Integration of over 9,000 mass spectrometry experiments builds a global map of human protein complexes

Abstract

Macromolecular protein complexes carry out many of the essential functions of cells, and many genetic diseases arise from disrupting the functions of such complexes. Currently, there is great interest in defining the complete set of human protein complexes, but recent published maps lack comprehensive coverage. Here, through the synthesis of over 9,000 published mass spectrometry experiments, we present hu.MAP, the most comprehensive and accurate human protein complex map to date, containing > 4,600 total complexes, > 7,700 proteins, and > 56,000 unique interactions, including thousands of confident protein interactions not identified by the original publications. hu.MAP accurately recapitulates known complexes withheld from the learning procedure, which was optimized with the aid of a new quantitative metric (k‐cliques) for comparing sets of sets. The vast majority of complexes in our map are significantly enriched with literature annotations, and the map overall shows improved coverage of many disease‐associated proteins, as we describe in detail for ciliopathies. Using hu.MAP, we predicted and experimentally validated candidate ciliopathy disease genes in vivo in a model vertebrate, discovering CCDC138, WDR90, and KIAA1328 to be new cilia basal body/centriolar satellite proteins, and identifying ANKRD55 as a novel member of the intraflagellar transport machinery. By offering significant improvements to the accuracy and coverage of human protein complexes, hu.MAP (http://proteincomplexes.org) serves as a valuable resource for better understanding the core cellular functions of human proteins and helping to determine mechanistic foundations of human disease.

Interrogation of Mammalian Protein Complex Structure, Function, and Membership Using Genome-Scale Fitness Screens

“…In order to test this observation for interacting proteins in general, we collated all large-scale, annotated protein-protein interaction (PPI) datasets generated by individual or joint research groups over the past five years (Drew et al, 2017; Hein et al, 2015; Marsh et al, 2013; Rolland et al, 2014; Thul et al, 2017; Wan et al, 2015), including Core CORUM as the gold-standard literature reference (Ruepp et al, 2010). We again found that gene pairs with an annotated PPI consistently exhibited greater fitness profile correlations across all datasets than gene pairs that did not have an annotated interaction (Figure S1D).…”

Identifying direct contacts between protein complex subunits from their conditional dependence in proteomics datasets

“…3,000 co-fractionation / mass spectrometry experiments [4, 6], and restrict direct contact predictions to known co-complex interactions. Specifically, we use complexes with structures in the PDB for evaluation and a set of 896 protein complexes larger than 4 unique subunits derived from >9000 published mass spectrometry proteomics experiments [1, 3, 4, 6] in hu.MAP [32], for all other predictions. In all, we identified 2,434 potential interactions ( S3 Table ).…”

“…Finally, we filtered our reported direct contact predictions by protein interactions that are present in 896 complexes larger than 4 subunits from the human protein complex map, hu.MAP [32]. This step was to ensure pairs of proteins are present in the same complex thereby increasing the likelihood of direct contact.…”

“…[10]. Similar to the method described in [32] we collapsed all crosslink interactions to one interaction per pair of proteins. We first generate a random overlap distribution by selecting random pairs of proteins from the crosslinking dataset and calculate the overlap with the direct contact predictions for 1000 repeated trials.…”

“…Specifically, we incorporate pseudo-counts, scale and transform the correlation matrix, use a sparse graphical model learning framework to compute conditionally dependent partial correlations, followed by StARS stability analysis [29] to re-score the resulting conditional dependency matrix such that each entry corresponds to the frequency with which it is supported by subsample trials. We retain non-zero scores between subunits within each pre-defined human protein complex [32] as our prediction of direct contacts.…”