Distinct Recruitment and Function of Gab1 and Gab2 in Met Receptor-mediated Epithelial Morphogenesis
Bibliographic record
Abstract
The Gab family of docking proteins (Gab1 and Gab2) are phosphorylated in response to various cytokines and growth factors. Gab1 acts to diversify the signal downstream from the Met receptor tyrosine kinase through the recruitment of multiple signaling proteins, and is essential for epithelial morphogenesis. To determine whether Gab1 and Gab2 are functionally redundant, we have examined the role of Gab2 in epithelial cells. Both Gab1 and Gab2 are expressed in epithelial cells and localize to cell-cell junctions. However, whereas overexpression of Gab1 promotes a morphogenic response, the overexpression of Gab2 fails to induce this response. We show that Gab2 recruitment to the Met receptor is dependent on the Grb2 adapter protein. In contrast, Gab1 recruitment to Met is both Grb2 dependent and Grb2 independent. The latter requires a novel amino acid sequence present in the Met-binding domain of Gab1 but not Gab2. Mutation of these residues in Gab1 impairs both association with the Met receptor and the ability of Gab1 to promote a morphogenic response, whereas their insertion into Gab2 increases Gab2 association with Met, but does not confer on Gab2 the ability to promote epithelial morphogenesis. We propose that the Grb2-independent recruitment of Gab proteins to Met is necessary but not sufficient to promote epithelial morphogenesis.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".