS identification . Quantitative variations on the reaction intensity of the immunoreactive spots were observed among the 2D-WB using the same dilution of the three pooled sera . However , a similar overall pattern of reactive spots was observed , but with higher signal intensity when using the INF serum pool when compared to the NE , which in turn showed higher signal intensity than NI serum pool ( Figure 3 ) . Qualitative variations of the immunoreactive spots were also visualized among the 2D-WB . Using AW-TOT and AW-TEG protein extracts it was observed that 9 spots were detectable exclusively with the INF serum pool and a single spot exclusively with the NE serum pool ( Table 3 ) . From those that reacted only with the INF serum pool , some strong immunoreactive spots of 40 kDa with approximately pI 7 . 0 were observed , as indicated by a circle in Figure 3 . Interestingly , the corresponding spots in the 2D-PAGE were weakly stained ( Figure 1A ) . The spots excised from this region in the 2D-PAGE were identified as major egg antigen , annexin and troponin T proteins . Two spots corresponding to major egg antigen were identified in all the triplicate assays of both AW protein extracts ( spots 14 and 15 in Figure 4 and Table 3 ) . One extra spot of the major egg antigen was identified in all triplicate assays of AW-TEG protein extract ( spot 42 in Figure 4 and Table 3 ) . The presence of major egg antigen was confirmed in all of the IPG strip pH ranges using the INF serum pool ( Table 2 ) . Annexin was identified in all triplicate assays of the AW-TEG protein extract , but major egg antigen was co-extracted in the same spot as they co-migrate ( spot 41 in Figure 4 and Table 3 ) . Two spots corresponding to troponin T were identified in the AW-TOT protein extract ( spots 31 and 32 in Figure 4 and Table 3 ) . However , they were not present in all 2D-WB triplicate experiments , two experiments showed the spot 32 and one , the spot 31 ( Figure 4 and Table 3 ) . Other two spots , also immunoreactive only with the INF serum pool , were localized above 60 kDa , within a pH range 6 . 0 and 7 . 0 in the triplicate of AW-TEG protein extract , as pointed by arrows in the Figure 3 . The corresponding proteins were identified as disulphide isomerase ER-60 precursor and filamin ( spots 44 and 45 , respectively , in Figure 4 and Table 3 ) . From spot 21 indicated by the arrowhead in the Figure 3 , two proteins were co-excised: actin and reticulocalbin ( Figure 4 and Table 3 ) , with low pI and at approximately 45 kDa . This spot was immunoreactive in the triplicate of AW-TEG protein extract and in one of the triplicate 2D-WB experiment of the AW-TOT protein extract when probed with INF serum pool ( Figure 3 ) . The transketolase ( spot 24 in Figure 4 and Table 3 ) was identified as an immunoreactive spot exclusively when probed with INF serum pool in one 2D-WB experiment of the AW-TOT triplicate . However , in two 2D-WB experiments of the AW-TEG triplicate this protein was immunoreactive to both INF and NE serum pools . Only one immunogenic spot reacted exclusively with NE serum pool in two 2D-WB experiments of the AW-TEG triplicate . This spot of approximately 33 kDa and pI 8 . 0 , as indicated by a dotted circle in Figure 3 , corresponds to eukaryotic translation elongation factor ( spot 40 in Figure 4 and Table 3 ) . Although highly immunoreactive , this protein showed a low expression levels in AW-TEG protein extract ( Figures 3 and 4 ) . All the immunoreactive proteins were clustered by Euclidean distance with complete-linkage method according to reactivity pattern against INF , NE and NI serum pools in triplicate assays with AW-TOT ( Figure 5A ) and AW-TEG ( Figure 5B ) . Using the heat map representation , the proteins which reacted exclusively with antibodies from the INF serum pool were clustered , and it was highlighted that the protein recognition pattern by NE and NI serum pools is closer than the NE and INF serum pools ( Figures 5A and 5B ) . Two proteins identified in the 2D-WB experiments were selected for further validation of the immunoreactive pattern to the serum pools as recombinant protein expressed in a cell free in vitro system . The major egg antigen ( MjE ) was selected since it was identified in several spots immunoreactive only to the INF serum pool in the 2D-WB experiments ( spots 14 , 15 , 41 and 42 in Table 3 ) using AW-TOT and AW-TEG protein extracts . The hemoglobinase precursor ( Hem ) was also selected since it was identified using all serum pools in the 2D-WB ( spot 11 in Table 3 ) . The coding region of the genes encoding these proteins was successfully amplified by PCR using S . mansoni adult worm cDNA library as template . The amplified fragments were inserted into pF3A WG ( BYDV ) Flexi Vector and the sequences confirmed by DNA sequencing . The in vitro coupled transcription-translation using the wheat germ system showed to be a suitable approach for expression of these schistosome proteins . The expressed proteins were visualized in the SDS-PAGE with the expected theoretical molecular mass , 40 . 3 kDa for MjE and 47 . 7 kDa for Hem , including the 6×His-tag ( Figure 6A , lanes 1 and 2 , respectively ) . In the negative control reaction , without DNA template , two protein bands of approximately 17 kDa were observed , as well as in the reactions using the plasmids containing the coding region of MjE and Hem . These bands correspond to newly synthesized biotinylated translation products of the TNT SP6 High-Yield Master Mix , which incorporate the labeled amino acid FluoroTect GreenLys and are seen as background ( Figure 6A , lane 3 ) . In the reaction using no DNA plasmid template and no FluoroTect GreenLys no fluorescent translation products were observed ( Figure 6A , lane 4 ) . Western blotting analysis of recombinant proteins expressed by in vitro wheat germ expression system was performed using serum pool of S . mansoni infected ( INF ) and non-infected ( NE ) individuals from endemic area and also of non-infected volunteers ( NI ) . The recombinant proteins maintained the recognition pattern of INF and NE serum pools used in the 2D-WB experiments , confirming their correct identification and the maintenance of the antigenic epitopes in the in vitro expressed proteins . MjE remained strongly reactive when tested against the INF serum pool , and was non- or weakly reactive with NE serum pool . The Hem recombinant protein reacted with both INF and NE serum pools , however , with greater reaction intensity against the INF serum pool . Neither MjE nor Hem was recognized by antibodies present in NI serum pool . Interestingly , the NI serum pool from UK volunteers reacted with a higher molecular weight protein from wheat germ extract , even in the negative reaction control using no DNA plasmid template . This reactive band was not observed using serum pools of individuals from schistosomiasis endemic area ( Figure 6B ) .
S . mansoni adult worms can survive for decades in the hepatic portal system of the vertebrate host in spite of the parasites being constantly exposed to the host immune system and must , therefore , display effective strategies to evade the host immune response [69] . On the other hand , it has been well demonstrated that the development of protective immunity against schistosomes depends on both humoral and cell-mediated immunity [70] . In this study , we aimed to identify parasite antigens applying an approach that would enable the screening of a large number of antibody targets using serum of individuals residing in a schistosomiasis endemic area . This approach allowed the identification of antigens associated to the disease infection or resistance status . A number of Schistosoma serological-proteomic studies have already been performed . However , this is the first which was conducted with S . mansoni using human sera , including sera of resistant and susceptible infection individuals living in an endemic area , allowing a more rational screening for new tangible human biomarker discovery . Although these studies have searched for schistosome vaccine candidates , most of them were based on animal models , with the caveat that they may not be directly translatable to humans [26] . In addition , similar studies with S . haematobium may not correlate with S . mansoni , as there is considerable variability in immune responses to crude antigens from both parasites [71] , [72] . In this study we were able to identify 47 different antigenic proteins , a slightly larger number when compared to previous S . mansoni serological-proteomic studies . This can be attributed to the use of different IPG strip pH ranges and to the fact that all experiments in this study were performed in triplicate , increasing our chances of identifying new antigens . Although previous serological-proteomic studies were performed using protein extracts from other Schistosoma species and serum sources , some proteins were commonly identified such as HSP-70 , enolase , GAPDH , triose phosphate isomerase , fructose-bisphosphate aldolase , glutathione S-transferase 28 kDa , 14-3-3 protein [30] , [59] , [73] . Among the immunoreactive proteins several are related to housekeeping metabolic pathways , such as glycolysis , gluconeogenesis and citric acid cycle; protein synthesis and proteolysis; transport; response to stress; detoxification process; cytoskeleton organization . In addition , some proteins that have already been tested as vaccine candidates , such as triose phosphate isomerase [74] , glutathione S-transferase 28 kDa [75] , fatty acid-binding protein ( Sm14 ) [13] and superoxide dismutase [76] were also identified in this study . For this work we decided to detect total immunoglobulins from sera of the different groups of individuals , since there is no clear mechanism of immunity in human schistosomiasis that defines a class of immunoglobulin as key for an effective immune response . Although some studies indicate IgE as an important immunoglobulin in schistosome post-treatment resistance , a vaccine trial for other helminth with an antigen that induces high IgE response showed significant adverse events [17] , [77] . Therefore , we performed an analysis of all immunoreactive proteins regardless of immunoglobulin isotype using polyvalent anti-human Ig . Mutapi and co-workers [60] showed that there are qualitative and quantitative differences in S . haematobium antigen recognition profiles by human antibody isotypes ( IgA , IgE , IgG1 and IgG4 ) although the majority of the adult worm antigens were recognized by all of these four isotypes . In earlier experiments , Delgado and McLaren [78] showed that IgG1 and IgG3 were involved in protective immunity against S . mansoni infection in mice . To address this possibility , we also preliminarily assayed for reactivity using anti-IgG1 and IgG3 in our serological screening . However we could not observe any significant differences in the antigenic pattern of INF , NE and NI sera recognition ( data not shown ) . Tegumental protein extract of S . mansoni adult worm was used to enrich our analysis with proteins that are directly exposed to host immune response . Although a large number of proteins were identified in both AW-TOT and AW-TEG protein extracts , there are still some differences between these extracts to be explored . Using 1D SDS-PAGE and LC-MS/MS , van Balkom and co-workers [40] identified 429 proteins , from which only 43 were specific to the tegument . All the tegumental specific proteins identified in our study were also identified by these investigators , and the proteins filamin and hydroxyacylglutathione hydrolase were exclusively identified in the tegumental protein fraction in both studies . Although we have used detergent buffer to solubilize integral membrane proteins for 2-DE in the AW-TEG , we were not able to identify immunoreactive proteins with transmembrane domains , as indicated in the SchistoDB database [67] . Despite extensive research , the large-scale analysis of membrane proteins by 2-DE remains a difficult task [79] . It is critical that other methods for membrane protein extraction that allow separation by 2-DE are developed . Serum of non-infected volunteers from non-endemic schistosomiasis area showed immunoreactivity to some protein spots of AW-TOT and AW-TEG . It has been previously shown by Losada and co-workers [80] that the sharing of molecules among organisms is an expected finding since there are several functional molecules that are conserved during the process of evolution . These molecules may elicit immune responses between different species of various genera and is responsible for antigenic cross-reactivity . According to these findings , Escherichia coli and Saccharomyces antigens induce cross-reactivity with S . mansoni crude antigens , sharing T- and B-lymphocyte epitopes [81] , [82] . Nevertheless , in our study 12 schistosome specific protein spots were detected only when sera of INF and NE were used . Although most immunoreactive spots were visible in its corresponding 2D-PAGE , some highly immunoreactive protein spots were barely visible in the 2D-PAGE . Our analysis was conducted using only adult worm protein extracts , and there is a different level of protein expression during the life cycle of the parasite [31] , [83] . Major egg antigen protein spots showed to be highly immunoreactive in the 2D-WB to the INF serum pool , although poorly expressed in AW-TOT and AW-TEG protein extracts . When a comparative analysis of the S . mansoni proteome among the life cycle stages was described by Curwen and co-workers [31] , the major egg antigen was among the top 40 proteins expressed in egg protein extract ( SEA ) . Therefore , the high level of major egg antigen immunoreactivity with the INF serum is probably due to the host immune response to this highly expressed protein in the parasite eggs that is also present in other life cycle stages . As described by Wilson and Coulson [69] a single “magic bullet” has been shown not to be an efficient target for the development of a schistosomiasis vaccine . An antigen cocktail is suggested as a way to acquire protection . In line with this principle , in the current study we were able to cluster proteins with similar immunoreactivity pattern when using serum pools of infected or non-infected individuals . We observed that the major egg antigen , annexin , troponin T , filamin , disulphide-isomerase ER-60 precursor , actin and reticulocalbin proteins reacted exclusively with serum antibodies of the infected individuals and the eukaryotic translation elongation factor with antibodies present in the serum of the non-infected individuals from endemic area . The major egg antigen , or Smp40 , has been described as highly immunogenic in humans [84] . The cytokine profile obtained by PBMC from S . mansoni infected patients stimulated with purified Smp40 was associated with a reduction of granuloma formation and anti-pathology vaccine [85] . This protein was also previously suggested as a potential antigen to be used in an immunodiagnostic test , since it was effectively immunoprecipitated by S . mansoni infected human and chronically infected mouse serum [86] , [87] . As for the Smp40 protein expression across the parasite life cycle , Nene and co-workers [86] showed that Smp40 could be easily detected by Western blotting assays in adults , cercariae , schistosomulum and egg stages , when probed with serum raised against a p40 fusion protein . Furthermore , van Balkom and co-workers [40] in their S . mansoni tegumental proteomics study have identified the Smp40 in both , tegumental and stripped worms protein fractions . Filamin proteins are mechanical linkers for actin filaments and are also involved in signal transduction and transcription [88] , [89] . Filamin was previously identified in an immunoscreening of cercarial cDNA library using IgG fraction of rabbit antiserum raised against immature female worms . A polyclonal antiserum specific to recombinant S . mansoni filamin revealed a tegument associated fluorescence in adult worms that reacted mainly with a band of 84 kDa , instead of the 280 kDa as indicated by the RNA sequence [90] . The filamin protein spot that was identified in this study using S . mansoni adult worm tegument protein extract was approximately 80 kDa , suggesting that they are the same protein . Previous studies using IgG specific antibodies to the recombinant filamin showed 36 . 6% killing of schistosomula in vitro and in a DNA vaccine immunization filamin induced a mean of 50% protection in mouse following challenge with adult worms by surgical transfer [90] , [91] . Troponin T is one of the three protein subunits of the troponin complex that mediate Ca2+-regulation that governs the actin-activated myosin motor function in striated muscle contraction [92] . Troponin T was initially suggested to be a good candidate for use in the diagnostic test for Taenia solium . However , ELISA tests using pooled sera from cysticercosis-positive and negative patients showed disappointing results [93] . Troponin T was identified by van Balkom and co-workers [40] in a non-tegumental fraction of S . mansoni adult worm protein extract . Our study is in agreement with their study since we also identified it only in total protein extract , but not in tegumental protein extract . Another muscle protein identified in our study was actin . Actin was also previously observed to be reactive to prepatent infected mouse serum [94] . Reticulocalbin is a Ca2+-binding protein . It is localized in the endoplasmic reticulum , being involved in the secretory pathway , although its detailed role remains unknown . Overexpression of reticulocalbin may also play a role in tumorigenesis , tumor invasion , and drug resistance [95] . This protein has not been previously indicated as a diagnostic test or vaccine candidate for schistosomiasis . Immunolocalization experiments and proteomic analysis of tegumental membrane preparations confirmed that annexin is a protein localized mainly in the tegument of S . mansoni schistosomula and adult worms [36] , [96] . In this study , annexin was again identified exclusively in tegumental protein extract . Schistosoma bovis recombinant annexin was shown to be biologically active in vitro , with fibrinolytic and anticoagulant properties [97] . Significant attention is being given to the excretory system of schistosomes , since accumulating evidence suggests that it plays an important role in the host-parasite interaction . The S . mansoni cysteine protease ER-60 is one of four members of the parasite disulfide-isomerase protein family . It is expressed in adult worms and larvae excretory organs , suggesting a role for ER-60 during the host-parasite interaction [98] , [99] . In this study , a disulphide-isomerase ER-60 precursor was recognized by INF serum in tegumental protein extract . The S . mansoni eukaryotic translation elongation factor was the only protein identified in this study that reacted exclusively with antibodies present in NE serum pool . In addition to its canonical function in polypeptide chain elongation , the isoform eEF1A has been associated to viral propagation , apoptosis in metazoans , cytoskeleton organization and unfolded protein degradation [100] . Moreover , elongation factor 1b/d ( 31 kDa ) has been shown to be immunoreactive to the sera of Echinococcus granulosus infected patients [101] . In our study , the immunoreactive spot corresponding to S . mansoni eukaryotic translation elongation factor was also approximately 31 kDa . Although we have identified only one protein that was recognized exclusively by serum of the natural resistant individuals , which represents our major candidate for a vaccine development , all other 46 proteins identified also are candidates , once they were recognized by antibodies present in serum of infected individuals . The next step would be to assess the level of protection induced by these proteins in animal models . Expression of recombinant proteins was important to confirm the antibody reactivity pattern , mainly for the proteins that were weakly stained in the 2D-PAGE , as it was performed with the major egg antigen . In vitro expressed S . mansoni major egg antigen was strongly recognized by the INF serum pool , maintaining a similar serum recognition pattern of the native protein which indicates the correct spot excision . Anti-human IgG were used in this Western blotting experiment , which means that major egg antigen is recognized by one of the IgG subclasses . However , in 2D-WB using anti-human IgG1 and IgG3 , the spots corresponding to major egg antigen were no longer detectable using INF serum pool ( data not shown ) . Additional studies with post-treatment sera and from individuals low stool egg counts will be important to test its potential , as well as of other promising candidates , as antigens for monitoring the cure and schistosomiasis infection . This will be particularly important for those individuals living in endemic areas for the detection of low infection rates . The antigens identified in this study may also be used as an immunodiagnostic test based , for example , on a qualitative predictive model able to distinguish the clinical status of the schistosomiasis endemic area residents . S . mansoni hemoglobinase was also in vitro expressed in wheat germ cell-free system to confirm the serum recognition pattern of the 2D-WB experiment . While hemoglobinase was found to be immunoreactive to all the pooled sera used in 2D-WB , the recombinant protein showed to be associated with the INF and NE pooled sera , but not with the NI . It may be due to the use of anti-human IgG in the Western blotting instead of anti-human Ig's in the 2D-WB experiments , suggesting a specific reaction of other immunoglobulin class in 2D-WB experiments . Serological-proteomics is a demanding methodology with a number of arduous steps , consequently the reproducibility in 2D-WB experiments is a difficult task [102] , causing missed immunoreactive spots in the triplicate experiments and among the immunoblots . Furthermore , matching the immunoreactive spots of 2D-WB to stained spots in 2D-PAGE gels used to excise the spots to MS/MS analyses is not a trivial task . To precisely locate immunoreactive spots in the 2D-PAGE gels , the molecular weight , pI and the distribution pattern of spots neighboring the spot of interest had to be taken into account . The same difficulty occurs when matching the spots among the immunoblots . It must also be taken into account that spots do not represent proteins but rather protein species with post-translational modifications , partly degraded polypeptides , or may be splicing variants or paralogues genes . Additionally , spots often contain several different proteins or protein species [102] . Despite these difficulties , serological-proteomics seems to be a good approach to characterizing the host immune response profile to parasite antigens in a large-scale analysis , overcoming the case-by-case and empirical science used in the past and providing prominent antigens for the development of new schistosomiasis diagnostics and vaccines . The manageable repertoire of S . mansoni antigens identified in this study warrants further investigation by profiling the antibody response of a larger panel of individual sera using different immunoglobulin classes/subclasses . Understanding the human immune response associated with the infection/protection profile to these antigens represents a huge step towards the improvement of diagnostic tools and development of vaccine against schistosomiasis , using not only one but multiple antigens .
|
Despite intensive efforts towards disease control , schistosomiasis is still highly prevalent in most endemic countries . Although effective treatment is available and widely used , it does not prevent reinfection , as it could be achieved with the use of a vaccine . Efforts to control and eradicate schistosomiasis rely on praziquantel , the only drug available for treatment . Therefore , the identification of antigens that can induce protective immunity is highly desirable , as well as the need for more sensitive assays , useful to detect low intensity infections and treatment follow-up . The occurrence of natural resistance in schistosome endemic areas suggests that there is protective immunity . However , the mechanisms involved in protection , or the proteins that induce this protective immunity , are not yet known . These proteins , once identified , may constitute the basis for a successful vaccine . In this study , we compared the profile of reactive proteins to the serum antibodies of infected and non-infected individuals residing in a schistosomiasis endemic area using two-dimensional western blotting . The association of proteomic and serological screening methodologies enabled the identification of immunogenic proteins of the parasite , which could be an informative source for the development of vaccines and new diagnostic assays . In this manuscript we describe the discovery of potential candidate proteins for subsequent testing as protective or diagnostic antigens .
|
[
"Abstract",
"Introduction",
"Materials",
"and",
"Methods",
"Results",
"Discussion"
] |
[
"biochemistry",
"spectrometric",
"identification",
"of",
"proteins",
"proteome",
"proteins",
"immunity",
"gene",
"expression",
"immunity",
"to",
"infections",
"immunology",
"recombinant",
"proteins",
"biology",
"molecular",
"cell",
"biology",
"proteomics"
] |
2014
|
Serological Screening of the Schistosoma mansoni Adult Worm Proteome
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Understanding the mechanisms that coordinate replication initiation with subsequent segregation of chromosomes is an important biological problem . Here we report two replication-control mechanisms mediated by a chromosome segregation protein , ParB2 , encoded by chromosome II of the model multichromosome bacterium , Vibrio cholerae . We find by the ChIP-chip assay that ParB2 , a centromere binding protein , spreads beyond the centromere and covers a replication inhibitory site ( a 39-mer ) . Unexpectedly , without nucleation at the centromere , ParB2 could also bind directly to a related 39-mer . The 39-mers are the strongest inhibitors of chromosome II replication and they mediate inhibition by binding the replication initiator protein . ParB2 thus appears to promote replication by out-competing initiator binding to the 39-mers using two mechanisms: spreading into one and direct binding to the other . We suggest that both these are novel mechanisms to coordinate replication initiation with segregation of chromosomes .
Studies in bacteria as well as in eukaryotes have shown that processes that maintain chromosomes , such as replication , recombination and repair , although able to occur independently of each other , often influence each other . Chromosome segregation is a major maintenance process but our knowledge of it in bacteria is relatively recent . This is because in well-studied bacteria such as Escherichia coli , genes dedicated to the segregation process have not been evident . Such genes were discovered in bacterial plasmids , called parA and parB . Subsequently , their homologs were found in a majority of sequenced bacterial chromosomes [1] , [2] . Wherever tested , the chromosomal parAB genes were capable of conferring segregational stability on unstable plasmids bearing parS ( “centromere” analogous ) sites [3] , [4] , [5] , [6] , and made at least some contribution to chromosome segregation [7] , [8] . In spite of limited study , it is becoming clear that chromosomal segregation systems can influence and be influenced by other chromosome maintenance processes . In bacteria , replication and transcription have been proposed to provide motive force in chromosome segregation [9] , [10] , [11] . Coupled transcription-translation of membrane proteins is also thought to play an important role in chromosome segregation [12] , [13] . One of the segregation proteins , ParB , can also spread and silence transcription of genes in its path [14] , [15] , [16] . The influence of segregation proteins in replication was suggested when ParB was found to load a condensin protein in the vicinity of the replication origin in Bacillus subtilis and in Streptococcus pneumoniae [17] , [18] , [19] . A more direct role was evident when ParA was found to influence the activity of the initiator DnaA in B . subtilis chromosome replication [20] , [21] and in replication of Vibrio cholerae chromosome I ( chrI ) [22] . Recently , ParB encoded by V . cholerae chromosome II ( chrII ) was also found to influence chrII replication [23] . Here we report two distinct mechanisms for this ParB-mediated effect . V . cholerae chrII replication is primarily controlled by its specific initiator protein , RctB [24] , [25] . RctB binds to two kinds of site in the replication origin of chrII . One kind , the 11- or 12-mers , plays both essential and regulatory roles [26] . The other kind , two 39-mers and a 29-mer ( a truncated 39-mer ) , plays only an inhibitory role in replication [26] , [27] . One of the 39-mers is situated at a locus called rctA , at one end of the origin , and the other is more centrally located in the origin ( Figure 1 , top ) . The 29-mer is located in front of the rctB gene and is involved primarily in autorepression of the gene [27] . The rctA locus contains , in addition to a 39-mer , one of the ParB2 binding sites , parS2-B [28] . It has been reported recently that parS2-B alleviates some of the replication inhibitory activity of rctA in a ParB2-dependent fashion , but the mechanism is unknown [23] . Here we show that ParB2 spreads from parS2-B into the rctA 39-mer , and suggest that the spreading likely interferes with RctB binding to the 39-mer and thereby restrains the inhibitory activity of rctA . Unexpectedly , we also found ParB2 promotes replication by directly binding to the central 39-mer , without requiring spreading from parS2-B . We provide evidence that ParB2 competes with RctB for binding to the central 39-mer specifically and could thereby restrain its activity . In addition to revealing new ways by which a Par protein might influence replication , our results are significant in demonstrating that a segregation protein can bind specifically outside of centromeric sites .
The origin region of chrII comprises three functional units: A region required for controlling initiation ( incII ) , a region minimally required for initiation ( oriII ) and a gene required for synthesizing the initiator protein ( RctB ) ( Figure 1 , top ) . The region covering the first two units , which consists mostly of sites for initiator binding , will be referred to as the origin . The rctA locus of incII exerts a strong inhibitory effect on chrII replication because of the 39-mer it contains [26] . The locus also has a site , parS2-B , for binding to the segregation protein ParB2 , and the inhibitory effect of rctA is reduced in the presence of ParB2 [23] . Knowing that ParB proteins can spread out from their binding sites to neighboring sequences [14] , we asked whether ParB2 spreading from parS2-B over the 39-mer might be a mechanism to control its inhibitory function . The extent of ParB2 spreading was tested by ChIP-chip analysis using antibody against ParB2 ( Figure 1 , bottom ) . Spreading was evident on either side of parS2-B ( grey profile ) . In contrast , when the antibody was against RctB , the immunoprecipitated DNA in the origin region was restricted to where RctB has specific binding sites ( black profile ) . These results suggest that ParB2 has the potential to modulate replication initiation activity by interfering with RctB binding . Spreading of proteins across genes can silence them [14] . For example , spreading into plasmid replication genes suitably close to a parS site can be lethal when selective pressure for plasmid retention is applied . By such an experimental test , we found that ParB2 can spread from parS2-B ( Figure S1A ) . Spreading is also suggested by the formation of ParB2-GFP fluorescent foci in parS2-B carrying plasmids ( Figure S1B ) . ParB2 could also silence two promoters , PrctA and PrctB , in the origin of chrII ( Figure 1 , top ) . PrctA is proximal to parS2-B whereas PrctB is located about 1 kb away at the other end of the origin . The activity of the promoters was assayed by fusing them to a promoter-less lacZ gene present in a multicopy plasmid in E . coli ( Figure 2 ) . The promoter fragments fused to lacZ carried either the entire origin including parS2-B ( 1A and 1B ) , or the origin lacking parS2-B ( 2A and 2B ) or no additional DNA ( 3A and 3B ) . ParB2 was supplied constitutively in trans at about an order of magnitude higher than the physiological level ( monitored by Western blotting; Figure S2 ) , using Ptrc promoter without an intact lac repressor binding-site ( lacO1 ) , which makes the promoter unresponsive to IPTG . The presence of ParB2 reduced the activities of PrctA and PrctB significantly , only when the parS2-B site was present ( Figure 2 , 1A and 1B ) . These results suggest that ParB2 can spread over the entire origin in the presence of parS2-B , and does not have a significant effect on either promoter in the absence of parS2-B . Since RctB has numerous binding sites in the origin , it appeared possible that RctB binding to them could counteract ParB2 spreading and reduce silencing of the promoters . This possibility was addressed by supplying RctB from an arabinose-inducible promoter , PBAD [24] , [26] , [27] , [29] . The induction of RctB alone ( at about two-fold the physiological level ) repressed PrctA marginally and PrctB about two fold ( Figure S3 , lanes 1 vs . 5 ) . Silencing by ParB2 exceeded 90% for both the promoters ( Figure S3 , lanes 1 vs . 4 ) . When RctB and ParB2 were supplied together , the repression of both the promoters was reduced about two fold compared to the level achieved with ParB2 alone ( Figure S3 , lanes 4 vs . 6; also inset ) . These results indicate that RctB can counteract the ParB2-mediated silencing . In the results presented above ( Figure 2 and Figure S3 ) , the level of ParB2 was about 14-fold the level normally present in V . cholerae ( Figure S2 ) . When the concentration was reduced to about 10-fold , ParB2 could silence only the parS2-B proximal PrctA , but not the distal PrctB promoter ( Figure S3 , lanes 1 vs . 3 ) . This reduced level of ParB2 was used in all subsequent experiments . In order to determine how far ParB2 can spread beyond PrctA , progressively increasing lengths of incII were fused to a foreign reporter promoter , PrepA , itself fused to lacZ [30] ( Figure 3 ) . In these experiments , in addition to a plasmid supplying ParB2 , another plasmid was used to supply RctB . The two proteins were expressed from inducible promoters , Plac and PBAD , respectively ( Figure 3 , cartoon at the top right corner ) . As expected , neither ParB2 nor RctB influenced the activity of PrepA itself ( Figure 3 , top panel ) . In contrast , when rctA was present , ParB2 reduced the activity of PrepA by two-fold ( second panel ) . We believe this is due to ParB2 spreading from parS2-B into PrepA , whose −35 box was only 167 bp away . RctB alone was ineffective , most likely because it does not spread , and its specific binding site , the rctA 39-mer , is well separated ( by 85 bp ) from the −35 box of PrepA . Supplying RctB was marginally effective in relieving the silencing by ParB2 . The next extension of the incII fragment included the 3x11-mers ( third panel ) . Neither ParB2 nor RctB could silence the reporter promoter in this case . This result suggests that the spreading may not extend too far beyond PrctA . A further extension of the incII fragment by only 74 bp that included the central 39-mer , restored ParB2-mediated repression of the reporter promoter ( fourth panel ) . This result was surprising since parS2 sites were not found within incII [28] . The effect of ParB2 was significantly reduced when RctB was supplied , which is to be expected since RctB binds strongly to the central 39-mer [26] . This result suggests that ParB2 and RctB can compete for binding to the central 39-mer . The largest fragment ( bottom panel ) did not show a significant ParB2 effect on the reporter promoter , suggesting that ParB2 may not spread significantly from the central 39-mer . Together , the results suggest that under the conditions tested , ParB2 affects the origin primarily through interactions near rctA and the central 39-mer . The interaction near the central 39-mer suggests that ParB2 might bind there directly . The possibility of site-specific binding of ParB2 within the origin but outside of parS2-B was tested by EMSA . Several fragments covering the origin were used . Fragments 1 and 2 , carrying the parS2-B site ( positive controls ) , showed maximal ParB2 binding ( Figure 4 ) . The next significant binding was with the fragment containing the central 39-mer ( fragment 5 ) . This fragment contained natural flanking sequences of only 3 bp and 32 bp beyond the central 39-mer . The sequences ( 3+39+32 ) are exactly those that were added to the incII fragment of the third panel to generate the silencing-proficient fragment of the fourth panel ( Figure 3 ) . We found that the flanking sequences do not contribute to the central 39-mer binding ( Figure S4 , fragment #1 ) . This result supports the inference from in vivo studies that ParB2 can directly bind to the central 39-mer without requiring parS2-B . Binding to the rctA 39-mer ( fragment 3 ) was considerably weaker , possibly because the two 39-mers have several mismatches between them ( Figure 1 of [26]; discussion related to Figure 5 below ) . The level of binding seen with the rctA 39-mer was comparable to the levels seen with fragments 4 , 6 , 8 and 9 , and the level was marginally above that of the negative control that lacks any chrII sequences , suggesting that ParB2 has significant non-specific DNA binding activity . The sequence requirement for specific binding of ParB2 to the central 39-mer was tested by variously mutating the sequence . The 39-mer has two conserved 9 bp direct repeats ( called A and B boxes ) flanking a 19 bp AT-rich spacer ( Figure S4 ) . The presence of both of the repeats and their proper phasing are important for RctB binding [26] . The AT richness of the spacer is also important but not the sequence per se . The parS2 sites are AT-rich inverted repeats , only 15 bp long . Notably , the 39-mer spacer also contains an inverted repeat , which has some similarity to the consensus parS2 site . However , the 39-mer spacer by itself was not sufficient for ParB2 binding; the presence of one of the direct repeats was necessary ( Figure S4 , fragments 4–6 ) . Either of the direct repeats alone was also not sufficient ( fragments 2–3 ) . The inverted repeat feature could also be destroyed without compromising the binding efficiency ( fragment 12 ) . When the same fragments were tested for RctB binding , only the ones with the intact 39-mer and 10 bp deletion or addition ( fragments 9–11 ) showed significant binding , as was also found earlier ( data not shown; [27] ) . It appears that while both ParB2 and RctB bind to the 39-mer , the presence of one of the direct repeats is not obligatory for ParB2 binding . Specific binding of ParB2 to the 39-mer was also verified by DNase I footprinting ( Figure S5 ) . Protection by ParB2 was conspicuous at the junction of the first direct repeat ( A-box ) and the AT-rich spacer . At this junction an intact parS-2B half site , 5′-TGTAAA , is present . This sequence is fully conserved in all 10 parS2 sites that were competent in ParB2 binding [28] . In Figure S4 , this half-site sequence was intact in all the binding positive fragments and mutant in all the fragments that failed to show specific binding . The half-site is also mutated to 5′-TTAAAC in the ParB2 binding-negative 39-mer in rctA ( Figure 4 , fragment #3 ) . The half site thus appears to be necessary for 39-mer binding of ParB2 . In further support of this inference , when we restored the original bases to some of the binding-negative 39-mer mutants to regenerate the half-site , binding proficiency was regained ( Figure 5 , fragments #3–6 ) . Although necessary , the half site was not sufficient for binding ParB2 ( fragment #7 ) . We conclude that extension of the half site either to the left or right is necessary . This is not surprising since the affinity drops by orders of magnitude when one half of a dyad symmetric site is mutated [31] , [32] . The minimal size of the extensions needed to regain binding activity of ParB2 remains to be determined . ParB2 and RctB can bind to rctA simultaneously [23] ( Figure 6 , top panel ) . This is not surprising since there are 34 bp of spacer sequence between the binding sites of the two proteins , and that ParB2 does not spread in vitro . The sites also remain functional when isolated from each other [33] . On the other hand , at the central 39-mer , the binding sites for the two proteins appeared to be largely overlapping , suggesting that they could not bind simultaneously . This was indeed the result ( Figure 6 , bottom panel ) . Even at the higher protein concentrations ( ++ ) , no new discrete species representative of dual binding was detected . The results indicate that ParB2 and RctB compete for binding to 39-mer , unlike the simultaneous binding that can occur on rctA . We previously showed that the central 39-mer is the most potent replication inhibitory site in incII and it functions through RctB binding [26] . If ParB2 competes with RctB for binding to the central 39-mer , this competition appeared likely to influence oriII activity without requiring the parS2-B site . This prediction was tested by determining the copy number of oriII-driven plasmids ( Figure 7 ) . The copy number of oriII plasmids depends on the extent of the incII sequences present [26] . Although the 39-mers are always inhibitory to replication , the 11- and 12-mers can either promote or inhibit replication depending upon whether the 39-mers are present or not . In the present experiments also , the oriII plasmid copy number first decreased and then increased with increasing deletion of incII ( Figure 7 , − ParB2 column ) . When ParB2 was additionally present , the copy number increased significantly in the first two 39-mer-carrying plasmids , the increase being maximal for the plasmid with the lowest copy number ( pTVC25 ) . In this plasmid , we suggest that the 39-mer was unencumbered by the 3x11-mers , and was maximally available for binding to ParB2 . Together , these results indicate that ParB2 has the potential to facilitate chrII replication by restraining the inhibitory activity of the incII sequences , and can do so whether parS2-B is present or not . If ParB2 spreading is one of the mechanisms by which the protein stimulates chrII replication , it might be possible to restrain this activity by placing a roadblock in the path of spreading . To this end , we inserted an array of five P1 RepA binding sites ( iterons ) between parS2-B and the 39-mer in rctA ( Figure 8 ) . The effectiveness of the roadblock in preventing the spreading of P1 ParB protein was demonstrated earlier [34] . Comparison of the top two rows of the Table in Figure 8 shows that in the absence of RepA ( that is in the absence of a roadblock ) , ParB2 was equally efficient in promoting cell growth that depended on the functioning of oriII plasmids . In other words , the P1 iterons in pBJH218 did not compromise ParB2 spreading in the absence of the roadblock . The same two plasmid-carrying cells behaved differently in the presence of RepA ( the last two rows ) . Upon induction of ParB2 production by IPTG , cell growth improved more in the case of pTVC20 than in the case of pBJH218 . In other words , ParB2 effect was compromised under the condition the roadblock was expected to be effective . These results are consistent with ParB2 spreading as a mechanism for stimulating chrII replication initiation . Note that some increase of growth rate was seen even when ParB spreading was inhibited by a roadblock ( generation time decreased 7% for cells in row #4 ) . This result is not surprising because ParB2 can bind to the central 39-mer without requiring spreading from parS2-B . Overall , the ParB2 effects were modest , which is to be expected because of the existence of multiple controls on chrII replication . In chromosome and plasmid segregation , ParB proteins serve to couple centromeres to ParA proteins ( NTPases ) and modulate the NTPase activity that is believed to provide the movement required for segregation [8] . The binding ParB2 to a 39-mer raises the possibility of an inherent centromeric function of the site . This was tested by cloning the central 39-mer into a miniF plasmid , which is unstable due to deletion of its own segregation genes [35] . The stability of the miniF plasmid improved with the inclusion of the parS2-B site but not with the 39-mer , when ParA and ParB proteins were supplied in trans ( Figure S6 ) . This result suggests that ParB2 binding to parS2-B and the central 39-mer is different in an important respect .
The spreading of ParB2 from a centromeric site into the origin of chrII was evident from in vivo cross-linking experiments ( Figures 1 , S7 ) , from silencing of promoters within the origin ( Figure 2 ) and from the reduction of reporter promoter activity when natural initiator ( RctB ) binding sites were present between the centromeric site and the promoter ( Figure 3 , third panel; Figure S3 , insets ) . This latter result indicates that RctB binding could create a natural roadblock to ParB2 spreading . The fact that the span of silencing lengthened with increased ParB2 concentration ( Figure S3 ) also supports the idea that the underlying mechanism involves spreading along the DNA . Finally , the results of placing an artificial roadblock were also consistent with the spreading mechanism ( Figure 8 ) . When a powerful replication inhibitory site ( the rctA 39-mer ) was present within the span of spreading , growth of cells dependent upon the functioning of the chrII origin improved . It was also reported earlier that ParB2 could increase replication of chrII origin carrying plasmids when they included the adjacent rctA region [23] . This increase was shown to be dependent on the presence of parS2-B . Together with the finding that ParB2 does not directly bind to the rctA 39-mer ( Figure 4 ) , and cannot spread from its binding site in the central 39-mer as discussed below ( Figures 3 ( last panel ) , S1A , S1B ) , the simplest explanation of these results is that by spreading from parS2-B , ParB2 compromises the inhibitory activity of the rctA 39-mer by interfering with RctB binding . ParB2 was also found to reduce the activity of another potent replication inhibitor ( the central 39-mer ) without requiring the centromeric site and spreading ( Figure 3 , S1 ) . The latter effect appears to be due to direct binding of ParB2 to the central 39-mer . This mode of ParB2 interaction with the 39-mer most likely also causes interference with RctB binding to this site ( Figure 6 ) . Since the 39-mers are the two sites most inhibitory to chrII replication and their activities are mediated through RctB binding , the reduction in binding suffices to explain how ParB2 could promote replication of chrII ( Figures 7 , 8 ) . Interference with binding of regulatory proteins to DNA by the spreading of a competing protein along DNA has also been invoked to explain transcriptional silencing , inhibition of DNA methylation and of DNA gyrase binding , and resistance to DNase I cleavage [37] , [38] , [39] , [40] . Although the only model we have entertained so far to explain the ParB2 effect is interference with specific binding of RctB , we have also tested whether ParB2 and RctB could interact directly . This possibility was suggested by the finding that ParA influences replication by protein-protein interaction rather than DNA-protein interaction [20] , [21] , [22] , [36] . However , ParB2 did not show any detectable interaction with RctB , as was also reported earlier ( Figure S8 ) [23] . ParA participates in a number of processes involving ParB [8] . Here , we asked whether binding of ParB2 to the central 39-mer is also influenced by ParA2 . The binding was assayed indirectly by fusing a foreign promoter close enough to the 39-mer that ParB2 binding to the site could interfere with the promoter activity . The promoter activity did not change significantly upon supply of ParA2 ( Figure S9; data with PrepA ) . This suggests ParB2 binding to the 39-mer is not influenced by ParA2 . We did find a minor influence of ParA2 on PrctA silencing by ParB2 spreading , the basis of which was not explored . In the case of P1 plasmid and B . subtilis chromosome , no ParA effect on ParB spreading was evident [14] , [41] . Whereas deletion of parS2-B in V . cholerae was easily tolerated ( Figure S7; [23] ) , deletion of the parB2 gene was essentially lethal [42] . In the absence of ParB2 , chrII loss is evident at every cell division that causes a severe growth defect . We were therefore unable to test conveniently the role of ParB2 on replication of chrII in the native host . On the other hand , there was no obvious effect of ParB2 on the growth of E . coli , in which we did most of our experiments . The validity of extrapolating the observations in E . coli to the native host appears warranted by the observation that ParB2 effects were seen in the context of the entire origin ( Figure 8; [23] ) , and by the finding that some of the inferences from the E . coli results were valid when tested in vitro ( Figure 6 ) . In the past , wherever chrII replication control was studied in both E . coli and V . cholerae , the results agreed [25] , [26] , [28] , [29] . Nonetheless , the ParB2 concentration required for spreading to proceed just over rctA was an order of magnitude higher than that is normally present in the native host . The reason for this discrepancy is not understood but a possibility is that ParB2 when supplied from a trans source is much less effective . A discrepancy in the amount of protein required from a cis vs . trans source has been noted in the case V . cholerae ParA1 [22] and ParA of Pseudomonas aeruginosa [43] . The production of one of the Par proteins without its partner could also have altered the protein activity and stability . The importance of maintaining the stoichiometry of Par proteins has also been indicated in studies of B . subtilis [20] , [44] . Another possibility is that higher protein concentration may be required to bind to a single parS site , as we have used here , than when there exists neighboring sites , as in the native host , that might allow cooperative binding . We show that in wild type V . cholerae cells ParB2 can bind and spread over the entire origin ( Figure 1 ) . We detected considerable ParB2 spreading , even with the deletion of the origin proximal centromeric site ( parS2-B ) ( Figure S7 ) . Most likely , this spreading originates from the neighboring parS2-A site 5 . 7 kb away ( Figure 1 ) . The spreading could add an additional layer of control over PrctA by silencing the promoter , which is independently repressed by RctB ( Figure S3 ) [24] , [45] . The PrctA activity in turn controls RctB binding to the rctA 39-mer [29] . The multiple feedback loops that operate to control the initiation of replication from the origin of chrII appear securely interlocked with the specific segregation system of this chromosome . The presence of multiple layers of control could compensate for a deficiency in any one of the regulators , and help in homeostasis of origin copy number . The finding that ParB2 could spread over the entire origin might suggest that it could be a mechanism to promote chromosome segregation . It might increase the effective size of the kinetochore , which might facilitate its interaction with ParA , the essential partner of ParB in chromosome segregation . However , this role has yet to be established [16] , [34] , [46] . ParB proteins of plasmids are known to be plasmid-specific and to bind to their cognate sites [47] . This helps to avoid segregation-mediated incompatibility if different plasmids happen to be present in the same host . By the same token , in multichromosome bacteria , the segregation systems should be chromosome-specific . Such is clearly the case in Burkholderia cenocepacia [5] and in V . cholerae [4] , [48] . The same ParB protein has been found to bind to variant parS sites but the sites are believed to be descendants of a common ancestor [49] . In this context , it is noteworthy that although the central 39-mer is largely non-homologous to parS2-B , the region of the 39-mer crucial for ParB2 binding shares six bp of perfect identity with parS2-B ( Figures 5 , S4 ) , suggesting the possibility of an evolutionary link between the sites here also . Chromosome segregation begins soon after replication initiation , thereby compressing the total time for the completion of these two processes . Their close coordination also allows segregation to proceed in a more orderly fashion than if the substrate for segregation were a pair of completed and entangled sister chromosomes . Here , we have described interactions that might assist in coordinating replication initiation and segregation . In V . cholerae , following replication initiation , the majority of the RctB binding sites ( 11- and 12-mers ) stay hemi-methylated and are unable to bind the initiator [50] . This stage of the cell cycle should favor spread of ParB2 into the origin ( Figure S7 ) , which is likely to favor origin segregation and at the same time discourage premature reinitiation . Spreading of ParB2 towards the origin is apparently prevented later in the cell cycle when the origin is remethylated , allowing RctB binding to 11- and 12-mers that eventually leads to initiation ( Figure 3 , 3rd panel ) . At these latter stages , when spreading is blocked , direct binding of ParB2 to the central 39-mer should favor initiation . Thus , depending upon the stage of the cell cycle , ParB2 appears to play opposite roles in controlling chrII replication , but in such a way as to promote the orderly sequence of chromosome replication followed by segregation . In the case of plasmids , which can complete replication in a tiny fraction of the cell division cycle , such coordination is neither necessary nor evident . We suggest that the acquisition of interactions such as we describe are a feature of the putative adaptation of an acquired plasmid to permanent residency as a second chromosome .
V . cholerae and E . coli strains , and plasmids used in this study are listed in Table S1 . ChrII fragments were amplified from N16961 ( CVC209 ) DNA by PCR using Phusion High-Fidelity polymerase ( NEB , Beverly , MA ) . The sequences of primers used for PCR are shown in Table S2 . For cloning sequences up to 100 bp , complementary oligonucleotides ( IDT , Skokie , IL ) were used after annealing the two [29] . The exact chrII coordinates of each cloned fragment are given in Table S1 . This was done in L broth cultures of E . coli strain BR8706 at OD600 between 0 . 4–0 . 5 , as described [24] . To account for any effect that ParB2 might have on the replication of the lacZ-reporter plasmid , β-galactosidase activities were normalized for the plasmid copy number in all cases . The copy number variation was small; one standard deviation was within 20% of the mean . The copy numbers were measured ( see below ) from aliquots of the same cultures that were used for β-galactosidase measurements . Some of the cultures were simultaneously monitored for ParB2 amounts by Western blotting ( Figure S2 ) . Note that +/− ParB2 refer to cells carrying pTVC501 ( that carries parB2 under IPTG control ) with and without IPTG induction , respectively . In Figure 2 and Figure S3 ( lanes 4 , 6 ) , + refers to cells carrying pTVC236 , which supplies ParB2 from a constitutive promoter and − refers to cells carrying the empty vector , pACYC184 . The copy number of lacZ-carrying plasmids ( Figures 2 , 3 , S3 , S9 ) were measured exactly as described [32] . Briefly , different experimental cultures were grown to log phase and mixed with separately grown cells carrying pNEB193 before plasmid isolation . The latter plasmid helped to account for plasmid loss , if any , during plasmid isolation steps . The copy number of oriII plasmids ( Figure 7 ) was determined similarly except that cells instead of growing in liquid cultures were obtained by washing out colonies from transformation plates directly , to avoid mutant accumulation , as described [26] . The origin fragments were first cloned in a plasmid vector driven by the γ-origin of plasmid R6K , and the clones were maintained in cells that supplied the cognate initiator ( π ) protein . The clones were electroporated into E . coli ( BR8706 ) carrying pTVC499 that supplied RctB ( but no π protein ) and pTVC501 that supplied parB2 . The DNA probes were made from plasmids by PCR using oligonucleotides TVC286 ( 5′-TCCGATTACGGCACCAAATCGA-3′ ) and TVC287 ( 5′- AACGTGGATAAACTTCCTGTAAT-3′ ) , which allowed amplification of extra 100 bp of vector sequences from each flank of the region of interest . The PCR products were labeled using 30 units T4 Polynucleotide Kinase ( NEB ) and 50 µCi of [γ32-ATP] ( Perkin-Elmer ) and purified by passing through G-50 columns ( Roche diagnostics ) . Binding was done in the presence of 300 ng poly dI-dC . Other details are as described [25] , except that the binding reactions were run in 0 . 5×TBE , which improved ParB2 binding . In Figure 5 , the probe was non-radioactive and was visualized with SYBR Gold nucleic acid gel stain ( Molecular Probes ) at 0 . 5 mg/ml for 30 min . As non-specific competitor , supercoiled pUC19 DNA was used instead of poly dI-dC , as the former stayed at the top of gels and did not interfere with visualization of probe bands . The images were recorded using Fuji LAS-3000 imaging system . ChIP assay was performed as described [50] . Briefly , cells of V . cholerae CVC209 were cultivated in L broth at 37°C to exponential phase and cross-linked with 1% formaldehyde . After cell lysis and sonication , RctB-DNA or ParB2-DNA complexes were immunoprecipitated using RctB or ParB2 antibody , respectively . The precipitated DNA was amplified , labeled and hybridized to a custom Agilent 8 X 60K V . cholerae oligonucleotide microarray representing the whole genome according to the manufacturer's protocol and as described [51] . The custom tiling array contained 60 bp probes specific for both the Crick and Watson strands . The consecutive probes were separated by 140 bp in each strand and by 10 bp between the Watson and Crick strands . Data was extracted using an Agilent scanner and Agilent Feature Extraction program . Individual ChIP ( Cy5 ) and input ( Cy3 ) signals were first normalized with respect to total Cy5 and Cy3 signals , respectively . Fold change was calculated by dividing the normalized Cy5 signals with normalized Cy3 signals . The values are mean from three independent experiments . The effect of roadblock to ParB2 spreading was tested by cloning an array of five consensus P1 plasmid iterons in front of chrII origin of pTVC20 , resulting in pBJH218 ( Figure 8 ) . Consensus iterons were used to avoid the PrepA promoter present within the array of natural iterons of P1ori . To clone the iterons , pTVC20 was modified by creating a NdeI restriction enzyme site between parS2-B and the 39-mer within rctA , using QuikChange II XL site-directed mutagenesis kit ( Agilent Technologies ) and oligonucleotides BJH472 and BJH473 . To the resulting plasmid ( pBJH217 ) , the iteron array , amplified from pALA753 [52] using oligonucleotides BJH475 and BJH476 , was cloned at the NdeI site , resulting in pBJH218 . The plasmid pair , pTVC20 and pBJH218 , was used in the same genetic background as used in Figure 7 , and additionally , in an otherwise isogenic host that supplied P1RepA protein from a constitutive promoter ( bla-p2 of pBR322 ) . The P1repA gene and the adjoining bla-p2 promoter was cloned in a λD69 vector and the resulting phage ( λDKC311 [53] ) was used to lysogenize BR8706 . The copy numbers of pTVC20 and pBJH218 were nearly identical , about four-fold lower than pTVC22 used in Figure 7 , as was found earlier for pTVC20 [29] . The copy number was estimated to be about one per cell when there should be four oriC . The low copy number of pTVC20 and pBJH218 , and the lack of an active partitioning system , made the plasmids unstable ( 130/130 cells lost the plasmids after seven generations of growth without selection ) . The effect of ParB2 was therefore checked only under selection . Young colonies ( ≤1 mm ) from selection plates were used to inoculate LB medium with appropriate drugs ( ampicillin at 50 µg/ml , chloramphenicol at 25 µg/ml and spectinomycin at 40 µg/ml ) and inducers ( arabinose at 0 . 02% and , when desired , IPTG at 100 µM ) , and the cultures were grown to early log phase ( OD600∼0 . 1 ) and stored in 0 . 01 M MgSO4 in ice . For calculating generation times , the cultures were diluted to OD600 = 0 . 002 and grown to early log phase . Generation times were calculated from OD600 values in the range 0 . 02–0 . 2 . Saturation of growth was avoided to prevent accumulation of faster growing revertants . Relative colony sizes were also determined from the MgSO4 suspensions on plates with and without IPTG but otherwise identical in volume and contents .
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Replication and segregation are the two main processes that maintain chromosomes in growing cells . In eukaryotes , the two processes are restricted to distinct phases of the cell cycle . In bacteria , segregation follows replication initiation with a modest lag . Influences of one process on the other have been postulated . The act of replication has been suggested to provide a motive force in chromosome segregation . Moreover , segregation proteins ( ParA ) have been found to interact with and control the replication initiator , DnaA . Here we show that in V . cholerae chromosome II , which is believed to have originated from a plasmid , a centromere binding protein ( ParB ) could control replication by two distinct mechanisms: spreading from a centromeric site into the replication-control region , and direct binding to the primary replication-control site , which has limited homology to the centromeric site . These studies establish that Par proteins can influence replication by at least three mechanisms . Homologous Par proteins participate in plasmid segregation but they are not known to influence plasmid replication . The expanded role of Par proteins appears likely to have been warranted to coordinate chromosomal replication and segregation with the cell cycle , which appears less of an issue in plasmid maintenance .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"biology"
] |
2013
|
Evidence for Two Different Regulatory Mechanisms Linking Replication and Segregation of Vibrio cholerae Chromosome II
|
Biomphalaria pfeifferi is highly compatible with the widespread human-infecting blood fluke Schistosoma mansoni and transmits more cases of this parasite to people than any other snail species . For these reasons , B . pfeifferi is the world’s most important vector snail for S . mansoni , yet we know relatively little at the molecular level regarding the interactions between B . pfeifferi and S . mansoni from early-stage sporocyst transformation to the development of cercariae . We sought to capture a portrait of the response of B . pfeifferi to S . mansoni as it occurs in nature by undertaking Illumina dual RNA-Seq on uninfected control B . pfeifferi and three intramolluscan developmental stages ( 1- and 3-days post infection and patent , cercariae-producing infections ) using field-derived west Kenyan specimens . A high-quality , well-annotated de novo B . pfeifferi transcriptome was assembled from over a half billion non-S . mansoni paired-end reads . Reads associated with potential symbionts were noted . Some infected snails yielded fewer normalized S . mansoni reads and showed different patterns of transcriptional response than others , an indication that the ability of field-derived snails to support and respond to infection is variable . Alterations in transcripts associated with reproduction were noted , including for the oviposition-related hormone ovipostatin and enzymes involved in metabolism of bioactive amines like dopamine or serotonin . Shedding snails exhibited responses consistent with the need for tissue repair . Both generalized stress and immune factors immune factors ( VIgLs , PGRPs , BGBPs , complement C1q-like , chitinases ) exhibited complex transcriptional responses in this compatible host-parasite system . This study provides for the first time a large sequence data set to help in interpreting the important vector role of the neglected snail B . pfeifferi in transmission of S . mansoni , including with an emphasis on more natural , field-derived specimens . We have identified B . pfeifferi targets particularly responsive during infection that enable further dissection of the functional role of these candidate molecules .
Schistosomiasis is one of the world’s most prevalent neglected tropical diseases with over 218 million people worldwide requiring preventive chemotherapy in 2015 , 92% of those occurring in 41 countries in Africa [1] . Human schistosomiasis has a greater public health impact than usually appreciated [2] , often with a disproportionate impact on children , in whom it can cause both cognitive and physical impairments [3–6] . There is a growing consensus that we need to supplement chemotherapy with other control methods , including control of the obligatory molluscan intermediate host of schistosomes [7–10] . Snail control has been identified as an important component of the most successful control programs [11] . Among the most important schistosome species infecting humans and the one with the broadest geographical range is Schistosoma mansoni . Biomphalaria pfeifferi is one of 18 Biomphalaria species known to transmit S . mansoni . Biomphalaria pfeifferi has a broad geographic distribution in sub-Saharan Africa where the majority of cases of S . mansoni occur and exhibits a high degree of susceptibility to S . mansoni [12–16] . For instance , B . pfeifferi typically shows high infection rates ( 50%+ ) following exposure to S . mansoni from locations throughout Africa , but even to isolates originating from the Americas [12] . For these reasons , it can be argued that B . pfeifferi is the world’s most important intermediate host for S . mansoni . Understanding the role of B . pfeifferi in human schistosomiasis transmission becomes more critical because expanding agriculture and water development schemes [17] and climate change [18 , 19] threaten to alter the geographic range of both this snail species and of S . mansoni as well . Given B . pfeifferi’s importance in transmission of S . mansoni , it is surprising we lack even the most basic information at the molecular level about its interactions with , and responses to , S . mansoni . Such responses could be particularly interesting in the case of B . pfeifferi because it differs from other major S . mansoni-transmitting snail species in that it is a strong preferential selfing species , a characteristic potentially resulting in low genetic diversity within populations [20–23] . Our relative ignorance regarding B . pfeifferi reflects the simple fact that it is often difficult to maintain this species in the laboratory , in contrast to the Neotropical snail B . glabrata which has been the standard model laboratory snail host for S . mansoni for decades [24] . Biomphalaria glabrata surely remains an important intermediate host of S . mansoni in the Neotropics , but given that the vast majority of S . mansoni cases occur in sub-Saharan Africa , it is critical that we extend more attention to the relevant African snail , B . pfeifferi . The advent of genomics approaches including high throughput sequencing techniques have lead over the past decade to several studies of Biomphalaria snails and their interactions with S . mansoni and other trematodes including echinostomes . All of these studies have been undertaken with B . glabrata and have been amply reviewed and discussed [25–36] . In addition , the report of the international consortium on the Biomphalaria glabrata genome has now been published [37] . Ironically , the African Biomphalaria species that are responsible for transmitting the most S . mansoni infections by far have been largely ignored with respect to application of modern high-throughput sequence-based tools . Projects going beyond the study of individual genes or gene families of B . glabrata began with studies of expressed sequence tags [38–40] , ORESTES studies [41 , 42] , and then microarrays [43 , 44] . These studies showed B . glabrata has the capacity for more diverse immune responsiveness than previously known , including production of diversified molecules like FREPs ( fibrinogen-related proteins ) [28 , 45 , 46] . Hanington et al . [47] examined the transcriptional responses of B . glabrata during the intramolluscan development of both S . mansoni and Echinostoma paraensei , and showed snail defense-related transcripts were generally down-regulated starting shortly after infection . A later generation array including ~31 , 000 ESTs from B . glabrata provided new insights into how the APO or amebocyte-producing organ of B . glabrata responds to immune challenge [48] , and to the effects on B . glabrata transcriptional responses of the molluscicide niclosamide that is commonly used for snail control operations [49] . Additional recent studies of the interactions between B . glabrata and S . mansoni have focused on genetic linkage studies to identify chromosome regions of interest that contain genes influencing resistance to infection [32 , 50 , 51] . Functional studies have also used RNAi to knock-down particular B . glabrata gene products shown to influence susceptibility to S . mansoni [30–32 , 52] . Relevant to the present study , Deleury et al . [53] published the first Illumina sequencing study with B . glabrata , and identified 1 , 685 genes that exhibited differential expression after immune challenge . More recent studies employing RNA-Seq have identified B . glabrata genes associated with a state of heightened innate immunity [54] or with differential response of FREPs in B . glabrata strains differing in their susceptibility to S . mansoni [34] . Despite the fairly extensive efforts with respect to gene and genomic sequencing , gene profiling , or transcriptomics for B . glabrata and to a lesser extent for Oncomelania hupensis [55 , 56] , the snail host of Schistosoma japonicum , to date there have been no equivalent studies published for B . pfeifferi , or for other schistosome-transmitting planorbid snails , including species of Bulinus , several of which transmit members of the Schistosoma haematobium species group in Africa , southern Europe and southwest Asia . With this in mind , we have undertaken an Illumina RNA-Seq study of B . pfeifferi , and of B . pfeifferi infected with S . mansoni for 1 or 3 days , or with naturally acquired cercariae-shedding or “patent” infections . The intramolluscan transcriptional responses of S . mansoni will be the subject of a separate paper . The challenge of parsing S . mansoni sequences from the aggregate of reads obtained from infected B . pfeifferi has been aided by availability of the S . mansoni genome [57] and stage-specific transcriptional studies for S . mansoni [58–60] . Our view of schistosome-snail encounters has also been largely formed by studies of lab-reared snails and schistosomes . RNA-Seq offers a way to bridge and expand upon these traditional views by revealing the detailed molecular and cellular mechanisms taking place in genetically diverse hosts and parasites . This is the first Illumina study performed on samples of both field-derived vector snails and their corresponding schistosome parasites , adding a unique perspective to our understanding of schistosome transmission “in the wild” in endemic regions . This approach also serves to remind us that the snails targeted for infection by schistosome miracidia in the field are best considered as holobionts with potentially complex sets of symbiotic associates [61 , 62] . Finally , we note that this study will add to the literature a considerable amount of new data for B . pfeifferi , an important neglected vector species that has hitherto been understudied . Included among the snail genes highlighted are several that relate to stress , immune or reproductive functions , or that may be key players in influencing the noteworthy widespread ability of this snail to support schistosomiasis transmission .
We enrolled human subjects who provided fecal samples containing Schistosoma mansoni eggs that were hatched to obtain miracidia used to infect some of the Biomphalaria pfeifferi snails used in this study . Fecal samples were obtained and pooled from five S . mansoni-positive primary school children aged 6–12 years from Obuon primary school in Asao , Nyakach area , Nyanza Province , western Kenya ( 00°19’01”S , 035°00’22”E ) . Written and signed consent was given by parents/guardians for all children . The KEMRI Ethics Review Committee ( SSC No . 2373 ) and the UNM Institution Review Board ( IRB 821021–1 ) approved all aspects of this project involving human subjects . All children found positive for S . mansoni were treated with praziquantel following standard protocols . Details of recruitment and participation of human subjects for fecal collection are described in Mutuku et al . [15] . This project was undertaken with approval of Kenya’s National Commission for Science , Technology , and Innovation ( permit number NACOSTI/P/15/9609/4270 ) , National Environment Management Authority ( NEMA/AGR/46/2014 ) and an export permit has been granted by the Kenya Wildlife Service ( 0004754 ) . Biomphalaria pfeifferi used in Illumina sequencing were collected from Kasabong stream in Asembo Village , Nyanza Province , western Kenya ( 34 . 42037°E , 0 . 15869°S ) in November 2013 . Snails were transferred to our field lab at The Centre for Global Health Research ( CGHR ) at Kisian , western Kenya . Snails sized 6-9mm in shell diameter were placed into 24-well culture plates and exposed to natural light to check for the shedding of digenetic trematode cercariae , including cercariae of S . mansoni [15] . Snails found to be shedding cercariae of other digenetic trematode species were excluded from this study . Snails shedding S . mansoni cercariae and non-shedding snails ( controls ) were separated and held for one day in aerated aquaria containing dechlorinated tap water and boiled leaf lettuce . After cleaning shells with 70% EtOH , whole shedding and control snails were placed individually into 1 . 5ml tubes with 1ml of TRIzol ( Invitrogen , Carlsbad CA ) and stored at -80°C until extraction . Biomphalaria pfeifferi confirmed to be uninfected were exposed to S . mansoni using standard methods to hatch the parasite eggs [15] . Snails were individually exposed to 20 miracidia for 6 hours in 24-well culture plates and then returned to aquaria . At 1 and 3 days post-infection ( d ) , snails were collected and stored in TRIzol as described above . We chose not to maintain the field-derived snails for longer intervals post-infection as we did not want them to lose their unique field-associated properties while maintained in laboratory aquaria . In addition to the Illumina RNA-Seq samples indicated above and mentioned throughout this study , we have RNA-Seq data from B . pfeifferi obtained from two 454 GS FLX ( Roche , Basel Switzerland ) runs and six Illumina-sequenced B . pfeifferi exposed to molluscicide , all field-derived from Kenya ( Table 1 ) . These reads were used to aid assembly of the B . pfeifferi de novo transcriptome and were not included in expression studies . Individual snails stored in TRIzol were homogenized using plastic pestles ( USA Scientific , Ocala FL ) . For each biological treatment ( control , 1d , 3d , and shedding ) , total RNA was purified separately from three individual snails ( each snail a biological replicate ) using the TRIzol protocol provided by the manufacturer ( Invitrogen , Carlsbad CA ) . RNA samples were further purified using the PureLink RNA Mini Kit ( ThermoFisher Scientific , Waltham MA ) . Genomic DNA contamination was removed with RNase-free DNase I ( New England BioLabs , Ipswich MA ) at 37°C for 10 minutes . This combination method based on the two RNA extraction assays had been developed in our lab and proved to produce a high quality of RNA from snail samples [47] . RNA quality and quantity was evaluated on a Bioanalyzer 2100 ( Agilent Technologies , Santa Clara CA ) and Nanodrop 2000 ( ThermoFisher Scientific , Waltham MA ) . Complementary DNA ( cDNA ) synthesis and Illumina Hi-Seq sequencing was performed at the National Center for Genome Resources ( NCGR ) in Santa Fe , NM . Most liquid handling was performed by a Sciclone G3 Automated Liquid Handling Workstation ( Caliper Life Sciences , Hopkinton MA ) with Multi TEC Control ( INHECO , Martinsried Germany ) . Synthesis of cDNA and library preparation was prepared using Illumina TruSeq protocol according to the manufacturer’s instructions ( Illumina , Carlsbad CA ) . Complementary DNA libraries were paired-end sequenced ( 2x 50 base reads ) on a HiSeq2000 instrument ( Illumina , Carlsbad CA ) . Sequencing adapters , nucleotides with a Phred quality score <20 within a sliding window of 4bp , and non-complex reads were removed using Trimmomatic v . 0 . 3 [63] . Raw read quality control checks were performed before and after Trimmomatic filtering using FastQC ( http://www . bioinformatics . babraham . ac . uk/projects/fastqc/ ) . To reduce assembly of chimeric transcripts , we created a novel pipeline to separate reads of related organisms when only one organism has a sequenced genome while also allowing for recovery of shared reads ( Fig 1 ) . First , all reads ( including control samples ) that passed quality filtering were aligned to the S . mansoni genome ( GeneDB: S . mansoni v5 . 0 ) using STAR v . 2 . 5 2-pass method [64] or Tophat v . 2 [65] ( see Table 1 for alignment percentages ) . From examination of the percentage values in Table 1 , it may be interpreted that unexposed control actually harbor S . mansoni . However , the reads contributing to the positive percentage values for the controls are ones that we have found to be shared with either B . glabrata or another organism such that they represent a background level of sequence similarity obtained by chance . Although partial mapping of reads may occur , none appear to be expressed S . mansoni transcripts . None of the unexposed control reads mapping to the S . mansoni genome are unequivocally S . mansoni . By contrast , S . mansoni-exposed snails ( 1d , 3d , shedding ) all expressed bona fide S . mansoni genes . Only in 1d , 3d , and shedding snails were transcripts clearly distinctive to S . mansoni found , such as venom allergen proteins ( SmVal ) ( Accessions: AAY43182 . 1 , AAY28955 . 1 , AAZ04924 . 1 , ABO09814 . 2 ) , tegument allergen-like proteins ( Accession: P14202 ) , and cercarial stage-specific proteins ( Accession: ABS87642 . 1 ) , verifying the presence of a S . mansoni infection . This explanation also serves to verify that individual snails ( such as 1dR2 ) with low S . mansoni percentages were indeed infected , such that they could be expected to be responsive to infection . Therefore , relatively low S . mansoni genome mapping , especially for shedding-R3 , should not be interpreted that the infection was not successful , but rather as an indication of the transcriptional activity . Reads that mapped to S . mansoni were also cross-examined by mapping to the version BglaB1 of the B . glabrata genome ( https://www . vectorbase . org/organisms/biomphalaria-glabrata ) using STAR . Reads that first mapped to S . mansoni and then also to B . glabrata were determined to be shared reads and added to the reads destined for B . pfeifferi transcriptome de novo assembly . One issue encountered was to deal with both paired- and single-end reads resulting from initial quality filtering and from discordant or single-mate mapping to the S . mansoni genome . Pseudo-mate reads were created to allow maximum read usage in all stages of analysis ( details and script available at https://github . com/lijingbu/RNA-Seq-Tools ) . This tool , pseudoFastqMate . pl , creates pseudo mate reads for single reads in a fastq file by generating a string of N’s the same length and quality score as its mate read . Reads entirely made up with Ns were ignored during the mapping process and have no impact on the final alignment and read counts . Unaligned paired and unpaired reads , determined not to solely belong to S . mansoni , were assembled using Trinity v2 . 2 RNA-Seq de novo assembler [66 , 67] . Trinity de novo and B . glabrata genome-guided assemblies were employed to maximize the chances of recovering unique B . pfeifferi transcripts . The de novo assemblies were concatenated and redundancy reduced using the EvidentialGene tr2aacds pipeline [68] . EvidentialGene determines the best set of transcripts based on the coding potential of transcripts generated from multiple assemblies . Only primary transcripts , denoted in EvidentialGene as “okay” and “okalt” were used in further analysis . In silico translation of the transcriptome was done using TransDecoder v3 . 0 ( https://transdecoder . github . io ) [65] to extract long open reading frames ( ORFs ) and identify ORFs with homology to known proteins with blast and pfam searches . Biomphalaria pfeifferi CDS were annotated based on their closest homologs and predicted functional domains in the following databases and tools: BLASTp with NCBI non-redundant protein database ( sequence identity >30% , E-value <10−06 ) , BLASTn with NCBI nucleotide database ( sequence identity >70% , E-value < 10−06 ) , Gene Ontology [69] , KEGG [70] , and InterProScan5 [71] . For query CDS whose top hit was “uncharacterized” , “hypothetical” , or otherwise unknown , the consensus hit ( of up to 20 hits that also meet minimum sequence identity and E-value requirements shown above is reported to help elucidate any putative function . Additionally , B . pfeifferi CDS were further scrutinized against molluscan transcripts and proteins identified in the literature . As a consequence of sequencing field-collected specimens , we expected some reads to be of non-B . pfeifferi and non-S . mansoni origin . Screening for the presence of third party symbionts was one of our motivations for investigating field-derived snails in the first place . We performed the de novo assembly pipeline without first removing non-snail or non-schistosome sequences to get a more complete view of the complex environment in which S . mansoni development takes place . CDS coverage , sequence identity , and E-value of BLASTn , BLASTp , and MEGABLAST results were all taken into consideration when determining organism identification . The BLASTn and MEGABLAST against the NCBI nucleotide database had minimum sequence identity of 70% and E-value <10−06 and the BLASTp against the NCBI protein database had a minimum sequence identity of 30% and E-value <10−06 . Query coverage ( qcov ) was also calculated in all BLASTs . When different BLASTs disagreed in their taxonomic assignment , the hit with highest percent query coverage , highest sequence identity , and lowest E-value was chosen , in that order . Although minimum parameters were set , nearly all CDS BLAST hits exceeded these bounds . BLASTp hits tended to have better quality hits because nucleotide sequences from the NCBI nucleotide database often contained non-coding regions that our CDS lack . CDS designated as “undetermined” had hits that did not meet minimum BLAST parameters . CDS that had a non-molluscan BLAST hit but still mapped to the B . glabrata genome ( sequence identity >70% , E-value <10−06 ) were considered “shared” sequences . Non-B . pfeifferi and non-S . mansoni CDS were categorized into 14 broad taxonomic groups: Mollusca , Amoebozoa , SAR , Viruses , Plantae , Fungi , Bacteria , Rotifera , Platyhelminthes , Arthropoda , Annelida , Nematoda , Chordata , and Miscellaneous . Potential trematode CDS were further filtered to require a minimum of 70% query coverage . Genomes and CDS of specific symbionts of interest ( if publicly available ) were interrogated using BLASTn ( >70% identity , E-value <10−06 , query coverage >70% ) . Given that a number of previous studies of Biomphalaria immunobiology have focused on molecules with TLR or immunoglobulin domains , we undertook an analysis of these groups of molecules . Biomphalaria pfeifferi CDS with a BLASTp or BLASTn annotation as a toll-like receptor ( TLR ) , were further screened for toll/interleukin-1 receptor ( TIR ) , leucine-rich repeats ( LRR ) , and transmembrane regions with InterProScan5 and TMHMM ( Transmembrane helix prediction based on hidden Markov model ) [72] . CDS identified as complete TLRs contained TIR , transmembrane , and LRR domains . Similarly , CDS annotated as a VIgL ( FREPs , CREPs , GREPs , and FREDs ) were scanned for an immunoglobulin domain and a fibrinogen , C-type lectin , or galectin domain using InterProScan5 . For CDS to be identified as a FREP , CREP , or GREP , they had to contain a lectin domain and at least one immunoglobulin domain . To estimate the completeness of our B . pfeifferi transcriptome assembly and assess similar transcripts across related species , B . pfeifferi predicted ORFs were compared to other molluscan peptides ( the cephalopod Octopus bimaculoides , the oysters Crassostrea gigas and Pinctada fucata , the owl limpet Lottia gigantea , the California sea hare A . californica , as well as two pulmonates: B . glabrata and Radix balthica ) using BLASTp ( sequence identity >30% , E-value <10−06 ) . ORFs with 100 or more amino acids were extracted from each transcriptome . To maximize sensitivity for retaining ORFs that may have functional significance , predicted ORFs were scanned for homology to known proteins in the Uniref90 database with a subsequent search using PFAM and hmmer3 to identify protein domains . Properly paired reads not filtered as S . mansoni were mapped to EvidentialGene-generated B . pfeifferi CDS with Bowtie2 [73] . Read abundance was quantified with RSEM ( RNA-Seq by expectation maximization ) [74] . Pairwise analyses for comparisons between control group and other infected groups were run in EBSeq [75] . Transcripts with a posterior probability of differential expression ( PPDE ) > = 0 . 95 were considered significant . With the aim of detecting less abundant transcripts that may still have significant biologically effects ( i . e . neuropeptides ) , we deliberately did not set a minimum read count threshold for detection of DE CDS in EBSeq . As noted above , field-collected specimens of both snails and schistosomes are naturally more genetically diverse than lab-reared counterparts , so variation in response among infected snails might be expected . In fact , by chance , for each of the time points studied , one of the 3 infected snails examined differed notably from the other two in having fewer normalized S . mansoni read counts ( suggestive of less extensive parasite activity and/or more effective host limitation of parasite development ) . We hypothesized that the snail response is influenced by the extent of S . mansoni representation , as assessed by examining normalized parasite read counts from each infected snail . In addition to doing “3 controls vs . 3 infected” ( 3v3 ) comparisons , for each time point we also examined “3 control vs . 2 infected” ( 3v2 ) comparisons where the two snails harbored higher S . mansoni read counts to identify CDS whose responses were associated with S . mansoni abundance . We also performed “3 control vs . 1 infected” ( 3v1 ) comparisons where the one infected snail was the one with low S . mansoni read counts . The overall DE results include all CDS that were differentially expressed in any of the three comparisons , the results for each comparison being separately singled out and enumerated . cDNA was synthesized from 5μg of total RNA from the original samples by the SuperScript II First-Strand Synthesis Kit for RT-PCR ( Invitrogen ) in a 20μl reaction using random hexamers . Manufacturer directions were followed for the reaction profile . An additional 80μl of molecular grade water was added to the cDNA for a final volume of 100μl . qPCR target primer sequences were generated in Primer3 software [76] and details are shown in S1 Table . We tested probes for single-copy genes only and final selection of qPCR targets were chosen to highlight the variability between replicates . Primer testing verified one product was produced in traditional PCR amplification and in melt curve analyses . RT-qPCR reactions were performed in 20μl reactions according to manufacturer’s directions using SsoAdvanced Universal SYBR Green Supermix ( Bio-Rad Laboratories , Hercules CA ) with 0 . 5μM primer concentration and 2μl cDNA . Reactions were denatured at 95°C for 2 minutes followed by 40 cycles of 95°C for 5 seconds and annealing/extension and plate read for 30 seconds . Melt curve analysis was performed from 65–95°C at 0 . 5°C increments for 5 seconds . All biological replicates were run in technical triplicate for each transcript on a Bio-Rad CFX96 system and analyzed with Bio-Rad CFX Manager software .
To investigate the gene expression profiles of B . pfeifferi following infection with S . mansoni , we analyzed the transcriptome from Illumina sequencing of infected snails at 1-day ( 1d ) , 3-day ( 3d ) , and from shedding snails using three biological replicates each ( Table 1 ) . The raw and assembled sequence data are available at NCBI under BioProject ID PRJNA383396 . The results and statistics describing the B . pfeifferi assembly are summarized in Table 2 . Trinity de novo transcript assemblies and additional reads from two 454 runs resulted in 1 , 856 , 831 contigs . The EvidentialGene program generated a non-redundant B . pfeifferi transcriptome of 194 , 344 protein-coding sequences ( CDS ) that includes isoforms . From nucleotide sequence length histograms , we calculated that more than half of the CDS were between 300–499 nucleotides with 6 . 7% > = 1500 nucleotides ( S1 Fig ) . Five publicly available databases were used to annotate and obtain functional information for the CDS ( S1 File; Table 3 ) . The top 20 most common GO assignments are shown in S2 Fig . Six KEGG categories are shown with their constituent classes organized by abundance in S3 Fig . Altogether , 179 , 030 of 194 , 344 total ( 92 . 1% ) CDS were annotated from at least one of the five databases shown in Table 3 . Pattern recognition receptors like TLRs and VIgLs ( FREPs , CREPS , and GREPs ) are key components of the innate immune response and their involvement in the B . glabrata defense response has been documented [28 , 77] . The B . glabrata genome contains 56 TLR ( toll-like receptor ) genes , 27 of which encode complete TLRs [37] . Our B . pfeifferi transcriptome had 190 CDS annotated as a homolog to a B . glabrata TLR ( Fig 2 ) . Note that numbers assigned to TLRs in B . glabrata were assigned in the order they were identified and not by homology to vertebrate TLRs . The TLR numbers we refer to for B . pfeifferi match most closely the TLR with the corresponding number from B . glabrata . InterProScan5 analysis revealed 78 of B . pfeifferi TLR CDS contain a TIR ( toll/interleukin receptor ) domain and 118 have at least one LRR ( leucine-rich repeat ) domain . In total , we found 48 complete B . pfeifferi TLRs ( TIR , transmembrane , LRR domains all present ) and 142 partial homologs to B . glabrata TLRs ( annotated as a TLR , but not all domains complete and/or confidently identified ) in our transcriptional study . Others may certainly exist in the genome of B . pfeifferi . There are 22 FREP genes in the B . glabrata genome [37 , 77] and all were represented in our B . pfeifferi transcriptome , at least in part . Our BLAST annotations identified 249 B . pfeifferi CDS homologous to B . glabrata FREPs and 12 of these were verified to be full-length FREP homologs ( Fig 3 ) . There were no full-length , complete GREPs identified in our transcriptome , but there were 5 CDS with a BLAST annotation homologous to one B . glabrata GREP identified by Dheilly et al . [77] ( Fig 3 ) . Four CREPs ( C-type lectin protein ) have been identified in B . glabrata [77] with 2 of the 14 full-length , complete B . pfeifferi CDS homologous to CREP 1 in B . glabrata ( Fig 3 ) . A BLASTp comparison between B . pfeifferi and B . glabrata shows high sequence similarity with 35 , 150 ( 95 . 8% ) polypeptides shared between the two species ( sequence identity >30% and E-value <1e-06 ) ( Table 4 ) . We found 1 , 525 B . glabrata polypeptides without homologs in our B . pfeifferi transcriptome . With respect to the 127 , 626 translated CDS that have homologs to B . glabrata polypeptides , more than half of these have a sequence identity greater than 90% ( S4 Fig ) . To further assess the completeness and to enhance annotation of our B . pfeifferi transcriptome , we searched for homologous polypeptides from genomes of two additional gastropods ( Aplysia californica and Lottia gigantea [78] ) , two bivalves ( Pinctada fucata [79] ) and Crassostrea gigas [80] ) , and one cephalopod ( Octopus bimaculoides [81] ) ( Table 4 ) . Shown in S5 Fig is one hypothesis of the phylogeny of molluscs , and mapped onto this are the mollusc genomes that are currently available [82] . Note that the percent identity of homologous sequences follows the general branching pattern . The California sea hare , A . californica , has 88 . 3% of its polypeptides homologous to B . pfeifferi peptides . The most distantly related mollusc , the California two-spot octopus , O . bimaculoides , is 56 . 7% homologous at the protein level to B . pfeifferi . Of the 194 , 344 CDS assembled post-S . mansoni read filtering , 18 , 907 ( 9 . 73% ) of these were determined to be of non-mollusc origin ( Fig 4 ) . Some of the non-B . pfeifferi transcripts found were bacteria with most belonging to the genera Escherichia , Mycoplasma , Aeromonas , and Pseudomonas ( Fig 5 ) . Among them , a CDS with homology to Neorickettsia sp , a known obligatory symbiont of digenetic trematodes [83] , was recovered and has read counts >10 in 2 of our samples that also had relatively high counts of S . mansoni ( 3d-R3 and shedding-R1 ) ( Table 1; S2 File ) . In addition , there are three CDS assembled from the infected 454 B . pfeifferi sample that were identified as Paenibacillus spp . and were similar , but not identical , to the snail pathogen Candidatus Paenibacillus glabratella ( S2 File ) [84] . Among the eukaryotic sequences retrieved from generation of the de novo assembly , there are some familiar snail symbionts listed in S2 and S3 Tables including 1 ) Chaetogaster annelids , 2 ) Trichodina ciliates , and 3 ) Capsaspora owczarzaki [85] and 4 ) microsporidians [86–89] ( see also S2 File and Discussion for further comments ) . In addition to prokaryotes and eukaryotes , nearly 1 , 300 of our assembled CDS were provisionally identified as viruses ( Fig 4 ) . Sample Control-R2 had the highest abundance of reads mapping to the viral sequences compared to the other samples , though some putative viral sequences were recovered from all 12 snails examined . Lastly , even after the initial screening and removal of S . mansoni reads from the nine snails with known S . mansoni infections , some reads remained that were classified as platyhelminth in origin ( Fig 4 ) . Two individual snails in particular , control-R3 and 3d-R2 , the latter a replicate with low S . mansoni read counts , had many platyhelminth reads ( Fig 5 ) . We sequenced a 28S rRNA gene from cDNA of control-R3 using digenean-specific primers [90] to determine if other digeneans were present in our sample . The resulting 28S sequence was identified as belonging to the genus Ribeiroia , members of which are known to occur in East Africa and to infect Biomphalaria [91] . Most of the platyhelminth CDS present in this sample were identified as “hypothetical” but CDS with the highest read abundance are involved in membrane transport and cell structural functions . For 3d-R2 , cox1 mitochondrial gene primers amplified an amphistome sequence that groups phylogenetically with an amphistome species ( provisionally Calicophoron sukari ) that uses B . pfeifferi from East Africa as a first intermediate host [92] . Like control-R3 , CDS with the highest read abundance in 3d-R2 were membrane associated and structural with the addition of several myoglobins and surface glycoprotein CDS . The extent of representation of S . mansoni in the dual transcriptome as measured by read counts is variable among the three replicates for each development time sampled in shedding snails ( Table 1 ) . Normalized read abundance of S . mansoni housekeeping genes remained consistently high across all samples , eliminating the possibility that S . mansoni read count variability was due to sampling effects . Because of this inherent variability , we performed additional DE comparisons to the traditional 3 control v 3 experimental ( 3v3 ) replicates isolating either the two snails that contained higher S . mansoni read counts ( 3v2 analysis ) or the one snail with the fewest S . mansoni read counts of each triplicate time point ( 3v1 ) . With respect to the overall response patterns of snails that yielded either high or low numbers of S . mansoni reads , in most cases , for both up- and down-regulated CDS , the majority of significantly differentially expressed CDS fell into the 3v3 comparison category ( Fig 6 ) , indicative of uniformity of response across infected snails . For up-regulated features , there were also substantial additional numbers of significant CDS in the 3v2 or 3v1 infected categories , with the latter being greater in 2 of 3 cases . By contrast , for the down-regulated features , at 1d , the snails with high or low S . mansoni read counts did not as clearly differentiate from one another , but the snails with low read counts for S . mansoni ( 3v1 ) clearly showed an additional allotment of down-regulated features . For the other two time points , the snails with high and low S . mansoni read counts did separate from one another , and especially noteworthy is the relatively small proportion of down-regulated features in the 3v1 comparisons . S3 File provides a summary of all CDS retrieved in the DE analysis , S4 File summarizes those general , reproduction or immune system features that were most differentially expressed , and Tables 5 and 6 distill CDS ( see Discussion also ) that we feel are most worthy of further functional study in B . pfeifferi . Multidimensional scaling ( MDS ) plots show that for each of the three groups of infected snails , overall transcript expression of the experimental groups is distinct from the control groups ( Fig 7 ) . At 1d , snails showed a slight preponderance of down-regulated over up-regulated CDS , but in both 3d and shedding snails , the opposite trend was observed ( Fig 8A and 8B ) . Overall , the most transcriptional activity was in the 3d snails . All three groups of infected snails ( 1d , 3d , shedding ) showed distinct transcriptional profiles , suggesting the snail response is different at each time point ( Fig 8C ) . Generally , each of the three groups has more unique responsive CDS than they do in common with one another . As anticipated , 1d and 3d snails have more shared transcripts both up- and down-regulated than either do with the shedding snails . It should also be noted that 59 CDS were up-regulated , and 63 CDS down-regulated in common to all three groups of infected snails ( Fig 8C ) . Those up-regulated across time points include hemocytin , CD209 antigen-like , DBH-like monooxygenase , and a fibrinolytic enzyme . Some ubiquitously down-regulated features include neural cell adhesion molecule 1-like , a TNF receptor , peroxiredoxin 5 , F-box/LRR repeat protein 4-like , the cytoprotective hypoxia up-regulated protein 1-like that is triggered by oxygen deprivation and oxidative stress , glutathione-S-transferase omega-1-like , type 1 serotonin receptor 5HT-1Hel , a feeding circuit activating peptide that induces feeding behavior [93] , and TLR 7 . In addition to identifying those CDS up- or down-regulated in common to all three groups of infected snails , we also identified CDS not known to be related to reproduction or defense that exhibited the highest fold expression changes in shedding snails . Snail CDS most highly up-regulated may represent molecules essential for the parasite to sustain a patent infection , or conversely , those most strongly down-regulated may otherwise interfere with parasite development in ways we do not presently understand . A selected few , that had an annotation and were consistently expressed compared to controls in each replicate , are shown in Table 5 . With respect to transcripts involved in reproduction and potentially associated with S . mansoni-induced parasitic castration , we identified homologs to more than 100 invertebrate neuropeptides , hormones , pheromones , and polypeptides involved in reproduction , most of which have been identified in Lymnaea stagnalis , the sea hare Aplysia californica , or in B . glabrata ( S4 File; Fig 9 , and see Discussion ) . We also searched for over 500 different genes identified from previous publications that are related to immune , defense or stress responses to various pathogens or environmental stressors ( S4 File; Fig 10 ) . Each gene of interest has been organized into one of six broad functional groups for ease of interpretation , although it must be noted that many of these genes have multiple roles and could belong in several functional categories . After 1d , the majority of immune , stress and defense features were up-regulated . Noteworthy from Fig 10B is that for snails with low reads counts for S . mansoni ( 3v1 comparison ) , proportionately more features were up-regulated than for snails with high S . mansoni read counts . In two out of three comparisons , snails with low read counts for S . mansoni had fewer down-regulated genes than snails with high levels of S . mansoni read counts . Quantitative RT-PCR ( qPCR ) was used to validate differential expression trends by quantifying mRNA transcripts of four single-copy genes ( 3 up-regulated and 1 down-regulated ) that highlight varying expression patterns in 1d , 3d , and shedding snails . Overall expression patterns are similar between the qPCR and Illumina DE results ( Fig 11 ) with the same variability in DE pattern between replicates echoed in the qPCR . The only difference seen was in the gene DAN4 where the shedding group was not considered significantly DE in the qPCR analysis but was in Illumina analysis .
This paper represents a novel pipeline for dual RNA-Seq studies where the genome of just one of the interacting partners , the parasite in this case , is available . It also highlights an advantage of using field specimens in RNA-Seq studies to reinforce the notion that individual snails are actually holobionts , and the symbiont species they carry with them may play a role in influencing susceptibility to schistosome infection or in modulating disease transmission . Also , variance among the individual snails within the groups examined presented challenges for traditional bioinformatics analyses but also revealed the heterogeneity that realistically exists among naturally diverse snails and schistosomes as they encounter one another in real-life settings in the field . We must also note that the identity and functional role for many of the CDS remain unknown thus posing rich opportunities for study for the future . The specific B . pfeifferi-S . mansoni system studied here is noteworthy for the high degree of susceptibility shown by the snail to infection [15 , 16] . Compatibility with S . mansoni is characteristic of B . pfeifferi throughout its range [12] . As a consequence , all snails exposed to S . mansoni or known to be shedding S . mansoni cercariae contained transcripts contributed by S . mansoni . The extent of representation of S . mansoni in the dual transcriptome is variable among the replicates for each time sampled ( Table 1 ) . Given the effects of both genetic diversity in S . mansoni [94] and in Biomphalaria snail hosts [34 , 95] on the rate or extent of S . mansoni development , it is not surprising that field-derived representatives will differ with respect to extent of parasite development and transcriptional activity . Here it should be noted that read counts may not always be fully indicative of S . mansoni biomass in snails as the transcriptional activity of the parasite may vary temporally , both daily [96] and at longer time scales [97] , and in response to other stimuli , as noted in the following section regarding symbionts . Whole snail transcriptome sequencing gave us the opportunity to identify sequences of non-mollusc and non-schistosome origin , including viruses , bacteria and eukaryotes . These sequences provide evidence of symbionts that are found in or on B . pfeifferi and/or S . mansoni . Some of the symbionts identified are surely worthy of further future investigation and may offer potential in application of novel and as yet unforeseen control efforts . With respect to viruses , in general the array of viruses found in invertebrates has recently been shown to be much more diverse than previously known , including in molluscs [98] . Of the nearly 1 , 300 of our assembled CDS identified provisionally as viruses , most have homology to Beihai paphia shell viruses , picorna-like viruses , and crawfish viruses . In terms of read abundance , the five most abundant viral CDS we found in B . pfeifferi had the most similarity to the Wenzhou picorna-like virus 33 from the channeled apple snail Pomacea canaliculata , Sanxia picorna-like virus 4 from a freshwater atyid shrimp , Beihai picorna-like virus 47 from a sesarmid crab , bivalve RNA virus G2 a picorna virus from the gills of a bivalve [99] , and Beihai hypo-like virus 1 from a razor shell [98] . Picorna viruses have recently been described in both B . glabrata from South America and B . pfeifferi from Oman [100] . Three novel RNA viruses were reported in the B . glabrata genome , the first with similarities to an iflavirus , the second with similarities to a Nora virus or Picornavirales , and the third with similarities to several viruses [37] . Further study is required to confidently designate any of the putative viral sequences recovered as actual infectious entities of snails , or possibly of schistosomes or other digeneans . They might infect other potential hosts like rotifers or diatoms among the symbionts living in B . pfeifferi . The recovery of a few sequences of the digenean-inhabiting Neorickettsia from two infected snails with relatively high percentages of S . mansoni reads ( 3d-R3 and shedding-R1 ) is suggestive of an association . Neorickettsia has been found from non-human schistosomes [101] but further study is needed to document the presence of Neorickettsia in human-infecting schistosomes . For example , the Neorickettsia might be associated with metacercariae of other digeneans that are commonly found encysted in B . pfeifferi from natural habitats . With respect to eukaryotes , CDS representing the following groups were recovered: 1 ) Chaetogaster annelids which mostly colonize the external soft surfaces of freshwater snails and are known to ingest digenean miracidia and cercariae [102–105]; 2 ) Trichodina ciliates known to live on the soft surfaces of snails but with poorly characterized influence on their snail hosts [106]; 3 ) Capsaspora owczarzaki , a Filasterean amoeba-like symbiont known from Biomphalaria glabrata [107 , 108]; 4 ) Microsporidians , not surprising for B . pfeifferi considering microsporidians are known from both Biomphalaria and Bulinus [109]; 5 ) Perkinsea , an alveolate group of considerable commercial significance in marine bivalves , but with at least two reports suggesting their presence in freshwater habitats as well [110 , 111]; 6 ) Rotifers ( possibly attached to the shell or ingested ) and diatoms ( probably ingested ) were frequently recovered as well; 7 ) Four tardigrade CDS were recovered , two from the uninfected control 454-sequenced snail similar to Richtersius coronifer and two from the Illumina de novo assembly similar to Ramazzottius varieornatus . Control-R1 had read counts >10 for the two R . coronifer CDS and 1d-R3 had read counts >10 for a R . varieornatus CDS . It is not unprecedented to find tardigrades associated with snails . Fox and García-Moll [112] identified the tardigrade Echiniscus molluscorum in the feces of land snails from Puerto Rico . Although the tardigrade may have been ingested along with food , the authors did not rule out the possibility that E . molluscorum may be a symbiont of the snail . It was not surprising that two of our snails yielded several reads mapping to sequences from other digeneans . The first , control-R3 , returned sequences consistent with Ribeiroia , representatives of which occur in East Africa and are known to infect Biomphalaria there [91] . It seems most likely this snail had an infection with Ribeiroia sporocysts and/or rediae , though the extent of this infection must have been minimal as the transcriptomics response of this snail was not unusual compared to the other control snails . It may also have been infected with Ribeiroia metacercariae which are most familiarly known to infect amphibians or fish [113 , 114] , but have been recovered and sequence-verified in specimens of Biomphalaria spp . from Kenya ( MR Laidemitt , personal communication , April 2017 ) . The other snail , 3d-R2 , yielded confirmed amphistome sequences , probably from the commonly recovered species Calicophoron sukari [91] , so it may have harbored developing larvae of both S . mansoni and an amphistome , reflective of real-life circumstances in the habitat of origin where this amphistome species is the most common digenean to infect B . pfeifferi [92] . This co-infection may help to explain the relatively low numbers of S . mansoni reads recovered from this snail relative to 3d-R1 and 3d-R3 . It has also been noted that B . pfeifferi ingests amphistome metacercariae ( A Gleichsner , personal communication , June 2017 ) which are abundant on the submerged vegetation in the habitat from which the snail was collected , so this may be an alternative explanation for the presence of amphistome reads in 3d-R2 . The peculiar nature of infection in this snail further justifies our rationale for including it in the separate analyses ( 3v1 ) described in the results . At 1d , snails showed proportionately more down-regulated CDS , possibly reflective of a strong parasite-induced immunomodulatory effect during the establishment phase of infection [54] . For the two additional time points examined , the majority of features in B . pfeifferi were up-regulated ( Fig 8; S3 File ) . This pattern differed from a previous microarray-based expression studies for susceptible B . glabrata for which a predominant trend of down-regulation was noted from 2–32 days post-exposure to S . mansoni [47] . The more comprehensive transcriptional picture resulting from next-gen sequencing provides a different overview of responses following infection with S . mansoni ( see also [54] ) . Many host CDS responded uniformly across individual snails regardless of the number of S . mansoni reads recovered . However , at 1d and 3d , snails with fewer S . mansoni reads had higher proportions of up-regulated features than did snails with higher numbers of S . mansoni reads . Furthermore , for both 3d and shedding snails , snails with low S . mansoni read counts had smaller proportions of down-regulated features . These patterns are suggestive that up-regulated host responses might limit S . mansoni gene expression and that snails with less parasite gene expression may be less vulnerable to gene down-regulation , but care in interpretation is required as alternative explanations may exist . For example , as noted above , replicate 3d-R2 also contained an amphistome infection . Negative interactions among the two digeneans which are known to occur from experimental studies ( MR Laidemitt , personal communication , April 2017 ) may account for the limited number of S . mansoni reads . At 1d , up-regulated responses , as exemplified by CDS for phospholipases , endoglucanases , and several proteases and protease inhibitors , were usually less pronounced than at 3d , suggesting it takes a few days to mobilize responses . Notable at 1d were down-regulation of CDS that might lower hemoglobin levels , and influence feeding behavior and heart beat rate . Infected snails exhibited complex mixed responses with respect to mucins , multidrug resistance proteins , glutathione-S-transferases and cytochrome P450 family members . Cytochrome P450s are part of the stress response shown by B . glabrata snails following exposure to molluscicides [49] and to biotic stressors [48] . For heat shock proteins , B . glabrata snails elaborated more complex up-regulated responses following exposure to molluscicides [49] than B . pfeifferi did following exposure to S . mansoni . Complex patterns in stress response gene families were also noted for 3d and shedding snails . It is noteworthy that exposure to S . mansoni , a specific extrinsic biotic stressor , also provokes components of a generalized stress response in B . pfeifferi and B . glabrata [115 , 116] . Snails with 3 day infections had the highest number of up-regulated CDS . Some of the features down-regulated at 1d were again down at 3d . Additionally , one CDS ( aryl hydrocarbon receptor ) associated with controlling circadian rhythm [117] was down-regulated . Daily feeding patterns of infected snails [119–121] or patterns of release of cercariae [96] could potentially be influenced by this CDS . Several gene families also showed complex patterns of responses at 3d . Among them were amine oxidases which , as noted by Zhang et al . [48] , are involved in oxidation of amine-containing compounds including neurotransmitters , histamines and polyamines [122] . The overall responses of shedding snails were surprising in not being more dramatically altered relative to controls than they were . This is because snails with more advanced schistosome infections ( 28+ day infections ) experience several noteworthy physiological changes , including altered feeding behavior , decreased locomotory activity , increased heartbeat rate [118–121 , 123] and castration ( see section below ) . From our shedding snails , we noted up-regulated levels of FMRF-amide receptor and small cardioactive peptides that influence heart beat rate . Shedding snails also uniquely showed up-regulated levels of CDS involved in collagen synthesis or epithelial cell and blood vessel formation , processes involved in wound healing [49 , 123 , 124] , of relevance to a snail experiencing the tissue damage associated with cercarial emergence . Other up-regulated features are indicative of stress . Modestly up-regulated levels of reverse transcriptase are of interest because of previous reports of enhanced RT activity in susceptible B . glabrata exposed to S . mansoni [115] . Down-regulated levels of features potentially helping to explain reduced growth rates [125 , 126] , reduced motility [119 , 120 , 127 , 128] or depleted levels of hemoglobin [129] observed in shedding snails were noted ( S3 File ) . Other down-regulated features of interest were noted including tyrosinase , which is involved in melanin synthesis ( see also discussion of reproduction ) . Snails infected with the proliferating larval stages of digenetic trematodes , including B . pfeifferi infected with S . mansoni , suffer parasitic castration , marked by a sharp or complete reduction in production of eggs [121 , 125 , 130] . In B . pfeifferi , egg-laying begins to decline 7–10 days following exposure to S . mansoni and is complete in most snails by 14 days . The time course and extent of castration are influenced by the age of the snail at the time of exposure and by the dose of miracidia received [130 , 131] . In some cases , a slight increase in egg production compared to unexposed controls can be seen in the pre-shedding period , but this is followed by castration [125 , 130 , 131] . Studies of the reproductive physiology of freshwater gastropods have identified a number of peptides and non-peptide mediators ( including biogenic monoamines ) involved in neuro-endocrine control of reproduction [132 , 133] . We found evidence for the presence and expression of homologs of over 50 of these neuropeptides in B . pfeifferi ( S4 File; Fig 9 ) and several additional neuropeptide precursors . It has also been noted that in B . glabrata castrated by S . mansoni , repeated exposure to serotonin enabled snails to resume egg-laying [134] . Furthermore , dopamine is present in reduced levels in infected snails , and administration of this catecholamine stimulated the release of secretory proteins from albumen gland cultures of B . glabrata [135] and the related snail Helisoma duryi [136] . Although infections of 1 or 3 days duration are too young to manifest castrating effects , up-regulation of some features with possible inhibitory effect on reproduction were noted at these times . Several features were also down-regulated at 1 day , including ovipostatin 2 , a type 1 serotonin receptor ( relevant because of serotonin’s ability to stimulate egg-laying ) , and schistosomin . Schistosomin has been implicated in Lymnaea stagnalis in inhibiting hormones involved in stimulating egg-laying or the albumen gland [137] . A role for schistosomin in reproduction or trematode-mediated castration was not found in B . glabrata infected with S . mansoni [138] and we saw no change in its expression in B . pfeifferi . Kynurenine 3-monooxygenase-like transcripts were up-regulated in all snails with 3 day infections . By degrading tryptophan , this enzyme may limit concentrations of serotonin . It was of interest to learn if the water-borne pheromones ( temptin , enticin , seduction , and attractin ) that favor aggregation in Aplysia [139] were expressed in B . pfeifferi , especially given its preference for self-fertilization . We found evidence only for the expression of temptin , which was up-regulated at 3d , but otherwise was not differentially expressed . Likewise , only temptin was isolated in proteins released from B . glabrata [37] and egg-mass proteins [140] . It has been shown to be an attractant for B . glabrata [141] . Our results with shedding snails are most pertinent with respect to parasitic castration . Several reproduction-related neuropeptides , including caudal dorsal cell hormone , and neuropeptides associated with production of egg and egg mass fluids such as snail yolk ferritin ( vitellogenin ) , galactogen synthesis , lipopolysaccharide binding protein/bacterial permeability-increasing proteins ( LBP/BPI ) or aplysianin/achacin-like protein [140] were not strongly down-regulated as a consequence of infection . Some of the most obvious changes we noted were up-regulated levels of transcripts encoding dopamine beta hydroxylase and especially dopamine beta-hydroxylase–like monooxygenase protein 1 , both of which convert dopamine to noradrenaline so their enhanced expression may help to explain the declining levels of dopamine noted in S . mansoni-infected snails [134] . This may in turn help to explain diminished egg production given dopamine’s effect on release of albumen gland proteins . Tyrosinase-1 , involved in production of melanin , is down-regulated in shedding snails and this may have the effect of preserving dopamine levels in these snails . At both earlier sampling points , tyrosinase-1 is strongly up-regulated especially in snails with abundant S . mansoni reads , and thus may mark an early phase in initiation of castration by diverting tyrosine to production of melanin as opposed to dopamine . Transcription of enzymes involved in dopamine metabolism are strongly affected in S . mansoni-infected snails . Tyrosinase-1 is also discussed in the next section regarding its potential involvement in defense responses . There are numerous ovipostatins produced in Biomphalaria ( we found 6 different versions in B . pfeifferi ) , with ovipostatin 5 being the most prominent responder in shedding snails . In L . stagnalis , ovipostatin is passed in seminal fluid from one individual to another during mating and inhibits oviposition in the recipient [132] . Although B . pfeifferi is predominantly a self-fertilizer [20] , ovipostatin 5 could potentially down-regulate oviposition in ways not reliant on copulation . Neuropeptide Y inhibits egg-laying in L . stagnalis [142] and though we did not observe up-regulation of this neuropeptide , up-regulated transcripts for neuropeptide Y receptor type 5-like protein in our shedding snails is consistent with a possible enhanced inhibitory effect on reproduction of neuropeptide Y . Strong up-regulation of transcripts for yolk ferritin-like and snail yolk ferritin molecules ( vitellogenins ) in shedding snails was also observed and is somewhat paradoxical but may suggest they are diverted to the parasite for metabolism since it is known that schistosomes require iron stores for development [143] . Notably , the extent of up-regulation for yolk ferritin-like and snail yolk ferritin , ovipostatin 5 , neuropeptide Y receptor type 5-like , and dopamine beta-hydroxylase-like , was the least in the shedding snail expressing the lowest number of normalized S . mansoni reads . Wang et al . [133] recently used proteomics methods ( liquid chromatography tandem mass spectrometry ) to examine and identify neuropeptides in central nervous system ( CNS ) ganglia dissected from B . glabrata , either from control snails or snails at 12 days post infection with S . mansoni . They noted many reproductive neuropeptides , such as egg laying hormone 2 , at significantly reduced levels at 12d compared to controls . They also reported an increase in some neuropeptides including FMRFamide , luqin , NKY , and sCAP in infected snail CNS . Based on predicted protein interaction networks , Wang et al . [133] suggested that snail-produced leucine aminopeptidase 2 ( LAP2 ) interacts with several S . mansoni miracidia peptides so may be a key player in regulating parasite-induced changes in host physiology . A homolog to the B . glabrata LAP2 was present in our transcriptome but was not differentially expressed in any sample . When comparing our results to those of Wang et al . [133] , it should be noted that our approach was transcriptome-centered , examined different time points post-infection , and was based on whole body extractions of B . pfeifferi , rather than B . glabrata . Our methods may bias against detection of changes in expression of potentially rare neuropeptide transcripts , but cast a wider net for potential downstream effects of castration , so provides a valuable complementary view to the approach taken by Wang et al . [133] . At 1d ( S4 File; Fig 10 ) , several immune-relevant CDS were up-regulated in all three snails including dermatopontins ( frequently noted in B . glabrata studies ) , ficolins [48] , and chitinase attacking enzymes [42 , 48] . For the two snails with the highest proportions of S . mansoni reads , up-regulated responses were observed for a number of additional immune features . Cu , Zn SOD is of particular interest because previous work has implicated high expression of certain alleles of Cu , Zn SOD with resistance to S . mansoni in the 13-16-R1 strain of B . glabrata , because of Cu , Zn SOD’s involvement in converting superoxide anion to schistosomicidal hydrogen peroxide [144–146] . Our study is in agreement with Hanington et al . [47] who noted up-regulated levels of Cu , Zn superoxide dismutase ( SOD ) at early time points following exposure of susceptible M line B . glabrata to either S . mansoni or E . paraensei . Hanington et al . [47] also found both FREP2 and FREP4 to be consistently up-regulated following exposure of M line B . glabrata to S . mansoni or E . paraensei , so much so either might be considered as markers of infection . Although a FREP2 homolog was consistently up-regulated following exposure of B . pfeifferi to infection , a FREP4 homolog was not expressed in B . pfeifferi at any of the time points we examined . In contrast , among CDS more up-regulated in the 1 day infected snail with a low proportion of S . mansoni reads were macrophage expressed gene-1 , known to be up-regulated in both abalone following bacterial infection [147] and from resistant and non-susceptible strains of B . glabrata in early exposure to S . mansoni [148] . Hemocytin was also up-regulated in the 1d snail with low proportion of S . mansoni reads . Hemocytin , a homolog for an insect humoral lectin with a role in hemocyte nodule formation [149] , was consistently up-regulated in all S . mansoni-infected snails at all three time points , especially at 3d when it was increased over 8-fold in expression . For both 1 and 3d , hemocytin expression was highest in those snails with fewer S . mansoni reads . FREP3 , previously implicated in resistance to S . mansoni in B . glabrata [52] , was minimally responsive in this compatible B . pfeifferi system . It was modestly up-regulated only at 1d , in the snail with fewest S . mansoni reads . Down-regulated immune features at 1d were relatively few but prominent among them were FREP12 and its precursors , toll-like receptor 8 and cytidine deaminase . FREP12 down-regulation has also been noted upon exposure of B . glabrata amebocyte-producing organs to fucoidan , a fucosyl-rich PAMP chosen to mimic the surface of S . mansoni sporocysts [48] , and in B . glabrata exposed to S . mansoni [47] . A strain of B . glabrata resistant to S . mansoni exhibits higher levels of a TLR on its immune cells , and exposure to S . mansoni significantly enhances their expression , whereas compatible snails show little response following exposure to infection [31] . Our B . pfeifferi showed no conspicuously up-regulated TLR genes at 1d , and we found no B . pfeifferi TLR with strong homology to the TLR reported by Pila et al . [31] , but the relatively strong down-regulation of TLR 8 in this model of compatibility is noteworthy . Although the immune role of cytidine deaminase is not clear , Bouchut et al . [150] associated higher levels of its expression with enhanced resistance to echinostome infections and Ittiprasert et al . [148] observed up-regulation of cytidine deaminase in resistant and non-susceptible B . glabrata in early exposure to S . mansoni . Down-regulation of cytidine deaminase might therefore be associated with lower responsiveness to S . mansoni infections , particularly early in infection ( down-regulation also noted at 3d , but not in shedding snails ) . The responses of putative immune factors were most extensive in snails at 3d and this is not surprising as this is a critical stage in the early establishment of the parasite . Several CDS mentioned with respect to the 1d response were again noted at 3d . Snails with more S . mansoni reads had high levels of several transcripts including for aplysianin-like proteins and FREP 5 . Aplysianin , first described from Aplysia , is an L-amino oxidase that has tumoricidal and bactericidal effects [151] , and a distinct aplysianin-like protein exists in egg mass fluids of B . glabrata [140] . Aplysianin-like transcripts were more abundant in echinostome-resistant than susceptible strains of B . glabrata [150] . FREP 5 was shown to be down-regulated in microarray studies of B . glabrata in response to successfully developing S . mansoni or Echinostoma paraensei [47] . The snail with relatively few S . mansoni reads at 3d revealed a different group of up-regulated transcripts , with hemocytin again being prominent . Also notable were distinctive CDS potentially involved in hemocyte aggregation [152] , FREP 7 , peptidoglycan-recognition proteins SC2-like ( PGRPs ) , and TLR 13 . PGRPs are well-known anti-bacterial factors and were found to be up-regulated following exposure of B . glabrata to LPS [153] and to bacteria [53] . Down-regulated features for snails with 3d infections again included cytidine deaminase , FREP12 precursors , and TLR 4 and 8 among others . Laccases and tyrosinases are two groups of phenoloxidases observed to be responsive in early S . mansoni infection within B . pfeifferi ( Table 6; S4 File ) . Tyrosinase has been isolated from B . glabrata egg masses with a presumptive immunoprotective effect for offspring [140 , 154] . As mentioned earlier with details of its reproductive consequences , tyrosinase-1 was up-regulated at 1d and 3d . Tyrosinase-1 was down-regulated in the shedding replicate with the least S . mansoni reads and tyrosinase-3 was down-regulated in the two replicates with the most S . mansoni reads . Another type of phenoloxidase , laccase , was shown to have decreased activity in B . glabrata hemolymph beginning at 7 weeks post-infection with S . mansoni [155] . We found laccase-15-like was up-regulated in all three comparisons ( 3v3 , 3v2 , 3v1 ) at both 1d and 3d . Laccase-1-like was up-regulated in all three comparisons at 1d and laccase-2-like was up-regulated in all comparisons at 3d . Laccases were not significantly DE in shedding snails . In B . pfeifferi , the up-regulation of two phenoloxidases , tyrosinase and laccase , at 1d and 3d suggests an increase in the synthesis of early-stage reactions in the melanin pathway , however , further work is needed to determine if melanization is involved in schistosome killing , especially in the B . pfeifferi model characterized by its compatibility . It is worth noting that members GTPase IMAP family ( GIMAP ) were found to be up-regulated in 1d and 3d ( mostly up-regulated in 3d ) . The possible role of GIMAPs in immunity has not been realized in protostomes until it was shown that several GIMAPs were up-regulated in the amebocyte organ of B . glabrata following exposure to extrinsic stimuli [48] . This finding was reconfirmed by later work , which demonstrated that GIMAPs not only play a role in immunity , but are highly diverse in the eastern oyster Crassostrea virginica where they were down-regulated following exposure to bacterial infection . GIMAPs may promote hemocyte survival by inhibiting apoptosis [156] . Immune-related responses for shedding snails were surprising for being mostly up-regulated ( Fig 10 ) , with only a few features being modestly down-regulated , among them galectin-6 . Galectins recognize carbohydrates associated with schistosome surfaces and are implicated as pattern recognition receptors for other pathogens as well [157] . Dihydropyrimidinase and cytidine deaminase , also down-regulated , are additional CDS potentially affecting pyrimidine levels in infected snails . Interestingly , in contrast to 1d and 3d responses , shedding snails did not show up-regulated Cu , Zn SOD levels . Among those up-regulated features , shedding snails with high levels of S . mansoni reads had distinctly higher responses for aplysianin-A-like , beta-1 , 3-glucan binding protein-like , and FREPS 2 , 7 and 14 . By contrast , the snail with a low percentage of S . mansoni reads expressed higher levels of macrophage-expressed gene , chitinase-3-like-protein , a distinct CDS with a leucine rich repeat and immunoglobulin domain , and TLR 3 . Features highlighted in recent genetic linkage studies [32 , 50 , 51] including components of the “Guadeloupe Resistance Complex” were sought among B . pfeifferi transcripts . Most did not show strong patterns of up- or down regulation in this compatible species following exposure to S . mansoni , but zinc metalloproteinase/disintegrin-like was down-regulated at 1d and zinc metalloproteinase nas-13- and -14-like showed some up-regulation in shedding snails . Probable serine carboxypeptidases ( versions 1–5 ) revealed a mixed pattern of expression at 3d , but were mostly up-regulated , whereas probable serine carboxypeptidase CPVL was down-regulated in shedding snails . Granulin , a growth factor that drives the proliferation of immune cells was up-regulated at both 1d and 3d [30 , 33] . Unlike B . glabrata for which isolates or inbred lines are known that are resistant to S . mansoni , B . pfeifferi is a species typically discussed in the context of its high compatibility with many S . mansoni isolates . Although particular lineages of B . pfeifferi may certainly come to light that exhibit strong incompatibility , key factors that dictate compatibility might best be sought not among the putative immune factors that characterize the B . glabrata response , but among those genes that exhibit the strongest transcriptional responses , up or down , to S . mansoni exposure ( Table 5; S3 File ) . Strongly up-regulated snail genes may be responsible for encoding proteins essential to S . mansoni development , and those strongly down-regulated may represent parasite-manipulated factors that if left un-manipulated would otherwise discourage parasite development . Certainly such a role has been proposed for schistosomes in altering expression of genes in compatible snails to their advantage [158–160] . Although many B . pfeifferi CDS that were highly altered in their expression are unknowns and thus represent intriguing subjects for future research , some did have homologs in the database and could also represent outstanding future targets for manipulation to discourage S . mansoni development . For example , we note the up-regulation of the protease inhibitor papilin-like and galactocerebrosidase-like . Galactocerebrosidase is an enzyme that removes galactose from galactocerebrocide ( a ceramide sphingolipid with a galactose residue ) to form a ceramide , an important lipid signaling molecule that has been reported in Crassostrea gigas [161] . A transcript coding for deleted in malignant brain tumor 1 protein-like ( DMBT1 ) was also highly up-regulated in all shedding snails . DMBT1 is a pattern recognition receptor in mammals that belongs to a group of secreted scavenger receptors involved in pathogen binding [162] . However , its role in invertebrate systems needs to be established [159] . In conclusion , provided here is a de novo assembled transcriptional database based on over half a billion paired-end reads for an understudied schistosome vector , B . pfeifferi , one that is probably responsible for transmission of more S . mansoni to people than any other Biomphalaria species . We have deliberately chosen to emphasize the study of field-derived B . pfeifferi and S . mansoni to provide a more realistic view of the context in which they live , and how they interact in the wild , including with third party symbionts . Our approach has revealed that the extent of S . mansoni transcriptional activity varies among snails and this is reflected in different transcriptional responses of the snails , suggestive of diverse trajectories in what is typically a highly compatible host-parasite model . We have highlighted several snail features warranting further study with respect to their roles in potentially supporting or enabling parasite development , that might limit the extent of development , and that might play a role in the diminished egg production typically shown by snails with shedding S . mansoni infections . Another generation of research exploiting the power of techniques like CRISPR-Cas , when it becomes available for snails , will enable further dissection of the functional role of these candidate molecules . A further challenge will then be to determine how the responses of compatible snails , or perhaps of the schistosome parasites within , can be exploited , ideally to prevent or suppress in a highly specific manner the development of schistosome parasites in snails .
|
Biomphalaria pfeifferi is the world’s most important snail vector for the widespread human-infecting blood fluke Schistosoma mansoni . Despite this , we know relatively little about the biology of this highly compatible African snail host of S . mansoni , especially for specimens from the field . Using an Illumina-based dual-seq approach , we captured a portrait of the transcriptional responses of Kenyan snails that were either uninfected with S . mansoni , or that harbored 1-day , 3-day , or cercariae-producing infections . Responses to infection were influenced both by the extent of schistosome gene expression and infection duration . We note and discuss several alterations in transcriptional activity in immune , stress and reproduction related genes in infected snails and the B . pfeifferi symbionts detected . Several host genes were highly up-regulated following infection and these might comprise excellent candidates for disruption to diminish compatibility . This study provides for the first time a large sequence dataset to help in interpreting the important vector role of B . pfeifferi in transmission of S . mansoni , including with an emphasis on more natural , field-derived specimens .
|
[
"Abstract",
"Introduction",
"Methods",
"Results",
"Discussion"
] |
[
"schistosoma",
"invertebrates",
"schistosoma",
"mansoni",
"medicine",
"and",
"health",
"sciences",
"biomphalaria",
"helminths",
"immunology",
"parasitic",
"diseases",
"animals",
"invertebrate",
"genomics",
"physiological",
"processes",
"gastropods",
"genome",
"analysis",
"snails",
"immune",
"system",
"proteins",
"genomics",
"molting",
"proteins",
"molluscs",
"animal",
"genomics",
"toll-like",
"receptors",
"biochemistry",
"signal",
"transduction",
"eukaryota",
"cell",
"biology",
"physiology",
"transcriptome",
"analysis",
"genetics",
"biology",
"and",
"life",
"sciences",
"immune",
"receptors",
"computational",
"biology",
"organisms"
] |
2017
|
Transcriptomic responses of Biomphalaria pfeifferi to Schistosoma mansoni: Investigation of a neglected African snail that supports more S. mansoni transmission than any other snail species
|
Salmonella enterica serotype Typhi is the cause of typhoid fever . It is a human-restricted pathogen , and few data exist on S . Typhi gene expression in humans . We applied an RNA capture and amplification technique , Selective Capture of Transcribed Sequences ( SCOTS ) , and microarray hybridization to identify S . Typhi transcripts expressed in the blood of five humans infected with S . Typhi in Bangladesh . In total , we detected the expression of mRNAs for 2 , 046 S . Typhi genes ( 44% of the S . Typhi genome ) in human blood; expression of 912 genes was detected in all 5 patients , and expression of 1 , 100 genes was detected in 4 or more patients . Identified transcripts were associated with the virulence-associated PhoP regulon , Salmonella pathogenicity islands , the use of alternative carbon and energy sources , synthesis and transport of iron , thiamine , and biotin , and resistance to antimicrobial peptides and oxidative stress . The most highly represented group were genes currently annotated as encoding proteins designated as hypothetical , unknown , or unclassified . Of the 2 , 046 detected transcripts , 1 , 320 ( 29% of the S . Typhi genome ) had significantly different levels of detection in human blood compared to in vitro cultures; detection of 141 transcripts was significantly different in all 5 patients , and detection of 331 transcripts varied in at least 4 patients . These mRNAs encode proteins of unknown function , those involved in energy metabolism , transport and binding , cell envelope , cellular processes , and pathogenesis . We confirmed increased expression of a subset of identified mRNAs by quantitative-PCR . We report the first characterization of bacterial transcriptional profiles in the blood of patients with typhoid fever . S . Typhi is an important global pathogen whose restricted host range has greatly inhibited laboratory studies . Our results suggest that S . Typhi uses a largely uncharacterized genetic repertoire to survive within cells and utilize alternate energy sources during infection .
Salmonella enterica serotype Typhi is a Gram-negative bacterium and the cause of typhoid fever . Typhoid fever affects over 21 million people each year , killing 200 , 000 [1] . S . Typhi is a human-restricted pathogen and this has greatly limited studies of S . Typhi pathogenesis . Our current understanding of S . Typhi responses during infection is largely based on the study of murine models with the related bacterium S . Typhimurium ( i . e . , a bacteria that causes a typhoid-like illness in mice ) [2] , a separate mouse model of S . Typhi infection [3] , and ex vivo macrophage and epithelial cell models of S . Typhi and S . Typhimurium [4] However , these studies have limitations , and do not fully replicate human disease . For instance , despite high sequence similarity , 13% of the genes in the S . Typhi genome are absent from S . Typhimurium , and the S . Typhi chromosome contains over 200 pseudogenes that S . Typhimurium does not [5] , [6] . Here we report the application of an mRNA/cDNA capture and amplification technology , Selective Capture of Transcribed Sequences ( SCOTS ) , combined with cDNA hybridization technology [7]–[12] , to directly assess the gene expression profile of S . Typhi in the blood of humans with typhoid fever in Bangladesh . We previously applied this technology to S . Paratyphi A , the 2nd leading cause of enteric fever , and detected expression of over 1700 bacterial genes during human infection [12] . Here we report the extension of this analysis to S . Typhi .
This study was approved by the Ethical and Research Review Committees of the International Centre for Diarrhoeal Disease Research , Dhaka , Bangladesh ( ICDDR , B ) and the Human Research Committee of Massachusetts General Hospital; the study was conducted according to the principles expressed in the Declaration of Helsinki/Belmont Report . Written informed consent was obtained from all individuals or their guardians prior to study participation . Individuals presenting to the International Centre for Diarrhoeal Disease Research , Bangladesh ( ICDDR , B ) Hospital or the Kamalapur field site of ICDDR , B were eligible for enrollment if they met the following criteria at presentation: age of 1–59 years , fever duration of 3–7 days ( ≥39°C ) , no obvious focus of infection , and no alternate diagnosis . We collected 2 ml of venous blood from participants , immediately placed these specimens in TRIzol ( Invitrogen Life Technologies , Carlsbad , CA ) at a 1 ( blood ) ∶2 ( TRIzol ) volume ratio , and stored the samples at −70°C for later analysis . We simultaneously obtained 3–5 ml of blood for microbiologic analysis using a BacT/Alert automated system . We sub-cultured positive bottles on MacConkey agar , and identified S . Typhi isolates using standard biochemical tests and reaction with Salmonella-specific antisera [13] . After we collected blood , we treated patients with parenteral ceftriaxone , oral ciprofloxacin , or oral cefixime for up to 14 days at the discretion of the attending physician . To generate S . Typhi cDNA from blood samples , we used TRIzol-preserved blood of patients whose initial cultures were subsequently confirmed to grow S . Typhi . To create a corresponding in vitro S . Typhi cDNA sample for comparison , we grew each patient's bacterial isolate to mid-log growth phase ( OD600 0 . 45–0 . 6 ) in Luria Bertani ( LB ) broth , and preserved the samples in TRIzol at a 1 ( mid-log culture ) ∶2 ( TRIzol ) volume ratio . We extracted total RNA from TRIzol preserved samples per the manufacturer's instructions ( Invitrogen ) and treated recovered RNA with DNase I on RNeasy columns ( Qiagen Inc . , Valencia , CA ) . We then converted 5 µg of total RNA into cDNA for each sample , as previously described with a few modifications [12] . Briefly , we used random priming ( T-PCR ) to obtain a representative amplifiable double-stranded cDNA population by using Superscript III ( Invitrogen ) with a conserved primer with a defined 5′ end terminal sequence and a random nonamer at the 3′ end [14] . We then synthesized second strands using the same primers and Klenow fragment ( Invitrogen ) according to the manufacturer's instructions , and then equilibrated samples based on 16S S . Typhi rRNA . We separated bacterial cDNA from host DNA using SCOTS , as previously described [12] . Briefly , we mixed denatured biotinylated S . Typhi gDNA with blocking ribosomal S . Typhi DNA , and added this denatured mixture to both in vivo and in vitro cDNA samples . After hybridizing samples overnight at 67°C , we captured biotinylated S . Typhi gDNA-cDNA hybrids using streptavidin-coated magnetic beads ( Dynabeads M-280 streptavidin , Invitrogen ) , eluted captured cDNA with NaOH , PCR-amplified cDNA samples with conserved primers , and purified products using Qiagen PCR column purification kits . We performed three rounds of capture and amplification to separate S . Typhi cDNA from host DNA and to generate the cDNA mixture used for microarray hybridization . We labelled in vivo and in vitro cDNA recovered from SCOTS with Cy3 and Cy5 , respectively , and hybridized these preparations to Salmonella ORF microarrays ( version STv7S; McClelland Laboratory , Vaccine Research Institute of San Diego , CA , http://www . sdibr . org/Faculty/mcclelland/mcclelland-lab ) in duplicate and with two dye reversals as previously described [12] . These microarrays contained gene-specific PCR-products of 4 , 600 ORFs from Salmonella enterica serotype Typhi CT18 ( 98 . 6% genome coverage ) and 4 , 318 ORFs of strain Ty2 ( 98 . 0% genome coverage . The arrays also contained 1049 S . enterica ORFs absent from the S . Typhi genome . We used an equal amount of in vivo and in vitro Cy dye-labeled product on all slides for a given patient . We used ScanArray software ( ScanArray express , version 3 . 0 . 1 ) to quantify signal intensities . For each individual patient , we considered a gene to be detected in vivo if at least 2 of the 3 replicate gene spots on each of the four slides for that infected human was at least ten median absolute deviations greater than the median of spots on the microarray corresponding to genes absent from the S . Typhi CT18 or Ty2 genomes . For those genes we detected in vivo , we evaluated whether there was a difference in expression when compared to detection levels for in vitro grown organisms . For this latter statistical analysis , we included genes with a coefficient of variation in signal intensity less than 50% within an array , and employed repeated measures ANOVA ( to within slide replicate spots ) with type ( in vivo versus in vitro ) and dye effects to LOESS-normalized , log-transformed data . Those genes with a False Discovery Rate of less than 0 . 05 computed using Benjamini-Hochberg multiple testing adjustment and a 2-fold variation in signal intensity were considered differentially expressed in vivo versus in vitro . We deposited data in the NCBI Gene Expression Omnibus ( GEO , www . ncbi . nlm . nih . gov/geo ) , accessible through GEO accession number GSE30565 . We based functional classification of genes on J . Craig Venter Institute annotations ( http://cmr . jcvi . org/tigr-scripts/CMR/CmrHomePage . cgi ) . We used quantitative real time PCR ( RT-qPCR ) to confirm microarray results for a subset of genes . We compared mRNA levels in the peripheral blood ( in vivo sample ) of infected patients ( i . e . the 5 patients included in our SCOTS array analysis and 5 additional patients ) to three in vitro culture replicates of a S . Typhi isolate ( from Patient 1 ) grown to mid-logarithmic phase in LB ( in vitro sample ) , as previously described [12] . To maximize the likelihood of detecting differences in gene expression in comparative samples , we selected eight representative genes from operons involved in intra-cellular invasion or survival ( STY4609 , sopE , invasion-associated secreted protein; STY3639 , trxA , thioredoxin ) ; alternate energy usage ( STY2244 , pduB , putative propranediol utilization protein; STY0417 , psiF , phosphate starvation-inducible protein; STY2701 , eutN , a putative ethanolamine utilization protein; STY0634 , fepC , a ferric enterobactin transport ATP-binding protein ) ; and bacterial adhesion ( STY0207 , staA , putative fimbrial protein and STY4543 , pilO , putative pilus assembly protein ) , focusing on genes with high baseline signals and fold-increases by SCOTS-cDNA hybridization analysis comparing in vivo ( high signal ) to in vitro ( low signal ) samples . We also quantified by RT-qPCR the expression levels of two house-keeping genes that were predicted by SCOTS-cDNA hybridization to be equally expressed in in vivo and in vitro samples ( STY0724 , encoding a glutaminyl-tRNA synthetase , glnS; and STY3081 , encoding an enolase , eno ) . We were unable to reproducibly assess expression levels of genes predicted by SCOTS-cDNA hybridization to be down-regulated in blood samples compared to in vitro grown organisms . To generate cDNA for quantitative RT-PCR from TRIzol-preserved samples , we used SuperScript II ( Invitrogen ) with random hexamers ( Sigma , St . Louis , MO ) according to the manufacturer's instructions , and performed RT-qPCR analysis using iQ SYBR Green Supermix reagent ( Bio-Rad; Hercules , CA ) and a CFX96 Real-time PCR detection system ( Bio-Rad; Hercules , CA ) as previously described [12] . Primers are listed in the Supplemental Table S1 . We used no-template controls and samples lacking reverse transcriptase as baseline reactions for each sample . After calculating the threshold cycle ( CT ) in the low/linear portion of product curves , we quantified gene copy numbers using pGEM-T Easy-based plasmids ( Promega , Madison , WI ) containing the gene of interest . To calculate the control gene copy number , we used plasmid size and A260 readings , and normalized gene copy numbers based on cDNA copies of 16S rRNA . We assessed singularity of product species and size by melting curve analysis , as previously described [15] .
Of the 89 patients enrolled for blood sample collection , we identified 10 patients with confirmed S . Typhi bacteremia at the time of TRIzol-preserved blood collection . We performed SCOTS-cDNA hybridization screening analysis using samples from patients 1–5 , and performed RT-qPCR on samples from patients 1–10 , as sample quantity permitted . Using SCOTS-cDNA hybridization technology , we detected expression of 2046 S . Typhi genes in the blood of bacteremic patients . This represents approximately 44% of the S . Typhi ORFeome ( Figure 1A , Supplemental Table S2 ) . Of these , we detected expression of 912 genes in all 5 patients ( 45% of detected transcripts ) , and 1100 in at least 4 of the 5 patients ( 54% of detected transcripts ) . The products encoded by the 1100 genes identified in 4 or more patients fell into a number of functional categories ( Figure 1B ) . The most highly represented group were genes currently annotated to encode hypothetical proteins or proteins designated as unknown or unclassified . The next most highly represented groups were genes that encode products involved with energy metabolism , transport and binding , followed by genes encoding products of the cell envelope or associated with cellular processes and pathogenesis . Ninety-five of the 1100 genes were located within known Salmonella pathogenicity islands ( SPI 1–7 , 9 , 10 , 13 , and 16 ) , and 29 are known components of the PhoP regulon , a major virulence regulon in Salmonella , involved in intra-macrophage survival . A total of 31 genes were detected in 4 or more patients in vivo , but not detected in any in vitro sample ( Table 1 ) . The majority of these genes are involved with survival in nutrient-limited conditions including psiF , a phosphate starvation-inducible protein; bioF and thiG involved in vitamin biosynthesis; eutD , oadG , and pduB involved in use of alternative carbon sources; and fepD involved in iron acquisition . Of the 2046 transcripts detected in human blood samples , 1320 ( representing 29% of S . Typhi ORFeome ) had significantly different levels of detection in in vivo samples compared to bacterial samples grown in vitro ( Figure 2A , Table S2 ) . Detection levels for 141 transcripts were significantly different between in vivo and in vitro samples in all 5 patients , and 331 in at least 4 patients . These 331 encode products that fall into a number of functional categories ( Figure 2B ) . The most highly represented group included proteins annotated as hypothetical , unknown , or unclassified . Other highly represented groups included energy metabolism , transport and binding , the cell envelope , and cellular processes and pathogenesis . To confirm S . Typhi mRNA expression levels in human blood compared to in vitro grown bacteria , we used RT-qPCR to assess the copy number of the following eight genes that had high in vivo baseline reactivity as well as fold-change between in vivo and in vitro samples by SCOTS array analysis: thioredoxin , trxA ( STY3639 ) ; a putative fimbrial protein , staA ( STY0207 ) ; an invasion-associated secreted protein , sopE ( STY4609 ) ; a putative propranediol utilization protein , pduB ( STY2244 ) ; a putative pilus assembly protein , pilO ( STY4543 ) ; an phosphate-inducible starvation protein , psiF ( STY0417 ) ; a putative ethanolamine utilization protein , eutN ( STY2701 ) ; and a ferric enterobactin transport ATP-binding protein , fepC ( STY0634 ) . Compared to expression levels in in vitro grown bacteria , we found increased expression of all 8 genes in the blood of infected humans , including in humans not analyzed by the SCOTS-cDNA hybridization screening protocol ( Figure 3 , A–H ) . As predicted by our SCOTS screening , we found no differences by RT-qPCR in the expression of housekeeping genes glnS ( STY0724 ) and eno ( STY3081 ) in blood versus in vitro bacterial samples ( Figure 3 , I-J ) .
S . Typhi is a human-restricted pathogen , the cause of typhoid fever , and a significant cause of global morbidity and mortality . Despite this , there are limited data on bacterial events within humans infected with S . Typhi . Here we describe the application of a cDNA capture-amplification approach combined with microarray hybridization technology to assess S . Typhi gene expression directly in the blood of infected humans . In total , we detected 2046 S . Typhi transcripts in human blood ( 45% of S . Typhi transcriptome ) ; we detected 1100 in at least 4 of 5 patients . Two major virulence determinants of Salmonella are the ability to invade host cells and the ability to survive and replicate within host cells . The PhoPQ-two component regulatory system is involved in intra-macrophage survival and antimicrobial resistance [16] , and Salmonella pathogenicity island-1 ( SPI-1 ) and SPI-2 encode type three secretion systems ( T3SSs ) involved in invasion of host cells and intracellular survival and replication , respectively [17] , [18] . In our analysis , we identified 29 genes involved in the PhoP regulon as more highly expressed in human samples , including the two component regulator itself , phoPQ; virk , a virulence protein; mgtBC , involved in magnesium transport; pmrF , a antimicrobial resistance protein; and slyB , an outer membrane lipoprotein [19] , [20] . We also identified 95 genes located within previously described SPIs , including SPI-1 and 2 , as well as genes within SPI-3–7 , 9 , 10 , 13 , and 16 . The role of SPI-1 in invasion of epithelial cells has been well established [21] . We detected a number of transcripts associated with SPI-1 genes , including a number that encode effector proteins injected into eukaryotic cells via the SPI-1 T3SS , such as SipB . We also detected a number of transcripts encoding SPI-1 T3SS effector proteins expressed from other SPIs , including sopE ( expressed from SPI-7 ) and sopB/sigD ( expressed from SPI-5 ) ; SopB/sigD is involved in creation and maintenance of the Salmonella Containing Vacuole ( SCV ) , crucial to intra-cellular survival of Salmonella in eukaryotic cells [22] . Of note , we similarly identified SPI-1 transcripts in our recent analysis of S . Paratyphi A cDNA in the blood of infected humans in Bangladesh [12] . Our detection of these transcripts in the blood of infected humans builds upon recent suggestions that the SPI-1 T3SS is involved in pathogenic events beyond intestinal epithelial cell invasion during enteric fever [23]–[25] . In addition to sopE , we also detected transcripts from the Type IV pilus operon encoded within SPI-7 , including pilL , pilO , pilQ , pilR , pilU , and pilV , which facilitates invasion of Salmonella into epithelial cells and monocytes [26] , [27] . Identification of SPI-7 genes in our analysis is of particular interest since SPI-7 is absent from S . Typhimurium and S . Paratyphi A , but present in S . Typhi , S . Paratyphi C , and S . Dublin [28] . In addition to those associated with SPIs and the PhoPQ regulon , we detected transcripts from a number of virulence-associated Salmonella genes in human blood . These include aromatic amino acid biosynthesis pathway genes ( aroG , aroD , aroH , aroE , aroB ) ; mutations in this pathway have been the basis of live attenuated S . Typhi vaccines [29] . We also detected transcripts from genes involved in purine biosynthesis ( guaB , purG , purA ) [30] and divalent cation transport including Mg2+ ( corA , mgtBC ) [31]–[33] , and Fe 2+ and Mn2+ uptake systems ( sitBC and mntH ) [34] that have all been associated with virulence in Salmonella . In order to adapt to the intracellular environment , Salmonella must alter its metabolism to available nutrient and energy sources . We detected transcripts of genes involved in the use of alternative carbon sources , the coenzyme B12-dependent 1 , 2-propranediol utilization pathway ( encoded by the pdu operon ) , and the ethanolamine utilization pathway ( encoded by the eut operon ) . We also found these operons to be up-regulated in our analysis of S . Paratyphi A genes detected in the blood of humans [12] , and mutations in these operons result in attenuation of virulence in S . Typhimurium infection models [35]–[37] . We also identified transcripts expressed from genes encoding three NiFe-uptake hydrogenases that have been associated with virulence in S . Typhimurium , including hydrogenase A , B and D [38] . Prior studies have shown that the hya and hyd operons are upregulated in murine and human phagocytes; hya genes are required for survival within macrophages , and both hya and hyd genes were detected in mice using the RIVET ( Resolvase In-Vivo Expression Technology ) reporter system that identifies genes expressed in vivo [39] . Our analysis shows that these genes are also expressed by S . Typhi during human infection . Other potential virulence-associated genes that we identified included genes involved in thiamine biosynthesis ( e . g . thiG , thiJ , abpA ) , biotin biosynthesis ( e . g . bioB , bioF , kbl ) , iron acquisition via siderophore biosynthesis ( e . g . iroA gene cluster , fes , fepECDB ) , and phosphate transport ( ugpBAEC operon ) , many of which were also detected in our transcriptional analysis of S . Paratyphi A in infected humans [12] . In addition to survival in nutrient-limited conditions , Salmonella must also be able to survive the action of antimicrobial peptides , oxidative killing , and nitric oxide in various ecologic niches within the human body . We detected genes that may be involved in survival of stressful environments , including a number involved in antimicrobial resistance ( e . g . pqaB , virK , pmrF , smvA , bacA , emrA , mdtC ) [40]–[45] , oxidative stress ( e . g . trxA ) [46] , resistance to acid tolerance ( e . g . narZYWV operon ) [47] , and genes involved in DNA recombination and repair ( e . g . recA , recBD , recN , recG , xthA ) [48] . Of note , the most highly represented group were genes currently annotated to encode hypothetical proteins or proteins designated as unknown or unclassified . When comparing expression levels of S . Typhi genes detected in our analysis in humans to expression levels of S . Typhi genes in in vitro grown cultures , equilibrating for S . Typhi 16S rRNA , we noted differing levels of S . Typhi mRNA for 65% of the genes detected in humans . In total , 331 S . Typhi transcripts had significantly different levels of detection in at least 4 patients compared to in vitro cultures , and 141 had significant differences in all 5 patients compared to mRNA detected in in vitro cultures . Identified genes were involved in iron ( fepB , fepC , fepD ) , thiamine ( thiG ) , and biotin ( bioF ) metabolism; use of alternative carbon sources including ethanolamine ( eutB , eutC , eutD , eutA , and eutN ) , oxacelatate ( oadAB and oadG ) , and propranediol ( pduB and pduK ) ; and antimicrobial resistance ( bacA , mdtC ) . We also identified these operons in our analysis of S . Paratyphi A , further supporting a potential role of these operons in the pathogenesis of enteric fever [12] . In addition , we identified 24 genes with significantly different levels of expression in in vivo compared to in vitro samples that are not present in the S . Typhimurium genome and may play an important role in S . Typhi pathogenesis , including genes encoded within the Type IV pilus cluster of SPI-7 ( i . e . pilO and pilL ) , and fimbrial proteins staA and steD . Of note , the largest grouping of S . Typhi genes identified in our comparison encoded proteins of unknown or unclassified function . Our findings are similar to prior Salmonella transcriptional analyses . We previously applied SCOTS-microarray analysis to S . Paratyphi A in the blood of infected humans , and the homologs of 75% of the bacterial transcripts identified in S . Paratyphi A infected patients were also identified in S . Typhi infected patients [12] . SCOTS analysis has also been previously applied to S . Typhi using an ex vivo macrophage model system by Faucher et al . [9] . Similar to our current analysis using blood of infected patients , the ex vivo analysis also detected transcripts of genes involved in intracellular survival including a number of genes encoded within SPI-2 , mgtBC in SPI-3 , the SPI-1 effector , sopE , and genes involved in antimicrobial peptide resistance . Both analyses suggested a role of SPI-1 beyond invasion of the intestinal epithelium and the potential role of alternative carbon sources in S . Typhi pathogenesis . In contrast to Faucher's analysis , we found higher levels of transcripts of genes involved in iron acquisition and transport in vivo including fes , fhu , feo , iro , and ent . Our detection of these genes may reflect a greater complexity or degree of iron-limitation in the blood of infected humans versus in a cultured macrophage model system . To our knowledge there has not been a prior analysis of S . Typhi gene expression across the transcriptome in humans . Our results highlight potential survival adaptations of S . Typhi within the human host , including expression of genes required for utilization of alternative carbon and energy sources , divalent cation transport , antimicrobial resistance , and oxidative stress resistance , as well as many genes whose function is currently unknown . Further study of these genes , especially those of unknown function , may further our understanding of S . Typhi pathogenesis and aid in vaccine , diagnostic , and/or drug target development .
|
Salmonella enterica serotype Typhi is the cause of typhoid fever and infects over 21 million cases and causes 200 , 000 deaths each year . S . Typhi only infects humans and this has greatly limited studies of S . Typhi pathogenesis . To study bacterial gene expression in human hosts , we used Selective Capture of Transcribed Sequences ( SCOTS ) and array hybridization to identify S . Typhi mRNAs expressed in the blood of 5 patients with S . Typhi infection . In total , we detected the expression of 2 , 046 S . Typhi genes ( 44% of the S . Typhi genome ) in human blood; of these , 1 , 320 ( 29% of the S . Typhi genome ) had significantly different levels of detection in human blood compared to in vitro cultures . Our results provide insight into S . Typhi pathogenesis , identifying both previously described and novel interactions occurring between host and microbe during the natural course of human infection . Further study of these genes , especially those of unknown function , may further our understanding of S . Typhi pathogenesis and aid in vaccine , diagnostic , and/or drug target development .
|
[
"Abstract",
"Introduction",
"Methods",
"Results",
"Discussion"
] |
[
"medicine",
"infectious",
"diseases",
"molecular",
"cell",
"biology",
"biology",
"genomics",
"microbiology",
"genetics",
"and",
"genomics"
] |
2011
|
In Vivo Expression of Salmonella enterica Serotype Typhi Genes in the Blood of Patients with Typhoid Fever in Bangladesh
|
Several recent studies have examined different aspects of mammalian higher order chromatin structure – replication timing , lamina association and Hi-C inter-locus interactions — and have suggested that most of these features of genome organisation are conserved over evolution . However , the extent of evolutionary divergence in higher order structure has not been rigorously measured across the mammalian genome , and until now little has been known about the characteristics of any divergent loci present . Here , we generate a dataset combining multiple measurements of chromatin structure and organisation over many embryonic cell types for both human and mouse that , for the first time , allows a comprehensive assessment of the extent of structural divergence between mammalian genomes . Comparison of orthologous regions confirms that all measurable facets of higher order structure are conserved between human and mouse , across the vast majority of the detectably orthologous genome . This broad similarity is observed in spite of many loci possessing cell type specific structures . However , we also identify hundreds of regions ( from 100 Kb to 2 . 7 Mb in size ) showing consistent evidence of divergence between these species , constituting at least 10% of the orthologous mammalian genome and encompassing many hundreds of human and mouse genes . These regions show unusual shifts in human GC content , are unevenly distributed across both genomes , and are enriched in human subtelomeric regions . Divergent regions are also relatively enriched for genes showing divergent expression patterns between human and mouse ES cells , implying these regions cause divergent regulation . Particular divergent loci are strikingly enriched in genes implicated in vertebrate development , suggesting important roles for structural divergence in the evolution of mammalian developmental programmes . These data suggest that , though relatively rare in the mammalian genome , divergence in higher order chromatin structure has played important roles during evolution .
Chromatin structure plays critical roles in genome functions such as transcription , replication and repair , it can mediate human disease processes [1] and is implicated in ageing [2] . The primary level of eukaryotic chromatin structure involves the DNA sequence wrapped around nucleosomes and the covalent modification of histones within the nucleosomes . Interactions between nucleosomes give rise to secondary structures , which may include a 30 nm chromatin fibre , and which vary in their degree of compaction across the genome [3] . Multiple higher levels of topological organisation , further structuring the genome , are also known to exist but their precise nature and their inter-relationships are the subjects of intense study and debate [4] . Genome-wide data relating to primary levels of chromatin structure ( nucleosome occupancy , histone modifications etc ) in a variety of mammalian cell types are abundant , due to the ability to profile these chromatin features by combinations of MNase digestion , chromatin immunoprecipitation and high-throughput sequencing [5] . However , the diversity of higher order structure across the genome is less well studied . An early genome-wide survey of higher order chromatin structure in the human genome discovered an undulating landscape of domains from hundreds of kilobases to many megabases in size; some relatively accessible or ‘open’ and others adopting a spectrum of more ‘closed’ condensed structures [3] . The most open domains corresponded to regions of relatively high gene density , replicating early in the cell cycle , and they may create an environment that facilitates transcriptional activation [6] . In contrast , more closed regions were relatively late replicating and gene poor . Replication timing profiles measured across the genome in multiple human and mouse cell types have also revealed the presence of domains on a similar scale , ranging from a few hundred kilobases to several megabases , that show coordinated replication timing during the cell cycle [7] , [8] . Other studies have examined different facets of higher order chromatin structure and organisation . Genomic regions interacting with tagged nuclear lamina components , and hence considered to be located at the nuclear periphery , have been mapped across the human and mouse genomes [9] , [10] . These lamina-associated domains ( LADs ) are relatively late replicating , gene poor regions from 40 Kb to 15 Mb in length and harbour genes with low transcriptional activity [10] . Overall LADs encompass around 40% of the genome and their locations and extent appear to be largely similar over cell types [10] . More recently , 3C-type physical contact maps , based on cross-linking frequencies , have been used to infer the spatial proximities and 3D- architecture between all possible 1 Mb segments of the human genome [11]–[13] . A familiar pattern of two spatial compartments within the nucleus also emerged from these data . One compartment composed of regions of gene rich , open , actively transcribed chromatin , and another containing regions with opposing features . These broad patterns emerge at the genome wide level , in spite of many regions that adopt cell type specific structures . Remarkably , given the diverse methodologies used to investigate them , significant correlations have been found among some of these coarse-grained facets of higher-order genome organisation and function . There is a strong overlap between the sequences that replicate together during the same temporal window of S phase , and those sequences that can be captured together by Hi-C [12] , [14] , consistent with the idea that genomic regions in close proximity tend to replicate at similar times and thereby define important features of chromosome organisation . These may well equate to the replication foci visible in the nucleus [15] . It has long been known that globally late replication tends to occur at the nuclear periphery [16] , [17] and this has been substantiated by more detailed analysis using fluorescence in situ hybridisation ( FISH ) of specific loci [7] , [14] . There is also a correlation between late replicating chromosomal domains and LADs [10] but it is not absolute and the relationship tends to breakdown at LAD borders and at particular genes . Moreover , such correlations present a moving target as genomic patterns of replication timing domains and LADs change upon differentiation and re-programming [8] , [10] . We also lack a comprehensive view of how genome-wide chromatin structure varies across cell types . Although cell type specific structures are clearly present , it seems that the higher order domains reflected in replication timing and Hi-C data remain largely unchanged over a variety of cell types and throughout the cell cycle [18] , [19] . Key questions in chromatin structure and nuclear organisation therefore relate to the ontology of the various structural domains that are known – namely how are they related and to what extent are they all aspects of the same entity ? Until recently there has been a lack of comparable , genome-wide chromatin structure data across species and comparative studies have therefore generally examined a single feature of chromatin structure in isolation . Ku et al [20] studied genome-wide Polycomb binding sites and histone modification data in mouse and human embryonic stem ( ES cells ) within orthologous promoter regions . They stressed the widespread conservation of chromatin states between species , with more than half of promoters showing the same state . Similarly , regions across the orthologous mammalian genome that are enriched for common histone modifications appear to be broadly conserved between human and mouse [21] . In contrast , sequence-specific transcription factor binding patterns appear to evolve rapidly in mammals , with binding events in a particular tissue shared only 10–22% of the time between human , mouse and dog genomes [22] . Higher order chromatin structures are generally assumed to show much less divergence , although detailed studies are rare . The numbers and size distributions of LADs in human lung fibroblasts are reported to be similar to those seen in mouse embryonic fibroblasts , as well as several other mouse cell types [10] . However it is not clear how the extent of divergence between cell types compares with divergence between species , or which genomic regions are involved in either . Replication timing appears generally conserved between human and mouse within large genomic regions showing conserved synteny , but notably less so than between orthologous human and mouse promoters [14] . This conservation has been maintained in spite of the numerous large-scale genome rearrangements separating the two species [23] . It also appears that the similarity in replication timing between species is heavily dependent on the particular cell type examined [14] . On the other hand , Hi-C data has suggested that the mouse and human genomes are separated into largely conserved , megabase sized interaction domains , that are similar between cell types [24] . The studies mentioned above provide complementary views of higher order chromatin structure . Each shows that the mammalian genome is organised into large , discrete domains of higher order chromatin with opposing properties ( levels of expression and accessibility , spatial positioning , and replication timing ) . These domains appear to be broadly similar across the different cells that have been examined , although many regions across the genome show cell type specific structure [8] , [10] , [14] . However , the actual extent to which these datasets intersect , and how they relate to one another across cell types and species , is poorly understood . Similarly , the genomic loci underlying divergence in chromatin structure between species , and the mechanisms underlying divergence , are unknown . Here we collate a large number of diverse mouse and human datasets to provide the most comprehensive overview of higher order chromatin structure in mammals to date . We undertake a systematic study of all orthologous regions in the mammalian genome and document the extent of conservation in higher order chromatin structure between cell types and during evolution . Our analysis identifies large tracts of structurally divergent chromatin , unevenly distributed across the genome , and containing intriguing enrichments of particular classes of genes .
Significant correlations were expected between replication timing ( RT ) , lamin association ( LA ) and interlocus contact patterns ( Hi-C ) as they appear to reflect somewhat overlapping aspects of higher order chromatin structure [10] , [14] , [23] . The degree of agreement overall among the 36 datasets is indeed strong and significant ( Spearman's Rho: 0 . 38 to 0 . 98 , p<1e-16 ) . In spite of differing experimental procedures , platforms , cell types , and species , moderate to strong positive correlations are ubiquitously observed ( Figure 1 ) . The highest agreement is usually observed between similar cell types from the same species , even across experimental platforms . For instance mouse RT data for a variety of ES and induced pluripotent stem cell ( iPSC ) types show strong correlations ( Rho: 0 . 7–0 . 9 , p<2 . 2e-16 ) with LAD data from mouse ES cells , and together they form a coherent cluster in the correlation matrix ( Figure 1 ) . However , there are also interesting exceptions to this rule , such as the human embryonic fibroblast LA data . Although this dataset shows the weakest correlations to all other datasets , the best agreement is to the mouse fibroblast LA and RT data and not to other human cell types . The reason for this may lie in cell cycle variation: ES and iPS data may be strongly influenced by the fact that these cells are almost entirely in S phase , whereas fibroblasts divide slowly and are mainly in G0/G1 . In any case it seems that certain aspects of higher order structure in particular cell types , such as association with the nuclear periphery in fibroblasts , have been more strongly conserved than others during evolution . Striking evidence of structural conservation across the mammalian genome is evident when examining contiguous stretches of orthologous regions ( Figure 2 ) . This suggests that many aspects of higher order chromatin structure have been conserved in embryonic cell types , over the ∼80 million years since the divergence of rodents and primates . However apparent divergence in higher order chromatin structure between species is also evident in specific regions . This is most simply seen as loci demonstrating a strong , consistent difference in mean normalised structure between the two species across all of the available datasets ( see representative regions depicted in Figure 2 ) . Although there are high correlations between many of these datasets , reflecting similar overall trends in structure as we traverse chromosomes , this can mask substantial variation between datasets at the level of the absolute normalised structural values for a given 100 Kb region ( Figure 2 ) . The critical question is therefore , which 100 Kb regions vary between species to an unexpected degree , given the extent of variation seen among all datasets ? This is the question we address below using a novel divergence metric based upon permutations of the original data . We systematically sought genomic regions showing strong and consistent structural divergence between species , across all cell types , using non-parametric tests for each orthologous 100 Kb region ( see Methods ) . The resulting p values were conservatively thresholded to ensure a low false discovery rate ( FDR ) and robust results . We defined two broad categories of regions based upon their levels of divergence: divergent regions ( generating significant p-values passing the FDR threshold ) and relatively static non-divergent regions ( nonsignificant ) ( Figure 2; Figure S2 ) . Viewed in this way divergence is necessarily bipolar , containing regions with mean structure values that are relatively open in human but closed in mouse , and vice versa . Such estimates of structural divergence are likely to be inherently conservative , since they depend upon strong consistent evidence for divergence over multiple cell types and experimental platforms . The divergent regions were found to constitute 10 . 22% ( 1 , 719 out of 16 , 820 ) of the orthologous regions examined , and possessed a similar ( Mann-Whitney test in human p = 0 . 17 , in mouse p = 0 . 52 ) protein-coding gene density to non-divergent regions . Human gene densities in nondivergent regions ( 2 . 34 per 100 Kb on average ) were not significantly different from either human open divergent regions ( 2 . 09 per 100 Kb; Mann-Whitney p = 0 . 45 ) , or human closed divergent regions ( 2 . 43 per 100 Kb; Mann-Whitney p = 0 . 72 ) . Similarly , mouse gene densities in nondivergent regions ( 1 . 77 per 100 Kb ) were not significantly different from either mouse open divergent regions ( 1 . 91 per 100 Kb; Mann-Whitney p = 0 . 97 ) , or mouse closed divergent regions ( 1 . 33 per 100 Kb; Mann-Whitney p = 0 . 51 ) . The distribution of divergent regions was far from uniform over the genome , with several chromosomes showing higher than expected densities ( see Methods; Chi-squared test in human p = 4 . 34e-06 , in mouse p = 1 . 19e-03 ) . For instance , human chromosomes 5 and 10 were found to have a 50% excess of divergent regions , while chromosomes 21 and 22 were found to have a greater than 60% depletion . This raises the question: does the distribution of divergent regions within chromosomes reflect larger tracts of divergent chromatin ? Cursory examination of these data ( e . g . the regions depicted in Figure 2 ) , suggests that a number of divergent 100 Kb regions are clustered in the genome at particular loci . We formally investigated the degree of clustering by measuring the length distribution of consecutive runs of divergent 100 Kb regions observed , relative to the distribution expected using a permutation strategy ( see Methods ) . The clustering observed was found to be highly significant , and we identified 159 unexpectedly large ( at least 400 Kb; p<1e-04 ) clusters of divergent regions with a median size of 800 Kb ( Figure 3; Table S2 ) . The same large orthologous clusters were detected in human and mouse genomes when the 100 Kb divergent regions in each genome were clustered ( Figure S3 ) , but were not evenly distributed across all chromosomes , for example human chromosomes 3 and 5 had around twice the density expected , but in contrast chromosomes 1 and 9 had around half the density expected . The size distribution of divergence clusters appeared similar to the ES cell chromatin-mediated regulatory domains ( median size 880 Kb ) recently reported in the mouse and human genomes [24] , suggesting that these stretches of divergent chromatin may represent divergent regulatory domains . We therefore examined the similarity in domain boundaries between these regulatory domains and the divergence clusters using a permutation approach ( see Methods ) . An important caveat is the resolution of these datasets , which means that all reported domain boundaries are estimates within tens or hundreds of kilobases . In the human genome the median distance between the boundaries of divergence clusters and the nearest ES cell regulatory domain boundaries was 207 , 852 bp , which is somewhat less , though not significantly different ( p = 0 . 054 ) from the expected median distance given 10 , 000 permuted datasets ( 235 , 581 bp ) . Similarly , in the mouse genome , the equivalent median distance was 260 , 000 bp , which is not significantly different ( p = 0 . 087 ) from the expected distance given 10 , 000 permuted datasets ( 290 , 095 bp ) . We conclude that overall there is no strong association between divergent regions and these regulatory domains , which is consistent with most structural divergence being selectively neutral . We also examined the correspondence between the divergent clusters and regions known to be structurally variable during cellular differentiation from ES cells [7] . Of the 1719 divergent regions , 60 overlapped these structurally dynamic regions , compared with an expected number ( mean overlaps in 10 , 000 permutated datasets ) of 99 . 73 which represents a significant depletion ( p<0 . 013 ) . The three largest ( 2 . 1–2 . 7 Mb ) regions of divergent chromatin were found to occupy subtelomeric regions of human chromosomes 2 , 6 and 9 ( Figure S4 ) , but in each case the orthologous mouse regions were long distances ( 80–100 Mb ) from mouse telomeres . This was found to reflect the distribution of chromatin divergence across the human genome in general , with unexpected excesses of divergence towards the ends of some human chromosomes ( Figure S5; Table S3 ) . This excess was most pronounced within the subtelomeric regions ( within 5 Mb of the ends of each chromosome sequence assembly ) of 4 human chromosomes ( 1 , 2 , 13 , 18 ) , and was also seen overall for the human genome ( p = 0 . 016 ) . In contrast most mouse ( 5 Mb ) subtelomeric regions showed a relative depletion of divergence , with none showing significant enrichment , and ( nonsignificant ) depletion over the mouse genome in general . ( No significant enrichment or depletion was found overall for pericentromeric regions in either species . ) There are well-characterised differences in the chromatin structures found at human and mouse telomeres , and mammalian telomere biology appears to have been a focus for evolutionary adaptation [25] . Subtelomeric regions are known to be amongst the most rapidly evolving DNA sequences in the genome and have been subject to extensive divergence recently in the primate lineage [26] . The current data suggest that the higher order chromatin structures at some primate subtelomeric regions have also been subject to dramatic change . Higher order chromatin structure itself is known to show strong positive correlations with GC content , such that relatively open regions are more GC rich and gene dense , and this is also seen here ( Figure 4; Human GC density versus chromatin structure Spearman's rho = 0 . 57 , p<2 . 2e-16; Mouse GC density versus chromatin structure Spearman's rho = 0 . 75 , p<2 . 2e-16 ) . Similarly , the human genome shows greater variability in GC content overall than in the mouse , consistent with the poor conservation of mammalian isochore structure in rodents [27] . The current data allow us to ask , for the first time , whether GC content is also associated with divergence in higher order structure . Comparison of the percentage of GC nucleotides between divergent and nondivergent regions across all orthologous 100 Kb regions shows intriguing contrasts between the human and mouse genomes ( Figure 4 ) . In the human genome there is a significant shift in human GC content between divergent and nondivergent regions , across the entire spectrum of normalised chromatin structure . Furthermore , this shift is to higher GC content ( 40 . 5% ) within divergent human closed regions , and lower GC content ( 34 . 9% ) within divergent human open regions , relative to nondivergent regions ( 37 . 5%; human divergent open GC versus human nondivergent GC Mann-Whitney p<2 . 2e-16; human divergent closed GC versus human nondivergent GC Mann-Whitney p<2 . 2e-16 ) . Thus the two divergence classes show the opposite human GC content bias to the expectation e . g . although open chromatin in the human genome is relatively GC rich ( Figure 4 ) , divergent regions that are open in human actually tend to be GC poor . These patterns are not seen in the GC content of the mouse genome , where there is no contradictory shift in the compositional biases of mouse sequences within divergent regions . Instead mouse divergent open regions are relatively GC rich ( 38 . 7% ) and divergent closed regions are relatively GC poor ( 33 . 4% ) , relative to nondivergent regions ( 35 . 5% ) . Correspondingly there is no global shift in mouse GC content between divergent and nondivergent regions ( Figure 4 ) . Thus overall , divergent regions are consistent with the GC content trends seen in the mouse genome , but show a complete contrast with the GC trends in the human genome . The magnitude of the human GC content shift varies between chromatin categories , as reflected in the varying separation between divergent and nondivergent regression lines ( Figure 4 ) . Further examination of these data suggests that the largest shifts are seen for regions towards the extreme ends ( i . e . unusually open or closed ) of the spectrum of chromatin structure categories ( Table S1 ) . It is not possible to disentangle cause and effect using the current data , to establish that changes in GC content drive structural change or vice versa . It is also not possible to establish which species has the derived or ancestral chromatin state . However , these observations do suggest that chromatin divergence is often associated with unusual shifts in GC content in the human lineage , which may reflect fluctuations in mutation or selection during primate evolution . If genes within divergent regions have undergone regulatory divergence we might expect to see some evidence of this in appropriate expression data . Although perfectly matched expression data is not available , the present data are mainly derived from embryonic cell types and previous studies have examined genome-wide regulatory divergence in human and mouse ES cells . Cai et al ( 2010 ) [28] sought significant differences in time-course expression patterns between mouse and human ES cells to rigorously measure regulatory divergence across orthologous genes . They were able to compile classes of genes showing either conserved regulation or divergent regulation in either mouse or human . We examined the distribution of these gene classes across all regions of divergent and nondivergent chromatin . Although the numbers of genes identified by Cai et al ( 2010 ) [28] that were also present within the orthologous regions studied here were modest ( 497 divergent and 126 conserved ) , we found enrichment ( odds ratio: 1 . 30; Fisher's Exact test p = 0 . 04 ) of divergently regulated genes within the 100 Kb regions of divergent higher order chromatin reported here . Genes with conserved regulation were also under-represented in divergent regions ( odds ratio = 0 . 76; p = 0 . 331 ) . These patterns were observed in spite of the fact that the data of Cai et al ( 2010 ) [28] is based upon human and mouse embryonic cell lines that are not represented in the chromatin data studied here . Another more recent study of expression divergence between human and mouse genes , examined expression over a time course in specialised immune ( macrophage ) cells induced by exposure to bacterial lipopolysaccharide , and reported significant results for larger numbers ( 186 divergent , 972 conserved ) of orthologous gene pairs [29] . We examined these data in the same way and found no significant enrichment of divergently regulated genes in divergent 100 Kb regions . Indeed the genes divergently regulated in these macrophage data showed the opposite trend , and were somewhat under-represented in regions of divergent chromatin ( odds ratio: 0 . 78; p = 0 . 46 ) . This suggests that the correspondence between chromatin divergence and expression divergence is specific to embryonic cell types . We also constructed a larger dataset measuring differential expression between mouse and human ES cells for orthologous gene pairs ( see Methods ) , based upon previous RNAseq studies [30] , [31] . These data provide a higher coverage dataset consisting of log fold change measurements for 7 , 673 gene pairs occurring within the orthologous 100 Kb regions studied here . This allowed us to examine the extent of expression divergence within the two possible bipolar categories of divergent regions , relative to nondivergent regions ( Figure 5 ) . We found a striking contrast , with regions open in human but closed in mouse showing a expression divergence consistent with upregulation of human genes ( nondivergent median log2 fold change: −0 . 48; divergent: −0 . 33; Wilcoxon p = 0 . 23 ) , while the opposite category ( closed in human , open in mouse ) showed evidence of upregulation of mouse genes ( nondivergent: −0 . 48; divergent: −1 . 00; Wilcoxon p = 3 . 41e-06 ) . This is the pattern of gene expression divergence expected within divergent regulatory domains conferring a respectively permissive or repressive environment for transcription of human genes . Again , these expression data were generated in embryonic cells similar to , but not identical to those used to derive the chromatin divergence data . It is important to note that there is a distinction between the relative bipolar classification of divergent regions ( human open/mouse closed and vice versa ) and their absolute normalised chromatin values . Thus , it is possible for a region that is relatively open in human and relatively closed in mouse to possess absolute values consistent with a closed conformation in both species . One might expect that using such absolute values to construct more specific divergent region categories might increase the differences seen ( Figure 5 ) . This was indeed the case in spite of the associated reductions in sample sizes . Regions open in human but closed in mouse ( where the absolute human value > 0 and the absolute mouse value < 0 ) showed a stronger expression divergence consistent with upregulation of human genes ( nondivergent median log2 fold change: −0 . 48; divergent: 5 . 03; Wilcoxon p<2 . 2e-16 ) , while the opposite category ( restricted to those with absolute human value<0 and absolute mouse value>0 ) showed stronger evidence of upregulation of mouse genes ( nondivergent: −0 . 48; divergent: −4 . 77; Wilcoxon p>2 . 2e-16 ) . These comparisons to expression data provide independent validation of our methodology and suggest a direct link between the regions of divergent chromatin identified and the regulation of resident genes . Using standard enrichment analyses , we identified over-representation of particular functional classes of genes in the divergent orthologous regions , and the results establish interesting themes . The 907 divergent 100 Kb regions relatively open in human ( but closed in mouse ) contain 1142 human genes and 757 mouse genes , and both show significant enrichments for multiple terms associated with olfactory receptors ( ORs ) at particular loci ( seen as enrichments for genes mapping to particular cytogenetic bands ) ( Table 1; Table S2 ) . The mouse genes involved are disproportionately those located in particular OR gene clusters on chromosome 7E3 and 6B1-B2 . 1 , while the human genes are clustered at the orthologous locations at 11p15 . 4 ( Figure 2A ) and 7q35 respectively , within extended regions of conserved synteny . Mouse OR genes have been shown to exhibit tightly regulated expression patterns during development , dependent upon repressive chromatin structures spanning clusters of OR genes [32] , including histone modifications associated with constitutive heterochromatin [33] . This raises the intriguing possibility of an association between divergent higher order chromatin structures and particular histone modifications . It also suggests that the repressive , relatively closed higher order chromatin structures consistently seen at this region of the mouse genome , but not evident in human cells , could have evolved as part of the regulatory landscape associated with OR gene cluster evolution in rodents . Other enriched terms include those related to a protocadherin ( Pcdh ) gene cluster present at 5q31 . 3 in the human genome , and to the orthologous mouse Pcdh cluster on mouse chromosome 18qB3 ( Table S2 ) . Recent work has shown this region adopts distinct chromatin architectures in different mouse neuronal cell types to affect Pcdh gene expression and thereby plays critical roles in establishing neuronal diversity and connectivity during development [34] . A third cluster of genes coincides with this class of divergent regions ( open in human , closed in mouse ) on mouse chromosome 8D3 ( and human 16q21 ) and is enriched for genes encoding MARVEL , a transmembrane domain involved in membrane apposition . The family of chemokine-like proteins containing this domain have been implicated in inflammation , immunity and development but most are not well characterised . Of the five MARVEL containing genes within the 8D3 divergent cluster , three are unstudied , but Cmtm2a and Cmtm3 are both implicated in the proliferation and development of particular testicular cells [35] , [36] . The human ortholog of Cmtm3 is present in the orthologous human divergent region at 16q21 and is a known tumour suppressor gene that shows frequent inactivation via chromatin-mediated silencing in several cancers [37] . It seems that developmental gene clusters showing cell type specific regulation are unexpectedly common at regions displaying divergent higher order chromatin . Other clusters of genes , enriched at other divergent regions are also present in the results but lack sufficient functional annotation to generate significant enrichment results after multiple testing corrections ( Table S2 ) . The genes within the divergent 812 orthologous human closed ( mouse open ) regions contain 1285 human genes and 1102 mouse genes . These also showed significant enrichment for genomic regions harbouring particular gene clusters . Both human and mouse genes in these regions show significant enrichment for terms associated with developmental genes containing Antennapedia type homeobox domains ( IPR001827 ) . The genes involved are exemplar developmental genes present at the HOXA ( human HOXA1-A7; Figure 2B ) and HOXD ( human HOXD1-4 ) clusters . Both clusters are implicated in multiple cancers and other disorders , and are tightly regulated via higher order chromatin domains [38] , [39] . It is thought that structural divergence within the chromatin domains harbouring these clusters underlies many important innovations in the vertebrate body plan [40] . Other , relatively poorly studied , homeodomain containing genes at other loci are also present within this class of ( human closed , mouse open ) divergent regions ( Table S2 ) . Again , it seems that developmentally regulated genes are over-represented within regions of divergent chromatin . However , it is worth noting that the proportion of divergent regions generating significant functional enrichments ( that is , those divergent regions possessing the genes responsible for the functional enrichments seen ) is modest overall , constituting 6% of human and 11% of mouse divergent regions in total . Most RNA genes are poorly functionally annotated which makes analogous enrichment analyses impossible , but we did examine the densities of the main RNA gene classes ( rRNA , snoRNA , snRNA , miRNA , lincRNA ) in structurally divergent regions . Only the lincRNA class showed significant differences , with higher densities of both human ( divergent mean density: 0 . 31 genes/Mb; nondivergent mean density: 0 . 20 genes/Mb; Wilcoxon p = 1 . 48e-08 ) and mouse ( divergent mean density: 0 . 12; nondivergent mean density: 0 . 09; Mann-Whitney p = 3 . 68e-04 ) lincRNA genes found in divergent ( human closed/mouse open ) regions . These molecules are thought to regulate ES cell differentiation via the assembly of chromatin complexes and the establishment of activating or repressive domains [23] . The present data suggest they may also have played roles in chromatin divergence . As expected the large divergence clusters showed similar patterns of functional enrichments as those discussed above ( Table 2; Table S2 ) . For example , the divergent regions mentioned already at 11p15 . 4 ( containing an OR gene cluster ) and 16q12 . 2 ( containing an IRX gene cluster ) were found to extend across 800 Kb and 1 . 5 Mb respectively . Similarly the divergent region containing the 7p15 . 2 HOXA genes was found to encompass 800 Kb , and to include neighbouring lincRNA genes such as HOTAIRM1 which is active in HOXA regulation during neurogenesis and differentiation [41] . An additional region at 7q21 . 3 showing a novel functional enrichment also emerged , which contains the paraoxonase gene cluster ( Table 2 ) , these genes are imprinted in the mouse genome and exhibit unusual , allele-specific expression dependent on developmental stage in human cells [42] . Again , it seems that structural divergence is disproportionately associated with particular developmental gene clusters , which follow tightly regulated expression patterns targeting specific cell types , and are often known to occupy unusual chromatin environments . Many of these genes have also been implicated in developmental adaptations during vertebrate evolution and in human disease processes . This may suggest that regions of divergent chromatin structure have evolved different chromatin conformations to facilitate functional divergence at these loci . However it is not possible to exclude non-adaptive hypotheses , for example where divergence in chromatin structure is a neutral consequence of gene family or repeat expansions or other changes in the underlying genomic sequences . Indeed , since the majority of divergent regions show no detectable functional enrichments , selectively neutral divergence appears to be the most likely scenario in most cases . Individual studies of various aspects of higher order chromatin structure have suggested widespread conservation across the mammalian genome , in spite of many interesting structural differences between cell types [10] , [14] , [23] . The comprehensive analyses presented here are consistent with this , and demonstrate the same signal across diverse datasets from studies that set out to observe nominally different aspects of structural genome organisation in many different embryonic cell types . We conclude that most measurable aspects of chromatin are conserved across the vast majority of the detectably orthologous genome . However , using a conservative approach ( requiring consistent evidence of divergence between species over all cell types and all structural datasets assayed ) we also observe divergent chromatin structure at 10 . 22% of orthologous 100 Kb genomic regions examined , encompassing over 170 Mb and including many hundreds of human and mouse genes . This suggests that structural divergence has played a major role in the evolution of many loci occupying these unusual genomic regions . Many of the regions identified form unexpectedly large tracts of divergent chromatin , nonrandomly distributed between and within chromosomes , and this clustering appears particularly pronounced at human subtelomeric regions . Overall the divergent regions of embryonic chromatin identified are significantly enriched for genes active in vertebrate development . These include homeodomain gene clusters , which have been implicated in evolutionary innovations to vertebrate developmental programmes , suggesting that selection may have modulated their regulation during evolution via alterations to chromatin . Consistent with this we find that genes showing evidence of regulatory divergence between human and mouse are over-represented within regions of divergent higher order chromatin structure . The mechanisms underlying divergence in higher order chromatin structure remain unknown , but one may speculate that alterations at lower levels of chromatin are likely to be involved . For example , changes in the diversity or abundance of relatively rapidly evolving ncRNAs , which can mediate chromatin remodelling between cell types [43] , could provide a molecular basis for divergence . Also the strong sequence-level correlates of human chromatin structure [44] , [45] and the unusual , lineage specific shifts in GC content seen here , suggest it is possible that sequence divergence underlies chromatin divergence . It may also be relevant that larger scale variation in chromatin structure within the mammalian genome is often associated with alterations in the spectrum of histone modifications at a region . For example , human LADs are reported to show enrichments of H3K9 and H3K27 methylation [46] , and OR gene clusters are now known to possess an unusual signature of histone modifications involving the molecular hallmarks of constitutive heterochromatin [33] . It is therefore possible that divergence in chromatin domains during evolution is caused by alterations in the constellations of histone modifications present . However , definitive evidence of the mechanisms underlying evolutionary divergence in higher order chromatin structure will require substantial future investigations .
All cell types and datasets , and their abbreviations are listed in Table S5 . Replication timing data in human and mouse embryonic cells were obtained from Hiratani et al [7] , and Ryba et al [14] as log2 ( early relicating/late replicating ) values . Nuclear lamina association data in human and mouse embryonic cells were obtained from Guelen et al [9] and Peric-Hupkes et al [10] . Both studies were based upon the DamID technique for labelling lamina associated sequence , where relative lamina association is represented by log2 ( Dam-fusion/Dam-only ) values . Finally , 100 Kb window genomic interaction probability matrix eigenvalues were defined for human lymphoblastoid cells using Hi-C by Lieberman-Aiden et al [11] . These values were found to largely reflect two relatively open and closed nuclear compartments of higher order chromatin . Although these data were not derived from embryonic cells it appears that many of the higher order patterns ( as represented by interaction matrix eigenvectors ) in Hi-C datasets are consistent between cell types [11] , [24] . Re-analysis of these interaction data has revealed the presence of systematic biases that afflict the Hi-C method , obscuring additional , finer scale structural compartments [12] . Although our analysis only concerns the course grained , two-compartment division between open and closed regions ( since we use eigenvalues of interaction matrices not interaction probabilities themselves ) we were concerned that our results might be affected by these biases . Consequently we examined an independent genomic interaction map produced for a similar lymphoblastoid cell line using a modified Hi-C method designed to mitigate the biases inherent in previous data [13] . When the original [11] interaction data were substituted with these new , nominally unbiased [13] data we observed very similar correlations with all other chromatin structure datasets . We conclude that the biases present in the Lieberman-Aiden et al [11] dataset have little effect on a course grained , two compartment classification of the genome based upon these data , and therefore that our search for structurally divergent regions is unaffected . Probe based replication timing and nuclear lamina association data coordinates were translated to the latest human or mouse genome assembly coordinates ( hg19 and mm9 ) using reciprocal liftOver transformations to ensure accurate remapping [47] . Probes failing to map reciprocally to overlapping coordinates between mouse and human genomes were discarded as unreliable . For each dataset the structural data values were averaged across probes into consecutive non-overlapping 100 Kb regions , but regions represented by fewer than 10 probes were discarded as potentially unreliable . This allowed comparisons between the probe based datasets and the Hi-C data , which has a fixed resolution of 100 Kb . Within each species 100 Kb regions were collated across datasets where their coordinates overlapped by 50% or more . The result was a set of 24 , 711 mouse and 28 , 786 human 100 Kb regions represented by higher order structural values from multiple datasets . Orthologous 100 Kb regions were defined as those regions with at least a 50% coordinate overlap between mouse and human genomes using reciprocal liftOver transformations . A total of 16 , 820 100 Kb orthologous regions , covering 54% of the human genome and 62% of the mouse genome , were defined in this way . A total of 11 , 966 human and 7 , 891 mouse regions , lacking an orthologous mapping using this protocol , were designated putatively lineage specific regions . As expected , lineage specific regions were highly enriched for segmental duplications , repeats and duplicated gene families , whereas orthologous regions were relatively rich in protein coding genes [48] . Examination of several techniques revealed that standard quantile normalisation procedures ( R/Bioconductor limma package ) [49] used to normalise across different microarray experiments were effective across the different experimental platforms and cell types here , therefore this normalisation technique was implemented across all structural datasets for all 100 Kb regions ( Figure S1; Figure S7 ) . The normalised structural data and chromosome coordinates for all 16 , 820 orthologous regions are provided in Table S6 . Structurally divergent regions were defined as orthologous 100 kb regions that showed a consistent difference in higher order structural values across human and mouse data . Non-parametric tests from the SAM package [50] , analogous to two class unpaired t-tests with permutation derived p-values , were used to assess divergence ( R package samr ) . These tests were developed for microarray data analysis but are appropriate for other types of non-microarray derived data [50] . The approach was developed to identify unusual genes that show a strong and consistent expression difference between treatments , given many variable replicate measurements . In the present case we identify unusual 100 Kb regions , showing a strong and consistent difference between species , given the many variable measurements of chromatin structure . In both cases the aim is to identify significant differences between states ( treatments , species ) for the measured entities ( genes , 100 Kb regions ) given a number of inherently noisy , variable observations . The permutation approach ensures that the observed variability in the observations is accounted for in the significance of the test result . Tests were carried out for each 100 Kb orthologous region , with the various normalised structural values for that region compared between species . 100 , 000 permutations of the normalised structure dataset were used to estimate the false discovery rate ( FDR ) , defined in this instance as the median number of false positive divergent regions expected ( given the permuted datasets ) , divided by the total number of divergent regions called . The FDR threshold was set to be relatively low ( FDR = 2e-04 ) to ensure that less than 1 false positive was expected within the 1719 divergent regions found . The results are necessarily bipolar with positive and negative divergent regions called to indicate human open/mouse closed or human closed/mouse open divergence respectively . Relatively static , nondivergent regions were classed as those with p values that did not pass the FDR threshold . The mean normalised structure values for 100 Kb regions , over all of the available datasets in a species , were calculated as a useful guide to trends in structure across chromosomes and the genome overall . The 100 Kb detectably orthologous regions defined above ( using a 50% overlap threshold ) will necessarily vary in the degree of similarity they show between species , it was therefore a concern that this might influence the measurement of structural divergence . Specifically it was important to show that the regions identified as structurally divergent are not simply those most poorly aligned between species at the sequence level . On closer examination the distributions of overlaps ( aligned nucleotides minus gaps ) were found to be very similar between structurally divergent and nondivergent regions , whether viewed in terms of the human ( hg19 ) genome ( divergent overlap mean = 0 . 80 , median = 0 . 81; nondivergent overlap mean = 0 . 79 , median = 0 . 80 ) , or the mouse ( mm9 ) genome ( divergent overlap mean = 0 . 73 , median = 0 . 72; nondivergent overlap mean = 0 . 72 , median = 0 . 71 ) sequence assemblies , based upon UCSC whole genome alignments . We concluded that our estimates of structural divergence are not a simple reflection of sequence divergence . We examined the distribution of divergent regions across chromosomes by comparing the expected numbers , given the proportion of orthologous 100 Kb regions on each chromosome , with those observed using chi-squared tests , and identified chromosomes of interest as those generating standardized residuals>1 . 96 . To define divergence clusters ( i . e . clustered groups of divergent 100 Kb regions ) we first identified all consecutive runs of significantly divergent regions across the orthologous human ( and separately the mouse ) genome , and the observed distribution of their lengths . Consecutive runs were required to maintain the polarity of divergence ( i . e . all regions involved must be either human open/mouse closed or vice versa ) . We then permuted the divergence data among orthologous 100 Kb regions within chromosomes 10 , 000 times , and noted the length distributions of consecutive runs within each permuted genome . The frequency with which a run of n consecutive divergent 100 Kb regions was seen in the permuted datasets was taken as an approximate p value for runs of length n in the observed dataset . Observed runs of divergent regions greater than or equal to 400 Kb were never seen in the permutated data ( p<0 . 0001 ) and were taken to be significant divergence clusters . This strategy is likely to be conservative in detecting large regions of divergent chromatin as it does not allow for gaps ( e . g . regions that may have marginally failed to reach significance in the test for divergence above ) within runs of divergent regions . 159 large divergent regions were discovered at the same , orthologous locations in the human and mouse genomes ( Table S3 ) . An additional 1 . 4 Mb divergent region ( at chr18: 11600000–12999999 ) was found in the mouse genome that lacked a reciprocally orthologous human region . Enrichment or depletion of 100 Kb divergent regions within subtelomeric or centromeric regions was assessed using a circular permutation strategy [51] to preserve the observed degree of clustering , over 10 , 000 permuted datasets . Each permuted dataset was generated by shifting the locations of all divergent regions on each chromosome by a random number ( less than the length of the chromosome ) . Regions assigned a shifted position greater than the final base pair of the chromosome are reassigned to the start of that chromosome ( plus the number of bases by which they exceeded the final base pair ) . Thus the permutations regard chromosomes as circularised , and thereby maintain the degree of clustering seen among the observed divergent regions . The number of permuted datasets , n , possessing a number of divergent regions within subtelomeric ( or centromeric ) regions greater than or equal to the observed number were noted , and used to calculate approximate p-values ( n/10 , 000 ) for enrichment . The significance of depletion was calculated analogously , according to the number of permuted datasets possessing the same or fewer divergent regions . Subtelomeric regions were defined as regions within 1 Mb , 5 Mb and 10 Mb of the first and final base pairs of the chromosome assemblies , and within the final base pair of the ( acrocentric ) mouse assemblies . Centromeric regions were defined as regions within 1 Mb , 5 Mb and 10 Mb of the first base pair of mouse and human chromosome q arm assemblies , and within the final base pair of human p arm assemblies . It is important to note that the density of orthologous 100 Kb regions within subtelomeric regions was not significantly different from the genome as a whole , either for human ( 5 Mb subtelomeric region mean density = 23 . 70; mean density across all genomic 5 Mb bins = 28 . 10 ) or mouse ( 5 Mb subtelomeric region mean density = 34 . 60; mean density across all genomic 5 Mb bins = 34 . 20 ) . The same circular permutation approach was used to measure the enrichment or depletion of divergent regions within domains that are structurally dynamic during cellular differentiation [7] . We also used a similar permutation strategy to compare the similarity ( i . e . proximity ) of domain boundaries between chromatin-mediated regulatory domains [24] and the boundaries of divergent clusters . The median distance between divergent cluster boundaries and the nearest regulatory domain boundaries was compared to the median distance seen in 10 , 000 datasets that had undergone circular permutation . The proportion of datasets generating a median distance less than or equal to the observed median distance was taken as an approximate p-value . Gene densities were calculated per Mb for divergent and nondivergent datasets and tested using nonparametric ( Mann-Whitney/Wilcoxon test ) statistics . Functional enrichments for protein coding genes were calculated using DAVID [52] using the total human and mouse genes present within the 16 , 820 orthologous 100 Kb regions as background sets for human and mouse enrichment analyses respectively . Enrichment of each annotation term in the set of human or mouse genes present within divergent regions was assessed using default options ( p-values calculated using the hypergeometric distribution with FDR correction ) . Enrichment of these gene sets within cytogenetic bands was also examined as this can reflect the clustering of divergent regions . Both protein coding and RNA genes were annotated by Ensembl ( http://www . ensembl . org ) and include lincRNAs predicted according to combinations of histone modifications and complementary EST and cDNA data . RPKM expression values for human H1 ES cells [30] and mouse E14 ES cells [31] were used to calculate log2 ( human RPKM/mouse RPKM ) for all one to one orthologous mouse human Ensembl gene pairs , as an estimate of fold change in expression .
|
The mammalian genome is organised into large multi-megabase domains defined by their physical structure , or higher order chromatin structure . Although these structures are believed to be well conserved between species , there have been few studies attempting to quantify such conservation , or identify divergent structures . We find that regions showing clear evidence of divergence in higher order chromatin structure encompass at least 10% of the mammalian genome , and include many hundreds of genes whose regulation may have been affected . At least some of these genes have been directly implicated in evolutionary innovations to vertebrate developmental programmes , so divergent regions may have been disproportionately important during evolution . In addition , we show that divergent regions occur in large stretches of more than 2 Mb in the human genome and are enriched towards telomeres at the ends of human chromosomes . This may reflect shifts in the nuclear organisation and regulatory functions of chromatin domains between human and mouse .
|
[
"Abstract",
"Introduction",
"Results/Discussion",
"Methods"
] |
[
"developmental",
"biology",
"genomics",
"biology",
"computational",
"biology",
"evolutionary",
"biology",
"genetics",
"and",
"genomics"
] |
2013
|
Divergence of Mammalian Higher Order Chromatin Structure Is Associated with Developmental Loci
|
Protein kinases are proven targets for drug development with an increasing number of eukaryotic Protein Kinase ( ePK ) inhibitors now approved as drugs . Mitogen-activated protein kinase ( MAPK ) family members connect cell-surface receptors to regulatory targets within cells and influence a number of tissue-specific biological activities such as cell proliferation , differentiation and survival . However , the contributions of members of the MAPK pathway to schistosome development and survival are unclear . We employed RNA interference ( RNAi ) to elucidate the functional roles of five S . mansoni genes ( SmCaMK2 , SmJNK , SmERK1 , SmERK2 and SmRas ) involved in MAPK signaling pathway . Mice were injected with post-infective larvae ( schistosomula ) subsequent to RNAi and the development of adult worms observed . The data demonstrate that SmJNK participates in parasite maturation and survival of the parasites , whereas SmERK are involved in egg production as infected mice had significantly lower egg burdens with female worms presenting underdeveloped ovaries . Furthermore , it was shown that the c-fos transcription factor was overexpressed in parasites submitted to RNAi of SmERK1 , SmJNK and SmCaMK2 indicating its putative involvement in gene regulation in this parasite's MAPK signaling cascade . We conclude that MAPKs proteins play important roles in the parasite in vivo survival , being essential for normal development and successful survival and reproduction of the schistosome parasite . Moreover SmERK and SmJNK are potential targets for drug development .
Schistosomes are parasitic flatworms ( Phylum Platyhelminths ) that can survive for years or decades in the mammalian host [1] , [2] . Besides strategies to inhibit or modulate host immune responses , the maintenance of homeostasis and complex cellular adaptations , Schistosoma integrates specific extracellular signals to generate an appropriate cellular response [3] . In this context , signal transduction has essential functions in the cell control involving non-linear integrated networks that interact mostly by switching the activity status of proteins . The mitogen-activated protein kinase ( MAP kinase/MAPK ) signaling pathway is activated by a variety of extracellular growth factor-receptor interactions in response to environmental stimuli and leads to the downstream transcriptional activation of specific genes [4] . For example , in mammals , activated ERK MAPKs can translocate into the nucleus and induce phosphorylation of specific transcription factors such as ELK-1 [5] . ELK-1 forms a complex with another transcription factor , SRF ( serum response factor ) , and the ELK-1/SRF complex is then able to bind to the promoter of the c-fos gene and trigger transcription [6] . MAPKs influence a number of tissue-specific biological activities like cell proliferation , survival and differentiation through the activation of other protein kinases , metabolic enzymes or by the phosphorylation of transcription factors and components of the cytoskeleton [7] . Recently we showed by in silico analyses that the MAPK signaling components are well conserved in the three main Schistosoma species that infect humans , namely S . mansoni , S . japonicum and S . haematobium [8] . These include representatives of the MAPK subfamilies ERK ( extracellular signal-regulated kinase ) , p38 , JNK ( c-Jun N-terminal kinase ) and nmo ( nemo MAPK ) . However , a detailed understanding of MAPK pathway in schistosome development and survival remains to be elucidated . In planarians , ERK plays a pivotal role in stem cell dynamics during regeneration . Activation of ERK signaling induces stem cells to exit proliferative state and enter the differentiating state [9] . In the C . elegans model nematode , ERK MAPKs are required for multiple developmental events , including the induction of vulval , uterine and spicule cell fates , and the promotion of germ line meiosis [10] . In S . mansoni Vicogne and colleagues ( 2004 ) [11] showed that the human epidermal growth factor ( EGF ) can activate the Ras/ERK pathway , which induces meiosis in oocytes . This is a relevant observation because oviposition is responsible for the pathogenesis of schistosomiasis . Females can release , on average , 300 highly immunoreactive eggs a day . Although , many eggs escape via body wastes , others become trapped in various tissues to elicit eosinophilic and granulomatous inflammatory reactions that give way to progressive fibrosis that can lead to organ dysfunction and , sometimes , death . These observations have led to our hypothesis that ERK MAPK pathway is involved in Schistosoma reproduction . Apart from MAPKs , c-Jun N-terminal kinase ( JNK ) proteins also have evolutionary conserved functions , including the control of cellular responses to stress stimuli induced by a range of intrinsic and environmental aggression , e . g . , UV irradiation , DNA damage , heat , bacterial antigens and inflammatory cytokines [12] . In addition , JNK signaling plays a crucial role during planarian regeneration by regulating the G2/M transition in the cell cycle of pluripotent stem cells [13] . In our in silico analyses , we showed that only one member of the MAPK JNK sub-family is encoded in the S . mansoni genome , in contrast to five genes expressed in Caenorhabditis elegans and three genes in humans [8] . This evolutionary constriction of the JNK subfamily in S . mansoni to just one enzyme suggests that SmJNK may be particularly worthy of investigation to understand its potential target for drug development as drug effectiveness can be marked when a single-copy gene is targeted [14] . The divalent cátion calcium ( Ca2+ ) is one of the most widely ion used as a second messenger in cell signaling , and much of this process is controlled by calmodulin-binding kinase ( CaMK ) [15] . As SmJNK , only one SmCaMK2 gene is encoded in the S . mansoni genome . In C . elegans , a JNK cell-specific pathway that is responsible for worm development , is activated by CaMK2 [10] , [16] . Against this background , our study aimed at elucidating the function of ERK , JNK , CAMK2 and RAS , proteins involved in the MAPKs signaling pathways in the parasite S . mansoni , using RNA interference ( RNAi ) . We show that RNAi of SmERK decreases egg production by female worms recovered from mice , which was consistent with the observations of an under-developed ovary and immature oocytes , and suggesting a direct involvement of SmERK in parasite reproduction . Furthermore , suppression of SmJNK gene expression killed the parasite and was associated with damage to the worm's tegument .
Brazilian national guidelines set out in the Law 11794/08 were followed , stipulating the conditions for the use of animals in scientific research and setting up the National Council for the Control of Animal Experimentation ( CONCEA ) requiring the establishment of ethics committees on the use of animals ( CEUA ) by institutions under operational standards set out in Decree 6899/2009 , including the principles of the Brazilian Society of Science in Laboratory Animals ( SBCAL ) . Accordingly , animal experiments carried out in this work were approved by the Ethics Commission for Animal Use ( CEUA ) of Fundação Oswaldo Cruz under the number P49/12-5 . The LE strain of Schistosoma mansoni was maintained at Centro de Pesquisas René Rachou – FIOCRUZ using Biomphalaria glabrata as the intermediate snail host . Schistosomula were obtained by mechanical transformation of cercariae according to Howells et al ( 1974 ) [17] and cultured in MEM medium ( Minimum Essential Medium Eagle ) supplemented with 20 mM Hepes , 2 mM glutamate , 1×10−6 M serotonin , 5×10−7 M hypoxanthine , 2×10−7 M hydrocortisone , 0 . 5% MEM vitamin solution 100X , antibiotics ( 100 U/ml penicillin and 100 µg/ml streptomycin ) , and 2% fetal bovine serum ( FBS ) . In order to establish the evolutionary relationships among ERK and JNK proteins , homologs from S . mansoni ( NCBI TaxID: 6183 ) , S . haematobium ( NCBI TaxID: 6185 ) , S . japonicum ( NCBI TaxID: 6182 ) , Caenorhabditis elegans ( NCBI taxID: 6239 ) , Drosophila melanogaster ( NCBI TaxID: 7227 ) , and Homo sapiens ( NCBI taxID: 9606 ) were selected for phylogenetic analysis . Amino acid sequences corresponding to the conserved catalytic domain ( PF00069 ) , present in JNK and ERK proteins , were aligned using MAFFT 7 with iterative refinement by the G-INS-i strategy [18] ( Figure S1 ) . The multiple sequence alignment comprising 34 sequences with 300 sites was manually refined using Jalview [19] and further used in phylogenetic analysis . To reconstruct the phylogenetic tree we used MrBayes ( version 3 . 2 . 1 ) , which performs Bayesian inference using a variant of the Markov chain Monte Carlo ( MCMC ) [20] . MCMC analyses were run as four chains for 10 , 000 , 000 generations and sampled every 100 generations . Of the initial samples , 25% were discarded as “burn-in . ” Mixed models were applied as a parameter to estimate the best-fit evolutionary model . Support values were estimated as Bayesian posterior probabilities . The S . mansoni sequences were downloaded from SchistoDB , version 3 . 0 [21] . We selected five genes from the MAPK signaling pathway to perform the RNAi experiments: SmCaMK2 ( Smp_011660 . 2 ) , SmJNK ( Smp_172240 ) , SmERK1 ( Smp_142050 ) , SmERK2 ( Smp_047900 ) and SmRas ( Smp_179910 , previously characterized by [22] ) . In addition to the evaluation of transcript levels of those five genes , the transcription factors SmSRF ( Smp_097730 ) , SmC-Fos1 ( Smp_124600 ) and SmC-Fos2 ( Smp_170130 ) were also included in the analysis , in order to evaluate downstream interactions . Procedures for dsRNA preparation , qPCR primer design and analysis , isolation of parasite RNA and reverse transcription to cDNA have been detailed previously [23] Primers were designed using the Primer 3 software ( http://frodo . wi . mit . edu/ ) [24] , [25] following strictly the MIQE guidelines [26] employing a 150–200 bp target product size for qPCR and 500–600 bp for templates of double stranded-RNA ( dsRNA ) ( Figure S2 ) . A T7 promoter tag was added to the 5′ end of all PCR primers designed for dsRNA template amplification ( Table 1 ) . A fragment of ∼500 bp of open reading frame for GFP ( from the plasmid vector pCRII-GFP ) was used as non- schistosome RNAi control [23] . Each qPCR primer was designed to anneal outside the targeted region of dsRNAs and was tested for primer annealing efficiency and optimal concentration . SmCaMK2 ( Smp_011660 . 1 ) has two predicted alternative splicing products ( Smp_011660 . 2 and Smp_011660 . 3 ) . The regions selected to design the dsRNA and to measure the transcription level by qPCR were identical in the three isoforms . Following amplification , PCR products were separated on 1% agarose gels and purified using QIAquick Gel Extraction Kit ( QIAGEN ) . DsRNAs targeting specific S . mansoni genes were generated from PCR products of approximately 500 bp that had been amplified from schistosomula cDNA using the T7 RiboMAX Express RNAi Kit ( Promega ) as described elsewhere [23] , [27] . Final dsRNA synthesis reactions were allowed to incubate for 16 h at 37°C prior to DNAse treatment . DsRNA was analyzed by electrophoresis in 1% agarose gels to ensure that the correct length of product was generated: sequence identity was confirmed by DNA Sanger sequencing . Schistosomula ( 2 , 000 worms ) were cultivated in 24-well polystyrene plates containing 2 mL MEM supplemented with 1% FBS , 100 U/ml penicillin and 100 µg/ml streptomycin . For each treatment , 100 nM of dsRNA were added in the first day . Incubations were carried for 2 , 4 or 7 days at 37°C under 5% CO2 . The experiments were performed in duplicate and in three biological replicates . For qPCR , total RNA was extracted using the RNeasy Mini Kit ( Qiagen ) . Residual DNA was removed by DNase digestion using the Turbo DNA-free kit ( Ambion , Life Technologies ) . RNA ( 100 ng ) was used to synthesize cDNA with the Superscript III cDNA Synthesis kit ( Life Technologies ) . Each cDNA sample was tested in three technical replicates per plate using a minimum of 3 biological replicates . Experiments were carried out in a 7500 Real Time PCR System ( Life Technologies ) using the Power SYBR Green Master mix ( Life Technologies ) . Reactions were carried out in a final volume of 25 µl in 96 well plates . S . mansoni cytochrome C oxidase I ( GenBank AF216698 ) was used as the sample normalizing transcript [28] , [29] , as it has been shown to be highly and constitutively expressed in various S . mansoni life-cycle stages [30] , [27] and GFP cDNA was used as endogenous control [31] . Two internal controls assessing both possible genomic DNA contaminations ( no reverse transcriptase ) and purity of the reagents ( no cDNA ) were included . The 2−ΔΔCt method was used to measure transcript levels post-RNAi [32] . Transcript levels were expressed as percentage of difference compared to those following exposure to the schistosome- unspecific GFP dsRNA . Statistical analysis employed the Mann-Whitney U-test ( p<0 . 05 ) . Swiss Webster mice were subcutaneously injected with 300 schistosomula 2 days after dsRNA treatment ( 3 independent experiments , 6 animals per group ) . After 37 days when the parasite has matured , mice were perfused according to Pellegrino and Siqueira ( 1956 ) [33] and the adult worms counted . Livers from infected animals were weighed and the eggs counted after digestion with 10% KOH . Statistical significance of the data was analyzed using the Mann-Whitney test ( Wilcoxon-Sum of Ranks , p<0 . 05 , N = 3 ) . Adult worm samples recovered after perfusion were analyzed by confocal microscopy . The parasites were fixed in AFA ( 2% acetic acid , 10% formaldehyde and 48% ethanol ) and stored at room temperature . Whole worms were stained with 2 . 5% hydrochloric carmine , dehydrated by passage through 70 , 90 and 100% ethanol , clarified with methyl salicylate and Canada balsam ( 1∶2 ) , and individually mounted on glass slides . Morphometric analyzes were performed on male and female worms using computer images ( Image Pro Plus - Media Cybernetics , USA ) captured by a Sony camera ( 640×480 pixels , RGB ) coupled to a light microscope ( Olympus BX50 ) . The following parameters were determined: number and area of testicular lobes , area of the ovary , the presence of eggs and vitelline glands , the integrity of tegument and presence of surface tubercles . Statistical significance of the data was analyzed using the Mann-Whitney test ( Wilcoxon-Sum of Ranks , p<0 . 05 ) . It was analyzed 5 females that were treated with SmERK dsRNA , 6 for SmJNK , 8 for SMCaMK2 and 6 GFP control; 13 males that were treated with SmERK dsRNA , 5 for SmJNK , 6 for SmCaMK2 and 9 for GFP control . Confocal microscopy images of the reproductive system and tegument were taken using a LSM-410 , ( Zeiss ) equipped with a 488 nm HeNe laser and a LP 585 filter in reflected mode .
It has previously been shown that S . mansoni expresses only one JNK sub-family member , which contrasts to the presence of five and three homologs in C . elegans and humans , respectively [8] . This evolutionary constriction of the JNK subfamily in S . mansoni suggests that the SmJNK protein may be a potential target for drug development . Aiming at characterizing the evolutionary relationships between ERK and JNK proteins encoded by parasites and free-living organisms , we performed phylogenetic analyses on selected homologs from three Platyhelminths ( S . mansoni , S . haematobium and S . japonicum ) , one nematode ( Caenorhabditis elegans ) , one arthropod ( Drosophila melanogaster ) and one chordate ( Homo sapiens ) . This taxon sampling covers important evolutionary innovations in processes in which kinases are directly involved in responses to environmental stimuli such as reproduction and development . As shown by Figure 1 , gene duplication followed by divergence was probably the main evolutionary mechanism driving the evolution of the ERK and JNK subfamily members . The tree topology shows two well-supported clades grouping ERK and JNK proteins , thus revealing that the catalytic domain ( PF00069 ) is sufficiently divergent to discriminate these two protein subfamilies . The number of orthologs in schistosomes and other metazoans varies and the presence of sequence variants may implicate structural and/or functional specializations . In most cases , when orthologs were identified in the three Schistosoma species , the relationships among them reflected the current knowledge regarding the origin and evolution of the Schistosoma lineage [34] . Together , these findings demonstrate that ERK and JNK proteins are evolutionarily conserved in metazoan species transducing signals from the cell surface to the nucleus . To functionally characterize MAPK pathway members ( SmERK1 , SmERK2 , SmJNK , SmCaMK2 and SmRas ) by RNAi , we co-incubated schistosomula with synthetic double-strand RNAs ( dsRNA ) in vitro . Relative to schistosome-unspecific controls using dsRNA to GFP , all genes targeted were sensitive to RNAi and were substantially suppressed after two , four or seven days ( Figure 2 ) . Transcript levels were reduced by up to 92% , for SmERK1after two days ( transcription levels relative to controls = 0 , 08+/−0 , 0079 ) to 42% for SmRas after four days ( transcription levels relative to controls = 0 , 58+/−0 , 04 ) ( Figure 2 ) . Additionally , decreased transcript levels of SmERK2 were observed in parasites two days after SmERK1 dsRNA exposure ( 56% of inhibition: transcription levels relative to controls = 0 , 44+/−0 , 006 ) ( data not shown ) , this could be due to the similarity between SmERK1 and SmERK2 . After this observation we decided to call the ERK1 treatment ERK1/2 . To investigate whether RNAi of SmCaMK2 , SmJNK and SmERK1/2 impacts parasite viability in vivo , schistosomula were first incubated for two days with dsRNA and then transferred into mice ( n = 6 per treatment ) . After 37 days , adult worms were perfused from the hepatic portal system and eggs recovered from livers . Due to the lack of effective RNAi knockdown , parasites treated with SmRas-dsRNA was not included in the in vivo test . RNAi of SmJNK in schistosomula resulted in the death of 56% of parasites relative to the GFP control ( Figure 3 ) . Also , the number of hepatic eggs was decreased by 59% ( Figure 4 ) . For SmCaMK2 and SmERK1/2 , no significant changes in the number of adult worms were observed post-RNAi ( Figure 3 ) ; also , RNAi of CaMK2 did not alter egg output . On the other hand , although the knockdown of SmERK1/2 did not seem to affect parasite survival , egg production was decreased by 44% relative to parasites GFP-dsRNA treated ( control ) ( Figure 4 ) . Transcript levels of SmCaMK2 , SmJNK and SmERK1/2 returned to its normal level of expression in 37 day-old worms ( data not shown ) . Confocal microscopy was employed to understand whether parasite morphology was also altered in association with the decreased viability and/or egg production after RNAi of SmJNK and SmERK1/2 . It was possible to observe that RNAi of SmJNK damaged the adult male tegument ( Figure 5 ) in which the tubercles were reduced ( Figure 5D ) and unusual dilations were observed ( Figure 5E ) . In addition , in the females control ( Figure 5C ) the ovary presents oocytes ranging from immature cells to mature cells with large and clearly nuclei and evident nucleolus , but the females worms treated with JNK dsRNA presented undifferentiated oocytes ( cells throughout the uterus present the same size ) ( Figure 5F ) . The knockdown of SmERK1/2 did not cause changes in male worms ( data not shown ) . The tegument and testicular lobes appeared to be normal and the seminal vesicle was full of spermatozoids . However , the females showed alterations in the reproductive system such as small ovaries ( ∼44% smaller than GFP controls ) ( Figure 6A ) containing immature oocytes ( Figure 6D ) or , even when mature oocytes were observed ( Figure 6E ) , a higher number of oocytes were present in the uterus ( Figure 6F ) whereas eggs were expected in this location , like the ones observed in the control group ( Figure 6C ) . In addition , RNAi of SmCaMK2 induced no apparent morphological alterations ( Figure S3 ) . In other organisms MAPK pathway , the downstream genes are transcribed when the ELK1/SRF complex binds to the promoter region of c-fos gene . To study the conservation of the MAPK pathway in S . mansoni compared to other metazoans , we measured the transcript levels of the SRF transcription factor and c-fos genes after RNAi of SmCaMK2 , SmJNK , SmRas and SmERK1 . RNAi of the first three targets caused the over expression of Smc-fos1 ( by 1 . 62+/−0 . 28; 1 . 65+/−0 . 14; 1 . 21+/−019 and 1 . 47+/−0 . 06 , respectively ) and Smc-fos2 ( by 1 . 65+/−0 . 15; 1 . 59+/−0 . 19; 1 . 95+/−0 . 24 and 1 . 53+/−0 . 02 , respectively ) ( relative to the GFP control ) ( Figure 7 ) . In addition , as the MAPKs ( SmJNK and SmERK-1 ) transcript levels increased up to seven days , the Smc-fos1 and Smc-fos2 RNA levels decreased ( 1 . 10+/−0 . 2 and 0 . 89+/−0 . 18 ) and ( 0 . 60+/−0 . 20 and 0 . 9+/−0 . 14 ) , respectively ( Figure 7 ) . SmSRF gene expression , in most cases , did not exhibit variation . A minor alteration in Smc-fos1 transcript level was observed after RNAi of SmRas ( Figure 7B ) .
MAPKs connect cell-surface receptors to regulatory targets within cells to coordinate gene expression . Members of this family regulate essential cellular processes and are conserved in eukaryotes [4] . It would be expected that MAPKs also have important functions in the schistosome parasite , however , little was known . Here , we demonstrate RNAi for genes related to MAPK signaling pathway , namely: SmJNK , SmERK-1 , SmERK-2 , SmCaMK2 , SmRas . Knockdown efficiency reached levels of up to 92% for SmERK-1 , whereas SmERK-2 was less susceptible with a 33% knockdown . Other authors [31] , [27] also reported variable efficiencies of RNAi across different targets and for specific dsRNA sequences . It is possible that some genes are expressed in cells and tissues that are inaccessible to dsRNA and/or that the employed delivery method ( soaking ) did provide for maximal penetration of the RNAi effect . Also , the secondary structure of some mRNA targets might prevent or affect activation of the RISC complex [35] . Having demonstrated RNAi for the MAPKs studied , we next asked whether RNAi would limit survival and development of the parasites upon their transfer to mice . Thus , RNAi of SmJNK seems to be partially lethal and 56% of the parasites did not survive to 37 days , at which time worms were harvested from mice and counted . In addition , the recovered worms had morphological changes in the tegument . It's important to emphasize that survived worms may be affected to a lesser extent or maybe even not affected by RNAi treatment . Mourão and colleagues [31] , after labeling the RNAi molecule with a fluorescent label , demonstrated that RNAi uptake was not equal among all parasites . So , the results suggest that SmJNK is an essential protein . This fact is reinforced by previous knowledge of JNK signaling pathway influencing metabolism , growth , regeneration , and stress tolerance in Drosophila lifespan regulation [36] . Moreover , in flies , the JNK signaling pathway is also involved in midgut epithelial homeostasis and may be important in other contexts , such as oxidative stress for protection against gut infections [37] . A strong inhibition of JNK signaling activity in Drosophila shortens lifespan due to complete inhibition of intestinal stem cells proliferation [36] . JNK signaling misregulation has also been implicated in regeneration , neurodegenerative diseases , diabetes , and cancer [38] , [39] , [40] , [41] , [13] . Moreover , JNK is only encoded by one gene in Schistosoma and Drosophila which is in contrast to the five subfamily members in C . elegans and three in humans . Accordingly , it's conceivable pivotal importance in the MAPK pathway and for downstream signaling may prove a valuable target point for small molecule interventions . In C . elegans , the JNK pathway is also activated by CaMK ( unc-43 , a calcium/calmodulin-dependent protein kinase ) in a cell-specific signaling pathway [10] , [16] . As JNK , only one CaMK2 protein was found in the predicted proteomes of S . mansoni [42] , [8] and S . haematobium . Although SmCaMK2 has been predicted to be an essential gene and potential drug target [42] , our present findings showed that RNAi of SmCaMK2 does not alter worm morphology or survival in mice . A simple explanation is that RNAi of CAMK2 was not efficient enough ( ranged between 46 and 67% ) to generate a phenotypic outcome . We also do not exclude the possibility that CaMK2 may regulate the JNK pathway only in particular cell type ( s ) or that the CaMK2 protein turnover is faster than that of SmJNK . Although , the same phenotype for SmJNK and SmCaMK2 was expected , since CaMK2 ( UNC-53 ) can activate JNK signaling pathway in C . elegans , no alteration was observed after CaMK2 dsRNA treatment in S . mansoni . There are at least two possible explanations to this outcome: i ) SmCaMK2 is not related to JNK signaling pathway or ii ) SmCaMK2 is not the only activator of JNK signaling pathway in Schistosoma . RNAi of SmERK1/2 decreased the number of parasite eggs recovered from the liver and apparently elicited morphological alterations only in the reproductive system of female worms . Our data are consistent with the known contributions of ERK to oocyte maturation and egg activation in other animals [43] , [44] . Thus , in Xenopus laevis , the ERK protein is involved in the coordination of oocyte maturation [45] . In C . elegans , the knockout of ERK , affects the development of the vulva ( necessary for egg-laying ) and oocytes , resulting in a loss of egg production [46] . In a closely related organism , Echinococcus multilocularis it has been demonstrated that the Erk-like MAPK is activated by soluble host growth factors that are released by host hepatocytes and triggers metacestode development in vitro [47] . Moreover , the use of Erk-like MAPK pathway inhibitors affected E . multilucularis development and growth , but did not induce mortality [48] . In mice , the inactivation of the ERK signaling pathway is associated with embryonic death caused by abnormal placental development [49] . Sandler and colleagues also demonstrated that ERK is involved in starfish egg apoptosis [50] . These data are consistent with the current results and suggest a functional conservation of the ERK pathway across metazoans . The effects observed after the knockdown of SmERK1/2 and SmJNK MAPKs were probably the consequence of gene transcription modulation that occur downstream of the MAPK signaling pathway . In other systems , SRF is a transcription factor known to regulate the transcription of the c-fos gene after MAPK activation [6] . For examples , in mammals , the c-fos gene has a variable level of transcription that is dependent on elk-1/SRF binding . The latter complex , in turn , has a less variable transcription rate as it presents a stable conformation in either active ( On ) or inactive ( Off ) modes [51] . In order to determine whether the MAPK pathway induces c-fos expression in S . mansoni , c-fos and SRF transcripts levels were evaluated after transcript knockdown of SmRas , SmERK1/2 , SmJNK and SmCaMK2 . In general , we noted that the transcript levels of SmSRF remained constant . However , it was noted a different regulation ( up or down ) of SmSRF after SmRAS and SmERK dsRNA treatment ( Figure 7 ) that may be an influence of some negative feedback regulation , a wide-spread mechanism among signaling molecules , especially in the MAPK pathway [52] , [53] . On the other hand , the transcription of Smc-fos1 and Smc-fos2 is upregulated after RNAi of MAPK pathway genes . Thus , SmERK1/2 , SmCaMK2 and SmJNK negatively regulated c-fos , whereby low levels of those proteins induce c-fos transcription . This contrasts with mammalian systems in which the inactivation of ERK and JNK prevents SRF activation , which , in turn , does not bind to the c-fos promoter region [5] . In contrast to the mammalian c-fos activation mechanism , C . elegans has a pathway that is consistent with our results observed for S . mansoni . Specifically , elk-1 ( LIN-31 in C . elegans ) and SRF ( LIN-1 in C . elegans ) form a complex when MAPKs are not phosphorylated that activates c-fos , which then inhibits vulval development . When MAPK is phosphorylated , the elk-1/SRF complex dissociates and elk-1 promotes vulval development in a signaling pathway that is activated by epidermal growth factor ( EGF ) [54] . Moreover , it was recently reported that pathways involved in activating c-fos gene expression might be themselves activated by calcium influx through the CaMK signaling pathway [50] . In this case , c-fos expression is induced by phosphorylation of CaMK2 which , in turn , phosphorylates SRF without a direct relationship to ERK or JNK proteins [55] . Together , it is possible that the high levels of Smc-fos1 and Smc-fos2 transcripts , as a result of RNAi of SmERK , SmJNK and SmCaMK2 , is related to the inactivation of the MAPK signaling pathway which then induces the formation of the elk-1/SRF complex ( Figure 8B–C ) . The elk-1/SRF complex is targeted by different signaling cascades and is involved in the regulation of c-fos . In S . mansoni , even though the outcomes of RNAi of SmJNK and SmCaMK2 were quite different , it does seem that both gene products contribute to the regulation of the c-fos gene . SmJNK and SmCaMK2 may be involved in independent pathways or they may simultaneously co-regulate the same gene in a particular cell type . On the other hand , SmRas and SmERK would act in the same pathway , as is the case for C . elegans , mammals and Drosophila , being directly involved in the development of S . mansoni eggs ( Figure 8A ) . Our findings using RNAi demonstrate that S . mansoni MAPKs are essential to worm survival and/or reproduction suggesting that one or more of these kinases may be of interest in the development of new compounds to treat schistosomiasis . The complete mechanism by which MAPKs regulate those systems in Schistosoma still have to be elucidated to better focus on the most promising drug target . Accession number for SchitoDB [21]: SmCaMK2 ( Smp_011660 . 2 ) , SmJNK ( Smp_172240 ) , SmERK1 ( Smp_142050 ) , SmERK2 ( Smp_047900 ) , SmRas ( Smp_179910 ) , SmSRF ( Smp_097730 ) , SmC-Fos ( Smp_124600 ) , SmC-Fos2 ( Smp_170130 ) .
|
Enzymes known as mitogen-activated protein kinases ( MAP kinases/MAPKs ) influence a number of essential biological activities , such as cell proliferation , differentiation and survival . However , for the Schistosoma mansoni flatworm parasite , very little is known about these enzymes . We used RNA interference ( RNAi ) , a technique designed to decrease or stop the production of specific proteins of interest , to examine the contributions of five Schistosoma mansoni MAPKs to parasite growth and survival . After inducing the RNAi effect in young parasites , we then transferred the worms into mice and after 37 days , counted the number of surviving adult worms in the bloodstream , eggs in the liver , and examined those surviving worms for morphological defects . We found that RNAi of SmJNK decreases parasite survival by 56% , whereas RNAi of SmERK slows the maturation of the ovary and , thus , egg-laying . We also noted that c-fos , that is responsible for activating genes in the genome , was upregulated after RNAi of MAPKs . Our results help define the importance of MAPKs in the normal development and survival of the schistosome parasite and suggest one or more of these enzymes may be useful as drug targets to treat schistosomiasis .
|
[
"Abstract",
"Introduction",
"Methods",
"Results",
"Discussion"
] |
[
"signal",
"transduction",
"infectious",
"diseases",
"medicine",
"and",
"health",
"sciences",
"helminth",
"infections",
"schistosomiasis",
"cell",
"biology",
"biology",
"and",
"life",
"sciences",
"molecular",
"cell",
"biology",
"parasitic",
"diseases"
] |
2014
|
Regulation of Schistosoma mansoni Development and Reproduction by the Mitogen-Activated Protein Kinase Signaling Pathway
|
High-density lipoprotein ( HDL ) is believed to play an important role in lowering cardiovascular disease ( CVD ) risk by mediating the process of reverse cholesterol transport ( RCT ) . Via RCT , excess cholesterol from peripheral tissues is carried back to the liver and hence should lead to the reduction of atherosclerotic plaques . The recent failures of HDL-cholesterol ( HDL-C ) raising therapies have initiated a re-examination of the link between CVD risk and the rate of RCT , and have brought into question whether all target modulations that raise HDL-C would be atheroprotective . To help address these issues , a novel in-silico model has been built to incorporate modern concepts of HDL biology , including: the geometric structure of HDL linking the core radius with the number of ApoA-I molecules on it , and the regeneration of lipid-poor ApoA-I from spherical HDL due to remodeling processes . The ODE model has been calibrated using data from the literature and validated by simulating additional experiments not used in the calibration . Using a virtual population , we show that the model provides possible explanations for a number of well-known relationships in cholesterol metabolism , including the epidemiological relationship between HDL-C and CVD risk and the correlations between some HDL-related lipoprotein markers . In particular , the model has been used to explore two HDL-C raising target modulations , Cholesteryl Ester Transfer Protein ( CETP ) inhibition and ATP-binding cassette transporter member 1 ( ABCA1 ) up-regulation . It predicts that while CETP inhibition would not result in an increased RCT rate , ABCA1 up-regulation should increase both HDL-C and RCT rate . Furthermore , the model predicts the two target modulations result in distinct changes in the lipoprotein measures . Finally , the model also allows for an evaluation of two candidate biomarkers for in-vivo whole-body ABCA1 activity: the absolute concentration and the % lipid-poor ApoA-I . These findings illustrate the potential utility of the model in drug development .
Epidemiological studies have shown that high levels of low-density lipoprotein cholesterol ( LDL-C ) as well as low levels of high-density lipoprotein cholesterol ( HDL-C ) are associated with increased cardiovascular disease ( CVD ) risk [1] , [2] . While LDL-C lowering therapies have been shown consistently to reduce CVD risk , there is significant residual risk that remains to be managed [2] . The strong inverse association between HDL-C and CVD risk has led to the “HDL-C hypothesis” , whereby all HDL-C raising therapies should be anti-atherogenic [2] , [3] . Currently , the anti-atherogenic activity of HDL is mainly attributed to its role in mediating reverse cholesterol transport ( RCT ) , whereby cholesterol is effluxed from peripheral tissues and transported to the liver for biliary excretion [4] . However , the recent failures of a number of HDL-C raising intervention trials [5]–[7] have called for a re-examination of the HDL-C hypothesis . It has long been thought that HDL-C is a reliable biomarker for cholesterol efflux from tissues [8] . However , the several recent failed HDL-C raising intervention trials provide mounting evidence that at least under certain conditions , the plasma concentration of HDL-C , a very simple and static measure , is inadequate for characterizing the rate of RCT , which is a complex and dynamic process [8] . A revision of the HDL-C hypothesis to the “HDL flux hypothesis” has been proposed , whereby interventions should be aimed at promoting cholesterol efflux to HDL , and hence the overall RCT rate , independently of their effects on HDL-C levels [9] , [10] . Hence , there is now a pressing need to better understand the role of HDL-C raising targets in the context of RCT and to identify biomarkers which could provide information on the flux rate through the RCT pathway [8] . Our modeling effort is focused on addressing these issues . A number of previous mathematical models have focused on various aspects of lipid metabolism; see [11] , [12] for recent reviews . Of the existing models , some describe metabolic processes at a mechanistic level [13]–[19] , while others have been empirically derived from tracer kinetic studies [20]–[22] . In general these models were built to describe the dynamics of HDL and the other major lipoprotein classes , which include LDL , intermediate density lipoprotein ( IDL ) and very low density lipoprotein ( VLDL ) , describing lipid transport between these particles mediated by the cholesteryl ester transport protein ( CETP ) in the normal or basal state , and the effects of genetic mutations and/or drug interventions on these processes . While valuable insights have been gained from these models , none can be used to predict the associated changes in the RCT rate since they lack a mechanistic description of ApoA-I dynamics and other key processes involved in the RCT pathway . The latter include the lipidation of lipid-poor ApoA-I via its interaction with ATP-binding cassette transporter member 1 ( ABCA1 ) , the key process in the initiation of RCT [8] , as well as processes of HDL remodeling which lead to the delivery of cholesterol from HDL to other lipoproteins and cells , and the regeneration of lipid poor ApoA-I [23] . In all the existing models except the ones by Hübner et al [16] and Adiels et al [24] , the dynamics of apolipoproteins that cover the surface of lipoprotein particles are not described . While each VLDL , IDL and LDL particle contains only one ApoB molecule per particle , for HDL particles the number of ApoA-I molecules per particle may vary from 2 to 4 or more depending on HDL size [25] . This variation results from HDL remodeling processes such as particle fusion , CETP-mediated lipid transport , lipolysis and esterification whereby particles can gain or lose core lipid content as well as ApoA-I molecules [23] . While it has been shown experimentally and theoretically that the number of ApoA-I molecules on a given HDL particle is intrinsically linked to the particle size [25] , this important relationship has yet to be incorporated into a mechanistic model of HDL metabolism . In this paper , we propose a novel model of lipoprotein metabolism and kinetics ( the LMK model ) that provides an integrated description of the dynamics of cholesterol and ApoA-I in plasma . In particular , the model captures the initiation of RCT from the lipidation of lipid-poor ApoA-I by the ABCA1 transporter , the generation of nascent discoidal and nascent spherical particles , HDL particle fusion , CETP mediated lipid transfer between HDL and other lipoproteins , and the dissociation of excess ApoA-I from mature spherical α-HDL due to remodeling processes . The model is calibrated to: lipoprotein measures for normal and CETP deficient subjects; cholesteryl ester ( CE ) and ApoA-I fluxes measured in normal subjects; data on the fractional catabolic rate ( FCR ) of ApoA-I . The structure and the kinetic constants of our model provide an explanation for the relationship between FCR of ApoA-I and HDL particle size . To our knowledge the LMK model is the first to provide a mechanistic basis for the linkage between the metabolism of ApoA-I and the cholesterol component of HDL . The model has been validated by simulating patients with genetic mutations in the HDL metabolism pathway and the predictions are compared with lipoprotein measures reported in literature . Finally , the model was used to evaluate targets that could potentially increase RCT and to identify relevant biomarkers , as part of the effort to support drug discovery and development using a model-based approach .
The LMK model is shown schematically in Figure 1 , focused on the RCT pathway and a number of targets contained within it , for instance CETP , ABCA1 , ApoA-I and SRB1 . The LMK model describes the synthesis of ApoA-I and the initiation of RCT by the interaction of lipid-poor ApoA-I with ABCA1 leading to the formation of mature , spherical α-HDL . The HDL remodeling processes represented in the model include: the fusion of spherical HDL particles ( arrow 5 of Figure 1 ) ; the exchange and elimination of CE in spherical HDL by interaction with CETP ( arrows 12–14 ) and SRB1 ( arrow 7 ) ; the regeneration of lipid-poor ApoA-I from spherical HDL particles ( arrow 3 ) . Lipid-poor ApoA-I is assumed to be eliminated via the kidney ( arrow 4 ) , while the spherical HDL particles are assumed to be eliminated by a holo-uptake mechanism with a rate dependent on the particle size ( arrow 6 ) . The transfer and elimination of CE in LDL and VLDL pools are also represented ( arrows 9–11 ) . Our approach is to adequately describe the metabolic processes , while keeping the model as simple as possible . The representations of lipoprotein components and metabolic processes in the LMK model reflect these principles . In order to increase confidence in its predictions , the LMK model has been validated by simulating a number of scenarios that have not been used in the calibration process . In particular , since ABCA1 and ApoA-I are important targets in the pathway , the literature data on subjects with mutations in these genes [46] , [47] are compared against the model simulations . The heterozygotes and homozygotes of ABCA1 mutation are simulated by setting ( representing ABCA1 activity ) to 50% and 0% of its nominal value respectively; similarly , heterozygotes and homozygotes of ApoA-I mutation are simulated by setting the parameter ( representing ApoA-I synthesis rate ) to 50% and 0% of its nominal value respectively . Figure 5 shows the mean and 95% confidence intervals of the model simulations , compared to the literature data ( mean and SD are given ) . An examination of the results for the heterozygotes shows that , encouragingly , the LMK model is able to differentiate between the effects of ABCA1 and ApoA-I mutations on HDL-C and ApoA-I levels: both quantities decrease more for ApoA-I heterozygotes as compared to ABCA1 heterozygotes . Furthermore , the LMK model predicts that heterozygotes of ABCA1 mutation have smaller HDL particles ( data not shown ) , consistent with the data of Asztalos et al [46] . Most of the calibration data are static in nature , hence it is of particular interest to perform dynamic simulations of the LMK model and compare them to existing data . As a validation , we would like to see if the LMK model reproduces the characteristic biphasic decay curves seen in tracer kinetic experiments with labelled ApoA-I . In the LMK model , the injection of radio-labelled dose is represented by a small addition to the pool of lipid-poor ApoA-I and the fractional dose remaining in the sum of the two pools of ApoA-I is plotted; refer to the Methods section for the details of the simulation methodology . This is simulated using the parameters identified for the nominal subject and the result is shown in Figure 6: it can be seen that the simulated decay curve is biphasic and similar to the data obtained by digitizing Figure 3 of Ikewaki et al [48] . Furthermore , the mean residence time ( which is the inverse of FCR ) of labelled ApoA-I computed from the model simulation is 4 . 2 days , which is in good agreement with the result of 4 . 8±0 . 3 days as measured in 4 subjects by Ikewaki et al [48] . Having calibrated and validated the LMK model , we use it as a platform for exploring the observed epidemiological relationship between HDL-C and CVD risk . For this purpose , a virtual population is generated in a manner analogous to that of reference [49] . In particular , model parameters are sampled from a multivariate normal distribution and for each set of parameters the “phenotype” of the corresponding virtual subject is simulated using the LMK model . As there is no information available on the correlation between model parameters in a real population , we have assumed them to be uncorrelated and each is drawn from a normal distribution with a relative SD = 15% around the value corresponding to the posterior values for the nominal subject ( see Table 5 ) . Despite the fact that the parameter distribution in the virtual population is uncorrelated , some of the simulation outputs show significant correlations as a result of the model structure . Of particular interest is the correlation between RCT rate ( as defined in ( 2 ) ) and plasma biomarkers . Shown in Figure 7 is the relationship between RCT rate and HDL-C within the virtual population: it can be seen that there is a surprisingly strong correlation between the two quantities ( r = 0 . 95 ) . We note that the RCT rate given in ( 2 ) corresponds to the input rate of HDL-CE into plasma: in fact , the plasma concentration of HDL-CE can be expressed as the following: ( 3 ) where the clearance is defined as the plasma volume multiplied by the sum of elimination rate constants . In the LMK model , elimination processes for HDL-CE include those mediated by CETP and SRB1 , as well as the holo-particle uptake . While the RCT rate shows a strong correlation with HDL-C , we see that in Figure 8 the clearance of HDL-CE shows a much weaker negative correlation with HDL-C ( ) . Hence , the simulation results suggest that the variation in HDL-C within the virtual population is largely attributed to variations in the RCT rate and not due to its clearance . Under the “HDL flux hypothesis” [2] that low RCT rate results in high CVD risk , the relationship shown in Figure 7 provides a plausible explanation for the epidemiological association between HDL-C and CVD risk . The same set of virtual subjects is also used in subsequent sections for target evaluation and biomarker identification . The LMK model can be used to evaluate actual and potential HDL-C raising therapies , by modulating targets of interest . We have used simulated the model for both the nominal subject , as well as for a virtual population . A number of studies have shown that CVD risk is correlated with plasma biomarkers such as HDL-C [1] , HDL-P [54] and pre-β1 [55] , [56] levels . In addition , the combination of NMR analysis of HDL with genotyping has also given a glimpse into the possible genes associated with HDL particle measures [57] . However , the mechanistic basis for these experimental observations as well as what underlies the correlations between the plasma biomarkers are not well understood . Using the proposed LMK model , we can reproduce and explain the correlations between these plasma biomarkers . In addressing these questions , the simulated biomarkers within the population of 2000 virtual patients ( as previously shown in Figure 7 ) were studied . The correlation between HDL-P and HDL-C within this set of virtual patients ( ) is shown in Figure 14 , panel A; we see that the simulation result is qualitatively similar to the positive correlation shown by Mackey et al [54] ( the absolute values of HDL-P obtained by NMR are approximately 2-fold greater than our simulations which are based on the updated Shen model; the discrepancy is discussed in [25] ) . A positive correlation also exists in the virtual population between HDL size and HDL-C ( ) , consistent with Mackey et al [54] ( see Figure 14 , panel B ) . Due to the growing appreciation for the importance of RCT [2] , [8] , [58] , there are on-going efforts in trying to quantitatively assess the steps involved in the process . The ABCA1 transporter is involved in the first step of RCT by removing cholesterol from peripheral tissues to plasma and its activity level in patients has been studied [59] . In particular , ABCA1 gene expression and protein concentration on leukocytes has been measured in patients with type 2 diabetes , where the data suggested a negative correlation between ABCA1 expression and HbA1c levels [59] . While there are assays that can quantify ABCA1 protein levels in specific cell types [60] , an experimental technique for the assessment of ABCA1 activity in-vivo at the whole body level has yet to be developed . Given the current experimental limitations , there is an interest to evaluate the potential effectiveness of plasma-based biomarkers for quantitatively assessing ABCA1 activity . Using the LMK model , we evaluated the potential effectiveness of two biomarkers for ABCA1 activity: firstly , the absolute concentration of lipid-poor ApoA-I; secondly , the relative concentration of lipid-poor ApoA-I as the percentage of total ApoA-I . Figure 15 panel A shows that the former is only weakly correlated with ABCA1 activity . In contrast , panel B shows that the latter exhibits a strong inverse correlation with ABCA1 activity; in fact , given a measured value of % lipid-poor ApoA-I , the relationship can be used to estimate ABCA1 activity . This result can be better understood by the following analysis . From equation ( 1a ) , the absolute concentration of lipid-poor ApoA-I at steady state can be expressed as: ( 4a ) ( 4b ) On the other hand , from ( 1b ) the % lipid-poor ApoA-I can be expressed as the following: ( 5a ) ( 5b ) Comparison of the denominators in ( 4a ) and ( 5a ) show that in the former expression , an additional parameter enters; however , it is small compared to ( the mean values being 2 . 42 and 95 . 18 respectively; see Table 5 ) . In the numerator , the main quantitative difference between the two expressions is the remodeling flux , , versus the ApoA-I normalized flux , . As shown in Figure 16 , the latter has a flatter dependence on as well as less variability due to other parameters . As a result , the ratio allows for a more precise estimate of compared to above . In conclusion , the analysis shows that the stronger inverse relationship shown in Figure 15 panel B can be attributed to the normalization of the remodeling flux by ApoA-I . The simulation results may further explain why , in some literature studies , % lipid-poor ApoA-I ( note that the absolute concentration of lipid-poor ApoA-I can be experimentally estimated by assays that measure pre-β1 [61] ) has been proposed as a risk factor , as well as how increased % lipid-poor ApoA-I could be associated with CVD risk . Our proposal of using the % lipid-poor ApoA-I as a surrogate measure for ABCA1 activity is in concordance with the previous suggestion by Asztalos et al [62] that the ratio pre- is a measure of the efficiency of RCT: a decrease in this ratio has been thought to reflect an enhanced RCT [62] , [63] . In addition , our finding of the inverse correlation between % lipid-poor ApoA-I and ABCA1 activity may explain the observation that increased fractional pre-β1 is associated with increased maximum intima-media thickness in both diabetics [64] and non-diabetic subjects [65] , as well as being associated with an increased risk for coronary heart disease and myocardial infarctions [66] . We foresee a number of potential future applications of the LMK model in the context of drug discovery and development , including the following: The LMK model is focused on capturing the dynamics of ApoA-I and CE transfers . However , extensions of the model to incorporate ApoA-II dynamics as well as explicitly representing triglyceride and phospholipid metabolism would be important for describing the effects of other drug classes , including the PPAR-α and γ agonists [67] , [68] or synthetic phospholipids [69] , [70] . These remain topics for further research . We have developed a novel , in-silico model of lipoprotein metabolism focused on the reverse cholesterol transport pathway . The model incorporates important concepts of HDL biology , including the regeneration of lipid-poor ApoA-I via α-HDL remodeling processes , and has been calibrated using literature data from a wide variety of sources . The model has been further validated by simulating scenarios not considered in the calibration process . These include its ability to reproduce the levels of HDL-C and ApoA-I in hetero- and homozygous subjects with either ABCA1 or ApoA-I mutation and the observed biphasic kinetics of ApoA-I seen in tracer kinetics studies . This provides an increased confidence in the LMK model predictions with respect to modulations of these important targets and in the model's ability to simulate time-dependent scenarios . In this paper , we have illustrated the applications of the LMK model in comparing the two target modulations , CETP inhibition and ABCA1 up-regulation . The results drawn from our model provide a possible explanation for the non-efficacy of dalcetrapib in the dal-OUTCOMES trial [7] as well as suggesting that ABCA1 is a target that would increase the RCT rate . The model provides predictions on the biomarker changes as a result of ABCA1 target modulation . Furthermore , computational experiments using a virtual population have shown why the % lipid-poor ApoA-I , rather than the absolute concentration of lipid-poor ApoA-I , is a better biomarker for assessing the in-vivo ABCA1 activity . By integrating mechanistic concepts and data , the model provides a way to quantitatively evaluate and explore hypotheses of lipoprotein metabolism .
In this section , prior estimates of model parameters are given , including references to the original literature and the rationale for the choice of prior and the level of uncertainty . In a manner similar to a previously proposed Bayesian approach [35] , uncertainty is increased by a factor in the following cases: No explicit prior correlations are assumed . In this section , we give the quantitative values and references for the data used in the calibration procedure . In this work , we assume that both the parameter prior and the data error are normally distributed . We employ the methodology of maximum a posteriori ( MAP ) [31] to combine the prior information with calibration data . Due to the conjugacy property [31] of the distributions , the posterior also has a normal distribution and the MAP solution is obtained by solving a nonlinear least squares problem . In our model , most of the parameters have an informative prior . For the set of parameters for which an informative prior is available , let denote the expected value of the prior distribution; otherwise , set to represent the lack of information . We take the covariance matrix for the prior distribution to have a diagonal structure: for parameters that have an informative prior , is the variance of the prior distribution; for parameters that have an uninformative prior , . That is , the prior distribution is assumed to be of the form [33]: ( 16 ) Let denote the vector of calibration data and the nonlinear mapping from model parameters to the observation , representing the model simulation of the data . Let denote the covariance matrix for the data . Hence , the conditional distribution of the data given the model parameter k is [33]: ( 17 ) Thus , the posterior distribution for the model parameters is given by ( 18 ) To find the MAP solution , the following nonlinear least squares problem is solved: with the objective function defined as , ( 19 ) the MAP solution is the minimizer: ( 20 ) Using parameter priors as given in Table 5 and calibration data as described in the previous section , the nonlinear least-squares problem was solved using genetic algorithm ga from the Matlab® Global Optimization Toolbox of MathWorks ( http://www . mathworks . com/ ) to obtain . In particular , the hybrid option was selected: 100 generations of the genetic algorithm was run with a PopulationSize = 500 , followed by constrained minimization ( fmincon ) using the setting MaxFunEvals = 10000 , MaxIter = 1000 . In all numerical integration of ODEs , the relative and absolute tolerances were set to 10−9 . The confidence interval is estimated using the following procedure: parameters are sampled around and for each parameter the ( with respect to its minimum , ) is computed according to the expression ( 19 ) . An estimate of the confidence region is obtained by examining the set of all parameters that lie within , where δ is computed from the number of degrees of freedom ( df ) and the desired confidence level [84] . Using df = 29 for the model and choosing the 95% confidence level , . A set of 1000 parameters satisfying are selected in estimating confidence intervals shown in the paper . The model simulations of the tracer kinetic experiment with labelled ApoA-I and the calculation of the FCR of ApoA-I were carried out using the technique of complex variable differentiation [85] . In particular , a small quantity of imaginary number representing the radio-labelled dose of ApoA-I is added to the lipid-poor pool at the start of tracer experiment and the imaginary component of the numerical solution is extracted to represent the dose remaining in the two pools of ApoA-I ( lipid-poor and α-HDL ) . This method relies on the complex extension of analytic functions from the real line , which can be easily implemented on the Matlab platform [85] . As compared to the finite-differencing approach , the complex variable methodology does not suffer from subtractive cancellation error and hence is more accurate [85] . While this approach has not been applied to tracer kinetic simulations , it has been applied to the sensitivity analysis of biological models [86] , [87] .
|
Epidemiological studies have shown a strong inverse association between HDL-C and cardiovascular risk and led to the formulation of the “HDL cholesterol hypothesis”: under this hypothesis , interventions raising HDL-C should decrease risk . However , the recent failures of HDL-C raising therapies in improving cardiovascular disease risk in outcomes trials have suggested a need to revise the hypothesis to account for the contrary data . An “HDL flux hypothesis” has emerged: it is not HDL-C level per se which forms the basis for reducing risk , but it is the flux rate of reverse cholesterol transport that drives risk reduction . We propose that , the concentration of HDL cholesteryl ester in plasma simply reflects the ratio of input rate of reverse cholesterol transport into the HDL compartments to its clearance rate . A challenge in identifying targets under the new conceptual framework is the feedback process that occurs between the input rate and the clearance rate of HDL-C . To meet this challenge , we have built a systems model which incorporates the main processes of HDL metabolism to elucidate the relationships between target modulations and the reverse cholesterol transport rate .
|
[
"Abstract",
"Introduction",
"Results/Discussion",
"Methods"
] |
[
"systems",
"biology",
"medicine",
"clinical",
"research",
"design",
"biophysic",
"al",
"simulations",
"atherosclerosis",
"biology",
"computational",
"biology",
"anatomy",
"and",
"physiology",
"cardiovascular",
"system",
"modeling",
"cardiovascular"
] |
2014
|
An In-Silico Model of Lipoprotein Metabolism and Kinetics for the Evaluation of Targets and Biomarkers in the Reverse Cholesterol Transport Pathway
|
In 2009 , the World Health Organization ( WHO ) proposed seven warning signs ( WS ) as criteria for hospitalization and predictors of severe dengue ( SD ) . We assessed their performance for predicting dengue hemorrhagic fever ( DHF ) and SD in adult dengue . DHF , WS and SD were defined according to the WHO 1997 and 2009 dengue guidelines . We analyzed the prevalence , sensitivity ( Sn ) , specificity ( Sp ) , positive predictive value ( PPV ) and negative predictive value ( NPV ) of WS before DHF and SD onset . Of 1507 cases , median age was 35 years ( 5th–95th percentile , 17–60 ) , illness duration on admission 4 days ( 5th–95th percentile , 2–6 ) and length of hospitalization 5 days ( 5th–95th percentile , 3–7 ) . DHF occurred in 298 ( 19 . 5% ) and SD in 248 ( 16 . 5% ) . Of these , WS occurred before DHF in 124 and SD in 65 at median of two days before DHF or SD . Three commonest warning signs were lethargy , abdominal pain/tenderness and mucosal bleeding . No single WS alone or combined had Sn >64% in predicting severe disease . Specificity was >90% for both DHF and SD with persistent vomiting , hepatomegaly , hematocrit rise and rapid platelet drop , clinical fluid accumulation , and any 3 or 4 WS . Any one of seven WS had 96% Sn but only 18% Sp for SD . No WS was highly sensitive in predicting subsequent DHF or SD in our confirmed adult dengue cohort . Persistent vomiting , hepatomegaly , hematocrit rise and rapid platelet drop , and clinical fluid accumulation , as well as any 3 or 4 WS were highly specific for DHF or SD .
Dengue is an acute febrile disease with a wide range of clinical presentations . The disease has been known for more than a century in the tropical areas of South East Asia and the Western Pacific regions [1] . Epidemics of dengue have now become a regular occurrence worldwide [2] . Although various diagnostic tests are available for diagnosis of dengue [3] , [4] , predicting disease outcome of dengue patients remains challenging . Early identification of signs that can predict severe dengue ( SD ) may save lives by facilitating early initiation of interventions and frequent monitoring [5] . Attempts at providing evidence-based predictors for severe disease have been made . A study on adult dengue inpatients in Singapore showed that dengue hemorrhagic fever ( DHF ) can be predicted by the presence of bleeding , hypoproteinemia , raised blood urea and lymphopenia [6] . Ramirez-Zepeda et al reported the presence of ascites , gum bleeding , hematemesis , thrombocytopenia and persistent vomiting as predictors of major complications [7] . Thomas et al demonstrated that abdominal pain , cough or diarrhea reported by patients at presentation were significantly associated with the development of severe manifestations [8] . A study from India reported that profound shock was preceded most commonly by sudden hypotension [9] . The World Health Organization ( WHO ) and the Special Program for Research and Training in Tropical Diseases ( TDR ) jointly published the dengue guidelines for diagnosis , treatment , prevention and control in 2009 , suggesting seven warning signs to identify patients at risk of SD . The proposed warning signs include abdominal pain or tenderness , persistent vomiting , clinical fluid accumulation , mucosal bleed , lethargy or restlessness , liver enlargement >2 cm , increase in hematocrit concurrent with rapid decrease in platelet count [10] . Barniol et al reported that the use of these warning signs for case management was of practical value [11] . Alexander et al described these warning signs associated with disease progression in a majority of younger patients [12] . In Singapore , 92 . 2% of dengue cases reported to Ministry of Health were older than 14 years [13] . Therefore , these warning signs need to be validated in adult dengue . We aimed to validate the utility of warning signs from the WHO 2009 guideline in laboratory-confirmed adult dengue inpatients . In particular , we aimed to determine the predictive value of warning signs to predict DHF as defined by the WHO 1997 guideline as well as SD as defined by the WHO 2009 guideline [10] , [14] .
Domain Specific Review Board , National Healthcare Group , Singapore approved the study . All data were anonymized . All patients were managed using a standardized dengue clinical care path that facilitated consistent capture of clinical and laboratory data . This retrospective study was performed by extracting demographic , clinical , laboratory , radiological , treatment and outcome data from laboratory-confirmed dengue inpatients managed by the Department of Infectious Diseases at Tan Tock Seng Hospital , Singapore in the years 2004 , 2007 and 2008 . The study cohorts were selected to represent different predominant dengue serotypes , being dengue serotype 1 ( DEN1 ) in 2004 and dengue serotype 2 ( DEN2 ) in 2007 and 2008 [13] . Our center is the largest single center in Singapore managing predominantly adult dengue , with nearly 40% of nationally reported cases in 2005 [15] . We included only patients with positive dengue polymerase chain reaction ( PCR ) during the early febrile viremic phase of their illness [3] . Warning signs recorded include: abdominal pain or tenderness , persistent vomiting , clinical fluid accumulation ( pleural effusion or ascites detected by physical examination or radiologically ) , mucosal bleed , lethargy , hepatomegaly , rise in hematocrit concurrent with rapid drop in platelet count [10] . Lethargy was not included in analysis of 2004 cohort as the information was not available . Clinical outcomes were DHF as defined by the WHO 1997 guideline , and SD as defined by the WHO 2009 guideline . Patients were diagnosed as DHF if they had fever , thrombocytopenia , bleeding and evidence of plasma leakage ( either hypoproteinemia , change in hematocrit of more than 20% , or clinical fluid accumulation ) [14] . Severe dengue was fulfilled if there was evidence of plasma leakage associated with shock or respiratory distress , severe bleeding or severe organ involvement [10] , [14] . Clinical outcomes were determined using data from the time of hospital presentation to the time of hospital discharge . The exact day patients fulfilled criteria for DHF and SD was noted . Warning signs were analyzed until patients reached the clinical outcomes , i . e . , developed DHF and/or SD . Cases with warning signs only occurring after clinical outcomes had reached were excluded from analysis . For descriptive analyses , frequency and percentages were used for categorical variables . For continuous variables , median , range and percentiles were used . Warning signs preceding development of clinical outcomes were classified as true positive ( TP ) cases . Likewise , presences of warning signs in patients without DHF and/or SD were classified as false positive ( FP ) cases . Sensitivity ( Sn ) , specificity ( Sp ) , positive predictive value ( PPV ) and negative predictive value ( NPV ) were determined for individual warning sign as well as for presence of any warning signs in predicting the clinical outcomes of DHF and/or SD . Predictive values for the presence of more than one WS were explored . The Statistical Package for the Social Sciences version 16 ( SPSS Inc . , Chicago , IL ) was used for data analyses .
There were 1 , 507 patients with PCR-confirmed dengue in our study: 917 in 2004 , 318 in 2007 and 272 in 2008 . Overall , the median age was 35 years ( 5th–95th percentile , 17 . 0–59 . 7 years ) , and 1 , 037 ( 68 . 8% ) were male . Majority was Chinese which constituted 1 , 110 ( 73 . 7% ) . In terms of clinical outcomes , 294 ( 19 . 5% ) patients developed DHF and 248 ( 16 . 5% ) patients had SD . One hundred and fifteen patients fulfilled both DHF and SD criteria . Among 248 patients with SD , 56 . 9% had severe plasma leakage with shock or respiratory distress , 37 . 9% had severe bleeding and 16 . 1% had severe organ involvement . Demographic and pertinent clinical data for each year were detailed in Table 1 . Table 2 showed the occurrence of warning signs during the entire clinical course ( i . e . from hospital presentation to hospital discharge ) as well as up to the day of clinical outcomes of DHF or SD . In our study , 787/1507 ( 52% ) patients had any of six warning signs ( without lethargy ) during clinical course , of which 125/294 ( 43% ) occurred before progression to DHF and 62/248 ( 25% ) before progression to SD . The three most common warning signs occurring before development of DHF and/or SD were lethargy , abdominal pain or tenderness , and mucosal bleeding . Detailed frequencies of warning signs are shown in Table 2 . Table 3 describes the performance of warning signs to predict DHF in 1507 patients . Having any of seven warning signs had 87% Sn to predict DHF , while having any of six warning signs ( without lethargy ) was marginally lower at 81% . Specificity was high for persistent vomiting ( 93% ) , hepatomegaly ( 99% ) , rise in hematocrit concurrent with rapid platelet count drop ( 92% ) and clinical fluid accumulation ( 98% ) . However , Sp was low at 18% for any of seven warning signs , which improved to 57% if lethargy was omitted . Positive predictive values of warning signs were low , varying from 16% to 31% . Only any of six warning signs without lethargy and mucosal bleeding had NPV exceeding 90% . Performances for the presence of strictly one or more than one WS in predicting DHF were also shown . The occurrence of three or four warning signs was associated with specificity of 96% and 98% respectively . The performance for warning signs for each year was found to be similar to the overall cohort analysis although there was a difference in predominant serotype ( data not shown ) . Table 4 showed the performance of warning signs to predict SD for all patients . Having any of seven warning signs had 96% Sn to predict SD , while having any of six warning signs ( without lethargy ) had 71% Sn to predict SD . Persistent vomiting ( 93% ) , hepatomegaly ( 99% ) , rise in hematocrit concurrent with rapid platelet count drop ( 94% ) , and clinical fluid accumulation ( 98% ) had good Sp for SD . Specificity was higher without lethargy ( 55% for any of six warning signs without lethargy versus 18% for any of seven warning signs ) . Positive predictive value for SD was even lower than for DHF , ranging from 6% to 18% . Individual warning signs had negative predictive value for SD less than 90% , compared with 96% for any one of seven warning signs and 97% for any one of six warning signs ( without lethargy ) . The occurrence of three or four warning signs was associated with specificity of 95% and 98% respectively . Most warning signs appeared at median illness day 4 ( 5th–95th percentile , 2–7 days ) and preceded DHF or SD at a median of 2 days before progression to DHF ( 5th–9th percentile , 1–4 days ) or SD ( 5th–9th percentile , 1–6 . 1 days ) ( Table 5 ) . Median duration from onset of individual warning signs to development DHF or SD were statistically different for DHF ( p<0 . 05 by Kruskal-Wallis test ) , but not for SD ( p = 0 . 80 by Kruskal-Wallis test ) . Among the six intensive care unit ( ICU ) admissions , five patients had warning signs; of these four patients presented with WS prior to ICU admission . Of the five , four cases had DHF and all five cases progressed to SD . The sole fatality fulfilled DHF ( two days after admission ) and SD criteria ( on admission day ) and had three WS , two of which occurred before DHF , namely abdominal pain or tenderness , and rise in hematocrit concurrent with rapid platelet count drop .
Warning signs were reported by Guzman et al in a study of 12 adult DHF deaths where 58 . 3% of patients manifested warning signs on the second or third day from illness onset , of which abdominal pain and persistent vomiting were the commonest and most frequent [16] . Of 17 patients with DHF grade IV in Lucknow , India ( both children and adults ) , the commonest warning sign was sudden hypotension ( 47% ) ; among the warning signs reported that were included in the WHO 2009 , vomiting occurred in 23% , severe abdominal pain and restlessness in 18% each [9] . In a study of 23 dengue deaths in Puerto Rico ( both children and adults ) , Rigau-Perez et al noted that any one of clinical alarm signs occurred in 48% , usually occurring on the day of deterioration; of these , severe abdominal pain occurred in 26% and persistent vomiting in 13% [17] . These important observations were subsequently supported by several studies that examined symptoms and signs at presentation to predict dengue severity . Carlos et al in a study of 359 children with dengue of which a third had DHF reported that restlessness , epistaxis and abdominal pain at hospital presentation were significantly associated with DHF ( P<0 . 05 ) [18] . In a study of 560 adults with dengue at Martinique , France , where severe dengue was defined as hypotension , encephalopathy , plasma leakage , platelet count <20×10∧9/liter , aminotransferase levels more than 10 times upper limit of normal , and severe bleeding , the sensitivity and specificity for predicting these subsequent severe manifestations for symptoms at hospital presentation were: abdominal pain , 62 . 6% and 52 . 7%; cough , 37 . 6% and 77 . 3%; and diarrhea , 65 . 9% and 74 . 4% [8] . In a study of 79 children and adults requiring major intervention versus 691 controls in Southeast Asia and Latin America , Alexander et al found that abdominal pain or tenderness , lethargy , mucosal bleeding and platelet decrease noted one day prior within days 4 to 7 of illness were independently associated with need for major interventions [12] . These data from the DENCO study provided the basis for the WHO 2009 recommendations of warning signs [10] . In a study of 181 children with dengue in Rio de Janeiro , Brazil , where 30 patients had severe dengue according to the WHO 2009 criteria , lethargy and abdominal pain were independently associated with severe dengue , but not vomiting , clinical fluid accumulation , hepatomegaly and bleeding [19] . We systematically studied the utility of warning signs as proposed by the WHO 2009 for predicting DHF and SD as defined by the WHO in 1997 and 2009 respectively . The first observation was that while warning signs occurred in 86% of 1507 adult dengue confirmed with PCR , lower proportion occurred before development of the two clinical outcomes , 52% for DHF and 42% for SD . If lethargy was removed , then the overall incidence decreased from 86% to 52% , for DHF from 52% to 43% and for SD from 42% to 25% . For warning signs that did occur before DHF or SD , the median duration was 1–3 days for DHF and 1 . 5–3 days for SD , which allowed a window of opportunity for intervention . The second observation was that many warning signs on their own were uncommon , but lethargy , abdominal pain or tenderness and mucosal bleeding were the three commonest occurring before the development of DHF or SD . Persistent vomiting , hepatomegaly , rise in hematocrit concurrent with rapid drop in platelet count , and clinical fluid accumulation occurred in less than 10% . The third observation was that the removal of lethargy in our adult cohort improved the specificity of any of remaining six warning signs for DHF or SD . The fourth observation was that four warning signs were highly specific for both DHF or SD , namely persistent vomiting , hepatomegaly , rise in hematocrit concurrent with rapid drop in platelet count , and clinical fluid accumulation , albeit they occurred infrequently . Our analysis in a large cohort of PCR-positive adult dengue patients from three years with predominant dengue serotypes 1 and 2 showed that the positive predictive value for DHF and SD were not high , ranging from 16% to 31% for DHF , and 6% to 18% for SD . This finding was compatible with findings by Kalayanarooj in a study of 247 children with dengue and 24 without dengue that warning signs occurred in 50% of non-dengue and 53 . 3% of dengue fever [20] . There may be variations among children and adults with dengue as warning signs occurred in 52% of DHF and 42% of SD in our study of adult dengue versus 83–100% in DHF grades I to IV of pediatric dengue [20] . As warning signs are recommended as criteria of hospitalization [10] , both sensitivity and specificity are important . High specificity is important to optimize the use of scarce hospital resources to manage patients at high risk of progressing to severe dengue [21] . At the same time sensitivity is critical to ensure that dengue patients are not being sent home with subsequent progression to DHF or SD . Our analysis showed that individual warning signs failed to fulfill this requirement for adult dengue . However , while any one of seven warning signs was associated with 95% sensitivity and 96% negative predictive value , its specificity of 18% may result in over-hospitalization if this were to be used as a criterion for hospital admission . Limitations of our study included its retrospective study design , study population limited to adult dengue , study setting in a developed country with all cases confirmed with PCR and hospitalized in a tertiary referral center , lack of primary or secondary dengue infection data , dengue serotype data in individual patients , and lack of data on lethargy in our 2004 cohort . Despite its retrospective nature , all patients were managed with a standardized dengue clinical care path which helped to improve the reliability of data on vital signs , full blood count , serum creatinine and aminotransferases , and clinical data vital to the classification of warning signs , DHF and SD . Our large sample size of 1507 PCR-positive adult dengue with 294 DHF and 248 SD contributed to better understanding of warning signs for dengue severity where available data were mainly in children . Notably , we did not study the utility of warning signs as diagnostic criteria for probable dengue [10] as all our patients were confirmed with PCR , and we could not assess their utility as admission criteria [10] as all our patients were hospitalized . In conclusion , our analysis showed that individual warning signs had low positive predictive value for DHF and SD in a large cohort of PCR-confirmed adult dengue with predominantly dengue serotypes 1 and 2 , occurring before the development of DHF in 52% and SD in 42% . Removal of lethargy as a warning sign in adults may improve specificity of remaining six warning signs for both DHF and SD . Common warning signs of lethargy , abdominal pain or tenderness , and mucosal bleeding were not as specific as less frequently observed warning signs of persistent vomiting , hepatomegaly , rise in hematocrit concurrent with rapid drop in platelet count , and clinical fluid accumulation .
|
Dengue is a mosquito-borne infection with significant public health burden in tropical and subtropical regions . Clinical presentations may vary from self-limiting fever to severe dengue including death . The World Health Organization 2009 dengue guidelines classified dengue into dengue with and without warning signs , and severe dengue . In our adult dengue cohort , we found that lethargy , abdominal pain/tenderness , and mucosal bleeding occurred commonly . As predictors of severe dengue , these were not as specific as persistent vomiting , hepatomegaly , hematocrit rise and rapid platelet drop , and clinical fluid accumulation which occurred infrequently . Presence of any one warning sign had high sensitivity , but low specificity for severe dengue . Removal of lethargy from the list increased the specificity of any one warning sign , but sensitivity decreased . Consideration of these findings may avoid over hospitalization of potentially non-severe dengue patients and reduce burden on the healthcare system .
|
[
"Abstract",
"Introduction",
"Methods",
"Results",
"Discussion"
] |
[
"medicine",
"infectious",
"diseases",
"public",
"health",
"and",
"epidemiology",
"global",
"health",
"dengue",
"fever",
"travel-associated",
"diseases",
"neglected",
"tropical",
"diseases",
"dengue",
"viral",
"diseases",
"public",
"health"
] |
2013
|
Utilities and Limitations of the World Health Organization 2009 Warning Signs for Adult Dengue Severity
|
NOD1 is an intracellular pathogen recognition receptor that contributes to anti-bacterial innate immune responses , adaptive immunity and tissue homeostasis . NOD1-induced signaling relies on actin remodeling , however , the details of the connection of NOD1 and the actin cytoskeleton remained elusive . Here , we identified in a druggable-genome wide siRNA screen the cofilin phosphatase SSH1 as a specific and essential component of the NOD1 pathway . We show that depletion of SSH1 impaired pathogen induced NOD1 signaling evident from diminished NF-κB activation and cytokine release . Chemical inhibition of actin polymerization using cytochalasin D rescued the loss of SSH1 . We further demonstrate that NOD1 directly interacted with SSH1 at F-actin rich sites . Finally , we show that enhanced cofilin activity is intimately linked to NOD1 signaling . Our data thus provide evidence that NOD1 requires the SSH1/cofilin network for signaling and to detect bacterial induced changes in actin dynamics leading to NF-κB activation and innate immune responses .
