Predicting sRNAs and their targets in bacteria

Genomic basis of environmental adaptation in the widespread poly-extremophilic Exiguobacterium group

Delineating cohesive ecological units and determining the genetic basis for their environmental adaptation are among the most important objectives in microbiology. In the last decade, many studies have been devoted to characterizing the genetic diversity in microbial populations to address these issues. However, the impact of extreme environmental conditions, such as temperature and salinity, on microbial ecology and evolution remains unclear so far. In order to better understand the mechanisms of adaptation, we studied the (pan)genome of Exiguobacterium, a poly-extremophile bacterium able to grow in a wide range of environments, from permafrost to hot springs. To have the genome for all known Exiguobacterium type strains, we first sequenced those that were not yet available. Using a reverse-ecology approach, we showed how the integration of phylogenomic information, genomic features, gene and pathway enrichment data, regulatory element analyses, protein amino acid composition, and protein structure analyses of the entire Exiguobacterium pangenome allows to sharply delineate ecological units consisting of mesophilic, psychrophilic, halophilic-mesophilic, and halophilic-thermophilic ecotypes. This in-depth study clarified the genetic basis of the defined ecotypes and identified some key mechanisms driving the environmental adaptation to extreme environments. Our study points the way to organizing the vast microbial diversity into meaningful ecologically units, which, in turn, provides insight into how microbial communities adapt and respond to different environmental conditions in a changing world.

The Fate and Functionality of Alien tRNA Fragments in Culturing Medium and Cells of Escherichia coli

Numerous observations have supported the idea that various types of noncoding RNAs, including tRNA fragments (tRFs), are involved in communications between the host and its microbial community. The possibility of using their signaling function has stimulated the study of secreted RNAs, potentially involved in the interspecies interaction of bacteria. This work aimed at identifying such RNAs and characterizing their maturation during transport. We applied an approach that allowed us to detect oligoribonucleotides secreted by Prevotella copri (Segatella copri) or Rhodospirillum rubrum inside Escherichia coli cells. Four tRFs imported by E. coli cells co-cultured with these bacteria were obtained via chemical synthesis, and all of them affected the growth of E. coli. Their successive modifications in the culture medium and recipient cells were studied by high-throughput cDNA sequencing. Instead of the expected accidental exonucleolysis, in the milieu, we observed nonrandom cleavage by endonucleases continued in recipient cells. We also found intramolecular rearrangements of synthetic oligonucleotides, which may be considered traces of intermediate RNA circular isomerization. Using custom software, we estimated the frequency of such events in transcriptomes and secretomes of E. coli and observed surprising reproducibility in positions of such rare events, assuming the functionality of ring isoforms or their permuted derivatives in bacteria.

The Acinetobacter baumannii model can explain the role of small non-coding RNAs as potential mediators of host-pathogen interactions

Bacterial small RNAs (sRNAs) research has accelerated over the past decade, boosted by advances in RNA-seq technologies and methodologies for capturing both protein-RNA and RNA-RNA interactions. The emerging picture is that these regulatory sRNAs play important roles in controlling complex physiological processes and are required to survive the antimicrobial challenge. In recent years, the RNA content of OMVs/EVs has also gained increasing attention, particularly in the context of infection. Secreted RNAs from several bacterial pathogens have been characterized but the exact mechanisms promoting pathogenicity remain elusive. In this review, we briefly discuss how secreted sRNAs interact with targets in infected cells, thus representing a novel perspective of host cell manipulation during bacterial infection. During the last decade, Acinetobacter baumannii became clinically relevant emerging pathogens responsible for nosocomial and community-acquired infections. Therefore, we also summarize recent findings of regulation by sRNAs in A. baumannii and discuss how this emerging bacterium utilizes many of these sRNAs to adapt to its niche and become successful human pathogen.

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.

Advances in the Sensing and Treatment of Wound Biofilms

Wound biofilms represent a particularly challenging problem in modern medicine. They are increasingly antibiotic resistant and can prevent the healing of chronic wounds. However, current treatment and diagnostic options are hampered by the complexity of the biofilm environment. In this review, we present new chemical avenues in biofilm sensors and new materials to treat wound biofilms, offering promise for better detection, chemical specificity, and biocompatibility. We briefly discuss existing methods for biofilm detection and focus on novel, sensor-based approaches that show promise for early, accurate detection of biofilm formation on wound sites and that can be translated to point-of-care settings. We then discuss technologies inspired by new materials for efficient biofilm eradication. We focus on ultrasound-induced microbubbles and nanomaterials that can both penetrate the biofilm and simultaneously carry active antimicrobials and discuss the benefits of those approaches in comparison to conventional methods.

