A dysregulated bile acid-gut microbiota axis contributes to obesity susceptibility

Abstract

Background: The composition of the bile acid (BA) pool is closely associated with obesity and is modified by gut microbiota. Perturbations of gut microbiota shape the BA composition, which, in turn, may alter important BA signaling and affect host metabolism.

Methods: We investigated BA composition of high BMI subjects from a human cohort study and a high fat diet (HFD) obesity prone (HF-OP) / HFD obesity resistant (HF-OR) mice model. Gut microbiota was analysed by metagenomics sequencing. GLP-1 secretion and gene regulation studies involved ELISA, qPCR, Western blot, Immunohistochemistry, and Immunofluorescence staining.

Findings: We found that the proportion of non-12-OH BAs was significantly decreased in the unhealthy high BMI subjects. The HF-OR mice had an enhanced level of non-12-OH BAs. Non-12-OH BAs including ursodeoxycholate (UDCA), chenodeoxycholate (CDCA), and lithocholate (LCA) were decreased in the HF-OP mice and associated with altered gut microbiota. Clostridium scindens was decreased in HF-OP mice and had a positive correlation with UDCA and LCA. Gavage of Clostridium scindens in mice increased the levels of hepatic non-12-OH BAs, accompanied by elevated serum 7α-hydroxy-4-cholesten-3-one (C4) levels. In HF-OP mice, altered BA composition was associated with significantly downregulated expression of GLP-1 in ileum and PGC1α, UCP1 in brown adipose tissue. In addition, we identified that UDCA attenuated the high fat diet-induced obesity via enhancing levels of non-12-OH BAs.

Interpretation: Our study highlights that dysregulated BA signaling mediated by gut microbiota contributes to obesity susceptibility, suggesting modulation of BAs could be a promising strategy for obesity therapy.

Keywords: Bile acids; Energy expenditure; GLP-1; Gut microbiota; Obesity; UCP1.

Conflict of interest statement

Declaration of Competing Interest The authors declare that they have no conflicts of interests.

Copyright © 2020 The Author(s). Published by Elsevier B.V. All rights reserved.

Figures

Fig. 1

Serum BA analysis from HHB and UHB group. (a) Total BA concentrations and major BA ratio of the subjects from the HHB and UHB group. BA species include unconjugated, taurine-conjugated, and glycine-conjugated BAs. The proportions of BA species were calculated as follows: concentrations of BA species / Total BA × 100%. n = 121 in HHB group, n = 62 in UHB group. HHB: healthy high BMI group; UHB: unhealthy high BMI group. **p<0•01 (Mann–Whitney U test). (b) ROC of non-12-OH BAs% in predicting healthy high BMI. AUC: area under curve.

Fig. 2

The physiological changes in the N, HF-OP and HF-OR group. (a) Body weights and daily energy intake (b) at different time points. Data are expressed as mean ± SD (n = 8 per group). **p<0•01 (unpaired Student's t-test) compared with N group. (c) Representative images of H&E staining of eWAT, BAT and Liver sections. Scale bars, 100 μm. eWAT: epididymal white adipose tissue. (d) Serum parameters. Data are expressed as mean ± SD (n = 8 per group). *p<0•05 and **p<0•01 (unpaired Student's t-test).

Fig. 3

Dysregulated BA profiles in the HF-OP group and relative expansion of non-12-OH BAs composition in the HF-OR group. (a) Orthogonal partial least squared-discriminant analysis (OPLS-DA) scores plot of serum BA profiles showing the groupings of N (blue) group, HF-OP (red) and HF-OR (green). (b) VIP scores of OPLS-DA based on the serum BA profiles between the HF-OP and HF-OR group. A BA with VIP more than 1 was considered important in the discrimination between the groups. (c) Dysregulated BAs in the HF-OP group. The data are presented as the mean ± SD. *p<0•05 and **p<0•01 (Mann–Whitney U test). (d) Heatmap of spearman correlation coefficients between serum BAs and blood biochemical parameters from all samples in the three groups (n = 24, 8 samples per group). The gradient colours represent the correlation coefficients, with red color being more positive and blue color indicating more negative. *p<0•05 (Spearman's correlation with the post hoc correction using the Holm method). (e) Differential BAs in liver tissue with a relative expansion of non-12-OH BA composition in HF-OR group. The data are presented as the mean ± SD. *p<0•05 and **p<0•01 (Mann–Whitney U test), ns showed no significance. (f) Pie graphs show the mean percentage of non-12-OH BAs in the liver among the three groups. (g) The relative mRNA levels of Fxr, Shp and critical enzymes responsible for BA synthesis in liver among the three groups. The data are presented as the mean ± SD. **p<0•01 (unpaired Student's t-test). n = 5 per group. (h) The expression of CYP8B1 (n = 4 per group) and CYP7B1 (n = 4 per group) in liver were detected by western blot. Data are presented as the mean ± SD. *p<0•05 and **p<0•01 (unpaired Student's t-test). (i) The expression of FXR and FGF15 in ileum were detected by western blot. Data are presented as the mean ± SD. *p<0•05 (unpaired Student's t-test). (j) Serum FGF15 levels were detected by ELISA. Data are presented as the mean ± SD. **p<0•01 (unpaired Student's t-test).

