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Record W2109116414 · doi:10.1128/mcb.00012-15

Molecular Mechanism for the Control of Eukaryotic Elongation Factor 2 Kinase by pH: Role in Cancer Cell Survival

2015· article· en· W2109116414 on OpenAlexafffund
Jianling Xie, Halina Mikolajek, Craig R. Pigott, Kelly J. Hooper, Toby Mellows, Claire E. Moore, Hafeez Mohammed, Jörn M. Werner, Gareth J. Thomas, Christopher G. Proud

Bibliographic record

VenueMolecular and Cellular Biology · 2015
Typearticle
Languageen
FieldChemistry
TopicMass Spectrometry Techniques and Applications
Canadian institutionsUniversity of British Columbia
FundersBiotechnology and Biological Sciences Research CouncilCanadian Institutes of Health ResearchFrancis Crick InstituteWellcome Trust
KeywordsBiologyCalmodulinCell biologyKinaseExtracellularProtein kinase ACancer cellElongation factorIntracellularBiochemistryCancerEnzymeRNA

Abstract

fetched live from OpenAlex

Acidification of the extracellular and/or intracellular environment is involved in many aspects of cell physiology and pathology. Eukaryotic elongation factor 2 kinase (eEF2K) is a Ca(2+)/calmodulin-dependent kinase that regulates translation elongation by phosphorylating and inhibiting eEF2. Here we show that extracellular acidosis elicits activation of eEF2K in vivo, leading to enhanced phosphorylation of eEF2. We identify five histidine residues in eEF2K that are crucial for the activation of eEF2K during acidosis. Three of them (H80, H87, and H94) are in its calmodulin-binding site, and their protonation appears to enhance the ability of calmodulin to activate eEF2K. The other two histidines (H227 and H230) lie in the catalytic domain of eEF2K. We also identify His108 in calmodulin as essential for activation of eEF2K. Acidification of cancer cell microenvironments is a hallmark of malignant solid tumors. Knocking down eEF2K in cancer cells attenuated the decrease in global protein synthesis when cells were cultured at acidic pH. Importantly, activation of eEF2K is linked to cancer cell survival under acidic conditions. Inhibition of eEF2K promotes cancer cell death under acidosis.

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 score0.214
Threshold uncertainty score0.445

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 head0.010
GPT teacher head0.246
Teacher spread0.236 · 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

Citations46
Published2015
Admission routes2
Has abstractyes

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