Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

UCP1 governs liver extracellular succinate and inflammatory pathogenesis

Abstract

Non-alcoholic fatty liver disease (NAFLD), the most prevalent liver pathology worldwide, is intimately linked with obesity and type 2 diabetes. Liver inflammation is a hallmark of NAFLD and is thought to contribute to tissue fibrosis and disease pathogenesis. Uncoupling protein 1 (UCP1) is exclusively expressed in brown and beige adipocytes, and has been extensively studied for its capacity to elevate thermogenesis and reverse obesity. Here we identify an endocrine pathway regulated by UCP1 that antagonizes liver inflammation and pathology, independent of effects on obesity. We show that, without UCP1, brown and beige fat exhibit a diminished capacity to clear succinate from the circulation. Moreover, UCP1KO mice exhibit elevated extracellular succinate in liver tissue that drives inflammation through ligation of its cognate receptor succinate receptor 1 (SUCNR1) in liver-resident stellate cell and macrophage populations. Conversely, increasing brown and beige adipocyte content in mice antagonizes SUCNR1-dependent inflammatory signalling in the liver. We show that this UCP1-succinate–SUCNR1 axis is necessary to regulate liver immune cell infiltration and pathology, and systemic glucose intolerance in an obesogenic environment. As such, the therapeutic use of brown and beige adipocytes and UCP1 extends beyond thermogenesis and may be leveraged to antagonize NAFLD and SUCNR1-dependent liver inflammation.

Access options

Rent or Buy article

Get time limited or full article access on ReadCube.

from$8.99

All prices are NET prices.

Fig. 1: Brown and beige adipose tissues regulate systemic inflammation and liver pathology independent of thermogenesis.
Fig. 2: The UCP1 catabolic circuit controls inflammation and myeloid cell populations in the liver.
Fig. 3: The UCP1 catabolic circuit controls liver extracellular succinate levels.
Fig. 4: The BAT/beige fat UCP1 catabolic circuit controls liver immune cell infiltration and inflammation via succinate–SUCNR1 signalling.
Fig. 5: Liver succinate–SUCNR1 signalling drives liver pathology and glucose intolerance, which is antagonized by the UCP1 catabolic circuit.
Fig. 6: Elevation of BAT and beige fat antagonizes NAFLD via SUCNR1.
Fig. 7: SUCNR1 regulates inflammation and activation in liver-resident Kupffer cell and HSC populations.

Data availability

Source data for all mouse experiments have been provided. Mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium via the PRIDE partner repository with the dataset identifier PXD024717. All other data are available from the corresponding author upon request. Source data are provided with this paper.

References

  1. 1.

    Younossi, Z. M. Non-alcoholic fatty liver disease—a global public health perspective. J. Hepatol. 70, 531–544 (2019).

    PubMed  PubMed Central  Google Scholar 

  2. 2.

    Lefere, S. & Tacke, F. Macrophages in obesity and non-alcoholic fatty liver disease: crosstalk with metabolism. JHEP Rep. 1, 30–43 (2019).

    PubMed  PubMed Central  Google Scholar 

  3. 3.

    Pfeifer, A. & Hoffmann, L. S. Brown, beige, and white: the new color code of fat and its pharmacological implications. Annu. Rev. Pharmacol. Toxicol. 55, 207–227 (2015).

    CAS  PubMed  Google Scholar 

  4. 4.

    Betz, M. J. & Enerback, S. Targeting thermogenesis in brown fat and muscle to treat obesity and metabolic disease. Nat. Rev. Endocrinol. 14, 77–87 (2018).

    CAS  PubMed  Google Scholar 

  5. 5.

    Mills, E. L. et al. Accumulation of succinate controls activation of adipose tissue thermogenesis. Nature 560, 102–106 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

  6. 6.

    Littlewood-Evans, A. et al. GPR91 senses extracellular succinate released from inflammatory macrophages and exacerbates rheumatoid arthritis. J. Exp. Med. 213, 1655–1662 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  7. 7.

    Mills, E. & O’Neill, L. A. Succinate: a metabolic signal in inflammation. Trends Cell Biol. 24, 313–320 (2014).

    CAS  PubMed  Google Scholar 

  8. 8.

    van Diepen, J. A. et al. SUCNR1-mediated chemotaxis of macrophages aggravates obesity-induced inflammation and diabetes. Diabetologia 60, 1304–1313 (2017).

    PubMed  PubMed Central  Google Scholar 

  9. 9.

    Rubic, T. et al. Triggering the succinate receptor GPR91 on dendritic cells enhances immunity. Nat. Immunol. 9, 1261–1269 (2008).

    CAS  PubMed  Google Scholar 

  10. 10.

