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Exercise‐Induced Expression, Function, and Localization of Protein Arginine Methyltransferases in Skeletal Muscle

2017· article· en· W4389021476 on OpenAlexafffundabout
Tiffany L. van Lieshout, Derek W. Stouth, Vladimir Ljubicic

Bibliographic record

VenueThe FASEB Journal · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer-related gene regulation
Canadian institutionsMcMaster University
FundersCanada Research Chairs
KeywordssedSkeletal muscleArginineEndocrinologyInternal medicineProtein arginine methyltransferase 5IntracellularCytosolBiologyWestern blotMethyltransferaseChemistryBiochemistryEnzymeMedicineMethylationAmino acidGene

Abstract

fetched live from OpenAlex

Protein arginine methyltransferase 1 (PRMT1), PRMT4, and PRMT5 catalyze the methylation of arginine residues on target proteins. In turn, these marked proteins mediate a variety of biological functions. By regulating molecules that are critical to the remodelling of skeletal muscle phenotype, PRMTs may influence skeletal muscle plasticity. Thus, our study tests the hypothesis that the intracellular signals required for muscle adaptation to exercise will be associated with the induction of PRMT expression and activity. C57BL/6 mice were assigned to one of three experimental groups: sedentary (SED), acute bout of exercise (0PE), or acute exercise followed by 180 minutes of recovery (3PE). The mice in the exercise groups performed a single bout of treadmill running at 15 m/min for 90 minutes. The extensor digitorum longus (EDL) and the soleus (SOL) muscles were utilized for RT‐qPCR and Western blot assays, while the gastrocnemius (GAST) muscle was employed to isolate nuclear and cytosolic compartments for protein localization analyses. AMPK activation status was 1.7–2.2 fold higher (p < 0.05) immediately post‐exercise (0PE) in the EDL and SOL muscles, and returned to baseline levels at 3PE. Furthermore, PGC‐1α mRNA expression was elevated by 10–13‐fold (p < 0.05) in both muscles at 0PE and 3PE, which demonstrates that the experimental design utilized in this study was effective at evoking an intracellular milieu indicative of the exercise response. The level of whole muscle PGC‐1α protein content was similar between SED, 0PE, and 3PE. In muscles from the SED group, PRMTs exhibited fiber type‐ and enzyme‐specific gene expression patterns at the mRNA and protein levels. PRMT1 and PRMT5 mRNA expression was similar between muscles, while PRMT4 transcript levels were significantly lower (−40%) in SOL compared to EDL muscles. PRMT1 and PRMT5 protein content was 90% and 140% higher in SOL relative to EDL muscles, respectively (p < 0.05), whereas in contrast PRMT4 displayed similar protein expression between muscle types. PRMT mRNA and protein content were similar between SED, 0PE, and 3PE. Assessment of muscle monomethylarginine (MMA) content was performed in order to examine total PRMT activity, while asymmetric dimethylarginine (ADMA) levels were assayed as a marker of PRMT1 and PRMT4 activity, and symmetric dimethylarginine (SDMA) content was analyzed to assess PRMT5 function. The presence of all three methylarginine species was significantly higher (40–100%) in the SOL muscles compared to the EDL muscles. As observed with PRMT gene expression, MMA, ADMA, and SDMA were similar between SED, 0PE, and 3PE. Analysis of GAST nuclear and cytosolic fractions demonstrated that PRMT protein expression was significantly higher in the cytosolic compartment versus the myonuclei. Cellular PRMT localization was similar between SED, 0PE, and 3PE. Collectively, this study reveals characteristics of PRMT biology that may important for the exercise‐induced remodelling of skeletal muscle. Support or Funding Information Natural Science and Engineering Research Council of Canada, Canada Research Chairs

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 score0.003

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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.011
GPT teacher head0.247
Teacher spread0.235 · 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".

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Citations0
Published2017
Admission routes3
Has abstractyes

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