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Is ATF4 Required for Skeletal Muscle Mitochondrial Biogenesis and Remodeling?

2020· article· en· W3016879058 on OpenAlexaffabout
Jonathan M. Memme, Zarah S. Mesbah Moosavi, David A. Hood

Bibliographic record

VenueThe FASEB Journal · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMuscle metabolism and nutrition
Canadian institutionsYork University
Fundersnot available
KeywordsProteostasisMitochondrial biogenesisCell biologyBiologySkeletal muscleMitochondrionUnfolded protein responseRegulatorOrganelle biogenesisAutophagyMitophagyMuscle atrophyATF4Myocytemitochondrial fusionMitochondrial DNABiogenesisEndocrinologyGeneticsEndoplasmic reticulumGene

Abstract

fetched live from OpenAlex

Skeletal muscle is an important tissue for the maintenance of whole‐body health and vitality. Regarded for its role in supporting posture and locomotion, the metabolic profile of muscle has further ramifications for mobility, risk of falls/injury, and the development of diseases. As mitochondria are responsible for the maintenance of metabolic health in muscle, they also contribute to muscle dysfunction and disease. The intricate regulation of mitochondrial content and function within muscle is essential to match the internal metabolic capability to the external demands being placed on the tissue. PGC‐1α is the master regulator of mitochondrial biogenesis, which refers to the synthesis of mitochondrial proteins transcribed by both nDNA and mtDNA. The synchronous expression of mitochondrial proteins from either genome is important in preserving proteostasis, as an imbalance in their expression can promote dysfunction within the organelle and trigger the mitochondrial unfolded protein response (UPR mt ). ATF4, identified as a primary regulator of the UPR mt , upregulates the expression of mitochondrial chaperones and proteostasis to augment the protein handling ability of the organelle, and to re‐establish homeostasis. As ATF4 responds to acute cellular stresses, it has been implicated in regulating skeletal muscle health by mediating aging‐related, and disuse‐induced muscle atrophy and decline. However, while it is understood that ATF4 is involved in mediating the mitochondrial stress response, it has yet to be determined whether ATF4 is necessary for mitochondrial biogenesis in skeletal muscle. We measured ATF4 expression in C2C12 cells prior to, and following 4‐days of differentiation, and found ATF4 protein levels to be elevated over 3‐fold in differentiated myotubes. This induction of ATF4 coincided with 3–5‐fold increases in protein expression of mitochondrial content markers COX I and IV, despite modest decreases in UPR mt factors, mtHSP70, HSP60, and CPN10. Moreover, overexpression and knockdown of ATF4 in cultured myoblasts affected their ability to form multinucleated myotubes, indicating that the expression of ATF4 must be regulated to facilitate myotube formation. We examined the induction of ATF4 following contractile activity (CA), both in C2C12 myotubes, and rat TA muscle. CA was sufficient to induce 50–80% increases in ATF4 mRNA and protein in tissue and cultured cells, respectively, which preceded 1.5–2.5‐fold increases in mitochondrial content. Additionally, we observed a 2‐fold increase in ATF4 protein expression in hindlimbs of mice subjected to unilateral sciatic denervation, which corresponded with a 15–20% decrease in mitochondrial content. Taken together, these data suggest a possible regulatory role for ATF4 in determining mitochondrial adaptation within muscle during development, exercise and chronic disuse. Subsequent work investigating the impact of ATF4 ablation and exogenous expression on mitochondrial biogenesis signaling, as well as on mitochondrial function following contractile activity will further illustrate whether ATF4 is necessary and sufficient to promote improvements in mitochondrial content and function. Support or Funding Information Work supported by NSERC, Canada.

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 score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.027
GPT teacher head0.257
Teacher spread0.230 · 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
Published2020
Admission routes2
Has abstractyes

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