Effective immune defense in mammals relies on the detection of conserved pathogen structures by pattern recognition receptors ( PRRs ) of the innate immune system to prime immune responses [1] . Several PRRs have been identified and extensively studied in the last decade . In particular , members of the NOD-like receptor ( NLR ) -family gained attention due to their intracellular localization [2] , [3] . One of the first NLRs shown to act as a PRR is NOD1 . NOD1 is an intracellular protein that can be activated by diaminopimelic acid-containing peptides derived from bacterial peptidoglycan and acts as a sensor for invasive bacteria such as Shigella flexneri [4]–[6] . A wealth of data suggest that NOD1 is an important PRR for a variety of bacteria in mammals , which also contributes to systemic activation of neutrophils , induction of adaptive immunity and immune tissue homeostasis ( reviewed in [2] , [3] ) . Upon activation , NOD1 forms a complex with the receptor-interacting serine/threonine-protein kinase 2 ( RIP2 ) , which results in the activation of NF-κB and mitogen-activated protein kinases ( MAPK ) signaling pathways [2] , [3] . Several components of the pathway downstream of NOD1 have been identified . For example , the NOD1 binding partner RIP2 mediates activation of the TGF-β-associated kinase 1 ( TAK1 ) complex which is induced by ubiquitylation of RIP2 through ubiquitin ligases including the X-linked inhibitor of apoptosis protein ( XIAP ) [7] and the cellular inhibitor of apoptosis protein-1 and -2 ( cIAP1 , and cIAP2 ) [8] . NOD1 is found at the plasma membrane where it co-localizes with F-actin . This localization was suggested to be a prerequisite for signaling because affecting actin polymerization changes NOD1 signaling [9] . Furthermore , the Salmonella effector SopE activates NOD1 , involving changes in small Rho GTPase activity [10] . Additionally , the RhoA guanine nucleotide exchange factor H1 ( GEF-H1 ) was linked to NOD1 activation [11] . Of note , the NOD1 related protein NOD2 is also regulated by the small GTPase Rac1 [12] , [13] and localizes at the plasma membrane at cortical F-actin structures , similar to NOD1 [9] , [13] , [14] . Together this indicates an intimate connection of NOD1 and NOD2 signaling with the actin cytoskeleton , although the mechanistic details remain largely elusive . Cellular actin dynamics are strictly controlled by the action of nucleation factors such as Arp2/3 , which bind to the sides of pre-existing filaments and promote the growth of new filaments at these sites . Actin binding proteins belonging to the actin depolymerization factors ( ADF ) /cofilin family control the disassembly of actin filaments by severing F-actin filaments , thereby generating new sites of actin polymerization . In addition , there is evidence that cofilin depolymerizes F-actin to provide new G-actin molecules for polymerization . Cofilin activity itself is tightly controlled by LIMK1 and LIMK2 , which phosphorylate cofilin at serine 3 whereby its activity is blocked . Accordingly , dephosphorylation by the phosphatase slingshot homolog 1 ( SSH1 ) reactivates cofilin ( reviewed in [15] ) . Here we identify the cofilin phosphatase SSH1 as an essential component of the human NOD1 signaling pathway and show that SSH1 links NOD1 activation to cofilin-mediated changes in actin remodeling .
To identify novel factors involved in NOD1-mediated NF-κB activation , we adapted a cell based NF-κB-luciferase reporter gene assay in HEK293T cells [16] for high-throughput ( HT ) small interfering RNA ( siRNA ) screening ( Figures S1A and B ) . A druggable-genome siRNA-library ( a sub-library of the human genome covering approximately 7000 genes with known protein domains ) containing four independent siRNAs per gene was screened in quadruplicate for hits inhibiting NOD1-mediated NF-κB activation upon treatment with the NOD1-specific elicitor TriDAP ( Figure S1A ) . After quality control and elimination of toxic siRNAs , preliminary candidates were selected using a probability-based algorithm ( redundant siRNA activity; RSA ) [17] ( Table S1 ) . Statistical analyses confirmed the high reproducibility of the results and the robustness of the assay controls ( p65 and the non-targeting Allstars siRNA ) ( Figure S2A ) . The top 435 of the RSA-ranked candidates with at least two hit siRNAs were differentially tested for TriDAP- as well as TNF-induced NF-κB activation ( referred to here as “validation screen” and “counter screen” , respectively ) , using two independent siRNAs in HEK293T cells ( Figure 1A and S1B ) . Knock-down of 173 genes for this set displayed an inhibitory effect on TriDAP-induced NF-κB activation . Of those , 66 genes were specifically involved in NOD1 signaling in HEK293T cells , i . e . they did not significantly affect TNF-mediated NF-κB activation ( Figure 1B , Table S1 ) . Among them , 28 known regulators of NF-κB , partly with known specificity for NOD1 signaling , could be retrieved , confirming the validity of the screening results ( Table S1 ) . Gene ontology ( GO ) enrichment analysis revealed that GO terms linked to immune function , and in particular to NLR function , were significantly overrepresented among the preliminary hits ( Figure S2B ) . In-depth analysis using Ingenuity pathway analysis highlighted that 56 of the 435 preliminary screen hits ( 12 . 9% ) are known components of NF-κB signaling ( Figure S2C ) . Among these 56 preliminary hits , 28 could be validated in the HEK293T validation screen , of which 14 were not influencing TNF-α-induced NF-κB activation . In order to further minimize false positive hits due to off-target effects of the used siRNAs and also to exclude a cell type specific bias , the 435 preliminary candidates were further tested for their effect on endogenous NOD1-mediated NF-κB activation in human myeloid THP1 cells ( THP1-blue reporter line ) ( Figure S2D ) , revealing a cluster of genes showing functional interactions as revealed by STRING analysis ( Figure S2E ) . The results confirmed 28 genes that showed an effect on NOD1-mediated NF-κB activation in both HEK293T and THP1 cells . Among those , receptor-interacting serine/threonine-protein kinase 2 ( RIPK2 ) , NOD1 , transcription factor p65 ( RELA ) , X-linked inhibitor of apoptosis protein ( XIAP ) , deltex 4 ( DTX4 ) , calreticulin ( CALR ) , olfactory receptor family 12 , subfamily D , member 2 ( OR12D2 ) , and ring finger protein 31 ( RNF31 ) were the strongest candidates ( >3 S . D . ) . Exclusion of the genes that affected TNF-induced NF-κB activation in HEK293T cells resulted in a short list of 18 genes ( Figure 1C , Table S1 ) . Although this candidate-list obtained in THP1 cells differed from that derived from HEK293T cells , the genes RIPK2 , XIAP , the uracil nucleotide/cysteinyl leukotriene receptor ( GPR17 ) , SSH1 , the snail family zinc finger 1 ( SNAI1 ) , and CHUK ( IKKα ) were confirmed as hits in both cell lines by this highly stringent procedure ( Figure 1C , Table S1 ) . Identification of RIPK2 , XIAP and the inhibitor of nuclear factor kappa-B kinase subunit alpha ( IKKα ) , all of which have recently been linked to the NOD1 pathway [7] , [18] , [19] validated the success of the screening procedure . To demonstrate that we can reversely reproduce the findings from the screen , XIAP was silenced with a screen-independent siRNA . This strongly impaired NF-κB activation upon both NOD1 or NOD2 stimulation in HEK293T cells ( Figure S3A and B ) and THP1-blue cells ( Figure S3C ) . Furthermore , TriDAP- or MDP-induced IL-8 secretion in THP1 cells was significantly reduced ( Figure S3D ) . Taken together , our screen validated XIAP as an essential component of the NOD1 signaling pathway , in line with previous reports showing an involvement of XIAP in NOD1 and NOD2 signaling [7] , [18] . XIAP was shown to mediate linear ubiquitylation of RIP2 [18] mediated by the so-called LUBAC complex . Of note , our screen also highlighted one component of the LUBAC complex , RNF31 ( HOIP ) as a strong candidate ( Table S1 ) , which was independently identified in a recent screen for components of the NOD2 signaling pathway [20] . Notably , we identified three novel genes , namely the uracil nucleotide/cysteinyl leukotriene receptor GPR17 , the cofilin phosphatase SSH1 and the transcriptional repressor SNAI1 that hitherto had not been reported in the context of NOD1 signaling . Among these stringently validated hits , the phosphatase SSH1 ( Table S1 ) , a key regulator of actin dynamics ( reviewed in [21] ) caught our attention . In order to validate SSH1 as a critical component of NOD1 signaling , we depleted the protein by two different siRNAs in myeloid-like differentiated THP1-blue cells and measured NF-κB activity and IL-8 release upon treatment with the NOD1 , NOD2 , TLR4 , and TNFR agonists TriDAP , MDP , LPS , and TNF , respectively ( Figure 2A and B ) . This revealed a significant reduction of NOD1- and NOD2-mediated inflammatory responses ( Figure 2A and B ) concurrent with a reduction in SSH1 levels by siRNA treatment ( Figure 2C ) . In contrast , TNF- and TLR4-induced responses were not highly significantly affected by reduced SSH1 levels ( Figure 2A and B ) . Similar results were obtained in THP1 cells not containing the reporter construct , showing that NOD1-mediated release of several key inflammatory cytokines was reduced upon SSH1 depletion ( Figure S4 ) . Immunoblotting showed that both siRNAs decreased the expression of SSH1 and revealed that SSH1 protein levels were increased upon PAMP stimulation ( Figure 2C ) . To evaluate the effect of SSH1 knock-down at early time points after activation , we measured IL-8 and SSH1 mRNA levels 3 h after TriDAP or TNF stimulation in THP1-blue cells . This showed that the reduction in SSH1 correlated with reduced IL-8 mRNA levels when cells were activated by TriDAP but not when stimulated with TNF ( Figure 2D ) . To elucidate the effect of SSH1 on physiological activation of NOD1 by bacteria , we infected HeLa cells with the Gram-negative invasive bacterial pathogen Shigella flexneri , which is sensed primarily by NOD1 in these cells . Depletion of SSH1 mRNA by the two SSH1-specific siRNA duplexes resulted in significantly impaired IL-8 and IL-6 production 6 h post infection with the invasive S . flexneri strain M90T ( Figure 3A ) . Notably , this was not due to reduced bacterial invasion and replication , as demonstrated by gentamicin protection assays ( Figure 3B ) . To decipher if SSH1 is involved preferentially in early or late events during the inflammatory response to S . flexneri , we measured IL-8 mRNA and IL-8 release at different time points after bacterial infection . Depletion of SSH1 ( Figure S5A ) led to greatly reduced IL-8 transcription as early as 30 min after infection ( Figure 3C ) . Two hours post infection , when IL-8 became measurable in the supernatant of infected cells , a significant difference in IL-8 secretion was observed between cells treated with SSH1 targeting siRNA and those treated with a non-targeting control siRNA ( Figure 3C ) . This suggests that SSH1 is already involved at early times of NOD1 activation . As expected , the knock-down of SSH1 led to a strong increase in phosphorylation of its substrate cofilin at serine 3 ( Figure S5B ) , proving that SSH1 is active in our cellular system . To rule out that the effects described above were related to the malignant origin of the cell lines , we assessed the phenotype of SSH1 depletion in primary human dermal fibroblasts . In line with the results obtained with cell lines , in primary human dermal fibroblasts NOD1-mediated IL-8 secretion was also significantly reduced upon SSH1 knock-down , whereas SSH1 depletion affected TNF-induced IL-8 secretion to a lesser extent ( Figure S5C ) . Taken together , our data identified SSH1 as an essential component of NOD1-mediated activation of pro-inflammatory responses in human myeloid and epithelial cells . SSH1 was reported to bind F-actin and to co-localize with actin stress fibres [22] , [23] . We confirmed that ectopically expressed SSH1 partly co-localized with F-actin in HeLa cells that stably express YFP-NOD1 . Although the two proteins showed slightly different localization patterns , a partial co-localization of SSH1 and NOD1 was also observed in confocal imaging ( Figure S6A ) . In co-immunoprecipitation experiments of transiently expressed SSH1 and NOD1/2 proteins , both NOD1 and NOD2 co-precipitated with SSH1 ( Figure 4A ) , validating that both NLR proteins are able to form a complex with SSH1 . Upon activation of NOD1 by TriDAP we observed a change in the stoichiometry of this complex with an increase in affinity about 30 min after TriDAP stimulation and reduced binding at later time points ( Figure 4B ) . To analyse this protein-protein interaction in more detail we employed in situ proximity ligation assays ( PLA ) . We found that GFP-SSH1 and Flag-NOD1 associated predominantly at F-actin positive structures ( Figure 4C ) . Quantitative analysis using high throughput microscopy revealed that the area covered by PLA spots was approximately 4-fold higher in cells expressing GFP-SSH1 and Flag-NOD1 than in neighbouring GFP-negative cells , confirming the specificity of the signal ( Figures 4C and S6B ) . Moreover , the phosphatase-dead mutant C393S of SSH1 gave similar results in the PLA assays as WT SSH1 ( Figure S6C ) showing that association of SSH1 and NOD1 was not dependent on the phosphatase activity of SSH1 . Accordingly , SSH1 was not involved in membrane targeting of NOD1 and NOD2 in HeLa cells , as the sub-cellular localization of transiently transfected NOD1 and NOD2 were not markedly changed in cells with highly reduced SSH1 expression compared to controls ( Figure S7A and S7B ) . It was reported that in epithelial cells SSH1 is enriched at the entry foci of Salmonella [24] . Likewise , NOD1 is enriched at entry sites of S . flexneri [9] . We thus analyzed the localization of SSH1 in S . flexneri-infected cells , revealing an enrichment of SSH1 at the bacterial entry foci ( Figure 4D ) . We previously reported that depolymerization of F-actin by the mycotoxin cytochalasin D enhances NOD1-mediated NF-κB activation [9] . Based on our results , we hypothesized that the impact of SSH1 on NOD1 signaling might be mediated by cofilin-controlled actin remodeling and that the formation of a SSH1-NOD1/2 complex might control the local NOD1/2 activity at sites of bacterial entry . To address this , we monitored SSH1 activity indirectly by measuring phosphorylation of its substrate cofilin at serine 3 ( p-cofilin ) after TriDAP-induced activation of NOD1 . TriDAP treatment of HEK293T cells expressing low levels of NOD1 strongly induced IL-8 release from these cells ( Figure 4E ) . Interestingly , basal p-cofilin levels decreased at the time when IL-8 transcription was highest ( about 180 min post TriDAP treatment ) ( Figure 4E ) . After longer periods of incubation ( 16 h ) , p-cofilin levels increased above the level seen in untreated cells ( Figure 4E ) . The slower kinetics in these experiments compared to S . flexneri infection in HeLa cells ( Figure 3 ) is likely due to the different kinetics of TriDAP uptake in HEK293T cells [5] . Notably , no obvious change in p-cofilin levels was observed after stimulation of HEK293T cells with TNF , although TNF induced high IL-8 release ( Figure 4F and S6D ) . Moreover , in cells in which NOD1 was depleted by siRNA TriDAP treatment did not robustly influence p-cofilin levels over time ( Figure 4F ) . Accordingly , TriDAP failed to induce IL-8 secretion form these cells ( Figure S6D ) . Moreover , expression of SSH1 did not result in increased basal NF-κB activity ( Figure S8B ) . Collectively , these data provide evidence that NOD1 signaling relies on the presence of SSH1 that acts downstream of NOD1 and involves the activation of cofilin . We next asked if other components of the cofilin regulatory network also contributed to NOD1 signaling outcome . Using siRNA-mediated knock-down we confirmed that reduction of cofilin resulted in a similar perturbation of NOD1 signaling as SSH1 knock-down ( Figure 5A ) . Cofilin is regulated primarily by phosphorylation through the kinases LIMK1/2 , which is counteracted by the phosphatase activity of SSH1 . Both SSH1 and LIMK1/2 are themselves regulated by phosphorylation events mediated by protein kinase D ( PKD ) , ROCK1/2 and PAK1/4 , respectively ( reviewed in [25] ) . Expression of a dominant negative form of ROCK1 ( KD-IA , which lacks kinase and Rho binding activity ) enhanced , albeit not significantly , NOD1-mediated responses in a dose-dependent manner , whereas a constitutively active mutant of ROCK1 ( delta1 ) significantly inhibited signaling by NOD1 ( Figure 5B ) . To further substantiate this , we tested the effect of two potent chemical inhibitors of ROCK - Y-27632 and Glycyl-H1152 - on NOD1-mediated signaling . In HEK293T cells , both inhibitors enhanced TriDAP-induced NOD1-mediated NF-κB activation in a dose dependent manner , this enhancement was significant in the case of Glycyl-H1152 ( Figure 5C ) . By contrast , both compounds led to a significant reduction of TNF-induced NF-κB responses ( Figure S8A ) . Chemical inhibition of ROCK also led to higher NOD1-mediated pro-inflammatory responses in TriDAP stimulated HeLa and THP1 cells ( Figures 5D and E ) . ROCK inhibition correlated in a dose dependent manner with reduced levels of p-cofilin , suggesting that increased cofilin activity causes this effect on NOD1 signaling . As shown before , stimulation of cells with TriDAP further enhanced dephosphorylation of cofilin ( Figures 5D and E ) . To provide direct evidence that the phosphatase activity of SSH1 is responsible for modulation of NOD1 activity , we overexpressed the phosphatase-dead mutant C535S of SSH1 in HEK293T cells . In line with our hypothesis , this did not affect NOD1-mediated signaling ( Figure S8C ) . These results show that perturbation of the cofilin pathway at different levels affected NOD1 signaling , suggesting that NOD1 signaling relies on cofilin-mediated changes in actin remodeling . Accordingly , NOD1 signaling induced by actin polymerization-perturbing mycotoxins should be SSH1 independent . As reported for HEK293T cells [9] , we found that depolymerization of F-actin using cytochalasin D strongly enhanced NOD1-mediated signaling in THP1 cells ( Figure 6A ) . In line with previous reports , cytochalasin D enhanced IL-8 release induced by other PAMPs about 2-fold [26] , [27] . However , in the case of NOD1 activation by TriDAP , a significantly higher increase to ∼3-fold was observed ( Figure 6B ) . Notably , this was not the case upon activation of NOD2 by MDP . Next , we depleted SSH1 expression in THP1-blue cells and subsequently disturbed actin polymerization by cytochalasin D treatment . Knockdown of SSH1 significantly reduced NOD1-mediated NF-κB activity in cells treated with TriDAP , however , treatment with cytochalasin D rescued the effect of SSH1 depletion on TriDAP-induced NOD1 activation ( Figure 6C ) . This strongly suggests that F-actin affects NOD1 signaling downstream of SSH1 . Taken together , our data support that NOD1 activation and induction of pro-inflammatory responses requires actin remodeling controlled by the SSH1 and cofilin network .
Using an unbiased high-throughput siRNA screen , we identified novel factors involved in the regulation of the NOD1 signaling cascade . The validity and quality of our screening approach is highlighted by the fact that the screen identified many factors involved in canonical NF-κB and/or NOD1 signaling . Most prominently , the primary screen validated the proteins RIPK2 ( reviewed in [2] ) , IKKα [19] , IKKβ ( reviewed in [2] ) , TAB2 [28] , [29] , RNF31 [30] , p50 and RELA [31] as essential positive regulators of NOD1 signaling . Beside RIP2 , XIAP ranked the highest throughout the whole screening procedure among the NOD1 specific hits . In line with a recent publication , we observed blunted responses of XIAP depleted cells to stimulation with NOD1 and NOD2 elicitors [7] . A recent study now provides the framework for the function of XIAP in this process , by showing that it acts as a ubiquitin ligase for RIP2 , catalyzing linear ubiquitylation events , at least in NOD2 signaling [18] . By using S . flexneri as an infection model we could recently demonstrate the physiologic relevance of these findings in vitro and in vivo , underscoring the impact of XIAP on anti-bacterial immunity [32] . With high confidence the screen identified a central regulator of actin cytoskeletal dynamics , the phosphatase SSH1 , as novel component of the NOD1 signaling cascade . Notably , SSH1 was recently also identified as a potential hit in two independent siRNA screening efforts searching for NOD1 and NOD2 signaling components , although it was not validated in neither of these studies [20] , [33] . SSH1's best described function is the dephosphorylation and subsequent activation of the actin depolymerization factor cofilin . Its activity is known to be counter-acted by LIMK1 and LIMK2 , which phosphorylate and thus inactivate cofilin on serine 3 ( reviewed in [21] ) . Using a highly stringent and unbiased multilayer screening approach offers high confidence in the obtained data . However , candidates can be overlooked due to loss because of mismatch of quality criteria . This likely explains why cofilin , ROCK1 , ROCK2 and others , although being represented in the screened library , were not identified as validated hits . We confirmed the function of SSH1 in NOD1 signaling by independent siRNA knock-down experiments in different human cell lines and primary human dermal fibroblasts . This validated that silencing of SSH1 significantly impaired NOD1-mediated responses in human cells triggered by TriDAP and infection with the invasive bacterial pathogen S . flexneri . Consistent with the screen data , SSH1 knock-down affected TNF and LPS-induced NF-κB activation to a far lesser extent than NOD1- and NOD2-mediated responses , showing that SSH1 contributes to NOD1 and NOD2 signaling in a rather specific manner . SSH1 thus contributed to NOD1 signaling at early times . Taken together , our results suggest that SSH1 affects NOD1 signaling through its phosphatase activity . This is best evidenced by the observation that NOD1-induced activation of IL-8 transcription was accompanied by a reduction of cofilin phosphorylation and the lack of effect of a phosphatase-dead mutant of SSH1 on NOD1 signaling . Our data do not allow drawing conclusions on how SSH1 activity is triggered in this process . However , the observed complex formation of SSH1 and NOD1 , that exhibited changed stochiometry upon triggering of NOD1 by its elicitor TriDAP , makes it tempting to speculate that binding of NOD1 to a SSH1-containing complex initiates local SSH1 activation . Noteworthy , we observed that treatment with several PAMPs resulted in enhanced SSH1 proteins levels in THP1 cells . A plausible interpretation of this finding might be that higher SSH1 levels might render host cells more prone for enhanced and more rapid NOD1-mediated immune signaling . Further research will help to address this and to establish the biological significance of this finding . Invasive bacteria , such as Shigella and Salmonella , depend on a tightly controlled spatial and local reorganization of F-actin at the plasma membrane to gain entry into the host cell . NOD1 is well-recognized as an important sensor of bacterial invasion and we showed earlier that it co-localizes with F-actin at the cell membrane and that depolymerization of F-actin by cytochalasin D augments NOD1 signaling in epithelial cells [9] . In the cell , actin dynamics are controlled by a balance between the activities of the small GTPases RhoA and Rac1 and it has been reported that changing their activity affects NOD1 and NOD2 signaling [12] , [13] , [34] . The pathogenic bacterium Klebsiella pneumonia seems to inhibit Rac1 activity to trigger NOD1 signaling , resulting in a dampened innate immunity response [34] . Additionally , the Rho activator guanine nucleotide exchange factor H1 ( GEF-H1 ) was identified as an essential component of NOD1-mediated signaling in response to Shigella and muropeptides [11] . In all these studies , the mechanistic link to the modulation of NOD1 signaling , however , was not conclusively identified . Our results show that NOD1 signaling competence relies on actin remodeling via cofilin . Activation of NOD1 by chemical ligands reduced cellular p-cofilin at the time when pro-inflammatory signaling was induced . Because SSH1 and NOD1 directly interact at the plasma membrane , SSH1 might act as a local platform to recruit NOD1 to the entry site of pathogens . The fact that cofilin activity is also modulated by RhoA and Rac1 activity [25] strongly suggests that SSH1 and cofilin are key effectors that link NOD1 activation to perturbations in the network of actin regulation . In support of this notion , our data show that “sterile” interference with the cofilin pathway at several levels , as well as pharmacological disruption of the actin cytoskeleton , modulated NOD1 signaling outcome . For example , we observed enhancement of NOD1 signaling upon overexpression of a dominant negative protein of the RhoA effector kinase ROCK or pharmacological inhibition of ROCK kinases . We cannot formally exclude that the inhibitors affected other cellular targets . However , in conclusion all data strongly support that interfering with the F-actin network downstream of RhoA and upstream of cofilin profoundly alters NOD1 signaling . Finally , we observed that induction of NOD1-mediated responses by depolymerization of F-actin is independent of SSH1 . Taken together , these experiments showed that NOD1 signaling outcome correlated directly with cofilin activity . F-actin depolymerization by cytochalasin D in myeloid cells was shown to affect NF-κB signaling in a broader manner , as confirmed by our results [26] , [27] . It should be noted , that a comparative analysis including multiple PRRs was not conducted in these studies . We observed a much higher synergy on the NOD1-induced NF-κB activation , indicating that NOD1 signaling is particularly prone to changes in actin dynamics . Surprisingly , also NOD2-induced IL-8 responses were less strongly enhanced by cytochalasin D in myeloid cells compared to NOD1 , although SSH1 interacted with NOD2 and knock-down of SSH1 also affected NOD2-mediated signaling . Further research is needed to define the surprising differences in the contribution of the actin cytoskeleton and SSH1 to NOD1 versus NOD2 signaling . Regulation of PRR signaling by actin is not without precedence , as a role for Rac1 in regulation TLR2 function has been shown before [35] . Furthermore , there are interesting parallels in the regulation of mammalian and plant NLRs , suggesting that effector triggered immunity ( ETI ) in plants brought about by activation of plant NLR proteins , is also intimately linked to actin dynamics . In Arabidopsis there is genetic evidence that the actin remodeling protein ADF-4 negatively affects RPS4-mediated ETI responses , although the authors do not disclose if this is linked to changed actin dynamics [36] . Very recently it has been proposed that NOD1 acts as a sensor of Rac1 and CDC42 activity induced by bacterial type III effector proteins , such as the Salmonella virulence factor SopE [10] . It is , however , still elusive how this is mechanistically linked to changes in NOD1 activity . In any case , bacterial- induced perturbation of actin dynamics that are needed for bacterial cell entry , in particular in epithelial cells , would result in enhanced NOD1-mediated inflammatory responses . The data reported here provide novel insights into the underlying mechanisms showing that SSH1-mediated actin remodeling is a central component of NOD1 activation and innate immune responses .
HEK293T , HeLa , THP1 and THP1-blue ( InvivoGen , France ) cells were cultured as described in in [37] . For immunofluorescence , a HeLa line stably expressing EGFP-tagged NOD1 was generated . All cell lines were continuously tested for absence of mycoplasma contamination by PCR . Primary human dermal fibroblasts were obtained as previously described [38] . Plasmids encoding myc tagged human NOD1 and NOD1 were generated by PCR cloning in a pCDNA3 . 1 backbone . SSH1 encoding plasmids are described in [39] . Plasmids encoding ROCK and mutants are described in [40] and RhoA and Rac1 plasmids were a kind gift from Monilola Olayioye ( University of Stuttgart ) . ROCK inhibitors and cytochalasin D were purchased from Tocris . siRNA-based knock-down in HeLa and THP1 cells was performed as described previously in [37] . siRNAs used: SSH1_1 : SI00123585 , SSH1_3: SI00123599 ( Qiagen ) and AllStars negative control ( Qiagen ) . For the infection with S . flexneri , HeLa cells were seeded in 24-well plates . Infection was performed using the strain M90T afaE as described previously [41] . Gentamycin ( 100 µg/ml ) was added to the cells 30 min after addition of the bacteria . As control , a non-invasive derivative ( BS176 afaE ) was used . Uptake of S . flexneri was analyzed by lysis of infected cells in 0 . 5% SDS/H2O . Serial dilutions of cell lysates were plated onto trypticase soy broth bacto agar plates without antibiotics and incubated at 37°C for 24 h . Colonies were counted and the recovery was determined . Immunoprecipitations and immunoblots were conducted using 9E10-agarose ( Santa Cruz ) essentially as described previously [41] . Cells were transiently transfected with SSH1 constructs and NOD1 or NOD2 expression plasmids for 24 h . Antibodies used: mouse anti-Flag ( Sigma , M2 ) , mouse anti-myc ( Santa Cruz , 9E10 ) , HRP-conjugated goat anti-mouse IgG ( Bio-Rad ) and HRP-conjugated goat anti-rabbit IgG ( Bio-Rad ) , rabbit anti-SSH1 ( Abcam , 76943 ) , rabbit anti-cofilin P-S3 ( Cell Signaling , 3313 ) , rabbit anti-cofilin ( Cell Signaling , 5175 ) , rabbit beta-actin HRP-conjugated ( Santa Cruz , sc-47778 HRP ) , rabbit anti-alpha tubulin ( Sigma , T7816 ) , rabbit anti-GAPDH ( Santa Cruz , 25778 ) . Activation of inflammatory pathways was measured using a luciferase reporter assay described previously [16] . The means and standard deviations were calculated from triplicates . Total RNA was extracted from cells using the RNeasy kit ( Qiagen ) . One µg of RNA was reverse transcribed using the First-Strand cDNA synthesis kit ( Fermentas ) . For quantitative PCR analyses , 50 ng cDNA was analyzed in a total volume of 25 µl using the iQ SYBR Green Supermix ( Bio-Rad ) , according to the manufacturer's protocol . All quantitative PCR reactions were run on a Bio-Rad iQ5 cycler , and data were evaluated by the iQ5 system software ( version 2 . 0 ) using the ΔΔCT method . For quantification of SSH1 , the following primers were used ( 5′-3′ ) : CGTTGCGAAGACAGAATCAA and CTCCACAGTCGGAGAACCAT . Primer for IL-8 , NOD1 , NOD2 , and GAPDH are described in [37] . Cells were transfected using Lipofectamine 2000 ( Invitrogen ) . After 16–24 h incubation , cells were fixed and processed as described previously [37] . DNA was stained using DAPI . Images were acquired on an Olympus Fluoview 1000 confocal microscope and processed using ImageJ . The proximity ligation assay was performed with the Duolink system ( Olink bioscience ) . HeLa cells grown on collagen-coated coverslips were transfected and fixed 24 h post transfection in 4% paraformaldehyde for 15 min , washed , permeabilized with 0 . 1% Triton X-100 , and blocked with blocking buffer ( Olink bioscience ) for 30 min at 37°C . The cells were incubated with the primary antibodies ( rabbit GFP-specific antibody and mouse Flag-specific antibody ) diluted in blocking buffer for 2 h . As a negative control , GFP-SSH1 and Flag-NOD1 transfected cells , which were incubated in antibody diluent without primary antibodies , were used . Incubation with secondary antibodies and ligation and amplification were done as recommended by the manufacturer . Cells were stained with HCS Cellmask deep red ( Life Technologies ) and mounted in mounting medium ( Olink bioscience ) . PLA dots were acquired with a LSM710 confocal microscope ( Zeiss ) . F-Actin labeling ( Alexa633-coupled phalloidin , Life Technologies ) was performed after PLA staining . Quantifications of PLA dots were performed with HCS/HTS – based automated PLA spot detection . In brief , images were acquired on a WiSCAN Hermes system ( Idea Biomedical , Israel ) , equipped with a Olympus 20× 0 . 75 NA objective . The quantitative spot analysis was performed using the WiSOFT image analysis software ( Idea Biomedical , Israel ) . Cells were segmented via the HCS cell mask deep red staining . After segmentation , cells were classified into GFP-positive- and negative cells using a threshold in the green channel . Spots were identified in the red channel and the total area covered by all spots in one cell was calculated . Spots outside of the cell mask were not considered . Measurement of cytokines was performed using the appropriate ELISA kits ( Duoset , R&D ) according to the manufacturer's instructions . Multiplex cytokine analysis was performed by flow cytometry using the human inflammation 2plex kit ( eBioscience ) . Data were analyzed by two-sided Student-t test using Microsoft Excel 2007 and GraphPad Prism 5 . 04 . The siRNA screen was performed using the human druggable-genome siRNA library from Qiagen ( Hilden , Germany ) consisting of four individual siRNAs for each gene . HEK293T cells were transfected with siRNA ( 20 nM ) using HiPerFect ( Qiagen ) and treated with TriDAP ( 0 . 5 µM , InvivoGen , San Diego , CA , USA ) or TNF ( 5 ng/ml ) , respectively , in case of the counterscreen . For screening , cells with a passage number of 2 were used . The whole assay procedure was performed automatically using a Biomek FXP laboratory automation workstation ( Beckman Coulter ) in 384 well plates ( Corning ) . 4 µl of 200 nM siRNAs ( Qiagen ) were pre-spotted on 384 well plates to allow reverse transfection of cells . All plates contained non-targeting ( Allstars; Qiagen ) as well as p65 , NOD1 , and PLK siRNAs as internal controls . For transfection , 8 µl medium per well were mixed with 0 . 25 µl HiPerFect and added to the siRNAs . The mixtures were incubated at RT for 15 min before adding 1 , 000 HEK293T cells in 30 µl medium . After 48 h incubation the medium was changes and cells were transfected with the NF-κB-luciferase reporter system ( 11 . 6 ng β-gal plasmid , 7 . 03 µl NF-κB-luciferase plasmid , 0 . 135 ng NOD1-expression plasmid , 8 . 78 ng pcDNA-plasmid , and 0 . 0918 µl Fugene6 ( Roche ) ) . Subsequently , cells were stimulated with 0 . 5 µM TriDAP ( InvivoGen ) in a volume of 3 µl H2O . For the TNF-counterscreen , 5 ng/ml TNF were added instead . After stimulation , cells were incubated at 37°C and 5% CO2 for 16 h . For read-out , cells were lysed by adding 30 µl 2xlysis buffer ( 50 mM Tris pH 8 . 0 , 16 mM MgCl2 , 2% Triton , 30% Glycerol , H2O ) and subsequently mixed by pipetting . 35 µl of the lysate were then added to a white 384 well plate containing 35 µl reading-buffer ( 1× lysis buffer w/o Triton containing 0 . 77 µg/ml D-luciferin and 1 . 33 mM ATP ) . Subsequently , bioluminescence of the samples was measured with an Envision plate reader ( PerkinElmer ) . For β-gal read-out , 35 µl of ONPG-development buffer ( 4 mg/ml ONPG in 60 mM Na2HPO4 , 40 mM NaH2PO4 , 10 mM KCl , 1 mM MgSO4 , pH 7 . 0 ) were added to the remaining lysate . After 15 min incubation at 37°C and 5% CO2 , the absorbance of the samples at 405 nm was measured automatically with an Envision plate reader ( PerkinElmer ) . Each individual siRNA was tested in 4 four biological replicates . For screening , the siRNAs were pre-spotted on 384 well cell culture plates . All plates contained Allstars , p65 , NOD1 , and PLK siRNAs as internal controls . For transfection , 0 . 25 µl HiPerFect were added to the siRNAs . The mixtures were incubated at RT for 15 min , before THP1-blue cells and 0 . 1 µM PMA ( Sigma , Munich , Germany ) were added . The cells were incubated for 72 h , while the growth medium was exchanged twice a day . Subsequently , cells were stimulated with TriDAP ( 10 µg/ml , InvivoGen ) . The cells were incubated for 16 h before read-out . For SEAP-detection , 10 µl supernatant per well were transferred to a plate containing 50 µl QUANTI-Blue SEAP detection medium ( InvivoGen ) and incubated for 5 h . 10 µl XTT reagent were added to the remaining 10 µl and incubated at 37°C for 1 h . Absorption at 632 nm and 485 nm respectively were measured using a PerkinElmer EnVision plate reader . Data was processed using the CellHTS2 package [42] , Bioconductor/R , and Excel ( Microsoft ) . By dividing the luciferase signal ( relative light units; RLU ) by the β-gal signal ( ABS405 ) , normalized relative light units ( RLU/ABS405 = nRLU ) were achieved . To exclude experimental artifacts , all data from a given plate was excluded , if the average β-gal signal of the non-targeting controls ( ABS405 ) was >2 . 5 , <0 . 2 , or had a standard deviation of >50% . Next , all wells showing a β-gal signal of <40% of the non-coding controls , supposedly due to low plasmid transfection efficiency or siRNA toxicity , were excluded from further analysis . Subsequently the nRLU where normalized relative to the inhibitory effect of the p65-control-siRNAs compared to the non-targeting controls ( normalized percent inhibition; NPI ) and median z-scores of the 4 biological replicates were calculated ( centered to the median of non-targeting controls ) , using CellHTS2 . In the next step , the median z-scores of individual siRNAs were used to calculate a ranked gene list , using the redundant siRNA analysis algorithm; genes with less than two hit-siRNAs ( ‘OPI-hits’ ) were excluded ( RSA ) [17] . This list comprises genes leading to a decreased p65 activity , when knocked down ( termed “inhibiting hits” ) . For TNF-counter screening in HEK293T cells , as well as for hit validation in HEK293T and THP1 cells , the top 435 inhibiting hits were selected . For each of these genes , the two siRNAs showing the strongest effect in the screen were re-synthezised and assembled on 384-well plates ( ‘validation plates’ ) . To validate the results of the primary screen , the experiments were repeated as described above . Data analysis using CellHTS2 was done as described above; siRNAs were selected as ‘inhibiting Tri-DAP-hits’ , if their median Z-score exceeded the median of non-targeting controls by more than two standard deviations . To exclude unspecific hits , all siRNAs selected for validation were screened for their influence on TNF-induced p65 activation . Data analysis was done analogous to the Tri-DAP validation screen . ‘Inhibiting TNF-hits’ were excluded from further analysis . Data from the THP1-blue screen consists of two parameters ( QUANTI-Blue absorption at 632 nm for Tri-DAP response [QB] , and XTT absorption at 485 nm for cell viability [XTT] ) and was processed similar as described above: QB-signal of each well was normalized to cell viability ( XTT ) , yielding nQB ( normalized QUANTI-Blue absorption; QB/XTT = nQB ) . After quality control and outlier flagging , the three best experimental replicates were NPI-normalized to non-targeting and NOD1-control-siRNAs using CellHTS2 , and median Z-scores were used for hit identification . All genes with two siRNAs showing a decrease of >1 . 5-fold standard deviation compared to the non-targeting control were regarded as validated inhibiting hits . A subset of these with one siRNA showing a decrease of >3 . 0-time standard deviation were categorized as ‘strong inhibiting hits’ ( 8 genes ) . SSH1: Gene ID 54434; NOD1: Gene ID 10392; NOD2: Gene ID 64127; ROCK1: Gene ID 6093; ROCK2: Gene ID 9475 .
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NOD1 was one of the first NLR-family members shown to act as an important intracellular pattern-recognition molecule mediating antimicrobial activities in mammals . It has been demonstrated that perturbation of F-actin and RhoGTPase activity affects NOD1 and NOD2 signaling , however , the effectors of this process remained elusive . By using a multilayered high-throughput druggable genome wide siRNA screening approach to discover novel components specific for the NOD1 pathway , we identified the cofilin phosphatase SSH1 , which acts downstream of RhoA-ROCK , as key regulator of NOD1 signaling . We show that SSH1 forms a complex with NOD1 at F-actin rich sites in human cells and is needed for NOD1-mediated responses towards TriDAP exposure and Shigella flexneri infection . Functionally this is achieved by SSH1-mediated activation of cofilin . Our findings reveal a previously unrecognized role for SSH1 in NOD1 signaling and provide a plausible unifying mechanistic explanation of how perturbations of the actin cytoskeleton can induce NOD1-mediated inflammatory responses .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"bacterial",
"gastroenteritis",
"bacterial",
"diseases",
"developmental",
"biology",
"innate",
"immune",
"system",
"medicine",
"and",
"health",
"sciences",
"inflammation",
"infectious",
"diseases",
"cytokines",
"immunity",
"gastroenterology",
"and",
"hepatology",
"gastroenteritis",
"molecular",
"development",
"biology",
"and",
"life",
"sciences",
"immunology",
"shigellosis",
"immune",
"response",
"immune",
"system"
] |
2014
|
The Cofilin Phosphatase Slingshot Homolog 1 (SSH1) Links NOD1 Signaling to Actin Remodeling
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Plant parasitic nematodes ( PPNs ) seriously threaten global food security . Conventionally an integrated approach to PPN management has relied heavily on carbamate , organophosphate and fumigant nematicides which are now being withdrawn over environmental health and safety concerns . This progressive withdrawal has left a significant shortcoming in our ability to manage these economically important parasites , and highlights the need for novel and robust control methods . Nematodes can assimilate exogenous peptides through retrograde transport along the chemosensory amphid neurons . Peptides can accumulate within cells of the central nerve ring and can elicit physiological effects when released to interact with receptors on adjoining cells . We have profiled bioactive neuropeptides from the neuropeptide-like protein ( NLP ) family of PPNs as novel nematicides , and have identified numerous discrete NLPs that negatively impact chemosensation , host invasion and stylet thrusting of the root knot nematode Meloidogyne incognita and the potato cyst nematode Globodera pallida . Transgenic secretion of these peptides from the rhizobacterium , Bacillus subtilis , and the terrestrial microalgae Chlamydomonas reinhardtii reduce tomato infection levels by up to 90% when compared with controls . These data pave the way for the exploitation of nematode neuropeptides as a novel class of plant protective nematicide , using novel non-food transgenic delivery systems which could be deployed on farmer-preferred cultivars .
Plant parasitic nematodes ( PPNs ) are responsible for an estimated 12 . 3% reduction in crop yield each year , which equates to losses of around $US80 billion worldwide [1 , 2] . Traditionally PPNs have been controlled through the use of fumigant , carbamate and organophosphate nematicides which are being withdrawn over environmental health and safety concerns , through global and EU level directives [3] . The fumigant methyl bromide was used extensively to control PPN infestations for more than 60 years , however the identification of ozone-depleting characteristics was recognised within the Montreal Protocol which aimed to eliminate methyl bromide use by 2010 [4] . Likewise , dibromochloropropane ( DBCP ) , a highly lipophilic brominated organochlorine was first used as a nematicide in the mid 1950’s before animal safety tests in the 1960’s demonstrated endocrine disrupting , and carcinogenic properties , alongside an increased incidence of developmental defects following exposure . Later studies further demonstrated strong mutagenic properties , and workers at the Occidental Chemical plant in California , which produced DBCP , displayed significantly higher rates of spermatogenic abnormalities relative to the rest of the population [5] . The carbamate nematicide aldicarb also triggers toxicity in non-target organisms through disruption of cholinergic neurons . Initial withdrawal of use across the USA in 1990 was followed by re-introductions to counteract a serious shortfall in alternative control options in 1995; similar dispensations have been afforded to EC states . The extensive withdrawal of frontline nematicides has left a significant shortfall in our ability to control PPNs . Transgenic approaches could provide a cost-effective means of PPN control . Much effort has focused on the development of in planta RNA interference ( RNAi ) to silence PPN genes necessary for successful parasitism [6–9] . Whilst many such studies have shown promise , concerns surround the persistence of RNAi trigger-expressing traits . It remains to be established if DNA methylation and transcriptional silencing of double stranded ( ds ) RNA-expressing transgenes is an issue in plants other than Arabidopsis thaliana [10] . Efforts to inhibit PPN nutrient acquisition through transgenic expression of cystatins that inhibit intestinal protease activity have also proven an effective strategy [6] . The utility of peptide resistance traits has also been demonstrated [7] , resulting in field level resistance and high target specificity [8] . Indeed , stacking peptide and cystatin resistance traits has proven extremely effective in plantain , triggering a 99% reduction in PPN infection levels at harvest , with a corresponding 86% increase in plantain yield [9] . Peptides have traditionally been viewed as poor drug candidates due to issues surrounding cellular uptake and half-life . However it has long been known that nematodes display an unusual neuronal uptake mechanism which is exploited by amphid dye-filling methods [11] . The amphid neurons assimilate exogenous peptides which subsequently accumulate in cells of the central nerve ring [11] , where they can interact with available receptors . Neuropeptides are highly enriched and conserved amongst nematodes , coordinating crucial aspects of physiology and behaviour [12–21] . The model nematode Caenorhabditis elegans encodes at least 113 neuropeptide genes , producing over 250 mature neuropeptides [16] . It is thought that this neurochemical diversity underpins the wide array of complex behaviours which are found within such neuroanatomically simple animals [16 , 22] . Many neuropeptides are known to be expressed within the anterior neurons of nematodes [16 , 22–24] , and it is likely that their cognate receptors are expressed in these or adjacent cells . The retrograde transport of exogenous peptides suggest that these receptors could be amenable to activation through signalling molecules following their uptake from the external environment . Conceptually , the mining of native neuropeptide complements for novel nematicides is an attractive prospect , based on the a priori assumption of bioactivity . An additional positive quality of neuropeptides is their characteristically high potency when acting on cognate receptors [13 , 25–30] . Furthermore , the high degree of phylogenetic sequence conservation suggests that neuropeptides could represent broad-spectrum nematicides as they share significant sequence similarity within and between parasite species [17 , 22 , 31 , 32] . Disrupting PPN behaviour through the dysregulation of native neuropeptide signalling could hinder the development of resistance traits anchored on target receptor mutation . Selective pressure drives the propagation of drug target variants which escape agonism / antagonism , or the development of enhanced efflux mechanisms [33 , 34] . Conceptually , the development of resistance to neuropeptides which coordinate crucial aspects of PPN biology would seem less likely . Nematode neuropeptide complements are organised into three broad groupings: i ) the FMRF-amide Like Peptides ( FLPs ) ; the INSulin like peptides ( INSs ) ; and iii ) the Neuropeptide-Like Proteins ( NLPs ) . FLPs represent the most widely studied and best understood family , characterised by a C-terminal RFamide motif , and are known to coordinate motor and sensory function [14 , 16 , 22] . In particular , C-terminal amidation is necessary for biological function , and so precludes FLPs from most transgenic delivery methods . INSs coordinate and integrate sensory signals with developmental circuits [35] and they share characteristic domain organisation and tertiary structure with vertebrate insulin peptides [16 , 36–40] . Specific proteolytic processing requirements suggest that INSs do not represent ideal candidates for transgenic delivery methods . The NLPs represent the least studied grouping of neuropeptides , comprising every neuropeptide that does not conform to the biosynthetic and structural characteristics of FLPs or INSs and encompassing multiple peptide families . Little is known about their function in nematodes , however many NLPs are expressed in anterior neurons and do not appear to require post-translational modifications [20 , 24 , 40–45] , making them more amenable to generation and delivery by transgenic systems than FLPs or INSs . A key gap in assessing the potential of unamidated NLPs as nematicides is the lack of data on their bioactivity in PPNs . Here we aimed to characterise the NLP complements in silico for two economically important PPNs that display different modes of infection and parasitism , M . incognita and G . pallida . Subsequently we aimed to screen NLPs for their ability to dysregulate the normal behaviour of infective stage juveniles ( J2s ) when applied exogenously and , simultaneously , to develop and assess novel transgenic delivery methods as next generation plant protection platforms .
Pro-peptide sequences of C . elegans NLPs predicted to be unamidated ( no C-terminal glycine; uNLPs ) were used as queries to conduct a BLASTp analysis of the predicted protein complements of both M . incognita and G . pallida [46 , 47] . A total of four nlp genes encoding 25 predicted uNLPs were found within the G . pallida genome , and seven nlp genes encoding 28 predicted uNLPs within the M . incognita genome ( Table 1 ) . Predicted uNLPs were synthesised and screened against M . incognita and G . pallida J2s for plant protective qualities . Chemotaxis , host-invasion , and stylet thrusting behaviours were assayed following J2 exposure to 100 μM of each uNLP for 24 h . Eleven of 27 tested uNLPs were found to disrupt normal chemotaxis towards root exudate collected from tomato cv . Moneymaker ( Fig 1A ) . Of particular interest is our observation that six of eight predicted Mi-nlp-15 peptides inhibit chemosensation ( Mi-NLP-15a/d , b , c , e , f ) . Analysis of the sequence similarity between these peptides suggest that the amino terminal variation of Mi-NLP-15g and h are responsible for observed functional differences . Two predicted Mi-nlp-9 peptides also inhibit chemosensation ( Mi-NLP-9b , f ) , however no clear amino acid differences correlate with functionality across predicted nlp-9 peptides . Likewise , 13 uNLPs were found to disrupt M . incognita host invasion ( tomato cv . Moneymaker ) compared to controls ( Fig 1B ) . Multiple active uNLPs originated from single nlp genes , however no obvious amino acid conservation could predict bioactivity across Mi-nlp-8 , -9 , -18 or -15 peptides . In contrast , Mi-NLP14a and c share a common ALDMxEGDDFIGG motif . Three predicted uNLPs ( Mi-NLP-15b , 9f , and 18a ) inhibited both chemosensation and host invasion . Eleven uNLPs were also found to disrupt the rate of serotonergic-induced M . incognita stylet thrusting ( positively or negatively ) compared with controls ( Fig 1C ) . Multiple such uNLPs originated from Mi-nlp-15 and -18 , however no common amino acid motif could be found relative to the inactive predicted peptides from either gene . Mi-NLP-14a and c were observed to differentially stimulate the inhibition and excitation of stylet thrusting respectively . The amino acid sequences of both peptides suggest that this difference must be mediated by differences in the 5th amino acid position , and/or differences at the carboxyl terminus . Mi-NLP-15b was the only predicted peptide to differentially regulate chemosensation , host invasion and stylet thrusting behaviours of M . incognita J2s ( Refer to supplemental S1 Data ) . 12 of 25 tested uNLPs were found to disrupt chemotaxis of G . pallida J2s towards root exudate ( tomato cv . Moneymaker ) , originating from Gp-nlp14 , -15 and -21 ( Fig 2A ) . Bioactivity of predicted peptides from Gp-nlp-15 and -21 does not correlate with an obvious amino acid sequence or motif , however Gp-NLP-14a and e peptides share an amino terminal ALDIL motif . Five predicted Gp-NLP-21 neuropeptides were found to disrupt G . pallida host invasion ( tomato cv . Moneymaker ) relative to controls ( Fig 2B ) . No obvious amino acid sequence or motif was predictive for bioactivity relative to the other inactive Gp-nlp-21 peptides . Both Gp-NLP-21b and g were found to inhibit both chemosensation and host invasion of G . pallida J2s . Three uNLPs were also found to modulate serotonergic-induced stylet thrusting of G . pallida J2s relative to controls groups ( Fig 2C ) . Gp-NLP-21h and -21i do not share any obvious amino acid similarity that is predictive for bioactivity relative to other inactive Gp-nlp-21 peptides . Gp-NLP-21h , -21i and Gp-NLP-15c were found to inhibit chemosensation alongside modulating stylet thrusting rates ( Refer to supplemental S1 Data ) . The potency of Mi-NLP-15b-induced disruption of chemotaxis and host invasion was assessed by exposing M . incognita J2s to various concentrations of synthetic Mi-NLP-15b for 24 h . Normal chemotaxis of M . incognita towards root exudate was inhibited across a range of dilutions , indicating high potency ( Fig 3A ) . We found that M . incongita J2 invasion was also inhibited across a range of Mi-NLP-15b concentrations ( Fig 3B; refer to supplemental S1 Data ) . Innoculation of C . reinhardtii cultures secreting selected uNLPs into the tomato invasion assay arena inhibited M . incognita invasion relative to untransformed C . rehinhardtii: Mi- NLP-9f ( 10 . 32% +/-10 . 32 , p<0 . 0001 ) , Mi-NLP-15b ( 10 . 82% +/-6 . 574 , p<0 . 0001 ) ( Fig 4A ) . Likewise , innoculation of B . subtilis cultures secreting selected uNLPs , significantly inhibited M . incognita invasion: Mi-NLP-15b ( 26 . 63% +/-8 . 12 , p = 0 . 0003 ) , Mi-NLP-40 ( 23 . 72% +/-5 . 448 , p = 0 . 0002 ) ( Fig 4B ) . C . reinhardtii expressing Gp-NLP-15b also inhibited G . pallida invasion relative to controls ( 30 . 95% +/-9 . 021 , p = 0 . 0042 ) ( Fig 4C ) . Similarly , innoculation with B . subtilis secreting Gp-NLP-15b inhibited G . pallida invasion relative to control groups ( 51 . 98% +/-13 . 29 ) , p = 0 . 0203 ( Fig 4D ) . Secretion of a His-tagged NLP-15b peptide from B . subtilis was confirmed by ELISA , indicating active secretion of 193 . 8 ±81 . 3 ng/ml in LB broth culture ( refer to supplemental S2 Data ) . BLAST was used to identify NLP-15b homologues across available expressed sequence tags ( ESTs ) or genomes of PPNs and non-target nematode species . PPNs with diverse life history traits share high levels of NLP-15b sequence similarity , however sequence similarity is reduced in non-target nematode species ( Table 2 ) . Incubation of mixed-stage C . elegans in selected PPN uNLPs ( 100 μM , 24 h ) had no statistically significant impact on chemotaxis towards the attractants: sodium acetate , pyrazine , benzaldehyde or diacetyl , relative to controls ( Fig 5D ) . Exposure of S . carpocapsae infective juveniles ( IJs ) to selected PPN uNLPs also had no statistically significant impact on insect host-finding ( Fig 5E ) .
We have identified seven nlp genes that putatively encode 27 mature unamidated peptides in the root knot nematode , M . incognita ( Mi-nlp-2 , -8 , -9 , -14 , -15 , -18 , -40 ) . Likewise , four nlp genes predicted to encode 24 mature unamidated peptides were identified in the potato cyst nematode , G . pallida ( Gp-nlp-8 , -14 , -15 , -21 ) ( Table 1 ) . Several predicted unamidated NLPs share high levels of amino acid sequence similarity between M . incognita and G . pallida , with one predicted peptide , designated NLP-15b , perfectly conserved between the two . Indeed , NLP-15b is highly conserved at the sequence level across PPN species with diverse life history traits; less sequence similarity is observed between NLP-15b from PPNs and non-target species such as S . carpocapsae , C . elegans or P . pacificus for example ( see Table 2 ) . Selected M . incognita and G . pallida peptides had a negative impact on PPN chemosensation and host-finding behaviours , but not on chemosensory or host-finding behaviours of mixed stage C . elegans or S . carpocapsae infective juveniles ( Figs 1 , 2 and 5 ) . This may be due to NLP sequence dissimilarity , or to different peptide uptake efficiencies between species . The attractants used to assay C . elegans chemotaxis operate via distinct neuroanatomical and biochemical pathways; sodium acetate is detected by the ASE neurons , benzaldehyde by the AWC neurons and prazine and diacetyl are both detected by the AWA neuron . The ASE , AWC and AWA neurons mediate aspects of water soluble and volatile chemotaxis in C . elegans [48 , 49] . Off-target NLP impacts were also assessed as a factor of host-finding ability in S . carpocapsae which will involve numerous neuroanatomical and biochemical pathways . Whilst these data on C . elegans and S . carpocapsae are far from exhaustive , they suggest that neuropeptide treatments that produce strong disruptive effects on the behaviours of M . incognita and G . pallida may be specific to PPNs . PPNs use a hollow protrusible stylet in order to pierce plant cells on entry to the plant root , and to secrete various parasitism effectors related initially to cell wall degradation , and subsequently to the re-programming of plant cells into giant cell ( RKN ) or syncytial ( PCN ) feeding sites . Our data reveal that both agonistic and antagonistic disruption of stylet thrusting can reduce host invasion rates , however modulation of stylet thrusting does not always correlate with modified invasion behaviour under the conditions tested here . Mi-NLP-14c , Mi-NLP-18b , and -18d agonise serotonergic stylet thrusting , have no negative impact on J2 chemosensory ability , and yet also reduce host invasion rates . Mi-NLP-15f reduces stylet thrusting rate , but does not impact on host invasion , whereas Mi-NLP-14a reduces stylet thrusting rate and does inhibit host invasion . None of the three uNLPs that dysregulate stylet thrusting in G . pallida have an impact on host invasion rate . We hypothesise that enhanced stylet thrusting rate may be beneficial for initial invasion events , however it seems likely that coordinated stylet thrusting behaviour is more beneficial during feeding site development for example . Our data do not point to an obvious outcome in this regard , however we do find that dysregulation of behaviour tends to lower plant invasion levels of both M . incognita and G . pallida J2s . Whilst it is tempting to extrapolate something on native NLP functionality from these data , we do not know if the aberrant phenotypes observed are due to interactions between tested NLPs and their cognate receptors . However , we do observe that exogenous NLPs can interact with endogenous neurophysiological circuits , interfering with host-finding , invasion and serotonergic stylet-thrusting behaviours of both M . incognita and G . pallida juveniles ( Figs 1 and 2 ) . This supports our initial hypothesis that nematode neuropeptides represent a valuable repository of nematicide candidates , which may elicit broad-spectrum activities against PPN species , but not off-target nematode species . Serial dilution of Mi-NLP-15b inhibited M . incognita chemosensation at concentrations as low as 10 pM , demonstrating high uNLP potency , which is a known characteristic of interactions between nematode neuropeptides and their cognate receptors [13 , 25–30 , 50 , 51] ( Fig 3 ) . While the potency of this peptide would support the specificty of the associated phenotypic impact , we advise some caution when interpreting these data as indicative of NLP function within either M . incognita or G . pallida J2s due to the potential for peptide interaction with other , non-cognate receptors . In order to further assess the efficacy of exogenous NLPs as nematicides , we developed two transgenic synthesis and delivery systems which could be deployed in the field , potentially through seed treatments or soil amendments . Gram positive Bacillus spp . are a major component of rhizosphere microbial communities [52 , 53] , and are frequently categorised as Plant Growth Promoting Rhizobacteria ( PRPR ) [54 , 55]; B . subtilis has also been shown effective in controlling Meloidogyne species [56] . More generally , B . subtilis represents an important organism for many biotechnology applications , and is classified as GRAS ( generally regarded as safe ) by the FDA [57 , 58] . It is increasingly well served by the development of synthetic biology tools [59] , and can persist in soil for long periods through the production of spores [60] . We modified B . subtilis to secrete a number of PPN NLPs , and found that transformed B . subtilis cultures confer significant levels of protection on tomato cv . Moneymaker against both M . incognita and G . pallida infective juveniles ( Fig 4 ) . This proof of concept demonstration employed a commercial B . subtilis strain and signal peptide sequence . It has however been reported that signal peptide identity can have a significant influence on the level of protein / peptide secreted by B . subtilis [61 , 62] . Unfortunately , we were unable to raise a suitable antisera to NLP-15b over several commercial synthesis rounds , due to the lack of NLP-15b immunogenicity . This restricted our ability to confirm amphidial uptake of the uNLPs , and to quantify microbial secretion of the uNLPs . Whilst we aimed to deliver proof of principle for this approach using commercially available and independently validated microbial synthesis and secretion systems , we confirmed secretion of a His-tagged NLP-15b from B . subtilis by ELISA ( S2 Data ) . We anticipate that signal peptide optimisation efforts could increase secretion and correspondingly enhance plant protection levels . Likewise , assessing other rhizobacteria strains may enhance efficacy . The secretion of uNLP nematicides could also be more targeted if driven by a plant root exudate-responsive promoter [63 , 64 , 65 , 66] . We also utilised the soil-dwelling microalgae , C . reinhardtii as a novel synthesis and delivery platform . Like B . subtilis , C . reinhardtii benefits from an improving suite of synthetic biology tools [67] . C . reinhardtii cultures secreting selected PPN NLPs also provided significant levels of protection to tomato cv . Moneymaker when challenged by either M . incognita or G . pallida infective juveniles ( Fig 4 ) . The NLP screening approach employed here may underestimate the efficacy achievable through a continuous transgenic delivery ( Figs 1 and 2 ) . For example , exogenous NLP-15b exposure inhibits G . pallida chemotaxis , but does not inhibit host invasion ( Fig 2 ) . However , when NLP-15b is delivered continuously to G . pallida infective juveniles via microbial secretion , we observe a significant inhibition of tomato invasion relative to J2s exposed to unmodified B . subtilis ( Fig 4 ) . This discrepency may be due to the recovery of G . pallida infective juveniles over the 24 hour timecourse of the tomato invasion assay . We expect that this may result in some false negative determinations in our NLP pre-screening approach . Our data demonstrate that unamidated NLPs represent a new class of potent and specific plant protective nematicide that could be deployed as a transgenic trait in crop plants , or through soil microorganisms such as the B . subtilis and C . reinhardtii systems developed here . In particular , these non-crop delivery approaches could facilitate rapid deployment to many different crop plant species and cultivars . A key consideration in the development of PPN resistance traits must be the maintenance of genetic diversity across crop cultivars and isolates . This reduces the chance of widespread pathology from other pests as a result of genetic bottlenecks introduced by a single preferred transgenic cultivar .
The predicted NLP complement of C . elegans [16] was used in a simple BLASTp and tBLASTn analysis of available genomic / transcriptomic sequence data of G . pallida and M . incognita [46 , 47] . All returned hits were curated by eye , and NLPs identified as per McVeigh et al . [17] . M . incognita were maintained in tomato plants ( cv . Moneymaker ) under greenhouse conditions . 8 weeks post infection M . incognita eggs were harvested from the roots by washing away excess soil and by briefly treating cleaned roots in 5% sodium hypochlorite to soften the root tissue and release the eggs . Eggs were cleaned from debris by passage through nested sieves ( 180 micron , 150 micron and 38 micron ) and washed thoroughly with water . Eggs were separated from remaining soil / silt by centrifugation ( 2000 rcf for 2 minutes ) in 100% sucrose solution and collected in a thin layer of spring water ( autoclaved and adjusted to pH 7 ) . Eggs were treated in antibiotic / antimycotic solution ( Sigma ) overnight , placed in a nylon net with a 38 micron pore size , immersed in spring water and maintained in darkness at 23°C , until infective juveniles emerged . Freshly hatched juveniles were used for each assay . G . pallida were maintained in potato ( cv . Cara ) at the Agri-Food and Biosciences Institute ( AFBI ) , Belfast . Soil was collected surrounding potato roots , dried for one week and washed through sieves to collect cysts . Cysts were incubated in potato root diffusate in the dark at 17°C until infective juveniles emerged . Freshly hatched juveniles were used for each assay . Predicted uNLPs from both M . incognita and G . pallida were synthesised by EZBiolab and dissolved into pH adjusted ddH2O to make a 5 mM stock which was aliquoted and stored at -20°C . J2s of both M . incognita and G . pallida were incubated for 24 hours in 200 μl of each peptide in a 24 well plate ( SPL Lifesciences , South Korea ) at a defined concentration . A 60 mm Petri dish was divided into two segments , a positive and a negative side , with a 0 . 5 cm 'dead zone' either side of the centre point . The petri dish was filled with 15 ml of 0 . 25% w/v agar which was allowed to solidify . 3 ml of 0 . 25% w/v agar slurry in spring water ( pH 7 , agitated with a magnetic stirrer for several hours to give a smooth consistency ) was added to the petri dish and spread evenly over the surface . Root diffusate ( attractant ) and water only ( control ) 0 . 25% agar plugs were embedded in the agar slurry , either side of the assay arena . Root diffusate was collected from 10 tomato plants , aged 3–6 weeks in 1 litre pots , by pouring 500 ml of ddH20 through the soil three times . Diffusate from each plant was combined , filter sterilised and stored at 4°C for a maximum of 1 month . Root diffusate agar plugs were made by melting 1 . 25% agar in ddH20 , cooling to 50°C before mixing with 4 parts of root diffusate . The agar was then allowed to solidify at room temperature . 100 uNLP pre-treated M . incognita or G . pallida J2s were added by pipette to the centre of the plate . J2s which moved out of the 'dead zone' after 3 hours were counted and their location ( +/- ) scored . The distribution of J2s were used to create a chemotaxis index [68] for each plate , which formed one replicate , a total of 10 replicates where completed for each uNLP treatment . Tomato seeds were sterilised with 2 . 5% NaOCl for 15 minutes , washed 5 times in ddH20 and germinated on 0 . 5% Murashige and Skoog plates at 23°C . An agar slurry was prepared by autoclaving 0 . 55% ( w/v ) agar ( using autoclaved spring water adjusted to pH 7 ) which was mechanically agitated overnight until it had a smooth consistency . Invasion assays were performed by mixing 500 pre-treated M . incognita or G . pallida J2s with agar slurry and a single tomato seedling ( 2 days post germination ) in a 6 well plate . Assays were left at 23°C for 24 hours in the case of M . incognita and at 18°C for 24 hours in the case of G . pallida under a 16 hour light and 8 hour darkness cycle . Seedlings were stained using acid fuschin [69] and the number of nematodes within the roots counted . At least five seedlings were used for M . incognita infections assays , with at least 15 seedlings used for G . pallida infections assays ( due to increased variation ) . Stylet thrusting assays where performed by incubating 100 M . incognita or G . pallida J2s for 15 minute in 5 mM or 2 mM serotonin ( Sigma Aldrich , USA ) , respectively . J2s were placed on a glass slide and stylet thrusts were counted for randomly selected J2s , for 1 minute each . Counts for a given cohort of J2s were taken in a maximum interval of 15 minutes . Longer counting intervals , making for longer serotonin incubations , yielded inconsistent results . At least 30 J2s were counted for each neuropeptide treatment . B . subtilis were grown overnight in LB media containing ampicillin ( 100 μg/ml ) at 37°C with shaking , and harvested in the log phase of growth determined by measuring OD600nm . Five ml of culture at 0 . 5 OD was spun down and the pellet mixed with 3 ml of agar slurry and 500 J2s from either G . pallida or M . incognita . C . reinhardtii clones were grown at 23°C with shaking , cultures in the log phase were measured at OD750 and 5 ml of culture at 0 . 5 OD was pelleted by centrifugation . C . reinhardtii pellets were mixed with 3 ml of agar slurry and 500 J2s from either G . pallida or M . incognita . Plant invasion assays were performed as described above . C . elegans wild-type N2 Bristol strain were obtained from the C . elegans Genomics Center and maintained on a Escherichia coli ( strain OP50 ) lawn on nematode growth medium ( NGM ) agar plates ( 3 g/l NaCl , 17 g/l agar , 2 . 5 g/l peptone , 5 mg/l cholesterol , 25 mM KH2PO4 ( pH 6 . 0 ) , 1 mM CaCl2 , 1 mM MgSO4 ) at 20°C [70] . Chemotaxis assays were performed in a 9 cm diameter Petri dish on NGM agar which was split into a positive and negative side with a central ‘dead zone’ of 1 . 5 cm diameter . 100 mixed-staged C . elegans were washed three times in M9 buffer and soaked in 100 μM PPN uNLP , or M9 vehicle control for 24 hours . 2 μl of 50 mM sodium acetate , 0 . 5% pyrazine , 0 . 5% benzaldehyde or 0 . 5% diacetyl was spotted onto the positive side , 2 μl of ddH20 was spotted onto the negative side . Pyrazine , benzaldehyde and diacetyl volatile attractants were assayed immediately whereas the water soluble sodium acetate was assayed 18 hours following addition to the plate . Assays were maintained in the dark at 20°C , and counted after 1 hour . Eight replicates were conducted for each C . elegans attraction assay . S . carpocapsae were cultured in Galleria mellonella at 23°C . Infective juveniles ( IJs ) were collected using a White trap [71] in PBS . Freshly emerged IJs were used for each assay . 100 IJs were incubated for 24 hours in 100 μM of selected uNLPs , and host-finding assays ( n = 5 ) performed as in Morris et al . [45] . Codon optimised DNA sequences coding for the desired neuropeptide flanked by restriction sites necessary to clone into the C . reinhardtii expression vector pChlamy_3 ( Life Technologies , USA ) or the B . subtilis expression vector pBE-S ( Clontech , USA ) were synthesised by GeneArt Gene Synthesis ( Life Technologies , USA ) . uNLP secretion inserts , and vector pChlamy_3 were digested using KpnI/XbaI ( New England Biolabs , USA ) , ligated using T4 ligase ( New England Biolabs , USA ) , and cloned into Escherichia coli One Shot TOP10 chemically competent cells ( Life Technologies , USA ) following manufacturer’s instructions . Ampicillin ( Sigma Aldrich , USA ) was used to select E . coli containing the pChlamy_3 plasmid , which was subsequently extracted using the High Pure Plasmid Isolation Kit ( Roche ) and sequenced ( Eurofins Genomics , UK ) to identify correct clones . C . reinhardtii was transformed by electroporation following manufacturer’s instructions ( GeneArt Chlamydomonas Engineering Kit , Life Technologies ) and individual colonies grown on TAP-Agar-Hygromycin plates ( 10 μg/mL ) ( Sigma Aldrich , USA ) at 23°C . Colonies were picked and grown at 23°C in 100 ml TAP growth media ( Invitrogen , USA ) with constant orbital agitation . qRT-PCR was performed to identify clones with the highest level of uNLP expression , which were then selected for downstream assays ( pChlamy universal FWD: CACTTTCAGCGACAAACGAG , nlp-15b REV: CTACTAGTCGAGGCCGGTA; Mi-nlp-9f REV: GAACGGGCGGATGAAGTAG ) . uNLP secretion inserts , and vector pBE-S were digested using XbaI/MluI ( New England Biolabs , USA ) , ligated using T4 ligase ( New England Biolabs , USA ) , and cloned into E . coli One Shot TOP10 chemically competent cells ( Life Technologies , USA ) following manufacturer’s instructions . Ampicillin ( Sigma Aldrich , USA ) was used to select E . coli containing the pBE-S plasmids , which were subsequently extracted using the High Pure Plasmid Isolation Kit ( Roche ) and sequenced ( Eurofins Genomics , UK ) to identify correct clones . B . subtilis RIK1285 competent cells ( Takara , USA ) were transformed according to manufacturer’s instructions and grown overnight at 37°C on kanamycin selective plates ( 10 μg/mL ) ( Sigma Aldrich , USA ) . Individual colonies were picked and grown in LB broth overnight at 37°C . qRT-PCR ( pBE-S universal FWD: GGATCAGCTTGTTGTTTGCGT , nlp-15b REV: CCTGGCCCAGTGAAAGAGTC , Mi-nlp-40 REV: TACCGGCTGCCAAGATACCA ) was performed to confirm the expression of uNLP secretion cassettes . Codon optimised NLP-15b , tagged with six histidine residues and an upstream aprE signal peptide , were cloned into the pBE-S vector ( GeneArt , Life Technologies ) and transformed into B . subtilis following manufacturer’s instructions ( Takara Bio , Inc . ) . NLP-15b transformed B . subtilis were grown at 37°C in 50 ml of LB ( kanamycin 10 μg/ml ) and wild type B . subtilis in 50 ml of LB without selection . Once growth passed the exponential phase ( OD 660 ) one tablet of cOmplete Protease Inhibitor Cocktail ( Roche ) was added to 10 ml of bacterial suspension and allowed to dissolve . Bacteria were removed from the LB by centrifugation at 10 , 000g for 10 minutes . Supernatant was collected and peptides were isolated by a MWCO 3 kDa filter ( Amicon , Sigma ) . Histidine tagged peptide concentration assessed using the His Tag protein ELISA Kit ( Cell Biolabs , Inc . ) following manufacturer’s instructions . The ELISA results were measured ( OD 450 ) using the FLUOstar Omega microplate reader ( BMG Labtech ) . A line of best fit was plotted and the slope used to calculate the concentration of peptide across individual samples ( n = >11 ) . Data pertaining to behavioural and invasion assays were assessed by Brown-Forsythe and Bartlett’s tests to examine homogeneity of variance between groups . One-way ANOVA was followed by Fisher’s Least Significant Difference ( LSD ) test . All statistical tests were performed using GraphPad Prism 6 .
|
Plant parasitic nematodes ( PPN ) reduce crop plant yield globally , undermining food security . Many of the chemicals used to kill these parasites are non-specific and highly toxic , and are being phased out of general use through governmental and EU regulation . The withdrawal of these chemicals is beneficial to the environment , but limits our ability to protect crops from infection . Efforts must now focus on developing environmentally safe PPN controls . PPNs can absorb various molecules directly from the environment into their nervous system , including peptides and proteins . Here we profiled the feasibility of using PPN neuropeptides , small signalling molecules , to interfere with normal PPN behaviour . We exposed PPNs to a variety of neuropeptides , and found that they could interfere with behaviours that are important to host-finding and invasion . We then developed soil-dwelling microbes that could generate and secrete these neuropeptides into the soil where the PPN infective juveniles are found . These transgenic microbes can protect host plants from infection , and represent a completely new approach to controlling PPNs in crop plants . Importantly , these neuropeptides appear to have no impact on other beneficial nematodes found in the soil .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"methods"
] |
[
"biotechnology",
"invertebrates",
"cell",
"motility",
"medicine",
"and",
"health",
"sciences",
"neurochemistry",
"pathology",
"and",
"laboratory",
"medicine",
"caenorhabditis",
"pathogens",
"bacillus",
"microbiology",
"neuroscience",
"parasitic",
"diseases",
"animals",
"hormones",
"nematode",
"infections",
"animal",
"models",
"prokaryotic",
"models",
"plant",
"science",
"model",
"organisms",
"caenorhabditis",
"elegans",
"genetically",
"modified",
"plants",
"experimental",
"organism",
"systems",
"neuropeptides",
"plants",
"bacteria",
"bacterial",
"pathogens",
"genetic",
"engineering",
"research",
"and",
"analysis",
"methods",
"genetically",
"modified",
"organisms",
"neurochemicals",
"medical",
"microbiology",
"microbial",
"pathogens",
"tomatoes",
"algae",
"chemotaxis",
"peptide",
"hormones",
"fruits",
"biochemistry",
"plant",
"and",
"algal",
"models",
"cell",
"biology",
"bacillus",
"subtilis",
"nematoda",
"biology",
"and",
"life",
"sciences",
"plant",
"biotechnology",
"organisms",
"chlamydomonas",
"reinhardtii"
] |
2017
|
Nematode neuropeptides as transgenic nematicides
|
In this study , we have investigated the effects of manganese superoxide dismutase ( SOD2 or MnSOD ) deficiency on mitochondrial function and oxidative stress during Chagas disease . For this , C57BL/6 wild type ( WT ) and MnSOD+/- mice were infected with Trypanosoma cruzi ( Tc ) , and evaluated at 150 days’ post-infection that corresponded to chronic disease phase . Genetic deletion of SOD2 decreased the expression and activity of MnSOD , but it had no effect on the expression of other members of the SOD family . The myocardial expression and activity of MnSOD were significantly decreased in chronically infected WT mice , and it was further worsened in MnSOD+/- mice . Chronic T . cruzi infection led to a decline in mitochondrial complex I and complex II driven , ADP-coupled respiration and ATP synthesis in the myocardium of WT mice . The baseline oxidative phosphorylation ( OXPHOS ) capacity in MnSOD+/- mice was decreased , and it had an additive effect on mitochondrial dysregulation of ATP synthesis capacity in chagasic myocardium . Further , MnSOD deficiency exacerbated the mitochondrial rate of reactive oxygen species ( ROS ) production and myocardial oxidative stress ( H2O2 , protein carbonyls , malondialdehyde , and 4-hydroxynonenal ) in Chagas disease . Peripheral and myocardial parasite burden and inflammatory response ( myeloperoxidase , IL-6 , lactate dehydrogenase , inflammatory infiltrate ) were increased in all chagasic WT and MnSOD+/- mice . We conclude that MnSOD deficiency exacerbates the loss in mitochondrial function and OXPHOS capacity and enhances the myocardial oxidative damage in chagasic cardiomyopathy . Mitochondria targeted , small molecule mitigators of MnSOD deficiency will offer potential benefits in averting the mitochondrial dysfunction and chronic oxidative stress in Chagas disease .
Chagasic cardiomyopathy is caused by the protozoan Trypanosoma cruzi ( Tc or T . cruzi ) [1] . Infected individuals exhibit an acute phase of peak blood parasitemia that is resolved in 2-3-months . Approximately , 30–40% of infected individuals progress to present ventricular fibrillation , thromboembolism , and congestive heart failure [2 , 3] . During the fetal heart development , cardiomyocytes are dependent on glycolysis as a source of energy . In the mature heart , fatty acid oxidation coupled with oxidative metabolism in mitochondria provides >90% of the energy required for continual contraction to supply the body with blood [4] . The reduced substrates ( NADH , FADH2 ) deliver electrons from complex I ( CI ) and complex II ( CII ) of the electron transport chain through complex III ( CIII ) and complex IV ( CIV ) to oxygen , causing protons to be pumped across the mitochondrial inner membrane , and setting proton motive force that drives protons back through the ATP synthase ( complex V ) , forming ATP from ADP and phosphate [5] . During this process , electrons may leak from the respiratory chain and react with oxygen to form superoxide [6] . The Q1 semi-ubiquinone of complex III in the electron transport chain is believed to be the major site of superoxide production . Superoxide anions are charged molecules that directly or indirectly contribute to formation of other reactive oxygen species ( ROS ) , and can result in cellular oxidative damage . Superoxide dismutases ( SODs ) are metallo-enzymes that catalyze the conversion of superoxide anion ( O2•- ) to hydrogen peroxide ( H2O2 ) . In higher eukaryotes , SODs are expressed by different genes , and have historically been designated as copper- and zinc-containing , cytosolic , homo-dimer enzyme ( CuZnSOD or SOD1 ) , manganese-containing , mitochondrial , homo-tetramer enzyme ( MnSOD or SOD2 ) , and copper- and zinc-containing tetramer enzyme that is secreted to extracellular spaces ( ECSOD or SOD3 ) [7] . The SOD2 enzyme binds one manganese ion per subunit , and is the major mitochondrial antioxidant . We have previously documented an increase in mitochondrial reactive oxygen species ( mtROS ) in chagasic hearts [8 , 9] . In this study , we aimed to determine if MnSOD deficiency worsens the mitochondrial health during Trypanosoma cruzi infection and Chagas disease . For this , C57BL/6 WT and MnSOD+/- mice were infected with T . cruzi , and we examined the effect of MnSOD deficiency on mitochondrial function , and oxidative and inflammatory stress in chagasic heart . We discuss the benefits of mitochondria targeted , small molecule mitigators of MnSOD deficiency in offering potential therapy against mitochondrial dysfunction and chronic oxidative stress in Chagas disease .
All animal experiments were performed according to the National Institutes of Health Guide for Care and Use of Experimental Animals , and approved by the Institutional Animal Care and Use Committee ( IACUC ) at the University of Texas Medical Branch , Galveston ( protocol number: 0805029 ) . C57BL/6 wild-type ( WT ) mice were purchased from Harlan Laboratories ( Indianapolis , IN ) . MnSOD+/- mice ( C57BL/6 background ) were kindly provided by Dr . H . Van Rammen , and have been described previously [10 , 11] [12] . All mice were bred at the UTMB animal facility . T . cruzi trypomastigotes ( SylvioX10/4 ) were propagated by in vitro passage in C2C12 immortalized mouse myoblast cells . Mice ( 5-6-weeks-old , body weight: 18 . 23 ± 1 . 67 g ) were infected with T . cruzi ( 10 , 000 trypomastigotes/mouse , intraperitoneal ) , and sacrificed at 150 days’ post-infection ( pi ) corresponding to chronic disease phase [13] . Sera/plasma and tissue samples were stored at 4°C and -80°C , respectively . Protein levels in all samples were determined by using the Bradford Protein Assay ( Bio-Rad , Hercules CA ) . All chemicals were of molecular grade ( >99% pure ) and purchased from Sigma-Aldrich ( St . Louis , MO ) . Tail biopsies from young pups or heart tissue sections ( 10 mg ) from chronically infected WT and MnSOD+/- mice were subjected to Proteinase-K lysis and total DNA was extracted and purified by phenol/chloroform extraction/ethanol precipitation method [14] . Tail DNA samples were analyzed by traditional PCR for genotyping WT and MnSOD+/- mice [15] . To examine , blood and tissue parasite burden , total DNA ( 100 ng ) was used as template with Tc18SrDNA-specific primers . A real-time quantitative PCR reaction was performed for 35 cycles with SYBR Green Supermix ( Bio-Rad ) on an iCycler thermal cycler . Cycling parameters were as follows: Initial denaturation at 95°C for 5 min , denature at 95°C for 15 sec , anneal at 60°C for 30 sec , then denature-anneal cycling for 34 more times . Single product amplification was confirmed in the melt curve analysis . The threshold cycle ( CT ) values for target DNAs were normalized to the CT values for the GAPDH housekeeping gene sequence ( ΔCT ) , and relative parasite burden was calculated as 2-ΔCt ( ΔCt = CtTc18SrDNA—CtGAPDH ) [16] . All oligonucleotides are listed in S1 Table . Heart tissue sections ( 10 mg ) were homogenized in TRIzol reagent ( Invitrogen , Carlsbad , CA; weight/volume ratio , 1:10 ) . Total RNA was extracted , precipitated , and purified of contaminating DNA , and analyzed for quality ( OD260/280 ratio ≥ 2 . 0 ) and quantity ( OD260 of 1 = 40 μg/ml RNA ) . Purified RNA ( 2 μg ) was reverse transcribed by using an iScript kit ( Bio-Rad ) , and cDNA was used as template with gene-specific oligonucleotide pairs ( S1 Table ) in real-time , quantitative PCR reaction for 35 cycles , as described above . The Ct values for target mRNA were normalized to geometric mean of GAPDH mRNA , and fold change in gene expression was calculated as 2−ΔΔCt , where ΔCt represents the Ct ( sample ) —Ct ( control ) [17] . Tissue sections ( tissue: buffer ratio , 1:10 w/v ) were homogenized in RIPA buffer ( Cell Signaling , Danvers , MA , #9806 , ) , centrifuged at 10 , 000 g , and supernatants were used as tissue lysates . To isolate mitochondria , freshly harvested heart tissues were suspended in homogenization buffer ( 50 mM Tris-HCl , pH 7 . 4 , 5 mM MgCl2 , 1 mM DTT , 25 μg/ml spermine , 25 μg/ml spermidine , and protease inhibitor cocktail ) containing 250 mM sucrose; tissue: buffer ratio , 1:20 ) and homogenized at 4°C by using a dounce homogenizer . The homogenates were centrifuged at 800 g for 15 min at 4°C , and supernatants were then centrifuged at 6000 g for 15 min . The resultant pellets were stored as mitochondrial fractions [18] . Western blotting was performed to examine the nuclear ( Lamin B ) , and mitochondrial ( COIV subunit ) proteins in all samples . Mitochondrial fractions that exhibited > 6% of contaminants were re-centrifuged as described above to ensure purity [19] . Heart homogenates ( 30 μg protein ) were electrophoresed on a 4–15% Mini-Protein TGX gel , and proteins were wet-transferred to a PVDF membrane . Membranes were blocked with 5% non-fat dry milk ( NFDM ) in 50 mM Tris-HCl ( pH 7 . 5 ) / 150 mM NaCl ( TBS ) , washed with TBS-0 . 1% Tween 20 ( TBST ) and TBS , and incubated overnight at 4°C with antibodies ( 1: 1000 dilution ) against MnSOD ( Abcam , Cambridge , UK , Ab13533 ) or GAPDH ( Cell Signaling , clone 14C10 ) . Membranes were washed , incubated with HRP-conjugated secondary antibody ( 1:5000 dilution , Southern Biotech , Birmingham , AL ) , and Amersham ECL Plus system ( GE Healthcare , Pittsburgh , MA ) was used to develop the signal . An ImageQuant LAS4000 system ( GE Healthcare ) was used to visualize and digitize the images , and a Fluorchem HD2 Imaging System ( Alpha-Innotech , San Leandro , CA ) was used to perform densitometry analysis of the images [19] . MnSOD activity in tissue homogenates was measured by using a Superoxide Dismutase Assay kit ( Cayman Chemicals , Ann Arbor , MI , #706002 ) . One unit of SOD was defined as the amount of MnSOD needed to exhibit 50% neutralization of superoxide radical ( standard curve: 0 . 005–0 . 05 U/ml recombinant CuZnSOD ) . Mitochondrial respiration was measured by using a Mitocell S200A Respirometry System ( Strathkelvin , Motherwell , UK ) [20] . Briefly , freshly isolated mitochondria ( 200 μg ) were added to the mitocell in 0 . 5 ml of MSP buffer ( 225 mM mannitol , 75 mM sucrose , 20 mM KH2PO4/K2HPO4 pH 7 . 6 ) . After equilibration , electron flow was supported by 10 mM pyruvate / 10 mM glutamate / 2 . 5 mM malate ( P+G+M , complex I substrates ) , and CI-dependent state 4 respiration was recorded . Then 230 μM ADP was added , and ADP-coupled , CI-dependent state 3 respiration was recorded . Next , 6 . 25 μM rotenone was added to inhibit electron flow from complex I , mitochondria were energized with 10 mM succinate ( complex II substrate ) , and C-II-dependent state 3 respiration was recorded . Finally , 1 μM antimycin ( inhibits electron flow at complex III ) and CII-supported state 4 was recorded . A high respiratory control ratio ( RCR = state 3/state 4 ) suggests mitochondrial capacity for substrate oxidation and ATP turnover and a low proton leak . The ADP/O ratio ( mitochondrial ATP production capacity ) was calculated as decrease in O2 concentration during state 3 respiration per O atom consumed . To measure mitochondrial rate of ROS generation , isolated mitochondria ( 25-μg protein ) were added in triplicate to 96-well , black flat-bottomed plates in 100 μl of reaction buffer ( 10 mM Tris-HCl at pH 7 . 4 , 250 mM sucrose , 1 mM EDTA ) , and energized with complex I or complex II substrates , as above . Mitochondria were loaded with 30-μM dihydroethidium ( DHE ) , and formation of fluorescent ethidium by intra-mitochondrial ROS was recorded at Ex498nm/Em598nm , by using a SpectraMax M2 microplate reader ( Molecular Devices , San Jose , CA ) . As an alternate method , mitochondria were incubated with 33-μM amplex red and 0 . 1 U/ml of horseradish peroxidase ( HRP ) , and HRP-catalyzed , ROS-mediated oxidation of amplex red to fluorescent resorufin was recorded at Ex563nm/Em587nm . Standard curves were prepared with etihidium ( 1–15 μM ) and H2O2 ( 50 nM–5 μM ) . To measure the H2O2 levels , 50 μl of tissue lysates ( 100 μg ) were added in triplicate to flat-bottom ( dark-walled ) 96-well plates . Then 100 μl of reaction mixture containing 0 . 05 M sodium phosphate , pH 7 . 4 , 33 μM amplex Red , and 0 . 1 U/ml HRP was added . The plates were incubated for 30 min in dark , and ROS levels were recorded as above . Protein carbonyls in tissue homogenates were measured by a colorimetric protein carbonyl assay ( Cayman Chemicals , #10005020 ) . Malonyldialdehyde ( MDA ) levels were measured by a TBARS assay ( Cayman Chemicals , #10009055 ) . Concentration of lipid peroxides was calculated as an MDA equivalent using the extinction coefficient for the MDA–TBA complex of 1 . 56x105 M−1 cm−1 at 532 nm . To examine the 4-hydroxynonenal ( 4-HNE ) levels , tissue lysates were subjected to Western blotting with anti-4-HNE antibody ( Abcam , ab46545 , 1:1000 dilution ) . The interleukin 6 ( IL-6 ) cytokine levels in plasma samples were measured by using IL-6 sandwich ELISA kit ( BD Biosciences , San Jose , CA ) . The change in absorbance as a measure of cytokine concentration was monitored at 450 nm by using a SpectraMax M5 spectrophotometer ( Molecular Devices ) . A standard curve was prepared with 0–1 , 000 pg/ml of recombinant cytokine . To measure myeloperoxidase ( MPO ) levels , plasma samples ( 10 μg of protein ) were added in triplicate to 0 . 53-mmol/L o-dianisidine dihydrochloride and 0 . 15 mmol/L H2O2 in 50 mmol/L potassium phosphate buffer ( pH , 6 . 0 ) . Reaction was stopped after 5 minutes , and absorbance was measured at 460 nm on a SpectraMax 190 microplate reader . One unit of MPO was defined as that degrading 1 nmol H2O2/min ( ε = 11 300M−1 . cm−1 ) . Heart tissue sections were fixed in 10% buffered formalin , dehydrated in absolute ethanol , cleared in xylene , and embedded in paraffin . Five-micron tissue sections were subjected to staining with hematoxylin and eosin ( H&E ) o at the Research Histopathology Core at the UTMB , and evaluated by light microscopy using an Olympus BX-15 microscope ( Center Valley , PA ) equipped with a digital camera and Simple PCI software ( v . 6 . 0; Compix , Sewickley , PA ) . Myocarditis ( presence of inflammatory cells ) in H&E stained tissue sections was scored as 0 ( absent ) , 1 ( focal/mild , ≤1 foci ) , 2 ( moderate , ≥2 inflammatory foci ) , 3 ( extensive coalescing of inflammatory foci or disseminated inflammation ) , and 4 ( diffused inflammation , tissue necrosis , interstitial edema , and loss of integrity ) . Inflammatory infiltrates was characterized as diffused or focal depending upon how closely the inflammatory cells were associated [21] . The WT and MnSOD+/- mice were randomly assigned to Tc infection and no infection groups ( n = 5 mice per group per experiment ) . All experiments were conducted at least twice , and a minimum of duplicate observations were acquired for each sample . All data were analyzed by using a GraphPad Prism 5 software ( La Jolla , CA ) and expressed as mean ± standard error mean ( SEM ) . Statistical significance was calculated by the student’s t test ( for comparison of 2 groups ) and one-way analysis of variance ( ANOVA ) with Tukey's post hoc test ( for comparison of more than two groups ) . Significance is presented by a MnSOD+/- vs . WT , b WT . Tc vs . WT , c MnSOD+/- . Tc vs . MnSOD+/- , d MnSOD+/- . Tc vs . WT . Tc , and e MnSOD+/- . Tc vs . WT mice ( p value < 0 . 05 ) .
The MnSOD+/- and WT mice were genotyped to confirm the presence of one and two copies of the MnSOD gene , respectively ( Fig 1A ) . We then evaluated the effect of Tc infection on the expression levels of the mammalian superoxide dismutases , including copper- and zinc-containing , cytosolic , homodimer enzyme ( SOD1 or CuZnSOD ) , manganese-containing , mitochondrial , tetramer enzyme ( SOD2 or MnSOD ) , and copper- and zinc-containing tetramer enzyme that is secreted to extracellular spaces ( SOD3 or ECSOD ) in WT and MnSOD+/- mice . The myocardial levels of SOD1 and SOD3 mRNAs were not statistically different in WT and MnSOD+/- mice , and Tc infection had no effects on SOD1 and SOD3 expression in WT and MnSOD+/- mice ( Fig 1B & 1D ) . The basal levels of MnSOD mRNA , protein , and enzymatic activity were decreased by 37 . 6% , 61 . 6% , and 73% , respectively , in the myocardium of MnSOD+/- ( vs . WT ) mice ( Fig 1C and 1E–1G , ap<0 . 05 ) . The myocardial levels of MnSOD mRNA , protein and activity in chronically infected WT . Tc ( vs . WT ) mice were decreased by 31% , 63% and 80% , respectively ( Fig 1C and 1E–1G bp<0 . 05 ) . The Tc-induced MnSOD deficiency was further worsened in MnSOD+/- mice as was evidenced by 63% , 56% , and 51% decline in MnSOD mRNA , protein , and activity , respectively , in MnSOD+/- . Tc ( vs . WT . Tc ) mice ( Fig 1C and 1E–1G , dp<0 . 05 ) mice . Together , these results suggest that a ) genetic deletion of SOD2 decreased the expression and activity of MnSOD , but it had no effect on the expression of other members of the SOD family , b ) myocardial expression of SOD1 and SOD3 were not changed in response to Tc infection , c ) the expression and activity of MnSOD was significantly decreased by chronic Tc infection in WT mice , and it was further worsened in MnSOD+/- mice . We next determined the effects of MnSOD deficiency on mitochondrial health in Chagas disease . There were no discernible differences in mitochondrial yield between WT and MnSOD+/- mice . The effects of MnSOD deficiency on complex I supported mitochondrial respiration ( ± Tc ) are shown in Fig 2A–2D . No significant change in state 4 respiration was observed in cardiac mitochondria of WT and MnSOD+/- mice ( Fig 2A ) , while basal level of complex I driven state 3 was decreased by 44–55% , and contributed to ~35% decline in RCR in cardiac mitochondria of MnSOD+/- ( vs . WT ) mice ( Fig 2B & 2C , ap<0 . 05 ) . The chronically infected WT . Tc ( vs . WT ) mice exhibited a 60 . 7% and 51% decline in myocardial , complex I driven state 4 and state 3 respirations , respectively ( Fig 2A & 2B , bp<0 . 05 ) , and no change in RCR value ( Fig 2C ) . In MnSOD+/- mice; T . cruzi infection worsened the complex I driven state 3 respiration by 40% ( vs . uninfected/MnSOD+/- , Fig 2B , cp<0 . 05 ) . The complex I-dependent ADP/O ratio ( indicates the ATP synthesis rate ) was decreased by 37% and 27% respectively , when MnSOD deficiency and chronic Tc infection were present individually , and by 49% in MnSOD+/- . Tc ( vs . WT ) mice ( Fig 2D , a-ep<0 . 05 ) . The complex II driven respiratory parameters in WT and MnSOD+/- mice ( ± Tc ) are shown in Fig 2E–2H . As above , complex II supported state 4 was not changed by MnSOD deficiency or Tc infection ( Fig 2E ) . However , complex II driven state 3 and RCR were decreased by 43–44% and 34–65% respectively , by MnSOD deficiency ( MnSOD+/- vs . WT , ap<0 . 05 ) or chronic Tc infection ( WT . Tc vs . WT , bp<0 . 05 ) , and MnSOD deficiency and Tc infection together resulted in >70% decline in complex II driven coupled respiration and RCR in the myocardium ( Fig 3F & 3G , compare MnSOD+/- . Tc vs . WT , ep<0 . 05 ) . Likewise , complex II supported ADP/O ratio was decreased by 34% due to MnSOD deficiency or chronic infection only ( Fig 3H , a , bp<0 . 05 ) , and by >75% with presence of MnSOD deficiency and chronic infection together ( Fig 3H , e<0 . 05 ) . Together , our finding of no change in state 4 above the basal level suggest that mitochondrial preparations were not damaged or uncoupled , and basal chemiosmosis gradient was not altered by MnSOD deficiency . Yet , MnSOD deficiency and chronic infection independently caused a decline in complex I and complex II supported , ADP-coupled respiration and ATP synthesis in murine myocardium , and the ATP synthesis capacity was increasingly deteriorated in MnSOD+/- mice with chagasic disease . The MnSOD is an essential mitochondrial antioxidant that detoxifies free radical superoxide ( O2•- ) generated by mitochondrial respiration . We next determined if MnSOD deficiency exacerbates the mtROS production in chagasic myocardium . For this , we incubated the isolated cardiac mitochondria with P+G+M to energize the electron transport chain at complex I , or with rotenone and succinate to inhibit the complex I and energize the electron transport chain at complex II . Then , we measured the rates of DHE oxidation to fluorescent hydroethidium ( detects intra-mitochondrial ROS ) and of amplex red to resorufin ( detects ROS release ) . The CI- and CII-driven DHE and amplex red oxidation were increased by 330–350% ( Fig 3A & 3B ) and 53–120% ( Fig 3C & 3D ) respectively , in cardiac mitochondria of MnSOD+/- ( vs . WT ) mice ( all , ap<0 . 05 ) . Chronic Tc infection resulted in 220–250% and 35–114% increase in CI- and CII-driven DHE and amplex red oxidation , respectively , in WT . Tc ( vs . WT ) mice ( all , bp<0 . 05 ) . An overall higher rate of mtROS production , evidenced by 50–89% increase in DHE oxidation and 30–70% increase in amplex red oxidation , was noted in chronically infected MnSOD+/- . Tc ( vs . WT . Tc ) mice ( Fig 3A–3D , dp<0 . 05 ) . Consequently , myocardial H2O2 levels were increased by 75% in MnSOD+/- ( vs . WT ) mice and by >200% in chagasic ( vs . non-infected ) WT and MnSOD+/- mice ( Fig 3E ) . Together , these results suggest that a ) MnSOD deficiency and chronic Tc infection , individually , increase the myocardial mtROS production and ROS level , and b ) MnSOD deficiency has an additive effect on Tc-induced mitochondrial and cardiac oxidative stress in Chagas disease . We next determined the effects of increased mtROS on myocardial oxidative damage in MnSOD+/- ( vs . WT ) mice . We examined 4-HNE that is an α , β-unsaturated hydroxyalkenal produced by lipid peroxidation , MDA that is a stable breakdown product of highly reactive lipid hydroperoxides formed by the action of ROS on polyunsaturated fatty acids , and carbonyls that are protein-derived aldehydes and ketones produced by direct oxidation of amino acids . No significant change in 4-HNE levels was noted in the myocardium of WT and MnSOD+/- mice ( Fig 4A ) , while basal levels of MDA and protein carbonyls were increased by 290–370% in MnSOD+/- ( vs . WT ) mice ( Fig 4B & 4C ) . In response to chronic infection , myocardial 4-HNE content was barely increased ( Fig 4A ) , and MDA and carbonyl levels were increased by 350% ( Fig 4B & 4C , bp<0 . 05 ) in WT . Tc ( vs . WT ) mice . The MnSOD+/- . Tc mice exhibited maximal myocardial oxidative stress , evidenced by 230% and 57 . 7% higher levels of MDA and protein carbonyls , respectively , when compared to normal MnSOD+/- and chronically infected WT mice ( Fig 4B & 4C , c , dp<0 . 05 ) ; and 1140% and 615% increase in MDA and protein carbonyls , respectively , when compared to normal WT mice ( Fig 4B & 4C , ep<0 . 05 ) . The myocardial 4-HNE levels were also highest in MnSOD+/- . Tc mice as compared to any other group of mice . Together , these results suggest that MnSOD deficiency exacerbated the damaging oxidants in the myocardium of chagasic mice . Finally , we examined peripheral and myocardial parasite burden , plasma levels of myeloperoxidase and IL-6 , and myocardial inflammatory infiltrate and LDH expression to evaluate the effect of parasite and MnSOD deficiency on inflammatory stress in Chagas disease . These data showed higher level of blood parasitemia and equal level of myocardial parasite burden in chronically infected MnSOD+/- ( vs . WT ) mice ( Fig 5A & 5B ) . The plasma levels of MPO and IL-6 and myocardial expression of LDH mRNA ( cellular injury marker ) were increased by >300% , 90% , and 97% respectively , in chronically infected WT . Tc ( vs . WT ) mice; and by 130% 339% , and 101% respectively , in chronically infected MnSOD+/- . Tc ( vs . MnSOD+/- ) mice ( Fig 5C–5E , all p<0 . 05 ) . Further , histological studies showed extensive , diffused inflammatory infiltrate in the myocardium of chronically infected WT ( histological score: 3 . 0 ± 0 . 41 ) and MnSOD+/- ( histological score: 4 . 0 ± 0 . 76 ) mice ( Fig 5Fb and 5Fd ) . Together , these data suggest that mitochondrial deficiency of MnSOD and increased mtROS contributed to a slight increase in peripheral and myocardial inflammatory stress but it did not further exacerbate the chronic parasite persistence in the heart in Chagas disease .
MnSOD is a primary antioxidant located on the matrix side of inner mitochondrial membrane , wherein it dismutates the superoxide byproducts of oxidative phosphorylation ( OXPHOS ) to H2O2 and the latter is further reduced by glutathione peroxidases and catalase [22] . Mutations in the gene encoding MnSOD have been associated with idiopathic cardiomyopathy , aging , and cancer . In this study , we demonstrate that host deficiency of MnSOD exacerbates the mitochondrial stress in chronic chagasic cardiomyopathy of infectious etiology . Our results in this study and other reports demonstrate that MnSOD levels were compromised with the development of chronic Chagas disease in mice [23] and humans [24] . NFE2L2 ( basic leucine zipper transcription factor ) binds to the antioxidant response element ( ARE ) in promoter region of antioxidant genes , and a decline in nuclear translocation and activity of NFE2L2 was suggested to contribute to decreased MnSOD expression during T . cruzi infection [14] . In another study , a therapeutic approach based on inhibition of phosphodiesterase 5 ( PDE5 ) was shown to enhance the ROS scavenging capacity and establish antioxidant/oxidant balance in chagasic myocardium by activation of MnSOD expression and activity [25] . Further studies will be required to delineate how and if PDE5 suppresses the antioxidant capacity via targeting the NFE2L2 pathway of antioxidant response in the heart . Yet , our previous findings in WT and MnSODtg mice [12 , 14] and comparative analysis of WT and MnSOD+/- mice in this study establish that MnSOD is essential to maintain mitochondrial respiratory function and arrest mtROS in the myocardium . We surmise that small molecule MnSOD mimetics will be beneficial in arresting the mtROS and oxidative adducts of the macromolecules such as DNA , lipids , and proteins in chagasic myocardium . ROS contributes to hypertrophy and remodeling of the failing myocardium through multiple mechanisms . For example , ROS signals phenotypic transformation of fibroblasts to myofibroblasts and triggers fibrosis , collagenosis , and the activation of matrix metalloproteinases [26 , 27] . ROS-dependent formation of advanced glycation end ( AGE ) products accelerates the crosslinking of collagens in diabetic heart [28 , 29] . In other instances , ROS mediated cellular injury resulted in loss of cardiomyocytes [30] . Thus , ROS can contribute to thickening as well as thinning of the LV walls . Indeed , enhancing the MnSOD levels improved the myocardial performance index through control of ROS-induced hypertrophy and cardiac injuries in chagasic mice [14] . It is also reported that ROS , through oxidation of IκB , promotes nuclear translocation of RelA/p65 and transcriptional activation of numerous genes involved in inflammatory and proliferative responses [31] . We have shown ROS-dependent increase in the expression of inflammatory cytokines ( IL-1β , TNF-α ) in cardiomyocytes infected by T . cruzi [32] . A control of inflammatory responses ( MPO , LDH ) and myocardial inflammatory infiltrate was also observed in chronically infected MnSODtg ( vs . WT ) mice [12] . Our finding of a moderate increase in inflammatory stress in chagasic MnSOD+/- ( vs . chagasic WT ) mice are in alignment with our previous findings and imply that mtROS contributes to chronic inflammatory stress in Chagas disease . It is worth noticing that sirtuin 1 ( SIRT1 ) deficiency also predisposed the chagasic heart to chronic inflammation through increased levels of acetylated ( functional ) form of p65/RelA [16] . Polyadenosine ribose polymerase ( PARP1 ) competes with SIRT1 for substrate , and an increase in PARP1-dependent cytokine gene expression was also noted in infected cardiomyocytes [33] . Consequently , treatment with PARP1 inhibitor or SIRT1 agonist arrested the NFκB-dependent inflammatory cytokine expression in infected cardiomyocytes [33] and chagasic heart [16] . We surmise that SIRT/PARP1 balance along with activators of SOD2 will provide promising new therapeutic strategies for arresting chronic oxidative and inflammatory stress and cardiac dysfunction in Chagas disease [34] . In summary , we have shown that MnSOD deficiency aggravates the mitochondrial dysfunction of electron transport chain , mtROS production , and oxidative adducts in Chagas disease . We propose that MnSOD mimetics capable of protecting the mitochondria from oxidant stress and maintain metabolic homeostasis will have potential utility as adjuvant therapy in arresting the evolution of chronic Chagas disease .
|
Infection by Trypanosoma cruzi parasitic protozoan remains endemic in Latin America . After acute parasitemia phase is controlled by host immune system , infected individuals remain clinically silent but manifest a number of micro and macro cardiac injuries for several years . Eventually many of the infected individuals develop chronic cardiomyopathy that leads to heart failure and sudden death . Cardiac muscle cells are rich in mitochondria and manganese superoxide dismutase ( MnSOD ) is the chief superoxide scavenging enzyme in the mitochondria . In this study , we show that a deficiency of MnSOD exacerbates the T . cruzi induced mitochondrial dysfunction of the electron transport chain and energy production in the heart . Further , MnSOD deficiency resulted in increased mitochondrial release of oxidants and caused excessive oxidative damage in the chagasic heart . Our results suggest that small molecule agonists of MnSOD will have potential utility as adjuvant therapy in preventing the development of chronic Chagas disease in infected individuals .
|
[
"Abstract",
"Introduction",
"Materials",
"and",
"methods",
"Results",
"Discussion"
] |
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] |
2018
|
Manganese superoxide dismutase deficiency exacerbates the mitochondrial ROS production and oxidative damage in Chagas disease
|
Although accurate assessment of the prevalence of Schistosoma mansoni is important for the design and evaluation of control programs , the most widely used tools for diagnosis are limited by suboptimal sensitivity , slow turn-around-time , or inability to distinguish current from former infections . Recently , two tests that detect circulating cathodic antigen ( CCA ) in urine of patients with schistosomiasis became commercially available . As part of a larger study on schistosomiasis prevalence in young children , we evaluated the performance and diagnostic accuracy of these tests—the carbon test strip designed for use in the laboratory and the cassette format test intended for field use . In comparison to 6 Kato-Katz exams , the carbon and cassette CCA tests had sensitivities of 88 . 4% and 94 . 2% and specificities of 70 . 9% and 59 . 4% , respectively . However , because of the known limitations of the Kato-Katz assay , we also utilized latent class analysis ( LCA ) incorporating the CCA , Kato-Katz , and schistosome-specific antibody results to determine their sensitivities and specificities . The laboratory-based CCA test had a sensitivity of 91 . 7% and a specificity of 89 . 4% by LCA while the cassette test had a sensitivity of 96 . 3% and a specificity of 74 . 7% . The intensity of the reaction in both urine CCA tests reflected stool egg burden and their performance was not affected by the presence of soil transmitted helminth infections . Our results suggest that urine-based assays for CCA may be valuable in screening for S . mansoni infections .
Recently , there has been increased interest in the development and assessment of control and elimination programs for schistosomiasis [1] . For design of effective control programs , it is important to determine an accurate estimate of infection prevalence in the program area . The method most commonly used for diagnosis of Schistosoma mansoni infection is the detection of eggs in stool by the Kato-Katz method . Benefits of the Kato-Katz method are very high specificity , low cost , and relatively simple technologic requirements . However , the sensitivity of this method is low [2] and may be affected by day to day variability in egg excretion [3] , [4] , [5] . The Kato-Katz method is also time consuming and exposes laboratory workers to potentially harmful fresh stools which can contain infectious agents . In order to overcome some of the pitfalls of the Kato-Katz method , there has been interest in developing new , more sensitive tests for the diagnosis of schistosomiasis . These tests often employ immunologic methods based on the detection of antibodies or antigens in blood or urine . Immunodiagnosis is generally more sensitive than examination of stool , particularly in low transmission areas where infection intensities are light [6] . Antibody assays can utilize crude antigen extracts such as schistosome egg antigen ( SEA ) or soluble adult worm antigen preparation ( SWAP ) , or can be constructed to detect purified antigens . While methods that measure antibody levels tend to be more sensitive than Kato-Katz , parasite-specific antibodies can remain for years after the infection has been cleared . As a result , they are unable to distinguish between current and previous infections . Antibody levels in serum also do not necessarily correlate with intensity of the schistosome infection as determined by mean fecal eggs per gram . Another method for the diagnosis of schistosomiasis is the detection of circulating anodic and cathodic antigens ( CAA and CCA ) in blood or urine [7] . Because CAA and CCA are released by viable adult worms , these assays are specific for current infections and can also provide some information about infection intensity [8] , [9] . While CCA detection in urine can be as sensitive as a single Kato-Katz test in areas that have a high intensity of infection [10] , few studies have compared the sensitivity and specificity of urine antigen detection tests with stool examination and serologic assays . This is in part because the antibodies used to detect CCA have been available in only a few laboratories and require preparation of reagents that are not readily deployable for field use . However , within the last few years , two urine CCA assays were developed and became commercially available . The first used a colloidal carbon conjugate of a monoclonal antibody specific for Schistosoma CCA and was designed for use in the laboratory [11] . A version of this assay was previously produced for research diagnostic purposes by European Veterinary Laboratory , and used in studies of children less than 3 years of age [12] and in school aged children with sensitivites and specificities in the low 80th percentiles when compared to stool egg data [13] . The second was a gold-conjugated , lateral flow cassette-based assay , which was designed to be a point of contact test . Since the initiation of this study , production of the test that utilized the carbon conjugate has been discontinued as a result of market considerations . We compared the performance of the two CCA assays with that of the Kato-Katz method and a SWAP-specific IgG ELISA . This comparison is part of a larger project addressing the prevalence of schistosomiasis in pre-school and school aged children in a village in western Kenya ( Verani et al . , manuscript in preparation ) . The study site is close to the shores of Lake Victoria where our previous studies have demonstrated high levels of S . mansoni infection but no S . haematobium transmission [14] , [15] . The specificities and sensitivities of the antibody and circulating antigen tests were assessed in relation to the Kato-Katz method as well as evaluated using latent class analysis ( LCA ) , which is a method for assessing the accuracy of a test when diagnosis lacks a true gold standard [16] , [17] . LCA is based on the assumption that the observed diagnostic test results for an individual are imperfect measures of the unobserved ( or latent ) true disease class to which this individual belongs [18] . This technique allows the prevalence of the latent classes , as well as the sensitivity and specificity of each diagnostic test , to be estimated by attributing the pattern of observed test results to the latent class membership . Basic LCA requires the assumption of conditional independence , meaning that the diagnostic tests are assumed independent within each disease class [19] . More complex LCA methods allow modeling of the dependence structure between diagnostic tests in various ways [19] , [20] , [21] . Estimates from a model in which the dependence structure is incorrectly specified or even ignored could be biased [22] , [23] . If a complex model is used to more accurately represent the dependence structure present in the data , however , interpretation can become difficult [23] , [24] and estimation of all parameters may not be possible [20] . Statistical analysis with LCA yields more accurate sensitivities and specificities of new tests than what is obtained by comparisons to an imperfect gold standard [22] , [24] and has previously been employed to evaluate tests for the diagnosis of schistosomiasis [25] , [26] , [27] . We also evaluated whether the results of the ELISA or CCA assays were affected by coinfection with soil-transmitted helminths ( STHs ) and if the results of these assays reflected the intensity of schistosome infection in the individual .
The study protocol was approved by the Scientific Steering Committee of the Kenya Medical Research Institute ( KEMRI ) , the National Ethics Review Committee of KEMRI and the Institutional Review Board of the Centers for Disease Control and Prevention . Written assent and consent were obtained from study participants and their parents or guardians , respectively . The samples collected in this study are part of a cross sectional study looking at childhood schistosomiasis in western Kenya . Samples were collected from children one to fifteen years of age in Usoma , a village in western Kenya on the shore of Lake Victoria . All age-eligible children were invited to participate; a total of 484 children were enrolled . Previous to this study , there had been no mass drug administration to treat schistosomiasis in this area . Any child who was determined to be schistosome or STH positive ( by stool ) was treated with the appropriate dose of praziquantel or albendazole , respectively . Field assistants collected three stool samples on consecutive days , single mid-stream urine samples , and finger-prick quantities of blood from each child enrolled in the study . Duplicate slides of each stool sample were examined using the Kato-Katz technique . Each slide was read by two trained microscopists and any discrepancies resolved before results were recorded as eggs per gram ( EPG ) feces . The results for all six slides were averaged . Stools were also examined for eggs of STHs ( hookworm , Ascaris lumbricoides , and Trichuris trichiura ) . A child was considered infected when at least one of the slides contained an egg . All data were entered into Microsoft Excel . ELISA plates were coated with 100µL of 0 . 01mg/ml SWAP in 0 . 5 M sodium carbonate buffer , pH 9 . 6 , for at least four hours at room temperature . Plates were blocked with 100µL of PBS containing 0 . 3% Tween 20 and 5% nonfat dried milk and were incubated overnight at 4°C . Diluted sera ( 1∶100 in PBS/Tween 20/ . 01% milk ) were added to the plates and incubated at room temperature for one hour , then washed five times in PBS containing 0 . 05% Tween 20 . Affinity purified , peroxidase labeled anti-human goat IgG ( CDC ) diluted 1∶1000 in PBS/Tween/0 . 01% milk was added for one hour at room temperature followed by five washes . Plates were developed with TMB substrate ( Kirkegaard & Perry Laboratories , Gaithersburg , MD ) and stopped with 18% sulfuric acid . The plates were read on a Molecular Diagnostics Vmax microplate reader ( Molecular Devices Corporation , Sunnyvale , CA ) at 450 nm and analyzed with Softmax software ( Molecular Devices ) . To ensure consistency between plates a standard curve was developed and included on each plate . A 1∶3 serial dilution curve was made from highly positive serum from adult male car washers from the area and assigned arbitrary units . A four-parameter curve fitting model was used to assign units to each unknown sera . The positive cutoff value was set at two standard deviations above the average anti-SWAP IgG value of 13 different ‘normal human serum’ samples ( sera from non-endemic individuals ) run in conjunction with the patient samples . Both CCA urine assays were obtained from Rapid Medical Diagnostics ( Pretoria , South Africa ) and performed at ambient temperature according to the manufacturer's instructions . The CCA urine assays were not available at time of sample collection; therefore , collected urine was stored at −20°C until the assays were run . Urine samples were completely thawed and vortexed before use . Briefly , for the laboratory-based test , 25 µL of urine was added to a tube containing dried carbon conjugated antibody , along with 75 µL of buffer that was supplied by the company . Test strips were added , and allowed to develop for 40 minutes . Strips were removed , allowed to dry , and read against standards provided by the manufacturer . As the CCA strips were read , they were compared to the standards and scored as 0 , + , ++ , or +++ . A score of 0 indicated a negative result , + indicated that a band was as dark as the 100 standard , ++ indicated a band was as dark as the 1 , 000 standard , and +++ indicated that a band was as dark as the 10 , 000 standard . Results were determined in a blinded fashion by at least two individuals . For the cassette assay , one drop of urine was added to the well of the testing cassette and allowed to absorb . Once fully absorbed , one drop of buffer ( provided with the kit ) was added to the well and the assay was allowed to develop . Twenty minutes after the buffer was added the tests were read . Tests were considered invalid if the control bands did not develop , or if the test sat for 25 minutes after the buffer was added before being read . In these cases , the sample was rerun with a new test cassette . Results were determined in a blinded fashion by at least two individuals and scored as either negative , + , ++ , or +++ . Due to the lack of standards designed for this test , the classification of the positive results as weak or strong was more subjective than the laboratory-based carbon assay . Sensitivities and specificities were first estimated using the Kato-Katz method as the reference test . Given that the Kato-Katz method yielded a positive result , the sensitivity of a test was defined as the percentage of subjects with a positive test result . Similarly , those with a negative Kato-Katz result were used to find the specificity of each test by finding the percentage of subjects with a negative result . We next performed latent class analysis ( LCA ) , in which the results of the four diagnostic assays ( Kato-Katz , anti-SWAP IgG ELISA , and the two urine CCA assays ) were combined as indicators of an underlying latent class , the true infection status of the individuals ( S . mansoni positive or negative ) . Using the relationship between the true disease class and the observed test patterns , sensitivity and specificity were estimated for each test . While the assumption that all tests are conditionally independent given the true disease status [23] is often made in LCA , it was not made in this analysis because the two CCA diagnostic tests identify the presence of the same antigen in urine samples and are expected to be correlated . The addition of a latent variable allowed for conditional dependence between these two tests [21] . LCA was performed using the software BLCM: Bayes Latent Class Models version 1 . 3 [28] . For evaluations of the effect of STH infection on assay performance , statistical analyses were performed using Kruskal-Wallis nonparametric one-way analysis of variance ( ANOVA ) and Fisher's exact test for contingency analysis . Similarly , analyses of test results in relation to schistosome infection intensity were performed by Kruskal-Wallis ANOVA . These analyses were performed using InStat GraphPad Software version 3 . 05 ( GraphPad Software , LaJolla , CA ) .
Between September and December 2007 , 247 boys and 237 girls between the ages of 1 and 15 provided stool , urine and blood for diagnostic testing . Of the 484 children enrolled in this study all three stool samples were obtained from 482 individuals . Of these , 187 ( 38 . 8% ) tested positive for S . mansoni by the Kato-Katz method . Among the positive individuals , 87 ( 46 . 5% ) were classified as having a low intensity infection ( 0–100 EPG ) , 68 ( 36 . 4% ) had moderate infections ( 101–400 EPG ) , and 32 ( 17 . 1% ) had heavy infections ( >400 EPG ) . Nineteen ( 3 . 9% ) , 77 ( 15 . 9% ) and 157 ( 32 . 4% ) individuals were infected with Ascaris lumbricoides , hookworm , and Trichuris trichiura , respectively . The number of children positive by each test is shown in Table 1 . Of the 484 individual sera evaluated by the SWAP ELISA , 298 ( 61 . 6% ) were positive for S . mansoni antibodies . Of the 426 patients' urines tested for CCA by the laboratory-based carbon assay , 226 ( 53 . 1% ) were positive; 423 urine samples were tested for CCA by the cassette assay and 264 ( 62 . 4% ) individuals were positive . An increase in prevalence with age was observed for all 4 tests ( Figure 1 ) . A complete specimen set ( three consecutive stools , blood , and urine ) was available for 413 of the 484 children enrolled in the study so that all four tests could be performed . Of these , 143 ( 34 . 6% ) were S . mansoni positive by all the tests and 95 individuals ( 23 . 0% ) were negative for S . mansoni in all assays . A total of 53 individuals ( 12 . 8% ) were egg negative , but positive by both CCA assays and the SWAP ELISA . Forty-four individuals ( 10 . 7% ) were positive only by the SWAP ELISA , 23 ( 5 . 6% ) were positive only by the cassette CCA assay , and three ( 0 . 7% ) were positive only by the carbon CCA assay . Four individuals ( 0 . 9% ) were positive by the Kato-Katz method and not by any other test; three of these children had relatively light infections ( 96 , 102 , and 18 EPG ) and one had an EPG count of 1 , 382 . The remaining 48 children ( 11 . 6% ) were positive by either two or three of the testing methods . There were 70 individuals who were carbon CCA positive , but egg negative . Out of these individuals , 56 ( 80% ) were positive by the SWAP ELISA . There were 99 individuals who were cassette CCA positive but were egg negative . Out of these individuals , 65 ( 65 . 6% ) were positive by the SWAP ELISA . We analyzed the sensitivity and specificity data in two ways ( Table 2 ) . In the first analysis , we compared the results to the detection of eggs in stool with the Kato-Katz method , an imperfect standard . When using the Kato-Katz results to determine the sensitivities and specificities of the CCA urine assays , the sensitivities were high , 88 . 4% and 94 . 2% for the carbon CCA assay and the cassette CCA assay , respectively . However , by this analysis , the specificities of the CCA assays were low , 70 . 9% for the carbon assay , and 59 . 4% for the cassette assay . The SWAP ELISA had a sensitivity of 92% but a specificity of only 57 . 3% when using the Kato-Katz method as the reference . We also analyzed the data using LCA to establish the infection status of the study participants ( Table 2 ) . In this analysis , the Kato-Katz method had the lowest sensitivity ( 74 . 1% ) out of the diagnostic tests . Both the SWAP ELISA ( 96 . 3% ) and the urine CCA assays ( 91 . 7% and 96 . 3% ) had high sensitivity by LCA . The specificities for these assays were not as high as the Kato-Katz method , but were higher than the values obtained when using Kato-Katz as the gold standard . To determine if infection with Ascaris lumbricoides , hookworm , or Trichuris trichiura modified the responses in the SWAP ELISA , we evaluated serologic responses of individuals that either were , or were not infected with STHs . There were no significant differences in the SWAP ELISA values between groups that did or did not have STHs for either schistosome negative or positive individuals ( Figure 2 ) . For this analysis , individuals were classified as ‘schistosome negative’ only when they were negative by all diagnostic assays . Individuals were classified as ‘schistosome positive’ when they were positive by the Kato-Katz method or either of the urine CCA assays . Similarly , we compared the CCA results from people infected with STHs to individuals who were negative for STH eggs by the Kato-Katz method ( Table 3 ) . The percentages of CCA positive individuals did not significantly change based on STH infection status of the individuals , suggesting that STH infections do not influence the urine CCA assay results . We also tested whether the ELISA and CCA results reflected the intensity of infection in the individuals as measured by stool egg count . SWAP ELISA values were averaged for the individuals who had varying levels of intensity: not infected ( no eggs found ) , light infection ( 0–100 EPG ) , moderate infection ( 101–400 EPG ) or heavy infections ( >400 EPG ) . The levels of total anti-SWAP IgG were correlated with intensity of infection as determined by EPG ( p<0 . 0001 , Figure 3 ) . To determine if band intensity of the CCA assays correlated with intensity of infection , we compared the average EPG found in each of the individuals to band strength ( Figure 4 ) . For both CCA tests , band intensity was associated with intensity of infection ( p<0 . 0001 ) .
The Kato-Katz assay has long been the backbone of schistosomiasis diagnosis in endemic areas . However , even when multiple samples are tested , the Kato-Katz method has inadequate sensitivity , especially in areas with lower rates of transmission [29] . This results in the challenging task of trying to evaluate other tests in comparison to an imperfect ‘gold standard’ . When using the Kato-Katz as the ‘gold standard’ to determine the sensitivities and specificities of the CCA urine assays , the sensitivities are rather high but the specificities are quite low . The low specificities obtained when using Kato-Katz as the ‘gold standard’ may be explained by the low sensitivity of the Kato-Katz method . Thus , to more accurately assess the sensitivities and specificities of these assays , we analyzed the results using LCA . We chose the Bayesian approach to Latent class analysis , considering the two CCA diagnostic assays correlated because they test for the same antigen in the same sample ( urine ) . Sensitivities and specificities of each of the four tests were calculated based on the latent variable ‘true disease status’ . As expected , the Kato-Katz method had the lowest sensitivity when analyzed by LCA . The SWAP ELISA and the cassette urine CCA assay were the most sensitive assays , albeit also the least specific . It is possible that false positive antibody responses could be present in children who were exposed to schistosome antigens but not infected ( e . g . , in utero , during the pregnancy of an infected mother ) or in older children who had been infected then cleared the infection due to natural worm death . Schistosomes that typically infect wild mammals , including some new and hybrid species , have also been described in the Lake Vitoria Basin near Kisumu [30] . However , it is not known how human exposure to these other schistosomes may affect performance of the ELISA . False positive CCA results may occur if the individual being tested has haematuria or pio-uria due to urinary tract infection , as stated on the CCA assay technical brochure . However due to the age of these children we feel that this would not likely make a large impact on our study . Similarly , we do not know what the effect of having frozen the urine had on the assay performance as we did not test any urine that had not been frozen . The product insert states that urine can be frozen for up to a year but we are unable to comment on whether or not the frozen urine was any less sensitive than urine collected and tested immediately . Of the 53 individuals who were negative for eggs in stool but positive by both of the CCA assays and the SWAP ELISA it is likely that they had light infections that were missed by the Kato-Katz even though stools were collected on three consecutive days . Of the four children who were positive by stool examination and not by any other test , three children had lighter infections ( 96 , 102 , and 18 EPG ) that may have been missed by the other diagnostic tests . However , one of the children had a high intensity infection ( 1 , 382 EPG ) , which was unlikely to be missed by the other assays . It is possible that the stool samples were mislabeled and not from the same individual that provided the other two samples types . This highlights a limitation of stool and urine data in that sample collection is typically not directly observed and either urine or stool may be substituted with samples from other individuals . In contrast , this is usually not a concern for blood samples collected by study personnel . Other factors that may have contributed to incongruous results between the various assays include a poor understanding of whether CCA levels demonstrate diurnal variations . In addition , volume of fluid intake or number of previous urinations in a given day may affect urine CCA concentration . Also , while our assumption was that most of the children in this study had not previously been treated for schistosomiasis as no mass treatments had recently been performed in this area , it is possible that some families had migrated into the area and that children may have been treated elsewhere and could thus be antibody positive but egg and antigen negative . Finally , although HIV-1 prevalence levels are high in this area of western Kenya and could theoretically affect antibody responsiveness , we do not expect that HIV-1 coinfection would significantly affect our observed results as the age of the majority of participants was such that previous exposure to HIV-1 was unlikely . In addition to the accuracy of a screening test , it is important to also consider practicality when comparing different tests [31] . Although the Kato-Katz test can be done at a relatively low cost , there are other factors that make this method less than ideal . For example , the Kato-Katz method requires one or more individuals trained in stool sample preparation and microscopy . There are also significant expenses associated with transport costs and the field staff time necessary for multiple field trips , to obtain consecutive stool samples and to provide treatment . In contrast , the cassette CCA assay is designed for point of contact use . Thus , health workers could combine screening and treatment during a single trip which would save on costs and possibly reduce the number of missed treatments of individuals who cannot be found on a follow-up visit . Currently , the individual test cost of the CCA assays is relatively high ( $1 . 98 US per test ) but future comparisons of expenses should include personnel time , transport and equipment expenses to determine which approach is more cost effective . In addition , cost of the CCA test may be reduced with greater use and increased scale of production . Although the SWAP ELISA had similar sensitivity as the cassette CCA assay , this assay is less practical in field based control programs because of the requirements for reagents and equipment , as well as the need for specialized training of laboratory personnel . Also , the inability of the total IgG antibody test to distinguish between past and current infections makes this a poor test for assessing prevalence in populations that have already received treatment . Our results are consistent with those of a recently published study that found good agreement between urine CCA assay results and a single stool analyzed by the Kato-Katz method [32] . This study evaluated a total 171 children , ages 6 to 17 , in 11 schools along the Kenyan and Tanzanian shore of Lake Victoria , including 14 children from Usoma , the school that serves the children in our study . Both studies found a strong correlation between stool egg concentration and intensity of the CCA test band ( [32] and Figure 4 ) . Like the authors of this previous study [32] , we conclude that the CCA urine assays are an effective screening tool for S . mansoni infections in areas of high prevalence . The CCA urine assays were more sensitive than examination of three stools by Kato-Katz and were as sensitive as the adult worm-specific antibody tests . The urine CCA assays are also easy to use and less time consuming than the other methods currently employed for S . mansoni screening . CCA assays also have the potential to asses cure , as CCA should not be present after the resolution of infection [33] . However , in this study , we were not able to assess cure rates or the ability of the tests to detect resolution of infections as we did not collect additional samples after treatment . Future studies including urine CCA assays should address this question as well as evaluating the performance of the tests in areas with lower intensities of infection . Table 4 summarizes the strengths and weaknesses of the assays used in this study for population screening purposes . How data from these different assays can be used to inform treatment decisions at the local level has been discussed by Standley et al . in a recent publication [34] . Results from this study indicate that the urine CCA assays are at least as sensitive as the Kato-Katz method of testing for schistosome eggs in stool . The company that produced both CCA tests has now halted production of the carbon CCA assay . Results from the discontinued test are included here because results from that assay contributed to the study analysis . Production of the cassette CCA assay continues and its ease of use and relatively simple sample collection make it an attractive tool for screening for S . mansoni infections in control programs .
|
Control efforts for schistosomiasis have in part been hampered by the lack of a sensitive and accurate test that can be utilized to rapidly map the prevalence of the disease in different areas . Recently , new tests have become commercially available that may address this problem . This study was designed to compare the new tests , which detect a schistosome antigen in patients' urine , with more traditional tests that look for parasite eggs in stool or anti-parasite antibodies in serum . We found that the new tests performed very well to detect schistosomiasis in children in western Kenya , an area with a high prevalence of Schistosoma mansoni infections . There was no apparent effect of soil transmitted helminth infections on the performance of the tests and the intensity of the antigen detection assays correlated well with the levels of S . mansoni eggs in the stool and schistosome-specific antibody in serum . Additional evaluation is needed in areas with lower schistosomiasis prevalence and intensity levels but we believe that point of contact testing of urine for schistosome antigen could be an effective tool in schistosomiasis mapping and control efforts .
|
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"and",
"epidemiology/screening"
] |
2011
|
Evaluation of Urine CCA Assays for Detection of Schistosoma mansoni Infection in Western Kenya
|
Because DNA double-strand breaks ( DSBs ) are one of the most cytotoxic DNA lesions and often cause genomic instability , precise repair of DSBs is vital for the maintenance of genomic stability . Xrs2/Nbs1 is a multi-functional regulatory subunit of the Mre11-Rad50-Xrs2/Nbs1 ( MRX/N ) complex , and its function is critical for the primary step of DSB repair , whether by homologous recombination ( HR ) or non-homologous end joining . In human NBS1 , mutations result truncation of the N-terminus region , which contains a forkhead-associated ( FHA ) domain , cause Nijmegen breakage syndrome . Here we show that the Xrs2 FHA domain of budding yeast is required both to suppress the imprecise repair of DSBs and to promote the robust activation of Tel1 in the DNA damage response pathway . The role of the Xrs2 FHA domain in Tel1 activation was independent of the Tel1-binding activity of the Xrs2 C terminus , which mediates Tel1 recruitment to DSB ends . Both the Xrs2 FHA domain and Tel1 were required for the timely removal of the Ku complex from DSB ends , which correlates with a reduced frequency of imprecise end-joining . Thus , the Xrs2 FHA domain and Tel1 kinase work in a coordinated manner to maintain DSB repair fidelity .
The DNA double-strand break ( DSB ) is one of the most severe types of DNA damage and is most often repaired by homologous recombination ( HR ) or canonical non-homologous end joining ( C-NHEJ ) which is known as precise NHEJ . There are , however , several other minor pathways for DSB repair , some of which generate serious rearrangements of DNA structure . It is thought that an incorrect choice among these repair pathways promotes genomic instability , which compromises biological activity and can with time , promote tumorigenesis in higher eukaryotes [1] . The Mre11-Rad50-Xrs2/Nbs1 ( MRX/N ) complex has many roles in the initial steps of DSB repair , whether by C-NHEJ or HR , and also in the recovery from stalled replication forks , in telomere maintenance , in meiotic recombination and in the Tel1/ATM-related DNA damage response ( DDR ) signaling [2–6] . Thus , MRX/N acts as an integrating hub of DDR pathways . In budding yeast , Saccharomyces cerevisiae , repair by C-NHEJ requires several multi-subunit complexes , namely MRX , Yku70-Yku80 ( Ku ) and Dnl4-Lif1-Nej1 ( DNA ligase IV ) . First , Ku binds to free double–stranded DNA ( dsDNA ) ends , without needing a specific DNA structure , and then is able to translocate to an internal region of the DNA molecule , including the single-stranded DNA ( ssDNA ) region [7 , 8] . Then , C-NHEJ is completed by DNA ligase IV to rejoin the broken ends . To function effectively , these complexes rely on physical interactions between components , for example , Ku80 binds Dnl4 and Mre11 and Xrs2 binds Lif1 [9 , 10] . Alternative non-homologous end joining ( A-NHEJ ) , also known as microhomology-mediated end joining ( MMEJ ) , is an auxiliary pathway for the repair of DSBs that occurs after end processing . MMEJ requires the MRX complex , Sae2 , Tel1 and Rad1/Rad10/Slx4 , but not Ku nor DNA ligase IV complexes [11 , 12] . Although the process of MMEJ is quite similar to the single-strand annealing ( SSA ) reaction , MMEJ in yeast is genetically distinguishable from SSA by its requirement for Rad52 , a protein that plays a key role in HR [11] . A further , minor pathway of NHEJ , often considered as a variant of C-NHEJ , is that of Ku-dependent imprecise end joining [13 , 14] . This pathway can rejoin broken ends with or without microhomology after limited ( <50 bases ) resection [12] . It is unclear what molecular complexes or events distinguish C-NHEJ from the Ku-dependent imprecise–end joining reaction . Thus , MMEJ and Ku-dependent imprecise end joining are classified as imprecise NHEJ . Mre11 has endo- and exonuclease activities , and Rad50 is a structural maintenance of chromosome ( SMC ) -like protein [15–18] . The Mre11-Rad50 sub-complex holds the two ends of a DSB together and facilitates their subsequent processing [19] . Mre11 and Rad50 are conserved from prokaryotes to mammals where they bind a third component called Nbs1 [20] . Xrs2 is the yeast ortholog of the Nbs1 subunit . Xrs2/Nbs1 is thus a eukaryote-specific multi-functional regulatory subunit of the MRX/N complex . The protein consists of a fork-head associated ( FHA ) domain , a pair of BRCA1 C terminus ( BRCT ) or BRCT-like domains , an Mre11-binding domain and a Tel1-binding domain [21–24] . The FHA domain is conserved in most of the orthologs in the N-terminal domain [21 , 22 , 25] and the motif generally has a well-known phospho-protein recognition function important for the DNA damage–related signaling pathway [26–28] . FHA domains are thus implicated in the recruitment of appropriate targets to sites of DNA damage through protein-protein interactions in the phosphorylation-transducing pathways , such as Rad53-Rad9 in budding yeast , Nbs1-Ctp1 in fission yeast and Nbs1-MDC1 , or RNF8-MDC1 , in humans [27–29] . In addition to the N-terminal FHA domain , the C-terminal region of Xrs2/Nbs1 harbors a Tel1/ATM-binding domain that is essential for Tel1/ATM recruitment to sites of DNA damage and to telomeres , as well as for its activity [22 , 23 , 30 , 31] . In addition to Tel1/ATM , Mec1/ATR also has a role in the DDR reaction . Whereas Tel1/ATM recruitment depends on Xrs2/Nbs1 , Mec1/ATR requires a replication protein A ( RPA ) -coated ssDNA stretch that results from Ddc2/ATRIP activity at the site of DNA damage [32] . Recent work suggests a role for RPA in MRX recruitment as well ( Seeber A . et al . , personal communication ) . In humans , truncation mutations of N-terminus region including FHA domain of Nbs1 have been identified as a causative factor for Nijmegen breakage syndrome ( NBS ) , which confers a high risk of cancer and immunodeficiency and was , originally identified as an ataxia telangiectasia–like disorder [27 , 33–36] . Consequently , cells in which the N-terminal region of NBS1 is truncated have abnormal cell cycle checkpoints , including the S-phase checkpoint , which is manifested as radio-resistant DNA synthesis [36 , 37] . Here we report that dysfunction of the Xrs2 FHA domain , as with the loss of Tel1 kinase activity , leads to the accumulation of the Ku complex at DSB ends , which leads to an abnormal increase in imprecise end joining . Moreover , the Xrs2 FHA domain is required for robust activation of Tel1/ATM kinase at DSB ends both during mitosis and meiosis . Our findings reveal a genetic relationship between the Xrs2 FHA domain and Tel1 kinase activity in the maintenance of DSB repair fidelity and provide insights relevant to the human disease NBS .
The FHA domain of Xrs2 is involved in NHEJ [9 , 10 , 22] . To learn more about the function of the FHA domain of Xrs2 in various NHEJ pathways , especially in imprecise end joining , we analyzed the effect of xrs2 mutations on the repair of two HO endonuclease–induced non-complementary DSBs at the MAT locus in budding yeast [11] . In this system , two HO cleavage sites with opposite orientations were inserted on either side of URA3 to allow repair by both Ku-dependent and Ku-independent pathways [14] ( Fig 1A ) . The survival rate of Ura− prototrophs corresponds to the frequency of repair of non-complementary DSB ends by imprecise end joining , which includes both MMEJ and Ku-dependent imprecise NHEJ ( Fig 1A ) [11 , 12] . In contrast , the survival rate of Ura+ prototrophs , which are caused by re-ligation of two HO-induced complementary ends , corresponds to the frequency of precise NHEJ [11] ( Fig 1A ) . In an xrs2Δ mutant , as in mre11Δ and rad50Δ mutants [11] , both imprecise end joining and precise NHEJ are compromised ( Fig 1C ) . Exonuclease defective mutations of MRE11 , which encodes a protein that is in the same complex with Xrs2 , show a completely different phenotype from that of mre11Δ in the various NHEJ pathways [14] . Thus , this assay is useful for revealing different functions within a given polypeptide . To determine the different roles played by Xrs2 , we used two mutant alleles that compromise the FHA function of Xrs2: two point mutations in the FHA domain , xrs2-SH ( S47A , H50A ) and a truncation mutant that lacks 313 amino acids of the N-terminal domain , xrs2-314M , which eliminates both the FHA and the BRCT-like motifs ( Fig 1B ) [22] . These xrs2 FHA mutants do not show any defects in MRX complex formation or , gamma ionizing radiation ( γIR ) sensitivity , but they do show a defect in NHEJ [10 , 22] . We analyzed these mutants for their effects on various types of DSB repair and observed a significant 2 . 3- and 2 . 2-fold increase in the frequency of imprecise end joining in xrs2-SH and xrs2-314M mutants , respectively , relative to wild-type cells ( Fig 1C ) . In contrast , the frequency of precise NHEJ , which was determined by the ratio of Ura+ prototrophs , was lower in these FHA domain mutants as compared with wild-type cells ( Fig 1C ) , which is due to impaired interaction with Lif1 [10] . Total loss of Xrs2 , in contrast , compromised both types of repair . This result indicated that the FHA domain of Xrs2 helps promote precise NHEJ and this or the FHA domain itself leads to the suppression of imprecise end-joining . The tel1Δ and sae2Δ mutants were reported to show an increase in both precise NHEJ and imprecise end joining [12 , 14] , probably because of reduced resection at the break . Consistently , a truncation of xrs2 ( xrs2-664 ) , which eliminates the Tel1-binding domain [22] ( Fig 1B ) , results in an increase in the re-ligation of linearized plasmids in vivo [10] . Using our assay , we confirmed that the tel1Δ mutant had imprecise–end joining activity , which was 2 . 2-fold higher than that of wild-type cells ( Fig 1D ) . Because the tel1Δ mutant was quite similar to these xrs2 FHA mutants with respect to the frequency of imprecise end joining , we then examined the relationship between the two deficiencies by scoring imprecise end-joining in the double mutants . The frequencies of imprecise end-joining of tel1Δ xrs2-314M and tel1Δ xrs2-SH mutants were indistinguishable from that of the tel1Δ single mutant ( Fig 1D ) , indicating that the increase in imprecise end joining in the xrs2 FHA and tel1Δ mutants reflects the loss of a single pathway . Interestingly , however , the drop in precise NHEJ frequency in the xrs2 FHA mutants was dominant over the increase observed in the tel1Δ mutant ( Ura+ , Fig 1D ) . We observed a similar result upon loss of Sae2 , which indirectly promotes Ku disassembly from DSBs through its activity in DSB end resection [38] . The imprecise–end joining frequency increased 10-fold over wild type , and the sae2Δ xrs2 FHA double mutants showed a higher level of imprecise–end joining activity than did the xrs2 FHA single mutants ( Fig 1C and 1E ) . The effect on precise NHEJ ( Ura+ ) frequencies showed a dominance similar to that of the xrs2 mutants relative to tel1Δ ( Fig 1D ) . However , the FHA domain of Xrs2 and Sae2 were not entirely epistatic to one another with respect to their effects on imprecise end joining ( Fig 1E ) . We further tested the effects of the yku70Δ mutation in these assays . yku70Δ was dominant over xrs2 FHA mutations and suppressed the abnormal increase in imprecise end joining ( Ura− ) observed in the xrs2 FHA mutants ( Fig 1F ) . In addition , we confirmed that most of the residual imprecise end joining in the yku70Δ xrs2 FHA double mutants was caused by the Ku-independent MMEJ pathway ( S1 Fig ) . yku mutations are also dominant over tel1Δ mutations in imprecise end joining [14] . These results indicate that the increase in imprecise end joining in the xrs2 FHA mutant is probably achieved by the Ku-dependent imprecise–end joining pathway , which also regulates events in the tel1Δ mutant . In our previous study , we showed that the Xrs2 FHA domain functions in NHEJ through an interaction with Lif1 , a component of DNA ligase IV in budding yeast [9 , 10] . This was also confirmed in this assay as a reduced frequency of Ura+ prototrophs , as described above . Interestingly , the xrs2 FHA mutation also suppressed precise NHEJ in the tel1Δ or sae2Δ background , which would most likely have been caused by an interaction defect with Lif1 . To confirm this , we identified two Xrs2-interacting domains in Lif1 and constructed lif1 mutations in each domain , named lif1-SST and -T113A , both of which lose the ability to interact with Xrs2 and compromise C-NHEJ [10] . We checked whether these lif1 mutations allow an increase in imprecise end joining , as observed for the xrs2 FHA-deficient mutant ( Fig 1G ) . However , both lif1-SST and lif1-T113A mutants showed a slight decrease in the frequency of imprecise end joining , as compared with wild type , along with the expected drop in precise NHEJ ( Fig 1G ) . In addition , both lif1-SST xrs2–SH and lif1-T113A xrs2-SH double mutants showed indistinguishable increases in imprecise end joining as compared with the xrs2-SH single mutant ( Fig 1G ) . This confirms that the increase in imprecise end joining detected in the FHA-deficient mutants reflects its interaction with Tel1 , rather than with Lif1 . In contrast , lif1 mutations were dominant over the xrs2-SH mutation in the suppression of precise NHEJ . This indicates that precise NHEJ activity in the FHA-deficient mutants depends on the Lif1 interaction . We next characterized DSB-repair events observed after the induction of non-complementary DSBs . As shown previously [12] , repair products can be classified into five categories ( Fig 2A ) . To distinguish the categories , we determined the junctions of repaired products amplified from Ura− prototrophs after induction of the non-complementary DSBs ( Fig 1A ) . Products in category-A are produced by a Ku- and a DNA ligase IV–independent imprecise pathway [13 , 39] . As expected , 95% of the products recovered in the yku70 mutant belong to category A ( Fig 2B and S1 and S2 Tables ) . This pathway is also called MMEJ in yeast [14] or A-NHEJ in mammalian cells [13] . In contrast , products in categories B–E are Ku dependent- and DNA ligase IV dependent [12] ( S1 Fig and S2 Table ) . In addition , DSB repair products in categories B and C are associated with DSB end-resection , whereas those of categories B and E are mediated by microhomology-dependent annealing to repair non-complementary DSBs ( Fig 2A and 2B , right ) . We analyzed these repair events in xrs2-SH , tel1 kinase-defective ( tel1-KN ) , xrs2-664 , xrs2Δ , and yku70Δ mutants for their effects in these end-joining events . First , we detected an increase in total frequencies for imprecise end joining in tel1-KN and xrs2-664 ( which truncates the Tel1-binding domain of Xrs2 ) mutants as well as in the xrs2-SH mutant ( Fig 2B and S3 Table ) . It is remarkable that the increase in imprecise end joining in these mutants is associated with an increase in Ku- and DNA ligase IV–dependent repair , leading to products of categories B–E ( Fig 2B , left ) . Only the xrs2-SH mutant maintained a high level of repair in category A , a Ku-independent pathway , as did wild-type cells ( 33 . 3 and 31 . 8% , respectively ) ( Fig 2B and S2 Table ) . In contrast , tel1-KN and xrs2-664 mutants showed a substantial reduction in this category to 0 . 8% and 2 . 1% , respectively ( S2 Table ) . This is consistent with a previous report showing that Tel1 function is essential for the Ku-independent MMEJ pathway [11] . In addition , category C products , which would be produced by simple re-ligation between processed ends , were not observed in the xrs2-SH mutant ( <0 . 58% ) . This phenomenon is distinct from that of the xrs2-664 and xrs2Δ mutants . Based on experiments with double mutants , the elevated level of imprecise end joining in xrs2 FHA mutants was sensitive to the yku70 mutation ( Fig 1F , gray bar ) . Sequence analysis revealed that the yku70Δ xrs2 FHA double mutant showed almost the same distribution for each category with the yku70Δ single mutant ( S1 Fig ) . This also indicates that the xrs2 FHA and tel1 mutants promote an unusual Ku-dependent–imprecise end joining pathway ( categories B–E ) . To assess which mechanisms were at work in the different mutants , we next analyzed the assembly of Xrs2 , yKu70 , Tel1 and Sae2 proteins on the HO-induced non-complementary DSB ends at the MAT locus on chromosome III by chromatin immunoprecipitation ( ChIP ) . Quantitative real-time PCR ( qPCR ) was carried out with a primer pair that is 100 base pairs from the DSB site ( Fig 3A ) . First , we examined assembly of mutant Xrs2 proteins at the DSB . We tagged wild-type Xrs2 and Xrs2–SH and Xrs2–314M mutant proteins with 13Myc epitopes at the C terminus , and confirmed normal recruitment of each mutant form following DSB induction ( Fig 3B ) . Next , we examined assembly of the Ku complex at the DSB by using FLAG-tagged yKu70 in wild-type , tel1Δ , xrs2-SH , or xrs2-314M cells . Although FLAG-tagged yKu70 showed a moderate defect both in imprecise end joining and C-NHEJ , these levels of end-joining activity were substantially higher than in the yku70Δ mutant ( S2A Fig ) . We observed a significant increase in yKu70 binding to the DSB ends in the tel1Δ , xrs2-SH and xrs2-314M mutants , compared with wild-type cells at 120 min after DSB-induction ( Figs 3C and S2B ) . In addition , in the xrs2-SH and tel1Δ , Ku-binding signals were detected from 30 min after DSB induction as a same level with that in wild type , and then , they were gradually increased than wild type in accordance of time elapsed ( Fig 3C ) . This indicates persistent binding of Ku at DSBs in the mutants . To determine whether a defect in the DSB resection indirectly affects the Ku removal from the DSB ends , we examined DSB resection in the xrs2 FHA and tel1Δ mutants . We measured DSB end resection at 1600 base pairs from the DSB site ( Fig 3A ) by quantitative amplification of single-stranded DNA ( QAOS ) [40 , 41] ( Fig 3D ) . First , we confirmed that the sae2Δ mutant showed significantly reduced ssDNA production at the DSB ends , as reported [42] . Then we showed that tel1Δ had DSB resection with the same kinetics as did wild type . In contrast , the xrs2-SH mutant showed a slight decrease in ssDNA end production in the initial phase ( 15–120 min ) but showed almost the same amount of resected DSB ends with wild type at 150 min , which is when accumulated yKu70 was observed at the ends ( Fig 3C ) . This argues that Xrs2 works together with Tel1 to evict Ku from DSB ends during DSB resection . As Xrs2 is involved in Tel1 recruitment to the DSB site though its C-terminal region [22] [23] , we examined Tel1 binding at the DSB using FLAG-tagged Tel1 . Interestingly , we detected Tel1 assembly at the DSB in xrs2-SH at wild-type levels and a significant increase in Tel1 binding in the xrs2-314M mutant cells ( Fig 3E ) . This was distinct from the effect of the xrs2-664 mutant , which lost Tel1 binding ( Fig 3E ) , as previously reported [23] . This result indicates that the xrs2 FHA mutation does not affect Tel1 recruitment to DSBs . As it is known that Tel1/Mec1 phosphorylation is required for Sae2 function [43–45] , we examined Sae2 recruitment using C terminally HA-tagged Sae2 , but there was no difference between the wild-type recruitment and that in the xrs2 FHA mutants ( Fig 3F ) . This argues that FHA function of Xrs2 is not necessary for Sae2 binding at DSB sites . We conclude that Xrs2 FHA function does not affect the initial recruitment of Tel1 kinase to DSBs yet is responsible for removing Ku from the DSB ends . This was also observed in tel1 mutant cells . We proposed that the Xrs2-FHA domain specifically supports Ku-removal by maintaining high Tel1 activity at DSB ends . We demonstrated that the FHA domain of Xrs2 is related to the function of Tel1 in imprecise NHEJ suppression but not to its recruitment to DSB sites . To understand the function of the FHA domain of Xrs2 in a Tel1-dependent DDR pathway , we analyzed γIR sensitivity in the xrs2 mutant cells . As reported previously [4] , a mec1Δ mutant showed severe sensitivity to γIR because of defects in the DDR . In contrast , a Tel1-defective mutant did not show similar sensitivity ( Fig 4A ) . This is because the Mec1-dependent pathway is the major pathway for survival in budding yeast after irradiation rather than the Tel1-dependent pathway [4] . rad50S and sae2Δ mutations , which have a defect in the initiation of DSB resection , can change the biased dependency on Mec1 by activating the Tel1 pathway through suppression of ssDNA production at broken ends [4 , 42] . Thus , the rad50S mutation suppresses the radiation sensitivity of mec1 mutant cells [4] . Consistently , the mec1 rad50S double mutant was 150-fold more resistant than mec1Δ alone to 500 Gy of γIR ( Fig 4B ) . We then examined whether the Xrs2 FHA domain plays a role in the DDR relative to γIR sensitivity . xrs2-SH is not sensitive to γIR [22] , which we confirmed here; we also confirmed that rad50S mutant cells were only slightly sensitive to high doses of γIR ( Fig 4A ) . Like rad50S mec1Δ , the mec1Δ xrs2-SH double mutant was 5 . 5-fold more resistant than mec1Δ alone to 500 Gy of γIR , indicating that the FHA mutation partially suppresses the DDR defect in mec1Δ . This suppression by xrs2-SH was less than that achieved with rad50S , however ( Fig 2A and 2B ) . This suggests that xrs2 FHA mutations may be able to change the biased dependency on Mec1 although activation of Tel1 might be incomplete . MEC1 is an essential gene in budding yeast , but mec1Δ cells grow in the presence of the sml1 mutation [46] . Interestingly , rad50S also suppresses mec1Δ lethality presumably by activating the Tel1 pathway , even in the absence of sml1Δ [4] ( Fig 4C , upper ) . Similarly , we found that the xrs2-SH mec1Δ double mutant was able to grow in the absence of the sml1Δ mutation , forming smaller but viable colonies ( Fig 4C , lower ) . These results indicated that loss of the Xrs2 FHA domain suppresses γIR sensitivity in mec1Δ sml1Δ mutants and suppresses the lethality of the mec1Δ mutation . It remains to be tested whether this was through Tel1 recruitment or activation or through another pathway . Tel1 activity in vivo depends largely on Xrs2 , because of the physical interaction of Tel1 with a domain located in the C terminus of Xrs2 [23 , 47] . Consistently , xrs2-664 [22] did not show sensitivity to γIR even in a tel1Δ background ( Fig 4D ) . Eliminating the Mec1 pathway in xrs2-664 mutants , in contrast to xrs2-664 tel1Δ mutant cells , showed a severe loss of viability after irradiation , much like the mec1Δ tel1Δ double mutant ( Fig 4D ) . In contrast to xrs2-664 , the xrs2-SH mutation partially suppressed the mec1Δ defect , as described above ( Fig 4B ) . Like the mec1Δ rad50S xrs2-664 triple mutant , the mec1Δ rad50S xrs2-SH triple mutant was more sensitive to γIR than the mec1Δ rad50S double mutant ( Fig 4B and 4D ) . Moreover , the rad50S mutation was not able to suppress the hypersensitivity of the mec1Δ xrs2-SH double mutant , especially at high doses of γIR ( Fig 4B ) . This indicates that the rad50S-dependent suppression of mec1Δ hypersensitivity to γIR requires the FHA function of Xrs2 , again acting most likely through Tel1 activation but not through the suppression of DSB processing in the rad50S mutation . We conclude that the Xrs2 FHA domain activates Tel1 , although its function is distinct from that of the Tel1-binding domain of Xrs2 . The Mec1-dependent pathway dominates the Tel1-dependent pathway in wild-type cells , but the Tel1 pathway will be equally activated in the rad50S mutant [4] . We hypothesized that this activation requires the Xrs2 FHA domain ( Fig 4E ) [40] . To test this hypothesis , we next examined DDR activity in the xrs2 FHA mutant cells by monitoring Rad53 activation . Rad53 is a downstream mediator kinase of the yeast DDR pathway and is a phospho-target of Mec1 and Tel1 [48 , 49] . We treated yeast haploid cells in vegetative growth with the DSB-inducing compound phleomycin and analyzed the Rad53 phosphorylation status by Western blotting at the indicated time points ( Fig 5A ) . We detected step-wise accumulation of multiple slower-migrating signals , which correspond to different phosphorylated forms of Rad53 , with robust phosphorylation achieved by 120 min in wild-type , xrs2-SH and rad50S cells ( Fig 5A ) . We also detected an initial phosphorylation of Rad53 at 15 minutes after phleomycin addition and secondary phosphorylations events after 60 min in mec1Δ rad50S mutant cells . In the mec1Δ rad50S xrs2-SH triple mutant , the initial phosphorylation was also observed with the same timing as in the mec1Δ rad50S double mutant , but accumulation of secondary phosphorylation was delayed ( Fig 5A ) . This indicates that the FHA domain of Xrs2 is not required for the initial step of Rad53 phosphorylation , although it is required for its robust activation in DDR signaling . To clarify the FHA function in Tel1 activation , we analyzed the recombination checkpoint during meiosis in the xrs2 FHA mutant . During meiosis , the rad50S mutation causes a complete block of DSB end resection because of the inability to remove covalent bonds between Spo11 and the DSB end; this leads to a Tel1-dependent delay in meiosis I entry [4 , 50 , 51] . In contrast , highly resected meiotic DSBs accumulate in dmc1Δ cells , provoking a Mec1-dependent arrest in prophase I [4 , 52] . First , we examined the effects of the xrs2 FHA mutation on progression meiosis I in the rad50S background . We observed that only 4 . 7% of the cells passed meiosis I in rad50S mutant cells after a 6-hr incubation in sporulation medium ( SPM ) , which was substantially lower than that in wild type ( 49 . 1% , Fig 5B , left ) . The delayed entry into meiosis I in rad50S mutant cells was suppressed by the tel1Δ mutation , as reported previously [4] , and a similar effect was observed with the xrs2-664 mutation , reflecting the loss of Tel1-binding ( Fig 5B , right ) . The rad50S xrs2-SH mutant cells also showed progression through meiosis I , with 39% having completed meiosis I after 6 hr in SPM , almost like wild-type cells ( Fig 5B , left ) . This suppression was also observed in other FHA truncation mutants , namely xrs2-314M , xrs2-228M and xrs2–84M ( S3A Fig ) , even with the different level of accumulation of un-resected DSBs in the rad50S background , which is caused by different amounts of Xrs2 protein [22] . Moreover , the xrs2-664/xrs2-SH heterozygotic diploid suppressed the delayed entry into meiosis I in the rad50S background ( S3B Fig ) , indicating that the two alleles in xrs2 do not complement each other through an intermolecular interaction . In contrast , the xrs2-SH mutation did not suppress prophase arrest in dmc1Δ ( Fig 5C ) , which is Mec1-dependent , indicating that the function of the FHA domain of Xrs2 is not required for Mec1 activation . A meiosis-specific axis component of the synaptonemal complex , Hop1 , is phosphorylated at T318 by both Mec1 and Tel1 [53] . To monitor Tel1 activity , we thus analyzed Hop1 phosphorylation at Hop1-T318 by using an antibody specific for phospho-T318 in the rad50S background ( Fig 5D and 5E ) . On Western blots , disappearance of Hop1 phosphorylation was delayed in rad50S ( Fig 5D , pT318 asterisk ) , and the timing of T318 de-phosphorylation corresponded to the timing of the meiosis I transition ( Fig 5B ) . The xrs2-SH mutation compromised Hop1-T318 phosphorylation when it was combined with rad50S , yet the level of phosphorylation was higher than that with the tel1Δ or xrs2-664 mutations ( Fig 5D , pT318 asterisk ) . Then we examined the localization of Hop1-pT318 on meiotic nuclear spreads after 4 hr in meiosis . In the rad50S single mutant , Hop1-T318 phosphorylation was observed as punctate foci on elongated Hop1 structures ( Fig 5E ) . Although we observed normal Hop1 staining , only a few Hop1-T318 phosphorylation signals were observed in the rad50S xrs2-SH double mutant , similar to the staining in rad50S tel1Δ and rad50S xrs2-664 cells . In contrast , in the xrs2-SH single mutant , Hop1-pT318 staining was indistinguishable from that of the wild-type cells ( Fig 5E ) . This result suggests that FHA domain of Xrs2 is required especially for phosphorylation of chromatin bound Hop1 or maintains phosphorylated Hop1 at DSB sites . Finally , these results indicated that the FHA domain of Xrs2 is dispensable for the initial activation of Tel1 in the presence of DSB ends but it is required for its robust , prolonged activation , during both mitosis and meiosis .
We previously demonstrated that mutations in the FHA domain of XRS2 cause defects in the rejoining of the ends of a linearized plasmid and in the repair of HO-induced ( complementary ) DSBs by binding the C-terminal region of Lif1 [10] . These events correspond to precise NHEJ in vivo . Here we showed that the Xrs2 FHA domain is involved in the suppression of imprecise end joining and , some extent , in the removal of Ku . Taken together , these results indicate that the fidelity of end-joining reactions is compromised by mutation of the Xrs2 FHA domain . Interestingly , mutation of the FHA domain leads to a defect in C-NHEJ [9 , 10] but did not affect Ku-dependent imprecise end joining ( Fig 2B ) . This indicates that Ku-dependent imprecise end joining is genetically distinguishable from C-NHEJ . Nijmegen breakage syndrome in humans is caused by truncation of the N-terminal region , which contains FHA domain , of Nbs1 , an ortholog of Xrs2 . These patients exhibit a high risk of cancer , as well as immunodeficiency , which often results from a defect in the class switch recombination pathway [54] . In addition , activation of ATM , the human ortholog of Tel1 , is required for AID/APE1 activation during class switch recombination [55] . Our work thus contributes to the understanding of this lethal human disease , which arises from alternative end-joining reactions . We have demonstrated that function of the Xrs2 FHA domain is needed for robust activation of Tel1 and for maintaining this activity during the DDR ( Fig 5 ) . However , the proper recruitment of Tel1 to a DSB site requires the Tel1-binding domain in the C terminus of Xrs2 [22 , 23 , 47] . We note that loss of the Xrs2 FHA domain does not impair Tel1 protein recruitment to an HO-induced DSB site , unlike the C-terminal truncation xrs2-664 ( Fig 3E ) . Interestingly , accumulation of Tel1 binding was observed in xrs2-314M but not in the xrs2-SH mutant . The xrs2-314M mutant lacks not only the FHA domain but also the BRCT-like domain ( Fig 1B ) ; it might thus be possible that the BRCT-like domain is involved in regulation of Tel1 stability at DSB ends . In addition , the xrs2-314M mutation produces a high amount of Xrs2 protein [22] . Although recruitment of excessive Xrs2 does not occur because Mre11 limits this step [22] ( Fig 3B ) , free Xrs2 protein might affect Tel1 stability at the DSB ends . Moreover , the FHA domain of Xrs2 is required not only for activation , but also for suppression of Tel1 activity in the mec1Δ background ( Fig 4C ) . Thus , Xrs2 is needed for regulation of Tel1 activation in multiple ways . The Xrs2-Tel1 interaction through the C-terminal domain of Xrs2 is not sufficient for robust activation and maintenance of Tel1 activity; the FHA domain of Xrs2 is required for a second step in Tel1 activation after recruitment . FHA domains are phospho-protein recognition sites [26] . In budding yeast , the FHA domain of Xrs2 interacts with Lif1 and is involved in recruitment of DNA ligase IV complex through the interaction [10] . In the fission yeast , Schizosaccharomyces pombe , the FHA domain of Nbs1 , an ortholog of Xrs2 , interacts with Ctp1 , an ortholog of Sae2 [56] . Similarly , phosphorylation at T90 of Sae2 is involved in its interaction with the Xrs2 FHA domain [57] . We analyzed the mutations of sae2 phosphoacceptor-site ( S4A Fig ) [43 , 58] with respect to the frequency of imprecise end joining . The resulting mutants showed phenotypes that were indistinguishable from that of the sae2Δ mutant , but were quite different from those of the tel1Δ and xrs2 FHA mutants ( S4B Fig , compare with Fig 1C and 1D ) . Thus Sae2 phosphorylation may create an interaction domain for Xrs2-FHA , although it probably also has other roles in repair . We note many of the human FHA domains that are associated with the BRCT domain , including that of Nbs1 , recognize poly ( ADP-ribose ) and are involved in the DNA damage repair process [59]; poly-ADP ribosylation polymerases ( PARPs ) , however , are absent in budding yeast [60] . The Xrs2 FHA domain was also required for robust activation of the Tel1 pathway during meiosis . We note that the initial Mec1 and Tel1 activation is shared between the mitotic DDR pathway and meiotic recombination checkpoint activation , yet the downstream signal transduction partners are quite different [61] . Xrs2 FHA function was not required for the Mec1-dependent pathway in meiosis ( Fig 5C ) . Thus our results indicate that the Xrs2 FHA ligand may be a Tel1-specific target that is shared by the mitotic DDR and meiotic recombination checkpoint process . This could be Sae2 , but there may be other candidates as well . We showed that the tel1Δ mutation was epistatic to the xrs2 FHA mutation with respect to an increase in imprecise end joining . In contrast , dysfunction of precise NHEJ in the FHA mutant results from a defect in the interaction of the DNA ligase IV complex with Lif1 [10] . Lif1 binding by Xrs2 FHA was not , however needed for suppression of imprecise end joining ( Fig 1G ) . Collectively , these results argue that the Xrs2 FHA domain is multi-functional . Thus , in xrs2 FHA mutant cells , addition to the defects in C-NHEJ through DNA ligase IV recruitment , compromised Tel1 activity would cause the abnormal increase of imprecise end joining . We conclude that the enhancement of imprecise NHEJ in the xrs2 FHA mutant is due to a partial defect in Tel1 function . Repair junction sequence analysis revealed that category A , which corresponds to Ku-independent A-NHEJ , was suppressed in xrs2-664 mutant cells as in the tel1-KN cells , indicating that Tel1 recruitment to the DSB site and its kinase activity are essential for A-NHEJ at the DSB ends . The xrs2 FHA mutant , however , only showed only a slight reduction in the frequency of A-NHEJ . This result suggests that robust activation of Tel1 is not essential for A-NHEJ formation . We found that the increase in imprecise end joining in the xrs2 FHA mutant was caused by an increase in Ku-dependent products , corresponding to categories B–E ( Fig 2B , S2 and S3 Tables ) . In addition , we showed that Ku accumulates at HO-induced DSB ends in the xrs2 FHA mutants and also , more importantly , in the tel1Δ mutant , which did not show any defect in DSB end resection ( Fig 3D ) . Therefore , the function of the Xrs2 FHA domain , acting through Tel1 activity , might promote Ku removal from DSB ends during end resection . Ku protein is first recruited to ds-DNA ends and possibly is then translocated to internal sites [7] . The abnormally high persistence of Ku protein or the accumulation of Ku protein at an inner region relative to processed DSB ends may activate incorrect end joining in the mutants through an interaction with Dnl4 [9] ( Fig 6A ) . As previously noted , Tel1 activity is required not only for suppression of imprecise end joining but also for suppression of precise NHEJ [14] ( Fig 1D ) . In contrast , the xrs2 FHA mutant had a defect in precise NHEJ because of a defect in the interaction between Xrs2 and Lif1 . Ku removal thus may be an important function of Tel1 in the initial steps of DDR pathway choice . In vertebrate , another DDR sensor kinase , DNA-PKcs is involved in C-NHEJ and recruited to DSB site with Ku [62] . DNA-PKcs might take charge of the yeast Tel1 function specific to Ku regulation at DSB ends . We envision the DSB repair process as follows: First , Tel1 is recruited to unresected DSB ends in an Xrs2 Tel1-binding domain–dependent manner ( Fig 6B ) . Then , robust activation of Tel1 through the Xrs2 FHA function is promoted at DSB ends ( Fig 6C ) . Phosphorylation of Sae2 by Tel1 and/or Mec1 plays an important role in DSB end resection as an initial step of HR [43 , 44] ( Fig 6D ) . Then , Sae2 and Mre11 promote subsequent Exo1 activity , which is required for extensive resection of DSB ends to facilitate efficient HR [63] . In contrast , Ku complexes compete with Exo1 at this step [63] . The robust activation of Tel1 , which is dependent on the Xrs2 FHA domain , is needed to remove Ku from the processed ends to prevent Ku-mediated end-bridging as well as to allow efficient and extensive resection of DSB ends . If there is no resection needed , the FHA domain of Xrs2 can promote precise NHEJ by interacting with DNA ligase IV and then again it promotes Ku removal to ensure faithful DSB repair ( Fig 6B ) . Given that NHEJ is the dominant mechanism of repair in mammalian cells , this latter pathway may be relevant for understanding how human NBS1 mutations in the FHA domain predispose cells to genomic instability and cancer .
All yeast strains and their genotypes are shown in S1 Table . We used isogenic Saccharomyces cerevisiae W303-1A [64] derivatives for γIR sensitivity determination , SLY19 [11] derivatives for the HO-induced non-complementary DSB rejoining assay and chromatin immunoprecipitation ( ChIP ) assay and the SK1 background NKY1551 [65] derivative for meiotic analysis . Rad53 and Hop1 antibodies were raised against purified recombinant proteins tagged with hexahistidine from Escherichia coli . Anti-Hop1-pT318 phosphospecific antibody was raised against synthesized polypeptide , ASIQPpTQFVSNC , and then , post-immune IgG was affinity purified by using this phosphopeptide and then titrated using a non-phosphorylated peptide , ASIQPTQFVSNC ( custom-made by MBL Co . , Ltd . ) . End-joining activities to repair noncomplementary DSBs and repaired junction sequences were analyzed using SLY19 [11] and its derivatives as described [12] . Briefly , for each assay , a single colony was grown to log phase , and that culture was inoculated into YP-raffinose medium and incubated for 14 hr at 30°C to a concentration of 2 . 5 x 106 cells/ml . Then , galactose was added to a final concentration of 2% ( w/v ) . After an additional 2 . 5 hr incubation , cells were plated on YP-galactose . To quantify the total number of cells , cells were plated in parallel on YPAD plates after appropriate dilutions . For DNA sequencing analysis of repaired junctions , genomic DNA , purified from the cells grown on YP-galactose and shown to be Ura− , was analyzed as described [12] . Each strain was analyzed for γIR sensitivity as described [22] . A Shimadzu Isostron RTGS-21 was used with 60Co as the ionizing radiation source ( Research Institute for Radiation Biology and Medicine , Hiroshima University ) . The ChIP assay was performed as described [12] with minor modifications . Cells grown to mid-log phase in YP-raffinose medium were collected before galactose addition ( DSB– ) and at 150 min after galactose addition ( DSB + ) , and were treated as described [12] . The following antibodies were used for immunoprecipitation: anti-DYKDDDDK tag ( 1E6 , Wako ) for yKu70-3FLAG and 3FLAG-Tel1 , anti-HA ( 16B12 , Covance ) for Sae2-3HA and anti-Myc ( MC045 , Nacalai Tesque ) for Xrs2-13Myc detection . qPCR was performed using the SYBR green system ( SsoFast EvaGreen super mix and Chromo4 , Bio-Rad ) with primer sets at for PHO5 on chromosome II ( control ) and for HO cutting sites ( DSB ) as follows: SLY19 DSB ChIP-f ( 5’-GGCCTTATAGAGTGTGGTCG-3’ ) and SLY19 DSB ChIP-r ( 5’-CAAAAGAGGCAAGTAGATAAGGG-3’ ) . The specific recruitment of protein to HO-induced DSB ends was indicated as the relative ratio to the non-DSB locus ( PHO5 ) control ( DSB/control ) . The y-axis values ( normalized DSB/control ) are the relative ratios of the immunoprecipitation value ( IP ) to the input value ( WCE; whole cell extract ) as follows: Normalized DSB/control = ( ( IPDSB/WCEDSB ) / ( IPControl/WCEControl ) ) . QAOS was performed at non-complementary DSB ends as described [40 , 41] . Genomic DNA samples , which were purified at the indicated time points after HO induction , were used as the template . Primer extension reaction was carried out using a native genomic DNA sample and a heat-denatured DNA sample at 72°C with Taq DNA polymerase ( Ex Taq , Takara Bio ) . qPCR was performed using the SYBR green system ( Fast SYBR green master mix and Step one plus , Applied Biosystems ) with primers for HO1 used in a previous study [41] after ExoSAP-IT ( Affymetrix ) treatment to remove primers from the previous reaction . The percent of ssDNA at the DSB site was calculated as follows: ssDNA % = QAOSnative/QAOSdenatured . Western blotting was performed as described [10] . Primary antibody binding was visualized with Alexa Fluor 680–labeled secondary antibodies ( Molecular Probes ) or IR dye 800–labeled secondary antibodies ( Rockland ) using an Odyssey infrared imaging system ( LI-COR Biosciences ) . Antibodies used in these assays were anti-Rad53 ( this study; rabbit , 1:1000 ) , anti-Hop1 ( this study , guinea pig , 1:1000 ) , anti-Hop1-pT318 ( this study; rabbit , 1:1000 ) and anti-α-tubulin ( MCA77G; AbD Serotec ) . Meiosis time course experiments were performed as described [66] . Meiotic progression was analyzed by counting the number of nuclei in each ascus under an epifluorescence microscope ( Zeiss Axioskop 2 ) after staining with 4' , 6-diamidino-2-phenylindole , dihydrochloride ( DAPI ) . The frequencies of post–meiosis I cells containing two , three and four DAPI-stained bodies were determined . More than 200 nuclei were analyzed for each time point . Immunostaining of yeast meiotic nuclear spreads was performed as described [10] . Stained samples were observed using an epifluorescence microscope ( Zeiss Axioskop 2 ) with LED fluorescence light sources ( X-Cite; Excelitas Technologies ) and a 100× objective ( Zeiss AxioPlan , NA1 . 4 ) . Images were captured with a CCD camera ( Retiga; Qimaging ) and processed using IP lab ( Silicon ) and Photoshop ( Adobe ) . Antibodies used in these assays were anti-Hop1 ( 1:1000 ) and anti-Hop1-pT318 ( 1:500 ) .
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Genomic DNA provides the essential blueprint for life , and therefore living organisms have several mechanisms for maintaining the stability of their own genomes . DNA double-strand breaks ( DSBs ) are one of the most severe forms of DNA damage , which , without precise repair , can provoke a loss of genetic information , leading to tumor formation . DSBs are repaired by two distinct pathways , homologous recombination ( HR ) and non-homologous end joining ( NHEJ ) , which can be precise or imprecise . In addition , the DNA damage response ( DDR ) is essential in the cell to integrate multiple events that need to occur after damage: activation of DNA repair enzymes , selection of repair pathway and control of cell cycle progression , transcription , and so on . Here we show that different domains of Xrs2 , a central DSB repair protein in budding yeast whose human ortholog , Nbs1 , is linked to a human hereditary disorder with a high risk of cancer , is required not only for repair pathway choice but also for full activation of DDR . This result indicates that DSB repair and the DDR are coordinated at multiple levels to ensure precise repair and thus to maintain genomic integrity .
|
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2016
|
The MRX Complex Ensures NHEJ Fidelity through Multiple Pathways Including Xrs2-FHA–Dependent Tel1 Activation
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Control of the differential abundance or activity of tRNAs can be important determinants of gene regulation . RNA polymerase ( RNAP ) III synthesizes all tRNAs in eukaryotes and it derepression is associated with cancer . Maf1 is a conserved general repressor of RNAP III under the control of the target of rapamycin ( TOR ) that acts to integrate transcriptional output and protein synthetic demand toward metabolic economy . Studies in budding yeast have indicated that the global tRNA gene activation that occurs with derepression of RNAP III via maf1-deletion is accompanied by a paradoxical loss of tRNA-mediated nonsense suppressor activity , manifested as an antisuppression phenotype , by an unknown mechanism . We show that maf1-antisuppression also occurs in the fission yeast S . pombe amidst general activation of RNAP III . We used tRNA-HydroSeq to document that little changes occurred in the relative levels of different tRNAs in maf1Δ cells . By contrast , the efficiency of N2 , N2-dimethyl G26 ( m22G26 ) modification on certain tRNAs was decreased in response to maf1-deletion and associated with antisuppression , and was validated by other methods . Over-expression of Trm1 , which produces m22G26 , reversed maf1-antisuppression . A model that emerges is that competition by increased tRNA levels in maf1Δ cells leads to m22G26 hypomodification due to limiting Trm1 , reducing the activity of suppressor-tRNASerUCA and accounting for antisuppression . Consistent with this , we show that RNAP III mutations associated with hypomyelinating leukodystrophy decrease tRNA transcription , increase m22G26 efficiency and reverse antisuppression . Extending this more broadly , we show that a decrease in tRNA synthesis by treatment with rapamycin leads to increased m22G26 modification and that this response is conserved among highly divergent yeasts and human cells .
Apart from their role in translation , tRNAs can regulate gene expression [1 , 2] and serve as metabolic sensors [3] , and their over-expression is associated with cell proliferation and transformation [4 , 5] . RNAP III is activated by oncogenes [6 , 7] whereas its repression reduces transformation and tumorigenesis [8] . Accumulating evidence indicate the importance of matching tRNA activity with mRNA codon demand [9] . Different cells and tissues show differences in tRNA abundances that vary with codon use [1 , 10] . tRNA specific activity for codon-specific decoding can be controlled by posttranscriptional modifications , most notably in the anticodon loop for nucleosides at wobble position 34 and position 37 [2 , 11–14] . Despite RNAP III ubiquity in eukaryotic cells , mutation in one of its catalytic subunits can manifest as a tissue-specific developmental defect in zebra fish [15 , 16] . In humans , mutations in either of the two catalytic subunits lead to a nervous system disorder , hypomyelinating leukodystrophy ( HLD ) and other tissue-specific defects ( [17] and refs therein ) , although how these mutations affect RNAP III transcription and cause disease is unknown . The highly conserved RNAP III repressor , Maf1 , acts in response to stress including lack of nutrient , and in S . cerevisiae , mammals and other species , is under the control of the target of rapamycin ( TOR ) kinase [18 , 19] , which integrates information from several environmental cues and stress states , and functions to sustain growth and homeostasis in various conditions [20] . When Maf1 is nonfunctional , cells produce much increased and unregulated transcription by RNAP III , the energy cost of which is wasted , highlighting a function for Maf1 as a key contributor to metabolic economy [21] . A striking phenotype of S . cerevisiae maf1-mutants is antisuppression [19 , 22] which reflects loss of suppressor-tRNA ( sup-tRNA ) TyrUUA mediated suppression of a nonsense codon in a mRNA encoding an adenine metabolic enzyme . Although described nearly 20 years ago and to date only for S . cerevisiae , maf1-antisuppression is paradoxical because it occurs amidst global increases in tRNA synthesis [19 , 22 , 23] . We deleted maf1+ from S . pombe and also observed antisuppression , in this case by sup-tRNASerUCA , amidst general increases in tRNA levels . We employed a tRNA-enriched limited hydrolysis sequencing method , termed tRNA-HydroSeq , on S . pombe maf1+ , maf1Δ and other strains . While the levels of different tRNAs relative to each other varied little upon maf1+ deletion or over-expression , consistent with global regulation , a sup-tRNASerUCA modification , N2 , N2-dimethylguanosine-26 ( m22G26 ) , was specifically decreased in maf1Δ and shown to be required for efficient suppression . Trm1 is a nuclear enzyme that produces m22G26 which likely contributes to proper tRNA folding [24 , 25] ( see Discussion ) . Trm1 activity is limiting in the context of increased tRNA production in maf1Δ cells and we show that its over-expression reverses antisuppression . Treatment with rapamycin or over-expression of maf1+ reduces tRNA transcription with increase in the m22G26 content of sup-tRNASerUCA and its specific activity for suppression . We also introduced mutations in a catalytic subunit of RNAP III associated with hypomyelinating leukodystrophy ( HLD ) to show that a general decrease in tRNA transcription by another mechanism also increases m22G26 modification efficiency and reverses antisuppression in S . pombe . The results establish a link between RNAP III activity , tRNA production and Trm1 modification activity that impacts tRNA function . We show that this response is conserved , as deletion of MAF1 from S . cerevisiae is also accompanied by m22G26 hypomodification , and maf1-antisuppression is reversed by over expression of TRM1 . Finally , we show that human cellular tRNA m22G26 modification efficiency increases with serum starvation or rapamycin treatment and decreases following serum stimulation .
Unlike for all other species examined , S . pombe is naturally resistant to the growth inhibitory effect of rapamycin [26] . Thus , it was important to determine if maf1+ regulates tRNA production in S . pombe and if it does so under TOR control . We created a maf1-deletion strain and showed that it lacked maf1+ mRNA relative to wild type ( WT; Fig 1A , WT/vector vs . maf1Δ/vector ) . Ectopic over-expression of plasmid-borne maf1+ in maf1Δ increased maf1+ mRNA about 4-fold relative to endogenous maf1+ in WT cells ( Fig 1A ) . Levels of tRNAAlaUGC and tRNASerGCU were increased in maf1Δ relative to WT but decreased relative to WT when maf1+ was over expressed ( Fig 1B ) . Quantitation of these tRNAs relative to U5 snRNA , a RNAP II transcript on the same blot , from triplicate cultures on triplicate blots revealed that three levels of maf1+ expression led to three levels of tRNA expression ( Fig 1C ) . We analyzed the effect of the TOR inhibitor , rapamycin on maf1Δ cell growth . Deletion of tit1+ , encoding the tRNA isopentenyltransferase ( MOD5 homolog , see below ) , which forms i6A37 on some tRNAs , is known to cause sensitivity to rapamycin [14] and served as a control ( Fig 1D ) . In media lacking rapamycin , these strains exhibited relatively similar growth ( Fig 1D , upper panel ) . While the control tit1Δ was sensitive to rapamycin , maf1Δ was insensitive ( Fig 1D , lower panel ) . By contrast to maf1Δ , the cells over-expressing maf1+ were sensitive to rapamycin ( Fig 1D , lower ) . To test whether S . pombe maf1+ regulates RNAP III in response to rapamycin , we analyzed tRNA from triplicate cultures of cells in logarithmic growth to which rapamycin was added and incubated for an additional hour . The northern blot in Fig 1E compares maf1Δ and maf1+ cells using probes to three tRNAs and control U5 RNA . In maf1+ cells , rapamycin decreased precursor and mature tRNA species relative to DMSO treatment while U5 was unchanged ( Fig 1E , lanes 1–3 vs . 4–6 ) . maf1Δ cells showed higher levels of tRNAs relative to maf1+ ( Fig 1E , lanes 1–3 vs . 7–9 ) . Rapamycin did not reduce tRNA levels in maf1Δ cells ( Fig 1E , lanes 7–9 vs . 10–12 ) . This established that the ability of S . pombe to repress tRNA production in response to rapamycin is dependent on maf1+ , as in other species . In addition , we conclude that maf1+ over-expression causes slow growth and rapamycin sensitivity , likely due at least in part , to decreased tRNA production . tRNA-mediated suppression ( TMS ) of adenine synthetic genes prevents accumulation of a red pigmented metabolic intermediate and is useful for studying biogenesis and activity of sup-tRNAs ( reviewed in [27] ) . Because all yeast tRNA genes including sup-tRNAs share similar promoters , and maf1-mutants are expected to activate RNAP III globally , maf1-antisuppression has been an unexplained paradox [22 , 23] . S . cerevisiae Maf1 was noted to affect cellular localization of Mod5 which carries out i6A37 formation , leading to the possibility that sup-tRNA i6A37 hypomodification is responsible for maf1-antisuppression [19] . We examined TMS in S . pombe maf1Δ , tit1Δ and wild-type ( WT; tit1+ , maf1+ ) strains all of which contain the opal suppressor sup-tRNASerUCA and the opal suppressible allele , ade6-704 . On limiting adenine , maf1Δ exhibited antisuppression relative to WT , similar to tit1Δ [28] ( Fig 2A , Ade10 ) . Significantly , over-expression of maf1+ in maf1Δ not only reversed antisuppression , it caused more suppression than in WT ( Fig 2A , Ade10 ) . Thus as RNAP III activity decreases from high to intermediate to low , sup-tRNASerUCA-mediated TMS activity goes in the opposite direction , from low to intermediate to high . As noted , i6A37 hypomodification was suggested to cause maf1-antisuppression [29 , 30] . Availability of methods to monitor i6A37 on total tRNAs and on specific tRNAs allowed us to test whether maf1+ deletion led to decreased i6A37 . Three tRNAsSer that decode serine UCN codons comprise the major i6A37-tRNA component in S . pombe while the shorter length tRNATyr and tRNATrp comprise a minor component [28] . Midwestern blotting using anti-i6A antibody [31] showed that the i6A37 content of tRNA differed only slightly among the strains ( Fig 2B ) . No signal was observed with this antibody in tit1Δ as expected [28] . The blot was also hybridized with an oligo-DNA probe complementary to U5 RNA as a control ( lower panel ) . To examine i6A37 levels in sup-tRNASerUCA , we used a PHA6 assay ( positive hybridization in the absence of i6A37 modification ) in which the northern blot signal intensity increases as i6A37 content decreases because the isopentenyl modification interferes with annealing of a probe targeted to the ACL ( anticodon loop ) , while a 'body' probe to the pseudo-U stem loop of the same tRNA serves as an internal control [14 , 28 , 32] . The EtBr stained gel in the upper panel of Fig 2C was blotted , probed , stripped and rehybridized with probes to the RNA species indicated to the right of the other panels . Specificities of the sup-tRNASerUCA ACL and body probes were revealed by paucity of signal in lanes 1 and 2 representing a strain that lacks the sup-tRNASerUCA allele . The ACL probe detected relatively high levels of sup-tRNASerUCA in tit1Δ as expected , reflecting lack of the i6A37 modification , but relatively low levels in maf1Δ and WT reflecting efficient i6A37 modification . A similar pattern of ACL vs . body probe signal was observed in WT , tit1Δ and maf1Δ , for endogenous tRNASerUGA which also carries i6A37 [28] . Quantification of sup-tRNASerUCA i6A37 modification efficiency for duplicate samples revealed that it was comparable in maf1Δ and maf1+ WT cells ( Fig 2D ) . We also quantified steady state levels of the tRNAs as monitored by their body probes relative to the U5 control , which confirmed that both were elevated in maf1Δ relative to maf1+ cells ( Fig 2E ) . The cumulative data suggest that deletion of maf1+ leads to a decrease in the specific activity of sup-tRNASerUCA for TMS while over-expression of maf1+ increases its specific activity for TMS . However , the decrease in sup-tRNASerUCA activity in the maf1Δ strain is not due to i6A37 hypomodification . Limitations to high throughput sequencing of tRNAs include inefficient adapter ligations due to secondary structure as well as the multiple modifications that cause reverse transcriptase to pause at each , processively diminishing generation of full length sequence reads . Recent advances have overcome some of the limitations by removing a subset of the blocking modifications by pre-treatment with specific demethylases and/or by use of highly processive thermostable reverse transcriptase [33 , 34] . Another approach used limited alkaline hydrolysis of total RNA and subsequent mining of reads corresponding to tRNAs [35] . Thus , by generating 19–35 nt hydrolysis products followed by adapter ligation , each fragment will have less potential to form secondary structures and significantly fewer modifications for reverse transcriptase to get past ( S1 Fig ) . We introduced a modification to the Karaca et al . method [35]; namely , purification of tRNA prior to hydrolysis . This was followed by adapter ligation to the fragments , reverse transcription , PCR amplification , and sequencing using Illumina HiSeq technology ( S1 Fig ) . S . pombe contains 171 tRNA genes that produce 61 unique tRNA sequences comprising 45 anticodon identities ( S1 Table ) . Although multicopy tRNA genes encode identical mature tRNAs they typically differ in the precursor sequences of 5’ leader , 3’ trailer and/or intron if present [36] . By this account , 150 of the 171 tRNA genes are unique . Sequence reads were first mapped to a reference list representing the 61 unique mature tRNA sequences . The remaining reads were then aligned to a reference list representing the 150 unique precursor-tRNA gene sequences . The total read counts listed in S1 Table provides evidence for expression of all of the tRNA genes in S . pombe . Quantitation using DEseq [37] revealed good correlations of the tRNA expression profiles from WT , maf1Δ and maf1Δ+maf1+ cells ( Fig 3A ) . This would be expected of Maf1 as a global regulator of RNAP III ( Discussion ) . tRNA-HydroSeq data included high levels of nucleoside misincorporations at specific positions in specific tRNAs . An example for tRNASerUGA using the IGV display tool is shown in Fig 3B; grey bars indicate match to genomic sequence and colored bars reveal positions at which mismatch was ≥15% as set by IGV . These positions were previously noted to undergo base modifications associated with misincorporation by reverse transcriptase [38] . Modifications of this type disrupt potential for hydrogen bonding and normal base pairing ( S2A Fig ) . We saw no misincorporation at i6A37 , as this modification would preserve the potential of adenine for hydrogen bonding ( S2B Fig ) , consistent with prior observations ( see [39] ) . Misincorporations observed at G9 , G26 , C32 and A58 occurred in tRNAs known to carry m1G9 , m22G26 , m3C32 and m1A58 in yeast and/or other species as well as at position 34 for the eleven tRNAs with encoded A34 , consistent with their deamination to inosine ( I ) [40 , 41] ( S3 Fig ) . G26 is modified by N2 , N2-dimethylation ( m22G26 ) in many tRNAs by the Trm1 methyltransferase [42] . Of the 36 tRNAs in S . pombe that have G26 , 27 showed significant misincorporation ( ≥10% ) at G26 ( Fig 3C ) . The extent of G26 misincorporation varied with tRNA identity from 10–80% ( Fig 3C ) . Biochemical studies of S . cerevisiae Trm1 identified determinants of modification including length of the variable loop [43] . Consistent with those data , we found that G26 tRNAs with variable loops of <5nt ( e . g . , GlyGCC , GlnTTG , GlnCTG , Fig 3C ) showed very low misincorporation . These and data described below suggest that the nine G26 tRNAs with misincorporations of ~1% are not Trm1 targets and reflect background ( Fig 3C ) . To confirm that G26 misincorporations are due to m22G26 modification , we deleted trm1+ from its genomic locus and examined misincorporation . The heat map in Fig 3D shows that G26 misincorporations were decreased to ≤1% in trm1Δ cells , demonstrating that they are due to m22G26 . Notably , expression of trm1+ from a high copy plasmid in trm1Δ cells restored the misincorporations to higher levels than in WT cells ( Fig 3D ) . This suggested that a significant amount of Trm1 substrates are not fully modified in WT cells because Trm1 activity is limiting . Comparative analysis of all tRNAs at all positions in WT , maf1Δ and maf1Δ+maf1+ cells revealed that misincorporation levels at G26 were specifically altered in Trm1 target tRNAs in response to three levels of maf1+ expression in a manner that positively correlated with TMS ( Fig 4A , G26 panel , compare with Fig 2A ) . Misincorporations detected at G9 , A34 and A58 , reflecting m1G9 , I34 and m1A58 , did not vary with maf1+ expression ( Fig 4A ) . The specific correlation of G26 misincorporations with three levels of maf1+ expression and TMS also fits with the finding that Trm1 , which appears limiting for G26 modification in WT cells ( Fig 3D ) may become more so as tRNA levels increase in maf1Δ cells , and as shown below , m22G26 is required for suppressor activity . To more directly link m22G26 to Maf1 and its effects on suppression phenotype , we followed three tacks . First , we analyzed sequence reads that uniquely mapped to the sup-tRNASerUCA for G26 misincorporation in WT , maf1Δ and maf1Δ+maf1+ cells ( Fig 4B ) . The Sup-tRNASerUCA G26 misincorporations in the three strains reflected the general pattern for the larger subset of Trm1 targets ( compare Fig 4A , G26 panel and Fig 4B ) . An antibody raised against a C-terminal peptide of S . pombe Trm1 was used to examine Trm1 levels . This revealed no significant difference in Trm1 levels in maf1Δ and WT cells ( Fig 4C ) . The data support a model in which as Trm1 substrates increase with elevated RNAP III activity in maf1Δ cells , the efficiency of m22G26 modification decreases presumably because a limiting supply of Trm1 cannot keep up with the increase in substrate , and TMS decreases leading to the antisuppression phenotype . A second tack was to monitor changes in G26 modification levels by an approach other than tRNA-HydroSeq . We devised a northern blot probing method to monitor G26 modification that we refer to as the PHA26 assay ( positive hybridization in the absence of G26 modification ) . Since m22G26 modification debilitates normal base pairing [39] , we expected it to inhibit annealing of a short probe , designated D-AC stem , to this region of a tRNA while a probe to the variable arm-T loop region of the same tRNA would serve as internal control ( Fig 4D ) . As proof of the PHA26 assay method , the D-AC stem probe showed high signal in trm1Δ cells but was decreased upon over-expression of trm1+ ( Fig 4E , tRNALeuCAA , D-AC stem; compare lanes 5 & 7 ) . Although tRNALeuCAA is not as differentially modified in WT , maf1Δ , and maf1Δ+maf1+ , as is the sup-tRNASerUCA , it does reflect some differential m22G26 modification ( Fig 4E , D-AC stem vs . T-loop , lanes 1–4 ) . This differential pattern was also seen for tRNALeuTAG ( Fig 4E , lanes 1–4 ) ; quantification of T-loop/D-AC stem signal is expressed as a modification index , in this case relative to lane 1 , below the lanes for each tRNA ( Fig 4E ) . Significantly , over-expression of trm1+ in maf1Δ decreased the D-AC stem probe signal ( Fig 4E , compare lanes 2 & 4 ) demonstrating that Trm1 activity is limiting in maf1Δ cells . PHA26 confirmed that the m22G26 content of tRNALeuTAG is lower than for tRNALeuCAA ( Fig 4E compare with Fig 3C ) . Moreover , PHA26 also suggested that tRNALeuTAG is not as ideal a substrate for trm1+ over-expression as compared to tRNALeuCAA ( Fig 4E , compare both tRNAs , lanes 6 & 7 , and see below ) . A third and most key approach was to determine if Trm1 is limiting for suppression in maf1Δ by over-expressing it and assaying for TMS . Deletion of trm1+ from our WT strain caused antisuppression ( Fig 4F ) . This demonstrated that m22G26 modification is required for the suppressor activity of sup-tRNASerUCA , confirming results in S . pombe with an ochre sup-tRNASerUUA [44] . Most relevantly , over-expression of trm1+ in maf1Δ led to substantial reversal of the antisuppression phenotype in the context of elevated tRNA levels in these cells ( Fig 4F ) . From this we can conclude that m22G26 hypomodification due to limiting Trm1 in maf1Δ is a determinant of antisuppression in S . pombe . Thus , changes in RNAP III activity inversely impact m22G26 modification and the functional specific activity of sup-tRNASerUCA with consequent phenotype . We wanted to ask if a decrease in RNAP III activity by a Maf1-independent mechanism would also affect functional G26 modification . RNAP III is a conserved enzyme whose two largest subunits , Rpc1 and Rpc2 , form the catalytic center while other subunits serve supportive and regulatory functions ( reviewed in [45] ) . Certain point mutations in Rpc1 and Rpc2 cause hypomyelinating leukodystrophy ( HLD ) , a tissue-specific developmental disorder , although if they might affect global tRNA transcription has not been reported [46] . Since most of these mutations affect residues invariant from yeast to humans , we introduced them into S . pombe RNAP III and examined activity after over-expression in vivo . S . pombe RNAP III had previously been used to characterize molecular defects of a zebra fish rpc2/polr3b-mutant , slimjim that exhibits a tissue-specific phenotype [15 , 16] . We examined two HLD mutations in Rpc1 , D366N in the catalytic center , and V891N at a critical interface with the Rpb5 subunit [45] , along with unmutated WT Rpc1 , in S . pombe . We assessed their effects on nascent precursor-tRNA levels , which are widely used to compare RNAP III transcription rates ( reviewed in [47] ) . By this measure , Fig 5A showed for the three tRNA genes examined that the mutations reduced RNAP III transcription relative to WT Rpc1 . According to the model proposed here , as RNAP III activity decreases , reduced amounts of pre-tRNA substrates would better meet the limited supply of Trm1 , and their modification efficiency , i . e . , the mole fraction of a mature tRNA bearing m22G26 , would increase . In agreement with this , tRNA-HydroSeq shows significantly more G26 misincorporation in both Rpc1 mutants relative to WT ( Fig 5B ) . This was confirmed by the PHA26 assay , which showed lower D-AC stem probe signal in the Rpc1 mutants relative to Rpc1-WT ( Fig 5C , lanes 1–3 ) . The Rpc1 mutations also led to m22G26 hypermodification in maf1Δ ( Fig 5C , lanes 4–6 ) . Moreover , both Rpc1 mutants robustly reversed antisuppression in the maf1Δ strain relative to wild-type Rpc1 and also increased TMS in WT cells ( Fig 5D ) . These data strengthen the model . As noted above , rapamycin induces nutrient-related stress through the TOR pathway . We examined effects of differing nutrient on m22G26 modification and TMS . tRNA-HydroSeq was performed on wild-type ( WT ) S . pombe cells grown in minimal ( EMM ) and rich ( YES ) media , the latter known to support faster growth , and in EMM in which trm1+ was over-expressed . Total G26 misincorporations in Trm1 targets were higher in YES relative to EMM , comparable to cells over-expressing trm1+ in EMM ( Fig 6A ) . Examination of individual tRNA G26 misincorporations in minimal ( EMM ) and rich ( YES ) media yielded intriguing results . Although some of the greatest increases were in tRNAs that were largely hypomodified in EMM , the response was nonuniform ( Fig 6B ) . Most strikingly was that a very similar pattern of increased misincorporation was observed for cells in YES and when trm1+ was over-expressed in EMM ( Fig 6B ) . This nonuniform response would appear to reflect individualized substrate-specific responses to an increase in Trm1 activity ( Discussion ) . The nine G26 tRNAs that showed no misincorporation in EMM ( ≤0 . 05 ) also showed no significant increases in misincorporation in YES or with trm1+ over-expression , providing more evidence that these are not substrates for m22G26 modification , non-targets of Trm1 ( Fig 6B ) . The increases in G26 misincorporation in WT cells grown in rich ( YES ) relative to minimal ( EMM ) media were greater for some tRNAs than others , and this was especially so for tRNAThrCGT ( Fig 6B ) . The PHA26 assay was used to validate this by comparing tRNAThrCGT m22G26 content in YES and EMM . Fig 6C showed that the D-AC stem probe signal for tRNAThrCGT was much lower in YES vs . EMM , while the T-loop probe yielded similar signals , indicating a relatively high level of m22G26 modification in the rich ( YES ) media . By contrast , tRNAGlnCTG in YES and EMM showed near equal reactivity with its D-AC stem and T loop probes ( Fig 6C ) . To gain insight into a potential mechanism controlling the differential m22G26 modification levels in minimal and rich media , we examined Trm1 levels in extracts from the WT cells grown in YES and EMM and the trm1+ over-expressing cells in EMM by western blotting using tubulin on the same blot as a loading control ( Fig 6D ) . Surprisingly , this showed similar levels of endogenous Trm1 in extracts from cells in grown in YES and EMM ( Fig 7D , lanes 1 , 2 ) . The over-expressed 3X-FLAG-tagged Trm1 was observed as a slower migrating band in lanes 3 and 4 indicated to the right of Fig 6D . Quantification using Odyssey infrared imaging revealed that the 3X-FLAG-Trm1 accumulated to about 4-fold higher than endogenous Trm1 in the same cell extracts ( lanes 3 , 4 ) . We conclude that while m22G26 modification efficiency differs dramatically in EMM and YES this is not reflected by Trm1 polypeptide levels detectable by western blotting , whereas over-expression of Trm1 is readily observed . We next reasoned that rapamycin , which induces a nutrient-related stress response that includes RNAP III repression [48] , would lead to increases in m22G26 modification efficiency and TMS . As alluded to above , the yYH1 ( WT; maf1+ trm1+ ) strain is partially suppressed relative to a wild-type ade6+ allele strain and can therefore reveal an increase or decrease in TMS ( [27] and refs therein ) . Fig 6E shows that while our WT strain is less suppressed relative to ade6+ but more suppressed than maf1Δ in the absence of rapamycin , its suppression increases relative to maf1Δ in the presence of rapamycin . Thus , rapamycin led to an increase in sup-tRNASerUCA-mediated suppression in maf1+ but not in maf1Δ or trm1Δ cells . Western blotting showed that Trm1 levels were comparable in the rapamycin and control ( DMSO ) treated WT ( maf1+ ) cells ( Fig 6F ) . The PHA26 assay showed a lower ratio of D-AC stem to T-Loop signal for tRNALeuCAA in WT ( maf1+ ) cells treated with rapamycin relative to no rapamycin whereas no difference in D-AC stem signal was observed for the maf1Δ cells ( Fig 6G ) . This reflected significant increase in m22G26 modification efficiency specific to rapamycin treated WT ( maf1+ ) cells . As expected , maf1Δ cells showed no response to rapamycin in the assay for sup-tRNASerUCA activity , TMS ( Fig 6E ) , or in m22G26 modification efficiency ( Fig 6G ) . S . cerevisiae MAF1 WT and maf1Δ cells were compared for tRNATyr m22G26 content by PHA26 ( Fig 7A ) . The quantitative modification index revealed 2-fold hypomodification in maf1Δ relative to WT ( MAF1 ) ( Fig 7A , mod index under lanes ) . Ectopic expression of TRM1 in S . cerevisiae maf1Δ cells carrying the SUP11 ochre suppressor-tRNATyrUUA and the ochre-suppressible ade2-1 allele led to significant reversal of the maf1-antisuppression phenotype ( Fig 7B ) . We also examined m22G26 modification efficiency in human embryonic kidney ( HEK ) 293 cell tRNAs in response to serum starvation ( Fig 7C , lanes 1–3 ) and treatment with rapamycin ( Fig 7D ) , both of which repress RNAP III and cellular proliferation [49] . In both conditions the m22G26 content of tRNAAsnGTT increased as reflected by the modification index ( Fig 7C lanes 1–3 , D ) . For the experiment in Fig 7C , after serum was added back to the serum-starved cells , their tRNAAsnGTT became less modified ( Fig 7C , compare mod index , lanes 3 & 4 ) . These results collectively indicate that the relationship between RNAP III activity and tRNA m22G26 modification efficiency has been conserved through evolution .
It is interesting that S . pombe cells in rich media harbor enough Trm1 activity for high efficiency m22G26 modification . However , although m22G26 modification efficiency was significantly higher in rich relative to minimal media ( Fig 6B ) , the levels of Trm1 protein in rich and minimal media were similar ( Fig 6D , lanes 1 , 2 ) , suggesting that Trm1 activity may be stimulated during growth in rich media by a posttranslational mechanism . All tRNAs share features that allow recognition by RNase P , RNase Z , and certain other enzymes , but each also harbors features that must contribute to their unique identity . The wide range of m22G26 modification efficiency seen in Figs 3C and 6B is consistent with a hierarchical substrate preference of Trm1 . Analysis in EMM and YES indicate increased m22G26 modification efficiency in the latter , more strikingly for some tRNAs than others , and this pattern was mimicked by over-expression of Trm1 . These data would appear to reflect a relationship between Trm1 and the distinctive specificities of its many substrates , consistent with biochemical studies [43] , but illustrated here for a wide range of unique cellular tRNAs on a tRNAomics-wide scale . S . cerevisiae TRM1 exhibits genetic interactions with a number of genes including ones encoding factors involved in tRNA biogenesis and metabolism including several other modification enzymes , the tRNA export factor LOS1 , the pre-tRNA chaperone and La protein homolog , LHP1 , and MAF1 ( see this at the Saccharomyces genome database , SGD , at http://www . yeastgenome . org/locus/S000002527/interaction ) . In the absence of TRM1 and m22G26 , some tRNAs are substrates for surveillance by rapid tRNA decay ( RTD ) in S . cerevisiae and the trm1Δ cells were shown to exhibit temperature-sensitive growth deficiency [53] . That m22G26 may affect tRNA structure is also consistent with findings that in its absence , tRNALysUUU and tRNATyrGUA become substrates for surveillance by 5'-3' exonuclease Xrn1-mediated RTD [54] . However , although m22G26 modification efficiencies of target tRNAs differed in S . pombe maf1Δ and maf1+ cells , their relative steady state levels remained similar ( Fig 3A ) . Moreover , there was no deficiency of sup-tRNASerUCA or tRNASerUGA levels in maf1+ relative to maf1Δ cells ( Fig 2C and 2E ) despite differences in the percent content of their m22G26 . Thus the data indicate that a difference in m22G26 content was a critical determinant to the function of sup-tRNASerUCA in maf1Δ and maf1+ cells . The cumulative results indicate that m22G26 increases the specific activity of the tRNA . Apparently , m22G26 also increases specific activity of S . cerevisiae sup-tRNATyrUUA ( Fig 7A and 7B ) , and we believe that it would be reasonable to expect that it may do so for some other tRNAs . We note that the tRNAs whose m22G26 modification efficiencies vary most upon changes in RNAP III activity may impact the translation of some mRNAs more than others , dependent on their cognate codon use bias , and that this may contribute to a phenotype or stress response ( see [9 , 11] ) although to attempt to determine if this is decipherable for the subset of m22G26-tRNAs would require substantial bioinformatics and experimental resources and is beyond the scope of this study . As noted above , evidence that Trm1 acts redundantly with the pre-tRNA chaperone , La protein , suggests that by modifying tRNA with m22G26 it may contribute to proper tRNA folding [24] . G26 resides at the junction between the D-stem and the anticodon stem , and its N2-dimethylation , which interferes with normal Watson-Crick base pairing may contribute to prevention of tRNA misfolding . It is also notable that treatment of cells with 5-flurouracil ( 5FU ) , which is incorporated into RNA , sensitizes S . cerevisiae to loss of genes that encode tRNA modification enzymes whose nucleoside targets localize at or near the stems junction , and include TRM1 [55] . These observations together with evidence that m22G26 can stabilize correctly folded anticodon stems [56] , suggest that it may enhance tRNA specific activity by improving fit in the ribosome . It has been known that inactivation of MAF1 leads to increased translation fidelity in S . cerevisiae although the mechanism has been unclear [57] . As a greater percentage of the tRNAs acquire m22G26 in maf1-mutants this may be a mechanism that contributes to their increased fidelity . Future studies that compare translational fidelity in maf1Δ single mutants with maf1Δ trm1Δ double mutants may address this . S . cerevisiae Trm1 is tethered to the inner nuclear membrane via a specific amino acid sequence tract [25 , 58] . A genome-wide global ORF analysis of S . pombe found Trm1-GFP as nucleoplasmic and mitochondrial with no noted observation of perinuclear localization [59] . Although nuclear residence may limit the time during which a nascent pre-tRNA transcript might have access to acquire the m22G26 modification , retrograde tRNA transport should theoretically allow iterative access to Trm1 ( see [54] ) . Therefore , the mechanism by which cells maintain Trm1 activity in a functionaly limiting amount in minimal media is unclear . In any case , the data suggest that regulation of Trm1 can under certain conditions , differentially impact tRNA activity . Others have developed means to identify RNA modifications from deep sequencing data sets [38] . The ablation of G26 misincorporations following deletion of trm1+ ( Fig 3D ) , provided essential evidence that the correlation of G26 misincorporations with the suspected modification was indeed due to m22G26 . Thus , this approach can be used by tRNA-HydroSeq and similar methods together with genetics to obtain quality and quantity information toward studying the biology of certain tRNA modifications . tRNA-HydroSeq detected misincorporations corresponding to m1G9 , m22G26 , m3C32 , A34I , and m1A58 in tRNAs known to carry these modifications in yeast and/or other species . As was the case for G26 , the G9 and A58 misincorporation levels varied in a tRNA-dependent manner ( S3 Fig ) . However , unlike G26 , we found no functional correlation of the other modifications with maf1+ expression , RNAP III activity , and suppression phenotype . Notably , A34I was distinguished from the other misincorporations in that there was uniformly efficient misincorporation in all tRNA substrates ( S3 Fig ) . In addition , we found an intriguing tRNA-specific effect on A34I for the Rpc1 mutants and for growth media ( S4 Fig ) . For 10 of the 11 tRNAs with A34 there was no significant difference in the Rpc1 mutants whereas a single tRNA , SerAGA showed reduced A34 misincorporations in both mutants ( S4A Fig ) . We also observed significant difference in A34 misincorporation unique to tRNASerAGA in YES vs . EMM ( S4B Fig ) . While the basis of this specificity and its significance is unknown , we note that while tRNASerAGA can decode both UCC and UCU codons and that the ratios of these differ greatly in high-expression vs . low-expression mRNAs [60] , only the UCC ( wobble ) codon decoding is dependent on I34 . These data provide examples of utilities of tRNA-HydroSeq beyond the ability to follow G26 modification . Although mutations in RNAP III catalytic subunits cause HLD , their effects on the RNAP III transcriptome had not been reported [46] . We recreated two of these mutations in S . pombe at residues highly conserved from yeast to man . The mutations caused decreased transcription of the three tRNA genes examined and were associated with alterations of m22G26 and A34I modification efficiencies . We wish to emphasize that these HLD mutations were introduced into S . pombe as a means to globally decrease RNAP III activity for the purposes of this study . Nonetheless it is tempting to speculate that these mutations might have similar effects on human RNAP III activity and possibly analogous changes in tRNAs . The results suggest that while RNAP III activity may be increased or decreased globally due to a number of mechanisms , the output with regard to tRNA activity may be asymmetric or nonumiform . In such cases , nonuniform alterations of tRNA activities on different subsets of codon-biased mRNAs may contribute to phenotype [1 , 9 , 10] . To the best of our knowledge maf1-antisuppression had been observed only in S . cerevisiae and for ochre sup-tRNAs of Tyr identity [22 , 30] , which in S . cerevisiae carry m22G26 . The present work extends this to S . pombe and sup-tRNASerUCA . The S . cerevisiae maf1-1 mutant was isolated from a mod5-mutant deficient for cytoplasmic i6A37 modification [29] . However , the hypothesis that i6A37 hypomodification was responsible for maf1-antisuppression had not been tested experimentally [19] . Our data show no i6A37 deficiency in S . pombe maf1Δ cells and that antisuppression occurs despite efficient i6A37 modification of sup-tRNASerUCA . Instead the data show that m22G26 hypomodification of sup-tRNASerUCA is responsible for maf1-antisuppression . In S . cerevisiae , the tRNATyrGUA , from which the ochre suppressor SUP11 was derived , contains G26 and is hypomodified in maf1Δ cells ( Fig 7A ) . In S . pombe , sup-tRNASerUCA contains G26 and is hypomodified in maf1Δ cells . Over-expression of Trm1 in both S . cerevisiae and S . pombe substantially reverses their maf1-antisuppression phenotypes ( Figs 4F and 7B ) . We note that antisuppression reversal by Trm1 over-expression was incomplete . Among other possibilities this suggests that other factors involved in TMS may be limited for suppression in the context of increased tRNA synthesis in maf1Δ cells . Treatment of S . pombe maf1+ cells with rapamycin , which represses RNAP III via maf1+ , increased suppression accompanied by m22G26 hypermodification . Similarly , human cells treated with rapamycin showed robust increase in m22G26 modification content . Serum-starvation led to increased m22G26 modification that decreased with serum replenishment ( Fig 7C ) . Likewise , S . cerevisiae tRNATyr was m22G26 hypomodified in maf1Δ relative to MAF1 cells . In S . pombe , unlike the other modifications examined , only m22G26 varied with maf1+ expression concordant with TMS activity . This specificity is noteworthy since although a genetic screen uncovered GCD10 and TRM10 , responsible for m1A58 and m1G9 tRNA modifications , as well as TRM1 [61] , our data showed that m1A58 and m1G9 were not altered in maf1Δ relative to WT or +maf1+ whereas m22G26 levels were . In summary , the link between RNAP III activity and m22G26 modification efficiency appears to be specific and conserved .
S . pombe strains used are listed in S2 Table . Cells were grown in minimal media ( EMM lacking uracil ) or in rich media ( YES ) to an OD600 of 1 . 0 . S . pombe cells were seeded to an OD600 of 0 . 4 , and ten-fold dilutions were plated on the appropriate media as indicated . For liquid growth , overnight cultures were diluted to OD600 of 0 . 25 and incubated for two hours after which rapamycin ( AG Scientific Inc . , R1018 ) at 200 ng/ml , or DMSO alone ( Sigma , D2650 ) was added one hour prior to RNA isolation . The trm1+ open reading frame was amplified from S . pombe genomic DNA using a forward primer containing sequence for 3X FLAG peptide and XhoI site and a reverse primer with XmaI site . The PCR products were digested with XhoI and XmaI and ligated into XhoI-XmaI digested pREP4X . The maf1+ gene and its 600 bp upstream region was PCR amplified from genomic DNA and cloned into the XhoI-PstI sites of pRep4X ( removing the nmt1+ promoter ) resulting in plasmid CB235 . Total RNA was isolated using hot phenol . In short , 50 ml cultures grown from an OD600 of 0 . 1 to 0 . 5 were harvested , washed with water and resuspended in 300 μl TES buffer ( 10 mM Tris Cl pH 7 , 10 mM EDTA , 1% SDS ) . 300 μl water-equilibrated phenol was added and incubated at 65°C for 45 minutes , with vortex every 15 min . To the samples , 300 μl chloroform was added and centrifuged . Supernatant was extracted twice with acid-phenol-chloroform and once with chloroform before precipitation with ethanol . Total RNA was resolved in 6% NuPAGE TBE-Urea gel ( Life Technologies ) and transferred to positively charged nylon membranes . Probing and washes were done as described previously [14] . Using affinity-purified anti-i6A from rabbit [31] ( a kind gift of Anita Hopper , OSU ) at 1:50 and processed for chemiluminescence was as described [28] . For tRNA isolation , 50 μg of total RNA was separated on a 6% TBE-Urea polyacrylamide gel ( 21 cm X 18 cm X 0 . 15 cm ) followed gel purification of RNA shorter than 5S rRNA . 300 ng purified tRNA was hydrolyzed in 10 mM bicarbonate buffer pH 9 . 7 at 90°C for 5 min . The hydrolyzed RNA was dephosphorylated using calf intestinal alkaline phosphatase ( NEB ) followed by 5' phosphorylation by T4 polynucleotide kinase ( NEB ) . Barcoded , pre-adenylated , 3’ blocked Illumina adapters were ligated to the 3’ end using T4 Rnl2 ( 1–249 ) K227Q enzyme ( NEB ) . After heat inactivation , all ligated samples were pooled in ethanol and precipitated . In parallel , two size marker RNA oligos of 19 and 35 nt were radiolabeled using T4 polynucleotide kinase and ligated to pre-adenylated adapter and pooled . Ligated tRNA samples and markers were resolved in a 15% TBE urea acrylamide gel followed by gel purification of tRNA samples between 19 nt and 35 nt guided by the marker lanes . 5’ adapter was ligated to the gel purified samples using T4 RNA ligase I ( Thermo ) . RNA with ligated 5’ and 3’ adapters were gel purified , subjected to reverse transcription ( Superscript III , Life Technologies ) , amplified by PCR ( 10–12 cycles ) and the band was gel purified and sequenced using Illumina HiSeq 2500 . tRNA read depths for all samples generally varied with tRNA gene copy number; from 278 for the lowest read from the single copy ArgCCG gene in one replicate to greater than one-million reads for highly abundant tRNAs . Sequence reads were mapped to a reference file comprising sequences of all 61 unique mature S . pombe tRNAs . Sequences that did not map to this file were then mapped to a file containing all 150 unique S . pombe precursor-tRNA genes . Read count tables were made using the mapping data and analyzed using DEseq software . The fraction of reads that mismatched the reference gene sequence at each position were tabulated . The average values of the fraction of misincorporation among replicates was calculated and plotted ( e . g . , Fig 3C ) . S . pombe cells were grown in 10 ml of the noted media to A600 of 0 . 7–1 , washed with water and resuspended in 400 ul of 20% trichloroacetic acid ( TCA ) . Glass beads ( 0 . 5 mm ) were added and vortexed for 1 min . The beads were separated from the material , washed with 5% TCA and the wash was pooled with the material recovered . This was centrifuged at 6000 RCF for 10 minutes , the supernatant discarded and the pellet washed twice with 1 ml acetone . The pellet was air dried and dissolved in 400 ul of 1X SDS sample buffer containing fresh beta-mercaptoethanol . Aliquots were resolved on a 4–12% Bis-Tris gel ( Life technologies ) followed by transfer to PVDF membrane . The blot was blocked for 1 hour with 5% non-fat milk in PBS . Polyclonal anti-Trm1 antiserum raised against the C-terminal peptide , GPKSKPGKRTIAEVDSKS , in rabbit ( Thermo Fisher Scientific , Waltham , MA; animal #PA9064 , day 56 bleed ) was used at 1:500 in blocking buffer with 0 . 1% Tween 20 . Anti-Tubulin ( Sigma , #T5168 ) was used at 1:4000 . After 1 hr . the blot was washed 4 times with PBS-Tween . Appropriate secondary Abs ( LI-COR ) of different fluorescent emittances were used at 1:20 , 000 in 5% milk solution in PBS with 0 . 2% Tween-20 and 0 . 01% SDS for 1 hour followed by 4 washes in PBS-T . The washed blot was scanned using LI-COR Odyssey Clx system and the images processed and bands quantified using ImageStudioLite software . The glyceraldehyde phosphate dehydrogenase ( GPD ) promoter followed by a 3X-HA tag was amplified from the pYM-16 plasmid ( PCR-toolbox , EUROSCARF ) and cloned into the SacI-NotI sites of pRS426 to generate the pRS426GPD vector . The S . cerevisiae TRM1 gene starting from the ATG start codon to 855 bp downstream of the stop codon was amplified from genomic DNA and digested with NotI and XhoI present in the primers used . The fragment was inserted in the corresponding site of pRS426GPD . The empty vector ( pRS426GPD ) and the Trm1 clone were used to transform S . cerevisiae maf1Δ strain , MB159-4DΔ [57] which carries SUP11 sup-tRNATyrUUA , and plated on SC agar lacking uracil with 10 mg/l adenine .
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Transfer RNAs ( tRNAs ) are molecular adapters necessary for translation of the genetic code from DNA to messenger RNA ( mRNA ) to synthesis of the proteins that constitute the energy producing enzymes and structural components of all cells and organisms on earth . In eukaryotic cells , tRNAs are synthesized by RNA polymerase III ( RNAP III ) . Proteins are composed of different amino acids , sequentially arranged according to the triplet sequence code , each carried to the ribosome by a different tRNA which reads or decodes the triplet sequence of the mRNA . After their synthesis by RNAP III , tRNAs are chemically modified by enzymes on multiple of their nucleosides . Here we report that one of these modifications , dimethyl-guanine-26 ( m22G26 ) varies in the efficiency by which it is added to its target tRNAs , in a manner that is dependent on the overall activity rate of RNAP III . We show that this is important because the m22G26 modification activates the tRNA for function to translate the code . This link between RNAP III activity rate and m22G26 modification efficiency was previously unknown , and we show that it is conserved from yeast to human cells .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[] |
2015
|
RNA Polymerase III Output Is Functionally Linked to tRNA Dimethyl-G26 Modification
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Neural stem cell self-renewal , neurogenesis , and cell fate determination are processes that control the generation of specific classes of neurons at the correct place and time . The transcription factor Pax6 is essential for neural stem cell proliferation , multipotency , and neurogenesis in many regions of the central nervous system , including the cerebral cortex . We used Pax6 as an entry point to define the cellular networks controlling neural stem cell self-renewal and neurogenesis in stem cells of the developing mouse cerebral cortex . We identified the genomic binding locations of Pax6 in neocortical stem cells during normal development and ascertained the functional significance of genes that we found to be regulated by Pax6 , finding that Pax6 positively and directly regulates cohorts of genes that promote neural stem cell self-renewal , basal progenitor cell genesis , and neurogenesis . Notably , we defined a core network regulating neocortical stem cell decision-making in which Pax6 interacts with three other regulators of neurogenesis , Neurog2 , Ascl1 , and Hes1 . Analyses of the biological function of Pax6 in neural stem cells through phenotypic analyses of Pax6 gain- and loss-of-function mutant cortices demonstrated that the Pax6-regulated networks operating in neural stem cells are highly dosage sensitive . Increasing Pax6 levels drives the system towards neurogenesis and basal progenitor cell genesis by increasing expression of a cohort of basal progenitor cell determinants , including the key transcription factor Eomes/Tbr2 , and thus towards neurogenesis at the expense of self-renewal . Removing Pax6 reduces cortical stem cell self-renewal by decreasing expression of key cell cycle regulators , resulting in excess early neurogenesis . We find that the relative levels of Pax6 , Hes1 , and Neurog2 are key determinants of a dynamic network that controls whether neural stem cells self-renew , generate cortical neurons , or generate basal progenitor cells , a mechanism that has marked parallels with the transcriptional control of embryonic stem cell self-renewal .
A fundamental feature of neural development is the production of defined types of neurons in a temporal order from multipotent , regionally-specified neural stem and progenitor cells [1] . During nervous system development , maintaining the balance between stem cell self-renewal and neurogenesis is essential for the generation of the correct proportions of different classes of neurons and subsequent circuit assembly . Little is known of the molecular control of the key neural stem ( NS ) cell properties of multipotency and self-renewal . This is in contrast to other classes of stem cells , most notably embryonic stem ( ES ) cells , in which a group of three transcription factors , Sox2 and the two ES-specific factors Oct4 and Nanog , co-operate to control pluripotency and self-renewal in a non-redundant manner [2] , [3] . The paired-domain , homeodomain-containing transcription factor Pax6 is highly conserved among vertebrate and invertebrate species and is essential for the development of much of the central nervous system , including the eye , spinal cord and cerebral cortex , as well as pancreatic islet cells [4]–[7] . Detailed analyses of neocortical and retinal development in mice mutant for Pax6 have identified defects in neural stem and progenitor cell proliferation , multipotency , neurogenesis , the generation of specific types of neurons , and marked changes in spatial pattern [8]–[19] . In the neocortex , loss of Pax6 function results in microcephaly , abnormal development of the secondary progenitor population of the subventricular zone ( SVZ , also known as basal progenitor cells , BP cells ) and a disproportionate reduction in the production of later-born , upper layer neurons [12] , [14] , [15] , [17] , [20]–[23] . Given the functions of Pax6 in stem cell self-renewal/proliferation and neurogenesis , a potentially fruitful approach to uncovering cellular pathways controlling these processes is to identify the downstream targets of Pax6 in neocortical stem cells . Therefore , in this study we used Pax6 as an entry point to define the cellular networks regulating neural stem cell self-renewal and neurogenesis by combining chromatin immunoprecipitation ( ChIP ) to identify Pax6-bound promoters with the anatomical phenotypes and gene expression changes observed in Pax6 mutant cortices . To do so , we identified where in the genome Pax6 binds in mouse neocortical stem cells during normal development , defining the potential cellular networks regulated by Pax6 . As binding does not necessarily imply regulation , we also studied the transcriptional consequences of altering Pax6 levels in the neocortex in vivo . Developing tissues are sensitive to Pax6 dosage: heterozygous human mutations in Pax6 result in aniridia and forebrain abnormalities [24] , [25] , as do a number of mouse mutations ( for reviews , see [7] , [26] ) , humans and mice homozygous for Pax6 mutations typically lack eyes and have marked microcephaly and absent olfactory bulbs [5] , [6] , [19] , whereas increasing Pax6 levels in transgenic mice results in microphthalmia and forebrain abnormalities [27]–[29] . Therefore , we examined the transcriptional consequences of both increasing and decreasing Pax6 levels in the developing cortex to identify those promoters actively regulated by Pax6 in neocortical stem and progenitor cells . We find that Pax6 controls the balance between self-renewal and differentiation in neural stem cells in a dose dependent manner , positively and directly regulating cohorts of genes that promote self-renewal , basal progenitor cell genesis and neurogenesis . In addition , we found that Pax6 interacts with three other regulators of cortical stem cell neurogenesis , Neurog2 , Ascl1 and Hes1 . The four transcription factors regulate one another and many of the same target genes in an antagonistic manner , defining a core self-renewal/neurogenesis network that is dependent on a critical level of Pax6 . In support of this , we found in phenotypic analyses of Pax6 gain and loss of function cortices that an increase in Pax6 levels drives the system towards neurogenesis and basal progenitor cell genesis at the expense of self-renewal , whereas removing Pax6 reduces cortical stem cell self-renewal . In both cases , altering the levels of Pax6 ultimately leads to microcephaly , but through different cellular and biological pathways .
To identify promoters targeted by Pax6 , we applied in vivo location analysis to identify where in the genome Pax6 is bound in neocortical stem and progenitor cells . We carried out chromatin immunoprecipitation ( ChIP ) for Pax6-bound DNA in the developing mouse neocortex at embryonic day 12 . 5 ( E12 . 5 ) , at which stage Pax6 is expressed by all neocortical ventricular zone stem and progenitor cells , but not by post-mitotic neurons [32] . A set of three biologically independent Pax6 ChIP experiments was carried out using oligonucleotide microarrays spanning ∼8 . 5 kb around the transcriptional start sites of over 17 , 000 mouse genes ( see Materials and Methods for details ) . As the arrays used sample the proximal promoters of these genes , this analysis will not include intronic or distally located enhancers bound by Pax6 , such as the Pax6-bound cortical enhancer of Neurog2 expression , found ∼9 kb upstream of the Neurog2 start site [33] , [34] . Data from the three experiments were analysed to identify regions of promoters bound by Pax6 in each ChIP and the individual analyses combined to define a set of 1560 genes with Pax6-bound promoters ( Figure 2; Table S1 ) , of which 1172 are genes with known or predicted functions ( Figure 2H ) . A set of five genes defined as Pax6-bound by the array study were confirmed as bound by qPCR analysis of additional Pax6 ChIP from the E12 . 5 cortex using two different Pax6 polyclonal antibodies ( Figure 2G ) . Functional annotation of the set of Pax6-bound genes by Gene Ontology analysis found a significant enrichment for developmental processes among Pax6 target genes , including nervous system and eye development ( Figure 3 ) . Broad functional categories enriched in the Pax6-bound set included cell cycle regulation , regulation of proliferation , cell-cell signalling , neurogenesis and neuron differentiation . At the functional level , Pax6-bound genes are enriched for genes with transcription factor activity and chromatin binding ( Figure 3A and 3D ) . Pax6 binds transcription factors that are expressed in stem and progenitor cells ( Pax6 itself , Hmga2 , Cutl1 , Nr2f2 , Emx2 , Sox9 , Neurog3 , Tle1 ) and basal progenitor cells in the cortex ( Eomes/Tbr2 , Neurod1 ) , as well as to transcription factors expressed in newly born , differentiating neurons ( Sox4 , Sox11 ) or in terminally differentiating cortical neurons ( Rorb , Etv1 ) . Together with the binding of Pax6 to sets of regulators of cell cycle progression and proliferation ( for example , Ccna1 , Pten , Cdkn1b , Cdk4 , Fzr1 and Ctnnb1 ) , regulation of these transcription factors confers the potential for Pax6 to control stem cell self-renewal/proliferation , neurogenesis and cell fate determination within the cortex . Pax6 binding data defines the potential networks controlled by Pax6 in this cell type . However , binding does not necessarily equate with activity . Therefore , to characterize the transcriptional networks within which Pax6 acts , we studied gene expression in the E12 . 5 mouse cortex , using microarrays , following Pax6 gain and loss of function ( Figure 4 ) . Intersection of genes that are positively or negatively regulated by Pax6 defined the transcriptional networks dependent on Pax6 , without discriminating between direct and indirect regulation . For Pax6 gain of function , we used the D6 enhancer that drives cortex-specific expression in the ventricular zone and cortical plate [35]–[37] to generate transgenic mice expressing the canonical Pax6 isoform , giving rise to animals with a two-fold increase in Pax6 protein in the ventricular zone , as assessed by immunohistochemistry ( Figure 4A–4C ) . Expression profiling of cortices from single wild-type and D6-Pax6 transgenic littermates at E12 . 5 found 3784 genes showing significantly altered expression ( false discovery rate , FDR , of 0 . 1 ) , of which 2238 ( 59% ) were upregulated ( Figure 4D; Table S2 ) . In comparison , expression profiling of the Pax6 homozygous mutant cortex ( Sey/Sey ) at E12 . 5 identified 938 genes with significantly altered expression , of which 600 ( 64% ) were up-regulated ( Figure 4E; Table S3 ) . Of the 938 genes showing altered expression in the Pax6 null mutant cortex , 298 ( 32% ) were also altered in expression in the D6-Pax6 cortex ( Figure 4F ) . From the transcriptome analyses , we defined two sets of genes showing Pax6-dependency: the set of genes showing positive dependency on Pax6 was the set formed by the union of genes up-regulated in the D6-Pax6 cortex and the genes down-regulated in the Pax6 mutant cortex ( Figure 4F and 4G; 2344 genes ) ; the set of genes showing negative dependency on Pax6 was the set formed by the union of genes down-regulated in the D6-Pax6 cortex and the genes up-regulated in the Pax6 mutant cortex ( Figure 4F and 4G; 1920 genes ) . Genes demonstrating positive dependency on Pax6 were notable for including many genes expressed in basal progenitor cells , including Eomes/Tbr2 , Gadd45g , Neurod1 , Tcfap2c and Hes6 ( Figure 4H ) . Genes similarly dependent on Pax6 for expression include genes expressed in cortical stem and progenitor cells associated with self-renewal and proliferation , such as the transcriptional regulators Hmga2 and Hes5 , and the cell cycle regulators Cdk2 , Cdk4 and Ccne1 . However , transcription factors associated with neurogenesis , such as Neurog2 , Sox4 and Sox21 , also show positive dependency on Pax6 for their expression . In addition , increasing Pax6 expression leads to an increase in expression of transcription factors that are preferentially expressed in cortical neurons of layers 5 and 6 ( Tbr1 , Zfp312/Fezf2 , Nfia , Nfib ) . In contrast , genes demonstrating negative dependency on Pax6 included genes with periodic expression in the cell cycle ( FoxM1 , Mcm3 , Mcm5 ) . These genes were reduced in expression in the Pax6-overexpressing cortex , indicating that increasing Pax6 may alter cell cycle length . Together , the transcriptional analyses demonstrate that Pax6 regulates neural stem cell maintenance , basal progenitor cell genesis and neurogenesis . To identify those genes that are both bound and regulated by Pax6 , we analysed the intersection between the sets of Pax6 bound genes and those genes showing Pax6 dependency from the gain and loss of function transcriptional analyses ( Figure 5 ) . Of the set of 1560 Pax6-bound genes identified by the in vivo location analysis , 343 ( 22% ) show significantly changed expression in either the Pax6 gain or loss of function cortex at E12 . 5 ( Figure 5A; Table S4 ) . Of the 343 bound and regulated genes , 180 were positively regulated and 143 negatively regulated by Pax6 ( Figure 5B and 5C ) , with 20 genes showing conflicting regulation ( either up- or down-regulated upon both gain and loss of Pax6 function ) . Using publicly available in situ hybridization data ( GenePaint . org; [38] ) , we assigned cellular expression to 279 of the 343 Pax6 bound and regulated genes in the E14 . 5 mouse cortex , the mRNAs of 223 of which were detectable in the cortex at that age ( Figure 5D–5F; Table S5 ) . Ventricular zone expression was found for 188 of those genes ( 84% ) , 81 of which were solely expressed in the ventricular and subventricular zone . A noteworthy minority of Pax6 bound and regulated genes ( 21; 9% of detectable mRNAs ) were exclusively expressed in differentiating neurons in the cortical plate . The combination of Pax6 binding data with the transcriptional profiling of Pax6 gain- and loss-of-function cortices enabled the delineation of the direct and indirect networks regulated by Pax6 ( Figure 6 ) and prediction of Pax6 functions in cortical stem and progenitor cells . As shown , Pax6 positively controls sets of genes promoting neural stem cell self-renewal and/or maintenance: Pax6 positively regulates transcription of Hmga2 , Tle1 and Cdk4 directly , promoting cell cycle progression and neural stem cell maintenance [39]–[41] . Furthermore , Pax6 controls expression of D-class cyclins , Hes5 and Notch ligands indirectly [39] , [42] , [43] , underlining the importance of Pax6 in promoting neural stem cell self-renewal . However , the self-renewal functions of Pax6 are offset by its binding to , and positive regulation of , genes and transcription factors that promote neurogenesis , including the tumour suppressor genes Pten and Fzr1/Cdh1 and the transcription factors Neurog2 and Sox4 [31] , [44]–[46] . In addition , Pax6 directly and positively controls genes that promote basal progenitor cell genesis , including one of the major determinants of the basal progenitor fate , Eomes/Tbr2 , as well as Neurod1 and Gadd45g [47]–[49] . Together , these functions of Pax6 indicate that one biological role for Pax6 is to promote neurogenesis by increasing the number of neocortical stem and progenitor cells either exiting the cell cycle or becoming basal progenitor cells , and thus neurons at their next division . In addition to roles in neurogenesis and self-renewal , Pax6 controls genes that regulate the neocortical identity of the neurons produced in the dorsal pallium . It does so by primarily negatively regulating genes associated with neuronal cell fates , and subpallially-derived inhibitory neuron and interneuron identity in particular , through repression of key transcription factors that confer interneuron fates ( Isl1 , Foxd1 , Ascl1 , Dlx1 , Lhx8; Figure 6; [50] ) . Many of the findings reported here on the functions of Pax6 in neurogenesis and self-renewal are in contrast with the recently described functions of the bHLH transcription factor Hes1 , sustained overexpression of which represses many of the genes upregulated by Pax6 [51] . Comparison of the expression data from Hes1 overexpression with the Pax6 data presented here shows that Pax6 and Hes1 have opposing functions on neurogenesis and basal progenitor genesis through the same sets of effector genes ( Figure 6 ) : Pax6 positively regulates Neurog2 and Eomes/Tbr2 , for example , whereas both of these key transcription factors are repressed by Hes1 . As discussed in more detail below , this overlap suggests that Pax6 and Hes1 are both regulating a core mechanism for controlling neural stem cell self-renewal and neurogenesis . To test the prediction of the functions of the Pax6-regulated network described above , we studied neurogenesis and cell fate determination in the Pax6 gain-of-function cortex ( D6-Pax6 transgenic mouse; Figure 7 ) . As predicted , increased Pax6 resulted in a marked increase in the expression of Eomes/Tbr2 at E12 . 5 , demonstrating the increase in the basal progenitor cell population . Furthermore , there was with an increase in early born , layer 6 neurons ( Tbr1-expressing cells ) , without an increase in the total number of neurons produced by this stage of development , compared to controls ( as evidenced by the number of cells expressing neuron-specific tubulin , Tuj1 , Figure 7 ) . However , by E14 . 5 the D6-Pax6 transgenic cortex was significantly smaller than that of controls , with a reduction in total neuron number ( Figure 7 ) . The reduction in cortical neuron number at this stage is consistent with the early increase in Pax6 expression driving cortical stem and progenitor cells towards an inappropriately early basal progenitor and neuronal fate . The reduction in cortical size is not due to an increase in cell death in the Pax6 overexpressing cortex , as no significant increase in apoptosis could be detected by TUNEL staining ( Figure S1 ) . The early depletion of the stem cell pool reduces the number of stem cells available for neurogenesis at subsequent stages , resulting in an overall reduction in cortical size and total cortical neurogenesis by E14 . 5 ( Figure 7 ) . Neurogenin2 ( Neurog2 ) and Ascl1/Mash1 are two proneural bHLH transcription factors with well-established roles in neocortical neurogenesis and cell fate [15] , [31] . Both interact with Pax6: Pax6 positively regulates Neurog2 via an enhancer [34] , whereas Ascl1 expression is upregulated in Pax6-null cortices [52] . Gene expression profiling of the Neurog2 mutant cortex and the Ascl1-null ventral telencephalon has been analysed to define genes downstream of both factors [53] . As with Hes1 , there are striking overlaps in the sets of genes downstream of Ascl1 , Neurog2 and Pax6 in the developing telencephalon . Placing Pax6 in the context of these three transcription factors controlling cortical neurogenesis , Hes1 , Ascl1 and Neurog2 , enables the definition of a core transcriptional circuit controlling cortical neural stem cell self-renewal and neurogenesis ( Figure 8A ) . Pax6 both positively regulates the expression of Neurog2 and also synergises with Neurog2 to promote basal progenitor cell genesis and thus production of cortical excitatory projection neurons , whereas Hes1 opposes this process by repressing many of the same genes . Ascl1 has complex functions in cortical neurogenesis: while it also promotes basal progenitor cell genesis , it also drives expression of transcription factors to promote inhibitory interneuron genesis ( Lhx8 and Isl1 , for example ) . Pax6 and Hes1 both repress Ascl1 , and Pax6 represses Lhx8 and Isl1 , to inhibit the interneuron-producing functions of Ascl1 . This network also leads to clear predictions of the normal functions of Pax6 in regulating neurogenesis and the consequences of altered Pax6 expression in the early cortex ( Figure 8 ) . The network indicates that Pax6 is essential for the cortical identity of the basal progenitor cells produced in the cortex , as it is an essential driver of Eomes/Tbr2 expression , a key determinant of cortical basal progenitor cell identity [47] , [48] . Given the repression of Ascl1 by Pax6 in cortical stem cells and the interneuron-promoting function of Ascl1 , loss of Pax6 function should result in a basal progenitor cell population lacking cortical identity ( due to loss of Eomes/Tbr2 expression ) , a decrease in the genesis of cortical pyramidal neurons and an increase in the production of inhibitory interneurons ( Figure 8B ) . These are all phenotypes observed in the Pax6 null cortex [8] , [9] , [14] , [52] . In contrast , increasing Pax6 expression would be predicted to increase basal progenitor genesis early in cortical development and increase pyramidal cell genesis both directly from the ventricular zone and indirectly from basal progenitor cells ( Figure 8C ) . In principle , Pax6 could increase cortical stem cell self-renewal/proliferation , but this would be in competition with all of the functions of Pax6 that promote neurogenesis: reduced proliferation/cell cycle exit ( via Pten and Fzr1/Cdh1 expression ) , basal progenitor cell genesis ( via Eomes/Tbr2 and Neurod1 ) and neurogenesis ( via Neurog2 and Sox4 ) . In the D6-Pax6 cortex , as described above , an increase in basal progenitor genesis is observed early in development , accompanied by an increase in the production of early-born cortical pyramidal cells . Our in vivo analysis supports the finding that Pax6 operates in and regulates a core transcriptional network that controls the balance between neurogenesis and stem cell self-renewal in a highly dosage-sensitive manner . Altering the amount of Pax6 in neural stem cells has profound effects on the output of neural stem cells , ultimately compromising the ability of neural stem cells to generate all of the required neurons for normal assembly of the cerebral cortex . This raises the question as to whether Pax6 levels do vary or oscillate in vivo , as has been reported for several other genes in developing systems [54] . The levels of Hes1 and Neurog2 proteins vary with cell cycle stage and have also been shown to oscillate in neocortical stem and progenitor cells with a 2–3 hour frequency [51] , in a Notch-dependent fashion in the case of Hes1 . Immunohistochemistry for Pax6 , Neurog2 and Hes1 shows that Pax6 does not show obvious cell cycle-dependent changes in levels , unlike Hes1 and Neurog2 , as assessed by nuclear location in the ventricular zone , as it is expressed in all neocortical stem and progenitor cells at relatively high levels ( Figure 9A; Figure S2 ) . This approach cannot resolve oscillations with a short periodicity , as observed for Hes1 and Neurog2 by live imaging [51] . However , Hes1-expressing cortical stem and progenitor cells also express high levels of Pax6 , so it is unlikely that Hes1 represses Pax6 expression as it does Neurog2 [51] . In the presence of Notch signalling , increased Hes1 and Hes5 activity suppresses neurogenesis and promotes self-renewal , in part by repression of Neurog2 , assisted by the activation of Hes5 expression by Pax6 ( Figure 9B ) . In the absence of Notch signalling and Hes1 activity , Pax6-driven increase in Neurog2 and the resulting drive to neurogenesis are unopposed , allowing Pax6 to promote neurogenesis ( Figure 9C ) . Therefore , the identification of the direct transcriptional targets of Pax6 in neocortical stem and progenitor cells , combined with phenotypic analyses of the Pax6 gain and loss of function cortex , have enabled the elucidation of a regulatory network controlling the balance between neurogenesis and self-renewal . The development of this model provides a framework in which to explore questions arising from the mechanism reported here . For example , only a subset of Pax6+/Hes1− stem cells in G1 phase of the cell cycle go on to generate neurons in the next round of cell division . Therefore , there are likely to be additional components of this network that promote self-renewal and suppress neurogenesis .
Neural stem cell self-renewal , neurogenesis and cell fate determination are three forces that control the generation of specific classes of neurons at the correct place and time during development . Much remains to be discovered of the cellular networks operating to control these processes . We report here that the transcription factor Pax6 directly regulates genes controlling the balance between neocortical stem cell maintenance , neurogenesis and the production of basal progenitor cells in a dosage-dependent fashion . While consistent with genetic loss-of-function studies [10] , [14] , [20] , [52] , [55]–[58] , the direct nature of the control of these processes by Pax6 and their dosage sensitivity are unexpected . We propose that this dosage sensitivity reflects the need for a critical level of Pax6 within neocortical stem and progenitor cells . Using Pax6 ChIP , we have identified a set of the promoters bound by Pax6 in neocortical stem cells in vivo at E12 . 5 . This set of Pax6-bound genes defines the components of potential networks regulated by Pax6 in this tissue , and is noteworthy for the enrichment for genes involved in controlling cell cycle progression , transcription factors expressed in the three main cell types found in the early cortex ( ventricular zone stem cells , basal progenitor cells and differentiating neurons ) and also transcription factors expressed specifically in non-cortical neurons , including the ventral forebrain , spinal cord and retina , as well as in pancreatic islet cells . These binding data are compatible with a number of models for Pax6 action . For example , Pax6 could repress expression of genes that are not normally expressed in the neocortex , or alternatively could simply bind to target sites in the promoters of genes normally expressed in other cell types in a Pax6-dependent manner , without driving their expression in the cortex . Similarly , for those genes expressed in cortex , Pax6 could either positively or negatively regulate cell cycle progression , and positively or negatively regulate basal progenitor cell genesis . Evidence for gene regulation by Pax6 is essential to resolve these questions . Therefore , we combined the binding data with transcriptome data from Pax6 gain- and loss-of-function experiments in the early developing cortex in order to identify those genes whose expression is dependent on Pax6 and the nature of that dependency , finding that 22% of Pax6-bound genes show evidence for regulation in vivo . Transcriptome analyses of Pax6 gain and loss of function cortices identified a subset of genes that show reciprocal regulation , but also clearly demonstrate that the gain and loss of function gene expression changes are not simply complementary , in agreement with the reported anatomical phenotypes of Pax6 null and Pax6 over-expressing cortices [14] , [21] , [27] , [29] . However , there is a striking overlap and complementarity in the changes of expression in basal progenitor genes observed in each mutant . We found that Pax6 directly promotes expression of a large set of genes specifically expressed in basal progenitor cells , including the key determinant of that cell type , the transcription factor Eomes/Tbr2: mutations in Eomes/Tbr2 lead to a loss of the cortical intermediate progenitor cell population , accompanied by a reduction in neurons in all cortical layers [47] , [48] . Increasing Pax6 levels drives basal progenitor cell genesis from cortical stem cells , primarily by increasing Eomes/Tbr2 expression , along with the other basal progenitor cell genes such as Gadd45g , Neurod1 , Sstr2 and Hes6 [49] . Basal progenitor cells undergo a limited number of mitotic divisions to generate neurons [59] , thus the overall effect of shifting the stem cell population towards basal progenitor cells is to increase neurogenesis at the expense of neural stem cell maintenance in the early stages of cortical development , ultimately resulting in microcephaly , as observed here . However , there are also changes in expression specific to either gain or loss of Pax6 function , with many more genes showing altered expression upon increased Pax6 levels . For example , from the combined Pax6 binding and regulation data we have found that Pax6 expression positively regulates stem cell self-renewal by promoting expression of the transcription factor Hmga2 and the G1 cyclin dependent kinase , Cdk4 . Hmga2 promotes neural stem cell self-renewal by reducing expression of two negative regulators of the cell cycle , p16Ink4a and p19Arf [39] . Hmga2 reduces expression of p16Ink4a and p19Arf indirectly via repression of JunB , a positive regulator of their expression , and we also found Pax6 binding to the promoter of JunB in cortical stem cells . p16Ink4a slows cell cycle progression by inhibiting the G1 cyclin-dependent kinase Cdk4 [60] , and Cdk4 is bound and positively-regulated by Pax6 in cortical stem cells . In contrast , Pax6 also directly promotes expression of Pten and Fzr1/Cdh1 , both of which reduce neural stem cell proliferation and self-renewal [44] , [61] . Thus , under normal conditions in vivo Pax6 has the potential to both promote and limit stem cell self-renewal . However , when Pax6 levels are increased , as in the D6-Pax6 transgenic cortex , the neurogenic functions of Pax6 are dominant over its ability to promote self-renewal . We have also placed Pax6 in the context of other transcriptional regulators of self-renewal and neurogenesis , Hes1 , Neurog2 and Ascl1/Mash1 , in order to extend our coverage of the cellular networks controlling these processes . The marked overlap between those genes directly and indirectly regulated by Pax6 with the genes regulated by all three of the other factors provides strong evidence for the operation and architecture of the network regulating cortical neurogenesis , and the central importance of the basal progenitor population as a major output of that network . Pax6 and Neurog2 cooperate to promote neurogenesis , both directly and via the basal progenitor population , and this is opposed by the oscillating expression of Hes1 [51] . At the same time , Pax6 also promotes stem cell self-renewal in a manner that counterbalances its neurogenesis-promoting activity . However , when over-expressed , the promotion of neurogenesis and basal progenitor cell genesis by Pax6 is dominant over the promotion of self-renewal . Therefore , we propose that there is an optimal level of Pax6 that determines the balance between neocortical stem cell self-renewal and neurogenesis: increasing that level drives stem cells to a neuronal or basal progenitor fate , whereas reducing the level leads to early cell cycle exit , manifest as increased early neurogenesis [14] . In both cases , altering Pax6 levels leads to a depletion of the stem cell population by exiting to neurogenesis , but by different pathways and with different neuronal fates: cortical pyramidal cells when Pax6 is increased , inhibitory interneurons when Pax6 is absent . The sensitivity of cortical development to Pax6 levels underlines the importance of assessing subtle structural and functional anomalies in humans heterozygous for Pax6 mutations , as has been done for aniridia patients [22] , [25] . Finally , the findings of Pax6 function in neocortical stem and progenitor cells presented here have similarities with the functions of the ES cell pluripotency regulator Oct4 [3] . Oct4 shows marked dosage effects in ES cells in vitro such that a reduction in Oct4 levels leads to trophectoderm differentiation and a two-fold increase in Oct4 levels leads to differentiation to primitive endoderm and mesoderm [3] . Loss of Pax6 leads to a depletion of the cortical stem cell pool , via increased early neurogenesis secondary to a failure to self-renew , and also a switch in the fates of the neurons produced from glutamatergic cortical neurons to an inhibitory interneuron identity [52] . Similarly , increased Pax6 expression also leads to depletion of the stem cell pool , but in this case by driving stem cells to a basal progenitor fate , leading to an overproduction of early-born , deep-layer cortical neurons . Thus the level of Pax6 controls whether neural stem cells will self-renew , generate cortical neurons or produce basal progenitor cells .
Chromatin immunoprecipitation ( ChIP ) was performed as described [62] , with minor modifications . An average of 36 neocortices from E12 . 5 MF1 mouse embryos were used for each ChIP . For these and subsequent studies , all animal work was approved by local ethics review committees and , where relevant , carried out according to UK Home Office national guidelines . ChIP was carried out with specific rabbit polyclonal Pax6 antibodies generated against C-terminal peptides that recognise both splice variants of Pax6: C-term 1 -Chemicon , Cat no . AB5409 and C-term 2 - Covance PRB-278P . For array analysis , Pax6-bound genomic DNA was purified by ChIP using the Chemicon antibody , and ChIP material and whole cell extract DNA were globally amplified by ligation-mediated PCR [62] . To validate ChIP-on-chip data , unamplified ChIP material prepared with both Pax6 antibodies and from control samples lacking the primary antibody were used for gene-specific , quantitative PCR . Primers to amplify 100–250 bp target regions surrounding the predicted genomic binding locations for Pax6 were designed using Primer3 ( http://frodo . wi . mit . edu/ ) [63] or Primer Express ( Applied Biosystems ) , and checked for specificity in the genome using the BLAT algorithm ( http://genome . ucsc . edu/ ) . Quantitative PCR was carried out using the Roche Lightcycler system or the Applied Biosystems 7300 system . The amount of target regions was quantified in Pax6 and control chromatin immunoprecipitations lacking the primary antibody ( no-antibody controls , NoAb ) . The enrichment for each gene was calculated by normalising the Pax6/NoAb ratio against the Pax6/NoAb ratio for a promoter region that was not found to be bound by Pax6 ( non-bound control region from the Syt8 gene ) . Amplified Pax6 ChIP and whole cell extract DNA were labelled by indirect incorporation of Cy3 or Cy5-labelled nucleotides and hybridised to Agilent mouse promoter 244 K arrays according to the manufacturer's instructions . Slides were scanned in an Agilent scanner and data extracted and normalised using Agilent Feature Extractor . Data were analysed by neighbour analysis [62] implemented in ChipAnalytics ( Agilent ) to calculate probability scores of Pax6 binding for each array oligonucleotide ( p[Xbar] scores ) . Binding events were identified by sliding a 1000 bp window across the genomic space covered by the promoter array . Within a window , the best p[Xbar] score from each of the three ChIP-chip experiments was identified . A binding event was called if: ( 1 ) 2 or more scores were < = 0 . 015 , and ( 2 ) the product of three scores was < = 0 . 000025 . Gene ontology analysis of Pax6-bound genes was performed using GOToolBox ( http://crfb . univ-mrs . fr/GOToolBox/home . php ) . To generate D6-Pax6 transgenic mice , the 5 . 7 Kb D6 promoter fragment was cloned upstream of the canonical Pax6 open reading frame [35]–[37] and injected into the pronucleus of fertilized ( C57BL/6×BALB/c ) F1 mouse oocytes to generate founder mice . In situ RNA hybridization using digoxigenin ( DIG ) -labeled RNA probes was performed according to methods described at the Rubenstein lab website ( http://physio . ucsf . edu/rubenstein/protocols/index . asp ) . Sections from the different genotypes ( WT and D6-Pax6 ) were processed in parallel . Basal ganglia expression was used an internal control to compare results between different experiments and between experimental and WT samples . Probes used: Pax6 ( P . Gruss ) , Neurog2 ( F . Guillemot ) , Tbr1 and Eomes/Tbr2 ( Rubenstein lab ) . Immunohistochemistry was performed on frozen sections ( 10 or 20 µm ) . Antibodies used: monoclonal anti-βIII-tubulin antibody ( clone TUJ1; Covance ) , 1∶1000; anti-phospho-Histone H3 ( Ser10 ) ( Upstate ) 1∶200; anti Pax6 ( Developmental Studies Hybridoma Bank ) 1∶1000; anti-Eomes/Tbr2 ( gift from Robert Hevner , University of Washington School of Medicine , Seattle ) . Pax6 levels were quantified in 9 wildtype and 14 D6-Pax6 tissue sections by the intensity of the immunofluorescent signal: the signal along the dorsal-ventral axis was quantified in the ventricular zone by histogram ( ImageJ , NIH ) , using the mean intensity . For this quantification the Developmental Studies Hybridoma Bank anti-Pax6 antibody was used at 1∶1000 . TUNEL analysis was performed on 20 µm cryostat sections using the Apoptag Kit following the manufacturer's recommendations ( Millipore , CA , USA ) . Similar results were observed with activated Caspase 3 staining ( data not shown ) . Triple immunohistochemistry for Pax6 , Hes1 and Neurog2 was carried out on sections of E12 . 5 cortex by standard techniques ( rabbit anti-Pax6 antibody , Covance PRB-278P; guinea pig anti-Hes1 antibody , gift from Ryoichiro Kageyama; goat anti-Neurog2 , Santa Cruz Biotechnology ) . Quantification of the fluorescent intensity of nuclear staining for each antibody was carried out on confocal microscrope images ( Radiance , Biorad ) of a minimum of three sections using Volocity software ( Improvision ) . Cortices were dissected from individual embryos in two litters of E12 . 5 Pax6Sey ( Edinburgh Small-eye , [6] ) mutant embryos and from one litter of E12 . 5 D6-Pax6 transgenic mice . Total RNA was extracted and cDNA synthesised using the SMART system , as described [64] . Gene expression in neocortices from three single Pax6Sey/Sey embryos was compared to that in four single wildtype littermates on six dye-swapped oligonucleotide microarrays; while gene expression in neocortices from three single D6-Pax6 embryos was compared to that in three single wildtype littermates at E12 . 5 in a set of 6 paired dye-swapped hybridizations . Arrays of the MEEBO oligonucleotide set ( Invitrogen ) , produced by the Pathology Department , University of Cambridge were used for all studies . cDNA labeling , array hybridization , slide scanning ( Axon GenePix microarray scanner , Molecular Devices ) and data extraction were performed as described [64] . Expression data were archived and lowess normalized using the Acuity system ( Molecular Devices ) . Log ratios of all expression measurements for each array were median-centered and expression ratios variance normalized across all of the arrays ( without adjusting the average fold-change ) . Genes were filtered on the basis of the number of arrays on which they were detected , being required to be present in 4 of the 6 microarrays . For the D6-Pax6 analysis , dye-swapped replicate pairs of arrays were averaged , and in the case of one missing value , the single value used . Significant differences in gene expression were identified using the significance analysis of microarrays ( SAM ) algorithm ( Version 2; one class , at least 200 permutations ) , using a false discovery rate ( FDR ) of 0 . 1 [65] . Dataset intersections between array datasets were performed using gene symbols . Gene symbols were retrieved using the SOURCE ( http://smd-www . stanford . edu/cgi-bin/source/sourceSearch ) database and the gene accession numbers provided by the array/oligonucleotide manufacturers . Network modeling was carried out using BioTapestry ( www . biotapestry . org ) [66] .
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Neural stem cells make all of the neurons in the brain . A key feature of these cells is the ability to regulate the balance between making more neural stem cells , the process of self-renewal , and making nerve cells , the process of neurogenesis . Too much self-renewal would result in a brain with too few neurons and abnormal circuitry; too much neurogenesis would deplete all of the neural stem cells too quickly , resulting in a small brain and neurological abnormalities . Little is currently known of the how neural stem cells control this fundamental choice . We used one transcription factor , Pax6 , which is important for this decision , as an entry point to define the cellular networks controlling neural stem cell self-renewal and neurogenesis in the developing mouse brain . We found that the relative amount of Pax6 controls the balance between self-renewal and neurogenesis in neural stem cells . Increasing Pax6 levels drives the system towards neurogenesis , at the expense of self-renewal , by turning on a genetic programme for making neurons , whereas decreasing Pax6 turns off the genetic programme for neural stem cell self-renewal . In both cases , altering the levels of Pax6 ultimately leads to a small brain , but through very different mechanisms .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"developmental",
"biology/neurodevelopment",
"developmental",
"biology/stem",
"cells",
"genetics",
"and",
"genomics/functional",
"genomics"
] |
2009
|
The Level of the Transcription Factor Pax6 Is Essential for Controlling the Balance between Neural Stem Cell Self-Renewal and Neurogenesis
|
Acquired resistance through genetic mutations is a major obstacle in targeted cancer therapy , but the underlying mechanisms are poorly understood . Here we studied mechanisms of acquired resistance of chronic myeloid leukemia ( CML ) to tyrosine kinase inhibitors ( TKIs ) by examining genome-wide gene expression changes in KCL-22 CML cells versus their resistant KCL-22M cells that acquire T315I BCR-ABL mutation following TKI exposure . Although T315I BCR-ABL is sufficient to confer resistance to TKIs in CML cells , surprisingly we found that multiple drug resistance pathways were activated in KCL-22M cells along with reduced expression of a set of myeloid differentiation genes . Forced myeloid differentiation by all-trans-retinoic acid ( ATRA ) effectively blocked acquisition of BCR-ABL mutations and resistance to the TKIs imatinib , nilotinib or dasatinib in our previously described in vitro models of acquired TKI resistance . ATRA induced robust expression of CD38 , a cell surface marker and cellular NADase . High levels of CD38 reduced intracellular nicotinamide adenine dinucleotide ( NAD+ ) levels and blocked acquired resistance by inhibiting the activity of the NAD+-dependent SIRT1 deacetylase that we have previously shown to promote resistance in CML cells by facilitating error-prone DNA damage repair . Consequently , ATRA treatment decreased DNA damage repair and suppressed acquisition of BCR-ABL mutations . This study sheds novel insight into mechanisms underlying acquired resistance in CML , and suggests potential benefit of combining ATRA with TKIs in treating CML , particularly in advanced phases .
