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Updated: Oct 1, 2026

Reliable Identification of Living Dopaminergic Neurons in Midbrain Cultures Using RNA Sequencing and TH-promoter-driven eGFP Expression
Published on: February 10, 2017
Developmentally Guided Differentiation of Ventral Midbrain Dopaminergic Cells Validated in Proteopathy-Based
Heechang Moon1, Heejeong Kim2,3, Elliot H Lee4,5
1Department of Biomedical Science, Graduate School of Biomedical Science and Engineering, Hanyang University, Seoul, Republic of Korea.
Abstract:
Parkinson's disease (PD) involves progressive degeneration of nigrostriatal ventral midbrain dopaminergic (vmDA) neurons and Lewy body proteopathy, necessitating scalable, lineage-faithful donor cells. However, variability in human pluripotent stem cell (hPSC) differentiation and incomplete ventral midbrain identity limit translational use. Here, we establish a developmentally guided differentiation protocol that reproducibly specifies EN1-positive vmDA progenitors through temporally optimized SHH, WNT/β-catenin, and FGF8 signaling. The resulting progenitors mature into vmDA neurons exhibiting stimulus-dependent dopamine release and maturation-associated pacemaking activity. Progenitors can be cryopreserved at a defined stage while retaining viability and neurogenic capacity. Functional validation was performed using complementary proteopathy-based PD models. In vitro, optogenetic induction of α-synuclein aggregation (OASIS) triggered robust aggregate formation and selective degeneration of TH-positive vmDA neurons in both two-dimensional cultures and three-dimensional neurospheroids. In vivo, we established a conditional β23 proteopathy-based PD mouse model exhibiting progressive nigrostriatal degeneration and motor impairment. Transplantation of hESC-derived vmDA progenitors into advanced-stage PD mice led to graft survival, differentiation into vmDA neurons, and significant motor improvement. Together, these findings define a robust vmDA differentiation framework validated across proteopathy-based disease modeling and transplantation contexts, supporting its application in PD modeling and cell therapy.
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