Characterizing the Co-evolution of Protein-protein and Regulatory Interactions

 描述（由申请人提供）：进化过程从根本上由蛋白质、DNA和其他生物分子的物理化学性质塑造：许多生物物理和生物化学机制将DNA突变与细胞的生存和繁殖能力联系起来。关于随机突变如何影响这些分子特性并最终塑造种群的进化命运，人们知之甚少。这些知识对于预测或控制细菌抗生素耐药性的演变尤为重要。的复杂性 结合相互作用和基因调控表明，单一蛋白质的突变可能对整个细胞产生深远的影响。该项目的目标是确定突变如何影响这些分子相互作用以及由此产生的细菌进化后果。使用理论和实验方法相结合，它测试的假设，蛋白质-蛋白质和调节相互作用的演变迅速和可预测的突变扰动的响应，而特定的补偿突变，针对个别蛋白质性状，如折叠稳定性，并在较长的时间内演变。该项目将首先开发一个多尺度模型，将蛋白质折叠，结合和调节的生化动力学与选择，突变和遗传漂变的进化动力学相结合。该模型的计算模拟将进行实验预测。然后，该项目将通过实验进化E。大肠杆菌的突变型二氢叶酸还原酶（DHFR），一种必需的代谢酶。进化种群的全基因组测序和表型分析将允许将实验与理论预测进行比较。这个项目将大大增加我们对突变如何影响细胞中分子相互作用的理解，以及这如何塑造进化结果。

 DESCRIPTION (provided by applicant): Evolutionary processes are fundamentally shaped by the physico-chemical properties of proteins, DNA, and other biomolecules: many layers of biophysical and biochemical mechanisms connect a DNA mutation to a cell's ability to survive and reproduce. Little is known about how random mutations affect these molecular properties and ultimately shape the evolutionary fate of a population. This knowledge is particularly crucial for predicting or controlling the evolution of antibiotic resistance in bacteria. The complexity of binding interactions and gene regulation suggests that a mutation to a single protein may have far-reaching effects throughout the cell. The goal of this project is to determine how mutations affect these molecular interactions and the resulting consequences for evolution in bacteria. Using a combination of theoretical and experimental approaches, it tests the hypothesis that protein-protein and regulatory interactions evolve rapidly and predictably in response to a mutational perturbation, while specific compensatory mutations that target individual protein traits, such as folding stability, and evolve over longer times. The project will first develop a multi-scale model that combines the biochemical kinetics of protein folding, binding, and regulation with the evolutionary dynamics of selection, mutation, and genetic drift. Computational simulations of the model will make experimental predictions. The project will then test these predictions by experimentally evolving E. coli with mutant dihydrofolate reductase (DHFR), an essential metabolic enzyme. Whole-genome sequencing and phenotyping of the evolved populations will allow comparison of the experiments with the theoretical predictions. This project will substantially increase our understanding of how mutations affect molecular interactions in cells, and how this shapes evolutionary outcomes.