Biological sounds produced on coral reefs may provide settlement cues to marine larvae. Sound fields are composed of pressure and particle motion, which is the back and forth movement of acoustic particles. Particle motion  is the relevant acoustic stimulus for many, if not most, marine animals. However, there have been no field measurements of reef particle motion. To address this deficiency, both pressure and particle motion were recorded at a range of distances from one Hawaiian coral reef at dawn and mid-morning on three separate days. Sound pressure attenuated with distance from the reef at dawn. Similar trends were apparent for particle velocity but with considerable variability. In general, average sound levels were low and perhaps too faint to be used as an orientation cue except very close to the reef. However, individual transient sounds that exceeded the mean values, sometimes by up to an order of magnitude, might be detectable far from the reef, depending on the hearing abilities of the larva. If sound is not being used as a long-range cue, it might still be useful for habitat selection or other biological activities within a reef. Coral reefs are hubs of marine biodiversity, and recruitment to these reefs provides the foundation of these ecosystems. Larval animals seeking the reef for settlement may use a variety of cues234Abudefduf saxatilis) would likely be able to use coral reef sounds as a significant navigation cue up to 500 m away. For some crab species, orientation and settlement responses were estimated at up to 40 km13It has been suggested that these reef soundscapes may offer a reef orientation cue at relatively large distances compared to some other stimuli189A. saxatilis) were most sensitive to 100–400 Hz sounds in a hearing test17181920The ability of a given larva to detect sound cues will depend on its hearing abilities. While hearing has been studied in only a few of the approximately 12,000 extant marine fish species that live in shallow water or close to shore, and for whom acoustic settlement cues might be relevant15Sound is a mechanical disturbance that can be described in terms of its pressure or particle motion 1821et al.27Bioacoustic larval settlement studies235128Indeed, there appear to be no direct measurements of reef particle motion in field conditions, limiting any estimation of the actual levels and ranges over which these settlement signals might be detectable. Nor are there data which quantify how this signal might vary in time. To address this deficiency, we carried out acoustic recording transects measuring both the particle motion and pressure components of reef sound at multiple distances from the reef. Measurements were made at two times of day (dawn and mid-morning) and repeated on three separate days to determine how the reef soundscape might change with time of day. Measurements were made in the summer (July 2015), coinciding with periods of fish and coral settlement29Sound pressure levels were generally highest on the reef and attenuated with distance during the dawn transect; such attenuation was not detectable during the mid-morning transect ; Table 1Power spectra followed a roughly similar shape across transect positions and time of day, with elevated low frequencies  and vertical (z) axes appeared to decrease with distance from the reef during the dawn transect and in the horizontal axis only during the mid-morning transect, although there was considerable variability around the mean ; Table 1Empirically derived spreading relationships for sound pressure and particle velocity in the horizontal and vertical axes were only statistically significant during the dawn transect for sound pressure and velocity in the x-y axis .Acceleration values in the x-axis were elevated at frequencies below 500 Hz in the dawn and mid-morning transects but did not follow a clear pattern with distance from the reef . SimilarMedian sound levels based on 5 ms segments of each recording pooled across days showed a similar trend to the averages with respect to attenuation with distance . HoweverA range of studies have demonstrated that larval fish and invertebrates may orient towards reef sound and perhaps even discern among sound types; however, there are very limited data on the distances over which acoustic cues might be used. Furthermore, there have been few direct measurements of acoustic particle motion, the relevant acoustic cue for most larval fishes and invertebrates, thus leaving this potential settlement cue overlooked. The current investigation represents an effort to fill this knowledge gap by quantifying this particle motion cue, particularly with respect to the distances over which reef sound propagates.Reef sound pressure did attenuate with distance from the reef but this varied both by frequency and time of day, likely as a result of variation in sound production. Attenuation was most apparent at dawn in both frequency bands and during the mid-morning in the high-frequency band only. Notably, the dip in sound level for the on-reef recorder (at the 400 m mark) during the dawn transect  may refl13The lack of agreement with cylindrical or spherical spreading predictions has been demonstrated on temperate reefs and has been postulated to be a result of a ”reef effect”Earlier work stressed the importance of identifying which coral reef soundscape components are the vital settlement cues: lower-frequency fish sounds or higher-frequency shrimp soundsHere we show that the lower-frequency fish sounds were both higher in amplitude and propagated farther, particularly during crepuscular chorus events. In addition, there was a much larger number of high-amplitude transients in the low-frequency band. Furthermore, this frequency band overlaps the predominant hearing range of many of the marine fish and invertebrates that have been tested15Particle velocity data collected on the M20 particle velocimeter corresponded somewhat to sound pressure data collected on the DMON acoustic recorder in terms of attenuation with distance, but there was considerable variability. The z axis showed velocities that were roughly as high as in the x-y axes. The reason for this is not obvious; while it may be a result of the influence of non-acoustic sources  despite the multiple absorption methods, physical movements of the mooring system are expected to be much lower frequency than the analysis bandwidths used here.The acceleration data did not display any clear trends with distance from the reef in either transect. Furthermore, the position with the highest acceleration values was different in the dawn transect (500 N) than in the mid-morning transect (150 m). This differs from the velocity data (which do show a trend with distance). This is perhaps due to the fact that the acceleration data are frequency-specific; as a result, these data are more variable than the velocity data to which they are proportional.et al.Carassius auratus), bigeye (Pempheris adspersa), and common triplefin (Forstergyian lappillum). The best hearing sensitivity for all three species was between 100–200 Hz and was approximately −60 dB re 1 m/s2, which is approximately 25 dB higher than the highest acceleration values measured at any position in this study, indicating that those species probably could not hear the average Olowalu reef signal at any of these distances. Conversely, Horodysky, et al.2 for the Atlantic croaker at 100 Hz), which suggests that some fishes could detect this reef at the distances measured. While the hearing abilities of larval and the majority of adult invertebrates have yet to be measured, Mooney, et al.Doryteuthis pealeii) and found that their best thresholds were −35 dB re 1 m/s2 at 200 Hz, indicating that these squid could not hear this reef at any distance. Similarly, Packard, et al.Sepia officinalis), squid (Loligo vulgaris), and octopus (Octopus vulgaris) and identified a threshold level of −40 dB re 1 m/s2 at 10 Hz. Finally, Roberts, et al.Mytilus edulis) and found a best sensitivity of −22 dB re 1 m/s2 at 10 Hz. Because reef sound is broadband and these hearing thresholds are derived using pure tones, it is prudent to increase the audiogram sensitivity by Given that many fishes are likely able to sense particle motion and that it is the primarily hearing modality for larval fishesC. auratus), catfish (Platydoras costatus), and sunfish (Lepomis gibbosus) found that in the presence of masking noise hearing thresholds are considerably elevatedThe majority of these hearing studies did not report background noise levels but see. The amoThe reef sound levels reported here are averages over a minute of recording. Thus, there will be variability above and below the mean, with some sounds exceeding the average levels. Whether those sounds are detectable will depend on their amplitude, spectral composition, the amount by which they exceed the background noise, and the larval hearing abilities of a given species. Indeed, when the SPL of short (5 ms) segments was pooled by recording position across the recording days and transect times, there were a considerable number of high-amplitude transient signals, some of which were 20 dB  above median levels . Many moIn conclusion, coral reef sound pressure levels attenuated with distance from the reef but not to the extent predicted by theory, perhaps as a result of the ambient noise levels of the area and the relatively shallow water (less than 100 m) off the reef. Attenuation with distance from the reef was more evident during dawn when, crepuscular biological activity is greatest. By mid-morning, such a relationship between sound level and distance was not apparent. Similar trends were apparent for particle velocity but with considerable variability, and no such trend was apparent for particle acceleration. Because there was no particle velocity sensor on the reef for the duration of each transect, it is not possible to state unequivocally that on-reef particle velocity levels were relatively constant over the course of the transect, even though within-transect temporal variability in sound pressure levels was limited. Average particle acceleration levels were at or below published hearing thresholds, which suggests that these sounds may be perhaps too faint to be used as an orientation cue for marine larvae in search of suitable settlement habitat, at least at distances beyond 150 m. However, the high amplitude transient signals present at nearly every distance from the reef and on both transects might be detectable at greater ranges. Additionally, if other reefs or other times of day exceeded the mean values presented here, those might be detectable, depending on their attributes and the hearing abilities of a given larva.These data show the temporal and spatial scales of the available acoustic cues vary, yet seemingly do not offer a long-distance  cue. However, the actual scales over which acoustic cues may function, at particular times and places, remain unresolved. If larvae are not using sound as a long-distance orientation cue but are responding directionally to sound, perhaps acoustic cues could offer a shorter range cue for settling animals; for example, once they are close to a reef. As many larvae approach reefs at night (when vision is presumably limited) sound cues might offer an indication that the larva is above that reef and could then successfully settle. More comprehensive measurements at key times  would be valuable