EPIC: Software Toolkit for Elution Profile-Based Inference of Protein Complexes

Heteromeric protein complexes are key macromolecular machines of the cell, but their description remains incomplete. We previously reported an experimental strategy for global characterization of native protein assemblies based on chromatographic fractionation of biological extracts coupled to precision mass spectrometry analysis (CF/MS), but the resulting data can be challenging to process and interpret. Here, we describe EPIC (Elution Profile-based Inference of Complexes), a software toolkit for automated scoring of CF/MS data for large-scale determination of high-confidence physical interaction networks and macromolecular assemblies from diverse biological specimens. As a case study, we used EPIC to map the global interactome of Caenorhabditis elegans, defining 590 putative worm protein complexes linked to diverse biological processes, including assemblies unique to nematodes. The EPIC software is freely available as a Jupyter notebook packaged in a Docker container (https://hub.docker.com/r/baderlab/bio-epic/), and the open source code is available via GitHub (https://github.com/BaderLab/EPIC).