The Signaling Mucins Msb2 and Hkr1 Differentially Regulate the Filamentation Mitogen-activated Protein Kinase Pathway and Contribute to a Multimodal Response
Bibliographic record
Abstract
A central question in the area of signal transduction is why pathways utilize common components. In the budding yeast Saccharomyces cerevisiae, the HOG and filamentous growth (FG) MAPK pathways require overlapping components but are thought to be induced by different stimuli and specify distinct outputs. To better understand the regulation of the FG pathway, we examined FG in one of yeast's native environments, the grape-producing plant Vitis vinifera. In this setting, different aspects of FG were induced in a temporal manner coupled to the nutrient cycle, which uncovered a multimodal feature of FG pathway signaling. FG pathway activity was modulated by the HOG pathway, which led to the finding that the signaling mucins Msb2p and Hkr1p, which operate at the head of the HOG pathway, differentially regulate the FG pathway. The two mucins exhibited different expression and secretion patterns, and their overproduction induced nonoverlapping sets of target genes. Moreover, Msb2p had a function in cell polarization through the adaptor protein Sho1p that Hkr1p did not. Differential MAPK activation by signaling mucins brings to light a new point of discrimination between MAPK pathways.
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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".