| Literature DB >> 33372654 |
Arnaud Belcour1, Clémence Frioux1,2,3,4, Méziane Aite1, Anthony Bretaudeau1,5,6, Falk Hildebrand3,4, Anne Siegel1.
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 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.Entities:
Keywords: computational biology; human; keystone species; metabolic complementarity; metabolic modelling; metagenomics; microbiota; systems biology
Mesh:
Year: 2020 PMID: 33372654 PMCID: PMC7861615 DOI: 10.7554/eLife.61968
Source DB: PubMed Journal: Elife ISSN: 2050-084X Impact factor: 8.140