Characterization of RNA Helicase Genes in Ustilago maydis Reveals Links to Stress Response and Teliospore Dormancy
Bibliographic record
Abstract
Fungi produce dormant structures that are responsible for protection during adverse environmental conditions and dispersal (disease spread). Ustilago maydis, a basidiomycete plant pathogen, is a model for understanding the molecular mechanisms of teliospore dormancy and germination. Dormant teliospores store components required for germination including mRNAs which may be stored as dsRNAs. RNA helicases are conserved enzymes that function to modulate, bind, and unwind RNA duplexes, and can displace other proteins. We hypothesize that RNA helicases function during teliospore dormancy to stabilize and/or modulate stored mRNAs. We identified the U. maydis udbp3 and uded1 as encoding RNA helicases of interest as they are upregulated in the dormant teliospore and decrease during germination. Experimental results suggest that udbp3 may function as a negative regulator of osmotic stress-responsive genes and that uded1 modulates stress response by repressing translation. The altered expression of uded1 also results in slow growth, polarized growth, and the formation of dsRNA. Together, the data support a role for both helicases modulating gene expression, in response to stress, leading to teliospore dormancy and also modulating responses for teliospore germination. Increasing our molecular understanding of these processes will aid in developing novel strategies to mitigate disease spread.
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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 | 0.001 | 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".