Small RNA gene identification and mRNA target predictions in bacteria

A Reduction of Transcriptional Regulation in Aquatic Oligotrophic Microorganisms Enhances Fitness in Nutrient-Poor Environments

In this review, we consider the regulatory strategies of aquatic oligotrophs, microbial cells that are adapted to thrive under low-nutrient concentrations in oceans, lakes, and other aquatic ecosystems. Many reports have concluded that oligotrophs use less transcriptional regulation than copiotrophic cells, which are adapted to high nutrient concentrations and are far more common subjects for laboratory investigations of regulation. It is theorized that oligotrophs have retained alternate mechanisms of regulation, such as riboswitches, that provide shorter response times and smaller amplitude responses and require fewer cellular resources. We examine the accumulated evidence for distinctive regulatory strategies in oligotrophs. We explore differences in the selective pressures copiotrophs and oligotrophs encounter and ask why, although evolutionary history gives copiotrophs and oligotrophs access to the same regulatory mechanisms, they might exhibit distinctly different patterns in how these mechanisms are used. We discuss the implications of these findings for understanding broad patterns in the evolution of microbial regulatory networks and their relationships to environmental niche and life history strategy. We ask whether these observations, which have emerged from a decade of increased investigation of the cell biology of oligotrophs, might be relevant to recent discoveries of many microbial cell lineages in nature that share with oligotrophs the property of reduced genome size.

Selective extracellular secretion of small double-stranded RNA by Tetragenococcus halophilus

Small double-stranded RNAs (dsRNAs) abundantly produced by lactic acid bacteria demonstrate immunomodulatory activity and antiviral protective immunity. However, the extracellular secretion of dsRNA from lactic acid bacteria and their compositional and functional differences compared to the intracellular dsRNA is unknown. In this study, we compared the intracellular and secreted extracellular dsRNA of the lactic acid bacteria, Tetragenococcus halophilus, commonly present in fermented foods, by growing in RNA-free and RNase-free media. We used RNA deep sequencing and in-silico analysis to annotate potential regulatory functions for the comparison. A time series sampling of T. halophilus culture demonstrated growth phase-dependent dynamics in extracellular dsRNA secretion with no major change in the intracellular dsRNA profile. The RNA deep sequencing resulted in thousands of diverse dsRNA fragments with 14-21 nucleotides in size from T. halophilus culture. Over 70% of the secreted extracellular dsRNAs were unique in their sequences compared to the intracellular dsRNAs. Furthermore, the extracellular dsRNA abundantly contains sequences that are not T. halophilus genome encoded, not detected intracellularly and showed higher hits on human transcriptome during in-silico analysis, which suggests the presence of extrachromosomal mobile regulatory elements. Further analysis showed significant enrichment of dsRNA target genes of human transcriptome on cancer pathways and transcription process, indicating the extracellular dsRNA of T. halophilus is different not only at the sequence level but also in function. Studying the bacterial extracellular dsRNA is a promising area of future research, particularly for developing postbiotic fermented functional foods and understanding the impact of commensal gut bacteria on human health.

Small regulatory RNAs of oral streptococci and periodontal bacteria

Small regulatory RNAs (sRNAs) belong to a family of non-coding RNAs, and many of which regulate expression of genes via interaction with mRNA. The recent popularity of high-throughput next generation sequencers have presented abundant sRNA-related data, including sRNAs of several different oral bacterial species. Some sRNA candidates have been validated in terms of their expression and interaction with target mRNAs. Since the oral cavity is an environment constantly exposed to various stimuli, such as fluctuations in temperature and pH, and osmotic pressure, as well as changes in nutrient availability, oral bacteria require rapid control of gene expression for adaptation to such diverse conditions, while regulation via interactions of sRNAs with mRNA provides advantages for rapid adaptation. This review summarizes methods effective for identification and validation of sRNAs, as well as sRNAs identified to be associated with oral bacterial species, including cariogenic and periodontal pathogens, together with their confirmed and putative target genes.

Involvement of non-coding RNAs during infection of rice by Acidovorax oryzae

The expression of non-coding RNAs (ncRNAs) has been observed in a variety of bacteria. However, the function of ncRNAs and their regulatory targets are largely unknown, and few ncRNAs are found to be associated with bacterial virulence. The bacterial brown stripe pathogen Acidovorax oryzae (Ao) RS-1 shows a high level of condition-dependent differential expression of ncRNA, which we identified in a genome wide screen. We experimentally validated 66 differentially expressed ncRNAs using an integrative analysis of conservative genome sequences and transcriptomic data during in vivo interaction of the bacterial pathogen with the rice plant. To test the relevance of the differentially expressed ncRNAs, we chose four with different positions within the genome, and with different secondary structures and promoter activities. The results show that the overexpression of the four ncRNAs caused a significant change in virulence-related phenotypes, resistance to various environmental stresses, expression of secretion systems and effector proteins, while changing the expression of ncRNA putative target genes. We conclude that these ncRNAs are examples for the inherent regulatory roles for many of the observed ncRNAs in response to changing conditions such as host interaction or environmental adaption.

Metatranscriptomic analyses of the oral microbiome

Although the composition of the oral human microbiome is now well studied, regulation of genes within oral microbial communities remains mostly uncharacterized. Current concepts of periodontal disease and caries highlight the importance of oral biofilms and their role as etiological agents of those diseases. Currently, there is increased interest in exploring and characterizing changes in the composition and gene-expression profiles of oral microbial communities. These efforts aim to identify changes in functional activities that could explain the transition from health to disease and the reason for the chronicity of those infections. It is now clear that the functions of distinct species within the subgingival microbiota are intimately intertwined with the rest of the microbial community. This point highlights the relevance of examining the expression profile of specific species within the subgingival microbiota in the case of periodontal disease or caries lesions, in the context of the other members of the biofilm in vivo. Metatranscriptomic analysis of the oral community is the starting point for identifying environmental signals that modulate the shift in metabolism of the community from commensal to dysbiotic. These studies give a snapshot of the expression patterns of microbial communities and also allow us to determine triggers to diseases. For example, in the case of caries, studies have unveiled a potential new pathway of sugar metabolism, namely the use of sorbitol as an additional source of carbon by Streptococcus mutans; and in the case of periodontal disease, high levels of extracellular potassium could be a signal of disease. Longitudinal studies are needed to identify the real markers of the initial stages of caries and periodontal disease. More information on the gene-expression profiles of the host, along with the patterns from the microbiome, will lead to a clearer understanding of the modulation of health and disease. This review presents a summary of these initial studies, which have opened the door to a new understanding of the dynamics of the oral community during the dysbiotic process in the oral cavity.

Comparative Transcriptomic and Functional Assessments of Linezolid-Responsive Small RNA Genes in Staphylococcus aureus

Bacterial small RNAs (sRNAs) are RNA molecules that can have important regulatory roles across gene expression networks. There is a growing understanding of the scope and potential breadth of impact of sRNAs on global gene expression patterns in Staphylococcus aureus, a major human pathogen. Here, transcriptome comparisons were used to examine the roles of sRNA genes with a potential role in the response of S. aureus to antibiotic exposure. Although no measurable impact on key bacterial phenotypes was observed after deleting each of 18 sRNAs identified by these comparisons, this research is significant because it underscores the subtle modes of action of these sometimes abundant molecules within the bacterium.

