Novel antimicrobial compounds from fermented food-derived Lacticaseibacillus paracasei B1 and Lactiplantibacillus plantarum O24 strains: Genomic and proteomic analysis
Bibliographic record
Abstract
This study investigated the genomic and functional characteristics of antimicrobial compounds produced by Lacticaseibacillus paracasei strain B1 and Lactiplantibacillus plantarum strain O24, previously isolated from traditional Polish fermented foods. Whole-genome sequencing and bioinformatics analyses revealed multiple gene regions encoding bacteriocins, including lactococcins, plantaricins, and enterolysin A, with genes on both chromosomes and plasmids. Experimental validation confirmed the proteinaceous nature of the active antimicrobial substances, as evidenced by their sensitivity to proteolytic enzymes (trypsin, pepsin, and proteinase K) and their stability under heat (40–100 °C) and acidic pH conditions. Antimicrobial activity was observed against Gram-positive and Gram-negative bacteria, significantly inhibiting Listeria monocytogenes and Escherichia coli O157:H7. Fourier-Transform Infrared (FT-IR) spectroscopy assessed functional groups and active sites. Purification and molecular weight estimation via SDS-PAGE analysis identified protein bands of approximately 15 kDa and 10 kDa. LC-MS/MS analysis confirmed these results and indicated partial homology with previously reported bacteriocins, suggesting they may represent novel bacteriocins or bacteriocin-like inhibitory substances. These findings highlight the potential of food-origin lactic acid bacteria strains as a source of diverse and robust antimicrobial compounds, paving the way for food preservation and antimicrobial therapy applications.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".