Abstract 14048: Snf1-related Kinase Improves Cardiac Metabolic Efficiency through a Decrease in Mitochondrial Uncoupling
Bibliographic record
Abstract
Introduction: Snf1-related Kinase (SNRK) is a serine/threonine kinase with sequence similarity to AMP-activated protein kinase, but its function is unknown. We found that SNRK is increased in hearts from patients with ischemic cardiomyopathy, and our gene array data suggested that SNRK alters metabolic genes. Here, we assessed the hypothesis that SNRK regulates cardiac metabolic efficiency. Results: Transgenic (TG) mice with cardiac-specific overexpression of SNRK were generated, and displayed decreased glycolysis (1267.66 vs. 1925.60 nmol/min/g, n=6), glucose oxidation (441.73 vs. 602.68 nmol/min/g), and palmitate oxidation (262.39 vs. 385.07 nmol/min/g) compared to wild type littermate controls in perfused working hearts. However, cardiac power, contractility, ATP, and triglyceride and glycogen stores were maintained, while oxygen consumption was reduced, suggesting that SNRK TG mice have increased metabolic efficiency. The hearts also exhibited decreased uncoupling protein 3 (UCP3) expression, mitochondrial uncoupling, and peroxisome proliferator-activated receptor α (PPARα) expression. SNRK homozygous knockout (KO) was embryonic lethal, but hearts from heterozygous SNRK KO mice had increased glucose and fatty acid oxidation and increased expression of UCP3 and PPARα. SNRK knockdown in cardiac cells also increased UCP3, mitochondrial depolarization, and substrate flux, which were all reversed with UCP3 knockdown. The SNRK-mediated changes in UCP3 were PPARα-dependent. To determine the mechanism of PPARα and UCP3 regulation by SNRK, we performed a yeast two hybrid screen and identified Tribbles homolog 3 (Trib3) as a binding partner of SNRK. SNRK transgenic mice had increased Trib3 expression, and Trib3 overexpression reversed the upregulation of PPARα and UCP3 by SNRK knockdown. Finally, SNRK overexpression in mice reduced infarct size compared to area-at-risk (53.01% vs. 37.95%, n=6) in response to myocardial ischemia/reperfusion. Conclusions: Our results demonstrate that SNRK increases cardiac metabolic efficiency and protects against ischemic damage through binding and upregulation of Trib3, leading to PPARα-driven UCP3 downregulation and improved mitochondrial coupling.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".