Genetic Analysis of Enteropathogenic and Enterohemorrhagic <i>Escherichia coli</i> Serogroup O103 Strains by Molecular Typing of Virulence and Housekeeping Genes and Pulsed-Field Gel Electrophoresis
Bibliographic record
Abstract
We investigated the genetic relationships of 54 Escherichia coli O103 strains from humans, animals, and meat by molecular typing of housekeeping and virulence genes and by pulsed-field gel electrophoresis (PFGE). Multilocus sequence typing (MLST) of seven housekeeping genes revealed seven profiles, I through VII. MLST profiles I plus III cover 45 Shiga toxin-producing E. coli (STEC) O103:H2 strains from Australia, Canada, France, Germany, and Northern Ireland that are characterized by the intimin (eae) epsilon gene and carry enterohemorrhagic E. coli (EHEC) virulence plasmids. MLST profile II groups five human and animal enteropathogenic E. coli (EPEC) O103:H2 strains that were positive for intimin (eae) beta. Although strains belonging to MLST groups II and I plus III are closely related to each other (92.6% identity), major differences were found in the housekeeping icdA gene and in the virulence-associated genes eae and escD. E. coli O103 strains with MLST patterns IV to VII are genetically distant from MLST I, II, and III strains, as are the non-O103 E. coli strains EDL933 (O157), MG1655 (K-12), and CFT073 (O6). Comparison of MLST results with those of PFGE and virulence typing demonstrated that E. coli O103 STEC and EPEC have recently acquired different virulence genes and DNA rearrangements, causing alterations in their PFGE patterns. PFGE typing was very useful for identification of genetically closely related subgroups among MLST I strains, such as Stx2-producing STEC O103 strains from patients with hemolytic uremic syndrome. Analysis of virulence genes contributed to grouping of E. coli O103 strains into EPEC and STEC. Novel virulence markers, such as efa (EHEC factor for adherence), paa (porcine adherence factor), and cif (cell cycle-inhibiting factor), were found widely associated with E. coli O103 EPEC and STEC strains.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".