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Record W2936193590 · doi:10.1242/jcs.225698

ERK1/2 phosphorylates HIF-2α and regulates its activity by controlling its CRM1-dependent nuclear shuttling

2019· article· en· W2936193590 on OpenAlexaff
Ioanna‐Maria Gkotinakou, Christina Befani, George Simos, Panagiotis Liakos

Bibliographic record

VenueJournal of Cell Science · 2019
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer, Hypoxia, and Metabolism
Canadian institutionsMcGill University
FundersState Scholarships Foundation
KeywordsBiologyPhosphorylationCell biologyNuclear export signalCell nucleusNucleus

Abstract

fetched live from OpenAlex

ABSTRACT Hypoxia-inducible factor 2 (HIF-2) is a principal component of the cellular response to oxygen deprivation (hypoxia). Its inducible subunit, HIF-2α (also known as EPAS1), is controlled by oxygen-dependent as well as oxygen-independent mechanisms, such as phosphorylation. We show here that HIF-2α is phosphorylated under hypoxia (1% O2) by extracellular signal-regulated protein kinases 1 and 2 (ERK1/2; also known as MAPK3 and MAPK1, respectively) at serine residue 672, as identified by in vitro phosphorylation assays. Mutation of this site to an alanine residue or inhibition of the ERK1/2 pathway decreases HIF-2 transcriptional activity and causes HIF-2α to mislocalize to the cytoplasm without changing its protein expression levels. Localization, reporter gene and immunoprecipitation experiments further show that HIF-2α associates with the exportin chromosomal maintenance 1 (CRM1, also known as XPO1) in a phosphorylation-sensitive manner and identify two critical leucine residues as part of an atypical CRM1-dependent nuclear export signal (NES) neighboring serine 672. Inhibition of CRM1 or mutation of these residues restores nuclear accumulation and activity of HIF-2α lacking the ERK1/2-mediated modification. In summary, we reveal a novel regulatory mechanism of HIF-2, involving ERK1/2-dependent phosphorylation of HIF-2α, which controls its nucleocytoplasmic shuttling and the HIF-2 transcriptional activity. This article has an associated First Person interview with the first author of the paper.

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)0.001
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 score0.046
Threshold uncertainty score0.437

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.005
GPT teacher head0.218
Teacher spread0.213 · 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
Published2019
Admission routes1
Has abstractyes

Explore more

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