text
string | predicted_class
string | confidence
float16 |
|---|---|---|
Second, creating categories of clinically bacterial and clinically viral etiology by means of biomarker, radiologic presentations and antibiotic pre-treatment was done arbitrarily to reflect real-life decision-making. These theoretical reflections were important to better understand the findings; however, and as noted above, retrospectively the actual decision-making process remained unclear.
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other
| 99.9 |
Third, the study included patients with upper and lower respiratory tract infections and did not exclude patients with antibiotic pre-treatment or significant underlying pathologic conditions, which may have biased the results but reflects clinical routine. Not having algorithms in place when to perform rtPCR testing or how to apply the results likewise mirrors the real-world scenario.
|
study
| 99.94 |
Fourth, the study’s multiplex rtPCR only included respiratory viruses. Newer generation assays additionally cover atypical and typical bacteria and increase the detection of potential respiratory pathogens, albeit with yet unresolved specificity issues as these typical bacterial pathogens might also represent carriage in the absence of disease .
|
study
| 99.94 |
Fifth, the prevalence of RSV was underestimated in this study. In the population of hospitalized children, rapid detection tests for RSV were performed initially and, if positive, no additional rtPCR was performed. Because the study included only patients in whom an rtPCR assay for respiratory viruses was performed, the number of RSV infections was lower than expected from epidemiological data.
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study
| 100.0 |
This study reveals the real-life impact of viral multiplex rtPCR in both children and adults, which was more limited in adults but improved when results were seen in the context of biomarkers, radiology, and antibiotic pre-treatment. As substantial reduction of unnecessary antibiotic prescriptions seems possible, it will be necessary to develop more structured management algorithms incorporating molecular diagnostics including bacterial pathogens, which need to be prospectively tested in their efficacy and safety in RTI.
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study
| 99.94 |
Ribosomal RNA (rRNA) is highly modified with the two most frequent modifications being 2΄-O-methyl groups and pseudouridine (Ψ) (1). 2΄-O-methylation can stabilise single base-pairs or hydrogen bonds and can strengthen or alter RNA folds while Ψ stabilises specific RNA structures (2,3). 2΄-O-methylation is found in almost all types of RNA in the cell, including tRNAs, mRNAs, small nuclear (sn)RNAs and micro (mi)RNAs (4). The majority of the 2΄-O-methyl groups are clustered in functionally important regions of the ribosome such as the peptidyl transferase domain, the decoding centre and the intersubunit bridge (1). The rRNA modification clusters are essential for cell growth (5–10) while loss of some individual modifications increases cellular sensitivity to stress and ribosome-specific antibiotics (11). The specificity of modification is important as 2΄-O-methylation of the wrong site can affect ribosome formation and/or function (12–14). Furthermore, with the recent observations that some sites in the rRNA are not 2΄-O-methylated to a 100% (15,16) and the interest in ‘specialised’ ribosomes (17), there is renewed interest in the mechanism controlling the complexity of rRNA modification.
|
review
| 95.75 |
In eukaryotes and archaea, 2΄-O-methylation is catalysed by box C/D snoRNPs and the related box C/D sRNPs, respectively (18). The RNA components of these complexes (snoRNAs and sRNAs) contain a conserved C/D motif at the termini of the RNA and an internal C΄/D΄ motif (Figure 1A). Both motifs share the same consensus, although the C/D motif is part of a stem-internal loop-stem structure, also known as a K-turn (Figure 1A), while the C΄/D΄ motif often forms a stem-loop structure, lacking stem I, which is known as a K-loop (18). The snoRNA/sRNA functions as a guide for modification by base-pairing to the target site with the nucleotide in the snoRNA–rRNA duplex five base-pairs upstream of box D or D΄ being 2΄-O-methylated (Figure 1A; (18)). The eukaryotic snoRNPs contain four common core proteins, Snu13 (15.5K in humans), Nop56, Nop58 and Nop1 (fibrillarin) while the archaeal complexes are associated with L7Ae, Nop5 and fibrillarin. Fibrillarin/Nop1 is the active methyltransferase subunit and L7Ae/Snu13 are the primary RNA-binding proteins that recognise the sheared GA base-pairs at the centre of the C/D and C΄/D΄ motifs (Figure 1B; (18)). Archaeal Nop5 homodimerises and this homodimer forms a structural scaffold that links the proteins bound to the C/D and C΄/D΄ motifs (19–22). In eukaryotes, Nop56 and Nop58, which are homologous to Nop5 are predicted to form a heterodimer that bridges the complex and contacts the C΄/D΄ and C/D motifs, respectively (Figure 1B).
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study
| 100.0 |
The 2΄-O-methylation activity of snR13, snR48, U18 and U24 C΄/D΄ motifs. (A) Schematic representation of the box C/D motif with the adjacent guide sequence base-paired to the rRNA target (shown in red with the target nucleotide indicated by an asterisk). The sequence of the C and D boxes are shown. The positions of stem I and II in the motif are indicated. Note that the C/D motif is rotated 180° relative to its orientation in (B) so that it is in the same orientation as the C΄/D΄ motif. (B) A schematic model of the box C/D snoRNP complex. The snoRNA is shown in black, with the C, D, C΄ and D΄ boxes indicated. The rRNA is shown in red, with the base-pairing interactions indicated. The asterisk represents the site modified. The box C/D snoRNP proteins are represented as grey filled ellipses. (C) rRNA (upper) and snoRNA (lower) sequences, with both conventional guide-rRNA interactions (rRNA shaded red) and novel extra (or accessory) base-pairing (rRNA shaded blue) interactions, for the S. cerevisiae box C/D snoRNAs that direct multi-site modification. Where sequences are shaded both red and blue, this indicates an overlap between the conventional and extra-base-pairing. The C΄ and D΄ sequences are shown in white with a black background. The guide sequences in the snoRNA are indicated. Note for snR48 there is no obvious D΄ box and the whole conserved area is marked (see later). The modified nucleotides are indicated by an asterisk together with the rRNA nucleotide number. (D) The guide sequence and D΄ motif of the artificial snoRNA constructs used to test the function of the various C΄/D΄ motifs is shown (the full sequence used is shown in Supplementary Figure S1B and C). The D΄ boxes are presented in white with a black background. The target 18S sequence (white text on red background) is shown with the expected (black background) and actual (asterisk) methylation sites indicated. (E) Constructs expressing artificial snoRNAs containing the C΄/D΄ motifs from U18, U24, snR13, snR48 and human (h)U24 (as indicated above each lane) were transformed into yeast cells. RNA was extracted from the cells and analysed by primer extension to detect rRNA methylation. The position of the stop corresponding to methylation of the target nucleotides, S1314 and S1316 in the 18S rRNA, are indicated on the left. Bands corresponding to 2΄-O-methylation are indicated by an asterisk. Northern blotting was used to control for snoRNA expression (Supplementary Figure S2A).
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study
| 100.0 |
High-resolution structures of assembled archaeal box C/D sRNP have been published (20–22) with some debate as to whether the complex is a dimer or monomer. It is worth noting that the only eukaryotic box C/D snoRNP structure published so far, the U3 snoRNP, is clearly a monomer (23). From the archaeal structures, however, it is clear that L7Ae and Nop5 contact the C/D and C΄/D΄ motifs with the C-terminal domain of Nop5 specifically contacting stem II (22). The N-terminal domain of Nop5 interacts with fibrillarin and this unit, referred to as the catalytic module, is mobile and docks onto the sRNA–rRNA duplex upon substrate binding. Fibrillarin binds nucleotides 1–6 of the guide-substrate duplex and a series of non-specific contacts with L7Ae and Nop5 lead to the correct positioning of the active site of this methyltransferase (22). The flexibility/movement of the catalytic module is likely important for binding and release of the modified rRNA. Based on the sequence homology of the various components and the work performed so far, the eukaryotic box C/D snoRNPs are predicted to have a similar structure to that seen for the archaeal sRNPs (18).
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study
| 99.94 |
While archaeal sRNAs are compact with highly conserved sequence motifs, the eukaryotic snoRNAs are significantly more varied (18). In archaea the C/D and C΄/D΄ motifs are highly conserved and very similar. In eukaryotes, while the C/D and C΄/D΄ motifs share the same consensus, the C/D motif is considerably more conserved than the C΄/D΄ motif (24). The eukaryotic C΄ box can contain insertions although it is unclear how this would be accommodated with respect to protein-binding (24). Furthermore, several C΄/D΄ motifs that are clearly active in directing 2΄-O-methylation, vary considerably from the consensus (24). In eukaryotes, an extra, accessory rRNA base-pairing element, that stimulates snoRNP-catalysed methylation by interacting with the rRNA adjacent to the target region of the snoRNA has been described in more than half of the box C/D snoRNAs (24). In yeast, the U18, U24, snR13 and snR48 snoRNAs have been suggested to modify more than one nucleotide in the target region using a single guide and C΄/D΄ region (Figure 1C). Recent deep-sequencing approaches indicate that, for each snoRNA, both sites are almost completely modified (15,16). In each case, deletion of the snoRNA abolishes both modifications (25,26) and, in the absence of alternative methytransferases, it is likely that the C΄/D΄ motifs of these snoRNAs direct multiple modifications. It is, however, unclear how the specificity of box C/D snoRNP catalysed methylation can be altered to enable the 2΄-O-methylation of multiple sites in one target region. We therefore set out to investigate the ability of the U18, U24, snR13 and snR48 snoRNAs to direct multiple modifications in a single target region.
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study
| 100.0 |
The artificial snoRNA construct, inserted in the intron of the actin gene and under the control of a GAL1 promoter, in the plasmid pRS416, was reported previously (24). C΄/D΄ regions, and the target site guide, were subsequently assembled from oligonucleotides and cloned into the NheI and MluI sites in the snoRNA coding sequence (Supplementary Figure S1). All experiments using these constructs were performed in S. cerevisiae strain W303 (leu2-3112 trp1-1 can1-100 ura3-1 ade2-1 his3-11,15).
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study
| 100.0 |
The snR13 gene was PCR amplified using primers snR13fw (5΄ AATAGGATCCCAACGTGAAGAAGCC 3΄) and snR13rev (5΄ AACAGAATTCGCTTGCTTAGGCCCAAC 3΄) and was cloned into the Acc65I/XhoI sites of pRS416. Plasmids expressing wild-type or mutant snR13 were then transformed into the yeast strain YS630 (ade2, his3, trp1, ura3, leu2, snR13::TRP) (27). Mutations in the snR13 coding sequence were generated using PCR-based mutagenesis.
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study
| 100.0 |
Methylation activity was determined by reverse transcription under limited nucleotide and enzyme concentrations (28) as described previously (24). A total of 8 μg RNA was annealed to 32P-, 5΄-end labelled primer and then incubated with M-MLV reverse transcriptase (40 u, Promega), 2 μl 5xRT buffer, 0.25 μl superasin and 1.25 mmol dNTP's. The reactions were separated on either a 6 or 8% polyacrylamide/7 M urea gel and then visualised using a phosphorimager. Primers used for mapping were Map1316 (5΄-TAGTCCCTCTAAGAAGTGGATAACC-3΄) and Map13 (5΄-CTAGATAGTAGATAGGGACAGTGG-3΄). To determine the expression of snoRNAs, Northern blot analysis was performed with the following probes snR13 (5΄-CCACACCGTTACTGATTTGGCAAAA GC-3΄), snR5 (5΄-TAAGCATGGTAATCCGGAAGATC-3΄), snR87 (5΄-TAGAACATGGCGGTGTTCCAA GTGAT-3΄), artificial snoRNA (5΄-AATTGCGATAACGCTAGCTACATC-3΄) and 5S rRNA (5΄-CTACTCGGTCAGGCTC-3΄) as described previously (24). In some cases, methylene blue staining of 5S rRNA was used to check for equal loading.
