Molecular role of the Ste50 adaptor protein in regulating mating-pheromone signaling specificity in «Saccharomyces cerevisiae»
Bibliographic record
Abstract
Living cells are continuously receiving stimuli from their external environments to bring out biological responses required for growth, maintenance and safety.Cells realize this through a network of signaling pathways that are dedicated to produce precise biological responses.Because pathways often share components, a fundamental question in the field of signal transduction is how the myriads of inputs are sensed, integrated and transduced accurately so that each elicits a specific and proper biological response.In the yeast Saccharomyces cerevisiae, three major mitogen activated protein kinase (MAPK) pathways, which control the mating process in response to pheromone, the glycerol production in response to hyperosmotic stress and the filamentous growth in response to nutrient deprivation, share a common Ste11MAP3K and an adaptor protein Ste50, which has an N-terminal SAM (sterile alpha motif) domain and a C-terminal RA (Rasassociation) domain.Ste11 and Ste50 interact through their respective SAM domains.The role of C-terminal Ste50-RA domain in conferring signaling specificity in the hyperosmolar glycerol and filamentous growth pathways has been established, however, the mechanism through which the Ste50-RA domain connects the mating pathway remains unknown.In this dissertation, I have demonstrated that RA domain of Ste50 adaptor protein uses genetically separable surfaces to differentially connect to distinct MAPK signaling pathways.Using random mutagenesis, I built and screened Ste50-RA domain mutant libraries and identified mutants with interesting phenotypes.The mutants were grouped into three classes displaying defects specific to the mating pathway, or to the HOG pathway, or to both signaling pathways.The RA domain residues involved in these different mutant classes, when mapped onto the solution structure of the folded RA domain, showed distinct structural localizations and clustering according to their phenotypic traits.Analyses with structural meta-prediction tools indicate that all these residues showed a high propensity to engage in protein-protein interactions.I further performed microscopic studies with GFP fusions of the different Ste50 alleles in cells under pheromone stimulation, and iii showed that wild type Ste50 accumulates at the polarization front of the shmoo structure, while the specifically pheromone response defective mutants are unable to form shmoos and fail to accumulate Ste50 at the polarized shmoo tip, indicating a loss of association of the ste50 mutants with the shmoo polarization complex.These results suggest that Ste50-RA domain uses differential interactions to connect different MAPK pathways to exert early layer control of signaling specificity.Subsequently, in detailed microscopic studies, I showed the dynamic cellular localization of the wild type Ste50 protein, as well as the location of the specifically-pheromone-signalingdefective Ste50 mutant protein.The mutant showed a strong defect in its dynamic cellular localization, suggesting a link between this localization and proper function of Ste50 in mating pheromone signaling.Finally, I performed a suppressor study to find genetic suppressor of the specificallypheromone-response-defective mutants.I expected that overexpressing some regulator(s) of Ste50 might identify suppressors that can compensate for the functional defects of these mutants.The genetic screen identified RIE1 as a Ste50 mutant dependent suppressor of the pheromone signaling pathway.Deleting RIE1 caused defective pheromone signaling, aberrant shmoo morphology and defective cell cycle arrest.These results suggest that RIE1 is a new component of the mating-pheromone response pathway.
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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) | 0.003 | 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".