Enterohaemorrhagic <i>Escherichia coli</i> gains a competitive advantage by using ethanolamine as a nitrogen source in the bovine intestinal content
Bibliographic record
Abstract
The bovine gastrointestinal tract is the main reservoir for enterohaemorrhagic Escherichia coli (EHEC) responsible for food-borne infections. Characterization of nutrients that promote the carriage of these pathogens by the ruminant would help to develop ecological strategies to reduce their survival in the bovine gastrointestinal tract. In this study, we show for the first time that free ethanolamine (EA) constitutes a nitrogen source for the O157:H7 EHEC strain EDL933 in the bovine intestinal content because of induction of the eut (ethanolamine utilization) gene cluster. In contrast, the eut gene cluster is absent in the genome of most species constituting the mammalian gut microbiota. Furthermore, the eutB gene (encoding a subunit of the enzyme that catalyses the release of ammonia from EA) is poorly expressed in non-pathogenic E. coli. Accordingly, EA is consumed by EHEC but is poorly metabolized by endogenous microbiota of the bovine small intestine, including commensal E. coli. Interestingly, the capacity to utilize EA as a nitrogen source confers a growth advantage to E. coli O157:H7 when the bacteria enter the stationary growth phase. These data demonstrate that EHEC strains take advantage of a nitrogen source that is not consumed by the resident microbiota, and suggest that EA represents an ecological niche favouring EHEC persistence in the bovine intestine.
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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 | 0.000 |
| 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 | 0.000 |
| 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".