<i>Candida albicans</i> Is Resistant to Polyglutamine Aggregation and Toxicity
Bibliographic record
Abstract
Disruption of protein quality control can be detrimental, having toxic effects on single cell organisms and contributing to neurodegenerative diseases such as Alzheimer's, Parkinson's and Huntington's in humans. Here, we examined the effects of polyglutamine (polyQ) aggregation in a major fungal pathogen of humans, Candida albicans, with the goal of identifying new approaches to disable this fungus. However, we discovered that expression of polyQ stretches up to 230Q had no effect on C. albicans ability to grow and withstand proteotoxic stress. Bioinformatics analysis demonstrates that C. albicans has a similarly glutamine-rich proteome to the unicellular fungus Saccharomyces cerevisiae, which exhibits polyQ toxicity with as few as 72Q. Surprisingly, global transcriptional profiles indicated no significant change upon induction of up to 230Q. Proteomic analysis highlighted two key interactors of 230Q, Sis1 and Sgt2; however, loss of either protein had no additional effect on C. albicans toxicity. Our data suggest that C. albicans has evolved powerful mechanisms to overcome the toxicity associated with aggregation-prone proteins, providing a unique model for studying polyQ-associated diseases.
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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 | 0.001 | 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".