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study
| 100.0 |
The box C/D or C΄/D΄ motif with an adjacent guide region has been shown to direct the modification of a single nucleotide in the rRNA five base-pairs away from the D/D΄ box (Figure 1A). This is performed by positioning of the active site of Nop1/fibrillarin, which binds the C/D or C΄/D΄ motif, at the nucleotide to be modified (Figure 1B). However, the C΄/D΄ motifs and respective guides of the naturally occurring yeast snR13, snR48, U18 and U24 snoRNAs have been shown to direct the modification of two nucleotides in the same target region of the rRNA (Figure 1C). For U18, U24 and snR13 these nucleotides are adjacent, while for snR48 the nucleotides are separated by one nucleotide. In each case, deletion of the snoRNA results in the loss of both modifications (25,26). The C΄/D΄ motifs of these snoRNAs, each of which deviates from the consensus ((24) C΄ – RUGAUGA; D΄ – CUGA), could result in the modification of multiple sites within the rRNA target region (Figure 1C). It is important to note that while motifs resembling the consensus D΄ motif could be found in snR13, U18 and U24, no such motif could be found for snR48 and the conserved region we have designated the D΄ box (see later) is six nucleotides long. However, it is also possible that other mechanisms, such as a second methytransferase that recognises the primary snoRNP-catalysed modification and methylates after this has occured, could generate the modification profiles seen with the U18, U24, snR13 and snR48 snoRNPs.
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study
| 100.0 |
To test whether the C΄/D΄ motifs of snR13, snR48, U18 and U24 alone are capable of directing multi-site modification we inserted the C΄/D΄ motifs from these snoRNAs into an artificial snoRNA construct, based on the human U24 snoRNA, that we have previously described (24). In the control construct for these experiments, the C΄/D΄ motif from the human U24 snoRNA (which unlike its yeast counterpart follows the consensus standard) was placed adjacent to a guide sequence that targets nt S1316, an unmodified region of the yeast 18S rRNA (Figure 1D; nt with black background indicates the predicted target site). The C΄/D΄ motifs of snR13, U18 and U24 were cloned into the artificial snoRNA construct to target site S1315 based on the established 5-base-pair rule for 2΄-O-methylation (Figure 1D). If the C΄/D΄ motifs are capable of multiple modifications then site S1316 should also be modified. Since snR48 does not contain a recognisable D΄ motif, we cloned the C΄/D΄ motif such that it should, based on snR48 modification of its natural target site, target nucleotides S1316 and S1314. The constructs expressing the artificial snoRNAs were transformed into yeast cells. Northern blotting was used to demonstrate that the snoRNAs were all expressed to the expected levels (Supplementary Figure S2A). The modified nucleotide in the target region of the 18S rRNA was then determined by primer extension under reduced nucleotide concentrations where 2΄-O-methylated nucleotides cause the reverse transcriptase to terminate at a higher frequency.
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study
| 100.0 |
A reverse-transcriptase stop, consistent with 2΄-O-methylation, was observed at nucleotide S1316 when the artificial snoRNA containing the human U24 C΄/D΄ motif (hU24) was expressed, but not in the absence of a snoRNA (Figure 1E; methylation bands indicated by asterisk). A weaker stop was frequently observed at nucleotide S1315 one nucleotide above the target site, as we have observed previously (24). It is important to note that we also observed a weak stop one nucleotide above almost all natural methylation sites in the rRNA that we tested. We believe that this additional, weaker band, is due to additional stalling by reverse transcriptase and does not reflect additional methylation. 2΄-O-methylation at nucleotide S1316 was also seen when snoRNAs containing the C΄/D΄ motifs of snR13 and U24 were expressed. In contrast, the snoRNA containing the U18 C΄/D΄ motif resulted in methylation of nucleotides S1316 and S1315 while the snR48 C΄/D΄ directed modification at sites S1316 and S1314 (Figure 1E). Our data clearly show that the C΄/D΄ motifs of U18 and snR48 directed the methylation of two distinct nucleotides in the target region. Indeed, the methylation pattern seen for the U18 and snR48 C΄/D΄ motifs replicated the 2΄-O-methylation pattern attributed to the full-length snoRNAs (Figure 1C and D). Surprisingly, while multiple-site methylation was not seen with the box C΄/D΄ snoRNA motifs of snR13 and U24, both motifs directed modification of a nucleotide six nucleotides upstream of the D΄ box (Figure 1D). Furthermore, our data suggest that for both U24 and snR13, other elements in the snoRNA, in addition to the C΄/D΄ motif, or possibly an additional trans-acting factor, play a role in the 2΄-O-methylation of multiple sites in their target region.
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study
| 100.0 |
Having shown that the U18 and snR48 C΄/D΄ motifs both direct multi-site 2΄-O-methylation, we were next interested in determining why these motifs have this unusual property. Starting first with U18, analysis of the U18 C΄/D΄ motif from all available yeast sequences ((24); Figure 2A) revealed that the D΄ box consensus (AUGA) is close to the canonical D΄ box sequence (CUGA) while the C΄ motif contains a single nucleotide insertion (AUGAGUGA). Analysis of the structure of the U18 C΄/D΄ motif revealed that the main variation is found in the stem II region (Figure 2B). One possible explanation for the 2΄-O-methylation of two adjacent nucleotides is that the D΄ region contains two distinct, overlapping D΄ boxes (Figure 2B; left structure AUGA and right structure UAUGA) that would result in two alternative structures for stem II (Figure 2B; canonical and alternative models). In the canonical structure, the extra nucleotide in box C΄ (AUGAGUGA) is not base-paired and bulges out, enabling normal stem II interactions between the two boxes. In the alternative structure model, the extra nucleotide base-pairs with the D΄ box and forms part of stem II. We therefore suggest that the two distinct structures of stem II could result in different positioning of the methyltransferase Nop1 in the complex in each case. The alternative modes of Nop1 binding could therefore place adjacent nucleotides into the active site of Nop1, therefore resulting in the modification of two distinct nucleotides.
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study
| 100.0 |
The 5΄ end of box D΄ and the extra nucleotide in box C΄ are both required for multiple site 2΄-O-methylation by the U18 snoRNA. (A) A WebLogo representation of the evolutionary conservation of the guide, D΄ box, accessory guide and C΄ box sequences (as indicated below) of the U18 snoRNA derived from the alignment of all the available yeast U18 snoRNA sequences (24). The consensus C΄ and D΄ sequences are shown above. The diagram was prepared using the WebLogo software (29). (B) Two secondary structure models, one showing canonical base-pairing the other an alternative structure for stem II, of the U18mutX box C΄/D΄ motif and guide sequence, in the context of the artificial snoRNA, base-paired to the 18S rRNA. Note, in the alternative structure a longer, 5 nucleotide box D΄ is used. The U18mutX RNA differs from the wild-type U18 in the sequence of the accessory guide region (Supplementary Figure S1C) that has been altered to base-pair with the 18S rRNA adjacent the region targeted by the artificial snoRNA. The arrows indicate the site modified. The box C΄/D΄ motif and the accessory guide are shown in white on a black background. The positions of the C΄, D΄ boxes and stem II are indicated. The sequence of the box C΄ and D΄ mutants is also shown to the right and left of the structures, respectively. The numbering system used starts at the first position of the canonical box sequence. (C) Plasmids expressing artificial snoRNAs containing the wild-type and mutant U18 C΄/D΄ motifs (as indicated above each lane) were transformed into yeast cells. RNA was extracted from the cells and analysed by primer extension to detect rRNA methylation. The position of the stop corresponding to methylation of the target nucleotides, S1315 and S1316 in the 18S rRNA, are indicated. The levels of the various snoRNAs were determined by Northern blotting (Supplementary Figure S2B).
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| 100.0 |
To investigate this further, we generated a series of mutants in the U18 C΄/D΄ region in the artificial construct to test the importance of the stem II sequence in multi-site 2΄-O-methylation (Figure 2B). For these experiments we also mutated the extra base-pairing element in the U18 C΄/D΄ such that it base-paired upstream of the 18S rRNA target site to fully replicate the base-pairing interactions seen with the wild-type U18 snoRNA and the 25S rRNA (U18mutX; Figure 2B and Supplementary Figure S1C). It is important to note that we found that the extra base-pairing played no role in multi-site modification or methylation efficiency by the U18C΄/D΄ region (data not shown). The constructs were transformed into yeast cells, the expression of the snoRNAs was monitored by Northern blotting (Supplementary Figure S2B) and the ability to direct 2΄-O-methylation was analysed by primer extension.
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Mutation of the first GA di-nucleotide in the C΄ box (C΄3,4 GA-CC) abolished methylation at both sites (Figure 2C) while mutation of the last A in the D΄ box (D΄4 A-C) abolished methylation at S1316 and severely reduced methylation at S1315. Interestingly, mutation of the second GA di-nucleotide in box C΄ (C΄7,8 GA-CC) abolished methylation at S1316 but not at S1315. From this we concluded that the GA base-pairs are needed for total activity and that changes to stem II affect the site targeted for methylation. Further mutation of the stem II sequence revealed that deletion of the G insertion (C΄5 ΔG) had little effect on the methylation of S1316 and S1315. However, mutation of this G to a U or A (C΄5 G-U; C΄5 G-A) biased the modification to site S1315 over S1316. Mutation D΄1 A-C, which generates the consensus D΄ box resulted in a reduction in 2΄-O-methylation at nucleotide S1316 but no change to methylation at S1315. Conversely, mutation D΄-1 U-C, which places a C at the 3΄ end of the guide region, resulted in methylation of S1316 and a reduction in the signal at S1315 to background levels (Figure 2C; compare D΄-1 U-C to hU24). These data indicate that the sequence of stem II in U18, in particular the 5΄ nt of the D΄ box and the 3΄ nucleotide of the guide, dictate which nucleotides are modified in the target sequence. Importantly, neither of these nucleotides is a C, the consensus nucleotide for the 5΄ end of box D΄, and mutation of either nucleotide to a C dramatically alters the methylation pattern. This therefore implies that the sequence/structure of stem II and, in particular, suboptimal sequences at the 5΄ end of box D΄ can result in the modification of two different nts in the target sequence.
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study
| 100.0 |
Having shown that the unusual C΄/D΄ motif, in particular the D΄ box, in U18 results in the modification of two sites in the target region, we were next interested to determine the elements needed for the unusual activity of the snR48 C΄/D΄ motif. Yeast snR48 guides the 2΄-O-methylation of two nucleotides (G2791 and G2793) in the snR48 target region of the 25S rRNA (helix 88 in domain V). Interestingly, by comparing the available yeast RNA sequences we found that the unusual D΄ box region of snR48 is a highly conserved 6 nt region (AUGUUA) that does not contain the CUGA consensus (Figure 3A). Conversely, the C΄ motif, in particular the 5΄ half, fits to the consensus sequence and is as conserved as most yeast C΄ boxes (24). As with U18, we found two possible base-pairing alternatives for the C΄/D΄ motif that may explain the ability of this motif to direct two 2΄-O-methylation events in the same target (Figure 3B). This secondary structure is also conserved, with only a couple of exceptions, across a diverse range of fungi. The UG in the D΄ box of S. cerevisiae snR48 (from 5΄ positions 2 and 3) is an AA in S. kluyveri snR48. This means that only one of the two base-pairing options seen in the S. cerevisiae snR48 is possible in the S. kluyveri RNA (Figure 3B). In addition, the C΄/D΄ motif in the snR48 snoRNAs from Lodderomyces elongisporus, Candida parapsilosis, Verticillium dahliae, Phaeosphaeria nodorum, Aspergillus flavus and Glomerella graminicola (Figure 3B and data not shown) also allow for only one of the two base-pairing interactions. To test the methylation activity of the different snR48 C΄/D΄ motifs, we mutated the S. cerevisiae sequence in the artificial construct to mimic the sequence of the S. kluyveri snR48 D΄ motif (Figure 3C; mutant D΄2,3 UG-AA). In addition, we cloned the C΄/D΄ region from the L. elongisporus snR48 snoRNA into the artificial snoRNA construct (Supplementary Figure S1). The ability of these artificial snoRNAs to direct methylation was then analysed as described above.
