Antibacterial Activities of Nisin Z Encapsulated in Liposomes or Produced In Situ by Mixed Culture during Cheddar Cheese Ripening
Bibliographic record
Abstract
This study investigated both the activity of nisin Z, either encapsulated in liposomes or produced in situ by a mixed starter, against Listeria innocua, Lactococcus spp., and Lactobacillus casei subsp. casei and the distribution of nisin Z in a Cheddar cheese matrix. Nisin Z molecules were visualized using gold-labeled anti-nisin Z monoclonal antibodies and transmission electron microscopy (immune-TEM). Experimental Cheddar cheeses were made using a nisinogenic mixed starter culture, containing Lactococcus lactis subsp. lactis biovar diacetylactis UL 719 as the nisin producer and two nisin-tolerant lactococcal strains and L. casei subsp. casei as secondary flora, and ripened at 7 degrees C for 6 months. In some trials, L. innocua was added to cheese milk at 10(5) to 10(6) CFU/ml. In 6-month-old cheeses, 90% of the initial activity of encapsulated nisin (280 +/- 14 IU/g) was recovered, in contrast to only 12% for initial nisin activity produced in situ by the nisinogenic starter (300 +/- 15 IU/g). During ripening, immune-TEM observations showed that encapsulated nisin was located mainly at the fat/casein interface and/or embedded in whey pockets while nisin produced by biovar diacetylactis UL 719 was uniformly distributed in the fresh cheese matrix but concentrated in the fat area as the cheeses aged. Cell membrane in lactococci appeared to be the main nisin target, while in L. casei subsp. casei and L. innocua, nisin was more commonly observed in the cytoplasm. Cell wall disruption and digestion and lysis vesicle formation were common observations among strains exposed to nisin. Immune-TEM observations suggest several modes of action for nisin Z, which may be genus and/or species specific and may include intracellular target-specific activity. It was concluded that nisin-containing liposomes can provide a powerful tool to improve nisin stability and availability in the cheese matrix.
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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".