4.7 Article

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

Journal

NATURE PROTOCOLS
Volume 18, Issue 3, Pages 659-+

Publisher

NATURE PORTFOLIO
DOI: 10.1038/s41596-022-00771-x

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Proteins regulate biological processes by altering their structure or abundance, and detecting protein structural changes can provide valuable information about functional states. The article presents an updated protocol for LiP-MS, a proteomics technique that combines limited proteolysis with mass spectrometry to detect protein structural alterations in complex backgrounds and on a proteome-wide scale.
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 similar to 1 d. These improvements expand the adaptability of LiP-MS and enable wide use in functional proteomics and translational applications.

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