title: 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.
authors.affiliation: Mathomics, Center for Mathematical Modeling, Universidad de Chile, Santiago, Chile.|Center for Genome Regulation (Fondap 15090007), Universidad de Chile, Santiago, Chile.
authors.forename: Philippe
authors.initials: P
authors.lastname: Bordron
authors.affiliation: Mathomics, Center for Mathematical Modeling, Universidad de Chile, Santiago, Chile.|Center for Genome Regulation (Fondap 15090007), Universidad de Chile, Santiago, Chile.|Laboratorio de Bioinformática y Expresión Génica, INTA, Universidad de Chile, Santiago, Chile.
authors.forename: Mauricio
authors.initials: M
authors.lastname: Latorre
authors.affiliation: Mathomics, Center for Mathematical Modeling, Universidad de Chile, Santiago, Chile.|Center for Genome Regulation (Fondap 15090007), Universidad de Chile, Santiago, Chile.
authors.forename: Maria-Paz
authors.initials: MP
authors.lastname: Cortés
authors.affiliation: Center for Genome Regulation (Fondap 15090007), Universidad de Chile, Santiago, Chile.|Laboratorio de Bioinformática y Expresión Génica, INTA, Universidad de Chile, Santiago, Chile.
authors.forename: Mauricio
authors.initials: M
authors.lastname: González
authors.affiliation: Max Planck Institute for Dynamics of Complex Technical Systems, Magdeburg, Germany.
authors.forename: Sven
authors.initials: S
authors.lastname: Thiele
authors.affiliation: IRISA, UMR 6074, CNRS, Rennes, France.|INRIA, Dyliss Team, Centre Rennes-Bretagne-Atlantique, Rennes, France.
authors.forename: Anne
authors.initials: A
authors.lastname: Siegel
authors.affiliation: Mathomics, Center for Mathematical Modeling, Universidad de Chile, Santiago, Chile.|Center for Genome Regulation (Fondap 15090007), Universidad de Chile, Santiago, Chile.|Department of Mathematical Engineering, Universidad de Chile, Santiago, Chile.
authors.forename: Alejandro
authors.initials: A
authors.lastname: Maass
authors.affiliation: LINA, UMR CNRS 6241, EMN, Université de Nantes, Nantes, France.
authors.forename: Damien
authors.initials: D
authors.lastname: Eveillard
mesh_terms: D041801:Acidiphilium / Q000235:genetics* / Q000378:metabolism; D042763:Acidithiobacillus / Q000235:genetics* / Q000378:metabolism; D000068016:Eubacteriales / Q000235:genetics* / Q000378:metabolism; D003300:Copper / Q000378:metabolism*; D004269:DNA, Bacterial / Q000235:genetics; D017753:Ecosystem; D016680:Genome, Bacterial / Q000235:genetics*; D053858:Metabolic Networks and Pathways / Q000235:genetics*; D056186:Metagenomics
chemical_list: D004269:DNA, Bacterial; D003300:Copper
keywords: Environmental microbiology; in silico analysis; metabolic pathways; molecular microbial ecology