Novel biochemical, structural and systems insights into inflammatory signaling revealed by contextual interaction proteomics

Protein-protein interactions (PPI) represent the main mode of the proteome organization in the cell. In the last decade, several large-scale representations of PPI networks have captured generic aspects of the functional organization of network components, but mostly lack the context of cellular states. However, the generation of contextual representations of PPI networks is essential for structural and systems-level modeling of biological processes and remains an unsolved challenge. In this study we describe an integrated experimental/computational strategy to achieve a contextualized modeling of PPI. This strategy defines the composition, stoichiometry, spatio-temporal organization and cellular requirements for the formation of target assemblies. We used this approach to generate an integrated model of the formation principles and architecture of a large signalosome, the TNF-receptor signaling complex (TNF-RSC). Overall, we show that the integration of systems- and structure-level information provides a generic, largely unexplored link between the modular proteome and cellular function. Significance StatementIn this work, we propose a critical shift in the way we analyze, and think the study of, protein-protein interactions (PPI), and present an experimental and computational framework to model them in the cellular context. We applied this framework to the signalosome tumor necrosis factor receptor signaling complex (TNF-RSC), and generated an integrated model of its formation and architecture that provides new insights and resolved controversies regarding its organization and regulation. To achieve a contextual modelling of PPIs, we first optimized and developed, and then combined, approaches to map the composition of a target complex, its absolute stoichiometry, its spatial organization and assembly/disassembly dynamics, its temporal dependence on signaling, and its reliance on cellular resources.