The Gab1 Docking Protein Links the B Cell Antigen Receptor to the Phosphatidylinositol 3-Kinase/Akt Signaling Pathway and to the SHP2 Tyrosine Phosphatase
Bibliographic record
Abstract
B cell antigen receptor (BCR) signaling causes tyrosine phosphorylation of the Gab1 docking protein. This allows phosphatidylinositol 3-kinase (PI3K) and the SHP2 tyrosine phosphatase to bind to Gab1. In this report, we tested the hypothesis that Gab1 acts as an amplifier of PI3K- and SHP2-dependent signaling in B lymphocytes. By overexpressing Gab1 in the WEHI-231 B cell line, we found that Gab1 can potentiate BCR-induced phosphorylation of Akt, a PI3K-dependent response. Gab1 expression also increased BCR-induced tyrosine phosphorylation of SHP2 as well as the binding of Grb2 to SHP2. We show that the pleckstrin homology (PH) domain of Gab1 is required for BCR-induced phosphorylation of Gab1 and for Gab1 participation in BCR signaling. Moreover, using confocal microscopy, we show that BCR ligation can induce the translocation of Gab1 from the cytosol to the plasma membrane and that this requires the Gab1 PH domain as well as PI3K activity. These findings are consistent with a model in which the binding of the Gab1 PH domain to PI3K-derived lipids brings Gab1 to the plasma membrane, where it can be tyrosine-phosphorylated and then act as an amplifier of BCR signaling.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".