IDOL regulates systemic energy balance through control of neuronal VLDLR expression

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Abstract

Liver X receptors limit cellular lipid uptake by stimulating the transcription of inducible degrader of the low-density lipoprotein receptor (IDOL), an E3 ubiquitin ligase that targets lipoprotein receptors for degradation. The function of IDOL in systemic metabolism is incompletely understood. Here we show that loss of IDOL in mice protects against the development of diet-induced obesity and metabolic dysfunction by altering food intake and thermogenesis. Unexpectedly, analysis of tissue-specific knockout mice revealed that IDOL affects energy balance, not through its actions in peripheral metabolic tissues (liver, adipose tissue, endothelium, intestine, and skeletal muscle) but by controlling lipoprotein receptor abundance in neurons. Single-cell RNA sequencing of the hypothalamus demonstrated that IDOL deletion altered gene expression linked to the control of metabolism. Finally, we identified very low-density lipoprotein receptor (VLDLR) rather than low-density lipoprotein receptor (LDLR) as the primary mediator of the effects of IDOL on energy balance. These data identify a role for the neuronal IDOL–VLDLR pathway in metabolic homoeostasis and diet-induced obesity.

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Fig. 1: Global IDOL knockout mice are protected from diet-induced metabolic dysfunction.
Fig. 2: Deletion of IDOL from peripheral tissues does not protect against diet-induced metabolic dysfunction.
Fig. 3: IDOL regulates systemic energy balance through VLDLR.
Fig. 4: Acute knockdown of IDOL in the CNS reduces adiposity by increasing energy expenditure.
Fig. 5: The single-cell transcriptional landscape of the hypothalamus is affected by deletion of IDOL.
Fig. 6: Conditional deletion of Idol from neurons drives the metabolic protection seen in global IDOL knockout mice.

Data Availability

The data that support the findings of this study are available from the corresponding author upon request and the Reporting Summary is available from the Nature Metabolism website. The single-cell RNA-seq data has been deposited in the NCBI Gene Expression Omnibus, accession number GSE119960. Source data for Figs. 16 and Extended Data Figs. 1 and 37 are available online.

References

  1. 1.

    Goldstein, J. L. & Brown, M. S. A century of cholesterol and coronaries: from plaques to genes to statins. Cell 161, 161–172 (2015).

  2. 2.

    Trommsdorff, M. et al. Reeler/disabled-like disruption of neuronal migration in knockout mice lacking the VLDL receptor and ApoE receptor 2. Cell 97, 689–701 (1999).

  3. 3.

    Goldstein, J. L., DeBose-Boyd, R. A. & Brown, M. S. Protein sensors for membrane sterols. Cell 124, 35–46 (2006).

  4. 4.

    Lee, S. D. & Tontonoz, P. Liver X receptors at the intersection of lipid metabolism and atherogenesis. Atherosclerosis 242, 29–36 (2015).

  5. 5.

    Hong, C. & Tontonoz, P. Liver X receptors in lipid metabolism: opportunities for drug discovery. Nat. Rev. Drug. Discov. 13, 433–444 (2014).

  6. 6.

    Rayner, K. J. et al. MiR-33 contributes to the regulation of cholesterol homeostasis. Science 328, 1570–1573 (2010).

  7. 7.

    Sallam, T. et al. Feedback modulation of cholesterol metabolism by the lipid-responsive non-coding RNA LeXis. Nature 534, 124–128 (2016).

  8. 8.

    Zelcer, N., Hong, C., Boyadjian, R. & Tontonoz, P. LXR regulates cholesterol uptake through Idol-dependent ubiquitination of the LDL receptor. Science 325, 100–104 (2009).

  9. 9.

    Hong, C. et al. The E3 ubiquitin ligase IDOL induces the degradation of the low density lipoprotein receptor family members VLDLR and ApoER2. J. Biol. Chem. 285, 19720–19726 (2010).

  10. 10.

    Scotti, E. et al. IDOL stimulates clathrin-independent endocytosis and multivesicular body-mediated lysosomal degradation of the low-density lipoprotein receptor. Mol. Cell. Biol. 33, 1503–1514 (2013).

  11. 11.

    Zhang, L., Xu, M., Scotti, E., Chen, Z. J. & Tontonoz, P. Both K63 and K48 ubiquitin linkages signal lysosomal degradation of the LDL receptor. J. Lipid Res. 54, 1410–1420 (2013).

