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Record W4394724366 · doi:10.1101/2024.04.08.588474

TRIP12 governs DNA Polymerase β involvement in DNA damage response and repair

2024· preprint· en· W4394724366 on OpenAlexaff
Burcu Inanç, Qingming Fang, Joel Andrews, Xuemei Zeng, Jennifer Clark, Jianfeng Li, Nupur B. Dey, Md Ibrahim, Peter Sykora, Zhongxun Yu, Andrea Braganza, Marcel Verheij, Jos Jonkers, Nathan A. Yates, Conchita Vens, Robert W. Sobol

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2024
Typepreprint
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicDNA Repair Mechanisms
Canadian institutionsInstitute of Cancer Research
Fundersnot available
KeywordsDNA damageDNA polymerasePolymeraseDNA repairDNAComputational biologyBiologyGenetics

Abstract

fetched live from OpenAlex

The multitude of DNA lesion types, and the nuclear dynamic context in which they occur, present a challenge for genome integrity maintenance as this requires the engagement of different DNA repair pathways. Specific 'repair controllers' that facilitate DNA repair pathway crosstalk between double strand break (DSB) repair and base excision repair (BER), and regulate BER protein trafficking at lesion sites, have yet to be identified. We find that DNA polymerase β (Polβ), crucial for BER, is ubiquitylated in a BER complex-dependent manner by TRIP12, an E3 ligase that partners with UBR5 and restrains DSB repair signaling. Here we find that, TRIP12, but not UBR5, controls cellular levels and chromatin loading of Polβ. Required for Polβ foci formation, TRIP12 regulates Polβ involvement after DNA damage. Notably, excessive TRIP12-mediated shuttling of Polβ affects DSB formation and radiation sensitivity, underscoring its precedence for BER. We conclude that the herein discovered trafficking function at the nexus of DNA repair signaling pathways, towards Polβ-directed BER, optimizes DNA repair pathway choice at complex lesion sites.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

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 communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.002

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 head0.009
GPT teacher head0.222
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 source (direct Gemma or distilled Codex), 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

Citations1
Published2024
Admission routes1
Has abstractyes

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