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Record W2028224002 · doi:10.1093/nar/gks222

CBX4-mediated SUMO modification regulates BMI1 recruitment at sites of DNA damage

2012· article· en· W2028224002 on OpenAlexafffund
Ismail Hassan Ismail, Jean‐Philippe Gagné, Marie‐Christine Caron, Darin McDonald, Zhizhong Xu, Jean‐Yves Masson, Guy G. Poirier, Michael J. Hendzel

Bibliographic record

VenueNucleic Acids Research · 2012
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicUbiquitin and proteasome pathways
Canadian institutionsUniversité LavalHôtel-Dieu de QuébecUniversity of Alberta
FundersCanadian Institutes of Health Research
KeywordsBiologyDNA damageBMI1Polycomb-group proteinsSUMO proteinCell biologyDNA repairGene silencingEpigeneticsDNAUbiquitin ligaseHistoneMolecular biologyGeneticsUbiquitinGeneStem cellRepressorTranscription factor

Abstract

fetched live from OpenAlex

Polycomb group (PcG) proteins are involved in epigenetic silencing where they function as major determinants of cell identity, stem cell pluripotency and the epigenetic gene silencing involved in cancer development. Recently numerous PcG proteins, including CBX4, have been shown to accumulate at sites of DNA damage. However, it remains unclear whether or not CBX4 or its E3 sumo ligase activity is directly involved in the DNA damage response (DDR). Here we define a novel role for CBX4 as an early DDR protein that mediates SUMO conjugation at sites of DNA lesions. DNA damage stimulates sumoylation of BMI1 by CBX4 at lysine 88, which is required for the accumulation of BMI1 at DNA damage sites. Moreover, we establish that CBX4 recruitment to the sites of laser micro-irradiation-induced DNA damage requires PARP activity but does not require H2AX, RNF8, BMI1 nor PI-3-related kinases. The importance of CBX4 in the DDR was confirmed by the depletion of CBX4, which resulted in decreased cellular resistance to ionizing radiation. Our results reveal a direct role for CBX4 in the DDR pathway.

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 score0.063
Threshold uncertainty score0.506

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 head0.138
GPT teacher head0.373
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

Citations143
Published2012
Admission routes2
Has abstractyes

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