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Insulin induces insulin receptor degradation in the liver through EphB4

Nature Metabolism volume 4, pages 1202–1213 (2022)Cite this article

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Abstract

Insulin signaling is essential for glucose metabolism, and insulin decreases insulin receptor (InsR) levels in a dose-dependent and time-dependent manner. However, the regulatory mechanisms of InsR reduction upon insulin stimulation remain poorly understood. Here, we show that Eph receptor B4 (EphB4), a tyrosine kinase receptor that modulates cell adhesion and migration, can bind directly to InsR, and this interaction is markedly enhanced by insulin. Due to the adaptor protein 2 (Ap2) complex binding motif in EphB4, the interaction of EphB4 and InsR facilitates clathrin-mediated InsR endocytosis and degradation in lysosomes. Hepatic overexpression of EphB4 decreases InsR and increases hepatic and systemic insulin resistance in chow-fed mice, whereas genetic or pharmacological inhibition of EphB4 improve insulin resistance and glucose intolerance in obese mice. These observations elucidate a role for EphB4 in insulin signaling, suggesting that EphB4 might represent a therapeutic target for the treatment of insulin resistance and type 2 diabetes.

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Fig. 1: Insulin treatment induced InsR degradation.
Fig. 2: EphB4 directly interacted with InsR.
Fig. 3: EphB4 promoted insulin-induced InsR degradation.
Fig. 4: EphB4 promoted InsR degradation in the lysosome.
Fig. 5: Hepatic EphB4 knockout improved metabolism in mice.
Fig. 6: Pharmacological EphB4 inhibition improved metabolism in db/db mice.

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Data availability

Primer sequences for qPCR are listed in Supplementary Tables 1 and 2. The sequence information for designing EPHB4 shRNAs is listed in Supplementary Table 3. The clinical features of the patients are listed in Supplementary Table 4. All source data for immunoblotting are shown in Supplementary Fig. 1. Other source data in this study are available from the corresponding author upon request. Source data are provided with this paper.

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Acknowledgements

We thank Jerrold M. Olefsky at the University of California San Diego for providing advice. We thank Xiaowei Zhang at Peking University for providing the albumin-cre mice. This work was supported by grants from the National Key R&D Program of China (2017YFA0205400), Beijing Outstanding Young Scientist Program (BJJWZYJH01201910023028), the National Natural Science Foundation China (81700767, 81622010, 81770800, 81874316 and 81703588), the Chinese Academy of Medical Sciences (CAMS) Innovation Fund for Medical Sciences (2021-I2M-1-016, 2016-I2M-1-011, 2016-I2M-3-008 and 2017-I2M-1-008), the CAMS Central Public-interest Scientific Institution Basal Research Fund (2017RC31009 and 2018PT35004) and the Drug Innovation Major Project from the National Science and Technology Department (2018ZX09711001-003-005 and 2018ZX09711001-003-001).

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Authors and Affiliations

  1. State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China

    Xingfeng Liu, Kai Wang, Shaocong Hou, Qian Jiang, Chunxiao Ma, Qijin Zhao, Lijuan Kong, Jingwen Chen, Zhenhe Wang, Yi Huan, Zhufang Shen, Zhuowei Hu, Bing Cui & Pingping Li

  2. Diabetes Research Center of Chinese Academy of Medical Sciences, Beijing, China

    Xingfeng Liu, Kai Wang, Shaocong Hou, Qian Jiang, Chunxiao Ma, Qijin Zhao, Lijuan Kong, Jingwen Chen, Huabing Zhang, Tao Yuan, Yuxiu Li, Yi Huan, Zhufang Shen & Pingping Li

  3. CAMS Key Laboratory of Molecular Mechanism and Target Discovery of Metabolic Disorder and Tumorigenesis, Beijing, China

    Xingfeng Liu, Kai Wang, Shaocong Hou, Qian Jiang, Chunxiao Ma, Qijin Zhao, Lijuan Kong, Jingwen Chen, Yi Huan, Zhufang Shen & Pingping Li

  4. Department of Endocrinology, Key Laboratory of Endocrinology, Ministry of Health, Peking Union Medical College Hospital, Beijing, China

    Huabing Zhang, Tao Yuan & Yuxiu Li

  5. The National Clinical Research Center for Metabolic Diseases, Department of Metabolism and Endocrinology, the Second Xiangya Hospital, Central Sothern University, Changsha, China

