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

作者：Annie Wing-Tung Lee, Iain Chi-Fung Ng, Evelyn Yin-Kwan Wong, Ivan Tak-Fai Wong, Rebecca Po-Po Sze, Kit-Yu Chan, Tsz-Yan So, Zhipeng Zhang, Sharon Ka-Yee Fung, Sally Choi-Ying Wong, Wing-Yin Tam, Hiu-Yin Lao, Lam-Kwong Lee, Jake Siu-Lun Leung, Chloe Toi-Mei Chan, Timothy Ting-Leung Ng, Franklin Wang‐Ngai Chow, Polly H. M. Leung, G. G. Siu · 发表于：bioRxiv (Cold Spring Harbor Laboratory) · 年份：2023 · DOI：10.1101/2023.10.15.562131 · 被引用次数：1 · 研究领域：Genomics and Phylogenetic Studies、Bacteriophages and microbial interactions、Bacterial Identification and Susceptibility Testing

Abstract Foodborne 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 identified Clostridium botulinum and Staphylococcus aureus as the predominant foodborne pathogens in the food samples, particularly prevalent in fresh, peeled, and minced foods. Importantly, RTE-vegetables, which harbored Acinetobacter baumannii and Toxoplasma gondii as the dominant foodborne pathogens, displayed the highest abundance of carbapenem resistance genes among the different food types. Exclusive bla CTX-M gene-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...