Comprehensive Identification of Pathogenic Microbes and Antimicrobial Resistance Genes in Food Products Using Nanopore Sequencing-Based Metagenomics

Abstract

AbstractFoodborne pathogens, particularly antimicrobial-resistant (AMR) bacteria, remain a significant threat to global health. Conventional culture-based approaches for detecting infectious agents are limited in scope and time-consuming. Metagenomic sequencing of food products offers a rapid and comprehensive approach to detect pathogenic microbes, including AMR bacteria. In this study, we used nanopore-based metagenomic sequencing to detect pathogenic microbes and antimicrobial resistance genes (ARGs) in 260 food products, including raw meat, sashimi, and ready-to-eat (RTE) vegetables. We identifiedClostridium botulinumandStaphylococcus aureusas the predominant foodborne pathogens in the food samples, particularly prevalent in fresh, peeled, and minced foods. Importantly, RTE-vegetables, which harboredAcinetobacter baumanniiandToxoplasma gondiias the dominant foodborne pathogens, displayed the highest abundance of carbapenem resistance genes among the different food types. ExclusiveblaCTX-Mgene-carrying plasmids were found in both RTE-vegetables and sashimi. Additionally, we assessed the impact of host DNA and sequencing depth on microbial profiling and ARG detection, highlighting the preference for nanopore sequencing over Illumina for ARG detection. A lower sequencing depth of around 25,000 is adequate for effectively profiling bacteria in food samples, whereas a higher sequencing depth of approximately 700,000 is required to detect ARGs. Our workflow provides insights into the development of food safety monitoring tools and can assess the potential risk to human health from foodborne pathogens and ARGs. This approach has the potential to revolutionize the screening of food products and enable more efficient and accurate detection of foodborne pathogens and ARGs, thereby reducing the risks of foodborne illness and improving public health.