The divergence of DHN-derived melanin pathways in <i>Metarhizium robertsii</i>
Bibliographic record
Abstract
Abstract The important role of dihydroxynaphthalene-(DHN) melanin in enhancing fungal stress resistance and its importance in fungal development and pathogenicity are well-established. This melanin also aids biocontrol fungi in surviving in the environment and effectively infecting insects. However, the biosynthetic origin of melanin in the biocontrol agents, Metarhizium spp., has remained elusive due to the complexity resulting from the divergence of two DHN-like biosynthetic pathways. Through the heterologous expression of biosynthetic enzymes from these two pathways in baker’s yeast Saccharomyces cerevisiae , we have confirmed the presence of DHN biosynthesis in M. roberstii , and discovered a novel naphthopyrone intermediate that can produce a different type of pigment. These two pigment biosynthetic pathways differ in terms of polyketide intermediate structures and subsequent modification steps. Stress resistance studies using recombinant yeast cells have demonstrated that both DHN and its intermediates confer resistance against UV light prior to polymerization; a similar result was observed for its naphthopyrone counterpart. This study contributes to the understanding of the intricate and diverse biosynthetic mechanisms of fungal melanin and has the potential to enhance the application efficiency of biocontrol fungi such as Metarhizium spp. in agriculture.
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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) | 0.000 | 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 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".