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Active NON-SBIR/STTR RPGS NIH (US)

Mapping Protein Social Network Dynamics with Photoproximity Profiling Platforms

$3.17M USD

Funder NATIONAL INSTITUTE OF GENERAL MEDICAL SCIENCES
Recipient Organization University of Chicago
Country United States
Start Date Sep 21, 2022
End Date Aug 31, 2026
Duration 1,440 days
Number of Grantees 1
Roles Principal Investigator
Data Source NIH (US)
Grant ID 10707896
Grant Description

Project Summary The ability to sense dynamic changes in the cellular environment and translate that information into rewired biomolecular interactions forms the backbone of cellular signal transduction. Despite significant interest and investment in methods capable of detecting and quantifying protein-protein and other protein-biomolecule

interactions, the most commonly employed methods solely map interactions in non-physiologic environments outside of cells where many important factors contributing to the interactions under study are lost. These methods are particularly poorly suited to study signaling events in cells that rely on the cellular architecture and chemical

environment in order to form and function. Therefore, new methods are needed to quantitatively map protein “social networks” inside of living systems. Here we propose to develop and validate several complementary light- dependent proximity profiling platforms capable of detecting protein interaction dynamics in live cells with high

spatial and temporal resolution, as well as minimal perturbation to the cellular environment. We will accomplish this goal through three interconnected aims that are supported by preliminary data and our previously published work with an intracellular photoproximity profiling platform. First, we will synthesize and test tunable

photoproximity chemical probes to map protein complexes at nanometer scale inside of cells. In parallel, we propose to test potentially more efficient catalytic photoproximity profiling platforms for increased resolution of low abundance macromolecular complexes inside of cells. Finally, we propose to apply these platforms to study

the dynamic sensing of altered metabolic and redox stress inside cells through the integrated antioxidant and unfolded protein response pathways. These proximity profiles will enable drafting of the first quantitative, comprehensive maps of the integrated stress response in cells, which will identify points of intervention for

diseases such as cancer, aging and neurogenerative disorders. Furthermore, the methods and proximity profiles developed herein will also be widely useful to the biological community for application to diverse questions in intracellular signal transduction.

All Grantees

University of Chicago

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