Linking long-term dietary patterns with gut microbial enterotypes

Abstract

Diet strongly affects human health, partly by modulating gut microbiome composition. We used diet inventories and 16S rDNA sequencing to characterize fecal samples from 98 individuals. Fecal communities clustered into enterotypes distinguished primarily by levels of Bacteroides and Prevotella. Enterotypes were strongly associated with long-term diets, particularly protein and animal fat (Bacteroides) versus carbohydrates (Prevotella). A controlled-feeding study of 10 subjects showed that microbiome composition changed detectably within 24 hours of initiating a high-fat/low-fiber or low-fat/high-fiber diet, but that enterotype identity remained stable during the 10-day study. Thus, alternative enterotype states are associated with long-term diet.

Figures

Fig. 1

Correlation of diet and gut microbial taxa identified in the cross-sectional COMBO analysis. Columns correspond to bacterial taxa quantified using 16S rDNA tags; rows correspond to nutrients measured by dietary questionnaire. Red and blue denote positive and negative association, respectively. The intensity of the colors represents the degree of association between the taxa abundances and nutrients as measured by the Spearman's correlations. Bacterial phyla are summarized by the color code on the bottom; lower-level taxonomic assignments specified are in fig. S1. The dots indicate the associations that are significant at an FDR of 25%. The FFQ data were used for this comparison (both FFQ and Recall dietary data are shown together in fig. S1). Columns and rows are clustered by Euclidean distance, with rows separated by the predominant nutrient category.

Fig. 2

Clustering of gut microbial taxa into entero-types is associated with long-term diet. (A) Clustering in the COMBO cross-sectional study using Jensen-Shannon distance. The left panel shows that the data are most naturally separated into two clusters by the PAM method. The x axis shows cluster number; the y axis shows silhouette width, a measure of cluster separation (12). The right panel shows the clustering on the first two principal components. (B) Proportions of bacterial taxa characteristic of each enterotype. Boxes represent the interquartile range (IQR) and the line inside represents the median. Whiskers denote the lowest and highest values within 1.5 × IQR. (C) The association of dietary components with each enterotype. The strength and direction of each association, as measured by the means of the standardized nutrient measurements, is shown by the color key at the lower right. Enterotype is shown at the right. Red indicates greater amounts, blue lesser amounts of each nutrient in each enterotype (complete lists of nutrients are in table S2). Columns were clustered by Euclidean distance.

Fig. 3

Changes in bacterial communities during controlled feeding. Ten subjects were randomized to high-fat/low-fiber or low-fat/high-fiber diets, and microbiome composition was monitored longitudinally for 10 days by sequencing 16S rDNA gene tags (CAFE study). (A) Cluster diagram–based principal coordinates analysis using unweighted UniFrac. Colors indicate samples from each individual. (B) Day 1 samples are outliers compared to all other days, indicating change in the gut microbiome within 24 hours of initiating controlled feeding. In this analysis, weighted UniFrac distances between samples are compared within subjects in two groups. The first collection of distances compares the day 1 samples to days 2 to 10; the second group compares samples from all days to all others excluding day 1, indicating rapid change (P = 0.0003, 10,000 permutations). Error bars indicate 1 SD of the distances.