Scalable generation of mature cerebellar organoids from human pluripotent stem cells and characterization by immunostaining

Teresa P. Silva, Tiago G. Fernandes, Diogo E.S. Nogueira, Carlos A.V. Rodrigues, Evguenia P. Bekman, Yas Hashimura, Sunghoon Jung, Brian Lee, Maria Carmo-Fonseca, Joaquim M.S. Cabral

Research output: Contribution to journalArticlepeer-review

29 Citations (Scopus)

Abstract

The cerebellum plays a critical role in the maintenance of balance and motor coordination, and a functional defect in different cerebellar neurons can trigger cerebellar dysfunction. Most of the current knowledge about disease-related neuronal phenotypes is based on postmortem tissues, which makes understanding of disease progression and development difficult. Animal models and immortalized cell lines have also been used as models for neurodegenerative disorders. However, they do not fully recapitulate human disease. Human induced pluripotent stem cells (iPSCs) have great potential for disease modeling and provide a valuable source for regenerative approaches. In recent years, the generation of cerebral organoids from patient-derived iPSCs improved the prospects for neurodegenerative disease modeling. However, protocols that produce large numbers of organoids and a high yield of mature neurons in 3D culture systems are lacking. The protocol presented is a new approach for reproducible and scalable generation of human iPSC-derived organoids under chemically-defined conditions using scalable single-use bioreactors, in which organoids acquire cerebellar identity. The generated organoids are characterized by the expression of specific markers at both mRNA and protein level. The analysis of specific groups of proteins allows the detection of different cerebellar cell populations, whose localization is important for the evaluation of organoid structure. Organoid cryosectioning and further immunostaining of organoid slices are used to evaluate the presence of specific cerebellar cell populations and their spatial organization.

Original languageEnglish
Article numbere61143
Pages (from-to)1-21
Number of pages21
JournalJournal of Visualized Experiments
Volume2020
Issue number160
DOIs
Publication statusPublished - Jun 2020
Externally publishedYes

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