大肠杆菌
计算生物学
小分子
基因
生物
定向分子进化
基因组
诱导剂
合成生物学
克隆(编程)
定向进化
遗传学
计算机科学
突变体
程序设计语言
作者
Adam J. Meyer,Thomas H. Segall-Shapiro,Emerson Glassey,Jing Zhang,Christopher A. Voigt
标识
DOI:10.1038/s41589-018-0168-3
摘要
Cellular processes are carried out by many genes, and their study and optimization requires multiple levers by which they can be independently controlled. The most common method is via a genetically encoded sensor that responds to a small molecule. However, these sensors are often suboptimal, exhibiting high background expression and low dynamic range. Further, using multiple sensors in one cell is limited by cross-talk and the taxing of cellular resources. Here, we have developed a directed evolution strategy to simultaneously select for lower background, high dynamic range, increased sensitivity, and low cross-talk. This is applied to generate a set of 12 high-performance sensors that exhibit >100-fold induction with low background and cross-reactivity. These are combined to build a single “sensor array” in the genomes of E. coli MG1655 (wild-type), DH10B (cloning), and BL21 (protein expression). These “Marionette” strains allow for the independent control of gene expression using 12 small-molecule inducers. A directed evolution approach was applied to optimize a set of 12 small-molecule-responsive biosensors, which led to the engineering of “Marionette” strains of Escherichia coli incorporating these sensors for biotechnological applications.
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