Staphylococcus aureus contains a repertoire of at least 50 and possibly 500 small RNAs (sRNAs). The functions of most sRNAs are not understood, although some are known to respond to environmental changes, including the presence of antibiotics. Here, in an effort to better understand the roles of sRNAs in the context of antibiotic exposure, we took a clinical methicillin-resistant S. aureus (MRSA) isolate and separately deleted eight sRNAs that were significantly upregulated in response to the last-line antibiotic linezolid as revealed by transcriptome sequencing (RNA-seq) comparisons. We also deleted an additional 10 sRNAs that were either highly expressed or previously found to respond to antibiotic exposure. There were no significant changes for any of the 18 mutants in a variety of phenotypic screens, including MIC screens, growth competition assays in the presence of linezolid, biofilm formation, and resistance to whole-blood killing. These data suggest sRNA functional redundancy, because despite their high expression levels upon antibiotic exposure, individual sRNA genes do not affect readily observable bacterial phenotypes. The sRNA transcriptional changes we measured during antibiotic exposure might also reflect sRNA “indifference,” that is, a general stress response not specifically related to sRNA function. These data underscore the need for sensitive assays and new approaches to try and decipher the functions of sRNA genes in S. aureus.

IMPORTANCE Bacterial small RNAs (sRNAs) are RNA molecules that can have important regulatory roles across gene expression networks. There is a growing understanding of the scope and potential breadth of impact of sRNAs on global gene expression patterns in Staphylococcus aureus, a major human pathogen. Here, transcriptome comparisons were used to examine the roles of sRNA genes with a potential role in the response of S. aureus to antibiotic exposure. Although no measurable impact on key bacterial phenotypes was observed after deleting each of 18 sRNAs identified by these comparisons, this research is significant because it underscores the subtle modes of action of these sometimes abundant molecules within the bacterium.

sRNA OsiA Stabilizes Catalase mRNA during Oxidative Stress Response of Deincoccus radiodurans R1

Deinococcus radiodurans adapts to challenging environments by modulating gene expression in response to oxidative stress. Recently, bacterial small noncoding RNAs (sRNAs) have been presumed to participate in the transcriptional or translational regulation of stress-responsive genes. We found 24 sRNAs that may be involved in the oxidative stress response of D. radiodurans by deep RNA sequencing. Moreover, a typical stress-inducible sRNA, IGR_3053, named OsiA, was predicted to bind to the mRNA of katA, katE, and sodC by the bioinformatics method. An osiA knockout of D. radiodurans displayed increased sensitivity to H₂O₂ and the decreased catalase activity and total antioxidant activity, suggesting that OsiA probably serves as a regulator in the adaptation to oxidative environments. Further microscale thermophoresis results demonstrated that OsiA can directly bind to the mRNA of katA, sodC, and katE. The stability test result of katA mRNA showed that its half-life was 2 min in the osiA mutant compared with 5 min in the wildtype(wt) strain. Our results indicated that OsiA can enhance the stability of katA mRNA and the activity of KatA and consequently the oxidation resistance of D.radiodurans. We are the first one to explore the super-strong oxidative stress resistance of D.radiodurans at the level of post-transcriptional regulation, and found a new pathway that provides a new explanation for the long-term adaptability of D.radiodurans in extreme environments.

Whole genome sequence of moderate halophilic marine bacterium Marinobacter litoralis SW-45: Abundance of non-coding RNAs

A report on the de novo Whole Genome Sequence (WGS) of Marinobacter litoralis SW-45, a moderately salt-tolerant bacterium isolated from the seawater in Malaysia is presented. The strain has a genome size of 3.45 Mb and is capable of producing halophilic lipase, protease and esterase enzymes. Computational prediction of non-coding RNA (ncRNA) genes in M. litoralis SW-45 was performed using standalone software known as the non-coding RNA characterization (nocoRNAc). In addition, a phylogenetic tree showing the evolutionary relationship between the strain and other members of the genus Marinobacter was constructed using 16SrRNA sequence information. A total of 385 ncRNA transcripts, 1124 terminator region, and 2350 Stress Induced Duplex Destabilization sites were predicted. The current WGS shotgun project has provided the relevant genetic information that may be useful for the strain's improvement studies. This manuscript gives the first description of M. litoralis with a complete genome.

High-throughput sequencing identification and characterization of potentially adhesion-related small RNAs in Streptococcus mutans

Purpose

Adherence capacity is one of the principal virulence factors of Streptococcus mutans, and adhesion virulence factors are controlled by small RNAs (sRNAs) at the post-transcriptional level in various bacteria. Here, we aimed to identify and decipher putative adhesion-related sRNAs in clinical strains of S. mutans.

Methodology

RNA deep-sequencing was performed to identify potential sRNAs under different adhesion conditions. The expression of sRNAs was analysed by quantitative real-time PCR (qRT-PCR), and bioinformatic methods were used to predict the functional characteristics of sRNAs.

Results

A total of 736 differentially expressed candidate sRNAs were predicted, and these included 352 sRNAs located on the antisense to mRNA (AM) and 384 sRNAs in intergenic regions (IGRs). The top 7 differentially expressed sRNAs were successfully validated by qRT-PCR in UA159, and 2 of these were further confirmed in 100 clinical isolates. Moreover, the sequences of two sRNAs were conserved in other Streptococcus species, indicating a conserved role in such closely related species. A good correlation between the expression of sRNAs and the adhesion of 100 clinical strains was observed, which, combined with GO and KEGG, provides a perspective for the comprehension of sRNA function annotation.

Conclusion

This study revealed a multitude of novel putative adhesion-related sRNAs in S. mutans and contributed to a better understanding of information concerning the transcriptional regulation of adhesion in S. mutans.

A comparative study of sequence- and structure-based features of small RNAs and other RNAs of bacteria

Small RNAs (sRNAs) in bacteria have emerged as key players in transcriptional and post-transcriptional regulation of gene expression. Here, we present a statistical analysis of different sequence- and structure-related features of bacterial sRNAs to identify the descriptors that could discriminate sRNAs from other bacterial RNAs. We investigated a comprehensive and heterogeneous collection of 816 sRNAs, identified by northern blotting across 33 bacterial species and compared their various features with other classes of bacterial RNAs, such as tRNAs, rRNAs and mRNAs. We observed that sRNAs differed significantly from the rest with respect to G+C composition, normalized minimum free energy of folding, motif frequency and several RNA-folding parameters like base-pairing propensity, Shannon entropy and base-pair distance. Based on the selected features, we developed a predictive model using Random Forests (RF) method to classify the above four classes of RNAs. Our model displayed an overall predictive accuracy of 89.5%. These findings would help to differentiate bacterial sRNAs from other RNAs and further promote prediction of novel sRNAs in different bacterial species.

A long and abundant non-coding RNA in Lactobacillus salivarius

Lactobacillus salivarius, found in the intestinal microbiota of humans and animals, is studied as an example of the sub-dominant intestinal commensals that may impart benefits upon their host. Strains typically harbour at least one megaplasmid that encodes functions contributing to contingency metabolism and environmental adaptation. RNA sequencing (RNA-seq)transcriptomic analysis of L. salivarius strain UCC118 identified the presence of a novel unusually abundant long non-coding RNA (lncRNA) encoded by the megaplasmid, and which represented more than 75 % of the total RNA-seq reads after depletion of rRNA species. The expression level of this 520 nt lncRNA in L. salivarius UCC118 exceeded that of the 16S rRNA, it accumulated during growth, was very stable over time and was also expressed during intestinal transit in a mouse. This lncRNA sequence is specific to the L. salivarius species; however, among 45 L. salivarius genomes analysed, not all (only 34) harboured the sequence for the lncRNA. This lncRNA was produced in 27 tested L. salivarius strains, but at strain-specific expression levels. High-level lncRNA expression correlated with high megaplasmid copy number. Transcriptome analysis of a deletion mutant lacking this lncRNA identified altered expression levels of genes in a number of pathways, but a definitive function of this new lncRNA was not identified. This lncRNA presents distinctive and unique properties, and suggests potential basic and applied scientific developments of this phenomenon.

