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Proteome-wide structural changes measured with limited proteolysis-mass spectrometry: an advanced protocol for high-throughput applications

Item Type:Article
Title:Proteome-wide structural changes measured with limited proteolysis-mass spectrometry: an advanced protocol for high-throughput applications
Creators Name:Malinovska, L. and Cappelletti, V. and Kohler, D. and Piazza, I. and Tsai, T.H. and Pepelnjak, M. and Stalder, P. and Dörig, C. and Sesterhenn, F. and Elsässer, F. and Kralickova, L. and Beaton, N. and Reiter, L. and de Souza, N. and Vitek, O. and Picotti, P.
Abstract:Proteins regulate biological processes by changing their structure or abundance to accomplish a specific function. In response to a perturbation, protein structure may be altered by various molecular events, such as post-translational modifications, protein-protein interactions, aggregation, allostery or binding to other molecules. The ability to probe these structural changes in thousands of proteins simultaneously in cells or tissues can provide valuable information about the functional state of biological processes and pathways. Here, we present an updated protocol for LiP-MS, a proteomics technique combining limited proteolysis with mass spectrometry, to detect protein structural alterations in complex backgrounds and on a proteome-wide scale. In LiP-MS, proteins undergo a brief proteolysis in native conditions followed by complete digestion in denaturing conditions, to generate structurally informative proteolytic fragments that are analyzed by mass spectrometry. We describe advances in the throughput and robustness of the LiP-MS workflow and implementation of data-independent acquisition-based mass spectrometry, which together achieve high reproducibility and sensitivity, even on large sample sizes. We introduce MSstatsLiP, an R package dedicated to the analysis of LiP-MS data for the identification of structurally altered peptides and differentially abundant proteins. The experimental procedures take 3 d, mass spectrometric measurement time and data processing depend on sample number and statistical analysis typically requires ~1 d. These improvements expand the adaptability of LiP-MS and enable wide use in functional proteomics and translational applications.
Keywords:High-Throughput Screening, Proteomics, Structural Biology
Source:Nature Protocols
Publisher:Nature Publishing Group
Page Range:659-682
Date:16 March 2023
Additional Information:Erratum in: Nat Protoc 2023 (In Press)
Official Publication:https://doi.org/10.1038/s41596-022-00771-x
PubMed:View item in PubMed

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