Background: Somatic cell reprogramming is routinely used to generate donor-specific human induced pluripotent stem cells (hiPSCs) to facilitate studies of disease in a human context. The directed differentiation of hiPSCs can generate large quantities of patient-derived cells; however, such methodologies frequently yield heterogeneous populations of neurons and glia that require extended timelines to achieve electrophysiological maturity. More recently, transcription factor-based induction protocols have been show to rapidly generate defined neuronal populations from hiPSCs.
New Method: In a manner similar to our previous adaption of NGN2-glutamatergic neuronal induction from hiPSC-derived neural progenitor cells (NPCs), we now adapt an established protocol of lentiviral overexpression of ASCL1 and DLX2 to hiPSC-NPCs.
Results: We demonstrate induction of a robust and highly pure population of functional GABAergic neurons (iGANs). Importantly, we successfully applied this technique to hiPSC-NPCs derived from ten donors across two independent laboratories, finding it to be an efficient and highly reproducible approach to generate induced GABAergic neurons. Our results show that, like hiPSC-iGANs, NPC-iGANs exhibit increased GABAergic marker expression, electrophysiological maturity, and have distinct transcriptional profiles that distinguish them from other cell-types of the brain. Nonetheless, until donor-matched hiPSCs-iGANs and NPC-iGANs are directly compared, we cannot rule out the possibility that subtle differences in patterning or maturity may exist between these populations; one should always control for cell source in all iGAN experiments.
Conclusions: This methodology, relying upon an easily cultured starting population of hiPSC-NPCs, makes possible the generation of large-scale defined co-cultures of induced glutamatergic and GABAergic neurons for hiPSC-based disease models and precision drug screening.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7426253 | PMC |
http://dx.doi.org/10.1016/j.jneumeth.2019.108548 | DOI Listing |
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