Abstract
The low-carbohydrate ketogenic diet (KD) has long been practiced for weight loss, but the underlying mechanisms remain elusive. Gut microbiota and metabolites have been suggested to mediate the metabolic changes caused by KD consumption, although the particular gut microbes or metabolites involved are unclear. Here, we show that KD consumption enhances serum levels of taurodeoxycholic acid (TDCA) and tauroursodeoxycholic acid (TUDCA) in mice to decrease body weight and fasting glucose levels. Mechanistically, KD feeding decreases the abundance of a bile salt hydrolase (BSH)-coding gut bacterium, Lactobacillus murinus ASF361. The reduction of L. murinus ASF361 or inhibition of BSH activity increases the circulating levels of TDCA and TUDCA, thereby reducing energy absorption by inhibiting intestinal carbonic anhydrase 1 expression, which leads to weight loss. TDCA and TUDCA treatments have been found to protect against obesity and its complications in multiple mouse models. Additionally, the associations among the abovementioned bile acids, microbial BSH and metabolic traits were consistently observed both in an observational study of healthy human participants (n = 416) and in a low-carbohydrate KD interventional study of participants who were either overweight or with obesity (n = 25). In summary, we uncover a unique host–gut microbiota metabolic interaction mechanism for KD consumption to decrease body weight and fasting glucose levels. Our findings support TDCA and TUDCA as two promising drug candidates for obesity and its complications in addition to a KD.
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Data availability
The raw data for this study are accessible through NODE (http://www.biosino.org/node, Project ID OEP005260). These include serum metabolomic data, metagenomic data, L. murinus ASF361 genomic data and intestinal transcriptome data from animal studies as well as basic characteristic data, BA-targeted metabolomic data and metagenomic data from human studies. Upon justified request and appropriate approvals, the data can be provided by submitting a formal application to the Oversight Group of the different cohorts, through their respective corresponding author. All shared data will be de-identified. For any additional information needed to reanalyze the reported data, please contact the lead authors: S. Hong (shangyu_hong@fudan.edu.cn) or Y. Zheng (yan_zheng@fudan.edu.cn). All other data supporting the findings of this study are provided as source data files accompanying this paper. Source data are provided with this paper.
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Acknowledgements
S.H. was supported by the National Key R&D Program of China (2019YFA0802302, 2018YFA0800600, 2021YFA0804801), National Natural Science Foundation of China (32271217, 31971082, 91957117), Shanghai Natural Science Foundation (23ZR1403700) and Open Research Fund of the National Key Laboratory of Genetic Engineering (SKLGE-2315). Y.Z. was supported by the National Key R&D Program of China (2021YFA1301000) and Shanghai Municipal Science and Technology Major Project (2023SHZDZX02). This work was also supported by the Strategic Priority CAS Project (XDB38010300), Shanghai Municipal Science and Technology Major Project (2017SHZDZX01) and the National Natural Science Foundation of China (81970684). We thank M. Chee, assistant professor at the University of Alberta, P. Pissios, senior scientist at Janssen Inc., K. Liao, professor at Shanghai Institute of Nutrition and Health, and Q. Tang and S. Zhao, professors at Fudan University, for comments that greatly improved this work. The data analysis server is supported by the Human Phenome Data Center of Fudan University, and we thank the center staff for their support. The computations in this research were performed using the CFFF platform of Fudan University.
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Contributions
X. Li and S.H. designed the animal studies. L.J., H.T. and Y.Z. designed the human observational study. X. Lin, Y.L., L.S. and X. Liu designed the LC feeding trial. X. Li, J.Y., C.D., L.X., Y.L., D.L., X.M., Y.D. and Z.J. conducted the experiments. X. Li, X.Z., M.K., C.L., Y.S., C.D., Y.L., D.L., X.M., Y.D., Y.Z. and S.H. analyzed the data. X. Li, J.Y., X.Z., Y.Z. and S.H. wrote the paper. X. Li was responsible for the visualization. Y.Z. and S.H. acquired the funding. X.G., L.J., H.T., Y.Z. and S.H. supervised the project.
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A provisional patent application has been filed that covers aspects of this work. X. Li, J.Y., H.T., Y.Z. and S.H. are inventors on that patent application. The other authors declare no competing interests.
