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Record W4409803473 · doi:10.1111/andr.70051

Identification of MEF2A, MEF2C, and MEF2D interactomes in basal and Fsk‐stimulated mouse MA‐10 Leydig cells

2025· article· en· W4409803473 on OpenAlex
Karine de Mattos, Marie‐Pier Scott‐Boyer, Arnaud Droit, Robert S. Viger, Jacques Tremblay

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueAndrology · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEpigenetics and DNA Methylation
Canadian institutionsUniversité Laval
FundersCentre Hospitalier Universitaire de QuébecCanadian Institutes of Health ResearchUniversité Laval
KeywordsMef2MEF2CInteractomeBiologyEnhancerTranscription factorCell biologyGeneticsGene

Abstract

fetched live from OpenAlex

BACKGROUND: Myocyte enhancer factor 2 transcription factors regulate essential transcriptional programs in various cell types. The activity of myocyte enhancer factor 2 factors is modulated through interactions with cofactors, chromatin remodelers, and other regulatory proteins, which are dependent on cell context and physiological state. In steroidogenic Leydig cells, MEF2A, MEF2C, and MEF2D are key regulators of genes involved in steroid hormone synthesis, reproductive function, and oxidative stress defense. However, the specific network of myocyte enhancer factor 2-interacting proteins in Leydig cells remains unknown. OBJECTIVE: To identify the interactome of each MEF2 factor present in Leydig cells. MATERIALS AND METHODS: TurboID proximity-mediated biotinylation combined with mass spectrometry and bioinformatic analyses were used to identify the protein‒protein interaction networks of MEF2A, MEF2C, and MEF2D in MA-10 Leydig cells under basal and stimulated conditions. RESULTS: We identified 109 potential myocyte enhancer factor 2-interacting proteins, including some previously known myocyte enhancer factor 2 partners. The interactome for each myocyte enhancer factor 2 factor is dynamic and exhibits unique and shared interaction networks between basal and stimulated conditions. Further analysis through Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment categorized these interactions, revealing involvement in pathways related to cellular metabolism, transcriptional regulation, and steroidogenesis. DISCUSSION AND CONCLUSION: These findings suggest that myocyte enhancer factor 2 factors can participate in diverse transcriptional activities, capable of gene activation or repression, depending on different protein‒protein interactions. In addition, the differential interactome for each myocyte enhancer factor 2 factor suggests unique regulatory roles for each factor in modulating Leydig cell function. Overall, this study provides new mechanistic insights into myocyte enhancer factor 2 action in Leydig cells by identifying interacting partners that likely influence their functions.

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.

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 score0.013
Threshold uncertainty score0.363

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)0.0000.000

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 head0.004
GPT teacher head0.260
Teacher spread0.256 · 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