    Larsen, C. M. et al. Sustained effects of interleukin-1 receptor antagonist treatment in type 2 diabetes. Diabetes Care 32, 1663–1668 (2009).

    CAS  PubMed  PubMed Central  Google Scholar 

  11. 11.

    Larsen, C. M. et al. Interleukin-1-receptor antagonist in type 2 diabetes mellitus. N. Engl. J. Med. 356, 1517–1526 (2007).

    CAS  PubMed  Google Scholar 

  12. 12.

    Chouchani, E. T., Kazak, L. & Spiegelman, B. M. New advances in adaptive thermogenesis: UCP1 and beyond. Cell Metab. 29, 27–37 (2019).

    CAS  PubMed  Google Scholar 

  13. 13.

    Kazak, L. et al. UCP1 deficiency causes brown fat respiratory chain depletion and sensitizes mitochondria to calcium overload-induced dysfunction. Proc. Natl Acad. Sci. USA 114, 7981–7986 (2017).

    CAS  PubMed  Google Scholar 

  14. 14.

    Febbraio, M. A. et al. Preclinical models for studying NASH-driven HCC: how useful are they? Cell Metab. 29, 18–26 (2019).

    CAS  PubMed  Google Scholar 

  15. 15.

    Asgharpour, A. et al. A diet-induced animal model of non-alcoholic fatty liver disease and hepatocellular cancer. J. Hepatol. 65, 579–588 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  16. 16.

    Liu, X. et al. Paradoxical resistance to diet-induced obesity in UCP1-deficient mice. J. Clin. Invest. 111, 399–407 (2003).

    CAS  PubMed  PubMed Central  Google Scholar 

  17. 17.

    Enerback, S. et al. Mice lacking mitochondrial uncoupling protein are cold-sensitive but not obese. Nature 387, 90–94 (1997).

    CAS  PubMed  Google Scholar 

  18. 18.

    Anunciado-Koza, R., Ukropec, J., Koza, R. A. & Kozak, L. P. Inactivation of UCP1 and the glycerol phosphate cycle synergistically increases energy expenditure to resist diet-induced obesity. J. Biol. Chem. 283, 27688–27697 (2008).

    CAS  PubMed  PubMed Central  Google Scholar 

  19. 19.

    Karsdal, M. A. et al. Novel insights into the function and dynamics of extracellular matrix in liver fibrosis. Am. J. Physiol. Gastrointest. Liver Physiol. 308, G807–G830 (2015).

    PubMed  PubMed Central  Google Scholar 

  20. 20.

    Munsterman, I. D. et al. Extracellular matrix components indicate remodelling activity in different fibrosis stages of human non-alcoholic fatty liver disease. Histopathology 73, 612–621 (2018).

    PubMed  Google Scholar 

  21. 21.

    Veyel, D. et al. Biomarker discovery for chronic liver diseases by multi-omics—a preclinical case study. Sci. Rep. 10, 1314 (2020).

    CAS  PubMed  PubMed Central  Google Scholar 

  22. 22.

    Marcher, A. B. et al. Transcriptional regulation of hepatic stellate cell activation in NASH. Sci. Rep. 9, 2324 (2019).

    PubMed  PubMed Central  Google Scholar 

  23. 23.

    Kubes, P. & Jenne, C. Immune responses in the liver. Annu Rev. Immunol. 36, 247–277 (2018).

    CAS  PubMed  Google Scholar 

  24. 24.

    Wiedemann, M. S., Wueest, S., Item, F., Schoenle, E. J. & Konrad, D. Adipose tissue inflammation contributes to short-term high-fat diet-induced hepatic insulin resistance. Am. J. Physiol. Endocrinol. Metab. 305, E388–E395 (2013).

    CAS  PubMed  Google Scholar 

  25. 25.

    Barka, T. & Popper, H. Liver enlargement and drug toxicity. Medicine 46, 103–117 (1967).

    CAS  PubMed  Google Scholar 

  26. 26.

    Carthew, P., Edwards, R. E. & Nolan, B. M. New approaches to the quantitation of hypertrophy and hyperplasia in hepatomegaly. Toxicol. Lett. 102-103, 411–415 (1998).

    CAS  PubMed  Google Scholar 

  27. 27.

    Huang, W. et al. Depletion of liver Kupffer cells prevents the development of diet-induced hepatic steatosis and insulin resistance. Diabetes 59, 347–357 (2010).

    CAS  PubMed  Google Scholar 

  28. 28.

    Karlmark, K. R. et al. Hepatic recruitment of the inflammatory Gr1+ monocyte subset upon liver injury promotes hepatic fibrosis. Hepatology 50, 261–274 (2009).

