Conformational states of syntaxin-1 govern the necessity of N-peptide binding in exocytosis of PC12 cells and <i>Caenorhabditis elegans</i>
Bibliographic record
Abstract
Syntaxin-1 is the central SNARE protein for neuronal exocytosis. It interacts with Munc18-1 through its cytoplasmic domains, including the N-terminal peptide (N-peptide). Here we examine the role of the N-peptide binding in two conformational states ("closed" vs. "open") of syntaxin-1 using PC12 cells and Caenorhabditis elegans. We show that expression of "closed" syntaxin-1A carrying N-terminal single point mutations (D3R, L8A) that perturb interaction with the hydrophobic pocket of Munc18-1 rescues impaired secretion in syntaxin-1-depleted PC12 cells and the lethality and lethargy of unc-64 (C. elegans orthologue of syntaxin-1)-null mutants. Conversely, expression of the "open" syntaxin-1A harboring the same mutations fails to rescue the impairments. Biochemically, the L8A mutation alone slightly weakens the binding between "closed" syntaxin-1A and Munc18-1, whereas the same mutation in the "open" syntaxin-1A disrupts it. Our results reveal a striking interplay between the syntaxin-1 N-peptide and the conformational state of the protein. We propose that the N-peptide plays a critical role in intracellular trafficking of syntaxin-1, which is dependent on the conformational state of this protein. Surprisingly, however, the N-peptide binding mode seems dispensable for SNARE-mediated exocytosis per se, as long as the protein is trafficked to the plasma membrane.
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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".