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Endogenous cell membrane interactome mapping for the GLP-1 receptor in different cell types

Nature Chemical Biology (2024)Cite this article

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Abstract

The GLP-1 receptor, one of the most successful drug targets for the treatment of type 2 diabetes and obesity, is known to engage multiple intracellular signaling proteins. However, it remains less explored how the receptor interacts with proteins on the cell membrane. Here, we present a ligand-based proximity labeling approach to interrogate the native cell membrane interactome for the GLP-1 receptor after agonist simulation. Our study identified several unreported putative cell membrane interactors for the endogenous receptor in either a pancreatic β cell line or a neuronal cell line. We further uncovered new regulators of GLP-1 receptor-mediated signaling and insulinotropic responses in β cells. Additionally, we obtained a time-resolved cell membrane interactome map for the receptor in β cells. Therefore, our study provides a new approach that is generalizable to map endogenous cell membrane interactomes for G-protein-coupled receptors to decipher the molecular basis of their cell-type-specific functional regulation.

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Fig. 1: Design of ligand-based proximity labeling and characterization of two GLP-1–PEX probes.
Fig. 2: Assessment of proximity labeling with two GLP-1–PEX probes in GLP-1R-expressing HEK293 cells.
Fig. 3: Assessment of proximity labeling with two GLP-1–PEX probes in two cell types expressing endogenous GLP-1R.
Fig. 4: Mapping endogenous cell membrane interactomes for GLP-1R in two cell types.
Fig. 5: Validation and functional assessment of selected GLP-1R-interacting proteins identified in INS-1E β cells.
Fig. 6: Time-resolved mapping of the cell membrane interactome engaged by GLP-1R in INS-1E β cells.

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Data availability

The raw LC–MS/MS data generated in this study have been deposited to the ProteomeXchange Consortium55 via the iProX partner repository56 with the dataset identifier IPX0007296000 or PXD046204. Protein identification and quantification results related to Figs. 4 and 6 are provided in Supplementary Tables 1–4. Source data are provided with this paper.

References

  1. Graaf, C. et al. Glucagon-like peptide-1 and its class B G protein-coupled receptors: a long march to therapeutic successes. Pharm. Rev. 68, 954–1013 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  2. Nauck, M. A., Quast, D. R., Wefers, J. & Meier, J. J. GLP-1 receptor agonists in the treatment of type 2 diabetes—state-of-the-art. Mol. Metab. 46, 101102 (2021).

    Article  CAS  PubMed  Google Scholar 

  3. Andersen, A., Lund, A., Knop, F. K. & Vilsboll, T. Glucagon-like peptide 1 in health and disease. Nat. Rev. Endocrinol. 14, 390–403 (2018).

    Article  CAS  PubMed  Google Scholar 

  4. Drucker, D. J. Mechanisms of action and therapeutic application of glucagon-like peptide-1. Cell Metab. 27, 740–756 (2018).

    Article  CAS  PubMed  Google Scholar 

  5. Marzook, A., Tomas, A. & Jones, B. The interplay of glucagon-like peptide-1 receptor trafficking and signalling in pancreatic β cells. Front. Endocrinol. 12, 678055 (2021).

    Article  Google Scholar 

  6. Schelshorn, D. et al. Lateral allosterism in the glucagon receptor family: glucagon-like peptide 1 induces G-protein-coupled receptor heteromer formation. Mol. Pharmacol. 81, 309–318 (2012).

    Article  CAS  PubMed  Google Scholar 

  7. Roed, S. N. et al. Functional consequences of glucagon-like peptide-1 receptor cross-talk and trafficking. J. Biol. Chem. 290, 1233–1243 (2015).

    Article  CAS  PubMed  Google Scholar 

  8. Lu, S.-C. et al. GIPR antagonist antibodies conjugated to GLP-1 peptide are bispecific molecules that decrease weight in obese mice and monkeys. Cell Rep. Med. 2, 100263 (2021).

    Article  PubMed  PubMed Central  Google Scholar 

  9. Wang, Y. Z., Yang, D. H. & Wang, M. W. Signaling profiles in HEK 293T cells co-expressing GLP-1 and GIP receptors. Acta Pharmacol. Sin. 43, 1453–1460 (2022).

