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.

CLSTN3β enforces adipocyte multilocularity to facilitate lipid utilization

Nature volume 613, pages 160–168 (2023)Cite this article

Subjects

Abstract

Multilocular adipocytes are a hallmark of thermogenic adipose tissue1,2, but the factors that enforce this cellular phenotype are largely unknown. Here, we show that an adipocyte-selective product of the Clstn3 locus (CLSTN3β) present in only placental mammals facilitates the efficient use of stored triglyceride by limiting lipid droplet (LD) expansion. CLSTN3β is an integral endoplasmic reticulum (ER) membrane protein that localizes to ER–LD contact sites through a conserved hairpin-like domain. Mice lacking CLSTN3β have abnormal LD morphology and altered substrate use in brown adipose tissue, and are more susceptible to cold-induced hypothermia despite having no defect in adrenergic signalling. Conversely, forced expression of CLSTN3β is sufficient to enforce a multilocular LD phenotype in cultured cells and adipose tissue. CLSTN3β associates with cell death-inducing DFFA-like effector proteins and impairs their ability to transfer lipid between LDs, thereby restricting LD fusion and expansion. Functionally, increased LD surface area in CLSTN3β-expressing adipocytes promotes engagement of the lipolytic machinery and facilitates fatty acid oxidation. In human fat, CLSTN3B is a selective marker of multilocular adipocytes. These findings define a molecular mechanism that regulates LD form and function to facilitate lipid utilization in thermogenic adipocytes.

This is a preview of subscription content, access via your institution

Access options

Rent or buy this article

Get just this article for as long as you need it

$39.95

Learn more

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: CLSTN3β is an ER-resident protein that localizes to ER–LD contact sites.
Fig. 2: Loss of CLSTN3β expression perturbs LD morphology and lipid utilization in BAT.
Fig. 3: Forced expression of CLSTN3β promotes multilocularity and lipid utilization in adipocytes.
Fig. 4: CLSTN3β expression is associated with multilocular adipose tissue in mice and humans.
Fig. 5: CLSTN3β associates with CIDE proteins and blocks LD fusion.

Data availability

Source data for all figures are provided with the paper. The RNA-sequencing dataset generated for this paper is available at accession number GSE181123. The previously published RNA-sequencing dataset used for LeafCutter splicing analysis in this paper is available at accession number GSE65776. All unique biological materials used are readily available from the authors or from standard commercial sources. 

References

  1. Wang, W. & Seale, P. Control of brown and beige fat development. Nat. Rev. Mol. Cell Biol. 17, 691–702 (2016).

    CAS  Google Scholar 

  2. Cohen, P. & Kajimura, S. The cellular and functional complexity of thermogenic fat. Nat. Rev. Mol. Cell Biol. 22, 393–409 (2021).

    CAS  Google Scholar 

  3. Trayhurn, P. Brown adipose tissue—a therapeutic target in obesity? Front. Physiol. 9, 1672 (2018).

    Google Scholar 

  4. Cannon, B. & Nedergaard, J. Brown adipose tissue: function and physiological significance. Physiol. Rev. 84, 277–359 (2004).

    CAS  Google Scholar 

  5. Rasmussen, A. T. The so‐called hibernating gland. J. Morphol. 38, 147–205 (1923).

    Google Scholar 

  6. Barneda, D. et al. The brown adipocyte protein CIDEA promotes lipid droplet fusion via a phosphatidic acid-binding amphipathic helix. eLife 4, e07485 (2015).

    Google Scholar 

  7. Nishimoto, Y. & Tamori, Y. CIDE family-mediated unique lipid droplet morphology in white adipose tissue and brown adipose tissue determines the adipocyte energy metabolism. J. Atherosclerosis Thrombosis 24, 989–998 (2017).

    CAS  Google Scholar 

  8. Xu, L., Zhou, L. & Li, P. CIDE proteins and lipid metabolism. Arter. Thromb. Vasc. Biol. 32, 1094–1098 (2012).

    CAS  Google Scholar 

  9. Gao, G. et al. Control of lipid droplet fusion and growth by CIDE family proteins. Biochim. Biophys. Acta Mol. Cell Biol. Lipids 1862, 1197–1204 (2017).

    CAS  Google Scholar 

  10. Puri, V. et al. Cidea is associated with lipid droplets and insulin sensitivity in humans. Proc. Natl Acad. Sci. USA 105, 7833–7838 (2008).

    ADS  CAS  Google Scholar 

  11. Gong, J. et al. Fsp27 promotes lipid droplet growth by lipid exchange and transfer at lipid droplet contact sites. J. Cell Biol. 195, 953–963 (2011).

    CAS  Google Scholar 

  12. Sun, Z. et al. Perilipin1 promotes unilocular lipid droplet formation through the activation of Fsp27 in adipocytes. Nat. Commun. 4, 1594 (2013).

    ADS  Google Scholar 

  13. Lyu, X. et al. A gel-like condensation of Cidec generates lipid-permeable plates for lipid droplet fusion. Dev. Cell 56, 2592–2606.e7 (2021).

    CAS  Google Scholar 

  14. Zhou, Z. et al. Cidea-deficient mice have lean phenotype and are resistant to obesity. Nat. Genet. 35, 49–56 (2003).

    Google Scholar 

  15. Nishimoto, Y. et al. Cell death-inducing DNA fragmentation factor A-like effector A and fat-specific protein 27β coordinately control lipid droplet size in brown adipocytes. J. Biol. Chem. 292, 10824–10834 (2017).

    CAS  Google Scholar 

  16. Li, J. Z. et al. Cideb regulates diet-induced obesity, liver steatosis, and insulin sensitivity by controlling lipogenesis and fatty acid oxidation. Diabetes 56, 2523–2532 (2007).

    CAS  Google Scholar 

  17. Zhou, L. et al. Cidea promotes hepatic steatosis by sensing dietary fatty acids. Hepatology 56, 95–107 (2012).

    CAS  Google Scholar 

  18. Xu, X., Park, J. G., So, J. S. & Lee, A. H. Transcriptional activation of Fsp27 by the liver-enriched transcription factor CREBH promotes lipid droplet growth and hepatic steatosis. Hepatology 61, 857–869 (2015).

