Advanced Detection and Bioinformatics of Foodborne Pathogens

A special issue of Pathogens (ISSN 2076-0817).

Deadline for manuscript submissions: 31 July 2025 | Viewed by 1430

Special Issue Editor


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Guest Editor
Department of Microbiology and Molecular Biology, Institute of Meat Hygiene and Technology, 11040 Belgrade, Serbia
Interests: foodborne pathogens; next-generation sequencing; machine learning and AI

Special Issue Information

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

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Keywords

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

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Published Papers (1 paper)

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Research

7 pages, 201 KiB  
Communication
Clinical Outcomes and Virulence Factors of Shiga Toxin-Producing Escherichia coli (STEC) from Southern Alberta, Canada, from 2020 to 2022
by Heather Glassman, Vivien Suttorp, Theron White, Kim Ziebell, Ashley Kearney, Kyrylo Bessonov, Vincent Li and Linda Chui
Pathogens 2024, 13(10), 822; https://doi.org/10.3390/pathogens13100822 - 24 Sep 2024
Viewed by 1072
Abstract
Shiga toxin-producing Escherichia coli (STEC) can cause severe clinical disease in humans, particularly in young children. Recent advances have led to greater availability of sequencing technologies. We sought to use whole genome sequencing data to identify the presence or absence of known virulence [...] Read more.
Shiga toxin-producing Escherichia coli (STEC) can cause severe clinical disease in humans, particularly in young children. Recent advances have led to greater availability of sequencing technologies. We sought to use whole genome sequencing data to identify the presence or absence of known virulence factors in all clinical isolates submitted to our laboratory from Southern Alberta dated 2020–2022 and correlate these virulence factors with clinical outcomes obtained through chart review. Overall, the majority of HUS and hospitalizations were seen in patients with O157:H7 serotypes, and HUS cases were primarily in young children. The frequency of virulence factors differed between O157:H7 and non-O157 serotypes. Within the O157:H7 cases, certain virulence factors, including espP, espX1, and katP, were more frequent in HUS cases. The number of samples was too low to determine statistical significance. Full article
(This article belongs to the Special Issue Advanced Detection and Bioinformatics of Foodborne Pathogens)
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