Genetic variation drives phenotypic diversity and influences the predisposition to metabolic disease. Here, we characterize the metabolic phenotypes of eight genetically distinct inbred mouse strains in response to a high-fat/high-sucrose diet. We found significant variation in diabetes-related phenotypes and gut microbiota composition among the different mouse strains in response to the dietary challenge and identified taxa associated with these traits. Follow-up microbiota transplant experiments showed that altering the composition of the gut microbiota modifies strain-specific susceptibility to diet-induced metabolic disease. Animals harboring microbial communities with enhanced capacity for processing dietary sugars and for generating hydrophobic bile acids showed increased susceptibility to metabolic disease. Notably, differences in glucose-stimulated insulin secretion between different mouse strains were partially recapitulated via gut microbiota transfer. Our results suggest that the gut microbiome contributes to the genetic and phenotypic diversity observed among mouse strains and provide a link between the gut microbiome and insulin secretion.

We examined the metabolic phenotypes and gut microbiota composition of the eight CC founder strains in response to chronic consumption of two defined diets: a high-fat/high-sucrose diet (HF/HS) and a control diet. We found remarkable variation in diabetes-related phenotypes and gut microbiota composition as a function of host genotype and diet, and we identified bacterial taxa that correlate with metabolic traits, including body weight, glucose, and insulin levels. Germ-free (GF) mice were colonized with microbiota derived from two founder strains that exhibited divergent metabotypes, C57BL/6J and CAST/EiJ. The transplanted animals were maintained on the HF/HS diet and then subjected to metabolomic and metagenomic analyses. We identified functional differences attributable to the two transplanted microbial communities, including insulin secretion responses and susceptibility to diet-induced metabolic disease.

Mouse genetics can be employed to explore the relationships between diet, host genetics, and metabolic responses (). The Collaborative Cross (CC) is a systems genetics mouse resource that consists of a panel of recombinant inbred lines and an outbred stock derived from eight genetically diverse founder strains. These include five classical inbred strains (A/J, C57BL/6J, 129S1/SvImJ, non-obese diabetic [NOD]/ShiLtJ, and NZO/HILtJ) and three wild-derived strains (CAST/EiJ, PWK/PhJ, and WSB/EiJ;).

Gut microbes also impact host physiology by modifying bile acids (BAs) synthesized by the host (). In addition to their role in emulsifying lipids, BAs function as hormones through their ability to activate nuclear hormone receptors () and G-coupled protein receptors (). They modulate glucose homeostasis, lipid metabolism, energy expenditure, and intestinal motility (). Primary BAs are synthesized from cholesterol in the liver (), stored in the gallbladder, and secreted into the duodenum upon ingestion of a meal. The gut microbiota catalyzes the production of secondary BAs via deconjugation, dehydrogenation, epimerization, and dehydroxylation of primary BAs (). BAs with different modifications vary in their ability to activate receptors and affect host physiology (). Subjects with T2D have altered circulating BA profiles. Treatment of T2D subjects with compounds that increase fecal excretion of BAs and modify BA composition improves their glycemic status ().

Dietary components that are not efficiently absorbed in the proximal intestine reach the distal gut, where they are metabolized by gut microbes. Intestinal microbes impact our health in part by generating numerous metabolites from our diet. Short-chain fatty acids (SCFAs), mainly acetate, propionate, and butyrate, are produced through bacterial fermentation of dietary carbohydrates. SCFAs serve as energy and signaling molecules in the intestine and peripheral organs (). Specifically, SCFAs are important regulators of both energy and glucose homeostasis (). For example, butyrate improves insulin sensitivity () and T2D patients have reduced levels of butyrate-producing bacteria (). Additionally, acetate modulates insulin secretion from β cells (). While primarily associated with metabolic benefits, increased concentrations of butyrate and acetate have been found in the cecum of obese mice, suggesting an increased ability of the microbiome to harvest energy from the diet ().