Chronic myeloid leukemia ( CML ) is a myeloproliferative disease resulting from the clonal hematopoietic stem cell disorder that is caused by the transformation of oncogenic breakpoint cluster region-Abelson ( BCR-ABL ) fusion gene [1] . Typically , CML progresses from chronic phase ( CP ) to accelerated phase ( AP ) then into blast crisis ( BC ) , which can be distinguished by the number and maturation of leukocytes . Treatment with imatinib mesylate ( IM ) , a BCR-ABL tyrosine kinase inhibitor , can effectively yield a durable complete cytogenetic response in CP patients and the drug is widely used as the first-line therapy for most CML patients [2] . However , residual leukemia cells persist in nearly all patients that may account for the disease recurrence if the treatment is discontinued [3] , [4] . The emergence of point mutations in the BCR-ABL kinase domain is a major cause of imatinib resistance in CML patients , especially in AP and BC [5] , [6] . These acquired mutations may alter kinase domain structure and impair drug binding affinity . The second generation tyrosine kinase inhibitors nilotinib and dasatinib show much more potent activity against BCR-ABL and most mutants , but some kinase domain mutations , especially T315I , are still resistant to these drugs [7]–[9] . Although TKIs such as Ponatinib [10] , with activity against the T315I mutation , have been developed , their application to CML therapy has been limited by concerns regarding toxicity . In addition , highly resistant compound mutations appear to be an emerging problem . Therefore , more rational therapeutic strategies still need to be developed to overcome the problem of TKI resistance . We have recently described a novel model of acquired resistance in CML using the blast crisis CML cell line KCL-22 [11] . In this model , the cells initially undergo apoptosis upon treatment with therapeutically effective doses of imatinib , but then re-grow within two weeks by development of resistance through T315I BCR-ABL mutation [11] . This model provides a very useful tool to study molecular mechanisms of acquisition of BCR-ABL mutations from its native chromatin locus . We have shown that the native BCR-ABL locus has nearly ten times higher mutagenesis potential than randomly integrated BCR-ABL cDNA in the same cells , suggesting the likely influence of the genetic instability or epigenetic deregulation from the translocation locus [11] . We have identified a key epigenetic regulator sirtuin 1 ( SIRT1 ) , a NAD+-dependent protein lysine deacetylase , that promotes BCR-ABL mutagenesis through stimulating error-prone DNA damage repair [12] . Using this model , we have also demonstrated that mitotic kinase Aurora A plays a crucial role in facilitating newly emerging mutant cells to pass through initial mitotic crisis , leading to eventual relapse [13] , which is in line with our proposal that acquisition of BCR-ABL mutations is a multi-step process [14] . To further delineate the mechanisms of BCR-ABL mutation acquisition , in the present study , we carried out microarray gene expression analysis of KCL-22 cells versus KCL-22M cells that are derived from KCL-22 cells after acquiring T315I mutation upon IM treatment [11] . Interestingly , we found that KCL-22M cells exhibit genome-wide gene expression changes in several pathways that may increase drug resistance , in addition to the presence of T315I mutation . Furthermore , altered expression of several myeloid differentiation genes indicates that KCL-22M cells are in a less differentiated state than KCL-22 cells . By exome sequencing , we found that the altered gene expression patterns are not obviously correlated with genome-wide codon mutations in KCL-22M cells . Inspired by the microarray analysis , we tested the effect of induced differentiation by all-trans retinoic acid ( ATRA ) that is frequently used in clinical treatment of acute promyelocytic leukemia ( APL ) [15] , [16] . We found that ATRA potently blocks acquisition of BCR-ABL mutations ( T315I , Y253H and E255K ) and regrowth of CML cells on imatinib treatment . ATRA executes its effect in part through activating expression of CD38 , a major NADase in mammalian cells [17] , which reduces cellular NAD+ levels and consequently inhibits the activity of SIRT1 . Consistently , we found that CD38 expression levels are significantly reduced as CML progresses from chronic phase to blast crisis , which may support high activity of SIRT1 in the late phase of the disease . This study suggests a novel role of cellular differentiation status and CD38 expression on acquisition of BCR-ABL mutations , and the potential therapeutic use of ATRA to inhibit CML acquired resistance to tyrosine kinase inhibitors .
We carried out microarray gene expression analysis of KCL-22M vs KCL-22 cells using Affymetrix gene chips . Triplicate RNA samples of each cell type were harvested and used for the study . Principal component analysis showed clear separation between KCL-22M and KCL-22 samples , indicting distinct biological groups ( Figure S1A ) . Expression of the vast majority of the genes from these two cell types was indistinguishable from the volcano plot ( Figure S1B ) , consistent with the fact these two cell types have only small biological difference except for IM resistance [11] . However , we identified 245 probe sets with expression change bigger than 1 . 5 fold and p value<0 . 05 , which formed separate hierarchical clusters ( Figure 1 and Table S1 ) . We compared these probe sets with the largest published microarray data of primary human CML samples by Radich et al [18] who showed signature gene expression changes as CML progresses from chronic to accelerated and blast crisis phases , as well as relapsed CML . By Venn diagram analysis , 21 probe sets were found overlapping with Radich's 3415 “phase reporter” gene sets ( Figure 1B ) . Since only 160 among the 245 probe sets were annotated ( Table S1 ) , the overlapping genes represented 13% of our annotated probe sets . Notably , among these 21 genes , many of them are involved in regulation of differentiation and development ( Figure 1B ) . Using gene set enrichment analysis ( GSEA ) [19] , we found that KCL-22M cells were significantly enriched for dasatinib resistance pathway genes [20] and doxorubicin/cisplatin resistance genes [21] found in solid tumors as well as genes activated in relapsed melanoma cells [22] ( Figure 2A–C ) . These changes were surprising given that the T315I BCR-ABL mutant is sufficient to confer resistance of KCL-22M cells to imatinib [11] and it would seem that activation of these resistance pathways would be unnecessary . The array data suggest that genome-wide transcriptome changes are likely coupled with BCR-ABL mutation acquisition process that occurs in KCL-22 cells in response to imatinib treatment , and which continues to be present in KCL-22M cells . This is in line with our previous finding that mutations in KCL-22M cells are acquired de novo instead of by simple outgrowth of cells with spontaneously acquired T315I mutation [11] , [14] . GSEA showed that KCL-22M cells had reduced expression of genes upregulated by NUP98/HOXA9 ( Figure 2D ) , a fusion gene that blocks differentiation and promotes CML transformation [23]–[25] , consistent with our previous finding that KCL-22M cells have reduced soft agar colony formation and transformation capability than KCL-22 cells [11] . Expression of mitotic genes was also significantly enriched in KCL-22M cells ( Figure 2E ) , consistent with the increased G2/M cell fractions in KCL-22M cells and their attempt to overcome mitotic crisis during the early stage of mutation acquisition [11] , [13] . Changes of several cell cycle related genes were also found in a previous study of primary CD34+ CML progenitor cells [26] , Figure S2 . Together , our microarray data faithfully recapitulate the experimental observations . By spectral karyotyping analysis , we previously showed that there are no gross chromosomal changes in KCL-22M cells compared to KCL-22 cells [11] . Interestingly , by analysis of KCL-22M>KCL-22 cells using the GSEA positional gene set analysis that allows identification of regional chromosomal changes ( indel , amplification & epigenetic silencing ) affecting gene expression [19] , we found 20 loci in KCL-22M cells with significant changes ( FDR<0 . 25 , p<0 . 05 , Table S2 ) , with the Chr4Q21 region having the most significant gene enrichment in KCL-22M cells ( Figure 2F ) . No significant loci were identified in the complimentary analysis ( KCL-22>KCL-22M ) as expected . These data indicate the possibility of some small chromosomal changes or epigenetic alteration accompanying with acquisition of BCR-ABL mutations . We then used Ingenuity Pathways Analysis to search for additional pathway changes in KCL-22M cells . The leading altered signaling pathway was “molecular mechanisms of cancer” ( Figure 3A ) . Among top ten canonical pathways , three were related with the increased stem cell functions including Wnt/β-catenin signaling ( Figure 3A ) . Hematopoietic development is one of the lead functional changes ( Figure S3 ) . Specifically , expression of 6 out of 7 myeloid cell differentiation pathway genes was significantly changed in a way to indicate the less differentiated status of KCL-22M cells than KCL-22 cells , and the expression changes of these genes were validated by real time PCR analysis ( Figure 3B ) . Both increased Wnt/β-catenin signaling and reduced myeloid differentiation are also among the top pathways for CML progression towards advanced disease in the Radich's study [18] . Two myeloid differentiation genes ( STAP1 and CSF1 ) were among the 21 overlapping genes mentioned above ( Figure 1B ) . Intriguingly , it is shown that chronic CML patients who relapsed after initially successful imatinib treatment ( many with acquisition of BCR-ABL mutations ) demonstrate gene expression signatures more similar to advanced disease than chronic phase [18] , and may have reduced differentiation as well . Therefore , our finding that BCR-ABL mutation acquisition process may be accompanied by reduced differentiation state of KCL-22 cells is clinically relevant . We next examined whether there are genetic alterations acquired in KCL-22M cells that may cause genome-wide gene expression changes . We performed Solexa exome capture sequencing of KCL-22 and KCL-22M cells , and generated about 130 million paired-end reads for each cell type . Over 98% of the sequences were aligned to human reference genome hg19 , covering more than 80% exons with >20× coverage . Single nucleotide variants ( SNVs ) identified in both cell types had >97% dbSNP concordance , and the overall transition/transversion ratio was the same at 1 . 90 in both cell types . After removing SNVs from KCL-22 cells , 3260 point mutations were identified specifically in KCL-22M cells . These mutations distributed throughout the chromosomes with a few mutation hot spots on several chromosomes ( Figure 4A ) . Among these mutations , only 208 were on coding exons of 194 genes , with a few genes bearing more than one mutation ( Table S3 ) . T315I mutation was identified as the only mutation on the ABL codons , consistent with our previous finding that T315I mutation is the sole mutation of BCR-ABL in KCL-22M cells [11] . No mutations were found in the known major epigenome regulators . By copy number variant analysis , we did not detect large amplification or deletion in KCL-22M cells compared to KCL-22 ( data not shown ) , in line with our previous spectral karyotyping analysis [11] . However , we identified 2206 small indels including 1643 deletions and 563 insertions specifically in KCL-22M cells , and they were distributed throughout chromosomes ( Figure 4B ) . The small indels caused frameshift in the codons of 33 genes ( Table S4 ) . Although Chr4Q21 was a most significant region for gene expression change , chromosome 4 carried mutation but not indel hot spots ( Figure 4A , B ) . When the 245 significant microarray probe sets were compared to genes with mutations and indels on coding exons , poor overlap was found ( Figure 4C ) , suggesting that global gene expression changes and mutations/indels may occur in parallel or separately . In line with this finding , we previously showed that BCR-ABL expression levels did not change in spite of its acquisition of T315I mutation in KCL-22M cells [11] . It is possible that global gene expression changes may be a result of certain yet-be-identified epigenome reprogramming process after BCR-ABL inhibition , not necessarily dependent on mutagenesis per se . KCL-22 cells are immature myeloid progenitor cells [27] . We set to explore if forced differentiation may affect CML acquired resistance by testing the effect of ATRA that can induce partial myeloid differentiation . ATRA is a therapeutically effective drug in treating APL patients by inducing differentiation in promyelocytic leukemia-retinoic acid receptor ( PML-RAR ) positive APL cells in which the differentiation is blocked [15] . We first examined whether ATRA co-treatment would prevent mutation acquisition and CML cell relapse on imatinib . We treated KCL-22 cells with 2 . 5 µM imatinib in combination with various concentrations of ATRA . ATRA co-treatment at concentrations of 0 . 1∼10 µM effectively blocked KCL-22 relapse ( Figure 5A ) . ATRA alone , at 5 µM and lower concentrations , did not significantly inhibit the growth or induce apoptosis of KCL-22 cells ( Figure 5B , C ) and did not change cell cycle ( not shown ) . ATRA co-treatment slightly increased the apoptosis rate upon imatinib treatment in KCL-22 cells ( Figure 5C ) , but did not significantly affect apoptosis in KCL-22M cells ( Figure 5D ) . In addition , KCL-22 cells relapse on the treatment with second generation tyrosine kinase inhibitors nilotinib and dasatinib through acquisition of T315I mutation [12] . We found that 1 µM ATRA co-treatment with nilotinib or dasatinib effectively blocked KCL-22 cell relapse as well ( Figure 5E , F ) . To determine if ATRA co-treatment may work for inhibiting CML acquired resistance by other BCR-ABL mutations or non-mutation-mediated resistance , we treated four CML resistance cell lines that were originated from KCL-22 cells but developed resistance differently: L1 , L7 and Ag11 lines through E255K , Y253H and T315I BCR-ABL mutations respectively , and Ag3 line through non-BCR-ABL mutation mediated mechanism [11] . We found that ATRA at 1 µM and higher concentrations blocked relapse of all four cell lines on IM ( Figure 6A ) . Interestingly , L1 , L7 , Ag3 and Ag 11 cells were more susceptible for apoptosis induction than KCL-22 cells when ATRA was combined with IM ( Figure 6B ) . However , apoptosis induction was not enhanced by ATRA/IM combination in K562 and KU812 CML cell lines ( data not shown ) . Together , these results indicate that combination of ATRA with a tyrosine kinase inhibitor can prevent acquired resistance through BCR-ABL mutations , and may also inhibit resistance by certain non-mutation-mediated mechanisms . We next examined how the timing of ATRA treatment may affect CML cell relapse . We treated KCL-22 cells with 0 . 1 , 1 , 5 , and 10 µM ATRA for 24 h , 48 h or 72 h , followed by removing the drug and washing cells thoroughly . The ATRA-primed cells were then treated with 2 . 5 µM IM in the absence of ATRA . As shown in Figure 7A , 24 h pre-treatment with 5 or 10 µM ATRA completely blocked cell relapse whereas 1 µM ATRA significantly delayed the relapse . The same results were seen for ATRA pre-treatment for 48 and 72 h ( Figure S4 ) . These data suggest that transient ( 24 h ) exposure to ATRA can significantly alter the ability of KCL-22 cells to acquire BCR-ABL mutations for IM resistance , even though the effect is less pronounced with lower concentrations of ATRA than when ATRA and IM are used simultaneously . We then determined the effect of adding ATRA after the initiation of IM treatment . KCL-22 cells were treated with 2 . 5 µM IM first , followed by the addition of 1 µM ATRA at different time points . Interestingly , ATRA was fully effective only if it was added simultaneously with imatinib or one day after the start of imatinib , and ATRA addition at 3 days after the start of imatinib or later could not block the relapse ( Figure 7B ) . These results suggest that de novo BCR-ABL mutation acquisition occurs rapidly , and may be mostly completed within 3 days of imatinib treatment; once completed , addition of ATRA can not block cell relapse . ATRA can induce dramatically increased expression of CD38 , a leukocyte differentiation antigen and cell marker for committed hematopoietic progenitor cells [28] , [29] . Indeed , we found that ATRA at concentrations as low as 0 . 1 µM efficiently converted KCL-22 cells from CD38− to CD38+ ( Figure 8A and Figure S5 ) , consistent with its role in promoting myeloid differentiation . Noticeably , early studies suggested that ATRA can stimulate myeloid differentiation of blast crisis and chronic phase CML cells in vitro and in vivo [30] , [31] . Besides being a cell marker , CD38 is also a potent cellular NAD+ regulator that hydrolyzes NAD+ to make cyclic ADP ribose [17] . Knockout of CD38 in mice significantly increases intracellular NAD+ content and SIRT1 activity [32] , [33] . Given that SIRT1 plays a crucial role in promoting acquisition of BCR-ABL mutation [12] , we hypothesized that ATRA-induced CD38 expression may impact cellular NAD+ metabolism and SIRT1 functions , and thus influence BCR-ABL mutation acquisition . Consistent with increased CD38 expression , we found that cellular NAD+ levels were significantly reduced upon ATRA treatment ( Figure 8B ) . We further sorted CD38high and CD38low/negative populations from KCL-22 cells after 24 h-treatment with 1 µM ATRA ( Figure 8C ) . The sorted cells were then subjected to IM treatment in the absence of ATRA . CD38high population showed a much more delayed relapse on IM treatment compared to CD38low/negative population ( Figure 8C ) , indicating that CD38 may play a role in CML cell relapse on imatinib . To examine if CD38 may have direct contribution , we constructed a CD38 overexpression cassette in the PITA-puro lentiviral vector . KCL-22 cells were transduced with the CD38-expressing or control vector and enriched by puromycin selection ( Figure 8D ) . CD38 over-expression significantly reduced cellular levels of NAD+ , but not NADH ( nicotinamide adenine dinucleotide plus hydrogen ) ( Figure 8E ) . CD38 over-expressing cells showed no difference in proliferation and survival compared to mock-transduced cells , but displayed slightly increased apoptosis on the IM treatment ( Figure 8F and not shown ) , similar to that seen with ATRA treatment ( Figure 5C ) . The puromycin enriched CD38 over-expressing cells exhibited a moderate delay in relapse on IM treatment and significant reduction of IM resistant soft agar colony formation ( Figure S6 ) . To remove interference from the remaining CD38− cells in puromycin enriched cells , we flow-sorted CD38+ cells ( gate R5 in the lower panel of Figure 8D ) . In the sorted CD38 over-expressing population , the cell relapse on IM was completely blocked in liquid culture , and this effect was partially reversed by supplying NAD+ to the culture medium ( Figure 8G ) . Similarly , the IM resistant colony formation on soft agar was eliminated in the sorted CD38 over-expressing cells , and the effect was partially rescued by NAD+ supplement ( Figure 8H ) . Our results suggest that CD38 expression in CML cells can inhibit the ability of the cells to acquire BCR-ABL mutations upon IM treatment through regulating NAD+ metabolism . SIRT1 promotes aberrant DNA damage repair and facilitates BCR-ABL mutation acquisition [12] . However , we did not observe significant change of SIRT1 protein levels in KCL-22 cells upon ATRA treatment ( not shown ) . To examine the impact of NAD+ reduction on SIRT1 enzymatic activity upon ATRA treatment , we analyzed acetylation of SIRT1 substrates FOXO1 and Ku70 . As shown in Figure 9A and B , FOXO1 acetylation was increased with ATRA treatment by flow cytometric analysis and Ku70 acetylation was increased by immunoprecipitation and Western blotting , suggesting inhibition of SIRT1 activity . We previously developed DNA damage repair reporter assays for non-homologous end joining ( NHEJ ) and homologous recombination ( HR ) repair in KCL-22 cells , and showed that SIRT1 promotes both NHEJ and HR repair in these cells [12] . We found that ATRA treatment significantly reduced both NHEJ and HR repair in KCL-22 cells ( Figure 9C ) , consistent with the reduction of SIRT1 activity . Altogether , our results indicate that ATRA-induced cellular differentiation blocks BCR-ABL mutation acquisition in CML cells , in which CD38 activation appears to play an important role by reducing cellular NAD+ content and thus inhibiting SIRT1 activity . Given the roles of CD38 described above , we examined if CD38 expression may change during CML progression . CD38 was not in the Radich's 3415 “phase reporter” gene sets and its mRNA change was less significant [18] . We therefore analyzed CD38 protein expression from archived cell sorting data of CML and normal CD34+ progenitor cells that were collected on the same cell sorter with the same parameters after pre-enrichment by density gradient and immunomagnetic column separation [34] . Intriguingly , we found that overall CD38 protein levels were increased in chronic phase CML , but reduced in blast crisis CML ( Figure 10 ) . Besides , variation of CD38 expression among samples was larger in CML than in normal CD34+ cells . The increase of CD38 protein in chronic CML is reminiscent of previous findings that BCR-ABL enhances differentiation of long-term repopulating stem cells and loss of cell quiescence [35] , [36] , whereas reduction of CD38 protein in blast crisis CML is in line with the reduced myeloid differentiation described by Radich et al [18] . Reduction of CD38 in blast crisis cells may allow sufficient NAD+ supply for markedly increased SIRT1 expression in blast crisis CML [37] .
Our microarray and exome sequencing analysis of the paired T315I BCR-ABL mutant KCL-22M cells vs parent KCL-22 cells not only provided data supporting our previous experimental observations , but also revealed several new features of the process of BCR-ABL mutation acquisition . 1 ) Mutation acquisition is accompanied by activation of several drug resistance pathways . 2 ) Mutant cells exhibit reduced expression of myeloid differentiation genes . 3 ) There are a number of exome-wide point mutations and small indels accumulated in the mutant cells , but these genetic lesions don't seem to determine the changes in global gene expression; instead , they may occur in parallel or separately . The gene expression changes suggest possibly a certain degree of epigenetic reprogramming in the parental KCL-22 cells in response to IM treatment . Intriguingly , drug resistance in a subset of non-small cell lung cancer patients is associated with epithelial-to-mesenchymal transition that transforms non-small cell lung cancer into small cell lung cancer [38] , which also suggests possible epigenome reprogramming in that setting . In line with potential epigenetic reprogramming during mutation acquisition , we showed that forced differentiation of KCL-22 cells by ATRA effectively blocked acquisition of resistance in KCL-22 cells on IM treatment . ATRA plays a wide variety of roles in regulating cell growth , development and differentiation . In the normal hematopoietic system , ATRA enhances the growth and differentiation of hematopoietic progenitors of the granulocytic lineage , and increases maintenance and self-renewal of murine long-term repopulating hematopoietic stem cells [39] , [40] . ATRA induces terminal differentiation of abnormal promyelocytes in APL and is the first-line drug for treating APL patients [41] . ATRA also induces myeloid differentiation of hematopoietic stem/progenitor cells from blast crisis CML in vitro and in vivo [30] , and from chronic CML in vitro [31] . As a pre-IM era drug , ATRA had only limited effect on CML treatment either in a single drug or combination with other drugs [42]–[44] . However , its effect with IM combination has not been tested . The potent effect of ATRA to prevent acquisition of BCR-ABL mutation shown in the present study suggests that ATRA could be a simple and effective agent to use in combination with tyrosine kinase inhibitors to prevent acquisition of resistance and improve outcomes of CML , particularly in the advanced phases . Although advanced CML without a history of IM treatment is extremely rare in developed countries nowadays , such patients are still more frequently seen in some developing countries and many of them have no or limited access to TKIs , especially newer generation drugs . A simple ATRA combination may significantly benefit these patients . For the clinical purpose , ATRA should be better administrated together with tyrosine kinase inhibitors . The concentrations of both IM and ATRA illustrated in this study are clinically achievable . The dosage of ATRA for CML patients ranges from 45 to 175 mg/m2/day [42] . Following 45 mg/m2/day oral dose of ATRA , the peak plasma concentration is from 0 . 1 to 8 µM , with a median peak concentration of about 1 µM [45] . Similarly , IM given to chronic phase CML patients at 400 mg/day produces an average peak plasma concentration of 4 . 4 µM and trough concentration of 2 . 0 µM [46] , and they will increase further in advanced phase patients with higher IM doses . Mechanistically , ATRA efficiently induced partial myeloid differentiation of KCL-22 cells with robust stimulation of CD38 expression . CD38 is widely expressed in most mature blood and immune cells and 90–99% of CD34+ hematopoietic progenitor cells [47] , [48] . In myeloid cells , expression of CD38 can be efficiently modulated by ATRA , 1α , 25-Dihydroxyvitamin D3 , IFN-α/γ , rotenone , etc . [28] , [49] , [50] . Other than being a cell surface marker , CD38 is also recognized as a multifunctional enzyme that uses NAD+ as a substrate to generate second messenger and participates in signal transduction pathways involved in the regulation of cell growth and differentiation [17] . Most notably , it is the main cellular NADase in mammals and regulates cellular levels of NAD+ in multiple tissues and cells . High levels of CD38 expression depleted cellular NAD+ and suppressed BCR-ABL mutation acquisition in KCL-22 cells . Importantly , such effect can be partially rescued by supplying NAD+ directly to the culture medium . Therefore , for the first time , to our knowledge , we revealed the status of cellular differentiation and CD38 expression can change the ability of cancer cells to acquire resistant genetic mutations to a therapeutic agent . NAD+ is required for functions of many cellular enzymes including sirtuins . Sirtuins regulate multiple physiological processes such as cell proliferation , survival , DNA damage repair , energy metabolism , insulin secretion , aging and longevity [51] , [52] . Sirtuins have diverse and often opposing roles in human cancer [53] , [54] . SIRT1 is the most studied sirtuin protein . SIRT1 is up-regulated in malignant cells in a variety of cancers [53] , [54] , and has a particularly important role in cancer drug resistance [55] . We have shown that BCR-ABL transformation activates SIRT1 through both kinase dependent and independent manners [37] . SIRT1 inhibition suppresses CML progression and sensitizes CML stem cells to IM–induced apoptosis [37] , [56] . SIRT1 also promotes acquisition of BCR-ABL mutation for IM resistance in CML cells through facilitating error prone DNA damage repair [12] . Consistently , our current study showed that reduction of NAD+ lowered SIRT1 enzymatic activity and DNA damage repair in KCL-22 cells , which may lead to inhibition of KCL-22 cell relapse on IM . Important to note that SIRT1 is a key epigenome regulator and deacetylates multiple histone substrates [53] . In this regard , however , it is unclear how and if SIRT1 may play a role in epigenome reprogramming of KCL-22 cells , which remains an interesting subject for future investigation . In addition , high levels of CD38 expression was required to block KCL-22 cell relapse and NAD+ supplementation only partially rescued the phenotypes in CD38 over-expressing cells , suggesting that additional effects of ATRA-induced differentiation or CD38 expression may have on these cells . CD38 is an important cell marker in human hematopoietic stem cells ( HSCs ) [48] . CD34+CD38− bone marrow cells are highly enriched for long-term repopulating HSCs while CD34+CD38+ cells are more committed progenitor cells . These same markers also apply to CML leukemic stem cells . Given that CD38− cells may have higher NAD+ levels and more active SIRT1 , CD34+CD38− CML stem cells might have more permissive cellular environment for acquisition of genetic mutations . This view is in line with a recent finding that primitive leukemic stem cells may be the origin of the cells acquiring resistant mutations in chronic CML [57] . In stark contrast , the majority of chronic CML patients benefit from years' IM treatment without acquiring BCR-ABL mutation even though CML stem cells are persistent . Although the precise mechanisms underlying this discrepancy are not known , there may be several explanations . First , SIRT1 is activated much more in advanced and blast crisis than in chronic phase CML CD34+ cells [37] . The lower levers of SIRT1 activation in chronic CML may be insufficient to promote strong mutagenic response . Second , CD38 levels are elevated in chronic CML , reducing NAD+ supply as mentioned above . Third , acquisition of BCR-ABL mutation may ironically inhibit its transformation ability in CD34+CD38− cells in the chronic phase CML , somewhat similar to that in KCL-22M cells described above . Fourth , chronic CML stem cells may have distinct epigenomic composition of the translocation locus unfavorable for mutagenic response to the treatment . In spite of these , a small percentage of chronic CML patients may eventually relapse with acquisition of BCR-ABL mutations . It remains possible that ATRA/TKI combination could also benefit the management of the disease in chronic phase , considering 1 ) relapsed chronic CML patients with or without acquisition of BCR-ABL mutations assume gene expression patterns closely related to blast crisis CML and likely with reduced differentiation [18]; 2 ) ATRA can still induce myeloid differentiation of chronic CML stem/progenitor cells [31] even though these cells have elevated CD38 levels as described above; 3 ) ATRA/TKI combination may inhibit certain acquired resistance in the absence of BCR-ABL mutations as described above . However , as in blast crisis CML , the maximal benefit of ATRA would be when it is applied with TKIs from the beginning or before mutations are acquired . Besides CML , CD38 expression is used as a prognostic indicator in chronic lymphocytic leukemia ( CLL ) , and CD38 expression is closely related with Ig V gene hypermutation status [58] . Patients with lower percentage of CD38+ B-CLL cells carry higher Ig VH mutations . It is believed that down-regulation of CD38 may promote this hypermutation phenotype , but its precise role remains elusive [59] . It would be interesting to determine if SIRT1 may be involved in such regulation . Finally , our study with ATRA on KCL-22 cell relapse revealed that acquisition of BCR-ABL mutation is a rapid process , likely completed within three days of IM treatment . Although it has been proposed that preexisting mutations account for acquired resistance in primary human cancers by mathematical model studies [60] , [61] , our finding of rapid mutation acquisition calls for caution of such a notion because the variation in timing of relapse in CML and other cancer patients in several weeks [60] , [61] would prevent distinction of pre-existing mutations from de novo acquired mutations . The precise mechanisms for rapid mutagenesis and critical timing of ATRA remain to be further determined . We previously showed that early apoptotic cells induced by IM sustain the highest levels of reactive oxygen species [11] . We hypothesized that a small fraction of early apoptotic cells may abolish apoptotic program while suffering substantial DNA damage , leading to mutagenesis [14] . The present study provides evidence of a large number of genome-wide genetic lesions likely as a consequence of massive DNA damage , and that upregulation of multiple resistant gene expression pathways perhaps by rapid epigenome reprogramming may help these cells abandon apoptotic program . ATRA treatment perhaps not only promotes myeloid differentiation but also provides a counter epigenetic reprogramming for global gene expression , which occurs in conjunction with reducing DNA damage repair , and thus its timing is crucial . Further studies will be needed to uncover this mystery . In summary , we have used microarray-based gene expression analysis to show that global gene expression changes accompany BCR-ABL mutation acquisition in response to IM treatment , and that forced differentiation of CML cells with ATRA stimulates CD38 expression and blocks BCR-ABL mutation acquisition and CML cell relapse on IM in part through down regulation of NAD+ levels and SIRT1 activity . This study has translational implication for potential use of ATRA in combination with BCR-ABL inhibitors to improve CML treatment .
CML cell lines KCL-22 , K562 and KU812 were purchased from German Collection of Cell Cultures , Braunschweig , Germany , and grown in RPMI 1640 medium with 10% fetal bovine serum ( Hyclone , SH30071 . 03 ) . KCL-22M cells harboring T315I BCR-ABL mutation were derived from KCL-22 cells [11] . Imatinib , nilotinib and dasatinib were purchased from LC Laboratories ( Woburn , MA ) . ATRA was purchased from Sigma . Imatinib resistance assay was performed as described before [11] . In brief , one half million KCL-22 cells were seeded in 1 ml medium per well in 24-well plates , and treated with IM alone or in combination with other drugs . Cell viability was assessed by trypan blue exclusion and cell count was performed every 3–5 days . Mutant cell clonogenic assay was performed using a standard two-layer soft agar culture ( 0 . 6% agarose for the bottom layer and 0 . 35% agarose for the top layer ) by seeding one million cells per well with imatinib in six-well plates . For plating efficiency control , 500 cells per well were seeded . Colonies were scored after staining with 0 . 005% Crystal Violet . Total RNA was extracted from KCL-22 and KCL-22M cells using Trizol ( Invitrogen ) . Triplicate RNA samples each were submitted to the City of Hope Functional Genomic Core for microarray expression analysis . Quality of RNA samples was checked using Agilent Bioanalyzer 2100 . Samples were processed with GeneChip Two-Cycle Target Labeling and Control Reagents ( Affymetrix , Santa Clara , CA ) , and hybridized to Affymetrix GeneChip Human Gene 1 . 0 ST Arrays . Microarray data analysis was performed using Partek Genomics Suite 6 . 6 ( Partek , Inc . ) . RMA algorithm was adopted to normalize and summarize the intensities of probes into gene-level expression . Appropriate statistical model was used to identify differentially expressed genes between KMP3 and KP7 sample groups . Genes with significantly differential expressions were selected by use of a cutoff of a 1 . 5-fold change in the level of expression and p-value cutoff of <0 . 05 . The normalized signals for the whole array for the 6 samples were analyzed using Gene Set Enrichment Analysis ( GSEA ) software to determine the enriched pathways between KMP3 and KP7 . Given the limit of sample size , gene-set permutation was adopted with 1000 permutations against molecular signatures database v3 . 0 . The tested signatures database included C1 positional gene sets , C2CP canonical pathways , C2CGP chemical and genetic perturbations and C5 GO gene sets . The genes showing altered expression were categorized and further investigated by enrichment analysis on the basis of their cellular components , biological processes , molecular functions , and canonical pathways using the Ingenuity Pathways Analysis ( Ingenuity , Mountain View , CA ) software . To obtain comprehensive view for the differentially expressed genes , core analysis was performed including network generation , functional analysis and canonical pathway analysis on the filtered ( |FC|>1 . 5 , P<0 . 05 ) genes . Microarray study was carried out in City of Hope Integrative Genomics Core . To validate the array data , SYBR green real-time qPCR was performed . Total RNA was extracted using Trizol ( Invitrogen ) and residual genomic DNA was removed by DNase-I treatment . One microgram of DNase-I treated total RNA per sample was used for cDNA synthesis using SuperScript III First-Strand Synthesis System ( Invitrogen ) with oligo ( dT ) . The synthesized cDNA was treated with RNase H for 20 min at 37°C to remove RNA . qPCR was performed in separate tubes using universal SYBR green master mixture ( KAPA Biosystems ) and gene specific primers on Applied Biosystems 2720 PCR thermal cycler . The PCR primers are listed in Supporting Table S5 . Three micrograms of genomic DNA was sheared by sonication using a Bioruptor ( Diagenode ) . The resultant 150- to 250-bp fragmented DNA was end-repaired and ligated to Illumina adaptor oligonucleotides . Ligation products were purified and successfully ligated fragments were amplified with a 10-cycle of PCR . The enriched PCR products ( 500 ng ) were subject to the exome capture procedure using the SureSelect Human All Exon v4 Target Enrichment Kit ( solution magnetic bead capture ) according to the manufacturer's protocols ( Agilent Technologies , Inc . ) . Post-capture LM-PCR amplification was performed using the Herculase II Fusion DNA Polymerase ( Agilent ) for 10 cycles of amplification with primer set ( Forward primer: 5′-CAAGCAGAAGACGGCATACG-3′; reverse primer: 5′-AATGATACGGCGACCACCGA-3′ ) . After the final Agencourt Ampure XP bead ( Beckman Coulter ) purification , quantity and size of the library was analyzed using the Agilent Bioanalyzer 2100 DNA high Sensitivity chip . Library templates were prepared for sequencing using Illumina's cBot cluster generation system with TruSeq PE Cluster V3 Kit . Sequencing runs were performed in paired-end mode using the Illumina HiSeq 2000 platforms and TruSeq SBS V3 Kits . Image analysis and base calling were performed using Illumina's default pipeline . Sequencing runs generated approximately 130 million paired reads for each sample . The sequences were aligned to the human genome reference sequence hg19 using Novoalign . The sequences that were PCR duplicates ( aligned to the same genome location ) were removed by Picard . SNVs ( single nucleotide variants ) in each sample were identified and their concordance to dbSNP134 was assessed . KCL-22M specific SNVs were identified by comparing to the KCL-22 sample and then annotated by SeattleSeP annotation web site . The missense/nonsense/splice site SNVs were kept . This produced 3260 KCL-22M specific mutations and among them , 208 were coding exon mutations . For copy number analysis , the average coverage in each 10 k non-overlapping window was calculated for each sample and then CNVs ( copy number variants ) were identified by using DNAcopy's CBS algorithm . For detection of indels , Samtools pileup file was parsed to select the positions with indels . These positions were filtered to select candidate indels in KCL-22M with the following criteria: minimum coverage ≥10 , indel coverage ≥3 , and indel frequency ≥15% . The indels present at the same position in KCL-22 were removed . The candidate indels that fell into coding exons were selected . The indels were annotated at SeattleSeq annotation web site and the ones causing frame shift were kept ( 33 indels ) . To search for additional deletions , insertions , inversions , tandem duplications and other structural variants , we used Pindel [62] . To prevent possibility of false positives , indels reported by Samtools in KCL-22 cells were removed , and indels located at genomic loci without any reads in KCL-22 cells , which does not have enough information to conclude a specific indel in KCL-22M , were removed . Additional criteria included total coverage in KCL-22M ≥5 and indel frequency ≥20% . These resulted in 1643 deletion and 563 insertion that were KCL-22M specific . Pindel did not report any KCL-22M specific inversion , tandem repeats or large insertion that seemed to be real when visually inspecting the region or manually realign the reads to hg19 with Blat . The above identified mutations and indels have not been validated by targeted re-sequencing except for BCR-ABL mutation . Exome sequencing study was carried out in the City of Hope Integrative Genomics Core . For fluorescence-activated cell sorting or analysis , half million cells were stained with fluorophore conjugated antibodies in a buffer ( 0 . 5% bovine serum albumin in phosphate-buffered saline ) for 15 min on ice . Antibodies used for analysis and sorting were: APC-anti CD38 , FITC-anti CD38 , PE-anti CD90 , APC-anti-CD11b ( BD Pharmingen ) , and rabbit polyclonal anti-acetylated FOXO1 ( Santa Cruz Biotech ) . Apoptosis was analyzed by annexin-V ( BD Pharmingen ) staining . Flow cytometry was performed at the City of Hope Flow Cytometry Core . For Western blot , rabbit monoclonal anti-human SIRT1 ( Epitomics ) , mouse monoclonal anti-Ku70 ( Neomarker ) were used . To analyze Ku70 acetylation , we pulled down Ku70 from total cell lysate with anti-Ku70 and protein A/G plus-agarose beads ( Santa Cruz ) followed by acetylation detection with the rabbit anti-acetyl lysine antibody ( Cell Signaling ) . CD38 cDNA was kindly gifted by Prof . Elena Zocchi and subcloned into PITA-puro lentiviral vector that contains a puromycin selection cassette . PITA-puro vector was used as a mock control plasmid . The lentiviral packaging for PITA-puro and PITA-CD38 was performed as described previously [11] . Transduction was typically carried out with multiplicity of infection around 5 . To enrich the transduced cells , cells were treated with 2 µg/mL puromycin for 4 days and allowed to recover in normal medium for 6 days before analysis . The doxycycline inducible DNA damage repair report systems in KCL-22 cells with DR-GFP for HR repair and EJ5-GFP for NHEJ repair were established previously [12] . These cells were then transfected with PITA-SCR or PITA-CD38 lenti-virus for 16 h followed by addition of 5 ng/mL doxycycline to induce I-SceI expression . After another 48 h culture , the cells were analyzed by flow cytometry for GFP expression to determine the repair efficiency . GFP+ cells were the successfully repaired cells . To determine the effect of ATRA treatment on DNA repair , cells were incubated with ATRA for 3 days then co-treated with 5 ng/mL doxycycline for another 48 h before flow cytometry analysis .
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Acquired resistance through genetic mutations is a major mechanism for cancer drug resistance and accounts for the short life of targeted therapy in several types of human cancer . Mechanistically , however , very little is understood about how resistant mutations are actually acquired during cancer therapy . In this manuscript , we used chronic myelogenous leukemia ( CML ) as a disease model and showed that mutation acquisition process is accompanied by global genome transcriptional reprogramming and reduction of cellular differentiation status . Forced cell differentiation by all-trans retinoic acid ( ATRA ) potently blocks acquisition of genetic mutations and CML acquired resistance . ATRA effect is mediated , in part , through stimulating CD38 gene expression , which reduces cellular cofactor nicotinamide adenine dinucleotide ( NAD+ ) content and thus the activity of NAD+-dependent protein deacetylase SIRT1 that promotes error-prone DNA damage repair and mutagenesis . Our findings provide novel insight of mutation acquisition process during targeted therapy for CML . This study has translational implication in clinical treatment of CML , and perhaps other malignancies , by combining a differentiation agent to overcome mutation-mediated drug resistance if possible .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"oncology",
"biochemistry",
"medicine",
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"health",
"sciences",
"genetics",
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2014
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ATRA-Induced Cellular Differentiation and CD38 Expression Inhibits Acquisition of BCR-ABL Mutations for CML Acquired Resistance
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The Staphylococcus aureus manganese transporter protein MntC is under investigation as a component of a prophylactic S . aureus vaccine . Passive immunization with monoclonal antibodies mAB 305-78-7 and mAB 305-101-8 produced using MntC was shown to significantly reduce S . aureus burden in an infant rat model of infection . Earlier interference mapping suggested that a total of 23 monoclonal antibodies generated against MntC could be subdivided into three interference groups , representing three independent immunogenic regions . In the current work binding epitopes for selected representatives of each of these interference groups ( mAB 305-72-5 – group 1 , mAB 305-78-7 – group 2 , and mAB 305-101-8 – group 3 ) were mapped using Hydrogen-Deuterium Exchange Mass Spectrometry ( DXMS ) . All of the identified epitopes are discontinuous , with binding surface formed by structural elements that are separated within the primary sequence of the protein but adjacent in the context of the three-dimensional structure . The approach was validated by co-crystallizing the Fab fragment of one of the antibodies ( mAB 305-78-7 ) with MntC and solving the three-dimensional structure of the complex . X-ray results themselves and localization of the mAB 305-78-7 epitope were further validated using antibody binding experiments with MntC variants containing substitutions of key amino acid residues . These results provided insight into the antigenic properties of MntC and how these properties may play a role in protecting the hostagainst S . aureus infection by preventing the capture and transport of Mn2+ , a key element that the pathogen uses to evade host immunity .
Staphylococcus aureus protein MntC is the ligand-binding component of the ABC-type manganese transporter MntABC , which is at least partially responsible for the organism’s resistance to the oxidative stress [1 , 2] . The protein is expressed during early stages of infection [3] and binds manganese with high affinity [4] . Active vaccination with recombinant S . aureus MntC reduced bacterial burden in a murine bacteremia model of infection [3] , making MntC a promising vaccine candidate . As such , MntC is a key component of an experimental four-antigen ( SA4Ag ) S . aureus vaccine which is currently undergoing clinical trials ( US government registry , trials #NCT01364571 , #NCT01643941 and #NCT02364596 –completed , trials #NCT02388165 and #NCT02492958 –ongoing ) . We have recently solved the 3-dimensional structure of MntC by X-ray crystallography ( PDB ID 4K3V , Fig 1 ) and provided detailed biophysical characterization of the protein [4] . Furthermore , in an earlier work from our laboratories [3] we reported generation of 23 monoclonal antibodies against MntC , with some of them being protective in an infant rat model of infection and being capable of inducing respiratory burst activity of neutrophils . Based on BIAcore binding interference patterns , these antibodies were subdivided into three interference groups [3] . In the current report we identified binding epitopes for selected representatives of each of those groups . Monoclonal antibodies are powerful tools for biomedical research and biotherapeutics . Their ability to recognize and bind specific targets with very high affinity is invaluable for a wide variety of in vitro and in vivo applications [5] . In vaccine research and development monoclonal antibodies are used , ( i ) to identify epitopes that elicit functional immune responses , ( ii ) to study surface expression of antigens on clinical isolates in vivo and in vitro , ( iii ) to assess preservation of the functionally important epitope ( s ) , ( iv ) in antigen identity testing , and ( v ) in product quality control . Understanding the mechanisms of the antibody-antigen interaction via epitope mapping is of utmost importance in biopharmaceutical research and development , and in biomedical research in general . The knowledge gained from monoclonal antibody epitope mapping can augment targeted vaccine development [6 , 7] , and aid in the development of new therapies . Furthermore , these studies can increase the understanding of the molecular mechanisms of existing therapies and shed light on the pathogenic mechanisms utilized by these disease-causing agents . One of the common strategies for monoclonal antibody epitope identification is synthesis of overlapping linear peptides derived from the antigen amino acid sequence , with subsequent identification of the peptides that bind to the antibody of interest [8] . A somewhat similar strategy involves attachment of the peptides to a solid support , creating peptide arrays [9] , followed by probing of the arrays with the antibody of interest . While straightforward , these approaches are limited to the identification of linear epitopes . As such , they are not particularly useful for identification of protective epitopes , the vast majority of which are conformational [10 , 11] . The same challenge hampers epitope mapping using phage display ( recently reviewed by Pande and co-workers [12] ) . Limited proteolysis followed by mass spectrometry [13–15] has the potential to identify conformational epitopes , however the resolution of this technique is quite limited . The only two approaches currently capable of providing residue-specific description of the antibody-binding epitopes are X-ray crystallography and NMR spectroscopy . Technical challenges associated with these methods include potential difficulties in co-crystallization of the antigen-antibody complexes for X-ray crystallographic analysis and antigen molecular mass restrictions for NMR spectroscopy . The need to produce Fab fragments of the antibodies , requirements for extremely pure material and low throughput further limit efficiency of the two techniques . Hydrogen-deuterium exchange mass spectrometry ( DXMS , also abbreviated as HDX-MS ) is emerging as a method of choice for monoclonal antibody epitope mapping . Distinct advantages of DXMS over many of the methods described above have been thoroughly reviewed elsewhere [16] , and will not be discussed here in detail . Briefly , DXMS is not limited to linear epitopes , provides higher resolution than proteolytic methods , does not require knowledge of the three-dimensional structure of the antigen , and provides higher throughput than X-ray crystallography without the same sample requirements ( i . e . , amount of material and high sample purity ) . The resolution of the method , however , may be lower than X-ray crystallography , although single amino acid resolution can be achieved in principle through method optimization , proper selection of proteolytic enzymes , digestion conditions or simultaneous fitting of the exchange data obtained from multiple overlapping peptides [17] . Basic principles of the technique have been described in several recently published review articles [18–20] , and will not be repeated here . DXMS was used in numerous studies to identify monoclonal antibody binding epitopes on diverse targets , ranging from food allergens to vaccine antigens [16 , 21–30] , as well as in several protein folding studies aimed at understanding of the folding intermediate structures [31 , 32] or identification of the core regions during amyloid formation [33] . Direct comparisons of DXMS results to the epitope mapping “gold standard” method of X-ray crystallography are still fairly scarce , however . In the current work we employed DXMS to identify binding epitopes of selected bactericidal monoclonal antibodies raised against MntC [3] . DXMS results were validated by co-crystallizing MntC with the Fab fragment of one of these antibodies , mAB 305-78-7 . The results were further confirmed in mAB 305-78-7 binding studies using MntC variants with site-directed amino acid substitutions at selected key residues involved in the epitope formation . Experimental data reported here provide useful insights into the mechanisms of protection afforded by the anti-MntC antibodies . It should be noted that an earlier work by Ahuja and co-workers [34] identified one of the protective epitopes on MntC . The results reported here identifed two more immunogenic regions on the protein and showed that the third antibody under study shares epitope with that of FabC1 identified by Ahuja et al .
General operational procedures and DXMS apparatus have been previously described in detail [35–39] . Optimization of proteolytic conditions and digest mapping of MntC have been reported elsewhere [4] . MntC and monoclonal antibodies were extensively dialyzed against PBS , pH 7 . 4 and concentrated to ~10 mg/mL using Amicon concentrators with molecular weight cutoff of 10 kDa . D2O-based PBS was prepared by diluting 10x PBS stock ( Cellgro , cat . # 46-013-CM ) with 100% D2O , thereby bringing deuterium oxide concentration to 90% . MntC was combined with the antibodies in a 1 . 5:1 molar ratio ( MntC:antibody , i . e . , 1 . 5 moles of MntC per 2 moles of binding sites ) to ensure that no unbound protein would remain in solution and incubated on ice for 60 minutes . Hydrogen-deuterium exchange was initiated by adding 4 . 3 volumes of cold D2O-based PBS to 1 volume of the antigen-antibody mixture ( final D2O concentration was , therefore , 73% ) . After 10 , 100 , 1 , 000 , 10 , 000 and 100 , 000 second incubation on ice , 64 μL samples were mixed with 96 μL of ice-cold quenching buffer ( 0 . 8% formic acid , 16 . 6% glycerol , 0 . 08 M Gdm-HCl ) to stop the exchange . Aliquots of 30 μL were frozen on dry ice and stored at -80°C until further use . Control samples ( without antibodies ) were prepared in the same way , except that they were initially diluted with H2O-based PBS to obtain desired protein concentration ( 15 μg total protein per 30 μL of the final frozen aliquot ) before initiating the exchange . To prepare non-deuterated MntC , 40 μL of 10 mg/mL protein stock was combined with 387 μL of H2O-based PBS and “quenched” as described above for the deuterated samples . Fully deuterated samples were prepared by incubating MntC ( 1 . 25 mg/mL final concentration ) in 0 . 5% formic acid , 73% D2O for 48 hours at room temperature and quenched , as described above . Proteolytic digestion , HPLC separation , mass spectrometric analysis and peptide identification were done exactly as previously described [4 , 40] . The amount of deuterium accumulating on each peptide at different time points with or without the antibody present was determined from changes in molecular weight of the corresponding peptide ( calculated from the peak centroids ) as a function of time #D=Dmax⋅Mw ( T ) −Mw ( ND ) Mw ( FD ) −Mw ( ND ) ( 1 ) where #D is the number of deuterons exchanged at each time point , Dmax is the maximum number of hydrogens that can be exchanged for deuterium on the peptide ( equal to the number of residues minus number of prolines minus 2 [41] ) , Mw ( T ) is the centroid peak value of the peptide at time T , Mw ( ND ) is the centroid peak value of the non-deuterated peptide , Mw ( FD ) is the centroid peak value of the fully deuterated peptide . Antibody binding epitopes were identified from the peptides showing decreased deuterium accumulation in the presence of the antibody . Back-exchange was not taken into account , since all samples were prepared identically and absolute deuterium accumulation numbers are not necessary to identify the epitopes . Cloning , expression and purification of recombinant MntC , as well as generation of the monoclonal antibody 305-78-7 , have been previously described [3] . The mAB 305-78-7 Fab fragment was generated using Thermo Scientific’s Pierce mouse IgG1 Fab and F ( ab’ ) 2 preparation kit ( catalog number 44980 ) , according to the kit manufacturer’s instructions . The macromolecular complex between MntC and the Fab fragment of mAB 305-78-7 was generated by combining equimolar amounts of MntC ( 40 mM Tris pH 7 . 5 , 0 . 3 M NaCl ) and the Fab fragment ( TBS pH 8 . 0 ) . The resulting solution was passed through a size exclusion column ( Superdex 200 ( 10/300 ) ) equilibrated in 10 mM HEPES pH 7 . 5 and 150 mM NaCl . The sample was concentrated to 5 . 16 mg/mL and crystals of the complex containing MntC and the Fab fragment of mAB 305-78-7 were grown by the hanging drop method using 1 M LiCl , 0 . 1 M MES , pH 6 . 0 and 20% PEG 6K as the precipitating reagents . The crystals were cryopreserved by adding 20% glycerol to the precipitating buffer and snap freezing in liquid nitrogen . The X-ray diffraction data were collected to 1 . 8 Å resolution at the Argonne National Laboratory ( APS ) using the 22-ID beamline ( SER-CAT , Southeast regional collaborative access team ) and then reduced and scaled with HKL2000 [42] . Initial phases were estimated by molecular replacement using the Fab fragment from PDB entry 1QGC as the input model in PHASER [43] . Molecular replacement yielded a single solution and the model was subjected to several rounds of rebuilding in COOT [44 , 45] alternating with subsequent minimization using BUSTER [46] . The quality of the model was judged by the decrease in R-factors . Refinement converged after several rebuilding cycles to an R-factor of 20 . 7% and Rfree of 23 . 6% . Crystallographic data collection and refinement statistics are summarized in S1 Table . The final model contains protein residues 16–113 and 118–292 for MntC , residues 1–212 for the Fab light chain , residues 1–126 and 134–213 for the Fab heavy chain , one glycerol molecule , one metal ion , and 197 water molecules . MntC residues 114–117 and Fab heavy chain residues 127–133 were not detected in the electron density maps due to disordering . All oligonucleotides were synthesized , and , when necessary , HPLC-purified by IDT ( Coralville , IA ) . Q5 High-Fidelity DNA Polymerase for PCR and all restriction endonucleases were purchased from New England Biolabs ( Ipswich , MA ) and were used according to manufacturer’s recommendations . pLH94 , a vector for expression of the MntC H234F E247L K254M variant protein with no 6xHis-tag ( used in the ITC experiments ) , was generated by two rounds of site-directed mutagenesis . To introduce MntC H234F and K254M substitutions into pLP1215 , a vector for expression of wild-type MntC , mutagenesis was performed with the QuikChange Lightning Multi Kit ( Agilent Technologies , Santa Clara , CA ) according to the manufacturer’s instructions . The QuikChange Primer Design Program ( Agilent Technologies ) was used to generate sequences of mutagenic oligonucleotides oLH553 , oLH556 , and oLH557 ( S2 Table ) , which were used in the first round of mutagenesis . The mutagenesis reaction was transformed into E . coli XL-10 Gold cells ( Agilent Technologies ) . The presence of mutations yielding the MntC H234F K254M allele and the absence of secondary mutations was confirmed by DNA sequencing . This resulting plasmid , pLH91 , was subjected to an additional round of mutagenesis with the QuikChange II XL kit ( Agilent Technologies ) . The kit was used according to the manufacturer’s instructions , and mutagenic oligonucleotides used in the reaction ( oLH569 and oLH570 , S2 Table ) , were designed with the QuikChange Primer Design Program . The mutagenesis reaction was transformed into E . coli XL-10 Gold cells . The presence of mutations yielding the MntC H234F E247L K254M allele and the absence of secondary mutations were confirmed by DNA sequencing . Recombinant protein was expressed and purified as described earlier [3] . Two additional primers ( S2 Table ) were used in generating vectors encoding histidine-tagged proteins subsequently used in Octet analysis . Wild-type , single mutant , and combination mutant MntC alleles were amplified by PCR with primers pLP1215 NdeI_S and pLP1215 BamHI_AS ( S2 Table ) , and the resulting fragments were cloned into pCR-Blunt II-TOPO vector ( Life Technologies , Carlsbad , CA ) . These inserts were excised with an NdeI/BamHI digest , gel-purified , and cloned into pET-19b at the NdeI/BamHI sites in-frame with the N-terminal His-tag encoded by the vector . The presence of the desired mutations and the absence of secondary mutations were confirmed by DNA sequencing . The final expression constructs were transformed into E . coli BL21 ( DE3 ) chemically competent cells ( Thermo Fisher Scientific , Waltham , MA ) . The expression host strains were grown in Terrific Broth ( 500 mL , 37°C , 225 rpm shaking ) until the cultures reached exponential phase . IPTG was added to a final concentration of 1 mM , and the cells were harvested 4 hours later . Cells were lysed with a French pressure cell press , and recombinant MntC proteins were purified with HisPur Ni-NTA Agarose ( Thermo Fisher Scientific ) in batch mode followed by size-exclusion chromatography . The folding state of MntC-pLH94 was confirmed using far- and near-UV CD spectroscopy . Far- and near-UV CD spectra were collected on a Jasco J-810 spectropolarimeter in rectangular quartz cuvettes with path lengths of 1 mm and 1 cm , respectively . Temperature was controlled using Jasco Peltier-type PTC-423S cell holder . Far-UV CD spectra were recorded in PBS , pH 7 . 4 at the protein concentration of 0 . 12 mg/mL . Spectral interval– 200–260 nm , step size– 0 . 1 nm , bandwidth– 3 nm , experimental temperature– 20°C , scanning speed– 50 nm/min , 5 accumulations were averaged for each spectrum . Near-UV CD spectra were recorded in 50 mM Na cacodylate pH 7 . 0 , 150 mM NaCl . Spectral interval of the near-UV CD data– 250–320 nm , other scan parameters were the same as in the far-UV CD experiments . Data were corrected by subtracting spectra of the corresponding buffers and smoothed using adjacent neighbor averaging of 21 points . All of the isothermal titration calorimetry experiments were done on a VP-ITC instrument ( Microcal , Northampton , MA ) . Mn2+ binding to the wild type MntC versus MntC-pLH-94 was characterized in 50 mM Na cacodylate pH 7 . 0 , 150 mM NaCl . 32 . 5 μM solution of wild type MntC or 31 . 8 μM solution of MntC-pLH94 were titrated with a 0 . 33 mM solution of MnCl2 at 37°C . An initial 2-μL injection was followed by 8-μL injections at 240 second intervals until no heat exchanges were observed . Injection rate was 0 . 5 μL/sec . Reference power was set to 15 μcal/sec . To characterize MntC interactions with mAB 305-78-7 , 3 . 3 μM solutions of the antibody in 50 mM Na cacodylate pH 7 . 0 , 150 mM NaCl were titrated with 112–143 μM solutions of either wild type MntC or MntC-pLH94 in the same buffer . Experiments were run at 37°C . An initial 2 μL injection was followed by 6 μL injections at 240 second intervals until no heat exchanges were observed . Mn2+ binding to MntC bound to the monoclonal antibodies was characterized in 50 mM Tris-HCl , 150 mM NaCl , pH 7 . 4 . 11–24 μM solutions of MntC were initially saturated with the Fab fragment of mAB 305-78-7 or intact antibodies 305-72-5 and 305-101-8 ( saturation was monitored by ITC ) and then titrated with 0 . 254 mM MnCl2 to saturation . Mn2+ and antibody binding data were fit to the “single class of binding sites” model using data analysis software provided by the ITC manufacturer to extract thermodynamic binding parameters . Peptides with sequences SVDKKAMESLSEETKKDIFGEVY ( corresponding to MntC residues 240–261 with a tyrosine residue added at the C-terminus for UV absorbance measurements ) and EINTEKQGTPEQMY ( corresponding to MntC residues 218–220 with a tyrosine residue added at the C-terminus for UV absorbance measurements ) were chemically synthesized via Thermo Scientific Custom Peptide Synthesis Service . Monoclonal antibodies 305-78-7 and 305-101-8 were dialyzed against 1x PBS , pH 7 . 4 and titrated with the corresponding peptides dissolved in the same buffer or full length MntC protein dialyzed against the same buffer at 25°C . When appropriate , data were fit to the binding model describing interaction with a single class of binding sites , as described above . Microtiter plate wells were coated overnight with 2 μg/mL of wild type MntC , MntC-pLH94 or BSA control ( 100 μL/well ) . Wells were subsequently blocked with 200 μL /well of 2% Nonfat Dry Milk in PBS , pH 7 . 4 , 0 . 05% Tween-20 ( blocking solution ) for 60 min at room temperature . Serial dilutions of mAB 305-78-7 ( 100 μL each ) were added to the wells and incubated at 37°C for 2 hours . Plates were then washed 3 times with the blocking solution ( 200 μL /well ) and incubated for 60 minutes at 37°C with alkaline phosphatase-conjugated goat anti-mouse IgG ( 1:3000 dilution , 100 μL /well ) . Immunocomplexes were detected via absorbance measurements at 405 nm using 1-Step pNPP ( “Pierce” , #37621 ) chromogenic substrate ( 100 μL /well ) . Dissociation constants were determined from fitting of the absorbance data to the equation A=Amax[L]Kd+[L] ( 2 ) where A is absorbance at ligand concentration [L] , Amax is absorbance at saturation and Kd is the dissociation constant . Binding affinity of mAB 305-78-7 to recombinant mutant MntC proteins was measured with a ForteBio Octet HTX instrument ( Pall Life Sciences , Menlo Park , CA ) . Experiments were conducted in 96-well black opaque plates ( Greiner Bio-One , Monroe , NC ) with 30°C incubation temperature and 1000 rpm agitation . To ensure proper immersion of the biosensors , each well contained a final volume of 200 μL . Anti-murine IgG Fv biosensors ( AMQ , Pall Life Sciences ) were saturated with mAB 305-78-7 and then incubated with two-fold serial dilutions of recombinant MntC proteins . Duplicate measurements were captured within each experiment by reusing the reagent samples with fresh biosensor tips . Kinetic measurements were repeated two times in independent experiments to determine average values . Data acquisition and analysis was performed with Octet software version 8 . 2 ( Pall Life Sciences ) . Buffer-subtracted kinetic data were globally fitted with a 2:1 Langmuir model to obtain a dissociation rate constant ( KD = koff/kon ) . Structural coordinates of MntC-Fab 305-78-7 complex have been submitted to the Protein Data Bank with the accession code 5HDQ .
Proteolytic digest mapping results ( a necessary prerequisite of DXMS experiments ) have been published [4] and will not be described here . Hydrogen exchange data are presented as deuterium accumulation plots . Number of deuterons exchanged onto the amide backbone within a given peptide is calculated as described in “Materials and Methods” and plotted as a function of incubation time in D2O . Each individual peptide is identified by the position of the first and last residue of that peptide within the amino acid sequence of the intact protein . Protein sequence aligned with the corresponding secondary structural elements is shown in Fig 2 . Examples of typical results of the on-exchange DXMS experiments used to map monoclonal antibody binding epitopes are presented as deuterium accumulation plots in Fig 3 and S1–S3 Figs . Antibody binding epitopes are identified through comparison of the deuterium accumulation plots for each peptide obtained with and without the antibody present . Conclusions on decreased deuterium accumulation in the presence of the antibodies ( or lack thereof ) were drawn based on the combination of multiple criteria: ( 1 ) significant difference in deuterium accumulation ( >10% of the maximum number of deuterons that can be exchanged onto a given peptide ) between the protein alone and the protein-antibody complex , ( 2 ) qualitative agreement between data from multiple time points for the same peptide , ( 3 ) quantitative agreement between data obtained for multiple charge states of the same peptide ( when available ) , and ( 4 ) consistency of the data obtained from multiple overlapping peptides covering the same part of the protein sequence . It should be noted that each peptide “reports” on the exchange that is happening starting with amino acid #3 of that peptide , since the exchange on the two N-terminal amino acids is instantaneous and is not informative [41] . For example , peptide 259–276 reports on residues 261–276 , since no information can be obtained for residues 259–260 . In some cases , it appears that a peptide may be exchanging more protons than physically possible . One has to keep in mind , that the fully deuterated sample used to determine Mw ( FD ) from Eq 1 was prepared at acidic pH , while individual time point samples were allowed to exchange at neutral pH . It is possible that conformation of the unfolded polypeptide chain at neutral pH is somewhat different than at acidic pH , with greater solvent accessibility of the backbone and , correspondingly , higher deuterium accumulation on the most flexible structural segments at neutral pH . This would produce apparent exchange levels greater than 100% . The issue can be disregarded , however , since the epitopes are identified from differences in deuterium exchange on the same structural segment with and without antibody present , rather than from the absolute levels of deuterium accumulation . Functional antibody mAB 305-78-7 belongs to the interference group 2 ( of the three interference groups identified in an earlier work [3] ) . A total of 128 common peptides could be identified between the digest maps of MntC alone versus MntC bound to the antibody ( presence of more than one charge state for some of the peptides brings the total number of deuterium accumulation plots used in the analysis to 177 ) . These peptides cover 100% of MntC sequence . Comparisons of the deuterium accumulation plots obtained in these experiments are shown in Fig 3 and S1 Fig . There is no difference in deuterium accumulation evident in any of the peptides up to ( and including ) the peptide 226–242 . Starting with peptide 226–247 , a small but persistent difference is observed in all peptides extending beyond amino acid D242 . This difference becomes noticeably greater as the C-termini of the peptides extend beyond amino acid L249 ( i . e . , starting with the peptide 239–258 , which is the first peptide to include amino acid S250 ) , and then essentially disappears once N-termini reach amino acid V261 and beyond ( peptides 259–275 and 259–276 are the first to include V261 ) . Based on these data , we can conclude that the functional monoclonal antibody mAB 305-78-7 binding epitope is located between K243 and E260 . Mapping these residues onto the three-dimensional structure of MntC ( Fig 4 ) shows that the epitope involves α-helix α8 , β-sheet β8 and a short loop connecting these two structural elements . Another functional monoclonal antibody that we mapped using DXMS , mAB 305-101-8 , belongs to the interference group 3 [3] . We identified a total of 132 peptides that are common between MntC and MntC bound to 305-101-8 ( 178 deuterium accumulation plots , which include more than one charge state for some of the peptides ) . Similar to the mAB 305-78-7 experiment , these peptides cover 100% of the protein sequence . Comparisons of the deuterium accumulation plots are shown in Fig 3 and S2 Fig . A small but consistent decrease in deuterium accumulation in the presence of the antibody is observed between amino acids 113–124 ( peptides that include these amino acids are 111–124 through 111–126 ) . A far greater decrease can be detected between residues N210 and M220 ( peptides 208–220 through 217–220 ) . Mapping these two fragments onto the MntC crystal structure ( Fig 4 ) shows that they can be in close proximity , given high flexibility of the long loop encoded by amino acids 113–124 , which connects β-sheet β4 and α-helix α4 . Residues within this loop are not even observed in one of the two MntC copies in the asymmetric unit of the X-ray structure 4K3V [4] or in the structure of MntC-Fab 305-78-7 complex described below . Residues 210–220 encode another loop that connects β6 and α7 , along with the first turn of the helix α7 . Based on our DXMS data and X-ray structure , we can conclude that mAB 305-101-8 binding epitope maps between residues N210-M220 , with an additional point of contact possibly provided by the tip of the loop connecting β4 and α4 ( Fig 4 ) . It should be noted that the epitope appears to overlap with the recently identified epitope of the monoclonal antibody fragment FabC1 , which was shown to prevent MntC interaction with the MntB membrane importer[34] . The third functional monoclonal antibody that we mapped , mAB 305-72-5 , belongs to the interference group 1 , as defined by Anderson and co-workers[3] . A total of 63 common peptides ( 84 deuterium accumulation plots ) were identified after proteolytic digestion of MntC alone and MntC in complex with the antibody . These peptides cover 93% of the sequence: no peptides representing the N-terminal 16 amino acids and a short fragment between amino acids 221–225 could be identified in the experiment with MntC bound to the antibody . However , the antibody binding epitope appears to be outside of either of these two regions . Comparisons of the deuterium accumulation plots used to map the mAB 305-72-5 epitope are shown in Fig 3 and S3 Fig . The first difference in deuterium accumulation in MntC vs . MntC bound to the antibody can be observed at peptides 28–51 and 37–51 . This apparent 1–2 deuteron difference is the same between 28–51 and 37–51 , suggesting that the epitope lies beyond amino acid 39 ( which is the first amino acid of the 37–51 peptide , where exchange can be detected by DXMS ) . The next series of peptides ( 52–66 and 53–66 ) show apparent difference of ~ 5 deuterons . Coupled with the peptide 37–51 results , a possible explanation is that the epitope covers the last few residues of peptide 37–51 and the first few residues of peptide 52–66 . The epitope structure , however , appears to be more complex: residues 69–81 show no difference in deuterium accumulation ( peptides 67–74 and 75–81 ) , however an apparent ~2 deuteron difference re-appears within the peptides extending beyond W81 to amino acid residue A100 . The difference is the same up to at least peptide 83–100 , suggesting that additional points of contact lie between amino acids 85–100 . Taking all of these results together , we can conclude that the mAB 305-72-5 binding epitope is conformational and that this deuterium exchange pattern can only be explained by the antibody binding at the continuous surface formed by residues that are located somewhere between H50-D66 and A85-A100 . Mapping these residues onto the X-ray structure of MntC ( Fig 4 ) illustrates that this surface is likely formed by α-helix 2 and the last turn of α-helix 3 . Crystallographic analysis of the MntC-Fab 305-78-7 complex was used to validate epitope mapping results obtained via DXMS . The complex was co-crystallized and the structure was solved to 1 . 8 Å resolution ( Fig 5A ) . MntC amino acid residues located within 4 Å of the heavy and light chains of the Fab fragment that are part of the binding interface ( but not necessarily forming hydrogen bonding or salt bridge interactions ) are listed in Table 1 . According to the X-ray data , mAB 305-78-7 binds to the C-terminal lobe of MntC . The interface is primarily formed by the α-helix α8 and β-sheet β8 . Fab residues potentially forming hydrogen bonds with MntC are highlighted in Table 1 and shown in Fig 5B . In addition , E247 of MntC may be forming a salt bridge with K58 on the heavy chain of the antibody . Amino acids involved in MntC-antibody contacts were identified from the crystal structure of the complex described above . A total of four MntC side chains form hydrogen bonding interactions with the antibody ( H234 , K254 , D256 and K272 ) , while E247 potentially forms a salt bridge with K58 on the heavy chain ( Table 1 ) . In an attempt to validate our epitope mapping results , while at the same time minimizing potential structural disruptions , we targeted only two residues involved in hydrogen bonding ( H234 and K254 ) and salt bridge-forming E247 for replacement . Alternative amino acids were chosen to minimize effects of substitutions on side chain geometry , while completely eliminating chemical functionality of the side chains . Mutated MntC variant MntC-pLH94 was designed to contain three amino acid substitutions: H234F , E247L and K254M . Folding state of MntC-pLH94 was confirmed via far- and near-UV CD spectroscopy . CD spectra of MntC-pLH94 are shown in S4 Fig , with CD spectra of the wild type MntC shown for comparison . According to these data , amino acid substitutions H234F , E247L and K254M had no detectable effect on secondary and tertiary structure of the protein: CD spectra of the wild type protein and MntC-pLH94 are essentially identical . To provide additional evidence for the lack of global structural change induced by the amino acid substitutions H234F , E247L and K254M , we conducted ITC experiments with MntC-pLH94 to monitor Mn2+ binding to the protein . A decrease or lack of Mn2+ binding as a result of these amino acid substitutions distal from the Mn2+ binding site would indicate that global protein structure has been significantly disrupted by the mutations . The results of the ITC experiments are shown in S5 Fig and binding parameters are listed in the S3 Table . Thermodynamic parameters of Mn2+ binding by MntC-pLH94 are essentially identical to those of the wild type protein , providing additional evidence that the H234F , E247L and K254M substitutions had no effect on the global structure of MntC . Binding of mAB 305-78-7 to MntC-pLH94 was tested using ITC and Enzyme-Linked Immunosorbent Assay ( ELISA ) , as described in Materials and Methods . ITC experiments showed that binding of the wild type MntC to mAB 305-78-7 was stoichiometric ( Fig 6A ) , indicating very high affinity of the interaction . The apparent Kd was 1 . 2 nM , and the binding enthalpy was -19 . 9 kcal/mol . No binding was observed in the case of MntC-pLH94 ( Fig 6B ) , indicating that amino acid substitutions H234F , E247L and K254M have indeed disrupted the mAB 305-78-7 binding epitope on MntC , as anticipated from the X-ray structure and DXMS data . Additional evidence for disruption of the MntC:mAB 305-78-7 interaction is provided by the ELISA results shown in Fig 7 . The dissociation constant of wild type MntC binding to the antibody is in excellent agreement with the ITC result . In contrast , MntC-pLH94 results are essentially identical to those obtained with an unrelated control protein ( BSA ) , once again confirming that the amino acid substitutions H234F , E247L and K254M within the mAB 305-78-7 epitope have indeed disrupted binding . To confirm that individual residue-residue interactions seen in the crystal structure indeed play roles in mAB 305-78-7 binding to MntC in solution and to characterize individual contributions of H234 , E247L and K254 to the complex formation , we have additionally cloned and expressed a series of MntC variants containing substitutions at those positions . No structural characterization was done for those variants , since no structural changes could be detected in the triple mutant described above , therefore it is reasonable to expect that single mutants would have no effect either . Binding of these mutants to the antibody was characterized using Bio-Layer Interferometry on an Octet HTX instrument , as described in “Materials and Methods” . The results are shown in Table 2 and Fig 8 , with Octet data for the triple mutant H234/E247L/K254M included as reference . As can be seen from the results , all of these amino acid substitutions affected binding of mAB 305-78-7 to MntC , albeit to a different degree . K254M substitution disrupted binding almost to the same degree as the three substitutions combined—no rate constants can be derived from the fits of experimental data . Binding of mAB 305-78-7 to the other two mutants , H234F and E247L , can still be detected , however it is clear from Fig 8 that both variants are characterized by significantly increased dissociation rate constants , as compared to the wild type , while the association rate constants remained relatively unaffected . This would translate to the reduced binding affinity , although this is not immediately obvious from Table 2 due to significant experimental variation . Taken together , these results suggest that X-ray crystallography has correctly identified amino acid residues involved in MntC-mAB 305-78-7 interaction . In an attempt to understand potential mechanisms of MntC-induced resistance to the S . aureus infection , we studied Mn2+ binding to the protein complexed with the antibodies . The results are shown in Fig 9 . Because Mn2+ binding to MntC is stoichiometric under experimental conditions used , we will not draw conclusions on the association constants derived from these experiments . It should be noted , however , that stoichiometries and binding enthalpies in the experiments with MntC bound to mAB 305-72-5 or mAB 305-101-8 are very comparable to those derived from the control experiment with free MntC , suggesting that these two antibodies do not affect Mn2+ binding by the protein . This is not the case with MntC bound to the Fab fragment of mAB 305-78-7 . Although the first Mn2+ injection does produce a noticeable heat exchange ( Fig 9 , red symbols ) , it is clear that mAB 305-78-7 interferes with manganese binding to the protein and no binding parameters can be derived . The ITC titration data suggest that protection mechanism afforded by the anti-MntC monoclonal antibodies can be , at least in part , explained by the interference with Mn2+ binding to this metal-binding component of the MntABC transporter and thus preventing Mn2+ transport into the bacterial cytoplasm .
In the current work , we mapped binding epitopes of the representative monoclonal antibodies from different interference groups reported earlier [3] . As expected for the protective antibodies [10 , 11] , all three epitopes were conformational . The DXMS data clearly show that the mAB 305-72-5 binding epitope ( interference group 1 ) involves two discontinuous segments . In the case of the other two antibodies one could argue ( based strictly on DXMS results ) that the epitopes could be linear: Our DXMS data did not provide sufficient resolution in those two cases . The X-ray structure of MntC in complex with mAB 305-78-7 ( interference group 2 ) , however , shows that there are several other isolated residues outside of the linear peptide 243–260 that are involved in the interaction , confirming that mAB 305-78-7 epitope is discontinuous , as well . To provide additional evidence for the conformational nature of the epitopes recognized by the antibodies mAB 305-78-7 and mAB 305-101-8 ( interference group 3 ) , we conducted ITC titrations of the antibodies under study with synthetic linear peptides derived from the amino acid sequences of the structural segments identified using DXMS . No binding could be detected in these experiments ( S6 Fig ) . These results confirm that the unique spatial arrangement of the residues dictated by the 3-dimensional folding of the identified peptide sequences is important for the antibody binding . Detailed comparison of the mAB 305-78-7 epitope mapped via DXMS and X-ray shows that both methods produce very similar results: the major binding surface is formed by the α-helix α8 , β-sheet β8 , and the loop connecting these two structural elements ( Fig 10 ) . Based on the available DXMS data , we concluded that the epitope is located between residues 243 and 260 . Analysis of the X-ray structure leads to essentially the same conclusion: residues 243 , 247 and 250–260 are all parts of the structural segment identified using DXMS . In addition , the X-ray structure shows that residues 228 , 234 , 237 and 272 may provide additional interactions that stabilize the complex . The DXMS data do show some differences in deuterium accumulation in the peptides that include those four residues , but we deemed those differences too small and inconsistent to say with confidence that these peptides originated from the part of the protein that is involved in the antibody binding . This observation illustrates the power of X-ray crystallography to provide residue-specific information with regards to the composition of the binding interface . However , DXMS data were obtained at a fraction of the cost and effort required for crystallographic analysis , yet still provided largely comparable results . The MntC variant pLH94 ( H234F , E247L/K254M ) was designed to further confirm mAB 305-78-7 epitope identification . We have chosen two residues that could potentially form intermolecular hydrogen bonds ( H234 , and K254 ) , along with a residue that appears to form an intermolecular salt bridge ( E247 ) . Our goal was to minimize the number of amino acid substitutions to minimize any potential disruption or alteration of MntC structure , hence only three out of five residues with side chains involved in intermolecular interactions were selected . Substitutions at these three positions were sufficient to completely disrupt binding , as evidenced by the ITC and ELISA results ( Figs 6 and 7 ) . To ensure that MntC-pLH94 was unable to bind mAB 305-78-7 due to the targeted replacements and not due to the disruption of the structure , we assessed secondary and tertiary structure of the mutant protein using CD spectroscopy . According to the CD data ( S4 Fig ) , amino acid substitutions H234F , E247L and K254M had no detectable effect on secondary and tertiary structure of the protein ( changes in spectral intensity observed between ~260–275 nm in the near-UV spectrum likely arise due to the introduction of an additional phenylalanine residue as a result of H234F substitution and do not necessarily reflect global structural changes ) , since CD spectra of the mutant are identical to the spectra of the wild type protein . In addition , MntC-pLH94 is capable of Mn2+ binding with the same thermodynamic parameters as the wild type protein ( S3 Table ) . Taken together the CD , ITC and ELISA results show that amino acid substitutions H234F , E247L and K254M had little to no effect on the global structure of the protein , while at the same time disrupted mAB 305-78-7 binding to the protein . Finally , results from the Bio-Layer Interferometry experiments demonstrated that each of those residues contributes to the interaction with the antibody , although to a different degree . Results from these experiments , therefore , confirm that mAB 305-78-7 binding epitope has been correctly identified . The results reported in this work shed light on the molecular mechanism of protection afforded by the anti-MntC antibodies . Another report from our laboratories [1] demonstrated that mutations in MntC gene make invasive S . aureus strains susceptible to the oxidative stress . Considering that manganese , which is the metal transported by MntC , is an essential co-factor of superoxide dismutases , we hypothesized that antibody binding could inhibit MntC-Mn2+ interaction or interfere with Mn2+ transport through the channel pore , making bacteria more susceptible to the attack by neutrophils . A recently published paper by Ahuja and co-workers [34] provided evidence that monoclonal antibody fragment FabC1 indeed interferes with Mn2+ transfer from MntC to the importer MntB . FabC1 and our monoclonal antibody mAB-101-8 have overlapping epitopes , thus , they both belong to the interference group 3 as defined by Anderson et al . [3]: residues 210–220 that show decreased deuterium accumulation in the presence of mAB-101-8 in our experiments include part of the α-helix 3 from the C-terminal lobe of MntC ( which corresponds to the α-helix 7 in our nomenclature ) shown to be involved in FabC1 binding [34] . Thus it is very likely that mAB 305-101-8 ( and any other antibodies belonging to the interference group 3 ) also sterically interferes with MntC-MntB interaction , preventing Mn2+ release into the channel pore . mAB-305-72-5 binding epitope lies on the same face of MntC molecule as that of mAB-101-8 , although on the N-terminal lobe of the structure . Binding of the antibody to this site therefore would also be expected to sterically interfere with MntC-MntB interaction , similar to mAB 305-101-8 or FabC1 interaction , once again preventing Mn2+ transfer into the channel pore . Our X-ray crystallography data published earlier [4] showed that two molecules of MntC are present in the asymmetric unit of the crystal , with one of the molecules completely missing electron density for residues 240–258 . DXMS and X-ray crystallography data reported here identified these residues as part of mAB 305-78-7 binding epitope . Disordering of these residues made Mn2+ binding site solvent accessible , while folding of these residues into an alpha-helix in another molecule of the asymmetric unit blocked solvent accessibility . It is tempting to speculate that binding of mAB 305-78-7 to residues 240–258 would stabilize the alpha-helix and , correspondingly , prevent binding of Mn2+ to the protein . This is indeed what seems to be happening . ITC titration of MntC bound to the Fab fragment of 305-78-7 ( Fig 9 ) showed that the antibody strongly interferes with ( if not completely abolishes ) Mn2+ binding to the protein—initial heat exchange could arise from Mn2+ binding to a small fraction of the free protein in equilibrium with MntC-Fab complex . Taken together , experimental data reported here , along with results from Anderson et al . [3] , Handke et al . [1] and Ahuja et al . [34] provide a plausible description of immunogenic properties of MntC and explain potential mechanism of protection afforded by the MntC-induced antibodies . Interference mapping [3] established that there are three non-interfering groups of the monoclonal mABs . DXMS and X-ray crystallography mapping of the epitopes recognized by selected representatives of each groups allowed us and others [34] to hypothesize that there are at least two potential mechanisms that can explain protection afforded by these antibodies . mAB’s belonging to the interference group 2 ( e . g . , mAB 305-78-7 ) block Mn2+ binding to MntC , making it impossible for S . aureus to acquire this critical metal . Antibodies belonging to the interference groups 1 ( e . g . , mAB 305-72-5 ) and 3 ( e . g . , mAB 305-101-8 and FabC1 ) prevent transport of the Mn2+ ions that were already acquired across the bacterial membrane . The net result of the impaired manganese transport would be reduced activity of superoxide dismutase and increased susceptibility of the pathogen to oxidative stress that the organism will encounter after opsonophagocytosis by the neutrophils . The protective antibodies that belong to these interference groups will effectively starve the bacterium of Mn2+ that it needs for survival . In conclusion , we would like to add that the results reported in this work provide deeper understanding of the MntC antigen mechanism of action within SA4Ag . Investigational clinical studies demonstrated that antibodies that compete with these functional monoclonal antibodies are not detected in humans without documented S . aureus infection , however they are rapidly generated as a result upon infection indicating that the antigen is expressed and exposed early in infection [47] . Identification of the protective epitopes reported in this study is therefore useful for the characterization of potential protective antibody responses induced by vaccines that are in clinical development .
|
Staphylococcus aureus protein MntC is a metal-binding protein of the ABC-type transporter involved in the acquisition of an essential nutrient , Mn2+ , by the pathogen . An earlier study demonstrated that use of MntC as an antigen in experimental vaccine can provide protection against staphylococcal infections in animals and identified three groups of protective monoclonal antibodies induced by the protein . In the current work we employed Deuterium-Hydrogen Exchange Mass Spectrometry ( DXMS ) to determine binding sites of selected representatives from each of those three groups . DXMS results were further validated using X-ray crystallography , site-directed mutagenesis and functional studies . Locations of the binding sites and results of the functional studies were used to draw conclusion on molecular mechanisms of protection afforded by MntC: antibodies belonging to two of the groups are predicted to interfere with Mn2+ transfer from the protein to the transmembrane channel pore , while the third group of the antibodies is expected to interfere with Mn2+ binding to MntC itself . The net result in both cases is impaired Mn2+ transport across the bacterial membrane and increased susceptibility of the bacterium to the oxidative stress , likely due to the reduced activity of superoxide dismutase which requires Mn2+ as an essential co-factor for activity .
|
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"Abstract",
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2016
|
High Resolution Mapping of Bactericidal Monoclonal Antibody Binding Epitopes on Staphylococcus aureus Antigen MntC
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Numerous signaling proteins use multivalent binding to increase the specificity and affinity of their interactions within the cell . Enhancement arises because the effective binding constant for multivalent binding is larger than the binding constants for each individual interaction . We seek to gain both qualitative and quantitative understanding of the multivalent interactions of an adaptor protein , growth factor receptor bound protein-2 ( Grb2 ) , containing two SH3 domains interacting with the nucleotide exchange factor son-of-sevenless 1 ( Sos1 ) containing multiple polyproline motifs separated by flexible unstructured regions . Grb2 mediates the recruitment of Sos1 from the cytosol to the plasma membrane where it activates Ras by inducing the exchange of GDP for GTP . First , using a combination of evolutionary information and binding energy calculations , we predict an additional polyproline motif in Sos1 that binds to the SH3 domains of Grb2 . This gives rise to a total of five polyproline motifs in Sos1 that are capable of binding to the two SH3 domains of Grb2 . Then , using a hybrid method combining molecular dynamics simulations and polymer models , we estimate the enhancement in local concentration of a polyproline motif on Sos1 near an unbound SH3 domain of Grb2 when its other SH3 domain is bound to a different polyproline motif on Sos1 . We show that the local concentration of the Sos1 motifs that a Grb2 SH3 domain experiences is approximately 1000 times greater than the cellular concentration of Sos1 . Finally , we calculate the intramolecular equilibrium constants for the crosslinking of Grb2 on Sos1 and use thermodynamic modeling to calculate the stoichiometry . With these equilibrium constants , we are able to predict the distribution of complexes that form at physiological concentrations . We believe this is the first systematic analysis that combines sequence , structure , and thermodynamic analyses to determine the stoichiometry of the complexes that are dominant in the cellular environment .
Grb2 contains one SH2 domain flanked on each side by an SH3 domain [1] , [2] , each of which forms complexes with multiple polyproline motifs on Sos1 . The activation of the Ras signaling pathway requires the recruitment of Sos1 from the cytosol to the plasma membrane where it activates Ras by inducing the exchange of GDP for GTP [3] , [4] . This recruitment is mediated by Grb2 , which couples Sos1 to phosphorylated receptors and scaffolding proteins that contain sequences of the binding motif for the Grb2 SH2 domain , YXNX . In T cells and mast cells , when the three terminal tyrosines of the scaffolding protein linker for activation of T cells ( LAT ) are phosphorylated , they become binding sites for the SH2 domain of Grb2 . Upon aggregation of T cell receptors on T cells and on mast cells , LAT is phosphorylated and aggregates [5]–[7] . When the concentration of Grb2 is sufficiently high compared to Sos1 , Grb2-Sos1-Grb2 complexes form and cross-link LAT molecules , unless the concentration of Grb2 is so high that unbound Grb2 fills the binding sites on LAT and blocks cross-linking [6] , [8] . Highly specific biomolecular signaling complexes such as the Grb2-Sos1 system often form by combining relatively weak promiscuous interactions . This strategy is widespread with signaling proteins exhibiting a variety of combinations of domains ( PH , PTB , SH2 , SH3 , etc . ) that allow them to attach to one or more proteins at multiple sites [9] . Grb2-Sos1 complex formation presents an excellent system for studying the role of multivalency in enhancing the binding affinity . There are four known proline-rich motifs on Sos1 that can bind to the SH3 domains of Grb2 [10] , [11] . The effective for the formation of a Sos1-Grb2 complex has been measured and is [6] , a hundred times smaller than the smallest for the binding of a single Grb2 SH3 domain to a proline-rich domain on Sos1 . To achieve such an enhancement in its effective equilibrium binding constant , Grb2 must attach to Sos1 through both its SH3 domains . When one SH3 domain is bound to Sos1 , the second SH3 domain of Grb2 samples a much higher local concentration of the second binding site than if it were free in solution . The two SH3 domains of Grb2 bind to two of the four proline-rich regions on Sos1 to form a 1∶1 Grb2-Sos1 binary complex . A second Grb2 can bind through both its SH3 domains to this complex to form a Grb2-Sos1-Grb2 ternary complex . At high concentrations of Grb2 , the 2∶1 complex is dominant [6] . However , peptide binding studies have shown that only one of the motifs in Sos1 binds strongly to the C-terminus SH3 domain ( C-SH3 ) of Grb2 . All the Sos1 motifs bind with moderate strength ( ) to the N-terminus SH3 ( N-SH3 ) domain [12] , [13] , raising the question of how the 2∶1 complex forms at physiological conditions . We present a theoretical study involving the synergistic combination of sequence , structure , molecular dynamics ( MD ) simulations , and polymer models to determine the stoichiometry of the complexes that dominate the cellular environment . First , a combination of evolutionary analysis of the sequences , and binding energy calculations is used to predict the presence of a new binding motif in Sos1 . Secondly , a simple polymer model is used in combination with MD simulations to calculate the enhancement in binding constants due to local concentration . The flexibility of both the modular protein and the disordered region containing binding motifs are taken into account while computing the local concentration effects . We conclude with an evaluation of the stoichiometry of Grb2-Sos1 complexes under physiological conditions and discuss its implications for cell signaling . The approach developed here has applicability beyond the current implementation and provides a framework for handling the multivalency of protein-protein interactions where disordered regions play a significant role .
The lack of well-defined structure in the disordered region of the Sos1 protein can , in principle , allow polyproline motifs to bind to SH3 domains of Grb2 in two different orientations [14] , [15] . Evolutionary analysis is performed below to identify the presence of any additional polyproline motifs in Sos1 that may bind to Grb2 . Previous sequence-based work on Sos1 has concentrated on the four polyproline motifs that bind in the class II ( ) orientation [6] , [13] . The C-terminal SH3 domain ( C-SH3 ) of Grb2 binds to class I and class II motifs [12] , [16] while the N-terminal SH3 domain ( N-SH3 ) of Grb2 is only known to bind with class II motifs . The Sos genes can be divided into three subfamilies - Sos1 and Sos2 , found in mammals and higher eukaryotes , and Sos found in flies and mosquitos . Shown in Figure 1 , are the four class II motifs on Sos1 ( P1 to P4 ) , five class II motifs on Sos2 ( M1 to M5 ) , and three class II motifs on Sos ( S1 to S3 ) that Grb2 binds to [17] , [18] . These motifs are highly conserved within their respective groups . The first two motifs in Sos1 , Sos2 , and Sos align in the sequence alignment of the Sos family . In addition , the length of the linker connecting these two motifs is highly conserved in all the Sos proteins ( 18–20 amino acids ) . The linker length between the second and third motifs is conserved within their respective groups but is highly variable between the different subfamilies even though P3 and M3 align with each other in the sequence alignment . Finally , the P4 motif in Sos1 aligns well with the M5 motif in Sos2 . An examination of the intrinsically disordered region in the Sos1 sequence reveals a highly conserved class I polyproline motif ( ) that had not been previously identified . This new motif is marked as RP ( residues R1271 - P1277 in Homo sapiens ) in Figure 1 . This region in the Sos1 sequence aligns with the M4 motif present in Sos2 such that the linker length between these two binding motifs is preserved , even though RP is a class I and M4 a class II motif . Based on its conservation within the Sos1 proteins and the linker length conservation across Sos2 and Sos1 , we propose that the RP motif on Sos1 is a fifth Grb2 binding motif . To test whether RP can bind to Grb2 , we first established and tested a protocol using AutoDock [19] to calculate the binding energies ( ) of the experimentally known Sos1 motifs P1 through P4 , that bind to the SH3 domains of Grb2 . For each peptide , we computationally predict the binding affinities and the sites on the SH3 domains where docking occurs . The binding calculations examine the binding of a full-length SH3 domain with a Sos1 peptide ligand of 9 or 10 amino acids . These ligands have more than 30 torsional degrees of freedom , while AutoDock is most reliable when the ligand has less than 10 degrees of freedom [20] . However , because the binding of the Sos1 peptides to the SH3 domains of Grb2 is enthalpically driven [6] , we have neglected the conformational flexibility in the backbones of the Sos1 peptides , which substantially reduces the ligand's degrees of freedom . Blind predictions of the binding sites and of motifs P1 to P4 in Sos1 with the N-SH3 domain of Grb2 display reasonable agreement with experimentally determined binding sites and energies [13] ( Table 1 and Figure 2A ) . The calculations predict , as has been observed [13] , that all four Sos1 peptides are capable of binding to N-SH3 in the class II orientation at the polyproline motif binding site . In Figure 2A , the theoretical prediction for the binding site of P1 on N-SH3 is compared with the experimentally determined binding site . The predicted conformation with the lowest binding energy displayed a RMSD of 2 . 04 Å for all non-hydrogen atoms with respect to the NMR structure ( PDB ID 1AZE [21] ) . Unlike for the Grb2 N-SH3 domain , the only high-resolution structure available for a peptide bound to the Grb2 C-SH3 domain is for a class I motif . Conformational changes are expected when a SH3 domain binds to a class I versus a class II motif [15] . As P1 to P4 are class II motifs , the protocol for blind binding predictions of the C-SH3 domain binding to P1 through P4 motifs required an additional step for generating the backbone conformations for the ligands and the conformation of the C-SH3 domain . A molecular dynamics ( MD ) simulation of the C-SH3 domain bound to a strong binding peptide P1 was used to generate conformations for the backbone of the peptides and the C-SH3 domain . These conformations were then used during the blind binding predictions of the class II motifs in Sos1 to C-SH3 . MD simulations have previously been used to produce good candidate conformations for binding energy predictions as , for example , in predicting novel inhibitors for RNA-editing ligases [22] . As seen in Figure 2B , the predicted binding sites for P1 on C-SH3 and N-SH3 are similar . The larger variation in the binding site conformation in Figure 2B compared to that in Figure 2A arises , in part , because the conformations for the backbone of the peptide and the C-SH3 domain used in the binding energy calculations vary from those of the experimental structure for the N-SH3 domain bound to P1 . Note that compared to the peptide motifs used in the docking calculation for binding of the peptides to the Grb2 N-SH3 domain , an additional amino acid at the N-terminus of these peptides was needed for accurate binding predictions to the C-SH3 domain . This extra amino acid was particularly critical for predicting the correct C-SH3 domain binding site for P3 . The predicted for P1 through P4 motifs on C-SH3 agree reasonably well with the measured quantities as shown in Table 2 . Also consistent with experiment , the predicted for the binding of the P1 motif to C-SH3 is greater than the for the domain binding to P2 , P3 , and P4 motifs . It is worth mentioning that we did consider the binding of P1–P4 peptides with flexible backbones to the SH3 domains . However , these calculations led to convergence issues with AutoDock due to the relatively large number of degrees of freedom of these flexible peptide fragments . The program was not able to discriminate between the experimentally known binding site and another binding site on the opposite side of the SH3 domain . Still , the free energy for binding to the experimentally determined site was comparable to the binding free energy obtained in Tables 1 and 2 ( with a difference of approx . 0 . 5 kcal/mol ) . To take the backbone flexibility into account we used an alternate approach . We performed the AutoDock calculations with ten different conformations from MD simulations for each of the peptides binding to the N-SH3 and C-SH3 domains of Grb2 ( Table S1 ) . Each conformation of the peptide bound SH3 domain exhibited some variability in the backbone conformation both in the peptide and the SH3 domain . Even though the means of the calculated binding energies were similar to what we originally reported , the variance of the energies did capture the influence of backbone flexibility . The variation in the calculated binding energies is larger for P1 binding to the C-SH3 domain than for any peptide-SH3 domain binding combination we tested . We expect this binding interface to be more fluxional due to the electrostatic nature of the three terminal arginines and its interactions with glutamic acids in the C-SH3 domain . Furthermore , to ensure that this approach is sensitive to the binding specificity of the SH3 domains , we mutated the three arginines at the C-terminus of the P1 motif to alanines . This mutated peptide is expected to present a low binding affinity for the motif because of the absence of the terminal arginine in the class II motif ( i . e . , a true negative versus a false positive test ) [16] . The theoretically predicted binding energy for the mutated motif to both N-SH3 and C-SH3 domains ( −4 . 8 and −4 . 7 kcal/mol respectively ) was found to be lower than the binding energies of the four wildtype motifs on Sos1 ( Tables 1 and 2 ) . Interestingly , for the P1 mutated sequence , there was a change in the predicted position of the binding site . The mutated form is predicted to bind on the opposite face of the SH3 -barrel than the motifs P1 to P4 . Thus , this protocol is sensitive to the specificity of the SH3 domains and can be used to validate whether the RP motif will bind to the SH3 domains . The same protocol for estimating was then used to test whether RP can bind to the N-SH3 and C-SH3 domains of Grb2 . This protocol predicts that the newly identified class I motif RP is capable of binding to the N-SH3 and C-SH3 domains of Grb2 with similar affinities as P3 . As shown in Figure 2C , the binding site and orientation predicted for RP are similar to the experimentally determined conformation of a class I motif bound to C-SH3 ( PDB ID 1IO6 [16] ) . All-atom MD simulations of N-SH3 bound to the RP motif were carried out to evaluate whether the N-SH3 forms a stable complex with RP . Consistent with the binding energy calculations , the peptide remains bound to N-SH3 after 300 ns of MD simulation , and all the critical interactions between the peptide and SH3 remain intact through this period . The main purpose of the extensive binding energy calculations provided above is to show that the newly identified RP motif in Sos1 binds to the SH3 domains of the Grb2 with similar affinities as some of the other poly-proline motifs from Sos1 . AutoDock , which was used to compute affinities , is less reliable at predicting the values of equilibrium constants than at predicting binding sites [23] . As can be seen from Tables 1 and 2 , binding calculations predict consistently higher affinities compared to the experimentally determined values . However , the trends between experimentally and computationally determined binding affinities are similar . Based on these trends , we expect the affinity of RP to be of the same order of magnitude as that of P3 . In the ensuing calculations of the intramolecular equilibrium constants , we will use the measured affinities for single site equilibrium constants and take the affinities of RP to be the same as P3 . Given that the class I ligand RP can bind to the SH3 domains of Grb2 , we examined the N-SH3 and C-SH3 domains for the presence of any structural signatures that might indicate why they are able to bind to both class I and class II ligands . According to previous studies [15] , the orientation of a conserved tryptophan switch ( W37 and W193 in Grb2 ) in the SH3 binding pocket determines specificity based on whether a SH3 domain is capable of forming a specific hydrogen bond with the backbone of class I or II motifs . On locally aligning all class I and class II-binding SH3 domains [15] , we find significant differences in orientation of the W switch between the two classes ( Figure 3A and B ) . An SH3 domain that binds to both class I and class II motifs has the inherent flexibility to exist in both class I and class II binding orientations in the absence of a ligand [15] . In order to estimate whether the W switches in Grb2 has the inherent flexibility to bind to both class I and class II ligands , all-atom MD simulations of Grb2 were carried out in explicit water in the presence ( Figure 3 ) and absence ( Figure 3 ) of a bound peptide . We compared the conformation of the conserved switches ( W37 and W193 in N-SH3 and C-SH3 respectively ) in Grb2 during the simulations with the conformation of the W switch in a class II ( PDB ID 1ABO [24] ) and a class I ( PDB ID 1CKA [25] ) peptide binding orientation . Here , each frame from the trajectory was overlapped with the class I and II binding SH3 domains based on a local alignment involving the backbone atoms of residues n−2 to n+2 where n refers to the W residue . The W switch is highly flexible and is capable of forming hydrogen bond interactions with class I and class II polyproline motifs as shown in Figure 3C . Despite the highly fluxional character in the conformations of W193 in the C-SH3 domain bound to P2 , the hydrogen bond between the side chain of W193 and the backbone of the peptide is maintained in most of the frames of the simulation . Hence , we find that orientations of the W switch of N- SH3 and C-SH3 are fluxional enough to bind both class I and II polyproline motifs in Sos1 . We have separately characterized the binding of each motif in Sos1 to the SH3 domains of Grb2 . As Grb2-Sos1 forms a multivalent complex , these interactions are influenced by local concentration effects after one motif in Sos1 binds to Grb2 . We wish to calculate the effective local concentration ( ) of Sos1 motifs that a free SH3 domain on Grb2 experiences when its other SH3 domain is bound to a motif on Sos1 . The concentration of Sos1 is assumed to be sufficiently low so that cross-linking of two Sos1 by a single Grb2 can be neglected . The binding of two motifs on Sos1 to the two SH3 domains of Grb2 follows the scheme shown in Figure 4 . There are two steps in the multivalent binding of Grb2 to Sos1 - the first is intermolecular while the second is intramolecular . We define and as the equilibrium binding constants for the binding of motifs and to the N-SH3 and C-SH3 domains of Grb2 respectively . ( 1 ) where , , and are the concentrations of unbound Grb2 , unbound Sos1 , and Grb2 bound to the motif of Sos1 with its N-SH3 domain . is similarly defined . In the case where and are motifs in the same Sos1 molecule tethered by a disordered protein segment , ( 2 ) where is the effective concentration of motif that the C-SH3 experiences when the N-SH3 of Grb2 is tethered to on Sos1 and is the concentration of doubly bound Grb2 . is defined as the effective equilibrium constant for the simultaneous binding of motifs and on a single Sos1 molecule to Grb2 and is given by: ( 3 ) Note that the effective binding constant of motifs and in Sos1 to the corresponding domains in Grb2 is independent of the order of binding of both motifs as required by detailed balance . While the intermolecular binding constant and are known experimentally [13] , the intramolecular equilibrium constants , and , have not been measured and it is difficult to measure these parameters directly . For a Grb2 with its N-SH3 domain bound , is proportional to the probability of finding the C-SH3 of Grb2 and the motif on Sos1 together in the same region of space . As shown in Figure 5 for binding of P1 and P2 to N- and C-SH3 domains of Grb2 respectively , we define to be the probability of finding on the tethered Sos1 at the position in the volume and to be the probability of finding the C-SH3 domain on the tethered Grb2 at the position in the volume . Assuming that the linker region does not interact with the SH3 domains in Grb2 , is given by the expression [26] , [27]: ( 4 ) A hybrid approach combining a polymer model and MD simulations is used to obtain expressions for the probability densities in Equation 4 . Ignoring any interactions between the linker and Grb2 , is obtained by treating the span of Sos1 from to as a polymer described by the worm-like chain ( WLC ) model [28] , [29] . When the length of the polymer is much longer than its persistence length ( ) , this model predicts that: ( 5 ) where Å for unfolded peptides [30]–[32] and is the contour length of the peptide ( where is the number of amino acids in the linker connecting motifs and ) . The probability density is shown in Figure 5C . Experimental studies indicate that the persistence length for native unstructured proteins is a weakly increasing function of the length of the protein [32] and for a 203 amino acid disordered region . To obtain the probability density for the vector distance between the SH3 domain binding sites in Grb2 , Zhou [26] used a composite WLC model representing two flexible linkers separated by a rigid rod to model the effect of the SH2 domain in Grb2 , but recognized that detailed effects such as excluded-volume and steric interactions were ignored in this approach and that MD or Monte Carlo simulations to obtain might be warranted . To estimate , we used a 400 ns MD simulation of Grb2 bound to P1 and P2 in the absence of a linker ( see Figure 5B for an example ) . This probability density will depend on what type of polyproline ligand ( class I or II ) each motif is , and on the order of the motifs and in the sequence of Sos1 ( see Figure 6 ) . An intrinsic problem with obtaining the probability distribution using MD simulations is that it may not reflect the true distribution because of limited conformational sampling . To test for convergence , we split the 400 ns MD simulation into two halves of 200 ns each . We calculated and based on both halves of the MD simulation separately . As the values of and are nearly the same between both halves of the MD simulation . Even though the MD simulations show that the probabilistic density of the distance between the binding sites ( ) tends to converge on the time scale of 200 ns , any global conformational changes on time scales longer than sub-microseconds will influence this distribution . The effect of these global conformational changes in can be incorporated by using coarse grained MD simulations such as the method proposed in [33] . In Table 3 , we list the calculated effective concentrations for all motifs on Sos1 that a SH3 domain on Grb2 experiences when its second SH3 domain is bound on the same Sos1 . Almost all the are in the mM range as was also obtained in [26] for the binding of Grb2 to a small bivalent ligand . In comparison , the cytoplasmic concentration of Sos1 in Jurkat cells is [8] . In Table S2 , we show that the is estimated to be in the mM range when the probability density of the distance between the binding sites ( ) is approximated using a set of delta functions . From the in Table 3 , and the experimentally measured equilibrium constants for the binding of peptides P1 to P4 on Sos1 to the N-SH3 and C-SH3 of Grb2 in Tables 1 and 2 [13] , one can quantify the enhancements in binding affinities that result from Grb2 having two SH3 domains that bind to multiple sites on the same Sos1 . Listed in Table 3 are the effective dissociation constants calculated from Eq ( 3 ) for the formation of doubly bound Grb2 . The single site affinities for the binding of SH3 domains to the RP motif have not been measured . To calculate an effective dissociation constant , we take the binding affinities of RP to the SH3 domains to be the same as those between P3 and the SH3 domains . Note that P3 is the poorest binder to Grb2 of the four motifs [13] . McDonald et al . showed that C-SH3 binds strongly to P1 , with a dissociation constant , but binds poorly , if at all , to P2 , P3 and P4 ( ) [13] . As a result , in Table 3 the strongest binding is predicted to occur for doubly bound Grb2 with its C-SH3 domain bound to P1 , with these effective binding constants being greater than the binding constants for singly bound Grb2 to any of the peptides . Thus , when the Grb2 concentration is much lower than the Sos1 concentration , we expect Grb2 to be doubly bound to Sos1 with its C-SH3 domain bound to the P1 domain . The binding constants for Grb2-Sos1 complex formation have been measured [6] . The 1∶1 Grb2-Sos1 complex is expected to consist of multiple species due to the presence of multivalent interactions between Grb2 and Sos1 . A Grb2 in a 1∶1 Grb2-Sos1 complex is bound either through one or both of its SH3 domains ( Figure 7A ) . From Eqs . ( 1 ) and ( 3 ) : ( 6 ) where ( 7 ) is the effective equilibrium constant for the formation of a Grb2-Sos1 complex . Because five binding sites on Sos1 can interact with the two Grb2 SH3 domains , there are 30 different possible 1∶1 Grb2-Sos1 complexes . A 2∶1 Grb2-Sos1-Grb2 complex can be composed of a Sos1 molecule bound to two singly bound Grb2 , to a singly and a doubly bound Grb2 , or to two doubly bound Grb2 ( Figure 7B ) . The overall concentration of the 2∶1 Grb2-Sos1-Grb2 ( [GSG] ) complex is: ( 8 ) The factor of two appears in the denominator because the Grb2 molecules are indistinguishable . In other words , the order of the different Grb2 molecules binding to the peptides does not matter as long as the same complex is formed . This equation can be rewritten as: ( 9 ) or in other words: ( 10 ) where is the effective equilibrium constant for the binding of a Grb2 from solution to a Grb2-Sos1 complex to form a Grb2-Sos1-Grb2 complex: ( 11 ) To make predictions about the binding of Grb2 to the complete polyproline rich domain of Sos1 ( 1117–1319 ) we must estimate the values of the unknown equilibrium constants for the binding of the N- and C-SH3 domains of Grb2 to RP on Sos1 . As in calculating the effective concentrations in Table 3 , we took these equilibrium constants to be the same as for binding to the P3 peptide . We predict that and . Chook et al . [34] found that the full Sos1 molecule , immobilized on a Biacore chip , bound Grb2 with a stoichiometry of 1∶1 and a dissociation constant of , about a factor of three lower than our calculated value of . The prediction of the computed effective equilibrium constant within a factor of four of the measured value is encouraging considering the approximations and the complexity of the system . In addition to the approximations associated with ( Eq . 4 ) as discussed above , the difference in single site affinity between a motif embedded in Sos1 and one that binds in isolation may have contributed to the observed discrepancy . The single site affinities used in our calculation are based on measurements of 12 amino acid length peptides ( lacking flanking sequences ) to the SH3 domains of Grb2 . However , one can expect changes in affinities due to flanking sequences [35] , [36] . The flanking regions may affect the binding affinity of each motif by a different factor . In such a scenario , the bivalent binding constants , which involve two motifs , will be modified by the product of the corresponding two factors ( Eq . 3 ) . However , we make the simplifying assumption that the flanking regions do not modify the binding affinity of the motifs to the SH3 domains in the full length Grb2 and Sos1 . Furthermore , we have neglected any allosteric communication between the two binding sites in Grb2 that could either increase or decrease the affinity for bivalent binding to Sos1 but have no effect on the monovalent binding affinities . Importantly , these effective equilibrium constants can be used to calculate , for example , the fraction of 1∶1 complexes that are composed of a singly or doubly bound Grb2 . The fraction with Grb2 singly bound is just the ratio of the first term in Equation 7 divided by . We predict that 10% of the Grb2-Sos1 complexes have Grb2 bound through a single SH3 domain while the remaining 90% have Grb2 bound through both its SH3 domains . Similarly , we predict that 68% of the Grb2-Sos1-Grb2 complexes have both Grb2 doubly bound to Sos1 , 27% have one Grb2 doubly bound and one singly bound , and 5% have both Grb2 singly bound . As the equilibrium binding constants for the binding of the N- and C-SH3 domains of Grb2 to RP have not been measured , it is difficult to judge the accuracy of the model from predictions that require knowledge of these equilibrium binding constants . Houtman et al . [6] , [37] have determined the equilibrium constant for the binding of Grb2 to a 96 amino acid N-terminal fragment of Sos1 ( Sos1NT ) that contained only the polyproline-rich motifs , P1 , P2 and P3 . Using isothermal titration calorimetry ( ITC ) they found the stoichiometry of the binding of Grb2 to Sos1NT to be 1∶1 with a . Our model calculations predict a for a 96 amino acid unstructured protein with [32] . However , since Sos1NT has three Grb2 binding sites the possibility arises that at sufficiently high ratios of Grb2 to Sos1NT , binding stoichiometries of 2∶1 ( ) and possibly 3∶1 may occur . In order to fit all the products to a 1∶1 complex , we predict the to be: ( 12 ) In Figure 5 of reference [37] , the interaction of Grb2 with Sos1NT was studied by titrating Grb2 to a maximum concentration of against Sos1NT , reaching a molar ratio of Grb2∶Sos1NT of 2–2 . 25 . For these experiments , where the free concentration of Grb2 is always less than , we predict that the effective stoichiometry of the Grb2-Sos1 complexes is . When the contribution of 2∶1 binding is taken into account , we calculate the effective , a factor of four higher than the measured value [6] , [37] . Using ITC Houtman et al . [6] also determined the equilibrium constant for binding of Grb2 to a C-terminal fragment of Sos1 ( Sos1CT ) that contained P4 and RP . They found the stoichiometry to be 1∶1 with . Our model calculations predict a much higher value , a . For this calculation we took the values of the unknown binding affinities of RP for the N- and C-terminal SH3 domains of Grb2 to be the same as the measured values of P3 , the proline-rich motif that is the weakest binder of Grb2 . The discrepancy between the measured and calculated values for Grb2 binding to Sos1CT suggests that we have underestimated the RP affinities , although other approximations that we have indicated are likely to also contribute to the discrepancy . When T cells are activated the transmembrane scaffolding protein LAT is rapidly phosphorylated [38] , followed by the formation of large aggregates of LAT [5] , [6] . The aggregation is mediated by Grb2 [6] . Fully phosphorylated LAT has three binding sites for the SH2 domain of Grb2 [39] . LAT aggregation is a result of Grb2-Sos1-Grb2 complexes bridging two LAT molecules; each Grb2 in the complex bound to a separate LAT molecule through its SH2 domain . If aggregates containing large numbers of LAT are to form , the cytosolic concentrations of Sos1 and Grb2 must favor formation of 2∶1 complex . In Jurkat E6 . 1 cells , the concentration of Grb2 is , which is 10 times higher than the concentration of Sos1 in these cells [8] . Assuming only 1∶1 and 2∶1 Grb2-Sos1 complexes form , the fraction of complexes containing two Grb2 , , equals 0 . 83 for the measured value for ( see Figure 8 ) . This is based on the experimental dissociation constant , , for the formation of the Grb2-Sos1-Grb2 complex from the Grb-Sos1 complex . Existence of such a large number of the complexes containing two Grb2 molecules are predicted to lead to the formation of large aggregates of LAT [7] . For our calculated value of , we predict that 0 . 27 of the complexes would contain two Grb2 . This seems low , suggesting that our value for is an underestimated , or that the measured concentration of Grb2 in Jurkat T cells is too low .
Many signaling proteins use multivalency , combining relatively weak promiscuous interactions to increase the strength and specificity of complex formation [40] , [41] . Intramolecular equilibrium constants associated with multivalency are difficult to measure and mostly remain undetermined . Typically , polymer models are utilized to fill the gap , when the biomolecular equilibrium constant for the individual sites are known [26] , [27] , [42] , [43] . At the heart of the method is the calculation of the effective concentration of a binding motif on one protein , that the binding site on the second protein experiences , when the two proteins are tethered . A simple polymer model , the WLC , has been used to characterize the flexibility of the portions of the proteins that participate in forming the intramolecular bond [26] , [27] , [42] , [43] . Barua et al . [44] analyzed a variety of in vitro studies of the binding of the tandem SH2 domains on the phosphoinositide 3-kinase ( PI-3 ) p85 regulatory domain to its bisphosphorylated binding site in the cytoplasmic domain of the platelet-derived growth factor –receptor ( ) . They concluded that the effective concentration for formation of the intramolecular bond was three orders of magnitude lower than predicted by the WLC model and that factors other than peptide dynamics , such as the conformational dynamics of the tandem SH2 domains , impose structural constraints on the interaction . Thus , using the WLC model to predict the spatial distribution of binding sites restricts the application of polymer based methods to unstructured proteins or regions of proteins that are disordered . We have chosen a hybrid MD-polymer approach to study the complex formation of a highly structured adaptor protein containing two SH3 domains , Grb2 , with a disordered region of the protein Sos1 that contains at least four , and possibly five , binding sites for the SH3 domains of Grb2 . Our hybrid MD-polymer methodology calculates by taking into account the flexibilities of the structured domains of Grb2 with MD simulations and the unstructured Sos1 with a simple polymer model . We expect that the WLC model provides a reasonable description of the spatial statistics of the linker connecting any two motifs in the disordered segment of Sos1 . The MD simulation of Grb2 in explicit water provides an accurate description of the probability density for the distance between the two SH3 binding sites when one site is bound . We show that the local concentration of the Sos1 motifs that a Grb2 SH3 domain experiences is approximately 1000 times greater than the cellular concentration of Sos1 . Unlike in the studies of Barua et al . [44] , binding studies on Grb2 and Sos1 suggests that the three orders of magnitude enhancement in local concentrations predicted using the hybrid method might be an underestimate . As all polyproline motifs occur in the disordered region of Sos1 , the inherent flexibility gives rise to a large number of molecular species in Grb2-Sos1 complexes . We used the measured single site equilibrium constants for the binding of the separate Grb2 SH3 domains to the peptides [13] to estimate the intramolecular equilibrium constants of these species contributing to complex formation . The calculated for the entire Sos1 molecule is a factor of three higher than the measured value [34] , while for the Sos1 fragment containing the first three binding motifs , , a factor of four higher than the measured value [6] , [37] . Lack of sampling and inaccuracies in the force field in the MD simulations , the simplicity of the WLC model , neglect of the interactions between linker and Grb2 , and neglect of any allostery between N-SH3 and C-SH3 domains in Grb2 , all may introduce errors in and contribute to the weaker binding predicted than observed . Also , the single site affinity values we use in our calculations , which come from binding studies using 12 amino acid length peptides lacking flanking sequences [13] , may differ from the values that would be obtained for binding motifs embedded in Sos1 [35] , [36] . Nevertheless , we were able to use a purely computational approach , in the absence of any additional parameters , to calculate an effective equilibrium constant for binding of Grb2 to Sos1 to within an order of magnitude of the experimental value . We are optimistic that such an approach could be used to estimate the effective equilibrium constants for multivalent complexes in the absence of experimental information . Finally , we want to comment on the nature of complexes that form under physiological concentrations and on the impact of the newly predicted fifth motif in Sos1 on downstream signaling . Binding studies of Grb2 to Sos1 under physiological conditions suggests that the valence of Sos1 for Grb2 is two and that a bound Grb2 has both its SH3 domains attached to Sos1 [6] . Our calculations clarify why , over the concentration ranges studied , this is a reasonable description of the binding . For these concentrations , only 1∶1 and 2∶1 complexes of Grb2 are predicted to form with measurable concentrations . The newly identified fifth proline-rich motif on Sos1 could lead to additional cross-linking . As the equilibrium constants for the Sos1 motifs to SH3 in Grb2 are low , [13] , and the concentration of Sos1 in Jurkat T cells is [8] , we expect cross-linking of two Sos1 by a single Grb2 to be negligible in the cytosol . However , the fifth site might play a role after Sos1 is brought close to the membrane . Once T cells are stimulated and Sos1 is recruited to LAT , the effective Sos1 concentration just below the plasma membrane becomes much higher than the cytosolic Sos1 concentration in the resting cell . This may lead to cross-linking of two Sos1 by a single Grb2 ( Figure 9 ) . The additional linking of Sos1 to LAT would increase the stability of Sos1-Grb2-LAT aggregates and thus , the lifetime of Sos1 at the plasma membrane .
Sos family sequences were obtained through a BLAST [45] search against the National Center for Biotechnology Information non-redundant ( NCBI-NR ) database using the Sos1 sequence from H . sapien as a seed and a E-value cutoff of . Only completely sequenced proteins were taken , and any sequence that did not belong to the Sos family was removed using phylogenetic analysis . The sequences obtained were aligned with CLUSTAL W [46] and improved manually . Conservation within each group is calculated by identity within each column in the multiple sequence alignment , and three representatives were chosen from each group for Figure 1 using Sequence QR [47] . All the above steps were performed in the Multiseq plugin [48] in VMD [49] . The structure of the N-SH3 domain and the backbone of the class I peptides were obtained from the NMR structure ( PDB ID 1AZE ) [21] . The structure of the N-SH3 domain bound to a RP peptide was obtained from a frame at 10 ns of the MD simulation after the RMSD converged . The structure of the C-SH3 domain and the backbone of the RP peptide were obtained from a NMR structure ( PDB ID 1IO6 ) [16] . The structure of the C-SH3 domain and the peptide P1 were obtained from a frame ( at 10 ns ) in the MD simulation well after the RMSD converged . The structure of the P1 to P4 and RP peptides were based on the backbone of P1 in the above structures and were generated using Scwrl [50] . The protocol for binding the P1 to P4 motifs to C-SH3 required an additional step that utilized MD simulations to generate the conformation for the backbone of the P1 through P4 motifs bound to C-SH3 . MD simulations have previously been used to produce good candidate conformations for AutoDock as , for example , in predicting novel inhibitors for RNA-editing ligases [22] . The backbones of the peptide and the receptor molecules were kept rigid during the docking procedure . All polar hydrogen atoms in the receptor and peptide molecules were added using AutoDock . Mass-centered grid maps were generated with 0 . 375 Å spacing by the AutoGrid program for the whole protein target . AutoDock4 parameters were used for all the atoms during the docking procedure . Lennard-Jones parameters 12–10 and 12–6 were used for modeling H-bonds and van der Waals interactions , respectively . A distance-dependent dielectric permittivity was used for the calculation of the electrostatic grid maps . The Lamarckian genetic algorithm ( LGA ) was used to predict the binding site and binding energy of the peptide to the SH3 domains . The number of generations was set to 250 million in all runs . Random starting positions on the entire protein surface , random orientations , and side-chain torsions were used for the ligands . The runs were performed with 50000 generations and the population size was set to be 150 . was calculated from MD simulations of Grb2 bound to the P1 and P2 peptides . The distances between the atoms of the appropriate terminii of these two peptides are calculated . The histogram ( H ( r ) ) of distance separation ( r ) is calculated using 100 bins . The probability density is calculated using the formula: ( 13 ) where is the width of each interval in the histogram . is substituted into Eq . to calculate .
|
Many biochemical interactions are mediated by multivalent binding where signaling proteins use relatively weak promiscuous interactions to increase the strength and specificity of complex formation . For a bivalent adaptor protein binding to a multivalent ligand , the tethering of one of the adaptors binding sites to a motif on a multivalent ligand constrains the adaptors second binding site to a region with a high local concentration of ligand binding motifs . Intramolecular equilibrium constants associated with multivalency are difficult to measure . Typically , polymer models are utilized to estimate the enhancement in local concentration and , when the biomolecular equilibrium constants for the individual sites are known , to obtain intramolecular equilibrium constants . However , flexibility of structured regions in proteins that contain the binding motifs restricts the application of simple polymer models for many systems . Here , we develop a hybrid method combining molecular dynamics simulations and polymer models to estimate the intramolecular equilibrium constants . We apply this method to study the multivalent interactions between the widely expressed adaptor protein growth factor receptor bound protein-2 ( Grb2 ) and the nucleotide exchange factor son of sevenless 1 ( Sos1 ) .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"biomacromolecule-ligand",
"interactions",
"biology",
"computational",
"biology",
"signaling",
"networks",
"biophysics"
] |
2011
|
Quantifying Intramolecular Binding in Multivalent Interactions: A Structure-Based Synergistic Study on Grb2-Sos1 Complex
|
Following DNA replication , sister chromatids must stay connected for the remainder of the cell cycle in order to ensure accurate segregation in the subsequent cell division . This important function involves an evolutionarily conserved protein complex known as cohesin; any loss of cohesin causes premature sister chromatid separation in mitosis . Here , we examined the role of cohesin in sister chromatid cohesion prior to mitosis , using fluorescence in situ hybridization ( FISH ) to assay the alignment of sister chromatids in interphase Drosophila cells . Surprisingly , we found that sister chromatid cohesion can be maintained in G2 with little to no cohesin . This capacity to maintain cohesion is widespread in Drosophila , unlike in other systems where a reduced dependence on cohesin for sister chromatid segregation has been observed only at specific chromosomal regions , such as the rDNA locus in budding yeast . Additionally , we show that condensin II antagonizes the alignment of sister chromatids in interphase , supporting a model wherein cohesin and condensin II oppose each other’s functions in the alignment of sister chromatids . Finally , because the maternal and paternal homologs are paired in the somatic cells of Drosophila , and because condensin II has been shown to antagonize this pairing , we consider the possibility that condensin II-regulated mechanisms for aligning homologous chromosomes may also contribute to sister chromatid cohesion .
It is well recognized that the three-dimensional organization of interphase nuclei is non-random and can affect gene expression , development , and numerous other processes [1–4] . In addition to cell-type specific interactions between and within chromosomes [5 , 6] , nuclear organization is shaped by chromosome-wide changes in structure that are inherent to the process of nuclear division . For instance , in addition to condensing their chromosomes into the compact forms found in metaphase , mitotically dividing cells double their DNA content and thus their chromosome number during S-phase . Diploid cells therefore transition from a G1 phase with two copies of each chromosome , called the maternal and paternal homologs , to a G2 phase with four copies of each chromosome , each homolog having been replicated to form a set of sister chromatids . Importantly , sister chromatids are held together by physical connections , beginning in S-phase and continuing through G2 into mitosis , that are critical for ensuring that the two chromatids ultimately segregate into different daughter cells [7–9] . Remarkably , these connections , known as cohesion , exist in G2 amidst a variety of other inter- and intra-chromosomal interactions and yet are uniquely maintained between sisters . This study focuses on mechanisms contributing to cohesion , defined as the connection between sister chromatids from the time of DNA replication until cell division [7 , 8] . In particular , we explore the possibility that cohesion may also reflect contributions from mechanisms in somatic cells that pair maternal and paternal chromosomes , which , like sister chromatids , share sequence homology ( reviewed by [10] ) . Sister chromatid cohesion is known to require a highly conserved , essential group of proteins known as the cohesin complex [11–13] . This complex consists of two members of the structural maintenance of chromosomes ( SMC ) protein family , Smc1 and Smc3 , a kleisin protein called Rad21/Scc1 , and an associated protein known as Stromalin/Scc3 ( reviewed by [7 , 14] ) . The association of cohesin with chromatin is regulated in a cell-cycle-dependent manner , starting with the loading of cohesin during the G1/S transition in yeast [12 , 15] and even earlier in vertebrates [13 , 16 , 17] . The establishment of cohesion during S-phase is essential for proper cohesin function in mitosis [13 , 18–20] . Once chromosomes have aligned at the metaphase plate in mitosis , Rad21 is cleaved and cohesin dissociates from the chromatin , allowing sister chromatid separation [21–25] . Consistent with this , loss of cohesin leads to premature sister chromatid separation in mitosis [11–13 , 26–29] . Structurally , the cohesin complex forms a ring-shape [30–32] , and artificially sealing the ring by chemical cross-linking prevents cohesin dissociation from DNA [33 , 34] . Based on these and other data , several models for how cohesin holds sister chromatids together have been proposed [30 , 32–40] . For example , a single cohesin molecule could encircle two sister chromatids , or cohesin molecules could bind individual chromatids and then self-associate . Importantly , as cohesin proteins have also been shown to participate in gene regulation , chromatin looping , and DNA repair ( reviewed by [41] ) , the mechanism of cohesin activity may differ across its different functions [14 , 42 , 43] and depend to varying degrees on contributions from other proteins or other types of inter-chromosomal interactions . The requirement of cohesin proteins for maintaining proper cohesion of metaphase chromosomes is well established in multiple organisms [11–13 , 26–29] . Interestingly , there is evidence suggesting that additional mechanisms contribute to cohesion as well ( reviewed by [44] , see also [45 , 46] ) . For example , sister chromatid separation at the rDNA locus during mitosis in S . cerevisiae requires the activity of other proteins in addition to cohesin cleavage , suggesting that this locus has connections between sisters that are independent of cohesin [47–51] . This cohesin-independent cohesion is region-specific , however , as other loci show sister chromatid separation soon after or even before the completion of DNA replication in the absence of cohesins [12 , 44 , 52] . Similarly , the extent of premature sister chromatid separation observed in metaphase in the absence of cohesin varies across chromosomes in Xenopus [29 , 53] , chicken [27] , and human cells [54] . These observations raise questions regarding the nature of cohesin-independent connections between sister chromatids , why the cell might have such connections in addition to those mediated by cohesin proteins , and how cohesin-independent mechanisms might contribute to other inter-chromosomal associations and nuclear organization throughout the cell cycle . The nuclei of Drosophila melanogaster and other Dipteran insects present a unique situation , where sister chromatid cohesion is not the only association between chromosomes that are homologous to each other . In these insects , maternal and paternal homologs show robust pairing in somatic cells throughout development ( reviewed by [55] ) , occurring in different stages of the cell cycle and in many different tissues . Additionally , this pairing impacts gene expression through mechanisms known as transvection ( reviewed by [56–58] , see also [59–63] ) . Therefore , homolog pairing is a prominent and functional feature of Dipteran nuclear organization . Since cohesion and homolog pairing are both interactions between chromosomes sharing sequence homology , we have asked whether the mechanisms underlying homolog pairing may also contribute to the cohesion of sister chromatids . The initial observations leading to our studies were obtained during a genome-wide RNAi screen in cultured Drosophila cells for genes involved in somatic homolog pairing and other forms of interphase nuclear organization . This screen assayed pairing at two distinct heterochromatic loci using high-throughput fluorescence in situ hybridization ( Hi-FISH ) [64] , where a single FISH signal indicated that all copies of the targeted locus were in close proximity to each other , and RNAi knockdowns leading to more or fewer FISH signals identified genes that were candidates for promoting or antagonizing pairing respectively [64] . We expected that cohesin knockdown would increase the number of signals observed in FISH assays because of sister chromatid separation ( Fig 1 ) . Such assays also tested whether cohesin contributes to homolog pairing; for example , cohesin molecules may encircle or otherwise spatially restrict homologs as well as sisters , or the presence of cohesion between sister chromatids may facilitate alignment and/or recombination of homologs , as occurs during meiosis in many organisms [65 , 66] . Surprisingly , cohesin proteins were not among the 105 genes identified in the screen . This was our first indication that Drosophila cells might have cohesin-independent pairing of homologous chromosomes and cohesion of sister chromatids . In contrast , the screen did identify multiple components of another SMC protein complex , condensin II , as anti-pairers [64] . Condensin II , as well as another condensin complex , called condensin I , are involved in chromosome compaction prior to mitosis in many organisms [67 , 68] . In Drosophila , condensin II had previously been shown to antagonize homolog pairing and transvection in vivo [69] . Interestingly , we also found that the SCF ubiquitin ligase component Slmb promotes pairing and , consistent with the negative regulation of condensin II by Slmb through ubiquitination of the condensin II subunit Cap-H2 [70] , the reduction of homolog pairing caused by Slmb knockdown is dependent on condensin II [64 , 70] . These and other studies of condensin II and its regulators highlight the importance of condensin II levels for proper nuclear organization [71–74] . Interestingly , condensin components have also been implicated in the regulation of sister chromatid cohesion in organisms where homolog pairing is not prevalent , including in budding yeast [47–51 , 75 , 76] . These findings suggest that homolog pairing in flies might be mechanistically related to cohesin-independent cohesion in other species , and that , in Drosophila , the mechanisms that act between sister chromatids may be similar to , or the same as , those that act between homologs . This model has also been proposed by Ono et al . based on studies demonstrating that condensin II in human cells begins resolving sister chromatids in S-phase [77] . Here , we present data showing that the cohesion of sister chromatids in G2 Drosophila cells can be maintained with little to no cohesin protein , and that knockdown of pairing regulators such as Slmb and Cap-H2 reveal a phenotype following cohesin loss . These results are consistent with what one might expect if the mechanisms of homolog pairing were also contributing to sister chromatid cohesion .
In our previously published screen for genes involved in homolog pairing [64] , we applied Hi-FISH to tetraploid Kc167 cells in 384-well plates seeded with a whole-genome RNAi library and assayed pairing at two pericentric heterochromatic loci , one consisting of the 359 satellite repeats [78] on the X chromosome and the other consisting of the dodeca satellite repeats [79 , 80] on chromosome 3 . In this study , the extent of homolog pairing was defined operationally as the percentage of nuclei in a population with one FISH signal per locus , and because a single signal would also require sister chromatid cohesion , our assay of homolog pairing also reflected sister chromatid cohesion in interphase . As no cohesin subunits or associated proteins were identified in the screen , our screen suggested that homolog pairing as well as sister chromatid cohesion can occur with little to no cohesin protein at the two loci assayed . Given the unexpected nature of these findings , we began our studies by determining whether our failure to identify cohesin in the screen was due to an artifact of culturing cells in 384-well plates and using Hi-FISH as part of the screening protocol and/or due to incomplete knockdown by RNAi . To do so , we performed studies using conventional slide-based FISH in both Kc167 cells and another Drosophila cell line , S2R+ . Under these conditions , we found that , compared to levels in control cells , the mRNA levels of Rad21 , Smc1 , Smc3 , and Stromalin ( SA ) were reduced by 83% , 87% , 92% , and 79% , respectively , following four days of RNAi , which was the duration of RNAi knockdown used in the screen ( S1 Fig ) . Consistent with this , Rad21 protein levels were also depleted when assayed by Western blot and immunofluorescence in both S2R+ ( Fig 2A and 2B ) and Kc167 cells ( S2 Fig ) ; by Western , the efficiency of Rad21 knockdown at the protein level was estimated to be 88–89% ( S3 Fig ) . Importantly , no significant reduction in the percentage of nuclei with only a single FISH signal was observed in cohesin RNAi-treated cells as compared to controls when we targeted FISH to 359 ( 81 . 8% versus 78 . 9% , P = 0 . 4526 ) and dodeca ( 40 . 9% versus 36 . 0% , P = 0 . 3909 ) , as well as the AACAC pericentric heterochromatic repeat locus [81] on chromosome 2 ( 55 . 0% versus 58 . 0% , P = 0 . 6214 ) ( Fig 2C; values are for S2R+ cells , but lack of a significant reduction was also observed with Kc167 cells , see Fig 3 for more details ) . We also tested simultaneous knockdowns of multiple cohesin proteins ( S4A Fig ) and longer RNAi treatments ( S4B Fig ) and found no consistently significant effects on the percentage of nuclei with single FISH signals . Although these data do not rule out degrees of sister chromatid separation that cannot be detected by diffraction-limited light microscopy ( Materials and Methods ) , they nevertheless argue that sister chromatids are able to remain in relatively close proximity with little to no cohesin protein . Efficient knockdown of cohesin was also confirmed by the observation of premature sister chromatid separation in metaphase following cohesin RNAi ( Fig 2D and S5 Fig ) . That is , after knockdown of Rad21 , Smc1 , or Smc3 , sister chromatids appeared as single chromosomes rather than the pairs of connected chromatids that are normally observed in metaphase spreads ( S5 Fig ) . We then extended this analysis , focusing on Rad21 because the extent of sister chromatid separation observed in metaphase following Rad21 knockdown was more severe than that observed following knockdown of either Smc1 or Smc3 ( S5 Fig ) . Here , we first determined the copy number of each chromosome in control cells by performing FISH on metaphase spreads , confirming that our S2R+ cell line has an irregular but stable karyotype , with two copies of the X , three copies of chromosome 2 , and four copies of chromosome 3 ( Fig 2D ) . We then applied FISH after Rad21 knockdown and observed an increase in the number of FISH signals at AACAC and dodeca ( P<0 . 0001 for both ) ; additionally , the median numbers of FISH signals increased from 3 . 0 and 4 . 0 signals in control cells at AACAC and dodeca , respectively , to 6 . 0 and 7 . 5 in Rad21 RNAi-treated cells ( Fig 2D ) . While we cannot rule out contributions from aneuploidy , the approximate doubling of the median along with the observation of separated chromatids is strongly indicative of mitotic sister chromatid separation after cohesin knockdown . These findings further suggest that at this stage of the cell cycle , there is little cohesin-independent cohesion , as has been previously observed [82] . Importantly , this loss of cohesion in mitotic cells was unlikely to have had a significant impact on the overall percentage of nuclei with single FISH signals in our screen or in subsequent experiments , since mitotic nuclei represent only a small percentage of a cycling population; we found the mitotic index following Rad21 knockdown to be around 7% , consistent with published results [28] . The fact that we do not see massive levels of aneuploidy following cohesin knockdown suggests that there may be residual cohesin contributing to segregation to some degree , despite being insufficient to keep sister chromatids tethered together during metaphase . Alternatively , it is possible that cohesin-independent mechanisms contribute to segregation . There is evidence to suggest that segregation is not completely disrupted following cohesin cleavage; for example , studies using TEV-protease to induce cleavage of cohesin in Drosophila have found that prematurely separated sister chromatids often segregate to opposite poles [83] , and that single chromatids form stable attachments to the spindle despite lacking tension provided by cohesin between sister chromatids [84] . Note that , while cohesin knockdown approximately doubled the median numbers of FISH signals in mitotic cells at AACAC and dodeca , it was not sufficient to completely disrupt cohesion at 359; while there was sometimes a significant increase in the number of FISH signals at 359 ( P = 0 . 0126 ) , indicative of some sister chromatid separation , the median was unchanged , remaining at 2 . 0 and indicating that sister chromatids remained connected in many cells ( Fig 2D; note that significance was not always achieved for 359 , see S10 Fig ) . It is possible that this result could be explained by residual cohesin protein that is present at the 359 locus . Alternatively , 359 may retain a cohesin-independent connection between sister chromatids even in mitosis . Either interpretation suggests that the 359 locus requires less cohesin than do other loci to maintain cohesion in mitosis . Intriguingly , the 359 locus is proximal to the rDNA locus on the Drosophila X chromosome [85] , raising the possibility that its cohesion is influenced by that of the rDNA; as mentioned earlier , the rDNA locus of S . cerevisiae displays cohesin-independent cohesion [47–51] . The sister chromatid separation observed in mitosis but not in interphase following Rad21 knockdown raises the possibility that the former reflects , at least to some extent , physical forces that disjoin sister chromatids in mitosis . As such , sister chromatid cohesion might be maintained in G2 not because sisters can be held together in the absence of cohesin , but because they are not being actively pulled apart . To address this possibility , we prepared metaphase spreads in both the absence and presence of colchicine , an inhibitor of microtubule polymerization . Addition of colchicine increased the number of metaphase spreads that were obtained from 1 . 25% to 3 . 88% of cells without RNAi , and from 1 . 86% to 4 . 84% of Rad21 RNAi-treated cells ( S1 Table ) , consistent with the role of colchicine in inhibiting mitosis by blocking spindle assembly . Importantly , we found that colchicine does not significantly alter cohesion in metaphase following Rad21 knockdown ( S1 Table ) ; the percentage of metaphase spreads with intact sister chromatid cohesion after knockdown was 25% without colchicine and 34% with colchicine ( P = 0 . 1570 ) . These values are both significantly less than the 77% of cells without RNAi having intact cohesion in the presence of colchicine ( P<0 . 0001 ) . These results argue that loss of cohesion in mitosis cannot be explained by spindle assembly , alone , and thus suggests that the failure of Rad21 knockdown to separate sister chromatids in G2 may entail another aspect of interphase cells , such as homolog pairing . To better understand the progression of cohesin depletion , we performed a timecourse of Rad21 knockdown in Kc167 cells and observed premature sister chromatid separation in mitotic cells as early as the third day following RNAi treatment ( S6C Fig ) . As Kc167 cells complete the cell cycle in 24–30 hours [86] , this observation argues that populations of cells that have been treated with RNAi for four or more days should have experienced cohesin depletion for the duration of at least one cell cycle . These studies also enabled us to address whether our inability to observe an effect of cohesin knockdown in interphase cells resulted from inadvertent disruption of the cell cycle; for example , arrest in G1 , prior to S phase , would necessarily preclude sister chromatid separation . Evidence against this explanation was the fact that , while Rad21 knockdown caused an increased mitotic index , cells continued cycling , albeit with a delay as compared to control cells ( S6A Fig ) , consistent with published results [28 , 84] . In addition , both FACS analysis ( S6B Fig ) and immunofluorescence for cyclin B , a protein that is expressed from S-phase through G2/M-phase [87–90] ( S12B Fig ) , confirmed that at least two-thirds of the cell population is in G2 following cohesin knockdown . These observations argue that the apparent maintenance of cohesion following cohesin knockdown cannot be explained by a paucity of G2 nuclei . Thus , in conjunction with the findings described above , our studies indicate that the 384-well FISH format cannot explain why cohesin was not identified as a candidate gene in our screen [64] , and further , that neither inefficient knockdown nor a paucity of G2 nuclei can explain why cohesin RNAi treatment does not disrupt sister chromatid cohesion or homolog pairing in interphase cells . As such , our studies suggest that either the low levels of residual cohesin protein remaining following RNAi treatment are sufficient for cohesion in G2 cells and/or that additional cohesin-independent mechanisms contribute to cohesion in interphase . As the three loci we initially examined by FISH were all located within pericentric heterochromatin , it was possible that the reduced requirement for cohesin we observed in interphase cells was specific to repetitive or heterochromatic sequences . Therefore , we used FISH to target eleven euchromatic regions in a variety of genomic locations following Rad21 knockdown ( Fig 3 ) . Applying Oligopaint [91] FISH probes to control and Rad21 RNAi-treated cells , we targeted eight euchromatic loci ranging in size from tens to hundreds of kilobases and representing all major Drosophila chromosomes: 5A ( X chromosome , target size 672 . 0 kb ) , 16E ( X , 700 . 0 kb ) , 24D ( 2L , 490 . 6 kb ) , 28B ( 2L , 680 . 0 kb ) , 69C ( 3L , 674 . 0kb ) , 89B ( 3R , 49 . 7 kb ) , 89E ( 3R , 49 . 7 kb ) and 100B ( 3R , 462 . 3 kb ) ( Fig 3A and 3C ) . Strikingly , we did not find the percentage of nuclei with a single FISH signal to be consistently and significantly reduced at any locus following Rad21 knockdown in either Kc167 or S2R+ cells ( Fig 3C ) . These data suggest that the reduced requirement of cohesin protein to maintain interphase cohesion and homolog pairing is a property of both single-copy euchromatic as well as pericentric repetitive regions . Considering the possibility that cohesin might be required to maintain sister chromatid cohesion and homolog pairing on a more global scale in ways not obvious from the analysis of short chromosomal regions , we also tested cohesin knockdowns with Oligopaints targeting three large regions on the right arm of chromosome 2 ( 3 . 1 Mb , 2 . 7 Mb and 2 . 6 Mb ) ( Fig 3B ) . Examining a large region minimized the chances of visualizing only late-replicating regions where , in early G2 , sister chromatids may not yet have formed . Additionally , large FISH targets allowed a greater dynamic range in the size of the FISH signals , permitting us to more easily measure the area of the FISH signals in maximum-Z projections , in addition to counting the number of signals . We reasoned that an assay of signal size might be more sensitive to local separation of sister chromatids and/or homologs occurring anywhere along the chromosome arm even if complete separation had not occurred . Following knockdown of Rad21 , neither the number of FISH signals nor the area of the image covered by these signals showed a significant increase , contrary to what might have been expected if sister chromatids had simply separated ( Fig 3C ) ; the combined area of the FISH signals was 23 . 8% and 17 . 5% of the nuclear area in control and Rad21 RNAi-treated cells , respectively ( P<0 . 0001 indicating a significant decrease ) . The decrease in signal areas we observed following Rad21 knockdown was unexpected , and could indicate an interesting role for cohesin in antagonizing compaction of chromatin , though further experiments are necessary to confirm this trend . Along these lines , it is interesting to note the significant increase in the percentage of nuclei with a single FISH signal at some loci examined with smaller FISH probe sets , specifically 89B in S2R+ cells and AACAC in Kc167 cells ( see Fig 3C ) . Regardless , our data suggest that sister chromatids can maintain cohesion and homologs can remain paired across all chromosome arms with very little or no Rad21 . We next addressed whether homolog pairing can contribute to the cohesion of sister chromatids in interphase , reducing the requirement for cohesin proteins . For example , the mechanisms that pair homologs might also act directly between sister chromatids , holding them together even in the absence of cohesin . Alternatively , it is possible that , because homologs are paired in G1 , the replication products of these chromosomes can remain closely associated in G2 without mechanisms acting directly to hold sisters together ( Fig 4A ) . To test this second possibility , we studied a chromosome that does not have a homolog , that is , the single X chromosome in a diploid XY male cell . We reasoned that if interphase cohesion between sisters following cohesin knockdown is dependent on the presence of a homolog and/or pairing between the homologs , the X chromosome in a male cell line should display disrupted cohesion while the autosomes , which are present in two copies , should not . For these studies we selected Drosophila Clone 8 ( Cl . 8+ ) cells , which we confirmed by karyotyping to be stably diploid and XY ( Fig 4B ) . Given the low efficiency of RNAi in Clone 8 cells ( S7 Fig ) , as versus Kc167 or S2R+ cells , we used GFP as a co-transfection marker for dsRNA . We carried out immunofluorescence for GFP , cyclin B ( a G2 marker ) , and Rad21 to identify the cells of interest ( positive for GFP and cyclin B and negative for Rad21 ) followed by FISH targeting region 16E on the X chromosome and dodeca on chromosome 3 ( Fig 4C; Materials and Methods ) . Consistent with our results in other cell lines , the percentage of nuclei with a single FISH signal at dodeca was not significantly different between control G2 cells and those treated with Rad21 RNAi ( 78 . 9% and 87 . 8% , respectively , P = 0 . 0654 ) ( Fig 4D ) . Remarkably , we found that sister chromatid cohesion at 16E on the X chromosome was also unaffected by cohesin knockdown , with 95 . 2% and 95 . 9% of control and Rad21 RNAi-treated G2 cells , respectively , having a single FISH signal ( P = 0 . 7992 ) ( Fig 4D ) . These observations argue that , barring intrinsic features that may be specific to the X chromosome , cohesion between sister chromatids can be maintained with little to no cohesin protein even when these chromosomes have never experienced homolog pairing . Thus , our data suggest that , whatever mechanism might be compensating for the loss of cohesin , it is not dependent on homolog pairing in the preceding G1 , and therefore may initiate in S-phase/G2 and act directly between sister chromatids . Note that 16E is located within the euchromatic arm of the X and >5 Mb away from the rDNA locus , which is positioned near the centromere . Thus , while the rDNA of the X and Y chromosomes can support local pairing [92] , we consider it unlikely that pairing of the rDNA loci accounts for cohesion with little to no cohesin at 16E . That being said , it remains possible that inter-chromosomal associations occurring near the centromere might influence the organization of a chromosome arm . For example , pairing of X and Y near the centromere might lead to nonhomologous “pairing” between their arms , which could influence sister chromatid cohesion . Although cohesion of sister chromatids in cohesin-depleted G2 cells may not require the presence of a homolog , it could still depend on mechanisms that also participate in homolog pairing . To test this idea , we combined cohesin knockdown with knockdown of Slmb , a gene which is required for homolog pairing; Slmb is a negative regulator of condensin II , and Slmb knockdown leads to an increased number of FISH signals and thus a decrease in the percentage of nuclei with a single FISH signal [64 , 70] . If Slmb is also required for cohesin-independent cohesion , we might expect simultaneous knockdown of both Slmb and cohesin to disrupt cohesion as well as homolog pairing , leading to even more FISH signals than when Slmb alone is knocked down . We performed double knockdowns of Slmb and Rad21 in S2R+ cells and , having confirmed by qPCR that the knockdown of each gene was efficient ( S8 Fig ) , assayed the number of FISH signals observed at pericentric heterochromatin ( Fig 5A ) . Knockdowns of Slmb , whether alone or in combination with Rad21 , reduced the percentages of nuclei with a single FISH signal at AACAC and dodeca from , respectively , 52 . 5% and 38 . 0% in control cells to 18 . 8% and 10 . 0% after Slmb knockdown and 26 . 0% and 11 . 9% following knockdown of both Slmb and Rad21 ( Fig 5B ) . Therefore , pairing levels were similarly reduced whether we knocked down only Slmb or both Rad21 and Slmb; however , when unpairing did occur , we often observed more FISH signals when both Rad21 and Slmb were knocked down ( Fig 5A and S9 Fig ) . In particular , the double knockdown of Rad21 and Slmb produced nuclei with four to six or more FISH signals at AACAC ( Chr 2 ) , or five to eight or more FISH signals at dodeca ( Chr 3 ) , which is noteworthy because our S2R+ cells typically carry only three copies of chromosome 2 and four copies of chromosome 3 ( Fig 2D ) . We reasoned that the "extra" FISH signals likely represented the separation of sister chromatids and applied this approach in subsequent analyses . That is , we considered the presence of more than three AACAC FISH signals or four dodeca FISH signals in a nucleus as indicative of sister chromatid separation . As this assay requires homolog pairing as well as the separation of sister chromatids , our measure of sister chromatid separation is likely an underestimate . Using this metric for identifying instances of sister chromatid separation , we observed that there is little sister chromatid separation following knockdown of Slmb alone; the percentages of nuclei with more than three FISH signals at AACAC or more than four FISH signals at dodeca were 4 . 7% and 11 . 2% , respectively , differing little from those of control cells ( Fig 5C ) . In contrast , these percentages were 15 . 2% and 23 . 5% when both Rad21 and Slmb were knocked down , both values representing significant increases as compared to the outcome of knocking down Slmb alone ( P<0 . 0001 and P = 0 . 0035 for AACAC and dodeca , respectively ) ( Fig 5C ) . These findings suggest that , unlike knockdown of either Slmb or Rad21 alone , the double knockdown of Slmb and Rad21 results in sister chromatid separation as well as homolog unpairing . As the extra FISH signals could be explained by aneuploidy , we analyzed metaphase spreads following knockdowns , but did not find evidence for increased aneuploidy after double knockdown of Rad21 and Slmb as compared to knockdown of Slmb alone ( S10 Fig ) . The extra FISH signals were also unlikely to reflect decompaction or fragmentation of heterochromatin , as double knockdowns of Rad21 and Slmb increased the number of signals at three out of five euchromatic loci studied ( S11 Fig ) . The relatively modest effects observed at euchromatic as versus heterochromatic loci may stem from the overall higher levels of homolog pairing at euchromatin [64 , 93 , 94] . We also considered the possibility that the increase of nuclei with extra FISH signals represented the arrest of cells in mitosis , when sister chromatid cohesion is lost following cohesin knockdown . Here , we combined FISH with immunofluorescence to phosphorylated histone H3 ( pH3 ) to identify mitotic cells [95] after knockdown of both Rad21 and Slmb , and found that exclusion of pH3-stained nuclei dropped the number of nuclei with more than three FISH signals at AACAC only slightly from 14 . 9% to 13 . 6% , which is still significantly higher than the percentage of interphase nuclei with more than three FISH signals after knockdown of Slmb alone ( 5 . 16% , P = 0 . 0005 ) . Furthermore , immunofluorescence for cyclin B confirmed that the increase in the number of FISH signals in the double knockdown was not caused by an enrichment of G2 cells ( S12 Fig ) ; knockdowns decreased the proportion of G2 cells from 66 . 9% in control cells to 46 . 2% after Slmb knockdown and 41 . 9% after knockdown of both Rad21 and Slmb . This decrease limits the number of nuclei where sister chromatid separation is possible , and may explain why the percentage of nuclei with extra FISH signals was never more than 30% . Therefore , while we cannot rule out any contribution of aneuploidy , disorganization of heterochromatin , or cell cycle arrest , we favor the hypothesis in which the extra FISH signals in the double knockdowns of Rad21 and Slmb are caused by sister chromatid separation in interphase . This interpretation suggests that Slmb contributes to cohesion independently of cohesin . However , we also note that , even if Slmb does not regulate cohesion , any of the alternative explanations mentioned would still indicate an interesting relationship between Rad21 and Slmb and , therefore , between cohesion and homolog pairing . Finally , we considered the role that Slmb plays in the negative regulation of condensin II [70] and asked whether condensin II might contribute to sister chromatid separation in our assays . Here , we asked whether the extra FISH signals we observed in the double knockdown of Rad21 and Slmb were dependent on condensin II by conducting a triple knockdown of Rad21 , Slmb , and Cap-H2 . Remarkably , the number of nuclei with extra FISH signals was suppressed to levels comparable to that observed for the knockdown of Rad21 or Slmb alone ( Fig 5A and 5C ) . In particular , while the percentages of nuclei with more than three FISH signals at AACAC or more than four FISH signals at dodeca were , respectively , 15 . 2% and 23 . 5% for the double knockdown of Rad21 and Slmb , the triple knockdown of Rad21 , Slmb and Cap-H2 gave significantly lower percentages , with only 5 . 0% and 4 . 8% of nuclei having extra FISH signals ( P = 0 . 0008 and P = 0 . 0016 for AACAC and dodeca , respectively ) ( Fig 5C ) . Importantly , this effect was not due to a reduction in the percentage of G2 cells in the triple knockdown ( S12 Fig ) . This suppression of the extra FISH signals by the triple knockdown also argues that the extra FISH signals observed in the double knockdown of Rad21 and Slmb were not an artifact of the double knockdown . Taken together , these results suggest that condensin II contributes to sister chromatid separation when Rad21 is compromised , raising the possibility that condensin II may contribute to sister chromatid separation under normal conditions , perhaps by removing cohesin-independent connections between sister chromatids . In light of the contributions of both condensin II and Slmb to homolog pairing [64 , 69–71] , these data further suggest that the mechanisms mediating cohesin-independent cohesion may be similar to , or the same as , those that mediate homolog pairing .
As mentioned previously , the idea that there may be cohesin-independent mechanisms that contribute to segregation of sister chromatids is not new . However , in most instances where a reduced dependence on cohesin has been observed , it has been documented in mitosis and only at specific regions [44] . As for studies of interphase in organisms other than Drosophila , those that have used FISH to assay the impact of cohesin loss have detected an increase in the number of FISH signals , increased distance between signals , or abnormally shaped signals [27 , 98–102] . These data indicate that in most organisms , cohesin loss is sufficient to cause chromatid separation in G2 , and that cohesin-independent mechanisms , if they do contribute to cohesion , do so in a locus-specific manner . Here we suggest that cohesin-independent mechanisms may be widespread in Drosophila , contributing to the pairing of homologs as well as to the cohesion of sister chromatids in G2 at 3 heterochromatic and 11 euchromatic loci , and therefore may act genome-wide . Based on our results , we cannot rule out that cohesin-independent mechanisms contributing to chromatid alignment are induced in response to cohesin knockdown . Nevertheless , these results demonstrate the potential for sister chromatids to remain aligned in interphase with little to no cohesin . It may well be no coincidence that Drosophila also supports extensive pairing of homologous chromosomes in somatic cells . We have also observed a genetic interaction between Rad21 and Slmb , a gene required for homolog pairing [64 , 70] . This finding suggests that homolog pairing and sister chromatid cohesion might be regulated by common mechanisms , consistent with a model that has been proposed by Ono et al . [77] . In particular , we favor a model in which the higher levels of condensin II activity caused by Slmb knockdown [70] separate sister chromatids as well as homologs in the absence of cohesin . This could happen if condensin II negatively regulates residual cohesin , or if cohesin-independent connections exist between sister chromatids as well as between homologs and condensin II antagonizes those connections ( Fig 6 ) . The latter model is supported by evidence from organisms other than Drosophila implicating condensin in the resolution of cohesin-independent connections between sister chromatids , including at the budding yeast rDNA locus [47–51] . In Drosophila , in addition to condensin II and several of its regulators being involved in homolog pairing [69–74] , the condensin I subunits Barren [103–105] , Cap-G [106 , 107] , and Cap-D2 [108] , as well as Smc4 ( present in both complexes ) [109] , are required for the complete resolution of sister chromatids in mitosis . In human cells , condensin II is necessary for sister chromatid resolution beginning in late S-phase [77] , and a significant amount of chromatid resolution by condensin II also takes place during prophase [110] . Consistent with these findings , our data suggest that condensin II-regulated mechanisms contribute to sister chromatid cohesion in interphase , and that this mechanism of cohesion is related to homolog pairing in Drosophila . As for whether cohesin-independent mechanisms contribute to cohesion in vivo , this possibility is supported by studies showing that cohesin cleavage induced via a TEV protease in Drosophila larvae does not noticeably disrupt polytene chromosome alignment [83] . In contrast , overexpression of the condensin II component Cap-H2 disrupted polytene alignment in the same cell type [69] . It will be of great interest to determine whether similar phenotypes are observed in actively dividing fly tissues . Our observations suggest that the mechanisms that act between sister chromatids may also act between homologs . This model is consistent with the idea that recognition of a pairing partner is based on DNA sequence or chromatin structure , as exemplified by the fact that chromosomal translocations can pair ( e . g . [111] , see also [112] ) , and that pairing can accommodate more than two copies of a chromosome , as has been observed most dramatically in polytene chromosomes ( e . g . [113] ) and polyploid cell lines ( e . g . [64 , 93 , 114] ) . Our work also pertains to the question of whether or not cells distinguish sisters from homologs ( e . g . [115] ) . If , as our work suggests , there are some aspects of chromosomal organization that do not distinguish sister chromatids from homologs , sister chromatids may influence gene expression beyond their contribution to chromosome copy number . For example , as homolog pairing can influence the communication between regulatory elements and promoters in cis as well as in trans [56–58] , sister chromatids may be able to join and influence this dialogue [93] . Indeed , just as transvection can occur between paired homologs , so might it occur between sister chromatids , making it possible for these two forms of transvection to be synergistic or mutually inhibitory during G2 ( S14 Fig ) . Importantly , inter-homolog communication and the contribution of sister chromatids to that process could vary by cell type , depending on the levels of cohesin-independent connections between sisters and homologs . Our data also address the long-standing question of when in the cell cycle homolog pairing can be established . While some studies have shown that levels of homolog pairing are higher in G1 than in G2 , suggesting that S-phase is a stage when pairing is more dynamic and possibly disrupted [64 , 116] , other work shows that pairing levels are similar in G1 and G2 [93] , possibly reflecting variability between cell types . Our experiments in the male diploid Clone 8 cell line suggest that cohesin-independent G2 cohesion of sisters , if it occurs , is not dependent on the presence of a homolog , which would indicate that cohesin-independent cohesion could be established de novo in G2 . As such , perhaps the pairing of homologs can also be established at this stage . Of course , S-phase/G2 may not be the only stage of the cell cycle when homolog pairing is established; G1 homolog pairing could represent either an additional establishment event following the disruption of pairing in anaphase [117] or , theoretically , the maintenance of homologous connections from the previous cell cycle through mitosis [64 , 93] . A major question concerns the potential nature of a cohesin-independent connection between chromosomes . There are several possibilities , including the contribution of factors , such as proteins or RNA , that function similarly to cohesin in keeping chromosomes together , but act specifically in interphase . For example , cohesion in somatic cells may involve multiple novel cohesin complexes , as is known to be the case in Drosophila meiosis [118–122] . Alternatively , cohesin-independent cohesion might involve direct connections between chromosomes themselves without any need for bridging factors , perhaps involving nontraditional base pairing or DNA catenations resulting from replication . In fact , one of the earliest models for cohesion , proposed before cohesin proteins were known , posited that sister chromatids could be held together by DNA catenations [123–125] . Consistent with this model , topoisomerase II , an enzyme that removes catenations formed during replication and other processes , is known to regulate the segregation of sister chromatids ( reviewed by [126] ) . Furthermore , recent work has shown not only that catenations contribute to cohesion but also that cohesin may play a role in maintaining catenations [34 , 127] . Additionally , a complex related to cohesin and condensin known as Smc5/6 is thought to bind chromosomes in response to sister chromatid intertwinings or other forms of topological stress and facilitate their resolution in yeast [128 , 129] . These observations raise the questions of whether catenations might be sufficient to maintain cohesion in interphase Drosophila cells in the absence of cohesin , and how condensin II might act to resolve catenations . The role of condensin II in regulating these sorts of topological connections may be to recruit or activate topoisomerase II; alternatively , condensin II may play a role in separating chromosomes independently of topoisomerase II ( reviewed by [130] , see also [76 , 131 , 132] ) . It is also possible that the activity of condensin II in compacting chromosomes , by forming more intra-chromosomal interactions , suppresses inter-chromosomal interactions ( Fig 6 ) [13 , 64 , 69 , 71] . Further experiments examining the roles of topoisomerase II and Smc 5/6 in interphase cohesion and their interactions , if any , with condensin II , will shed light on these questions . Given the mechanistic relatedness we have observed between homolog pairing and cohesion , it is possible that homolog pairing is also mediated at least in part by DNA catenations or entanglements [59 , 64 , 93 , 133 , 134] . If so , the widespread nature of homolog pairing in Drosophila cells might imply that these cells are more permissive for the formation of catenations . For example , homologs may become catenated when they are replicated in close proximity , perhaps via replication fork collapse and repair , or when they recombine , especially at the repetitive sequences of pericentric heterochromatin [135] . Interestingly , inhibition of topoisomerase II reduces levels of homolog pairing in Drosophila cells , which may reflect different roles for topoisomerase in sister chromatid cohesion as versus homolog pairing ( [93] , see discussion within ) . Drosophila cells may also differ from other organisms in the timing of the resolution of catenations; for example , retention of catenations until mitosis , when perhaps they are resolved in response to spindle formation [131] or other mitosis-specific factors , might explain why cohesin knockdown did not perturb the cohesion of sister chromatids in G2 . Indeed , the recent identification of ultrafine bridges in human cells demonstrates that catenations can remain until anaphase at certain regions ( reviewed by [136] ) . If cohesin-independent connections exist between sister chromatids , why maintain another mechanism of cohesion in the form of the highly conserved and essential cohesin proteins ? One explanation may be the requirement for unique connections between sister chromatids in order to ensure their segregation . Such connections may be provided by cohesin , whose establishment is coupled to DNA replication [18–20] , while cohesin-independent mechanisms may contribute to genome organization in other ways . Secondly , cohesin-independent connections may allow cohesion to be maintained at chromosomal regions where cohesin protein is not always bound at a high density . This would enable cohesin binding to be spatially and temporally dynamic [42 , 137] and permit additional roles of cohesin in interphase , such as in the regulation of transcription and DNA repair [14 , 138] . Thus , cohesin-independent mechanisms contributing to cohesion , perhaps including the maintenance of catenations , may be especially important in cell types having a long G2 stage , such as the cells used in this study . Finally , having a diversity of cohesion mechanisms may allow for a more layered regulation of cohesion removal as cells enter mitosis [75] . In fact , in higher eukaryotes , cohesin proteins are removed from different parts of the chromosome at different times; while a small population of cohesin is retained at the centromeres and cleaved at anaphase [96 , 97 , 139] , the bulk of cohesin on the chromosome arms is removed during prophase by Wapl and Pds5 [17 , 97 , 140–144] . Telomeric cohesion involves yet additional regulation [145–147] . Thus , cohesin-independent cohesion may constitute a further layer to be removed during the segregation of sister chromatids , the regulation of which may be useful in determining the order of segregation [51] or the length of the cell cycle . Since all these processes must be coordinated with the condensation of chromosomes prior to mitosis , perhaps it is not surprising that condensin proteins are involved in antagonizing cohesion ( reviewed by [130] ) or that cohesin and cohesin regulators play a role in condensation [11 , 46 , 148–150] . Overall , these observations and the work presented here indicate interesting interactions between different SMC complexes in the maintenance of interphase nuclear organization as well as the ways in which homologous DNA sequences interact with each other , whether between sister chromatids or between maternal and paternal homologs .
Kc167 , S2R+ and Clone 8 cells were cultured according to standard protocols ( see www . flyrnai . org for more details ) . RNAi treatments were started in each case one day after the cells had been split as part of their regular passaging . RNAi treatments lasted for four days unless otherwise specified . For Kc167 and S2R+ , cells were seeded at 0 . 5–0 . 8 million cells/mL with 15 μg of RNA per well in a 6-well plate or 5 μg of RNA per well in a 24-well plate ( for double or triple knockdowns , these amounts were scaled accordingly , with the amount of RNA for each target being kept the same as in the single knockdowns ) . For Clone 8 , cells were transfected with dsRNA using Effectene transfection reagent from Qiagen , with a GFP-expressing plasmid as a co-transfection marker . When using Effectene , the amount of dsRNA was reduced to 1 . 2 μg per well in a 24-well plate . dsRNA primers were designed using the SnapDragon tool for primer design ( http://www . flyrnai . org/cgi-bin/RNAi_find_primers . pl ) and synthesized by PCR amplification from genomic DNA followed by an in vitro transcription reaction using a MEGAscript T7 Transcription Kit ( Thermo Fisher Scientific ) . Quantitative PCR was used to assay efficiency of RNAi knockdowns according to standard techniques . Briefly , total RNA was isolated from cells using a Qiagen RNeasy Plus kit and then converted to cDNA using the Invitrogen SuperScript III First-Strand Synthesis System for RT-PCR . Primers for qPCR were designed using the Primer-BLAST website ( http://www . ncbi . nlm . nih . gov/tools/primer-blast/ ) . Reactions were set up using KAPA SYBR FAST qPCR kits and run on an Applied Biosystems 7300 Real-Time PCR System . Cells were collected after four days of RNAi and their protein levels were analyzed by Western blot according to standard protocols . Blots were probed using a rabbit anti-Rad21 antibody ( generous gift from Dr . Stefan Heidmann; used at 1:3000 ) to assay cohesin knockdown and a mouse anti-α-tubulin antibody ( Sigma-Aldrich; 1:5000 ) to assay loading , followed by secondary antibodies conjugated to HRP ( GE Healthcare Life Sciences ) , anti-rabbit ( 1:5000 ) and anti-mouse ( 1:10000 ) . Blots were then stained using Pierce ECL Western Blotting Substrate ( ThermoFisher Scientific ) . Band intensities were estimated using the gel analysis tools in ImageJ [151] . Following RNAi treatment , cells were harvested , resuspended in ice cold 100% ethanol , allowed to warm up to 37°C and then stained using a PI/RNase Staining Buffer ( BD Pharmingen ) . Cell populations were assayed based on DNA content to determine their cell cycle profile using a BD LSR II Analyzer . Cells were plated onto slides at concentrations of 1–5 million cells/mL and allowed to adhere for 1–2 hours . The cells were then washed in PBS , and fixed in 4% paraformaldehyde for 5–10 minutes . The slides were then washed in PBS and used immediately or stored in PBS at 4°C . IF slides were washed in PBS-T ( PBS with 0 . 1% Tween-20 ) , blocked in 1% BSA/PBS-T for 30 minutes at room temperature , and incubated with primary antibody at 4°C overnight followed by three more PBS-T washes and incubation with secondary antibody either for 2 hours at room temperature or overnight at 4°C . Slides were then washed in PBS-T and mounted using Slowfade with DAPI ( Thermo Fisher Scientific ) , followed by imaging . Primary antibodies used: rabbit α-Rad21 ( gift of Dr . Stefan Heidmann; 1:200 ) , mouse α-cyclin B ( Developmental Studies Hybridoma Bank; 1:100 ) , rabbit α-pH3 S10 ( Epitomics , 1:100 ) . Secondary antibodies used ( Jackson ImmunoResearch Laboratories ) : Cy3-conjugated anti-rabbit ( 1:165 ) , 488-conjugated anti-mouse ( 1:100 ) , Cy5-conjugated anti-mouse ( 1:20 ) . Our protocol for fluorescence in situ hybridization has been previously published [64 , 91] and was adapted from standard protocols [85 , 152 , 153] . In brief , cells were fixed as above and then washed in PBS , 2x SSCT ( 0 . 3M sodium chloride , 0 . 03M sodium citrate , 0 . 1% Tween-20 ) , and 50% formamide/2x SSCT . Slides were either used for FISH immediately or stored in 50% formamide/2x SSCT at 4°C . FISH slides were pre-denatured in 50% formamide/2x SSCT at 92°C for 2 . 5 minutes and then at 60°C for 20 minutes . FISH probes were added in a hybridization solution of 10% dextran sulphate/2x SSCT/50% formamide containing 10–20 pmol of probe per hybridization . The slides were then denatured by placing them on a heat block at 92°C for 2 . 5 minutes and allowed to hybridize overnight at room temperature for heterochromatic probes and at 37–42°C for euchromatic probes . Following hybridization , slides were washed in 2x SSCT at 60°C for 15 minutes , 2x SSCT at room temperature for 10 minutes , and 0 . 2x SSC at room temperature for 10 minutes before being mounted using Slowfade with DAPI ( Thermo Fisher Scientific ) and imaged . In cases where both IF and FISH were carried out , generally the two protocols were carried out in succession and the slides imaged afterwards . For some more sensitive antibodies , the cells were imaged following IF , then washed , used for FISH , and re-imaged , using software-assisted stage navigation to relocate the same fields . Most euchromatic FISH probes used in this study were designed and generated using our published Oligopaints protocol [91] , including 5A , 16E , 24D , 28B , 69C , 89B , 89E , and 100B , as well as the chromosome paints on 2R ( 41E-44C , 50D-53C , 58D-60E ) . One experiment at the 28B locus used a probe synthesized from a P1 plasmid ( Berkeley Drosophila Genome Project ) containing cloned Drosophila genomic DNA corresponding to chromosomal regions 28B1-28B2 ( DS01529 ) and then labeled by nick translation/direct labeling ( Vysis ) . Heterochromatic repeat regions were assayed using previously described FISH probe sequences [85 , 152] synthesized by Integrated DNA Technologies ( IDT ) . Metaphase cells were prepared using protocols adapted from published methods [154 , 155] . Cells were obtained from actively growing cultures without the use of drugs to increase mitotic index unless otherwise specified . In the case where microtubule inhibitors were used , colchicine was added to growing cells at a concentration of 30 μM for 2 hours prior to spread preparation . For all spreads , cells from 5 mL of culture were spun down , washed once in PBS , and then gradually resuspended in 10 mL 1% sodium citrate . The cells were incubated at room temperature for 30 minutes . We then added 1 mL of cold fixative ( 3:1 methanol: glacial acetic acid solution ) , spun down the cells , and washed three more times in 10 mL of the same fixative . Finally cells were resuspended in 100–500 μL fixative and dropped onto a glass slide under humidified conditions . The slide was allowed to dry and then washed in 70% , 90% and 100% ethanol successively , before being dried and imaged . For metaphase FISH , these slides were then denatured in 70% formamide/2X SSCT at 70°C for 90 seconds followed by washes in cold 70% , 90% and 100% ethanol . FISH probes were added and the cells were allowed to hybridize without any additional denaturing , followed by our standard FISH washes . When scoring sister chromatid separation in metaphase spreads ( without FISH ) , each spread was examined for the presence of single chromatids not attached to a sister along the entire chromosome arm . If unattached chromatids were visible , that metaphase was scored as having premature loss of cohesion , while if no unpaired chromatids were visible , it would be scored as having intact cohesion . When using FISH , the numbers of discrete FISH signals per metaphase were counted , as premature sister chromatid separation increases the number of FISH signals at pericentric loci from 1 to 2 . All images were obtained using an Olympus IX83 epifluorescence microscope with a 60x oil objective and the CellSens acquisition software . The raw TIFF files obtained were analyzed using custom-written MATLAB scripts ( first described in [64] and subsequently adapted ) for measuring different properties such as the number of FISH dots per nucleus , their area , and the intensity of IF signals . All uniquely identifiable foci of fluorescent signal ( above background ) were counted as FISH signals , regardless of the distance between them . The number of FISH signals and the area of FISH signals following cohesin knockdown was used as a measure of cohesion , defined as the close alignment of sister chromatids in interphase . When assaying the number of FISH signals in a nucleus , a whole population of cells was scored and each nucleus classified as either having one signal ( homolog pairing as well as sister chromatid cohesion intact ) or more than one signal ( homologs have become unpaired or sisters have lost cohesion ) . The relative numbers of cells having one signal or more than one signal were then compared between different conditions using a two-tailed Fisher’s Exact Test . This type of analysis was also used when examining nuclei with higher numbers of FISH signals ( i . e . nuclei were classified as having either up to four , or more than four , FISH signals per nucleus , etc . ) . When multiple trials of certain conditions were being compared , a two-tailed Student’s t-test was used to compare the percentages of nuclei with a single signal obtained under different conditions . A Student’s t-test was also used when comparing the distribution of FISH signal areas obtained when examining larger chromosomal regions . Finally , when examining the number of FISH signals in metaphase spreads , a Mann-Whitney U test was used to compare the different conditions .
|
As cells grow , they replicate their DNA to give rise to two copies of each chromosome , known as sister chromatids , which separate from each other once the cell divides . To ensure that sister chromatids end up in different daughter cells , they are kept together from DNA replication until mitosis via a connection known as cohesion . A protein complex known as cohesin is essential for this process . Our work in Drosophila cells suggests that factors other than cohesin also contribute to sister chromatid cohesion in interphase . Additionally , we observed that the alignment of sister chromatids is regulated by condensin II , a protein complex involved in the compaction of chromosomes prior to division as well as the regulation of inter-chromosomal associations . These findings highlight that , in addition to their important individual functions , cohesin and condensin II proteins may interact to organize chromosomes over the course of the cell cycle . Finally , building on prior observations that condensin II is involved in the regulation of somatic homolog pairing in Drosophila , our work suggests that the mechanisms underlying homolog pairing may also contribute to sister chromatid cohesion .
|
[
"Abstract",
"Introduction",
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"Methods"
] |
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2016
|
Investigating the Interplay between Sister Chromatid Cohesion and Homolog Pairing in Drosophila Nuclei
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Human cystic echinococcosis is a chronic , complex and neglected infection . Its clinical management has evolved over decades without adequate evaluation of efficacy . Recent expert opinion recommends that uncomplicated inactive cysts of the liver should be left untreated and solely monitored over time ( “watch-and-wait” approach ) . However , clinical data supporting this approach are still scant and published mostly as conference proceedings . In this study , we report our experience with long-term sonographic and serological follow-up of inactive cysts of the liver . From March 1994 to October 2013 , 38 patients with 47 liver cysts , diagnosed as inactive without any previous treatment history , were followed with ultrasound and serology at 6–12 months intervals for a period of at least 24 months ( median follow-up 51 . 95 months ) in our outpatient clinic . In 97 . 4% of patients , the cysts remained inactive over time and in only one case was reactivation of the cyst detected . No complications occurred during the time of monitoring . During follow-up , serology tests for CE were negative at diagnosis or became negative in 74 . 1% and were positive or became positive in 25 . 9% of cases . Patients with inactive cysts on ultrasound but positive serological tests were also investigated by CT scan ( chest and abdomen ) to rule out extra-hepatic cyst localization . This study confirms the importance of a stage-specific approach to the management of cystic echinococcosis and supports the use of a monitoring-only approach to inactive , uncomplicated cysts of the liver . It also confirms that serology plays only an ancillary role in the clinical management of these patients , compared to ultrasound and other imaging techniques . The implications of these findings for clinical management and natural history of cystic echinococcosis are discussed .
Cystic echinococcosis ( CE ) is a chronic , complex and neglected infection caused by Echinococcus granulosus , a cestode with a worldwide distribution affecting an estimated 1 . 2 million people , mainly in pastoral communities [1] , [2] , [3] . Its life cycle develops between the dog and other canids , which harbor the adult tapeworm in the intestine and shed parasite eggs in feces , and herbivores that are intermediate hosts . Humans are dead-end occasional intermediate hosts and acquire the infection through accidental ingestion of Echinococcus eggs . In humans , the larval stage of the tapeworm forms a cyst that is located in the liver in about 80% of cases but may occur in almost any organ [4] . Although often asymptomatic , this chronic infection accounts for an estimated 3 . 6 million DALYs ( Disability Adjusted Life Years ) lost globally every year [2] . Diagnosis and clinical management of hepatic CE currently rely on imaging techniques , especially ultrasound ( US ) [5] , and a number of sonographic classifications of CE have been proposed in the past 30 years [6] , [7] , [8] . The current classification , issued by the WHO-IWGE ( World Health Organization-Informal Working Group on Echinococcosis ) , allows the distinction into active ( CE1 and CE2 ) , transitional ( CE3 ) and inactive ( CE4 and CE5 ) cyst stages [8] ( figure 1 ) . This classification is supported by the different biological activity demonstrated in distinct cyst stages [9] , which in turn supports the clinical observation that different stages respond differently to non-surgical therapy [10] . Altogether , these support the concept of a stage-specific approach to treatment , at least for hepatic locations [4] , [10] . According to the stage-specific approach proposed by WHO-IWGE , uncomplicated cysts of the liver should be treated by non-surgical options ( percutaneous drainage and medical treatment with benzimidazoles ) , while surgery should be used when complications are present and in other selected circumstances [4] , [11] . Furthermore , recent expert opinion also recommends that inactive CE4-CE5 cysts that are asymptomatic and uncomplicated should be left untreated and solely monitored regularly by ultrasound , using the so-called “watch-and-wait” approach [4] , [11] , [12] . However , these different options have never been systematically evaluated and properly compared , at least in part due to the chronicity of the infection and its evolution , which would require years-long follow-up to be properly evaluated , a requirement that is extremely difficult to achieve . As a consequence , the “best” treatment for echinococcal cysts is still the subject of debate . The watch-and-wait approach for inactive hepatic CE cysts is increasingly used in selected cases in referral centers; however medical or surgical treatments are still commonly performed elsewhere for these cases . Long-term follow-up with ultrasound is required to assess the evolution of the CE4–CE5 cyst biological activity over time . Serological tests may be useful to confirm US diagnosis of CE , but they are not reliable for assessing cyst viability and often a positive serology induces clinicians unfamiliar with CE to treat inactive cysts unnecessarily , while antibody titers may persist for years even after complete surgical removal of the cyst [13] , [14] . Moreover , serological tests lack standardization and show variable diagnostic performance , which depends on many factors such as prevalence of infection , cross-reaction with other parasites , and stage , location , and size of the cysts [15] , thus making their results and implications for clinical management difficult to interpret . Although published studies based on ultrasound surveys support the use of watchful monitoring of asymptomatic inactive CE [16] , [17] , to date , no data on the safety and effectiveness of the watch-and-wait approach have been published from a clinical setting in clinically well-defined patients . To start filling this gap , we report our experience with long-term sonographic and serological monitoring of a well-defined group of patients with uncomplicated hepatic inactive cysts that were in the inactive stage at the time of first diagnosis .
The study protocol was approved by the ethical committee of San Matteo Hospital Foundation , Pavia , Italy , and all patients gave their written informed consent . Clinical records of patients who were diagnosed in our clinic with exclusively inactive echinococcal cysts ( i . e . cysts that reached the inactive stage spontaneously at the time of diagnosis ) of the liver until October 2013 were extracted from our electronic archive . Data ( demographic and contact details , characteristics of the cysts at diagnosis and during follow-up , serology , treatment , and development of any symptoms or complications ) have been routinely recorded for CE patients at each visit from March 1994 and were available for analysis . Our Centre has been the WHO collaborating Centre for the Clinical Management of Cystic Echinococcosis since 2009 . In the last 30 years , more than 690 patients with CE have been seen and clinically followed , both from Italy ( about 2/3 ) and other endemic countries ( about 1/3 ) , with 24 new diagnoses of CE in 2012 alone . Patients were selected among those who met the following inclusion criteria: ( i ) harboring exclusively uncomplicated inactive hepatic CE4 or CE5 cysts that were in the inactive stage at the time of first diagnosis , ( ii ) follow-up defined as abdominal ultrasound and serological tests performed every 6–12 months in our center , and ( iii ) minimum length of follow-up of 24 months in our center . Patients with cysts that became inactive over time , spontaneously or as a result of treatment , and/or with concomitant presence of active or transitional cysts in the liver or elsewhere , were excluded from the analysis . All patients were examined by an infectious disease clinician with long-standing experience in US and clinical management of CE ( EB ) using a commercially available US scanner with 3 . 5–5 MHz convex probes ( Hitachi 19 , Hitachi , Japan and Aloka ProSound ALPHA 10 , Tokyo , Japan ) . For each patient , number , stage , size and location of the cysts were recorded . Solid cysts were classified as CE4 or CE5 according to the WHO-IWGE standardized US classification for CE [8] ( Figure 1 ) . All patients were tested for anti-Echinococcus antibodies by commercial IgG Enzyme-Linked Immunosorbent Assay ( ELISA , Cypress Diagnostic , Langdorp , Belgium , marked CE ) in the parasitology laboratory of our hospital , according to manufacturer's instructions . Because cut-off values changed in 2003 , here we evaluated the serology results only of those patients diagnosed after this date . For each patient , demographic details , characteristics of the cysts at diagnosis and during follow-up , previous treatments , and development of any symptoms or complications were obtained . Sonographic and serological changes , if any , during the follow-up were also recorded . Median follow-up and inter-quartile range ( IQR ) were calculated only from the follow-up time performed by regular visits in our center . The visualization of daughter cyst development within the cyst , i . e . a stage shift from CE4 or CE5 to CE3b , was considered a reactivation . The McNemar's test was applied to analyze the difference in cyst stage at diagnosis and last follow-up visit for each patient . Quantitative serological results were summarized as negative ( constantly below cut-off for positivity ) , positive ( constantly above cut-off ) , negativization or positivization ( evolution from above to below cut-off values or vice versa , respectively , at least once during follow-up ) . Patients with inactive cysts but positive serological tests were investigated by CT scan ( chest and abdomen ) to rule out the presence of extra hepatic cysts that might have remained undiagnosed , which could explain serological positivity . Patients included in the study series were divided into three groups , as follows: i ) patients still in follow-up in our centre in October 2013 , ii ) patients no longer in regular follow-up but reached by telephone , and iii ) patients not reachable by telephone . Medians between groups were compared using the Kruskal-Wallis test and the Mann-Whitney U test . Percentages between groups were compared using the Chi-square tests . Where appropriate , the Bonferroni correction was applied to adjust for multiple comparisons . Statistical analysis was carried out in SPSS Statistics 17 . 0 ( IBM ) . A p-value≤0 . 05 was considered significant .
From March 1994 to October 2013 , 127 patients with exclusively inactive , uncomplicated liver cysts , which were already inactive at first diagnosis , were seen in our clinic . The demographic and clinical characteristics of the 38 patients included in the analysis are summarized in table 1 , while 89 did not meet the inclusion criteria ( table 2 ) . All patients were diagnosed with inactive cysts during sonographic scans performed to investigate symptoms compatible with , but ultimately unrelated to , CE ( abdominal pain , fever , increase of transaminases ) . The median follow-up period in our center was 51 . 95 months ( IQR 35 . 69–95 . 04 months ) ( table 1 ) . The distribution of follow-up length and present follow-up situation of patients included in the study series is shown in figure 2 . The 38 selected patients harbored a total of 47 hepatic cysts: 26 CE4 cysts and 21 CE5 cysts . Twenty nine patients had only one cyst , while 9 patients had two cysts ( table 1 ) . In 37 ( 97 . 4% ) patients , the cysts remained inactive throughout the observation period , and no change from CE4 to CE5 was recorded . In 1 patient a cyst reactivation was detected , from inactive CE4 to transitional CE3b , after 2 years of follow-up . This patient had never been treated and the reactivated CE3b cyst has remained stable to date ( 7 years after reactivation ) in the absence of treatment . The difference in cyst stage between diagnosis and last visit was not statistically significant . Twenty one ( 55 . 2% ) patients who were included in our study were not seen during follow-up for >12 months after the last control . To gain a more complete understanding of the follow-up outcome , and to assess the presence of systematic differences between patients still visited in our center and those lost to follow-up , these were re-contacted by telephone . Ten patients ( 47 . 6% - 7 Italians and 3 foreigners ) could not be reached at the telephone number provided at the time of the last visit , while 11 ( 52 . 4% ) could be interviewed , with no complications reported ( table 1 ) . Age , sex , median follow-up length , and CE4 or CE5 cyst stage distribution were not statistically different between patients groups , while patients lost to follow-up but reached by telephone had statistically higher numbers of cysts compared to the other two groups ( p = 0 . 03 for both comparisons ) . Eighty nine patients did not meet the inclusion criteria ( table 2 and figure 2 ) . To gain a more complete understanding of the follow-up outcome , we re-contacted by telephone the 61 patients who were not seen during follow-up for >12 months from their last visit . Thirty patients ( 15 Italians and 15 foreigners ) could not be reached at the telephone number provided at the time of the visit . The results of the interview of the remaining 31 patients who could be reached by telephone are shown in table 2 . Only one of these patients , currently followed in another hospital , reported to have suffered from complications , but it was not possible to clarify the nature and relation to CE cyst by telephone . Serology results ( table 1 ) were remarkably stable over time . ELISA was persistently negative in 19 patients ( 70 . 4% ) , positive in 6 ( 22 . 2% ) , while 2 ( 7 . 4% ) patients converted/reverted . Of note , the OD value of the patient showing CE4 to CE3b change was negative at the time of reactivation , and has remained so . These results were confirmed by a second serology test ( IHA , Cellognost Echinococcosis; Dade Behring , Newark , USA; data not shown ) . Patients with positive serology for CE did not harbor cysts in extra hepatic locations as shown by abdominal and thoracic CT scans .
Cystic echinococcosis is among the most neglected parasitic diseases , and development of new drugs and other treatment modalities for this infection receives very little attention [2] . In addition , CE is a complex disease due to the possible involvement of different organs and tissues , the presence of different cyst stages ranging from active to inactive , and its wide spectrum of clinical presentations ranging from asymptomatic to life-threatening complications such as anaphylactic shock and pulmonary embolism [4] . Moreover , CE infection and its evolution is chronic , further hampering its study , and would require many years follow-up , which is extremely difficult to achieve . As a consequence of both neglect , complexity , and chronicity of CE , clinical management procedures have evolved over decades without adequate evaluation of essential features such as efficacy , rate of adverse reactions , relapse frequency and cost . The advent of modern imaging techniques , in particular ultrasound , represented a breakthrough in the diagnosis , treatment and follow-up of patients with CE . As a consequence , clinicians have been striving for the past 30 years for an imaging-based classification of CE cysts to harmonize the interpretation of scientific studies and to guide clinical management of CE [6] , [7] , [8] . Concomitantly , progress was made to correlate individual stages of these classifications with the natural history of the cyst and involution processes accelerated by treatment , although controversy still exists on this subject [18] . Surgery , percutaneous interventions and chemotherapy with benzimidazoles are three available treatment options; however they have never been systematically evaluated and properly compared , at least in part due to the chronicity of CE infection , which would require many years- if not decades of regular follow-up , very difficult to achieve in a large number of patients . Despite this , the WHO-IWGE classification , which groups cysts into active , transitional and inactive , has made a rational , stage-specific approach possible [4] , [8] . Recently , experts have suggested that uncomplicated inactive cysts should be left untreated and simply monitored by ultrasound , a “watch-and-wait” approach alternative to treatment [4] , [11] . As illustrated by Junghanss et al . [19] , the idea of leaving uncomplicated , inactive cysts untreated and solely monitored over time follows the observation that a good proportion of cysts become spontaneously inactive without any treatment and such cysts are likely to remain stable over time . Although the watch-and-wait approach is being increasingly used in selected cases in referral centers , and published studies based on ultrasound surveys support the use of watchful monitoring of asymptomatic inactive CE , no data on the safety and effectiveness of this approach in well-defined patients in a clinical setting have been published . In almost all ( 97 . 4% ) patients with spontaneously inactive cysts followed in our center for at least two years over a period of 19 years , the cysts remained inactive . In only one patient were we able to detect reactivation of a single CE4 inactive cyst to a transitional CE3b type after a 2 year follow-up period . Equally important is the fact that no complications were recorded and the patients had no symptoms related to the presence of the cyst in the liver during their follow-up . Furthermore , although the administration of albendazole to eight patients for 1 to 6 months before being seen at our center excluded them from the study series , this treatment did not produce any noticeable change in the features of their already-inactive cysts . These results certainly support the watch-and-wait approach to spontaneously inactivated CE4–CE5 cysts , notwithstanding the limitations of our retrospective study . Loss to follow-up of CE patients ( 64 . 6% ) , a problem commonly faced by clinicians , is not limited to patients managed with watch-and-wait in our experience . The dynamic of loss to follow-up in our center seems bimodal , as shown in figure 2 , with most patients either never entering a follow-up after the first visit ( 54 . 9% of all patients lost to follow-up ) or interrupting the follow-up after a few years of regular visits . About half of patients included in our series who did not have a follow-up visit in the year or more before data cut-off could be reached by telephone , and , of these , half declared that they did not seek further medical advice because they were asymptomatic and they did not consider a control visit necessary , while the other half are routinely followed in other centers . The remaining patients could not be reached because of change of contact information , and this was found equally in Italians and non-Italians . These figures apply when considering either patients included in our case series , in those excluded , or both groups combined . All but one of patients reached by telephone were declared to be asymptomatic and those followed elsewhere have their cysts unchanged . Although the information collected by telephone interview is limited , we focused on three conditions ( whether follow-up was performed elsewhere; reasons for absence to follow-up; and , patient's health status as far as CE-related symptoms were concerned ) which we believed could be reasonably assessed without a first-hand visit . If limited to those people included in our study series , it is possible to speculate that the same absence of complications applies to the subgroup not reachable by telephone , considering the homogeneity of baseline conditions with those patients still in follow-up or reached by telephone . Conversely , the fate of those patients lost to follow-up very shortly after the first visit cannot be extrapolated . Clearly , an improvement in the doctor-patient relationship and a better explanation of the necessity of regular follow-up of even inactive and asymptomatic CE cysts are needed . Indeed , the only cyst reactivation we observed was detected after 2 years of follow-up , highlighting the importance of a long-term follow-up of these patients , to detect promptly any reactivation and complication . Altogether , these results , with all the limitations of a retrospective , single center based data set , provide initial support , for the first time in a clinical setting , for the simple sonographic monitoring of uncomplicated inactive CE4 and CE5 cysts of the liver that reach the inactive stage spontaneously . This particular distinction is important because the rate of reactivation of inactive cysts which became inactive as the result of therapy may instead be variable depending on the pre-treatment cyst stage , and the clinical management and follow-up of these “induced” inactive cysts is consequently different [20] . Importantly , our data highlight the need for a long-term follow-up of patients with inactive cysts , and for better patient education and patient recall system , to minimize the loss to follow-up and its possible consequences . Our data confirm the marginal usefulness of serology in the follow-up of patients with CE cysts [15] . ELISA test was positive in 6 patients , and in 1 of these patients the test became positive over time without US evidence of reactivation , while the only case of reactivation had a persistently negative serology . These results were not due to the presence of cysts in extra-hepatic locations , as ruled out by abdominal and thoracic CT scans . This behavior is well known to clinicians caring for patients with CE , as serological tests may remain positive for years even after complete surgical removal , and do not imply the presence of active ( re ) infection [13] , [21] . It is possible that temporary release of antigens from breaches in cyst integrity boosts antibody production in these cases . Acknowledging that serology has only a complementary role and cannot be used alone to guide the clinical management of CE has important consequences in terms of avoiding unnecessary treatment and reducing the patient's ( and physician's ) anxiety . Clinicians with little experience with this disease are often led to believe that positive serology automatically implies active disease even if cysts are nowhere to be found and this often translates into unnecessary and long-term administration of albendazole , with attendant side effects and cost . To the best of our knowledge , this is the first time that long-term ( median 5 years over a 19 years period ) monitoring of inactive cysts of patients on a clinical rather than epidemiological basis has been reported , contributing to the debate on the best treatment for CE using a stage-specific approach . Moreover , our results shed further light on the natural history of CE and the relationship between cyst stage and antibody responses in a large cohort of patients where cysts reached the inactive stage spontaneously . Although large prospective and multi-centric studies will be needed to provide definitive recommendations for the clinical management of this patient category , our data from a relatively small series of well-defined patients with spontaneously inactivated asymptomatic cysts of the liver support the WHO-IWGE indications for these cases . These patients can be managed expectantly in the majority of cases , provided they can be monitored by regular US follow-up , without administering unnecessary drugs and incurring avoidable costs .
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Human cystic echinococcosis ( CE ) is a chronic , complex and neglected parasitic infection presenting mostly as hepatic cysts , which are staged by ultrasound . Recent expert opinion recommends that uncomplicated inactive cysts should be left untreated and solely monitored over time , using the so-called “watch-and-wait” approach . Currently , no reliable biological marker of cyst activity is available . Positive antibody titers may persist for years even after removal of a cyst; therefore a long-term follow-up is required to assess the evolution of the cyst's biological activity over time . The watch-and-wait approach to inactive hepatic CE cysts is increasingly used in selected cases in referral centers; however , no data on its safety and effectiveness has yet been published . We retrospectively studied 47 inactive uncomplicated cysts at diagnosis , managed by a watch-and-wait approach , with a median follow-up of 51 . 95 months . We observed that these cysts remained inactive over time in almost all cases , without any complications . These results support the watch-and-wait approach to these cysts . Furthermore , we confirmed that serology only plays an ancillary role in the clinical management of these patients , compared to ultrasound and other imaging techniques .
|
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"Abstract",
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"Methods",
"Results",
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"diseases",
"medicine",
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"health",
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2014
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Long-term Sonographic and Serological Follow-up of Inactive Echinococcal Cysts of the Liver: Hints for a “Watch-and-Wait” Approach
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Ty elements are high copy number , dispersed repeated sequences in the Saccharomyces cerevisiae genome known to mediate gross chromosomal rearrangements ( GCRs ) . Here we found that introduction of Ty912 , a previously identified Ty1 element , onto the non-essential terminal region of the left arm of chromosome V led to a 380-fold increase in the rate of accumulating GCRs in a wild-type strain . A survey of 48 different mutations identified those that either increased or decreased the rate of Ty-mediated GCRs and demonstrated that suppression of Ty-mediated GCRs differs from that of both low copy repeat sequence- and single copy sequence-mediated GCRs . The majority of the Ty912-mediated GCRs observed were monocentric nonreciprocal translocations mediated by RAD52-dependent homologous recombination ( HR ) between Ty912 and a Ty element on another chromosome arm . The remaining Ty912-mediated GCRs appeared to involve Ty912-mediated formation of unstable dicentric translocation chromosomes that were resolved by one or more Ty-mediated breakage-fusion-bridge cycles . Overall , the results demonstrate that the Ty912-mediated GCR assay is an excellent model for understanding mechanisms and pathways that suppress genome rearrangements mediated by high copy number repeat sequences , as well as the mechanisms by which such rearrangements occur .
Gross chromosomal rearrangements ( GCRs ) are associated with many different diseases . Disease-causing GCRs include translocations , deletions , and inversions that can inactivate genes , form chimeric genes encoding proteins with altered activity , or change gene copy numbers or gene expression . The human genome contains many highly duplicated elements , such as Alu and LINE elements , which collectively comprise nearly 40–50% of the human genome [1]–[3] . Non-allelic homologous recombination ( HR ) between repeated sequences can mediate rearrangements leading to segmental duplications [4] , numerous human genetic diseases [5] including certain sex disorders thought to be due to HR between palindromic regions on the Y chromosome [6] , and many of the GCRs present in adult solid tumors [7] . Despite the importance of suppressing non-allelic recombination between highly duplicated repeats to maintain genome stability , little is known about the genetic factors that suppress these types of rearrangements . Studies in the yeast Saccharomyces cerevisiae have contributed greatly to our general understanding of the suppression and formation of GCRs mediated by both single-copy sequence and , more recently , low copy number segmental duplications [8]–[11] . These studies , however , have not generally addressed the roles of highly repeated genomic elements . The Ty1 family of retrotransposons is the most common class of retrotransposons in S . cerevisiae [12] . A full length Ty1 element is ∼5 . 9 kb long and consists of ∼5 . 2 kb of unique sequence ( known as the epsilon sequence ) flanked by one copy of a ∼332 bp Long Terminal Repeat ( LTR ) sequence ( also known as a delta sequence ) at each end . The LTR sequences are both oriented in the same direction and homologous recombination between them results in the deletion of the internal Ty1 epsilon sequence and one copy of the delta sequences , giving rise to a “solo delta” element [13] . The reference S288c S . cerevisiae genome sequence contains at least 32 full length Ty1s and at least 217 solo delta sequences , comprising at least 2 . 1% of the genome [12] . Because Ty1-related sequences are the most repetitive components of the S . cerevisiae genome , they are the best S . cerevisiae analog to the highly repetitive human Alu sequences , which are smaller than Ty elements , and LINE sequences , which are similar in size to Ty elements . Like highly repetitive human elements , Ty1s appear to mediate many types of chromosomal rearrangements , including inversions , deletions , and both reciprocal and non-reciprocal translocations [14]–[18] . Such events are believed to result from the repair of DNA double strand breaks ( DSBs ) at or near Ty1 sequences and indeed induction of such DSBs through fragile sites , unstable inverted repeats , ionizing radiation and formation of unstable dicentric chromosomes stimulates Ty-mediated GCRs [18]–[27] . A number of mechanisms have been proposed to account for these Ty-mediated GCRs , including Break Induced Replication ( BIR ) between a Ty element on a broken chromosome and a Ty element at another site on either a broken or intact chromosome , and crossing over between two Ty elements potentially mediated by single strand annealing ( SSA ) and other HR mechanisms [17] , [22] , [25] , [27]–[30] . Ty1 sequences are also a target of GCR-causing rearrangements involving non-repetitive sequences [31] . Because GCRs mediated by highly repetitive genome sequences underlie a number of human diseases and because there is currently a dearth of information about which pathways prevent such GCRs , we developed a quantitative genetic assay that measures the rate of Ty1-mediated GCRs . Our results demonstrate that repetitive sequences greatly contribute to genomic instability and we identify genes and pathways that suppress and promote these Ty1-mediated GCRs . In addition , we characterized 88 Ty1-mediated GCRs at varying levels of detail and demonstrated that the most common Ty1-mediated GCRs appear to involve non-reciprocal HR between ectopic Ty sequences that often results in the duplication of stretches of sequences bounded by a target Ty element at one end and a telomere at the other end . In a small number of cases , we observed complex rearrangements consistent with multiple exchanges between target sequences , as well as rearrangements consistent with the formation and resolution of dicentric chromosomes initially formed by HR between Ty elements .
To identify how Ty elements influence GCRs , we placed Ty912 , a Ty1 retrotransposon originally isolated during a screen for spontaneous histidine auxotrophic mutants [32] , in a nonessential region of the left arm of chromosome V between the NPR2 and CIN8 genes ( Figure 1a ) . This site is between the most telomeric essential gene on the left arm of chromosome V ( PCM1 ) and two counter-selectable genes ( CAN1 and hxt13::URA3 ) used in the original GCR assay [9] . We chose this integration site for the Ty912 because it allows direct analysis of the effect of a Ty element on GCRs mediated by a well characterized single copy sequence GCR breakpoint region . We determined the rate of accumulating GCRs by measuring the rate of simultaneous loss of CAN1 and URA3 by fluctuation analysis . The presence of Ty912 on chromosome V ( hereafter referred to as +Ty912 ) in a wild-type strain resulted in a 380-fold increase in the rate of accumulating Canr 5FOAr progeny compared to an isogenic wild-type strain without the Ty912 insertion ( hereafter referred to as −Ty ) ( Table 1 ) . As will be demonstrated below , the Canr 5FOAr progeny that accumulated in the +Ty912 strain were the result of Ty1-mediated translocations . We next surveyed a series of mutations for their effects on GCR rates in both the −Ty and +Ty912 strain backgrounds ( Table 1; Table S1 ) . The selected mutations affected many pathways , including HR , DNA replication , checkpoints , Ty transposition , mismatch repair , post replication repair , chromatin structure and assembly , transcription , accumulation of oxidative DNA damage , and telomere synthesis . To simplify the analysis of the mutations in this survey , we divided the mutations into three classes , Class I , II , and III , that caused +Ty912 GCR rates that were higher than , the same as , or lower than the wild-type +Ty912 GCR rate , respectively . Each class was then divided into two subclasses , A and B , depending on whether or not the −Ty GCR rate was greater than , or the same or lower than , the wild-type −Ty GCR rate . Class IA mutations increased the GCR rate in both assays and comprised the largest proportion of the mutations tested ( 20 of 48; 42% ) . Of these , 4 caused a similar fold increase in both the −Ty and +Ty912 rates , 13 caused a greater fold increase in the −Ty rate , and 3 ( sgs1Δ , mms1Δ , and tsa1Δ ) caused a greater fold increase in the +Ty912 rate . Both sgs1Δ and tsa1Δ were previously identified as mutations that significantly increased the GCR rate in the segmental duplication-mediated GCR assay relative to assays that detected single copy sequence-mediated GCRs ( Table S1 ) [11] , [33] . There were a smaller number of Class IB mutations that increased the +Ty912 GCR rate and had no effect on the −Ty GCR rate . Mutations in many of the Class IB genes , including SRS2 , RRM3 , MRC1 , MSH2 MLH1 and RTT109 increased GCRs mediated by segmental duplications ( Table S1 ) [11] , which suggests that the Class IB genes play general roles in suppressing various aspects of non-allelic HR . In addition , this class of mutations also included csm3Δ and rtt107Δ , which have not been tested in the segmental duplication assay . Intriguingly , RTT107/ESC4 and RTT109 are both genes that affect the rate of Ty transposition [34] , modulate chromatin structure [35] , [36] , and play roles in processing stalled replication forks [37] . Three Class IIA mutations ( rad9Δ and rad59Δ single mutations , and the rad51Δ rad59Δ double mutation ) did not significantly increase the +Ty912 GCR rate but did increase the −Ty GCR rate . In contrast , there were 8 Class IIB mutations that caused little to no effect in either GCR assay . These Class IIB mutations represented individual deletions of a number of genes , including SPT2 , SPT4 , SPT8 , RTT102 , and SIR4 , involved in suppressing Ty1 transposition and/or transcription [34] , [38]–[40] . The Class IIIA mutations that decreased the +Ty912 GCR rate and increased the −Ty GCR rate were restricted to a small number of mutations in mutant backgrounds containing a deletion of RAD52 ( rad52Δ , rad52Δ rad51Δ , rad52Δ rad59Δ , and rad52Δ rad51Δ rad59Δ ) . There were also 3 Class IIIB mutations that did not appear to affect the −Ty GCR rate , but did decrease the +Ty912 GCR rate . Each of these mutations have been previously identified as affecting Ty1 biology; deletions of PMR1 and RTT103 alter the rate of Ty1 transposition [34] , [41] and deletion of GAL11 affects Ty1 transcription [42] . Mutations affecting genes encoding core HR proteins belonged to several different mutation classes ( IA , IIA , and IIIA ) , indicating a range of effects on the +Ty912 GCR assay . Deletion of RAD52 , which eliminates most if not all HR in S . cerevisiae [43] , suppressed the +Ty912 GCR rate ( Table 1 ) to a level not significantly different from that caused by a RAD52 deletion in the −Ty background ( unpaired Wilcoxon rank sum test; p = 0 . 067 ) . This suggested that Ty1 sequence-specific GCRs are RAD52-dependent . RAD52 is involved in two HR subpathways mediated by RAD51 and RAD59 . In contrast to a deletion of RAD52 , the rad51Δ mutation increased the GCR rate in the +Ty912 GCR assay by 7-fold ( unpaired Wilcoxon rank sum test; p = 4 . 89×10−7 ) , suggesting RAD51-dependent repair events normally suppress Ty1-mediated GCRs . This is somewhat consistent with a previous report , which found that deletion of RAD51 caused an increase in the rate of deletions mediated by direct repeat recombination between Ty1 LTRs but caused a decrease in recombination of Ty1s resulting in conversion events [44] . In contrast , deletion of RAD59 alone had no significant effect on the GCR rate in the +Ty912 GCR assay ( unpaired Wilcoxon rank sum test; p = 0 . 34 ) . However , deletion of RAD59 suppressed the increased GCR rate of a rad51Δ mutant and led to a GCR rate that was not statistically different from that of a wild-type strain ( unpaired Wilcoxon rank sum test; p = 0 . 89 ) ; this suggests that RAD59 is responsible for mediating the formation of many of the GCRs that occur in a rad51Δ mutant , consistent with previous reports of RAD59-dependent , RAD51-independent recombination events [28] , [45]–[48] . Furthermore , the GCR rate of the rad51Δ rad59Δ double mutant in the +Ty912 GCR assay was significantly higher than the GCR rate caused by a rad52Δ mutation in the +Ty912 GCR assay ( unpaired Wilcoxon rank sum test; p = 5 . 59×10−4 ) . This is consistent with the existence of an inefficient RAD52-dependent , RAD51- and RAD59-independent HR pathway [11] , [46]; accordingly , the rad52Δ rad51Δ , rad52Δ rad59Δ , and rad52Δ rad51Δ rad59Δ double and triple mutants had GCR rates in the +Ty912 GCR assay that were not statistically different than the GCR rate seen in a rad52Δ mutant with the +Ty912 GCR assay ( unpaired Wilcoxon rank sum tests; p = 0 . 21 , 0 . 10 , 0 . 95 , respectively ) . Among the mutations selected for testing were a number originally isolated as altering either transcription [38] , [39] , [42] or transposition [34] of Ty1 elements , many of which had not previously been tested for their effects on GCR rates . Mutations affecting the transcription of Ty1 elements had no ( spt2Δ , spt4Δ , and spt8Δ ) , suppressive ( gal11Δ ) , or stimulating ( spt21Δ ) effects on the +Ty912 GCR rate . Of the mutations affecting Ty1 transcription , only spt21Δ significantly increased the GCR rate in the −Ty assay; it was not possible to determine if the gal11Δ mutant had reduced GCR rates in the −Ty assay because the −Ty GCR rate of this mutant was too low to measure . Mutations known to affect the transposition of Ty1 elements also had variable effects on the +Ty912 GCR rate , with some mutations causing no change ( rtt102Δ and rtt106Δ ) , an increased rate ( rtt101Δ , rrm3Δ , rtt105Δ , rtt107Δ , rtt109Δ , and elg1Δ ) , or a decreased rate ( rtt103Δ and pmr1Δ ) . Half of the mutations causing increased +Ty912 GCR rates ( rtt101Δ , rtt105Δ , and elg1Δ ) , also increased the GCR rate in the −Ty assay; rrm3Δ and rtt109Δ are also known to increase the rate of GCRs mediated by segmental duplications ( Table S1 ) [11] . It was not possible to determine if the rtt103Δ and pmr1Δ mutants had reduced GCR rates in the −Ty assay because the −Ty GCR rate of these mutants were too low to measure . Thus , many of the mutations that affect both the +Ty912 GCR rate and either Ty1 transcription or transposition that could be evaluated in the −Ty GCR assay also similarly affect non-Ty1 mediated genome rearrangements . Taken together , these data are consistent with a view in which Ty-mediated genome instability is generally independent of mechanisms of Ty propagation and Ty-mediated gene silencing and suggest results from the +Ty912 assay will be broadly applicable to the study of genome instability mediated by highly repetitive sequences . To understand how Ty912 increases GCR rates , we first used array Comparative Genomic Hybridization ( aCGH ) to analyze 7 independent GCR-containing strains isolated from the wild-type −Ty strain ( I1–I7; Table S2 ) . All 7 GCR-containing strains had terminal deletions of the left arm of chromosome V starting at positions between the PCM1 and CAN1 genes and extending to the left telomere TEL05L ( Figure S1a ) . These strains contained no additional copy number changes of other chromosomal regions . The aCGH results were consistent with the smaller chromosome Vs identified by a combination of pulse-field gel electrophoresis ( PFGE ) followed by Southern blot analysis using a probe to MCM3 , an essential gene on the left arm of chromosome V ( Figure S1b ) . The data suggest that GCRs from all 7 isolates from the −Ty background were formed by breakage of the left arm of chromosome V followed by healing of the chromosome end by de novo telomere addition , similar to GCRs formed in other wild-type strains lacking repetitive elements in their breakpoint regions [9] , [49] . We then performed aCGH analysis on 10 GCR-containing strains isolated from the wild-type +Ty912 strain , and 78 GCR-containing strains isolated from 11 different mutant +Ty912 strains ( I8–I94 , Table S2 ) . Unlike the wild-type −Ty GCR-containing strains , only 5 of 88 GCR-containing strains isolated from the +Ty912 GCR assay had aCGH patterns consistent with terminal deletions associated with de novo telomere additions ( Class I GCRs; Table 2; Figure S2a–g ) . Two of these events also contained putative copy number changes of small internal regions on the terminally deleted chromosome V with no duplications or deletions on other chromosomes . Strikingly , the majority ( 83 of 88 ) of GCR-containing strains isolated using the +Ty912 GCR assay and analyzed by aCGH had a deletion from Ty912 to TEL05L ( Ty912-TEL05L deletion ) and had one or more duplicated regions that were bounded at least on one side by a full-length Ty1 or a solo Ty1 or Ty2 delta element in the reference genome . None of these duplicated regions spanned centromeres . In addition , 5 of the 83 cases ( 4 occurring in the rtt109Δ mutant and 1 occurring in the rad53Δ sml1Δ mutant ) appeared to also be disomic for at least one chromosome ( I53 , I55 , I56 , I58 , and I67; Table S2 ) . Based on the aCGH analysis of these 83 isolates , we observed four additional classes of rearrangements ( Class II to V GCRs ) containing the chromosome V Ty912-TEL05L deletion and additional copy number changes bounded by Ty-related sequences that are described below . The 53 Class II GCR-containing strains ( 60 . 2% of the total surveyed ) contained both the chromosome V Ty912-TEL05L deletion ( Figure 1b ) and a single duplicated region of another chromosome arm extending from a Ty1 element or solo Ty1 delta element to a telomere . In this class , the Ty1 elements were transcriptionally oriented towards the telomere and away from the centromere ( Figure 1c; Table 2 ) ; this is the same orientation as the Ty912 element . In spite of the fact that 121 full-length Ty1 , solo Ty1 delta , and solo Ty2 delta elements are oriented appropriately to generate Class II GCRs , only 16 such elements in the S288c genome reference sequence were involved as targets in the observed Class II rearrangements as determined by the aCGH data , suggesting the distribution of Ty elements mediating the rearrangements is non-random ( Figure 1d ) . Several lines of evidence support the idea that a non-reciprocal HR-mediated process , such as BIR or half-crossovers [29] , [43] , [50]–[55] , occurred between Ty912 and the Ty target to generate the observed products . First , the orientations of the Ty1 sequences at the boundaries of the duplications relative to the duplicated regions are consistent with a homology-driven translocation process . Second , PFGE and Southern blotting with a probe to MCM3 revealed that the seven analyzed GCR-containing strains in this class ( I8 , I10 , I11 , I13 , I15 , I16 , and I17 ) had a single abnormally-sized chromosome V that was consistent with loss of 36 kb from the left arm of chromosome V ( from the Ty912-TEL05L deletion ) and gain of sequence equal to the length of the duplicated region from the target chromosome ( Figure 2a; Table 3 ) . Third , the predicted junctions from these seven isolates could be amplified by PCR using primers in unique sequences flanking the Ty-mediated junction or verified by cloning the junction and sequencing of the resulting plasmid; the sequences of these amplified junction had SNPs in the 5′ ends of the junctions that generally corresponded to the Ty912 sequence from chromosome V and had SNPs in the 3′ ends of the junctions that generally corresponded to the target Ty1 sequences ( Figure 2b; Table 4 ) . Fourth , the pattern of SNPs observed across the Ty fusion junction indicated that breakpoints occurred throughout the region of homology between Ty912 and the target Ty sequences and were not restricted to terminal delta elements . Although all of the 7 Class II GCR fusion junctions that were amplified and analyzed featured a pattern of 5′ SNPs consistent with Ty912 sequence and a pattern of 3′ SNPs consistent with the target Ty1 sequence bordering the duplication , the fusion junctions from I10 , I13 , I16 , and I17 contained other notable features ( Figure 2b ) . The junction sequence from isolate I10 featured an almost continuous block of SNPs at the 3′ end of its epsilon sequence that could not be attributed to the Ty912 or to an unannotated solo delta near YCRWdelta10 that bordered the duplicated region . However , this sequence region had 100% sequence identity to other Ty1s elsewhere in the genome ( YHRCTy1-1 , YMLWTy1-1 , YPRWTy1-3 , and YDRWTy1-4 ) . This SNP pattern was consistent with a tripartite fusion in which Ty912 first recombined with one of the 4 ectopic Ty1 elements ( YHRCTy1-1 , YMLWTy1-1 , YPRWTy1-3 , or YDRWTy1-4 ) followed by a second recombination event between the 3′ delta sequence of the target Ty1 and the unannotated delta sequence next to YCRWdelta10 on chromosome III . In contrast , the amplified junction regions from I13 , I16 , and I17 were approximately twice the size of a full-length Ty1 element , and sequencing of the regions with primers internal to Ty1 elements revealed heterozygous SNPs consistent with the fusion junction containing more than one Ty element . In the case of I17 , the chromosome X target consisted of two tandem Ty1s ( YJRWTy1-1 and YJRWTy1-2 ) . The size of the amplified region and the fact that the observed SNPs included Ty912 SNPs , YJRWTy1-1 SNPs , and a mixture of homozygous and heterozygous SNPs from YJRWTy1-1 and YJRWTy1-2 , is consistent with a Ty912 fusion to YJRWTy1-1 resulting in a junction containing two Ty1 elements . The features of I13 and I16 suggest a similar rearrangement structure as I17; however , because the sequences at the target junctions were annotated in the reference sequence as solo deltas ( an unannotated delta near YCRWdelta10 and YCRWdelta10 itself ) , we lacked sufficient sequence information to perform full SNP analyses of the multiple Ty1 elements found in the fusion junctions . The 11 Class III GCR-containing strains ( 12 . 5% ) resembled the more common Class II GCRs , except that the duplicated region on the target chromosomes were bounded by Ty sequences that the reference genome suggested were transcriptionally oriented towards the centromere rather than towards the telomere ( Table 2 ) . In each of these 11 cases , homology-driven rearrangements between the telomere-oriented Ty912 and the centromere-oriented target would be expected to duplicate a region on the centromeric side of the target Ty element in contrast to duplication on the telomeric side , as was observed in all 11 cases . Such events have been previously observed [17] , [30] , but their structure has not been investigated in detail . Eight of the 133 centromere-oriented Ty sequences present in the reference sequence bordered regions that were duplicated in the 11 Class III GCR-containing strains ( Figure 1d ) . To understand the nature of this unexpected class of GCRs , we first examined 6 of these 8 native Ty loci; the remaining 2 loci were located in the repetitive regions of chromosome XII and could not be definitively analyzed . Southern analyses of the six target Ty loci in the wild-type parental strain ( RDKY6076 ) revealed that only YMLWTy1-1 ( targeted in isolate I9 ) had increased size compared to the reference sequence ( Table 5 ) . The change in size of the YMLWTy1-1 locus was consistent with the presence of an additional full-length Ty1 element and subsequent analysis showed that our strains contained 2 tandem Ty1s ( termed YMLWTy1-1A and YMLWTy1-1B below ) at the YMLWTy1-1 locus that were oriented towards the centromere . We chose two isolates of this class ( I9 and I14 ) to analyze further . Both isolates had a single abnormally-sized chromosome V consistent with fusion of Ty912 to the duplicated region ( Figure 2a; Table 3 ) . Details of the structure of each isolate are described below . Isolate I9 , derived from a wild-type strain , contained a GCR associated with the chromosome V Ty912-TEL05L deletion ( Figure 3a ) and a 184 kb chromosome XIII duplication from TEL13L to the tandem centromere-oriented Ty1s , YMLWTy1-1A and YMLWTy1-1B ( Figure 3b ) ; no other region of the genome was observed to be duplicated . To confirm that chromosome V was indeed fused to a copy of the left arm of chromosome XIII , we cloned the fusion junction by: 1 ) integrating plasmid pRDK1564 into the region adjacent to the junction on chromosome V , 2 ) isolating genomic DNA , 3 ) cutting the genomic DNA with the restriction enzyme Xba I that cut once within the plasmid but not within Ty-related sequences , 4 ) circularizing the resulting fragments , and 5 ) recovering the plasmid by transformation into E . coli ( Figure 3c ) . Partial sequencing of the cloned junction confirmed that the I9 GCR contained the duplicated region of chromosome XIII at the YMLWTy1-1A/B locus fused to chromosome V at the Ty912 locus . This analysis also verified the orientations of YMLWTy1-1A/B and Ty912 . Restriction mapping of the recovered plasmid indicated that the cloned Ty fusion junction was unexpectedly large ( ∼25 kb ) and consistent with the size of approximately four Ty1 elements . Sequencing of the junction with internal Ty1-specific primers resulted in a highly heterozygous sequencing read consistent with the simultaneous sequencing of 2 or more unique Ty1 sequences ( Figure 3d ) . The large size of the junction , combined with the sequencing data and the fact that only chromosome XIII sequences were observed to be duplicated , suggests that the extra Ty1 sequences in the fusion junction arose as a result of a complex rearrangement mechanism , such as a breakage-fusion-bridge event driven by the formation of an initial dicentric chromosome that amplified the Ty1 sequences present on the 2 partner chromosomes ( Figure 3e ) . Ty-mediated resolution of dicentric translocation chromosomes have been previously observed during both an analysis of the structure of dicentric GCRs [25] and an analysis of GCRs derived from endogenous inverted Ty1 repeats [27] . We also investigated isolate I14 , which contained both the chromosome V Ty912-TEL05L deletion and a 145 kb duplication of the right arm of chromosome V between YERCdelta14 and TEL05R ( Figure 4a , 4b ) . Based on the aCGH data , we originally predicted that Ty912 had fused to YERCdelta14 . However , after cloning and sequencing the fusion junction containing Ty912 , we found that Ty912 underwent a HR-mediated fusion with YERCTy1-1 , a centromere-oriented Ty1 located approximately 17 . 5 kb telomeric to YERCdelta14 ( Figure 4c ) . The size of the cloned junction was consistent with a single Ty1 element fused to the unique chromosome V sequence downstream of YERCTy1-1 . This cloned Ty912/YERCTy1-1 fusion indicated the initial rearrangement could have resulted in either a dicentric chromosome if two copies of chromosome V were involved ( Figure 4d ) or a ring chromosome if only one copy of chromosome V was involved . The data strongly suggest that I14 initially formed a dicentric chromosome that later rearranged rather than a ring chromosome because ( 1 ) chromosome V from I14 was not trapped in a well during PFGE ( Figure 2a ) , ( 2 ) the region telomeric to YERCTy1-1 was duplicated , ( 3 ) the region centromeric to YERCdelta14 was not duplicated , and ( 4 ) dicentric chromosomes , but not ring chromosomes , are known to be unstable [25] . The aCGH data are consistent with the initial dicentric chromosome breaking at or near the centromere-oriented delta sequence YERCdelta14 allowing the chromosome end to then invade the telomere-oriented YERWdelta17 or an unannotated telomere-oriented delta we call YERWdelta20B ( ChrV: 449316-449625; Figure 4c ) and copy to the telomere , possibly by BIR ( Figure 4d ) . Regardless of the final fusion event , it is clear that the GCR present in isolate I14 , like the GCR present in isolate I9 , was the product of multiple rearrangements . The 14 Class IV GCR-containing strains each had both the chromosome V Ty912-TEL05L deletion and a single duplicated region of another chromosome extending from a telomere to a region of DNA containing a cluster of Ty-related elements in both telomeric and centromeric orientations ( Figure 1d; Table 2; Figure S3a–S3c ) . No other duplicated or deleted regions were identified . Based on the hypothesis that these rearrangements arose by the same mechanisms that gave rise to Class II and III GCRs , we successfully amplified fusion junctions for isolates I23 , I65 , I76 , I58 , and I48 , indicating the telomere-oriented Ty1 loci YLRWTy1-2 , YLRWTy1-2 , YLRWTy1-2 , YHLCdelta1 , and YGRWTy1-1 mediated the respective fusion junctions ( Figure S3d ) and that these 5 GCRs were all Class II GCRs . Since Class IV rearrangements were unlikely to be mechanistically distinct from Class II and III GCRs and since Class IV GCRs had similar aCGH patterns to those analyzed above , we did not further analyze other GCRs of this class .
In the present study , we describe the development of a quantitative genetic assay that allows for the assessment of the impact of genetic defects on the rate of Ty1-mediated GCRs and facilitates analyses of the structures of the resulting Ty1-mediated GCRs . The results described here demonstrate that presence of a telomere-oriented Ty912 on a nonessential terminal arm of chromosome V greatly increases the spontaneous rate of loss of that chromosome arm . Furthermore , this loss appears to be driven primarily by non-reciprocal translocations between Ty912 and other Ty-related elements in the genome , resulting in a broken chromosome V joined to a fragment of another chromosome that terminates with a telomere . The observed rearrangement products are consistent with HR-mediated processes , such as BIR and half crossovers [29] , [43] , [50]–[55] , which result in translocation breakpoints occurring at regions of homology mediated by RAD52-dependent HR . The majority of the Ty1-mediated GCRs observed ( ∼60 . 2% ) were simple non-reciprocal translocations likely mediated by HR between the telomere-oriented Ty912 on chromosome V and a single telomere-oriented Ty elements located on another chromosome arm . These results are consistent with a simple model in which a resection of a spontaneous DSB on chromosome V exposes single stranded Ty912 DNA that then invades a telomere oriented Ty element on another chromosome arm and leads to the replication of DNA from this Ty element to the telomere by BIR [17] , [22] , [24] , [25] , [28] , [56] . The results are also consistent with another model in which spontaneous DSBs form on both chromosome V and another target chromosome during the G2 phase of the cell cycle . These DSBs are followed by HR between Ty912 on chromosome V and a Ty element on the broken target chromosome . Mitosis then occurs , and the cell containing the remaining intact copy of chromosome V is selected against in the assay selection system; such HR events could be mediated by SSA as well as other HR mechanisms [27] , [29] , [30] , [55] , [57] . Other GCRs identified , such as those that involved the duplication of telomeric regions adjacent to centromere-oriented Ty elements or those that involved the duplication of multiple chromosomal regions , appear to be the products of more complicated mechanisms , ranging from the formation and resolution of unstable dicentric translocation chromosomes [25] , [27] to sequential linked monocentric translocations consistent with template switching during BIR [58] , [59] . In all of the events observed , it is possible that the initiating DSBs occurred at the site of participating Ty elements . However , it is more likely that the initiating DSBs occurred randomly and were resected to the participating Ty elements; the selection of Ty-mediated GCR events was due to the fact that the rates of HR mediated GCRs are much higher than those of single copy sequence mediated GCRs ( Table 1; [11] ) . Surprisingly , most of the genetic defects that increased the rate of Ty912-mediated GCRs did not appear to significantly alter the types of GCRs recovered ( Table S2 ) in spite of the fact that Ty elements targeted in rearrangements had an apparently nonrandom distribution ( Figure 1d ) . This observation raises the possibility that Ty-mediated repair of DNA damage may be biased to target specific locations or Ty elements in the genome . However , because our data were pooled from the results of analyses of GCRs isolated in multiple mutant backgrounds , and because we currently lack a rapid , cost efficient method to identify very large numbers of chromosome arm duplications , we were unable to determine whether this result was due to the analysis of a biased set of GCRs or was a manifestation of true repair target bias . To gain insights into whether the pathways affecting Ty1-mediated GCRs were similar to those affecting other types of GCRs , we surveyed mutations previously demonstrated to affect GCR rates as well as mutations known to affect Ty metabolism . Most of the mutations that increased rates of single copy sequence-mediated GCRs also increased GCR rates in the +Ty912 GCR assay , as well as in the segmental duplication GCR assay [11] , suggesting that these increases are likely due to elevated levels of DNA damage leading to aberrant repair . In addition , all of the mutations tested that specifically increase GCRs mediated by segmental duplications ( mrc1Δ , sgs1Δ , srs2Δ , rrm3Δ , rtt109Δ , and rad6Δ ) increased the rate of Ty912-mediated GCRs , indicating an overlap between the pathways that suppress segmental duplication-mediated GCRs and the Ty912-mediated GCRs . These mutations potentially cause defects in pathways that specifically suppress non-allelic HR . Interestingly , the wild-type strain containing the Ty912 on chromosome V had a higher GCR rate than that of the wild-type strain containing the segmental duplication-mediated GCR assay . This is likely due at least partially to both the larger size of the Ty912 element and the larger number of potential alternative repair templates available in the genome . In contrast , most of the gene defects affecting Ty1 transcription and transposition seemed to have little or no specific effects on the rate of Ty912-mediated GCRs , as many of the mutations that increased the +Ty912 GCR rate also increased the GCR rates in other GCR assays that did not involve Ty1 elements . This suggests that the +Ty912 GCR assay is an excellent model for understanding mechanisms suppressing rearrangements between high copy number repeats . Some of the mutations tested had distinct effects in the Ty1-mediated GCR assay that were surprisingly different than their effect in other GCR assays , including the segmental duplication assay . First , a rad52Δ that decreases HR increases the rate of single copy sequence-mediated GCRs [8] and decreases the rate of Ty1- and other duplication-mediated GCRs [11]; this is expected as HR is thought to play a central role in the formation of duplication mediated GCRs , but promotes the correct repair of DNA damage that would otherwise lead to single copy sequence-mediated GCRs . Second , deletion of rad51Δ increased both single copy-mediated and Ty-mediated GCRs ( Table 1 ) , but had relatively little effect on low-copy segmental duplication-mediated GCRs . This was surprising , especially given the fact that products of Ty-mediated HR in a wild-type strain were most consistent with the products of BIR , a process that is highly dependent on RAD51 [50] . A previous report found that a rad51Δdeletion caused an increased Ty1 recombination rate that led to a rise in the formation of solo LTRs but suppression of Ty conversion events [44] . Our study also revealed an increase in Ty-mediated GCRs upon deletion of RAD51 and suggested that another HR mechanism , such as a RAD59-dependent RAD51-independent single-stranded annealing event followed by a half-crossover [29] , [55] , could be responsible for the formation of Ty-mediated GCRs and that furthermore , the mechanism of repair was mutagenic and suppressed by RAD51 . Deletion of both RAD51 and RAD59 resulted in a GCR rate equivalent to that of a wild-type strain in the +Ty912 GCR assay ( Table 1 ) , which is consistent with a view that RAD59 promotes the mutagenic repair of DNA in the presence of the Ty912 and absence of RAD51 . Third , the rad51Δ rad59Δ double deletion resulted in a GCR rate that was higher than that of a rad52Δ strain ( unpaired Wilcoxon rank sum test; p = 5 . 59×10−4 ) , a pattern which was not observed in the segmental duplication assay [11] , but has been noted in a previous assay [46] . This difference suggests that other RAD52-dependent factors besides RAD51 and RAD59 play a larger role in the formation of Ty1-mediated GCRs than in the formation of lower copy segmental duplication-mediated GCRs . Fourth , we identified mutations that significantly reduced the +Ty912 GCR rate , but did not affect the rate of single copy sequence-mediated GCRs . These mutations include pmr1Δ , rtt103Δ and gal11Δ , all of which alter Ty metabolism [34] , [41] , [42] . This suggests that some aspects of normal Ty metabolism may impact the formation of GCRs . Overall , the genetic analysis performed as part of the present study indicates that the +Ty912 GCR assay is a high sensitivity assay suitable for the analysis of pathways that affect the rate of GCRs mediated by repetitive DNA and provides a means to detect common pathways that suppress genome instability , novel pathways that affect repetitive DNA , and different aspects of known GCR suppression pathways not previously studied . The work presented here indicates that dispersed repetitive elements in S . cerevisiae DNA , like the Ty elements that are analogous to human LINE and Alu elements in abundance , are chromosomal features that result in increased genomic instability . Analysis of this genomic instability has provided insights into both the HR-based mechanisms that yield Ty-mediated GCRs and the pathways that normally act to prevent such GCRs . In humans , suppression of non-allelic HR is likely important for preventing GCRs from occurring due to the large numbers of dispersed repetitive sequences in the human genome , particularly because such GCRs have been seen to underlie genetic diseases and are found among the genome rearrangements in many cancers . Our observations on the pathways that preferentially suppress Ty-mediated GCRs and on the mechanisms that produce such GCRs suggest that the structures of GCRs observed in disease situations will provide signatures diagnostic for particular genome instability-causing genetic defects .
We constructed the plasmid pRDK1251 containing Ty912 [32] surrounded by chromosome V targeting sequence to integrate the Ty1 element into the NPR2-CIN8 intergenic region . The flanking targeting sequence from CIN8 ( ChrV: 39724-36426 ) was amplified by PCR from S . cerevisiae genomic DNA with primers JCP41 and JCP42 ( Table S3 ) , which introduced flanking Sac I and Sma I restriction sites . The flanking targeting sequence from NPR2 ( ChrV: 36340-33913 ) was also amplified with primers JCP43 and JCP44 , which introduced flanking BamH I and Xba I restriction sites . Ty912 was amplified from plasmid B155 ( FB118 ) , a generous gift of Dr . Fred Winston ( Harvard Medical School ) , with JCP39 and JCP40 , which introduced flanking Sma I and BamH I restriction sites . The pRDK1251 plasmid was generated by sequentially subcloning the Sac I-CIN8-Sma I , Sma I-Ty912-Xba I , and BamH I-NPR2-Xba I fragments into pUC19 [61] , such that the NPR2 fragment was joined to the Ty912-XbaI site at the Xba I site present at genomic coordinate 35 , 997 . We sequentially transformed URA3 and HIS3 markers into the intergenic region between NPR2 and CIN8 in RDKY6078 ( MATa lys2-10A , hom3-10 , ura3Δ0 , leu2Δ0 , trp1Δ63 , his3Δ200 ) to generate strain RDKY6081 . We released the Ty912 cassette from pRDK1251 by Xba I digestion and then transformed the Ty912 cassette ( ∼10 ug ) into RDKY6081 using standard lithium acetate transformation protocols and plated the putative transformed colonies onto YPD plates . After one day of growth at 30°C , this YPD plate was replica-plated to a uracil dropout plate containing 1 g/L 5-fluoroorotic Acid ( 5FOA ) . After ∼2 days of growth at 30°C , the resulting colonies were replica-plated from the dropout plate containing 5FOA to a separate histidine dropout plate . Colonies were screened for growth on the uracil dropout plate containing 5FOA and for non-growth on the histidine dropout plate . We verified the insertion of Ty912 between NPR2 and CIN8 on the Crick strand of RDKY6082 by PCR ( primer pair JCP44 & JCP85; primer pair JCP125 & JCP349 ( Table S3 ) ) . A hxt13::URA3 KO cassette was amplified from RDKY3615 ( MATa , ura3-52 , leu2Δ1 , trp1Δ63 , his3Δ200 , lys2-Bgl , hom3-10 , ade2Δ1 , ade8 , hxt13::URA3 ) by PCR ( primer pair JCP28 & JCP29 ( Table S3 ) ) and transformed into RDKY6082 to create RDKY6084 . RDKY6084 was then backcrossed to RDKY6079 ( MATalpha lys2-10A , hom3-10 , ura3Δ0 , leu2Δ0 , trp1Δ63 , his3Δ200 ) and our +Ty912 wild type haploids RDKY6076/6077 ( MATa lys2-10A , hom3-10 , ura3Δ0 , leu2Δ0 , trp1Δ63 , his3Δ200 iYEL062w::Ty912 hxt13::URA3 ) were isolated . The −Ty wild-type strains RDKY6088/6089 ( MATa lys2-10A , hom3-10 , ura3Δ0 , leu2Δ0 , trp1Δ63 , his3Δ200 hxt13::URA3 ) were isolated by first transforming the previously isolated hxt13::URA3 cassette into RDKY6078 , backcrossing the resulting strain to RDKY6079 , and isolating haploids . All strains used in the experiments were isogenic to either RDKY6076 ( +Ty912 ) or RDKY6088 ( −Ty ) , which differ only by the presence of the Ty912 insertion ( Table S4 ) . Strains with kanMX4 marked deletions of interest were created using kanMX4 cassettes amplified from the systematic S . cerevisiae knockout library [62] . Strains with deletions marked with TRP1 and HIS3 cassettes were created by amplifying the cassettes from the pRS series of plasmids [63] with PCR primers that added 50 bases of the target homology of interest . These cassettes were then transformed into strains of interest using standard lithium acetate transformation protocols followed by verification of the correct insertion by PCR with flanking and internal primers . All strains used in the experiments are available upon request ( Table S4 ) , as are the primer sequences used in their construction . General methods , including use of YPD and synthetic dropout medias , have been described previously [9] . For each strain , we used 14 or more independent cultures in our fluctuation analyses [64] to calculate the median rates [65] . For each strain of interest , 1 µg of DNA was labeled with either Cy5 or Cy3 and applied to one of four wells of a Nimblegen 4-plex microarray . The GeneChip Microarray Core ( UC San Diego School of Medicine ) performed the hybridization and scanning . Probes on the array had a median base pair spacing of ∼200 bp between probes . DNA for seven independent GCR isolates and one −Ty wild type strain ( RDKY6088 ) were applied to each 4-plex microarray . Each microarray thus contained either a GCR isolate hybridized along with the −Ty wild-type DNA or with DNA from another GCR isolate ( Table S5 ) . The R package Ringo ( > = 1 . 8 . 0 ) [66] , an add-on to the Bioconductor suite ( > = 2 . 4 . 1 ) [67] , was used in combination with the SignalMap software ( > = 1 . 9 ) from Nimblegen to visualize the aCGH data . Increased copy numbers of probes were revealed by identifying continuous regions whose log ratios deviated from 0 . Deletions were identified by analyses of the raw intensity data and identification of regions with continuously low regional intensity .
|
In this study , we developed a Saccharomyces cerevisiae gross chromosomal rearrangement ( GCR ) assay that measures the rate of GCRs mediated by high copy , dispersed repeat sequences in the S . cerevisiae genome known as Ty elements . Like LINE and Alu elements found in the human genome , Ty elements are repeated throughout the yeast genome . Our results demonstrate that presence of this high-copy repetitive DNA increases the rate of GCRs . These results also show that there exist differences between the pathways that affect these genome rearrangements and those that suppress GCRs mediated by either low- or single-copy DNA sequences . The majority of the Ty-mediated GCRs observed were monocentric nonreciprocal translocations mediated by RAD52-dependent HR between the Ty element present on the assay chromosome and Ty elements located on other chromosomes . The remaining Ty-mediated GCRs appeared to involve the Ty-mediated formation of unstable dicentric translocation chromosomes that were resolved by one or more Ty element-mediated breakage-fusion-bridge cycles . Because the human genome consists of nearly 50% repetitive DNA , our work establishing this S . cerevisiae assay as a useful tool for studying non-allelic recombination between dispersed , high-copy repeat elements can give insight into those pathways that help maintain the stability of the human genome .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Methods"
] |
[
"biochemistry",
"cancer",
"genetics",
"dna",
"replication",
"nucleic",
"acids",
"genetics",
"dna",
"biology",
"dna",
"recombination",
"dna",
"repair",
"genetics",
"of",
"disease",
"molecular",
"genetics",
"genetics",
"and",
"genomics"
] |
2011
|
A Genetic and Structural Study of Genome Rearrangements Mediated by High Copy Repeat Ty1 Elements
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Dynamin-1 ( Dnm1 ) encodes a large multimeric GTPase necessary for activity-dependent membrane recycling in neurons , including synaptic vesicle endocytosis . Mice heterozygous for a novel spontaneous Dnm1 mutation—fitful—experience recurrent seizures , and homozygotes have more debilitating , often lethal seizures in addition to severe ataxia and neurosensory deficits . Fitful is a missense mutation in an exon that defines the DNM1a isoform , leaving intact the alternatively spliced exon that encodes DNM1b . The expression of the corresponding alternate transcripts is developmentally regulated , with DNM1b expression highest during early neuronal development and DNM1a expression increasing postnatally with synaptic maturation . Mutant DNM1a does not efficiently self-assemble into higher order complexes known to be necessary for proper dynamin function , and it also interferes with endocytic recycling in cell culture . In mice , the mutation results in defective synaptic transmission characterized by a slower recovery from depression after trains of stimulation . The DNM1a and DNM1b isoform pair is highly conserved in vertebrate evolution , whereas invertebrates have only one isoform . We speculate that the emergence of more specialized forms of DNM1 may be important in organisms with complex neuronal function .
Epilepsy affects about 1% of the population and approximately 30% of cases are idiopathic , with no obvious explanation such as head injury , stroke , lesions or tumors [1] . Genetic factors are thought to lie behind idiopathic epilepsy [1] . Several human epilepsy genes have been identified [2] , [3] but most genes for common idiopathic epilepsy remain unknown , in part due to the complex genetics . Employing a forward genetics approach , we have studied the mutant “ fitful” mouse which exhibits spontaneous limbic and generalized tonic-clonic seizures upon routine handling , due to a spontaneous mutation in the gene encoding dynamin-1 . Heterozygous fitful mice develop epilepsy by two to three months of age , but are otherwise outwardly normal . Homozygous mice have a more severe neurological phenotype at a much younger age - three weeks - including ataxia , hearing and vision defects and lethal seizures . Dynamin-1 belongs to a family of large GTPases that function in endocytosis , vesicle scission , membrane recycling , organelle division , cytokinesis and antiviral activity [4]–[10] . In mammals , there are three dynamin genes ( Dnm1 , Dnm2 , and Dnm3 ) each of which undergoes complex alternative splicing resulting in over 25 dynamin isoforms . Dnm2 is expressed in all tissues [11] . Dnm1 is expressed only in the brain , localizing to the presynaptic terminal [12] , [13] . Dnm3 is expressed in the brain ( where it is associated with the postsynaptic compartment ) and the testes [12] , [14] . Flies carrying mutant temperature-sensitive alleles of shibire , the Drosophila homolog of dynamin , exhibit paralysis at the restrictive temperature that is due to depletion of synaptic vesicles in a use-dependent manner [15] . Dynamin-1 has an established role in endocytic vesicle fission from the plasma membrane [16] and its expression is upregulated in the brain during postnatal development , concomitant with synaptogenesis . In primary neuronal culture , the expression and protein levels of dynamin-1 increase steadily in conjunction with the formation of neurites over time in culture , peaking as synapse formation occurs [9] , [12] , [17] . This expression pattern mimics that of other synaptic vesicle proteins such as synaptophysin and suggests a critical role for dynamin-1 in synaptic vesicle recycling based on its developmental expression pattern as well as localization to presynaptic compartments and known function in membrane recycling and endocytosis . Dynamin molecules assemble into tetrameric structures that hydrolyse GTP to scission vesicle membrane , including synaptic vesicles which recycle after neurotransmitter release . Dynamin monomers are 100KD polypeptides containing 5 functional domains: a GTPase domain that binds and hydrolyses GTP , a middle domain that is involved in oligomerization , a GTPase effector domain ( GED ) that is involved in oligomerization and stimulation of GTPase activity , and plextrin-homology ( PH ) and proline-rich ( PRD ) domains that mediate lipid- and protein-protein interactions . In fitful mice , a single nucleotide change results in an amino acid substitution in the highly conserved coding region of the middle domain of the protein . This domain is involved in the dimerization and higher order assembly of the dynamin tetramers [18]–[20] . Interestingly , mutations in the corresponding middle domain of dynamin-2 underlie human disease such as autosomal dominant centronuclear myopathy [21] and a canine mutation in Dnm1 located at the GTPase/middle domain border results in an exercise induced collapse disorder in Labrador retrievers [22] . Mice that completely lack Dnm1 survive into the second week of life demonstrating that Dnm1 is not necessary for embryonic development or for perinatal synaptic transmission [9] . In Dnm1 null mice , inhibitory neurons are more sensitive to the loss of Dnm1 and experience endocytic defects [9] , [10] , but neither the homozygous nor the heterozygous Dnm1 null mice have seizures [9] . In cortical neuron cultures established from Dnm1 null mice , inhibitory neurons are shown to be the most sensitive to loss of Dnm1 , acquiring a large build up of endocytic intermediates during spontaneous network activity [10] . Silencing transmission relieves the endocytic defect - suggesting that the high intrinsic level of tonic activity of these cortical inhibitory neurons makes them more vulnerable to the lack of Dnm1 [10] . Dnm1 , as well as Dnm2 and Dnm3 , is alternatively spliced at two locations in the transcript resulting in the possibility of nine Dnm1 isoforms . In this study , we show that the fitful mutation in Dnm1 interferes with the normal expression of the first alternatively spliced region during postnatal development . This region is located within the middle domain required for oligomerization , a process that is affected in fitful mutants . Given that Dnm1 is essential for synaptic vesicle endocytosis , fitful mice are likely to have a lack of sufficient vesicles for extended synaptic transmission . This may be particularly problematic for the recycling of synaptic vesicles at tonically firing inhibitory synapses in light of findings in dynamin-1 null mice [9] , [10] . Disruption of this process would consequently upset the balance between inhibition and excitation resulting in abnormal propagation of neuronal excitability and recurrent seizures . Previous studies have extensively examined the function and mechanisms of action of Dnm1 , but this study is the first to identify a Dnm1 mutation that leads to epilepsy . Furthermore , our study suggests that there are distinct roles for the alternatively spliced Dnm1 isoforms which have not previously been examined in vivo . The fitful mouse model provides a unique resource for understanding the role of the Dnm1 isoforms in brain as well as for studying the frequency-dependent weakening of synaptic inhibition as has been seen in other genetic models of generalized epilepsy , such as SCN1A [23] , [24] .
The fitful mutation ( allele symbol: Ftfl ) arose spontaneously in C57BL/6J ( B6 ) mice and was identified initially by the occurrence of recurrent , non-lethal seizures . The overall phenotype of Ftfl is semidominant . Heterozygotes develop partial and generalized tonic-clonic seizures upon routine handling from approximately two to three months of age ( Figure 1A and 1D ) , but otherwise appear normal and have a lifespan similar to wildtype littermates . Heterozygotes have a modest reduction in seizure threshold to an acute electrical stimulus , about 0 . 25 mA lower than controls ( Figure 1B ) . Although this effect is statistically significant , it is smaller than the difference ( >0 . 5 mA ) we have reported in other seizure-prone mice on the B6 background - some of which go on to develop epilepsy ( Brunol4Ff; [25] ) , and others that do not ( Szt2;[26] ) . Nevertheless , heterozygous fitful mice develop kindled seizures much more readily than wildtype mice in response to repeated electrical stimuli , suggesting that they are more epileptogenic ( Figure 1C ) . Homozygous fitful mutants have more severe phenotypes , including ataxia and spontaneous convulsive seizures that usually result in death before weaning age ( see Video S1 ) . Homozygous pups are born with the expected Mendelian genotype ratio , but only survive into the second or third week of life depending on strain background . Mutant pups are viable and indistinguishable from their wildtype littermates at birth and for the first week of life . At approximately post-natal day 12 ( P12 ) , the mutants become discernible from wildtype as they develop a progressive ataxia characterized by an abnormal and uncoordinated stance and gait . Homozygotes show tonic-clonic seizures at P14–P16 . A seizure episode typically lasts 30 seconds to one minute and is immediately followed by a clear diminishment in health and movement . Typically , mutants die before P18 from either a lethal seizure or lack of nourishment brought on by continued weakening of physical movement . Mutant pups that receive nutritional supplementation tend to survive about one to two days longer . Routine histology showed no obvious brain abnormalities in homozygous mice ( data not shown ) . However , when examined by immunofluorescence , Purkinje cell dendritic trees were markedly smaller in all homozygous mice examined at P17 ( Figure 1E ) . In mutants , Purkinje cell dendrites were polydendritic and the size of the dendritic arbor and degree of branching was reduced compared to wildtype ( Figure 1E , bottom panels ) . The wildtype Purkinje cell layer had more regular somas that are ordered in structure and dendrites that are noticeably smoother than the mutants that showed spiny dendrites along with a disorderly arrangement of soma . We suspected that the homozygotes might have neurosensory defects . Given their lethality at three weeks of age , hearing was the most practical sense to test in detail . To examine hearing , we evaluated the auditory brainstem response ( ABR ) of P14–17 fitful homozygous mice and compared with wildtype and heterozygous littermates . Fitful homozygotes display a modest ABR threshold increase , approximately 15 dB , across all sound frequencies tested ( Figure 1F , left panel ) . We also found that the latencies of most ABR peaks were progressively prolonged ( Figure 1F , right panel ) and the amplitude of some of the ABR peaks was reduced in the mutants . The first peak ( peak I ) was reduced and delayed reflecting impaired function of the inner hair cell-afferent synapse and a reduction in synchronous spiral ganglion activation [27] , [28] . To rule out a defect in outer hair cell function , we measured distortion product otoacoustic emissions . This showed intact outer hair cell function in fitful homozygotes ( Figure S1 ) . Thus , the hearing impairment is most likely due to a deficit in sound coding at the inner hair cell synapse that could be due to a lack of a rapid resupply of readily-releasable vesicles [29] . Whole genome scans were done to map both the dominant seizure phenotype , and the recessive ataxia phenotype , to Chromosome 2 . Further fine mapping narrowed the region to two Mb including the Dnm1 gene and several other candidate genes with high expression in the brain: Mapkap1 , Fibcd1 , Ppapdc1 , and Stxbp1 . Expression analysis of these genes did not reveal any differences between wildtype and mutant brain RNA , and further cDNA sequencing of Stxbp1 specifically revealed no mutations . In Dnm1 a single nucleotide change was discovered by sequence analysis of mutant cDNA , revealing a G-to-A nucleotide mutation in the first of two alternatively spliced regions ( Figure 2A ) . Dnm1 encodes several isoform variants resulting from alternative mRNA splicing events at two regions: the middle domain , which contains the fitful mutation , and the C-terminal PRD domain . Splicing results in either DNM1ax or DNM1bx , where a or b are the middle domain splice variants and x is any of the three alternatively spliced terminal exons . The middle domain variant differs only by a peptide encoded by two tandemly arranged exons , with 14 residues varying within a 46 amino acid region ( Figure 2A ) . This particular alternative exon pair of Dnm1 and Dnm2 is conserved in all vertebrates including mice ( e . g . Dnm1ax and Dnm1bx ) and humans ( Dnm1 and Dnm1 “alternative” ) , but it is not present in Dnm3 nor is it in invertebrate dynamin ( Figure 2A–2C; [30] , [31] , reviewed in [32]; see Figure 2B legend for more details ) . The fitful missense mutation results in an alanine to threonine substitution at amino acid 408 , an evolutionarily conserved residue ( Figure 2A and 2B ) . Noticeably , fitful only affects the Dnm1ax isoform sequences; the “a” exon is spliced out in the Dnm1bx forms , resulting in potentially all three Dnm1ax transcripts being altered . To provide genetic confirmation that the Ftfl phenotype is caused by the missense mutation in Dnm1 , we crossed heterozygous Dnm1Ftfl mice to mice heterozygous for the null mutation ( Dnm1tm1Pdc; [9] ) . Compound heterozygous Dnm1tm1Pdc/Dnm1Ftfl pups were born very near to the expected Mendelian ratio of 1∶4 ( Figure 3 ) . We observed 80 compound heterozygotes out of 46 litters having a total of 334 pups . The average litter size was 6–8 pups depending on background strain . The phenotype of the resulting Dnm1tm1Pdc/Dnm1Ftfl compound heterozygous mice was in many ways similar to that of Ftfl homozygotes , including seizures by the third week of life and death before weaning . We observed 15 compound heterozygous mice to have seizures during their shortened lifespan , while no such seizures were observed in wildtype , or deleted or fitful heterozygous littermates at this age ( Figure 3 ) . There were four confirmed deaths due to seizures , with three more suspected by virtue of finding carcasses with hindlimb or forelimb tonic extension . Although the onset and appearance of lethal seizures was very similar between fitful homozygotes and compound heterozygotes , these two classes had different locomotor phenotypes; the compound heterozygotes were not ataxic , although they had a slight tremor and hunched appearance that continually increased in severity . Together with the mapping and mutation analysis , these results provide strong evidence that fitful is an allele of Dnm1 . They also reinforce the suggestion that wildtype Dnm1 is necessary for normal postnatal neurodevelopment . Dynamin-1 increases in abundance during early postnatal brain development [9] , [12] . We examined the expression of Dnm1ax and Dnm1bx during brain development in mutants . cDNA amplification using a single set of primers for both isoforms , followed by restriction with HphI which has a recognition site present only in exon 10b , allowed for direct visualization of the relative expression of exon 10a and exon 10b containing isoforms . From E17 . 5 through P14 , the overall increase in Dnm1 is due to isoforms containing exon 10a , while isoforms containing exon 10b either remain constant or diminish slightly with age ( Figure 4A ) . Interestingly , in homozygous mutant , there was a delay in this shift; isoforms containing exon 10b remained upregulated longer ( compare at P0 ) during development . This was significant as P0 through P14 is the period of extensive synaptic maturation and regulated endocytosis . Quantification of exon 10b-containing isoforms relative to the total amount of Dnm1 mRNA in whole brain was calculated and showed a clear trend suggesting that Dnm1bx is more prominent in mutants than wildtype throughout development ( Figure 4B , left panel ) . This shift was confirmed by quantification of relative isoform transcript levels using pyrosequencing ( Figure 4B , right panel ) and did not result in a significant change in overall Dnm1 transcript abundance . The alteration in isoform expression was confirmed and extended at the protein level using isoform-specific antibodies ( see Figure S3 for details ) . Figure 4C shows one of three replicate western blots demonstrating a decrease in protein containing exon 10a peptides ( DNM1a ) at each age examined in mutants as compared to wildtype . There is a parallel increase corresponding to exon 10b containing peptides ( DNM1b ) . Least square regression analysis with age , genotype and replicates as independent variables revealed a significant ( p<0 . 05 ) increase in the expression of DNM1b in mutant animals after two weeks of age . These results suggest the possibility that altered dynamin-1 isoform composition during this important period of synaptic maturation may contribute to the disease phenotypes . The fitful mutation resides within the “middle” domain of dynamin ( Figure 2A ) , previously shown to be required for self-assembly into dimers and further higher-order assembly into tetrameric structures [18]–[20] . We examined the ability of DNM1Ftfl to properly assemble into dimers and higher order oligomers using protein extracts from normal and fitful brain . Protein extracts were incubated with a cross-linking agent , 1-Ethyl-3-[3-dimethylaminopropyl]carbodiimide hydrochloride ( EDC ) , of zero length , to bind proteins intimately associated in dimer or tetramer formation [33] . Equal amounts of extract were treated with or without EDC and separated by SDS-PAGE . Protein from wildtype brains exhibited the ability to form dimers and tetramers in the presence of cross-linker ( Figure 5A , left panel ) . Over half the DNM1 protein detected was assembled , with 28% in tetrameric form and 36% in dimeric form . While the homozygous fitful brain extract appeared to contain DNM1 dimers upon the addition of EDC , the amount of higher order structures ( tetramers in this assay ) was reduced with only 9% of detected DNM1 in tetrameric form ( Figure 5A , left ) . This result indicates a defect in the ability of DNM1AFtfl to form multimeric DNM1 complexes . The dimer band in the mutant extracts , which was 45% of the DNM1 signal , was possibly due to the assembly of normal DNM1b . To explore this further , we analyzed the ability of exogenous DNM1 isoforms to self-assemble in cells . We made isoform-specific constructs that express GFP fused to the C-terminal of DNM1 . Equal amounts of each GFP-tagged DNM1 isoform construct was transfected individually into COS-7 cells . Both exogenous wildtype proteins , DNM1a and DNM1b , formed dimers efficiently ( Figure 5A , right panel ) . This dimerization was accompanied by a corresponding reduction in monomer amount . Notably , mutant DNM1aFtfl did not form dimers efficiently and remained mostly monomeric in COS-7 cells ( Figure 5A , right panel ) . These results confirm that DNM1aFtfl is defective in self-assembly . To determine whether the mutant monomer can assemble with wildtype monomers to form heterodimers , we doubly-transfected COS-7 cells with equal amounts of GFP- and HA- C-terminal tagged dynamin-1 constructs . Upon cross-linking and analysis with GFP or HA antibodies , we observed that the mutant DNM1aFtfl protein can dimerize with each wildtype isoform ( Figure 5B ) , albeit to a lesser extent than wildtype DNM1a . Dynamins are catalytic for endocytosis . Extensive previous studies introducing various dynamin mutant constructs into mammalian cells have demonstrated that overexpression of mutant dynamin blocks endocytosis and causes an accumulation of endocytic intermediates [32] . Several of these mutations ( e . g . K44A ) are dominant-negative , binding to endogenous dynamin and preventing it from properly functioning [4] , [16] . Specifically , dynamin GTPase domain mutations that inhibit endocytosis when expressed in COS-7 cells have a reticular type of localization as opposed to the more diffuse cytoplasmic localization of wildtype dynamin [34] . In prior studies to more closely examine these mutants by electron microscopy , the cells expressing mutant dynamin were observed to contain dynamin-coated plasma membrane tubules that had not undergone fission [34] . To examine the cellular localization of DNM1aFtfl , we expressed GFP-tagged DNM1 isoform constructs in mammalian COS-7 cells . Wildtype DNM1a-GFP and DNM1b-GFP exhibited localization patterns similar to each other , characterized by a diffuse cytosolic distribution with bright puncta in the more highly expressing cells . However , in cells expressing DNM1aFtfl-GFP the pattern was strikingly different . Notably , many of the transfected cells were observed to have fluorescent tubular networks very similar to the structures observed by others previously ( see Figure 6A; [34] ) . In order to determine whether DNM1aFtfl interferes with endocytosis , transfected COS-7 cells were tested for uptake of fluorescently labeled transferrin . Transferrin uptake was observed in cells expressing wildtype DNM1a ( Figure 6B ) and wildtype DNM1b ( data not shown ) , but cells expressing mutant DNM1aFtfl were deficient in general transferrin uptake as characterized by the lack of perinuclear transferrin localization ( Figure 6B ) . Overall , 82% and 79% of cells transfected with the wildtype DNM1a and Dnm1b , respectively , were observed to have taken up and properly localized the transferrin . However , only 27% of cells transfected with DNM1aFtfl had taken up transferrin; 73% either had no transferrin visible or it was mislocalized ( Figure 6C ) , but often exhibited a notable co-localization with DNM1aFtfl at the tubular structures ( Figure 6B , arrow ) . This observation is in agreement with the work carried out with dynamin GTPase mutants previously noted in which further investigation revealed transferrin-rich membrane invaginations continuous with the plasma membrane [34] . These results suggest that unlike wildtype DNM1a , DNM1aFtfl cannot support endocytosis in COS-7 cells . Furthermore , DNM1aFtfl seems to act in a dominant-negative manner , interfering with the function of endogenous DNM2 - the dynamin that normally carries out these functions in COS-7 cells - similar to previously described dynamin GTPase mutants that are not able to catalyze the fission of membrane and inhibit endocytosis [34] . Dominant-negative effects are currently thought to be due to hetero-oligomerization of the mutant oligomer with endogenous dynamin oligomers , perturbing normal function . We examined synaptic properties of cortical neurons in acute slices for evidence of abnormalities in fitful homozygotes . We focused on GABAergic transmission because recent studies using neuronal cell culture demonstrated that the loss of Dnm1 preferentially affects inhibition [9] . First , we recorded quantal GABAergic IPSCs ( mIPSCs ) in layer V pyramidal neurons in the somatosensory cortex at P14–15 . Cells with comparable series resistance were analyzed ( 9 . 3±0 . 5 MW , n = 21 cells from three wildtype mice; 9 . 3±0 . 5 MW , n = 22 cells from three mutant mice ) . Samples of GABAergic mIPSCs recorded from a wildtype ( upper trace ) and a fitful ( lower trace ) layer V pyramidal neuron are shown in Figure 7A . Fitful neurons demonstrated more prolonged quantal events than those in wildtype mice ( Figure 7B ) . The mean decay time constant was 5 . 2±0 . 2 ms ( n = 22 ) for mutant cells , and 4 . 1±0 . 2 ms ( n = 21 ) for wildtype ( p<0 . 005 , Mann-Whitney test ) . Quantal events in mutant also had slower rise time . The mean rise time ( from 20 to 80% of the peak ) was 0 . 49±0 . 01 ms for mutant , and 0 . 42±0 . 01 ms for wildtype , which was significantly different . There were no significant differences between mutant and wildtype in the frequency ( 10 . 8±0 . 8 Hz vs . 10 . 9±0 . 8 Hz; p>0 . 8 ) or peak amplitude of mIPSCs ( 42 . 9±3 . 8 pA vs . 34 . 5±3 . 2 pA; p>0 . 06; data not shown ) . To determine whether the fitful mutation leads to a deficit in vesicle membrane recycling , we recorded monosynaptic GABAergic responses by applying current pulses through stimulation electrodes placed in layer V . There was no significant difference between mutant and wildtype cells in the maximum IPSC ( 1254±113 pA , n = ten cells from three mutant mice; 1209±132 pA , n = ten cells from three wildtype mice; p>0 . 5; data not shown ) . Trains of 10-Hz stimulation were applied at intensities that achieve 40 to 60% of the maximum response . As illustrated in Figure 7E and 7F , the amplitude of IPSCs decreased more rapidly in mutant than wildtype cells during 10-Hz stimulations . The recovery was tested by applying stimuli at 0 . 1 Hz immediately following 1000 stimuli at 10 Hz . The recovery of IPSCs was much slower in mutant than wildtype cells ( Figure 7G; n = nine cells from two mutant mice; n = eight cells from two wildtype mice ) . The depression and the reduced rate of recovery in IPSC amplitude were affected in fitful , similar to the results in Dnm1 null primary neuron culture [9] . These differences in evoked GABAergic response are consistent with a likely deficit in vesicle membrane recycling in mutant cells and suggests that the mutation in dynamin-1 interferes with sustained evoked release .
