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Record W2028586759 · doi:10.1016/j.cell.2011.01.013

DNA Damage in Oocytes Induces a Switch of the Quality Control Factor TAp63α from Dimer to Tetramer

2011· article· en· W2028586759 on OpenAlexfundno aff
Gregor B. Deutsch, Elisabeth M. Zielonka, Daniel Coutandin, Tobias Weber, Birgit Schäfer, Jens Hannewald, Laura M. Luh, Florian Durst, Mohamed F. M. Ibrahim, Jan Hoffmann, F. Niesen, Aycan Sentürk, Hana Kunkel, Bernd Brutschy, Enrico Schleiff, Stefan Knapp, Amparo Acker‐Palmer, Manuel Grez, Frank McKeon, Volker Dötsch

Bibliographic record

VenueCell · 2011
Typearticle
Languageen
FieldMedicine
TopicCancer-related Molecular Pathways
Canadian institutionsnot available
FundersCanadian Institutes of Health ResearchWellcome Trust
KeywordsTransactivationTetramerBiologyDephosphorylationCell biologyPhosphorylationDNADimerBiophysicsBiochemistryTranscription factorEnzymePhosphataseChemistryGene

Abstract

fetched live from OpenAlex

TAp63α, a homolog of the p53 tumor suppressor, is a quality control factor in the female germline. Remarkably, already undamaged oocytes express high levels of the protein, suggesting that TAp63α's activity is under tight control of an inhibitory mechanism. Biochemical studies have proposed that inhibition requires the C-terminal transactivation inhibitory domain. However, the structural mechanism of TAp63α inhibition remains unknown. Here, we show that TAp63α is kept in an inactive dimeric state. We reveal that relief of inhibition leads to tetramer formation with ∼20-fold higher DNA affinity. In vivo, phosphorylation-triggered tetramerization of TAp63α is not reversible by dephosphorylation. Furthermore, we show that a helix in the oligomerization domain of p63 is crucial for tetramer stabilization and competes with the transactivation domain for the same binding site. Our results demonstrate how TAp63α is inhibited by complex domain-domain interactions that provide the basis for regulating quality control in oocytes.

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 score0.325
Threshold uncertainty score0.638

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)0.0010.000

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 head0.040
GPT teacher head0.274
Teacher spread0.234 · 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

Citations144
Published2011
Admission routes1
Has abstractyes

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