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Record W4313281268 · doi:10.1002/jcp.30938

Phosphoproteomic analysis identifies supervillin as an ERK3 substrate regulating cytokinesis and cell ploidy

2022· article· en· W4313281268 on OpenAlexafffund
Joaquim Javary, Eugénie Goupil, Mathilde Soulez, Evgeny Kanshin, Antoine Bouchard, Ole Morten Seternes, Pierre Thibault, Jean‐Claude Labbé, Sylvain Meloche

Bibliographic record

VenueJournal of Cellular Physiology · 2022
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCellular Mechanics and Interactions
Canadian institutionsUniversité de MontréalMontreal Clinical Research InstituteInstitute for Research in Immunology and Cancer
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health ResearchCancer Research SocietyGenome Canada
KeywordsCytokinesisCell biologyPhosphoproteomicsBiologyKinaseProtein kinase ACell divisionCellGeneticsProtein phosphorylation

Abstract

fetched live from OpenAlex

Extracellular signal-regulated kinase 3 (ERK3) is a poorly characterized member of the mitogen-activated protein (MAP) kinase family. Functional analysis of the ERK3 signaling pathway has been hampered by a lack of knowledge about the substrates and downstream effectors of the kinase. Here, we used large-scale quantitative phosphoproteomics and targeted gene silencing to identify direct ERK3 substrates and gain insight into its cellular functions. Detailed validation of one candidate substrate identified the gelsolin/villin family member supervillin (SVIL) as a bona fide ERK3 substrate. We show that ERK3 phosphorylates SVIL on Ser245 to regulate myosin II activation and cytokinesis completion in dividing cells. Depletion of SVIL or ERK3 leads to increased cytokinesis failure and multinucleation, a phenotype rescued by wild type SVIL but not by the non-phosphorylatable S245A mutant. Our results unveil a new function of the atypical MAP kinase ERK3 in cell division and the regulation of cell ploidy.

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 score0.007
Threshold uncertainty score0.689

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 head0.007
GPT teacher head0.224
Teacher spread0.217 · 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

Citations6
Published2022
Admission routes2
Has abstractyes

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