Fitful mutant mice reveal intriguing differences between underlying dynamin-1 mutations and the respective phenotypes . Alternative splicing in the molecular assembly-associated domain of dynamin-1 appears to play a key role in these phenotypes and in the proper function of dynamin-1 . Fitful mice have a complex neurological disorder in which epilepsy is a major and consistent feature . Adult heterozygotes have recurrent limbic and tonic-clonic seizures , a modestly reduced seizure threshold , and a predisposition for becoming epileptic , but no other obvious phenotypic abnormalities . This dominant phenotype provides a new model for common idiopathic generalized epilepsy ( IGE ) , for which few causative genes are known and progress is slowed by the complex genetic architecture underlying this disorder . In contrast , fitful homozygotes have multiple neurological deficits by three weeks of age , including delayed growth , cerebellar ataxia , hearing loss , and severe , ultimately lethal , tonic-clonic seizures . Fitful creates an amino acid substitution in the highly conserved DNM1ax isoform encoded by Dnm1 exon 10 , leaving DNM1bx structurally intact . While DNM1aFtfl protein is expressed in mutant mice , it does not efficiently assemble into higher order oligomeric dynamin complexes . In addition , similar to previously described dominant-negative alleles of Dnm1 , characterized only in vitro ( e . g . K44A; [4] ) , DNM1aFtfl also interferes with normal endocytosis in COS-7 cells . Our heterologous expression experiments provide insight into the biochemical consequences of the DNM1aFtfl mutation , with its dominant-negative effect on endocytosis evidenced by a lack of transferrin uptake and subsequent proper trafficking . We can envision three ways in which this effect is manifest . First , sequestration of interacting proteins necessary for endocytosis could reduce the pool available for endocytosis . Preliminarily , however , we have found no evidence for altered abundance of several known dynamin-associated proteins , such as amphiphysin I and auxilin , in fitful homozygotes ( our unpublished results ) . Second , assembly of non-functional DNM2 and DNM1aFtfl heterodimers could inhibit proper DNM2 function . This remains a possibility as we find that DNM1aFtfl can interact with DNM2 to some extent , both in COS-7 cells and also in brain ( unpublished data ) , however we find no evidence of colocalization by immunofluorescence ( unpublished data ) . We do find evidence for heterodimerization of DNM1aFtfl with each of the wildtype dynamin-1 isoforms ( Figure 5B ) , suggesting a dominant negative effect whereby mutant protein binds with wildtype protein resulting in non-functional heterodimers that cannot fission membrane . Third , the accumulation of unassembled DNM1aFtfl at sites of fission could stall endocytosis . This is an attractive possibility for fitful mice . The appearance of tubules in cells that overexpress DNM1aFtfl is reminiscent of previous dynamin mutations [34] and narrow tubules were also observed in dynamin-1 null neurons [9] . While tubules may represent a buildup of invaginating membrane that cannot be fissioned , they could alternatively result from stalled clathrin-mediated endocytosis at the invagination stage ( a stage at which dynamin is thought to be a checkpoint; [35] ) . Membrane invagination and fission are mediated by two separate mechanisms carried out by dynamin [7] and both assembly-independent GTPase and assembly-stimulated GTPase activities are needed to carry out these process [35]–[37] . The assembly/disassembly cycle is required for association and disassociation with the membrane . Self-assembly defective DNM1aFtfl would presumably not have the assembly-stimulated activity required for fission , but would retain the assembly-independent activity necessary for membrane invagination . Furthermore , unassembled dynamin has been proposed to be the molecular checkpoint during early stages of clathrin-mediated endocytosis , potentially allowing the abortion or progression of clathrin-coated particle ( CCP ) intermediates through maturation [35] , [37] . Dynamin assembly is suggested to control the transition from early to late events in CCP maturation [37] . Such a model would imply that unassembled dynamin can monitor CCP formation and is a separate activity from membrane fission as catalyzed by assembled dynamin . Our data showing that unassembled DNM1aFtfl can tubulate membranes but cannot fission them are consistent with this hypothesis . We speculate that the seizure phenotype in fitful but not in Dnm1-null heterozygotes may result from the unique presence of mutant DNM1aFtfl stalling such an endocytic checkpoint . This would also provide an explanation for the reduced phenotype severity of compound heterozygous mice as compared with homozygous fitful ( e . g . Figure 3A ) ; homozygous fitful would have up to twice the amount of abnormal protein , accumulating and exerting its negative effect with a quicker timecourse . However , even the compound heterozygotes ultimately succumb to lethal seizures . This dominant effect of DNM1aFtfl presumably leads to a lack of sufficient vesicles for extended inhibitory transmission - particularly problematic for tonically firing inhibitory synapses [9] , [10] . The genetic and phenotypic differences between fitful and Dnm1 null mice - in particular , epilepsy in fitful heterozygotes but not in Dnm1 null mice of either genotype ( [9]; P . de Camilli , personal comm . ; our unpublished observations ) – further suggests that DNM1aFtfl protein confers unique properties relevant for disease . We examined both spontaneous and evoked IPSCs in layer V pyramidal neurons in acute brain slices . The peak amplitude of spontaneous or mIPSCs was not significantly different between fitful mutant and wildtype mice . This is in contrast with the results obtained in Dnm1-null cortical cultures where Dnm1-null neurons show a large increase in the peak amplitude of mIPSCs [9] . The reason for this difference is unknown . Dnm1-null neurons have larger diameter synaptic vesicles , which may lead to an increase in quantal content . This increase in vesicle size observed in Dnm1-null neurons may be caused by direct or compensatory mechanisms . It is possible that the presence of the mutated dynamin-1 in fitful mice attenuates compensatory responses . Another possibility is that fitful causes changes in the cable ( electrical ) properties of neurons or the location of GABAergic synapses , so that recordings from the soma are unable to detect changes in mIPSCs at the dendrites . Indeed , the slower kinetics of mIPSCs observed in fiftful neurons is consistent with this possibility . However , the evoked IPSC responses in fitful acute slice preparations were similar to those shown previously in Dnm1-null primary neurons [9] , reflecting a loss-of-function . Compared with wildtype , both alleles confer a more rapid depression of evoked IPSCs in response to 10-Hz stimulation , and a much slower recovery from depression . These findings , together with recent results obtained using a selective blocker of dynamin [38] , demonstrate a critical role of dynamin in synaptic vesicle recycling . During repetitive stimulation , neurotransmission relies on the rapid reuse of synaptic vesicles endocytosed in a dynamin-dependent manner [9] , [38] . Without efficient recovery of these rapidly reused vesicles , there is very likely a frequency-dependent exhaustion of synaptic inhibition , such a seen in other models of generalized epilepsy [23] , [24] . The inability of DNM1aFtfl to assemble efficiently into oligomers is a plausible explanation for the biochemical defect , but to fully understand the development of disease , it may be important to consider functional differences between the two isoforms . Despite the high degree of conservation , functional differences conferred by the respective protein isoforms have not been demonstrated in vivo , but insight has been gained from heterologous systems [39] , [40] . The alternate splice in exon 10 that occurs in Dnm1 and Dnm2 , but not Dnm3 or in the dynamin-related protein Drp , has been recognized previously . We observe that this diversification is present in all jawed vertebrates and is even present in sea lamprey - a primitive , jawless freshwater fish – which , despite having these alternate exons , unlike other vertebrates possesses only a single dynamin gene ( Figure 2B ) . Furthermore , neighbor-joining best tree analysis suggests that invertebrate dynamins are closer to DNM1b ( and DNM2 ) , whereas DNM1a forms a more isolated phylogenetic group ( Figure 2C ) . The divergent exon 10a may well be a specialization that is unique to vertebrates . The developmental shift in isoform expression may also provide clues into function . DNM1b expression is highest during embryonic and early postnatal development and decreases with synaptogenesis as DNM1a expression increases ( Figure 4A and 4C ) . This may be to accommodate changing requirements for endocytosis over the course of development . At the onset of synaptogenesis , basal endocytosis is down-regulated and stimulation-induced endocytosis takes over as the major form of SV recycling [41] . If one form of endocytosis relies more heavily on a specific DNM1 isoform , then the altered isoform expression in fitful may disrupt the changes in endocytosis necessary for maturation , resulting in a number of adverse consequences . Early endocytosis is required for many vital processes such as growth cone development , cellular migration , axonal arborization and dendritic branching . It is possible that the significantly stunted Purkinje cell arborization observed in the homozygous fitful mutants is one consequence of an early developmental abnormality . Alternatively , inappropriate expression of DNM1b in mature fitful neurons that should predominately express DNM1a , may adversely affect the kinetics of endocytosis , in a manner suggested above . It is intriguing that a missense mutation in a discrete splice variant of Dnm1 can lead to significant neurological disease phenotypes . We speculate that Dnm1 isoforms confer specificity to both the developmental program of endocytosis and also to variant endocytic response to stimuli ( e . g . clathrin-mediated vs . activity-dependent bulk endocytosis ) . In the future , studies using conditional isoform-specific expression will help to distinguish these possibilities .
All animal procedures followed Association for Assessment and Accreditation of Laboratory Animal Care guidelines and were approved by institutional Animal Care and Use Committee . The fitful mice arose at The Jackson Laboratory ( Bar Harbor , ME ) as a spontaneous mutation on the C57BL/6J inbred strain in 2000 . B6 . 129s1-Dnm1tm1PDC mice were a gift from P . De Camilli [9] . To generate GFP mice used for cerebellar histology , fitful heterozygotes were mated to a B6 mouse strain carrying a transgene with the parvalbumin promoter fused to the GFP gene ( strain # B20; [42] ) . All strains were housed in the Research Animal Facility at The Jackson Laboratory where animal procedures were approved by the ACUC . Two separate genome scans were used to map fitful to mouse Chromosome 2 . To map the dominant seizure phenotype , B6-Ftfl heterozygotes were crossed to FVB/NJ mice . Two ( of six total ) resultant F1 hybrids were noted to have spontaneous limbic and tonic-clonic seizures after two months of age upon routine handling and weekly cage changes . The F1 hybrids were backcrossed to FVB/NJ mice , and the resultant N2 progeny were aged and observed at least weekly for seizures . Genomic tail DNA was prepared from 79 backcross mice , 22 of which showed at least two limbic and tonic-clonic behavioral seizures , and a genome scan was performed with seizure occurrence as a binary trait using microsatellite markers . The mutation was provisionally mapped to proximal Chromosome 2 and the critical interval for the recessive phenotype was ultimately refined to the genomic region between D2Mit152 and D2Mit203 after typing a total of 487 F2 , F3 and F4 progeny . Independently , the recessive ataxia and early onset seizure phenotypes were mapped after crossing B6-Ftfl heterozygotes to CAST/Ei , and subsequently crossing the F1 hybrids inter se . Provisional linkage to Chromosome 2 was established in 20 affected mice , and the critical interval for the recessive phenotype was ultimately refined to the genomic region between D2Mit80 and D2Mit72 after typing a total of 990 F2 , F3 and F4 progeny . Genotyping Dnm1Ftfl ( fitful ) was done by PCR using the primers: Dnm1 MwoI F2 ( 5′-CGGACGGGCCTCTTCACACCTG-3′ ) and Dnm1 MwoI R ( 5′-GCGGCCATACCTTTTCACTA-3′ ) . The PCR product was digested for 2 hours at 60°C with the restriction enzyme MwoI ( NEB ) . The digestion products were separated and visualized on a 4% Metaphor agarose ( Lonza ) gel by electrophoresis . The Dnm1ab , Dnm1aFtflb , or Dnm1bb sequence was cloned into the pCMV-GFP and pCMV-HA vectors , in frame . The “b” alternative exon 22 was chosen because it is the most represented isoform found in Ensembl and the UCSC Genome Browser . This isoform was also the most abundant to clone from mouse cDNA . All constructs were confirmed by direct sequencing . Primers used to amplify Dnm1 sequences were: Dnm1u ( 5′-CCATCGATATGGGCAACCGCGGCATGG-3′ ) ; Dnm1d ( 5′-CCGCTCGAGGGGGTCACTGATAGTGATTC-3′ ) . COS-7 cells were maintained in supplemented Dulbecco's modified Eagle's medium ( DMEM; 10% fetal bovine serum , 30U/ml penicillin , 30µg/ml streptomycin ) at 37°C in a 5% CO2 humidified atmosphere . Cells were split twice a week . Transient transfection of COS-7 cells was performed with 1–2µg of DNA/well in 6-well culture dishes using the Lipofectamine Plus Reagent ( Invitrogen ) according to the manufacturer's protocol . To assay endocytosis , cells transfected ( on coverslips ) with GFP tagged proteins were incubated in serum-free DMEM ( Invitrogen ) for 1 hour at 37°C followed by the addition of 25µg/ml AlexaFluor-555 conjugated transferrin ( Invitrogen ) for 15 minutes at 37°C . Cells were washed three times with PBS , and in some experiments , were incubated in an acidic solution ( 0 . 5M NaCl , 0 . 2M acetic acid in PBS; pH 3 . 0 ) for 4 minutes at 4°C to strip surface bound transferrin and washed immediately with PBS , fixed in 4% paraformaldehyde , 4% sucrose in PBS for 10 minutes at RT and mounted on slides with Gel/Mount ( biomeda ) . Total RNA was prepared from brains of E17 . 5 , P0 and P14 fitful homozygous and wildtype littermates with Trizol ( Invitrogen ) following the manufacturer's suggested conditions and protocol . RNA ( 2µg ) was reverse transcribed with AMV reverse transcriptase ( Promega ) . cDNA was diluted and amplified for 25 cycles at an annealing temperature of 55°C with the following pair of primers: Dnm1 ex9F ( 5′-GAACTGCGA AGGGAGATCAG-3′ ) and Dnm1 ex12R ( 5′-GGTCACAATTCGCTCCATCT-3′ ) corresponding to Dnm1 exon 9 forward and exon 12 reverse , respectively . The PCR amplifications from three pairs of age-matched mice were run in triplicate . The PCR products were digested with the HphI restriction enzyme ( NEB ) overnight at 37°C and examined on a 2% agarose gel . Pyrosequencing of cDNA from wildtype , heterozygous and fitful P15 brains was carried out by the Transgenic Genotyping Services facility at The Jackson Laboratory . PCR amplification of Dnm1 was done with an initial denaturation step of 94°C for 5 min , followed by 50 cycles of denaturation at 94°C for 20 s , annealing at 60°C for 10 s , and extension at 65°C for 30 s . Final termination of the elongation step was carried out at 65°C for 5 min . The sequences of all of the primers are listed below . The biotinylated PCR products were prepared for pyrosequencing analysis by the use of a Vacuum Pre Workstation ( Biotage AB ) , and the sequencing reactions were carried out on a PSQ 96MA system ( Biotage AB ) as described by the manufacturer . Sequence analysis software ( Biotage AB ) was used for measurement of the peak heights . Primers: pIMR220F1 , AGCTATGCTATCAAAAATATCCA; pIMR221R1 , Biotin ACCATGTCCACACACTTGA; pIMR222S1b , CTCTTTACCCCAGACATG; pIMR223S1a , CTCTTCACACCTGACCTC . Protein extracts were made in IP lysis buffer ( 20mM Tris , 0 . 5mM EDTA , 100mM NaCl , 0 . 5% NP-40 ) with Complete-mini proteinase inhibitor mix ( Roche ) added fresh . Extracts were quantified using the Bradford reagent ( Bio-Rad ) . Extracts ( 50–100µg protein ) were diluted in Laemmli buffer , incubated at 95°C for 5 minutes , resolved by SDS-PAGE and transferred to nitrocellulose membrane . All membrane blotting steps were carried out in TBS plus Tween ( TBST ) with 5% non-fat dry milk . Blots were incubated at RT with primary antibody ( for specific dilutions see below ) for 1–2h , HRP-conjugated secondary antibody ( 1∶5000 ) for 1h and visualized with the ECL plus kit ( VWR Scientific ) . Membranes were incubated with Restore Western blot stripping buffer ( Fisher ) at 37°C for 15 min while shaking to remove antibodies for subsequent hybridization . Primary antibodies used were dynamin-1 ( 1∶1000; Affinity BioReagents , PA1-660 ) , dynamin-1 ( 1∶500; Chemicon , MAB5402 ) , dynamin 2 ( 1∶200; Santa Cruz Biotechnology , sc-6400 ) , dynamin 2 ( 1∶250; BD Biosciences , 61025 ) , dynamin 3 ( 1∶1000; Affinity BioReagents , PA1-662 ) , dynamin-1a ( 1∶500; Affinity BioReagents ) , dynamin-1b ( 1∶300; Affinity BioReagents ) . Secondary antibodies used were HRP anti-goat ( 1∶5000; Santa Cruz Biotechnology ) , HRP anti-mouse ( 1∶5000; Thermo Scientific ) , HRP anti-rabbit ( 1∶5000; BioRad ) and HRP anti-chicken ( 1∶5000; Santa Cruz ) . Protein extracts made with IP lysis buffer were used for oligomerization assays . 50 or 100µg of protein was incubated with 0 or 20mM EDC ( 1-Ethyl-3-[3-dimethylaminopropyl]carbodiimide Hydrochloride; Pierce ) in a final constant volume between samples for 45 minutes at RT in the dark . Samples were then diluted in Laemmli buffer , incubated at 95°C for 5 minutes , resolved by SDS-PAGE , transferred to nitrocellulose membrane and processed as for Western blots ( see above ) . For cryosection staining , sections were fixed with 4% paraformaldehyde , 4% sucrose in PBS for 15 minutes at RT . Slides were washed 3 times with PBS and blocked and permeabilized in PBS , 3% BSA and 0 . 5% Triton-X . The slides were incubated with primary antibody ( anti-Calbindin; Swant , CB38 ) diluted in block overnight at 4°C , washed three times with PBS-T and incubated with secondary antibodies diluted in block for 1 hour at RT . Cells were washed three times with PBS , stained for 5 minutes with DAPI , washed and mounted with GelMount ( Biomeda ) . To analyze the GFP-Purkinje cells , brains from F2 homozygous fitful and controls were dissected at 17 days of age for fixation in Z-fix buffer ( Anatech , Battle Creek , MI , USA ) for 3–4 h . Vibrotome sagittal sections ( 60–100 µm ) were mounted onto slides with Clear-mount ( Zymed , San Francisco , CA , USA ) . The sections were viewed using a Leica SP5 AOBS spectral confocal microscope , with a 63× , 1 . 3 NA glycerol immersion objective . Excitation was at 488 nm , with emission collection optimized to detect green fluorescence . For electroconvulsive testing , we followed procedures described previously with some modifications [43] , [44] . Briefly , mice were restrained , a drop of anesthetic containing 0 . 5% tetracaine and 0 . 9% NaCl was placed onto each eye and a fixed electrical current was applied via silver transcorneal electrodes using an electroconvulsive stimulator ( Ugo Basile model 7801 ) . For acute electroconvulsive threshold ECT , the stimulator was set to produce rectangular wave pulses with the following parameters: 299 Hz , 0 . 2 s duration , 1 . 6 ms pulse width . The threshold to a minimal clonic forebrain seizure was determined by testing individual mice approximately daily until the endpoint was observed and group means were calculated . For determining the latency to kindling , the same electrodes were used with parameters that were estimated to yield a similar integrated RMS as described previously by others using sinusoidal waveforms [45]; 299 Hz , 3 . 0 s duration , 0 . 2 ms pulse width , 4 . 5 mA . Individual mice were challenged once daily until a partial seizure was observed , and group means were calculated to determine mean latency . Experiments were performed as described in [46] , complied with national animal care guidelines and were approved by the University of Goettingen Board for animal welfare and the animal welfare office of the state of Lower Saxony . In brief , animals were anaesthetized intraperitoneally with a combination of ketamine ( 125 mg/kg ) and xylazin ( 2 . 5 mg/kg ) and the core temperature was maintained constant at 37°C . For stimulus generation , presentation and data acquisition we used the TDT III Systems ( Tucker-Davis-Technologies , Ft Lauderdale , FL ) run by BioSig32 software ( TDT ) . Tone bursts ( 4/8/12/16/24/32 kHz , 10 ms plateau , 1 ms cos2 rise/fall , calibrated and provided in dB SPL rms ) were applied at 20 Hz in the free field ipsilaterally using a Monacor DT-119 ( Monacor , Bremen , Germany ) . The difference potential between vertex and mastoid intradermal needles was amplified ( 5×104-times ) , filtered ( low pass: 4 kHz , high pass: 400 Hz ) and sampled at a rate of 50 kHz for 20 ms , 2×2000 times to obtain two mean ABR traces for each sound intensity . Hearing threshold was determined with 10 dB precisions as the lowest stimulus intensity that evoked a reproducible response waveform in both traces , as judged by visual inspection . Acute brain slices were prepared from Ftfl homozygotes and wildtype littermates at P14 using methods described previously [47] . Briefly , mice were anesthetized with tribromoethanol ( 250 mg/kg , i . p . ) and decapitated . Brains were quickly removed and transferred into ice-cold solution containing ( in mM ) : 210 sucrose , 3 . 0 KCl , 1 . 0 CaCl2 , 3 . 0 MgSO4 , 1 . 0 NaH2PO4 , 26 NaHCO3 , 10 glucose , saturated with 95% O2 and 5% CO2 . Coronal slices were cut at 300 µm on a vibratome ( VT 1000s , Leica ) and kept in artificial cerebral spinal fluid ( ACSF ) containing ( in mM ) : 124 NaCl , 3 . 0 KCl , 1 . 5 CaCl2 , 1 . 3 MgSO4 , 1 . 0 NaH2PO4 , 26 NaHCO3 , and 20 glucose , saturated with 95% O2 and 5% CO2 at room temperature ( 21–23°C ) . Slices were allowed to recover for at least 1 hr before any recording . Recordings were made at 32–34°C using whole-cell patch-clamp techniques . Each slice was transferred to a submerge-type chamber where it was continuously exposed to ACSF heated to 32–34°C , saturated with 95% O2 and 5% CO2 , and flowing at rate of 2 . 0±0 . 2 ml/min . Whole-cell patch clamp recordings were made at the soma of layer 5 pyramidal neurons of the somatosensory cortex using a 40× water immersion objective ( 40×/0 . 80W , Nikon ) and infrared Nomarski optics . Patch pipettes were pulled from thick wall borosilicate glass ( 1 . 5/0 . 84 mm , WPI ) on a horizontal puller ( P-97 , Sutter Instruments ) . Resistance of electrodes was between 2 and 4 MΩ . Liquid junction potential was not corrected . Seal resistance was greater than 2 GΩ . Recordings were made with a Multiclamp 700B amplifier ( Molecular Devices ) . The series resistance ( Rs ) , usually between 8 and 14 MΩ , was monitored throughout the recording , and data were discarded when Rs varied by 20% or more over the course of the recording . GABAergic IPSCs were selectively recorded by blocking ionotropic glutamate receptors with 20 µM DNQX ( 6 , 7-dinitro-quinoxaline-2 , 3-dione ) and 1 mM kynurenic acid . For evoked IPSCs , the pipette solution contained ( in mM ) : 110 Cs methylsulfate , 20 TEA-Cl , 15 CsCl , 4 ATP-Mg , 0 . 3 GTP-Na , 4 QX-314 , 0 . 5 EGTA , and 20 HEPES ( pH 7 . 2 , 270–280 mOsm ) . A pair of twisted nichrome microwires ( 38 mm in diameter , A-M Systems ) were placed in layer V about 200 mm away from the recorded neuron . IPSCs were evoked by current pulses ( 20–400 mA , 50 ms ) . For mIPSC recording , the pipette solution contained ( in mM ) : 130 KCl , 4 ATP-Mg , 0 . 3 GTP-Na , 0 . 5 EGTA , and 20 HEPES ( pH 7 . 3 , 270–280 mOsm with sucrose ) . Quantal events were recorded in the presence of tetrodotoxin ( TTX , 0 . 4 µM ) . DNQX and QX-314 were obtained from Tocris; all other chemicals were obtained from Sigma-Aldrich USA . Experiments were conducted using the AxoGraph X program ( AxoGraph Scientific ) with a PowerMac G5 connected to an ITC-18 interface . Data were filtered at 4 kHz and digitized at 16 kHz . Data were analyzed using AxoGraph X and IgorPro ( WaveMetrics ) . Quantal IPSCs were detected using variable amplitude template functions with the rise time set at 0 . 5 ms and decay times . The detection threshold was set at four times the standard deviation of baseline noise . At least 100 isolated events for each cell were aligned and averaged to give the mean response .
|
Epilepsy , a group of chronic disorders characterized by recurrent seizures , results from abnormal , synchronized neuronal activity in the brain . The mouse represents a powerful system to study novel mutations that model neurological disease , including epilepsy . Here we describe a new mouse mutation ( “fitful” ) in the gene encoding dynamin-1 . Fitful mice have recurrent seizures and other neurological defects , including impaired hearing . Dynamin-1 is very well studied , but has yet to be linked to neurological disease . Dynamin-1 is a large multimeric enzyme that functions in membrane fission , primarily of vesicles after they release neurotransmitter at neuronal synapses . Fitful occurs in the region of dynamin-1 that is important for self-assembly of single dynamin subunits into the multimers required for enzymatic function . We show that fitful interferes with dynamin-1 self-assembly and with endocytosis . Moreover , the mutation resides in one of two alternate forms of dynamin-1 and affects what may be a necessary shift during brain development , with the expression of the mutated form being higher after maturation in fitful mice . This particular genetic specialization is unique to vertebrate dynamin . We speculate that specialized forms of dynamin-1 are important for modifying the self-assembly process to meet the demands complex brain activity in higher organisms .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"cell",
"biology/neuronal",
"signaling",
"mechanisms",
"genetics",
"and",
"genomics/disease",
"models",
"neuroscience/neurodevelopment",
"developmental",
"biology/neurodevelopment",
"neurological",
"disorders/epilepsy"
] |
2010
|
A Missense Mutation in a Highly Conserved Alternate Exon of Dynamin-1 Causes Epilepsy in Fitful Mice
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The large tegument proteins of herpesviruses contain N-terminal cysteine proteases with potent ubiquitin and NEDD8-specific deconjugase activities , but the function of the enzymes during virus replication remains largely unknown . Using as model BPLF1 , the homologue encoded by Epstein-Barr virus ( EBV ) , we found that induction of the productive virus cycle does not affect the total level of ubiquitin-conjugation but is accompanied by a BPLF1-dependent decrease of NEDD8-adducts and accumulation of free NEDD8 . Expression of BPLF1 promotes cullin degradation and the stabilization of cullin-RING ligases ( CRLs ) substrates in the nucleus , while cytoplasmic CRLs and their substrates are not affected . The inactivation of nuclear CRLs is reversed by the N-terminus of CAND1 , which inhibits the binding of BPLF1 to cullins and prevents efficient viral DNA replication . Targeting of the deneddylase activity to the nucleus is dependent on processing of the catalytic N-terminus by caspase-1 . Inhibition of caspase-1 severely impairs viral DNA synthesis and the release of infectious virus , pointing a previously unrecognized role of the cellular response to danger signals triggered by EBV reactivation in promoting virus replication .
Post-translational modification of proteins by covalent linkage of ubiquitin ( Ub ) or ubiquitin-like proteins ( UbLs ) , such as SUMO , NEDD8 , ISG15 , regulates diverse cellular processes , including cell cycle progression , DNA repair , transcription , signal transduction and immune responses [1] , [2] . Cytosolic and nuclear proteins tagged with multiple Lys48-linked Ub moieties are targeted to the proteasome for degradation , whereas the attachment of single or multiple Ub or UbLs regulates a variety of non-proteolytic events , including protein-protein interactions and intracellular traffic [3] . Conjugation of the modifiers is accomplished by an enzymatic cascade composed of activating enzymes ( E1 ) , conjugating enzymes ( E2 ) and substrate-specific ligases ( E3 ) , and is reversed by substrate-specific cysteine or metallo-protease that control the turnover of the modification and play thereby a key role in determining the functional outcome . Although each modifier is involved in unique cellular functions , important cross-talk has been highlighted by the demonstration that NEDD8 and SUMO regulate the activity of certain ubiquitin ligases . Thus , the best characterized substrates of NEDD8 conjugation are cullins that function as scaffolds for the assembly of cullin-RING ubiquitin ligases ( CRLs ) [4] , [5] , while SUMOylation is required for substrate recognition and subsequent ubiquitination by a family of SUMO-targeted ubiquitin ligases ( STUbLs ) [6] . Furthermore , several deconjugases , including USP21 [7] , Ataxin-3 [8] PfUCH54 [9] , UCH-L1 and UCH-L3 [10] , exhibit dual specificity for Ub and NEDD8 conjugates , while SENP8 is both a NEDD8 and SUMO deconjugase [11] . The significance of these multiple specificities in the context of biological processes remains , however , undefined . Viruses rely on the host cell machinery for replication . Given the key role of Ub and UbL modifications in the regulation of cellular and immunological functions , modulation of these signaling pathways is essential for viral DNA synthesis and for the survival of the virus during acute , chronic and latent infections [12] . Two viral interference strategies have been documented in the infected cells . Viral proteins were shown to regulate the expression or capture the activity of cellular components of the Ub and UbL signaling networks and to redirect their function towards preferred cellular or viral substrates [13] . In addition , there are numerous examples of virus-encoded homologs of cellular ligases and deconjugases [14] . These viral enzymes are often multifunctional proteins that share little homology with their cellular counterparts and are therefore attractive targets for selective inhibition . Adenovirus [15] , severe acute respiratory syndrome coronavirus [16] , and all members of the herpesvirus family [17] , [18] , encode their own deconjugase . The homologs encoded in the N-terminus of the large tegument proteins of herpesviruses show very little sequence similarity but the residues implicated in the formation of the catalytic site are strictly conserved . All the tested homologs have potent ubiquitin-specific protease activity and their overexpression in transfected cells is associated with a dramatic decrease of polyubiquitinated substrates [17] , [18] . Expression of the active enzymes was confirmed during infection by human CMV ( HCMV ) [19] , [20] , murine gamma-herpesvirus 68 ( MHV-68 ) [12] , Marek's disease virus ( MDV ) [21] , and pseudorabies virus ( PrV ) [22] . Although not essential for viral DNA synthesis , disruption of the catalytic function correlated with severe impairment of viral replication in in vivo models of infection [12] , [21] , [22] . The Epstein-Barr virus ( EBV ) encoded homolog , BPLF1 , has very potent ubiquitin deconjugase activity in various experimental models . Anchoring the enzymatic domain to the ER membrane [23] or injection of the purified protein in semi-intact cells [24] promoted the dislocation of ubiquitinated ERAD substrates , resulting in their stabilization in the cytosol . Overexpression of the N-terminus was associated with deubiquitination of the viral ribonucleotide reductase ( RR ) [25] and the cellular DNA polymerase processivity factor PCNA [26] , resulting in downregulation of the viral RR activity and attenuation of Polη at DNA damage sites . Furthermore , expression of the catalytically active BPLF1 was shown to correlate with deubiquitination of TRAF6 and inhibition of NF-κB signaling during productive EBV infection [27] . We have previously reported that , in addition to their deubiquitinating activity , BPLF1 and the homologs encoded by HSV1 , KSHV and MHV-68 exhibit strong activity against NEDD8 conjugates [28] . BPLF1 hydrolyzes NEDD8 conjugates in vitro and stabilizes several CRL substrates in transfected cells , including the cellular DNA-replication licensing factor CDT1 . Expression of BPLF1 alone or in the context of the productive virus cycle induced the accumulation of CDT1 and arrest of the cells in S-phase , while re-expression of CDT1 was sufficient to revert the inhibition of virus replication induced by BPLF1 knockdown . This phenotype is dependent on direct binding of BPLF1 to CRLs via interaction of the conserved helix-2 of BPLF1 with the C-terminal domain ( CTD ) of cullins , at a site that is also engaged by the CRL regulator CAND1 [29] . While the double specificity of this family of viral enzymes is experimentally documented , the importance of the ubiquitin and NEDD8-specific deconjugase activities in infected cells is not easily understood since deubiquitination or inactivation of the specific ubiquitin ligase may have similar effects on individual substrates . Thus , it remains unclear whether both the ubiquitin- and NEDD8-specific deconjugase activities operate during virus replication and , if so , how the different functions are regulated or compartmentalized in the infected cells . Here we report that induction of the productive virus cycle has no appreciable effects on the global levels of protein ubiquitination but is accompanied by a BPLF1-dependent decrease of cullin neddylation and stabilization of nuclear CRL substrates . Targeting of catalytic N-terminus of BPLF1 to the nucleus is dependent on cleavage by caspase-1 , and inhibition of the caspase halts virus replication and the release of infectious virus .
The Akata-Bx1 cell line was used to study the contribution of the Ub- and NEDD8-specific deconjugase activities of the EBV large tegument protein BPLF1 to the productive virus cycle . Treatment of Akata-Bx1 with anti-IgG antibodies promotes upregulation of the lytic cycle transactivator BZLF1 , followed in temporal succession by the expression of immediate early , early and late viral gene products ( Supplementary , Figure S1 ) . Conjugated and free Ub and NEDD8 were quantified in western blots probed with specific antibodies using cells lysates made in the presence of cysteine protease inhibitors ( Figure 1 ) . The levels of conjugated and free Ub remained virtually unchanged over time ( Figure 1A and 1B ) , whereas , consistent with the occurrence of deneddylation , the conjugated NEDD8 progressively decreased in parallel with increase of free NEDD8 ( Figure 1C and 1D ) . In order to assess the involvement of BPLF1 , a previously characterized specific shRNA [28] was transfected in Akata-Bx1 before induction of the productive cycle . As shown in Figures 2A and 2B , the effect was abrogated in cells expressing the BPLF1 specific shRNA , confirming that the phenotype is dependent on BPLF1 expression and supporting the conclusion that endogenous enzyme acts as a deneddylase during virus replication . Transfection of the catalytically active BPLF1 in HeLa cells promotes cullin deneddylation and their proteasomal degradation [29] . We asked therefore whether this phenotype is reproduced when the endogenous enzyme is expressed during virus replication . As illustrated by the representative western blot shown in Figure 3A , induction of the productive virus cycle was accompanied by a gradual decrease of the Cul1 , Cul3 , Cul4A and Cul5 specific bands in Akata-Bx1 . This was not due to a global impairment of protein synthesis since neither Cul2 , nor the CRL subunit RBX1 were affected . Furthermore , the decrease was rescued by treatment with MG132 confirming that cullins are degraded by the proteasome ( Figure 3B ) . This finding is consistent with a scenario where the inactivation of CRLs by BPLF1-mediated deneddylation of cullins , and their subsequent proteasomal degradation , are key requirements for efficient virus replication . However , the failure to degrade Cul2 is surprising since the BPLF1 binding site on cullins is highly conserved [29] . To explore the possible cause of this observation , the abundance of Cul1 , Cul2 , Cul3 , Cul4A and Cul5 was monitored over time in the nucleus and cytoplasm of the induced cells . The fractionation procedure was validated by probing of western blots with antibodies to PARP , histone H1 and β-actin . In line with their known subcellular localization , PARP and H1 were exclusively detected in the nuclear fractions , whereas β-actin was enriched in the cytoplasmic fraction ( Figure 3C ) . Variable amounts of nuclear and cytoplasmic cullins were detected in untreated Akata-Bx1 , with prevalent nuclear localization of Cul1 , Cul3 , Cul4A and Cul5 , whereas Cul2 was detected almost exclusively in the cytoplasmic fraction ( Figure 3C ) . Induction of the productive virus cycle was accompanied by a progressive decrease of nuclear pool of Cul1 , Cul3 , Cul4A and Cul5 , whereas the amount of proteins detected in the cytoplasm remained unchanged throughout the observation period ( Figure 3C and 3D ) . There was no detectable change in the expression of cytoplasmic Cul2 , further supporting the conclusion that only nuclear cullins are affected . We then monitored the abundance of known nuclear and cytoplasmic CRL substrates . In agreement with the destabilization of the ligases , induction of the productive cycle was accompanied by the accumulation of several nuclear substrates of CRL1 and CRL4A , including p21 , p27 , CDT1 and Cdc25A , whereas two cytosolic substrates of CRL2 , the Rho GTP exchange factor VAV [30] , and the hypoxia induced factor HIF1α that is continuously degraded in normoxic conditions [31] , were not affected ( Figure 4A and 4B ) . IκBα , a cytosolic substrate of CRL1-βTRCP , was progressively degraded , confirming that the ligase is inactivated only in the nucleus . The involvement of BPLF1 in the degradation of nuclear cullins and stabilization of nuclear CRL substrates was confirmed by shRNA knockdown ( Figure 4C ) . Thus , expression of the BPLF1 specific shRNA rescued the downregulation of Cul1 , Cul3 , Cul4A and Cul5 and promoted destabilization of their nuclear substrates p21 , p27 , CDT1 and Cdc25A , whereas the levels of Cul2 , VAV and HIF1α ( not shown ) remained unchanged . Interestingly , the levels of IκBα were significantly increased in cells expressing the BPLF1 specific shRNA suggesting that the viral protein may indirectly regulate the activity of NFκB . We have previously shown that the capacity of BPLF1 to promote the deneddylation and degradation of cullins is dependent on binding to cullins at a site overlapping with the binding site of the regulator CAND1 . The interaction is inhibited by overexpression of the N-terminus of CAND1 , which rescues cullin deneddylation and degradation [29] . In order to assess whether this regulatory interaction may operate during virus replication , the productive cycle was induced in Akata-Bx1 cells transiently transfected with plasmids expressing Myc-tagged CAND1 or the CAND1 N-terminus that compete for BPLF1 binding to cullins , or , as controls , the CAND1 C-terminus that binds to the opposite end of the cullin scaffold , and the empty vector ( Figure 5A ) . Expression of comparable amounts of the transfected proteins was confirmed in western blots probed with a Myc-specific antibody ( Figure 5A , upper panels ) . In line with the above documented effects , low levels of Cul1 , Cu4A and Cul5 and high levels of the CRL substrate CDT1 were detected upon induction of the productive cycle in cells transfected with the empty vector . The degradation of cullins and stabilization of CDT1 were reversed in cells expressing the full length or the N-terminus of CAND1 that compete for binding of BPLF1 , whereas the C-terminus of CAND1 had no effect ( Figure 5A ) . To assess the functional significance of this finding , the efficiency of viral DNA replication was measured by Q-PCRs in Akata-Bx1 transfected with CAND1 or the deletion mutants using primers specific for unique sequences in the BZLF1 and EBNA1 coding genes ( Figure 5B ) . Induction of the productive cycle was associated with more than 10-fold increase of viral DNA content in cell transfected with the empty vector or the CAND1 C-terminus while viral DNA replication was strongly impaired in cells expressing the full-length CAND1 or the CAND1 N-terminus . It is noteworthy that only the full-length CAND1 that blocks both the N-terminal and C-terminal domains of cullins regulates the neddylation cycle in non-infected cells . Thus , the capacity of the N-terminal domain to fully reverse the inactivation of CRLs in infected cells is consistent with a mechanism of action based on inhibition of the binding of BPLF1 to cullins , and identifies CAND1 as a potent and specific cellular inhibitor of EBV replication . The large tegument proteins of herpesviruses are huge proteins predominantly localized in the cytoplasm of the infected cells where they play a key role in the delivery of viral DNA to the nuclear pore during primary infection and in the secondary envelopment and egress of mature virions [32] . However , the preferential effect on nuclear cullins and their substrates implies that the enzymatic activity of endogenous BPLF1 is compartmentalized to the nucleus . To find a possible cause of this puzzling observation , the subcellular localization of BPLF1 was investigated using a polyclonal rabbit serum raised against the catalytic N-terminus ( amino acids 1-325 ) . To confirm recognition of the active enzyme , lysates of untreated and induced Akata-Bx1 were labeled with the HA-Ub-VS and FLAG-NEDD8-VS functional probes that covalently bind to the catalytic cysteine . Western blots of anti-HA and anti-FLAG immunoprecipitates were then probed with antibodies to HA , FLAG and BPLF1 . As illustrated by the representative blots shown in Figure 6A , the anti-HA and anti-FLAG antibodies detected two de-novo expressed enzymatic activities associated with polypeptides of >300 kD and approximately 38 kD in the lysates of induced cells . Probing of parallel blots with affinity purified antibodies to BPLF1 confirmed that the high molecular weight species corresponds to the full-length BPLF1 , while the 38 kD species is likely to represent an approximately 25 kD N-terminal catalytic domain cross-linked to the 11 kD probe . Prediction algorithms were then used to screen the amino acid sequence of BPLF1 for the presence of cleavage sites for known cytosolic endo-peptidases . Several putative caspase-cleavage sites were identified in the first 2000 amino acids of BPLF1 ( Supplementary , Figure S2 ) . In particular , a high-score caspase-1 cleavage site in position Asp222 may generate a catalytically active fragment of the observed size . To test whether BPLF1 is cleaved by capsase-1 , the productive cycle was induced in Akata-Bx1 treated with the pan-caspase inhibitor ZVAD-FMK , and the specific caspase-1 inhibitors YVAD-CHO and small molecule VX-765 . Cell lysates collected after 48 h were labeled with HA-Ub-VS ( not shown ) and FLAG-NEDD8-VS . As shown in Figure 6B , both the full length and the 38 kD species were readily detected by the anti-FLAG antibody , although the 38 kD species was significantly stronger , which may be due to more efficient cross-linking of the probe or to poorer transfer of the high molecular weight full length enzyme . The intensity of the 38 kD fragment was strongly decreased when the induction was carried out in the presence of caspase inhibitors while the intensity of the full length species was slightly but consistently increased , confirming that the catalytic N-terminus of BPLF1 is cleaved by caspase-1 . Having established the specificity of the antibody , we then turned to investigate the subcellular localization of BPLF1 . Staining of Akata-Bx1 with the affinity purified rabbit serum revealed a diffuse cytoplasmic and nuclear fluorescence 48 h after induction ( Figure 6C ) , with essentially no background in cells stained with TRITC-conjugated secondary antibody alone . The specificity of the staining was confirmed by its virtual abrogation in induced cells expressing a BPLF1-specific shRNA . The nuclear fluorescence was virtually abolished when the induction was performed in the presence of the pan-caspase inhibitor ( not shown ) or the caspase-1 inhibitors YVAD-CHO ( Figure 6C , 6D ) and VX-765 ( not shown ) . Thus , accumulation of the catalytic N-terminus of BPLF1 in the nucleus is dependent on cleavage of the cytosolic protein by caspase-1 . Since the enzymatic activity of BPLF1 is required for efficient EBV DNA replication [27] , [28] , we tested whether the latter is affected by inhibition of caspase-1 . In line with the constitutive IL-1 production of B-lymphoma cell lines [33] , [34] , two bands of approximately 48 kD and 20 kD , corresponding to the pro-caspase and active caspase-1 , were detected in western blots of untreated Akata-Bx1 probed with a caspase-1 specific antibody ( Figure 7A ) . The intensity of the 20 kD band increased upon induction of the productive cycle , which was prevented by addition of the caspase-1 inhibitors YVAD-CHO ( Figure 7A ) and VX-765 ( not shown ) . Inhibition of caspase-1 did not affect the expression of the viral transactivator BZLF1 , nor the subsequent expression of the early antigen BORF2 and late antigen gp350/220 ( Figure 7A ) . Nevertheless , the treatment abrogated the BPLF1-dependent degradation of Cul1 and Cul4A and consequent stabilization of the CRL substrates CDT1 and Cdc25A ( Figure 7B ) . In line with the requirement of CDT1 stabilization for efficient viral DNA replication [28] , the yield of viral DNA was significantly impaired ( Figure 7C ) . Similar levels of inhibition were achieved in cells treated with the pan-caspase inhibitor ZVAD-FMK and the caspase-1 specific inhibitors YVAD-CHO and VX-765 . Thus , caspase-1 appears to be the sole responsible for BPLF1 processing . In the final set of experiments we asked whether the effect of caspase-1 is restricted to Akata-Bx1 cell line . To this end , the productive virus cycle was induced by culturing the prototype EBV producer cell line B95 . 8 in medium supplemented with 2% FCS , 20 ng/ml TPA in the presence or absence of increasing concentrations of VX-765 . As shown in Figure S4 , the marmoset cell line expresses a conserved caspase-1 species that is detected by the cross-reactive antibody used in our experiments , and the intensity of a polypeptide of approximately 20 kD , corresponding to the active caspase-1 , increased upon induction of the productive cycle . Inhibition of caspase-1 activity by addition of VX-765 resulted in a dose-dependent inhibition of viral DNA synthesis , with maximal inhibition observed in the presence of 20 µM VX-765 ( Figure 7D ) . This was paralleled by a corresponding dose-dependent inhibition of the release of infectious virus assessed by the capacity of spent supernatants to induce the expression of EBNA2 in the EBV negative BJAB cell line ( Figure 7E ) .
Our present study addresses an ongoing debate on the contribution of the deneddylase encoded in the large tegument protein of herpesviruses to virus replication , and provides a clear example of how , under physiologic conditions of expression , compartmentalization and binding to relevant substrates may determine the function of an enzyme with double specificity for both Ub and UbL conjugates . Several lines of evidence support the notion that endogenously expressed BPLF1 promotes EBV replication by acting as a deneddylase . The recombinant enzyme has potent ubiquitin deconjugase activity in vitro , and overexpression of the catalytic N-terminus induces a global decrease of ubiquitin conjugates in transfected cells [24] , [28] . However , induction of the productive cycle was not accompanied by significant changes in the amount of ubiquitinated proteins or free ubiquitin in Akata-Bx1 , whereas neddylated proteins decreased and free NEDD8 increased in a BPLF1-dependent manner ( Figures 1 and 2 ) . While inconsistent with the potent deconjugase activity of BPLF1 in experimental settings , our failure to detect appreciable change in the global levels of ubiquitination during productive infection does not formally exclude that the viral enzyme might selectively target few ubiquitinated substrates . Yet , it should be stressed that evidence for the capacity of BPLF1 to deubiquitinate specific substrates , such as the EBV ribonucleotide reductase [35] , PCNA [26] and TRAF6 [27] , was in all cases obtained by overexpressing the catalytic N-terminus in transfected cells . In the experiments of Saito et al . reconstitution of the viral enzyme in cells infected with a mutant EBV strain that lacks BPLF1 was associated with deubiquitination of TRAF6 [27] . However , induction of the productive virus cycle was associated with strong TRAF6 deubiquitination also in the absence of BPLF1 , suggesting that other factors are primarily responsible for this effect and for the subsequent downregulation of NF-κB target genes . This interpretation is also supported by our findings that the NFκB inhibitor IκBα was stabilized upon silencing of the endogenous BPLF1 in induced Akata-Bx1 ( Figure 4C ) , which may be explained by failure to phosphorylate IκBα due to a BPLF1-independent inhibition of TRAF6 signaling associated with replicative cycle . Similar to the effect of BPLF1 in transfected cells [28] , [29] , we found that endogenously expressed BPLF1 is required for the selective degradation of cullins in productively infected cells and for the stabilization of several CRL substrates that regulate the cell cycle and facilitate EBV DNA replication ( Figures 3 and 4 ) . The reversion of this phenotype by overexpression of the CRL regulator CAND1 ( Figure 5 ) strengthens the notion that BPLF1 plays a key role in cullin deneddylation and degradation under physiological conditions of expression . We have previously reported that the conserved N-terminal domains of BPLF1 and CAND1 share a binding site on the C-terminus of cullins [29] . CAND1 regulates the activity of CRLs by sequestering cullins that are deneddylated after substrate ubiquitination , which promotes the exchange of substrate-adaptor modules , broadening the substrate repertoire and allowing rapid adaptation to a variety of metabolic conditions [36] . Cullins are the only known binding partners of CAND1 and it is therefore reasonable to assume that the reduced EBV DNA replication in cells overexpressing CAND1 , and in particular the truncated CAND1 N-terminus that lacks the protein exchange function of the intact protein , is due to inhibition of the binding of BPLF1 of cullins . Collectively these findings support the notion that binding to the neddylated substrate determines the activity of this potentially promiscuous enzyme under physiological conditions of expression . This has two important implications . First , it underscores the possibility of experimental artifacts due to altered stoichiometry of the interacting partners in transfected cells . More importantly , it emphasizes the likelihood that interference with binding may have substantial downstream effects . In the case of EBV infection this could offer a new target for specific inhibition of virus replication . We have shown that endogenously expressed BPLF1 acts on nuclear cullins and stabilizes nuclear CRL substrates while cytosolic CRLs and their substrates are not affected . This nuclear compartmentalization is dependent on cleavage of the catalytic N-terminus by caspase-1 ( Figure 6 ) . The processed fragment does not contain a putative nuclear localization signal but the size is sufficiently small for free diffusion through the nuclear pore that accommodates particles of up to 40 kD . Processing of BPLF1 is likely to be a key regulatory event in virus replication . It is noteworthy that a catalytically active N-terminal fragments of the BPLF1 homolog UL36 has been detected in cells infected with HSV1 [17] , and preliminary results suggest that blockade of caspase-1 has a comparable inhibitory effect on HSV1 replication ( Gastaldello et al . unpublished ) . Although processing of the tegument protein was not detected in cells infected with HCMV [19] , [20] , KSHV [37] or MHV-68 [38] , and the full length enzymes encoded by these viruses are active DUBs , we have previously shown that the catalytic N-terminus of KSHV and MHV-68 share the cullin-binding capacity of BPLF1 and inactivate CRLs in transfected cells [28] , [29] . It remains to be seen whether the failure to detect processing of some tegument proteins is explained by different experimental procedures or whether it might reflect true differences in the interaction of these viruses with the infected cells . In the case of BPLF1 , it is tempting to speculate that , in addition to facilitating nuclear accumulation , cleavage of the catalytic N-terminus may also activate the viral enzyme . This possibility is supported by the observation that the band corresponding to the processed BPLF1 bound to the Ub-VS and NEDD8-VS functional probes was significantly stronger than the full length protein in lysates of induced cells ( Figure 6A and 6B ) . Furthermore , cullins were not degraded in the cytosol , suggesting that the cytosolic enzyme is either inactive or cannot reach its targets . It is also possible that , while acting as a deneddylase in the nucleus , BPLF1 , or perhaps the unprocessed form of the enzyme , may act as an ubiquitin-specific deconjugase in the cytoplasm of the infected cells . Experimental testing of this possibility remains an interesting focus for future work , pending the identification of substrates that are affected under physiologic conditions of expression . In this context it is noteworthy that cytosolic tegument proteins associated with the virion play important roles in the early and late phases of infection by contributing to the delivery of viral DNA to the nuclear pore and to the secondary envelopment and egress of mature virions [32] . Conceivably , a different set of cellular and viral substrates may be affected during these phases of the infection . An unforeseen outcome of our study is the demonstration that the infected cell may regulate the efficiency of virus replication via caspase-1 mediated processing of BPLF1 . Caspase-1 is well known for its role as the converging target of danger signals such as physical stress , extracellular ATP , bacterial and viral products , that are detected in the cytosol by sensing molecules and adaptors that promote the assembly of a multisubunit complex known as the inflammasome [39] . The inflammasome triggers the self-activation of caspase-1 , which in turn mediates the maturation of pro-inflammatory cytokines like interleukin ( IL ) -1β and IL-18 , and executes a rapid program of cell death known as pyroptosis [40] . Additional cellular substrates of caspase-1 include the Sterol Regulatory Element Binding Proteins ( SREBPs ) that are activated following changes in intracellular ions [41] . Thus , caspase-1 plays pleyotropic roles in the activation of innate and adaptive immune responses as well as in processes that link changes of the intracellular environment with lipid metabolism , membrane biogenesis and cell survival . Many viruses are known to inhibit the inflammasome or directly block the activity of caspase-1 in order to counteract antiviral responses [42] . Our findings highlight a previously unrecognized role of the cellular response to danger signals triggered by EBV reactivation in promoting rather than inhibiting virus replication . This further illustrates the complexity and multilayer regulation of the interaction of EBV with its host where the capacity of the virus to adapt to and exploit physiologic cellular responses underlies the establishment of life-long persistent infections .
DL-Dithiothreitol ( DTT , D0632 ) , N-Ethylmaleimide ( NEM , E1271 ) , Phenylmethanesulfonylfluoride ( PMSF , P7626 ) , Iodoacetamide ( I1149 ) , IGEPAL CA-630 ( NP40 , I3021 ) , Sodium deoxycholate monohydrate ( DOC , D5670 ) , Triton X-100 ( T9284 ) , bovine serum albumin ( BSA , A7906 ) , 1 , 10-phenanthroline ( o-phe , P9375 ) , Sodium dodecyl sulfate ( SDS , L3771 ) , Tween-20 ( P9416 ) , Ethylenediaminetetraacetic acid disodium salt dehydrate ( EDTA-E4884 ) , Trizma base ( Tris , 93349 ) , Sodium butyrate ( NaBut , B5887 ) , Monoclonal Anti-HA conjugated agarose ( A2095 ) , Anti-FLAG conjugated agarose ( A2220 ) , Influenza hemagglutinin ( HA ) peptide ( I2149 ) , 3xFLAG peptide ( F4799 ) were from Sigma Aldrich ( St . Louis , MO ) . 12-O-Tertadecanoylphorbol-13-Acetate ( TPA , 4174 ) was from Cell Signaling Technology ( Danvers , MA ) . Complete protease inhibitors cocktail tablets ( protease inhibitors ) from Roche Diagnostic ( Mannheim , Germany ) . HA-Ubiquitin-Vinyl Sulfone ( HA-Ub-VS , U-212 ) , FLAG-NEDD8-Vinyl Sulfone ( FLAG-NEDD8-VS , UL-803 ) from Boston Biochem ( Boston , MA ) . ZVAD-FMK , General Caspase Inhibitor ( 550377 ) was from BD Biosciences ( Bedford , MA ) . Caspase-1 inhibitor I , cell-permeable ( 400011 ) was from EMD Millipore ( Billerica , MA ) . The caspase-1 inhibitor VX-765 ( CT-VX765 ) was from ChemieTek ( Indianapolis , IN ) . Antibodies and their suppliers were: β-actin ( AC-15 , 1∶5000 ) , RBX1 ( 1∶1000 ) from Sigma Aldrich; CDT1 ( sc-28262 , 1∶1000 ) , Cdc25A ( sc-7157 , 1∶1000 ) , EBV EA-R p85 ( BORF2 , sc-56979 , 1∶1000 ) , HIF1α ( H206 , 1∶1000 ) and EBV zebra ( BZLF1 , sc-53094 ) , from Santa Cruz Biotechnology ( Santa Cruz , CA ) ; Cul1 ( ab53049 , 1∶1000 ) , Cul2 ( ab1870 , 1∶1000 ) , Cul3 ( ab72187 , 1∶1000 ) , Cul4A ( rabbit polyclonal ab2618 , 1∶10000 ) , Cul5 ( ab33053 , 1∶1000 ) , Histone H1 ( ab62884 , 1∶500 ) and VAV-GEF ( ab40875 , 1∶1500 ) from AbCam ( Cambridge , MA ) ; hCAND1 ( MCA4466Z , 1∶1000 ) from AbD Serotec ( Oxford , UK ) ; p21/Cip1/WAF1 ( 610233 , 1∶1000 ) from BD Bioscience ( Bedford , MA ) ; Ubiquitin ( Z0458 , 1∶5000 ) , p27/Kip1 ( M7203 , 1∶1000 ) and anti-human IgG polyclonal Rabbit antibodies ( A0423 , 1∶50 ) from DAKO ( Glostrup , Denmark ) ; NEDD8 ( 1∶1000 ) from Millennium Pharmaceuticals ( Takeda Oncology Co , Cambridge , MA ) ; Caspase-1 ( 06-503 , 1∶1000 ) from EMD Millipore ( Billerica , MA ) ; Caspase-3 ( 06735 , 1∶1000 ) , Caspase-9 ( 05572 , 1∶1000 ) from Upstate Biotechnology ( Lake Placid , NY ) ; Poly- ( ADP-ribose ) -polymerase ( PARP ) ( BML-SA250 , 1∶1000 ) from Enzo Life Science ( Lörrach , Germany ) . A mouse monoclonal antibody to EBV-gp350/220 was a kind gift of Jaap M . Middeldorp , CCA-VUMC , Amsterdam , The Netherlands . A polyclonal rabbit antibody to BPLF1 was generated by immunization with purified GST-BPLF1 amino acid 1-325 ( ASLA Biotech , Riga , Latvia ) . The antibody fraction was affinity purified from serum obtained from the third immunization , by NHS-activated sepharose ( 17-0906-02 , GE Healthcare , Uppsala , Sweden ) conjugated with HIS-BPLF1 1-325 . After elution with 2M Glycine-HCl pH 2 . 2 , and neutralization with 1 M Tris base , the antibody was used in western blot at dilution 1∶5000 and in immunofluorescence at dilution 1∶100 . Plasmids encoding a BPLF1 specific shRNA [28] , and Myc-tagged full-length human CAND1 , the CAND1 C-terminus ( CAND1-C ) and N-terminus ( CAND1-N ) [29] were described previously . Recombinant lentiviruses were produced in HEK293T cells transfected with the recombinant pLKO . 1 expressing a control scrambled or BPLF1-specific shRNA and the packaging plasmids , psPAX2 and pMD2 . G [43] ( Addgene , Dr . Didier Trono , EPFL Lousanne , Switzerland ) by Calcium Phosphate precipitation and supernatant containing viral particles was collected after 48 h . Virus titers were assessed by QuickTiter lentivirus titer kit , a HIV p24 specific ELISA ( Cell Biolabs Inc . , San Diego , CA ) . Akata-Bx1 cells that carries a recombinant EBV where the thymidine kinase gene was replaced by a CMV immediate early promoter driven GFP [44] were cultured in Roswell Park Memorial Institute Medium ( RPMI-1640 , R8758 SIGMA-Aldrich , UK ) , supplemented with 10% Fetal Calf Serum ( 10270 , GIBCO-Invitrogen , Carlsbad CA ) , Penicillin-Streptomycin ( P0781 , SIGMA-Aldrich , UK ) , L-Glutamine ( G7513 , SIGMA-Aldrich , UK ) ( complete medium ) and Geneticin ( 10131-027 , 200 µg/ml , GIBCO-Invitrogen , Carlsbad CA ) . Infection with recombinant lentiviruses was performed at m . o . i . 2 . 55E10 in the presence of 8 mg/ml Polybrene ( AL-118 , Sigma Aldrich ) . Induction of the productive virus cycle was initiated 24 h after infection . The cells were transfected with the Cell Line Nucleofector Kit V ( AMAXA , Lonza Group , Ambroise , France ) . The productive virus cycle was induced in Akata-Bx1 by incubating cell pellets for 1 h at 37°C with polyclonal rabbit anti-human IgG ( 1∶50 , DAKO , Denmark ) and monitored by the increased of GFP fluorescence or by probing western blots with antibodies specific for the EBV transactivator BZLF1 . For induction of the productive cycle in the B95 . 8 cell line the cells were placed in a six well plate at the density of 5×104 cells/ml in 5 ml medium supplemented with 2% FCS and 20 ng/ml TPA and the spent supernatant was harvested after 2 weeks [45] . Where indicated , the caspase-1 inhibitor VX-765 was added to the culture medium . Quantitative-PCR was performed on DNA extracted from the cell pellets and culture supernatant . Total DNA was purified with the DNAZol reagent ( Invitrogen ) and EBV DNA content was assayed by qPCR with the KAPA SYBR FAST qPCR Kit ( KK4604 , KAPA Biosystems , Cape Town , South Africa ) and an AbiPrism 7000 Sequence detection system using 100 ng of DNA and the probes: EBNA1: 5′GGACGTGGAGAACAGTCATC3′/5′CACTCCTGCCCTTCCTCACC3′ , product 364 bp; BZLF1: 5′CACTACCAGGTGCCTTTTGT3′/5′GAGACTGGGAACAGC TGAGG3′ , product 364 bp; GAPDH: 5′AAGGTCGGAGTCAACGGATT3′/5′CTCCTGGAAGATGGTGATGG3′ , product 224 bp . The cycling conditions were: initial step 50°C 2 min , denaturation 95°C 10 min , followed by 40 cycles of 95°C for 15 seconds , 60°C for 1 min , 95°C for 15 seconds , 60°C for 20 seconds and 95°C for 15 seconds . A final extension for 10 min at 72°C and melting curve between 65°C to 90°C , 1°C/second transition were incorporated . Optical raw data were exported to Microsoft Excel for analysis . All qPCR reactions were performed in triplicate and Ct values were averaged . The fold change in the target gene relative to the GAPDH endogenous housekeeping control gene is determined by: Fold Change = 2−Δ ( ΔCt ) where ΔCt = Cttarget - CtGAPDH and Δ ( ΔCT ) = ΔCtinduced - ΔCtcontrol , according to the Minimum Information for Publication of Quantitative Real-Time PCR Experiments ( MIQE ) guidelines . Production of infectious virus was induced by culturing the B95 . 8 cell line in medium supplemented with 2% FCS and TPA in the presence or absence of the indicated concentrations of the caspase-1 inhibitor VX-765 . The presence of infectious virus in spent supernatants of the B95 . 8 cell line was assayed by infection of the EBV negative cell line BJAB . The percentage EBNA2 positive cells was assessed by immunofluorescence using the PE2 mouse monoclonal antibody ( 1∶150 , NCL-EBV-PE2 , Leica , Wetzlar , Germany ) 48 h after infection . The subcellular localization of BPLF1 was investigated by immunofluorescence in Akata-Bx1 cells 48 h after induction in the presence or absence of caspase inhibitors . Eight ×104 cells were deposited on glass slides by cytospin centrifugation , fixed with 4% paraformaldehyde and permeabilized with 0 . 5% v/v TritonX-100 in PBS for 20 min . The slides were then treated with blocking solution ( 0 . 5% BSA in PBS ) for 2 h at RT and incubated with the anti-BPLF1 antibody O/N at 4°C followed by incubation for 1 h with TRITC conjugate anti-rabbit Ig ( 1∶200 , R0270 , DAKO ) . The slides were mounted with Vectashield mounting medium containing DAPI ( H-1200 , Vector Laboratories ) and images were captured with a Zeiss LSM510 META confocal microscope and analyzed with the ImageJ 1 . 42q software ( Wayne Rasband , National Institutes of Health , USA ) . Akata-Bx1 cells were washed in cold PBS containing 0 . 2 M freshly added iodoacetamide and resuspended in hypotonic lysis buffer ( 10 mM HEPES , pH 7 . 9 , 1 . 5 mM MgCl2 , 10 mM KCl , 0 . 1% NP-40 , 1 mM DTT , 20 mM iodoacetamide , 1 mM ortho-phenantroline , 10 mM NEM and protease inhibitors cocktail . After incubation on ice for 30 min , the membranes were broken by passage through a 25–26 G needle and the nuclei were pelleted by centrifugation for 1 min at 10800 rpm . The supernatant was used as cytoplasmic fraction . The nuclei were washed three times with hypotonic buffer and lysed in buffer containing 50 mM Tris-HCl , pH 7 . 5 , 150 mM NaCl , 1% NP40 , 0 . 5% DOC and protease inhibitors cocktail . Protein concentration was measured with a Protein Assay kit ( Bio-Rad Laboratories , CA ) . Total cell lysates were prepared in lysis buffer ( 50 mM Tris-HCl pH 7 . 4 , 150 mM NaCl , 1 mM DTT , 1 mM EDTA pH 8 . 0 , 0 . 5% NP40 , 0 . 01% SDS , 20 mM NEM , 1 mM ortho-phenantroline , protease inhibitors cocktail ) and protein concentration was measured with a Protein Assay kit ( Bio-Rad Laboratories , Solna , Sweden ) . Twenty µg of cell lysate were denatured for 10 min at 100°C in loading buffer and fractionated in acrylamide Bis-Tris 4–12% gradient gel ( Invitrogen , Carlsbad , CA ) . After transfer to PVDF membranes ( Millipore , Bedford , MA ) , the filters were blocked in PBS containing 0 . 1% Tween-20 and 5% non-fat milk or 3% BSA and incubated with the primary antibodies for either 1 h at room temperature or overnight at 4°C followed by incubation for 1 h with the appropriate horseradish peroxidase-conjugated secondary antibodies . The complexes were visualized by chemiluminescence ( ECL , GE Healthcare , Uppsala , Sweden ) . Deconjugase activity was assayed by labeling with the HA-Ub-VS and FLAG-NEDD8-VS functional probes ( Boston Biochem , Boston , MA ) as described [46] . Ten ×106 cells were lysed in 300 µl of buffer containing 50 mM Tris-Cl pH 7 . 4 , 50 mM NaCl , 1 mM DTT , 1 mM PMSF , 0 . 5% NP40 , 250 mM Glucose , 5 mM MgCl2 ( lysis and labeling buffer , LLB ) followed by 20 strokes through a G30 needle . Functional labeling was performed by addition of 2 . 5 µg of HA-Ubiquitin-VS or FLAG-NEDD8-VS followed incubation for 45 min at 37°C . The cross-linked proteins were immunoprecipitated with Anti-HA-agarose or Anti-FLAG-agarose beads for 4 h at 4°C with rotation and eluted by competition with 25 µg/ml of the HA or FLAG peptides in LLB . Enzymatically active proteins were detected in western blots probed with anti-HA or anti-FLAG antibodies . Putative caspase cleavage sites were searched in the BPLF1 amino acid sequence using the GraBCas software [47] . Sites with the highest probability of cleavage were identified by setting the cut-off scores to >15 . Statistical analysis was performed using Student's t-test . P-values <0 . 05 were considered as significant .
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Viruses rely on the host cell for replication and have evolved sophisticated strategies to manipulate and harness the cellular metabolic pathways and defense responses . A better knowledge of these viral strategies will provide new targets for antiviral therapies . The N-terminus of the large tegument proteins of herpesviruses encodes an ubiquitin and NEDD8-specific deconjugase , but the function of the enzyme during virus replication is largely unknown . Here we report that , endogenously expressed BPLF1 , the homolog encoded by Epstein-Barr virus ( EBV ) , promotes a dramatic decrease of NEDD8-conjugates and the accumulation of free NEDD8 in cells entering the productive virus cycle . BPLF1 exerts its deneddylase activity in the nucleus , which promotes the accumulation of cullin-RING ligase ( CRL ) substrates that are required for efficient virus replication . Targeting of the viral enzyme to the nucleus is dependent on processing of the catalytic N-terminus by caspase-1 . Inhibition of caspase-1 severely impairs viral DNA synthesis and the release of infectious virus , pointing to an unexpected role of the cellular response to danger signals triggered by EBV reactivation in promoting virus replication .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[] |
2013
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Caspase-1 Promotes Epstein-Barr Virus Replication by Targeting the Large Tegument Protein Deneddylase to the Nucleus of Productively Infected Cells
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De novo DNA methylation and the maintenance of DNA methylation in asymmetrical sequence contexts is catalyzed by homologous proteins in plants ( DRM2 ) and animals ( DNMT3a/b ) . In plants , targeting of DRM2 depends on small interfering RNAs ( siRNAs ) , although the molecular details are still unclear . Here , we show that two SRA-domain proteins ( SUVH9 and SUVH2 ) are also essential for DRM2-mediated de novo and maintenance DNA methylation in Arabidopsis thaliana . At some loci , SUVH9 and SUVH2 act redundantly , while at other loci only SUVH2 is required , and this locus specificity correlates with the differing DNA-binding affinity of the SRA domains within SUVH9 and SUVH2 . Specifically , SUVH9 preferentially binds methylated asymmetric sites , while SUVH2 preferentially binds methylated CG sites . The suvh9 and suvh2 mutations do not eliminate siRNAs , suggesting a role for SUVH9 and SUVH2 late in the RNA-directed DNA methylation pathway . With these new results , it is clear that SRA-domain proteins are involved in each of the three pathways leading to DNA methylation in Arabidopsis .
Cytosine methylation is found in the genomes of most eukaryotes and plays a critical role in repression of transposable elements as well as in the epigenetic regulation of select genes [1]–[4] . In Arabidopsis thaliana cytosine methylation occurs in all sequence contexts , with the highest frequency occurring at CG , followed by CHG and then CHH sequences ( where H is any base other than a G ) [5] . Maintenance of CG methylation is catalyzed by MET1 , a homolog of mammalian DNMT1 [6] , [7] . DNMT1 functions at the replication fork , prefers hemi-methylated DNA as a template , and interacts with PCNA in vivo [8] . Recent studies have shown that an SRA-domain protein is required to efficiently target DNMT1 to the replication fork and to maintain high levels of CG methylation [9]–[11] . A key to this targeting in mammals was shown to involve preferential binding of the UHRF1 SRA domain to hemi-methylated CG sites [10] , which are the physiological substrates for DNMT1 that are generated after replication of methylated DNA . A plant homolog of UHRF1 , VIM1/ORTH2 , also binds methylated CG sites and is required for maintenance of DNA methylation in Arabidopsis [12] , [13] , suggesting that this pathway is widely conserved in eukaryotes . In Arabidopsis CHG methylation is primarily catalyzed by CHROMOMETHYLASE 3 ( CMT3 ) , which is also dependent on an SRA-domain protein , KRYPTONITE ( KYP/SUVH4 ) [14] , [15] . In this case , KYP is the main enzyme catalyzing methylation of histone H3 lysine 9 , providing a binding site for CMT3 through its chromodomain [16] . Two other SRA-SET proteins ( SUVH5 and SUVH6 ) , which also methylate H3 lysine 9 , contribute to this pathway as well [17]–[19] . Just as CMT3 binds to the mark put on by KYP , KYP and SUVH6 have been shown to bind directly to DNA methylated at CHG sites through their SRA domains , leading to a reinforcing loop between histone lysine 9 methylation and CHG methylation [12] . The de novo DNA methyltransferase DOMAINS REARRANGED METHYLTRANSFERASE ( DRM2 ) , a homolog of mammalian DNMT3 enzymes , is required for maintenance of non-CG methylation at some loci and initiation of DNA methylation in all contexts [20] , [21] . Targeting of DRM2 to specific loci is dependent on several proteins involved in siRNA biosynthesis ( RNA polymerase IVa: NRPD1a and NRPD2; RNA polymerase IVb: NRPD1b and NRPD2; RNA-dependent RNA polymerase: RDR2; Dicer-like3: DCL3 ) along with an argonaute protein ( AGO4 ) and two SNF-related genes ( DRD1 and CLASSY ) [22]–[26] . We show here that two SRA-domain containing proteins , SUVH9 and SUVH2 , are also essential to the DRM2 pathway . Furthermore , we show that the SRA domains of SUVH9 and SUVH2 bind directly to methylated DNA and that mutations in the SRA domains reduce DRM2 function in vivo . Thus , SRA domain proteins play critical roles in all three of the major DNA methylation pathways in Arabidopsis controlled by the MET1 , CMT3 and DRM2 methyltransferases .
The importance of SRA-domain proteins in both the MET1 and CMT3 pathways led us to investigate other members of these families in Arabidopsis . There are nine SRA-SET proteins ( SUVH1-9 ) , six SRA-RING proteins ( VIM1-6 ) and two proteins that contain only an SRA domain [12] . SUVH9 and SUVH2 are closely related to each other , but divergent from other members of the SUVH group ( Figure S1A ) . KYP , SUVH5 and SUVH6 form a second clade , while SUVH1 , SUVH3 , SUVH7 and SUVH8 form a third clade . We obtained T-DNA insertion lines in each of the SUVH genes [27] , [28] and constructed a series of single , double , triple , and quadruple homozygous mutant combinations . While none of the single T-DNA mutants had any obvious phenotype , a suvh9 suvh2 kyp triple mutant displayed morphological differences from wild type . These morphological defects are indistinguishable from those displayed by a DNA methyltransferase triple mutant drm1 drm2 cmt3 ( Figure 1A–B; DRM1 and DRM2 are tightly linked genes and in all cases the double mutant is examined though no activity has been ascribed to DRM1 ) [20] , [29] . This phenotype , which consists of curling of the leaves and short stature , has recently been shown to be caused by the ectopic expression of an F-box gene , SUPPRESSOR of DRM1 DRM2 CMT3 ( SDC ) , which is silenced by non-CG DNA methylation occurring at tandem repeats found in its promoter [30] . Simultaneous disabling of both the CMT3 pathway and the DRM2 pathway is required for activation of SDC and the appearance of this developmental phenotype . In this respect , mutations in siRNA biosynthesis pathway genes can substitute for drm2 mutations , and kyp mutations can substitute for cmt3 mutations . For example , the SDC overexpression developmental phenotype can also be seen in the following triple mutants: drm1 drm2 kyp , nrpd2a nrpd2b kyp , and nrpd2a nrpd2b cmt3 [29] , [30] . Based on the morphological defect of the suvh9 suvh2 kyp triple mutant , we therefore reasoned that these mutations must also be blocking both the DRM2 and the CMT3 pathways . Furthermore , since KYP has clearly been shown to be required for CMT3 but not DRM2 activity [14] , [15] , suvh9 suvh2 is likely preventing DRM2 function . To confirm that the suvh9 suvh2 kyp phenotype was indeed due to reactivation of SDC , RNA levels were measured using reverse transcription quantitative PCR ( RT-qPCR; Figure 1C ) . We found SDC expression in suvh9 suvh2 kyp was elevated 10 , 000-fold over wild-type expression levels ( normalized to ACTIN ) . This is similar to what is observed in the drm1 drm2 cmt3 mutant ( Figure 1C ) . The suvh2 mutant alone had no effect on SDC expression and suvh9 had a weak affect ( 10 fold above wild type control ) . The double mutant suvh9 suvh2 increased expression 100 fold above the control , but was still 100 fold lower than the triple mutant suvh9 suvh2 kyp . The level of expression in suvh9suvh2 is below what is required to observe a full morphological phenotype . Since expression of SDC is inhibited by non-CG promoter DNA methylation , the extent of methylation at the SDC repeats was examined in the suvh mutants using bisulfite sequencing . We found that disruption of either suvh2 or suvh9 or both resulted in a reduction of the CHH methylation , with little change in other types of methylation ( Figure 1D and Figure S2 ) . This is comparable to what has been previously observed in a drm1 drm2 mutant ( Figure S2 and [30] ) . While the suvh9 suvh2 kyp triple mutant shows a loss of both CHG and CHH methylation , it has little effect on CG methylation ( Figure 1D ) . This differs from drm1 drm2 cmt3 which shows almost complete loss of all methylation ( Figure 1D ) . We hypothesized that the residual methylation is suvh9 suvh2 kyp might be due to CMT3 activity , because it is known that SUVH6 functions redundantly at some loci to control CMT3 action [18] . We therefore analyzed the suvh9 suvh2 suvh6 kyp quadruple mutant and found a complete loss of all DNA methylation ( Figure 1D ) . These results suggest that the combination of these four SRA-SET mutants efficiently blocks both the DRM2 and CMT3 pathways and reinforces our hypothesis that SUVH9 and SUVH2 act in the DRM2 pathway . Maintenance of non-CG methylation is performed by both the CMT3 pathway and the DRM2 pathway in a locus specific manner , i . e . some loci require just DRM2 or CMT3 and others require both enzymes to maintain non-CG methylation [20] . To determine the specificity of the SUVH9 and SUVH2 proteins , we assessed the level of methylation at several well-characterized loci . In contrast to the SDC locus where SUVH9 and SUVH2 act redundantly , we found that at two DRM2-dependent loci , MEA-ISR ( tandem repeats near the MEA gene ) [20] and FWA [21] , non-CG methylation was mostly dependent on SUVH2 ( compare Figure 2A , 2D and 2E with Figure 1D; see also Figure S2 ) . At two loci whose non-CG methylation mostly depends on CMT3 , the 180 base pair CEN repeats ( Figure 2C ) and the retrotransposon Ta3 ( data not shown ) , we did not observe an effect on either CG methylation or CHG methylation , further suggesting that SUVH9 and SUVH2 are specific to the DRM pathway . Methylation of Ta3 and the CEN repeats is also strongly dependent on the MET1 pathway , indicating the SUVH9 and SUVH2 do not affect this pathway either . At the single copy SINE element , AtSN1 , which is methylated by both DRM2 and CMT3 , suvh9 again had no effect while suvh2 reduced non-CG methylation by 50% . At this locus suvh9 suvh2 had an effect similar to drm1 drm2 , and suvh9 suvh2 kyp reduced the CG and CHG methylation even further , to a similar level as observed in drm1 drm2 cmt3 ( Figure 2F and Figure S2 ) . CHG methylation at the repetitive 5S locus is strongly reduced in cmt3 and slightly reduced in drm1 drm2 , and we also observed a slight reduction in suvh9 suvh2 and suvh9 suvh2 kyp mutants ( Figure 2B ) . Together , these results are consistent with SUVH9 and SUVH2 functioning solely in the DRM2 pathway , where they act redundantly at some sites ( AtSN1 , SDC ) and at other sites depend only on SUVH2 ( MEA-ISR , FWA ) . Our results are not consistent with a previous report of a role of SUVH2 in control of MET1-dependent CG methylation [31] . In order to confirm that the phenotypes we observed were indeed caused by disruption of SUVH9 and SUVH2 , we transformed plants with genomic clones containing amino-terminally tagged SUVH9 or SUVH2 under the control of their endogenous promoters ( Figure 3A ) . To test for complementation of suvh9 , myc-tagged SUVH9 was transformed into suvh9 suvh2 kyp and expression of SDC was analyzed by RT-qPCR ( Figure 3B ) . We observed a 30× reduction in SDC expression , indicating the tagged SUVH9 transgene was able to complement the mutant phenotype and allow resilencing of SDC . For suvh2 complementation , we transformed HA-tagged SUVH2 into a suvh2 mutant and tested for DNA methylation at MEA-ISR ( Figure 3C ) . Efficient complementation was observed as the reappearance of DRM2-dependent non-CG DNA methylation . The epitope-tagged complementing transgenes also allowed us to evaluate the expression level of the SUVH9 and SUVH2 proteins in vivo . Expression of either myc-SUVH9 or HA-SUVH9 could be easily detected in leaves or flowers by western blot , but the level of expression of HA-SUVH2 was much lower and required immunoprecipitation in order to detect ( Figure 3D ) . This is consistent with mRNA expression data from publicly available microarray experiments from 79 Arabidopsis tissues [32] that showed both SUVH9 and SUVH2 to be ubiquitously expressed , with SUVH9 showing a more than five-fold higher mRNA expression value than SUVH2 ( Figure 3E ) . Although the microarray data is not particularly quantitative ( because of noise introduced by the potentially different efficiencies of the probe sets for the two different genes ) the large difference in signal suggests that SUVH9 is expressed more highly than SUVH2 . These results suggest that the stronger effect of the suvh2 single mutant as compared to the suvh9 single mutant at loci such as MEA-ISR and FWA ( Figure 2 ) cannot be explained simply by relative expression levels of the SUVH2 and SUVH9 and instead suggests that these proteins are functionally different . A well-established method for assaying de novo methylation in Arabidopsis involves transforming plants with an unmethylated FWA transgene using Agrobacterium . The promoter region of the FWA gene contains two large and two small repeat sequences that are methylated upon integration into the plant genome , silencing the FWA gene and allowing for normal flowering time [21] , [33] . In a drm1 drm2 mutant background , the FWA transgene does not become methylated , allowing ectopic expression and causing late flowering . To investigate the role of SUVH9 and SUVH2 in the establishment of methylation , we assayed for de novo methylation using the FWA transformation assay and measured flowering time by counting the number of leaves produced before the transition to flowering . In the wild-type line ( Columbia ) , flowering time changed very little upon transformation indicating efficient establishment of methylation on the FWA transgene ( Figure 4A ) . In suvh2 , most transformants flowered at the same time as untransformed plants , but 24% of the plants flowered later than the latest flowering plant in the untransformed control ( Figure 4B ) , presumably due to an inability to methylate and silence the FWA transgene . In suvh9 , 50% of the transformants flowered later than the untransformed control ( Figure 4C ) and in suvh9 suvh2 , 91% of the transformants were late-flowering ( Figure 4D ) . To confirm the defect in FWA de novo DNA methylation , DNA from late-flowering T1 plants was isolated , and the methylation of the FWA transgene was analyzed by bisulfite sequencing . We found a significant reduction of DNA methylation in the FWA transgene from both a late-flowering suvh2 T1 plant ( flowered at 32 leaves ) and a late-flowering suvh9 T1 plant ( flowered at 36 leaves ) , compared to the wild-type control ( Figure 4E ) . The suvh9 suvh2 late-flowering T1 plant had no detectable DNA methylation in the FWA transgene . These results suggest SUVH9 and SUVH2 act redundantly in the DRM2 pathway during establishment of methylation at FWA . Notably , these results are distinct from those obtained when assessing maintenance of non-CG methylation at FWA , which we find is dependent exclusively on SUVH2 ( Figure 2E ) . Previous studies have shown that RNA Pol IVa , RDR2 and DCL3 are required to generate siRNAs and thus act upstream from RNA Pol IVb , AGO4 , DRD1 and DRM2 , which have only modest effects on siRNA abundance [25] We investigated whether SUVH9 and SUVH2 function before or after siRNA synthesis by analyzing their effect on siRNA levels at DRM2-dependent loci . Using siRNA blot analysis we analyzed the levels of siRNAs from two representative loci , 5S and SDC . While the levels of siRNAs were somewhat reduced in some mutant backgrounds , they were not eliminated in suvh9 suvh2 double mutants ( Figure 4F ) . This was similar to what was observed with the drm1 drm2 mutant and in contrast to the complete loss of siRNAs observed in rdr2 ( Figure 4F ) . These results indicate that SUVH9 and SUVH2 function at a point in the RNA-directed DRM2 DNA methylation pathway downstream of the initial biosynthesis of siRNAs . However , the modest reduction of siRNA levels in suvh2 suvh9 may indicate a role in feedback between DNA methylation and the siRNA machinery , as has been suggested for other DRM2 pathway mutants [23] . The SET domains of SUVH9 and SUVH2 align closest to the H3K9 methyltransferases and yet are highly divergent ( Figure S1B ) , suggesting that SUVH9 and SUVH2 could have evolved a function different from the other H3K9 methyltransferases . To determine the specificity of SUVH9 and SUVH2 SET domains , histone methylation marks associated with heterochromatin and gene silencing were examined by immunostaining of nuclei using well-characterized antibodies . Previous studies reported a decrease in H3K9me1 , H3K9me2 , H3K27me1 , H3K27me2 and H4K20me1 in suvh2 background [31] . However , we could not find any significant differences using well-characterized antibodies to H3K9me1 or H3K9me2 in suvh2 , suvh9 ( data not shown ) , or in suvh9 suvh2 nuclei compared to the wild-type Columbia line ( Figure 5A ) . Consistent with previous reports showing that the KYP , SUVH5 , and SUVH6 proteins add one or two methyl groups to H3K9 in vitro and all play a role in targeting CMT3 [17] , [19] , H3K9me1 and H3K9me2 staining of chromocenters in kyp suvh5 suvh6 nuclei was significantly reduced ( Figure 5A ) . We next tested H3K27me1 , a mark found in heterochromatin , in the quadruple mutant suvh9 suvh2 suvh6 kyp and found no difference compared to wild-type Columbia ( Figure 5B ) . H3K27me2 is found only in euchromatin ( data not shown ) and H4K20me has not been detected by mass spectrometry [34] nor could we detect a signal by immunofluorescence ( data not shown ) . Thus , SUVH9 and SUVH2 do not appear to be required for the overall presence of the main histone methylation marks associated with gene silencing and may act either in a more locus-specific manner or on non-histone substrates . To further explore the possibility that SUVH9 and SUVH2 are histone methyltransferases , various in vitro histone methylation assays were conducted . Amino-terminal glutathione S-transferase fusions with SUVH9 and SUVH2 containing the Pre-SET and SET domains were constructed and purified from E . coli along with KYP-SET as a positive control . With KYP-SET we readily detected methylation of H3 using either calf thymus histones or Arabidopsis nucleosomes ( Figure 5C ) . However , using a variety of different buffers we did not detect activity with either SUVH9-SET or SUVH2-SET ( Figure 5C ) . Since it is possible that SUVH9 or SUVH2 must be in a complex for activity , affinity-tagged SUVH9 and SUVH2 were immunoprecipitated from Arabidopsis extracts prepared from complementing transgenic lines , and immunoprecipitates were assayed for histone methylation activity using either calf thymus histones or Arabidopsis nucleosomes , but no activity above background levels was observed ( data not shown ) . Finally we tested the ability of SUVH9 or SUVH2 to bind S-adenosylmethionine ( AdoMet ) , which would indicate they have the potential to be active methyltransferases . AdoMet binding to SET domains can be detected by crosslinking with ultraviolet light using 3H-AdoMet [35] . While binding of AdoMet to KYP-SET was easily detected , binding to either SUVH9-SET or SUVH2-SET was undetectable ( Figure 5D ) . The lack of binding to AdoMet suggests the possibility that SUVH9 and SUVH2 may not be active methyltransferases , or may require other factors to be active . In addition to the SET domain , SUVH9 and SUVH2 also possess an SRA domain that could be important for its function in the DRM2 pathway , similar to what has been observed in the CMT3 and MET1 pathways . SRA-domains are methyl-cytosine binding domains that vary in their sequence specificity [9] , [10] , [12] , [13] . To determine the sequence specificity for the SUVH9 and SUVH2 SRA domains , GST-SRA fusions were expressed and purified from bacteria . We measured binding to various double-stranded oligonucleotide substrates in the presence of 1000× molar excess of unmethylated competitor using mobility shift assays . The SUVH9 SRA showed a strong preference for methylated CHH over CHG or CG oligonucleotides with little affinity for hemi-methylated DNA , whereas no binding was detected to unmethylated DNA ( Figure 6A and Figure S4 ) . In contrast , the SUVH2 SRA showed strong binding to methylated CG sites , with a very low affinity for methylated CHG , CHH , hemi-methylated or unmethylated DNA ( Figure 6A and Figure S4 ) . These two SRA domains , therefore , have specificities that distinguish them from each other as well as from the other SRA-domains that have been characterized to date . If the methyl DNA-binding activity of SUVH9 and SUVH2 is important for DRM2 activity , then their SRA domains should be necessary for successful genomic complementation . To test this , mutations analogous to those isolated in the KYP SRA-domain [12] were introduced into the otherwise complementing SUVH9 and SUVH2 epitope-tagged transgenes , and mutant transgenic lines were used in complementation experiments . RT-qPCR of the SDC gene revealed that the SRA mutation in SUVH9 ( S252F: equivalent to KYP S200F ) resulted in an increase of expression 10 fold above what was observed in suv9 suvh2 kyp/SUVH9 ( Figure 6B ) . A SUVH2 SRA mutant ( E262K: equivalent to KYP E208K ) also showed a loss of activity as measured by methylation of MEA-ISR ( Figure 6C ) . In neither case did the mutation destabilize the protein in plants ( Figure 6B and Figure 6C , lower panels ) . These results suggest that the SRA domains of SUVH9 and SUVH2 are critical to their function in DRM2-mediated DNA methylation .
DRM2 is the major enzyme responsible for de novo methylation and maintenance of non-CG methylation in Arabidopsis . siRNAs produced by RNA Pol IV , RDR2 , and DCL3 and bound by AGO4 are necessary for targeting DRM2 to specific sequences resulting in DNA methylation [36] , [37] . This process has also been shown to involve two SNF2 homologs , DRD1 and CLASSY , and a chromosome architectural protein ( DMS3 ) homologous to the hinge region of SMC [37] , [38] . We show here that SUVH9 and SUVH2 are also required for RNA-directed DNA methylation . Knocking out SUVH9 and/or SUVH2 blocks maintenance of non-CG methylation by DRM2 at multiple loci and prevents de novo methylation of the FWA transgene . Furthermore , we show that these two proteins function after the initial biosynthesis of siRNAs , suggesting they may be involved in a later step in the DRM2 pathway . SUVH9 and SUVH2 have two notable domains: the SRA methyl-cytosine DNA binding domain and the SET methyltransferase domain . The SET domain aligns closest to the H3K9 methyltransferases , but one of the most conserved sequences in the carboxy-terminal region of the SET domain ( RFxNHxCxPN ) is highly diverged , replaced with a sequence that is highly conserved between SUVH9 and SUVH2 homologs in rice and poplar ( CYxSHSxxPN; Figure S1 ) . SUVH9 , SUVH2 , and their homologs are also missing the post-SET domain . This conservation suggests that this region is important functionally , but may have a distinct activity compared to the other SUVH proteins . Conflicting results have been reported regarding the histone methyltransferase activity of these enzymes . One report found no histone methyltransferase activity in SUVH9 and SUVH2 GST fusion proteins using calf thymus histones as substrates , whereas activity for SUVH4 ( KYP ) , SUVH5 and SUVH6 fusions was easily observed [19] . In a second report , recombinant nucleosomes were used as a substrate and SUVH2 activity was detected on both H3 and H4 [31] . We repeated these assays for both SUVH2 and SUVH9 and did not observe activity in vitro using either histones or nucleosomes as a substrate . Another possibility is that SUVH9 and SUVH2 have diverged such that they methylate non-histone protein substrates [39]–[41] . One obvious candidate is DRM2 , however in vitro assays using DRM2 as a substrate were also negative ( data not shown ) . Furthermore , we could detect binding of AdoMet ( the methyl donor for methyltransferase enzymes ) to KYP but not to SUVH9 or SUVH2 , suggesting that these two proteins may have lost methyltransferase activity . It is possible that SUVH9 and SUVH2 require another protein for activity , or possibly dimerize in vivo to create an active site [42]–[45] . For instance , the Drosophila SU ( VAR ) 3-9 is most active as a dimer and requires the amino terminus to dimerize . We immunoprecipitated SUVH9 and SUVH2 from plants and assayed their ability to methylate histones or nucleosomes , but again no activity was observed . Thus , while our results cannot rule out that SUVH9 and SUVH2 are active methyltransferases , they do raise the possibility that the SET domains are acting in a different manner . For instance , there are several examples in other systems where catalytically inactive homologs are important [46] , [47] . The SUVH9 and SUVH2 proteins also contain SRA domains that are active in binding methylated DNA and differ from each other in their sequence specificity . SUVH9 prefers methylated CHH , binding with a higher affinity when a G residue is not located in the two adjacent positions . This differs from KYP and SUVH6 which preferentially bind to CHG [12] . Biologically this preference for CHH makes sense because DRM2 is essential for maintaining CHH residues . SUVH2 binding specificity for methylated CG sites was more surprising . DRM2 from tobacco is active in vitro , and preferentially methylates CHH and CHG and only methylates CG residues at a low frequency [48] . Hence , SUVH2 appears to be binding to a sequence not commonly maintained by DRM2 . However , it has been previously shown that eliminating CG methylation in met1 mutant lines results in loss of non-CG methylation at certain loci [20] , [30] , [49] . Thus , one possibility is that SUVH2 may function by linking CG methylation and non-CG methylation . The difference in binding specificity of the SRA domains of SUVH2 and SUVH9 correlates well with the loci that are preferentially affected in the mutants . Both MEA-ISR and FWA are rich in methylated CG residues ( 8 mCGs:4 methylated non-CGs in MEA-ISR; 20 mCGs:4 methylated non-CGs in FWA; see Figure 2 ) and show a strong dependence on SUVH2 which preferentially binds to methylated CGs . On the other hand , SDC and AtSN1 are more heavily CHH and CHG methylated ( 5 mCGs:9 methylated non-CGs at SDC; 3 mCGs:14 methylated non-CGs at AtSN1; see Figure 1D and Figure 2E ) and only show a strong reduction of methylation in the suvh9 suvh2 double mutant background , suggesting less of a dependence on SUVH2 . An attractive model to explain the role of SUVH9 and SUVH2 in de novo methylation may be that they function to retain DRM2 at methylated regions immediately after the establishment of methylation ( even in initiation assays DNA methylation must be maintained through many rounds of replication and mitoses before the DNA methylation is analyzed ) . One possibility is that SUVH2 could retain DRM2 at sites rich in methylated CG and SUVH9 could do the same at sites rich in non-CG methylation . These SRA proteins would then provide a link between establishment of methylation and maintenance methylation . Alternatively , SUVH9 and SUVH2 may recruit or retain a component of the DRM2 pathway which is needed for DRM2 activity . It is also possible that SUVH2 and SUVH9 directly participate in the silencing of DNA methylated genes , and that some of the loss of DNA methylation observed in suvh2 and suvh9 mutants is due to secondary effects of the loss of gene silencing or other chromatin marks . Regardless of the specific mechanism involved , these results show that each of the major methylation systems in Arabidopsis require an SRA-domain protein for function . CG methylation by MET1 involves VIM1 ( an SRA protein homologous to UHRF1 which specifically binds hemimethylated CG sites; [10] , [13] ) CMT3 is dependent on KYP , which specifically binds methylated CHG; and DRM2 requires SUVH9 and SUVH2 , which bind to methylated CHH or methylated CG , respectively .
The drm1 drm2 cmt3 and drm1 drm2 kyp triple mutants were generated in the Columbia background and have been described previously [29] . The kyp mutant is Salk T-DNA_041474 and was described previously [12] . SUVH5 mutant T DNA was obtained from GABI-Kat ( line 263C05 , [50] ) and disrupts the open reading frame at amino acid 40 . SUVH6 mutant T-DNA was obtained from Syngenta ( Garlic_1244_F04 . b . 1a; [27] ) and disrupts the open reading frame in the middle of the pre-SET domain . SUVH2 mutant T-DNA ( Salk _079574 . 17 . 40 ) disrupts the open reading frame at amino acid 101 and has been previously characterized [31] . The SUVH9 mutant T-DNA ( Salk_048033 ) disrupts the open reading frame at amino acid 43 . Plants were grown under continuous light for scoring the SDC over-expression leaf-curling phenotype and under long days for measuring flowering time . suvh9 suvh2 kyp morphological phenotypes were examined over several generations of inbreeding and differences between generations were not observed . Total RNA was extracted from several pooled 3 week-old plants using Trizol reagent ( Invitrogen ) and analyzed by RT-qPCR . Two to three biological replicas were sampled and standard deviations determined . Primers for SDC amplification were JP3395 and JP3396 ( primers are listed in Table S1 ) using SYBR green and ACTIN amplification was done using JP2452 and JP2453 using a Taqman probe ( M17 ) . Small RNAs were extracted from flowers and analyzed by Northern blotting as previously described [51] . Approximately 0 . 5 to 1 . 0 µg of genomic DNA ( from flowers and rosette leaves ) was bisulfite treated using the EZ DNA Methylation-Gold kit ( Zymo research cat . No . D5005 ) . The MEA-ISR , AtSN1 , and SDC loci were amplified using 1 µl of bisulfite treated DNA in a 50 ul PCR reaction using Ex Taq polymerase ( Takara Cat . No . TAK RR001 A ) and JP5392 , JP5393 ( MEA-ISR ) ; JP1821 , JP1822 ( AtSN1 ) ; JP4039 , JP4045 ( SDC ) . FWA methylation was determined from DNA isolated from rosette leaves for bisulfite treatment and amplified with JP2004 , JP4423 . PCR products were TA cloned in to pCR2 . 1 ( Invitrogen cat No . K4500-01 ) and approximately 20 individual clones were sequenced using the M13 reverse primer by the High Throughput Genomics Unit at the University of Washington . See Figure S3 for alignments . For Southern blots , 3–5 µg of genomic DNA was run on 1% agarose gels , transferred to Hybond N+ membranes , blocked and washed according to manufacture instructions ( GE Healthcare ) . Membranes where probed using PCR products radiolabeled with alpha 32P-dCTP using the Megaprime DNA Labeling System ( GE cat . No . RPN1606 ) . MEA-ISR , Ta3 and CEN180 probes were amplified as described previously [20] , [52] . GST fusions were made using either the Gateway cloning system from Invitrogen or the pGEX-4T1 plasmid from GE Healthcare . The GST fusion containing the KYP SET was described previously [12] . pLJ248 is pDEST15 containing amino acids 387–650 of SUVH9 , the entire carboxy-terminal end of the protein ( GST-preSET-SET construct: abbreviated 9-SET ) . pLJ205 is pDEST15 containing amino acids 387–651 of SUVH2 ( GST-preSET-SET contruct: abbreviated 2-SET ) . pLJ176 is pDEST15 containing amino acids 137–356 of SUVH9 ( GST-SRA: abbreviated 9-SRA ) and pLJ242 is pGEX-4T1 with amino acids 201 to 400 of SUVH2 ( GST-SRA: abbreviated 2-SRA ) . The GST fusion proteins were expressed in BL21 AI cells and purified as described previously except that the final buffer for the GST-SET proteins was 50 mM Tris-HCl pH 8 . 0 , 50 mM NaCl , 1 mM DTT , 40% glycerol and the GST-SRA proteins were dialyzed into 50 mM Tris-HCl pH 6 . 8 , 300 mM NaCl , 1 mM DTT , 40% glycerol . Epitope-tagged protein constructs were made using a modified Gateway cloning system for expression in plants . Specifically , the biotin ligase gene ( BirA ) under the control of the ACTIN promoter was added into the single Sbf1 site of the pEarleyGate302 destination vector [53] and the C-terminal Flag tag was removed by site directed mutagenesis using JP 4225 and JP 4226 primers ( JP746; Figure S5 ) . 1 . 4 kb of genomic DNA upstream the SUVH9 ORF and the entire ORF was cloned into pENTR . A Kpn I restriction site was introduced at the ATG and either a 9xMyc epitope tag ( pLJ217 ) or a 3xHA ( pLJ214 ) epitope tag was introduced . Both of these tags also contain the biotin ligase recognition peptide ( BLRP ) and a 3C protease site . These tagged constructs were then recombined into JP746 and introduced into Agrobacterium strain AGLO . pLJ213 contains 2 . 1 kb upstream of the SUVH2 ORF , the ORF , and 1 kb downstream of the ORF ( SUVH2 contains an intron and an untranslated exon in the 3′ end ) with the BLRP-3C-3xHA epitope tag inserted at the ATG via an introduced Kpn I site in vector JP746 . Mutations in the SRA domain were introduced using QuikChange Kit ( Stratagene ) . Plasmids were transformed into the Agrobacterium strain AGLO and then introduced into Arabidopsis using the floral dip method of transformation . Transformed lines were selected with Basta . Nuclei were isolated and stained as described in [12] . The H3K9me1 and H3K9me2 antibodies used in this study were a gift from Thomas Jenuwein ( lot #4858 and lot #4677 , respectively ) . The H3K9me3 was obtained from Abcam ( #8898-100 ) . The H3K27me1 antibody was obtained from Upstate Biotechnology ( #24439 ) . Immuno staining was done as described previously with the additional use of a Zeiss ApoTome [53] . Histone methylation assays were done as described in [54] . Specifically , 8 ug GST fusion proteins purified from E . coli were incubated in 50 mM Tris pH 8 . 8 , 20 mM KCl , 10 mM MgCl2 , 10 mM β-mercaptoethanol , 250 mM sucrose and 3H-S-AdoMet ( GE Healthcare , #TRK581 ) with either 10 ug of calf thymus histones or Arabidopsis nucleosomes [55] . Reaction mixtures were incubated at room temperature for 3 hours before separating proteins on 15% polyacrylamide gel . Incorporation of tritium was detected by autoradiography . AdoMet crosslinking was done as described in [35] using approximately 15 ug of purified GST-fusion proteins . The DNA probes used in the electrophoretic mobility shift assays were described previously [12] . GST-SUVH2-SRA ( 60 nM final concentration ) or GST-SUVH9-SRA ( 0 . 4 nM final concentration ) was incubated with 32P-labeled probe in the presence of 1000× molar excess of unmethylated DNA as competitor in buffer ( 25 mM Tris , pH 6 . 8 , 10 mM MgCl2 , 1 mM DTT , 5% glycerol , 0 . 4 mg/ml BSA ) for 30 minutes . Samples were electrophoresed on an 8% polyacrylamide gel , which was then fixed in 5% acetic acid and dried . 32P-labeled DNA was detected by autoradiography . GST-fusion proteins isolated from E . coli vary in the amount of active protein , so it is unclear whether SUVH9 binds methylated DNA with a higher affinity than SUVH2 .
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Our genetic heritage plays an important role in determining who we are and the characteristics we possess . However , in the past decade it has become increasingly clear that in addition to the genes we inherit , a second level of information is critical for expression of these genes . This information takes the form of modifications to either the DNA ( DNA methylation ) or the proteins that package the DNA ( histones ) . These modifications can determine whether a gene is expressed or silenced . In this paper , we identify two new genes that are part of a DNA methylation–targeting pathway in the model plant A . thaliana . Disruption of these two closely related genes prevents DNA methylation by one of the cellular DNA methyltransferases . However , these genes are not simply redundant . They are both capable of binding methylated DNA , but differ in their preference for specific sequences in the genome . This ability to bind to methylated DNA suggests that these proteins help target or retain the modification apparatus at particular regions of the genome . These results are important in that they identify two new players in this vital cellular process and bring us closer to understanding how epigenetic modifications can be targeted to specific genes .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Material",
"and",
"Methods"
] |
[
"genetics",
"and",
"genomics/epigenetics",
"genetics",
"and",
"genomics/gene",
"function",
"plant",
"biology/plant",
"genetics",
"and",
"gene",
"expression",
"genetics",
"and",
"genomics/plant",
"genetics",
"and",
"gene",
"expression"
] |
2008
|
SRA-Domain Proteins Required for DRM2-Mediated De Novo DNA Methylation
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Mutations in the ribosomal protein Rpl10 ( uL16 ) can be drivers of T-cell acute lymphoblastic leukemia ( T-ALL ) . We previously showed that these T-ALL mutations disrupt late cytoplasmic maturation of the 60S ribosomal subunit , blocking the release of the trans-acting factors Nmd3 and Tif6 in S . cerevisiae . Consequently , these mutant ribosomes do not efficiently pass the cytoplasmic quality control checkpoint and are blocked from engaging in translation . Here , we characterize suppressing mutations of the T-ALL-related rpl10-R98S mutant that bypass this block and show that the molecular defect of rpl10-R98S is a failure to release Nmd3 from the P site . Suppressing mutations were identified in Nmd3 and Tif6 that disrupted interactions between Nmd3 and the ribosome , or between Nmd3 and Tif6 . Using an in vitro system with purified components , we found that Nmd3 inhibited Sdo1-stimulated Efl1 activity on mutant rpl10-R98S but not wild-type 60S subunits . Importantly , this inhibition was overcome in vitro by mutations in Nmd3 that suppressed rpl10-R98S in vivo . These results strongly support a model that Nmd3 must be dislodged from the P site to allow Sdo1 activation of Efl1 , and define a failure in the removal of Nmd3 as the molecular defect of the T-ALL-associated rpl10-R98S mutation .
The eukaryotic ribosome is composed of 4 ribosomal RNA molecules and roughly 80 ribosomal proteins that come together to form the large ( 60S ) and small ( 40S ) subunits that make up mature 80S ribosomes . Eukaryotic ribosome biogenesis is an intricate assembly pathway that requires the assistance of hundreds of trans-acting factors [1–6] , and although ribosomes catalyze protein synthesis in the cytoplasm , this process takes place predominantly in the nucleus . Each nascent subunit must therefore be exported through the nuclear pore complex , a process that is dependent on the export receptor Crm1 [7–9] . In 60S export , Crm1 is recruited via the export adapter Nmd3 , which contains a leucine-rich nuclear export signal ( NES ) [10–12] . In yeast , additional factors assist in 60S export , including the non-canonical export receptor Arx1 [13 , 14] , the mRNA export receptor Mex67-Mtr2 [15] , Ecm1 [16] , and Bud20 [17] . However , only Nmd3 appears to be universally conserved in eukaryotes as a dedicated 60S export factor [9–12] . Nascent 60S subunits entering the cytoplasm are bound by additional trans-acting factors , including the anti-association factor Tif6 ( eIF6 in mammalian cells ) [18] . Trans-acting factors bound to subunits in the cytoplasm block important functional regions and are thought to prevent immature subunits from engaging prematurely with the translational machinery ( reviewed in [19] ) . For example , Tif6 binds to the inter-subunit face of the 60S subunit and sterically block 40S joining [20 , 21] . In addition , our lab and others have recently shown that Nmd3 occupies the A , P , and E sites of the tRNA channel where it would prevent association of ligands for these sites [22 , 23] . Newly exported subunits also lack several critical ribosomal proteins , including Rpl10 [6 , 24] . [Note that Rpl10 is also named uL16 in the new nomenclature [25] , however , we use Rpl10 here for clarity with genetic mutations] . As such , pre-60S particles enter the cytoplasm in an inactive state and must undergo cytoplasmic maturation , a process of shedding trans-acting factors and assembling the final ribosomal proteins [26 , 27] . 60S cytoplasmic maturation events take place in a highly ordered pathway [28] , and the final two known steps include the release of Tif6 by Efl1 and Sdo1 [18 , 29 , 30] and the release of Nmd3 , dependent on the GTPase Lsg1 [24 , 31] . After these steps , 60S subunits are competent to participate in translation . Genetic analyses place the release of Nmd3 downstream of and dependent on the prior release of Tif6 [28 , 32 , 33] . However , recent structures of pre-60S particles call that order of events into question [34] . A critical event that takes place upstream of Tif6 and Nmd3 release in cytoplasmic maturation is the addition of ribosomal protein Rpl10 [24 , 35] , which binds in a cleft between the central protuberance and the P stalk of the 60S subunit ( Fig 1A ) . An internal loop of Rpl10 ( referred to here as the P site loop ) extends toward the catalytic center of the ribosome where it completes the peptidyl-transferase center and makes contact with the acceptor stem of P site ligands , including tRNA , during translation [36] . Extensive genetic analyses have demonstrated the importance of Rpl10 in 60S cytoplasmic maturation . Specifically , the P site loop of Rpl10 is required for the release of both Tif6 and Nmd3 [32 , 37] . While the mechanism of Nmd3 release is not understood , Tif6 release has been shown to depend on Sdo1 binding in the ribosomal P site where it cooperates with the GTPase Efl1 , a paralog of the translation elongation factor EF2 , to evict Tif6 [34] . Although Sdo1 has been shown to stimulate Efl1 GTPase activity on 60S subunits [33] , structural studies suggest that Efl1 may release Tif6 by competing with it for binding , independent of GTPase activity [34] . We and others have proposed that the release of Tif6 by Efl1 and Sdo1 acts as a quasi-functional “test drive” of nascent 60S subunits in which translation factor-mimics assess the functionality of newly made subunits . Subunits that fail the test drive ( including Rpl10 mutants ) retain Tif6 and Nmd3 , and are prevented from engaging in translation [32 , 34] . Deficiencies in the human Sdo1 protein , the Shwachman-Bodian-Diamond syndrome protein ( SBDS ) , are associated with Shwachman-Diamond syndrome ( SDS ) , a congenital disorder characterized by bone marrow failure and exocrine pancreatic insufficiency [38] . Interestingly , SDS is also associated with an elevated risk of myelodysplastic syndrome and acute myeloid leukemia development [39] . In addition , recurring mutations in RPL10 are associated with pediatric T-cell acute lymphoblastic leukemia ( T-ALL ) in humans , with the most commonly identified mutation being rpl10-R98S [40] . These mutations in T-ALL , like those in SDS , block the release of Tif6 and Nmd3 . Together , these findings suggest that defects in late 60S cytoplasmic maturation may contribute to carcinogenesis . Mutations in RPL10 are thought to block late 60S maturation by specifically impairing the Efl1- and Sdo1-dependent release of Tif6 . A previous mutational analysis of the P site loop of Rpl10 in yeast identified a class of mutants , typified by rpl10-S104D , that arrest ribosome biogenesis by failing to promote the Efl1-dependent release of Tif6 [32] . This arrest appears similar to that observed in sdo1 mutants as wells as in T-ALL-associated rpl10-R98S mutants . The RPL10 mutations also appear similar to disease-related mutations in SBDS in their impact on the binding affinity of Sdo1 to 60S subunits in vivo [34] and to mature ribosomes in vitro [41 , 42] . While reduced binding of Sdo1 to 60S subunits could explain the defect in Tif6 release , an understanding of how this leads to a block in Nmd3 release is unknown . Moreover , how Tif6 release is coordinated with Nmd3 release is not well understood . In this work , we explore the molecular defect of the T-ALL related rpl10-R98S mutant in ribosome assembly using Saccharomyces cerevisiae . Despite phenotypic similarity , the rpl10-R98S mutant blocks 60S biogenesis by a mechanism that is distinct from the P loop rpl10-S104D mutant . We show that the molecular defect of the T-ALL associated rpl10-R98S mutation is a failure to release Nmd3 from the P site , thereby preventing the release of both Nmd3 and Tif6 .
Mutations in RPL10 were identified as driver-mutations in pediatric T-cell acute lymphoblastic leukemia ( T-ALL ) [40] . These mutations occurred almost exclusively at residue arginine 98 ( R98 ) , with the exception of one patient harboring the Q123P mutation , which lies adjacent to R98 at the base of the P site loop of the Rpl10 ( Fig 1A ) . We previously showed that these T-ALL mutants exhibited a large subunit biogenesis defect in which Tif6 and Nmd3 release were blocked [40] . This phenotype appeared similar to the defect observed in a class of Rpl10 P site loop mutants , typified by the rpl10-S104D mutant , identified in an earlier mutational analysis of RPL10 [32] . We therefore anticipated that the molecular defect of the T-ALL related rpl10-R98S mutation was the same as that caused by rpl10-S104D and would be suppressed by the same mutations . We previously showed that rpl10-S104D can be suppressed by the dominant TIF6 mutant , TIF6-V192F , which belongs to a class of mutations that map to the 60S-binding surface of Tif6 [32] . Such dominant mutations in TIF6 also suppress the growth defects due to loss of Efl1 [18 , 29] or Sdo1 [30] by weakening Tif6 affinity for the 60S subunit , thereby uncoupling the release of Tif6 from the requirement for Efl1 and Sdo1 . We also identified mutations in EFL1 itself that suppressed rpl10-S104D . These mutations are thought to predispose Efl1 to undergo a conformational change that normally requires proper signaling through Sdo1 binding in the P site [32] . Thus , a probable explanation for the effect of rpl10-S104D on the release of Tif6 is that the Rpl10 mutant ribosome is defective for Sdo1 binding . Indeed , we recently found that both rpl10-S104D and rpl10-R98S ribosomes had a weakened affinity for Sdo1 compared to wild-type ribosomes in vitro [41 , 42] , while others have also demonstrated that the T-ALL associated RPL10 alleles impair Sdo1 binding to the 60S subunit in vivo [34] . Unexpectedly , we found that although TIF6-V192F and EFL1 mutants could suppress the rpl10-S104D growth defect , they could not suppress the rpl10-R98S defect ( Fig 1B ) . This result was surprising because both rpl10 mutants are defective for Tif6 release , and the lower affinity of Tif6-V192F for 60S should promote its release . We considered two possibilities to explain the difference between the two rpl10 mutations: 1 ) Tif6-V192F remains trapped on rpl10-R98S pre-60S subunits or 2 ) Tif6-V192F is released from rpl10-R98S subunits , but its release does not suppress the full biogenesis defect . To determine whether Tif6-V192F was released , we monitored the localization of Tif6-GFP versus Tif6-V192F-GFP in rpl10-R98S cells , and in rpl10-S104D cells as a control . The nuclear localization of Tif6 in wild-type cells reflects its ability to be released from pre-60S subunits in the cytoplasm and subsequently recycled to the nucleus [18 , 28 , 30 , 43] . As previously reported [32 , 40] , wild-type Tif6-GFP was mislocalized to the cytoplasm in both rpl10 mutants , indicating a failure in Tif6 release from the 60S subunit ( Fig 1C , left panels ) . Also in agreement with previous observations , we found that the steady state localization of Tif6-V192F-GFP was nuclear in rpl10-S104D cells , demonstrating that it recycles back to the nucleus [32] . Unexpectedly , we found that Tif6-V192F-GFP was also localized to the nucleus in rpl10-R98S cells ( Fig 1C , row 3 ) . These results indicate that TIF6-V192F can bypass the block in its release in both rpl10 mutants . However , while its release could suppress rpl10-S104D , the release of Tif6-V192F was not sufficient to suppress the rpl10-R98S growth defect . The results described above suggest that while the rpl10-S104D mutant is specifically defective in the Efl1-dependent release of Tif6 , the rpl10-R98S defect is more complex . To gain insight into the mechanism by which the rpl10-R98S mutant stalls 60S biogenesis , we identified extragenic suppressors of the rpl10-R98S growth defect . We isolated multiple independently-derived spontaneous suppressors of rpl10-R98S that appeared readily as fast-growing colonies among the severely growth-impaired rpl10-R98S background . Because Nmd3 release , in addition to Tif6 release , is impaired in rpl10-R98S cells , we considered the possibility that mutations in Nmd3 that promote its release might suppress the rpl10-R98S growth defect . The idea that suppressing mutations could be identified in NMD3 was also supported by our earlier observation that ectopic expression of WT NMD3 partially suppressed the rpl10-R98S growth defect [40] ( Fig 2A ) . Thus , we began by sequencing the NMD3 genomic locus in each of the suppressors . Remarkably , of 18 spontaneous suppressors analyzed , 16 contained mutations in NMD3 ( Table 1 ) ( the NMD3-Y379D mutant was described previously [42] ) . To confirm that the NMD3 mutations were responsible for rpl10-R98S suppression , we expressed the mutants ectopically and found that all NMD3 alleles tested were dominant suppressors of rpl10-R98S ( Fig 2A ) . Because the remaining two spontaneous suppressors contained wild-type NMD3 , we performed whole genome sequencing on one isolate to identify mutations elsewhere in the genome that could be responsible for rpl10-R98S suppression . SNP analysis revealed a mutation in TIF6 , resulting in a Gly to Val change at amino acid position 189 ( TIF6-G189V ) . Sanger sequencing of the TIF6 locus from the final remaining suppressor identified the TIF6-T185A allele . To identify additional mutations in TIF6 that could suppress rpl10-R98S , we performed random PCR mutagenesis of TIF6 and identified additional suppressing mutations at amino acid positions T185 and G189 as well as mutations at P163 and T211 ( Fig 2B and Table 2 ) . Thus , despite the fact that we had initially discounted TIF6 as a target of suppressing mutations because TIF6-V192F did not suppress rpl10-R98S , other alleles of TIF6 are suppressors . Unlike the case for NMD3 , ectopic expression of WT TIF6 did not suppress rpl10-R98S and , in fact , slightly inhibited growth ( Fig 2B ) . On the other hand , Tif6-V192F , which has weakened affinity for 60S subunits , neither inhibited nor suppressed the growth of rpl10-R98S cells , suggesting that the mechanism by which the TIF6 suppressing mutations acted was not through weakening the interaction between Tif6 and the ribosome . Suppression of the rpl10-R98S growth defect implies that the NMD3 and TIF6 alleles identified above restore ribosome biogenesis by allowing the release of Tif6 and Nmd3 from mutant 60S subunits . We examined ribosomal subunit levels from rpl10-R98S cells harboring representative NMD3 and TIF6 mutants using sucrose density gradient sedimentation . This analysis confirmed that the biogenesis defect of rpl10-R98S cells was suppressed by either NMD3-Y379D or TIF6-G189V , evidenced by the apparent wild-type 60S:40S ratio and the disappearance of halfmer polysomes ( Fig 2C ) . We also checked the localization of both Tif6 and Nmd3 in rpl10-R98S mutant cells suppressed with either NMD3-Y379D or TIF6-G189V . To monitor Tif6 localization , a C-terminal GFP tag was integrated into the TIF6 genomic locus in wild-type RPL10 cells , rpl10-R98S cells , and rpl10-R98S cells harboring the suppressing NMD3-Y379D or TIF6-G189V alleles in the genome . Again , we saw that Tif6 was mislocalized to the cytoplasm in rpl10-R98S cells ( Fig 2D , compare row 2 to row 1 ) , consistent with a failure in its release from pre-60S subunits . However , the localization of Tif6-GFP was restored in rpl10-R98S cells containing NMD3-Y379D ( Fig 2D , row 3 ) . In addition , although wild-type Tif6-GFP was mislocalized to the cytoplasm in rpl10-R98S cells , Tif6-G189V-GFP localization was restored to the nucleus ( Fig 2D , row 4 ) . Because Nmd3 is distributed throughout the cytoplasm during steady-state conditions [44] , we monitored the localization of Nmd3 in strains containing the leptomycin B ( LMB ) -sensitive crm1-T539C mutation [45] . Treatment with LMB in this mutant background blocks Crm1-dependent nuclear export , and the subsequent nuclear accumulation of Nmd3 in wild-type RPL10 cells reflects its ability to be released from pre-60S subunits in the cytoplasm and shuttle back to the nucleus [10 , 11] ( Fig 2E , row 1 ) . As previously reported , Nmd3 could shuttle to the nucleus in wild-type RPL10 cells , but was distributed throughout the cytoplasm in rpl10-R98S cells ( Fig 2E , row 2 ) [40] . However , Nmd3-Y379D could shuttle to the nucleus in rpl10-R98S cells , and wild-type Nmd3 shuttling was restored in rpl10-R98S cells expressing Tif6-G189V ( Fig 2E , rows 3–4 ) . These results demonstrate that the NMD3-Y379D and TIF6-G189V suppressors simultaneously restore the localization of both Tif6 and Nmd3 . The ability of mutant Nmd3 to restore the release and nuclear shuttling of Tif6 was a surprising result because previous genetic analyses suggested that the release of Nmd3 was downstream of the release of Tif6 [28 , 32] . The results shown here are the first indication that a block in Nmd3 release could inhibit Tif6 release . Tif6 binds to the 60S subunit primarily through Rpl23/uL14 [21] , and mutations such as Tif6-V192F , map to this interface and weaken the binding of Tif6 to the subunit [18 , 29 , 30] . Unlike Tif6-V192F , the four residues in Tif6 that are mutated in the rpl10-R98S suppressors cluster together on a surface of Tif6 that is close to , but distinct from , the Tif6-60S interface ( Fig 3A ) . The position of the rpl10-R98S suppressing mutations in the Tif6 structure suggests that they act by a different mechanism . Intriguingly , the rpl10-R98S suppressing mutations in TIF6 cluster in a region that interacts directly with Nmd3 [22] ( see below ) . Because this distinct class of TIF6 alleles ( and NMD3 alleles ) could restore Tif6 release in rpl10-R98S cells , we wondered whether their mechanism ( s ) of suppression was specific to rpl10-R98S , or if they could suppress other mutants that block Tif6 release . As discussed earlier , rpl10-S104D mutants are also defective for Tif6 release . We transformed rpl10-S104D cells with either WT or mutant TIF6 or NMD3 vectors . While NMD3-Y379D and TIF6-G189V dramatically improved rpl10-R98S cell growth , neither mutant could suppress the rpl10-S104D growth defect ( Fig 3B ) . Depletion of Efl1 also prevents Tif6 release [18 , 29] . We transformed a glucose-repressible EFL1 strain ( PGAL-EFL1 ) with either WT or mutant TIF6 or NMD3 vectors and plated onto glucose-containing medium . Again , we found that while TIF6-V192F could suppress Efl1 depletion , neither NMD3-Y379D nor TIF6-G189V suppressed the loss of Efl1 ( Fig 3C ) . These results suggest that the mechanism ( s ) by which NMD3-Y379D and TIF6-G189V restored Tif6 release in rpl10-R98S cells is not a general Tif6-promoting mechanism , but specifically bypasses the rpl10-R98S defect . We recently resolved the structure of Nmd3 on the 60S subunit [22] , providing important insights into how Rpl10 , Nmd3 , and Tif6 interact . Nmd3 consists of three domains: an eIF5A-like domain associates with the L1 stalk and occupies the ribosomal E site , an eL22-like domain occupies the P site and displaces the Rpl10 P site loop from its observed position in mature ribosomes ( Fig 4A ) , while the N-terminal domain extends from the P site toward the SRL and contacts Tif6 , providing a direct link between Nmd3 and Tif6 ( Fig 4A and 4B ) . That we could resolve the N-terminal domain of Nmd3 only in the presence of Tif6 suggests that Tif6 stabilizes Nmd3 through their direct interaction . Importantly , all TIF6 alleles that suppress rpl10-R98S can be mapped to this Tif6-Nmd3 interface ( Fig 4B ) . In addition , several of the rpl10-R98S suppressing mutations in NMD3 also occur in the zinc-binding N-terminal domain that contacts Tif6 ( Table 1 ) . Although the resolution of the N-terminal 39 residues of Nmd3 was not sufficient to unambiguously trace chains , it is likely that the mutated residues within this domain of Nmd3 affect its interaction with Tif6 . In addition to mutations in the N-terminal domain of Nmd3 , the majority of mutations that suppressed rpl10-R98S occurred in the eL22- and eIF5A-like domains of Nmd3 , and mapped to the Nmd3-60S interface ( Table 1 , Fig 4C ) . We therefore considered the possibility that these mutations in Nmd3 might alter its interaction with the 60S subunit . Although residue Y379 , ( mutated in the NMD3-Y379D suppressor ) does not make a direct interaction with the ribosome , it is located between N378 and N380 , which make hydrogen bonds to eL42 and 25S rRNA , respectively ( Fig 4D ) . The substitution of aspartate for tyrosine at position 379 likely destabilizes these interactions , leading to suppression of rpl10-R98S . To test this idea , we made alanine substitutions in N378 and N380 to directly disrupt their interactions with the ribosome and asked whether this mutant , NMD3-N378A , N390A , could suppress the rpl10-R98S growth defect . Indeed , the NMD3-N378A , N390A mutant suppressed the rpl10-R98S growth defect to a similar degree as NMD3-Y379D ( Fig 4E ) . To further test if the Nmd3 mutants identified as rpl10-R98S suppressors altered the interaction between Nmd3 and the 60S subunit , we compared the co-sedimentation of wild-type and mutant Nmd3 with 60S subunits . We tested the eIF5A-like domain mutant , NMD3-Y379D , and an N-terminal domain mutant , NMD3-C35G , both of which could complement in the absence of wild-type NMD3 ( S1 Fig ) . We found that while wild-type Nmd3 sedimented predominantly in the 60S-containing fractions and was absent from the top of the gradient ( indicating that very little free protein was present in cells ) , both Nmd3-Y379D and Nmd3-C35G mutant proteins were enriched in the free protein fractions at the top of the gradients ( Fig 4F ) . A larger population of free protein relative to 60S-bound Nmd3 could result from a weakened affinity of Nmd3 for the 60S subunit , or from an increased rate of Nmd3 release . While sedimentation cannot distinguish between these possibilities , each scenario suggests an altered interaction between Nmd3 and the 60S subunit . Nmd3-C35G is predicted to disrupt the stabilizing interaction between Nmd3 and Tif6 . To further test the significance of this interaction , we asked if the rpl10-R98S suppressing TIF6 mutations had an impact on Nmd3 sedimentation . We compared Nmd3 sedimentation in cells expressing either wild-type or mutant TIF6 as the sole copy . We found that both mutants tested ( TIF6-G189V and TIF6-P163L ) could complement in the absence of wild-type TIF6 ( S2 Fig ) . However , while the majority of Nmd3 was found in the 60S fraction in wild-type TIF6 cells , Nmd3 was distributed in 60S fractions as well as lighter fractions in TIF6-G189V and TIF6-P163L cells ( Fig 4G ) . This altered Nmd3 sedimentation observed in TIF6 mutants suggests that , like rpl10-R98S suppressing mutations in NMD3 , mutations in TIF6 alter the interaction of Nmd3 with the 60S subunit . In our recent Nmd3-60S structural work , we observed Nmd3 engaged with the L1 stalk in multiple L1 stalk positions , ranging from partially open to fully closed [22] . In the fully closed position , the eL22-like domain of Nmd3 occupies the ribosomal P site in a position that is incompatible with Sdo1 binding in the P site . Nmd3 binding in the P site should therefore prevent the Sdo1-dependent activation of Efl1 . We tested this idea in vitro with purified components . It has been shown previously that Sdo1 activates the GTPase activity of Efl1 in the presence of 60S subunits [33] . We used this assay to ask if Nmd3 would inhibit Sdo1-dependent Efl1 activity . We found that although Nmd3 binds to 60S subunits and activates Lsg1 [22] , the presence of Nmd3 did not inhibit the Sdo1-dependent activation of Efl1 ( Fig 5A ) . We were unable to test the effect of Tif6 stabilization of Nmd3 because in our hands the addition of Tif6 completely inhibits Sdo1-dependent Efl1 GTPase activity ( S3 Fig ) . The rpl10-R98S mutant blocks both Tif6 and Nmd3 release in vivo , and genetic suppression of this T-ALL associated mutant showed that mutations in Nmd3 restored Tif6 release . In addition , rpl10-R98S suppressing mutations alter the interaction of Nmd3 with 60S subunits , possibly destabilizing Nmd3 binding in the P site . Based on these observations , we considered that the Tif6 release defect in rpl10-R98S mutant ribosomes might be attributed to stabilization of Nmd3 in the P site , thereby blocking Sdo1 binding . We reasoned that the suppressing mutations identified in NMD3 could destabilize Nmd3 from the fully engaged state in the P site . We found that whereas the addition of Nmd3 to wild-type subunits had no effect on Sdo1-dependent activation of Efl1 , the addition of Nmd3 to rpl10-R98S subunits inhibited Sdo1-dependent activation of Efl1 GTPase ( Fig 5B , compare lanes 3 and 4 to lanes 7 and 8 ) . In contrast , the addition of Nmd3-Y379D , which suppresses the rpl10-R98S mutant in vivo , restored Sdo1-dependent activation of Efl1 GTPase in the presence of rpl10-R98S subunits ( Fig 5B , lane 9 ) . Thus , a mutation that alters the interaction of Nmd3 with the subunit overcomes the defect in Efl1 activation . These results strongly suggest that the molecular defect of the T-ALL-associated rpl10-R98S mutation is stabilization of Nmd3 in the P site where it blocks productive binding of Sdo1 . We considered the possibility that the Nmd3-Y379D mutant failed to inhibit Efl1 activity due to a weakened affinity for 60S subunits . To test this , we used an in vitro assay for Nmd3-dependent Lsg1 activation . Because we previously showed that Nmd3 binding to 60S subunits was required for Lsg1 GTPase activation [22] , we used Lsg1 activation as a proxy to test Nmd3 binding . We compared Lsg1 activation in the presence of either wild-type 60S subunits or rpl10-R98S 60S subunits and either wild-type Nmd3 or Nmd3-Y379D . We found that wild-type Nmd3 stimulated Lsg1 GTPase on both wild-type and rpl10-R98S 60S subunits ( Fig 5C , lanes 4 and 8 , Fig 6D ) . Interestingly , rpl10-R98S subunits supported slightly higher stimulation of Lsg1 GTPase activity compared to wild-type subunits . A similar increase in Lsg1 activity was previously observed in the presence of Tif6 , which stabilizes Nmd3 in the fully engaged conformation where the eL22-like domain occupies the P site [22] . Thus , the increase in Lsg1 activation with rpl10-R98S subunits provides additional evidence that rpl10-R98S subunits trap Nmd3 in the fully engaged conformation . In contrast to wild-type Nmd3 , Nmd3-Y379D supported only a low level of Lsg1 activation in the presence of wild-type 60S ( Fig 5C , compare lanes 4 and 5 ) . If Nmd3-Y379D simply had a reduced affinity for subunits , we would expect the reduced Lsg1 activity to be overcome at higher concentrations of Nmd3-Y379D , where more Nmd3 protein would be bound . However , Lsg1 activity was not recovered by increasing the concentration of Nmd3 ( Fig 5D ) . Because the eIF5A domain of Nmd3 can bind to the L1 stalk independently of the eL22 domain binding in the P site , increasing concentrations of Nmd3 may saturate binding to the ribosome via the L1 stalk without increasing binding in the P site , explaining the lower activation of Lsg1 by Nmd3-Y379D on wild-type ribosomes . Interestingly , in the presence of rpl10-R98S subunits , Nmd3-Y379D stimulated Lsg1 to a greater extent than that observed for wild-type Nmd3 with wild-type 60S subunits ( Fig 5C and 5D ) . This suggests that rpl10-R98S subunits might stabilize both wild-type and mutant Nmd3 in the P site , but Nmd3-Y379D can be repositioned in the presence of Sdo1 . Together , these results argue strongly that the T-ALL-associated mutation rpl10-R98S traps Nmd3 in the P site . Mutations in Nmd3 that suppress rpl10-R98S weaken the interaction of Nmd3 with the P site , restoring the ability of Nmd3 to be retracted from the P site in the presence of Sdo1 .
Mutations in the ribosomal protein Rpl10 ( uL16 ) can be drivers of T-ALL [40] . We previously showed that these T-ALL mutations , including rpl10-R98S , disrupt late steps in cytoplasmic maturation of the 60S subunit , preventing the release of Nmd3 and Tif6 [40] . However , in that work we did not identify the molecular mechanism that led to the block in Tif6 and Nmd3 release . Because genetic analysis had placed the release of Nmd3 after the release of Tif6 [28] , we expected that mutations that enhanced the release of Tif6 would suppress rpl10-R98S . Indeed , we had shown that one such mutant , TIF6-V192F , suppressed some mutations within the P site loop of Rpl10 ( rpl10-S104D ) . Surprisingly , we found here that TIF6-V192F could not suppress rpl10-R98S . Instead , we found that mutations that enhanced the release of Nmd3 could suppress rpl10-R98S . This was difficult to reconcile with our earlier genetic analysis . However , recent atomic structures of Nmd3 on the 60S subunit revealed that Nmd3 spans the joining face of the 60S subunit , interacting with Rpl1 ( uL1 ) of the L1 stalk , stretching through the E and P sites , and interacting directly with Tif6 [22 , 23] . Notably , the domain of Nmd3 in the P site would sterically block Sdo1 binding and prevent Tif6 release . Based on this structure , we proposed that Nmd3 interaction with Tif6 must be broken to permit the retraction of Nmd3 from the P site by the opening of the L1 stalk [22] . This retraction would allow Sdo1 to bind in the P site to trigger the release of Tif6 . Thus , a model emerged that the defect of rpl10-R98S may be a failure in retraction of Nmd3 from the P site ( Fig 6 ) . The eL22-like domain of Nmd3 contains an extended loop that projects into the mouth of the polypeptide exit tunnel . Because the P site loop of Rpl10 and the loop of Nmd3 occupy a similar position , it was recently suggested that the loading of Rpl10 could potentially influence Nmd3 release [23] . Arginine 98 is at the base of the Rpl10 loop and interacts with the sugar phosphate backbone of residues 1126 and 1127 of 25S rRNA . Loss of this interaction is expected to destabilize the P site loop and alter the interaction between Nmd3 and Rpl10 . Although this could , in principle , affect the loading of Rpl10 , our results indicate that the R98S mutation prevents the retraction of Nmd3 from the P site rather than the loading of Rpl10 . This model of rpl10-R98S function is strongly supported by the genetic and biochemical results reported here . We identified mutations in NMD3 and TIF6 that were extragenic suppressors of rpl10-R98S . These mutations mapped to the interface between Nmd3 and the 60S subunit and between Nmd3 and Tif6 and altered the interaction of Nmd3 with the 60S subunit . In addition , mutations in Nmd3 engineered to specifically disrupt hydrogen bonding with eL42 and rRNA also suppressed rpl10-R98S . Thus , mutations that destabilized Nmd3 on the pre-60S subunit suppressed rpl10-R98S . From a genetic perspective , it may seem counterintuitive that mutations that weaken the affinity of Nmd3 for the ribosome can act as dominant suppressors . However , their dominant nature can be readily explained . For example , wild-type Nmd3 will become trapped on pre-60S subunits in the cytosol , preventing entry of those 60S subunits into the translating pool but also sequester wild-type Nmd3 on the stalled subunits . Mutant Nmd3 that can be released will recycle to the nucleus unimpeded and support ribosome production . We were also able to recapitulate the genetic effects of rpl10-R98S and suppression by mutations in Nmd3 with a reconstituted system of purified components . For this work , we used the activation of Efl1 by Sdo1 as a proxy for productive Sdo1 binding . Whereas wild-type Nmd3 did not compete with Sdo1 for binding in the P site on wild-type ribosomes , Nmd3 inhibited Sdo1 binding in the presence of rpl10-R98S ribosomes . Furthermore , this inhibition was reversed by an Nmd3 mutant , Nmd3-Y379D , that suppresses rpl10-R98S mutant cells in vivo . These results identify the defect of rpl10-R98S-containing ribosomes as a failure to release Nmd3 from the P site , and show that suppressing mutations bypass the entrapment of Nmd3 by destabilizing interactions of Nmd3 with the 60S subunit . We proposed previously that Nmd3 is retracted from the P site by opening of the L1 stalk [22] . But whether Nmd3 release is coincident with retraction of the stalk or is a subsequent step remains an unanswered question . The persistence of Nmd3 binding to the L1 stalk could explain the observation that lsg1 mutants , or the depletion of Lsg1 , prevent recycling of Nmd3 but not Tif6 [22 , 31] , leading to the conclusion that Nmd3 is released after Tif6 . Although our results cannot definitively distinguish between these two models , several observations lead us to favor the latter . First , single particle reconstruction of the Nmd3-60S complex revealed Nmd3 bound to the L1-stalk in multiple conformations from partially open to fully closed , suggesting that Nmd3 interaction with Rpl1 is maintained independently of other interactions on the subunit [22] . And second , Nmd3-Y379D , which bypassed the inhibition of Efl1 activation on rpl10-R98S subunits , could efficiently stimulate Lsg1 GTPase on rpl10-R98S subunits . However , in the presence of wild-type 60S subunits , Nmd3-Y379D failed to activate Lsg1 to the same degree as did wild-type Nmd3 , regardless of the concentration of protein . If Nmd3-Y379D simply had lower affinity for 60S , we would expect the defect in Lsg1 activation to be overcome at higher concentrations of Nmd3-Y379D . That we did not observe this is consistent with the interpretation that Nmd3-Y379D binding to the L1 stalk could be saturated , but its lower affinity for the P site prevented maximal activation of Lsg1 . Thus , the Y379D mutation preferentially affects Nmd3 binding in the P site relative to overall subunit binding . Thus far , our results imply a fairly simple model for suppression of rpl10-R98S—weakened interaction of Nmd3 for the subunit overcomes the retention of Nmd3 in the P site . This can be accomplished by mutations in Nmd3 or Tif6 , all of which appear to reduce the affinity of Nmd3 for the ribosome . However , we would also expect mutations that weaken the affinity of Tif6 for the ribosome , such as TIF6-V192F , to suppress rpl10-R98S . That they do not suppress suggests additional subtleties to the mechanism of Nmd3 release . One interpretation is that bypass of rpl10-R98S requires stable association of Tif6 with the subunit . Although Efl1 does not appear to be required for the release of Nmd3 from wild-type subunits , it may assist in dislodging Nmd3 from the P site in rpl10-R98S mutant subunits . The molecular defect of rpl10-R98S revealed in this work in yeast is likely relevant to human ribosomes in T-ALL patient cells . This conclusion is based on the high degree of conservation of Nmd3 and Rpl10—both human proteins can replace their yeast counterpart [12 , 46] and the amino acid sequence of Rpl10/uL16 is highly conserved across eukaryotes , with amino acid 98 invariantly an arginine . In addition , rpl10-R98S patients express only mutant RPL10 in the mutated cells , and rpl10-R98S inhibited ribosome biogenesis in mammalian cells , as we have observed in yeast [40] . However , how this defect in ribosome biogenesis ultimately promotes T-ALL is not understood . We previously demonstrated that the rpl10-R98S mutation had a severe impact on yeast ribosomes at both the structural and functional level , and proposed that rpl10-R98S promotes defective translational fidelity [42] . Within the context of T-ALL , we suspect that rpl10-R98S is a mutation arising early in disease pathogenesis . Whereas translation fidelity defects might support disease development by shifting the spectrum of expressed proteins toward a more oncogenic profile , the ribosome biogenesis defect and resulting lack of functional ribosomes is probably not beneficial for pre-leukemic cells , likely imposing high pressure on these cells to acquire additional mutations that suppress the biogenesis defect . While suppression would reverse the proliferation defect , it may come at the risk of allowing defective ribosomes to be used in translation . So far , the nature of suppressor mutations acquired in rpl10-R98S positive T-ALLs is unclear . Mutations in NMD3 and eIF6 ( human Tif6 ) have not been detected in human rpl10-R98S positive T-ALL cases [42 , 47] , suggesting that alternative suppressor mutations occur in the human patients . Thus , a current challenge is to identify and characterize rpl10-R98S suppressing mutations in T-ALL positive cells .
Yeast strains and plasmids used in this work are listed in Tables A and B of S1 Text . Oligos used in this work are listed in Table C of S1 Text . All cells were grown at 30°C in rich media ( yeast extract and peptone ) or appropriate synthetic drop-out medium with 2% glucose or 1% galactose as the carbon source . Strains AJY2781 and AJY2784 were made by introducing plasmid pAJ2522 or pAJ2726 into the rpl10 deletion strain AJY1437 [32] by plasmid shuffle . Spontaneous suppressing mutations were identified in the AJY2784 background , including NMD3-Y379D ( AJY2846 ) and TIF6-G189V ( AJY2848 ) . AJY2781 , AJY2784 , AJY2846 , and AJY2848 were used to generate AJY3937 , AJY3938 , AJY3939 , and AJY3940 , respectively: pDEGQ2 was introduced into each strain , and the TIF6-GFP::His3MX cassette ( amplified from TIF6-GFP cells ( Open Biosystems ) using AJO454 and AJO1384 ) was integrated into the genome by homologous recombination . AJY3909 was made by crossing AJY2846 and AJY1837 [31] and AJY3943 was made by crossing AJY2848 with AJY1958 . Strain AJY1958 was made by crossing relevant mutants . To make AJY3941 , the TIF6 locus was amplified in two parts from TIF6-GFP strain ( Open Biosystems ) genomic DNA , using mutagenic oligos to introduce the V192F mutation . The 5’ half of TIF6-GFP was amplified using AJO453 and AJO933 , and the remaining half of was amplified with AJO932 and AJO454 , such that the two PCR products overlapped . PCR products derived from these reactions were used in a final reaction to make the full length TIF6-V192F-GFP PCR product , which was integrated into the genome of AJY3901 ( NatMX::PGAL-RPL10 Δtif6::KanMX ) by homologous recombination . AJY3249 was made by amplifying the His3MX-PGAL1-3HA cassette [48] with homology to the NMD3 locus using AJO2031 and AJO2032 , integrating into BY4743 ( Open Biosystems ) , followed by sporulation and dissection . To make pAJ2805 , NMD3-Y379D was gap-rescued from the genome of AJY2846 using pAJ409 digested with SnaBI and HpaI . NMD3-Y379D was amplified from pAJ2805 using oligos AJO360 and AJO2035 , digested with NdeI and SpeI restriction enzymes , and ligated into the same sites in pAJ2392 . pAJ3609 was generated by inverse PCR of pAJ409 using oligos AJO2558 and AJO2554 . Similarly , pAJ3581 was made by inverse PCR of pAJ409 using AJO2704 and AJO2705 . pAJ729 was made by amplifying the TIF6 locus from genomic DNA using oligos AJO453 and AJO454 . PCR product was digested with SalI and HindIII and inserted into the same sites in pRS426 . pAJ2846 was made by digesting TIF6 sequence from pAJ2665 [32] with BamHI and XhoI and ligating into the same sites in pRS415 . pAJ2828 was made by inverse PCR using oligos AJO1820 and AJO1821 with pAJ2665 as template . To make pAJ2833 , the TIF6-G189V sequence was digested from pAJ2828 using SstI and XhoI enzymes , and ligated into the same sites in pRS415 . pAJ3023 was made by digesting the TIF6 allele from pAJ2828 using XhoI and SacI enzymes , and ligating into the same sites in pRS426 . pAJ3024 was generated by digesting TIF6-V192F from pAJ2240 [32] using XhoI and BamHI enzymes , and ligating into the same sites in pRS426 . pAJ2839 and pAJ2840 were made by digesting RPL10 from pAJ2522/pAJ2726 using SacI and BamHI , and ligating into the same sites in pRS313 . To make pAJ2982 , genomic DNA was amplified using oligos AJO1413 and AJO1414 , digested with NdeI and XhoI restriction enzymes , and inserted into the same sites in pET21a . The kemptide tag was added by inverse PCR using AJO1762 and AJO1763 . To make pAJ3114 , an internal 8HIS tag was integrated between EFL1 amino acids 458 and 459 in a pET21d vector containing EFL1 with its natural C-terminus . Spontaneous suppressors of rpl10-R98S were identified in AJY2784 . Individual slow-growing colonies were cultured independently and passaged several times before plating . After streaking for single colonies , large ‘fast-growing’ colonies were isolated and genomic DNA was prepared . The RPL10 allele was amplified ( using AJO264 and AJO268 ) and sequenced to confirm that cells had not reverted to WT . The NMD3 allele was amplified ( using AJO238 and AJO329 ) and sequenced to identify NMD3 suppressing alleles . The identified NMD3- Y379D suppressor was saved as strain AJY2846 . The TIF6-G189V mutant was identified by high-throughput SOLiD sequencing of gDNA from a suppressor isolate , saved as strain AJY2848 . Sequencing and SNP analysis was carried out by the Genome Sequencing and Analysis Facility at the University of Texas at Austin . The open reading frame of TIF6 was randomly mutagenized by PCR using Taq DNA polymerase and oligos AJO453 and AJO454 , with wild-type TIF6 plasmid pAJ2846 as template . PCR product was then co-transformed with gapped starting vector , to allow recombination of the mutagenized PCR products back into the starting vector , in AJY3901 . Fast growing colonies were selected and TIF6-containing plasmids were extracted and sequenced . TIF6 mutant plasmids were then re-introduced into rpl10-R98S cells to confirm suppression . For direct fluorescence experiments , cells were grown to saturation in selective medium containing galactose , then diluted back 20-fold in medium containing 2% glucose and grown for an additional hour to repress the expression of genomic RPL10 . Images were captured using a Nikon E800 microscope fitted with a 100x Plan Apo objective and a Photometrics CoolSNAP ES camera controlled by NIS- Elements software . For indirect immunofluorescence , cells were grown in selective medium containing galactose before adding glucose to 2% to repress the expression of wild-type genomic RPL10 for 2h . LMB was added to a final concentration of 0 . 1 μg/ml for 15 min to block Nmd3 shuttling . Cells were fixed with a 1:9 volume of 37% formaldehyde for 40min , then washed with Ksorb buffer ( 0 . 1 M potassium phosphate [pH 6 . 6] , 1 . 2 M sorbitol ) . Cells were permeabilized in cold methanol followed by washing in acetone . Anti-Nmd3 antibody [49] was diluted 3 , 000 fold in PBS with 0 . 1% BSA . Cy3-conjugated donkey anti—rabbit antibody ( Jackson ImmunoResearch Laboratories , Inc . ) was used at a 300-fold dilution . After antibody application , cells were incubated for 1 min in 1 μg/ml DAPI and mounted in Aqua-Poly/Mount . For polysome profile analysis , cells were initially grown to saturation in the presence of galactose then diluted back to 3x106 cells/ml in glucose-containing media , and growth was continued until cultures reached 1 . 2x107 cells/ml . 100μg/ml cycloheximide ( CHX ) was added to each culture , followed by incubation for an addition 10min at 30°C . Cultures were then immediately poured over ice and harvested by centrifugation . To monitor Nmd3 sedimentation , cells were grown only in glucose-containing selective media . Liquid cultures were grown to mid-log phase , treated with CHX and harvested as previously described . Cell extracts were prepared at 0–4°C: Cells were washed with lysis buffer ( 100mM KCl , 50mM Tris-HCl pH 7 . 5 , 5mM MgCl2 , 100μg/ml CHX , 6mM beta-mercaptoethanol ( βME ) , 1mM PMSF , 1μg/ml leupeptin , 1μg/ml pepstatin A ) , and lysed by vortexing in the presence of glass beads . Extracts were clarified by centrifugation for 10 min at 15 , 000 g at 4°C , and 9A260 units of clarified extract were loaded onto 7–47% sucrose gradients , prepared in lysis buffer , and centrifuged for 2 . 5 hours at 40 , 000 rpm ( Beckman SW40 ) . Gradients were fractionated ( ISCO Model 640 ) with continuous monitoring at 254nm . To monitor Nmd3 sedimentation , fractions were precipitated with 100% EtOH overnight at -20°C , then centrifuged for 30min , 15 , 000 g at 4°C . Pellets were resuspended in Laemmli buffer and boiled at 99°C for 3 min . Proteins were separated on 10% SDS-PAGE gels , transferred to a nitrocellulose membrane , and subjected to Western blot analysis using anti-Nmd3 [49] and anti-Rpl8 ( from K . Lo ) antibodies . Specified amounts of Efl1 , Sdo1 , Lsg1 , Nmd3 , and 60S , as indicated in the figure legends , were mixed in a 20ul volume in 1x GTPase buffer ( 20mM HEPES-KOH , pH 7 . 4 , 2mM MgOAc , 50mM KOAc , 1mMDTT ) containing 25uM GTP . Reactions were spiked with approximately 1x105 cpm of [gamma -32P]-GTP to trace the hydrolysis of gamma phosphate . Reactions were incubated at 30°C for 10 minutes and stopped by addition of 5ul of 0 . 5M EDTA . 1ul of each reaction was spotted on a TLC plate ( PEI-cellulose , Sigma-Aldrich ) . Free phosphate was separated from GTP by developing the TLC plate for 10 minutes in 0 . 8M LiCl , 0 . 8M CH3COOH . Plates were imaged on a phosphoimager screen and signal intensities for free phosphate and GTP were analyzed using ImageJ software . All samples were corrected for non-enzymatic background hydrolysis . Reactions containing Nmd3 were corrected for background hydrolysis by free Nmd3 protein . Percent GTP hydrolysis was calculated as ( free phosphate/total phosphate ) and picomoles of phosphate release were calculated as Percent GTP hydrolysis*[GTP] . Picomole phosphate release values from Nmd3 titration assays were fitted to saturating-specific single site binding curves using Graphpad Prizm software . Lsg1-6His: Yeast Lsg1 protein with a C-terminal 6xHis tag was purified from Codon plus ( RIL ) E . coli cells ( Stratagene ) with pAJ3420 as described in [22] . MBP-TEV-His6-Nmd3: For WT Nmd3 1 liter of BJ5464 with pAJ1381 was grown to OD600 of 0 . 6 in selective medium containing 2% glucose . For Nmd3-Y379D , 25 ml overnight culture of BJ5464 with pAJ2849 grown in selective medium with 2% glucose was diluted to OD600 = 0 . 03 in 100ml of same medium and grown for 8–10 hours , then diluted to OD600 = 0 . 03 in 500ml of selective medium with 1% raffinose and grown overnight at 30°C . The culture was then induced at OD600 = 0 . 4 by adding galactose to 1% final concentration . Both WT and mutant proteins were purified using the same method: cells were harvested , washed , and resuspended in two volumes of extract buffer ( 50mM Tris , pH 8 , 450mM NaCl , 100 mM KCl , 10% glycerol , 1mM PMSF , 1μg/ml leupeptin , 1μg/ml pepstatin A ) . Cells were disrupted by vortexing with glass beads and crude extract was clarified by centrifugation at 4°C , first for 10 min at 10 , 000 g and then for 20 minutes at 25 , 000 g . Imidazole was added to 10mM and clarified lysate was incubated with 0 . 5ml Ni-NTA Agarose beads ( Invitrogen , R901-15 ) equilibrated in extract buffer for 1 hour at 4°C . The beads were washed twice with 10ml of extract buffer containing 10mM and 20mM imidazole respectively and the protein was eluted in 0 . 25ml fractions of extract buffer supplemented with 250mM imidazole . Fractions containing protein were pooled and diluted in 9 volumes of Q buffer ( 40mM Tris-HCl , pH 7 . 0 , 10% glycerol and 1mM DTT ) . Bound proteins were eluted with a 20ml linear NaCl gradient ( 50mM to 1M ) in Q buffer . Fractions containing Nmd3 were pooled and dialyzed in 20mM Tris , pH7 . 5 , 150mM KOAc , 1mM DTT and 10% glycerol . Dialyzed protein was stored at -80°C . Efl1-internal His8: Yeast Efl1 protein with an internal 8xHis tag in domain II of the protein was purified from Codon plus ( RIL ) E . coli cells ( Stratagene ) with pAJ3114 . 1 liter of bacterial culture was grown to OD600 of 0 . 5 and induced with 1mM IPTG for 4 hours at 30°C . Cells were harvested and washed with Lysis buffer ( 40mM Tris , pH 8 . 0 , 500mM NaCl and 10% glycerol ) . The cell pellet was resuspended in 40ml Lysis buffer ( supplemented with 5mM βME , 1mM PMSF and 1μM each leupeptin and pepstatin ) and disrupted by sonication . Lysates were cleared by centrifugation at 20 , 000 g for 20 minutes . Imidazole was added to 10mM . Clarified lysate was bound to a 1ml Ni-NTA column ( HisTrap HP , GE Healthcare ) by pumping at 1ml/min . The column was first washed with 10ml lysis buffer supplemented with 10mM imidazole and 5mM βME and then with low salt buffer ( 40mM Tris , pH 8 . 0 , 50mM NaCl , 10% glycerol , 20mM imidazole and 5mM βME ) . Bound protein was eluted with low salt buffer with 125mM imidazole . Fractions containing protein were pooled and bound to 2ml Source Q ( GE Healthcare ) column pre-equilibrated with buffer A ( 100mM Tris pH 8 . 0 , 50mM NaCl , 2mM DTT and 0 . 2mM EDTA ) . Column was washed with 10ml buffer A . Bound proteins were eluted with a 20ml linear NaCl gradient ( 50mM to 1M ) in buffer A . Fractions containing Efl1 were pooled and dialyzed in 20mM Tris , pH 7 . 5 , 150mM KOAc , 1mM DTT and 10% glycerol . Dialyzed protein was stored at -80°C . Sdo1-kemptide-6His: Yeast Sdo1 protein with C-terminal kemptide and 6xHis tag was purified from Codon plus ( RIL ) E . coli cells ( Stratagene ) with pAJ2982 . 1 liter of bacterial culture was grown to OD600 of 0 . 5 and induced with 1mM IPTG for 4 hours at 30°C . Cells were harvested and washed with Lysis buffer ( 40mM Tris , pH 8 . 0 , 500mM NaCl and 10% glycerol ) . The cell pellet was resuspended in 40ml Lysis buffer ( supplemented with 5mM βME , 1mM PMSF and 1μM each leupeptin and pepstatin ) and disrupted by sonication . Lysates were cleared by centrifugation at 20 , 000 g for 20 minutes . Imidazole was added to 10mM . Clarified lysate was bound to a 2 ml Ni-NTA column ( HisTrap HP , GE Healthcare ) by pumping at 1ml/min . The column was first washed with 20ml lysis buffer supplemented with 10mM imidazole and 5mM βME and then with 20ml lysis buffer supplemented with 30mM imidazole and 5mM βME . Bound protein was eluted using lysis buffer with 250mM imidazole in 0 . 67ml fractions . Fractions containing Sdo1 protein were pooled and loaded on 150ml Sephacryl S-200 ( Pharmacia ) gel filtration column pre-equilibrated in S-200 buffer ( 40mM Tris-HCl pH 8 . 0 , 150mM NaCl , 10% glycerol , 5mM βME ) . Bound protein was eluted in S-200 buffer . Fractions containing Sdo1 were pooled and dialyzed in 20mM Tris , pH 7 . 5 , 150mM KOAc , 1mM DTT and 10% glycerol . Dialyzed protein was stored at -80°C . Yeast strains AJY2781 and AJY2846 were grown in 2L of YPD to OD600 of 1 . 0 . Cells were transferred to ice for 1h before harvesting by centrifugation at 4°C . Cell pellets were washed and resuspended in 6ml of binding buffer ( 20mM HEPES-KOH , pH 7 . 6 , 60mM NH4Cl , 5mM Mg ( oAc ) 2 , 2mM DTT , 1mM PMSF ) . Cells were disrupted by glass bead lysis and cleared by centrifugation at 30 , 000 g for 25 min at 4°C . Active 80S ribosomes were purified from cell extracts using cysteine-charged sulfolink columns as described [41] . To dissociate subunits , ribosome pellets were resuspended in 1ml elution buffer ( 20mM HEPES-KOH , pH 7 . 6 , 60mM NH4Cl , 500mM KCl , 10mM Mg ( oAc ) 2 , 2mM DTT , 1mM PMSF and 1uM each leupeptin and pepstatin ) and incubated at 37°C for 30 min after the addition of puromycin and GTP , each to 1mM final concentration . The sample was then centrifuged through 10–30% sucrose gradients in elution buffer for 4h at 32 , 000 rpm in an SW40 rotor ( Beckman Coulter ) . Fractions containing the 60S and 40S peaks were pooled separately and concentrated using an Amicon Ultra-4 50 K ( Millipore ) , and buffer was changed to Ribosome storage buffer ( 20mM HEPES-KOH , pH 7 . 6 , 100mM KCl , 5mM Mg ( oAc ) 2 , 2mM DTT , 250mM sucrose ) .
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The ribosome is a large and structurally complex macromolecular machine , responsible for synthesizing proteins in all living cells , across all domains of life . The correct assembly of ribosomes is important for their ability to faithfully decode messenger RNAs and synthesize proteins . The insertion of the ribosomal protein Rpl10 into the ribosome completes the catalytic center of the large subunit and is necessary for the removal of the assembly factors Nmd3 and Tif6 , which allows the subunit to participate in translation . The insertion of Rpl10 is monitored by proteins that mimic translation factors during a quality control check for ribosome function . Ribosomes containing mutations in Rpl10 associated with pediatric T-cell leukemia fail in this quality control check and prevent the removal of Tif6 and Nmd3 . However , it was not known how these mutations in Rpl10 block the quality control check . We recently presented the structure of Nmd3 and Tif6 on the large ribosomal subunit from yeast . In this work , we take advantage of our recent structural work and use a combination of genetic and biochemical techniques to delineate the molecular defect in the ribosome when Rpl10 is mutated .
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2017
|
The T-cell leukemia related rpl10-R98S mutant traps the 60S export adapter Nmd3 in the ribosomal P site in yeast
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The success of S . pneumoniae as a major human pathogen is largely due to its remarkable genomic plasticity , allowing efficient escape from antimicrobials action and host immune response . Natural transformation , or the active uptake and chromosomal integration of exogenous DNA during the transitory differentiated state competence , is the main mechanism for horizontal gene transfer and genomic makeover in pneumococci . Although transforming DNA has been proposed to be captured by Type 4 pili ( T4P ) in Gram-negative bacteria , and a competence-inducible comG operon encoding proteins homologous to T4P-biogenesis components is present in transformable Gram-positive bacteria , a prevailing hypothesis has been that S . pneumoniae assembles only short pseudopili to destabilize the cell wall for DNA entry . We recently identified a micrometer-sized T4P-like pilus on competent pneumococci , which likely serves as initial DNA receptor . A subsequent study , however , visualized a different structure - short , ‘plaited’ polymers - released in the medium of competent S . pneumoniae . Biochemical observation of concurrent pilin secretion led the authors to propose that the ‘plaited’ structures correspond to transformation pili acting as peptidoglycan drills that leave DNA entry pores upon secretion . Here we show that the ‘plaited’ filaments are not related to natural transformation as they are released by non-competent pneumococci , as well as by cells with disrupted pilus biogenesis components . Combining electron microscopy visualization with structural , biochemical and proteomic analyses , we further identify the ‘plaited’ polymers as spirosomes: macromolecular assemblies of the fermentative acetaldehyde-alcohol dehydrogenase enzyme AdhE that is well conserved in a broad range of Gram-positive and Gram-negative bacteria .
Despite medical advances and vaccination campaigns , respiratory tract invasion by Streptococcus pneumoniae remains a leading mortality cause worldwide [1–3] . A particular challenge in the prevention and treatment of pneumococcal infections lies in the bacterium’s striking genomic plasticity , as it allows for efficient antibiotic resistance development , capsular serotype switching and vaccine escape [4] . Horizontal gene transfer and chromosomal rearrangements typically result from the avid uptake and recombination of exogenous DNA known as natural transformation . A strictly regulated event , it occurs during a transitory state of the bacterium’s life cycle—competence—and requires the timed expression of a dedicated set of genes [5] . Among these are the genes of the comG operon , which are conserved among naturally competent Gram-positive bacteria and are homologous to the ones encoding Type 4 pili ( T4P ) and Type 2 secretion system ( T2SS ) pseudo-pili components in Gram-negative bacteria [6 , 7] . Although mechanistic studies of structural determinants for DNA uptake—such as putative transformation-specific cellular appendages—hold promise for the development of novel antiinfectives and helper compounds , there have been only limited and contradictory reports on the initial steps of this important biological process [8–10] . As until recently no pilus-like structure had been observed in any transformable Gram-positive bacterium , it had been postulated that the pneumococcal comG operon encodes a short T2SS-like pseudo-pilus that serves to destabilize the cell wall peptidoglycan for DNA entry [6 , 9 , 11] . The main experimental evidence for this model comes from a different transformable organism , Bacillus subtilis , where pilus length was indirectly deduced from biochemical data [9] . Our team identified a long , micrometer-sized , T4P-like pilus protruding on the surface of competent cells from different pneumococcal strains with wild-type genotype ( Fig 1A ) [10] . Among these are two highly transformable laboratory strains of different genetic background—R6 and TCP1251—as well as a capsulated clinical isolate—the G54 strain [10] . We showed that major constituent of the transformation pilus is the ComGC pilin and that the pilus is sensitive to mechanical stress , which can lead to its detachment from the cell ( shearing ) [10 , 12] . Finally , we showed that this transformation pilus binds extracellular DNA and proposed that it acts as the initial DNA receptor on the surface of competent pneumococci [10] . A subsequent study visualized completely different structures—short , ‘plaited’ polymers—in the medium of competence-induced S . pneumoniae [8] . Biochemical observation of significant ComGC release in the medium during competence convinced the authors that the ‘plaited’ structures corresponded to secreted transformation pili . After failing to immunolabel these structures , they expressed heterologously the whole comG operon in Escherichia coli and visualized the release of similar polymers [8] . Finally , they proposed a model , which is consistent with the classical but speculative model of transformation pseudo-pili: rather than acting as a DNA receptor , the pneumococcal transformation pilus acts as a peptidoglycan-drilling device whose release leaves a gateway for transforming DNA to find the uptake machinery [8 , 10] . Here we show definitive experimental evidence that the short ‘plaited’ filaments are not transformation pili or other structural determinants of natural transformation . We further identify the structures as fermentative spirosomes , or macromolecular complexes of the acetaldehyde-alcohol dehydrogenase enzyme AdhE , which is widely conserved across the bacterial kingdom . Being aware of the limited view and resolution that observation by electron microscopy provides , we underscore the need for thorough validation by orthogonal approaches . Finally , we briefly synthesize the present-day published collective knowledge by proposing an updated model of pneumococcal transformation .
Perhaps the most intriguing aspect of the Balaban et al . study is the distinctive morphology of the reported ‘plaited’ filaments themselves [8] . As the authors point out , the genetic makeup of the comG operon resembles significantly that of operons encoding T4P or T2SS components in Gram-negative bacteria [5 , 7 , 8 , 13] . This includes from sequence homology of the individual genes through their intraoperon organization to the putative bioassembly platform and post-translational modifications of the encoded components . The structure of both T4 pili and T2SS pseudo-pili has been extensively studied [14 , 15] . Generally T4 pilins pack tightly into thin but extremely strong and several micrometers long surface-attached helical filaments [14] . Typical dimensions vary from 5–6 nm width for the T4aP of many bacteria ( Pseudomonas aeurginosa , Neisseria gonorrhoeae and others ) to the thicker , about 8 nm wide T4bP of enteropathogens such as Vibrio cholerae and Salmonella enterica serovar Typhi [14] . Conversely , structural models of T2SS pseudopili , which normally act as short , protein ejecting pistons in the periplasm , present an architecture that is very similar to that of gonococcal T4aP ( Fig 1B ) [15] . Both T4P and T2SS pseudo-pili feature a grooved surface with relatively small protuberations characteristic of the pilin helical packing [14 , 15] . The characteristic structural features of T4P were conserved in the transformation pili that we visualized previously on the surface of competence-induced pneumococci from several different wild-type strains [10] . In contrast , the ‘plaited’ structures visualized subsequently represent short , 40–200 nm long structures that are significantly thicker ( ~ 10 nm ) and present large protuberant domains on their helical surface ( Fig 1C ) [8] . The authors proposed that the filaments are ‘plaited’ , i . e . composed of two interlaced transformation pili [8] . Given the tight pilin packing in known T4P structures , however , we found it quite striking that homologous pili could sustain such a significant deformation to form an interlaced dimer . Although molecular dynamics simulations revealed that T2SS pseudo-pili can adopt a wide range of helical twist angles , they were not shown to have a propensity for short-range bending [16] . Moreover , while many T4P can form bundles , those can be hundreds of nanometers thick , contain a large number of pili and present much more limited distortion at the level of individual filaments [14] . Intrigued by the striking new features of the ‘plaited’ filaments we wanted to see whether the transformation pili we previously reported could form similar structures . We were able to visualize the ‘plaited’ polymers along with the T4P-like long transformation pili in wild-type pneumococci ( Fig 1D ) . However , in a strain with an additional FLAG-tagged ectopic copy of comGC gene for the major pilin [10] ( S1 Table ) , we were able to immunolabel only the long , surface-attached pili using an anti-FLAG antibody ( Fig 1E ) . Similar results were reported by Balaban and colleagues who failed to immunolabel the ‘plaited’ structures with a different antibody raised against ComGC [8] . As negative immunolabeling results are difficult to interpret and can be due to a variety of technical and structural factors , we proceeded to investigate the role of the plaited filaments in competence . We tested three negative control strains carrying either single-gene deletions for essential pilus biogenesis components ( S1 Table ) —the assembly platform protein ComGB [17] or the associated powering ATP-ase ComGA—or expressing a preprocessing incompetent ComGC variant ( ComGCE20V , or ComGCE5V in mature pilin residue numbering ) . As shown previously , although these mutants can express monomeric pilins , they cannot assemble surface exposed pili and are transformation-incompetent [8 , 10 , 17] . In all three ΔcomGA , ΔcomGB and comGCE20V strains we still detected release of ‘plaited’ filaments while expression of the long , T4P-like transformation pilus was abolished ( Fig 1F and Fig 1G and S1 ) . Finally , we observed significant release of these structures even in the absence of competence induction ( Fig 2A ) , further confirming that they are not related to pilus biogenesis during natural transformation . To identify the building subunits of the ‘plaited’ filaments , we developed an enrichment and purification protocol based on differential ultracentrifugation , microfiltration and size exclusion chromatography . Electron microscopy imaging of the purified polymers showed a homogeneous sample composed primarily of the characteristic coiled polymers with an average length of 100–300 nm ( Fig 2A ) . SDS-PAGE analysis of the corresponding fraction showed the presence of a predominant protein species with a molecular weight of ~100 kDa . LC-MS/MS proteomic analyses on the excised , trypsin-digested gel band , as well as on the total purified filaments fraction ( S2 Table ) , unambiguously identified the predominant protein as bifunctional acetaldehyde-alcohol dehydrogenase AdhE , and the result was validated biochemically by Western blot detection using an anti-AdhE antibody ( Fig 2B ) . Heterologous expression of the S . pneumoniae adhE gene in Escherichia coli and affinity purification of the expressed protein showed spontaneous coiled filament formation in the eluted fraction ( Fig 2C ) . Finally , the protein composition of the ‘plaited’ polymers was validated by affinity pull-down with anti-FLAG antibody-conjugated resin on samples from a S . pneumoniae strain carrying an additional ectopic adhE gene copy for competence-inducible expression of a C-terminally FLAG-tagged protein ( Fig 2D ) . AdhE is a 98 kDa protein with an N-terminal acetylating aldehyde dehydrogenase domain ( AldDH ) and a C-terminal Fe-dependent alcohol dehydrogenase domain ( Fe-ADH ) ( Fig 2E ) [18] . Homologous dual domain proteins are common among fermentative bacteria and are reported to catalyze the NADH-dependent conversion of acetyl-CoA to ethanol via an aldehyde intermediate . Most importantly , in many species AdhE has been shown to polymerize into fine helical filaments called spirosomes [19–26] that are morphologically consistent with the ‘plaited’ filaments discussed here and reported as self-secreting , ‘plaited’ transformation pili by Balaban and colleagues [8] . A high resolution structural model of spirosome assembly by the closely homologous AdhE of Geobacillus thermoglucosidasius shows multimeric arrangement of the individual subunits into a right-handed spiral filament with six protomers per helical turn and overall pitch and width parameters consistent with negatively stained class averages of its pneumococcal counterpart ( Fig 2E and 2F ) [19] . It is also important to note that the proposed spirosome structure—which is based on crystallographic and in-solution biophysical data , homology modeling and in silico macromolecular docking—corresponds to a single-start helix rather than a ‘plaited’ polymer of two or more interlaced filaments [19] . To examine a putative role of AdhE in natural transformation , we first followed the protein’s expression over the course of competence induction that was verified by the detection of a competence-inducible FLAG-tagged ectopic copy of ComGC . While we have shown competence-specific ComGC expression in wild-type genetic background previously [10] , AdhE protein levels remained stable over the course of the experiment ( Fig 3A ) . We next constructed an adhE-null Streptococcus pneumoniae R6 mutant ( ΔadhE ) and examined its transformation efficiency for uptake of resistance-encoding DNA cassette under challenge with the corresponding antibiotic . While the ΔadhE mutant shows slightly decreased transformation efficiency ( ~ 2-fold ) , this change is negligible compared to typical results under comGC disruption ( ~ 10 000-fold ) and can be due to reduced metabolic fitness under the microaerobic conditions of the experiment ( Fig 3B ) . Our data are consistent with a previous genome-wide study aiming to identify genes essential for natural transformation in Streptococcus pneumoniae , which have failed to identify AdhE as a requirement for DNA uptake [27] . Finally , while no spirosome release was detected for the competence-induced ΔadhE pneumococci , typical T4P-like transformation pili were observed ( Fig 3C and 3D ) . Formation of spirosomes has been reported in a variety of Gram-positive and Gram-negative bacteria , with the first studies dating back several decades and refering to the building protein , AdhE , as spirosin [19–26] . AdhE conservation across representative species with confirmed spirosome formation shows significant sequence homology even among relatively distant taxa ( Table 1 ) . Nevertheless , sequence similarity mapping along the AdhEG . thermoglucosidasius structural model reveals that highly conserved residues cluster in only few surface-exposed patches [19 , 28] . These correspond to the deep active site clefts of the two dehydrogenase domains , as well as sites at or near the interdomain linker . The latter would likely remain buried in the context of mature spirosomes , as they stabilize embrace-like interactions between AdhE monomers in the high-resolution structural model of G . thermoglucosidasius spirosomes [19] ( S2 Fig ) . Thus the exposed spirosome surface would retain significant variability , which in turn could translate into differences in spirosome morphology and stability across species . Moreover , earlier reports have demonstrated that spirosome helix parameters can vary significantly depending on the presence and type of small molecule and metal ion cofactors [20 , 21] . In addition to S . pneumoniae , we observed spirosome release in cultures of Clostridium difficile , Streptococcus sanguinis , and E . coli ( Fig 4A–4C and Table 1 ) [29 , 30] . An adhE null strain of S . sanguinis [30] showed no release of morphologically consistent filaments , serving as an additional control for correct target identification . For the two Gram-positive species , C . difficile and S . sanguinis , spirosome morphology was practically indistinguishable from that of S . pneumoniae . The helical filaments we observed in E . coli cultures , on the other hand , were visibly more tightly coiled ( Fig 4D ) To verify that those correspond to AdhE macromolecular complexes we purified an enriched spirosome fraction and validated its major component as the bifunctional dehydrogenase using proteomic and biochemical methods ( Fig 4D and S3 Table ) . Thus , although we expect morphological variations to be commonplace across species and even sample handling protocols , we are confident that spirosome assembly and extracellular release can be detected in many more environmental , clinically isolated , or genetically engineered bacterial strains .
The major horizontal gene transfer mechanism in S . pneumoniae—natural transformation—requires regulated expression of the comG pilus biogenesis operon , homologous to operons encoding T4P and T2SS pseudopili in Gram-negative bacteria [5 , 7 , 8 , 13] . Recent studies have reported conflicting results regarding the morphology and function of pneumococcal transformation pili . One proposed mechanism is that S . pneumoniae expresses a long , DNA-binding , T4P-like cell surface appendage to ‘fish’ extracellular transforming DNA [10] , while an alternative hypothesis argues that competent pneumococci express short , self-secreting T2SS plaited pili that perforate the cell wall peptidoglycan to allow for DNA entry [8] . Here we show that the ‘plaited’ filamentous polymers are not related to natural transformation or pilus biogenesis but are instead widely conserved and well documented macromolecular complexes of the fermentative enzyme bifunctional acetaldehyde-alcohol dehydrogenase AdhE . Its tandem domain architecture secures the two-step NADH-dependent reduction of acetyl-CoA to ethanol via an aldehyde intermediate [19–25 , 31] . Although the biological significance of AdhE polymerization in such massive structures remains enigmatic , it is plausible that spirosome assembly delivers spatially localized metabolic flux to limit diffusion of the highly reactive aldehyde species and secure optimized conversion kinetics [32] . In addition , the high resolution structural model of G . thermoglucosidasius spirosomes shows that polymer assembly buries ~ 6 500 Å2 of surface area per monomer , which could have dramatic effects on protein stability and function [19 , 31] . Extracellular spirosome release by cultured bacteria appears to be the result of random cell lysis as no biological function or secretion mechanism can be assigned to the phenomenon . As expected for a fermentative enzyme and consistent with reports in the literature , AdhE expression and spirosome assembly is expected to increase under microaerobic and anaerobic conditions as opposed to aerobic cultures [23 , 33] . Anaerobic growth and increased cell lysis are both common in cultures of competence-induced pneumococci , where the signaling process of fratricide kills non-competent cells to release extracellular DNA available for uptake [17 , 34] . This can explain why the spirosomes were initially associated to natural transformation in S . pneumoniae and reported to represent ‘plaited’ transformation pili [8] . Conversely , in their study Balaban and colleagues attempted to reconstitute expression of pneumococcal transformation pili in E . coli by heterologous expression of the entire comG operon [8] . As a result , extracellular release of spirosomes was readily detected and the AdhE polymers were again labeled erroneously . It remains unclear why the authors failed to detect spirosomes in their negative control culture . One possibility is that the structures were omitted in the limited observation field that high-magnification electron microscopy experiments provide . Conversely , it is possible that overexpression of several non-native proteins—among which a macromolecular complex targeted to the inner membrane—could have had destabilizing effects on the expression strain , leading to increased cell lysis and spirosome release [35 , 36] . In our quest to identify the structures observed by Balaban and colleagues [8] , we initially hypothesized that they were randomly released RecA nucleofilaments due to their striking similarity to polymerized RecA homologs from other bacterial and eukaryotic species . Such structures have been extensively documented in the literature: forming characteristic helical coils , RecA filaments can be more or less extended depending on the presence and type of DNA and small-molecule ligands [37–39] . Essential but not exclusive to natural transformation , cytosolic RecA is massively expressed during competence and its polymerization on the incoming single-stranded DNA is key to DNA protection and subsequent integration in the genome ( Fig 5 ) [40] . Nevertheless , while ΔrecA cells display normal DNA uptake during competence , RecA-based recombination plays pivotal role in DNA repair throughout the bacterial life cycle [40 , 41] . This indicates that pilus-dependent DNA uptake and RecA polymerization are intrinsically uncoupled and could have explained the continuous release of ‘plaited’ filaments in the pilus-defficient strains . We were indeed able to detect RecA release in the medium of competence-induced cultures of both wild-type and ΔcomGB cells ( S3 Fig panel A ) . Also , although with slightly different parameters in terms of helical width and pitch , the ‘plaited’ filaments were structurally similar to both the coiled structure of a eukaryotic RecA homolog ( S3 Fig panel B ) [37] , as well as to in vitro reconstituted RecAS . pneumoniae nucleofilaments ( S3 Fig panel C ) . Nevertheless , release of the characteristic polymers persisted in a ΔrecA strain ( S3 Fig panel D ) and we were unable to detect the protein in the filament-enriched fractions following purification ( S1 Table ) . It is therefore important to note that macromolecular organization in helical filaments is not uncommon among proteins from both the bacterial and other taxa . These include but are not limited to nucleic acid-binding proteins , cytoskeletal elements , building blocks of cell surface appendages and phage capsid subunits [39 , 42–44] . This , together with the markedly different helical parameters of the highly conserved E . coli spirosomes shown here underscores the fact that limited-view , low-resolution morphology imaging and bulk biochemical experiments alone are often insufficient to deduce the nature of macromolecular assemblies . Rather , a combination of orthogonal approaches that spans the different resolution levels and integrates genetic , biochemical and structural data in a meaningful way is generally warranted to avoid false-positive or otherwise erroneous results . Taken together , our data rule out the existence of short ‘plaited’ transformation pili in competent pneumococci and reassert the expression of a long , 5–6 nanometer wide appendage , structurally and compositionally similar to T4P in Gram-negative bacteria [10] . This finding bridges Gram-negative and Gram-positives DNA uptake systems and provides a comprehensive picture of this major lateral gene transfer event . Indeed , a recent study showed the existence of a T4-pilus on competent V . cholerae , which shares many features with the pneumococcal transformation pilus: competence-induced expression , prerequisite for DNA uptake , and roughly a single copy per cell [45] . Apart from morphology alone , however , it is interesting to discuss the probable mechanism through which the transformation pili secure DNA entry into competent pneumococci . Although expression of any type of pilus would require overcoming the physical barriers of cell-wall peptidoglycan and overlaying capsule—and thus possibly facilitate DNA entry—the similarities among transformation pili of Gram-positive and Gram-negative bacteria suggest that naturally transformable species might have evolved a conserved and more sophisticated mechanism of pilus function than simple cell-wall destabilization . In agreement with a long-standing ‘pseudo-pilus’ hypothesis , Balaban and colleagues proposed a model in which the transformation pili self-secrete in the medium of competent S . pneumoniae , thus opening gateways in the cell wall peptidoglycan for passive exogenous DNA entry [8 , 9] . Their hypothesis was supported by the observation that ComGC found in the supernatant of different S . pneumoniae strains after centrifugation correlates with the peak of transformation efficiency [8] . Since we previously showed that transformation pilus expression is absolutely required for DNA uptake , it is not surprising to observe correlation between extracellular ComGC and transformation efficiency [10] . However , ComGC release in culture supernatants can be a result from both cell lysis and/or compromised pilus integrity . As we showed previously , pneumococcal transformation pili are fairly sensitive to mechanical stress and short vortexing and centrifugation are routinely used for their shearing and isolation [10 , 12] . Such mechanical forces , however , are unlikely to be exerted in nature , where competent pneumococci are typically cushioned in protective biofilm matrix [46] . As we have conducted only single time point visualization experiments , it is theoretically possible that the expresses transformation pili eventually detach from the cell to open entry pores for transforming DNA ( Fig 5 ) . However , the sheer size and ATP-dependent assembly of the transformation pilus makes such self-secretion hypothesis unlikely: the observed long native pili would be energetically taxing on the cells if their sole function were to be ejected prior to DNA uptake . Finally , it has been previously reported that native transformation pili bind and co-purify with DNA already present in the cell culture and that DNA binding at the surface of competent pneumococci is abolished in a pilus-deficient strain [10 , 47] . DNA-binding is also conserved in the homologous T4P of Gram-negative bacteria [14 , 48 , 49] . In such a DNA-binding context , pilus release would actually inhibit transformation by titrating out DNA available for uptake ( Fig 5 ) . This once again argues against a self-secreting mechanism of function and reinforces a cell-surface attached role for the pilus in transformation . While no mechanistic or quantitative data on DNA binding by the pilus are available , electron microscopy showed extensive contact interfaces between the long transformation pili and DNA chains [10] . It is therefore plausible that multiple weak interactions along the helical pilus lattice stabilize this interaction and allow its reversal upon DNA uptake . Such a scenario would also explain why no DNA binding to a non-polymerizing ComGC truncation has ever been detected [8 , 50] . Even more interesting , however , is the question of how pilus-bound DNA gets brought to the DNA uptake machinery in the cell membrane . In Gram-negative bacteria , T4P-bound DNA is proposed to be actively hauled to the cell by rapid bottom-up pilus depolymerization powered by a dedicated retraction ATPase [14] . Although a similar mechanism has been proposed for S . pneumoniae and other transformable Gram-positive bacteria , pneumococci lack homologous retraction ATPase and are likely to utilize a distinct mechanism for DNA entry . In addition , transforming DNA uptake occurs at much lower speeds in Gram-positive bacteria than Gram-negative T4P retraction [51 , 52] . Many sequence-specific DNA binding proteins can scan DNA for their target sites at speeds several orders of magnitude higher than the upper limit for a three-dimensional diffusion-controlled process [53] . This can generally be achieved by at least two passive mechanisms , which involve sequence non-specific DNA binding and subsequent translocation of the protein along the DNA: 1 ) charge-based protein sliding , where the protein engages in a one-dimensional random walk along the DNA in search of its target , and 2 ) direct intersegment transfer , where the protein can bind and hop between two remote regions on the DNA without losing the non-specifically bound state [53] . Although we can not exclude the involvement of an unidentified retraction ATPase or additional receptor proteins in exogenous DNA uptake , we favor a model where the pneumococcal transformation pilus provides a similar facilitated diffusion framework ( Fig 5 ) . By preserving multiple dynamic non-specific interactions with the pilus , transforming DNA would overcome the thermodynamic limitations of a three-dimensional diffusion process until it passively finds the membrane associated uptake machinery and becomes actively pumped in the cell ( Fig 5 ) .
Streptococcus pneumoniae spirosomes were observed in both competent and non-competent cells . For competence induction cells were grown in microaerobic conditions , without agitation , at 37°C in Casamino Acid-Tryptone ( CAT ) medium supplemented with 0 . 2% glucose , 15mM dipotassium phosphate , 3mM sodium hydroxide and 1mM calcium chloride and adjusted to pH 7 . 8 . Competence was triggered by the addition of Competence Stimulating Peptide ( CSP ) at OD600 = 0 . 15 for 10–30 min . Non-competent pneumococci and Escherichia coli cells were grown similarly in LB to OD600 = 0 . 3 and OD600 = 0 . 6 , respectively . Clostridium difficile cells were grown at 37°C under strict anaerobic conditions on Tryptone-Yeast extract-Glucose ( TYG ) plates supplemented with 0 . 1% thioglycolate . Streptococcus sanguinis cells were grown anaerobically , without agitation , at 37°C in CAT medium to OD600 = 0 . 3 . For spirosome visualization cells were scraped off the plates or pelleted by centrifugation and resuspended in TBS ( 50 mM Tris-HCl pH 7 . 6 , 150 mM NaCl ) at ~ 5 μl TBS per milliliter of culture at OD600 = 0 . 3 . 5 μl drops of each suspension were then placed directly on glow discharged carbon coated grids ( EMS , USA ) for 1 minute . The grids were then blot-dried on filter paper , washed on a drop of ultrapure water , and negatively stained with 2% uranyl acetate in water . Specimens were examined on an FEI Tecnai T12 BioTWIN LaB6 electron microscope operating at 120 kV at nominal magnifications of 18500–68000 and 1–3 μm defocus . Images were recorded on a Gatan Ultrascan 4000 CCD camera . An adhE deletion ( strain AD001 ) was introduced in the R1501 genetic background by transformation with a DNA cassette carrying a kanamycin resistance gene inserted between two ~1000 base pair fragments corresponding to the S . pneumoniae genomic regions flanking adhE . Briefly , the genomic region upstream from the AdhE open reading frame was amplified using forward and reverse primers 5’-ACA TGG CAA TCC GAT TCA TAA GGG G-3’ and 5’-GCC ATC TAT GTG TCG GAA CGA TAT CCT TTG TTA ATT TTT TCA CAA GTT TAT TAT AAC G-3’ , respectively , while the genomic region downstream of the adhE gene was amplified the following primer pair 5’-AAA ATG TGT TTT TCT TTG TTT TGT TTA TCA GTC TAG AAG CAA GAC AAA AAC TCA A-3’ and 5’-TTG CTA TTT ATG CAT GCA GAA GAC CAA ATG-3’ . A third pcr reaction was used to amplify a kanamycin-resistance gene using the pR411 plasmid as template DNA [54] and forward and reverse primers 5’-AGG ATA TCG TTC CGA CAC ATA GAT GGC GTC GCT AGT-3’ and 5’-GCT TCT AGA CTG ATA AAC AAA ACA AAG AAA AAC ACA TTT TTT TGT CAA AAT TCG TTT-3’ , carrying complementarity to the 3’-end of the adhE-upstream and 5’-end of the adhE-downstream fragments , respectively . The three pcr products were then assembled using overlap extension PCR and the purified DNA cassette was used for transformation of competence-induced S . pneumoniae R1501 cells . adhE-null mutants ( strain AD001 ) were positively selected by growth in the presence of kanamycin ( 60 μg/ml ) and adhE deletion was confirmed independently by DNA sequencing and western blot detection using an anti-AdhE antibody . For all transformation experiments , competence was triggered as above at OD600 = 0 . 15 for 10 minutes , followed by DNA addition and 20 minute incubation at 30°C . Transformants were selected on Columbia Agar supplemented with 5% horse blood and appropriate antibiotics . For the transformation efficiency assays , cells were transformed with 100 ng of a DNA cassette , amplified from S . pneumoniae R304 genomic DNA and containing the streptomycin resistance gene str41 . Bacteria were plated in the presence and absence of streptomycin ( 100 μg/ml ) and incubated at 37°C overnight before colony counting . All steps of the purification protocol were performed at 4°C . 8L of S . pneumoniae culture grown in LB to OD600 = 0 . 3 or 4L of E . coli culture grown to OD600 = 0 . 6 were pelleted by centrifugation ( 20 min at 5000 g ) and resuspended in 6 ml of cold TBS , vortexed briefly and centrifuged to remove the bulk of intact cells and debris ( 10 min at 12000 g followed by 15 min at 50000 g ) . Triton x-100 was added to the supernatant at final concentration of 0 . 25% . Following 30 minute agitation for solubilization of remaining membrane fragments , the samples were filtered through a 0 . 45 μm cellulose acetate filter ( Corning ) and centrifuged for 1h at 125000 g for spirosome pelleting . After careful removal of the supernatant , the pellet was resuspended in 50 μl TBS , re-filtered and loaded on a Superose 6 3 . 2/300 size exclusion column ( GE Healthcare ) . Spirosome enriched fractions were found to elute with the void volume . Sample preparation for electron microscopy was performed as above . Trypsin digestion was performed as described previously [55] and the digests were analyzed under standard conditions on an LTQ-Orbitrap Velos ( Thermo Fisher , Bremen ) equipped with Ultimate 3000 nano-HPLC ( Dionex ) . Briefly , tryptic peptides were desalted and separated on a C-18 nano-HPLC column under a gradient of acetonitrile . Minimum signal threshold for triggering an MS/MS event was set to 5000 counts . After a survey scan , the 10 most intense precursor ions were selected for CID fragmentation ( top10 ) . Raw files were processed with MaxQuant 1 . 4 . 1 . 2 [56] . Protein identification was done using Andromeda against a Streptococcus pneumoniae ( strain ATCC BAA-255 / R6 ) ( Taxonomy 171101–1947 proteins ) or Escherichia coli ( strain K12 / MC4100 / BW2952 ) ( Taxonomy 595496–4043 proteins ) database . A false-discovery rate of 1% was used for both peptide and protein identification . Reverse and contaminant proteins were excluded and only proteins identified with a minimum of 2 peptides were considered . Spirosomes and transformation pili were visualized by EM as above at nominal magnifications of 49000 and 68000 , respectively . The contrast transfer function parameters were assessed using CTFFIND3 [57] , and the phase flipping was done in SPIDER [58] . Linear filament segments were boxed with e2helixboxer and single particle stacks were generated for each dataset ( EMAN2 [59] ) : 4309 particles for the transformation pilus ( 134x134 pixel box , 1 . 5 Å/pixel ) , 728 particles for the S . pneumoniae spirosomes ( 180x180 pixel box , 2 . 2 Å/pixel ) and 555 particles for the E . coli spirosomes ( 180x180 pixel box , 2 . 2 Å/pixel ) . Normalization , centering , multi-reference alignment , multi-statistical analysis , and classification ( 15–40 particles per class ) were done in IMAGIC-4D ( Image Science Software , GmbH ) . IMAGIC-4D was also used for generation of two-dimensional reprojections of the T2SS pilus and the G . thermoglucosidasius spirosome . The coding sequence for AdhES . pneumoniae was cloned in-frame in a pET21a vector for heterologous expression of C-terminally hexahistidine-tagged protein in E . coli . Briefly , the AdhES . pneumoniae open reading frame was PCR-amplified from S . pneumoniae R1501 genomic DNA using forward and reverse primers 5’-CAT ATG AAA GCT ATG GAG GAA AAT ATG GCT G-3’ and 5’-GCG GCC GCT TTA CGG CGT CCT GGT CTT TCT TTG-3’ , respectively . The pET21a vector was pcr-amplified using forward and reverse primers 5’-GGA CGC CGT AAA GCG GCC GCA CTC GAG CAC CAC CAC-3’ and 5’-CAT ATT TTC CTC CAT AGC TTT CAT ATG TAT ATC TCC TTC TTA-3’ , respectively . 90 ng of linearized vector DNA were incubated in 1:1 molar ratio with the AdhE pcr product in an In-Fusion cloning reaction ( Clontech ) and transformed into Top10 cells ( Invitrogen ) . Plasmid DNA was purified from individual clones , verified for AdhE coding region insertion and used for transformation in BL21 ( DE3 ) cells ( Invitrogen ) . For expression , transformed BL21 ( DE3 ) cells were grown under agitation at 37°C in LB to OD600 = 0 . 6 and expression was induced with 0 . 7 mM IPTG for 2h . Cells were pelleted by centrifugation ( 4500 g for 20 min ) , resuspended in TBS supplemented with cOmplete Protease Inhibitor Cocktail ( Roche ) and disrupted by sonication . Cellular debris were removed by centrifugation ( 20 000 g for 30 min ) and the lysates were incubated with batch Talon metal affinity resin ( Clontech ) for 30 min at room temperature . The resin was extensively washed ( TBS , 15 mM imidazole ) and bound protein was eluted with TBS supplemented with 140 mM Imidazole . For EM observation eluted protein was immediately applied on glow-discharged continuous carbon grids , stained , and imaged as above . For AdhE spirosome pull-down , a strain carrying an additional competence-inducible FLAG-tagged ectopic copy of the adhE gene was constructed . Briefly , the adhE gene was PCR-amplified using S . pneumoniae R1501 genomic DNA as template and primer pair 5’-GAG GAA GAA ACC ATG TTG AAA GCT ATG GAG GAA AAT ATG GCT GAT AAA AAA AC-3’ and 5’-AAA ATC AAA CGG ATC TTA CTT GTC ATC GTC ATC CTT GTA ATC TTT ACG GCG TCC TGG TCT TTC TTT G-3’ , the latter designed to add a C-terminal FLAG tag to the encoded protein . In parallel , pCEPx vector DNA [60] was digested with NcoI and BamHI restriction enzymes . 90ng of the linearized vector were incubated in 1:1 molar ratio with the adhE-FLAG pcr product in an In-Fusion cloning reaction ( Clontech ) and transformed into Top10 E . coli cells ( Invitrogen ) . Plasmid DNA was purified from individual clones , verified for AdhE-FLAG coding region insertion , and transformed into competence-induced R1501 cells , followed by selection with kanamycin ( Kan ) . The resulting SO007 strain was sequence-verified for the pCEPx-derived adhE-FLAG–KanR cassette recombination [60] and cultured in CAT medium to OD600 = 0 . 15 . CSP-induced and non-induced cells were pelleted by centrifugation and resuspended in TBS by brief vortexing in the presence of millimeter-sized glass beads for increased cell lysis . Cells were pelleted again , and the supernatants were incubated with anti-FLAG M2 affinity resin ( Sigma-Aldrich A2220 ) for 1h at RT and under agitation . After washing with TBS , the resin-bound fraction was eluted by the addition of 100 μg/mL 3X FLAG peptide ( Sigma Aldrich F4799 ) and mixing for additional 15 min at 4°C . The samples were then subjected to SDS-PAGE and EM analyses . 2 . 5 μM purified RecAS . pneumoniae was incubated with 50 mM KCl , 0 . 5 mM DTT , 10 mM Tris-HCl pH 7 . 5 , 2 mM magnesium acetate , and 2 mM ATP-γ-S for 15 minutes at 37°C . RecA nucleofilament formation was induced by the addition of a 54-nucleotide-long single-stranded DNA fragment or single-stranded M13mp18 DNA ( New England Biolabs ) at nucleotide:RecA monomer ratio of 3:1 . After additional 15 minutes at 37°C , the samples were prepared for EM observation as above .
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Streptococcus pneumoniae often escapes prevention and treatment through rapid horizontal gene transfer via natural transformation . Uptake of exogenous DNA requires expression of a transformation pilus but two markedly different models for pilus assembly and function have been proposed . We previously reported a long , Type 4 pilus-like appendage on the surface of competent pneumococci that binds extracellular DNA as initial receptor , while a separate study proposed that secreted short , ‘plaited’ transformation pili act simply as peptidoglycan drills to open DNA gateways . Here we show that the ‘plaited’ structures are not competence-specific or related to transformation . We further demonstrate that these are macromolecular assemblies of the metabolic enzyme acetaldehyde-alcohol dehydrogenase—or spirosomes—broadly conserved across the bacterial kingdom .
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[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[] |
2015
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Conserved Streptococcus pneumoniae Spirosomes Suggest a Single Type of Transformation Pilus in Competence
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Gene expression is intrinsically a stochastic ( noisy ) process with important implications for cellular functions . Deciphering the underlying mechanisms of gene expression noise remains one of the key challenges of regulatory biology . Theoretical models of transcription often incorporate the kinetics of how transcription factors ( TFs ) interact with a single promoter to impact gene expression noise . However , inside single cells multiple identical gene copies as well as additional binding sites can compete for a limiting pool of TFs . Here we develop a simple kinetic model of transcription , which explicitly incorporates this interplay between TF copy number and its binding sites . We show that TF sharing enhances noise in mRNA distribution across an isogenic population of cells . Moreover , when a single gene copy shares it’s TFs with multiple competitor sites , the mRNA variance as a function of the mean remains unaltered by their presence . Hence , all the data for variance as a function of mean expression collapse onto a single master curve independent of the strength and number of competitor sites . However , this result does not hold true when the competition stems from multiple copies of the same gene . Therefore , although previous studies showed that the mean expression follows a universal master curve , our findings suggest that different scenarios of competition bear distinct signatures at the level of variance . Intriguingly , the introduction of competitor sites can transform a unimodal mRNA distribution into a multimodal distribution . These results demonstrate the impact of limited availability of TF resource on the regulation of noise in gene expression .
Every living organism regulates gene expression through the action of transcription factors ( TFs ) , enabling the cell to respond to intra-cellular and environmental cues [1] . The binding and unbinding of both RNAP molecules and the TFs ( DNA binding proteins that abet or hinder RNAP binding ) to the promoter [2–4] , are inherently stochastic processes and this stochasticity is manifested in the output of gene expression [5–11] . Consequently , at the single cell level , the numbers of mRNA and protein molecules fluctuate in time and across populations . Such fluctuations in expression can be detrimental to cell fitness [12–14] and the development of multicellular organisms [15] . On the contrary , noisy expression can benefit a population of genetically identical cells by creating phenotypic heterogeneity [16–21 , 21–30] . This raises the question of how noise in gene expression is regulated [31 , 32] . Over the past decade or so , theorists have sought to unravel how gene expression noise is regulated [33–40] . Meanwhile , experimentalists have measured noise at both the mRNA and protein level in prokaryotes [41–45] and eukaryotes [46–48] , in order to systematically test the predictions of these models , and refine our understanding . Models of transcription quintessentially hinge on the details of the promoter architecture such as the number and affinity of TF binding sites and relative binding positions on the gene [39 , 49–54] . Most of these theoretical models implicitly assume that the number of TFs is in excess with respect to the number of its binding sites in the cell . However , inside the cell this assumption often breaks down . For example , TFs get shared by multiple gene copies , in highly replicated viral DNA genes [55] , genes expressed on plasmids [56] , and in multiple identical copies on the chromosome [57–61] . Furthermore , the majority of TFs are entrusted with the regulation of multiple genes; for instance , cAMP receptor protein ( CRP ) is reported to have nearly 400 binding sites per E . coli genome copy [62 , 63] . It is therefore crucial to predict gene expression noise due to limited availability of TF resource , in order to dissect how the sharing of TFs among multiple genes contributes to noise . Some studies have explored the interplay of TF sharing between genes and other competing binding sites in different scenarios [44 , 64–72] . For instance , in a recent study , Rydenfelt et al . [73] have theoretically explored the effect of TF sharing on the mean level of gene expression , which has since been verified experimentally [65 , 67] . However , few studies have systematically explored how competition , for TF binding influences gene expression noise [68–71] . In one such study , it was found that in the context of a single auto-regulated gene copy , the addition of decoy binding sites can lead to bimodal protein distributions in an isogenic population . Although these studies provide useful insights , nevertheless a general theoretical framework of understanding how TF resource sharing affects noise in gene expression remains in its infancy . The goal of this study is to develop such a framework . Here we examine a simple model of transcription , where a number of TFs are shared between a comparable number of gene copies and other competitor sites . We explicitly envisage two different scenarios of competition , demonstrated schematically in Fig 1: ( i ) multiple identical promoters sharing their TFs ( Fig 1B ) , and ( ii ) promoters sharing their TFs with other competitor sites ( Fig 1C ) . These competitor sites can represent ‘decoy sites’ or promoters driving expression of other gene species . We find that competition enhances noise across an isogenic population , i . e . the Fano factor ( defined as the variance divided by the mean ) of the mRNA distribution shows a peak when the TF number becomes comparable to the promoter number . Interestingly when a single promoter copy shares TFs with multiple competitor sites in a cell , we find that there exists a master curve for the mRNA variance as a function of its mean that is independent of the binding , unbinding rates and the number of competitor sites . However , this result does not hold when a number of promoter copies compete for a pool of TFs . In other words , these different scenarios of TF competition bear distinct signatures at the variance level . This finding stands in sharp contrast to the behavior at the mean level [67] , which follows a universal master curve irrespective of the nature of competition . We further find that a unimodal mRNA distribution without any competitor sites can be transformed into a multimodal distribution when competitor sites are introduced . For such a multimodal distribution , different modes arise and diminish as the number of competitor sites is systematically tuned . While our model predictions are consistent with recent experimental [67] and theoretical [73] studies at the mean level of expression , we also find that TF competition can have a complex impact on the noise in expression which results in multimodality and a scaling with mean expression level that depends on the source of the competition .
In order to investigate how TF sharing affects cell-to-cell variability at the mRNA level across a population of genetically identical cells , we examine a simple model of transcription , where a number of TFs are shared between a comparable number of identical promoter copies and competitor sites ( see Fig 1B and 1C ) . Moreover , as case studies , we consider two regulatory motifs of transcription in E . coli [74]: 1 ) a promoter containing a single binding site where a repressor molecule can bind and hinder transcription , and 2 ) a promoter consisting of a single binding site where an activator molecule can bind and increase the rate of transcription . These regulatory architectures have been extensively explored in different studies , using the implicit assumption that TFs are in abundance [38 , 64 , 75–79] . We construct a general model of transcription , that explicitly incorporates the interplay between TF copy number and its binding sites . To elucidate the model , we first consider a number of identical promoters sharing a pool of TFs , as shown in Fig 2A in the absence of any competitor sites . We can easily incorporate the presence of competitor sites in our model , as shown in the later sections . For the sake of generality we discuss the process of TF binding and unbinding generically without regard to their regulatory functions; later we will outline the influence of activators and repressors separately . Let us consider NTF number of TFs being shared by NP number of promoters , where each promoter contains a single TF binding site . A TF binds to a promoter at a rate kon , and it unbinds from it at a rate koff ( see Fig 2A ) . For mathematical convenience we view the process of TF binding to a promoter as the formation of a ‘TF-promoter’ complex , and the unbinding of the TF as dissociation of the complex [80] . Consequently , complex formation rate per TF per promoter is kon , while dissociation rate per complex is koff ( see Fig 2B ) . The number of TF-promoter complexes determines the transcriptional output . In the case of activators , mRNA production takes place when the activator is bound to a promoter ( see Fig 2C ) . Each of the activator-promoter complexes produces mRNA molecules at a rate r , which then subsequently degrades at a rate γ . Here we have assumed for simplicity that the basal transcription rate , when the promoter is not bound to an activator , is zero , as it is negligible for many activator regulated genes [62] . However , all our results still qualitatively hold even when we incorporate a non-zero basal rate of transcription ( see Fig D in S1 Text ) . On the other hand , since repressor binding to a promoter hinders the attachment of RNA polymerases to the promoter , each promoter produces mRNA molecules at a rate r , only when it is not bound to a repressor , as shown in Fig 2E . In the limit of one promoter copy , our model reduces to the well known ON-OFF model [75 , 81–84] , where the promoter switches between an active and an inactive state , and transcription can ensue only in the active state . The above processes can be depicted as trajectories in the space of TF-promoter complex number and mRNA copy number , as shown in Fig 2B , 2D and 2F . By employing a stochastic framework , we monitor the time evolution of two random variables: the instantaneous number of TF-promoter complexes , n ( t ) and the instantaneous number of mRNA molecules , m ( t ) . Evidently for activators , the instantaneous mRNA production rate is proportional to the number of complexes ( n ) ; while for repressors , the mRNA production rate is proportional to the number of unbound promoters ( NP − n ) ( compare Fig 2D and 2F ) . Using the master equation approach , we write down the time-evolution equation for the joint probability distribution P ( n , m , t ) of having n complexes and m mRNA molecules at a time t . For instance , the master equation for activators is given by d P ( n , m , t ) d t = k on ( N TF − n + 1 ) ( N P − n + 1 ) P ( n − 1 , m , t ) + k off ( n + 1 ) P ( n + 1 , m , t ) + r n P ( n , m − 1 , t ) + γ ( m + 1 ) P ( n , m + 1 , t ) − [ k on ( N TF − n ) ( N P − n ) + k off n + r n + γ m ] P ( n , m , t ) . ( 1 ) The above equation is built by counting all possible steps that lead to either a change in complex number ( n ) or in mRNA copy number ( m ) by one ( see trajectories in Fig 2B and 2D ) . Similarly , we could also write the master equation for repressors by combining the trajectories depicted in Fig 2B and 2F ( see S1 Text for details ) . In principle , we can obtain the relevant moments of the mRNA distribution from these master equations . However , exact expressions of mean ( 〈m〉 ) and variance ( var ( m ) ) of the mRNA distribution can only be obtained for the simplest case of one promoter . For the general case of multiple promoters , deriving exact closed-from expressions for the moments is challenging , because the system of equations for the moments do not close . Nonetheless , we can obtain approximate analytical solutions ( see S1 Text for details ) . Since we do not have exact analytical solutions for the moments of the mRNA distribution , we simulate the kinetic processes defined above using the Gillespie algorithm [85] . This allows us to numerically generate multiple time-traces of the random numbers n and m , using realistic values of the kinetic rates suitable for E . coli promoters ( see Table 1 ) . From these different time traces , we calculate the values of the mean and variance of the steady state mRNA distribution . The approximate analytical solutions match reasonably well with our simulation data ( see Fig A in S1 Text ) . While there is a systematic deviation which results from ignoring higher order terms ( beyond second order ) , these closed form relations can be useful in understanding the qualitative behaviors of these curves , which the analytical solutions do capture ( see S1 Text for details ) . Below we summarize our main results , obtained from the Gillespie simulations . Armed with the framework established above , we first investigate the scenario when multiple identical promoter copies compete for a pool of TFs ( as shown in Fig 1B ) . Our model predicts the effect of TF sharing on the mean ( 〈m〉 ) and variance ( var ( m ) ) of the steady-state mRNA distribution . We shall first discuss the case when the TFs act as activators , and then shift our focus to the case of repressors . We explore the effect of activator sharing in the fold-change of mean expression , a quantity often measured in bulk assays ( see Fig 3A ) [67 , 73] . Here we define the fold-change as the ratio of the mean expression 〈m〉 to its maximum value NP ( r/γ ) . The mean of the mRNA distribution , increases steadily with activator number , and asymptotically goes towards the value of NP ( r/γ ) ( see Fig F in S1 Text ) . In the limit of activator copy number being much greater than the promoter copy number , all the promoters essentially remain bound to activators . Accordingly each of these activator-promoter complexes contributes , on average , r/γ mRNA molecules , resulting in the production of NP ( r/γ ) mRNA molecules on average , in the steady state . The qualitative behavior of fold-change , which first monotonically increases with activator number and asymptotically approaches one , is in agreement with previous studies [73] . In contrast to the fold-change , variance is a non-monotonic function of the number of activator molecules , which peaks when the number of activators equals the promoter copy-number ( see Fig 3B and also see Fig F in S1 Text ) . The origin of the peak in variance lies in the activator-promoter complex number variability . In fact the variance in complex number also peaks when the promoter copy number equals activator copy number ( see Fig B in S1 Text ) . In other words , when activator number is comparable to promoter copy-number , there is enhanced variability in complex number stemming from the stochastic complex formation and dissociation processes , which subsequently gets reflected at the level of mRNA distribution . On the contrary , if the numbe of activators is either much greater or much less than the promoter number ( in the limits of NTF ≫ NP and NTF ⪡ NP ) , the effect of competition disappears , as all the promoters remain either bound or unbound to activators . If we consider the example of activator number being much higher than promoter number , all the identical gene copies driven by the promoters will be expressed all the time . This will lead to each gene copy producing mRNA molecules which is Poisson distributed across an isogenic population [54] . Hence the distribution of all the mRNAs produced from all the identical gene copies will be given by the sum of the numbers of mRNA produced from every gene , leading to a reduction in mRNA variability and a sharply peaked distribution . We further show in Fig 3C the effect of activator sharing on the Fano factor ( var ( m ) /〈m〉 ) . Just like the mRNA variance , the Fano factor also exhibits non-monotonicity as a function of activator number , and peaks when the activator and promoter numbers become equal . Turning our attention to repressors , we find an analogous result where instead of gene expression being proportional to the number of activator-promoter complexes; it is now proportional to the number of promoters not bound to repressors . As such , we find that the fold-change , defined by 〈m〉/ ( NPr/γ ) , monotonically decreases with increasing repressor number , and asymptotically approaches zero ( see Fig 3D ) . Moreover , the variance is a non-monotonic function of repressor number , and exhibits a sharp peak when the number of repressors equal promoter copy number , as was the case for activators ( see Fig 3E ) . As before the appearance of these peaks can be understood from a corresponding enhancement in complex number variability ( see Fig B in S1 Text ) . Finally , the non-monotonic behavior of Fano factor , found in the case of activators , also persists for repressors , when the Fano factor is plotted as a function of the repressor number ( see Fig 3D ) . However , there is a distinction between the cases of activators and repressors at the level of Fano factor . Unlike the activators , the Fano factor for repressors do not peak exactly when the repressor number equals the promoter number; rather the peaks appear when the repressor number is slightly greater than ( although comparable to ) the promoter number ( see Fig 3D ) . These behaviors are very robust with respect to changes in the different parameter values associated with the model ( for details see the S1 Text , Figs G-I ) . In summary , a key prediction of our model is that TF sharing among identical promoters leads to a substantial increase in gene expression noise when TF and promoter copy number become comparable to each other . Sharp peaks arise in mRNA variance and Fano factor as a function of TF copy number , which bears the signature of pronounced competition . Inside single cells , TFs often promiscuously bind to different competitor sites [42 , 88 , 89] such as ‘decoy sites’ or promoters driving expression of other gene species , compelling a promoter of interest to compete with these sites for a limiting pool of TFs ( as shown in Fig 1C ) . Recent bulk studies have theoretically [68 , 73] and experimentally [67 , 90] studied this scenario inside bacterial cells , by synthetically integrating multiple competitor sites at several chromosomal locations or on plasmids . To explore how this interplay affects the cell-to-cell variability at the mRNA level , we incorporate TF binding to competitor sites , and extend our model as described before to consider NP number of promoters competing for NTF number of TFs in the presence of NC number of competitor sites ( shown in Fig 4A ) . Consequently , every TF can bind either to a promoter or to a competitor site . The rates at which a TF binds to a competitor site and unbinds from it are given by k on C and k off C respectively . We first discuss how the competition of a single promoter copy ( NP = 1 ) with multiple competitor sites affects the variability at the mRNA level . A key prediction of this model is that for both activators and repressors , the variance as a function of the mean remains unaltered , regardless of the number and the strength of the competitor sites , as shown in Fig 4B and 4C ( also see Fig E in S1 Text ) . In other words , when we tune the variance as a function of the mean by altering TF number NTF , all the data points for variance , generated from numerical simulations using different parameter values for the number of competitor sites collapse onto a single master curve . This result holds true even for different TF binding/unbinding rates to the competitor sites ( please see Fig E in S1 Text ) . In order to develop an intuition for this result , we employ already existing analytical results involving TF regulating a single promoter copy [37] . In fact , when the number of competitor sites is zero , it is easy to obtain exact analytical expressions for the variance and the mean from the master equation ( Eq 1 ) , which are given by , 〈 m 〉 = r γ k on N TF ( k on N TF + k off ) var ( m ) = 〈 m 〉 [ 1 + k off ( k on N TF + k off ) r ( γ + k on N TF + k off ) ] ( for activators ) , 〈 m 〉 = r γ k off ( k on N TF + k off ) var ( m ) = 〈 m 〉 [ 1 + k on N TF ( k on N TF + k off ) r ( γ + k on N TF + k off ) ] ( for repressors ) . ( 2 ) It is conceivable from the above analytical expressions , that both the variance and the mean can be expressed as simple functions of an ‘effective’ binding rate of the TFs to the promoter , k on eff = k on N TF ( also see Eq . 14-15 in S1 Text ) . The presence of the competitor sites essentially modifies the TF pool as seen by the promoter i . e . the effective binding rate of the TFs to the promoter without altering any of the other parameters such as , koff , r and γ . Hence we can express the variance as a function of the mean by eliminating the dependence of these functions on the effective binding rate , k on eff . For both the activators and repressors , we can thus express the variances as functions of the means given by , var ( m ) = 〈 m 〉 + 〈 m 〉 [ ( r / γ ) − 〈 m 〉 ] 2 γ γ [ ( r / γ ) − 〈 m 〉 ] + ( r / γ ) k off ( for activators ) , var ( m ) = 〈 m 〉 + 〈 m 〉 2 [ ( r / γ ) − 〈 m 〉 ] γ γ 〈 m 〉 + ( r / γ ) k off ( for repressors ) . ( 3 ) These are the functional forms of the master curves , which exactly match the collapsed data , as shown in Fig 4B and 4C . In other words , for a single promoter copy , noise at the mRNA level changes only as a function of the mean , irrespective of whether the promoter of interest is competing for a pool of TFs with competitor sites or not . Moreover , this result holds true even when there exists a basal rate of transcription for promoters not bound to activators ( see Fig E in S1 Text ) . This highlights an intriguing prediction for transcriptional noise in the face of competition; the noise depends only on the mean , and it is determined solely by an effective binding rate of the TFs to that promoter , irrespective of the interaction of the TFs with the competitor sites . In fact this result also implies that variance as a function of the mean cannot be used as a signature to distinguish scenarios where a single promoter copy is in competition for a pool of TF with other competitor sites . Next , we investigate the case of multiple promoter copies competing for a pool of TFs with a number of competitor sites . Our model predicts that the collapse , as observed in the variance as a function of the mean for a single promoter copy does not hold anymore . To explicate this further , we consider the hypothetical situation of two promoter copies , competing with other competitor sites . When we systematically tune the number of competitor sites and using gillespie simulations obtain the variance as a function of the mean , we find that the different curves , defining the variance per promoter as a function of the mean per promoter , no longer collapse onto a single master curve , as shown in Fig 4B and 4C ( open symbols ) . We note that the TF copy number variation , affects mRNA production from both the promoter copies . Hence the numbers of mRNAs produced from the two copies become correlated [73] . Owing to this correlation , the mean and variance cannot be simply expressed in terms of some effective variable , such as konNTF , as before ( see Eq . 17 in S1 Text , where nonlinear terms , like k on 2 N TF 2 , appear in the expressions ) . However , in the limit of the TF copy number or the number of competitor sites becoming much greater than one ( i . e . NTF ≫ 1 or NC ≫ 1 ) , the correlation between the number of mRNAs produced from different promoter copies become negligible . In both these limits the data for variance per promoter versus mean per promoter again fall on the master curve obtained for a single promoter copy , signifying that the promoters behave independently ( see Fig 4B and 4C ) . The observations in the last two sections suggest that the mRNA distribution passes through an interesting regime when the TF number is comparable to the number of binding sites ( promoter copies and competitor sites ) . In order to examine the features of mRNA distribution , we consider activator sharing between multiple promoter copies driving the expression of the same target gene . We find that multimodal mRNA distributions arise as activator number is tuned for a given number of promoter copies ( see Fig 5A ) , when the binding and unbinding rates of activators ( kon and koff respectively ) to the promoters are much slower compared to the mRNA production and degradation rates ( r and γ respectively ) ( see Table 1 ) . Multi-modal mRNA distribution implies that mRNA molecules are present in multiple distinct abundances across an isogenic cell population . The appearance of multimodality at the mRNA level can be intuited by examining the steady state activator-promoter complex number distribution , since mRNA production is directly proportional to the number of activator-promoter complexes . In order to elucidate this point further , we consider the scenario when there are three activator copies , shared by two promoters . As evident , we can have three possible values of the complex number: zero , one or two . Since the binding and unbinding of the activator molecule to the promoters are much slower than the mRNA production and degradation rates , the promoters remain in activator bound and unbound states for a long time , such that sampling of mRNA molecules across a population can capture the effect of distinct relative abundances . Consequently in a genetically identical cell population , we may find three sub-populations , with one population having one complex producing ∼r/γ amount of mRNA molecules on average , another population having two complexes producing ∼2r/γ amount of mRNA molecules on average; and the other population having zero mRNA molecules on average due to the absence of any activator-promoter complexes . However , for our particular choice of parameters , the relative probability of having zero complexes becomes much smaller than having one or two complexes . Consequently the peak at zero vanishes , and we obtain a bi-modal mRNA distribution with two peaks , approximately at 2r/γ and r/γ ( see the blue curve in Fig 5A ) . Nevertheless , with suitable choices of parameters one could recover all the three modes ( see Fig J in S1 Text ) . In the limit of activator copy number being much greater than the promoter copy number , all the promoters are essentially occupied and the mRNA distribution approaches a uni-modal distribution , sharply peaked around NPr/γ ( NP being the number of promoter copies ) . For identical promoter copies competing for repressor molecules , we again find bi-modal mRNA distribution in certain parameter regime , as shown in Fig 5B . The appearance of bimodal distribution is known theoretically for a single ‘two-state’ promoter switching between ‘on’ and ‘off’ states , when the state switching rates are slower than mRNA production and degradation rates [37 , 91] . The fact that we consider more than one competing identical promoters leads to the possibility of obtaining more than two modes as we tune the TF copy number , since it allows for the formation of more than one TF-promoter complex . However , it is to be noted that multimodality can be observed only for a certain parameter regime , namely when the binding and unbinding rates of the TFs are much slower than mRNA production and degradation rates ( {r , γ} > {kon , koff} ) . When this stringent condition is met , sharing of TFs among promoters alters the relative proportion of the different modes , making them either more or less prominent . On the other hand , if the condition is not met , the distribution becomes unimodal . For example , see the inset of Fig 5A and 5B , where we choose the TF binding rate kon to be higher than the mRNA degradation rate γ . Next , we investigate how the presence of competitor sites affects the distribution of mRNAs produced by multiple copies of a promoter of interest . In the case of activator sharing , one of the key findings is that the introduction of competitor sites can lead to multi-modality even when the binding rate of TFs to the promoter is faster than the degradation rate of the mRNA . In order to explain this further let us consider the example discussed above , where two competing promoters of interest produce a unimodal mRNA distribution in the absence of any competitor sites ( Fig 5A , inset ) . By systematically increasing the number of competitor sites , we find that the unimodal mRNA distribution transforms into a multimodal distribution ( see Fig 5C ) . This is because the activators can now also bind to the competitor sites , restricting the pool of freely available activators ( ones that are not bound to any binding sites ) . Since the free activator number is restricted due to competition , the promoters can stay in unoccupied states for sufficiently long time , even when the binding rate of the activators are faster than the mRNA degradation rate . Hence the only requirement for observing multimodality is that the unbinding rate of activators to the promoter has to be slower than mRNA degradation rate , such that promoters can also stay occupied for a sufficiently long time , allowing the system to again sample the relative abundances of mRNA molecules . It should be noted that for quite a few known TFs , such as LacI , or lambda CI repressors in E . Coli , the unbinding rate from the promoter is slower or comparable to the mRNA degradation rate [42 , 92] . This is also true for many TFs in yeast [93–95] . Please see the Methods section for a comprehensive discussion of the rates we choose . Similarly , for two promoter copies sharing repressors with a number of competitor sites , our model predicts emergence of multi-modal mRNA distribution , as shown in Fig 5D . Just like the case of activators , different modes of mRNA distribution arise and diminish as the number of competitor sites is tuned . In the results above , we assumed for simplicity that the TFs have the same binding and unbinding rate to both the promoters and competitor sites . Nevertheless , our conclusions remain intact even when the TFs bind or unbind to the competitor sites with a different rate than to the promoters ( see Fig K in S1 Text ) . To further validate our model prediction that multi-modal mRNA distribution stems from the promoters of interest competing with the competitor sites for a pool of TFs , we also look at the Pearson correlation coefficient between the numbers of mRNA molecules produced from two promoters of interest . If the number of competitor sites is much smaller than the promoter number , and the TF number is much higher than the promoter number , effectively each promoter is expected to express independently . Thus , a nonzero correlation coefficient can be regarded as a signature of competition . For our choice of parameters , we see that the correlation starts from zero , reaches a minimum and then asymptotically approaches zero as the number of competitor sites is increased ( See Fig L in S1 Text ) . Hence the rise of multimodality at the mRNA level coincides with nonzero values of correlation coefficient , signifying that this effect stems from the competition between the promoters and competitor sites . One central finding of this section is that altering the number of competitor sites and changing the number of TFs in the absence of competitor sites yield qualitatively distinct responses at the level of the mRNA distribution and correlation ( see Fig M in S1 Text ) .
The impact of transcriptional dynamics on gene expression noise has been a topic of intense enquiry , in the field of quantitative regulatory biology [33–37 , 39] . Most of these studies have investigated models of transcription , hinging on the properties of the cis regulatory elements , such as the number of TF binding sites , their binding strength , etc [39 , 49 , 54] . The key assumption these studies make is that we can treat each gene in isolation while dissecting their transcriptional dynamics and its impact on noise in expression . In reality this assumption often breaks down when a TF for a gene of interest gets shared by other genes or competitor sites on the chromosomal DNA or plasmids [55–61] . Hence in order to understand how transcriptional dynamics influences noise in gene expression , theoretical studies need to include the global effect of TF sharing . The model of transcription developed here offers a way to incorporate the interplay of TF copy number and its binding sites and make predictions for how this interplay impacts gene expression noise . Predictions of this model , for the mean mRNA expression as a function of TF copy number is in agreement with recent bulk studies [67] ( see Fig C in S1 Text ) . Moreover , for identical promoters competing for a pool of TFs , we find that both the variance and Fano factor of the mRNA distribution are non-monotonic functions of the TF copy number and show a peak when the TF and promoter copy numbers are comparable . The incorporation of competitor sites into this model gives rise to intriguing predictions at the noise level . As has been expounded in recent studies [65] , at the mean level , gene expression profiles from a wide range of competition scenarios in the presence of competitor sites can be collapsed onto a single master curve by considering the natural variable of the problem . However , at the level of variance this elegant universality ceases to exist . Although there exists a master curve in the variance as a function of the mean for a single promoter copy competing with multiple competitor sites , for more than one promoter copy , this result no longer holds . In other words , for more than one promoter copy , the simple picture of each promoter seeing an effective pool of TFs fails . Although introduction of competitor sites would imply a change in free TF concentration , one key implication of our results is that altering the number of competitor sites has a qualitatively different impact than directly changing the number of TFs in the absence of competitor sites . As is evident , one major outcome of this study is that different scenarios of TF sharing lead to qualitatively distinct noise characteristics at the mRNA level . In a recent set of experiments in E . coli , Jones et al . [44] systematically tuned the number of LacI repressors and counted mRNA molecules across an isogenic population in order to demonstrate the effect of promoter architecture on gene expression noise . Similar strategies could be adopted to systematically test the different scenarios of TF resource sharing by altering the number and strength of competing binding sites , as we have outlined above . We also find that the presence of competitor sites can further lead to a multi-modal distribution , so long as unbinding rates of TFs to the promoters of interest are slower than the mRNA production and degradation rates . Multi-modal distributions in expression , across an isogenic population can provide a fitness advantage in a changing environment , by giving rise to phenotypic diversity [96] . Certain cis regulatory elements have been demonstrated to lead to bimodal expression patterns [71 , 91 , 97 , 98] . Here we demonstrate that a generic feature of promoters competing for a finite TF resource in the presence of competitor sites lead to a multi-modal distribution at the mRNA level . Whether such differential control is used by cells to control the shape and modality of the mRNA distributions is a fascinating question . In general , the impact of global properties of transcription , such as the limited availability of TF [99] or sigma factor [100 , 101] resources on gene expression noise remain poorly understood . In this light our theoretical framework provides a way of deciphering the global effect of genetic resource sharing on expression noise .
For E . Coli , there are several experimental studies that measure the degradation rates of the different mRNAs . In particular genome wide studies in E . Coli have shown that the average lifetime of mRNAs in E . coli is 2 . 5 minutes in the exponential phase and 4 . 5 minutes in the stationary phase respectively , as shown in Figure 3A of [95] . On the other hand numerous studies have measured the binding and unbinding rates of TFs to the promoters , as we have cited in the manuscript . For a lot of these TF such as the well-known Lac and Lambda cI repressors , the average residence times of minutes up to tens of minutes [42 , 92 , 102] . In other words the residence time is longer or comparable than the degradation rates of the mRNA molecules , justifying the assumption we make . For eukaryotes , genome wide studies ( see Figure 2A of [93] ) in yeast have measured the lifetime of mRNA molecules from 4687 genes . These studies found that around 1700 genes have an average lifetime of less than 10 minutes . Although we do not know of genome wide studies that characterize the unbinding rates of all TFs to all binding sequences , we can find examples where the residence time of different TFs to the DNA were measured or inferred [94] . For TFs such as Rap I and Gcr I , the residence times are of the order or 10 minutes . As binding and unbinding rates of different TFs are discovered more of them might have a long residence time at the promoter . In order to compute the mRNA distribution across an isogenic population , we performed Gillespie simulations [85] using codes written in C++ .
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Genetically identical cells , even when they are exposed to the same environmental conditions , display incredible diversity . Gene expression noise is attributed to be a key source of this phenotypic diversity . Transcriptional dynamics is a dominant source of expression noise . Although scores of theoretical and experimental studies have explored how noise is regulated at the level of transcription , most of them focus on the gene specific , cis regulatory elements , such as the number of transcription factor ( TF ) binding sites , their binding strength , etc . However , how the global properties of transcription , such as the limited availability of TFs impact noise in gene expression remains rather elusive . Here we build a theoretical model that incorporates the effect of limiting TF pool on gene expression noise . We find that competition between genes for TFs leads to enhanced variability in mRNA copy number across an isogenic population . Moreover , for gene copies sharing TFs with other competitor sites , mRNA variance as a function of the mean shows distinct imprints for one gene copy and multiple gene copies respectively . This stands in sharp contrast to the universal behavior found in mean expression irrespective of the different scenarios of competition . An interesting feature of competition is that introduction of competitor sites can transform a unimodal mRNA distribution into a multimodal distribution , which could lead to phenotypic variability .
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"proteins",
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"dna",
"transcription",
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"factors",
"population",
"biology",
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"gene",
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"biochemistry",
"rna",
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] |
2017
|
Effect of transcription factor resource sharing on gene expression noise
|
In this study , we have identified a unique mechanism in which human cytomegalovirus ( HCMV ) protein pUL79 acts as an elongation factor to direct cellular RNA polymerase II for viral transcription during late times of infection . We and others previously reported that pUL79 and its homologues are required for viral transcript accumulation after viral DNA synthesis . We hypothesized that pUL79 represented a unique mechanism to regulate viral transcription at late times during HCMV infection . To test this hypothesis , we analyzed the proteome associated with pUL79 during virus infection by mass spectrometry . We identified both cellular transcriptional factors , including multiple RNA polymerase II ( RNAP II ) subunits , and novel viral transactivators , including pUL87 and pUL95 , as protein binding partners of pUL79 . Co-immunoprecipitation ( co-IP ) followed by immunoblot analysis confirmed the pUL79-RNAP II interaction , and this interaction was independent of any other viral proteins . Using a recombinant HCMV virus where pUL79 protein is conditionally regulated by a protein destabilization domain ddFKBP , we showed that this interaction did not alter the total levels of RNAP II or its recruitment to viral late promoters . Furthermore , pUL79 did not alter the phosphorylation profiles of the RNAP II C-terminal domain , which was critical for transcriptional regulation . Rather , a nuclear run-on assay indicated that , in the absence of pUL79 , RNAP II failed to elongate and stalled on the viral DNA . pUL79-dependent RNAP II elongation was required for transcription from all three kinetic classes of viral genes ( i . e . immediate-early , early , and late ) at late times during virus infection . In contrast , host gene transcription during HCMV infection was independent of pUL79 . In summary , we have identified a novel viral mechanism by which pUL79 , and potentially other viral factors , regulates the rate of RNAP II transcription machinery on viral transcription during late stages of HCMV infection .
HCMV is a prototypical beta-herpesvirus and a ubiquitous pathogen in the human population . Upon primary infection , HCMV establishes a lifelong persistent and latent/recurrent infection in a host [1] . Even though HCMV infection is usually asymptomatic , it acts as an opportunistic pathogen and is a major cause of morbidity and mortality in immunocompromised individuals , including transplant recipients and AIDS/HIV patients [2] . Importantly , HCMV is the leading infectious cause of birth defects in newborns [3] . Furthermore , there is evidence for HCMV to act as a risk factor in the development of vascular diseases , such as atherosclerosis , transplant vascular sclerosis , and coronary restenosis after angioplasty surgery [4]–[10] . Finally , HCMV has also been suggested to be relevant to multiple forms of human cancers , where it may have a potential contribution to oncogenic transformation , onco-modulation , and tumor cell immune evasion [11]–[14] . During lytic infection , HCMV genes are expressed in a highly ordered temporal cascade ( reviewed in [15]–[18] ) . Viral transcripts accumulate with three kinetic classes , namely immediate-early , early , and late . The HCMV major IE ( MIE ) genes UL123 ( IE1 ) and UL122 ( IE2 ) play critical roles in predisposing the cellular environment to infection and also act as transactivators to induce early gene transcription . Many early genes encode proteins required for viral DNA synthesis [19]–[21] . The transcript accumulation of early genes is independent of viral DNA synthesis; however , the continued accumulation of a subset of genes ( i . e . , early-late ) is enhanced by the onset of viral DNA synthesis [22] . Following viral DNA replication , late viral genes , which mainly encode structural proteins , start to transcribe and ultimately lead to the assembly and release of infectious particles . Previous studies have shown that the activation of both beta- and gamma-herpesvirus late gene promoters is dependent on the origin of viral DNA synthesis ( OriLyt ) in cis [23]–[25] . This further supports the notion that late gene transcription is tightly coupled to viral DNA synthesis . However , whether viral late gene expression is subjected to additional viral regulation remains poorly defined . In many DNA viruses , viral gene expression during productive infection is also temporally regulated and can be divided into early and late phases separated by viral genome replication . However , the mechanisms of late gene expression are diverse . Simian virus 40 ( SV40 ) requires viral DNA replication in trans to relieve the repression of viral late promoters [26] , [27] , and the viral large T antigen also plays a critical role to activate the late promoters [28] , [29] . Viral late gene expression during papillomavirus infection is tightly associated with keratinocyte differentiation and mediated in part by alternative mRNA splicing [30] . For adenoviruses , activation of late gene expression requires both cis elements of viral DNA replication [31] , [32] and trans acting factors to titrate an inhibitory factor during viral DNA synthesis [33] . For herpesviruses , viral late gene expression has been studied extensively with herpes simplex virus ( HSV ) . In HSV , viral DNA replication is required in cis for activity of late promoters [34] , [35] . HSV proteins , including ICP4 , ICP8 , and ICP27 , facilitate the assembly of transcription preinitiation complexes [36] , [37] , and are required for efficient expression of late genes by interacting with the general transcription machinery [38]–[40] . However , the regulatory activities of these viral proteins in late gene expression are not well conserved in beta- and gamma-herpesviruses . Recently , we and others have demonstrated that HCMV encodes five essential proteins , UL79 , UL87 , UL91 , UL92 , and UL95 , which are required for the expression of viral late genes after viral DNA synthesis [41]–[43] . Murine cytomegalovirus ( MCMV ) M79 and M92 , homologs of HCMV UL79 and UL92 , respectively , are also required for late gene expression [44] , [45] . Homologs of UL79 , UL87 , UL91 , UL92 , and UL95 are found in murine gammaherpesvirus 68 ( MHV-68 ) ( ORF18 , ORF24 , ORF30 , ORF31 , and ORF34 , respectively ) , which have been shown to have similar functions [46]–[49] . Epstein-Barr virus ( EBV ) BcRF1 , a UL87 homolog , is a novel viral TATA-box binding protein with greater specificity for a non-classical TATA-box sequence [50] , [51] . Intriguingly , these factors are conserved only in beta- and gamma-herpesviruses and have no known homologues in herpes simplex virus ( HSV ) [18] , [41] , suggesting a unique viral regulatory mechanism shared by these two herpesviral subfamilies . However , the underlying mechanisms of how these viral factors regulate late gene expression are incompletely understood . During cytomegalovirus infection , viral genes are transcribed by cellular RNA polymerase II ( RNAP II ) . Its largest subunit Rpb1 has a carboxy terminal domain ( CTD ) containing 52 repeats of a heptapeptide ( Tyr1-Ser2-Pro3-Thr4-Ser5-Pro6-Ser7 ) [52] . The CTD acts as a scaffold to interact with other transcription factors and coordinate transcription with other processes , such as mRNA maturation and chromatin modification [53] , [54] . This activity is tightly regulated by the phosphorylation status of the CTD [55] , [56] . Unphosphorylated RNAP II is recruited to preinitiation complexes ( PIC ) [57] . Once bound to a promoter , CTD Ser5 is phosphorylated by cdk7 to release RNAP II from the PIC [58] and also promote the recruitment of capping/splicing factors and histone modification complexes [53] . RNAP II then proceeds to intrinsic pausing sites where it is halted by negative elongation factors ( NELFs ) . The onset of productive elongation requires the positive transcription elongation factor P-TEFb composed of cdk9 and cyclin T , which phosphorylates CTD Ser2 [59] . At the 3′ end of the coding region , phosphatases Ssu72 and Fcp1 dephosphorylate the CTD . RNAP II dissociates from the DNA template and is recycled as an unphosphorylated , initiation-competent form for another round of transcription [60] , [61] . HCMV utilizes RNAP II and the accompanying host machinery for transcription of viral genes . During early times of viral infection , RNAP II and other transcription machinery are recruited to early replication sites to drive viral IE and early gene expression [62] . The protein levels of RNAP II , including hyper-phosphorylated forms , increase as infection progresses [62] , [63] . Treatment of infected cells with cdk inhibitors inhibits viral gene expression as well as viral replication [64] . During late stages of viral infection , cdk kinase and RNAP II-associated transcriptional machinery proteins continue to accumulate and relocate into the peri-replication center [65] . However , how RNAP II transcription machinery remains active on viral loci during late infection requires further investigation . In this study , we dissected the mechanism of HCMV late gene expression by investigating the proteins that are associated with late transcription regulator pUL79 during HCMV infection . We found that pUL79 interacted with a panel of viral and host proteins , including RNAP II , other novel late transcription regulators pUL87 and pUL95 , as well as components of the viral DNA replication complex . We delineated the pUL79-RNAP II interaction and found that pUL79 bound to RNAP II in the nucleus independent of additional viral factors . Mechanistically , pUL79 did not alter RNAP II protein levels or the phosphorylation profile of its CTD . Instead , in the absence of pUL79 , RNAP II stalled on viral DNA loci , including those of viral immediate-early , early , and late genes , but not those of host genes , during late times of infection . This resulted in a significantly diminished elongation rate of RNAP II-driven transcription on viral loci . We conclude that during late times of infection HCMV induces the formation of unique transcriptional machinery in which pUL79 acts as an elongation factor to specifically drive RNAP II-mediated transcription on the viral genome .
To investigate proteins associated with pUL79 , we first generated a recombinant HCMV in which the UL79 coding sequence was tagged with the 3×FLAG sequence ( ADflagUL79 ) so that protein complexes containing pUL79 in infected cell lysate could be isolated by immunoprecipitation ( IP ) with an anti-FLAG antibody ( Fig . 1A ) . Both growth and protein expression profile ( Figs . 1B–1C ) of ADflagUL79 was indistinguishable from those of wildtype AD169 strain ( ADwt ) in human foreskin fibroblasts cells ( HFFs ) . These results indicate that the addition of 3×FLAG tag to the N-terminus of the UL79 coding sequence does not compromise the function of pUL79 . To identify proteins that interacted with FLAG-pUL79 , lysates from HFF cells infected with virus ADflagUL79 or ADwt ( negative control ) were collected at 72 hours post infection ( hpi ) and immunoprecipitated with the anti-FLAG antibody . Immunoprecipitated proteins were resolved by SDS-PAGE and visualized by silver staining ( Fig . 1D ) . Protein bands unique to ADflagUL79 were extracted and their identities were determined by mass spectrometry . For the negative control , we also extracted gel bands from the ADwt sample with migrating positions corresponding to those of ADflagUL79-specific protein bands as negative controls for mass-spectrometry analysis . The full set of proteins that were identified by this approach and unique to ADflagUL79 is listed in Table 1 . These pUL79-interacting proteins could be categorized into several functional groups . Most notably , four out of twelve core subunits of human RNA polymerase II ( RNAP II ) , namely Rpb1 , Rpb2 , Rpb3 , and Rpb5 , were identified ( Table 1 ) . Rpb1 is the largest subunit of RNAP II and its C-terminal domain ( CTD ) plays a critical role in transcription regulation by interacting with various transcriptional factors . Second , several viral proteins that are conserved among beta- and gamma- herpesviruses , including pUL87 , pUL95 , pUL49 , and pUL92 , were found in the pUL79-protein complexes . pUL87 and pUL95 ( shown in Table 1 ) , together with pUL79 , are required for viral late gene expression and are reported to be recruited to the viral pre-replication complexes [42] , [43] . pUL92 , another HCMV protein required for viral late gene expression , was also identified in this mass spectrometry analysis as a pUL79-interacting protein and has been reported as such in a separate study [44] . These data together suggest that pUL79 interacts with other viral regulatory proteins involved in late gene expression during HCMV infection . Third , proteins involved in viral DNA synthesis or shown to be associated with viral lytic origin of replication ( OriLyt ) [66] , including pUL44 , pIRS1 , and pUL112/113 , were also found in pUL79 protein complexes . Copurification of pUL79 and viral DNA replication factors suggests that pUL79 may have a role in coordinating viral DNA synthesis and late gene expression . Finally , several cellular proteins involved in protein translation , such as ribosomal protein subunits and elongation factor 1-alpha1 , were co-purified with pUL79 . In this study , we focused on the interaction between pUL79 and RNAP II subunits . As RNAP II transcribes viral genes during infection , we hypothesized that pUL79 interacts with RNAP II to modify and promote its activity for viral transcription during late stages of infection . To further investigate the association of the RNAP II complex with pUL79 , we first validated this interaction by immunoprecipitation analysis . HFFs were infected with either ADflagUL79 or ADwt ( negative control ) , cell lysates were collected at 72 hpi , and proteins were immunoprecipitated by using antibodies against RNAP II or FLAG , followed by immunoblot analysis ( Fig . 2 ) . For the cells infected with ADflagUL79 , two RNAP II subunits , Rpb1 and Rpb2 , were co-immunoprecipitated with FLAG-pUL79 but were not co-immunoprecipitated from ADwt-infected samples ( Fig . 2A ) . In a reciprocal experiment , an anti-Rpb1 antibody co-immunoprecipitated not only the RNAP II complex ( indicated by Rpb1 and Rpb2 ) in both ADflagUL79- and ADwt- infected samples , but also FLAG-pUL79 in ADflagUL79-infected samples ( Fig . 2B ) . Taken together , these results indicate that pUL79 is associated with the RNAP II complex during viral infection . The RNAP II complex binds to both DNA and RNA fragments . It is possible that the observed interaction of pUL79 with RNAP II is indirect , and is instead the result of the association of both proteins with the same DNA or RNA fragment . To determine if nucleic acids are required for the pUL79-RNAP II interaction , cell lysates were treated with a nonspecific nuclease ( Benzonase ) prior to immunoprecipitation [67] . Benzonase treatment was effective , reducing RNA/DNA to undetectable levels in ethidium bromide-stained agarose gel electrophoresis analysis ( Fig . 2A and Fig . 2B ) . In the presence of nuclease , pUL79 , Rpb1 , and Rpb2 remained co-immunoprecipitated in ADflagUL79-infected lysates ( Fig . 2A and 2B ) . Taken together , these results indicate that pUL79 and RNAP II associate with one another , and that this association is not mediated by nucleic acids . We then sought to determine whether the pUL79-RNAP II interaction could form independent of additional viral factors . To achieve this , we transfected HEK-293T cells with a plasmid expressing HA-tagged pUL79 or an empty vector plasmid . pUL79 contains a PY-nuclear localization signal directing it into the nucleus [68] and is located in viral replication compartments during infection [42] , [43] . Therefore , we extracted nuclear lysates of transfected cells , and performed co-immunoprecipitation analysis to examine the pUL79-RNAP II interaction using either an anti-HA antibody or anti-Rpb1 antibody in the presence of nuclease . As anticipated , HA-pUL79 was present in the nuclear extracts ( Fig . 2C and 2D ) . Anti-HA antibody immunoprecipitated HA-pUL79 together with Rpb1 , particularly the Rpb1 CTD phosphorylated at Serine 2 ( pSer2-CTD ) ( Fig . 2C ) . As pSer2-CTD is a marker of RNAP II undergoing transcriptional elongation , this result suggests that pUL79 may interact with RNAP II during the transcription cycle to modulate its elongation . Reciprocal co-immunoprecipitation using an anti-Rpb1 antibody further confirmed the association of RNAP II with pUL79 ( Fig . 2D ) . Together , these results indicate that pUL79 can interact with RNAP II independent of other viral factors . The presence of pSer2-CTD in the pUL79-RNAP II complex also suggests that pUL79 may regulate the elongation activity of RNAP II . A previous study found that HCMV promotes the accumulation of RNAP II at late times during infection [63] . Various isoforms of phosphorylated RNAP II , including pSer2-CTD and pSer5-CTD ( i . e . CTD phosphorylated at Serine 5 , a hallmark of successful transcription initiation ) also accumulate at these late times [62] , [63] , [69] . However , the mechanism of how HCMV regulates these RNAP II-mediated transcriptional events is not clear . To determine whether the pUL79-RNAP II association can stabilize the RNAP II complex to increase its protein levels , we measured RNAP II protein accumulation during HCMV infection in the presence or absence of pUL79 protein . We have previously constructed a recombinant HCMV virus ADddUL79 in which the UL79 coding sequence was tagged with the highly unstable ddFKBP domain [42] . This allowed us to abrogate pUL79 function by targeting it for rapid degradation , or maintain its function by stabilizing the protein with the synthetic ligand Shield-1 ( Shld1 ) [42] . Here , we infected HFF cells with ADddUL79 in the presence or absence of Shld1 , and analyzed infected cell lysates by immunoblotting at various times post infection . As anticipated , in the presence of Shld1 , ddFKBP-pUL79 was detected at 72 hpi from total cell lysates ( Fig . 3 ) or nuclear extracts ( Fig . S1 ) using the antibody recognizing the ddFKBP epitope . In the absence of Shld1 , ddFKBP-pUL79 was markedly reduced and barely visible only after prolonged exposure by immunoblot analysis . To confirm this regulation of pUL79 activity , we also examined expression profiles of representative viral immediate-early ( IE1 ) , early ( pUL44 ) , and late ( pp71 ) proteins . In the presence of pUL79 , all three classes of viral proteins were accumulated with the expected kinetics ( Fig . 3 ) . In the absence of pUL79 , immediate-early and early proteins accumulated normally but the accumulation of the late protein was dramatically reduced ( Fig . 3 ) . These results were consistent with the previous study [42] , and validated the effectiveness of Shld1-mediated regulation of pUL79 activity in this study . Importantly , the protein levels of Rbp2 and Rpb1 ( both total Rpb1 and various CTD-phosphor isoforms ) increased as expected when infection progressed [62] , [63] , but the accumulations were independent of the presence or absence of pUL79 ( Fig . 3 ) . Together , these results indicate that total RNAP II as well as its CTD modified forms accumulate during viral infection in a pUL79-independent manner . A previous study showed that MHV-68 ORF30 and ORF34 , homologues of HCMV UL91 and UL95 , respectively , are required for the recruitment of RNAP II to the viral late promoters [48] . Like ORF30 and ORF34 , both UL91 and UL95 were reported to be essential for late gene expression [41] , [43] . In this study , we identified pUL95 as a protein partner of pUL79 ( Table 1 ) . Therefore , we hypothesized that pUL79 forms a complex with pUL95 and other binding partners to recruit RNAP II and promote assembly of the transcription initiation complex at viral late promoters . To test this , we determined the occupancy of RNAP II on viral late promoters with or without pUL79 during infection using a chromatin immunoprecipitation ( ChIP ) assay . HFFs were infected with ADddUL79 in the presence or absence of Shld1 and chromatin fractions from infected cells were collected at 72 hpi and analyzed by ChIP assay using a rabbit anti-RNAP II antibody . The amounts of input and output ( immunoprecipitated ) DNA were measured by quantitative real-time PCR ( qPCR ) analysis using primers specific to the promoter or transcript regions of viral genes or the cellular housekeeping gene GAPDH ( Table S2 ) . The localizations of qPCR primers and sizes of qPCR products are diagramed in Fig . 4A . The qPCR results were presented as relative output-to-input ratios to account for the percentages of host/viral genomes occupied by RNAP II during viral infection ( Fig . 4B ) . The levels of viral and cellular DNA immunoprecipitated by Rbp1 antibody were readily detectable whereas DNA immunoprecipitated by control IgG was minimal , indicating the specific binding of Rbp1 to the DNA sequences detected in this assay . However , to our surprise , the occupancy of Rpb1 at the promoter or transcript regions of viral genes was not reduced in the absence of pUL79 , suggesting that pUL79 is not required for RNAP II recruitment to viral promoters ( Fig . 4B ) . Instead , without pUL79 , Rpb1 levels on viral DNA were ∼2–2 . 5 fold higher than those with pUL79 . Importantly , during late times of infection ( 72 hpi ) , elevated Rpb1 accumulation occurred not only on the loci of viral late genes ( UL32 and UL75 ) , it also occurred on those of viral immediate-early genes ( MIE ) and early genes ( UL54 ) ( Fig . 4B ) . Moreover , this increased association of RNAP II with viral DNA occurred at both promoter regions and transcript regions . By comparison , Rpb1 occupancy on the host gene GAPDH was not altered by pUL79 . If pUL79 modulates RNAP II occupancy on viral loci , we would then expect that pUL79 is associated with RNAP II on viral loci . To test this hypothesis , we determined the occupancy of pUL79 on either viral or host loci during infection . HFFs were infected with ADflagUL79 or ADwt viruses and chromatin fractions from infected cells were collected at 72 hpi and analyzed by ChIP assay using either an anti-FLAG antibody , which recognizes the 3× FLAG-tagged UL79 protein , or a control IgG antibody . The amounts of input and output ( immunoprecipitated ) DNA were measured by qPCR analysis using primers identical to those in Fig . 4B . Viral DNA immunoprecipitated by the FLAG antibody from ADflagUL79 samples was readily detectable whereas DNA immunoprecipitated by control IgG was minimal , indicating the specific binding of the FLAG tagged pUL79 to the DNA sequences detected in this assay ( Figs . 4C and S3 ) . Although certain amounts of background DNA were also immunoprecipitated by the FLAG antibody from ADwt samples , the amounts of viral DNA immunoprecipitated from ADflagUL79 samples were generally higher , as determined by ChIP-qPCR . This supports the hypothesis that pUL79 occupies viral loci at late times of viral infection . Finally , amounts of cellular DNA ( i . e . GAPDH ) immunoprecipitated from both ADflagUL79 and ADwt samples were minimal and indistinguishable , suggesting that pUL79 is not associated with the host genome during viral infection ( Fig . 4C ) . Taken together , these results indicate that pUL79 regulates the occupancy of RNAP II on viral loci , but not its recruitment to viral promoters , during late times of viral infection . Next , we wanted to determine how the observed dysregulated elevation in the occupancy of RNAP II on viral DNA when pUL79 was abrogated contributed to its diminished ability to transcribe viral genes . Specifically , we wanted to determine which stage of the RNAP II transcription cycle ( i . e . initiation , elongation , or termination ) was altered by pUL79 by performing ChIP analysis using antibodies that recognize various forms of RNAP II CTD modifications . In a transcription cycle , Ser5 of RNAP II CTD is rapidly phosphorylated ( pSer5-CTD ) to facilitate the dissociation of RNAP II from the promoter and recruitment of RNA capping and splicing factors . After that , pSer5 CTD levels decrease with a concomitant increase in Ser2 phosphorylation ( pSer2-CTD ) to facilitate efficient transcription elongation . At 72 hpi , we found that both pSer5-CTD and pSer2-CTD levels significantly increased on viral loci in the absence of pUL79 compared to those in the presence of pUL79 ( Fig . 5A ) . However , the increase of unphosphorlyated CTDs on viral loci also paralleled that of phosphorylated CTD ( Fig . 5A ) . Therefore pUL79 abrogation appeared to elevate all forms of CTD modifications tested at viral loci . To more specifically determine whether the elevated accumulation of RNAP II on viral DNA arose from a specific CTD modification in the absence of pUL79 , we normalized the ChIP occupancy values of pSer5-CTD , pSer2-CTD , and unphosphorylated CTD to that of total RNAP II . Occupancies of various CTD modifications were proportional to that of total RNAP II , and we found no evidence for the preferential occupancy of a particular CTD modification on any viral locus examined ( Fig . 5B ) . Therefore , elevated RNAP II occupancy in the absence of pUL79 was unlikely to be due to the dysregulation of CTD phosphorylation . Consistently , protein levels of CTD kinases ( Cyclin T1 and CDK9 ) and CTD phospho-isoforms ( pSer2-CTD , pSer5-CTD , pSer5/pSer2-CTD ) were not altered by the presence or absence of pUL79 ( Fig . 3 ) . These results together indicate that pUL79 is not involved in phosphorylation of RNAP II CTD , and suggest that without pUL79 , RNAP II simply stalls during the transcription cycle , resulting in its elevated accumulation at viral loci . Based on the above results , we hypothesized that pUL79 was required for efficient elongation of RNAP II-driven transcription at viral loci . To test this , we determined RNAP II elongation activity using a nuclear run-on ( NRO ) assay . The NRO assay allowed us to monitor the contribution of RNAP II transcriptional activity to transcript levels independent of the effect of RNA stability [70] . To do this , HFF cells were infected with ADddUL79 in the presence or absence of Shld1 and the nuclei of infected cells were isolated at 24 hpi ( early timepoint ) or 72 hpi ( late timepoint ) and analyzed by NRO assay . The amounts of newly synthesized run-on RNA were measured by quantitative reverse transcription-coupled quantitative PCR ( RT-qPCR ) analysis using primers specific to the promoter or transcript regions of viral genes or cellular genes ( Fig . 6A and Table S2 ) . Additionally , total RNA was also harvested to monitor the total transcript accumulation . We found that in the absence of pUL79 , the run-on RNA levels of both MIE and late genes ( UL99 and UL32 ) were reduced at late times of infection ( 72 hpi ) to approximately 40% of those in the presence of pUL79 ( Figs . 6B–6C ) . The run-on RNA levels of early genes ( UL44 and UL54 ) without pUL79 were also reduced to approximately 60% of those with pUL79 ( Fig . 6C ) . As RNAP II transcribes at the rate of 1 . 3–4 . 0 kb/minute [71] , our NRO assay was performed for 30 minutes , which is long enough for RNAP II to transcribe all the viral genes tested . However , without pUL79 , RNAP II still failed to transcribe viral genes at the levels comparable to those in pUL79-containing controls at late times of viral infection . We have observed more RNAP II on viral loci in the absence of pUL79 during late stages of viral infection ( Figs . 4–5 ) . If these RNAP II complexes functioned properly , we would expect more RNA transcripts to be made in a NRO assay that specifically measured the transcriptional elongation rate . However , we instead found that the RNAP II elongation rate was reduced on viral loci in the absence of pUL79 . This is consistent with the hypothesis that the slow-moving RNAP II complexes jammed along viral loci , resulting in its excessive accumulation on viral DNA . Finally , the run-on transcript levels of early genes were indistinguishable at early times of viral infection ( i . e . 24 hpi ) with or without pUL79 ( Fig . 6C ) . Therefore , we conclude that pUL79 is required for the RNAP II elongation on viral loci at late times of viral infection . As a control , we also examined the run-on RNA levels of host genes GAPDH , RPL30 ( which encodes a 60S ribosomal protein ) , and MxA ( which is a human interferon stimulated gene ) . Both GAPDH and RPL30 possess a pattern of histone modifications typical of permissive chromatin , similar to those associated with most CMV viral loci during late times of infection [72] . MxA does not encode a TATA box in its promoter [73] and its transcription is suppressed during HCMV infection [74] . In contrast to viral genes , neither the run-on RNA levels nor total RNA accumulations of three host genes were altered by pUL79 at early or late times of viral infection ( Fig . 6D ) . This is consistent with the ChIP analysis in that the occupancy of RNAP II at GAPDH was found unaltered in the absence of pUL79 ( Fig . 4B ) , and indicates that RNAP II does not stall at host genomic loci even without pUL79 . Therefore , pUL79 is specifically required for efficient transcription of viral genes but not host genes . The HCMV genome is dense and many viral regions are transcribed in both directions , resulting in multiple overlapping or co-terminal transcripts . Therefore , the result of analyzing only one viral locus may be complicated by the presence of overlapping transcripts from neighboring genes . We therefore also examined the RNAP II occupancy and elongation rate at multiple loci of UL48 ( Fig . 7A ) , the longest HCMV gene with late kinetics and where RNAP II occupancy has been characterized in a previous study [75] . Similar to other late viral genes that we examined in this study , RNAP II occupancy on all three loci of the UL48 region examined was increased in the absence of pUL79 ( Fig . 7B ) . Without pUL79 , RNAP II accumulated excessively throughout the UL48 transcribed region , in proportion to its CTD phosphorylations ( Figs . 7C–D ) . However , UL48 transcripts failed to accumulate efficiently in the absence of pUL79 at late times of viral infection ( Fig . 7E ) . Consistently , at late times of infection RNAP II elongation was reduced on all three UL48 loci in the absence of pUL79 , even though the reduction in elongation rates appeared to vary among different UL48 loci ( Fig . 7F ) . Taken together , our results from the NRO assay provide definitive evidence that pUL79 positively regulates the transcription rates of viral genes but not those of host genes . In the absence of pUL79 , RNAP II may still elongate at viral loci but does so at a much slower pace at late times of infection , and ultimately fails to support productive viral gene transcription and viral progeny production .
