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Inferring ancient metabolism using ancestral core metabolic models of enterobacteria

BACKGROUND: Enterobacteriaceae diversified from an ancestral lineage ~300-500 million years ago (mya) into a wide variety of free-living and host-associated lifestyles. Nutrient availability varies across niches, and evolution of metabolic networks likely played a key role in adaptation. RESULTS: He...

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Autores principales: Baumler, David J, Ma, Bing, Reed, Jennifer L, Perna, Nicole T
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3694032/
https://www.ncbi.nlm.nih.gov/pubmed/23758866
http://dx.doi.org/10.1186/1752-0509-7-46
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author Baumler, David J
Ma, Bing
Reed, Jennifer L
Perna, Nicole T
author_facet Baumler, David J
Ma, Bing
Reed, Jennifer L
Perna, Nicole T
author_sort Baumler, David J
collection PubMed
description BACKGROUND: Enterobacteriaceae diversified from an ancestral lineage ~300-500 million years ago (mya) into a wide variety of free-living and host-associated lifestyles. Nutrient availability varies across niches, and evolution of metabolic networks likely played a key role in adaptation. RESULTS: Here we use a paleo systems biology approach to reconstruct and model metabolic networks of ancestral nodes of the enterobacteria phylogeny to investigate metabolism of ancient microorganisms and evolution of the networks. Specifically, we identified orthologous genes across genomes of 72 free-living enterobacteria (16 genera), and constructed core metabolic networks capturing conserved components for ancestral lineages leading to E. coli/Shigella (~10 mya), E. coli/Shigella/Salmonella (~100 mya), and all enterobacteria (~300-500 mya). Using these models we analyzed the capacity for carbon, nitrogen, phosphorous, sulfur, and iron utilization in aerobic and anaerobic conditions, identified conserved and differentiating catabolic phenotypes, and validated predictions by comparison to experimental data from extant organisms. CONCLUSIONS: This is a novel approach using quantitative ancestral models to study metabolic network evolution and may be useful for identification of new targets to control infectious diseases caused by enterobacteria.
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spelling pubmed-36940322013-06-27 Inferring ancient metabolism using ancestral core metabolic models of enterobacteria Baumler, David J Ma, Bing Reed, Jennifer L Perna, Nicole T BMC Syst Biol Research Article BACKGROUND: Enterobacteriaceae diversified from an ancestral lineage ~300-500 million years ago (mya) into a wide variety of free-living and host-associated lifestyles. Nutrient availability varies across niches, and evolution of metabolic networks likely played a key role in adaptation. RESULTS: Here we use a paleo systems biology approach to reconstruct and model metabolic networks of ancestral nodes of the enterobacteria phylogeny to investigate metabolism of ancient microorganisms and evolution of the networks. Specifically, we identified orthologous genes across genomes of 72 free-living enterobacteria (16 genera), and constructed core metabolic networks capturing conserved components for ancestral lineages leading to E. coli/Shigella (~10 mya), E. coli/Shigella/Salmonella (~100 mya), and all enterobacteria (~300-500 mya). Using these models we analyzed the capacity for carbon, nitrogen, phosphorous, sulfur, and iron utilization in aerobic and anaerobic conditions, identified conserved and differentiating catabolic phenotypes, and validated predictions by comparison to experimental data from extant organisms. CONCLUSIONS: This is a novel approach using quantitative ancestral models to study metabolic network evolution and may be useful for identification of new targets to control infectious diseases caused by enterobacteria. BioMed Central 2013-06-11 /pmc/articles/PMC3694032/ /pubmed/23758866 http://dx.doi.org/10.1186/1752-0509-7-46 Text en Copyright © 2013 Baumler et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 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.
spellingShingle Research Article
Baumler, David J
Ma, Bing
Reed, Jennifer L
Perna, Nicole T
Inferring ancient metabolism using ancestral core metabolic models of enterobacteria
title Inferring ancient metabolism using ancestral core metabolic models of enterobacteria
title_full Inferring ancient metabolism using ancestral core metabolic models of enterobacteria
title_fullStr Inferring ancient metabolism using ancestral core metabolic models of enterobacteria
title_full_unstemmed Inferring ancient metabolism using ancestral core metabolic models of enterobacteria
title_short Inferring ancient metabolism using ancestral core metabolic models of enterobacteria
title_sort inferring ancient metabolism using ancestral core metabolic models of enterobacteria
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3694032/
https://www.ncbi.nlm.nih.gov/pubmed/23758866
http://dx.doi.org/10.1186/1752-0509-7-46
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