Transcriptomic and genomic changes associated with radioadaptation in <i>Exophiala dermatitidis</i>
Bibliographic record
Abstract
Melanized fungi have been isolated from some of the harshest radioactive environments, and their ability to thrive in these locations is in part due to the pigment melanin. Melanin imparts a selective advantage to fungi by providing a physical shield, a chemical shield, and possibly a signaling mechanism. In previous work we demonstrated that protracted exposure of the melanized yeast Exophiala dermatitidis to mixed alpha-, beta-, and gamma-emitting radiation resulted in an adapted strain able to mount a unique response to ionizing radiation in the environment in a melanin-dependent fashion. By exploring the genome and transcriptome of this adapted melanized strain relative to a non-irradiated control we determined the altered response was transcriptomic in nature, as whole genome sequencing revealed limited variation. Transcriptomic analysis indicated that of the adapted isolates analyzed, two lineages existed: one like the naïve, non-adapted strain, and one with a unique transcriptomic signature that exhibited downregulation of metabolic processes, and upregulation of translation-associated genes. Analysis of differential gene expression in the adapted strain showed an overlap in response between the control conditions and reactive oxygen species conditions, whereas exposure to an alpha particle source resulted in a robust downregulation of metabolic processes and upregulation of DNA replication and repair genes, and RNA metabolic processes. This suggest previous exposure to radiation primes the fungus to respond to subsequent exposures in a unique way. By exploring this unique response, we have expanded our knowledge of how melanized fungi interact with and respond to ionizing radiation in their environment.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".