Identifying Mutations that Promote Microbial Evolvability

进化性描述了一个有机体产生后代的能力，这些后代更好地适应给定的环境。 环境提高整体点突变率的突变可以使细菌在环境中更容易进化。 在某些情况下，从而加速慢性感染的进展，并增加 抗生素耐药性发生率。目前对突变如何影响其他细胞的知之甚少。 过程影响微生物的进化性或关于进化性通常如何随着微生物 由于遗传漂变而经历随机突变或通过有益突变适应更高的适应性。 该研究系统地研究了不同类型的突变如何影响 实验室进化实验中的大肠杆菌。第一个目的是测试三个不同的菌株系列， 主要是有害的，有益的或随机的突变，以建立基线预期。第二 目的是恢复基因型，最终战胜竞争对手的更高的健身，因为他们更多的是 通过使用深度测序、高通量、 基因分型、缺失和微卫星标记。第三个目标是构建染色体 用于测量基因扩增和缺失率的选择性标记。这些记者将 用于分离新的基因组不稳定性突变体，并检查是否存在类似的缺陷， 在20年的进化实验中，加强了一种罕见的代谢创新的进化。 在整个过程中，将通过比较 标记轨迹在重复进化实验种群遗传模拟和执行 终点分离株和参考菌株之间的共培养竞争试验。当发现一种菌株， 异常高或低的进化性，因果突变将通过基因组重新测序来鉴定， 生理后果将被调查，以找出为什么它会影响进化潜力。

Evolvability describes an organism's capacity for producing descendants that are better adapted to a given environment. Mutations that elevate overall point mutation rates can make bacteria more evolvable under certain circumstances and consequently speed the progression of chronic infections and increase the incidence of antibiotic resistance. Little is currently known about how mutations affecting other cellular processes impact microbial evolvability or about how evolvability typically varies as microorganisms experience random mutations due to genetic drift or adapt by beneficial mutations to higher fitness. The proposed research systematically investigates how different kinds of mutations affect the evolvability of Escherichia coli in laboratory evolution experiments. The first aim is to test three strain series differing by predominantly deleterious, beneficial, or random mutations to establish baseline expectations. The second aim is to recover genotypes that eventually prevail over competitors of higher fitness because they are more evolvable by chronicling mutation dynamics in evolution experiments using deep sequencing, highthroughput genotyping, and deletion and microsatellite markers. The third aim is to construct chromosomal reporters with selectable markers for measuring gene amplification and deletion rates. These reporters will be used to isolate new kinds of genomic instability mutators and to examine whether a similar defect potentiated the evolution of a rare metabolic innovation in a 20-year evolution experiment. Throughout, evolvability will be measured on multiple time scales by comparing the initial divergence of marker trajectories in replicate evolution experiments to population genetic simulations and by performing co-culture competition assays between endpoint isolates and a reference strain. When a strain is found with unusually high or low evolvability, the causal mutation will be identified by genome re-sequencing, and its physiological consequences will be investigated to find out why it affects evolutionary potential.