to assess the scales over which reef sounds may play a role in larval processes. Additionally, acoustic signals are now known to operate as a contact call for some fishesThis study was conducted on July 17, 19, and 20, 2015 immediately after the new moon at one southwest-facing reef, Olowalu, which is located on Maui’s  leeward side . During the data collection period, sea state on all three of these days was less than Beaufort 2 . Olowalu is a broad, relatively flat reef dominated by branching corals with some massive corals and sand channels. Much of the reef is found from approximately 6–11 m depth. This reef has approximately 70% live coral cover, and 33 fish species were observed in visual surveys . The benthic cover changes from coral-dominated structure to sand with increasing distance from the reef.Acoustic data were collected as follows. At the start of the experiment, a stationary DMON digital acoustic recorder  was deployed on a mooring on the reef (approximately 1 m off the bottom) to record sounds directly on the reef and monitor the natural temporal changes in sound production during the course of the study . The mooTo measure the reef sound propagation, vessel-based transects were conducted, recording reef sounds at various distances from the reef. The vessel recording package consisted of two instruments: a DMON set up as above to measure sound pressure in a manner identical to the mooring, and a M20 particle velocimeter  to record particle velocity . The M20 contains three vector sensors , an omnidirectional hydrophone, and digital magnetometer/accelerometer chip for instrument orientation sensing housed in a negatively buoyant aluminum can. The M20 has a usable frequency range of up to 3 kHz; accordingly, sample rates of either 6000 or 12500 Hz were used for all four channels, with data recorded directly onto a laptop via a data acquisition card , using a customized Matlab  program. The instruments were deployed at approximately 10 m depth (the maximum possible depth given the depth of the reef) on a mooring consisting of two communication cables married to a ¼-inch polypropylene line. An Anchor Buddy  was fastened to the top and bottom of the mooring setup to dampen wave-driven vertical movements. The M20 was affixed by eye bolt to the bottom of this line with the DMON slightly above it, oriented in a hydrophone-down position. A 2-lb lead weight was affixed to the line adjacent to the DMON  to help ensure a vertical mooring orientation. At the surface, 12 1-lb gillnet floats were associated to the line in an effort to further dampen wave activity.Recordings were made at specific points  along twAll acoustic analyses were carried out in Matlab 8.6. Each recording from both DMONs and the M20 was reduced into a 1-minute segment to remove any extraneous noise associated with deployment. Any segments containing vessel noise were excluded from subsequent analyses; however, segments with limited wave noise were retained. The remaining segments were detrended to remove any DC offset, corrected for instrument sensitivity, and band pass filtered at 200–4900 Hz (full band DMON), 200–1000 Hz (low-frequency (LF) band DMON), 2–4 kHz (high-frequency (HF) band DMON), and 200–2800 Hz (M20) using four-pole Butterworth filters. The high pass filter (200 Hz) for all bands was set to ensure that any low-frequency periodic signals from physical motion  were significantly  below the filter’s frequency.Sound pressure levels  and power spectral density estimates  were calculated for the entire 1-minute segment of the DMON hydrophone recordings. In addition, SPL was also calculated in 5 ms windows in the DMON LF and HF band to examine variability within the minute-long records.Mean particle velocity measurements and power spectral density estimates  were calculated in the 200–2800 Hz band for each of the M20 accelerometer axes. As a result of the sensor orientation chip malfunction, it was not possible to correct the particle velocity axes with measured pitch, roll, and heading. Nevertheless, because the bottom of the mooring was weighted, the z axis can be reliably referred to as the vertical axis and the x- and y-axes as the horizontal axes. Accordingly, the x- and y-axes were combined so as to present a total magnitude of horizontal velocity.in situ spreading, exponential decay functions were fitted to the sound pressure and particle velocity attenuation data.Attenuation with distance from a source is a result of spreading loss and absorption, the latter of which is negligible at these frequencies and distancesParticle acceleration, the temporal differentiation of particle velocity, can be found using the relationship How to cite this article: Kaplan, M. B. and Mooney, T. A. Coral reef soundscapes may not be detectable far from the reef. Sci. Rep.6, 31862; doi: 10.1038/srep31862 (2016).


RNA sequencing methods have already altered our view of the extent and complexity of bacterial and eukaryotic transcriptomes, revealing rare transcript isoforms  that could play an important role in their biology.M. pneumoniae and P. aeruginosa, as well as mixtures of both. We found that rare transcript isoforms detected by conventional pipelines of analysis could be artifacts of the experimental procedure used in the library preparation, and that they are protocol-dependent.We performed an analysis of chimera formation by four different computational approaches, including a custom designed pipeline, to study the transcriptomes of By using a customized pipeline we show that optimal library preparation protocol and the pipeline to analyze the results are crucial to identify real chimeric RNAs.The online version of this article (doi:10.1186/1471-2164-15-633) contains supplementary material, which is available to authorized users. In recent years, different groups have shown the existence of RNA editing in different species –3, and mSeveral computational approaches have been developed for the detection of chimeric transcripts in RNA-seq data –26. AlthPseudomonas aeruginosa) and gram positive (Mycoplasma pneumoniae) classes. Both genomes are fully sequenced [M. pneumoniae, aside from being very small (816 Kb) a genome-wide transcriptome analysis is available [P. aeruginosa and M. pneumoniae at different stages of the RNA extraction and preparation, and performed RNA-seq of the isolated and mixed samples. We analyzed two widely used protocols for library preparation  and TruSeq stranded RNAseq , see Methods) to study the impact of these protocols on chimera formation. Both protocols are widely used in the analysis of eukaryotic and prokaryotic transcriptomes. Whilst the first one is mainly used for small RNAs in eukaryotes, such as siRNAs or microRNAs, the second is mostly used for mRNA sequencing [Here, we want to determine if prokaryotic RNA chimeras exist and to what extent they may be the result of artifact generation both in the library preparation protocols and the analysis methods. To do so we chose two bacteria belonging to gram negative , as well as non-mixed samples. Mixing was done immediately after RNA extraction. Another sample was obtained by mixing the cells of both bacteria prior to RNA extraction (Cell Mix). Libraries were prepared using the Directional RNA-seq library protocol (see Methods). We used two alternative short read mappers: GEM-mapper and Bowtie [To analyze the origin of chimeric RNAs and to discern if they are artifacts derived of library preparation or natural chimeric RNAs, we prepared different samples by mixing RNA of d Bowtie , 39. Witd Bowtie . In contM. pneumoniae and P. aeruginosa samples in the RNA mix samples showed a significant number of chimeric candidates (33389 in the 1:1 ratio RNA mix sample), the majority of them involving tRNAs and rRNAs in both species . The reason behind the poor correlation in P. aeruginosa, is the high abundance of ribosomal RNA in the samples , which results in lower deep sequencing coverage . Therefore, to find a true chimera, the number of reads supporting the junction has to be significant compared to the expression of the genes forming the chimera. This issue was assessed via two confidence scores . These scores relate the number of reads of a chimeric RNA to its expression. The least expressed gene comprising the chimera was chosen to evaluate the expression, as the limiting factor for its formation. Figure Second, we considered the expression levels of the genes located at both sides of the junction. The expression values were calculated based on the fully mapped reads from the RNAseq datasets. The reason for considering expression levels is the fact that in e Figure A  and another formed by intra-species chimeras. We tested different sets of parameters and used the ones that were able to eliminate the inter-species chimeras in the final set of results. With this approach, in the end we were able to obtain a set of 29 P. aeruginosa RNA concentration decreased, no chimeras appeared from this species and only few chimeras of M. pneumoniae were found. All putative chimeras found after the filtering are represented in Figure We applied the filtering with these same thresholds to the remaining samples. It was observed that in the RNA mixtures 1:5 and 1:50, in which the P. aeruginosa). Furthermore, the three methods interrogated found chimeras formed by transcripts different than rRNAs and tRNAs, the most abundant ones in bacterial genomes. Whereas TopHat Fusion found 16 fusion transcripts formed by protein-coding or non-coding RNAs , FusionMap found 32 (0.88%) and ChimeraScan found 22 (0.71%). Interestingly, as shown in the case of the 1:1 RNA mixture of both bacteria, not a single common fusion transcript was found by all three methods  to prepare the libraries for deep sequencing of the e Figure A. In thie Figure B. After e Figure C and no e Figure C. Also, Nowadays, RNA-Seq is becoming one of the most used approaches for transcriptome profiling. Different studies using this methodology have suggested the existence of chimeric RNAs and circular rRNAs in different organisms. We showed that these RNAs could be artifacts generated during library preparation, and that they are protocol-dependent. We compared two different protocols for RNA-seq library preparation and observed that theyled to very different results in terms of reported chimeric RNAs. Moreover, different sequence analysis methodologies including ours don’t eliminate all non-real chimeras. Therefore, care should be taken when selecting a protocol for library preparation and sequencing, as well as a pipeline for the analysis of the results.M. pneumoniae M129 was grown in 25 cm2 tissue culture flasks with 5 mL of modified Hayflick medium at 37°C as previously described [Pseudomonas aeruginosa PAO1 cells were grown at 37°C under agitation (100 rpm) in 25 ml of 7H9 broth medium from BD plus ADC with 0.5% glycerol and 0.05% tween80.escribed . PseudomM. penumoniae during 96 h at 37°C, cells were washed twice with PBS and lysated with 700 μl of Qiazol buffer.After growing P. aeruginosa cells were grown during 4 days at 37°C, after cell centrifugation the pellet was washed twice with PBS. Then, samples were lysated with 700 μl of Qiazol buffer.RNA extractions were performed by using miRNeasy mini Kit (Qiagen) following the instructions of the manufacturer.P. aeruginosa:M. pneumoniae). These mixtures together with non-mixed wild-type RNAs were used for RNA-seq library preparation.RNAs obtained