Complex gene–environment interactions are considered important in the development of obesity1. The composition of the gut microbiota can determine the efficacy of energy harvest from food2,3,4 and changes in dietary composition have been associated with changes in the composition of gut microbial populations5,6. The capacity to explore microbiota composition was markedly improved by the development of metagenomic approaches7,8, which have already allowed production of the first human gut microbial gene catalogue9 and stratifying individuals by their gut genomic profile into different enterotypes10, but the analyses were carried out mainly in non-intervention settings. To investigate the temporal relationships between food intake, gut microbiota and metabolic and inflammatory phenotypes, we conducted diet-induced weight-loss and weight-stabilization interventions in a study sample of 38 obese and 11 overweight individuals. Here we report that individuals with reduced microbial gene richness (40%) present more pronounced dys-metabolism and low-grade inflammation, as observed concomitantly in the accompanying paper11. Dietary intervention improves low gene richness and clinical phenotypes, but seems to be less efficient for inflammation variables in individuals with lower gene richness. Low gene richness may therefore have predictive potential for the efficacy of intervention.
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European Nucleotide Archive
The raw solid read data for all samples has been deposited in the European Bioinformatics Institute (EBI) European Nucleotide Archive (ENA) under the accession number ERP003699.
We are grateful to O. Pedersen (Univ. Copenhagen) for helpful comments on this manuscript and to the MetaHIT consortium for providing the gene profiles of the Danish subjects used to test the ROC models in advance of publication and the DNA samples sequenced on the SOLiD platform for comparison with the Illumina platform used in the accompanying manuscript. We thank C. Baudoin, P. Ancel and V. Pelloux who contributed to the clinical investigation study; S. Fellahi and J.-P. Bastard for analyses of inflammatory markers; D. Bonnefont-Rousselot and R. Bittar for help with the analysis of plasma lipid profile. This work was supported by Agence Nationale de la Recherche (ANR MICRO-Obes, ANR, Nutra2sens, ANR-10-IAHU-05), the Metagenopolis grant ANR-11-DPBS-0001, KOT-Ceprodi (Florence Massiera), Danone Research (Damien Paineau) and the associations Fondacoeur, and Louis-Bonduelle. Additional funding came from the European Commission FP7 grant HEALTH-F4-2007-201052 and METACARDIS.
About this article
Mucosal Immunology (2019)