Quantification of mutation-derived bias for alternate mating functionalities of the<i>Saccharomyces cerevisiae</i>Ste2p pheromone receptor
Bibliographic record
Abstract
Although well documented for mammalian G-protein-coupled receptors, alternate functionalities and associated alternate signalling remain to be unequivocally established for the Saccharomyces cerevisiae pheromone Ste2p receptor. Here, evidence supporting alternate functionalities for Ste2p is re-evaluated, extended and quantified. In particular, strong mating and constitutive signalling mutations, focusing on residues S254, P258 and S259 in TM6 of Ste2p, are stacked and investigated in terms of their effects on classical G-protein-mediated signal transduction associated with cell cycle arrest, and alternatively, their impact on downstream mating projection and zygote formation events. In relative dose response experiments, accounting for systemic and observational bias, mutational-derived functional differences were observed, validating the S254L-derived bias for downstream mating responses and highlighting complex relationships between TM6-mutation derived constitutive signalling and ligand-induced functionalities. Mechanistically, localization studies suggest that alterations to receptor trafficking may contribute to mutational bias, in addition to expected receptor conformational stabilization effects. Overall, these results extend previous observations and quantify the contributions of Ste2p variants to mediating cell cycle arrest versus downstream mating functionalities.
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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 | 0.001 |
| 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".