定向进化
体细胞突变
定向分子进化
选择(遗传算法)
DNA洗牌
突变
生物进化
单元格排序
分子进化
生物
分类
计算机科学
遗传学
基因
人工智能
细胞
系统发育学
算法
B细胞
突变体
抗体
作者
Rosana S. Molina,Gordon Rix,Amanuella A. Mengiste,Beatriz Álvarez,Daeje Seo,Haiqi Chen,Juan E. Hurtado,Qiong Zhang,Jorge D. García-García,Zachary Heins,Patrick J. Almhjell,Frances H. Arnold,Ahmad S. Khalil,Andrew D. Hanson,John E. Dueber,David V. Schaffer,Fei Chen,Seokhee Kim,Luis Ángel Fernández,Matthew D. Shoulders,Chang C. Liu
标识
DOI:10.1038/s43586-022-00119-5
摘要
Directed evolution has revolutionized biomolecular engineering by applying cycles of mutation, amplification and selection to genes of interest (GOIs). However, classical directed evolution methods that rely on manually staged evolutionary cycles constrain the scale and depth of the evolutionary search that is possible. We describe genetic systems that achieve cycles of rapid mutation, amplification and selection fully inside living cells, enabling the continuous evolution of GOIs as cells grow. These systems advance the scale, evolutionary search depth, ease and overall power of directed evolution and access important new areas of protein evolution and engineering. In vivo continuous evolution is a form of directed evolution that takes advantage of cycles of rapid mutation, amplification and selection inside living cells. Molina, Rix et al. discuss best practices for designing and conducting experiments for drug discovery, enzyme engineering and fluorescence-activated cell sorting (FACS)-based evolution.
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