Identification of bacterial small non-coding RNAs: experimental approaches

Role of Small Non-Coding RNA in Gram-Negative Bacteria: New Insights and Comprehensive Review of Mechanisms, Functions, and Potential Applications

Small non-coding RNAs (sRNAs) are a key part of gene expression regulation in bacteria. Many physiologic activities like adaptation to environmental stresses, antibiotic resistance, quorum sensing, and modulation of the host immune response are regulated directly or indirectly by sRNAs in Gram-negative bacteria. Therefore, sRNAs can be considered as potentially useful therapeutic options. They have opened promising perspectives in the field of diagnosis of pathogens and treatment of infections caused by antibiotic-resistant organisms. Identification of sRNAs can be executed by sequence and expression-based methods. Despite the valuable progress in the last two decades, and discovery of new sRNAs, their exact role in biological pathways especially in co-operation with other biomolecules involved in gene expression regulation such as RNA-binding proteins (RBPs), riboswitches, and other sRNAs needs further investigation. Although the numerous RNA databases are available, including 59 databases used by RNAcentral, there remains a significant gap in the absence of a comprehensive and professional database that categorizes experimentally validated sRNAs in Gram-negative pathogens. Here, we review the present knowledge about most recent and important sRNAs and their regulatory mechanism, strengths and weaknesses of current methods of sRNAs identification. Also, we try to demonstrate the potential applications and new insights of sRNAs for future studies.

Non-coding regulatory sRNAs from bacteria of the Burkholderia cepacia complex

Small non-coding RNAs (sRNAs) are key regulators of post-transcriptional gene expression in bacteria. Hundreds of sRNAs have been found using in silico genome analysis and experimentally based approaches in bacteria of the Burkholderia cepacia complex (Bcc). However, and despite the hundreds of sRNAs identified so far, the number of functionally characterized sRNAs from these bacteria remains very limited. In this mini-review, we describe the general characteristics of sRNAs and the main mechanisms involved in their action as regulators of post-transcriptional gene expression, as well as the work done so far in the identification and characterization of sRNAs from Bcc. The number of functionally characterized sRNAs from Bcc is expected to increase and to add new knowledge on the biology of these bacteria, leading to novel therapeutic approaches to tackle the infections caused by these opportunistic pathogens, particularly severe among cystic fibrosis patients. KEY POINTS: •Hundreds of sRNAs have been identified in Burkholderia cepacia complex bacteria (Bcc). •A few sRNAs have been functionally characterized in Bcc. •Functionally characterized Bcc sRNAs play major roles in metabolism, biofilm formation, and virulence.

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.

Small regulatory RNAs in Vibrio cholerae

Vibrio cholerae is a major human pathogen causing the diarrheal disease, cholera. Regulation of virulence in V. cholerae is a multifaceted process involving gene expression changes at the transcriptional and post-transcriptional level. Whereas various transcription factors have been reported to modulate virulence in V. cholerae, small regulatory RNAs (sRNAs) have now been established to also participate in virulence control and the regulation of virulence-associated processes, such as biofilm formation, quorum sensing, stress response, and metabolism. In most cases, these sRNAs act by base-pairing with multiple target transcripts and this process typically requires the aid of an RNA-binding protein, such as the widely conserved Hfq protein. This review article summarizes the functional roles of sRNAs in V. cholerae, their underlying mechanisms of gene expression control, and how sRNAs partner with transcription factors to modulate complex regulatory programs. In addition, we will discuss regulatory principles discovered in V. cholerae that not only apply to other Vibrio species, but further extend into the large field of RNA-mediated gene expression control in bacteria.

A novel synthetic sRNA promoting protein overexpression in cell-free systems

Bacterial small RNAs (sRNAs) that regulate gene expression have been engineered for uses in synthetic biology and metabolic engineering. Here, we designed a novel non-Hfq-dependent sRNA scaffold that uses a modifiable 20 nucleotide antisense binding region to target mRNAs selectively and influence protein expression. The system was developed for regulation of a fluorescent reporter in vivo using Escherichia coli, but the system was found to be more responsive and produced statistically significant results when applied to protein synthesis using in vitro cell-free systems (CFS). Antisense binding sequences were designed to target not only translation initiation regions but various secondary structures in the reporter mRNA. Targeting a high-energy stem loop structure and the 3' end of mRNA yielded protein expression knock-downs that approached 70%. Notably, targeting a low-energy stem structure near a potential RNase E binding site led to a statistically significant 65% increase in protein expression (p < 0.05). These results were not obtainable in vivo, and the underlying mechanism was translated from the reporter system to achieve better than 75% increase in recombinant diaphorase expression in a CFS. It is possible the designs developed here can be applied to improve/regulate expression of other proteins in a CFS.

Identification and Regulatory Roles of a New Csr Small RNA from Arctic Pseudoalteromonas fuliginea BSW20308 in Temperature Responses

