An Efficient 2D Protocol for Differentiation of iPSCs into Mature Postmitotic Dopaminergic Neurons: Application for Modeling Parkinson's Disease
- PMID: 37108456
- PMCID: PMC10139404
- DOI: 10.3390/ijms24087297
An Efficient 2D Protocol for Differentiation of iPSCs into Mature Postmitotic Dopaminergic Neurons: Application for Modeling Parkinson's Disease
Abstract
About 15% of patients with parkinsonism have a hereditary form of Parkinson's disease (PD). Studies on the early stages of PD pathogenesis are challenging due to the lack of relevant models. The most promising ones are models based on dopaminergic neurons (DAns) differentiated from induced pluripotent stem cells (iPSCs) of patients with hereditary forms of PD. This work describes a highly efficient 2D protocol for obtaining DAns from iPSCs. The protocol is rather simple, comparable in efficiency with previously published protocols, and does not require viral vectors. The resulting neurons have a similar transcriptome profile to previously published data for neurons, and have a high level of maturity marker expression. The proportion of sensitive (SOX6+) DAns in the population calculated from the level of gene expression is higher than resistant (CALB+) DAns. Electrophysiological studies of the DAns confirmed their voltage sensitivity and showed that a mutation in the PARK8 gene is associated with enhanced store-operated calcium entry. The study of high-purity DAns differentiated from the iPSCs of patients with hereditary PD using this differentiation protocol will allow for investigators to combine various research methods, from patch clamp to omics technologies, and maximize information about cell function in normal and pathological conditions.
Keywords: Parkinson’s disease; SOCE currents; calcium; differentiation protocol; disease modeling; high purity of neuron culture; iPSCs.
Conflict of interest statement
The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.
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