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Comprehensive identification of pathogenic microbes and antimicrobial resistance genes in food products using nanopore sequencing-based metagenomics.
Lee, Annie Wing-Tung; Ng, Iain Chi-Fung; Wong, Evelyn Yin-Kwan; Wong, Ivan Tak-Fai; Sze, Rebecca Po-Po; Chan, Kit-Yu; So, Tsz-Yan; Zhang, Zhipeng; Ka-Yee Fung, Sharon; Choi-Ying Wong, Sally; Tam, Wing-Yin; Lao, Hiu-Yin; Lee, Lam-Kwong; Leung, Jake Siu-Lun; Chan, Chloe Toi-Mei; Ng, Timothy Ting-Leung; Zhang, Jiaying; Chow, Franklin Wang-Ngai; Leung, Polly Hang-Mei; Siu, Gilman Kit-Hang.
Afiliación
  • Lee AW; Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Hong Kong Special Administrative Region, China.
  • Ng IC; Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Hong Kong Special Administrative Region, China.
  • Wong EY; Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Hong Kong Special Administrative Region, China.
  • Wong IT; Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Hong Kong Special Administrative Region, China.
  • Sze RP; Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Hong Kong Special Administrative Region, China.
  • Chan KY; Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Hong Kong Special Administrative Region, China.
  • So TY; Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Hong Kong Special Administrative Region, China.
  • Zhang Z; Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Hong Kong Special Administrative Region, China.
  • Ka-Yee Fung S; Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Hong Kong Special Administrative Region, China.
  • Choi-Ying Wong S; Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Hong Kong Special Administrative Region, China.
  • Tam WY; Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Hong Kong Special Administrative Region, China.
  • Lao HY; Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Hong Kong Special Administrative Region, China.
  • Lee LK; Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Hong Kong Special Administrative Region, China.
  • Leung JS; Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Hong Kong Special Administrative Region, China.
  • Chan CT; Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Hong Kong Special Administrative Region, China.
  • Ng TT; Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Hong Kong Special Administrative Region, China.
  • Zhang J; Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Hong Kong Special Administrative Region, China.
  • Chow FW; Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Hong Kong Special Administrative Region, China.
  • Leung PH; Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Hong Kong Special Administrative Region, China.
  • Siu GK; Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Hong Kong Special Administrative Region, China. Electronic address: gilman.siu@polyu.edu.hk.
Food Microbiol ; 121: 104493, 2024 Aug.
Article en En | MEDLINE | ID: mdl-38637066
ABSTRACT
Foodborne pathogens, particularly antimicrobial-resistant (AMR) bacteria, remain a significant threat to global health. Given the limitations of conventional culture-based approaches, which are limited in scope and time-consuming, metagenomic sequencing of food products emerges as a promising solution. This method provides a fast and comprehensive way to detect the presence of pathogenic microbes and antimicrobial resistance genes (ARGs). Notably, nanopore long-read sequencing provides more accurate bacterial taxonomic classification in comparison to short-read sequencing. Here, we revealed the impact of food types and attributes (origin, retail place, and food processing methods) on microbial communities and the AMR profile using nanopore metagenomic sequencing. We analyzed a total of 260 food products, including raw meat, sashimi, and ready-to-eat (RTE) vegetables. Clostridium botulinum, Acinetobacter baumannii, and Vibrio parahaemolyticus were identified as the top three foodborne pathogens in raw meat and sashimi. Importantly, even with low pathogen abundance, higher percentages of samples containing carbapenem and cephalosporin resistance genes were identified in chicken and RTE vegetables, respectively. In parallel, our results demonstrated that fresh, peeled, and minced foods exhibited higher levels of pathogenic bacteria. In conclusion, this comprehensive study offers invaluable data that can contribute to food safety assessments and serve as a basis for quality indicators.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Secuenciación de Nanoporos / Antiinfecciosos Idioma: En Revista: Food Microbiol Asunto de la revista: CIENCIAS DA NUTRICAO / MICROBIOLOGIA Año: 2024 Tipo del documento: Article País de afiliación: China Pais de publicación: Reino Unido
Texto completo
Añadir a Mi BVS
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Secuenciación de Nanoporos / Antiinfecciosos Idioma: En Revista: Food Microbiol Asunto de la revista: CIENCIAS DA NUTRICAO / MICROBIOLOGIA Año: 2024 Tipo del documento: Article País de afiliación: China Pais de publicación: Reino Unido