Calsequestrin, a new modulator of unfolded protein response in skeletal and cardiac muscle
Bibliographic record
Abstract
Cellular responses to stress are an integral part of muscle physiology and pathology. To deal with stress, cardiac and skeletal muscle cells utilize various mechanisms, engaging intercellular organelles including the endoplasmic reticulum/sarcoplasmic reticulum (ER/SR) [1]. The disruptions of ER functions are often observed in ischemic, hypertrophic and failing hearts [1]. However, the molecular mechanisms governing muscle ER stress regulation in the muscle are still unclear. Disruption of ER/SR hemostasis with physiological and pathological stimuli triggers a coping response, so called unfolded protein response (UPR). One of the UPR signaling pathways involves stress sensor inositol‐requiring enzyme 1α (IRE1α), an integral ER/SR membrane protein kinase and mRNA splicing enzyme. Here, we discovered that calsequestrin, a muscle Ca 2+ binding protein localized to junctional SR, interacts with UPR stress sensor IRE1α, and contribute to the modulation of stress responses in the muscle. Both skeletal and cardiac isoforms of calsequestrin bind directly to IRE1α as measured by Microscale Thermophoresis (MST), Surface Plasmon Resonance (SPR), and His‐tag Ni‐NTA‐agarose pull down techniques. Although calsequestrin contains three thioredoxin‐like domains its interaction with IRE1α did not involve cysteine residues in IRE1α. Iodixanol gradient fractionation and immunostaining of skeletal muscle sections or isolated cardiomyocytes showed enrichment of IRE1α protein in junctional SR where it is colocalized with calsequestrin. MST analysis revealed that calsequestrin binding to IRE1α has inhibitory effect on IRE1α by preventing dimerization/oligomerization IRE1α required for X‐box binding protein 1 (XBP1) splicing activity. Consequently, cardiac calsequestrin‐deficient cardiomyocytes have increased activity of IRE1α. We concluded that calsequestrin is a new IRE1α binding partner and the protein plays a role in modulation of stress responses in skeletal and cardiac muscle. Support or Funding Information Canada Institutes of Health Research (CIHR) This abstract is from the Experimental Biology 2018 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .
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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".