Identification Of Small Non-coding RNAs Research Articles

Multi-omics characterization and identification of small non-coding RNAs in Spiroplasma eriocheiris

Spiroplasma eriocheiris is the major pathogen in the aquaculture shrimp and crab tremor disease; its infection causes heavy losses in aquaculture. Previous investigations concentrated on how the host responds to S. eriocheiris infection, with little known on the regulation of virulence and pathogenesis by the bacteria themselves. A body of increasing evidence shows that bacterial small noncoding RNAs (sRNAs) play a crucial part in regulating bacterial virulence and pathogenesis; however, whether there are some sRNAs in S. eriocheiris and how those sRNAs regulate virulence and pathogenesis are still unclear. This study analyzed multi-omics data integration to identify the potential sRNAs and their mediated regulatory network in S. eriocheiris. First, through an integration analysis of the public genomic and transcriptomic data, 54 potential sRNAs were identified in S. eriocheiris with a 50–250 nt length distribution and the base composition mainly AT. Next, sRNA profiling of the in vitro logarithmic and decline phase of S. eriocheiris, as well as the early and onset stage of infection in Eriocheir sinensis, was performed, showing that 4 sRNAs (SR01, SR05, SR08, and S04) were both down-regulated in the logarithmic and the onset stage of infection. Subsequently, integrated with sRNAs target gene prediction and target gene expression analysis, a regulatory network composed of four sRNAs and 96 target genes was constructed. Last, an RNA pull-down experiment was performed on the SR01, which exhibited the highest abundance and the highest number of target genes, resulting in 37 highly credible target genes with multiple genes related to bacterial virulence, such as GTPases and virulence factor coding genes. Collectively, this study identified the sRNAs in S. eriocheiris and revealed their mediated regulatory network for regulating virulence and pathogenesis, thus paving a new avenue for disease prevention and control in aquaculture.

Identification of small non-coding RNAs from Rhizobium etli by integrated genome-wide and transcriptome-based methods

BackgroundSmall non-coding RNAs (sRNAs) are regulatory molecules, present in all forms of life, known to regulate various biological processes in response to the different environmental signals. In recent years, deep sequencing and various other computational prediction methods have been employed to identify and analyze sRNAs.ResultsIn the present study, we have applied an improved sRNA scanner method to predict sRNAs from the genome of Rhizobium etli, based on PWM matrix of conditional sigma factor 32. sRNAs predicted from the genome are integrated with the available stress specific transcriptome data to predict putative conditional specific sRNAs. A total of 271 sRNAs from the genome and 173 sRNAs from the transcriptome are computationally predicted. Of these, 25 sRNAs are found in both genome and transcriptome data. Putative targets for these sRNAs are predicted using TargetRNA2 and these targets are involved in a wide array of cellular functions such as cell division, transport and metabolism of amino acids, carbohydrates, energy production and conversion, translation, cell wall/membrane biogenesis, post-translation modification, protein turnover and chaperones. Predicted targets are functionally classified based on COG analysis and GO annotations.ConclusionsRNAs predicted from the genome, using PWM matrices for conditional sigma factor 32 could be a better method to identify the conditional specific sRNAs which expand the list of putative sRNAs from the intergenic regions (IgRs) of R. etli and closely related α-proteobacteria. sRNAs identified in this study would be helpful to explore their regulatory role in biological cellular process during the stress.

Identification of small non-coding RNAs as sperm quality biomarkers for in vitro fertilization

Identification of small non-coding RNAs as sperm quality biomarkers for in vitro fertilization

Association of Circulating Transfer RNA fragments with antibody response to Mycoplasma bovis in beef cattle

BackgroundHigh throughput sequencing allows identification of small non-coding RNAs. Transfer RNA Fragments are a class of small non-coding RNAs, and have been identified as being involved in inhibition of gene expression. Given their role, it is possible they may be involved in mediating the infection-induced defense response in the host. Therefore, the objective of this study was to identify 5′ transfer RNA fragments (tRF5s) associated with a serum antibody response to M. bovis in beef cattle.ResultsThe tRF5s encoding alanine, glutamic acid, glycine, lysine, proline, selenocysteine, threonine, and valine were associated (P < 0.05) with antibody response against M. bovis. tRF5s encoding alanine, glutamine, glutamic acid, glycine, histidine, lysine, proline, selenocysteine, threonine, and valine were associated (P < 0.05) with season, which could be attributed to calf growth. There were interactions (P < 0.05) between antibody response to M. bovis and season for tRF5 encoding selenocysteine (anticodon UGA), proline (anticodon CGG), and glutamine (anticodon TTG). Selenocysteine is a rarely used amino acid that is incorporated into proteins by the opal stop codon (UGA), and its function is not well understood.ConclusionsDifferential expression of tRF5s was identified between ELISA-positive and negative animals. Production of tRF5s may be associated with a host defense mechanism triggered by bacterial infection, or it may provide some advantage to a pathogen during infection of a host. Further studies are needed to establish if tRF5s could be used as a diagnostic marker of chronic exposure.

