特质
对偶(语法数字)
选择(遗传算法)
生物
遗传学
酵母
计算生物学
进化生物学
计算机科学
人工智能
艺术
文学类
程序设计语言
作者
Kevin B. Reed,Wantae Kim,Hongyuan Lu,Clayton T. Larue,Shirley X. Guo,Sierra M. Brooks,Michael R. Montez,J Wagner,Yan Zhang,Hal S. Alper
标识
DOI:10.1073/pnas.2317027121
摘要
The enzyme 5-enolpyruvylshikimate-3-phosphate synthase (EPSPS) functions in the shikimate pathway which is responsible for the production of aromatic amino acids and precursors of other essential secondary metabolites in all plant species. EPSPS is also the molecular target of the herbicide glyphosate. While some plant EPSPS variants have been characterized with reduced glyphosate sensitivity and have been used in biotechnology, the glyphosate insensitivity typically comes with a cost to catalytic efficiency. Thus, there exists a need to generate additional EPSPS variants that maintain both high catalytic efficiency and high glyphosate tolerance. Here, we create a synthetic yeast system to rapidly study and evolve heterologous EPSP synthases for these dual traits. Using known EPSPS variants, we first validate that our synthetic yeast system is capable of recapitulating growth characteristics observed in plants grown in varying levels of glyphosate. Next, we demonstrate that variants from mutagenesis libraries with distinct phenotypic traits can be isolated depending on the selection criteria applied. By applying strong dual-trait selection pressure, we identify a notable EPSPS mutant after just a single round of evolution that displays robust glyphosate tolerance (K
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