Mutacins and their Potential Use in Food Preservation
Bibliographic record
Abstract
Mutacins are proteinaceous antibacterial substances produced by Streptococcus mutans, an indigenous bacterial inhabitant of the oral cavity. The metabolism of S. mutans is similar to that of lactic acid bacteria (LAB) used in fermented food. Actually, only a few wellstudied mutacins have been described. Mutacins B-Ny266, B-JH1140, I, III, and K8 are linear lantibiotics. Mutacins II and H-29B are globular lantibiotics. Mutacins GS-5/Smb and BHT-A are dipeptide lantibiotics. Mutacins N and BHT-B are non-lantibiotic peptides while mutacin IV is a non-lantibiotic dipeptide. Some of these mutacins are active against most Gram-positive foodborne pathogens. Nisin is actually the only lantibiotic bacteriocin used as a food additive and pediocin-like bacteriocins are considered to be next in line if more antibacterial proteins are to be approved in the future. However, nisin- and pediocin-resistant mutants appear relatively easily while resistant mutants against mutacins B-JH1140 and B-Ny266 could not be obtained. Mutacins thus have potential for controlling foodborne pathogens and spoilage bacteria. New methods for producing and purifying these small peptides will contribute towards developing food grade antimicrobials for use in food products. More research is needed on the applications of bacteriocins in food systems.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".