Diet dominates host genotype in shaping the murine gut microbiota

Abstract

Mammals exhibit marked interindividual variations in their gut microbiota, but it remains unclear if this is primarily driven by host genetics or by extrinsic factors like dietary intake. To address this, we examined the effect of dietary perturbations on the gut microbiota of five inbred mouse strains, mice deficient for genes relevant to host-microbial interactions (MyD88(-/-), NOD2(-/-), ob/ob, and Rag1(-/-)), and >200 outbred mice. In each experiment, consumption of a high-fat, high-sugar diet reproducibly altered the gut microbiota despite differences in host genotype. The gut microbiota exhibited a linear dose response to dietary perturbations, taking an average of 3.5 days for each diet-responsive bacterial group to reach a new steady state. Repeated dietary shifts demonstrated that most changes to the gut microbiota are reversible, while also uncovering bacteria whose abundance depends on prior consumption. These results emphasize the dominant role that diet plays in shaping interindividual variations in host-associated microbial communities.

Figure 1. Microbial responses to the high-fat, high-sugar diet in inbred mice

(A) Microbial community structure is primarily determined by diet (see PC1; F=38.0, p-value<0.001, PERMANOVA on Bray-Curtis distances). Secondary clustering is by host genotype [see PC2; F=9.8, p-value<0.001 (LFPP) and F=2.9, p-value<0.001 (HFHS), PERMANOVA after splitting the datasets by diet]. Bray-Curtis dissimilarity-based principal coordinates analysis (PCoA) was performed on 16S rRNA gene sequencing data; the first two coordinates are shown (representing 48% of the total variance). Values are mean ± sem (n=2–13 animals/group). (B) Relative abundance of major taxonomic orders in 5 strains fed a LFPP or HFHS diet. Groups within the same bacterial phyla are indicated by different shades of the same color. Taxa with a mean relative abundance >1% are shown. (C) Diet-dependent bacterial genera with distinctive changes between genotypes. See Table S2a for the full set of taxa. Different genotypes are indicated by the shade of each line. Values in panels B,C are means (n=2–13 animals/group). See also Figure S1 and Tables S1,S2.

Figure 2. Genotype-associated shifts in the gut microbiota are robust to cage effects

(A) Microbial community structure is consistent between cages. Bray-Curtis dissimilarity-based principal coordinates analysis (PCoA) was performed on 16S rRNA gene sequencing data collected during consumption of the LFPP diet. Each point represents a different cage; colored lines connect cages housing mice from the same genotype. (B–D) Relative abundance of bacterial genera that are associated with host genotype on the LFPP diet: (B) 129S1/SvlmJ (red), (C) C57BL/6J (green), and (D) NZO/HILtJ (blue) (also see Table S3a). Values are mean ± sem (n=2–5 mice/cage; 2–4 cages/genotype). Asterisks represent significant differences (p-value<0.05, Kruskal-Wallis test with Dunn’s multiple comparisons test). See also Figure S1 and Tables S1,S3.

Figure 3. Microbial responses to the high-fat, high-sugar diet in transgenic mice

(A) Microbial community structure is primarily determined by diet (see PC1; F=60.8, p-value<0.001, PERMANOVA on Bray-Curtis distances). Secondary clustering is by host genotype (see PC2; F=17.9, p-value<0.001). Bray-Curtis dissimilarity-based principal coordinates analysis (PCoA) was performed on 16S rRNA gene sequencing data; the first two coordinates are shown (representing 37% of the total variance). Values are mean ± sem (n=15–20 samples/group). (B) Analysis of the microbial response to the HFHS diet over time, using the first principal coordinate from the Bray-Curtis-based PCoA. Points and lines are labeled based on host genotype. Values are mean ± sem (n=5 mice/group). The asterisk represents significant differences at the final timepoint relative to wild-type controls (p-value<0.05, Kruskal-Wallis test with Dunn’s multiple comparisons test). (C–F) Bray-Curtis-based PCoA of the fecal microbiota of animals on a LFPP (white filled symbols) or HFHS (black filled symbols) diet (n=15 samples/group). Wild-type controls are included in all panels, indicated by white triangles (LFPP diet) and inverted black triangles (HFHS diet). Transgenic mice include: (C) MyD88^−/− LFPP (white diamonds) and HFHS (black leftward triangles); (D) NOD2^−/− LFPP (white circles) and HFHS (black circles); (E) ob/ob LFPP (white pentagons) and HFHS (black squares); and (F) Rag1^−/− LFPP (white squares) and HFHS (black tilted triangles). See also Figure S1 and Tables S1,S2.