An improved method for identification of small non-coding RNAs in bacteria using support vector machine

Bacterial small non-coding RNAs (sRNAs) are not translated into proteins, but act as functional RNAs. They are involved in diverse biological processes like virulence, stress response and quorum sensing. Several high-throughput techniques have enabled identification of sRNAs in bacteria, but experimental detection remains a challenge and grossly incomplete for most species. Thus, there is a need to develop computational tools to predict bacterial sRNAs. Here, we propose a computational method to identify sRNAs in bacteria using support vector machine (SVM) classifier. The primary sequence and secondary structure features of experimentally-validated sRNAs of Salmonella Typhimurium LT2 (SLT2) was used to build the optimal SVM model. We found that a tri-nucleotide composition feature of sRNAs achieved an accuracy of 88.35% for SLT2. We validated the SVM model also on the experimentally-detected sRNAs of E. coli and Salmonella Typhi. The proposed model had robustly attained an accuracy of 81.25% and 88.82% for E. coli K-12 and S. Typhi Ty2, respectively. We confirmed that this method significantly improved the identification of sRNAs in bacteria. Furthermore, we used a sliding window-based method and identified sRNAs from complete genomes of SLT2, S. Typhi Ty2 and E. coli K-12 with sensitivities of 89.09%, 83.33% and 67.39%, respectively.

Systematic and functional identification of small non-coding RNAs associated with exogenous biofuel stress in cyanobacterium Synechocystis sp. PCC 6803

BackgroundThe unicellular model cyanobacterium Synechocystis sp. PCC 6803 is considered a promising microbial chassis for biofuel production. However, its low tolerance to biofuel toxicity limits its potential application. Although recent studies showed that bacterial small RNAs (sRNAs) play important roles in regulating cellular processes in response to various stresses, the role of sRNAs in resisting exogenous biofuels is yet to be determined.ResultsBased on genome-wide sRNA sequencing combined with systematic analysis of previous transcriptomic and proteomic data under the same biofuel or environmental perturbations, we report the identification of 133 trans-encoded sRNA transcripts with high-resolution mapping of sRNAs in Synechocystis, including 23 novel sRNAs identified for the first time. In addition, according to quantitative expression analysis and sRNA regulatory network prediction, sRNAs potentially involved in biofuel tolerance were identified and functionally confirmed by constructing sRNA overexpression or suppression strains of Synechocystis. Notably, overexpression of sRNA Nc117 revealed an improved tolerance to ethanol and butanol, while suppression of Nc117 led to increased sensitivity.ConclusionsThe study provided the first comprehensive responses to exogenous biofuels at the sRNA level in Synechocystis and opens an avenue to engineering sRNA regulatory elements for improved biofuel tolerance in the cyanobacterium Synechocystis.

Role of Non-coding Regulatory RNA in the Virulence of Human Pathogenic Vibrios.

In recent decades, the identification of small non-coding RNAs in bacteria has revealed an important regulatory mechanism of gene expression involved in the response to environmental signals and to the control of virulence. In the family Vibrionaceae, which includes several human and animal pathogens, small non-coding RNAs (sRNAs) are closely related to important processes including metabolism, quorum sensing, virulence, and fitness. Studies conducted in silico and experiments using microarrays and high-throughput RNA sequencing have led to the discovery of an unexpected number of sRNAs in Vibrios. The present review discusses the most relevant reports regarding the mechanisms of action of sRNAs and their implications in the virulence of the main human pathogens in the family Vibrionaceae: Vibrio parahaemolyticus, V. vulnificus and V. cholerae.

Experimental Identification of Small Non-Coding RNAs in the Model Marine Bacterium Ruegeria pomeroyi DSS-3.

