sRNAdb: a small non-coding RNA database for gram-positive bacteria

Agnodice: indexing experimentally supported bacterial sRNA-RNA interactions

In the last decade, the immense growth in the field of bacterial small RNAs (sRNAs), along with the biotechnological breakthroughs in Deep Sequencing permitted the deeper understanding of sRNA-RNA interactions. However, microbiology is currently lacking a thoroughly curated collection of this rapidly expanding universe. We present Agnodice (https://dianalab.e-ce.uth.gr/agnodice), our effort to systematically catalog and annotate experimentally supported bacterial sRNA-RNA interactions. Agnodice, for the first time, incorporates thousands of bacterial sRNA-RNA interactions derived from a diverse set of experimental methodologies including state-of-the-art Deep Sequencing interactome identification techniques. It comprises 39,600 entries which are annotated at strain-level resolution and pertain to 399 sRNAs and 12,137 target RNAs identified in 71 bacterial strains. The database content is exclusively experimentally supported, incorporating interactions derived via low yield as well as state-of-the-art high-throughput methods. The entire content of the database is freely accessible and can be directly downloaded for further analysis. Agnodice will serve as a valuable source, enabling microbiologists to form novel hypotheses, design/identify novel sRNA-based drug targets, and explore the therapeutic potential of microbiomes from the perspective of small regulatory RNAs.IMPORTANCEAgnodice (https://dianalab.e-ce.uth.gr/agnodice) is an effort to systematically catalog and annotate experimentally supported bacterial small RNA (sRNA)-RNA interactions. Agnodice, for the first time, incorporates thousands of bacterial sRNA-RNA interactions derived from a diverse set of experimental methodologies including state-of-the-art Next Generation Sequencing interactome identification techniques.

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.

Small RNAs beyond Model Organisms: Have We Only Scratched the Surface?

Small RNAs (sRNAs) are essential regulators in the adaptation of bacteria to environmental changes and act by binding targeted mRNAs through base complementarity. Approximately 550 distinct families of sRNAs have been identified since their initial characterization in the 1980s, accelerated by the emergence of RNA-sequencing. Small RNAs are found in a wide range of bacterial phyla, but they are more prominent in highly researched model organisms compared to the rest of the sequenced bacteria. Indeed, Escherichia coli and Salmonella enterica contain the highest number of sRNAs, with 98 and 118, respectively, with Enterobacteriaceae encoding 145 distinct sRNAs, while other bacteria families have only seven sRNAs on average. Although the past years brought major advances in research on sRNAs, we have perhaps only scratched the surface, even more so considering RNA annotations trail behind gene annotations. A distinctive trend can be observed for genes, whereby their number increases with genome size, but this is not observable for RNAs, although they would be expected to follow the same trend. In this perspective, we aimed at establishing a more accurate representation of the occurrence of sRNAs in bacteria, emphasizing the potential for novel sRNA discoveries.

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.

Noncoding RNAs Databases: Current Status and Trends

One of the most important resources for researchers of noncoding RNAs is the information available in public databases spread over the internet. However, the effective exploration of this data can represent a daunting task, given the large amount of databases available and the variety of stored data. This chapter describes a classification of databases based on information source, type of RNA, source organisms, data formats, and the mechanisms for information retrieval, detailing the relevance of each of these classifications and its usability by researchers. This classification is used to update a 2012 review, indexing now more than 229 public databases. This review will include an assessment of the new trends for ncRNA research based on the information that is being offered by the databases. Additionally, we will expand the previous analysis focusing on the usability and application of these databases in pathogen and disease research. Finally, this chapter will analyze how currently available database schemas can help the development of new and improved web resources.

Linking common non-coding RNAs of human lung cancer and M. tuberculosis

Lung cancer and pulmonary tuberculosis caused by Mycobacterium are two major causes of deaths worldwide. Tuberculosis linked lung cancer is known. However, the precise molecular mechanism of Mycobacterium associated increased risk of lung cancer is not understood. We report 45 common human miRNAs deregulated in both pulmonary tuberculosis and lung cancer. We show that sRNA_1096 and sRNA_1414 from M. tuberculosis have sequence homology with human mir-21. Hence, the potential role of these three small non-coding RNAs in rifampicin resistance in pulmonary tuberculosis is implied. Further, the linking of sRNA_1096 and sRNA_1414 from M. tuberculosis with the host lung tumorigenesis is inferred. Nonetheless, further analysis and validation is required to associate these three non-coding RNAs with Mycobacterium associated increased risk of lung cancer.

