Thermal proximity coaggregation for system-wide profiling of protein complex dynamics in cells

Taking the heat together Many of the processes in living cells are mediated by protein complexes that dynamically assemble and dissociate depending on cellular needs. Tan et al. developed a method called thermal proximity coaggregation (TPCA) to monitor the dynamics of native protein complexes inside cells (see the Perspective by Li et al.). The method is based on the idea that proteins within a complex will coaggregate upon heat denaturation. It uses a previously described cellular shift assay to determine melting curves for thousands of proteins and assigns a TPCA signature on the basis of similarity between the curves. The method was validated by detection of many known protein complexes. It identified cell-specific interactions in six cell lines, highlighting the potential for identifying protein complexes that are modulated by disease. Science, this issue p. 1170; see also p. 1105 A readily deployable approach for system-wide intracellular studies of protein complex dynamics in nonengineered cells and tissues is discussed. Proteins differentially interact with each other across cellular states and conditions, but an efficient proteome-wide strategy to monitor them is lacking. We report the application of thermal proximity coaggregation (TPCA) for high-throughput intracellular monitoring of protein complex dynamics. Significant TPCA signatures observed among well-validated protein-protein interactions correlate positively with interaction stoichiometry and are statistically observable in more than 350 annotated human protein complexes. Using TPCA, we identified many complexes without detectable differential protein expression, including chromatin-associated complexes, modulated in S phase of the cell cycle. Comparison of six cell lines by TPCA revealed cell-specific interactions even in fundamental cellular processes. TPCA constitutes an approach for system-wide studies of protein complexes in nonengineered cells and tissues and might be used to identify protein complexes that are modulated in diseases.

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