The malS-5′UTR regulates hisG, a key gene in the histidine biosynthetic pathway in Salmonella enterica serovar Typhi

Bacterial noncoding RNAs (ncRNA) regulate diverse cellular processes, including virulence and environmental fitness. The malS 5′ untranslated region (named malS-5′UTR) was identified as a regulatory ncRNA that increases the invasive capacity of Salmonella enterica serovar Typhi. An IntaRNA search suggested base pairing between malS-5′UTR and hisG mRNA, a key gene in the histidine biosynthetic pathway. Overexpression of malS-5′UTR markedly reduced bacterial growth in minimal medium without histidine. Overexpression of malS-5′UTR increased mRNA from his operon genes, independently of the bax gene, and decreased HisG protein in Salmonella Typhi. RNA structure analysis showed base pairing of the malS-5′UTR RNA with the hisG mRNA across the ribosome binding site. Thus, we propose that malS-5′UTR inhibited hisG translation, probably by base pairing to the Shine–Dalgarno sequence.

Identification and validation of sRNAs in Edwardsiella tarda S08

Bacterial small non-coding RNAs (sRNAs) are known as novel regulators involved in virulence, stress responsibility, and so on. Recently, a lot of new researches have highlighted the critical roles of sRNAs in fine-tune gene regulation in both prokaryotes and eukaryotes. Edwardsiella tarda (E. tarda) is a gram-negative, intracellular pathogen that causes edwardsiellosis in fish. Thus far, no sRNA has been reported in E. tarda. The present study represents the first attempt to identify sRNAs in E. tarda S08. Ten sRNAs were validated by RNA sequencing and quantitative PCR (qPCR). ET_sRNA_1 and ET_sRNA_2 were homolous to tmRNA and GcvB, respectively. However, the other candidate sRNAs have not been reported till now. The cellular abundance of 10 validated sRNA was detected by qPCR at different growth phases to monitor their biosynthesis. Nine candidate sRNAs were expressed in the late-stage of exponential growth and stationary stages of growth (36~60 h). And the expression of the nine sRNAs was growth phase-dependent. But ET_sRNA_10 was almost expressed all the time and reached the highest peak at 48 h. Their targets were predicted by TargetRNA2 and each sRNA target contains some genes that directly or indirectly relate to virulence. These results preliminary showed that sRNAs probably play a regulatory role of virulence in E. tarda.

Transcriptome sequencing analysis of novel sRNAs of Kineococcus radiotolerans in response to ionizing radiation

Kineococcus radiotolerans is a Gram-positive, radio-resistant bacterium isolated from a radioactive environment. The small noncoding RNAs (sRNAs) in bacteria are reported to play roles in the immediate response to stress and/or the recovery from stress. The analysis of K. radiotolerans transcriptome sequencing results can identify these sRNAs in a genome-wide detection, using RNA sequencing (RNA-seq) by the deep sequencing technique. In this study, the raw data of radiation-exposed samples (RS) and control samples (CS) were acquired separately from the sequencing platform. There were 217 common sRNA candidates in the two samples screened in the genome-wide scale by bioinformatics analysis. There were 43 differentially expressed sRNA candidates, including 28 up-regulated and 15 down-regulated ones. The down-regulated sRNAs were selected for the sRNA target prediction, of which 12 sRNAs that may modulate the genes related to the transcription regulation and DNA repair were considered as the candidates involved in the radio-resistance regulation system.

Towards the complete small RNome of Acinetobacter baumannii

In recent years, the Gram-negative bacterium Acinetobacter baumannii has garnered considerable attention for its unprecedented capacity to rapidly develop resistance to antibacterial therapeutics. This is coupled with the seemingly epidemic emergence of new hyper-virulent strains. Although strain-specific differences for A. baumannii isolates have been well described, these studies have primarily focused on proteinaceous factors. At present, only limited publications have investigated the presence and role of small regulatory RNA (sRNA) transcripts. Herein, we perform such an analysis, describing the RNA-seq-based identification of 78 A. baumannii sRNAs in the AB5075 background. Together with six previously identified elements, we include each of these in a new genome annotation file, which will serve as a tool to investigate regulatory events in this organism. Our work reveals that the sRNAs display high expression, accounting for >50 % of the 20 most strongly expressed genes. Through conservation analysis we identified six classes of similar sRNAs, with one found to be particularly abundant and homologous to regulatory, C4 antisense RNAs found in bacteriophages. These elements appear to be processed from larger transcripts in an analogous manner to the phage C4 molecule and are putatively controlled by two further sRNAs that are strongly antisense to them. Collectively, this study offers a detailed view of the sRNA content of A. baumannii, exposing sequence and structural conservation amongst these elements, and provides novel insight into the potential evolution, and role, of these understudied regulatory molecules.

A Prophage-Encoded Small RNA Controls Metabolism and Cell Division in Escherichia coli

Hundreds of small RNAs (sRNAs) have been identified in diverse bacterial species, and while the functions of most remain unknown, some regulate key processes, particularly stress responses. The sRNA DicF was identified over 25 years ago as an inhibitor of cell division but since then has remained uncharacterized. DicF consists of 53 nucleotides and is encoded by a gene carried on a prophage (Qin) in the genomes of many Escherichia coli strains. We demonstrated that DicF inhibits cell division via direct base pairing with ftsZ mRNA to repress translation and prevent new synthesis of the bacterial tubulin homolog FtsZ. Systems analysis using computational and experimental methods identified additional mRNA targets of DicF: xylR and pykA mRNAs, encoding the xylose uptake and catabolism regulator and pyruvate kinase, respectively. Genetic analyses showed that DicF directly base pairs with and represses translation of these targets. Phenotypes of cells expressing DicF variants demonstrated that DicF-associated growth inhibition is not solely due to repression of ftsZ, indicating that the physiological consequences of DicF-mediated regulation extend beyond effects on cell division caused by reduced FtsZ synthesis. IMPORTANCE sRNAs are ubiquitous and versatile regulators of bacterial gene expression. A number of well-characterized examples in E. coli are highly conserved and present in the E. coli core genome. In contrast, the sRNA DicF (identified over 20 years ago but remaining poorly characterized) is encoded by a gene carried on a defective prophage element in many E. coli genomes. Here, we characterize DicF in order to better understand how horizontally acquired sRNA regulators impact bacterial gene expression and physiology. Our data confirm the long-hypothesized DicF-mediated regulation of ftsZ, encoding the bacterial tubulin homolog required for cell division. We further uncover DicF-mediated posttranscriptional control of metabolic gene expression. Ectopic production of DicF is highly toxic to E. coli cells, but the toxicity is not attributable to DicF regulation of ftsZ. Further work is needed to reveal the biological roles of and benefits for the host conferred by DicF and other products encoded by defective prophages.

The Mechanisms of Virulence Regulation by Small Noncoding RNAs in Low GC Gram-Positive Pathogens

The discovery of small noncoding regulatory RNAs (sRNAs) in bacteria has grown tremendously recently, giving new insights into gene regulation. The implementation of computational analysis and RNA sequencing has provided new tools to discover and analyze potential sRNAs. Small regulatory RNAs that act by base-pairing to target mRNAs have been found to be ubiquitous and are the most abundant class of post-transcriptional regulators in bacteria. The majority of sRNA studies has been limited to E. coli and other gram-negative bacteria. However, examples of sRNAs in gram-positive bacteria are still plentiful although the detailed gene regulation mechanisms behind them are not as well understood. Strict virulence control is critical for a pathogen’s survival and many sRNAs have been found to be involved in that process. This review outlines the targets and currently known mechanisms of trans-acting sRNAs involved in virulence regulation in various gram-positive pathogens. In addition, their shared characteristics such as CU interaction motifs, the role of Hfq, and involvement in two-component regulators, riboswitches, quorum sensing, or toxin/antitoxin systems are described.