Listeriomics: an Interactive Web Platform for Systems Biology of Listeria

In the last decades, Listeria has become a key model organism for the study of host-pathogen interactions, noncoding RNA regulation, and bacterial adaptation to stress. To study these mechanisms, several genomics, transcriptomics, and proteomics data sets have been produced. We have developed Listeriomics, an interactive web platform to browse and correlate these heterogeneous sources of information. Our website will allow listeriologists and microbiologists to decipher key regulation mechanism by using a systems biology approach.

As for many model organisms, the amount of Listeria omics data produced has recently increased exponentially. There are now >80 published complete Listeria genomes, around 350 different transcriptomic data sets, and 25 proteomic data sets available. The analysis of these data sets through a systems biology approach and the generation of tools for biologists to browse these various data are a challenge for bioinformaticians. We have developed a web-based platform, named Listeriomics, that integrates different tools for omics data analyses, i.e., (i) an interactive genome viewer to display gene expression arrays, tiling arrays, and sequencing data sets along with proteomics and genomics data sets; (ii) an expression and protein atlas that connects every gene, small RNA, antisense RNA, or protein with the most relevant omics data; (iii) a specific tool for exploring protein conservation through the Listeria phylogenomic tree; and (iv) a coexpression network tool for the discovery of potential new regulations. Our platform integrates all the complete Listeria species genomes, transcriptomes, and proteomes published to date. This website allows navigation among all these data sets with enriched metadata in a user-friendly format and can be used as a central database for systems biology analysis.

IMPORTANCE In the last decades, Listeria has become a key model organism for the study of host-pathogen interactions, noncoding RNA regulation, and bacterial adaptation to stress. To study these mechanisms, several genomics, transcriptomics, and proteomics data sets have been produced. We have developed Listeriomics, an interactive web platform to browse and correlate these heterogeneous sources of information. Our website will allow listeriologists and microbiologists to decipher key regulation mechanism by using a systems biology approach.

Two novel members of the LhrC family of small RNAs in Listeria monocytogenes with overlapping regulatory functions but distinctive expression profiles

Multicopy small RNAs (sRNAs) have gained recognition as an important feature of bacterial gene regulation. In the human pathogen Listeria monocytogenes, 5 homologous sRNAs, called LhrC1-5, control gene expression by base pairing to target mRNAs though 3 conserved UCCC motifs common to all 5 LhrCs. We show here that the sRNAs Rli22 and Rli33-1 are structurally and functionally related to LhrC1-5, expanding the LhrC family to 7 members, which makes it the largest multicopy sRNA family reported so far. Rli22 and Rli33-1 both contain 2 UCCC motifs important for post-transcriptional repression of 3 LhrC target genes. One such target, oppA, encodes a virulence-associated oligo-peptide binding protein. Like LhrC1-5, Rli22 and Rli33-1 employ their UCCC motifs to recognize the Shine-Dalgarno region of oppA mRNA and prevent formation of the ribosomal complex, demonstrating that the 7 sRNAs act in a functionally redundant manner. However, differential expression profiles of the sRNAs under infection-relevant conditions suggest that they might also possess non-overlapping functions. Collectively, this makes the LhrC family a unique case for studying the purpose of sRNA multiplicity in the context of bacterial virulence.

sRNATarBase 3.0: an updated database for sRNA-target interactions in bacteria

Bacterial sRNAs are a class of small regulatory RNAs of about 40–500 nt in length; they play multiple biological roles through binding to their target mRNAs or proteins. Therefore, elucidating sRNA targets is very important. However, only targets of a few sRNAs have been described. To facilitate sRNA functional studies such as developing sRNA target prediction models, we updated the sRNATarBase database, which was initially developed in 2010. The new version (recently moved to http://ccb1.bmi.ac.cn/srnatarbase/) contains 771 sRNA-target entries manually collected from 213 papers, and 23 290 and 11 750 predicted targets from sRNATarget and sTarPicker, respectively. Among the 771 entries, 475 and 17 were involved in validated sRNA–mRNA and sRNA–protein interactions, respectively, while 279 had no reported interactions. We also presented detailed information for 316 binding regions of sRNA-target mRNA interactions and related mutation experiments, as well as new features, including NCBI sequence viewer, sRNA regulatory network, target prediction-based GO and pathway annotations, and error report system. The new version provides a comprehensive annotation of validated sRNA-target interactions, and will be a useful resource for bacterial sRNA studies.

