Advanced Detection and Bioinformatics of Foodborne Pathogens

Dear Colleagues,

From the beginning of the 21st century, modern phenomena, such as the facilitation of global trading from planting and harvesting to processing, packaging, and distribution to retail locations, climate change, and changes in eating habits, such as increased consumption of raw and "green" food, significantly accelerated scientific efforts invested into understanding major foodborne pathogens, such as norovirus, Campylobacter spp., Salmonella spp., Listeria monocytogenes, and shigatoxigenic E. coli, with the final aim of contributing to the decline in health burden to human populations worldwide.

However, in the realm of food microbiology, both challenges and advances are continually evolving. There is still a considerable amount of scientific research that has to be carried out in order to gain a better understanding of emerging foodborne pathogens such Arcobacter, Cyclospora, hepatitis E virus, and Clostridium perfringens type E, which have recently increased in prevalence or have newly emerged as significant threats to food safety. These pathogens may have adapted to new environments, developed resistance to antimicrobial agents, or evolved to infect new hosts. Furthermore, conventional techniques used to identify and analyze foodborne pathogens through culturing have been shown to be time-consuming, labor-intensive, and requiring extensive infrastructure. Therefore, these approaches are not suitable for future prospects of food production and processing.

In this Special Issue, we aim to provide a platform for food microbiology researchers to present their recent research advances and solutions involving rapid pathogen detection methods, bioinformatics and metagenomics, nanotechnology, AI, the prevalence of antibiotic resistance in foodborne pathogens, and precision agriculture. We welcome you to submit original research articles, communications, or reviews.

I firmly believe that these contributions will have a positive impact on transforming the safety dimensions of the food industry sector and allow stakeholders to utilize the data acquired to minimize their operational and public health risks.

Dr. Branko Velebit
Guest Editor

Manuscript Submission Information

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• foodborne pathogens
• rapid detection methods
• bioinformatics
• antimicrobial resistance
• electrochemical biosensors
• machine learning
• artificial intelligence
• big data and analytics
• nanotechnology