Advantages of mixing bioinformatics and visualization approaches for analyzing sRNA-mediated regulatory bacterial networks

The revolution in high-throughput sequencing technologies has enabled the acquisition of gigabytes of RNA sequences in many different conditions and has highlighted an unexpected number of small RNAs (sRNAs) in bacteria. Ongoing exploitation of these data enables numerous applications for investigating bacterial transacting sRNA-mediated regulation networks. Focusing on sRNAs that regulate mRNA translation in trans, recent works have noted several sRNA-based regulatory pathways that are essential for key cellular processes. Although the number of known bacterial sRNAs is increasing, the experimental validation of their interactions with mRNA targets remains challenging and involves expensive and time-consuming experimental strategies. Hence, bioinformatics is crucial for selecting and prioritizing candidates before designing any experimental work. However, current software for target prediction produces a prohibitive number of candidates because of the lack of biological knowledge regarding the rules governing sRNA-mRNA interactions. Therefore, there is a real need to develop new approaches to help biologists focus on the most promising predicted sRNA-mRNA interactions. In this perspective, this review aims at presenting the advantages of mixing bioinformatics and visualization approaches for analyzing predicted sRNA-mediated regulatory bacterial networks.

Small RNA Transcriptome of the Oral Microbiome during Periodontitis Progression

The oral microbiome is one of the most complex microbial communities in the human body, and due to circumstances not completely understood, the healthy microbial community becomes dysbiotic, giving rise to periodontitis, a polymicrobial inflammatory disease. We previously reported the results of community-wide gene expression changes in the oral microbiome during periodontitis progression and identified signatures associated with increasing severity of the disease. Small noncoding RNAs (sRNAs) are key players in posttranscriptional regulation, especially in fast-changing environments such as the oral cavity. Here, we expanded our analysis to the study of the sRNA metatranscriptome during periodontitis progression on the same samples for which mRNA expression changes were analyzed. We observed differential expression of 12,097 sRNAs, identifying a total of 20 Rfam sRNA families as being overrepresented in progression and 23 at baseline. Gene ontology activities regulated by the differentially expressed (DE) sRNAs included amino acid metabolism, ethanolamine catabolism, signal recognition particle-dependent cotranslational protein targeting to membrane, intron splicing, carbohydrate metabolism, control of plasmid copy number, and response to stress. In integrating patterns of expression of protein coding transcripts and sRNAs, we found that functional activities of genes that correlated positively with profiles of expression of DE sRNAs were involved in pathogenesis, proteolysis, ferrous iron transport, and oligopeptide transport. These findings represent the first integrated sequencing analysis of the community-wide sRNA transcriptome of the oral microbiome during periodontitis progression and show that sRNAs are key regulatory elements of the dysbiotic process leading to disease.

Rapid and high-throughput construction of microbial cell-factories with regulatory noncoding RNAs

Due to global crises such as pollution and depletion of fossil fuels, sustainable technologies based on microbial cell-factories have been garnering great interest as an alternative to chemical factories. The development of microbial cell-factories is imperative in cutting down the overall manufacturing cost. Thus, diverse metabolic engineering strategies and engineering tools have been established to obtain a preferred genotype and phenotype displaying superior productivity. However, these tools are limited to only a handful of genes with permanent modification of a genome and significant labor costs, and this is one of the bottlenecks associated with biofactory construction. Therefore, a groundbreaking rapid and high-throughput engineering tool is needed for efficient construction of microbial cell-factories. During the last decade, copious small noncoding RNAs (ncRNAs) have been discovered in bacteria. These are involved in substantial regulatory roles like transcriptional and post-transcriptional gene regulation by modulating mRNA elongation, stability, or translational efficiency. Because of their vulnerability, ncRNAs can be used as another layer of conditional control over gene expression without modifying chromosomal sequences, and hence would be a promising high-throughput tool for metabolic engineering. Here, we review successful design principles and applications of ncRNAs for high-throughput metabolic engineering or physiological studies of diverse industrially important microorganisms.

A dual reporter system for detecting RNA interactions in bacterial cells

Detecting RNA-partner interactions in cells is often difficult due to a lack of suitable tools. Here we describe a dual reporter system capable of detecting intracellular interactions in which one of the partners is an RNA. The system utilizes two fluorescent proteins with similar maturation rates but distinct spectral properties, specifically cyan fluorescent protein (CFP) and yellow fluorescent protein (YFP). By placing the CFP gene upstream and the YFP gene downstream of an RNA gene of interest, the production of YFP becomes sensitive to RNA-partner interaction, whereas the synthesis of CFP is not disturbed. Therefore, the RNA-partner interaction can be simply measured by the change in the ratio of fluorescence of YFP over CFP. The utility of our approach is demonstrated through verification of three known RNA-partner interactions in the model bacterium Escherichia coli. Our two-reporter strategy should be broadly useful to the study of RNA-targeted interactions in bacteria.

Regulation of Hfq mRNA and protein levels in Escherichia coli and Pseudomonas aeruginosa by the Burkholderia cenocepacia MtvR sRNA

Small non-coding RNAs (sRNAs) are important players of gene expression regulation in bacterial pathogens. MtvR is a 136-nucleotide long sRNA previously identified in the human pathogen Burkholderia cenocepacia J2315 and with homologues restricted to bacteria of the Burkholderia cepacia complex. In this work we have investigated the effects of expressing MtvR in Escherichia coli and Pseudomonas aeruginosa. Results are presented showing that MtvR negatively regulates the hfq mRNA levels in both bacterial species. In the case of E. coli, this negative regulation is shown to involve binding of MtvR to the 5′-UTR region of the hfq_Ec mRNA. Results presented also show that expression of MtvR in E. coli and P. aeruginosa originates multiple phenotypes, including reduced resistance to selected stresses, biofilm formation ability, and increased susceptibility to various antibiotics.

Genome-wide identification of Hfq-regulated small RNAs in the fire blight pathogen Erwinia amylovora discovered small RNAs with virulence regulatory function

BACKGROUND

Erwinia amylovora is a phytopathogenic bacterium and causal agent of fire blight disease in apples and pears. Although many virulence factors have been characterized, the coordination of expression of these virulence factors in E. amylovora is still not clear. Regulatory small RNAs (sRNAs) are important post-transcriptional regulatory components in bacteria. A large number of sRNAs require the RNA chaperone Hfq for both stability and functional activation. In E. amylovora, Hfq was identified as a major regulator of virulence and various virulence traits. However, information is still lacking about Hfq-dependent sRNAs on a genome scale, including the virulence regulatory functions of these sRNAs in E. amylovora.

RESULTS

Using both an RNA-seq analysis and a Rho-independent terminator search, 40 candidate Hfq-dependent sRNAs were identified in E. amylovora. The expression and sizes of 12 sRNAs and the sequence boundaries of seven sRNAs were confirmed by Northern blot and 5' RACE assay respectively. Sequence conservation analysis identified sRNAs conserved only in the Erwinia genus as well as E. amylovora species-specific sRNAs. In addition, a dynamic re-patterning of expression of Hfq-dependent sRNAs was observed at 6 and 12 hours after induction in Hrp-inducing minimal medium. Furthermore, sRNAs that control virulence traits were characterized, among which ArcZ positively controls the type III secretion system (T3SS), amylovoran exopolysaccahride production, biofilm formation, and motility, and negatively modulates attachment while RmaA (Hrs6) and OmrAB both negatively regulate amylovoran production and positively regulate motility.

CONCLUSIONS

This study has significantly enhanced our understanding of the Hfq-dependent sRNAs in E. amylovora at the genome level. The identification of multiple virulence-regulating sRNAs also suggests that post-transcriptional regulation by sRNAs may play a role in the deployment of virulence factors needed during varying stages of pathogenesis during host invasion by E. amylovora.

