(From the grant associated with this supplement request R35GM119536) Cells continuously sense, integrate, and process environmental parameters to inform physiological outcomes, (e.g. how to utilize glucose or whether to enter mitosis). Protein phosphorylation is the most extensively studied mechanism by which cells rapidly sense signals and execute decisions. Summarizing these events with simple models has proved a valuable way for investigators to conceptualize signaling pathways and formulate new hypotheses. However, without discovery experiments it is difficult to ascertain comprehensive models. Models missing key components lead to misdirected hypotheses, and thus present a major barrier to understanding cellular decisions. More than one hundred thousand mammalian phosphorylation sites have been described to date, but systematic quantitative data on their regulation by relevant signaling pathways within individual cell-types remains scarce. This type of data is necessary to build predictive models and to understand what goes wrong in complex scenarios like insulin resistance or cancer. In the short term we will develop and use mass spectrometry-based phosphoproteomics to systematically interrogate the signaling network and reveal the design principles of signal integration. This knowledge will be crucial to understanding why different cell types respond differently to the same stimuli to accomplish different functions. We will also focus on providing a functional context to novel phosphorylation sites we discovered on ubiquitin, and that connect phosphorylation-driven signaling to signaling mediated by ubiquitin. In the long term, we shall be able to predict cellular behavior from measuring a relevant set of phosphorylation events. For example we will be able to predict how cancer cells respond to a particular drug. Furthermore, we will have detailed knowledge of the signaling nodes that are suitable for intervention in disease conditions, reverting the malignant phenotype without inferring with other cellular functions. Finally, we will be able to program cellular phenotypes, for example increasing the production of a particular metabolite, or modulating migratory ability.
This research will provide signal integration modules, critical signaling hubs, and quantitative input/output maps of the cell, which will allow achieving control of the cellular communication system. This will be relevant in combating diseases where signaling malfunctions, including cancer, metabolic, neurological and infectious diseases.
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