Localization and Mobility of Synaptic Vesicles in Myosin VI Mutants of Drosophila
Bibliographic record
Abstract
BACKGROUND: At the Drosophila neuromuscular junction (NMJ), synaptic vesicles are mobile; however, the mechanisms that regulate vesicle traffic at the nerve terminal are not fully understood. Myosin VI has been shown to be important for proper synaptic physiology and morphology at the NMJ, likely by functioning as a vesicle tether. Here we investigate vesicle dynamics in Myosin VI mutants of Drosophila. RESULTS: In Drosophila, Myosin VI is encoded by the gene, jaguar (jar). To visualize active vesicle cycling we used FM dye loading and compared loss of function alleles of jar with controls. These studies revealed a differential distribution of vesicles at the jar mutant nerve terminal, with the newly endocytosed vesicles observed throughout the mutant boutons in contrast to the peripheral localization visualized at control NMJs. This finding is consistent with a role for Myosin VI in restraining vesicle mobility at the synapse to ensure proper localization. To further investigate regulation of vesicle dynamics by Myosin VI, FRAP analysis was used to analyze movement of GFP-labeled synaptic vesicles within individual boutons. FRAP revealed that synaptic vesicles are moving more freely in the jar mutant boutons, indicated by changes in initial bleach depth and rapid recovery of fluorescence following photobleaching. CONCLUSION: This data provides insights into the role for Myosin VI in mediating synaptic vesicle dynamics at the nerve terminal. We observed mislocalization of actively cycling vesicles and an apparent increase in vesicle mobility when Myosin VI levels are reduced. These observations support the notion that a major function of Myosin VI in the nerve terminal is tethering synaptic vesicles to proper sub-cellular location within the bouton.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".