Emergent Protein Assemblies in Cytoplasm

University Of Washington, Seattle WA

Investigators

Abstract

Proteins are the work horses inside a cell by participating all aspects of cellular function. They function through the formation of higher-order assemblies facilitated by the interactions with one another. One of the functions they perform is metabolism. This is a process where protein enzymes collectively break down large nutrients such as carbohydrates into smaller molecules, turning them into biofuels or building blocks of other biomass in a cell. This project will study how these enzymes assemble into complexes that regulate or are regulated by metabolism. The knowledge learned from this project will enable far-reaching impacts on the efficient production of biofuels or biomass that benefits the bioeconomy. This project will actively recruit the transfer and continuing students from the community colleges to participate in research at the University of Washington at Seattle (UW) through collaboration with the Pacific Northwest Louise-Stokes Alliance for Minority Participation (PNW LSAMP). The transfer and continuing undergraduate students at UW are derived prominently from the historically under-represented marginalized (URM) groups in Science, Technology, Engineering, and Mathematics (STEM). The broader impact from this program will bolster the retention of transfer and continuing students in STEM higher education and augment the number of URM students going into graduate programs. The goal of this project is to establish testable models of protein assemblies in response to metabolic changes in a cell. Sequential protein enzymes form transient supramolecular assemblies, or metabolons, in a metabolic pathway within living cells. We will elucidate the physical mechanism responsible for their assembly into spatial networks, and how these complexes regulate or are regulated by metabolism with computer simulations. This work will build on an advanced theoretical framework to characterize the rapid formation and disassembly of molecular clusters in a crowded, open multicomponent system, with quantitative variables learned from experimental data and protein structural models. The expected outcome will provide novel opportunities to develop empirically testable hypotheses derived from complex molecular models as biomarkers to predict a cell's metabolic state. The long-term goal of the research program aligns with one of the ten big ideas from the NSF on Understanding the Rule of Life. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.