    Article  CAS  PubMed  Google Scholar 

  10. Rowlands, J., Heng, J., Newsholme, P. & Carlessi, R. Pleiotropic effects of GLP-1 and analogs on cell signaling, metabolism, and function. Front. Endocrinol. 9, 672 (2018).

    Article  Google Scholar 

  11. Ast, J. et al. Revealing the tissue-level complexity of endogenous glucagon-like peptide-1 receptor expression and signaling. Nat. Commun. 14, 301 (2023).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Zhang, M. et al. Progesterone receptor membrane component 1 is a functional part of the glucagon-like peptide-1 (GLP-1) receptor complex in pancreatic β cells. Mol. Cell. Proteom. 13, 3049–3062 (2014).

    Article  CAS  Google Scholar 

  13. Huang, X. et al. The identification of novel proteins that interact with the GLP-1 receptor and restrain its activity. Mol. Endocrinol. 27, 1550–1563 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Dai, F. F. et al. A novel GLP1 receptor interacting protein ATP6ap2 regulates insulin secretion in pancreatic β cells. J. Biol. Chem. 290, 25045–25061 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Qin, W., Cho, K. F., Cavanagh, P. E. & Ting, A. Y. Deciphering molecular interactions by proximity labeling. Nat. Methods 18, 133–143 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Loh, K. H. et al. Proteomic analysis of unbounded cellular compartments: synaptic clefts. Cell 166, 1295–1307 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Markmiller, S. et al. Context-dependent and disease-specific diversity in protein interactions within stress granules. Cell 172, 590–604 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Go, C. D. et al. A proximity-dependent biotinylation map of a human cell. Nature 595, 120–124 (2021).

    Article  CAS  PubMed  Google Scholar 

  19. Lobingier, B. T. et al. An approach to spatiotemporally resolve protein interaction networks in living cells. Cell 169, 350–360 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Paek, J. et al. Multidimensional tracking of GPCR signaling via peroxidase-catalyzed proximity labeling. Cell 169, 338–349 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Qin, W. et al. Dynamic mapping of proteome trafficking within and between living cells by TransitID. Cell 186, 3307–3324 (2023).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Polacco, B. J. et al. Profiling the proximal proteome of the activated μ-opioid receptor. Nat. Chem. Biol. 20, 1133–1143 (2024).

    Google Scholar 

  23. Feng, W. et al. Identifying the cardiac dyad proteome in vivo by a BioID2 knock-in strategy. Circulation 141, 940–942 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  24. Trowbridge, A. D. et al. Small molecule photocatalysis enables drug target identification via energy transfer. Proc. Natl Acad. Sci. USA 119, e2208077119 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Zhang, Y. et al. Cryo-EM structure of the activated GLP-1 receptor in complex with a G protein. Nature 546, 248–253 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Zhang, X. et al. Differential GLP-1R binding and activation by peptide and non-peptide agonists. Mol. Cell 80, 485–500 (2020).

    Article  CAS  PubMed  Google Scholar 

  27. Martell, J. D. et al. Engineered ascorbate peroxidase as a genetically encoded reporter for electron microscopy. Nat. Biotechnol. 30, 1143–1148 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Buenaventura, T. et al. Agonist-induced membrane nanodomain clustering drives GLP-1 receptor responses in pancreatic β cells. PLoS Biol. 17, e3000097 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Gillet, L. C. et al. Targeted data extraction of the MS/MS spectra generated by data-independent acquisition: a new concept for consistent and accurate proteome analysis. Mol. Cell Proteom. 11, O111.016717 (2012).

    Article  Google Scholar 

  30. Ludwig, C. et al. Data-independent acquisition-based SWATH–MS for quantitative proteomics: a tutorial. Mol. Syst. Biol. 14, e8126 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  31. Muntel, J. et al. Comparison of protein quantification in a complex background by DIA and TMT workflows with fixed instrument time. J. Proteome Res. 18, 1340–1351 (2019).

