Abstract 16374: Perm1 Regulates Mitochondrial Energetics Through O-Glcnacylation in Cardiomyocytes
Bibliographic record
Abstract
O-GlcNAcylation is a post-translational modification of proteins that plays an important role in cellular homeostasis and stress responses. Two enzymes regulate O-GlcNAcylation: O-GlcNAc transferase (OGT) that adds O-GlcNAc to proteins; O-GlcNAcase (OGA) that removes O-GlcNAc from proteins. While O-GlcNAcylation is necessary to respond to ischemia/reperfusion injury, chronic activation of O-GlcNAcylation in the heart has adverse effects, and excessive O-GlcNAcylation leads to the development of heart failure. However, there is currently no therapy for heart failure that targets O-GlcNAcylation. Perm1 is a striated muscle-specific regulator of mitochondrial bioenergetics. We previously demonstrated that Perm1-knockout mice exhibit reduced cardiac function and myocardial energy reserve, in association with excessive O-GlcNAcylation and upregulation of OGT. Here, we hypothesized that Perm1 maintains mitochondrial energetics by suppressing O-GlcNAcylation. We found that adenovirus-mediated overexpression of Perm1 in cardiomyocytes significantly decreased O-GlcNAcylation (Figure 1A-B) and increased the basal and maximal respiration and ATP production rates as compared with control in Cell Mito Stress Test using a Seahorse 96x flux analyzer (orange vs. green, Figure 1C-D). Furthermore, the increased levels of O-GlcNAcylated proteins (215% of control, p<0.05) via silencing OGA (si-OGA) in cardiomyocytes significantly decreased the basal and maximal respiration capacity and ATP production rates as compared with control (green vs. purple, Figure 1C-D), all which were completely rescued by Perm1 overexpression (blue, Figure 1C-D). These results suggest that Perm1 positively regulates mitochondrial energetics, in part, via suppressing O-GlcNAcylation and that Perm1 might be a new therapeutic target of heart failure that maintains mitochondrial function through preventing excessive O-GlcNAcylation under pathological stress.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".