Small RNAs (sRNAs) play a very important role in gene regulation at the posttranscriptional level. However, sRNAs from nonmodel microorganisms, extremophiles in particular, have been rarely explored. We discovered a putative sRNA, termed Pf1 sRNA, in Pseudoalteromonas fuliginea BSW20308 isolated from the polar regions in our previous work. In this study, we identified the sRNA and investigated its regulatory role in gene expression under different temperatures. Pf1 sRNA was confirmed to be a new member of the CsrB family but has little sequence similarity with Escherichia coli CsrB. However, Pf1 sRNA was able to bind to CsrA from E. coli and P. fuliginea BSW20308 to regulate glycogen synthesis. The Pf1 sRNA knockout strain (ΔPf1) affected motility, fitness, and global gene expression in transcriptomes and proteomes at 4°C and 32°C. Genes related to carbon metabolism, amino acid metabolism, salinity tolerance, antibiotic resistance, oxidative stress, motility, chemotaxis, biofilm, and secretion systems were differentially expressed in the wild-type strain and the ΔPf1 mutant. Our study suggested that Pf1 sRNA might play an important role in response to environmental changes by regulating global gene expression. Specific targets of the Pf1 sRNA-CsrA system were tentatively proposed, such as genes involved in the type VI secretion system, TonB-dependent receptors, and response regulators, but most of them have an unknown function. Since this is the first study of CsrB family sRNA in Pseudoalteromonas and microbes from the polar regions, it provides a novel insight at the posttranscriptional level into the responses and adaptation to temperature changes in bacteria from extreme environments. This study also sheds light on the evolution of sRNA in extreme environments and expands the bacterial sRNA database. IMPORTANCE Previous research on microbial temperature adaptation has focused primarily on functional genes, with little attention paid to posttranscriptional regulation. Small RNAs, the major posttranscriptional modulators of gene expression, are greatly underexplored, especially in nonpathogenic and nonmodel microorganisms. In this study, we verified the first Csr sRNA, named Pf1 sRNA, from Pseudoalteromonas, a model genus for studying cold adaptation. We revealed that Pf1 sRNA played an important role in global regulation and was indispensable in improving fitness. This study provided us a comprehensive view of sRNAs from Pseudoalteromonas and expanded our understanding of bacterial sRNAs from extreme environments.

Do small RNAs unlock the below ground microbiome-plant interaction mystery?

Over the past few decades, regulatory RNAs, such as small RNAs (sRNAs), have received increasing attention in the context of host-microbe interactions due to their diverse roles in controlling various biological processes in eukaryotes. In addition, studies have identified an increasing number of sRNAs with novel functions across a wide range of bacteria. What is not well understood is why cells regulate gene expression through post-transcriptional mechanisms rather than at the initiation of transcription. The finding of a multitude of sRNAs and their identified associated targets has allowed further investigation into the role of sRNAs in mediating gene regulation. These foundational data allow for further development of hypotheses concerning how a precise control of gene activity is accomplished through the combination of transcriptional and post-transcriptional regulation. Recently, sRNAs have been reported to participate in interkingdom communication and signalling where sRNAs originating from one kingdom are able to target or control gene expression in another kingdom. For example, small RNAs of fungal pathogens that silence plant genes and vice-versa plant sRNAs that mediate bacterial gene expression. However, there is currently a lack of evidence regarding sRNA-based inter-kingdom signalling across more than two interacting organisms. A habitat that provides an excellent opportunity to investigate interconnectivity is the plant rhizosphere, a multifaceted ecosystem where plants and associated soil microbes are known to interact. In this paper, we discuss how the interconnectivity of bacteria, fungi, and plants within the rhizosphere may be mediated by bacterial sRNAs with a particular focus on disease suppressive and non-suppressive soils. We discuss the potential roles sRNAs may play in the below-ground world and identify potential areas of future research, particularly in reference to the regulation of plant immunity genes by bacterial and fungal communities in disease-suppressive and non-disease-suppressive soils.

Prediction of Bacterial sRNAs Using Sequence-Derived Features and Machine Learning

Small ribonucleic acid (sRNA) sequences are 50–500 nucleotide long, noncoding RNA (ncRNA) sequences that play an important role in regulating transcription and translation within a bacterial cell. As such, identifying sRNA sequences within an organism’s genome is essential to understand the impact of the RNA molecules on cellular processes. Recently, numerous machine learning models have been applied to predict sRNAs within bacterial genomes. In this study, we considered the sRNA prediction as an imbalanced binary classification problem to distinguish minor positive sRNAs from major negative ones within imbalanced data and then performed a comparative study with six learning algorithms and seven assessment metrics. First, we collected numerical feature groups extracted from known sRNAs previously identified in Salmonella typhimurium LT2 (SLT2) and Escherichia coli K12 (E. coli K12) genomes. Second, as a preliminary study, we characterized the sRNA-size distribution with the conformity test for Benford’s law. Third, we applied six traditional classification algorithms to sRNA features and assessed classification performance with seven metrics, varying positive-to-negative instance ratios, and utilizing stratified 10-fold cross-validation. We revisited important individual features and feature groups and found that classification with combined features perform better than with either an individual feature or a single feature group in terms of Area Under Precision-Recall curve (AUPR). We reconfirmed that AUPR properly measures classification performance on imbalanced data with varying imbalance ratios, which is consistent with previous studies on classification metrics for imbalanced data. Overall, eXtreme Gradient Boosting (XGBoost), even without exploiting optimal hyperparameter values, performed better than the other five algorithms with specific optimal parameter settings. As a future work, we plan to extend XGBoost further to a large amount of published sRNAs in bacterial genomes and compare its classification performance with recent machine learning models’ performance.

Key players in regulatory RNA realm of bacteria

Precise regulation of gene expression is crucial for living cells to adapt for survival in diverse environmental conditions. Among the common cellular regulatory mechanisms, RNA-based regulators play a key role in all domains of life. Discovery of regulatory RNAs have made a paradigm shift in molecular biology as many regulatory functions of RNA have been identified beyond its canonical roles as messenger, ribosomal and transfer RNA. In the complex regulatory RNA network, riboswitches, small RNAs, and RNA thermometers can be identified as some of the key players. Herein, we review the discovery, mechanism, and potential therapeutic use of these classes of regulatory RNAs mainly found in bacteria. Being highly adaptive organisms that inhabit a broad range of ecological niches, bacteria have adopted tight and rapid-responding gene regulation mechanisms. This review aims to highlight how bacteria utilize versatile RNA structures and sequences to build a sophisticated gene regulation network.

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The three major classes of prokaryotic ncRNAs and their characterized mechanisms of operation in gene regulation.

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sRNAs emerging as major players in global gene regulatory networks.

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Riboswitch mediated gene control mechanisms through on/off switches in response to ligand binding.

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RNA thermo sensors for temperature-dependent gene expression.

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Therapeutic importance of ncRNAs and computational approaches involved in the discovery of ncRNAs.

