A novel antimicrobial peptide significantly enhances acid-induced killing of Shiga toxin-producing Escherichia coli O157 and non-O157 serotypes
Bibliographic record
Abstract
Shiga toxin-producing Escherichia coli (STEC) colonizes the human intestine, causing haemorrhagic colitis and haemolytic uraemic syndrome (HUS). Treatment options are limited to intravenous fluids in part because sublethal doses of some antibiotics have been shown to stimulate increased toxin release and enhance the risk of progression to HUS. Preventative antimicrobial agents, especially those that build on the natural antimicrobial action of the host defence, may provide a better option. In order to survive the acid stress of gastric passage, STEC is equipped with numerous acid resistance and DNA repair mechanisms. Inhibition of acid-induced DNA repair may offer a strategy to target survival of ingested STEC. We report here that brief pretreatment with a novel antimicrobial peptide, which was previously shown to inhibit bacterial DNA repair, significantly and profoundly reduces survival of acid-stressed O157 : H7 and non-O157 : H7 STEC seropathotypes that are highly associated with HUS. Reduction in survival rates of STEC range from 3 to 5 log. We also show that peptide/acid treatment results in little or no increase in toxin production, thereby reducing the risk of progression to HUS. This study identifies the peptide wrwycr as a potential new candidate for a preventative antimicrobial for STEC infection.
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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 | 0.000 | 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) | 0.000 | 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".