from two bacteria were mixed in different proportions: 1:1, 1:5 and 1:50 (ratio M. pneumoniae:P. aeruginosa).Also a RNA extraction was performed after mixing the cells 1:1 (Libraries for RNA-seq were prepared following two different protocols: i) Directional RNA-seq library preparation and sequencing; ii) Illumina TruSeq stranded RNAseq sample preparation.One μg of total RNA was fragmented to around 100–150 nt using NEB Next Magnesium RNA Fragmentation Module . Treatments with Antarctic phosphatase  and PNK  were performed in order to make the 5′ and 3′ ends of the RNA available for adapter ligation. Samples were further processed using the TruSeq small RNA Sample Prep Kit  according to the manufacturer’s protocol. Briefly, 3′ adapters and subsequently 5′ adapters were ligated to the RNA. cDNA was synthesized using reverse transcriptase  and a specific primer (RNA RT Primer) complementary to the 3′ RNA adapter. cDNA was further amplified by PCR using indexed adapters supplied in the kit. Finally, size selection of the libraries pas performed using 6% Novex® TBE Gels . Fragments with insert sizes of 100 to 130 bp were cut from the gel, and cDNA was precipitated and eluted in 10 μl EB.Libraries were prepared using the TruSeq Stranded mRNA Sample Prep Kit v2 (ref. RS-122-2101/2) according to the manufacturer’s protocol. Briefly, 1 μg of total RNA were fragmented to approximately 300 bp. cDNA was synthesized using reverse transcriptase  and random primers. The second strand of the cDNA was done by removing the RNA template and synthesizes a replacement strand, incorporating dUTP in place of dTTP to generate ds cDNA. Then ds cDNA was used for library preparation. dsDNA was subjected to end repair, addition of “A” bases to 3′ ends and ligation of the barcoded Truseq adapters. All purification steps were performed using Qiagen PCR purification columns (refs. 50928106 and 50928006). Library size selection was done with 2% low-range agarose gels. Fragments with insert sizes of 200 to 400 bp were cut from the gel, and DNA was extracted using QIAquick Gel extraction kit  and eluted in 20 μl EB. Library amplification was performed by PCR on the size selected fragments using the primer cocktail supplied in the kit.Final libraries were analyzed using Agilent DNA 1000 chip to estimate the quantity and check size distribution, and were then quantified by qPCR using the KAPA Library Quantification Kit  prior to amplification with Illumina’s cBot. Libraries were loaded at a concentration of 1.66 pM onto the flowcell, and were paired-end sequenced, with a mate read length of 50 nts on Illumina’s HiSeq 2000.The workflow followed to identify the chimeric RNA candidates is shown in Figure M. pneumoniae M129 or P. aeruginosa PAO1. For the experiments in which both RNAs were mixed, reads were mapped against an artificial genome formed by the union of the chromosomes of both species.For each experiment, both mates of the paired-end reads were considered as independent single-end reads. They were mapped using GEM  to the rP. aeruginosa has four rRNA operons. Three of them were removed artificially from the reference genome, considering the remaining one as the reference rRNA operon. This was aimed not to discard all putative chimeras coming from any of them.As no rRNA depletion was performed during sample preparation, the vast majority of the mapped reads correspond to the rRNAs of both bacteria. Reads that were not mapped in this first round were retrieved and remapped using GEM-split-mapper, a component of the GEM suite . This maIn order to validate the mapping of the split reads, a BLAST search of them against the reference genome was performed. Only the reads showing an agreement in between the split-mapping and the first hits of the BLAST results were retrieved and considered as single-end candidates  based on the two different methods for the analysis . Each of them considers the number of reads supporting each chimeric RNA and the gene expression levels of the different mRNAs that comprise this hybrid RNA. The scores are calculated as follows:To discern between real and artifactual chimeric RNAs we have defined two scores ; L is the gene length of the least expressed gene in the chimera.ΩHere, we considered the number of unique reads (non-duplicated reads) spanning each chimeric junction. To establish a threshold, we used a score that related the number of unique sequences per chimera to the number of total reads mapping to this same chimera.In addition to that, we also considered the distribution of the reads spanning the chimeric junction. This distribution should be uniform and there should not be any over-represented read, showing a staircase pattern upon coverage representation Figure E, 3F. ToAdditional file 1: Figure S1: Percentages of different RNA molecules. Histogram represents the percentages of different chimeric RNAs in the 1:1 ratio RNA mix sample . Pie chart represents the percentage of tRNA and rRNA that are circular or chimeric RNAs. Values next to the pie charts for the rRNA-rRNA and tRNA-tRNA bars represent the percentage of circular RNAs from the total of chimeras of these classes. (PDF 289 KB)Table S2.Mycoplasma pneumoniae chimeric RNAs obtained after validation in directional RNA-seq library preparation. Table S3.Pseudomonas aeruginosa chimeric RNAs obtained after validation in directional RNA-seq library preparation. Table S4. Putative chimeric RNAs in the 1:1 RNA mixture found by TopHat-Fusion. Table S5. Putative chimeric RNAs in the 1:1 RNA mixture found by FusionMap. Table S6. Putative chimeric RNAs in the 1:1 RNA mixture found by ChimeraScan. (XLSX 1 MB)Additional file 2: Table S1: Putative chimeras found by the 4 pipelines tested in two samples from different library preparation protocols. Numbers in parenthesis represent the number of chimeras clustered by genomic location (if applicable). Additional file 3: Figure S2: Results of the different pipelines used to analyze the data. A) Venn diagram showing the number of chimeras found by each of the pipelines used and the concordances among them. The diagram shows the values for the analysis of the 1:1 RNA mix sample, using the directional RNA-seq library preparation protocol. B) Bar plot showing the percentages of chimeras of each type found by the different pipelines tested. THF: TopHat-Fusion, CS: ChimeraScan, FM: FusionMap, OURS: Our custom designed pipeline. (PDF 458 KB)


Assembled RNA polymerase III (Pol III) complexes exert local effects on chromatin processes, including influencing transcription of neighboring RNA polymerase II (Pol II) transcribed genes. These properties have been designated as ‘extra-transcriptional’ effects of the Pol III complex. Previous coding sequence microarray studies using Pol III factor mutants to determine global effects of Pol III complex assembly on Pol II promoter activity revealed only modest effects that did not correlate with the proximity of Pol III complex binding sites.Given our recent results demonstrating that tDNAs block progression of intergenic Pol II transcription, we hypothesized that extra-transcriptional effects within intergenic regions were not identified in the microarray study. To reconsider global impacts of Pol III complex binding, we used RNA sequencing to compare transcriptomes of wild type versus Pol III transcription factor TFIIIC depleted mutants. The results reveal altered intergenic Pol II transcription near TFIIIC binding sites in the mutant strains, where we observe readthrough of upstream transcripts that normally terminate near these sites, 5′- and 3′-extended transcripts, and de-repression of adjacent genes and intergenic regions.ETC sites in yeast. The results may also be relevant to synthetic biology efforts to design a minimal yeast genome.The results suggest that effects of assembled Pol III complexes on transcription of neighboring Pol II promoters are of greater magnitude than previously appreciated, that such effects influence expression of adjacent genes at transcriptional start site and translational levels, and may explain a function of the conserved The online version of this article (doi:10.1186/s12915-014-0089-x) contains supplementary material, which is available to authorized users. Saccharomyces cerevisiae includes transfer RNAs (tRNAs), 5S ribosomal RNA (5S rRNA), 7SL RNA, U6 spliceosome RNA, snR52 small nucleolar RNA as well as the RNA component of RNaseP .


In recent years, a variety of small RNAs derived from other RNAs with well-known functions such as tRNAs and snoRNAs, have been identified. The functional relevance of these RNAs is largely unknown. To gain insight into the complexity of snoRNA processing and the functional relevance of snoRNA-derived small RNAs, we sequence long and short RNAs, small RNAs that co-precipitate with the Argonaute 2 protein and RNA fragments obtained in photoreactive nucleotide-enhanced crosslinking and immunoprecipitation (PAR-CLIP) of core snoRNA-associated proteins.Analysis of these data sets reveals that many loci in the human genome reproducibly give rise to C/D box-like snoRNAs, whose expression and evolutionary conservation are typically less pronounced relative to the snoRNAs that are currently cataloged. We further find that virtually all C/D box snoRNAs are specifically processed inside the regions of terminal complementarity, retaining in the mature form only 4-5 nucleotides upstream of the C box and 2-5 nucleotides downstream of the D box. Sequencing of the total and Argonaute 2-associated populations of small RNAs reveals that despite their cellular abundance, C/D box-derived small RNAs are not efficiently incorporated into the Ago2 protein.We conclude that the human genome encodes a large number of snoRNAs that are processed along the canonical pathway and expressed at relatively low levels. Generation of snoRNA-derived processing products with alternative, particularly miRNA-like, functions appears to be uncommon. Small nucleolar RNAs (snoRNAs) are a specific class of small non-protein coding RNAs that are best known for their function as guides of modifications (2'-O-methylation and pseudouridylation) of other non-protein coding RNAs such as ribosomal, small nuclear and transfer RNAs  -3. BasedImmediately upstream of the D box and/or the D' box, C/D box snoRNAs contain 10 to 21 nucleotide-long antisense elements that are complementary to sites in their target RNAs -15. The Deep-sequencing studies revealed a surprising diversity of small RNAs derived from non-coding RNAs (ncRNAs) known as small derived RNAs (sdRNAs) with well-established functions such as tRNAs ,19, Y RNTo gain insight into the complexity of snoRNA processing and the functional relevance of the derived sdRNAs, we undertook a comprehensive characterization of products generated from snoRNA loci, combining high-throughput sequencing of long and short RNA fragments with photoactivatable-ribonucleoside-enhanced cross-linking and immunoprecipitation (PAR-CLIP) of core snoRNA-associated proteins and with data from Argonaute 2 (Ago2) immunoprecipitation sequencing (IP-seq) experiments. We found that many loci in the human genome can give rise to C/D box-like snoRNAs. Among the novel snoRNAs that we identified are very short sequences, extending little beyond the C and D boxes, which are essential for the binding of core snoRNA proteins. Compared to the snoRNAs that are already known, the novel snoRNA candidates exhibit a lower level