Advances in the Sensing and Treatment of Wound Biofilms

Wound biofilms represent a particularly challenging problem in modern medicine. They are increasingly antibiotic resistant and can prevent the healing of chronic wounds. However, current treatment and diagnostic options are hampered by the complexity of the biofilm environment. In this review, we present new chemical avenues in biofilm sensors and new materials to treat wound biofilms, offering promise for better detection, chemical specificity, and biocompatibility. We briefly discuss existing methods for biofilm detection and focus on novel, sensor‐based approaches that show promise for early, accurate detection of biofilm formation on wound sites and that can be translated to point‐of‐care settings. We then discuss technologies inspired by new materials for efficient biofilm eradication. We focus on ultrasound‐induced microbubbles and nanomaterials that can both penetrate the biofilm and simultaneously carry active antimicrobials and discuss the benefits of those approaches in comparison to conventional methods.

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.

Recent Research Advances in Small Regulatory RNAs in Streptococcus

Small non-coding RNAs (sRNAs) are a class of regulatory RNAs 20-500 nucleotides in length, which have recently been discovered in prokaryotic organisms. sRNAs are key regulators in many biological processes, such as sensing various environmental changes and regulating intracellular gene expression through binding target mRNAs or proteins. Bacterial sRNAs have recently been rapidly mined, thus providing new insights into the regulatory network of biological functions in prokaryotes. Although most bacterial sRNAs have been discovered and studied in Escherichia coli and other Gram-negative bacteria, sRNAs have increasingly been predicted and verified in Gram-positive bacteria in the past decade. The genus Streptococcus includes many commensal and pathogenic Gram-positive bacteria. However, current understanding of sRNA-mediated regulation in Streptococcus is limited. Most known sRNAs in Streptococcus are associated with the regulation of virulence. In this review, we summarize recent advances in understanding of the functions and mechanisms of sRNAs in Streptococcus, and we discuss the RNA chaperone protein and synthetic sRNA-mediated gene regulation, with the aim of providing a reference for the study of microbial sRNAs.

The Small RNAs PA2952.1 and PrrH as Regulators of Virulence, Motility, and Iron Metabolism in Pseudomonas aeruginosa

Pseudomonas aeruginosa is a Gram-negative opportunistic pathogen that undergoes swarming motility in response to semisolid conditions with amino acids as a nitrogen source. With a genome encoding hundreds of potential intergenic small RNAs (sRNAs), P. aeruginosa can easily adapt to different conditions and stresses. We previously identified 20 sRNAs that were differentially expressed (DE) under swarming conditions. Here, these sRNAs were overexpressed in strain PAO1 and were subjected to an array of phenotypic screens. Overexpression of the PrrH sRNA resulted in decreased swimming motility, whereas a ΔprrH mutant had decreased cytotoxicity and increased pyoverdine production. Overexpression of the previously uncharacterized PA2952.1 sRNA resulted in decreased swarming and swimming motilities, increased gentamicin and tobramycin resistance under swarming conditions, and increased trimethoprim susceptibility. Transcriptome sequencing (RNA-Seq) and proteomic analysis were performed on the wild type (WT) overexpressing PA2952.1 compared to the empty vector control under swarming conditions, and these revealed the differential expression (absolute fold change [FC] ≥ 1.5) of 784 genes and the differential abundance (absolute FC ≥ 1.25) of 59 proteins. Among these were found 73 transcriptional regulators, two-component systems, and sigma and anti-sigma factors. Downstream effectors included downregulated pilus and flagellar genes, the upregulated efflux pump MexGHI-OpmD, and the upregulated arn operon. Genes involved in iron and zinc uptake were generally upregulated, and certain pyoverdine genes were upregulated. Overall, the sRNAs PA2952.1 and PrrH appeared to be involved in regulating virulence-related programs in P. aeruginosa, including iron acquisition and motility.IMPORTANCE Due to the rising incidence of multidrug-resistant (MDR) strains and the difficulty of eliminating P. aeruginosa infections, it is important to understand the regulatory mechanisms that allow this bacterium to adapt to and thrive under a variety of conditions. Small RNAs (sRNAs) are one regulatory mechanism that allows bacteria to change the amount of protein synthesized. In this study, we overexpressed 20 different sRNAs in order to investigate how this might affect different bacterial behaviors. We found that one of the sRNAs, PrrH, played a role in swimming motility and virulence phenotypes, indicating a potentially important role in clinical infections. Another sRNA, PA2952.1, affected other clinically relevant phenotypes, including motility and antibiotic resistance. RNA-Seq and proteomics of the strain overexpressing PA2952.1 revealed the differential expression of 784 genes and 59 proteins, with a total of 73 regulatory factors. This substantial dysregulation indicates an important role for the sRNA PA2952.1.