    CAS  Google Scholar 

  19. Puri, V. et al. Fat-specific protein 27, a novel lipid droplet protein that enhances triglyceride storage. J. Biol. Chem. 282, 34213–34218 (2007).

    CAS  Google Scholar 

  20. Nishino, N. et al. FSP27 contributes to efficient energy storage in murine white adipocytes by promoting the formation of unilocular lipid droplets. J. Clin. Invest. 118, 2808–2821 (2008).

    CAS  Google Scholar 

  21. Toh, S. Y. et al. Up-regulation of mitochondrial activity and acquirement of brown adipose tissue-like property in the white adipose tissue of Fsp27 deficient mice. PLoS ONE 3, e2890 (2008).

    ADS  Google Scholar 

  22. Rubio-Cabezas, O. et al. Partial lipodystrophy and insulin resistant diabetes in a patient with a homozygous nonsense mutation in CIDEC. EMBO Mol. Med. 1, 280–287 (2009).

    CAS  Google Scholar 

  23. Ye, J. et al. Cideb, an ER- and lipid droplet-associated protein, mediates VLDL lipidation and maturation by interacting with apolipoprotein B. Cell Metab. 9, 177–190 (2009).

    CAS  Google Scholar 

  24. Wu, L. Z. et al. Cidea controls lipid droplet fusion and lipid storage in brown and white adipose tissue. Sci. China Life Sci. 57, 107–116 (2014).

    CAS  Google Scholar 

  25. Zhang, S. et al. Cidea control of lipid storage and secretion in mouse and human sebaceous glands. Mol. Cell. Biol. 34, 1827–1838 (2014).

    Google Scholar 

  26. Zeng, X. et al. Innervation of thermogenic adipose tissue via a calsyntenin 3β–S100b axis. Nature 569, 229–235 (2019).

    ADS  Google Scholar 

  27. Li, Y. I. et al. Annotation-free quantification of RNA splicing using LeafCutter. Nat. Genet. 50, 151–158 (2018).

    CAS  Google Scholar 

  28. Siersbæk, M. S. et al. Genome-wide profiling of peroxisome proliferator-activated receptor γ in primary epididymal, inguinal, and brown adipocytes reveals depot-selective binding correlated with gene expression. Mol. Cell. Biol. 32, 3452–3463 (2012).

    Google Scholar 

  29. Martell, J. D., Deerinck, T. J., Lam, S. S., Ellisman, M. H. & Ting, A. Y. Electron microscopy using the genetically encoded APEX2 tag in cultured mammalian cells. Nat. Protoc. 12, 1792–1816 (2017).

    CAS  Google Scholar 

  30. Krogh, A., Larsson, B., Von Heijne, G. & Sonnhammer, E. L. L. Predicting transmembrane protein topology with a hidden Markov model: Application to complete genomes. J. Mol. Biol. 305, 567–580 (2001).

    CAS  Google Scholar 

  31. Yang, J. & Zhang, Y. I-TASSER server: New development for protein structure and function predictions. Nucleic Acids Res. 43, W174–W181 (2015).

    ADS  CAS  Google Scholar 

  32. Buchan, D. W. A. & Jones, D. T. The PSIPRED Protein Analysis Workbench: 20 years on. Nucleic Acids Res. 47, W402–W407 (2019).

    CAS  Google Scholar 

  33. Källberg, M. et al. Template-based protein structure modeling using the RaptorX web server. Nat. Protoc. 7, 1511–1522 (2012).

    Google Scholar 

  34. Baek, M. et al. Accurate prediction of protein structures and interactions using a three-track neural network. Science (80-.). 373, 871–876 (2021).

    ADS  CAS  Google Scholar 

  35. Hung, V. et al. Spatially resolved proteomic mapping in living cells with the engineered peroxidase APEX2. Nat. Protoc. 11, 456–475 (2016).

    CAS  Google Scholar 

  36. Stevenson, J., Huang, E. Y. & Olzmann, J. A. Endoplasmic reticulum-associated degradation and lipid homeostasis. Annual Rev. Nutrition 36, 511–542 (2016).

    CAS  Google Scholar 

  37. Olzmann, J. A. & Carvalho, P. Dynamics and functions of lipid droplets. Nat. Rev. Mol. Cell Biol. 20, 137–155 (2019).

    CAS  Google Scholar 

  38. Roberts, M. A. & Olzmann, J. A. Protein quality control and lipid droplet metabolism. Annu. Rev. Cell Dev. Biol. 36, 115–139 (2020).

    CAS  Google Scholar 

  39. Ruggiano, A., Mora, G., Buxó, L. & Carvalho, P. Spatial control of lipid droplet proteins by the ERAD ubiquitin ligase Doa10. EMBO J. 35, 1644–1655 (2016).

    CAS  Google Scholar 

  40. Bersuker, K. et al. A proximity labeling strategy provides insights into the composition and dynamics of lipid droplet proteomes. Dev. Cell 44, 97–112.e7 (2018).

    CAS  Google Scholar 

  41. Huang, E. Y. et al. A VCP inhibitor substrate trapping approach (VISTA) enables proteomic profiling of endogenous ERAD substrates. Mol. Biol. Cell 29, 1021–1030 (2018).

    Google Scholar 

  42. Song, B. L., Sever, N. & DeBose-Boyd, R. A. Gp78, a membrane-anchored ubiquitin ligase, associates with Insig-1 and couples sterol-regulated ubiquitination to degradation of HMG CoA reductase. Mol. Cell 19, 829–840 (2005).

    CAS  Google Scholar 

  43. Guo, Y. et al. Functional genomic screen reveals genes involved in lipid-droplet formation and utilization. Nature 453, 657–661 (2008).

    ADS  CAS  Google Scholar 

  44. Bagchi, D. P., Forss, I., Mandrup, S. & MacDougald, O. A. SnapShot: niche determines adipocyte character I. Cell Metabolism 27, 264–264.e1 (2018).

