CNN-assisted multimodal biosensing of Staphylococcus aureus using a bimetallic MOF@MXene hybrid nanomaterial

The rapid and accurate detection of foodborne pathogenic bacteria is critical for ensuring public health and mitigating the global burden of foodborne diseases. Here, we present a multimodal sensing platform enabled by a novel bimetallic hybrid nanomaterial, Au/MOF-919/Ti 3 C 2 T X , which integrates intrinsic electrochemical properties with dual enzyme-mimetic activities. This innovative material serves as the cornerstone of a highly sensitive and selective biosensor for the detection of Staphylococcus aureus ( S. aureus ), a major foodborne pathogen. The detection mechanism leverages a catalytic hairpin assembly cascade reaction on magnetic nanoparticles, amplified by the multifunctional Au/MOF-919/Ti 3 C 2 T X , to generate electrochemical and colorimetric signals proportional to the target concentration. Convolutional neural networks were employed to classify and quantify S. aureus concentrations from captured images, enabling intelligent, real-time pathogen identification with precision. The biosensor demonstrates exceptional performance, with a broad linear detection range (10–10 8 CFU mL −1 ) and low detection limits of 5.5 CFU mL −1 (electrochemical) and 6.6 CFU mL −1 (colorimetric). Validated in complex food matrices, this platform represents a transformative advance in food safety monitoring, offering a robust, rapid, and scalable solution for pathogen detection. Its integration of nanotechnology, artificial intelligence, and multimodal sensing heralds a new era in biosensing technology, with far-reaching implications for public health and food security.