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The snR48 C'D' motif is unique and directs 2΄-O-methylation at multiple sites in the target region. (A) A WebLogo representation of the conservation of the guide, D΄ box and C΄ box sequences of the snR48 snoRNA derived from the alignment of all the available yeast snR48 sequences (24). The consensus sequence for the C΄ and D΄ boxes is shown above the WebLogo image. Note, two potential alternative positions for the D΄ box are shown. The diagram was prepared using the WebLogo software (29). (B) Secondary structure of the snR48 box C΄/D΄ motif and guide sequence base-paired to the 25S rRNA from S. cerevisiae, S. kluyveri and L. elongisporus. Note two alternative structures are shown for the S. cerevisiae snR48. The C΄ and D΄ boxes are shown in white on a black background. Arrows indicate the site to be modified. (C) Secondary structure of the snR48 box C΄/D΄ motif, in the context of the artificial snoRNA targeting sites 1314 and 1316 in the 18S rRNA. The C΄ and D΄ boxes are shown in white on a black background. Arrows indicate the site to be modified. The mutations to the C΄ and D΄ boxes are shown to the right. (D) Constructs expressing artificial snoRNAs containing the wild-type and mutant snR48 C΄/D΄ motifs (as indicated above each lane) were transformed into yeast cells. RNA was extracted from the cells and analysed by primer extension to detect rRNA methylation. The position of the two target nucleotides (S1314 and S1316) is indicated on the right. L.elo is the artificial snoRNA with the C΄/D΄ motif from L. elongisporus snR48. snR48 glucose: yeast containing the plasmid encoding the artificial snoRNA with the snR48 C΄/D΄ motif, grown on glucose containing media. The levels of the various snoRNAs were determined by Northern blotting (Supplementary Figure S2C).
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The use of the S. kluyveri D' box resulted in the preferential 2΄-O-methyation of site S1314 and all but abolished modification at S1316 (Figure 3D; D΄2,3 UG-AA). This is consistent with the fact that this mutation would interrupt base-pairing with the lower D΄ box and therefore methylation at S1316. Interestingly, reverse transcriptase stops, above background levels, were also seen 1 nt above and below S1314 indicating that the methylation machinery bound to this motif is somewhat promiscuous. The L. elongisporus C΄/D΄ motif (Figure 3D; L.elo) also directed modification of S1314 and, to a lesser extent, S1313 but not S1316. This indicates that snR48 C΄/D΄ motifs generally direct the 2΄-O-methylation of multiple sites in the target region. However, the pattern of modification in different yeast species can vary from that seen in S. cerevisiae depending on the sequence of the C΄/D΄ motif.
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We were next interested in analysing the sequence and structural features of the C΄/D΄ motif of the snR48 snoRNA from S. cerevisiae. To this end, we generated a series of mutations in the C΄ and D΄ boxes (Figure 3C) and analysed their effect on 2΄-O-methylation (Figure 3D). Mutation C΄9,10 AA-CC, which altered nucleotides just downstream of the C΄ box, had no noticeable effect on methylation at either site while the D΄6,7 AG-CC and C΄3,4 GA-CC mutations severely reduced and completely abolished modification at both sites, respectively. The D΄6,7 AG-CC mutation altered the last nucleotide of the predicted D΄ box and suggests that the 3΄ end of the D΄ motif is required for both modification events. A slight reduction in methylation at site S1314 was observed with the D΄5,6 UU-CC and D΄8,9 GA-CC mutations. The D΄1,2 AU-CC and C΄4,5 AA-CC mutations severely reduced 2΄-O-methylation at site S1314, while not significantly affecting modification of S1316. Mutations C΄-1,1 AA-CC and C΄4,5 AA-UU reduced methylation at both sites. Interestingly, the C΄4,5 AA-CC and C΄4,5 AA-UU mutations change the same 2 nt but have different outcomes. Deletion of the first 2 nt of box D΄ (Figure 3C; D΄1,2 ΔAU) replaced the AU of the D΄ box with the UU of the guide region and moved the predicted target sites (now S1316 and S1318). This mutant resulted in methylation of S1316 but not S1318 (Figure 3D). Our data indicate that the whole of the D΄ box is essential for the multi-site modification of the target region guided by snR48. However, only the 3΄ A of the D΄ box was absolutely essential for rRNA modification. As with U18, the insertion of C's in the 5΄ end of the D΄ region (mutants D΄1,2 AU-CC) significantly influenced the nucleotide modified. The C΄ box of snR48 appears to be comparable to C΄ boxes found in other yeast snoRNAs. Our data are consistent with snR48 containing two different structures for the C΄/D΄ motif using two overlapping D΄ boxes. However, the interaction between the consensus C΄ box and the D΄ box contains one to two Watson–Crick base-pairs and three non-Watson–Crick base-pairs making it difficult to predict exactly how these boxes and, especially very divergent sequences, interact with each other (see Discussion). This point is exemplified by the fact that the D΄1,2 AU-CC mutation would be predicted to block methylation at S1316, in a similar manner to the D΄1,3 UG-AA mutation, but actually affects 2΄-O-methylation at site S1314 and suggests not only that the complete D΄ region is required for both modifications but that a C at the 5΄ end of the D' box determines which nucleotide is modified.
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From the analysis of U18 and snR48, our data indicate that the presence of a C at the 3΄ end of the guide region, particularly where the D΄ box lacks a 5΄ C, can influence the site methylated in the rRNA and extend the D΄ box to five nucleotides. From this we predict that C would not frequently be found at the 3΄ end of the guide region. We therefore compared the sequence of the last three nucleotides of guides, before the D or D΄ box, known to direct 2΄-O-methylation in the S. cerevisiae snoRNAs. There was no sequence bias in the nucleotides three and two positions before the D/D΄ box (Figure 4A). In contrast, in 60% of the RNAs a U was present in the last position of the guide, A was represented normally, G slightly under-represented and C only present in two cases (Figure 4A). In one case, snR13, the C present at the 3΄ end of the guide is probably part of a longer D΄ box (see later). The data therefore indicate that in S. cerevisiae, U is the preferred nucleotide for the last position in the guide region and that C is significantly under-represented. We next compared the sequence of the last nucleotide of the guide region in 2033 active and 556 inactive (i.e. the guide regions that are not conserved and have no obvious target) guides adjacent to the D΄ box for all available yeast snoRNAs that were characterised in our previous bioinformatics analysis (24). While there was a slight bias towards C, and against G, in the inactive guides, this revealed no real significant sequence bias (Figure 4B). However, in the active guides, the sequence was again biased towards U, with C found at this position in only 9% of the snoRNAs. Interestingly, G was also under-represented at this position. These data therefore support our hypothesis that a C at the 3΄ nucleotide of the guide region may interfere with 2΄-O-methylation specificity.
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The last nucleotide of the guide region can influence the site to be 2΄-O-methylated in the target RNA. (A) A schematic representation of the conservation of the active guide and D΄/D box sequences of the S. cerevisiae snoRNAs (24). The diagram was prepared using the WebLogo software (29). (B) Comparison of the 3΄ nucleotide of the active and inactive (no guide) guide regions of the available yeast box C/D snoRNAs (24). (C) Secondary structure of the hU24 box C΄/D΄ motif, in the context of the artificial snoRNA targeting sites 1316 in the 18S rRNA. The C΄ and D΄ boxes are shown in white on a black background. The arrow indicates the site to be modified. The mutations to the D΄ box are shown to the left. (D) Constructs expressing artificial snoRNAs containing the wild-type and mutant hU24 C΄/D΄ motifs (as indicated above each lane) were transformed into yeast cells. RNA was extracted from the cells and analysed by primer extension to detect rRNA methylation. The position of the stop corresponding to methylation of the target nucleotides, S1315 and S1316 in the 18S rRNA, are indicated. The levels of the various snoRNAs were determined by Northern blotting (Supplementary Figure S2D).
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We therefore next tested the importance of the last nucleotide of the guide and first nucleotide of the D΄ box in the human U24 C΄/D΄ motif, which modifies a single site when expressed in the context of our artificial snoRNA targeting S1316. Insertion of a U between the C and U of the D΄ box, changing the last nucleotide of the guide to C and the first nucleotide of the D΄ box to U (Figure 4C; D΄1 Uins) should, based on the five nucleotide rule, result in modification of S1315. However, this mutation resulted in the modification of position S1316 (Figure 4D). Importantly, when a U was inserted between the guide and the D΄ box site (Figure 4C; D΄-1 Uins) nucleotide S1315 was modified. This therefore supports our proposal that the last nucleotide of the guide can influence the site to be modified.
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The U24 and snR13 C΄/D΄ motifs both directed methylation six nucleotides from the originally predicted D΄ box (Figure 1E) but neither element, in the context of the artificial snoRNA system, targeted methylation of two adjacent nucleotides. We therefore next investigated whether other elements in the snoRNAs contribute to multi-site modification of the target region. To our surprise, many of the mutations to guide and/or C΄/D΄ regions of yeast U24 frequently affected snoRNA levels to the extent that we could not draw any conclusions from our analysis of this snoRNA (data not shown). We therefore turned our attention to the snR13 snoRNA which directs 2΄-O-methylation of nucleotides L2280 and L2281 in the 25S rRNA. snR13 contains an extra base-pairing region or accessory guide (Figure 5A and B; (24)). The snR13 D΄ box is evolutionarily well conserved and again possibly has two D΄ boxes, one four nucleotides (Figure 5B; UCGA) and one five nucleotides in length (CUCGA). Based on the work presented above, the CU present at the 5΄ end of the D΄ box likely contributes to the targeting of the nucleotide six nucleotides into the guide. Given that multi-site modification was not achieved with the artificial snoRNA system, we analysed the role of the extra base-pairing region and the 5΄ end of the D' box in the level and specificity of 2΄-O-methylation by the natural snR13 snoRNA. An empty vector or plasmids expressing wild-type snR13 or mutated snR13 (Figure 5B and C), were introduced into a yeast strain where the endogenous snR13 gene had been deleted. RNA was extracted from these strains and 2΄-O-methylation was analysed by primer extension.
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An unusual D΄ box and the extra base-pairing sequence are required for multi-site 2΄-O-methylation by the snR13 snoRNA. (A) A schematic representation of the conservation of the active guide and D΄/D box sequences of the snR13 snoRNA (24).The consensus for the C΄ and D΄ sequences is shown above the image. The diagram was prepared using the WebLogo software (29). (B) Secondary structure models of the snR13 box C΄/D΄ motif, guide region and accessory guide with the natural rRNA target site (shown in red) in the 25S rRNA. The C΄ and D΄ boxes are shown in white on a black background. The arrow indicates the site to be modified. The mutations to the D΄ box are shown to the left and the mutation to the accessory guide is shown on the right. Arrows indicate the site in the rRNA to be modified. Note, in the alternative structure a longer, five nucleotide box D΄ is used. (C) Constructs expressing wild-type and mutant snR13 snoRNAs (as indicated above each lane) were transformed into yeast cells. RNA was extracted from the cells and analysed by primer extension to detect rRNA methylation. The position of the stop corresponding to methylation of the target nucleotides, L2280 and L2281 in the 25S rRNA, are indicated. The levels of the various snoRNAs were determined by Northern blotting (Supplementary Figure S2E). (E) The data presented in (D) was analysed using imagequant software and the relative levels of the bands corresponding to the L2280 and L2281, relative to the signal seen for the modification at L2288, were calculated and plotted. The data were adjusted to the WT signal at L2280. Error bars indicate standard deviation from three separate experiments.
