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      Comparative genomics reveals 104 candidate structured RNAs from bacteria, archaea, and their metagenomes

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          Abstract

          Novel motifs identified in a comparative genomic analysis of bacterial, archaeal and metagenomic data reveals over 100 candidate structured RNAs.

          Abstract

          Background

          Structured noncoding RNAs perform many functions that are essential for protein synthesis, RNA processing, and gene regulation. Structured RNAs can be detected by comparative genomics, in which homologous sequences are identified and inspected for mutations that conserve RNA secondary structure.

          Results

          By applying a comparative genomics-based approach to genome and metagenome sequences from bacteria and archaea, we identified 104 candidate structured RNAs and inferred putative functions for many of these. Twelve candidate metabolite-binding RNAs were identified, three of which were validated, including one reported herein that binds the coenzyme S-adenosylmethionine. Newly identified cis-regulatory RNAs are implicated in photosynthesis or nitrogen regulation in cyanobacteria, purine and one-carbon metabolism, stomach infection by Helicobacter, and many other physiological processes. A candidate riboswitch termed crcB is represented in both bacteria and archaea. Another RNA motif may control gene expression from 3'-untranslated regions of mRNAs, which is unusual for bacteria. Many noncoding RNAs that likely act in trans are also revealed, and several of the noncoding RNA candidates are found mostly or exclusively in metagenome DNA sequences.

          Conclusions

          This work greatly expands the variety of highly structured noncoding RNAs known to exist in bacteria and archaea and provides a starting point for biochemical and genetic studies needed to validate their biologic functions. Given the sustained rate of RNA discovery over several similar projects, we expect that far more structured RNAs remain to be discovered from bacterial and archaeal organisms.

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          Most cited references 156

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          Gapped BLAST and PSI-BLAST: a new generation of protein database search programs.

           S Altschul (1997)
          The BLAST programs are widely used tools for searching protein and DNA databases for sequence similarities. For protein comparisons, a variety of definitional, algorithmic and statistical refinements described here permits the execution time of the BLAST programs to be decreased substantially while enhancing their sensitivity to weak similarities. A new criterion for triggering the extension of word hits, combined with a new heuristic for generating gapped alignments, yields a gapped BLAST program that runs at approximately three times the speed of the original. In addition, a method is introduced for automatically combining statistically significant alignments produced by BLAST into a position-specific score matrix, and searching the database using this matrix. The resulting Position-Specific Iterated BLAST (PSI-BLAST) program runs at approximately the same speed per iteration as gapped BLAST, but in many cases is much more sensitive to weak but biologically relevant sequence similarities. PSI-BLAST is used to uncover several new and interesting members of the BRCT superfamily.
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            tRNAscan-SE: a program for improved detection of transfer RNA genes in genomic sequence.

            We describe a program, tRNAscan-SE, which identifies 99-100% of transfer RNA genes in DNA sequence while giving less than one false positive per 15 gigabases. Two previously described tRNA detection programs are used as fast, first-pass prefilters to identify candidate tRNAs, which are then analyzed by a highly selective tRNA covariance model. This work represents a practical application of RNA covariance models, which are general, probabilistic secondary structure profiles based on stochastic context-free grammars. tRNAscan-SE searches at approximately 30 000 bp/s. Additional extensions to tRNAscan-SE detect unusual tRNA homologues such as selenocysteine tRNAs, tRNA-derived repetitive elements and tRNA pseudogenes.
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              An obesity-associated gut microbiome with increased capacity for energy harvest.

              The worldwide obesity epidemic is stimulating efforts to identify host and environmental factors that affect energy balance. Comparisons of the distal gut microbiota of genetically obese mice and their lean littermates, as well as those of obese and lean human volunteers have revealed that obesity is associated with changes in the relative abundance of the two dominant bacterial divisions, the Bacteroidetes and the Firmicutes. Here we demonstrate through metagenomic and biochemical analyses that these changes affect the metabolic potential of the mouse gut microbiota. Our results indicate that the obese microbiome has an increased capacity to harvest energy from the diet. Furthermore, this trait is transmissible: colonization of germ-free mice with an 'obese microbiota' results in a significantly greater increase in total body fat than colonization with a 'lean microbiota'. These results identify the gut microbiota as an additional contributing factor to the pathophysiology of obesity.
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                Author and article information

                Journal
                Genome Biol
                Genome Biology
                BioMed Central
                1465-6906
                1465-6914
                2010
                15 March 2010
                : 11
                : 3
                : R31
                Affiliations
                [1 ]Howard Hughes Medical Institute, Yale University, P.O. Box 208103, New Haven, CT 06520-8103, USA
                [2 ]Department of Molecular, Cellular and Developmental Biology, Yale University, P.O. Box 208103, New Haven, CT 06520-8103, USA
                [3 ]Department of Molecular Biophysics and Biochemistry, Yale University, P.O. Box 208103, New Haven, CT 06520-8103, USA
                [4 ]Current address: Department of Biology, University of Rochester, Rochester, NY 14627, USA
                [5 ]Current address: School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
                Article
                gb-2010-11-3-r31
                10.1186/gb-2010-11-3-r31
                2864571
                20230605
                Copyright ©2010 Weinberg et al.; licensee BioMed Central, Ltd.

                This is an open access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                Categories
                Research

                Genetics

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