In Silico Prediction for ncRNAs in Prokaryotes

The identification and characterization of non-coding RNAs (ncRNAs) in prokaryotes is an important step in the study of the interaction of these molecules with mRNAs-or target proteins, in the post-transcriptional regulation process. Here, we describe one of the main in silico prediction methods in prokaryotes, using the TargetRNA2 tool to predict target mRNAs.

An Integrated Database of Small RNAs and Their Interplay With Transcriptional Gene Regulatory Networks in Corynebacteria

Small RNAs (sRNAs) are one of the key players in the post-transcriptional regulation of bacterial gene expression. These molecules, together with transcription factors, form regulatory networks and greatly influence the bacterial regulatory landscape. Little is known concerning sRNAs and their influence on the regulatory machinery in the genus Corynebacterium, despite its medical, veterinary and biotechnological importance. Here, we expand corynebacterial regulatory knowledge by integrating sRNAs and their regulatory interactions into the transcriptional regulatory networks of six corynebacterial species, covering four human and animal pathogens, and integrate this data into the CoryneRegNet database. To this end, we predicted sRNAs to regulate 754 genes, including 206 transcription factors, in corynebacterial gene regulatory networks. Amongst them, the sRNA Cd-NCTC13129-sRNA-2 is predicted to directly regulate ydfH, which indirectly regulates 66 genes, including the global regulator glxR in C. diphtheriae. All of the sRNA-enriched regulatory networks of the genus Corynebacterium have been made publicly available in the newest release of CoryneRegNet(www.exbio.wzw.tum.de/coryneregnet/) to aid in providing valuable insights and to guide future experiments.

Research on the Mechanism of Soybean Resistance to Phytophthora Infection Using Machine Learning Methods

Since the emergence of the Phytophthora sojae infection, economic losses of 10-20 billion U.S. dollars have been annually reported. Studies have revealed that P. sojae works by releasing effect factors such as small RNA in the process of infecting soybeans, but research on the interaction mechanism between plants and fungi at the small RNA level remains vague and unclear. For this reason, studying the resistance mechanism of the hosts after P. sojae invades soybeans has critical theoretical and practical significance for increasing soybean yield. The present article is premised on the high-throughput data published by the National Center of Biotechnology Information (NCBI). We selected 732 sRNA sequences through big data analysis whose expression level increased sharply after soybean was infected by P. sojae and 36 sRNA sequences with massive expression levels newly generated after infection. This article analyzes the resistance mechanism of soybean to P. sojae from two aspects of plant's own passive stress and active resistance. This article analyzes the resistance mechanism of soybean to P. sojae from two aspects of plant's own passive stress and active resistance. These 768 sRNA sequences are targeted to soybean mRNA and P. sojae mRNA, and 2,979 and 1,683 targets are obtained, respectively. The PageRank algorithm was used to screen the core functional clusters, and 50 core nodes targeted to soybeans were obtained, which were analyzed for functional enrichment, and 12 KEGG_Pathway and 18 Go(BP) were obtained. The node targeted to P. sojae was subjected to functional enrichment analysis to obtain 11 KEGG_Pathway. The results show that there are multiple Go(BP) and KEGG_Pathway related to soybean growth and defense and reverse resistance of P. sojae. In addition, by comparing the small RNA prediction model of soybean resistance with Phytophthora pathogenicity constructed by the three machine learning methods of random forest, support vector machine, and XGBoost, about the accuracy, precision, recall rate, and F-measure, the results show that the three models have satisfied classification effect. Among the three models, XGBoost had an accuracy rate of 86.98% in the verification set.

Research on Transboundary Regulation of Plant-Derived Exogenous MiRNA Based on Biological Big Data

In recent years, researchers have discovered plant miRNA (plant xenomiR) in mammalian samples, but it is unclear whether it exists stably and participates in regulation. In this paper, a cross-border regulation model of plant miRNAs based on biological big data is constructed to study the possible cross-border regulation of plant miRNAs. Firstly, a variety of human edible plants were selected, and based on the miRNA data detected in human experimental studies, screening was performed to obtain the plant xenomiR that may stably exist in the human body. Then, we use plant and animal target gene prediction methods to obtain the mRNAs of animals and plants that may be regulated, respectively. Finally, we use GO (Gene Ontology) and the Multiple Dimensional Scaling (MDS) algorithm to analyze the biological processes regulated by plants and animals. We obtain the relationship between different biological processes and explore the regulatory commonality and individuality of plant xenomiR in plants and humans. Studies have shown that the development and metabolic functions of the human body are affected by daily eating habits. Soybeans, corn, and rice can not only affect the daily development and metabolism of the human body but also regulate biological processes such as protein modification and mitosis. This conclusion explains the reasons for the different physiological functions of the human body. This research is an important meaning for the design of small RNA drugs in Chinese herbal medicine and the treatment of human nutritional diseases.

Divergently Transcribed ncRNAs in Escherichia coli: Refinement of the Transcription Starts Assumes Functional Diversification

Non-coding regulatory RNAs (ncRNAs) comprise specialized group of essential genetically encoded biological molecules involved in the wide variety of cellular metabolic processes. The progressive increase in the number of newly identified ncRNAs and the defining of their genome location indicate their predominant nesting in intergenic regions and expression under the control of their own regulatory elements. At the same time, the regulation of ncRNA's transcription cannot be considered in isolation from the processes occurring in the immediate genetic environment. A number of experimental data indicate the notable impact of positional regulation of gene expression mediated by dynamic temporal DNA rearrangements accompanying transcription events in the vicinity of neighboring genes. This issue can be perceived as particularly significant for divergently transcribed ncRNAs being actually subjected to double regulatory pressure. Based on available results of RNAseq experiments for Escherichia coli, we screened out divergent ncRNAs and the adjacent genes for the exact positions of transcription start sites (TSSs) and relative efficiency of RNA production. This analysis revealed extension or shortening of some previously annotated ncRNAs resulting in modified secondary structure, confirmed stable expression of four ncRNAs annotated earlier as putative, and approved the possibility of expression of divergently transcribed ncRNAs containing repetitive extragenic palindromic (REP) elements. The biogenesis of secreted ncRNAs from divergently transcribed ffs, chiX, ralA, and ryhB is discussed taking into account positions of TSSs. Refinement of TSSs for the neighboring genes renders some ncRNAs as true antisense overlapping with 5'UTR of divergently transcribed mRNAs.

