Purification and characterization of enterocin MC13 produced by a potential aquaculture probiont<i>Enterococcus faecium</i>MC13 isolated from the gut of<i>Mugil cephalus</i>
Bibliographic record
Abstract
A bacteriocin producer strain MC13 was isolated from the gut of Mugil cephalus (grey mullet) and identified as Enterococcus faecium. The bacteriocin of E. faecium MC13 was purified to homogeneity, as confirmed by Tricine sodium dodecyl sulphate - polyacrylamide gel electrophoresis (SDS-PAGE). Reverse-phase high-performance liquid chromatography (HPLC) analysis showed a single active fraction eluted at 26 min, and matrix-assisted laser desorption ionization time of flight (MALDI-TOF) mass spectrometry analysis showed the molecular mass to be 2.148 kDa. The clear zone in native PAGE corresponding to enterocin MC13 band further substantiated its molecular mass. A dialyzed sample (semicrude preparation) of enterocin MC13 was broad spectrum in its action and inhibited important seafood-borne pathogens: Listeria monocytogenes , Vibrio parahaemolyticus, and Vibrio vulnificus. This antibacterial substance was sensitive to proteolytic enzymes: trypsin, protease, and chymotrypsin but insensitive to catalase and lipase, confirming that inhibition was due to the proteinaceous molecule, i.e., bacteriocin, and not due to hydrogen peroxide. Enterocin MC13 tolerated heat treatment (up to 90 °C for 20 min). Enterococcus faecium MC13 was effective in bile salt tolerance, acid tolerance, and adhesion to the HT-29 cell line. These properties reveal the potential of E. faecium MC13 to be a probiotic bacterium. Enterococcus faecium MC13 could be used as potential fish probiotic against pathogens such as V. parahaemolyticus, Vibrio harveyi, and Aeromonas hydrophila in fisheries. Also, this could be a valuable seafood biopreservative against L. monocytogenes.
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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) | 0.000 | 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 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".