eLife Assessment: Persistent cross-species transmission systems dominate Shiga toxin-producing Escherichia coli O157:H7 epidemiology in a high incidence region: a genomic epidemiology study
Bibliographic record
Abstract
Several areas of the world suffer notably high incidence of Shiga toxin-producing Escherichia coli, among them Alberta, Canada. We assessed the role of persistent cross-species transmission systems in Alberta’s E. coli O157:H7 epidemiology.We sequenced and assembled 229 E. coli O157:H7 isolates originating from collocated cattle (n=108) and human (n=121) populations from 2007-2015 in Alberta. We constructed a timed phylogeny using BEAST2 using a structured coalescent model. We then extended the tree with human isolates through 2019 (n=432) to assess the long-term disease impact of local persistent lineages. Shiga toxin gene (stx) profile was determined for all isolates.During 2007 to 2015, we estimated 107 (95% HPD 101, 111) human lineages arose from cattle lineages, and 31 (95% HPD 22, 43) from other human lineages; i.e., 77.5% of human lineages arose from cattle lineages. We identified 11 persistent lineages local to Alberta, which were associated with 36.4% (95% CI 27.8%, 45.6%) of human isolates. Of 115 isolates in local persistent lineages, 6.1% carried only stx2a and the rest stx1a/stx2a. During the later period, six local persistent lineages continued to be associated with human illness, including 74.7% (95% CI 68.3%, 80.3%) of reported cases in 2018 and 2019. The stx profile of isolates in local persistent lineages shifted from the earlier period, with 51.2% encoding only stx2a.Our study identified multiple locally evolving lineages transmitted between cattle and humans persistently associated with E. coli O157:H7 illnesses for up to 13 years. Of concern, there was a dramatic shift in the local persistent lineages toward strains with the more virulent stx2a-only profile. We hypothesize that the large proportion of disease associated with local transmission systems is a principal cause of Alberta’s high E. coli O157:H7 incidence.
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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 | 0.003 | 0.005 |
| 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 | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".