Genome-wide identification of Azospirillum brasilense Sp245 small RNAs responsive to nitrogen starvation and likely involvement in plant-microbe interactions

BACKGROUND

Small RNAs (sRNAs) are non-coding RNAs known to regulate various biological functions such as stress adaptation, metabolism, virulence as well as pathogenicity across a wide range of bacteria, mainly by controlling mRNA stabilization or regulating translation. Identification and functional characterization of sRNAs has been carried out in various plant growth-promoting bacteria and they have been shown to help the cells cope up with environmental stress. No study has been carried out to uncover these regulatory molecules in the diazotrophic alpha-proteobacterium Azospirillum brasilense Sp245 to date.

RESULTS

Expression-based sRNA identification (RNA-seq) revealed the first list of ~ 468 sRNA candidate genes in A. brasilense Sp245 that were differentially expressed in nitrogen starvation versus non-starved conditions. In parallel, in silico tools also identified 2 of the above as candidate sRNAs. Altogether, putative candidates were stringently curated from RNA-seq data based on known sRNA parameters (size, location, secondary structure, and abundance). In total, ~ 59 significantly expressed sRNAs were identified in this study of which 53 are potentially novel sRNAs as they have no Rfam and BSRD homologs. Sixteen sRNAs were randomly selected and validated for differential expression, which largely was found to be in congruence with the RNA-seq data.

CONCLUSIONS

Differential expression of 468 A. brasilense sRNAs was indicated by RNA-seq data, a subset of which was confirmed by expression analysis. Four of the significantly expressed sRNAs were not observed in nitrogen starvation while 16 sRNAs were found to be exclusively expressed in nitrogen depletion. Putative candidate sRNAs identified have potential mRNA targets primarily involved in stress (abiotic and biotic) adaptability; regulation of bacterial cellular, biological and molecular pathways such as nitrogen fixation, polyhydroxybutyrate synthesis, chemotaxis, biofilm formation and transcriptional regulation. In addition to directly influencing bacteria, some of these sRNAs also have targets influencing plant-microbe interactions through adhesion of bacteria to plant roots directly, suppressing host response, inducing plant defence and signalling.

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.

Identification, Prediction and Data Analysis of Noncoding RNAs: A Review

BACKGROUND

Noncoding RNAs (ncRNAs) which play an important role in various cellular processes are important in medicine as well as in drug design strategies. Different studies have shown that ncRNAs are dis-regulated in cancer cells and play an important role in human tumorigenesis. Therefore, it is important to identify and predict such molecules by experimental and computational methods, respectively. However, to avoid expensive experimental methods, computational algorithms have been developed for accurately and fast prediction of ncRNAs.

OBJECTIVE

The aim of this review was to introduce the experimental and computational methods to identify and predict ncRNAs structure. Also, we explained the ncRNA's roles in cellular processes and drugs design, briefly.

METHOD

In this survey, we will introduce ncRNAs and their roles in biological and medicinal processes. Then, some important laboratory techniques will be studied to identify ncRNAs. Finally, the state-of-the-art models and algorithms will be introduced along with important tools and databases.

RESULTS

The results showed that the integration of experimental and computational approaches improves to identify ncRNAs. Moreover, the high accurate databases, algorithms and tools were compared to predict the ncRNAs.

CONCLUSION

ncRNAs prediction is an exciting research field, but there are different difficulties. It requires accurate and reliable algorithms and tools. Also, it should be mentioned that computational costs of such algorithm including running time and usage memory are very important. Finally, some suggestions were presented to improve computational methods of ncRNAs gene and structural prediction.

Sequence-based bacterial small RNAs prediction using ensemble learning strategies

Background

Bacterial small non-coding RNAs (sRNAs) have emerged as important elements in diverse physiological processes, including growth, development, cell proliferation, differentiation, metabolic reactions and carbon metabolism, and attract great attention. Accurate prediction of sRNAs is important and challenging, and helps to explore functions and mechanism of sRNAs.

Results

In this paper, we utilize a variety of sRNA sequence-derived features to develop ensemble learning methods for the sRNA prediction. First, we compile a balanced dataset and four imbalanced datasets. Then, we investigate various sRNA sequence-derived features, such as spectrum profile, mismatch profile, reverse compliment k-mer and pseudo nucleotide composition. Finally, we consider two ensemble learning strategies to integrate all features for building ensemble learning models for the sRNA prediction. One is the weighted average ensemble method (WAEM), which uses the linear weighted sum of outputs from the individual feature-based predictors to predict sRNAs. The other is the neural network ensemble method (NNEM), which trains a deep neural network by combining diverse features. In the computational experiments, we evaluate our methods on these five datasets by using 5-fold cross validation. WAEM and NNEM can produce better results than existing state-of-the-art sRNA prediction methods.

Conclusions

WAEM and NNEM have great potential for the sRNA prediction, and are helpful for understanding the biological mechanism of bacteria.

The small RNA, SdsR, acts as a novel type of toxin in Escherichia coli

Most small noncoding RNAs (sRNAs) are known to base pair with target mRNAs and regulate mRNA stability or translation to trigger various changes in the cell metabolism of Escherichia coli. The SdsR sRNA is expressed specifically during the stationary phase and represses tolC and mutS expression. However, it was not previously known whether the growth-phase-dependent regulation of SdsR is important for cell growth. Here, we ectopically expressed SdsR during the exponential phase and examined cell growth and survival. We found that ectopic expression of SdsR led to a significant and Hfq-dependent cell death with accompanying cell filamentation. This SdsR-driven cell death was alleviated by overexpression of RyeA, an sRNA transcribed on the opposite DNA strand, suggesting that SdsR/RyeA is a novel type of toxin-antitoxin (T/A) system in which both the toxin and the antitoxin are sRNAs. We defined the minimal region required for the SdsR-driven cell death. We also performed RNA-seq analysis and identified 209 genes whose expression levels were altered by more than two-fold following pulse expression of ectopic SdsR at exponential phase. Finally, we found that that the observed SdsR-driven cell death was mainly caused by the SdsR-mediated repression of yhcB, which encodes an inner membrane protein.