In this study , we discovered a novel regulatory mechanism of viral transcription mediated by HCMV protein pUL79 . We identified cellular RNA polymerase II ( RNAP II ) as a key factor that interacted with pUL79 . This interaction did not alter the overall accumulation of total RNAP II or its various phospho-isoforms during viral infection . Rather , our data suggest that this interaction allowed pUL79 to act as a virus-encoded elongation factor to stimulate transcriptional elongation activity of RNAP II on viral loci during late stages of viral infection where pUL79 is expressed . Without pUL79 , RNAP II elongation failed to proceed efficiently and stalled on the viral genome . This caused slow turnover and excessive amounts of RNAP II accumulation on viral loci . Ultimately , this led to the failure of productive viral late transcription and progeny production . Why is pUL79 only required for viral transcription at late times but not at early times during infection , even though pUL79-mediated regulation occurs at viral loci of all three kinetic classes ( immediate-early , early , and late ) ( Fig . 6 ) ? pUL79 is a late protein and is not expressed until late times of infection . We and others have shown that immediate-early and early genes are transcribed efficiently at early times before pUL79 is expressed ( Fig . 6 ) [42] , [43] . It is possible that some transcripts made at early times are stable and persist to late times of infection . When overall transcript accumulations were analyzed , the presence of these pre-existing transcripts could render it difficult to reveal the effect of pUL79 on transcription of immediate-early and early genes at late times during infection . However , the NRO assay measures relative transcription elongation rates at specific gene loci at defined times post infection , and is not affected by pre-existing transcripts . Therefore , it reveals more viral genes than previously expected where pUL79 drives the transcription during late times of viral infection . A more systematic NRO analysis , such as global run-on sequencing ( GRO-seq ) of virally infected cells , will further define the scope of viral transcription regulated by pUL79 . Many viral factors have been shown to enhance transcription subsequent to initiation through diverse mechanisms . HIV Tat binds to host positive transcription elongation factor ( P-TEFb ) to remove the blockage of transcription elongation imposed by NELF and DSIF . The Tat/P-TEFb complex stimulates elongation and co-transcriptional processing of proviral transcripts ( Reviewed in [76] ) . During human adenovirus ( HAdV ) infection , viral protein E1A recruits hPaf1 complex to enhance transcriptional elongation of viral early genes [77] . In herpesviruses , HSV-1 ICP27 interacts with RNAP II CTD to recruit the RNAP II complex to viral promoters [78] . HSV-1 ICP22 binds cdk9 to reduce the serine-2 phosphorylated CTD form of RNAP II [79]–[81] . Together , they regulate the recruitment and proteasome-dependent degradation of RNAP II complex during infection to facilitate viral gene transcription . However , during HCMV infection , RNAP II complex does not undergo extensive protein degradation . In contrast , various isoforms of RNAP II , including the serine-2 phosphorylated CTD form , accumulate as viral infection progresses ( Fig . 3 ) . pUL79 does not alter either RNAP II protein accumulation ( Fig . 3 ) or enhance RNAP II recruitment ( Fig . 4 ) . Therefore , pUL79 uses a mechanism distinct from other known viral transcriptional elongation regulators to facilitate RNAP II elongation . Recently , human elongin B was shown to increase the efficiency of RNAP II elongation on viral loci [75] . The siRNA knockdown of elongin B decreases viral mRNA expression as well as reduces RNAP II protein accumulation and occupancy of its serine-2 phosphorylated form on viral loci [75] . Interestingly , elongin B is required for viral mRNA expression of various kinetic classes throughout the whole infection cycle . In contrast , pUL79 is only required at late stages of infection and does not appear to alter the occupancy of various CTD phospho-isoforms of RNAP II on viral loci ( Fig . 5 ) . Whether pUL79 interacts with host elongation factors such as elongin B to exert its activity , or how pUL79 selectively modulates the transcription elongation complex at late times of infection , requires further exploration . What is the potential mechanism for pUL79 to modulate the elongation rate of RNAP II ? It is possible that pUL79 enhances promoter clearance , a step in which RNAP II transfers from the initiation state to the elongation state ( Fig . 8A ) . During the transcription cycle , RNAP II is recruited to promoters by cellular TATA-box binding protein ( TBP ) and other general transcription factors ( GTFs ) to form the pre-initiation complexes ( PIC ) . The PIC places RNAP II at transcription start sites , denatures DNA , and positions DNA into the RNAP II active site for transcription [82] . Once transcription initiates , RNAP II dissociates from the PIC and recruits elongation factors for efficient transcription . The dissociation of RNAP II from the PIC is mediated by TFIIH and other cellular kinases to facilitate exchange between initiation factors and elongation factors [83] , [84] . Inefficient dissociation from PIC reduces the rate of RNAP II elongation , resulting in the failure to transcribe genes [83] . Several herpesviral proteins have been reported to act as viral transcription initiation factors to form a unique viral PIC . For example , the homologues of HCMV UL87 in gamma-herpesviruses were reported to encode viral TBPs and regulate late transcript accumulation [23] , [50] . However , in general TBP loads onto the promoter independent of other factors , and this is consistent with the observation that EBV BcRF1 ( homologue of HCMV pUL87 ) binds to the viral promoter independent of any other partners [50] . Because of this and also the observation that the total RNAP II accumulation on viral loci is not reduced in the absence of pUL79 ( Fig . 4B ) , we hypothesize that pUL79 is not required for the recruitment of pUL87 or subsequently RNAP II to viral promoters . MHV68 ORF30 and ORF34 , homologues of HCMV UL91 and UL95 , are shown to be required for RNAP II recruitment to viral late promoters [48] . However , RNAP II recruitment to viral promoters is not reduced in the absence pUL79 , suggesting that pUL79 is not required for this putative activity of pUL95 ( Fig . 4B ) . Together , we hypothesize that pUL79 is not required for transcription initiation ( Fig . 4B ) . However , the elongation rate of RNAP II at viral loci is reduced drastically , suggesting that pUL79 is essential for a transcription step downstream of initiation ( Fig . 6 ) . Strikingly , pUL79 co-purifies with pUL87 and pUL95 , two viral factors potentially involved in viral PIC assembly ( Table 1 ) . Therefore , even though pUL79 is unlikely to facilitate pUL87 and pUL95 to mediate viral PIC assembly , it is intriguing to speculate that pUL79 may regulate the activity of pUL87 and pUL95 downstream of transcription initiation . As the viral PIC complex may not be recognized by host dissociation factors , it is possible that pUL79 plays a role in the release of RNAP II from viral PIC prior to elongation ( Fig . 8A ) . To test this , further analysis is required to determine the composition of RNAP II/viral PIC as well as their distribution on the viral DNA . It is also possible that pUL79 plays a role in epigenetic regulation to modulate viral transcription ( Fig . 8B ) . During HCMV infection , viral DNA is chromatinized and undergoes histone modifications to facilitate gene expression [85] . In particular , upon the onset of viral DNA replication , newly synthesized viral DNA is wrapped with histone 3 with lysine 4 methylation ( H3K4me2 ) , a modification that favors active transcription , suggesting the potential involvement of epigenetic regulation in viral late transcription [72] . Even though pUL79 was not required for methylating H3K4 [72] , the possibility remains that pUL79 may act as an epigenetic reader to recognize histone modifications unique to viral DNA , and unwrap viral DNA packaged by histones to facilitate RNAP II elongation ( Fig . 8B ) . How does pUL79 specifically regulate transcription of viral loci ? In this study , we showed that pUL79-mediated transcriptional regulation was limited to viral genes , but not host genes ( i . e . GAPDH , RPL30 , and MxA ) . This specificity may be partially due to the localization of pUL79 during infection as pUL79 is enriched in viral replication compartments where late viral transcription occurs [42] . In addition , late promoters of beta- and gamma-herpesviruses contain a non-canonical TATA box sequence [50] . EBV BcRF1 , the homologue of HCMV pUL87 , is a viral TATA-box binding protein which preferentially binds to this non-canonical TATA box over the canonical sequence . This suggests that viral transcription machinery directs RNAP II to viral late promoters during late stages of viral infection [50] . In HCMV , several characterized viral late promoters also contain the same non-canonical TATA sequences [86]–[91] . Therefore , pUL79 may also act as a viral specific TATA-box binding protein . However , in this study we observed an overall decrease in transcription rates among all three kinetic classes of viral loci during late times of infection ( Fig . 6 ) . Further analysis is needed to understand how pUL79 can regulate the rate of viral transcription regardless of the structures of gene promoters . In this study , we found that pUL79 also co-purified with other viral regulators of HCMV late gene expression , suggesting that pUL79 may interact with these regulators to form complexes during viral infection ( Table 1 ) . It is not known whether these viral regulators use similar mechanisms to regulate viral transcription . For example , pUL91 and pUL92 were shown to specifically regulate only true late genes [41] . It is possible that these regulators have conserved functions and yet still possess different specificities . In addition , pUL79 also co-purified with viral DNA replication factors ( Table 1 ) . Previously , we have shown that pUL79-mediated viral transcription requires the onset of viral DNA synthesis [42] . Expression of neither pUL79 alone nor the combination of all known late gene regulators alters the expression kinetics of viral genes , especially viral late genes [41] , [42] . Therefore , it is also possible that viral DNA synthesis events predispose viral DNA to late transcription via interactions between replication factors and pUL79 . In conclusion , we have used a systematic proteomic approach to elucidate the mechanism underlying the activity of the HCMV late gene expression regulator pUL79 . pUL79 interacts with RNAP II to modulate its transcription rate at viral loci during late times of viral infection . This unique viral mechanism is potentially conserved among beta- and gamma- herpesviruses , and provides insight into the design of novel antivirals targeting steps after viral DNA synthesis .
pYD-C755 ( i . e . pLKO ) was a pLKO-based lentiviral vector ( also referred as pLKO . DCMV . TetO . mcs in [92] , a generous gift from Roger Everett , University of Glasgow Centre for Viral Research ) . pYD-C751 ( i . e . pLKO-HA-pUL79 ) was created by cloning a PCR fragment containing the UL79 coding sequence along with an N-terminal hemagglutinin ( HA ) tag into the multiple cloning site of pYD-C755 . pYD-C744 was derived from pGalK [93] , and carried a cassette in which 3×FLAG tag was followed by a GalK/kanamycin dual expression cassette flanked by the Flp recognition target ( FRT ) sequence [94] . The synthetic chemical ligand Shield-1 ( Shld1 ) used to regulate the stability of ddFKBP-tagged proteins was purchased from Cheminpharma ( Farmington , CT ) . Benzonase was purchased from EMD Millipore . The following primary antibodies were used in this study: anti-beta actin ( clone AC15 , Abcam ) ; anti-FLAG ( clone M2/F1804 and M2/F3165 , Sigma-Aldrich ) ; anti-HA ( clone 16B12 , Covance; clone 3F10 , Roche ) ; anti FKBP12 ( clone 8/FKBP12 , BD Biosciences ) ; anti-Rpb1 ( clone N-20 from Santa Cruz to detect total Rpb1; or clone 8WG16 from Abcam to detect both total Rpb1 and the unphosphorylated CTD form of Rbp1 ) ; anti-Rpb2 ( S-20 , Santa Cruz ) ; anti-Rpb1 phospho-CTD Ser5/Ser2 ( clone H-14 , Covance ) ; anti-Rpb1 phospho-CTD Ser5 ( clone 3E8 , Millipore ) ; anti-Rpb1 phospho-CTD Ser2 ( ab5095 , Abcam ) ; anti-CDK9 ( clone H-169 , Santa Cruz ) ; anti-cyclin T1 ( clone H-245 , Santa Cruz ) ; anti-pUL44 ( clone 10D8 , Virusys ) ; anti-IE1 , anti-pp28 , and anti-pp71 ( generous gifts from Thomas Shenk , Princeton University ) . Primary human newborn foreskin fibroblasts ( HFFs ) and HEK-293T cells were propagated in Dulbecco modified Eagle medium ( DMEM ) supplemented with 10% fetal calf serum , nonessential amino acids , sodium pyruvate , and penicillin-streptomycin . Three HCMV recombinant viruses , ADwt , ADddUL79 , and ADflagUL79 , were used in this study . The wildtype virus ADwt was reconstituted from the BAC-HCMV clone pADwt ( also referred as pAD-GFP in the previous study [42] ) . pADwt carries the full-length genome of HCMV strain AD169 , with the exception that it contains a simian virus 40 ( SV40 ) early promoter-driven green fluorescent protein ( GFP ) gene in place of the viral US4–US6 region that is dispensable for viral replication in HFFs [95] , [96] . ADddUL79 was derived from ADwt using BAC recombineering , where the pUL79 coding sequence was fused to that of destabilizing domain ddFKBP [42] . ADflagUL79 was reconstituted from the BAC clone pADflagUL79 . This BAC clone was derived from pADwt , and was constructed by using a linear recombination approach in the bacterial strain SW105 that contained an arabinose-inducible Flp gene for the transient expression of Flp recombinase [94] . Briefly , the cassette that carried 3×FLAG followed by the GalK/kanamycin dual marker was first generated by PCR from pYD-C744 with a pair of 70-bp primers , so that the PCR-generated cassette was also flanked by 50-bp viral sequences immediately upstream or downstream of the 5′-end of the UL79 coding sequence . The cassette was recombined into pADwt at the 5′-end of the UL79 coding sequence by using linear recombination . The GalK/kanamycin marker was subsequently removed by Flp-FRT recombination [94] . The final clone pADflagUL79 contained the 3×FLAG sequence along with a small FRT site fused in frame at the 5′-terminus of the UL79 coding sequence ( Fig . 1A ) . To reconstitute virus , 2 µg of the BAC-HCMV DNA and 1 µg of the pp71 expression plasmid were transfected into HFF cells by electroporation [96] , and the culture medium was changed 24 hours later . For reconstitution of ADddUL79 virus , Shld1 was added every 48 hours to maintain the concentration at 1 µM . Reconstituted virus was harvested by collecting cell-free culture supernatant when the entire monolayer of cells was lysed . To produce virus stocks , cell-free culture supernatants were collected from HFFs infected at an MOI of 0 . 01 . Viruses were pelleted by ultracentrifugation through a 20% D-sorbitol cushion at an average relative centrifugal force of 53 , 000×g for 1 hour , resuspended in DMEM with 10% tissue fetal calf serum , and saved as viral stocks . HCMV titers were determined by 50% culture infectious dose ( TCID50 ) assay in HFFs [42] . Four µg of plasmid DNA and 12 µl polyethylenimine ( PEI ) ( 1 mg/ml , Polysciences ) were mixed with 100 µl OPTI-MEM ( Invitrogen ) and incubated at room temperature for 10 minutes . The mixture was then added to 900 µl complete medium containing 10% fetal calf serum , and applied to 5×106 HEK-293T cells that were seeded one day before . Cells were incubated for 4 hours before medium was changed . For total cell lysates , immunoprecipitation was performed using a protocol modified from previous studies [67] , [97] , [98] . In brief , HFF cells ( 5×107 ) were infected with HCMV ADflagUL79 or ADwt at a multiplicity of infection ( MOI ) of 3 . At 72 hpi , cells were collected , rinsed twice with cold phosphate-buffered saline ( PBS ) , and lysed in 2 ml EBC2 buffer ( 50 mM Tris [pH 8 . 0] , 300 mM NaCl , 0 . 5% NP40 ) supplemented with protease and phosphatase inhibitors . Cell lysates were then supplemented with 250 unit ( U ) Benzonase nuclease ( Millipore ) , incubated at 4°C for 15 minutes . One aliquot of cell lysates was saved as the input control and boiled in the LDS sample buffer in the presence of sample reducing agent ( Novex ) . The remainder was clarified by centrifugation at 10 , 000×g at 4°C for 15 minutes . The supernatant was incubated with protein A-dynabeads ( Novex ) conjugated with antibody to FLAG ( M2 ) or Rpb1 ( N-20 ) together with an additional 250 U of Benzonase at 4°C overnight . In addition , to confirm the nuclease activity of Benzonase , an aliquot of the supernatant was analyzed on a 0 . 8% agarose gel containing 100 µg/ml ethidium bromide for the detection of DNA/RNA . The following day the beads were washed three times with 1 ml EBC2 buffer and once with EBC2 buffer without NP40 . The immuneprecipitants were eluted by boiling in reducing sample buffer for 5 minutes . For nuclear extracts , immunoprecipitation was performed using the Nuclear Complex Co-IP kit according to the manufacturer's instructions ( Active Motif ) . For mass spectrometry analysis , cell lysates were prepared in the presence of Benzonase ( 250 U per 5×107 HFF cells ) , and the efficiency of enzyme digestion was examined in ethidium bromide-stained agarose gel electrophoresis analysis ( Fig . S2 ) . Proteins precipitated by anti-FLAG antibody were resolved on a NuPAGE 4–12% gradient gel ( Novex ) and subsequently stained using a ProteoSilver Silver Stain kit ( Sigma-Aldrich ) according to the manufacturer's instruction . Protein bands unique to ADflagUL79-infected sample were extracted . In addition , gel bands from the ADwt-infected sample with migrating positions corresponding to those of ADflagUL79-specific bands were also extracted as negative controls . Extracted gel samples were submitted to the Keck Mass Spectrometry and Proteomics Facility ( School of Medicine , Yale University ) for liquid chromatography ( LC ) -mass spectrometry analysis for protein identification . Protein amounts were determined by immunoblot analysis as previously described [42] . In brief , proteins were resolved on an SDS polyacrylamide gel , transferred to a polyvinylidene difluoride ( PVDF ) membrane , hybridized with a primary antibody , reacted with the horseradish peroxidase-conjugated secondary antibody , and visualized using chemiluminescent substrate ( Thermo Scientific ) . The ChIP was performed using the MAGnify chromatin-immunoprecipitation system ( Life Technologies ) and reagents provided in the kit according to the manufacturer's protocol with modifications . To prepare the chromatin lysates of ADddUL79 infected cells , 2×106 HFFs were infected with ADddUL79 at an MOI of 3 . 0 in the presence or absence of Shld1 . To prepare the chromatin lysates of ADflagUL79 or ADwt infected cells , 2×106 HFFs were infected with ADflagUL79 or ADwt viruses without Shld1 . At 72 hours , infected cells were washed twice with PBS , trypsinized , and crosslinked with 1% formaldehyde at room temperature with mixing for 10 minutes . Glycine was added to the final concentration of 125 mM and incubated at room temperature for 5 minutes to stop the cross-linking reaction . Cells were collected by centrifugation at 4°C , 200×g for 10 minutes , washed twice in ice-cold PBS , and lysed in 100 µl lysis buffer with protease inhibitors . Chromatins were sheared into 200–500 bp fragments using either a cup-horn Branson Sonifier 450 ( 30-second pulse and 60% output with 40-second interval for 70 times in ice water ) or a NGS Bioruptor ( Diagenode ) ( 3×10 cycles of 15-seconds on/45-seconds off in a automatic water cooling system ) . Samples were gently vortexed every five sonication cycles and allowed to cool in ice water for an additional 2 minutes . Lysates were cleared by centrifugation ( 20 , 000×g , 15 minutes; 4°C ) and stored as 20-µl aliquots . To confirm the size of sheared chromatin fragments , one 20-µl aliquot was treated with RNase A at 37°C for 1 hour and de-crosslinked by protease K treatment overnight . DNA was purified and analyzed by agarose gel electrophoresis ( data not shown ) . To immunoprecipitate protein-bound chromatin fragments , each 20-µl aliquot was diluted in dilution buffer with protease inhibitors , and first incubated with 40 µl BSA-preblocked protein A/G Dynabeads to pre-clean for 2 hours . Beads were removed , and one tenth volume of the supernatant was saved as the input sample . The remainder of the supernatant was incubated with appropriate antibodies to generate protein-antibody complexes or with IgG ( negative control ) ( Table S1 ) at 4°C for 16 hours . Forty µl BSA-preblocked protein A/G Dynabeads ( Invitrogen ) was added to the samples and incubated at 4°C for another 1 . 5 hours to immunoprecipitate the complexes . Beads were collected , washed twice with IP Buffer 1 and three times with IP Buffer 2 . Protein-antibody complexes were eluted from Dynabeads by incubation with reverse crosslinking buffer with proteinase K at 55°C for 15 minutes . Dynabeads were removed , and crosslinking of protein-antibody complexes in the supernatant were reversed by incubation at 65°C for 15 minutes . In addition , the input sample was also treated with the reverse crosslinking buffer in the same procedure to reverse crosslinking . Both input and immunoprecipitated DNAs were isolated by DNA purification on magnetic beads . DNA fragments were quantified by quantitative PCR ( qPCR ) using SYBR Select Mix ( Invitrogen ) kit or Taqman Fast Advanced Master Mix kit ( Invitrogen ) . The sequences of primers and Taqman probes are listed in Table S2 . The protocol of the NRO assay was adapted from previous studies with modifications [70] , [99] , [100] . 1×107 HFFs were infected with ADddUL79 at an MOI of 3 in the presence or absence of Shld1 . At 72 hpi , cells were washed twice with PBS , trypsinized , collected by centrifugation ( 4°C , 270×g ) , and washed twice with cold PBS again to remove residual calcium and magnesium . To extract nuclei , cell pellets were resuspended in 4 mL cell lysis buffer ( 10 mM Tris-HCl , pH 7 . 2 , 3 mM MgCl2 , 10 mM NaCl , 150 mM sucrose , and 0 . 5% NP40 ) for 5 minutes on ice . Extracted nuclei were collected by centrifugation ( 4°C , 170×g ) and gently washed with cell lysis buffer to remove NP40 . Pellets were resuspended in 300 µl freezing buffer ( 50 mM Tris-HCl , pH 8 . 3 , 40% glycerol , 5 mM MgCl2 , and 0 . 1 mM EDTA ) , washed once with 1× run-on reaction buffer ( 20 mM Tris-HCl , pH 7 . 5 , 10 mM MgCl2 , 150 mM KCl , and 20% ( v/v ) glycerol ) . To perform NRO assay , 107 nuclei were incubated in 100 µl 1× run-on reaction buffer with ATP , CTP , GTP ( 0 . 5 mM each ) , and 0 . 2 mM biotin-16-UTP ( Invitrogen ) at 29°C for 30 minutes . The reaction was stopped by snap freezing in liquid nitrogen . As negative controls , run-on reactions were also performed with UTP instead of biotin-16-UTP . To isolate biotin-labeled run-on transcripts , streptavidin-coated Dynabeads ( Dynabeads MyOne Streptavidin C1 , Invitrogen ) were resuspended in binding buffer ( 10 mM Tris-HCl , pH 7 . 5 , 1 mM EDTA , and 2 M NaCl ) , and mixed with an equal volume of run-on transcripts . The samples were incubated at 42°C for 20 minutes and then at room temperature for 1 . 5 hours . Beads were collected , and washed twice with 15% formamide and three times with 2× standard saline citrate ( Invitrogen ) . Biotinylated RNAs on the beads were reverse transcribed to generate cDNA using SuperScript VILO cDNA Synthesis Kit ( Invitrogen ) , and quantified by reverse transcription-coupled qPCR ( RT-qPCR ) analysis . The relative transcript amounts were normalized to those of 18S rRNA ( that is transcribed by RNA polymerase I ( RNAP I ) so is an unbiased internal control for RNAP II activity ) . In addition , total RNA of infected cells was also isolated separately by TRIzol extraction ( Invitrogen ) and the amounts were determined by RT-qPCR analysis ( see Table S2 for primer sequences ) .
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In this study , we report a novel mechanism used by human cytomegalovirus ( HCMV ) to regulate the elongation rate of RNA polymerase II ( RNAP II ) to facilitate viral transcription during late stages of infection . Recently , we and others have identified several viral factors that regulate gene expression during late infection . These factors are functionally conserved among beta- and gamma- herpesviruses , suggesting a unique transcriptional regulation shared by viruses of these two subfamilies . However , the mechanism remains elusive . Here we show that HCMV pUL79 , one of these factors , interacts with RNAP II as well as other viral factors involved in late gene expression . We have started to elucidate the nature of the pUL79-RNAP II interaction , finding that pUL79 does not alter the protein levels of RNAP II or its recruitment to viral promoters . However , during late times of infection , pUL79 helps RNAP II efficiently elongate along the viral DNA template to transcribe HCMV genes . Host genes are not regulated by this pUL79-mediated mechanism . Therefore , our study discovers a previously uncharacterized mechanism where RNAP II activity is modulated by viral factor pUL79 , and potentially other viral factors as well , for coordinated viral transcription .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"cell",
"biology",
"virology",
"gene",
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"genetics",
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] |
2014
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Human Cytomegalovirus pUL79 Is an Elongation Factor of RNA Polymerase II for Viral Gene Transcription
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Antibiotic use on animals demonstrates improved growth regardless of whether or not there is clinical evidence of infectious disease . Antibiotics used for trachoma control may play an unintended benefit of improving child growth . In this sub-study of a larger randomized controlled trial , we assess anthropometry of pre-school children in a community-randomized trial of mass oral azithromycin distributions for trachoma in Niger . We measured height , weight , and mid-upper arm circumference ( MUAC ) in 12 communities randomized to receive annual mass azithromycin treatment of everyone versus 12 communities randomized to receive biannual mass azithromycin treatments for children , 3 years after the initial mass treatment . We collected measurements in 1 , 034 children aged 6–60 months of age . We found no difference in the prevalence of wasting among children in the 12 annually treated communities that received three mass azithromycin distributions compared to the 12 biannually treated communities that received six mass azithromycin distributions ( odds ratio = 0 . 88 , 95% confidence interval = 0 . 53 to 1 . 49 ) . We were unable to demonstrate a statistically significant difference in stunting , underweight , and low MUAC of pre-school children in communities randomized to annual mass azithromycin treatment or biannual mass azithromycin treatment . The role of antibiotics on child growth and nutrition remains unclear , but larger studies and longitudinal trials may help determine any association .
Non-specific antibiotic use has been employed to enhance weight gain in livestock since the 1950s [1] . Previous studies have examined the association between antibiotics and livestock [1]–[6] . These studies have identified benefits of using antimicrobials to improve animal growth , prevent and treat infections , and enhance feed efficiency [7] . In Africa , studies have investigated the effect of antibiotics to prevent and treat disease outbreaks among animals [8] . Anti-parasitic agents have been shown to increase weight in humans , presumably due to their effect on soil-transmitted helminthes [5] . Childhood illnesses such as diarrhea , pneumonia , and malaria have been linked to malnutrition [9] . The World Health Organization ( WHO ) recommends repeated community-wide oral azithromycin distribution for the control of blinding trachoma . Azithromycin is effective against the ocular strains of chlamydia that cause trachoma but may also have an effect on common childhood diseases associated with malnutrition , such as diarrhea , pneumonia , and malaria . Undernutrition is typical in the trachoma-endemic areas where these antibiotic distributions take place . For example , approximately half of Nigerien children under-5 years of age live with chronic malnutrition and one in 10 face severe acute malnutrition [10] , [11] . Here , we collect anthropometric measurements from pre-school children in a community-randomized trial of mass oral azithromycin distributions for trachoma in Matameye , Niger . We compare height , weight , and MUAC in communities that have received 3 years of mass azithromycin treatments: annual versus biannual ( twice-yearly ) . We hypothesize that anthropometric indices are improved in children who are randomized to receive more treatments .
The study obtained ethical approval from the University of California , San Francisco Committee for Human Research and the Comité d'Ethique du Niger ( the Ethical Committee of Niger ) . This study is registered at ClinicalTrials . gov , number NCT00792922 . The study was carried out in accordance with the Declaration of Helsinki . Verbal consent was obtained from the local chiefs of each community before randomization . Verbal informed consent from each child participant's guardian was obtained prior to the examination . This consent process was appropriate given the high rates of illiteracy in the study area and was approved by all institutional review boards . The Partnership for the Rapid Elimination of Trachoma ( PRET ) is a cluster-randomized clinical trial ( clinicaltrials . gov trial , NCT00792922 ) [12] in the Matameye district of the Zinder region in Niger . A 2×2 factorial design was used to assess the effects of standard ( 80% ) and enhanced coverage ( 90% ) of annual mass azithromycin treatment of everyone versus biannual mass azithromycin treatment of children ( 6 months to 12 years ) for trachoma and infection . Each cluster , referred to as a community in this manuscript , is in a government health unit from one of six health centers ( Centres de Santé Intégrée , CSI ) . Within each CSI , we conducted stratified blocked randomization of communities by high or low prevalence of clinical trachoma prevalence in children to account for community-level predictors in study arms prior to treatment . As previously described , communities were randomized to treatment arms , and individual participants were randomly selected from communities for trachoma monitoring [13] . Inclusion criteria for the PRET communities in Matameye were: population between 250–600 at the previous census , and ≥10% prevalence of active trachoma among children ( <60 months of age ) ( trachomatous inflammation - follicular [TF] and/or trachomatous inflammation – intense [TI] per WHO trachoma grading system ) [14] . Of 235 communities in the Zinder region of Niger , 72 communities were eligible for the PRET study . 48 were randomly selected for the PRET study . TCP generated the random allocation sequence of clusters using the statistical package R ( version 2 . 12; R Foundation for Statistical Computing , Vienna , Austria; www . r-project . org ) [15] by TCP [13] . Individuals were randomly selected for trachoma monitoring using MS Access ( v2007 ) by study staff . Study staff enrolled and assigned clusters to interventions . In this substudy , we collected anthropometric measurements from pre-school children from 12 communities randomized to annual treatment of everyone and 12 communities randomized to biannual treatment of children during the 36-month study visit in August/September 2013 . From the PRET study census in May 2013 , individuals were randomly selected for anthropometry using the statistical package R prior to field data collection [15] by TCP [13] . Annually treated communities received three rounds of mass azithromycin treatment . Biannually treated communities received six rounds of mass azithromycin treatment . In annually treated communities , participants aged 6 months and older received a directly observed dose of oral azithromycin ( 1 mg/kg with a maximum dose of 1 gm ) . Study participants in biannually treated communities aged 6 months to 12 years were offered oral azithromycin . In both study arms , those less than 6 months of age were offered topical tetracycline ointment ( 1% ) applied to both eyes twice a day for 6 weeks . Our goal was to collect anthropometric measurements of 50 children in each community . To that end , 62 children , aged 6–60 months at the time of this sub-study , were randomly selected from the randomized registration lists generated from the follow-up PRET study census . Thus , these children were under 30 months of age at the PRET baseline census . Anthropometric measurements were collected at a centralized exam station in each community . If there were less than 50 children in the community , then anthropometric measurements were collected for all children . Prior to the 36-month study visit , four individuals from the Niger Ministry of Health participated in a 1-day interactive WHO anthropometry training [16] in Niamey , Niger led by the F . I . Proctor Foundation team ( University of California at San Francisco ) . In a previous study in Ethiopia , we demonstrated reproducibility of anthropometric measurements among team members who participated in our training [17] . Two of the four trainees had previous experience in anthropometry . The training curriculum included measuring recumbent length , standing height , weight , and MUAC . For children younger than 2 years of age , we measured recumbent length; standing height was measured for children older than 2 years ( Schorrboard; Schorr Productions , LLC , Olney , MD ) . Height and length were measured to the nearest 0 . 1 cm . For children who were unable to stand on their own due to sickness or weakness , we measured recumbent length and subtracted 0 . 7 cm for an estimated height per the WHO conversion formula [18] . Children were weighed individually with little or no clothing; if necessary , children were weighed while being held by a parent or guardian using the taring function ( seca 874 flat floor scale; seca GMBH & Co . Kg , Hamburg , Germany ) . Trained anthropometrists ensured the scale was on a flat surface . Weight was measured to the nearest 0 . 1 kg . MUAC was measured to the nearest 0 . 1 cm with non-stretchable measuring tape developed by Johns Hopkins University [19] . Measurements were collected in triplicate . Children with severe malnutrition or illness were referred to local health posts for treatment . Anthropometrists recorded data on paper forms and sent to San Francisco for data entry . They were masked to treatment allocation and antibiotic coverage data . Community members were not masked to treatment allocation . For our outcome measurements to assess the difference in anthropometric measurements of pre-school children in communities randomized to annual or biannual mass azithromycin treatment , we used the WHO Anthro R macros [20] based on the 2006 WHO child growth standards [21] and converted anthropometric measurements: age- and sex-adjusted community-level nutritional Z scores for wasting ( weight-for-height Z score [WHZ] ) , low MUAC ( MUAC Z score [MUACZ] ) , stunting ( height-for-age Z score [HAZ] ) , and underweight ( weight-for-age Z score [WAZ] ) . We defined low anthropometric scores as Z<−2 . 0 ( based on the WHO reference population ) [22] . For each of the following variables , we used the indicated cutoffs to produce a binary outcome variable: wasting , stunting , underweight , severe underweight ( Z<−3 ) , and low MUAC . For the binary variables , we used clustered logistic regression with CSI and community as random effects , and treatment arm as a fixed effect predictor . We used the log-link to yield estimates for the odds ratios . We also analyzed anthropometric measurements as continuous outcomes using the Wilcoxon signed rank test to compare community means . In addition , we report the pseudomedian ( Hodges-Lehmann estimator ) for these means by arm . In all communities , inclusion was restricted to participants who took their assigned treatment . Overall , 1 , 034 individuals were included in this analysis . As a secondary analysis , for WHZ scores , we only included child participants in this sub-study who received their assigned study treatment: annual ( three times ) or biannual ( six times ) . To confirm this , we included participants who received their assigned treatment in the annual communities for WHZ scores . We estimated that 24 communities ( 12 communities per group ) would provide greater than 80% power to detect an absolute difference of 6% wasting between the two arms , assuming 50 children per community , 2-sided α = 0 . 05 and an intraclass correlation coefficient ( ICC ) of 0 . 015 [23] and a prevalence of wasting of 8% . For all statistical analyses , we used the statistical CI package STATA 10 ( Stata Corp . , College Station , TX ) [15] . For this single cross-sectional visit comparison , there were no interim analyses or stopping guidelines .
All 24 communities remained in this substudy ( Figure 1 ) . In the PRET study , the 12 annually treated communities received treatment three times ( June/July 2010 , June/July 2011 , and June/July 2012 ) . The 12 biannually treated communities were treated six times ( June/July 2010 , December 2010/January 2011 , June/July 2011 , December 2011/January 2012 , June/July 2012 , and December 2012/January 2013 ) . We collected anthropometric measurements from a total of 1 , 034 children in 24 communities ( 486 annual treatment arm; 548 biannual treatment arm ) . The confidence intervals ( CI ) for antibiotic coverages among children in the 12 annual communities are 93 . 8–96 . 5 , 88 . 4–94 . 6 , and 87 . 5–94 . 1 . In the 12 biannual communities , the CI for antibiotic coverages among children were 92 . 4–95 . 9 , 90 . 8–96 . 5 , 91 . 9–95 . 6 , 87 . 1–96 . 3 , 87 . 3–91 . 3 , and 87 . 5–94 . 1 . We collected anthropometric measurements in August and September 2013 , which was more than 1 year after the last treatment for the annually treated communities and about 8 months after the last treatment for the biannually treated communities . As shown in Table 1 , the baseline characteristics of children who were eligible for inclusion in this study ( includes ≤30 months of age for follow-up 3 years post-baseline ) are comparable between treatment arms . All study communities were treated per study protocol and no communities were lost to follow-up . There were no serious adverse events reported for the study medication . In the biannually treated communities and the annually treated communities ( mixed effects logistic regression with community and CSI as a random effect ) , the odds ratio for wasting in the biannually treated communities relative to the annually treated communities was 0 . 89 ( 95% CI = 0 . 53 to 1 . 49 ) , odds ratio for stunting was 0 . 78 ( 95% CI = 0 . 54 to 1 . 13 ) , and odds ratio for underweight was 0 . 88 ( 95% CI = 0 . 66 to 1 . 19 ) . When restricted to ages 6 to 24 months , the odds ratio for stunting was 0 . 85 ( 95% CI = 0 . 51 to 1 . 42 ) . Among children under 5 years of age , the odds ratio for MUAC was 0 . 62 ( 95% = 0 . 32 to 1 . 17 ) . In the annually and biannually treated communities , the mean prevalence of severe wasting ( WHZ<−3 . 0 ) was not significantly different ( OR = 0 . 85 , 95% CI = 0 . 34 to 2 . 12 ) . The estimated ICC was 0 . 024 ( 95% CI = 0 . 019 to 0 . 077 , bootstrap percentile ) for height and 0 . 008 ( 95% CI = 0 . 007 to 0 . 060 , bootstrap percentile ) for weight . As shown in Tables 2 and 3 , we were unable to demonstrate a significant difference in anthropometric measurements among children from annually treated communities and biannually treated communities .
Our community-randomized clinical trial demonstrated no significant difference in anthropometric measurements of pre-school children from communities randomized to annual mass azithromycin treatments of everyone in the community versus biannual mass azithromycin treatments of children only . Therefore , not only was the frequency of mass treatments different between the study arms , but so were the populations treated . While pre-school children in annually treated communities had a higher prevalence of wasting , stunting , low MUAC , and underweight in comparison to biannually treated communities , these differences were not statistically significant . Our study has some important limitations worthy of discussion . First , we examined the effects of mass azithromycin distributions on children who received annual treatment and biannual treatment . However , if we examined children from communities who received no antibiotics and children from communities who received many treatments , differences in child growth and nutrition might have been more apparent . In addition , any effect on wasting , if present at all , might be more likely to be observed closer to the time of the antibiotic distribution . Second , this study was a subset of communities from a larger trial; perhaps a larger study could detect a significant difference . Future studies could be powered to detect a smaller effect on height and weight . Third , the study design was post-test only ( no baseline data were collected ) and we did not collect longitudinal data . The inclusion of baseline data can sometimes improve power , if using a change score or using baseline as a covariate predicting final outcome . Note however that the majority of 0–5 year-olds at the end of the study had not been born at the start of the study . The randomized post-test design does permit valid inference , since the treatment assignments are stochastically independent of any other explanatory covariate ( including baseline anthropometry ) [24] . In addition , this was in an area meso-endemic for trachoma , which may be a sign of poor socioeconomic conditions . It is unclear what , if any , effect would have been seen in poorer or wealthier areas . Finally , it may be difficult to assess the true effect of antibiotics on anthropometry due to a possible seasonal effect in this local context . These measurements were collected towards the end of August and September , near the end of the rainy season and before the harvest , coinciding with Niger's season of rains , hunger , and malaria ( June to October ) . During this time , the rate of acute malnutrition in children under 5 years of age is high , surpassing the global emergency threshold for malnutrition [10] . Antibiotics might not be expected to affect acute malnutrition–indeed we find no significant difference in wasting between the two arms . Children also become more susceptible to other infectious diseases such as malaria , acute respiratory diseases , and diarrheal diseases among other infections [10] . The burden of malnutrition and malaria is detrimental to child health . In Niger , malaria is the leading cause of death among children under 5 years of age and pregnant women [10] . These factors may make it more challenging to detect an effect of azithromycin on child growth and nutrition . A recent cluster-randomized trial in the same study area of Niger , but in different communities , did not find significant difference in anthropometric measurements due to mass antibiotic treatments at 1 year [25] . Children from communities randomized to two azithromycin treatments had higher anthropometry indices compared to children from communities randomized to only one , although differences were not statistically significant . There are positive and negative effects of the mass oral azithromycin distributions . Mass antibiotic distributions have been successful for trachoma control and azithromycin is well tolerated [26] . Studies demonstrate that azithromycin may be beneficial for infectious diseases such as pneumonia [27] , diarrhea [28] , [29] , and malaria [30] . In addition , previous case-control [31] and cluster-randomized [32] trials in Ethiopia found significant reductions in childhood mortality with mass azithromycin distributions . Mass antibiotic distribution programs also have the potential to select for antibiotic resistance . Distributions have been proven to select for nasophargyngeal pneumococcus [33] , although resistance decreased when mass treatments were discontinued [34] . In addition , there is potential for azithromycin to affect the proposed pathway from small intestinal mucosal damage to growth faltering in two ways: ( i ) it may reduce or modulate the intestinal microbial load , thereby reducing microbial translocation and/or ( ii ) as a macrolide , it may directly reduce systemic immune activation via its well-recognized immunomodulatory effects [35] . In conclusion , we did not find a significant difference in height , weight , and MUAC of pre-school children in communities randomized to annual mass azithromycin treatment versus biannual mass azithromycin treatment , and cannot support a role of antibiotics on child growth and nutrition . Additional studies are needed to further explore the potential impact of antibiotics on child growth . If antibiotics do enhance child growth and nutrition , this could significantly reduce infant and child mortality worldwide .
|
Recent studies suggest that antibiotic use could have an effect on growth in humans . Azithromycin is an antibiotic used for trachoma control , and hence , may have an unintended benefit of improving child growth . Niger is a trachoma-endemic country where mass antibiotic distributions for trachoma take place and where malnutrition is widespread among children . In addition , azithromycin may have an effect on common childhood diseases associated with malnutrition , such as diarrhea , pneumonia , and malaria . In a community-randomized trachoma trial in Matameye , Niger , we assessed child growth by measuring height , weight , and mid-upper arm circumference of pre-school children who have received 3 years of annual or biannual mass azithromycin treatment . While these measures were better in the biannually treated communities , the difference was not statistically significant . Thus , further research will help determine the impact of antibiotics on child growth and nutrition .
|
[
"Abstract",
"Introduction",
"Methods",
"Results",
"Discussion"
] |
[
"public",
"and",
"occupational",
"health",
"medicine",
"and",
"health",
"sciences",
"global",
"health"
] |
2014
|
Does Mass Azithromycin Distribution Impact Child Growth and Nutrition in Niger? A Cluster-Randomized Trial
|
Schistosomiasis is among the most prevalent parasitic infections worldwide . However , current Global Burden of Disease ( GBD ) disability-adjusted life year estimates indicate that its population-level impact is negligible . Recent studies suggest that GBD methodologies may significantly underestimate the burden of parasitic diseases , including schistosomiasis . Furthermore , strain-specific disability weights have not been established for schistosomiasis , and the magnitude of human disease burden due to Schistosoma japonicum remains controversial . We used a decision model to quantify an alternative disability weight estimate of the burden of human disease due to S . japonicum . We reviewed S . japonicum morbidity data , and constructed decision trees for all infected persons and two age-specific strata , <15 years ( y ) and ≥15 y . We conducted stochastic and probabilistic sensitivity analyses for each model . Infection with S . japonicum was associated with an average disability weight of 0 . 132 , with age-specific disability weights of 0 . 098 ( <15 y ) and 0 . 186 ( ≥15 y ) . Re-estimated disability weights were seven to 46 times greater than current GBD measures; no simulations produced disability weight estimates lower than 0 . 009 . Nutritional morbidities had the greatest contribution to the S . japonicum disability weight in the <15 y model , whereas major organ pathologies were the most critical variables in the older age group . GBD disability weights for schistosomiasis urgently need to be revised , and species-specific disability weights should be established . Even a marginal increase in current estimates would result in a substantial rise in the estimated global burden of schistosomiasis , and have considerable implications for public health prioritization and resource allocation for schistosomiasis research , monitoring , and control .
Schistosomiasis is one of the most prevalent parasitic infections worldwide . An estimated 779 million people are at risk for schistosomiasis , with 207 million infected in 76 countries and territories [1] , [2] . Approximately 120 million people are symptomatic and 20 million have severe and debilitating disease [3]–[5] . Schistosomiasis accounts for 1 . 7 [6] , [7] to 4 . 5 million disability-adjusted life years ( DALYs ) [8] lost each year worldwide , among the highest of all neglected tropical diseases . Schistosomiasis japonica is caused by the trematode Schistosoma japonicum . Schistosome egg deposition in tissue and subsequent inflammatory immune response result in extensive clinical manifestations , including hepatomegaly , splenomegaly , and liver fibrosis [9]–[16] , as well as “subtle” morbidities such as anemia , diarrhea , growth retardation , and cognitive deficits [10] , [17]–[21] . Schistosomiasis japonica may be more pathogenic compared to other schistosomes affecting humans , due to comparatively higher egg production [22] . However , the burden of human disease due to S . japonicum infection is not well-established . Global Burden of Disease ( GBD ) estimates indicate that the population-level impact of schistosomiasis is negligible . Schistosomiasis accounts for only 0 . 1% of the global burden of disease [23] . A major limitation of the GBD burden estimates for schistosomiasis is their restriction to the period of acute infection , excluding a number of chronic , severe , and debilitating morbidities , such as liver cirrhosis and cognitive deficits , which were included in disability estimations for other infections . As a result , age-specific GBD disability weights were estimated to be 0 . 005 for those <15 years ( y ) of age and 0 . 006 for those ≥15 y , on a scale from 0 ( no impairment ) to 1 ( death ) [8] , [17] , [19] , [24] . Similar GBD weights have been assigned to relatively minor conditions such as facial vitiligo [8] , [17] , [19] , [24] . In contrast , some studies [19] , [24] have suggested that the actual burden of schistosomiasis is several-fold higher than current GBD estimates [8] , [17] , [19] , [24] . For example , a recent systematic review and meta-analysis of all schistosome strains [19] and a community-based study of chronic schistosomiasis japonica in China [16] concluded that the GBD disability weights underestimate the extent of disability due to schistosomiasis; re-estimated disability weights for schistosomiasis were four to 30 times higher than current GBD measures [19] , [23] , [25]–[27] . Another limitation of the GBD study [23] , [25]–[27] and subsequent schistosomiasis burden assessments [19] , [24] was their estimation of disability weights for all three major schistosome species ( S . japonicum , S . mansoni and S . haematobium ) together , despite their distinct pathophysiology and associated morbidities . A recent community-based study in China using a standard quality of life measurement scale ( EuroQol ) suggested that species-specific estimation of disability weights for schistosomiasis is warranted , and that GBD values aggregated across all schistosome species may underestimate the disability associated with S . japonicum [16] . However , this study excluded nutritional and neurological morbidities , and may therefore still underestimate the burden of human disease due to S . japonicum infection . The burden of schistosomiasis has not been re-examined in over a decade , despite three revisions to the GBD study [25]–[27] and a strong recommendation from the World Health Organization ( WHO ) [8] . Additionally , there is a lack of international consensus in disease burden assessment criteria , disability weights , and estimated burden for schistosomiasis . For example , in 2002 , a WHO Technical Report recalculated the global burden of schistosomiasis at 4 . 5 million DALYs , and asserted that the previous estimate of 1 . 7 million DALYs lost to schistosomiasis ( 2001 ) “represents a serious underestimate and should be revised” [8] . However , the WHO continues to report the 1 . 7 million DALYs figure from 2001 [6] , [7] . Further , there is a more than ten-fold difference between GBD and WHO estimates for schistosomiasis-related mortality , or 15 , 000 to 280 , 000 deaths per year [8] , [23] . At present , no global species-specific burden assessment exists for schistosomiasis . The burden due to S . japonicum remains controversial and warrants further investigation . This study was conducted to quantify age-specific disability weight estimates for the burden of human disease due to S . japonicum infection using a decision model approach .
We conducted a structured literature search using MEDLINE electronic database to identify published studies from Jan 1 , 1966 to May 1 , 2007 . A detailed summary of key words and search headings are provided in Appendix S1 . Additional sources were identified from bibliographies of published studies , hand searches of scientific meeting abstracts , expert committee reports , and unpublished manuscripts and theses at Brown University , United States . We also solicited unpublished studies from known schistosomiasis japonica researchers via e-mail to minimize publication bias . These sources were retrieved , collected , indexed , and assessed for morbidity and disability outcome data . The initial inclusion criteria for this review were the availability of an abstract and a focus on human infection with schistosomiasis . The abstracts of all remaining studies were reviewed and the following inclusion criteria were applied: ( i ) focus on S . japonicum; ( ii ) human studies; ( iii ) experimental or observational ( treatment , morbidity ) study designs; and ( iv ) description of S . japonicum morbidity measures and their respective prevalences and/or disability weights ( Figure 1 ) . Additional information on publication date , author , location , population , study type , and relevant outcomes were recorded . Where available , we collected morbidity estimates based upon standardized clinical physiological data and WHO diagnostic criteria [28] such as grades I through III clinical classification for hepatic fibrosis and cirrhosis [29] or Hackett score ≥2 to define splenomegaly [30] . Although major organ pathologies such as hepatic and spleen morbidities have not been extensively studied in schistosomiasis , these morbidities were included as disability-related outcomes in the GBD disease burden assessment for other conditions . We included these morbidities in this assessment of disability-related outcomes in S . japonicum , based on our a priori hypothesis that they may impose a heavy burden on infected individuals . We identified a broad spectrum of morbidities associated with S . japonicum , namely: diarrhea , gastrointestinal bleeding , abdominal pain , hepatomegaly ( mild/moderate , severe ) , hepatic fibrosis and cirrhosis ( mild , moderate , severe ) , splenomegaly , cognitive deficits , stunting , wasting , anemia ( mild , moderate , severe ) , central nervous system disease ( i . e . , including non-epilepsy neurological manifestations ) , and epilepsy . Decision trees were used to systematically combine a large number of prevalence and disability data for S . japonicum morbidities [31] . The disability weight for schistosomiasis was estimated in three models to represent all ages , those aged <15 y and those aged ≥15 y , in order to facilitate comparison with the GBD study . For each model , the disability weight was estimated as:where PmorbidityA represents the probability of the Ath morbidity , DmorbidityA represents the disability weight associated with the Ath morbidity , and N is the total number of morbidities considered . In general , we structured the decision trees to allow for all plausible combinations of morbidities , with the presence or absence of any single morbidity considered independently from other morbidities , with the exception of liver morbidity . Our model was therefore a series of successive binary branches , each depicting the presence or absence of a single morbidity . This means that although the probability of developing each morbidity was less than 1 by definition , the sum of all morbidity probabilities could exceed 1 . Based on available hepatic pathophysiology data , we conservatively structured the model to restrict liver pathologies according to usual liver disease progression ( i . e . hepatomegaly to fibrosis to cirrhosis ) , and allow for the co-occurrence of only hepatomegaly and fibrosis . This is because , as the disease progresses to more severe pathology , the associated disability weight also increases . Therefore , if a combination of several liver co-morbidities had been allowed , the disability weight for liver disease could be overestimated . Figure 2 illustrates the branch of the decision tree for the liver pathologies . We calculated a baseline disability weight for each model using the most conservative mean estimates for disability weight inputs for all morbidities . We re-evaluated each model after systematically excluding each input to evaluate the independent contribution of each variable to the overall disability weight estimate . Model inputs were considered critical variables if they contributed more than 10% to the overall disability weight .
The retrieval search strategy for study selection and details regarding study inclusion and exclusion in this analysis are diagrammatically represented in Figure 1 . We identified 1093 potentially relevant studies from 1966 to May 1 , 2007 . We excluded 187 studies because no abstract was available . From the remaining 906 publications , 438 non-human studies were excluded , and 468 studies were retrieved for a detailed review . After careful examination of the publications , a total of 420 studies were excluded , including: 42 additional non-human studies , 44 non-S . japonicum , 32 case reports , 98 review articles , and 204 with no morbidity measure linked to schistosomiasis and/or no useable information on morbidity outcomes . A total of 48 studies met the inclusion criteria for this assessment , including 34 primary publications and 14 secondary papers from the same studies ( Figure 1 ) .
Our findings indicate that age-specific disability weights of 0 . 098 to 0 . 186 would be a more appropriate estimate for the burden of human disease due to S . japonicum infection . It is noteworthy that even the most conservative estimates were seven times greater than current GBD disability weights for schistosomiasis ( Table 3 ) [23] , [25]–[27] . Findings in this study are consistent with King et al . 's [19] meta-analysis of disability-related outcomes in all strains of schistosomiasis . Minimum re-estimated disability weights in our assessment of 0 . 044 ( <15 y ) and 0 . 123 ( ≥15 y ) were similar in magnitude to King et al's estimates of 0 . 02 to 0 . 15 , although our median values and upper estimates were considerably higher . This is concordant with the assertion that S . japonicum is more pathogenic than other schistosomes [22] . Our disability weight estimates are also consistent with findings from a community-based study in China that focused on chronic schistosomiasis japonica , reporting an overall disability weight of 0 . 191 and age-specific estimates of 0 . 095 ( 5–14 y ) and 0 . 159 ( 15–44 y ) [16] . Current findings and burden re-assessments by King and colleagues and Jia and colleagues are in contrast to two earlier reviews that suggested a minimal public health impact of schistosomiasis [34] , [35] . There are several differences in King et al . 's meta-analysis of all schistosomes [19] and the China study focusing on chronic infections due to S . japonicum [16] compared to our analysis , particularly regarding the selection of schistosomiasis-related health conditions . In contrast to King et al . 's [19] assessment , we accounted for hepato-splenic pathologies due to S . japonicum infection , and identified them as critical disability-related outcomes , as did the Chinese study [16] . The exclusions of organ pathologies in King et al . 's assessment [19] and nutritional morbidities in the China study [16] may contribute to an underestimation of disability weights , relative to our findings . We also excluded work and school performance outcomes in our assessment , due to the limited availability of such studies in S . japonicum and a lack of objective standardized measures for these outcomes . Inclusion of these functional outcomes in future studies is expected to further increase estimated disability weights for S . japonicum . There are several study limitations . Few incidence studies were available , and results are based on review of only 34 primary papers ( 48 total ) with usable outcome information . Due to the nature of this analysis , which is to describe the natural history of acute and chronic S . japonicum infection , we decided not to formally score each study based on the quality of the information included . Hence , we assumed that every report represented the best available information for the specified population and outcomes at the time the study was undertaken [31] . Our analysis was limited by the research designs and topical foci of earlier studies . We did not include the entire range of possible morbidities and disabilities due to S . japonicum infection . We also excluded mortality-related outcomes and did not account for treatment status , co-morbidities with other infectious or non-infectious diseases , infection intensity , re-infection , or disease progression in order to facilitate comparability of findings to the GBD assessment [23] , [25]–[27] . There is a possibility of publication bias in every review . To limit this , we solicited both published and unpublished manuscripts and consulted with experts in order to limit publication bias , and intentionally biased our model estimates to the lower ranges for each model parameter , in order to obtain conservative estimates . In addition , when more than one publication described the frequency of occurrence of a specific morbidity associated with schistosomiasis , the most conservative estimate was included in the assessment . These exclusions and limitations in available studies would likely lead to an underestimation of re-estimated model disability weights . In schistosomiasis-endemic regions , polyparasitism , malnutrition , and other infectious diseases are ubiquitous . Therefore , it is important to interpret findings in the context of concurrent infections . For example , some disability-related outcomes , including anemia and diarrhea , may be due to the presence of other parasitic infections . Although polyparasitism may have contributed to an over-estimation of disability weights attributable to S . japonicum , this is unlikely since we used highly conservative estimates in this analysis . Recent studies have challenged the ability of experts to quantify patient-centered disability , particularly in chronic conditions characterized by low mortality [17] , [19] , [36] , [37] and extensive co-morbidities [19] , [38] , [39] . However , the extent of the disparity between expert opinion and patient's experience is unknown . Expert panel methodologies may also underestimate the disability-related impact of nutritional morbidities , in favor of more standardized and observable organ pathologies . Therefore , the fundamental reliance on GBD disability weights in this assessment also represents an important study limitation . Decision model estimation is a useful analytic method for conducting disease burden assessments; however , deterministic and probabilistic sensitivity analyses are exploratory , rather than explanatory . As a result , decision model estimation does not facilitate evaluation of the statistical significance or robustness of findings , which represents a study limitation . The β-distribution was selected for this analysis based on its satisfaction of a priori requirements to restrict the estimate ranges from 0 and 1 , calculation and summarization of data , and evaluation of the level of estimate uncertainty [32] . Similar to other distributions , the β-distribution is influenced by the quality , availability , and level of skewness in model inputs . Therefore , availability and quality of epidemiological and disease burden data remain study limitations . Further research is needed to examine the broad range of morbidities associated with schistosomiasis , particularly on methods to parse attributable causation of specific infections in the context of polyparasitism and other comorbid conditions . Additionally , the separation between specific causes of disease from associated morbidities , and the exclusion of selected conditions partially attributable to other infections in the GBD assessment may contribute to an underestimation of disability weights for schistosomiasis . Lastly , as a zoonotic disease , schistosomiasis japonica is also a veterinary and agricultural public health issue . Future interdisciplinary research should consider the direct impact on human health and the indirect impact on animal health and economic productivity . Methods described by Budke et al . [40] and Carabin et al . [41] could also be utilized to broaden S . japonicum burden assessment to incorporate cost-effectiveness measures [40]–[42] . In conclusion , a minimum disability weight of 0 . 033 to 0 . 091 would be a more accurate estimate of disability due to S . japonicum . GBD methodologies underestimate the burden of disease attributable to S . japonicum , and hence they should be revised . Even a minimal increase in current estimates would result in a substantial rise in the estimated global burden of schistosomiasis , and have considerable implications for public health prioritization , health policy , and resource allocation for research , monitoring , and control .
|
Schistosomiasis is a parasitic infection caused by a flatworm that disproportionately affects the world's poorest populations . Schistosomiasis is one of the most common infections worldwide , affecting over 207 million people in 76 countries . Current international estimates indicate that schistosomiasis has a minimal impact at the population level . This has contributed to its low prioritization in global health and subsequent resource allocation for disease control . However , recent studies indicate that these measures underestimate the extent of neglected tropical diseases , including schistosomiasis . Despite World Health Organization recommendations , the burden of schistosomiasis has not been re-examined in over a decade , and there are no established estimates for different types of schistosomiasis . The impact of symptoms associated with the Asian strain , Schistosoma japonicum , remains controversial . This study was conducted to provide an alternate measure of the burden of S . japonicum . We reviewed the literature and calculated a summary estimate for S . japonicum which was seven to 46 times greater than current measures for schistosomiasis . Findings suggest that current measures severely underestimate the extent of schistosomiasis , and urgently need to be revised . Further research is needed to examine the burden of schistosomiasis and other forgotten tropical diseases affecting the world's poorest people in endemic countries .
|
[
"Abstract",
"Introduction",
"Methods",
"Results",
"Discussion"
] |
[
"infectious",
"diseases/helminth",
"infections",
"public",
"health",
"and",
"epidemiology/global",
"health",
"infectious",
"diseases/epidemiology",
"and",
"control",
"of",
"infectious",
"diseases",
"infectious",
"diseases/neglected",
"tropical",
"diseases"
] |
2008
|
Decision-Model Estimation of the Age-Specific Disability Weight for Schistosomiasis Japonica: A Systematic Review of the Literature
|
Leptospirosis is a neglected zoonosis with worldwide distribution . The causative agents are spirochete bacteria of the Leptospira genus , displaying huge diversity of serovars , the identity of which is critical for effective diagnosis and vaccination purposes . Among many other mammalian species , Leptospira infects cattle , eliciting acute signs in calves , and chronic disease in adult animals often leading to abortions . In South America , and including in Uruguay , beef and dairy export are leading sources of national income . Despite the importance of bovine health , food safety , and bovine-related dissemination of leptospirosis to humans , extremely limited information is available as to the identity of Leptospira species and serovars infecting cattle in Uruguay and the South American subcontinent . Here we report a multicentric 3-year study resulting in the isolation and detailed characterization of 40 strains of Leptospira spp . obtained from infected cattle . Combined serologic and molecular typing identified these isolates as L . interrogans serogroup Pomona serovar Kennewicki ( 20 strains ) , L . interrogans serogroup Canicola serovar Canicola ( 1 strain ) , L . borgpetersenii serogroup Sejroe serovar Hardjo ( 10 strains ) and L . noguchii ( 9 strains ) . The latter showed remarkable phenotypic and genetic variability , belonging to 6 distinct serogroups , including 3 that did not react with a large panel of reference serogrouping antisera . Approximately 20% of cattle sampled in the field were found to be shedding pathogenic Leptospira in their urine , uncovering a threat for public health that is being largely neglected . The two L . interrogans serovars that we isolated from cattle displayed identical genetic signatures to those of human isolates that had previously been obtained from leptospirosis patients . This report of local Leptospira strains shall improve diagnostic tools and the understanding of leptospirosis epidemiology in South America . These strains could also be used as new components within bacterin vaccines to protect against the pathogenic Leptospira strains that are actually circulating , a direct measure to reduce the risk of human leptospirosis .
Leptospirosis is a zoonotic disease of worldwide importance caused by pathogenic spirochetes belonging to the genus Leptospira [1] . It affects humans and a broad range of domestic animals and wildlife . In cattle , leptospirosis is an important cause of reproductive failure , including abortions and stillbirths [2] . Infected bovines also constitute an active reservoir for the spread of the zoonotic disease , especially for humans in direct contact with infected animals including veterinarians , abattoir and farm workers , hunters , as well as scientists handling laboratory animals or during fieldwork [3 , 4] . Domestic and wild animals are important reservoirs in rural areas , unlike urban settings where rats play a major dissemination role [5 , 6] . Human infection with Leptospira spp . results from direct exposure if the source of infection is animal tissue , body fluids or urine , and from indirect exposure if the source is environmental , such as soil or urine-contaminated water . While the disease is endemic in many countries , it often presents as epidemic outbreaks , causing severe , sometimes fatal disease in both humans and animals [7 , 8] . Since the first systematic studies in 1960–1970 , serologic studies in animals have repeatedly shown high prevalence of exposure to Leptospira in Uruguay , with individual seropositivity in the 25–50% range , and herd prevalence figures of 50–70% [9 , 10] . Leptospirosis is considered as a re-emerging bovine disease in Uruguay since 1998 [10] , after what stricter epidemiologic surveillance policies have been adopted by governmental agencies . Human leptospirosis has been included into the official list of diseases of mandatory notification . Leptospirosis in Uruguay is endemic , with limited epidemic outbreaks in rural areas . The annual incidence of human leptospirosis is estimated at 15 per 100 , 000 [11] , with precise figures not determined due to under-reporting and extremely scarce systematic studies in southern Latin America of morbidity/mortality burden [7] . The human disease appears to be associated with bovine infection , as well as to rainfalls and floods [11] , with recent isolation efforts revealing the presence of three L . interrogans serovars , two L . kirschneri and one L . borgpetersenii [12 , 13] . Despite the relevance of bovine leptospirosis as a cause of bovine abortions and infertility in Uruguay , there have been no extensive studies on the actual identities of Leptospira species and serovars obtained from animals in the field . There are currently no repositories of autochthonous isolates available in the public domain , thus constraining vaccine companies to the use of foreign strains as vaccine antigens . Even though Hardjo serovars have been suspected for years to be involved in bovine infection cases [2 , 14] , to the best of our knowledge only four L . interrogans and two L . borgpetersenii isolates belonging to this serovar have been reported in South America [15–17] obtained in Brazil and Chile . An early study also reported six Hardjo isolates in Argentina , without distinguishing the species [18] , and two isolates of L . interrogans Hardjo were also reported , one in sheep from Brazil [19] and one in cattle from Mexico [20] . We now report the first results of a multicentric effort , over the course of 3 years , aimed at isolating pathogenic Leptospira strains in Uruguay , from infected cattle in the field and at abattoirs . A detailed serologic and genetic characterization of such isolates uncovers a larger than expected variety of Leptospira species and serovars . These data will be instrumental for the design of better bacterin vaccines , as well as for improving diagnosis and epidemiologic studies in Uruguay and neighboring South American countries .
Urine and blood sampling from cattle in the field were performed by professional veterinarians , respecting international recommendations for animal welfare , with approval granted by the Ethics Committee for the Use of Animals for Experimentation ( Comisión de Etica en el Uso de Animales de Experimentación CEUA ) , DILAVE , Ministry of Livestock , Agriculture and Fishery ( Ministerio de Ganaderia , Agricultura y Pesca MGAP ) , Uruguay , according to national law #18 , 611 . Permission to take samples for the study was received from the animal owners and the abattoirs . Forty-eight herds from both dairy and beef farms were sampled in this study , during a 33-month period ( Jan 2015-Sep 2017 ) . Private veterinarians who suspected the disease sent the first samples to our laboratory at the Ministry of Livestock , Agriculture and Fishery . Following current protocols in Uruguay , serum samples from 12 animals from each suspected herd , were screened by the microscopic agglutination test ( MAT ) [21] for preexisting antibodies against Leptospira ( S1 Table ) . Farm selection for subsequent sample collection prioritized those herds with presumptive diagnosis of leptospirosis ( MAT titers ≥200 against ≥1 pathogenic Leptospira reference serogroups ) . Farms with recorded history of abortions , infertility or acute disease , were also prioritized . Selected farms were visited from January 2015 to September 2017 , and individual blood and urine samples from 19 animals were collected ( aiming for ≥1 seropositive animal with a 95% confidence interval , using a conservative seroprevalence figure of ≥15% on a reference population of 1000 individuals; seroprevalence estimates from background serologic data in Uruguay are actually higher; the number of individual animals to sample was calculated with the software WinEpi http://www . winepi . net ) . Due to logistic constraints , in a few cases the number of animals per herd was slightly higher , overall sampling a total of 963 individual animals . Individuals to be sampled in each farm were selected according to recorded history when available , prioritizing animals with clinical signs of acute disease ( especially calves with rectal temperature ≥ 39 . 5°C , jaundice and/or hemoglobinuria ) , previous antibody titers ≥200 by MAT , and/or history of abortions or infertility . If less than 19 animals met the latter criteria , additional animals ( heifers or adult cows ) from the same herd were included to complete the required number . A questionnaire was distributed to farmers , gathering information about history of leptospirosis and recent vaccination ( <12 months ) in the farm . Blood samples were collected by coccygeal venipuncture using 5 mL tubes with clot activator . Sera were then stored at -20°C . Intramuscular administration of diuretics ( ~150 mg furosemide , Furo R , Ripoll ) and thorough genital organ cleansing ( wiping with 70% ethanol ) preceded urine collection from individual animals . Approximately 60 mL of midstream urine was collected in sterile 120 mL containers ( Bioset , Medicplast ) . Urine samples ( 100 μL ) were inoculated in the field , immediately or within 2 h of sample collection ( for the rationale , see first section of Results ) , in 5 mL Ellinghausen-McCullough-Johnson-Harris ( EMJH ) medium ( prepared with Leptospira Medium Base EMJH [Gibco] and albumin BovoLep [Bovogen Biologicals PTY Ltd] ) , supplemented with 100 μg/mL 5-fluorouracil ( 5-FU; Sigma ) [21] , and transported at 4°C to the laboratory together with the corresponding blood/serum samples in Vacutainer tubes ( Vacutainer , BD-NJ , USA ) . In the laboratory , two serial 1:50 dilutions were made from the first urine-inoculated tube , in 5 mL EMJH medium supplemented with 5-FU ( EMJH/FU ) , and all three dilutions were incubated at 29°C . The remaining volume of urine samples was conserved at 4°C for subsequent lipL32 gene amplification ( see below ) . Sera were used to determine anti-Leptospira titers by MAT following reported procedures [21] . Routine MAT tests used the national guide of positivity cutoff at titers ≥200 . For comparison of reference vs local strains as MAT antigens ( S5 Table ) , sera from animals from which pathogenic Leptospira spp . were isolated ( only from those herds with no recent vaccination history ) were tested by serial two-fold dilutions [21] starting from 1:100 . The local strains used for the latter MATs , were chosen to represent each of the different serogroups identified in this work ( IP1506001 , IP1605021 , IP1611024 , IP1611025 , IP1512017 , IP1703027 , IP1711049 and IP1512011 , according to the numbering scheme defined in Table 1 ) . Random samples of urine ( vesical puncture ) and kidneys were obtained at 22 slaughterhouses that received animals from geographic regions throughout the country . No indications of reproductive failure nor of any other health problems were recorded for slaughtered animals . Due to pipeline logistics at slaughterhouses , kidneys and urine samples did not correspond to the same animal such that individual samples were treated as independent . Urine samples were immediately inoculated in EMJH/FU , according to the same protocol as with field samples . Kidneys were transported in 4°C-refrigerated boxes to the laboratory and processed on arrival , 2–6 hours after sampling . A fragment of approximately 10 g of tissue was placed in a funnel , surface-sterilized by dousing with alcohol and flamed with a Bunsen burner . The tissue was then placed in a sterile stomacher bag and 10 mL of phosphate-buffered saline ( PBS ) were aseptically added . After breaking the tissue down to a pulp in the stomacher machine , the obtained suspension was allowed to settle for 15 minutes , 250 μL of supernatant were drawn and inoculated in 5 mL EMJH/FU ( called tube A ) . From tube A , 500 μL were transferred to a second 5 mL EMJH/FU tube ( tube B ) , thus obtaining also a 10-fold diluted culture . Finally , a third culture was also prepared from each sample by directly inoculating 5 mL Fletcher medium with a small cylinder of kidney tissue obtained with a Pasteur pipette . All cultures were incubated at 29°C . In order to define a precise protocol for culture inoculation in the field after urine collection , decreasing numbers of L . borgpetersenii serovar Hardjo strain Sponselee cells , ranging from 107 to 1 bacterium , were incubated in 1 mL filter-sterilized bovine urine . After variable times , 100 μL urine were inoculated in 5 mL EMJH for culture , and bacterial growth weekly monitored under a dark-field microscope . For isolations , Leptospira cultures were incubated at 29°C and observed under dark-field microscopy weekly for up to 6 months [21] . In case of contamination by other microorganisms , the cultures were filtrated through a 0 . 22 μm sterile syringe filter ( Millipore Corporation , MA , USA ) and sub-cultured in fresh EMJH media . As soon as spirochete-like bacteria grew in specific cultures , the presence of pathogenic Leptospira species was assessed by PCR amplification of the lipL32 gene ( see below ) . Once no contamination observed , PCR-confirmed cultures were sub-cultured in EMJH media without 5-FU until exponential growth phase . Leptospira spp . isolates were then conserved at ≥108 cells/mL in EMJH with 2 . 5% of dimethyl sulfoxide ( Sigma ) and flash-cooled in liquid nitrogen . The lipL32 gene was chosen as a marker of pathogenic Leptospira species [22–24] . PCR amplification of lipL32 was performed using purified DNA from 10 mL of bovine urine samples . The urine was centrifuged at 10 , 000 g for 15 min , the pellet rinsed once with PBS pH 7 . 4 , and total DNA was extracted with the PureLink Genomic DNA MiniKit ( Invitrogen ) . lipL32 PCR-amplification was achieved using oligonucleotide primers lipL32F ( 5´-ATCTCCGTTGCACTCTTTGC-3´ ) and lipL32R ( 5´-ACCATCATCATCATCGTCCA-3´ ) [25] . The PCR was performed in 50 μL 10 mM Tris . HCl pH 8 . 4 , 50 mM KCl , 1 . 5 mM MgCl2 , 200 μM dNTPs , 0 . 25 mg/mL bovine serum albumin ( Sigma ) , 2 μM oligonucleotide primers , 1 U Taq DNA polymerase ( Invitrogen ) and 5 μL template DNA . PCR cycling comprised 1 denaturation step ( 5 min at 95°C ) , 35 amplification cycles ( each cycle 30 s at 94°C , 30 s at 58°C and 1 min at 72°C ) and a final extension step ( 7 min at 72°C ) . PCR products were analyzed by agarose gel electrophoresis and ethidium bromide staining , seeking for the expected 474 bp amplicon . Bovine serum albumin ( Sigma ) was added in the PCR reaction mix , 0 . 25 mg/mL , greatly reducing sporadic inhibitory effects of certain urine samples on the amplification reaction . An internal control was always included to quantify this potential inhibition issue , by spiking analyzed samples with 40 ng of L . borgpetersenii DNA . Positive amplifications products were randomly chosen in a few field samples , and sequenced confirming specific amplification of Leptospira DNA . This lipL32 PCR procedure was also performed to rank bacterial cultures ( prioritizing more careful follow-ups ) , after DNA purification from 1 mL of EMJH cultures where suspect spirochetes had been observed by dark-field microscopy . DNA from Leptospira spp . bovine and human isolates were purified from 1 mL of EMJH culture using the PureLink Genomic DNA MiniKit ( Invitrogen ) . Primers LeptoA ( 5´- GGCGGCGCGTCTTAAACATG-3´ ) and LeptoB ( 5´- TTCCCCCCATTGAGCAAGATT-3´ ) were used to amplify the 5’-terminal 331 bp fragment of the 16S rRNA gene ( rrs ) as previously described [26] . The resulting amplicons were sequenced in both senses using internal primers LeptoC ( Forward ) ( 5´-CAAGTCAAGCGGAGTAGCA-3´ ) and Rs4 ( Reverse ) ( 5´-TCTTAACTGCTGCCTCCCGT-3´ ) . Sequence quality was verified with the Chromas software , and consensus sequences were defined using BioEdit . All rrs sequences were deposited in GenBank ( S2 Table ) . Consensus sequences were then compared with available sequences in GenBank using BLAST . Multilocus variable-number tandem repeat ( VNTR ) analyses were performed according to published methods [27] using five discriminatory markers for VNTR loci 4 , 7 , 10 , Lb4 and Lb5 . Purified DNA from each isolate was used to amplify the VNTR4 , VNTR7 and VNTR10 loci in L . interrogans , and the VNTR10 , VNTRLb4 and VNTRLb5 loci in L . borgpetersenii . The GelAnalyzer 2010a software ( http://www . gelanalyzer . com ) was used to analyze the ethidium bromide-stained agarose electrophoresis gels , in which PCR products were resolved in parallel to 100-bp DNA ladder ( Thermo Scientific ) as molecular weight marker . The number of repeats for each VNTR locus was determined as: number of repeats = [PCR product size ( bp ) —flanking region ( bp ) ] / repeat unit length ( bp ) . DNA from Leptospira spp . bovine and human isolates were purified from 1 mL of EMJH culture using the PureLink Genomic DNA MiniKit ( Invitrogen ) . The secY gene was partially amplified by PCR with primers SecYF ( 5´-ATGCCGATCATTTTTGCTTC-3´ ) and SecYR ( 5´-CCGTCCCTTAATTTTAGACTTCTTC-3´ ) as described [28] . The resulting 549 bp amplicon was sequenced in both senses . Sequence quality was verified with the Chromas software , and consensus sequences were defined using BioEdit . All secY sequences were deposited in GenBank ( S2 Table ) and compared to those available in PubMed , MLST ( https://pubmlst . org/leptospira ) and PATRIC ( https://www . patricbrc . org ) [29] databases . The phylogenetic analyses based on secY sequences were performed with MEGA 6 . 0 software ( www . megasoftware . net ) using the neighbor-joining method . The evolutionary distances were computed using the Tamura-Nei method and are in the units of the number of base substitutions per site . The reliability of branches was validated by generating 1000 bootstrap replicates . Based on the analysis of sequence similarities , secY genotypes were assigned . To determine the serogroup of isolated Leptospira strains , MAT was used with a panel of serogroup-specific rabbit antisera , spanning 24 Leptospira serogroups ( KIT Royal Tropical Institute , S3 Table ) , performed in microtiter plates , mixing equal volumes of viable leptospires with serial 2-fold dilutions of each rabbit antiserum . After 2 h incubation at 37°C , agglutination of bacteria was observed under dark-field microscopy . The strain’s serogroup was assigned according to the antiserum that gave highest agglutination titer . Based on the combination of results from both serogroup determination and molecular typing ( rrs gene partial sequencing and VNTR analysis ) , a presumptive serovar was assigned to all isolates belonging to L . interrogans , and L . borgpetersenii species , as previously described [27] .
Initial attempts to isolate Leptospira strains from bovine urine samples were unsuccessful . The initial protocol was based on collecting the urine from all sampled animals , and then inoculating them into the tubes with culture media . We asked whether bacterial cell viability could be compromised due to exposure to urine over time . As a first approach to address this issue , the particularly fastidious L . borgpetersenii serovar Hardjo was chosen [30] to perform in vitro tests of viability kinetics in bovine urine . Indeed , a critical maximum time of exposure was defined at less than 2 h ( S4 Table ) , above which subsequent isolation success rates decreased significantly . Although it cannot be ruled out that other serovars might behave differently , based on these observations , all urine samples were inoculated in the field within 2 h of collection , resulting in successful isolations . A second logistic challenge for isolation efforts from urine samples , was the high number of cultures subject to follow-up under dark-field microscopy . PCR amplification of Leptospira lipL32 gene was optimized on bovine urine , eventually resulting in a robust method to prioritize cultures ( Fig 1 ) , identifying those samples that proved positive for pathogenic Leptospira spp . A strong inhibitory effect on lipL32 PCR amplification was frequently observed , dependent on the urine sample ( Fig 1A ) . This sample-dependent inhibition issue was solved by washing the bacterial pellet obtained after urine centrifugation with PBS pH 7 . 4 ( Fig 1B ) , and then adding bovine serum albumin in the PCR mix ( Fig 1C ) . The sensitivity of this PCR method was ≥100 Leptospira cells , estimated by spiking known amounts of bacteria to sterile urine samples . Specificity was assessed confirming a positive reaction with relevant serovars of pathogenic Leptospira species ( L . interrogans , L . noguchii , L . weilii , L . borgpetersenii and L . santarosai ) , while undetectable with non-pathogenic Leptospira ( L . biflexa ) nor with unrelated species ( Escherichia coli , Pseudomonas aeruginosa , Salmonella sp . , Staphylococcus aureus and Enterococcus sp . ) . Using this screening strategy , the presence of pathogenic Leptospira spp . DNA was confirmed in 193 urine samples , indicating that at least ~20% ( 193/963 ) of all studied animals were excreting pathogenic Leptospira in their urine ( Fig 1D and 1E ) . False positive results from collected samples are highly unlikely , considering that lipL32 is only present in the genomes of pathogenic Leptospira species [22] , that no detectable amplification was observed with non-specific bacteria , and that randomly chosen amplicons from bovine urine samples confirmed 100% sequence identity with Leptospira lipL32 . An environmental source of pathogenic bacteria during urine sample collection is highly unlikely as well , considering the sample collection procedure and the number of bacteria needed to attain the PCR sensitivity threshold . Following up with this approach at the herd level , 77% of the farms ( 37/48 ) that were studied , harbored ≥1 animal ( s ) excreting pathogenic Leptospira . The sampling strategies , as detailed in Methods , were chosen to maximize the odds of isolating local strains of pathogenic Leptospira spp . from infected cattle . A two-pronged approach was followed: i- active and directed sampling in the field , at farms with suspicion of Leptospira infection; and , ii- random postmortem sampling of animals at slaughterhouses . Field sampling . A total of 48 farms representing both beef and dairy cattle herds were visited from January 2015 to September 2017 . They were distributed in 12 out of the 19 geographic departments in which the Uruguayan territory is divided . A total of 963 urine samples were collected and subjected to bacterial culture attempts and lipL32 PCR screening . On average , Leptospira growth was detected by dark-field microscopy on cultures after 28 days ( range 7–56 days ) . Cultures that showed suspect bacteria , were subjected to lipL32 PCR amplification , initially identifying 42 positive cultures from independent urine samples . Considering that 193 urine samples were positive by PCR screening , an estimated recovery rate of 21 . 7% ( 42/193 ) positive cultures from urine samples was achieved . From the original 42 positives , we ultimately obtained 32 pure cultures of Leptospira spp . ( Table 1 ) from field animals , representing a 76 . 2% rate of success in isolating these bacteria from positive cultures , and a 3 . 3% global isolation success rate when considering the whole set of input urine samples ( 32/963 ) . This latter figure should not be taken as a prevalence estimation of animals shedding leptospires ( PCR-positive urine samples is a better indicator ) , since challenges in cultivating these fastidious bacteria are included in the global isolation rate . Sampling at abattoirs . A total of 288 kidneys and 289 urine samples ( representing 577 individual animals ) were collected at slaughterhouses . According to the origin of slaughtered animals , all 19 departments of the country were included . 18 positive cultures of Leptospira were identified by dark-field microscopy and PCR amplification ( rrs and lipL32 genes ) , from which 8 isolates were eventually obtained , 3 from urine and 5 from kidney samples ( Table 1 ) . Overall , a total of 40 strains of pathogenic Leptospira were isolated from cattle along the course of this study , and characterized by combining serologic and molecular methods ( Table 1 ) . Recalling that initially 60 cultures had proved positive for Leptospira growth , the figures reveal that 20 could not be isolated ( 10 from field animals and 10 from slaughterhouses ) , due to overgrowth by contaminant species . Among the 40 characterized strains , 32 were isolated from live animals in the field ( 30 from cows or heifers , and 2 from calves with signs of acute leptospirosis ) , and 8 from adult carcasses at abattoirs ( Table 1 ) . The Leptospira species were determined by PCR amplification and partial sequencing of the 16S rRNA gene ( rrs ) . Three different pathogenic species were thus identified ( Table 1 ) : L . interrogans ( n = 21 ) , L . borgpetersenii ( n = 10 ) and L . noguchii ( n = 9 ) . Serogrouping of isolates was performed by MAT with a collection of 24 rabbit antisera against reference pathogenic serovars . All but one of the L . interrogans isolates corresponded to serogroup Pomona , the different one belonging to serogroup Canicola . The L . borgpetersenii strains all classed within serogroup Sejroe . In contrast , the L . noguchii isolates showed a broader variety of serogroups , including Pyrogenes ( n = 1 ) , Australis ( n = 1 ) , Autumnalis ( n = 4 ) , and 3 L . noguchii isolates that did not agglutinate with any of the reference antisera used . Taking into account the identification of species and serogroup , together with the VNTR profiles ( S1 Fig ) , it was possible to assign 20 L . interrogans strains to serovar Kennewicki , 1 L . interrogans to serovar Canicola , and the 10 L . borgpetersenii isolates to serovar Hardjo ( Table 1 ) . The serovars of the L . noguchii isolates could not be predicted , given that current VNTR profiling tables do not allow yet for serovar assignment of this species . Twelve L . interrogans , five L . borgpetersenii and one L . noguchii strains , were isolated from farms with no history of vaccination ( Table 2 ) . Among such animals , MAT agglutination titers against reference strains were positive in ten cases ( considering that national guidelines currently define less than 200 as non-reactive ) . However , when local isolates were added to the panel of MAT antigens for comparative purposes , 16 out of the 18 sera from non-vaccinated herds showed anti-Leptospira titers against the homologous autochthonous strain that was isolated ( S5 Table ) . These results suggest that including local isolates of Leptospira spp . in the panel of antigens used for MAT may improve the sensitivity of the method . All the isolates recovered from herds with no history of vaccination , belonged to the homologous serogroup as shown by the seroreactivity data ( S5 Table ) . Genetic analysis of the 501bp secY allele was performed on the 40 typed isolates described in this work . Comparison to other L . interrogans ( serovars Pomona and Canicola ) , L . borgpetersenii ( serovar Hardjo ) and L . noguchii sequences , obtained from other geographical regions and available in public databases , allowed to build a picture of related groups . Also included in this analysis were secY sequences obtained from 4 Leptospira strains recently isolated from human infections in Uruguay by one of the groups of our consortium [12 , 13] . Such human isolates correspond to L . interrogans , L . kirschneri and L . borgpetersenii species . The dendrogram of partial secY sequence clustering , uncovered four phylogenetic clades that corresponded to genomospecies identified by partial rrs gene sequencing: L . interrogans , L . borgpetersenii , L . kirschneri and L . noguchii ( Fig 2 ) . The same 4-clades scenario emerged by calculating phylogeny with rrs gene sequences ( S2 Fig ) . Only one homogeneous cluster was observed for the L . interrogans secY sequences , indicating that bovine isolates from Uruguay belonging to this species have close homology with isolates from South America ( mainly from Brazil and Argentina ) [31] . It is worth noting that two L . interrogans strains that had recently been isolated from human leptospirosis cases in Uruguay affecting rural workers [12 , 13] clustered in the same secY clade together with the L . interrogans bovine isolates that we now describe . Concerning the L . borgpetersenii bovine strains , they also clustered with L . borgpetersenii serogroup Sejroe isolates from human and bovine sources in South America , Australia and USA; however , they showed no homology with the uruguayan L . borgpetersenii human isolate , which belongs to serogroup Ballum ( F Schelotto , personal communication ) . Contrasting with such homogeneous clustering of L . interrogans and L . borgpetersenii strains , secY sequence analysis of the L . noguchii isolates revealed a substantially broader diversity , with isolates grouped in two distinct clusters . The first included two isolates , from Panama and Peru . The second cluster , with slight heterogeneity within , comprised all the L . noguchii isolates we are now reporting from Uruguay , as well as a number of other strains obtained from both human and animal origin in several countries of the American continent ( Brazil , Nicaragua , Peru , Trinidad & Tobago , USA ) . Worth highlighting , the secY sequences of our bovine isolates IP1611024 , IP1708035 and IP1709037 , are identical to some of the L . noguchii strains recently reported in Brazil , isolated from cattle [32] and humans [33] .
We are now reporting the isolation and typing of 40 native strains of pathogenic Leptospira spp . from infected cattle in Uruguay . This is the first systematic effort to isolate and type autochthonous Leptospira strains from cattle in this country , where bovine leptospirosis is a major concern as a cause of abortions and zoonotic dissemination . L . interrogans serovar Kennewicki ( serogroup Pomona ) , our most frequent bovine isolate , has actually been also recovered from human patients with leptospirosis in Uruguay [12] . To further confirm this potential link between cattle and humans , we have now shown that the secY genotypes of both L . interrogans Kennewicki and Canicola serovars , are identical in Leptospira strains isolated from patients ( rural workers ) and from cattle ( Fig 2 ) , strongly suggesting that the latter disseminate the infection to exposed humans . The successful culture of leptospires from bovine samples has likely been boosted by optimizing field sampling protocols , especially after quantifying time-dependent Leptospira viability in bovine urine . PCR screening has also been instrumental in prioritizing cultures , the number of which increased dramatically due to the systematic use of three culture dilutions per animal , themselves important to improve purity in some cases . A total of 963 urine samples that were processed , eventually produced 42 positive cultures . Among these 42 , 9 had produced negative PCR results at the time of urine sample screening . Two different scenarios explain such discrepancies: 8 of the 9 negative results , appeared early during our studies , and eventually proved to be the consequence of urine inhibition , triggering the optimization of our protocols ( see Methods and Fig 1 ) . Only in one sample we can strongly suggest that it is the PCR method’s sensitivity that explains the divergent result . In sum , lipL32 PCR screening is an instrumental strategy to prioritize culture follow-ups , albeit not leading to discarding ongoing cultures . We are now optimizing a more sensitive real-time PCR approach , anticipated to also being more robust for screening purposes . Regarding important , and frequently neglected factors that can lead to success or failure in nation-wide efforts based on field sampling , it is worth highlighting the voluntary participation of farmers and private veterinarians . Early arrangements ensuring for such implications were critical logistic factors for a swift sample collection strategy and for gathering useful information about herds and individual animals . Serial dilutions of the biologic samples on separate culture tubes were successfully used as a means to tackle contamination issues . Most of the positive cultures were successfully purified using the first two dilutions A and B , roughly 50% success from each one . Further diluting the inocula ( tube C ) allowed the recovery/purification of only 4 additional isolates . Overall , EMJH media outperformed Fletcher in our hands , with only two isolates grown from the latter that were also obtained with EMJH . Combined serologic and molecular approaches revealed the presence of three different Leptospira species . Besides the anticipated L . interrogans and L . borgpetersenii species , known to be major infectious agents in cattle [2 , 34] , an important number of isolates corresponded to L . noguchii , both from field samples as well as from abattoirs . L . noguchii has been isolated from cattle in South America [14 , 32 , 33] , but had never been reported in Uruguay , and extremely limited information is currently available about its epidemiologic importance . Are L . noguchii strains a relevant cause of acute disease or reproductive problems in cattle ? One of the two strains that we have isolated from calves with signs of acute leptospirosis , was actually identified as L . noguchii , but more information is urgently needed in order to establish the contribution of this unanticipated species in the burden of veterinarian and human leptospirosis in South America . The other strain infecting a suspected acute case was confirmed as L . interrogans serogroup Canicola serovar Canicola , a highly virulent variant often isolated from dogs . Serovar Canicola is however not considered to be adapted to cattle , although it has been reported to infect bovine hosts incidentally , including recent reports in Brazil [35] . It is interesting to note that the isolates belonging to L . interrogans and L . borgpetersenii , displayed limited variation . The latter revealed a single VNTR profile ( consistent with a single serovar , Hardjo , within the Sejroe serogroup ) , also coherent with a unique secY genotype ( B ) . As for the L . interrogans strains , once again quite homogeneous features were found for all isolates , with 20 out of 21 compatible with serovar Kennewicki ( serogroup Pomona ) , and displaying a single secY genotype ( A ) . Only one L . interrogans was different , VNTR clearly matching the one expected for serovar Canicola ( in line with Canicola serogroup sero-agglutination ) , yet sharing the same secY genotype A as the Pomona Kennewicki strains . In stark contrast , the 9 L . noguchii isolates uncovered an unexpected variety of serogroups . We have not yet assigned serovar types to these L . noguchii strains , given that the VNTR multilocus analysis scheme has not been validated for this Leptospira species on the basis of cross-agglutinin absorption tests ( CAAT ) with serovar-specific antisera . We are currently sequencing the whole genomes for all isolates and actively pursuing direct serovar identification by CAAT for the L . noguchii strains . However , it can immediately be recognized that all nine L . noguchii strains likely correspond to 9 distinct serovars , combining the information of serogrouping and secY genotypes . Three of them did not agglutinate with any of the reference antisera tested , which span 24 serogroups that cover major pathogenic Leptospira [36] . The other six corresponded to serogroups Pyrogenes , Australis and Autumnalis , the latter including four different isolates , all of which differed in secY genotypes ( D , F , G and H ) . The three L . noguchii isolates that did not react with serogroup-specific reference antisera , revealed as yet three additional secY genotypes ( C , F and I ) , hence likely pertaining to three disparate serovars as well . Serogroup Pomona is one of the most common variants isolated from animals worldwide [37] . This serogroup displays important genetic diversity , as revealed by restriction endonuclease analysis ( REA ) [38] , even within serovars . However , the REA-based genetic profiles of Pomona serovar Kennewicki , show high stability among isolates from a single outbreak [39] and , interestingly , a strong correlation between specific hosts and corresponding REA profile . Those results are consistent with our study: analyzed by secY allele genotyping , a high homogeneity was observed in all Pomona Kennewicki isolates from cattle , despite the broad geographic distribution of the isolates , including those obtained in the field and from slaughterhouses . Serovar Kennewicki is recognized as an animal pathogen [40] , apparently adapted to pigs as maintenance host . Even though in Uruguay domestic pigs are not usually raised together with cattle , a forbidden practice in dairy farms , we should not rule out wild boars or other wild animals as potential hosts for this serovar , nor an endemic cycle in domestic cattle [2] . More information is needed to evaluate the prevalence of the serovars we have isolated in the whole country , and neighboring ones in South America . Furthermore , the virulence of these strains in relevant leptospirosis models will be important evidence that must be investigated , regarding pathogenicity ( e . g . mortality in the hamster model ) and renal colonization ( e . g . in the bovine host ) . It is worth highlighting that we have isolated similar Leptospira species and sero-variants from chronic and acute cases in the field , as well as from dead animals from abattoirs , suggesting they represent a genuine sampling of the true population distribution of infectious Leptospira spp . in cattle . To be conclusive , an epidemiologic study with national geographic coverage is a necessary next step , as well as an in-depth molecular analysis of the Leptospira DNA recovered from PCR-positive urine samples that did not result in positive cultures . At the individual animal level , and only considering herds with no recent history of vaccination ( 18 cases ) , the MAT technique correctly predicted the serogroup ( Pomona ) of 9 out of the 12 animals where L . interrogans strains were isolated ( Table 2 ) . In contrast , none of the 5 cases with L . borgpetersenii infections , nor the one from which a L . noguchii strain was isolated , presented detectable antibody titers using the diagnostic panel of reference available at the national diagnostics laboratory ( DILAVE , MGAP ) . This is likely due to low sensitivity of the MAT , a known issue when it comes to host-acclimated serovars such as Hardjo in cattle [41] . The MAT did not identify any of the L . noguchii isolates , as these were not included within the reference antigen panel in the national diagnostics laboratories ( DILAVE , Ministry of Livestock , Agriculture and Fishery ) . This finding is important , as L . noguchii is a recognized pathogenic species for animals and humans [33 , 42] . However , when autochthonous L . interrogans serogroup Pomona , L . borgpetersenii serogroup Sejroe and representative serogroups of the L . noguchii strains were included for anti-Leptospira antibodies titration by MAT , we did observe an increase of sensitivity: analyzing those herds with no history of recent vaccination , all the animals from which L . borgpetersenii strains were isolated showed reactivity against the local isolate , as it was also the case for an animal from which L . noguchii serogroup Pyrogenes was isolated ( S5 Table ) . As a consequence of this study , the inclusion of these native strains among the antigens for MAT diagnostics and seroprevalence epidemiologic studies , must be an immediate action . Such policies will be important to increase MAT-based diagnostics sensitivity and accuracy [43] , and to improve the estimations of prevalence and incidence of bovine leptospirosis infection in the country . Furthermore , isolation and characterization of circulating Leptospira strains , are ongoing activities as a result of our multicentric consortium efforts . We anticipate that new variants and/or species may be discovered , achieving a more complete understanding of current diversity of Leptospira in South America . A recent study of bovine Leptospira spp . isolates obtained from animals in slaughterhouses in Brazil , shows an important diversity in terms of species and serovars [14] . Libonati et al . report two L . interrogans strains belonging to serogroup Sejroe , and four different serogroups assigned to each of the other two L . santarosai and L . noguchii species identified . Our results now demonstrate a similar diversity of bovine isolates in terms of species and serovars . We have isolated L . borgpetersenii serogroup Sejroe strains , although so far , no L . santarosai isolates nor L . interrogans serogroup Sejroe have been recovered . Instead , we did isolate several strains of L . interrogans serogroup Pomona ( presumptive serovar Kennewicki ) and one Canicola ( presumptive serovar Canicola ) . With regards to L . noguchii , the broad range of serogroups that we have detected seems to be a shared scenario with the situation in Brazil , with Autumnalis , Australis and Pyrogenes identified in both countries ( additionally , serogroup Panama has also been identified in Brazil [32] ) . However , three L . noguchii isolates could not be classified in any serogroup , failing to agglutinate with the broad panel of reference antisera that was used . These results were confirmed in three different laboratories within our consortium , including the Paris center ( WHO Collaborating Center and French reference laboratory for leptospirosis ) . In any case , these novel serogroups are distinct from the L . noguchii strains so far isolated in Brazil . It does not escape our attention that most of the serovars that we are now reporting , are not included in the vaccines currently available to the farmers . Except for L . borgpetersenii serovar Hardjo and L . interrogans serovar Canicola , to the best of our knowledge neither serovar Kennewicki ( L . interrogans ) nor any of the L . noguchii serogroups/serovars that we identified , are being included in bacterin formulations that different companies produce and commercialize as bovine vaccines in South America ( Table 2 ) . Bacterins confer little or no cross-protection between serovars , hence the serovars that actually circulate in each region should be included to aim for efficacious vaccines [34] . Indeed , in our study we have obtained several isolates from one herd before and after vaccination . We will now perform closer analyses of naturally exposed herds , following up the effects of vaccination at the individual level . That current vaccines might have shifted the serovar profile of currently circulating Leptospira strains in Uruguay , is a plausible scenario . Proper bacterin vaccination should result in herd protection . We should have thus observed lower isolation rates from vaccinated herds , but we have not . Urine shedding of leptospires can be effectively controlled or significantly reduced in livestock , by using the correct bacterin formulations , according to recent studies with naturally exposed sheep herds [44] or with experimental vaccination/challenge approaches in cattle [45] . Significant reduction in bovine renal colonization and bacterial urinary shedding are achieved by vaccination with bacterins that include the infectious serovars [46] , ultimately controlling endemic cycles of infection . Moreover , a systematic vaccination and surveillance program for pig and cattle leptospirosis in New Zealand , demonstrated a correlative dramatic decrease in the incidence , not only of the animal disease , but also of human leptospirosis [47] . Nevertheless , further research is needed to obtain long-lasting vaccination effects and complete protection against bacterial infection . Likely a protective cellular immune response is needed in the cattle model [46 , 48 , 49] to generate a highly efficacious vaccine against leptospirosis , and not only the humoral response triggered by killed-cell bacterins . The latter are also known to trigger a biased response towards the serovar-specific bacterial lipopolysaccharide antigen , T-independent with lack of memory response [50] . A more thorough understanding of leptospirosis epidemiology , including maintenance hosts and impact in livestock production , is essential to understand and design effective control strategies for this zoonosis . Efficacy studies with currently available vaccines for bovine leptospirosis in our region are also urgently needed . The assembly of this multicentric consortium ( S1 Text ) gathering the complementary expertise of several key research and governmental institutions in Uruguay , has made possible to obtain the first repository of Leptospira isolates in the public domain , most of them already typed in terms of species , serogroup and serovar . This is a major milestone in the way of controlling leptospirosis in Uruguay , with the associated far-reaching aim of reducing the risk for the human population .
|
Several species of the genus Leptospira cause leptospirosis , a disease that is transmitted from animals to humans ( zoonosis ) . Leptospirosis is the most extended zoonosis worldwide , with over a million human cases each year . Leptospira spp . infect a broad range of wildlife and domestic animals , including cattle . In several South American countries beef and dairy exports rank among the most important national income sources , explaining why in Uruguay cattle outnumber human population by a factor of 4 . Yet , we did not know which Leptospira species and serovariants ( serovars ) circulate among Uruguayan cattle . Current serologic diagnostic methods and whole killed-cell vaccination approaches , critically depend on using the proper serovars , which are hugely variable in Leptospira spp . from different regions of the world . Through a multidisciplinary consortium effort , we now report the isolation and typing of 40 strains of pathogenic Leptospira spp . An unexpectedly large variation in terms of species and serovars was found . These data are extremely important: 1- to improve diagnostics by updating the available reference antigen panels; 2- to evaluate the efficacy of novel vaccines; and , 3- to implement efficacious bovine vaccination as a means of reducing the incidence of bovine and human leptospirosis .
|
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"Abstract",
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] |
2018
|
Isolation of pathogenic Leptospira strains from naturally infected cattle in Uruguay reveals high serovar diversity, and uncovers a relevant risk for human leptospirosis
|
Theory predicts that selection for pathogen virulence and horizontal transmission is highest at the onset of an epidemic but decreases thereafter , as the epidemic depletes the pool of susceptible hosts . We tested this prediction by tracking the competition between the latent bacteriophage λ and its virulent mutant λcI857 throughout experimental epidemics taking place in continuous cultures of Escherichia coli . As expected , the virulent λcI857 is strongly favored in the early stage of the epidemic , but loses competition with the latent virus as prevalence increases . We show that the observed transient selection for virulence and horizontal transmission can be fully explained within the framework of evolutionary epidemiology theory . This experimental validation of our predictions is a key step towards a predictive theory for the evolution of virulence in emerging infectious diseases .
Understanding and predicting the conditions under which pathogens evolve towards higher levels of virulence ( pathogen induced host mortality ) is a major challenge in the control of infectious diseases [1] , [2] . Nevertheless , the theoretical understanding of virulence evolution is often based on several major simplifying assumptions . In particular , the classical adaptive dynamics framework assumes that mutations are rare and thus that evolution occurs on a much slower time scale than epidemiological dynamics [2] . In other words , adaptive dynamics theory relies on the assumption that there is very little amount of genetic variation in the pathogen population and that a single pathogen strain reaches an equilibrium before a new strain arises by mutation . However , ecological and evolutionary time scales may overlap when the amount of genetic variation is high [3]–[5] . This is the case for many pathogens , and in particular for viruses with large mutation rates . The recurrent introduction of new mutants violates a major assumption of adaptive dynamics since many different strains may compete with each other before the system reaches a new endemic equilibrium [6]–[10] . Previous theoretical analyses suggest that the outcome of this competition changes strikingly throughout an epidemic; even though selection can act against virulent mutants at the endemic equilibrium , there is a transitory phase during the early stage of the epidemic where the abundance of susceptible hosts can favor the more transmissible and aggressive strains [11]–[18] . Studying selection on virulence in the field is notoriously difficult because the characterization of the pathogen phenotypes can be obscured by host heterogeneity and healthcare measures . The unambiguous demonstration of the evolution of virulence evolution during an epidemic requires an experimental approach . Two different types of experimental setups can be used [19] . First , in a top-down approach , the evolution of the pathogen population is monitored in different environments ( e . g . before and after an epidemic ) . In this case , making quantitative predictions on the epidemiology and evolution of the pathogen remains out of reach because evolutionary trajectories rely on random mutations occurring during the experiment . In contrast , the bottom-up approach attempts to measure and/or manipulate the initial amount of genetic variation in the pathogen population and try to predict the evolution from this standing genetic variation . Although many stochastic factors like new mutations may alter the quality of the predictions in the long term , this approach may provide good quantitative predictions in the short term . For this reason , we follow the bottom-up approach to analyze the interplay between the epidemiology and the evolution of the bacteriophage λ . To study the dynamics of selection on virulence we monitor the competition of the bacteriophage λ and its virulent mutant λcI857 throughout the development of an epidemic in continuous cultures of E . coli . Bacteriophage λ is a typical temperate virus which integrates into the host genome and transmits vertically to daughter cells at cell division . Integration of phage λ into the genome protects the host cell against superinfection of other λ phage particles and this way provides lifelong immunity to superinfection by other λ phage particles [20] . Nevertheless stochastic reactivation of the integrated phage results in lysis and destruction of the host cell , causing pathogen induced host mortality . Lysis of its host prevents vertical transmission but allows the phage to be transmitted horizontally to uninfected susceptible cells . Whereas the non-virulent λ wildtype transmits mostly vertically by dormant integration into the host genome , the virulent mutant λcI857 transmits mostly horizontally by host lysis ( see Figure 1 ) . This difference in virulence and transmission mode is the result of a point mutation in the λ virulence repressor protein cI which actively controls the decision to ‘kill or not to kill’ the host cell [21]–[23] . This active control of the fate of the infected cell has been shown to respond rapidly to different selection regimes [24] . Studying the competition between such cI variants is particularly relevant to study phage evolution during and epidemic . In order to predict the competition between the temperate λ and the virulent λcI857 we first measured the effect of the cI857 mutation on several aspects of the viral life-cycle . In particular we focused on the effects of the cI857 mutation on the life-history traits known to be under the direct control of protein cI . We thus measured the ability to integrate into the genome of its host after infection , and the spontaneous lysis rate of the lysogenic bacteria for both the λ wildtype and the mutant λcI857 ( Figure S3 ) . We used these life-history estimates and other estimates from the literature to parameterize an evolutionary epidemiology model which generated three clear-cut predictions . Our evolutionary experiments confirmed all three predictions and thus demonstrate the predictive power of evolutionary epidemiology theory .
We modeled the competition of the temperate bacteriophage λ with its virulent mutant λcI857 throughout the course of an epidemic in chemostat cultures of its bacterial host E . coli . To understand and predict the competition dynamics of these two viruses throughout an epidemic we first developed a mathematical model . The epidemiology of phage λ can be described by the following set of ordinary differential equations for the densities of susceptible hosts , , infected hosts , , and free viral particles , : ( 1 ) where susceptible hosts and infected hosts grow at rate and , respectively , to a carrying capacity and die at a background mortality rate . Infected hosts spontaneously switch to lysis at rate and produce free viral particles . Viral particles adsorb to bacterial cells at rate , and inject their genome with probability . Injected viral genomes either replicate and destroy the host cell with probability to release viral particles , or integrate into the host genome with probability . Integration of the virus into the genome of the host cell excludes superinfection by a second phage particle of the same kind [20] . Open and closed subscripts indicate averaged trait values taken over the provirus and the free virus stage , respectively ( see section S1 . 2 in Text S1 ) . To capture the evolution of viral traits we track the frequency of a strain among all genome integrated provirus , and among free viral particles as follows ( see section S1 . 2 in Text S1 ) : ( 2 . 1 ) ( 2 . 2 ) The above two equations readily show the different forces that affect the change in frequency of the virulent type in these two stages of the virus life cycle . First , in the provirus stage , the frequency of a virulent mutant decreases because of its increased lysis rate ( first term in 2 . 1 ) and its lower rate of genome integration ( second term in 2 . 1 ) . But this frequency may increase by gene flow from the free virus stage ( the last term in 2 . 1 ) , because the frequency of the virulent mutant tends to be higher in the free virus stage ( see prediction ii below ) . Second , in the free virus stage , the frequency of a virulent mutant increases because it has a lower rate of genome integration and a higher rate of lysis ( first two terms in 2 . 2 ) . Yet this frequency may decrease by gene flow from the provirus stage ( last term in 2 . 2 ) , because the frequency of the virulent mutant tends to be lower in the provirus stage ( see prediction ii below ) . Epidemiology , evolution and their interactions are fully integrated in the above five equations . Three general predictions emerge from the analysis of this model ( see Figure 2 ) : ( i ) The virulent mutant initially wins the competition with the wildtype when susceptible hosts are abundant , but the competitive outcome is reversed as soon as the epidemic reaches high prevalence; ( ii ) The virulent mutant is , at all times , more frequent among free viruses than among proviruses; and ( iii ) Lower initial prevalences result in a higher increase in virulence during the epidemic . To test these three predictions , we infected E . coli chemostat cultures with a range of initial infection prevalences ( between 1% and 100% ) and monitored viral competition between λcI857 and λ ( in a 1∶1 starting ratio at the provirus stage ) during the spread of the epidemic . We introduced two fluorescent protein marker colors ( CFP and YFP ) into λcI857 and λ strains to measure their frequencies during competition . To experimentally control for a small marker color effect ( see Table S2 . 1 in Text S1 ) , we replicated the experiment switching marker colors between the two virus strains . We monitored strain frequencies in the provirus by flow cytometry , and in the free virus by marker specific qPCR ( see section S2 . 1 . 2 in Text S1 and Figure S4 ) . In a first experiment , we tracked the change in prevalence ( proportion of infected bacteria ) and strain frequencies ( in both the provirus and the free virus stages of the phage life cycle ) by sampling hourly in 8 chemostats ( 2 marker/virulence combinations , 2 replicates and 2 initial prevalences: 1% and 100% ) . We performed a second experiment to further investigate the impact of initial prevalence using 6 chemostats ( 2 marker/virulence combinations and 3 initial prevalences: 1% , 10% and 99%; see section S2 . 3 in Text S1 ) . Starting from an initial prevalence of 1% the epidemic spread rapidly until nearly all hosts were infected , roughly 10 h later ( Figure 3A ) . The virulent λcI857 rapidly outnumbered λ in both the provirus and the free virus compartments . Yet , despite this initial advantage in the first 7 h of the epidemic , the frequency of the virulent λcI857 started to decrease in both compartments thereafter ( Figure 3 and Figure 4 ) . This confirms our first theoretical prediction . Furthermore , the frequency of the virulent mutant λcI857 remained higher among free viruses than among proviruses during the entire course of the epidemics ( Figure 3 and Figure 4 ) . This confirms our second prediction . Moreover , as expected from our third prediction , at an initial prevalence of 100% the virulent mutant λcI857 lost the competition from the outset of the experiment ( Figures 3B , C ) . The third prediction got additional support from the second experiment where the value of the peak frequency of the virulent mutant decreased with higher initial prevalence ( Figure 4 and Figure S6 ) .
To demonstrate that epidemiology can affect selection on viral virulence and transmission mode we studied the competition between two viral strains during experimental epidemics in chemostats . The two main life-history traits that govern virulence and transmission in λ ( the ability to integrate into the genome of its host after infection , and the lysis rate of the lysogenic bacteria ) were measured for these two viral strains . We parameterized a model for the competition of several viral strains throughout an epidemic using estimations for the remaining parameter values from other published studies ( Table S1 in Text S1 ) . This model was used to generate three qualitative predictions on the epidemiology and the evolution of the bacteriophage λ . Our experimental results agree well with all three theoretical predictions . This demonstrates the predictive power of the bottom-up approach we used to model this system . This study confirms the importance of modeling both epidemiology and evolution to accurately predict the transient evolution of pathogens . In particular , the shift between positive and negative selection on the virulent mutant makes only sense because we took into account the feed-back of epidemiology on the evolution of the virus . Our theoretical predictions are based on the competition between two pathogen variants in a fully susceptible host population . In this way we focus on the short-term evolutionary dynamics taking place during an epidemic . As pointed out above , the accuracy of these predictions is expected to drop as other mutations in virus or host come into play . In particular , compensatory mutations that reduce phage virulence could alter the ultimate trajectory of λcI857 , as it would no longer pay the cost of virulence in the long run . In the present experiment , we did not find evidence of such compensation ( Figure S5 ) . Nevertheless , we can readily include compensation in our model to judge its effect on short and long-term dynamics . We found that if we allow for these compensatory mutations the above short term predictions still hold ( Figure S1 ) . Another evolutionary route the pathogen could take is to escape superinfection inhibition , which would allow it to gain access to hosts even when all the bacteria are infected [25] . However , in λ the rate of mutation towards such ultravirulent strains has been shown to be very small and is thus unlikely to affect the short-term evolutionary dynamics [26] . In the long term , however , the coevolution between superinfection inhibition and the resistance to superinfection inhibition may play a major role for the evolutionary maintenance of viral latency and the emergence of diversity in λ-like phages [27] . In addition , the E . coli host cell may also acquire resistance to λ by well known mechanisms [28]–[29] . We did find some evidence of host resistance evolution but only in the large volume chemostats ( 50 mL , second experiment ) and not before 40 h ( Figure S7 and Figure S8 ) , which indicates that the appearance of these mutations is limited by population size and by time . Again , including host resistance in our model confirms that the above three qualitative predictions hold in the short-term ( Figure S2 ) . Our model assumes that all the parameter values governing phage life cycle remain constant throughout the experiment . The lyzogenisation rate of phage λ , however , is known to vary with the multiplicity of infection ( MOI ) , which is the number of virus entering the bacteria . The higher the MOI , the higher the lysogenization rate [22] , [30] . For the sake of simplicity we do not consider this effect in our model but additional simulations indicate that it does not alter qualitatively our conclusions ( not shown ) because both the wild type and the cI857 mutant harbor this phenotypic plasticity [30] . Our model , however , may shed some light on the adaptive nature of the sensitivity of the rate of lysogenisation to the MOI . The MOI provides accurate information of the epidemiological state of the environment . When the MOI is low the number of susceptible hosts is likely to be high and it is a good strategy to lyse and to try infecting new hosts horizontally . In contrast , when the MOI becomes high , it is very unlikely that a free virus particle will encounter a susceptible host . In this case the phage would benefit more from investing into lyzogeny and vertical transmission [31]–[32] . In other words , the evolution of plasticity may be another evolutionary outcome resulting from the epidemiological feedback during an epidemic . When do we expect epidemiology to feed back on the evolution of virulence ? In our experimental system , this feedback operates because the spread of the virus in the population reduces the density of susceptible hosts . This erodes the benefit of virulence ( horizontal transmission ) while the cost of virulence ( induced host mortality ) remains . Note that this qualitative result is robust to variations of the initial frequency of the mutant strain ( not shown ) . In our system , the cost of virulence acts mainly via the reduction of vertical transmission . Yet , in the absence of vertical transmission , a similar pattern is expected when horizontal transmission carries other costs . In many lytic phages these fitness costs result from the trade-off between lysis time and burst size [33] . The virus with short lysis time ( and small burst size ) may only outcompete the virus with longer lysis time ( and larger burst size ) at the beginning of the epidemic when the availability of susceptible bacteria is maximal [34] . Similar patterns of transient evolution are also expected in pathogens that transmit throughout the course of the infection . In this case , higher rates of horizontal transmission are often associated with more aggressive host exploitation strategies which reduce host life-span and pathogen's infectious period . Shortened infectious period can result in substantial fitness costs for the virulent pathogens . It is only during the early stages of an epidemic that such virulent strains may outcompete the others [3]–[6] . Hence , the transient evolution we report in our study is expected whenever there is a fitness cost associated with increased virulence and horizontal transmission . Epidemic feedback on the evolution of virulence is likely to be widespread and could affect many other pathogens . For example , this feedback may also operate during viral invasion into a multicellular host organism ( within-host evolution ) . During this within-host spread of the infection the availability of susceptible cells is expected to drop . Noteworthy this effect is particularly strong for viruses with superinfection exclusion like herpes- and retroviruses as well as phage λ , where infected cells remain resistant to a second infection and can vertically pass on this immunity to daughter cells [35]–[36] . A similar evolutionary trajectory is expected in large scale epidemics ( between-host evolution ) when the spread of the infection reduces the availability of susceptible hosts because both infected and recovered individuals tend to be immune to new infections [36] , [37] . If multiple infections or superinfections are possible , the evolution of virulence results from selection acting on two different levels: within and between hosts [38]–[40] . Nevertheless it is possible to modify our model to allow for this additional level of complexity but the evolutionary outcome depends on the relative competitive abilities of different variants which can be obtained in some pathogens [40] and could thus be used to provide quantitative predictions when these two levels of selection are acting on the evolution of virulence . Our experimental epidemics occur in a small and well-mixed community free of the considerable complications arising from stochasticity , multi-host life cycles , host immunity , input of new mutations and spatial structuring of host populations . Albeit a necessary simplification of a more complex reality , our experiments provide a unique opportunity to understand pathogen evolution during the course of an infection ( within-host dynamics ) . In HIV and HCV , for instance , the replicative fitness and the ability of the virus to resist therapeutic drugs has been shown to change throughout the course of the infection [41]–[43] . The understanding of such within-host evolution is key to providing more effective therapies that are not necessarily aimed towards eradication of the pathogen but towards patient health improvement [44]–[45] . On a larger spatial scale , the interplay between epidemiology and evolution that we demonstrate here can have far reaching consequences for emergent epidemics during the spread into a host population ( between-host dynamics ) [6] . More specifically , we expect drastic changes of virulence between early and later stages of global pandemics , but also between different stages of the pathogen life cycle . Our joint theoretical and experimental approach is a first step towards a framework aiming to forecast both the epidemiological and evolutionary trajectories of pathogens .
The GFP-Kan cassette from λGFP ( from reference [21] ) was amplified with primers λ20165F ( CGCAGAAGCGGCATCAGCAA ) and λ22543R ( GGACAGCAGGCCACTCAATA ) and subcloned into pUC18 . Subsequently GFP was mutated to CFP and YFP by a quick-change PCR approach with megaprimers amplified from pDH3 and pDH5 ( Yeast Resource center , University of Washington , primers: Fwd TGGCCAACACTTGTCACTAC , Rev AGAAGGACCATGTGGTCTCT ) . CFP-Kan and YFP-Kan cassettes were integrated into the prophage of K12[λ] and KL740[λcI857] ( Yale E . coli Stock Center ) by the aid of recombineering plasmid pKM201 ( Addgene ) . Fluorescent lysogens were induced by 10 µM MitomycinC and chloroformed lysate was used to reinfect E . coli MG1655 . Our method for the detection of selection on virulence is based on the competition of the non-virulent λ wildtype against the virulent λcI857 . In order to verify the expected differences in life-history traits between those strains and to obtain rough parameter estimates for the simulations we measured the viral life-history traits virus production ( PFU/mL ) , genome integration rate ( % lysogenized ) and vertical transmission ( CFU/mL ) . We determined these traits for all constructed viruses ( λcI857CFP , λcI857YFP and λCFP , λYFP ) by independent life-history assays prior to competition in the chemostat . The life-history traits were measured by the following three independent assays . ( 1 ) Virus production ( PFU/mL ) ( Figure S3A ) was determined by growing lysogen cultures to OD600 nm = 0 . 6 at 30°C and shifting them to 35°C and 38°C for 2 h until lysis occurred . From these lysates , viral titers were determined by qPCR on a Roche LightCycler480 ( primers F:5′AATGAAGGCAGGAAGTA3′ R:5′GCTTTCCATTCCATCGG3′ ) . Viral titers were calculated from a calibration curve based on CP values of a dilution series of a lysate of λvir of known titer ( 3×109 pfu ) . ( 2 ) Vertical transmission ( CFU/mL ) ( Figure S3A ) was measured by diluting lysogen cultures of λCFP , λYFP and λcI857CFP , λcI857YFP to OD600 nm = 0 . 07 and growing them for 6 h at 35°C and 38°C in eight replicates each in 96-well plates on a Titramax shaker ( Heidolph , Germany ) at 900 rpm . Every hour OD600 nm was measured in an Infinity200 microplate reader ( Tecan , Austria ) . OD600 nm values were converted to CFU's by a calibration curve which was obtained by plating . ( 3 ) Lysogenization rate ( Figure S3B ) was determined by challenging non-infected E . coli MG1655 with 108 PFU/mL free virus particles of λCFP , λYFP , λcI857CFP and λcI857YFP for 24 h . After 24 h , the proportion of lysogenized ( fluorescent ) cells was determined by flow cytometry . Media , 0 . 25 x LB , 0 . 2% Maltose , 10 mM MgSO4 and 5 mM IPTG . Dilution rate 0 . 8/h with 5 mL chamber volume at 35°C ( 50 mL chamber volume in the second experiment ) . Samples were drawn at 1 h intervals and stored at 2°C in 10 mM Na-citrate . To follow the relative prevalence of each strain in experimental epidemics we distinguished cells infected by CFP and YFP tagged virus through flow cytometry . CFP was detected at 405 nm excitation and 510/50BP emission and YFP was detected at 488 nm excitation and 530/30BP emission on a BD FacsCantoII flowcytometer . We used the FlowJo7 ( Tree Star , Inc . ) software to apply automatic compensation and gating . To quantify the amount of each strain in the free virus stage we developed CFP and YFP specific qPCR primer sets that match the functional substitution T203Y , which is responsible for the spectral shift from GFP to YFP and V163A and N164H which are used as fluorescence enhancers of CFP ( Table S3 in Text S1 ) . Our primers show no non-specific amplification even in large excess of the non-specific template ( Figure S4 ) but high amplification efficiencies ( AE ) on their specific template ( AE = 2 . 0 for CFP and AE = 1 . 98 for YFP ) .
|
Why are some pathogens more virulent than others ? Theory predicts that pathogens that ‘keep their host alive’ can sometimes outcompete virulent pathogens in times when transmission to new susceptible hosts is unlikely . Yet , this prospect of finding a new susceptible host changes itself throughout an epidemic . In the early stage of an epidemic susceptible hosts are abundant and virulent pathogens that invest more into horizontal transmission should win the competition . Later on , the spread of the infection reduces the pool of susceptible hosts and may reverse the selection on virulence . This may favor benign pathogens after the acute phase of the epidemic . We model this transient benefit for virulence and predict both the epidemiology and the evolution of pathogens during an epidemic . To put these predictions to the test we monitor the competition of the temperate bacterial virus λ and its virulent mutant λcI857 in experimental epidemics . Our experimental results agree remarkably well with all our theoretical predictions . This demonstrates the ability of evolutionary epidemiology to predict selection for virulence in an ongoing epidemic .
|
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2013
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Evolution of Virulence in Emerging Epidemics
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Sir2 is a central regulator of yeast aging and its deficiency increases daughter cell inheritance of stress- and aging-induced misfolded proteins deposited in aggregates and inclusion bodies . Here , by quantifying traits predicted to affect aggregate inheritance in a passive manner , we found that a passive diffusion model cannot explain Sir2-dependent failures in mother-biased segregation of either the small aggregates formed by the misfolded Huntingtin , Htt103Q , disease protein or heat-induced Hsp104-associated aggregates . Instead , we found that the genetic interaction network of SIR2 comprises specific essential genes required for mother-biased segregation including those encoding components of the actin cytoskeleton , the actin-associated myosin V motor protein Myo2 , and the actin organization protein calmodulin , Cmd1 . Co-staining with Hsp104-GFP demonstrated that misfolded Htt103Q is sequestered into small aggregates , akin to stress foci formed upon heat stress , that fail to coalesce into inclusion bodies . Importantly , these Htt103Q foci , as well as the ATPase-defective Hsp104Y662A-associated structures previously shown to be stable stress foci , co-localized with Cmd1 and Myo2-enriched structures and super-resolution 3-D microscopy demonstrated that they are associated with actin cables . Moreover , we found that Hsp42 is required for formation of heat-induced Hsp104Y662A foci but not Htt103Q foci suggesting that the routes employed for foci formation are not identical . In addition to genes involved in actin-dependent processes , SIR2-interactors required for asymmetrical inheritance of Htt103Q and heat-induced aggregates encode essential sec genes involved in ER-to-Golgi trafficking/ER homeostasis .
Cell division in budding yeast , Saccharomyces cerevisiae , and specific adult stem/progenitor cells includes asymmetrical inheritance of oxidized proteins , ensuring low levels of cytosolic damage in a specific cell lineage [1]–[3] . In both yeast and adult precursor cells , the lineage inheriting less damage display a longer life expectancy [1]–[3] . Thus , these singular division events provide a tractable model for how age physiognomies are reset in the progeny , which might provide clues towards therapeutically halting , or even reversing , senescence and tissue decline In budding yeast , the control of aggregate inheritance encompasses an Hsp104-dependent retention of damaged/aggregated proteins in the mother cell [4] , [5] , a spatial protein quality control ( SQC ) that relies also on the deposition of aggregates into specific protein inclusions called Insoluble Protein Deposit ( IPOD ) and JUxta Nuclear Quality control compartment ( JUNQ ) [6]–[8] . Besides the protein remodeling factor Hsp104 , the yeast gerontogene Sir2 [9]–[11] is required for asymmetrical segregation of oxidized and aggregated proteins [1] , [4] , [12] , [13] . The role of both Hsp104 and Sir2 in establishing damage asymmetry has been linked to actin cable-dependent processes and the polarisome [5] , [14]; a complex at the tip of the daughter cell required for actin cable nucleation [15] , [16] . Actin cables are suggested to play a role in aggregate retention due to their ( and prions' ) physical association with the actin cytoskeleton preventing their free diffusion into the daughter [5] , [14] , [17]–[19] . Sir2 deficiency reduces actin cable abundance , cytoskeletal functions , and the velocity of retrograde actin flow from the polarisome region [4] , [14] , [20] . This link between Sir2 and actin cable functions are consistent with data demonstrating that Sir2 affects the rate of actin folding by modulating the activity of the chaperonin CCT [14] . Actin-cables and the small heat shock protein Hsp42 are also required for the formation of peripheral aggregates [21] . Based on such results , it has been suggested that asymmetrical segregation of damaged proteins is a factor-dependent , genetically determined process , which results in the association of aggregates with structures/organelles limiting their inheritance into the daughter cell [1] , [4]–[6] , [14] , [19] . This view is contrasting that of Li and colleagues [21] , which , based on aggregate tracking experiments and modeling , argues that asymmetric inheritance is a predictable , and purely passive , outcome of aggregates' slow , random diffusion and the geometry of yeast cells . In this view , aggregate inheritance is dictated solely by the diameter of the bud neck and for how long this neck is open ( generation time ) for diffusion of aggregates . However , there is a large and unexplained amount of diversity in the supposedly random movement of aggregates in the aggregate population recorded by Zhou et al . , [22] such that many aggregates appears stationary in the mother cell while others move in a ballistic fashion . Thus , the usefulness of employing an average diffusion coefficient for this diverse population of aggregate movements in attempting to draw conclusions about inheritance being factor dependent or purely passive has been questioned [6] . In addition , it was shown that the large aggregates in the Zhou et al . , [22] study is IPOD and JUNQ inclusions that cannot diffuse freely , or randomly , since they are tethered to the vacuole and nucleus , respectively [6] . In the present work , we tested whether the passive diffusion model or the factor-dependent tethering model appear most relevant for our understanding of asymmetrical inheritance of aggregates and the asymmetry defects observed in cells lacking Sir2 . To do so , we analyzed the inheritance of two reporters; the spontaneously misfolding and aggregating Huntingtin Htt103Q protein and heat-induced , Hsp104-associated aggregates and quantified the traits of sir2 mutant cells predicted to affect the inheritance of such aggregates in a passive manner . In addition , we identified hitherto unknown factors required for asymmetrical inheritance among essential genes displaying synthetic genetic interactions with SIR2 , in order to determine if inheritance defects is linked to specific biological processes/components or governed by passive traits . The data obtained suggest that slow and passive diffusion is not sufficient for establishing the mother-biased segregation displayed by wild type yeast cells . Instead , we found that the essential actin-associated myosin V motor protein Myo2 and the actin organization protein calmodulin , Cmd1 , are required for asymmetrical inheritance and that both Htt103Q foci and heat-induced Hsp104-associated stress foci/peripheral aggregates co-localize with Myo2/Cmd1-enriched structures . Super-resolution 3-D structured illumination microscopy further showed that both Htt103Q and Hsp104 foci co-localize with actin cables . In addition , the data suggest that a fully functional ER-Golgi trafficking/ER homeostasis activity is required for restricting aggregate inheritance during yeast cytokinesis .
For obtaining empirical , quantitative , datasets on aggregate inheritance , we used both heat-induced aggregate formation detected by Hsp104-GFP and the aggregation-prone Huntington's disease protein Htt103Q-GFP ( detailed information of this construct can be found in Wang et al . 2007 [22] ) , which , in contrast to heat-induced aggregates , forms small and stable aggregates rather than large IPOD/JUNQ inclusions ( Figure 1A; [23]–[25] ) . Reduced inheritance ( e . g . by aggregate retention in mother cells ) and aggregate removal ( e . g . by disaggregation or retrograde aggregate movement in daughter cells ) [14] , [19] are the two processes required for establishing asymmetric aggregate distribution . Figure 1B shows a schematic illustration of how these two processes can be distinguished experimentally . Upon HTT103Q induction ( leading to Htt103Q aggregation ) by the addition of galactose , cells are stained with a fluorescent conA ( concanavalinA ) conjugate , which binds to glycoproteins in the cell wall . During the subsequent addition of glucose , which represses further HTT103Q expression , conA is washed away . This protocol enables discrimination between daughter cells present during induction of HTT103Q expression and aggregate formation ( stained with conA ) , and cells generated after turning off synthesis of the aggregating protein ( not stained with conA ) that can only display aggregates if they ( or possibly small aggregation nucleation particles ) have been inherited from the mother cell ( Figure 1B ) . Analyzing the inheritance of all visible Htt103Q foci demonstrated that wild type yeast mother cells retained Htt103Q aggregates in a quantitatively similar way as heat-induced aggregates [14] , [21] during cytokinesis ( Figure 1C&D ) and that the absence of Sir2 reduced this retention capacity about 2-fold ( Figure 1C; p = 0 . 02 ) . During the time frame of the experiment , we found little or no clearance of the Htt103Q protein in conA-stained daughter cells ( Figure 1E ) . Thus , establishment of asymmetrical aggregate distribution of both small aggregation-prone disease proteins and indigenous heat-induced Hsp104-associated inclusion bodies [6] , [14] are dependent on Sir2 and involves aggregate retention in mother cells . Simulations suggest [21] that to allow for the 2-fold increased inheritance the bud neck between the mother and daughter has to be enlarged by a factor of 2 . 2–3 . 0 provided the aggregates move by random walk [21] and that the generation time and aggregate number is similar in the wild type and mutant cells . Using the septin ring component Shs1-Gfp as a reporter for the bud neck , we found no evidence that the mean and median bud neck diameter in wild type and sir2Δ mutant cells was different ( Figure 2A&B ) . In addition , the generation time of Sir2-deficient cells was not significantly longer than that of wild type cells ( Figure 2C ) . Moreover , the average length of a sir2Δ mutant mother cell is longer than a wild type mother cell ( Figure 2D ) , which would mean that the average aggregate in a sir2Δ mother have to embark on a longer journey to reach the daughter , which would yield a more pronounced asymmetry in Sir2-deficient cells provided aggregate distribution was solely dependent on random walk . Finally , the distribution and average number of the Htt103Q aggregates observed was similar in wild type and Sir2-deficient cells ( Figure 2E ) as was the number of heat-induced , Hsp104-associated aggregates ( Figure S1 ) . Thus , changes in geometrical parameters , generation time , or aggregate abundance did not explain increased inheritance of aggregates in sir2Δ daughter cells . The passive aggregate diffusion model predicts that cells displaying a reduced growth rate will suffer from a generally increased daughter-cell inheritance of aggregates since the aggregates are allowed a longer time to randomly find their way into , and equilibrate with , the daughter cell . Therefore , we investigated to what extent Htt103Q aggregate inheritance could be enhanced in wild type cells when the generation time was slowed-down after aggregate formation by different concentrations of the protein synthesis inhibitor cyclohexamide . It has been shown that exponential cultures treated with low concentration of cycloheximide do not display arrest in any specific cell cycle stage but instead grow at a slowed exponential fashion with a prolonged cell cycle [26] . Since septum formation occurs only after the completion of mitotic events [27] the bud neck should remain open for a prolonged time upon exposure to low concentrations of cycloheximide . The Htt103Q-GFP reporter is a useful model protein for this experiment ( see Figure 2F for the experimental rationale ) because Htt103Q aggregates are stable ( not cleared ) during long periods of time ( Figure 1E ) and aggregate formation does not involve changes in temperatures , which would affect diffusion rates . The segregation analysis demonstrated that prolonging the generation time more than two-fold did not result in an increased inheritance of Htt103Q aggregates ( Figure 2G ) , suggesting that the establishment of aggregate asymmetry cannot rely on slow and random diffusion alone . To approach the passive diffusion model and factor-dependent models further , we next identified which Sir2-dependent functions are involved in restricting aggregate transfer to daughter cells . Therefore , we supplemented the previously identified genetic interaction network of SIR2 [14] with essential alleles included in the ordered , temperature-sensitive ( ts ) , mutant library reported by Li et al . [28] . The rational for this approach is based on data suggesting that a failure to segregate protein damage can result in a reduced fitness [14] , [29] , [30] and it has previously been shown [14] that machineries involved in the partitioning of protein damage could be identified among the genes interacting ( as synthetic sick or lethal ) with a sir2 deletion using synthetic genetic arrays ( SGA ) analysis [31]–[33] . The protocol for allowing a sir2Δ mutant to mate and produce spores in an SGA screen has been reported previously and includes deletion of the HMR and HML silent mating type loci in the SIR2 query strain [14] . The sir2Δ × ts-allele crosses were tested for growth at varying temperatures because different ts-mutants in the library display fitness defects under different semi-permissive conditions . We found that 6% of the 787 alleles included in the ts-library displayed statistically significant negative genetic interaction with SIR2 . As seen in Table S2 and figures 3A&B , SIR2 displayed negative genetic interactions with genes involved in actin polarity , actin folding , and actin nucleation consistent with previous results [1] , [4] , [14] , [20] . Analysis of functional relationships and known physical interactions identified 4 additional , previously unknown , functional groups of the SIR2 interaction network: 1 . ‘SPB , microtubule nucleation’ , 2 . ‘ER-Golgi trafficking/function’ , 3 . ‘chromosome/sister chromatid segregation’ , and 4 . ‘proteasome regulatory particle’ ( Figure 3A&B ) . A sir2Δ mutant contains a higher ratio of unfolded/folded actin monomers than wild type cells and the chaperonin CCT isolated from sir2Δ cells displays a reduced rate of actin folding [14] . Consistently , the cct1-2 allele , similar to the cct6-18 allele [14] , was found here to cause severe synthetic sickness in combination with sir2Δ ( Figure 3C ) . The CCT chaperonin is also providing the microtubule cytoskeletal system with folded tubulin , which could explain why tub mutants are also synthetic sick in combination with sir2Δ and why genes of the ‘SPB , microtubule nucleation’ and ‘chromosome/sister chromatid segregation’ functional groups interacts negatively with sir2Δ . The SIR2 interactors of these groups are functionally related and interconnected also by physical interactions between Cdc5 , Mps3 and Smc2 ( Figure 3B ) . Mps3 and Cdc5 are required for SPB duplication and separation , respectively , and Mps3 interacts physically with Smc2 of the Smc2/4 condensin complex . Both smc2 and smc4 mutants displayed synthetic sickness in combination with sir2Δ ( Table S2; Figure 3A&B ) , which is interesting as the cohesin subunit Smc3 displays elevated levels of acetylation in a sir2Δ mutant following α-factor treatment [34] . Like CCT , CMD1 , encoding calmodulin , is required for proper function of both the actin and microtubule cytoskeletons [35] . Consistently , cmd1-1 mutant cells were severely impaired for growth when combined with sir2Δ ( Figure 3D ) . Essential genetic SIR2 interactors also included a relative large number of SEC genes involved in ER/Golgi functionality and trafficking ( Figure 3A&B ) ; specifically , sec18/20/22 involved in retrograde transport between the ER and Golgi , sec7 , required for intra-Golgi and ER-to-Golgi transport , sec53 required for folding and glycosylation of proteins in the ER lumen , and sec11 needed for targeting proteins to the ER . In line with Sir2 buffering against defects in ER functions , the cdc48-3 allele encoding a temperature sensitive AAA+ chaperone , which facilitates extraction of ubiquitylated misfolded proteins from the ER , also displayed negative genetic interaction with sir2Δ ( Table S2; Figure 3A&B ) . The ‘ER-Golgi trafficking/quality control’ group of genes is more distantly connected functionally to the CCT/CMD1 groups with respect to genetic interactions [33] , [36] suggesting that this group of genes display genetic interaction with SIR2 for other reasons than defects in CCT and actin/microtubule functionality . By crossing the HSP104-GFP fusion into the essential ts-mutant library using synthetic genetic array technology , we next tested whether any of the functional groups of the essential SIR2 genetic interaction network displayed aberrant aggregate inheritance of heat-induced Hsp104-associate aggregates and then followed up by testing if asymmetrical Htt103Q inheritance required the same factors . Among all the essential alleles interacting with SIR2 , about 40% caused a defect in establishing Hsp104-aggregate asymmetry . One of the most severely affected mutants , cmd1-1 , encoding calmodulin , belong to the group of genes involved in actin cable organization and function ( Figure 4A ) . In addition , defects in the organization of both tubulin ( tub4-Y445D ) and the SPB ( spc110-220 ) affected asymmetry ( Figure 4A ) , suggesting that the machineries required for nuclei segregation are also required for establishing aggregate asymmetry . This is consistent with data demonstrating that aberrant nuclei segregation can lead to daughter-cell inheritance of protein inclusions , especially JUNQ [6] . With the exception of cdc48-3 , mutants of the ‘proteasome regulatory particle’ and ‘chromosome/sister chromatid segregation’ groups did not display aberrant aggregate asymmetry , whereas all alleles in the ‘ER/Golgi trafficking/function’ group did ( Figure 4A ) . Calmodulin regulates many processes apart from actin cable organization , including vacuole inheritance , endocytosis , microautophagy , and organization and formation of the SBP . Therefore , we next tested if any or all of these processes/components are either required for preventing the inheritance of aggregates ( retention in mother cells ) , clearance of aggregates ( in daughter cells ) , or both using the ConA protocol ( see Figure 1 ) . Mutations in CMD1 have been reported to cause actin cytoskeletal defects by reducing the levels of the signaling molecule phosphatidylinositol ( 4 , 5 ) -bisphosphate [37] . We found that the sir2Δ interactor mss4-102 , a mutant allele of the phosphatidylinositol ( 4 , 5 ) -bisphosphate kinase , increased aggregate inheritance and decreased aggregate removal in daughter cells ( Figure 4B ) . In addition , Cmd1 is required for polarized growth and inheritance of the vacuole by daughter cells through its interaction with the type V myosin motor protein Myo2 [38] , [39] , and cells harboring the myo2-14 or myo2-16 alleles , like cmd1-1 cells , displayed severe defects in both aggregate inheritance and removal ( Figure 4B ) . Likewise , Spc110 , which requires Cmd1 for its proper localization to the SPB [35] , [40] , and tubulin ( tub4-Y445D ) were required for both asymmetrical inheritance and removal of aggregates ( Figure 4B ) . In contrast , deficiencies in Cmd1-dependent microautophagy , which is mediated by Vtc2 and Vtc3 [41] , were not affecting aggregate asymmetry ( Figure 4B ) . Among the calmodulin-independent genes of the SIR2 interaction network , all involved in ER/Golgi trafficking/functionality and the UPR/ERAD , displayed deficiencies in establishing aggregate asymmetry ( Figure 4A ) and by testing some selected alleles in this group including sec53-6 , sec20-1 , sec22-1 , sec18-1 , kar2-ts , and cdc48-3 using the conA protocol we found that all these genes were required for preventing aggregate inheritance in daughter cells ( Figure 4B ) . The mutations identified causing an increased daughter-cell inheritance of protein aggregates could be doing so by affecting aggregate numbers if aggregate partitioning is predominantly due to random diffusion . Therefore , we quantified aggregates in the mutants of the functional groups found to be required for asymmetrical inheritance . This analysis demonstrated that the absence of most genes identified here as being required for aggregate asymmetry , did not significantly increase aggregate numbers ( Figure 4C&D , Figure S2 ) . However , there are some intriguing exceptions; reduced activity of Cmd1 and the ER chaperone Kar2 caused a marked increase in the average number of aggregates per cell indicating that these proteins are required for inclusion body formation ( Figure 4C&D , Figure S2 ) . Nevertheless , alterations in aggregate inheritance in the majority of the mutants identified are uncoupled from changes in aggregate numbers . Defects in aggregate partitioning could also be due to diminished levels of Hsp104 [4] , [5] . However , for the mutants tested herein , the defects in inheritance was not accompanied by reduced Hsp104 levels ( Figure 4E ) , or elevated total levels of insoluble proteins , which were separated from soluble proteins by ultracentrifugation ( Figure 4F ) . To test to what extent alterations in generation times might contribute to changes in aggregate inheritance , we recorded daughter cell inheritance for the ts-mutants analyzed as a function of the generation time obtained during the aggregate segregation analysis . The mutants and temperatures analyzed generated generation times within a 1 . 5 fold difference from the wild type cells . The data was subjected to linear regression analysis together with confidence and prediction interval determinations to quantify the contribution of generation times on inheritance . A number of important observations can be made from this analysis . First , within the confidence interval ( i . e . the interval displaying little difference in generation times ) vastly different degrees of inheritance were recorded ( Figure 4G ) , demonstrating that the effects on inheritance must be governed by other means than alterations in the generation time within this group of mutants . Second , in contrast to the predictions of the passive diffusion model , the best linear fit shows a weak trend towards a decreased inheritance with increased generation times but the adjusted R-squared value and p-value of −0 . 04346 and 0 . 7752 , respectively , demonstrate that this trend is not statistically significant . To test if the segregation defect seen in sec mutants could be linked to aberrancies in actin cytoskeleton organization , we analyzed actin polarity as described in [42] , and found that sec53-5 , like cmd1 and myo2 mutants , displayed a markedly aberrant actin polarity ( increase number of cells with more than 6 actin patches ) whereas the sec18-1 mutant showed a decreased number of patches ( Figure 4H&I ) . Thus , it is possible that some SEC and ER-associated mutants fail to segregate aggregates asymmetrically due to polarity defects . We next tested selected alleles that markedly reduced mother cell-biased segregation of heat-induced Hsp104-associated aggregates for their effect on asymmetrical segregation of Htt103Q . We found that both Cmd1 and Myo2 , as well as the SEC genes ( SEC18 and SEC53 ) were required for asymmetrical segregation of Htt103Q ( Figure 5A ) . As for heat induced Hsp104-associated aggregates , this defect was not due to elevated levels of unfolded and insoluble Htt103Q in these cells ( Figure 5B ) . The requisite of the same factors for asymmetrical segregation of both heat-induced Hsp104-associated aggregates and Htt103Q is somewhat unexpected as the former is sequestered into distinct , inclusion bodies ( IBs ) , IPOD and JUNQ , upon heat stress [7] , whereas Htt103Q forms multiple small aggregates throughout the cytoplasm [23] , [24] , [43] . However , before the formation of IPOD/JUNQ , misfolded , Hsp104-associated , proteins assemble into small stress foci ( [6]; also called Q-bodies [30] or peripheral aggregates [44] ) , reminiscent of the smaller Htt103Q aggregates . We therefore tested if Hsp104-GFP co-localized with Htt103Q immediately after heat stress and found this to be the case; co-localization can be observed in about 97 . 1% cells displaying both Htt103 and Hsp104 aggregates ( Figure 5C ) , indicating that Htt103Q may be sequestered at terminally stable stress foci-like structures . It has been suggested that amyloids and heat-denatured proteins are sequestered to spatially different quality control sites [7] . Therefore , we tested whether Htt103Q formed amyloids using Thioflavin-T staining but found no evidence for this whereas the positive control , Rnq1-mRFP aggregates readily stained with Thioflavin-T ( Figure 5D ) . Next , we analyzed if Htt103Q foci co-localized with Cmd1 and/or Myo2 , which could explain , in a direct physical manner , why retention in the mother cell relies on these factors . In cells where Cmd1 or Myo2 were enriched in visible structures , 94 . 4% and 92 . 2% showed co-localization between Htt103Q and such Cmd1 or Myo2 structures , respectively ( Figure 5E ) . In addition , the ATPase-deficient Hsp104 , Hsp104Y662A , which has previously been shown to be ‘locked’ in a stress foci stage [6] , similarly co-localized with Cmd1 ( in 74 . 4% of cells ) and Myo2 ( in 56 . 6% of cells ) enriched structures ( Figure S3 ) . We found less co-localization between Htt103Q foci and Sec18 ( about 48% of cell showing both Sec18 structures and Htt103Q foci ) whereas no clear co-localization could be observed between Htt103Q foci and Sec53 ( displaying a diffuse signal ) ( Figure 5E ) . In contrast , in cells with heat induced Hsp104Y662A foci a clear co-localization can be observed between Hsp104Y662A and Sec53 ( 82 . 7%; Figure S3 ) . Some of the Htt103Q and Hsp104Y662A foci appeared to reside in the vicinity of the ER , as detected by Rtn1-GFP co-staining ( Figure S4 ) . Previous studies have shown that the small heat shock protein Hsp42 affects sequestration of misfolded proteins; specifically , in the absence of Hsp42 misfolded proteins are predominantly directed to the juxtanuclear JUNQ deposition site instead of peripheral , nucleus-distant , aggregation sites [8] , [44] . Importantly , we found that the absence of Hsp42 redirected Hsp104Y662A to inclusions ( cells with 1 or 2 aggregates; i . e . class 1 and 2 cells ) rather than peripheral aggregates/stress foci ( 3 or more aggregates; class 3 cells ) whereas formation of Htt103Q foci was unaltered ( Figure 5F , G ) . Co-staining with DAPI demonstrated that the number of cells with a single juxtanuclear-localized aggregate were increased in the hsp42Δ mutant ( Figure S5 ) . These data indicate that while Hsp104Y662A and Htt103Q are directed to overlapping , Cmd1/Myo2-associated , foci , the routes/factors employed for sequestering heat-induced stress foci and Htt103Q to such sites may be different . Cmd1 and Myo2 are intimately associated with the actin cytoskeleton and protein aggregates and prions have been found previously to reside in areas rich in actin-enriched structures using proximity ligation assays and co-localization fluorescence microscopy [14] , [18] , [19] , [43] , [45] . However , one major drawback with conventional fluorescence microscopy is that the x–y axial resolution is limited to about 250 nm and the z axial resolution to about 500 nm [46] , [47] . Therefore , to more precisely analyze the spatial relationship between protein aggregates/stress foci and the actin cytoskeleton , we performed super-resolution three-dimensional structured illumination microscopy ( 3D-SIM ) [48] to analyze possible aggregate and actin cytoskeleton interactions in vivo . With this technique an approximately 8-fold smaller volume can be resolved in comparison to conventional microscopy equating about 100 nm in x-y and 200 nm in the z axial [46] , [49] . The 3D-SIM analyses revealed that both Htt103Q and Hsp104Y662A foci line up along actin cables and are in some instances wrapping around the cables ( Figure 6A–D , Figure S6 and Movie S1 ) . At this resolution , using multiple Z-stacks , it is clear that the co-localization is not due to actin oligomers residing in the aggregates themselves ( Figure 6B&D ) . Moreover , we found that Hsp104Y662A-mCherry stress foci displayed a considerable co-localization with the actin cable-associated protein Abp140-3GFP further supporting an association between stress foci and actin cables ( Figure 6E&F ) .
The development of an in situ protocol for detecting oxidatively damaged ( carbonylated ) proteins in single cells of S . cerevisiae led to the discovery that damaged proteins display a mother cell-biased segregation during cytokinesis [1] and it was later shown that such oxidatively damaged proteins coalesce into aggregates upon aging that rely on both Hsp104 [4] , [5] and Sir2 [1] , [14] , [50] for their asymmetrical inheritance . Data accompanying the original discovery showed also that elevating damage in the mother cell by a transient exposure to oxidants rendered asymmetrical inheritance even more pronounced indicating that asymmetry was not entirely due to a passive effect of slow diffusion [1] . The data presented in this work is consistent with this notion: If aggregates would find their way into a daughter cell purely by passive and random movement , increasing the time for completing cytokinesis would enhance aggregate inheritance - we show here that this is not the case . Further , mutants with increased daughter-cell inheritance should , if aggregates diffuse randomly , either display a larger bud-neck diameter , a longer generation time , or increased number of aggregates; none of these traits could be established for sir2Δ cells or the other mutants displaying elevated inheritance . Prevention of inheritance of both the misfolded polyQ protein Htt103Q and heat-induced aggregates relies instead on specific cellular processes/components , including the actin-associated proteins Cmd1 and Myo2 and Sec proteins involved in ER to Golgi trafficking and ER homeostasis . It is possible that a reduction in actin cable abundance affects aggregate diffusion , as an intact actin cytoskeleton in dictyostelium appears to slow down the diffusion rates of soluble GFP proteins [51] . However , since both Htt103Q and heat-induced foci co-localized with Cmd1- and Myo2-enriched structures , the retention of aggregates might be linked to a more direct physical interaction between these components and aggregates . Cmd1 and Myo2 are intimately associated with actin cables and super-resolution 3-D SIM microscopy demonstrating that stable foci of both Htt103Q and Hsp104Y662A are associated with the actin cytoskeleton ( and the actin-binding protein Abp140 ) in the nm-scale . These data is further supporting a role of actin cable assembly [1] , [4] , [44] , actin folding [14] , and actin polarity [19] in aggregate inheritance control . Interestingly , the Htt103Q foci co-localized with the Hsp104 stress foci formed early upon a heat shock . Thus , misfolded Htt103Q and heat-denatured proteins appears to be sequestered into the same spatial sites . In further support of this notion , the disaggregase-defective Hsp104Y662A-GFP , which upon heat stress forms stable stress foci [6] , like Htt103Q , co-localized with Cmd1 and Myo2 . However , we found that only Hsp104Y662A-associated misfolded proteins , and not Htt103Q , required Hsp42 for foci formation . The absence of Hsp42 has been shown previously to redirect heat-denatured misfolded proteins to the nucleus-proximal JUNQ deposition site at the expense of peripheral aggregation sites at least in the presence of a proteasome inhibitor [8] , [44] but we found that Htt103Q foci formation was unaffected by Hsp42 deficiency . Inversely , we found that Cmd1- and Kar2-deficiency reduced the cells' ability to form Hsp104-associated inclusions upon a heat shock; that is , heat-induced aggregates appear ‘locked’ in the stress foci stage in these mutants . The participation of the Myo2 motor protein and calmodulin in asymmetrical inheritance of aggregates suggests that the role of actin cables and polarity in this process may be linked also to vesicle/organelle trafficking . In support of this notion , the IPOD inclusions are associated with the vacuole [6] , [7] and it is conceivable that misfolded proteins reach such deposit sites in an actin cytoskeleton- and vesicle trafficking-dependent way . Indeed , Specht et al . , [44] have demonstrated that misfolded proteins fail to form peripheral aggregates when actin cables are depolarized with Latranculin and Kaganovitch et al . , [7] , using benomyl treatment , demonstrated the requirement also of microtubule in the formation of inclusion bodies . However , it was later shown that the effect of benomyl in inclusion body formation might be microtubule-independent [44] . The effect of abrogated ER/Golgi function on aggregate segregation could also be linked to effects on actin/calmodulin/Myo2-dependent vesicle/vacuole trafficking since the ER/Golgi is involved in lipid modifications of specific proteins , e . g palmitoylation and myristoylation , required for anchoring Myo2 to targets at vesicle membranes [52] . In this scenario , Myo2 might act as a tethering factor required for misfolded/aggregated proteins to become linked to actin cables and/or deposition sites on the surface of the vacuole since misfolded proteins have been demonstrated to associate with membrane vesicles [17] , [43] . In addition , a recent report shows that misfolded Ubc9ts proteins form puncta called Q-bodies that are associated with ER [30] . However , it should be noted that Ubc9ts-Q-bodies move in an actin-cable-independent ( but energy-dependent ) manner suggesting that these structures are not themselves associated with actin . The apparent difference with respect to actin-association of Ubc9ts Q-bodies and Htt103Q foci is interesting and may suggest that different misfolded proteins are sequestered to different spatial locations . Another possible reason for the different results is the use of different protocols; whereas Htt103Q readily aggregate upon its production Ubc9ts aggregation is triggered by elevating the temperature , a protocol that disrupts actin cables . Also , while Ubc9ts Q-bodies move in an actin cable-independent manner [30] , it is not clear if their subsequent progression to IPOD/JUNQ inclusion sites require functional actin cables or not since the dynamics , morphology and inheritance of cortical ER ( which the Ubc9ts Q-bodies associate with ) have been linked to actin cytoskeleton components [53]–[55] . Elucidating the exact cytological , biochemical , and genetic nature of stress foci , Q-bodies , peripheral aggregates , and IPOD/JUNQ inclusions and their relevance for different aggregate reporters appears an important task for future research . It has recently been shown that aggregate accumulation during replicative aging of mother cells follow a delineated path; virgin and young cells display no protein aggregates , middle-aged mother cells harbor one to two protein inclusions , first JUNQ then also IPODs , while old cells display , in addition to JUNQ and IPODs , multiple peripheral aggregates resembling stress foci [56] . It will be interesting to learn to what extent these foci are connected to Cmd1/Myo2 and the actin cytoskeleton and if such associations are actually a cause of aging . We envision that the tethering of multiple aggregates will disturb actin cable-dependent trafficking processes and eventually cause a complete collapse in the physical integrity of the actin cytoskeleton . In addition , the new and previously unknown genetic interactions between SIR2 and essential genes recorded herein points to additional Sir2-related functions of potential relevance for life span control . Specifically , since Sir2 buffers against deficiencies in microtubule/spindle pole body and chromosome/sister chromatid segregation functions , it is tempting to speculate that the diminishing level/activity of Sir2 observed in aging cells [57] leads to problems also in performing proper chromosome/nuclei segregation . Further studies appear warranted to elucidate how this sirtuin is mechanistically buffering against defects in these essential functions and how they might relate to sirtuins acting as gerontogenes .
Yeast strains used in this study are listed in Supplemental Table S1 . The Yeast conditional temperature-sensitive ( ts ) collection of essential genes for the SGA analysis was a gift from Prof . Charles Boone . Yeast cells were grown in YPD or synthetic drop-out media with antibiotics added as indicated . The SIR2 ( ts ) SGA analysis was performed in duplicates as described [28] . The screen was run in the 1536-spot format using a SINGER ROTOR HDA Robot ( Singer Instrument Co . Ltd . ) . Hits with the highest statistical probability to be true interactions were confirmed by microcultivation experiments in triplicate at 30 , 34 , and 38°C using the Bioscreen C system ( Labsystems Oy , Helsinki , Finland ) . The optical density was measured every 30 minutes for 72 hours . The LSC ( Logarithmic Strain Coefficient ) values of growth rates were calculated and scored as described [28] . The heat map was made using TreeView [58] and Ospery 1 . 2 . 0 [59] was used for SIR2 essential gene network analysis . The physical interactions between SGA hits were obtained based on the BioGRID interaction database [60] . A Zeiss Axiovert 200 M fluorescence microscope was used to obtain images using GFP , Cy3 and DAPI channels . The ImageJ plugin “Iterative deconvolve 3-D” was used for all deconvolution images . Cells containing the pYES2-HttQ103-GFP plasmid were grown at 30°C to exponential phase ( OD600 about 0 . 5 ) in YNB-URA 2% raffinose . Htt103Q-GFP expression was induced by adding galactose to a final concentration of 2% . After 4 hours at 30°C cells were washed and resuspended in 1 . 5 ml Buffer P ( 10 mM NaH2PO4 , 150 mM NaCl , 2% galactose; pH 7 . 2 ) . All cells present during the expression of Htt103Q-GFP were marked by staining the cell wall components α-mannopyranosyl and α-glucopyranosyl with 0 . 2 mg/ml concanavalin A Alexa Fluor 647 ( Invitrogen ) for 30 minutes at room temperature . The cells were then washed in Buffer P , resuspended in YNB-URA with 2% glucose , which will switch off the Htt103Q-GFP expression , and grown at 30°C for one budding event . This makes it possible to distinguish between concanavalin A stained daughter cells present during Htt103Q-GFP expression and daughter cells produced subsequent to Htt103Q-GFP expression . Cells were fixed in 3 . 7% formaldehyde and segregation of aggregates was analyzed using fluorescence microscopy . The segregation assay of ts-alleles were performed in the same way but without concanvalin A staining . Cells were grown at 22°C to exponential phase , followed by induction and budding at different temperatures ( 26°C for sec18-1 and sec53-6 , 28°C for cmd1-1 and 32°C for myo2-14 ) . The retention efficiency assay was performed as described [14] with concanavalin A staining ( as described above ) before the heat shock treatment . Aggregate retention and removal was distuinguished upon image analysis . Retention is determined as the percentage of aggregate-containing buds of the total number of buds generated from an aggregate-containing mother cell after the heat shock treatment ( buds free of conA ) ; Removal efficiency is determined as the perecentage of aggregate-free buds of the total number of buds already existing before heatshock; i . e . stained with conA . More than 300 budding events were quantified for each strains . All statistical calculations were done in R-3 . 0 . 0 ( www . r-project . org ) . Regression analysis was performed and showed that there is no statistically significant difference at p<0 . 05 to test that whether there is a correlation between ‘relative generation time’ and ‘deviation in asymmetry’ . The in vivo expression of mHtt103Q-GFP protein was induced by galactose addition to yeast cells in mid-exponential phase ( OD600 = 0 . 5 ) grown in media with 2% raffinose . 10 µg/ml of cycloheximide ( CHX ) was added into the culture after 3 hours of induction to stop translation . Cells were continued to be cultured at 30°C with shaking . Aliquots were then taken and fixed at 0 , 1 , 2 , 3 , 4 and 12 hours after the addition of CHX . GFP signal intensity for each sample was quantified by flow cytometry ( FACS Aria , BD equipment ) . 10000 events were counted for each sample . A cut-off value was picked based on an un-induced control . Stability is measured as mean signal intensity from Htt103Q-GFP aggregates as a function of time after inhibition of protein synthesis by adding CHX . Cells containing the pYES2-HttQ103-GFP plasmid were grown at 30°C until OD600 reached approximately 0 . 5 in SC-URA +2% raffinose . The expression of Htt103Q-GFP was induced by adding 2% galactose for 4 hours at 30°C . Cells were then stained with ConA as described above . The cell density was adjusted to OD600 = 0 . 5 . The cells were divided into 3 groups and recovered at 30°C for different times until the cells grow to the same optical density value as the untreated control with different concentrations of cycloheximide . Further expression of HttQ103-GFP was inhibited by adding 2% glucose to the medium during bud formation . The cycloheximide treatment was performed as follows: In the untreated group , no cycloheximide was added during the budding period and the cells were recovered for 4 hours at 30°C to let the cells generate new buds and grow to a OD600 reaching 0 . 8 . In the two cycloheximide treatment groups , 0 . 05 or 0 . 1 mg/ml cycloheximide were added to the cell cultures and grown at 30°C until OD600 reaches the same value ( 0 . 8 ) as in the untreated control group . Then cells were fixed in 3 . 7% formaldehyde and budding events with newly generated buds were analysed for aggregate inheritance using a Zeiss fluorescence microscope . 20 mL OD600 = 0 . 7 Yeast cells were collected after heat shock and recovery then resuspended in 800 µl 0 . 1 M NaOH for 5 minutes ( room temperature ) and then pellet . The cells were boiled for 3 minutes in 125 µl lysis buffer ( 50 mM Tris , pH 7 . 4 , 5 mM EDTA , 5 Mm NEM , 1% SDS ) with protease inhibitor ( Roche , 11697498001 ) . The supernatant was mixed with equal amount laemmli buffer and heated at 95°C for 3 minutes . Denatured proteins were loaded onto NuPAGE Novex 10% Bis-Tris Gels ( Invitrogen , NP0315BOX ) and transferred to PVDF membranes to perform western blotting . Antibody to GFP ( Roche , 11814460001 ) and pGK ( Invitrogen , 459250 , as loading control ) were used in this study . After western blotting , the membranes were scanned by Odyssey Infrared Imaging System and quantified by Odyssey 2 . 1 software . Fold ratios were calculated based on three biological repeat experiments . Solubility assays were carried out as described in [61] . Same volume of protein solution of each sample was loaded on precasted SDS-PAGE gels ( Life Technologies ) . For testing heat-induced aggregates , the gel was then stained by Coomassie Brilliant Blue and scanned with a GS-800 Calibrated Densitometer ( BioRad ) . For Htt-103Q-GFP expressing cells , the Htt-103Q-GFP protein was detected by Western blotting with mouse anti-GFP monoclonal antibody ( Roche ) . The scanned gels and Western membranes were then quantified by ImageJ software . Relative ratio of soluble and aggregated protein for each tested strain were then calculated and plotted . Thioflavin T staining of amyloid was performed according to a protocol from [62] with minor changes . Cells were fixed in 50 mM KPO4 ( pH 6 . 5 ) , 1 mM MgCl2 , 4% formaldehyde for 10 minutes and then washed three times with PM buffer [0 . 1 M KPO4 ( pH 7 . 5 ) , 1 mM MgCl2] and resuspended in PMST [0 . 1 M KPO4 ( pH 7 . 5 ) , 1 mM MgCl2 , 1 M Sorbitol , 0 . 1% Tween 20] . Cells were treated with 0 . 125 mg/ml Zymolase at room temperature for 15 minutes in the presence of 0 . 6% beta-mercaptoethanol . Spheroplasted cells were washed once and then resuspended in PMST and stained with 0 . 001% Thioflavin T for 20 minutes at room temperature . After five times of washing with PMST , the cells were observed under a Zeiss Observer Z1 microscope at CFP channel for the staining . Mid-log phase cells ( OD = 0 . 5 ) were incubated at 42°C for 10 minutes and then 30°C for 30 minutes . These cells were then fixed with 3 . 7% formaldehyde and washed twice with PBS ( pH 7 . 4 ) and stored for microscopy . At least 100 cells with both visible structures ( formed by GFP-tagged proteins ) and red aggregates ( formed by Hsp104-Y662A-mCherry or Htt103Q-mRFP ) were analyzed . Among them , cells with any overlapping green and red signals were considered as cells with co-localization , the percentage of which were then calculated . Z-stack images were used for aggregate morphology quantification and more than 100 cells showing aggregates were quantified . Cells were divided into 3 classes based on the number of aggregates in the cell ( Class 1 , cells with 1 aggregate; Class2 , cells with 2 aggregates; Class 3 , cells with 3 or more aggregates ) . Aggregates were counted throughout all Z-stacks . Actin depolarization was quantified according to Ho et al . [42] . All budding events that have a small or medium bud were counted for number of actin patches in the mother cells . Mother cells bearing more than 6 actin patches were counted and the percentage of them over all mother cells were calculated and plotted . Cells carrying Hsp104Y662A-mCherry were incubated at 42°C for 10 minutes and then 30°C for 10–20 minutes . And cells with Htt103Q-GFP was induced by adding 2% galactose for 4 hours at 30°C . Then cells were fixed with 3 . 7% formaldehyde and washed twice with PBS ( pH 7 . 4 ) . Actin cytoskeleton was stained using Alexa Fluor 568 Phalloidin ( Ivitrogen , A12380 ) as described in the manual . Cells expressing both Abp140-3GFP and Hsp104Y662A-mCherry were heat treated as above . For super-resolution three-dimensional structured illumination microscopy , the ELYRA PS . 1 LSM780 setup from Zeiss ( Carl Zeiss , Jena Germany ) was used . 3D-SIM images of the protein aggregates ( Hsp104Y662A-GFP ) and actin cytoskeleton ( Alexa fluor 568 phalloidinor Abp140-3GFP ) were taken with 100×/1 . 46 Plan-Apochromat oil-immersion objective with excitation light wavelengths of 488 nm and 561 nm . Z-stacks with an interval of 100 nm were used to scan the whole yeast in 3D-SIM . For acquisition and super-resolution processing and calculation as well as for 3D reconstruction , the Zen2011 software ( Carl Zeiss , Jena Germany ) was used . The ELYRA System was corrected for chromatic aberration in x- , y- , and z-directions using multicolor beads , and all obtained images were examined and aligned accordingly .
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Asymmetric cell division is key to cellular rejuvenation and budding yeast exploits this mode of cytokinesis to generate a young daughter cell from a mother cell that with each division grows progressively older . Thus , age physiognomies are reset in the progeny during division , a phenomenon that requires a mother-biased segregation of cytoplasmic ‘aging factors’ , including damaged/aggregated proteins . There are two models for how aggregated proteins are segregating in a mother cell-biased fashion; one holds that asymmetric inheritance is a purely passive outcome of the aggregates' random but slow diffusion whereas the other model reasons that specific factors/organelles prevent free diffusion of aggregates into the daughter cell . In the present work , we tested whether the passive diffusion model or the factor-dependent model appear most relevant in explaining asymmetrical inheritance by quantifying traits predicted to affect inheritance by passive diffusion and identifying factors required for asymmetrical inheritance amongst essential genes interacting with SIR2; a gene shown previously to be required for mother-biased segregation . We show that passive diffusion of aggregates is not sufficient to establish mother-biased segregation and that ER to Golgi trafficking , in addition to the actin cytoskeleton , calmodulin , and the Myo2 motor protein , are key components restricting the inheritance of both heat stressed-induced aggregates and aggregates formed of the Huntington disease protein Htt103Q .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"cell",
"biology",
"genetics",
"biology",
"and",
"life",
"sciences",
"microbiology",
"genomics",
"molecular",
"cell",
"biology"
] |
2014
|
Essential Genetic Interactors of SIR2 Required for Spatial Sequestration and Asymmetrical Inheritance of Protein Aggregates
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DNA adenine methylation is widely used to control many DNA transactions , including replication . In Escherichia coli , methylation serves to silence newly synthesized ( hemimethylated ) sister origins . SeqA , a protein that binds to hemimethylated DNA , mediates the silencing , and this is necessary to restrict replication to once per cell cycle . The methylation , however , is not essential for replication initiation per se but appeared so when the origins ( oriI and oriII ) of the two Vibrio cholerae chromosomes were used to drive plasmid replication in E . coli . Here we show that , as in the case of E . coli , methylation is not essential for oriI when it drives chromosomal replication and is needed for once-per-cell-cycle replication in a SeqA-dependent fashion . We found that oriII also needs SeqA for once-per-cell-cycle replication and , additionally , full methylation for efficient initiator binding . The requirement for initiator binding might suffice to make methylation an essential function in V . cholerae . The structure of oriII suggests that it originated from a plasmid , but unlike plasmids , oriII makes use of methylation for once-per-cell-cycle replication , the norm for chromosomal but not plasmid replication .
The regulatory potential of canonical DNA sequences can be greatly expanded by epigenetic modifications . Methylation is the most common modification of DNA and is widely used to control many cellular processes [1] . In bacteria , DNA methylation is restricted to adenine and cytosine residues [2] , and can facilitate or interfere with DNA-protein interactions , thereby modulating various DNA transactions [3] . Such transactions include gene expression , DNA restriction , DNA mismatch repair , and chromosome replication and segregation [4] , [5] . Most of our knowledge regarding the role of methylation in chromosome replication comes from studies in Caulobacter crescentus and Escherichia coli . In C . crescentus , initiation of DNA replication requires the adenines of the GANTC sequences in the origin of replication to be methylated on both the top and bottom strands by the methylase CcrM . How the methylation helps the origin function is not known , although methylation lowers DNA stability [6] , [7] and thereby could facilitate origin-opening , an essential step in the replication initiation process . It is also possible that the methylation changes DNA structure to facilitate protein-DNA interactions at the origin [8] . Irrespective of the mechanism , methylation not only controls the timing of initiation but also restricts initiation to once per cell cycle [9] . Following initiation , the hemimethylated sister origins cannot be reused in the same cell cycle , as the CcrM methylase is not synthesized until the end of the replication cycle . In E . coli , the methylase is called Dam and acts on the adenines of GATC sequences , which are particularly frequent in the origin of replication , oriC . In this bacterium also the methylation most likely helps in origin-opening [8] , [10] but plays a more definite role in restricting the initiation to once per cell cycle [11] . In E . coli , immediate reinitiation is prevented , not by delaying the synthesis of the methylase , but by preventing its action through sequestration of hemimethylated sister origins by a hemimethylation-specific DNA binding protein , SeqA [12] . Sequestration renders DNA unavailable to the methylase . The sequestration also allows initiation synchrony whereby the multiple origins that E . coli maintains during rapid growth fire nearly simultaneously . It is believed that the sequestration process continues at least until all the origins have fired . This happens in a narrow window of time giving rise to the initiation synchrony phenotype [13] . In the absence of Dam , the newly replicated origins , without their hemimethylation marks , remain indistinguishable from the unreplicated ones . The choice of origin for replication being random , once-per-cell-cycle initiation from each origin is no longer guaranteed . As a result , in dam mutants , the initiation becomes asynchronous and cells can have origins that do not fire at all or fire more than once in the same cell cycle . The consequences are the same in seqA mutants , because without sequestration , replicated origins also remain competent for reinitiation . The lack of discrimination between replicated and unreplicated origins can lead to origin incompatibility [14] . If extra copies of oriC are introduced as plasmids into wild type ( WT ) E . coli , the plasmid copies do not compete with the chromosomal oriC because of sequestration of newly replicated origins . Without sequestration , in dam or seqA mutants , the plasmid copies remain available for reinitiation , and under selection they can block the growth of cells in which the chromosomal origins did not get a chance to fire . Sequestration-deficient strains are therefore not easily transformed with oriC plasmids [15] . Thus , although not normally required , Dam or SeqA can be essential in a competitive situation . Vibrio cholerae has two chromosomes ( chrI and chrII ) . The origin of chrI ( oriI ) shares 58% identity with the E . coli oriC , and both have similarly high densities of GATC sites . The origin of chrII ( oriII ) also has a high density of GATC sites but has a second feature of a major class of plasmids: repeated initiator-binding sites ( iterons ) [16] . The dam gene is also essential for V . cholerae , although the reason has remained unknown [17] . Our interest in the role of methylation in V . cholerae chromosomal replication stems from the fact that although the bacterium is a close relative of E . coli , plasmids with either oriI or oriII could transform WT E . coli , but not when it lacked Dam [18] . It remained unclear whether the failure to recover transformants in the case of oriI is because the origin could not function or because of competition ( incompatibility ) with the closely related chromosomal oriC [14] , [18] . Incompatibility is unlikely the case of oriII , since it has little similarity to oriC . Moreover , while oriI and oriC are regulated by the DnaA initiator protein , oriII is regulated by its own specific initiator , RctB [19] . The reason for the Dam requirement of oriII could thus be for the functioning of the origin itself . Here we show that oriC can be replaced by oriI in the E . coli chromosome , and in this chromosomal context oriI functions without requiring Dam or SeqA . Incompatibility with the chromosomal oriC thus remains a satisfactory explanation of the earlier finding of a Dam requirement for oriI plasmids [18] . For oriII , Dam but not SeqA appears to be required as only fully methylated oriII DNA , but not hemi- or un-methylated DNA , could bind efficiently to the oriII-specific initiator RctB in vitro . Since the binding of RctB is a prerequisite for oriII function , this provides an explanation for why Dam is essential for V . cholerae , chrII being indispensable . Finally , we show that SeqA is necessary to restrict initiation to once per cell cycle for both oriI and oriII , as is the norm for chromosomal origins . Although chrII is believed to have originated from a plasmid , our findings of the methylation requirement for its initiation and cell-cycle specific regulation are unprecedented in studies of plasmids [20] , [21] . It appears that a plasmid origin acquired methylation to function as a chromosomal origin , thus providing a novel example of origin evolution in bacteria .
The E . coli origin of replication , oriC , does not require dam and seqA to initiate replication . In contrast , plasmids driven by oriC are highly deficient in transformation of dam mutants [11] . This is believed to be due to irreversible sequestration of hemimethylated plasmid origins by the SeqA protein after the first round of replication [22] . Indeed , seqA and dam seqA strains can be transformed by oriC plasmids , although the efficiency is lower compared to WT due to incompatibility with the chromosomal copy of the origin [15] . The requirement of dam thus is not intrinsic to oriC function and appears so only in the plasmid context . The dam requirement of V . cholerae oriI has so far been studied only in the plasmid context . However , in contrast to oriC plasmids , oriI plasmids not only failed to transform an E . coli dam mutant but also a seqA or a dam seqA mutant , raising the possibility that the genes could be essential for oriI [11] , [18] . We confirmed the plasmid results using E . coli MG1655 ( BR1703 ) and its dam ( CVC1415 ) , seqA ( BR1704 ) and dam seqA ( CVC1424 ) mutant derivatives . As before , the dam , seqA and dam seqA mutants could not be transformed with an oriI plasmid , and only the dam mutant could not be transformed with the oriC plasmid ( Figure 1A ) . We suggest below that the oriI plasmid possibly replicated in the absence of dam or seqA , which competed out replication from the chromosomal oriC and led to inviability of the transformants . To avoid plasmid-mediated competition ( incompatibility ) , we studied oriI by placing it in the E . coli chromosome . Using the Red recombineering system , we replaced the minimal oriC region with the corresponding oriI region ( Materials and Methods ) . The resultant strain , MG1655ΔoriC::oriI-zeo ( CVC1400 , Table 1; hereafter called MG1655ΔoriC::oriI ) , could be made dam minus by P1 transduction , using dam-16::aph ( CVC1383 ) as the source of the mutant dam allele [23] . We could also replace the oriC region of MG1655ΔseqA10 with ΔoriC::oriI by P1 transduction . The viability of dam , seqA or dam seqA mutant derivatives of MG1655ΔoriC::oriI ( CVC1401 , CVC1416 and CVC1425 , respectively ) indicates that oriI does not require Dam and SeqA for functioning in E . coli . To understand why oriI and oriC behave similarly in the chromosomal context but differently in the plasmid context , we repeated the transformation experiments using MG1655ΔoriC::oriI cells as the host . The oriI plasmid could now transform the seqA and the dam seqA derivatives of MG1655ΔoriC::oriI efficiently but not the dam derivative ( Figure 1A and 1B ) . The failure to transform the dam derivative can be attributed to permanent sequestration . In contrast to oriI , oriC not only failed to transform the dam derivative but also the damseqA derivative of MG1655ΔoriC::oriI . The results can be understood assuming initiation from oriI to be more efficient than from oriC . Most likely , the weaker oriC failed to compete with oriI in the chromosome ( incompatibility ) that led to inviability of the transformants . It is known in E . coli that incompatibility problems can be aggravated when the incoming and recipient origins have unequal efficiencies [24] . oriI and oriC were further analyzed using flow cytometry [25] . Replication initiation and cell division were blocked by antibiotics rifampicin and cephalexin , respectively , but sufficient time was allowed after drug addition to complete replication elongation ( replication run-out ) . This method provides a measure of the fraction of the population that already initiated replication at the time of drug addition . In LB , after the replication run-out , MG1655 cells were distributed mostly into two populations , one with four and the other with eight full chromosomes ( Figure 2A ) . This indicates that cells were born with four origins and they all fired synchronously once , giving rise to the eight chromosome peak . In the dam and seqA mutants , cells had a widely varying number of chromosomes indicating asynchronous initiation ( Figure 2C and 2E ) [22] , [26] . There were also cells with more than eight chromosomes indicating that initiation was no longer restricted to once per cell cycle . In the engineered strain , MG1655ΔoriC::oriI , replication initiation was synchronous ( Figure 2B ) but not in its dam or seqA derivatives ( Figure 2D and 2F ) . The requirements of dam and seqA for synchronous and once-per-cell-cycle initiation are thus maintained when oriI replaces oriC . Compared to the WT , replication initiation was less frequent in dam mutants but more frequent in seqA mutants in the case of both the origins . As is oriC , Dam seems to be playing a positive role and SeqA a negative role in replication initiation from oriI . It was reported earlier , and we confirmed , that oriII plasmids can not transform an E . coli dam mutant but can transform a seqA mutant [18] . The oriII plasmids also failed to transform the dam seqA mutant , indicating that irreversible sequestration cannot account for the dam requirement . The oriII function could not be tested in the chromosomal context , as was done for oriI , because attempts to replace oriC with oriII failed . In any event , incompatibility between oriC and oriII appears to be an unlikely explanation for the dam requirement , as the structure and control elements of the two origins are different [19] . We show below that the reason for the dam requirement could be for binding of oriII to its specific initiator RctB . A distinguishing feature of oriII is that its putative RctB binding sites , called 11- and 12-mers , all contain a GATC site . This prompted us to test whether methylation of the sites might be important for RctB binding ( Figure 3A ) . We first tested binding to the six tandem 12-mers within the minimal oriII by an electrophoretic mobility shift assay . Purified RctB bound efficiently to the 12-mer fragment , when it was fully methylated ( Figure 3B ) . The binding was nearly saturated because most of the DNA molecules were maximally retarded . Binding to hemimethylated DNA , where either the top or the bottom strand carried the methylation marks , and to unmethylated DNA was significantly less . In these cases , most of the bound species appeared as a smear , indicative of weaker binding . The binding improved when the DNA samples were remethylated using Dam in vitro ( Figure 3B ) . The binding of RctB to the three 11-mers or to a pair of 12- and 11-mers in the negative-control region of oriII was also efficient when the sites were fully methylated ( Figure S1A and S1B ) . Mutating GATC sites to GATG in the 11- or the 12-mer abolished the binding ( Figure S1C ) . These results indicate that full methylation can significantly improve the affinity of RctB to the 11- and 12-mers . To confirm these results in vivo , RctB binding to a plasmid with the six 12-mers was studied in MG1655 or its dam derivative by chromatin immunoprecipitation ( ChIP ) , and the immunoprecipitated DNA analyzed by quantitative PCR . Compared to the vector , the plasmid with the 12-mers was preferentially enriched by immunoprecipitation when the DNA samples were from WT cells ( Figure 3D ) . No significant enrichment was obtained when the DNA samples were from the dam mutant . These results show the importance of methylation for efficient RctB binding in vivo , and therefore , for replication of chrII . To test how well the results obtained in vitro and in E . coli reproduce in the native host , the dam gene of V . cholerae was deleted in the presence of a complementing plasmid , pTS-PBADdam ( pGD93 , Table 2 ) . The replication of this plasmid is temperature sensitive and the cloned V . cholerae dam gene is under the control of an arabinose-inducible and glucose-repressible promoter , PBAD . On LB plates , under the permissive condition ( 30°C and in the presence of arabinose ) , the Δdam/pTS-PBADdam strain grew as well as the WT but under the restrictive condition ( 42°C and in the presence of glucose ) , single colonies were barely visible ( Figure 4A ) . In LB broth , under the restrictive condition , the mutant grew slower than the WT ( with generation times of 27 min and 22 min , respectively ) , and the growth plateaued to an OD of 0 . 53 only ( Figure 4B ) . Moreover , the number of viable cells in the mutant culture was only 0 . 02% of the number of viable WT cells , when initially similar cultures of both were grown for seven and a half hours under restrictive conditions ( Figure 4C ) . The viable cells in the mutant all retained the dam complementing plasmid without selection for it . The results thus appear consistent with an earlier report that Dam is essential for V . cholerae [17] . Under the condition of dam depletion , we expected that initiation at oriII would decrease more than initiation at oriI . This was tested by determining the relative replication efficiencies of the two chromosomes in exponentially growing cells by qPCR . We quantified the amount of DNA at the two origins and the two termini to obtain the ratios oriI/oriII , oriI/terI , oriII/terII and terI/terII . Under the restrictive condition , there was a significant increase ( 4-fold ) in the value of oriI/oriII and of terI/terII , while the values of oriI/terI and oriII/terII remained unchanged ( Figure 4D ) . These results are consistent with our expectation that compared to chrI , replication of chrII is more dependent on Dam . The hemimethylation period , the time to remethylate a GATC site after passage of the replication fork , is particularly prolonged at oriC because of the presence of high density of GATC sites within the origin [12] . The prevalence of high density of GATC sites in both oriI and oriII ( Figure 5A ) prompted us to examine their hemimethylation period , as was done using asynchronous exponential cultures [27] , [28] . We examined the hemimethylation period of a GATC site within the origin and , for comparison , another site external to the origin ( about 300 kb away ) for each of the chromosomes . In oriI , the GATC site chosen is between DnaA boxes R3 and R4 , and in oriII , it is between the fourth and the fifth 12-mers ( arrows , Figure 5A ) . Total genomic DNA was extracted and digested with restriction enzymes whose recognition sequences overlap a GATC site and whose cleavage is inhibited when the site is fully methylated but not in one of the two hemimethylated sister sites , generated by passage of the replication fork ( Figure 5B ) . The fraction of hemimethylated ( cut ) DNA at each of the origin sites was significantly higher than at the external sites ( Figure 5C ) . The values were 11±3% and 56±8% for oriI and oriII , respectively , while at the external markers they were 4±0 . 8% and 8±3% , respectively ( Figure 5D ) . The results indicate that as in E . coli , the hemimethylation period is prolonged at the two V . cholerae origins but the duration of the period can be significantly different for the two . From the E . coli paradigm , we expected that SeqA would be required to prolong the hemimethylation periods at both the origins [22] . To test for the requirement , a partial in-frame deletion of seqA was made where the deleted region was substituted with a zeocin drug-resistance cassette , maintaining the seqA reading frame ( Figure S2A ) . The resulting gene was called ΔseqAP and the strain CVC1410 . Replication run-out experiments indicated that initiation of one or both the chromosomes has become asynchronous ( Figure S2B ) , and in this respect , V . cholerae appears to be similar to E . coli ( Figure 2A and 2E ) [22] . For the GATC site tested in oriI , the fraction of hemimethylated DNA increased from 11% in WT to 68% in ΔseqAP ( Figure 6A and 6C ) . Providing Dam or SeqA from a plasmid in the ΔseqAP background decreased the fraction of hemimethylated DNA . The decrease by providing excess of Dam was expected because it converts hemimethylated DNA to fully methylated DNA . The increase in the absence of SeqA and decrease in its presence were unexpected , if SeqA were responsible for prolonging the period . The seqA plasmid did not change the period significantly in the WT background ( Figure S3 ) . The results indicate that it is the absence of SeqA that causes the increase of hemimethylated oriI DNA , a result opposite to that found for oriC [29] . The behavior of oriII was similar to that of oriC: The fraction of hemimethylated DNA decreased from 75% in WT to 17% in ΔseqAP ( Figure 6B and 6C ) . Thus seqA effects can be opposite in different origins at specific GATC sites . It remains to be seen whether the results are site-specific or true for the entire origins . The opposite response of the GATC sites tested in oriI and oriII was also seen in a V . cholerae mutant where seqA was completely deleted ( ΔseqAT , CVC2003; Figure S4 ) . oriI also responded opposite to oriC in E . coli ( Figure 7 ) . While the percent of hemimethylated DNA at oriC dropped from 13% in MG1655 to 9% in MG1655ΔseqA10 , the values at oriI increased from 9% in MG1655ΔoriC::oriI to 25% in its ΔseqA10 derivative . These results suggest that the opposite behavior of oriI and oriC upon seqA deletion is intrinsic to the sequence context of the GATC sites tested in the two origins rather than the sequestration machinery of the two bacteria . Thus depending upon the context , SeqA can both shorten and prolong the hemimethylation period of a GATC site . Although a role of SeqA in restraining replication initiation in V . cholerae was suggested by the flow cytometry results ( Figure S2B ) , they did not allow us to distinguish whether one or both the chromosomes were affected . We used fluorescence microscopy to follow replication initiation of the two chromosomes individually . The numbers and positions of oriI and oriII were determined in WT and ΔseqAP strains of V . cholerae by the GFP-P1ParB/parS system [30] , [31] . For oriI in WT , 94% of the cells had two to four foci and the rest one or three foci , indicating synchronous and once-per-cell-cycle initiation ( Figure 8A and 8E ) . In contrast , only 45% of ΔseqAP cells showed this pattern ( Figure 8B and 8E ) . The remaining cells had five to nine foci . The significant increase in the number of cells with odd numbers of foci and more than four foci indicates that initiation is no longer synchronous and no longer limited to once per cell cycle in the absence of SeqA . The regulation of chrII initiation was also affected . While 100% of the cells in the presence of SeqA showed one to two foci ( Figure 8C and 8E ) , this was true for 83% of the ΔseqAP cells ( Figure 8D and 8E ) . The remaining cells showed three to six foci . SeqA thus contributes to synchronous and once-per-cell-cycle initiation of both the chromosomes .
Our work started by questioning the essentiality of Dam and SeqA for functioning of oriI since a similar origin , oriC , can do without them [18] . We find that the requirements are not real for oriI but were imposed due to the use of plasmids to check the origin function . When we replaced oriC in the E . coli chromosome with oriI , making it the only origin in the cell , both the dam and seqA genes could be deleted ( Figure 1 ) . Thus for the functioning of oriI and oriC , methylation is not essential but it improves chromosomal replication initiation and its control ( Figure 2A–2D ) , including the ability to tolerate extra copies of the origin in trans ( Figure 1 ) . In bacteria such as Bacillus subtilis that are naturally devoid of the methylation system , ori plasmids can exert an inhibitory effect ( incompatibility ) on chromosomal replication [32] . Methylation thus can help bacterial survival in a competitive situation . Dam plays a previously unrecognized role for oriII . It significantly promotes binding of the chrII-specific initiator , RctB , to the origin , thus possibly serving an essential function ( Figure 3 ) . Origin methylation is known to be essential for replication of C . crescentus chromosome , and of plasmids P1 and ColV-K30 in E . coli [33] , [34] , [35] . The reason is not clear in these cases , but unlikely to be for initiator binding . The initiator binding sites in these systems lack the sequences required for methylation . In contrast , RctB binding sites have an internal Dam recognition site , and methylation of the sites is required for initiator binding ( Figure 3 and Figure S1 ) . Thus , for oriII , the mechanism whereby methylation could be essential for its function and , therefore , for the bacterial survival is clear . We show that seqA is not an essential gene in V . cholerae by obtaining viable seqA deletion mutants of V . cholerae . Although earlier studies suggested the gene to be essential , the finding that both oriI and oriII could function without SeqA in E . coli encouraged us to attempt isolation of the deletion mutants [18] , [28] . In a deletion mutant , the number of both oriI and oriII per cell was found to be greater than in the WT ( Figure 8 ) . The overreplication indicates a breakdown of once-per-cell-cycle replication and reveals that SeqA is a negative regulator of replication . The latter was also concluded when the role of SeqA was studied by SeqA overproduction [28] . There was also an increase in the number of cells with odd number of origins for both the chromosomes , indicating loss of initiation synchrony . Thus , SeqA appears to contribute to both once-per-cell-cycle replication and initiation synchrony . An unexpected finding of this study is that the hemimethylation period of oriI and oriC changed in opposite ways upon seqA deletion: for oriC it decreased whereas for oriI it increased ( Figure 6 and Figure 7 ) . The decrease in the case of oriC is expected since SeqA is believed to be the key factor that prolongs the period [22] . A significant increase of the period without requiring SeqA shows that there are other ways to prolong the period , and that SeqA can play an opposite role of shortening the period . The opposite roles of SeqA were seen in isogenic strains of both V . cholerae and E . coli , suggesting that the reason cannot be due to species-specific factors ( Figure 6 and Figure 7 ) . The period also changed in opposite ways for oriI and oriII in the same seqA mutants of V . cholerae . SeqA thus has the capacity to both increase and decrease the duration of the period . SeqA binding to DNA is favored in GATC-dense areas [36] , [37] . The density of GATC sites around the diagnostic GATC site happens to be quite different in the three origins . In particular , the diagnostic site in oriI is present in a relatively isolated position ( Figure 7A ) . It is possible that the results therein might be site-specific and not representative of the entire origin . Proteins other than SeqA that interact with origins can also explain the differences in the hemimethylated periods of the origins . DnaA is known to compete with SeqA for binding to some of the sites in oriC [38] , and can significantly prolong the period even without SeqA [37] . Thus , DnaA is a likely candidate for prolonging the period for oriI in the absence of SeqA . Upon seqA deletion , although the hemimethylation period changed oppositely for oriI and oriII , both the chromosomes over-replicated ( Figure 8 ) . The prolongation of the period thus may not always be diagnostic of the role of SeqA in the negative regulation of replication . As stated above , competition with DnaA for oriI binding could be another way for SeqA to exert its negative regulatory role [38] . The correlation of the prolongation of the period and the strength of negative regulation was also poor in the case of oriII . Although , the period reduced drastically in a seqA mutant , the corresponding relaxation of replication was modest ( Figure 8 ) . In oriII , the negative control is mediated primarily by limiting RctB , which apparently makes the contribution of sequestration to regulation less significant [19] . ChrII has many plasmid-like features including the organization of its origin . Plasmids generally initiate their replication randomly in the cell cycle and control it independently of the chromosome [16] , [20] , [31] , [39] . Plasmid copy number can vary among individual cells due to replication error and unequal segregation . To maintain the mean copy number , plasmids adjust for fluctuations in copy number by replicating more in cells that receive fewer copies than the mean , and replicating less in cells with more copies than the mean . Thus , once-per-cell-cycle replication is not suited for the maintenance of plasmid copy number . We show here that unlike plasmids , chrII replicates once per cell cycle , like other bacterial chromosomes . The high density of GATC sites of oriII is not typical for plasmid origins but is a conserved feature of all sequenced strains of the family Vibrionaceae [18] . It appears that the involvement of methylation has rendered functioning of a plasmid-like origin similar to that of a chromosomal origin . Why does initiation need to be cell-cycle specific for the chromosome ? Completion of cell division demands that the septum forming area be cleared of DNA [40] . Plasmids are generally small and have correspondingly short replication elongation periods . Incompletely replicated plasmids are unlikely to cause steric hindrance to cell division for a significant period , unlike incompletely replicated chromosomes [41] . If chrII were to initiate replication randomly in the cell cycle like the plasmids , late-initiating chrII would likely delay cell division and create heterogeneity in cell generation times . V . cholerae ΔseqA cells did form elongated cells , indicative of a cell division defect ( our unpublished results ) . One reason for this could be steric hindrance to cell division from late-initiating chrII . We suggest that a chromosome replicating from an origin with a plasmid provenance is subject to selection pressure to make the initiation cell-cycle specific , and the acquisition of methylation sites could allow that . Understanding the role of methylation can also be important for another reason . It has been suggested that one of the common conspicuous features of the two origins being the high density of GATC sites , their methylation could be a mechanism to coordinate the replication between the two chromosomes [18] . Methylation is essential for the viability of bacteria with multiple chromosomes such as Rhizobium meliloti [42] , Brucella abortus [43] and Agrobacterium tumefasciens [44] in addition to V . cholerae [17] . Although there is no evidence yet for direct communication among the chromosomes for replication initiation in any system , it is possible that in these bacteria methylation could be coordinating the replication to the cell cycle , as is does for V . cholerae and possibly other members of the family of Vibrionaceae .
Bacterial strains and plasmids used in this study are listed in Table 1 and Table 2 , respectively . Primers are listed in Text S1 . E . coli and V . cholerae were grown in LB ( 10 g tryptone +5 g yeast extract +5 g NaCl per liter , pH adjusted with NaOH to ∼7 ) or M63 medium ( KH2PO4 3 g + K2HPO4 7 g + ( NH4 ) 2SO4 2 g + FeSO4 0 . 5 mg + MgSO4 . 7H2O 0 . 25 g , pH adjusted with KOH to ∼7 ) supplemented with 2 mM MgSO4 , 0 . 1 mM CaCl2 , 0 . 01% thiamine and 0 . 2% glucose , and additionally 0 . 1% casamino acids when desired . Antibiotics were used at the following concentrations: ampicillin , 100 µg/ml; chloramphenicol , 25 µg/ml for E . coli , 5 µg/ml for V . cholerae; erythromycin , 20 µg/ml; kanamycin , 25 µg/ml; spectinomycin , 50µg/ml; tetracycline , 15 µg/ml; and zeocin , 25 µg/ml . Diaminopimelic acid ( DAP ) was used at 0 . 8 mM , L-arabinose at 2 or 0 . 2 mg/ml , IPTG at 100 µM and thymidine at 0 . 3 mM . To replace oriC ( coordinates 3923756–3924022 ) with oriI ( coordinates 2961130–364 ) , the latter was amplified from DNA of CVC209 by PCR using primers GD113 and GD114 . The PCR product was digested with EcoRI and BamHI , and ligated to similarly digested pEM7-Zeo . The resulting plasmid , pGD83 , was digested with SacI and BamHI , and the fragment containing the oriI-zeo region was ligated to a similarly digested vector , pSW23 , generating pGD79 . The oriI-zeo region of pGD79 was amplified with primers GD124 and GD125 , and the product used to replace oriC of CVC1394 by the mini-λ Red recombineering method [45] . The mini-λ prophage was eliminated from the strain by a 30°C to 42°C temperature shift . The resultant strain was called MG1655ΔoriC::oriI-zeo ( CVC1400 ) , and the replacement was confirmed by sequencing of the origin region . The genomic DNA of the dam mutant derivative ( CVC1401 ) was confirmed for the absence of adenine methylation by its resistance to DpnI but not to MboI and BfuCI restriction enzymes ( data not shown ) . Cultures of E . coli were grown in LB to OD600≈0 . 2 and processed for flow cytometry after replication run-out in the presence of rifampicin ( 150 µg/ml ) and cephalexin ( 10 µg/ml ) for three hours as described [46] . The peak fluorescence intensity of an overnight grown E . coli culture in M63 + 0 . 2% glucose medium ( without casamino acids ) was taken to represent one genome equivalent . A fragment with six 12-mers was obtained from pGD61 by digestion with XhoI and NotI . Fragments with three 11-mers and a pair of 12- and 11-mers were obtained from pTVC86 and pTVC88 , respectively , by digestion with XhoI and BamHI . For methylated and unmethylated fragments , the plasmids were from a dam+ ( BR2699 ) and a dam− ( CVC1060 ) strain , respectively . The fragments were gel-purified , dephosphorylated with Shrimp Alkaline Phosphatase ( USB Corporation ) , and end-labeled with 50 µCi [γ-32P]ATP ( PerkinElmer ) by using 30 units of T4 polynucleotide kinase ( New England Biolabs ) and purified through ProbeQuant G-50 micro columns ( GE Healthcare ) . To obtain hemimethylated DNA , oligonucleotide primers , TVC64 and TVC138 ( Sigma-Genosys ) , were end-labeled and purified as above . The labeled primers were then used for PCR one at a time with methylated DNA as template for one cycle to obtain two populations of hemimethylated DNA , one with methylation on the top strand and the other on the bottom strand . The binding reactions were essentially as described [47] . A partial deletion of seqA was made by deleting codons 51 to 140 and substituting the deleted region with a zeocin cassette maintaining the seqA reading frame as follows . The seqA gene was amplified from CVC209 by PCR with primers GD87 and GD88 . The product was digested with EcoRI and cloned in similarly digested vector , pSW4426T . The resultant plasmid was used as template for PCR with primers GD91 and GD92 to amplify the 5′ end of seqA , the plasmid backbone and the 3′end of seqA . After digestion with MfeI , a site of which was present within GD91 and GD92 primers , the PCR product was ligated to the zeocin cassette . The cassette was obtained from pEM7-Zeo by PCR , using primers GD89 and GD90 and digested with EcoRI before ligating to the MfeI fragment . The resulting plasmid , pGD70 , containing the ΔseqAP::zeo allele was used to replace seqA of CVC209 by the allele-exchange method [48] . The resulting ΔseqAP::zeo mutant ( CVC1410 ) grew slower than the WT . In LB at 37°C , the doubling times of the mutant was 32±2 min as opposed to 19±2 min for the WT . The ΔseqAP::zeo allele is called hereafter ΔseqAP . The entire seqA ORF was also deleted and substituted with the zeocin cassette as follows . First , a kilobase region located downstream the stop codon of seqA was amplified by PCR with primers GD228 and GD229 , the product digested with EcoRI and BamHI and cloned in a derivate of pEM7-Zeo ( pGD111 ) , previously digested with the same enzymes , generating pGD113 . pGD111 is essentially same as pEM7-Zeo except that the multi-cloning site upstream of zeo is modified to include KpnI and NdeI restriction sites . Next , a kilobase region located upstream of the start codon of seqA was amplified by PCR with primers GD230 and GD231 , the product digested with KpnI and NdeI and cloned in pGD113 , previously digested with the same enzymes , generating pGD114 . The flanking regions of seqA , now flanking the zeocin cassette , was amplified by PCR with primers GD257 and GD258 and the linear product was introduced by natural transformation in a hapR+ Δdns derivative of N16961 ( CVC1121 ) essentially as described [49] , [50] . The transformants were selected for zeocin resistance and checked for the replacement of the seqA gene by the zeocin cassette by PCR and DNA sequencing . The resulting ΔseqAT::zeo mutant ( CVC2003 ) grew as slow as the ΔseqAP::zeo mutant with a doubling time of 32±2 min . The ΔseqAT::zeo allele is called hereafter ΔseqAT . A complete deletion of the dam ORF and its substitution with a zeocin cassette was obtained by the allele-exchange method in the presence of a complementing plasmid , pGD93 . The replication of the plasmid was thermo-sensitive and it carried the V . cholerae dam under the PBAD promoter . pGD93 was made as follows: the dam gene was amplified by PCR with primers GD72 and GD73 , and the product after digestion with EcoRI and KpnI was cloned in pBAD24 , previously digested with the same enzymes , generating pGD55 . Next , the NdeI-HindIII fragment from pGD55 containing the dam gene was cloned in pKOBEGA , previously digested by NdeI and HindIII , generating the pGD93 . For allele-exchange , a kilobase region located downstream of the stop codon of dam was amplified by PCR with primers GD261 and GD262 , and the product after digestion with EcoRI and BamHI was cloned in a derivative of pEM7-zeo , previously digested with the same enzymes , generating pGD117 . A 700 bp region located upstream of the start codon of dam was amplified by PCR with primers GD263 and GD264 , and the product after digestion with KpnI and NdeI was cloned in pGD117 , previously digested with the same enzymes , generating pGD118 . The zeocin cassette with the flanking regions of dam was amplified by PCR with primers GD268 and GD269 , and the product cloned as a blunt end fragment in pSW23 , previously digested with SmaI , generating the pGD120 . The plasmid was digested with SacI and SalI , and the fragment with the zeocin cassette was cloned into pDS132 , previously digested also with the same enzymes . The resulting plasmid , pGD121 , was used to replace dam of CVC209/pGD93 . The resulting strain , CVC2023 , was confirmed for the replacement of dam by the zeocin cassette by PCR and by DNA sequencing . To deplete Dam , single colonies grown in the presence of ampicillin ( to select pGD93 ) and arabinose ( to express dam ) were used to inoculate LB without any drug but containing glucose ( to repress dam expression ) and the cultures were grown at 42°C ( to stop plasmid replication ) . Genomic DNA was isolated from cells of log phase cultures ( OD600≈0 . 3 ) , using the Genelute Bacterial Genomic DNA kit ( Sigma ) . For analyzing chrI and E . coli DNA , 1 µg of DNA was digested 2 hours with 7 . 5 or 15 units of HphI ( New England Biolabs ) at 37°C , and the products resolved in a 1 . 5% agarose gel . For chrII , the conditions were similar except that TaqαI was used at 65°C . The origin probes were prepared by PCR using primers GD36 and GD37 for oriI , GD40 and GD41 for oriII , GD67 and GD68 for oriC , and GD150 and GD151 for ΔoriC::oriI . The primers for external markers on the three chromosomes were GD38 and GD39 , GD42 and GD43 , and GD128 and GD129 , respectively . The probes for ori and the external markers were made radioactive using the RediPrimeII random primer labeling kit ( GE Healthcare ) and [α-32P] dCTP ( PerkingElmer ) and mixed separately for the two chromosomes . The band intensities were recorded and quantified as described earlier [46] . Marker frequency was determined by qPCR using a PTC-200 Peltier Thermal Cycler ( MJ Research ) and a LightCycler 480 SYBR Green I Master ( Roche ) . Genomic DNA was prepared from log phase cultures in LB with Genelute Bacterial Genomic DNA kit ( Sigma ) , and 313 pg was used in each reaction as template . The primers were used at 0 . 3 µM each . They were proximal to either oriI ( GD136 and GD137 ) or oriII ( GD156 and GD157 ) or terI ( GD142 and GD143 ) or terII ( GD140 and GD141 ) region of the two chromosomes , and were identical to those described [39] . The primer pairs were such that they produced ∼100 to 130 bp fragments in all cases . Cp ( crossing point ) values were determined and used for calculating the oriI/oriII , oriI/terI , oriII/terII and terI/terII ratios . The ratios were normalized to those of a culture grown to stationary phase in supplemented M63 medium ( without casamino acids ) . Mean ratios were obtained from DNA prepared from three cultures , each grown from independent colonies , and each DNA was analyzed in triplicate . The method was modified from the one described by Lin and Grossman [51] . Briefly , cultures at OD600nm = 0 . 3 were treated with 1% formaldehyde at room temperature for 30 min . After cell lysis and sonication , RctB complexes were precipitated with antibody against RctB ( IP DNA ) and Dynabeads-Protein G magnetic beads ( Invitrogen ) , followed by stringent washings ( see Text S1 for the detailed ChIP protocol ) . After reversal of the cross-links by incubation at 65°C overnight , the samples were treated by protease K ( Sigma ) and then purified with a PCR purification Kit ( Qiagen ) . To quantify the enrichment of RctB binding sites in the IP DNA , 5 µl of 1∶100 dilution of the IP DNA was used to perform locus-specific real-time qPCR with primers GD218 and GD219 , specific to the vector backbone of the plasmid carrying the RctB binding sites , and primers GD191 and GD192 , specific to a gene in the E . coli genome that served as a reference , as described [52] .
|
Bacteria usually have one chromosome but can have extrachromosomal replicons , called plasmids . Although normally dispensable , plasmids can confer adaptive advantage to cells in stressful environments . Bacteria can also have multiple chromosomes , each carrying essential genes , as in eukaryotes . In all organisms , chromosomes duplicate once before the cells divide so that the daughter cells can receive equal genetic dowry , but this is not usually the case with bacterial plasmids . Vibrio cholerae , the causative agent for the disease cholera , has a typical bacterial chromosome like the chromosome of the well-studied bacterium Escherichia coli and has a second chromosome with many signatures indicating its origin from a plasmid . Here we show that , in spite of the distinct nature of the two chromosomes , they both duplicate once per cell cycle , and they both require DNA adenine methylation for this purpose . Our study suggests that once-per-cell-cycle replication is a necessary feature of a chromosome in multichromosome bacteria , and provides a paradigm of how methylation could endow extrachromosomal replicons with the capacity to duplicate like chromosomes .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"biochemistry/replication",
"and",
"repair",
"microbiology/microbial",
"evolution",
"and",
"genomics",
"genetics",
"and",
"genomics/chromosome",
"biology"
] |
2010
|
DNA Adenine Methylation Is Required to Replicate Both Vibrio cholerae Chromosomes Once per Cell Cycle
|
The unraveling and control of protein stability at different temperatures is a fundamental problem in biophysics that is substantially far from being quantitatively and accurately solved , as it requires a precise knowledge of the temperature dependence of amino acid interactions . In this paper we attempt to gain insight into the thermal stability of proteins by designing a tool to predict the full stability curve as a function of the temperature for a set of 45 proteins belonging to 11 homologous families , given their sequence and structure , as well as the melting temperature ( ) and the change in heat capacity ( ) of proteins belonging to the same family . Stability curves constitute a fundamental instrument to analyze in detail the thermal stability and its relation to the thermodynamic stability , and to estimate the enthalpic and entropic contributions to the folding free energy . In summary , our approach for predicting the protein stability curves relies on temperature-dependent statistical potentials derived from three datasets of protein structures with targeted thermal stability properties . Using these potentials , the folding free energies ( ) at three different temperatures were computed for each protein . The Gibbs-Helmholtz equation was then used to predict the protein's stability curve as the curve that best fits these three points . The results are quite encouraging: the standard deviations between the experimental and predicted 's , 's and folding free energies at room temperature ( ) are equal to 13 , 1 . 3 ) and 4 . 1 , respectively , in cross-validation . The main sources of error and some further improvements and perspectives are briefly discussed .
The understanding of the mechanisms used by nature to stabilize proteins against thermal inactivation is still an open issue of primary importance . From a theoretical perspective , such comprehension is fundamental in the study of the adaptive strategies used by the organisms to inhabit extreme environments . Due to evolution , such organisms are not only able to tolerate extreme temperature conditions , that range from less than ten degree Celsius to more than 120 , but require these conditions for their survival . The control of the thermal resistance is also important from an applicative perspective , as it would allow the optimization of a wide series of industrial , bioanalytical and pharmaceutical bioprocesses through the design and manufacture of new and more efficient enzymes [1]–[3] . In the last decades , different attempts and methods have been developed to obtain proteins of increased thermal stability . Protein engineering methods that include directed evolution methods [4]–[6] have been quite successful even if their applicability remains limited due to the intensive work required . In silico engineering approaches based on sequence conservation or free energy calculation methods have also been developed but with only partial success [7]–[12] . Recently , we developed a thermal stability prediction tool based on ( melting ) -temperature dependent statistical potentials that are derived from datasets in which only proteins with given thermostability properties are included [13]–[15] . The introduction of such potentials in the thermal stability framework is motivated by the fact that the amino acid pair interactions are temperature dependent , which means that some of them are more stabilizing than others in the high temperature regime and less stabilizing at lower temperatures ( and vice versa ) [16]–[29] . This peculiar approach allowed us to study the thermal properties of proteins without detour through their thermodynamical stability , which is advantageous since it is well known that the two types of stability are poorly correlated . Proteins use different ways to promote their thermoresistance , which can – in a first approximation – be classified in three main strategies according to the Nojima analysis [30] ( for a more recent review see also [31] ) . Let us start by introducing the stability curve of a protein , which can be described by the Gibbs-Helmholtz equation: ( 1 ) where is the free energy change associated to the folding transition from the unfolded to the native state , and the change in enthalpy and entropy measured at the reference temperature , and the change of the heat capacity across the transition . To obtain this equation , one has to fix the pressure of the system , to consider two-state transitions only , and to take as temperature independent . Usually , the melting temperature , which is the midpoint of the thermal denaturation , is chosen as the reference temperature . Eq . ( 1 ) can then be rewritten as: ( 2 ) where is the enthalpy measured at . Sometimes , the reference temperature is taken equal to , the temperature of maximal stability , which yields the equation: ( 3 ) The first strategy that a protein can use to increase its thermostability [30] is to make the enthalpy change ( ) measured at more negative . This yields an overall decrease of for all temperatures as we can see from Eq . ( 3 ) ( Figure 1 . a ) . In the second strategy , becomes less negative , which leads to an increase of through a modification of the shape of the curve ( see Eq . ( 2 ) and Figure 1 . b ) . The last strategy consists in an increase of the maximum stability temperature , , defined at the minimum of the curve , where the transition is purely enthalpic . This shifts the curve towards the high temperature region ( see Figure 1 . c ) . It is , in general , not obvious to determine which type of strategy is adopted by a given protein; often several strategies are used in combination [31] . A realistic example of stability curve is depicted in Figure 1 . d: the value of the folding free energy is plotted both for a thermostable protein , the -methyl-guanine-DNA methyltransferase from Thermococcus kodakaraensis ( Tk-MGMT ) with = 98 . 6 , and for its mesostable counterpart , the C-terminal Ada protein from Escherichia coli ( Ec-AdaC ) with = 54 . 8 , as determined experimentally in [32] . We can clearly see that in this case the three strategies are used simultaneously in the achievement of a higher thermal stability . The strategies for improving the thermal resistance of a protein sometimes also improve the thermodynamic stability , defined by the folding free energy at room temperature ( 25 ) , and sometimes not . The first strategy clearly does; for the other two strategies , it depends on the relative values of and ( see Figures 1a–c ) . It is unfortunately quite difficult to get accurate predictions of thermal stability . The results described in the literature are in general family-dependent and sometimes even contradictory [16]–[29] . Indeed , the temperature-dependent nature of the amino acid interactions makes the thermal stability analyses quite intricate and the mechanism behind it difficult to unravel . Predicting the thermodynamic stability is not easy either . There are no methods for predicting the thermodynamic stability of a given protein , with the notable exception of molecular dynamic simulations , which are however very time-consuming and not applicable on a large or medium scale . Only methods for predicting thermodynamic stability changes upon point mutations ( ) have been developed and reach good scores [33]–[43] . No predictions of the enthalpy or entropy do exist either . In contrast , the prediction of is relatively easy since it is strongly correlated to the change of accessible surface area upon unfolding [44]–[46] . In this paper we go a step further than previous analyses aiming at evaluating either , or . We indeed present a method for predicting the whole stability curve of a protein from its sequence and structure , in the temperature range that is relevant for such systems ( ) , using as main tool the temperature-dependent statistical potentials developed and tested in [13] . We would like to emphasize that this is , to our knowledge , the first prediction method that outputs the complete stability curve . To get a satisfactory performance , we used in the predictions some information about proteins belonging to the same homologous family , and more precisely their and . The predicted stability curve yields an estimation of the melting temperature , the thermodynamic stability , the temperature of optimal stability , the , as well as the enthalpy and the entropy at certain temperatures . We present our results in cross validation for a set of 45 proteins belonging to eleven homologous families ( for the list of their PDB codes [47] and their characteristics , see Table S1 of Supporting Material ) . The predicted values are compared with the experimentally determined values when available , and the different strategies used by the proteins for thermal stabilization are investigated and discussed .
In this section we describe the main tools used in this analysis , namely the statistical potentials , and how they have been optimized for the current investigation . The main steps of our approach are schematically illustrated in Figure 2 . The statistical potentials are well known since some seminal papers [48]–[50] . They are derived from the frequency of associations between certain sequence and structure elements in a dataset of experimentally determined native protein structures . Even though such potentials have been extensively and successfully used in the analysis of the thermodynamic stability of proteins , they have only recently been applied in the thermal stability context , where the temperature dependence of the amino acid interactions must be taken into account [13]–[15] . To deal with this , potentials that depend on the melting temperature were derived from different datasets in which only proteins with given thermal properties were included . Three such datasets were considered [15]: a set containing only mesostable proteins , denoted and characterized by a mean value of the melting temperature of its entries ( ) of about , a thermostable ensemble , denoted , with , and a reference set containing both mesostable and thermostable proteins , denoted , with . The list of proteins belonging to these datasets are given in Table S0–S11 and Table S13 of the Supplementary Material of [15] . From these different datasets , statistical potentials were derived using the standard formalism of the inverse Boltzmann law [13] , [14]: ( 4 ) where is the relative frequency of observation of the sequence element associated to the structure element , and and are the frequencies of observation of the sequence element and of the structure element , respectively . In this computation , corresponds either to the amino acid type of residue along the polypeptide chain , or to the amino acid types of residues and , while is either the backbone torsion angle domain of residue , as defined in [51] , or the spatial distance between the residues and . The former are called torsion potentials and the latter distance potentials . While the torsion potentials describe local interactions along the chain and are a measure of the propensity of a given amino acid to adopt certain backbone torsion angles , the distance potentials describe the tertiary interactions and measure the propensity of amino acids to be separated by a certain spatial distance . The values of the distance between two residues , defined as the distance between the geometrical centers of the heavy side chain atoms , range between 3 . 0 and 8 . 0 and were grouped into 25 bins of 0 . 2 width , with two additional bins that contain distances larger than 8 . 0 and smaller than 3 . 0 , respectively . Note that we have made the -dependence of the frequencies explicit to stress that these are computed from a dataset associated with specific thermal properties , characterized by . As a consequence , the potentials are -dependent and reflect the thermal characteristics of the dataset from which they are derived . Due to the smallness of the dataset , some techniques are required to smooth the potentials and improve their performances . A first modification that has been performed is a correction for sparse data consisting in rewriting the frequencies as [52]: ( 5 ) where is an adjustable parameter chosen to be equal to 10 for the distance potentials and to 20 for the torsion potentials ( based on preliminary tests ) , and where is equal to . This correction ensures that the potentials tend to zero when the number of observations in the data set is too small . A second trick that has been used consists , for a given bin , in summing the number of occurrences of the neighboring bins giving them a decreasing weight: ( 6 ) where is the number of occurrences in bin . Predicting the stability curve of proteins from their sequence and structure alone is quite a difficult task . To slightly simplify the problem , we focused on families of homologous proteins , and make predictions that take into account some informations from the other family members . We therefore searched the full protein set for families of homologous proteins with at least three members of known . We found 11 such families containing both mesostable and thermostable proteins . They are: -amylase , acylphosphatase , lysozyme , myoglobin , -lactamase , -lactalbumin , adenylate kinase , cell 12A endoglucanase , cold shock protein , cytochrome P450 and ribonuclease . The complete list of the 45 proteins belonging to these families is given in Table S1 of Supporting Material . Some quantities ( such as the number of residues , , etc . ) remain approximately constant inside a given family . This obviously makes the prediction method simpler to build . Such family-dependent analysis remains nevertheless quite intricate , since the thermostability properties of the proteins of a given family are sometimes very different . In order to improve the performance of our method , the datasets , and have been further enlarged by adding proteins that belong to the protein family considered but whose was estimated from their environmental temperature instead of being experimentally determined; note that the pairwise sequence identity within each set was kept below 25% to avoid biasing the potentials ( see [15] for details about the dataset construction procedure ) . Strictly speaking , this modification makes the datasets and the corresponding potentials family dependent . The folding free energy of a given protein is computed at the temperatures , and from the ( melting- ) temperature dependent potentials defined in the previous subsections . More precisely , we have: ( 7 ) ( 8 ) ( 9 ) where for the distance potentials , for the torsion potentials , and the parameters are positive real numbers . The normalization coefficient is defined as: ( 10 ) The temperatures ( , , ) correspond to the average melting temperatures of the mesostable , thermostable and average datasets . The real -dependence of the folding free energies is obviously related to these melting temperatures . However , it would be a very strong ( and obviously wrong ) assumption to suppose that the average melting temperatures and the real temperatures are equal . Rather , as will be seen in the next subsection , a scale parameter must be introduced to relate the 's to the real . The strategy for identifying the parameter values consists in maximizing the anticorrelation between the melting temperature and the difference in free energies . Indeed , has been shown to be much more correlated to the melting temperature than the folding free energy [15] . The optimization is performed on all proteins with known ( listed in Table S1 ) , excluding those of the protein family that we want to predict: ( 11 ) The subscript indicates the family-dependent nature of the coefficients since their optimization is performed without the proteins of . This avoids the overestimation of the performance , and amounts to cross validation . All the optimizations described in this paper are performed using the ordinary least square regression method implemented in Mathemetica 7 . 0 . In the next steps of the computation , we estimate the full stability curve given by Eq . ( 2 ) from the three values of the folding free energies given by Eqs ( 7–9 ) , for the set of 45 proteins from the 11 protein families . Let us assume for the moment that the -dependence is the true -dependence of the potentials . Under this assumption , the stability curve can easily be obtained: it is has the form ( 2 ) and depends on the thermodynamic quantities ( , and ) , viewed as parameters , which are identified to best fit the three data points: ( 12 ) However , this simple approach does not give accurate predictions , both because the - and -dependences differ and because the error on these three points , which are moreover quite close along the -axis , leads to large errors on the whole curve . Three different issues must be solved to get reasonable stability curves . The first issue concerns the sign of the second derivative of the curve . In a few cases ( less than 10% ) , this sign is wrong , which implies that the curve is upside-down and the protein seems unfolded in the physiological temperature range . This error is related to the fact that the three points given in Eq . ( 12 ) are too close along the axis; this is due to the limited number of known proteins with very low or very high . The shape of the curve depends thus strongly on the relative position of the average point relative to the mesostable and thermostable points and . Sometimes even a small variation of these values can lead to the inversion of the shape of the curve . To overcome this problem , we imposed a fourth point in the fitting procedure , in addition to those given in Eq . ( 12 ) . This point is taken at a temperature of 0°K , where we impose to be equal to the average of the 's of the other proteins that belong to the same family . This quantity has no physical interpretation , as the inverse bell shape of the stability curve may not be extrapolated to zero temperature; indeed , we have in reality . This trick is however quite useful to impose the correct sign of the second derivative of the curve in the physiological temperature range . This procedure has been applied when the predicted curve is upside-down , but also when the value of deviates by more than one standard deviation from the mean computed inside the family . This leads to an overall improvement of the results since it smooths out possible errors on the average point , which is amplified in the curve derivation procedure . The second issue is the determination of the overall scaling factor of the curve . When more than one value of was experimentally determined within the considered family , we fix for the protein in the family as the ratio: ( 13 ) where is extracted from the predicted curves as the coefficient of the term , is the experimental value and the sum is over the proteins belonging to excluding ; this again amounts to obtain predictions in cross validation . If only one or no values were available for the family , we took as normalization factor the mean of the values found for the other families , excluding the largest and smallest values . This is a rough approximation since this quantity is expected to be strongly family dependent . However , despite the crude approximations made , the final result shows a fair performance that will certainly improve when more data or an independent determination will be available . The last issue concerns the real temperature dependence of the potentials . Strictly speaking , the -dependence of the potentials is different from the real -dependence , even though they are obviously related . Indeed , the temperature resistant interactions can be expected to play a fundamental role in the stabilization in the high temperature regime and vice versa in the low temperature region ( see [16]–[20] for the temperature dependence of the amino acid interactions ) . The assumption that we made is that the real value at which the potentials are calculated is related to the value of by a multiplicative factor that we call , which is assumed to be different for each protein . The strategy for fixing it is the following: once the function has been estimated for all the proteins of a given family , we determined the temperature at which it is zero . We identified for a protein so as to minimize the cost function: ( 14 ) Since we are working in cross validation , the sum is over the proteins that belong to family . For a given protein , the folding free energy is thus given as .
The prediction of the mechanisms used by proteins to enhance their thermoresistance is a highly non-trivial issue . The principal mechanisms of this stabilization can be schematically described in terms of three strategies ( see Figures 1a–c ) . The first consists in a global decrease of the folding free energy at all temperatures , which automatically implies an increase of the melting temperature . The second strategy consists of less negative values of , which broadens the stability curve . In the third strategy the temperature of maximal stability undergoes a shift towards the high temperature region . It is not simple to understand which mechanism is used by each protein and if it is used alone or in combination [31] . Moreover , different proteins of the same family can reach higher thermostability through completely different mechanisms . In order to gain understanding into the thermal stability enhancement strategies and to obtain some quantitative predictions , we designed a method to predict the full stability curve of 45 proteins that belong to 11 homologous families ( see Methods section ) . The results are the 45 stability curves given explicitly in Table S3 and plotted in Figure 3 . To make the analysis quantitative , we extracted from these predicted stability curves three independent thermodynamic parameters that define the transition , namely , and at 25 , and compared them with the experimental values . For the melting temperature , the experimental values are known for all 45 entries while for the other two quantities , they are known for 17 and 16 proteins , respectively ( see Table S2 ) . We report in Table 1 the standard deviation between the computed and the experimental values , as well as the correlation coefficient between the two quantities with the corresponding P-values . Let us start with the analysis of the melting temperature whose values are simply extracted from the protein stability curves by looking for the zero of Eq . ( 2 ) , since by definition: ( 15 ) The value of the standard deviation between the experimental and the so computed 's is , in cross validation , equal to about 13 and reduces to 10 when the 10% worst predicted entries are excluded ( Table 1 ) . This value is comparable with the one found previously with a different method [15] , with the notable difference that we predict here simultaneously the whole stability curve . In Figure 4 . a , the predicted versus the experimental 's are plotted; the corresponding correlation coefficient is found to be equal to 0 . 69 ( P-value ) , and to increase to 0 . 76 upon exclusion of the 10% worst predicted proteins . We also computed the for all the proteins belonging to the eleven homologous families . In this prediction , the identification of the normalization factor defined in Eq . ( 13 ) is fundamental . Unfortunately , we do not have enough input data , i . e . experimental 's , to identify this parameter inside each family: only for 17 entries is the known , with moreover often quite large experimental errors ( of the order of 10–20% ) . When performing predictions in cross-validation , we have thus to fix independently of the other proteins of the family ( using the procedure explained in Methods ) for more than half of the entries , which inevitably gives rise the errors . The standard deviation between the experimental and the predicted values of is reported in Table 1 . It is equal to 1 . 3 ) and reduces to 0 . 8 when the two worst predicted proteins are excluded . The experimental and predicted values are plotted in Figure 4 . b; the correlation between the two quantities is equal to 0 . 92 ( P-value ) , but falls down to 0 . 41 upon exclusion of the two worst predictions . We chose as last independent quantity that can be extracted from the predicted curves the folding free energy at 25 ( ) . The considerations made in the previous paragraph about the normalization factor are valid for this quantity too and thus we cannot expect a perfect correlation between the predicted and experimental values due to the lack of data . We found indeed a standard deviation of 4 . 1 between predicted and measured 's , which reduces to 2 . 6 when the two worst predicted proteins are excluded . The correlation coefficient between the experimental and the predicted values is 0 . 4 ( P-value 0 . 05 ) and 0 . 7 upon exclusion of the two worst predictions . These results are shown in Table 1 and plotted in Figure 4 . c . A list of values of , , and predicted from the 45 stability curves , as well as the corresponding experimental values where available , are reported in Table S2 of Supporting Material . A further outcome that can be derived from the predicted stability curves is a better understanding of the strategies used within each protein family to reach a higher thermal stability . In particular , we can evaluate quantitatively the correlation between the thermodynamic and thermal stabilities: the linear anticorrelation between and ( usually taken as the descriptor of the thermodynamic stability ) is relatively high and is of the order of 0 . 7 when the two worst predicted families are excluded . The increase of the thermodynamic stability thus remains the principal mechanism for the thermal stability enhancement . The reason for this is that single amino acid substitutions can cause much easier an increase of the number of thermodynamically stabilizing interactions , such as hydrogen bonds and hydrophobic interactions , than for example a shift of the optimal stability temperature towards higher , for which more complex amino acid substitutions are in general necessary . This result , which has already been obtained on the basis of experimental data [31] , [53] , is here derived purely on the basis of our predictions . The other two mechanisms for enhancing the thermostability , discussed in the previous sections , turn out to be important too even though they show a lower correlation with the melting temperature . In particular , the shift of the maximum stability temperature has a linear correlation coefficient of about 0 . 5 with and the change in heat capacity an anticorrelation coefficient of about 0 . 3 , when excluding the two worst predicted families . These predicted values can be compared with experimental data for the few proteins for which the full stability curve has been determined and thus similar correlation coefficients between and , and between and can be computed ( see for example [53] ) . Notably , the experimental correlation coefficients and are equal to 0 . 6 and 0 . 2 , respectively , and are thus quite close to the correlation coefficient predicted by our method . The shift of towards higher appears thus to be a preferred method for enhancing the thermostability compared to the change in . In other words , the reduction of the conformational entropy in the denaturated state or its increase in the native state seems easier to achieve compared to a change of .
The full understanding of protein thermal stability remains a challenge in protein science despite the large amount of research on this topic the last decades . As a matter of fact , it is globally more intricate to understand than the thermodynamic stability . Indeed , besides the problem due to the marginal stabilization achieved by a delicate balance of opposite forces , it poses the additional – and not the least – issue of the temperature dependence of the amino acid interactions , which is barely known . We have designed a method based on ( melting ) temperature-dependent statistical potentials to deepen the thermal stability investigation . The basic idea behind this approach is simple and consists in constructing different datasets in which only proteins with given thermal properties were considered . Mean force potentials were extracted from sequence-structure frequencies computed from these datasets , following the standard statistical potential formalism , and hence reflect their thermal characteristics . They actually represent the amino acid interactions at some temperature that is related to the average of the proteins in the dataset . The folding free energy of a given protein at a given temperature was estimated on the basis of these -dependent potentials . More precisely , three different datasets with different average 's were constructed , from which three folding free energies at these 's were computed for each protein . The identification of the protein's full stability curve was accomplished by the identification of the modified Gibbs-Helmholtz equation ( 2 ) that best fits these three points . Before concluding with future perspectives , let us summarize briefly the performance of the method and the main errors that affect it . The standard deviations between the experimental and computed quantities are equal , in cross-validation , to 13 , 1 . 3 ) and 4 . 0 for the melting temperature , the and the folding free energy at 25 , respectively . These results can be considered as rather good especially if one considers the three main sources of error that we have encountered . The first source is certainly the lack of data . As already stressed in the main text and in [15] , we do not have enough experimentally resolved proteins with known to build larger datasets and thus more accurate potentials , even though we introduced some tricks to partly overcome this problem . This issue will certainly be improved when more experimental data will be available . The second source of error is related to the presence of ligands in some of the analyzed families , which contribute strongly to the protein stabilization but which we unfortunately cannot take into account with our statistical potentials . Finally , the measurement errors are sometimes quite significant , especially due to the fact that the experiments are not performed exactly in the same environmental conditions . These different issues taken together significantly increase the error on the predictions . A noteworthy result that can be deduced from our predictive approach is that the preferred mechanism for enhancing the thermostability is an increase of the thermodynamic stability , in agreement with previous results based on experimental data [31] . Unfortunately , this does not allow us to construct an accurate predictor for the melting temperature on the basis of the thermodynamic stability only [15] , since the other thermostabilizing mechanisms turned out to be important too – although to a lesser extent . Taking these other mechanisms into consideration as we did in this paper led us to a prediction method with much better performances , which we moreover hope to further improve in the near future . Furthermore , the analysis of the thermal stability optimization strategies has also shown that it is not possible to determine a unique molecular cause or a thermodynamic effect that explains the complexity of the thermal resistance modulation for the different families , since different strategies are used in combination . We would like to underline the main strength of our approach that is the possibility to predict at once all the thermodynamic parameters that characterize the protein folding transition . We can indeed predict with our method both the thermodynamic and thermal stabilities in a large temperature range . As far as we know this is the only method that is able to do that , and moreover it does so in a fast and relatively accurate way . Neither the standard statistical potential formalism nor the molecular dynamics simulations or the coarse-grained computational approaches to protein folding are able to consider explicitly the temperature dependence of the amino acid interactions and give predictions for both kinds of stabilities . However , some points of the present analysis can still be improved , and we plan to do so in a future investigation . In particular , we will try to supply to the lack of data by enlarging the dataset of proteins whose thermal properties have been measured experimentally and subdivide it in more than three subsets so as to be able to get more reliable fits of the stability curves . Two different ways can be explored to enlarge the datasets . The first consists in adding proteins with known structure but unknown melting temperature . To decide to which of the thermal ensembles these additional proteins belong , one could estimate their from the method presented in this paper or from the environmental temperature of their host organism . The other strategy consists in the use of proteins with known melting temperature , whose structures are unknown but could be obtained by comparative modeling techniques . This approach is motivated by earlier analyses that tested modeled structures for the prediction of thermodynamic stability changes upon point mutations on the basis of standard statistical potentials [54] . Indeed , predictions applied on modeled structures have been shown to undergo a surprisingly small accuracy loss compared to experimental structures owing to the coarse-grained structural representation on which the potentials are based . This finding lets foresee an increase of the overall accuracy of our prediction method due to the enrichment of the datasets with modeled structures . But it also foreshadows the applicability of the resulting prediction method to low-resolution or modeled structures , with good performances . This undoubtedly increases the potentialities and interest of our approach . We expect the enlargement of the datasets to play an important role in the reduction of the prediction errors , since it will allow us to define more than three datasets and thus to compute the folding free energies of a target protein at more than three different temperatures . This should definitely reduce the consequence of the errors on the predicted points in the -plane when fitting the stability curve through those points . Moreover , larger datasets will allow us to consider more types of statistical potentials ( for example potentials that depend simultaneously on amino acid types , interresidue distances and backbone torsion angle domains [52] ) , which are now forbidden for statistical significance reasons . Note finally that the current version of our prediction method is family-dependent , as the datasets vary slightly from one family to another and the optimization of some parameters is performed inside the families ( see Methods section ) . We would like to stress that this procedure does in no way bias the predictions . All our tests are indeed performed in pure cross validation . Rather , this procedure improves the predictions by exploiting relevant information that characterizes the homologous families . Another promising improvement of our prediction method , which would make it applicable to any target protein of known structure , consists in extending the current version without too much accuracy loss to the more general case that ignores any reference to homologous proteins . In conclusion , although there is still room for improvements and generalizations , our approach has opened a novel and original way for designing fast and accurate predictors of protein stability at different temperatures .
|
The prediction of protein stability remains one of the key goals of protein science . Despite the significant efforts of the last decades , faster and more accurate stability predictors on the proteomic-wide scale are currently demanded . The determination and control of protein stability are indeed fundamental steps on the path towards de novo design . In this paper we develop a method for predicting the stability curve of proteins . This curve encodes the temperature dependence of the folding free energy ( ) . Its knowledge is important in the study of protein stability since all the thermodynamic parameters characterizing the folding transition can be extracted from it . Our prediction method is based on temperature-dependent mean force potentials and uses the tertiary structure of the target protein as well as the melting temperature ( ) and the heat capacity change ( ) of some other proteins belonging to the same family . From the predicted stability curves , the , the and the at room temperature can be inferred . The predictions obtained are compared with experimental data and show reasonable performances .
|
[
"Abstract",
"Introduction",
"Methods",
"Results",
"Discussion"
] |
[
"biochemistry",
"proteins",
"protein",
"structure",
"biology",
"and",
"life",
"sciences",
"computational",
"biology",
"biophysics"
] |
2014
|
Stability Curve Prediction of Homologous Proteins Using Temperature-Dependent Statistical Potentials
|
Modifiers of Mendelian disorders can provide insights into disease mechanisms and guide therapeutic strategies . A recent genome-wide association ( GWA ) study discovered genetic modifiers of Huntington's disease ( HD ) onset in Europeans . Here , we performed whole genome sequencing and GWA analysis of a Venezuelan HD cluster whose families were crucial for the original mapping of the HD gene defect . The Venezuelan HD subjects develop motor symptoms earlier than their European counterparts , implying the potential for population-specific modifiers . The main Venezuelan HD family inherits HTT haplotype hap . 03 , which differs subtly at the sequence level from European HD hap . 03 , suggesting a different ancestral origin but not explaining the earlier age at onset in these Venezuelans . GWA analysis of the Venezuelan HD cluster suggests both population-specific and population-shared genetic modifiers . Genome-wide significant signals at 7p21 . 2–21 . 1 and suggestive association signals at 4p14 and 17q21 . 2 are evident only in Venezuelan HD , but genome-wide significant association signals at the established European chromosome 15 modifier locus are improved when Venezuelan HD data are included in the meta-analysis . Venezuelan-specific association signals on chromosome 7 center on SOSTDC1 , which encodes a bone morphogenetic protein antagonist . The corresponding SNPs are associated with reduced expression of SOSTDC1 in non-Venezuelan tissue samples , suggesting that interaction of reduced SOSTDC1 expression with a population-specific genetic or environmental factor may be responsible for modification of HD onset in Venezuela . Detection of population-specific modification in Venezuelan HD supports the value of distinct disease populations in revealing novel aspects of a disease and population-relevant therapeutic strategies .
Huntington's disease ( HD; MIM 143100 ) , a familial neurodegenerative disorder characterized by progressive movement disorder , cognitive decline , and psychiatric disturbances , is caused by an expanded CAG glutamine codon repeat in HTT , which encodes huntingtin [1–3] . This genetic defect was originally mapped to chromosome 4p16 . 3 using linkage analysis in part in Venezuelan families from an HD population cluster whose generous participation in this fundamental HD genetic research also contributed , along with many North American and European families also carrying a CAG expansion mutation , to the discovery of HTT [3–6] . The HTT repeat is polymorphic in the normal population [7] , but inheritance of >35 CAGs can lead to HD , while repeats of >40 CAGs are fully penetrant within a normal lifespan [8 , 9] . Expanded repeats show frequent germline instability so that HD individuals may not have a CAG repeat length identical to their transmitting parent [10–12] . Rare de novo cases of HD are generated sporadically in the population by intergenerational expansion of a normal length CAG repeat [13 , 14] . The length of the inherited HTT CAG repeat is the primary determinant of the age at onset of diagnostic neurological signs , accounting for ~65% of the variance in this phenotype , with longer repeats leading on average to earlier clinical manifestations [7 , 15–18] . Individuals with biallelic HD mutations ( i . e . , HD homozygotes ) have been reported and support complete dominance with respect to the pathogenic mechanism leading to disease manifestations since the age at onset of an individual with two expanded HTT CAG repeats is comparable to that of a heterozygote with the longer of the two repeats [7 , 19] . Interestingly , based upon one report , despite an age at onset similar to HD heterozygotes , individuals with two expanded HTT CAG repeats may display more rapid decline in functional capacity [20] . Although the timing of disease onset is CAG repeat size-dependent , the duration of manifest disease ( i . e . , the length of time from onset to death ) is not [21] , suggesting that progression to death involves different tissues or mechanisms than those leading to clinical onset . The relationship between CAG repeat size and HD clinical onset has played an important role in guiding 1 ) the generation of animal models [22–26] , 2 ) design/interpretation of molecular studies [27] , and 3 ) identification of genetic modifiers [28] . The extensive accumulated experimental data and complete dominance of the mutant allele are most consistent with a gain-of-function mechanism , which has prompted exploration of mutant allele-specific interference with HTT expression as a treatment option [29] . Although highly promising in model systems , gene-targeting approaches are just now beginning human trials of safety and efficacy . An alternative strategy for the identification of therapeutic targets is to capitalize on observations from humans with HD to discover naturally occurring modifiers of disease . Although CAG length accounts for a significant proportion of the variance in HD age at onset [15 , 16 , 18] , each CAG repeat size in the HD population is associated with a wide range of onset ages [7] . Since individual differences between the observed age at clinical onset and the age at clinical onset expected based upon the size of the mutation ( i . e . , residual age at onset ) are partially heritable [30 , 31] , both genetic and environmental factors are thought to influence the timing of onset in addition to CAG length [32] . The HD-associated CAG expansion sits on diverse haplotypes [33–38] , reflecting multiple independent mutation events on different polymorphic chromosome backbones . However , none of the most frequent disease chromosome haplotypes is associated with a difference in age at onset [34] , arguing that HD is not commonly modified by a common cis genetic factor at HTT . Similarly , age at diagnostic motor onset of HD is not influenced by the length of the normal CAG repeat [7 , 32] , or by the presence of a second mutant allele [7] , suggesting that heritable variance in age at onset for a given CAG repeat is largely due to unlinked trans factors [39] . To identify these , we performed an initial genome-wide association ( GWA ) analysis in HD subjects of European descent that revealed the first set of genome-wide significant loci associated with residual age at onset of motor symptoms . Briefly , there were two independent onset modification signals on chromosome 15 [28] , one modification signal on chromosome 8 [28] , and one modification signal on chromosome 3 [40] . Two of the modifier loci acted to delay onset and two acted to hasten onset [28 , 40 , 41] . These findings established the proof-of-principle that the pathogenesis of HD can be altered prior to emergence of clinical disease . Consistent with single SNP analysis results , pathway analysis supported a role for DNA repair/maintenance pathways in modifying the age at onset of HD , suggesting that somatic size changes of the CAG repeat may play a role in modification of the HD pathogenic process that leads to diagnostic clinical signs [28] . Together , these observations demonstrated that genetic factors in humans are capable of modifying the rate of HD pathogenesis prior to diagnosis and point to an approach based upon such human observations for therapeutic targeting to delay HD onset . Most genome-wide analyses to date have focused on Europeans , providing important but potentially limited insights into the genetic contribution to disease risk and normal traits ( GWAS Catalog; https://www . ebi . ac . uk/gwas/ ) . Our initial European HD GWA study [28] was highly successful in revealing significant modifier loci of relatively strong effect based upon a smaller sample size than most common disease genetic risk studies ( GWAS Catalog; https://www . ebi . ac . uk/gwas/ ) . However , we might have missed genetic modifiers not present in Europeans . Here , we have extended our genetic analysis to the Venezuelan HD cluster of non-European HD subjects to: 1 ) determine the full sequence of HTT on the chromosome bearing the CAG expansion mutation; 2 ) to investigate its origin , and 3 ) to determine whether modification of age at onset in this Venezuelan population is associated with specific naturally occurring genetic factors .
From 1979 to 1999 , an interdisciplinary team of investigators annually visited Venezuela to solicit the participation of a large cluster of HD families in research , to document their disease and to obtain blood samples for DNA analysis and preparation of lymphoblastoid cell lines , which were banked for future studies . These HD families contributed to both the localization of the HD defect to chromosome 4 and to discovery of HTT and its expanded CAG repeat mutation [3–6] . In 2004 , a publication summarizing more than two decades of work by the U . S . –Venezuela Collaborative Research Project described this HD cluster and presented evidence for both genetic and environmental modifiers of HD [30] . For the current study , we prepared DNA from lymphoblastoid cell lines banked prior to 1999 that had relevant clinical and/or relationship information recorded . In all , we genotyped 443 HD and 106 related non-HD Venezuelan subjects using the Illumina Omni2 . 5 array platform [28] and performed genome-wide imputation using the Michigan Imputation Server ( https://imputationserver . sph . umich . edu/index . html ) with 1000 Genomes Project data ( mixed population ) as the reference panel . After quality control ( QC ) analysis , 374 HD subjects carrying adult onset HD CAG repeat sizes ( CAG 40–55 ) with recorded age at onset of motor symptoms were analyzed in this study . Ancestry of subjects was characterized by comparing to 1000 Genomes Project data ( S1 Fig; open black squares represent Venezuelan study subjects ) , which confirmed the strongest similarity with Columbians ( pink square ) and Puerto Ricans ( pink cross ) . In addition , familial relationships were inferred based upon estimated IBD from the genome-wide genotype data ( S2 Fig ) , revealing that subjects were from 22 families of quite variable size ( S3 Fig ) . The largest family , arbitrarily termed Family 1 , comprised 218 HD individuals with the HD mutation on hap . 03 , which matches the third most frequent disease chromosome in European HD subjects ( S3 Fig ) [34 , 38] . Many of the smaller families ( e . g . , Family 6 and Family 12 ) also carry hap . 03 and appear to be distantly related to members of the main family , consistent with pedigree reconstruction by the U . S . -Venezuela Collaborative Research Project ( S3 Fig ) . However , the expanded HTT CAG repeats in some smaller families occur on different HTT haplotypes , including hap . 01 ( the most frequent European HD haplotype ) , hap . 02 , hap . 06 , hap . 07 and hap . 12 [34 , 38] , indicating that most but not all HD chromosomes in the Venezuelan cluster are ancestrally related . The mean CAG sizes across all haplotypes among the Venezuelans were 45 . 9 and 19 for longer and shorter alleles , respectively , and the average age at onset was 35 . 5 ( S4 Fig ) . The expected decrease in onset age with increasing repeat length was readily observed in this data set ( Fig 1A ) . Notably , 12 subjects carried two expanded alleles ( Fig 1A; red circles ) , and , as predicted from our previous European-based analysis [7] , their ages at onset were best explained by the longer allele in each individual ( Fig 1A; shorter allele p-value in a regression analysis , 0 . 111 ) , supporting full dominance . Interestingly , as noted previously [32] , the age at onset of Venezuelan HD subjects was distinctly earlier than that in European HD subjects ( Fig 1B; ~5 years earlier ) . While such a difference could theoretically occur due to systematic biases in calling motor onset in different countries/study populations , we believe this is unlikely because the Venezuelan HD subjects show a disease duration ( the time interval between onset and death , which is CAG-independent ) indistinguishable from European HD ( Fig 1C; Wilcoxon test p-value = 0 . 2783 ) [21] . The consistency of mean disease duration across populations [21 , 42] argues that the earlier disease diagnosis for Venezuelan HD subjects does not represent a systematic calling of the diagnosis earlier in the disease process , which would result in longer durations , but rather truly reflects a more rapid CAG-dependent disease pathogenesis leading to motor onset . Among European HD subjects , residual age at onset ( i . e . , observed age at diagnostic motor onset minus expected age at onset based on individual CAG repeat size ) was not different between HD subjects carrying different common haplotypes [34] , and the HTT locus did not emerge as associated with this phenotype in our GWA study of variations of >1% allele frequency [28] . For example , as summarized in Fig 1B , age at onset of European HD subjects with hap . 01 ( the major European disease haplotype , blue circles ) is very similar to that of European HD subjects with hap . 03 ( blue triangles ) . Similarly , although based on a small number of samples , the most frequent Venezuelan haplotype hap . 03 disease chromosomes ( red triangles ) did not appear to be consistently associated with earlier age at onset compared to Venezuelan hap . 01 disease chromosomes ( red circles ) . These data suggest that the striking difference in age at onset between European HD and Venezuelan HD subjects is not likely to be due to a cis-factor on the hap . 03 HTT haplotype . To more directly assess the possibility that the HD-associated Venezuelan hap . 03 chromosome carries novel genetic variations in HTT that are responsible for earlier onset than in Europeans , we determined the HTT genomic sequence by whole genome sequencing of a representative nuclear Venezuelan HD family from Family 1 ( S1 and S5 Figs ) , carrying hap . 03 as the mutant haplotype . This nuclear family comprises 2 parents and 7 offspring ( S5 Fig ) , so independently phased sequences of each trio ( S6 Fig ) were merged to define the consensus allele of the mutant HD chromosome at each site ( Fig 2A ) . Except for some repeat regions and a small number of inconsistent sites ( S6 Fig ) , the sequence analysis determined 99 . 02% of HTT bases of the Venezuelan hap . 03 HD disease chromosome ( Fig 2 ) . Compared with the hg19 reference sequence ( chr4:3066408–3255687; hg19 coordinates ) , the Venezuelan hap . 03 disease chromosome carries alternative alleles at 28 variable sites , including a novel SNP ( rs966032869 in intron 56 ) that was not described previously in public databases ( Fig 2A ) . None of the variants at sites where Venezuelan hap . 03 HD subjects carry non-reference alleles: 1 ) changes an amino acid , 2 ) is located in a splicing site , or 3 ) is associated with altered HTT mRNA expression levels ( based on GTEx portal; https://www . gtexportal . org/home/ ) . Additional Sanger sequencing analysis of HTT exon 1 revealed that the affected parent of this family ( S5 Fig ) carries a typical codon configuration in the polyglutamine/polyproline region consisting of 45 pure CAGs , 1 CAA , 1 CAG , and downstream elements of 1 CCG , 1 CCA , 7 CCGs , and 2 CCT codons ( Fig 2B ) . These data collectively add to the argument that variations at the HTT locus are not likely to underlie the earlier age at onset in the Venezuelan HD subjects and suggest that this difference from European HD subjects may instead be due to unknown Venezuela-specific genetic and/or environmental factors [32] . Our full sequence data provide an unprecedented opportunity to assess the origin of the CAG expansion mutation currently shared by most subjects in the Venezuela HD cluster . Consequently , we compared the full HTT sequence of the Venezuelan hap . 03 HD chromosome to European hap . 03 disease chromosomes from HD subjects with Northern European , Spanish , and Portuguese ancestries ( S7 Fig ) . The European hap . 03 HD chromosomes do not differ from each other and are identical to the Venezuelan hap . 03 HD chromosome at all but 2 sites: the novel SNP ( rs966032869 ) and one annotated rare SNP ( rs192188940 ) ( S7 and S8 Figs ) . Interestingly , examination of these sites in a Brazilian HD subject carrying hap . 03 revealed identity with the European hap . 03 , supporting an independent origin of the Venezuelan hap . 03 HD chromosome . Next , we compared the Venezuelan HD hap . 03 sequence to 1000 Genomes Project data ( Phase 3 ) to identify normal control subjects who may have identical sequences . Among various populations in the 1000 Genomes Project data , including Africans , Ad Mixed Americans , East Asians , Europeans , and South Asians , only one Mexican individual ( NA19774 ) has sequence identical across 5864 comparable variation sites to the Venezuelan hap . 03 disease chromosome , including at rs192188940 but excluding the novel SNP , rs966032869 . The presence , but extreme rarity ( MAF<0 . 001 based on UCSC Genome Browser ) of rs192188940 on both normal chromosomes in the general population and on the Venezuelan hap . 03 HD chromosome is most consistent with the CAG expansion mutation having occurred on a normal hap . 03 chromosome that already carried the minor allele of this SNP . This normal chromosome may also have carried the rs966032869 minor allele or the latter may have arisen as a private mutation after CAG expansion . In any event , the most parsimonious explanation is that the major HD chromosome in the Venezuelan HD cluster arose by an ancestral CAG expansion event distinct from that associated with the common European hap . 03 haplotype , potentially in an individual already geographically located in South America . We recently reported for the major European HD haplotype , hap . 01 , that an allele-specific CRISPR/Cas strategy based upon pairs of PAM site-altering SNPs could be used to inactivate the mutant HTT allele while leaving the normal HTT allele intact [43] . To provide the basis for future exploration of this potential therapeutic approach to benefit the Venezuelan HD population , we capitalized on the full sequence data to reveal variation sites suitable for mutant allele-specific silencing in this CRISPR/Cas strategy . Comparison to the haplotype most common in the normal population ( i . e . , hap . 08 haplotype in 1000 Genomes Project , Phase 3 data ) revealed Venezuelan hap . 03-specific NGG CRISPR/Cas9 PAM-sites . For example , two CRISPR gRNAs depending on PAM-sites generated by rs2857935 and rs7659144 on the Venezuelan hap . 03 would result in excision of the transcription start site and first two exons of the mutant gene , completely preventing generation of mutant HTT mRNA ( S9 Fig; red arrows ) . This sequence-based precision medicine strategy holds promise for HD and other dominant disorders [43] , and the definition of CRISPR/Cas PAM sites specific to hap . 03 ensures that if substantial social , political , logistical and financial hurdles are overcome the development and consequent benefit of completely allele-specific gene targeting treatment strategies need not be limited on scientific grounds to European populations but could be extended to the Venezuelan HD cluster . Population stratification makes a genome-wide approach to identify genetic factors that are responsible for the earlier age at onset in combined Venezuelan and European HD subject cohorts problematic . However , the broad distribution of age at onset within the Venezuelan HD cohort does allow for statistical investigation of genetic modifiers present within this population using a GWA strategy . Consequently , we set out to identify genetic modifiers of HD in the Venezuela cluster by modeling residual age at diagnostic onset as a function of a SNP genotype and other covariates in linear mixed effect models to correct for familial relationships . Residual age at onset represents the difference between observed age at onset and expected age at onset predicted from CAG repeat size in this population ( Fig 1B , red line ) , thus reflecting the degree of modification of onset age by factors other than CAG repeat size ( S10 Fig ) . In a GWA analysis of 374 Venezuelan HD individuals ( Fig 3; S11 Fig ) , we observed one genome-wide significant modifier locus on chromosome 7 ( Fig 4 ) and loci of suggestive significance on chromosomes 4 ( S12A Fig ) and 17 ( S12B Fig ) . Considering the small sample size in our genetic analysis , detection of genome-wide significant signals was surprising , although common modifiers may show stronger effect sizes than typical common disease risk alleles in GWA studies [28] . In any event , additional analyses argue against statistical inflation ( S11 Fig ) . Interestingly , the chromosome 7 locus that shows genome-wide significant association signals in the Venezuelan HD subjects ( Fig 4A ) was not significantly associated with residual age at onset in European HD subjects ( Fig 4B ) . The same is true for suggestive significant loci on chromosomes 4 and 17 . The top SNP at the chromosome 7 locus , rs12668183 , is associated with a -2 . 8 year effect size per minor allele in Venezuelan HD , but no effect in European HD subjects ( Fig 4C; S13 Fig ) , indicating population-specific modification of HD . Intrigued by this , we performed genetic modification score analysis using a polygenic risk score method to compare these HD populations . Based upon association analysis results from European HD subjects [28] , we constructed a polygenic modification scoring routine using effect sizes of 44 independent suggestive SNPs ( p-value < 0 . 00001 ) and the number of effect alleles of scoring SNPs . Then the same scoring method was applied to the training set ( European HD subjects ) and the Venezuela test set to judge how well the European-based HD modification score explains phenotypic variance in the Venezuelan HD cluster . As anticipated , the European polygenic modifier score explained a significant amount of variation in residual age at onset among European HD subjects ( S14A Fig; modifier score p-value < 2E-16; R-squared , 19 . 9% ) . However , the modification score did not explain the variance in residual age at onset in the Venezuelan HD subjects ( S14B Fig; modifier score p-value , 0 . 75; R-squared , 0 . 03% ) . Consistent with the chromosome 7 modification signals , this difference may reflect a major contribution of population-specific factors to modification of HD . The genetic modifier signals previously discovered on chromosomes 15 , 8 and 3 in the larger European HD GWA study [28] were not detected in the Venezuela HD GWA sample ( Fig 3 ) . This is likely due to the reduced power of the much smaller Venezuela HD sample . Indeed , the association signals at those loci that were genome-wide significant in European HD subjects ( both rare and common modifier signals ) were modestly improved by adding Venezuelan HD subject data into the meta-analysis ( Fig 5A ) , consistent with these known HD modifiers also acting to modify HD in Venezuelans . For example , on chromosome 15 , when meta-analysis was performed to combine European HD data and Venezuelan HD data , the overall association signals were improved , revealing the strongest modification signal at the SNP rs150393409 , a predicted deleterious missense alteration in FAN1 that is likely to be the functional variant responsible for modification ( Fig 5B ) . Effect sizes for this SNP were similar between the two populations ( -6 . 4 and -5 . 5 years/minor allele , respectively ) ( Fig 5C ) . Together , our association analysis results indicate that there may be both population-shared and population-specific modifying genetic factors that influence the rate of pathogenesis in HD . Focusing on the Venezuelan-specific modification signals on chromosome 7 , the top SNP in this region , rs12668183 , is common in all 1000 Genome Project populations with minor allele frequencies ranging from 30% in Europeans and 35% in the Ad Mixed Americans to 46% in East Asians . When SNPs in this region were conditioned by rs12668183 , no SNPs remained significantly associated ( Fig 4D ) , indicating that the significant SNPs all tag a single modifier effect . The association signals were not contributed by CNV since the frequency of CNV in the region was very low ( S15A Fig ) and when samples carrying CNV were excluded from the analysis , association signals were virtually unchanged ( S15B Fig ) . The association signals were not solely contributed by Family 1 , since association analysis based separately on this family and on all other families as a group generated similar significance levels ( S16 Fig ) , suggesting roughly equal contributions to the overall association signals . The association signals also were not due to skewing of the quantitative analysis by a few inaccurately phenotyped individuals since dichotomous analysis comparing allele frequencies of extreme residual age at onset groups was consistent with the continuous QTL GWA analysis result ( S17 Fig ) . The associated SNPs tagged a single modifier haplotype at SOSTDC1 ( Fig 4 ) , which encodes a member of the sclerostin family ( https://www . ncbi . nlm . nih . gov/gene/25928 ) that functions as a bone morphogenetic protein ( BMP ) antagonist , and plays a role in signaling during cellular proliferation , differentiation , and programmed cell death [44–47] . Each minor allele of the top SNP was associated with a hastening of onset by 2 . 8 years compared to those homozygous for the major allele . The most significant SNPs associated with HD age at onset are located just 3’ to SOSTDC1 , and also show significant eQTL ( expression quantitative trait loci ) signals for SOSTDC1 in the GTEx data set ( http://www . gtexportal . org/home/eqtls/byGene ? geneId=sostdc1&tissueName=All ) ( Fig 6 ) whereas none of these SNPs show evidence of association with expression of any of the other genes in the region . Interestingly , the minor alleles of SNPs most significantly associated with modification of HD onset are associated with reduced expression of SOSTDC1 in some GTEx tissues ( e . g . , ovary , artery-tibial , thyroid ) ( Fig 6A ) but not with increased expression ( Fig 6B ) . This relationship supports the hypothesis that the accelerated onset of HD caused by this modifier locus is due to reduced levels of SOSTDC1 .
Investigation of haplotypes in HD subjects , including family members from the large Venezuelan HD cluster and many families from North America and Europe , originally permitted delineation of the chromosomal localization of the HD mutation [4–6 , 35] , and ultimately led to identification of the cause of the disease [3] . The most frequent HTT haplotype on HD chromosomes , currently named hap . 01 [34 , 38 , 48] and defined by a standard panel of frequent SNPs , accounts for the largest proportion of HD subjects of European ancestry [34 , 37 , 38] , but CAG expansions also occur on a variety of other haplotypes [33–38] , indicating that multiple mutational events have produced HD and emphasizing the unstable nature of HTT CAG repeats [16 , 24 , 49 , 50] . The third most frequent HTT disease haplotype among HD subjects throughout Europe is hap . 03 . Consistent with our observation of a Brazilian subject with a hap . 03 HD chromosome comparable to that in Northern European , Spanish and Portuguese subjects , HTT CAG expansion mutations of HD subjects in Latin America have been hypothesized to be of European origin [51] . However , sequence differences on the Venezuelan HD cluster hap . 03 disease chromosome are most consistent with an independent origin of their HD mutation , possibly due to CAG expansion in an individual in South America . With the full sequence of the Venezuelan HD chromosome now available , a finer definition of the origin of this disease mutation may ensue from the accumulation of more extensive genomic data from geographically defined normal populations . Similar studies of other geographically separated HD clusters could also provide further insights into how normal range CAG repeats expand into the disease-causing range , the emergence of new cases of HD and genetic anticipation . The discovery of the cause of HD made possible the generation of model systems [22] and numerous hypotheses regarding disease mechanisms have subsequently been raised [1 , 9] . However , many mechanism-based therapeutic targets that were highly efficient in animal models have turned out not to be effective in humans [52 , 53] , perhaps due to species-specific differences in the effects of , or in the response to , the HD mutation or to the use of extreme CAG repeat lengths in most models . An alternative route to developing rational treatments is to capitalize on the genetic information that can be obtained from studies of human HD subjects . We have pursued two distinct directions in this regard , both of which are augmented by our findings concerning the Venezuelan HD cluster . The most readily definable therapeutic target in HD is the mutant gene itself , since elimination of its expression would remove the factor that ultimately precipitates all aspects of the disease . Our previous sequence analysis of hap . 01 , the major European haplotype , enabled us to develop allele-specific CRISPR/Cas targeting strategies [38 , 43 , 48] to inactivate the mutant HTT allele without damaging the normal HTT allele , providing a novel route to developing a treatment . The full sequence of the Venezuelan hap . 03 HD chromosome and consequent definition of mutant allele-specific CRISPR/Cas9 PAM sites supports this same approach , ensuring that further therapeutic development of these allele-specific inactivation strategies need not be limited on scientific grounds to European HD subjects , but , if societal hurdles were overcome , could also benefit those in the Venezuelan HD cluster who have contributed so much to HD research . We have also reasoned that more traditional pharmaceutical development for HD could benefit from rational , in-human validated , therapeutic targets discovered by identifying genes that act to significantly modify disease pathogenesis in the subjects themselves . The well-established inverse relationship between CAG repeat length and age at clinical onset of HD pointed both to the CAG repeat size as the driver of the rate of HD pathogenesis and to a role for genetic and environmental factors in modifying the impact of the CAG repeat [7 , 15–18 , 30–32 , 54] . Our haplotype analyses indicated that other genetic variations at HTT are not a common source of HD modification [34] , yet the variance in age at onset at any given repeat length is large and heritable , so we pursued a GWA analysis of subjects of European ancestry to discover significant unlinked modifiers of the age at clinical onset . The most significant locus hastens onset by approximately 6 years per rare allele demonstrating that quite strong modifier effects are possible in humans [28] . These modifier effects are due to naturally occurring variations in particular genes and pathways , and it can be expected that pharmaceuticals developed to target the same pathways could have even larger effects . Our initial European HD GWA analysis and follow-up study highlighted the importance of DNA maintenance/repair pathways in modifying the rate of CAG-dependent HD pathogenesis and suggested that somatic instability of the CAG repeat accelerates the disease [28 , 40] . While we saw some evidence that these processes also act to influence HD onset in Venezuela , a much stronger result from our unbiased genetic study of Venezuelan HD subjects points to a different modifier process . The genome-wide significant modification signals are focused at SOSTDC1 ( sclerostin domain containing 1 ) whose protein product functions as a bone morphogenetic protein ( BMP ) antagonist [46 , 55] and therefore negatively regulates BMP signaling . The expression of this gene is altered in various cancers [45 , 56–58] . The locus is also associated with lipid-lowering in response to statins [59] ( https://www . ebi . ac . uk/gwas/ ) , providing a clear example of a phenotype determined by gene-environment interaction . Compared to European HD , the Venezuelan HD subjects display a similar CAG size/age at onset relationship , and full dominance of the longest CAG allele , but at equivalent CAG sizes , they develop motor symptoms earlier , suggesting the potential for population-specific genetic or environmental influences that accelerate HD pathogenesis . Our GWA analysis appears to have detected one such locus , whose combination of high allele frequency ( 38% ) and large effect size ( almost 3 years earlier onset per minor allele ) made it detectable at genome-wide significance in only a few hundred Venezuela subjects . Population-specific modifiers of a disease have been reported only rarely in the literature [60] but examples of population-specific disease risk association are reported frequently [61–67] . Population-specific studies can therefore provide deeper insights into genetic architecture of human traits and diseases , although the relative contribution of population-specific variants , gene-gene interactions and gene-environment interactions has not been fully assessed . The fact that the chromosome 7 HD modifier locus does not yield evidence of modification in European HD suggests that the modifier effect is due either to a Venezuela-specific functional variant at the locus or to interaction of the locus with some genetic or environmental feature specific to the Venezuelans . Assessment of the former possibility will require detailed sequence comparison and functional dissection of the locus , but the observation that the top SNPs are also associated with reduced expression of SOSTDC1 in non-Venezuela data suggests that the second alternative is also worthy of consideration . Our data are consistent with the possibility that reduced expression of SOSTDC1 in individuals carrying the chromosome 7 modifier haplotype interacts with a population-specific factor to modify HD in Venezuela . A role for shared environmental factors in influencing age at onset in the Venezuelan HD cluster has been proposed previously [32] and in an initial assessment of potential genetic interaction involving the chromosome 7 locus , we detected suggestive signals ( S18 Fig ) that might reflect functional genetic interaction . Identification of the Venezuela-specific factor at the chromosome 7 locus , at an interacting locus , or in the environment that contributes to the modifier effect could yield insight into the mechanism of HD and provide another route to treatment that might be applicable in both the Venezuelan and other HD populations . Interestingly , SNPs whose alternative alleles are associated with increased levels of SOSTDC1 have much lower allele frequencies among our study subjects , potentially explaining the failure to yield significant signals in the modifier GWA . However , those alleles do show trends toward positive modification , implying that increased levels of SOSTDC1 may delay age at onset in this population . From this perspective , identification of factors that induce increased levels of SOSTDC1 may also have therapeutic utility . In summary , our comprehensive genetic investigation of a distinct disease population has revealed intriguing aspects of HD , which are directly relevant for gene-based and traditional target-directed small molecule therapeutic development , both for this population and potentially for HD more generally .
