Data from: Impact of diet and individual variation on intestinal microbiota composition and fermentation products in obese men

There is growing interest in understanding how diet affects the intestinal microbiota, including its possible associations with systemic diseases such as metabolic syndrome. Here we report a comprehensive and deep microbiota analysis of fourteen obese males consuming fully controlled diets supplemented with resistant starch (RS) or non-starch polysaccharides (NSP), and a weight-loss diet (WL). We analyzed the composition, diversity and dynamics of the faecal microbiota on each dietary regime by phylogenetic microarray and quantitative PCR analysis. Additionally, we analyzed faecal short chain fatty acids (SCFA) as a proxy of colonic fermentation, and indices of insulin sensitivity from blood samples. The diet explained around 10% of the total variance in microbiota composition, which was substantially less than the inter-individual variance. Yet, each of the study diets induced clear and distinct changes in the microbiota. Multiple Ruminococcaceae phylotypes increased on the RS diet, whereas mostly Lachnospiraceae phylotypes increased on the NSP diet. Bifidobacteria decreased significantly on the WL diet. The RS diet decreased significantly diversity of the microbiota. The total 16S rRNA gene signal estimated by qPCR correlated positively with the three major SCFAs, while the amount of propionate specifically correlated with the Bacteroidetes. The dietary responsiveness of the individual’s microbiota varied substantially and associated inversely with its diversity, suggesting that individuals can be stratified into responders and non-responders based on the features of their intestinal microbiota.,HITChip microarray dataThe file contains phylogenetic microarray signal intensities for 130 intestinal genus-like bacterial groups (≥ 90% sequence similarity in the 16S rRNA gene) derived from the 55 faecal samples analysed during four different diets, for details see Supplementary Figure S1 in the article. The sample ID indicates volunteer number followed by a letter code for dietary regime as well as number of days passed from beginning of the trial. More information about the phylogenetic design of the HITChip can be found at http://onlinelibrary.wiley.com/doi/10.1111/j.1462-2920.2009.01900.x/full. The data were extracted with using min-max normalisation (Bolstad et al. 2003, Bioinformatics 19:185) and log-transformed.ISMEJ_Salonen_HITChip L2_Dryad.txt