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Open AccessJournal ArticleDOI

Comparative genomics provides structural and functional insights into Bacteroides RNA biology

TLDR
In this paper, a comparative genomics approach was used to investigate RNA biology in an understudied gut bacterium, using Bacteroides thetaiotaomicron as a representative microbiota member.
Abstract
Bacteria employ noncoding RNA molecules for a wide range of biological processes, including scaffolding large molecular complexes, catalyzing chemical reactions, defending against phages, and controlling gene expression. Secondary structures, binding partners, and molecular mechanisms have been determined for numerous small noncoding RNAs (sRNAs) in model aerobic bacteria. However, technical hurdles have largely prevented analogous analyses in the anaerobic gut microbiota. While experimental techniques are being developed to investigate the sRNAs of gut commensals, computational tools and comparative genomics can provide immediate functional insight. Here, using Bacteroides thetaiotaomicron as a representative microbiota member, we illustrate how comparative genomics improves our understanding of RNA biology in an understudied gut bacterium. We investigate putative RNA-binding proteins and predict a Bacteroides cold-shock protein homolog to have an RNA-related function. We apply an in silico protocol incorporating both sequence and structural analysis to determine the consensus structures and conservation of nine Bacteroides noncoding RNA families. Using structure probing, we validate and refine these predictions and deposit them in the Rfam database. Through synteny analyses, we illustrate how genomic coconservation can serve as a predictor of sRNA function. Altogether, this work showcases the power of RNA informatics for investigating the RNA biology of anaerobic microbiota members.

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Posted ContentDOI

An integrated transcriptomics–functional genomics approach reveals a small RNA that modulates Bacteroides thetaiotaomicron sensitivity to tetracyclines

TL;DR: In this paper , the authors map transcriptional units and profile their expression levels in Bacteroides thetaiotaomicron over a suite of 15 defined experimental conditions that are relevant in vivo, such as variation of temperature, pH, and oxygen tension, exposure to antibiotic stress, and growth on simple carbohydrates or on host mucin derived glycans.
References
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Journal ArticleDOI

Transcriptional noise and exaptation as sources for bacterial sRNAs.

TL;DR: In this article, the authors introduce relevant concepts from evolutionary biology and review recent work that has begun to shed light on the timescales and processes through which non-functional transcriptional noise is co-opted to provide regulatory functions.
Journal ArticleDOI

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TL;DR: It is suggested that the ProQ NTD specifically recognizes 3′ intrinsic terminators of RNA substrates, and that the discrimination between RNA ligands by E. coli ProQ and Hfq depends both on positive determinants for binding to Pro Q and negative determinants against binding to HfQ.
Journal ArticleDOI

Genetic identification of the functional surface for RNA binding by Escherichia coli ProQ.

TL;DR: A group of highly conserved residues on ProQ’s NTD are identified as the primary face for in vivo recognition of two RNAs, and it is proposed that the NTD structure serves as an electrostatic scaffold to recognize the shape of an RNA duplex.
Journal ArticleDOI

An RNA-centric global view of Clostridioides difficile reveals broad activity of Hfq in a clinically important gram-positive bacterium

TL;DR: In this article, a single-nucleotide-resolution RNA map of C. difficile 5′ and 3′ untranslated regions, operon structures, and noncoding regulators, including 42 sRNAs, were used to understand clostridial riboregulation with implications for the infection process and provide evidence for a global role of Hfq in posttranscriptional regulation.
Journal ArticleDOI

Studying RNA Homology and Conservation with Infernal: From Single Sequences to RNA Families

TL;DR: The Infernal software package as mentioned in this paper provides a step-by-step iterative protocol for identifying ncRNA homologs and then constructing an alignment and corresponding covariance model.
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