Physiological roles of small RNA molecules

Unlike proteins, RNA molecules have emerged lately as key players in regulation in bacteria. Most reviews hitherto focused on the experimental and/or in silico methods used to identify genes encoding small RNAs (sRNAs) or on the diverse mechanisms of these RNA regulators to modulate expression of their targets. However, less is known about their biological functions and their implications in various physiological responses. This review aims to compile what is known presently about the diverse roles of sRNA transcripts in the regulation of metabolic processes, in different growth conditions, in adaptation to stress and in microbial pathogenesis. Several recent studies revealed that sRNA molecules are implicated in carbon metabolism and transport, amino acid metabolism or metal sensing. Moreover, regulatory RNAs participate in cellular adaptation to environmental changes, e.g. through quorum sensing systems or development of biofilms, and analyses of several sRNAs under various physiological stresses and culture conditions have already been performed. In addition, recent experiments performed with Gram-positive and Gram-negative pathogens showed that regulatory RNAs play important roles in microbial virulence and during infection. The combined results show the diversity of regulation mechanisms and physiological processes in which sRNA molecules are key actors.

Small regulatory RNAs in Archaea

Small regulatory RNAs (sRNAs) are universally distributed in all three domains of life, Archaea, Bacteria, and Eukaryotes. In bacteria, sRNAs typically function by binding near the translation start site of their target mRNAs and thereby inhibit or activate translation. In eukaryotes, miRNAs and siRNAs typically bind to the 3′-untranslated region (3′-UTR) of their target mRNAs and influence translation efficiency and/or mRNA stability. In archaea, sRNAs have been identified in all species investigated using bioinformatic approaches, RNomics, and RNA-Seq. Their size can vary significantly between less than 50 to more than 500 nucleotides. Differential expression of sRNA genes has been studied using northern blot analysis, microarrays, and RNA-Seq. In addition, biological functions have been unraveled by genetic approaches, i.e., by characterization of designed mutants. As in bacteria, it was revealed that archaeal sRNAs are involved in many biological processes, including metabolic regulation, adaptation to extreme conditions, stress responses, and even in regulation of morphology and cellular behavior. Recently, the first target mRNAs were identified in archaea, including one sRNA that binds to the 5′-region of two mRNAs in Methanosarcina mazei Gö1 and a few sRNAs that bind to 3′-UTRs in Sulfolobus solfataricus, three Pyrobaculum species, and Haloferax volcanii, indicating that archaeal sRNAs appear to be able to target both the 5′-UTR or the 3′-UTRs of their respective target mRNAs. In addition, archaea contain tRNA-derived fragments (tRFs), and one tRF has been identified as a major ribosome-binding sRNA in H. volcanii, which downregulates translation in response to stress. Besides regulatory sRNAs, archaea contain further classes of sRNAs, e.g., CRISPR RNAs (crRNAs) and snoRNAs.

Prediction and characterization of small non-coding RNAs related to secondary metabolites in Saccharopolyspora erythraea

Saccharopolyspora erythraea produces a large number of secondary metabolites with biological activities, including erythromycin. Elucidation of the mechanisms through which the production of these secondary metabolites is regulated may help to identify new strategies for improved biosynthesis of erythromycin. In this paper, we describe the systematic prediction and analysis of small non-coding RNAs (sRNAs) in S. erythraea, with the aim to elucidate sRNA-mediated regulation of secondary metabolite biosynthesis. In silico and deep-sequencing technologies were applied to predict sRNAs in S. erythraea. Six hundred and forty-seven potential sRNA loci were identified, of which 382 cis-encoded antisense RNA are complementary to protein-coding regions and 265 predicted transcripts are located in intergenic regions. Six candidate sRNAs (sernc292, sernc293, sernc350, sernc351, sernc361, and sernc389) belong to four gene clusters (tpc3, pke, pks6, and nrps5) that are involved in secondary metabolite biosynthesis. Deep-sequencing data showed that the expression of all sRNAs in the strain HL3168 E3 (E3) was higher than that in NRRL23338 (M), except for sernc292 and sernc361 expression. The relative expression of six sRNAs in strain M and E3 were validated by qRT-PCR at three different time points (24, 48, and 72 h). The results showed that, at each time point, the transcription levels of sernc293, sernc350, sernc351, and sernc389 were higher in E3 than in M, with the largest difference observed at 72 h, whereas no signals for sernc292 and sernc361 were detected. sernc293, sernc350, sernc351, and sernc389 probably regulate iron transport, terpene metabolism, geosmin synthesis, and polyketide biosynthesis, respectively. The major significance of this study is the successful prediction and identification of sRNAs in genomic regions close to the secondary metabolism-related genes in S. erythraea. A better understanding of the sRNA-target interaction would help to elucidate the complete range of functions of sRNAs in S. erythraea, including sRNA-mediated regulation of erythromycin biosynthesis.

Directional RNA-seq reveals highly complex condition-dependent transcriptomes in E. coli K12 through accurate full-length transcripts assembling

BACKGROUND

Although prokaryotic gene transcription has been studied over decades, many aspects of the process remain poorly understood. Particularly, recent studies have revealed that transcriptomes in many prokaryotes are far more complex than previously thought. Genes in an operon are often alternatively and dynamically transcribed under different conditions, and a large portion of genes and intergenic regions have antisense RNA (asRNA) and non-coding RNA (ncRNA) transcripts, respectively. Ironically, similar studies have not been conducted in the model bacterium E coli K12, thus it is unknown whether or not the bacterium possesses similar complex transcriptomes. Furthermore, although RNA-seq becomes the major method for analyzing the complexity of prokaryotic transcriptome, it is still a challenging task to accurately assemble full length transcripts using short RNA-seq reads.

RESULTS

To fill these gaps, we have profiled the transcriptomes of E. coli K12 under different culture conditions and growth phases using a highly specific directional RNA-seq technique that can capture various types of transcripts in the bacterial cells, combined with a highly accurate and robust algorithm and tool TruHMM (http://bioinfolab.uncc.edu/TruHmm_package/) for assembling full length transcripts. We found that 46.9 ~ 63.4% of expressed operons were utilized in their putative alternative forms, 72.23 ~ 89.54% genes had putative asRNA transcripts and 51.37 ~ 72.74% intergenic regions had putative ncRNA transcripts under different culture conditions and growth phases.

CONCLUSIONS

As has been demonstrated in many other prokaryotes, E. coli K12 also has a highly complex and dynamic transcriptomes under different culture conditions and growth phases. Such complex and dynamic transcriptomes might play important roles in the physiology of the bacterium. TruHMM is a highly accurate and robust algorithm for assembling full-length transcripts in prokaryotes using directional RNA-seq short reads.

Linking plant nutritional status to plant-microbe interactions

Plants have developed a wide-range of adaptations to overcome nutrient limitation, including changes to the quantity and composition of carbon-containing compounds released by roots. Root-associated bacteria are largely influenced by these compounds which can be perceived as signals or substrates. Here, we evaluate the effect of root exudates collected from maize plants grown under nitrogen (N), phosphate (P), iron (Fe) and potassium (K) deficiencies on the transcriptome of the plant growth promoting rhizobacterium (PGPR) Bacillus amyloliquefaciens FZB42. The largest shifts in gene expression patterns were observed in cells exposed to exudates from N-, followed by P-deficient plants. Exudates from N-deprived maize triggered a general stress response in FZB42 in the exponential growth phase, which was evidenced by the suppression of numerous genes involved in protein synthesis. Exudates from P-deficient plants induced bacterial genes involved in chemotaxis and motility whilst exudates released by Fe and K deficient plants did not cause dramatic changes in the bacterial transcriptome during exponential growth phase. Global transcriptional changes in bacteria elicited by nutrient deficient maize exudates were significantly correlated with concentrations of the amino acids aspartate, valine and glutamate in root exudates suggesting that transcriptional profiling of FZB42 associated with metabolomics of N, P, Fe and K-deficient maize root exudates is a powerful approach to better understand plant-microbe interactions under conditions of nutritional stress.

