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Record W3021650619 · doi:10.1242/jcs.243071

AURKA destruction is decoupled from its activity at mitotic exit but is essential to suppress interphase activity

2020· article· en· W3021650619 on OpenAlexfundno aff
Ahmed Abdelbaki, H. Begum Akman, Marion Poteau, Rhys Grant, Olivier Gavet, Giulia Guarguaglini, Catherine Lindon

Bibliographic record

VenueJournal of Cell Science · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMicrotubule and mitosis dynamics
Canadian institutionsnot available
FundersBiotechnology and Biological Sciences Research CouncilAgence Nationale de la RechercheAssociazione Italiana per la Ricerca sul CancroMedical Research Council CanadaMedical Research CouncilCambridge TrustRoyal Society
KeywordsBiologyInterphaseMitosisCell biology

Abstract

fetched live from OpenAlex

ABSTRACT Activity of AURKA is controlled through multiple mechanisms including phosphorylation, ubiquitin-mediated degradation and allosteric interaction with TPX2. Activity peaks at mitosis, before AURKA is degraded during and after mitotic exit in a process strictly dependent on the APC/C coactivator FZR1. We used FZR1 knockout cells (FZR1KO) and a novel FRET-based AURKA biosensor to investigate how AURKA activity is regulated in the absence of destruction. We found that AURKA activity in FZR1KO cells dropped at mitotic exit as rapidly as in parental cells, despite absence of AURKA destruction. Unexpectedly, TPX2 was degraded normally in FZR1KO cells. Overexpression of an N-terminal TPX2 fragment sufficient for AURKA binding, but that is not degraded at mitotic exit, caused delay in AURKA inactivation. We conclude that inactivation of AURKA at mitotic exit is determined not by AURKA degradation but by degradation of TPX2 and therefore is dependent on CDC20 rather than FZR1. The biosensor revealed that FZR1 instead suppresses AURKA activity in interphase and is critically required for assembly of the interphase mitochondrial network after mitosis. This article has an associated First Person interview with the first authors 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)0.000
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 score0.008
Threshold uncertainty score0.515

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 head0.012
GPT teacher head0.262
Teacher spread0.250 · 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

Citations38
Published2020
Admission routes1
Has abstractyes

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