The study was approved by the Partners HealthCare Institutional Review Board as Protocol #: 2009P000566/PHS , “Genetic Variation that Modifies HD Phenotype” and performed on DNA samples deposited previously , based upon oral consent , into a Partners HealthCare Institutional Review Board approved repository ( currently Protocol# 2010P001611/PHS , “CHGR Neurodegenerative Repository” ) . In a study approved by the Partners HealthCare Institutional Review Board , the Genetic Modifiers of HD ( GeM-HD ) Consortium carried out genotyping for 3 , 447 HD subject samples from the Massachusetts Huntington’s Disease Center without Walls repository , which included banked samples from North American , European and Venezuelan families who had previously donated blood samples for HD research , and from the European Huntington's Disease Network ( EHDN ) Registry study [68] . Data from Illumina Omni2 . 5 arrays were generated at the Broad Institute and European HD subjects from this dataset ( namely , HD GWA3 ) were analyzed with previous HD GWA data in order to identify genetic modifiers of HD in Europeans [28] . 549 subjects from the Venezuela HD cluster , described in Wexler et al . , 2004 [30] , were excluded from the previous analysis due to ancestry , and these form the primary population investigated in this study . As previously described [28] , we applied quality control ( QC ) metrics such as SNP call rate >95% , minor allele frequency ( MAF ) >1% , Hardy-Weinberg equilibrium p-value >1E-6 , sample call rate >95% to prepare high quality genotype data ( 538 subjects ) . Ancestry of samples was confirmed by principal components analysis using the PLINK program [69]; MDS ( multidimensional scaling ) values of study subjects were compared to those of 1000 Genome Project samples . Familial relationships were determined based on pair-wise IBD ( identity-by-descent ) estimation using the PLINK program and compared with existing pedigree charts from the U . S . -Venezuela Collaborative Research Project [32] . For a given individual , all related individuals with PLINK PI_HAT value greater than 0 . 125 were identified , and grouped into a family . Subsequently , we checked if the rest of samples were related to any of members of that family based on the same PI_HAT value criteria , and newly discovered related individuals were merged with previously defined family . These procedures were repeated exhaustively to identify all related subjects , generating 22 families with variable sizes . Therefore , an individual within a given re-constructed family is related to at least one other subject . Since we used estimated IBD values in identifying relatives to re-construct families , some families may have somewhat distantly related members . Haplotype phase of study subjects was based on computational phasing of 21 tagging SNPs [34 , 38] , generating the names of haplotypes for each individual ( e . g . , hap . 01 - hap . 16 ) . Since all HD subjects in each family share the same ancestral HD disease haplotype , the most frequent haplotype in the family was assigned as the HD disease chromosome haplotype . Genotype imputation was performed by the Michigan Imputation Server ( https://imputationserver . sph . umich . edu/index . html ) using the 1000 Genomes Project mixed population as a reference panel . The SHAPEIT phasing program ( https://mathgen . stats . ox . ac . uk/genetics_software/shapeit/shapeit . html ) was used for pre-phasing study samples . The same QC parameters were applied to imputed data to ensure the quality of genotype data . Methods to determine the sizes of HTT CAG repeats for each Venezuelan study subject are described elsewhere [70] . Age at onset was determined either prospectively or retrospectively based upon examination of subjects by experienced neurologists as described by the U . S . –Venezuela Collaborative Research Project [32] . Regression modeling analysis was performed to describe the specific relationship between age at onset and CAG repeat size in these Venezuelans . Briefly , natural log transformed age at onset of Venezuelan HD and European HD were modeled as a function of the size of expanded CAG repeat; study population-specific intercepts were estimated by including a covariate specifying individual population in the regression model . When a HD subject carries two expanded alleles ( CAG > 35 ) , the longer one was used because of complete dominance [7] . This regression model described the overall relationship between CAG and age at onset , and still permitted the revelation of any differences between Venezuelan HD and European HD . Using this regression model , predicted age at onset was estimated based on CAG repeat size , and subsequently was subtracted from actual age at onset to calculate residual age at onset for each HD individual . Residual age at onset represents how early or late a HD subject develops motor symptoms compared to expectation based on his or her expanded CAG repeat length . A positive residual age at onset means an HD individual developed symptoms later than expectation , and a negative residual age at onset means an HD individual developed symptoms earlier than expectation . For a selected nuclear family , where the HD mutation was transmitted on the hap . 03 haplotype , we performed whole genome sequencing analysis as described previously [48] . Sequencing was performed by Complete Genomics , generating variant calling files containing sequence variants with confidence scores . Since we aimed at maximizing SNP discovery and the inclusion of related samples provided the opportunity to assess sequencing errors , we examined all variants originally reported by Complete Genomics . For this study , we focused on a genomic region ( chr4:3066408–3255687; hg19 coordinates ) . Haplotype phasing was performed by using father-mother-child trio data as summarized in S5 Fig . Seven trios with a HD parent , normal spouse and HD child were defined in this family , and therefore the same parents were members of 7 trios , but data pre-processing and trio phasing was performed for each trio independently . Briefly , a variant site was excluded in a given trio if 1 ) genotypes in all 3 individuals were unknown , 2 ) all 3 individuals were identically heterozygous or 3 ) a Mendelian error was detected . Since we aimed at maximizing variation coverage , we included sites with partially missing data even though this makes detection of Mendelian errors difficult . Thus , Mendelian error detection was based on checking the genotype data for the following: 1 ) variant sites without any missing data , 2 ) sites with no missing data in the child and one or two alleles missing in only one parent , and 3 ) sites with one allele missing in the child and none missing in parents . This detection pipeline could still miss certain Mendelian errors due to missing genotypes , but these errors could be further identified by subsequent merging of multiple phased haplotypes in the family . After removing sites with Mendelian errors , sites that could not be confidently phased due to missing genotypes , and sites heterozygous in all 3 members of the trio , we phased the alleles at all remaining sites to produce fully phased hap . 03 disease haplotype for each trio . After data pre-processing , trio genotype data were phased using the BEAGLE program ( https://faculty . washington . edu/browning/beagle/beagle . html ) , and the HD disease chromosome haplotypes were further analyzed . One hap . 03 disease chromosome haplotype , inherited from the father , was obtained for each of the seven trios , and we merged these to discover any inconsistent alleles for additional QC analysis . Locations and numbers of Mendelian errors and inconsistent alleles are summarized in S6 Fig . We then finalized the hap . 03 disease haplotype by 1 ) taking alleles for sites with at least two phased allele calls , 2 ) assigning ‘N’ for sites that were unphaseable , or had missing genotype or Mendelian errors , and 3 ) assigning ‘ ? ’ for the inconsistent sites . These procedures yielded phased haplotypes covering 99 . 02% of the sites in the region . A novel SNP variation was identified , and submitted to dbSNP Build 150 ( rs966032869 ) . In order to validate Venezuelan HD whole genome sequencing data and compare to the hap . 03 disease chromosome in European HD subjects , we performed capture sequencing for an additional 8 Venezuelan HD subjects and 7 unrelated European HD subjects . Haplotypes of disease and normal chromosomes were based on computational phasing [34] of our GWA samples [28] . Capture probes were designed to enrich the target region chr4:3066408–3255687 ( hg19 coordinates ) using the Agilent SureDesign online tool . This generated ultra-long 120-mer biotinylated complementary RNA baits , and these capture probes were used for solution-based SureSelect target enrichment . Briefly , genomic DNAs were sheared to produce smaller fragments and libraries prepared with sequencer specific adaptors and indexes for multiplexing . DNA libraries were hybridized with biotinylated cRNA baits , which were complementary to regions of interest . The bait-library complexes were pulled down by magnetic beads . After the beads were washed , the RNA bait was digested to obtain the target DNA of interest , and subjected to sequencing using Illumina HiSeq 100bp paired-end sequencing at the Broad Institute . Sequence reads were aligned for variant calling using the Genome Analysis Toolkit Best Practices workflow ( https://software . broadinstitute . org/gatk/ ) . Additional genotyping for specific sites was performed by conventional Sanger sequencing . Residual age at onset was modeled by SNP , gender , and ancestry covariates ( i . e . , MDS 1–4 ) in a linear mixed effect model based on kinship matrix using the GEMMA program ( http://www . xzlab . org/software . html ) . We applied an additive model for each SNP whose minor allele frequency is greater than 5% in the study population . GWA analysis using imputed genotypes revealed genome-wide significant SNPs at a locus on chromosome 7 . Subsequently , we compared genotypes ( chr7: 16150000–16815000 , hg 19 ) of 5 Venezuelan HD individuals who had both sequence and imputed genotype data , revealing a mean concordance rate of 98 . 7% ( range , 98 . 2 ~ 99 . 3% ) . Genomic inflation factor was calculated using the GenABEL package ( median method ) ( http://www . genabel . org/manuals/GenABEL ) . Recombination rate was obtained from HapMap data ( http://www . sanger . ac . uk/resources/downloads/human/hapmap3 . html ) , and plotted on the secondary Y-axis of regional association plots . In order to determine dependency of SNPs in a given region , linear mixed effect models were constructed similarly but included the most significant SNP as a covariate . Significances of SNPs in the ordinary association analysis were compared to those in conditional analysis . Also , we performed extreme dichotomous analysis to determine whether a small number of data points drove the significant association . We directly compared SNP allele frequencies of those individuals whose residual age at motor onset was among the 10% extremes of earlier and later than expected onset . Logistic regression analysis was performed using the GEMMA program . Genome-wide copy number variation was determined from GWA data using PENNCNV program ( http://penncnv . openbioinformatics . org/en/latest/ ) . For chromosome 15 region , we meta-analyzed association analysis results of Venezuelan HD and European HD using the METAL program ( https://genome . sph . umich . edu/wiki/METAL_Documentation ) . In order to determine whether a polygenic modification score based on European HD subjects captured individual deviation from the expected age at onset for a given CAG size in Venezuelan HD , we obtained effect sizes and significances of SNPs based on the European HD subjects . Polygenic modification score is defined as the sum of effect allele count X effect size for each HD subject . We used independent SNPs with suggestive significance ( p-value < 0 . 00001 ) . This scoring method was applied to European HD and Venezuelan HD to calculate individual modification score . Subsequently , polygenic modification score was used as the independent variable with gender and ancestry covariates to explain residual age at onset in each population . For SNPs in the chromosome 7 region , we evaluated the significance of eQTL with genes in the region using the GTEx portal data base ( http://www . gtexportal . org/home/ ) . Among ISPD , SOSTDC1 , and LRRC72 , ISPD and SOSTDC1 generated significant eQTL signals in GTEx data set , and therefore these SNPs were downloaded for subsequent analysis . 42 and 231 SNPs ( non-unique ) were significantly associated with expression of ISPD and SOSTDC1 in various human tissues , respectively . For those significant eQTL SNPs , we compared the significance ( -log10 ( p-value ) ) in our modifier association analysis to those in GTEx cis eQTL analysis , revealing a correspondence between GWA significance and eQTL significance only for SOSTDC1 . Venezuelan HD subjects were separated into two groups based on chromosome 7 modifier genotype ( rs12668183 ) , resulting in rs12668183-carriers and non-rs12668183-carriers . For each group of Venezuelan HD subjects , independent GWA analysis was performed . In order to reduce outlier effects in the continuous analysis , subjects were sorted based on residual age at onset , and top and bottom 40% of subjects were analyzed using dichotomized phenotype data , focusing on comparing allele frequency differences between early and late onset groups . Mixed effect models were used to correct familial relationship .
|
Huntington’s disease ( HD ) is a dominantly inherited neurodegenerative disorder caused by a CAG trinucleotide expansion in HTT , which encodes huntingtin . HD involves various neurological manifestations such as involuntary movements , cognitive decline , and personality change; age at onset of diagnostic signs is partly determined by the length of the CAG repeat . However , genome-wide analysis of European HD subjects revealed that age at onset corrected for individual CAG repeat size is modified by other genetic factors , revealing potential disease-delaying pathways that form targets for therapeutic strategies . In this study , we set out to identify genetic modifiers in a Venezuelan HD cluster whose families were crucial for discovering the cause of HD . Through genome-wide association analysis using age at onset corrected for CAG repeat size as the phenotype , we found genome-wide significant ( chromosome 7 ) and suggestive significant association signals ( chromosomes 4 and 17 ) . Significant modification signals in Venezuelan HD appear to be population-specific because genetic analysis of European HD subjects did not reveal modification signals at those locations . Nevertheless , established modification signals in European HD at a chromosome 15 locus were also augmented by Venezuelan HD data , supporting the existence of both shared and population-specific genetic modifiers in HD . Together with the full sequence of HTT shared by the majority of these Venezuelan HD subjects , our genetic analysis provides insights into the geographical origin of the founder mutation , meaningful allele-specific sites for gene targeting approaches , and potential targets for disease-modifying intervention in this population .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Methods"
] |
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2018
|
Population-specific genetic modification of Huntington's disease in Venezuela
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For the last 500 years , the Americas have been a melting pot both for genetically diverse humans and for the pathogenic and commensal organisms associated with them . One such organism is the stomach-dwelling bacterium Helicobacter pylori , which is highly prevalent in Latin America where it is a major current public health challenge because of its strong association with gastric cancer . By analyzing the genome sequence of H . pylori isolated in North , Central and South America , we found evidence for admixture between H . pylori of European and African origin throughout the Americas , without substantial input from pre-Columbian ( hspAmerind ) bacteria . In the US , strains of African and European origin have remained genetically distinct , while in Colombia and Nicaragua , bottlenecks and rampant genetic exchange amongst isolates have led to the formation of national gene pools . We found three outer membrane proteins with atypical levels of Asian ancestry in American strains , as well as alleles that were nearly fixed specifically in South American isolates , suggesting a role for the ethnic makeup of hosts in the colonization of incoming strains . Our results show that new H . pylori subpopulations can rapidly arise , spread and adapt during times of demographic flux , and suggest that differences in transmission ecology between high and low prevalence areas may substantially affect the composition of bacterial populations .
In 1492 , Christopher Columbus initiated a rapid colonization of the New World , principally by European migrants and Africans brought as slaves that had catastrophic consequences for the indigenous population . The new migrants brought unfamiliar weapons and pathogens [1] , including new populations of the stomach-colonizing bacterium Helicobacter pylori . H . pylori can persist for decades in the stomach , and is often transmitted vertically from parent to child but can also be acquired from individuals in close proximity . H . pylori evolves rapidly by both mutation and homologous recombination with other co-colonizing strains [2] . Studies of the global diversity of H . pylori have shown that Europeans , Africans and Native Americans carry genetically distinct populations of bacteria; named hpEurope , hpAfrica1 and hpAfrica2 , and hspAmerind , respectively [3] . The relationships between bacterial populations reflect differentiation that has arisen during the complex migration history of humans , with the prefix “hp” indicating a population and “hsp” indicating a subpopulation , which are genetically distinct from each other but less differentiated than populations . hspAmerind bacteria are presumed to be descendants of the strains present in the Americas prior to 1492 , and are a subpopulation of hspEAsia , which is found in Asian countries such as China and Japan . However , these strains are rare even within groups with substantial Native American ancestry and may being dying out in competition with other strains , due to low diversity within the population or other factors [4] . hpEurope bacteria are themselves ancient hybrids between two populations , whose close relatives are currently found in unadmixed populations in North East Africa ( hpNEAfrica ) and central Asia ( hpAsia2 ) . The Tyrolean Iceman , Ötzi , who died 5300 years ago in central Europe , was infected by an hpAsia2 strain with little or no African ancestry [5] , suggesting that the admixture probably took place within the last few thousand years . In Latin America , gastric cancer is a leading cause of cancer death , and some countries in the region have among the highest mortality rates worldwide [6] . However , the mortality rates vary in different geographic regions , both between neighboring countries and within nations [6 , 7] . Several studies have been performed comparing H . pylori ancestry in high- and low risk areas and have linked phylogeographic origin of the bacteria , as well as discordant origin of bacteria and host , to increased risk of gastric cancer development [3 , 8] . However , these studies have been performed using MLST analysis that , being based only on seven housekeeping genes , is limited in its resolution compared to whole-genome comparisons . To investigate if American H . pylori strains have differentiated from those found in the Old World by mixture , genetic drift or natural selection , we combined hundreds of publicly available genomes with over hundred newly sequenced genomes of H . pylori sampled in Latin America ( Mexico , Nicaragua , and Colombia ) , Europe , and Central Asia . We show that the American bacterial populations have undergone substantial evolution within 500 years and our results also suggest that H . pylori transmission biology has been as important as human migration in determining extant patterns of diversity .
Each of the 7 populations found in the Old World has been reported previously with the exception that , with the addition of the large number of isolates in this study , hpEurope isolates separated into two distinct groups , which we provisionally label hspEuropeN and hspEuropeS ( Fig 1 ) . Our geographical sampling within Europe is limited but this split is likely to reflect the previously observed North to South gene frequency cline [12 , 13] , with the hspEuropeS isolates having a larger fraction of their palette from African populations and hspEuropeN having a higher proportion from hpAsia2 . The other five populations , hpAfrica2 , hspAfrica1SAfrica , hspAfrica1WAfrica , hpEastAsia and hpAsia2 are highly distinct from each other , each receiving more than half of their palette from their own population in the Old World painting . Among the isolates from the Americas , five additional subpopulations could be distinguished; four have palettes consistent with being European/African hybrids , according to the Old World painting ( Fig 2A ) . The population with the highest African ancestry is hspAfrica1NAmerica , isolated from 30 individuals in the US , one in Canada , one in Nicaragua , and one in Colombia , followed by hspAfrica1Nicaragua , which only contains isolates from Nicaragua; hspMiscAmerica , which consists of a number of strains of Mexican and Colombian origin; and hspEuropeColombia , which contains most of the Colombian isolates in our data set , and has a palette similar to hspEuropeS ( Fig 1 ) . The fifth population , hspAmerind , has a palette similar to hpEastAsia but with more hpEurope ancestry . These results are congruent to those obtained using D statistics ( Table 1 ) , which also imply that European and post-Colombian New World subpopulations are hybrids . In our sample , several isolates from the Americas cluster within the two hpEurope subpopulations ( Fig 1 ) . The hpEurope strains from North America largely cluster with hspEuropeN while those from Central and Southern America cluster with hspEuropeS . There was also substantial variation in the proportion of the genomic palette stemming from hspAfrica1WAfrica and hspAfrica1SAfrica , both between and within New World populations . hspAfrica1WAfrica is the major African source in isolates from hspMiscAmerica , hspEuropeColombia as well as hspEuropeS while hspAfrica1SAfrica is a more important source for hspAfrica1NAmerica and hspAfrica1Nicaragua populations . A handful of isolates from both hspEuropeColombia and hspAfrica1Nicaragua populations have elevated hspAfrica1SAfrica proportions , consistent with recent genetic mixture ( Fig 2A ) . In the global painting , the strains from the New World populations received a large proportion from their palette from within their own subpopulation , meaning that they have differentiated both from the Old World isolates as well as from the other New World subpopulations . The formation of differentiated populations in the Americas is suggestive of recent demographic bottlenecks ( see discussion below ) but the New World populations have nucleotide diversity as high as or slightly higher than the Old World populations from which they evolved ( Fig 3 ) , presumably because the diversity lost in bottlenecks has been replaced by admixture . Identifying the components of the ancestry of the New World populations that have undergone higher levels of drift provides insight into the process of differentiation . Drift is likely to be caused by the expansion of particular clones or lineages , for example , due to transmission bottlenecks . Specifically , we focused on signatures of DNA that had the most recent coalescent with other members within the same population . We tabulated the proportion of such sites with each distinct ancestry source in the Old World painting that were inferred to instead be derived from other members of their own population in the New World painting ( Table 2 ) . Bottlenecks allow small numbers of clones to propagate , leading to high rates of within population coalescence for genomes sampled from the population . This will in turn increase the proportion of sites inferred to have donors within the same population in the New World painting , rather than from Old World or other sources . Diversity acquired by admixture on the other hand , is more likely to be copied from other populations , unless the admixture sources have themselves been subject to a strong bottleneck . For hspAfrica1NAmerica and hspAfrica1Nicaragua , the most drifted component is the African component . The level of drift of the African component is significantly higher than that of other components ( p < 10−15 and p < 10−8 by Wilcoxon’s rank sum test in hspAfrica1NAmerica and hspAfrica1Nicaragua , respectively ) . It suggests that African lineages may have undergone rapid demographic increases during their spread in the Americas and thus that they may have a transmission advantage . Aside from the isolation of hspAmerind strains from three countries and a single hspAfrica1NAmerica isolate from Colombian and Nicaraguan , there was no indication of sharing of ancestry between North , Central and South American gene pools . There is also no evidence from the palettes of hspAmerind having contributed DNA to any other New World strains . Amongst the Mexican isolates , a few hspMiscAmerica isolates have a substantial hspAfrica1NAmerica component but there is no sign of elevated ancestry from the Colombian or Nicaraguan populations . The palettes provide evidence of genetic mixture between populations within countries . The hspEuropeS isolates from Nicaragua have more hspAfrica1Nicaragua in their palette than those from other locations , while Colombian isolates that are not assigned to the hspEuropeColombia have a higher ratio of hspEuropeColombia/hspEuropeS than found elsewhere , which is consistent with recent genetic exchange . Conversely , there is no evidence for elevated hspAfrica1NAmerica ancestry in hspEuropeN isolates from North America . The hspAfrica1NAmerica population has more hpEurope ancestry than hpAfrica1 isolates from Africa but there is little variation between strains , contrary to what would be expected if there was substantial ongoing gene flow . The spread of H . pylori populations in the Americas provides an opportunity to investigate adaptive introgression as the bacteria encountered new populations of humans , as well as novel diets and environmental conditions . This is of specific interest since H . pylori has an outstanding capacity for recombination between co-colonising strains [2 , 14] . We performed a scan of the core genome for genomic regions with enrichment of specific ancestry components . To this end , we painted the strains from each New World population , using Old World strains as donors and recorded whether the donor was European , African or Asian in origin . We found several genes where alleles showed significantly higher or lower ancestry from another Old world donor population than would be expected based on the overall ancestry of that isolate ( p < 10−8 , Table 3 ) . Among these were three genes that had ancestry from an unexpected Old World source in more than one of the New World populations . These were the genes encoding for AlpB ( HP0913 ) , HofC ( HP0486 ) , and FrpB4 ( HP1512 ) , which notably all are outer membrane proteins ( S1 Fig ) and all enriched for Asian ancestry in at least one population . The regions in alpB ( S1A Fig ) consist of clusters of 24 and 32 polymorphic sites enriched for Asian ancestry ( lowest p-value 9 . 8 x 10−15 ) within 49 and 65bp in hspEuropeColombia and hspAfrica1Nicaragua populations , respectively . The regions in hofC ( S1B Fig ) consist of 2 SNPs with interval 171bp and 4 successive SNPs enriched for Asian ancestry ( lowest p-value 7 . 8 x 10−15 ) in hspEuropeColombia and hspAfrica1NAmerica populations , respectively . The regions in frpB4 ( S1C Fig ) consist of 2 successive SNPs and 26 SNPs within 156 bp enriched for Asian ancestry ( lowest p-value 3 . 5 x 10−10 ) in hspEuropeColombia and hspAfrica1Nicaragua populations , respectively . To investigate the basis of the low p values in more detail , we first constructed phylogenetic trees of the three genes . Linkage disequilibrium extends over very short distances in H . pylori so these trees do not necessarily reflect the genealogy of the gene as a whole . Nevertheless interesting patterns were found in alpB and hofC trees ( Fig 4 ) . For each gene at least one major separate clade of Latin American isolates could be observed , regardless of H . pylori population . The tree for frpB4 can be found in S2 Fig . For alpB there are three major clusters; one predominantly Asian cluster including a majority of the Latin American strains , both Amerind isolates and isolates from the New World subpopulations , one predominantly European cluster , also with a number of Latin American strains , and one African cluster where isolates from Africa group together with isolates the hspAfrica1NAmerica . Notably , in the Asian group the Latin American isolates from multiple H . pylori populations cluster together while in the European group they are interspersed with the other isolates ( Fig 4A ) . For hofC there is one clearly distinct South American clade , including all the Amerindian strains except for Aklavik117 and a majority of the strains belonging to the New World subpopulations hspMiscAmericas , hspAfrica1Nicaragua and hspEuropeColombia . The other three main clades are dominated by either: ( i ) hspAfrica1WAfrica , hpAfrica2 and hspAfrica1NAmerica isolates; ( ii ) hspAfrica1SAfrica , European and US/Canadian hpEurope isolates or; ( iii ) Asian isolates , respectively ( Fig 4B ) . Notably , for hofC the Mexican isolates did not group within the main South American clade but within clade i and ii . Investigating the hofC gene alignment in more detail using Fst values revealed that the sequence variation strongly contributing to the tree clade structure were nucleotides 826–926 of the gene . We found 10 nucleotide positions with a Fixation index of higher than 0 . 3 in the Latin American isolates compared to isolates from rest of the World ( S4A Fig ) , out of which the 8 highest were localized in the above-mentioned region . Notably , these Fst values were also among the highest out of all nucleotide positions in the core genome ( Table 4 ) . Within this stretch , several amino acids were completely fixed in the South American clade and were not found in the other isolates ( Fig 5 ) . The ones with strongest Fst and unique to the South American clade were a Glutamic acid instead of a Glycine at position 278 , Asparagine or Aspartic Acid instead of Leucine at position 280 , a strong tendency to have Glycine instead of Glutamic Acid at position 292 and a Serine instead of Aspartic Acid at position 309 ( Fig 5 ) . These changes , which in most of the cases entirely changes the residue characteristics have spread to a large proportion of isolates in all of the populations found in South America , suggesting they confer an adaptive advantage , and stand out strongly in the Fst analyses even though this includes all Latin American isolates and not only the specific clade in the tree . Our collection of multiple genomes from each population allowed us to examine patterns of gene presence and absence . A neighbour-joining tree based on gene sharing distance between isolates largely recovered the populations and sub-populations identified based on core genome sequence , but with distinct clusters for isolates carrying the Cag Pathogenicity Island ( cagPAI ) positive and for cagPAI negative isolates respectively ( S5 Fig ) . The cagPAI is an approximately 40 kb cluster of genes encoding for a Type IV secretion system . This secretion system is translocating the CagA protein into host cells and has been shown to be of high importance for bacterial virulence [15 , 16] . In order to assess whether the pan genome evolved by the same processes of clonal descent and genetic exchange as the core genome , we examined the frequency of different pan genome elements in different populations . Specifically , we jointly analysed the frequency genes of triplets of populations , two of which are close representatives of the presumed ancestral source population and a third putative hybrid , with projections of the resulting 3D plots shown in Fig 6 . Fig 6A shows the expectations if the pan genome of the descendent population had identical gene frequencies to either source or a 50–50 hybrid . It has been previously shown that for the core genome , hpEurope bacteria are hybrids between hpAsia2 and hpNEAfrica ( which is related to hpAfrica1 ) , with higher hpAsia2 ancestry proportions in Northern Europe [12 , 17] . The same pattern for the pan genome could also be observed in our analysis , where the hpEurope population has a profile that is intermediate between that of hpAsia2 and hpAfrica1 , but with considerable variation in the pattern amongst genes , consistent with genetic drift in the thousands of years since hybridization ( Fig 6B , S1 Movie ) . We confirmed this visual impression using an ANOVA ( S3 Table ) . Specifically , we tabulated the genes that differed in frequency amongst the three populations and found that the average deviations from equality were largest for genes with pattern showing either hpEurope being similar in frequency to hpAsia2 or hpEurope being similar in frequency to hpAfrica1 . For the New World populations , hspEuropeColombia has a profile that is intermediate between Africa1 and European isolates ( Fig 6D , S3 Movie ) , with the ANOVA implying that gene frequencies are more similar to hpEurope than to hpAfrica1 ( S3 Table ) . hspAfrica1Nicaragua and hspAfrica1NAmerica have pan genomes that are more similar to those of hpAfrica1 than hpEurope ( Fig 6C–6E , S2 and S4 Movies , S3 Table ) .
Millions of people from diverse geographical and ethnic backgrounds have migrated from the Old World to the Americas in the last 500 years and it is likely that a majority carried H . pylori . Transmission between ethnicities and DNA exchange between strains might be expected to scramble the relationship between bacterial and human ancestry at the individual level , but in the absence of selection or bottlenecks , overall H . pylori ancestry should largely recapitulate the ancestry found in humans [12 , 17 , 18] . Consistent with this expectation , we find diverse populations of hpEurope bacteria in Northern and Latin America , with chromosome painting profiles comparable to those found in European isolates . We find a broad North-South divide amongst hpEurope isolates , both in the New and Old World , with higher relatedness to hpAfrica1 DNA in the southern populations . This is consistent with the gene frequency cline already observed in Europe and known differences in the colonization history of North and South America [19] . However , H . pylori genomic variation does not necessarily recapitulate patterns found in humans . The Americas constituted both a new physical and dietary environment and a new ethnic mix of hosts . Particular bacterial lineages may have had , or acquired , traits that adapted them to these new conditions . In extreme cases , human migrations that have little or no effect on human ancestry might precipitate substantial changes in H . pylori populations . For example , hspAmerind strains are rare even in populations with substantial Native American ancestry [3] . This suggests that after more than 10 , 000 years of independent evolution , resident H . pylori lineages were poorly equipped to compete with incoming lineages or with changes in the environment caused by the new settlers . We also found evidence of substantial differentiation of New World H . pylori populations from their ancestors , which suggests that there have been bottlenecks with particular lineages contributing disproportionately to extant populations . These bottlenecks have most strongly affected African components of ancestry ( Table 2 ) , suggesting that bacteria of African origin may have been particularly effective in colonizing the new continent . We identified three differentiated populations in the Americas , in addition to hspAmerind . The hspAfrica1NAmerica population includes the non-European isolates from the US , also found in single Canadian , Colombian and Nicaraguan isolates . This population has an ancestry profile consistent with it being a mix of West African , South African and European sources . However , our global chromosome painting results ( Fig 2B ) show that within genomic regions of African origin , the DNA of hspAfrica1NAmerica is distinct from that found in modern Gambian and South African populations . Differentiation at the DNA sequence level is also found in the hspEuropeColombia and hspAfrica1Nicaragua populations , whose gene pools are distinct from each other and from those in Mexico and Europe . The three larger groups of samples , from Mexico ( Mexico City ) , Nicaragua ( Managua ) and Colombia ( Bogotá ) respectively , were all collected at hospitals that are tertiary referral centres for endoscopy with large catchment areas , while all but one of the US isolates came from a hospital in Cleveland , a cosmopolitan city . Therefore , our findings likely reflect broad patterns of diversity within large geographic regions . Within our sample , there are regional differences in the proportions of European , African and Amerind ancestry and wider sampling might have differentiated the picture further . Nevertheless , the distinct patterns of H . pylori ancestry in the four countries indicate that recent population movements have been strongly influenced by national boundaries . H . pylori can undergo high levels of recombination during mixed infection . Over time , this might lead to bacteria acquiring an ancestry profile that reflects their local gene pool rather than their continent of origin . Recombination has not proceeded this far anywhere in the Americas and multiple populations with distinct ancestry profiles are found in most locations . hspAmerind strains have not contributed substantially to the ancestry of bacteria from any other population , but do appear to have acquired hpEurope DNA themselves . In Nicaragua and Colombia , recombination has transmitted distinctive DNA between populations , e . g . the brown shaded component in the hspEuropeS isolates from Nicaragua ( Fig 2B ) , leading to what can informally be thought of as a national signature in the H . pylori DNA . There is no equivalent signal of hspAfrica1NAmerica DNA amongst the hpEurope bacteria from the US , indicating that recombination between these populations has been less extensive , and there is also no evidence within our sample of a distinctive population of hpEurope bacteria evolving within the US . Similar patterns of higher admixture in African American and Hispanic American individuals than in American individuals of European descent have been observed also on human genomic level [19] . The differences in the extent of admixture in the New World populations can have several explanations including differences in dates of colonization and extent of European and African influx/admixture in Latin America compared to the US . Another important factor can be the prevalence of infection in different areas . The prevalence of H . pylori infection remains high in Latin American countries , ranging from 70 . 1% to 84 . 7% of adults in a recent multi-country study [20] . In the US , the prevalence has been declining from high levels and according to data from the end of the 1990’s , is around 32 . 5% [21] . The prevalence was different between the ethnic groups: 52 . 7% in non-Hispanic blacks; 61 . 6% in Mexican Americans and; 26 . 2% in non-Hispanic whites [21] . High prevalence likely entails higher occurrence of horizontal transmission and mixed infections and thus the possibility of recombination between distantly related strains [22] [23] . Our sample of Old World sources is incomplete , both in Africa and Europe , and therefore it is likely that Old World sub-populations exist that are more closely related to the New World populations than those in our sample , one such area being the Iberian peninsula . Also , even if we sample extensively in modern human groups , this may not fully reflect structure 500 years ago . The absence of sampling of close surrogates of the true ancestral subpopulations may alter our conclusions about selection or drift , which we have interpreted to have taken place in the New World rather than in the Old World . Sampling limitations for example make it unclear how much of the extensive mixture between African and European DNA observed in many Central and Southern American isolates actually took place in the Americas . Nevertheless , it is difficult to explain the local affinities within the diverse gene pools in both Nicaragua and Colombia , except by local genetic exchange . The hspAfrica1NAmerica isolates are homogeneous in their ancestry profile , suggesting that they also form a distinct gene pool that has acquired its characteristics through substantial evolution within the USA , although some of this evolution may have happened in an as yet unsampled subpopulation in Africa . hspAfrica1NAmerica appears to be an approximately panmictic population . For example , all isolates have approximately the same level of hpEurope ancestry in Fig 1 . This feature is difficult to reconcile with the low levels of genetic exchange observed with hpEurope isolates from the US . Since it has been shown that H . pylori from the same population ( hpEastAsia ) can exchange 10% of their genome during a single four year mixed infection in human [24] , the ancestral pattern in US H . pylori implies barriers to recombination between the two populations . Such barriers may be the result of ethnic segregation and thus less diverse co-infections , of differential uptake or incorporation of DNA from different populations , or of efficient competitive exclusion of bacteria from one population by bacteria from the other within individual stomachs . In the New World populations , four genes encoding for outer membrane proteins have sequence with ancestry that differed from that inferred for the overall core genome in more than one of the New World population . Interestingly , several of these variants were common for Latin American isolates regardless of which ancestral population they belonged to . AlpB is an adhesin binding to laminins in the extracellular matrix [25] that is present in all H . pylori strains [26] . Together with AlpA , it is required for colonization in experimental models and for efficient adhesion to gastric epithelial cells [27] . The HofC protein is also required for H . pylori colonization in mice and gerbils [28 , 29] but is not well characterized and little is known about its function . FrpB4 is important in the bacterial adaptation to variation in the microenvironment . FrpB4 is regulated by the levels of nickel , a micronutrient essential for H . pylori survival , growth and expression of virulence factors in the human stomach [30–32] . The enrichment pattern in hofC in a high number of the South American isolates was largely explained by the positions in region 276–309 of the 528 amino acid protein . The variants were found in all the South American Amerindian strains as well as almost all of the hspAfrica1Nicaragua and a majority of hspEuropeColombia strains together with strains from Peru and El Salvador . No Mexican strains were found in this clade . Since the HofC protein structure and function are not characterised in detail , we are unfortunately unable to predict how these alleles contribute to the function or specificity of the protein . Interestingly , also in FrpB4 there were several positions of high Fst in Latin America compared to the rest of the world ( S4 Fig ) but nor in this case we are able speculate in the functional impact of these specific positions . Nevertheless , the very pronounced enrichment pattern , as well as that in the other genes , is consistent with the New World H . pylori having adapted to their respective human populations , allowing certain traits to propagate relative to the overall genetic background . This could be important in understanding the differences in pathogenicity in different areas and different host/bacterial interactions , suggesting a need for further investigation of the function of these proteins . Our analysis of the accessory genome shows that H . pylori gene content , as well as nucleotide composition , is mixed during admixture between host populations . For example , the gene content of hpEurope is intermediate between that of hpAfrica1 and hpAsia2 , but with substantial variation that may reflect the large time that has elapsed since admixture . hspEuropeColombia is more African in genome content than the average hpEurope bacteria from Europe , as would be expected because of its higher African ancestry at the nucleotide level . However , the genome content of strains from the hspAfrica1Nicaragua population is more African than would be expected given its substantial co-ancestry with hpEurope within the core genome . This observation is concordant with recent observations showing that restriction modification inhibits non homologous but not homologous recombination [33] , suggesting that core genome ancestry may mix more readily between populations than accessory elements if restriction modification is an important barrier to exchange . Our results on the population structure in the Americas sheds new light on the relationship between human migration and H . pylori diversity . In particular , we show that at least during human population upheavals , evolution within geographic locations is far more dynamic than the broad correlation with human genetic variation would suggest and that novel subpopulations can arise by a combination of genetic drift and admixture within hundreds of years .
We used both publicly available and newly sequenced genomes of H . pylori isolates , 401 in total ( S1 Table ) . Nicaraguan isolates were collected at Hospital Escuela Antonio Lenin Fonseca ( HEALF ) in Managua , within the international collaboration “Immunological Biomarkers in Gastric Cancer development” and previously described in [34] . Colombian isolates that are not previously described were collected at the Oncology hospital ( INCAN ) in Bogota , and the Mexican isolates were collected at the Oncology and General Hospital in Mexico City . All three hospitals are tertiary referral centres for endoscopy and patients may thus come from other locations within the countries . For the cases we had more detailed data on the origin of the individuals , this is noted in S1 Table . The publicly available Colombian and North American genomes were those reported in preceding studies , i . e [35–37] . All of the genome sequences were imported into the Bacterial Isolate Genome sequence database ( BIGSdb ) [38] . After this , a gene-by-gene alignment was performed using CDS sequences of the H . pylori 26695 strains as reference , and the alignments were exported from the database . Both the genome sequences and the alignment are available at the public data repository Dryad ( http://datadryad . org/ ) , with doi doi:10 . 5061/dryad . 8qp4n . We conducted SNP calling for each alignment , and imputation for polymorphic sites with missing frequency < 1% using BEAGLE [39] as our preceding study [40] . We combined in total 401350 SNPs in 1232 genes while preserving information of SNP positions in the reference genome , to prepare genome-wide haplotype data . We inferred population structure among the strains from the genome-wide haplotype data by using the chromosome painting and fineSTRUCTURE [9] , according to a procedure of our preceding study that applied them to H . pylori genomes [10] . Briefly , we used ChromoPainter ( version 0 . 04 ) to infer chunks of DNA donated from a donor to a recipient for each recipient haplotype , and summarized the results into a “co-ancestry matrix” which contains the number of recombination-derived chunks from each donor to each recipient individual . We then ran fineSTRUCTURE ( version 0 . 02 ) for 100 , 000 iterations of both the burn-in and Markov chain Monte Carlo ( MCMC ) chain in order to conduct clustering of individuals based on the co-ancestry matrix . Principal Component Analysis was performed by applying the standard PCA implemented in Eigensoft to our data ( more precisely , all biallelic data after pruning of SNPs with r2 > 0 . 7 ) . D-statistics were calculated by using popstats ( https://github . com/pontussk/popstats ) and specifying POP1 as hpAfrica2 , POP2 as hspAfrica1WAfrica , POP3 as hpAsia2 , and POP4 as either of the remaining 9 populations , respectively . We conducted two types of chromosome painting; “Old World chromosome painting” using only Old world isolates as donors , and “Global chromosome painting” in which each isolate is painted using all of the others . For this purpose , we used ChromoPainterV2 software [9] . To identify genomic regions with enrichment of unexpected ancestry components in the New World populations hspAfrica1NAmerica , hspAfrica1Nicaragua , and hspEuropeColombia , we conducted a novel statistical test for each of the 401350 SNPs . This was done using the Old world strains as donors , grouped into African , Asian and European geographic origin respectively . We aim to count the number of recipient haplotypes from a certain donor population at each SNP . However , we do not observe whether a recipient i uses a particular donor population a , but instead the probability that it does at each locus l . The distribution of the total number of isolates at locus l from donor population a is ~ Poisson-Binomial ( plia ) . If we let the genome-wide painting probability be pia= ( ∑l=1Lplia ) /L , then the distribution expected under the null that there is no local structure to the painting donors is ~ Poisson-Binomial ( pia ) . We therefore report the p-values to test whether locus i has significantly enriched for donor a ( and likewise to test for de-enrichment ) . We used P<10−8 as a significance level , which corresponds to P<0 . 05 after Bonferroni correction . Because a ) the variance of a Poisson-Binomial is highest when is close to 0 . 5 , and b ) the distribution is discrete , this statistic has less power to detect high ancestry contributions from components that have high genome-wide ancestry , especially when sample size is small . In practice this has limited our power to detect regions that have an excess of African ancestry . Multiple alignments of the genes were performed using MUSCLE [41] and the alignment manually inspected to remove sequences with incomplete coverage before a PhyML maximum likelihood tree was created using the SeaView software [42] . All trees were visualized using Evolview [43] . Fixation index ( Fst ) analysis was performed using the R package PopGenome [44] . For all the 1232 core-genome multiple alignments were converted to VCF format using SNP-sites [45] and site-wise Fst was calculated over all biallelic sites for the subpopulation consisting of all isolates that were geographically originating from Latin America . In total 164 358 positions in 933 of the genes were eligible for the analysis . Of those 187 positions had an Fst of more than 0 . 25 in the Latin American isolates compared to strains from the rest of the World ( S2 Table ) . WebLogo plots were generated using [46] . A pan-genome was constructed with all loci present in at least one of our 401 strains to examine presence/absence of all H . pylori genes . This pan-genome list of 2462 genes was used as queries of BLASTN against each genome analysed in this study through the BIGSdb Genome Comparator pipeline [38] . Gene presence was judged by a BLASTN match of ≥70% identity over ≥50% of the locus length [47] . The Genome Comparator Output matrix obtained with BIGSdb was used to build a distance matrix ( MATLAB R2015a , The MathWorks , Inc . , Natick , Massachusetts , United States ) . A tree was obtained using SplitsTree4 [48] and was visualised with Evolview [43] .
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Helicobacter pylori is one of the best studied examples of an intimate association between bacteria and humans , due to its ability to colonize the stomach for decades and to transmit from generation to generation . A number of studies have sought to link diversity in H . pylori to human migrations but there are some discordant signals such as an “out of Africa” dispersal within the last few thousand years that has left a much stronger signal in bacterial genomes than in human ones . In order to understand how such discrepancies arise , we have investigated the evolution of H . pylori during the recent colonization of the Americas . We find that bacterial populations evolve quickly and can spread rapidly to people of different ethnicities . Distinct new bacterial subpopulations have formed in Colombia from a European source and in Nicaragua and the US from African sources . Genetic exchange between bacterial populations is rampant within Central and South America but is uncommon within North America , which may reflect differences in prevalence . Our results also suggest that adaptation of bacteria to particular human ethnic groups may be confined to a handful of genes involved in interaction with the immune system .
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2017
|
Rapid evolution of distinct Helicobacter pylori subpopulations in the Americas
|
Mast cells are implicated in the pathogenesis of inflammatory and autoimmune diseases . However , this notion based on studies in mast cell-deficient mice is controversial . We therefore established an in vivo model for hyperactive mast cells by specifically ablating the NF-κB negative feedback regulator A20 . While A20 deficiency did not affect mast cell degranulation , it resulted in amplified pro-inflammatory responses downstream of IgE/FcεRI , TLRs , IL-1R , and IL-33R . As a consequence house dust mite- and IL-33-driven lung inflammation , late phase cutaneous anaphylaxis , and collagen-induced arthritis were aggravated , in contrast to experimental autoimmune encephalomyelitis and immediate anaphylaxis . Our results provide in vivo evidence that hyperactive mast cells can exacerbate inflammatory disorders and define diseases that might benefit from therapeutic intervention with mast cell function .
Mast cells are innate immune cells that localize preferentially to vascularized tissues at the host-environment barrier . Through their high-affinity IgE receptor ( FcεRI ) they can capture circulating IgE and are hence primed to degranulate and produce cytokines upon antigen encounter . Mast cells store large amounts of histamine , heparin , and various proteases , which they release within minutes during degranulation . In contrast , the release of pro-inflammatory lipid mediators and most cytokines requires de novo synthesis upon activation [1] , [2] . Mast cells are also equipped with a range of cell surface receptors allowing them to sense microbial invasion , inflammation , and tissue damage , among them several TLRs , the IL-1R , and the receptor for the alarmin IL-33 , the IL-33R . Engagement of these receptors initiates a pro-inflammatory gene expression program via NF-κB transcription factors [1] , [3] , [4] . More than 100 years after their discovery , the physiological roles of mast cells in health and disease remain heavily disputed [5] . It is widely accepted that they are central mediators of IgE-dependent allergic responses , which can cause life-threatening anaphylactic shock in susceptible individuals [2] . These deleterious mast cell properties could be overshooting , misdirected responses originally designed as components of allergic host defense against environmental irritants , noxious foreign substances , and envenomation [6] . Although these functions might explain the evolutionary pressure that led to the development and preservation of mast cells , it is generally believed that further protective properties await identification . Furthermore , the observation that human patients suffering from asthma , allergic rhinitis , atopic dermatitis , and autoimmune and malignant disorders consistently contained mast cell accumulations at affected locations indicated a role for mast cells in these diseases [3] , [7] . Mouse strains lacking mast cells due to different loss-of-function mutations in the receptor tyrosine kinase c-Kit were instrumental to elucidate mast cell in vivo functions . However , in the context of autoimmune , inflammatory , allergic , and malignant disease studies , these mouse strains often yielded conflicting results , presumably due to additional effects of c-Kit deficiency [5] . Moreover , recent experiments employing novel Kit-independent mast cell-deficient mouse models have challenged some of their initially proposed functions [8]–[10] . Regardless of the particular model , loss-of-function approaches describe the consequences of absent function , which is not always inversely correlated with excessive function , and functional compensation by other cell types can be a problem . We aimed to establish a new mouse strain modeling gain-of-function of inflammatory mast cell responses , as they are at the center of controversy . In various immune lineages , the ubiquitin-editing enzyme and NF-κB negative feedback regulator A20 ( also known as Tnfaip3 ) is critical for the prevention of inflammation and autoimmunity [11]–[16] . Polymorphisms in the A20 gene locus or its binding partner TNIP1 are significantly associated with a number of human inflammatory and autoimmune conditions [17] , [18] and in case of TNIP1 also with asthma [19] . Therefore , we postulated that A20 deficiency in mast cells should provide an ideal genetic model system to address their pro-inflammatory properties in a gain-of-function approach . We employed conditional gene ablation to demonstrate that A20 restricts NF-κB activation downstream of the IgE:FcεRI module , TLRs , the IL-1R , and the IL-33R in mast cells . Exaggerated signaling from these receptors to NF-κB strongly enhanced mast cell pro-inflammatory responses , but did not affect degranulation . The presence of these hyperactive inflammatory mast cells exacerbated late phase cutaneous anaphylaxis reactions , allergic lung , and autoimmune joint inflammation . Our findings are , to our knowledge , the first direct demonstration that enhanced inflammatory mast cell responses can contribute to disease pathology .
Upon priming with IgE and subsequent aggregation , the mast cell FcεRI activates NF-κB in a similar way to B and T cell antigen receptors [20] , whereas the receptor for IL-33 initiates signaling cascades analogous to TLR and IL-1R engagement via MyD88 and TRAF6 [4] . We thus hypothesized that in analogy with other immune cells [18] , induced expression of A20 could restrict NF-κB activation downstream of the IgE/FcεRI module and the IL-33R , as well as the IL-1R and TLRs in mast cells . To biochemically address this hypothesis , we first investigated A20 expression kinetics in murine bone-marrow-derived mast cells ( BMMCs ) upon activation by LPS , IL-1β , IL-33 , and FcεRI cross-linking . A20 transcript levels peaked 3 h after activation and declined steadily afterwards , with IL-33 being the most potent inducer ( Figure 1A and Figure S1A ) . A20 protein levels increased 3–6 h after activation and remained elevated for up to 12 h ( Figure 1A and Figure S1B ) . In order to avoid potential biases through effects of gene deficiencies during mast cell in vitro development , we employed the novel KitCreERT2 transgene [21] , [22] . This allowed very efficient inducible expression of a fluorescent reporter protein ( Figure 1B ) , and excision of conditional A20 and MyD88 alleles in BMMCs ( Figure 1C ) did not affect c-Kit and FcεRI levels ( Figure S1C ) . A20-deficient mast cells activated by LPS , IL-33 , and FcεRI cross-linking showed enhanced activation of NF-κB as indicated by prolonged degradation and delayed resynthesis of its inhibitor I-κBα , while no differences in the activation of MAPK signaling were observed ( Figure 1D–F and Figure S1D ) . Collectively , these results show that A20 is a central negative feedback regulator of NF-κB signaling and mast cell activation in response to TLR ligands , IL-33 , and antigen/IgE complexes . We observed dramatically enhanced NF-κB activation in A20-deficient mast cells in response to various physiologically relevant stimuli in vitro . Therefore , we generated mice lacking A20 specifically in connective tissue-type mast cells ( Mcpt5Cre A20F/F ) [16] , [23] . In order to specifically dissect innate MyD88-dependent from other signals , we generated mice containing mast cells deficient for both A20 and MyD88 ( Mcpt5Cre A20F/FMyD88F/F ) [24] . Most experiments were controlled with Mcpt5Cre transgenic animals and , to a lesser extent , with nontransgenic littermates . As we did not observe any differences between those two groups , they are shown together as control mice . Mcpt5Cre A20F/F mice developed normally , showing no macroscopic signs of disease ( unpublished data ) . A20-deficient mast cells homed to their natural positions in the dermis and normal proportions were located in close proximity to blood vessels ( Figure 2A ) . Mast cell numbers in the ear and dorsal skin were not significantly altered in Mcpt5Cre A20F/F compared to control mice ( Figure 2A and Figure S2A ) . A20 deficiency did not affect the proportions ( Figure 2B ) or surface phenotype ( Figure 2C ) of mast cells in the peritoneal cavity . However , absolute mast cell numbers were significantly increased in Mcpt5Cre A20F/F mice in comparison to controls , due to an overall increase in peritoneal cellularity ( Figure 2D ) . Furthermore , we observed enhanced frequencies of TNF- , IL-4– , and IL-13–producing peritoneal mast cells in Mcpt5Cre A20F/F in comparison to control mice ( Figure 2E and Figure S2B ) . Ablation of MyD88 in addition to A20 led to a normalization of mast cell numbers ( Figure 2D ) and cytokine production ( Figure 2E and Figure S2B ) . Complete ablation of A20 and MyD88 was confirmed by Western blotting of peritoneal cavity-derived mast cell ( PMC ) cultures ( Figure S2C ) . To confirm that the Mcpt5Cre transgene does not lead to A20 deletion in cell types other than mast cells , we performed quantitative probe-based real-time PCR on genomic DNA from cell populations purified from Mcpt5Cre A20F/F animals . Using this sensitive approach we determined that less than 0 . 1% of A20-deficient cells are contained among sorted leukocytes ( T and B cells ) and various myeloid cell populations ( Figure S2D ) , if any . Interestingly , analysis of secondary lymphoid organs revealed minor splenomegaly in Mcpt5Cre A20F/F mice in comparison to controls , which depended on signals via MyD88 ( Figure S2E ) . Our results thus indicate that MyD88-dependent signals in vivo induce a preactivated or poised state in A20-deficient mast cells without causing spontaneous general inflammation . Mcpt5Cre A20F/F mice showed elevated mast cell numbers in the peritoneal cavity . This could be due to enhanced mast cell survival as A20 has also been implicated in cell death responses [13] , [15] , [16] , [18] . To clarify the function of A20 in mast cell survival , we studied growth factor deprivation-induced apoptosis , which in BMMCs is antagonized by prosurvival members of the Bcl-2 family including the NF-κB target genes Bcl-xL and A1 [25] . As A20-deficient mast cells showed stronger NF-κB activation in response to stimulation , we reasoned that loss of A20 could protect activated mast cells from IL-3 and SCF withdrawal-induced cell death . A20 deficiency per se did not affect growth factor deprivation-induced cell death , and stimulation with monomeric IgE generally enhanced mast cell survival by an A20-independent pathway ( Figure 3A ) . However , treatment with LPS remarkably increased survival only of mast cells lacking A20 . IL-33 had a small effect on wild-type mast cells but profoundly inhibited cell death in the absence of A20 ( Figure 3A ) . Stimulation with LPS or IL-33 enhanced the transcription of all tested pro-survival members of the Bcl-2 family in A20-deficient cells in comparison to controls , with A1 being most prominently affected ( Figure 3B ) . Enhanced expression of Bcl-xL protein was confirmed by Western blotting ( Figure 3C ) . All these processes were strictly MyD88-dependent ( Figure 3A–C ) . We thus conclude that A20 deficiency increases the up-regulation of pro-survival Bcl-2 family members upon innate activation . This is one potential mechanism of how loss of A20 can lead to a dramatically enhanced protection against apoptosis . In addition , cell cycle analysis showed an increase in proliferative activity of LPS and IL-33–stimulated A20-deficient mast cells , which depended on signals transmitted via MyD88 ( Figure 3D ) . Collectively , these results indicate that naturally occurring MyD88-transmitted stimuli can promote the survival and proliferation of A20-deficient mast cells . Next we investigated the consequences of mast cell-specific A20 deficiency in allergic , inflammatory , and autoimmune conditions . Asthma is a chronic inflammatory disease of the airways characterized by increased presence of eosinophils and production of Th2 cytokines , such as IL-13 , that causes bronchial hyperreactivity and goblet cell metaplasia . The classical mouse asthma model , which is induced by injection of ovalbumin ( OVA ) together with alum adjuvant , is mast cell independent in KitW/Wv and KitW-sh/W-sh mice . In contrast , a clear role for mast cells has been demonstrated in models of asthma that employ OVA as an allergen in the absence of alum [26] , [27] . To address the effect of mast cell-specific A20 deficiency in mouse asthma models , we immunized mice with OVA either in the presence or absence of alum , and challenged mice 10 d later with 1% OVA aerosols . In the OVA/alum model , loss of A20 in mast cells did not affect the number of bronchoalveolar lavage ( BAL ) fluid eosinophils , B and T cells , and the production of IL-13 by mediastinal lymph node ( MLN ) mononuclear cells or serum levels of OVA-specific IgE ( Figure 4A ) . In contrast , when mice were actively sensitized to OVA in the absence of alum , all these parameters were significantly elevated in Mcpt5Cre A20F/F compared to control mice ( Figure 4B ) . House dust mite ( HDM ) allergens are the most common triggers of allergic asthma and robustly induce IgE-dependent lung inflammation with many features of human asthma in mice [28]–[30] . To our knowledge , the role of mast cells has not yet been genetically addressed in this arguably more relevant model . Thus we measured the responses of Mcpt5Cre A20F/F and control mice to active sensitization induced by administration of HDM extracts via the nasal route followed by five HDM challenges 7 d later . Mast cell-specific ablation of A20 caused increased levels of BAL fluid eosinophils and B cells , and HDM-specific serum IgE ( Figure 5A ) . Dendritic cells ( DCs ) induce and maintain Th2 immunity to inhaled allergens such as HDM and OVA [31] and are necessary and sufficient for the development of asthma [29] . Suto et al . showed that mast cells control the activation of DCs via the release of TNF [32] . We therefore evaluated whether A20 deficiency in mast cells affects DC responses to HDM exposure . Indeed HDM treatment led to enhanced recruitment of DCs to the lung and MLNs in Mcpt5Cre A20F/F mice in comparison to controls . In addition , these DCs had taken up significantly more fluorescent antigen ( Figure 5B ) . These findings are in line with our observations that A20-deficient mast cells produce more TNF upon activation . As mast cells have been shown to control vascular permeability [9] , we wondered whether the increase in airway inflammation in Mcpt5Cre A20F/F mice could also be linked to enhanced vascular leakage . Therefore , we injected fluorescently labeled 500 nm microspheres intravenously 1 h after HDM allergen challenge and measured their extravasation 5 min later . In line with our hypothesis , Mcpt5Cre A20F/F mice displayed a strong increase in vascular leakage compared to control mice ( Figure 5C ) . We and others have previously reported that the HDM-driven model of asthma depends on the activity of IL-33 and is driven by antigen-presenting DCs [28] , [33] . In control mice , three intranasal administrations of IL-33 induced an increase in the total cell and DC influx into the lungs , which was enhanced by ablation of A20 specifically in mast cells ( Figure 5D ) . In addition , there was a trend towards increased numbers of eosinophils , neutrophils , and monocytes in the lungs of Mcpt5Cre A20F/F mice ( Figure S3 ) . Hence , the increased sensitivity of A20-deficient mast cells towards IL-33 could contribute to the enhanced allergic responses observed in Mcpt5Cre A20F/F mice . This notion is supported by the fact that Mcpt5Cre A20F/F mice showed significantly elevated numbers of granulocytes , lymphocytes , and DCs in the BAL fluid after OVA aerosol challenge , when the OVA sensitization occurred in the presence of IL-33 ( Figure 5E ) . We employed the above-described PCR assay ( see Figure S2D ) to confirm that under inflammatory conditions , Mcpt5Cre-mediated recombination of loxP-flanked A20 alleles is still restricted to mast cells . We did not detect recombination of conditional alleles in the following cellular subsets purified and pooled from eight HDM-challenged Mcpt5Cre A20F/F mice , which exceeded the background signal detected in the corresponding population purified and pooled from eight A20F/F mice: Lung B cells , DCs , monocytes and neutrophils , BAL fluid eosinophils , and peritoneal cavity macrophages ( unpublished data ) . In summary , we show that enhanced connective tissue-type mast cell responses to allergens and the alarmin IL-33 significantly aggravate allergic lung inflammation . We showed that A20-deficient mast cells worsen inflammation during allergic airway responses . Mast cells were also implicated in autoimmune diseases such as multiple sclerosis and arthritis [7] , [34] . However , the absence of mast cells had contradicting effects during the induction of model diseases in the mouse [5] , [8] , [35]–[37] . Hence we revisited this important issue in our novel gain-of-function model . We induced EAE through standard protocols in control and Mcpt5Cre A20F/F mice . Monitoring of disease incidence as well as severity ( clinical score ) did not yield any differences between both groups ( Figure 6A ) . Thus , A20-deficient connective tissue-type mast cells do not influence T-cell-driven EAE . Both genetic association studies and experimental approaches in mouse models suggested that mast cells and A20 play a pathological role in rheumatoid arthritis [12] , [18] , [34] . Interestingly , many studies showed a pathological role of IL-33 in CIA [38] , [39] . In line with our previous results , suggesting an important role for A20 in controlling IL-33R signaling , Mcpt5Cre A20F/F mice exhibited an earlier onset of disease after immunization compared to control mice ( Figure 6B ) . Also disease incidence and severity , as assessed by clinical score and paw swelling ( Figure 6B and Figure S4A ) , were significantly exacerbated by A20 deficiency in mast cells . Evaluation of pathology by histology corresponded well with the clinical scores ( Figure S4B ) . Systemically , we detected slightly elevated levels of TNF ( Figure S4C ) and an expansion of splenic B and T cell numbers in Mcpt5Cre A20F/F mice , pointing to increased inflammation ( Figure S4D ) . Concomitant ablation of MyD88 reversed the effects of mast cell-specific A20 loss during arthritis induction to a large extent ( Figure 6B and Figure S4A–D ) , indicating essential roles for IL-33 , TLR ligands , and/or IL-1β . Taken together , our data show that A20-deficient connective tissue-type mast cells did not affect EAE , but increased the severity of arthritis-associated inflammation . In order to dissect how A20-deficient mast cells exacerbate pathological immune responses in vivo , we first addressed IgE/FcεRI-induced mast cell activation that prominently provokes degranulation , in addition to pro-inflammatory NF-κB activation [20] . To explore consequences of A20 deficiency in connective tissue-type mast cells on anaphylactic responses in vivo , we performed FcεRI-mediated immediate phase passive cutaneous anaphylaxis ( PCA ) and passive systemic anaphylaxis ( PSA ) experiments , which depend on mast cell degranulation [8] , [20] . The vascular leakage in IgE primed ears in immediate phase PCA reactions ( Figure 7A ) , as well as changes in core body and skin temperature during PSA reactions ( Figure 7B and Figure S5A ) , did not differ significantly between control and Mcpt5Cre A20F/F mice . However , we observed a minor trend towards stronger responses in Mcpt5Cre A20F/F mice . Therefore , we embarked on extensive in vitro degranulation analyses using both BMMCs and PMCs . IgE/FcεRI engagement by antigen induced the same extent of degranulation in A20-deficient BMMCs ( Figure 7C and D ) and PMCs ( Figure 7E ) in comparison to controls . Prolonged priming with IgE and stimulation with IL-33 or TLR ligands alone or in addition to antigenic challenge did not reveal a role for A20 during degranulation and histamine release ( Figure S5B–F ) . Therefore , the minor increase in in vivo responses might be due to the slightly elevated mast cell numbers in Mcpt5Cre A20F/F in comparison to control mice . Collectively , our results show that A20 does not regulate degranulation and hence anaphylactic responses . We next performed late phase PCA responses , which are thought to be promoted by NF-κB activation in mast cells [20] . In this model , Mcpt5Cre A20F/F mice showed significantly enhanced ear swelling compared to controls ( Figure 7F and Figure S5G ) . Our data thus demonstrate that A20 does not regulate IgE/FcεRI-induced signals leading to degranulation and immediate anaphylactic events but rather late phase reactions . As A20 deficiency did not affect mast cell degranulation , we examined if enhanced pro-inflammatory reactions could account for the exacerbated responses observed in Mcpt5Cre A20F/F mice . Hence , we dissected the activation state of A20-deficient mast cells in vitro . Stimulation with LPS , IL-33 , and IL-1β induced dramatically augmented transcription and secretion of pro-inflammatory cytokines such as TNF , IL-6 , and IL-13 from A20-deficient in comparison to control mast cells ( Figure 8A and Figure S6A–C ) . PMA/Iono-induced release of IL-2 was unchanged ( Figure S6D ) . A trend towards an increase in IL-1β secretion was also observed ( Figure S6E ) . In addition , the enhanced responses of A20-deficient mast cells to LPS and IL-33 were demonstrated by increased up-regulation of the activation markers OX40L , CD30L , CD25 , Fas , and 4-1BB ( Figure 8B ) . Ablation of MyD88 completely abolished the enhanced production of cytokines and rescued the hyperactive phenotype caused by A20 deficiency ( Figure 8A and B and Figure S6B , C , and E ) . A20-deficient mast cells also produced more pro-inflammatory cytokines than wild-type mast cells in response to priming with IgE and to FcεRI cross-linking ( Figure 8C and Figure S6F and G ) . A recent study proposed that during arthritis IL-33 released by synovial fibroblasts activates mast cells , which in turn , by their secretion of pro-inflammatory cytokines , could enhance IL-33 expression in the former , leading to a paracrine feed-forward loop [38] . Supernatants of IL-33–stimulated A20-deficient hyperactive mast cells induced significantly more IL-33 production in synovial fibroblasts than supernatants of IL-33–stimulated control mast cells ( Figure 8D ) . This indicates that the lack of A20 in mast cells could amplify local IL-33–mediated feed-forward loops to exacerbate inflammation . Collectively , our results demonstrate that in mast cells A20 is a selective negative feedback regulator of NF-κB–mediated inflammatory signaling events but not of anaphylactic IgE:FcεRI–induced degranulation . Loss of A20 dramatically enhances their pro-inflammatory properties and causes profound mast cell hyperactivation . A20-deficient hyperactive connective tissue-type mast cells exacerbate lung as well as late phase skin inflammation and CIA , pointing to an important contribution of mast cells in these diseases .
Experiments in mast cell-deficient mice that carry hypomorphic c-Kit mutations have not only positioned mast cells as central mediators of allergic and anaphylactic responses but also in inflammatory and autoimmune diseases . However , recent experiments employing novel Kit-independent mast cell-deficient mice challenged this notion , which urged for a reassessment of their exact role in immunological and inflammatory reactions [5] . To study their contribution to particular immune reactions , one can assay the presence of mast cells and their activation status , the effects of mast cell deficiency , or the effects of mast cell hyperactivity , akin to the modified Koch's postulates for immunology [40] . Hence , we established a novel gain-of-function in vivo approach by ablating the NF-κB negative feedback regulator A20 specifically in connective tissue-type mast cells . This led to hyperactive mast cells with overshooting inflammatory responses to common disease-causing stimuli . We cannot completely exclude the possibility that loss of A20 has consequences on mast cell differentiation and/or functions in addition to amplifying inflammatory signaling and that this might influence the outcome of our experiments . However , A20's function as a very potent activation-induced negative feedback regulator in mast cells indicates that our interpretation of its role in the context of inflammatory diseases is warranted . This view is strongly supported by the fact that many of the phenotypes we observed can be neutralized by co-ablation of MyD88 . Our results demonstrate that A20 does not regulate instant degranulation , which is triggered by antigen binding to the IgE:FcεRI module and is critical for immediate cutaneous and systemic anaphylactic reactions . In contrast , A20 serves as a feedback inhibitor of FcεRI-initiated NF-κB activity and in its absence the secretion of pro-inflammatory cytokines , and thereby late phase PCA reactions are strongly amplified . Therefore , it should be possible to modulate A20 function without provoking anaphylactic reactions . Although pharmacological augmentation of A20 function is mainly discussed in the context of treating inflammatory and autoimmune diseases [17] , its inhibition might be beneficial to enhance immunogenicity of vaccines and the management of viral infections [14] , [41] . In addition , also in mast cells A20 limits pro-inflammatory gene expression upon stimulation with TLR ligands and cytokines . Furthermore , inflammation can be triggered by alarmins released by dying cells , such as the recently identified IL-33 [42] . Mast cells can sense IL-33 by virtue of their characteristic high constitutive IL-33R α-chain expression [43] . We discovered that A20 acts as a key negative feedback inhibitor of IL-33–induced MyD88-dependent NF-κB but not MAPK activation in mast cells . A20 deficiency leads to dramatically enhanced cytokine production , activation marker expression , resistance to apoptosis , and increased proliferation upon stimulation with IL-33 . As IL-33 can also be sensed by dendritic and myeloid cells [44] , IL-33–induced activation in the steady state could contribute to the spontaneous MyD88-dependent pathologies observed in mice that lack A20 specifically in these cell types [12] , [14] . Furthermore , IL-33 triggers activation of group 2 innate lymphoid cells , Th2 cells , NKT cells , B cells , NK cells , eosinophils , and basophils [44] . We therefore propose that A20's role in limiting IL-33–mediated NF-κB activation is of general importance in the immune system . Loss of A20 in connective tissue-type mast cells in vivo did not cause dramatic spontaneous inflammation . However , A20-deficient peritoneal mast cells displayed a pre-activated or poised state , which depended entirely on the presence of MyD88 . This indicates that mast cells , similar to other innate leukocytes [12] , [14] , constantly receive tonic signals that are controlled by A20 , via one or more MyD88-dependent receptors , such as TLR , IL-1R , IL-18R , or IL-33R . The fact that A20-deficient connective tissue-type mast cells , unlike macrophages or DCs lacking A20 [12]–[14] , do not cause pronounced spontaneous inflammation suggests that these cells are intrinsically less potent inducers of inflammatory reactions and/or have developed additional control mechanisms . A20 is a susceptibility gene locus for rheumatoid arthritis [17] , [18] , and mast cells are implicated in the pathogenesis of this disease [34] . Several recent studies pointed to a crucial role of IL-33 during arthritis [45] , which could promote joint inflammation , at least in part , by activating mast cells [38] . This notion is in line with our observation that hyperactive A20-deficient mast cells caused earlier onset as well as exacerbation of CIA symptoms . In contrast , A20-deficient connective tissue-type mast cells did not worsen symptoms of MOG peptide-induced EAE , possibly because initiation of this disease is IL-33 independent [33] . Our results do not strictly exclude a role of mast cells in this model , as it remains possible that general mast cell hyperactivation might have different or more pronounced effects than those elicited by the loss of A20 in connective tissue-type mast cells alone . Nevertheless , our results illustrate that profound hyperactivation of the inflammatory properties of connective tissue-type mast cells does not affect the outcome of EAE induction . Arthritis can develop in absence of an adaptive immune system , driven solely by A20-deficient innate immune cells [12] . We propose that in the context of autoimmune arthritis , A20-deficient mast cells exacerbate local inflammation in the joint . Tissue damage or physical stress during the early stages of arthritis development cause local release of endogenous TLR ligands or alarmins such as IL-33 . Pro-inflammatory cytokine secretion by A20-deficient mast cells results in a locally restricted auto-amplification loop by enhancing IL-33 expression in synovial fibroblasts leading to stronger mast cell activation in a paracrine fashion . This scenario is supported by our data that MyD88 deficiency in mast cells counteracts the early onset and disease severity caused by ablation of A20 . Amplification of detrimental IL-33–mediated feed-forward loops by loss of A20 function might not be restricted to initial stages in arthritis but could also play an important role in other inflammatory conditions including psoriasis , systemic sclerosis , inflammatory bowel disease , and asthma , which have an IL-33 component and are associated with A20 or A20 binding partner ( TNIP1 ) gene locus polymorphisms [17]–[19] , [44] , [45] . Furthermore , IL-33 is increased in human asthmatics , and recent genome-wide association studies have identified the genes encoding for IL-33 and its receptor as susceptibility loci for asthma [44] . Also in our asthma models , IL-33 is released by stromal cells , such as epithelial and smooth muscle cells , after HDM provocation [28] , [46] . Mast cell numbers increase during allergic airway inflammation and then localize within the smooth muscle , where they enhance bronchial hyperreactivity [47] . This localization hence enables mast cells to easily sense IL-33 , and A20 deficiency amplifies their ensuing responses , exacerbating immune cell activation and lung inflammation . Fittingly , IL-33 could also be used as an adjuvant to induce Th2 immunity , which was enhanced by mast cells in Mcpt5Cre A20F/F mice , possibly by promoting an initial pro Th2 innate response to IL-33 as indicated by the increased DC numbers in the airways . The stronger general immune activation elicited by alum probably overrides these mast cell-dependent effects in the OVA/alum model [26] , [27] . Since the HDM model is much closer to the human situation , our data clearly indicate that inflammatory functions of connective tissue-type mast cells can contribute to allergic inflammatory airway diseases . The role of mast cells in airway hyperreactivity has been studied predominantly in mast cell-deficient c-Kit mutant mouse strains , which did not allow dissecting the role of individual mast cell subsets [26] , [27] . Our model , with selective hyperinflammatory properties of connective tissue-type mast cells , points to an important role for this subset in controlling asthma . However , our findings do exclude a role for mucosal mast cells in this disease . In conclusion , our data demonstrate that loss of A20 specifically amplifies NF-κB controlled gene expression programs in connective tissue-type mast cells during inflammatory , allergic , and autoimmune conditions . We demonstrate that , in addition to its known function downstream of TLRs and the IL-1R , A20 also plays a critical role as a negative feedback inhibitor of IL-33R– and FcεRI-initiated pro-inflammatory signaling pathways . It does not , however , regulate IgE-dependent anaphylactic responses . As a result , the magnitude of inflammatory responses can be controlled through pharmacological intervention modulating A20 levels or activity without affecting anaphylactic reactions . Our study demonstrates , to our knowledge for the first time , the consequences of inflammatory mast cell hyperreactivity , identifying mast cells as therapeutic targets in airway inflammation and autoimmune arthritis . Our data also suggest that alterations in mast cell function could contribute to the pathologies linked to genetic polymorphisms in the A20 gene locus or some of its binding partners ( for example , TNIP1 ) that are associated with autoimmune , such as rheumatoid arthritis , or allergic diseases [17]–[19] .
Mcpt5Cre [23] , A20F [16] , MyD88F [24] , R26-StopFYFP [48] , and KitCreERT2 mice [21] , [22] were kept on a C57BL/6 genetic background . All animal procedures were approved by the Regierung of Oberbayern and the Animal Ethics Committee of the University of Ghent . For immediate phase PCA reactions , mice were passively sensitized by intradermal injection of 100 ng anti-DNP IgE ( SPE-7 supernatant ) into one ear and PBS into the contralateral ear . After 24 h , mice were challenged by intravenous ( i . v . ) injection of 200 µg DNP-HSA in 0 . 5% Evans blue ( both Sigma-Aldrich ) . Extravasation was quantified by dimethylformamid extraction and photometric quantification . For late phase PCA reactions , mice were sensitized by i . v . injection of 20 µg anti-DNP IgE ( SPE-7 supernatant ) and 24 h later challenged by epicutaneous application of 20 µL 0 . 2% DNFB ( Sigma-Aldrich ) in acetone/olive oil ( 4∶1 ) to one ear and vehicle to the contralateral ear followed by measuring ear thickness over time using a thickness gauge ( Mitutoyo ) . For PSA reactions , mice were sensitized by intraperitoneal ( i . p . ) injection of 10 µg anti-DNP IgE ( SPE-7 supernatant ) and 24 h later challenged by i . p . injection of 100 µg DNP-HSA . Systemic anaphylactic response was monitored by measuring changes in body temperature using a rectal thermometer ( Bioseb ) or changes of dorsal skin temperature using a thermography camera ( Jenoptik ) . OVA-specific allergic airway inflammation was induced in 6–10-wk-old mice , either by immunization with i . p . injections of 10 µg OVA on 7 alternated days or by an i . p . injection of OVA/Alum ( 10 µg OVA adsorbed to 1 mg aluminum hydroxide; Sigma-Aldrich ) at day 0 and day 7 . In both models , mice were challenged 10 d after the last i . p . OVA injection with OVA aerosols delivered from a jet nebulizer delivering 1% OVA in PBS for 30 min/day for 3 consecutive days . Twenty-four hours after the last challenge , BAL fluid , blood , and the MLNs were collected . IL-13 was measured in the supernatant of 106 MLN cells restimulated with 15 µg/mL OVA for 4 d . To induce HDM-specific allergic airway inflammation , mice were sensitized intranasally ( i . n . ) with 1 µg HDM extracts ( Greer Laboratories ) on day 0 under isoflurane sedation and were subsequently challenged with 10 µg HDM i . n . on days 7–11 . On day 15 , allergic airway inflammation was characterized as described above . To assay DC responses , mice received 100 µg HDM extracts ( Greer Laboratories ) and 10 µg OVA-AF647 ( Invitrogen ) intratracheally under isoflurane sedation and were analyzed 18 h later . To address the innate immune response to IL-33 , mice were treated on 3 consecutive days with 100 ng IL-33 i . n . , and lungs were harvested on day 4 . To provoke IL-33–induced airway inflammation , mice were sensitized with 25 ng IL-33 ( BioLegend ) and 10 µg OVA and boosted with 10 µg OVA day 7 . OVA aerosols challenges were given from day 17 to 19 , and at day 20 airway inflammation was assessed as described above . Mice were immunized subcutaneously at two sites with 200 µg MOG35–55 emulsified in Freund's adjuvant ( Sigma-Aldrich ) supplemented with 5 mg/mL Mycobacterium tuberculosis ( strain H37Ra , Difco ) . On the day of and 2 d after immunization , 400 ng pertussis toxin ( List Biological Laboratories ) was administered i . p . EAE severity was assessed every day based on a clinical scoring system [49]: 0 , normal; 0 . 5 , partial limp tail; 1 , complete paralysis of the tail; 2 , loss in coordinated movement , hind limb weakness; 2 . 5 , one hind limb paralyzed; 3 , both hind limbs paralyzed; 4 , forelimbs paralyzed; and 5 , moribund or dead . Male mice were immunized intradermally at two sites at the base of the tail with 200 µg chicken type II collagen in Freund's Adjuvant containing 1 mg/mL Mycobacterium tuberculosis ( Sigma-Aldrich ) essentially as described [50] . Arthritis severity was assessed every second day based on a clinical scoring system: 0 , normal; 1 , slight swelling and/or erythema; 2 , pronounced edematous swelling; and 3 , ankylosis . Each limb was graded , giving a maximum score of 12 . Paw thickness was measured every second day using a thickness gauge ( Mitutoyo ) . For histology hind paws were fixed in 4% PFA , decalcified in 10% buffered EDTA , embedded in paraffin , sectioned , and stained with hematoxylin and eosin . Nonspecific binding of antibodies to isolated single cells was minimized by Fc-block ( CD16/32 , 93 , eBioscience; 2 . 4G2 , BD ) , and cells were stained with monoclonal antibodies against 4-1BB ( 17B5 ) , B220 ( RA3-6B2 ) , CD3ε ( 145-2C11 ) CD4 ( RM4-5 ) , CD8 ( 53-6 . 7 ) , CD11b ( M1/70 ) , CD11c ( N418 ) , CD19 ( 1D3 ) , CD25 ( PC61 . 5 ) , CD30L ( RM153 ) , CD44 ( IM7 ) , CD45 . 2 ( 104 ) , CD62L ( MEL-14 ) , CD80 ( 16-10A1 ) , CD86 ( GL1 ) , c-Kit ( 2B8 ) , FcεRI ( MAR-1 ) , Gr-1 ( RB6-8C5 ) , Ly6C ( HK1 . 4 ) , MHC Class I ( AF6-88 . 5 . 5 . 3 ) , MHC Class II ( M5/114 . 15 . 2 ) , OX40L ( RM134L ) , TCRβ ( H57-597 ) ( all eBioscience ) , Fas ( Jo2 ) , Ly6G ( 1A8 ) , Siglec-F ( E50-2440 ) ( all BD ) , and ST2 ( DJ8 , MD Bioproducts ) . Biotinylated antibodies were detected with fluorophore-conjugated streptavidin ( eBioscience ) . Cytokine secretion of peritoneal cells was blocked for 4 h with monensin ( eBioscience ) in the absence of stimulation . Cells were fixed with 2% paraformaldehyde ( PFA ) , permeabilized with 1% saponin ( Sigma-Aldrich ) , and stained with monoclonal antibodies against IL-4 ( BVD-24G2 ) , IL-13 ( eBio13A ) , and TNF ( MP6-XT22 ) ( all eBioscience ) . Dead cells were excluded using 7-AAD ( eBioscience ) or EMA ( Invitrogen ) . Samples were acquired on FACSCalibur and FACSCantoII or sorted on FACSAriaII ( BD ) machines , and analyzed with FlowJo software ( Treestar ) . To initiate growth factor deprivation-induced apoptosis , BMMCs were extensively washed with PBS and cultured in simple mast cell medium lacking IL-3 and SCF or supplemented with 5 µg/mL anti-DNP IgE , 10 µg/mL LPS ( both Sigma-Aldrich ) , or 10 ng/mL IL-33 ( PeproTech ) . Cell death was quantified at the indicated time points after propidium iodide staining ( 10 µg/mL; Sigma-Aldrich ) and flow cytometric analysis . Cell cycle analysis was conducted by staining EtOH-fixed BMMCs treated with 100 µg/mL RNase A using 50 µg/mL propidium iodide ( both Sigma-Aldrich ) . Flow cytometric analysis of BAL fluid composition was performed according to a recently described method [29] . To prepare skin single-cell suspensions , dissected ears were digested in DMEM ( Gibco ) containing 25 mM Hepes ( PAN ) , 0 . 05 mg/mL Liberase TM , 0 . 2 mg/mL DNase I ( both Roche Diagnostics ) , and 0 . 5 mg/mL Hyaluronidase ( Sigma-Aldrich ) at 37°C for 1 h and grinded through a 70 µm cell strainer ( BD ) . To prepare lung and MLN single-cell suspensions , lungs and MLNs were digested using RPMI containing 0 . 02 mg/mL Liberase TM and 10 U DNase ( both Roche Diagnostics ) . For whole-mount ear skin immunohistology , ears were separated into dorsal and ventral sheets , and cartilage-free ear sheets were fixed by floating on 1% PFA overnight at 4°C . For back skin immunohistology , frozen 12 µm sections were thawed , air dried , and fixed with methanol for 10 min at −20°C . Ear sheets and back skin sections were blocked with 1% BSA and stained with a rabbit anti-laminin antibody ( gift from Michael Sixt ) followed by Cy3-conjugated anti-rabbit ( Jackson ImmunoResearch ) , and FITC-conjugated avidin ( Zymed ) . Images were acquired with a fluorescent microscope ( Zeiss AxioImager Z1 ) . To study vascular permeability in the airways , mice were sensitized ( day 0; 1 µg/mouse , intratracheally ( i . t . ) ) and challenged ( day 7; 10 µg/mouse; i . t . ) with HDM . One hour after the i . t . application , mice were injected intravenously with FITC+ 500 nm microbeads ( Invitrogen ) . Five minutes later mice were sacrificed , blood was removed by perfusion with PBS followed by PFA , and the trachea was isolated and cleaned . Blood vessels were visualized by subsequent incubation of the trachea with 5% normal goat serum in PBS with 3% Triton X-100 ( PBS plus ) ( 1 h , RT ) , rat anti-mouse CD31 ( 1/500 in PBS plus , overnight , 4°C ) , and AF647 coupled goat anti-rat IgG ( 1/500 in PBS plus , 4 h , RT ) , separated by several washes with PBS plus . Trachea whole mounts were embedded in polyvinyl alcohol mounting medium ( DABCO Fluca ) . Beads and blood vessels were visualized by confocal microscopy ( Zeiss LSM 710 ) . To generate BMMCs and PMCs , bulk bone marrow or peritoneal cells were cultured in suspension in mast cell medium: DMEM ( Gibco ) supplemented with 10% FCS ( PAA ) , 2% supernatant from X63/0 cells expressing IL-3 ( gift from Ton Rolink ) , 0 . 5% supernatant from CHO cells expressing SCF ( gift from Patrice Dubreuil ) , Glutamax ( Gibco ) , Non Essential Amino Acids ( Gibco ) , 50 µM 2-mercaptoethanol ( Merck ) , and 25 mM Hepes ( PAN ) . After 4 wk , BMMCs were cultured in mast cell medium containing 1 µM 4-hydroxytamoxifen ( Sigma-Aldrich ) for 7 d to delete conditional alleles in vitro ( BMMCs , KitCreERT2/+ = Wt; KitCreERT2/+A20+/F = A20wt/−; KitCreERT2/+A20F/F = A20−/−; KitCreERT2/+MyD88F/F = MyD88−/−; KitCreERT2/+A20F/FMyD88F/F = A20−/−MyD88−/−; PMCs , Mcpt5Cre = Wt; Mcpt5Cre A20F/F = A20−/−; Mcpt5Cre A20F/FMyD88F/F = A20−/−MyD88−/− ) . Purity was checked based on the expression of FcεRI and c-Kit by flow cytometric analysis . Murine synovial fibroblasts were isolated and cultured as described previously [51] with slight modifications . In brief , ankle joints were dissected , separated by cutting through the joint space , and digested in DMEM ( Gibco ) containing 25 mM Hepes ( PAN ) , 0 . 05 mg/mL Liberase TM , and 0 . 2 mg/mL DNase I ( both Roche Diagnostics ) at 37°C for 1 h . Whole cell lysates were prepared by lysing cells for 30 min on ice in RIPA buffer ( 50 mM Tris/HCl pH 7 . 4 , 150 mM NaCl , 1% NP40 , 1 mM EDTA , 0 . 25% Na-deoxycholate ) supplemented with 10 µg/mL Aprotinin , 10 µg/mL Leupeptin , 0 . 1 mM Na3VO4 , 1 mM PMSF , 10 mM NaF , 1 mM DTT , and 8 mM β-Glycerophosphate after stimulation with LPS ( Sigma-Aldrich ) , TNFα , IL-1β , IL-33 ( all PeproTech ) , or FcεRI cross-linking ( anti-DNP IgE , SPE-7 supernatants; DNP-HSA , Sigma-Aldrich ) . PVDF membranes were blotted with the following antibodies: A20 , I-κBα ( both Santa Cruz ) , Bcl-xL ( BD ) , AKT , phospho-AKT , ERK , phospho-ERK , phospho-I-κBα , JNK , phospho-JNK , p38 , phospho-p38 ( all Cell Signaling ) , MyD88 ( Stressgen ) , IL-33 ( Enzo Life Sciences ) , and GAPDH ( Calbiochem ) . TNF , IL-13 , IL-1β ( all PeproTech ) , IL-6 , and IL-2 ( both BD ) levels were determined by ELISA as recommended by the manufacturer . RNA was isolated ( USB ) and reverse transcribed ( Promega ) for quantitative real-time PCR using TaqMan Gene Expression Assays ( A1 , Applied Biosystems ) or Universal Probe Library ( all other genes , Roche Diagnostics ) probes and primers as recommended by the manufacturer . DNA from sorted cells was isolated ( Life Technologies ) , and quantitative real-time PCR ( 10 min 95°C , 50 cycles: 10 s 95°C , 30 s 60°C , 1 s 72°C ) was performed on DNA corresponding to 10 , 000 cells in a reaction volume of 20 µL containing 1× TaqMan Probe Master ( Roche Diagnostics ) , 1 µM of each forward and reverse primers ( A20 locus a , 5′-ACTGTTTGAAGCATGCACGA-3′; b , 5′-ACAACCTGTCAAATCCATATTCAG-3′; A20 deleted c , 5′-AAATCTGGACAGCTGATTCCT-3′; d , 5′-CAACATCTCAGAAGGACACCAT-3′ ) and 0 . 1 µM TaqMan probe #68 ( A , Roche Diagnostics ) or loxP probe ( B , 5′-6-FAM-atAaCtTCgtatagCATaCattatac-BHQ-1-3′; capital letters = LNA; Eurogentec ) . In order to evaluate sensitivity of the real-time PCR , we generated samples containing 1 , 000 ( 10% ) , 100 ( 1% ) , or 10 ( 0 . 1% ) A20−/− BMMCs among 9 , 000 , 9 , 900 , or 9 , 990 A20F/F splenocytes . To induce degranulation , BMMCs and PMCs were loaded for 2 or 24 h with 1 µg/mL anti-DNP IgE ( SPE-7 supernatant ) . After washing in Tyrode's buffer ( 10 mM Hepes , pH 7 . 3 , 135 mM NaCl , 5 mM KCl , 1 . 8 mM CaCl2 , 1 mM MgCl2 , 5 . 6 mM glucose , 0 . 5 mg/mL BSA ) , cells were stimulated with the concentrations of DNP–HSA indicated in the figure , 10 ng/mL IL-33 , 10 µg/mL LPS , or 500 ng/mL A23187 for 30 min . β-hexosaminidase activity in supernatants and cell pellets solubilized with 0 . 5% Triton X-100 in Tyrode's buffer were measured with p-nitrophenyl-N-acetyl-β-D-glucosaminide ( Sigma-Aldrich ) . To measure degranulation using Annexin V binding , after 20 min of FcεRI cross-linking , BMMCs were washed in Annexin V binding buffer ( 25 mM Hepes , pH 7 . 2 , 140 mM NaCl , 2 . 5 mM CaCl2 ) , and Cy3-conjugated Annexin V ( gift from Dirk Mielenz ) binding was analyzed by flow cytometric analysis . To measure histamine release , PMCs were loaded 24 h with 1 µg/mL anti-DNP IgE ( SPE-7 supernatant ) , stimulated with the concentrations of DNP–HSA indicated in the figure , 10 ng/mL IL-33 , 10 µg/mL LPS , or 500 ng/mL A23187 for 30 min , and histamine levels were determined by EIA as recommended by the manufacturer ( Immunotech ) . Statistical analysis of the results was performed by Log-rank ( Mantel-Cox ) test , Mann-Whitney U test , Student's t test , or by one-way ANOVA followed by Tukey's test . The p values are presented in figure legends where a statistically significant difference was found .
|
Mast cells mediate allergic and anaphylactic immune reactions . They are also equipped with innate pattern recognition , cytokine , and alarmin receptors , which induce inflammatory responses . Correlative studies in human patients hinted at roles for mast cells in autoimmune and inflammatory diseases . However , studies using mast cell-deficient mice have yielded contradictory results in this context . In this study we determined that A20 , the negative feedback regulator , restricts inflammation downstream of the mast cell antigen ( allergen ) receptor module , innate pattern recognition receptors , and the alarmin receptor IL-33R . By mast cell–specific ablation of A20 we established a mouse model for exaggerated inflammatory but normal anaphylactic mast cell signaling . With these mice we evaluated the impact of increased mast cell-mediated inflammation under experimental conditions aimed at mimicking several inflammatory human diseases . Our results demonstrated that the lack of A20 from mast cells exacerbated disease in mouse models for rheumatoid arthritis and innate forms of asthma , but did not impact disease progression in a mouse model for multiple sclerosis . Our data provide direct evidence that enhanced inflammatory mast cell responses can contribute to disease pathology and do so via sensing and amplifying local inflammatory reactions driven by “danger” stimuli and/or tissue damage that leads to the release of alarmins .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"inflammation",
"immune",
"cells",
"cytokines",
"genetics",
"of",
"the",
"immune",
"system",
"immunity",
"innate",
"immunity",
"allergy",
"and",
"hypersensitivity",
"immunology",
"biology",
"autoimmunity",
"immune",
"system"
] |
2014
|
A20-Deficient Mast Cells Exacerbate Inflammatory Responses In Vivo
|
Human cytomegalovirus ( HCMV ) has been shown to induce increased lipogenesis in infected cells , and this is believed to be required for proper virion envelopment . We show here that this increase is a consequence of the virus-induced redistribution of the host protein viperin to mitochondria and its capacity to interact with and block the function of the mitochondrial trifunctional protein ( TFP ) , the enzyme that mediates fatty acid-β-oxidation . The resulting decrease in cellular ATP levels activates the enzyme AMP-activated protein kinase ( AMPK ) , which induces expression of the glucose transporter GLUT4 , resulting in increased glucose import and translocation to the nucleus of the glucose-regulated transcription factor ChREBP . This induces increased transcription of genes encoding lipogenic enzymes , increased lipid synthesis and lipid droplet accumulation , and generation of the viral envelope . Viperin-dependent lipogenesis is required for optimal production of infectious virus . We show that all of these metabolic outcomes can be replicated by direct targeting of viperin to mitochondria in the absence of HCMV infection , and that the motif responsible for Fe-S cluster binding by viperin is essential . The data indicate that viperin is the major effector underlying the ability of HCMV to regulate cellular lipid metabolism .
Human cytomegalovirus ( HCMV ) is associated with acute and chronic disease in both healthy and immunocompromised populations [1] , [2] , [3] . A characteristic of HCMV is that it modulates the metabolism of an infected cell in ways that favor viral replication [4] , [5] , [6] . HCMV infection has been shown to induce the expression of glucose transporter 4 ( GLUT4 ) and its translocation to the cell surface , which results in an increase in cytoplasmic glucose that is used for de novo fatty acid biosynthesis [4] , [5] , [6] , [7] , [8] . The increase in GLUT4 expression during HCMV infection has been shown to result from activation of AMP-activated protein kinase ( AMPK ) [9] . The increase in fatty acid biosynthesis leads to the accumulation of lipids that are used for formation of the viral envelope [10] , [11] . Consistent with this , pharmacological inhibition or siRNA-mediated knockdown of fatty acid synthetic enzymes reduces HCMV replication [5] , [10] . Two major classes of transcription factors regulate de novo fatty acid synthesis by inducing the expression of lipogenic enzymes . These are sterol regulatory element binding proteins ( SREBPs ) and carbohydrate responsive element binding protein ( ChREBP ) , which are insulin- and glucose-responsive transcription factors , respectively [12] , [13] , [14] , [15] , [16] , [17] . In cells with sufficient sterol levels , SREBPs remain in the endoplasmic reticulum ( ER ) . When sterol levels are depleted , the insulin-stimulated SREBPs are transported to the Golgi where they are cleaved to a mature form and translocated into the nucleus . The cleaved forms of SREBPs up-regulate the expression of lipogenic genes [13] , [14] , [15] . ChREBP is also an important transcriptional regulator for de novo lipogenesis . Glucose activates ChREBP by regulating its redistribution from the cytosol to the nucleus by a phosphorylation dependent mechanism [18] , [19] . Recently , it was shown that in adipose tissue GLUT4-mediated glucose uptake induces ChREBP , which activates de novo lipogenesis [20] . HCMV infection has been shown to induce the cleavage of SREBPs and also to maintain constitutive lipid synthesis by overriding sterol feedback control during infection [10] , [11] . However , the fundamental mechanisms responsible for HCMV-induced activation of lipid synthesis remain poorly understood . Upon infection HCMV directly induces the interferon ( IFN ) -inducible iron-sulfur ( Fe-S ) cluster-binding protein , viperin [21] , [22] , [23] , and we recently showed that the HCMV-encoded vMIA protein binds viperin and translocates it to mitochondria where it inhibits fatty acid β-oxidation [24] . This results in reduced cellular ATP levels and disruption of the actin cytoskeleton , previously shown to increase viral infectivity [25] , [26] , [27] , [28] . Here we demonstrate that the induced viperin is also responsible for the increases in AMPK activity , GLUT4 and lipogenic enzyme transcription , and enhanced lipid synthesis observed in HCMV-infected cells . The interaction of viperin , but not a mutant lacking the Fe-S cluster binding motif , with the mitochondrial trifunctional protein ( TFP ) that mediates fatty acid β-oxidation [29] , [30] is critical for these effects . These data suggest that viperin is the key molecule that regulates lipid metabolism during HCMV infection .
Viperin interaction with the mitochondrial trifunctional protein ( TFP ) depletes cytoplasmic ATP [24] . ATP depletion generally results in AMP accumulation , which leads to the activation of AMPK [31] , [32] , [33] , and AMPK has been shown to be important for HCMV-mediated alterations in metabolism [9] . To test whether viperin expression mediated by HCMV infection is required for AMPK activation , immortalized human fibroblasts ( HFtelo ) , expressing either no shRNA ( wild type ) , luciferase-specific ( Luc ) shRNA ( control ) , or two different viperin shRNAs ( viperin knockdown ) , were infected as previously described ( Figure S1A ) [24] . The AMPK activity in control cells at 2 days post infection ( dpi ) was increased by 3-fold over that in non-infected cells , while no change was observed in cells expressing viperin-specific shRNAs ( Figure 1A ) . The addition of Compound C , a specific AMPK inhibitor [34] , suppressed the measured enhancement . Activation of AMPK induces GLUT4 expression [9] , [35] , and HCMV infection has been shown to activate GLUT4 independently of its normal control mechanisms , which include external glucose concentration , ATP-citrate lyase ( ACL ) activation , insulin stimulation , and Akt activity [8] . We asked whether viperin expression affects GLUT4 expression and GLUT4-mediated glucose uptake . HFTelo cells expressing no shRNA , control shRNA or viperin shRNAs were infected with HCMV and GLUT4 mRNA was measured by quantitative RT-PCR ( Figure 1B ) . The mRNA levels significantly increased in infected cells expressing no shRNA or Luc shRNA , while no increase occurred in the viperin knockdown cells at 1 dpi and increases at 3 dpi were minimal ( Figure 1B ) . These data indicate that viperin expression is required for induction of GLUT4 during HCMV infection . Because GLUT4 expression should increase glucose import , we also measured the levels of glycolysis in the infected control and viperin-specific shRNA-expressing cells . Consistent with GLUT4-dependent glucose accumulation , glycolysis was increased in control cells but not viperin knockdown cells ( Figure S1B ) . ChREBP is a glucose-responsive transcription factor that activates the transcription of lipogenic enzymes and is highly regulated by GLUT4 in adipose tissue [20] . To determine if ChREBP plays a role in HCMV infection , we measured the mRNA levels of ChREBPα ( the canonical isoform ) and ChREBPβ ( a novel isoform ) [20] in control and viperin knockdown cells ( Figure 1C ) . Both transcripts of ChREBP were increased upon HCMV infection , and in both cases the increase was significantly blocked in cells expressing viperin shRNA ( Figure 1C ) . This was particularly evident at 3 dpi . ChREBP translocates from the cytoplasm to the nucleus to function as a transcription factor , and we examined the intracellular localization of ChREBP in HCMV-infected cells . ChREBP was detected in both cytoplasm and nucleus of control cells ( over 50% of HCMV-infected cells ) at 3 dpi , while in the viperin knockdown cells it was not present in the nucleus ( Figure 1D ) . ChREBP translocation to the nucleus induces lipogenic enzyme transcription , and HCMV infection is known to increase de novo fatty acid synthesis by inducing expression of lipogenic enzymes [10] , [11] . We therefore measured mRNA levels for the key lipogenic enzymes ATP-citrate lyase ( ACL ) , Acetyl-coenzyme A ( CoA ) carboxylase ( ACC ) 2 , fatty acid synthase ( FAS ) , diacylglycerol acyltransferase ( DGAT ) 1 , and DGAT2 . All of these transcripts were increased upon HCMV infection of cells expressing no shRNA or Luc shRNA , and in all cases the increase was substantially blocked in cells expressing viperin-specific shRNA ( Figure 2A ) . This was particularly evident at 3 dpi . Interestingly , SREBP1 cleavage was independent of viperin expression during HCMV infection ( Figure S2A ) , although inhibition of SREBP1 cleavage has been shown to reduce lipid synthesis and impair HCMV growth [10] , [11] . The results suggest that in HCMV-infected fibroblasts , like in adipose tissue , GLUT4-mediated glucose uptake and de novo lipogenesis are dominantly regulated by ChREBP rather than SREBP1 , and that this process is viperin-dependent . To address this we measured lipogenesis in cells expressing GLUT4- and ChREBP-specific shRNAs during HCMV infection ( Figure S2B and S2C ) . The mRNA levels of ChREBP and lipogenic enzymes were substantially lower in GLUT4 knockdown cells than control cells during HCMV infection ( Figure S2C ) . Like in control cells , GLUT4 mRNA content was increased in ChREBP knockdown cells , while the increases in lipogenic enzyme mRNA levels were substantially blocked at 1 and 3 dpi ( Figure S2C ) . The data support a mechanism in which viperin induces GLUT4 expression , increasing glucose uptake and thus ChREBP , which in turn activates de novo lipogenesis during HCMV infection . The increase in lipogenic enzyme levels upon HCMV infection results in increased lipid synthesis and lipid droplet ( LD ) induction [10] , [11] . We therefore measured total lipid synthesis in the HCMV-infected cells using 14C-labeled acetate . Total lipid synthesis in control cells at 2 dpi during a 3 hour labeling period was increased by 2 . 5-fold over that in non-infected cells , while no change was observed in the viperin shRNA-expressing cells ( Figure 2B ) . We also examined formation of LDs , which are storage compartments for triglycerides and long chain fatty acids [36] , [37] . LDs increased in diameter by approximately 3–4-fold in the HCMV-infected control cells at 3 dpi , while both the number and size of the induced LDs were dramatically reduced in viperin shRNA expressing cells ( Figure 2C and D ) . No changes in LD number or size were observed upon viperin knockdown without HCMV infection . These data suggest that in the absence of viperin HCMV consumes pre-existing lipids , reducing the size and number of LDs , but cannot induce lipids to replenish them . Having previously observed that HCMV-encoded vMIA is responsible for targeting viperin to the mitochondria [24] , we asked whether vMIA expression affects viperin-dependent lipogenesis during HCMV infection . MRC5 fibroblasts were infected with RVHB5 ( control wild type HCMV ) , or RVHB5ΔvMIA , a mutant of this virus lacking vMIA , in the presence of ZVAD-FMK , a broad-spectrum caspase inhibitor that prevents apoptosis otherwise induced by HCMV lacking vMIA [38] . In contrast to the results with cells infected by wild type virus , in RVHB5ΔvMIA-infected cells viperin did not substantially co-localize with mitochondria at 1 dpi ( Figure S2D ) and lipogenesis was substantially blocked ( Figure S2E ) . These results indicate that viperin translocation to the mitochondria by vMIA is required for the lipogenesis induced during HCMV infection . Enhanced lipid synthesis is thought to provide the membrane necessary for proper HCMV envelope formation . To explore the role of viperin in this process we analyzed the viral particles generated in the presence and absence of viperin by quantitating cytoplasmic non-enveloped particles ( capsids and tegumented capsids ) and enveloped particles ( double-layered particles formed by tegumentation and secondary envelopment in the secretory pathway ) in control and viperin knockdown cells by electron microscopy , late in infection to allow accumulation of quantifiable virions ( Figure 3A ) . In normal cells or those expressing the control shRNA approximately 65% of the cytoplasmic viral particles were enveloped and this was reduced to approximately 25% in the viperin shRNA expressing cells ( Figure 3B ) . We also observed a substantial decrease in the production of infectious extracellular and intracellular virus in the cells expressing viperin shRNA ( Figure 3C ) . However , the viral genome copy numbers present in both extracellular and intracellular particles produced from the cells after infection were similar , regardless of shRNA expression ( Figure 3D ) . In addition , we observed no change in the expression of the intracellular HCMV viral proteins MCP ( a capsid protein ) , gB ( an envelope protein ) , and pp65 and pp28 ( tegument proteins ) ( Figure 3E ) . The data indicate that cells with impaired viperin expression produce a similar number of viral particles but many of them are non-infectious because of defective envelopment . The reduction in cellular ATP levels and disruption of the actin cytoskeleton induced by vMIA-mediated transfer of viperin to mitochondria can be replicated in the absence of infection by directly targeting viperin using a mitochondrial localization sequence ( MLS ) [24] . The activity requires a functional Fe-S cluster binding site [24] . To determine if this is also true for the effects on lipogenesis , we used previously described chimeric mouse viperin constructs: MLS-viperin , in which the N-terminal amphipathic α-helix of viperin , responsible for its ER and LD association [39] , [40] , was replaced by the MLS of vMIA , and MLS-viperin ( DCA ) in which two cysteine residues ( 88 and 91 ) required for Fe-S cluster association were mutated to alanine [24] . We also used a fusion construct with the enhanced green fluorescent protein ( EGFP ) attached to MLS-viperin , and one with the MLS linked to EGFP directly . Transfected cells were purified by Streptavidin Microbeads using a biotinylated antibody to Thy1 . 1 , also encoded in the construct and separated by an IRES . We examined the expression of GLUT4 and ChREBP ( Figure 4A ) , the intracellular localization of ChREBP ( Figure S3A ) , the expression of lipogenic enzymes ( Figure 4B ) , the accumulation of LDs ( Figure 4C ) , and total lipid synthesis using 14C-labeled acetate as a substrate ( Figure 4D ) in human viperin knockdown cells expressing the chimeric proteins . Expression of the mouse constructs is not affected by the human-specific shRNAs . In contrast to the cells expressing a control vector or MLS-GFP , the cells expressing MLS-viperin or MLS-viperin-GFP significantly increased GLUT4 , ChREBP and lipogenic gene expression , showed nuclear localization of ChREBP , exhibited increased total lipid synthesis , and accumulated LDs ( Figure 4A–4D and S3A ) , indicating that mitochondrial viperin directly induces GLUT4-mediated de novo lipogenesis . Cells expressing wild type viperin , which does not accumulate in mitochondria , or MLS-viperin ( DCA ) did not show the increase in mRNA levels , nor did they increase total lipid synthesis or accumulate LDs ( Figure 4A–4D ) . This indicates that the viperin effects on lipid metabolism require mitochondrial localization and Fe-S cluster binding . Similar results were observed in viperin knockdown cells expressing a chimeric viperin protein with the N-terminal α-helix replaced by the MLS of Tom70 , a host cellular mitochondrial protein ( Figure S3B ) . This excludes the possibility that the MLS from vMIA was itself responsible for the effect . To determine whether the de novo lipogenesis observed was dependent on GLUT4-mediated glucose uptake we measured lipogenic enzyme transcripts in cells expressing the chimeric proteins in the presence or absence of glucose in the medium ( Figure 4E ) . In the absence of glucose the cells expressing MLS-viperin-GFP had significantly increased GLUT4 mRNA content , but mRNA levels for ChREBP and the lipogenic enzymes were unchanged . We also examined lipogenesis in GLUT4 and ChREBP knockdown cells expressing the chimeric proteins ( Figure S3C ) . The expression of ChREBP and lipogenic enzymes in GLUT4 knockdown cells expressing MLS-viperin-GFP was unaffected . However , GLUT4 expression was induced in ChREBP knockdown cells expressing MLS-viperin-GFP , while the expression of lipogenic enzymes was unaffected ( Figure S3C ) . The data support a mechanism in which mitochondrial viperin enhances GLUT4 expression , increasing glucose uptake and thus ChREBP activation , which in turn activates de novo lipogenesis . Similar results were generated using viperin knockout murine embryonic fibroblasts ( MEFs ) expressing the chimeric proteins ( Figure S4 ) . In contrast to the cells expressing a control vector or MLS-GFP , cells expressing MLS-viperin-GFP exhibited significantly increased lipogenic gene expression ( Figure S4A ) , accumulated LDs ( Figure S4B ) , and increased total lipid synthesis ( Figure S4C ) . Our previous work showed that viperin interaction with the mitochondrial enzyme TFP inhibits fatty acid β-oxidation [24] . To determine whether this interaction is responsible for the observed effects on lipid metabolism , we measured lipogenesis in human fibroblasts genetically deficient in the TFP β subunit ( HADHB ) transiently expressing each chimeric protein . In contrast to the results with wild type fibroblasts , lipogenesis in TFP-deficient fibroblasts expressing either MLS-viperin-GFP or Tom70MLS-viperin was unaffected ( Figure 5 and S5 ) . These results indicate that the viperin interaction with TFP is required for the enhanced lipid synthesis induced by HCMV infection , suggesting that GLUT4 activation and lipogenic enzyme stimulation are likely downstream of the inhibition of fatty acid β-oxidation . To address this we examined lipogenesis in cells treated with etomoxir , an inhibitor of mitochondrial long chain fatty acid oxidation ( Figure 6 ) . As anticipated , increased expression of GLUT4 , ChREBP and lipogenic enzymes , as well as accumulation of LDs , were all observed in the etomoxir-treated cells . Taken together , the data indicate that the interaction of viperin with TFP and consequent inhibition of fatty acid β-oxidation is required for the induction of lipogenesis . Finally , to control for the specificity of the viperin shRNA effects and confirm that viperin is involved in lipogenesis in the context of viral infection , we infected cells with a recombinant HCMV ( HCMV . mVIP ) in which the loci US7–US16 , nonessential for in vitro replication , were replaced by mouse viperin-GFP under an inducible promoter such that expression could be enhanced by the addition of doxycycline , although some breakthrough transcription occurred in the absence of doxycycline [24] . Expression of mouse viperin-GFP upon HCMV . mVIP infection restored the wild type phenotype in human viperin knockdown cells in terms of expression of GLUT4 , ChREBP and lipogenic enzymes ( Figure 7A and B ) , accumulation of LDs ( Figure 7C ) , formation of viral envelope ( Figure S6 ) , and production of infectious extracellular and intracellular virus ( Figure 7D ) .
The effects of HCMV upon the metabolic status of infected cells reflect a commitment to macromolecular synthesis , including lipid biosynthesis , rather than generation of energy [4] , [5] , [6] , [7] . Intracellular ATP levels actually decrease , and this has been postulated to induce disruption of the actin cytoskeleton that enhances viral replication [25] , [26] , [27] , [28] . Lipogenesis is increased and LDs accumulate , interpreted to reflect the requirement for viral envelope [4] , [5] , [6] , [7] , [10] , [11] . We previously showed that the decrease in ATP and cytoskeletal actin modulation is because viperin , induced by HCMV and translocated to mitochondria by vMIA , interacts with TFP and inhibits fatty acid β-oxidation [24] . We now show that these events are also responsible for increased lipogenesis . When viperin expression is prevented in HCMV-infected cells they do not exhibit the alterations of lipid metabolism normally observed and , although viral protein synthesis is unaffected and capsids are generated , envelope formation is impaired and the production of infectious virus is reduced . Furthermore , all of these features are restored when mouse viperin is expressed from an HCMV recombinant . In addition , infection by an HCMV mutant lacking vMIA , and therefore unable to transfer viperin to mitochondria , fails to induce lipogenesis . Targeting viperin to mitochondria induces these metabolic changes directly , but not when the cells lack functional TFP , and an activity of viperin mediated by Fe-S cluster binding is essential . The cumulative data suggests that viperin-mediated inhibition of fatty acid β-oxidation reduces the generation of ATP and activates AMPK , which results in the induction of GLUT4 to increase glucose uptake . Activation of AMPK has been shown to be important for HCMV-mediated alterations in metabolism [9] . The increase in cytosolic glucose , in addition to inducing glycolysis , induces ChREBP , which , upon binding glucose , accumulates in the nucleus and activates the transcription of genes encoding lipogenic enzymes , enhancing lipid synthesis during HCMV infection . Interestingly , in HCMV-infected cells expressing viperin-specific shRNAs ChREBP translocation to the nucleus was indeed inhibited , but it was polarized rather than remaining diffuse and cytosolic ( Fig . 1D ) . The localization is reminiscent of the localization of the complex virus assembly compartment that develops in HCMV-infected cells , but as HCMV infection causes multiple effects on cellular morphology the meaning of this observation is unclear . It is also conceivable that the apparent redistribution of ChREBP may an artifact since HCMV expresses an Fc receptor that localizes to the AC late in infection and binds non-specifically to polyclonal rabbit antibodies . This requires further analysis . Consistent with the role of GLUT4-mediated glucose import in inducing ChREBP activity , when viperin is targeted to mitochondria directly in cells cultured without glucose , GLUT4 transcription is still induced but ChREBP transcription is not; nor is the transcription of the lipogenic enzymes that depend on ChREBP expression . We do not know how rapidly these effects on metabolism begin after HCMV infection . Most measurements have been performed at day 1 post-infection or later . However , the kinetics of viperin and vMIA expression are very similar , and viperin substantially co-localizes with mitochondria after 24 hrs , so we might expect that these effects are initiated quite rapidly during the infection . Lipid synthesis is induced by HCMV infection , and in cells lacking viperin expression this increased synthesis is not observed . Presumably because of this the increase in size and number of LDs induced by infection is also not seen in the viperin shRNA-expressing cells . These findings are precisely replicated in the same cells uninfected but expressing mitochondrially-targeted viperin . HCMV infection in the absence of viperin induction both eliminates the size increase and reduces the number of LDs , suggesting that initiating viral envelope formation consumes pre-existing lipids but without the viperin-mediated induction of lipogenesis they are not replaced . This results in a significant decrease in the production of infectious virus . Envelopment of HCMV proceeds by a complex process , involving initial envelopment in nuclear membrane that is shed in the cytoplasm . Secondary envelopment occurs by budding into the secretory pathway . Electron microscopy clearly showed that the number of enveloped particles formed in the secretory pathway was substantially reduced in the viperin knock down cells . However , the synthesis of viral proteins and the total number of viral particles , assessed by genome copy number was unaffected . Although HCMV-induced cleavage of SREBP1 is independent of viperin expression , HCMV infection does not induce expression of lipogenic enzymes and lipid synthesis in the absence of viperin . There are two genes encoding SREBPs , SREBP1 and SREBP2 , and SREBP1 exists in two forms , a and c , depending on the use of alternate promoters . This renders a simple interpretation difficult , but mice lacking SREBP1c do exhibit a reduction of some , but not all lipogenic enzyme transcripts in the liver [41] . Hepatic mRNA expression levels of lipogenic genes were also decreased in ChREBP knockout mice , resulting in a 65% reduction of fatty acid synthesis rates , despite normal mRNA levels of SREBP1c and cleavage of SREBP1 protein [12] . In the case of HCMV infection SREBP1 cleavage may be insufficient to substantially activate lipogenesis in the absence of ChREBP induction , even though preventing SREBP1 cleavage using an shRNA specific for the enzyme SCAP ( SREBP-cleavage activating protein ) inhibited lipid synthesis and HCMV growth [10] , [11] . SREB1a also activates genes controlling cholesterol biosynthesis , which may be why inhibiting SREBP cleavage also affects HCMV replication . Thus there may be synergy between SREBP1 and ChREBP in ensuring efficient membrane generation . Nevertheless , the viperin-dependent induction of lipogenesis by ChREBP is clearly essential for a successful HCMV infection . Overall , the data indicate that viperin is the key regulator of HCMV-induced modulation of lipid metabolism , and it may present a novel target for HCMV therapy . We are still left , however , with the vexed question of the normal function of viperin . Are there physiological circumstances in which a modification of lipogenesis mediated by viperin would be important , and if that is so , how does the molecule enter mitochondria to mediate this effect ? Does this play a role in any of the inhibitory effects on other viruses that have been attributed to viperin ? The answers to these questions await further experiments .
Human foreskin fibroblast ( HFF ) cells were purchased from Yale Skin Diseases Research Center Core . Telomerase-immortalized human fibroflast ( HFtelo ) cells were kindly provided by Dr . T . Shenk ( Princeton University ) . Trifunctional protein ( TFP ) β subunit ( HADHB ) deficient fibroblasts ( GM20265 and GM20266 ) were obtained from the Coriell Institute . MRC5 fibroblasts were kindly provided by Dr . E . S . Mocarski ( Emory University ) . Murine embryonic fibroblasts ( MEFs ) used in the study were isolated from viperin ( Rsad2 ) knockout C57BL/6 mice [24] , [42] and immortalized by serial passages as described previously [43] . HCMV strain AD169 was kindly provided by Dr . W . J . Britt ( University of Alabama at Birmingham ) . HCMV strain RVHB5 and HCMV mutant RVHB5ΔvMIA were provided by Dr . E . S . Mocarski ( Emory University ) [38] . Recombinant HCMV . mVIP used in the study was previously constructed utilizing a recombination strategy to insert Tet-on inducible mouse viperin-GFP fusion plasmid into the HCMV genome maintained in a bacterial artificial chromosome ( BAC ) [24] . HCMV-encoded proteins were detected with monoclonal antibodies ( mAb ) . mAbs to MCP ( UL86 ) ( 28-4 ) , pp65 ( UL83 ) ( 28-19 ) , pp28 ( UL99 ) ( 41-18 ) , gB ( UL55 ) ( 27-78 ) and IE-1 ( UL123 ) ( P63-27 ) were gifts from Dr . W . J . Britt ( University of Alabama at Birmingham ) . mAb to viperin ( aa 263-277 ) ( MaP . VIP ) was described previously [44] , [45] . mAbs to adipose differentiation-related protein ( ADRP ) ( Progen ) , SREBP1 ( IgG-2A4 , BD Pharmingen ) and GRP 94 ( Research Diagnostics ) were used . Polyclonal rabbit Abs to ChREBP ( Abcam ) and actin ( Santa Cruz Biotech ) were also used . Goat anti-rabbit and anti-mouse Ig secondary Abs were purchased from Molecular Probes . Caspase inhibitor I , ZVAD ( OMe ) -FMK ( Calbiochem ) and AMPK inhibitor , Compound C ( Sigma ) were used . HFtelo cells stably expressing the indicated shRNAs were plated in duplicate and serum starved for 24 hr . Cells were infected with HCMV at a multiplicity of infection ( moi ) of 2 . The cells were treated with DMSO or the AMPK inhibitor , Compound C ( 5 µM ) . At 2 dpi , the cells were harvested in lysis buffer ( 50 mM Tris-HCl , pH 7 . 4 , 1% Triton X-100 , 1 mM EGTA , protease inhibitor cocktail ( +EDTA ) ( Roche ) , Phosphatase inhibitor cocktail ( Roche ) and 1 mM DTT ) . The cell lysates were assayed for AMPK activity using CycLex AMPK Kinase Assay Kit ( MBL International Corporation ) . Absorbance of each sample was measured at wavelength of 450 nm using a Victor2 fluorometer ( PerkinElmer ) . Previously generated HFtelo cells stably expressing two distinct short hairpin target sequences to viperin ( Viperin shRNA1 and 2 ) and a negative control , a target sequence to luciferase ( Luc shRNA ) were used [24] . pGIPZ lentiviral plasmids with the short hairpin target sequences to GLUT4 and ChREBP were used ( Open Biosystems ) . To increase knockdown efficiency , two lentiviral plasmids including different target sequences were combined: GLUT4 shRNA1 ( clone ID: V3LHS_376729 and V3LHS_376733 ) , GLUT4 shRNA2 ( clone ID: V3LHS_376728 and V3LHS_376730 ) , ChREBP shRNA1 ( clone ID: V3LHS_334248 and V3LHS_334249 ) and ChREBP shRNA2 ( clone ID: V3LHS_334249 and V3LHS_313472 ) . HFtelo cells stably expressing the indicated shRNAs were generated as described previously [24] . Knockdown efficiency was assessed by western blot or RT-PCR analysis . Lipid synthesis was measured as described [11] , [46] . Briefly , HFtelo cells stably expressing the indicated shRNAs were plated in triplicate and serum starved for 24 hr . The cells were infected with HCMV at a multiplicity of infection ( moi ) of 2 . At 2 hpi , cells were washed , re-fed with fresh serum-free DMEM , and incubated at 37°C for 2 days . For transient expression assays , viperin knockout MEFs were transfected with plasmids encoding chimeric proteins . At 1 day after transfection , the cells were washed , re-fed with fresh serum-free DMEM , and incubated at 37°C for 24 hr . The cells were then counted and incubated in fresh serum-free DMEM containing [1 , 2-14C] acetate ( 2 µCi/ml ) and incubated at 37°C for 3 hr . Labeled cells were washed three times with ice-cold PBS and lysed in 0 . 3 ml of Triton X-100 ( 0 . 5% in H2O ) . Lipids were extracted by sequentially adding 0 . 75 ml of methanol , 0 . 75 ml of chloroform , 0 . 75 ml of chloroform , and 0 . 75 ml of H2O , with vortexing . Samples were centrifuged at 4 , 000 rpm for 15 min; 1 . 2 ml of organic phase ( lower phase ) was recovered and counted in a scintillation counter . The mouse wild type viperin cDNA construct of was generated by PCR amplification and then cloned into pMXs-IRES-Thy1 . 1 . Chimeric viperin constructs were also generated in which residues 1–42 of WT viperin , WT viperin-GFP or mutant viperin ( DCA , substitution of cysteine residues 88 and 91 to alanine residues ) were replaced by the residues 1–34 ( mitochondrial localization sequence , MLS ) of vMIA and then cloned into pMXs-IRES-Thy1 . 1 to yield MLS-viperin , MLS-viperin-GFP or MLS-viperin ( DCA ) , respectively . For the chimeric viperin construct Tom70-MLS-viperin , residues 1–42 of WT viperin were replaced by the MLS ( residues 35–68 ) of human Tom70 and cloned into pMXs-IRES-Thy1 . 1 . EGFP was also fused to residues 1–34 of vMIA ( MLS-GFP ) or residues 35–68 of Tom70 ( Tom70-MLS-GFP ) . Plasmids were electroporated into viperin , GLUT4 and ChREBP knockdown HFtelo cells and TFP β subunit ( HADHB ) deficient HFF cells using a Nucleofector kit ( Lonza ) . At 24 hr after transfection , the transfected cells were sorted by Streptavidin Microbeads ( MACS Miltenyi Biotec ) according to the manufacturer's instructions . The sorted cells were used for quantitative RT-PCR to measure the mRNA levels of lipogenic enzymes . Lipid droplets ( LDs ) were monitored by immunofluorescence . The HCMV-infected or transfected fibroblasts were grown in 24-well tissue culture plates containing a 13-mm-diameter coverslip . The coverslips were harvested by first washing the cells with PBS and then fixing the cells for 45 min at room temperature in 3% paraformaldehyde freshly prepared in PBS . The coverslips were washed in PBS and permeabilized with 0 . 5% saponin in PBS for 10 min . The coverslips were then blocked with 0 . 2% Tween in PBS containing 10% normal goat serum for 20 min at room temperature , followed by the addition of the anti ADRP mAb , and incubated for 1 hr at room temperature . Following washing with 0 . 2% Tween in PBS , the coverslips were incubated with goat anti-mouse Ig secondary Ab conjugated to dye diluted in 0 . 2% Tween in PBS containing 2 . 5% normal goat serum for 1 hr at room temperature . The coverslips were washed three times , rinsed once in PBS and mounted with ProLong Gold Antifade reagent ( Molecular Probes ) . The images were acquired with a Leica TCS SP2 confocal microscope . HFtelo cells stably expressing the indicated shRNAs were infected with HCMV or recombinant HCMV . mVIP at an moi of 2 and examined by electron microscopy at 7 dpi as described previously [45] , [47] . Briefly , the cells were fixed with 2 . 5% glutaraldehyde and post-fixed with 1% osmium tetroxide . Cells were en bloc stained with 2% uranyl acetate , dehydrated , infiltrated , and embedded in Epon . Sixty nanometer sections were stained with lead citrate and examined using a Tecnai 12 Biotwin electron microscope . Cleavage of SREBP1 was assayed by immunoblot as described [10] . Cells were washed with PBS and solubilized in disruption buffer ( 50 mM Tris ( pH 7 . 4 ) , 2% SDS , 5% 2-mercaptoethanol , 2 . 75% sucrose ) containing proteinase inhibitors . The extracts were boiled for 5 min , and centrifuged at 14 , 000 g for 3 min . Supernatants were collected and boiled in reducing sample buffer . The supernatants were separated on 8% SDS-PAGE gels and transferred to PVDF membranes ( Millipore ) . The immunoblots were blocked in 5% skim milk , 0 . 05% Tween in PBS and incubated with mAb against SREBP1 , probed with anti-mouse Ig horseradish-conjugated secondary antibody , followed by incubation with enhanced chemiluminescence ( ECL ) reagents ( Pierce ) . HCMV proteins were detected by immunoblotting . Cell pellets were lysed in 1% Triton X-100 in TBS containing proteinase inhibitors . Supernatants of lysates were collected and mixed with reducing sample buffer . The supernatants were separated on 8% or 10% SDS-PAGE gels . The immunoblots were probed with the indicated antibodies as described above . Cells were collected and total RNA extracted using the RNeasy Mini kit ( Qiagen ) . cDNA synthesis was performed with 1–2 µg RNA using AffinityScript Multi Temperature cDNA synthesis kit according to the manufacturer's instructions ( Stratagen ) . The cDNA obtained from cells was quantified by real-time quantitative PCR ( Q-PCR ) using SYBR Green ( Applied Biosystems ) on Stratagene Mx3000P QPCR system . The following primers were used; β actin , GCTCCGGCATGTGCAA ( Fwd ) and AGGATCTTCATGAGGTAGT ( Rev ) ; GLUT4 , GGAGCTGGTGTGGTCAACACA ( Fwd ) and GGAGCAGAGCCACAGTCATCA ( Rev ) ; ACL , TGTAACAGAGCCAGGAACCC ( Fwd ) and CTGTACCCCAGTGGCTGTTT ( Rev ) ; ACC2 , GACCACAGGTGAAGCTGAGA ( Fwd ) and GTGTTCCCGTCCCCTCTTC ( Rev ) ; FAS , AGGCTGAGACGGAGGCCATA ( Fwd ) and AAAGCTCAGCTCCTGGCGGT ( Rev ) ; DGAT1 , TCGCCTGCAGGATTCTTTAT ( Fwd ) and GCATCACCACACACCAGTTC ( Rev ) ; DGAT2 , TCACCTGGCTCAATAGGTCCA ( Fwd ) and CCAGCAATCAGTGCAGAATATG ( Rev ) ; ChREBPα , AGTGCTTGAGCCTGGCCTAC ( Fwd ) and TTGTTCAGGCGGATCTTGTC ( Rev ) ; ChREBPβ , AGCGGATTCCAGGTGAGG ( Fwd ) and TTGTTCAGGCGGATCTTGTC ( Rev ) . The Q-PCR was performed in triplicate for each sample . Quantitation was performed by the comparative Ct ( 2–[delta][delta]Ct ) method . The Ct value for each sample was normalized by the value for β actin gene . Three independent experiments were analyzed statistically for differences in the mean values , and P values are indicated in the figures . The viral genome copy number was also quantified by real-time PCR as described previously [47] , [48] . Viral DNA were isolated by QIAamp DNA blood kit ( Qiagen ) . The following primers , which amplify a segment of the HCMV UL55 gene were used; ACGTGAAGGAATCGCCAGGA ( Fwd ) and AGTTCCAGTACCCTGAAGTC ( Rev ) . HFFs or HFtelo cells stably expressing the indicated shRNA were infected with HCMV or recombinant HCMV ( HCMV . mVIP ) at an moi of 0 . 2 for 2 hr , washed , and cultured in normal medium or medium supplemented with doxycycline . Supernatants and cells were harvested at 6 dpi , and virus yield was measured by a fluorescence-based virus infectivity assay [49] . Results from all studies were compared with unpaired two-tailed Student's t test using GraphPad Prism 4 software . P values less than 0 . 05 were considered significant .
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Virus infection induces the production of interferons , which in turn stimulate the production of a set of proteins that often have antiviral functions . One of these interferon-inducible proteins is viperin , the product of the human Rsad2 gene . Human cytomegalovirus ( HCMV ) paradoxically induces expression of viperin independently of the interferon response , and we previously showed that a virus-encoded protein transports the induced viperin to mitochondria where it interferes with fatty acid b-oxidation , a major energy generating system of the cell . We show here that this ultimately results in enhanced lipid synthesis by the infected cell that is essential for production of infectious virus . The mechanism involves sensing the depletion in ATP levels caused by inhibition of fatty acid b-oxidation by the enzyme AMP-induced protein kinase . This induces a cascade of events that result in the increased transcription of genes encoding lipogenic enzymes and consequent lipid biogenesis that is needed by the virus for adequate membrane envelope formation . Thus HCMV uses the interferon-inducible protein viperin , known to be antiviral for other viruses , even for HCMV itself if viperin is pre-expressed in cells prior to infection , to modulate the metabolic status of the cell to facilitate its replication .
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[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"medicine",
"biology"
] |
2013
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Viperin Regulates Cellular Lipid Metabolism during Human Cytomegalovirus Infection
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The scale-up of antiretroviral therapy ( ART ) in South Africa substantially reduced AIDS-related deaths and new HIV infections . However , its success is threatened by the emergence of resistance to non-nucleoside reverse-transcriptase inhibitors ( NNRTI ) . The MARISA ( Modelling Antiretroviral drug Resistance In South Africa ) model presented here aims at investigating the time trends and factors driving NNRTI resistance in South Africa . MARISA is a compartmental model that includes the key aspects of the local HIV epidemic: continuum of care , disease progression , and gender . The dynamics of NNRTI resistance emergence and transmission are then added to this framework . Model parameters are informed using data from HIV cohorts participating in the International epidemiology Databases to Evaluate AIDS ( IeDEA ) and literature estimates , or fitted to UNAIDS estimates . Using this novel approach of triangulating clinical and resistance data from various sources , MARISA reproduces the time trends of HIV in South Africa in 2005–2016 , with a decrease in new infections , undiagnosed individuals , and AIDS-related deaths . MARISA captures the dynamics of the spread of NNRTI resistance: high levels of acquired drug resistance ( ADR , in 83% of first-line treatment failures in 2016 ) , and increasing transmitted drug resistance ( TDR , in 8 . 1% of ART initiators in 2016 ) . Simulation of counter-factual scenarios reflecting alternative public health policies shows that increasing treatment coverage would have resulted in fewer new infections and deaths , at the cost of higher TDR ( 11 . 6% in 2016 for doubling the treatment rate ) . Conversely , improving switching to second-line treatment would have led to lower TDR ( 6 . 5% in 2016 for doubling the switching rate ) and fewer new infections and deaths . Implementing drug resistance testing would have had little impact . The rapid ART scale-up and inadequate switching to second-line treatment were the key drivers of the spread of NNRTI resistance in South Africa . However , even though some interventions could have substantially reduced the level of NNRTI resistance , no policy including NNRTI-based first line regimens could have prevented this spread . Thus , by combining epidemiological data on HIV in South Africa with biological data on resistance evolution , our modelling approach identified key factors driving NNRTI resistance , highlighting the need of alternative first-line regimens .
Since ART has been introduced in Southern Africa in 2004 , ART coverage has continuously increased . In 2016 , 55% of individuals living with HIV were receiving ART in the region , the great majority being treated with a standard first-line regimen consisting of two nucleoside reverse transcriptase inhibitors ( NRTI ) and one non-nucleoside reverse transcriptase inhibitor ( NNRTI ) [1] . The scale-up of ART led to a substantial reduction in mortality but the emergence of drug resistance could jeopardize its long-term success [2] . Of particular concern are NNRTIs , as this class has a relatively low genetic barrier to resistance [3] . As documented by the World Health Organization ( WHO ) , the level of pretreatment NNRTI resistance has rapidly increased and reached the 10% threshold in the Southern Africa region in 2015 [4] . According to WHO , this threshold should trigger considerations on changing the first-line regimen . By contrast , resistance to NRTIs , though relevant at the individual level , is only rarely transmitted [4] . In South Africa , adult HIV deaths have decreased from 220 , 000 in 2006 to 99 , 000 in 2014 [2] . In 2016 , an estimated 63% of HIV positive people were on ART in South Africa [1] . While initially only people with CD4 counts lower than 200 cells/μL were eligible to start ART , South Africa adopted the “Treat All” policy in 2017 , which recommends ART for all HIV-positive people regardless of their CD4 counts [5] . The goal is to reach 90% of diagnosed people on ART in 2020 , in line with the 90-90-90 targets of UNAIDS [6] . While the HIV epidemic in South Africa has been well described and extensively modelled [2 , 7 , 8] , relatively little work has been done on drug resistance [9 , 10] . The rapid increase in ART coverage might fuel further increase in drug resistance as more and more people become exposed to the drug , but the impact of the scaling up of ART on the development of NNRTI resistance is not well defined at present . Another key question is whether a better management of treatment failure would have mitigated NNRTI resistance . While understanding the drivers of antiretroviral resistance is crucial for public health , representative , longitudinal data on drug resistance are scarce , compared to the large amount of cohort data available on the clinical and public health epidemiology of HIV . Moreover , quantifying the spread of resistance is challenging because it involves both epidemiological ( transmission , cascade of care , disease progression ) and evolutionary processes ( emergence and selection of resistance mutations ) [11–13] , with the parameters governing the latter typically unknown [13] . We aimed to capture the dynamics of NNRTI resistance in South Africa during 2005–2016 and to quantify the impact that different policy changes would have had on the rise of drug resistance . To this end we developed MARISA ( Modelling Antiretroviral drug Resistance In South Africa ) , a mathematical model integrating the specificities of HIV epidemiology in the country with the evolutionary epidemiology of drug resistance . MARISA is a compartmental , deterministic model whose structure reflects gender-specific dynamics of continuum of care and disease progression , as well as acquisition and transmission of HIV NNRTI resistance . We calibrated the model using data from the International epidemiology Databases to Evaluate AIDS in Southern Africa ( IeDEA-SA , www . iedea-sa . org , [14] ) , literature estimates and HIV key outcomes provided by UNAIDS [1] . The acquisition and transmission of NNRTI drug resistance was integrated within the general dynamics of the HIV epidemic in the country and parametrized with estimates derived from other cohorts . This allowed the estimation of the yearly levels of acquired and transmitted drug resistance ( ADR and TDR , respectively ) . We then assessed the impact of counter-factual scenarios reflecting alternative countrywide public health policies , including policies of increasing ART coverage , improving management of treatment failure , broadening ART indications , or implementing drug resistance testing before initiation .
MARISA is a mechanistic , compartmental model . The first dimension of the model accounts for the whole continuum of care: infection of susceptible individuals , diagnosis , first-line treatment including NNRTI with subsequent suppression or failure , and second-line treatment including protease inhibitors ( PI ) with subsequent suppression or failure ( 8 classes ) . We then consider three additional dimensions: disease progression as characterized by CD4+ T cell counts ( 4 classes ) ; NNRTI resistance status ( 2 classes ) ; and gender ( 2 classes ) . This leads to a total of 128 compartments . The first two dimensions describe the different care stages and their interaction with HIV progression . The third dimension is key to capture the acquisition of NNRTI resistance by individuals with first-line treatment failure ( with rate σres ) , the transmission of resistant strains of HIV to susceptible individuals , and the reversion of HIV resistance mutations when no more drug pressure is exerted ( with rate σrev ) . We assume that individuals infected with the NNRTI resistant virus have higher failure and lower viral suppression rates ( hazard ratio α and α−1 , respectively ) . As one mutation ( e . g . the K103N mutation ) alone confers high-level resistance to NNRTI drugs [15] , only one layer is used to represent NNRTI resistance . The fourth dimension reflects differences observed between women and men , with diagnosis and treatment rates being higher for women than for men [16 , 17] . This dimension is also involved in modelling HIV transmission among adults ( ≥15 years old ) . Movement between compartments is determined by different rates , some of which change over time to reflect modifications in treatment policies or in behavior . Adults living in South Africa who are not infected are represented by the susceptible compartment ( Susc ) , as shown in Fig 1 . The I compartments represent undiagnosed HIV-positive individuals . The force of infection considers three transmission routes among adults: a man can either be infected by a woman ( “heterosexual” or HET transmission ) or , less commonly , by a man ( “men having sex with men” or MSM transmission ) , while a woman can only be infected by a man . HET and MSM populations are only implicitly modelled: we assume a density-dependent transmission that accounts for different risk behaviors according to knowledge of HIV status ( monthly number of unprotected sexual contacts βu and βd for undiagnosed and diagnosed HIV-infected individuals , respectively ) and the expected proportion of HET and MSM among men . Inflow of infected children reaching the age of 15 is also taken into account by using estimates from the Thembisa model and published literature ( See Section 1 . 5 in S1 File ) [2 , 17–19] . Infected individuals become diagnosed at a rate γI→D ( t ) that is allowed to vary over time , by CD4 count and by gender . Once diagnosed ( compartment D ) , individuals will start treatment at a rate γD→T1 ( t ) that also varies over time , reflecting the successive changes in ART guidelines . This rate also depends on the CD4 count , as individuals with lower counts will initiate treatment at higher rates ( see Section 1 . 3 in S1 File ) . First-line ART initiation is represented by the T1 compartment , which characterizes individuals who have been on ART for three months or less . After this period , they can either suppress viral replication ( S1 ) or fail treatment ( F1 ) . These two compartments reflect the use of viral load monitoring in South Africa to identify patients failing first-line treatment that should switch to second-line regimen . We assume that virally suppressed individuals cannot transmit the virus . When failing first-line treatment , individuals are switched to second-line treatment ( compartment T2 ) at rate γF1→T2 . Care and disease progression on second line treatment are modelled identically to first-line therapy . Mortality at each stage differs according to disease progression and care stage . In addition , the mortality rates for patients with CD4 counts below 200 cells/μl are time-dependent , due to the highly variable mortality risk in this class [20] . Overall , the model contains 137 different rates . The total population of each gender follows the WHO estimates for South Africa , and initial conditions in each compartment reflect UNAIDS estimates for 2005 . Further details on the MARISA model are available in Sections 1 and 2 in S1 File . We parameterized and calibrated the model in two successive steps . First , some parameters were given fixed values using external sources . Literature estimates were used for parameters related to NNRTI resistance ( σres , σrev , and α ) , for transmission probabilities per sexual contact , for the proportion of MSM and for the mortality risks ( relatively to suppressed individuals with more than 500 CD4/μL ) . Similarly , values were defined for the time-dependent diagnosis rates ( differentiating between testing asymptomatic individuals , symptomatic individuals and pregnant women , and relatively to the treatment rate in 2005 ) and treatment rates ( relatively to the treatment rate for an eligible individual with less than 200 CD4/μL in 2005 ) . We used estimates from studies conducted in South Africa whenever available . For parameters related to disease progression ( movements between CD4 strata ) and to the continuum of care after starting first-line treatment ( rates of suppression , treatment failure , switching to second line , and treatment interruption ) , we used data from five IeDEA cohorts in South Africa ( Aurum Institute , Hlabisa , Khayelitsha , Kheth’Impilo and Tygerberg ) that provided longitudinal information for 54 , 016 HIV-infected adults [14] . The majority of them were female ( 62% ) . All patients started a first-line regimen and 3905 ( 7 . 2% ) received a second-line regimen . Viral load measurements were used to identify the occurrence of suppression or treatment failure in treated individuals ( using a threshold of 1000 copies/mL ) . Because of low monitoring frequency , the number of available measurements per patient was limited and some intermediate steps in disease or care progression were missing . We thus adapted methods from survival analysis in order to reconstruct patients’ care histories ( see Section 3 . 1 in S1 File ) . See Table 1 for more details about parameters . During the second phase , the 7 remaining unknown parameters were estimated by fitting the model to estimates from the Thembisa model for the period 2005 to 2015: annual numbers of new HIV infections , number of undiagnosed individuals , annual number of AIDS-related deaths and ART coverage ( Table 2 and Fig 2 ) . The Thembisa model is a compartmental model providing UNAIDS with estimates on the South African HIV epidemic . Inference relied upon a maximum likelihood approach , assuming Poisson-distributed errors . We thus obtained point estimates for the monthly numbers of unprotected sexual contacts βu and βd , for the base diagnosis rate in 2005 and its increase between 2005 and 2016 , for the treatment rate in 2005 , for a scale parameter modelling the decrease in the proportion of individuals with CD4 <50 cells/μL ( only used for mortality estimates ) , and for the mortality rate of suppressed individuals with more than 500 CD4/μL ( see Table 1 ) . Further details are available in the Section 3 in S1 File . The model was simulated from 2005 to 2016 using the specified parameter values and a monthly time step . Several outcomes were computed from the output , including the proportions of NNRTI ADR ( proportion of individuals in F1 compartments with NNRTI resistance , see Eq 15 in S1 File ) and of NNRTI TDR ( proportion of individuals coming from I to D compartments with NNRTI resistance ) . When not specified otherwise , NNRTI TDR is measured in newly diagnosed patients ( D ) ( see Eq 16 in S1 File ) . Alternatively , we determine the proportion of NNRTI resistance in newly infected patients , newly diagnosed patients or in ART initiators . In this latter case , as it comprises drug-experienced people , we used the term pre-treatment drug resistance ( PDR ) , rather than TDR . Four counterfactual scenarios were examined with the model . The first counterfactual scenario assessed the impact of treatment initiation ( γD→T1 ) increased by factors 2 , 3 or 5 . The second counterfactual scenario investigated the impact of an earlier switch to second-line regimen ( γF1→T2 ) when failing the first-line regimen , by factors 2 , 5 or 10 . The third and fourth scenario examined the impact of different testing and treatment policies . In the third scenario , the “Treat All” policy , i . e . initiating first-line treatment of diagnosed individuals regardless of CD4 counts , was implemented at a hypothetical earlier point in time ( moved forward by 1 . 5 , 3 or 6 years ) . The fourth scenario implemented drug resistance testing and immediate second-line treatment of individuals harboring a resistant strain at baseline . We performed a multivariate sensitivity analysis in order to quantify the impact of uncertainty on the values of 1 ) four parameters related to NNRTI resistance ( σres , σrev , α and the rates of treatment interruption ) and 2 ) three parameters related to HIV transmission ( percentage of MSM , probability of male-to-male infection per sexual contact , and ratio between HIV prevalence in MSM and HET ) . Multivariate uncertainty within specified ranges was introduced using Latin hypercube sampling [29] . Each model estimate is reported with a 100% sensitivity range . Further details are available in Section 4 . 2 in S1 File .
The model reproduces the main time trends of the HIV epidemic in South Africa 2005–2016 ( Fig 2A–2D ) . There is a clear increase in ART coverage since 2005 , attaining 48% of infected individuals in 2015 , and a significant drop in the number of undiagnosed individuals , as a result of the increasing number of HIV tests performed annually . In 2015 , the model estimated that 0 . 79 million of the 6 . 9 million infected individuals ( 11 . 4% ) were not yet diagnosed . The number of yearly newly-infected individuals decreased from over 400 , 000 individuals in 2006 to about 300 , 000 in 2016 . The decrease in risk behavior due to testing among HIV-positive individuals is estimated at 46% ( βd/βu = 0 . 54 ) , in line with a behavioral study conducted in South Africa in 2013 [30] . Finally , HIV-related deaths dropped from over 200 , 000 in 2006 to 109 , 000 in 2016 . The MARISA model also captures the dynamics of NNRTI ADR and TDR , showing very high levels of ADR ( Fig 2E ) and increasing levels of TDR ( Fig 2F ) in South Africa after 2004 . The model estimates that 73% of the individuals failing the first-line regimen had ADR to NNRTI in 2008 , with a slight yet steady increase in the following years , surpassing 83% in 2016 . Moreover , the model estimated that 13 . 8% of these individuals were already resistant at the time of failure . NNRTI TDR among newly diagnosed individuals increased from 0 . 9% to 8 . 1% during the period . Interestingly , the model indicates substantial variation in TDR levels over the four CD4 strata , ranging from 2 . 9% for newly diagnosed individuals with less than 200 CD4/μL to 10 . 0% for those with more than 500 CD4/μL in 2016 . For newly infected individuals , the NNRTI TDR level reaches 15 . 0% in 2016 . We also observe a high PDR prevalence among individuals initiating first-line ART ( 6 . 5% in 2016 ) . Finally , the model estimated that 16 . 9% of ADR cases in 2016 were related to TDR ( see Eq 17 , in S1 File ) . In the first scenario , increasing the treatment rate by a factor 2 , 3 or 5 during the whole period would have led to a substantial reduction of the number of annual deaths , but would have had little effect on the number of newly-infected or the number of undiagnosed individuals ( Fig 3 ) . The decrease in new infections due to increased treatment rates is modest for two reasons: 1 ) the low proportion of HIV-infected individuals who are ART eligible ( only 28% of HIV-infected individuals are diagnosed in 2005 ) and 2 ) the decrease in the number of deaths of infectious individuals when increasing ART coverage ( 67 , 000 deaths of infectious individuals prevented per year in 2005–2012 under the 5-fold increase scenario ) . As expected , increasing treatment rates would not have impacted NNRTI ADR levels . On the other hand , by increasing the number of individuals at risk of acquiring NNRTI resistance , it would have led to a considerable increase of NNRTI TDR levels , surpassing 15 . 0% in 2016 in the 5-fold increase scenario . In the second scenario , increasing the rate of switching to second-line treatment in case of first-line treatment failure ( i . e . dividing the time spent in treatment failure ) by factors 2 , 5 or 10 would not have influenced the four key HIV outcomes ( Fig 4 ) . However , the model predicts a substantial decrease in the levels of both NNRTI ADR and TDR ( to 51 . 5% and 3 . 1% , respectively ) , for the 10-fold increase scenario compared to 83% and 8 . 1% , respectively , for the baseline model in 2016 . Moving the “Treat-All” policy forward in time by 1 . 5 , 3 or 6 years in the third scenario , would have hardly reduced mortality , as it targets individuals with high CD4 counts . On the other hand , removing infectious individuals with high CD4 counts , who are most likely to achieve viral suppression , would have led to a decrease in the number of new infections ( 256 , 000 for the 6-year-early implementation scenario instead of 302 , 000 in the baseline model in 2016 ) . Increasing ART coverage might , however , increase the spread of resistance as NNRTI TDR increased to 10 . 3% in this scenario . Finally , in the fourth scenario , drug resistance testing , by directly starting individuals with NNRTI resistance on second-line regimens , would have slightly improved viral suppression among resistant individuals ( 59 . 3% instead of 56 . 9% in the baseline model ) and also reduced the transmission of resistance ( 14 . 4% instead of 15% resistant among newly infected in 2016 ) . The relative impact of each counterfactual scenario on the number of new infections , AIDS-related deaths and the numbers of both new NNRTI TDR and ADR cases in 2016 , as well as their relative percentages is shown in Table 3 . Sensitivity analyses showed that uncertainty in the values of four resistance-related parameters ( σres , σrev , α and the rates of treatment interruption ) and of three parameters related to HIV transmission ( percentage of MSM , probability of male-to-male infection per sexual contact , and ratio between HIV prevalence in MSM and HET ) did not modify substantially the main outcomes of the MARISA model ( Fig 2 ) .
In this comprehensive modelling study , we show that the MARISA model captured the dynamics of the HIV epidemic in South Africa over the years 2005–2016 . More importantly , it reproduced the emergence of NNRTI resistance , following the roll-out of ART in 2004 . The four counterfactual scenarios provided insights into the drivers of NNRTI resistance . They highlighted the close association between the magnitude of ART roll-out and the extent of NNRTI drug resistance . The results also suggest that a better management of first-line treatment failure , improving identification of treatment failure and switching to second-line treatment , might have reduced AIDS-related mortality and new HIV infections , while offering a better control of NNRTI resistance . However , our results also show that while some policies result in substantial reductions in NNRTI TDR , no measure could have stopped its increase . Even with optimal monitoring and management , NNRTI resistance would have rapidly spread in South Africa , suggesting that NNRTI resistance is inevitable if NNRTI-based regimens are used for first-line therapy . The MARISA model fit was good regarding all four key outcomes of the HIV epidemic in South Africa produced by Thembisa/UNAIDS for the period of study: new infections , number of undiagnosed individuals , AIDS-related deaths and ART coverage [1 , 17] . The estimates related to the “90-90-90” target provided by our model are also in line with those from UNAIDS . The proportion of HIV-infected individuals knowing their HIV status was estimated at 88% and 86% in 2015 by our model and UNAIDS , respectively . The second “90” was slightly underestimated by the MARISA model: the proportion of individuals with diagnosed HIV infection receiving ART was estimated at 52% in 2015 , compared to estimates of 56% and 60% from Thembisa and UNAIDS , respectively . Finally , the proportion of individuals receiving ART achieving viral suppression was estimated at 79% , compared to 78% by UNAIDS [1] . NNRTI ADR and TDR levels estimated by the MARISA model were comparable , though slightly lower , to estimates from six cross-sectional studies conducted during this period [21 , 27 , 31–33] . Of note , these observational data were not used for model calibration and the resistance-specific processes of the MARISA model were partly informed using published estimates from other settings ( in particular the rate of reversion to a drug-susceptible strain [22] and the positive association between drug resistance and treatment failure [23] ) , since no data for South Africa were available . Beyond sampling variability in the estimates from the cross-sectional studies , the discrepancy in ADR and TDR estimates between MARISA and the cross-sectional studies could be explained by several factors: a higher proportion of individuals with previous exposure to ART in the studied samples ( e . g . through prevention of mother-to-child transmission , not included in the MARISA model ) , selection bias in the cross-sectional studies ( e . g . regarding gender , age , socio-economic features or time since infection ) , publication bias by which lower measurements of ADR and TDR are less likely to be published , or possibly a misspecification of some parameters of the MARISA model due to geographical differences . Note that TDR and ADR reflect different populations and processes . ADR is measured in people failing therapy , while TDR is measured in newly diagnosed individuals . The term ADR is somewhat imprecise since we measure it as the proportion of all drug resistant infections among individuals failing treatment and some of these individuals acquired the resistance already by infection . It reflects , however , the terminology used in resource limited settings , where baseline resistance tests are not routinely performed . Our simulations showed that the vast majority of these ADR cases were indeed acquired after treatment failure: in 2016 , only 16 . 9% of ADR cases resulted from treatment failing in individuals already infected with a resistant virus , while the remaining resulted from the selection of resistance mutations in individuals failing on therapy with an initially sensitive virus ( see Eq 17 in S1 File ) . This patterns also explains the relatively weak increase over time ( from a high initial level ) that is observed for ADR ( Fig 2E ) . Interestingly , MARISA revealed heterogeneity in NNRTI TDR levels across CD4 strata , with higher levels of NNRTI TDR associated with higher CD4 counts . This can be explained by the fact that individuals with high CD4 counts are more likely to have been recently infected , and thus exposed to a higher risk of NNRTI TDR as the prevalence of NNRTI-resistance increases with time . Other studies have indeed observed a higher NNRTI TDR level among acutely than chronically HIV-infected patients [34] . Given that untreated patients with low CD4 counts might have been infected for a longer time , another explanation could be the increased probability of reversion from a drug-resistant to a wild-type strain in these patients . The counterfactual scenarios identified two main drivers of the emergence and spread of NNRTI-resistance: the magnitude of the ART roll-out and low frequency of monitoring of first-line treatment failure . The first scenario underlined the inherent risks of resistance emergence induced by a rapid and generalized ART scale-up . This observation is supported by findings of Hamers et al . [35] that the level of NNRTI TDR is associated with time since ART roll out in sub-Saharan Africa . According to the first scenario , policies focused on increasing ART coverage would have allowed a better control of the HIV epidemic , reducing both mortality and new infections . However , such policies would have likely resulted in even higher levels of NNRTI TDR during 2005–2016 , leaving doubt about the long-term sustainability of this approach . As seen in the second counterfactual scenario , an earlier treatment switch for individuals failing NNRTI-based treatment would not have prevented resistance from emerging . In this context , the high NNRTI-mutation rate ( after on average 6 months in the presence of treatment failure ) makes the emergence of NNRTI resistance almost inevitable . For instance , we observe an emergence of TDR ( 3 . 3% in 2016 ) and a substantial level of ADR ( 50% in 2016 ) , even when assuming that from 2005 an optimal management of treatment failure complying with the South African Department of Health 2016 guidelines [36] was in place . The guidelines recommend a VL measure every six months and an immediate switch to second-line ART after failure of two months of adherence counselling ( corresponding to an average time before switching of 1/γF1→T2 = 5 months ) . Still , policies focused on improving first-line treatment failure identification and early switching to second-line treatment would have likely led to better control of both the HIV epidemic ( with fewer AIDS-related deaths and new infections ) and the extent of NNRTI resistance in South Africa . An earlier implementation of the “Treat-All” policy in the third scenario would have modestly decreased mortality , as it extends ART to individuals with high CD4 counts . However , the simulations emphasized the risk of increased levels of NNRTI TDR following implementation of this policy , in a similar way to policies simply increasing ART coverage . Finally , the fourth scenario showed the limited impact on HIV outcomes of implementing drug resistance testing at baseline . Immediate PI-based treatment in patients with TDR only slightly diminished NNRTI TDR prevalence . This small effect may be explained by the limited number of patients affected by the policy ( i . e . newly-infected individuals carrying a resistant strain and initiating ART ) , whose contribution to the transmission of resistance was relatively small ( TDR accounts for only 16 . 9% of ADR cases ) . We acknowledge that assuming the same failure rates in the counterfactual scenario for patients on a PI-based first-line regimen as for patients on a PI-based second-line regimen may lead to under estimation of the effect of baseline resistance monitoring , because rates of failure in patients on first-line PI-based regimen are probably lower . The model has several limitations . First , as the estimates from the Thembisa model were used to fit MARISA , findings produced by MARISA partly rely on the accuracy of Thembisa model . Second , it does not take into account NRTI mutations , which could also affect the success of first-line treatment . However , as transmission of NRTI mutations remains at a low level , their impact on the overall effectiveness of first-line regimens is limited [4] . Third , adherence is not modelled explicitly in the model , as it is not systematically assessed in the IeDEA cohorts . Nevertheless , adherence is implicitly included in MARISA , as estimates of suppression and failure rates rely on a large cohort of individuals with different levels of adherence . Moreover , modelling of HIV transmission was based on simplified assumptions: the model only distinguished male from female transmission and attributed two different transmission rates according to awareness of HIV-status . The probability of HIV-infection per sexual act was assumed to be identical for all unsuppressed individuals . The heterogeneity in sexual behavior within genders was only approximated , and MARISA does not account for interactions between resistance status and sexual behavior . However , in view of the good fit to the number of new infections , there is no need for introducing a more complex representation of HIV transmission dynamics . Finally , the model does not simulate prevention of mother-to-child transmission , which could be an important source of NNRTI resistance . Overall , there is a trade-off between these potential additional layers of complexity and the limited knowledge about specific mechanisms . We argue that the ability of the MARISA model to capture the dynamics of NNRTI resistance with parameters fixed to known values from external data supports the validity of these simplifications . As it stands , the model does not make any unverifiable assumptions , and the sensitivity analyses showed that conclusions were robust , despite uncertainty in the main parameters related to resistance and transmission . Furthermore , the relatively simple representation of NNRTI resistance emergence and transmission makes the model easily interpretable . MARISA can be adapted to address other questions on HIV drug resistance by adding further layers of complexity . The imminent roll-out of Dolutegravir ( DTG ) has been presented as a response to the NNRTI resistance epidemic [5] . In South Africa , DTG in combination with two NRTI-class drugs will progressively replace NNRTI as the first-line regimen for men , but there is uncertainty as to whether it should be recommended for women of reproductive age due to safety issues [37] . DTG will also be prescribed to patients failing NNRTI-based regimens . As NRTI resistance mutations might already have occurred in these patients , this could affect the future success of the DTG-based regimen [38 , 39] . From this basis , MARISA can be extended in order to evaluate the potential impact of introducing DTG-based regimens , either for men and women or for men only . While the overall structure of the model in terms of care and disease progression will stay unchanged , the resistance dimension can be expanded by adding key NRTI-resistance mutations ( e . g . K65R and M184V ) . We could also stratify the model by age group in order to represent the difference in drug prescription ( NNRTI or DTG ) in women according to age . MARISA could thus be used to predict the spread of NRTI- and NNRTI-resistance mutations according to the different strategies of DTG roll-out and their impact on the overall success of HIV-epidemic . To conclude , we propose MARISA , a mechanistic model aimed at providing insight into the NNRTI resistance epidemic in South Africa in 2005–2016 . Integrating information from several sources , including local cohorts of HIV-infected individuals , the model captured the essence of NNRTI resistance emergence in South Africa . Counter-factual scenarios identified key drivers of the NNRTI resistance epidemic at the policy level: a rapid , large-scale ART roll-out and an insufficient monitoring of first-line treatment failure . The model also showed that the rapid rate of acquisition and slow rate of reversion of NNRTI drug resistance mutations make it difficult to prevent their spread if NNRTI-based treatments are used as a first-line regimen , and it indicated the limited effect of drug resistance testing . Understanding future challenges in HIV drug resistance such as the introduction of DTG , its effect on the epidemic , the possibility of DTG resistance , and the impact of NRTI mutations on DTG based regimens will require the modelling of a more complex and uncertain mutational landscape . MARISA , with its backbone of a simple yet adequate epidemiological model will provide a suitable foundation to address this challenge .
|
Resistance to non-nucleoside reverse transcriptase inhibitors ( NNRTI ) threatens the long-term success of antiretroviral therapy ( ART ) roll-out in South Africa . We developed a compartmental model integrating the local HIV epidemiology with biological mechanisms of drug resistance . A first dimension of the model accounts for the continuum of care: infection , diagnosis , first-line treatment with suppression or failure , and second-line treatment . Other dimensions include: disease progression ( CD4 counts ) , gender , and acquisition and transmission of NNRTI resistance . Whenever possible , we informed the parameters using the data available from local cohorts . Other parameters were informed using literature or UNAIDS estimates . The model captured the rise of NNRTI resistance during the period . We assessed the impact of counter-factual scenarios reflecting alternative countrywide policies during the period 2005 to 2016 , considering either increasing ART coverage , improving management of treatment failure , broadening ART eligibility , or implementing drug resistance testing before ART initiation . We identified key drivers of the NNRTI resistance epidemic: large-scale ART roll-out and insufficient monitoring of first-line treatment failure . The model also suggested that no policy including NNRTI-based first line regimens could have prevented the spread of NNRTI resistance .
|
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2019
|
Bridging the gap between HIV epidemiology and antiretroviral resistance evolution: Modelling the spread of resistance in South Africa
|
The spindle checkpoint is a mitotic surveillance system which ensures equal segregation of sister chromatids . It delays anaphase onset by inhibiting the action of the E3 ubiquitin ligase known as the anaphase promoting complex or cyclosome ( APC/C ) . Mad3/BubR1 is a key component of the mitotic checkpoint complex ( MCC ) which binds and inhibits the APC/C early in mitosis . Mps1Mph1 kinase is critical for checkpoint signalling and MCC-APC/C inhibition , yet few substrates have been identified . Here we identify Mad3 as a substrate of fission yeast Mps1Mph1 kinase . We map and mutate phosphorylation sites in Mad3 , producing mutants that are targeted to kinetochores and assembled into MCC , yet display reduced APC/C binding and are unable to maintain checkpoint arrests . We show biochemically that Mad3 phospho-mimics are potent APC/C inhibitors in vitro , demonstrating that Mad3p modification can directly influence Cdc20Slp1-APC/C activity . This genetic dissection of APC/C inhibition demonstrates that Mps1Mph1 kinase-dependent modifications of Mad3 and Mad2 act in a concerted manner to maintain spindle checkpoint arrests .
Defects in chromosome segregation result in aneuploidy , which can lead to disease or cell death [1 , 2 , 3] . Mitosis is an extremely complicated and well orchestrated stage of the cell cycle , and many controls are employed to ensure its high fidelity . One of the major controls is the spindle checkpoint which acts as a surveillance system monitoring kinetochore-microtubule attachments . It delays anaphase onset until all sister-chromatid pairs are bi-oriented on the mitotic spindle [4 , 5 , 6] . Anaphase onset is initiated by an E3 ubiquitin ligase , known as the anaphase promoting complex or cyclosome ( APC/C ) , and its activating co-factor Cdc20Slp1 [7 , 8] . Cdc20Slp1-APC/C targets the separase inhibitor securin and the CDK1 activating subunit cyclin B for destruction by the 26S proteasome [9 , 10 , 11] . Once securin is destroyed , cohesin is cleaved and sister chromatids separate and segregate in anaphase [12] . The spindle checkpoint utilises several mechanisms to efficiently inhibit Cdc20Slp1-APC/C . These include sequestration and phosphorylation of Cdc20Slp1 [13] , formation of the mitotic checkpoint complex ( MCC ) that typically consists of the spindle checkpoint proteins Mad2 , BubR1/Mad3 , Bub3 and Cdc20Slp1 [14 , 15 , 16 , 17 , 18] and MCC binding to the APC/C [19 , 20 , 21 , 22] . Spindle checkpoint components are highly conserved from yeast to humans , and include the MAD ( mitotic-arrest deficient ) and the BUB ( budding uninhibitied by benzimidazole ) genes [23 , 24] . Spindle checkpoint kinases include Mps1Mph1 , Bub1 and Aurora BArk1 , but their precise signalling roles remain far from clear [25 , 26 , 27 , 28] . S . pombe Mph1 is a structural and functional homologue of S . cerevisiae Mps1 , but it is neither required for spindle pole duplication nor essential for cell viability [29] . Homologues in higher organisms have been shown to be essential for the spindle checkpoint and for efficient chromosome segregation [30 , 31 , 32 , 33 , 34 , 35 , 36] . The fission yeast Mps1Mph1 substrates identified to date are KNL1Spc7 [37 , 38] and Mad2 [39] . KNL1Spc7 is an important Mps1Mph1 substrate at kinetochores , which when phosphorylated becomes the kinetochore binding site for the Bub1-Bub3 complex [37 , 38] . This role is conserved in budding yeast and vertebrates [38 , 40 , 41 , 42] , and structural studies have shown that it is Bub3 that binds directly to the MELT motifs after they are phosphorylated by Mps1Mph1 [43 , 44] . In budding yeast it has been shown that Mps1Mph1 kinase then phosphorylates kinetochore-bound Bub1 to enhance the recruitment of the Mad1-Mad2 complex [45] , but this remains to be confirmed in other systems . Thus Mps1Mph1 kinase has a key role in assembling the checkpoint signalling scaffold ( KNL1Spc7-Bub1-Mad1 ) at yeast kinetochores . Additional substrates of Mps1Mph1 kinase have been identified , including spindle pole body components [46 , 47] , the Borealin component of the human chromosomal passenger complex ( CPC ) [30] , and the Dam1 [48] and Ndc80 [49] kinetochore proteins . Thus it is clear that Mps1Mph1 kinase is a central player in mitotic regulation [27] . In a previous study we identified Mad2 as an Mps1Mph1 checkpoint substrate and described the mad2-S92A allele that displayed reduced MCC-APC/C binding and reduced ability to maintain spindle checkpoint arrest [39] . Here we demonstrate that Mad3 is another important checkpoint substrate for Mps1Mph1 kinase . Twelve in vivo phosphorylation sites were mapped in Mad3 , probably due to the action of multiple protein kinases ( CDK , Mph1 and Ark1 ) and sixteen phospho-modifications were generated and mapped in vitro through the direct action of Mps1Mph1 kinase . A series of phosphorylation site mutants were generated , and mutations in the C-terminus of Mad3 were found to have impaired checkpoint function . These defects were compounded in strains where the mad3-C9A allele was combined with mad2-S92A . Importantly , when C-terminal Mad3 phosphomimics were directly tested in vitro they were found to be potent APC/C inhibitors . We propose that Mps1Mph1 kinase phosphorylates multiple components of the fission yeast MCC to stabilise its interaction with the APC/C and thereby maintain spindle checkpoint arrests .
We previously reported that Mad2p is phosphorylated by Mps1Mph1 kinase , and that mutation of Mad2p phosphorylation sites partially abrogated the spindle checkpoint [39] . However , the checkpoint phenotype of Mps1Mph1 kinase-dead alleles was much stronger , indicating that other relevant Mps1Mph1 substrates remain to be found . Whilst phosphorylation of KNL1Spc7 at kinetochores may account for some of this checkpoint function [37 , 38] , there was still a defect apparent in the mps1∆ spc7-T12E strain where all the Mps1Mph1 sites in KNL1Spc7 had been mutated to phosphomimic ( Glutamate ) residues [38] , again arguing for additional Mps1Mph1 substrates . The bub3∆ phenotype , where Bub1p , Mad3p , Mad1p and Mad2p all fail to be recruited to kinetochores yet the checkpoint arrest remains robust , also argues against an absolute requirement for checkpoint proteins to be recruited to KNL1Spc7 and kinetochores in fission yeast [50 , 51 , 52] . In the absence of Mps1Mph1 kinase activity the mitotic checkpoint complex ( MCC ) is not tightly associated with APC/C [39] , so we tested whether fission yeast Mad3p is also a substrate of Mps1Mph1 kinase . First we analysed the in vivo dependence of Mad3p modification on Mps1Mph1 kinase . No clear gel shifts were apparent for Mad3p on regular SDS-PAGE and so we employed 2D gel-immunoblotting , comparing Mad3p modification in wild-type cells and cells lacking Mps1Mph1 kinase activity . As mps1-kd cells are unable to checkpoint arrest [39] we compared Mad3p modification after cells had been mitotically arrested through overexpression of Mad2p [53] . Fig 1A shows a clear charge-related shift for Mad3p isoforms in the two mitotic yeast extracts , demonstrating that Mad3p is modified in an Mps1Mph1 -dependent manner in fission yeast during mitosis . Next we carried out in vitro Mps1Mph1 kinase assays using recombinant Mad3-MBP as substrate ( Fig 1B ) . These assays were analysed by mass-spectrometry , both with and without phosphopeptide enrichment on titanium oxide beads ( see Materials and Methods ) . Under these conditions , sixteen in vitro Mps1Mph1 sites in Mad3p ( see Fig 1C and S2 Fig for spectra ) were identified . To confirm these are phosphorylation sites in vivo we purified checkpoint complexes ( purifying Mad3-TAP and Apc4-TAP ) containing Mad3p from both cycling and checkpoint arrested ( nda3 ) fission yeast cells , and analysed them by MudPIT [54] . We were able to confirm that eight of the in vitro Mps1Mph1 sites ( S19 , S31 , S33 , T64 , T259 , S276 , T278 , S279 ) are also modified in Mad3p purified from yeast cells ( in vivo ) . In addition , four other in vivo sites ( T82 , S246 , S251 and S289 ) were found in Mad3p , identifying modifications that are presumably made by other protein kinases . Whilst we do not know the identity of the other Mad3p kinase ( s ) , we think it extremely likely that S289 is a CDK site and note that T82 fits the Aurora ( Ark1 ) consensus . Mutation of the CDK site alone had no detectable phenotype ( see S3 Fig ) . Several of the Mps1Mph1 sites are conserved in fission yeasts ( see S1 Fig ) . Whilst none of the Mps1Mph1 sites are particularly well conserved in other organisms , we think it noteworthy that there are conserved clusters of Mps1Mph1 phosphorylatable residues flanking both of the Mad3p KEN boxes and that seven of these clustered residues ( S19 , S31 , S33 , T259 , S276 , T278 , S279 ) were only modified in mitotic samples . The Mad3p phosphorylation sites that we identified are summarised in Fig 1C and S1B Fig . To test the physiological relevance of these Mps1Mph1 dependent modifications , we constructed mutations in Mad3p phosphorylation sites in various combinations , substituting serine and threonine residues with non-phosphorylatable alanines ( mad3-N9A , mad3-C9A and mad3-18A –see S1A Fig for full fission yeast Mad3p alignments ) . In vitro kinase assays were performed using Mps1Mph1 kinase and recombinant Mad3-MBP fusion proteins containing these mutations ( Fig 1D ) . Quantitation demonstrated that the N-terminal sites account for ~50% of the in vitro modification and the C-terminal sites ~30% . Importantly , mutation of all 18 sites reduced phosphorylation by ~80% , indicating that we have identified almost all of the in vitro sites for Mps1Mph1 kinase . These mutations were then tested in yeast , by replacing the endogenous mad3+ gene with the mutant alleles . They had no effect on Mad3 protein targeting to kinetochores ( Fig 2A ) nor lead to significant growth defects when grown on plates containing the anti-microtubule drug benomyl ( see S3 Fig ) . However , when we employed more sensitive assays for loss of spindle checkpoint function significant defects became apparent . The mad3 alleles were tested for their ability to checkpoint arrest cells containing kinetochore defects , by employing the temperature-sensitive nuf2-3 allele [55] at 32°C , where typically ~30% of cells should arrest with short spindles after 4 hours ( Fig 2B ) . This experiment demonstrates that whilst mutation of nine N-terminal phosphorylation sites in Mad3p had no effect on the ability of cells to arrest in response to kinetochore attachment defects , mutation of nine C-terminal sites reduced the efficiency of the nuf2-3 arrest by ~40% . Mutating all eighteen sites to alanine made the arrest even worse ( ~50% efficiency ) , but this further decrease is hard to interpret as it could partly be due to the reduced stability of this mutant Mad3 protein . The levels of the mutant Mad3 proteins were ~75% for mad3-C9A but only ~20% for mad3-18A , and others have shown that when Mad3p falls below 30% of its normal level it can perturb the checkpoint [56] . We propose that phosphorylation of Mad3p , in particular towards its C-terminus , can enhance its ability to maintain a checkpoint arrest and thereby delay anaphase onset . These results lead us to focus on the C-terminal Mad3p phosphorylation sites for the rest of this study . To confirm their checkpoint defect we challenged mitotic mad3-C9A cells growing in liquid culture with the anti-microtubule drug carbendazim ( CBZ ) and analysed their rate of septation ( mitotic exit ) . Failure to maintain spindle checkpoint arrest leads to an increase in septation index . We pre-synchronised cdc25 strains in G2 ( growing them for 3 . 5 hrs at 36°C ) and then released them ( shifting down to 24°C ) to undergo synchronous mitoses . Twenty minutes after G2 release we added 75μg/ml CBZ to depolymerise their microtubules . Using this assay we compared the mad3-C9A allele with the mad2-S92A and mps1-kd alleles we have previously described [39] . Fig 2C shows that the mad3-C9A cells fail to effectively maintain a checkpoint arrest and septate with very similar kinetics to mad2-S92A . We made a double mutant ( mad3-C9A mad2-S92A ) and found that these cells have a synthetic checkpoint defect and septate at a faster rate , in between that of the single mutants and the mps1-kd allele ( see S4A Fig for representative images ) . We note that in some of these septating cells Mad3-GFP can still be detected on kinetochores after cells have septated ( see S4B Fig ) : this observation is consistent with such cells having a downstream defect in maintenance of their checkpoint arrest , rather than a Mad3 defect in checkpoint signalling at kinetochores and/or their checkpoint being satisfied due to proper kinetochore-microtubule attachments being formed . The synthetic effect of the double mutant was also observed when the checkpoint was activated in the nda3 mutant , with 33% of mad3-C9A mad2-S92A cells unable to maintain a checkpoint arrest after 8 hours ( compared to 0 . 5% of wild type , 2% of mad3-C9A and 11% of mad2-S92A leaking through the arrest , Fig 2D ) . We conclude that reduced phosphorylation of either Mad3p or Mad2p impairs maintenance of a checkpoint arrest , and that reduced phosphorylation of both proteins further reduces their ability to maintain a robust checkpoint response . Our interpretation is that Mad3p and Mad2p are both phosphorylated by Mps1Mph1 kinase and that these modifications act in concert to inhibit Cdc20Slp1-APC/C . Next we wanted to analyse whether the phosphorylation of the Mad3p C-terminus was relevant to MCC assembly and/or stabilisation . To do this , we carried out cdc25 ( G2 ) block and release time courses and monitored MCC assembly in the mad3-C9A , mad2-S92A , mad3-C9A mad2-S92A double mutants and mps1-kd mutants . Cdc20Slp1-pull downs , employing an internally-engineered 3xFLAG tag ( see Materials and Methods ) demonstrated that MCC was assembled with normal kinetics in mad3-C9A and mad2-S92A alleles ( Fig 3A ) , but that there were slightly reduced MCC levels in the double mutant . We note that MCC levels dropped significantly , by 70% compared to wild-type at 45 minutes , in the mps1-kd strain ( Fig 3B ) . Quantitation of the Cdc20Slp1 protein levels in extracts through these time courses ( see S6 Fig ) shows that they are only reduced in the mps1-kd mutant , and there only by 20% which can not explain why the MCC levels drop by 70–80% in this strain . No clear effect on mitotic progression was observed in these unperturbed mitoses ( Fig 3C ) , suggesting that it is not MCC levels that are rate-limiting . We conclude that phosphorylation of neither the C-terminus of Mad3p nor of Mad2p are critical for MCC assembly . Even when both Mad3p and Mad2p phosphorylation are impaired , only slightly reduced MCC levels result ( 20–30% reduction in bound Mad2p relative to wild-type levels ) . This compares with the far more significant reduction in MCC levels observed in the mps1-kd cells . Having detected only subtle MCC assembly defects in mad3-C9A and mad3-C9A mad2-S92A , we wanted to test the ability of the mutant MCC produced to bind to APC/C . These C-terminal phosphorylation sites lie close to the second KEN box in Mad3p ( KEN2 ) , which has been argued to be important for APC/C interactions in vertebrate cells [57] . Our previous work has shown that the first Mad3p KEN box ( KEN1 ) is critical for Cdc20 Slp1 binding and MCC assembly , and that whilst KEN2 is not required for MCC assembly it is needed for fission yeast checkpoint arrest [20] . To analyse this further , we carried out cdc25 block and release time courses and monitored APC/C binding with the mad3-KEN mutants . The anti-microtubule drug carbendazim ( CBZ ) was added 20 minutes after cdc25 release to test whether these mad3 alleles could maintain a spindle checkpoint arrest . As expected , the mad3-KEN1 allele displayed no APC/C binding , for either Mad3p or Mad2p ( Fig 4 ) . The mad3-KEN2 allele displays comparable MCC-APC/C binding to wild-type Mad3p at early time points ( 45 minutes ) , but was unable to maintain MCC-APC/C levels or the checkpoint arrest ( MCC-APC/C levels had already fallen to ~65% of wild-type levels at 60 minutes ) . We scored maintenance of checkpoint arrest by analysing when cells exit mitosis and septated during these time courses ( Fig 4C ) . 50–60% of cells had septated by 2 hours in mad3∆ , mad3-KEN1 and mad3-KEN2 . These findings are consistent with KEN2 not being required for MCC assembly or initial APC/C binding ( at 45 minutes ) , but instead being needed to maintain APC/C binding . A vertebrate study has argued that the BubR1Mad3-KEN2 box can compete with securin/cyclin substrates and thereby prolong spindle checkpoint delays [57] . Another , more recent study proposed the involvement of the BubR1-KEN2 box in mediating interaction of a second molecule of Cdc20Slp1 , bound to APC/C [58] . This latter model is currently being analysed in S . pombe ( see Discussion ) . To test whether mutation of the C-terminal Mad3p phospho-sites flanking KEN2 perturbed MCC-APC/C binding , we carried out cdc25 ( G2 ) block and release time courses and immunoprecipitated the APC/C from mad3-C9A mutants . This experiment demonstrates that the mad3-C9A and the mad2-S92A alleles displayed significantly reduced APC/C binding to Mad3p and Mad2p at 45 and 60 minutes ( Fig 5A and 5B ) , ie . at times when rather little effect on MCC assembly was observed ( see Fig 3B ) . The levels of Mad2p and Mad3p bound to the APC/C in mad3-C9A mad2-S92A were only 20% of those in wild-type at 45 and 60 minutes ( Fig 5B ) . Importantly , at equivalent times in mitosis their MCC levels were 70–100% of those in wild-type cells ( Fig 3B ) . We scored maintenance of checkpoint arrest by analysing when cells exit mitosis and septated during such time courses ( Fig 5C ) . The mad2-S92A and mad3-C9A strains both septate ahead of wild-type , and the double mutant is even more advanced although not quite as fast as the mps1-kd strain ( see S5 Fig for representative images and a direct comparison with the mad3-KEN mutants ) . These data strongly support a model in which Mps1Mph1-dependent phosphorylation of both Mad2p and Mad3p are required to stabilise their APC/C binding and thus to maintain the MCC-APC/C complex and spindle checkpoint arrest . Phosphorylation of Mad3p does not appear to regulate its kinetochore targeting ( Fig 2A ) or assembly into MCC ( Fig 3 ) . Even so , the effects we have observed on MCC-APC/C interactions ( Fig 5 ) and checkpoint arrest ( Fig 2B–2D ) could be indirect consequences of a defective upstream signalling event . To confirm that Mad3p modification has a direct role in APC/C inhibition we developed an in vitro APC/C assay , based on those previously described for both budding and fission yeasts ( see Materials and Methods , [59 , 60 , 61] ) . Fig 6 demonstrates that recombinant fission yeast Mad3p can directly inhibit in vitro Cdc20Slp1-APC/C activity: as the concentration of recombinant Mad3p was increased , a corresponding decrease in Cdc20 Slp1-APC/C dependent ubiquitination of the radio-labelled securinCut2 substrate was observed . Note this experiment was performed in the presence of Mad2p . Recombinant Mad3p inhibited APC/C activity on its own , but was approximately 30% less potent than the Mad3p-Mad2p combination . To test the effects of Mad3p phosphorylation on APC/C activity , we made a series of mutants containing phospho-mimics ( S/D and/or T/E substitutions ) . These phosphorylation sites are in close proximity to the KEN2 box , suggested to be important for Mad3p-APC/C interaction and/or competing with substrates for APC/C binding ( Fig 6A ) . We analysed their ability to directly inhibit Cdc20Slp1-APC/C activity in vitro ( Fig 6B and 6C ) . The mad3-double KEN mutant protein ( KEN1 , 2-AAA ) was used here as a negative control . This experiment was repeated three times and Fig 6C shows quantitation of the combined data . These experiments demonstrate that the Mad3 phosphomimics are better in vitro APC/C inhibitors than the recombinant wild-type Mad3 protein and that they display a graded increase in potency ( c . f . 0 , 3 , 4 and 7 phospho-mimicking D/E residues ) . We conclude that mimicking phosphorylation of Mad3p near its C-terminal KEN2 box can directly improve its ability to inhibit Cdc20Slp1-APC/C activity . To test whether Mad3p modification is sufficient to induce a mitotic delay in vivo , we replaced wild-type mad3 with alleles expressing 3 , 4 , 6 or 7D/E residues . These alleles produce stable proteins ( see S7A Fig ) that can be targeted to kinetochores in an apparently normal manner ( S7B Fig ) . We released these strains from a cdc25-ts ( G2 ) block into a synchronous mitosis , but no significant metaphase delay was observed . Further studies demonstrate that the mad3-3D/E and -4D/E alleles perform as well as wild-type in other checkpoint assays , but that they do not act as gain-of-function alleles ( see S7C and S7D Fig for further details ) . Thus we conclude that such Mad3p modifications are not sufficient to induce and maintain a spindle checkpoint delay in cells .
The Mad3/BubR1 protein is a target of many mitotic kinases . Budding yeast Mad3p is a target of both PoloCdc5 [64] and Aurora BIpl1 kinases [65] , the latter being required for cells to respond to lack of tension at kinetochores . In Drosophila it was reported that Polo promotes Mps1Mph1 kinetochore localisation and that this is required for BubR1 phosphorylation and stable MCC production [66] . In Xenopus egg extracts BubR1 is phosphorylated by Plx1 , generating the 3F3/2 epitope , and this is required for checkpoint arrest [67] . However , in human cells BubR1 phosphorylation by Plk1 was shown to be important for regulating the stability of kinetochore-microtubule attachments [68] . The C-terminal KARD domain in BubR1 , not present in yeast Mad3 , is modified by both Polo and CDK kinases and this modification regulates recruitment of PP2A regulatory sub-units to kinetochores [69] . Once there , PP2A can oppose the action ( s ) of Aurora B and play a part in the onset of mitotic exit . Thus Mad3/BubR1 is a highly regulated phospho-protein , consistent with it being a key regulator of mitotic progression . However , the specific kinases involved and the mechanistic roles of Mad3/BubR1 phosphorylation vary between model systems . Here we have demonstrated that fission yeast Mad3p is modified by several mitotic kinases: Mps1Mph1 and most likely CDK and AuroraArk1 . Our studies indicate that the C-terminal Mps1Mph1 sites flanking the Mad3p KEN2 box are particularly important , and that their modification can enhance the ability of this checkpoint protein to bind to and inhibit Cdc20Slp1-APC/C . Our in vivo studies of the phospho-mimic mutants ( see S7 Fig ) argue that these C-terminal Mad3p modifications are not sufficient to stabilise MCC-APC/C binding enough to induce a dominant mitotic delay . We propose that additional modifications , perhaps on Mad2p , Cdc20Slp1 or APC/C subunits would be needed to generate such a gain-of-function phenotype in vivo . In addition , cells probably have multiple checkpoint silencing pathways , not all of which would necessarily involve de-phosphorylation . In addition to the C-terminus of Mad3p ( this study ) , Mad2p ( here and [39 , 70] ) and Cdc20Slp1 [13 , 71 , 72] are phosphorylated and their modification is also thought to ensure efficient APC/C inhibition . Figs 2 and 5 demonstrate the synthetic defect of mutating Mad3p and Mad2p phosphorylation sites . Whilst the crystal structure of fission yeast MCC beautifully demonstrated the importance of the N-terminal KEN box and conserved TPR domain in MCC formation [18] , this structure lacked the N-terminus of Cdc20Slp1 and the C-terminus of Mad3p . Both of these apparently unstructured regions are post-translationally modified and both are critical for in vivo regulation of Cdc20Slp1-APC/C activity ( our study and [72] ) . It has recently been suggested that a second molecule of vertebrate Cdc20Slp1 might be involved in MCC-Cdc20Slp1-APC/C complexes [58] . We are currently assessing this model in fission yeast cells , but it is clear that further structural analyses employing recombinant , full-length Cdc20Slp1 ( s ) and Mad3p will be needed before MCC interactions with Cdc20Slp1-APC/C can be fully understood .
Phosphorylation mutants were created from pJK-Mad3 , which is based on the vector pJK148 [73] . It contains 500 bp of 5’UTR , followed by the mad3 ORF and 500 bp of 3’UTR . All mad3 strains were generated by integration of pJK-Mad3 vectors into a mad3Δ strain at the endogenous mad3 locus . Mad3 gene synthesis ( GeneArt ) was used to generate the 18A allele ( see Fig 1 ) . The C9A and N9A alleles were created from the 18A vector by sub-cloning , using an Xho1 site present in the Mad3 gene . All other point mutations were introduced using the Quikchange Kit for Site Directed Mutagenesis ( Stratagene ) . For the APC/C binding assays C-terminal GFP tags were introduced using the Bahler cassette system ( Bahler et al . 1998 ) Recombinant wild-type ( wt ) and phospho-mimic Mad3 mutants as well as the closed Mad2 mutant ( cMad2 [39] ) used for the APC/C activity assays were constructed via Gateway cloning using the donor vector pDONR201 ( Life technologies ) and the destination vector pHMGWA described previously [74] containing 6xHis and Maltose Binding Protein ( MBP ) tags . Proteins were expressed in BL21 RIL cells with 0 . 25 mM IPTG at 18°C for 16hrs . Cells were harvested by centrifugation and pellets were frozen at -20°C until further use . Cells were lysed by sonication in lysis buffer A containing 50 mM potassium phosphate pH 7 . 0 , 300 mM NaCl , 5% glycerol , 1mM DTT and 1% glucose supplemented with 1 mM Pefabloc ( SIGMA Aldrich ) and a cocktail protease inhibitor tablet ( Roche ) . cMad2 and Mad3 proteins were affinity purified using amylose beads ( NEB ) and eluted with buffer A containing 15 mM maltose . Eluted fractions were pooled together and further purified by size exclusion chromatography using a Superdex S200 column ( GE Healthcare ) either in buffer B ( for cMad2 ) containing 25 mM HEPES pH 7 . 5 , 150 mM NaCl , or in buffer C ( for Mad3 proteins ) containing 25 mM potassium phosphate pH 7 . 0 , 200 mM NaCl , 5% glycerol , 1mM DTT , 1% glucose and 1 mg/ml NVOY polymer ( Expedeon ) . Protein purity was visualised by SDS-PAGE . First , the 3’ UTR of the Slp1Cdc20 gene ( 460 base pairs downstream of the stop codon ) was marked with the Hygromycin B resistance gene through PCR based gene modification in yeast . Then the genomic DNA of the Slp1Cdc20 gene with this inserted Hyg B resistance marker was amplified by PCR and cloned into the Gateway® pDONR 201 vector ( Life Technologies ) . A 5’ fragment of the Slp1Cdc20 gene ( the first 450 base pairs ) , with an insertion of three tandem copies of the FLAG-tag between nucleotides 191 and 192 , was commercially synthesised ( Geneart® Life Technologies ) and then cloned into the Slp1Cdc20 gene in the vector . The final construct was then linearised and used to transform haploid wild type yeast cells . Transformants were selected through their Hygromycin B resistance , and correct integration was confirmed by PCR and DNA sequencing . FLAG-Slp1Cdc20 expression was confirmed by immunoblotting . Yeasts strains are listed in S1 Table . For nuf2-3 arrests , cells were grown overnight in YES medium at 25°C to mid-log phase and then shifted to 32°C for 4 hrs followed by fixation at -20°C in 100% methanol . For microscopy , cells were mounted with 20 μg/ml DAPI ( Sigma ) . nda3-KM311 ( cs ) cells were grown overnight in yeast extract plus supplements ( YES ) medium at 30°C to mid-log phase and then shifted to 18°C for 6 hrs . 10-fold serial dilutions were plated on YES plates containing 0 , 7 , 8 . 5 μg/ml of the microtubule depolymerising drug benomyl . Plates were incubated at 30°C for 3 days before images were taken . 10–50 ml of overnight culture were harvested and then fixed with -80°C cold methanol and washed twice with PEM ( 100 mM PIPES , pH 7 . 6 , 1 mM MgSO4 , 1 mM EGTA ) . Cell walls were then digested in PEMS ( PEM , 1 M sorbitol ) with 0 . 4 mg/ml Zymolyase ( MP Bio-medicals ) for 30–45 min . Cells were then sequentially washed once with PEMS , PEMS-TritonX-100 ( 1% ) and PEM . Cells were blocked with PEMBAL ( 1% BSA , 0 . 1% L-Lysine in PEM ) for 1 h and then incubated overnight with TAT1 ( mouse anti-tubulin ) antibody ( 1:50 ) ( kindly provided by Keith Gull , Oxford , UK ) . Cells were washed once with PEM and then incubated with anti- mouse secondary antibody ( Alexa Fluor–Molecular Probes ) at 1:1000 for 1 h . Mitotic spindles were visualized using an Intelligent Imaging Innovations Marianas microscope ( Zeiss Axiovert 200M , using a x100 1 . 3NA objective lens ) , CoolSnap CCD , and Slidebook software ( Intelligent Imaging Innovations , Inc . , Boulder , CO ) . Purified Mps1Mph1 kinase coupled to S-protein agarose beads was washed twice with 1 x kinase buffer ( 50 mM Hepes pH 7 . 5 , 10 mM MgCl2 , 0 . 5 mM DTT ) . 25 μl of kinase reaction buffer ( 12 . 5 μl 2x kinase buffer ( 100 mM Hepes , pH7 . 5 , 20 mM MgCl2 , 1 mM DTT ) , 0 . 5 μl P32 gamma-ATP , 0 . 5 μl 1 mM ATP , made up with substrate in a final volume of 25 μl was then added to the beads . Reactions were typically carried out with 1 . 5 μg of substrate/recombinant protein . The reaction was incubated at 30°C for 30 minutes . Cold kinase assays were carried out with 100 mM ATP and further analysed by mass spectrometry . Peptides were loaded onto a column needle self-packed [78] with ReproSil-Pur C18-AQ material ( 3 μm , Dr . Maisch , Germany ) at a flow rate of 0 . 7 μl/min . Peptides were separated using an Aligent 1100 binary nanopump LC , with HTC Pal Auto sampler ( CTC ) , using either a two-step linear gradient of 0%-20% B in 35 min , 20%-80% B in 4 min and 80% B for 2 min or a two-step linear gradient of 0%-20% B in 75 min , 20%-80% B in 13 min and 80% for 10 min ( Mobile phases were ( A ) 5% acetonitrile , 0 . 5% acetic acid and ( B ) 99 . 5% acetonitrile , 0 . 5% acetic acid ) . Peptides were eluted into an LTQ-Orbitrap mass spectrometer ( Thermo Fisher Scientific ) using a flow rate of 300 nl/min and a spray voltage of 1 . 8kV . DTAsupercharge ( V1 . 18 ) was used to create peak lists from raw data . Peak lists were then used within Mascot daemon ( V2 . 2 . 0 ) to search against the UniProt/SwissProt Schizosaccharomyces pombe database . Search parameters were set to: precursor mass tolerance of 10 ppm , fragment ion mass tolerance to 0 . 8 Da , enzyme as trypsin , allowing 3 missed cleavages . Carboamidomethylation of cysteine was set as a fixed modification , with oxidation of methionines , phosphorylation of serine , threonine , and tyrosine as variable modifications . Six litres of yeast cells were grown at 30°C in concentrated rich medium to high densities that could still support active proliferation and mitotic arrests . Mitotically arrested cells ( harbouring cold-sensitive β-tubulin alleles ) were obtained by rapid cooling on iced-water and shifting cultures to 18°C for 7 hours . Cells were harvested by centrifugation at 3 , 500g for 8 minutes at 4°C . Pelleted cells were frozen into pea-sized drops using liquid nitrogen and stored at -80°C until further processing . Approximately 25 g of cell mass was disrupted using a mixing mill ( MM 400; Retsch , Germany ) with grinding balls under cryogenic conditions ( 5 cycles of 3 minutes at 30 Hz ) . Yeast lysates were reconstituted in lysis buffer A containing 50mM Bis-Tris Propane-HCl pH 7 . 6 , 10% ( v/v ) glycerol , 100 mM KCl , 5 mM EGTA and 1% Triton X100 supplemented with a ‘complete EDTA-free protease inhibitor’ tablet ( per 50 ml ) , 1mM Pefabloc SC , 10 μg/mL leupeptin/pepstatin/chymostatin ( all from Roche ) , 20 mM β-glycerophosphate , 5mM NaN3 , 0 . 4 mM Na3VO4 and 2 μM microcystin-LR ( Axxora Life Sciences , CA , USA ) . Following further lysis , by sonication , cell debris was pelleted at 4 , 000g for 5 min at 4°C and the supernatant was filtered through a 1 . 6 μm syringe filter . Proteins were bound to IgG-Dynabeads by incubating the cleared lysates for 20 min at 4°C ( 1 mg IgG-Dynabeads per 1 g of cell input ) whilst mixing . Dynabeads with bound proteins were then washed four times with buffer A and twice with buffer B [50 mM HEPES-KOH pH 7 . 0 , 50 mM KCl] . Proteins were eluted from Dynabeads by two x 5 min incubations with 150 μl of 100mM glycine-HCl ( pH 2 . 5 ) at room temperature and precipitated with 100 μl of cold 100% ( w/v ) trichloroacetic acid . Proteins were pelleted at 4°C by centrifugation for 30 min at 22 , 000g . Supernatant was removed and pellets were washed twice with 500 μl of ice-cold acetone . and air-dried . Proteins were reduced , alkylated and digested with trypsin . Peptides were pressure vessel loaded onto a biphasic ( C18-SCX ) column . Peptides were separated by MuDPIT ( Washburn et al . , 2001 ) using an Aligent 1100 quaternery LC with a 1:1000 split flow system . Peptides were eluted into an LTQ mass spectrometer ( Thermo Fisher Scientific ) at spray voltage of 2 . 6 kV . Eight data-dependant ms/ms were collected per primary scan . MS3 scans were triggered with neutral loss values of 32 . 50 , 49 . 00 and 98 . 00 . Fission yeast genes E1 ( Uba1 ) and E2s ( Ubc1 , 4 and 11 ) inserted in pMAL and pET16b plasmids respectively were kindly provided by Hiro Yamano ( Ors et al . , 2009 ) . These were used to recombinantly express proteins in BL21 RIL cells as described above for the Mad3 constructs . MBP-Uba1 and His-tagged E2s were then affinity purified using either amylose ( NEB ) or talon resin ( Clonetech ) . MBP-Uba1 was subjected to further purification by size exclusion chromatography using a Sephadex S200 column . Full-length APC/C activator Cdc20 Slp1 and radiolabelled [Met S35] APC/C substrate , Securincut2 were generated by in vitro translation using the TNT Quick Coupled Transcription/Translation kit ( Promega ) according to manufacturer’s instructions using 1μg of pHY22-Cdc20Slp1 and pHY22-Securincut2 plasmids also provided by Hiro Yamano . Lid1-TAP APC/C was affinity purified using IgG agarose beads ( GE Healthcare ) as previously described [59 , 79] from S . pombe cells carrying the ts slp1-362 mutation [80] to allow the isolation of the APC/C free from endogenous Cdc20slp1 . In vitro APC/C ubiquitination assays were performed following a method based on assays previously described for budding , fission yeast and human proteins [59 , 61 , 81] . In brief , 0 . 05 mg/ml Uba1 , 0 . 5mg/ml E2s ( ubc1 , ubc4 and ubc11 ) and 0 . 3 mM ATP were mixed with 1 . 5 mg/ml wild-type mono-ubiquitin ( Sigma Aldrich ) , 2μM ubiquitin aldehyde ( Boston Biochem ) in a ubiquitination buffer containing 25 mM HEPES pH 7 . 5 , 100 mM KCl , 3mM ATP , 2 . 5 mM MgCl2 , and 0 . 2 mM DTT . The ubiquitination mix was incubated at 23°C for 20 min . 0 . 5 μM APC/C , 4 ul and 2 ul of Cdc20Slp1 and SecurinCut2 respectively were then added to the mix in a total reaction volume of 20 μl . Reactions were carried out at 23°C for 45 min and stopped by adding 4xSDS gel buffer . Samples were subjected to SDS-PAGE electrophoresis and visualised by radiography using the Typhoon phosphoimager . The ubiquitination of SecurinCut2 by APC/C was analysed using the ImageQuant software ( GE Healthcare ) by quantifying the decrease in intensity of the unmodified Securin band ( labelled “*Securin” in Fig 6B ) . The ability of Mad3 and phospho-mimic mutants to inhibit the activity of APC/C was assessed by pre-incubating APC/C , Cdc20Slp1 and cMad2 with the corresponding Mad3 protein at 4°C for 30 min prior to adding them to the ubiquitination mix .
|
When cells divide they need to ensure that a complete copy of their genetic material is transmitted to both daughter cells . Cells have evolved many controls to ensure that every division is carried out with very high fidelity . The spindle checkpoint is one such control , which acts as a surveillance system during mitosis . Defects in this checkpoint control lead to unequal segregation of DNA/chromosomes , termed aneuploidy , which is responsible for human birth defects and is very common in tumour cells . The molecular components of the spindle checkpoint , identified initially through yeast genetics , include several protein kinases . Surprisingly few of their substrates have been identified . Here we identify the checkpoint protein Mad3 as an important substrate of the Mps1Mph1 kinase . We show that Mps1Mph1-dependent modification of Mad3 and Mad2 acts to delay cell division in situations where the genetic material would not be equally inherited by daughter cells . This delay enables the cell to correct any problems within the division machinery and thus avoid aneuploidy .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
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"phosphorylation",
"anaphase",
"cell",
"cycle",
"and",
"cell",
"division",
"cell",
"processes",
"biochemical",
"analysis",
"mitosis",
"fungi",
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"kinase",
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"schizosaccharomyces",
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"methods",
"chromosome",
"biology",
"proteins",
"schizosaccharomyces",
"pombe",
"ubiquitination",
"precipitation",
"techniques",
"yeast",
"biochemistry",
"cell",
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"post-translational",
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] |
2016
|
Mps1Mph1 Kinase Phosphorylates Mad3 to Inhibit Cdc20Slp1-APC/C and Maintain Spindle Checkpoint Arrests
|
Three prime repair exonuclease 1 ( TREX1 ) is an essential exonuclease in mammalian cells , and numerous in vivo and in vitro data evidenced its participation in immunity regulation and in genotoxicity remediation . In these very complicated cellular functions , the molecular mechanisms by which duplex DNA substrates are processed are mostly elusive because of the lack of structure information . Here , we report multiple crystal structures of TREX1 complexed with various substrates to provide the structure basis for overhang excision and terminal unwinding of DNA duplexes . The substrates were designed to mimic the intermediate structural DNAs involved in various repair pathways . The results showed that the Leu24-Pro25-Ser26 cluster of TREX1 served to cap the nonscissile 5′-end of the DNA for precise removal of the short 3′-overhang in L- and Y-structural DNA or to wedge into the double-stranded region for further digestion along the duplex . Biochemical assays were also conducted to demonstrate that TREX1 can indeed degrade double-stranded DNA ( dsDNA ) to a full extent . Overall , this study provided unprecedented knowledge at the molecular level on the enzymatic substrate processing involved in prevention of immune activation and in responses to genotoxic stresses . For example , Arg128 , whose mutation in TREX1 was linked to a disease state , were shown to exhibit consistent interaction patterns with the nonscissile strand in all of the structures we solved . Such structure basis is expected to play an indispensable role in elucidating the functional activities of TREX1 at the cellular level and in vivo .
Three prime repair exonuclease 1 ( TREX1 ) is a member of the DEDDh family of exonucleases and accounts for most of the 3′–5′ exonuclease activity in mammalian cells [1 , 2] . Anchored in the plasma membrane of the endoplasmic reticulum ( ER ) through the C-terminal domain , TREX1 degrades a variety of substrates to prevent initiation of autoimmunity [3–8] . The targeted nucleic acids in this activity include single-stranded DNA ( ssDNA ) [3 , 5] and double-stranded DNA ( dsDNA ) [9–11] . It was also suggested that DNA/RNA hybrids are potential targets of TREX1 , since the deficiencies of TREX1 demonstrate similar features of autoimmune diseases as those of RNase H2 that was known for processing the hybrid substrates [12–15] . Such genetic materials in the cytoplasm are mostly originated from replication of aberrant DNA intermediates and possibly also due to unrestrained endogenous retroelements [8 , 13–17] . Malfunctioning of TREX1 has thus been shown to lead to inflammation and autoimmune diseases such as inflammatory myocarditis in Trex1-/- mice [18] and systemic lupus erythematosus ( SLE ) , Aicardi-Goutières syndrome ( AGS ) , retinal vasculopathy , cerebral leukodystrophy , and familial chilblain lupus ( FCL ) in TREX1-deficient humans [14 , 19 , 20] . The ability of TREX1 in modulating immune responses is also exploited by type 1 human immunodeficiency retrovirus ( HIV-1 ) that enslaves cytosolic TREX1 to degrade its cDNA , thereby escaping detection by the nucleic acid sensors of the infected host and hence the concomitant antiviral responses [21] . Recent studies indeed showed that TREX1 knockdown in human tissues and humanized mice delayed HIV infection and suppressed local viral replication with increased production of type 1 interferons [22] . Moreover , TREX1 was shown to respond to the events of DNA damage or Granzyme A ( GzmA ) -mediated apoptosis with concomitant translocation to the nucleus [3 , 23 , 24] . TREX1 was indeed characterized as an exonuclease that involves in DNA repair and in DNA proofreading via working with other nuclear enzymes such as Poly [ADP-ribose] polymerase 1 ( PARP-1 ) and DNA polymerase β [1 , 24 , 25] . Additionally , TREX1 was established to play a role in GzmA-mediated cytotoxicity [23] . Cytotoxic T lymphocytes and natural killer cells secrete GzmA proteases to induce cell death of the targeted cancer cells or virus-infected cells by releasing TREX1 and nonmetastatic protein 23 homolog 1 ( NM23-H1 ) from ER-bound patient SE translocation protein ( SET ) complex , and their translocation to the nucleus promoted chromosomal DNA fragmentation [23] . With such diverse activities toward a variety of nucleic acid substrates—including ssDNA , dsDNA , DNA/RNA duplexes , structural DNAs , and DNA hybrids with an interject nick—the linkage of TREX1 to apoptotic DNA degradation in dying cells [26] and in chromosomal fragmentation during telomere crisis [27] was hence not unexpected . Regulation of the exonuclease activity of TREX1 was indeed recognized as an influential factor in cancer therapy [28–30] . The broad attendance of TREX1 in the activities of immune silencing and responding to genotoxic stresses highlights the elementary role of properly processing the nucleic acids that are involved in these vital yet very complicated cellular functions . Mechanistic understanding of substrate handling is hence key to comprehending the connections between different enzymes in the pathways . However , such knowledge is mostly elusive as informative molecular details are lacking . For example , precise excision of short 3′-overhangs in generation of blunt-end dsDNAs and the terminal unwinding of these duplexes for further degradation are two events in urgent need of structure basis . Although X-ray structures of TREX1 with ssDNA [7 , 31] and Y-structural DNA are available [10] , the 3′- and 5′-overhang of the substrates therein were rather long ( >4 nt ) . Therefore , the structure information is currently insufficient to deduce the mechanism by which double-stranded substrates are processed ( see Discussion ) . TREX1 is , in fact , unique in the DEDDh family for the activity of dsDNA degradation , which enables its participation in preventing autoimmune responses and in restricting retrotransposons [9–11] . The DEDDh family , also named DnaQ-like exonuclease family , or RNase T superfamily in the protein families ( Pfam ) database ( https://pfam . xfam . org/ ) , contains over 17 , 000 members across more than 3 , 000 species [32 , 33] . Toward ssDNA substrates , the catalytic properties of TREX1 are similar to those of the Escherichia coli homolog , RNase T . When first reported , both enzymes were shown to exhibit activities involved in DNA repair , namely trimming the single-stranded segments of the mispaired ends in a DNA duplex , such as the single-stranded 3′-overhangs in duplex , Y- , or flap structural DNAs [1 , 34 , 35] . The analogy in this activity is in line with the in vivo and in vitro experiments that concluded that the two nucleases likely play similar roles in various pathways of DNA repair [24 , 33] . Furthermore , TREX1 can digest single-stranded RNA ( ssRNA ) as RNase T does , and this RNase activity of TREX1 is potentially responsible for degrading DNA/RNA hybrids in the cytosol [13 , 14] and/or during tRNA maturation [36] . The main difference between TREX1 and RNase T , though , is the catalytic ability of TREX1 in degrading dsDNA , for which RNase T lacks [35 , 37] . In this work , we solved 4 X-ray structures of TREX1 with representative DNA substrates to delineate the molecular details of the multifaceted catalytic properties of TREX1 . On one hand , TREX1 allows precise trimming of structural DNAs to generate blunt-end products in preparation for specific pathways of DNA repair . On the other hand , the enzyme enables digestion of dsDNA for immunity regulation . The 4 new structures we presented here reveal how TREX1 removes the single-stranded 3′-overhang in producing DNA duplexes with blunt ends and , for the first time , illustrate how the enzyme overcomes the resistance of the double-strand structure for degradation of dsDNA . The structural DNA substrates in our analysis were also specifically designed to mimic the DNA intermediates in various DNA repair pathways . Therefore , the new structures presented in this work provide unprecedented insights into the functional roles of TREX1 at the molecular level . Together with measurements of nuclease activities , the structure-based mechanism was also employed to discuss the cellular functions of TREX1 in DNA repair and in immune silencing .
Two members of DEDDh exonucleases , Thermus thermophiles TTHB178 and E . coli RNase T , were identified as DNA repair–related exonucleases [33 , 38] . Both enzymes can remove deaminated bases like dI ( also named hypoxanthine ) and uracil in ssDNA with similar efficiencies as in digesting regular nitrogenous bases in vitro [33 , 38] . In addition , in vivo studies showed that TTHB178 and RNase T exhibited similar responses to the genotoxic stresses of H2O2 and UV irradiation [33 , 38] . Since TREX1 was shown to respond to such genotoxic stress by translocating to the nucleus [24] , it would be of interest to characterize whether TREX1 can digest DNA substrates damaged by H2O2 and UV irradiation as TTHB178 and RNase T do . Therefore , we incubated TREX1 with ssDNA substrates that each contain a methylated base , a deaminated base , an oxidized base , or an abasic site at the 3′-terminal end ( 5′-GAGTCCTATAX-3′ ) and measured the activities of TREX1 in ssDNA degradation . The results presented in S2A Fig clearly showed that TREX1 exhibited similar activities in digesting ssDNAs containing a methylated base ( O4-methylthymine [O4-mT] and O6-methylguanine [O6-mG] ) or a deaminated base ( uracil and hypoxanthine ) as in digesting ssDNAs with regular bases ( adenine ) . The ssDNA with an abasic site or an oxidized base ( 8-oxoguanine [8-oxoG] ) , though , was more resistant to TREX1 . Therefore , the base preference of TREX1 to ssDNA substrates is similar to that of TTHB178 and RNase T in the DEDDh family . RNase T showed in in vitro experiments that it can serve as a downstream exonuclease of Endonuclease V ( Endo V ) –mediated alternative base excision repair ( AER ) [33] . Endo V–mediated AER repairs DNA lesions originated from deamination of the adenine base ( hypoxanthine ) , frame shift mutations , or replication errors [39–41] . The initiation step is making a nick at the 3′ side 1 base away from the damaged site . Expression of eukaryotic Endo V in DNA repair–deficient E . coli cells reduced the mutation frequency in the host , suggesting that the DNA repair function of Endo V may commonly display in E . coli and mammalian cells [40 , 41] . Therefore , TREX1 may also serve as a downstream exonuclease of Endo V , as RNase T does . In addition to DNA substrates , recent studies showed that both Endo V and TREX1 are also ribonucleases , as they exhibited considerable activities in digesting RNA substrates [28 , 32] . Despite the common ground at the level of enzyme activity , the involvement of TREX1 in this DNA repair pathway and its specific roles would require further investigation to establish . A prominent question , therefore , is whether TREX1 can process the structural DNAs generated by Endo V . In this regard , we designed and synthesized a bubbled dsDNA containing a dI with or without the 5′-overhang to mimic the end product of the enzyme ( Fig 2A and 2B ) . This double-stranded substrate is referred to as dI-dsDNA . The Tris-borate-EDTA ( TBE ) gel electrophoresis was used to check the structure property of dI-dsDNA . With identical numbers of bases , the moving speed of dI-dsDNA in the gel was in between that of a Y-structural dsDNA and that of a regular dsDNA , indicating an intermediate , bubbled structure ( S2B Fig ) . The results of our nuclease activity assay showed that TREX1 indeed broke the terminal base pairing and removed the last base pair near the penultimate hypoxanthine base at the 3′-end of dI-dsDNA ( the 2 site labeled in Fig 2B ) . In addition , TREX1 also removed the penultimate hypoxanthine base and antepenultimate adenine base ( the 1 and 0 sites labeled in Fig 2B ) . For the dI-dsDNA substrate with 5′-overhang , similar results were observed , indicating that the dangling 5′-ends did not affect TREX1 in processing the dsDNA . In summary , our activity measurements established that TREX1 not only digested the dI in ssDNA; the enzyme can also extend into the duplex region and removed the last 3 bases at the 3′-end of a bubbled dI-dsDNA that mimics the product of Endo V . These results also highlighted that TREX1 is able to unwind the terminal base pairs in a DNA duplex to conduct digestion . To provide the structural basis for TREX1 in complexing an ssDNA substrate containing dI , we determined the TREX1-dI-ssDNA structure . Fig 2C showed that the 3′-end of dI-ssDNA is inserted into the active site of TREX1 in each of the dimer in the asymmetric unit . The last nucleotide at the 3′-end is stacked by Leu24 and Ile84 ( Fig 2C ) . Each active site contained 2 Mg2+ , MgA and MgB . MgA coordinates with Asp18 , Glu20 , and Asp200 of TREX1 and was in contact with the phosphate oxygens of the scissile DNA strand . The His195 general base in the active site lacked the nucleophilic water that would bind MgA , a commonly observed configuration among the structures of DEDDh members [10 , 33 , 37] . MgB in the structure coordinated with 6 partners in the octahedral geometry , including Asp18 , 2 phosphate oxygens in the scissile DNA stand , and 3 water molecules ( Fig 2C ) . Both active sites of TREX1 in the asymmetric unit showed an active conformation as in the structures of other classical DEDDh exonucleases ( S3A Fig ) . In the TREX1-dI-ssDNA structure , the hypoxanthine base was designed to locate in the penultimate position at the 3′-end of dI-ssDNA as the products generated by Endo V ( Fig 2A and 2C ) . The omitted electron density map of the hypoxanthine base in ssDNA fits very well to the three-dimensional structure ( Fig 2C ) . Superposition of the structure of the TREX1-dI-ssDNA structure with that of TREX1 bound with a regular ssDNA showed that TREX1 bound both substrates with high structure similarity ( S3B Fig ) . Therefore , the chemical modification into a hypoxanthine base at the penultimate position of the 3′-end did not affect the binding mode of TREX1 with ssDNA and its active site structure . In the TREX1-dI-T-dsDNA structure we solved , both protomers bound with a dI-dsDNA , as shown in Fig 3A . Both active sites of the enzyme dimer displayed the same active conformation as in the TREX1-dI-ssDNA structure . The omitted electron density maps in the double-strand region of both dI-dsDNA strands , though , were well defined for structure determination . In contrast , the electron densities of the 2 short 5′-overhang were not as continuous and weak , suggesting that the 3-nt-long 5′-overhangs were disordered ( S4A Fig ) . The structure of the TREX1-dI-T-dsDNA complex vividly illustrated the mode by which TREX1 broke the last base pairing in the duplex region . In particular , the Leu24-Pro25-Ser26 cluster acted as a wedge to chisel the duplex end formed by the last G-C pair and the dI-T wobble pair , and the DNA adopted a Y-like structure ( Fig 3A and 3B ) . The complex of TREX1-dI-T-dsDNA hence provided a first structural basis for the ability of TREX1 in unwinding the duplex region of dsDNA . In addition to the Leu24-Pro25-Ser26 cluster , the structure indicated that the narrow pocket of the TREX1 active site was also involved in breaking the double-stranded structure as Leu24 and Ile84 stacked with the last nucleotide at the 3′-end ( Fig 3A ) . Furthermore , the last nucleotide at the 3′-end of the substrate formed several hydrogen bonds with Glu20 , Ala21 , and Tyr129 in the narrow pocket ( S4B Fig ) . These couplings to the 3′-end would thus facilitate unwinding of the terminal base pair . In summary , TREX1 exhibited the delicate machinery that the Leu24-Pro25-Ser26 cluster partnering with the narrow active site pocket to unwind the duplex end for digestion of dsDNA . The mechanistic insights provided by the TREX1-dI-T-dsDNA complex structure were in line with the biochemical assay measurements presented earlier that TREX1 removed the 2 to −1 bases at the 3′-end of the bubbled dI-dsDNA ( Fig 2B ) . Our results thus illustrated that the unique catalytic properties of TREX1 in digesting dsDNA and in processing the hypoxanthine base can serve to digest the product generated by Endo V . This finding represented an evidence that a DEDDh member like TREX1 and RNase T may act as a downstream exonuclease for Endo V–mediated AER in DNA repair . Our activity measurements showed that TREX1 can remove the single-stranded regions in structural DNAs , and blunt-end duplexes are a main form of product of TREX1 ( Figs 4A and 5A ) . To uncover the molecular origin of such precise removal of the 3′-overhang , we determined the structures of TREX1 complexed with the substrates that we devised to mimic the intermediates in UV-induced DNA repair . The structures of TREX1-L-structural dsDNA and TREX1-Y-structural dsDNA were solved at 1 . 7 Å and 2 . 0 Å resolution , respectively . The protein residues interacting with the DNA substrates in these two structures are shown in S5 Fig . The active sites in both structures also adopted the active form of conformation . Both structures contain regions of short 3′-overhang ( 1-nt- or 2-nt-long ) to illustrate how the 3′-overhang was removed . In the TREX1-L-structural dsDNA structure , 1 asymmetric unit contained 2 TREX1 monomers and 2 ssDNAs of 6 and 9 nt in length ( Fig 4B ) . The 2 strands paired to their symmetric ssDNA in the crystal via GC-rich regions . The annealed DNA strands formed 2 duplexes of 1-nt- and 4-nt-long 3′-overhang , respectively . Each 3′-terminus of the DNAs displayed an L-like conformation , and for both duplexes , the 3′-overhang was inserted into the narrow active site of a TREX1 monomer . We designate molecule A as the TREX1 monomer that bound with the duplex DNA with a 1-nt-long 3′-overhang , 1-nt-L-DNA and molecule B as the TREX1 monomer that bound with the DNA duplex with a 4-nt-long 3′-overhang , 4-nt-L-DNA ( Fig 4B ) . Superposition of 1-nt-L-DNA and 4-nt-L-DNA revealed 2 distinct modes of binding duplex DNA for molecule A and molecule B ( Fig 4D and S6A Fig ) . It can be seen clearly that the duplex segments of 1-nt-L-DNA and 4-nt-L-DNA sit at 2 different loci with respect to the protein . The Leu24-Pro25-Ser26 cluster of molecule A capped the 5′-end of 1-nt-L-DNA via contact with the last base of the nonscissile strand ( Fig 4C ) . Leu24 and Ile84 in the narrow pocket of the active site in molecule A also stacked with the last nucleotide at the 3′-end of the scissile strand as in the TREX1-dI-T-dsDNA structure , indicating joint actions of the two structure motifs for removal of the 3′-overhang . Molecule A also formed 4 hydrogen bonds with the nonscissile strand of 1-nt-L-DNA and via Ser26 , Arg128 , and Lys160 . In molecule B , however , it was a groove composed of Ala161 , Leu162 , Ala214 , Gln217 , and Trp218 on the other side of the Leu24-Pro25-Ser26 cluster that contacted with the 5′-end of 4-nt-L-DNA ( S6B Fig ) . Moreover , molecule B did not form any hydrogen bonds or stacking interactions with the nonscissile strand of 4-nt-L-DNA . Therefore , the TREX1-L-structural dsDNA structure showed that , in trimming a duplex DNA to generate duplexes with blunt ends , TREX1 can cap the nonscissile 5′-end via the Leu24-Pro25-Ser26 cluster and form hydrogen bonds and stacking interactions with the nonscissile strand . Such binding mode was neither observed in the case of molecule B bound with 4-nt-L-DNA ( Fig 4D and S6B Fig ) nor in earlier structures of TREX1 with substrates that contain a longer 3′-overhang [10] . The binding mode of Leu24-Pro25-Ser26 capping the nonscissile 5′-end was also observed in the TREX1-Y-structural dsDNA structure . In this case , the crystal also contained 2 TREX1 molecules in the asymmetry unit , and both bound with a Y-structural DNA of 2-nt-long 3′- and 5′-overhang . The sequence and structure of the substrate are shown in Fig 5B . The scissile strand of the Y-structural DNA was trapped by TREX1 via more than 10 amino acids , and the last nucleotide of the 3′-end was inserted into the active site and stacked by Leu24 and Ile84 in the narrow active site pocket , as observed in the structures of TREX1-dI-T-dsDNA and TREX1-L-structural dsDNA . The last base ( G1 ) at the 5′-overhang of the substrate sits in the gap between TREX1 and the last base at the duplex region of Y-structural DNA and was flanked by the Leu24-Pro25-Ser26 cluster of TREX1 and the T3 base on the nonscissile strand ( Fig 5B and 5C ) . With the nonpairing T2 base of the nonscissile strand flipped out , this binding mode is similar to that of molecule A bound with 1-nt-L-DNA in the TREX1-L-structural dsDNA structure ( Fig 5C ) . Therefore , both structures that contain duplex DNAs with a short 3′-overhang revealed the binding mode of Leu24-Pro25-Ser26 cluster in TREX1 capping the nonscissile 5′-end . Signature of this mode also highlighted the joint actions of the Leu24-Pro25-Ser26 cluster and the active site pocket in coupling to the 3′-end of the scissile strand , and specific interactions with the nonscissile strand were observed as well . These results provide the structural basis for duplex DNAs without a 3′-overhang being a major product form of TREX1 in activity assays ( Figs 4A and 5A ) . The Leu24-Pro25-Ser26 cluster that wedged the nonscissile 5′-end in the TREX1-dI-T-dsDNA complex structure located at the N-terminal of a short helix of Pro25 to Ser27 , and the helix was linked to the β strands of β1 and β2 by 2 loops . Although β1 and β2 are highly conserved , bioinformatics analysis indicated that the sequence and structure of the region in between exhibits significant variation in the DEDDh exonuclease family ( Fig 6A and S7A Fig ) . Only TREX1 and TREX2 in the family , the corresponding region of Pro25 to Ser27 , adopted a wedge-liked structure involving a small helix , whereas the corresponding region in other family members adopted a loop form of structure ( Fig 6A ) . In targeting a single-stranded substrate , the X-ray structures of TREX1 resolved in this work ( the TREX1-dI-ssDNA structure , Fig 2C ) and those of RNase T [35] indicated that this region stacked the substrate with residues in the active site pocket in either a helical or loop form of secondary structure , and the nuclease activities of TREX1 and RNase T toward ssDNAs were similar . In TREX1 , the helical form of the Leu24-Pro25-Ser26 cluster in between β1 and β2 shaped a wedge-like structure , which can cap the 5′-end for producing blunt-end duplexes ( the TREX1-L-structural dsDNA structure , Fig 4B and the TREX1-Y-structural dsDNA structure , Fig 5B ) and even overcome the hindrance of duplex regions for processing dsDNAs ( the TREX1-dI-T-dsDNA structure , Fig 3 ) . Such unique catalytic powers compared to other members in the DEDDh family echoed the distinct helical structure form of the Leu24-Pro25-Ser26 cluster in TREX1 and the concomitant higher mechanical strength . With a loop form of structure in the corresponding region , the nuclease assay of E . coli RNase T did not reveal any activity toward dsDNA , even at an enzyme concentration as high as 10 μM under the same reaction conditions ( Fig 6B and S7B Fig ) . The capability of digesting duplex structures was only observed for the closely related homolog TREX2 that also contained a wedge helix ( Fig 6B and S7B Fig ) . Indeed , over the incubation time of our nuclease activity assays , TREX1 was shown to fully consume ssDNA as well as dsDNA , albeit the enzyme concentration for the double-stranded substrate was higher ( Fig 6C ) . To further examine the roles of Leu24-Pro25-Ser26 cluster in the activity of TREX1 , we generated 4 single-site mutants ( L24G , L24A , L24W and S26W ) and 2 triple mutants ( L24G/P25G/S26G and L24W/P25W/S26W ) of the enzyme and measured the activities of these TREX1 mutants against ssDNA and dsDNA substrates . In comparison to the wild type , all mutants showed reduced activities toward both dsDNA and ssDNA substrates ( Fig 6D , 6E and 6F and S7C , S7D and S7E Fig ) . Therefore , it can be inferred that perturbations to the Leu24-Pro25-Ser26 cluster due to these mutations affected not only the ability of stacking the last base at the 3′-end ( with Ile84 ) to properly position the substrate in the active site for catalysis ( Figs 2C , 3A , 4C and 5B ) ; they also eliminated the power of breaking the terminal base pairing . Our mutagenesis and activity characterizations highlighted the importance of the Leu24-Pro25-Ser26 cluster in both terminal unwinding of dsDNA and 3′-ended nucleotide stacking for TREX1 . As the enzyme concentration was further raised to 500 nM , the measured activity for digesting the duplex regions was also augmented to accomplish full digestion of dsDNA as long as 708 bp ( Fig 6C ) . At an enzyme concentration of 50 nM , on the other hand , TREX1 processed the ssDNA region of 3′-overhang in double-stranded substrates , leaving a blunt-end dsDNA ( Figs 4A and 5A ) ; the enzyme also trimmed the weaker pairing of a damaged base at a duplex terminal , as in the case of a nicked DNA generated by Endo V ( Fig 2B ) . These results showed that the dsDNA degradation activity is concentration dependent , and under the in vivo scenario , other factors could also come to modulate the activity . For example , it is highly likely that the activity of TREX1 is coupled with partner proteins such as high mobility group box 2 ( HMGB-2 ) . HMGB-2 is also a component of ER-associated SET complex and is related to cytosolic nucleic acid–mediated innate immune responses [42–44] . The activity of HMGB-2 in bending the dsDNA structure potentially would generate distorted structures to facilitate dsDNA degradation by TREX1 . Our preliminary results of activity measurements showed raised ability of TREX1 in digesting PCR products in the presence of mouse HMGB-2 ( mHMGB-2 ) ( S9 Fig ) . With mHMGB-2 , TREX1 can fully digest PCR product at a lower enzyme concentration of 0 . 2 μM , evidencing the interplay between mHMGB-2 and TREX1 in modulating DNase activities .
To date , the reported structures of duplex-bound TREX1 contained a substrate with a long 3′-overhang ( ≥4-nt-long ) [10] . As a result , consensus features in such structures of binding were only observed for the last 2 nucleotides at the end of the 3′-overhang , while the farther-away regions of the scissile and nonscissile strands exhibited different directions and orientations ( Fig 7A and S8A Fig ) . Therefore , using dsDNA substrates with a long 3′-overhang experienced significant difficulties in revealing the molecular mechanism by which TREX1 conducts overhang trimming and terminal unwinding . On the contrary , a consistent mode of binding was observed in the structures resolved in this work that TREX1 complexed a dsDNA with a short 3′-overhang . The 3′-end of the scissile strand and the 5′-end of the nonscissile strand ( Fig 7B ) exhibited reproducible patterns in the TREX1-L-structural dsDNA , TREX1-Y-structural dsDNA , and TREX1-dI-T-dsDNA structures . For example , stacking between the nonscissile strand and the Leu24-Pro25-Ser26 cluster as well as the hydrogen bonding between Arg128 and the nonscissile strand ( S4 and S5 Figs ) are both prominent features that were commonly observed in these structures . Based on the 4 structures newly resolved in this work and literature data , we summarize the binding modes of TREX1 with various structural DNAs in Fig 7C and 7D . The first mode is for ssDNAs longer than 4 nt and , in this case , TREX1 bound to the last 4 nucleotides at the 3′-end with the 5′-end of the strand dangling . For damaged ssDNAs with hypoxanthine bases , we showed that TREX1 digested such substrates with a similar activity as degrading DNAs with normal nitrogenous bases . The ability of TREX1 in processing dI-ssDNA also pointed to a possible role in Endo V–mediated AER . TREX1 , though , lacked the activity of cutting abasic site and 8-oxoG sites as the extra oxygen could hinder the enzyme to stack bases in the substrate . The resistance of 8-oxoG to TREX1 appears as an intrinsic design for transferring the signal of oxidative DNA damage by triggering stimulator of interferon genes complex ( STING ) –dependent immune sensing in cytoplasm [45] . Two members in DEDDh exonuclease family , T . thermophiles TTHB178 and E . coli RNase T , are homologous to TREX1 and demonstrated similar base preference , suggesting that these proteins perform similar functions in oxidative DNA damage signaling . The second mode is for the class of duplex L- and Y-structural DNA substrates with a long 3′-overhang ( ≥4 nt ) , and most of the hydrogen bonds formed between TREX1 and the substrate were in the last 3 nucleotides at the 3′-end , i . e . , in the 3′-overhang region . The nonscissile strand , on the other hand , did not land on consensus positions on the protein surface ( Fig 7A and S8 Fig ) . Therefore , in binding DNA duplexes with a longer 3′-overhang , TREX1 more tightly coupled to the last 3 bases of the 3′-overhang region , and the rest of the substrate exhibited different conformations ( Fig 7D ) . For structural DNAs containing a short ( <4 nt ) 3′-overhang , the structures resolved in this work revealed the third class of TREX1-DNA binding . The Leu24-Pro25-Ser26 cluster in TREX1 was identified as a wedge to stack and interact with the 5′-end of the nonscissile strand , particularly at the last base in the double-stranded segment . Such specific couplings of capping the nonscissile 5′-end were not observed for TREX1 structures in binding with substrates that contained a longer 3′-overhang and provided a clear structural basis for the generation of blunt-end duplexes as the main product form after removal of the 3′-overhang ( Fig 7D ) . Our structure analysis also showed that the Leu24-Pro25-Ser26 cluster plays a critical role for TREX1 to break the terminal base pairing in dsDNAs . In the activity assays of TREX1 with duplex DNAs , minor products that lacked the last 1 or 2 nucleotides at 3′-end in the double-strand region were also observed ( Figs 2B , 4A and 5A ) . For the structure with a wobble base pair shown in Fig 3 , the last base pair was indeed separated for digestion . Together , these results indicate that the Leu24-Pro25-Ser26 cluster and other specific interactions enable TREX1 to break the base pairing around the nonscissile 5′-end and hence allow further nucleotide removal in the scissile strand . The terminal unwinding activity , in fact , allowed TREX1 to process the wobble-paired dsDNA generated by Endo V and to conduct dsDNA degradation as shown in Figs 2B and 6C . Another key residue that was identified through the TREX1 structures resolved in this work is Arg128 , which makes several contacts with the nonscissile strand in a duplex . As stated earlier , for all of the dsDNA substrates that we designed to have a short ( <4 nt ) 3′-overhang , the specific interactions of Arg128 are with the nonscissile strand . On the contrary , in the structures of TREX1 with a dsDNA containing a long 3′-overhang , Arg128 instead made contact with the single-stranded region of the scissile strand , and the mode of interactions is similar to that seen in the TREX1 structures with an ssDNA [10 , 31 , 46] . Mutation of the satellite residue Arg128 in TREX1 has been shown to result in an approximately 8-fold reduction in the activity of digesting dsDNA , but only about 2-fold of activity reduction was observed for ssDNA degradation [47] . This result highlighted the greater importance of Arg128 in dsDNA degradation . Our structures thus provide the necessary molecular details for understanding this result as the binding mode of TREX1 with a DNA duplex that contains a short 3′-overhang is different from that of binding an ssDNA . Since dsDNAs are primary substrates for immune silencing , our results also provide structure basis for the in vivo observation that Arg128 mutation is related to an autoimmune disease of SLE [20] . A mystery of TREX1 in DNA repair is that the rate of spontaneous mutation in TREX1-/- mice did not increase [18] , despite the fact that genotoxic stress did lead to translocation of TREX1 to the nucleus and elevated expression levels of the enzyme [3 , 24] . A hypothesis that offers a potential explanation is participation of TREX1 in DNA repair processes like Endo V–mediated AER , and in this case , other pathways such as base excision repair ( BER ) for repairing DNAs with a hypoxanthine base would functionally overlap with those of TREX1 [48–50] . Although this scenario is subject to further studies to firmly establish , it is in line with the substrate compatibility of TREX1 with Endo V products , as observed in our activity characterization . As such , a single-gene knockout in either of the two overlapping pathways might not result in a significant increase in the rate of spontaneous mutation . An analogue example was that double mutations of DNA glycosylase and Endo V ( nfi ) were shown as necessary for an increased rate of spontaneous mutation to be observed , and transforming only intact gene 1 of 2 into the doubly mutated E . coli was sufficient to rescue the phenotype of a higher rate of spontaneous mutation [40 , 41] . Entanglement of multiple pathways would thus complicate the characterization of physiological impact for TREX1 , and it is thus essential to consider that this enzyme is likely coupled to other partners in DNA repair–related processes . For example , TREX1 is also expected to respond to UV light–induced DNA stress since translocation of the enzyme was observed upon exposure to UV illumination [24] . The consequent repairing processes include removal of L- or Y-structural dsDNA in the replication restart pathway , gap-filling homologous recombination , and RecA-dependent homologous recombination that the TREX1 homolog E . coli RNase T is also known to perform [33] . In this regard , the activity of TREX1 in trimming Y-structural dsDNA probably overlaps with that of the endonuclease Mus81-Mms4 ( Slx2-Slx3 ) , which also targets similar structures [51 , 52] . Along a similar line , the proofreading function of TREX1 in BER would overlap with that of Ape1 , which bears a 3′–5′ exonuclease activity and interacts with DNA polymerase β in editing mismatched nucleotides [53–55] . Furthermore , TREX1 may also involve in other DNA repair pathways , such as by interacting with and regulating PARP-1 , a DNA repair enzyme for which the molecular details await further studies to resolve [25] . The overlapping model thus provides a rationale for the unaffected rates of spontaneous mutation in TREX1 knockout mice , and for the proficiency of double-strand break ( DSB ) repair and BER in TREX1-deficient fibroblasts [5 , 18] . It is important to highlight that the DNA repair functions require TREX1 to be present in the nucleus . Translocation of TREX1 to the nucleus was observed during GzmA-mediated apoptosis or under genotoxic stresses in several works via immunoprecipitation and/or immunofluorescence microscopy [3 , 23 , 24] . TREX1 was also found in the nucleus and was shown to interact with a well-known DNA repair enzyme , PARP-1 , via western blotting and coimmunoprecipitation [25] . However , TREX1 translocation to the nucleus was not observed in the immunofluorescence microscopy data of a recent work [5] , suggesting the need of further studies to characterize the DNA repair function of TREX1 . TREX1 provides the major 3′–5′ exonuclease activity in mammalian cells [1 , 2] as numerous in vivo studies showed that TREX1 broadly displayed important roles in immune silencing [3 , 21] , genotoxicity responses [3 , 24] , apoptotic DNA degradation in dying cells [26] , and chromosomal fragmentation during telomere crisis [27] . In this work , we aim to provide the structure basis for the molecular origin of TREX1 that enables such diverse activities toward a wide range of nucleic acid substrates , including ssDNA , dsDNA , DNA/RNA duplexes , and structural DNAs . The endeavor of crystallizing TREX1 with various duplex DNA substrates with a short 3′-overhang revealed the structure details for the unique catalytic powers of TREX1 . We identified that the Leu24-Pro25-Ser26 cluster at the N-terminal of a short helix can cap the nonscissile 5′-end for trimming the 3′-overhang for producing a blunt-end duplex and can wedge into the duplex end to unwind the terminal base pairing in a dsDNA . These results also provide sophisticated molecular pictures for rationalizing the cellular functions of TREX1 in DNA repair , DNA proofreading , and immune silencing .
The trex1 gene from Mus musculus , with a length of 1–242 amino acids , was subcloned into BamHI/XhoI site in plasmid pET28a . The trex2 gene from M . musculus was subcloned into NdeI/XhoI site in plasmid pET28a . The expression vector was transformed into E . coli BL21-CodonPlus ( DE3 ) -RIPL or Rosetta2 ( DE3 ) pLysS strain ( Stratagene , United States ) cultured in LB medium supplemented with 50 μg/mL Kanamycin . Cells were grown to an OD600 of 0 . 5–0 . 6 and induced by 1 mM IPTG at 18 °C for 20 h . The harvested cells were disrupted by sonication in 50 mM Tris-HCl ( pH 7 . 5 ) containing 300 mM NaCl for 20 min . TREX1 and TREX2 were further purified by Ni-NTA resin affinity column ( QIAGEN ) , HiTrap Heparin ( GE Healthcare ) , and a Superdex 200 gel filtration column ( GE Healthcare ) . The purified proteins in 50 mM Tris-HCl , pH 7 . 0 and 300 mM NaCl were concentrated to suitable concentrations and stored at −20 °C until use . All of the TREX1 mutants were generated by QuickChange site-directed mutagenesis kits ( Stratagene ) and purified by the same procedures as for wild-type TREX1 . His-tagged TREX1 were treated with thrombin to generate non-His-tagged TREX1 for crystallization experiments . RNase T was purified as previous described [33] . The sequences of DNA substrates are listed in S2 Table . DNA substrates were synthesized by BEX Co . , Tokyo , Japan , or MDBio , Inc . , Taiwan . Substrates were labeled at the 5′-end with γ-32P or FAM . The γ-32P was labeled at the 5′-end of substrate DNA by T4 polynucleotide kinase ( New England Biolabs ) and then purified by a Microspin G-25 column ( GE Healthcare ) to remove the nonincorporated nucleotides . Labeled substrates ( 0 . 5 μM ) were then incubated with the exonuclease mixture in 120 mM NaCl and 20 mM Tris-HCl at pH 7 . 0 and 37 °C . The reaction was stopped by adding DNA-loading dye at 95 °C for 5 min . The digestion patterns were resolved on 20% denaturing polyacrylamide gels and visualized by autoradiography ( Fujifilm , FLA-5000 ) or UV light . When the substrate was a PCR product , we added protease K into the reaction mixture at 37 °C for 1 h to stop the reaction . The DNA digestion patterns were resolved on 1% agarose gel and visualized by UV light . His-tagged or non-His-tagged TREX1 ( 15–25 mg/mL ) in 300 mM NaCl and 50 mM Tris-HCl , pH 7 . 0 were mixed with different DNA substrates in the molar ratio of 1:1 . 5 . Detailed information regarding DNA sequences and crystallization conditions of the 4 structures are given in S1 Table . All crystals were cryoprotected by Paraton-N ( Hampton Research , USA ) for data collection at BL13C1 , BL13B1 , and BL15A1 in NSRRC , Taiwan , or at the BL44XU beamline at SPring-8 , Japan . All diffraction data were processed by HKL2000 , and diffraction statistics are listed in Fig 1 . Structures were solved by the molecular replacement method and using the crystal structure of M . musculus TREX1 ( PDB: 3MXM ) as the search model by MOLREP of CCP4 [56] . The models were built by Coot [57] and refined by Phenix [58] . Diffraction structure factors and structural coordinates have been deposited in the RCSB PDB with the PDB ID code of 5YWV for the TREX1-dI ssDNA complex , 5YWU for the TREX1-dI-T-dsDNA complex , 5YWT for the TREX1-L-structural dsDNA complex , and 5YWS for the TREX1-Y-structural dsDNA complex .
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Three prime repair exonuclease 1 ( TREX1 ) was shown to participate in various cellular events such as DNA repair , immunity regulation , and viral infection . In addition to relating to autoimmune diseases , this exonuclease also acts as a potential protein target for anticancer or antiviral therapies . A key for such broad attendance of TREX1 is the activities of precise trimming of the 3′-overhang in a double-stranded ( dsDNA ) and breaking of the terminal base pairing of the duplex . Here , we designed a series of structural DNA substrates and activity assays to delineate the underlying mechanisms . The structures newly resolved in this work indicated that the Leu24-Pro25-Ser26 cluster of TREX1 is essential for the enzyme to carry out the aforementioned activities . Together , our results established an integrated structure view into the versatile exonuclease functions of TREX1 and illuminated the molecular origin for the unique catalytic properties of TREX1 in processing various DNA intermediates in DNA repair and in cytosolic immunity regulation .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"methods"
] |
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"crystal",
"structure",
"nucleases",
"enzymes",
"condensed",
"matter",
"physics",
"dna-binding",
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2018
|
Structural basis for overhang excision and terminal unwinding of DNA duplexes by TREX1
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Semen liquefaction changes semen from a gel-like to watery consistency and is required for sperm to gain mobility and swim to the fertilization site in the Fallopian tubes . Kallikrein-related peptidases 3 ( KLK3 ) and other kallikrein-related peptidases from male prostate glands are responsible for semen liquefaction by cleaving gel-forming proteins ( semenogelin and collagen ) . In a physiological context , the liquefaction process occurs within the female reproductive tract . How seminal proteins interact with the female reproductive environment is still largely unexplored . We previously reported that conditional genetic ablation of Esr1 ( estrogen receptor α ) in the epithelial cells of the female reproductive tract ( Wnt7aCre/+;Esr1f/f ) causes female infertility , partly due to a drastic reduction in the number of motile sperm entering the oviduct . In this study , we found that post-ejaculated semen from fertile wild-type males was solidified and the sperm were entrapped in Wnt7aCre/+;Esr1f/f uteri , compared to the watery semen ( liquefied ) found in Esr1f/f controls . In addition , semenogelin and collagen were not degraded in Wnt7aCre/+;Esr1f/f uteri . Amongst multiple gene families aberrantly expressed in the absence of epithelial ESR1 , we have identified that a lack of Klks in the uterus is a potential cause for the liquefaction defect . Pharmacological inhibition of KLKs in the uterus replicated the phenotype observed in Wnt7aCre/+;Esr1f/f uteri , suggesting that loss of uterine and seminal KLK function causes this liquefaction defect . In human cervical cell culture , expression of several KLKs and their inhibitors ( SPINKs ) was regulated by estrogen in an ESR1-dependent manner . Our study demonstrates that estrogen/ESR1 signaling in the female reproductive tract plays an indispensable role in normal semen liquefaction , providing fundamental evidence that exposure of post-ejaculated semen to the suboptimal microenvironment in the female reproductive tract leads to faulty liquefaction and subsequently causes a fertility defect .
In the United States , approximately 46% of women are unable to conceive within the first 12 months of trying to get pregnant [1] . Infertile couples may experience psychological distresses , including low self-esteem , isolation , and depression . Cumulatively , the infertile couples in the United States have spent more than ~$5 billion per year for diagnosis and treatment in fertility clinics [2] . These circumstances emphasize the need for a better understanding of the causes of infertility . In humans , a semen coagulum is composed of the secretory products from male accessory organs , including the prostate glands , seminal vesicles , and coagulating glands . After ejaculation , both semen and sperm are deposited to the anterior wall of the vagina , adjacent to the ectocervical tissues . In order for the sperm to travel through the reproductive tract to fertilize the eggs in the oviduct ( or Fallopian tube in humans ) [3] , the semen must undergo the process of liquefaction . Congenital absence , obstruction , or surgical removal of the seminal vesicles causes sterility in men and rodents [4 , 5] , indicating that not only are the secretory products from the seminal vesicles and prostate crucial for sperm motility , sperm viability , and chromatin stability of the sperm [6] , but that they are also important for semen liquefaction . Tissue kallikrein-related peptidases , or KLKs , are members of a serine protease family that exhibit trypsin- and chymotrypsin-like activities . Of the 37 Klk genes in the mouse genome , 26 encode functional proteins [7] . KLKs are translated as pre-pro-KLKs and are regulated by a proteolytic activation cascade that produces active KLKs , which are secreted from the kidneys , liver , salivary glands , and male and female reproductive organs [8 , 9] . Sperm in the ejaculate are entrapped in a seminal coagulum , which is comprised mainly of semenogelins ( SEMGs ) , fibronectin , and collagen secreted from the seminal vesicles [10 , 11] . Liquefaction is mainly modulated by prostate derived KLK3 [10] . In females , KLKs 5–8 , 10–11 , and 13–15 are expressed at very high levels in the cervix and vagina compared to in other adult tissues [12 , 13] . Moreover , KLK1 and KLK3 transcripts are expressed at the highest level in human endometrium when circulating estradiol ( E2 ) is elevated [14 , 15] . In rodents , E2 increases KLK expression in the uterus [16 , 17] . These findings suggest that KLKs are expressed in the human and mouse reproductive tracts and that some of the KLKs in the uteri are regulated by E2 . However , the role of the female reproductive tract in regulation of post-ejaculated seminal KLKs remains unclear . E2 is a steroid hormone secreted from the granulosa cells of the ovary . Estrogens exert their functions through estrogen receptor α and β ( ESR1 and ESR2 ) . ESR1 is predominantly expressed in the female reproductive tissues , which include the ovary , oviduct , uterus , and mammary gland [18] . We previously reported that mice lacking ESR1 in the epithelial cells ( using Esr1f/f crossed with Wnt7aCre/+ mice ) are infertile [19] , partly due to a reduction in the number of sperm able to reach the oviduct [20] . However , the effect of ESR1 loss in the epithelial cells on sperm transport in the uterus has not yet been investigated . In this study , we showed 1 ) the expression of KLKs in the mouse uterus is downstream of E2 signaling acting through epithelial ESR1 , and 2 ) loss of epithelial ESR1 disrupts sperm transport by affecting semen liquefaction and sperm motility . Additionally , as the semen is deposited at the ectocervix in humans , we examined whether human ectocervical cells express KLK transcripts and whether this expression is modulated by E2 . Our studies provide the first evidence of how the interplay between semen and the female reproductive tract could impact fertility .
Our previous findings demonstrated that loss of ESR1 in the mouse uterine and oviductal epithelial cells causes a reduction of the number of sperm in the oviduct [20] , however , the cause of this sperm reduction is unknown . Therefore , we evaluated the uterine morphology of these mice to gain insight of the potential explanation . To assess the effect of the absence of ESR1 in the uterine epithelial cells on sperm transport , the Esr1f/f and Wnt7aCre/+;Esr1f/f females were mated with the WT male proven breeder and the uteri were collected at 0 . 5 dpc . The absence of ESR1 protein in the uterine luminal ( LE ) and glandular ( GE ) epithelial cells was confirmed in the Wnt7aCre/+;Esr1f/f compared to Esr1f/f females using immunohistochemical ( IHC ) analysis ( Fig 1A ) . Gross morphology of Esr1f/f uteri collected at approximately 8 h after mating showed ballooning uteri , however , Wnt7aCre/+;Esr1f/f uteri did not ( Fig 1B ) . As a result , the uterine diameter of Wnt7aCre/+;Esr1f/f animals was significantly smaller than those of Esr1f/f controls ( Fig 1C ) . In addition , total fluid volume from the uterine lumen was significantly lower in Wnt7aCre/+;Esr1f/f than in Esr1f/f animals ( Fig 1D ) . Astwood demonstrated that E2 increases fluid accumulation in the uterine lumen and this E2-induced water imbibition is regulated through aquaporin ( AQP ) water channels [21 , 22] . Our microarray analysis showed that E2 treatment robustly increased the expression of Aqp1 , Aqp5 , and Aqp8 transcripts at 2 h , however , at 24 h , the induction of Aqp transcripts was not as strong as the 2 h treatment in the control uteri ( S1 Table ) . These Aqp genes were expressed at significantly lower levels in Wnt7aCre/+;Esr1f/f compared to Esr1f/f uteri 2 h or 24 h after E2 treatment , except Aqp5 at 24 h ( S1 Table ) . To determine whether Aqps were aberrantly expressed in Wnt7aCre/+;Esr1f/f at 8 h after mating , we collected uterine samples and performed real time RT-PCR analysis and found that the expression of the highly expressed Aqps in the uterus , including Aqp1 , Aqp5 , Aqp8 , and Aqp11 , were detected at comparable levels between Esr1f/f and Wnt7aCre/+;Esr1f/f uteri at 0 . 5 dpc ( Fig 1E ) . These findings suggest the water imbibition was rapidly mediated by E2 through an up-regulation of Aqps in control uteri . However , at 8 h after mating , transcript levels of Aqps were not differentially expressed in Esr1f/f and Wnt7aCre/+;Esr1f/f uteri , regardless of a lack of ballooning in Wnt7aCre/+;Esr1f/f uteri . Strikingly , semen liquefaction is affected by a lack of uterine epithelial ESR1 . The liquefaction time was determined by the time it took for semen collected from Esr1f/f and Wnt7aCre/+;Esr1f/f uteri to fill a 25-μL capillary tube . In Esr1f/f uteri , the semen liquefaction time was 1 . 86±0 . 15 min , whereas the semen collected from Wnt7aCre/+;Esr1f/f uteri was too viscous and could not fill the tube by the end of the 1 h experimental time ( Fig 1F ) . This evidence is the first illustration that semen from a WT male can be solidified as a result of exposure to the Wnt7aCre/+;Esr1f/f female reproductive tract , which could likely lead to the severely reduced sperm number in the oviduct observed in our previous findings [20] . Histological analysis of uterine cross-sections demonstrated that the semen present in the Esr1f/f uterine lumen appears loose , whereas dense materials were observed only in the Wnt7aCre/+;Esr1f/f uteri ( Fig 1G ) . The sperm density was measured to evaluate if the viscous semen or the dense materials within the Wnt7aCre/+;Esr1f/f uterine lumen contribute to the sperm entrapment/blockade within the uterus . We found the density of sperm/mm2 in the Wnt7aCre/+;Esr1f/f uteri was significantly higher in comparison to the sperm present in the Esr1f/f uteri ( Fig 1H ) . Because the sperm density was higher in the Wnt7aCre/+;Esr1f/f uteri , we assessed whether the total sperm count per seminal volume was different in Esr1f/f and Wnt7aCre/+;Esr1f/f uteri . We found there was no significant difference in total sperm count between Wnt7aCre/+;Esr1f/f and Esr1f/f animals 8 h after mating ( Fig 1I ) . To determine whether the sperm present in the uteri were motile , we counted the percentage of motile sperm per microscopic field and found that the sperm collected from Wnt7aCre/+;Esr1f/f uteri had significantly higher numbers of immotile sperm compared to those from Esr1f/f uteri ( Fig 1J; S1 and S2 Videos ) . Conversely , a significantly smaller percentage of sperm with rapid progressive motility was observed in the semen collected from Wnt7aCre/+;Esr1f/f compared to those from Esr1f/f uteri . This finding suggests that in the absence of uterine epithelial ESR1 , normal sperm were unable to dislodge from the seminal coagulum , leading to a decreased number of motile sperm . Degradation of semen coagulants such as collagen and SEMG1 leads to liquefaction [10 , 11] . To determine whether the liquefaction defect observed in Wnt7aCre/+;Esr1f/f uteri was due to defective degradation of semen coagulants , we evaluated the presence of collagen and SEMG1 within the uterus after mating . Using Masson’s Trichrome staining , the results indicated that material present in the uterine lumen of Wnt7aCre/+;Esr1f/f animals contained a considerable amount of collagen compared to Esr1f/f animals ( Fig 2A ) . Additionally , measurable levels of cleaved SEMG1 were present only in the Esr1f/f animals , and were not detected in Wnt7aCre/+;Esr1f/f animals ( Fig 2B and 2C ) . This suggests that lacking uterine epithelial ESR1 contributes to a liquefaction defect due to reduced semen coagulant degradation . In humans , it is known that KLK3 secreted from male accessory sex organs regulates semen liquefaction [10 , 23] . However , we have reported here that liquefaction could also be modulated by the female reproductive tract . To elucidate whether the Klk family is present in the uterus and the expression is regulated by E2 signaling , our previously published microarray dataset of the uteri from Esr1f/f and Wnt7aCre/+;Esr1f/f animals treated with E2 for 2 h [24] was analyzed . Transcript levels of the Klk1 and Klk1b families were increased in E2 treated Esr1f/f uteri at 2 h compared to vehicle treatment ( Fig 3A ) . However , these E2-induced Klk1 and Klk1b family expressions were minimally detected or were not at a detectable level in Wnt7aCre/+;Esr1f/f uteri compared to vehicle treatment . To validate expression at the transcriptional level in the presence of male ejaculates at 0 . 5 dpc , the mRNA expression of Klk1 and Klk1b5 was determined , as these two genes were abundant among other Klk1 family members . Klk1 and Klk1b5 expression was significantly reduced in Wnt7aCre/+;Esr1f/f uteri compared to Esr1f/f uteri ( Fig 3B ) . Moreover , we found that the KLK1B5 protein level was significantly lower in the Wnt7aCre/+;Esr1f/f uteri compared to Esr1f/f uteri at 0 . 5 dpc ( Fig 3C and 3D ) . It has been previously shown that Klk1 mRNA is expressed in the endometrial glands of humans and mice [15 , 17] . Therefore , glandular epithelial cells may be the potential source of KLK production in the uterine tissues . To determine whether the loss of uterine epithelial ESR1 affects cell proliferation and subsequently disrupts the Klk transcript levels , we evaluated the proliferation of all uterine cell types including luminal , glandular , and stromal cells at 0 . 5 dpc in Esr1f/f and Wnt7aCre/+;Esr1f/f animals . Ki67 was used as a marker to visualize cell proliferation . The percentages of Ki67 positive luminal epithelial and stromal cells were comparable between Esr1f/f and Wnt7aCre/+;Esr1f/f uteri ( Fig 4A and 4B ) . However , Ki67 positive glandular epithelial cells were detected at a significantly higher level in Wnt7aCre/+;Esr1f/f than those of Esr1f/f uteri ( Fig 4B ) . Additionally , the marker of the gland , Foxa2 , was expressed at a significantly higher level in Wnt7aCre/+;Esr1f/f compared to Esr1f/f uteri ( Fig 4C ) . These results suggest that a lack of Klk transcripts in the absence of epithelial ESR1 was not due to a loss of glandular epithelial cells; in fact , the marker of glandular epithelial cells was expressed at a higher level in uteri lacking epithelial ESR1 . Human KLK activity can be effectively inhibited by endogenous protease inhibitors such as serine protease inhibitors ( SERPINs ) , serine protease inhibitors , Kazal type ( SPINKs ) , elafin , and α1-antitrypsin [25 , 26] . It has been previously shown that SERPIN inhibits KLK activity by interacting with the reactive loop , causing an irreversible protein conformational change of KLK [27 , 28] . In addition , changes in expression levels of other proteinases and protease inhibitors could also affect KLK activity . Therefore , to explore whether the liquefaction defect observed in Wnt7aCre/+;Esr1f/f uteri was due to aberrant expression of protease inhibitors , proteinases , and proteinase inhibitors , in addition to a loss of Klk production , the microarray dataset of E2 treated Esr1f/f and Wnt7aCre/+;Esr1f/f uteri was assessed ( Table 1 ) . To compare the expression level of proteases and protease inhibitors , we listed the signal intensities of genes relative to Esr1 in Table 1 . Esr2 was used as a negative control . We found that 7 of 22 Serpin gene family members had higher signal intensities , whereas the intensities of 3 of 22 Serpins were lower in Wnt7aCre/+;Esr1f/f compared to Esr1f/f uteri ( Table 1 ) . However , 54% ( 12 of 22 ) of the Serpin genes in Wnt7aCre/+;Esr1f/f were expressed at comparable levels to those of Esr1f/f uteri . In addition , we evaluated the expression of other proteinases and proteinase inhibitors such as Spinks , matrix metalloprotenases ( Mmps ) , tissue inhibitor of metalloproteinases ( Timps ) , cysteine proteases and protease inhibitors , which include defensins ( Def ) , cathepsins ( Cts ) , α2-macrogobulin ( A2m ) , and secretory leukocyte peptidase inhibitor ( Slpi ) . The expression levels of these proteases and protease inhibitors were at comparable levels between E2-treated Wnt7aCre/+;Esr1f/f and E2-treated Esr1f/f uteri ( Table 1 ) . The only exceptions were the expression of Def3 was significantly lower and Ctsw was significantly higher in E2-treated Wnt7aCre/+;Esr1f/f uteri compared to E2-treated Esr1f/f uteri . To identify whether these genes were expressed and regulated by epithelial ESR1 during early pregnancy , we collected the uterine tissues at 0 . 5 dpc from Esr1f/f and Wnt7aCre/+;Esr1f/f animals and evaluated the expression levels using real-time PCR analysis . Serpina1b , Serpina1d , Serpinb7 , Serpinh1 , Spink3 , Mmp2 , Mmp9 , Mmp11 , Mmp14 , Mmp17 , Timp1 , Timp2 , and Timp3 genes were selected for real-time PCR analysis based on their moderate to high levels of signal intensities ( from the microarray dataset mentioned in the previous section ) compared to other genes in the families . We found that Serpina1b , Serpina1d , and Spink3 were expressed at comparable level between Esr1f/f and Wnt7aCre/+;Esr1f/f uteri at 0 . 5 dpc ( Fig 5A ) . However , expression of Serpinb7 and Serpinh1 were significantly higher in Wnt7aCre/+;Esr1f/f compared to Esr1f/f uteri ( Fig 5A ) . We evaluated the protein expression of the most abundant uterine SERPIN , SERPINH1 , using immunoblotting and found that although the transcription level of Serpinh1 was significantly higher in Wnt7aCre/+;Esr1f/f compared to Esr1f/f uteri , the translation of SERPINH1 was at comparable levels ( Fig 5B and 5C ) . In addition , only Mmp2 , not other Mmps nor Timps , was expressed at a significantly higher level in Wnt7aCre/+;Esr1f/f compared to Esr1f/f uteri ( Fig 5D and 5E ) . These results suggest that E2 not only regulates the expression of Klk transcripts , but that it also regulates the transcription of serine protease inhibitors ( Serpinb7 and Serpinh1 ) . However , SERPINH1 protein level was not altered in the absence of uterine epithelial ESR1 . To explore the possibility that alteration of KLK activity in the uteri can disrupt the post-ejaculated semen liquefaction process , we injected into the uterine lumen a tissue KLK inhibitor ( 4- ( 2-Aminoethyl ) benzenesulfonyl fluoride hydrochloride or AEBSF ) to inhibit serine proteases including multiple tissues’ KLKs [29] . Note that KLKs in the uterus of a mated female could originate from both the semen and the female reproductive tract . Compared to the Wnt7aCre/+;Esr1f/f uteri , which lack Klk transcripts , the AEBSF treatment stimulated a significant reduction in KLK activities without an alteration of other E2-targeted pathways . The uterine diameter as well as intrauterine fluid volume of semen collected from female mice treated with AEBSF were significantly reduced compared to those of saline treated mice ( Fig 6A and 6B ) . However , we were unable to determine the liquefaction time of the semen collected from AEBSF treated animals , as the volume of semen was insufficient for measurement ( Fig 6C ) . More importantly , the number of sperm that reached the oviducts was drastically decreased in the female mice treated with AEBSF compared to the saline treated controls ( Fig 6D ) . In addition , we found that the SEMG2 protein tended to be expressed at a higher level in the AEBSF treated group , whereas the cleaved SEMG1 protein tended to be lower in the AEBSF compared to the saline treated group ( Fig 6E and 6F ) . This finding indicates that the use of a pharmacological inhibitor of serine protease activity ( including KLKs ) recapitulates the phenotype observed in Wnt7aCre/+;Esr1f/f uteri . Due to anatomical differences in the location of semen after ejaculation between mice and humans , as well as the difference between human and mouse KLKs , we tested whether human cervical cells , particularly ectocervical ( hEct1 ) and endocervical ( hEnd1 ) cells , express KLKs and their inhibitors , SPINKs . We found that in the absence of hormonal treatment , KLK1 and KLK7 were expressed at minimal levels in hEct1 and hEnd1 cells ( Fig 7A ) . As expected , prostate-specific KLKs ( KLK2 and KLK3 ) were expressed only in the prostate cancer ( LNCaP ) cell line . hEct1 cells expressed KLK4 , KLK5 , and KLK8 at high levels relative to other KLKs . hEnd1 cells also expressed KLK4 and KLK5 , but at lower levels , and showed a slightly higher level of KLK8 compared to hEct1 cells . SPINK5 and SPINK6 were expressed in hEct1 cells . However , hEnd1 cells only expressed SPINK5 , and not SPINK6 . In addition , KLK15 was expressed only in the LNCaP cells . Ishikawa ( endometrial cancer ) cells were used as a negative control . hEct1 cells were chosen to assess whether E2 regulates the expression of KLKs and SPINKs based on their anatomical location , as they are the first cells semen comes in contact with after ejaculation . First , we identified whether hEct1 cells expressed ESR1 in comparison to other cell types using RT-PCR . The transcript level of ESR1 was approximately 15-fold higher in hEct1 cells compared to hEnd1 and LNCaP cell lines , and ESR1 expression in Ishikawa cells remained below the detection threshold ( Fig 7B ) . Protein levels of ESR1 were confirmed using immunoblotting ( Fig 7C ) . The low level of β-ACTIN in the LNCaP cell line is likely due to the nature of LNCaP cells , which do not tightly adhere to the culture dish , and thus require fewer actin filaments . After confirming the presence of ESR1 in hEct1 cells , hEct1 cells were treated with E2 in the presence or absence of ICI 182 , 780 ( ICI; ESR antagonist ) to inhibit the action of ESR1 . E2 at a dose of 10 nM significantly increased the expressions of KLK4 , KLK5 , KLK8 , SPINK5 , and SPINK6 ( Fig 7D ) . In the presence of ICI , E2-induced expression of those genes was completely abolished ( Fig 7D ) . Collectively , these results indicate that human cervical cells expressed distinct family members of KLKs compared to those in prostate cells , and the expression of KLKs and their inhibitors in ectocervical cells was regulated through E2/ESR1 action . We propose a network of pathways to explain our observations of the process of semen liquefaction in the female reproductive tract ( Fig 8 ) . When semen , which contains KLKs , enters the uterus , it is exposed to uterine KLKs and KLK inhibitors that have been produced in response to E2 stimulation of ESR1 . Normally , total KLK enzymatic activity overwhelms inhibitory action and produces liquefaction of the semen , which frees the sperm to swim into the oviduct . In addition , E2/ESR1 signaling may upregulate Aqp genes to increase fluidity of uterine contents and further support sperm movement into the oviduct . This proposed network should guide future exploration of the processes of liquefaction of semen and release of sperm to ascend to the site of fertilization .
