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Record W1995351663 · doi:10.1016/j.celrep.2012.08.035

Lysine Deacetylases Hda1 and Rpd3 Regulate Hsp90 Function thereby Governing Fungal Drug Resistance

2012· article· en· W1995351663 on OpenAlexafffund
Nicole Robbins, Michelle D. Leach, Leah E. Cowen

Bibliographic record

VenueCell Reports · 2012
Typearticle
Languageen
FieldImmunology and Microbiology
TopicAntimicrobial Peptides and Activities
Canadian institutionsUniversity of Toronto
FundersCanadian Institutes of Health ResearchWellcome Trust
KeywordsAcetylationBiologyCandida albicansSaccharomyces cerevisiaeHsp90Cell biologyLysineRegulatorBiochemistryGeneticsYeastHeat shock proteinAmino acidGene

Abstract

fetched live from OpenAlex

The molecular chaperone Hsp90 is a hub of protein homeostasis and regulatory circuitry. Hsp90 function is regulated by posttranslational modifications including acetylation in mammals; however, whether this regulation is conserved remains unknown. In fungi, Hsp90 governs the evolution of drug resistance by stabilizing signal transducers. Here, we establish that pharmacological inhibition of lysine deacetylases (KDACs) blocks the emergence and maintenance of Hsp90-dependent resistance to the most widely deployed antifungals, the azoles, in the human fungal pathogen Candida albicans and the model yeast Saccharomyces cerevisiae. S. cerevisiae Hsp90 is acetylated on lysine 27 and 270, and key KDACs for drug resistance are Hda1 and Rpd3. Compromising KDACs alters stability and function of Hsp90 client proteins, including the drug-resistance regulator calcineurin. Thus, we establish acetylation as a mechanism of posttranslational control of Hsp90 function in fungi, functional redundancy between KDACs Hda1 and Rpd3, as well as a mechanism governing fungal drug resistance with broad therapeutic potential.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.007
GPT teacher head0.188
Teacher spread0.182 · 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 source (direct Gemma or distilled Codex), 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

Citations126
Published2012
Admission routes2
Has abstractyes

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