  12. 12.

    Zhang, L. et al. The IDOL-UBE2D complex mediates sterol-dependent degradation of the LDL receptor. Genes Dev. 25, 1262–1274 (2011).

  13. 13.

    Calkin, A. C. et al. FERM-dependent E3 ligase recognition is a conserved mechanism for targeted degradation of lipoprotein receptors. Proc. Natl Acad. Sci. USA 108, 20107–20112 (2011).

  14. 14.

    Hong, C. et al. The LXR-Idol axis differentially regulates plasma LDL levels in primates and mice. Cell Metab. 20, 910–918 (2014).

  15. 15.

    Teslovich, T. M. et al. Biological, clinical and population relevance of 95 loci for blood lipids. Nature 466, 707–713 (2010).

  16. 16.

    Sorrentino, V. et al. Identification of a loss-of-function inducible degrader of the low-density lipoprotein receptor variant in individuals with low circulating low-density lipoprotein. Eur. Heart J. 34, 1292–1297 (2013).

  17. 17.

    Weissglas-Volkov, D. et al. The N342S MYLIP polymorphism is associated with high total cholesterol and increased LDL receptor degradation in humans. J. Clin. Invest. 121, 3062–3071 (2011).

  18. 18.

    Calkin, A. C. et al. Transgenic expression of dominant-active IDOL in liver causes diet-induced hypercholesterolemia and atherosclerosis in mice. Circ. Res. 115, 442–449 (2014).

  19. 19.

    Eguchi, J. et al. Transcriptional control of adipose lipid handling by IRF4. Cell Metab. 13, 249–259 (2011).

  20. 20.

    Yagyu, H. et al. Very low density lipoprotein (VLDL) receptor-deficient mice have reduced lipoprotein lipase activity. Possible causes of hypertriglyceridemia and reduced body mass with VLDL receptor deficiency. J. Biol. Chem. 277, 10037–10043 (2002).

  21. 21.

    Garcia-Arcos, I. et al. Adipose-specific lipoprotein lipase deficiency more profoundly affects brown than white fat biology. J. Biol. Chem. 288, 14046–14058 (2013).

  22. 22.

    Goudriaan, J. R. et al. The VLDL receptor plays a major role in chylomicron metabolism by enhancing LPL-mediated triglyceride hydrolysis. J. Lipid Res. 45, 1475–1481 (2004).

  23. 23.

    Obunike, J. C. et al. Transcytosis of lipoprotein lipase across cultured endothelial cells requires both heparan sulfate proteoglycans and the very low density lipoprotein receptor. J. Biol. Chem. 276, 8934–8941 (2001).

  24. 24.

    Alva, J. A. et al. VE-Cadherin-Cre-recombinase transgenic mouse: a tool for lineage analysis and gene deletion in endothelial cells. Dev. Dyn. 235, 759–767 (2006).

  25. 25.

    Brüning, J. C. et al. A muscle-specific insulin receptor knockout exhibits features of the metabolic syndrome of NIDDM without altering glucose tolerance. Mol. Cell 2, 559–569 (1998).

  26. 26.

    Andersen, O. M. et al. Essential role of the apolipoprotein E receptor-2 in sperm development. J. Biol. Chem. 278, 23989–23995 (2003).

  27. 27.

    Frykman, P. K., Brown, M. S., Yamamoto, T., Goldstein, J. L. & Herz, J. Normal plasma lipoproteins and fertility in gene-targeted mice homozygous for a disruption in the gene encoding very low density lipoprotein receptor. Proc. Natl Acad. Sci. USA 92, 8453–8457 (1995).

  28. 28.

    Goudriaan, J. R. et al. Protection from obesity in mice lacking the VLDL receptor. Arterioscler. Thromb. Vasc. Biol. 21, 1488–1493 (2001).

  29. 29.

    Choi, J. et al. The E3 ubiquitin ligase Idol controls brain LDL receptor expression, ApoE clearance, and Aβ amyloidosis. Sci. Transl. Med. 7, 314ra184 (2015).

  30. 30.

    Gao, J. et al. The E3 ubiquitin ligase IDOL regulates synaptic ApoER2 levels and is important for plasticity and learning. eLife 6, 1741 (2017).

  31. 31.

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

  32. 32.

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

  33. 33.

    Berbée, J. F. P. et al. Brown fat activation reduces hypercholesterolaemia and protects from atherosclerosis development. Nat. Commun. 6, 6356 (2015).

