Supplementary file 1_Electrostatically driven fluorescent sensor for rapid detection of AChE activity and organophosphate pesticides via dual-enzyme cascade amplification.docx

IntroductionThe widespread use of organophosphorus pesticides (OPs) in Chinese herbal medicines cultivation raises urgent concerns about residue contamination. Conventional detection methods [e.g., gas chromatography-mass spectrometry (GC-MS) and enzyme-linked immunosorbent assay (ELISA)] suffer from poor portability and instability of antibody inactivation in complex matrices, hindering on-site analysis.
MethodsThis study proposed a novel “electrostatic adsorption-driven cascade reaction chain” strategy for rapid detection of acetylcholinesterase (AChE) activity and OPs. Leveraging the electrostatic self-assembly between a positively charged acetylcholine chloride (ACh, 26.47 ± 1.63 mV) and a negatively charged choline oxidase (CHO, −30.81 ± 1.85 mV), a nanoscale fluorescence sensor (CA-B NPs) was constructed by encapsulating the Azo-Bodipy 685. This design created a spatially confined and componentially co-localized nanoreactor that restricted substrate diffusion distance to the nanoscale and utilized a dual-enzyme cascade system (AChE-CHO) to yield a signal amplification effect.
ResultsThe obtained CA-B NPs exhibited excellent analytical performance, including: (1) a low detection limit of 4.1 ng/mL for triazophos; (2) high recovery of 88.13%−113.09% in complex Citrus reticulata Blanco matrices, along with strong anti-interference capabilities by organically dividing the reaction and detection sections; (3) a total assay time of only 20 min for real samples, suitable for rapid, on-site, high-throughput screening.
DiscussionThis study not only embedded the entire reaction chain [AChE-CHO-hydrogen peroxide (H2O2)] into the sensor to improve space utilization efficiency and detection efficiency, but also established a novel paradigm for enzyme spatial organization based on electrostatic complementarity, providing new insights into the rational design of nanostructured multi-enzyme sensing platforms.