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Contractile activity activates redundant signaling pathways toward TFEB and TFE3 transcription in skeletal muscle cells to initiate lysosome biogenesis

2025· article· en· W4411876239 on OpenAlexaff
Neushaw Moradi, David A. Hood

Bibliographic record

VenuePhysiology · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicUbiquitin and proteasome pathways
Canadian institutionsYork University
Fundersnot available
KeywordsTFEBLysosomeTFE3Cell biologyBasic helix-loop-helix leucine zipper transcription factorsBiogenesisTranscription factorTranscription (linguistics)BiologySkeletal muscleNeuroscienceAnatomyGeneBiochemistryDNA-binding protein

Abstract

fetched live from OpenAlex

Mitophagy is the cellular process that degrades mitochondria when these organelles become dysfunctional, exhibited by increases in reactive oxygen species (ROS) production, and reduced oxidative phosphorylation. The terminal step of mitophagy is mediated by the lysosome which functions to degrade defective cellular cargo. In skeletal muscle, contractile activity and/or exercise activate mitophagy, and repeated bouts of exercise produce increases in the levels of lysosomal proteins, suggestive of augmented organelle biogenesis. The signaling cascades which lead to the transcriptional activation of genes encoding lysosomal proteins likely begin with as little as a single bout of exercise, termed acute contractile activity (ACA). However, the nature of these signals remains unresolved. In this study, we evaluated three known signaling pathways which modify gene expression in muscle, namely intracellular calcium levels, ROS production, and AMPK activation. To investigate this, we pre-treated C2C12 myotubes with inhibitors known to target these pathways, then subjected these cells to a single bout of electrical pulse stimulation for 3 hours to represent ACA. We then measured changes in promoter activity and mRNA levels of the transcription factors TFEB and TFE3, widely recognized as master regulators of lysosomal biogenesis. Some myotubes were also subjected to ACA and allowed to recover for 24 hours to assess the transient nature of the signaling pathways. The inhibition of calcium, ROS, or AMPK was induced by 100 μM BAPTA-AM, 20 mM N-acetylcysteine (NAC), or 40 μM Compound C (CC), respectively. Changes in promoter activity were captured via dual-luciferase promoter-reporter assay while mRNA changes were assessed using qPCR. ACA increased the transcription of both TFEB and TFE3 by 1.6-2.0-fold, with corresponding changes in mRNA levels. However, TFEB and TFE3 promoter activities were differentially affected by pathway inhibition in both quiescent cells, and in response to ACA and recovery. TFEB transcription was reduced by 40-65% by all 3 treatments in non-contracting myotubes, whereas no effect was observed for TFE3 promoter activity. However, these treatments completely abolished TFE3 transcriptional activation in response to ACA, whereas TFEB transcription remained unaffected by ROS inhibition, and was reduced by calcium and AMPK inhibition only. TFEB transcription was also reduced to basal levels during recovery, whereas TFE3 promoter activity remained elevated, even 24 hours later. These observations suggest that all three pathways are active in maintaining the level of TFEB, but not TFE3, in quiescent cells. Changes in intracellular calcium as well as AMPK activation are the most important signaling pathways for the coordinated transcriptional activation of both TFEB and TFE3 in response to ACA. These data reveal the nature of the redundant signaling pathways induced by contractile activity that lead to the transcription and expression of both TFEB and TFE3 that ultimately lead to lysosomal adaptations in muscle responding to exercise. This research is supported by NSERC. This abstract was presented at the American Physiology Summit 2025 and is only available in HTML format. There is no downloadable file or PDF version. The Physiology editorial board was not involved in the peer review process.

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)0.000
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 score0.016
Threshold uncertainty score0.854

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 head0.019
GPT teacher head0.253
Teacher spread0.233 · 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".

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Citations0
Published2025
Admission routes1
Has abstractyes

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