Modular Dispensability of Dysferlin C2 Domains Reveals Rational Design for Mini-dysferlin Molecules
Post-publication record
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Bibliographic record
Abstract
Dysferlin is a large transmembrane protein composed of a C-terminal transmembrane domain, two DysF domains, and seven C2 domains that mediate lipid- and protein-binding interactions. Recessive loss-of-function mutations in dysferlin lead to muscular dystrophies, for which no treatment is currently available. The large size of dysferlin precludes its encapsulation into an adeno-associated virus (AAV), the vector of choice for gene delivery to muscle. To design mini-dysferlin molecules suitable for AAV-mediated gene transfer, we tested internally truncated dysferlin constructs, each lacking one of the seven C2 domains, for their ability to localize to the plasma membrane and to repair laser-induced plasmalemmal wounds in dysferlin-deficient human myoblasts. We demonstrate that the dysferlin C2B, C2C, C2D, and C2E domains are dispensable for correct plasmalemmal localization. Furthermore, we show that the C2B, C2C, and C2E domains and, to a lesser extent, the C2D domain are dispensable for dysferlin membrane repair function. On the basis of these results, we designed small dysferlin molecules that can localize to the plasma membrane and reseal laser-induced plasmalemmal injuries and that are small enough to be incorporated into AAV. These results lay the groundwork for AAV-mediated gene therapy experiments in dysferlin-deficient mouse models.
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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) | 0.001 | 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 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".