Metage2Metabo, microbiota-scale metabolic complementarity for the identification of key species
FRIOUX, Clémence
Quadram Institute
Dynamics, Logics and Inference for biological Systems and Sequences [Dyliss]
Pleiade, from patterns to models in computational biodiversity and biotechnology [PLEIADE]
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Quadram Institute
Dynamics, Logics and Inference for biological Systems and Sequences [Dyliss]
Pleiade, from patterns to models in computational biodiversity and biotechnology [PLEIADE]
FRIOUX, Clémence
Quadram Institute
Dynamics, Logics and Inference for biological Systems and Sequences [Dyliss]
Pleiade, from patterns to models in computational biodiversity and biotechnology [PLEIADE]
Quadram Institute
Dynamics, Logics and Inference for biological Systems and Sequences [Dyliss]
Pleiade, from patterns to models in computational biodiversity and biotechnology [PLEIADE]
BRETAUDEAU, Anthony
Plateforme bioinformatique GenOuest [Rennes]
Institut de Génétique, Environnement et Protection des Plantes [IGEPP]
< Reduce
Plateforme bioinformatique GenOuest [Rennes]
Institut de Génétique, Environnement et Protection des Plantes [IGEPP]
Language
en
Article de revue
This item was published in
eLife. 2020-12-29, vol. 9
eLife Sciences Publication
English Abstract
To capture the functional diversity of microbiota, one must identify metabolic functions and species of interest within hundreds or thousands of microorganisms. We present Metage2Metabo (M2M) a resource that meets the need ...Read more >
To capture the functional diversity of microbiota, one must identify metabolic functions and species of interest within hundreds or thousands of microorganisms. We present Metage2Metabo (M2M) a resource that meets the need for de-novo functional screening of genome-scale metabolic networks (GSMNs) at the scale of a metagenome, and the identification of critical species with respect to metabolic cooperation. M2M comprises a flexible pipeline for the characterisation of individual metabolisms and collective metabolic complementarity. In addition, M2M identifies key species, that are meaningful members of the community for functions of interest. We demonstrate that M2M is applicable to collections of genomes as well as metagenome-assembled genomes, permits an efficient GSMN reconstruction with Pathway Tools, and assesses the cooperation potential between species. M2M identifies key organisms by reducing the complexity of a large-scale microbiota into minimal communities with equivalent properties, suitable for further analyses.Read less <
English Keywords
computational biology
human
keystone species
metabolic complementarity
metabolic modelling
metagenomics
microbiota
systems biology
ANR Project
Biotechnologies pour la valorisation des macroalgues - ANR-10-BTBR-0004
Origin
Hal imported