A robust protocol for the generation of human midbrain organoids
The lack of advanced in vitro models recapitulating the human brain complexity is still a major obstacle in brain development and neurological disease research. Here, we describe a robust protocol to derive human midbrain organoids from neuroepithelial stem cells. These complex 3D models are charact...
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Published in: | STAR protocols Vol. 2; no. 2; p. 100524 |
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Main Authors: | , , , |
Format: | Journal Article |
Language: | English |
Published: |
United States
Elsevier Inc
18-06-2021
Elsevier |
Subjects: | |
Online Access: | Get full text |
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Summary: | The lack of advanced in vitro models recapitulating the human brain complexity is still a major obstacle in brain development and neurological disease research. Here, we describe a robust protocol to derive human midbrain organoids from neuroepithelial stem cells. These complex 3D models are characterized by the presence of functional neurons, including dopaminergic neurons and glial cells, making them particularly attractive for the study of Parkinson disease.
For complete details on the use and execution of this protocol, please refer to Monzel et al. (2017).
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•Reproducible generation of midbrain organoids from patterned neural precursor cells•Midbrain organoids comprise dopaminergic neurons, astrocytes, and oligodendrocytes•Cellular interaction and maturation are boosted by extracellular matrix embedding•Suitable for in vitro midbrain development research and disease modeling
The lack of advanced in vitro models recapitulating the human brain complexity is still a major obstacle in brain development and neurological disease research. Here, we describe a robust protocol to derive human midbrain organoids from neuroepithelial stem cells. These complex 3D models are characterized by the presence of functional neurons, including dopaminergic neurons and glial cells, making them particularly attractive for the study of Parkinson disease. |
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 Technical contact These authors contributed equally Lead contact |
ISSN: | 2666-1667 2666-1667 |
DOI: | 10.1016/j.xpro.2021.100524 |