Antimicrobial Activity of Synthetic Enterocins A, B, P, SEK4, and L50, Alone and in Combinations, against Clostridium perfringens
Bibliographic record
Abstract
Multidrug-resistant Clostridium perfringens infections are a major threat to the poultry industry. Effective alternatives to antibiotics are urgently needed to prevent these infections and limit the spread of multidrug-resistant bacteria. The aim of the study was to produce by chemical synthesis a set of enterocins of different subgroups of class II bacteriocins and to compare their spectrum of inhibitory activity, either alone or in combination, against a panel of twenty C. perfringens isolates. Enterocins A, P, SEK4 (class IIa bacteriocins), B (unsubgrouped class II bacteriocin), and L50 (class IId leaderless bacteriocin) were produced by microwave-assisted solid-phase peptide synthesis. Their antimicrobial activity was determined by agar well diffusion and microtitration methods against twenty C. perfringens isolates and against other pathogens. The FICINDEX of different combinations of the selected enterocins was calculated in order to identify combinations with synergistic effects. The results showed that synthetic analogs of L50A and L50B were the most active against C. perfringens. These peptides also showed the broadest spectrum of activity when tested against other non-clostridial indicator strains, including Listeria monocytogenes, methicillin-resistant Staphylococcus aureus, Streptococcus suis, Streptococcus pyogenes, Enterococcus cecorum, Enterococcus faecalis, as well as Gram-negative bacteria (Campylobacter coli and Pseudomonas aeruginosa), among others. The selected synthetic enterocins were combined on the basis of their different mechanisms of action, and all combinations tested showed synergy or partial synergy against C. perfringens. In conclusion, because of their high activity against C. perfringens and other pathogens, the use of synthetic enterocins alone or as a consortium can be a good alternative to the use of antibiotics in the poultry sector.
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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".