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Record W2077587582 · doi:10.1074/jbc.m411250200

SUMO Modification of the Ets-related Transcription Factor ERM Inhibits Its Transcriptional Activity

2005· article· en· W2077587582 on OpenAlexfundno aff
Cindy Degerny, Didier Monté, Claude Beaudoin, Ellis Jaffray, Laurence Portois, Ronald T. Hay, Yvan de Launoit, Jean‐Luc Baert

Bibliographic record

VenueJournal of Biological Chemistry · 2005
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicUbiquitin and proteasome pathways
Canadian institutionsnot available
FundersEuropean Regional Development FundCanadian Institutes of Health ResearchCentre National de la Recherche Scientifique
KeywordsSUMO proteinTranscription factorTranscription (linguistics)UbiquitinCell biologySubcellular localizationPromoterProteaseChemistryBiologyBiochemistryEnzymeGeneGene expression

Abstract

fetched live from OpenAlex

A variety of transcription factors are post-translationally modified by SUMO, a 97-residue ubiquitin-like protein bound covalently to the targeted lysine. Here we describe SUMO modification of the Ets family member ERM at positions 89, 263, 293, and 350. To investigate how SUMO modification affects the function of ERM, Ets-responsive intercellular adhesion molecule 1 (ICAM-1) and E74 reporter plasmids were employed to demonstrate that SUMO modification causes inhibition of ERM-dependent transcription without affecting the subcellular localization, stability, or DNA-binding capacity of the protein. When the adenoviral protein Gam1 or the SUMO protease SENP1 was used to inhibit the SUMO modification pathway, ERM-dependent transcription was de-repressed. These results demonstrate that ERM is subject to SUMO modification and that this post-translational modification causes inhibition of transcription-enhancing activity.

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 score0.001
Threshold uncertainty score0.004

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 communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.041
GPT teacher head0.263
Teacher spread0.221 · 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

Citations45
Published2005
Admission routes1
Has abstractyes

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