Multilocus Genotype Analysis of Escherichia coli O157 Isolates from Australia and the United States Provides Evidence of Geographic Divergence
Bibliographic record
Abstract
Escherichia coli O157 is a food-borne pathogen whose major reservoir has been identified as cattle. Recent genetic information has indicated that populations of E. coli O157 from cattle and humans can differ genetically and that this variation may have an impact on their ability to cause severe human disease. In addition, there is emerging evidence that E. coli O157 strains from different geographical regions may also be genetically divergent. To investigate the extent of this variation, we used Shiga toxin bacteriophage insertion sites (SBI), lineage-specific polymorphisms (LSPA-6), multilocus variable-number tandem-repeat analysis (MLVA), and a tir 255T>A polymorphism to examine 606 isolates representing both Australian and U.S. cattle and human populations. Both uni- and multivariate analyses of these data show a strong association between the country of origin and multilocus genotypes (P < 0.0001). In addition, our results identify factors that may play a role in virulence that also differed in isolates from each country, including the carriage of stx1 in the argW locus uniquely observed in Australian isolates and the much higher frequency of stx2-positive (also referred to as stx2a) strains in the U.S. isolates (4% of Australian isolates versus 72% of U.S. isolates). LSPA-6 lineages differed between the two continents, with the majority of Australian isolates belonging to lineage I/II (LI/II) (LI, 2%; LI/II, 85%; LII, 13%) and the majority of U.S. isolates belonging to LI (LI, 60%; LI/II, 16%; LII, 25%). The results of this study provide strong evidence of phylogeographic structuring of E. coli O157 populations, suggesting divergent evolution of enterohemorrhagic E. coli O157 in Australia and the United States.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| 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 | 0.002 |
| 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".