SRD: a Staphylococcus regulatory RNA database

An overflow of regulatory RNAs (sRNAs) was identified in a wide range of bacteria. We designed and implemented a new resource for the hundreds of sRNAs identified in Staphylococci, with primary focus on the human pathogen Staphylococcus aureus. The "Staphylococcal Regulatory RNA Database" (SRD, http://srd.genouest.org/) compiled all published data in a single interface including genetic locations, sequences and other features. SRD proposes novel and simplified identifiers for Staphylococcal regulatory RNAs (srn) based on the sRNA's genetic location in S. aureus strain N315 which served as a reference. From a set of 894 sequences and after an in-depth cleaning, SRD provides a list of 575 srn exempt of redundant sequences. For each sRNA, their experimental support(s) is provided, allowing the user to individually assess their validity and significance. RNA-seq analysis performed on strains N315, NCTC8325, and Newman allowed us to provide further details, upgrade the initial annotation, and identified 159 RNA-seq independent transcribed sRNAs. The lists of 575 and 159 sRNAs sequences were used to predict the number and location of srns in 18 S. aureus strains and 10 other Staphylococci. A comparison of the srn contents within 32 Staphylococcal genomes revealed a poor conservation between species. In addition, sRNA structure predictions obtained with MFold are accessible. A BLAST server and the intaRNA program, which is dedicated to target prediction, were implemented. SRD is the first sRNA database centered on a genus; it is a user-friendly and scalable device with the possibility to submit new sequences that should spread in the literature.

Ultra deep sequencing of Listeria monocytogenes sRNA transcriptome revealed new antisense RNAs

Listeria monocytogenes, a gram-positive pathogen, and causative agent of listeriosis, has become a widely used model organism for intracellular infections. Recent studies have identified small non-coding RNAs (sRNAs) as important factors for regulating gene expression and pathogenicity of L. monocytogenes. Increased speed and reduced costs of high throughput sequencing (HTS) techniques have made RNA sequencing (RNA-Seq) the state-of-the-art method to study bacterial transcriptomes. We created a large transcriptome dataset of L. monocytogenes containing a total of 21 million reads, using the SOLiD sequencing technology. The dataset contained cDNA sequences generated from L. monocytogenes RNA collected under intracellular and extracellular condition and additionally was size fractioned into three different size ranges from <40 nt, 40–150 nt and >150 nt. We report here, the identification of nine new sRNAs candidates of L. monocytogenes and a reevaluation of known sRNAs of L. monocytogenes EGD-e. Automatic comparison to known sRNAs revealed a high recovery rate of 55%, which was increased to 90% by manual revision of the data. Moreover, thorough classification of known sRNAs shed further light on their possible biological functions. Interestingly among the newly identified sRNA candidates are antisense RNAs (asRNAs) associated to the housekeeping genes purA, fumC and pgi and potentially their regulation, emphasizing the significance of sRNAs for metabolic adaptation in L. monocytogenes.

Comprehensive discovery and characterization of small RNAs in Corynebacterium glutamicum ATCC 13032

Background

Recent discoveries on bacterial transcriptomes gave evidence that small RNAs (sRNAs) have important regulatory roles in prokaryotic cells. Modern high-throughput sequencing approaches (RNA-Seq) enable the most detailed view on transcriptomes offering an unmatched comprehensiveness and single-base resolution. Whole transcriptome data obtained by RNA-Seq can be used to detect and characterize all transcript species, including small RNAs. Here, we describe an RNA-Seq approach for comprehensive detection and characterization of small RNAs from Corynebacterium glutamicum, an actinobacterium of high industrial relevance and model organism for medically important Corynebacterianeae, such as C. diphtheriae and Mycobacterium tuberculosis.

