Artificial intelligence-enabled microsphere imaging immunosensor based on magnetic metal-organic frameworks-assisted sample pretreatment for detecting aflatoxin B1 in peanuts
Yongzhen Dong, Meijie Ren, Jia Tu, Yiping Chen
Abstract
Sensitive and rapid detection of aflatoxin B 1 (AFB 1 ) is vital for safeguarding food safety, considering its potent carcinogenic toxicity. Herein, an artificial intelligence-enabled microsphere imaging (AI-MI) immunosensor based on magnetic metal-organic frameworks-assisted sample pretreatment was developed for detecting AFB 1 in peanuts. In this work, Fe 3 O 4 @MIL-101(Fe) served as a magnetic adsorbent to efficiently enrich AFB 1 . Based on the competitive immunoreaction, the enriched AFB 1 modulated the amount of horseradish peroxidase (HRP)-labeled goat anti-mouse antibody conjugated on the polystyrene (PS) immuno-microsphere. The HRP can catalyze the rapid formation of polydopamine on the surface of the PS microsphere with additional hydrogen peroxide . Due to the abundant functional groups, the polydopamine coating could adsorb amino-functionalized magnetic nanoparticles to form PS probes. The PS probes were magnetically separated, visualized with an optical microscope, and counted using a computer vision algorithm. Finally, the changes in the number of PS probes were correlated with the amount of AFB 1 . Under optimized conditions, Fe 3 O 4 @MIL-101(Fe) exhibited remarkable enrichment capacity (1.59 mg/g), and the AI-MI immunosensor showed a high sensitivity (4.90 pg/mL, 19-fold improvement over enzyme-linked immunosorbent assay) and a wide linear range (from 0.01 to 500 ng/mL) for AFB 1 . This AI-MI immunosensor holds significant promise for intelligent detection of trace toxins.