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Record W4417259948 · doi:10.1186/s13395-025-00404-3

N-acetylglucosamine facilitates coordinated flow-like movement of myoblasts, forming a foundation for efficient myogenesis

2025· article· en· W4417259948 on OpenAlexafffund
Masahiko S. Satoh, Ann Rancourt, Guillaume St‐Pierre, Elizabeth Bouchard, Maude Fillion, Kana Hagiwara, Kazuki Nakajima, Sachiko Sato

Bibliographic record

VenueSkeletal Muscle · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGlycosylation and Glycoproteins Research
Canadian institutionsUniversité Laval
FundersDefeat Duchenne CanadaCanadian Glycomics NetworkCanadian Institutes of Health ResearchCanada Foundation for Innovation
KeywordsMyogenesisMovement (music)Foundation (evidence)MyocyteSkeletal muscleMuscle contraction

Abstract

fetched live from OpenAlex

BACKGROUND: Skeletal muscle comprises 30-40% of a mammal's body mass, maintaining its integrity through efficient muscle fiber regeneration, which involves myoblast differentiation into myotubes. Previously, we reported that N-acetylglucosamine (GlcNAc) promotes myogenesis in C2C12 cells, although the underlying processes remained unclear. GlcNAc's activated form, UDP-GlcNAc, is critical for the biosynthesis of highly branched (N-acetyllactosamine-rich) N-linked oligosaccharides, which are recognized by galectin-3 (Gal-3), a protein that facilitates dynamic cell-cell and cell-matrix interactions and modulating the motility dynamics of membrane-associated proteins. METHODS: In this study, we used primary myoblasts from both wild-type and Gal-3 null (Gal-3KO) mice, observing myotube formation through long-term live-cell imaging and single-cell tracking to reveal the dynamic process that occurred during the myotube formation. RESULTS: We found that GlcNAc enhances myoblast fusion in a dose-dependent manner, and that the addition of Gal-3 with GlcNAc leads to the formation of larger myotubes. Gal-3KO myoblasts exhibited a reduced capacity for myotube formation-a deficiency that was rectified by supplementing with GlcNAc and Gal-3. Our results highlight the role of Gal-3 interaction with oligosaccharides, whose synthesis is promoted by GlcNAc in facilitating myotube formation. Single-cell tracking revealed that GlcNAc and Gal-3 increase myoblast motility, leading to a faster, coordinated, flow-like movement-a collective behavior, along which myotubes form through cell fusion. Interestingly, myoblasts contributing to myotube formation were pre-positioned along the eventual shape of the myotubes before this flow-like movement was fully established. These myoblasts moved along the flow, paused, and even moved against it, suggesting that both coordinated flow and initial spatial positioning contribute to myoblast alignment along the axis of future myotubes. CONCLUSION: Our findings suggest that GlcNAc, in conjunction with Gal-3, enhances myotube formation by fostering an environment conducive to myoblast positioning, establishing optimal coordinated flow-like movement, and facilitating fusion. This suggests potential therapeutic applications of GlcNAc in muscle repair and muscle disorders.

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 integrity0.0000.000
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 head0.010
GPT teacher head0.274
Teacher spread0.264 · 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
Published2025
Admission routes2
Has abstractyes

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