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Colonic metaproteomic signatures of active bacteria and the host in obesity
Author(s) -
Kolmeder Carolin A.,
Ritari Jarmo,
Verdam Froukje J.,
Muth Thilo,
Keskitalo Salla,
Varjosalo Markku,
Fuentes Susana,
Greve Jan Willem,
Buurman Wim A.,
Reichl Udo,
Rapp Erdmann,
Martens Lennart,
Palva Airi,
Salonen Anne,
Rensen Sander S.,
Vos Willem M.
Publication year - 2015
Publication title -
proteomics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.26
H-Index - 167
eISSN - 1615-9861
pISSN - 1615-9853
DOI - 10.1002/pmic.201500049
Subject(s) - metaproteomics , biology , phylogenetic tree , bacteroidetes , gene , host (biology) , computational biology , phylogenetics , genetics , gut flora , metagenomics , 16s ribosomal rna , biochemistry
Obesity is associated with the intestinal microbiota in humans but the underlying mechanisms are yet to be fully understood. Our previous phylogenetic study showed that the faecal microbiota profiles of nonobese versus obese and morbidly obese individuals differed. Here, we have extended this analysis with a characterization of the faecal metaproteome, in order to detect differences at a functional level. Proteins were extracted from crude faecal samples of 29 subjects, separated by 1D gel electrophoresis and characterized using RP LC–MS/MS. The peptide data were analyzed in database searches with two complementary algorithms, OMSSA and X!Tandem, to increase the number of identifications. Evolutionary genealogy of genes: nonsupervised orthologous groups (EggNOG) database searches resulted in the functional annotation of over 90% of the identified microbial and human proteins. Based on both bacterial and human proteins, a clear clustering of obese and nonobese samples was obtained that exceeded the phylogenetic separation in dimension. Moreover, integration of the metaproteomics and phylogenetic datasets revealed notably that the phylum Bacteroidetes was metabolically more active in the obese than nonobese subjects. Finally, significant correlations between clinical measurements and bacterial gene functions were identified. This study emphasizes the importance of integrating data of the host and microbiota to understand their interactions.