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Extended data
Extended Data Fig. 1 KD affects the metabolism of specific taurine-conjugated BAs.
a, The curve of body weight change in mice (dietary intervention experiment one, six biological replicates for each group). Each fitted curve is calculated based on 23 days of measured body weight values over the course of the study. Shading represents the 95% CI; middle line represented the LOESS fitted curve. b, c, Body weight (b) and fasting glucose (c) after CD or KD consumption (six biological replicates for each group). d, Principal component analysis (PCA) of serum metabolomes (six biological replicates for each group). Each point represents one sample. e, f, Body weight (e) and fasting glucose (f) after CD, KD, or KDM consumption (dietary intervention experiment two, five biological replicates for each group). g, Percentage stratification of conjugated and unconjugated BAs in serum (five biological replicates for each group). h, Ratio of conjugated to unconjugated BAs in serum (five biological replicates for each group). i, Percentage stratification of primary and secondary BAs in serum (five biological replicates for each group). j, Ratio of primary to secondary BAs in serum (five biological replicates for each group). k, Serum free taurine levels (five biological replicates for each group). l, The levels of conjugated and unconjugated BAs in cecal contents (five biological replicates for each group). m, Boxplot showing the cecal content levels of six unconjugated BAs (five biological replicates for each group). Boxplot, median and quartiles; whiskers, data range. Error bars, s.e.m.; ns, not significant; **P < 0.01, ***P < 0.001 determined by two-tailed Student’s t-test (b, c), PERMANOVA based on the Euclid distance (d), and one-way ANOVA with Tukey’s post-hoc test (e-l). In g and i, %P < 0.05 (CD vs. KD); &P < 0.05 (KD vs. KDM).
Extended Data Fig. 2 Gut microbiota is critical for KD-induced improvement in glucose homeostasis.
a-d, GTT and the associated AUC values in ABX treatment experiment (five biological replicates for each group) (a, b) and FMT experiment one (ten biological replicates for each group) (c, d). e, f, Fasting glucose after FMT (e) and after stopping FMT (f) (FMT experiment two, five biological replicates for each group). g, h, Serum levels of THCA (g) and TαMCA/TβMCA (h) after dietary intervention and ABX treatment (five biological replicates for each group). Error bars, s.e.m.; ns, not significant; *P < 0.05, **P < 0.01, ***P < 0.001 determined by one-way ANOVA with Tukey’s post-hoc test.
Extended Data Fig. 3 L. murinus ASF361 gavage affects body weight, fasting glucose and glucose tolerance.
a-d, Body weight (a), fasting glucose (b), GTT (c), and the associated AUC values (d) after 10 days of L. murinus and A. muciniphila administrations (KDM condition, bacterial strain administration experiment two, seven biological replicates for each group). e, f, Serum levels of THCA (e) and TβMCA (f) after L. murinus oral supplementation (KDM condition, bacterial strain administration experiment one, five biological replicates for each group). g, h, Cecal content levels of HCA (g) and βMCA (h) after L. murinus oral supplementation (bacterial strain administration experiment one, five biological replicates for each group). i, The genomic architecture of the L. murinus ASF361. From outside to center: forward strand coding sequence (CDS), reverse strand CDS, the scaffolds containing the genes described in the main text, GC content, GC skew value, genome size ruler. j, Growth curve of L. murinus with or without methionine in the MRS culture media fitted by 4-PL (n = five replicates/treatment). k-n, Changes in TDCA (k), TUDCA (l), DCA (m) and UDCA (n) levels in the MRS culture media with or without methionine after co-cultured with L. murinus ASF361 in vitro (three biological replicates for each group, Shadings indicate s.e.m.). o, The gene arrow map displaying the specific genetic elements in scaffold67 (GC content shown in the lower track) in the L. murinus genome. Error bars, s.e.m.; ns, not significant; **P < 0.01, ***P < 0.001 determined by one-way ANOVA with Tukey’s post-hoc test (a, b, and d), two-tailed Student’s t-test (e-h and k-n), and two-way ANOVA (j). Lactobacillus murinus ASF361 = L. murinus, Akkermansia muciniphila ATCC BAA-835 = A. muciniphila.
