Zhang Yan, Zou Zhen-Ping, Chen Sheng-Yan, Wei Wen-Ping, Zhou Ying, Ye Bang-Ce
Laboratory of Biosystems and Microanalysis, Institute of Engineering Biology and Health, State Key Laboratory of Bioreactor Engineering, East China University of Science and Technology, Shanghai, 200237, China; School of Chemistry and Chemical Engineering/Key Laboratory of Environmental Monitoring and Pollutant Control of Xinjiang Bingtuan, Shihezi University, Shihezi, 832003, China.
Laboratory of Biosystems and Microanalysis, Institute of Engineering Biology and Health, State Key Laboratory of Bioreactor Engineering, East China University of Science and Technology, Shanghai, 200237, China.
Biosens Bioelectron. 2022 Jul 1;207:114205. doi: 10.1016/j.bios.2022.114205. Epub 2022 Mar 21.
The detection of mine-based explosives poses a serious threat to the lives of deminers, and carcinogenic residues may cause severe environmental pollution. Whole-cell biosensors that can detect on-site in dangerous or inaccessible environments have great potential to replace conventional methods. Synthetic biology based on engineering modularity serves as a new tool that could be used to engineer microbes to acquire desired functions through artificial design and precise regulation. In this study, we designed artificial genetic circuits in Escherichia coli MG1655 by reconstructing the transcription factor YhaJ-based system to detect explosive composition 2,4-dinitrotoluene (2,4-DNT). These genetic circuits were optimized at the transcriptional, translational, and post-translational levels. The binding affinity of the transcription factor YhaJ with inducer 2,4-DNT metabolites was enhanced via directed evolution, and several activator binding sites were inserted in sensing yqjF promoter (P) to further improve the output level. The optimized biosensor P-TEV-(mYhaJ + GFP)-Ssr had a maximum induction ratio of 189 with green fluorescent signal output, and it could perceive at least 1 μg/mL 2,4-DNT. Its effective and robust performance was verified in different water samples. Our results demonstrate the use of synthetic biology tools to systematically optimize the performance of sensors for 2,4-DNT detection, that lay the foundation for practical applications.
基于地雷的爆炸物检测对排雷人员的生命构成严重威胁,且致癌残留物可能会造成严重的环境污染。能够在危险或难以进入的环境中进行现场检测的全细胞生物传感器,在取代传统方法方面具有巨大潜力。基于工程模块化的合成生物学是一种新工具,可用于通过人工设计和精确调控对微生物进行工程改造,使其获得所需功能。在本研究中,我们通过重建基于转录因子YhaJ的系统,在大肠杆菌MG1655中设计了人工遗传电路,以检测爆炸物成分2,4-二硝基甲苯(2,4-DNT)。这些遗传电路在转录、翻译和翻译后水平上进行了优化。通过定向进化提高了转录因子YhaJ与诱导剂2,4-DNT代谢物的结合亲和力,并在传感yqjF启动子(P)中插入了几个激活剂结合位点,以进一步提高输出水平。优化后的生物传感器P-TEV-(mYhaJ + GFP)-Ssr的绿色荧光信号输出最大诱导率为189,并且能够感知至少1μg/mL的2,4-DNT。其在不同水样中的有效性和稳健性能得到了验证。我们的结果证明了利用合成生物学工具系统优化用于2,4-DNT检测的传感器性能,为实际应用奠定了基础。