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No 2΄-O-methylation of sites L2280 and L2281 was seen in the strain lacking snR13 and methylation was restored at these two sites when the wild-type snR13 was expressed from a plasmid (Figure 5D; compare lanes 1 and 2). Mutation of the nucleotide just before the D΄ box to an A (D΄-1 C-A) resulted in a reproducible increase in modification at site L2280 with a corresponding decrease to modification at site L2281 (Figure 5C (lane 4) and D). Interestingly, this change was not seen when this nucleotide was changed to a U (D΄-1 C-U; lane 6). The C to U change would still allow base-pairing with the second G in the C΄ box (RUGAUGA) while a C to A change would likely abolish this interaction. Mutation of the extra-base-pairing region (Xmut) resulted in a significant reduction of 2΄-O-methylation by snR13 at L2280 while modification of nucleotide L2281 was not detectable (lane 3). Interestingly, combining Xmut with the D΄-1 C-A mutation (Xmut-D΄-1 C-A; lane 5) resulted in a slight reduction at modification at site L2280 but a dramatic reduction in 2΄-O-methylation at L2281. In contrast, combining Xmut with the D΄-1 C-U mutation gave the same result as the Xmut alone (Xmut-D΄-1 C-U; lane 7). Extra base-pairing can affect the level of methylation (24) but we were surprised to find that this base-pairing interaction can also affect target specificity. Taken together, our data show that the combination of an unusual D΄ box and extra base-pairing lead to the efficient 2΄-O-methylation of two sites in the target region by snR13.
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Here, we have investigated how a subset of box C/D snoRNAs can modify multiple nucleotides within the rRNA target region using a single guide and C΄/D΄ motif. Our data indicate that this is primarily achieved using unusual C΄/D΄ motifs. The established rule is that the position in the rRNA five nucleotides upstream of the D or D΄ box is methylated (Figure 1A) (25). However, the U18 and snR48 C΄/D΄ motifs, when used in an artificial snoRNA construct, direct the modification of multiple sites in the target region, while the snR13 C΄/D΄ motif directed the modification of the position in the rRNA six nucleotides upstream of the ‘canonical’ D΄ box. The snR48 snoRNA contains a long and unusual D΄ box that lacks a sequence comparable to the consensus and we predict contains both a four and six nucleotide long D΄ motif. In snR13 and U18, the D' motif lacks the C at the 5΄ end (CUGA) which our data indicate is not essential for the level of modification but is important for the correct selection of the target nucleotide. We propose that the snR13 and U18 snoRNAs contain two, overlapping four and five nucleotide long D΄ boxes. The five nucleotide long D΄ boxes include the last (3΄) nucleotide of what is considered the guide region (Figures 2B and 5B). We showed that having a C at the last nucleotide of the guide, which is found naturally in snR13, effectively lengthens the D΄ box by one nucleotide and causes methylation of the target site at a position one nucleotide further away in the target rRNA. Therefore, a C at this position in the guide would be predicted to interfere with target specificity. This is supported by our observation that a C at this position is significantly under-represented in the active guide/D΄ motifs of yeast snoRNAs. The D΄ box has always been considered to function as part of a ‘molecular ruler’ in defining the nucleotide for 2΄-O-methylation. Our data, however, indicate that the 5΄ end of the D΄ box, in particular, is the element that determines which nucleotide will be modified. We propose that there are two, overlapping D΄ boxes in snR13, U18 and snR48, which form alternative interactions with the C’ box, and depending on which D΄ box is recognised/used, this determines which nucleotide is modified. One explanation for the ability of these snoRNAs to direct the modification of multiple sites in target region is that each snoRNA can form two structural isoforms, with each capable of modifying a single, distinct, nucleotide. While we believe that the structural isoforms will be stable, especially when the proteins are bound, and two sub-populations of snoRNP exist. However, we cannot rule out the possibility that the snoRNP can alternate between the two conformations.
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The D΄ box interacts with the C΄ box to form a protein-binding site that functions to position multiple proteins, including the catalytic subunit fibrillarin/Nop1, onto the snoRNA. Based on the structure of the Archaeal box C/D sRNPs (22), both the C/D and C΄/D΄ motifs are bi-partite structures. The GA base-pairs and the first U in the C/C΄ box, form the L7Ae (Snu13 in yeast) binding site (Figure 6A and B). Stem II is bound by Nop5 (Nop58 or Nop56 in yeast). Importantly, the only sequence specific contacts between Nop5 and stem II are between Q296 and R339 in the Nop domain of Nop5 the C in the D/D΄ box and the last GA in the C/C΄ box (Figure 6A and B). Nop5 is homologous to both Nop56 and Nop58 and the Q296 and R339 are evolutionarily highly conserved. We therefore assume that Nop56 would interact with stem II of the eukaryotic C΄/D΄ motif in a similar manner. The catalytic subunit, fibrillarin (Nop1 in yeast) does not contact the C/D or C΄/D΄ motifs and is held in position by its interaction with Nop5. Assuming that this is also the case in eukaryotes, the docking site of Nop56 on the C΄/D΄ motif would therefore dictate where Nop1 is positioned on the substrate RNA (Figure 6A). Based on our data, the C at the 5΄ end of D box appears a major determinant for Nop56 binding and moving this C one nucleotide upstream in the snoRNA causes a similar move in the position of Nop1 on the target rRNA and therefore a one nucleotide shift in the target nucleotide. Figure 6C shows the predicted association of Snu13, Nop56 and Nop1 (fibrillarin) on the artificial snoRNA containing the hU24 C΄/D΄ motif to demonstrate this. Interestingly, only one hydrogen bond is predicted to form between the D΄ box C nucleotide and Nop56, while four hydrogen bonds are expected between Nop56 and the G and A in box C΄. From this we predict that the importance of the C in the D΄ box lies, in part, in positioning the G and A in the C΄ box and therefore creating the Nop56-binding site. Our data indicate that the use of alternative D΄ motifs, which differ in the use of a ‘normal’ and extended D΄ box, accounts for the modification of two nucleotides in the target region by snR13, snR48 and U18. We believe that, for each snoRNA, the cell contains two distinct snoRNPs, which differ in the folding of the C΄/D΄ motif, based on the D΄ box used, which in turn, alters the binding site of Nop56 to the snoRNA. Figure 6D shows the predicted association of Snu13, Nop56 and Nop1 (fibrillarin) with the two alternative structures of the U18 C΄/D΄ motif to illustrate this point. As Nop56 positions Nop1 in the snoRNP, the alternative binding of Nop56 leads to different positioning of Nop1 in the two snoRNPs, relative the rRNA, and therefore results in the modification of different nucleotides in the target region. Furthermore, our data fit nicely with the archaeal structure and support the idea that RNA–protein contacts in the eukaryotic snoRNP will be very similar to those seen in the archaeal box C/D sRNP.
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Interaction of Nop56 with stem II of the C΄/D΄ motif dictates the site of 2΄-O-methylation. (A) Schematic model of the Archaeal C΄/D΄ motif and guide region base-paired to a target rRNA (shown in red). The box C/D snoRNP proteins are represented as grey filled ellipses. The black dot indicates the active site of fibrillarin (Nop1 in yeast) and is positioned over the nucleotide to be modified. The Q and R in Nop5 represent amino acids Q296 and R339 that make contact with stem II of both the C/D and C΄/D΄ motif motifs. Stem II is the C΄/D΄ motif is shown in white on a red background. The upper part of the C΄/D΄ motif, which is bound by L7Ae, is shown in white with a black background. (B) Recognition of stem II of the box C/D motif by the Nop domain of Archaeal Nop5 (22). Cartoon views of the relevant regions of Nop5 and L7Ae are shown. Amino acid side chains are only shown for Q296 and R339. The snoRNA is shown in cartoon form and only the C΄/D΄ motif is shown for clarity. Stem II is shown in red and the upper part, bound by L7Ae, is shown in dark grey. The identity of the nucleotides in stem II is indicated. Hydrogen bonds between Q296 and R339 I Nop5 and stem II of the C΄/D΄ motif are shown in yellow. (C) Organisation of the snoRNP proteins on the artificial snoRNA containing the hU24 C΄/D΄ motif and the D΄ box insertions presented in Figure 4. The schematic organisation is the same as in (A) except the whole C΄/D΄ motif is shown in white with a black background. Note the slight, one nucleotide shift, in the position of Nop56, and he corresponding change in Nop1 position, in the complex based on the recognition of stem II in the C΄/D΄ motif. (D) Organisation of the snoRNP proteins on the U18 snoRNA based on the canonical and alternative secondary structures presented in Figure 2B. The schematic organisation is the same as in (C).
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We have also shown that the combination of the unusual C΄/D΄ motif together with the extra base-pairing function together to target the two adjacent nucleotides (L2280 and L2281) in the 25S rRNA by snR13. The extra base-pairing interaction, with it overlapping with the guide region, could also influence the structure of the complex as well as increasing the efficiency of rRNA methylation. However, we have found several instances of overlap between guide and extra-base-pairing interactions in snoRNAs that modify a single site. Extra base-pairing clearly enhances modification at both sites, although the reason why modification at L2281 is more dependent on this than 2΄-O-methylation at L2280 is unclear.
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Taken together, our data provide clear examples of how one snoRNA can modify multiple nucleotides in the target region by forming two different snoRNP complexes that differ in the positioning of Nop56 and Nop1 (fibrillarin) in the complex. This is different to the normal approach taken by snoRNPs, in which two separate guide regions are used to target different nucleotides. It is clear from our data that the unique D΄ box, in particular with snR13, is evolutionarily conserved and we believe that this scenario is not just found in the S. cerevisiae snoRNAs, but will be seen in most yeasts and potentially other eukaryotes. Indeed, evidence suggests that human U24 is also capable of modifying multiple sites within one target region (25). Therefore, with minor changes to the C΄/D΄ motif box C/D snoRNPs can be adapted to increase the complexity of rRNA modification without the need for additional snoRNAs.
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The retina is the primary light detecting tissue in mammals and performs an essential role in vision. The retina is organised into three cellular layers containing six major neuronal cell types, each tasked with performing different functional roles12. Rods and cones of the outer retina detect light, and are modulated by feedback inhibition from horizontal cells. Bipolar cells and amacrine cells of the inner retina modulate and integrate rod and cone driven signals and provide synaptic input to retinal ganglion cells (RGCs) that ultimately project light information to retinorecipient areas of the brain. Müller cells are the major glial cell type of the retina and provide homeostatic and metabolic support for retinal neurons, and may also perform roles in transmission of light to outer retinal photoreceptors34. Like all neuronal tissues, the cells of the retina use changes in membrane potential and intracellular ion concentrations to generate and transmit electrical signals, and ultimately encode visual information. However, the signalling pathways of the retina are highly complex and the precise roles performed by distinct classes of ion channels are currently unknown. Most notably, the K+ ion channels responsible for regulating the resting membrane potential and cellular excitability of retinal ganglion cells (RGCs) remain to be determined. RGCs are the first cells in the visual pathway to encode light as tonic and transient patterns of action potential firing5 and are required to maintain responses over a wide range of light intensities6. The regulation of RGC excitability is therefore fundamental to preventing signal saturation and increasing the dynamic range of the retina. Furthermore, different components of the visual signal are encoded by distinct subtypes of RGC which show characteristically different levels of sustained activity and responses to light (sustained and transient ON, OFF and ON-OFF responses for example)27. However, the mechanisms that set resting membrane potential and regulate these differing levels of tonic and transient activity in RGCs remain to be fully determined89.
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The importance of K+ leak currents to resting membrane potential and neuronal function was first proposed in the original Hodgkin-Huxley model of action potential generation10. The continuous efflux of K+ ions across the cell membrane is essential for setting a hyperpolarised resting cell membrane potential and directly influences the likelihood, duration and frequency of action potential firings1112. However, it was not until the late 1990’s, and the discovery of the two-pore domain (K2P) potassium channels1314, that the ion channels responsible for generating background leak K+ currents were identified. K2P channels are characterised by the presence of two pore forming regions and four trans-membrane spanning (4TMS) regions in each channel subunit and unlike other classes of K+ channels form functional dimers (not tetramers). Typically these channels elicit spontaneously active, outwardly rectifying ‘background leak’ type K+ conductances and show no classical time-dependent or voltage-dependent activity111516171819.