Extended Data Fig. 4 Interventions of methionine, microbes or BAs do not affect energy expenditure and intake.
a, Energy expenditure of vehicle-treated or TDCA-treated mice over 72 h and mean energy expenditure per mouse basis (corrected by body weight, five biological replicates for each group). b, Energy expenditure of vehicle-treated or TUDCA-treated mice over 72 h and mean energy expenditure per mouse basis (corrected by body weight, four biological replicates for each group). c, d, Daily food intake (c) (n = seven replicates/treatment) and water intake (d) (n = four replicates/treatment) per mouse basis in TDCA-treated and vehicle-treated groups. e, f, Daily food intake (e) (n = seven replicates/treatment) and water intake (f) (n = four replicates/treatment) per mouse basis in TUDCA-treated and vehicle-treated groups. g-i, Fecal energy in ABX treatment experiment (six biological replicates for each group) (g), FMT experiment one (five biological replicates for each group) (h), and bacteria strain administration experiment (seven biological replicates for each group) (i). Boxplot, median and quartiles; whiskers, data range. j-o, Daily food intake (n = seven replicates/intervention) and water intake (n = four replicates/ intervention) per mouse basis in ABX treatment experiment (j, k), FMT experiment one (l, m), and oral administration of bacterial strains experiment (n, o). No significant differences in all groups. Error bars, s.e.m.; ns, not significant ; *P < 0.05, **P < 0.01, ***P < 0.001 determined by two-tailed Student’s t-test (a-f) and one-way ANOVA with Tukey’s post-hoc test (g-o).
Extended Data Fig. 5 TDCA and TUDCA treatments significantly downregulate Car1 expression in vivo and in vitro.
a, RT-qPCR result of ileal mCar1 mRNA levels in mice after vehicle, TDCA or TUDCA treatment (normalized to the housekeeping gene, mHprt1) (six biological replicates for each group). b, RT-qPCR result of hCAR1 mRNA levels after the administration of PBS (control), TDCA, or TUDCA in Caco-2 cells (normalized to the housekeeping gene, hHPRT1) (four biological replicates for each group). c, Body weight of mice after vehicle or CAR inhibitors (MTZ and TPM) treatment (five biological replicates for each group). d, e, Representative images (d) and fluorescence quantification (e) of intestinal sections from mice gavaged with fatty acid conjugated BODIPY fluorophore after vehicle, MTZ, or TPM treatment (three biological replicates for each group). f, g, Representative images (f) and quantification (g) of Oil Red O staining of Caco-2 cells after vehicle, MTZ, or TPM treatment (three biological replicates for each group). h, Fecal energy of CD-fed mice after treatment with vehicle, TDCA, TUDCA, TDCA plus D-Phe or TUDCA plus D-Phe (five biological replicates for each group). Boxplot, median and quartiles; whiskers, data range. i-k, RT-qPCR results of ileal Shp (i), ileal Fgf15 (j) and liver Cyp7a1 (k) mRNA levels in mice after CD, KD, or KDM intervention (normalized to the housekeeping gene, Gapdh) (five biological replicates for each group). l, Serum total BA levels in mice after CD, KD or KDM intervention (five biological replicates for each group). m-o, RT-qPCR results of ileal Shp (m), ileal Fgf15 (n) and liver Cyp7a1 (o) mRNA levels in mice after vehicle or L. murinus gavage (normalized to the housekeeping gene, Gapdh) (five biological replicates for each group). p, Serum C4 (the primary BA precursor metabolite) levels in mice after vehicle or L. murinus gavage (five biological replicates for each group). q-s, Fecal energy (q), body weight (r) and fasting glucose (s) after CD, KD, or KD plus GW4064 intervention (five biological replicates for each group). Boxplot, median and quartiles; whiskers, data range. Error bars, s.e.m; ns, not significant; *P < 0.05, **P < 0.01, ***P < 0.001 determined by one-way ANOVA with Tukey’s post-hoc test (a-l and q-s) and two-tailed Student’s t-test (m-p). Lactobacillus murinus ASF361 = L. murinus.
Extended Data Fig. 6 Interventions of methionine, microbes or BAs do not affect serum levels of ketone bodies.
a-d, Fasting ketones after ABX treatment (a, five biological replicates for each group), FMT (b, five biological replicates for each group), bacterial strains gavage (c, seven biological replicates for each group) or TDCA and TUDCA treatments (d, five biological replicates for each group). ns, not significant; ***P < 0.001 determined by one-way ANOVA with Tukey’s post-hoc test. Lactobacillus murinus ASF361 = L. murinus, Akkermansia muciniphila ATCC BAA-835 = A. muciniphila.
