Identification and characterization of components of the <i>Candida albicans</i> inner kinetochore
Bibliographic record
Abstract
Despite the significant global health burden posed by Candida albicans, a large proportion of its genome has yet to be characterized. While insights from model yeasts have historically provided valuable functional clues, their utility is approaching its limits given the increasing evidence of divergence across fungal species. The C. albicans inner kinetochore is a poorly characterized cellular structure. In particular, the constitutive centromere-associated network has only four previously known components, likely due to DNA sequence divergence between orthologous complex members from Saccharomyces cerevisiae or Schizosaccharomyces pombe. Here, we leveraged a structure-focused approach to identify seven components of the C. albicans constitutive centromere-associated network. Phenotypic characterization of loss-of-function mutants confirmed important roles in fitness and cell cycle progression for various kinetochore subunits. Furthermore, protein interactions identified through affinity purification-mass spectrometry as well as confocal microscopy confirmed the interaction and localization of these predicted kinetochore components with known kinetochore members. Overall, this work significantly enhances our understanding of a key cellular structure in C. albicans and underscores the urgent need for pathogen-specific research to better understand its unique biological mechanisms.
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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) | 0.000 | 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".