Dataset Information


Efficient myotube formation in 3D bioprinted tissue construct by biochemical and topographical cues.

ABSTRACT: Biochemical and biophysical cues directly affect cell morphology, adhesion, proliferation, and phenotype, as well as differentiation; thus, they have been commonly utilized for designing and developing biomaterial systems for tissue engineering applications. To bioengineer skeletal muscle tissues, the efficient and stable formation of aligned fibrous multinucleated myotubes is essential. To achieve this goal, we employed a decellularized extracellular matrix (dECM) as a biochemical component and a modified three-dimensional (3D) cell-printing process to produce an in situ uniaxially aligned/micro-topographical structure. The dECM was derived from the decellularization of porcine skeletal muscles and chemically modified by methacrylate process to enhance mechanical stability. By using this ECM-based material and the 3D printing capability, we were able to produce a cell-laden dECM-based structure with unique topographical cues. The myoblasts (C2C12 cell line) laden in the printed structure were aligned and differentiated with a high degree of myotube formation, owing to the synergistic effect of the skeletal muscle-specific biochemical and topographical cues. In particular, the increase of the gene-expression levels of the dECM structure with topographical cues was approximately 1.5-1.8-fold compared with those of a gelatin methacrylate (GelMA)-based structure with the same topographical cues and a dECM-based structure without topographical cues. According to these in vitro cellular responses, the 3D printed dECM-based structures with topographical cues have the potential for bioengineering functional skeletal muscle tissues, and this strategy can be extended for many musculoskeletal tissues, such as tendons and ligaments and utilized for developing in vitro tissue-on-a-chip models in drug screening and development.

PROVIDER: S-EPMC7141931 | BioStudies |

REPOSITORIES: biostudies

Similar Datasets

| S-EPMC7052892 | BioStudies
| S-EPMC7847672 | BioStudies
| S-EPMC5561246 | BioStudies
2019-02-22 | GSE126877 | GEO
| S-EPMC6768828 | BioStudies
| S-EPMC7681100 | BioStudies
| S-EPMC6639139 | BioStudies
| S-EPMC6746184 | BioStudies
| S-EPMC7292471 | BioStudies
| S-EPMC9313433 | BioStudies