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基因编码生物传感器工程在定向进化中的应用。

Genetically Encoded Biosensor Engineering for Application in Directed Evolution.

机构信息

National Engineering Research Center for Cereal Fermentation and Food Biomanufacturing, Jiangnan University, 1800 Lihu Road, Wuxi, Jiangsu 214122, P.R. China.

Jiangsu Provincial Research Center for Bioactive Product Processing Technology, Jiangnan University, 1800 Lihu Road, Wuxi, Jiangsu 214122, P.R. China.

出版信息

J Microbiol Biotechnol. 2023 Oct 28;33(10):1257-1267. doi: 10.4014/jmb.2304.04031. Epub 2023 Jul 14.

Abstract

Although rational genetic engineering is nowadays the favored method for microbial strain improvement, building up mutant libraries based on directed evolution for improvement is still in many cases the better option. In this regard, the demand for precise and efficient screening methods for mutants with high performance has stimulated the development of biosensor-based high-throughput screening strategies. Genetically encoded biosensors provide powerful tools to couple the desired phenotype to a detectable signal, such as fluorescence and growth rate. Herein, we review recent advances in engineering several classes of biosensors and their applications in directed evolution. Furthermore, we compare and discuss the screening advantages and limitations of two-component biosensors, transcription-factor-based biosensors, and RNA-based biosensors. Engineering these biosensors has focused mainly on modifying the expression level or structure of the biosensor components to optimize the dynamic range, specificity, and detection range. Finally, the applications of biosensors in the evolution of proteins, metabolic pathways, and genome-scale metabolic networks are described. This review provides potential guidance in the design of biosensors and their applications in improving the bioproduction of microbial cell factories through directed evolution.

摘要

虽然理性的基因工程是现今微生物菌株改良的首选方法,但基于定向进化构建突变文库在许多情况下仍然是更好的选择。在这方面,对具有高性能的突变体进行精确和高效筛选方法的需求刺激了基于生物传感器的高通量筛选策略的发展。遗传编码的生物传感器为将所需表型与可检测信号(如荧光和生长速率)耦合提供了强大的工具。本文综述了近年来工程化几类生物传感器及其在定向进化中的应用的最新进展。此外,我们比较和讨论了基于二组分生物传感器、转录因子生物传感器和 RNA 生物传感器的筛选优势和局限性。这些生物传感器的工程设计主要集中在修饰生物传感器组件的表达水平或结构上,以优化动态范围、特异性和检测范围。最后,描述了生物传感器在蛋白质、代谢途径和基因组规模代谢网络进化中的应用。本综述为生物传感器的设计及其在通过定向进化改善微生物细胞工厂的生物生产中的应用提供了潜在的指导。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0403/10619561/6852dd35f287/jmb-33-10-1257-f1.jpg

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