Previous studies illustrated that female mice lacking ESR1 in the uterine and oviductal epithelial cells show a severely reduced number of sperm in the oviduct [20] , however , the cause of this decrease was unclear . After ejaculation , sperm need to be dislodged from the seminal coagulum prior to traveling into the oviduct . In humans , semen from fertile men is completely liquefied after 20 to 30 minutes post-ejaculation in vitro [30] . It is known that liquefaction defects such as semen hyperviscosity is one of the causes of infertility in men [31] , however , defective liquefaction caused by female conditions has never been reported . After ejaculation , semen is exposed to secretory proteins in the female reproductive tract , which possess a dynamic range of enzymatic activities including SPINKs [25] . Herein , we observed a liquefaction defect in Wnt7aCre/+;Esr1f/f uteri when these females mated with a male proven breeder , indicating that liquefaction can be modulated and disrupted by an exposure to a suboptimal environment in the female reproductive tract . Therefore , we proposed that these complex enzymatic activities in the female reproductive tract can disrupt post-ejaculated semen liquefaction . Our findings suggest that a lack of E2 signaling in the epithelial cells of the female reproductive tract causes faulty liquefaction and results in a fertility defect . Due to a difference in uterine morphology between Esr1f/f and Wnt7aCre/+;Esr1f/f females after mating , we investigated possible pathways that could lead to a lack of uterine ballooning or imbibition . One likely mechanism is E2-induced water transport channel activation . Astwood showed that luminal fluid volume is increased after 6 h of E2 treatment [21] . Later , Zhang et al . demonstrated that this E2-induced fluid accumulation is due to regulation through AQP5 and AQP8 by using Aqp5-/- and Aqp8-/- mouse models [22] . Analysis of our microarray data on the aquaporin gene family showed that E2 robustly induced the expression of Aqp1 , Aqp5 , and Aqp8 2 h after treatment in the uteri of ovariectomized control mice , and the effect declined 24 h after E2 treatment . However , these robust E2-induced Aqp1 , Aqp5 , and Aqp8 transcripts were not observed in the absence of uterine epithelial ESR1 . We did not observe differential expression of Aqp transcripts in the Wnt7aCre/+;Esr1f/f uteri after mating compared to controls . This is likely because the expression of Aqps had already declined to basal levels as the circulating level of E2 dropped after mating . These findings suggest that Aqp1 , Aqp5 , and Aqp8 are upregulated by E2/ESR1 signaling . Zhang et al . demonstrated that Aqp5−/−;Aqp8−/− mice are capable of having 80% of embryo implantation sites compared to controls , regardless of the significant decrease of intrauterine fluid accumulation [22] . However , Zhang et al . did not directly evaluate whether the reduction of uterine fluid disrupts sperm motility . Thus , the loss of fluid flow due to reduced uterine fluid volume could also result in the sperm motility defect observed in Wnt7aCre/+;Esr1f/f females . KLKs are a family of serine proteases secreted from epithelial cells that play a central role in extracellular matrix remodeling , inflammation , and regulation of blood flow . There is limited knowledge regarding the proteolytic activities of seminal proteins after deposition in the female reproductive tract [32] , therefore , it is likely that undetermined interactions between seminal proteins and secretions from the female reproductive tract may contribute to the liquefaction defect observed in Wnt7aCre/+;Esr1f/f female mice . In males , KLK2 and KLK3 transcripts are regulated by androgens; and androgen responsive elements ( ARE ) are present in the promoters of both KLK2 and 3 [33] . Conversely , KLK1 expression in mouse and rat uteri is influenced by E2 [17]; and an estrogen responsive element ( ERE ) is found in the Klk1 promoter [34] . In humans , KLK levels in cervical and vaginal fluid are positively correlated with pregnancy and are possibly regulated by female steroid hormones [13] . As KLKs are secreted proteins , there is considerable overlap in the protein composition of fluids from the different parts of the female reproductive tract in both mice [35] and humans [25] . In mice , we demonstrated that mRNA levels of Klks and their inhibitors are differentially expressed in the uterus and oviducts [20 , 24] . Similar to mice , different KLKs are expressed in different cell types along the epithelial lining of the reproductive tract in women [12] . The secretory protein levels of KLKs correlate with the expression of each KLK member along the reproductive tract [25] . These findings suggest that the differential regulation of KLK expression in each region of the female reproductive tract also plays a crucial part in regulating local KLK activities . Seminal KLKs inhabit a different environment from their site of secretion when they are deposited in the female reproductive tract . Our study showed that a lack of ESR1 in mouse uterine epithelial cells caused severely reduced expression of genes in the Klk family . However , our previous studies show that in the absence of epithelial ESR1 in the oviduct , expression of Klks is induced [20] . Therefore , these findings indicate that Klk expression in response to E2 is differentially regulated between the uterus and the oviducts . This novel finding suggests that E2-regulated Klk transcripts in the female reproductive tract are tightly regulated in a tissue-specific manner , and the induction of Klks through ESR1 in the uterus may be a mechanism for post-ejaculated semen liquefaction in the female reproductive tract . We speculate this differential regulation mechanism is used in part to locally regulate KLK activity . E2 mediates the cell proliferation processes that are pivotal for cellular growth and differentiation . In both humans and mice , E2 increases the proliferation of cells in the female reproductive tract [36 , 37] . Our previous work elucidates that normal uterine epithelial and stromal cell proliferation during early pregnancy is dependent on epithelial ESR1 [24] . To distinguish whether a loss of Klk production in the Wnt7aCre/+;Esr1f/f mice compared to Esr1f/f mice was due to a difference in epithelial cell growth and proliferation , we assessed the proliferative index . We found the percentage of positive Ki67 luminal epithelial and stromal cells was comparable between Esr1f/f and Wnt7aCre/+;Esr1f/f animals . However , in Wnt7aCre/+;Esr1f/f uteri , glandular epithelial cells had a significantly higher percentage of Ki67 positive cells compared to Esr1f/f uteri . Thus to indirectly validate the gland formation , we evaluated the expression of Foxa2 , a glandular epithelial cell marker [38] , and observed a higher level of Foxa2 expression in Wnt7aCre/+;Esr1f/f compared to Esr1f/f uteri . We reasoned that elevated Foxa2 expression as well as the glandular epithelial cell proliferation in the absence of epithelial ESR1 were due to a compensation for the lack of glandular products/secretions that normally provide positive feedback to stimulate uterine gland development . The increase in cell proliferation of glandular epithelium does not promote the expression of the Klks in the mouse , and the change of Klk expression is not a secondary effect from cell proliferation due to a lack of ESR1 . Matsuda et al . demonstrated that 30 min of proteinase inhibitor treatment causes a solidification of human semen and results in a sperm motility defect [39] . In addition , the serine protease inhibitor SPINK3 is capable of inhibiting protease activity in the mouse uterus [40] . These findings indicate that the presence of protease inhibitors can disrupt semen liquefaction by suppressing protease activities from the semen . Our study demonstrated that the lack of ESR1 in epithelial cells of the female reproductive tract significantly increases the expression of the serine protease inhibitors Serpinb7 and Serpinh1 . However , the translational level of SERPINH1 protein was not different . Moreover , transgenic mice overexpressing Serpinb7 showed normal fertility [41] . Thus , it is unlikely that the liquefaction defect in Wnt7aCre/+;Esr1f/f mice was due to excess protease inhibitors . In addition to serine proteases , other proteases like MMPs are also capable of degrading extracellular matrix proteins . Although MMP proteins do not possess the catalytic triads required for proteolytic function in KLKs ( His57 , Asp102 , and Ser195 ) [42] , neutrophils bearing proMMP9 can be attracted by seminal plasma and their activities are elevated post-coitus in the female uterus [43] . In our model , all Mmp transcripts and their inhibitors were expressed at the same level between Esr1f/f and Wnt7aCre/+;Esr1f/f uteri . The only exception was a higher level of Mmp2 in Wnt7aCre/+;Esr1f/f compared to Esr1f/f uteri . MMP2 targets gelatin , collagen IV , V , VII , X and XI , fibronectin , laminin , elastin , and aggrecan [44] . Therefore , it is possible that the increased level of MMP2 transcripts was a response to the presence of an elevated collagen content ( Fig 2A ) . Nevertheless , the elevated Mmp2 level fails to correct the faulty semen liquefaction in the absence of uterine epithelial ESR1 . In addition to MMPs and SERPINs , the female reproductive tract also expresses several other proteases and protease inhibitors such as cathepsins , defensins , and SPLI , as part of their innate immune response to bacterial and viral infection [45] . Overall expression of these proteases and protease inhibitors was at comparable levels in Esr1f/f and Wnt7aCre/+;Esr1f/f uteri . Minor changes in the transcripts for some of these genes did not alter our conclusion that a loss of E2 regulation in the uterine epithelial cells causes a disruption in Klk transcript levels , but not other proteases or protease inhibitors . We investigated whether inhibition of multiple KLK activities in the uterus could mimic the phenotype of Wnt7aCre/+;Esr1f/f animals using AEBSF , an irreversible serine protease inhibitor that also affects tissue KLKs . We found that AEBSF treatment resulted in a drastic decrease in the number of sperm that reached the oviduct . However , the cleavage of SEMG1 in AEBSF treated animals was not significantly different from saline treated controls . It is possible that AEBSF could have unintended effects in the female reproductive tract . This could include inhibition of other serine proteases such as chymotrypsin and trypsin , which are present in semen and the uterus . This inhibitory effect could suppress the degradation of collagen and disrupt liquefaction . Moreover , post-mating uteri also contain the seminal KLKs . The suppression of KLK activities using AEBSF cannot rule out that liquefaction and semenogelin and collagen cleavage are catalyzed by seminal KLKs . Nevertheless , several proteases and protease inhibitors were present in both Esr1f/f and Wnt7aCre/+;Esr1f/f uteri , and the solidified semen was only observed in the condition where uterine Klks were minimally expressed . Histological analysis demonstrated a semen liquefaction defect of entrapped sperm within the semen coagulum in the uterus in the absence of epithelial ESR1 . The denser semen resulted in a prolonged liquefaction time in Wnt7aCre/+;Esr1f/f animals . The majority of sperm entrapped in the solidified semen were immotile as they were unable to dislodge from the seminal coagulum and the higher sperm density in Wnt7aCre/+;Esr1f/f uteri was attributed to a reduced fluid volume in the uterus . There was no statistically significant difference between total sperm number in Wnt7aCre/+;Esr1f/f and Esr1f/f uteri . We further identified that gel-forming proteins in the seminal plasma , SEMG1 and collagen , were not degraded in Wnt7aCre/+;Esr1f/f uteri . Collectively , these results indicate that ejaculated semen requires additional regulation in the female reproductive tract to lyse gel-forming proteins and allow effective liquefaction . In women , post-ejaculated semen is deposited at the anterior wall of vagina adjacent to the ectocervix . To explore whether KLKs are also expressed and regulated by E2/ESR1 signaling in human cervical cells , we determined the expression pattern of all KLK family members using immortalized hEct1 and hEnd1 cells . The results indicated that KLKs were expressed in the hEct1 cells and that KLK4 , KLK5 , and KLK8 were the most abundant serine proteases . This finding is relevant to reproductive medicine as it was previously shown that KLK4 , KLK5 , and KLK8 are able to cleave fibronectin [46] , another important protein that contributes to semen coagulation [47] . KLK5 is also responsible for digestion of collagen and modification of mucin to facilitate sperm transport [13 , 25] . In addition , Pro-KLK2 , 3 , 7 , 8 , and 14 in the semen are activated by KLK5 [48] , which is self-activated over time [9] . More importantly , this study indicates that KLK inhibitors SPINK5 and SPINK6 were highly expressed in the hEct1 cell line . E2 increases KLK and SPINK expression through an ESR1-dependent pathway . SPINK5 specifically inhibits KLK5 , KLK7 , and KLK14 activity , and mutations in SPINK5 cause Netherton Syndrome , a severe skin disorder [49 , 50] . The function of SPINK6 is less well-established [51] . Although human seminal fluid contains KLK2 , 3 , 4 , 5 , 8 , 11 , 12 , 14 , and 15 [52] , the function of SPINKs in semen liquefaction is unclear . Inhibition of KLK5 by SPINK5 and 6 can prevent the activation of other KLKs in the semen . Ultimately , inhibition of KLK5 could potentially lead to two problems: 1 ) a failure to activate KLK2 and 3 , preventing the degradation of SEMG and causing faulty semen liquefaction and sperm liberation , and 2 ) a defective cervical mucin remodeling , as KLK5 and 12 are responsible for cleavage of mucin 4 and 5B , the main cervical mucus proteins [25 , 53] to guide the sperm to go through the cervix . These findings strongly suggest that human KLKs and KLK inhibitors from the female reproductive tract are indispensable for normal semen liquefaction and sperm transport . This study demonstrated a novel interaction between semen and the microenvironment in the female reproductive tract . It uncovered a post-ejaculated semen liquefaction process that occurs inside the female reproductive tract , a topic that has not yet been explored . The conclusion of the experiments proposed that abnormal E2 signaling in the female reproductive tract leads to a semen liquefaction defect associated with defective SEMG cleavage and sperm transport and may be a possible cause for some cases of infertility . We proposed the explanation that the semen liquefaction defect could be caused by diminished KLK activity in female mice , however , this hypothesis should first be tested in multiple Klk knockout mouse models . This discovery regarding post-ejaculated liquefaction is crucial for advancing the field of reproductive medicine and can lead to potential diagnostic tools for unexplained infertility cases and to developing a novel contraception technology to entrap sperm .
Animals were handled according to Washington State University ( WSU ) Animal Care and Use Committee guidelines and in compliance with WSU-approved animal protocols #4702 and 4735 . Adult female mice ( 7 to 12 weeks old ) with a selective deletion of ESR1 in the epithelial cells of the female reproductive tract ( Wnt7aCre/+;Esr1f/f ) [19] and their control littermates ( Esr1f/f ) were used in the experiments . The genotyping of the animals was carried out as previously described [19] . The deletion of ESR1 was confirmed using IHC analysis ( details described below ) . Female mice were singly housed and bred overnight with a wild-type ( WT ) C57B6/J male . If a copulatory plug was observed the next morning at 8 a . m . , the female was designated as 0 . 5 days post coitus ( dpc ) . For the microarray analysis , the animals were ovariectomized , randomly divided into groups , and treated with the vehicle control ( sesame oil ) or 17β-estradiol ( E2 at a dose of 0 . 25 μg/mouse ) for 2 and 24 h as described previously [24] . Microarray data in this publication were deposited in NCBI's Gene Expression Omnibus and are accessible through GEO Series accession number GSE23072 ( WT samples ) and GSE53812 ( Wnt7aCre/+;Esr1f/f samples ) . The differentially expressed genes and statistical analysis for the microarray dataset were analyzed using Partek Genomics Suite ( version 6 . 6Beta 6 . 11 . 1115 , St . Louis , MO ) as described previously [24] . At the time of tissue collection , animals were euthanized using CO2 asphyxiation with cervical dislocation . Uterine diameters were measured using a ruler before tissue dissection . Semen was collected from the uteri and liquefaction time was determined by recording the time used to fill a 25 μL capillary tube using an adapted method as previously reported [54] . One uterine horn from each animal was snap frozen and stored at -80°C for RNA and protein extraction . Contralateral horns were fixed in 10% phosphate-buffered formalin for histological analysis . Formalin-fixed uterine tissues were dehydrated and embedded in paraffin . The tissues were cross-sectioned at 5 microns and stained with hematoxylin and eosin ( H&E ) using a standard histological protocol . For IHC staining , paraffin sections were rehydrated and the antigen was retrieved using citrate buffer in the decloaking chamber ( BioCare Medical , Concord , CA ) . Endogenous peroxidase activity was blocked using 3% H2O2 . The uterine sections were blocked with 10% normal horse serum ( NHS ) diluted in automation buffer ( 50 mM Tris , 20 mM NaCl , 0 . 05% Tween-20 ) for 1 h at room temperature , then incubated with the primary antibodies against ESR1 ( 1:200 , # MA5-13191 , ThermoFisher Scientific , Carlsbad , CA ) or Ki67 ( 1:200 , #550609 , BD Pharminogen , San Jose , CA ) in 10% NHS for 1 h at room temperature . Mouse IgG was used in place of primary antibodies for a negative control . The secondary antibody ( 1:1000 biotinylated horse anti-mouse , Vector Laboratories , Burlingame , CA ) was applied to the sections for 30 min at room temperature . Vectastain RTU Elite and ImmPact kits ( Vector Laboratories ) were used according to the manufacturer’s protocols to detect the positive signals . Tissues were counterstained with hematoxylin , dehydrated , and coverslipped with Permount . The presence of collagen in the uterine content was determined using Masson’s Trichrome staining kit . Blue staining indicates the presence of collagen and red indicates cytoplasm . Quantification of Ki67 IHC was determined using ImageJ version 2 . 0 . 0-rc-43/1 . 51e ( imagej . nih . gov ) with Cell Counter Tool Plugins as previously described [24] . Three images from each animal were captured using the Leica Application Suite ( Leica Microsystems Inc . , Buffalo Grove , IL ) . The number of Ki67 positive cells was counted and calculated as the percentage of positive cells per each cell type ( luminal epithelial , glandular epithelial , and stromal cells ) in each image . Semen was collected from the uteri of Esr1f/f and Wnt7aCre/+;Esr1f/f females approximately 8 h after mating . The female reproductive tract including the vagina was collected . The area between the uterus and cervix was cut open into a 1 . 5 mL microcentrifuge tube in order to collect the semen . The uterine horns were squeezed using toothless forceps from the ovarian end to the vaginal end to extract semen from the uterine lumen . The tubes were spun down briefly and the uterine fluid volume was determined . The semen was then diluted 1:200 in diH2O and the number of sperm was counted using a hemocytometer . The total sperm number was calculated and normalized to the total fluid volume collected . Simultaneously , another 5 μL of fresh semen was dropped onto a glass slide and covered with a coverslip . Bright field video images of sperm motility were recorded with the 100x objective lens ( 4–8 different microscopic fields/sample ) using a DMi8 Leica Microscope ( Leica Microsystems ) . The sperm motility within each microscopic field was sorted into four categories: immotile , non-progressive , slow progressive , and rapid progressive , and the percentage of sperm in each category was calculated . The total number of sperm evaluated was 339 for Esr1f/f and 414 for Wnt7aCre/+;Esr1f/f groups ( n = 3 females/genotype ) . The time between animal euthanasia and sperm video recording was within 5 min to preserve the maximal sperm viability . The sperm density was determined from H&E stained tissues collected from 0 . 5 dpc uteri and observed with the 20x objective lens . The genotype of the animals was blinded from the observer . The number of sperm within the uterine lumen was counted manually using winDRP software ( v1 . 6 . 4 ) [55] , the total area was measured and used to calculate the sperm density per mm2 . Data were collected from 7 Esr1f/f and 10 Wnt7aCre/+;Esr1f/f animals ( 1 image per animal ) . Adult female C57BL6/J mice ( 7–12 weeks old ) were used . The estrus stage of the estrous cycle was determined using a vaginal smear . At 5 p . m . on the determined day of estrus , females were administered 15 μL of saline pH 5 . 5 or 15 μL of AEBSF ( 4- ( 2-Aminoethyl ) benzenesulfonyl fluoride hydrochloride , Amresco , Dallas , TX ) at a dose of 300 μg/mouse through transcervical treatment using a Non Surgical Embryo Transfer ( NSET ) device [56] . The 300 μg dose of AEBSF was selected based on the demonstration of Sun et al . that a single intraluminal injection effectively inhibits embryo-uterine implantation [57] . The females were immediately housed with a proven male breeder overnight . The next morning , presence of a copulatory plug was designated as 0 . 5 dpc . The animals were euthanized at 8 a . m . and the uteri were collected as described above . The oviducts were flushed with 100 μL of diH2O onto the glass slide . The total number of sperm in the oviduct was counted manually under a brightfield microscope with the 20x objective lens . RNA was extracted from the uteri or human cell lines using RiboZol ME Reagent ( Amresco , Solon , OH ) according to the manufacturer’s protocol . A total of 1 μg RNA was used as a template for the reverse transcriptase reaction according to the manufacturer’s protocol ( qScript cDNA SuperMix , QuantaBio , Beverly , MA ) . The cDNA products were diluted at 1:10 in nuclease-free H2O . Diluted cDNA ( 1 μL ) was used as a template for the PCR reaction ( PerfeCTa SYBR Green FastMix , QuantaBio ) according to the manufacturer’s protocol . PCR reactions were run and raw data were recorded in a 7500 Fast Real-Time PCR System ( Applied Biosystems , ThermoFisher ) . Expression values in uterine samples were calculated as fold change normalized to ribosomal protein L7 ( Rpl7 ) expression , relative to the vehicle or Esr1f/f . Expression of human KLKs , SPINKs , and ESR1 was calculated relative to RPL5 expression . The primer sequences used in the experiments are listed in S2 Table . Protein was extracted from uterine tissues using T-PER tissue protein extraction reagent ( ThermoFisher ) with Halt protease and phosphatase inhibitors ( ThermoFisher ) . The protein concentration was determined using a BCA protein assay ( ThermoFisher ) . A total of 20 μg protein was loaded into each lane of a 10% acrylamide gel . The protein gels were transferred to a nitrocellulose membrane using Trans-Blot Turbo ( Bio-Rad Laboratories Inc . , Hercules , CA ) . To visualize the equal protein loading and transfer , the membranes were incubated with 0 . 1% Ponceau S in 1% acetic acid . Membranes were then blocked with 5% non-fat dry milk in Tris-buffered saline with 0 . 1% tween-20 ( TBST ) for 1 h at room temperature . The membranes were then incubated with primary antibodies ( 1:1000 of KLK1B5 #MBS175442 , MyBioSource , San Diego , CA; 1:1000 of SERPINH1 ( or HSP47 ) , # MAB9166 , R&D Systems , Minneapolis , MN; 1:2000 of β-ACTIN #SC-47778 , Santa Cruz Biotechnology , Inc . , Dallas , TX , 1:1000 of SEMG1 #ab139405 , Abcam , Cambridge , MA ) in 5% milk TBST at 4°C overnight . The secondary antibodies were incubated for 1 h at room temperature with a dilution of 1:5000 in 5% milk TBST . The blotting was detected using Amersham ECL Select ( GE Healthcare Bio-Sciences , Pittsburgh , PA ) . The chemiluminescent signals were detected and images were captured using ChemiDoc MP System ( Bio-Rad ) . Immortalized human ectocervical ( hEct1 ) and endocervical ( hEnd1 ) cells were purchased from ATCC ( Manassas , VA ) . Human endometrial cancer ( Ishikawa ) cells derived from the 3H12 clone [58] and human prostate cancer ( LNCaP ) cells ( ATCC ) were used as controls for the experiments . Immortalized hEct1 and hEnd1 cells were cultured in keratinocyteserum-free medium ( ThermoFisher ) with 0 . 1 ng/mL human recombinant epidermal growth factor , 0 . 05 mg/mL bovine pituitary extract , and 0 . 4 mM calcium chloride ( complete KSFM ) at 37°C with 5% CO2 . Ishikawa and LNCaP cells were cultured in RMPI medium ( Hyclone , South Logan , UT ) supplemented with 10% fetal bovine serum ( Gemini Bio-Products Inc . , Woodland , CA ) , 100 U/mL penicillin , and 100 μg/mL streptomycin . Cells were cultured to 80–90% confluence , washed with phosphate buffered saline ( PBS ) , and harvested using 0 . 25% trypsin-EDTA ( Sigma , St . Louis , MO ) . RNA was extracted using RiboZol ME as described above . For the analysis of endogenous gene expression in hEct1 cells in response to E2 , the cells were plated at a density of 1 . 33x106 cells/mL in a 6-well plate containing complete KSFM media . Cells were grown to 80–90% confluence , then treated with vehicle ( 0 . 1% ethanol ) or E2 ( 1 and 10 nM ) in the presence or absence of ICI 182 , 780 ( ICI; 1 μM ) for another 24 h . Cells were then harvested and RNA was extracted using RiboZol ME as indicated above . Data are represented as mean±SEM and analyzed using GraphPad Prism version 6 . 0 for Mac OS X . Data were evaluated for statistically significant differences ( p<0 . 05 ) using an unpaired student t-test , unless otherwise indicated .
|
Semen liquefaction has been considered to be solely modulated by prostate-derived kallikrein-related peptidases ( KLKs ) , especially KLK3 ( or prostate specific antigen ) . However , our research demonstrated that female mice lacking estrogen receptor alpha ( ERα ) in the uterine epithelial cells had a drastic decrease in Klk transcripts and semen from fertile males fails to liquefy within the uteri of these females . Therefore , our results provide a novel aspect that , due to an interplay between semen and female reproductive tract secretions , the physiology of semen liquefaction is more complicated than previously assumed . This information will advance research on semen liquefaction in the female reproductive tract , an area that has never been explored , and could lead to the development of diagnostic tools for unexplained infertility cases and non-invasive contraception technologies .
|
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"and",
"methods"
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2017
|
Crucial role of estrogen for the mammalian female in regulating semen coagulation and liquefaction in vivo
|
Early in an epidemic , high densities of susceptible hosts select for relatively high parasite virulence; later in the epidemic , lower susceptible densities select for lower virulence . Thus over the course of a typical epidemic the average virulence of parasite strains increases initially , peaks partway through the epidemic , then declines again . However , precise quantitative outcomes , such as the peak virulence reached and its timing , may depend sensitively on epidemiological details . Fraser et al . proposed a model for the eco-evolutionary dynamics of HIV that incorporates the tradeoffs between transmission and virulence ( mediated by set-point viral load , SPVL ) and their heritability between hosts . Their model used implicit equations to capture the effects of partnership dynamics that are at the core of epidemics of sexually transmitted diseases . Our models combine HIV virulence tradeoffs with a range of contact models , explicitly modeling partnership formation and dissolution and allowing for individuals to transmit disease outside of partnerships . We assess summary statistics such as the peak virulence ( corresponding to the maximum value of population mean log10 SPVL achieved throughout the epidemic ) across models for a range of parameters applicable to the HIV epidemic in sub-Saharan Africa . Although virulence trajectories are broadly similar across models , the timing and magnitude of the virulence peak vary considerably . Previously developed implicit models predicted lower virulence and slower progression at the peak ( a maximum of 3 . 5 log10 SPVL ) compared both to more realistic models and to simple random-mixing models with no partnership structure at all ( both with a maximum of ≈ 4 . 7 log10 SPVL ) . In this range of models , the simplest random-mixing structure best approximates the most realistic model; this surprising outcome occurs because the dominance of extra-pair contact in the realistic model swamps the effects of partnership structure .
The evolution of pathogen virulence ( the harm done to the pathogen’s host ) has both theoretical and , potentially , practical importance . Evolutionary theory suggests that pathogens with higher reproduction numbers ( R 0 ) —the number of secondary infections caused by a single infected host over the course of its infectious period—will increase in prevalence relative to strains with lower reproductive ratios . Pathogens can increase their reproduction numbers either by increasing their transmission rate , the rate ( per infected host ) at which they infect new hosts , or by decreasing their clearance or disease-induced mortality rate , the rate at which hosts recover or die from disease . The trade-off theory [1] postulates that transmission and disease-induced mortality rates are both driven by the rate at which the pathogen exploits host resources for within-host reproduction , and that pathogen evolution will thus strike a balance between the pathogen’s rate of transmission to new hosts and its rate of killing its host ( or of provoking the host’s immune system to eliminate it ) . Some biologists have criticized the tradeoff theory [2 , 3] , but others have successfully applied it to a variety of host-pathogen systems [4–7] . Fraser et al . have showed that HIV appears to satisfy the prerequisites of the tradeoff theory . The set-point viral load ( SPVL: i . e . , the characteristic virus load measured in blood during the intermediate stage of infection ) is a measurable proxy for the rate of HIV within-host reproduction . Higher viral loads are correlated with faster progression to AIDS ( higher virulence ) . Studies of discordant partnerships—stable sexual partnerships with one infected and one uninfected partner—have shown that SPVL is ( 1 ) positively correlated with transmission ( people with higher SPVL transmit HIV to their uninfected partners sooner ) and ( 2 ) heritable ( when the uninfected partner does become infected , their SPVL is similar to their originally infected partner’s ) . Furthermore , the rate of increase in transmission has a decreasing slope as progression time decreases , fulfilling the requirements of the tradeoff theory [8] . Subsequent studies [9–11] used these data to parameterize mechanistic models of HIV virulence evolution , suggesting that HIV invading a novel population would initially evolve increased virulence , peaking after approximately 100-200 years and then declining slightly to a long-term stable virulence level . The work of Shirreff et al . [9] , and particularly the predicted transient peak in HIV virulence midway through the epidemic , highlights the importance of interactions between epidemiological and evolutionary factors [12 , 13] . However , despite these studies’ attention to detail at the individual or physiological level , the population-level contact structures used in these models are relatively simple . Many existing models of HIV eco-evolutionary dynamics use implicit models that incorporate the average effects of within-couple sexual contact—without representing the explicit dynamics of partnership formation and dissolution or accounting for extra-pair contact; agent-based formulations are more realistic , but can make it difficult to tease apart the reasons behind particular epidemic phenomena . Here we explore the effects of incorporating explicit contact structure in eco-evolutionary models . Because our main goal is to explore how conclusions about virulence evolution depend on the way in which contact structure is modeled , we consider a series of models with increasing levels of complexity in the contact structure , but simplify some of the other epidemiological processes ( such as the within-host life history of HIV ) . We evaluate our models across a wide range of parameters , using a Latin hypercube design; for each model run , we compute a set of metrics that summarize the evolutionary trajectory of SPVL over the course of the epidemic .
Our models explicitly track the evolution of the distribution of log10 SPVL ( which we denote as α ) rather than the rate of progression to AIDS itself ( hereafter we use “virulence” to denote log10 SPVL ) . We use a single-stage model of HIV that assumes constant infectivity over the course of an exponentially distributed infectious period . This assumption contrasts with Shirreff et al . ’s previous model which explicitly tracked three stages of HIV infection ( primary , asymptomatic , and AIDS ) and used a more realistic Weibull-distributed infectious period . We show below that our results are not overly sensitive to this simplification , although it could conceivably affect our conclusions about the evolution of virulence ( e . g . , Kretzschmar and Dietz [14] show that pair formation dynamics and multiple stages of infectivity have interactive effects on R 0 ) . In Shirreff et al . ’s model , the transmission rate and infection duration depend on virus load only during the asymptomatic stage . In order to adapt their parameterization to our single-stage model , we used their parameters to compute the SPVL-dependent transmission rate and duration during the asymptomatic stage and then derived the overall duration of the infectious period as the sum of the three stage durations and the average transmission rate as the duration-weighted average of the three stage-specific transmission rates . Thus the within-couple transmission rate , β ( see “Contact Structure” below ) , for our models is given by: β ( α ) = D P β P + D A ( α ) β A ( α ) + D D β D D P + D A ( α ) + D D , ( 1 ) where the duration of infection ( DP and DD ) and rate of transmission ( βP and βD ) of the Primary and Disease stages of infection are independent of the host’s SPVL ( Table 1 gives definitions , units , and values for all parameters ) . Following Shirreff et al . , the duration of infection ( DA ) and rate of transmission ( βA ) for the Asymptomatic stage are Hill functions of the SPVL: D A ( α ) = D max D 50 D k V ( α ) D k + D 50 D k , β A ( α ) = β max V ( α ) β k V ( α ) β k + β 50 β k , ( 2 ) where V ( α ) = 10α . In models that allow extra-pair contact , the uncoupled and extra-couple transmission rates ( i . e . , the rates of transmission among people outside of a stable partnership , or between people inside of a stable partnership and people other than their partner ) are scaled by multiplying the within-couple transmission rate β by the contact ratios cu/cw and ce/cw ( see S1 Appendix ) . Over the course of infection , mutation occurs within the host . However , we follow Shirreff et al . in assuming that SPVL of the strain transmitted by an infected individual is determined by the SPVL at the time of infection and is not further affected by within-host mutation . Instead , the mutational effect is modeled as occurring in a single step at the time of transmission . First , the distribution of log10 SPVL is discretized into a vector: α i = α min + ( α max - α min ) i - 1 n - 1 i = 1 , 2 , 3 , … n . ( 3 ) We have experimented with varying degrees of discretization in the strain distribution ( i . e . , values of n ) ; in our model runs comparing results with Shirreff et al . [9] ( Fig 1 ) we use n = 51 ( i . e . a bin width of 0 . 1 log10 SPVL for α ) , but reducing n to 21 ( bin width = 0 . 25 log10 SPVL ) makes little difference; we use this coarser grid for all other simulations reported . We then construct an n × n mutational matrix , M—which is multiplied with the transmission term—so that Mij is the probability that a newly infected individual will have log10 SPVL of αj given that their infected partner has log10 SPVL of αi . Finally , the probabilities are normalized so that each row sums to 1: M i j = Φ ( α j + d / 2 ; i ) - Φ ( α j - d / 2 ; i ) Φ ( α max + d / 2 ; i ) - Φ ( α min - d / 2 ; i ) , ( 4 ) where Φ ( x;i ) is the Gaussian cumulative distribution function with mean αi and variance of σ M 2 , and d = ( αmax − αmin ) / ( n − 1 ) . Unlike Shirreff et al . , who allowed for variation in the expressed phenotype ( SPVL ) of each genotype , we use a one-to-one genotype-phenotype map . Thus there is a single value for within-couple transmission rate and for progression rate corresponding to each SPVL compartment in the model: β i = β ( α i ) , λ i = 1 D P + D A ( α i ) + D D . ( 5 ) We developed seven multi-strain evolutionary models covering a gamut including Champredon et al . ’s relatively realistic [15] and Shirreff et al . ’s relatively simple [9] contact structures , each of which is based on different assumptions regarding contact structure and partnership dynamics . Specifically , we focus on the effects of the assumptions of ( 1 ) instantaneous vs . non-instantaneous partnership formation; ( 2 ) zero vs . positive extra-pair sexual contact and transmission; and ( 3 ) homogeneous vs . heterogeneous levels of sexual activity on the evolution of mean log10 SPVL . Our first four models ( Fig 2 ) explicitly consider partnership dynamics [15] . The first ( Fig 2d ) assumes non-instantaneous partnership formation ( i . e . individuals spend some time uncoupled , outside of partnerships ) and consists of five states that are classified by infection status and partnership status; single ( uncoupled ) susceptible individuals ( S ) , single infected individuals ( I ) , concordant negative ( susceptible-susceptible ) couples ( SS ) , discordant ( susceptible-infected ) couples ( SI ) , and concordant positive ( infected-infected ) couples ( II ) . The rates of pair formation are based on the numbers of uncoupled susceptible and infected individuals and the pair-formation rate; partnerships can either dissolve into singletons or be transformed into other types of partnerships by infection of one partner . This model also includes extra-pair contact with both uncoupled individuals and individuals in other partnerships ( we denote it “pairform+epc” ) , so that susceptible uncoupled individuals and susceptible partners in any type of partnership can be infected by infected uncoupled individuals or infected partners in any type of partnership . Specifically , single individuals ( S and I ) form partnerships at a per capita rate ρ , and partnerships dissolve at a rate c . Infected individuals in a discordant partnership infect their susceptible partner at a rate β ( within-couple transmission rate ) and susceptible individuals outside the partnership at a rate ce ( extra-couple transmission rate ) . Infected individuals in seropositive ( II ) partnerships can also infect any susceptible individual at rate ce . Likewise , single infected individuals ( I ) can infect any susceptible individuals ( single individuals S , or susceptible members of SS or SI partnerships ) at a rate cu through uncoupled mixing . This parameterization follows Champredon et al . ; we have adapted some of the details of their model to a multi-strain scenario , so that we track ( for example ) a matrix IIij that records the number of concordant , HIV-positive partnerships in which the two partners have log10 SPVL of αi and αj . Our second model ( “pairform” , Fig 2c ) only considers within-couple transmission , in which case infection can only occur within a serodiscordant partnership; that is , we set ce and cu to zero . Our third and fourth models , which are intended to bridge the gap between models with fully explicit pair-formation dynamics and the simpler , implicit models used by Shirreff et al . [9] , assume instantaneous partnership formation ( “instswitch” ) . The compartmental structure thus omits the single states S and I , comprising only the three partnered states: SS , SI , and II . Like the first two models , this pair of models differs in their inclusion of extra-pair contact: the third model ( “instswitch+epc” , Fig 2b ) includes extra-pair contact ( now only with individuals in other partnerships , since uncoupled individuals do not exist in this model ) while the fourth ( “instswitch” , Fig 2a ) only considers within-couple transmission . Although these models can also be implemented by setting the partnership formation rate of the explicit partnership models to a high value ( we have tested that both methods in fact produce same results ) , we model instantaneous partnership formation models independently so that scaling the partnership formation rate during model calibration ( see Simulation runs below ) does not affect the eco-evolutionary dynamics . The fifth and sixth models represent extreme simplifications of sexual partnership dynamics . The fifth ( “implicit” ) is an implicit serial monogamy model based on the epidemiological model used by Shirreff et al . [9] . It is a random-mixing model that explicitly tracks only the total number of susceptible and infected individuals . However , to reflect the effect of partnership structure , it uses an adjusted transmission rate derived from an approximation of the basic reproduction number of a serial monogamy model with instantaneous pair formation [16] . The sixth model ( “random” ) is a simple random-mixing model . Lastly , we incorporated heterogeneity in sexual activity into the models . Individuals are divided into different risk groups based on their level of sexual activity; we scale all aspects of sexual activity , assuming that sexual activity level in both within- and extra-couple contacts is directly proportional to number of non-cohabiting ( extra-couple and uncoupled ) partners per year [17] ( see S1 Appendix for full model details ) . We assume random activity-weighted mixing between risk groups [18] . ( In the main text we focus on the model with non-instantaneous pair formation , extra-pair contact ( “pairform+epc” ) and heterogeneous sexual activity , which we denote as “hetero”; Fig D in S2 Appendix presents results on the effect of adding heterogeneity to other model variants . ) While this model lacks some important elements , such as age-structured mixing patterns , needed for realistic models of HIV transmission in sub-Saharan Africa , it represents a first step toward assessing the effects of epidemiological complexity . As even the models shown here push the limits of compartmental-based models ( the heterogeneity model comprises 24530 coupled ordinary differential equations ) , adding further complexity will probably require a shift to an agent-based model framework , as well as considerable effort in model calibration [10 , 19 , 20] . For simplicity ( and following Shirreff et al . ) , all of our base models use an SIS ( susceptible-infected-susceptible ) formulation , where there is no natural mortality ( and no explicit introduction of newly sexually active individuals into the susceptible pool ) . Individuals who die from AIDS are immediately replaced by an individual in the uncoupled-susceptible compartment . While admittedly unrealistic , this approach is reasonable given that ( 1 ) the natural mortality rate is low relative to the epidemiological dynamics and ( 2 ) the infectious period is long , so that the overall rates of disease-induced mortality and recruitment of newly sexually active individuals would roughly balance . To check the importance of this assumption , we also built models with vital dynamics where individuals dying from AIDS are removed from the population , with constant recruitment rates and constant low per capita natural mortality rates; this additional structure had only minor effects on the results . Choosing the initial conditions for the simulations is challenging . In many modeling studies , researchers are primarily interested in equilibria ( or other long-term dynamical attractors such as limit cycles ) and are exploring models that have a single stable attractor , so initial conditions can be ignored as long as we run models for long enough . In eco-evolutionary dynamics , however , the initial conditions do affect our conclusions . We have no empirical information that would justify a particular choice of the fraction infected and the mean and variance of the distribution of SPVL at the point when the pandemic strain of HIV-1 entered the human population; in any case , the level of realism of our model does not support such a detailed consideration of the early dynamics of HIV . In most cases , we started with an initial log10 SPVL of 3 . 0 , to match the value used by Shirreff et al . [9] . Shirreff et al . use an initial prevalence I ( 0 ) = 10−3; because we calibrated parameters based on the initial epidemic growth rate ( see “Simulation runs” below ) , we set I ( 0 ) to 10−4 for most runs to ensure that the exponential growth phase lasted long enough for reliable estimation of the initial growth rate . S1 Appendix provides further details on initial conditions , such as the initial distribution of SPVL around the mean and the distribution of initial infected density across single people and different partnership types . We ran most of our models across a wide range of parameters , as described in the next ( Latin hypercube sampling ) section . In several cases , however , we inspected only a few parameter sets , to qualitatively assess the sensitivity of the models to initial conditions or to model structure . In particular , we tested model sensitivity to the initial prevalence , I ( 0 ) , and initial mean log10 SPVL , α ( 0 ) , using baseline values of all parameters ( Table 1 ) . Using baseline parameter values , we also ran all four basic model structures ( Fig 2 ) with vital dynamics and with heterogeneity in sexual contact , to assess the sensitivity of our results to these phenomena . Despite considerable effort [15 , 16] , the parameters determining the rate and structure of sexual partnership change and contact are still very uncertain; this uncertainty led Champredon et al . [15] to adopt a Latin hypercube sampling ( LHS ) strategy [21] that evaluates model outcomes over a range of parameter values . In order to make sure that our comparisons among models apply across the entire space of reasonable parameter values , and in order to evaluate the differential sensitivity of different model structures to parameter values , we follow a similar protocol and perform LHS over a parameter set including both the early- and late-stage transmission and duration parameters ( βP , DP , βD , DD ) and contact/partnership parameters ( ρ , c , cu/cw , and ce/cw ) . For the heterogeneity model , the mean and squared coefficient of variation ( CV ) for the number of non-cohabiting partners are sampled as well . We do not allow for uncertainty in parameters that are directly related to the evolutionary process ( βmax , β50 , βk , Dmax , D50 , Dk , σM ) , instead using Shirreff et al . ’s point estimates throughout [9] . Latin hypercube sampling is done as in Champredon et al . [15] . For each parameter , z , its range is divided into N = 1000 equal intervals on a log scale: z i = exp log ( z min ) + [log ( z max ) - log ( z min ) ] i - 1 N - 1 i = 1 , 2 , 3 , … , N . ( 6 ) Random permutations of these vectors form columns in a sample parameter matrix; each row contains a different parameter set that is used for one simulation run . Table 1 gives the ranges of the model parameters used for LHS . Ranges of parameters controlling contact and partnership dynamics ( ρ , c , and ce/cw ) are taken from Champredon et al . [15] , whereas those controlling infection ( βP , DP , βD , and DD ) are taken from Hollingsworth et al . [16] . The remaining parameter values are taken from Shirreff et al . [9] . One new parameter in our model , the ratio of uncoupled to within-couple transmission cu/cw , is needed to more flexibly contrast uncoupled and extra-couple transmission dynamics within multi-strain models ( see S1 Appendix ) . Since it appears neither in either Shirreff et al . nor Champredon et al . ’s models , we need to pick a reasonable range for it . Champredon et al . [15] assume that the effective within-couple contact rate and effective uncoupled contact rate have the same range of 0 . 05—0 . 25 . Given Champredon et al . ’s parameter range , the possible maximum and minimum values of cu/cw are 5 and 1/5 . Therefore , we use 1/5-5 as the range for the parameter cu/cw . Although this adds more uncertainty to the parameter cu—Champredon et al . ’s range implies a 5-fold difference whereas ours gives a 25-fold difference—we consider the wider range appropriate , as little is known about the uncoupled transmission rate . Two parameters , mean and the squared coefficient of variation ( CV ) of number of non-cohabiting partners , are sampled for heterogeneity in sexual activity . To allow for a wide range of uncertainty , range for the mean number of non-cohabiting partners was taken from unmarried men , as that was the group with the largest variability [17] . Omori et al . [17] give a very wide range for the coefficient of variation ( ≈ 0—20 , corresponding to squared CV range of 0-400 ) : we narrowed this range for CV2 to 0 . 01-100 . At the bottom end of the range , an observation that a group behaves perfectly homogeneously ( CV = 0 ) is likely to be a sampling artifact; at the upper end , the estimate is also likely to be noisy because of the low mean value among married females ( who have the largest range of CV ) . We assume that the number of non-cohabiting partners follows a Gamma distribution . One of the hardest parts of model comparison is finding parameter sets that are commensurate across radically different model structures . For the most part , our models are too complex to derive analytical correspondences among the parameters for different models . Given a numerical criterion , such as r ( initial exponential growth rate ) or R 0 ( intrinsic reproductive number ) , we can adjust one or more parameters by brute force to ensure that all of the models match according to that criterion . While R 0 is often considered the most fundamental property of an epidemic , and might thus seem to be a natural matching criterion , here we focus on matching the initial growth rate r for several reasons . First , our primary interest is in the transient evolutionary dynamics of virulence , which are more strongly affected by r than R 0 . Second , r is more directly observable in real epidemics; r can be estimated by fitting an exponential curve to the initial incidence or prevalence curves [22] , while R 0 typically requires either ( 1 ) knowledge of all epidemic parameters or ( 2 ) calculations based on r and knowledge of the serial interval or generation interval of the disease [23] . Thus , we scale parameters so that every run has the same initial exponential growth rate in disease prevalence . In order to allow for all models to have equal initial exponential growth rate , r , we need to pick a parameter , s , such that lims→0 r ( s ) = 0 and lims→∞ r ( s ) = ∞ . As adjusting either partnership change rate ( i . e . partnership formation and dissolution rate ) or transmission rate fails this requirement for some of our models , we scaled both partnership change rate and transmission rate by the same factor γ: βadj = γ βbase , cadj = γ cbase , ρadj = γ ρbase . Since transmission rate is scaled by γ , uncoupled and extra-couple transmission rates are adjusted as well . For the instantaneous-switching and implicit models , none of which track single individuals , only the transmission rate and partnership dissolution rate ( in this case equivalent to the partnership change rate ) are adjusted . We run each model for each of 1000 parameter sets chosen by Latin hypercube sampling , with fixed starting conditions of mean log10 SPVL of 3 . 0 , standard deviation of log10 SPVL of 0 . 2 , and epidemic size of 10−4 . After each run , the initial exponential growth rate is calculated . Then the parameters are scaled as described above so that the initial exponential growth rate is scaled to 0 . 04 year−1 , a value that approximates the growth rates of Shirreff et al . ’s original models . When calibrating , we run each model for only 500 years ( full simulations are run for 4000 years ) , which is always long enough to capture the exponential growth phase of the model . We use a 4/5 order Runge-Kutta method ( ode45 from the deSolve package [24] ) for all simulations . ( For the heterogeneous model , approximately 10% of the samples failed due to numerical instability; we discarded these runs . ) For each model we derive the following summary statistics: maximum population mean log10 SPVL; time at which this maximum occurs ( corresponding to peak virulence—this is also the time at which the maximum rate of progression and maximum transmission rate occur ) ; equilibrium log10 SPVL; and minimum expected time to progression . Minimum expected progression time is obtained by applying the Hill function ( eq 2 ) to the maximum mean log10 SPVL of each run . Equilibrium log10 SPVL is calculated after 4000 years of simulated time . Although most simulations reach equilibrium much earlier than 4000 years , we set this very long time horizon because a small subset of the simulation runs show very slow evolution rates . Knowing the peak log10 SPVL , timing of the peak log10 SPVL/peak virulence , and equilibrium log10 SPVL provides sufficient detail to identify the overall shape of the virulence trajectory . In particular , knowing the timing of the peak virulence ( how many years into the epidemic the virulence peaks ) can help epidemiologists guess whether the virulence of an emerging pathogen is likely ( 1 ) to peak early , possibly even before the pathogen is detected spreading in the population , and decline over the remaining course of the epidemic; ( 2 ) to increase , peak , and decline over the foreseeable future; or ( 3 ) to increase very slowly , peaking only in the far future . To the extent that our simplistic model for HIV reflects reality , we would take the peak time of 150-300 years ( Fig 1c ) to mean that , in the absence of treatment , the epidemic would probably still be increasing in virulence .
Our simplifications of Shirreff et al . ’s model [9] reproduce its qualitative behaviour—in particular , its predictions of virulence dynamics—reasonably well . As we calibrate the parameters to achieve initial epidemic growth rates r ranging from 0 . 042 year−1 to 0 . 084 year−1 ( the former value matching the initial rate of increase in prevalence in Shirreff et al . ’s full model ) the initial trajectory of increasing virulence brackets the rate from the original model ( Fig 1a ) . For matching initial growth rates ( r = 0 . 042 ) the peak log10 SPVL occurs at the same time ( ≈ 200 years ) but the peak virulence is lower than Shirreff’s ( ≈ 4 . 3 vs . ≈ 4 . 6 log10 SPVL ) , as is equilibrium virulence ( ≈ 4 . 25 vs . ≈ 4 . 5 log10 SPVL ) . Changing the initial infectious density ( I ( 0 ) ) has little effect on the virulence trajectory . Decreasing I ( 0 ) makes SPVL peak slightly later and higher , because it allows a longer exponential-growth phase before the transition to endemic dynamics ( Fig 1b ) . Decreasing the initial SPVL also leads to progressively later , higher peaks in SPVL ( Fig 1c ) . In this case the delay in the peak is more pronounced than for low I ( 0 ) , because the rate of SPVL increase is eventually limited by the mutation rate . The peak SPVL is actually larger for a lower starting SPVL , presumably because lower SPVL also allows for a longer epidemic phase . However , the peaks are similar across the entire range of initial conditions , because even in the most limited ( high-I ( 0 ) , high-α ( 0 ) ) cases HIV can evolve close to its optimal growth-phase SPVL . Across the entire range of parameters covered by the Latin hypercube samples , all of our models produce qualitatively similar virulence trajectories , which we quantify in terms of population mean log10 SPVL ( Fig 3: higher population mean log10 SPVL corresponds to higher virulence ) . Although the speed of virulence evolution varies , leading to wide variation in the peak log10 SPVL ( ranging from 3 to 5 . 5 ) because HIV can evolve farther toward its growth-phase optimum before the transition to the endemic phase , virulence peaks between 200 and 300 years in all models . Our chosen summary statistics ( peak time , maximum mean log10 SPVL , equilibrium mean log10 SPVL , and minimum mean progression time ) all vary considerably across models ( Fig 4 ) . We first consider the models of intermediate realism: implicit , instantaneous-switching with and without extra-pair contact , and pair formation without extra-pair contact . Some parameter sets for these models lead to low equilibrium virulence ( 2 . 3-3 log10 SPVL ) . For these data sets , virulence may either increase from its initial value , reaching an early peak ( ≈ 200 years ) between 3 and 4 log10 SPVL and then declining to a lower equilibrium value , or in extreme cases virulence may decline immediately , leading to a peak virulence ( as we have defined it ) equal to the starting value of α ( 0 ) = 3 log10 SPVL at t = 0 ( Fig 5 ) . At the opposite extreme , parameter sets that produce high equilibrium virulence ( 4 . 7 log10 SPVL ) also produce late peaks ( > 200 years ) and high peak virulence ( 5 . 6 log10 SPVL ) . The most striking aspect of the univariate comparisons in Fig 4 ( and the bivariate comparisons in Fig 5 ) , is the similarity between the results of the least ( random-mixing ) and the most complex ( pair formation with extra-pair contact and pairform+epc with heterogeneity ) models . The random-mixing model has the lowest variability , because it is unaffected by uncertainty in pair formation and extra-pair contact parameters , but otherwise the virulence dynamics of these three extreme models are remarkably similar . This phenomenon is driven by the strong effects of extra-pair contact in the model with explicit pair formation and extra-pair contact ( “pairform+epc” in Figs 3–6 ) . When individuals spend time uncoupled between partnerships , and when these single individuals can transmit disease to coupled individuals , the resulting unstructured mixing overwhelms the effect of structured mixing within partnerships , leading to mixing that is effectively close to random . Once unstructured mixing is strong , adding realistic heterogeneity of mixing to the model has little effect other than increasing the variability in the outcomes . The random-mixing , pairform+epc , and heterogeneous models all predict high population mean log10 SPVL at the virulence peak ( median ( 95% CI ) = 4 . 7 ( 4 . 65-4 . 79 ) , 4 . 72 ( 4 . 37-4 . 96 ) , 4 . 72 ( 4 . 09-5 . 03 ) ) . In contrast , the implicit model predicts a much lower peak log10 SPVL value: 3 . 52 ( 3-4 . 02 ) years . The random-mixing , pairform+epc , and heterogeneous models predict rapid progression to AIDS at the virulence peak ( median/95% CI = 6 . 1 ( 5 . 7-6 . 3 ) , 6 . 02 ( 5 . 04-7 . 7 ) , 6 . 03 ( 4 . 8-9 . 2 ) ) , while the implicit model predicts minimum progression times about twice as long ( 12 . 5 ( 9 . 6-15 . 6 ) years ) . The corresponding differences in mean within-couple transmission probability at the peak are even more extreme , about a fourfold difference: 0 . 249 ( 0 . 24-0 . 26 ) , 0 . 252 ( 0 . 19-0 . 28 ) , and 0 . 252 ( 0 . 15-0 . 28 ) per year for the random and pairform+epc models vs . 0 . 059 ( 0 . 02-0 . 13 ) per year for the implicit model . ( S2 Appendix presents plots showing univariate summaries of expected progression time to AIDS and transmission probability . ) Bivariate relationships ( Fig 5 ) help distinguish the results of different models with similar univariate distributions of dynamical summaries . While the relationship between equilibrium log10 SPVL and peak time is similar for all model structures ( top left panel ) , the other relationships show more variation . In particular , the implicit and pair-formation ( without extra-pair contact ) models are very similar to each other , but distinct from the other models . We still do not have a convincing explanation for this distinction; we would have expected the implicit model to be most similar to the the instantaneous-switching model without extra-pair contact , which most closely matches its underlying assumptions . However , we note that the implicit model derivation is based on defining the force of infection to match a scaled version of R 0 , and as such would be expected to match the equilibrium behaviour but not necessarily the epidemic-phase behaviour of a model with explicit partnership dynamics . Finally , the sensitivity plot ( Fig 6 ) shows the effects of each parameter on the summary statistics . The most notable difference can be observed by comparing the scaled parameters ( e . g . βP , βD , c , ρ ) with the unscaled parameters ( e . g . DP , DD , ce/cw , cu/cw , κ , μ ) ; the effects of βD and DD are not shown in Fig 6 as they show patterns almost identical to βP and DP , respectively . For the scaled parameters , the parameter ranges ( horizontal axis ) are compressed for models without extra-pair contact because these models require a large amount of parameter scaling in order to achieve the specified initial epidemic growth rate ( r = 0 . 04 ) . In contrast , models with extra-pair contact show a wide range of parameters as they can display a wide range of dynamics depending on ce/cw ( as well as cu/cw for models with uncoupled mixing ) and thus require a wide range of scaling factors to achieve the target growth rate . Parameter ranges for the random-mixing model ( especially c ) are severely compressed because this model has little flexibility . For parameters involved in partnership turnover ( c and ρ ) , the figure again shows differences between models with and without extra-pair contact . Models with extra-pair contact show a gradual decrease in peak time , maximum log10 SPVL , and equilibrium log10 SPVL with increasing turnover rates . Increases in the other parameters lead to increases in all three summary statistics . In these models , increased turnover rates diminish the effect of extra-pair contact , thus selecting for lower log10 SPVL . For models without extra-pair contact , increased turnover rates decrease the level of structured mixing ( mimicking extra-pair contact models ) , resulting in selection for higher log10 SPVL . The implicit model and the instantaneous partnership formation model show similar patterns in scaled parameters . In fact , the effect of partnership dissolution rate , c , on equilibrium log10 SPVL is almost identical in these models ( although they can be distinguished in Fig 5 ) . Lastly , increasing in transmission rates ( βP and βD ) causes the summary statistics to decrease in all models except the random-mixing model . Surprisingly , once calibration is taken into account , the unscaled parameters have little effect overall . Increase in duration ( DP , DD ) in the primary and disease stages generally decreases the equilibrium virulence , peak virulence , and peak time , although the models with uncoupled mixing and random-mixing model have high , relatively constant values with respect to these parameters . The ratio of extra-pair to within-pair contact ( ce/cw ) affects summary statistics in the instantaneous-switching +epc model , but not the pair-formation+epc model ( probably because the uncoupled individuals present in the pair-formation+epc model make extra-pair contact by coupled individuals less important ) . Similarly , increasing the ratio of uncoupled to within-pair contact , cu/cw , increases peak and equilibrium log10 SPVL and delays peak time of the pair-formation+epc model but has almost no effect on the heterogeneous model . Neither the uncoupled contact rate nor the mean ( μ ) or CV2 of the number of non-cohabiting sexual partners has much systematic effect in the heterogeneous model . Finally , incorporating additional realism to the model , i . e . combining heterogeneity with all four basic contact structures or allowing for vital dynamics rather than assuming an SIS model , leads to only small differences in the conclusions stated so far ( Fig D in S2 Appendix ) . Relative to our baseline SIS assumption , the effect of adding vital dynamics is to delay the virulence peak slightly and increase both the peak and equilibrium virulence . The changes are small , however: across all models , the maximum increase in time until the virulence peak is 40 years ( for the instswitch+epc model ) , in the peak log10 SPVL is 0 . 24 units ( instswitch ) , and in the equilibrium log10 SPVL is 0 . 4 units ( pairform ) . The changes in the most realistic model ( pairform+epc ) are considerably smaller: an increase of 2 years vs . a decrease of 13 years in the time to the virulence peak for the models with vital dynamics and heterogeneity , respectively; an increase of 0 . 1 units vs . a decrease of 0 . 01 units in peak log10 SPVL; and an increase of 0 . 145 units vs . a decrease of 0 . 03 units in equilibrium log10 SPVL . Thus , while we can never rule out the possibility of some higher-order interaction among epidemiological phenomena leading to significant changes in our conclusions , we are reasonably confident that the results reported here are robust to additional complexities .
How contact structures are modeled can strongly affect researchers’ conclusions about the evolutionary dynamics of virulence . In particular , a relatively simple , strategic eco-evolutionary model of HIV can predict peak log10 set-point viral loads ( over the course of an epidemic ) ranging from 3 . 5 to 4 . 8 depending on the specific model of sexual partnership behaviour used . This difference in log10 SPVL is epidemiologically significant , corresponding to a twofold difference ( 12 vs . 6 years ) in expected time to progression . The restriction of transmission within stable partnerships strongly limits eco-evolutionary dynamics by limiting the maximum speed of epidemic growth . An HIV genotype that optimizes SPVL to maximize the speed of spread in a homogeneous population will be sub-optimal in a context where infection can only spread beyond a partnership once it dissolves . This finding echoes a long line of studies that show that population structure leads to the evolution of “prudent” parasites , although most of these studies focus on equilibrium optima rather than eco-evolutionary dynamics [25–28] . The more complex contact structures we modeled mitigate these constraints by allowing HIV to spread among uncoupled individuals ( through finite pair-formation ) and members of stable partnerships ( through extra-pair contact ) , albeit at lower rates than within partnerships . Thus , we see the biggest differences not between the simplest and the most complex contact structures , which either ignore pair structure completely or allow for extra-pair contact that reduces its impact , but between the complex contact structures and models of intermediate complexity . These intermediate-complexity models attempt , quite reasonably , to add at least some of the realism of human sexual behaviour , but err by neglecting the apparently insignificant detail of extra-pair contact . If partial complexity may lead to such mistakes , how can modelers do anything but always strive to build the most realistic models possible ? All models must simplify the world . Many constraints—among them data availability , computation time , and code complexity—drive the need for parsimony , with different constraints applying in different contexts . The critical question that modelers must ask is whether the simplified model gives adequate answers , or whether the simplifications lead to qualitative or quantitative errors . This question is especially important for modelers who are hoping that their conclusions will guide management decisions . In the particular example of HIV virulence eco-evolutionary dynamics and the complexity of contact structures we reach the slightly ironic conclusion that the effort put into building a more realistic model essentially cancels out , putting us back where we started when used a naive random-mixing contact model . However , we are not quite back where we started , as the complex models lead to wider , presumably more realistic confidence intervals on the predictions . In general , unstructured mixing—whether occurring through purely random mixing , or through extra-pair contact and contact among people outside of stable partnerships—tends to drive faster virulence evolution , leading to higher peak virulence and lower times to progression at the peak time . Taking further steps to make the model even more realistic might add further structure , making the random-mixing model predictions less accurate . For example , our model forms partnerships randomly , and assumes that extra-pair contact is randomly mixing across the population; one could instead model extra-pair contact as arising from multiple concurrent partnerships ( some , such as contact with sex workers , of very short duration ) and/or more structured partnership formation ( by age , ethnicity , or behaviour group ) . In contrast , the elevated viral load in the early stage of HIV infection , neglected in our model , will likely lead to higher maximum epidemic growth rates and allow more scope for transient viral evolution , although only if extra-pair contact is possible . The effects of other realistic complications such as explicit modeling of two sexes ( both in contact structure and differential transmission probabilities ) , temporal and spatial variation in epidemic processes , or presence of genetic variation in hosts are harder to predict . As mentioned above , our compartmental model already requires tens of thousands of coupled differential equations , which will increase multiplicatively with additional model dimensions such as age , sex , or HIV stage . Thus , further model elaboration will best be done with agent-based models . Parameterization is one of the biggest challenges of epidemiological modeling . In addition to following Champredon et al . [15] by doing Latin hypercube sampling across a wide range of epidemiological parameters , we calibrated each set of parameters to the same initial epidemic growth rate , chosen to match the results of previous models [9] . Previous models in this area have drawn their parameters from cohort studies from the 1990s [16 , 29] rather than doing any explicit calibration to epidemic curves , but they give reasonable order-of-magnitude growth rates ( ≈ 0 . 04 year−1 ) for the early stages of the HIV epidemic ( although considerably lower than estimates of ≈ 0 . 07 − 0 . 1 year−1 based on population genetic reconstructions [30] ) . However , our reason for calibrating was not to match any specific observed epidemic , but rather to make sure that we were making meaningful comparisons across a range of models with radically different contact structures , and hence involving different interpretations of the same quantitative parameters . For example , in models with instantaneous switching the partnership dissolution rate c is identical to the partnership formation rate; in models with explicit partnership formation , the partnership formation rate is also c at equilibrium , but might vary over the course of an epidemic . Models with equal parameters but different structures cannot be compared directly; calibration solves this problem . More generally , any model that wants to be taken seriously for management and forecasting purposes should be calibrated to all available data , using informative priors to incorporate both realistic distributions of uncertainty for all parameters from independent measurements [31] and calibration from population-level observations of epidemic trajectories . Such a procedure would also be an improvement on the common—although not universal—practice , which we have followed here , of assessing uncertainty over uniform ranges rather than using distributions that allow more continuous variation in support over the range of a parameter . Researchers have documented that HIV virulence and set-point viral load are changing , on time scales comparable to those portrayed here ( e . g . , compare Fig 3 to Herbeck et al . ’s estimated rate of change of 1 . 3 log10 SPVL per century [95% CI -0 . 1 to 3] [32] ) , and have begun to build relatively realistic models that attempt to describe how interventions such as mass antiretroviral therapy ( ART ) can be expected to change the trajectory of virulence evolution [11 , 33 , 34] . While these efforts are well-intentioned , we caution that structural details that are currently omitted from these models could significantly change their conclusions .
|
Pathogens such as HIV can evolve rapidly when the environment changes . One important aspect of a pathogen’s environment is the probability that an infectious contact ( a sneeze for a respiratory disease , or an unprotected sex act for a sexually transmitted disease ) encounters an uninfected person and thus has a chance to transmit the pathogen . As an epidemic grows the number of uninfected people shrinks , changing evolutionary pressures on the pathogen . While researchers have used models to explore pathogen evolution during epidemics , their models usually neglect important processes such as people entering and leaving sexual partnerships . We compared several evolutionary models for HIV that include partnership dynamics as well as sexual contact outside of stable partnerships . Models of intermediate complexity predicted lower virulence midway through the epidemic ( a minimum of 15 years to progress to AIDS ) than either more realistic models or simple models with no partnership structure ( both with a minimum of 7 . 25 years to progress to AIDS ) , because random sexual contacts tended to wash out the effects of stable partnerships . Researchers trying to predict the evolution of pathogens must try to understand the implications of their modeling choices; models of intermediate complexity may not produce intermediate conclusions .
|
[
"Abstract",
"Introduction",
"Materials",
"and",
"methods",
"Results",
"Discussion"
] |
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] |
2017
|
Effects of contact structure on the transient evolution of HIV virulence
|
This paper assesses the impact of a counselling intervention on reducing leprosy-related stigma in Cirebon District , Indonesia . The unique features of this intervention are its rights-based approach , the underlying Cognitive Behavioural Therapy ( CBT ) model , the three types of counselling and the lay and peer counsellors who were involved . Mixed methods ( e . g . three scales , interviews , focus group discussions and reflection notes ) were used to assess the impact of the intervention , which ran over a two-year period . There was a control area with no interventions . The study participants were people affected by leprosy and other key persons ( e . g . family members ) . The sample size differs per method , for example , data regarding 67 counselling clients and 57 controls from a cohort , and notes from 207 counselling clients were examined . The notes showed that most clients faced stigma on a daily basis , whether internalized , anticipated and/or enacted . A significant reduction was found between the before and after total scores of the SARI Stigma Scale ( p-value < 0 . 001 ) , Participation Scale Short ( p-value < 0 . 001 ) and WHO Quality of Life score ( p-value < 0 . 001 ) among the counselling clients . While there is also an effect in the control group , it is much larger in the intervention group . Qualitative data indicates that knowledge and rights trigger change . Clients took steps to improve their life such as re-connecting with neighbours , helping in household activities and applying for jobs . Challenges include the wish to conceal their condition . The findings show that the counselling intervention was effective in reducing stigma , promoting the rights of people with leprosy and facilitating their social participation . More research is needed on how to create a more sustainable intervention , preferably structurally embedded in the health or social services .
In the past , stigma was primarily considered an attribute; a legacy of Goffman’s seminal work [21] , or of its interpretation . The current emphasis lies much more on stigma as a social process and thus goes beyond the individual body [22] . A well-known definition of health-related stigma that we employ in this study is: To distinguish different types of stigma , Weiss [24] extended the Hidden Distress Model of Scambler [25] , and identified three types for those who stigmatize and three for those who are stigmatized . This paper focuses mainly on the types of stigma faced by those who are stigmatized: anticipated , internalized and/or enacted [25 , 26] . The latter refers to the experience of discrimination , and is also called experienced stigma . Anticipated or perceived stigma is the fear of being discriminated against . Finally , internalized or self-stigma is the stigma people apply to themselves due to negative views about the self , which could lead to feelings of shame and guilt . It is an internalized perception of being devalued or "not as good as" another individual , and is seen as a source of anguish and unhappiness [25] . A different categorization of stigma is based on three levels: structural , social and individual [27–30] , and this paper considers the social level ( interpersonal ) and individual level ( intrapersonal ) . It is not easy to assess a concept as complex as stigma [20] . We decided to assess experiences of stigma , and two aspects that are negatively affected by it: participation and quality of life . Studies in India , the Netherlands and the Philippines have shown that leprosy and , in particular , leprosy-related impairments , can negatively affect one’s social participation [31–33] . This association was studied and confirmed in Indonesia . Van Brakel et al . [7] found that 60% of the people with a leprosy-related impairment experience restrictions on their participation . Quality of life is another well-known overall measurement . The effect of leprosy or leprosy-related stigma on the quality of life is interesting but has been little studied , and when it has , the results are mixed . Brouwers et al . [34] did not find a significant association in a multivariate analysis on data from East Nepal , while Tsutsumi et al . [5] did find an association between anticipated stigma and quality of life in Bangladesh . By assessing stigma , participation restriction and quality of life we hoped to gain a broad impression of the impact of the counselling intervention on stigma .
This study is part of the Stigma Assessment and Reduction of Impact ( SARI ) project conducted in Cirebon District , Indonesia ( 2010–2015 ) . The SARI project aimed to assess the effectiveness of three stigma-reduction interventions in persons affected by leprosy in Cirebon District , West-Java , Indonesia: counselling , contact [35] and Social Economic Development ( SED ) . The SARI project is a cluster-randomized controlled intervention study and uses the Interactive Learning and Action approach [36] as a guiding methodology . The SARI team is interdisciplinary and inclusive—the scientific staff comes from a range of disciplines and several team members are affected by leprosy or have a disability . For instance , the first author ( ML ) has a visual disability , the principal investigator ( I ) uses a wheelchair , and four of the ten local research assistants have a disability or have been affected by leprosy . The SARI team works closely with local , provincial and national Health Offices and with a local Disabled People’s Organisation ( DPO ) . Cirebon District was selected as the study area because it has a relatively high number of new cases annually and—according to national experts—a higher level of leprosy-related stigma than in other districts and no interventions to address this . Thirty sub-districts of Cirebon District were randomly allocated a paired intervention or became a control area where no interventions were made . The interventions areas included: ( i ) ‘Counselling—Contact’; ( ii ) ‘Contact—SED’; ( iii ) ‘SED—Counselling’; and ( iv ) ‘Control’ . The baseline study was conducted in 2011 , the counselling intervention ran from January 2012 to December 2013 and the final survey was made in the second quarter of 2014 . This enables us to assess a relatively long-term impact . The study population included people affected by leprosy living in the area where the interventions were offered . Data was also collected regarding current counselling clients , their family members , health professionals , lay and peer counsellors and SARI’s research assistants to get a rich perspective on the effect of the intervention and to enhance the validity of this study . The counselling intervention was developed during the first year of the project and the idea was that it would address stigma primarily at the individual , and secondarily at the social level . An exploratory study was conducted ( see [3 , 10 , 37] ) and based on its findings a counselling practice was drafted and piloted , which led to the Rights-Based Counselling Module ( RBCM ) ( see Box 1 ) . This module can be managed by lay and peer counsellors . The SARI project selected 28 people as potential lay and peer counsellors , including the project’s ten research assistants . They attended 56 hours of RBCM training , and eventually 23 became a counsellor ( 15 men and eight women; ten were affected by leprosy , six have a physical disability , one has a visual impairment and six had no disability or leprosy ) . They worked in teams of three and were supervised by the first author ( ML ) ( for more details on the selection , training and perceptions of lay counsellors [38] ) . In total , 260 persons affected by leprosy were offered counselling: 62 during the pilot phase and 198 during RBCM phase . The counselling offered during the two phases was broadly similar in terms of counselling types and style , but adjustments in , for example , the number of sessions , were made to make it more appropriate and therefore more effective . Of these 260 persons , 53 ( 20 . 4% ) decided during the first session that they did not need or want to receive counselling . Reasons given by these 53 persons included no or limited stigma and fear for disclosure . The remaining persons became the counselling clients ( n = 207 ) . The number of sessions and type of counselling differed by client and depended on their needs and wishes ( see Table 1 ) . Mixed methods were used to get an in-depth understanding of the effects of the counselling and how these were achieved ( see questions in introduction ) and to still be able to generalize the findings . Three scales were used: the SARI Stigma Scale ( SSS ) , Participation Scale Short ( PSS ) and the World Health Organization Quality of Life instrument ( WHO-QOL BREF ) . The SSS aims to assess stigma and is based on the HIV Stigma Scale developed by Berger et al . [39] . The scale has 21 items ( score 0–3 , min-max total score 0–63 ) and four domains: experienced stigma ( min-max total score 0–21 ) , disclosure concerns ( min-max total score 0–12 ) , internalized stigma ( min-max total score 0–18 ) and anticipated stigma ( min-max total score 0–12 ) . The cross-cultural validity of the SSS was tested in Cirebon District and found to be adequate for the Bahasa Indonesia-speaking population [59] . The Participation scale assesses participation restrictions and is based on the Participation domain of the International Classification of Functioning , Disability and Health [40] . The validity of this scale has been tested and found to be adequate in several Asian countries [40–42] . A shortened version of the Participation scale , the Participation Scale Short , has 13 items ( score 0–5 , min-max total score 0–65 ) [43] . This is the version we applied . The WHO-QOL BREF instrument is a shorter version of the original WHO-QOL instrument , comprising 26 items ( score 1–5 , min-max total score 26–130 ) , which measure the broad domains of physical health , psychological health , social relationships and environment . The validity has been tested and was found to be adequate in an Indonesian-speaking sample [44] . Some of the domains and items of these scales are more relevant than others . Of particular interest are , for instance , the SSS internalized stigma and the psychological health domain of the WHOQOL-BREF . Applying multiple instruments can be quite burdensome for respondents . If the interviewer noted that a respondent was tired and not so keen on continuing the interview , they were instructed to drop the WHO-QOL BREF . Based on a sample-size calculation and an anticipated loss to follow-up it was decided that 600 people affected by leprosy had to be part of the quantitative part of the baseline . Health professionals invited people affected by leprosy ( currently in treatment or cured ) to different health clinics for an interview . In addition , in-depth interviews ( IDI ) and Focus Group Discussions ( FGD ) were applied using purposive sampling to ensure adequate representation of men and women , different age groups and intervention areas . For the IDI in the final survey , clients whose lay or peer counsellors expected positive outcomes as well as those with limited or no positive outcomes were selected . We aimed for 80 interviews for the baseline and 25 for the final survey . As many paired interviews as possible were conducted ( same interviewee for baseline and final survey ) . The IDIs aimed to gain insight in the extent of stigma in people affected by leprosy before and after the intervention . The topics addressed were: leprosy history , feelings , family and friends , community , economic condition , and future . The FGDs aimed to assess the impact of the counselling after the intervention . Different groups of participants joined these discussions including counselling clients and their family members , health professionals , lay and peer counsellors and research assistants . Topics of the FGD were changes that occurred due to counselling , influence of the type of counselling , role of the type of counsellor and strengths and weaknesses of the counselling . Finally , two types of notes were prepared . The Participant Reflection Notes ( PRN ) were written at the end of the counselling and aimed to identify the benefits of counselling for the clients . Clients received nine questions to guide their reflections ( e . g . changes experienced , remaining expectations from counselling ) . These notes were not written during the pilot but only during the implementation of the RBCM . The Counsellor Reflection Notes ( CRN ) aimed to provide insight into the types of stigma the client experiences , if and what changes occurred during the counselling sessions and how counselling might have contributed to these changes . Table 2 provides an overview of all the methods . The interviews and FGDs were recorded , transcribed and translated into English . This data was analysed by ML . The quantitative data was entered into an Epi Info for Windows database ( version 3 . 5 . 3 ) and analysed using Stata 12 . 1 by RP . Demographic variables included sex , age ( in years ) , married ( yes/no ) , education , disability grade ( 0/1/2 ) ( using the WHO leprosy disability grading system [45] . This paper addresses the impact of the counselling intervention as a whole and not the impact of its individual activities . Therefore , all participants who were part of either the pilot counselling given by ML or of the RBCM given by lay and peer counsellors were combined in one group for the main analysis . To investigate the effect of the interventions , we calculated means , SD , and performed simple regressions ( t-test , paired t-test , Wilcoxon matched-pairs signed-ranks test ) . P-values less than . 05 were taken as significant . Permission to undertake the study was obtained from the relevant government offices . Written informed consent was obtained from individual study participants . The control area in this study was a “care-as-usual” area .
Scales were administered in 523 people affected by leprosy living in the study area during the baseline . For the final survey only people affected by leprosy whose interview was administered in Bahasa Indonesia and whom we were able to interview again were included . This resulted in 237 matched observations ( see Fig 1 ) . Given the number lost to follow-up we compared the 237 observations with those who could not be interviewed again to see if there were any systematic differences that might indicate bias ( Table 3 ) . No significant differences were found . As shown in Fig 1 , of these , 111 ( 57+54 ) people affected by leprosy lived in the areas where counselling was offered . In total , 67 of the cohort joined the intervention: 23 received counselling during the pilot from ML ( of which seven were selected and also became peer counsellors ) and 44 received counselling from lay and peer counsellors using the RBCM . Of the 67 clients , 18 also participated in SED-related activities ( received microcredit , attended a training or received livestock ) and 34 lived in areas where events were organised that aimed improve negative community perspectives and attitudes . The socio-demographic characteristics of the participants of the counselling intervention are shown in Table 4 . Also more detailed information about the differences between male and female ( the men affected by leprosy in this cohort are less often married and have a higher level of education ) are provided . Seventy-seven IDI were conducted during the baseline and 24 during the final survey; five were paired . Of these 77 IDI , 38 were with women and 39 with men; mean age was 32 ( youngest was 16 and eldest was 70 ) . Of the 24 IDI in the final survey , 14 were with women and 10 with men; the mean age was 44 ( youngest was 18 and oldest was 70 ) . There were nine FGD in the final survey with a total of 64 participants ( see Table 5 for a detailed overview ) . PRN were written by 145 clients and CRN were written by ML and 12 lay and peer counsellors on the counselling sessions of 207 clients ( five went missing ) . The CRN notes show that most clients faced daily internalized , anticipated and/or enacted stigma . Usually they faced combined types of stigma , but often one type was dominant . According to the CRN of the 202 clients 93 ( 46% ) dealt mostly with internalized stigma , 54 ( 27% ) mostly with anticipated stigma , 38 ( 19% ) mostly with enacted stigma , while 17 ( 8% ) experienced no stigma . Those facing internalized stigma mentioned that they felt shame , were worried , felt dirty because of the lesions on their face and body , feared impairment , and had lost confidence . As a result , some of them opted to conceal their disease from their family , decided to stop working , preferred to stay at home , did not want to meet people and rejected invitations . About 5% of them admitted to having had suicidal thoughts . Most of those who experienced anticipated stigma feared being excluded and/or suffering discrimination . These clients wondered whether leprosy can be transmitted and whether it can be cured . Again a wish to conceal was found in this group . Those who experienced enacted stigma said they were treated badly by family and community members , which restricted their participation in their daily lives . Some had to stop going to school , lost their job , and lost their family and friends . Table 6 provides sections from the CRN notes to illustrate how each type of stigma manifested itself . Occasionally the counsellors concluded that the client experienced little or no stigma . While these clients also faced negative attitudes they dealt with these in a very positive way , they were full of spirit , accepted their disease , did not care about what others said about them and had sufficient medical information about leprosy . This categorization is a simplification of the clients’ complex reality . As mentioned , most clients dealt with a combination of types of stigma at the same time: This analysis of the qualitative baseline data shows that stigma is a real , important and complex problem for many , but not all , people affected by leprosy . Stigma was an important problem for many people affected by leprosy in Cirebon District and the counselling intervention had a positive impact on their lives . How was this impact achieved and how did the different aspects of the intervention ( raising knowledge , awareness of rights , involvement of lay and peer counsellors , combination of individual , family and group counselling ) contribute to the changes ? In the introduction several questions were raised , which we address here .
Rafferty [12] stated that “if patients are cured , the stigmatization can remain an insurmountable obstacle to the resumption of a normal life” . This study shows that the obstacle is not insurmountable . The findings demonstrate that the counselling intervention is effective in decreasing stigma , promoting the rights of people with leprosy and in facilitating their participation in family and community life . We recommend its application on a larger scale . More research is needed to create a more sustainable implementation of the counselling , preferably structurally embedded in the health or social services .
|
Can building knowledge , increasing the awareness of rights and developing confidence through counselling empower people affected by leprosy and reduce the stigma that surrounds them ? In this paper the authors describe the impact of a counselling module designed to address the widespread issue of stigma in Cirebon District , Indonesia . The module ran for a two-year period and has some unique features . For example , it integrates three different types of counselling: individual , family and group . During the counselling , medical information about leprosy was provided and awareness of rights ( e . g . right to healthcare , right to education ) was raised . The counselling was offered by lay and peer counsellors , the latter having been affected by leprosy , to a total 260 people . This study showed that counselling can be effective in reducing stigma . The authors recommend its application on a larger scale .
|
[
"Abstract",
"Introduction",
"Methods",
"Results",
"Discussion"
] |
[
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] |
2016
|
The Impact of a Rights-Based Counselling Intervention to Reduce Stigma in People Affected by Leprosy in Indonesia
|
There are no effective vaccines for visceral leishmaniasis ( VL ) , a neglected parasitic disease second only to malaria in global mortality . We previously identified 14 protective candidates in a screen of 100 Leishmania antigens as DNA vaccines in mice . Here we employ whole blood assays to evaluate human cytokine responses to 11 of these antigens , in comparison to known defined and crude antigen preparations . Whole blood assays were employed to measure IFN-γ , TNF-α and IL-10 responses to peptide pools of the novel antigens R71 , Q51 , L37 , N52 , L302 . 06 , J89 , M18 , J41 , M22 , M63 , M57 , as well as to recombinant proteins of tryparedoxin peroxidase ( TRYP ) , Leishmania homolog of the receptor for activated C kinase ( LACK ) and to crude soluble Leishmania antigen ( SLA ) , in Indian patients with active ( n = 8 ) or cured ( n = 16 ) VL , and in modified Quantiferon positive ( EHC+ve , n = 20 ) or modified Quantiferon negative ( EHC−ve , n = 9 ) endemic healthy controls ( EHC ) . Active VL , cured VL and EHC+ve groups showed elevated SLA-specific IFN-γ , but only active VL patients produced IL-10 and EHC+ve did not make TNF-α . IFN-γ to IL-10 and TNF-α to IL-10 ratios in response to TRYP and LACK antigens were higher in cured VL and EHC+ve exposed individuals compared to active VL . Five of the eleven novel candidates ( R71 , L37 , N52 , J41 , and M22 ) elicited IFN-γ and TNF-α , but not IL-10 , responses in cured VL ( 55–87 . 5% responders ) and EHC+ve ( 40–65% responders ) subjects . Our results are consistent with an important balance between pro-inflammatory IFNγ and TNFγ cytokine responses and anti-inflammatory IL-10 in determining outcome of VL in India , as highlighted by response to both crude and defined protein antigens . Importantly , cured VL patients and endemic Quantiferon positive individuals recognise 5 novel vaccine candidate antigens , confirming our recent data for L . chagasi in Brazil , and their potential as cross-species vaccine candidates .
Visceral leishmaniasis ( VL ) , also known as kala-azar , is a potentially fatal disease caused by obligate intracellular parasites of the Leishmania donovani species complex . VL is a serious public health problem in indigenous and rural populations in India , accounting for enormous morbidity and mortality , as well as major costs to both local and national health budgets . The estimated annual global incidence of VL is 200 , 000 to 400 , 000 , and >90% of these cases occur in India , Bangladesh , Sudan , South Sudan , Ethiopia and Brazil [1] . Interestingly , 80 to 90% of human infections are subclinical or asymptomatic , and this asymptomatic infection is associated with strong cell-mediated immunity [2] , [3] , [4] , [5] , [6] . Only a small percentage of infected individuals develop severe disease [7] , [8] , and patients who recover from VL display resistance to reinfection [5] . This suggests the development of protective immunity and provides a rational basis for the development of vaccines that impart potent cell-mediated immune responses . Furthermore , the factors that skew the immune response toward T helper 1 ( Th1 ) or Th2/T regulatory ( Treg ) cell dominance are partially understood , and it is believed that direct interaction between parasite antigens and host immune cells participate to shape the subsequent pathogenic or protective immune responses [9] , [10] . A key mechanism by which T cells mediate their effector functions is through the production of cytokines . However , heterogeneity of CD4+ T-cell cytokine responses has made it difficult to define immune correlates of protection after vaccination in leishmaniasis . In murine cutaneous leishmaniasis , the degree of protection in vaccinated mice was predicted by the frequency of CD4+ T cells simultaneously producing interferon-γ ( IFN-γ ) , interleukin ( IL ) -2 and tumour necrosis factor ( TNF , formerly TNF-α ) [11] . These multi-functional effector CD4+ T cells elicited by all vaccines tested were unique in producing high amounts of IFN-γ [11] . In our own studies comparing vaccines with different efficacies in mice , we found that the balance between antigen-specific CD4 T cell-derived pro-inflammatory IFN-γ and regulatory IL-10 ( and to a lesser extent IL-4 and IL-5 ) , rather than magnitude of IFN-γ per se , provided the best correlate of a protective immune response [12] . A strong tumour necrosis factor-α ( TNF-α ) response concurrent with IFN-γ has also been shown to be important in models of VL [13] . A crucial step in vaccine development against human disease requires improved understanding of the functional heterogeneity of T-cell cytokine responses generated by candidate vaccine antigens . For example , one study in malaria reported that peptide-specific IFN-γ to a conserved epitope of the circumsporozoite surface protein was strongly associated with protection of humans again infection and disease [14] , providing a precise target for vaccine design . Without a convincing single marker of protective immunity against leishmaniasis , vaccine development has to rely on screening a range of cytokines to gauge the balance between Th1 and Th2/T regulatory ( Treg ) responses . Advances in our understanding of Leishmania pathogenesis and of the generation of host protective immunity , together with completed Leishmania genome sequences , have opened new avenues for vaccine research . Although significant progress has been made to understand mechanisms of VL immunity in humans [9] , [10] , there is no effective vaccine available for humans against any form of leishmaniasis . Drugs used in leishmaniasis therapy are significantly toxic , expensive and faced with increasing resistance . Limitations in pharmacotherapy argue for the development of a vaccine for VL . Vaccination with live virulent parasites , termed leishmanization , was practiced from ancient times until recently in many endemic areas [15] . Vaccine trials involving whole , killed parasites were conducted in the 1970s and 1980s [16] , [17] . Although no overall statistically significant protection has been associated with any trial of these killed vaccines [18] , [19] , [20] , [21] , [22] , a common theme has been protection in persons who showed conversion of Leishmania-specific delayed type hypersensitivity ( DTH ) skin test responses during the trial , whether or not they received the vaccine . The latter points to the importance of understanding the immune response in exposed individuals who become infected but do not progress to clinical disease , which in the Indian endemic area has been equated to a positive modified Quantiferon response to leishmanial antigens in whole blood assays [23] . The genome sequence and proteome data ( ∼33 . 6 Mb genome and ∼8300 protein coding genes ) of Leishmania major [24] provides a rich source of potential vaccine candidates . We recently described the identification of novel Leishmania antigens delivered as DNA vaccines to susceptible BALB/c mice , and identified 14 protective candidate antigens in a screen of 100 amastigote-expressed genes [25] . To determine their potential as vaccine candidates for humans , we here evaluate the ability of 11 of these novel Leishmania vaccine candidates , along with soluble Leishmania antigen ( SLA ) , recombinant Leishmania homolog of the receptor for activated C kinase ( LACK ) , and tryparedoxin peroxidase ( TRYP ) proteins , to stimulate cytokine responses in whole blood from active and cured VL patients , and from modified Quantiferon positive and negative endemic health controls ( EHC ) , in India .
The study was approved by the Ethics Committee of the Banaras Hindu University , Varanasi , India . Written informed consent was obtained from all adult subjects included in the study , or from the parents or guardians of individuals less than 18 years of age . Subjects belonged to 4 clinically well characterized groups: ( i ) active VL: cases of parasitologically confirmed , active VL ( n = 8 ) ; ( ii ) cured VL: subjects who were definitively cured of VL and shown to have no parasites in splenic aspirates at least 6 months after treatment ( n = 16 ) ; ( iii ) EHC with a positive antigen-specific IFN-γ response measured by modified Quantiferon ( Cellestis , Chadstone , Australia ) assay ( cf . below ) ( EHC+ve , n = 20 ) ; and ( iv ) EHC testing negative by modified Quantiferon assay ( EHC−ve , n = 9 ) . Subjects having fever within the past month , and children less than five years of age , were excluded . Follow up visits were made to the homes of the EHC+ve and cured subjects 6 and 12 months after enrolment to monitor for the development of active VL . Demographic and clinical characteristics of participants enrolled in the vaccine study are summarized in Table 1 . None of the cured VL or EHC subjects developed clinical VL during the 1 year follow-up . SLA from an Ethiopian strain of L . donovani ( LV9 ) or L . major ( LV39 ) were prepared at the Cambridge Institute for Medical Research , University of Cambridge School of Clinical Medicine , UK as described previously [12] . SLA from an Indian strain of L . donovani was prepared at the Infectious Disease Research Laboratory , Banaras Hindu University , according to the published protocol of Scott and co-workers [26] . The protein concentration was estimated using the BCA method [27] . SLA was stored at −80°C until use . Recombinant LACK and TRYP proteins were prepared as described [11] , [12] , with large-scale preparation , endotoxin removal and protein estimation out-sourced to Novexin Ltd . ( Cambridge , UK ) . As previously described [28] , overlapping 13–20-mer peptides ( minimal overlap of 12 amino acids to ensure complete coverage of epitopes , 7–31 peptides/antigen depending on amino acid length of the protein ) representing 11 ( R71 , Q51 , L37 , N52 , L302 . 06 , J89 , M18 , J41 , M22 , M63 , M57 ) of 14 novel antigens identified [25] were synthesized commercially ( Peptide2 . 0 , Chantilly , VA ) , initially solubilized in dimethylsulfoxide ( final concentration in the well <0 . 1% DMSO ) , and pooled ( for peptides within each antigen ) in endotoxin-free phosphate-buffered saline at a final concentration of 50 µg/mL per individual peptide . Peptides pools were stored at −80°C . Due to the size of peptides in the pools , some natural processing is required for epitope selection prior to epitope binding to class II and presentation to CD4+ T cells . The Quantiferon ( Cellestis , Chadstone , Australia ) whole blood assay was conducted on 147 endemic healthy individuals according to the manufacturer's instructions or to our published modifications [6] , [23] . From these data , 20 highly positive ( above the cut-off value generated by the ROC curve ) individuals were selected as the EHC+ve study group , and 9 individuals selected at random from below the cut-off value as the EHC−ve study group . Blood ( 5 mL ) was collected into heparinised tubes , and samples diluted 1 in 8 in serum-free complete medium comprising RPMI supplemented with 2 mM L-glutamine , 100 µg/mL streptomycin , 100 IU/mL penicillin ( Gibco , USA ) . Diluted blood ( 180 µL/well ) was plated into 96-well U-bottomed plates ( Nunc , Rochester , USA ) and antigen added in triplicate wells at a final concentration of 10 µg/mL for TRYP , LACK and SLA , 5 µg/mL for PPD , PHA and the 11 novel antigen peptide pools , and made up to a volume of 200 µL . Plates were incubated at 37°C in 5% CO2 for 24 hours , 72 hours or 6 days . Supernatants from replicate wells were harvested , pooled and stored at −80°C until analysed by ELISA . Cytokine release ( IFN-γ , TNF-α and IL-10 ) by antigen stimulated whole blood cells was measured at 24 hours , 72 hours , or 6 days . IFN-γ , TNF-α and IL-10 were measured using matched antibody pairs ( BD Pharmingen , Franklin Lakes , NJ , USA ) by ELISA . The limit of detection for these ELISAs was 31 pg/mL . Background levels in non-stimulated control wells were deducted from antigen-stimulated values to determine antigen specific cytokine responses ( with negative values recorded as zero ) . To control for inter-plate and intra-plate variation , a positive-control supernatant ( 1∶4 and 1∶8 dilution of PHA stimulated Non Endemic Healthy Controls ( NEHC ) whole blood pooled supernatant ) was used in duplicate on each ELISA plate . The mean variability of these duplicate measurements was 2 . 53% ( intra-plate variation ) . The coefficient of variation between plates ( inter-plate variation ) was 20 . 74% for IFN-γ , 10 . 78% for TNF-α and 18 . 04% for IL-10 . Because data were generally not normally distributed ( as determined using the Kolgomorov-Smirnov test ) , data are plotted using box and whiskers ( Tukey ) plots , and statistical differences ( P<0 . 05 ) between pairs of groups were determined using nonparametric 2-tailed Mann-Whitney tests . Nominal P-values are presented throughout ( i . e . without correction for multiple testing ) . Plots were generated using GraphPad Prism 5 ( San Diago , USA ) , and statistical analyses were performed using GraphPad Prism 5 or SPSS software v18 . 0 .
To investigate antigen specific production of IFN-γ , TNF-α and IL-10 cytokines , diluted whole blood from different patient groups was initially stimulated with SLA from an Indian L . donovani strain . Comparison of responses over time post stimulation in active VL cases showed that all 3 cytokines were highest , and less variable , at the 24 hour time point ( Fig . 1A–C ) . Active cases made variable responses to PPD reflecting prior exposure to Mycobacterium and indicating that ability to make a response to mycobacterial antigens is not compromised in active VL patients . Cured cases made similarly variable responses to PPD ( Fig . S1 ) . Between group comparisons at 24 hours post stimulation showed that active VL , cured VL , and EHC+ve study groups all made higher IFN-γ responses relative to EHC−ve subjects ( Fig . 1D ) . The observation that active VL cases make a significant amount of IFN-γ is in line with our recent observations for whole blood assays using undiluted blood in a modified Quantiferon assay [6] , [23] . Of interest , while cured VL and active VL groups generated TNF-α concomitant with IFN-γ , the EHC+ve group did not ( Fig . 1E ) , suggesting that production of this cytokine might relate to the pathogenic role of TNF-α in VL disease [29] . Note , however , that this was not true for responses to putative vaccine candidates outlined below , which all elicited TNF-α concomitant with IFN-γ in the EHC+ve group . Importantly , only the active VL group made IL-10 in response to Indian L . donovani SLA ( Fig . 1F ) , supporting previous data indicating that IL-10 is a key regulatory cytokine in VL patients [10] , [30] . Cytokine responses to 3 different Leishmania strains , an Indian L . donovani strain ( designated SLA ) , an Ethiopian L . donovani strain ( LV9 ) and L . major strain ( LV39 ) were compared ( Fig . 2 ) . For IFN-γ responses the two L . donovani preparations stimulated equivalent responses ( Fig . 2A ) . Interestingly , SLA prepared from the local Indian L . donovani strain elicited significantly stronger 24 h TNF-α ( Fig . 2B ) and IL-10 responses ( Fig . 2C ) compared to Ethiopian L . donovani ( p = 0 . 0003; p = 0 . 004 ) or the L . major strain ( p = 0 . 028; p = 0 . 007 ) . The L . major antigen was more variable in eliciting responses across all cytokines and time points . The ability of diluted whole blood assay samples to respond to mitogenic stimulation with PHA ( Tables S1 and S2 ) confirmed the viability of the cells from all donors . We previously demonstrated that high CD4-derived IFN-γ to low IL-10 ratios predicted vaccine success in mice when comparing TRYP and LACK as DNA with/without Modified Vaccinia Ankara vaccines [12] , [31] . Here , we examined immune responses to these potential vaccine antigens in clinically well characterized groups of human subjects . The full set of results for IFN-γ , TNF-α and IL-10 responses to TRYP ( Fig . S2 ) and LACK ( Fig . S3 ) at 24 hours , 72 hours and 6 days post stimulation in active VL , cured VL , EHC+ve and EHC−ve study groups is provided in the figures S2 and S3 . Of note , although the EHC−ve group comprised negative responders to Indian SLA by the modified Quantiferon assay , their cytokine responses to TRYP and LACK was rarely significantly different as a group from cured VL and EHC+ve groups . Hence , we conclude that there are exposed individuals amongst this EHC group , although we did not test non-endemic healthy control responses to these antigens . As this exposure status is variable and equivocal , we exclude them from further analysis of between group responses . Results for active VL , cured VL and EHC+ve groups are summarised in figures 3 ( TRYP ) and 4 ( LACK ) . For both antigens , the pattern of IFN-γ and TNF-α responses across the 3 groups is generally established at 24 hours , and clear cut by 72 hours and 6 days , post stimulation . For these two cytokines , responses were significantly lower in active VL compared to cured VL and EHC+ve groups at 72 hours and 6 days post stimulation . The pattern of responses for IL-10 was similar ( i . e . higher in cured VL and EHC+ve compared to active VL ) , but more clearly apparent at 24 hours post-stimulation . This led to interesting between group differences in the ratios of IFN-γ to IL-10 and TNF-α to IL-10 at 24 hours , when ratios were significantly higher in the active VL group compared to cured VL and EHC+ve groups ( particularly for TRYP ) , compared to 6 days of stimulation where the reverse was true for both antigens . For both antigens , the ratios of IFN-γ to IL-10 and TNF-α to IL-10 were highest in the EHC+ve group , suggesting that a potent pro-inflammatory response relative to modest levels of IL-10 may correlate with protection from disease in this confirmed Quantiferon positive exposed EHC group . We previously identified 14 protective Leishmania antigens in a screen of 100 candidates delivered as DNA vaccines to susceptible BALB/c mice [25] . We measured IFN-γ and TNF-α as effector pro-inflammatory cytokine responses to peptide pools for each of 11 of these antigens in diluted whole blood assays , and IL-10 as a measure of their ability to elicit a regulatory cytokine response . A full summary of responder status on a categorical scale ( − = <20 pg/ml; + = 20–99 pg/ml; ++ = 100–249; +++ = 250–499 pg/ml; ++++ = 500–10000 pg/ml; ++++ = >10000 pg/ml ) to each of the 11 antigens , and to control SLA , PPD and PHA stimulations , is provided for all individuals in Tables S1 and S2 . As these antigens were based on L . major sequence data , the antigens are presented throughout in order of their percent identity to L . infantum , as reported by us previously [28] . As would be predicted on the basis of genetic heterogeneity in HLA-restricted T cell responses and other background genetic and environmental factors , not all individuals make a response to individual candidate vaccine antigens . Using cured VL patients as an initial evaluation of percent responders ( ≥20 ng/mL above background ) with time post stimulation , we observed maximal IFN-γ responders at 24 hours and 72 hours post stimulation ( Fig . 5A ) , with 55–87 . 5% responders to 5 of the novel antigens ( R71 , L37 , N52 , J41 and M22; of these L37 exceptional in eliciting the highest sustained IFN-γ responses at day 6 post stimulation , see also Table S2 ) . Comparing across groups for the 72 hour time point ( Fig . 5B ) , we observed 40–65% responders to these 5 novel antigens in the EHC+ve group , with ≥25% of active VL cases also making IFN-γ responses to these antigens . Looking across cytokine responses for these 5 antigens ( Fig . 6 ) , we observe a similar profile of TNF-α responses in cured VL and EHC+ve groups as we observed for IFN-γ , but no IL-10 . Even amongst active VL cases , N52 was the only antigen to elicit IL-10 responses ( Fig . 6L ) . As for TRYP and LACK , a small number ( 22–33% ) of responders was observed in the EHC−ve group , consistent with evidence of exposure in these individuals despite their negative response in the modified Quantiferon assay . Alternatively , these might represent non-specific responses to these antigens as we did not include non-endemic controls in our study . In summary , we have identified five Leishmania antigens from 11 putative vaccine candidates tested that stimulate potent pro-inflammatory recall responses in exposed but protected individuals ( cured VL patients and EHC+ve ) in the absence of regulatory IL-10 , providing potential immunotherapeutic or vaccine targets for future investigation .
A variety of defined antigens have been investigated as vaccine antigen candidates for VL in animal models [32] , [33] , [34] , but few have advanced to human clinical trials [35] , [36] . One limitation in the search for an effective vaccine for leishmaniasis is the lack of information on immunological correlates of natural and vaccine-mediated protection in humans . In recent studies we have highlighted the use of a modified Quantiferon assay to screen for naturally exposed resistant individuals in the Indian study area [6] . That assay relies on 3 mL of undiluted whole blood . Here we show that individuals positive by the modified Quantiferon assay are also positive in our 96-well plate assays using diluted whole blood , providing the means to more efficient screening in large-scale epidemiological studies as has been used previously in studies of mycobacterial diseases [37] , [38] , [39] . Importantly too , our 96-well plate assay also showed that active VL patients were positive for IFN-γ in these diluted whole blood 96-well plate assays . Our initial demonstration [23] that active VL patients are positive for IFN-γ in the modified Quantiferon assay was remarkable given the numerous previous studies that had failed to observe cellular proliferation or IFN-γ release after stimulation of peripheral blood mononuclear cells from active VL patients with crude Leishmania antigen [10] , [40] , [41] , [42] . Ability to measure this IFN-γ response in the diluted whole blood assay described here will also facilitate more efficient screening of active VL cases using smaller blood volumes in a 96-well plate format . In human and murine cells infected in vitro , and in mice in vivo , clearance of Leishmania parasites requires IFN-γ . However , IFN-γ alone does not predict vaccine-mediated protection in mice [12] , [31] , [43] , [44] . Rather , the simultaneous production of IFN-γ , IL-2 and TNF-α by a particular subset of CD4 T cells [11] , and/or the balance between pro-inflammatory IFN-γ/TNF-α and regulatory IL-10 [12] , [31] , [44] , [45] , have been variously shown to be predictive of vaccine outcome . Epidemiological studies indicate that patients drug-cured from L . donovani infection are protected against subsequent clinical disease [46] , and it is thought that exposed individuals who test as positive to crude leishmanial antigens in the modified Quantiferon assay employed in our study area in India are infected asymptomatic individuals who are resistant to developing active VL disease [6] . Therefore , in the analysis of human immune responses to known and novel antigens presented here , we hypothesized that ability to stimulate IFN-γ , TNF-α and IL-10 in cured VL and EHC+ve individuals , compared to active VL cases , would provide some insight into their potential as vaccine candidates . Our investigations focused initially on the known vaccine candidates TRYP and LACK . Although others have found LACK protective in murine models of cutaneous leishmaniasis [47] , in the virulent model of visceralising L . major LV39 infection in mice we found that TRYP was protective but LACK was not [12] . Although the vaccine-induced IFN-γ responses were similar between the two antigens in mice , lower IL-10 was elicited by TRYP than LACK , resulting in higher IFN-γ to IL-10 ratios as correlates of protective immunity . In the human studies described here , we found that TRYP and LACK were equivalent to each other in the magnitudes of IFN-γ , TNF-α and IL-10 responses elicited , and in generating higher IFN-γ to IL-10 and TNF-α to IL-10 ratios in putatively protected cured VL and EHC+ve individuals than in active VL cases . It was of interest that in India , the asymptomatic EHC+ve group had equivalent responses to the cured VL group , whereas in our recent study [28] of the same antigens ( and antigen preparations ) in Brazil , we found that asymptomatic DTH+ve individuals had lower ratios of IFN-γ to IL-10 and TNF-α to IL-10 compared to cured VL patients . This was due to higher IL-10 responses in the DTH+ve group compared to the cured VL group , leading us to suggest that a measure of modulation of the pro-inflammatory response by IL-10 in the DTH+ve group might contribute to the protective response . In active VL disease , high levels of TNF-α contribute to fever and cachexia , and are detrimental [29] , and it is not yet known what role in pathogenesis is played by the strong 24 hour IFN-γ responses observed in whole blood assays in active VL [6] , [23] . In our analysis of novel vaccine candidates , we found that 5 antigens ( R71 , L37 , N52 , J41 and M22 ) elicited IFN-γ and TNF-α responses in a high percentage of cured VL ( 55–87 . 5% ) and EHC+ve ( 40–65% ) subjects . This represents remarkable replication of recent findings from an area endemic for L . infantum chagasi in northern Brazil , where 4 of these antigens ( R71 , L37 , N52 and M22; same preparations of peptide pools ) also elicited strong IFN-γ and TNF-α responses in both cured VL and exposed asympotmatic DTH+ individuals [28] . In Brazil , responses to J41 were only observed in the cured VL group , but the sample size for DTH+ individuals was small ( n = 4 ) . Strong responses were also observed in Brazil to two additional antigens , L302 . 06 and M18 , for which a lower percentage ( <30% ) of responders were observed in India . This may reflect small samples sizes , differences in amino acid sequences of the parasites , and/or differences in HLA alleles between the two populations . On balance , all of these antigens remain strong candidates in the context of a multivalent cross-species vaccine against leishmaniasis . R71 and L37 are ribosomal proteins with high ( 100 and 99% , respectively ) percentage identity at the amino acid level between L . major and L . infantum [28] . N52 is a V-ATPase subunit F which also has high ( 94% ) identity across the two species . J41 and M22 are hypothetical proteins of unknown function which , despite lower percent identities ( 73% and 61% , respectively ) between L . major and L . infantum , appear to provide cross-reactive epitopes that are recognised in both Brazil [28] and India . An important contrast between the two endemic regions was the almost complete lack of IL-10 responses to these novel antigens ( same preparations of peptide pools ) in the Indian study in both cured VL and EHC+ve groups , whereas in the Brazilian study cured VL subjects who were positive for IFN-γ and TNF-α responses also produced IL-10 . N52 was also unique in being the only antigen to stimulate IL-10 responses in active VL patients , suggesting that responses to this antigen might provide an important early diagnostic biomarker for disease-associated IL-10 in VL . Further studies are needed to evaluate more carefully the differences in cytokine responses to individual antigens in active compared to cured VL groups , as well as between cured VL and exposed asymptomatic DTH+ or modified Quantiferon positive groups . Unlike Brazil [4] , [5] , DTH responses have not provided a sensitive means of evaluating cell mediated immune response in cured VL or exposed individuals in India [48] , pointing to potential differences in cell-mediated responses between DTH+ compared to Quantiferon positive exposed asymptomatic individuals that might hold the key to uncovering the true correlates of vaccine-induced immunity in leishmaniasis . Results of our study demonstrate that only a percentage of individuals respond to vaccine antigens that have individually been shown to be protective in mice . This suggests that defined vaccine for use in humans will need to be complex multi-epitope/antigens vaccines . To date , only one multicomponent vaccine , Leish-111f , has been assessed in a large clinical trial [49] . Our recent small-scale clinical trial in a L . donovani endemic area showed Leish-F1-MPL-SE was safe and well tolerated in people with and without prior VL exposure and induced strong antigen-specific T cell responses [36] . The data presented here , and in our earlier study from Brazil [28] , provide evidence to support a number of novel candidates that could be taken forward as vaccines against human leishmaniasis .
|
Visceral leishmaniasis is a parasitic infection that results in death in susceptible people unless they are treated . Current drugs are expensive and toxic , and there are no vaccines in use in humans . We know that it is possible to become immune to infection with this parasite because people who have been cured using drug treatment are resistant to further infection . In addition , a large percentage of people infected with the parasite remain asymptomatic and develop a specific immune response that can be measured using crude leishmanial antigens . We hypothesized that these resistant people might hold the key to understanding the kind of immune response required for protection . In this paper we compared the immune response to a series of novel vaccine candidates in people with active disease , in those drug-cured from the disease , and in the naturally resistant individuals . We show that immune individuals make strong cytokine responses to five of eleven novel vaccine candidates that were tested , making them ideal candidates to take forward in the development of a defined vaccine against leishmaniasis .
|
[
"Abstract",
"Introduction",
"Materials",
"and",
"Methods",
"Results",
"Discussion"
] |
[
"medicine",
"infectious",
"diseases",
"neglected",
"tropical",
"diseases",
"immunology",
"biology",
"parasitic",
"diseases"
] |
2012
|
Cytokine Responses to Novel Antigens in an Indian Population Living in an Area Endemic for Visceral Leishmaniasis
|
Chromosome inheritance during sexual reproduction relies on deliberate induction of double-strand DNA breaks ( DSBs ) and repair of a subset of these breaks as interhomolog crossovers ( COs ) . Here we provide a direct demonstration , based on our analysis of rad-50 mutants , that the meiotic program in Caenorhabditis elegans involves both acquisition and loss of a specialized mode of double-strand break repair ( DSBR ) . In premeiotic germ cells , RAD-50 is not required to load strand-exchange protein RAD-51 at sites of spontaneous or ionizing radiation ( IR ) -induced DSBs . A specialized meiotic DSBR mode is engaged at the onset of meiotic prophase , coincident with assembly of meiotic chromosome axis structures . This meiotic DSBR mode is characterized both by dependence on RAD-50 for rapid accumulation of RAD-51 at DSB sites and by competence for converting DSBs into interhomolog COs . At the mid-pachytene to late pachytene transition , germ cells undergo an abrupt release from the meiotic DSBR mode , characterized by reversion to RAD-50-independent loading of RAD-51 and loss of competence to convert DSBs into interhomolog COs . This transition in DSBR mode is dependent on MAP kinase-triggered prophase progression and coincides temporally with a major remodeling of chromosome architecture . We propose that at least two developmentally programmed switches in DSBR mode , likely conferred by changes in chromosome architecture , operate in the C . elegans germ line to allow formation of meiotic crossovers without jeopardizing genomic integrity . Our data further suggest that meiotic cohesin component REC-8 may play a role in limiting the activity of SPO-11 in generating meiotic DSBs and that RAD-50 may function in counteracting this inhibition .
Faithful inheritance of chromosomes during meiosis relies on crossover ( CO ) recombination events between the DNA molecules of homologous chromosomes . Interhomolog COs underpin the formation of chiasmata that temporarily link homologs and allow them to orient and segregate toward opposite poles of the meiosis I spindle [1] . This requirement for crossovers to ensure homolog segregation poses a challenge for sexually reproducing organisms , however , as meiotic recombination is initiated by formation of double-strand DNA breaks ( DSBs ) [2] , lesions that constitute a danger to genomic integrity in other contexts . Thus , it is crucial that germ cells possess mechanisms not only for converting a subset of meiotic DSBs into interhomolog COs but also for limiting the number of DSBs formed and for repairing any excess DSBs prior to the meiotic cell divisions . As interhomolog COs are rare during mitotic cell cycles , the need for specialized features that promote crossing over between homologs during meiosis has long been apparent . Consequently , research in a variety of experimental systems has yielded substantial knowledge regarding components of the machinery and mechanisms involved in promoting meiotic crossing over . However , relatively little attention has been focused on the importance of mechanisms that can constrain the activity of Spo11 , the DSB-forming endonuclease [2] . Likewise , the idea that germ cells might possess mechanisms to inactivate features of the meiotic recombination program that serve as impediments to DSB repair ( DSBR ) has not been widely articulated . Although we had previously proposed that distinct modes of DSBR might operate during different stages of meiotic prophase in C . elegans to ensure restoration of intact chromosomes [3 , 4] , the prior evidence for this assertion was indirect and largely circumstantial . In the current work , we now provide a direct demonstration that the meiotic program in C . elegans germ cells involves both acquisition and loss of a specialized mode of DSBR during meiotic prophase progression . This conclusion emerged during the course of analyzing DNA damage responses in mutants defective in rad-50 , which encodes a component of the conserved Mre11/Rad50 complex that has been implicated in numerous aspects of both meiotic recombination programs and the DNA damage response in mitotically dividing cells [5–8] . The spatial organization of the C . elegans germ line was instrumental in this analysis . The fact that germ cells undergoing mitotic proliferation and germ cells entering and progressing through meiotic prophase are arranged in a temporal/spatial gradient along the distal-proximal axis of the gonad enabled simultaneous visualization of responses to DNA damage in germ cells at all stages of meiotic prophase . Further , this organization also enabled us to perform a “reverse time course” analysis in which we assessed outcomes for germ cells that were at progressively earlier stages of meiotic prophase at the time of exposure to an acute break-inducing treatment . Our analysis shows that germ cells switch abruptly to a specialized meiotic mode of DSBR at the onset of meiotic prophase , visualized cytologically as acquisition of a requirement for RAD-50 to allow rapid accumulation of DNA strand exchange protein RAD-51 at DSB sites . Moreover , we show that germ cells undergo a second developmentally-programmed switch in DSBR mode as they pass through a MAP kinase-dependent transition from the mid-pachytene to late pachytene stage of meiotic prophase [9] . This second switch is characterized by loss of RAD-50 dependence for RAD-51 loading and by loss of competence to convert DSBs into interhomolog COs . Each of these switches coincides temporally with a major remodeling of chromosome architecture [10–12] , supporting the view that specialized aspects of the meiotic DSBR program are imposed or enforced by meiosis-specific differentiation of chromosome axis structures . Further , we also provide evidence suggesting that meiosis-specific cohesins may play an inhibitory role that limits the formation of meiotic DSBs . Together these features help to explain how germ cells are able to balance the imperative to generate recombination-based linkages that ensure chromosome inheritance with the imperative to preserve the integrity of their genomes .
The rad-50 gene encodes the C . elegans ortholog of eukaryotic Rad50 and bacterial SbcC . Based on the structure of its orthologs , the N- and C-terminal domains of RAD-50 are predicted to comprise a bipartite ABC-type ATPase domain , with the intervening portion of the protein forming an extended intramolecular α-helical coiled-coil and a zinc-coordinating “hook” dimerization motif located at the end of the coiled-coil distant from the ATPase domain [13–15]; this structural organization is similar to that of the SMC components of the condensin and cohesin complexes [16] . RAD-50 associates with conserved SbcD nuclease-domain protein MRE-11 [17] , and complexes containing their orthologs have demonstrated endonuclease , exonuclease , DNA unwinding , and end-tethering activities in vitro [5–8] . The rad-50 ( ok197 ) allele contains a 1 , 517 bp deletion that removes the first 1 , 065 bp of coding sequence plus 124 bp immediately upstream of the predicted initiation codon . As this deletion eliminates the exons encoding the entire N-terminal portion of the ATPase domain ( including the Walker A box ) and about one-third of the N-terminal segment of the coiled-coil domain ( which interacts with MRE-11 ) , rad-50 ( ok197 ) is predicted to be a null allele . Homozygous rad-50 mutant hermaphrodites from heterozygous ( rad-50/+ ) mothers are viable but exhibit a set of phenotypes characteristic of mutants defective in meiotic recombination , similar to those previously reported for C . elegans mre-11 mutants [18] . They produce 98 . 4% dead embryos ( mainly reflecting aneuploidy resulting from autosomal missegregation ) and a high incidence of XO males among the surviving progeny ( the “Him” phenotype , reflecting X chromosome missegregation ) ( Table 1 ) . Further , cytological examination of oocyte nuclei at diakinesis ( the last stage of meiotic prophase ) indicates that this chromosome segregation defect results from a lack of chiasmata connecting homologous chromosomes ( Figure 1 ) , presumably reflecting a failure to form interhomolog crossovers . DAPI staining , immunofluorescence , and fluorescence in situ hybridization ( FISH ) experiments revealed apparently normal pairing and synapsis of homologous chromosomes in rad-50 mutant germ lines . As in wild-type meiosis [11] , chromosome axis protein HIM-3 and synaptonemal complex ( SC ) central region protein SYP-1 colocalized at the interface between parallel-aligned DAPI tracks in pachytene nuclei of rad-50 mutants , indicating successful assembly of the SC ( Figure 1 ) . Further , we detected a single focus or two closely-spaced foci in pachytene nuclei both in FISH experiments assessing pairing at the 5S rDNA locus on chromosome V ( Figure S1 ) and in experiments assessing pairing at the pairing center ( PC ) domain of the X chromosomes ( by immunofluorescence of PC-binding protein HIM-8 [19 , 20]; Figure 1 ) . The success of homologous pairing and synapsis indicates that the defect in chiasma formation in rad-50 mutants most likely results from a defect in the process of recombination per se . Immunostaining for DNA strand exchange protein RAD-51 [3 , 21] revealed abnormalities in rad-50 mutant germ lines . First , rad-50 mutants exhibited severely reduced levels of SPO-11-dependent meiotic RAD-51 foci ( Figure 2A and 2B ) . We quantified the number of foci stained with RAD-51 antibody in premeiotic germ cells and in germ cells entering and progressing through meiotic prophase . In wild-type control germ lines , levels of RAD-51 foci rose following entry into meiotic prophase and peaked in the early to mid-pachytene stage . Numbers of RAD-51 foci were greatly reduced in nuclei at the corresponding stages of meiotic prophase in rad-50 mutants , paralleling previous reports of reduced RAD-51 foci in mre-11 mutants [21] . This reduction in meiotic prophase RAD-51 foci indicates either that meiotic DSB formation is reduced in rad-50 mutants or that RAD-50 is required to accumulate RAD-51 at meiotic DSBs . Second , rad-50 mutants exhibited elevated levels of SPO-11-independent RAD-51 foci ( Figure 2B ) . Although levels of RAD-51 foci in meiotic prophase nuclei were severely reduced in the rad-50 mutant , residual levels of RAD-51 foci were higher than in spo-11 mutant germ lines ( which lack meiotic DSBs [3 , 22] ) , and numbers of foci in premeiotic nuclei were elevated compared to either wild-type or spo-11 controls . spo-11; rad-50 double mutant germ lines exhibited RAD-51 focus profiles similar to those of the rad-50 single mutant , indicating that most ( if not all ) of the RAD-51 foci observed in rad-50 mutants were SPO-11-independent in origin ( Figure 2B ) . Further , the SPO-11-independent foci observed both in the premeiotic and meiotic prophase regions of rad-50 and spo-11; rad-50 mutant germ lines appeared larger and brighter than either the SPO-11-dependent foci or premeiotic foci observed in controls ( Figure 2C and unpublished data ) . These bright SPO-11-independent RAD-51 foci likely represent spontaneous DNA breaks and/or single-strand gaps that arose during the course of DNA replication; their presence suggests that RAD-50 is not required to load RAD-51 at lesions incurred in premeiotic nuclei . Further , the SPO-11-independent RAD-51 foci observed in meiotic prophase nuclei likely represent persistence of unrepaired breaks that occurred prior to meiotic prophase entry . Consistent with the presence of unrepaired DSBs , the rad-50 mutant exhibited elevated levels of apoptosis in the late pachytene region of the germ line , where the pachytene DNA damage checkpoint operates to cull nuclei with persistent DNA damage [23] . Using Nomarski differential interference contrast ( DIC ) microscopy to score apoptosis in adult ( 24–28 h post L4 ) germ lines [24] , we observed an average of 4 . 5 apoptotic nuclei per gonad arm in rad-50 ( ok197 ) mutants ( n = 24 gonad arms ) , compared with an average of 1 . 1 apoptotic nuclei per gonad arm in wild-type controls ( n = 21 gonad arms ) ( p < 0 . 0001 for Mann-Whitney test ) . Experiments aimed at assessing the response of rad-50 mutants to ionizing radiation ( IR ) unexpectedly revealed that C . elegans germ cells switch abruptly between RAD-50-independent and RAD-50-dependent modes of accumulation of RAD-51 at DNA break sites as they enter and progress through meiotic prophase . To focus on IR-induced breaks in the absence of endogenous meiotic breaks , we exposed spo-11 control and spo-11; rad-50 double mutant worms to 1 , 000 rad γ-irradiation and dissected and fixed their gonads 1 h post irradiation . Immunostaining revealed abundant RAD-51 foci in nuclei throughout the germ lines of irradiated spo-11 single mutant controls and irradiated wild-type worms ( Figures 3 and S2 ) , indicating that premeiotic germ cells and germ cells at all stages of meiotic prophase are capable of installing RAD-51 onto chromosomes , presumably at break sites . Similar to these controls , the germ lines of spo-11; rad-50 mutant worms also exhibited abundant IR-induced RAD-51 foci both in the premeiotic region and in the region containing nuclei from late pachytene through diakinesis stages of meiotic prophase ( Figure 3 ) . In contrast to controls , however , irradiated spo-11; rad-50 double mutant germ lines contained a region extending from the transition zone ( where nuclei enter meiotic prophase ) through mid-pachytene in which most nuclei were devoid of RAD-51 foci; within this region , germ lines appeared similar to the corresponding regions of unirradiated spo-11; rad-50 controls ( i . e . , with a subset of nuclei containing 1–2 bright spontaneous RAD-51 foci ) . An identical “dark zone” lacking IR-induced RAD-51 foci was also seen in the germ lines of rad-50 and mre-11 single mutant worms exposed to 1 krad γ-irradiation ( Figures 4 and S2 ) ; similar observations for the mre-11 mutant were also made in an independent study ( A . Penkner and J . Loidl , personal communication . ) . Further , the contrast between the “dark zone” and regions with abundant IR-induced RAD-51 foci was even more pronounced following exposure of rad-50 mutants to a 5 krad dose ( Figure S3 ) . Interestingly , the region of the germ line where IR-induced foci were lacking in irradiated spo-11; rad-50 and rad-50 worms corresponds to the region where meiotic RAD-51 foci are most abundant in unirradiated wild-type germ lines ( Figures 2A and 4; [3] ) . We will operationally use the term “RAD-51 loading” to refer to the rapid formation of RAD-51 foci following break-inducing treatment . Although both association and dissociation of RAD-51 subunits will contribute to the immunofluorescence signals observed , evidence presented below supports the interpretation that slow/delayed formation of RAD-51 foci , rather than accelerated turnover of RAD-51-containing complexes , is responsible for the lack of IR-induced RAD-51 foci in germ cells within the “dark zone” of rad-50 mutant gonads . Simultaneous immunolocalization of RAD-51 and meiotic chromosome structural proteins in the distal germ lines of IR-treated rad-50 worms demonstrated that a switch from RAD-50 independence to RAD-50 dependence for RAD-51 loading occurs at the onset of meiotic prophase . The earliest marker of meiotic prophase is concentration of HTP-3 protein onto nascent chromosome axis structures [19] , first detected as discontinuous stretches and then as continuous bright lines . Whereas IR-induced RAD-51 foci were abundant in premeiotic nuclei ( which exhibited diffuse HTP-3 staining on chromatin ) , there was an abrupt transition to a RAD-51-negative state in nuclei that had begun to acquire meiotic organization of HTP-3 structures ( Figure 4A ) . Similar results were obtained in experiments imaging RAD-51 together with SYP-1 , which assembles onto chromosomes following initial assembly of chromosome axes [11] . IR-induced RAD-51 foci were abundant in premeiotic nuclei lacking SYP-1 immunofluorescence ( IF ) signals , but were lacking in nuclei in which SYP-1 was extensively associated with chromosomes ( Figure 4B ) . Together these results indicate that entry into meiotic prophase is accompanied by imposition of a requirement for RAD-50 to allow rapid accumulation of RAD-51 at sites of DNA breaks . A second transition , in which nuclei revert to RAD-50-independence for loading of RAD-51 , is observed as nuclei progress from mid-pachytene to late pachytene regions of the germ line ( Figures 3 and 4C ) . Previous work showed that progression from mid to late pachytene requires a MAP kinase-dependent signaling event , visualized cytologically as a transient rise in the activated , diphosphorylated form of MAP kinase [9 , 25] . In wild-type germ lines , this peak in activated MAP kinase is found in a position just proximal to the zone in which SPO-11-dependent meiotic RAD-51 foci gradually decline in numbers , presumably reflecting progression of meiotic recombination ( Figure 4C ) . The peak of activated MAP kinase was found in a similar position in the germ lines of irradiated rad-50 mutants ( Figure 4C ) , indicating that activation of MAP kinase in this context does not require RAD-50 . Moreover , the position of the peak is just distal to the abrupt transition to high levels of IR-induced RAD-51 foci . Further , the germ lines of irradiated mpk-1 ( ga111ts ) ; rad-50 double mutants , in which meiotic prophase progression was arrested at the mid-pachytene stage , did not exhibit a rise in levels of IR-induced RAD-51 foci in the corresponding region ( Figure S4 ) . Together these data indicate that reversion to a RAD-50-independent mode of RAD-51 loading requires MAP kinase-dependent developmental progression from the mid-pachytene to late pachytene stage . We will use the term “constrained region” to refer to the region of the germ line , extending from the onset of meiotic prophase to the mid-pachytene to late pachytene transition , in which germ cells exhibit the requirement for RAD-50 to achieve rapid accumulation of RAD-51 . Examination of spo-11; rad-50 germ lines that were fixed at additional time points ( 3 , 6 and 12 h ) after irradiation supports the interpretation that the dearth of IR-induced RAD-51 foci observed in the constrained region of spo-11; rad-50 germ lines ( and rad-50 or mre-11 germ lines ) is indicative of a prolonged delay in and/or severely reduced rate of accumulation of RAD-51 at break sites . At both the 3 h and 6 h post-irradiation time points , we continued to observe a robust RAD-51-dark zone in the central portion of spo-11; rad-50 mutant germ lines , indicating that IR-induced RAD-51 focus formation remained strongly inhibited in germ cells within this region ( Figure 5 ) . By 12 h post irradiation , however , a clear RAD-51-dark zone was no longer visible . At this 12 h time point , many transition zone nuclei and some early pachytene nuclei contained multiple bright RAD-51 signals ( Figure S5 ) ; these bright signals reflect persistence of preassembled RAD-51 foci in nuclei that had been in the premeiotic region at the time of irradiation ( [26]; S . Mlynarczyk-Evans and A . Villeneuve , unpublished data ) . Further , we also observed some smaller/less intense RAD-51 foci in the majority of nuclei within the mid-pachytene region of these germ lines ( Figures 5 , S5 , and S6B ) ; this eventual rise in RAD-51 foci in the mid-pachytene region cannot be explained by movement and developmental progression of nuclei with pre-installed foci , as most nuclei within the mid-pachytene region at the 12 h time point had entered meiotic prophase prior to the time of irradiation ( [26]; S . Mlynarczyk-Evans and A . Villeneuve , unpublished data ) . These observations strongly suggest that installation of RAD-51 at DSB sites in nuclei within the constrained region of rad-50 mutant germ lines is severely delayed and/or occurs at a substantially reduced rate . Moreover , they argue against the alternative interpretation that failure to detect IR-induced RAD-51 foci in the constrained region is consequence of accelerated turnover of RAD-51-containing complexes . We previously showed that IR-induced DSBs can bypass the requirement for SPO-11 in initiating meiotic recombination , leading to formation of crossovers and functional chiasmata in spo-11 mutants [22 , 27] . In these prior experiments , the ability of IR-induced breaks to form chiasmata was assessed by examining diakinesis-stage oocytes 18 hrs following irradiation; based on a recent temporal analysis of meiotic prophase progression [26] , we infer that the oocytes scored had been in the mid-pachytene stage at the time of irradiation . To assess whether the transition from mid to late pachytene affects the ability to convert breaks into chiasmata , we performed a “reverse time course analysis” in which we assessed the efficacy for chiasma formation of breaks induced by IR at several time points spanning this transition , ranging from 18 to 12 h prior to fixation for scoring at late diakinesis ( Table 2 ) . Chiasmata were efficiently generated by IR delivered at the mid-pachytene time point ( 18 h ) ; an average of 6 . 5 DAPI-stained bodies were detected , indicating that all six chromosome pairs were linked by chiasmata in most nuclei . In contrast , IR breaks introduced at the late pachytene time point ( 12 h ) were almost completely ineffective at triggering chiasma formation; an average of 11 . 4 DAPI-stained bodies were detected , similar to the 11 . 5 average seen in the unirradiated control . Further , a bimodal distribution in the numbers of DAPI-stained bodies per nucleus was evident at all time points , suggesting that germ cells undergo an abrupt transition between chiasma-competent and chiasma-incompetent states at the mid-pachytene to late pachytene transition . As the onset of the requirement for RAD-50 to load RAD-51 at IR-induced breaks coincides with assembly of meiosis-specific chromosome structures , we tested whether loss of components of these structures might eliminate or mitigate this requirement . First , we found that loss of SC central region proteins does not alleviate this requirement . The overall RAD-51 IF pattern in both unirradiated and irradiated rad-50 syp-1 germ lines appeared very similar to rad-50 single mutant counterparts ( Figure 6; unpublished data ) . The one notable difference was that the size of the zone of late pachytene nuclei exhibiting RAD-50-independent RAD-51 loading was reduced in the rad-50 syp-1 double mutant; the transition to the RAD-50-independent mode correlated with exit from the persistent state of chromosome clustering characteristic of syp-1 mutants [11] . In contrast , we found that RAD-50 dependence within the constrained region was partially abrogated in both him-3; rad-50 and htp-1; rad-50 double mutants ( Figures 6 and S3 ) . HIM-3 and HTP-1 are two of four C . elegans paralogs of the meiosis-enriched HORMA domain protein family that also includes Saccharomyces cerevisiae Hop1 and Arabidpopsis Asy1 and Asy2 [4 , 10 , 28–31] . Both proteins localize to meiotic chromosome axes prior to SC assembly and persist in association with chromosome axes after SC disassembly , and both have been hypothesized to play roles in inhibiting use of the sister chromatid as a DSBR partner during meiotic prophase ( [4 , 10 , 12 , 30]; E . Martinez-Perez , A . Dernburg and A . Villeneuve , unpublished data ) . In the absence of irradiation , RAD-51 IF patterns in him-3; rad-50 and htp-1; rad-50 germ lines appeared similar to that of the rad-50 single mutant ( unpublished data ) . Following IR treatment , however , we observed RAD-51 IF patterns in htp-1; rad-50 and him-3; rad-50 mutant germ lines that were intermediate in appearance between those of irradiated htp-1 or him-3 single mutants and those observed in irradiated rad-50 single mutants . Whereas over 120 rad-50 single mutant gonads examined invariably exhibited a robust inhibition of IR-induced RAD-51 foci throughout the constrained region ( extending from the zone of meiotic entry through the mid-to-late pachytene transition ) , IR-induced RAD-51 foci were frequently detected in nuclei within the constrained region in htp-1; rad-50 mutant germ lines . In 35% of htp-1; rad-50 gonads examined following a 1 krad IR treatment ( n = 26; p < 0 . 0001 ) and in 97% of htp-1; rad-50 gonads examined following a 5 krad IR treatment ( n = 32; p < 0 . 0001 ) , we detected IR-induced RAD-51 foci in nuclei throughout most or all of the mid-pachytene region ( Figures 6 and S3 ) . In contrast to htp-1 single mutants , however , all htp-1; rad-50 gonads contained at least a small domain of transition zone and/or early pachytene nuclei in which IR-induced RAD-51 foci were strongly inhibited ( Figure S3 ) . Similarly , 36% of him-3; rad-50 gonads exposed to 1 krad IR treatment clearly exhibited IR-induced RAD-51 foci within the constrained region ( n = 50; p < 0 . 0001 ) . However , the altered pattern observed in him-3; rad-50 gonads differed from that seen in htp-1; rad-50 gonads in that when IR-induced RAD-51 foci were detected within the constrained region , they were present in nuclei throughout the entire region . In both cases , the IR-induced foci within the constrained region appeared smaller and/or less intense than those in either the premeiotic region or in late pachytene , suggesting that RAD-51 loading was slower and/or occurred over more limited stretches . The fact that RAD-50 dependence is only partially abrogated in him-3 or htp-1 mutant backgrounds may be a consequence of partial redundancy among the meiosis-enrich HORMA domain proteins , as all four C . elegans paralogs show similar localization to meiotic chromosomes ( [4 , 10 , 19 , 30]; E . Martinez-Perez , A . Dernburg and A . Villeneuve , unpublished data ) . Partial alleviation of the requirement for RAD-50 within the constrained region in these double mutants strongly suggests that proteins associated with meiosis-specific chromosome axis structure play a role in imposing this requirement . Further , the pattern of IR-induced foci observed in the htp-1; rad-50 double mutants suggests that germ cells lacking HTP-1 can at least partially engage the meiotic DSBR program at the onset of meiotic prophase but then undergo a premature release from the constraints that make rapid accumulation of RAD-51 dependent on RAD-50 . Interestingly , this finding and interpretation parallels the previously proposed hypothesis that HTP-1 is required to prevent premature release from meiotic prophase constraints that inhibit use of sister chromatids as meiotic recombination partners [4] . In light of our finding that RAD-50 is required within the constrained region for normal accumulation of RAD-51 at DSB sites , it was necessary to revisit the question of whether RAD-50 is also required for meiotic DSB formation . Collectively , the data reported in this section suggest that although RAD-50 likely plays a role in promoting normal levels of meiotic DSB formation , it is not strictly required for SPO-11 to be active in generating DSBs . Several lines of evidence support the conclusion that SPO-11dependent DSB formation is reduced in rad-50 mutants . First , we did not observe a rise in abundance of RAD-51 foci in late pachytene or diplotene nuclei in unirradiated rad-50 , rad-50 syp-1 , him-3; rad-50 or htp-1; rad-50 germ lines ( Figure 2; unpublished data ) ; such a rise might have been expected following the transition to late pachytene if chromosomes had experienced SPO-11-generated breaks during earlier prophase . Second , analysis of rad-51; rad-50 double mutants also suggests that meiotic DSBs are reduced in number in rad-50 mutants . The rad-50 mutation suppresses the embryonic lethality of a rad-51 mutant [21] ( Table 1 ) : whereas rad-51 mutant hermaphrodites produced no viable embryos ( n = 4 , 169 ) , rad-51; rad-50 hermaphrodites produced 1% viable progeny ( n = 3 , 055 ) , similar to rad-50 single mutants . Most progeny lethality associated with the rad-50 mutation can be explained as a consequence of aneuploidy resulting from meiotic missegregation , whereas the complete lethality of the rad-51 progeny is thought to be a combined consequence of both missegregation and failed and/or defective repair of meiotic DSBs [21 , 32]; thus suppression of rad-51 progeny lethality by the rad-50 mutation suggests that meiotic DSBs are diminished in number by the rad-50 mutation . Similarly , the rad-50 mutation also suppresses cytological correlates of DSB formation visible in diakinesis-stage oocytes of rad-51 mutants ( Figure 7 ) . Aggregated , poorly condensed chromatin masses are frequently observed in diakinesis-stage oocytes in rad-51 mutant and in rad-51 ( RNAi ) worms [21 , 33 , 34]; this pathology is apparently a consequence of defective repair of meiotic DSBs , as it is suppressed by a spo-11 mutation . The rad-51 aggregated chromatin phenotype is similarly suppressed by the rad-50 mutation , as distinct univalents are seen in rad-51; rad-50 diakinesis nuclei . Although suppression of the rad-51 defects by the rad-50 mutation is most simply explained by a reduction in meiotic DSBs , suppression is also consistent with the rad-50 mutation allowing use of alternative repair pathways and/or preventing entry of DSBs into a pathological dead-end pathway . This alternative explanation seems less likely to account for the above-mentioned lack of a late-prophase rise in RAD-51 foci in most unirradiated rad-50 single and double mutants , however , given that RAD-51 protein is present and can eventually be loaded at IR-induced DSBs incurred during early meiotic prophase ( albeit with a substantial delay ) . Thus , taken together these observations suggest that SPO-11dependent DSB formation may be abrogated in rad-50 mutants . Despite this evidence supporting a role for RAD-50 in promoting meiotic DSB formation , however , analysis of rec-8 ( ok978 ) ; rad-50 double mutant germ lines provided compelling evidence that SPO-11-dependent meiotic DSBs can nevertheless be formed in the absence of functional RAD-50 . rec-8 encodes a meiosis-enriched α-kleisin subunit of cohesin [16 , 35] , and the rec-8 ( ok978 ) mutation carries a deletion that is predicted to severely reduce or eliminate rec-8 function . Meiotic prophase nuclei in the germ lines of unirradiated rec-8 ( ok978 ) single mutant worms exhibited highly elevated levels of RAD-51 foci that persisted through late pachytene , diplotene and early diakinesis stages ( Figure 8A ) , as seen previously for rec-8 RNAi and rec-8 ( cosuppression ) worms [21] . Several observations clearly indicate that SPO-11-dependent meiotic DSBs are formed in rec-8; rad-50 double mutant germ cells . First , whereas RAD-51 immunostaining in rec-8; rad-50 germ lines appeared similar to that in rad-50 and spo-11; rad-50 throughout most of meiotic prophase ( i . e . , with a subset of nuclei exhibiting one or a few bright foci and most nuclei lacking foci ) , there was a sharp rise in abundance of RAD-51 foci at late pachytene in rec-8; rad-50 germ lines , and foci persisted at high levels through diplotene and early diakinesis stages ( Figure 8A and 8B ) . This late pachytene rise is SPO-11 dependent , as it does not occur in spo-11 rec-8; rad-50 triple mutants . Second , diakinesis nuclei in rec-8; rad-50 mutants exhibited severely fragmented chromosomes and highly abnormal chromosome morphology ( Figure 8B ) . This fragmentation reflects the presence of SPO-11-dependent DSBs , as it is abolished in spo-11 rec-8; rad-50 triple mutants . Third , whereas rec-8; rad-50 mutant hermaphrodites do not produce any viable offspring , spo-11 rec-8; rad-50 hermaphrodites do produce significant numbers of viable offspring ( Table 1 ) . Together these findings demonstrate that formation of SPO-11-dependent DSBs does not strictly require RAD-50 , at least in the context of the rec-8 mutant background . These findings were corroborated by analysis of a rec-8; mre-11 double mutant , which also exhibited both a sharp rise in and persistence of RAD-51 foci in late prophase and fragmented chromosomes at diakinesis ( unpublished data ) . Further , an independent study similarly found evidence that MRE-11 is dispensable for DSB formation in the context of compromised cohesin ( Y . Mamnun , A . Baudrimont , V . Jantsch and J . Loidl , personal communication ) . REC-8 protein is detected cytologically in nuclei throughout the distal premeiotic region of the germ line [35 , 36] , although the significance of this premeiotic localization has not been understood . In the course of this analysis , we observed that in addition to exhibiting high levels of meiotic RAD-51 foci , rec-8 single mutants also exhibited significantly elevated levels of RAD-51 foci in premeiotic germ cells ( Figure 8C ) . This elevation was observed within the distal-most 15 rows of germ cells , most of which are actively undergoing mitotic cell cycles [37 , 38] . This finding suggests that REC-8 may function in germ cells even prior to the transition to the meiotic mode of DNA replication [26] .
Our analysis has identified roles for C . elegans RAD-50 in multiple events required for genome stability and chromosome inheritance , during germ cell proliferation , within the context of meiotic recombination , and following exit from the meiotic DSB repair mode in late prophase ( see below ) . First , a requirement for RAD-50 is evident in the distal ( premeiotic ) region of the germ line , where germ cells are undergoing mitotic proliferation , as rad-50 mutants exhibit an elevated incidence of RAD-51 foci in this region . Further , these spo-11-independent RAD-51 foci are brighter than meiotic RAD-51 foci and persist as germ cells enter and progress through the meiotic program . These findings suggest that RAD-50 plays a role in repairing and/or preventing accumulation of DSBs and/or single-stranded DNA during mitotic proliferation , a role that may reflect the previously-demonstrated requirement for C . elegans MRE-11 to recruit DNA damage response proteins ATR , RPA and BARD1 ( but not RAD-51 ) to sites of IR-induced DSBs in proliferating germ cells [39 , 40] . Second , RAD-50 appears to play several distinct roles in promoting the formation of interhomolog crossovers during the meiotic recombination program . During the “constrained” portion of meiotic prophase , RAD-50 is required for rapid accumulation of RAD-51 at sites of DSBs . This requirement likely reflects a role for the MRE-11/RAD-50 complex in promoting DSB resection in this context . Unresected meiotic DSBs accumulate in rad50s and mre11s ( separation of function ) mutants in S . cerevisiae [41 , 42] , and because Spo11 is found covalently attached to the 5′ overhang at DSBs in these mutants [43] , it has been proposed that the requirement for Mre11/Rad50 in DSB resection reflects a requirement for removing Spo11p from DNA ends . A role for Mre11/Rad50 in Spo11 removal was further demonstrated by the recent identification of covalently-linked Spo11-oligonucleotide complexes in wild-type meiosis that are both dependent on Mre11/Rad50 and structurally consistent with expectations for products of its demonstrated endonuclease activity [44]; however , these studies left open the question of whether Mre11/Rad50 might also be required to process recombination intermediates after Spo11 removal . Our demonstration that RAD-50 is required for rapid formation of RAD-51 foci at IR-induced breaks during the period when the meiotic mode of DSBR is engaged strongly supports a role for RAD-50 in DSBR during meiosis beyond removal of SPO-11 from DSB ends , likely in promoting continued end resection . Further , whereas our analysis of rec-8; rad-50 mutants clearly demonstrates that RAD-50 is not strictly required for SPO-11-dependent meiotic DSB-forming activity , multiple other data suggest that RAD-50 likely does normally play a role in promoting meiotic DSB formation . Rescue of rad-51-associated diakinesis chromosome morphology and progeny lethality in rad-51; rad-50 double mutants as well as the absence of a late prophase rise in RAD-51 foci and the intact appearance of diakinesis univalents in unirradiated him-3; rad-50 and rad-50 syp-1 double mutants are most readily explained as reflections of a substantial reduction in DSB formation in the absence of RAD-50 , and consequently as evidence that RAD-50 does play a role in promoting meiotic DSB formation in C . elegans . A requirement for Mre11/Rad50 at the DSB step is clearly not a universal feature of the meiotic program , however . Although such a requirement is well-documented in S . cerevisiae [2] , no such requirement exists in S . pombe ( where persistent meiotic DSBs in rad50Δ mutants are detected by gel assays [45] ) , in Arabidopsis ( where loss of Mre11 results in Spo11-dependent chromosome fragmentation [46] ) , or in Drosophila ( where persistent γHis2Av foci are detected in a rad50 mutant [47] ) . Moreover , even in S . cerevisiae , Mre11 and Rad50 are present in a protein complex that is distinct from the complexes that contain Spo11 or several non-conserved proteins required for DSB formation [48–50] . Consequently , the reason for the requirement for Mre11/Rad50 in DSB induction has remained largely mysterious . Our finding that an apparent requirement for C . elegans RAD-50 in meiotic DSB formation is mitigated in a rec-8 mutant background provides new framework for thinking about this issue . Our observations can be reconciled in the context of a model proposing that REC-8 and RAD-50 promote counterbalancing influences on chromosome structure that create an environment in which regulated DSB formation can occur . Very high levels of RAD-51 foci are observed in the rec-8 mutant immediately after entry into meiotic prophase ( [21]; unpublished data ) , raising the possibility that in addition to promoting normal/timely repair of meiotic DSBs , REC-8 may also play an inhibitory role that limits the activity of SPO-11 in DSB formation . In one version of this model , RAD-50 would play a role in counteracting the inhibitory effects of REC-8 , perhaps through local action at DSB sites; in the absence of the REC-8 inhibitory effect , the requirement for RAD-50 would be ( at least partially ) alleviated . An implicit assumption of this scenario is that the SPO-11-dependent DSBs detected as RAD-51 foci and chromosome fragments in late prophase in rec-8; rad-50 germ lines were formed during early prophase ( but were not detected because the meiotic requirement for RAD-50 to load RAD-51 is still functional in the rec-8 mutant background [unpublished data] ) . An alternative possibility is that the late foci and breaks in the rec-8; rad-50 mutant might instead reflect abnormally late activity of SPO-11 in the double mutant . This alternative scenario would also imply a role for REC-8 in inhibiting SPO-11-dependent DSB formation , in this case in preventing DSB formation from occurring during late prophase , within a context in which RAD-50 is no longer required to promote SPO-11 activity . In light of the former model , we are intrigued by the possibility that the requirement for Mre11/Rad50 for meiotic DSB formation in budding yeast might similarly reflect a role in counteracting an inhibitory effect of Rec8 . Although this possibility has not been investigated , it is interesting to note that chromatin IP experiments have revealed a negative correlation between cohesin binding sites and meiotic DSB sites [51 , 52] . Our data provide evidence for one additional role for RAD-50 in C . elegans germ cells as they complete prophase and restructure their chromosomes in preparation for the meiotic divisions . Specifically , the fragmented late diakinesis chromosomes and complete progeny lethality observed in rec-8; rad-50 double mutants indicate that RAD-50 is also required to restore chromosome integrity even after germ cells have undergone a switch to a “post-meiotic” DNA repair mode at the mid-pachytene to late pachytene transition , at least in the context of high levels of breaks and/or altered relationships between sister chromatids . It has long been appreciated that the dependence of meiotic chromosome segregation on interhomolog crossovers requires both ( 1 ) an ability to generate meiotic DSBs to serve as initiating events and ( 2 ) acquisition of a specialized mode of DSBR that promotes conversion of a subset of DSBs into interhomolog crossovers . Meiotic specializations include mechanisms for inhibiting sister-directed repair as well as recruitment of meiosis-specific recombination proteins that promote the crossover outcome . We had previously proposed that meiotic cells might also possess an “exit strategy” involving a late prophase release from the constraints imposed by the meiotic mode of DSBR and reversion to a default DSBR mode as a means to ensure restoration of intact chromosomes prior to the meiotic divisions [3 , 4] . A similar idea was suggested by Mahadevaiah et al . [53] to explain the disappearance of DSB-associated markers in chromosome regions undergoing heterosynapsis in mouse spermatocytes . Until recently , however , the evidence for such a late prophase switch in DSBR mode was largely circumstantial and indirect . The analysis of IR-induced RAD-51 focus formation in rad-50 mutants reported here has provided a means to visualize directly a programmed shift in the requirements for DSBR that is imposed upon meiotic prophase entry and released in late prophase . Specifically , we have demonstrated that a requirement for RAD-50/MRE-11 to achieve rapid accumulation of RAD-51 at DSBs is acquired at the onset of meiotic prophase in C . elegans and is lost following progression of germ cells through a MAP kinase-dependent transition from the mid-pachytene to late pachytene stage . Our data suggest that the “meiotic DSBR mode” ( characterized by RAD-50 dependence for RAD-51 loading ) is imposed , at least in part , by meiosis-specific differentiation of chromosome axis structures . The switch to RAD-50 dependent RAD-51 loading is engaged at the onset of prophase and coincides temporally with assembly of meiotic chromosome axes . Further , this dependence is partially alleviated in mutants lacking either HIM-3 or HTP-1 , which are major components of meiotic chromosome axes ( [10]; E . Martinez-Perez , A . Dernburg and A . Villeneuve , unpublished data ) . The fact that RAD-50 dependence is partially abrogated in htp-1 and him-3 mutants argues against a trivial explanation for RAD-50 dependence , i . e . , absence of expression of a compensating nuclease during the window of RAD-50 dependence . In contrast , SC central region assembly is not required to confer RAD-50 dependence , as the requirement persists in syp-1 mutants . Interestingly , both him-3 and htp-1 mutants have been proposed to be defective in inhibiting use of sister chromatids as DSBR partners ( based on approximately normal kinetics of disappearance of RAD-51 foci despite lack of association between homologous partner chromosomes , suggesting the occurrence of sister chromatid-directed DSBR ) , whereas the barrier to sister-directed repair appears to be largely intact in syp-1 and syp-2 mutants ( based on prolonged persistence of meiotic RAD-51 foci ) . It is striking that both ( 1 ) dependence of RAD-51 removal on association between homologs and ( 2 ) dependence of RAD-51 loading on RAD-50 are either retained or relieved in parallel under different mutant conditions , suggesting that these features are coordinately implemented as part of an integrated meiotic DSBR program . This in turn suggests that RAD-50 dependence of IR-induced RAD-51 focus formation can serve as a convenient surrogate for engagement of multiple aspects of the meiotic mode of DSBR . How might HTP-1 and HIM-3 function to inhibit RAD-51 loading in the absence of RAD-50 ? One possibility is that these chromosome axis-associated proteins might generate a structural barrier that prevents alternative nuclease complexes from gaining access to DSBs generated within the constrained region . This type of mechanism would imply that DSBs may become associated with chromosome axis structures even if they are initially formed at distant positions within chromatin loops , as suggested previously by Blat et al . [51] . An alternative possibility is that the prolonged delay in RAD-51 accumulation at IR-induced breaks in rad-50 mutants represents a checkpoint response , and that HIM-3 and HTP-1 play a role in the operation of this checkpoint . This model is appealing for several reasons . First , HTP-1 was previously proposed to function in checkpoint-like mechanisms that coordinate homolog recognition with SC assembly , in a manner analogous to the spindle assembly checkpoint [4] . Second , these proteins share an unusual conserved structural motif , the HORMA domain , with Mad2 , a central player in the spindle assembly checkpoint [54] . Under this model , a DSB formed within the constrained region would generate a “wait resection” signal that inhibits progression of repair until a meiosis-specific recombination complex can be assembled; in a rad-50 mutant , the conditions required to satisfy the checkpoint are not met , resulting in the observed delay in RAD-51 loading . Our finding that germ cells revert to RAD-50 independence for RAD-51 loading in late prophase demonstrates the existence of a second developmentally programmed switch in the mode of DSBR . This switch occurs following a transient activation of MAP kinase that is required for progression from the mid-pachytene to late pachytene stage of meiotic prophase and is dependent on MAP kinase . Further , we showed that the switch occurs within the same time frame as loss of the capacity to convert IR-induced DSBs into interhomolog crossovers , suggesting that multiple aspects of the meiotic mode of DSBR are shut down simultaneously . We suggest that MAP kinase activation at the mid-late pachytene transition triggers a coordinate release from multiple constraints operating during earlier stages of meiotic prophase that together promote DSBR through formation of interhomolog crossovers . This mid-late pachytene switch in DSBR mode occurs contemporaneously with a major remodeling of meiotic chromosome architecture . Whereas SC central region proteins ( e . g . , SYP-1 ) and meiotic chromosome axis proteins colocalize uniformly along the full lengths of synapsed homologs from early-mid pachytene , components of these structures undergo a dramatic relocalization beginning in late pachytene . Even prior to desynapsis , SYP-1 becomes concentrated to a localized domain on each homolog pair ( in the vicinity of and distal to the single emerging chiasma ) , while a subset of chromosome axis components ( including HTP-1 ) become concentrated to the reciprocal chromosomal domains ( [12]; E . Martinez-Perez and A . Villeneuve , unpublished data ) . In a recent analysis of synapsis-defective mutants [55] , Smolikov et al . noted a correlation between chromosome organization within meiotic prophase nuclei ( i . e . , chromosomes clustered toward one side of the nucleus versus chromosomes dispersed about the nuclear periphery ) and ability to remove SPO-11-dependent RAD-51 foci as an indicator of progression of DSBR . Based on their findings , they suggested a model in which chromosome clustering would inhibit some modes of DSBR , while chromosome dispersal might create an environment more permissive for multiple modes of DSBR . In the current analysis , we found that reversion to the RAD-50 independent mode of RAD-51 loading in rad-50 syp-1 double mutants did not occur until chromosomes finally dispersed at the very end of the pachytene region , in keeping with the idea that persistent chromosome clustering may inhibit use of alternative modes of DSBR . However , our analysis also demonstrated that chromosome dispersal per se is not sufficient to confer a fully permissive DSBR environment . Our work provides insight into the mechanisms that allow germ cells to generate recombination-based linkages that promote segregation of homologous chromosomes at meiosis while at the same time safeguarding the integrity of the genome . We show that C . elegans germ cells engage a specialized mode of DSBR at the onset of meiotic prophase , characterized by dependence on RAD-50 for rapid accumulation of RAD-51 at DSBs and by competence to convert DNA breaks into interhomolog crossovers . This requirement for RAD-50 is imposed , at least in part , by meiosis-specific differentiation of chromosome axis structures . Our data further suggest a model in which features of chromosome structure conferred by the meiotic cohesin component REC-8 may limit the activity of SPO-11 in generating meiotic DSBs . Finally , we show that germ cells undergo a second developmentally programmed switch in DSBR mode at the mid-late pachytene transition , characterized by reversion to a RAD-50 independent mode of RAD-51 loading and loss of competence to generate interhomolog crossovers . Observations from several different experimental systems suggest that a capacity to switch from a highly specialized meiotic DSBR mode to a less constrained DSBR mode during prophase progression may be a widespread feature of meiotic programs . For example , Mehrotra and McKim [47] recently reported that formation of γ-His2Av foci in response to X-ray-induced DSBs occurs much more slowly in the early pachytene stage than in the late pachytene stage during Drosophila female meiosis , even in repair-proficient germ cells . The authors propose that this may reflect repression of the normal DSB response during early meiotic prophase , followed by alleviation of this repression at the transition to the late pachytene stage . Further , during mouse spermatocyte meiosis , disappearance of DSB-associated markers from heterosynapsed chromosome regions occurs in a later time window than disappearance of markers from correctly synapsed chromosomes [53] , likewise suggesting a change in the rules governing DSB repair during prophase progression . We suggest that a late prophase switch to a less constrained DSBR environment serves as fail-safe mechanism for safeguarding the genome by providing an opportunity to restore chromosome integrity prior to chromosome segregation .
Except where specified , all C . elegans strains were cultured at 20 °C under standard conditions [56] . The following mutations and chromosome rearrangements were used: Chromosome III: unc-79 ( e1068 ) , mpk-1 ( ga111ts ) ; Chromosome IV: dpy-13 ( e184 ) , htp-1 ( gk174 ) , him-3 ( gk149 ) , spo-11 ( ok79 , me44 ) , rad-51 ( lg8701 ) , rec-8 ( ok978 ) , dpy-4 ( e1166 ) ; Chromosome V: mre-11 ( ok179 ) , rad-50 ( ok197 ) , syp-1 ( me17 ) Balancers: nT1 IV;V . nT1[ unc- ? ( n754 ) let- ? qIs50] IV; nT1 V . nT1 IV; nT1[qIs51] V The following balanced heterozygous stocks were generated for this analysis: AV158 +/ nT1 [unc- ? ( n754 ) let- ? qIs50] IV; rad-50 ( ok197 ) / nT1 V AV270 spo-11 ( ok79 ) / nT1[ unc- ? ( n754 ) let- ? qIs50] IV; rad-50 ( ok197 ) / nT1 V AV457 +/ nT1 IV; rad-50 ( ok197 ) syp-1 ( me17 ) / nT1 [qIs51]V AV451 him-3 ( gk149 ) /nT1[ unc- ? ( n754 ) let- ? qIs50] IV; rad-50 ( ok197 ) / nT1 [qIs51] V AV443 htp-1 ( gk174 ) /nT1[ unc- ? ( n754 ) let- ? qIs50] IV; rad-50 ( ok197 ) / nT1 [qIs51] V AV414 dpy-13 ( e184 ) rad-51 ( lg8701 ) /nT1[ unc- ? ( n754 ) let- ? qIs50] IV; rad-50 ( ok197 ) / nT1 V AV417 rad-51 ( lg8701 ) /nT1[unc- ? ( n754 ) let- ? qIs50] IV; rad-50 ( ok197 ) / nT1 V AV423 rec-8 ( ok978 ) /nT1[unc- ? ( n754 ) let- ? qIs50] IV; rad-50 ( ok197 ) / nT1 [qIs51] V AV468 rec-8 ( ok978 ) dpy-4 ( e1166 ) /nT1 IV; rad-50 ( ok197 ) / nT1 [qIs51] V AV469 spo-11 ( me44 ) rec-8 ( ok978 ) dpy-4 ( e1166 ) /nT1 IV; rad-50 ( ok197 ) / nT1 [qIs51]V AV462 unc-79 ( e1068 ) mpk-1 ( ga111ts ) III; +/ nT1 [unc- ? ( n754 ) let- ? qIs50] IV; rad-50 ( ok197 ) / nT1 V For all experiments with meiotic mutants , homozygous mutant worms were derived from balanced heterozygous parents either by selecting progeny worms lacking a dominant marker ( Unc and/ or GFP ) associated with the balancer chromosome or by selecting worms homozygous for a cis-linked recessive marker . To evaluate acquisition of IR-induced RAD-51 foci in unc-79 mpk-1 ( ga111ts ) ; rad-50 hermaphrodites at non-permissive temperature , we shifted unc-79 mpk-1 ( ga111ts ) ; rad-50 ( ok197 ) / nT1 [ unc- ? ( n754 ) let- ? qIs50] IV;V gravid adults from 15 °C to 26 °C , allowed them to produce self-progeny , and selected non-GFP progeny at the L4 stage . At 20 h post L4 , worms were exposed to IR and subsequently processed for IF as described below . The rad-50 ( ok197 ) deletion was isolated from unbalanced heterozygotes obtained from the C . elegans Gene Knockout Consortium . Sequencing of the deletion fragment amplified by PCR from rad-50 ( ok197 ) homozygotes revealed a deletion of 1 , 571 bp , from coordinates 12246298 to 12247814 on chromosome V . The sequences flanking the deletion are: gaatttcactttacttagtc , tgaaattatttagcactgcc . The spo-11 ( me44 ) allele contains a G to A transition at coordinate 11125782 of chromosome IV , the last coding base of exon 6 . Although this represents a change in the splice donor sequence , this change is not predicted to interfere with splicing and is instead predicted to act as a missense mutation , changing a highly conserved Glycine to an Aspartic acid at residue 290 of the 425 amino acid protein . The affected residue is in the middle of the TOPRIM_TopoIIB_SPO cd00223 motif ( at the junction between the TOPRIM domain and the dimer interface ) and is conserved as a Glycine in all SPO11 proteins for which functional data are available [2] as well as in 92% of 51 aligned sequences defining the motif in CDD . Previous functional characterization indicates that spo-11 ( me44 ) behaves as a severe loss-of-function or null allele in meiotic recombination assays [57] . rec-8 ( ok978 ) is an insertion/deletion allele in which 1 , 577 bp of the rec-8 gene are deleted and replaced by an insertion of 371 bp . Depending on the outcome of RNA processing , the altered gene may have the capacity to encode for a truncated product comprising less than half of the 781 amino acids present in the wild-type protein . Comparison with previously-reported rec-8 ( RNAi ) and rec-8 ( cosuppression ) phenotypes [3 , 21 , 35] suggests that rec-8 ( ok978 ) severely reduces or eliminates gene function . Except where noted below , fixation , DAPI-staining , immunostaining and acquisition and processing of images using the Deltavision deconvolution microscopy system was carried out as in [4] , using gonads dissected from 18–20 h post-L4 adults . The following primary antibodies were used at the indicated dilutions: guinea pig α-SYP-1 ( 1:200 ) [11] , rabbit α-RAD-51 ( 1:50 ) [3] , rabbit α-HIM-3 ( 1:200 ) [10] , chicken α-HTP-3 ( 1:500 ) [19] , guinea pig α-HIM-8 ( 1:500 ) [20] . Secondary antibodies used were: Alexa 488 α-rabbit , Alexa 555 α-guinea pig , Alexa 555 α-chicken . For most double-labeling experiments , primary antibody incubations were performed simultaneously , followed by simultaneous incubation with secondary antibodies . For SYP-1 and RAD-51 double staining , slides were incubated sequentially with α-RAD-51 primary , α-rabbit secondary , α-SYP-1 primary , α-guinea pig secondary . Images were collected in z-series representing a longitudinal bisection of each gonad arm; images shown are projections through data stacks encompassing whole nuclei . For most experiments assessing formation of RAD-51 foci following IR treatment , 20 h post-L4 worms were exposed to 1 krad of γ-irradiation from a 137Cs source; gonads were dissected and fixed for IF at 1 h post irradiation . The 1 krad dose used in these experiments is 5–7-fold lower than the doses typically used in most prior analyses of DSBR in C . elegans germ cells ( e . g . , [4 , 18 , 39 , 40] ) . This dose was used because it was sufficient to elicit abundant RAD-51 foci in both wild-type and spo-11 mutant germ lines and to restore chiasma formation in a spo-11 mutant [22] , but does not lead to the poorly condensed , aggregated and/or fragmented appearance of chromosomes observed in diakinesis-stage oocytes in mre-11 or rad-50 mutants following a 5 krad exposure ( [18] and unpublished data ) . For Figure S3 , a 5 krad dose was used; for Figures 5 , S5 , and S6 , germ lines were fixed at the indicated times following irradiation at the 1 krad dose . For Figure 2B and 2C , gonads were dissected from 21 h post-L4 adults; slides were transferred to 100% methanol at −20 °C for 30–60 s , then post-fixed with 4% formaldehyde in 1× PBS , 80 mM HEPES , pH 6 . 9 , 1 . 6 mM MgSO4 for 30 min . Slides were washed in PBST and held at 4 °C until post-fixing was complete for all slides . Slides were blocked with 0 . 5% BSA for 1 h , then incubated with RAD-51 antibody ( 1:100 dilution in 50 μL PBST for 2 h at room temperature , then overnight at 4°C . Slides were washed 3× in PBST for 15 min; Cy3-labelled secondary antibody ( Jackson Laboratories ) was applied at a dilution of 1:200 in PBST and slides were incubated as for primary antibody . Slides were washed 3× in PBST for 15 min then stained with DAPI , mounted , and imaged , as in [11] . Quantitation of RAD-51 foci in zones distributed along the distal-proximal gonad axis was performed as in [3] . Correspondence of stages indicated on Figure 2B to the zones used in Colaiacovo et al . are as follows: “premeiotic ( pm ) ” , zones 1 and 2; “transition zone ( tz ) ” , zone 3; “early-mid pachytene ( e/m pt ) ” , zones 4 and 5; “late pachytene ( l pt ) ” , zone 6 ( Note that zone 6 in [3] corresponds to zone 7 in several subsequent studies , e . g . , [4] ) . Numbers of nuclei scored were as follows: Wild-type: pm , 424; tz , 191; e/m pt , 285; l pt , 91 . rad-50: pm , 248; tz , 78; e/m pt , 134; l pt , 54 . spo-11: pm , 565; tz , 168; e/m pt , 416; l pt , 118 . spo-1; rad-50: pm , 292; tz , 149; e/m pt , 261; l pt , 89 . For Figure 4C , double labeling with α-RAD-51 and mouse monoclonal antibody M8159 ( Anti-MAP Kinase , Activated [Diphosphorylated ERK-1&2] [Sigma] , used at 1:1 , 000 dilution ) was performed following the method of [58] , with modifications ( Y Sasagawa , personal communication ) . Gonads dissected from 20 h post-L4 worms were fixed in 2% paraformaldehyde for 1 h at room temperature , then post-fixed for 10 min with dimethylformamide at −20 °C . Slides were washed with 1× PBST three times for 10 min and blocked with 3% BSA , 2mM MgCl2 , 0 . 1% Tween-20 for 20 min . Slides were incubated with primary antibodies in 1× PBS , 0 . 1%BSA , 0 . 5%Triton X-100 , 0 . 05% sodium azide , 1mM EDTA overnight in a humid chamber at 4 °C . Slides were washed as above and incubated with secondary antibodies ( Alexa 488 α-rabbit and Alexa 555 α-mouse ) for 2 h at 25 °C . For quantitation of achiasmate chromosomes in the rad-50 ( ok197 ) mutant , whole worms were fixed with Carnoy's fixative at 48 h post L4 and stained with DAPI as in [59] . For experiments assessing chiasma formation in spo-11 ( ok79 ) worms following exposure to ionizing radiation , whole worms were fixed in ethanol and stained with DAPI as in [60] . Twenty h post-L4 adult worms were exposed to 1 krad of γ-irradiation from a 137Cs source , and cohorts were fixed 12 , 14 , 16 , or 18 h later; unirradiated controls were fixed at the 18-h time point ( 38 h post-L4 ) . Since individual univalents or bivalents in some oocyte nuclei lie too close to each other to be resolved unambiguously , these assays tend to underestimate the frequency of achiasmate chromosomes . Although the dose used in these experiments was 5-fold lower than that used in previous reports ( 5 krad ) , sufficient breaks were generated to restore chiasma formation for the full complement of chromosomes at high frequency .
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Faithful inheritance of chromosomes during sexual reproduction depends on the deliberate formation of double-strand DNA breaks ( DSBs ) and subsequent repair of a subset of these breaks by a mechanism that leads to crossovers between homologous chromosome pairs . The requirement for crossovers to ensure chromosome segregation poses a challenge for sexually reproducing organisms , as DSBs constitute a danger to genomic integrity in other contexts . This manuscript provides insight into the mechanisms that allow germ cells to generate recombination-based linkages that ensure chromosome inheritance while at the same time protecting the integrity of their genomes . Specifically , we provide a direct demonstration , based on our analysis of rad-50 mutants , that the meiotic program in C . elegans involves both acquisition and loss of a specialized meiotic mode of double-strand break repair ( DSBR ) . We propose that the ability to revert to a less constrained DSBR environment at a late stage of meiotic prophase serves as a fail-safe mechanism for safeguarding the genome , as it provides an opportunity to repair any remaining DBSs and restore chromosome integrity prior to chromosome segregation .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"developmental",
"biology",
"cell",
"biology",
"caenorhabditis",
"eukaryotes",
"animals",
"molecular",
"biology",
"genetics",
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"nematodes"
] |
2007
|
C. elegans Germ Cells Switch between Distinct Modes of Double-Strand Break Repair During Meiotic Prophase Progression
|
The human brain efficiently solves certain operations such as object recognition and categorization through a massively parallel network of dedicated processors . However , human cognition also relies on the ability to perform an arbitrarily large set of tasks by flexibly recombining different processors into a novel chain . This flexibility comes at the cost of a severe slowing down and a seriality of operations ( 100–500 ms per step ) . A limit on parallel processing is demonstrated in experimental setups such as the psychological refractory period ( PRP ) and the attentional blink ( AB ) in which the processing of an element either significantly delays ( PRP ) or impedes conscious access ( AB ) of a second , rapidly presented element . Here we present a spiking-neuron implementation of a cognitive architecture where a large number of local parallel processors assemble together to produce goal-driven behavior . The precise mapping of incoming sensory stimuli onto motor representations relies on a “router” network capable of flexibly interconnecting processors and rapidly changing its configuration from one task to another . Simulations show that , when presented with dual-task stimuli , the network exhibits parallel processing at peripheral sensory levels , a memory buffer capable of keeping the result of sensory processing on hold , and a slow serial performance at the router stage , resulting in a performance bottleneck . The network captures the detailed dynamics of human behavior during dual-task-performance , including both mean RTs and RT distributions , and establishes concrete predictions on neuronal dynamics during dual-task experiments in humans and non-human primates .
A ubiquitous aspect of brain function is its modular organization , with a large number of processors ( neurons , columns , or entire areas ) operating simultaneously and in parallel . Human cognition relies , to a large extent , on the ability to perform an arbitrarily large set of tasks by flexibly recombining different processors into a novel chain ( e . g . respond with the right hand to the red square ) [1]–[3] . Yet this flexibility does not happen without a cost . Chaining individual computations is done at a very slow pace ( 100–500 ms per step ) and with a considerable temporary tying-up of the brain's resources , generating what is known as “dual-task interference” – the inability to perform several tasks at once [4]–[8] . Several cognitive theories support this view , arguing that while most mental operations are modular and parallel , certain specific processes which establish flexible links amongst existing processors impose a serial processing bottleneck [3] , [9]–[15] . The psychological refractory period ( PRP ) provides a classic and clear demonstration in experimental psychology of the coexistence of parallel processing and serial processing bottlenecks within a cognitive task . When performing two tasks in rapid succession on two successively presented targets T1 and T2 , delays are observed in some but not all of the T2 processing stages . Analysis of these delays suggests that a “central decision stage” suffers from seriality while perceptual and response operations occur in parallel [4] , [6] , [7] , [16] , [17] . Despite the fact that the PRP has been one the most widely studied paradigms to investigate dual-task interference , no network implementation had been proposed which provides a plausible implementation of its underlying mechanisms . Boxological and schematical models of the PRP [4] , [18] , [19] have successfully determined a theoretical framework which provides a synthesis of two basic aspects of cognitive architecture: 1 ) its chronometric organization , 2 ) its components that can act in parallel and those that impose seriality . According to these models , each task involves three successive stages of processing: a perceptual , a central , and a motor component . The perceptual stage of sensory processing - which is performed in a modular ( parallel ) fashion - does not provide a major contribution to temporal variability . A subsequent stage of serial processing involves a stochastic integration process , traditionally used to model decision making in single tasks [20]–[23] and is a main source for the variability in response time . In contrast , the last motor processing stage has only a small contribution to response variability and can be performed in parallel without interfering with other processing stages from concurrent tasks . Despite their simplicity , these models have been very successful in explaining a broad range of behavioral data , including the complex response time distributions of dual-task experiments , which can be precisely predicted only after untangling the serial and parallel stages of each task [18] . Until now , the modeling of dual tasks is only specified at a level of mathematical description and functional cognitive architecture [4] , [18] , [24] , [25] . At the neurophysiological level , understanding what kind of collective neural organization leads from massively parallel single-unit processing to a serial unfolding of two successive decisions has not been established . This situation is , to a large degree , due to the fact that there have been detailed monkey electrophysiology of single-task decision making [26] , [27] , but no comparable investigation of dual-tasks . Here we present an effort to bridge this gap between an abstract mathematical description and the underlying complex neurophysiology . We present a detailed model , based on realistic properties of spiking neurons which is capable of flexibly linking processors to form novel tasks . As a consequence of this flexibility , the network exhibits a functional serial bottleneck at the level of the “router” circuit needed to link processors . The model presents detailed predictions for future electrophysiological studies of dual-tasks and serial computations in the human and non-human primate brain .
In accordance with previous theoretical proposals [28] , [29] here we propose that seriality in dual ( or multiple ) task performance results as a consequence of inhibition within the control networks needed for precise “routing” of information flow across a vast , virtually infinite , number of possible task configurations . To examine this hypothesis , we will explore dual-task performance in a recurrent network of spiking neurons capable of performing flexible routing of information according to specific task instructions . Contrary to previous computational work addressing flexible mapping [30]–[33] , our objective is not to study flexible behavior per se but to understand the conditions under which a computational model capable of flexible sensory-motor mapping shows patterns of interference when two tasks have to be performed simultaneously or in close succession [17] , [18] , [34] . Following classic experimental procedures of the PRP [35] , the interference experiments we address here involve different sensory modalities , to avoid sources of interference in early sensory processing ( with the exception of the last section , where we investigate the effects of masking ) . The model that we simulate is described in detail in the Materials and Methods section and in Figure 1 . It includes two sensory modalities organized in a hierarchy in which each successive layer receives inputs from neurons of the previous layer thus generating progressively complex receptive fields . Within each hierarchical level , for simplicity we explore in detail only two distinct neural populations for each sensory modality , which correspond to the neural coding of the two task-relevant dimensions ( red and orange populations in Figure 1 representing , for example , a high and low pitch sound , respectively ) . Other task-irrelevant stimuli were encoded by a large pool of non task-selective excitatory neurons ( pink populations in Figure 1 ) , as done in many other spiking networks modeling decision-making [36] . Each element in this sensory hierarchy is a canonical cortical circuit comprising excitatory pyramidal cells and local inhibitory cells , previously shown to be capable of performing elementary functions of working memory and decision making [36]–[38] . Only excitatory pyramidal cells project with long-range connections to neurons higher and lower in the sensory hierarchy , while inhibitory neurons only project locally . Feedforward and feedback connections in the model differ both in the properties of the receptors that mediate the transmission as well as in their specificity [39]–[42] . Feedforward connections are highly specific: Each neuron projects to a single homogeneous population in the next higher level . For simplicity , they are assumed to be all mediated by fast AMPA receptors , although in reality a small fraction of NMDA receptors would be expected . In the reciprocal direction , feedback connections are more broadly connected: each neuron sends non-specific feedback connections to all excitatory cells in the previous level [40] , [41] . Again , for simplicity we assume that feedback transmission is mediated by slow NMDA receptors . Since the contribution of NMDA receptors to synaptic transmission varies with the level of postsynaptic depolarization , this ordering of glutamate receptors between the feedforward and feedback streams broadly assigns a driving role to the feedforward input and a modulatory one to the feedback , as in previous models [43] . Both sensory modalities project to a router which connects the sensory representations to a set of possible responses . Neurons in the router integrate sensory evidence and trigger a response when their activity reaches a threshold [44] . An explicit instruction - presented before the stimulus – sets the task for a given trial , i . e . specifies the specific mapping which indicates which response has to be executed when the stimulus is presented . The network that stores task instructions is referred throughout this work as the task-setting network . Excitatory populations in this network are activated by the presence of task-relevant stimuli in sensory areas and , through their patterns of projection to “router” neurons ( see below ) , encode different stimulus-response mappings . As with the sensory modalities , we only simulate two task-setting populations which are sufficient for the experiments considered here . An important aspect of our model is a circuit which we refer as the “router” . As in previous models of flexible decision making that do not rely on synaptic plasticity to dynamically adjust their behavior [33] , [45] , [46] , task-setting neurons affect the decision process by gating a specific subset of “router” neurons , which implement the possible mappings between stimuli and responses . Here we assume a reduced ensemble of stimuli and responses and simply model as many selective populations in the router as there are combinations of stimuli and responses [33] , [47] . Simulating a completely flexible network capable of mapping arbitrarily large stimulus and response sets , would require a high degree of overlap in the cortical representation implemented by task-setting and routing neurons . We will come back to this possibility and its possible implications for serial processing in the discussion . As with all other neurons in the network , task-setting neurons are entailed with self excitation and lateral inhibition . Excitatory neurons in the task-setting network are connected to the router through NMDA connections . When an excitatory population of the task-setting network is in an “active” state it excites the subset of neurons in the router receiving inputs from task relevant sensory populations and connecting them to the appropriate motor populations . A neuron in the router which receives excitation from task-setting neurons is set in a mode of integration in which it can accumulate sensory information ( Text S1 , A ) . This architecture also serves as a selection mechanism , assuring that task-irrelevant stimuli that are represented in sensory cortex do not elicit any output ( Figure 2 ) . Response execution is triggered in response selection networks ( motor 1 and 2 in Figure 1 ) by a set of bursting neurons that signal a threshold-crossing of the input received from the integrating neurons , modeled as in previous work by Wang and collaborators [44] . To ensure that the network did not enter in a response perseveration mode ( Figure S1 ) , we implemented an inhibition of return mechanism [48] typical of a control network . After response execution , response neurons feed back to inhibit the sensory , routing and task-setting neurons involved in the task ( similar to the “termination” signals in Dehaene and Changeux , 1997 [49] and recently observed in single-cell recordings in awake behaving monkeys performing a sequential task [50] ) . This architecture ensured that the network did not respond spontaneously , to irrelevant stimuli or to mappings different than those set by the explicit task-instruction and that it did not show perseveration of responses to task-relevant stimuli . We emphasize that here we have not investigated how a large repertoire of tasks can be encoded with a finite number of neurons . Rather , we ensure that the network has stable performance for a small number of tasks and then explore the operation of this network during dual-task performance . Our simulations of dual task experiments showed that when both tasks were close together in time , response order could be reversed on a fraction of trials so that the first response was given to the stimulus that was presented second ( Figure S2 ) . This coincides with experimental observation in task-interference experiments when the response order is not fixed [51] . Here we wanted to explore a comparatively simpler situation , typically studied in psychophysical experiments , in which participants are explicitly told to respond to two tasks in a specific order , as fast as possible . This required the implementation of a task-setting network [52] that determined the order of the tasks . The task-setting network was bistable . It was composed of two excitatory populations that projected to the inhibitory population of the other task . Three hundred milliseconds before the presentation of the first stimulus , excitatory neurons in the order-setting network are activated by a brief ( 100 ms ) external input . Due to the strong self-recurrent connections , the network maintains high levels of activity after removal of the external input and tonically inhibits T2 neurons in the task-setting network . When the response to T1 is emitted , inhibition from the router resets the order-network permitting the activation of T2 task setting-neurons ( Text S1 , B ) . In summary , we generated a network based on a large-scale implementation of simple canonical neuronal circuits endowed with self-recurrence and lateral inhibition . The network has a hierarchical sensory organization which ultimately feeds stochastic evidence to “router” neurons which ( if activated by a specific task-setting context ) both accumulate evidence towards a motor decision and route sensory input to the relevant motor neurons . Each stimulus has four features . The four populations encoding low-level features of a stimulus receive a brief pulse of constant current during stimulus presentation ( 100 ms ) . This initial impulse generates a transient response in the earliest input neurons ( Figure 2A–D ) , which increase their firing rate from the default level of around 2 Hz to around 40 Hz . This transient response initiates a wave of activation that propagates through the network [47] , [53] , [54] . Each layer works as an integrator of the previous layer and thus the neural response becomes increasingly expanded in time as one progress in the hierarchy . At the highest level , recurrent connections are strong enough to assure a very low decay rate of stimulus information , resulting in an effective form of working memory as observed in several areas of occipito-temporal and frontal cortex [55]–[57] . The last stage in the sensory hierarchy projects to the router using AMPA receptors . Neurons in the router also receive currents from task-setting neurons , but these projections use NMDA receptors . These NMDA currents control the recurrence in the router , and they determine the degree of integration of AMPA currents . As a result of this architecture , neurons in the router act as detectors of the conjunction of stimulus presence and task relevance as observed in [58]–[60] . A neuron which receives task-setting currents integrates the sensory input rapidly ( Figure 2B ) , while a neuron that does not integrates the input only partially ( Figure 2E–H ) . Thus , task-setting neurons accomplish their role by assuring that the wave in the sensory system initiated by an irrelevant stimulus does not trigger a response . The integration process continues until a threshold is crossed , which is signaled by a nonlinear response: a powerful burst of spikes in the motor network ( Figure 2D ) . The activation of these response neurons , in turn , initiates a cascade of feed-back inhibition that resets activation in task-related neurons [50] . The principal aim of this paper is to explore the operation of the model in a classic dual-task paradigm: the psychologically refractory period ( PRP ) , widely studied in the psychophysical literature . We explored the response of the model with two different stimuli , presented simultaneously or at a short stimulus onset asynchrony ( SOA ) . When the separation between stimuli ( SOA ) is much longer than the response time to the first task ( RT1 ) , the neural activations associated with the first and second task do not interfere with each other and the observed dynamics is similar to that observed during single-task performance ( Figure 2A–D ) . The most interesting situation is for SOA values close to or shorter than RT1 ( Figure 3A–D , SOA = 100ms ) in which case the two waves of activation evoked by each stimulus partially interfere . In the model , this interference does not occur at the sensory level: even at short SOA , while a first target T1 is being processed , sensory neurons associated with the second target T2 still initiate a wave of activations which is very similar to that in the single-task condition . However , due to competition between task-setting neurons , the routing neurons of T2 are not gated and hence do not integrate sensory information while T1 is being processed . In this instance there is a very interesting dissociation: local-recurrence in the sensory hierarchy is sufficient to maintain T2 stimulus information , but this information is not piped to the motor response and awaits liberation of the router . This constitutes a key aspect of this network – during a temporary waiting period , T2 has to be maintained in a “local memory” which does not propagate throughout the network . After the response to the first task has been executed , the T1 pathway is reset and Task 2 setting neurons activate , gating the router neurons of T2 and allowing them to begin to integrate information about the second incoming stimulus . Thus , the shift in the locus of “task-related attention” ( which information is amplified in sensory areas and routed to response networks ) is the natural consequence of the progression of the task in the router and task-setting network . Note that the second key aspect of our network is that routing neurons of T1 and T2 cannot be simultaneously activated . In our network this is controlled through a competition between task setting neurons , but a similar result would be obtained if this competition would be implemented by lateral inhibition between routing neurons . This would occur , for example , if the number of possible mappings largely exceeds the number of neurons in the router so that routing can only occur by a distributed assembly of active cells . We will come back to this possibility in the discussion . In the interference regime , the network includes groups of neurons with very different response properties ( Figure 3E ) ; the existence of these different types of neuronal firing patterns constitutes a key prediction of our simulations . Early sensory neurons show a response which is essentially unaffected by interference , reflecting fully parallel behavior . In contrast , the motor and task-setting neurons are strictly serial , only showing strong activation after task 1 has been completed . The behavior of the router neurons is intermediate; they are mostly serial , but can undergo moderate integration ( insufficient to boost a response ) before completion of T1 . Interestingly , late sensory neurons act as a buffer . They have an onset which is locked to the stimulus and are active until the response , so that they hold a memory of T2 which is retrieved when the router becomes available . This population of neurons is therefore engaged in different components of the task; first , a transient response which results in stimulus encoding , and second , a later memory trace which is eventually broadcasted to the motor neurons involved in the second task . All the previous analysis relied on spiking activity . Recently , much effort has been devoted to understand the relevance of complementary measures of brain function such as synaptic currents , local field potentials , and induced oscillations . Our neuronal network has the potential to study these measures . We first explored whether input currents in the router could be more informative than spiking activity of T2 processing stages . We measured input currents to the router at different processing stages of T2: Spontaneous activity , S2 queuing ( memory phase ) , and S2 routing . During queuing , currents in the router reflected a steady level of activity which was significantly larger than during spontaneous activity ( Figure S3 ) . Thus , during this regime , subthreshold activity in the router is tightly coupled to spiking activity of late sensory neurons . During the routing stage , synaptic current activity ramps , coupling to the progression of spiking activity in the router . An interesting observation was that this pattern was virtually identical for all receptor currents ( NMDA , AMPA and GABA ) . Although the input from the task-setting network is carried by NMDA-receptors , the local amplification in the router circuit also engages AMPA currents and the NMDA specificity is lost very rapidly ( Figure S3 ) . The task-switching circuit was endowed with high efficiency inhibition to achieve rapid switching from one task-setting program to another . This endowed the task-setting circuit with high frequency oscillations as can be seen in the raster plots of Figure 2 . Since the task-setting circuit drives the router , we asked how these oscillations propagate into the network and whether measures of oscillatory activity could be more informative than simply spiking activity to identify distinct processing stages from neuronal responses . We analyzed the spectrogram of sensory , routing and task setting T2 neurons throughout the trial ( Figure S4 ) . Responses were locked to RT1 . Both router and task setting neurons showed clear event-related spectrograms , as seen for firing rates . The spectral content of the responses of both populations are quite distinct: task-setting circuit activity occurs in high-frequency bands ( peaking around 70 Hz ) while router neurons , which act as slow integrators , display low-frequency responses ( ∼20 Hz ) . Router neurons do not inherit high frequency oscillations of the driving task-setting neurons because these connections are mostly mediated through NMDA receptors which have a slow time constant . Rhythmic activity in the sensory neurons showed distinct oscillatory activity during buffering and routing ( Figure S4 , left panel ) . During routing , responses of sensory neurons showed high power in the 40–60 Hz range while during routing they were more broad band and showed an increase in lower-frequency activity . Firing rates of sensory neurons during buffering and routing were not different ( Figure 2 ) . Spike density coherence between sensory and router neurons also showed distinct profiles during distinct phases of task processing: phase coherence was not-significant during spontaneous activity , it showed significant coupling for low frequencies during routing and broad-band coherence during T2 queuing ( Figure S5 ) . An appealing aspect of the PRP paradigm ( Figure 4A–B ) is that it is associated with a large number of chronometric observations . We explored whether the network shows a behavior in accordance with these observations including the dependence of mean RT ( and RT distributions ) with SOA and the differential effects of pre and post-bottleneck manipulations . Specifically , the main experimental characteristics of the PRP phenomenon are [18] , [34] , [35]: We first explored the main effects of the PRP ( without specific task manipulations ) by simulating an experiment in which two stimuli were presented at an SOA which varied between 0 and 800 ms , sampled at [0 , 50 , 100 , 150 , 200 , 250 , 300 , 400 , 500 , 600 , 700 , 800] ms ( Figure 4C ) . Response times were defined as the time interval between the onset of the stimulus signaling each task and the peak of the motor burst . The network virtually made no mistakes ( error rates were less than 0 . 1% for both tasks ) , which was expected given that the two different stimuli have non-overlapping representations in each sensory modality . We observed that the network behavior captured all the predictions listed above ( Figures 4 and 5 ) . RT1 was unaffected by SOA ( Figure 4C–G ) . Although , the presentation of the second stimulus provides input to the task-setting neurons of T2 , this network is configured in a winner-take-all mode and the top-down control of T1 over the router neurons is virtually unaffected by the incoming stimuli . Thus , S2 was never strong enough to overwrite T1 in the task setting network as long as this task was ongoing . Second , we observed the classic RT2 profile with varying SOA values: An initial decrease with a slope of −1 ( Figure 4C ) . This indicates that T2 completion is strictly serial even though some aspects of T2 processing are carried out in parallel with T1 ( Figure 3 ) . As SOA increased and reached the average value of RT1 , the two tasks became increasingly independent . The stochasticity of the system ( see below for an analysis of RT distributions ) assured that this elbow –i . e . the regime in which RT2 becomes independent of SOA was not sharp and thus RT2 showed a curved decay which reached a horizontal asymptote after about 300 ms , as observed in human psychophysics ( Figure 4C ) . Based on typical experimental procedures , we then explored the effect of different manipulations on the first and second task on mean response times , and their interaction with SOA ( Figure 4D–G ) . First we investigated the effect of changing the complexity of sensory processing . In a number comparison task , changing the notation ( for instance replacing the digit 3 by the word three ) results in an increase in response time which is absorbed during the PRP ( i . e . , more elaborate sensory processing of S2 can occur while central processing for T2 is blocked by the processing of task 1 , therefore not increasing RT2 at short SOA ) [18] . A simple model of word recognition predicts that complex combinations of characters are encoded in successive layers of a feed-forward scheme [53] , [61] . To model this experimental factor in our network , we simply added an additional processing level in the sensory hierarchy . We first applied this manipulation to task 1 , and observed an additive effect on RT1 , which did not depend on the SOA ( Figure 4F ) . This effect propagated to RT2 in the interference regime . This shows that the network functions strictly in a first-come first-served basis . Manipulating the second task affected RT2 for long SOA values , but had no effect at short SOA ( Figure 4D ) , indicating that the additional sensory processing can be carried out in parallel with T1 processing . This absorption of pre-bottleneck manipulations constitutes one of the critical predictions of theoretical models of the PRP ( Text S1 , C ) . We then explored another important manipulation which affects the complexity of the sensory-motor mapping , i . e . the amount of sensory evidence in favor of the correct decision . In experiments in which a decision is taken on an analog variable ( movement , intensity , numerosity , size etc… ) the two competing stimuli can be made arbitrarily close , rendering the decision progressively more difficult . This results in increased errors and RTs , and attractor dynamic networks have been very successful in modeling these phenomena [37] , [62] . This distance manipulation in a PRP setup results in a bottleneck manipulation which is not absorbed in the PRP . Here , as conventionally done , we modulated the amount of evidence by changing the relative input currents of each of the two competing sensory populations ( Figure 4E , G ) . We applied this manipulation to the first task , and observed an increase in RT1 unaffected by SOA ( Figure 4G ) . This effect propagated to RT2 in the interference regime . When the manipulation was applied to the task performed second ( Figure 4E ) , the first task was unaffected but the second task showed an additive effect not absorbed at short SOA values . This effect is what would be expected from bottleneck manipulations . The statistical significance of these observations was evaluated with a series of ANOVAs using the R software package ( http://www . r-project . org/ ) ( Table S1 ) . The response times histogram for SOA = 0 ms is displayed in Figure 5 ( A , B ) . The results of the model capture an important experimental observation that the variability in RT2 is higher at short SOA , as RT2 accumulates the variability of both tasks . Response times for T2 become faster and less variable as SOA increases , as seen by plotting the cumulative response time distributions for varying SOA ( Figure 5F ) [18] . Interference and seriality are also observed in the scatter plots of RT1 vs . RT2 , for different SOA values: for short SOA values RT2 is tightly correlated to RT1 indicating that RT2 is sequentially locked to Task 1 completion . For long SOA values , RT1 and RT2 become independent measures ( Figure 5 C–E ) . The previous results showed that our model can explain the precise shape of response time distributions in dual-task performance . Here we investigate the underlying physiological markers which result in such distributions , i . e . the relation between neuronal and response time variability . All neurons in the model receive strong background Poisson inputs , which assures a spontaneous activity of 2–5 spikes/s . We hypothesized that in trials in which input noise in the sensory neurons coincides with stimulus presentation ( presented for 100 ms ) response times would be faster . We also hypothesized that in the case of low-frequency noise ( ∼5Hz ) , the coincidence effect of external-stimulus and internal noise fluctuations , should manifest in a phase-locking relation of stimulus presentation to internal rhythms , as observed in both psychophysical [63] , [64] and neurophysiological [65] experiments . We first used a general linear regression model to investigate how noise fluctuations affected response times in the PRP . The explanatory ( independent ) variables were external noise fluctuations for each population group and temporal bin , and the response ( dependent ) variable was either RT1 ( Figure 6A ) or RT2 ( Figure 6B ) . We simulated 900 trials of the PRP for an SOA of 50 ms . For each trial , the population average of - dynamic gating variable mediating background AMPA currents ( see Materials and Methods section ) - was measured every 1 ms , assigning a value of 0 if its value exceeded the median value over all trials , and a value of 1 otherwise , independently for each population and time step . Independent variables were obtained by averaging these values within windows of 100 ms . Similar populations - for example , all neurons in the first level of the sensory hierarchy selective to the same stimulus - were averaged together . A positive regression coefficient means that higher activity of a group of neurons leads to faster responses . The time-course of the coefficients of the regression ( Figure 6 ) showed a very clear temporal organization . For Task-1 sensory neurons ( Figure 6A ) , fluctuations in the first sensory level which were coincident with stimulus presentations were highly predictive of RT1 . On the contrary , fluctuations beyond this window were essentially independent of response time . In successive stages of the hierarchy the window of correlation was delayed . As we showed previously , RT2 variability accumulates RT1 variability ( due to changes in the onset of the routing of T2 ) and intrinsic variability of the T2 routing process . To understand the impact of noise on each of these processes , we measured the time-course of the noise input to Task-2 responding neurons locked to the response to Task 1 ( Figure 6B ) . Significant noise contributions were observed before the integration onset ( Figure 6B , upper panel ) , suggesting that although sensory integration is delayed during the PRP , fluctuations in the memory trace of S2 during T2 queuing or before have an influence on RT2 . Thus , spontaneous Poisson-noise fluctuations were effective when they coincided in time with external stimulus currents . If noise currents were carried by low-frequency oscillations [66] this effect could result in phase locking of RTs to the rhythmic oscillatory activity . We tested explicitly this possibility by running single-task simulations where excitatory neurons in the first sensory level received a low-frequency ( 5 Hz ) , low-amplitude ( 0 . 06% of the external background noise ) , oscillatory input . This additional input resulted in a small synchronous fluctuation on top of the large external background input . The phase of the stimulus onset relative to the background rhythm was varied across trials in order to study its effects on average response times and their distributions ( Figure 6C ) . The relative phase between stimulus onset and rhythmic background activity had a marked effect on response times , compatible with recent experimental findings [65] and theoretical proposals [66] linking low-frequency oscillations to attentional selection . Our model provides a simple physiological explanation of why phase-locking stimulus to low-frequency oscillations may result in shorter response times . When the phase is such that the peak of noise fluctuations coincides with stimulus presentation , the stimulus is enhanced and this reduces response time . On the contrary , when stimulus presentation coincides with the valley of noise oscillations , input to the router is less effective and response times are longer . Behavioral experiments which have combined the basic features of different manifestations of central processing such as the PRP ( two rapid responses ) or the attentional blink ( extinction of a second rapidly presented stimulus ) have suggested that both forms of processing limitations may arise in part from a common bottleneck [67]–[70] . The main differences between the PRP and the AB is that in the PRP a speeded response is required to the first target and , most importantly , that in the AB the visibility of the second target is reduced , generally by masking it or by embedding it in a rapid visual serial presentation ( RSVP ) . To evaluate whether our model could , without modification , also account for AB experiments , we studied the effect of a mask applied after T2 . The mask was modeled as a brief stimulation of non-specific excitatory cells in the first layer of the sensory hierarchy , thus modeling the activation of a neural representation competing with the target T2 [71] . The mask lasted 100 ms and was presented immediately following T2 . In the majority of AB experiments , both T2 and the T1 are masked . Here , for direct comparison with the PRP simulations , we considered a special AB case in which the T1's fleetingness is obtained by virtue of its weak strength , rather than masking [72] . We simulated 100 trials at each SOA value , varying the SOA between 50 and 500 ms at 50 ms intervals . In contrast to the previous PRP simulations , when the SOA between T1 and T2 was short we observed a small ( but significant ) number of errors and , most importantly , a large number of trials in which the network failed to respond to T2 ( Figure 7A ) . For simplicity and to follow the convention of prior experimental work , we refer to trials in which the network responds correctly as seen , and those in which it fails to respond as unseen . For example , at SOA = 50 ms we obtained 49±5% seen trials , 47±4 . 99% unseen trials , and 4±1 . 96% errors; for SOA = 500 ms , we obtained 90±3% seen trials , 9±2 . 86% unseen trials , and 1±0 . 01% errors . As observed in the Attentional Blink and in mixed AB-PRP paradigms , the brief mask after T2 is only effective when T2 is presented within a short temporal window – typically of around 500 ms – following T1 presentation . For short SOA values , the network exhibits a highly stochastic behavior: the same configuration of stimuli and SOA may lead to seen or unseen responses depending on the inner state of the network . Figure 7B–D shows the time-course of activity of a representative seen and unseen trial and reveals the cause of the blink . In the unseen trial , RT1 was longer and thus at the moment in which inhibition of T2 task-setting neurons was released , T2 sensory activation had faded out . As a consequence , T2 task-setting neurons failed to respond and this impeded the integration and routing of T2 . This can also be seen when averaging across all trials ( for an SOA of 100 ms ) according to whether the network responded or failed to respond to T2 ( Figure 7E ) . T2 non-responded trials resulted – on average - from a delayed response of the T1 task setting neurons . This observation establishes a concrete prediction for the dynamics of routing neurons in a AB experiment and is consistent with physiological and behavioral experiments which have shown that the extent of T1 processing has an impact on T2 visibility [69] , [73] , in accordance with the behavior of the sequential bottleneck model . The interpretation of our results is that the mask results in an accelerated exponential fading of the representation of T2 stimulus in short-term memory [74] , [75] . As a result , if the waiting time of T2 is too long , due to the concurrent processing of T1 , the remaining activation is insufficient to ignite the router and task-setting neurons and the network fails to respond to T2 . Consistent with this interpretation , we verified that early responses evoked by the second stimulus in seen trials showed a small , but significant effect in the amplitude – but not in the latency - of the transient responses when compared to unseen trials ( Figure 7E ) . These small fluctuations are strongly amplified in the router and task-setting neurons , which show an almost all-or-none difference ( Figure 7E ) . This result is consistent with electrophysiological experiments of the blink and the PRP which have observed a modest effect in early sensory components and a massive all-or-none effect in late P3 components [73] , [76] , [77] . A series of experimental observations have shown that the AB is attenuated ( i . e . the probability of seeing T2 increases ) with increased T1 strength . For example , the blink is attenuated when a blank is placed after T1 , i . e . masking is delayed [10] . This observation is in contradiction with pure T1–T2 competition models of the AB since these models predict the opposite effect: increased T1 strength should result in a reduced likelihood of perceiving T2 [78] , [79] . However , it seems compatible with our network operation , since a stronger T1 stimulus should result in a faster conclusion of Task 1 , increasing the probability of retrieving the second stimulus before it has fade out . We examined this hypothesis performing two different simulations . First , we increased the strength of T1 by 10% relative to the previous PRP and AB simulations . This resulted in an attenuated AB for the second task ( 76±4% correct vs . 49±5% correct without the manipulation; p-value <0 . 0005; 100 trials at a fixed SOA of 50 ms ) . Despite perfect performance for T1 in these simulations , RT1 was smaller when T1 was stronger ( with strong T1: RT1 = 318±5 ms; without the manipulation: RT1 = 396±9 ms; p-value<0 . 0005 ) . Thus increasing T1 strength decreases RT1 and increases the probability of retrieving the second stimulus . The second manipulation , conversely , involved masking the first target T1 , simulating the most typical AB paradigm in which both T1 and T2 are masked . As for the first manipulation , 100 trials were simulated at a fixed SOA of 50 ms and we now added a mask identical to the one previously used for T2 . In this condition , performance in the first task was still accurate ( 92±3% correct ) while T2 visibility was decreased significantly ( 26±4% correct ) . This effect can be understood by the increased latency of the inhibitory signal following routing of T1 , which increased RT1 from 396±9 ms in the unmasked condition to 869±50 ms when T1 was masked . In summary , our simulations show that T1 manipulations that facilitate the first task and therefore reduce its duration have the effect of reducing the attentional blink for T2 , as experimentally observed [5] , [80] . Since RT1 is typically not measured in most AB tasks , where the task is to covertly commit T1 to memory for delayed report , only the reduced blink for T2 would have been noticed experimentally – but our network suggests that , if RT1 was measured by an on-line task , then the reduced AB would be replication and would be mediated by a faster RT1 .
The present model constitutes , to our knowledge , the first spiking-neuron model of a global architecture capable of simulating the entire sensory-motor chain of processing in a dual-task setting . We could explain the detailed dynamics of behavior ( including both mean RTs and RT distributions ) during dual-task-performance , by simulating a large-scale network of realistic neurons , comprising about 20 . 000 spiking neurons and 46 . 000 . 000 synaptic connections . For consistency with the majority of previous PRP experiments , we simulated an experimental design in which stimuli involve distinct sensory modalities and the responses distinct effectors . Under these circumstances , interference occurs exclusively at the routing stage , commonly referred to in psychology as the response selection stage [4] . The central aspect of our model is a detailed neuronal implementation of this flexible “routing” and how it manages to change from one task to another in hundreds of milliseconds , using an area that maps stimuli onto responses which we have termed the router network . The model capitalizes on a number of existing elements: ( 1 ) perceptual attractor networks capable of encoding stimuli and maintaining them in an exponentially decaying buffer [62] , [71] , ( 2 ) an accumulation-to-threshold mechanism , comprising both recurrent neuronal assemblies [36] and a thresholding device inspired by the architecture of basal ganglia [81]; ( 3 ) a control network comprising rule-coding units capable of modulating other areas in a top-down manner [32] , [45] , [55] , [82]–[85]; ( 4 ) the concept of a routing circuit implemented by neurons with broad connectivity , capable of transiently interconnecting other brain processors in a flexible manner [33] , [47] , [86]–[89] . The novel aspect of the present simulations is to integrate these theoretical constructs into a global functional architecture . We observed that the interplay between these control and routing mechanisms resulted in a central limitation during dual-task processing , which manifested itself either as a delay in the second task ( PRP ) , or a complete interruption of the processing of a second target ( Attentional Blink ) . Based solely on the known dynamics of neurotransmitter receptors , the model reproduces , in a quantitative manner , a large number of behavioral observations of dual-task interference ( see [17] , [18] , [35] ) : These results are in full accordance with the central interference model [17] , [35] , [90] , by which certain processes are carried out in parallel and routing and accumulation are intrinsically serial . Our model provides a detailed neuronal implementation of this classical psychological model and makes many new predictions for the neurophysiological correlates of the PRP . Several brain-imaging experiments implicated a number of cortical systems in the PRP phenomenon . The cerebral basis of processing bottlenecks has been investigated with Event Related Potential studies ( ERPs ) , which have shown that the PRP results in reduced and/or delayed components [91]–[97] . Using time-resolved fMRI [98]–[100] , Dux and collaborators showed a slight delay in the peak fMRI activity in prefrontal cortex during a PRP paradigm [101] , implying that the PFC was one of the fundamental nodes responsible for the central bottleneck of information processing . Recently , using both time-resolved fMRI and high density ERP recordings we could fully parse the execution of two concurrent tasks in a discrete sequence of processing stages . The ERP analysis demonstrated that a late P3-like complex is in fact delayed by an amount comparable to the PRP effect on RTs , and time-resolved fMRI confirmed that the PRP delayed parietal and prefrontal activation by several hundreds of milliseconds [77] . The notion that the global P3 indexes a late capacity-limited central stage fits with results from the AB . As we could show in the simulations the main difference between the PRP and the AB can be accounted for solely by the masks used to produce the AB , which interfere with the local memory of T2 . The result is that T2 processing is not merely delayed ( PRP ) , but erased and it therefore escapes from consciousness . During AB , the initial ERP components up to about 270 ms are essentially intact , but the P3 component is essentially abolished [73] , [76] , [102] , [103] . The P3 component can only be detected in seen trials , in an all-or-none fashion [73] , [104] . We observed this precise dependence for the activity of routing neurons and the onset of task-setting neurons , suggesting that the P3 is likely to constitute a large-scale electrophysiological marker of the router system . Also , as indicated by our simulations , increased latencies in T1 processing resulted in higher probability of the second target being blinked [73] , [105] , [106] . Direct comparison of AB and PRP paradigms suggests that both affect the same P3 component [95] . The spatial resolution of EEG is very imprecise and thus a better characterization of the locus of central processing bottlenecks in the brain comes from fMRI studies , which have pinpointed a broad parietofrontal network that exhibits various manifestations of central capacity limits [67] , [107] , including the AB [67] , [105] , [108] and the PRP [77] , [101] , [109] , [110] . This network is ubiquitously activated by a large variety of goal directed tasks [107] suggesting that it plays an important role in flexible routing information between remote neuronal representations . Our network postulates a hierarchical organization of this system: neurons controlling the whole-task structure ( order network ) gate neurons controlling the individual tasks ( task-setting network ) , which , in turn , gate the routing from the sensory representations to the motor intention stage . Such a hierarchical organization has been demonstrated in humans in the prefrontal cortex as the Broca region and its homologue in the right hemisphere implement executive processes that control start and end states as well as the nesting of task segments that combine in hierarchically organized action plans [52] , [111]–[114] . A hierarchical organization involved in planning of complex sequential tasks has also been found in non-human primates [113] , [115] . Understanding the emergence of serial behavior in the human brain is an important and central theoretical question in cognitive psychology as modularity and parallel processing are hallmarks of brain computations . Different authors have proposed cognitive architectures that can explain how components of the mind work to produce coherent cognition [14] , [24] , [86] , [116]–[118] . Concrete implementations of these ideas have shown that these coherent states which transiently bind together existing modular processors naturally result in serial behavior [14] , [43] . Here we have tentatively proposed that seriality in dual ( or multiple ) task performance results from the necessity to establish a task set through the activation of a “router” network . This router network is shared by all sensory-motor mappings and its activity can , potentially , code for a virtually infinite number of possible tasks . A task-setting program acts as a gate , permitting routing neurons to propagate information if they receive the appropriate sensory input . This system acts as a control mechanism that avoids erroneous , conflicting or unwanted stimulus-response associations . We showed that a concrete implementation of such a control system results in serial behavior of the routing process when probed in dual-task situations . In our network , seriality and its behavioral manifestations , the PRP and the Attentional Blink , emerged from competition between task-setting neurons which , through a lateral inhibition process , prevented the simultaneous activation of two task settings . This form of control is necessary to ensure correct task performance in conflicting mappings - as classically demonstrated in the Stroop paradigm in which the same stimulus may lead to distinct responses according to task requirements [119] . While this mechanism is strictly required only in conflicting response mapping situations , which is not the case in our present simulations , it is possible that it has emerged as a ubiquitous mechanism in control networks to assure correct task performance . Seriality in non-conflicting tasks would therefore emerge as a consequence of the need for a flexible mechanism linking stimuli with multiple responses according to context [28] , [29] . Another possible origin of seriality relates to the coding properties of the router ( for a simple illustration see Figure S6 ) . Here we have explored a comparatively simplified situation of a small number of tasks , stimuli and responses in which all possible routings were coded by distinct neural populations . This mechanism would result in a combinatorial explosion in a more realistic setup , arguing that the code of router neurons should be distributed , i . e . each routing scheme should be encoded in a large population of neurons . This is consistent with many findings in prefrontal cortex neurons which have found that a large fraction of neurons respond to virtually all tasks [83] . In this scheme , the precise pattern of active and inactive neurons determines the code and thus superposing two routing configurations ( of two distinct tasks ) should result in a mixture leading to erroneous mapping properties . Avoidance of incorrect mappings in a combinatorial router can be implemented by the same mechanism shown here , leading to serial routing in the composition of flexible task settings ( Figure S6 ) . Previous modeling efforts have established cognitive architectures which can account for human complex problem solving [14] , [24] , [116] . The adaptive control of thought–rational ( ACT-R ) , for example , proposes a theory of distinct modules that interact with each other to produce coherent cognition [14] . While ACT-R is based on a sequential scheme , the temporal constant of the sequential step in ACT-R and in the PRP are not comparable: in ACT-R , productions ( if-then structures representing procedural knowledge ) fire approximately every 50 ms , about five times faster than the PRP delay . The 50 ms delay of individual productions is consistent with other experimental approaches which have suggested a discrete organization of cognition at a frequency close to 13 Hz [120] . These observations of ∼50 ms productions and the comparably slower ∼300 ms PRP delay can be reconciled by modeling the entire routing program as a sequence of productions , as in the ACT-R implementation of the PRP of Byrne and Anderson [25] . Sensory modules in the ACT-R involve a two-layer structure , a visual module ( mapped to occipital/temporal regions ) and a visual buffer ( mapped to parietal regions ) . The visual buffer incorporates a selection mechanism that determines the contents of the visual system which will be available to other processors . Our model provides a concrete neuronal implementation of these mechanisms . In our model , the sensory hierarchy acts as a module which can select and maintain information locally ( unless a subsequent element such as the mask overrides the buffer ) . This information can be broadcasted to the rest of the network . Similarly , in ACT-R the selection of actions is achieved by a loop that mimics the Basal-Ganglia- cortical connections . By building up on previous architecture for thresholding and gating sensory information through striatal-cortical interactions [44] our model provides a neuronal implementation of these mechanisms . The router circuit in our model builds on previous computational models which have studied the role of contextual signals on transient sensory-motor mappings [30] , [33] , [121] , [122] . Salinas ( 2004 ) showed that a linear read-out of sensory input could result in arbitrary sensory-response mappings if sensory responses are modulated by ( a non-linear ) contextual influence . A concrete implementation of flexible mapping by rule-setting contextual signals was developed by Deco and Rolls [47] , [123] . In the present model , the router binds sensory and motor representations . Similar conceptions of flexible routing circuits have been applied to other instances of information binding such as , linking the attributes of an object in pattern recognition [89] or linking discrete objects to temporal contexts through distributed representations as recently proposed by Wyble and Bowman [124] . Olshausen and colleagues implemented a routing scheme in a set of control neurons which rapidly modify the strength of intra-cortical connections to implement the attentional gating of information flow from early visual representations to a higher level object-centered reference frame [89] , [125] . The SAIM model of selective attention [88] , [126] has shown how this ‘dynamic routing’ model can be extended to account for a wide range of results of visual experiments with competing stimuli in space , i . e . neglect [127] or in time , i . e . inhibition of return [88] in both normal and impaired subjects . The SAIM model [88] shares many features with our network: it implements a routing neuron which is modulated by a control ( task-setting ) network and thus acts as a coincidence-detector of a task-setting program and current sensory state . Recently , Heinke and collaborators showed how the SAIM model can be implemented with spiking units [126] . Our network provides an implementation of simple boxological models of dual-task execution in the PRP [17] , [34] , [35] . While very simple , these models have established a vast range of predictions in behavioral experiments regarding the precise functional dependence of RTs with SOA and how these functions should change with different manipulations . By incorporating ideas of models of decision making , we previously generated a schematic model that accounts for the entire distribution of RTs and how it changes in the interference regime [18] . Here we have shown that these ideas can be implemented robustly in realistic network architecture . A critical aspect of our network is that while the router is occupied by T1 , the T2 stimulus was maintained in the recurrent activity of high-level sensory units , thus forming a memory which remains local because it cannot activate the router . This coexistence of parallel mechanisms – a cascade of sensory processes which encode the stimulus - and of serial bottlenecks – queuing by the routing process - constitutes a hallmark of PRP observations . Our network implemented this local memory as a local attractor showing progressive integration and exhibiting a metastable form of memory that could be maintained for a few hundred milliseconds . According to this proposed mechanism , the memory trace remains stored in a local network and is relatively fragile as it can readily be overridden by a mask . The critical observation is that the mask can only override processing of T2 if it the router is occupied by T1 . To our knowledge , our model is the first one to propose a concrete neural implementation of the mechanisms leading to the PRP . In contrast , several computational models have been recently proposed for the attentional blink [43] , [78] , [128]–[130] . Two current explanations include the simultaneous type serial token ( ST2 ) model [78] which proposes that access of sensory representations to working memory is gated by an episodic-driven attentional signal and the boost and bounce model [130] which suggests that a target initiates an attentional boost which is interrupted when the trailing task-irrelevant stimulus is accidentally boosted . Our model shares with the ST2 model the idea of gating of a router-system and with the boost and bounce model that task-setting activation is not a phasic event , but rather , can stay active until it is inhibited by a termination signal . We emphasize that our model does not intend to give a detailed account of all the findings from attentional blink experiments , but instead to show how the same mechanisms that lead to delayed responses in the PRP can lead to missed targets in the AB . Recent reviews of the extensive AB literature argue for a multifactor origin in this processing deficit [131] , and thus it might be impossible to pinpoint a single mechanism behind the full diversity of experimental findings ( although see [132] , [133] ) . Nevertheless , our results show that limited capacity operations – as the one implemented by our router/task-setting network – may play a central role in the attentional blink [72] , [134] . One aspect of the attentional blink phenomena which our model fails to replicate is the relative increase in performance observed at very short SOA ( ∼100 ms ) , an effect known as lag-1 sparing [5] . This effect is not observed when T1 and T2 involve different modalities [135] ( as in our simulations of the AB ) or spatial locations [136] . Recent experiments show that the sparing can even be spread to several targets presented rapidly without intervening distractors [137] , [138] , suggesting that the unit of selection of a serial attentional process is not the individual target but an extended event which may include several rapidly presented targets [132] , [139] , [140] . This grouping does not happen without a cost , since order swapping and performance tradeoffs between different targets do occur [78] , [141] . In our model , the task-setting configuration is sustained until information is routed to the motor system , and thus it might be possible to extend the present model such that more than one target in a RVSP benefits from the same task-setting configuration . Processing a temporally extended event encompassing several targets would require broadening – in feature space - the action of the task-setting network as well as making the router/task-setting complex capable of flexibly routing information not only to motor areas but also to mnemonic [142] or sensory areas in order to achieve recursive computations . In fact , we see the extension of the present model along the lines just discussed: the different types of neurons used in our implementation ( briefly reviewed in the next section ) have been found in the awake behaving monkey and may serve as a basis from which to construct complex cognitive programs , as those implemented in systems like ACT-R [3] or SOAR [143] - but with a stronger grounding on neurophysiological findings [144] . In this implementation , we see router neurons as capable of accumulating evidence not only towards a motor response , but implementing a full production system [145] , [146] where stochastic rules are selected according to the information contained in different mnemonic systems which are in turn updated by external stimuli and by the action of the productions themselves . These ideas will form the basis for a future extension of the present model to flexible series of chained tasks . Most , if not all , types of neurons used in our implementation have been observed in studies that measured single-neuron activity in awake behaving monkeys during single-task performance . Here we will briefly mention the main types of neurons in the various areas of our model and compare them to neurophysiological data , a comparison that will have to remain somewhat superficial as we cannot attempt to discuss the precise relationships between the variety of tasks employed in the neurophysiological studies and the PRP task implemented here . Firstly , the properties of the sensory areas of our model are consistent with what is known about representations in areas of sensory cortex . Neuronal activity in low level sensory cortex is largely ( but not entirely ) determined by the incoming sensory information [147] , while neurons in higher areas carry information about the behavioral relevance of stimuli , as well as traces of stimuli to be remembered [148] . Secondly , neurons in areas of parietal and frontal cortex have response properties consistent with the routing process proposed by our model . Many of these cells are tuned to categories of stimuli that are associated with a particular behavioral response [149]–[151] and integrate evidence in favor of one of a number of possible actions until a threshold is reached , just as is required by the model's router [152]–[154] . Thirdly , some neurons in the frontal cortex only respond if a particular stimulus maps onto a particular motor response , but not when the same stimulus or response is part of a different stimulus-response mapping [60] , and yet other prefrontal neurons code abstract rules [84] . Clearly , the response properties of these neurons are in accordance with the model's task-switching network . Finally , neurons in the motor response selection stage of our model have either a gradually increasing activity before the response or they respond with a sharp burst at the time of the response . Neurons with gradually increasing activity before the motor response and cells with a motor burst are indeed observed in areas of the motor cortex [155] , [156] as well as in the basal ganglia [157] . These results , taken together , indicate that the types of units required by our implementation are broadly consistent with the types of neurons that are observed in neurophysiological experiments . Our network can also explain timing and latencies of the sequence of events identified in single-task physiological experiments in monkeys [158]–[160] and humans [161] . Accumulation of information about the upcoming response influences the firing rate of routing neurons at a latency of about 200 ms , a latency that may be relatively fixed for a given task [162] . This latency cannot be explained solely by synaptic delays , since measurements of conduction velocity of cortical feedforward and feedback connections showed that they can be rapid , even faster than intrinsic connections within a cortical area [163] , [164] . A previous neurophysiological study showed that the onset of response modulation in the visual cortex depends of the sequencing of subtasks , with later modulation for subtasks that occur later in a sequence [165] . Our model grasps this observation: the latency of the response of routing neurons depends on the order in which the two subtasks are executed ( Figure 3B–C ) . The present results suggest that the latency of feedback modulation may reflect the time required by the network to settle into a brain-scale state of coherent activity [18] , [87] , which in our model is reflected by a coherent pattern of activity across sensory , router , and task-setting networks coding different aspects of the same subtask . Our observations also raise a note of caution on the interpretation of processing latencies from physiological data . A concrete example is conveyed in our model by the measurement of activity in the routing neurons . Spiking activity shows a clear sequential scheme: routing neurons of T2 start integrating only once routing of T1 has completed ( Figure 3B ) . Thus , the latency at which spiking activity exceeds a certain threshold constitutes a physiological marker of the PRP effect . The picture is quite distinct if one would measure synaptic router activity ( Figure S3 ) . During the time in which T1 is being routed and T2 is being buffered , T2 sensory neurons spike and project silently ( i . e . without evoking spiking responses ) to router neurons . Hence synaptic activity in T2 router neurons increases during T2 compared to baseline . A consequence of this observation , which may be of relevance beyond the specifics of this study , is that timing analysis based on synaptic or spiking activity yield qualitatively different observations . Various studies have simultaneously measured different markers of neurophysiological activity such as multi-unit activity ( MUA ) , laminar current-source density ( CSD ) and local field potentials ( LFP ) [166] and fMRI [167] or EEG [168] . Multimodal interactions have been shown to display such a mixed effect in response latencies . Primary auditory cortex shows a clear CSD response to somatosensory stimulation , without observable changes in the spiking response as measured by MUA [169] . Computational models may be a useful link to bridge information gathered at different scales . Our data showed that fluctuation in response time could be accounted by the dynamics of noise fluctuations in relation to the timing of stimulus routing ( Figure 6 ) . When noise is oscillatory , this is determined by a precise phase relation . Our model does not explain how this relation can be entrained . Neurophysiological data of multi-sensory integration suggests that somatosensory stimuli can reset the phase of ongoing oscillations in primary auditory cortex such that auditory stimuli are boosted if presented during the high excitability phase [169] , [170] . Also , it has been shown that neuronal oscillations can entrain to environmental rhythms improving discriminative performance and decreasing response times [65] , [66] . As mentioned , these aspects lie outside the scope of the present model . The correlates of the bottleneck have yet to be studied at the single cell level and our simulations therefore generated a number of new predictions that could be tested in future neurophysiological experiments . First the model establishes the existence of routing and task-setting neurons with well distinct dynamics and connectivity with different neuronal populations . At the anatomical level , routing neurons should receive inputs from all sensory modalities and from task setting neurons . At the functional level , they should be characterized by their firing in response to specific conjunctions of stimuli and responses , a preference which may change dynamically according to task context , on a time scale of about 100 ms or more ( for supporting evidence , see [60] , [113] ) . Task-setting neurons should engage in a competition such that two task-setting programs or routing schemes cannot coexist in time . This should avoid unwanted mappings but also causes an inertia which results in relatively slow switching ( >100 ms ) from one task-setting to another leading to seriality in the routing process . In a PRP experiment , neurons coding for the memory T2 stimulus should show a characteristic temporal profile , comprising ( 1 ) a phasic sensory response , time-locked to actual stimulus presentation , ( 2 ) a sustained response exhibiting a slow exponential decay , and ( 3 ) a late amplification at the time when task 1 routing is completed and the router neurons of task 2 become active . On the contrary , the onset of router and task-setting neurons of Task 2 should be delayed at short SOA , with a delay that should decrease with SOA because task 2 router neurons are released from the inhibition of task 1 as soon as it is completed . In trial-by-trial comparisons , at short SOA values , the onset of router and task-setting neurons of T2 should be locked to the response time of the first task . While sharing the onset , the model predicts distinguishable time-courses of activations for router and task-setting neurons . Task-setting neurons should show sustained high-levels of activation throughout the duration of the task while router-neurons activity should ramp to a critical threshold . In an AB experiment task-setting neurons of T2 should be active both in seen and unseen trials . Only in unseen trials should the memory of T2 fade below a threshold ( either due to fluctuations in transient response or in the durations of the memory due to the extension of T1 ) impeding routing and broadcasting to the rest of the network . These predictions will become testable once an awake animal model of dual-task performance is defined .
The model contains 21 , 000 neurons and 46 , 634 , 400 synapses . Neurons were either excitatory or inhibitory . All neurons were modeled as conductance-based leaky integrate and fire units . The membrane potential of each cell below the threshold for spike generation is described by: ( 1 ) where is the total synaptic current flowing into the cell , = −70 mV is the resting potential , is the membrane capacitance ( 0 . 5 nF for pyramidal cells and 0 . 2 nF for interneurons ) , and is the membrane leak conductance ( 25 nS for pyramidal cells and 20 nS for interneurons ) . The threshold for spike generation was set to −50 mV . The reset potential after spike generation is −55 mV , and the refractory period is 2 ms for pyramidal cells and 1 ms for interneurons . All neurons receive large amounts of background synaptic activity which determines the level of spontaneous activity . External inputs and background activity are mediated exclusively by AMPA receptors . Recurrent excitation is mediated by AMPA and NMDA receptors , and inhibition is mediated by GABA receptors . The total synaptic currents are given by: ( 2 ) in which ( 3 ) ( 4 ) ( 5 ) ( 6 ) where = 0 mV and = −70 mV . The extracellular magnesium concentration = 1 mM controls the voltage dependence of NMDA currents [171] . and are the number of excitatory and inhibitory inputs , respectively . The values of the synaptic efficacies g are given below . The dimensionless factor w controls the strength of recurrent connections between neurons with similar response properties ( see below ) . in equations 3–6 is the gating variable - or fraction of open channels –updated according to the activity of the presynaptic neuron j and the identity of the receptor mediating the transmission . The dynamics of the gating variables are as follows . When a neuron receives a presynaptic action potential the appropriate gating variable s is increased . Otherwise , these variables decay exponentially . For AMPA and GABA receptors: ( 7 ) For NMDA receptors: ( 8 ) where is the time of presynaptic spike k and α = 0 . 63 controls the saturation properties of NMDA channels . The decay time constants are τNMDA = 100 ms , τAMPA = 2 ms , and τGABA = 10 ms . Neurons are grouped into homogeneous populations . A total of 84 unique populations were included in the simulations . In sensory and routing areas these homogeneous populations were grouped into larger groups , forming local modules as used in previous studies [36] , [37] . The proposed network simulates a generic PRP experiment . Observers ( and the network ) must perform two tasks as fast as possible , in a pre-specified order . Each task involves a simple two-alternative decision . In the network , the set of possible task-related stimuli in each modality is restricted to two , as is often the case in real PRP experiments . All neurons receive background Poisson input to maintain a spontaneous activity of a few Hertz . The presentation of a task-relevant stimulus increased the external input of the four selective populations in the first level sensory network , from the background level of 2 , 400 Hz ( as may result from 800 afferent neurons spiking at a spontaneous rate of 3Hz ) to 2 , 717 Hz , for 100 ms ( thus ) . All external inputs , both background and stimulus-related , are mediated exclusively by AMPA receptors . In Figure 4 we investigated the effect of changing the complexity of sensory processing . This was implemented by adding one additional module in the sensory hierarchy , between levels two and three . This additional module had the same number of neurons and recurrent , feedforward , and feedback parameters as the other sensory modules , with w = 1 . 94 . In the same figure we also showed the effect of changing the amount of sensory evidence in favor of the correct decision . In this case , the input to the stimulus projecting to the correct response was and to the other , with f = 0 . 92 in the high ambiguity case ( f = 1 in all other simulations ) . In the attentional blink ( AB ) simulations , a mask is presented after the task-relevant stimulus . This was modeled as in previous studies [71] . After the stimulus is removed , the external input to the non-selective cells in the first level sensory network is increased , from the background level of 2 , 400 Hz to 2 , 880 Hz , during 100 ms ( thus ) . Each simulated trial lasted 3400 ms . The first stimulus was presented at 700 ms , and the second stimulus was presented according to the SOA . The code was written in C++ , and simulations were performed in the CECAR computer cluster ( Buenos Aires University ) . Equations were integrated with the first-order Euler method , with a time step of 0 . 05 ms . When run on a Linux 3 . 16 Ghz Pentium IV PC , each trial takes about 3 minutes to complete .
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A ubiquitous aspect of brain function is its quasi-modular and massively parallel organization . The paradox is that this extraordinary parallel machine is incapable of performing a single large arithmetic calculation . How come it is so easy to recognize moving objects , but so difficult to multiply 357 times 289 ? And why , if we can simultaneously coordinate walking , group contours , segment surfaces , talk and listen to noisy speech , can we only make one decision at a time ? Here we explored the emergence of serial processing in the primate brain . We developed a spiking-neuron implementation of a cognitive architecture in which the precise sensory-motor mapping relies on a network capable of flexibly interconnecting processors and rapidly changing its configuration from one task to another . Simulations show that , when presented with dual-task stimuli , the network exhibits parallel processing at peripheral sensory levels , a memory buffer capable of keeping the result of sensory processing on hold . However , control routing mechanisms result in serial performance at the router stage . Our results suggest that seriality in dual ( or multiple ) task performance results as a consequence of inhibition within the control networks needed for precise “routing” of information flow across a vast number of possible task configurations .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"neuroscience/behavioral",
"neuroscience",
"neuroscience/cognitive",
"neuroscience",
"neuroscience",
"neuroscience/experimental",
"psychology",
"neuroscience/theoretical",
"neuroscience"
] |
2010
|
The Brain's Router: A Cortical Network Model of Serial Processing in the Primate Brain
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Genome Wide Association Studies ( GWAS ) and expression quantitative trait locus ( eQTL ) analyses have identified genetic associations with a wide range of human phenotypes . However , many of these variants have weak effects and understanding their combined effect remains a challenge . One hypothesis is that multiple SNPs interact in complex networks to influence functional processes that ultimately lead to complex phenotypes , including disease states . Here we present CONDOR , a method that represents both cis- and trans-acting SNPs and the genes with which they are associated as a bipartite graph and then uses the modular structure of that graph to place SNPs into a functional context . In applying CONDOR to eQTLs in chronic obstructive pulmonary disease ( COPD ) , we found the global network “hub” SNPs were devoid of disease associations through GWAS . However , the network was organized into 52 communities of SNPs and genes , many of which were enriched for genes in specific functional classes . We identified local hubs within each community ( “core SNPs” ) and these were enriched for GWAS SNPs for COPD and many other diseases . These results speak to our intuition: rather than single SNPs influencing single genes , we see groups of SNPs associated with the expression of families of functionally related genes and that disease SNPs are associated with the perturbation of those functions . These methods are not limited in their application to COPD and can be used in the analysis of a wide variety of disease processes and other phenotypic traits .
Genome Wide Association Studies ( GWAS ) have created new opportunities to understand the genetic factors that influence complex traits . Excepting highly-penetrant Mendelian disorders , the majority of genetic associations seem to be driven by many factors , each of which has a relatively small effect . In a recent study [1] , 697 SNPs were associated with height in humans at genome-wide significance , yet these SNPs were able to explain only ∼20% of height variability; ∼9 , 500 SNPs were needed to raise that to ∼29% . In addition , ∼95% of GWAS variants map to non-coding regions [2] , complicating biological interpretation of their functional impact . To bridge the functional gap between genetic variant and complex trait , expression Quantitative Trait Locus ( eQTL ) analysis associates SNP genotype with gene expression levels . The first empirical , genome-wide linkage study with gene expression in yeast was published in 2002 , linking expression levels of 570 genes to genetic loci [3] . In humans , loci have been associated with the expression of thousands of genes [2 , 4] , and eQTLs are enriched for phenotype associations and vice versa [5–7] . Most eQTL analyses have focused on cis-SNPs—those near the Transcriptional Start Site ( TSS ) of the gene in the association test . Recent computational developments [8] and work demonstrating the impact and replicability of trans-eQTLs [9 , 10] have increased interest in identifying and understanding the role played by trans-acting SNPs . However , new methods are needed to elucidate the potential functional impact of the thousands of GWAS SNPs and tens to hundreds of thousands of eQTL SNPs that can be detected in a single study . Here we present CONDOR , COmplex Network Description Of Regulators , ( Fig 1 ) a method that incorporates both cis- and trans- associations to identify groups of SNPs that are linked to groups of genes and systematically interrogate their biological functions . The method has been implemented as an R package and is publicly available at https://github . com/jplatig/condor . We then validate this approach using genotyping and gene expression data from 163 lung tissue samples in a study of Chronic Obstructive Pulmonary Disease ( COPD ) by the Lung Genomics Research Consortium ( LGRC ) .
We used the MatrixEQTL package in R to calculate cis- and trans-eQTLs , considering only autosomal SNPs , using age , sex , and pack-years as covariates ( see Methods ) . The cis- and trans- associations were run separately , with an FDR threshold of 10% . This analysis identified 40 , 183 cis-eQTLs and 32 , 813 trans-eQTLs . Quantile-quantile plots for both cis- and trans- are shown in Fig 2 . In total , 72 , 996 statistically significant associations were detected between 57 , 062 SNPs and 7 , 051 genes . We represented these associations as a bipartite network consisting of two classes of nodes—SNPs and genes—with edges from SNPs to the genes with which they are significantly associated based on the eQTL FDR cut-off . The network had a Giant Connected Component ( GCC ) with 41 , 813 links , 28 , 593 SNPs , and 3 , 091 genes . As a network diagnostic , we estimated whether or not we could reject the hypothesis that the SNP and gene degree distributions were power-law distributed . To test this , we fit each degree distribution to a power law , and determined the goodness of fit using the method described in [11] ( see Methods ) . If the edges from all connected components are considered , the p-value for the SNP degree is very low , Ppl ≈ 0 , suggesting that we can rule out a power law distribution . However , if very small connected components ( fewer than 5 SNPs and 5 genes ) are excluded , the SNP degree may follow a power-law ( Ppl < 0 . 8 ) as shown in Fig 3a . The gene degree distribution ( Fig 3b ) may be power-law distributed when considering all connected components or only those with more that 5 SNPs and 5 genes ( Ppl < 0 . 4 in both cases ) and there are multiple network hubs , shown in the tail of the distribution in Fig 3b . For our further analysis we considered all connected components with more than 5 SNPs and 5 genes . It is often cited in complex networks literature that the hubs , those nodes in the network that are most highly connected , represent critical elements whose removal can disrupt the entire network [12 , 13] . As a result , one widely-held belief about biological networks is that disease-related elements should be over-represented among the network hubs [14] . To test the hypothesis that disease-associated SNPs are concentrated in the hubs , we projected GWAS-identified SNPs associated with a wide range of diseases and phenotypes onto the SNP degree distribution ( Fig 4 ) . We used the gwascat package [15] in R to download GWAS SNPs annotated in the NHGRI GWAS catalog; 274 of those SNPs mapped to the eQTL network ( S1 Table ) . To our surprise , the network hubs—the right tail of Fig 4—were devoid of disease-associated SNPs which were instead scattered through the upper left half of the degree distribution . The difference in degree distributions did not appear to be driven by linkage disequilibrium or distance to nearest gene ( see Methods and S1 , S2 , S3 and S4 Figs ) . While the SNPs associated with a single gene are easier to interpret , the concentration of disease-associated SNPs in the middle of the distribution prompted us to look at other features of the network and its structure . Given the low phenotypic variance explained by any single GWAS SNP , we expected groups of SNPs to cluster with groups of functionally-related genes in our eQTL network . Unlike previous work [16–18] which imposes “known” pathway annotations and other data to posit the function of GWAS SNPs or identifies modules with only a handful of SNPs [19] , we used the structure of the eQTL network to identify densely connected groups of SNPs and genes and then tested those groups for biological enrichment . Our goal is the identification of those densely connected communities in the bipartite network . Methods for finding bicliques ( subgraphs with all-to-all connections within the larger bipartite network ) have been described for bipartite networks with a small number ( ∼102 ) of nodes in each connected component [20] . However , these methods do not scale to networks with connected components containing thousands of nodes [20 , 21] . Further , we do not expect biologically meaningful eQTL clusters to contain only all-to-all connections . To cluster our eQTL network , we adapted a well-established strategy [22] , community structure detection , which has been shown to scale well to large networks [23] . Many real-world networks have a complex structure consisting of “communities” of nodes [24] . These communities are often defined as a group of network nodes that are more likely to be connected to other nodes within their community than they are to those outside of the community . A widely used measure of community structure is the modularity , which can be interpreted as an enrichment for links within communities minus an expected enrichment given the network degree distribution [22] . To partition the nodes from the eQTL network into communities—which contain both SNPs and genes—we maximized the bipartite modularity [25] . As recursive cluster identification and optimization can be computationally slow , we calculated an initial community structure assignment on the weighted , gene-space projection , using a fast uni-partite modularity maximization algorithm [23] available in the R igraph package [26] , then iteratively converged ( ΔQ < 10−4 ) on a community structure corresponding to a maximum bipartite modularity . The bipartite modularity is defined in Eq ( 1 ) , where m is the number of links in the network , A ˜ i j is the upper right block of the network adjacency matrix ( a binary matrix where a 1 represents a connection between a SNP and a gene and 0 otherwise ) , ki is the degree of SNP i , dj is the degree of gene j , and Ci , Cj the community indices of SNP i and gene j , respectively ( see [25] for further details ) . Q = 1 m ∑ i , j A ˜ i j - k i d j m δ ( C i , C j ) ( 1 ) This analysis identified 52 communities across 10 connected components in the LGRC data , with 34 of those communities mapping to the GCC ( Qgcc = 0 . 79; Fig 5 ) . The density of these communities can be seen in Fig 5 . In Fig 5b , there is visible enrichment for links within each community ( colored links ) compared to links between different communities ( black links ) . These communities represent groups of SNPs and genes that are highly connected to each other and span multiple chromosomes ( see Fig 6 ) , suggesting that groups of genes may be jointly moderated by groups of SNPs that together represent specific biological processes . To investigate this hypothesis , we tested each community for GO term enrichment using Fisher’s Exact Test ( available in the R package GOstats [27] ) and found 11 of the 52 communities contained genes enriched for specific Gene Ontology terms ( see S2 Table ) ( P < 5e − 4; overlap >4 ) , encompassing a broad collection of cellular functions that are not generally associated with COPD . Indeed , this is what one might expect as the genetic background of an individual should have an effect not only on disease-specific processes , but more globally on the physiology of his or her individual cells . A number of communities do , however , show enrichment for biological processes that are known to be involved in COPD , including genes previously associated with the disease . For example , Community 29 ( see Fig 5 and S2 Table ) was enriched for chromatin and nucleosome assembly/organization and includes members of the HIST1H gene superfamily . Community 33 ( see Fig 5 and S2 Table ) included GO term enrichment for functions related to the HLA gene family , including T cell function and immune response; autoimmunity has been suggested as a potential contributor to COPD pathogenesis [28] . This community also contains PSORS1C1 , which has been previously implicated in COPD [29] . Another of the genes in Community 33 , AGER , has been implicated in COPD [30] and encodes sRAGE , a biomarker for emphysema . Its expression is negatively associated via eQTL analysis ( β = −0 . 3 ) with rs6924102 . This SNP has been observed to be an eQTL in a large blood eQTL dataset for a number of neighboring genes [9] , but it has not previously been described as an eQTL for AGER . This SNP lies in a region containing a DNase peak in cell lines analyzed by ENCODE [31] ( indicating it sits in a region of open chromatin ) and there is evidence of POLR2A binding from ChIP-Seq data in the GM12878 cell line as reported by ENCODE ( http://regulomedb . org/snp/chr6/32811382 ) . This suggests that rs6924102 may inhibit the expression of AGER through disruption of RNA Polymerase II binding and subsequent mRNA synthesis . This SNP is located ∼700KB from the well-studied non-synonymous AGER SNP , rs2070600 . Examining Fig 5a , it is evident that within each community there are local hubs that are highly connected to the genes within that community . While a wide array of network node metrics exist ( for example , [32 , 33] and references in [33] ) , most of these metrics are global measures that do not consider a node’s role in its local cluster/community and so may miss SNPs that are central to their communities and therefore likely to alter gene expression of functionally associated genes . Such within-community hubs have been observed in protein-protein interaction networks [34] and metabolic networks [35] . We defined a core score that estimates importance of a SNP in the structure of its community . For SNP i in community h , its core score , Qih , Eq ( 2 ) , is the fraction of the modularity of community h , Qh , Eq ( 3 ) , contributed by SNP i . This allows for comparison of SNPs from different communities , as each community does not have the same modularity , Qh . Q i h = 1 m ∑ j ( A ˜ i j − k i d j m ) δ ( C i , h ) δ ( C j , h ) Q h ( 2 ) Q h = 1 m ∑ i , j ( A ˜ i j − k i d j m ) δ ( C i , h ) δ ( C j , h ) ( 3 ) If one views disease as the disruption of a process leading to cellular or organismal dysfunction , one natural hypothesis is that SNPs with the greatest potential to disrupt cellular processes might be enriched for disease association . To test this we used both the Wilcoxon rank-sum and Kolmogorov-Smirnov ( KS ) tests to assay whether the 274 NHGRI GWAS-annotated SNPs in the network were more likely to have high Qih scores . For both tests , the distribution of Qih scores for GWAS-associated SNPs were compared to the distribution of non-GWAS SNP scores . To obtain an empirical p-value for these tests , we permuted the GWAS/non-GWAS labels and recalculated the KS and Wilcoxon tests 105 times . Histograms of the test statistics are shown in Figs 7 and 8 . The red dot in the histogram represents the test score with the true labeling . Both tests had highly significant permutation p-values , with P < 10−5 for the KS and Wilcoxon tests , indicating that GWAS SNPs were over-represented among SNPs with high core scores . Furthermore , the median core score for the GWAS SNPs was 1 . 74 times higher than the median core score for the non-GWAS SNPs . To test this result for dependence on Linkage Disequilibrium ( LD ) and gene distance , we reran the KS and Wilcoxon permutation tests with a subset of SNPs matching the LD structure and distance to nearest gene of the 274 GWAS SNPs ( see Methods for details ) . Neither the LD structure ( P < 0 . 001 for KS and Wilcoxon tests , S5 and S6 Figs ) nor distance from the nearest gene ( P < 0 . 001 for KS and Wilcoxon tests , S7 and S8 Figs ) of the GWAS SNPs was signficantly associated with the core score . Thus , while global hubs are devoid of GWAS associations with disease , local hubs within communities are significantly enriched for disease associations . As a way of further assessing the link between GWAS significance and functional perturbation in COPD , we calculated a GWAS-FDR for all SNPs clustered in our network that had a reported p-value from a recent GWAS and meta-analysis of COPD [36] ( see Methods ) . There were 30 SNPs with an FDR < 0 . 05 , and 28 of the 30 had evidence of functional impact according to RegulomeDB [37] , with 15 SNPs identified as likely to affect transcription factor binding and linked to expression ( See Fig 9 and S3 Table ) . These 30 SNPs mapped to 3 different communities ( see S3 Table ) including Community 33 , which contains other COPD-associated SNPs and genes , and is enriched for GO terms describing T cell function and immune response . One of the SNPs in this community likely to affect binding ( S3 Table ) is rs9268528 , which is linked by our network to HLA-DRA , HLA-DRB4 , and HLA-DRB5; the cis-eQTL associations between rs9268528 and both HLA-DRA and HLA-DRB5 have been previously observed in lymphoblastoid cells [38] . All three HLA genes lie in Community 33 and contribute to the community’s enrichment for T cell receptor signaling pathway ( GO:0050852 ) [39] . To determine the network influence of these 30 SNPs , we compared their core score , Qih , to the core scores of SNPs with a GWAS-FDR ≥ 0 . 05 ( See Fig 10 ) . The median Qih value for the 30 GWAS-FDR significant SNPs was 20 . 3 times higher than the median for SNPs with an FDR ≥ 0 . 05 . Using the KS and Wilcoxon tests described in the Methods , these core scores were not significantly associated with LD structure ( P < 0 . 001 , S9 and S10 Figs ) or distance to nearest GSS ( P < 0 . 001 , S11 and S12 Figs ) . Genome-wide association studies have searched for genomic variants that influence complex traits , including the development and progression of disease . However , the number of highly-penetrant Mendelian variants that have been found is surprisingly small , with most disease-associated SNPs having a weak phenotypic effect . GWAS studies have also identified many SNPs that do not alter protein coding and have found significant loci that are shared in common across multiple diseases . This body of evidence suggests that in most instances it is not a single genetic variant that leads to disease , but many variants of smaller effect that together can disrupt cellular processes that lead to disease phenotypes . The challenge has been to find these variants of small effect and to place them into a coherent biological context . We chose to address this problem by analyzing the link between genetic variants and the most immediate phenotypic measure , gene expression . In doing so , we chose not to focus solely on cis-acting SNPs , but also to consider trans-acting variants . Our motivation was , in part , to try to understand SNPs found through GWAS studies to be associated with phenotypes , but that could not be immediately placed into a functional context . After performing a genome-wide cis- and trans-eQTL analysis , we identified a large number of many-to-many associations: single SNPs associated with many genes as well as single genes that were significantly associated with many SNPs . To represent those associations , we constructed a bipartite network , one that contains two types of nodes—SNPs and genes—with edges connecting SNPs to the genes with which they were significantly associated . Our analysis of that network led to a number of observations that independently speak to our intuition about disease and the genetic factors that control it . First is the observation that the highly connected SNPs , the global hubs in the network , are devoid of variants that have been identified as being disease-associated in the hundreds of studies collected in the NHGRI GWAS catalog . While initially surprising , further consideration suggests that this may be the result of negative selection . Since a true hub SNP influences genes across the genome that are involved in many biological processes , highly disruptive variants that are hubs are likely to significantly affect cellular function . In fact , this is the expected impact of a hub—its disruption should lead to the catastrophic collapse of the network . And so , disruptive SNPs that would be network hubs are likely to be lethal or highly debilitating and therefore strongly selected against and quickly swept from the genome . Second , we found that SNPs and their target genes form highly connected communities that are enriched for specific biological functions . This too speaks to our inituition and to the evidence about polygenic traits that has accumulated over time . They are not the result of a single SNP that regulates a single gene , but a family of SNPs that together help mediate a group of functionally-related genes . Third , the enrichment for GWAS disease associations among the high core score SNPs has a very simple and intuitive interpretation . The SNPs that are most significantly connected within a particular functionally-related group are those most likely to disrupt that process and therefore be discovered in GWAS analysis . After all , diseases do not develop because the cell’s entire functionality collapses , but because specific processes within the cell are disrupted . What our analysis provides is a new way of exploring cis- and trans-eQTL analysis and GWAS . What one must do is to consider not only the local effects of genetic variants , but also the complex network of genetic interactions that help regulate phenotypes , including gene expression . This method also suggests a new way of filtering genes for inclusion in GWAS analysis . Since many disease-associated SNPs appear to be either cis-acting or those which are central to functionally-defined communities , one could focus on those SNPs most likely perturb specific biological processes rather than considering the entirety of SNPs in the genome . One might note that this analysis was carried out using data on genetic variation and gene expression from the LGRC representing COPD and control lung tissue and question both the generalizability of the results and the use of GWAS-associated disease SNPs from many diseases in the analysis . While these are potentially legitimate concerns , many of the community-based processes we find are not specific to COPD or to the lung but instead are active in nearly all human cell types . Although one might expect some processes to change in different disease states , the impact of common variants and the structure of the network is likely to be highly similar . Consequently , although there may be some SNPs whose impact is disease- and tissue-specific , many are likely to be independent of disease state . This suggests that it may be useful to develop eQTL networks across disease states and tissue types and to explore changes in the overall network and community structure across and between phenotypes due to rare variants and tissue-specific expression . Validating individual associations in the eQTL network is a difficult challenge . Most eQTL studies limit their validation efforts to downstream effects of high-confidence cis-acting eQTLs . The bipartite network presented here captures not only these strong cis-eQTLs but also the weak effects of many more cis- and trans-acting SNPs . So the likelihood that any individual association can be easily validated may not be that great , as it is likely to be of small phenotypic effect and important in only a subset of individuals . However , this is not the point . What is important for the phenotype is not any single SNP-gene association , but the “mesoscale” organization of genes and SNPs represented by the communities in the network . We believe this intermediate structure better reflects the aggregation of weak genetic effects that contribute to late-onset complex diseases . What we hope to have demonstrated in this manuscript is that the higher order structure , which was not an input to the network model , provides insight into a number of aspects of the genetics and manifestation of polygenic traits .
For each empirical degree distribution , we fit the two parameters for a power-law: the minimum degree at which the power-law behavior starts , dmin , and the exponent , α . A Kolmogorov-Smirnov test was then used to estimate the goodness of fit between 5 , 000 randomly generated power-law distributed synthetic data sets given dmin and α and their corresponding power-law fit . The p-value , Ppl , used to reject the power-law hypothesis is then the fraction of times a synthetic data set has a KS statistic larger than that of the true test . For both the SNP and gene degree distributions , Ppl was calculated using the 5 , 000 goodness of fit values ( code for the parameter estimation , goodness of fit and probability estimation was obtained from the website associated with [11] ) . To test the effect of LD and distance from Gene Start Site ( GSS ) on the degree distribution and core score ( Qih ) distribution of a set of GWAS SNPs , we created equivalently sized sets of SNPs that matched on a given characteristic of interest ( LD or GSS ) and compared that subset to all other SNPs . We repeated this process for each GWAS SNP set 1000 times . For the LD testing , we calculated LD blocks using the PLINK [41] “blocks” flag , estimating blocks using all SNPs that passed quality control . To achieve adequate sample sizes in the resampling , we binned LD blocks in 5kb windows , grouped all blocks >100kb into one bin and grouped all SNPs not in a block into one bin . For each resampling , the random set matched the GWAS set for both the LD bin and the number of SNPs in LD together within a block . As a proxy for the gene density of a region , we used each SNP’s distance from the nearest GSS . Distances were grouped into 1kb bins , with all distances >400kb grouped into one bin . The resampled sets were then matched on the GWAS SNP sets such that the number of SNPs in each bin was the same .
|
Large-scale studies have identified thousands of genetic variants associated with different phenotypes without explaining their function . Expression quantitative trait locus analysis associates the compendium of genetic variants with expression levels of individual genes , providing the opportunity to link those variants to functions . But the complexity of those associations has caused most analyses to focus solely on genetic variants immediately adjacent to the genes they may influence . We describe a method that embraces the complexity , representing all variant-gene associations as a bipartite graph . The graph contains highly modular , functional communities in which disease-associated variants emerge as those likely to perturb the structure of the network and the function of the genes in these communities .
|
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"Abstract",
"Introduction",
"Results",
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] |
2016
|
Bipartite Community Structure of eQTLs
|
Many pathogenic bacteria , fungi , and protozoa achieve chronic infection through an immune evasion strategy known as antigenic variation . In the human malaria parasite Plasmodium falciparum , this involves transcriptional switching among members of the var gene family , causing parasites with different antigenic and phenotypic characteristics to appear at different times within a population . Here we use a genome-wide approach to explore this process in vitro within a set of cloned parasite populations . Our analyses reveal a non-random , highly structured switch pathway where an initially dominant transcript switches via a set of switch-intermediates either to a new dominant transcript , or back to the original . We show that this specific pathway can arise through an evolutionary conflict in which the pathogen has to optimise between safeguarding its limited antigenic repertoire and remaining capable of establishing infections in non-naïve individuals . Our results thus demonstrate a crucial role for structured switching during the early phases of infections and provide a unifying theory of antigenic variation in P . falciparum malaria as a balanced process of parasite-intrinsic switching and immune-mediated selection .
During blood-stage of infection with P . falciparum , members of the var gene encoded Erythrocyte Membrane Protein 1 ( PfEMP1 ) family are exposed on the surface of infected red blood cells . Here they act as important virulence factors by mediating adherence to a variety of host cell types , causing sequestration of infected red cells in the deep vasculature [1] , [2] , [3] , [4] , [5] . PfEMP1 are also an important target for host protective antibody responses and contribute to the development of acquired immunity [6] , [7] . This family of proteins has therefore been the focus of intense interest because of the role that it plays in both pathogenesis and the development of protection against clinical disease . Mutually exclusive transcriptional switching occurs between individual members of the ∼60 var genes that encode this family . This changes the PfEMP1 presented on the red cell surface [8] , [9] , [10] , resulting in an evasion of the antibody response through a process of antigenic variation [11] . To date , switching is known to be under epigenetic control , with the transcribed gene located at a specific region of euchromatin found at the nuclear periphery , [12] , [13] . Silencing of the non-transcribed genes seems to involve elements in the intron and the upstream regulatory region [14] and may require the pairing of two promoters [15] , [16] . Confirmation that var genes are expressed in a mutually exclusive manner has been obtained by the demonstration that the placing of a var gene promoter upstream of a selectable marker results in the silencing of the entire var repertoire once the marker is selected for [17] , [18] . In addition to the control of the activation/repression of members of the var gene family , a mechanism must also exist whereby a molecular memory of the gene that was active in the previous cycle can be passed on to daughter parasites during cell division . Recent evidence suggests that one component of this memory is the selective modification of histones . Silent genes are characterised by a specific methylation of histone H3 , H3K9me3 , [19] , [20] , whereas active var genes are associated with the presence of H3K4me2 and H3K4me3 [20] . It has also been reported that the silencing of telomeric members of the var gene family is accompanied by the spreading of heterochromatin involving histone hypoacetylation and PfSIR2 [21] . While our knowledge of some of the molecular mechanisms involved in the control of var gene expression is accumulating rapidly , we still have very little understanding of how these processes are coordinated at the whole cell and population level in a way which provides the parasite with maximum potential to evade the immune response . We have previously proposed that structuring of parasite populations such that individual variants are only expressed one at a time might be achieved by short-lived cross-reacting antibody responses against epitopes shared between subsets of individual variants [22] . However , early infection kinetics will not be affected by these adaptive immune responses and some additional , intrinsic control might therefore be require at this stage . Previous experiments in our laboratory have suggested that the rate at which individual var genes become transcriptionally activated or silenced are characteristic of that gene and relatively stable over time [23] . Recently , Frank and colleagues [24] have suggested that var genes that are within internal chromosome clusters have intrinsically slow off-rates whilst those in the sub-telomeres have rapid off-rates . Thus , they observe that central var genes tend to be the most predominantly expressed in parasites that are cultured for an extended period . To investigate further the overall control of var gene expression we have derived a number of parasite clones from both the IT and 3D7 lineages and monitored var gene expression over an extended period of in vitro culture . Analysing the resulting transcription timecourses for their underlying switching dynamics we find a conserved and highly structured pattern of transcriptional change which is common to most of the clones . In an independent analysis based on optimal fitness we show how this particular pattern could have evolved as an optimal strategy between repertoire protection and immune evasion and how it allows the pathogen to successfully establish infections in non-naïve individuals .
We derived a number of clones from two different genotypes ( IT and 3D7 ) and from these clones , selected a number of parasites that expressed a single dominant var transcript ( as evidenced by Northern blot , data not shown ) . Using quantitative real time PCR , we then measured the expression levels of all var genes at various time points over an extended period of in vitro culture . In the resulting timecourses , transcription profiles of the initial state , as expected , were characterised by a dominant transcript with some minor transcripts also present . We chose transcription profiles of seven clones , for further analysis . Note , for simplicity , in the main figures we only present data for the five most prominent transcripts . An example showing all var gene transcripts of a replicate timeseries of clone 3D7_AS2 both as percentage of total signal and relative transcript level , including the experimental variation between runs , can be found in the supplementary material ( Figs . S1A and B ) ; the reproducibility of our data is further evidenced in Fig . S2 where we show the variation in transcript distribution of repeated timecourses of a single clone . In three clones ( IT_2F6 , IT_3G8 and IT_CSA ) we observed no change in the initial dominant transcript , which persisted for as long as we followed the culture ( up to 80 generations ) with small variations in the abundance of the minor transcripts ( Fig . 1A , 1C and 1E and Table 1 ) . In three other clones ( IT_2B2 , 3D7_AS2 and 3D7_AS3 ) by contrast , the initial dominant transcript declined with time and was eventually replaced by an alternate dominant transcript ( Fig . 1B , 1D , and 1F and Table 1 ) . The final clone ( NF54_NR13 ) showed a behaviour that was intermediate between these two states . In this case , the original transcript continues to be the most abundant over 90 cycles , but other transcripts rise to levels of around 80% of the original ( Fig . S3 and Table 1 ) . The fact that we consistently find only two major types of transcriptional change in different clones strongly suggests that these are not simply down to random fluctuations or experimental oddities but must represent some inherent characteristic of var gene switching . We [23] and others [24] have previously noted that some var genes appear to have very slow off-rates based on stable , dominant transcription levels over many generations of in vitro culture; for these we would not expect to see major changes in transcript levels over the time course of the experiment . For those variants with significantly faster off-rates , on the other hand , we would expect that the culture eventually expresses a wide range of different genes and that the amount of each variant being determined by its intrinsic on- and off-rates . Instead , we observe a replacement of the dominant transcript over a timescale that is inconsistent with the idea that it is a result of direct switching between the two . To investigate this apparent phenomenon of transcript replacement more closely , we analysed the timecourses mathematically for their underlying switching dynamics . Initial studies showed that simple variation in variant growth rates could not give rise to the observed pattern ( data not shown ) Thus , assuming no in vitro growth rate differences between parasites expressing different var genes , the dynamics of a variant can then be described purely by its intrinsic on- and off-rates . A variant's on-rate is effectively the result of other genes switching towards this particular variant at a certain rate and bias . Bias in this context simply refers to the probability of a switch from variant i to variant j . We used an iterative process ( see Methods ) to find the combination of off-rates and switch biases that would best explain the observed switching pattern . In this model constraints are imposed such that we assume that switch rates are constant over time and necessarily require that the total sum of the switch biases of each variant add up to one . Despite the remaining large parameter space of possible on- and off-rate combinations , our method consistently converged upon a particular qualitative structure where the initial variant switches at medium off-rate with no preferential bias to a subset of variants . Each variant in this subset has a high off-rate and a high transcription probability biased towards a single new variant . We refer to this structure hereafter , for simplicity , as the single-many-single or sms pathway . Fig . 2 shows the result of our analysis for three data sets . The left panel depicts the resulting switch-matrices , where the size of each circle in row i and column j corresponds to the transcription probability from variant i to j , and the off-rate vectors where the size of each circle corresponds to the variant's off-rate . Note , in our analysis we only used a subset of the var transcripts , in this case the 12 most dominant variants , which we determined to be optimal given the available data ( see Methods ) . Most other var gene transcripts remain at very low levels over the entire time course ( see e . g . Figs . S1 and S2 ) , however , and these are unlikely to have a significant effect on the observed switching pattern . The predicted sms pathway can be seen within the matrix as an unbiased switch away from the initial variant ( here variant 1 ) to a set of variants with a strong bias towards the second dominant variant ( here variant 2 ) . This particular pattern is illustrated by highlighting the major switch pathways as flow-diagrams in the middle panel of Fig . 2 . In every case the initial variant switches to a group of variants which then switch at high rate and similar bias to another variant that will then become the dominant transcript . The right panel shows the qualitative comparison between the experimental transcription profiles ( of the five most prominent transcripts ) and the timecourses generated by our model . In each case there is good agreement between the data and model output . In line with Fig . 1 and for illustrative purposes only we chose to show only a subset of variants; an example showing all 12 variants can be found in the supplementary material ( Fig . S4A and B ) . To compare the fit of the predicted switch pathway to other possible pathways we applied various constraints to our model such that only one or a small number of variants are allowed to have switch biases and thus contribute to the observed switching pattern ( see supplementary Fig . S5 ) . This clearly showed that simple differences in switch rates could not explain the data . It also highlighted the fact that a direct one-to-one switch from the first dominant variant to the second one is incompatible with the observed data . We also considered the parasite clones in which a single dominant transcript in these profiles remained stable . One feature of these data that was difficult to explain was the fact that a series of minor transcripts was always present and in most cases their abundance showed slight or significant fluctuations over time . Since all of these parasites are clonal , the minor transcripts must have arisen from some daughters switching away from the original var type present in the original clone . Why then did this switching process not continue so that the proportion of the dominant transcript decreased observably over time ? Applying the above analysis to this series of data we discovered that in these cases also , an SMS pathway was the best fit to the data , as exemplified by Fig . 2C . Our analysis thus suggests that although these clones exhibit a phenotype of stable expression of a single variant , a much more dynamic situation may exist in which the dominant var gene is continuously switching to a subset of other var genes ( the minor transcripts that fluctuate ) which continue to switch back to the original dominant transcript . Finally we applied our analysis to transcription profiles previously generated by Frank et al . [19] and found the same switching pattern underlying their data ( see Fig . S6 ) . The fact that we can recapture the same pattern from two independently derived sets of data from different parasite genotypes and multiple independent clones strongly suggests that this particular pathway is an intrinsic feature of var gene switching . We next investigated why this unusual pattern of switching might have evolved . In vivo , P . falciparum is faced with two opposing pressures . If the host is rapidly exposed to the majority of the antigenic repertoire , then there is the danger of the elimination of the parasite by the immune response . Thus the parasite needs to minimise the proportion of the antigenic repertoire to which the host will become exposed . At the same time , in order to maximise the potential for immune evasion , every var gene should be readily accessible , in terms of being switched to , from every other gene within the repertoire . To investigate if the observed pathway could have arisen as a result of this evolutionary conflict , we envisaged the var gene repertoire as a network in which the nodes represent individual gene variants and the edges the transition , i . e . switches , between them . We used a genetic algorithm to ‘evolve’ an initially random network to optimise over two traits: ( i ) average distance through the network , which corresponds to repertoire protection and indirectly infection length , and ( ii ) robustness to the removal of individual nodes , which corresponds to the ability to adapt to selection pressure , e . g . through pre-existing antibody responses . As expected , optimising a network to maximise robustness led to a fully connected network where variants switch to every other variant within the network , whereas optimising for repertoire protection alone results in a ring-like structure where every variant switches to one other variant only ( Fig . 3 ) . Optimising over both traits simultaneously , however , results in a lattice-type network containing nodes with either a high out-degree , i . e . variants that switch to a high number of other variants , or nodes with a high in-degree , i . e . variants which are being switched to by a high number of other variants . Together , these ‘source’ and ‘sink’ nodes , highlighted in blue and red in Fig . 3 , respectively , form the basis of an expansion - contraction process that embodies the evolutionary trade-off between adaptability and repertoire protection in var gene switching . We note that this expansion – contraction process incorporated in the ‘lattice-type’ switching pattern closely resembles the sms pathway we predicted to underlie the observed in vitro switching . However , the optimised network does not take into account switch rates and biases but rather presents a net flow , or transition , between any two variants . For a better qualitative comparison we can represent the switching matrices together with their respective off-rate vectors as a directed network where each edge corresponds to the switch direction from one variant ( node ) to another , simply calculated from the sign of the net transition , ( see Methods ) . In this case we find the resulting network again divided into nodes with either a high in-degree or out-degree , shown in Figs . S7A and S7B for clones 3D7_AS2 and IT_2B2 , respectively , underlining the similarity between the sms and lattice-type pattern .
