Three-Dimensional Microsphere Sensing Based on Oil-Immersion Microscopy and Computer Vision for DNA Extraction-Free and Multiplexed Detection of Foodborne Pathogens.

Abstract

Sensitive, rapid, and multiplexed detection of foodborne pathogens is critical for ensuring food safety, given the prevalence of multipathogen contamination in foods. Herein, we developed a polystyrene (PS) microsphere-enabled three-dimensional (color/size/number) sensing strategy and further established an oil-immersion microscopy and computer vision-integrated imaging biosensor for multiplexed detection of foodborne pathogens. This method employed differentially colored and sized microspheres as signal probes for pathogen encoding. By the integration of aptamer-binding reactions with the computer vision algorithm-based decode and counting process, the number of PS probes was correlated with the corresponding pathogen concentration. Meanwhile, the oil-immersion imaging system significantly enhanced microsphere image clarity and resolution, reducing method dependence on algorithmic and instrumental performance while improving applicability. This biosensor enables the simultaneous detection of multiple foodborne pathogens (e.g., Salmonella, Listeria monocytogenes, and Staphylococcus aureus) within 50 min at detection limits below 100 CFU/mL without DNA extraction, providing an intelligent platform for food safety assurance.