Non-coding RNAs in marine Synechococcus and their regulation under environmentally relevant stress conditions

Regulatory small RNAs (sRNAs) have crucial roles in the adaptive responses of bacteria to changes in the environment. Thus far, potential regulatory RNAs have been studied mainly in marine picocyanobacteria in genetically intractable Prochlorococcus, rendering their molecular analysis difficult. Synechococcus sp. WH7803 is a model cyanobacterium, representative of the picocyanobacteria from the mesotrophic areas of the ocean. Similar to the closely related Prochlorococcus it possesses a relatively streamlined genome and a small number of genes, but is genetically tractable. Here, a comparative genome analysis was performed for this and four additional marine Synechococcus to identify the suite of possible sRNAs and other RNA elements. Based on the prediction and on complementary microarray profiling, we have identified several known as well as 32 novel sRNAs. Some sRNAs overlap adjacent coding regions, for instance for the central photosynthetic gene psbA. Several of these novel sRNAs responded specifically to environmentally relevant stress conditions. Among them are six sRNAs changing their accumulation level under cold stress, six responding to high light and two to iron limitation. Target predictions suggested genes encoding components of the light-harvesting apparatus as targets of sRNAs originating from genomic islands and that one of the iron-regulated sRNAs might be a functional homolog of RyhB. These data suggest that marine Synechococcus mount adaptive responses to these different stresses involving regulatory sRNAs.     

Comparative genome‐wide analysis of small RNAs of major Gram‐positive pathogens: from identification to application

In the recent years, the number of drug- and multi-drug-resistant microbial strains has increased rapidly. Therefore, the need to identify innovative approaches for development of novel anti-infectives and new therapeutic targets is of high priority in global health care. The detection of small RNAs (sRNAs) in bacteria has attracted considerable attention as an emerging class of new gene expression regulators. Several experimental technologies to predict sRNA have been established for the Gram-negative model organism Escherichia coli. In many respects, sRNA screens in this model system have set a blueprint for the global and functional identification of sRNAs for Gram-positive microbes, but the functional role of sRNAs in colonization and pathogenicity for Listeria monocytogenes, Staphylococcus aureus, Streptococcus pyogenes, Enterococcus faecalis and Clostridium difficile is almost completely unknown. Here, we report the current knowledge about the sRNAs of these socioeconomically relevant Gram-positive pathogens, overview the state-of-the-art high-throughput sRNA screening methods and summarize bioinformatics approaches for genome-wide sRNA identification and target prediction. Finally, we discuss the use of modified peptide nucleic acids (PNAs) as a novel tool to inactivate potential sRNA and their applications in rapid and specific detection of pathogenic bacteria.     

Multiple small RNAs identified in Mycobacterium bovis BCG are also expressed in Mycobacterium tuberculosis and Mycobacterium smegmatis

Tuberculosis (TB) is a major global health problem, infecting millions of people each year. The causative agent of TB, Mycobacterium tuberculosis, is one of the world’s most ancient and successful pathogens. However, until recently, no work on small regulatory RNAs had been performed in this organism. Regulatory RNAs are found in all three domains of life, and have already been shown to regulate virulence in well-known pathogens, such as Staphylococcus aureus and Vibrio cholera. Here we report the discovery of 34 novel small RNAs (sRNAs) in the TB-complex M. bovis BCG, using a combination of experimental and computational approaches. Putative homologues of many of these sRNAs were also identified in M. tuberculosis and/or M. smegmatis. Those sRNAs that are also expressed in the non-pathogenic M. smegmatis could be functioning to regulate conserved cellular functions. In contrast, those sRNAs identified specifically in M. tuberculosis could be functioning in mediation of virulence, thus rendering them potential targets for novel antimycobacterials. Various features and regulatory aspects of some of these sRNAs are discussed.     