    CAS  PubMed  Google Scholar 

  29. 29.

    Duffield, J. S. et al. Selective depletion of macrophages reveals distinct, opposing roles during liver injury and repair. J. Clin. Invest. 115, 56–65 (2005).

    CAS  PubMed  PubMed Central  Google Scholar 

  30. 30.

    Ramachandran, P. et al. Differential Ly-6C expression identifies the recruited macrophage phenotype, which orchestrates the regression of murine liver fibrosis. Proc. Natl Acad. Sci. USA 109, E3186–E3195 (2012).

    CAS  PubMed  Google Scholar 

  31. 31.

    Liaskou, E., Wilson, D. V. & Oo, Y. H. Innate immune cells in liver inflammation. Mediators Inflamm. 2012, 949157 (2012).

    PubMed  PubMed Central  Google Scholar 

  32. 32.

    Miyachi, Y. et al. Roles for cell-cell adhesion and contact in obesity-induced hepatic myeloid cell accumulation and glucose intolerance. Cell Rep. 18, 2766–2779 (2017).

    CAS  PubMed  Google Scholar 

  33. 33.

    Zang, S. et al. Neutrophils play a crucial role in the early stage of nonalcoholic steatohepatitis via neutrophil elastase in mice. Cell Biochem. Biophys. 73, 479–487 (2015).

    CAS  PubMed  Google Scholar 

  34. 34.

    Alkhouri, N. et al. Neutrophil to lymphocyte ratio: a new marker for predicting steatohepatitis and fibrosis in patients with nonalcoholic fatty liver disease. Liver Int. 32, 297–302 (2012).

    CAS  PubMed  Google Scholar 

  35. 35.

    Kanda, H. et al. MCP-1 contributes to macrophage infiltration into adipose tissue, insulin resistance, and hepatic steatosis in obesity. J. Clin. Invest. 116, 1494–1505 (2006).

    CAS  PubMed  PubMed Central  Google Scholar 

  36. 36.

    Tosello-Trampont, A. C., Landes, S. G., Nguyen, V., Novobrantseva, T. I. & Hahn, Y. S. Kuppfer cells trigger nonalcoholic steatohepatitis development in diet-induced mouse model through tumor necrosis factor-alpha production. J. Biol. Chem. 287, 40161–40172 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  37. 37.

    Stienstra, R. et al. Kupffer cells promote hepatic steatosis via interleukin-1beta-dependent suppression of peroxisome proliferator-activated receptor alpha activity. Hepatology 51, 511–522 (2010).

    CAS  PubMed  Google Scholar 

  38. 38.

    Sanderson, N. et al. Hepatic expression of mature transforming growth factor beta 1 in transgenic mice results in multiple tissue lesions. Proc. Natl Acad. Sci. USA 92, 2572–2576 (1995).

    CAS  PubMed  Google Scholar 

  39. 39.

    Roberts, A. B. et al. Transforming growth factor type beta: rapid induction of fibrosis and angiogenesis in vivo and stimulation of collagen formation in vitro. Proc. Natl Acad. Sci. USA 83, 4167–4171 (1986).

    CAS  PubMed  Google Scholar 

  40. 40.

    Wieckowska, A. et al. Increased hepatic and circulating interleukin-6 levels in human nonalcoholic steatohepatitis. Am. J. Gastroenterol. 103, 1372–1379 (2008).

    CAS  PubMed  Google Scholar 

  41. 41.

    Yoneshiro, T. et al. BCAA catabolism in brown fat controls energy homeostasis through SLC25A44. Nature 572, 614–619 (2019).

    CAS  PubMed  PubMed Central  Google Scholar 

  42. 42.

    Spinelli, J. B. et al. Metabolic recycling of ammonia via glutamate dehydrogenase supports breast cancer biomass. Science 358, 941–946 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  43. 43.

    Sullivan, M. R. et al. Quantification of microenvironmental metabolites in murine cancers reveals determinants of tumor nutrient availability. eLife 8, e44235 (2019).

    CAS  PubMed  PubMed Central  Google Scholar 

  44. 44.

    Mantena, S. K. et al. High fat diet induces dysregulation of hepatic oxygen gradients and mitochondrial function in vivo. Biochem. J. 417, 183–193 (2009).

    CAS  PubMed  Google Scholar 

  45. 45.

    Reddy, A. et al. pH-gated succinate secretion regulates muscle remodeling in response to exercise. Cell 183, 62–75 e17 (2020).

    CAS  PubMed  Google Scholar 

  46. 46.

    Xiao, C., Goldgof, M., Gavrilova, O. & Reitman, M. L. Anti-obesity and metabolic efficacy of the beta3-adrenergic agonist, CL316243, in mice at thermoneutrality compared to 22 degrees C. Obesity 23, 1450–1459 (2015).