    Zhuowei Hu

  6. School of Pharmaceutical Sciences, Wenzhou Medical University, Wenzhou, China

    Zhifeng Huang

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Contributions

X.L. performed the overall experiments and analyzed the data. K.W. and J.C. isolated the primary hepatocytes from mice and performed the gluconeogenesis assay. S.H. and Q.J. performed the clamp experiment. L.K., Q.J., Z.W., C.M., Q.Z. and Y.H. assisted with the tissue collection and qPCR experiment. T.Y., Z.S., H.Z. and Y.L. assisted with the animal and cell experiments. P.L. conceived the project and directed the research. Z. Huang, Z. Hu and B.C. provided constructive advice. X.L., B.C. and P.L. wrote the paper with input from the other authors.

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Correspondence to Pingping Li.

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Nature Metabolism thanks Heiko Lickert and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Primary Handling Editor: Isabella Samuelson, in collaboration with the Nature Metabolism team.

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Extended data

Extended Data Fig. 1 HFD induced hyperinsulinemia and InsR protein reduction.

a-g, Body weight curve (a, n = 3 mice), blood insulin curve (b, n = 3 mice), plasma glucose curve (c, n = 3 mice), and hepatic InsR protein levels (d, e, n = 3 mice) in C57BL/6J mice during HFD feeding. f, InsR protein level in epi-WAT of HFD-fed mice (age: 24 weeks, HFD: 16 weeks, n = 3 mice). g, InsR protein level in muscles of HFD-fed mice (n = 3 mice). h, Hepatic InsR mRNA levels (n = 3 mice). For statistical analysis in a-c and e-h, comparisons were versus related controls, using two-sided Student’s t-test. p values in a denoted by *** were p < 0.0001. Values are expressed as the mean ± SEM. NC, normal chow; HFD, high fat diet.

Source data

Extended Data Fig. 2 Insulin decreased InsR protein levels.

a-c, Dose-dependent effect of insulin (6 h) on InsR protein levels in primary hepatocytes from C57BL/6J mice. n = 3 cells examined over 2 independent experiments in b, c. d-f, Time-dependent effect of insulin (100 nM) on InsR protein levels in primary hepatocytes from C57BL/6J mice. n = 3 cells examined over 2 independent experiments in e, f. For statistical analysis in b-c and e-f, comparisons were versus related controls, using two-sided Student’s t-test. p values in b denoted by asterisks (from left to right): p = 0.020, p = 0.024, p = 0.012, p = 0.0043. p values in c denoted by asterisks (from left to right): p = 0.033, p = 0.021, p = 0.012, p = 0.013, p = 0.0014. p values in e denoted by asterisks (from left to right): p = 0.010, p = 0.0053, p = 0.0020. p values in f denoted by asterisks (from left to right): p = 0.013, p = 0.031, p = 0.014, p = 0.029, p = 0.043. Values are presented as the mean ± SEM.

Source data

Extended Data Fig. 3 EphB4 interacted with InsR.

a, The identified peptide from EPHB4 by mass spectrum in INSR interaction protein screening in HepG2 cells. The b- and y-type product ions are marked on the mass spectrum and also illustrated in the peptide sequence shown above. b, c, Expression pattern of EphA and EphB families in C57BL/6 J mice by semiquantitative PCR. d, Interactions of homologous proteins of EPHB4 with InsR in HepG2 cells. e, Interaction of EPHB4 with other tyrosine kinases in HepG2 cells. f, Interaction of EPHB4 with IGF1R in HepG2 cells. g, h, Interaction of EPHB4-HA and Flag-INSR in HEK293T cells after Flag-INSR or EPHB4-HA was immunoprecipitated. i, Co-localization of EPHB4 and INSR detected using endogenous antibodies. Pearson’s R value: 0.57. j, Direct binding of EPHB4 and InsR in a pull-down assay using purified proteins. k, Diagrammatic sketch of the InsR protein structure. The short line indicates the truncated mutants of the full-length InsR protein. l, Interaction of EPHB4 with INSR domains with INSR truncation mutants. m, Diagrammatic sketch of the EPHB4 protein structure. The short line indicates the mutants in which part of the sequence was deleted from the full-length EPHB4 protein. n, Interaction of INSR with EPHB4 domains in EPHB4 deletion mutants. o, p, Interaction of INSR with EPHB4 (WT) and its kinase-dead mutant (KD) in HepG2 cells. n = 3 independent experiments in p. For statistical analysis in p, comparisons were versus related controls, using two-sided Student’s t-test. Values are presented as the mean ± SEM.