of evolutionary conservation and a lower expression level. These findings indicate that the C/D box snoRNA structure evolves relatively easily and that C/D box snoRNA-like molecules are produced from many more genomic loci than are currently annotated. We further found that C/D box snoRNAs are very specifically processed inside the regions of terminal complementarity, retaining in the mature form only four to five nucleotides upstream of the C box and two to five nucleotides downstream of the D box. Sequencing of the small RNA population as well as of the small RNAs isolated after Ago2 immunoprecipitation revealed that despite their cellular abundance, C/D box-derived small RNAs are not efficiently incorporated into the Ago2 protein. Our extensive data thus indicate that, contrary to previous suggestions ,33, snoRTo investigate the RNA population comprehensively that associates with both C/D box and H/ACA box small nucleolar ribonucleoproteins we performed PAR-CLIP as previously described  with antvice versa. This could be caused by the close spatial arrangement of snoRNPs on the target molecule, or could indicate that H/ACA box snoRNAs and C/D box snoRNAs guide modifications on each other.Compared to the libraries that we previously generated for HuR and Ago2 , two proAs mentioned in the introduction, both C/D box and H/ACA box snoRNAs carry very specific functional sequence and structure elements, which are recognized by the snoRNP core proteins. We thus asked whether different C/D box core proteins have distinct preferences in binding different regions of the C/D box snoRNAs. Figure z-scores of the average coverage per position in the guide region relative to the entire snoRNA, Figure We further asked whether the binding pattern of Fibrillarin reflected in the abundance of CLIP reads differs between guide regions of the snoRNAs that have a target annotated in snoRNA-LBME-db and orphan guide regions. For guide regions, we took the nine nucleotides upstream of the D and D' boxes and as a reference we compared the coverage of the D and D' boxes themselves Figure . We founz-score for coverage compared to the entire snoRNA. This is expected because these snoRNAs are highly structured, with most nucleotides being engaged in base pairs in the two hairpin stems and a few nucleotides are free to interact with the proteins.For H/ACA box snoRNAs we found that Dyskerin strongly prefers the H box nucleotides Figure , which iWe screened the top 500 clusters from each PAR-CLIP library that did not overlap with known ncRNAs, mRNAs or repeat elements for potentially novel snoRNA genes. To identify H/ACA box genes we employed the SnoReport program , while fE-value ≤ 10-3). We further compared the loci of the putative snoRNAs with the snoRNA annotation available in ENSEMBL release 65  ATP (10 µCi/µl) were used to radiolabel 10 µg of RNA at the 5'-ends. The RNA was separated together with a radiolabeled 20-nucleotide ladder on a 12% polyacrylamide gel, the bands corresponding to 18 to 30 nucleotides (for sdRNA sequencing libraries) or 20 to 200 nucleotides (for sRNA sequencing libraries) were excised, the RNA was extracted overnight in a 0.4-M NaCl solution and finally precipitated with ethanol. Small RNA libraries were prepared according to a published protocol  and sequFor each PAR-CLIP library we inferred binding regions of the proteins of interest by clustering reads whose corresponding loci were at most 25 nucleotides apart. To annotate known snoRNA and scaRNA genes we first retrieved sequences from the snoRNA-LBME-db , mapped Candidates that showed expression of at least 1 TPM per nucleotide in the 20 to 200 nucleotides small RNA sequencing run (only uniquely mapped reads that covered at least 50% of the candidate snoRNA sequence were considered), and had at least 1 TPM per nucleotide in at least one of the type-specific CLIP libraries were considered putative snoRNAs. They were consecutively numbered, and named as 'ZL#'. To further validate the newly found snoRNAs, we searched for evidence of expression in recently published small RNA-seq libraries from the ENCODE project . Files wTo identify 2'-O-methylated residues we used a reverse transcriptase-based method coupled with polyacrylamide gel analysis as described in . The metTo map pseudouridines in candidate RNAs we used a method that relies on chemical modification of RNA bases with N-cyclohexyl-N'-β (4-methyl morpholinium) -ethylcarbodiimide (CMC) . The metTo predict C/D box snoRNAs that could guide 2'-O-methylation, we searched for 8-mer complementarity  to regions immediately or one nucleotide upstream of the D and D' boxes of C/D box and C/D box-like snoRNAs. To predict H/ACA box snoRNAs that could guide pseudouridylations, we used the program RNAsnoop . We firsMitotic cells were collected using mitotic shake-off ,69, a teAgo2 was immunoprecipitated from mitotic and asynchronous cells; the Ago2-associated RNAs were extracted and used to prepare cDNA libraries as described above , which wAgo2: Argonaute 2; CB: Cajal body; CLIP: cross-linking and immunoprecipitation; DKC1: Dyskerin; dNTP: deoxynucleotide triphosphate; FBL: Fibrillarin; IP: immunoprecipitation; IP-seq: immunoprecipitation sequencing; miRNA: micro RNA; MNase: micrococcal nuclease; ncRNA: non-coding RNA; PAR-CLIP: photoactivatable-ribonucleoside-enhanced cross-linking and immunoprecipitation; rRNA: ribosomal RNA; scaRNA: small Cajal body-specific RNA; sdRNA: small derived RNA; snoRNA: small nucleolar RNA; snoRNP: small nucleolar ribonucleoprotein; snRNA: small nuclear RNA; sRNA: small RNA; TPM: tags per million; tRNA: transfer RNA.SK and MZ conceived the project. SK performed the experiments, with help from DJJ (Ago2 IP and primer extensions) and APS . ARG performed the computational analysis of the sequencing data, with help from HJ . ARG, DJJ, SK and MZ wrote the manuscript. All authors read and approved the final manuscript.Profiles of PAR-CLIPs reads obtained with various core snoRNP proteins for snoRNAs and scaRNAs. The proteins and normalized read counts are shown on the y-axis. The snoRNA and location of boxes are shown at the bottom. Red bars in the profiles indicate the number of T→C mutations observed at individual nucleotides in the PAR-CLIP reads.Click here for fileList of novel C/D box, C/D box-like snoRNAs and mini-snoRNAs obtained in this study.Click here for fileList of novel H/ACA snoRNAs or homologs of known snoRNAs (indicated in the 'BLAST hits' column) that were obtained in this study.Click here for fileRNA-seq read profiles from selected ENCODE small RNA-seq samples along the novel C/D box and H/ACA box snoRNA loci identified in our study.Click here for fileNorthern blots for selected novel C/D box snoRNAs. Among the 20 most abundantly expressed  novel C/D box snoRNAs we could confirm the presence of ZL1, ZL2, ZL8, ZL11, ZL63, ZL107, ZL116, ZL126 and ZL127 by Northern blotting.Click here for fileExpression of C/D box and C/D box-like snoRNAs in our small RNA-seq run . Only reads that cover at least 50% of the snoRNA locus were considered.Click here for fileSCARNA21 has a C/D box H/ACA box hybrid structure. (A) Screenshot from the UCSC genome browser showing conserved C and D box elements. (B) Northern blot probing for H/ACA box structure only (left) and for the hybrid structure (right).Click here for filePrimer extension assays for U2 snRNA. Primer extension assay reveals a 2'-O-methyl modification site for nucleotide U47.Click here for filePrimer extension assays for non-canonical snoRNA targets. Primer extension runs reveal 2'-O-methyl (A-C) and pseudouridine (D-G) modification sites in several non-canonical RNAs. (A) SNORA61: G50. (B) VTRNA1-2: G30, U31, C33, A34. (C) 7SK RNA: C137, G139, C141, G148, C150, G151. (D) SNORD16: U52, U55. (E) SNORD35A: U26, U31, U37, U43, U45, U51. (F) 7SK RNA: U250. (G) 7SL RNA: U226, U233, U236, U266, U273.Click here for fileSummary of nucleotide modifications detected by primer extension assays and predicted guide snoRNA-target interactions.Click here for fileAnalysis of PAR-CLIP clusters overlapping with mRNA exon annotation. Shown are genome coordinates, host transcript and exon identifier, the number of C and D boxes predicted within the genomic region, snoRNAs to whose guide regions these mRNA fragments are complementary and the number of  reads obtained from the regions in various PAR-CLIP libraries.Click here for fileDetailed list of reads mapping to snoRNA loci in Ago2 IP-seq libraries.Click here for fileSupplementary materials and methods. Detailed information about the experimental methods . In addition, the annotated C/D and H/ACA snoRNAs used in this study are listed.Click here for filePrimer extension assays on spliceosomal RNA U6. (A) Primer extension assay on spliceosomal RNA U6 detected documented 2'-O-methylation as well as potentially novel 2'-O-methylation sites. (B) Primer extension assay detected documented pseudouridine sites in U6. CTRL indicates the untreated sample, +CMC the sample treated with 1-cyclohexyl-3-(2-morpholinoethyl)carbodiimide metho-p-toluenesulfonate (CMC).Click here for fileAsynchronous and mitotic GFP-tagged HeLa cells. Green fluorescent protein appears in green and cell boundaries in orange. (A) In an asynchronous cell culture only a few cells are in the mitotic phase, which can be seen from the condensed chromatin and the rounded cell morphology. (B) Cell obtained with mitotic shake-off. The procedure enriches for round cells containing condensed chromatin.Click here for fileExtended version of Figure 4B showing all snoRNA genes expressed in HEK293 cells.Click here for file


Influenza viruses subvert the transcriptional machinery of their hosts to synthesize their own viral mRNA. Ongoing transcription by cellular RNA polymerase II (Pol II) is required for viral mRNA synthesis. By a process known as cap snatching, the virus steals short 5′ capped RNA fragments from host capped RNAs and uses them to prime viral transcription. An interaction between the influenza A virus RNA polymerase and the C-terminal domain (CTD) of the large subunit of Pol II has been established, but the molecular details of this interaction remain unknown. We show here that the influenza virus ribonucleoprotein (vRNP) complex binds to the CTD of transcriptionally engaged Pol II. Furthermore, we provide evidence that the viral polymerase binds directly to the serine-5-phosphorylated form of the Pol II CTD, both in the presence and in the absence of viral RNA, and show that this interaction is conserved in evolutionarily distant influenza viruses. We propose a model in which direct binding of the viral RNA polymerase in the context of vRNPs to Pol II early in infection facilitates cap snatching, while we suggest that binding of free viral polymerase to Pol II late in infection may trigger Pol II degradation.IMPORTANCE Influenza viruses cause yearly epidemics and occasional pandemics that pose a threat to human health, as well as represent a large economic burden to health care systems globally. Existing vaccines are not always effective, as they may not exactly match the circulating viruses. Furthermore, there are a limited number of antivirals available, and development of resistance to these is a concern. New measures to combat influenza are needed, but before they can be developed, it is necessary to better understand the molecular interactions between influenza viruses and their host cells. By providing further