Optimisation of a gold nanoparticle-based aptasensor integrated with image processing for the colorimetric detection of acephate using response surface methodology.

Abstract

Acephate (Ac) is an organophosphate (OP) compound, which is able to inhibit the activity of acetylcholinesterase. Thus, the aim of this study was to optimize the detection of Ac using a thiolated acephate binding aptamer-citrate capped gold nanoparticle (TABA–Cit-AuNP) sensor that also incorporated an image processing technique. The effects of independent variables, such as the incubation period of TABA–Cit-AuNPs (3–24 h) for binding TABA to Cit-AuNPs, the concentration of phosphate buffer saline (PBS) (0.001–0.01 M), the concentration of thiolated acephate binding aptamer (TABA) (50–200 nM), and the concentration of magnesium sulphate (MgSO4) (1–300 mM) were investigated. A quadratic model was developed using a central composite design (CCD) from response surface methodology (RSM) to predict the sensing response to Ac. The optimum conditions such as the concentration of PBS (0.01 M), the concentration of TABA (200 nM), the incubation period of TABA–Cit-AuNPs (3 h), and the concentration of MgSO4 (1 mM) were used to produce a TABA–Cit-AuNPs sensor for the detection of Ac. Under optimal conditions, this sensor showed a detection ranging from 0.01 to 2.73 μM and a limit of detection (LOD) of 0.06 μM. Real sample analysis demonstrated this aptasensor as a good analytical method to detect Ac.