Figure 4. Microbial responses are proportional to the degree of dietary perturbation

(A–C) Physiological responses of mice to diets with differing HFHS contents: (A) food intake decreases as dietary HFHS content increases; nevertheless both (B) caloric intake and (C) body fat increase on HFHS-rich diets. (D) Dose-dependent relationship between dietary HFHS content and the first principal coordinate from a Bray-Curtis dissimilarity-based PCoA of microbial community composition. (E, F) Dose-dependent relationships between dietary HFHS content and the two most abundant diet-associated bacterial phyla: (E) Firmicutes increase with HFHS content; (F) Bacteroidetes decrease with HFHS content. Within each panel, the upper graph (colored circles) represents data collected during gradient feeding, whereas the lower graph (grey squares) represents data collected during the baseline week, when mice had been assigned to a diet group but had not yet initiated gradient feeding. R² and p-values reflect linear regression (n=4–5 animals/group). See also Figure S1 and Tables S1,S2.

Figure 5. A rapid and reproducible microbial response to the high-fat, high-sugar diet in outbred mice

(A) Bray-Curtis-based PCoA analysis of the fecal microbiota of animals on a LFPP (blue) or HFHS (red) diet. The first two principal coordinates are shown (representing 27% of the total variance), which clearly separate the 977 fecal samples by diet. (B) Analysis of the microbial response to the HFHS diet over time, using the first principal coordinate from the Bray-Curtis-based PCoA. Points are labeled based on the current diet: LFPP (blue) or HFHS (red). Samples were collected weekly, with daily sampling during the first week of the HFHS diet (indicated by the number of days post shift, dps). On average, 52 mice were sampled at each timepoint. Values are mean ± sem. (C) Time-map of consistently responsive species-level bacterial operational taxonomic units (OTUs) in outbred mice. The selected OTUs were present, responsive, and had consistent temporal patterns in ≥50% of mice. Each row represents a consensus temporal signature (aggregated model estimates across mice) for an OTU, ordered by agglomerative clustering of signatures. Blue indicates relative abundances below the mean abundance for the entire signature, and red indicates relative abundances above the mean. Values represent model estimates, in units of log transformed and standardized relative abundances. The taxonomic assignment for each OTU is indicated on the right of the heatmap: Bacteroidales (black), Clostridiales (orange), and Lactobacillales (pink). (D) Relaxation time constant distributions on the second HFHS diet regimen, for OTUs belonging to the bacterial orders Clostridiales and Bacteroidales (data from all OTUs are shown, including those with inconsistent behavior across mice). Relaxation time characterizes how quickly an OTU’s relative abundance reaches an equilibrium level, with shorter times indicating more rapid equilibration. See also Figures S1–4 and Tables S1,S2,S4.

Figure 6. Impact of successive dietary shifts on the gut microbiota

(A) Analysis of the microbial response to the LFPP (blue) and HFHS (red) diet over time, using the first principal coordinate from the Bray-Curtis-based PCoA. The two oscillating groups are indicated by a solid line (group 1) or a dashed line (group 2). Timepoints are colored based on the diet consumed over the prior 24 hours; i.e. oscillator group 1 was switched onto the HFHS diet on day zero. (B) Results from control mice continuously fed a LFPP (solid line) or HFHS diet (dashed line). The full time series, including additional baseline and maintenance samples, is shown in Figure S6a,b. (C,D) The abundance of (C) the Bacteroidales (phylum: Bacteroidetes) and (D) Clostridiales (phylum: Firmicutes) is shown over time. The two oscillating groups are indicated by a solid line (group 1) or a dashed line (group 2). Values are mean ± sem (n=3–5 mice per group). See also Figures S1,S5,S6 and Tables S1,S2.

Figure 7. Identification of bacterial species and genes dependent on prior dietary intake

(A) Relative abundance of species-level OTUs that were consistently present, responsive to diet, had consistent temporal patterns, and exhibited dependence of levels on serial dietary changes (see Experimental Procedures for thresholds used). Each row represents a temporal signature for an OTU (model estimate from combined data from the staggered dietary oscillation groups). Blue indicates relative abundances below the mean abundance for the entire signature, and red indicates relative abundances above the mean. Values represent model estimates, in units of log transformed and standardized relative abundances. The taxonomic assignments for each OTU are labeled on the right of each heatmap: Bacteroidales (black), Clostridiales (orange), Erysipelotrichales (blue), Coriobacteriales (green), and RF39 (brown). *OTUs with detailed graphs shown in Figure S7a–e. (B) Bacterial gene content (KEGG orthologous groups) was inferred using an ancestral state reconstruction method (Langille et al., 2013). The MC-TIMME algorithm identified 47 clusters of orthologous groups (mean of 68 orthologous groups per cluster) showing consistent differences in abundance on the LFPP versus HFHS diets. Each row in the time-map represents a consensus temporal signature for the indicated cluster. Blue indicates relative abundances below the mean abundance for the entire signature, and red indicates relative abundances above the mean. Values represent model estimates, in units of log transformed and standardized relative abundances. The top 37 clusters (above the white line) exhibited dependence of their levels over time on the serial dietary switches (hysteresis). See also Figures S1,S4,S6,S7 and Tables S1,S4.