    CAS  Google Scholar 

  45. Oelkrug, R. et al. Brown fat in a protoendothermic mammal fuels eutherian evolution. Nat. Commun. 4, 2140 (2013).

    ADS  Google Scholar 

  46. Jespersen, N. Z. et al. Heterogeneity in the perirenal region of humans suggests presence of dormant brown adipose tissue that contains brown fat precursor cells. Mol. Metab. 24, 30–43 (2019).

    CAS  Google Scholar 

  47. Plucińska, K. et al. Calsyntenin 3β is dynamically regulated by temperature in murine brown adipose and marks human multilocular fat. Front. Endocrinol. 11, 767 (2020).

    Google Scholar 

  48. Vergnes, L. et al. Adipocyte browning and higher mitochondrial function in periadrenal but not SC fat in pheochromocytoma. J. Clin. Endocrinol. Metab. 101, 4440–4448 (2016).

    CAS  Google Scholar 

  49. Wang, F. et al. RNAscope: a novel in situ RNA analysis platform for formalin-fixed, paraffin-embedded tissues. J. Mol. Diagnostics 14, 22–29 (2012).

    CAS  Google Scholar 

  50. Christianson, J. L., Boutet, E., Puri, V., Chawla, A. & Czech, M. P. Identification of the lipid droplet targeting domain of the Cidea protein. J. Lipid Res. 51, 3455–3462 (2010).

    CAS  Google Scholar 

  51. Cypess, A. M. et al. Identification and importance of brown adipose tissue in adult humans. N. Engl. J. Med. 360, 1509–1517 (2009).

    CAS  Google Scholar 

  52. van Marken Lichtenbelt, W. D. et al. Cold-activated brown adipose tissue in healthy men. N. Engl. J. Med. 360, 1500–1508 (2009).

    Google Scholar 

  53. Virtanen, K. A. et al. Functional brown adipose tissue in healthy adults. N. Engl. J. Med. 360, 1518–1525 (2009).

    CAS  Google Scholar 

  54. Cypess, A. M. et al. Activation of human brown adipose tissue by a β3-adrenergic receptor agonist. Cell Metab. 21, 33–38 (2015).

    CAS  Google Scholar 

  55. Becher, T. et al. Brown adipose tissue is associated with cardiometabolic health. Nat. Med. 27, 58–65 (2021).

    CAS  Google Scholar 

  56. de Jong, J. M. A. et al. Human brown adipose tissue is phenocopied by classical brown adipose tissue in physiologically humanized mice. Nat. Metab. 1, 830–843 (2019).

    Google Scholar 

  57. Sass, F. et al. TFEB deficiency attenuates mitochondrial degradation upon brown adipose tissue whitening at thermoneutrality. Mol. Metab. 47, 101173 (2021).

    CAS  Google Scholar 

  58. Schlein, C. et al. Endogenous fatty acid synthesis drives brown adipose tissue involution. Cell Rep. 34, 108624 (2021).

    CAS  Google Scholar 

  59. Bai, N. et al. CLSTN3 gene variant associates with obesity risk and contributes to dysfunction in white adipose tissue. Mol. Metab. 63, 101531 (2022).

    CAS  Google Scholar 

  60. Rajbhandari, P. et al. IL-10 signaling remodels adipose chromatin architecture to limit thermogenesis and energy expenditure. Cell 172, 218–233.e17 (2018).

    CAS  Google Scholar 

  61. Brinkman, E. K., Chen, T., Amendola, M. & Van Steensel, B. Easy quantitative assessment of genome editing by sequence trace decomposition. Nucleic Acids Res. 42, e168–e168 (2014).

    Google Scholar 

  62. Dehairs, J., Talebi, A., Cherifi, Y. & Swinnen, J. V. CRISP-ID: decoding CRISPR mediated indels by Sanger sequencing. Sci. Rep. 6, 28973 (2016).

    ADS  CAS  Google Scholar 

  63. Xie, Z. et al. Gene set knowledge discovery with Enrichr. Curr. Protoc. 1, e90 (2021).

    CAS  Google Scholar 

  64. Mina, A. I. et al. CalR: a web-based analysis tool for indirect calorimetry experiments. Cell Metab. 28, 656–666.e1 (2018).

    CAS  Google Scholar 

  65. Chi, J. et al. Three-dimensional adipose tissue imaging reveals regional variation in beige fat biogenesis and PRDM16-dependent sympathetic neurite density. Cell Metab. 27, 226–236.e3 (2018).

    CAS  Google Scholar 

  66. Chi, J., Crane, A., Wu, Z. & Cohen, P. Adipo-clear: a tissue clearing method for three-dimensional imaging of adipose tissue. J. Vis. Exp. 2018, 58271 (2018).

    Google Scholar 

  67. Richter, K. N. et al. Glyoxal as an alternative fixative to formaldehyde in immunostaining and super‐resolution microscopy. EMBO J. 37, 139–159 (2018).

    CAS  Google Scholar 

  68. Wang, J. et al. Polybasic RKKR motif in the linker region of lipid droplet (LD)–associated protein CIDEC inhibits LD fusion activity by interacting with acidic phospholipids. J. Biol. Chem. 293, 19330–19343 (2018).

    CAS  Google Scholar 

  69. Wang, J., Chua, B. T., Li, P. & Chen, F.-J. Lipid-exchange rate assay for lipid droplet fusion in live cells. Bio-Protocol 9, e3309 (2019).

    CAS  Google Scholar 

Download references

Acknowledgements

We thank H. Yang for sharing valuable expertise. We thank A. Ferrari, J. Sandhu, P. Rajbhandari and all other current and former members of the Tontonoz laboratory for technical assistance and valuable discussions. We thank S. Zhang for unwavering support. Confocal microscopy was performed at the California NanoSystems Institute Advanced Light Microscopy and Spectroscopy Laboratory. PET–CT was performed at the Crump Institute Preclinical Imaging Technology Center. RNAscope was performed at the UCLA Translational Pathology Core Laboratory. This work was supported by grants from the the National Natural Science Foundation of China (grant no. 91857103 to F.-J.C.), NIH (grant nos. R01DK120851 and R01HL136618 to P.T.) and Fondation Leducq (grant no. 19CVD04 to P.T.). K.Q. was supported by grant no. NIH F30DK123986 and a David Geffen Medical Scholarship.

