State Key Laboratory on Integrated Optoelectronics, Jilin Key Laboratory on Advanced Gas Sensor, College of Electronic Science and Engineering, Jilin University, Changchun 130012, People's Republic of China.
J Mater Chem B. 2019 Feb 28;7(8):1230-1237. doi: 10.1039/c8tb02987c. Epub 2019 Jan 28.
Point-of-care monitoring of acetylcholinesterase (AChE) is of significant importance for pesticide poisoning and disease diagnosis because it plays a pivotal role in biological nerve conduction systems. Herein, we designed a colorimetric strategy for the facile and accurate detection of AChE based on tandem catalysis with a multi-enzyme system, which is constituted by cobalt oxyhydroxide nanoflakes (CoOOH NFs) and choline oxidase (CHO). In this sensor, AChE catalytically hydrolyzed acetylcholine (ACh) to produce choline, which was further efficiently oxidized by CHO to yield HO. CoOOH NFs, as a nanozyme, efficiently catalyzed 3,3',5,5'-tetramethylbenzidine (TMB) into blue oxTMB with the help of HO, accompanied by an enhancement of absorbance intensity. The resulting intensity could be employed as the signal output of the CHO/CoOOH/ACh system in monitoring AChE. Under optimal conditions, the developed sensor possessed a sensitive response to AChE with a detection limit of 33 μU mL. Interestingly, the proposed platform was applied to fabricate a paper-based sensor for rapidly recognizing AChE by direct observation with the naked eyes. Combined with a smartphone and ImageJ software, we further developed an image-processing algorithm for the quantitative detection of AChE with highly promising results, which validated the outstanding potential of on-site application in clinical diagnostics and pesticide poisoning.
基于多酶体系的串联催化作用,我们设计了一种简便、准确检测乙酰胆碱酯酶(AChE)的比色策略,该体系由氢氧化钴纳米片(CoOOH NFs)和胆碱氧化酶(CHO)组成。在该传感器中,AChE 催化乙酰胆碱(ACh)水解生成胆碱,然后 CHO 进一步将其高效氧化生成 HO。CoOOH NFs 作为一种纳米酶,在 HO 的帮助下高效催化 3,3',5,5'-四甲基联苯胺(TMB)生成蓝色的 oxTMB,同时伴随着吸光度强度的增强。所得强度可作为 CHO/CoOOH/ACh 体系监测 AChE 的信号输出。在最佳条件下,所开发的传感器对 AChE 具有灵敏的响应,检测限低至 33 μU mL。有趣的是,该平台被应用于制备一种纸基传感器,通过肉眼直接观察快速识别 AChE。结合智能手机和 ImageJ 软件,我们进一步开发了一种用于 AChE 定量检测的图像处理算法,取得了非常有前景的结果,验证了其在临床诊断和农药中毒现场应用的巨大潜力。