  34. 34.

    Gautron, L., Elmquist, J. K. & Williams, K. W. Neural control of energy balance: translating circuits to therapies. Cell 161, 133–145 (2015).

  35. 35.

    Tschöp, M. H. et al. A guide to analysis of mouse energy metabolism. Nat. Methods 9, 57–63 (2012).

  36. 36.

    Caron, A., Lee, S., Elmquist, J. K. & Gautron, L. Leptin and brain-adipose crosstalks. Nat. Rev. Neurosci. 19, 153–165 (2018).

  37. 37.

    Kong, D. et al. GABAergic RIP-Cre neurons in the arcuate nucleus selectively regulate energy expenditure. Cell 151, 645–657 (2012).

  38. 38.

    Ruan, H.-B. et al. O-GlcNAc transferase enables AgRP neurons to suppress browning of white fat. Cell 159, 306–317 (2014).

  39. 39.

    van Loon, N. M. et al. Inactivation of the E3 ubiquitin ligase IDOL attenuates diet-induced obesity and metabolic dysfunction in mice. Arterioscler. Thromb. Vasc. Biol. 38, 1785–1795 (2018).

  40. 40.

    Waterson, M. J. & Horvath, T. L. Neuronal regulation of energy homeostasis: beyond the hypothalamus and feeding. Cell Metab. 22, 962–970 (2015).

  41. 41.

    Nectow, A. R. et al. Identification of a brainstem circuit controlling feeding. Cell 170, 429–442.e11 (2017).

  42. 42.

    Williams, K. W. & Elmquist, J. K. From neuroanatomy to behavior: central integration of peripheral signals regulating feeding behavior. Nat. Neurosci. 15, 1350–1355 (2012).

  43. 43.

    Chechi, K., Carpentier, A. C. & Richard, D. Understanding the brown adipocyte as a contributor to energy homeostasis. Trends Endocrinol. Metab. 24, 408–420 (2013).

  44. 44.

    Bamshad, M., Song, C. K. & Bartness, T. J. CNS origins of the sympathetic nervous system outflow to brown adipose tissue. Am. J. Physiol. 276, R1569–R1578 (1999).

  45. 45.

    Friedman, J. 20 years of leptin: leptin at 20: an overview. J. Endocrinol. 223, T1–T8 (2014).

  46. 46.

    Owen, B. M. et al. FGF21 acts centrally to induce sympathetic nerve activity, energy expenditure, and weight loss. Cell Metab. 20, 670–677 (2014).

  47. 47.

    Lu, M. et al. Brain PPAR-γ promotes obesity and is required for the insulin-sensitizing effect of thiazolidinediones. Nat. Med. 17, 618–622 (2011).

  48. 48.

    Xu, Y., O’Malley, B. W. & Elmquist, J. K. Brain nuclear receptors and body weight regulation. J. Clin. Invest. 127, 1172–1180 (2017).

  49. 49.

    López, M. et al. Hypothalamic AMPK and fatty acid metabolism mediate thyroid regulation of energy balance. Nat. Med. 16, 1001–1008 (2010).

  50. 50.

    Alvarez-Crespo, M. et al. Essential role of UCP1 modulating the central effects of thyroid hormones on energy balance. Mol. Metab. 5, 271–282 (2016).

  51. 51.

    Mancini, G. & Horvath, T. L. Viral vectors for studying brain mechanisms that control energy homeostasis. Cell Metab. 27, 1168–1175 (2018).

  52. 52.

    Schwartz, M. W., Woods, S. C., Porte, D., Seeley, R. J. & Baskin, D. G. Central nervous system control of food intake. Nature 404, 661–671 (2000).

  53. 53.

    Leeb, C., Eresheim, C. & Nimpf, J. Clusterin is a ligand for apolipoprotein E receptor 2 (ApoER2) and very low density lipoprotein receptor (VLDLR) and signals via the Reelin-signaling pathway. J. Biol. Chem. 289, 4161–4172 (2014).

  54. 54.

    Pohlkamp, T., Wasser, C. R. & Herz, J. Functional roles of the interaction of APP and lipoprotein receptors. Front Mol. Neurosci. 10, 54 (2017).

  55. 55.

    Zisman, S. et al. Proteolysis and membrane capture of F-spondin generates combinatorial guidance cues from a single molecule. J. Cell Biol. 178, 1237–1249 (2007).

  56. 56.