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To date at least 15 different K2P channels have been identified in mammals, that can be broadly split into six subfamilies according to their biophysical characteristics and pharmacological properties1115171820. These include the weak inward rectifiers (TWIK-1, TWIK-2 and TWIK-3), acid sensitive rectifiers (TASK-1, TASK-3, and TASK-5), lipid sensitive mechano-gated channels (TREK-1, TREK-2 and TRAAK), halothane inhibited channels (THIK-1 and THIK-2), alkaline sensitive channels (TALK-I, TALK-2 and TASK-2) and the fatty acid inhibited calcium activated channel (TRESK). In addition to important biophysical stimuli, such as pH, temperature and mechanical pressure, K2P channels are also targets for a range of clinically important drugs including inhalational and local anaesthetics, anti-psychotics, anti-depressants and neuroprotective agents (for reviews see refs 19, 21, 22, 23, 24, 25). K2P channels are also widely modulated by G protein signalling pathways and show sensitivities to a diverse array of second messenger systems111517182627. K2P channels are therefore capable of fine-tuning levels of cellular excitability under a wide range of biochemical and physiological conditions, and can be considered as central regulators of neuronal activity. Alternate splicing28293031, alternative translation initiation32, and hetero-dimerisation of K2P channel subunits333435 further increases the level of functional complexity achievable by K2P channels.
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At least one member of the K2P channel family has been identified in all mammalian cells investigated (neuronal and non-neuronal), with numerous cell types shown to express multiple K2P channels simultaneously (for example see ref. 36). K2P channels have been assigned prominent roles in many physiological systems, including cardiovascular3738, pain3940, respiration41, hearing4243, taste44, anaesthesia224546 and sleep474849. K2P channels have also been implicated in a number of pathological conditions, including autoimmune and degenerative diseases50, tumourgenesis5152, mental retardation (Barel-Birk-syndrome)53, migraine54, ischemia465556, epilepsy46 and depression465758. However, despite the accepted importance of K2P channels to neuronal function12161759, the expression and role of these channels in the retina remains largely unexplored. To date only one study has confirmed a role for K2P channels in the retina. Ford et al.60, have shown that TREK-1 contributes to slow after-hyperpolarisation events and regulates the frequency of retinal waves within starburst amacrine cells during early postnatal development. However, this study did not investigate the role of TREK-1 (or other K2P channels) in the adult retina.
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In this study we have used qPCR and immunohistochemistry to conduct the first comprehensive study of K2P channel expression in the mouse retina. We show that K2P channels are widely expressed in the retina, with multiple K2P channels detected within Müller cells and retinal ganglion cells. These data offer new insight into the mechanisms that regulate electrical activity within the retina and indicate that K2P channels likely perform important physiological functions within visual signalling pathways.
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Quantitative PCR analysis shows widespread expression of K2P channel mRNA in the wildtype mouse retina (n = 5, P135, tissue collected at Zeitgeber time ZT8, 8 hours after light onset) (Fig. 1). The highest levels of mRNA expression were detected for TWIK-1, TASK-1, TRAAK, and TRESK, with mRNA transcripts for TWIK-2, TWIK-3, TREK-1, TREK-2, TASK-3, TASK-5 and THIK-1 detected at lower levels. mRNA encoding TASK-2, THIK-2 and TALK-1 were not detected in retina cDNA samples (as determined by a lack of measurable CT value after 40 cycles of PCR). Levels of K2P channel mRNA expression are seemingly highly dynamic in the mouse retina with developmental and circadian variation of expression detected for nearly all channels investigated (Supplementary Figure 1). For the majority of K2P channels, including TWIK-2, TREK-1, TRAAK, TASK-1, TASK-3, TASK-5, and TRESK, a clear up regulation of mRNA expression was detected throughout postnatal development with expression typically reaching maximal levels by P14. By contrast, TWIK-1 and TASK-2 were expressed at higher levels early during postnatal development (all tissue collected at ZT8) (Supplementary Figure 1A). Furthermore, numerous K2P channels were found to exhibit rhythmic patterns of mRNA expression under 12:12 light dark cycles (Supplementary Figure 1B). For the majority of channels, including TWIK-1, TWIK-2, TRAAK, TASK-1, TASK-3 and TASK-5, levels of mRNA expression were highest during the subjective night and typically lowest 8 hours after light onset (ZT8). In contrast, TREK-1 and TRESK showed opposing patterns of expression, with mRNA for these channels peaking at ZT8.
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Following qPCR analysis, immunohistochemistry was performed with anti-K2P channel antibodies to confirm the expression and localisation of K2P channel proteins within the mouse retina. Overall our data show that TWIK-type, TREK-type and TASK-type channels are widely expressed in the mouse retina, with the highest levels of expression detected within retinal ganglion cells (TASK-1, TREK-1, TWIK-1, TWIK-2, TWIK-3, and to a lesser extent TREK-2, TRAAK, and TRESK) and Müller cells (TWIK-1, TASK-3, TRAAK, and TREK-2) (Figs 2, 3, 4, 5, 6, results summarised in Table 1).
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TWIK-1; Expression of TWIK-1 was detected in numerous cell types of the adult mouse retina (Fig. 2), and showed a different pattern of expression throughout postnatal development (Supplementary Figure 2). In the adult retina, TWIK-1 immunoreactivity was detected predominantly in Mϋller cells and a subset of cells located in the ganglion cell layer (GCL) (Fig. 2A–C). The intensity of TWIK-1 immunoreactivity within Müller cells was found to be somewhat variable across the adult retina, with areas of high and low expression often observed in the same retina sections. Based on our analysis it was not possible to determine the extent or patterning of this distribution across the entire retina. Double labelling for the retinal ganglion cell marker Brn3a (brain-specific homeobox/POU domain protein 3A) that is expressed in the majority, but not all classes of retinal ganglion cells61, confirms the expression of TWIK-1 within 30.7% of RGCs (68 of 196 cells counted), but was also detected in a number of Brn3a negative cells (Fig. 2D–F). In addition to expression of TWIK-1 in Mϋller cells and RGCs of the adult retina, we also observed TWIK-1 immunoreactivity during early development in a population of cells located in the middle of the neuroblastic cell layer, resembling developing horizontal cells (Supplementary Figure 2). Immunoreactivity was weak in these cells at P3, and was increased by P5. By P10 the morphology of these cells clearly resembled horizontal cells, with strong labelling of processes evident in the forming outer plexiform layer. TWIK-1 immunoreactivity was absent from these presumed horizontal cells after P10. Although expression of the RGC marker Brn3a was detected as early as P0, TWIK-1 immunoreactivity was absent from these developing ganglion cells prior to P10 and shows a significant increase by P14 and P30 (Supplementary Figure 2). TWIK-1 immunoreactivity was absent from Müller cells during early postnatal development (Supplementary Figure 2).
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TWIK-2; TWIK-2 immunoreactivity was consistently detected in cells of the GCL (Fig. 2G,H). Double labelling with Brn3a confirms these cells to be RGCs, with TWIK-2 immunoreactivity detected for 60.8% (73 of 120 cells counted) of all Brn3a positive RGCs in the adult retina including RGCs with multiple distinct morphologies (Fig. 2I). Typically, the highest level of TWIK-2 immunoreactivity was observed along dendrites of immunoreactive cells, with lower levels of immunoreactivity observed for cell bodies. Consistent with qPCR analysis (Supplementary Figure 1), levels of TWIK-2 expression are low during early postnatal development with TWIK-2 immunoreactivity not detected within RGCs prior to P10, and increased by P14 and P30 (Supplementary Figure 3). TWIK-3; TWIK-3 immunoreactivity was observed for 50.5% (54 of 107 cells counted) of cells within the ganglion cell layer of the adult retina (Fig. 2J–L). TWIK-3 immunoreactivity was largely restricted to the cell membrane of reactive cell bodies, with only minimal labelling detected along cellular process. However, due to species limitations it was not possible perform double labelling with this TWIK-3 antibody and the Brn3a antibody used to identify RGCs (both raised in goat).
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TASK-1; Of all the K2P channel antibodies tested, the highest levels of immunoreactivity were observed for TASK-1 (Fig. 3). In adult retina TASK-1 immunoreactivity was restricted to the inner retina, with the highest levels of staining detected for cells located in the GCL (Fig. 3A–C). Double labelling with Brn3a and TASK-1 antibodies confirmed the expression of TASK-1 in 67.4% of RGCs (91 of 135 cells counted) with high levels of TASK-1 immunoreactivity detected on the cell bodies and also along the dendrites of labelled cells (Fig. 3D–F). Lower levels of TASK-1 staining were also observed for a subset of cells located in the INL, consistent with the location of amacrine cells (Fig. 3A). TASK-1 immunoreactivity was detected throughout postnatal development. Consistent with our qPCR data, low levels of TASK-1 immunoreactivity were observed for Brn3a positive RGCs as early as P0, with levels of TASK-1 staining increasing through postnatal development and reaching maximal levels by P14 (Supplementary Figure 4). In addition, during postnatal development TASK-1 immunoreactivity was also observed for cells located in the neuroblastic cell layer, with morphologies resembling developing horizontal cells. TASK-1 immunoreactivity was evident in these cells only between P3 and P10, was absent from these cells by P14, and was not detected in P30 adult samples (Supplementary Figure 4).
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TASK-3; TASK-3 immunoreactivity was predominantly observed for Müller cells (Fig. 3G), where expression of TASK-3 within Müller cells was confirmed by double labelling for the Mϋller cell marker glutamine synthetase62 (Fig. 3G–I). TASK-5; Due to the low levels of TASK-5 mRNA detected in the mouse retina we have not investigated the expression and distribution of TASK-5 protein.
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TREK-1; TREK-1 immunoreactivity was detected for multiple cell types in the adult mouse retina (Fig. 4). The highest levels of TREK-1 immunoreactivity were observed for cells located in the GCL (Fig. 4A,B), with 63.6% (75 of 118 cells counted) of Brn3a positive RGCs labelled for TREK-1 (Fig. 4D–F). Weaker labelling of TREK-1 was also detected for a number of cells located on the inner surface of the INL, likely amacrine cells (Fig. 4A), and a number of cells positioned towards the outer surface of the INL with morphologies resembling horizontal cells (Fig. 4C). TREK-1 immunoreactivity was also detected in the outer retina, with TREK-1 labelling observed for photoreceptor outer segments and also photoreceptor pedicles located in the outer plexiform layer (OPL) (Fig. 4A). Consistent with qPCR analysis (Supplementary Figure 1), expression of TREK-1 protein was not detected in the retina prior to P10 (Supplementary Figure 5).
