Proteomic and functional mapping of cardiac Na <sub>V</sub> 1.5 channel phosphorylation reveals multisite regulation of surface expression and gating
Bibliographic record
Abstract
Abstract Phosphorylation of Na V 1.5 channels regulates cardiac excitability, yet the phosphorylation sites regulating channel function and the underlying mechanisms remain largely unknown. Using a systematic quantitative phosphoproteomic approach, we analyzed Na V 1.5 channel complexes purified from non-failing and failing mouse left ventricles, and we identified 42 phosphorylation sites on Na V 1.5. Most sites are clustered, and three of these clusters are highly phosphorylated. Analyses of phosphosilent and phosphomimetic Na V 1.5 mutants revealed the roles of three phosphosites in regulating Na V 1.5 channel expression and gating. The phosphorylated serines-664 and -667 regulate the voltage-dependence of channel activation in a cumulative manner, whereas phosphorylation of the nearby serine-671, which is increased in failing hearts, decreases cell surface Na V 1.5 expression and peak Na + current. No additional roles could be assigned to the other clusters of phosphosites. Taken together, the results demonstrate that ventricular Na V 1.5 is highly phosphorylated, and that the phosphorylation-dependent regulation of Na V 1.5-encoded channels is highly complex, site-specific and dynamic. Abbreviations A, alanine; E, glutamate; HEK-293, Human Embryonic Kidney 293 cells; I Na , peak Na + current; I NaL , late Na + current; IP, immunoprecipitation; mαNa V PAN, anti-Na V channel subunit mouse monoclonal antibody; MS, Mass Spectrometry; MS1, mass spectrum of peptide precursors; MS2 or MS/MS, fragmentation mass spectrum of peptides selected in narrow mass range (2 Da) from MS1 scan; Na V , voltage-gated Na + channel; pS, phosphoserine; pT, phosphothreonine; S, serine; T, threonine; TAC, Transverse Aortic Constriction; TMT, Tandem Mass Tag.
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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".