Source data

Extended Data Fig. 4 EphB4 expression pattern.

a, b, EphB4 mRNA (a, n = 3 mice) and protein (b, n = 3 mice) levels in the livers of HFD-fed mice. EPHB4 proteins were detected in the same samples used to detect Actin levels in Extended Data Fig. 1d. c, d, EPHB4 mRNA level in HepG2 cells (c, n = 5 biologically independent cells) and primary hepatocytes (d, n = 4 biologically independent cells) stimulated with insulin (100 nM). For statistical analysis in a-d, comparisons were versus related controls, using two-sided Student’s t-test. Values are presented as the mean ± SEM. NC, normal chow; HFD, high fat diet.

Source data

Extended Data Fig. 5 EphB4 promoted InsR degradation.

a, b, InsR protein levels upon insulin treatment and EPHB4 overexpression in primary hepatocytes. n = 3 biologically independent cells in b. c, d, Plasma membrane INSR protein levels were detected in control and EPHB4-overexpressing HepG2 cells by measuring surface biotinylation. n = 3 independent experiments in d. e, Body weight of Ad-EPHB4 mice. Age: 8 weeks. n = 11 mice. f, Plasma AST levels in Ad-EPHB4 mice. n = 11 mice. g, Plasma ALT levels in Ad-EPHB4 mice. n = 11 mice. h, Plasma insulin levels in in Ad-EPHB4 mice. n = 11 mice. i, InsR mRNA level in the Ad-EPHB4 mouse liver. n = 11 mice. j, k, Levels of ER stress-related proteins in EPHB4-overexpressing primary hepatocytes (i, n = 3 biologically independent cells) and livers (j, n = 6 mice). l, Protein synthesis assay using O-propargyl-puromycin (OPP) labeling. For statistical analysis in b and d-i, comparisons were versus related controls, using two-sided Student’s t-test. Values are presented as the mean ± SEM.

Source data

Extended Data Fig. 6 EphB4 promoted InsR degradation in the lysosome.

a, Effect of EPHB4 on INSR ubiquitination in HepG2 cells. b, c, Effect of proteasome inhibitors on EPHB4-induced INSR degradation. n = 3 biologically independent cell samples in c. d, Colocalization of EPHB4, INSR and Clathrin light chain (Clta) in HepG2 cells. Enlarged images are indicated by the white frames. Pearson’s R value for the colocalization of INSR with Clta: 0.65. e, Effect of EPHB4 overexpression on the interaction between InsR and the early endosome marker EEA1. f, Effect of EPHB4 overexpression on the interaction between INSR and the late endosome marker RAB7. g, Effect of EPHB4 overexpression on the interaction between INSR and the recycling endosome marker RAB11. h, Colocalization of EPHB4, INSR and RAB11 in HepG2 cells. Enlarged images were indicated by the white frames. Pearson’s R value for the colocalization of INSR with RAB11: 0.38. i, Interaction of AP2M1 with EPHB4 domains in EPHB4 truncation mutants. j, Ap2 binding motif sequence. k, Predicted Ap2 binding motifs in EPHB4. l, Statistical analysis of the rescue effect of mutants in the Ap2 binding motifs in EPHB4 on INSR degradation in HepG2 cells. n = 4 biologically independent cell samples. For statistical analysis in c and l, comparisons were versus related controls, using two-sided Student’s t-test. Values are expressed as the mean ± SEM.

Source data

Extended Data Fig. 7 Lipids and inflammatory profiles in EphB4 LKO mice.

a, b, EPHB4 knockdown by two specific shRNAs in HepG2 cells. n = 4 biologically independent cell samples. c, EphB4 mRNA levels determined using qPCR in tissues from EphB4 LKO mice fed NC. Age: 5 weeks, n = 7 mice. d, e, Hepatic EphB4 and InsR protein levels in EphB4 LKO mice. n = 8 mice. f, Body weight of EphB4 LKO mice fed NC. n = 10 mice. g, GTT of EphB4 LKO mice fed NC. n = 10 mice. h, ITT of EphB4 LKO mice fed NC. n = 10 mice. i, Body weight of EphB4 LKO mice fed an HFD. n = 10 mice. j, Expression of inflammation-related genes in the liver of EphB4 LKO mice fed an HFD. n = 8 mice. k, Expression of inflammation-related genes in Epi-WAT of EphB4 LKO mice fed an HFD. n = 8 mice. For statistical analysis in b-c and e-k, comparisons were versus related controls, using two-sided Student’s t-test. Values are presented as the mean ± SEM. NC, normal chow.