Two virulent sRNAs identified by genomic sequencing target the type III secretion system in rice bacterial blight pathogen

BACKGROUND

Small non-coding RNA (sRNA) short sequences regulate various biological processes in all organisms, including bacteria that are animal or plant pathogens. Virulent or pathogenicity-associated sRNAs have been increasingly elucidated in animal pathogens but little is known about similar category of sRNAs in plant-pathogenic bacteria. This is particularly true regarding rice bacterial blight pathogen Xanthomonas oryzae pathovar oryzae (Xoo) as studies on the virulent role of Xoo sRNAs is very limited at present.

RESULTS

The number and genomic distribution of sRNAs in Xoo were determined by bioinformatics analysis based on high throughput sequencing (sRNA-Seq) of the bacterial cultures from virulence-inducing and standard growth media, respectively. A total of 601 sRNAs were identified in the Xoo genome and ten virulent sRNA candidates were screened out based on significant differences of their expression levels between the culture conditions. In addition, trans3287 and trans3288 were also selected as candidates due to high expression levels in both media. The differential expression of 12 sRNAs evidenced by the sRNA-Seq data was confirmed by a convincing quantitative method. Based on genetic analysis of Xoo ΔsRNA mutants generated by deletion of the 12 single sRNAs, trans217 and trans3287 were characterized as virulent sRNAs. They are essential not only for the formation of bacterial blight in a susceptible rice variety Nipponbare but also for the induction of hypersensitive response (HR) in nonhost plant tobacco. Xoo Δtrans217 and Δtrans3287 mutants fail to induce bacterial blight in Nipponbare and also fail to induce the HR in tobacco, whereas, genetic complementation restores both mutants to the wild type in the virulent performance and HR induction. Similar effects of gene knockout and complementation were found in the expression of hrpG and hrpX genes, which encode regulatory proteins of the type III secretion system. Consistently, secretion of a type III effector, PthXo1, is blocked in Δtrans217 or Δtrans3287 bacterial cultures but retrieved by genetic complementation to both mutants.

CONCLUSIONS

The genetic analysis characterizes trans217 and trans3287 as pathogenicity-associated sRNAs essential for the bacterial virulence on the susceptible rice variety and for the HR elicitation in the nonhost plant. The molecular evidence suggests that both virulent sRNAs regulate the bacterial virulence by targeting the type III secretion system.

The Use of Biosensors to Explore the Potential of Probiotic Strains to Reduce the SOS Response and Mutagenesis in Bacteria

A model system based on the Escherichia coli MG1655 (pRecA-lux) Lux-biosensor was used to evaluate the ability of the fermentates of eight probiotic strains to reduce the SOS response stimulated by ciprofloxacin in bacteria and mutagenesis mediated by it. Preliminary attempts to estimate the chemical nature of active components of the fermentates were conducted.

6S RNA is involved in acid resistance and invasion of epithelial cells in Salmonella enterica serovar Typhimurium

AIM

Acid is an important environmental condition encountered frequently by Salmonella enterica serovar Typhimurium during its pathogenesis, but the role of small-noncoding RNAs (sRNAs) in response to acid stress is poorly understood.

METHODS

We used RNA sequencing to explore acid-responsive sRNAs in S. Typhimurium.

RESULTS

It identified that 6S RNA encoded by the ssrS was significantly upregulated at pH 3.0. The 6S RNA knockout strain showed a reduced ability to survive at pH 3.0. Additionally, genes in Salmonella pathogenicity island-1 were downregulated in the 6S RNA knockout strain. The loss of 6S RNA significantly reduced S. Typhimurium invasion ability in HeLa cells and virulence in a mouse model.

CONCLUSION

These findings demonstrate that 6S RNA plays an important role in S. Typhimurium survival under extremely acid conditions and for invasion of epithelial cells.

Small RNAs in Bacterial Virulence and Communication

Bacterial pathogens must endure or adapt to different environments and stresses during transmission and infection. Posttranscriptional gene expression control by regulatory RNAs, such as small RNAs and riboswitches, is now considered central to adaptation in many bacteria, including pathogens. The study of RNA-based regulation (riboregulation) in pathogenic species has provided novel insight into how these bacteria regulate virulence gene expression. It has also uncovered diverse mechanisms by which bacterial small RNAs, in general, globally control gene expression. Riboregulators as well as their targets may also prove to be alternative targets or provide new strategies for antimicrobials. In this article, we present an overview of the general mechanisms that bacteria use to regulate with RNA, focusing on examples from pathogens. In addition, we also briefly review how deep sequencing approaches have aided in opening new perspectives in small RNA identification and the study of their functions. Finally, we discuss examples of riboregulators in two model pathogens that control virulence factor expression or survival-associated phenotypes, such as stress tolerance, biofilm formation, or cell-cell communication, to illustrate how riboregulation factors into regulatory networks in bacterial pathogens.

Genome-Wide Detection of Small Regulatory RNAs in Deep-Sea Bacterium Shewanella piezotolerans WP3

Shewanella are one of the most abundant Proteobacteria in the deep-sea and are renowned for their versatile electron accepting capacities. The molecular mechanisms involved in their adaptation to diverse and extreme environments are not well understood. Small non-coding RNAs (sRNAs) are known for modulating the gene expression at transcriptional and posttranscriptional levels, subsequently playing a key role in microbial adaptation. To understand the potential roles of sRNAs in the adaptation of Shewanella toward deep-sea environments, here an in silico approach was utilized to detect the sRNAs in the genome of Shewanella piezotolerans WP3, a piezotolerant and psychrotolerant deep-sea iron reducing bacterium. After scanning 3673 sets of 5' and 3' UTRs of orthologous genes, 209 sRNA candidates were identified with high confidence in S. piezotolerans WP3. About 92% (193 out of 209) of these putative sRNAs belong to the class trans-encoded RNAs, suggesting that trans-regulatory RNAs are the dominant class of sRNAs in S. piezotolerans WP3. The remaining 16 cis-regulatory RNAs were validated through quantitative polymerase chain reaction. Five cis-sRNAs were further shown to act as cold regulated sRNAs. Our study provided additional evidence at the transcriptional level to decipher the microbial adaptation mechanisms to extreme environmental conditions.