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| 100.0 |
TREK-2; TREK-2 immunoreactivity was detected predominantly within Mϋller cells (Fig. 4G,H and J,K). However, low levels of TREK-2 immunoreactivity were also observed for a number of cells located in the GCL (Fig. 4H and K) and also the INL (typically only 3–5 cells per retina section) (Fig. 4J), including 30.3% (30 of 99 cells counted) of Brn3a positive RGCs (Fig. 4L). TRAAK; The pattern of TRAAK immunoreactivity observed in the adult mouse retina was highly similar to that observed for TREK-2 (Fig. 5). TRAAK immunoreactivity was detected at high levels within Mϋller cells (Fig. 5A,B), with lower levels of staining observed for a subset of cells located in the GCL (Fig. 5B) and INL (Fig. 5C). Low levels of TRAAK immunoreactivity were detected for 15.5% (14 of 90 cells counted) of Brn3a positive RGCs. (Fig. 5D–F). Consistent with our qPCR data, TRAAK immunoreactivity was not observed in the retina prior to P14.
|
study
| 100.0 |
TRESK; Despite the high levels of TRESK mRNA detected by qPCR analysis, the levels of TRESK immunoreactivity detected in the adult mouse retina were low with the antibody used in this study (Fig. 6A–C). TRESK immunoreactivity was limited to a small number of cells in the GCL, typically only 4–6 cells per section. However, positive staining with this antibody was inconsistent between different retina samples.
|
study
| 100.0 |
TASK-2; Our qPCR analysis indicates only minimal expression of any TALK type channels in the adult mouse retina. Consistent with our mRNA studies, we could not detect expression of TASK-2 protein in the adult mouse retina with the antibody used in this study (Fig. 6D). However, strong TASK-2 immunoreactivity was observed in the conjunctival epithelium which covers the outer surface of the sclera (not included in retina samples used for mRNA analysis) (Fig. 6E,F). Collectively, our data indicate a lack of TASK-2 expression in the adult mouse retina. TALK-1 and THIK type channels; Due to lack of detectable mRNA expression in the retina we have not investigated the expression of TALK-1 protein, nor the expression of THIK type channel proteins in the mouse retina.
|
study
| 100.0 |
This study represents the first comprehensive investigation of two-pore domain (K2P) K+ ion channel expression within the mammalian retina. Our data indicate that mRNA transcripts for numerous K2P channels are detected in the mouse retina, including inwardly rectifying TWIK-type channels, acid sensitive TASK-type channels, arachidonic acid mechanosensitive TREK-type channels and calcium sensitive TRESK channels, with many K2P channel transcripts showing dynamic patterns of expression throughout the day and during postnatal development. Antibody labelling confirms the widespread expression of K2P channels in the mouse retina and indicates that the highest levels of K2P channel expression are observed in retinal ganglion cells and Müller cells. Overall, levels of K2P channel protein detected are broadly consistent with our mRNA studies in adult tissue and during postnatal development. Typically, channels showing high levels of mRNA expression resulted in high levels of convincing immunoreactivity (TWIK-1, TASK-1, TREK-1, TRAAK), whereas channels showing low levels of mRNA expression typically showed low or absent levels of protein expression (TASK-2). One notable exception was TRESK. Despite high levels of mRNA consistently detected by qPCR analysis (and by gene microarray analysis – Hughes et al., unpublished data) we detected only low levels of TRESK protein, with few cells convincingly labelled (including samples collected at various circadian time points). The reasons for this discrepancy are not clear, but likely reflect technical limitations of the antibody used.
|
study
| 100.0 |
There have been a small number of previous reports indicating the expression of certain K2P channels in the mammalian retina, most commonly as part of the initial tissue panel screen conducted following cloning of the specific channel subunits. For example, expression of TRAAK in the mouse retina has previously been confirmed by RT-PCR and in situ hybridisation63 whereas RT-PCR and immunohistochemistry indicate expression of TWIK-3 (previously termed TWIK-2) in the ganglion cell layer of the mouse retina64. However, in both cases the specific cell types expressing these channels has not been determined. A further report has indicated that TASK-2 (a TALK type channel) is expressed in the majority of ganglion cells and both dopaminergic and cholinergic amacrine cells of the rat retina65. Our data are largely consistent with these previous reports. In agreement with Fink et al.63, TRAAK was identified in the mouse retina, although we now confirm this expression is largely restricted to Müller cells with lower levels of expression detected for RGCs. We also confirm that TWIK-3 is expressed within RGCs as previously indicated64. However, contrary to previous reports in the rat retina, we did not detect TASK-2 in the adult mouse retina using either qPCR or immunostaining methods. We did however detect TASK-2 mRNA in the postnatal mouse retina, potentially indicating different roles for TASK-2 in the mouse and rat retina. In addition to validating these earlier studies, our data show that the expression of K2P channels in the mammalian retina is highly complex with multiple K2P channels detected within RGCs and Müller cells.
|
study
| 100.0 |
Our data indicate that at least five and possibly as many as eight distinct K2P channels may be expressed within RGCs, including inward rectifying TWIK-type channels, acid sensitive TASK-type channels and arachidonic acid mechanosensitive TREK/TRAAK type channels. Based on levels of immunoreactivity, and the number of positively stained cells, TASK-1 is seemingly expressed at the highest levels, followed by TREK-1, TWIK-2, TWIK-1 and TWIK-3, with TREK-2 and TRAAK detected at only at low levels and TRESK only rarely (and inconsistently) detected. Based on the high number of positively stained cells observed for several K2P channel antibodies, it is highly likely that individual RGCs express multiple K2P channels simultaneously - likely generating complex profiles of K+ leak conductances within these cells36. Further work will be required to determine the precise functional roles performed by K2P channels within RGCs. However, based on their biophysical properties and known roles in other cell types we might expect K2P channels to make significant contributions to setting resting membrane potential and the regulation of action potential firing, as well as potentially performing roles in signal desensitisation and adaptation111666. In addition to their originally prescribed role as background leak channels it is now becoming clear that the function of many K2P channels is far more complex16. K2P channels may contribute directly to action potential waveforms and drive repolarisation of rapidly firing neurones16, with TASK-1 and TREK-1 capable of supporting action potential generation in the absence of voltage gated K+ channels67. It is therefore possible that K2P channels perform a number of diverse roles in RGCs, regulating both the likelihood and also the nature of electrical signalling events.
|
study
| 99.94 |
Based on our data the membrane potential of RGCs, and therefore levels of excitability, are likely sensitive to a wide range of physiological and pharmacological factors to which K2P channels show sensitivities. For example TASK-1 channels are characteristically sensitive to changes in extracellular pH and hypoxia686970, whereas TREK-1 channels (and TREK-2 and TRAAK) are mechanosensitive, temperature sensitive, and are directly modulated by lysophospholipids and polyunsaturated fatty acids (PUFAs)27467172. By contrast TWIK channels typically show lower levels of modulation compared to other K2P channels and can be considered as more typical K+ leak channels16. It would therefore seem that K2P channels are well placed to act as central regulators of RGC excitability (and therefore photosensitivity) under a wide range of conditions. We propose that the differential profile of K2P channel expression likely contributes to the functional diversity of RGC subtypes7, and offers a potential mechanism to fine tune the functional properties of individual RGCs under specific physiological conditions. Further work will be required to determine if the differential expression of K2P channels contribute to the different levels of sustained and transient activity observed from distinct subtypes of RGCs9.
|
study
| 100.0 |
It is interesting to note that the majority of K2P channels show an up-regulation of expression in the retina between P10 and P14, at a similar time point to the functional maturation of visual pathways of the mouse retina7374. This observation may indicate that K2P channels perform important roles in vision. Glutamate is the key neurotransmitter by which bipolar cells transmit rod and cone derived signals to RGCs757677, and a previous study has described the presence of a glutamate sensitive background leak type K+ current in cultured mouse RGCs with properties of a TASK like current, most likely TASK-1 or TASK-378. Inhibition of this TASK-type current by the group I mGluR agonist (S)-3,5-dihydroxyphenylglycine (DHPG) results in the depolarisation of retinal ganglion cells and increased levels of action potential firing, suggesting a significant role for TASK type channels in the regulation of RGC excitability by glutamate. Based on the results of our immunostaining data it would seem likely that TASK-1 channels, and not TASK-3 channels, may be responsible for the K+ leak current identified by these authors. However, in addition to TASK-1 (and TASK-3), several other K2P channels are known to be modulated by glutamate signalling pathways, including TREK-1 and TREK-2798081. It is therefore likely that K2P channels may mediate complex responses to glutamate within RGCs via multiple mechanisms.
|
study
| 100.0 |
Compared to RGCs, only low levels of K2P channel expression were detected within other retinal neurones, including photoreceptors, horizontal cells, bipolar cells and amacrine cells. This pattern of expression is potentially in keeping the nature of electrical activity observed within the retina. With the exception of RGCs (and a few specialised subtypes of bipolar cells82 and amacrine cells8384), the majority of retinal cell types do not classically encode light signals as patterns of action potential firing but instead show graded changes in membrane potential28586. It is therefore possible that these cell types show less functional reliance on K+ leak currents than typical spike firing neurones, such as RGCs. Our data do however indicate the expression of at least four distinct K2P channels within Müller cells, including TWIK-1, TASK-3, TRAAK, and TREK-2. A previous study has reported the presence of a pH sensitive background leak K+ current in Müller cells of mice (and also rat and guinea pig)87, and expression of multiple K2P channels have been reported in Müller cells of the amphibian retina (Rana pipiens) where they have been shown to perform roles in cell volume regulation and responses to retinal ischemia8788. Based on our data it is possible that TWIK-1, TASK-3, TRAAK and TREK-2 may perform similar roles in Müller cells of the mammalian retina, and that TASK-3 may be responsible for the pH sensitive current previously described.
|
study
| 100.0 |
In summary we have shown that K2P channels are widely expressed within the adult mammalian retina, with the highest levels of expression detected within RGCs and Müller cells. Our data suggest that K2P channels likely perform important roles in retinal function and vision, and likely contribute significantly to the resting membrane potential and cellular excitability of retinal ganglion cells under a diverse array of physiological conditions. The prominent role of K2P channels in neuroprotective pathways45465689 offers new potential avenues of research into the treatment of retinal disease. Notably, K2P channels may represent valuable targets for manipulation of resting membrane potential and suppression of pathological increases in spontaneous spike firing rates observed from RGCs following retinal degeneration909192.
|
study
| 99.94 |
All animal procedures were performed in accordance with the United Kingdom Animals (Scientific Procedures) Act of 1986 and the University of Oxford Policy on the Use of Animals in Scientific Research. All experiments were approved by the University of Oxford Animal Welfare and Ethical Review Board, and were conducted under PPL 30/3068.
|
other
| 99.94 |
C3H mice (C3H/He; not carrying rd mutation)93 were housed under a 12:12 LD cycle with food and water ad libitum. For initial qPCR and antibody analysis eyes (n = 5, P130–135) were collected at Zeitgeber time ZT8 (8 hours after light onset) and processed as described below. Developmental and circadian samples (mRNA and retina sections) were originally collected as part of a previous study94. Developmental samples were collected from wildtype C3H/He mice at P0, P3, P5, P10, P14 and P30 (n = 6) at ZT8. Circadian samples were collected from wildtype C3H/He mice (>P45) at ZT3, ZT8, ZT13, ZT18 and ZT23 (n = 6).
|
study
| 100.0 |
Following enucleation, retinae were dissected, flash frozen on dry ice and stored at −80 °C prior to use. Tissue was homogenised in TRIzol Reagent (Life Technologies) and total RNA isolated using RNeasy spin columns (Qiagen) with on column DNase treatment (Qiagen). 1 μg of total RNA was reverse transcribed using SuperScript III with oligo(dT)20 primers (Life Technologies) and quantitative PCR performed using Quantifast Sybr Green PCR mastermix (Qiagen) on a StepOne thermal cycler (Applied Biosystems) as described previously95. Quantification of transcript levels was performed using a comparative CT approach with levels of target gene expression normalised to the geometric mean expression of three house-keeping genes96. K2P channel primers were designed using PrimerBlast (NCBI). Primer sequences are shown in Table 2.
|
study
| 100.0 |
Preparation and labelling of retina cryostat sections was performed as described previously9798. Briefly, 18 μm sections were permeabilised with 0.2% Triton-X100 (Sigma) for 20 minutes, blocked with 10% normal donkey serum (Sigma) before incubation with primary antibodies for 24 h at 4 °C. Details of all antibodies used are shown in Table 3. Secondary antibodies were donkey anti-rabbit, donkey anti-goat and donkey anti-mouse labelled with Alexa488 and Alexa568 fluorophores (Life Technologies) incubated at 1:200 for 2 h at RT. All antibodies were diluted in PBS containing 2% normal donkey serum and 0.2% Triton-X100. Sections were mounted with Prolong Gold anti-fade media containing DAPI (Life Technologies).