Target evaluation of the non-coding csRNAs reveals a link of the two-component regulatory system CiaRH to competence control in Streptococcus pneumoniae R6

The two-component regulatory system CiaRH of Streptococcus pneumoniae controls 25 genes, five of which specify homologous small non-coding csRNAs (cia-dependent small RNAs). The csRNAs were predicted to act regulatory as base-pairing sRNAs, but their targets have not been identified. By csRNA gene inactivations we established that the major phenotypes associated with a hyperactive CiaRH system, enhanced β-lactam resistance and prevention of genetic competence, are dependent on the csRNAs. Computational target predictions and evaluations by translational fusions identified six genes to be under csRNA control: spr0081, spr0371, spr0159, spr0551, spr1097 and spr2043(comC). Measuring the effect of single csRNAs on three targets indicated that they acted additively. One of the targets, comC(spr2043), encoding the precursor of the competence stimulating pheromone CSP, constitutes a link of CiaRH to competence control. Partially disrupting predicted csRNA-comC complementarity led to strongly diminished repression by the csRNAs and to transformability in a strain with a hyperactive CiaRH. Thus, a hyperactive CiaRH system prevents competence development by csRNA-dependent post-transcriptional repression of CSP production. The csRNAs are also involved in competence regulation in the wild-type strain R6, but their activity is only apparent in the absence of the protease gene htrA, another CiaRH regulon member.

Computational identification of functional RNA homologs in metagenomic data

A key step toward understanding a metagenomics data set is the identification of functional sequence elements within it, such as protein coding genes and structural RNAs. Relative to protein coding genes, structural RNAs are more difficult to identify because of their reduced alphabet size, lack of open reading frames, and short length. Infernal is a software package that implements “covariance models” (CMs) for RNA homology search, which harness both sequence and structural conservation when searching for RNA homologs. Thanks to the added statistical signal inherent in the secondary structure conservation of many RNA families, Infernal is more powerful than sequence-only based methods such as BLAST and profile HMMs. Together with the Rfam database of CMs, Infernal is a useful tool for identifying RNAs in metagenomics data sets.

Bacterial sRNAs: regulation in stress

Bacteria are often exposed to a hostile environment and have developed a plethora of cellular processes in order to survive. A burgeoning list of small non-coding RNAs (sRNAs) has been identified and reported to orchestrate crucial stress responses in bacteria. Among them, cis-encoded sRNA, trans-encoded sRNA, and 5'-untranslated regions (UTRs) of the protein coding sequence are influential in the bacterial response to environmental cues, such as fluctuation of temperature and pH as well as other stress conditions. This review summarizes the role of bacterial sRNAs in modulating selected stress conditions and highlights the alliance between stress response and clustered regularly interspaced short palindromic repeats (CRISPR) in bacterial defense.

The AfaR small RNA controls expression of the AfaD-VIII invasin in pathogenic Escherichia coli strains

Pathogenic Escherichia coli strains carrying the afa-8 gene cluster are frequently associated with extra-intestinal infections in humans and animals. The afa-8 A to E genes determine the formation of an afimbrial adhesive sheath consisting of the AfaD-VIII invasin and the AfaE-VIII adhesin at the bacterial cell surface. This structure is thought to be required for host colonization. We characterized a new gene encoding the small RNA AfaR, which is transcribed in cis from the complementary strand of the 3' untranslated region of the afaD messenger RNA, within the afaD-afaE intercistronic region. AfaR is a trans-acting Hfq-dependent antisense small RNA that binds the 5' untranslated region of the afaD messenger RNA, initiating several ribonuclease E-dependent cleavages, thereby downregulating production of the AfaD-VIII invasin. AfaR transcription is dependent on σ(E), a member of the stress response family of extracytoplasmic alternative sigma factors. We found that the AfaR-dependent regulatory pathway was controlled by temperature, allowing the production of the AfaD-VIII invasin at temperatures above 37 °C. Our findings suggest that the entry of afa-8-positive pathogenic E. coli strains into epithelial cells is tightly regulated by the AfaR small RNA.

Computational small RNA prediction in bacteria

Bacterial, small RNAs were once regarded as potent regulators of gene expression and are now being considered as essential for their diversified roles. Many small RNAs are now reported to have a wide array of regulatory functions, ranging from environmental sensing to pathogenesis. Traditionally, noncoding transcripts were rarely detected by means of genetic screens. However, the availability of approximately 2200 prokaryotic genome sequences in public databases facilitates the efficient computational search of those molecules, followed by experimental validation. In principle, the following four major computational methods were applied for the prediction of sRNA locations from bacterial genome sequences: (1) comparative genomics, (2) secondary structure and thermodynamic stability, (3) ‘Orphan’ transcriptional signals and (4) ab initio methods regardless of sequence or structure similarity; most of these tools were applied to locate the putative genomic sRNA locations followed by experimental validation of those transcripts. Therefore, computational screening has simplified the sRNA identification process in bacteria. In this review, a plethora of small RNA prediction methods and tools that have been reported in the past decade are discussed comprehensively and assessed based on their attributes, compatibility, and their prediction accuracy.

Regulatory RNAs in archaea: first target identification in Methanoarchaea

sRNAs (small non-coding RNAs) representing important players in many cellular and regulatory processes have been identified in all three domains of life. In Eukarya and Bacteria, functions have been assigned for many sRNAs, whereas the sRNA populations in Archaea are considerably less well characterized. Recent analyses on a genome-wide scale particularly using high-throughput sequencing techniques demonstrated the presence of high numbers of sRNA candidates in several archaea. However, elucidation of the molecular mechanism of sRNA action, as well as understanding their physiological roles, is in general still challenging, particularly in Archaea, since efficient genetic tools are missing. The identification of cellular targets of identified archaeal sRNAs by experimental approaches or computational prediction programs has begun only recently. At present, targets have been identified for one archaeal sRNA, sRNA162 in Methanosarcina mazei, which interacts with the 5′ region of its targets, a cis-encoded and a trans-encoded target, blurring the paradigm of a border between cis- and trans-encoded sRNAs. Besides, the first experimental implications have been obtained in Haloarchaea and Pyrobaculum that archaeal sRNAs also target 3′ regions of mRNAs. The present review summarizes our current knowledge on archaeal sRNAs and their biological functions and targets.

Predicting sRNAs and their targets in bacteria

Bacterial small RNAs (sRNAs) are an emerging class of regulatory RNAs of about 40–500 nucleotides in length and, by binding to their target mRNAs or proteins, get involved in many biological processes such as sensing environmental changes and regulating gene expression. Thus, identification of bacterial sRNAs and their targets has become an important part of sRNA biology. Current strategies for discovery of sRNAs and their targets usually involve bioinformatics prediction followed by experimental validation, emphasizing a key role for bioinformatics prediction. Here, therefore, we provided an overview on prediction methods, focusing on the merits and limitations of each class of models. Finally, we will present our thinking on developing related bioinformatics models in future.

Comparative transcriptomics of pathogenic and non-pathogenic Listeria species

Comparative RNA-seq analysis of two related pathogenic and non-pathogenic bacterial strains reveals a hidden layer of divergence in the non-coding genome as well as conserved, widespread regulatory structures called ‘Excludons', which mediate regulation through long non-coding antisense RNAs.

Comparative transcriptome sequencing of two closely related bacterial strains reveals a hidden layer of divergence in the non-coding genome.

Pathogen-specific non-coding RNAs, which might contribute to virulence, are revealed.

The Listeria genome contains a class of unusually long antisense RNAs (lasRNAs) which spans divergent genes and repress expression of the genes located opposite to them while activating the other. The genetic organization of these lasRNAs and operon was named an excludon.

