Dilated cardiomyopathy variant R14del increases phospholamban pentamer stability, blunting dynamic regulation of calcium
Bibliographic record
Abstract
The sarco(endo)plasmic reticulum Ca 2+ ATPase (SERCA) is a membrane transporter that creates and maintains intracellular Ca 2+ stores. In the heart, SERCA is regulated by an inhibitory interaction with the monomeric form of the transmembrane micropeptide phospholamban (PLB). PLB also forms avid homo-pentamers, and the dynamic exchange of PLB between pentamers and SERCA is an important determinant of cardiac responsiveness to exercise. Here, we investigated two naturally occurring pathogenic variants of PLB: a cysteine substitution of Arg9 (R9C) and an in-frame deletion of Arg14 (R14del). Both variants are associated with dilated cardiomyopathy. We previously showed that the R9C mutation causes disulfide crosslinking and hyperstabilization of pentamers. While the pathogenic mechanism of R14del is unclear, we hypothesized this mutation may also alter pentamer stability. Immunoblots revealed a significantly increased pentamer: monomer ratio for R14del-PLB compared to WT-PLB. We quantified homo-oligomerization and SERCA-binding in live cells using fluorescence resonance energy transfer (FRET) microscopy. R14del-PLB showed an increased affinity for homo-oligomerization and decreased binding affinity for SERCA compared to WT. The data suggest that, like R9C, the R14del mutation stabilizes PLB in pentamers, decreasing its ability to regulate SERCA. The R14del mutation reduced the rate of PLB unbinding from pentamers after transient elevations of Ca 2+ , limiting the recovery of PLB-SERCA complexes. A computational model predicted that hyperstabilization of PLB pentamers by R14del impairs the ability of cardiac Ca 2+ handling to respond to changing heart rates between rest and exercise. We postulate that impaired responsiveness to physiological stress contributes to arrhythmogenesis in human carriers of the R14del mutation.
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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) | 0.001 | 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".