RT-qPCR with chimeric dU stem-loop primer is efficient for the detection of bacterial small RNAs

Small non-coding RNAs are considered be involved in the regulation of multiple cellular processes. Quantitative reverse transcription PCR (RT-qPCR) is widely used in the detection of eukaryotic microRNA, and the stem-loop primers can improve the specificity and efficiency of reverse transcription. However, the loop structure of primers probably influence the next quantitative amplification due to the base stacking and steric hindrance. Here, we designed a chimeric stem-loop primer with a deoxyuracil (dU) base located near the RNA matching part. After the reverse transcription, uracil-DNA glycosylase (UDG) treatment was used to remove the dU base and destroy the stem-loop structure of RT product. Enzymatic assay confirmed that the recombinant UDG could efficiently eliminate the dU base in the oligonucleotide. Transcriptions of two small RNAs (TFF and ryeA) in Escherichia coli were detected by RT-qPCR with different primers. Results showed that the use of the chimeric dU stem-loop primer and UDG treatment could enhance the detection specificity and sensitivity about 1.1- to 3.4-fold, compared to those with traditional stem-loop primer and linear primer. Total RNA of 1-10 pg was enough for efficient detection with the chimeric stem-loop primers. In a word, this strategy could promote the RT-qPCR detection efficiency on the transcription of bacterial small RNAs even in trace samples and can facilitate the detection of exiguous change in cellular metabolism.

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.

Modeling sRNA-Regulated Plasmid Maintenance

We study a theoretical model for the toxin-antitoxin (hok/sok) mechanism for plasmid maintenance in bacteria. Toxin-antitoxin systems enforce the maintenance of a plasmid through post-segregational killing of cells that have lost the plasmid. Key to their function is the tight regulation of expression of a protein toxin by an sRNA antitoxin. Here, we focus on the nonlinear nature of the regulatory circuit dynamics of the toxin-antitoxin mechanism. The mechanism relies on a transient increase in protein concentration rather than on the steady state of the genetic circuit. Through a systematic analysis of the parameter dependence of this transient increase, we confirm some known design features of this system and identify new ones: for an efficient toxin-antitoxin mechanism, the synthesis rate of the toxin’s mRNA template should be lower that of the sRNA antitoxin, the mRNA template should be more stable than the sRNA antitoxin, and the mRNA-sRNA complex should be more stable than the sRNA antitoxin. Moreover, a short half-life of the protein toxin is also beneficial to the function of the toxin-antitoxin system. In addition, we study a therapeutic scenario in which a competitor mRNA is introduced to sequester the sRNA antitoxin, causing the toxic protein to be expressed.

Bacterial Small Regulatory RNAs and Hfq Protein

Small regulatory RNA (sRNA) is a unique noncoding RNA involved in regulation of gene expression in both eukaryotic and bacterial cells. This short review discusses examples of positive and negative translation regulation by sRNAs in bacteria and participation of Hfq in these processes. The importance of structure investigation of nucleotide-protein and RNA-protein complexes for designing a model of Hfq interaction with both mRNA and sRNA simultaneously is demonstrated.

Active Shiga-Like Toxin Produced by Some Aeromonas spp., Isolated in Mexico City

RNA silencing is a conserved mechanism that utilizes small RNAs (sRNAs) to direct the regulation of gene expression at the transcriptional or post-transcriptional level. Plants utilizing RNA silencing machinery to defend pathogen infection was first identified in plant–virus interaction and later was observed in distinct plant–pathogen interactions. RNA silencing is not only responsible for suppressing RNA accumulation and movement of virus and viroid, but also facilitates plant immune responses against bacterial, oomycete, and fungal infection. Interestingly, even the same plant sRNA can perform different roles when encounters with different pathogens. On the other side, pathogens counteract by generating sRNAs that directly regulate pathogen gene expression to increase virulence or target host genes to facilitate pathogen infection. Here, we summarize the current knowledge of the characterization and biogenesis of host- and pathogen-derived sRNAs, as well as the different RNA silencing machineries that plants utilize to defend against different pathogens. The functions of these sRNAs in defense and counter-defense and their mechanisms for regulation during different plant–pathogen interactions are also discussed.

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.

The Small RNA DsrA Influences the Acid Tolerance Response and Virulence of Salmonella enterica Serovar Typhimurium

The Gram-negative, enteropathogen Salmonella enterica serovar Typhimurium (S. Typhimurium) is exposed to various stress conditions during pathogenesis, of which acid stress serves as a major defense mechanism in the host. Such environments are encountered in the stomach and Salmonella containing vacuole of phagocytic and non-phagocytic cells. It is only recently that small RNAs (sRNAs) have come to the forefront as major regulators of stress response networks. Consequently, the sRNA DsrA which regulates acid resistance in Escherichia coli, has not been characterized in the acid tolerance response (ATR) of Salmonella. In this study, we show dsrA to be induced two and threefold under adaptation and challenge phases of the ATR, respectively. Additionally, an isogenic mutant lacking dsrA (ΔDsrA) displayed lower viability under the ATR along with reduced motility, feeble adhesion and defective invasion efficacy in vitro. Expression analysis revealed down regulation of several Salmonella pathogenicity island-1 (SPI-1) effectors in ΔDsrA compared to the wild-type, under SPI-1 inducing conditions. Additionally, our in vivo data revealed ΔDsrA to be unable to cause gut inflammation in C57BL/6 mice at 72 h post infection, although intracellular survival and systemic dissemination remained unaffected. A possible explanation may be the significantly reduced expression of flagellin structural genes fliC and fljB in ΔDsrA, which have been implicated as major proinflammatory determinants. This study serves to highlight the role of sRNAs such as DsrA in both acid tolerance and virulence of S. Typhimurium. Additionally the robust phenotype of non-invasiveness could be exploited in developing SPI-I attenuated S. Typhimurium strains without disrupting SPI-I genes.

