A simple, supersensitive and highly selective electrochemical aptasensor for Microcystin-LR based on synergistic signal amplification strategy with graphene, DNase I enzyme and Au nanoparticles

As cyanobacteria with high potential hepatotoxicity, Microcystin-LR (MC-LR) in water sample is highly concerned, but is very hard to directly detect by convenient electrochemistry technique due to its lack of electrochemical activity. In this work, an effective signal-on electrochemical aptasensing platform towards MC-LR has been proposed by designing a synergistic signal amplification system subtly and simply controlled by graphene bi-functional assembly. MC-LR binding aptamers were combined onto graphene surface, obtaining aptamer-graphene complex, and used as recognition element. Au nanoparticles (NPs) were modified onto Au electrode (Au NPs/Au) to act as the probe substrate. When it was functionalized by alkylate thiol, the electron transfer (eT) on Au NPs/Au could be greatly blocked, which could only be recovered by free graphene, while not by aptamer-graphene complex. According to this property, graphene was herein used bi-functionally, serving as not only the binder to recognition element, aptamer, by pi-pi stacking, but also the eT tunnel regulator to give a concentration-dependent response turn-on signal to MC-LR. DNase I enzyme, which can selective cleavage the aptamers bound with MC-LR, was simultaneously added to the system to release MC-LR and to give additional target recycling signal amplification. At the optimized condition, the dose-response curve of MC-LR and the current signal was established with a wide linear range of 1.0-100 pM, and a low detection limit of 0.8 pM, better than many reported literature. Moreover, this aptasensor system shows good selectivity towards MC-LR in the presence of 100-fold other contaminants. The potential sensing principle and recognition mechanism were discussed. A promising and convenient monitoring platform for MC-LR and other organic pollutants has thus been provided. (c) 2018 Elsevier Ltd. All rights reserved.