Cell Surface Expression of Human Ether-a-go-go-related Gene (hERG) Channels Is Regulated by Caveolin-3 Protein via the Ubiquitin Ligase Nedd4-2
Bibliographic record
Abstract
The human ether-a-go-go-related gene (hERG) encodes the rapidly activating delayed rectifier potassium channel (I(Kr)) which plays an important role in cardiac repolarization. A reduction or increase in hERG current can cause long or short QT syndrome, respectively, leading to fatal cardiac arrhythmias. The channel density in the plasma membrane is a key determinant of the whole cell current amplitude. To gain insight into the molecular mechanisms for the regulation of hERG density at the plasma membrane, we used whole cell voltage clamp, Western blotting, and immunocytochemical methods to investigate the effects of an integral membrane protein, caveolin-3 (Cav3) on hERG expression levels. Our data demonstrate that Cav3, hERG, and ubiquitin-ligase Nedd4-2 interact with each other and form a complex. Expression of Cav3 thus enhances the hERG-Nedd4-2 interaction, leading to an increased ubiquitination and degradation of mature, plasma-membrane localized hERG channels. Disrupting Nedd4-2 interaction with hERG by mutations eliminates the effects of Cav3 on hERG channels. Knockdown of endogenous Cav3 or Nedd4-2 in cultured neonatal rat ventricular myocytes using siRNA led to an increase in native I(Kr). Our data demonstrate that hERG expression in the plasma membrane is regulated by Cav3 via Nedd4-2. These findings extend our understanding of the regulation of hERG channels and cardiac electrophysiology.
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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".