    Bajari, T. M., Strasser, V., Nimpf, J. & Schneider, W. J. A model for modulation of leptin activity by association with clusterin. FASEB J. 17, 1505–1507 (2003).

  57. 57.

    Oomura, Y., Nakamura, T., Sugimori, M. & Yamada, Y. Effect of free fatty acid on the rat lateral hypothalamic neurons. Physiol. Behav. 14, 483–486 (1975).

  58. 58.

    Lam, T. K. T. et al. Hypothalamic sensing of circulating fatty acids is required for glucose homeostasis. Nat. Med. 11, 320–327 (2005).

  59. 59.

    Lam, T. K. T., Schwartz, G. J. & Rossetti, L. Hypothalamic sensing of fatty acids. Nat. Neurosci. 8, 579–584 (2005).

  60. 60.

    Yue, J. T. Y. et al. A fatty acid-dependent hypothalamic-DVC neurocircuitry that regulates hepatic secretion of triglyceride-rich lipoproteins. Nat. Commun. 6, 5970 (2015).

  61. 61.

    Scotti, E. et al. Targeted disruption of the idol gene alters cellular regulation of the low-density lipoprotein receptor by sterols and liver x receptor agonists. Mol. Cell. Biol. 31, 1885–1893 (2011).

  62. 62.

    Postic, C. et al. Dual roles for glucokinase in glucose homeostasis as determined by liver and pancreatic beta cell-specific gene knock-outs using Cre recombinase. J. Biol. Chem. 274, 305–315 (1999).

  63. 63.

    Swayze, E. E. et al. Antisense oligonucleotides containing locked nucleic acid improve potency but cause significant hepatotoxicity in animals. Nucleic Acids Res. 35, 687–700 (2007).

  64. 64.

    Seth, P. P. et al. Synthesis and biophysical evaluation of 2’,4’-constrained 2’O-methoxyethyl and 2’,4‘-constrained 2’O-ethyl nucleic acid analogues. J. Org. Chem. 75, 1569–1581 (2010).

  65. 65.

    Østergaard, M. E. et al. Rational design of antisense oligonucleotides targeting single nucleotide polymorphisms for potent and allele selective suppression of mutant Huntingtin in the CNS. Nucleic Acids Res. 41, 9634–9650 (2013).

  66. 66.

    Brewer, G. J. & Torricelli, J. R. Isolation and culture of adult neurons and neurospheres. Nat. Protoc. 2, 1490–1498 (2007).

  67. 67.

    Poon, K., Barson, J. R., Fagan, S. E. & Leibowitz, S. F. Developmental changes in embryonic hypothalamic neurons during prenatal fat exposure. Am. J. Physiol. Endocrinol. Metab. 303, E432–E441 (2012).

  68. 68.

    Macosko, E. Z. et al. Highly parallel genome-wide expression profiling of individual cells using nanoliter droplets. Cell 161, 1202–1214 (2015).

  69. 69.

    Waltman, L. & van Eck, N. J. A smart local moving algorithm for large-scale modularity-based community detection. Eur. Phys. J. B 86, 75 (2013).

  70. 70.

    Chung, N. C. & Storey, J. D. Statistical significance of variables driving systematic variation in high-dimensional data. Bioinformatics 31, 545–554 (2015).

  71. 71.

    Romanov, R. A. et al. Molecular interrogation of hypothalamic organization reveals distinct dopamine neuronal subtypes. Nat. Neurosci. 20, 176–188 (2017).

  72. 72.

    Chen, R., Wu, X., Jiang, L. & Zhang, Y. Single-cell RNA-seq reveals hypothalamic cell diversity. Cell Rep. 18, 3227–3241 (2017).

  73. 73.

    Campbell, J. N. et al. A molecular census of arcuate hypothalamus and median eminence cell types. Nat. Neurosci. 20, 484–496 (2017).

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Acknowledgements

Further information and requests for resources and reagents should be directed to, and will be fulfilled by, the lead contact, Peter Tontonoz (PTontonoz@mednet.ucla.edu). Funding for this project was provided by grants to P.T. from the National Institutes of Health (HL066088, HL136618, and DK063491). S.D.L. was supported by a fellowship from the Canadian Institutes of Health Research and by a grant from the National Institutes of Health (P30 DK063491). C.P. was supported by an F32 fellowship from the National Institutes of Health (HL123236). A.C.C. was supported by a fellowship from the National Heart Foundation of Australia (O 08 M 3934). J.G. was supported by a K99/R00 pathway to independence award from the National Institutes of Health (AG054736). C.H. was supported by AHA grant 3BGIA17110079 and ADA grant 1-14-JF-33.

