TY - JOUR TI - Metage2Metabo, microbiota-scale metabolic complementarity for the identification of key species AU - Belcour, Arnaud AU - Frioux, Clémence AU - Aite, Méziane AU - Bretaudeau, Anthony AU - Hildebrand, Falk AU - Siegel, Anne A2 - Zambrano, María Mercedes A2 - Storz, Gisela A2 - Machado, Daniel A2 - Ebenhoh, Oliver VL - 9 PY - 2020 DA - 2020/12/29 SP - e61968 C1 - eLife 2020;9:e61968 DO - 10.7554/eLife.61968 UR - https://doi.org/10.7554/eLife.61968 AB - 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. KW - systems biology KW - metabolic modelling KW - microbiota KW - metagenomics KW - keystone species KW - metabolic complementarity JF - eLife SN - 2050-084X PB - eLife Sciences Publications, Ltd ER -