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Abstract Staphylococcus aureus(S. aureus), a common foodborne pathogen, poses significant public health challenges due to its association with various infectious diseases. A key player in its pathogenicity, which is the IsdA protein, is an essential virulence factor inS. aureusinfections. In this work, we present an integrated in‐silico and experimental approach using MD simulations and surface plasmon resonance (SPR)‐based aptasensing measurements to investigateS. aureusbiorecognition via IsdA surface protein binding. SPR, a powerful real‐time and label‐free technique, was utilized to characterize interaction dynamics between the aptamer and IsdA protein, and MD simulations was used to characterize the stable and dynamic binding regions. By characterizing and optimizing pivotal parameters such as aptamer concentration and buffer conditions, we determined the aptamer's binding performance. Under optimal conditions of pH 7.4 and 150 mM NaCl concentration, the kinetic parameters were determined;k_a = 3.789 × 10⁴/Ms,k_d = 1.798 × 10³/s, andK_D = 4.745 × 10⁻⁸ M. The simulations revealed regions of interest in the IsdA‐aptamer complex. Region I, which includes interactions between amino acid residues H106 and R107 and nucleotide residues 9G, 10U, 11G and 12U of the aptamer, had the strongest interaction, based on ΔG and B‐factor values, and hence contributed the most to the stability of the interaction. Region II, which covers residue 37A reflects the dynamic nature of the interaction due to frequent contacts. The approach presents a rigorous characterization of aptamer‐IsdA binding behavior, supporting the potential application of the IsdA‐binding aptamer system forS. aureusbiosensing. 

Microbial foodborne pathogens present significant challenges to public health and the food industry, requiring rapid and accurate detection methods to prevent infections and ensure food safety. Conventional single biosensing techniques often exhibit limitations in terms of sensitivity, specificity, and rapidity. In response, there has been a growing interest in multimodal biosensing approaches that combine multiple sensing techniques to enhance the efficacy, accuracy, and precision in detecting these pathogens. This review investigates the current state of multimodal biosensing technologies and their potential applications within the food industry. Various multimodal biosensing platforms, such as opto-electrochemical, optical nanomaterial, multiple nanomaterial-based systems, hybrid biosensing microfluidics, and microfabrication techniques are discussed. The review provides an in-depth analysis of the advantages, challenges, and future prospects of multimodal biosensing for foodborne pathogens, emphasizing its transformative potential for food safety and public health. This comprehensive analysis aims to contribute to the development of innovative strategies for combating foodborne infections and ensuring the reliability of the global food supply chain.