The intestinal microbiota exerts a profound influence on development, physiology, and health (). Although there is substantial interpersonal variation in the composition of the gut microbiota among unrelated healthy subjects, sequencing studies have revealed distal gut community patterns associated with different pathological states, including obesity and diabetes (). Remarkably, alterations in the intestinal microbiota composition have been shown to modulate insulin sensitivity (), a key feature in metabolic disease and type 2 diabetes (T2D), and thus play a role in diabetes susceptibility.

BAs regulate insulin secretion through the activation of specific receptors in islets. For instance, BAs can directly increase insulin secretion and production through activation of farnesoid X receptor (Fxr) in β cells (). Expression of Fxr is increased in an agonist-dependent manner (). Remarkably, we found that expression of Fxr was significantly higher in B6islets compared with B6islets ( Figure 6 B). These results suggest that the gut microbiota modulate BA-dependent signaling in pancreatic islets.

Recent in vitro studies have also identified BAs as important regulators of islet function (). We investigated the plasma BA profiles in the B6and B6mice used for insulin secretion studies ( Figures S6 C and S6D). B6BA profiles were composed of a significantly higher percentage of hydrophilic BAs ( Figure S6 C). Consistent with a previous report (), BA profiles were dominated by taurine-conjugated species, with TωMCA and TβMCA being the two most abundant in both groups of animals ( Figure S6 D). In B6mice, the hydrophobic secondary BAs DCA and LCA were significantly higher than in B6mice ( Figure S6 D).

Circulating acetate is capable of modulating insulin secretion from pancreatic islets. Specifically, recent studies have shown that acetate directly enhances glucose-stimulated insulin secretion through activation of free fatty acid receptors on β cells () and the parasympathetic nervous system (). Therefore, we measured concentrations of SCFAs in plasma and cecum but found no differences in levels of acetate between B6and B6mice ( Figures S6 A and S6B), suggesting that the divergent effects of the B6 and CAST microbiota on insulin secretion are unlikely to stem from differences in acetate.

The isolated islets partially recapitulated the reduced insulin secretion observed in the CAST-colonized mice in vivo ( Figure 3 E). The comparison between the B6-GF mice receiving B6 versus CAST microbiota allowed us to estimate the contribution of the microbiota to the strain difference in insulin secretion ( Figure 6 A). Accordingly, the reduction in insulin secretion caused by CAST microbiota colonization in B6 mice was ∼33%.

(A) Total islet insulin content and glucose-stimulated insulin secretion in response to low glucose (3.3 mM), low glucose plus KCl (40 mM), high glucose (16.7 mM), and high glucose plus GLP-1 (100 mM) from islets isolated from B6 B6 and B6 CAST mice. The number of islets and the insulin content per islet were not different between the groups.

The most dramatic phenotype difference we observed between B6and B6mice was in insulin secretion, where B6mice had a blunted insulin response during the oGTT ( Figure 3 E). This attenuated response in B6mice may also reflect low insulin secretion from β cells and/or increased insulin clearance. To determine whether the differential insulin response during the oGTT in the B6versus B6mice resulted from altered insulin secretion, we performed ex vivo insulin secretion assays on isolated islets. Islets were harvested from B6-GF mice 1 month after successful colonization with either CAST-CR or B6-CR cecum-derived microbiota ( Figure S5 ).