Bacterial antisense RNAs are mainly the product of transcriptional noise

cis-Encoded antisense RNAs (asRNAs) are widespread along bacterial transcriptomes. However, the role of most of these RNAs remains unknown, and there is an ongoing discussion as to what extent these transcripts are the result of transcriptional noise. We show, by comparative transcriptomics of 20 bacterial species and one chloroplast, that the number of asRNAs is exponentially dependent on the genomic AT content and that expression of asRNA at low levels exerts little impact in terms of energy consumption. A transcription model simulating mRNA and asRNA production indicates that the asRNA regulatory effect is only observed above certain expression thresholds, substantially higher than physiological transcript levels. These predictions were verified experimentally by overexpressing nine different asRNAs in Mycoplasma pneumoniae. Our results suggest that most of the antisense transcripts found in bacteria are the consequence of transcriptional noise, arising at spurious promoters throughout the genome.

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.

Experimental approaches to identify small RNAs and their diverse roles in bacteria--what we have learnt in one decade of MicA research

Nowadays the identification of small RNAs (sRNAs) and characterization of their role within regulatory networks takes a prominent place in deciphering complex bacterial phenotypes. Compared to the study of other components of bacterial cells, this is a relatively new but fast-growing research field. Although reports on new sRNAs appear regularly, some sRNAs are already subject of research for a longer time. One of such sRNAs is MicA, a sRNA best described for its role in outer membrane remodeling, but probably having a much broader function than anticipated. An overview of what we have learnt from MicA led to the conclusion that even for this well-described sRNA, we still do not have the overall picture. More general, the story of MicA might become an experimental lead for unraveling the many sRNAs with unknown functions. In this review, three important topics in the sRNA field are covered, exemplified from the perspective of MicA: (i) identification of new sRNAs, (ii) target identification and unraveling the biological function, (iii) structural analysis. The complex mechanisms of action of MicA deliver some original insights in the sRNA field which includes the existence of dimer formation or simultaneous cis and trans regulation, and might further inspire the understanding of the function of other sRNAs.

Genome-wide analyses in bacteria show small-RNA enrichment for long and conserved intergenic regions

Interest in finding small RNAs (sRNAs) in bacteria has significantly increased in recent years due to their regulatory functions. Development of high-throughput methods and more sophisticated computational algorithms has allowed rapid identification of sRNA candidates in different species. However, given their various sizes (50 to 500 nucleotides [nt]) and their potential genomic locations in the 5' and 3' untranslated regions as well as in intergenic regions, identification and validation of true sRNAs have been challenging. In addition, the evolution of bacterial sRNAs across different species continues to be puzzling, given that they can exert similar functions with various sequences and structures. In this study, we analyzed the enrichment patterns of sRNAs in 13 well-annotated bacterial species using existing transcriptome and experimental data. All intergenic regions were analyzed by WU-BLAST to examine conservation levels relative to species within or outside their genus. In total, more than 900 validated bacterial sRNAs and 23,000 intergenic regions were analyzed. The results indicate that sRNAs are enriched in intergenic regions, which are longer and more conserved than the average intergenic regions in the corresponding bacterial genome. We also found that sRNA-coding regions have different conservation levels relative to their flanking regions. This work provides a way to analyze how noncoding RNAs are distributed in bacterial genomes and also shows conserved features of intergenic regions that encode sRNAs. These results also provide insight into the functions of regions surrounding sRNAs and into optimization of RNA search algorithms.

Mycobacterial RNA isolation optimized for non-coding RNA: high fidelity isolation of 5S rRNA from Mycobacterium bovis BCG reveals novel post-transcriptional processing and a complete spectrum of modified ribonucleosides

A major challenge in the study of mycobacterial RNA biology is the lack of a comprehensive RNA isolation method that overcomes the unusual cell wall to faithfully yield the full spectrum of non-coding RNA (ncRNA) species. Here, we describe a simple and robust procedure optimized for the isolation of total ncRNA, including 5S, 16S and 23S ribosomal RNA (rRNA) and tRNA, from mycobacteria, using Mycobacterium bovis BCG to illustrate the method. Based on a combination of mechanical disruption and liquid and solid-phase technologies, the method produces all major species of ncRNA in high yield and with high integrity, enabling direct chemical and sequence analysis of the ncRNA species. The reproducibility of the method with BCG was evident in bioanalyzer electrophoretic analysis of isolated RNA, which revealed quantitatively significant differences in the ncRNA profiles of exponentially growing and non-replicating hypoxic bacilli. The method also overcame an historical inconsistency in 5S rRNA isolation, with direct sequencing revealing a novel post-transcriptional processing of 5S rRNA to its functional form and with chemical analysis revealing seven post-transcriptional ribonucleoside modifications in the 5S rRNA. This optimized RNA isolation procedure thus provides a means to more rigorously explore the biology of ncRNA species in mycobacteria.

Transcriptional landscape and essential genes of Neisseria gonorrhoeae

The WHO has recently classified Neisseria gonorrhoeae as a super-bacterium due to the rapid spread of antibiotic resistant derivatives and an overall dramatic increase in infection incidences. Genome sequencing has identified potential genes, however, little is known about the transcriptional organization and the presence of non-coding RNAs in gonococci. We performed RNA sequencing to define the transcriptome and the transcriptional start sites of all gonococcal genes and operons. Numerous new transcripts including 253 potentially non-coding RNAs transcribed from intergenic regions or antisense to coding genes were identified. Strikingly, strong antisense transcription was detected for the phase-variable opa genes coding for a family of adhesins and invasins in pathogenic Neisseria, that may have regulatory functions. Based on the defined transcriptional start sites, promoter motifs were identified. We further generated and sequenced a high density Tn5 transposon library to predict a core of 827 gonococcal essential genes, 133 of which have no known function. Our combined RNA-Seq and Tn-Seq approach establishes a detailed map of gonococcal genes and defines the first core set of essential gonococcal genes.