    CAS  PubMed  Google Scholar 

  47. 47.

    Granneman, J. G., Li, P., Zhu, Z. & Lu, Y. Metabolic and cellular plasticity in white adipose tissue I: effects of beta3-adrenergic receptor activation. Am. J. Physiol. Endocrinol. Metab. 289, E608–E616 (2005).

    CAS  PubMed  Google Scholar 

  48. 48.

    Gospodarska, E., Nowialis, P. & Kozak, L. P. Mitochondrial turnover: a phenotype distinguishing brown adipocytes from interscapular brown adipose tissue and white adipose tissue. J. Biol. Chem. 290, 8243–8255 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  49. 49.

    Himms-Hagen, J. et al. Effect of CL-316,243, a thermogenic beta 3-agonist, on energy balance and brown and white adipose tissues in rats. Am. J. Physiol. 266, R1371–R1382 (1994).

    CAS  PubMed  Google Scholar 

  50. 50.

    He, W. et al. Citric acid cycle intermediates as ligands for orphan G-protein-coupled receptors. Nature 429, 188–193 (2004).

    CAS  PubMed  Google Scholar 

  51. 51.

    McCreath, K. J. et al. Targeted disruption of the SUCNR1 metabolic receptor leads to dichotomous effects on obesity. Diabetes 64, 1154–1167 (2015).

    CAS  PubMed  Google Scholar 

  52. 52.

    Keiran, N. et al. SUCNR1 controls an anti-inflammatory program in macrophages to regulate the metabolic response to obesity. Nat. Immunol. 20, 581–592 (2019).

    CAS  PubMed  Google Scholar 

  53. 53.

    Li, Y. H. et al. Sirtuin 3 (SIRT3) Regulates alpha-smooth muscle actin (alpha-SMA) production through the succinate dehydrogenase-G protein-coupled receptor 91 (GPR91) pathway in hepatic stellate cells. J. Biol. Chem. 291, 10277–10292 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  54. 54.

    Li, Y. H., Woo, S. H., Choi, D. H. & Cho, E. H. Succinate causes alpha-SMA production through GPR91 activation in hepatic stellate cells. Biochem. Biophys. Res. Commun. 463, 853–858 (2015).

    CAS  PubMed  Google Scholar 

  55. 55.

    Cypess, A. M. et al. Cold but not sympathomimetics activates human brown adipose tissue in vivo. Proc. Natl Acad. Sci. USA 109, 10001–10005 (2012).

    CAS  PubMed  Google Scholar 

  56. 56.

    Haukeland, J. W. et al. Systemic inflammation in nonalcoholic fatty liver disease is characterized by elevated levels of CCL2. J. Hepatol. 44, 1167–1174 (2006).

    CAS  PubMed  Google Scholar 

  57. 57.

    Kao, Y. H. et al. Upregulation of hepatoma-derived growth factor is involved in murine hepatic fibrogenesis. J. Hepatol. 52, 96–105 (2010).

    CAS  PubMed  Google Scholar 

  58. 58.

    Kim, J. et al. Thymosin beta-4 regulates activation of hepatic stellate cells via hedgehog signaling. Sci. Rep. 7, 3815 (2017).

    PubMed  PubMed Central  Google Scholar 

  59. 59.

    Hochachka, P. W., Owen, T. G., Allen, J. F. & Whittow, G. C. Multiple end products of anaerobiosis in diving vertebrates. Comp. Biochem Physiol. B. 50, 17–22 (1975).

    CAS  PubMed  Google Scholar 

  60. 60.

    Hochachka, P. W. & Dressendorfer, R. H. Succinate accumulation in man during exercise. Eur. J. Appl Physiol. Occup. Physiol. 35, 235–242 (1976).

    CAS  PubMed  Google Scholar 

  61. 61.

    Gravel, S. P., Andrzejewski, S., Avizonis, D. & St-Pierre, J. Stable isotope tracer analysis in isolated mitochondria from mammalian systems. Metabolites 4, 166–183 (2014).

    PubMed  PubMed Central  Google Scholar 

  62. 62.

    Navarrete-Perea, J., Yu, Q., Gygi, S. P. & Paulo, J. A. Streamlined tandem mass tag (SL-TMT) protocol: an efficient strategy for quantitative (phospho)proteome profiling using tandem mass tag-synchronous precursor selection-MS3. J. Proteome Res. 17, 2226–2236 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

  63. 63.

    Schweppe, D. K. et al. Full-featured, real-time database searching platform enables fast and accurate multiplexed quantitative proteomics. J. Proteome Res. 19, 2026–2034 (2020).

