EPICOME is an evolving resource for mass spectrometry-based analyses of human and murine proteomes and protein networks. Complex-Complex Interaction (CCI) Resource is currently available through msGPS (mass spectrometry gene products) portal.
CCI Resource
Complex-Complex Interaction (CCI) resource hosts information on the analysis of the human endogenous complexome, based on >3,000 immunoprecipitation experiments that were sequenced with mass spectrometry. This web portal allows users to query CCI networks of interacting proteins grouped in minimal endogenous modules (MEMOs).
Protein-protein interactions constitute the molecular backbone of cell biology, where select proteins assemble into meta-stable complexes to form bioactive units. These complexes then dynamically associate with each other in context of larger networks to carry out diverse biological functions. Thus, understanding the basic mechanisms of cell homeostasis requires both knowledge of the composition of protein complexes and the interactions between them.
Here, we offer analyses that reveal the intrinsic tiered organization of the interactome in three discrete layers. These are (1) the minimal endogenous core complex modules (‘MEMOs’), (2) the unique core complex isoforms (‘uniCOREs’), and (3) the complex-complex interaction networks (CCIs).
To better convey such modularity, we identified 'obligatory' protein modules in protein complexes (minimal endogenous core complex modules, or MEMOs). These modules represent complexes of proteins with stoichiometric interdependence across the entire IP/MS dataset and serve as the conceptual building blocks of the protein complexome. Each of the human protein-coding gene products is assigned to one MEMO only. MEMOs are then used to reconstitute all distinct protein complex ‘isoforms’, which we call unique cores (uniCOREs). The multi-subunit protein complexes conventionally described in the literature most closely correspond to uniCOREs in our resource and likely impart biological functional classification.
Higher-order, weaker, and non-stoichiometric associations between different MEMOs/uniCOREs form the complex-complex interaction (CCI) networks. We suggest that CCIs represent the backbone of regulatory biology.
This work was initiated by the Nuclear Receptor Signaling Atlas Consortium (NURSA; www.NURSA.org). NURSA is a trans-NIH consortium supported by the National Institutes of Diabetes and Digestive & Kidney diseases (NIDDK), Heart Lung and Blood (NHLBI) and Environmental Health Sciences (NIEHS). The mission of NURSA is to foster a broad understanding of the biology of nuclear receptors and their transcriptional coregulators.
CCI information is provided as is, and represents our best efforts to date at resolving high order protein interactions based on the extensive HT-IP/MS study of endogenous human protein complexes. In reference to this resource, please cite this article (the above description of the organizational schema for the complexome is adapted from this publication):
Support for this project includes NIH NURSA grant U19-DK62434 with the Proteomics Strand funding to Bert W.O'Malley and Jun Qin and the Collaborative Bridging Project funding to Rainer B.Lanz, significant financial contributions from the Alkek Center for Molecular Discovery and the McLean Foundation at Baylor College of Medicine, and NIH grants HD08188, DK059820, CA84199, and GM080703.
