Influence of growth parameters on bacteriocin-like inhibitory substances (BLIS) production by lactic acid bacteria
Bibliographic record
Abstract
This study aimed to investigate the possible production of bacteriocin-like inhibitory substances (BLIS) and optimize it by Lactobacillus sakei and combined Lactobacillus curvatus/Pediococcus acidilactici, lactic acid bacteria used for the meat fermentation. The effect of growth parameters on BLIS production was evaluated by measuring the antibacterial activity of the cell-free supernatant of these bacteria. The stability of the cell-free supernatant of combined L.curvatus/P.acidilactici bacteria was also examined after heat treatment and pH variations. Results showed highest BLIS production by L.curvatus/P.acidilactici was at growth temperatures of 28°C and pH 5, while the optimum condition for production of BLIS by L.sakei was 24°C and pH 6.5. The BLIS production by L. curvatus/P. acidilactici bacteria was greatly influenced by carbon and nitrogen sources. The antimicrobial activity of BLIS in supplemented De Man, Rosa, and Sharpe broth (MRS) was 2044.44 AU/mL, 4.84-fold greater than unsupplemented MRS. None of the carbon sources used in this study affected the BLIS production by the L.sakei, while pea peptone enhanced the antimicrobial activity and showed a value of 188.89 AU/mL, 1.47-fold greater than unsupplemented MRS. The characterization of the cell-free supernatant of L. curvatus/P. acidilactici bacteria showed the heat stability and activity of BLIS at pH 2-10.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".