Bionic Magnetic Nanorobots Combined with AI-Assisted Microscopic Imaging for Argonaute-Powered Multiplexed Foodborne Pathogens Detection

Multiplexed and ultrasensitive identification of foodborne pathogens is crucial for food safety. However, conventional methods are limited by complex matrices, insufficient signal conversion tools, and low sensitivity. Herein, we constructed bionic nanorobots by optimizing phenylboronic acid density on magnetic nanoparticles via polyethylene glycol linkers, achieving 92.21% Gram-positive bacteria capture within 20 min with 25 day stability. Additionally, we developed an artificial intelligence (AI)-powered microscopic imaging strategy based on polystyrene microsphere size-encoding and Clostridium butyricum Argonaute (CbAgo) decoding. The rational-designed CbAgo activates cyclic cleavage circuits for multiplexed decoding, with AI-mediated counting as readout. Without DNA amplification, the entire detection can be completed within 1.5 h, and the platform achieved dual-pathogen detection across 5 orders of magnitude (10 2 –10 6 CFU/mL), with a detection limit of 10 2 CFU/mL. Compared with quantitative polymerase chain reaction, the platform demonstrates 10-fold sensitivity improvement. Overall, this platform provides a robust tool for multiplexed pathogen detection in complex environments.