Antimicrobial activity of bacteriocin-producing lactic acid bacteria isolated from cheeses and yogurts
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Bibliographic record
Abstract
The biopreservation of foods using bacteriocinogenic lactic acid bacteria (LAB) isolated directly from foods is an innovative approach. The objectives of this study were to isolate and identify bacteriocinogenic LAB from various cheeses and yogurts and evaluate their antimicrobial effects on selected spoilage and pathogenic microorganisms in vitro as well as on a food commodity.LAB were isolated using MRS and M17 media. The agar diffusion bioassay was used to screen for bacteriocin or bacteriocin-like substances (BLS) producing LAB using Lactobacillus sakei and Listeria innocua as indicator organisms. Out of 138 LAB isolates, 28 were found to inhibit these bacteria and were identified as strains of Enterococcus faecium, Streptococcus thermophilus, Lactobacillus casei and Lactobacillus sakei subsp. sakei using 16S rRNA gene sequencing. Eight isolates were tested for antimicrobial activity at 5°C and 20°C against L. innocua, Escherichia coli, Bacillus cereus, Pseudomonas fluorescens, Erwinia carotovora, and Leuconostoc mesenteroides subsp. mesenteroides using the agar diffusion bioassay, and also against Penicillium expansum, Botrytis cinerea and Monilinia frucitcola using the microdilution plate method. The effect of selected LAB strains on L. innocua inoculated onto fresh-cut onions was also investigated.Twenty percent of our isolates produced BLS inhibiting the growth of L. innocua and/or Lact. sakei. Organic acids and/or H2O2 produced by LAB and not the BLS had strong antimicrobial effects on all microorganisms tested with the exception of E. coli. Ent. faecium, Strep. thermophilus and Lact. casei effectively inhibited the growth of natural microflora and L. innocua inoculated onto fresh-cut onions. Bacteriocinogenic LAB present in cheeses and yogurts may have potential to be used as biopreservatives in foods.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 it