Core and Panmetabolism in Escherichia coli

Author:

Vieira Gilles1,Sabarly Victor23,Bourguignon Pierre-Yves1,Durot Maxime1,Le Fèvre François1,Mornico Damien1,Vallenet David1,Bouvet Odile2,Denamur Erick2,Schachter Vincent14,Médigue Claudine1

Affiliation:

1. CNRS UMR 8030, Université d'Evry, CEA, IG, Genoscope, 2 rue Gaston Crémieux, CP5706, F-91057 Evry Cedex, France

2. INSERM U722 and Université Paris Diderot, 16 rue Henri Huchard, 75018 Paris, France

3. INRA, UMR de Génétique Végétale, INRA/CNRS/Université Paris-Sud/AgroParistech, Ferme du Moulon, F-91190 Gif sur Yvette, France

4. Present address: TOTAL Gas and Power, 2 place Jean Miller, La Défense 6, F-92078 Paris La Défense Cedex, France.

Abstract

ABSTRACT Escherichia coli exhibits a wide range of lifestyles encompassing commensalism and various pathogenic behaviors which its highly dynamic genome contributes to develop. How environmental and host factors shape the genetic structure of E. coli strains remains, however, largely unknown. Following a previous study of E. coli genomic diversity, we investigated its diversity at the metabolic level by building and analyzing the genome-scale metabolic networks of 29 E. coli strains (8 commensal and 21 pathogenic strains, including 6 Shigella strains). Using a tailor-made reconstruction strategy, we significantly improved the completeness and accuracy of the metabolic networks over default automatic reconstruction processes. Among the 1,545 reactions forming E. coli panmetabolism, 885 reactions were common to all strains. This high proportion of core reactions (57%) was found to be in sharp contrast to the low proportion (13%) of core genes in the E. coli pangenome, suggesting less diversity of metabolic functions compared to that of all gene functions. Core reactions were significantly overrepresented among biosynthetic reactions compared to the more variable degradation processes. Differences between metabolic networks were found to follow E. coli phylogeny rather than pathogenic phenotypes, except for Shigella networks, which were significantly more distant from the others. This suggests that most metabolic changes in non- Shigella strains were not driven by their pathogenic phenotypes. Using a supervised method, we were yet able to identify small sets of reactions related to pathogenicity or commensalism. The quality of our reconstructed networks also makes them reliable bases for building metabolic models.

Publisher

American Society for Microbiology

Subject

Molecular Biology,Microbiology

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