<i>Saccharomyces cerevisiae</i> strains display robust phenotypes in the presence of Dyskeratosis congenita mutations in the <i>Cbf5</i> gene
Bibliographic record
Abstract
Abstract Dyskeratosis congenita is a rare, congenital disorder affecting the skin, nails and oral mucosa of patients that often progresses to bone marrow failure and an increased predisposition for a variety of carcinomas. Mutations in the human dyskerin gene have been identified as the most prevalent cause of the disease. Dyskerin is a pseudouridine synthase and the catalytic subunit of H/ACA ribonucleoproteins (RNPs) responsible for the modification of uridines to pseudouridine in ribosomal RNA (rRNA), but dyskerin also binds to the telomerase RNA component (TERC). Accordingly, Dyskeratosis congenita mutations have been reported to affect both telomerase function as well as ribosome biogenesis, but the relative contribution of each pathway to the diseases is under debate. As the yeast homolog of dyskerin, Cbf5, does not interact with telomerase RNA, Saccharomyces cerevisiae is an ideal model to identify the selective impact of Dyskeratosis congenita mutations on ribosome biogenesis. Therefore, chromosomal mutations in the yeast homologue of dyskerin, Cbf5, were introduced at positions corresponding to the mutations in human dyskerin that result in Dyskeratosis congenita. To determine if the mutations affect cellular fitness, we screened for growth defects in yeast. Growth curves at different temperatures and yeast spot assays under several stress conditions revealed that the mutations in cbf5 did not impair growth compared to wild type. These findings suggest that in the yeast cell, Dyskeratosis congenita mutations do not significantly affect ribosome biogenesis, and we discuss the implications for understanding the molecular cause of Dyskeratosis congenita.
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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 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".