Calpain-2 specifically cleaves Junctophilin-2 at the same site as Calpain-1 but with less efficacy
Bibliographic record
Abstract
Calpain proteolysis contributes to the pathogenesis of heart failure but the calpain isoforms responsible and their substrate specificities have not been rigorously defined. One substrate, Junctophilin-2 (JP2), is essential for maintaining junctional cardiac dyads and excitation-contraction coupling. We previously demonstrated that mouse JP2 is cleaved by calpain-1 (CAPN1) between Arginine 565 (R565) and Threonine 566 (T566). Recently, calpain-2 (CAPN2) was reported to cleave JP2 at a novel site between Glycine 482 (G482) and Threonine 483 (T483). We aimed to directly compare the contributions of each calpain isoform, their Ca2+ sensitivity, and their cleavage site selection for JP2. We find CAPN1, CAPN2 and their requisite CAPNS1 regulatory subunit are induced by pressure overload stress that is concurrent with JP2 cleavage. Using in vitro calpain cleavage assays, we demonstrate that CAPN1 and CAPN2 cleave JP2 into similar 75 kD N-terminal (JP2NT) and 25 kD C-terminal fragments (JP2CT) with CAPNS1 co-expression enhancing proteolysis. Deletion mutagenesis shows both CAPN1 and CAPN2 require R565/T566 but not G482/T483. When heterologously expressed, the JP2CT peptide corresponding to R565/T566 cleavage approximates the 25 kD species found during cardiac stress while the C-terminal peptide from potential cleavage at G482/T483 produces a 35 kD product. Similar results were obtained for human JP2. Finally, we show that CAPN1 has higher Ca2+ sensitivity and cleavage efficacy than CAPN2 on JP2 and other cardiac substrates including cTnT, cTnI and β2-spectrin. We conclude that CAPN2 cleaves JP2 at the same functionally conserved R565/T566 site as CAPN1 but with less efficacy and suggest heart failure may be targeted through specific inhibition of CAPN1.
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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 | 0.000 | 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".