Author information

Authors and Affiliations

  1. Department of Pathology and Laboratory Medicine, University of California, Los Angeles, Los Angeles, CA, USA

    Kevin Qian, Marcus J. Tol, Lauren F. Uchiyama, Xu Xiao, Liujuan Cui, Alexander H. Bedard, Yuta Shimanaka & Peter Tontonoz

  2. Department of Biological Chemistry, University of California, Los Angeles, Los Angeles, CA, USA

    Kevin Qian, Marcus J. Tol, Lauren F. Uchiyama, Xu Xiao, Liujuan Cui, Alexander H. Bedard, Yuta Shimanaka, Yasaman Jami-Alahmadi, Bryce T. Bajar, James A. Wohlschlegel & Peter Tontonoz

  3. Molecular Biology Institute, University of California, Los Angeles, Los Angeles, CA, USA

    Kevin Qian, Marcus J. Tol, Lauren F. Uchiyama, Xu Xiao, Liujuan Cui, Alexander H. Bedard, Yuta Shimanaka & Peter Tontonoz

  4. Institute of Metabolism and Integrative Biology, Fudan University, Shanghai, China

    Jin Wu, Yesheng Yin, Feng-Jung Chen & Peng Li

  5. Department of Medicine, Division of Cardiology, University of California, Los Angeles, Los Angeles, CA, USA

    Thomas A. Weston & Stephen G. Young

  6. Department of Human Genetics, University of California, Los Angeles, Los Angeles, CA, USA

    Thomas A. Weston, Laurent Vergnes, Karen Reue & Stephen G. Young

  7. Cardiac Arrhythmia Center and Neurocardiology Research Program of Excellence, University of California, Los Angeles, Los Angeles, CA, USA

    Pradeep S. Rajendran & Kalyanam Shivkumar

  8. Department of Medicine, Massachusetts General Hospital, Boston, MA, USA

    Pradeep S. Rajendran

  9. Pasarow Mass Spectrometry Laboratory, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, Los Angeles, CA, USA

    Whitaker Cohn & Julian P. Whitelegge

  10. Department of Microbiology, Immunology, and Molecular Genetics, University of California, Los Angeles, Los Angeles, CA, USA

    Chia-Ho Lin & Douglas L. Black

  11. Department of Physiology, University of California, Los Angeles, Los Angeles, CA, USA

    Benita Jin & Laura A. DeNardo

  12. School of Life Sciences, Tsinghua University, Beijing, China

    Peng Li

Authors
  1. Kevin Qian
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Marcus J. Tol
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Jin Wu
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Lauren F. Uchiyama
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Xu Xiao
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Liujuan Cui
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Alexander H. Bedard
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Thomas A. Weston
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Pradeep S. Rajendran
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Laurent Vergnes
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. Yuta Shimanaka
    View author publications

    You can also search for this author in PubMed Google Scholar

  12. Yesheng Yin
    View author publications

    You can also search for this author in PubMed Google Scholar

  13. Yasaman Jami-Alahmadi
    View author publications

    You can also search for this author in PubMed Google Scholar

  14. Whitaker Cohn
    View author publications

    You can also search for this author in PubMed Google Scholar

  15. Bryce T. Bajar
    View author publications

    You can also search for this author in PubMed Google Scholar

  16. Chia-Ho Lin
    View author publications

    You can also search for this author in PubMed Google Scholar

  17. Benita Jin
    View author publications

    You can also search for this author in PubMed Google Scholar

  18. Laura A. DeNardo
    View author publications

    You can also search for this author in PubMed Google Scholar

  19. Douglas L. Black
    View author publications

    You can also search for this author in PubMed Google Scholar

  20. Julian P. Whitelegge
    View author publications

    You can also search for this author in PubMed Google Scholar

  21. James A. Wohlschlegel
    View author publications

    You can also search for this author in PubMed Google Scholar

  22. Karen Reue
    View author publications

    You can also search for this author in PubMed Google Scholar

  23. Kalyanam Shivkumar
    View author publications

    You can also search for this author in PubMed Google Scholar

  24. Feng-Jung Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

  25. Stephen G. Young
    View author publications

    You can also search for this author in PubMed Google Scholar

  26. Peng Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  27. Peter Tontonoz
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

Conceptualization was done by K.Q., M.J.T., P.L. and P.T. Methodology was developed by K.Q., M.J.T., L.C., A.H.B., T.A.W., P.S.R., Y.S., B.T.B., J.P.W., J.A.W. and P.L. Software was written by K.Q., B.T.B. and C.-H.L. Validation was carried out by K.Q., M.J.T., J.W., L.F.U., X.X., L.C., A.H.B., T.A.W., P.S.R., L.V., Y.S., Y.Y., Y.J.-A., W.C. and B.J. Formal analysis was carried out by K.Q., M.J.T., J.W., A.H.B., L.V., Y.J.-A., W.C., B.T.B. and C.-H.L. Investigation was done by K.Q., M.J.T., J.W., L.F.U., X.X., L.C., A.H.B., T.A.W., P.S.R., L.V., Y.S., Y.Y., Y.J.-A., W.C. and B.J. Resources were provided by L.A.D., D.L.B., J.P.W., J.A.W., K.R., K.S., F.-J.C., S.G.Y., P.L. and P.T. Data were curated by K.Q., M.J.T., J.W., L.F.U., A.H.B., T.A.W., P.S.R., L.V., Y.Y., Y.J.-A., W.C., B.T.B., C.-H.L. and B.J. The original draft was written by K.Q. and P.T. Review and editing of the draft were done by K.Q., M.J.T., J.W., L.F.U., X.X., L.C., A.H.B., T.A.W., P.S.R., L.V., Y.S., Y.Y., Y.J.-A., W.C., B.T.B., C.-H.L., B.J., L.A.D., D.L.B., J.P.W., J.A.W., K.R., K.S., F.-J.C., S.G.Y., P.L. and P.T. Visualization was done by K.Q., M.J.T., J.W., L.F.U., X.X., L.C., A.H.B., T.A.W., P.S.R., Y.Y., C.-H.L., B.J. and P.T. Supervision was the responsibility of K.Q., D.L.B., K.R., F.-J.C., S.G.Y., P.L. and P.T. Project administration was done by K.Q., F.-J.C., P.L. and P.T. Funding was acquired by S.G.Y., P.L. and P.T.