B6-CR and B6mice had a significantly greater representation of hydrophobic BA species (e.g., deoxycholic acid and lithocholic acid; Figures 5 B and 5C), which are elevated in humans and mice with insulin resistance (). Microbial metabolism of bile acids generally leads to a more hydrophobic bile acid pool, which facilitates fecal elimination of bile acids. Bile salt hydrolases (BSH) are involved in the hydrolysis of conjugated BAs, a necessary step for the production of secondary BAs. Consistent with the results presented above, there were a higher number of distinct BSH genes in the B6 microbiota relative to CAST microbiota (13 annotated BSH genes highly abundant in the B6 microbiota relative to CAST versus two annotated BSH genes highly abundant in the CAST microbiota relative to B6; Table S4 ). Furthermore, the two groups of recipient mice had vastly different fecal BA profiles. Chenodeoxycholic acid (CDCA) (p < 0.05), deoxycholic acid (DCA) (p < 0.01), lithocholic acid (LCA) (p < 0.01), ω-muricholic acid (ωMCA) (p < 0.05), and tauro-ω-muricholic acid (TωMCA) (p < 0.05) were all significantly higher in B6than in B6 Figure 5 B). DCA was the most abundant BA species in B6mice and was also ∼5-fold more abundant in B6-CR versus CAST-CR mice. DCA contributes to microbial dysbiosis, a hallmark of metabolic disease, and is positively associated with higher levels of Firmicutes (). Tauroursodeoxycholic acid (TUDCA) was >2-fold higher in CAST-CR mice compared to the transplanted animals but was not detected in B6-CR mice. Interestingly, administration of TUDCA has been shown to decrease hepatic steatosis and improve insulin resistance in genetically obese mice (), suggesting a potential protective role. These results reveal differences in BA profiles linked to both host genotype and gut microbial composition. They also suggest that the differential responses to prolonged HF/HS diet consumption between B6 and CAST mice could be mediated at least in part by differences in microbial BA metabolism.

Although the B6microbiota composition resembled that of CAST-CR ( Figure 4 A), there were significant differences in BA profiles between these groups, suggesting that variation in circulating BAs is under the control of both host genetics and gut microbiota. For example, the primary BAs cholic acid (CA), chenodeoxycolic acid (CDCA), and α-muricholic acid (α-MCA) were significantly higher in CAST-CR mice compared to B6mice (p < 0.01, p < 0.05, and p < 0.01, respectively; Figure 5 B). Moreover, taurine-conjugated muricholic acids (MCAs) were significantly higher in CAST-CR mice compared with B6mice. In contrast, these differences in taurine conjugation were not present between B6-CR and B6mice. Taurine conjugation of MCAs is a host process (), further highlighting the interaction of host genetics and microbiome in modulating host BA profiles.

Gut microbes impact host physiology in part by modulating the composition of the BA pool. We determined fecal BA profiles of the transplanted mice and HF/HS-fed B6-CR and CAST-CR mice by ultra performance liquid chromatography-mass spectrometry (UPLC/MS)-based quantification of primary and the most abundant secondary BAs. The BA composition of B6mice closely resembled that of B6-CR donor mice, whereas B6exhibited a BA profile that was intermediate between CAST-CR and B6-CR mice ( Figure 5 A). Microbiota composition was also a significant predictor of BA composition. Bray-Curtis dissimilarity-based principal-component analysis (PCA) revealed clustering of the BA profiles by microbiota composition.

(B and C) Abundance of fecal bile acids (B) and relative abundance of hydrophobic and hydrophilic BA species (C) determined by UPLC-MS/MS from fecal samples collected at 12 weeks post-colonization. ∗ p < 0.05, ∗∗ p < 0.01, and ∗∗∗ p < 0.001 by one-way ANOVA with Bonferroni’s multiple comparisons test.

(A) Principal-component analysis of the square root proportion of 14 major bile acid species (ng/mg). Each dot represents the bile acid profile of an individual mouse. Percent variation explained by each PC is shown in parentheses.

