Simple and sensitive detection of pesticides using the liquid crystal droplet patterns platform

Abstract

The alignment of liquid crystal (LC) is known to be sensitive to the properties of a bounding interface. Here, we report a LC droplet pattern platform based on enzymatic event of acetylcholinesterase (AChE) for sensitive detection of pesticides. In this method, the dark cross appearances of LC droplet patterns are obtained due to the formation of myristoylcholine (Myr) monolayer at the aqueous/LC interface after transferring Myr solution, which is corresponding to the perpendicular alignment of LC molecules at the interface. On the one hand, AChE mediates the hydrolysis of Myr to disrupt the surfactant monolayer, and the process leads to the bright fan-shaped images of LC droplet patterns when in contact with the pre-incubated mixture of AChE and Myr, which is indicating a planar orientation of LCs at the interface. On the other hand, the hydrolysis of Myr is inhibited in the presence of AChE-inhibiting pesticides such as baycarb and dimethoate, as a result, the LC droplet patterns present the dark cross appearances. On the basis of the principle, the LC droplet patterns could be utilized as an effective method to detect the pesticides. The results demonstrated that the LC droplet patterns were sensitive to baycarb with a detection limit of 1ng/mL and dimethoate with a detection limit of 0.1ng/mL. The constructed LC-based sensing platform is quite simple and convenient, and shows high promise for label-free detection of pesticides with very high sensitivity.