CAREER: Experimentally integrated modeling of quality control during eukaryotic mRNA protein synthesis

Fred Hutchinson Cancer Center, Seattle WA

Investigators

Abstract

To grow and divide, living cells need to produce proteins rapidly. However, in cases of chemical damage or nutrient scarcity, cells use a kind of safety valve to slow the speed of protein production. This so-called quality control mechanism serves as a fail-safe to make sure that proteins are produced accurately and in the right quantities. Then, as the cellular environment becomes more favorable, the block on protein synthesis needs to be removed. Understanding how cells resume normal function is the goal of this project. Successful completion of this research will enable scientists to accurately predict the quantity of proteins that cells produce under different conditions. The research will use both computational and experimental approaches, which will provide valuable interdisciplinary training opportunities for graduate students taking part in the research. Related training will be offered through a graduate course, "Tools for Computational Biology," for first year students in the Molecular and Cellular Biology Ph.D. program run by the Fred Hutchinson Cancer Research Center and University of Washington. Participation in summer research programs will engage undergraduate interns and high school students in research related to the project goals. During the process of protein production by translation, ribosomes typically move rapidly along mRNAs while catalyzing addition of amino acids to growing peptide chains. At times, ribosomes can encounter roadblocks and stall their motion for long periods. To rescue these stalled ribosomes, cells rely on several enzymes that are collectively referred to as quality control factors. A major unresolved question in the field of translation research is how quality control factors recognize and rescue stalled ribosomes, without any adverse effect on normally translating ribosomes. Recent results have provided an important clue: efficient quality control occurs only on mRNAs with high rates of translation initiation. Using data from high resolution measurements of protein and mRNA levels in the budding yeast Saccharomyces cerevisiae, computational models have been formulated to test the hypothesis that collisions between multiple ribosomes serve as the trigger for quality control. Computational models will provide predictive information to guide experiments aimed at exploring this idea. Genetic and biochemical experiments will be used to dissect the enzymes that mediate the effect of ribosome collisions on quality control and to identify mRNAs in the cell whose translation is affected by ribosome collisions. The results will provide unprecedented insights into the mechanisms and dynamics of this important quality control process. 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.