Chitinase and β-1,3-glucanase enzyme production by the mycoparasite<i>Clonostachys rosea</i>f.<i>catenulata</i>against fungal plant pathogens
Bibliographic record
Abstract
Clonostachys rosea f. catenulata (syn. Gliocladium catenulatum) is an effective fungal biological agent against Fusarium root and stem rot and Pythium damping-off diseases on cucumber plants. Both chitinase and beta-1,3-glucanase enzymes were produced when C. rosea was grown on a synthetic medium containing chitin or laminarin as a sole carbon source, respectively. Chitinase production was also induced by Fusarium cell walls, while beta-1,3-glucanase activity was induced by both Fusarium and Pythium cell walls, as well as by growth on homogenized cucumber roots and on low-carbon media. Mycelial growth of Fusarium and Pythium, when exposed to C. rosea culture filtrates that contain glucanase activity, was significantly reduced compared with the controls, and cell walls of both pathogens were degraded. On excised cucumber roots, hyphae of C. rosea formed appressorium-like structures and coiled around hyphae of Pythium. In culture, C. rosea caused localized degradation of Fusarium hyphae. Cucumber root tissues colonized by C. rosea showed higher levels of beta-1,3-glucanase activity at 7 days post-application compared with untreated controls. To determine if this activity was derived from C. rosea, glucanase isoforms were separated on activity gels. Fungal culture filtrates and root extracts contained the same predominant 20 kDa isoform. Reverse-transcription polymerase chain reaction (RT-PCR) using primers designed to amplify a beta-1,3-glucanase gene in C. rosea confirmed glucanase expression on roots. These results show that C. rosea produces beta-1,3-glucanase in situ, which can degrade hyphae of Fusarium and Pythium and contribute to biological control efficacy.
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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 | 0.000 |
| 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".