In oligotrophic ocean waters where bacteria are often subjected to chronic nutrient limitation, community transcriptome sequencing has pointed to the presence of highly abundant small RNAs (sRNAs). The role of sRNAs in regulating response to nutrient stress was investigated in a model heterotrophic marine bacterium Ruegeria pomeroyi grown in continuous culture under carbon (C) and nitrogen (N) limitation. RNAseq analysis identified 99 putative sRNAs. Sixty-nine were cis-encoded and located antisense to a presumed target gene. Thirty were trans-encoded and initial target prediction was performed computationally. The most prevalent functional roles of genes anti-sense to the cis-sRNAs were transport, cell-cell interactions, signal transduction, and transcriptional regulation. Most sRNAs were transcribed equally under both C and N limitation, and may be involved in a general stress response. However, 14 were regulated differentially between the C and N treatments and may respond to specific nutrient limitations. A network analysis of the predicted target genes of the R. pomeroyi cis-sRNAs indicated that they average fewer connections than typical protein-encoding genes, and appear to be more important in peripheral or niche-defining functions encoded in the pan genome.

Transcriptome-Wide Identification of Hfq-Associated RNAs in Brucella suis by Deep Sequencing.

Recent breakthroughs in next-generation sequencing technologies have led to the identification of small noncoding RNAs (sRNAs) as a new important class of regulatory molecules. In prokaryotes, sRNAs are often bound to the chaperone protein Hfq, which allows them to interact with their partner mRNA(s). We screened the genome of the zoonotic and human pathogen Brucella suis 1330 for the presence of this class of RNAs. We designed a coimmunoprecipitation strategy that relies on the use of Hfq as a bait to enrich the sample with sRNAs and eventually their target mRNAs. By deep sequencing analysis of the Hfq-bound transcripts, we identified a number of mRNAs and 33 sRNA candidates associated with Hfq. The expression of 10 sRNAs in the early stationary growth phase was experimentally confirmed by Northern blotting and/or reverse transcriptase PCR. Brucella organisms are facultative intracellular pathogens that use stealth strategies to avoid host defenses. Adaptation to the host environment requires tight control of gene expression. Recently, small noncoding RNAs (sRNAs) and the sRNA chaperone Hfq have been shown to play a role in the fine-tuning of gene expression. Here we have used RNA sequencing to identify RNAs associated with the B. suis Hfq protein. We have identified a novel list of 33 sRNAs and 62 Hfq-associated mRNAs for future studies aiming to understand the intracellular lifestyle of this pathogen.

Structural and Biochemical Studies of the RNA-Associated Sm Protein Superfamily

Sm proteins comprise a broad, evolutionarily conserved family that plays key roles in RNA processing, in organisms ranging from bacteria to human. Eukaryotic Sm proteins form snRNP cores and help organize the RNA splicing machinery, while bacterial Sm proteins (Hfq) interact with small noncoding RNAs to regulate quorum sensing and other sRNA-based pathways; the existence of Sm-like proteins in the Archaea suggests the importance of this ancient family in the early evolution of RNA processing. To decipher the intricate structure ↔ function ↔ evolution relationships in this family, we are pursuing three lines of work that encompass computational analysis and experimental discovery: (i) development of a quantitative ‘definition’ of the Sm fold, enabling structural analyses and comparison to other small nucleic acid-binding folds, as well as molecular dynamics simulations of Sm proteins; (ii) discovery and identification of small noncoding RNAs bound in vivo by Sm homologs from deep-branching phyla; (iii) crystallographic studies of archaeal Sm proteins and assemblies. Recent results from these directions will be presented.

Identification of small non-coding RNAs in the planarian Dugesia japonica via deep sequencing

Freshwater planarian flatworm possesses an extraordinary ability to regenerate lost body parts after amputation; it is perfect organism model in regeneration and stem cell biology. Recently, small RNAs have been an increasing concern and studied in many aspects, including regeneration and stem cell biology, among others. In the current study, the large-scale cloning and sequencing of sRNAs from the intact and regenerative planarian Dugesia japonica are reported. Sequence analysis shows that sRNAs between 18nt and 40nt are mainly microRNAs and piRNAs. In addition, 209 conserved miRNAs and 12 novel miRNAs are identified. Especially, a better screening target method, negative-correlation relationship of miRNAs and mRNA, is adopted to improve target prediction accuracy. Similar to miRNAs, a diverse population of piRNAs and changes in the two samples are also listed. The present study is the first to report on the important role of sRNAs during planarian Dugesia japonica regeneration.

