RNA dynamics in aging bacterial spores.

Upon starvation, the bacterium Bacillus subtilis enters the process of sporulation, lasting several hours and culminating in formation of a spore, the most resilient cell type known. We show that a few days following sporulation, the RNA profile of spores is highly dynamic. In aging spores incubated at high temperatures, RNA content is globally decreased by degradation over several days. This degradation might be a strategy utilized by the spore to facilitate its dormancy. However, spores kept at low temperature exhibit a different RNA profile with evidence supporting transcription. Further, we demonstrate that germination is affected by spore age, incubation temperature, and RNA state, implying that spores can acquire dissimilar characteristics at a time they are considered dormant. We propose that, in contrast to current thinking, entering dormancy lasts a few days, during which spores are affected by the environment and undergo corresponding molecular changes influencing their emergence from quiescence.

Bacterial RNA Biology on a Genome Scale.

Bacteria are an exceedingly diverse group of organisms whose molecular exploration is experiencing a renaissance. While the classical view of bacterial gene expression was relatively simple, the emerging view is more complex, encompassing extensive post-transcriptional control involving riboswitches, RNA thermometers, and regulatory small RNAs (sRNAs) associated with the RNA-binding proteins CsrA, Hfq, and ProQ, as well as CRISPR/Cas systems that are programmed by RNAs. Moreover, increasing interest in members of the human microbiota and environmental microbial communities has highlighted the importance of understudied bacterial species with largely unknown transcriptome structures and RNA-based control mechanisms. Collectively, this creates a need for global RNA biology approaches that can rapidly and comprehensively analyze the RNA composition of a bacterium of interest. We review such approaches with a focus on RNA-seq as a versatile tool to investigate the different layers of gene expression in which RNA is made, processed, regulated, modified, translated, and turned over.

Rfam 14: expanded coverage of metagenomic, viral and microRNA families.

Rfam is a database of RNA families where each of the 3444 families is represented by a multiple sequence alignment of known RNA sequences and a covariance model that can be used to search for additional members of the family. Recent developments have involved expert collaborations to improve the quality and coverage of Rfam data, focusing on microRNAs, viral and bacterial RNAs. We have completed the first phase of synchronising microRNA families in Rfam and miRBase, creating 356 new Rfam families and updating 40. We established a procedure for comprehensive annotation of viral RNA families starting with Flavivirus and Coronaviridae RNAs. We have also increased the coverage of bacterial and metagenome-based RNA families from the ZWD database. These developments have enabled a significant growth of the database, with the addition of 759 new families in Rfam 14. To facilitate further community contribution to Rfam, expert users are now able to build and submit new families using the newly developed Rfam Cloud family curation system. New Rfam website features include a new sequence similarity search powered by RNAcentral, as well as search and visualisation of families with pseudoknots. Rfam is freely available at https://rfam.org.

Regulation of bacterial metabolism by small RNAs using diverse mechanisms.

Bacteria live in many dynamic environments with alternating cycles of feast or famine that have resulted in the evolution of mechanisms to quickly alter their metabolic capabilities. Such alterations often involve complex regulatory networks that modulate expression of genes involved in nutrient uptake and metabolism. A great number of protein regulators of metabolism have been characterized in depth. However, our ever-increasing understanding of the roles played by RNA regulators has revealed far greater complexity to regulation of metabolism in bacteria. Here, we review the mechanisms and functions of selected bacterial RNA regulators and discuss their importance in modulating nutrient uptake as well as primary and secondary metabolic pathways.

PresRAT: a server for identification of bacterial small-RNA sequences and their targets with probable binding region.

Bacterial small-RNA (sRNA) sequences are functional RNAs, which play an important role in regulating the expression of a diverse class of genes. It is thus critical to identify such sRNA sequences and their probable mRNA targets. Here, we discuss new procedures to identify and characterize sRNA and their targets via the introduction of an integrated online platform 'PresRAT'. PresRAT uses the primary and secondary structural attributes of sRNA sequences to predict sRNA from a given sequence or bacterial genome. PresRAT also finds probable target mRNAs of sRNA sequences from a given bacterial chromosome and further concentrates on the identification of the probable sRNA-mRNA binding regions. Using PresRAT, we have identified a total of 66,209 potential sRNA sequences from 292 bacterial genomes and 2247 potential targets from 13 bacterial genomes. We have also implemented a protocol to build and refine 3D models of sRNA and sRNA-mRNA duplex regions and generated 3D models of 50 known sRNAs and 81 sRNA-mRNA duplexes using this platform. Along with the server part, PresRAT also contains a database section, which enlists the predicted sRNA sequences, sRNA targets, and their corresponding 3D models with structural dynamics information.

