mini-Complexome Profiling, an FDR-controlled workflow for global targeted Detection of protein complexes (Hek293 data)

Co-fractionation mass spectrometry experiments (CF-MS) using native-like protein separations such as Blue Native electrophoresis (BNE) or size exclusion chromatography (SEC) enable a global characterization of protein networks, and a better understanding of cellular functions. They do, however, pose significant requirements on sample amounts, on wet lab and on instrument time, which frequently renders statistically useful replication or comparative experiments between multiple biological states non-feasible. Here we present a fast workflow called mini-Complexome Profiling (mCP) for global targeted detection of annotated protein-protein complexes. It comprises mild extraction of complexes, fractionation by BNE and analysis by data independent acquisition mass spectrometry (DIA-MS). Of note, BNE fractionation into 35 fractions is achieved using commercial mini-gels, with minimal requirements on sample amounts. Complexes are detected using a novel, bespoke R package with a controlled false discovery rate (FDR) approach. The tool is available to the community on a Github repository (https://github.com/hugoagno3/mCP ). We first benchmarked our workflow using Hek293 cell lysates as a well established cell line model. We then challenged mCP by investigating changes in the complexome of mouse cardiomyocytes isolated from different heart cavities of single mice. In these challenging and limited samples we detected 48 annotated protein complexes per compartment on average and were able to perform differential inter-cavity comparisons from single animals. These reduced sample and instrument time requirements suggest the suitability of our workflow for complexome screening in sparse samples, e.g. in human patient biopsies.