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Genetic and Computational Identification of a Conserved Bacterial Metabolic Module
We have experimentally and computationally defined a set of genes that form a conserved metabolic module in the α-proteobacterium Caulobacter crescentus and used this module to illustrate a schema for the propagation of pathway-level annotation across bacterial genera. Applying comprehensive forward...
Autores principales: | , , , , , , , |
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Formato: | Texto |
Lenguaje: | English |
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Public Library of Science
2008
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2597717/ https://www.ncbi.nlm.nih.gov/pubmed/19096521 http://dx.doi.org/10.1371/journal.pgen.1000310 |
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author | Boutte, Cara C. Srinivasan, Balaji S. Flannick, Jason A. Novak, Antal F. Martens, Andrew T. Batzoglou, Serafim Viollier, Patrick H. Crosson, Sean |
author_facet | Boutte, Cara C. Srinivasan, Balaji S. Flannick, Jason A. Novak, Antal F. Martens, Andrew T. Batzoglou, Serafim Viollier, Patrick H. Crosson, Sean |
author_sort | Boutte, Cara C. |
collection | PubMed |
description | We have experimentally and computationally defined a set of genes that form a conserved metabolic module in the α-proteobacterium Caulobacter crescentus and used this module to illustrate a schema for the propagation of pathway-level annotation across bacterial genera. Applying comprehensive forward and reverse genetic methods and genome-wide transcriptional analysis, we (1) confirmed the presence of genes involved in catabolism of the abundant environmental sugar myo-inositol, (2) defined an operon encoding an ABC-family myo-inositol transmembrane transporter, and (3) identified a novel myo-inositol regulator protein and cis-acting regulatory motif that control expression of genes in this metabolic module. Despite being encoded from non-contiguous loci on the C. crescentus chromosome, these myo-inositol catabolic enzymes and transporter proteins form a tightly linked functional group in a computationally inferred network of protein associations. Primary sequence comparison was not sufficient to confidently extend annotation of all components of this novel metabolic module to related bacterial genera. Consequently, we implemented the Graemlin multiple-network alignment algorithm to generate cross-species predictions of genes involved in myo-inositol transport and catabolism in other α-proteobacteria. Although the chromosomal organization of genes in this functional module varied between species, the upstream regions of genes in this aligned network were enriched for the same palindromic cis-regulatory motif identified experimentally in C. crescentus. Transposon disruption of the operon encoding the computationally predicted ABC myo-inositol transporter of Sinorhizobium meliloti abolished growth on myo-inositol as the sole carbon source, confirming our cross-genera functional prediction. Thus, we have defined regulatory, transport, and catabolic genes and a cis-acting regulatory sequence that form a conserved module required for myo-inositol metabolism in select α-proteobacteria. Moreover, this study describes a forward validation of gene-network alignment, and illustrates a strategy for reliably transferring pathway-level annotation across bacterial species. |
format | Text |
id | pubmed-2597717 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2008 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-25977172008-12-19 Genetic and Computational Identification of a Conserved Bacterial Metabolic Module Boutte, Cara C. Srinivasan, Balaji S. Flannick, Jason A. Novak, Antal F. Martens, Andrew T. Batzoglou, Serafim Viollier, Patrick H. Crosson, Sean PLoS Genet Research Article We have experimentally and computationally defined a set of genes that form a conserved metabolic module in the α-proteobacterium Caulobacter crescentus and used this module to illustrate a schema for the propagation of pathway-level annotation across bacterial genera. Applying comprehensive forward and reverse genetic methods and genome-wide transcriptional analysis, we (1) confirmed the presence of genes involved in catabolism of the abundant environmental sugar myo-inositol, (2) defined an operon encoding an ABC-family myo-inositol transmembrane transporter, and (3) identified a novel myo-inositol regulator protein and cis-acting regulatory motif that control expression of genes in this metabolic module. Despite being encoded from non-contiguous loci on the C. crescentus chromosome, these myo-inositol catabolic enzymes and transporter proteins form a tightly linked functional group in a computationally inferred network of protein associations. Primary sequence comparison was not sufficient to confidently extend annotation of all components of this novel metabolic module to related bacterial genera. Consequently, we implemented the Graemlin multiple-network alignment algorithm to generate cross-species predictions of genes involved in myo-inositol transport and catabolism in other α-proteobacteria. Although the chromosomal organization of genes in this functional module varied between species, the upstream regions of genes in this aligned network were enriched for the same palindromic cis-regulatory motif identified experimentally in C. crescentus. Transposon disruption of the operon encoding the computationally predicted ABC myo-inositol transporter of Sinorhizobium meliloti abolished growth on myo-inositol as the sole carbon source, confirming our cross-genera functional prediction. Thus, we have defined regulatory, transport, and catabolic genes and a cis-acting regulatory sequence that form a conserved module required for myo-inositol metabolism in select α-proteobacteria. Moreover, this study describes a forward validation of gene-network alignment, and illustrates a strategy for reliably transferring pathway-level annotation across bacterial species. Public Library of Science 2008-12-19 /pmc/articles/PMC2597717/ /pubmed/19096521 http://dx.doi.org/10.1371/journal.pgen.1000310 Text en Boutte et al. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. |
spellingShingle | Research Article Boutte, Cara C. Srinivasan, Balaji S. Flannick, Jason A. Novak, Antal F. Martens, Andrew T. Batzoglou, Serafim Viollier, Patrick H. Crosson, Sean Genetic and Computational Identification of a Conserved Bacterial Metabolic Module |
title | Genetic and Computational Identification of a Conserved Bacterial Metabolic Module |
title_full | Genetic and Computational Identification of a Conserved Bacterial Metabolic Module |
title_fullStr | Genetic and Computational Identification of a Conserved Bacterial Metabolic Module |
title_full_unstemmed | Genetic and Computational Identification of a Conserved Bacterial Metabolic Module |
title_short | Genetic and Computational Identification of a Conserved Bacterial Metabolic Module |
title_sort | genetic and computational identification of a conserved bacterial metabolic module |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2597717/ https://www.ncbi.nlm.nih.gov/pubmed/19096521 http://dx.doi.org/10.1371/journal.pgen.1000310 |
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