Molecular mechanisms determining conserved properties of short-term synaptic depression revealed in NSF and SNAP-25 conditional mutants
Bibliographic record
Abstract
Current models of synaptic vesicle trafficking implicate a core complex of proteins comprised of N-ethylmaleimide-sensitive factor (NSF), soluble NSF attachment proteins (SNAPs), and SNAREs in synaptic vesicle fusion and neurotransmitter release. Despite this progress, major challenges remain in establishing the in vivo functions of these proteins and their roles in determining the physiological properties of synapses. The present study employs glutamatergic adult neuromuscular synapses of Drosophila, which exhibit conserved properties of short-term synaptic plasticity with respect to mammalian glutamatergic synapses, to address these issues through genetic analysis. Our findings establish an in vivo role for SNAP-25 in synaptic vesicle priming, and support a zippering model of SNARE function in this process. Moreover, these studies define the contribution of SNAP-25-dependent vesicle priming to the detailed properties of short-term depression elicited by paired-pulse (PP) and train stimulation. In contrast, NSF is shown here not to be required for WT PP depression, but to be critical for maintaining neurotransmitter release during sustained stimulation. In keeping with this role, disruption of NSF function results in activity-dependent redistribution of the t-SNARE proteins, SYNTAXIN and SNAP-25, away from neurotransmitter release sites (active zones). These findings support a role for NSF in replenishing active zone t-SNAREs for subsequent vesicle priming, and provide new insight into the spatial organization of SNARE protein cycling during synaptic activity. Together, the results reported here establish in vivo contributions of SNAP-25 and NSF to synaptic vesicle trafficking and define molecular mechanisms determining conserved functional properties of short-term depression.
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) | 0.000 | 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".