Abstract
Differentiating cerebellar organoids can be challenging due to complex cell organization and structure in the cerebellum. Different approaches were investigated to recapitulate differentiation process of the cerebellum from human-induced pluripotent stem cells (hiPSCs) without high efficiency. This study was carried out to test the hypothesis that the combination of different signaling factors including retinoic acid (RA), Wnt activator, and sonic hedgehog (SHH) activator promotes the cerebellar differentiation of hiPSCs. Wnt, RA, and SHH pathways were activated by CHIR99021 (CHIR), RA, and purmorphamine (PMR), respectively. Different combinations of the morphogens (RA/CHIR, RA/PMR, CHIR/PMR, and RA/CHIR/PMR) were utilized, and the spheroids (day 35) were characterized for the markers of three cerebellum layers (the molecular layer, the Purkinje cell layer, and the granule cell layer). Of all the combinations tested, RA/CHIR/PMR promoted both the Purkinje cell layer and the granule cell layer differentiation. The cells also exhibited electrophysiological characteristics using whole-cell patch clamp recording, especially demonstrating Purkinje cell electrophysiology. This study should advance the understanding of different signaling pathways during cerebellar development to engineer cerebellum organoids for drug screening and disease modeling. Impact statement This study investigated the synergistic effects of retinoic acid, Wnt activator, and sonic hedgehog activator on cerebellar patterning of human-induced pluripotent stem cell (hiPSC) spheroids and organoids. The results indicate that the combination promotes the differentiation of the Purkinje cell layer and the granule cell layer. The cells also exhibit electrophysiological characteristics using whole-cell patch clamp recording, especially demonstrating Purkinje cell electrophysiology. The findings are significant for understanding the biochemical signaling of three-dimensional microenvironment on neural patterning of hiPSCs for applications in organoid engineering, disease modeling, and drug screening.