Author information

S.D.L., C.P., C.H., P.T., S.M.C., X.Y., M.B., P.Å., D.L., H.B., and M.B.-Y. were responsible for conceptualization of the study. S.D.L., C.P., D.V.A., M.B., and P.T. were responsible for formal analysis. Funding was acquired by P.T. and by AstraZeneca AB. S.D.L., C.P., M.B., J.G., J.E.V., M.G.M., J.K., D.V.A., I.S.A., G.D., H.A., M.P., A.C., A.A., F.S., I.M., P.E., M.A., and C.H. were responsible for investigations. S.D.L., C.P., C.H., J.G., D.A., I.S.A., G.D., J.E.V., P.R., M.B., A.C.C., H.A., P.Å., D.L., H.B., M.B.-Y., S.M.C., X.Y., and P.T. were responsible for the methodology. M.B., M.A., P.Å., D.L., H.B., and P.T. were responsible for project administration. A.C.C., P.R., T.A.C., R.L., M.A., P.Å., H.B., M.B.-Y., S.M.C., X.Y., and P.T. were responsible for resources. P.T., X.Y., S.M.C., P.Å., D.L., H.B., and M.B.-Y. supervised the study. S.D.L., C.P., C.H., J.G., D.A., I.S.A., G.D., J.E.V., P.R., M.B., and A.C.C. were responsible for validation. S.D.L., C.P., M.B., D.V.A., J.E.V., S.M.C., and P.T. were responsible for visualization. S.D.L., P.T., and M.B. wrote the original draft. S.D.L., C.P., M.B., J.E.V., P.Å., D.L., H.B., M.B.-Y., S.M.C., and P.T. reviewed and edited the manuscript.

Correspondence to Peter Tontonoz.

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Competing interests

M.B., H.A., M.P., A.C., A.A., F.S., I.M., P.E., M.A., P.Å., D.L., H.B., and M.B.-Y. are employees of AstraZeneca AB. T.A.C. and R.L. are employees of Ionis Pharmaceuticals. The other authors have no competing interests.

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Extended data

Extended Data Fig. 1 Metabolic phenotype of IDOL-deficient mice.

a,b, 18-month-old IDOL KO mice are protected against age-induced adiposity. a, Mean mass and standard error of the mean; n = 9 WT, n = 10 KO mice, ***p < 0.001, ****p < 0.0001 vs. WT by two-tailed t-test. b, Mean body fat percentage +/− the standard error of the mean; n = 9 WT, n = 10 KO mice, ***p < 0.001, ****p < 0.0001 vs. WT 2-tailed t-test. c, Growth curve for littermate male mice fed a 60% kcal high fat diet (HFD) starting when the mice were 6 weeks old. The mean values are shown +/− the standard error of the mean; n = 5 WT and n = 6 KO mice *p < 0.05 by repeat measures ANOVA. d, Growth curve for littermate male IDOL(AZ)f/f mice with or without whole-body Rosa26 Cre fed a low-fat diet from 8 weeks of age. The mean mass is shown +/− SEM; n = 10 mice per group. e, Growth curve for littermate male IDOL(AZ)f/f mice with or without whole-body Rosa26 Cre fed a high fat high cholesterol diet from 8-weeks of age; n = 8 Idol(AZ)f/f mice n = 9 CreR26+Idol(AZ)f/f mice; *p < 0.05 by repeat measures ANOVA f, Unchanged lean body mass in male IDOL knockout mice administered test diets despite adiposity changes measured by MRI. Mean lean mass is shown +/− SEM; n = 9 WT and n = 10 KO mice fed Chow, n = 5 WT and n = 7 mice fed western diet, n = 5 WT and n = 6 KO mice fed the 60% HFD, p-values calculated by two-way ANOVA with Sidak post hoc tests. g, Body length measured from nose to anus at 20 weeks of age for male mice fed either a low-fat diet (LFD) or a high-fat high-cholesterol diet (HFHC) for 12 weeks. The mean values are shown +/− the standard error of the mean. Low-fat diet: n = 10 mice per genotype. High Fat High Cholesterol diet: n = 8 Idol(AZ)f/f mice and n = 9 CreR26+Idol(AZ)f/f mice. P-values calculated by repeat measures ANOVA. h, Mean body temperature +/− SEM measured rectally in response to fasting in mice fed a high-fat high-cholesterol diet; n = 8 WT and n = 9 IDOL KO mice. The precise n-number, p-value, and details of all statistical testing are provided in the source data file. Source data