|
study
| 50.53 |
Fluorescence images were collected using an inverted LSM 710 laser scanning confocal microscope (Zeiss) and Zen 2009 image acquisition software (Zeiss). Individual channels were collected sequentially. Laser lines for excitation were 405 nm, 488 nm and 561 nm, with emissions collected between 440–480, 505–550 and 580–625 nm for blue, green and red fluorescence respectively. Typically, images were collected using a x40 objective with images collected every 1 μm in the z-axis. Global enhancement of brightness and contrast was performed using ZenLite 2011 software (Zeiss).
|
other
| 99.9 |
The percentage of retinal ganglion cells (RGCs) showing K2P channel immunoreactivity was determined by manual counting of adult retinal sections co-stained for the RGC marker Brn3a (brain-specific homeobox/POU domain protein 3A) and relevant K2P channel antibodies. Data values shown represent pooled analysis from counting cells from randomly chosen areas of multiple sections (>10) collected from n = 3 mice at P30.
|
study
| 99.94 |
Eumeninae or potter wasps are the largest subfamily of the Vespidae with 3773 valid species in 205 genera (Carpenter 1986; Zhou et al. 2011; Tan et al. 2015, 2018a; Pannure et al. 2016; Carpenter unpubl.). Eumeninae have a cosmopolitan distribution and are morphologically very diverse. The generic classification of Eumeninae is chaotic and has a troubled taxonomic history. The extreme splitting haphazardly pursued during much of the 20th century has contributed much to this current state (Hermes et al. 2014). Clearly, the situation with the generic classification will have to be rationalized by future synonymy of numerous taxa after their phylogeny is better known (Carpenter and Cumming 1985; Carpenter and Garcete-Barrett 2003; Hermes et al. 2014). The need for taxonomic work on Eumeninae is underlined by the lack of adequate and well-illustrated keys, both to genera and to species (Pannure et al. 2016). The few generic keys available concern one region or a country: Yamane (1990) revised the Japanese fauna of Eumeninae with a key to 18 genera, Carpenter and Garcete-Barrett (2003) presented a key to the genera of Neotropical Eumeninae and Pannure et al. (2016) included a key to the 31 eumenine genera known from South India. We present the first illustrated key to genera of Eumeninae from a major area encompassing two faunal regions and the first complete key to genera of Chinese Eumeninae. It is a major step to facilitate the classification of Chinese Eumeninae. Nevertheless, the status of several genera remains problematical; only a combined approach using molecular, biological, and morphological data will make it possible to decide their taxonomic position.
|
study
| 99.5 |
The Chinese Eumeninae were first catalogued by Liu (1936–1937) resulting in a list of 57 species divided among nine genera. Unfortunately, his research stopped after his only revision (Pareumenes; Liu 1941). Lee (1982a, 1985) published the most recent key to the genera of Eumeninae in China, including only 25 genera (for 65 species and 13 subspecies). Finally, Zhou et al. (2011) listed 45 genera present in China and included 172 species and 50 subspecies. Several scattered papers have been published on Chinese Eumeninae, but a thorough inventory is lacking (Zhou et al. 2012, 2013; Li and Chen 2014a, 2014b, 2015, 2016a, 2016b; You et al. 2013; Ma et al. 2016, 2017; Nguyen and Xu 2014; 2015; 2017; Yeh and Lu 2017; Tan et al. 2018a). The illustrated key to the genera of Chinese Eumeninae presented here includes 51 genera and the checklist contains 267 species and subspecies in total. One genus (Nortozumia van der Vecht, 1937) is reported as new to China. Two replacement names are proposed for junior primary homonyms: Ancistrocerus rufofrustius Tan & Carpenter, nom. n. replacing Ancistrocerus rufopictus (Kostylev) and Orientalicesa confasciatus Tan & Carpenter, nom. n. replacing Orientalicesa unifasciatus (von Schulthess, 1934).
|
review
| 99.8 |
Specimens were collected by hand net or with Malaise traps. The studied specimens are deposited in the collections of College of Life Sciences, Northwest University, Xi’an (NWUX); Northwest A&F University Entomological Museum, Yangling, Shaanxi (NWAY); Zhejiang University Hymenoptera Museum, Hangzhou (ZJUH); General Station of Forest Pest Management, State Forestry Administration, Shenyang (GSFA); American Museum of Natural History, New York (AMNH); Naturalis Biodiversity Center, Leiden (RMNH); Museum national d’Histoire naturelle, Paris (MNHN); and Senckenberg Deutsches Entomologisches Institut, Müncheberg (SDEI).
|
other
| 99.94 |
Morphological terminology follows Carpenter and Cumming (1985), Yamane (1990), and Carpenter and Garcete-Barrett (2003). Observations and descriptions were made with an Olympus SZX11 stereomicroscope and fluorescent lamps. Photographic images were made with Keyence VHX-5000 digital microscope (NWUX, Xi’an), Olympus SZX 12 stereomicroscope with analySIS Soft Imaging System software (RMNH, Leiden), and Microptics-USA/Visionary Digital photomicrographic system, developed by Roy Larimer, multiple layers stacked using Helicon Focus (AMNH, New York).
|
other
| 99.9 |
Metasomal terga I-II, dorsal view: a Eumenes m. mediterraneus (Kriechbaumer) (left 1), Pseudozumia indica (de Saussure) (left 2), Calligaster cyanoptera de Saussure (middle) aa Antepipona deflenda lepeletieri (Blüthgen) (right 2), Symmorphus foveolatus (Gussakovskij) (right1).
|
other
| 99.9 |
Head and pronotum (a, e, aa, ee), part of mesonotum in dorsal view (b, bb, dd), metanotum magnified (d), and metasomal segment I in lateral view (c, cc): a–e Labus spiniger (de Saussure) aa, ee, lower cc Leptomicrodynerus tieshengi Giordani Soika bb, dd, upper cc Cyrtolabulus suavis van der Vecht.
|
other
| 99.9 |
Forewing (a, aa), metasomal sternum I (SI) (b, bb), head in dorsal view (c, cc) and hind tibia (d, dd). a–b Pareumenes quadrispinosus conjunctus Liu c, d Pareumenes s. sansibaricus (von Schulthess) aa–cc Pseumenes d. depressus (de Saussure); dd. Pseumenes depressus annulatus van der Vecht.
|
other
| 99.9 |
Maxillary palpus (a, a’ and aa), labial palpus of female (b, bb) and mandibles of male (c, cc, cc’). a–c Pterocheilus p. phaleratus (Panzer) a’ Pterocheilus c. chobauti Dusmet; aa–bb Onychopterocheilus mochii Giordani Soika cc Onychopterocheilus pallasii (Klug) cc’ Onychopterocheilus sp.
|
other
| 99.9 |
Head and pronotum in dorsal view (a, aa, aa’), part of mesosoma in dorsal view (b) and propodeum lateral view (c). a, c Stenodynerus c. chinensis (de Saussure) b Stenodynerus frauenfeldi (de Saussure) aa Stenodyneriellus sp. aa’ Brachyodynerus magnificus (Morawitz).
|
other
| 99.9 |
Head in frontal view (a, aa), metasoma in dorsal view (c, cc), anterior face of pronotum (b, bb) and antenna (d, dd). a–d Apodynerus troglodytes (de Saussure) aa, cc Antepipona silaos (de Saussure) bb Antepipona menkei Giordani Soika; dd. Antepipona rufescens (Smith).
|
other
| 99.9 |
Metasomal tergum I (a, aa) in dorsal view, propodeum in lateral view (b, bb), mesosoma in lateral view (c, cc) and metanotum in dorsal view (d, dd). a–d Leptochilus m. mauritanicus (Lepeletier) aa Gribodia confluenta (Smith) bb, cc Stenodyneriellus guttulatus (de Saussure) dd Stenodyneriellus sp.
|
other
| 99.75 |
Maxillary palpus (a left) and labial palpus (b right), mouthpart palpi (aa), head in dorsal view (b, bb), part of mesosoma in dorso-caudal view (c, cc, cc’). a–c Gribodia sp. aa, bb Stenodyneriellus guttulatus (de Saussure) cc Stenodyneriellus sp. cc’ Epsilon dyscherum (de Saussure).
|
other
| 99.9 |
With the development of ultrasound, more and more fetal anomalies can be detected in antenatal period. However, the experience of prenatal diagnosis of fetal intracranial tumors is very limited because of the low incidence. The imaging appearances of various congenital intracranial tumors still overlap, and the final diagnosis still depends on the pathological examination. So far we have found few literatures about prenatal diagnosis of congenital intracranial tumors.
|
review
| 98.1 |
Ultrasound (Fig. 1) showed that the tumor was 2.5 × 2.3 × 2.1 cm3 in size, located in the sellar region. It was regular shape and slightly heterogeneous solid mass with a little cystic component. No color flow was present inside the tumor but the peripheral encirclement by arterial circle of Willis. The lateral ventricles and the head circumference were normal. Fetal heart Tei-index was 0.32 (normal). The evaluation of fetal Middle Cerebral Artery (MCA) and umbilical artery (UA) was normal. The amniotic fluid was normal, and no other associated malformations were detected.
|
clinical case
| 99.94 |
Fetal ultrasonography performed in the 30th week of gestation showed a 2.5 × 2.3 × 2.1 cm3 slightly heterogeneous solid mass with a little cystic component (arrowhead) in the sellar region (A) with peripheral encirclement by arterial circle of Willis (B). The red and blue colors indicate the direction of blood flow (yellow arrowhead).
|
clinical case
| 99.94 |
Magnetic resonance imaging (MRI) which was taken subsequently confirmed the result of ultrasound. Meanwhile, it also provided more detailed information on the fetal central nervous system (CNS) including fetal brain dysplasia and the possible compression of optic nerves caused by the tumor (Fig. 2). The parents were informed that the most likely diagnosis was optical nerve glioma; however, the malignant intracranial tumor was difficult to be excluded prenatally.
|
clinical case
| 99.94 |
Fetal intracranial tumor was shown (red arrowhead) by axial view (A), sagittal view (B) and coronal view (C) of MRI. Fetal brain dysplasia (D) was diagnosed by the poor developed gyri and sulci of the frontal lobe (red arrowhead). MRI = magnetic resonance imaging.
|
clinical case
| 99.8 |
The pregnant woman underwent cord blood samplings because of the congenital malformations. Single-nucleotide polymorphism (SNP)-based chromosomal microarray analysis (CMA) (Fig. 3) was performed for prenatal genetic analysis used with fetal cord blood and parental blood samples after the normal chromosomal karyotype analysis was revealed. It detected a 0.72-Mb duplication at 4q35.2 in fetus which was associated with epilepsy (https://decipher.sanger.ac.uk/patient/290426#phenotype/patient-phenotypes) and cardiac anomalies (https://decipher.sanger.ac.uk/patient/288182#phenotype/patient-phenotypes). It encompassed the FRG1 and FRG2 genes. In addition, the CMA also revealed a 0.13-Mb deletion at 6q26 which was located inside the PARK2 gene. The mutation in the PARK2 gene (OMIM ID: ∗602544) is known to be related to autosomal recessive juvenile Parkinson disease. Neither the duplication nor deletion was inherited from the parents.
|
clinical case
| 99.94 |
Microarray testing results. (A) A 0.72-Mb duplication at chromosome 4q35.2 (red arrowhead) which encompassed the FRG1 and FRG2 genes. (B) A 0.13-Mb deletion in chromosome 6q26 (red arrowhead), which was located inside the PARK2 gene. The chromosome numbers and cytobands are shown and labeled on the right side. The view on the left side shows the detected segments, regions, and reference annotations in detail. Chromosomal duplication segments are denoted by upward triangle (blue), whereas deletion segments are denoted by downward triangle (red).
