ABSTRACT – PROTEOMICS CORE Signaling networks are crucial for the orchestration of cellular functions in response to stimuli. Knowledge of the structure of these networks provides a basis for understanding the pathological consequences of their malfunction and offers opportunities for designing therapeutic interventions. The complexity of these networks and the speed with which signals are transmitted in cells makes mapping them a formidable challenge. The typical approach for elucidating the structure of cellular signaling networks involves an iterative process of creating signaling protein disruptions, domain mutants and site-directed mutants followed by characterization of each mutant through a battery of cellular activation assays. As a complementary approach, modern proteomic methods using quantitative mass spectrometry can facilitate the hypothesis-driven characterization of signaling pathways by providing a global view of cellular phosphorylation and protein-protein interactions through a variety of activation states. The Core B, Proteomics core will make cutting-edge, quantitative proteomic capabilities and computational analysis available to the investigators of this program project. The core will provide identification and relative quantitation of the protein composition and post-translational modification state of proteins using modern LC/MS techniques. This core has a strong track record of fruitful collaboration with the PI's of the program project culminating in the generation of 7 large phosphoproteomic and 8 CoIP-LCMS protein interaction datasets and publication of collaborative papers which elucidated the molecular details of how ZAP-70 is recruited to LAT and how the catalytic activity of ZAP-70 mediates basal signaling and negative feedback of T cell receptor signaling. The core has recently developed new technologies for the characterization of protein interaction networks in living cells using TurboID and the deepest possible characterization of phosphorylation networks using Src SH2 domain Superbinder and TMT BOOST channels. These newly developed methods will be leveraged to support the project PIs to determine protein-protein interactors and phosphorylation sites from T cell lines and primary mouse T cells. The core also has a suite of computational tools to provide rigorous statistical analysis of the proteomic data and to make new signaling pathway predictions.