Efficient Generation of Skeletal Myogenic Progenitors from Human Pluripotent Stem Cells
| Autor: | Rita C.R. Perlingeiro, Jaemin Kim, Alessandro Magli |
|---|---|
| Rok vydání: | 2016 |
| Předmět: |
0301 basic medicine
Myogenesis Biology Paraxial mesoderm formation Cell biology Cell therapy 03 medical and health sciences 030104 developmental biology 0302 clinical medicine Directed differentiation Paraxial mesoderm Progenitor cell PAX7 Induced pluripotent stem cell 030217 neurology & neurosurgery |
| Zdroj: | Working with Stem Cells ISBN: 9783319305806 |
| DOI: | 10.1007/978-3-319-30582-0_16 |
| Popis: | The rapid progress of research involving pluripotent stem cells in recent years provides an unprecedented opportunity to develop new and efficient cell replacement therapies for the treatment of degenerative diseases, such as muscular dystrophies. Nevertheless, the directed differentiation of pluripotent stem cells into a specific lineage is challenging, particularly the skeletal myogenic lineage which is poorly recapitulated during the in vitro differentiation of pluripotent stem cells. As demonstrated by our previous work, this limitation can be overcome by controlled expression of PAX7, which forces the commitment and expansion of human skeletal myogenic progenitors. Since variation in paraxial mesoderm formation among different human pluripotent stem cell lines/clones can affect the ability of PAX7 to induce the skeletal myogenic lineage, here we describe the optimization of our previously published protocol for deriving skeletal myogenic progenitors from these cells. This method takes advantage of the ability of the GSK3β inhibitor to induce paraxial mesoderm commitment in differentiating cells. In addition, upon flow cytometry purification, human PAX7-induced skeletal myogenic progenitors can be propagated and differentiated into skeletal myotubes. The following protocol will enable researchers to derive skeletal myogenic progenitors from pluripotent stem cells for disease modeling as wells as therapeutic purposes. |
| Databáze: | OpenAIRE |
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