|
clinical case
| 99.44 |
Ultimately, the parents chose termination of pregnancy (TOP). The abnormal imaging findings were confirmed by autopsy (Fig. 4). The histological examination showed low-grade neuroepithelial tumor. A mixed neuronal-glial tumor was final diagnosis because 2 cell types (neuronal cells and glial cells) existed in the tumor. The diagnosis was confirmed by immunohistochemistry results.
|
clinical case
| 99.94 |
Congenital intracranial tumors as a group are quite rare, representing only 0.5% to 1.5% of all pediatric brain neoplasms, of which most were congenital intracranial teratomas.[4–8] Prenatal ultrasonography during the whole pregnancy is of particular importance for screening fetal central nervous system tumors. However, few examples of fetal intracranial mixed neuronal-glial tumors have been described by imaging and fewer cases have been confirmed by histopathological examination. Our case contributes to the limited literature focused on the imaging (ultrasonography and MRI), pathological and genetic discoveries of intracranial mixed neuronal-glial tumor in the prenatal period. Searching through the literatures, we only noticed that Chung et al reported a congenital gangliocytoma in 1998 which fell into this category of intracranial mixed neuronal-glial tumor. Its ultrasound features contained both cystic and solid components, located suprasellar and caused marked displacement of the circle of Willis.
|
clinical case
| 99.9 |
We have reviewed the literatures for fetal intracranial tumors which included primarily single case reports published in the last decade assessed by ultrasound (Table 1).[4,6,10–16] Cassart et al retrospectively analyzed imaging findings of congenital craniopharyngioma which was a different pathological type. It showed supra-sellar mass with color flow in its periphery which had the similar sonographic features as our case.
|
clinical case
| 99.4 |
Notwithstanding the ultrasonography has permitted description of fetal brain anomalies during the antenatal period, the imaging appearances of various congenital intracranial tumors still overlap. Subsequent prenatal MRI allows the confirmation of ultrasound findings and detection for other anomalies that may be present, in particular, intracranial tumor extension. It has been reported that more precise morphology could be provided by MRI at earlier stages of gestation, which makes earlier diagnosis and prompt initiation of treatment possible. Cassart et al noted that MRI was more sensitive than ultrasound for the detection of this heterogeneity. Although there are many advantages of MRI, it must be noted that fetal MRI does not replace ultrasound as a screening tool.
|
review
| 99.9 |
Recently studies on application of CMA for various fetal anomalies have also been published. It has been strongly suggested by the early onset of these neoplasms and their embryonal appearance that prenatal factors are important, especially genetic factors. So CMA was performed after fetal chromosomal karyotype analysis was normal. A 0.72-Mb duplication at 4q35.2 was detected in fetus which was associated with epilepsy. It is consistent with the fact that epilepsy is the most common symptom for intracranial neuroepithelial tumor. The CMA also revealed a 0.13-Mb deletion at 6q26 located inside PARK2 gene, and the PARK2 gene mutation has involvement in autosomal recessive juvenile Parkinson disease. The clinical phenotypes of this disease included shaking palsy, slow moving and myodystony, and so on. However, the microduplication at 4q35.2 and the microdeletion at 6q26 were still defined as being of uncertain clinical significance.
|
clinical case
| 99.9 |
Prenatal detection of mixed neuronal-glial tumors is very rare. Ultrasound and MRI are helpful for diagnosing intracranial tumors, but the precise histologic type of the tumor was depended on pathological examination. CMA should be necessary for the fetuses with congenital intracranial tumors. This finding not only provides information for clinical consultation but may also allow more accurate genetic diagnosis.
|
other
| 99.0 |
Clinical laboratory tests provide information to screen, diagnose, and manage patient health and disease risk and status. While fitness and physical activity are recognized as important contributors to health and attenuating risk for cardiovascular diseases , information regarding the influence of aerobic and strength exercise participation on laboratory test results is sparse. Because clinical laboratory tests quantify key physiologic systems, changes in laboratory test values in terms of exercise frequency and type may offer a way to quantify improved fitness and reduction of risk of important chronic diseases, such as cardiovascular disease. In addition, results are usually interpreted in accordance with reported reference intervals that were established based on the middle 95% of a healthy population with similar characteristics . However, some evidence suggests that physical exercise may affect levels of clinical laboratory tests, where results may fall outside of the reported reference intervals in highly trained athletes . Characterization of the effects of exercise on clinical laboratory tests may offer a way to assess the significance of such observations.
|
review
| 99.8 |
About 21% of the adult population in the United States meet the physical activity guidelines for both aerobic physical and muscle-strengthening activity . In this population, laboratory test results that fall outside of the typical reference intervals may actually be a healthy adaptation to exercise training, which might be indicated by observing a change of results toward values considered more desirable based on risk. Accordingly, prior research has suggested the need for reference intervals more reflective of the athletic population to avoid misinterpretation of results . Thus, the purpose of this investigation was to explore the effects of type (aerobic and strength) and frequency of exercise participation on clinical laboratory tests in a large healthy young-adult population.
|
study
| 99.94 |
We evaluated the effects of self-reported frequency (days per week) of aerobic and strength exercise participation on circulating levels of 26 blood-based biomarkers commonly evaluated in medicine using linear regression models and percentile distribution analyses. In accord with ethical standards this study was deemed exempt by the Western Institutional Review Board. Exception status was deemed as the research was based on the analysis of existing anonymized participant data.
|
study
| 100.0 |
The analytical sample included n = 80,111 adult (aged 18 to 34 y, mean = 30 y, SD = 3.5 y) employees or their spouses and partners. The working employees are from many different companies national wide who participated in an employee wellness program between December 2008 and April 2014. Of those reporting race and ethnicity data, the population was 57% female, 66% Caucasian, 19% Asian, 10% Hispanic, and 5% African American. The prevalence values of self- reported medical conditions are summarized in Table 1. Individuals with incomplete age, gender, or reported exercise frequency data were excluded from the analysis. Sample size per biomarker varied by marker, ranging from 27,715 to 45,725 for women and 14,384 to 34,325 for men depending which tests were included in the program for a given year.
|
study
| 100.0 |
Participants were instructed to fast for 8–12 hours prior to the blood collection. Blood specimens were analyzed for hemoglobin A1c (HbA1c), albumin:globulin ratio (A:G ratio), albumin, alkaline phosphatase (ALP), alanine aminotransferase (ALT), aspartate aminotransferase (AST), bilirubin (total), calcium, high sensitivity C-reactive protein (CRP), total cholesterol, creatinine, estimated glomerular filtration rate (eGFR), ferritin, gamma-glutamyl transferase (GGT), globulin, glucose, high density lipoprotein (HDL), cholesterol: high density lipoprotein ratio (CHOL: HDL ratio), total iron binding capacity (IBC), iron, low density lipoprotein (LDL), percent saturation (pctSat), protein (total), triglycerides, thyroid stimulating hormone (TSH) and uric acid. Hemoglobin A1c analysis was performed on the Cobas Integra 800. Both TSH and ferritin analysis were performed on the Siemens Centaur XP. C-reactive protein analysis was performed on the Dade Behring BNII. All other tests were performed on the Beckman Coulter Olympus 5800 platform. LDL analysis was performed as a direct LDL method. All reagents used were manufactured by the corresponding platform manufacturer with the exception of HDL which was performed using Roche reagents. Specimen analysis was performed by the Quest Diagnostics Lenexa Laboratory in Lenexa, Kansas. All allowable imprecision meets or does not exceed the College of American Pathologists (CAP) recommended allowable Total Error (TEa) for each assay.
|
study
| 99.94 |
Physical activity was measured as self-reported days per week of aerobic and strength training exercise (0, 1, 2, 3, 4, or 5+ days per week). Data were collected by self-administered online questionnaire. Aerobic and strength exercise participation were evaluated with the following questions: In an average week how many times do you participate in Aerobic exercise? Response options were_ 0 _ 1 _2 _3 _4 _5 or more times. In an average week how many times do you participate in: Strength training exercise? Response options were_ 0 _ 1 _2 _3 _4 _5 or more times.
|
study
| 99.94 |
Potential confounding effects of age and health status (defined as the absence of a health condition reported in Table 1) on exercise participation frequency were examined using ANOVA. The influence of aerobic and strength exercise participation on circulating levels of biomarkers were evaluated using linear regression models and percentile distribution analyses.
|
study
| 100.0 |
The effects of each type of exercise on the biomarkers were first visualized by comparing the percentile distribution among four types of activity level: 0 days/week for aerobic exercise and 0 days/week for strength exercise (A0 S0); 0 days/week for aerobic exercise and 5+ days/week for strength exercise (A0 S5); 5+ days/week for aerobic exercise and 0 days/week for strength exercise (A5 S0); and 5+ days/week for aerobic exercise and 5+ days/week for strength exercise (A5 S5). The exercise frequencies of 0 and 5+ days of activity were utilized for comparison in order to compare the most different groups of the sample.
|
study
| 100.0 |
For linear regression modeling, the data were first aggregated into the average biomarker level by all 36 possible combinations between each type of activity level (aerobic 0 to 5+ days/week combined with strength 0 to 5+ days/week). Regression was then performed on the summary data with average biomarker level as y, aerobic exercise frequency as x1, and strength exercise as x2 for each biomarker and each gender respectively. Potential interaction effect between aerobic and strength activities were also examined by the effect of adding the interaction term (x1 * x2) into the model, and potential quadratic effect of exercise was evaluated by adding quadratic terms (x12 and x22) into the model.
|
study
| 100.0 |
All analysis was done in R, version 3.2.1 (The R Foundation for Statistical Computing, Auckland, New Zealand). The weighted least square regression was fitted in R using the “lm” function as follows: lm(y ∼ b0 + b1 ∙ x1 + b2 ∙ x2 + b3 ∙ x1 ∙ x2 + b4 ∙ x12 + b5 ∙ x12, weight = N), where b0 is the intercept and b1 to b5 are the coefficients for each term. The P value and standard errors of parameters for each group (gender and biomarker) were used to evaluate the significance of each coefficient. R squared, Cross validation, AIC and BIC were used to determine the best model for each biomarker.
|
study
| 100.0 |
The proportion of individuals without a reported health condition was higher for individuals reporting more days of strength or exercise participation. Younger age was associated with greater strength exercise participation, but the maximum effect in mean age was only 0.2 year for aerobic exercise and 0.67 year for strength exercise, thus clinically insignificant to account for the difference on biomarker levels. Physical exercise participation was related to clinical laboratory test results for a variety of biomarkers. The graphical presentation of the percentile distributions among the activity level groups for each marker is presented in Figs 1–4. According to the regression models (Table 2), more days of either aerobic or strength exercise were associated with lower levels of glucose, HbA1c, LDL, HDL ratio, triglycerides, eGFR, globulin, and CRP in both women and men. More days of participation in aerobic or strength exercise were associated with higher levels of HDL, creatinine, percent saturation, and iron in both men and women. Mode of exercise or gender (Figs 1–10) influenced the observed relationships between exercise frequency and cholesterol (total), bilirubin, A:G ratio, ALB, ALT, AST, ALP, calcium, ferritin, GGT, IBC, protein (total), and uric acid results. Predicted mean values based exercise frequency from the regression analysis for women and men participating in 0 and 5+ days of aerobic or strength exercise are shown in Table 3. Exercise frequency had no effect on TSH level in men or women.
|
study
| 99.94 |
This study reports that type (aerobic and strength) and frequency of exercise are related to a variety of clinical laboratory tests in healthy young adult men and women. In many cases the direction of the influence of exercise could be suggestive of better health. Yet mode of exercise and gender influenced the relationships between exercise and biomarker results for several measures for undefined reasons that require follow-up studies. Reported relationships may help in the understanding and interpretation of common laboratory results and avoid potential misinterpretation of acceptable results that may be a healthy adaptation to exercise training. Results may contribute to the eventual generation of laboratory reference intervals that are more appropriate based on factors such as physical activity.
|
study
| 99.94 |
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