A novel small RNA regulates Locus of Enterocyte Effacement and site-specific colonization of enterohemorrhagic Escherichia coli O157:H7 in gut
Bibliographic record
Abstract
Enterohemorrhagic Escherichia coli (EHEC) is a contagious foodborne pathogen that specifically colonizes the human large intestine, which is regulated by different environmental stimuli within the gut. Transcriptional regulation of EHEC virulence and infection has been extensively studied, while the posttranscriptional regulation of these processes by small RNAs (sRNAs) remains not fully understood. Here we present a virulence-regulating pathway in EHEC O157:H7, in which the sRNA EvrS binds to and destabilizes the mRNA of Z2269, a novel transcriptional regulator. In turn, Z2269 indirectly activates the expression of LEE (locus of enterocyte effacement) pathogenicity island through the master regulator Ler. Importantly, the expression of EvrS is modulated by environmental oxygen levels. EvrS also exhibits lower expression in the colon compared to the ileum, influencing the site-specific colonization of EHEC O157:H7 in mice. These results indicate that the oxygen status within the intestine may regulate the expression of EvrS, thereby modulating virulence factors of EHEC and contributing to successful infection in vivo. This study has broader implications for understanding sRNA functions in spatiotemporal virulence control of EHEC and may provide novel strategies to prevent EHEC infections.
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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".