Global characterization of ubiquitin information networks with mass spectrometry

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DESCRIPTION (provided by applicant): Defects in ubiquitin (Ub) pathways are often responsible for cancer and devastating neurodegenerative diseases. Because of its central role in biological circuits and the potential for therapeutic intervention, the Ub system is an intense research area. However, Ub biology is highly complex, e.g. in humans it is supported by over 500 Ub ligases and 95 deubiquitinases (DUBs). Currently, this complexity and our limited understanding of players and their interactions are a severe hindrance for targeted intervention for many diseases. Recent advances in mass spectrometry (MS)-based technologies open up the exciting possibility to characterize the entire Ub information network in an unbiased and global manner. While in the long term our studies will be performed in human cells, we will first characterize this network in yeast, which allows comparatively easy global proteomic measurements and protein expression manipulations. We will collect global measurements surrounding each of ~120 genes implicated as Ub-dependent enzymes (all E3 ligases, F-box proteins, DUBs). We term this the UR120 set for "ubiquitin-regulatory" genes. The collection of hundreds of global datasets requires multiplexing to sustain throughput. Specifically, in Aim 1, we will profile Ub conjugates across individual UR120 deletion strains including a panel of ten conditions where ubiquitylation plays specific roles in cellular response and regulation, thus identifying ubiquitylation events occurring in a condition-dependent manner. In Aim 2, deletions strains for the UR120 genes will be globally profiled for protein expression under the same ten conditions as in Aim 1 to detect stable and dynamic changes in protein expression. In Aim 3, we will develop a pipeline for the large-scale analysis of protein interactions specific to the Ub pathway. A library of the UR120 genes will be created with HA-tagged proteins under endogenous expression levels and their interactions identified by affinity purification (AP)-MS. The same ten conditions will be examined to learn how the UR120 interaction network responds to changes in cellular environment. We will also perform AP-MS analyses for inactive variants of ligases and dequbiquitinases to stabilize enzyme-substrate pairing. The final result of this work will be a three-pronged information network comprised of conjugate profiling, expression profiling, and physical interaction studies. From this, we will prepare a first-of-its-kind draft o a comprehensive map of all potential enzyme-substrate relationships for ligases and DUBs. By examining the UR120 set under multiple conditions directly relevant to Ub biology, we can begin to understand how different elements cooperate throughout a normal cell-cycle and in response to perturbations. These data will provide a comprehensive assessment of the protein ubiquitylation profiles and can be used to uncover enzyme-substrate relationships. Upon completion, our next step will be to create the complementary information networks for human genes.