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 ~8 d of wet-laboratory work, 15 d of mass spectrometry measurement time and 7 d of computational analysis.
Highlights
Proteins are major effectors and regulators of biological processes and can elicit or participate in multiple functions depending on their interaction with other proteins and most catalytic, regulatory and structural functions are carried out by protein complexes
We recently developed a variant of this strategy, complex-centric proteome profiling, which extends the concepts of targeted proteomics to the level of native protein complex analysis
With increasing technical abilities in the area of mass spectrometry based proteomics, highthroughput methodologies for detecting protein-protein interactions (PPIs) by affinity-purification coupled to mass spectrometry (AP-MS) have emerged as gold-standard technique for mapping large PPI interaction networks 1–3
Summary
Proteins are major effectors and regulators of biological processes and can elicit or participate in multiple functions depending on their interaction with other proteins and most catalytic, regulatory and structural functions are carried out by protein complexes. To interrogate potential protein complex assembly intermediates or other protein complex variants that are observable from a set of query subunit profiles additional to the best scoring peak group, secondary peak groups of each complex query are subsequently appended to the FDR filtered list of detected protein complex signals For these assignments a less strict minimum local peak-correlation cutoff is selected manually for the respective dataset. The list of confidently detected protein complex features contains information about the presence and abundance of individual protein complexes, but further entails information about proteome modularity such as protein complex assembly intermediates and subunit stoichiometry ( see Figure 5D/E and anticipated results section) Up to this point in the complex-centric analysis workflow, each protein complex signal detected by CCprofiler is directly linked to one specific protein complex query provided by the prior protein connectivity information. It is important to note that the FDR estimation strategy in CCprofiler operates at the level of protein complex queries and does not propagate to the level of collapsed protein complex signals and the precise error estimations among those collapsed results remain de facto unknown and the subject of future work
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