Source data

Extended Data Fig. 8 Inflammatory profiles in db/db-EphB4 LKO mice.

a, Body weight of db/db-EphB4 LKO mice (n = 12 mice). b, Hepatic EphB4 protein levels in db/db-EphB4 LKO mice (n = 3 mice). c, Liver weight of db/db-EphB4 LKO mice (n = 9 mice). d, Liver index of db/db-EphB4 LKO mice (n = 9 mice). e, Epi-WAT mass of db/db-EphB4 LKO mice (n = 9 mice). f, Epi-WAT index of db/db-EphB4 LKO mice (n = 9 mice). g, Inflammatory gene expression in the livers of db/db-EphB4 LKO mice (n = 9 mice). h to j, Time-dependent effect of insulin (100 nM) on InsR protein levels in primary hepatocytes from EphB4 fl/fl and EphB4 LKO mice. n = 4 cells examined over 2 independent experiments. For statistical analysis in a-g and i-j, comparisons were versus related controls, using two-sided Student’s t-test. Values are expressed as the mean ± SEM.

Source data

Extended Data Fig. 9 A pharmacological EphB4 inhibitor improved metabolism in mice.

a, b, c, Effect of LCA on the insulin-stimulated increase in p-AKT levels in HepG2 cells (a, b, n = 3 biologically independent cell samples) and primary hepatocytes (c). d, e, Gluconeogenesis in primary hepatocytes from HFD-fed mice (d, n = 4 biologically independent cell samples) or db/db mice (e, n = 3 biologically independent cell samples) treated with LCA. f, Body weight of db/db mice grouped for drug administration (age: 8 weeks, n = 10 mice). g, Fasting plasma glucose level in db/db mice grouped for drug administration (n = 10 mice). h, Percent decrease in glucose levels after the insulin injection and drug administration (n = 10 mice). i, GTT of LCA-treated db/db mice (n = 9 mice). j, ITT of LCA-treated db/db mice (n = 9 mice). k, Serum TG levels in NVP-BHG712- or LCA-treated db/db mice (n = 9 mice). l-n, InsR protein level (n = 7 mice) and p-Akt levels (n = 3 mice) in the livers of LCA-treated db/db mice. For statistical analysis in b, d-e, i-k and m-n, comparisons were versus related controls, using two-sided Student’s t-test. For statistical analysis in f-h, comparisons were made for the three groups, using one-way ANOVA. p values in i denoted by asterisks (from left to right): p = 0.0069, p = 0.047, p = 0.0032, p = 0.0076, p = 0.0040. p values in j denoted by asterisks (from left to right): p = 0.022, p = 0.047, p = 0.042. Values are expressed as the mean ± SEM.

Source data

Extended Data Fig. 10 EphB4 shRNA improved metabolism in mice.

a, Body weight of db/db mice injected with the EphB4 shRNA (ctr shRNA n = 8 mice, EphB4 shRNA n = 14 mice). b, Hepatic EphB4 mRNA levels in EphB4 shRNA-injected mice (ctr shRNA n = 8 mice, EphB4 shRNA n = 14 mice). c, Hepatic EphB4 mRNA levels in EphB4 shRNA-injected mice. (ctr shRNA n = 6 mice, EphB4 shRNA n = 4 mice). d-e, p-Akt levels in the livers of EphB4 shRNA-injected mice after the insulin (0.75 U/kg) injection (age: 10 weeks, n = 3 mice in e). f, Gluconeogenesis assay in primary hepatocytes from EphB4 shRNA-injected mice (n = 5 biologically independent cell samples). g, Serum TG levels in EphB4 shRNA-injected mice (ctr shRNA n = 8 mice, EphB4 shRNA n = 14 mice). h, Graphic summary on insulin receptor degradation in the liver through EphB4. For statistical analysis in b-d and f-g, comparisons were versus related controls, using two-sided Student’s t-test. Values are expressed as the mean ± SEM.

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Liu, X., Wang, K., Hou, S. et al. Insulin induces insulin receptor degradation in the liver through EphB4. Nat Metab 4, 1202–1213 (2022). https://doi.org/10.1038/s42255-022-00634-5

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