Multilocus Sequence Typing and Virulence Gene Profiles Associated with <i>Escherichia coli</i> from Human and Animal Sources
Bibliographic record
Abstract
We investigated whether specific sequence types, and their shared virulence gene profiles, may be associated with both human and food animal reservoirs. A total of 600 Escherichia coli isolates were assembled from human (n=265) and food-animal (n=335) sources from overlapping geographic areas and time periods (2005-2010) in Canada. The entire collection was subjected to multilocus sequence typing and a subset of 286 E. coli isolates was subjected to an E. coli-specific virulence gene microarray. The most common sequence type (ST) was E. coli ST10, which was present in all human and food-animal sources, followed by ST69, ST73, ST95, ST117, and ST131. A core group of virulence genes was associated with all 10 common STs including artJ, ycfZ, csgA, csgE, fimA, fimH, gad, hlyE, ibeB, mviM, mviN, and ompA. STs 73, 92, and 95 exhibited the largest number of virulence genes, and all were exclusively identified from human infections. ST117 was found in both human and food-animal sources and shared virulence genes common in extraintestinal pathogenic E. coli lineages. Select groups of E. coli may be found in both human and food-animal reservoirs.
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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 | 0.001 | 0.001 |
| 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) | 0.001 | 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".