Triple-helix molecular switch-based light-addressable potentiometric aptasensor for the multi-channel highly sensitive label-free detection and spatiotemporal imaging of okadaic acid

Okadaic acid (OA) has attracted considerable attention in the fields of human health and public safety because it can cause severe virulence and is widely distributed. Therefore, it is of immediate significance to explore a novel method for highly sensitive, low-consumption, efficient, and convenient OA detection. In this study, a triple-helix molecular switch (THMS)-based light-addressable potentiometric aptasensor (LAPA) is proposed for the highly sensitive and selective label-free detection and spatiotemporal imaging of OA. In this method, a THMS containing an OA aptamer served as the recognition element, and a DNA microarray including a light-addressable potentiometric sensor was designed as the transducer. Meanwhile, poly (allylamine hydrochloride) was modified on the chip surface to enhance DNA absorption and signal detection. A detection platform was constructed to measure signals and scan spatiotemporal images. The realized biosensing system enabled the multichannel detection of OA in a linear range of 0.05-100 nM with low sample consumption, a detection limit of 0.03 nM, and a detection time of 27 min/channel and spatiotemporal imaging analysis with a resolution of 400 & mu;m2/pixel and frame duration of 3.2 min/frame. Considering the technical developing of aptamer-based THMS and micro/nano biosensor, the proposed method will provide a promising approach for label-free detection and spatiotemporal analysis of OA with high sensitivity, specificity, and detection efficiency; low sample dosage; and simple operation.

Automated summary

A novel method based on a triple-helix molecular switch (THMS)-based light-addressable potentiometric aptasensor (LAPA) is proposed for highly sensitive and selective label-free detection and spatiotemporal imaging of Okadaic acid (OA). The detection platform allows for the multichannel detection of OA with low sample consumption and a detection time of 27 min/channel, as well as spatiotemporal imaging analysis with high resolution and frame duration. This method provides a promising approach for label-free detection and spatiotemporal analysis of OA with high sensitivity, specificity, and detection efficiency; low sample dosage; and simple operation.