Synthetase of the methyl donor S-adenosylmethionine from nitrogen-fixing α-rhizobia can bind functionally diverse RNA species.

Function of bacterial small non-coding RNAs (sRNAs) and overall RNA metabolism is largely shaped by a vast diversity of RNA-protein interactions. However, in non-model bacteria with defined non-coding transcriptomes the sRNA interactome remains almost unexplored. We used affinity chromatography to capture proteins associated in vivo with MS2-tagged trans-sRNAs that regulate nutrient uptake (AbcR2 and NfeR1) and cell cycle (EcpR1) mRNAs by antisense-based translational inhibition in the nitrogen-fixing α-rhizobia Sinorhizobium meliloti. The three proteomes were rather distinct, with that of EcpR1 particularly enriched in cell cycle-related enzymes, whilst sharing several transcription/translation-related proteins recurrently identified associated with sRNAs. Strikingly, MetK, the synthetase of the major methyl donor S-adenosylmethionine, was reliably recovered as a binding partner of the three sRNAs, which reciprocally co-immunoprecipitated with a FLAG-tagged MetK variant. Induced (over)expression of the trans-sRNAs and MetK depletion did not influence canonical riboregulatory traits, `for example, protein titration or sRNA stability, respectively. An in vitro filter assay confirmed binding of AbcR2, NfeR1 and EcpR1 to MetK and further revealed interaction of the protein with other non-coding and coding transcripts but not with the 5S rRNA. These findings uncover a broad specificity for RNA binding as an unprecedented feature of this housekeeping prokaryotic enzyme.

APERO: a genome-wide approach for identifying bacterial small RNAs from RNA-Seq data.

Small non-coding RNAs (sRNAs) regulate numerous cellular processes in all domains of life. Several approaches have been developed to identify them from RNA-seq data, which are efficient for eukaryotic sRNAs but remain inaccurate for the longer and highly structured bacterial sRNAs. We present APERO, a new algorithm to detect small transcripts from paired-end bacterial RNA-seq data. In contrast to previous approaches that start from the read coverage distribution, APERO analyzes boundaries of individual sequenced fragments to infer the 5' and 3' ends of all transcripts. Since sRNAs are about the same size as individual fragments (50-350 nucleotides), this algorithm provides a significantly higher accuracy and robustness, e.g., with respect to spontaneous internal breaking sites. To demonstrate this improvement, we develop a comparative assessment on datasets from Escherichia coli and Salmonella enterica, based on experimentally validated sRNAs. We also identify the small transcript repertoire of Dickeya dadantii including putative intergenic RNAs, 5' UTR or 3' UTR-derived RNA products and antisense RNAs. Comparisons to annotations as well as RACE-PCR experimental data confirm the precision of the detected transcripts. Altogether, APERO outperforms all existing methods in terms of sRNA detection and boundary precision, which is crucial for comprehensive genome annotations. It is freely available as an open source R package on https://github.com/Simon-Leonard/APERO.

Prediction of novel non-coding RNAs relevant for the growth of Pseudomonas putida in a bioreactor.

Pseudomonas putida is a micro-organism with great potential for industry due to its stress-endurance traits and easy manipulation of the metabolism. However, optimization is still required to improve production yields. In the last years, manipulation of bacterial small non-coding RNAs (ncRNAs) has been recognized as an effective tool to improve the production of industrial compounds. So far, very few ncRNAs are annotated in P. putida beyond the generally conserved. In the present study, P. putida was cultivated in a two-compartment scale-down bioreactor that simulates large-scale industrial bioreactors. We performed RNA-Seq of samples collected at distinct locations and time-points to predict novel and potentially important ncRNAs for the adaptation of P. putida to bioreactor stress conditions. Instead of using a purely genomic approach, we have rather identified regions of putative ncRNAs with high expression levels using two different programs (Artemis and sRNA detect). Only the regions identified with both approaches were considered for further analysis and, in total, 725 novel ncRNAs were predicted. We also found that their expression was not constant throughout the bioreactor, showing different patterns of expression with time and position. This is the first work focusing on the ncRNAs whose expression is triggered in a bioreactor environment. This information is of great importance for industry, since it provides possible targets to engineer more effective P. putida strains for large-scale production.

Coupled catabolism and anabolism in autocatalytic RNA sets.

