Mast cell granule motility and exocytosis is driven by dynamic microtubule formation and kinesin-1 motor function
Bibliographic record
Abstract
Mast cells are tissue-resident immune cells that have numerous cytoplasmic granules which contain preformed pro-inflammatory mediators. Upon antigen stimulation, sensitized mast cells undergo profound changes to their morphology and rapidly release granule mediators by regulated exocytosis, also known as degranulation. We have previously shown that Rho GTPases regulate exocytosis, which suggests that cytoskeleton remodeling is involved in granule transport. Here, we used live-cell imaging to analyze cytoskeleton remodeling and granule transport in real-time as mast cells were antigen stimulated. We found that granule transport to the cell periphery was coordinated by de novo microtubule formation and not F-actin. Kinesore, a drug that activates the microtubule motor kinesin-1 in the absence of cargo, inhibited microtubule-granule association and significantly reduced exocytosis. Likewise, shRNA knock-down of Kif5b, the kinesin-1 heavy chain, also reduced exocytosis. Imaging showed granules accumulated in the perinuclear region after kinesore treatment or Kif5b knock-down. Complete microtubule depolymerization with nocodazole or colchicine resulted in the same effect. A biochemically enriched granule fraction showed kinesin-1 levels increase in antigen-stimulated cells, but are reduced by pre-treatment with kinesore. Kinesore had no effect on the levels of Slp3, a mast cell granule cargo adaptor, in the granule-enriched fraction which suggests that cargo adaptor recruitment to granules is independent of motor association. Taken together, these results show that granules associate with microtubules and are driven by kinesin-1 to facilitate exocytosis.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.001 | 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 teacher head, 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".