As we’ve seen in numerous cases in 2015, food contamination is a real issue for a number of different food types. Vegetable, meat, packaged, fresh – even pet food – we’ve seen too many examples of how bacteria can outsmart our best food safety practices. The Canadian government estimates 1 of every 8 Canadians experiences food-borne illness each year, leading to 11,600 hospitalizations and 238 deaths. As we’ve often discussed on this blog, a common culprit for food contamination is Listeria monocytogenes, in part because of Listeria’s ability to grow in food storage conditions.
Food safety requires stringent food preparation methods and proper detection of contaminants. Awareness campaigns have improved both ends of this equation, and now technological advances are being applied to bacterial detection. New research in the Journal of Clinical Microbiology discusses the use of whole-genome sequencing (WGS) as a way to track outbreaks and identify contaminant sources. The research, conducted by a team of researchers led by Dr. Benjamin Howard at the University of Melbourne, concludes that WGS compares favorably against alternative methods of outbreak tracking.
To test the power of this technique, the team compared WGS analyses of 423 L. monocytogenes isolates to several traditional typing techniques, including multilocus sequence typing (MLST) and PCR-serotyping. WGS analyses showed that the isolates derived from three distinct lineages based on 158,707 single nucleotide polymorphisms. When the same isolates were analyzed using MLST or serotype groups, most of the isolates grouped similarly (see the figure, right: compare the innermost phylogenetic tree to the color-coded groupings based on method or isolate source). In fact, WGS was able to better resolve strains previously grouped together.
The group then tested the ability of WGS to identify outbreak clusters in a prospective study. 97 isolates were analyzed with lineage-specific references identified by MLST analysis. This allowed the scientists to predict the relatedness of isolates, which were characterized as likely related, possibly related, or likely unrelated. The sequences from these isolates were then compared to those from food industry sampling. By applying these methods, the scientific team was able to find a human isolate identical to a food isolate – possibly identifying the source of a contamination event. Matching patient strains to foodborne isolates requires a database of currently distributed strains, emphasizing the importance of surveillance of food industry.
The use of WGS in food safety monitoring is a new application of this technology that offers several advantages over traditional techniques. Because the authors were able to automate much of the sample prep, they found WGS to be less labor intensive – and less expensive. This may offset the high cost of sequencing machines and automatated robots, an issue that has prevented instituting WGS more broadly.
Should WGS be adopted for ongoing surveillance, it would allow rapid identification of the source of an outbreak. This last point is very important for food safety, as misidentified sources cause food waste, monetary and reputation loss to uninvolved companies, and continued spread of contaminated food items. As the case number of foodborne illnesses caused by L. monocytogenes has increased in the past year, this new technology comes at a propitious time.
-- Julie Wolf