Diversity of enterococcal bacteriocins and their grouping in a new classification scheme
Bibliographic record
Abstract
Enterococci are lactic acid bacteria of importance in food, public health and medical microbiology. Many strains produce bacteriocins, some of which have been well characterized. This review describes the structural and genetic characteristics of enterocins, the bacteriocins produced by enterococci. Some of these can be grouped with typical bacteriocins produced by lactic acid bacteria according to traditional classification, whereas others are atypical and structurally distinct from the general classes of bacteriocins. These atypical enterocins recently played an important role in and prompted reclassification of the class II bacteriocins into a new scheme. In this review, a more simplified classification scheme for enterocins based on amino acid sequence homologies is proposed. Enterocins are of interest for their diversity and potential for use as food biopreservatives. The emergence of multiple antibiotic-resistant enterococci among agents of nosocomial disease and the presence of virulence factors among food isolates requires a careful safety evaluation of isolates intended for potential biotechnical use. Nevertheless, enterococcal bacteriocins produced by heterologous hosts or added as cell-free preparations may still be attractive for application in food preservation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".