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An integrated workflow for enhanced taxonomic and functional coverage of the mouse fecal metaproteome

dc.contributor.authorNalpas, Nicolas
dc.contributor.authorHoyles, Lesley
dc.contributor.authorAnselm, Viktoria
dc.contributor.authorGanief, Tariq
dc.contributor.authorMartinez-Gili, Laura
dc.contributor.authorGrau, Cristina
dc.contributor.authorDroste-Borel, Irina
dc.contributor.authorDavidovic, Laetitia
dc.contributor.authorAltafaj, Xavier
dc.contributor.authorDumas, Marc-Emmanuel
dc.contributor.authorMacek, Boris
dc.date.accessioned2021-03-30T15:45:35Z
dc.date.available2021-03-30T15:45:35Z
dc.date.issued2021-11-17
dc.date.updated2021-03-30T15:45:35Z
dc.description.abstractThe intestinal microbiota plays a key role in shaping host homeostasis by regulating metabolism, immune responses and behaviour. Its dysregulation has been associated with metabolic, immune and neuropsychiatric disorders and is accompanied by changes in bacterial metabolic regulation. Although proteomics is well suited for analysis of individual microbes, metaproteomics of faecal samples is challenging due to the physical structure of the sample, presence of contaminating host proteins and coexistence of hundreds of species. Furthermore, there is a lack of consensus regarding preparation of faecal samples, as well as downstream bioinformatic analyses following metaproteomic data acquisition. Here we assess sample preparation and data analysis strategies applied to mouse faeces in a typical LC-MS/MS metaproteomic experiment. We show that low speed centrifugation (LSC) of faecal samples leads to high protein identification rates and a balanced taxonomic representation. During database search, protein sequence databases derived from matched mouse faecal metagenomes provided up to four times more MS/MS identifications compared to other database construction strategies, while a two-step database search strategy led to accumulation of false positive protein identifications. Comparison of matching metaproteome and metagenome data revealed a positive correlation between protein and gene abundances, as well as significant overlap and correlation in taxonomic representation. Notably, nearly all functional categories of detected protein groups were differentially abundant in the metaproteome compared to what would be expected from the metagenome, highlighting the need to perform metaproteomics when studying complex microbiome samples.
dc.format.extent23 p.
dc.format.mimetypeapplication/pdf
dc.identifier.idgrec718019
dc.identifier.urihttps://hdl.handle.net/2445/175918
dc.language.isoeng
dc.publisherTaylor & Francis
dc.relation.isformatofReproducció del document publicat a: https://doi.org/10.1080/19490976.2021.1994836
dc.relation.ispartofGut Microbes, 2021, vol. 13, num. 1, 1994836
dc.relation.projectIDinfo:eu-repo/grantAgreement/EC/FP7/291840/EU//ERA-NET NEURON II
dc.relation.urihttps://doi.org/10.1080/19490976.2021.1994836
dc.rightscc-by-nc (c) Nalpas et al., 2020
dc.rights.accessRightsinfo:eu-repo/semantics/openAccess
dc.rights.urihttp://creativecommons.org/licenses/by-nc/3.0/es/*
dc.sourceArticles publicats en revistes (Biomedicina)
dc.subject.classificationMicrobiota intestinal
dc.subject.otherGastrointestinal microbiome
dc.titleAn integrated workflow for enhanced taxonomic and functional coverage of the mouse fecal metaproteome
dc.typeinfo:eu-repo/semantics/publishedVersion
dc.typeinfo:eu-repo/semantics/article

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