We characterized the functional potential of transplanted communities by sequencing and analyzing their metagenomes. Metagenomic analysis of the same samples further validated that the B6- and CAST-derived microbiota were distinct from one another, with donors clustering with their respective transplant recipients ( Figure 4 D). We identified several thousand genes differentially represented between the B6 and CAST microbiota ( Table S4 ). This metagenomic analysis also revealed microbial functions that were enriched in each transplanted microbial community ( Table S5 ). The most enriched microbial pathways in B6mice included genes involved in membrane transport and carbohydrate and lipid metabolism ( Figure 4 E). For example, the ABC transporters and phosphotransferase system (PTS) pathways were enriched in mice colonized with the B6 microbiota (p < 0.01). PTS are a class of transport systems involved in the uptake and phosphorylation of a variety of carbohydrates that can be subsequently fermented to SCFAs (). It has been previously reported that diet-induced obese mice have a concomitant enrichment of microbial pathways involved in PTS and elevated concentrations of SCFAs (), reflecting an increased capacity for energy harvest. Consistent with these results, targeted gas chromatography-mass spectrometry (GC-MS) analysis of SCFAs in cecal contents disclosed that B6mice had an increased concentration of the major fermentation end products compared with B6 Figure 4 F). Conversely, B6microbiota were enriched in genes related to the vitamin B12 (cobalamin) biosynthetic pathway ( Figure S4 A), synthesis of other B vitamins and enzyme co-factors, as well as lipopolysaccharide (LPS) biosynthesis ( Figures 4 E and S4 B). A difference in LPS biosynthetic potential may reflect the composition of the B6microbiota, which has a significantly higher relative abundance of gram-negative Bacteroidetes than the B6microbiota ( Figure S3 B). Our findings mirror those described previously in T2D patients relative to diabetes-free control patients ()—both the microbiota of T2D patients and our metabolically diseased mice with B6 microbiota show enrichment in Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways involved in membrane transport, whereas diabetes-free patients and mice with the CAST microbiota exhibit enrichment in vitamin and co-factor biosynthesis.

16S rRNA gene profiling of the donor cecal inoculum and transplant recipient fecal samples show that recipient mice were successfully colonized with the donor’s microbiota. B6and B6mice assumed a phylogenetically similar composition to that of their respective donors as confirmed by PCoA of unweighted UniFrac distances ( Figure 4 A). As seen in the founders, Bacteroidetes and Firmicutes comprised ∼90% of the microbiome, although the abundance of Firmicutes was higher in B6(p < 0.05; Figure 4 B). We identified taxonomic differences in the microbiota composition between the two recipient groups using linear discriminant analysis (LDA) effect size (LEfSe) with LDA score > 2 (). We found 20 microbial families that were differentially enriched in the fecal microbiota of B6versus B6mice. There were 12 microbial families that were enriched in B6, of which seven belonged to the Firmicutes phyla ( Figure 4 C). Some of the families differentially represented in the transplanted animals overlap with taxa that are significantly correlated with metabolic phenotypes in the founder strains ( Figure 2 ). Notably, B6mice exhibited higher levels of Clostridiaceae (p < 0.01), which is positively associated with insulin secretion in the founder strains ( Figure 2 ), whereas B6mice had higher levels of Bacteroidaceae (p < 0.01), which is negatively associated with body weight and insulin secretion ( Figure 2 ). These results are concordant with the metabolic phenotypes observed in the transplanted mice and suggest that the distinct microbial gut communities influence metabolic changes evoked by HF/HS feeding, including insulin secretion.

Recipient mice recapitulated microbial and metabolic phenotypes observed in the respective donor strains ( Figures 3 and 4 ). B6mice gained ∼25% more weight, had larger epididymal fat pad mass, and showed greater hepatic triglyceride accumulation than B6mice ( Figure 3 ). Additionally, oGTT revealed that, whereas the plasma glucose levels resulting from an orally administered bolus of glucose did not significantly differ between the two groups of transplanted mice ( Figure 3 E), the insulin responses were dramatically different ( Figure 3 F). The glucose challenge evoked a much larger insulin response in B6mice than in B6mice. The low insulin response in B6mice resembled the insulin response of the CAST-CR donors ( Figures 1 F and S1 F). These results suggest that the effectiveness of insulin to maintain euglycemia was greater in the mice receiving the CAST microbiota than in mice receiving the B6 microbiota ( Figures 3 E and 3F).

