Journal of Microbiology and Biotechnology

The Korean Society for Microbiology and Biotechnology (한국미생물·생명공학회)
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Genetically Encoded Biosensor Engineering for Application in Directed Evolution

  • Yin Mao (National Engineering Research Center for Cereal Fermentation and Food Biomanufacturing, Jiangnan University) ;
  • Chao Huang (National Engineering Research Center for Cereal Fermentation and Food Biomanufacturing, Jiangnan University) ;
  • Xuan Zhou (National Engineering Research Center for Cereal Fermentation and Food Biomanufacturing, Jiangnan University) ;
  • Runhua Han (McKetta Department of Chemical Engineering, The University of Texas at Austin) ;
  • Yu Deng (National Engineering Research Center for Cereal Fermentation and Food Biomanufacturing, Jiangnan University) ;
  • Shenghu Zhou (National Engineering Research Center for Cereal Fermentation and Food Biomanufacturing, Jiangnan University)
  • Received : 2023.04.20
  • Accepted : 2023.06.06
  • Published : 2023.10.28
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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.

Keywords

Acknowledgement

This work was supported by the National Key R&D Program of China (2019YFA0905500), the Key R&D Project of Jiangsu Province (Modern Agriculture) (BE2022322), the Distinguished Young Scholars of Jiangsu Province (BK20220089), and the Tianjin Synthetic Biotechnology Innovation Capacity Improvement Project (TSBICIP-KJGG-015).

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