Extended Data Fig. 2 Glucose and insulin tolerance tests conducted on Idolf/f and conditional knockouts with tissue-specific deletion of IDOL.

ab, Mean blood glucose levels +/− SEM for liver-specific conditional IDOL KO mice challenged with an oral glucose tolerance test (2 g/kg) at 22 weeks of age fed either a, the low-fat diet; n = 12 mice per genotype or b, the high-fat high-cholesterol diet for 16 weeks; n = 11 mice per genotype. cj, Mean blood glucose levels +/− SEM for male mice fed a western diet challenged with an intraperitoneal glucose tolerance test (1 g/kg, shown on the left) after six weeks on diet and an intraperitoneal insulin tolerance test (1 U/kg, shown on the right) after ten weeks on diet. c,d, Adipose-specific conditional IDOL KO; n = 11 Idolf/f, n = 9 CreAdipoQIdolf/f mice. e,f, Endothelium-specific conditional IDOL KO; n = 13 Idolf/f, n = 10 CreCdh5Idolf/f mice. g,h, Intestine-specific conditional IDOL KO; n = 8 Idolf/f, n = 4 CreVilIdolf/f mice. i,j, Muscle-specific conditional IDOL KO; n = 10 mice per genotype for the GTT and n = 10 Idolf/f, n = 9 CreMckIdolf/f mice for the ITT.

Extended Data Fig. 3 Adipose-specific transgenic IDOL mice are not protected from diet-induced obesity.

a, Ablation of VLDLR protein levels in the subcutaneous inguinal white adipose tissue of the aP2-IDOL transgenic mice. This blot is representative of many independent experiments conducted by two independent researchers. b, Reduced VLDLR protein in the interscapular brown adipose tissue of the aP2-IDOL transgenic mice. This blot is representative of many independent experiments conducted by two independent researchers. c, Growth curve for WT and aP2-IDOL transgenic mice fed a western diet from 5 weeks of age showing the mean mass +/− SEM; n = 13 WT and n = 9 aP2-IDOL transgenic mice d, Mean body composition measured by MRI +/− SEM for n = 13 WT and n-9 aP2-IDOL transgenic mice after 12 weeks of western diet feeding. e, Intraperitoneal glucose tolerance test (1 g/kg) administered after six weeks of western diet feeding; n = 13 WT and n-9 aP2-IDOL transgenic mice. f, Intraperitoneal insulin tolerance test (1U/kg) administered after ten weeks of western diet feeding n = 13 WT and n-9 aP2-IDOL transgenic mice. Source data

Extended Data Fig. 4 IDOL regulates systemic energy balance through the VLDL receptor.

100ug of RIPA isolate from the hypothalamus of individual wild-type (WT), Idol-/- (KO), Idol-/-Ldlr-/- (LDLR DKO), or Idol-/-Vldlr-/- (VLDLR DKO) mice was loaded per lane of a Tris-Acetate NuPAGE gel. The image is representative of many independent experiments. These samples were repeated twice to assess reproducibility. a, Western blot analysis of VLDLR protein levels in the hypothalamus at study termination. b, Western blot analysis of LDLR protein levels in the hypothalamus at study termination. Source data

Extended Data Fig. 5 Acute knockdown of Idol in the central nervous system increases energy expenditure.