    CAS  PubMed  PubMed Central  Google Scholar 

  64. 64.

    McAlister, G. C. et al. MultiNotch MS3 enables accurate, sensitive, and multiplexed detection of differential expression across cancer cell line proteomes. Anal. Chem. 86, 7150–7158 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  65. 65.

    Schweppe, D. K. et al. Characterization and optimization of multiplexed quantitative analyses using high-field asymmetric-waveform ion mobility mass spectrometry. Anal. Chem. 91, 4010–4016 (2019).

    CAS  PubMed  PubMed Central  Google Scholar 

  66. 66.

    Eng, J. K., Jahan, T. A. & Hoopmann, M. R. Comet: an open-source MS/MS sequence database search tool. Proteomics 13, 22–24 (2013).

    CAS  PubMed  Google Scholar 

  67. 67.

    Elias, J. E. & Gygi, S. P. Target-decoy search strategy for increased confidence in large-scale protein identifications by mass spectrometry. Nat. Methods 4, 207–214 (2007).

    CAS  PubMed  Google Scholar 

  68. 68.

    Huttlin, E. L. et al. A tissue-specific atlas of mouse protein phosphorylation and expression. Cell 143, 1174–1189 (2010).

    CAS  PubMed  PubMed Central  Google Scholar 

  69. 69.

    Peng, J., Elias, J. E., Thoreen, C. C., Licklider, L. J. & Gygi, S. P. Evaluation of multidimensional chromatography coupled with tandem mass spectrometry (LC/LC-MS/MS) for large-scale protein analysis: the yeast proteome. J. Proteome Res 2, 43–50 (2003).

    CAS  PubMed  Google Scholar 

  70. 70.

    Chen, E. Y. et al. Enrichr: interactive and collaborative HTML5 gene list enrichment analysis tool. BMC Bioinf. 14, 128 (2013).

    Google Scholar 

  71. 71.

    Kuleshov, M. V. et al. Enrichr: a comprehensive gene set enrichment analysis web server 2016 update. Nucleic Acids Res. 44, W90–W97 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  72. 72.

    Perez-Riverol, Y. et al. The PRIDE database and related tools and resources in 2019: improving support for quantification data. Nucleic Acids Res. 47, D442–D450 (2019).

    CAS  PubMed  PubMed Central  Google Scholar 

  73. 73.

    Ravussin, Y., Gutman, R., LeDuc, C. A. & Leibel, R. L. Estimating energy expenditure in mice using an energy balance technique. Int J. Obes. 37, 399–403 (2013).

    CAS  Google Scholar 

  74. 74.

    Goldgof, M. et al. The chemical uncoupler 2,4-dinitrophenol (DNP) protects against diet-induced obesity and improves energy homeostasis in mice at thermoneutrality. J. Biol. Chem. 289, 19341–19350 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  75. 75.

    Guo, J. & Hall, K. D. Predicting changes of body weight, body fat, energy expenditure and metabolic fuel selection in C57BL/6 mice. PLoS ONE 6, e15961 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  76. 76.

    Mederacke, I., Dapito, D. H., Affo, S., Uchinami, H. & Schwabe, R. F. High-yield and high-purity isolation of hepatic stellate cells from normal and fibrotic mouse livers. Nat. Protoc. 10, 305–315 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  77. 77.

    Zhang, Q. et al. Isolation and culture of single cell types from rat liver. Cells Tissues Organs 201, 253–267 (2016).

    PubMed  Google Scholar 

Download references

Acknowledgements

This work was supported by the Claudia Adams Barr Program, the Lavine Family Fund and NIH grant no. DK123095 (E.T.C), NIH grant no. DK123321 (E.L.M.), the National Cancer Center (H.X.), grant no. R01DK078081 (N.N.D.) and the Juvenile Diabetes Research Foundation (A.F.). We thank B. Spiegelman, P. Puigserver, K. Sharabi, E. Rosen, S. Patel and R. Bronson for discussions, the Nikon Imaging Center at Harvard Medical School and the Harvard Center for Biological Imaging for assistance with microscopy, Dana-Farber/Harvard Cancer Center Rodent Histopathology Core (grant no. NIH-5-P30-CA06516) for preparing histology slides and the Harvard Digestive Disease Center, Core D for assistance with bomb calorimetry. Cartoon illustrations in Figs. 1f, 3a, 3h, 4c were created with BioRender.com.