Corresponding author

Correspondence to Peter Tontonoz.

Ethics declarations

Competing interests

The authors declare no competing interests.

Peer review

Peer review information

Nature thanks the anonymous reviewers for their contribution to the peer review of this work.

Additional information

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

Extended data figures and tables

Extended Data Fig. 1 Identification of Clstn3b transcript species.

a, RNA-, ATAC-, CAGE-, and H3K4me3 ChIP-seq reads at the Clstn3 locus in mouse preadipocytes (day 0 of differentiation), adipocytes (day 5 of differentiation), cortex, and BAT. b, Summary of mouse Clstn3b transcript variants. Arrows mark positions of possible start codons (ATGs that are in-frame with Clstn3 exons 17/18). c, LeafCutter analysis of differential splice site utilization in mouse BAT and cerebral cortex. Intron clusters are ranked by statistical significance. Clstn3 (rank 8) is highlighted in red. d, LeafCutter output for the Clstn3 intron cluster. e, 5’RLM-RACE products from mouse BAT using gene-specific primers targeting Clstn3 exon 17. f, RT-PCR products from mouse BAT using primers targeting Clstn3b transcript variant 2. Black arrows mark positions of primers (F1-F7 = forward 1 through forward 7, R = reverse). *This splice site is actually two splice sites that are 4 base pairs apart. One (30%) is in-frame with Clstn3 exons 17/18 and produces a protein-coding transcript. The other (5.3%) is out-of-frame with Clstn3 exons 17/18 and produces a non-coding transcript.

Source data

Extended Data Fig. 2 Identification of CLSTN3β protein species and transcriptional regulation of Clstn3b.

a, Whole cell lysates (WCL) and membrane preparations (MP) of control and Clstn3 exon 17 KO Pre-BAT cells (pools of CRISPR-modified immortalized brown preadipocytes differentiated for 5 days). Western blot analysis with a previously unvalidated commercial antibody targeting the C-terminus of CLSTN3 (shared with CLSTN3β) identifies two specific bands in brown adipocytes. b, Membrane preparations of Pre-BAT cells (day 5 of differentiation) and HeLa cells transfected with Clstn3b transcript variant 2 or 3 (only variants with protein-coding potential). Western blot analysis with the CLSTN3 antibody shows that Clstn3b transcript variant 2 produces two bands of the same size as those expressed endogenously in brown adipocytes. c, Membrane preparations of three different Pre-BAT CRISPR pools: control, 3′ (gRNA targeting 3′ end of variant 2, downstream of all possible start codons), and 5′ (gRNA targeting 5′ end of variant 2, downstream of start codon generating longest ORF). Scissors mark positions of gRNAs and black arrows mark possible start codons immediately upstream of gRNAs. Western blot analysis with the CLSTN3 antibody shows that the ~25 kDa band is not a cleavage product of the ~40 kDa band and can be translated from variant 2 independently. d, Whole cell lysates of Pre-BAT cells (day 5 of differentiation) and HeLa cells transfected with Clstn3b transcript variant 2 containing ATG to AAG mutations at each possible start codon (positions marked by arrows). Western blot analysis with the CLSTN3 antibody shows that the first possible start codon (generating shortest ORF) initiates translation of a ~25 kDa protein product. e, Immunoprecipitation (IP) of the endogenous ~25 kDa protein from control (C) and 3′ gRNA (KO) Pre-BAT CRISPR pools (day 5 of differentiation) using the CLSTN3 antibody. f, Fragmentation spectrum of a CLSTN3β-specific peptide identified by IP-MS/MS. g, qPCR analysis of Clstn3 exons 1/2, Clstn3 exons 17/18, and Clstn3b expression in a panel of 15 mouse tissues (n = 5). h, (Left) Clstn3b expression in BAT of mice housed at 30 °C for 2 weeks, 22 °C, or 4 °C for 24 h (n = 4, 5, 5). (Right) Clstn3b expression in iWAT of mice housed at 30 °C for 2 weeks, 22 °C, or 4 °C for 48 h (n = 4, 5, 5). i, Clstn3b expression in BAT, iWAT, and eWAT of mice injected with PBS or 1 mg/kg/day CL-316,243 (CL) for 4 days (n = 4). j, Fold induction of Clstn3 exons 17/18 expression from day 0 to day 5 of differentiation in white and brown preadipocyte cell lines (n = 3). 3T3-L1, (C3H/)10T1/2, and (3T3-)F442A refer to three commonly-used white preadipocyte cell lines. Pre-BAT 1, 2, and 3 refer to three distinct single cell clones isolated from a pool of immortalized primary mouse brown preadipocytes. k, Clstn3b expression in eWAT of mice fed normal chow or a 60% high-fat diet (HFD) for 4 days (n = 5, 4). l, Clstn3b expression in eWAT of mice gavaged with vehicle, GW7647 (PPARα agonist, 10 mg/kg), or rosiglitazone (PPARγ agonist, 10 mg/kg) 3 times in 2 days (n = 8). m, ChIP-qPCR analysis of PPARγ binding to Fabp4, Clstn3b, and Clstn3 promoter elements in 10T1/2 cells (n = 3). n, PPARγ ChIP-seq reads at the Clstn3 locus in primary mouse BAT, iWAT, and eWAT adipocytes and 3T3-L1 cells. Genomic regions targeted in ChIP-qPCR experiment (m) are annotated. Bar plots show mean ± SEM. Each point represents a biological replicate. Two-sided **P < 0.01, ***P < 0.001 by ordinary one-way ANOVA with Dunnett’s multiple comparisons test (h, l), multiple t-tests with Holm-Sidak correction (i, m), or Welch’s t-test (k).