a, Optimization of the dose of ASO required to suppress Idol expression in whole-brain homogenates measured 8-weeks post-injection. The values represent the mean expression of Idol in a whole brain homogenate 8-weeks post-injection +/− SEM; n = 4 mice per time point. b, Growth curve for male mice placed on western diet one week after intracerebroventricular injection of Idol-targeting antisense oligonucleotide (IDOL ASO) or CNS-optimized control (CTRL ASO). The mean masses are shown +/− SEM; *p < 0.05, **p < 0.01, ***p < 0.001 by repeat measures two-way ANOVA, n = 10 mice treated with CTRL and n = 5 mice treated with IDOL ASO. c, Macroscopic view of interscapular brown adipose tissue depots after seven weeks on western diet. These images are representative of the ten mice per group in the ASO study. d, Macroscopic view of subcutaneous (inguinal) white adipose tissue depots after seven weeks on western diet. These samples are representative of the ten mice per group in the ASO study. e, No statistically significant differences in body composition at the onset of CLAMS experiment. The mean total body mass, lean body mass, and fat body mass are shown +/− SEM; statistical significance determined by two-way ANOVA to account for multiple testing, n = 10 mice per group. The precise n-number, p-value, and details of all statistical testing are provided in the source data file file. f, Reduced lipid accumulation in the livers of ASO treated mice evident with hematoxylin and eosin staining of 5 μm sections of liver (10x objective). These images are representative of three mice per treatment group that were analysed for histology. g, Calculation of carbohydrate metabolism in the n = 10 mice per group. The mean energy expenditure derived from carbohydrate metabolism for the mice in Fig. 4f is shown +/− s.e.m. for each time point. h, Calculation of lipid oxidation in the n = 10 mice per group. The mean energy expenditure derived from lipid metabolism for the mice in Fig. 4f is shown +/− s.e.m. for each time point. Source data

Extended Data Fig. 6 Single cell RNA sequencing examination of the transcriptional landscape of the hypothalamus with Drop-seq.

Clustering analysis combined with expression profiling of a panel of marker genes allowed us to discriminate 26 unique clusters of cells in the hypothalamus. a, Violin plots demonstrate the expression patterns of the 38 marker genes used to identify the cell clusters. Individual data points indicating the magnitude of gene expression in a single cell are superimposed on a probability density plot for the distribution of the data; the expression analysis is based on the data collected from n = 11,453 single cells. b, Global gene expression relationships in the 11,453 single cells isolated from the hypothalamic tissues of six mice projected onto two dimensions using t-distributed Stochastic Neighbour Embedding (tSNE). The clusters were defined using shared nearest neighbour graph-based clustering. c, tSNE plot of the neuronal cells identified in the Drop-seq experiment (n = 3369 single cells). d, Violin plot demonstrating that Vldlr is only appreciably expressed in neuron and oligodendrocyte cell populations. Individual data points indicating the magnitude of gene expression in a single cell; the expression analysis is based on the unique molecular identities (UMI) data collected from n = 11,453 single cells. ef, Volcano plots of the differentially expressed genes analyzed by two-sided Wilcoxon rank sum tests in e, POMC+ (n = 24 WT and n = 26 Idol-/- cells) and f, Histaminergic neurons (n = 23 WT and n = 11 Idol-/- neurons. Labelled genes are linked to whole body metabolic homeostasis – see Supplemental Data Table 2 for details. Source data

Extended Data Fig. 7 Neuron-specific virogenetic deletion of IDOL from individual hypothalamic nuclei is insufficient to protect against diet-induced obesity.

ac, Adeno-associated virus (AAV) expressing either GFP-Cre or GFP regulated by the Synapsin I (SynI) promoter were injected into the arcuate nucleus (ARC: panels a-c) or the paraventricular nucleus of the hypothalamus (PVH: panels d-f). ac, Deletion of IDOL from neurons in the ARC had no effect on body mass or food intake for mice fed a western diet for 12 weeks; n = 8 mice injected with AAV-expressing GFP (GFPARC-SynI), n = 8 mice injected with AAV expressing Cre-GFP (CreARC-SynI). a, An image of the ARC showing GFP-positive cells to demonstrate successful infection of neurons; the image is representative of the sixteen mice injected in the ARC study. b, Growth curve showing the mean mass of the mice from each treatment group +/− one standard deviation. c, The mean cumulative mass of food consumed per mouse +/− one standard deviation. df, Deletion of IDOL from neurons in the PVH had no effect on body mass or food intake for mice fed a western diet for 12 weeks; n = 8 mice injected with AAV expressing GFP (GFPPVH-SynI), n = 9 mice injected with AAV expressing Cre-GFP (CrePVH-SynI). d, An image of the PVH showing GFP-positive cells to demonstrate successful infection of neurons; the image is representative of the seventeen mice injected in the PVH experiment. e, Growth curve showing the mean mass of the mice from each treatment group +/− one standard deviation. f, The mean cumulative mass of food consumed per mouse +/− one standard deviation. Source data

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Lee, S.D., Priest, C., Bjursell, M. et al. IDOL regulates systemic energy balance through control of neuronal VLDLR expression. Nat Metab 1, 1089–1100 (2019) doi:10.1038/s42255-019-0127-7

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