Extended Data Fig. 7 TDCA and TUDCA improve glucose tolerance and reduce hepatic lipid accumulation in obese and diabetic models.
a-d, GTT and the associated AUC values of DIO mice (a), STZ mice (b), ob/ob mice (c), db/db mice (d) after 3 weeks of TDCA and TUDCA treatments (five biological replicates for each group). e, f, Representative H&E-stained (e) and Oil Red O-stained (f) histological sections from livers of four mouse models (three biological replicates for each group). g-j, The hepatic triglycerides levels in DIO mice (g), STZ mice (h), ob/ob mice (i), db/db mice (j) after TDCA and TUDCA treatments (five biological replicates for each group). k-l, The hepatic triglycerides levels in CD-fed (k) and KDM-fed (l) mice after TDCA and TUDCA treatments (five biological replicates for each group). Error bars, s.e.m.; ns. not significant; *P < 0.05, **P < 0.01, ***P < 0.001 determined by one-way ANOVA with Tukey’s post-hoc test.
Extended Data Fig. 8 DCA and UDCA species associate with BMI and fasting glucose in humans.
a, b, Body weight (a) and fasting glucose (b) of CD-fed mice after 3 weeks of GDCA and GUDCA treatments (six biological replicates for each group). c, Heatmap displaying the correlations between plasma taurine-conjugated or glycine-conjugated DCA and UDCA levels (n = 406) or fecal unconjugated DCA and UDCA levels (n = 381) and BMI or fasting glucose. The dark blue and light blue rectangles represent the conjugated BAs and unconjugated BAs, respectively. d-g, The raincloud plots showing the differences in plasma levels of TDCA (d), GDCA (e), TUDCA (f) and GUDCA (g) in overweight individuals (BMI ≥ 24 kg m-2, n = 124) and non-overweight individuals (BMI < 24 kg m-2, n = 282). Boxplot, median and quartiles; whiskers, data range. h, i, The bar charts showing the differences in fecal levels of DCA (h) and UDCA (i) in overweight individuals (BMI ≥ 24 kg m-2, n = 123) and non-overweight individuals (BMI < 24 kg m-2, n = 258). Boxplot, median and quartiles; whiskers, data range. j, The raincloud plot showing the differences in microbial ‘obesity-related’ BSH gene abundance in overweight individuals (BMI ≥ 24 kg m-2, n = 115) and non-overweight individuals (BMI < 24 kg m-2, n = 264). Boxplot, median and quartiles; whiskers, data range. Error bars, s.e.m.; indicate SEM. #P < 0.1, *P < 0.05, **P < 0.01, ***P < 0.001 determined by one-way ANOVA with Tukey’s post-hoc test (a, b), Spearman’s rank correlation (c), and two-sided Mann-Whitney U-test (d-j).
Extended Data Fig. 9 Changes in DCA and UDCA species and microbial BSHs associate with changes in BMI and fasting glucose in LC intervention participants.
a, Heatmap displaying the correlations between changes in plasma taurine-conjugated or glycine-conjugated DCA and UDCA levels, or fecal unconjugated DCA and UDCA levels and changes in BMI or fasting glucose levels induced by the 12-week intervention with LC. The dark blue and light blue rectangles represent the conjugated BAs and unconjugated BAs, respectively. b, Heatmap showing the correlations between changes in ‘obesity-related’ BSH gene abundance and changes in BMI or fasting glucose levels induced by 12-week intervention with LC. c, Heatmap displaying the correlations between changes in plasma taurine-conjugated or glycine-conjugated DCA and UDCA levels, or fecal unconjugated DCA and UDCA levels and changes in ‘obesity-related’ BSH gene abundance induced by the 12-week intervention with LC. The dark blue and light blue rectangles represent the conjugated BAs and unconjugated BAs, respectively. d, The circus correlation plot showing associations among plasma or fecal DCA and UDCA species levels, ‘obesity-related’ BSH gene abundance, BMI and fasting glucose levels. Red and blue represent positive and negative correlations, respectively. The black border highlights the significant associations with P < 0.05. The outer circle represents different omics. n = 24. #P < 0.1, *P < 0.05, **P < 0.01, ***P < 0.001 determined by Spearman’s rank correlation.
Supplementary information
Supplementary Information
Supplementary Tables 1–11, Supplementary Tables 13–19, Supplementary Schematic Diagram, Resources.
Supplementary Table 12
The associations between the putative taxonomic BSH genes and BMI or fasting glucose.
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Li, X., Yang, J., Zhou, X. et al. Ketogenic diet-induced bile acids protect against obesity through reduced calorie absorption. Nat Metab 6, 1397–1414 (2024). https://doi.org/10.1038/s42255-024-01072-1
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DOI: https://doi.org/10.1038/s42255-024-01072-1
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