Putative bacterial interactions from metagenomic knowledge with an integrative systems ecology approach - Inria - Institut national de recherche en sciences et technologies du numérique
Journal Articles MicrobiologyOpen Year : 2016

Putative bacterial interactions from metagenomic knowledge with an integrative systems ecology approach

Abstract

Following the trend of studies that investigate microbial ecosystems using different metagenomic techniques, we propose a new integrative systems ecology approach that aims to decipher functional roles within a consortium through the integration of genomic and metabolic knowledge at genome scale. For the sake of application, using public genomes of five bacterial strains involved in copper bioleaching: Acidiphilium cryptum, Acidithiobacillus ferrooxidans, Acidithiobacillus thiooxidans, Leptospirillum ferriphilum, and Sulfobacillus thermosulfidooxidans, we first reconstructed a global metabolic network. Next, using a parsimony assumption, we deciphered sets of genes, called Sets from Genome Segments (SGS), that (1) are close on their respective genomes, (2) take an active part in metabolic pathways and (3) whose associated metabolic reactions are also closely connected within metabolic networks. Overall, this SGS paradigm depicts genomic functional units that emphasize respective roles of bacterial strains to catalyze metabolic pathways and environmental processes. Our analysis suggested that only few functional metabolic genes are horizontally transferred within the consortium and that no single bacterial strain can accomplish by itself the whole copper bioleaching. The use of SGS pinpoints a functional compartmentalization among the investigated species and exhibits putative bacterial interactions necessary for promoting these pathways.

Dates and versions

hal-01246173 , version 1 (18-12-2015)

Identifiers

Cite

Philippe Bordron, Mauricio Latorre, Maria-Paz Cortés, Mauricio Gonzales, Sven Thiele, et al.. Putative bacterial interactions from metagenomic knowledge with an integrative systems ecology approach. MicrobiologyOpen, 2016, 5 (1), pp.106-117. ⟨10.1002/mbo3.315⟩. ⟨hal-01246173⟩
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