Molecular call and response: the physiology of bacterial small RNAs

The vital role of bacterial small RNAs (sRNAs) in cellular regulation is now well-established. Although many diverse mechanisms by which sRNAs bring about changes in gene expression have been thoroughly described, comparatively less is known about their biological roles and effects on cell physiology. Nevertheless, for some sRNAs, insight has been gained into the intricate regulatory interplay that is required to sense external environmental and internal metabolic cues and turn them into physiological outcomes. Here, we review examples of regulation by selected sRNAs, emphasizing signals and regulators required for sRNA expression, sRNA regulatory targets, and the resulting consequences for the cell. We highlight sRNAs involved in regulation of the processes of iron homeostasis (RyhB, PrrF, and FsrA) and carbon metabolism (Spot 42, CyaR, and SgrS).     

Identifying expression of new small RNAs by microarrays

Although a large number of small RNAs (sRNAs) have been discovered, it is very likely that the screens conducted so far have not reached saturation. Recently, many methods for predicting and identifying new sRNAs have been developed. However, it remains unclear what the total number of sRNAs within a genome is and how many types of sRNAs exist in plants and animals. In this article, combined methods of dynamic programming prediction, enrichment of sRNAs, and microarray analysis are developed to screen and evaluate a new class of sRNAs from introns of human, protein-encoding genes. The methods used by our laboratories to design capture probes and label enriched small RNAs are thoroughly described here. The microarray results show that our modified technologies are useful to enhance sensitivity and specificity of arrays, identify expression patterns within different cells, and discover differential expression of sRNAs during the differentiation process of bone marrow stem cells. Accordingly, the combination of computational prediction and microarray analysis may be a feasible and practical approach for profiling studies of both known and predicted small RNAs.     

Predicting sRNAs and Their Targets in Bacteria

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

An integrated approach for finding overlooked genes in Shigella

Background

The completion of numerous genome sequences introduced an era of whole-genome study. However, many genes are missed during genome annotation, including small RNAs (sRNAs) and small open reading frames (sORFs). In order to improve genome annotation, we aimed to identify novel sRNAs and sORFs in Shigella, the principal etiologic agents of bacillary dysentery.

Methodology/Principal Findings

We identified 64 sRNAs in Shigella, which were experimentally validated in other bacteria based on sequence conservation. We employed computer-based and tiling array-based methods to search for sRNAs, followed by RT-PCR and northern blots, to identify nine sRNAs in Shigella flexneri strain 301 (Sf301) and 256 regions containing possible sRNA genes. We found 29 candidate sORFs using bioinformatic prediction, array hybridization and RT-PCR verification. We experimentally validated 557 (57.9%) DOOR operon predictions in the chromosomes of Sf301 and 46 (76.7%) in virulence plasmid.We found 40 additional co-expressed gene pairs that were not predicted by DOOR.

Conclusions/Significance

We provide an updated and comprehensive annotation of the Shigella genome. Our study increased the expected numbers of sORFs and sRNAs, which will impact on future functional genomics and proteomics studies. Our method can be used for large scale reannotation of sRNAs and sORFs in any microbe with a known genome sequence.     

Small RNAs and Gene Network in a Durable Disease Resistance Gene—Mediated Defense Responses in Rice

Accumulating data have suggested that small RNAs (sRNAs) have important functions in plant responses to pathogen invasion. However, it is largely unknown whether and how sRNAs are involved in the regulation of rice responses to the invasion of Xanthomonas oryzae pv. oryzae (Xoo), which causes bacterial blight, the most devastating bacterial disease of rice worldwide. We performed simultaneous genome-wide analyses of the expression of sRNAs and genes during early defense responses of rice to Xoo mediated by a major disease resistance gene, Xa3/Xa26, which confers durable and race-specific qualitative resistance. A large number of sRNAs and genes showed differential expression in Xa3/Xa26-mediated resistance. These differentially expressed sRNAs include known microRNAs (miRNAs), unreported miRNAs, and small interfering RNAs. The candidate genes, with expression that was negatively correlated with the expression of sRNAs, were identified, indicating that these genes may be regulated by sRNAs in disease resistance in rice. These results provide a new perspective regarding the putative roles of sRNA candidates and their putative target genes in durable disease resistance in rice.