    Article  CAS  PubMed  Google Scholar 

  32. Thul, P. J. et al. A subcellular map of the human proteome. Science 356, eaal3321 (2017).

    Article  PubMed  Google Scholar 

  33. Oughtred, R. et al. The BioGRID database: a comprehensive biomedical resource of curated protein, genetic, and chemical interactions. Protein Sci. 30, 187–200 (2021).

    Article  CAS  PubMed  Google Scholar 

  34. Owada, S. et al. Glucose decreases Na+,K+-ATPase activity in pancreatic β-cells. An effect mediated via Ca2+-independent phospholipase A2 and protein kinase C-dependent phosphorylation of the α-subunit. J. Biol. Chem. 274, 2000–2008 (1999).

    Article  CAS  PubMed  Google Scholar 

  35. Di Paola, R. et al. ENPP1 affects insulin action and secretion: evidences from in vitro studies. PLoS ONE 6, e19462 (2011).

    Article  PubMed  PubMed Central  Google Scholar 

  36. Zhu, H. J. et al. The changes of serum glypican4 in obese patients with different glucose metabolism status. J. Clin. Endocrinol. Metab. 99, E2697–E2701 (2014).

    Article  CAS  PubMed  Google Scholar 

  37. Ashok, A. & Singh, N. Prion protein modulates glucose homeostasis by altering intracellular iron. Sci. Rep. 8, 6556 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  38. Gervais, M., Labouebe, G., Picard, A., Thorens, B. & Croizier, S. EphrinB1 modulates glutamatergic inputs into POMC-expressing progenitors and controls glucose homeostasis. PLoS Biol. 18, e3000680 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Rachdi, L. et al. Regulated expression and function of the GABAB receptor in human pancreatic β cell line and islets. Sci. Rep. 10, 13469 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. Brown, M. R. et al. Electrogenic sodium bicarbonate cotransporter NBCe1 regulates pancreatic β cell function in type 2 diabetes. J. Clin. Invest. 131, e142365 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Manchanda, Y. et al. Enhanced endosomal signaling and desensitization of GLP-1R vs GIPR in pancreatic β cells. Endocrinology 164, bqad028 (2023).

    Article  PubMed  PubMed Central  Google Scholar 

  42. Thomsen, A. R. B. et al. GPCR–G protein–β-arrestin super-complex mediates sustained G protein signaling. Cell 166, 907–919 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. Li, J. et al. Cell-surface proteomic profiling in the fly brain uncovers wiring regulators. Cell 180, 373–386 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Li, Y. et al. Rapid enzyme-mediated biotinylation for cell surface proteome profiling. Anal. Chem. 93, 4542–4551 (2021).

    Article  CAS  PubMed  Google Scholar 

  45. Bosch, J. A., Chen, C. L. & Perrimon, N. Proximity-dependent labeling methods for proteomic profiling in living cells: an update. Wiley Interdiscip. Rev. Dev. Biol. 10, e392 (2021).

    Article  CAS  PubMed  Google Scholar 

  46. Bulur, N. et al. Expression of the electrogenic Na+-HCO3–-cotransporter NBCe1 in tumoral insulin-producing BRIN-BD11 cells. Cell. Physiol. Biochem. 24, 187–192 (2009).

    Article  CAS  PubMed  Google Scholar 

  47. Wang, Y. J. et al. Single-cell transcriptomics of the human endocrine pancreas. Diabetes 65, 3028–3038 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Fico, A., Maina, F. & Dono, R. Fine-tuning of cell signaling by glypicans. Cell. Mol. Life Sci. 68, 923–929 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Ussar, S., Bezy, O., Blüher, M. & Kahn, C. R. Glypican-4 enhances insulin signaling via interaction with the insulin receptor and serves as a novel adipokine. Diabetes 61, 2289–2298 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Cong, L. et al. Multiplex genome engineering using CRISPR/Cas systems. Science 339, 819–823 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  51. Demichev, V., Messner, C. B., Vernardis, S. I., Lilley, K. S. & Ralser, M. DIA-NN: neural networks and interference correction enable deep proteome coverage in high throughput. Nat. Methods 17, 41–44 (2020).