Deep sequencing-based identification of small non-coding RNAs in Streptomyces coelicolor

Streptomyces coelicolor is considered the model organism among Gram positive, GC rich bacteria. Its genome has been sequenced but little is known about the occurrence and distribution of small non-coding RNAs in this biotechnologically relevant organism. Using deep sequencing we analyzed the transcriptome at the end of exponential growth, which corresponds to the onset of secondary metabolism. We mapped 193 transcriptional start sites of mRNA genes and identified putative new and alternative open reading frames. We identified 63 non-coding RNAs including 29 cis encoded antisense RNAs, and confirmed expression for 11, most of them being growth-phase dependent. A comparison between the sequencing results and bioinformatic sRNA predictions using Dynalign and RNAz revealed only a small overlap between the different approaches.

Identification of Small Noncoding RNAs in Helicobacter pylori by a Bioinformatics-Based Approach

Small noncoding RNAs (sRNAs) are a group of regulatory RNA molecules normally without a protein-coding function. In recent years, the importance of sRNAs as mediators of gene expression in bacteria has begun to be recognized. More than 70 sRNAs have been known in Escherichia coli. However, little is known about sRNAs in Helicobacter pylori, a human pathogen associated with gastric diseases. Here, we systematically identified sRNAs in the H. pylori genome by a computational approach based on gene location, sequence conservation, promoter and terminator search, and secondary structure. Among a total of six candidate sRNAs initially predicted, two novel sRNAs (IG-443 and IG-524) were confirmed by Northern blot and reverse transcription-polymerase chain reaction (RT-PCR). Virtually, they were a class of natural antisense transcripts, which were complementary to partial sequences of the following genes: flagellar motor switch gene (fliM) and fumarase (fumC). Taken together, the results indicate that there exist novel sRNAs in H. pylori and these RNAs might play a potential role in regulating gene expression.

Identification of small non-coding RNAs from mitochondria and chloroplasts

Small non-protein-coding RNAs (ncRNAs) have been identified in a wide spectrum of organisms ranging from bacteria to humans. In eukarya, systematic searches for ncRNAs have so far been restricted to the nuclear or cytosolic compartments of cells. Whether or not small stable non-coding RNA species also exist in cell organelles, in addition to tRNAs or ribosomal RNAs, is unknown. We have thus generated cDNA libraries from size-selected mammalian mitochondrial RNA and plant chloroplast RNA and searched for small ncRNA species in these two types of DNA-containing cell organelles. In total, we have identified 18 novel candidates for organellar ncRNAs in these two cellular compartments and confirmed expression of six of them by northern blot analysis or RNase A protection assays. Most candidate ncRNA genes map to intergenic regions of the organellar genomes. As found previously in bacteria, the presumptive ancestors of present-day chloroplasts and mitochondria, we also observed examples of antisense ncRNAs that potentially could target organelle-encoded mRNAs. The structural features of the identified ncRNAs as well as their possible cellular functions are discussed. The absence from our libraries of abundant small RNA species that are not encoded by the organellar genomes suggests that the import of RNAs into cell organelles is of very limited significance or does not occur at all.

Experimental RNomics in Aquifex aeolicus: identification of small non-coding RNAs and the putative 6S RNA homolog

By an experimental RNomics approach, we have generated a cDNA library from small RNAs expressed from the genome of the hyperthermophilic bacterium Aquifex aeolicus. The library included RNAs that were antisense to mRNAs and tRNAs as well as RNAs encoded in intergenic regions. Substantial steady-state levels in A.aeolicus cells were confirmed for several of the cloned RNAs by northern blot analysis. The most abundant intergenic RNA of the library was identified as the 6S RNA homolog of A.aeolicus. Although shorter in size (150 nt) than its γ-proteobacterial homologs (∼185 nt), it is predicted to have the most stable structure among known 6S RNAs. As in the γ-proteobacteria, the A.aeolicus 6S RNA gene (ssrS) is located immediately upstream of the ygfA gene encoding a widely conserved 5-formyltetrahydrofolate cyclo-ligase. We identifed novel 6S RNA candidates within the γ-proteobacteria but were unable to identify reasonable 6S RNA candidates in other bacterial branches, utilizing mfold analyses of the region immediately upstream of ygfA combined with 6S RNA blastn searches. By RACE experiments, we mapped the major transcription initiation site of A.aeolicus 6S RNA primary transcripts, located within the pheT gene preceding ygfA, as well as three processing sites.