Transcriptome Profiling of Staphylococcus aureus Associated Extracellular Vesicles Reveals Presence of Small RNA-Cargo

Bacterial extracellular vesicles (EVs) have a vital role in bacterial pathogenesis. However, to date, the small RNA-cargo of EVs released by the opportunistic pathogen Staphylococcus aureus has not been characterized. Here, we shed light on the association of small RNAs with EVs secreted by S. aureus MSSA476 cultured in iron-depleted bacteriologic media supplemented with a subinhibitory dosage of vancomycin to mimic infection condition. Confocal microscopy analysis on intact RNase-treated EVs indicated that RNA is associated with EV particles. Transcriptomic followed by bioinformatics analysis of EV-associated RNA revealed the presence of potential gene regulatory small RNAs and high levels of tRNAs. Among the EV-associated enriched small RNAs were SsrA, RsaC and RNAIII. Our finding invites new insights into the potential role of EV-associated RNA as a modulator of host-pathogen interaction.

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.

A survey of non-coding RNAs in the social and predatory myxobacterium Myxococcus xanthus DK1622

Prokaryotic ncRNAs are important regulators of gene expression, and can be involved in complex signalling networks. The myxobacteria are model organisms for studies into multicellular development and microbial predation, being particularly renowned for their large genomes and exceptionally sophisticated signalling networks. However, apart from two specific examples, little is known about their regulatory ncRNAs. Here, we integrate bioinformatic predictions and transcriptome sequence data to provide a comprehensive survey of the ncRNAs made by the exemplar myxobacterium M. xanthus DK1622. M. xanthus RNA-seq data from four experimental conditions was interrogated to identify transcripts mapping outside coding sequences and to known ncRNAs. The resulting 37 ncRNAs were clustered on the genome and most (30/37) were conserved across the myxobacteria. A majority of ncRNAs (22/37) were intergenic, while 13 were at least partially antisense to protein-coding genes. Predicted promoter and terminator sequences explained the start/stop sites of 18 ncRNAs. mRNA targets for the ncRNAs were predicted, including plausible candidates for a known regulatory ncRNA. 22 ncRNAs were differentially expressed by nutrient availability and expression of 25 predicted targets was found to correlate strongly with that of their regulatory ncRNAs. Sharing of predicted mRNA targets by multiple ncRNAs suggests that some ncRNAs might regulate each other within signalling networks. This genomic survey of M. xanthus ncRNA biology provides a starting point for further studies of myxobacterial ncRNAs, which are likely to have important functions in these industrially important and sophisticated organisms.

Overexpression of the Small RNA PA0805.1 in Pseudomonas aeruginosa Modulates the Expression of a Large Set of Genes and Proteins, Resulting in Altered Motility, Cytotoxicity, and Tobramycin Resistance

P. aeruginosa is an opportunistic pathogen of humans. With roughly 10% of its genes encoding transcriptional regulators, and hundreds of small noncoding RNAs (sRNAs) interspersed throughout the genome, P. aeruginosa is able to fine-tune its response to adapt and survive in the host and resist antimicrobial agents. Understanding mechanisms of genetic regulation is therefore crucial to combat pathogenesis. The previously uncharacterized sRNA PA0805.1 was overexpressed in P. aeruginosa strain PAO1, resulting in decreased motility, increased adherence, cytotoxicity, and tobramycin resistance. In contrast, a ΔPA0805.1 deletion mutant had increased susceptibility to tobramycin under swarming conditions. Omic approaches uncovered 1,121 transcriptomic and 258 proteomic changes in the overexpression strain compared with the empty-vector strain, which included 106 regulatory factors. Downstream of these regulators were upregulated adherence factors, multidrug efflux systems, and virulence factors in both transcriptomics and proteomics. This study provides insights into the role of the sRNA PA0805.1 in modulating bacterial adaptations.

Pseudomonas aeruginosa is a motile species that initiates swarming motility in response to specific environmental cues, i.e., a semisolid surface with amino acids as a nitrogen source (relevant to the human lung). Swarming is an intricately regulated process, but to date posttranscriptional regulation has not been extensively investigated. Small noncoding RNAs (sRNAs) are hypothesized to play posttranscriptional regulatory roles, largely through suppression of translation, and we previously demonstrated 20 sRNA species that were dysregulated under swarming conditions. One of these, sRNA PA0805.1 (which was 5-fold upregulated under swarming conditions), when cloned, transformed into wild-type (WT) PAO1, and overexpressed, led to broad phenotypic changes, including reduced swarming, swimming, and twitching motilities, as well as increased adherence, cytotoxicity, and tobramycin resistance. A ΔPA0805.1 deletion mutant was more susceptible to tobramycin than the WT under swarming conditions. The strain overexpressing PA0805.1 was compared to the empty-vector strain by transcriptome sequencing (RNA-Seq) and proteomics under swarming conditions to determine sRNA targets. Broad transcriptional and proteomic profiles showed 1,121 differentially expressed genes and 258 proteins with significantly different abundance. Importantly, these included 106 transcriptional regulators, two-component regulatory systems, and sigma and anti-sigma factors. Downstream of these regulators were found downregulated type IV pilus genes, many upregulated adherence and virulence factors, and two multidrug efflux systems, mexXY and mexGHI-opmD. Therefore, the sRNA PA0805.1 appears to be a global regulator that influences diverse bacterial lifestyles, most likely through a regulatory cascade.

