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

为了生长和分裂，活细胞需要快速产生蛋白质。 然而，在化学损伤或营养缺乏的情况下，细胞会使用一种安全阀来减缓蛋白质生产的速度。 这种所谓的质量控制机制是一种故障安全机制，以确保蛋白质的准确生产和正确的数量。 然后，随着细胞环境变得更加有利，需要去除蛋白质合成的障碍。 了解细胞如何恢复正常功能是这个项目的目标。 这项研究的成功完成将使科学家能够准确预测细胞在不同条件下产生的蛋白质的数量。 该研究将使用计算和实验方法，这将为参与研究的研究生提供宝贵的跨学科培训机会。相关培训将通过研究生课程提供，“计算生物学工具”，为分子和细胞生物学博士的一年级学生。该项目由弗雷德哈钦森癌症研究中心和华盛顿大学联合开展。参与暑期研究项目将吸引本科实习生和高中生参与与项目目标相关的研究。在翻译蛋白质生产的过程中，核糖体通常沿着mRNA快速移动，同时催化氨基酸添加到生长的肽链中。 有时，核糖体会遇到障碍物，长时间停止运动。 为了拯救这些停滞的核糖体，细胞依赖于几种酶，这些酶统称为质量控制因子。 翻译研究领域中一个尚未解决的主要问题是质量控制因子如何识别和拯救停滞的核糖体，而不会对正常翻译的核糖体产生任何不利影响。 最近的研究结果提供了一个重要的线索：有效的质量控制只发生在翻译起始速率高的mRNA上。使用高分辨率的蛋白质和mRNA水平的测量数据，在芽殖酵母酿酒酵母，计算模型已制定测试的假设，多个核糖体之间的碰撞作为触发器的质量控制。 计算模型将提供预测信息，以指导旨在探索这一想法的实验。遗传学和生物化学实验将用于解剖介导核糖体碰撞对质量控制的影响的酶，并鉴定细胞中其翻译受核糖体碰撞影响的mRNA。 该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

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.