C2 Domains of Munc13-4 Are Crucial for Ca2+-Dependent Degranulation and Cytotoxicity in NK Cells
Bibliographic record
Abstract
Abstract In the immune system, degranulation/exocytosis from lymphocytes is crucial for life through facilitating eradication of infected and malignant cells. Dysfunction of the NK cell exocytosis process has been implicated with devastating immune diseases, such as familial hemophagocytic lymphohistiocytosis, yet the underlying molecular mechanisms of such processes have remained elusive. In particular, although the lytic granule exocytosis from NK cells is strictly Ca2+-dependent, the molecular identity of the Ca2+ sensor has yet to be identified. In this article, we show multiple lines of evidence in which point mutations in aspartic acid residues in both C2 domains of human Munc13-4, whose mutation underlies familial hemophagocytic lymphohistiocytosis type 3, diminished exocytosis with dramatically altered Ca2+ sensitivity in both mouse primary NK cells as well as rat mast cell lines. Furthermore, these mutations within the C2 domains severely impaired NK cell cytotoxicity against malignant cells. Total internal reflection fluorescence microscopy analysis revealed that the mutations strikingly altered Ca2+ dependence of fusion pore opening of each single granule and frequency of fusion events. Our results demonstrate that both C2 domains of Munc13-4 play critical roles in Ca2+-dependent exocytosis and cytotoxicity by regulating single-granule membrane fusion dynamics in immune cells.
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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) | 0.001 | 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".