Unveiling the Broad Substrate Specificity of Deoxynivalenol Oxidation Enzyme DepA and Its Role in Detoxifying Trichothecene Mycotoxins
Bibliographic record
Abstract
mutans 17-2-E-8, exhibits versatility in oxidizing deoxynivalenol (DON) and its derivatives. This study explored DepA's substrate specificity and enzyme kinetics, focusing on DON and 15-acetyl-DON. Besides efficiently oxidizing DON, DepA also transforms 15-acetyl-DON into 15-acetyl-3-keto-DON, as identified via LC-MS/MS and NMR analysis. The kinetic parameters, including the maximum reaction rate, turnover number, and catalytic efficiency, were thoroughly evaluated. DepA-PQQ complex docking was deployed to rationalize the substrate specificity of DepA. This study further delves into the reduced toxicity of the transformation products, as demonstrated via enzyme homology modeling and in silico docking analysis with yeast 80S ribosomes, indicating a potential decrease in toxicity due to lower binding affinity. Utilizing the response surface methodology and central composite rotational design, mathematical models were developed to elucidate the relationship between the enzyme and cofactor concentrations, guiding the future development of detoxification systems for liquid feeds and grain processing. This comprehensive analysis underscores DepA's potential for use in mycotoxin detoxification, offering insights for future applications.
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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".