IMPORTANCEP. aeruginosa is an opportunistic pathogen of humans. With roughly 10% of its genes encoding transcriptional regulators, and hundreds of small noncoding RNAs (sRNAs) interspersed throughout the genome, P. aeruginosa is able to fine-tune its response to adapt and survive in the host and resist antimicrobial agents. Understanding mechanisms of genetic regulation is therefore crucial to combat pathogenesis. The previously uncharacterized sRNA PA0805.1 was overexpressed in P. aeruginosa strain PAO1, resulting in decreased motility, increased adherence, cytotoxicity, and tobramycin resistance. In contrast, a ΔPA0805.1 deletion mutant had increased susceptibility to tobramycin under swarming conditions. Omic approaches uncovered 1,121 transcriptomic and 258 proteomic changes in the overexpression strain compared with the empty-vector strain, which included 106 regulatory factors. Downstream of these regulators were upregulated adherence factors, multidrug efflux systems, and virulence factors in both transcriptomics and proteomics. This study provides insights into the role of the sRNA PA0805.1 in modulating bacterial adaptations.

Transcriptome Analysis of Gene Expression in Dermacoccus abyssi HZAU 226 under Lysozyme Stress

Lysozyme acts as a kind of cationic antimicrobial protein and effectively hydrolyzes bacterial peptidoglycan to have a bactericidal effect, which also plays an important role in protecting eggs from microbial contamination. Dermacoccus abyssi HZAU 226, a Gram-positive bacterium isolated from spoiled eggs, has egg white and lysozyme tolerance, but its survival mechanism is unknown, especially from a transcriptomics point of view. In this study, the high lysozyme tolerance of D. abyssi HZAU 226 was characterized by three independent experiments, and then the Illumina RNA-seq was used to compare the transcriptional profiles of this strain in Luria–Bertani (LB) medium with and without 5 mg/mL lysozyme to identify differentially expressed genes (DEGs); 1024 DEGs were identified by expression analysis, including 544 up-regulated genes and 480 down-regulated genes in response to lysozyme treatment. The functional annotation analysis results of DEGs showed that these genes were mainly involved in glutathione biosynthesis and metabolism, ion transport, energy metabolism pathways, and peptidoglycan biosynthesis. This study is the first report of bacterial-related lysozyme RNA-seq, and our results help in understanding the lysozyme-tolerance mechanism of bacteria from a new perspective and provide transcriptome resources for subsequent research in related fields.

Prevalence of small base-pairing RNAs derived from diverse genomic loci

Small RNAs (sRNAs) that act by base-pairing have been shown to play important roles in fine-tuning the levels and translation of their target transcripts across a variety of model and pathogenic organisms. Work from many different groups in a wide range of bacterial species has provided evidence for the importance and complexity of sRNA regulatory networks, which allow bacteria to quickly respond to changes in their environment. However, despite the expansive literature, much remains to be learned about all aspects of sRNA-mediated regulation, particularly in bacteria beyond the well-characterized Escherichia coli and Salmonella enterica species. Here we discuss what is known, and what remains to be learned, about the identification of regulatory base-pairing RNAs produced from diverse genomic loci including how their expression is regulated. This article is part of a Special Issue entitled: RNA and gene control in bacteria edited by Dr. M. Guillier and F. Repoila.

Utilization of Small RNA Genes to Distinguish Vibrio cholerae Biotypes via Multiplex Polymerase Chain Reaction

The diarrheal disease "cholera" is caused by Vibrio cholerae, and is primarily confined to endemic regions, mostly in Africa and Asia. It is punctuated by outbreaks and creates severe challenges to public health. The disease-causing strains are most-often members of serogroups O1 and O139. PCR-based methods allow rapid diagnosis of these pathogens, including the identification of their biotypes. However, this necessitates the selection of specific target sequences to differentiate even the closely related biotypes of V. cholerae. Oligonucleotides for selective amplification of small RNA (sRNA) genes that are specific to these V. cholerae subtypes were designed. The resulting multiplex PCR assay was validated using V. cholerae cultures (i.e., 19 V. cholerae and 22 non-V. cholerae isolates) and spiked stool samples. The validation using V. cholerae cultures and spiked stool suspensions revealed detection limits of 10-100 pg DNA per reaction and 1.5 cells/mL suspension, respectively. The multiplex PCR assay that targets sRNA genes for amplification enables the sensitive and specific detection, as well as the differentiation of V. cholerae-O1 classical, O1 El Tor, and O139 biotypes. Most importantly, the assay enables fast and cheaper diagnosis compared with classic culture-based methods.

