The Agriculture and Food Laboratory has successfully completed the research project “OAF-2019-100464 - Evaluation of a High Throughput CRISPR Sequence-Based Method for Identification of Multiple Salmonella Serovars in a Sample from Poultry Production Environments”.  The project was funded via a competitive grant by the Ontario Ministry of Agriculture, Food and Rural Affairs (OMAFRA) under the Canadian Agricultural Partnership, a five-year federal-provincial-territorial initiative program (http://www.omafra.gov.on.ca/english/cap/index.ht).

Principle Researchers: Dr. Shu Chen (PI) and Dr. Carlos Leon-Velarde (Co-PI), the Agriculture and Food Laboratory, University of Guelph

Project Summary:

Salmonella is one of the most important agents of human food-borne illness. Public Health Agency of Canada estimates Salmonella causes 80,000 cases each year in Canada. Salmonella resides with poultry as a major reservoir and consists of over 2600 serovars, differing in transmission route and pathogenic capacity. Poultry production environments are known to have a high risk of Salmonella contamination associated with many different serovars. Accurate detection of all Salmonella serovars present in a sample is important in monitoring practices and outbreak investigations. Current detection protocols are limited to detecting a predominant serovar in a sample, missing identification of less abundant serovars. In this project, an alternative molecular method, called CRISPR-SeroSeq, was validated, which employs amplification and high-throughput sequencing of CRISPR spacer sequences to identify multiple serovars present in a sample.

The new method successfully detected 45 Salmonella serovars that are most frequently reported in outbreak cases or associated with poultry environments. The detection limit was 104 CFU/mL as determined using Salmonella-negative environmental enrichment samples post-spiked with one of 15 different serovars, plus 2 additional serovars at 1 log CFU/mL higher abundance. When the method was applied to 442 naturally contaminated environmental samples collected from 192 poultry farms in Ontario, 25 different serovars were identified from 430 of the samples. In 73.1% of the samples, 2 to 7 serovars were detected with serovars Kiambu (55.7%), Infantis (48.4%), Kentucky (27.1%), Livingstone (26.6%) and Mbandaka/Montevideo (23.4%) being the most prevalent on the farms. Culture isolates from 384 samples were also analyzed using a traditional culture-based serotyping method, and the same serovar identified by culture was detected by the new method in 96.1% (369/384) of samples with the traditional method missing detection of additional and sometimes critical serovars, especially Salmonella Enteritidis. The surveillance data obtained during a 10-month period using the new method also revealed a significant emergence of S. Kiambu and S. Rissen on poultry farms in Ontario.

The validated CRISPR-SeroSeq method represents an advanced alternative molecular tool to traditional culture-based serotyping method that can detect multiple Salmonella serovars in a sample and provide rapid serovar results without the need of selective enrichment and culture isolation. The application of the method in government and industry surveillance programs can improve effectiveness of Salmonella monitoring and interventions based on a more complete picture of Salmonella contamination in poultry production environments. The Salmonella serovar results highlight not only the effectiveness of the new method, but also the need of monitoring Salmonella serovars in poultry environments to improve current surveillance programs. The updated surveillance data provide timely information on emergence of different Salmonella serovars on poultry farms in Ontario and support improved on-farm risk assessment and risk management of Salmonella to enhance food safety.