Pathogens and Food Safety

Food Science MSc. student Matthew Dallner observes cell cultures in the inverted microscope for research on Human Norovirus in laboratory level 2+, Canadian Research Institute in Food Safety

Food from Thought uses big data analytics to study ecosystems at the smallest scale, the microcosm, to promote food safety, prevent zoonotic disease, and enhance livestock health. Using big data, Food from Thought studies pathogens and their relationships with their hosts, addressing concerns that intensive food production systems can lead to consumer safety and livestock health threats.

Approximately four million cases of foodborne illness occur in Canada every year with the potential to cause severe health impacts or, rarely, death. We need to better understand the ecology and virulence of foodborne pathogens and the causes of deadly outbreaks to better predict and manage outbreaks; additionally, we lack rapid and sensitive methods to detect and inactivate foodborne viruses. Food from Thought researchers are collecting data from around the world to model foodborne illness outbreaks, predict the emergence of pathogens, and develop novel methods to detect and inactivate foodborne viruses and pathogens.

Avian influenza viruses present a major threat to the poultry industry, resulting in economic losses and trade impacts, but also presents a risk to human health, as all human pandemic influenza viruses in the last century have had an avian origin. Developing strategies to understand, predict and control the spread of avian influenza viruses is of primary importance. Food from Thought researchers scan for the presence of avian influenza viruses in wildlife species in Canada, study and model the transmission of avian influenza viruses at the individual and population level, develop methods to detect and control virus transmission, and are creating a decision support system to prioritize avian influenza intervention strategies.

The most common clinical issue for Canadian swine nurseries is Streptococcus suis, which is commonly found on the tonsils of healthy animals but can sometimes become a systemic pathogen with the ability to cause severe clinical disease. It is currently unknown why this disease can become systemically present; novel ‘big data’ approaches offer an opportunity to better understand this production-limiting disease. Food from Thought researchers are collecting information on the s. suis pathogen and identifying factors that contribute to disease severity, including host characteristics and genomic information, farm management practices, and the tonsillar microbiome. This project will feed into a greater data library of current data resources related to production-limiting diseases across all livestock species.