IntaRNAhelix-composing RNA–RNA interactions from stable inter-molecular helices boosts bacterial sRNA target prediction

Efficient computational tools for the identification of putative target RNAs regulated by prokaryotic sRNAs rely on thermodynamic models of RNA secondary structures. While they typically predict RNA–RNA interaction complexes accurately, they yield many highly-ranked false positives in target screens. One obvious source of this low specificity appears to be the disability of current secondary-structure-based models to reflect steric constraints, which nevertheless govern the kinetic formation of RNA–RNA interactions. For example, often — even thermodynamically favorable — extensions of short initial kissing hairpin interactions are kinetically prohibited, since this would require unwinding of intra-molecular helices as well as sterically impossible bending of the interaction helix. Another source is the consideration of instable and thus unlikely subinteractions that enable better scoring of longer interactions. In consequence, the efficient prediction methods that do not consider such effects show a high false positive rate.

To increase the prediction accuracy we devise IntaRNAhelix, a dynamic programming algorithm that length-restricts the runs of consecutive inter-molecular base pairs (perfect canonical stackings), which we hypothesize to implicitly model the steric and kinetic effects. The novel method is implemented by extending the state-of-the-art tool IntaRNA.

Our comprehensive bacterial sRNA target prediction benchmark demonstrates significant improvements of the prediction accuracy and enables more than 40-times faster computations. These results indicate — supporting our hypothesis — that stable helix composition increases the accuracy of interaction prediction models compared to the current state-of-the-art approach.

The roles of small RNAs: insights from bacterial quorum sensing

Ribonucleic acids (RNAs) mainly played auxiliary roles in regulations of genetic processes while recent explorations into small non-coding RNAs (sRNAs) in bacteria have broadened the scope of RNAs studies in these processes. sRNAs have been demonstrated to be involved in various genetic processes and to regulate a variety of bacterial physiologies. Comparatively, quorum sensing (QS) is a mature bacterial cell signaling system which regulates bacteria physiologies as well. Prokaryotic sRNAs studies in the status quo have revealed an emerging picture of trans-kingdom signaling regulation and increasing investigations have demonstrated the feasibility of inter-kingdom signaling as the consequence of QS. We therefore review such phenomena and their similarities to investigate the potential of prokaryote-sourced interkingdom signaling and regulation.

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

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

Regulatory non-coding sRNAs in bacterial metabolic pathway engineering

Non-coding RNAs (ncRNAs) are versatile and powerful controllers of gene expression that have been increasingly linked to cellular metabolism and phenotype. In bacteria, identified and characterized ncRNAs range from trans-acting, multi-target small non-coding RNAs to dynamic, cis-encoded regulatory untranslated regions and riboswitches. These native regulators have inspired the design and construction of many synthetic RNA devices. In this work, we review the design, characterization, and impact of ncRNAs in engineering both native and exogenous metabolic pathways in bacteria. We also consider the opportunities afforded by recent high-throughput approaches for characterizing sRNA regulators and their corresponding networks to showcase their potential applications and impact in engineering bacterial metabolism.

RNomic identification and evaluation of npcTB_6715, a non-protein-coding RNA gene as a potential biomarker for the detection of Mycobacterium tuberculosis

Technological advances in RNA biology greatly improved transcriptome profiling during the last two decades. Besides the discovery of many small RNAs (sRNA) that are involved in the physiological and pathophysiological regulation of various cellular circuits, it becomes evident that the corresponding RNA genes might also serve as potential biomarkers to monitor the progression of disease and treatment. sRNA gene candidate npcTB_6715 was previously identified via experimental RNomic (unpublished data), and we report its application as potential biomarker for the detection of Mycobacterium tuberculosis (MTB) in patient samples. For proof of principle, we developed a multiplex PCR assay and report its validation with 500 clinical cultures, positive for Mycobacteria. The analysis revealed 98.9% sensitivity, 96.1% specificity, positive and negative predictive values of 98.6% and 96.8%, respectively. These results underscore the diagnostic value of the sRNA gene as diagnostic marker for the specific detection of MTB in clinical samples. Its successful application and the general ease of PCR‐based detection compared to standard bacterial culture techniques might be the first step towards ‘point‐of‐care’ diagnostics of Mycobacteria. To the best of our knowledge, this is the first time for the design of diagnostic applications based on sRNA genes, in Mycobacteria.

Small RNAs of Borrelia burgdorferi: Characterizing Functional Regulators in a Sea of sRNAs

Borrelia (Borreliella) burgdorferi and closely related genospecies are the causative agents of Lyme disease, the most common tick-borne disease north of the equator. The bacterium, a member of the spirochete phylum, is acquired by a tick vector that feeds on an infected vertebrate host and is transmitted to another vertebrate during subsequent feeding by the next tick stage. The precise navigation of this enzootic cycle entails the regulation of genes required for these two host-specific phases as well as the transitions between them. Recently, an expansive swath of small RNAs has been identified in B. burgdorferi and likely many, if not most, are involved in regulating gene expression. Regardless, with only a few exceptions, the functions of these RNAs are completely unknown. However, several state-of-the-art approaches are available to identify the targets of these RNAs and provide insight into their role in the enzootic cycle and infection.