Differential expression of small RNAs from Burkholderia thailandensis in response to varying environmental and stress conditions

BACKGROUND

Bacterial small RNAs (sRNAs) regulate gene expression by base-pairing with downstream target mRNAs to attenuate translation of mRNA into protein at the post-transcriptional level. In response to specific environmental changes, sRNAs can modulate the expression levels of target genes, thus enabling adaptation of cellular physiology.

RESULTS

We profiled sRNA expression in the Gram-negative bacteria Burkholderia thailandensis cultured under 54 distinct growth conditions using a Burkholderia-specific microarray that contains probe sets to all intergenic regions greater than 90 bases. We identified 38 novel sRNAs and performed experimental validation on five sRNAs that play a role in adaptation of Burkholderia to cell stressors. In particular, the trans-encoded BTH_s1 and s39 exhibited differential expression profiles dependent on growth phase and cell stimuli, such as antibiotics and serum. Furthermore, knockdown of the highly-expressed BTH_s39 by antisense transcripts reduced B. thailandensis cell growth and attenuated host immune response upon infection, indicating that BTH_s39 functions in bacterial metabolism and adaptation to the host. In addition, expression of cis-encoded BTH_s13 and s19 found in the 5' untranslated regions of their cognate genes correlated with tight regulation of gene transcript levels. This sRNA-mediated downregulation of gene expression may be a conserved mechanism of post-transcriptional gene dosage control.

CONCLUSIONS

These studies provide a broad analysis of differential Burkholderia sRNA expression profiles and illustrate the complexity of bacterial gene regulation in response to different environmental stress conditions.

Discovery of ethanol-responsive small RNAs in Zymomonas mobilis

Zymomonas mobilis is a bacterium that can produce ethanol by fermentation. Due to its unique metabolism and efficient ethanol production, Z. mobilis has attracted special interest for biofuel energy applications; an important area of study is the regulation of those specific metabolic pathways. Small RNAs (sRNAs) have been studied as molecules that function as transcriptional regulators in response to cellular stresses. While sRNAs have been discovered in various organisms by computational prediction and experimental approaches, their discovery in Z. mobilis has not yet been reported. In this study, we have applied transcriptome analysis and computational predictions to facilitate identification and validation of 15 novel sRNAs in Z. mobilis. We furthermore characterized their expression in the context of high and low levels of intracellular ethanol. Here, we report that 3 of the sRNAs (Zms2, Zms4, and Zms6) are differentially expressed under aerobic and anaerobic conditions, when low and high ethanol productions are observed, respectively. Importantly, when we tested the effect of ethanol stress on the expression of sRNAs in Z. mobilis, Zms2, Zms6, and Zms18 showed differential expression under 5% ethanol stress conditions. These data suggest that in this organism regulatory RNAs can be associated with metabolic functions involved in ethanol stress responses.

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.

A model system for studying the transcriptomic and physiological changes associated with mammalian host-adaptation by Leptospira interrogans serovar Copenhageni

Leptospirosis, an emerging zoonotic disease with worldwide distribution, is caused by spirochetes belonging to the genus Leptospira. More than 500,000 cases of severe leptospirosis are reported annually, with >10% of these being fatal. Leptospires can survive for weeks in suitably moist conditions before encountering a new host. Reservoir hosts, typically rodents, exhibit little to no signs of disease but shed large numbers of organisms in their urine. Transmission occurs when mucosal surfaces or abraded skin come into contact with infected urine or urine-contaminated water or soil. In humans, leptospires can cause a variety of clinical manifestations, ranging from asymptomatic or mild fever to severe icteric (Weil's) disease and pulmonary haemorrhage. Currently, little is known about how Leptospira persist within a reservoir host. Prior in vitro studies have suggested that leptospires alter their transcriptomic and proteomic profiles in response to environmental signals encountered during mammalian infection. However, no study has examined gene expression by leptospires within a mammalian host-adapted state. To obtain a more faithful representation of how leptospires respond to host-derived signals, we used RNA-Seq to compare the transcriptome of L. interrogans cultivated within dialysis membrane chambers (DMCs) implanted into the peritoneal cavities of rats with that of organisms grown in vitro. In addition to determining the relative expression levels of “core” housekeeping genes under both growth conditions, we identified 166 genes that are differentially-expressed by L. interrogans in vivo. Our analyses highlight physiological aspects of host adaptation by leptospires relating to heme uptake and utilization. We also identified 11 novel non-coding transcripts that are candidate small regulatory RNAs. The DMC model provides a facile system for studying the transcriptional and antigenic changes associated with mammalian host-adaption, selection of targets for mutagenesis, and the identification of previously unrecognized virulence determinants.

Leptospirosis, a global disease caused by the unusual bacterium Leptospira, is transmitted from animals to humans. Pathogenic species of Leptospira are excreted in urine from infected animals and can continue to survive in suitable environments before coming into contact with a new reservoir or accidental host. Leptospires have an inherent ability to survive a wide range of conditions encountered in nature during transmission and within mammals. However, we know very little about the regulatory pathways and gene products that promote mammalian host adaptation and enable leptospires to establish infection. In this study, we used a novel system whereby leptospires are cultivated in dialysis membrane chambers implanted into the peritoneal cavities of rats to compare the gene expression profiles of mammalian host-adapted and in vitro-cultivated organisms. In addition to providing a facile system for studying the transcriptional and physiologic changes leptospires undergo during mammalian infection, our data provide a rational basis for selecting new targets for mutagenesis.

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.