Defence of Agaricus bisporus against toxic secondary metabolites from Trichoderma aggressivum.
Bibliographic record
Abstract
Trichoderma spp are effective competitors against other fungi because they are mycoparasitic and produce hydrolytic enzymes and secondary metabolites that inhibit the growth of their competitors. Inhibitory compounds produced by Trichoderma aggressivum, the causative agent of green mold disease, are more toxic to the hybrid off-white strains of Agaricus bisporus than the commercial brown strains, consistent with the commercial brown strain’s increased resistance to the disease. This project looked at the response of hybrid off-white and commercial brown strains of A. bisporus to the presence of T. aggressivum metabolites with regard to three A. bisporus genes: laccase 1, laccase 2, and manganese peroxidase. The addition of T. aggressivum toxic metabolites had no significant effect on MnP or lcc1 transcript abundance. Alternatively, laccase 2 appears to be involved in resistance to T. aggressivum because the presence of T. aggressivum metabolites results in higher lcc2 transcript abundance and laccase activity, especially in the commercial brown strain. The difference in laccase expression and activity between A. bisporus strains was not a result of regulatory or coding sequence differences. Alteration of laccase transcription by RNAi resulted in transformants with variable levels of laccase transcript abundance. Transformants with a low number of lcc transcripts were very sensitive to T. aggressivum toxins, while those with a high number of lcc transcripts had increased resistance. These results indicated that laccase activity, in particular that encoded by lcc2, serves as a defense response of A. bisporus to T. aggressivum toxins and contributes to green mold disease resistance in commercial brown strains.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".