| Literature DB >> 33687722 |
Andrea Fossati1, Fabian Frommelt1, Federico Uliana1, Claudia Martelli1, Matej Vizovisek1, Ludovic Gillet1, Ben Collins2, Matthias Gstaiger1, Ruedi Aebersold3,4.
Abstract
In living cells, most proteins are organized in stable or transient functional assemblies, protein complexes, which control a multitude of vital cellular processes such as cell cycle progression, metabolism, and signal transduction. Over several decades, specific protein complexes have been analyzed by structural biology methods, initially X-ray crystallography and more recently single particle cryoEM. In parallel, mass spectrometry (MS)-based methods including in vitro affinity-purification coupled to MS or in vivo protein proximity-dependent labeling methods have proven particularly effective to detect complexes, thus nominating new assemblies for structural analysis. Those approaches, however, are either of limited in throughput or require specifically engineered protein systems.In this chapter, we present protocols for a workflow that supports the parallel analysis of multiple complexes from the same biological sample with respect to abundance, subunit composition, and stoichiometry. It consists of the separation of native complexes by size-exclusion chromatography (SEC) and the subsequent mass spectrometric analysis of the proteins in consecutive SEC fractions. In particular, we describe (1) optimized conditions to achieve native protein complex separation by SEC, (2) the preparation of the SEC fractions for MS analysis, (3) the acquisition of the MS data at high throughput via SWATH/DIA (data-independent analysis) mass spectrometry and short chromatographic gradients, and (4) a set of bioinformatic tools for the targeted analysis of protein complexes. Altogether, the parallel measurement of a high number of complexes from a single biological sample results in unprecedented system-level insights into the remodeling of cellular protein complexes in response to perturbations of a broad range of cellular systems.Keywords: Protein co-elution profiling; Protein complex analysis; SEC–MS
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Year: 2021 PMID: 33687722 DOI: 10.1007/978-1-0716-1178-4_18
Source DB: PubMed Journal: Methods Mol Biol ISSN: 1064-3745