文献类型：期刊文献

英文题名：Design and optimization of E. coli artificial genetic circuits for detection of explosive composition 2,4-dinitrotoluene

作者：Zhang, Yan[1,2];Zou, Zhen-Ping[1];Chen, Sheng-Yan[2];Wei, Wen-Ping[3];Zhou, Ying[1];Ye, Bang-Ce[1,2,3,4]

机构：[1]East China Univ Sci & Technol, Inst Engn Biol & Hlth, Lab Biosyst & Microanal, State Key Lab Bioreactor Engn, Shanghai 200237, Peoples R China;[2]Shihezi Univ, Sch Chem & Chem Engn, Key Lab Environm Monitoring & Pollutant Control Xi, Shihezi 832003, Peoples R China;[3]Zhejiang Univ Technol, Inst Engn Biol & Hlth, Coll Pharmaceut Sci, Collaborat Innovat Ctr Yangtze River Delta Reg Gre, Hangzhou 310014, Zhejiang, Peoples R China;[4]East China Univ Sci & Technol, Inst Engn Biol & Hlth, State Key Lab Bioreactor Engn, Lab Biosyst & Microanal, Shanghai 200237, Peoples R China

年份：2022

卷号：207

外文期刊名：BIOSENSORS & BIOELECTRONICS

收录：;EI(收录号：20221311836642);WOS:【SCI-EXPANDED(收录号:WOS:000789665800004)】；

基金：Acknowledgements This wok was sponsored by the National Natural Science Foundation of China (22134003) and the National Key Research and Development Program of China (2020YFA0908800)

语种：英文

外文关键词：Whole-cell biosensor; Genetic circuit; 2,4-Dinitrotoluene; Explosives; Synthetic biology

摘要：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 2,4dinitrotoluene (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 (PyqjF) to further improve the output level. The optimized biosensor P-yqjFx2-TEV-(mYhaJ + GFP)-Ssr had a maximum induction ratio of 189 with green fluorescent signal output, and it could perceive at least 1 mu g/mL 2,4DNT. 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.