Analysis of sucrose-induced small RNAs in Streptococcus mutans in the presence of different sucrose concentrations

Streptococcus mutans (S. mutans) is the major pathogen contributing to dental caries. Sucrose is an important carbohydrate source for S. mutans and is crucial for dental caries. Small RNAs (sRNAs) are key post-transcriptional regulators of stress adaptation and virulence in bacteria. Here, for the first time, we created three replicate RNA libraries exposed to either 1 or 5% sucrose. The expression levels of sRNAs and target genes (gtfB, gtfC, and spaP) related to virulence were assessed. In addition, some phenotypic traits were evaluated. We obtained 2125 sRNA candidates with at least 100 average reads in 1% sucrose or 5% sucrose. Of these candidates, 2 were upregulated and 20 were downregulated in 1% sucrose. Six of these 22 differentially expressed sRNAs were validated by qRT-PCR. The expression level of target gene gtfB was higher in 1% sucrose. The adherence ratio of S. mutans was higher in 1% sucrose than in 5% sucrose. The synthesis of water-insoluble glucans (WIGs) was significantly higher in 5% sucrose than in 1% sucrose. These data suggest that a series of sRNAs can be induced in response to sucrose, and that some sRNAs might be involved in the regulation of phenotypes, providing new insight into the prevention of caries.

Detecting RNA-RNA interactions in E. coli using a modified CLASH method

Background

Bacterial small regulatory RNAs (sRNAs) play important roles in sensing environment changes through sRNA-target mRNA interactions. However, the current strategy for detecting sRNA-mRNA interactions usually combines bioinformatics prediction and experimental verification, which is hampered by low prediction accuracy and low-throughput. Additionally, among the 4736 sequenced bacterial genomes, only about 2164 sRNAs from 319 strains have been described. Furthermore, target mRNAs of only 157 sRNAs have been uncovered. Obviously, highly efficient methods were required to detect sRNA-mRNA interactions in the sequenced genomes. This study aimed to apply a modified CLASH (cross-linking, ligation and sequencing hybrids) method to detect RNA-RNA interactions in E. coli, a model bacterial organism.

Results

Statistically significant interactions were detected in 29 transcript pairs. To the best of our knowledge, 24 pairs were reported for the first time and were novel RNA interactions, including tRNA-tRNA, tRNA-ncRNA (non-coding RNA), tRNA-rRNA, rRNA-mRNA, rRNA-ncRNA, rRNA-rRNA, rRNA-IGT (intergenic transcript), and tRNA-IGT interactions.

Conclusions

Discovery of novel RNA-RNA interactions in the present study demonstrates that RNA-RNA interactions might be far more complicated than ever expected. New methods may be required to help discover more novel RNA-RNA interactions. The present work describes a high-throughput protocol not only for discovering new RNA interactions, but also directly obtaining base-pairing sequences, which should be useful in assessing RNA structure and interactions.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-017-3725-3) contains supplementary material, which is available to authorized users.

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.

Differentiation of ncRNAs from small mRNAs in Escherichia coli O157:H7 EDL933 (EHEC) by combined RNAseq and RIBOseq - ryhB encodes the regulatory RNA RyhB and a peptide, RyhP

Background

While NGS allows rapid global detection of transcripts, it remains difficult to distinguish ncRNAs from short mRNAs. To detect potentially translated RNAs, we developed an improved protocol for bacterial ribosomal footprinting (RIBOseq). This allowed distinguishing ncRNA from mRNA in EHEC. A high ratio of ribosomal footprints per transcript (ribosomal coverage value, RCV) is expected to indicate a translated RNA, while a low RCV should point to a non-translated RNA.

Results

Based on their low RCV, 150 novel non-translated EHEC transcripts were identified as putative ncRNAs, representing both antisense and intergenic transcripts, 74 of which had expressed homologs in E. coli MG1655. Bioinformatics analysis predicted statistically significant target regulons for 15 of the intergenic transcripts; experimental analysis revealed 4-fold or higher differential expression of 46 novel ncRNA in different growth media. Out of 329 annotated EHEC ncRNAs, 52 showed an RCV similar to protein-coding genes, of those, 16 had RIBOseq patterns matching annotated genes in other enterobacteriaceae, and 11 seem to possess a Shine-Dalgarno sequence, suggesting that such ncRNAs may encode small proteins instead of being solely non-coding. To support that the RIBOseq signals are reflecting translation, we tested the ribosomal-footprint covered ORF of ryhB and found a phenotype for the encoded peptide in iron-limiting condition.

Conclusion

Determination of the RCV is a useful approach for a rapid first-step differentiation between bacterial ncRNAs and small mRNAs. Further, many known ncRNAs may encode proteins as well.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-017-3586-9) contains supplementary material, which is available to authorized users.