insights into the molecular details of how influenza viruses hijack the host transcriptional machinery, we aim to uncover novel targets for the development of antivirals. The segmented negative-sense RNA genome of influenza A virus is transcribed and replicated by the viral RNA-dependent RNA polymerase, which consists of three subunits, the polymerase basic 1 (PB1), PB2, and polymerase acidic (PA) proteins 13. Transc6–12–Despite the clear functional and physical links between the viral and host transcriptional machineries, the details of this interaction remain poorly understood. In particular, it is not clear whether only free polymerase interacts with the CTD of Pol II or whether viral polymerase in the context of vRNPs can also interact. Although the influenza virus polymerase requires active Pol II to provide it with a source of capped RNA primers, the viral polymerase has also been linked to Pol II degradation. This occurs at late times during infection , 18, wheg for 5 min. Cell lysates were supplemented with MgSO4 and CaCl2 to final concentrations of 10 and 1 mM, respectively, and treated with RNase-free DNase  for 30 min at 37°C. The reaction was stopped by adding EDTA to a final concentration of 20 mM. These samples were immunoprecipitated overnight at 4°C with antibodies specific for PA (kind gift from T. Toyoda) and Pol II  and protein G-Sepharose (Sigma). Immunocomplexes were washed with 10 mM Tris-HCl (pH 8.0)–0.1% Igepal–1 mM phenylmethylsulfonyl fluoride (PMSF)–1 mM EDTA containing 150 mM NaCl (once), 1 M NaCl (three times), and 0.5 M LiCl (three times). Cross-links were reversed in both immunocomplexes and input samples by the addition of elution buffer  and heating at 65°C overnight. Protein G-Sepharose was removed by centrifugation, and samples were treated with proteinase K for 30 min at 45°C. RNA was extracted with phenol-chloroform and precipitated with ethanol in the presence of tRNA carrier. RNA samples were subjected to primer extension analysis of viral neuraminidase (NA) and NP segment-specific RNAs as previously described (RNA immunoprecipitation (RIP) was performed as previously described , 18, 22,Peptides were chemically synthesized by Cambridge Peptides Ltd. by solid-phase peptide synthesis. Peptides were designed to contain four repeats of the heptapeptide consensus sequence of the Pol II CTD (YSPTSPS) with modifications representing different phosphorylation states of the CTD. Full amino acid sequences are shown in g for 5 min at 4°C, and lysates were precleared by incubation with streptavidin agarose resin  for 2 h. Pol II CTD mimic peptides were bound to the beads for 2 h. Peptide-coated beads were washed three times in wash buffer , blocked with 1% bovine serum albumin for 1 h, and washed twice. Precleared lysates were bound to the peptide-coated beads for 2 h at 4°C, and unbound material was removed by washing three times. The beads were split into two aliquots during the last wash, and they were boiled for 5 min in sample buffer  for protein analysis or the RNA was extracted with TRIzol (Ambion), precipitated in the presence of glycogen carrier, and analyzed by primer extension as described above. For detection of viral proteins by Western blot analysis, a custom-made rabbit polyclonal antibody raised against the trimeric influenza virus polymerase (Eurogentec) . Debris was removed by centrifugation at 16,200 × ogentec)  or a rab2, 0.1 mM MnCl2, 0.5 mM tris(2-carboxyl)phosphine] with a 2- to 3-fold molar excess of two synthetic RNA oligonucleotides corresponding to the vRNA 5′ and 3′ termini (5′-AGUAGAAACAAGGCC-3′ and 5′-GGCCUGCUUUUGCU-3′). The NaCl concentration of the mixture was then reduced to 0.5 M overnight by dialysis. After dialysis, the polymerase-RNA complex was purified away from unbound RNA by gel filtration as described previously  , 26 and eviously .32P]ATP for 1 h at 30°C with T4 polynucleotide kinase (Fermentas). Both reactions were carried out in Tango buffer (Fermentas). Labeled RNA was mixed with formamide, heated at 95°C for 3 min, analyzed on 20% polyacrylamide gels containing 7 M urea in Tris-borate-EDTA (TBE) buffer, and visualized by autoradiography.Pol II CTD mimic peptides were bound to streptavidin agarose resin as described above for the pulldown assays. Viral polymerase purified from either HEK 293T or Sf9 cells was bound to the peptide-coated beads by incubation for 2 h at 4°C. Complexes were washed three times with wash buffer and split into two aliquots during the last wash. For protein analysis, beads were boiled for 5 min in sample buffer and analyzed by silver staining. For RNA analysis, the RNA in the bound complexes was extracted with TRIzol (Ambion) and precipitated in the presence of glycogen. RNA was dephosphorylated for 10 min at 37°C with FastAP (Fermentas), and the enzyme was inactivated by heating at 75°C for 5 min. Dephosphorylated RNA was 5′ end labeled with [γ-32P]GTP incorporation assay as previously described (32P]GTP (PerkinElmer), 10 ng of β-globin mRNA (Sigma), 5 mM MgCl2, 2 mM DTT, and 1 U/μl RNasin (Promega) for 2 h at 30°C; mixed with 10 μl of formamide; and heated at 95°C for 3 min. Transcription products were analyzed on 16% polyacrylamide gels containing 7 M urea in TBE buffer and visualized by autoradiography.The viral polymerase was immobilized on streptavidin resin coated with Pol II CTD mimic peptides as described above, and its transcriptional activity was evaluated with an ATP, and analyzed on a polyacrylamide gel. As expected, the 37-nt-long vRNA was present in the complexes bound to the CTD mimic peptide phosphorylated on serine-5  was able to bind specifically to a Pol II CTD mimic peptide that was phosphorylated on serine-5. We were not able to detect any binding when polymerase subunits were individually expressed and purified (data not shown). This result is in agreement with previous data showing that none of the individually expressed polymerase subunits, or combinations of two subunits, copurified with a tagged version of the Pol II CTD . HoweverIn terms of evolution, influenza A and B viruses are more closely related to each other than they are to influenza C virus , 33. In Our data show that both RNA-free viral polymerase and vRNPs associate with the CTD of Pol II. The association of vRNPs with the CTD likely provides the viral polymerase with a platform to carry out transcription, enabling the polymerase to access nascent host capped RNAs, as well as splicing factors and factors required for mRNP assembly . The CTDWhat would be the function of RNA-free trimeric polymerase associating with Pol II? Such a polymerase, lacking template vRNA, would not be competent in cap snatching, as the polymerase needs to be associated with both the 5′ and 3′ ends of the vRNA to cap snatch efficiently –40. Infl–It is not clear how binding of the polymerase to the CTD of Pol II would trigger Pol II degradation. However, the ubiquitin-proteasome system is likely to be involved. Our group reported that increasing amounts of ubiquitylated Pol II are present late in infection and the expression of the viral polymerase trimer is sufficient to trigger ubiquitylation of the serine-5-phosphorylated form of Pol II. Furthermore, the expression of a mutant viral polymerase with reduced Pol II-binding activity induced reduced levels of ubiquitylated Pol II . We alsoBunyaviridae, encode the NSs protein that is known to trigger a DNA damage response-like degradation of transcribing RNA Pol II (Induction of Pol II degradation is not unique to influenza virus. La Crosse and Schmallenberg viruses, both members of the family A Pol II , 46. PerTaken together, the results of this study show that both vRNP-bound and free RNA polymerases associate with Pol II and we propose that the two associations have different roles during the viral replication cycle . On the


New insights into the natural roles of these transporters are described and discussed, focusing on the knowledge obtained or suggested by post-genomic research. The new information reviewed here provides clues into the unexpectedly complex roles of these transporters, including a proposed indirect regulation of the stress response machinery and control of membrane potential and/or internal pH, with a special emphasis on a genome-wide view of the regulation and evolution of MDR/MXR-MFS transporters.Multidrug/Multixenobiotic resistance (MDR/MXR) is a widespread phenomenon with clinical, agricultural and biotechnological implications, where MDR/MXR transporters that are presumably able to catalyze the efflux of multiple cytotoxic compounds play a key role in the acquisition of resistance. However, although these proteins have been traditionally considered drug exporters, the physiological function of MDR/MXR transporters and the exact mechanism of their involvement in resistance to cytotoxic compounds are still open to debate. In fact, the wide range of structurally and functionally unrelated substrates that these transporters are presumably able to export has puzzled researchers for years. The discussion has now shifted toward the possibility of at least some MDR/MXR transporters exerting their effect as the result of a natural physiological role in the cell, rather than through the direct export of cytotoxic compounds, while the hypothesis that MDR/MXR transporters may have evolved in nature for other purposes than conferring chemoprotection has been gaining momentum in recent years. This review focuses on the drug transporters of the Major Facilitator Superfamily (MFS; drug:H All living cells exhibit elaborate molecular mechanisms to protect themselves from external assault, such as the exposure to drugs and other cytotoxic compounds. The simultaneous acquisition of resistance to a wide range of structurally and functionally unrelated cytotoxic chemicals has become a widespread phenomenon in nature known as Multidrug/Multixenobiotic resistance (MDR/MXR)  and confer MDR/MXR resistance in bacteria, fungi and more complex eukaryotes.Although drug resistance might be mediated by various mechanisms, membrane transporters that presumably catalyze the efflux of a broad range of cytotoxic substrates play an important role in MDR/MXR processes  to guide the development of new prophylactic, diagnosis, and therapeutic approaches to the rising number of drug resistant fungal infections  approaches has gained considerable momentum in recent years. Remarkably, the identification of alterations occurring in gene or protein expression following exposure to a drug or xenobiotic compound can contribute to identify the cellular pathways that are most relevant to the stress response, including MDR/MXR transporters and how their complex regulation and putative physiological roles may also influence drug resistance. Genomic/proteomic variations can be identified through transcriptomics and quantitative proteomics. Expression proteomic approaches are also important to identify alterations at the level of post-translational modifications associated with exposure to xenobiotic and cytotoxic compounds. Another very important tool in yeast research are gene knockout collections. Chemogenomic analyses to identify determinants of resistance to a particular compound in yeast can be performed using homozygous , haploinsufficiency  and multicopy- and overexpression (gene dosage > 100%) collections. Many MDR/MXR transporters are directly linked to the ability of cells to grow in the presence