4.8 Article

EPIC: software toolkit for elution profile-based inference of protein complexes

Journal

NATURE METHODS
Volume 16, Issue 8, Pages 737-+

Publisher

NATURE PUBLISHING GROUP
DOI: 10.1038/s41592-019-0461-4

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Funding

  1. Canadian Institute of Health Research (CIHR) [148399]
  2. US National Institutes of Health [P41 GM103504, GM070743]
  3. Natural Sciences and Engineering Research Council of Canada (NSERC) Mass Spectrometry-Enabled Science and Engineering (MS-ESE) program
  4. NIH Office of Research Infrastructure Programs [P40 OD010440]

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Protein complexes are key macromolecular machines of the cell, but their description remains incomplete. We and others 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 (chromatographic fractionation-mass spectrometry, CF-MS), but the resulting data are challenging to process and interpret. Here, we describe EPIC (elution profile-based inference of complexes), a software toolkit for automated scoring of large-scale CF-MS data to define high-confidence multi-component macromolecules from diverse biological specimens. As a case study, we used EPIC to map the global inter-actome of Caenorhabditis elegans, defining 612 putative worm protein complexes linked to diverse biological processes. These included novel subunits and assemblies unique to nematodes that we validated using orthogonal methods. The open source EPIC software is freely available as a Jupyter notebook packaged in a Docker container (https://hub.docker.com/r/baderlab/bio-epic/).

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