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Complex-centric proteome profiling by SEC-SWATH-MS for the parallel detection of hundreds of protein complexes.

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Bludau,  Isabell
Mann, Matthias / Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, Max Planck Society;

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Citation

Bludau, I., Heusel, M., Frank, M., Rosenberger, G., Hafen, R., Banaei-Esfahani, A., et al. (2020). Complex-centric proteome profiling by SEC-SWATH-MS for the parallel detection of hundreds of protein complexes. Nature Protocols, 15(8), 2341-2386. doi:10.1038/s41596-020-0332-6.


Cite as: http://hdl.handle.net/21.11116/0000-0007-7DE0-0
Abstract
Most catalytic, structural and regulatory functions of the cell are carried out by functional modules, typically complexes containing or consisting of proteins. The composition and abundance of these complexes and the quantitative distribution of specific proteins across different modules are therefore of major significance in basic and translational biology. However, detection and quantification of protein complexes on a proteome-wide scale is technically challenging. We have recently extended the targeted proteomics rationale to the level of native protein complex analysis (complex-centric proteome profiling). The complex-centric workflow described herein consists of size exclusion chromatography (SEC) to fractionate native protein complexes, data-independent acquisition mass spectrometry to precisely quantify the proteins in each SEC fraction based on a set of proteotypic peptides and targeted, complex-centric analysis where prior information from generic protein interaction maps is used to detect and quantify protein complexes with high selectivity and statistical error control via the computational framework CCprofiler (https://github.com/CCprofiler/CCprofiler). Complex-centric proteome profiling captures most proteins in complex-assembled state and reveals their organization into hundreds of complexes and complex variants observable in a given cellular state. The protocol is applicable to cultured cells and can potentially also be adapted to primary tissue and does not require any genetic engineering of the respective sample sources. At present, it requires similar to 8 d of wet-laboratory work, 15 d of mass spectrometry measurement time and 7 d of computational analysis.