Shiga Toxin–Producing Escherichia coli (STEC) and STEC-Associated Virulence Genes in Raw Ground Pork in Canada
Bibliographic record
Abstract
ABSTRACT: Shiga toxin-producing Escherichia coli (STEC) O157:H7/nonmotile and some non-O157 STEC strains are foodborne pathogens. In response to pork-associated O157 STEC outbreaks in Canada, we investigated the occurrence of STEC in Canadian retail raw ground pork during the period of 1 November 2014 to 31 March 2016. Isolated STEC strains were characterized to determine the Shiga toxin gene (stx) subtype and the presence of virulence genes encoding intimin (eae) and enterohemorrhagic E. coli hemolysin (hlyA). O157 STEC and non-O157 STEC strains were isolated from 1 (0.11%) of 879 and 13 (2.24%) of 580 pork samples, respectively. STEC virulence gene profiles containing both eae and hlyA were found only in the O157 STEC (stx2a, eae, hlyA) isolate. The eae gene was absent from all non-O157 STEC isolates. Of the 13 non-O157 STEC isolates, two virulence genes of stx1a and hlyA were found in four (30.8%) O91:H14 STEC isolates, whereas one virulence gene of stx2e, stx1a, and stx2a was identified in five (38.5%), two (15.4%), and one (7.7%) STEC isolates, respectively, of various serotypes. The remaining non-O157 STEC isolate carried stx2, but the subtype is unknown because this isolate could not be recovered for sequencing. O91:H14 STEC (stx1a, hlyA) was previously reported in association with diarrheal illnesses, whereas the other non-O157 STEC isolates identified in this study are not known to be associated with severe human illnesses. Virulence gene profiles identified in this study indicate that the occurrence of non-O157 STEC capable of causing severe human illness is rare in Canadian retail pork. However, O157 STEC in ground pork can occasionally occur; therefore, education regarding the potential risks associated with STEC contamination of pork would be beneficial for the public and those in the food industry to help reduce foodborne illnesses.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".