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Record W2058148408 · doi:10.1016/j.celrep.2014.03.029

Rewiring AMPK and Mitochondrial Retrograde Signaling for Metabolic Control of Aging and Histone Acetylation in Respiratory-Defective Cells

2014· article· en· W2058148408 on OpenAlexafffund
R. Magnus N. Friis, John Paul Glaves, Tao Huan, Liang Li, Brian D. Sykes, Michael C. Schultz

Bibliographic record

VenueCell Reports · 2014
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEndoplasmic Reticulum Stress and Disease
Canadian institutionsUniversity of Alberta
FundersCanadian Institutes of Health Research
KeywordsAcetylationHistone AcetyltransferasesBiologyAMPKHistoneCell biologyMitochondrionBiochemistryKinaseGeneProtein kinase A

Abstract

fetched live from OpenAlex

Abnormal respiratory metabolism plays a role in numerous human disorders. We find that regulation of overall histone acetylation is perturbed in respiratory-incompetent (ρ(0)) yeast. Because histone acetylation is highly sensitive to acetyl-coenzyme A (acetyl-CoA) availability, we sought interventions that suppress this ρ(0) phenotype through reprogramming metabolism. Nutritional intervention studies led to the discovery that genetic coactivation of the mitochondrion-to-nucleus retrograde (RTG) response and the AMPK (Snf1) pathway prevents abnormal histone deacetylation in ρ(0) cells. Metabolic profiling of signaling mutants uncovered links between chromatin-dependent phenotypes of ρ(0) cells and metabolism of ATP, acetyl-CoA, glutathione, branched-chain amino acids, and the storage carbohydrate trehalose. Importantly, RTG/AMPK activation reprograms energy metabolism to increase the supply of acetyl-CoA to lysine acetyltransferases and extend the chronological lifespan of ρ(0) cells. Our results strengthen the framework for rational design of nutrient supplementation schemes and drug-discovery initiatives aimed at mimicking the therapeutic benefits of dietary interventions.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.016
Threshold uncertainty score0.408

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.006
GPT teacher head0.239
Teacher spread0.234 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations43
Published2014
Admission routes2
Has abstractyes

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