Development and Optimization of a 3D Bioprinted Experimental Model of Skeletal Muscle
Notice bibliographique
Résumé
Background Traditional cell culture has been the foundation of biomedical research for over 100 years and remains an essential scientific tool. Yet it is becoming increasingly recognized that biological and technical deficiencies limit the relevance of cell culture to health and disease. These deficiencies are especially relevant to muscle tissues; it is difficult to measure contraction in cultured cells, and physical interactions between cells and the physical environment can modulate tissue‐level function. To fill this gap, we used 3D bioprinting technology to create a free‐floating and bioreactor‐free experimental model of skeletal muscle. The model is designed for contraction to be assessed as muscle shortening against a physiologically relevant auxotonic load. Methods C2C12 mouse skeletal muscle myoblasts were bioprinted at 2.5×10 7 cells/mL in a bioink containing 0.25–1.25% RGD‐coupled‐alginate, 1–2 mg/mL collagen‐I and 0–20 mg/mL fibrinogen using an Aspect Biosystems RX‐1 bioprinter. Cells were printed as a 10 mm diameter ring, with or without an acellular frame providing an auxotonic load opposing contraction. Cells were thrombin treated to polymerise fibrinogen, cultured with or without the antifibrinolytic agent aprotinin (20 μg/mL), and differentiated on day 1–5 in a low serum media with high glucose and insulin. Tissue structure was assessed by live cell phase contract microscopy and filamentous actin immunofluorescence. Cell phenotype was assessed by qPCR for contraction‐relevant genes. Results Cells printed in stiff alginate (≥0.5%) did not form cell‐cell contacts required for myotube differentiation. Soft alginate (<0.5%) allowed cell elongation but rings rapidly collapsed, necessitating the use of a very stiff acellular supporting frame (≥1.0% alginate). Early bioinks including only alginate and collagen promoted myotube formation but fibres tore themselves apart under their own contractile tone. Fibrinogen dose dependently improved fibre integrity, and culturing with 20 g/mL aprotinin dramatically improved overall tissue structure (lifespan >10 days) with extensive formation of elongated, multinucleated and f‐actin‐rich myotubes. Final design parameters of: 0.25% cellular alginate; 1 mg/mL collagen; 20 mg/mL fibrinogen; 1% alginate acellular frame; differentiated on day 3; maintained until day 10, resulted in 30‐fold upregulation of myosin heavy chain 1, with a switch from β‐ to α‐actin and reduction in muscle cadherin expression. These outcomes are entirely consistent with the formation of physically stable contractile myotubes. Conclusion Our 3D bioprinted skeletal muscle represents a novel model for studying muscle biology in vitro , incorporating a physiologically relevant 3D structure, realistic mechanical environment, and the ability to directly measure contraction. The standalone structure requires no specialist bioreactor to produce or maintain, making the model easily accessible to a wide range of biomedical researchers, to better replicate health and disease states. Support or Funding Information Funding: NSERC Discovery Grant (ARW), Research Manitoba Studentship (SS, JO), University of Manitoba Undergraduate Research Award (AK) A freshly 3D bioprinted skeletal muscle construct within a 24 mm diameter ThinCert membrane. The translucent structural (red arrow) and opaque muscle layers (blue arrow) can clearly be seen. The texture of the crosshatching in the structural layer can be seen, providing an auxotonic load opposing muscle contraction. Figure 1 Widefield immunofluorescence of 3D bioprinted skeletal muscle constructs showing actin filaments (red) and nuclei (blue) after 7 days of differentiation in a low serum media with high glucose, insulin and 20 ug/mL aprotinin. There is extensive formation of elongated multinucleated cells, corresponding with >30‐fold increase in myosin heavy chain 1 (MYH1) mRNA abundance, and a switch from β‐ to α‐actin expression. Figure 2
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».