of a particular stressing condition, and most of the compounds to which these transporters provide protection have been identified through the assessment of the fitness phenotypes of the corresponding deletion mutants under chemical stress. In fact, under control conditions these growth phenotypes are not detectable and would not have been identified. Furthermore, in several cases the presence of the gene is required for growth under a given stress, and yet there are no alterations at the expression or protein content level, meaning that many of these conditions would not have been discovered using expression-based methodologies such as DNA microarrays or proteomics. However, the identification of an MDR/MXR transporter-encoding gene as a determinant of resistance does not necessarily mean that the gene product is involved directly in the efflux of that compound from the cell. As discussed in Section The MDR/MXR Phenomenon, some of these transporters might have natural physiological roles that indirectly enable chemoprotection, for example through the alteration of plasma membrane potential and/or lipid composition. For this reason, lipidomic analyses can also be of particular interest, given the role of sphingolipids and ceramides as signaling mediators in a growing number of pathways and in lipid-based signaling in the yeast response to stress   and the 14-spanner drug:H+ antiporter family 2 (DHA2)  might also provide an explanation for the involvement of Qdr2 in the oxidative stress response  and mono- and divalent cations , ARN1, ARN2, SIT, and ENB1 (ARN subfamily), GEX1 and GEX2 (GEX subfamily)  Table . Unlike y) Table . Among ty) Table . ConversVBA5 was associated with MDR, its overexpression leading to increased susceptibility to 4-NQO and quinidine  have been obtained, based on the increasing abundance of available genome sequences, which may help to understand several of the issues raised regarding the action of such transporters , with the identification of 10 main gene lineages  was also reconstructed  further hints at a more complex involvement of these MDR/MXR-MFS transporters in chemoprotection.S. cerevisiae, mostly coming from genome-wide experiments. This information, gathered in the YEASTRACT database (www.yeastract.com)  whose expression and/or localization was found to change in response to MMS treatment leading to replicative stress , Msn2 (71%), Msn4 (64%), and Yap1 (61%) regulating more than 60% of the DHA1/DAG genes Figure . Msn2 anAll but one of the DHA1/DAG genes are also regulated by nutrient availability transcription factors. Thirteen transcription factors involved in the response to amino acid availability have been found to regulate 70% of the DHA1/DAG genes. Among these transcription factors, Gcn4 and Bas1 stand out as the two that regulate the majority (more than 60%) of these genes Figure . Gcn4 isqdr3 null mutants under glucose deprivation , Hap2 (36%), and Tye7 (32%). Mig3 plays a major role in carbon catabolite repression and ethanol response, but is also involved in the response to toxic agents, while Hap2 is one of the key regulators of respiration and Tye7 is an activator of glycolytic gene expression. Among the 27 DHA genes regulated by carbon source related transcription factors, eight are regulated by five or more of these transcription factors, including Atr1 (5 TFs), Vba4 (5 TFs), Arn3 (6 TFs), Arn4 (5 TFs), Ymr279c (7 TFs), Hol1 (5 TFs), Tpo1 (5 TFs), and Aqr1 (12 TFs) Figure . Very liARN2, TPO1, and TPO4 was registered in cells growing on oleate as carbon source  or direct  evidences, and the number of independent studies supporting each regulatory interaction can vary greatly. Here we have opted to show all interactions described for each TF-target gene considered, although we distinguish between expression evidence and DNA-binding evidence  show that it is at least partially similar to that in S. cerevisiae .Further characterization of drug resistance MFS proteins in pathogenic yeasts or phytopathogenic fungi will benefit from studies in S. cerevisiae to higher eukaryotes, Tpo1 homologs encoding putative plasma membrane MFS transporters from the plant model Arabidopsis thaliana were analyzed to uncover new roles for these transporters in plant abiotic stress tolerance (Cabrito et al., ZIFL1 transcription levels were found to be elevated in plants treated with the herbicide 2,4-D, and heterologous expression in yeast complemented the sensitivity phenotype in tpo1 null mutant cells stressed with 2,4-D (Cabrito et al., S. cerevisiae and A. thaliana, to uncover novel roles for plant MFS transporters, which may open new avenues for the development of efficient strategies to improve crop productivity or decontaminate polluted soils.The knowledge gathered in yeast MDR/MXR-MFS transporters can also be extrapolated to other systems and less accessible higher eukaryotes such as plants. Abiotic stress is an important contributor to loss of plant productivity worldwide under agricultural conditions. The clarification of the mechanisms underlying MDR/MXR in plants will be instrumental in paving the way for the development of efficient strategies to improve crop tolerance to abiotic stress, in particular regarding the potential role of MDR/MXR transporters in the plant response to heavy-metal contamination, high salinity, pesticides, and other xenobiotic compounds. Considerable progress has been made on the characterization of plant ABC transporters, which have been shown to play a pivotal role in numerous physiological processes (van den Brule and Smart, S. cerevisiae has significantly increased our knowledge on the evolution, physiology and regulation of MDR/MXR-MFS transporters, contributing to elucidate the mystery of the redundancy and promiscuity of these transporters and their physiological relevance. In the near future, more specialized global approaches such as metabolomics and lipidomics are expected to expand on the recent findings here reviewed, in particular regarding the possible indirect role of these transporters in the regulation of the stress response, either through metabolic regulation, alteration of the plasma membrane composition, or other mechanisms. The exploitation of high-throughput technologies and the knowledge gathered in yeast can prove invaluable to guide studies in pathogenic fungi, to develop more robust yeast strains for biotechnological applications, and to improve crop protection, with promising repercussions from medicine to biotechnology and agriculture.In recent years, the use of genome-wide approaches in the model yeast The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Novel RNA-guided cellular functions are paralleled by an increasing number of RNA-binding proteins (RBPs). Here we present ‘serial RNA interactome capture' (serIC), a multiple purification procedure of ultraviolet-crosslinked poly(A)–RNA–protein complexes that enables global RBP detection with high specificity. We apply serIC to the nuclei of proliferating K562 cells to obtain the first human nuclear RNA interactome. The domain composition of the 382 identified nuclear RBPs markedly differs from previous IC experiments, including few factors without known RNA-binding domains that are in good agreement with computationally predicted RNA binding. serIC extends the number of DNA–RNA-binding proteins (DRBPs), and reveals a network of RBPs involved in p53 signalling and double-strand break repair. serIC is an effective tool to couple global RBP capture with additional selection or labelling steps for specific detection of highly purified RBPs. RNA-binding proteins are involved in the posttranscriptional regulation of a large number of cellular processes and several recent studies have sought to describe the extent of the RNA-binding proteome. Here, Conrad et al. describe serIC, a stringent approach they apply towards defining the RNA-binding proteome of the mammalian nucleus. Advances in RNA research have revolutionized our understanding of RNA biology during the last decade248101112in vivo protein–RNA interactions on a cellular scale141416The underlying protein–RNA interactions within such functional networks are still mostly deciphered on a gene-by-gene basis. Novel tools to accurately identify and characterize these interactions are therefore highly desired. Two landmark studies introduced the RNA interactome capture technique (IC), which for the first time enabled identification of in vivo RBP detection with maximal specificity, we have developed serial IC (serIC), a method that includes repeated high-stringency RBP purifications. serIC can be easily coupled to intermittent enzymatic treatments or additional selection and modification steps to obtain highly selected RNA–protein complexes. When applied to isolated cell nuclei, serIC recovers substantially fewer proteins without predicted RNA-binding function than previous single-IC studies, and is thus in better agreement with computational RNA-binding predictions. With this nuclear RNA interactome we provide a high confidence list of dual specificity DNA–RNA binders, including transcription factors and chromatin components, with minimal background from DNA-binding proteins. Novel DRBPs extensively link transcription regulation with RNA processing. We also reveal a dense network of RNA-binding DNA repair factors involved in the p53 response and NHEJ, supporting the emerging concept of an RNA-guided DDR.One limitation of previous global IC profiles is the lack of subcellular spatial resolution, which is especially relevant if the biological context of novel protein–RNA interactions is unknown. To catalogue the RNA–protein network involved in transcriptional regulation, nuclear RNA processing, chromatin structure and DNA repair, we thus set out to identify the nuclear RNA interactome. To enable comprehensive 9 K562 cells with ultraviolet light to induce protein–RNA crosslinks, and subsequently extracted whole nuclei or chromatin via biochemical fractionation1814We initially set out to define a nuclear RNA interactome by applying IC to the nuclear and chromatin compartment of K562 myeloid leukaemia cells. We chose this cell line, since growth in suspension culture more easily allows scaling up starting material for IC by three- to fivefold compared with the two previous whole-cell studies, to compensate for the reduced material obtained from the nuclear compartment14P value 9.5 × 10−217), confirming the specificity of the method , or to the K562 nuclear proteome . Further corroborating this finding, no-RBD proteins detected by serIC display a significantly reduced amino-acid complexity compared with the K562 nuclear proteome (P=0.006), while complexity in IC-only candidates is indistinguishable from the background -RNA–protein interactions with subcellular resolution. The resulting nuclear RNA interactome includes novel RBPs that link transcription, RNA processing, chromatin regulation and DNA repair, and will serve as a stepping-stone for further investigation of the underlying molecular mechanisms using gene-centered methods.Here we introduce serIC for global in vivo crosslinking event, while the proportions of different RBP classes are not expected to change during more stringent washes. Conversely, more stringent purification procedures are expected to preferentially reduce the contribution from non-crosslinked non-specific protein interactions. In line with this, we observe non-crosslinked