Source data

Extended Data Fig. 3 Structural features of CLSTN3β.

a, Electron microscopy of immortalized brown adipocytes (day 4 of differentiation) stably expressing (left) no APEX2 or (right) an N-terminal APEX2-CLSTN3β fusion. APEX2-CLSTN3β is poorly expressed and thus its localization is not visualized. b, Biochemical extraction of CLSTN3β-Flag (integral membrane protein) and S6 (peripheral membrane protein) from membranes of HEK293T cells treated with OA (250 µM, overnight). P = pellet, S = supernatant. c, Protease protection assay on membranes from HEK293T cells transfected with CLSTN3β-Flag (C-terminal tag) and treated with OA (250 µM, overnight). Calreticulin = inside ER, S6 = outside ER. d, Helical wheel plots of representative α-helices from CLSTN3β, generated using HeliQuest. e, Summary of CLSTN3β secondary structure predictions. Putative hydrophobic hairpins and β-strand domain are underlined. Positively charged and hydrophobic residues in the β-strand domain are colored green and yellow, respectively. f, RoseTTAFold model of full-length CLSTN3β. (Left) Model positioned to highlight hairpin domain (red) and TM domain (green). (Right) Model positioned to highlight hairpin 1 (cyan), hairpin 2 (magenta), hairpin 3 (yellow), and TM domain (green). g, Schematic of CLSTN3β hairpin mutants. h, Confocal microscopy of OA-treated (1 mM, overnight) HeLa cells transfected with ∆H1, ∆H2, ∆H3, ∆H12, ∆H13, or ∆H23 CLSTN3β-Flag constructs and stained with BODIPY 488 or LipidTOX 647. Scale bar = 5 µm.

Extended Data Fig. 4 ER-localized CLSTN3β is degraded by ERAD.

a, Venn diagram showing the number of proteins identified as potential CLSTN3β binding partners by APEX proximity labeling (PL) and Flag immunoprecipitation (IP). b, (Left) Gene ontology (GO) analysis of the high-confidence CLSTN3β interactome (287 proteins). (Right) Partial list of ERAD proteins in the high-confidence CLSTN3β interactome. c, Immortalized brown adipocytes (day 6 of differentiation) were treated with cycloheximide (CHX, 100 µg/mL) for the indicated times and pretreated with either vehicle (DMSO) or CB-5083 (5 µM) for 30 min. d, Confocal microscopy of HeLa cells transfected with CLSTN3β-Flag and GFP-SEC61β and treated with either vehicle (DMSO) or CB-5083 (2.5 µM) for 8 h. Scale bar = 10 µm. e, CLSTN3β-Flag immunoprecipitation from HEK293T cells co-transfected with HA-ubiquitin and treated with either MG132 (25 µM) or CB-5083 (2.5 µM) for 4 h. f, CLSTN3β-Flag immunoprecipitation from HEK293T cells co-transfected with either HA-gp78 or myc-UBE2G2 and treated with CB-5083 (2.5 µM) for 4 h. g, HEK293T cells were co-transfected with CLSTN3β-Flag and either control or gp78 siRNA and treated with CHX (100 µg/mL) for the indicated times.

Source data

Extended Data Fig. 5 Analysis of thermogenesis in CLSTN3β-deficient mice.

a, (Top) Schematic of CRISPR strategy used to generate CLSTN3β KO mice. Scissors mark position of gRNA. (Middle) CRISP-ID analysis of Sanger sequencing trace from CLSTN3β KO founder. PAM sequence is underlined in red. (Bottom) Nucleotide sequences of WT and CLSTN3β KO alleles. Bases altered in KO allele are highlighted in red and premature stop codon is underlined. b, Western blot analysis of membrane preparations of brain and BAT from WT and CLSTN3β KO mice housed at 22 °C. c, Schematic of Cre-Lox strategy used to generate AdC3KO mice. d, qPCR analysis of Clstn3 exons 17/18 expression in (left) brain from WT and AdC3KO mice housed at 22 °C (n = 4, 4) and (right) BAT and iWAT from WT and AdC3KO mice housed at 4 °C for 4 days (n = 8, 6). e, Body weights and compositions of 10-12 week-old male WT and AdC3KO mice on a normal chow diet (n = 18, 22). f, Core body temperatures, g, BAT TAG content, and h, diameters of largest LDs (n = 40, 40) in i, H&E sections of BAT from 10-11 week-old male WT and AdC3KO mice housed at 4 °C for 4 days (n = 8, 6). Scale bar = 50 µm. j, qPCR analysis of BAT and iWAT from 10-11 week-old male WT and AdC3KO mice housed at 4 °C for 4 days (n = 8, 6). k, qPCR analysis and l, H&E sections of BAT and iWAT from 12-14 week-old male WT and AdC3KO mice fed a 10% kcal fat diet containing 50 mg/kg rosiglitazone for 2 weeks (n = 4, 5). Scale bar = 50 µm. Bar plots show mean ± SEM. Each point represents a biological replicate. Violin plots show median (dashed) and quartiles (dotted). Two-sided *P < 0.05, **P < 0.01, ***P < 0.001 by multiple t-tests with Holm-Sidak correction (d, j-k) or Welch’s t-test (g-h).

Source data

Extended Data Fig. 6 Analysis of lipolysis in CLSTN3β-deficient mice.

(a-b), Western blot analysis of BAT LDs and post-nuclear supernatants (PNS) isolated from female WT and AdC3KO mice housed at 22 °C or 4 °C for 24 h (n = 2 mice per lane). Equal amounts of TAG from each condition were loaded onto the gels. From the same experiment as Fig. 5I. c, Ex vivo lipolysis assay performed on iWAT from 11-12 week-old female WT and AdC3KO mice (n = 5, 5). NT = no treatment, ISO = isoproterenol (2 μM). Bar plots show mean ± SEM. Each point represents a biological replicate.