(C) Microbial families differentially enriched in either B6 CAST (blue) or B6 B6 (orange) as determined by linear discriminant analysis (LDA) with effect size (LEfSe).

(A) Principal-coordinate analysis (PCoA) of unweighted UniFrac distances for the fecal microbiota of transplant donors and recipients at sacrifice. Each circle represents an individual mouse. Percent variation explained by each PC is shown in parentheses.

We transplanted cecal microbiota from either conventionally raised B6 (B6-CR) or CAST (CAST-CR) donor mice into 9-week-old B6-GF recipient mice to yield B6or B6mice, respectively. Transplanted animals were housed by treatment group in separate vinyl gnotobiotic isolators and maintained on a HF/HS diet for 16 weeks following colonization ( Figure 3 A). A dietary treatment of 16 weeks allows robust development of metabolic phenotypes associated with consumption of HF/HS diet.

(E–G) Glucose and insulin values during oGTT (E and F) and AUC insulin (G) in B6 B6 and B6 CAST mice. All measurements shown were collected 16 weeks post-colonization.

As mentioned above, B6 and CAST mice had significantly different intestinal microbiota (PERMANOVA; F = 4.86; p < 0.001; Figure S3 A). B6 mice harbored a significantly greater abundance of microbial families with strong positive correlations with metabolic traits, such as weight and insulin (i.e., Clostridiaceae; p < 0.05), whereas CAST mice had a greater representation of families with significant negative correlations (i.e., Bacteroidaceae; p < 0.01; Figures 2 A and S3 C).

To directly test the influence of gut microbes on the metabolic phenotypes observed among the founder strains, we performed cecal transplants into germ-free B6 (B6-GF) hosts, leveraging two CC founder strains that showed disparate responsiveness to the HF/HS diet. The B6 strain became obese, insulin resistant, and glucose intolerant, whereas the CAST strain remained lean and insulin-sensitive despite HF/HS feeding ( Figure 1 ).

These results suggest that diet and genetic background are major determinants of gut microbial composition and metabolic disease. However, the relative contributions of host genetic variance versus microbial-derived genetic variation across different mouse strains in the development of diet-induced metabolic phenotypes remain largely unknown.

Some of the correlations mentioned above varied significantly as a function of host diet and strain ( Table S2 ). For example, the negative correlation observed between fasting insulin levels and Bacteroidaceae had a significant strain effect (p < 0.0001). We also observed a slight diet effect (p < 0.001), which is likely driven by the low abundance and high fasting insulin levels in the chow-fed NZO mice ( Figure 2 B). We also observed a significant diet effect for the relationship between Clostridiaceae and fasting insulin levels (p < 0.05), but there was also a strain difference that seems to be driven by NZO on chow diet (p < 0.001; Figure 2 C).

To determine whether strain-dependent variability in microbiota composition was associated with the dramatic differences in the diabetes-related clinical traits, we computed Pearson’s correlations between abundance of family-level taxa and the metabolic traits among the eight CC founder mice ( Figure 2 A). We focused our analysis on families that were present in at least seven of the founder strains. Bacteroidaceae was among the most negatively correlated with several metabolic phenotypes, including body weight, fasting plasma insulin, and AUCduring the oGTT. The Bacteroidaceae family belongs to the Bacteroidetes phylum and is typically found at higher levels in fecal samples of lean versus obese individuals (). Conversely, Clostridiaceae and Rikenellaceae showed the strongest positive correlations with plasma insulin levels. Our analysis also identified strong positive correlations between fasting plasma glucose and the Streptococcaceae and Desulfovibrionaceae families. Members of these families have previously been shown to be enriched in the fecal microbiome of patients with T2D ().