background proteins in non-irradiated controls after a single round of purification, which are eliminated after the second purification step of serIC. The enrichment of unfolded-protein binding chaperones in IC samples suggests that specific non-crosslinked interactions can be induced when captured RNA molecules are coupled to unfolded proteins in crosslinked samples, leading to false-positive RBP identification when comparing with non-crosslinked controls.We observe a shift in domain composition of the nuclear RNA interactome compared with previous RBP catalogues derived by IC. The most substantial reduction is observed for previous candidate RBPs without known RBDs, despite high abundance of individual candidates in K562 nuclei, while observing no differences in purification efficiency or detection sensitivity of serIC compared with IC experiments14The distinct biological and structural features of the nuclear RNA interactome provide additional evidence for the high purity of RBP catalogues derived by serIC. No-RBD proteins detected by serIC are enriched for known features of classic RBPs compared with IC-only candidates, including a higher proportion of amino acids in disordered and low complexity regions15Coupling of serIC to intermittent enzymatic treatment is effective for the elimination of contaminating DNA, as evidenced by the removal of 38 DNA-binding proteins compared with IC. Elution of intact RBP–poly(A)-RNA complexes into low-salt conditions after each round of purification enables coupling of serIC to any additional isolation- or modification step, such as differential centrifugation, enzymatic treatment, labelling or affinity purifications. As long as these intermittent treatments leave RNA–polypeptide complexes intact, additional rounds of oligod(T)-capture can be performed.Having ensured elimination of DNA from serIC samples, recovered DNA-binding proteins are likely to have dual DNA–RNA-binding specificities. Several modes of action have been proposed for DRBPs. DRBPs can bind DNA and RNA independently to execute multiple related or unrelated functions5456foci is RNAse sensitive and dependent on the local production of small RNAs that are generated in a Drosha and Dicer dependent manner12376061A notable feature of the nuclear RNA interactome is the extended network of RNA binding DDR components. The identification of multiple regulators and effectors of p53 signalling and the recovery of the NHEJ module by serIC is in line with the emergent role of RNA biology in the DDR33343536bona fide RBPs in vivo. At the same time, novel tools to globally recover non-polyadenylated RNA–protein complexes are needed to complete our picture of the RNA interactome. Accordingly, some aspects of the first RNA interactomes may have to be reassessed as we have certainly not yet unraveled the full extent of RBPs in the human genome.Taken together, the first human nuclear RNA interactome presented here provides a resource for the future investigation of RNA-guided nuclear processes. In addition to the improved specificity provided by the serIC method, continuous refinement of experimental approaches and increasing MS sensitivity will further improve the ability to detect 2. For one replicate serIC experiment, 4 × 500 ml suspension culture were amplified to a density of 1 × 106 cells per ml and collected by centrifugation at 200g and 4 °C. Cells were combined, washed with cold PBS, split in half and irradiated in a stratalinker with 0.4 J cm−2 UVC light (256 nm) or used as non-crosslinked control. Cells were recollected by centrifugation and resuspended in NP-40 lysis buffer ; 1/2,000 SUPERaseIn RNase Inhibitor (Thermo Fisher)). After 5-min incubation on ice, cells were gently layered over a cold sucrose cushion  and centrifuged for 10 min at 1,000g. Nuclei were resuspended in IC lysis buffer  and DNA was sheared by passing through a 20 1/2G needle.K562 (ATTC) cells were grown in suspension culture at 75 r.p.m. in RPMI1640 medium supplemented with 10% fetal calf serum and antibiotics, and maintained at 37 °C and 5% COg. The chromatin pellet was rinsed in cold PBS, snap frozen in liquid nitrogen, resuspended in chromatin lysis buffer A ) and crushed by passage through a 10-ml syringe and 20 1/2G needle. After adding chromatin lysis buffer B , the sample was filtered through a 100-μm cell strainer.For chromatin isolation, nuclei were instead resuspended in Glycerol buffer , mixed with Urea buffer  and centrifuged for 3 min at 3,500First purification. The first part of the serIC purification was done largely as described by Castello et al.Enzymatic treatment and second purification. Triplicate eluates were pooled in 5-ml Eppendorf LoBind tubes. We added Turbo DNAse buffer and 40 μl Turbo DNAse; 40 μl superRNAsin; complete protease inhibitor; and incubated in 1.5-ml protein Lobind Eppendorf tubes at 37 °C for 20 min. Samples were transferred into falcon tubes and 3.5 ml fresh oligo (dT) dynabeads equilibrated in 12 ml IC lysis buffer were added. After 1 h rotation at RT, beads were collected on a magnet and the supernatant was kept on 4 °C for repeated purification. Beads were washed with IC lysis buffer for 5 min at RT, collected on a magnet and transferred to a 5-ml protein Lobind tube. Beads were washed twice with wash buffer 1; twice with wash buffer 2; and twice with wash buffer 3. After transfer to a 1.5-ml LoBind tube, RNA–protein complexes were incubated in elution buffer at 55 °C and 1,100 r.p.m. for 2 min. Beads were collected on a magnet, and the supernatant cleared on the magnet one more time. The cleared eluate was snap frozen and stored at −80 °C. Beads were resuspended in IC Lysis buffer and added back to the supernatant for two additional rounds of purification. All three eluates were pooled before downstream analysis.RNAse buffer  and RNAse A/T1 (200 U) were added to the remaining eluate and incubated for 1 h at 37 °C. One per cent of the material was used for SDS–PAGE and silver staining with the Pierce Silver Stain Kit (Thermo Fisher). The rest was used in LC-MS/MS.2) and 5 μg proteinase K for 1 h at 50 °C. RNA and DNA were isolated with Phenol chloroform. Reverse transcription was performed with and without RT-enzyme to monitor DNA contamination. RNA was reverse transcribed using the High-Capacity RNA-to-cDNA Kit (Invitrogen 4387406). cDNA was quantified on a 7900HT Fast Real-Time PCR system (Applied Biosystems) using the SYBR Green PCR Master Mix (Invitrogen 4364344).To isolate RNA, 1% of the final pooled eluate was incubated with proteinase K buffer . Nanoelectrospray was generated by applying 3 kV. A cycle of one full Fourier transformation scan mass spectrum  was followed by 12 data-dependent MS/MS scans with a normalised collision energy of 25 eV. A dynamic exclusion window of 30 s was used to avoid repeated sequencing of the same peptides. MS data were analysed by MaxQuant (v1.5.0.0)Samples for the serial RNA interactome capture were reduced in 50 mM DTT at 56 °C for 1 h and alkylated with a final concentration of 5.5 mM chloroacetamide for 30 min. Proteins were precipitated by four excess volumes of acetone at −20 C° ON. After two sequential acetone washes, lyophilized pellets were resuspended in 50 mM ammonium bicarbonate and 10% acetonitrile on a thermo rocker and proteins were digested by 0.75 μg trypsin at 37 °C ON. Peptides were desalted using C18 StageTips  and lyophilized. 10% of each sample was used for direct LC–MS analysis, the rest was further separated using six pH fractions  of strong anion-exchange chromatography , according to ref. P values were obtained by the method of Benjamini–Hochberg.GO annotations, Pfam and Interpro Domain annotations for the identified proteins were retrieved from the geneontology website and using ENSEMBL Biomart and the Ensembl Human release 81 (GRCh38.p3). Proteins were grouped for the presence of classic or non-classic RNA binding domains as in ref. For each amino-acid position in a protein a score for intrinsic disorder was derived using IUPredPPI interaction networks were calculated using the GeneMANIA algorithm. We used the full information provided by the GeneMANIA database, including 287 co-expression data sets, 3 co-localization data sets, 7 genetic interaction data sets, 7 pathway collections, 190 data sets with physical interactions and 42 interaction prediction data sets were used to identify the 20 next neighbouring proteins of the 22 DDR-related query genes. Only physical and pathway interactions were used to visualize the network map.Accession codes: The mass spectrometry proteomics data have been deposited to the ProteomeXchange with the dataset identifier PXD003664.How to cite this article: Conrad, T. et al. Serial interactome capture of the human cell nucleus. Nat. Commun. 7:11212 doi: 10.1038/ncomms11212 (2016).Supplementary Figures 1-6 and Supplementary MethodsOverview of identified proteins in noCl and UV treated samples


Lutjanus campechanus 13 km off Port Mansfield, Texas, at a reef composed of more than 4000 concrete culverts. The study spanned from May to June in 2013 and 2014, and sites sampled included natural reefs, bare areas, and varying culvert patch density categories, ranging from 1–190 culverts. Abundances of adults and species evenness of juvenile populations differed between the years. Fish communities did not significantly differ among density categories; however, highest species richness and total abundances were observed at intermediate culvert densities and at natural reefs. Whereas the abundance of L. campechanus did not differ among density categories, mean total lengths of L. campechanus were greatest at the lower density. Our findings suggest that reefs should be deployed with intermediate patch density of 71–120 culverts in a 30-m radius to yield the highest fish abundances.Artificial reefs continue to be added as habitat throughout the world, yet questions remain about how reef design affects fish diversity and abundance. In the present study, the effects of reef density were assessed for fish communities and sizes of economically valuable  Natural reef cover is sparse or diminishing in many locations, including the Middle East, Pacific Ocean, Caribbean Sea, and the Gulf of Mexico –4. ArtifConcrete is commonly used for artificial reefs due to its availability, low cost, nontoxic characteristics, and durability . ConcretLutjanus campechanus and its over-fished status in the Gulf of Mexico (GOM) since the 1980s [Lutjanus campechanus is a relatively long-lived fish commonly found over hard structure in the GOM that undergoes ontogenic habitat shifts as it grows [L. campechanus utilize low-relief, rubble-shell habitat, then move to more complex habitats, such as nearshore reefs [L. campechanus over different reefs.Artificial reefs have been attributed to improved sport and commercial fisheries ,17. Anglhe 1980s –20. Lutjit grows ,21,22. Ere reefs . Years lre reefs ,23. ThesL. campechanus populations and mean total lengths were compared separately across all reef categories. Our predictions were that:In research comparing artificial reefs to local natural reefs, some studies have found that natural reefs have higher species abundance and richness –26. MorePatch reefs with higher concrete density would have higher fish diversity and abundance.Natural reef patches would have the highest diversity of fishes and abundance of juveniles due to their structural complexity, as compared to concrete reef