Source data

Extended Data Fig. 7 Characterization of CLSTN3β-deficient mice on a HFD.

a, Body weights and compositions of male and female WT/AdC3KO and WT/CLSTN3β KO mice on 45% and 60% HFD. Male WT/AdC3KO 45% HFD (n = 7, 8), male WT/AdC3KO 60% HFD (n = 6, 13), female WT/AdC3KO 45% HFD (n = 11, 7), female WT/AdC3KO 60% HFD (n = 11, 8), male WT/CLSTN3β KO 45% HFD (n = 13, 11), male WT/CLSTN3β KO 60% HFD (n = 15, 9), female WT/CLSTN3β KO 45% HFD (n = 13, 8), female WT/CLSTN3β KO 60% HFD (n = 15, 10). b, BAT weights from (left) male WT and AdC3KO mice on a 45% HFD for 10 weeks (n = 7, 7) or (right) male WT and CLSTN3β KO mice on a 45% HFD for 12 weeks (n = 13, 11). c, iWAT, eWAT, and liver weights from (left) male WT and AdC3KO mice on a 45% HFD for 10 weeks (n = 7, 8) or (right) male WT and CLSTN3β KO mice on a 45% HFD for 12 weeks (n = 13, 11). d, Intraperitoneal glucose tolerance test performed on male WT and CLSTN3β KO mice on a 45% HFD for 12 weeks (n = 6, 6). e, Oxygen consumption (VO2) in 10-12 week-old male WT and AdC3KO mice housed at 22 °C and fed a normal chow diet (n = 18, 22). Bar/line plots show mean ± SEM. Each point represents a biological replicate. Two-sided *P < 0.05 by Welch’s t-test (b) or ANOVA (e).

Source data

Extended Data Fig. 8 Analysis of adipose innervation and adrenergic signaling in CLSTN3β-deficient mice.

(a—c) Representative slices and maximum intensity projections (MIPs) of whole BAT lobe tyrosine hydroxylase (TH) immunostaining. Scale bar = 100 µm. a, 4% paraformaldehyde (PFA) vs. 3% glyoxal fixation. b, 11-12 week-old male WT and AdC3KO mice housed at 22 °C. c, 5–6 week-old male control and ob/ob mice housed at 22 °C. ob/ob samples were imaged at the same laser power as control samples as well as at maximum laser power. Control vs. ob/ob comparison was performed as a positive control for differences in BAT TH immunostaining. d, Quantification of TH staining in WT vs. AdC3KO (n = 4, 4) and control vs. ob/ob (n = 3, 3) mice. (Left) One value reported per mouse, (right) one value reported per sub-volume (60 sub-volumes per mouse). Western blot analysis of e, BAT from 11 week-old male WT and AdC3KO mice housed at 22 °C, f, BAT from 17-18 week-old male WT and CLSTN3β KO mice housed at 22 °C, g, BAT from 10-11 week-old male WT and AdC3KO mice housed at 4 °C for 4 days, h, iWAT from 10-11 week-old male WT and AdC3KO mice housed at 4 °C for 4 days, and i, BAT from 17-18 week-old male WT and CLSTN3β KO mice housed at 22 °C. j, Western blot analysis of conditioned media (CM) and whole cell lysates (WCL) from HEK293T cells transfected/treated with the indicated constructs/compounds. FSK = forskolin (5 µM). *These β-Actin blots are the same. Extended Data Fig. 8F, I are from the same experiment but were split up for presentation purposes. Bar plots show mean ± SEM. Each point represents a biological replicate. Violin plots show median (dashed) and quartiles (dotted). Two-sided ***P < 0.001 by ordinary one-way ANOVA with Dunnett’s multiple comparisons test (d).

Source data

Extended Data Fig. 9 Characterization of cells and mice re-expressing CLSTN3β.

a, (Top) CRISP-ID analysis of Sanger sequencing trace from immortalized CLSTN3β KO brown preadipocyte clone. PAM sequence is underlined in red. CRISPR strategy is identical to that depicted in Extended Data Fig. 5A. (Bottom) Nucleotide sequences of WT and CLSTN3β KO alleles. Bases deleted in KO alleles are highlighted in red. b, Light microscopy of immortalized CLSTN3β KO brown adipocytes stably expressing (left) mCherry or (right) CLSTN3β-mCherry (day 5 of differentiation). Scale bar = 50 µm. c, (Left) Seahorse respirometry analysis of oxygen consumption rates (OCR) in immortalized CLSTN3β KO brown adipocytes stably expressing mCherry (mCh) or CLSTN3β-mCherry (C3β-mCh) (day 6 of differentiation) and treated with isoproterenol (ISO, 10 µM), oligomycin (oligo, 4 µM), FCCP (2 µM), and rotenone/myxothiazol (RM, 7.5 µM). Cells were pre-treated with atglistatin (ATGLi, 40 µM) for 30-45 min where indicated. (Right) FCCP-induced OCR normalized to protein content (n = 6). d, Western blot analysis of immortalized CLSTN3β KO brown adipocytes stably expressing mCh or C3β-mCh (day 6 of differentiation). e, Silver stain analysis of large (500 g), medium (8,000 g), and small (200,000 g) LDs isolated from immortalized CLSTN3β KO brown adipocytes stably expressing mCh or C3β-mCh (day 8 of differentiation). Equal amounts of TAG from each condition were loaded onto the gel. f, Same experiment as Fig. 4A–E. Western blot analysis of BAT. g, Same experiment as Fig. 4F. CLSTN3 immunohistochemistry (IHC) of asWAT and BAT. Scale bar = 50 µm. Bar/line plots show mean ± SEM. Each point represents a biological replicate. Two-sided *P < 0.05 by multiple t-tests with Holm-Sidak correction (c).