The exhaustive transcriptome information from this publication is provided as an open resource with a web-accessible transcriptome browser.

Listeria monocytogenes is a human, food-borne pathogen. Genomic comparisons between L. monocytogenes and Listeria innocua, a closely related non-pathogenic species, were pivotal in the identification of protein-coding genes essential for virulence. However, no comprehensive comparison has focused on the non-coding genome. We used strand-specific cDNA sequencing to produce genome-wide transcription start site maps for both organisms, and developed a publicly available integrative browser to visualize and analyze both transcriptomes in different growth conditions and genetic backgrounds. Our data revealed conservation across most transcripts, but significant divergence between the species in a subset of non-coding RNAs. In L. monocytogenes, we identified 113 small RNAs (33 novel) and 70 antisense RNAs (53 novel), significantly increasing the repertoire of ncRNAs in this species. Remarkably, we identified a class of long antisense transcripts (lasRNAs) that overlap one gene while also serving as the 5′ UTR of the adjacent divergent gene. Experimental evidence suggests that lasRNAs transcription inhibits expression of one operon while activating the expression of another. Such a lasRNA/operon structure, that we named ‘excludon', might represent a novel form of regulation in bacteria.

Computational prediction of efficient splice sites for trans-splicing ribozymes

Group I introns have been engineered into trans-splicing ribozymes capable of replacing the 3'-terminal portion of an external mRNA with their own 3'-exon. Although this design makes trans-splicing ribozymes potentially useful for therapeutic application, their trans-splicing efficiency is usually too low for medical use. One factor that strongly influences trans-splicing efficiency is the position of the target splice site on the mRNA substrate. Viable splice sites are currently determined using a biochemical trans-tagging assay. Here, we propose a rapid and inexpensive alternative approach to identify efficient splice sites. This approach involves the computation of the binding free energies between ribozyme and mRNA substrate. We found that the computed binding free energies correlate well with the trans-splicing efficiency experimentally determined at 18 different splice sites on the mRNA of chloramphenicol acetyl transferase. In contrast, our results from the trans-tagging assay correlate less well with measured trans-splicing efficiency. The computed free energy components suggest that splice site efficiency depends on the following secondary structure rearrangements: hybridization of the ribozyme's internal guide sequence (IGS) with mRNA substrate (most important), unfolding of substrate proximal to the splice site, and release of the IGS from the 3'-exon (least important). The proposed computational approach can also be extended to fulfill additional design requirements of efficient trans-splicing ribozymes, such as the optimization of 3'-exon and extended guide sequences.

The small RNA RybA regulates key-genes in the biosynthesis of aromatic amino acids under peroxide stress in E. coli

In bacteria, adaptive response to external stimuli is often regulated by small RNAs (sRNAs). In Escherichia coli, the organism in which sRNAs have been best characterized so far, no function could be attributed to 40 out of 79 sRNAs. Here we decipher the function of RybA, one of these orphan sRNAs. RybA was discovered in 2001 by Wassarman et al. using comparative genomics. This sRNA is conserved between E. coli, Salmonella typhimurium and Klebsiella pneumoniae. We determined the expression pattern of RybA under different growth conditions and identified its exact 5' and 3' ends. Using microarray and Northern analysis we show that, under peroxide stress, the absence of RybA leads to an upregulation of key genes of the TyrR regulon involved in the metabolism of aromatic compounds including the aromatic amino acids. Although containing an open reading frame, which might have an independent function, RybA does not require translation for this activity and therefore acts at the RNA level. Furthermore we demonstrate that regulation requires the transcription regulator TyrR. The mechanism of activation of TyrR, probably the primary target of RybA, remains to be elucidated. The downregulation of aromatic amino acid biosynthesis might regulate the cellular concentration of chorismate and its availability for other downstream products like ubiquinone or enterobactin. While ubiquinone participates in the defense against oxidative stress in the cytoplasmic membrane, enterobactin is involved in iron import and is therefore detrimental under oxidative stress.

Unexpected Diversity of Chloroplast Noncoding RNAs as Revealed by Deep Sequencing of the Arabidopsis Transcriptome

Noncoding RNAs (ncRNA) are widely expressed in both prokaryotes and eukaryotes. Eukaryotic ncRNAs are commonly micro- and small-interfering RNAs (18-25 nt) involved in posttranscriptional gene silencing, whereas prokaryotic ncRNAs vary in size and are involved in various aspects of gene regulation. Given the prokaryotic origin of organelles, the presence of ncRNAs might be expected; however, the full spectrum of organellar ncRNAs has not been determined systematically. Here, strand-specific RNA-Seq analysis was used to identify 107 candidate ncRNAs from Arabidopsis thaliana chloroplasts, primarily encoded opposite protein-coding and tRNA genes. Forty-eight ncRNAs were shown to accumulate by RNA gel blot as discrete transcripts in wild-type (WT) plants and/or the pnp1-1 mutant, which lacks the chloroplast ribonuclease polynucleotide phosphorylase (cpPNPase). Ninety-eight percent of the ncRNAs detected by RNA gel blot had different transcript patterns between WT and pnp1-1, suggesting cpPNPase has a significant role in chloroplast ncRNA biogenesis and accumulation. Analysis of materials deficient for other major chloroplast ribonucleases, RNase R, RNase E, and RNase J, showed differential effects on ncRNA accumulation and/or form, suggesting specificity in RNase-ncRNA interactions. 5' end mapping demonstrates that some ncRNAs are transcribed from dedicated promoters, whereas others result from transcriptional read-through. Finally, correlations between accumulation of some ncRNAs and the symmetrically transcribed sense RNA are consistent with a role in RNA stability. Overall, our data suggest that this extensive population of ncRNAs has the potential to underpin a previously underappreciated regulatory mode in the chloroplast.

An in silico model for identification of small RNAs in whole bacterial genomes: characterization of antisense RNAs in pathogenic Escherichia coli and Streptococcus agalactiae strains

Characterization of small non-coding ribonucleic acids (sRNA) among the large volume of data generated by high-throughput RNA-seq or tiling microarray analyses remains a challenge. Thus, there is still a need for accurate in silico prediction methods to identify sRNAs within a given bacterial species. After years of effort, dedicated software were developed based on comparative genomic analyses or mathematical/statistical models. Although these genomic analyses enabled sRNAs in intergenic regions to be efficiently identified, they all failed to predict antisense sRNA genes (asRNA), i.e. RNA genes located on the DNA strand complementary to that which encodes the protein. The statistical models enabled any genomic region to be analyzed theorically but not efficiently. We present a new model for in silico identification of sRNA and asRNA candidates within an entire bacterial genome. This model was successfully used to analyze the Gram-negative Escherichia coli and Gram-positive Streptococcus agalactiae. In both bacteria, numerous asRNAs are transcribed from the complementary strand of genes located in pathogenicity islands, strongly suggesting that these asRNAs are regulators of the virulence expression. In particular, we characterized an asRNA that acted as an enhancer-like regulator of the type 1 fimbriae production involved in the virulence of extra-intestinal pathogenic E. coli.

The challenge of relating gene expression to the virulence of Salmonella enterica serovar Typhimurium

The first decade of transcriptomic studies of Salmonella enterica serovar Typhimurium focused upon gene expression in vitro, and during the infection of mammalian cells. The published regulons and stimulons show that the three Type Three Secretion Systems of S. Typhimurium respond to a diverse range of environmental conditions, and are controlled by a hierarchy of regulatory proteins. The integration of in vitro generated transcriptomic data with global gene expression of S. Typhimurium during infection is beginning to yield valuable information. The coordinated regulation of Salmonella gene expression is a key process for survival, adaptation and virulence capacities of the pathogen.

