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In order to prevent frequent outbreaks of foodborne pathogens, accurate pathogen monitoring throughout the food supply chain is essential. In this study, we will develop an accurate, cost effective, user-friendly, and, most importantly, rapid pathogen detection system for simultaneous identification of multiple foodborne bacterial pathogens. The proposed magnetoelastic particle (MEP) biosensors are composed of nanobiomolecular recognition elements (phage-displayed oligopeptide probes) and magnetostrictive particle platforms. We have previously demonstrated the efficacy of our nanobiomolecular elements coated MEP biosensors for accurate and rapid detection of individual pathogens. In this study, we will develop a multiplex system capable of detecting the presence of several common foodborne bacterial pathogens including Salmonella enterica, Escherichia coli O157:H7, Clostridium perfringens, and Campylobacter jejuni in less than 20 minutes, including the sample preparation. We will achieve our goal via three Specific Aims:1. Construct singleplex MEP biosensors for rapid detection of common foodborne bacterial pathogens.2. Further improve MEP biosensors for multiplexing3. Demonstrate the efficacy of the multiplex MEP biosensors on various food items including meats, vegetables, fruits, and liquids. Success of the proposed research will yield a prototype multiplex biosensor that is highly accurate and can be used by anyone involved in food industry from farmers to food processors to consumers.
As demonstrated by frequent announcements of foodborne pathogen outbreaks and recalls of contaminated foods, we need better pathogen detection systems for identifying contaminated foods before they can be distributed for consumption by the unsuspecting public. The current systems are inadequate to be used by nonprofessionals for real-time pathogen detection because they require long time (hours to days and weeks), expensive instruments, and extensive training of the personnel. The detection system we propose to develop in this study requires only a few minutes, inexpensive, and require very little training to be adapted and used by anyone involved in food industry. In this study, we propose to develop a system for simultaneous detection of several most common foodborne bacterial pathogens. However, as we improve our system in future studies, it can be expanded to include viruses and toxins to become a comprehensive detection system for any foodborne pathogens to improve public safety.