College of Biotechnology, Tianjin University of Science and Technology, Tianjin 300457, China.
Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin 300308, China.
ACS Synth Biol. 2023 Jun 16;12(6):1761-1771. doi: 10.1021/acssynbio.3c00059. Epub 2023 May 17.
Genetically encoded biosensors are powerful tools for product-driven high-throughput screening in synthetic biology and metabolic engineering. However, most biosensors can only properly function in a limited concentration cutoff, and the incompatible performance characteristics of biosensors will lead to false positives or failure in screening. The transcription factor (TF)-based biosensors are usually organized in modular architecture and function in a regulator-depended manner, whose performance properties can be fine-tuned by modifying the expression level of the TF. In this study, we modulated the performance characteristics, including sensitivity and operating range, of an MphR-based erythromycin biosensor by fine-adjusting regulator expression levels via ribosome-binding site (RBS) engineering and obtained a panel of biosensors with varied sensitivities by iterative fluorescence-assisted cell sorting (FACS) in to accommodate different screening purposes. To exemplify their application potential, two engineered biosensors with 10-fold different sensitivities were employed in the precise high-throughput screening by microfluidic-based fluorescence-activated droplet sorting (FADS) of mutant libraries with different starting erythromycin productions, and mutants representing as high as 6.8 folds and over 100% of production improvements were obtained starting from the wild-type strain and the high-producing industrial strain, respectively. This work demonstrated a simple strategy to engineer biosensor performance properties, which was significant to stepwise strain engineering and production improvement.
基因编码生物传感器是合成生物学和代谢工程中用于产品驱动的高通量筛选的强大工具。然而,大多数生物传感器只能在有限的浓度截止值下正常工作,而生物传感器的不兼容性能特征会导致筛选中的假阳性或失败。基于转录因子 (TF) 的生物传感器通常采用模块化架构组织,并以依赖调节剂的方式发挥作用,其性能特征可以通过修饰 TF 的表达水平来进行微调。在这项研究中,我们通过核糖体结合位点 (RBS) 工程精细调节调节剂表达水平,从而调节基于 MphR 的红霉素生物传感器的性能特征,包括灵敏度和工作范围,并通过迭代荧光辅助细胞分选 (FACS) 获得了一系列具有不同灵敏度的生物传感器,以适应不同的筛选目的。为了举例说明它们的应用潜力,我们在基于微流控的荧光激活液滴分选 (FADS) 的精确高通量筛选中,使用了两个灵敏度差异 10 倍的工程生物传感器,对具有不同起始红霉素产量的 突变文库进行了筛选,分别从野生型菌株和高产量的工业菌株中获得了高达 6.8 倍和超过 100%的产量提高的突变体。这项工作展示了一种简单的生物传感器性能设计策略,对于逐步的菌株工程和产量提高具有重要意义。