Investigations of proteome turnover kinetics under cellular differentiation

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PROJECT SUMMARY This administrative supplement application for undergraduate summer research is being submitted to PA-20-272 in accordance to NOT-GM-22-009. The scope of the parent project remains unchanged. Summary of Parent Project R35-GM146815: Proteins are in a constant flux of continuous synthesis and degradation. Both components of the protein turnover cycle contribute to protein abundance. Although this fact has been known for 80 years, currently most biological inquiries are limited to static snapshots of overall transcript and protein levels, whereas knowledge into the dynamic changes of protein turnover remains severely lagging. This ESI MIRA proposal seeks to advance the current understanding of how cellular proteomes remodel during cell state transitions, by incorporating protein turnover kinetics information at key stages of human induced pluripotent stem cell (iPSC) differentiation into distinct cellular lineages. Working with collaborators, we previously developed deuterium stable isotope labeling, mass spectrometry, and kinetic modeling methods to quantitate protein turnover in animal models and in human. In doing so, we found many novel cell states and disease markers may be discovered from integrating orthogonal protein abundance and kinetics information. In the next five years, we propose to: (1) apply these methods to acquire a high temporal density map of human iPSC trilineage differentiation into cardiomyocyte, hepatocyte, and neuroprogenitor cells; (2) interrogate the regulatory principles that govern turnover flux across different differentiation stages; and (3) assess the functional consequences of protein degradation on the success and cell maturity of terminal cell production. Finally, a limitation of current techniques is that the kinetic models used in protein turnover studies largely assume a non-changing protein pool size at steady state, which does not apply to differentiating cells or progressing diseases. We propose to expand current models of analyzing heavy water stable isotope label experiments toward dynamical systems with variable protein pool sizes. If successful, the proposed research would greatly expand the current knowledge of molecular events that take place during human iPSC differentiation, as well as generate publicly available data sets and software tools to advance protein turnover studies in diverse areas.