Tracking Foodborne Pathogens and Antimicrobial Resistance

Dear Colleagues,

Foodborne pathogens have been a problem for all human societies. Although standards in food treatment and production have improved in many countries, they still remain a global problem according to the World Health Organization (WHO). The WHO estimates that there are 31 types of foodborne infections that result in 600 million illnesses annually and more than 400,000 deaths. Foodborne illnesses are caused by the transmission of infectious agents (e.g., bacteria, viruses, fungi, and parasites) and their toxins. The growing presence of antimicrobial resistance (AMR), i.e., microorganisms able to withstand current antimicrobial treatments, leads to harder treatments of foodborne illnesses. In addition, there is an increased risk of transferring AMR genes from the food chain into other microorganisms. A key factor with which to tackle the spread of pathogenic microorganisms and AMR outbreaks in the food chain is the development of more reliable and accurate surveillance methods. The latest techniques of whole-genome sequencing combined with high-throughput data analyses have improved the speed and accuracy of surveillance systems. Moreover, the spread of AMR in the food chain causes the need to experiment on alternative methods to antibiotics.

This Special Issue welcomes groundbreaking articles that aim to improve the real-time detection and tracking of foodborne pathogens in addition to the spread of AMR, as well as alternative methods (e.g., bacteriophages) to overcome the current AMR problem. This Special Issue is open to a wide range of articles and reviews, including modeling (WGS biomarkers, AI, deep learning, etc.), basic science, and applied research articles. Articles that evaluate the social/economic impacts, well-being benefits, and potential improvements of current technologies are also welcome.

Dr. Pere Puigbò
Guest Editor

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