Proteostasis Core: Quantitative global proteomics

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Project Summary / Abstract (Core C) Core C will conduct global proteomics experiments for project participants. This work will be performed under the leadership of Drs. Steve Gygi and Daniel Finley at Harvard Medical School (HMS). The renowned facility at HMS can provide quantitative readouts of protein levels of 10 samples at once, using the TMT-MS3 method of global proteomics developed by the Gygi group. A single run of 10 samples provides detailed quantitative data on 10 experimental proteomes. This comprehensive view of perturbations under defined experimental conditions yield a wealth of information, including the levels of over 1000 components of the proteostasis network (PN), such as proteasomes and chaperones, the state of thousands of substrates of these enzymes, and the occupancy of ~30,000 protein modification sites. Importantly, each TMT-MS3 run will provide a fingerprint of the state of the PN at a given time and condition. Thus, the phenotypic characterization of new mutants in the PN, such as transgenic mutants with enhanced proteasome activity, will be accomplished at the highest resolution possible at present. Core C will also give researchers access to a second proteomics signature: a global account of ubiquitin modifications of proteins. This will be accomplished using the “GG pulldown” method, in which tryptic peptides bearing diglycine remnants from ubiquitin are enriched via immunopurification prior to mass spectrometry. TMT proteomics and ubiquitin proteomics, applied in parallel, will provide a uniquely detailed and informative snapshot of the state of the PN in a cell. These analytical approaches will be invaluable to all projects within the team, including core projects that focus on biosensors (Core B) and chemical regulators of the PN (Core D). In addition, proteomics approaches of the proteasome and autophagy projects (2 and 3), involving in vivo work in the mouse, will be closely coordinated so that the resulting datasets can be integrated and subjected to metadata analysis. Thus, the methodologies of Core C will help to unite the research efforts of the project and to drive our understanding of PNs to a more quantitative and systematic level.