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Record W2589769972 · doi:10.1371/journal.pgen.1006626

Lysine acetyltransferase NuA4 and acetyl-CoA regulate glucose-deprived stress granule formation in Saccharomyces cerevisiae

2017· article· en· W2589769972 on OpenAlexafffund
Meaghen Rollins, Sylvain Huard, Alan Morettin, Jennifer Takuski, Trang T. Pham, Morgan D. Fullerton, Jocelyn Côté, Kristin Baetz

Bibliographic record

VenuePLoS Genetics · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEndoplasmic Reticulum Stress and Disease
Canadian institutionsUniversity of Ottawa
FundersInstitute of Musculoskeletal Health and ArthritisNatural Sciences and Engineering Research Council of CanadaInstitute of Cancer ResearchUniversity of TorontoCanadian Institutes of Health ResearchGovernment of Ontario
KeywordsStress granuleBiologySaccharomyces cerevisiaeCell biologyBiochemistryAcetyltransferaseAcetylationYeastMessenger RNAGene

Abstract

fetched live from OpenAlex

Eukaryotic cells form stress granules under a variety of stresses, however the signaling pathways regulating their formation remain largely unknown. We have determined that the Saccharomyces cerevisiae lysine acetyltransferase complex NuA4 is required for stress granule formation upon glucose deprivation but not heat stress. Further, the Tip60 complex, the human homolog of the NuA4 complex, is required for stress granule formation in cancer cell lines. Surprisingly, the impact of NuA4 on glucose-deprived stress granule formation is partially mediated through regulation of acetyl-CoA levels, which are elevated in NuA4 mutants. While elevated acetyl-CoA levels suppress the formation of glucose-deprived stress granules, decreased acetyl-CoA levels enhance stress granule formation upon glucose deprivation. Further our work suggests that NuA4 regulates acetyl-CoA levels through the Acetyl-CoA carboxylase Acc1. Altogether this work establishes both NuA4 and the metabolite acetyl-CoA as critical signaling pathways regulating the formation of glucose-deprived stress granules.

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 score0.027
Threshold uncertainty score0.911

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 head0.013
GPT teacher head0.248
Teacher spread0.235 · 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

Citations25
Published2017
Admission routes2
Has abstractyes

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