Differential curvature sensing and generating activities of dynamin isoforms provide opportunities for tissue-specific regulation
Bibliographic record
Abstract
Dynamin 1 (Dyn1) and Dyn2 are neuronal and ubiquitously expressed isoforms, respectively, of the multidomain GTPase required for clathrin-mediated endocytosis (CME). Although they are 79% identical, Dyn1 and Dyn2 are not fully functionally redundant. Through direct measurements of basal and assembly-stimulated GTPase activities, membrane binding, self-assembly, and membrane fission on planar and curved templates, we have shown that Dyn1 is an efficient curvature generator, whereas Dyn2 is primarily a curvature sensor. Using Dyn1/Dyn2 chimeras, we identified the lipid-binding pleckstrin homology domain as being responsible for the differential in vitro properties of these two isoforms. Remarkably, their in vitro activities were reversed by a single amino acid change in the membrane-binding variable loop 3. Reconstitution of KO mouse embryo fibroblasts showed that both the pleckstrin homology and the Pro/Arg-rich domains determine the differential abilities of these two isoforms to support CME. These domains are specific to classical dynamins and are involved in regulating their activity. Our findings reveal opportunities for fundamental differences in the regulation of Dyn1, which mediates rapid endocytosis at the synapse, vs. Dyn2, which regulates early and late events in CME in nonneuronal 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) | 0.000 | 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".