KvLQT1 Modulates the Distribution and Biophysical Properties of HERG
Bibliographic record
Abstract
Cardiac repolarization is under joint control of the slow (IKs) and rapid (IKr) delayed rectifier currents. Experimental and clinical evidence indicates important functional interactions between these components. We hypothesized that there might be more direct interactions between the KvLQT1 and HERG alpha-subunits of IKs and IKr and tested this notion with a combination of biophysical and biochemical techniques. Co-expression of KvLQT1 with HERG in a mammalian expression system significantly accelerated HERG current deactivation at physiologically relevant potentials by increasing the contribution of the fast component (e.g. upon repolarization from +20 mV to -50 mV: from 20 +/- 3 to 32 +/- 5%, p < 0.05), making HERG current more like native IKr. In addition, HERG current density was approximately doubled (e.g. tail current after a step to +10 mV: 18 +/- 3 versus 39 +/- 7 pA/picofarad, p < 0.01) by co-expression with KvLQT1. KvLQT1 co-expression also increased the membrane immunolocalization of HERG by approximately 2-fold (p < 0.05). HERG and KvLQT1 co-immunolocalized in canine ventricular myocytes and co-immunoprecipitated in cultured Chinese hamster ovary cells as well as in native cardiac tissue, indicating physical interactions between HERG and KvLQT1 proteins in vitro and in vivo. Protein interaction assays also demonstrated binding of KvLQT1 (but not another K+ channel alpha-subunit, Kv3.4) to a C-terminal HERG glutathione S-transferase fusion protein. Co-expression with HERG did not affect the membrane localization or ionic current properties of KvLQT1. This study shows that the alpha-subunit of IKs can interact with and modify the localization and current-carrying properties of the alpha-subunit of IKr, providing potentially novel insights into the molecular function of the delayed rectifier current system.
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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 | 0.001 |
| 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".