National Engineering Laboratory for Cereal Fermentation Technology (NELCF), Jiangnan University, 1800 Lihu Road, Wuxi, Jiangsu 214122, China.
Jiangsu Provincial Research Center for Bioactive Product Processing Technology, Jiangnan University, 1800 Lihu Road, Wuxi, Jiangsu 214122, China.
ACS Synth Biol. 2021 May 21;10(5):911-922. doi: 10.1021/acssynbio.0c00252. Epub 2021 Apr 25.
Transcription-factor-based biosensors (TFBs) are often used for metabolite detection, adaptive evolution, and metabolic flux control. However, designing TFBs with superior performance for applications in synthetic biology remains challenging. Specifically, natural TFBs often do not meet real-time detection requirements owing to their slow response times and inappropriate dynamic ranges, detection ranges, sensitivity, and selectivity. Furthermore, designing and optimizing complex dynamic regulation networks is time-consuming and labor-intensive. This Review highlights TFB-based applications and recent engineering strategies ranging from traditional trial-and-error approaches to novel computer-model-based rational design approaches. The limitations of the applications and these engineering strategies are additionally reviewed.
基于转录因子的生物传感器 (TFBs) 常用于代谢物检测、适应性进化和代谢通量控制。然而,设计具有卓越性能的 TFBs 以应用于合成生物学仍然具有挑战性。具体而言,由于响应时间慢以及动态范围、检测范围、灵敏度和选择性不合适,天然 TFBs 通常无法满足实时检测要求。此外,设计和优化复杂的动态调节网络既费时又费力。本综述重点介绍了基于 TFB 的应用以及从传统的试错方法到新型基于计算机模型的合理设计方法的最新工程策略。还审查了这些应用和工程策略的局限性。