Role of thiols and ascladiol production in patulin degradation by lactobacilli
Bibliographic record
Abstract
Patulin is a mycotoxin contaminant in various foods with apple products being its major dietary source. Yeast can reduce patulin levels during fermentation via biotransformation and thiol-adduct formation, with the ability of patulin to react with thiols being well known. Conversion of patulin to ascladiol by lactobacilli has been sparsely reported, while the contribution of thiols in reduction of patulin levels by lactobacilli remains undocumented. In this study, 11 strains of lactobacilli were screened for ascladiol formation in apple juice fermentation. Highest bioconversion was obtained for Lactiplantibacillus plantarum strains followed by Levilactobacillus brevis TMW1.465. Ascladiol production was also detected in several other lactobacilli species albeit in trace amounts. Reduction in patulin levels by Fructilactobacillus sanfranciscensis DMS 20451 and its glutathione reductase (ΔgshR) negative mutant was also assayed to determine the contribution of thiols. The hydrocinnamic acid reductase of Furfurilactobacillus milii did not contribute to reduction of patulin levels. In conclusion, this study demonstrated the potential of various lactobacilli in reduction of patulin levels via biotransformation of patulin to ascladiol, while also providing evidence for the role of thiol formation by lactobacilli and its presence in reducing patulin levels during fermentation.
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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".