<i>MFα1</i> , the Gene Encoding the α Mating Pheromone of <i>Candida albicans</i>
Bibliographic record
Abstract
Candida albicans, the single most frequently isolated human fungal pathogen, was thought to be asexual until the recent discovery of the mating-type-like locus (MTL). Homozygous MTL strains were constructed and shown to mate. Furthermore, it has been demonstrated that opaque-phase cells are more efficient in mating than white-phase cells. The similarity of the genes involved in the mating pathway in Saccharomyces cerevisiae and C. albicans includes at least one gene (KEX2) that is involved in the processing of the alpha mating pheromone in the two yeasts. Taking into account this similarity, we searched the C. albicans genome for sequences that would encode the alpha pheromone gene. Here we report the isolation and characterization of the gene MFalpha1, which codes for the precursor of the alpha mating pheromone in C. albicans. Two active alpha-peptides, 13 and 14 amino acids long, would be generated after the precursor molecule is processed in C. albicans. To examine the role of this gene in mating, we constructed an mfalpha1 null mutant of C. albicans. The mfalpha1 null mutant fails to mate as MTLalpha, while MTLa mfalpha1 cells are still mating competent. Experiments performed with the synthetic alpha-peptides show that they are capable of inducing growth arrest, as demonstrated by halo tests, and also induce shmooing in MTLa cells of C. albicans. These peptides are also able to complement the mating defect of an MTLalpha kex2 mutant strain when added exogenously, thereby confirming their roles as alpha mating pheromones.
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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".