A proteome-wide map of 20(S)-hydroxycholesterol interactors in cell membranes
Abstract
Oxysterols (OHCs) are hydroxylated cholesterol metabolites that play ubiquitous roles in health and disease. Due to the non-covalent nature of their interactions and their unique partitioning in membranes, the analysis of live-cell, proteome-wide interactions of OHCs remains an unmet challenge. Here, we present a structurally precise chemoproteomics probe for the biologically active molecule 20(S)-hydroxycholesterol (20(S)-OHC) and provide a map of its proteome-wide targets in the membranes of living cells. Our target catalog consolidates diverse OHC ontologies and demonstrates that OHC-interacting proteins cluster with specific processes in immune response and cancer. Competition experiments reveal that 20(S)-OHC is a chemo-, regio- and stereoselective ligand for the protein transmembrane protein 97 (Tmem97/the σ2 receptor), enabling us to reconstruct the 20(S)-OHC–Tmem97 binding site. Our results demonstrate that multiplexed, quantitative analysis of cellular target engagement can expose new dimensions of metabolite activity and identify actionable targets for molecular therapy.
Additional Information
© 2021 Nature Publishing Group. Received 19 February 2021; Accepted 25 September 2021; Published 19 November 2021. The authors thank A. Li for synthesizing 20(R)-OHC intermediates, the Beckman Institute/Caltech Flow Cytometry Cell Sorting Facility for cell sorting and A.K. Menon and F.R. Maxfield for helpful discussions. This work was funded by the Margaret Early Foundation Research Trust (A.E.O.), a John Stauffer Charitable Trust SURF Fellowship (T.Z.), a William N. Lacy SURF fellowship (S.P.) and NIH training grant NIH GM07616 (G.C.Z.). The Proteome Exploration Laboratory was supported by NIH OD010788, NIH OD020013, the Betty and Gordon Moore Foundation through grant GBMF775 and the Beckman Institute at Caltech. Data availability: Raw MS data for this study have been deposited to the ProteomeXchange Consortium via the PRIDE partner repository with the dataset identifier PXD027787. Source data are provided with this paper. Code availability: Code used for MS data analysis is available on GitHub at https://github.com/alex-ondrus/mass_spec_data_imputation. Author Contributions: Y.-S.C. performed all gel- and MS-based chemoproteomics experiments, MS data processing, cloning, gene editing and coimmunoprecipitation experiments. T.Z., X.M., Y.-S.C. and G.C.Z. performed chemical synthesis. S.P. performed homology modeling and molecular docking experiments. G.C.Z. performed Shh-LIGHT2 signaling assays. A.A.O. performed MS data analysis and visualization. A.M. performed molecular dynamics simulations. B.L. participated in experimental design, provided new reagents/analytical tools and participated in data analysis. J.J.J. participated in data analysis. A.E.O., Y.-S.C., T.Z. and S.P. wrote the manuscript. The authors declare no competing interests. Peer review information: Nature Chemical Biology thanks Anant Menon and other anonymous reviewer(s) for their contribution to the peer review of this work.Attached Files
Accepted Version - nihms-1743436.pdf
Supplemental Material - 41589_2021_907_Fig10_ESM.webp
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Additional details
- PMCID
- PMC8607797
- Eprint ID
- 111995
- Resolver ID
- CaltechAUTHORS:20211122-235754279
- Margaret Early Foundation Research Trust
- Caltech Summer Undergraduate Research Fellowship (SURF)
- NIH Predoctoral Fellowship
- GM07616
- NIH
- OD010788
- NIH
- OD020013
- Gordon and Betty Moore Foundation
- GBMF775
- Caltech Beckman Institute
- Created
-
2021-11-23Created from EPrint's datestamp field
- Updated
-
2022-06-08Created from EPrint's last_modified field