Transcriptome profiling of human pluripotent stem cell-derived cerebellar organoids reveals faster commitment under dynamic conditions

类有机物 诱导多能干细胞 转录组 生物 小脑 神经科学 细胞生物学 胚胎干细胞 基因表达 基因 遗传学
作者
Teresa P. Silva,Rui Sousa‐Luís,Tiago G. Fernandes,Evguenia Bekman,Carlos A. V. Rodrigues,Sandra H. Vaz,Leonilde M. Moreira,Yas Hashimura,Sunghoon Jung,Brian Lee,Maria Carmo‐Fonseca,Joaquim M. S. Cabral
出处
期刊: [Cold Spring Harbor Laboratory]
被引量:1
标识
DOI:10.1101/2021.01.27.428468
摘要

Abstract Human induced pluripotent stem cells (iPSCs) have great potential for disease modeling. However, generating iPSC-derived models to study brain diseases remains a challenge. In particular, the ability to recapitulate cerebellar development in vitro is still limited. We presented a reproducible and scalable production of cerebellar organoids by using the novel Vertical-Wheel single-use bioreactors, in which functional cerebellar neurons were obtained. Here, we evaluate the global gene expression profiles by RNA sequencing (RNA-seq) across cerebellar differentiation, demonstrating a faster cerebellar commitment in this novel dynamic differentiation protocol. Furthermore, transcriptomic profiles suggest a significant enrichment of extracellular matrix (ECM) in dynamic-derived cerebellar organoids, which can better mimic the neural microenvironment and support a consistent neuronal network. Thus, an efficient generation of organoids with cerebellar identity was achieved for the first time in a continuous process using a dynamic system without the need of organoids encapsulation in ECM-based hydrogels, allowing the possibility of large-scale production and application in high-throughput processes. The presence of factors that favors angiogenesis onset was also detected in dynamic condition, which can enhance functional maturation of cerebellar organoids. We anticipate that large-scale production of cerebellar organoids may help developing models for drug screening, toxicological tests and studying pathological pathways involved in cerebellar degeneration.
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