A computational strategy for the search of regulatory small RNAs in Actinobacillus pleuropneumoniae

Bacterial regulatory small RNAs (sRNAs) play important roles in gene regulation and are frequently connected to the expression of virulence factors in diverse bacteria. Only a few sRNAs have been described for Pasteurellaceae pathogens and no in-depth analysis of sRNAs has been described for Actinobacillus pleuropneumoniae, the causative agent of porcine pleuropneumonia, responsible for considerable losses in the swine industry. To search for sRNAs in A. pleuropneumoniae, we developed a strategy for the computational analysis of the bacterial genome by using four algorithms with different approaches, followed by experimental validation. The coding strand and expression of 17 out of 23 RNA candidates were confirmed by Northern blotting, RT-PCR, and RNA sequencing. Among them, two are likely riboswitches, three are housekeeping regulatory RNAs, two are the widely studied GcvB and 6S sRNAs, and 10 are putative novel trans-acting sRNAs, never before described for any bacteria. The latter group has several potential mRNA targets, many of which are involved with virulence, stress resistance, or metabolism, and connect the sRNAs in a complex gene regulatory network. The sRNAs identified are well conserved among the Pasteurellaceae that are evolutionarily closer to A. pleuropneumoniae and/or share the same host. Our results show that the combination of newly developed computational programs can be successfully utilized for the discovery of novel sRNAs and indicate an intricate system of gene regulation through sRNAs in A. pleuropneumoniae and in other Pasteurellaceae, thus providing clues for novel aspects of virulence that will be explored in further studies.

A game of tag: MAPS catches up on RNA interactomes

In the last few decades, small regulatory RNA (sRNA) molecules emerged as key regulators in every kingdom of life. Resolving the full targetome of sRNAs has however remained a challenge. To address this, we used an in vivo tagging MS2-affinity purification protocol coupled with RNA sequencing technology, namely MAPS, to assemble full bacterial small RNAs targetomes. The impressive potential of MAPS has been supported by a number of reports. Here, we concisely overview RNA-tagging history that preceded the development of the MAPS assay and expose the range of possible uses of this technology.

Novel small RNA (sRNA) landscape of the starvation-stress response transcriptome of Salmonella enterica serovar typhimurium

Small RNAs (sRNAs) are short (∼50-200 nucleotides) noncoding RNAs that regulate cellular activities across bacteria. Salmonella enterica starved of a carbon-energy (C) source experience a host of genetic and physiological changes broadly referred to as the starvation-stress response (SSR). In an attempt to identify novel sRNAs contributing to SSR control, we grew log-phase, 5-h C-starved and 24-h C-starved cultures of the virulent Salmonella enterica subspecies enterica serovar Typhimurium strain SL1344 and comprehensively sequenced their small RNA transcriptomes. Strikingly, after employing a novel strategy for sRNA discovery based on identifying dynamic transcripts arising from "gene-empty" regions, we identify 58 wholly undescribed Salmonella sRNA genes potentially regulating SSR averaging an ∼1,000-fold change in expression between log-phase and C-starved cells. Importantly, the expressions of individual sRNA loci were confirmed by both comprehensive transcriptome analyses and northern blotting of select candidates. Of note, we find 43 candidate sRNAs share significant sequence identity to characterized sRNAs in other bacteria, and ∼70% of our sRNAs likely assume characteristic sRNA structural conformations. In addition, we find 53 of our 58 candidate sRNAs either overlap neighboring mRNA loci or share significant sequence complementarity to mRNAs transcribed elsewhere in the SL1344 genome strongly suggesting they regulate the expression of transcripts via antisense base-pairing. Finally, in addition to this work resulting in the identification of 58 entirely novel Salmonella enterica genes likely participating in the SSR, we also find evidence suggesting that sRNAs are significantly more prevalent than currently appreciated and that Salmonella sRNAs may actually number in the thousands.

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.

Comprehensive analysis reveals how single nucleotides contribute to noncoding RNA function in bacterial quorum sensing

Five homologous noncoding small RNAs (sRNAs), called the Qrr1-5 sRNAs, function in the Vibrio harveyi quorum-sensing cascade to drive its operation. Qrr1-5 use four different regulatory mechanisms to control the expression of ∼ 20 mRNA targets. Little is known about the roles individual nucleotides play in mRNA target selection, in determining regulatory mechanism, or in defining Qrr potency and dynamics of target regulation. To identify the nucleotides vital for Qrr function, we developed a method we call RSort-Seq that combines saturating mutagenesis, fluorescence-activated cell sorting, high-throughput sequencing, and mutual information theory to explore the role that every nucleotide in Qrr4 plays in regulation of two mRNA targets, luxR and luxO. Companion biochemical assays allowed us to assign specific regulatory functions/underlying molecular mechanisms to each important base. This strategy yielded a regional map of nucleotides in Qrr4 vital for stability, Hfq interaction, stem-loop formation, and base pairing to both luxR and luxO, to luxR only, and to luxO only. In terms of nucleotides critical for sRNA function, the RSort-Seq analysis provided strikingly different results from those predicted by commonly used regulatory RNA-folding algorithms. This approach is applicable to any RNA-RNA interaction, including sRNAs in other bacteria and regulatory RNAs in higher organisms.

