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.

Public Health Relevance

The ubiquitin system is an intense research area with great promise for the improvement of human health. In addition to its critical role in normal physiology, malfunctions in ubiquitin biology have been implicated as a contributing factor in the causation of many diseases as diverse as diabetes, cancer, and Alzheimer's disease. This proposal will apply mass spectrometry-based technologies to systematically map the substrates of every enzyme in the yeast ubiquitin system (all ligases and deubiquitinases).

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Project (R01)
Project #
5R01GM067945-11
Application #
8641377
Study Section
Membrane Biology and Protein Processing (MBPP)
Program Officer
Gerratana, Barbara
Project Start
2003-05-15
Project End
2017-02-28
Budget Start
2014-03-01
Budget End
2015-02-28
Support Year
11
Fiscal Year
2014
Total Cost
$494,852
Indirect Cost
$202,904
Name
Harvard University
Department
Anatomy/Cell Biology
Type
Schools of Medicine
DUNS #
047006379
City
Boston
State
MA
Country
United States
Zip Code
02115
Weekes, Michael P; Tomasec, Peter; Huttlin, Edward L et al. (2014) Quantitative temporal viromics: an approach to investigate host-pathogen interaction. Cell 157:1460-72
Murphy, J Patrick; Everley, Robert A; Coloff, Jonathan L et al. (2014) Combining amine metabolomics and quantitative proteomics of cancer cells using derivatization with isobaric tags. Anal Chem 86:3585-93
McAlister, Graeme C; Nusinow, David P; Jedrychowski, Mark P et al. (2014) MultiNotch MS3 enables accurate, sensitive, and multiplexed detection of differential expression across cancer cell line proteomes. Anal Chem 86:7150-8
Chantranupong, Lynne; Wolfson, Rachel L; Orozco, Jose M et al. (2014) The Sestrins interact with GATOR2 to negatively regulate the amino-acid-sensing pathway upstream of mTORC1. Cell Rep 9:1-8
Ordureau, Alban; Sarraf, Shireen A; Duda, David M et al. (2014) Quantitative proteomics reveal a feedforward mechanism for mitochondrial PARKIN translocation and ubiquitin chain synthesis. Mol Cell 56:360-75
Goranov, Alexi I; Gulati, Amneet; Dephoure, Noah et al. (2013) Changes in cell morphology are coordinated with cell growth through the TORC1 pathway. Curr Biol 23:1269-79
Wilson-Grady, Joshua T; Haas, Wilhelm; Gygi, Steven P (2013) Quantitative comparison of the fasted and re-fed mouse liver phosphoproteomes using lower pH reductive dimethylation. Methods 61:277-86
Armour, Sean M; Bennett, Eric J; Braun, Craig R et al. (2013) A high-confidence interaction map identifies SIRT1 as a mediator of acetylation of USP22 and the SAGA coactivator complex. Mol Cell Biol 33:1487-502
Johnson, Aaron; Wu, Ronghu; Peetz, Matthew et al. (2013) Heterochromatic gene silencing by activator interference and a transcription elongation barrier. J Biol Chem 288:28771-82
McAllister, Fiona E; Gygi, Steven P (2013) Correlation profiling for determining kinase-substrate relationships. Methods 61:227-35

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