Author information

Affiliations

Authors

Contributions

E.L.M. designed research, carried out experiments and analysed data. H.X., M.P.J., J.S., G.A.B. and A.F. carried out and analysed data from mass spectrometry experiments. R.G. and N.V.T. assisted with animal physiology experiments. C.H. and H.P. assisted with flow cytometry experiments. A.R. assisted with imaging experiments. S.P.G. and N.N.D. oversaw mass spectrometry experiments. L.L. oversaw flow cytometry experiments. E.T.C. directed research and cowrote the paper with assistance from the other authors.

Corresponding author

Correspondence to Edward T. Chouchani.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

Peer review information Nature Metabolism thanks the anonymous reviewers for their contribution to the peer review of this work. Primary Handling Editor: George Caputa.

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data

Extended Data Fig. 1 UCP1KO depletes the UCP1 catabolic circuit in BAT.

a, Protein abundance differences between WT and UCP1KO BAT of mitochondrial respiratory chain proteins (WT n = 5; UCP1KO n = 4). b, Depiction of the UCP1 catabolic circuit that includes UCP1 and the mitochondrial respiratory chain components that generate mitochondrial membrane potential, which is subsequently dissipated by UCP1. KO of UCP1 depletes the entire circuit in BAT, as shown in (a). See source data for precise p values.

Source data

Extended Data Fig. 2 Validation of western diet as a model of NAFLD, food intake during WD, chow diet liver assessment and lymphoid immune populations.

a, b, Relative gene expression in liver of mice following 14 weeks on chow or western diet (n = 4 except Cd11b chow n = 3, Cd11c WD n = 3). c, Levels of ALT (left) and AST (right) in plasma following 14 weeks chow or WD feeding (n = 4). d, Calories consumed during 14 weeks WD feeding comparing WT and UCP1KO mice (n = 10). e-i, Protein abundance differences of annotated pathways proteins or HSC activation proteins between WT and UCP1KO liver following 14 weeks chow feeding. (WT n = 4, UCP1KO n = 5). Data represent fold over WT. j, Fraction of CD45+ cells for each indicated population from livers of WT and UCP1KO mice following 14 weeks on WD (CD3, CD8 WT n = 10, UCP1KO n = 13; CD4 WT n = 10, UCP1KO n = 12; CD19 WT n = 13, UCP1KO n = 16). *P < 0.05, **P < 0.01, ***P < 0.001 (two-tailed Student’s t-test for pairwise comparisons). Data are mean ± s.e.m. See source data for precise p values.

Source data

Extended Data Fig. 3 The UCP1 catabolic circuit controls liver extracellular succinate levels.

a, Extracellular fluid extraction protocol. b, Liver tissue metabolomics: All annotated metabolites (grey), metabolites significantly changed (black), succinate (red) following 14 weeks on WD (n = 10). c, Absolute succinate concentration in liver and epi EF following 14 weeks on WD (Liver EF: WT, UCP1KO n = 8; SUCNR1/UCP1KO n = 9; Epi EF: WT n = 5; UCP1KO, SUCNR1/UCP1KO n = 9). d, e, BAT succinate catabolism determines as % of 2 min (m + 4) 13C-succinate and downstream (m + 4) 13C-TCA cycle metabolites remaining at 30 mins in BAT (c) and subQ (d) following 10 days daily injection with vehicle or i.p. β-adrenoreceptor agonism with CL-316,243 (1 mg/kg) and subsequent bolus i.v. 13C-succinate (100 mg/kg) for the indicated times (n = 5, except vehicle 2 min n = 4 in d). f, Abundance of succinate in TCA metabolites in BAT (left) and SubQ (right) following either 29 °C housing or 2 weeks 4 °C exposure (n = 5). g, (m + 4) 13C-succinate and downstream (m + 4) TCA cycle metabolite abundance following pre-treatment with vehicle or i.p. β-adrenoreceptor agonism with CL-316,243 (1 mg/kg; 30 min) and subsequent bolus i.v. 13C-succinate (100 mg/kg) for the indicated times. (Fumarate: 0 min n = 11, 2 min veh n = 11, 5 min veh n = 13, 30 min veh n = 12, 2 min CL n = 11, 5 min CL n = 13, 30 min CL n = 12; malate: 0 min n = 10, 2 min veh n = 11, 5 min veh n = 13, 30 min veh n = 12, 2 min CL n = 11, 5 min CL n = 13, 30 min CL n = 12; succinate: 0 min n = 10, 2 min veh n = 11, 5 min veh n = 13, 30 min veh n = 12, 2 min CL n = 11, 5 min CL n = 12, 30 min CL n = 11). *P < 0.05, **P < 0.01, ***P < 0.001. (two-tailed Student’s t-test for pairwise comparisons, one-way ANOVA for multiple comparisons involving independent variable, two-way ANOVA for multiple comparisons involving two independent variables). Data are mean ± s.e.m. See source data for precise p values.

