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

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 (PyqjF) to further improve the output level. The optimized biosensor PyqjF×2-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.