We detected eight bacterial phyla among the mice ( Figure S3 B). Bacteroidetes and Firmicutes dominated the gut of all strains on either diet, accounting for >90% of the sequenced reads. As reported by other studies, we observed a decrease in the Bacteroidetes:Firmicutes ratio and an increase in Proteobacteria in the HF/HS-fed mice (). In fact, Proteobacteria showed the greatest fold change in abundance in response to diet: HF/HS feeding caused an average 5.4-fold change (p < 0.0001), although the relative increase varied among strains.

Gut microbes influence the development of metabolic disease. We characterized the cecal microbiomes of the eight CC founder strains by 16S rRNA sequencing. We compared the cecal microbiomes employing UniFrac, a phylogenetic distance metric used to measure differences in bacterial community structure (). Principal-coordinates analysis (PCoA) of 16S rRNA unweighted UniFrac distances revealed a strong influence of strain (PERMANOVA; p < 0.001) and diet (PERMANOVA; p < 0.001) on microbial community composition ( Figure S3 A). Consistent with previous studies, the effect of diet on gut microbial composition varied among the strains (), where B6, CAST, and NOD mice showed the greatest microbiome response to diet ( Figure S3 A).

To assess whole-body glucose homeostasis and more directly evaluate the underlying role of the pancreatic islets in the control of plasma insulin, we measured plasma glucose and insulin during an oral glucose tolerance test (oGTT). Both plasma glucose and insulin during the oGTT varied dramatically between the strains. We computed the area under the curve (AUC) for each trait to determine the overall excursion in glucose and insulin that occurred during the oGTT ( Figures 1 E, 1F, and S2 ). We observed a wide inter-strain range of responses in plasma insulin during the oGTT (F = 12.84; p < 0.0001; Figures 1 F and 2 B ). Changes in plasma insulin may reflect altered insulin secretion from β cells, peripheral insulin resistance, reduced insulin clearance, or any combination thereof. 129 and WSB showed diet-induced glucose intolerance but minimal changes in their insulin response during the oGTT ( Figures 1 E, 1F, and S2 A), suggesting that their glucose intolerance may be driven by altered insulin secretion and/or enhanced insulin clearance. Remarkably, insulin secretion and glucose tolerance were completely unaffected by the HF/HS diet in CAST. Furthermore, the kinetics of the glucose and insulin responses were more rapid in CAST than in all other strains ( Figure S2 ), suggesting that CAST mice may employ different pathways underlying glucose-stimulated insulin secretion and whole-body glucose disposal.

(B and C) Contributions of strain and diet on the correlations observed between fasting insulin and (B) the Bacteroidaceae family and (C) the Clostridiaceae family.

(A) Heatmap illustrates Pearson’s pairwise correlation between microbial families and diabetes-related clinical traits measured in the eight CC founder mice (n ≥ 9 mice/genotype/diet). Microbial families are ordered by their correlation to body weight. Red, positive correlation; blue, negative. Area under the curve (AUC) values for insulin and glucose were computed from oGTT conducted at 22 weeks; other metrics were collected at 26 weeks. Correlation coefficients and p values are found in Table S2

The CC founder strains displayed a wide range of body weight and metabolic responses to the dietary challenge ( Figures 1 and S1 ). Two-way ANOVA analysis of the clinical traits revealed a significant strain effect for fasting insulin (F = 14.94; p < 0.0001). We also observed significant strain-diet interactions for body weight (F = 3.19; p < 0.01) and fasting glucose (F = 2.81; p < 0.01). Significant strain and diet effects were also seen for hepatic triglyceride content (F = 10.96, p < 0.0001; F = 11.92, p < 0.001, respectively). Liver triglyceride content showed high inter-strain variation, with 129 having the most significant response to diet (p < 0.05; Figure 1 D). NZO mice were the only strain to become overtly diabetic (glucose levels > 300 mg/dL) as a consequence of HF/HS feeding. With the exception of NZO mice, which did not survive past 18 weeks on the HF/HS diet, B6 mice were the most responsive to diet. HF/HS-fed B6 mice became obese (p < 0.01) and developed insulin resistance and glucose intolerance after ∼8 weeks ( Figures 1 A and S1 A–S1C). In addition to differences in diet responsiveness, the strains varied in both absolute levels of insulin and change in insulin levels over time, suggesting a significant divergence in insulin sensitivity among the strains ( Figure S1 B).

