Compensatory regulation of HDAC5 in muscle maintains metabolic adaptive responses and metabolism in response to energetic stress
Bibliographic record
Abstract
Some gene deletions or mutations have little effect on metabolism and metabolic adaptation because of redundancy and/or compensation in metabolic pathways. The mechanisms for redundancy and/ or compensation in metabolic adaptation in mammalian cells are unidentified. Here, we show that in mouse muscle and myogenic cells, compensatory regulation of the histone deacetylase (HDAC5) transcriptional repressor maintains metabolic integrity. HDAC5 phosphorylation regulated the expression of diverse metabolic genes and glucose metabolism in mouse C2C12 myogenic cells. However, loss of AMP‐activated protein kinase (AMPK), a HDAC5 kinase, in muscle did not affect HDAC5 phosphorylation in mouse skeletal muscle during exercise, but resulted in a compensatory increase (32.6%) in the activation of protein kinase D (PKD), an alternate HDAC5 kinase. Constitutive PKD activation in mouse C2C12 myogenic cells regulated metabolic genes and glucose metabolism. Although aspects of this response were HDAC5 phosphorylation dependent, blocking HDAC5 phosphorylation when PKD was active engaged an alternative compensatory adaptive mechanism, which involved post‐transcriptional reductions in HDAC5 mRNA (–93.1%) and protein. This enhanced the expression of a specific subset of metabolic genes and mitochondrial metabolism. These data show that compensatory regulation of HDAC5 maintains metabolic integrity in mammalian cells and reinforces the importance of preserving the cellular metabolic adaptive response.—McGee, S. L., Swinton, C., Morrison, S., Gaur, V., Campbell, D. E., Jorgensen, S. B., Kemp, B. E., Baar, K., Steinberg, G. R., Hargreaves, M. Compensatory regulation of HDAC5 in muscle maintains metabolic adaptive responses and metabolism in response to energetic stress. FASEB J. 28, 3384–3395 (2014). www.fasebj.org
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".