化学
生物传感器
有机磷
纳米技术
检出限
基质(水族馆)
信号(编程语言)
生物分子
电化学
碳纳米管
组合化学
分析物
作者
Zachary T. Johnson,Scott A. Trammell,Joyce C. Breger,Jeffrey S. Erickson,Meghna Thakur,Igor L. Medintz,David A. Stenger
标识
DOI:10.1021/acs.analchem.5c04795
摘要
Exposure to organophosphates poses a threat to aquatic ecosystems and the public due to their acute toxicity. The dangers caused by organophosphates motivate the development of technologies for prompt detection. Therefore, engineering a portable and compact device that can monitor organophosphate vapors is vital. Electrochemical biosensors present a unique solution for rapid and selective detection of organophosphates, as these sensors are small and sense in real-time. Herein, this study investigates a dual-modal electrochemical system for the detection of dimethyl methylphosphonate (DMMP), a model organophosphate. The enzymes phosphotriesterase (PTE) and acetylcholinesterase (AChE) were chosen for detecting DMMP vapors, as these enzymes chemically engage with the target substrate and produce electrochemically measurable signals. These reaction-specific signals can be read using open circuit potentiometry and amperometry, which produce a turn-on/turn-off signal readout. The turn-on/turn-off signal readout demonstrates the dual-modal mechanism and serves as a complementary verification, thus circumventing the propensity for false positives typically associated with AChE-functionalized biosensors. Deep eutectic solvent films (∼20 μL) compatible with each enzyme were developed to achieve a truly field-deployable device that does not dry out during operation. The PTE- and AChE-modified biosensors yielded detection limits of 17.6 ± 8.7 and 2.5 ± 0.6 ppm, respectively. The dual-sensing device was further validated against a broader range of organophosphates, demonstrating the device's utility as a functional organophosphate sensor. A dual-modal biosensing system presents a unique approach for organophosphate vapor mapping, which results in proper agricultural stewardship.
科研通智能强力驱动
Strongly Powered by AbleSci AI