Prevalence of Shiga Toxin-Producing Escherichia coli (STEC) and Risk Characterization Based on Virulence Genes in Retail Raw Ground Meat of Beef, Veal, and Lamb in Canada
Bibliographic record
Abstract
Shiga toxin-producing Escherichia coli (STEC) are potentially pathogenic E. coli that may cause mild to severe gastrointestinal illnesses. STEC-contaminated foods of animal origin have been the most frequently implicated sources of foodborne outbreaks. A multiyear (2016 to 2021) targeted survey was conducted to investigate the prevalence of STEC in retail ground meats (beef, veal, and lamb). Samples were screened for the presence of Shiga toxin genes (stx) to identify presumptive samples, followed by culture and molecular confirmation of isolates to confirm the presence of stx genes and subsequent characterization by whole-genome-sequencing (WGS) for O serogroup and virulence genes (e.g., stx, eae, aggR). A total of 175 STEC strains were isolated from a total of 148 samples where the presence of viable STEC was confirmed out of 2,398 ground meat samples. This represented 1.2% (7/589 positive, 8 unique strains) of the beef samples, 4.7% (58/1,241 positive, 67 unique strains) of the veal samples, and 14.6% (83/568 positive, 100 unique strains) of the lamb samples. The intimin virulence gene, eae, was identified in the STEC strains of veal origin (9/67, 13.4%) only and were classified as belonging to risk level 1 (1/67), level 3 (2/67), and level 4 (6/67) according to the FAO/WHO risk categories. Risk level 2 STEC strains were of beef (2/8, 25.0%), veal (8/67, 11.9%), and lamb (1/100, 1.0%) origin. The majority of the STEC strains, 75.0% (6/8) of the beef, 67.2% (45/67) of the veal, and 94.0% (94/100) of the lamb STEC strains were classified as risk level 5 (lowest level) of the FAO/WHO risk categories. This study's findings indicate that the current food safety control measures implemented for ground meats in Canada are effective at maintaining an acceptable level of possible contamination with STEC strains associated with severe clinical outcomes. Continued application of effective control measures and safe food handling practices by consumers will minimize the potential risk of foodborne infections from raw ground meats.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".