The ability to process molecules available in the environment into useable building blocks characterizes catabolism in contemporary cells and was probably critical for the initiation of life. Here we show that a catabolic process in collectively autocatalytic sets of RNAs allows diversified substrates to be assimilated. We modify fragments of the Azoarcus group I intron and find that the system is able to restore the original native fragments by a multi-step reaction pathway. This allows in turn the formation of catalysts by an anabolic process, eventually leading to the accumulation of ribozymes. These results demonstrate that rudimentary self-reproducing RNA systems based on recombination possess an inherent capacity to assimilate an expanded repertoire of chemical resources and suggest that coupled catabolism and anabolism could have arisen at a very early stage in primordial living systems.

Deep genome annotation of the opportunistic human pathogen Streptococcus pneumoniae D39.

A precise understanding of the genomic organization into transcriptional units and their regulation is essential for our comprehension of opportunistic human pathogens and how they cause disease. Using single-molecule real-time (PacBio) sequencing we unambiguously determined the genome sequence of Streptococcus pneumoniae strain D39 and revealed several inversions previously undetected by short-read sequencing. Significantly, a chromosomal inversion results in antigenic variation of PhtD, an important surface-exposed virulence factor. We generated a new genome annotation using automated tools, followed by manual curation, reflecting the current knowledge in the field. By combining sequence-driven terminator prediction, deep paired-end transcriptome sequencing and enrichment of primary transcripts by Cappable-Seq, we mapped 1015 transcriptional start sites and 748 termination sites. We show that the pneumococcal transcriptional landscape is complex and includes many secondary, antisense and internal promoters. Using this new genomic map, we identified several new small RNAs (sRNAs), RNA switches (including sixteen previously misidentified as sRNAs), and antisense RNAs. In total, we annotated 89 new protein-encoding genes, 34 sRNAs and 165 pseudogenes, bringing the S. pneumoniae D39 repertoire to 2146 genetic elements. We report operon structures and observed that 9% of operons are leaderless. The genome data are accessible in an online resource called PneumoBrowse (https://veeninglab.com/pneumobrowse) providing one of the most complete inventories of a bacterial genome to date. PneumoBrowse will accelerate pneumococcal research and the development of new prevention and treatment strategies.

Genetic Regulation of Streptococci by Small RNAs.

Streptococcal species constitute a large group of commensal and pathogenic Gram-positive bacteria that exist in a wide variety of habitats. The family of small RNAs is typically ranged in size from 50 to 300 nucleotides, and acts as regulators in bacteria. The last decade has witnessed the increasing findings of small RNAs (sRNAs), which play important regulatory roles in the variety of biological processes in streptococci. In this review, we summarized the recent achievements in the identification of streptococcal sRNAs, mainly in Streptococcus pyogenes and Streptococcus pneumoniae. In addition, we particularly focused on the functions that sRNAs exert in the regulatory networks of both phenotypical traits and pathogenicity. The fact that sRNAs act as a critical fine-tuning regulator of streptococci may not only reveal in-depth mechanisms of bacterial post-transcriptional regulations in response to environmental perturbance, but also provide promising approaches to the better management of streptococcal infections.

Prospects for riboswitch discovery and analysis.

An expanding number of metabolite-binding riboswitch classes are being discovered in the noncoding portions of bacterial genomes. Findings over the last decade indicate that bacteria commonly use these RNA genetic elements as regulators of metabolic pathways and as mediators of changes in cell physiology. Some riboswitches are surprisingly complex, and they rival protein factors in their structural and functional sophistication. Each new riboswitch discovery expands our knowledge of the biochemical capabilities of RNA, and some give rise to new questions that require additional study to be addressed. Some of the greatest prospects for riboswitch research and some of the more interesting mysteries are discussed in this review.

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

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

The skin microbiome of cow-nose rays (Rhinoptera bonasus) in an aquarium touch-tank exhibit.

Public aquaria offer numerous educational opportunities for visitors while touch-tank exhibits offer guests the ability to directly interact with marine life via physical contact. Despite the popularity of touch-tanks, there is a paucity of research about animal health in these exhibits and, in particular, there is little research on the microbial communities in these highly interactive exhibits. Microbial community structure can have implications for both host health and habitat function. To better understand the microbiome of a touch-tank we used high-throughput sequencing of the 16S rRNA gene to analyze the microbial community on the dorsal and ventral surfaces of cow-nose rays (Rhinoptera bonasus) as well as their environment in a frequently visited touch-tank exhibit at the New England Aquarium. Our analyses revealed a distinct microbial community associated with the skin of the ray that had lower diversity than the surrounding habitat. The ray skin was dominated by three orders: Burkholderiales (∼55%), Flavobacteriales (∼19%), and Pseudomonadales (∼12%), taxonomic groups commonly associated with other fish species. Our results provide a survey of ray-associated bacterial communities in a touch-tank environment, thereby laying the foundation for future studies examining the role of potential challenges to ray microbiota and their associated health.