Results

In our RNA-Seq approach, total RNA from C. glutamicum ATCC 13032 was prepared from cultures grown in minimal medium at exponential growth or challenged by physical (heat shock, cold shock) or by chemical stresses (diamide, H₂O₂, NaCl) at this time point. Total RNA samples were pooled and sequencing libraries were prepared from the isolated small RNA fraction. High throughput short read sequencing and mapping yielded over 800 sRNA genes. By determining their 5′- and 3′-ends and inspection of their locations, these potential sRNA genes were classified into UTRs of mRNAs (316), cis-antisense sRNAs (543), and trans-encoded sRNAs (262). For 77 of trans-encoded sRNAs significant sequence and secondary structure conservation was found by a computational approach using a whole genome alignment with the closely related species C. efficiens YS-314 and C. diphtheriae NCTC 13129. Three selected trans-encoded sRNAs were characterized by Northern blot analysis and stress-specific transcript patterns were found.

Conclusions

The study showed comparable numbers of sRNAs known from genome-wide surveys in other bacteria. In detail, our results give deep insight into the comprehensive equipment of sRNAs in C. glutamicum and provide a sound basis for further studies concerning the functions of these sRNAs.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-14-714) contains supplementary material, which is available to authorized users.

Reassessment of the Listeria monocytogenes pan-genome reveals dynamic integration hotspots and mobile genetic elements as major components of the accessory genome

Background

Listeria monocytogenes is an important food-borne pathogen and model organism for host-pathogen interaction, thus representing an invaluable target considering research on the forces governing the evolution of such microbes. The diversity of this species has not been exhaustively explored yet, as previous efforts have focused on analyses of serotypes primarily implicated in human listeriosis. We conducted complete genome sequencing of 11 strains employing 454 GS FLX technology, thereby achieving full coverage of all serotypes including the first complete strains of serotypes 1/2b, 3c, 3b, 4c, 4d, and 4e. These were comparatively analyzed in conjunction with publicly available data and assessed for pathogenicity in the Galleria mellonella insect model.

Results

The species pan-genome of L. monocytogenes is highly stable but open, suggesting an ability to adapt to new niches by generating or including new genetic information. The majority of gene-scale differences represented by the accessory genome resulted from nine hyper variable hotspots, a similar number of different prophages, three transposons (Tn916, Tn554, IS3-like), and two mobilizable islands. Only a subset of strains showed CRISPR/Cas bacteriophage resistance systems of different subtypes, suggesting a supplementary function in maintenance of chromosomal stability. Multiple phylogenetic branches of the genus Listeria imply long common histories of strains of each lineage as revealed by a SNP-based core genome tree highlighting the impact of small mutations for the evolution of species L. monocytogenes. Frequent loss or truncation of genes described to be vital for virulence or pathogenicity was confirmed as a recurring pattern, especially for strains belonging to lineages III and II. New candidate genes implicated in virulence function were predicted based on functional domains and phylogenetic distribution. A comparative analysis of small regulatory RNA candidates supports observations of a differential distribution of trans-encoded RNA, hinting at a diverse range of adaptations and regulatory impact.

Conclusions

This study determined commonly occurring hyper variable hotspots and mobile elements as primary effectors of quantitative gene-scale evolution of species L. monocytogenes, while gene decay and SNPs seem to represent major factors influencing long-term evolution. The discovery of common and disparately distributed genes considering lineages, serogroups, serotypes and strains of species L. monocytogenes will assist in diagnostic, phylogenetic and functional research, supported by the comparative genomic GECO-LisDB analysis server (http://bioinfo.mikrobio.med.uni-giessen.de/geco2lisdb).

Common regulators of virulence in streptococci

Streptococcal species are a diverse group of bacteria which can be found in animals and humans. Their interactions with host organisms can vary from commensal to pathogenic. Many of the pathogenic species are causative agents of severe, invasive infections in their hosts, accounting for a high burden of morbidity and mortality, associated with high economic costs in industry and health care. Among them, Streptococcus pyogenes, Streptococcus agalactiae, Streptococcus pneumoniae, and Streptococcus suis are discussed here. An environmentally stimulated and tightly controlled expression of their virulence factors is of utmost importance for their pathogenic potential. Thus, the most universal and widespread regulators from the classes of stand-alone transcriptional regulators, two-component signal transduction systems (TCS), eukaryotic-like serine/threonine kinases, and small noncoding RNAs are the topic of this chapter. The regulatory levels are reviewed with respect to function, activity, and their role in pathogenesis. Understanding of and interfering with transcriptional regulation mechanisms and networks is a promising basis for the development of novel anti-infective therapies.