Retinal Organoid Induction System for Derivation of 3D Retinal Tissues from Human Pluripotent Stem Cells.

IF 1.2 4区 综合性期刊 Q3 MULTIDISCIPLINARY SCIENCES
Yuanyuan Guan, Bingbing Xie, Xiufeng Zhong
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引用次数: 6

Abstract

Retinal degenerative diseases are the main causes of irreversible blindness without effective treatment. Pluripotent stem cells that have the potential to differentiate into all types of retinal cells, even mini-retinal tissues, hold huge promises for patients with these diseases and many opportunities in disease modeling and drug screening. However, the induction process from hPSCs to retinal cells is complicated and time-consuming. Here, we describe an optimized retinal induction protocol to generate retinal tissues with high reproducibility and efficiency, suitable for various human pluripotent stem cells. This protocol is performed without the addition of retinoic acid, which benefits the enrichment of cone photoreceptors. The advantage of this protocol is the quantification of EB size and plating density to significantly enhance the efficiency and repeatability of retinal induction. With this method, all major retinal cells sequentially appear and recapitulate the main steps of retinal development. It will facilitate downstream applications, such as disease modeling and cell therapy.

从人多能干细胞衍生三维视网膜组织的视网膜类器官诱导系统。
视网膜退行性疾病是无法有效治疗的不可逆失明的主要原因。多能干细胞有潜力分化成所有类型的视网膜细胞,甚至是微型视网膜组织,为患有这些疾病的患者带来了巨大的希望,在疾病建模和药物筛选方面也有很多机会。然而,从造血干细胞到视网膜细胞的诱导过程是复杂和耗时的。在这里,我们描述了一种优化的视网膜诱导方案,以产生高可重复性和效率的视网膜组织,适用于各种人类多能干细胞。该方案是在没有添加视黄酸的情况下进行的,这有利于锥体光感受器的富集。该方案的优点是量化EB大小和镀密度,显著提高视网膜诱导的效率和可重复性。用这种方法,所有主要的视网膜细胞依次出现,再现了视网膜发育的主要步骤。它将促进下游应用,如疾病建模和细胞治疗。
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来源期刊
Jove-Journal of Visualized Experiments
Jove-Journal of Visualized Experiments MULTIDISCIPLINARY SCIENCES-
CiteScore
2.10
自引率
0.00%
发文量
992
期刊介绍: JoVE, the Journal of Visualized Experiments, is the world''s first peer reviewed scientific video journal. Established in 2006, JoVE is devoted to publishing scientific research in a visual format to help researchers overcome two of the biggest challenges facing the scientific research community today; poor reproducibility and the time and labor intensive nature of learning new experimental techniques.
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