Small RNA Regulation of TolC, the Outer Membrane Component of Bacterial Multidrug Transporters.

UNLABELLED: Bacteria use multidrug efflux pumps to export drugs and toxic compounds out of the cell. One of the most important efflux pumps in Escherichia coli is the AcrAB-TolC system. Small regulatory RNAs (sRNAs) are known to be major posttranscriptional regulators that can enhance or repress translation by binding to the 5' untranslated region (UTR) of mRNA targets with the help of a chaperone protein, Hfq. In this study, we investigated the expression of acrA, acrB, and tolC translational fusions using 27 Hfq-dependent sRNAs overexpressed from plasmids. No significant sRNA regulation of acrA or acrB was detected. SdsR (also known as RyeB), an abundant and well-conserved stationary-phase sRNA, was found to repress the expression of tolC, the gene encoding the outer membrane protein of many multidrug resistance efflux pumps. This repression was shown to be by direct base pairing occurring upstream from the ribosomal binding site. SdsR overexpression and its regulation of tolC were found to reduce resistance to novobiocin and crystal violet. Our results suggest that additional targets for SdsR exist that contribute to increased antibiotic sensitivity and reduced biofilm formation. In an effort to identify phenotypes associated with single-copy SdsR and its regulation of tolC, the effect of a deletion of sdsR or mutations in tolC that should block SdsR pairing were investigated using a Biolog phenotypic microarray. However, no significant phenotypes were identified. Therefore, SdsR appears to modulate rather than act as a major regulator of its targets. IMPORTANCE: AcrAB-TolC is a major efflux pump present in E. coli and Gram-negative bacteria used to export toxic compounds; the pump confers resistance to many antibiotics of unrelated classes. In this study, we found that SdsR, a small RNA expressed in stationary phase, repressed the expression of tolC, resulting in increased sensitivity to some antibiotics. This extends the findings of previous studies showing that sRNAs contribute to the regulation of many outer membrane proteins; manipulating or enhancing their action might help in sensitizing bacteria to antibiotics.

Comparative genomics boosts target prediction for bacterial small RNAs.

Small RNAs (sRNAs) constitute a large and heterogeneous class of bacterial gene expression regulators. Much like eukaryotic microRNAs, these sRNAs typically target multiple mRNAs through short seed pairing, thereby acting as global posttranscriptional regulators. In some bacteria, evidence for hundreds to possibly more than 1,000 different sRNAs has been obtained by transcriptome sequencing. However, the experimental identification of possible targets and, therefore, their confirmation as functional regulators of gene expression has remained laborious. Here, we present a strategy that integrates phylogenetic information to predict sRNA targets at the genomic scale and reconstructs regulatory networks upon functional enrichment and network analysis (CopraRNA, for Comparative Prediction Algorithm for sRNA Targets). Furthermore, CopraRNA precisely predicts the sRNA domains for target recognition and interaction. When applied to several model sRNAs, CopraRNA revealed additional targets and functions for the sRNAs CyaR, FnrS, RybB, RyhB, SgrS, and Spot42. Moreover, the mRNAs gdhA, lrp, marA, nagZ, ptsI, sdhA, and yobF-cspC were suggested as regulatory hubs targeted by up to seven different sRNAs. The verification of many previously undetected targets by CopraRNA, even for extensively investigated sRNAs, demonstrates its advantages and shows that CopraRNA-based analyses can compete with experimental target prediction approaches. A Web interface allows high-confidence target prediction and efficient classification of bacterial sRNAs.

Robust identification of noncoding RNA from transcriptomes requires phylogenetically-informed sampling.