patches.Lutjanus campechanus would be largest at the densest concrete reefs, but smallest at natural reefs because of their low-relief, which is characteristic of juvenile habitat.The study was conducted at the PS-1047 Reef (N 26° 31.535’–W 97° 09.215’), which has an average depth of 21 m. PS-1047 is part of the Texas Artificial Reef Nearshore Reefing Program, and is located 13 km from the Port Mansfield jetties in Texas state waters. As of August 21, 2011, 4,922 concrete culverts of various sizes occupied the sand and mud sea floor in patch formations. Natural reef patches were also identified at the fringes of the reefing area and outside of the reefing area at the same 21-m depth. Natural reefs were composed of hard clay and sandstone base with solitary soft corals and octocorals, algae, sponges, and polychaete worms. The natural reef patches surveyed in this study were similar to Seven and One-Half Fathom Reef, a well-studied reef of lacustrine origin composed of hard clay and sandstone with sponges, hydroids, ascidians, and polychaete worms –31.At each survey site, all structure within a 30-m radius was quantified, and six patch categories were used overall : naturalInitially, culvert sites were located with a low resolution survey map provided by Texas Parks and Wildlife Department. Each potential site was further surveyed by SCUBA divers to assess the type of structure present. Later, a side scan sonar unit  was acquired to further characterize existing sites, and locate additional sites, including natural patches. In June and July of 2013, twelve sites consisting of four categories (sample size) were sampled: B (3); CC1 (3); CC2 (3); & CC4 (3). The same sites were sampled again in May to July 2014. Additionally in 2014, more reef sites were surveyed for a total of 20 sites and five categories consisting of: CC1 (4); CC2 (3); CC3 (3); CC4 (4); and N (6).To characterize each survey site, still frames from three 200-m transect lines of side scan sonar (40.176 pixels/m) were produced from SonarTRX software . The frames were later imported into ImageJ processing software  to count culverts, and to better describe the culvert categories. While the side scan sonar in this study was used to detect large scale differences in relief (>0.2 m), small complexity differences (<0.1 m) were not measured. Additional measures of habitat characteristics were calculated from ImageJ, including substrate rugosity, percent substrate cover (%), and vertical relief . To measure substrate rugosity, a line was drawn tracing the structural relief over a 60-m length of the reef site. The length of the line was then divided by 60 m to calculate a substrate rugosity index for each site. Percent substrate cover was calculated by measuring how much of the reef site (in a 30-m radius circle) was covered by structure. Average and maximum vertical relief were calculated by measuring substrate height every meter along the 60-m length of the reef site.Visual SCUBA fish surveys were conducted for 15 min as follows: reef-associated fishes were quantified via stationary cylinder census , and cryL. campechanus lengths using parallel lasers, 0.3 m apart, mounted on an aluminum flat bar (3.9 x 70.0 x 0.3 cm) with a high definition camera attached . The second diver aimed the lasers at the broad side of L. campechanus to record as many as possible in the 15-min period. To reduce the chances of sampling the same individual, the diver stayed at the same location in the water column. Lutjanus campechanus total lengths were collected from scaled videos and manual measurements using a ruler in Adobe Premier Pro software . In some cases, video attenuation did not allow for accurate estimation of L. campechanus sizes, and these recordings were excluded. On average, 78 ± 8 L. campechanus were measured in each reef category. Ages were then estimated from 558 total length measurements using the Von Bertalanffy Growth Model derived by Syc (2011):Alongside the surveys in 2014, a second diver recorded For adult, juvenile, and whole community abundances, the following analyses were applied. Species abundances in sites sampled both years were square-root transformed, and were compared against initial reef categories and year in a two-way permutational analysis of variance (PERMANOVA), using the Bray-Curtis similarity index . Reef viSimilar analyses were conducted to assess species abundances of adults, juveniles, and whole communities over all reef categories surveyed in 2014 in one-way PERMANOVAs. Principal Components Analysis (PCA) was conducted to assess how sample sites differed among substrate rugosity, average vertical relief, maximum vertical relief, and percent cover. All multivariate analyses were performed using PRIMER-E v6 package.Lutjanus campechanus abundances and lengths were both compared among reef categories in 2014 using one-way ANOVAs. All univariate analyses were performed using SPSS IBM Statistics v20 package.Species indices  were assessed over reef categories and year using two-way analyses of variance (ANOVA). Species indices from 2014, with five reef categories were assessed using one-way ANOVAs. No specific permissions were required for any of the activities undertaken during the research at any of the sites visited. The study was conducted at a publicly accessible reef (PS-1047) that is in Texas state waters, and is part of the Texas Artificial Reef Nearshore Reefing Program. The reef does not lie in protected areas, or in a state park or national park. Endangered or protected species were not involved during any part of the field studies. Vertebrates were studied in the water via visual SCUBA surveys and via video recordings. No vertebrates were collected or sacrificed, and no contact with animals was conducted during any part of the field studies. No approval was required from the Institutional Animal Care and Use Committee, and no field permits were necessary during any part of the experiment.Balistes capriscus, Haemulon aurolineatum, Lutjanus campechanus, Parablennius marmoreus, Pareques umbrosus, and Serranus subligarius. Bare areas did not exhibit reef-associated fishes. Among culvert categories, no significant differences were found among overall community compositions  = 0.844, P = 0.622) or between years  = 1.196, P = 0.271), using multivariate approaches. Reef visibility did not predict differences between surveys regardless of the year  = 0.951, P = 0.500). However, higher adult abundances were observed in 2013 than in 2014 , average vertical relief (0–1.49 m), maximum vertical relief (0–2.95 m), and percent substrate cover (0.76–100%). Two PCs explained 91.6% of variation among the variables tested , and botL. campechanus were observed in this study. No juveniles were observed at culvert sites, but shoals of juveniles were seen at natural sites. Abundance of L. campechanus did not significantly differ among any reef categories  = 1.721, P = 0.205), however the highest abundances were observed over natural reefs and CC3 . Reefs that had fewer than 31 culverts exhibited significantly higher mean lengths of L. campechanus than all other reef categories . All other reef categories did not significantly differ from one another  Von Bertalanffy growth curve equation coefficients, 03 years . When co03 years , average19 years ,34.As expected, bare areas surveyed lacked adult and juvenile reef fishes, while areas with artificial reef habitat had diverse populations of reef fishes. Regardless of the number of culverts present in each patch category, reef fish species were observed at culvert reef sites with relatively similar abundances. The lack of difference in fish communities may be due to the structural similarity of the concrete culverts. While culverts found at PS-1047 are not all the same shape and size, the majority are smooth concrete cylinders averaging 1 m wide by 3 m long. A similar study tested the effects of culvert block shape (flat end vs. flush block reefs) and found no significant differences with regard to colonization rate, species richness, or diversity .Some studies suggest that artificial reefs should be structurally complex, and should be similar to natural reefs to better mimic fish habitat ,36. HoweIn the present study, although natural and artificial reefs had similar fish community compositions, natural reefs and the third culvert category (CC3: 71–120 culverts) had the highest observed species abundance and richness. Assessing adult and juvenile populations may better elucidate observed patterns, because habitat selection is different for both age groups of certain species –40. JuveLutjanus campechanus have started to recover due to increased management practices and additional habitat [L. campechanus are using artificial habitat. In the present study, L. campechanus abundances did not vary among reef density categories, however highest values were observed at CC3 and natural sites. Although the effect of habitat density on the abundance of L. campechanus is unclear, shoals of L. campechanus were observed at all sights studied. Such findings insinuate that PS-1047 holds suitable habitat for this species.In recent years, populations of  habitat . Yet resL. campechanus juveniles were only seen at low-relief natural reefs, not at culvert reefs. Natural reefs have more complex habitats, with varying substrate sizes, and may indeed serve as nursery grounds for L. campechanus [L. campechanus are reported to move to an environment with higher relief [L. campechanus at natural and culvert reefs. Some young adults might remain at natural patches to continue growing, while others might move to the higher-relief culvert reefs.As expected, pechanus ,23. Predpechanus . As adulr relief , such asL. campechanus at natural and culvert reefs, mean lengths were significantly larger at the lowest culvert density (CC1). This suggests some density dependent effect at the smallest reef patch category, where larger fish could monopolize the structures and drive away smaller individuals. Reports of similar density-dependent behaviors have been observed for L. campechanus [Mycteroperca microlepis [Despite similar mean lengths of pechanus  and for crolepis .L. campechanus in this study was estimated at 2 years old. These age estimates should be verified with otolith samples taken directly from PS-1047 populations, but such a small average age suggests that many L. campechanus at these patch reefs are not yet sexually mature [L. campechanus ages from otolith samples of recreational and commercial catches [L. campechanus to grow before moving to other areas [When lengths were converted into ages, the average age of y mature . Other s catches ,34,51–53 catches , or the The findings in the present study suggest that an intermediate density of culverts (71–120 culverts) would be the most efficient use of the material deployed. Moreover, culvert reefs at the intermediate density hold similar species abundances as natural reefs surveyed in this study. In future deployments, an intermediate density of culverts in a 30-m radius will be a more effective and efficient use of concrete structure, and will yield high fish diversity and secondary production.S1 Appendix(DOCX)Click here for additional data file.S2 AppendixCC1: 1–30 culverts, CC2: 31–70 culverts, CC3: 71–120 culverts, CC4: 121–190 culverts, and Natural: naturally-occurring reefs. Error bars represent standard error (± 1).(TIF)Click here for additional data file.