    Article  CAS  PubMed  Google Scholar 

  52. Kong, A. T., Leprevost, F. V., Avtonomov, D. M., Mellacheruvu, D. & Nesvizhskii, A. I. MSFragger: ultrafast and comprehensive peptide identification in mass spectrometry-based proteomics. Nat. Methods 14, 513–520 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  53. Szklarczyk, D. et al. The STRING database in 2023: protein–protein association networks and functional enrichment analyses for any sequenced genome of interest. Nucleic Acids Res. 51, D638–D646 (2023).

    Article  CAS  PubMed  Google Scholar 

  54. Zhang, B. et al. A novel G protein-biased and subtype-selective agonist for a G protein-coupled receptor discovered from screening herbal extracts. ACS Cent. Sci. 6, 213–225 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  55. Deutsch, E. W. et al. The ProteomeXchange Consortium at 10 years: 2023 update. Nucleic Acids Res. 51, D1539–D1548 (2023).

    Article  PubMed  Google Scholar 

  56. Chen, T. et al. iProX in 2021: connecting proteomics data sharing with big data. Nucleic Acids Res. 50, D1522–D1527 (2022).

    Article  CAS  PubMed  Google Scholar 

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Acknowledgements

We are grateful to Q. Wang from ShanghaiTech University for the generous gifts of His-SUMO and ULP1 plasmids and Y. Liu for help with the insulin secretion assay. We also thank T. Mao from Structure Therapeutics, X. Liu, C. Tian and other staff members of the Assay, Mammalian, Cloning, and Imaging Core Facilities of iHuman Institute for their great help or technical support. This work was funded by the National Key R&D Program of China (2022YFA1302902 to W.S.; 2021YFA0804700 to M.Z.), National Natural Science Foundation of China (32171439 to W.S.; 32301250 to B.Z.), ShanghaiTech University, Shanghai Frontiers Science Center for Biomacromolecules and Precision Medicine at ShanghaiTech University (to W.S. and M.Z.) and the Innovative Research Team of High-Level Local Universities in Shanghai (to M.Z.).

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Author notes

  1. These authors contributed equally: Ting Dang, Jie Yu, Zhihe Cao.

Authors and Affiliations

  1. iHuman Institute, ShanghaiTech University, Shanghai, China

    Ting Dang, Jie Yu, Bingjie Zhang, Shanshan Li, Ye Xin, Lingyun Yang, Ronghui Lou & Wenqing Shui

  2. School of Life Science and Technology, ShanghaiTech University, Shanghai, China

    Ting Dang, Jie Yu, Zhihe Cao, Ye Xin, Lingyun Yang, Ronghui Lou, Min Zhuang & Wenqing Shui

  3. University of Chinese Academy of Sciences, Beijing, China

    Ting Dang, Jie Yu, Zhihe Cao, Ye Xin, Lingyun Yang & Ronghui Lou

  4. Lingang Laboratory, Shanghai, China

    Jie Yu

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Contributions

W.S. and M.Z. conceived and supervised the project. T.D. developed the method and performed proximity labeling, proteomic analysis and functional assays in INS-1E cells. J.Y. performed proximity labeling and proteomic analyses in SK-N-SH cells. Z.C. prepared the labeling probes and assisted in labeling experiments. B.Z., S.L., Y.X., L.Y. and R.L. assisted in functional assays, proteomic experiments or data processing. W.S. and T.D. wrote the manuscript with input from all other authors.

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Correspondence to Min Zhuang or Wenqing Shui.

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Nature Chemical Biology thanks Alejandra Tomas and the other, anonymous reviewers for their contribution to the peer review of this work.

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Supplementary Figs. 1–9 and Note.

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Supplementary Tables 1–5.

Supplementary Data 1

Unprocessed western blots for Supplementary Figs. 1, 3 and 7.

Supplementary Data 2

Statistical source data for Supplementary Figs. 1, 4, 7 and 8.

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Source Data Fig. 1

Statistical source data.

Source Data Fig. 5

Statistical source data.

Source Data Fig. 5

Unprocessed western blots.

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Dang, T., Yu, J., Cao, Z. et al. Endogenous cell membrane interactome mapping for the GLP-1 receptor in different cell types. Nat Chem Biol (2024). https://doi.org/10.1038/s41589-024-01714-1

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