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Abstract 5431: Activation of Myocardin Function by an Ubiquitin E3 Ligase, EDD

2009· article· en· W6712257 on OpenAlexaff
Guoqing Hu, Darren N. Saunders, Michelle J. Henderson, Amanda J. Russell, B. Paul Herring, Jiliang Zhou

Bibliographic record

VenueCirculation · 2009
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicUbiquitin and proteasome pathways
Canadian institutionsBC Cancer Agency
Fundersnot available
KeywordsMedicineUbiquitin ligaseMyocardinUbiquitinCell biologyGeneticsTranscription factorBiology

Abstract

fetched live from OpenAlex

Fully differentiated mature smooth muscle cells (SMCs) are characterized by the presence of a unique repertoire of contractile proteins. The expression of these proteins is markedly attenuated during the de-differentiation of smooth muscle that occurs under many pathological conditions. SRF is a transcription factor that plays a central role in the expression of these smooth muscle-specific genes through physical association with various cell-restricted or signal dependent accessory factors. Of the SRF-associated proteins identified, myocardin is the most potent for stimulating expression of smooth muscle-specific genes. Although several proteins have been identified that can modify myocardin function, the mechanism of how myocardin regulation is still poorly understood. To identify additional myocardin associated proteins that are required for myocardin-dependent activation smooth muscle-specific genes we performed a yeast 2-hybrid screen of mouse embryo cDNA library using myocardin as bait. From this screen we identified a HECT domain containing protein EDD as a myocardin binding protein. Previous studies have shown that HECT domain containing proteins are ubiquitin E3 ligases that play an important role in protein degradation. EDD has however, also been shown to regulate transcription independent of its E3 ligase activity. In the current study we demonstrated that the amino-terminal domain of myocardin bound to the HECT domain of EDD. We also show that EDD specifically enhanced trans-activation of smooth muscle-specific promoters by myocardin. Furthermore, EDD significantly augmented myocardin’s ability to induce expression of endogenous SMC marker genes, and these effects of EDD were independent on its E3 ligase function. Conversely, depletion of endogenous EDD in fibroblast cells by RNAi attenuated myocardin-induced smooth muscle-specific gene expression, and EDD knockdown in smooth muscle cells resulted in down-regulation of smooth muscle-specific genes. Ongoing experiments are investigating the mechanism by which EDD activates myocardin function. This study reveals an unexpected role for the ubiquitin E3 ligase EDD as an activator of smooth muscle differentiation through its ability to potentiate myocardin function. This research has received full or partial funding support from the American Heart Association, National Center.

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 score0.003
Threshold uncertainty score0.009

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)0.0030.001

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 head0.015
GPT teacher head0.247
Teacher spread0.232 · 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

Citations0
Published2009
Admission routes1
Has abstractyes

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