Data analysis of LiP-MS data for high-throughput applications

Proteins regulate biological processes by changing their structure or abundance to accomplish a specific function. In response to any perturbation or stimulus, protein structure may be altered by a variety of 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 a variety 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 (Cappelletti et al., 2021; Piazza et al., 2020; Schopper et al., 2017). We describe advances in the throughput and robustness of the LiP-MS workflow and implementation of data-independent acquisition (DIA) based mass spectrometry, which together achieve high reproducibility and sensitivity, even on large sample sizes.  In addition, 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. Altogether, the newly proposed improvements expand the adaptability of the method and allow for its wide use in systematic functional proteomic studies and translational applications.