Transcriptomic analysis of melanin production in <i>Exophiala dermatitidis</i> conditional albino mutants on two different carbon sources
Bibliographic record
Abstract
Abstract Exophiala dermatitidis is a polymorphic black yeast found in various habitats and man-made environments such as soil, sinks and saunas. Melanin plays a key role in E. dermatitidis virulence and environmental adaptation. The E. dermatitidis genome sequence has revealed the presence of genes responsible for production of melanin via three different pathways (1,8-DHN melanin, DOPA melanin, and pyomelanin) but besides DHN melanin not much is known about the activation of the other pathways. Our previous work identified three conditional albino mutants ( alb1 , alb2 and alb3 ) that can recover melanin production despite mutation in PKS1 . In this study RNA Transcriptomics was used as a tool to investigate gene expression differences between the three conditional albinos, two obligate albinos ( alb10 and alb12 ) and wildtype to account for variation in melanization using two treatments (dextrose and galactose) as carbon sources. Differential gene expression analysis revealed a higher number of significantly upregulated genes in the conditional albinos on galactose (YPG) compared to the obligate albinos. Overrepresentation analysis revealed a higher number of significantly enriched GO terms in the conditional albinos compared to the wildtype and the obligate albinos. Multiple genes involved in 1,8-DHN melanin and pyomelanin were also found to be upregulated on YPG in the conditional albinos. Besides genes involved in melanization, genes involved in various aspects of cell wall regulation were also upregulated on YPG. To this date this is the first study that has demonstrated the activation of genes involved in multiple different melanin pathways in E. dermatitidis grown on different carbon sources.
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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) | 0.001 | 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".