Small RNA Transcriptome of the Oral Microbiome during Periodontitis Progression

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

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

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

Genome-wide analyses of small non-coding RNAs in streptococci

Streptococci represent a diverse group of Gram-positive bacteria, which colonize a wide range of hosts among animals and humans. Streptococcal species occur as commensal as well as pathogenic organisms. Many of the pathogenic species can cause severe, invasive infections in their hosts leading to a high morbidity and mortality. The consequence is a tremendous suffering on the part of men and livestock besides the significant financial burden in the agricultural and healthcare sectors. An environmentally stimulated and tightly controlled expression of virulence factor genes is of fundamental importance for streptococcal pathogenicity. Bacterial small non-coding RNAs (sRNAs) modulate the expression of genes involved in stress response, sugar metabolism, surface composition, and other properties that are related to bacterial virulence. Even though the regulatory character is shared by this class of RNAs, variation on the molecular level results in a high diversity of functional mechanisms. The knowledge about the role of sRNAs in streptococci is still limited, but in recent years, genome-wide screens for sRNAs have been conducted in an increasing number of species. Bioinformatics prediction approaches have been employed as well as expression analyses by classical array techniques or next generation sequencing. This review will give an overview of whole genome screens for sRNAs in streptococci with a focus on describing the different methods and comparing their outcome considering sRNA conservation among species, functional similarities, and relevance for streptococcal infection.

Small RNA Deep-Sequencing Analyses Reveal a New Regulator of Virulence in Agrobacterium fabrum C58

Novel ways of regulating Ti plasmid functions were investigated by studying small RNAs (sRNAs) that are known to act as posttranscriptional regulators in plant pathogenic bacteria. sRNA-seq analyses of Agrobacterium fabrum C58 allowed us to identify 1,108 small transcripts expressed in several growth conditions that could be sRNAs. A quarter of them were confirmed by bioinformatics or by biological experiments. Antisense RNAs represent 24% of the candidates and they are over-represented on the pTi (with 62% of pTi sRNAs), suggesting differences in the regulatory mechanisms between the essential and accessory replicons. Moreover, a large number of these pTi antisense RNAs are transcribed opposite to those genes involved in virulence. Others are 5'- and 3'-untranslated region RNAs and trans-encoded RNAs. We have validated, by rapid amplification of cDNA ends polymerase chain reaction, the transcription of 14 trans-encoded RNAs, among which RNA1111 is expressed from the pTiC58. Its deletion decreased the aggressiveness of A. fabrum C58 on tomatoes, tobaccos, and kalanchoe, suggesting that this sRNA activates virulence. The identification of its putative target mRNAs (6b gene, virC2, virD3, and traA) suggests that this sRNA may coordinate two of the major pTi functions, the infection of plants and its dissemination among bacteria.

A multiobjective method for robust identification of bacterial small non-coding RNAs

MOTIVATION

Small non-coding RNAs (sRNAs) have major roles in the post-transcriptional regulation in prokaryotes. The experimental validation of a relatively small number of sRNAs in few species requires developing computational algorithms capable of robustly encoding the available knowledge and using this knowledge to predict sRNAs within and across species.

RESULTS

We present a novel methodology designed to identify bacterial sRNAs by incorporating the knowledge encoded by different sRNA prediction methods and optimally aggregating them as potential predictors. Because some of these methods emphasize specificity, whereas others emphasize sensitivity while detecting sRNAs, their optimal aggregation constitutes trade-off solutions between these two contradictory objectives that enhance their individual merits. Many non-redundant optimal aggregations uncovered by using multiobjective optimization techniques are then combined into a multiclassifier, which ensures robustness during detection and prediction even in genomes with distinct nucleotide composition. By training with sRNAs in Salmonella enterica Typhimurium, we were able to successfully predict sRNAs in Sinorhizobium meliloti, as well as in multiple and poorly annotated species. The proposed methodology, like a meta-analysis approach, may begin to lay a possible foundation for developing robust predictive methods across a wide spectrum of genomic variability.

AVAILABILITY AND IMPLEMENTATION

Scripts created for the experimentation are available at http://m4m.ugr.es/SupInfo/sRNAOS/sRNAOSscripts.zip.

CONTACT

delval@decsai.ugr.es

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Identifying and characterizing Hfq-RNA interactions

To regulate stress responses and virulence, bacteria use small regulatory RNAs (sRNAs). These RNAs can up or down regulate target mRNAs through base pairing by influencing ribosomal access and RNA decay. A large class of these sRNAs, called trans-encoded sRNAs, requires the RNA binding protein Hfq to facilitate base pairing between the regulatory RNA and its target mRNA. The resulting network of regulation is best characterized in Escherichia coli and Salmonella typhimurium, but the importance of Hfq dependent sRNA regulation is recognized in a diverse population of bacteria. In this review we present the approaches and methods used to discover Hfq binding RNAs, characterize their interactions and elucidate their functions.