Noncoding RNAs are integral to a wide range of biological processes, including translation, gene regulation, host-pathogen interactions and environmental sensing. While genomics is now a mature field, our capacity to identify noncoding RNA elements in bacterial and archaeal genomes is hampered by the difficulty of de novo identification. The emergence of new technologies for characterizing transcriptome outputs, notably RNA-seq, are improving noncoding RNA identification and expression quantification. However, a major challenge is to robustly distinguish functional outputs from transcriptional noise. To establish whether annotation of existing transcriptome data has effectively captured all functional outputs, we analysed over 400 publicly available RNA-seq datasets spanning 37 different Archaea and Bacteria. Using comparative tools, we identify close to a thousand highly-expressed candidate noncoding RNAs. However, our analyses reveal that capacity to identify noncoding RNA outputs is strongly dependent on phylogenetic sampling. Surprisingly, and in stark contrast to protein-coding genes, the phylogenetic window for effective use of comparative methods is perversely narrow: aggregating public datasets only produced one phylogenetic cluster where these tools could be used to robustly separate unannotated noncoding RNAs from a null hypothesis of transcriptional noise. Our results show that for the full potential of transcriptomics data to be realized, a change in experimental design is paramount: effective transcriptomics requires phylogeny-aware sampling.

CRISPRmap: an automated classification of repeat conservation in prokaryotic adaptive immune systems.

Central to Clustered Regularly Interspaced Short Palindromic Repeat (CRISPR)-Cas systems are repeated RNA sequences that serve as Cas-protein-binding templates. Classification is based on the architectural composition of associated Cas proteins, considering repeat evolution is essential to complete the picture. We compiled the largest data set of CRISPRs to date, performed comprehensive, independent clustering analyses and identified a novel set of 40 conserved sequence families and 33 potential structure motifs for Cas-endoribonucleases with some distinct conservation patterns. Evolutionary relationships are presented as a hierarchical map of sequence and structure similarities for both a quick and detailed insight into the diversity of CRISPR-Cas systems. In a comparison with Cas-subtypes, I-C, I-E, I-F and type II were strongly coupled and the remaining type I and type III subtypes were loosely coupled to repeat and Cas1 evolution, respectively. Subtypes with a strong link to CRISPR evolution were almost exclusive to bacteria; nevertheless, we identified rare examples of potential horizontal transfer of I-C and I-E systems into archaeal organisms. Our easy-to-use web server provides an automated assignment of newly sequenced CRISPRs to our classification system and enables more informed choices on future hypotheses in CRISPR-Cas research: http://rna.informatik.uni-freiburg.de/CRISPRmap.

Most RNAs regulating ribosomal protein biosynthesis in Escherichia coli are narrowly distributed to Gammaproteobacteria.

In Escherichia coli, 12 distinct RNA structures within the transcripts encoding ribosomal proteins interact with specific ribosomal proteins to allow autogenous regulation of expression from large multi-gene operons, thus coordinating ribosomal protein biosynthesis across multiple operons. However, these RNA structures are typically not represented in the RNA Families Database or annotated in genomic sequences databases, and their phylogenetic distribution is largely unknown. To investigate the extent to which these RNA structures are conserved across eubacterial phyla, we created multiple sequence alignments representing 10 of these messenger RNA (mRNA) structures in E. coli. We find that while three RNA structures are widely distributed across many phyla of bacteria, seven of the RNAs are narrowly distributed to a few orders of Gammaproteobacteria. To experimentally validate our computational predictions, we biochemically confirmed dual L1-binding sites identified in many Firmicute species. This work reveals that RNA-based regulation of ribosomal protein biosynthesis is used in nearly all eubacterial phyla, but the specific RNA structures that regulate ribosomal protein biosynthesis in E. coli are narrowly distributed. These results highlight the limits of our knowledge regarding ribosomal protein biosynthesis regulation outside of E. coli, and the potential for alternative RNA structures responsible for regulating ribosomal proteins in other eubacteria.

Dissemination of 6S RNA among bacteria.

6S RNA is a highly abundant small non-coding RNA widely spread among diverse bacterial groups. By competing with DNA promoters for binding to RNA polymerase (RNAP), the RNA regulates transcription on a global scale. RNAP produces small product RNAs derived from 6S RNA as template, which rearranges the 6S RNA structure leading to dissociation of 6S RNA:RNAP complexes. Although 6S RNA has been experimentally analysed in detail for some species, such as Escherichia coli and Bacillus subtilis, and was computationally predicted in many diverse bacteria, a complete and up-to-date overview of the distribution among all bacteria is missing. In this study we searched with new methods for 6S RNA genes in all currently available bacterial genomes. We ended up with a set of 1,750 6S RNA genes, of which 1,367 are novel and bona fide, distributed among 1,610 bacteria, and had a few tentative candidates among the remaining 510 assembled bacterial genomes accessible. We were able to confirm two tentative candidates by Northern blot analysis. We extended 6S RNA genes of the Flavobacteriia significantly in length compared to the present Rfam entry. We describe multiple homologs of 6S RNAs (including split 6S RNA genes) and performed a detailed synteny analysis.