Source data

Extended Data Fig. 10 Conservation of CLSTN3B in humans.

a, Amino acid alignment of CLSTN3β from representative placental mammals. b, RNA-seq reads at the CLSTN3 locus in human cortex and adipose tissue. c, Microarray analysis of CLSTN3 expression in periadrenal adipose tissue from control patients, pheochromocytoma patients with unilocular fat (PheoUni), and pheochromocytoma patients with multilocular fat (PheoMulti) (n = 4). d, qPCR analysis of CLSTN3 exons 1/2, CLSTN3 exons 17/18, CLSTN3B, and UCP1 expression in human unilocular and multilocular adipose tissue (n = 26, 12). Unilocular group includes both control and PheoUni patients. e, RNAscope analysis of CLSTN3B expression in unilocular periadrenal adipose tissue from lean control, obese control, and pheochromocytoma (PheoUni) patients. Scale bar = 50 µm. f, Cloning of human CLSTN3B. g, Confocal microscopy of OA-treated (1 mM, overnight) HeLa cells transfected with human CLSTN3β-Flag and stained with LipidTOX 647. Scale bar = 5 µm. h, Amino acid alignment of mouse and human CLSTN3β (reference sequences). Putative hydrophobic hairpins, β-strand domain, and TM domain are colored red, blue, and purple, respectively. Underlined residues are altered in the patient from which human CLSTN3β was cloned for this study. Bar plots show mean ± SEM. Each point represents a biological replicate. Two-sided *P < 0.05, **P < 0.01, ***P < 0.001 by ordinary one-way ANOVA with Dunnett’s multiple comparisons test (c) or multiple t-tests with Holm-Sidak correction (d).

Source data

Extended Data Fig. 11 CLSTN3β associates with CIDE proteins and blocks LD fusion.

(a—d) Western blot analysis of CLSTN3β-Flag co-immunoprecipitation assays in transfected HEK293FT cells. a, CIDEC-HA, b, CIDEA-HA, CIDECα-HA, and CIDECβ-HA, c, RAB18-HA and CGI58-HA, d, HA-tagged CIDEC C-terminal region (CIDEC-C-HA). e, Co-localization of CLSTN3β-GFP and CIDEA-HA in transfected 3T3-L1 preadipocytes treated with OA. Scale bar = 5 µm. (f—h) Fluorescence recovery after photobleaching (FRAP)-based lipid exchange rate assay in transfected 3T3-L1 preadipocytes incubated with 200 µM OA and 1 µg/mL BODIPY 558/568 C12 fatty acid for 16 h. f, Calculated lipid exchange rates (n = 15, 14, 17 cells). Cells used for representative traces are highlighted in red. g, Representative mean optical intensity traces for one pair of LDs from each group. h, Representative images of FRAP-based lipid exchange rate assay. Yellow arrows point to bleached LDs. Bar plots show mean ± SEM. Each point represents a biological replicate. Two-sided ***P < 0.001 by ordinary one-way ANOVA with Tukey’s multiple comparisons test (f).

Source data

Extended Data Fig. 12 CLSTN3β associates with CIDE proteins and blocks LD fusion.

a, Confocal microscopy of HeLa cells stably expressing CIDEC and transiently expressing either GFP or CLSTN3β-GFP. Cells were treated with OA and LDs were stained with BODIPY 665. Scale bar = 5 µm. b, Confocal microscopy of immortalized CLSTN3β KO brown adipocytes stably expressing mCherry or CLSTN3β-mCherry and CIDEC-v5 (day 5 of differentiation). Cells were stained with BODIPY 488, DAPI, and anti-v5, and mCherry signal was amplified with anti-mCherry Alexa Fluor 594. Scale bar = 5 µm. c, (Top) Western blot analysis of BAT from male WT and AdC3KO mice housed at (left) 22 °C or (right) 4 °C for 4 days. (Bottom) Quantification of above Western blots. d, Representative images of FRAP-based phase separation assay. Yellow arrows point to bleached signal at LD–LD contact sites (LDCS). Scale bar = 2 µm. e, Quantification of FRAP-based phase separation assay (n = 22 cells). f, Percentage of cells with CIDEC condensates in the absence or presence of CLSTN3β (n = 3). Bar/line plots show mean ± SEM. Each point represents a biological replicate. Two-sided *P < 0.05, **P < 0.01 by Welch’s t-test (c).

Source data

Supplementary information

Supplementary Fig. 1

Gel source data.

Reporting Summary

Supplementary Table 1

Primer and guide RNA sequences used in this study.

Supplementary Discussion

Further discussion and associated references.

Supplementary Data 1

Intron clusters with differential splice site use in cerebral cortex and BAT.

Supplementary Data 2

High-confidence CLSTN3β interactome.

Supplementary Data 3

Mouse Clstn3b-specific ORF BLAST hits (by species).

Supplementary Data 4

Mouse Clstn3b-specific ORF BLAST hits (by taxon).

Supplementary Video 1

Tyrosine hydroxylase immunostaining of whole WT BAT lobe. Three-dimensional reconstruction and animation of a whole WT BAT lobe, stained for tyrosine hydroxylase using a modified Adipo-Clear protocol and imaged using a light sheet microscope.

Supplementary Video 2

Tyrosine hydroxylase immunostaining of whole AdC3KO BAT lobe. Three-dimensional reconstruction and animation of a whole AdC3KO BAT lobe, stained for tyrosine hydroxylase using a modified Adipo-Clear protocol and imaged using a light sheet microscope.

Supplementary Video 3

Effect of CLSTN3β on CIDEC lipid transfer activity. FRAP-based lipid exchange rate assay for CIDEC in the absence or presence of CLSTN3β.

Source data

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and Permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Qian, K., Tol, M.J., Wu, J. et al. CLSTN3β enforces adipocyte multilocularity to facilitate lipid utilization. Nature 613, 160–168 (2023). https://doi.org/10.1038/s41586-022-05507-1

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41586-022-05507-1

This article is cited by

Comments

By submitting a comment you agree to abide by our Terms and Community Guidelines. If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate.

Search

Advanced 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