A role for a complex between activated G protein-coupled receptors in yeast cellular mating
Bibliographic record
Abstract
Cell-cell fusion is a fundamental process that facilitates a wide variety of biological events in organisms ranging from yeast to humans. However, relatively little is actually understood with respect to fusion mechanisms. In the model organism Saccharomyces cerevisiae, mating of opposite-type cells is triggered by pheromone activation of the G protein-coupled receptors, alpha-factor receptor (Ste2p) and a-factor receptor (Ste3p), leading to mitogen-activated protein kinase signaling, growth arrest, and cellular fusion events. Herein we now provide evidence of a role for these receptors in the later cell fusion stage of mating. In vitro assays demonstrated the ability of the receptors to promote mixing of proteoliposomes containing phosphatidylserine, potentially based on a pheromone-dependent interaction between Ste2p and Ste3p that was confirmed by tandem affinity purification and cellular pull-down assays. The cellular mating activity of Ste2p was subsequently probed in vivo. Notably, a receptor-null yeast strain expressing N-terminally truncated Ste2p yielded a phenotype demonstrating wild-type signaling but arrested mating. The arrested prezygotes showed evidence of some cell wall erosion but no membrane juxtaposition at the fusion site. Further, in vitro analyses correlated this mutation with loss of the interaction between Ste2p and Ste3p and inhibition of related lipid mixing. Overall, these results support a role for a complex between activated yeast pheromone receptors in later cell fusion stages of mating, possibly mediating events at the level of cell wall digestion and membrane juxtaposition before membrane fusion.
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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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".