The effect of sucrose-induced osmotic stress on the sensitivity of <i>Escherichia coli</i> to bacteriocins
Bibliographic record
Abstract
Bacteriocins are antimicrobial peptides, produced by Gram-positive bacteria such as lactococci and staphylococci, that have limited bactericidal action against Gram-negative bacteria. The aim of this paper was to study the sensitivity of three strains of Escherichia coli to bacteriocins: nisin (as Nisaplin®) and two staphylococcal peptides (warnerin and hominin) during sucrose-induced osmotic stress. We found that all peptides in a 0.3 g·mL −1 sucrose solution significantly reduced the number of viable E. coli. The most pronounced antibacterial effect was achieved by nisin against E. coli K-12 (3 log reduction). Slightly less bactericidal effects were observed with warnerin (1 mg·mL −1 ) and hominin (1 mg·mL −1 ) in sucrose solution. The lytic activity of staphylococcal peptides was detected by decreased optical density and viable cell counts. Moreover, it was confirmed by the increased amount of DNA and protein in the medium and the morphological changes detected by atomic force microscopy after 20 h of treatment. Zymographic analysis revealed the release of lytic enzymes from E. coli cells after treatment with staphylococcal peptides and sucrose. These results indicated that the antimicrobial action of peptides can be extended to Gram-negative bacteria via combination with high concentrations of sucrose.
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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".