Open AccessPhotoproximity Profiling of Protein–Protein Interactions in Cells
Author(s) -
David C. McCutcheon,
Gihoon Lee,
Anthony J. Carlos,
Jeffrey E. Montgomery,
Raymond E. Moellering
Publication year - 2019
Publication title -
journal of the american chemical society
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 7.115
H-Index - 612
eISSN - 1520-5126
pISSN - 0002-7863
DOI - 10.1021/jacs.9b06528
Subject(s) - diazirine , bioorthogonal chemistry , chemistry , protein–protein interaction , protein aggregation , cleave , biophysics , linker , biochemistry , microbiology and biotechnology , computational biology , click chemistry , combinatorial chemistry , enzyme , computer science , biology , operating system
We report a novel photoproximity protein interaction (PhotoPPI) profiling method to map protein-protein interactions in vitro and in live cells. This approach utilizes a bioorthogonal, multifunctional chemical probe that can be targeted to a genetically encoded protein of interest (POI) through a modular SNAP-Tag/benzylguanine covalent interaction. A first generation photoproximity probe, PP1, responds to 365 nm light to simultaneously cleave a central nitroveratryl linker and a peripheral diazirine group, resulting in diffusion of a highly reactive carbene nucleophile away from the POI. We demonstrate facile probe loading, and subsequent interaction- and light-dependent proximal labeling of a model protein-protein interaction (PPI) in vitro. Integration of the PhotoPPI workflow with quantitative LC-MS/MS enabled unbiased interaction mapping for the redox regulated sensor protein, KEAP1, for the first time in live cells. We validated known and novel interactions between KEAP1 and the proteins PGAM5 and HK2, among others, under basal cellular conditions. By contrast, comparison of PhotoPPI profiles in cells experiencing metabolic or redox stress confirmed that KEAP1 sheds many basal interactions and becomes associated with known lysosomal trafficking and proteolytic proteins like SQSTM1, CTSD, and LGMN. Together, these data establish PhotoPPI as a method capable of tracking the dynamic subcellular and protein interaction "social network" of a redox-sensitive protein in cells with high temporal resolution.