GEF-H1 Transduces FcεRI Signaling in Mast Cells to Activate RhoA and Focal Adhesion Formation during Exocytosis
Bibliographic record
Abstract
When antigen-stimulated, mast cells release preformed inflammatory mediators stored in cytoplasmic granules. This occurs via a robust exocytosis mechanism termed degranulation. Our previous studies revealed that RhoA and Rac1 are activated during mast cell antigen stimulation and are required for mediator release. Here, we show that the RhoGEF, GEF-H1, acts as a signal transducer of antigen stimulation to activate RhoA and promote mast cell spreading via focal adhesion (FA) formation. Cell spreading, granule movement, and exocytosis were all reduced in antigen-stimulated mast cells when GEF-H1 was depleted by RNA interference. GEF-H1-depleted cells also showed a significant reduction in RhoA activation, resulting in reduced stress fiber formation without altering lamellipodia formation. Ectopic expression of a constitutively active RhoA mutant restored normal morphology in GEF-H1-depleted cells. FA formation during antigen stimulation required GEF-H1, suggesting it is a downstream target of the GEF-H1-RhoA signaling axis. GEF-H1 was activated by phosphorylation in conjunction with antigen stimulation. Syk kinase is linked to the FcεRI signaling pathway and the Syk inhibitor, GS-9973, blocked GEF-H1 activation and also suppressed cell spreading, granule movement, and exocytosis. We concluded that during FcεRI receptor stimulation, GEF-H1 transmits signals to RhoA activation and FA formation to facilitate the exocytosis mechanism.
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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".