RT Journal Article
SR Electronic
T1 Metage2Metabo: metabolic complementarity applied to genomes of large-scale microbiotas for the identification of keystone species
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 803056
DO 10.1101/803056
A1 Arnaud Belcour
A1 Clémence Frioux
A1 Méziane Aite
A1 Anthony Bretaudeau
A1 Anne Siegel
YR 2019
UL http://biorxiv.org/content/early/2019/10/15/803056.abstract
AB Capturing the functional diversity of microbiotas entails identifying metabolic functions and species of interest within hundreds or thousands. Starting from genomes, a way to functionally analyse genetic information is to build metabolic networks. Yet, no method enables a functional screening of such a large number of metabolic networks nor the identification of critical species with respect to metabolic cooperation.Metage2Metabo (M2M) addresses scalability issues raised by metagenomics datasets to identify keystone, essential and alternative symbionts in large microbiotas communities with respect to individual metabolism and collective metabolic complementarity. Genome-scale metabolic networks for the community can be either provided by the user or very efficiently reconstructed from a large family of genomes thanks to a multi-processing solution to run the Pathway Tools software. The pipeline was applied to 1,520 genomes from the gut microbiota and 913 metagenome-assembled genomes of the rumen microbiota. Reconstruction of metabolic networks and subsequent metabolic analyses were performed in a reasonable time.M2M identifies keystone, essential and alternative organisms by reducing the complexity of a large-scale microbiota into minimal communities with equivalent properties, suitable for further analyses.M2Mmetage2metaboGSMNGenome-Scale Metabolic NetworkMAGMetagenome-Assembled GenomeGFFGeneric Feature FormatRAMRandom-Access MemoryPGDBPathway Genome DataBaseSBMLSystems Biology Markup LanguageGUIGraphical User InterfacePNPower Node