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Identification of risk factors and hotspots of antibiotic resistance along the food chain using next‐generation sequencing

机译:使用下一代测序鉴定沿食物链抗生素抗性的危险因素和热点

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摘要

Bacterial antimicrobial resistance (AMR) is considered to be very alarming following an upward trend and thus posing a primary threat to public health. AMR has tremendous adverse effects on humans, farm animals, healthcare, the environment, agriculture and, thus, on national economies. Several tools have been proposed and adopted by numerous countries after comprehending the need for antimicrobial stewardship and for a rational use of antibiotics. These tools include diagnostics for infections or AMR detection, for measuring and monitoring antibiotic consumption (e.g. surveillance tools) and for guiding medical doctors and veterinarians in selecting suitable antibiotics. In addition, it has been known that the food chain represents a leading vector for the transmission of pathogens to humans via various routes (direct or indirect). Considerable efforts have been made and are still in progress both at international and national levels in order to control and mitigate the spread of pathogens and thus ensure food safety. During the last decades, a new concern has risen regarding the food chain playing a potential major role in the transmission of resistant bacteria as well as resistance genes from the animal kingdom to humans. Several recent studies highlight the role of food processing environments as potential AMR hotspots contributing to this spread phenomenon. Next‐generation sequencing (NGS) technologies are becoming broadly used in the AMR field, since they allow the surveillance of resistant microorganisms, AMR determinants and mobile genetic elements. Moreover, NGS is capable of providing information on the mechanisms driving and spreading AMR throughout the food chain. In the current work programme, the aim was to acquire knowledge and skills to track AMR genes and mobile genetic elements in the food chain through NGS methodologies in order to implement a quantitative risk assessment and identify hotspots and routes of transmission of AMR along the food chain.

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