High-Fat Diet Determines the Composition of the Murine Gut Microbiome Independently of Obesity

Background & Aims

The composition of the gut microbiome is affected by host phenotype, genotype, immune function, and diet. Here, we used the phenotype of RELMβ knockout (KO) mice to assess the influence of these factors.

Methods

Both wild-type and RELMβ KO mice were lean on a standard chow diet, but, upon switching to a high-fat diet, wild-type mice became obese, whereas RELMβ KO mice remained comparatively lean. To investigate the influence of diet, genotype, and obesity on microbiome composition, we used deep sequencing to characterize 25,790 16S rDNA sequences from uncultured bacterial communities from both genotypes on both diets.

Results

We found large alterations associated with switching to the high-fat diet, including a decrease in Bacteroidetes and an increase in both Firmicutes and Proteobacteria. This was seen for both genotypes (ie, in the presence and absence of obesity), indicating that the high-fat diet itself, and not the obese state, mainly accounted for the observed changes in the gut microbiota. The RELMβ genotype also modestly influenced microbiome composition independently of diet. Metagenomic analysis of 537,604 sequence reads documented extensive changes in gene content because of a high-fat diet, including an increase in transporters and 2-component sensor responders as well as a general decrease in metabolic genes. Unexpectedly, we found a substantial amount of murine DNA in our samples that increased in proportion on a high-fat diet.

Conclusions

These results demonstrate the importance of diet as a determinant of gut microbiome composition and suggest the need to control for dietary variation when evaluating the composition of the human gut microbiome.

Abbreviations used in this paper: ABC, ATP binding cassette, BLAST, basic local alignment search tool, db, diabetes, KEGG, Kyoto encyclopedia of genes and genomes, KO, knockout, NAST, nearest alignment space termination, PCR, polymerase chain reaction, RAST, rapid annotation using subsystems technology, rDNA, DNA encoding ribosomal RNA, SEED, database of subsystems used for metagenomic analysis