In all panels, ∗ p < 0.05, ∗∗ p < 0.01, ∗∗∗ p < 0.001, and ∗∗∗∗ p < 0.0001 by two-way ANOVA (diet and strain) with Bonferroni’s multiple comparisons test to assess within-strain differences. Data are mean ± SEM; n ≥ 9 mice/genotype/diet.

(E and F) Areas under the curve (AUC) for (E) glucose and (F) insulin during oral glucose tolerance test (oGTT) conducted at 22 weeks of age. Insulin and glucose values were determined from plasma following a 4-hr fast. No data (ND) were collected for NZO mice during oGTT.

(A–D) Body weight (A), fasting plasma glucose (B) and insulin (C), and hepatic triglyceride (D) content determined for all mice at 26 weeks of age.

Male mice were maintained on the high-fat/high-sucrose (HF/HS) or a control diet for 22 weeks beginning at 4 weeks of age.

We assessed the variability of diet-induced metabolic responses of the eight genetically diverse CC founder strains: A/J; C57BL/6J (B6); 129S1/SvImJ (129); NOD/ShiLtJ (NOD); NZO/HILtJ (NZO); CAST/EiJ (CAST); PWK/PhJ (PWK); and WSB/EiJ (WSB). All mice were obtained from The Jackson Laboratory, maintained in the same vivarium, and fed the same diet so that the only known difference among the strains is genetics. We placed 4-week-old male mice from each strain on either a control or a HF/HS diet for 22 weeks ( Table S1 ).

Discussion

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Yokota A. Bile acid is a host factor that regulates the composition of the cecal microbiota in rats. B6 had a significantly greater relative abundance of Firmicutes and fecal DCA than CAST-CR and B6 CAST ( CAST had a higher abundance of hydrophilic BAs and the majority of the BA pool was comprised of the mouse primary BA, βMCA ( Gut microbes are responsible for the production of the highly hydrophobic secondary BAs DCA and LCA through the dehydroxylation of the primary BAs, CA and CDCA, in the colon. Removal of glycine/taurine BA conjugates via BSH enzymes is a prerequisite for 7α/β-dehydroxylation of primary BAs into secondary BAs (). Interestingly, there were 13 predicted BSH genes that were more abundant in the B6 metagenome but only two in the CAST metagenome. One possible interpretation of this result is that there may be more bacterial species present in the B6 microbiome that are able to deconjugate BA. Consistent with this, B6mice had significantly higher levels of secondary BA as well as hydrophobic BA species than B6mice ( Figures 5 B, 5C, S6 C, and S6D), both of which are elevated in humans and mice with insulin resistance (). Furthermore, DCA has been positively associated with higher levels of Firmicutes (). This is consistent with our findings as B6-CR founders and B6had a significantly greater relative abundance of Firmicutes and fecal DCA than CAST-CR and B6 Figures S3 B and 5 B). Conversely, B6had a higher abundance of hydrophilic BAs and the majority of the BA pool was comprised of the mouse primary BA, βMCA ( Figures 5 B and 5C).

We have highlighted four examples of microbial-derived products, vitamin B12, SCFAs, LPS, and BAs, as plausible mediators of the microbiome effect on insulin secretion. However, there are thousands of other metabolites that were not characterized in our study and could also play an important role in regulating host metabolism. Future experiments using gnotobiotic mice colonized with defined communities that have different metabolic capabilities will provide mechanistic insights into the communication between gut microbes and the host.