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Four functional profiles for fibre and mucin metabolism in the human gut microbiome

hal.structure.identifierPleiade, from patterns to models in computational biodiversity and biotechnology [PLEIADE]
hal.structure.identifierBiodiversité, Gènes & Communautés [BioGeCo]
hal.structure.identifierMathématiques et Informatique Appliquées du Génome à l'Environnement [Jouy-En-Josas] [MaIAGE]
dc.contributor.authorLABARTHE, Simon
hal.structure.identifierUnité de Mathématiques et Informatique Appliquées de Toulouse [MIAT INRAE]
hal.structure.identifierMathématiques et Informatique Appliquées du Génome à l'Environnement [Jouy-En-Josas] [MaIAGE]
dc.contributor.authorPLANCADE, Sandra
hal.structure.identifierMathématiques et Informatique Appliquées du Génome à l'Environnement [Jouy-En-Josas] [MaIAGE]
hal.structure.identifierEarlham Institute [Norwich]
hal.structure.identifierPleiade, from patterns to models in computational biodiversity and biotechnology [PLEIADE]
dc.contributor.authorRAGUIDEAU, Sébastien
dc.contributor.authorPLAZA OÑATE, Florian
hal.structure.identifierMetaGenoPolis [MGP (US 1367)]
dc.contributor.authorLE CHATELIER, Emmanuelle
hal.structure.identifierMICrobiologie de l'ALImentation au Service de la Santé [MICALIS]
hal.structure.identifierPendulum Therapeutics [San Francisco]
dc.contributor.authorLECLERC, Marion
hal.structure.identifierMathématiques et Informatique Appliquées du Génome à l'Environnement [Jouy-En-Josas] [MaIAGE]
hal.structure.identifierDynamiques de populations multi-échelles pour des systèmes physiologiques [MUSCA]
dc.contributor.authorLAROCHE, Béatrice
dc.date.issued2023-12
dc.description.abstractEnBackground With the emergence of metagenomic data, multiple links between the gut microbiome and the host health have been shown. Deciphering these complex interactions require evolved analysis methods focusing on the microbial ecosystem functions. Despite the fact that host or diet-derived fibres are the most abundant nutrients available in the gut, the presence of distinct functional traits regarding fibre and mucin hydrolysis, fermentation and hydrogenotrophic processes has never been investigated. Results After manually selecting 91 KEGG orthologies and 33 glycoside hydrolases further aggregated in 101 functional descriptors representative of fibre and mucin degradation pathways in the gut microbiome, we used non-negative matrix factorization to mine metagenomic datasets. Four distinct metabolic profiles were further identified on a training set of 1153 samples and thoroughly validated on a large database of 2571 unseen samples from 5 external metagenomic cohorts. Profiles 1 and 2 are the main contributors to the fibre-degradation-related metagenome: they present contrasted involvement in fibre degradation and sugar metabolism and are differentially linked to dysbiosis, metabolic disease and inflammation. Profile 1 takes over Profile 2 inhealthy samples, and unbalance of these profiles characterize dysbiotic samples. Furthermore, high fibre diet favours a healthy balance between Profiles 1 and Profile 2. Profile 3 takes over Profile 2 during Crohn’s disease, inducing functional reorientations towards unusual metabolism such as fucose and H2S degradation or propionate, acetone and butanediol production. Profile 4 gathers under-represented functions, like methanogenesis. Two taxonomic makes up of the profiles were investigated, using either the covariation of 203 prevalent genomes or metagenomic species, both providing consistent results in line with their functional characteristics. This taxonomic characterization showed that Profiles 1 and 2 were respectively mainly composed of bacteria from the phyla Bacteroidetes and Firmicutes while Profile 3 is representative of Proteobacteria and Profile 4 of methanogens.Conclusions Integrating anaerobic microbiology knowledge with statistical learning can narrow down the metagenomic analysis to investigate functional profiles. Applying this approach to fibre degradation in the gut ended with 4 distinct functional profiles that can be easily monitored as markers of diet, dysbiosis, inflammation and disease.
dc.description.sponsorshipMetaGenoPolis - ANR-11-DPBS-0001
dc.language.isoen
dc.publisherBioMed Central
dc.rights.urihttp://creativecommons.org/licenses/by/
dc.subject.enMetagenomics
dc.subject.enNMF
dc.subject.enFunctional profling
dc.subject.enStatistical learning
dc.title.enFour functional profiles for fibre and mucin metabolism in the human gut microbiome
dc.typeArticle de revue
dc.identifier.doi10.1186/s40168-023-01667-y
dc.subject.halInformatique [cs]/Modélisation et simulation
dc.subject.halInformatique [cs]/Bio-informatique [q-bio.QM]
dc.subject.halSciences du Vivant [q-bio]
dc.description.sponsorshipEuropeAgreenSkills+
bordeaux.journalMicrobiome
bordeaux.page231
bordeaux.volume11
bordeaux.issue1
bordeaux.peerReviewedoui
hal.identifierhal-03918193
hal.version1
hal.popularnon
hal.audienceInternationale
hal.origin.linkhttps://hal.archives-ouvertes.fr//hal-03918193v1
bordeaux.COinSctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.jtitle=Microbiome&rft.date=2023-12&rft.volume=11&rft.issue=1&rft.spage=231&rft.epage=231&rft.au=LABARTHE,%20Simon&PLANCADE,%20Sandra&RAGUIDEAU,%20S%C3%A9bastien&PLAZA%20O%C3%91ATE,%20Florian&LE%20CHATELIER,%20Emmanuelle&rft.genre=article


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