Source data

Extended Data Fig. 4 Assessment of UCP1/SUCNR1KO energy expenditure, caloric absorption and caloric intake during WD.

a-c, Whole body energy expenditure of mice during 7 days WD feeding for WT, UCP1KO, and UCP1/SUCNR1KO mice (n = 8 except a WT n = 7) as determined by indirect calorimetry. d, e, Caloric absorption (d) and energy assimilation (e) during 7 days WD feeding. Proportion of energy assimilated from diet was determined by subtracting the total calories remaining in mouse feces from the total calories consumed in the same period (n = 8 from one assessment). f, Calories consumed during 14 weeks WD feeding (n = 10). One-way ANOVA for multiple comparisons involving independent variable, two-way ANOVA for multiple comparisons involving two independent variables, ANCOVA for b, c. Data are mean ± s.e.m. Assessments of UCP1/SUCNR1KO mice were performed simultaneously with WT and UCP1KO as depicted in Extended Data Fig. 2, so WT and UCP1KO presentations in this figure are from the same underlying data reported in Figure Extended Data Fig. 2. See source data for precise p values.

Source data

Extended Data Fig. 5 Assessment of UCP1/SUCNR1KO during WD and succinate drinking water experiments.

a, Representative cytofluorimetric dot plots for indicated immune cell populations from livers of WT, UCP1KO and UCP1/SUCNR1KO mice following 14 weeks on WD. b, Relative gene expression in WT, UCP1KO, and UCP1/SUCNR1KO livers following 14 weeks WD feeding (n = 10 except Il6, Nos2 n = 9 in WT and Nos2 n = 9 in UCP1/SUCNR1KO). c, Fraction of CD45+ cells for each indicated gated cell population from livers of WT, UCP1KO and UCP1/SUCNR1KO mice following 14 weeks on WD (n = 9 except CD8 n = 7 in UCP1/SUCNR1KO). d-h, Protein abundance differences of annotated pathways proteins or HSC activation proteins between vehicle and 1.5% succinate-treated UCP1KO liver following 6 weeks HFD (n = 3). Data represent fold over 0%. i, Sirius red staining observed in liver harvested from mice following 14 weeks WD feeding (upper panels 20x magnification, scale bars 100 μm; middle panels, 10x magnification, scale bars 200 μm, lower panels, 4x magnification, scale bars 200 μm; n = 4 biological replicates/genotype imaged). j, Relative abundance of hydroxyproline in plasma following 14 weeks on WD WT (n = 10). *P < 0.05, **P < 0.01, ***P < 0.001. (two-tailed Student’s t-test for pairwise comparisons, one-way ANOVA for multiple comparisons involving independent variable). Data are mean ± s.e.m. Assessments of UCP1/SUCNR1KO mice were performed simultaneously with WT and UCP1KO as depicted in Fig. 2 and Extended Data Fig. 2, so WT and UCP1KO presentations in this figure are from the same underlying data reported in Fig. 2 and Extended Data Fig. 2. See source data for precise p values.

Source data

Extended Data Fig. 6 Physiological assessment of WT and SUCNR1KO mice upon WD feeding.

a, b, Change in body mass (a) and final body weight (b) during WD feeding (22 °C n = 18, 29 °C n = 26). c, Body composition of mice following 14 weeks WD feeding (22 °C n = 18, 29 °C n = 26). d, Relative Ucp1 gene expression in BAT following 14 weeks on WD (n = 8). e, f, Change in body mass (e) and final body weight (f) of SUCNR1KO mice during 14 weeks WD feeding (22 °C n = 27, 29 °C n = 30). g, Body composition of mice following 14 weeks WD feeding (22 °C n = 27, 29 °C n = 30). h, Relative Ucp1 gene expression in BAT following 14 weeks on western diet (n = 8). i, ANCOVA analysis of energy expenditure following 14 weeks WD feeding. (WT 22 °C n = 18, WT 29 °C n = 27, SUCNR1KO 22 °C n = 27, SUCNR1KO 29 °C n = 30). j, Calories consumed during 14 weeks WD feeding. (WT 22 °C n = 19, WT 29 °C n = 26, SUCNR1KO 22 °C n = 27, SUCNR1KO 29 °C n = 31). **P < 0.01, ***P < 0.001. (two-tailed Student’s t-test for pairwise comparisons, ANCOVA for i). Data are mean ± s.e.m. See source data for precise p values.