Fig. 4

The time-dependent alteration of the fecal BAs profile. (a) Partial least squares-discriminant analysis (PLS-DA) analysis of the fecal BAs profile from different time points of the three groups (n = 8 per group). (b) Dysregulated BAs in feces of N, HF-OP and HF-OR groups at week 82. The data are presented as the mean ± SD. **p<0•01 (Mann–Whitney U test). n = 8 per group.

Fig. 5

Altered BA profiles were associated with gut microbiota. (a) Partial least-square discriminant analysis (PLS-DA) at species level identified by metagenomic sequencing. The HF-OP group is shown in red, the HF-OP group is shown in green, and the N group is shown in blue. PC1 and PC2 account for 18% and 8% respectively. n = 5 per group. (b) VIP scores of top 20 species in PLS-DA model between HF-OP and HF-OR group. (c) Visualization of differentially expressed species-level bacteria by volcano plots. Red dots represent significantly high abundance in the HF-OP group compared with the HF-OR group; blue dots represent significantly low abundance in the HF-OP group compared with the HF-OR group. (d) The abundance of Clostridium scindens and Clostridium hylemonae were significantly decreased in the HF-OP group. Data are presented as the mean ± SD. **p<0•01 (unpaired Student's t-test). (e) Spearman correlations of the relative BA abundance (% total) in feces with the relative abundance of differential microbial species from the samples in the group of N (n = 5), HF-OP (n = 5) and HF-OR (n = 5). The gradient colours represent the correlation coefficients, with red color being more positive and blue color indicating more negative. *p<0•05 (Spearman's correlation after the post hoc correction using the FDR method). (f) The BA profile in the mouse liver and serum C4 levels after 2 weeks Clostridium scindens gavage (n = 7 per group). The data are presented as the mean ± SD. Vehicle: PBS group; KCS: heat-killed C. scindens group; LCS: live C. scindens group. *p<0•05 and **p<0•01 (Mann–Whitney U test).

Fig. 6

GLP-1 levels in ileum and energy expenditure were decreased significantly in HF-OP group. (a) Representative immunofluorescent images showing TGR5(red), GLP-1(green) in the ileum tissue of N, HF-OP and HF-OR groups. Scale bars, 50 μm. GLP-1 positive cells count was expressed as counts per mm2 of mucosal area. Five fields of view were chosen randomly per sample to calculate mean count and area, values are presented as mean ± SD. n = 5 per group. The count and area were analysed using image J software. *p<0•05 and **p<0•01 (unpaired Student's t-test). (b) The GLP-1 precursor Glucagon and Tgr5 mRNA in ileum tissue were measured using real-time PCR assay. Data are presented as the mean ± SD. *p<0•05 and **p<0•01 (unpaired Student's t-test). n = 4 per group. (c) GLP-1 secretion was detected in STC-1 and NCI-H716 cells using ELISA with treatment of BAs, and data were obtained from 3 independent experiments. *p<0•05 and **p<0•01 (unpaired Student's t-test). (d) Representative UCP1 immunostaining of BAT sections from the three groups. Scale bars, 50 μm. (e) Quantification of UCP1 immunostaining average optical density. Data are presented as the mean ± SD. n = 3 per group. *p<0•05 and **p<0•01 (unpaired Student's t-test). (f) The expression of UCP1 (n = 8 per group) and PGC-1α (n = 7 per group) in BAT were detected by western blot. Data are presented as the mean ± SD. **p<0•01 (unpaired Student's t-test).

Fig. 7

UDCA treatment attenuated obesity induced by high fat diet. (a) UDCA improved the metabolic profile: changes of body weight and serum paraments. Data are presented as the mean ± SD. n = 5 per group. *p<0•05 and **p<0•01 (unpaired Student's t-test), HFD group vs N group; #p <0•05 and ##p<0•01 (unpaired Student's t-test), HFD+UDCA group vs HFD group. (b) Heatmap of serum bile acids profile of normal diet group (N), high fat diet group (H) and high fat diet + UDCA group (HU). The gradient colours in the heatmap depicted the z-scale value of serum bile acids concentration. (c) The mean percentage of 12-OH bile acids and non-12 bile acids in serum from all the samples of the three group (n = 5 per group). (d) The principal component analysis (PCA) analysis of serum bile acids. n = 5 per group. N: normal diet group; H: high fat diet group; HU: high fat diet group+0•5%UDCA group. (e) Relative mRNA levels of Cyp7a1, Cyp8b1, Cyp27a1 and Cyp7b1 in liver detected by q-PCR assay. All data are presented as the mean ± SD. n = 4 per group. *p<0•05 (unpaired Student's t-test). (f) The expression of CYP8B1 and CYP7B1 in liver of three group mice were detected by western blot. Data are presented as the mean ± SD. n = 3 per group. *p<0•05 (unpaired Student's t-test).