A highly conserved protein of unknown function in Sinorhizobium meliloti affects sRNA regulation similar to Hfq

The SMc01113/YbeY protein, belonging to the UPF0054 family, is highly conserved in nearly every bacterium. However, the function of these proteins still remains elusive. Our results show that SMc01113/YbeY proteins share structural similarities with the MID domain of the Argonaute (AGO) proteins, and might similarly bind to a small-RNA (sRNA) seed, making a special interaction with the phosphate on the 5′-side of the seed, suggesting they may form a component of the bacterial sRNA pathway. Indeed, eliminating SMc01113/YbeY expression in Sinorhizobium meliloti produces symbiotic and physiological phenotypes strikingly similar to those of the hfq mutant. Hfq, an RNA chaperone, is central to bacterial sRNA-pathway. We evaluated the expression of 13 target genes in the smc01113 and hfq mutants. Further, we predicted the sRNAs that may potentially target these genes, and evaluated the accumulation of nine sRNAs in WT and smc01113 and hfq mutants. Similar to hfq, smc01113 regulates the accumulation of sRNAs as well as the target mRNAs. AGOs are central components of the eukaryotic sRNA machinery and conceptual parallels between the prokaryotic and eukaryotic sRNA pathways have long been drawn. Our study provides the first line of evidence for such conceptual parallels. Furthermore, our investigation gives insights into the sRNA-mediated regulation of stress adaptation in S. meliloti.

nocoRNAc: characterization of non-coding RNAs in prokaryotes

Background

The interest in non-coding RNAs (ncRNAs) constantly rose during the past few years because of the wide spectrum of biological processes in which they are involved. This led to the discovery of numerous ncRNA genes across many species. However, for most organisms the non-coding transcriptome still remains unexplored to a great extent. Various experimental techniques for the identification of ncRNA transcripts are available, but as these methods are costly and time-consuming, there is a need for computational methods that allow the detection of functional RNAs in complete genomes in order to suggest elements for further experiments. Several programs for the genome-wide prediction of functional RNAs have been developed but most of them predict a genomic locus with no indication whether the element is transcribed or not.

Results

We present NOCORNAc, a program for the genome-wide prediction of ncRNA transcripts in bacteria. NOCORNAc incorporates various procedures for the detection of transcriptional features which are then integrated with functional ncRNA loci to determine the transcript coordinates. We applied RNAz and NOCORNAc to the genome of Streptomyces coelicolor and detected more than 800 putative ncRNA transcripts most of them located antisense to protein-coding regions. Using a custom design microarray we profiled the expression of about 400 of these elements and found more than 300 to be transcribed, 38 of them are predicted novel ncRNA genes in intergenic regions. The expression patterns of many ncRNAs are similarly complex as those of the protein-coding genes, in particular many antisense ncRNAs show a high expression correlation with their protein-coding partner.

Conclusions

We have developed NOCORNAc, a framework that facilitates the automated characterization of functional ncRNAs. NOCORNAc increases the confidence of predicted ncRNA loci, especially if they contain transcribed ncRNAs. NOCORNAc is not restricted to intergenic regions, but it is applicable to the prediction of ncRNA transcripts in whole microbial genomes. The software as well as a user guide and example data is available at http://www.zbit.uni-tuebingen.de/pas/nocornac.htm.

sRNATarBase: a comprehensive database of bacterial sRNA targets verified by experiments

Bacterial sRNAs are an emerging class of small regulatory RNAs, 40-500 nt in length, which play a variety of important roles in many biological processes through binding to their mRNA or protein targets. A comprehensive database of experimentally confirmed sRNA targets would be helpful in understanding sRNA functions systematically and provide support for developing prediction models. Here we report on such a database--sRNATarBase. The database holds 138 sRNA-target interactions and 252 noninteraction entries, which were manually collected from peer-reviewed papers. The detailed information for each entry, such as supporting experimental protocols, BLAST-based phylogenetic analysis of sRNA-mRNA target interaction in closely related bacteria, predicted secondary structures for both sRNAs and their targets, and available binding regions, is provided as accurately as possible. This database also provides hyperlinks to other databases including GenBank, SWISS-PROT, and MPIDB. The database is available from the web page http://ccb.bmi.ac.cn/srnatarbase/.

Non-coding RNA detection methods combined to improve usability, reproducibility and precision

Background

Non-coding RNAs gain more attention as their diverse roles in many cellular processes are discovered. At the same time, the need for efficient computational prediction of ncRNAs increases with the pace of sequencing technology. Existing tools are based on various approaches and techniques, but none of them provides a reliable ncRNA detector yet. Consequently, a natural approach is to combine existing tools. Due to a lack of standard input and output formats combination and comparison of existing tools is difficult. Also, for genomic scans they often need to be incorporated in detection workflows using custom scripts, which decreases transparency and reproducibility.

Results

We developed a Java-based framework to integrate existing tools and methods for ncRNA detection. This framework enables users to construct transparent detection workflows and to combine and compare different methods efficiently. We demonstrate the effectiveness of combining detection methods in case studies with the small genomes of Escherichia coli, Listeria monocytogenes and Streptococcus pyogenes. With the combined method, we gained 10% to 20% precision for sensitivities from 30% to 80%. Further, we investigated Streptococcus pyogenes for novel ncRNAs. Using multiple methods--integrated by our framework--we determined four highly probable candidates. We verified all four candidates experimentally using RT-PCR.

Conclusions

We have created an extensible framework for practical, transparent and reproducible combination and comparison of ncRNA detection methods. We have proven the effectiveness of this approach in tests and by guiding experiments to find new ncRNAs. The software is freely available under the GNU General Public License (GPL), version 3 at http://www.sbi.uni-rostock.de/moses along with source code, screen shots, examples and tutorial material.

Legionella pneumophila 6S RNA optimizes intracellular multiplication

Legionella pneumophila is a Gram-negative opportunistic human pathogen that infects and multiplies in a broad range of phagocytic protozoan and mammalian phagocytes. Based on the observation that small regulatory RNAs (sRNAs) play an important role in controlling virulence-related genes in several pathogenic bacteria, we attempted to identify sRNAs expressed by L. pneumophila. We used computational prediction followed by experimental verification to identify and characterize sRNAs encoded in the L. pneumophila genome. A 50-mer probe microarray was constructed to test the expression of predicted sRNAs in bacteria grown under a variety of conditions. This strategy successfully identified 22 expressed RNAs, out of which 6 were confirmed by northern blot and RACE. One of the identified sRNAs is highly expressed in postexponential phase, and computational prediction of its secondary structure reveals a striking similarity to the structure of 6S RNA, a widely distributed prokaryotic sRNA, known to regulate the activity of sigma(70)-containing RNA polymerase. A 70-mer probe microarray was used to identify genes affected by L. pneumophila 6S RNA in stationary phase. The 6S RNA positively regulates expression of genes encoding type IVB secretion system effectors, stress response genes such as groES and recA, as well as many genes involved in acquisition of nutrients and genes with unknown or hypothetical functions. Deletion of 6S RNA significantly reduced L. pneumophila intracellular multiplication in both protist and mammalian host cells, but had no detectable effect on growth in rich media.

Integration of ‘omics’ data: does it lead to new insights into host–microbe interactions?

The interaction between both beneficial and pathogenic microbes and their host has been the subject of many studies. Although the field of systems biology is rapidly evolving, the use of a systems biology approach by means of high-throughput techniques to study host–microbe interactions is just beginning to be explored. In this review, we discuss some of the most recently developed high-throughput ‘omics’ techniques and their use in the context of host–microbe interaction. Moreover, we highlight studies combining several techniques that are pioneering the integration of ‘omics’ data related to host–microbe interactions. Finally, we list the major challenges ahead for successful systems biology research on host–microbe interactions.