Source data

Extended Data Fig. 7 SUCNR1 ablation is protective against liver dysfunction initiated by thermoneutral housing.

a, Protein abundance differences of annotated pathway proteins between WT and SUCNR1KO liver following 14 weeks WD feeding at thermoneutrality. Top pathways enriched in proteins exhibiting > 30% decrease between groups highlighted; (WT n = 7, SUCNR1KO n = 8). b-e, Protein abundance differences of top enriched pathways between WT and SUCNR1KO liver following 14 weeks WD feeding at thermoneutrality. (WT n = 7, SUCNR1KO n = 8). Data represent fold over WT. For (e, j): 1. Innate immune response in mucosa; 2. MyD88-dependent toll-like receptor signalling pathway; 3. Positive regulation of cell-matrix adhesion; 4. Interleukin-12-mediated signaling pathway; 5. Transforming growth factor beta receptor signaling pathway. 6. Additional inflammatory proteins not annotated in pathways. f, Protein abundance differences of annotated pathway proteins between WT and SUCNR1KO liver following 14 weeks WD feeding at room temperature. Top pathways found to be enriched in proteins exhibiting > 30% decrease between WT and SUCNR1KO at thermoneutrality in (a) are highlighted; (WT n = 7, SUCNR1KO n = 8). g-j, Protein abundance differences of annotated pathways proteins between WT and SUCNR1KO liver following 14 weeks WD feeding at room temperature. (WT n = 7, SUCNR1KO n = 8). Data represent fold over WT. k, Protein abundance differences of annotated pathway proteins between WT and SUCNR1KO liver following 14 weeks WD feeding at room temperature. Top pathways found to be enriched in proteins exhibiting > 30% decrease between WT and SUCNR1KO at room temperature are highlighted; (WT n = 7, SUCNR1KO n = 8). l, Protein abundance differences of annotated pathway proteins between WT and SUCNR1KO liver following 14 weeks WD feeding at room temperature. (WT n = 7, SUCNR1KO n = 8). Data represent fold over WT. *P < 0.05, **P < 0.01, ***P < 0.001. (two-tailed Student’s t-test for pairwise comparisons). Data are mean ± s.e.m. See source data for precise p values.

Source data

Extended Data Fig. 8 SUCNR1 ablation limits WD-induced inflammatory and ECM remodelling protein abundance at thermoneutrality but not at room temperature.

a-h, Protein abundance differences of annotated pathways proteins between WT and SUCNR1KO liver following 14 weeks WD feeding at thermoneutrality (a, c, e, g) or room temperature (b, d, f, h). (WT n = 10-11, SUCNR1KO n = 10-12; except A4, GAS6, ICAM2, LAMA1, LOXL2, ITA4, MMP14, WT n = 5–7, SUCNR1KO n = 8). Data represent fold over WT at each temperature. Illustrated proteins are from top pathways found to be enriched in proteins exhibiting > 50% increase between WT and UCP1KO in Fig. 2. i, 13C4-succinate uptake into brown adipocytes, KC and HSCs following 2 min incubation with 13C4-succinate (100 μM). Data represent relative signal normalized to cell number (n = 3). Data represent fold over brown adipocytes vehicle. j, UCP1 protein abundance (sum signal to noise ratio) in BAT, KC and HSCs (BAT n = 5; KC, HSC n = 3). k, Relative Ucp1 expression in BAT, KC and HSCs (BAT n = 5; KC, HSC n = 3). Data represent fold over BAT. *P < 0.05, **P < 0.01, ***P < 0.001. (two-tailed Student’s t-test for pairwise comparisons). Data are mean ± s.e.m. See source data for precise p values.

Source data

Supplementary information

Supplementary Information

Supplementary Figs. 1 and 2

Reporting Summary

Supplementary Tables

Supplementary Tables 1–13

Source data

Source Data Fig. 1

Statistical source data.

Source Data Fig. 2

Statistical source data.

Source Data Fig. 3

Statistical source data.

Source Data Fig. 4

Statistical source data.

Source Data Fig. 5

Statistical source data.

Source Data Fig. 6

Statistical source data.

Source Data Fig. 7

Statistical source data.

Source Data Extended Data Fig. 1

Statistical source data.

Source Data Extended Data Fig. 2

Statistical source data.

Source Data Extended Data Fig. 3

Statistical source data.

Source Data Extended Data Fig. 4

Statistical source data.

Source Data Extended Data Fig. 5

Statistical source data.

Source Data Extended Data Fig. 6

Statistical source data.

Source Data Extended Data Fig. 7

Statistical source data.

Source Data Extended Data Fig. 8

Statistical source data.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Mills, E.L., Harmon, C., Jedrychowski, M.P. et al. UCP1 governs liver extracellular succinate and inflammatory pathogenesis. Nat Metab 3, 604–617 (2021). https://doi.org/10.1038/s42255-021-00389-5

Download citation

Search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing