Farber’s project studied the interactions between common foodborne pathogens, host environments, and how potential deterrents, such as beneficial bacteria, can be used to effectively combat the growth of such pathogens in human and livestock populations.
New strategies are urgently needed to detect and manage foodborne pathogens in the Canadian food systems to ensure food safety, prevent zoonotic diseases, and promote livestock health. Effectively managing both endemic and emerging pathogens requires a deeper understanding of host-pathogen relationships and the dynamics at play in both human and livestock populations. Big data approaches, including machine learning and advanced data technologies, are increasingly being applied to pathogen management, offering new opportunities for improving monitoring and control. However, there is still much to be done. Big data not only enables more efficient surveillance but also provides the potential to uncover valuable insights into host-pathogen interactions. These discoveries can drive future research and lead to more effective interventions for common pathogens such as Listeria monocytogenes and others.
Dr. Jeff Farber’s multidisciplinary project comprised several streams of work that explored the complex host-pathogen relationships that drive the emergence of pathogens in both animal and human populations. Collaborating with experts at the University of Guelph, the project integrated expertise in the fields of microbiology, epidemiology, and data science to explore how pathogens evolve and spread. One central theme in Farber’s research was the application of big data analytics to investigate disease processes at the molecular and population levels, enabling the development of predictive models that can forecast potential outbreaks and help control the spread of disease. Farber’s research team also discovered and tested novel compounds or probiotics capable of inhibiting pathogen growth and supressing virulence -associated gene expression, in microbes in the human gastrointestinal tract. Finally, the team conducted qualitative risk assessments for emerging nutrition sources to establish best practices to mitigate the risk of pathogens both in the production and consumption of these foods. These intertwining projects all served to develop more effective strategies for pathogen control and prevention, ultimately reducing the public health burden of foodborne illnesses.
The research conducted serves to reduce foodborne illnesses both within Canada and internationally through multidisciplinary d approaches. The discovery of certain beneficial bacteria strains that may control foodborne pathogens is an important finding that can inform safer production and consumption of common foods. Further, the advances in big data and machine learning identified by Farber’s team can further reduce the risk of foodborne illnesses and their associated economic impacts, whether data models are used to detect sources of outbreaks, predict the emergence of viruses, or to identify the most cost-effective ways to prevent outbreaks. The findings from this research can also be applied to other foodborne pathogens beyond the scope of the study, benefiting agriculture and food production across Canada and beyond.
Chantapakul, B. V.R. Parreira and J.M. Farber. 2024. Effect of bacterial endophytes isolated from tropical fruits against Listeria monocytogenes and Cronobacter sakazakii in model food products. J. Food Protect. 87(9):100330. doi: 10.1016/j.jfp.2024.100330.
Dallner, M. T. (n.d.). The use of Potentially Probiotic Bacteria for their Biocontrol Effects on the Foodborne Pathogen Human Norovirus GII.4 and its Surrogate Virus Murine Norovirus-.
Farber, J., Dara, R., & Ronholm, J. (Eds.). (2023). Harnessing Big Data in Food Safety. Springer International Publishing. https://doi.org/10.1007/978-3-031-07179-9
Gemmell, C. T., Parreira, V. R., & Farber, J. M. (2022). Controlling Listeria monocytogenes Growth and Biofilm Formation Using Flavonoids. Journal of Food Protection, 85(4), 639–646. https://doi.org/10.4315/JFP-21-135
Kaviani, M., Dara, R., & Farber, J. M. (2023). Machine Learning Application in Food Safety, Production, and Quality. In J. Farber, R. Dara, & J. Ronholm (Eds.), Harnessing Big Data in Food Safety (pp. 1–21). Springer International Publishing. https://doi.org/10.1007/978-3-031-07179-9_1
Kaviani, M. R. Dara and J.M. Farber. (2022). The Need for Data Standardization in the Food Supply Chain. In “Harnessing Big Data in Food Safety”, pp. 125-140. Eds. JM Farber, R. Dara and J. Ronholm. Springer, Switzerland.
Ke, A., V.R. Parreira, L. Goodridge and J.M. Farber. (2021). Current and future perspectives on the role of probiotics, prebiotics, and synbiotics in controlling pathogenic Cronobacter spp. in infants. Frontiers in Microbiology 12.
Ke A., V.R. Parreira, J.M. Farber and L. Goodridge. (2022). Inhibition of Cronobacter sakazakii in an infant simulator of the human intestinal microbial ecosystem using a potential synbiotic. Frontiers Microbiol. 13:947624. doi: 10.3389/fmicb.2022.947624.
Ke, A., V. Parreira, J.M. Farber and L. Goodridge. (2022). Selection of a potential synbiotic against Cronobacter sakazakii. J. Food Protect. https://doi.org/10.4315/JFP-22-048
Kireina, D., V. R. Parreira, L. Goodridge and J.M. Farber. (2024). Survival and expression of rpoS and grxB of Cronobacter sakazakii in powdered infant formula under simulated gastric conditions of newborns. J. Food Protect. 87: (5). https://doi.org/10.1016/j.jfp.2024.100269
Parreira, VR and JM Farber. (2022). The Role of Policy and Regulations in the Adoption of Big Data Technologies in Food Safety and Quality. In “Harnessing Big Data in Food Safety”, pp. 151-160. Eds. JM Farber, R. Dara and J. Ronholm. Springer, Switzerland.
Walia, K., Kapoor, A., & Farber, J. M. (2018). Qualitative risk assessment of cricket powder to be used to treat undernutrition in infants and children in Cambodia. Food Control, 92, 169–182. https://doi.org/10.1016/j.foodcont.2018.04.047
Walia, K., Kapoor, A., & Farber, J. M. (2019). Qualitative Microbiological Risk Assessment of Moringa oleifera Leaf Powder To Be Used To Treat Undernutrition in Infants and Children in
Cambodia and India: A Review. Journal of Food Protection, 82(3), 513–521. https://doi.org/10.4315/0362-028X.JFP-18-252
Zhang, L., VR Parreira, A Rahman, BA Smith, DS Munther and JM Farber. (2023). Survival and predictive modeling of Listeria monocytogenes under simulated human gastric conditions in the presence of bovine milk products. Intern. J. Food Microbiol. 396, 110201.
Dr. Jan Sargeant, Dr. Charlotte Winder, Dr. Valeria Parreiria, Dr. Jianhong Wu, Dr. Ben Smith
Nikola May, Krishna Gelda, Bowornnan (Tim) Chantapakuk, Mathew Dallner, Devita Kireina, Linkang Zhang, Christopher Gemmell, Alfred Ke, Vivian Ly, Gabrielle Bui, Grant Brierley, Ryan Cuzzi
York University, Public Health Agency of Canada