Establishing chronic infections is particularly important among vector borne pathogens since vector abundance may be seasonal or otherwise uncertain . For pathogens with a limited antigenic repertoire , such as P . falciparum , control over variant expression is therefore essential . Despite some differences in results and interpretation , it is becoming clear that the var gene repertoire of P . falciparum is divided into slow and fast switching phenotypes ( this paper , [23] , [24] , [25] ) . This could potentially introduce a switch hierarchy by which stable variants are more prominently expressed during the early phases of infection . However , with only ∼60 members of the var gene family among which to switch [26] and typical clinical parasite burdens of >1010 , it is very difficult to envisage how this partitioning of on- or off-rates alone could prevent the entire repertoire from being expressed early on . Here we report that var gene switching might occur in a highly structured pattern which can offer a partial solution to this problem . This particular pathway not only depends on inherent differences in the rates at which var genes become transcriptionally active or silent but crucially on intrinsic switch biases between individual genes . Importantly , we also found that very high on-rates and very low off-rates can both be explained by the same principal mechanism of biased switching in which a subset of variants switch at high bias either to a new variant or back to the original . We therefore note that var gene activation cannot be simply seen as an ‘intrinsic’ property but should be viewed in context of a whole var gene switching network . This further implies that the fate of a gene is crucially dependent on the ‘starting position’ within this network such that a variant that quickly gains dominance in a particular situation might not reach significant levels under different circumstances if it is part of a different ‘sub-network’ , i . e . when it does not get switched to at sufficiently high rates from other variants , and vice versa . Other antigenically variable organisms such as Trypanosoma spp or Borrelia hermsii also exhibit programmed sequences of gene activation [27] , [28] , [29] , [30] . In contrast to P . falciparum , however , these may partly be mediated by sequence homologies between the expression site and the donor site used for recombination [31] . One major drawback of tightly ordered gene activation is that it requires every subsequent variant to be able to evade current immune responses and therefore may be compromised by previous infections . For organisms such as T . brucei or B . hermsii , which predominantly infect naive hosts or are less constrained in their generation of antigenic diversity during infection , this is not a major problem . For P . falciparum , however , most infections occur in non-naive individuals and complete discordance between the infecting parasite and the immune repertoire of the host cannot be guaranteed . Furthermore , the rate of mitotic recombination between var genes [32] , [33] is unlikely to be fast enough to evade pre-existing immune responses . The initial expansion or diversification process towards a group of variants within the sms pathway might therefore significantly improve the chance of evading early immune responses whilst the subsequent contraction protects the remaining repertoire from further exposure . With regards to how the aforementioned trade-off within which this particular switch pattern has evolved it is interesting to note that it represents two selective forces acting at both the within- and the between-host levels . That is , the within-host infection dynamics are dominated by the pathogen's need to survive for as long as possible to enhance its chance for onward transmission . This requirement would usually favour a tightly regulated sequence of gene activation to minimise the exposure of the parasite's antigenic repertoire . On the other hand , though , a strict order of expression together with its accompanying immune signature would leave the parasite highly vulnerable when encountering hosts with previous exposure to similar strains . Therefore , having a more flexible yet still structured switch pattern , as the one reported here , could potentially ease competition between antigenically similar strains . Furthermore , as the activation of gene variants appears to be governed by the whole var gene switching network , and in particular the starting variant , population level exhaustion of potentially dominant , i . e . intrinsically over-expressed variants is further minimised . Switch or activation hierarchies have previously been proposed to explain the sequential appearance of antigenic variants during trypanosome infections [34] , [35] . Although it was indicated that this coordinated expression can occur even with a small variant repertoire [35] , it is unclear whether it can be stably maintained over longer periods . We have previously demonstrated that immune mediated selection , by means of short-lived cross-reacting antibody responses against shared epitopes , can structure the parasite populations into sequential dominance of individual variants [22] . While this model was very successful in producing chronic infection , the time taken to establish the cross-reactive antibody responses in vivo meant that the model could not accurately reflect early infection kinetics where parasite intrinsic factors , such as structured switching , are more likely to play a role . The sms pattern of switching reported in this paper has the potential to unite the two mechanisms by producing a realistic progression in expression of variants in the early stages of infection while setting up the conditions , in this case , a network of partially cross-reactive responses , that reliably leads to chronic infection . The antigenic relationship between the variants within a specific switching pathway also appears to play an important role . In particular , the model predicts that in both the sms and lattice-type switching pathways the initial switch should be to a set of antigenically similar variants which then all switch to an antigenically distinct one . In this process , ‘switch intermediates’ are effectively controlled by the cross-reactive responses elicited by the initial variant and can therefore be ‘used’ again during the later stages of infection . This conclusion would be consistent with the in vivo observations of Kaestli et al . [36] that observed the reappearance of the same variant in patients monitored longitudinally . What are the implications of our findings for the molecular mechanisms that underlie the switching process ? Frank et al . [24] suggested from their experiments that the expression of a stable , non-switching transcript is associated with centrally positioned var genes ( those bearing an UpsC type promoter sequence ) whereas rapidly switching var genes are located in the sub-telomeres . We also see a preponderance of central genes in the non-switching clones but also telomeric genes such as PFD0020c and var2CSA from both genotypes . Similarly we note a 3∶1 ratio of telomeric to central genes in those clones that switched rapidly . Thus an association with genomic position may exist , but this is not absolute . In the data that we have available , we also observe that switches occur only to var genes located on other chromosomes , or to var genes located in central versus telomeric clusters on the same chromosome . Switches to closely linked genes appear to be prohibited unless accompanied by a local deletion event [37] , [38] . It has been shown that active var loci occupy a ‘transcriptionally permissive zone’ in the parasite nucleus [39] as part of a cluster of telomere ends [33] . Therefore , it may be that other var genes in the cluster containing the active gene are favored for activation . We were unable to find any strict association of these switching patterns with primary sequence features . However , these data now permit a systematic description , perhaps through parasite transfection experiments , of the sequences and molecules responsible for these switching patterns . Together , our results highlight the intriguing interplay between parasite-controlled switching and immune-mediated selection and reinforce the hypothesis that structured switching in P . falciparum has evolved as an evolutionary compromise between the protection of its limited antigenic repertoire and the flexibility to fully utilise this repertoire when needed .
Quantitative ‘real-time’ PCR was performed using a Rotorgene thermal cycler system ( Corbett Research ) . Reactions were performed in 15 µl volumes using 2X QuantiTect SYBR Green PCR master mix ( Qiagen ) , var-specific primers at . 5 µM , and the appropriate volume of DEPC-treated H20 ( Qiagen ) . The PCR cycling conditions were further optimized for P . falciparum cDNA were 95°C for 15 min followed by 40 cycles of 94°C for 30 s , 58°C for 25 s and 68°C for 30 s followed by a final extension step at 68°C for 10 minutes . To give more consistent reaction efficiency , we found it necessary to redesign seven primer sets which were placed near or inside the transmembrane-encoding sequence ( Supplementary Methods ) : PFI1830c , PF08_0106 , PF07_0139 , PF11_0008 , PFD1000c , PFD1245c , and PFD1015c . Primers were stored at a 10× concentration at 4°C and cDNA was kept in single-use aliquots . The fluorescent signal was acquired at the end of the elongation step of each reaction cycle . After the reaction , product specificity was verified by melting-curve analysis and gel electrophoresis of each PCR product . Quantification using the ‘Comparative Quantitation’ method packaged with ROTORGENE software version 6 . 0 . All primer pairs were tested on identical aliquots of genomic DNA , and the median ‘Take-Off Point’ value for the primer set was calculated . The ‘Take-Off Point’ is analogous to the ‘CT-value’ employed by the ΔΔCT method , except the ‘Take-Off Point’ is computationally determined and its measurement does not require a standard curve for each primer set . Furthermore the ‘Take-Off Point’ is based on the kinetics of each reaction , not a critical fluorescence value that may favour certain transcripts over others . Primer pairs with ‘Take-Off’ values varying by +/− 50% of the median value when tested on the same sample of DNA were redesigned and retested . To account for amplification bias in the reaction conditions , a correction factor equal to the average variation from the mean ‘Take-Off’ point over 5 trials was applied . We used seryl-tRNA synthetase as an endogenous control as it displayed the most uniform transcription profile in different parasite isolates and an unchanged pattern throughout the parasite life cycle . All transcript levels were then normalised with respect to the most abundant variants as this allowed for better comparison in transcript levels and their respective change over the time course . We devised a time-discrete model to describe the change in the proportion of var gene transcripts from generation to generation , assuming each variant has a constant rate and bias at which it will switch towards another variant . The proportion of variant i , vi , at generation t+1 is therefore the sum of variants j switching towards variant i minus the proportion that has switched away from variant i . The dynamics of the variants can then be written as follows:with vi ( t ) = proportion of variant i at generation t , ωi = off-rate of variant i , and βji = switch bias from variant j to variant i . To determine the switch matrix , ( βji ) , and off-rate vector , ( ωi ) , we used a Markov Chain Monte Carlo ( MCMC ) -like method to find the best model fit to the data by iteratively modifying the switch rates and switch biases . An initial matrix and off-rate vector are randomly filled and then repeatedly subjected to small perturbations . At each iterative step , i . e . after each perturbation , we calculated the deviation between data and model output by defining the following error:where is the measured transcript level of variant i at time point t and is the model output . If the perturbed matrix and vector yield a smaller error than the original ones they will be updated and again subjected to small perturbations . This process is repeated until a chosen convergence criteria ( on ε ) is fulfilled . Because of the high number of free parameters and small number of available data points we chose to use a reduced system . That is , instead of trying to fit the full 60×60 switch matrix and 60 off-rates we used a 12 dimensional matrix and vector instead . This was also motivated by the fact that only a subset of measured transcript was above a 5% confidence level . However , we also investigated smaller and bigger systems and found that while this did not change the qualitative nature of the results presented here , the 12 dimensional system seemed optimal in terms of computational speed , goodness-of-fit and convergence . That is , using a much reduced system resulted in a noticeably poorer fit whereas increasing its dimension did not significantly improve the fit between model outcome and the data after a given number of iterations ( see Fig . S8 ) . To determine an optimal switch strategy between immune evasion and repertoire protection we employed a genetic algorithm . The aim was to optimise a network for both a ) average distance through the network ( corresponding to infection length ) , and b ) robustness to the removal of nodes ( corresponding to evading ongoing or pre-existing immune responses ) . Average distance was defined as the mean number of edges that must be traversed by the shortest path between every pair of nodes in the network ( the geodesic distance ) , normalised to a value between zero and one by dividing by the maximum possible . Robustness was measured as the average proportion of nodes that must be removed in order to fragment the network into more than one component , based on 500 simulations of the progressive removal of random nodes for each network . A simple multiplicative fitness function was defined based on these network parameters , since both were normalised to values between 0 and 1 , and randomly generated networks were modified iteratively; random deletions and additions of edges that improved the network's fitness were kept and built upon , whereas random deletions and additions that lowered its fitness were discarded . To simulate the effect of structured switching on malaria infection dynamics we employed a stochastic , mathematical model based on a previous antigenic variation framework [20]; full model details can be found as online supplemental content ( Text S1 ) .
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The malaria parasite Plasmodium falciparum avoids recognition and clearance by the immune system by sequentially switching between members of the var multi-gene family which encode the immunodominant surface proteins PfEMP1 . However , some mechanism must exist to prevent rapid exposure of the pathogen's entire antigenic repertoire as this would quickly terminate the infection . It has previously been shown that the immune system can play an important role in orchestrating the sequential display of variants once an infection is established; however this does not explain how repertoire exhaustion is avoided in the initial phases of infection before an immune response has been established . Here we show that P . falciparum has evolved a highly structured switching pattern to prevent repertoire exhaustion in the early stages of infection without compromising the ability to establish new infections among partially immune individuals .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Methods"
] |
[
"infectious",
"diseases",
"molecular",
"biology",
"infectious",
"diseases/epidemiology",
"and",
"control",
"of",
"infectious",
"diseases",
"infectious",
"diseases/tropical",
"and",
"travel-associated",
"diseases"
] |
2011
|
Antigenic Variation in Plasmodium falciparum Malaria
Involves a Highly Structured Switching Pattern
|
Legionella pneumophila is a gram-negative bacterial pathogen that replicates in host macrophages and causes a severe pneumonia called Legionnaires' Disease . The innate immune response to L . pneumophila remains poorly understood . Here we focused on identifying host and bacterial factors involved in the production of type I interferons ( IFN ) in response to L . pneumophila . It was previously suggested that the delivery of L . pneumophila DNA to the host cell cytosol is the primary signal that induces the type I IFN response . However , our data are not easily reconciled with this model . We provide genetic evidence that two RNA-sensing proteins , RIG-I and MDA5 , participate in the IFN response to L . pneumophila . Importantly , these sensors do not seem to be required for the IFN response to L . pneumophila DNA , whereas we found that RIG-I was required for the response to L . pneumophila RNA . Thus , we hypothesize that bacterial RNA , or perhaps an induced host RNA , is the primary stimulus inducing the IFN response to L . pneumophila . Our study also identified a secreted effector protein , SdhA , as a key suppressor of the IFN response to L . pneumophila . Although viral suppressors of cytosolic RNA-sensing pathways have been previously identified , analogous bacterial factors have not been described . Thus , our results provide new insights into the molecular mechanisms by which an intracellular bacterial pathogen activates and also represses innate immune responses .
The intracellular bacterium Legionella pneumophila has become a valuable model for the study of immunosurveillance pathways . L . pneumophila is a motile gram-negative bacterium that is the cause of a severe pneumonia called Legionnaires' Disease [1] . In the environment , L . pneumophila is believed to replicate in various species of freshwater amoebae . In humans , L . pneumophila causes disease by replicating within alveolar macrophages in the lung [2] . Replication in macrophages and amoebae requires a type IV secretion system that the bacterium uses to inject effector proteins into the host cell cytosol [3] . These effectors are believed to orchestrate the creation of an intracellular vacuole in which L . pneumophila can replicate . Interestingly , there appears to be considerable redundancy among the effectors , and there are few examples of single effector mutations that have a large effect on intracellular replication of L . pneumophila . One L . pneumophila effector required for intracellular replication is SdhA [4] , but the mechanism by which SdhA acts on host cells remains uncertain [4] . A variety of immunosurveillance pathways that detect L . pneumophila infection have been described [5] , [6] , [7] , [8] . The best characterized cytosolic immunosurveillance pathway requires the host proteins Naip5 and Ipaf to detect the cytosolic presence of L . pneumophila flagellin , leading to activation of caspase-1 , rapid pyroptotic macrophage death , and efficient restriction of bacterial replication [9] , [10] , [11] , [12] , [13] . L . pneumophila has also been observed to induce transcriptional activation of type I interferon ( IFN ) genes in macrophages and epithelial-like cell lines by a mechanism that remains incompletely characterized [14] , [15] . Induction of type I IFNs by L . pneumophila is independent of the flagellin-sensing pathway [16] , but also appears to contribute to restriction of bacterial replication in macrophages [16] , [17] and epithelial-like cell lines [14] . Type I IFNs are an important class of cytokines that orchestrate diverse immune responses to pathogens [18] . Encoded by a single IFNβ gene as well as multiple IFNα and other ( e . g . , IFNε , κ , δ , ζ ) genes , type I IFNs are transcriptionally induced by a number of immunosurveillance pathways , including Toll-like receptors ( TLRs ) and a variety of cytosolic sensors [19] . For example , cytosolic RNA is recognized by two distinct helicase and CARD-containing sensors , RIG-I and MDA5 [20] , that signal through the adaptor IPS-1 ( also called MAVS , CARDIF , or VISA ) [21] , [22] , [23] , [24] , [25] . The cytosolic presence of DNA also induces type I IFNs , but this phenomenon is less well understood [15] , [26] . Studies with Ips-1-deficient mice have indicated that cytosolic DNA can signal independently of Ips-1 in many cell types , including macrophages [25] . However , cytosolic responses to DNA appear to require IPS-1 in certain cell types , including 293T cells [26] , [27] . Indeed , two recent reports have described a pathway by which AT-rich DNA can signal via IPS-1 [28] , [29] . In this pathway , DNA is transcribed by RNA polymerase III to form an RNA intermediate that can be sensed by RIG-I . The RNA Pol III pathway appears to be operational in macrophages , but is redundant with other DNA-sensing pathways in these cells . A couple of reports have proposed that DAI ( also called ZBP-1 ) is a cytosolic DNA-sensor [30] , [31] , but Zbp1-deficient mice appear to respond normally to cytosolic DNA [32] , consistent with the existence of multiple cytosolic sensors for DNA . Other small molecule compounds , such as cyclic-di-GMP and DMXAA , can also trigger cytosolic immunosurveillance pathways leading to induction of type I IFNs , but these remain to be fully characterized [33] , [34] , [35] . Type I IFNs are typically considered antiviral cytokines that act locally to induce an antiviral state and systemically to induce cellular innate and adaptive immune responses [19] . Mice deficient in the type I IFN receptor ( Ifnar ) are unable to respond to type I IFNs , and are highly susceptible to viral infections . Interestingly , most bacterial infections also trigger production of type I IFNs , but the physiological significance of type I IFNs in immune defense against bacteria is complex . Type I IFN appears to protect against infection with group B Streptococcus [36] , but this is not the case for many other bacterial infections . For example , the intracellular gram-positive bacterium Listeria monocytogenes induces a potent type I IFN response [37] , [38] , but Ifnar-deficient mice are actually more resistant to L . monocytogenes infection than are wildtype mice [39] , [40] , [41] . Many bacterial pathogens , including Francisella tularensis , Mycobacterium tuberculosis , Brucella abortus , and group B Streptococcus , induce type I IFN production by macrophages via a cytosolic TLR-independent pathway [42] , [43] , [44] , [45] , but the bacterial ligands and host sensors required for the interferon response of macrophages to these bacteria remain unknown . It was demonstrated that induction of type I IFN by L . pneumophila in macrophages did not require bacterial replication or signaling through the TLR-adaptors MyD88 or Trif , but did require the bacterial Dot/Icm type IV secretion system [15] . Because the IFN response could be recapitulated with transfected DNA [15] , [26] and because Dot/Icm system has been shown to conjugate DNA plasmids to recipient bacteria [46] , it was proposed that perhaps L . pneumophila induced type I IFN via a cytosolic DNA-sensing pathway [15] . Another report used RNA interference to implicate the signaling adaptor IPS-1 ( MAVS ) in the IFN response to L . pneumophila in human A549 epithelial-like cells [14] . However , the significance of this latter finding is unclear since RNAi-mediated knockdown of RIG-I and MDA5 , the two sensor proteins directly upstream of IPS-1 , did not have an effect on induction of type I IFN by L . pneumophila [14] . Moreover , the A549 response to L . pneumophila may be distinct from the macrophage or in vivo response . Recently , one report proposed that L . pneumophila DNA was recognized in the cytosol by RNA polymerase III [29] , resulting in the production of an RNA intermediate that triggered IFN production via the IPS-1 pathway . Apparently consistent with this proposal , Ips-1-deficient mouse macrophages did not produce type I IFN in response to L . pneumophila [29] . Moreover , since Pol III acts preferentially on AT-rich substrates , it is plausible that Pol III would recognize the L . pneumophila genome , which has a high proportion ( 62% ) of A:T basepairs . However , the response to L . pneumophila DNA was not investigated [29] . In addition , the same report , as well as others [28] , [34] , observed that the type I IFN response to AT-rich ( or any other ) DNA is not Ips-1-dependent in mouse cells . Thus , if L . pneumophila DNA was reaching the cytosol , the simplest prediction would be that the resulting type I IFN response would be independent of Ips-1 , instead of Ips-1-dependent , as was shown [29] . Thus , the mechanism of IFN induction by L . pneumophila remains unclear . In the present study , we sought to define bacterial and host factors controlling the macrophage type I IFN response to L . pneumophila . In agreement with previous studies [14] , [29] , we find that Ips-1 is required for optimal induction of type I IFN in response to L . pneumophila infection in vitro . We extend this observation by demonstrating that Ips-1 also contributes to the type I IFN response in an in vivo model of Legionnaires' Disease . Furthermore , we provide the first evidence that two RNA sensors upstream of Ips-1 , Rig-i and Mda5 , are involved in the macrophage interferon response to L . pneumophila . Importantly , however , we did not observe a role for the Pol III pathway in the type I IFN response to L . pneumophila . Instead , we found that L . pneumophila genomic DNA stimulates an Ips-1/Mda5/Rig-i-independent IFN response in macrophages , which contrasts with the Ips-1-dependent response to L . pneumophila infection . On the other hand , we found that L . pneumophila RNA stimulated a Rig-i-dependent IFN response . Thus , our data are consistent with a model in which L . pneumophila RNA , or host RNA , rather than L . pneumophila DNA , is the primary ligand that stimulates the host IFN response . We also investigated whether bacterial factors that modulate the host type I IFN response . Although numerous viral proteins that interfere with IFN signaling have been described [19] , similar bacterial proteins have not been documented . It is therefore interesting that we were able to identify a secreted bacterial effector , SdhA , as an inhibitor of the Ips-1-dependent IFN response to L . pneumophila . Taken together , our findings provide surprising evidence that cytosolic RNA-sensing pathways are not specific for viral infections but can also respond to bacterial infections , and moreover , our data provide a specific example of a bacterial factor that suppresses the host IFN response .
We hypothesized that a cytosolic innate immune sensing pathway controls the type I IFN response to L . pneumophila . To test this hypothesis , we determined whether macrophages deficient in known cytosolic RNA and DNA sensing pathway components can induce type I IFNs in response to L . pneumophila . Macrophages were infected with L . pneumophila at a multiplicity of infection ( MOI ) of 1 and induction of interferon beta ( Ifnb ) message was analyzed by quantitative RT-PCR after 4 hours ( Figure 1A–D ) . As previously reported [29] , Ips-1−/− macrophages showed a significantly reduced induction of Ifnb in response to infection with wild type L . pneumophila compared to Ips-1+/+ macrophages ( p<0 . 05; Figure 1A ) . Induction of Ifnb was not completely eliminated in Ips-1−/− macrophages , however , as Irf3−/− macrophages exhibited an even lower induction of Ifnb compared to Ips-1−/− ( p<0 . 05; Figure 1A ) . Consistent with previous reports [15] , we found that the Dot/Icm type IV secretion system was required to elicit the macrophage type I interferon response since Δdot L . pneumophila did not induce a robust type I interferon response ( Figure 1A ) . These results suggest that L . pneumophila induces type I IFN via a cytosolic RNA immunosurveillance pathway that involves the adaptor Ips-1 . We hypothesized that a cytosolic RNA sensor that functions upstream of Ips-1 could be involved in the type I interferon host response to L . pneumophila . However , knockdown experiments in A549 cells previously failed to reveal a role for the known sensors ( MDA5 and RIG-I ) upstream of IPS-1 [14] . Therefore , we tested Mda5−/− knockout macrophages ( Figure 1B ) and found reduced induction of Ifnb message as compared to control Mda5+/+ macrophages . Importantly , however , Dot-dependent induction of type I IFN was not completely abolished in Mda5−/− macrophages , implying that other redundant pathways are also involved . Rig-i knockout mice die as embryos , so we were unable to obtain Rig-i−/− knockout macrophages . To circumvent this problem , we stably transduced immortalized macrophages with a retrovirus expressing an shRNA to knock down Rig-i expression . Quantitative RT-PCR demonstrated that the knockdown was effective , even in infected macrophages ( Figure 1C ) , and that Rig-i knockdown had a significant effect on the induction of type I interferon by L . pneumophila ( Figure 1D ) . In the experiments in Figures 1C and 1D we used the ΔflaA strain of L . pneumophila , but similar results were obtained with wildtype , and it was previously shown that flagellin is not required for the IFN response to L . pneumophila [14] , [16] . It is unusual , but not unprecedented , that a pathogen would stimulate both the RIG-I and MDA5 RNA-sensing pathways [47] . At present , only one candidate cytosolic DNA sensor involved in the IFN response has been described [30] , [31] . To determine whether this sensor , called Dai ( or Zpb1 ) , is involved in the type I interferon response to L . pneumophila , we tested whether Zbp1−/− macrophages respond to L . pneumophila . We observed similar levels of Ifnb induction in Zbp1+/+ and Zbp1−/− macrophages ( Figure 1E ) . Taken together , these results imply that the RNA sensors Rig-i and Mda5 , but not the DNA sensor Zbp1 , are involved in sensing L . pneumophila infection . We tested whether loss of signaling through the RNA sensing components Ips-1 or Mda5 could mimic the previously observed permissiveness of Ifnar−/− macrophages [16] . However , neither Ips-1−/− nor Mda5−/− macrophages were permissive to L . pneumophila , suggesting that the low levels of IFNβ produced in the absence of Ips-1 or Mda5 are sufficient to restrict L . pneumophila growth ( Figure S1 ) . To identify bacterial components that modulate the type I interferon response to L . pneumophila , we conducted a transposon mutagenesis screen . The LP02 strain of L . pneumophila was mutagenized with a mariner transposon as described previously [12] . Individual transposon mutants were used to infect MyD88−/−Trif−/− bone marrow-derived macrophages at an MOI of 1 , and after approximately 16 hours , supernatants were collected and overlayed on type I IFN reporter cells [48] . Induction of type I IFN was compared to wild type ( LP02 ) and Δdot L . pneumophila controls . We tested approximately 2000 independent mutants and isolated eight mutants that were confirmed to be defective in induction of type I IFN . All these mutants harbored insertions in genes required for the function of the Dot/Icm apparatus ( e . g . , icmB , icmC , icmD , icmX , icmJ ) , thereby validating the screen . Interestingly , a single transposon mutant , 11C11 , was found that consistently hyperinduced the type I interferon response . The transposon insertion mapped to the 3′ end ( nucleotide position 3421 of the open reading frame ) of a gene , sdhA , that was previously shown [4] to encode a type IV secreted effector protein of 1429 amino acids ( 166kDa ) ( Figure 2A ) . SdhA has previously been shown to be essential for bacterial replication in macrophages [4] , but a connection to type I IFNs was not previously noted . To confirm that the hyperinduction of type I interferon was due to mutation of sdhA , the 11C11 transposon mutant was compared to an unmarked clean deletion of sdhA ( Figure 2B ) . Both the 11C11 mutant and ΔsdhA L . pneumophila showed similar levels of hyperinduction of type I interferon . The L . pneumophila genome contains 2 paralogs of sdhA , called sidH and sdhB . A triple knockout strain , ΔsdhAΔsdhBΔsidH , was compared to single deletion of sdhA to determine if either paralog regulated the induction of type I IFNs . Similar levels of IFNβ were induced ΔsdhAΔsdhBΔsidH and ΔsdhA ( Figure 2B ) . Similar results were obtained when induction of Ifnb was assessed by quantitative RT-PCR ( Figure 2C ) . A role for sdhA in regulating the interferon response was further confirmed by complementing the ΔsdhA mutation with an sdhA expression plasmid [4] . As expected , the complemented strain induced significantly less type I IFN than the control ΔsdhA strain harboring an empty plasmid ( Figure 2D ) . These results indicate that SdhA functions , directly or indirectly , to repress the induction of type I IFN by L . pneumophila . It was possible that ΔsdhA mutants hyperinduced type I IFN via a pathway distinct from the normal cytosolic RNA-sensing pathway that responds to wildtype L . pneumophila . Therefore , to determine whether hyperinduction of type I interferon by ΔsdhA occurs through the same pathway that responds to wild type L . pneumophila , we infected Ips-1−/− and Mda5−/− macrophages with ΔsdhA L . pneumophila . Induction of Ifnb message was determined by quantitative RT-PCR . The hyperinduction of Ifnb seen in Ips-1+/+ macrophages was almost abolished in Ips-1−/− macrophages ( p<0 . 001; Figure 3A ) . As a control , induction of Ifnb by poly I:C , a double-stranded synthetic RNA analog , was also Ips-1-dependent as expected . Similarly , the hyperinduction of Ifnb was also reduced in Mda5−/− macrophages ( p<0 . 01; Figure 3B ) . However , the Mda5−/− macrophages still induced significant amounts of Ifnb , suggesting that the requirement for Mda5 is not complete . We also tested the ΔsdhA mutant in Rig-i knockdown macrophages . Rig-i knockdown appeared to be effective ( Figure 3C ) and specifically diminished Ifnb expression ( Figure 3D ) . Thus , the residual Ifnb induction in Mda5−/− may be due to Rig-i , or to another uncharacterized pathway . As a control , Theiler's virus ( TMEV ) induced Ifnb in a completely Mda5-dependent manner , as expected ( Figure 3B ) . It was previously shown that ΔsdhA mutants induce a rapid death of infected macrophages that is dependent upon activation of multiple cell death pathways [4] . Consequently , we hypothesized that the hyperinduction of type I IFN by the ΔsdhA mutant might be due to the release of molecules from dying cells , such as DNA , that could induce Ifnb expression . To rule out this explanation , we infected Casp1−/− macrophages , which are resistant to cell death at the early timepoints examined ( e . g . , 4h post infection ) , and asked whether type I interferon was still hyperinduced in response to ΔsdhA L . pneumophila . In fact , we found that Casp1−/−macrophages infected with the ΔsdhA mutant hyperinduced Ifnb to levels above that observed in B6 macrophages ( Figure 4A ) . We suspect that the increased Ifnb induction seen in Casp1−/− cells was an indirect consequence of the lower levels of cell death in these cells , and was not due to a specific suppression of type I interferon transcription by Casp1 activation . In any case , our results indicated that the hyperinduction of type I IFN by the ΔsdhA mutant was not due to increased cell death induced by the mutant . As a control , we confirmed that Casp1−/− macrophages were resistant to cell death at the 4h timepoint tested ( Figure 4B ) . Induction of Ifnb is often regulated by a positive feedback loop in which initial production of IFNβ results in signaling through the type I IFN receptor ( Ifnar ) and synergistically stimulates the production of additional type I IFN . We therefore examined whether the hyperinduction of Ifnb by the ΔsdhA mutant might be due to positive feedback through the type I IFN receptor . To test this possibility we examined induction of Ifnb by the ΔsdhA mutant in Ifnar−/− macrophages . We found that hyperinduction of Ifnb by ΔsdhA L . pneumophila occurs even in the absence of signaling from the type I interferon receptor , since Ifnar−/− macrophages hyperinduce Ifnb in response to infection with ΔsdhA L . pneumophila ( Figure 4A ) . The mechanism by which the ΔsdhA mutant induces cell death remains unclear [4] . Studies with the intracellular bacterial pathogen Francisella tularensis have demonstrated the existence of a type I IFN-inducible caspase-1-dependent cell death pathway [43] . Therefore , we sought to establish if caspase-1-dependent cell death occurred in the absence of Ifnar signaling in response to wild type and ΔsdhA L . pneumophila . Ifnar−/− macrophages were infected at an MOI of 1 and assayed for release of the intracellular enzyme lactate dehydrogenase ( LDH ) 4 hours post infection . Ifnar−/− macrophages exhibited similar LDH release as B6 macrophages , whether infected with WT or ΔsdhA L . pneumophila , and this LDH release was dependent upon caspase-1 activation ( Figure 4B ) . These data demonstrate that caspase1-dependent pyroptotic death occurs independently of the type I interferon receptor during infection with wild type and ΔsdhA L . pneumophila . Since growth of the ΔsdhA mutant is severely attenuated in macrophages [4] , we hypothesized that hyperinduction of type I interferon might contribute to the restriction of replication of the ΔsdhA mutant . To test this hypothesis , we infected lfnar−/− macrophages with luminescent strains of L . pneumophila at an MOI of 0 . 01 and monitored bacterial replication over a 72 hour time period . As previously reported [16] , lfnar−/− macrophages were more permissive to WT and ΔflaA L . pneumophila as compared to C57BL/6 macrophages ( Figure S2A , C ) . However , the ΔsdhA or ΔflaAΔsdhA L . pneumophila strains were still significantly restricted in Ifnar−/− macrophages ( Figure S2B , D ) . Thus , SdhA is required for bacterial replication in macrophages primarily via a mechanism independent of its role in suppressing type I IFN . As expected , Δdot L . pneumophila did not replicate in WT or Ifnar−/− macrophages ( Figure S2E ) . Since SdhA is a secreted effector , we hypothesized that SdhA may act in the host cell cytosol , rather than in the bacterium , to repress Ifnb induction . To test this hypothesis , we co-expressed SdhA with MDA5 or RIG-I , by transient transfection of HEK293T cells , and assessed interferon expression with an IFNβ-luciferase reporter . Expression of either MDA5 or RIG-I robustly induced the IFNβ-luc reporter upon stimulation with poly I:C ( Figure S3 ) . When SdhA was co-expressed with MDA5 , a dose-dependent repression of the IFNβ-luc reporter was observed ( Figure S3A ) . Co-expression of SdhA also resulted in a dose-dependent repression of RIG-I-dependent induction of the IFNβ-luc reporter ( Figure S3B ) . However , SdhA co-expression did not affect TRIF-dependent induction of the IFNβ-luc reporter ( Figure S3C ) , arguing against the possibility that SdhA expression has non-specific effects on IFNβ-luc induction . These results must be interpreted with caution since the 293T IFNβ-luc reporter system is highly artificial; moreover , we have not demonstrated a direct interaction of SdhA with signaling components in the RNA-sensing pathway . In fact , the reported effects of SdhA on mitochondria [4] suggest the effect may be somewhat indirect ( see Discussion ) . Nevertheless , the 293T transfection results suggest that SdhA can act in the host cytosol to specifically repress induction of the RIG-I/MDA5 pathway . Based on our observation that the host type I IFN response requires the L . pneumophila Dot/Icm type IV secretion system and was at least partly Ips-1 , Rig-i , and Mda5-dependent , we hypothesized that L . pneumophila nucleic acids ( RNA , DNA or both ) might gain access to the macrophage cytosol via the type IV secretion system and induce a host type I interferon response . To test if L . pneumophila nucleic acids are sufficient to induce type I interferon , we transfected MyD88−/−Trif−/− macrophages with purified L . pneumophila genomic DNA or total RNA and determined the induction of type I interferons by bioassay . Poly ( dA-dT ) :poly ( dA-dT ) ( abbreviated as pA:T ) was used as a non-CpG containing DNA control and poly I:C was used as an RNA control . Nucleic acid preparations were treated with DNase and/or RNase to eliminate contaminating nucleic acids . Both purified L . pneumophila DNA and the crude RNA preparation induced IFNβ ( Figure 5A ) . L . pneumophila RNA treated with RNase also induced IFNβ , presumably due to ( contaminating ) DNA in the preparation ( Figure 5A ) . However , L . pneumophila RNA treated with DNase induced type I interferon to a level above that induced by L . pneumophila RNA treated with both RNase and DNase , suggesting that L . pneumophila RNA alone can induce type I interferon production ( Figure 5A ) . The induction of type I IFN by L . pneumophila RNA was modest , possibly because bacterial RNA is less stable than DNA . Nevertheless , these results suggest that both L . pneumophila RNA and DNA can induce a type I interferon host response . Next , we determined if L . pneumophila nucleic acids could induce type I interferon in an Ips-1-dependent manner in macrophages . In certain cell types , though not mouse macrophages [34] , AT-rich DNA has been shown to induce type I IFN via IPS-1 [26] , [27] , [28] , [29] . It was important to assess whether L . pneumophila DNA , in particular , might signal in an Ips-1-dependent manner since the L . pneumophila type IV secretion system has previously been shown to translocate DNA [46] . Ips-1+/− and Ips-1−/− macrophages were transfected with pA:T and L . pneumophila DNA , as well as infected with Sendai virus , a virus previously determined to induce an Ips-1-dependent IFN response . Stimulation with pA:T or L . pneumophila DNA failed to induce Ifnb in an Ips-1-dependent manner , whereas Sendai virus induced significantly more Ifnb in Ips-1+/− versus Ips-1−/− macrophages ( Figure 5B ) . Similar results were obtained in Mda5−/− macrophages: induction of type I IFN with pA:T or L . pneumophila genomic DNA showed no requirement for Mda5 , whereas a control simulation , Theiler's Virus , showed Mda5-dependent induction of IFNβ , as expected ( Figure 5C ) . It was possible that at high concentrations of DNA , an Ips-1-independent DNA-sensing pathway overwhelmed any putative Ips-1-dependent recognition of DNA . However , induction of Ifnb was independent of Ips-1 even when titrated amounts of pA:T or L . pneumophila genomic DNA were transfected into macrophages ( Figure 5D , 5E ) . Thus , these results suggest that while transfected L . pneumophila DNA robustly induces type I interferon , L . pneumophila genomic DNA does not appear to induce the Ips-1-dependent IFN response that is characteristic of L . pneumophila infection . To determine whether L . pneumophila RNA could be recognized by Rig-i , we transfected L . pneumophila RNA into macrophages in which Rig-i expression had been stably knocked down . Importantly , the Rig-i knockdown was performed in immortalized bone-marrow-derived macrophages that lack MyD88 and Trif , in order to avoid potential activation of known RNA-sensing TLRs . Knockdown of Rig-i was effective under our transfection conditions , as Rig-i message was significantly lower in macrophages transduced with a Rig-i shRNA compared to a control shRNA ( p<0 . 05; Figure 6A ) . Crude L . pneumophila RNA ( which also contains genomic DNA contaminants ) induced Ifnb robustly in both control shRNA and Rig-i shRNA macrophages , even upon treatment with RNase A ( Figure 6B ) . However , transfection of DNase-treated L . pneumophila nucleic acids induced significantly less Ifnb in Rig-i knockdown macrophages as compared to control knockdown macrophages ( p<0 . 05; Figure 6B . ) This result suggests that L . pneumophila RNA can induce Rig-i-dependent type I interferon . It was not possible to perform a similar experiment in the Ips-1−/− macrophages because these macrophages were MyD88/Trif+ and exhibited background interferon , presumably due to TLR3 signaling . A recent report found that an inhibitor of RNA polymerase III , ML-60218 [49] , blocked the type I IFN response to L . pneumophila [29] . It was proposed that L . pneumophila DNA is translocated into macrophages and transcribed by Pol III into a ligand that could be recognized by RIG-I [29] . In contrast , we did not see an effect of ML-60218 on induction of type I IFN by L . pneumophila in bone marrow-derived macrophages ( Figure 7A ) . The lack of an effect does not appear to be due to redundant recognition by another DNA sensor in macrophages because the interferon induction was still largely Ips-1-dependent ( Figure 7A ) . Because our results with the Pol III inhibitor were negative , we cannot rule out the possibility that the Pol III inhibitor fails to function in macrophages . However , we also tested 293T cells , which express only the Pol III pathway for cytosolic recognition of DNA [28] , [29] . As expected , 293T cells responded to pA:T in an ML-60218-inhibitable manner , but did not respond well to L . pneumophila genomic DNA ( Figure 7B ) , again suggesting that L . pneumophila genomic DNA is not an efficient substrate for the Pol III pathway . The Pol III inhibitor also appeared to have little effect on L . pneumophila replication in bone-marrow macrophages ( Figure 7C–E ) . This latter result was expected , since we found that even Ips-1−/− macrophages exhibit normal restriction of L . pneumophila replication ( Figure S1 ) , despite significantly reduced IFN induction . In order to validate our findings in vivo , we infected Ips-1−/− and littermate Ips-1+/− mice with L . pneumophila ( 2 . 5×106 LP01 ΔflaA per mouse , infected intranasally ) and assayed type I interferon production in bronchoalveolar lavage fluid 20 hours post infection by bioassay . Ips-1+/− mice induced an IFN response that was statistically significantly greater than the response of Ips-1−/− mice ( Student's t-test , p = 0 . 01; Figure 8A ) . The difference in IFN production was not explained by a difference in bacterial burden in the Ips-1+/− and Ips-1−/− mice , since both genotypes exhibited similar levels of bacterial colonization ( p = 0 . 76 , Student's t-test; Figure 8B ) . The lack of an effect of Ips-1-deficiency on bacterial replication in vivo was not surprising given that we also failed to observe an effect of Ifnar-deficiency on bacterial replication in vivo ( data not shown ) . We suspect that type II IFN ( IFNλ ) , which is not made by macrophages in vitro , or another in vivo pathway , may compensate for loss of type I IFN in vivo . Nevertheless , our results provided an important validation of our in vitro studies and affirm a role for Ips-1 in the in vivo type I interferon response to L . pneumophila . Since Ips-1-deficient mice still mounted a measurable IFN response in vivo , it appears that additional Ips-1-independent pathways ( e . g . , TLR-dependent pathways , possibly involving other cell types [50] ) also play a role in vivo .
Type I interferons ( IFNs ) have long been appreciated as critical players in antiviral immune defense , and recent work has identified several molecular immunosurveillance pathways that induce type I IFN expression in response to viruses [18] , [19] . In contrast , the roles of type I IFNs in response to bacteria , and the pathways by which bacteria induce type I IFNs , are considerably less well understood . In this study , we sought to characterize the type I IFN response to the gram-negative bacterial pathogen Legionella pneumophila . Our study focused on the type I IFN response mounted by macrophages , since this is the cell type that is believed to be the primary replicative niche in the pathogenesis of Legionnaires' Disease . In agreement with previous work [15] , we found that L . pneumophila induces type I IFNs in macrophages via a TLR-independent pathway that requires expression of the bacterial type IV secretion system . These results suggested that a cytosolic immunosurveillance pathway controls the IFN response in macrophages . In this report we identify the cytosolic RNA-sensing pathway as a key responder to L . pneumophila infection ( Figure 1 ) and , in agreement with previous results using human A549 cells [51] , we did not observe a role for Dai ( Zbp1 ) , a gene implicated in the response to cytosolic DNA [30] , [31] . A previous study using RNA interference in the human A549 epithelial-like cell line also found a role for IPS-1 in the type I IFN response to L . pneumophila [14] . However , knockdown of RIG-I or MDA5 did not appear to affect the IFN response [14] , so the role of the IPS-1 pathway was unclear . In our study , we used mice harboring targeted gene deletions to establish a role for Mda5 and Ips-1 in the type I IFN response to L . pneumophila in macrophages , and uncovered a role for Rig-i using an shRNA knockdown strategy . We also found that the cytosolic RNA-surveillance pathway regulated the IFN response in vivo in a mouse model of Legionnaires' Disease . After our manuscript was submitted , a report published by Chiu and colleagues also concluded that Ips-1 is required for the macrophage type I IFN response to L . pneumophila [29] . However , the report of Chiu et al differs considerably from our current work by proposing that the type I IFN response to L . pneumophila occurs via a novel and unexpected pathway in which L . pneumophila DNA reaches the host cytosol and is transcribed by RNA polymerase III to generate an RNA intermediate that is sensed by RIG-I . Others have found that the Pol III pathway can be activated by viral and AT-rich DNA in certain cell types [28] . Our data , however , are not easily reconciled with a role for the Pol III pathway in recognition of L . pneumophila . First , and perhaps most important , is the observation that the response to DNA ( in contrast to the response to L . pneumophila infection ) has never been seen to be Ips-1-dependent in macrophages ( [34]; Figure 5 ) . This suggests that the response to L . pneumophila is not simply a response to DNA , regardless of the mechanisms by which potentially translocated DNA might be recognized . We considered the possibility that L . pneumophila DNA exhibits unique properties that cause it to be a particularly efficient substrate for the Pol III pathway . Indeed , the L . pneumophila genome does contain stretches of highly AT-rich DNA , and it has been reported that only highly AT-rich DNA is an efficient substrate for the Pol III pathway [28] , [29] . Therefore we tested whether L . pneumophila genomic DNA , unlike other DNA , could induce an Ips-1-dependent response in macrophages . Although L . pneumophila DNA induced a robust IFN response , the response was not Ips-1-dependent ( Figure 5B , E ) . Indeed , even the optimal Pol III substrate poly ( dA–dT ) :poly ( dA–dT ) ( abbreviated as pA:T ) does not appear to induce an Ips-1-dependent IFN response in macrophages ( Figure 5B , D and [34] ) . The lack of Ips-1-dependence in the response to pA:T appears to be due to an unidentified Ips-1-independent DNA-sensing pathway that recognizes pA:T and dominates over the Pol III pathway in bone marrow macrophages [28] . Thus , if translocated DNA is the relevant bacterial ligand that stimulates the Ips-1-dependent host type I IFN response , an explanation is required for how the dominant and unidentified DNA-sensing pathway is not activated . While L . pneumophila could selectively inhibit or evade the dominant DNA-sensing pathway , there is at present no evidence to support this mechanism . Moreover , in our hands , the Pol III inhibitor used by Chiu et al ( ML-60218 ) failed to affect IFN induction or bacterial replication in macrophages ( Figure 7 ) , in contrast to what would be predicted if the Pol III pathway was selectively activated in response to L . pneumophila infection . Therefore , our data lead us to consider alternative models . Although Chiu et al primarily used the RAW macrophage-like cell line in their experiments with L . pneumophila , we do not believe that cell-type-specific effects can account for the discrepancy in results . Although it is possible that RAW cells express only the Pol III pathway , this would not change the fact that the proposed model of Chiu et al invokes DNA as the primary IFN-inducing ligand produced by L . pneumophila . The simplest prediction of such a model would be that the response of bone marrow macrophages to L . pneumophila would be Ips-1-independent , as is the response of macrophages to all forms of DNA that have been tested . In contrast , as documented here ( Figure 1 ) and by Chiu et al [29] , the response to L . pneumophila is Ips-1-dependent . Moreover , 293T cells , which express only the Pol III DNA-sensing pathway [28] , [29] , failed to respond significantly to L . pneumophila genomic DNA , despite a robust response to pA:T ( Figure 7B ) . Therefore , our data suggest that recognition of L . pneumophila genomic DNA by Pol III is not responsible for the Ips-1-dependent IFN response to L . pneumophila . We considered two other models to explain how L . pneumophila induces a type I interferon response . The first is that L . pneumophila translocates RNA into host cells . In support of this model , we demonstrate that L . pneumophila RNA , unlike any form of DNA tested , induced a Rig-i-dependent type I IFN response in macrophages ( Figures 5A , 6 ) . However , we did not demonstrate that L . pneumophila RNA species are translocated into host cells , and this will be important to examine in future studies . Interestingly , it was recently reported that purified Helicobacter pylori RNA stimulates RIG-I in transfected 293T cells [52] . A second model to explain type I IFN induction by L . pneumophila is that infection induces a host response that indirectly results in signaling via the MDA5/RIG-I/IPS-1 pathways . L . pneumophila secretes a large number of effectors into the host cytosol and these effectors disrupt or alter a large number of host cell processes [53] . Such disruption may either lead to the generation of host-derived RNA ligands for the RIG-I and MDA5 sensors , or may result in signaling through these sensors in the absence of specific ligands . It was previously proposed that a host nuclease , RNaseL , can generate self-RNA ligands for the RIG-I and MDA5 pathways in response to viral infection [54] . Although we could not observe a role for RNaseL in the response to L . pneumophila ( K . M . Monroe , unpublished data ) , it is conceivable that a different host enzyme can fulfill a similar function . Our finding that a secreted bacterial effector , SdhA , previously shown to suppress host cell death , also suppresses the IFN response to L . pneumophila , is consistent with a model in which a host cell stress response leads to direct or indirect activation of the cytosolic RNA-sensing pathway . However , the mechanism by which SdhA acts on host cells remains mysterious . Laguna and colleagues provided evidence that SdhA is critical for prevention of mitochondrial disruption that occurs when host cells are infected with the ΔsdhA mutant [4] . Given that Ips-1 localizes to mitochondria and requires mitochondrial localization for its function [21] , it is tempting to speculate that SdhA acts on mitochondria in a way that both prevents their disruption and interferes with the function of Ips-1 . To provide evidence that SdhA acts specifically on the RIG-I/MDA5 pathway , we used transient transfections of 293T cells . SdhA repressed induction of Ifnb when co-expressed with Mda5 or Rig-I but not Trif ( Figure S3 ) . Given these results and the evidence that SdhA is translocated into host cells [4] , we favor the idea that SdhA acts within host cells . Mutation of sdhA was reported not to affect translocation of other effectors into host cells [4]; thus , we tend not to support the alternative possibility that SdhA blocks translocation of the putative IFN-stimulatory ligand through the type IV secretion system . SdhA is a large protein of 1429 amino acids , but does not contain domains of known function , except for a putative coiled coil ( a . a . 1037–1068 ) . In future studies it will be important to address whether subdomains of SdhA can be identified that are required for suppression of the IFN response . It will also be important to determine whether these subdomains are distinguishable from any putative subdomains required for suppression of host cell death . In fact , our data have suggested that suppression of cell death and the IFN response may be separable functions of SdhA . We found that cell death was not required for hyperinduction of IFN by the ΔsdhA mutant , and conversely , we also found that hyperinduction of type I IFN does not lead to increased cell death ( Figure 4 ) . Our studies demonstrate a partial role for both Mda5 and Rig-i RNA sensors in response to L . pneumophila . Although these sensors are typically thought to respond to distinct classes of viruses , there are indications that they can also function cooperatively in response to certain stimuli , e . g . , West Nile Virus [47] . Our results suggest that L . pneumophila produces ligands that can stimulate both Mda5 and Rig-i and that these two sensors cooperatively signal via Ips-1 . Fitting with this model , we found that Ips-1-deficiency generally had a more severe impact on type I IFN induction than did Mda5 or Rig-i deficiency . Cytosolic RNA-sensing pathways are believed to respond exclusively to viral infection , and it is therefore surprising that L . pneumophila appears to trigger these pathways . Other bacterial species , such as Listeria monocytogenes and Francisella tularensis , have been shown to induce an Ips-1-independent cytosolic pathway leading to type I IFN induction [25] , [43] , [55] . The sensor ( s ) required for the IFN response to Listeria or Francisella have not yet been identified , but are widely assumed to be identical to the ( also unknown ) sensor ( s ) that respond to cytosolic DNA [15] , [26] . Ips-1 or Mda5-deficiency , as well as Rig-i knockdown , did not result in a complete elimination of the type I IFN response ( Figure 1 , Figure 3 ) . Thus , a cytosolic DNA-sensing pathway may also be stimulated in response to L . pneumophila infection . A minor role for a cytosolic DNA-sensing pathway would be consistent with the observation that the L . pneumophila Dot/Icm type IV secretion system can translocate DNA into recipient cells [46] . However , as discussed above , our results with purified L . pneumophila DNA suggest that cytosolic sensing of L . pneumophila DNA does not account for the Ips-1-dependent induction of IFN that we observe ( Figure 5 ) . One last possibility that we cannot eliminate is that a non-DNA , non-RNA ligand is translocated into host cells and stimulates the Ips-1 pathway . In fact , in separate work , we have found that a small bacterial cyclic dinucleotide , c-di-GMP , can trigger a type I IFN response in macrophages , but importantly , this response is entirely independent of the Ips-1 pathway [34] . Nevertheless , there may be other small molecules that can be translocated by the Dot/Icm secretion system and signal in host cells via Ips-1 . Taken together , our results lead to new insights into the host immunosurveillance pathways that provide innate defense against bacterial pathogens . We demonstrate an unexpected role for a viral RNA-sensing pathway in the response to L . pneumophila , and identify a secreted bacterial effector , SdhA , that can suppress this response . Our results therefore open new possibilities for immunosurveillance of bacterial pathogens .
Animal experiments were approved by the University of California , Berkeley , Institutional Animal Care and Use Committee . Bone marrow derived macrophages were derived from the following mouse strains: C57BL/6J ( B6 ) , Ips-1−/− [25] , Mda5−/− [56] , Ifnar−/− [57] , Zbp1−/− [32] , MyD88/Trif−/− , and Casp1−/− [58] . C57BL/6J mice were purchased from the Jackson Laboratory . Ips-1−/− mice were from Z . Chen ( University of Texas Southwestern Medical Center ) . Ips-1−/− were obtained on a mixed B6/129 background and Ips-1−/− and Ips-1+/− littermate controls were generated by breeding ( Ips-1−/− x B6 ) F1 mice to Ips-1−/− . Mda5−/− mice were from M . Colonna and S . Gilfillan ( Washington University ) . L929-ISRE IFN reporter cells were from B . Beutler ( The Scripps Research Institute ) . Viruses to immortalize MyD88−/−Trif−/− immortalized bone marrow derived macrophages were the generous gift of K . Fitzgerald , D . Golenbock ( U . Mass , Worcester ) and D . Kalvakolanu ( U . Maryland ) . The complementation plasmid ( pJB908-SdhA ) was generously provided by R . Isberg ( Tufts ) . Expression constructs pEF-BOS-RIG-I and pEF-BOS-MDA5 were generously provided by J . Jung ( Harvard Medical School ) . LP02 is a streptomycin-resistant thymidine auxotroph derivative of Legionella pneumophila strain LP01 . LP02ΔsdhA and LP02ΔsdhAΔsdhBΔsidH were a generous gift from R . Isberg ( Tufts University ) . The ΔflaAΔsdhA strain was generated by introducing an unmarked deletion of flaA in LP02ΔsdhA using the allelic exchange vector pSR47S-ΔflaA [12] . L929-ISRE and HEK293T cells were cultured in DMEM supplemented with 10% FBS , 2 mM L-glutamine , 100 µM streptomycin , and 100 U/mL penicillin . Macrophages were derived from bone marrow cells cultured for eight days in RPMI supplemented with 10% FBS , 2 mM L-glutamine , 100 µM streptomycin , 100 U/mL penicillin , and 10% supernatant from 3T3-CSF cells , with feeding on the fifth day of growth . MyD88−/−Trif−/− immortalized macrophages were cultured in RPMI supplemented with 10% FBS , 2 mM L-glutamine , 100 µM streptomycin , and 100 U/mL penicillin . Poly I:C was from GE Biosciences , pA:T ( poly ( dA-dT ) :poly ( dA-dT ) ) was from Sigma , and Sendai Virus was from Charles River Laboratories . Wildtype Theiler's Virus GDVII was from M . Brahic and E . Freundt ( Stanford University ) . Pol III inhibitor ( ML-60218 ) was from Calbiochem . Total bacterial RNA was isolated using RNAprotect Bacterial Reagent ( Qiagen ) and RNeasy kit ( Qiagen ) . Genomic DNA was isolated by guanidinium thiocyanate followed by phenol:chloroform extraction . Nucleic acids were treated with RQ1 RNase-Free DNase ( Promega ) and/or RNaseA ( Sigma ) . Bone marrow derived macrophages were plated at a density of 2×106 per well in 6 well plates and infected with an MOI of 1 . Macrophage RNA was harvested 4 hours post infection and isolated with the RNeasy kit ( Qiagen ) according to the manufacturer's protocol . RNA was DNase treated with RQ1 RNase-Free DNase ( Promega ) and reverse transcribed with Superscript III ( Invitrogen ) . Quantitative PCR assays were performed on the Step One Plus RT PCR System ( Applied Biosystems ) with Platinum Taq DNA polymerase ( Invitrogen ) and EvaGreen dye ( Biotium ) . Gene expression values were normalized to Rps17 ( mouse ) or S9 ( human ) levels for each sample . The following primer sequences were used: mouse Ifnb , F , 5′-ATAAGCAGCTCCAGCTCCAA-3′and R , 5′-CTGTCTGCTGGTGGAGTTCA-3′; mouse Rps17 , F , 5′-CGCCATTATCCCCAGCAAG-3′ and R , 5′- TGTCGGGATCCACCTCAATG-3′; mouse Rig-i , F , 5′-ATTGTCGGCGTCCACAAAG-3′ and R , 5′-GTGCATCGTTGTATTTCCGCA-3′ , human Ifnb , F , 5′-AAACTCATGAGCAGTCTGCA-3′ and R , 5′- AGGAGATCTTCAGTTTCGGAG G-3′; human S9 , F , 5′-ATCCGCCAGCGCCATA-3′ and R , 5′-TCAATGTGCTTCTGGGAATCC-3′ . Cell stimulants were transfected with Lipofectamine 2000 ( LF2000 , Invitrogen ) according to the manufacturer's protocol . Nucleic acids were mixed with LF2000 in Optimem ( Invitrogen ) at a ratio of 1 . 0 µl LF2000/µg nucleic acid and incubated for 20 minutes at room temperature . The ligand-lipid complexes were added to cells at a final concentration of 3 . 3 µg/ml ( 96-well plates ) and 1 . 0 µg/ml ( 6 well plates ) . For poly I:C , the stock solution ( 2 . 5 mg/ml ) was heated at 55°C for 10 minutes and cooled to room temperature immediately before mixing with LF2000 . Transfection experiments were incubated for 8 hours , unless otherwise stated . RIG-I , MDA5 , TRIF and SdhA expression plasmids , along with an IFNβ-firefly luciferase reporter and TK-Renilla luciferase plasmids , were transfected with FuGENE 6 ( Roche ) according to the manufacturer's protocol . Nucleic acids were mixed with FuGENE 6 in Optimem at 0 . 5 µl/96 well and incubated for 15 minutes . Total transfected DNA was normalized to 200 ng per well using an empty pcDNA3 plasmid . Cells were stimulated 20 hours after transfection of expression plasmids . Cell culture supernatants or bronchoalveolar lavage fluid ( BALF ) was overlayed on L929-ISRE IFN reporter cells in a 96-well plate format and incubated for 4 hours at 37°C and 5%CO2 . L929-ISRE IFN reporter cells and HEK293T cells expressing an IFNβ-firefly luciferase reporter and TK-Renilla luciferase were lysed in Passive Lysis Buffer ( Promega ) for 5 minutes at room temperature and relative light units were measured upon injection of firefly luciferin substrate ( Biosynth ) or Renilla substrate with the LmaxII384 luminometer ( Molecular Devices ) . For transient transfection reporter assays , luciferase values were normalized to an internal Renilla control . Cytotoxicity of bacterial strains was determined by measuring lactate dehydrogenase release essentially as previously described [59] . Macrophages were plated at a density of 1×105 in a 96-well plate and infected with stationary phase L . pneumophila at a multiplicity of infection ( MOI ) of 1 . Plates were spun at 400×g for 10 minutes to allow equivalent infectivity of non-motile and motile strains [12] . Plates were re-spun 4 hours post infection and cell culture supernatants were assayed for LDH activity . Specific lysis was calculated as a percentage of detergent lysed cells . Bacterial growth was determined as previously described [16] . Bone marrow derived macrophages were plated at a density of 1×105 per well in white 96-well plates ( Nunc ) and allowed to adhere overnight . Macrophages were infected with stationary-phase L . pneumophila at a multiplicity of infection ( MOI ) of 0 . 01 . Growth of luminescent L . pneumophila strains was assessed by RLU with the LmaxII384 luminometer ( Molecular Devices ) . Nonluminescent bacterial strains were analyzed for colony-forming units on buffered charcoal yeast extract plates . Transposon mutagenesis of LP02 was previously described [12] . Briefly , the pSC123 mariner transposon was mated from E . coli SM10 λpir into the L . pneumophila strain LP02 . Matings were plated on buffered yeast extract charcoal plates with streptomycin ( 100 µg/ml ) and kanamycin ( 25 µg/ml ) . Single colonies were isolated and grown in overnight cultures and used to infect bone marrow derived MyD88−/−Trif−/− macrophages . After overnight incubation , levels of type I interferon in the supernatant was determined by bioassay . The site of transposon insertion was determined by Y-linker PCR [60] . Age and sex-matched Ips-1−/− and littermate Ips-1+/− mice were infected intranasally with 2 . 5×106 LP01 ΔflaA in 20 µl PBS . Bronchoalveolar lavage was performed 20 hours post infection via the trachea using a catheter ( BD Angiocath 18 g , 1 . 3×48 mm ) and 800 µl PBS . Type I interferon induction was determined by bioassay . Type I interferon amounts were calculated using a 4-parameter standard curve determined by dilution of recombinant IFNβ ( R&D Systems ) . CFUs were determined by hypotonic lysis of cells from the brochoalveolar lavage fluid ( BALF ) . In parallel experiments , it was determined that CFU in the BALF was representative of total CFU in the lung . Knockdown constructs were generated with the MSCV/LTRmiR30-PIG ( LMP ) vector from Open Biosystems . shRNA PCR products were cloned into the LMP vector using XhoI and EcoRI sites . Rig-i sequence: 5′-GCCCATTGAAACCAAGAAATT-3′ , control shRNA sequence: 5′-TGACAGTGTCTTCGCTAATGAA-3′ . MyD88−/−Trif−/− immortalized bone marrow derived macrophages were transduced with retrovirus as previously described [10] . GFP+ macrophages were sorted with the DAKO-Cytomation MoFlo High Speed Sorter .
|
Initial detection of invading microorganisms is one of the primary tasks of the innate immune system . However , the molecular mechanisms by which pathogens are recognized remain incompletely understood . Here , we provide evidence that an immunosurveillance pathway ( called the RIG-I/MDA5 pathway ) , thought primarily to detect viruses , is also involved in the innate immune response to an intracellular bacterial pathogen , Legionella pneumophila . In the response to viruses , the RIG-I/MDA5 immunosurveillance pathway has been shown to respond to viral RNA or DNA . We found that the RIG-I pathway was required for the response to L . pneumophila RNA , but was not required for the response to L . pneumophila DNA . Thus , one explanation of our results is that L . pneumophila RNA may access the host cell cytosol , where it triggers the RIG-I/MDA5 pathway . This is unexpected since bacteria have not previously been thought to translocate RNA into host cells . We also found that L . pneumophila encodes a secreted bacterial protein , SdhA , which suppresses the RIG-I/MDA5 pathway . Several viral repressors of the RIG-I/MDA5 pathway have been described , but bacterial repressors of RIG-I/MDA5 are not known . Thus , our study provides novel insights into the molecular mechanisms by which the immune system detects bacterial infection , and conversely , by which bacteria suppress innate immune responses .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"microbiology/innate",
"immunity",
"immunology/innate",
"immunity"
] |
2009
|
Identification of Host Cytosolic Sensors and Bacterial Factors Regulating the Type I Interferon Response to Legionella pneumophila
|
Several studies suggest that HTLV-1 infection may be associated with a wider spectrum of neurologic manifestations that do not meet diagnostic criteria for HAM/TSP . These conditions may later progress to HAM/TSP or constitute an intermediate clinical form , between asymptomatic HTLV-1 carriers and those with full myelopathy . Our aim was to determine the prevalence of HTLV-1-associated disease in subjects without HAM/TSP , and the relationship between these findings with HTLV-1 proviral load ( PVL ) . Methods: 175 HTLV-1-infected subjects were submitted to a careful neurological evaluation , during their regular follow up at the HTLV outpatient clinic of the Institute of Infectious Diseases “Emilio Ribas” , São Paulo city , Brazil . Clinical evaluation and blinded standardized neurological screening were performed for all the subjects by the same neurologist ( MH ) . Results: After the neurological evaluation , 133 patients were classified as asymptomatic and 42 fulfilled the criteria for intermediate syndrome ( IS ) . The mean age of the enrolled subjects was 46 . 3 years and 130 ( 74 . 3% ) were females . Clinical classification shows that neurological symptoms ( p<0 . 001 ) , visual disorders ( p = 0 . 001 ) , oral conditions ( p = 0 . 001 ) , skin lesions ( p<0 . 001 ) , bladder disorders ( p<0 . 001 ) , and rheumatological symptoms ( p = 0 . 001 ) , were strongly associated to IS , except for disautonomy ( p = 0 . 21 ) . A multivariate analysis revealed that HTLV-1 proviral load , oral conditions , bladder disorders and rheumatological symptoms were independently associated with the IS . Conclusions: We found some early alterations in 42 patients ( 24% ) , particularly the presence of previously not acknowledged clinical and neurological symptoms , among subjects previously classified as "asymptomatic" , who we reclassified as having an intermediate syndrome .
HTLV-1 , a human retrovirus , is the causative agent of Adult T Leukemia/Lymphoma ( ATLL ) and HTLV-1-associated myelopathy ( HAM/TSP ) [1] , at least 5–10 million people infected worldwide , almost 5–10% of them in Brazil [2] . However high , such numbers may be an underestimate since only 2/3 of the world has been mapped for HTLV infection [3] . Clinically , HAM/TSP is characterized by muscle weakness , hyperreflexia , spasticity in the lower extremities and urinary disturbances associated with preferential damage to the thoracic spinal cord [4] . HTLV-1 has been shown to be associated not only with HAM/TSP but also with several inflammatory diseases , such as alveolitis , polymyositis , arthritis , infective dermatitis , Sjögren syndrome and uveitis [5–9] . In addition , sensory and gait abnormalities , isolated bladder dysfunction , erectile dysfunction , and sicca syndrome , have all been reported among HTLV-1–infected individuals without HAM/TSP [10] . Several neurological manifestations that are not explained by myelopathy have been described in so-called symptomatic persons , such as peripheral polyneuropathy , myositis , dysautonomia and cognitive alterations , as well as cranial neuropathies , movement disorders and an amyotrophic lateral sclerosis ( ALS ) -like syndrome [11] . Despite the fact that few patients ( <10% ) will develop classical syndromes ( ATLL and HAM/TSP ) , preliminary observations indicate that other symptoms and subclinical neurological disturbances can develop in those individuals [12] , but they have not been well-defined as new clinical outcomes related to early inflammation process . In addition , peripheral neuropathy is significantly more frequent in the seropositive group . In a study with 153 HTLV-1-infected carriers , the presence of higher frequency of motor and bladder dysfunctions in HTLV-1 patients as compared with uninfected control subjects was found [13] . Those data suggest that HTLV-1-infected individuals may exhibit a wide variety of neurological manifestations distinct from the classical picture of HAM/TSP [13] . It is unclear whether such manifestations share a common characteristic with the spinal cord disease . This study aims to demonstrate that some clinical conditions , neurological finds and HTLV-1 proviral load may be associated with further development of full-blown HAM/TSP , in individuals considered free of the disease according to currently used criteria for its diagnosis . To do so we studied patients from a large cohort of asymptomatic HTLV-1 carriers who have been followed for more than twenty years .
Clinical evaluation and a standardized screening neurological examination were performed by MH ( a board-certified neurologist , and blinded for HTLV-1 clinical condition ) for all subjects . Only symptoms/signals already associated with HTLV-I infection in previous reports were considered , and they should have no other clinical explanation . Each patient had at least one neurological/clinical evaluation , and a standardized questionnaire was used , with separate questions for clinical and neurological aspects [15] . HAM/TSP diagnostic criteria was based on recommendations from an international consortium [16] . Briefly , definite HAM/TSP is a non-remitting progressive spastic paraparesis with sufficiently impaired gait to be perceived by the patient . Sensory symptoms or signs may or may not be present but when present , they are subtle and without a clear-cut sensory level . Urinary and anal sphincter signs or symptoms may or may not be present , and the presence of anti-HTLV-1 antibodies in the cerebro spinal cord fluid ( CSF ) . Probable HAM/TSP was defined by a monosymptomatic presentation: spasticity or hyperreflexia in the lower limbs or isolated Babinski sign with or without subtle sensory signs or symptoms , or neurogenic bladder only confirmed by urodynamic tests . For both definite and probable definitions , clinicians must exclude an array of disorders that can mimic HAM/TSP . We described a possible intermediate state of HAM not fulfilling the classical definition ( 16 ) . To be considered as an intermediate syndrome case the patient must present more three signs , found during a neurological evaluation , with the investigator blinded to the patient’s HTLV status . For this present study , only clinical findings previously associated with HTLV-1 were considered , such as dermatological , ophthalmological , rheumatological , urinary , disautonomic , and oral changes [17] . Neurological evaluation included tests of strength in upper and lower limbs , cranial nerves function and patellar , biceps and plantar reflexes , as well as an appraisal of the vibration sense . The presence of minimal changes in muscular strength or gait was explored: subjects were asked to walk on their heels , toes , tandem gait , and rise from a chair without help from their arms . A large clinical and laboratory database has been organized on an internet based platform using REDCap , software developed at the Vanderbilt University by an informatics core . All clinical data , which have been updated on a regular basis over the last 20 years , were entered into a specific REDCap database [18] . HTLV-1 proviral load was quantified by real-time PCR , using primers and probes targeting the pol gene: SK110 and SK111 , the internal HTLV-1 Taq Man probe was selected using Oligo ( National Biosciences ) . All samples were run in duplicate , and results expressed as HTLV-1 DNA copies/104 peripheral blood mononuclear cells ( PBMCs ) , as described elsewhere [19] . The Ethical Board of the IIER approved the protocol ( Number 86379218 . 6 . 1001 . 0061 ) . We obtained signed informed consent from all participants prior to study inclusion , and all participants were adults . Statistical analysis was conducted using Student’s t-test for parametric data , and the chi-square test for proportions . Bivariate logistic analysis was performed to identify independent variables associated with the intermediate syndrome ( IS ) . Variables associated with the outcome at a significance level of p<0 . 20 ( IS ) in the bivariate analysis were included in a multivariate logistic model , in a stepwise forward fashion . Such variables were: visual symptoms , skin lesions , oral conditions , bladder disfunction , and rheumatological conditions . The best fitting model was selected . The logistic analysis was performed with the aid of Stata 12 software ( StataCorp . 2011 . Stata: Release12 . Statistical Software . College Station , TX ) .
We enrolled 175 HTLV-1 patients on this study and classified them as having or not criteria for the diagnosis of the intermediate syndrome . Based on a thorough neurological examination , 42 patients met the criteria for making the diagnosis of the intermediate syndrome , whereas 133 did not and were called “asymptomatic” ( not having the intermediate syndrome ) . All of them had intermediate symptoms that were classified as probable HAM/TSP at entry , primarily neurogenic bladder confirmed by urodynamic study . Table 1 shows the univariate analyses of socio demographic variables and proviral load of all volunteers; mean age of the enrolled subjects ( n = 175 ) was 46 . 3 years and 130 ( 74 . 3% ) were females . Most of the patients were white ( 56 . 5% ) , and the PVL from the IS cases was six times that from patients without IS ( p<0 . 001 ) . Clinical classificafion on Table 2 shows that neurologic symptoms/signals ( p<0 . 001 ) , visual disorders ( p = 0 . 001 ) , oral manifestations ( p = 0 . 001 ) , skin lesions ( p<0 . 001 ) , bladder disorders ( p<0 . 001 ) , and rheumatologic symptoms ( p = 0 . 001 ) , were strongly associated to IS , except for disautonomy ( p = 0 . 21 ) . On a multivariate model analysis , including gender , age , and PVL and several clinical conditions , such as oral conditions , bladder disorders and rheumatological symptoms were independently associated with SI outcome . In this same model , all these variables and age were also significantly associated with the outcome , when included as continuous variables ( Table 3 ) . Table 4 shows that the presence of more than three or more signs and/or symptoms was significantly associated with the intermediate syndrome ( p = 0 . 006 ) , therefore the the cut-off point for that diagnosis was set at this point .
This study aimed to define the early neurological disorders that can be present in HTLV-1-infected subjects . We found 24% of HTLV-1-infected patients from our outpatient service who were initially considered asymptomatic to have enough signs and symptoms putting them on a novel category , called intermediate syndrome . The correlation between some of their symptoms and the proviral load also reinforces the importance of such mild forms , which may constitute either an independent clinical intermediate syndrome or markers for an early diagnosis of HAM/TSP . A significantly PVL was also present in patients presenting three or more symptoms or signs . HAM/TSP is a chronic progressive myelopathy characterized by bilateral pyramidal tract involvement with sphincter disturbances . Why only a small proportion of HTLV-1-infected individuals develops classical HAM/TSP is not known [11] . The main neurological symptoms of the disease are progressive and lead to deterioration in the quality of life , but minor neurological symptoms can also be found among HTLV-1 carriers [11] . In a study with 153 HTLV-1-infected carriers and 388 HTLV-2-infected subjects , the presence of neurological abnormalities was prospectively ascertained , with a higher frequency of motor and bladder dysfunctions in HTLV-1 as compared with uninfected control subjects [10] . All those data suggest that HTLV-1-infected individuals can exhibit a wide variety of neurological manifestations distinct from the classical picture of HAM/TSP [11] . It is unclear whether those manifestations share a common characteristic with this diagnosis . We and others have shown a correlation between proviral load and Tax gene expression with the presence of HAM/TSP [14 , 19 , 20] . We hypothesize that the burden of HTLV-1 was correlated with neurological disturbances that fall short of HAM/TSP , and with cognitive dysfunction . Demonstration of that hypothesis might provide a link between HTLV-1 burden and early neurological dysfunctions , providing impetus to the development of methods aiming to reduce the proviral load in infected subjects . Perhaps the explanation for the observed neurological findings lies in the white matter . The white matter present in the CNS has the important function of transporting neural signals from subcortical regions to the cortex and from the cortex to the subcortical regions . In the CNS , ischemic and traumatic injuries often result in significant functional deficit , most of which can be attributed to white matter dysfunction [21–23] . In the case of HTLV-1 , there is participation of components of the inflammatory response on the mechanisms underlying the demyelination process characteristic of this disease [20] . We found that HTLV-1 infection is associated with a variety of clinical manifestations occurring in patients who either do not have or who did not have developed full HAM/TSP yet . The correlation between some of their symptoms and the proviral load also reinforces the importance of such milder forms , which may constitute either an independent clinical SI or markers for an early diagnosis of HAM/TSP . A significantly higher proviral load was present in patients presenting more than three symptoms/signs , a cut-off point that can constitute a surrogate marker for clinical progression . In conclusion , this preliminary report identified the presence of some clinical and neurological symptoms , in subjects classified originally as "asymptomatic , " which may be promising markers for early HAM/TSP progression . This knowledge may contribute for a stricter clinical vigilance of the so-called asymptomatic HTLV-1 positive patients , prompting the introduction of a treatment for the infection , if and when it becomes available in the future .
|
At least 5–10 million people live with the Human T-Cell Lymphotropic Virus type 1 ( HTLV-1 ) worldwide , and around 0 . 25–5% of them may develop HTLV-1-associated myelopathy/Tropical spastic paraparesis ( HAM/TSP ) , which is associated with chronic inflammation . In this study , involving 175 HTLV-1-infected subjects originally classified as asymptomatic , we found that 42 of them in reality presented some early clinical conditions , including alterations related not only to the neurological system , but also to the eyes and the skin . We called such conditions intermediate syndrome . Thus , it seems reasonable to suggest that all HTLV-1-infected subjects should be monitored for symptoms that may arise earlier in the course of their infection .
|
[
"Abstract",
"Introduction",
"Methods",
"Results",
"Discussion"
] |
[
"urology",
"cognitive",
"neurology",
"medicine",
"and",
"health",
"sciences",
"bladder",
"and",
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2019
|
Detection of clinical and neurological signs in apparently asymptomatic HTLV-1 infected carriers: Association with high proviral load
|
Protegrin peptides are potent antimicrobial agents believed to act against a variety of pathogens by forming nonselective transmembrane pores in the bacterial cell membrane . We have employed 3D Poisson-Nernst-Planck ( PNP ) calculations to determine the steady-state ion conduction characteristics of such pores at applied voltages in the range of −100 to +100 mV in 0 . 1 M KCl bath solutions . We have tested a variety of pore structures extracted from molecular dynamics ( MD ) simulations based on an experimentally proposed octomeric pore structure . The computed single-channel conductance values were in the range of 290–680 pS . Better agreement with the experimental range of 40–360 pS was obtained using structures from the last 40 ns of the MD simulation , where conductance values range from 280 to 430 pS . We observed no significant variation of the conductance with applied voltage in any of the structures that we tested , suggesting that the voltage dependence observed experimentally is a result of voltage-dependent channel formation rather than an inherent feature of the open pore structure . We have found the pore to be highly selective for anions , with anionic to cationic current ratios ( ICl−/IK+ ) on the order of 103 . This is consistent with the highly cationic nature of the pore but surprisingly in disagreement with the experimental finding of only slight anionic selectivity . We have additionally tested the sensitivity of our PNP model to several parameters and found the ion diffusion coefficients to have a significant influence on conductance characteristics . The best agreement with experimental data was obtained using a diffusion coefficient for each ion set to 10% of the bulk literature value everywhere inside the channel , a scaling used by several other studies employing PNP calculations . Overall , this work presents a useful link between previous work focused on the structure of protegrin pores and experimental efforts aimed at investigating their conductance characteristics .
Antimicrobial peptides ( AMPs ) are small proteins produced by the innate immune system of many plants and animals as a first line of defense against bacterial infections [1] , [2] . Due to their persistence in nature as well as their nonspecific mechanism of action , there has been significant research activity aimed at designing novel antibiotics based on AMPs [3]; the expectation is that bacteria will not develop significant resistance to antibiotics designed based on these peptides . Thus far , such drug design efforts have been largely hampered by a lack of understanding of the fundamental mechanism of action of AMPs . Although recent evidence suggests that intracellular targets may play an important role in the action of many AMPs [2] , [4]–[7] , there is a strong body of evidence suggesting that the ability of peptides to interact with and disrupt the bacterial membrane is essential to their mechanism of action [1] , [8]–[10] . AMPs of various structural classes have been shown to have significant disruptive effects on both living bacterial membranes and model membrane systems , such as lipid bilayers [8] , [11] , [12] and lipid monolayers [8] , [13] , [14] . For thorough reviews of several proposed mechanisms of membrane disruption , the reader is referred to [10] . Most relevant for the present work is the model in which AMPs aggregate to form large , nonselective pores in the bacterial membrane , which result in uncontrolled ion leakage , decay of the transmembrane potential , uncontrolled water transport , loss of cell contents and ultimately cell death . We have focused our efforts on protegrin-1 , a particularly potent antimicrobial peptide , which has recently been shown to form such pores in lipid bilayers of certain compositions . Protegrins are small peptides isolated from porcine leukocytes that exhibit strong antimicrobial activity against a broad range of both Gram-positive and Gram-negative bacteria [15] . Protegrins are characterized by a β-hairpin conformation that is held together by two cysteine-cysteine disulfide bonds . They contain 16–18 amino acids , and are typically highly cationic ( charge of +7 ) , with the positive charges arising from arginine residues at the hairpin turn region and the two termini . In the present work , we focus on the most prevalent natural form of protegrin , designated as PG-1 , with the amino acid sequence RGGRLCYCRRRFCVCVGR-NH2 ( PDB entry 1pg1 ) . Mani and coworkers [16] have conducted solid-state NMR experiments to investigate the membrane-bound structure of a PG-1 peptide , and have concluded that this peptide likely forms octomeric pores in lipid bilayers composed of a 3∶1 mixture of palmitoyloleoyl-phosphatidylethanolamine ( POPE ) to palmitoyloleoyl-phosphatidylglycerol ( POPG ) [16] . Langham and coworkers used the structure suggested from these NMR experiments as the starting configuration of a molecular dynamics simulation in a lipid bilayer of the same composition [17] . This simulation showed the pore to be stable over more than 150 ns . Figure 1 shows a cartoon representation a single protegrin peptide , as well as a side view of the proposed pore structure . Prior to these studies of the pore structure of protegrin , early evidence of protegrin pores was provided by the experiments of Mangoni and coworkers [18] and Sokolov and coworkers [19] , in which the conductance characteristics of protegrin-treated membranes were measured . Such knowledge of the nonequlibrium ion flow through protegrin pores may be closely related to their mechanism of action , since the unrestricted flow of ions through the membrane could result in potentially lethal membrane depolarization . Mangoni and coworkers conducted voltage clamp experiments in Xenopus laevis oocyte membranes treated with protegrin-1 and several analogues [18] . They found that protegrins form weakly anion selective pores in the presence of several different salts , with KCl solutions exhibiting almost no selectivity . Furthermore , they found that the conductance of such pores does not exhibit any voltage dependence over a voltage range of −100 to +30 mV . Sokolov and coworkers [19] carried out conductance measurements across several different types of planar phospholipid bilayers treated with protegrin-1 as well as protegrin-3 ( PG3 , amino RGGGLCYCRRRFCVCVGR; note the only difference between PG-1 and PG-3 is the substitution of a glycine residue at the third position in PG-3 instead of the arginine residue in PG-1 ) . These authors found that both protegrin analogues form weakly anion selective channels in mixed phospholipid bilayers , and moderately cation-selective channels in bilayers containing negatively charged bacterial lipopolysaccharide ( LPS ) . They reported a voltage-dependent single-channel conductance in the range of 40–360 picoSiemens ( pS ) , depending on the peptide used , the lipid bilayer composition , and the applied voltage . In the present work , we attempt to explain and quantify the conductance behaviour of protegrin pores in terms of the structural information from NMR experiments [16] and molecular dynamics simulations [17] . In particular , we explore the connection between structural features such as the size of the pore opening and the magnitude of the conductance , as well as the surprising experimental finding of both Mangoni and coworkers [18] and Sokolov and coworkers [19] that the protegrin pore is only slightly anion selective , despite having a total charge of +56 . Our investigation is based on the Poisson-Nernst-Planck ( PNP ) theory , a continuum method of calculating non-equilibrium ion concentrations and fluxes around a fixed structure in the presence of an applied electrical voltage . In our model , we simulate a voltage across a protegrin pore embedded in a lipid bilayer patch , and measure the resulting current . Since the PNP model requires a rigid structure , we perform the calculations using several snapshots from the MD simulations of Langham and coworkers [17] . The description of the underlying equations and the numerical scheme used to solve them is deferred to the Methods section below .
In all of the results presented herein , we have modeled electrodiffusion of ions through a protegrin pore bathed in KCl solutions under a constant applied voltage . The solution of the PNP equations yields the nonequilibrium concentration profiles of both ions and the electrostatic potential profile . Figure 2 shows a plot of the concentration profiles of both potassium and chloride ions as a function of location along the pore axis for typical model parameters . The values shown represent average concentrations in small planar slabs along the pore axis . From the concentration and electrostatic potential profiles , the net current can be obtained using equation 7 ( see Methods section ) . Repeating this for multiple voltage values yields a current-voltage ( I–V ) relationship that can be compared to experimental results . Figure 3 shows the I–V curve obtained for a snapshot at 93 . 5 ns of the NPT segment of the MD simulations of Langham and coworkers [17] , along with experimental data from Sokolov and coworkers [19] . In both cases , these data correspond to 100 mM KCl solutions on both sides of the lipid bilayer . The data in Figure 3 were obtained by setting the diffusion coefficient to 10% of its bulk value everywhere inside the channel , which represents an empirically adjusted value used to partially account for the approximate nature of PNP theory . The sensitivity of the calculations to the choice of diffusion coefficient is discussed below . The corresponding conductance ( the slope of the line in Figure 3 ) is approximately 280 pS over the entire voltage range , in agreement with the experimental range of 40–360 pS [19] . The value of the voltage in our model corresponds to the side nearest to the protegrin termini , while virtual ground is defined on the side of the hairpin turns ( refer to Figure 1 ) . Table 1 shows the conductance characteristics obtained for several simulated structures , along with dimensions that characterize these structures . The nanosecond values in the structure description column indicate the simulation time from the start of the constant pressure and temperature ( NPT ) segment of the MD simulations of Langham and coworkers [17] . All data except the reversal potential correspond to a symmetric 100 mM KCl solution with an applied voltage of −20 mV . We also analyzed the sensitivity of the results to several model parameters , and found the diffusion coefficient profile to have the most significant effect . Four diffusion coefficient profiles were used , shown in Figure 3 in the Methods section below . The resulting conductance characteristics obtained using the pore structure at 93 . 5 ns are tabulated in Table 2 . The rationale for each diffusion coefficient profile is discussed in greater detail in the methods section . In order to quantify the relative importance of certain charged moieties within the structure , we analyzed the effects of removing the positive charges of the arginine residues of the peptides in one case , the negative charges in the POPG lipids in another case , and both in a third case , all the while keeping the rest of the system unchanged . The results are summarized in Table 3 .
The results of the PNP model solved for various structures are summarized in Table 1 . None of the structures described showed any significant voltage-dependence in an applied voltage range of +/−100 mV ( data not shown ) . The conductance values obtained based on structures extracted from the molecular dynamics simulations are all in good agreement with the experimentally observed values in anionic lipid bilayers ( 60–360 pS ) . The diameter of the smallest channel constriction in these structures ranges from 6–10 Å , which is on the lower end of the applicability of PNP modeling ( see discussion below ) , but nonetheless sufficiently large to yield meaningful results . The variations that exist among different snapshots are the results of minor conformational changes caused by thermal fluctuations , in particular the motion of side chains into and out of the pore opening . Although these effects are noticeable , they are not drastic , and not as large as the differences between the MD structures from 60–93 . 5 ns and the other three structures . It is also worth noting that the diameter of the narrowest constriction , while it does somewhat correlate with conductance , is not the sole factor influencing it . For instance , the snapshot at 93 . 5 ns has a larger constriction diameter than either the 85 . 5 or 91 . 5 ns snapshots by almost 2 Å , and yet shows the same conductance as the 85 . 5 ns snapshot , and a lower conductance than the 91 . 5 ns snapshot . Thus , while steric effects clearly affect ion permeation , there are other conformational changes that have significant influence on pore conductance . These are likely electrostatic effects that arise from conformational changes of the charged side chains ( e . g . arginine ) . These are explored in further detail below . The results for the last three structures shown in Table 1 correspond most closely to the structure proposed by Mani and coworkers [16] , which was used to start the MD simulations . This structure has a larger opening than the molecular dynamics simulations , and yields much higher conductance values . Even considering the inaccuracies in our model , these values are not in good agreement with experimentally measured values , which may suggest that the corresponding structures are not the dominant conformers . Since the NMR experiments do not directly resolve the positions of all side chains , we posit that the narrower opening observed in molecular dynamics simulations , which is primarily due to the motion of side chains into the interior of the pore , represents a more realistic structure . However , as discussed below , there are several other considerations that can significantly affect the conductance values obtained from PNP modeling . In order to explain the conductance behavior observed in our model in terms of more specific structural features , we have analyzed the molecular dynamics simulations in greater detail . The high selectivity of the pore for anions that we observe in PNP calculations is likely due to electrostatic attraction between the positively charged guanidinium groups in the arginine side chains and negatively charged chloride ions ( this is compellingly confirmed in the section ‘Influence of embedded charges’ below ) . However , competing with this interaction is the attraction of arginine side chains to negatively charged phosphate groups in the lipid head groups . In order to investigate the relative importance of these interactions , we have computed radial distribution functions for both chloride and phosphate groups from the ζ-carbon of all arginine side chains . For brevity , the resulting 48 plots are included as online supporting information ( Text S1 ) . Due to the axial symmetry of the pore and the equivalence of all eight peptides ( except perhaps with respect to dimer pairings ) , we confine our discussion to averaged data for each arginine position . Figure 4 shows the number of chloride and phosphate atoms within 7 . 5 Å of the arginine ζ-carbon at each position , averaged over time as well as over all eight peptides . The value of 7 . 5 Å was selected to include the first large peak in all of the radial distribution functions ( see Text S1 ) . As shown , arginine side chains at all positions interact fairly strongly with both phosphate groups and chloride ions . Arginine at position 1 exhibits a much stronger interaction with phosphate groups , indicated by an average value of 2 . 45 phosphate groups , as compared to 0 . 64 chloride ions . Also noteworthy is the difference at position 11 , where phosphate interactions are again significantly stronger than chloride interactions . Although it may appear based on the averaged data that interactions with phosphate groups do not generally exclude interactions with chloride ions , the individual radial distribution functions ( Text S1 ) show that in many cases , strong interactions of a particular residue with phosphate lead to weak interactions of that residue with chloride , and vice versa . However , considering the equivalence of all eight peptides , it is the averaged data that are more significant; the individual residue data in this case only reflect the fact that binding of particular arginine residues to phosphate or chloride ions often persists on the time scale of the molecular dynamics simulations . Another notable feature in Figure 4 is the stronger interaction of arginine at position 4 with chloride as compared to the other arginine residues . Although the difference is not drastic ( 1 . 31 chloride ions for position 4 compared to 0 . 64 for position 1 , or 1 . 14 for position 10 ) , this may represent a significant electrostatic feature of the protegrin pore , particularly considering that the data represent an average over all eight peptides . The arginine side chain at position 4 is in a favorable location to be interacting with the aqueous pore interior , where it can have the largest effects on conduction characteristics . Considering the location of the other arginine residues near the termini and the β-sheet turn , as well as the discussion of phosphate interactions in the preceding paragraph , one could hypothesize that the purpose of arginine at position 4 is primarily to attract anions through the pore . In contrast , the remaining arginine side chains interact more strongly with lipid head groups in order to facilitate peptide insertion and stabilize the pore structure . This is consistent with the fact that arginine residues at position 4 have the weakest interactions with phosphate groups . We investigate this hypothesis in further detail in the section ‘Influence of embedded charges’ below . Additionally , we have also investigated the rotameric conformations of all arginine side chains in order to confirm that they are indeed well-sampled and found in reasonable rotameric states throughout the relevant portion of the molecular dynamics simulations . Figure 5 shows the definition of the side chain dihedral angles that we have used . We have included plots of all dihedral angles for all arginine side chains as online supporting information ( Text S1 ) . Plots are labeled as “peptide-position” - for example , plot P1-6 corresponds to peptide 1 , position 6 . Dihedral angle χ1 generally occurs in the energetically favorable trans conformation ( values near ±180° ) , but also occasionally in a gauche conformation ( values near ±60° ) , as in P4-1 to P4-18 , and P8-1 to P8-9 . Dihedral angle χ2 is largely found in the trans conformation , with only a handful of noticeable exceptions in the gauche conformations ( P2-10 , P3-9 , 10 , 11 , P6-9 , P7-18 and P8-9 ) . The same general trend of preference for trans conformations is true for angles χ3 and χ4 , with χ4 ( blue ) showing perhaps the greatest flexibility ( see , for instance , the variation in P1-1 , 18; P3-1 , 10 , 11; P7-1; P8-18 ) . Angle χ5 is exclusively found in an eclipsed conformation ( value near 0° ) , shown by the yellow bands in the centres of all plots . This is not surprising , considering the partial charge in the CHARMM27 force field is −0 . 47 for N1 and +0 . 64 for Cζ , resulting in a strong attraction between these atoms ( refer to Figure 5 above for atom labels ) . Overall , while some variation occurs due to thermal fluctuations , the arginine side chains are largely found in common rotameric states . One of the most important parameters required for successful PNP modeling is the space-dependent diffusion coefficient of all diffusing ionic species . The diffusion coefficient is often empirically adjusted to account for the approximate nature of the PNP theory . The value of the diffusion coefficient is expected to be different from the bulk literature values in the constricted molecular geometry of the pore interior [25] , [26] . Unfortunately , the diffusion coefficients inside the pore are also one of the most difficult parameters to assign . As far as we are aware , no experimental techniques are capable of measuring the diffusion coefficient of ions within a molecular pore to a high accuracy and with sufficiently high spatial resolution; certainly no such data are available for the protegrin pore . We have therefore used four different empirically-derived diffusion coefficient profiles , denoted as D1–D4 . Plots of the diffusion coefficient of potassium and chloride as a function of the pore axial coordinate for each profile are shown in Figure 6 in the Methods section below . In all cases , the diffusion coefficient was assumed to be isotropic and invariant in the x and y directions ( in the plane of the bilayer ) . The PNP system was solved for all four diffusion coefficient profiles ( D1–D4 ) using the structure at 80 ns of the MD simulation . The results are summarized in Table 2 , along with a brief description of each profile . None of the cases tested showed any significant voltage-dependence for applied voltages in the range of +/−100 mV . As already mentioned , the experimentally reported conductance is 50–100 pS in black lipid membranes and 60–360 pS in anionic membranes [19] . Clearly , diffusion coefficient profiles D1 and D2 result in unacceptably high conductance values , indicating that the diffusion coefficient inside the channel should be significantly lower . Using the hydrodynamic model of [27] , which was also employed successfully in references [28] , [29] in PNP models of α-hemolysin channels , yields a slightly lower value , but still outside of the range of the experimentally determined conductance . The diffusion coefficient profile D4 yields the best agreement with experimental conductance data . Although setting the diffusion coefficient to 10% of the bulk value may seem a low estimate , similar scaling was used by Furini and coworkers [30] and Kurnikova and coworkers [31] in successfully modeling KcsA channels and Gramicidin A channels , respectively . Considering the differences between our model and the experimental systems , variations due to minor structure fluctuations , as well as the approximate nature of our model , profile D4 appears to be a reasonable estimate for the diffusion coefficients , and can be treated as an effective fitting parameter . As shown in Table 3 , the positively charged arginine residues , which impart the pore a total charge of +56 , are by far the dominant factor influencing conductance behaviour . Removal of the arginine charges decreases conductance by a full order of magnitude , and changes the selectivity of the pore from strongly anionic to cationic . If the POPG charges are also removed , the selectivity becomes only slightly cationic , and the total conductance is even lower . Turning off the charges in the POPG bilayer while retaining the arginine charges does not result in a significant difference in the total conductance or the current ratio . This suggests that in the presence of charged arginine residues , charges in the lipid bilayer do not have an appreciable direct effect on conductance characteristics in a formed pore , as the former clearly dominate all electrostatic behavior ( however , the POPG charges clearly have a significant impact on the ability of the peptides to form a pore in the first place ) . Although complete removal of the arginine charges would not happen in any realistic physical situation , the results in this section show how drastic an effect these charges have . In order to investigate the effects of individual arginine residues , we solved the PNP model for six additional situations , each corresponding to turning off the positive charges on the arginine residues for all peptides at a particular position . The calculations discussed were all performed on the structure corresponding to a snapshot at 93 . 5 ns of the NPT segment of the MD simulations of Langham and coworkers [17] , using diffusion coefficient profile D4 . The results are summarized in Table 4 . As shown in Table 4 , the most significant effect is attained by turning off the charge at arginine position 4 , which results in the largest drop in the conductance as well as the selectivity . This corroborates the hypothesis that the arginine residues at position 4 interact more strongly with the pore interior , likely due to their physical location within the pore . As such , while the other arginine residues likely play a larger role in peptide insertion , it would seem that the purpose of arginine-4 is primarily to effect ion passage through the pore by attracting chloride ions . However , it should be noted that the data in Table 4 represent only the conductance characteristics of one particular snapshot . Nonetheless , considering the consistency with the findings in the section ‘Specific interactions of arginine side chains’ , this appears to be a worthwhile hypothesis that warrants further future investigation . Since the characteristic dimensions of a typical transmembrane pore are commensurate with the size of ions , it behooves us to discuss the validity of a continuum theory in studying such systems . The PNP theory has been shown to overestimate channel conductance in an OmpF porin model by approximately 50% relative to a more rigorous Brownian dynamics ( BD ) approach [32] . Considering that the narrowest constriction in an OmpF porin channel has an area of 15 Å2 , or an effective diameter of ∼4 . 4 Å [33] , this agreement is surprisingly good for a theory that treats ions in a purely continuum representation . In another study designed to test the validity of the PNP theory , Corry and coworkers found that conductance values computed by PNP theory and BD simulations become equivalent for cylindrical pores with a diameter of 32 Å , with PNP results improving in charged channels [20] . Additionally , several studies have used PNP theory to model ion conduction through the α-hemolysin channel , which , at its narrowest constriction point , has an open cross-section with a diameter of approximately 15 Å [28] . Noskov and coworkers [28] as well as Dyrka and coworkers [29] found that the PNP theory overestimated experimental channel conductance values by approximately 30–60% . Furini and coworkers applied PNP modeling to a KcsA channel , which has a mean diameter of 2 . 8 Å in one region and 10–14 Å in another [30] . They obtained good agreement with experimental results , albeit by using an adjusted diffusion coefficient . The narrowest constriction point of the protegrin channel that we are interested in has a diameter ranging from 6–15 Å , depending on the conformation used . Considering the range of applications described above that have employed PNP theory and met with reasonable success , we believe the protegrin pore is a good candidate for such a study . More rigorous approaches such as Brownian dynamics or molecular dynamics with applied voltages are far more computationally demanding ( particularly the latter ) , and would not have allowed us to explore an extensive parameter space . We have applied the PNP theory to predict the conductance characteristics of several variations of a protegrin pore structure . We found that the best agreement with the experimentally measured net conductance was obtained using structures extracted from the latter part of molecular dynamics simulations of Langham and coworkers . Even considering variations in structures due to thermal fluctuations , all of these structures yielded conductance values near the experimental upper bound of 360 pS . The structure of the pore as surmised from NMR experiments has a larger opening at its narrowest constriction point than the structures from MD simulations , primarily due to differences in the orientation of amino acid side chains in the pore interior . PNP models based on this NMR structure yielded conductance values that are significantly higher than the experimentally measured values , even considering the expected typical errors arising from PNP theory . This suggests that the narrower structures observed in molecular dynamics simulations may be more realistic . In all of the structures tested , we observed an extremely high anion selectivity , which is to be expected for such a cationic pore , but surprisingly disagrees with the experimental findings of Sokolov and coworkers [19] . No significant voltage dependence of the conductance was observed in any of our models , corroborating the hypothesis that the voltage-dependence observed by Sokolov and coworkers [19] is a result of voltage-dependent channel formation , rather than an inherent feature of the protegrin pore structure . Due to the high sensitivity of PNP calculations to the diffusion coefficient profile , we have tested several different alternatives . We found that a diffusion coefficient set to 10% of the bulk value inside the channel yielded the best agreement with experimental data; this value therefore effectively represents a fitted parameter that accounts for several shortcomings in the mean field model . Even with these and other limitations of PNP theory in mind , we believe the general trends observed herein form a useful connection between the structural features and conductance characteristics of protegrin pores .
In the PNP theory , ion flux Ji is modeled according to the Nernst-Planck equation , which includes a Fickian diffusion term and a drift term to account for the effects of the electrostatic field: ( 3 ) Where At steady state conditions , mass continuity yields: ( 4 ) Substituting equation ( 3 ) above for the species flux Ji yields: ( 5 ) This is the steady-state Nernst-Planck equation , which determines ion concentrations given an electrostatic potential field . The electrostatic potential field , φ , depends on any fixed charges arising from the protein channel as well as the mobile charge arising from the space-dependent ion concentrations through the Poisson equation: ( 6 ) Here , ρf represents the fixed charge density and ε is the ( space-dependent ) dielectric constant . In the present work , we solve the coupled equations ( 5 ) and ( 6 ) numerically to obtain the steady-state ion concentrations and electrostatic potential . The electrical current across the pore can subsequently be calculated as: ( 7 ) Equation ( 7 ) above can be applied at any z-position along the pore axis , and shows only minor differences in the current values Iz due to numerical inaccuracies . In most cases presented here , these variations are on the order of ∼2% . The coupled PNP system ( equations 5 and 6 ) is solved on a three-dimensional domain defined by the protegrin pore structure . The fixed charge density ρf is determined from the positions and charges of the protein and lipid atoms in the pore structure . The boundary conditions in the plane of the bilayer are periodic for all ion concentrations as well as for the electrostatic potential . In the direction perpendicular to the bilayer , the electrostatic potential is set to zero far away from the pore on the side of the protegrin β-sheet turns , and to the applied voltage ( Vapplied ) far away from the pore on the opposing side , nearest to the protegrin termini ( refer to Figure 1 ) . Similarly , ion concentrations are set to their bulk values far away from the pore in the direction perpendicular to the bilayer . Additionally , there is a no-flux boundary surrounding the peptide and lipid atoms that prevents ions from penetrating through the region occupied by the peptides and lipids . This can be physically interpreted as an approximate way to account for the short-range van der Waals repulsion between ions and peptide or lipid atoms . Throughout the remainder of this manuscript , the z-direction will refer to the direction along the axis of the channel , perpendicular to the plane of the bilayer . The applied voltage values correspond to the value of the potential on the side of the pore nearest to the termini of the peptides . Letting Lx , Ly and Lz represent the length of the computational domain , we can summarize the above boundary conditions as: ( 8 ) The charge density ρf was obtained by assigning to each atom location a point charge corresponding to the partial charge of that atom in the charmm27 force field [34] . Charges were distributed to the nearest grid points using a trilinear interpolation scheme . The ion accessibility region was defined by excluding all of the space occupied by peptide or lipid atoms . This space consists of a sphere with a radius equal to the sum of the atom's van der Waals radius ( as given in the charmm27 force field ) and the probe radius . For all of the results presented in the current work , a value of 1 . 4 Å was used for the probe radius , roughly corresponding to the effective radius of a water molecule . Probe radii corresponding to the radii of the ions were also tested and found to have relatively minor effects on conductance characteristics . The dielectric constant profile was obtained by assigning an appropriate value to the space surrounding each atom . Values of ε = 2 were assigned to lipid tail atoms , and values of ε = 5 were assigned to peptide and lipid head group atoms . Regions not occupied by any of the channel's atoms were assumed to be occupied by water , and assigned a relative dielectric constant of ε = 78 . A few other schemes of assigning the dielectric constant were also tested , and found to have relatively minor effects on overall conductance characteristics ( data not shown ) . In all cases , the dielectric constant profile was numerically smoothed with a Gaussian convolution filter of width σ = 1 . 5 Å . This improved numerical stability , and likely corresponds to a more realistic physical situation . Conductance characteristics were found to be insensitive to the choice of the smoothing parameter within a reasonable range ( data not shown ) . Four different methods were used to assign the space-dependent diffusion coefficient , as mentioned in the Results section . The resulting diffusion coefficient profiles were dubbed D1–D4 , shown in Figure 6 . Profile D1 consists simply of assigning the bulk literature value in all regions of the channel for both ions . These are 0 . 203 Å2/ps for chloride and 0 . 196 Å2/ps for potassium [35] . Since ion diffusion coefficients are likely to change in confined geometries [25] , this profile likely represents a generous upper bound estimate . Profile D2 is based on measuring the diffusion coefficient of chloride and sodium ions from molecular dynamics simulations carried out by Langham et al [17]; however , as already mentioned , there were only 2 events of sodium ions crossing the pore , and the sampling was simply not adequate to obtain reliable diffusion coefficient measurements inside the channel . Furthermore , the TIP3P water model [36] along with the charmm27 force field [34] used in the simulations is known to overestimate the diffusion coefficient of water by a factor of 2 [37]; as such , direct measurements of the diffusion coefficients of ions is not likely to yield accurate results . Instead , we looked at the approximate scaling of the diffusion coefficients in the MD simulations as compared to the measured bulk value , and applied the same scaling to the literature bulk value to create profile D2 for both ions . This amounts to a smooth decrease in the diffusion coefficient from the bulk value at the entrance of the channel to approximately 1/3 of the bulk value at the channel's centre . Profile D3 is based on considering hydrodynamic effects of narrow constrictions on spherical particles . Based on the work of Paine and Scherr [27] , Noskov et al [28] used the following correlation to calculate the diffusion coefficient of ions as a function of channel radius: ( 9 ) Where β = Rion/Rpore , and the empirical fitting parameters have the values given in Noskov et al ( A = 0 . 64309 , B = 0 . 00044 , C = 0 . 06894 , D = 0 . 35647 , E = 0 . 19409 ) . To ion radii used in our model are the van der Waals radii specified in the charmm27 force field ( RCl− = 2 . 27 Å , RK+ = 1 . 764 Å ) , and the radius of the pore is calculated as an effective radius corresponding to the cross-sectional area found from a grid search . The resulting diffusion coefficient profiles for a snapshot at 93 . 5 ns are shown in Figure 6 ( profile D3 ) . Profile D4 corresponds to setting the diffusion coefficients of both ions to their bulk literature values outside the channel , and to 10% of these values inside the channel . For chloride , this translates to a diffusion coefficient of 0 . 203 Å2/ps in the bulk region , and 0 . 0203 Å2/ps in the channel region . For potassium , the diffusion coefficient is 0 . 196 Å2/ps in the bulk region , and 0 . 0196 Å2/ps in the channel region . The channel region here is defined as the ion-accessible region bounded at 25 Å above and below the centre of the channel ( i . e . −25<z<25 , with z = 0 corresponding to the channel centre ) . Similar scaling was used by [31] and [30] in their PNP modeling of gramicidin S and KcSA , respectively , and was found to yield good agreement with experimental results . Although 10% of the bulk value likely underestimates the diffusion coefficient of ions inside the channel [26] , given the success of this scaling , it may well be that it represents an effective correction of the tendency of PNP theory to overestimate ionic currents due to overestimation of the screening effects [20] . The numerical algorithm used in the present work closely follows the finite difference ( FD ) method developed by Im and Roux [32] based on the algorithm proposed by Kurnikova et al [31] . In fact , the code we employed for the PNP solver is built closely on the main solver module of the 3d-PNP code provided on the website of Dr . Benoit Roux: http://thallium . bsd . uchicago . edu/RouxLab/pbpnp . html Briefly , the numerical scheme consists of first converting the Nernst-Planck equation ( 5 ) to a Laplace-like form with the substitution ( 10 ) This is known as a Slotboom transformation [38] , and converts the Nernst-Planck equations to the form: ( 11 ) Where The finite difference representation of equation 11 above leads to the following expression for a given point in the finite difference grid ( corresponding to the index 0 ) in terms of its neighbours ( corresponding to the index j = 1 , . . , 6 ) . ( 12 ) where represents the effective concentration ( vis . eq . 10 ) at neighbouring point j , and . The no-flux boundary condition is implemented by setting the value of to zero for all points in the ion-inaccessible region . This has the same effect as setting the components of the flux perpendicular to the bounding region of the ion-inaccessible surface to zero . Ion concentrations are also initially set to 0 inside the ion-inaccessible region , and do not change due to the implementation of the no-flux boundary condition . Similarly , the Poisson equation ( 6 ) has the following finite-difference representation of the central point in terms of its neighbours: ( 13 ) Here , the summation over the index j represents summation over neighbouring grid points , while summation over i refers to summation over the ionic species , in this case only potassium and chloride . In equation ( 13 ) above , refers to the fixed charge density , and . Equations ( 12 ) and ( 13 ) above form the basis of successive overrelaxation ( SOR ) schemes for solving the Nernst-Planck and Poisson equations , respectively . The Poisson equation is solved first , using either zero everywhere or the solution of the linearized Poisson-Boltzmann equation as an initial guess for the potential . The computed electrostatic potential is then used to construct the effective concentration ψi and εeff profiles ( see equations ( 10 ) and ( 11 ) ) , and this alternate form of the Nernst-Planck equation is solved using the FD scheme above ( equation 12 ) . The ion concentrations are then passed back to the Poisson equation , and a new potential is computed . The process is repeated until convergence of both equations is obtained . In order to achieve stability of the solver , it is necessary to mix the solution from any given iteration of the Poisson equation with the solution from the previous iteration: ( 14 ) Here , φnew represents the electrostatic potential computed at a given iteration of the Poisson equation , and φold represents the potential at the previous iteration . The mixing parameter λ is typically set to 0 . 03 , and increased during the iterative process whenever the concentration profiles do not change appreciably from one iteration of the Nernst-Planck equation to the next . Additionally , due to the high charge of the protegrin pore , we occasionally encountered numerical instabilities early on in the solution process . We employed a continuation strategy based on solving the equations to a low tolerance with a scaled down charge density or a high dielectric constant , then gradually increasing the charge density or decreasing the dielectric constant to their real values after achieving convergence at each intermediate value . Numerical tolerances were typically set to 10−14 Å−3 , or 1 . 7×10−11 M for the concentrations , and 10−8 e−/Å , or 1 . 4×10−4 mV for the electrostatic potential . The grid resolution used for all runs was 0 . 5 Å/grid point . A difference of around 17% in the measured current was observed between a resolution of 1 . 0 Å/grid point and the 0 . 5 Å/grid point resolution . Although we did not explore finer grid resolutions , we do not expect any significant impact on the results to arise from higher resolution grids . The measured conductance characteristics were found to be insensitive to dimensions larger than 115×115 Å in the bilayer plane , and 80 Å in the direction perpendicular to the bilayer ( corresponding to a buffer of ∼15 Å of water on each side of the bilayer patch ) .
|
Protegrins are small peptides with strong antimicrobial properties , believed to kill bacteria primarily by forming nonselective pores in the bacterial membrane . This nonspecific and highly effective mechanism of action has created significant excitement about the use of protegrins as therapeutic antibiotics . However , a lack of understanding of the fundamental processes that lead to pore formation and bacterial death has proven to be a major bottleneck in the rational design of protegrin-based antibiotics . In the present work , we have carried out computational investigations of the diffusion of ions through a protegrin pore . We have thereby provided a connection between previous experimental and simulation work aimed at elucidating the structure of the protegrin pore and earlier experimental work investigating the ion transport characteristics of protegrin pores . The ion diffusion characteristics of protegrin pores are likely to be important in their ability to kill bacteria , as the uncontrolled flow of ions through a bacterial membrane will result in membrane depolarization and the loss of vital membrane functions . The present work thus represents an important first step in modeling and quantifying the timeline of events that lead to the killing of bacteria by protegrins . Furthermore , the computational tools that we have presented herein are easily extendible to similar systems , in particular other antimicrobial peptides .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Methods"
] |
[
"biophysics/theory",
"and",
"simulation",
"computational",
"biology"
] |
2009
|
Poisson-Nernst-Planck Models of Nonequilibrium Ion Electrodiffusion through a Protegrin Transmembrane Pore
|
A four-helix bundle is a well-characterized motif often used as a target for designed pharmaceutical therapeutics and nutritional supplements . Recently , we discovered a new structural complexity within this motif created by a disulphide bridge in the long-chain helical bundle cytokine leptin . When oxidized , leptin contains a disulphide bridge creating a covalent-loop through which part of the polypeptide chain is threaded ( as seen in knotted proteins ) . We explored whether other proteins contain a similar intriguing knot-like structure as in leptin and discovered 11 structurally homologous proteins in the PDB . We call this new helical family class the Pierced Lasso Bundle ( PLB ) and the knot-like threaded structural motif a Pierced Lasso ( PL ) . In the current study , we use structure-based simulation to investigate the threading/folding mechanisms for all the PLBs along with three unthreaded homologs as the covalent loop ( or lasso ) in leptin is important in folding dynamics and activity . We find that the presence of a small covalent loop leads to a mechanism where structural elements slipknot to thread through the covalent loop . Larger loops use a piercing mechanism where the free terminal plugs through the covalent loop . Remarkably , the position of the loop as well as its size influences the native state dynamics , which can impact receptor binding and biological activity . This previously unrecognized complexity of knot-like proteins within the helical bundle family comprises a completely new class within the knot family , and the hidden complexity we unraveled in the PLBs is expected to be found in other protein structures outside the four-helix bundles . The insights gained here provide critical new elements for future investigation of this emerging class of proteins , where function and the energetic landscape can be controlled by hidden topology , and should be take into account in ab initio predictions of newly identified protein targets .
The four-helix bundle is a common motif in nature [1] , [2] , [3] , [4] often used as a target for designed pharmaceutical and nutritional biomolecules [5] , [6] , [7] . The cytokine subfamily is a family of four-helix bundles that are soluble proteins secreted from different organs/tissues . Cytokines act as chemical messengers important in intercellular communication . They regulate differentiation , proliferation , activation and death of many cell types , with particular involvement in the regulation of the circulatory system and production of immunity and inflammatory responses [8] . Most four-helix bundles also have conserved cysteines within the motif , whose disulphide bonds help maintain their structure and stability [2] . Every protein containing a disulphide bridge forms a covalently closed loop . When the N- and C-termini are covalently linked you have the simplest knotted topology in mathematics , termed a “zero knot” [9] . The “zero knot” is present in the cytokine Interleukin-36 [10] , the θ-defensins as well as other lower organism circular proteins as reviewed in [11] ( Figure 1 , top left ) . Nonetheless , a true “zero knot” is rare in the case of proteins . More commonly , the covalent loop creates a “cinch” in the polypeptide chain within the central sequence and the N- and C-terminal ends extend from the internal covalent loop ( Figure 1A , top right ) . Occasionally , either an N- or C-terminal cysteine residue participates in forming the closed loop to generate a “lasso-like” structure ( Figure 1 , bottom left ) . The size of the covalent loop depends on the sequence separation between the two cysteines forming the covalent loop . If the size of the loop is big enough , it is possible for part of the polypeptide chain to thread through and create what we term a Pierced Lasso ( PL , Figure 1 , bottom right ) . Recently , we discovered complexity in leptin's fold created by a single disulphide bond [12] between residue C96 and the C-terminal cysteine ( C146 ) , which creates a lasso as described in Figure 2A . The folding complexity in leptin comes from threading a helical-hairpin through the closed covalent loop in order to reach the native fold [13] , [14] , [15] , [16] to form a PL Bundle ( PLB , Figure 1A ) . This threading is reminiscent of the more common knotted proteins , where a protein terminal must thread across a twisted loop [15] , [16] , [17] . In the case of leptin , the structure is analogous to slipknotted proteins , where part of the protein adopts a hairpin-like configuration that threads across the covalent loop ( Figure 1A ) . A slipknotted polypeptide geometry ( topology ) adds folding complexity that was unrecognized until recently [13] , [14] , [15] , [18] , [19] , [20] , [21] . Since the PL in leptin is distinct from knotted/slipknotted proteins , where the protein backbone ties a knot , and from the cystine knot that is created by at least three disulphide bonds [22] , [23] , [24] , [25] , we called this new motif a Pierced Lasso Bundle ( PLB , Figure 2A ) [12] . This new class of proteins is distinct from previously classified cystine knotted proteins . In the PLB case , a closed covalent loop is created from a single disulphide bridge enclosing one of the terminals with one of the loops where part of the amino acid chain threads through and pierces the covalent loop . In the cystine knotted class , the added complexity beyond a closed loop is created by an additional side-chain mediated chemically cross-linked knot through the covalent loop [28] . PLBs , unlike cystine knots , are able to unfold their threaded elements . Furthermore , unlike knotted/slipknotted proteins , PLBs can modulate their complex topology based on the oxidation conditions of the disulphide bridge . Thus , breaking the bond/contact between the two cysteines also breaks the covalent loop and thereby unthreads the structure . Because of the exciting functional consequences these dynamics may have , we searched for other proteins containing a similar PLB topology . A comprehensive search of the Protein Data Bank ( PDB ) found 11 structures with a similar threaded motif . Leptin has many structurally homologous proteins where disulphide bridges create a covalent loop , but only 11 had a threaded element through the covalent loop . Interestingly , there is a difference between leptin and the other threaded structures in terms of the location of the closed loop . The covalent loop in leptin is located at the C-terminal end while all other structures , found to date , are knotted at the N-terminal end ( Figure 2A and B ) . The threaded structure of leptin influences the Native State Dynamics ( NSD ) and thus the biological activity [12] . Here , we explore the effects of a C- versus N-terminal pierced lasso as well as the folding and the NSD in the related structures . Additionally , we investigate the threading mechanism as the effect ( s ) of loop size . Structure Based Models ( SBMs ) were used to study the human and murine interleukin 3 and two zebra fish interferons ( Figure 2B and C ) . Additionally , we compare the folding mechanism for three of the unthreaded four-helix bundles ( the G-CSF , LIF and hGH , Figure 2B and C ) , which are members of the leptin family of long-chain helical cytokines . The results show that all PLB proteins stabilize the covalent loop as an initial step in folding ( independent of an N- or C-terminal lasso ) . The disulphide bridge helps stabilize the secondary structure formation that builds the base of the lasso . Remarkably , leptin and mIL-3 mainly slipknot structural components through their lassos , whereas the remaining PLBs thread the C-terminal helix through the N-terminal lasso by a so-called plugging mechanism [26] , [27] . We provide , for the first time , direct evidence that the size of the covalent loop influences the threading mechanism . A small loop primarily uses a slipknotting route while the bigger loops are preferentially pierced by a plugging mechanism . In all cases , the N-terminal receptor-binding helix ( helix A ) is the last element to fold . All PLBs found to date , save leptin , have an N-terminal lasso that pins down the canonical helix A via a covalent linkage , while leptin's helix A has freedom to reorient and fray in the C-terminal PLB . This permutation from the more common N-terminal to C-terminal linkage of the PLBs results in an intriguing switch of the receptor binding helix A from tethered to dynamic and suggests that while the functional landscapes are shared in PLBs , variations in protein-receptor interface dynamics may be needed for signaling activity .
Cytokines are soluble proteins secreted from different organs/tissues that act as chemical messengers important in intercellular communication . All cytokines bind to a subset of homologous membrane bound receptors , activating similar intercellular signaling pathways [29] , [30] , [31] . The conserved cytokine motif , a four-helix bundle , indicates that the helical cytokines may have evolved from the same ancestral origin ( Supporting Figure S1 and Supporting Table S1 ) . Despite the structural identities , there are little or no sequence similarities within the family due to co-evolution , where each ligand and its specific receptor have diverged in sequence from its ancestors . Therefore , recognition by commonly used sequence homology methods is not possible [32] . Instead , structural methods are used to classify these four-helix bundles as cytokines . Furthermore , all cytokines share a characteristic up-up-down-down fold , forming a two-layer packing of anti-parallel helix pairs were helix A and D packs against helix C and B . The superfamily of helical cytokines is divided into three families: long-chain helical cytokines , short-chain helical cytokines and interferons/interleukin 10 ( Figure 3 ) [32] . While the overall geometry of the cytokines is conserved , there are differences in structure such as chain length and secondary structural elements ( Supporting Table S1 ) . The PLB protein motif in leptin is a unique fold for proteins in general . A search of the PDB lead to the discovery of an additional 11 proteins with a similar threaded motif . Here , we compare leptin dynamics and threading to four PLBs , two Zebra fish interferons , human ( hIL-3 ) and murine ( mIL-3 ) interleukin 3 ( Supporting Table S1 ) . Additionally , three unthreaded four-helix bundles were investigated as controls , namely Granulocyte colony-stimulating factor ( G-CSF ) , Leukemia inhibitory factor ( LIF ) and human Growth Hormone ( hGH ) . Figure 2 displays the various structures as well as a cartoon describing the position of cysteines ( yellow ) creating the two types of lassos , i . e . the N-terminal loop ( light blue ) and the C-terminal loop ( dark blue ) . The four canonical helices making up the core of each protein are labeled A–D . Additional helices are numbered from the position in sequence; for example , the extra helix in leptin is the fourth helix in sequence and is labeled 4′ . Structure-based simulations were used to investigate the folding mechanism of the PLB proteins . Two different oxidation states were investigated for the disulphide bridge involved in the lasso , i . e . the reduced state ( blue ) and the oxidized sate ( red ) ( details in Section Methods ) . Three unthreaded helical bundles were used as controls and their reduced states ( DD , details in Section Methods ) are plotted in black . Additionally , both the reduced and oxidized state of hGH were plotted as a control for an unthreaded structure , as it has a large “empty” covalent loop , where nothing is threaded through this element . The folding transition is monitored by the fraction of native contacts formed ( Q ) along the folding trajectory . A native contact is a contact formed between two residues that are close in the native state . Q varies from 0 , completely denatured , to 1 , completely native . The folding mechanism is monitored via q ( segment ) , the fraction of native contacts formed by a secondary structure element . q ( segment ) versus Q shows the average number of contacts a segment makes as a function of the overall folding progress , and therefore discerns the average order of events during folding . The results are plotted in Figure 4 and Supplementary Figure S2 , S3 , S4 . The diagonal dashed gray line shows where q ( segment ) is tracking the overall folding progress . The boxes represent the actual positioning of the covalent loop from Figure 2 , where light blue represents the N-terminal loop , dark blue the C-terminal loop and gray the unthreaded structures . The NSD for leptin together with in vitro activity assays revealed that the disulphide-bond plays an important role in controlling receptor binding [40] and thus biological activity by controlling local motions on distal receptor-binding sites far removed from the disulphide-bridge ( Figure 6 ) . These shifts are seen , for example , in helix A as well as in loop four , despite leptin is a C-terminal PLB [12] . To quantify the NSD for the PLBs we performed all-atom structure- based simulations far below the folding temperature , where the protein is effectively always in the folded basin . We calculated the essential dynamics , of the backbone , by projecting the trajectory onto the first four principle components . Oxidation has a significant effect on the amplitude of fluctuation of individual amino acids along the sequence for the PLBs due to topological constraints introduced by the threaded element [41] ( Figure 7 and Supporting Figure S5 ) . These modulations in fluctuations are not limited to the regions in the vicinity of the disulphide . Since the disulphide bridge mobilizes helix A , the dynamics of the N-terminal PLBs show the largest shifts . Both interferons show additional small increased NSD in the reduced state around the helical hairpin ( loop 2 , helix B and C ) , which is part of the closed loop . The interleukins show increased dynamics in both terminals in the reduced state . Indeed , in hIL-3 helix A even unfolds completely up on reduction . Taken together , the NSD data indicate that both the interferons and interleukins are more dynamic in the reduced state . However , leptin is unique in that it introduces increased dynamics in the oxidized state . As a control , we performed NSD for the empty covalent loop homolog protein , hGH . This protein shows no significant changes between the oxidized and reduced protein , with the exception of the expected increased local dynamics in the vicinity of the disulphide bridge upon reduction . Taken together , this data indicates that the observed long-range changes in dynamics in the PLBs are a direct result of the effect of a closed loop in the presence of a threaded element of the polypeptide chain . In the case of leptin , increased dynamics distal to the knot in the oxidized state is likely a consequence of the inability to relax the tension introduced into the vicinity of the small closed loop in the lasso . In the other cases discovered to date , local motions are enhanced by increasing the size of the loop and the expected reduction in dynamics upon disulphide bond formation are observed . That is , the simple formation of the closed loop effects only the local but not the global dynamics in the helical bundles , while the presence of a PL alters the global NSDs in both expected and unexpected ways . Frustrated surface regions have been proposed as sites relevant for allostery [42] . NSD and frustration in proteins have shown to be essential to protein function [43] , [44] . The conserved region for receptor binding within the cytokine family is helix A [45] , [46] , [47] , [48] , [49] , [50] , [51] . The late formation of helix A as well as the fraying of helix A in the reduced state of the PLBs implies that the dynamics is important to receptor binding and activity of the PLBs [12] . As an example , we show the receptor complex of leptin and the changed dynamics between the reduced and oxidized state in Figure 6 . This suggests that the malleability of the substrate and receptor interface has been conserved throughout evolution ( Supporting Figure S1 ) . More importantly , leptin has kept the malleability in helix A by forming its covalent loop at the C-terminal end . Interestingly , comparing the oxidized and reduced NSD data for leptin reveals a altered dynamics of helix A where the oxidized protein of leptin has greater dynamics then the reduced state . In vitro activity assays showed that oxidized leptin is more active than the reduced protein , and supports that a dynamic structure is of importance for biological activity [12] . Nevertheless , all unthreaded helical bundles show reduced dynamic of helix A in general than the PLBs suggesting an overall more rigid structure . Our results suggest that a threaded topology is an important factor designating function . Here we focus on the knot-like four helix bundle class of proteins , however based on the current results we expect that other proteins will have a similar complex topology . We have found a new class of knotted proteins , namely the Pierced Lasso Bundles ( PLBs ) . The PLB topology is defined as a four-helix bundle where a disulphide bridge closes a covalent loop , and part of the polypeptide chain is slipknotted/plugged through this covalent loop . All PLBs discovered , save leptin , have their covalent loop at the N-terminal end and plug the C-terminal helix through the covalent loop . In contrast , leptin mainly slipknots a helical-hairpin through its C-terminal loop . The closed loop also changes the dynamics of helix A which is important for activity and receptor interaction [45] , [46] , [47] , [48] , [49] , [50] , [51] . The NSD reveals that oxidized leptin is more flexible than the reduced state , implying that dynamics in helix A is biologically important for leptin . Interestingly , sequence alignments of leptin homologs reveal that chicken and turkey leptin has three cysteines , one at the C-terminal end , one at position 100 and one at the N-terminal end [52] , [53] , [54] . Additionally , natural genetic polymorphism in bovine leptin has developed a sequence with a single cysteine substitution at the N-terminal end ( R4C ) [52] , [53] , [54] . This actually allows for three different combinations of covalent loops: ( 1 ) Closure of the C-terminal covalent loop , as seen in wild-type leptin , forming a disulphide bridge between residue C96 and C146 . ( 2 ) The formation of an almost completely circularized protein where residue C4 and C146 form a disulphide bridge , creating a “zero knot” . ( 3 ) The formation of an N-terminal covalent loop where residue C4 binds to residue C96 . In the latter case , the C-terminal helix could either slipknot or plug through the closed loop . Future in vitro experiments can distinguish the three states from each other and the effect of a long N-terminal PLB ( 90 residues ) versus the shorter C-terminal PLB as well as investigate fully circularized “zero knot” protein as a template for understanding knot formation and threading control of function in the PLBs ( Figure 1 ) . The folding landscape of these three states of leptin could additionally be studied by traditional mutagenic analyses [55] , [56] , [57] . However , the analysis of the full landscape is complicated by the early threading of the covalent loop that occurs at the level of the transition state . While threading mechanisms have previously been investigated through Fluorescence Resonance Energy Transfer ( FRET ) [58] this is not an optimal technique in the case of leptin as the loop is 50 residues long and big probes could compromise the threading event . On the other hand , leptin is an optimal system for pulling experiments . For example , a major issue in the field is the inability to untie knots with denaturant [59] . In the case of leptin , simply reducing the disulphide bridge unthreads the structure and we are assured that we are comparing the energetics of the fully threaded and fully unthreaded states . Additionally , reversibly knotting proteins with pulling experiments is extremely complicated [60] , while for leptin the experiment is straightforward and can be used to investigate rate of loop threading . Nevertheless , understanding the topological constraints will lead to a broader understanding of the exotic shapes of the free energy landscapes in the growing class of knot-like PLB proteins . Moreover , one should point out that there are probably other undiscovered PL structures deposited in the PDB , where they proteins are bold up of β-strands and/or mixed α/β proteins where the loop is a cinch instead of a lasso . Finally , knowledge about topological constraints in the PLBs could increase the interest of researchers to pharmacologically modulate the pleiotropic hormone leptin [61] and other cytokines , as they have become a hotspot for many medical disorders as cancer , reproduction , diabetes , obesity among others [62] , [63] , [64] , [65] . Taken into account that the PLBs identified here show a different behavior than the unthreaded four-helix bundles suggests that the importance of the threaded element should be considered in modulating receptor ligand interactions for therapeutic development .
In this work we used a Cα SBMs [66] , [67] to investigate the folding of eight helical cytokines , including five PLB proteins ( PDB code 1AX8 , 3PIV , 3PIW , 1JLI and 2L3O ) and three unthreaded four-helix bundles ( 1RHG , 1EMR and 1HGU ) . Each amino acid is represented as a single bead and attractive interactions are given to residue pairs close in the native state . These native interactions are identified based on a shadow map [68] , [69] . The basic Hamiltonian is , Native interactions have a repulsive term plus an attractive Gaussian term . The R ( rij ) Gij ( rij ) term is a correction that anchors the minimum of each contact -ε ( where the last two corresponds respectively to attractive and repulsive non-bonded interactions [70] . denotes the native distance between atoms i and j along the sequence . The local topology of the chain is described by the native angles between the bonds connecting residue pairs ij and jk , and by the native dihedrals or torsional angles between the planes defined by atoms ijk and jkl . The strengths of the interactions are given in reduced energy units by the constants kb = 2×104 ε/nm2 , ka = 40 ε/rad2 , k1d = ε and k2d = 0 . 5ε , where ε is the reduced energy unit . Σ = 4 Å . The details of the model are characterised elsewhere [70] , [71] . We used the web server SMOG ( http://smog-server . org/ ) to create the input files for our simulations [66] , [68] , [69] . The GROMACS 4 . 5 . 3 package was used to perform the molecular dynamics simulations [72] . The integration steps were t = 0 . 005 , stochastic dynamics with coupling constant 2 was used to maintain temperature . The apparent folding temperatures are estimated from each maximum peak in each specific heat curve . For a formed native contact the energy gain is measured by epsilon ( ε ) , and thus the temperatures and energies reported in this paper are measured in units of ε . For sufficient sampling of the transition states some proteins required umbrella sampling along Q as in [73] . Corrected folding mechanisms ( Q versus q ( segment ) ) were then created with the Weighted Histogram Analysis Method ( WHAM ) [74] , [75] . To mimic the experimental conditions/environment for the disulphide bridge building up the covalent loop we used two comparable in silico models , i . e . a reduced state ( blue in all plots ) , an oxidized state ( red in all plots ) . The ability of the disulphide to make and break during folding also was employed to mimic the conditions where folding takes place at the respective reduction potential of the disulphide bridge . This state , the DynamicDisulphide , is best studied in silico where it can be explicitly defined . This state was also simulated for the unthreaded structures ( G-CSF and LIF , black in all plots ) , see Haglund et al for a full description of the states of the disulphide bridge [12] . The hGH was simulated as a control for covalent loop formation , as one of the disulphide bridges ( C53–C163 , forming a so called “cinch” ) forms a large “empty” covalent loop of 112 residues . This loop is classified as “empty” as no part of the polypeptide chain is threaded through the loop . This construct can help show the effects of the threaded element in PLBs . All-atom structure-based simulations [66] , [76] were performed to characterize the NSDs . To investigate the contribution of the threaded topology we performed simulations of both reduced and oxidized states for all PLBs as well as for hGH . A reduced state was simulated for the unthreaded structures ( G-CSF and LIF ) . The slow component of the dynamics described by the first four eigenvector was analysed as described in Haglund et al [12] . Some of the crystal structures have gaps in the sequence . Therefore , the Arch pred server [77] was used to recreate the spaces in the structure of leptin , G-CSF and hGH . Due to problems with aggregation the interleukins are truncated at the N-terminal end [49] , [50] ( Supporting Table S1 ) . Also , most of the proteins do not show complete density for the entire sequence as is stated in Supporting Table S1 . To align all four-helix bundles with leptin we used the PDB tool “Compare Structures” using the comparison method jFATCAT-ridged and jFATCAT-flexible ( http://www . pdb . org/pdb/workbench/workbench . do ) [78] . The sequence alignment tools used to align all sequences to leptin were ALIGN Query ( http://xylian . igh . cnrs . fr/bin/align-guess . cgi , for sequence identity ) and ClustalW multiple sequence alignment ( http://www . ebi . ac . uk/Tools/msa/clustalw2/ , for sequence similarity ) . The results from the structural and sequence alignments are shown in Supporting Table S1 . To find other proteins with a PLB topology we performed geometrical threading on precompiled all verses all input based on the structure of leptin given by jfatcat server . We used a 4 Å rmsd threshold during trace of the fragment matrix . In the second step , we analyzed the discovered structures with P-values lower than 4 . 0E−8 with two conditions: ( 1 ) Four-helix motif ( all possible combination – motif to thread ) . ( 2 ) Distance along sequence for amino acids which form cysteine bridge has to be bigger than 40 amino acids but shorter than 200 . The final set of structures were visually inspected and new motifs were used to repeat the same procedure . Other PL topologies/configurations likely exist; however , they are the subject of future studies as they would reside in a different fold family .
|
We discovered a new class of helical bundle proteins with knot-like structures where part of the polypeptide chain is threaded through a covalently bound loop . We call this unique structural motif a Pierced Lasso Bundle . We discovered 12 structurally homologous proteins in the PDB . Our results indicate that the PLB topology is important for regulating the global native state dynamics , especially for a conserved helix that forms part of the canonical receptor interface surface . As a correctly folded structure is necessary condition for function , we explore kinetic folding data to the active conformation and observe two distinct mechanisms to pierce the lasso on route to the native structure , a slipknotting or a plugging event . Threaded elements predominantly slipknot through small covalent loops ( 50–63 amino acids ) while structural components plug through large covalent loops ( 68–95 amino acids ) . This information is important for protein design as the loop length and threading mechanism affect dynamics important for function and ease of folding a native structure for potential therapeutic uses .
|
[
"Abstract",
"Introduction",
"Results",
"and",
"Discussion",
"Methods"
] |
[
"physics",
"biochemistry",
"developmental",
"biology",
"cytokines",
"proteins",
"protein",
"folding",
"molecular",
"development",
"protein",
"structure",
"biology",
"and",
"life",
"sciences",
"physical",
"sciences",
"computational",
"biology",
"biophysics",
"molecular",
"biology",
"macromolecular",
"structure",
"analysis"
] |
2014
|
Pierced Lasso Bundles Are a New Class of Knot-like Motifs
|
Controlled synthesis of silicon is a major challenge in nanotechnology and material science . Diatoms , the unicellular algae , are an inspiring example of silica biosynthesis , producing complex and delicate nano-structures . This happens in several cell compartments , including cytoplasm and silica deposition vesicle ( SDV ) . Considering the low concentration of silicic acid in oceans , cells have developed silicon transporter proteins ( SIT ) . Moreover , cells change the level of active SITs during one cell cycle , likely as a response to the level of external nutrients and internal deposition rates . Despite this topic being of fundamental interest , the intracellular dynamics of nutrients and cell regulation strategies remain poorly understood . One reason is the difficulties in measurements and manipulation of these mechanisms at such small scales , and even when possible , data often contain large errors . Therefore , using computational techniques seems inevitable . We have constructed a mathematical model for silicon dynamics in the diatom Thalassiosira pseudonana in four compartments: external environment , cytoplasm , SDV and deposited silica . The model builds on mass conservation and Michaelis-Menten kinetics as mass transport equations . In order to find the free parameters of the model from sparse , noisy experimental data , an optimization technique ( global and local search ) , together with enzyme related penalty terms , has been applied . We have connected population-level data to individual-cell-level quantities including the effect of early division of non-synchronized cells . Our model is robust , proven by sensitivity and perturbation analysis , and predicts dynamics of intracellular nutrients and enzymes in different compartments . The model produces different uptake regimes , previously recognized as surge , externally-controlled and internally-controlled uptakes . Finally , we imposed a flux of SITs to the model and compared it with previous classical kinetics . The model introduced can be generalized in order to analyze different biomineralizing organisms and to test different chemical pathways only by switching the system of mass transport equations .
Diatoms are the eukaryotic unicellular organisms , living in marine and fresh water environments . Diatoms are producers in the food chain . They generate around 40% of all organic carbon in the sea [9] . They contribute to the global carbon cycle , by photosynthetic carbon fixation as much as all the terrestrial rain forests do [10] , [11] and therefore , it's likely that they have influenced the global climate over millions of years , by the inward flux of carbon dioxide to the oceans [12] . Moreover , they are major players in the silicon cycle of the oceans [13] . The distinctive feature of diatoms is that they synthesize a wall around themselves , called frustule , made of amorphous silica , which is delicately patterned down to the scale of nanometers . The frustule structure varies between different species of diatoms and also between different growth conditions . [14]–[16] . The precision in controlled mineralization is one of the reasons that they have been attracting increasing interest for a long time , from a material science perspective [14] , [17]–[21] . The oldest diatom fossils have been dated back to 185 Mya [22] . It is suggested that the abundance and ecological success of diatoms can be a result of their silica walls - living in a “glass house” [23] , [24] . Diatom frustules are typically composed of two parts: the valve , which forms the larger outer surface and girdle bands , which are rings of silica being produced during cell growth ( Figure 1A ) . The necessity of silica formation for diatom cells imposes special steps in their cell cycle . Figure 1A depicts the asexual cell cycle of a typical diatom . Before a cell divides , new silica valves for the next generation are formed inside a specialized vesicle , the Silica Deposition Vesicle ( SDV ) [25] , [26] . After this event , daughter cells separate and start growing , which includes the growth in the cell volume and also the silica girdle bands until the cell reaches its largest size . If the amount of silicon in the environment is depleted to almost zero; most cells will be arrested in the G1-phase or G2-M phase , with the G1 arrest point being generally predominant [27]–[29] . This property has been very useful in diatom studies because under silicon starvation condition , cells become mostly synchronized in their cell cycle and therefore , an individual cell can be studied easier with the data from population-level quantities . However , even in the best case usually up to 80% of the cells are synchronized and , therefore , there will be an error in downscaling to a single cell dynamics from macroscopic quantities . Because of the specific cell division form , including one valve growing inside another , in many species of diatoms , one of the daughter cells becomes smaller after each generation . To overcome this problem , after many generations , cells that are smaller than a critical threshold will be regenerated to the original size via sexual reproduction [30] . For some species of diatoms , however , sexual reproduction has never been observed . [31] , [32] . A study on the frustule formation based on fluorescence imaging of the species Thalassiosira pseudonana , suggests that sometimes girdle bands close to the cell center expand and are thus able to accommodate a new valve , which is not smaller than parent's valves [29] . The silica wall architecture is a species-specific characteristic of diatoms , which is an indication that the synthesis of silica is highly genetically controlled , in addition to being chemically and physically controlled . Since the entire genome of some species of diatoms has been sequenced ( Thalassiosira pseudonana: [33] and Phaeodactylum tricornutum: [34] ) , there have recently been greater insights into this genetic control [35] , [36] . Figure 2 is a diagram showing cell control mechanisms . It is believed that such control takes place mainly through two processes . Firstly , via synthesizing and providing special membranes like SDV and secondly , via producing functional biomolecules . The first type of silicification-related biomolecules regulate uptake and transport of silicon and the second type are involved in deposition of silica including proteins and polyamines , which play the role of catalyst or a structure forming scaffold [4] , [5] , [37]–[39] . Our model organism is Thalassiosira pseudonana . Figure 1B and 1C shows a scanning electron microscope ( SEM ) image of this species . In Figure 1B the silica structure of valves , which is specific for this species , and girdle bands , which have a finer and more regular structure , are presented . Figure 1C shows the image of a diatom captured during the last step of cell division . It is clear in this image that the daughter cells already have completed valves before division takes place . Diatoms uptake silicon mostly in the form of neutral orthosilicic acid Si ( OH ) 4 [40] , [41] . The low concentration of silicic acid in present oceans might be the reason for the development of active transportation . Cells synthesize special silicic acid transporter proteins ( SITs ) to act on the membrane for making an inward silicon flux in the cell . The role of SITs has been discussed in several studies [e . g . 42 , 43] . In T . pseudonana three distinct SIT genes have been analyzed for their regulatory mechanisms . It has been shown that SIT protein levels change during a synchronized cell cycle ( up to 50% changes around an average value ) and that the peaks of their profile occur during silica deposition periods of the cell cycle . Moreover , the peaks in mRNA levels happen in S-phase , where the period prior to valve formation shows the highest uptake rate [44] . This causes non-classical enzyme kinetics , which is when the kinetic coefficients are time-dependent in contrast to classical enzyme kinetics when the coefficients are assumed to be constant . In this case , the maximum uptake rate is not constant , but it is a dynamic quantity due to the flux of enzyme production and dynamic enzyme activities [44] . This effect changes the chemical pathways [45] . More interestingly , the SIT3 mRNA level is much lower than SIT1 and SIT2 and also SIT3 is not up-regulated in response to silicon starvation or cell cycle as much [33] , [44] . This suggests that SIT3 might act as a sensor for external silicon concentration [46] . The sensor role of some proteins has been observed in other cells like yeast ( e . g . [47] ) . In that case when the nutrient concentration is lower than a threshold a different type of transporter with a high affinity is produced . This behavior is associated with a dual-transport system , which has been shown in the case of yeast that it prolongs the preparation for starvation and it facilitate the subsequent recovery of cells [47] . After cell uptakes silicon it stores it partly in a soluble silicon pool and then transports it through cytoplasm to reach the SDV , the location of the new synthesizing walls . Currently , the intracellular location of the pool and the mechanisms by which it transports to SDV is not completely understood . Interestingly , if we consider all the intracellular silicon pool in the form of monosilicic acid , considering the small volume of the cell , it should have a concentration higher than the solubility of monosilicic acid , which is around 2mM at pHs below 9 [48] . It has thus been an open question as to how the cell can maintain this concentration without deposition . There are different scenarios for explaining the storage and transport of silicon in the pool . One of these scenarios assumes that the silicic acid binds to some type of organic molecule and thus makes a soluble silicon pool [49] and therefore it turns the silicic acid into another chemical form . This explanation is in agreement with the uptake behavior of diatoms after different starvation conditions [50] . Another scenario assumes the existence of special silicon transport vesicles ( STVs ) , which transport silicic acid from the cell membrane and release their content into SDV by fusing to its membrane [51] , however , the existence of silicon inside such vesicles , to the best of our knowledge , has not been proved . A third scenario shows that oligomerization indeed starts inside the cell as soon as there is some monosilicic acid available in cytoplasm , generating precursors for later deposition inside SDVs . This explanation is based on NMR data from silicon pools ( see the following ) . Recently , the NMR chemical shift technique has been a powerful way for understanding the forms of silicic acid based on their connections to other molecules . With this data it has been shown that the majority of silicon in the entire cell is in a polymerized form [52] . However , this data does not necessarily exclude the possibility that the first explanation could have a role ( because this method cannot distinguish between free monosilicic acid and its attachment to an organic molecule ) , but it shows clearly that intracellular silicon is mostly in the form of oligomers . Finally , after the nutrient ( oligomers of silicic acid and pre-synthesized silica ) is provided for SDV , silica precipitation and pattern formation occurs . In this study , we model silicon uptake , transportation and synthesis in diatoms . We use the nonlinear Michaelis-Menten kinetics for protein activities as mass transport equations . The model is composed of four compartments: external environment , cytoplasm , SDV and deposited silica . In order to find the unknown parameters of our compartmental model , scatter search , ( a global optimization technique ) , has been applied for fitting the model to experimental data on silicon consumption and cell population growth . To add constraints to the model , a penalty term is added to the objective function . Additionally , the optimized solutions have been tested with sensitivity and perturbation analysis . The resulting robust optimized solutions predict silicon dynamics and intracellular biosilicification rates which are in agreement with experimental measurements . With the insight from SITs expression level data , we then impose a flux of proteins during the cell cycle and investigate its effect on silicon uptake rates .
In order to model the distribution and transportation of materials in cells , two computational methods have been commonly used . In the first method , spatial and temporal quantities are both important and a system of PDEs should be solved with some degree of accuracy . However , in many cases , cell processes are not diffusion-limited , meaning that the rate of another event that plays the role of a sink or a source , is slower than diffusion rate and thus diffusion is fast enough to keep the distribution of materials homogenous in the time-scale of interest . To investigate the effect of diffusion on transport of silicon two types of diffusion rates have been calculated . For the detailed calculation see Text S1 from supplementary materials . The first type is diffusion through membrane . Even though the membrane is semi-permeable for monosilicic acid , which is a small , uncharged molecule , the rate of diffusion is much smaller than the observed uptake rate [53]–[56] . Therefore , it seems that active transporters are the most important method for the transport . The second type of diffusion is responsible for distribution of materials close to the membrane in each of its sides . In text S1 we show that diffusion of silicic acid in water is fast enough compared to the rate of uptake , that it will not be a controlling factor ( See Figure S2 in Text S1 ) . The diffusion-mediated Michaelis-Menten equation also shows that the effect of diffusion on the total rate is negligible [45] . This allows us to use compartmental modeling as a good approximation . If cells have several compartments , the chemical and physiological characteristics of inside and outside compartments can differ significantly . This is an efficient mechanism for regulating special events and as expected it requires energy for synthesizing new biomaterials for membranes . In such a process that is not diffusion-limited the second modeling approach , compartmental modeling , is suitable . Compartmental modeling includes a system of ODEs that describes the dynamics of materials inside and its transportation between compartments . There are several reasons that the uptake of silicon , in the form of mono silicic acid , is mostly controlled by enzymatic reactions . For instance , cells use the so-called SIT ( silicon transporters ) genes to produce proteins with active uptake sites and subsequently lower the energy barrier for silicon uptake through membranes . Although in most studies of SITs , the focus is on the SITs on cell membranes , but the expression level and other relevant data usually is derived from the whole cell proteins analysis . Since in diatom cells , there is a specialized compartment for silica synthesis and deposition which is surrounded by a membrane , there is no reason why this membrane shouldn't be equipped with SITs; either in the same form or a similar form . Moreover , the permeability of intracellular membranes to silicic acid is low enough that transporter proteins still are likely the major way of transportation [53] . Our compartmental model includes four compartments ( see Figure 3 ) and we aim to model the temporal changes in amount of silicon ( mol ) , regardless of the form of the silicon compound , inside those four parts . Once silicic acid is inside the cell , it will likely undergo polymerization [52] . The silica polymerization chain of reactions contains many reaction terms , giving rise to a high degree of complexity . Moreover , there is not much known about the oligomer form of silicic acid in diatoms . Therefore , a useful and applicable approach is to consider the total amount of silicon in each compartment and calculate the temporal changes of this quantity . In order to include the deposition of silica in the SDV , we consider deposited amorphous silica as one compartment . Biological molecules , which consist mainly of proteins and long chain polyamines ( LCPAs ) , have a major role in silica polymerization and pattern formation [35]–[39] . The process by which they guide biomineralization is studied to some extent but still not completely understood . Moreover , there are a variety of complex events happening in SDV , including self-aggregation of organic molecules and organic matrix formation , polymerization of silicic acid and formation of oligomers both from monosilicic acid and also from precursors of oligomers , nucleation and phase separation and formation of silica under a controlled condition of concentrations and pH values . Also those events have different time and spatial scales [4]–[6] . It is apparent that the entire process is too complex to study it in a single model . In our model , we present the equilibrium condition of the SDV membrane to be described by a catalytic process . Moreover , we introduce the phase separation event , the transport between the soluble and deposited silica in SDV , as the transport between compartments 3 and 4 . Figure 3 also shows the cell control over level of SITs , which is regulated in response to changes in external concentrations of silicic acid and internal consumption of silicon , as discussed earlier in the introduction . We introduce this control in one of our experiments by adding a flux term to the rate equation of the SITs . In this model the focus is on uptake and transportation of silicic acid through the cell membrane and cytoplasm . This step is vital in providing the material for the silica depositing compartment and , consequently , vital for the cell division .
Using scatter search simulation in the search space of parameter values , the minimum for the objective function has been achieved . The search space that we have used here is listed in table 1 . The approximate values for proteins came from literature , which are mostly based on macroscopic properties of enzyme kinetics . Figure 5 shows the best values for the objective function . The algorithm stops searching when the acceptance criteria is achieved , which is when the algorithm has not found any better solution for a long time and the objective function is close to the optimum value . Since we have considered a weighted objective function for 10 data points ( eq . 13 ) the best meaningful value for objective function is 10 and if the search algorithm arrives at values less than 10 , all of those solutions are acceptable and there is no preference among them , in order to avoid overfitting problem . In the simulation shown here , the objective function is around 15 . So , with the considered search space for parameters , this model is able to closely reproduce the experimental data with a relatively small fitting violation . The solution does not change by repeating the scatter search or by changing the initial point ( results are not shown ) . We also make sure that the model equations hold the conservation law for nutrients and enzymes . Figure 6A shows that the relative error in conservation of silicon is of the order of and Figure 6B shows the relative error of total protein conservation is , both of which show a very good accuracy of the numerical solvers . The problem has several solutions all in the same range of the minimum cost function value . These accepted parameters are shown in a scatter plot of parameters in Figure 7 . To clarify the role of penalty terms , two cases of simulation have been performed , as discussed in previous section . In the first case , no penalty function imposed to the model ( Figure 7A ) and in the second one penalty terms are added to cost function ( Figure 7B ) . From the results it is clear that with no penalty , parameter values are mostly scattered , but applying the penalty , besides and , they mostly form one cluster and are not significantly scattered . This means that in the second case , most parameters are very well identified . Moreover , with the optimized parameters , we return to the forward problem and calculate temporal dynamics of intercellular quantities . Applying an accepted set of parameters , we test the variations in the model variables to make sure there is not a different behavior when changing from one solution to another . Figure 8 shows the concentration dynamics of silicon and enzymes in all cell compartments with and without the penalty term . With no penalty , the dynamics of most variables changes for different set of parameters , however , after applying penalty , although there are some variations in few of the variables , still there is the same dynamics for concentrations , especially concentration of silicon in different compartments . In Figure 9 , experimental values for silicon concentration in the medium together with the model output is shown . The fitting to data , considering experimental error is appropriate . This figure also shows the two curves illustrating the effect of the two terms in eq . ( 5 ) , which was discussed in earlier . We calculated the integral of each term , with a trapezoidal method , to calculate their contribution in silicon consumption . It appears that term 2 in the beginning does not have a significant effect and term 1 has the major role . However , the absolute value of term 2 starts to grow through time and reaches a considerable value . This effect is consistent with the behavior of the diatom cell cycle in a bulk . First , cells are not dividing , but instead up-taking silica with the highest rate in order to build the silica valves for daughter cells . Even though , some cells divide earlier than others , they are only in the beginning of girdle band growth and the uptake rate is not very high and therefore , the first term becomes dominant . By the end of the experiment's duration , the second term has a considerable role , which shows that it has to be included in the calculations of synchronized cell cultures . To this point we concluded to the solution of compartmental dynamics based on our mathematical model . The fact that parameters are mostly not scattered is a good sign . However , if a model is very sensitive to certain parameters , even a small change can possibly affect the dynamics significantly . Therefore , in order to check the robustness of our model , we first performed sensitivity analysis on solutions and then measured the effect more clearly by means of perturbation analysis . Figure 10 shows the normalized sensitivity of observables by changing parameters . Since we have only used the data from medium concentration and deposited silica , we investigate their sensitivity . is most sensitive to parameters and , especially at the end of the experiment where decrease has a smaller slope . shows greatest sensitivity to . To bring an understanding of the amount of change that can be produced by these important parameters , we have again performed perturbation analysis . In Figure 11 the results of parameter perturbation are shown in terms of objective function and temporal dynamics of concentrations . We can see that with a relatively large change in the parameters ( 10% perturbation ) , the behavior of solutions remains the same . For a nonlinear system , this is a reasonable amount of change and it means that our model is robust and stable . Figure 12A shows the silicon content dynamics in different compartments . From the total amount of silicon uptake by cell , the biggest amount becomes in the form of deposited silica , as we desired . However , there is some silicon in cytoplasm or , as it's called , the silicon pool . The concentration of non-deposited ( dissolved ) silicon in SDV ( ) is very low . This makes sense considering very small volume of SDV and also the fact that SDV grows together with silica valves and thus leaving only a small portion of the compartment for non-deposited silicon . As we discussed previously , cells control the uptake and transport of silicon through changing the expression level of SITs . To test the effect of these changes on uptake rates by the cell , we have added a flux term to equations S2–3 and S2–6 for the amount of free enzymes ( SITs ) during time and again solved the inverse problem . We have chosen this flux as a function of time based on changes in protein level from the experiments [44] . The relative change of SITs that we applied to our model is shown in Figure 13 . This function is chosen based on experimental data , but it only shows the behavior of the SITs expression level . The main idea is that during the S-phase , while silicon deposition is minimum , the amount of proteins is also at its minimum . Figure 12B is the result of imposing the protein flux on the silicon amount in different compartments . It shows that even though the total dynamics are more or less the same , but there are some differences . For example , in experimental measurements it seems that silicon deposition happens in a low rate immediately after adding silicon to the starved cells . This might be because of silicon storage in cytoplasm in the beginning [29] . The dynamics in Figure 12B is closer to this behavior than in Figure 12A . An important measure in nutrient uptake is the uptake rate . In Figure 14A we have shown uptake rates versus medium concentration , measured by imposing different initial values for silicic acid concentration in the medium or cell culture ( ) and then the calculating the uptake rates at different time points . The uptake rate-silicic acid concentration curve is a saturated curve as expected . Uptake rates in the first time step , after 2 minutes , are much higher than later uptake rates . This can be a result of the initial condition of the model , zero value of silicon inside the cell , which we assumed based on the fact that cells have been kept in silicon starvation for a long time ( 24 hours ) prior to the measurement . Also this big drop shows the nonlinear nature of the system . This sudden decrease has been seen in experiments on diatoms . It is called surge-uptake . Also experiments suggest that in low concentrations of silicic acid , uptake is almost linear and thus it is referred to as externally controlled ( cells uptake as fast as the diffusion of external nutrient allows them ) . However , in high concentrations of silicic acid , the uptake rate reached its maximum value and , therefore , it is called internally controlled uptake . Interestingly , this model is able to produce all three phases of uptake: ( surge uptake , internally controlled and externally controlled ) , with only the enzyme kinetics and considering cell compartments and without any other assumptions on the presence of different phases of uptake in diatom cells . Figure 14B is the same measure for the case when we applied changes to the total amount of SITs . Compared to 14A , the decrease in uptake rates accrues slower , which is closer to some experimental data of uptake rates in different incubation times [50] . Moreover , the uptake rate increases again at the time of starting valve formation , when the cell needs a high amount of silicon .
Studying intracellular processes is a difficult task , largely because of the difficulties of in-vivo measurements at such small scales . As a consequence of this , the modeling approach is a good candidate for understanding the different mechanisms and temporal behavior , such as nutrient uptake and transportation of materials . We have introduced a multi-compartmental model for silicon transport and synthesis in diatoms . This is the first nonlinear compartmental model designed for this purpose . The model uses experimental population-level ( macroscopic ) data and therefore an accurate equation for the connection of macroscopic data to sub-cellular data has been derived . This equation accounts for the effect of a portion of cells that are not synchronized in the cell culture . To estimate the free parameters of the model , we have solved the inverse problem of parameter estimation , which includes the constraints related to enzyme kinetics via the penalty method . The use of constraints together with sensitivity and perturbation analysis makes it possible to infer the sub-cellular dynamics even with sparse and noisy data . Taking into account the amount of silicon ( mol ) in the model in order to simplify different polymerization and other reactions in cells , the model is still able to produce the transport and the dynamics of nutrients with a good agreement to experimentally obtained evidence . For example , the equations of the model can generate different regimes of uptake , namely: surge , externally-controlled and internally-controlled . This model constitutes a framework by which to study cell compartments and to infer dynamics based on the known facts and data . More importantly , it brings with it the ability to manipulate cell processes such as uptake rates and protein regulation , which are normally difficult to manipulate experimentally . As an example , we have imposed changes in the total amount of SITs through time; a mechanism for cells to control the uptake and transport of materials . We have observed that applying a protein flux results in more realistic silicon dynamics and uptake rates , and can postpone the start of silica deposition in favor of silicon storage in the silicon pool . The model presented here can be generalized to other chemical pathways by changing only the system of ODEs , which lie at the core of the model , and then applying the same procedure . One interesting area in this framework would be to introduce changes in the expression level of enzymes during time as a function of the internal and external changes , and try to connect the cell cycle and silicon cycle of diatoms together . Another interesting addition to this type of model would be to consider the statistical distribution of individual cells' dynamics in the culture , which will introduce more complexities . This can be achieved by applying individual-based modeling , or with an ensemble based modeling to fulfill the role of cells in different phases .
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Understanding complex biological systems , especially at intracellular scales , has always been a big challenge , owing to the difficulties in measuring and manipulating such small quantities . Computational modeling brings promising possibilities to this area . The model organism we have studied here is the diatom , a single cellular silicifying organism . Diatoms live in most water habitats and they use the very low concentrations of silicon in the oceans to develop beautifully complex silica structures . The cell control strategies acting on this process have been a long-standing open question . In this work , we have modeled the silicon uptake , transport and synthesis in diatoms in different cell compartments . To find the best set of free parameters of the model we solved the inverse problem using parameter identifiability , global optimization , sensitivity and perturbation techniques . The resulting model is a framework for manipulating and testing different properties of cells; for example , we have tested the cell control on silicon uptake by changing the expression level of the transporter proteins . Such modeling , described in this work , is both a necessary and important tool for understanding the cell strategies over control of material transport and synthesis .
|
[
"Abstract",
"Introduction",
"Materials",
"and",
"Methods",
"Results",
"Discussion"
] |
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"systems",
"biology",
"biochemistry",
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"physiological",
"processes",
"biomineralization",
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2014
|
Understanding the Sub-Cellular Dynamics of Silicon Transportation and Synthesis in Diatoms Using Population-Level Data and Computational Optimization
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SARS coronavirus ( SCoV ) nonstructural protein ( nsp ) 1 , a potent inhibitor of host gene expression , possesses a unique mode of action: it binds to 40S ribosomes to inactivate their translation functions and induces host mRNA degradation . Our previous study demonstrated that nsp1 induces RNA modification near the 5′-end of a reporter mRNA having a short 5′ untranslated region and RNA cleavage in the encephalomyocarditis virus internal ribosome entry site ( IRES ) region of a dicistronic RNA template , but not in those IRES elements from hepatitis C or cricket paralysis viruses . By using primarily cell-free , in vitro translation systems , the present study revealed that the nsp1 induced endonucleolytic RNA cleavage mainly near the 5′ untranslated region of capped mRNA templates . Experiments using dicistronic mRNAs carrying different IRESes showed that nsp1 induced endonucleolytic RNA cleavage within the ribosome loading region of type I and type II picornavirus IRES elements , but not that of classical swine fever virus IRES , which is characterized as a hepatitis C virus-like IRES . The nsp1-induced RNA cleavage of template mRNAs exhibited no apparent preference for a specific nucleotide sequence at the RNA cleavage sites . Remarkably , SCoV mRNAs , which have a 5′ cap structure and 3′ poly A tail like those of typical host mRNAs , were not susceptible to nsp1-mediated RNA cleavage and importantly , the presence of the 5′-end leader sequence protected the SCoV mRNAs from nsp1-induced endonucleolytic RNA cleavage . The escape of viral mRNAs from nsp1-induced RNA cleavage may be an important strategy by which the virus circumvents the action of nsp1 leading to the efficient accumulation of viral mRNAs and viral proteins during infection .
Severe acute respiratory syndrome ( SARS ) coronavirus ( SCoV ) is the causative agent of SARS , which was first recognized in southern China in 2002 and spread to different areas of the world in a 2002-2003 epidemic [1]-[3] . It is believed that the bat-derived SCoV-like CoV [4] , [5] underwent several mutations enabling the virus to cross the species barrier and replicate efficiently in humans [6] . Although it is uncertain whether SCoV-like CoV will re-emerge in the human community and initiate another SARS epidemic , the previous SARS outbreak made it apparent that CoVs , which usually cause only mild or moderate self-limiting symptoms in healthy humans , can cause a severe epidemic disease in our communities . SCoV , which belongs to the betaCoV genus among the alpha , beta and gammaCoV genera in the family Coronaviridae , is an enveloped RNA virus carrying a long ( ∼30 kb ) , single-stranded , positive-sense genomic RNA . The 5′-proximal ∼22 kb-long gene 1 region of SCoV genomic RNA has two partially overlapping open reading frames ( ORFs ) 1a and 1b ( Figure 1 ) . Immediately after infection , the genomic RNA is translated to produce two large polyproteins; one is from ORF1a and the other from ORF1a and 1b via a ribosomal frame-shift mechanism [6] , [7] . These two polyproteins are processed by two viral proteinases to generate 16 mature proteins , nsp1-nsp16 ( Figure 1 ) . Most of the gene 1 proteins are involved in viral RNA synthesis [8]-[16] , while some have other biological functions [17]-[21] . To carry out viral gene expression , nine species of virus-specific mRNAs , including mRNA1 , which is the intracellular form of genomic RNA , and eight species of subgenomic mRNAs , i . e . , mRNA 2-mRNA 9 , are produced in infected cells . These viral mRNAs make up a 3′-co-terminal , nested-set structure and accumulate in different quantities . Located at the 5′-end of all of these intracellular viral mRNAs and genomic RNAs is a ∼70 nt-long identical leader sequence . SCoV nsp1 protein , which is the most N-terminal product of the gene 1 polyproteins , suppresses host gene expression in expressed cells and in infected cells [19] , [22] . Nsp1 prevents type I interferon production in infected cells [23] , and the expressed nsp1 suppresses the host antiviral signaling pathways [24] . Furthermore , the nsp1 of a closely related mouse hepatitis virus suppresses host gene expression , interferes with the type I interferon system , and is a virulence factor [25] . These data led us to suggest that SCoV nsp1 plays important roles in SARS pathogenesis . SCoV nsp1 suppresses host gene expression by using a novel , two-pronged strategy [19] , [22] . Nsp1 binds to 40S ribosomes , leading to the inhibition of host protein synthesis . Ribosome-bound nsp1 further induces RNA modification of a capped mRNA , rendering it translationally incompetent [22] . Nsp1 protein promotes host mRNA degradation both in transiently transfected cells expressing nsp1 and in infected cells [19] , [22] , [23] , [26]; cellular RNA decay functions most likely influence the efficient degradation of host mRNAs that undergo the nsp1-induced modification . The nsp1-induced RNA modification is template-dependent . Incubation of nsp1 in rabbit reticulocyte lysate ( RRL ) with a dicistronic RNA transcript harboring the encephalomyocarditis virus ( EMCV ) internal ribosome entry site ( IRES ) between two reporter genes results in RNA cleavage near the 3′-region of the EMCV IRES element , whereas nsp1 does not induce RNA cleavage in the IRES region of dicistronic RNA transcripts containing either the hepatitis C virus ( HCV ) IRES or the cricket paralysis virus ( CrPV ) IRES [22] . The molecular basis for the nsp1-mediated selective endonucleolytic RNA cleavage among these IRESes is unclear . Incubation of capped and polyadenylated reporter mRNA encoding the Renilla luciferase ( rluc ) gene with nsp1 in RRL and subsequent primer extension analysis of the reporter mRNA showed that the nsp1 induces several premature primer extension termination signals near the 5′-end of the mRNA [22] . Neither the nature of the nsp1-induced modification of capped mRNA nor the mechanism of the RNA modification site selection is known . Also unknown is the effect of nsp1 on SCoV mRNAs . Similar amounts of virus-specific mRNAs are detected in SCoV-infected cells and in cells infected with a SCoV mutant , SCoV-mt , which encodes the nsp1-mt protein carrying K164A and H165A mutations [23] . This mutated form of nsp1 neither binds to 40S ribosome subunits [22] nor promotes mRNA degradation [23] , which suggests that SCoV mRNAs may escape from the nsp1-induced mRNA modification . The present study was undertaken to clarify the nature of the nsp1-induced modification in capped mRNAs , explore the basis of the RNA modification site selection , characterize the template-dependent properties of the nsp1-induced RNA modification , and examine the effect ( s ) of nsp1 on the integrity of SCoV mRNAs primarily by using cell-free in vitro assays . Our data demonstrate that endonucleolytic RNA cleavage was the nature of the nsp1-induced modification of RNA templates , and RNAs carrying selective groups of IRESes were susceptible to the nsp1-induced RNA cleavage . The contribution of RNA secondary structures of template mRNAs for the selection of the RNA cleavage sites is also suggested . Finally , we discovered that SCoV mRNAs were resistant to the nsp1-induced RNA modification , a finding suggesting that SCoV has developed a strategy to selectively protect its own mRNAs from nsp1-induced RNA modifications to ensure efficient viral gene expression during infection .
SCoV nsp1 induces endonucleolytic RNA cleavage near the 3′-region of the EMCV IRES of dicistronic RNA transcripts , Ren-EMCV-FF , in which expression of the upstream rluc ORF is mediated by cap-dependent translation and the translation of downstream firefly luciferase ( fluc ) ORF is driven by the EMCV IRES in both RRL [22] and cultured cells [27] . In contrast , SCoV nsp1 does not induce RNA cleavage in similar dicistronic RNA transcripts carrying the HCV IRES or the CrPV IRES between rluc and fluc genes in RRL [22] . EMCV , HCV and CrPV belong to the picornavirus family , flavivirus family and dicistrovirus family , respectively . Although currently divided into four distinct categories [28] , picornavirus IRES elements were originally grouped into type I and type II IRESes based on their primary sequence and secondary structure similarities [29] . IRES elements within the same IRES group display a high homology in RNA secondary structures , but only modest similarity in their primary sequences , while IRESes from different groups have distinct RNA secondary structures . Picornavirus type I IRESes include IRESes derived from poliovirus , coxsackie B virus ( CVB ) and human rhinovirus ( HRV ) , while picornavirus type II IRESes include those derived from EMCV and Theiler's murine encephalomyelitis ( TMEV ) . Because HCV , CrPV and picornavirus type I and type II IRESes are distinct in terms of their primary sequences , secondary structures and requirements for translation initiation factors ( for review refer to [30]-[32] ) , testing the susceptibilities of these IRESes to nsp1-induced endonucleolytic RNA cleavage would provide a clue towards understanding the role of RNA secondary structures and host translation initiation factors in the nsp1-induced RNA cleavage . To determine the molecular basis for the nsp1-induced , template-dependent endonucleolytic RNA cleavage , we tested whether nsp1 induced RNA cleavage in the IRES region of a series of dicistronic RNA transcripts , each containing an IRES derived from different picornaviruses , including TMEV ( Ren-TMEV-FF ) , poliovirus ( Ren-PV-FF ) , CVB ( Ren-CVB-FF ) , and HRV 2 ( Ren-HRV2-FF ) or a flavivirus , classical swine fever virus ( CSFV ) ( Ren-CSFV-FF ) ; the latter IRES has an HCV-like IRES structure . In all transcripts , expression of the upstream rluc ORF was mediated by cap-dependent translation and the translation of downstream fluc ORF driven by the IRES . The Ren-TMEV-FF or Ren-CSFV-FF transcripts were incubated in RRL with a recombinant nsp1 protein , which was initially expressed as glutathione S-transferase ( GST ) -nsp1 fusion protein in E . coli . The GST tag was subsequently eliminated [19] . For analysis of Ren-PV-FF , Ren-CVB-FF and Ren-HRV2-FF transcripts , RRL containing 20% ( vol/vol ) HeLa S10 extract [33] ( RRL+HeLa ) was used; translation activities of these picornavirus-derived IRESes require host factors that are missing or exist in low abundance in RRL [34]-[36] . Thus , RRL+HeLa is used for translation mediated by these IRESes [37] . As controls , the RNA was left untreated or incubated with a non-specific control protein , GST or a mutated form of nsp1 , nsp1-mt with K164A and H165A mutations [23] . Nsp1-mt does not bind to 40S ribosomes and lacks the translational suppression and template RNA modification activities [19] , [23] . After incubation , RNAs were extracted and subjected to Northern blot analysis by using an rluc probe hybridizing to the rluc ORF and a fluc probe hybridizing to the fluc ORF ( Figure 2 and Figure S1 ) . To estimate the RNA cleavage sites , we included three RNA size markers for each template RNA; they were an untreated template ( full length ) , RNA 1 containing the region from the 5′-end to the 3′-end of the inter-cistronic region of the template , and RNA 2 containing the region from the 5′-end to the end of the rluc ORF of the template ( Figure 2A ) . As expected , incubation of all RNA transcripts with GST or nsp1-mt did not induce RNA cleavage ( marked as GST and nsp1 mt in Figure 2 and Figure S1 ) . Incubation of Ren-TMEV-FF with nsp1 resulted in reduction of full-length transcript abundance and generation of two major RNA fragments ( Figure 2B ) . The size of the 5′-fragment , which was detected by the rluc probe , indicated that nsp1 induced an endonucleolytic cleavage near the 3′-end of TMEV IRES . All RNA transcripts carrying picornavirus type I IRES , including Ren-PV-FF , Ren-CVB-FF and Ren-HRV2-FF , underwent the nsp1-induced RNA cleavage ( Figure 2C , Figures S1B and S1C ) . Ren-PV-FF preparations contained an unexpected RNA band , which was detected by the rluc probe and was slightly smaller than the RNA 1 marker ( denoted by the asterisk in Figure 2C ) , leading us to suggest that this RNA was generated by premature transcriptional termination near the 3′ end of the poliovirus IRES . The 5′ fragment of dicistronic transcripts carrying picornavirus type II IRES and the RNA 1 markers showed a similar migration in the gel ( Figure 2B ) [22] , whereas the corresponding RNA fragment of dicistronic transcripts carrying a picornavirus type I IRES migrated slightly faster than did the RNA 1 markers in the gels; the size difference between the 5′ fragment of Ren-HRV2-FF and the RNA 1 maker was less prominent than those between the 5′ fragment of Ren-PV-FF or Ren-CVB-FF and their RNA 1 makers ( Figure 2 and Figures S1B and S1C ) . In contrast to dicistronic transcripts carrying picornavirus type I IRES or type II IRES , nsp1 did not induce RNA cleavage in Ren-CSFV-FF ( Figure 2D ) . We previously reported that co-transfection of a plasmid encoding nsp1 and one that encoded dicistronic RNA transcripts carrying the EMCV IRES resulted in RNA cleavage of the expressed dicistronic RNA transcripts , demonstrating that expressed nsp1 exerts RNA cleavage in cultured cells [27] . The finding of RNA cleavage following co-expression in cultured cells of nsp1 , but not nsp1-mt or chloramphenicol acetyltransferase ( CAT ) , with dicistronic RNA transcripts carrying the TMEV IRES or poliovirus IRES , but not those carrying the HCV IRES or CSFV IRES , ( Figure S2 ) demonstrated that expressed nsp1 exerted template-dependent endonucleolytic RNA cleavage . In addition , nsp1 expression reduced the abundances of the full-length RNAs of all of the expressed RNA transcripts . Because the nsp1 induces modification at the 5′ region of the capped RNA transcripts in RRL [22] , we suspect that expressed RNAs most likely underwent nsp1-induced modification near the 5′ end and were degraded by host mRNA decay functions , resulting in the reduction of the abundance of the expressed RNA transcripts in nsp1-expressing cells . In summary , nsp1 induced endonucleolytic RNA cleavage in RNA transcripts carrying the IRESes of picornaviruses , but not in those carrying CSFV IRES , both in vitro and in vivo . We next determined the nsp1-induced RNA cleavage sites in Ren-EMCV-FF and Ren-PV-FF RNA . We took advantage of the fact that the RNA structure as well as the structural and functional relationships of the EMCV IRES and the poliovirus IRES are well characterized [38] , [39] . Ren-EMCV-FF that had been incubated with GST , nsp1 or nsp1-mt in RRL was subjected to primer extension analysis using the 5′-end labeled primer that binds at a site ∼100 nt downstream of the fluc gene initiation codon . Three strong ( sites 3 , 7 and 11 ) and several minor primer extension termination signals were detected in the sample that was incubated with nsp1 , but not with GST or nsp1-mt ( Figure 3A ) . Site 3 was located 3-nt downstream of the translation initiation AUG ( AUG-834 ) of the EMCV IRES ( underlined AUG in Figure 3C ) , while sites 7 and 11 were located within the 5′ region of the fluc ORF . Two minor primer extension termination sites 1 and 2 existed upstream of AUG-834 and other minor sites were detected between AUG-834 and site 11 . Previous studies reported the possibility that the 43S pre-initiation complex , which is made up with 40S ribosome , eIF1 , eIF1A , ternary complex ( eIF2 , Met-tRNA , and GTP ) , and eIF3 , loads onto the EMCV IRES at or near the AUG-834 [40] , [41] . Hence , our data may indicate that nsp1 induced several endonucleolytic RNA cleavages at or in the proximity of the ribosome loading site of the EMCV IRES of Ren-EMCV-FF . Northern blot analysis indicated that the nsp1 induced the RNA cleavage roughly 100-200 nt upstream of the initiation codon of the downstream fluc ORF of Ren-PV-FF ( Figure 2C ) ; hence , for primer extension analysis of Ren-PV-FF we used a primer that binds at a site 6 nt downstream of the translation initiation codon of the fluc ORF . Primer extension analysis of Ren-PV-FF that had been incubated with nsp1 , but not with GST or nsp1-mt , in RRL+HeLa revealed three major extension termination signals , namely sites 1 , 2 and 8 , near an AUG ( AUG-586 ) , which corresponds to the AUG at 586 nt of the poliovirus genome , located within the poliovirus IRES domain VI ( Figures 3B and 3D ) . All three major sites 1 , 2 and 8 , and a minor site 7 were located in close proximity within the computer-predicted secondary structure of poliovirus IRES domain VI ( Figure 3D ) . Other minor primer extension termination sites were located downstream of AUG-586 , which is considered to be a part of ribosome binding site within poliovirus IRES . It should be noted that AUG-586 is not used for viral translation initiation [42]; viral translation initiates from another AUG triplet ( AUG-743 ) located ∼150 nt downstream of this silent AUG-586 by ribosome shunting or scanning mechanisms [42]-[44] . In the Ren-PV-FF transcripts , AUG-743 served as the translation initiation codon for the fluc gene . Judging from the migration of the 5′ RNA cleavage product of the Ren-PV-FF relative to marker RNA 1 , which is an RNA fragment corresponding to the 5′-end of Ren-PV-FF to 30-nt downstream of AUG-743 ( Figure 2C ) , the size of the 5′ RNA fragment of Ren-PV-FF and the major RNA cleavage sites 1 , 2 and 8 in Ren-PV-FF were in good agreement . We did not detect major primer extension termination products near AUG-743 following the use of another primer that binds ∼100 nt downstream of the AUG-743 ( data not shown ) . These data strongly suggested that nsp1 induced RNA cleavage at or near the 40S ribosome loading site within poliovirus IRES of Ren-PV-FF . Our previous studies used rluc RNA , which is a capped and polyadenylated mRNA encoding the rluc gene , as a model mRNA template for characterizing the nsp1-induced capped mRNA modification [22] . Incubation of rluc RNA with nsp1 in RRL generated several premature primer extension termination products indicative of cleavage near the 5′-end of rluc RNA , and the modified rluc RNA became translationally inactive [22] . The nature of the nsp1-induced modification , which causes primer extension terminations , in the rluc RNA is unknown . The rluc RNA has a short , 5′ untranslated region ( UTR ) of only 11 nt , which is atypical for most host mRNAs which have 5′ UTRs ranging from 20-100 nt in length [45] . Rabbit globin mRNA having a 53 nt-long 5′ UTR and β-actin mRNA carrying an 84 nt-long 5′ UTR are two of the host mRNAs widely utilized in molecular biology studies [46]-[50] . Thus , we used two in vitro-synthesized capped and polyadenylated mRNAs encoding the rluc gene which carried the 5′ UTR of human β-actin mRNA or that of rabbit β-globin mRNA to characterize nsp1-mediated RNA modification of capped , monocistronic mRNAs . Incubation of ALA mRNA ( containing the β-actin 5′ UTR ) or GLA mRNA ( containing the rabbit β-globin 5′ UTR ) with nsp1 , but not GST or nsp1-mt , in RRL resulted in the efficient suppression of rluc protein expression ( Figures 4A and 5A ) . Primer extension analysis of ALA mRNA , which was extracted from RRL after incubation with nsp1 , but not with GST or nsp1-mt , showed two main premature primer extension termination products at nucleotides 29 ( site 3 ) and 39 ( site 4 ) ( Figure 4B , indicated by asterisks ) and several minor premature primer extension termination signals ( Figure 4B , arrows ) . Incubation of GLA mRNA with nsp1 , but not GST or nsp1-mt , resulted in a major premature primer extension termination product at nucleotide 17 ( site 4 ) and several additional minor premature primer-extension termination sites ( Figure 5B , arrows ) . The computer-assisted modeling of secondary structure [51] of the 5′ UTR of ALA mRNA showed a proximal location of sites 3 and 4 in a stem region of a stem-loop structure ( Figure 4D ) . Likewise , a major RNA modification site 4 and a minor RNA modification site 5 of GLA mRNA were detected in close proximity to one another within a stem region of a predicted stem-loop structure ( Figure 5D ) . To confirm that nsp1 also induces RNA modification in naturally occurring host mRNAs , rabbit β-globin mRNA obtained from RRL was incubated with GST , nsp1 or nsp1-mt in RRL , and the extracted RNA was subjected to primer extension analysis . A major premature extension termination site and ∼8 minor products were detected in the sample incubated with nsp1 , but not nsp1-mt or GST ( Figure 6 ) . All three RNA modification sites within the 5′ UTRs of β-globin mRNA were also detected at the corresponding sites of the nsp1-treated GLA mRNA , whereas the most 5′-end minor modification sites 1-3 of GLA mRNA ( Figures 5B and 5C ) were barely detected in β-globin mRNA . The amount of the full-length primer extension product of the nsp1-treated β-globin mRNA was very low ( Figure 6 ) , which indicated that there was efficient nsp1-induced RNA modification in the naturally occurring β-globin mRNA . To further clarify the nature of the nsp1-induced RNA modification of the capped mRNAs , 32P cap-labeled ALA mRNA , extracted after incubation with GST , nsp1 or nsp1-mt in RRL , was subjected to electrophoresis in a 10% polyacrylamide/8M urea sequencing gel . A major ∼29 nt RNA product was detected in the sample incubated with nsp1 , but not with GST or nsp1-mt ( Figure 7 ) , which showed that nsp1 induced an endonucleolytic RNA cleavage in ALA mRNA . Notably , this endonucleolytic RNA cleavage product appeared to correspond to a major primer extension termination site 3 ( Figure 4 ) . Experiments using Ren-EMCV-FF , Ren-PV-FF , GLA mRNA , β-globin mRNA , or ALA mRNA collectively showed that the nsp1 induced endonucleolytic RNA cleavages adjacent to any of the four nucleotides and between different di-nucleotide pairs , which may imply there is little or no preference for specific nucleotides at the RNA cleavage site . Computer-assisted RNA secondary structure analysis implicated a main RNA cleavage and another RNA cleavage occurring at highly proximal positions within stem-loop structures in the 5′ noncoding region of ALA , β-globin and GLA mRNAs and the 3′-region of the poliovirus IRES of Ren-PV-IRES transcripts . To clarify the importance of the di-nucleotide sequence around the cleavage site for the nsp1-induced RNA cleavage , we examined the nsp1-induced endonucleolytic RNA cleavage sites in a mutated GLA mRNA mt 1 , which had the same predicted RNA secondary structure as that of GLA mRNA at the 5′ noncoding region and carried two nucleotide substitutions from C17A18 to G17U18 at the major cleavage site and another two nucleotide substitutions from U25G26 to A25C26; the latter two nucleotide substitutions were necessary to retain the predicted RNA secondary structure ( refer to Figure 8C ) . Primer extension analysis showed that nsp1 induced a major endonucleolytic RNA cleavage at nucleotides 18 and 26 of GLA mt 1 ( Figure 8A ) , supporting the notion that there is little or no requirement for a specific nucleotide sequence at the RNA cleavage site for nsp1-induced RNA cleavage . Unlike GLA mRNA , GLA mRNA mt 1 had an additional cleavage site at nucleotide 9 ( Figure 8A ) . Incubation of nsp1 with GLA mRNA mt 2 ( carrying only a C17A18 to G17U18 change at the major cleavage site and having an altered predicted RNA secondary structure ) in RRL resulted in major and minor cleavages at nucleotides 9 and 16 , respectively ( Figure 8B ) . These data led us to conclude that the nsp1-induced endonucleolytic RNA cleavage of the template mRNAs displayed no apparent nucleotide preference at the RNA cleavage site , while altering the RNA secondary structure affected the pattern of cleavage . Efficient viral gene expression occurs in SCoV-infected cells in spite of the nsp1-mediated host gene expression suppression [52] . Furthermore , cells infected with SCoV and those infected with SCoV-mt , a SCoV mutant encoding nsp1-mt , accumulated similar amounts of SCoV mRNAs [23] . These data led us to hypothesize that viral mRNAs are resistant to the nsp1-induced endonucleolytic RNA cleavage . To test this hypothesis , poly ( A ) containing intracellular RNAs were purified from SCoV-infected cells and incubated with GST , nsp1 , or nsp1-mt in RRL . The RNAs were then extracted and subjected to primer extension analysis by using a 5′-end labeled primer that binds to a region ∼120 nt from the 5′-end of SCoV mRNA 9 , the smallest and most abundant viral mRNA encoding the N protein . Due to the 3′ co-terminal nested structure of coronavirus mRNAs , it was predicted that this primer should bind to all 9 different SCoV mRNAs and generate primer extension products from all viral mRNAs . The expected sizes of the full-length primer extension products of viral mRNA 1 to mRNA 8 would exceed 300 nt , and our primer extension conditions were not suitable for precisely detecting potential nsp1-induced endonucleolytic RNA cleavage sites in these viral mRNAs . Hence , we examined whether nsp1 induced endonucleolytic RNA cleavage in mRNA 9 , for which the expected length of full-length cDNA product was ∼120 nt . Remarkably , we did not detect primer extension premature termination signals that were specific for the sample incubated with nsp1 ( Figure 9A ) . Furthermore , the amount of the full-length cDNA product of mRNA 9 was similar among these three samples . These data demonstrated that SCoV mRNA 9 was not susceptible to nsp1-mediated endonucleolytic RNA cleavage . To exclude an unlikely possibility that nsp1 exerts modification at the 5′-region of SCoV mRNAs in infected cells and cannot further modify viral mRNAs in RRL , we repeated the experiments by using mRNAs from cells infected with SCoV-mt . SCoV-mt encodes nsp1-mt [23] that does not induce modification of non-viral mRNAs [22] , [23] , and thus host and viral mRNAs in SCoV-mt-infected cells should not undergo the nsp1-induced endonucleolytic RNA cleavage . If SCoV mRNAs do not undergo the nsp1-induced endonucleolytic RNA cleavage in infected cells , then SCoV mRNA 9 and SCoV-mt mRNA 9 should have the same RNA sequence and structure . In the absence of nsp1 , the size of the full-length primer extension product of SCoV-mt mRNA 9 and that of SCoV mRNA 9 was the same ( Figure 9B ) . Similar to the results observed when SCoV mRNA 9 was unaffected in the presence of nsp1 , incubation of SCoV-mt mRNA 9 with nsp1 did not generate premature primer extension termination signals . These data excluded the possibility that nsp1 induces endonucleolytic RNA cleavage near the 5′-region of SCoV mRNAs in infected cells and further support the conclusion that SCoV mRNA 9 is resistant to nsp1-mediated endonucleolytic RNA cleavage . We also performed primer extension analysis of mRNA 3 from SCoV-infected cells by using a primer that binds to a region about 150 nt from the 5′-end of mRNA 3 ( Figure 9C ) . The nsp1-treated sample showed neither a reduced amount of the full-length cDNA product nor specific premature primer extension termination products , demonstrating that nsp1 did not induce endonucleolytic RNA cleavage in SCoV mRNA 3 . To identify the RNA element ( s ) in SCoV mRNAs that protects the viral mRNAs from the nsp1-induced endonucleolytic RNA cleavage , we prepared five different SCoV mRNA 9-like RNAs ( Figure 10A ) . m9LN3 RNA has the following elements: a 5′-end cap structure , the authentic 5′ UTR of SCoV mRNA 9 , carrying the common 72 nt-long leader sequence found in all SCoV mRNAs and an additional 8 nt sequence , the N gene ORF , the 3′ UTR , and a 20-nt long poly ( A ) sequence; naturally occurring SCoV mRNA 9 and m9LN3 are nearly identical in sequence , except that the coronavirus mRNAs have a longer 3′ poly ( A ) tail [53] . m9LN lacks the 3′ UTR and the 20 nt poly ( A ) sequence of m9LN3 , while m9N3 lacks the 5′-end leader sequence of m9LN3 . In m9Lrluc3 , an rluc gene ORF is inserted in the place of the N gene ORF in m9LN3 . In m9Lactin3 , the 5′ UTR of actin mRNA is replaced with the 5′ UTR of SCoV mRNA 9; in vitro-synthesized actin mRNA served as a control . These RNAs were incubated with GST , nsp1 or nsp1-mt in RRL and subjected to primer extension analysis ( Figures 10B-10F ) . Similar levels of the full-length primer extension products of expected sizes were detected in the m9LN3 , m9LN , m9Lrluc3 , and m9Lactin3 samples incubated with nsp1 , GST or nsp1-mt ( Figures 10B , 10C , 10E and 10F ) . We also did not detect any premature primer extension products in the nsp1-incubated samples . In contrast , incubation of m9N3 RNA with nsp1 resulted in the generation of two major premature primer extension products and a reduction in the levels of the full-length primer extension product ( Figure 10D ) . As expected , nsp1 induced the endonucleolytic RNA cleavage in actin mRNA ( Figure S3 ) . These data showed that the presence of the leader sequence protected the viral mRNAs from the nsp1-induced endonucleolytic RNA cleavage . Next , we tested the importance of the 5′-terminal sequence of the SCoV leader in protecting viral mRNAs from the nsp1-induced endonucleolytic RNA cleavage . To this end , we generated two SCoV mRNA 9-derived mutants , SCoV mRNA 9 mt 1 and SCoV mRNA 9 mt 2 . SCoV mRNA 9 mt 1 has an additional G at the 5′-end and SCoV mRNA 9 mt 2 carries a U to G mutation in the second nucleotide from the 5′-end . The 5′-end of SCoV mRNAs start with the sequence “m7GpppAUAU- - -” , while SCoV mRNA 9 mt 1 and SCoV mRNA 9 mt 2 start with “m7GpppGAUAU- - -” and “m7GpppAGAU- - -” , sequences , respectively ( the additional G nucleotide and the mutated second nucleotide are underlined ) . A computer-assisted structural analysis showed that the 5′ UTR of SCoV mRNA 9 and the two mutants had the same RNA secondary structure ( Figure 11A ) and previous structural probing analysis confirmed the existence of three stem-loops within the leader sequence [54] . Nsp1 induced an endonucleolytic RNA cleavage in both mutants ( Figures 11B and 11C ) , demonstrating the importance of an accurate and authentic 5′-terminal sequence of the SCoV leader in the protection of RNAs from the nsp1-induced endonucleolytic RNA cleavage . To determine if nsp1 suppresses the translation of viral mRNAs , poly ( A ) containing RNAs were extracted from SCoV-infected or mock-infected cells and subjected to in vitro translation in RRL in the presence of nsp1 , nsp1-mt , or GST . GLA mRNA served as a control . As shown in Figure S4A , the synthesis of the major viral protein , N , was substantially reduced in the presence of nsp1 , but not GST or nsp1-mt , suggesting that nsp1 suppressed the translation of viral mRNAs in RRL . We could not examine the effect of nsp1 on translation of viral mRNAs in HeLa S10 extracts using a similar radiolabeling assay due to the relatively lower translational activity of HeLa S10 extracts compared to RRL ( data not shown ) . Instead , we used a reporter assay to show that nsp1 suppressed the translation of the SCoV mRNA 9-like RNA , m9Lrluc3 RNA ( Figure 10A ) , in the HeLa S10 extract ( Figure S4B ) . These data showed that nsp1 did not induce endonucleolytic RNA cleavage in viral mRNAs but was able to suppress the translation of viral mRNAs in vitro .
Nsp1 induced an endonucleolytic RNA cleavage within the IRES region of different dicistronic RNAs containing a picornavirus type I IRES or type II IRES [22] ( Figure 2 and Figure S1 ) . Incubation of cap-labeled ALA mRNA with nsp1 in RRL resulted in the generation of a cap-labeled RNA fragment 29 nt in length ( Figure 7 ) , demonstrating that nsp1 induced an endonucleolytic RNA cleavage in the ALA mRNA . Thus , the nature of the nsp1-mediated RNA modification is endonucleolytic RNA cleavage . This conclusion leads to the question as to the identity of the enzyme responsible for the endonucleolytic RNA cleavage . Based on the data that SCoV nsp1 has no similarities in its primary amino acid sequence or protein structure with any known host proteins , including RNases [55] , and that binding of nsp1 to 40S ribosomal subunits is required for the nsp1-induced endonucleolytic RNA cleavage [22] , we hypothesize that nsp1 is not an RNase , but uses a host RNase to induce endonucleolytic cleavage of template mRNAs that interact with 40S ribosomes . Several host endonucleases are involved in the mRNA surveillance pathways to detect stalls in translation and are known to exert their function in association with stalled ribosomes . The host cell RNase , SMG6 , has been shown to play a central role in nonsense-mediated mRNA decay by inducing an endonucleolytic RNA cleavage in ribosome-associated host mRNAs containing a pre-mature termination codon [56] . The no-go mRNA decay pathway detects stalled ribosomes on mRNAs during translation elongation , and the yeast dom34/Hbs1 complex is involved in the endonucleolytic cleavage of mRNAs near the stalled site [57] , [58] . The archaeal homolog of the yeast Dom34 , Pelota , also exhibits an endonuclease activity [59] . The exosome is involved in the decay of nonstop mRNAs that lack a stop codon [60] , and one of the subunits of the core eukaryotic exosome has endonuclease activity [61]-[63] . It is conceivable that nsp1 , in association with ribosomes , uses one of the host endonucleases involved in mRNA surveillance pathways to induce RNA cleavage . We identified the nsp1-induced RNA cleavage sites of several mRNAs . For Ren-EMCV-FF and Ren-PV-FF , RNA cleavage mainly occurred near the 3′-end of the IRES elements , where the 40S ribosome is recruited ( Figures 2 and 3 ) . Many nsp1-induced cleavage sites in capped mRNAs were mapped within 30 nt of the 5′ UTR ( Figures 4 , 5 and 6 ) , and the ribosome footprint on an mRNA is about 28 nt in length [64] , [65] . Thus the cleavage sites of template mRNAs were either in or proximal to the initial ribosome binding sites . From these data , we speculate that nsp1-induced RNA cleavage occurs as soon as a complex of nsp1 , 40S ribosome , and translation initiation factors that bind to 40S ribosomes , e . g . , eIF1 , eIF1A , ternary complex , and eIF3 ( we refer to this complex as the nsp1-40S complex ) loads onto mRNA templates . Gel electrophoresis of 32P cap-labeled ALA mRNA that had been incubated with nsp1 showed a discrete ∼29 nt 32P cap-labeled RNA fragment ( Figure 7 ) . Similarly , primer extension analysis of ALA mRNA that was incubated with nsp1 also showed a major premature termination site that corresponded to nucleotide 29 ( site 3 ) ( Figure 4B ) . Hence , two different experimental approaches convincingly demonstrated that the 29 nt-long RNA fragment was generated by nsp1-induced endonucleolytic RNA cleavage . Furthermore , the results of experiments using primer extension analysis of ALA mRNA ( Figure 4 ) and gel electrophoresis analysis of cap-labeled ALA mRNA that underwent nsp1-induced RNA cleavage ( Figure 7 ) led us to speculate that upon loading of the nsp1-40S complex onto ALA mRNA , an initial endonucleolytic RNA cleavage occurred at site 3 in ALA mRNA and the ALA mRNA transcripts that had undergone the initial RNA cleavage at site 3 were subjected to a second cleavage at site 4 . RNA secondary structure modeling placed these sites in the vicinity of a stem-loop structure within the 5′ UTR ( Figure 4D ) , which may imply that an RNase carrying out the initial RNA cleavage at site 3 could easily access site 4 and perform an additional RNA cleavage . However , the possibility of a host exonuclease further processing the endonucleolytically cleaved ALA mRNA at site 3 resulting in the generation of the primer extension termination site 4 cannot be excluded . Interestingly , the nsp1-induced RNA cleavage occurred between various dinucleotide sequences ( Figures 3 , 4 , 5 , 6 and 8 ) , implying that the enzyme exerting endonucleolytic RNA cleavage exhibited little nucleotide preference . Our previous and present studies showed that the nsp1-induced endonucleolytic RNA cleavage is template dependent . Nsp1 induced RNA cleavage within the 5′ UTR of capped mRNAs and within the picornavirus type I and type II IRES elements , while IRESes of HCV , CSFV , and CrPV were resistant to nsp1-induced RNA cleavage . There are differences in the requirement for translation initiation factors and mechanism of translation initiation among capped cellular mRNAs and mRNAs harboring different IRES elements . For cap-dependent translation initiation of host mRNAs , the 43S pre-initiation complex loads onto the 5′-region of mRNA through its interaction with the eIF4F , which binds to the 5′-end of mRNA and is formed by cap-binding eIF4E , eIF4A and eIF4G [30] , [31] . Translation mediated by picornavirus type I and type II IRESes is independent of the cap-binding eIF4E , and it has been suggested that IRES-bound eIF4G and eIF4A recruit the 43S ribosome complex to viral mRNAs [37] . In contrast , HCV IRES-mediated translation starts by direct loading of the 40S ribosome onto the HCV IRES [30] , [31] independent of any translation initiation factors . This is followed by the joining of eIF3 and the ternary complex to the HCV IRES-40S ribosome complex; it is believed that CSFV IRES-mediated translation initiation uses a similar mechanism [30] , [31] . Only the 40S and 60S ribosomes , but not any translation initiation factors , are needed for translation initiation for the CrPV IRES [30] . Due to differences in the mechanism of translation initiation between capped cellular mRNAs and mRNAs with IRESes , several models are conceivable to explain the template-dependent nature of the nsp1-induced endonucleolytic RNA cleavage . One model proposes that eIF4A and eIF4G are required for nsp1-induced RNA cleavage . Namely , eIF4A and/or eIF4G when associated with mRNA templates may bind nsp1 , which then induces activation of a putative RNase to carry out the RNA cleavage , and hence the absence of complex formation of HCV , CSFV or CrPV IRESes with eIF4A and eIF4G prevents the nsp1-induced RNA cleavage . Another model postulates that the nature of the complex between nsp1-40S ribosome and the IRESes of HCV , CSFV and CrPV and the resulting interface between the RNA and the 40S ribosome is such that it prevents the putative RNase from accessing and cleaving these IRESes . The third model proposes that binding of nsp1 to the 40S ribosome may induce a substantial conformational change in 40S ribosomes such that HCV , CSFV or CrPV IRESes may not be able to interact with the 40S-nsp1 complex . Thus , these latter mRNAs would not be in close proximity to the RNase activity induced by the formation of the nsp1-40S ribosome complex . The data that SCoV mRNA 3 and mRNA 9 were not susceptible to nsp1-mediated endonucleolytic RNA cleavage in RRL , along with the report that nsp1 did not suppress viral mRNA accumulation in infected cells [23] , strongly suggest that SCoV mRNAs are resistant to nsp1-induced RNA cleavage in infected cells . In vitro-synthesized SCoV-like mRNAs containing the SCoV leader sequence were resistant to nsp1-induced RNA cleavage , while SCoV-like mRNA lacking the leader sequence was susceptible to the nsp1-induced RNA cleavage ( Figures 9 and 10 ) . Furthermore , the N gene ORF was dispensable for the resistance of virus-like mRNAs to nsp1-induced RNA cleavage ( Figure 10 ) , ruling out the possibility that N protein synthesized from SCoV mRNA 9 in RRL might have acted in trans to prevent the RNA cleavage . Thus , it was the leader sequence that protected viral and virus-like mRNAs from the nsp1-induced RNA cleavage . Several mechanisms are conceivable as to how SCoV mRNAs escaped from the nsp1-induced endonucleolytic RNA cleavage . One is that the nsp1-40S complex loads onto SCoV mRNAs in such a way that the putative RNase that carries out the RNA cleavage cannot interact with SCoV mRNAs . Because nsp1 induced an RNA cleavage at the very 5′-end of SCoV mRNA 9 mt 1 , carrying an extra G residue at the 5′-end of the transcripts , and SCoV mRNA 9 mt 2 , carrying a U to G substitution at the second nucleotide position from the 5′-end , ( Figure 11 ) , the 5′-terminal region of the SCoV leader sequence may play a role in preventing the putative RNase from associating with the viral mRNAs . Alternatively , the binding of nsp1 to 40S ribosomes may induce structural alterations of the 40S ribosome such that interaction between nsp1-40S complex and SCoV mRNAs does not occur , and hence the putative RNase that carries out the nsp1-induced endonucleolytic RNA cleavage cannot gain access to the SCoV mRNAs . Like typical host mRNAs , SCoV mRNAs have a 5′ cap structure [6] , [7] , [52] and a 3′-end poly ( A ) tract . Also , preventing the interaction between eIF4E and eIF4G that inhibits cap-dependent translation also blocked coronavirus replication [66]; therefore , the SCoV mRNAs probably undergo cap-dependent translation . Accordingly , it is also possible that SCoV mRNAs and IRESes of HCV , CSFV or CrPV use different strategies to escape from the nsp1-induced RNA cleavage . For example , the leader sequence of SCoV mRNAs could recruit a host protein ( s ) to protect the viral mRNAs from RNA cleavage . Although SCoV mRNAs are resistant to nsp1-induced endonucleolytic RNA cleavage , translation of SCoV mRNAs and a reporter mRNA carrying the 5′ and 3′ UTRs of SCoV mRNA was suppressed in the presence of nsp1 ( Figure S4 ) . These data were not surprising , because nsp1 inactivates the translation functions of 40S ribosomes [22] . Although the stoichiometry between nsp1 and 40S ribosomes in SCoV-infected cells is unknown , the abundance of 40S ribosomal subunits most likely exceeds that of nsp1 in infected cells . SCoV mRNAs may be dissociated easily from the nsp1-40S complex or may not interact at all with the nsp1-40S complex and efficiently use the nsp1-free 40S ribosomes for their translation . In addition , there may be a mechanism whereby nsp1-40S ribosomes are excluded from sub-cellular locations where efficient viral translation takes place in infected cells to reduce the possibility that viral mRNAs interact with the nsp1-40S ribosome complex .
Vero E6 cells were infected with the Urbani strain SCoV or SCoV-mt [23] at a multiplicity of infection of 1 . At 15 h post-infection , intracellular RNAs were extracted by using TRIzol reagent ( Invitrogen ) . Total RNA was obtained from nuclease-untreated rabbit reticulocyte lysates ( Promega ) by proteinase K digestion , phenol/chloroform extraction and ethanol precipitation . In both samples , poly A+ mRNAs were further prepared by using Oligotex poly A+ RNA purification Kit ( Qiagen ) . Replacing the rluc gene of pRL-SV40 ( Promega ) with the PCR product containing a T7 promoter sequence , 5′ UTR of human β-actin mRNA , rluc gene and a 50-nt-long poly ( A ) tail resulted in pALA-SV40 encoding ALA mRNA . A similar method was used to generate pGLA-SV40 encoding GLA mRNA , except that the 5′ UTR of human β-actin mRNA in pALA-SV40 was replaced by the 5′ UTR of rabbit β-globin mRNA . By using pGLA-SV40 as a template , we employed a QuikChange site-directed Mutagenesis Kit ( Stratagene ) to generate plasmids encoding GLA mRNA mutants . A reporter plasmid , pRL-HL , carrying in the following order: a CMV promoter , T7 promoter , rluc ORF , HCV IRES and fluc ORF , was described previously [22] , [67] . The plasmids pRL-TMEV-FL , pRL-PV IRES-FL , pRL-CVB3 IRES-FL , pRL-HRV2 IRES-FL and pRL-CSFV IRES-FL were constructed by replacing the HCV IRES region of plasmid pRL-HL with that of following viruses and the nucleotide sequences of the viral genome from which they were derived: the DA strain of TMEV IRES , nt 395-1068; type 1 poliovirus IRES , nt 108-745; coxsackievirus B3 IRES , 100-741; human rhinovirus 2 IRES , nt 101-610; and classical swine fever virus IRES , nt 1-441 . The RT-PCR product encoding rabbit β-globin mRNA was cloned into cloning vector pSMART ( Lucigen ) , yielding pSG . The RT-PCR product of full-length SCoV mRNA 9 was cloned into pcDNA3 . 1 myc/His ( Invitrogen ) , generating pcDm9LN3 . The PCR product carrying a T7 class II Φ2 . 5 promoter , human β-actin mRNA ( amplified from HEK 293 cells ) and a 20-nt-long poly ( A ) tail was cloned into the vector pSMART , yielding pSA . The plasmid , pSm9Lactin3 , encoding human β-actin mRNA carrying the 5′ UTR of SCoV mRNA 9 , was generated by replacing the 5′ UTR of human β-actin mRNA in pSA with the 5′ UTR of SCoV mRNA 9 . Sequence analyses of the plasmids confirmed the presence of the expected sequence . Transcription of dicistronic RNA transcripts was described previously [22] , [67] . Capped and polyadenylated RNA transcripts were synthesized from linearized plasmids in vitro by using the mMESSAGE mMACHINE T7 kit or T7 Ultra kit ( Applied Biosystems ) according to the manufacturer′s protocol . Synthesis of SCoV mRNA 9 was performed as previously described [68] , [69] . The PCR product of full-length SCoV mRNA 9 was generated by using pcDm9LN3 as a template and primers T7 phi2 . 5-5′SARS , 5′-CGGAGTAATACGACTCACTATTATATTAGGTTTTTACCTACCC-OH , and SARS 3′ UTR primer , 5′-TTTTTTTTTTTTTTTTTTTTGTCATTCTCCTAAGAAG-OH; to ensure that the 5′-proximal sequence of the in vitro synthesized RNA was identical to that of authentic SCoV mRNA 9 , the T7 class II Φ2 . 5 promoter ( underlined sequence ) was used to initiate transcription by ATP , instead of GTP [70] . To serve as a template for the synthesis of m9N3 RNA , SCoV mRNA 9 mt 1 RNA , and SCoV mRNA 9 mt 2 RNA , a PCR product was generated using the following forward primers with the SARS 3′ UTR primer , respectively: 5′-AATTAATACGACTCACTATAG AACAAATTAAAATGTCTGATA ATGG-OH ( T7 promoter sequence underlined ) ; 5′-AATTAATACGACTCACTATAG ATATTAGGTTTTTACCTACC-OH ( T7 promoter sequence underlined ) ; and 5′-CGGGATCCGAG TAATACGACTCACTATT AGATTAGGTTTTTACCTACCC-OH ( the T7 class II Φ2 . 5 promoter sequence underlined ) . The amplicon , purified on an agarose gel , served as a template for the synthesis of uncapped SCoV mRNA 9 using the MEGAscript T7 kit ( Applied Biosystems ) . The in vitro synthesized SCoV mRNA 9 was purified with the RNeasy mini kit ( Qiagen ) , capped with vaccinia virus capping enzyme using the ScriptCap m7G Capping System ( Epicentre Biotechnology ) and further purified with the RNeasy mini kit ( Qiagen ) . Similar procedures were used for the generation of m9LN and m9LrLuc3 RNAs , except that the PCR products , as shown in Figure 10 , serve as templates for RNA synthesis , and a reverse primer that binds to the 3′-end of N gene was used to generate the PCR for transcription of m9LN RNA . In vitro translation was performed using the Retic Lysate IVT kit ( Applied Biosystems ) . RRL was initially incubated with 1 µg GST protein , nsp1 protein or nsp1-mt protein purified from E . coli at 4oC for 10 min [22] . Then , 0 . 25 µg mRNA and an amino acid mixture ( Promega , to a final concentration of 1 mM ) were added; the molar ratio of nsp1 to mRNA was approximately 200∶1 . Samples were incubated at 30°C for 10 min . In some experiments , HeLa S10 extract was added to RRL at a final concentration of 20% [71] , as indicated , and translation was performed at 30°C for 10 min . After incubation , the samples were incubated with proteinase K , and the extracted RNAs were subjected to Northern blot or primer extension analyses . In some experiments , luc assays were performed by adding 5 µl translation product in 100 µl Renilla Luciferase Lysis Buffer ( Promega ) . Luminescence was measured by using a Renilla luciferase assay system ( Promega ) . After incubation of RNA samples with the 5′-end 32P labeled primers ( 40 , 000 c . p . m ) , primer extension was performed by using the Primer Extension System ( Promega ) according to the manufacturer's protocol . The RNAs , primer sequence , and primer-binding site and conditions are as follows: GLA and ALA mRNAs , 5′-TTTTTCTGAATCATAATAATTAA-3′ , ∼100 nt downstream of rluc translation initiation codon , incubation at 42°C for 1 h and subsequent incubation at room temperature for 10 min; Ren-EMCV-FF , 5′-AGCAATTGTTCCAGGAACCAGGG , ∼100 nt downstream of fluc translation initiation codon , incubation at 55°C for 1 h and subsequent incubation at room temperature for 10 min; Ren-PV-FF , 5′-GGGCCTTTCTTTATGTTTTTGGCG , ∼6 nt downstream of AUG translation initiation codon of fluc gene , incubation at 55°C for 1 h and subsequent incubation at room temperature for 10 min; SCoV mRNA 9 , m9LN3 , and m9LN , 5′-GGGTCCACCAAATGTAATGC-3′ , ∼44 nt downstream of N gene translation initiation codon , incubation at 50°C for 1 h and subsequent incubation at room temperature for 10 min; SCoV mRNA 3 , 5′-TGTAGCATGAACAGTACTTGC-3′ , ∼75 nt downstream of 3a gene translation initiation codon , incubation at 50°C for 1 h and subsequent incubation at room temperature for 10 min; m9LrLuc3 , 5′- TTTTTCTGAATCATAATAATTAA-3′ , ∼100 nt downstream of rluc translation initiation codon , incubation at 42°C for 1 h and subsequent incubation at room temperature for 10 min; and m9N3 , 5′-GTCCTCCATTCTGGTTATTGTC-3′ , ∼76 nt downstream of N gene translation initiation codon , incubation at 50°C for 1 h and subsequent incubation at room temperature for 10 min; m9Lactin3 and actin , 5′- AGCGCGGCGATATCATCATC-3′ , ∼1 nt downstream of the AUG translation initiation codon of β-actin gene , incubation at 55°C for 1 h and subsequent incubation at room temperature for 10 min . AMV reverse transcriptase was used for primer extension . After ethanol precipitation , the primer extension products were resolved in 8% polyacrylamide/7M Urea DNA sequencing gels . Uncapped and polyadenylated ALA mRNA was prepared by using the MEGAscript in vitro transcription kit ( Applied Biosystems ) . Cap labeling was performed by incubation of 30 µg of uncapped RNA with vaccinia virus capping enzyme ( ScriptCap m7G capping system ) in the presence of α-32P GTP ( 3 , 000 Ci/mmole , MP ) at 37°C for 1 h . Cap-radiolabeled ALA mRNA was purified with the RNeasy mini kit and 0 . 75 µg RNA ( approximately 100 , 000 cpm/µg ) was used for in vitro translation in RRL . Then the sample was incubated with proteinase K , and RNA was extracted by phenol/chloroform . The RNA size marker ( ranging from 10 nt to 150 nt ) was prepared with the Decade Marker system ( Applied Biosystems ) according to the manufacturer's instruction with modifications . Full-length Decade Marker RNA ( 0 . 5 µg ) of 150 nt in length was cap labeled with vaccinia virus capping enzyme in the presence of α-32P GTP ( 3 , 000 Ci/mmole , MP ) . After ethanol precipitation , the cap-labeled marker RNA was dissolved in a solution containing 8 µl H2O , 1 µl 10X kinase buffer ( Decade Marker system , Applied Biosystems ) and 1 µl 10X cleavage reagent ( Decade Marker system , Applied Biosystems ) . The full-length RNA marker was cleaved into an RNA ladder by incubation at room temperature for 5 min . The produced RNA ladder contained a set of cap-labeled RNA molecular weight markers of 150 , 100 , 90 , 80 , 70 , 60 , 50 , 40 , 30 , 20 and 10 nt in length . An equal volume of 2x proteinase K digestion buffer was added to the prepared Decade Marker RNA ladder to adjust the salt concentration to a level similar to that of RNA samples extracted from RRL . The RNA samples were analyzed on 10% polyacrylamide/7M Urea DNA sequencing gels .
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Severe acute respiratory syndrome ( SARS ) coronavirus ( SCoV ) is the causative agent of SARS . The nsp1 protein of SCoV blocks host protein synthesis , including type I interferon , a general inhibitor of virus replication , in infected cells . This finding suggests that SCoV nsp1 protein plays a key role in the severe symptoms that accompany SARS infection . Nsp1 binds to the 40S ribosome subunit , which is an essential component for protein synthesis , and inactivates the translation activity of the ribosome . Furthermore , nsp1 binding to the 40S ribosome induces the modification of host mRNAs , leading to the accelerated decay of these RNAs in SCoV-infected cells . We found that the nature of nsp1-induced RNA modification was RNA cleavage and that nsp1 did not recognize specific nucleotides in host mRNAs to induce this cleavage . Interestingly , nsp1 did not induce RNA cleavage in SCoV mRNAs . These data indicate that nsp1 induces RNA cleavage of host mRNAs to suppress the expression of host genes , including those having antiviral functions; yet viral mRNAs are spared from such cleavage events , which , most likely , facilitate efficient SCoV protein synthesis and virus replication in infected cells .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"medicine",
"infectious",
"diseases",
"biology",
"microbiology",
"molecular",
"cell",
"biology"
] |
2011
|
SARS Coronavirus nsp1 Protein Induces Template-Dependent Endonucleolytic Cleavage of mRNAs: Viral mRNAs Are Resistant to nsp1-Induced RNA Cleavage
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Endogenous bornavirus-like nucleoprotein elements ( EBLNs ) , the nucleotide sequence elements derived from the nucleoprotein gene of ancient bornavirus-like viruses , have been identified in many animal genomes . Here we show evidence that EBLNs encode functional proteins in their host . Some afrotherian EBLNs were observed to have been maintained for more than 83 . 3 million years under negative selection . Splice variants were expressed from the genomic loci of EBLNs in elephant , and some were translated into proteins . The EBLN proteins appeared to be localized to the rough endoplasmic reticulum in African elephant cells , in contrast to the nuclear localization of bornavirus N . These observations suggest that afrotherian EBLNs have acquired a novel function in their host . Interestingly , genomic sequences of the first exon and its flanking regions in these EBLN loci were homologous to those of transmembrane protein 106B ( TMEM106B ) . The upstream region of the first exon in the EBLN loci exhibited a promoter activity , suggesting that the ability of these EBLNs to be transcribed in the host cell was gained through capturing a partial duplicate of TMEM106B . In conclusion , our results strongly support for exaptation of EBLNs to encode host proteins in afrotherians .
Many eukaryotic genomes contain endogenous viral elements ( EVEs ) , which are derived from viruses [1 , 2] . Retroviruses are known as a major source of EVEs , such that approximately 8% of the human genome consists of endogenous retroviruses ( ERVs ) [3] . These EVEs not only serve as molecular fossil records representing the development of ancient to modern relationships between retroviruses and hosts , but also occasionally contribute to the evolution of hosts through exaptation [4–7] . For example , the Syncytin genes derived from envelope genes of retroviruses are involved in placentation in mammals [6] . In addition , some ERVs are involved in EVE-derived immunity ( EDI ) , which acts as an anti-virus factor against exogenous retrovirus infections [4 , 5 , 7] . Recently , EVEs derived from non-retroviral DNA and RNA viruses were discovered in many eukaryotic genomes [8–12] . An endogenous bornavirus-like element ( EBL ) was the first EVE identified to be derived from a non-retroviral RNA virus in mammalian genomes [10] . EBLs are most closely related to bornavirus , which is a mononegavirus encoding a nucleoprotein ( N ) , phosphoprotein ( P ) , matrix protein ( M ) , glycoprotein ( G ) , RNA-dependent RNA polymerase ( L ) , and accessory protein ( X ) [13 , 14] . To date EBLs derived from N , M , G , and L genes have been identified and designated as EBLN , EBLM , EBLG , and EBLL , respectively [9] . Some EBL sequences are apparently initiated with a bornavirus transcription start site and ended with a polyA and flanked by target-site duplications ( TSDs ) , suggesting that they were generated through the LINE-1 machinery [8–12] . EBLNs are found in the genomes of diverse animals including snakes , turtles , moles , rodents , primates , and afrotherians [8–17] . ORFs found in EBLNs are in most cases fragmented by premature termination codons , although occasionally EBLNs with relatively long ORFs have been identified . Haplorhini primates have maintained an EBLN encoding 366 amino acids ( aa ) , which is similar in length to bornavirus N ( 370 aa ) , for more than 40 million years ( MY ) . However , no natural selection has been detected on primate EBLNs at the amino acid sequence level [15] . Thirteen-lined ground squirrel ( Ictidomys tridecemlineatus ) has harbored an EBLN ( itEBLN ) encoding 207 aa for ~0 . 3 MY [18] . A recombinant itEBLN protein conferred resistance to bornavirus infection on human cells by being incorporated into bornavirus particles as incompetent nucleoproteins [19] , suggesting a possibility that itEBLN might act as an EDI protein , which should be tested in thirteen-lined ground squirrel . Overall , there is little evidence indicating that EBLNs encode a functional protein in their hosts . Here , in a search for EBLNs that have been co-opted to encode functional proteins in the host , we investigated afrotherian EBLNs containing relatively long ORFs . Afrotherians are a diverse group of mammals that originated in Africa 83 . 3 MY ago ( MYA ) [20] . The superorder Afrotheria includes orders Proboscidea ( e . g . , elephant ) , Sirenia ( e . g . , dugong and manatee ) , Hyracoidea ( e . g . , hyracoid ) , Macroscelidea ( e . g . , elephant-shrew ) , Tubulidentata ( e . g . , aardvark ) , and Tenrecoidea ( e . g . , tenrec and golden mole ) [21] . We present evidence for the existence of EBLNs encoding functional proteins and their evolutionary mechanisms in afrotherians .
Using the amino acid sequence of bornavirus N ( strain name: H1499 , accession number: AY374520 ) as the query , a tBLASTn search was conducted against whole genome shotgun sequences of afrotherians ( taxid: 311790 ) on June 24th , 2015 . A total of 25 EBLNs were identified from African elephant ( Loxodonta africana ) , rock hyrax ( Procavia capensi ) , Florida manatee ( Trichechus manatus latirostris ) , Cape golden mole ( Chrysochloris asiatica ) , Cape elephant shrew ( Elephantulus edwardii ) , and aardvark ( Orycteropus afer ) , with an e-value threshold of E-20 ( S1 Table ) . Two EBLNs each in African elephant , rock hyrax , Florida manatee , Cape elephant shrew , and aardvark contained relatively long ORFs encoding 341–350 aa , which were similar in length to bornavirus N ( 370 aa ) ( S1 Fig ) . Although two EBLNs were identified in Cape golden mole , the ORF of one EBLN ( Ca/AMDV01031468 ) was separated into two fragments encoding 196 aa and 142 aa . The other EBLN ( Ca/AMDV01100225 ) contained an ORF encoding 314 aa , which showed the highest amino acid sequence identity of 53% to bornavirus N among the afrotherian EBLNs identified in this study . In the phylogenetic tree of afrotherian EBLNs and bornavirus N ( Fig 1A and S2 Fig ) , all EBLNs encoding 341–350 aa as well as the EBLN of Cape golden mole with separated ORFs ( Ca/AMDV01031468 ) formed a monophyletic cluster ( cluster I ) . The topology of cluster I EBLNs in Fig 1A reflected that of the host species [21] . In addition , the flanking genomic nucleotide sequences of cluster I EBLNs were alignable between afrotherians ( S3 Fig ) , suggesting that cluster I EBLNs originated from a single integration event of viral N gene into the genome of ancestral afrotherians more than 83 . 3 MYA ( Fig 1A ) [20] . Afrotherian EBLNs with fragmented ORFs formed another cluster ( cluster II ) , which contained EBLNs from African elephant , Folorida manatee , and aardvark . When EBLN sequences identified from non-afrotherian species were added to the phylogenetic tree , cluster I EBLNs and cluster II EBLNs were still monophyletic and constituted a larger cluster with Strepsirrhini EBLNs ( S4 Fig ) . These results suggest that afrotherians have suffered from infection by bornavirus-like virus from the time of their origin and that colonizaiton of EBLNs has occurred at least twice during evolution of afrotherians . When the degree of sequence divergence ( branch lengths ) was compared between cluster I and cluster II EBLNs , it was evident that the amino acid sequences encoded by the former EBLNs evolved more slowly than those encoded by the latter ( Fig 1A and S2 Fig ) , suggesting the functionality of amino acid sequences encoded by cluster I EBLNs . Indeed , the average dN/dS ratio was estimated to be 0 . 34 and negative selection was detected ( p = 2 . 1 × 10−24 by the likelihood ratio test ) for the entire phylogenetic tree of cluster I EBLNs ( Fig 1C ) . In addition , when the dN/dS ratio was estimated at each branch of the phylogenetic tree for cluster I EBLNs , the dN/dS ratio was smaller than one and negative selection was detected ( p < 0 . 05 by the likelihood ratio test ) at most of the branches ( Fig 1C and S2 Table ) . These results indicate that cluster I EBLNs may encode functional proteins in afrotherians . In cluster I , there were two EBLNs obtained from African elephant , named laEBLN-1 ( contig accession number: AAGU03015684 ) and laEBLN-2 ( contig accession number: AAGU03015682 ) ( Fig 1A ) . These EBLNs contained ORFs encoding 344 aa of identical sequences except for a single site ( S1 Fig ) , each of which was 33% identical with the sequence of bornavirus N ( S5 Fig ) . laEBLN-1 and laEBLN-2 were mapped ~45 kb apart on the same chromosome of African elephant ( Loxafr3 . 0 , supercontig 5 ) ( Fig 2 and S3 Table ) . The genomic region encompassing these loci were flanked by transmembrane protein 106B ( TMEM106B ) ( accession number: XM_003407108 ) and scinderin ( SCIN ) ( accession number: XM_003407107 ) . The syntenic relationship among TMEM106B , two copies of cluster I EBLNs , and SCIN as above was also observed in the genome of Florida manatee ( S6 Fig ) . Although the syntenic relationship of TMEM106B and SCIN was observed in the genomes of many vertebrates ( S4 Table ) , no sequence element related to laEBLN-1 or laEBLN-2 was identified between them in non-afrotherian genomes ( S7 Fig ) , supporting the notion that the integration event of cluster I EBLNs took place on the lineage of afrotherians . To examine whether laEBLN-1 and laEBLN-2 were transcribed into mRNAs , RT-PCR was conducted with a set of primers that was designed to amplify DNA fragments of the same size from these EBLNs ( S8 Fig and S5 Table ) . A DNA fragment of the expected size was amplified from total RNA extracted from liver and muscle tissues from an adult male Asian elephant ( Elephas maximus ) and cell lines established from African elephant ear ( LACF-NANAI ) and gum ( LACF-NANAII ) tissues ( Fig 3A and S9 Fig ) . These results suggest that mRNAs containing laEBLN-1 and/or laEBLN-2 and their orthologues are transcribed ubiquitously in African and Asian elephants , respectively . Complete nucleotide sequences of mRNAs containing laEBLN-1 and laEBLN-2 , named laEBLN-1v1 ( accrssion number: LC093509 ) and laEBLN-2v1 ( accession number: LC093510 ) , respectively , were determined by 5’ and 3’ RACEs . Both mRNAs consisted of two exons , 1 and 2 , where EBLN was embedded in exon 2 . Exon 1 and its upstream region , exon 2 and its downstream region , and the intron were all homologous between the genomic loci for laEBLN-1v1 and laEBLN-2v1 ( S10 Fig ) , suggesting that these loci were generated through gene duplication at the DNA level . It should be noted that mRNAs apparently transcribed from the same genomic loci as laEBLN-1v1 and laEBLN-2v1 but processed in alternative splicing forms have been deposited in the RNAseq database for African elephant ( BioSample: SAMN02953622 ) , and were named laEBLN-1v2 ( accession number: LOC104845604 ) and laEBLN-2v2 ( accession number: LOC104845603 ) , respectively , in this study ( Fig 2 ) . Both of the alternatively spliced forms consisted of three exons , 1 , 2 , and 3 . Exon 1 and a part of exon 2 were shared between laEBLN-1v1 and laEBLN-1v2 and between laEBLN-2v1 and laEBLN-2v2 ( S11 Fig ) . When the mRNA expression of laEBLN-1v1 , laEBLN-1v2 , laEBLN-2v1 , and laEBLN-2v2 was examined separately by RT-PCR with four sets of primers that were designed to amplify individual mRNAs ( S8 Fig and S5 Table ) , laEBLN-1v1 , laEBLN-1v2 , and laEBLN-2v1 were detected in both LACF-NANAI and LACF-NANAII ( Fig 3B ) . In contrast , laEBLN-2v2 was not detected in either cell line , suggesting a differentiation in expression patterns between splice variants . The expected molecular weights of the proteins encoded by laEBLN-1v1 , laEBLN-1v2 , laEBLN-2v1 , and laEBLN-2v2 were 38 , 888 Da , 39 , 670 Da , 38 , 860 Da , and 39 , 642 Da , respectively . To examine whether proteins were expressed from these mRNAs , rabbits were immunized with a recombinant laEBLN-1v1 ( rlaEBLN-1v1 ) protein expressed in E . coli to induce polyclonal antibodies , which were confirmed to react with rlaEBLN-1v1 ( Fig 4 , lane 6 ) . The rabbit polyclonal antiserum was also found to react with both of laEBLN-1v1 and laEBLN-1v2 proteins expressed in 293F cells in the western blot analysis ( Fig 4 , lanes 3 and 4 ) . When the western blot analysis using the rabbit polyclonal antiserum was performed on the whole protein extracts from LACF-NANAI and LACF-NANAII , a single band was observed at ~38 kDa ( Fig 4 , lanes 1 and 2 ) , indicating protein expression from some laEBLN mRNAs in African elephant cells . To examine the cellular localization of each variant protein , FLAG-tagged laEBLN-1v1 and His-tagged laEBLN-1v2 proteins , which were confirmed to react with rabbit polyclonal antibodies ( Fig 4 , lanes 7 and 8 ) , were expressed in LACF-NANAI , and were stained with anti-DDDDK- and anti-His-mouse monoclonal antibodies . Note that in the bioinformatic analysis of the amino acid sequences of laEBLN-1v1 and laEBLN-1v2 proteins using PSORT II [22] , the former was predicted to be localized to the cytoplasm , whereas the latter to the nucleus ( S6 Table ) . Consistently , the signal of FLAG-tagged laEBLN-1v1 protein was detected in the cytoplasm ( Fig 5A ) , whereas the singal of His-tagged laEBLN-1v2 protein in the nucleus ( Fig 5B ) . Similar cellular localizations of laEBLN proteins were also observed in 293F cells ( S12 Fig ) , suggesting that laEBLN-1v1 and laEBLN-1v2 proteins may play different functions . It should be noted that bornavirus N is known to be localized to the nucleus of infected cells . It is therefore conceivable that the protein product of laEBLN-1v1 may have acquired a novel function in afrotherians . We then stained LACF-NANAI and LACF-NANAII with rabbit polyclonal antibodies to identify the cellular localizations of endogenous protein products from laEBLN mRNAs . Positive signals were detected around the nucleus in the cytoplasm , co-localizing with the perinuclear part of the endoplasmic reticulum ( ER ) ( Fig 6A ) and , in particular , with the ribosome ( Fig 6B ) , suggesting that laEBLN proteins were associated with the rough ER ( rER ) in African elephant cells . The presence and absence of positive signals in the cytoplasm and nucleus , respectively , may reflect relative abundance of laEBLN proteins in African elephant cells . Assuming that the rabbit polyclonal antibodies could recognize all of the protein products from laEBLN-1v1 , laEBLN-1v2 , laEBLN-2v1 , and laEBLN-2v2 and the cellular localizations of the protein products from laEBLN-1v1 and laEBLN-2v1 were cytoplasmic and those from laEBLN-1v2 and laEBLN-2v2 were nuclear , the observed pattern of positive signals may be consistent with the result obtained above that mRNA expression of laEBLN-2v2 was not detected in African elephant cells ( Fig 3B ) . In the genomic sequence of African elephant , laEBLN-1 and laEBLN-2 were both followed by transcription stop site ( T1 ) and polyA ( Fig 7 ) . The sequence regions encompassing laEBLN-1 and its polyA and laEBLN-2 and its polyA were both flanked by TSDs with similar sequences . In addition , a 6 nt sequence related to a transcription start site ( S1 ) of bornavirus was observed immediately downstream of the 5’ TSD ( TSD1 ) and 5 nt upstream of the start codon in laEBLN-1 . These observations indicate that laEBLN-1 and laEBLN-2 have originated from a common integration event of a reverse-transcribed mRNA for viral N gene through the LINE-1 machinery , similarly to the case for the EBLNs previously identified in other animal species [8 , 10] . Here it should be noted that bornavirus N mRNA does not contain an eukaryotic promoter sequence , and thus it is unclear how the integrated sequence element gained the ability to be transcribed in the host cell . Interestingly , exon 1 and its flanking regions in the genomic loci for laEBLN-1v1/1v2 and laEBLN-2v1/2v2 in African elephant were discovered to be homologous to those for TMEM106B ( Fig 8A and S13 Fig ) . In particular , the 5’ splice site ( GU ) for the first intron of laEBLN-1v1/1v2 and laEBLN-2v1/2v2 appeared to be derived from the corresponding site of TMEM106B ( S14 Fig ) . It was then hypothesized that laEBLN-1 and laEBLN-2 gained the ability to be transcribed in the host cell by capturing a partial duplicate of TMEM106B , which contained a copy of the promoter and transcription start site ( TSS ) for TMEM106B . To test this hypothesis , we conducted a promoter assay by constructing a series of luciferase expression plasmids , in which the luciferase gene was placed downstream of ( 1 ) exon 1 of laEBLN-1v1/1v2 ( pGL4 . 10E-1u ) , ( 2 ) exon 1 of laEBLN-2v1/2v2 ( pGL4 . 10E-2 ) , ( 3 ) exon 1 and upstream 454 nt of laEBLN-1v1/1v2 ( pGL4 . 10E-1u ) , and ( 4 ) exon 1 and upstream 442 nt of laEBLN-2v1/2v2 ( pGL4 . 10E-2u ) ( Fig 8B ) . Note that 454 nt and 442 nt upstream of exon 1 of laEBLN-1v1/1v2 and laEBLN-2v1/2v2 , respectively , were homologous to the upstream sequence of exon 1 of TMEM106B ( Fig 8A ) . It was observed that luciferase activities of pGL4 . 10E-1u and pGL4 . 10E-2u were ~100 times higher than those of pGL4 . 10E-1 and pGL4 . 10E-2 ( p < 0 . 01 by Student’s t test ) , respectively ( Fig 8B ) , supporting the above hypothesis .
In this study , we found that afrotherian EBLNs were clustered into two phylogenetically distinct classes , i . e . , cluster I and cluster II EBLNs , with an exception of the EBLN of Cape golden mole encoding 314 aa . Cluster I EBLNs originated from a single integration event of N mRNA from a bornavirus-like virus into the ancestral genome of afrotherians through the LINE-1 machinery more than 83 . 3 MYA , which overlaps with the time period when LINE-1 was active in afrotherians [23–25] . On the other hand , cluster II EBLNs were observed only in the genomes of African elephant , Florida manatee , and aardvark , suggesting that the integration event of cluster II EBLNs into the afrotherian genomes may have taken place relatively recently compared to cluster I EBLNs . Amino acid sequences encoded by relatively long ORFs in cluster I EBLNs have been negatively selected , suggesting that they were co-opted in afrotherians as functional proteins . In contrast , ORFs in cluster II EBLNs were fragmented and apparently have evolved without functional constraint at the amino acid sequence level . The difference in the fates of cluster I and cluster II EBLN ORFs may have stemmed from the presence or absence of a partial duplicate of TMEM106B upstream of EBLNs in the genome . The promoter and TSS of human TMEM106B are located in the CpG island ( S15 Fig ) , which is known to be associated with ubiquitously expressed genes such as house keeping genes , and human TMEM106B mRNA has been reported to be expressed ubiquitously [26–29] . In the genome of African elephant , GC content in the 100 nt upstream of laEBLN-1v1/1v2 and laEBLN-2v1/2v2 is 65% and 61% , respectively , suggesting that the promoter and TSS of these mRNAs are also located in the CpG island . Indeed , the overall expression of laEBLN-1v1/1v2 and laEBLN-2v1/2v2 was ubiquitous in elephant . It is conceivable that the partial duplicate of TMEM106B provided cluster I EBLNs with an opportunity to be transcribed ubiquitously in afrotherians , which may have facilitated the EBLN proteins to acquire novel functions in the host before the occurrence of deleterious mutations in the ORF . It should be noted , however , that acquisition of intrinsic promoter and TSS may not be necessary for transcription of EBLNs in the host cell , because all of seven EBLNs in human were shown to be transcribed in some tissues although their association with intrinsic promoters and TSS has not been identified [10 , 30 , 31] . In addition , mRNAs containing the cluster II African elephant EBLN ( La/AAGU03023585 , RNAseq accession number: XM_010588552 ) and the Cape golden mole EBLN encoding 314 aa ( Ca/AMDV01100225 , RNAseq accession number: XM_006861214 ) were found in the RNAseq database . It is possible that mRNAs containing these EBLNs were not expressed in sufficiently large numbers of tissues for acquisition of novel functions in the host before the occurrence of deleterious mutations in the ORF . However , it should also be noted that the protein function once acquired by EBLNs can be lost during evolution of the hosts . In afrotherians , the ORF of cluster I EBLN in Cape golden mole ( Ca/AMDV0103146 ) was separated into two fragments , and Lesser hedgehog tenrec ( Echionps telfairi ) contained only remnants of cluster I EBLNs ( contig accession numbers: AAIY02040498 and AAIY02084943 ) , which could not be detected by the tBLASTn search conducted in this study . Interestingly , these species are closely related as members of Tenrecoidea . These information may be useful for understanding the protein function of cluster I EBLNs in other species . Cluster I EBLNs were tandemly duplicated in afrotherian genomes , and were transcribed in alternatively spliced forms in African elephant , generating laEBLN-1v1 , laEBLN-1v2 , laEBLN-2v1 , and laEBLN-2v2 . Although these mRNAs as a whole appeared to be expressed ubiquitously , the expression profile of laEBLN-2v2 was diversified from those of laEBLN-1v1 , laEBLN-1v2 , and laEBLN-2v1 . In addition , protein products of laEBLN-1v1 and laEBLN-2v1 were expected to be different from those of laEBLN-1v2 and laEBLN-2v2 at the C-terminal 20 aa , and the FLAG-tagged laEBLN-1v1 and His-tagged laEBLN-1v2 proteins showed different subcellular localizations in elephant cells . These observations were indicative of a functional differentiation among laEBLN proteins . Nevertheless , the splice donor site ( GU ) for the second intron to generate laEBLN-1v2 and laEBLN-2v2 were identified only in elephant , manatee , and hylax ( Fig 9A ) , suggesting that expression of splice variants corresponding to laEBLN-1v2 and laEBLN-2v2 may be limited to these species . It was unclear whether these species gained or other species lost the splice variants because these scenarios were equally likely from the inference of ancestral sequences at the splice donor site according to the parsimony principle ( Fig 9B ) . It has been reported that the protein product of squirrel EBLN ( itEBLN ) , which was identical to bornavirus N at 77% of amino acid sites , may suppress bornavirus infection by disrupting the function of N [19] . In contrast , bornavirus infection was not suppressed by the protein product of hsEBLN-1 , which shared 41% of amino acid sequence with bornavirus N . The amino acid sequences encoded by afrotherian EBLNs were more divergent from bornavirus N than the sequence encoded by hsEBLN-1 . In addition , endogenous laEBLN protein was observed to be localized to the rER in African elephant cells , which was in sharp contrast to the fact that bornavirus N is localized to the nucleus in infected cells [32 , 33] . These observations suggest that laEBLN proteins have acquired a novel function associated with rER in afrotherian cells . The rER is associated with ribosomes and involved in the translation of cytoplasmic , secretory , and membrane proteins . There are mechanisms to deliver mRNAs from the cytoplasm to the rER membrane by the action of RNA-binding proteins , such as STAU1 , STAU2 , Pum1 , and Pum2 [34–36] . Because mononegavirus N has an ability to bind to RNA and laEBLN proteins are localized to rER , it is interesting to assess the involvement of laEBLN proteins in mRNA delivery . The hydropathy plot of the amino acid sequence encoded by laEBLN-1v1 showed that laEBLN-1v1 protein may be soluble ( Fig 10 ) , which was consistent with the characteristic of the rlaEBLN-1v1 protein produced in E . coli ( See Materials and Methods ) . In the window analysis of the dN/dS ratio for the ORF in cluster I EBLNs , it appeared that negative selection has operated more strongly on hydrophilic regions ( average dN/dS ratio = 0 . 41 ) than on hydrophobic regions ( average dN/dS ratio = 0 . 48 ) ( p < 0 . 05 by z-test where the variance of average dN/dS ratio was estimated with bootstrap resampling of windows ) ( Fig 10 ) , suggesting that the protein product of cluster I EBLNs may interact with other molecules and the interaction may be critical in afrotherians . It is interesting to clarify the function of laEBLN proteins to understand the impact of viruses on the evolution of their hosts .
Afrotherian EBLNs were identified by a tBLASTn search using the amino acid sequence of bornavirus N ( strain name: H1499; accession number: AY374520 ) as the query against the database of whole genome shotgun ( WGS ) sequences for afrotherians ( taxid: 311790 ) on June 24th , 2015 . Sequence hits with an e-value threshold of E-20 were identified as EBLNs . EBLNs in non-afrotherian species were also identified from the database of WGS sequences for vertebrates ( taxid: 7742 ) on May 18th , 2016 by the same criterion as described above . Amino acid sequences encoded by EBLNs were subjected to HMMER for examining the existence of domains that have been deposited in the Pfam database . Multiple alignments of amino acid sequences for EBLNs and bornavirus N were made by mapping each of the amino acid sequences encoded by EBLNs onto that of bornavirus N ( strain name: H1499; accession number: AY374520 ) according to the pairwise alignment of these sequences produced in the tBLASTn search ( S1 File ) . In each EBLN sequence , the amino acid sites differentially aligned to bornavirus N in different tBLASTn hits were treated as gaps . In a dot-plot analysis , the genomic sequences of the genes of interest together with their upstream 1 , 500 nt were retrieved from Ensemble on 12th May , 2015 , and were compared using YASS [37] . Genomic sequences of the regions 46 , 200 , 000–46 , 700 , 000 in scaffold_5 , supercontig loxFar3 of African elephant and 12 , 200 , 000–12 , 700 , 000 in chromosome 7 , GRCh38 of human were subjected to synteny analysis using GeneMatcher ( version 2 . 014 ) [38] , in which BLASTn and tBLASTn searches were conducted for identifying homologous segments between these sequences . The phylogenetic tree of EBLNs and bornavirus N was constructed by the maximum likelihood ( ML ) and nighbour-joing ( NJ ) methods with the partial deletion and pairwise deletion options in MEGA 6 , respectively [39] . The JTT+G model was chosen as the best fit model of amino acid substitution with the smallest Bayesian information criterion score . The nearest-neighbor interchange was selected as the ML heustric method . The reliability of interior branches in the phylogenetic tree was assessed by computing the bootstrap probability with 1 , 000 resamplings . Divergence times between afrotherians were obtained from TimeTree [20] . The dN/dS ratio for the entire phylogenetic tree as well as for each branch of cluster I EBLNs was estimated by the ML method using the codon substitution model in PAML ver . 4 . 0 [40] . The equilibrium codon frequencies were treated as free parameters . The selective neutrality was tested for the entire phylogenetic tree or for each branch by the likelihood ratio test . Window analysis of the dN/dS ratio was conducted between laEBLN-1v1 and each of other cluster I EBLNs , i . e . , Tm/AHIN01138425 , Tm/AHIN01138426 , Pc/ABRQ02082163 , Pc/ABRQ02082168 , Oa/ALYB01141940 , Oa/ALYB01141942 , Ee/AMGZ01016176 , and Ee/AMGZ01016178 , with a window size of 20 codons and a step size of 1 codon using ADAPTSITE [41] . Hydropathy scores along the amino acid sequences encoded by laEBLN-1v1 , Tm/AHIN01138425 , Tm/AHIN01138426 , Pc/ABRQ02082163 , Pc/ABRQ02082168 , Oa/ALYB01141940 , Oa/ALYB01141942 , Ee/AMGZ01016176 , and Ee/AMGZ01016178 were calculated as the Kyte and Doolittle index with a window size of 20 amino acids and a step size of 1 amino acid using GENETYX ( version 10 . 1 . 1 ) ( Genetyx , Tokyo , Japan ) . Liver and muscle tissue samples were collected from an adult male of Asian elephant dead at Kobe Oji Zoo in Japan , and were stored at -80°C until use . Cell lines LACF-NANAI ( RIKEN Cell Bank: RCB2319 ) and LACF-NANAII ( RIKEN Cell Bank: RCB2320 ) , which had been established from the gum and the ear of African elephant , respectively , were provided by RIKEN Cell Bank , Japan , and were maintained in Dulbecco’s modified Eagle’s medium ( DMEM; GIBCO/BRL ) containing 10% fetal bovine serum ( FBS ) , L-glutamine , and penicillin-streptomycin under 5% CO2 at 37°C . The 293F cells ( Invitrogen ) were maintained in Eagle’s minimum essential medium ( EMEM; GIBCO/BRL ) containing 5% FBS , L-glutamine , and penicillin-streptomycin under 5% CO2 at 37°C . BHK-21 cells ( RIKEN Cell Bank: RCB1423 ) , which were provided by RIKEN Cell Bank , were maintained in DMEM containing 10% FBS , L-glutamine , and penicillin-streptomycin under 5% CO2 at 37°C . Total RNA was extracted from the liver and muscle tissues of an Asian elephant; 50 mg of each tissue was frozen with beads ( TOMY ) and 1 ml of ISOGEN ( Nippon Gene ) in liquid nitrogen , and homogenized using TOMY Micro Smash MS-100R ( TOMY ) . The homogenized sample was mixed with 200 μl of 100% chloroform , and the mixture was centrifuged at 12 , 000 × g for 15 min at 4°C . The supernatant with 600 μl of 70% ethanol was added to an RNeasy Spin Column provided in the RNeasy Mini Kit ( QIAGEN ) , and RNA was extracted following manufacturer’s instructions . Total RNA was also extracted from LACF-NANAI , LACE-NANAII , Baby Hamster Kidney ( BHK ) cells , and 293F cells using an RNeasy Mini Kit according to manufacturer’s instructions . DNase digestion was performed on all samples during the extraction process using RNase-free DNase set ( QIAGEN ) . Expression of mRNAs containing laEBLN-1 and laEBLN-2 or their orthologues in the elephant samples was examined by RT-PCR . One-step RT-PCR was conducted using a SuperScript III/Platinum Taq one-step RT-PCR kit ( Invitrogen ) in a final volume of 25 μl containing 1 × reaction mixture , 0 . 4 μM primers , 1 μl SuperScript III RT/Platinum Taq Mix , and 20 ng of total RNA . Primer sequences were designed with Primer Blast in NCBI as listed in S5 Table . RT-PCR was performed as follows; reverse transcription at 50°C for 60 min , 40 cycles of 94°C for 30 sec , 60°C for 30 sec , and 72°C for 30–90 sec , followed by a final extension at 72°C for 3 min . In 2-step RT-PCR , cDNA was synthesized from mRNAs using oligodT primer with or without SuperScript III Reverse Transcriptase ( Invitrogen ) , and the product was used as the template for PCR . In brief , PCR was performed in a final volume of 25 μl containing 1 × PCR Buffer , 0 . 2 mM dNTP , 0 . 4 μM primers , 1 . 25 U Blend Taq ( TOYOBO ) , and 1μl of the above template . PCR reaction was performed as follows; 94°C for 2 min and 40 cycles of 94°C for 30 sec , 55°C for 30 sec , and 72°C for 30 sec . The size of the products was analyzed by agarose gel electrophoresis . The 5’ and 3’ RACEs for laEBLN-1v1 and laEBLN-2v1 were performed using 2 . 75–3 . 75 μl of total RNA collected from LACF-NANAII with SMARTer RACE cDNA Amplification Kit ( Clontech ) . Briefly , after incubation of the total RNA with 12 μM 5’ and 3’ CDS primers at 72°C for 3 min and at 42°C for 2 min , the first-strand cDNA synthesis for 3’ ( 5’ ) RACE was performed in a final volume of 10 μl containing 1 × First-Strand Buffer , 20 mM DTT , 10 mM dNTP mix , 10 U RNase Inhibitor , ( 12 μM SMARTer II A Oligonucleotide , ) and 50 U SMARTScribe Reverse Transcriptase at 42°C for 90 min , followed by a termination process at 70°C for 10 min . The reaction mixture was diluted to 100 μl with Tricine-EDTA buffer , and was used as the template for PCR in a final volume of 25 μl containing 1 × PCR Buffer , 0 . 2 mM dNTP , 0 . 4 μM primers , 1 . 25 U Blend Taq ( TOYOBO ) , and 1 μl of the above cDNA mixture . Nested-PCR was performed using the PCR products diluted 500-fold with distilled water , and the products were purified with Wizard SV Gel and PCR Clean-Up System ( Promega ) . The nested-PCR products were ligated into the pGEM-T Easy vector ( Promega ) using T4 DNA ligase ( New England Biolabs ) , and the plasmids were transformed into TOP10 Competent Cells ( Life Technologies ) . For each of 5’ and 3’ RACEs , at least 10 colonies were selected by direct-colony PCR and the plasmids were purified from the colonies using the Wizard Plus SV Minipreps DNA Purification System ( Promega ) . Nucleotide sequences of the inserts were determined using BigDye Terminator v3 . 1 Cycle Sequencing Kit with ABI Prism 3130 ( ABI ) . Genomic DNA was extracted from LACF-NANAII using a QIAamp DNA Blood Mini Kit ( QIAGEN ) according to manufacturer’s instructions . The ORF of laEBLN-1v1 was amplified from genomic DNA with the primer pair AFEBLN_pET_F and AFEBLN_pET_R ( S5 Table ) . The PCR product was ligated into the PET100 vector ( Invitrogen ) using Ligation high ver . 2 ( TOYOBO ) at 16°C for 30 min , and the plasmid was transformed into BL21 cells . Colonies harboring the plasmids were selected and propagated in LB medium containing 0 . 02% lactose , 0 . 05% glucose , 0 . 5% glycerine , 2 mM MgSO4 , and phosphate buffer for overexpression of the protein encoded by laEBLN-1v1 . BL21 cells were disrupted using ultrasonic wave , and centrifuged at 6 , 000 × g for 30 min at 4°C . The recombinant laEBLN-1v1 ( rlaEBLN-1v1 ) protein was purified from the supernatant with His-Trap HP and Hi-trap desalting column ( GE Healthcare ) , and was used as the antigen for immune induction . In the immune induction , the rlaEBLN-1v1 protein and Gold Titer Max ( CytRx Corporation ) were mixed in equal volumes , and 200 μl of the mixture containing 100 mg antigen was inoculated subcutaneously at four sites in the back of 90 day old rabbits ( New Zealand White , female , SLC Japan ) . The intradermal injection was conducted four times within 1 . 5 months with intervals of 1 or 2 weeks . Whole blood was collected from the rabbits by cardiac puncture under anesthesia with pentobarbital Na ( 25 mg/kg ) , and the rabbits were euthanized with an overdose of pentobarbital Na ( 100 mg/kg ) . Increases in the antibody titers against rlaEBLN-1v1 protein in the rabbits were confirmed by ELISA . Rabbit polyclonal antiserum was collected from the whole blood and was used for western blot analysis and immunohistochemical staining . The animal husbandry methods and experimental design were endorsed by the Nihon University Animal Health Laboratory’s Animal Ethics Committee ( Permit number: AP14B087 ) . This animal ethic has been established based on the “Law for Humane Treatment and Management of Animals” and “Standards Relating to the Care and Management of Laboratory” , administered by the Ministry of the Environment and “Fundamental Guidelines for Proper Conduct of Animal Experiment and Related Activities in Academic Research Institutions” administered by the Ministry of Education , Culture , Sports , Science and Technology in Japan . cDNAs reverse-transcribed from laEBLN-1v1 and laEBLN-1v2 mRNAs were amplified by PCR using Blend taq ( TOYOBO ) with the primer pairs listed in S5 Table . The PCR product of laEBLN-1v1 was ligated into 3×FLAG-CMV-14 vector ( SIGMA ) using Ligation high ver . 2 ( TOYOBO ) after digestion with the restriction enzymes HindIII and BamHI ( New England Biolabs ) at 37°C for 60 min . The PCR product of laEBLN-1v2 was ligated into V5-His-TOPO vector ( Life Technologies ) according to manufacture’s instructions . The plasmids transformed into TOP10 Competent Cells ( Life Technologies ) were collected using PureYield Plasmid Midiprep System ( Promega ) after confirming the insert with nucleotide sequencing . In addition , sub-cloning of ORFs in laEBLN-1v1 and laEBLN-1v2 into pcDNA3 . 10 vector ( Thermo Fisher Scientific ) was conducted using the above plasmids as templates for PCR , which were digested with HindIII and BamHI ( New England Biolabs ) . The 293F cells were seeded onto 6 well plate at 5 × 105 cells/well . On the following day , the above plasmids of 500 ng were transfected into the cells using ViaFect ( Promega ) according to manufacturer’s instructions , and after 24 hrs the whole cellular protein was extracted from the 293F cells . In addition , whole cellular proteins were extracted from LACF-NANAI , LACF-NANAII , and 293F cells propagated in 100 mm2 dishes . In brief , after washing cells propagated in 100 mm2 dishes or 6 well plates with physiological salt solution , RIPA buffer ( Santa Cruz Biotechnology ) was added to each dish and each well , and the cells were incubated on ice for 15 min . The cells were scraped into 1 . 5 ml tubes , and were again incubated on ice for 60 min . The cells were disrupted with ultrasonic wave , and centrifuged at 12 , 000 rpm for 10 min at 4°C . The concentration of total proteins collected from LACF-NANAI , LACF-NANAII , and 293F cells was quantified using the Pierce 660 nm Protein Assay Reagent ( Thermo Scientific ) with Quick Start Bovine Serum Albumin Standard ( Bio-Rad ) by Multiscan GO ( Termo Scientific ) . The whole celluer protein samples were boiled with SDS sample buffer , and electrophoresed in a 12% TGX Stain-Free Fastcast acrylamide Gel ( Bio-Rad ) at 20 mA for 60 min . After trans-blotting onto a PVDF membrane using Trans-Blot Turbo Transfer System ( Bio-Rad ) , the membrane was blocked using BlockAce ( DS Pharma Biomedical ) for 60 min . The membrane was incubated with 1 , 000-fold diluted rabbit polyclonal antiserum and 2 , 000-fold diluted mouse anti-alpha-Tubulin monoclonal antibody ( MBL ) in Can Get Signal solution 1 ( TOYOBO ) overnight at 4°C . After washing in PBS with 0 . 2% Tween 20 ( PBST ) , the membrane was incubated with 50 , 000-fold diluted peroxidase-conjugated anti-rabbit secondary antibody and 25 , 000-fold diluted peroxidase-conjugated anti-mouse secondary antibody ( GE Healthcare ) in Can Get Signal solution 2 ( TOYOBO ) for 60 min at room temperature . ECL signal on the membrane was detected with ECL select solution ( GE Healthcare ) using an ImageQuant LAS-4000 imaging system ( GE Healthcare ) . The LACF-NANAI and 293F cells were seeded onto a glass slide at 1 × 104 and 2 × 105 cells/slide ( Matsunami Glass ) , and 500 ng of EBLN expression plasmids were transfected into the cells . After 48 hrs , these cells were fixed with 4% formaldehyde solution in PBS ( PFA ) for 15 min at room temperature . In addition , to observe subcellular localization of endogenous laEBLN proteins , LACF-NANAI and LACF-NANAII were harvested onto a glass slide , and fixed with 4% PFA for 15 min at room temperature . These cells were subjected to 0 . 1% triton in PBS for 10 min at room temperature . The 200-fold diluted rabbit polyclonal antiserum against laEBLN-1v1 protein and 1 , 000-fold diluted Alexa Fluor 594 Goat Anti-rabbit IgG antibody ( Invitrogen ) were used for detection of endogenous laEBLN proteins . In addition , 100-fold diluted Alexa Fluor 488 conjugated anti-KDEL polyclonal antibodies ( Funakoshi ) and 400-fold diluted Alexa Fluor 488 conjugated anti-S6 Ribosomal protein monoclonal antibody ( Cell Signaling Technology ) were used for detection of the ER and ribosomes in the cells , respectively . The 1 , 000-fold diluted Anti-DDDDK-tag mAb-Alexa Fluor 488 ( MBL ) and Anti-His-tag mAb-Alexa Fluor 488 ( MBL ) were used to detect FLAG-tagged laEBLN-1v1 and His-tagged laEBLN-1v2 proteins expressed in LACF-NANAI and 293F cells . Immunohistochemical imaging of the cells was performed using an Olympus Microscope IX71 . Genomic DNA was extracted from LACF-NANAII using a QIAamp DNA Blood Mini Kit ( QIAGEN ) according to manufacturer’s instructions . PCRs for cloning exon 1 and upstream regions of laEBLN-1v1/1v2 and laEBLN-2v1/2v2 was performed in a final volume of 25 μl containing 1 × PCR Buffer , 0 . 2 mM dNTP , 0 . 4 μM primers , 1 . 25 U Blend Taq ( TOYOBO ) , and 1 μl of genomic DNA , and the PCR products were purified with a Wizard SV Gel and PCR Clean-Up System ( Promega ) . After digestion of the PCR products and the firefly luciferase ( pGL4 . 10 ) vector ( Promega ) with the restriction enzyme KpnI , HindIII , or EcoRV ( New England Biolabs ) at 37°C for 60 min , the PCR products were ligated into the vector using Ligation high ver . 2 ( TOYOBO ) at 16°C for 30 min , and the plasmids were transformed into TOP10 Competent Cells ( Life Technologies ) . Colonies containing plasmids were selected by direct-colony PCR , and plasmids were collected from the colonies using PureYield Plasmid Midiprep System ( Promega ) . The 293F cells were seeded onto 24 well plates at 5 × 103 cells/well . On the following day , 100 ng of firefly luciferase plasmids containing exon 1 with or without upstream region of laEBLN-1v1/1v2 or laEBLN-2v1/2v2 was transfected into the cells using ViaFect ( Promega ) according to manufacturer’s instructions . As a normalization control , 10 ng of renilla luciferase ( pRL-TK ) vector ( Promega ) was also used for transfection . At 24 hrs after transfection , cells were lysed with Passive lysis buffer ( Promega ) , and the luciferase activity was measured by a microplate luminometer ( Centro LB 960 , Berthold Technologies , Bad Wildbad , Germany ) using a Dual-Luciferase Reporter Assay System ( Promega ) . Activity values for firefly luciferase were normalized to those for renilla luciferase . The assay was conducted three times in tripricate wells .
|
Endogenous retroviruses are representative of endogenous viral elements ( EVEs ) , which are known to have occasionally served as the source of evolutionary innovations of the host . Endogenous bornavirus-like nucleoprotein element ( EBLN ) was the first EVE identified in mammalian genomes to have been derived from a non-retroviral RNA virus . Here we show evidence that EBLNs that were integrated into afrotherian genomes more than 83 . 3 million years ago have gained novel protein functions associated with rough endoplasmic reticulum in afrotherians . In the amino acid sequence of EBLN proteins , negative selection appeared to have operated more strongly on hydrophilic regions than on hydrophobic regions , suggesting that EBLN proteins may interact with other molecules in their host cells . In addition , we clarified the mechanism how EBLNs have acquired an ability to be transcribed in the host cell; they captured a partial duplicate of an intrinsic gene , transmembrane protein 106B , which retained an intrinsic promoter activity . Our findings suggest that not only retroviral EVEs but also non-retroviral EVEs may have contributed to the host evolution .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"sequencing",
"techniques",
"split-decomposition",
"method",
"messenger",
"rna",
"vertebrates",
"animals",
"mammals",
"plasmid",
"construction",
"viruses",
"multiple",
"alignment",
"calculation",
"rna",
"viruses",
"bornaviruses",
"dna",
"construction",
"molecular",
"biology",
"techniques",
"research",
"and",
"analysis",
"methods",
"sequence",
"analysis",
"sequence",
"alignment",
"artificial",
"gene",
"amplification",
"and",
"extension",
"molecular",
"biology",
"elephants",
"biochemistry",
"rna",
"computational",
"techniques",
"nucleic",
"acids",
"polymerase",
"chain",
"reaction",
"biology",
"and",
"life",
"sciences",
"amniotes",
"protein",
"sequencing",
"organisms"
] |
2016
|
Exaptation of Bornavirus-Like Nucleoprotein Elements in Afrotherians
|
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