4.7 Review

Modular tuning engineering and versatile applications of genetically encoded biosensors

期刊

CRITICAL REVIEWS IN BIOTECHNOLOGY
卷 42, 期 7, 页码 1010-1027

出版社

TAYLOR & FRANCIS LTD
DOI: 10.1080/07388551.2021.1982858

关键词

Genetically encoded biosensors; synthetic biology; function fine-tuning; response curve; input signal extending; output signal

资金

  1. National Key R&D Program of China [2019YFA0904900]
  2. National Natural Science Foundation of China [31730003, 31670047, 31670077]
  3. Young Scholars Program of Shandong University

向作者/读者索取更多资源

Genetically encoded biosensors have a wide range of detectable signals and potential applications, with continuous improvement in performance and functions. Strategies for tuning biosensors and expanding input signals have been summarized. Analysis of different output signals and their practical requirements in biotechnology, biomedical applications, and environmental safety provides insight for improving design and optimization of biosensors in various application scenarios.
Genetically encoded biosensors have a diverse range of detectable signals and potential applications in many fields, including metabolism control and high-throughput screening. Their ability to be used in situ with minimal interference to the bioprocess of interest could revolutionize synthetic biology and microbial cell factories. The performance and functions of these biosensors have been extensively studied and have been rapidly improved. We review here current biosensor tuning strategies and attempt to unravel how to obtain ideal biosensor functions through experimental adjustments. Strategies for expanding the biosensor input signals that increases the number of detectable compounds have also been summarized. Finally, different output signals and their practical requirements for biotechnology and biomedical applications and environmental safety concerns have been analyzed. This in-depth review of the responses and regulation mechanisms of genetically encoded biosensors will assist to improve their design and optimization in various application scenarios.

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