Abstract
BackgroundBacterial sRNA-mediated regulatory networks has been introduced as a powerful way to analyze the fast rewiring capabilities of a bacteria in response to changing environmental conditions. The identification of mRNA targets of bacterial sRNAs is essential to investigate their functional activities. However, this step remains challenging with the lack of knowledge of the topological and biological constraints behind the formation of sRNA-mRNA duplexes. Even with the most sophisticated bioinformatics target prediction tools, the large proportion of false predictions may be prohibitive for further analyses. To deal with this issue, sRNA target analyses can be carried out from the resulting gene lists given by RNA-SEQ experiments when available. However, the number of resulting target candidates may be still huge and cannot be easily interpreted by domain experts who need to confront various biological features to prioritize the target candidates. Therefore, novel strategies have to be carried out to improve the specificity of computational prediction results, before proposing new candidates for an expensive experimental validation stage.ResultTo address this issue, we propose a new visualization tool rNAV 2.0, for detecting and filtering bacterial sRNA targets for regulatory networks. rNAV is designed to cope with a variety of biological constraints, including the gene annotations, the conserved regions of interaction or specific patterns of regulation. Depending on the application, these constraints can be variously combined to analyze the target candidates, prioritized for instance by a known conserved interaction region, or because of a common function.ConclusionThe standalone application implements a set of known algorithms and interaction techniques, and applies them to the new problem of identifying reasonable sRNA target candidates.
Highlights
Bacterial Small Rubonucleic acid (sRNA)-mediated regulatory networks has been introduced as a powerful way to analyze the fast rewiring capabilities of a bacteria in response to changing environmental conditions
We performed an analytical pipeline based on the sRNAmediated regulatory network of Escherichia coli with the two sRNAs, FnrS and RyhB
We present a new software for developing bioinformatics strategies to explore sRNA-mediated networks
Summary
Bacterial sRNA-mediated regulatory networks has been introduced as a powerful way to analyze the fast rewiring capabilities of a bacteria in response to changing environmental conditions. Some bacterial RNA regulators were identified since the early 80’s, their involvement in numerous physiological responses and the idea of their probable universal distribution in the prokaryotic world have only emerged recently [1] These findings are deeply modifying our view on the way bacteria can regulate gene expression to Focusing on sRNAs acting as negative or positive posttranscriptional regulators by base-pairing mRNAs, the identification of their targets is challenging and needs a better understanding of the topological and biological constraints behind the formation of sRNA-mRNA interactions. Even with the most sophisticated bioinformatics target prediction tool, the large proportion of false predictions may be prohibitive to enable further analysis To deal with this issue, sRNA target analysis can be run from the resulting gene lists given by RNA-SEQ experiments when available. The number of resulting target candidates may be still huge and cannot be interpreted by biologist experts who needs to confront various biological features to prioritize the target candidates
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