Cargando…

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...

Descripción completa

Detalles Bibliográficos
Autores principales: Boutte, Cara C., Srinivasan, Balaji S., Flannick, Jason A., Novak, Antal F., Martens, Andrew T., Batzoglou, Serafim, Viollier, Patrick H., Crosson, Sean
Formato: Texto
Lenguaje:English
Publicado: Public Library of Science 2008
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
_version_ 1782161891755294720
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
work_keys_str_mv AT bouttecarac geneticandcomputationalidentificationofaconservedbacterialmetabolicmodule
AT srinivasanbalajis geneticandcomputationalidentificationofaconservedbacterialmetabolicmodule
AT flannickjasona geneticandcomputationalidentificationofaconservedbacterialmetabolicmodule
AT novakantalf geneticandcomputationalidentificationofaconservedbacterialmetabolicmodule
AT martensandrewt geneticandcomputationalidentificationofaconservedbacterialmetabolicmodule
AT batzoglouserafim geneticandcomputationalidentificationofaconservedbacterialmetabolicmodule
AT viollierpatrickh geneticandcomputationalidentificationofaconservedbacterialmetabolicmodule
AT crossonsean geneticandcomputationalidentificationofaconservedbacterialmetabolicmodule