Transcription Factor-Mediated Differentiation of Motor Neurons from Human Pluripotent Stem Cells
Summary
Studying the pathogenesis of neurological diseases with animal models might not always truly recapitulate their pathophysiology, due to species differences. Fortunately, human pluripotent stem cells (hPSCs) including embryonic stem cells (ESCs) and induced pluripotent stem cells (iPSCs), especially derived from patients, have been widely employed to induce neural progenitor cells (NPCs) and further multiple neural subtypes. Particularly in the past decade, hPSC-based cell sources have been applied in studying neural development, cell therapy, disease modeling, and drug screening, among others. The generation of unlimited amount of neurons also facilitates a variety of biochemical assays, mass spectrometry, omic analysis, and next-generation sequencing, which thus provides an excellent tool in modeling neurodegenerative and neurodevelopmental diseases. Dysfunction or death of motor neurons (MNs) in the spinal cord and motor cortex is implicated in various motor neuron diseases (MNDs). Yet, producing high-purity and high-yield MNs remains a major challenge due to the complexity of MN specification during development. In this chapter, we describe a method of generating functional MNs via lentiviral delivery of transcription factors, based on the preservable NPC platform derived from hPSCs. Specifically, we transduce NPCs with a single lentivirus co-expressing three transcription factors including NGN2, ISL1, and LHX3, which is necessary and sufficient to induce mature MNs with high efficiencies (~90%) within 3 weeks. This chapter thus provides a robust method to generate high-purity hPSC-MNs at very high yields, enabling the acquisition of rich patient-specific MNs to be used for modeling the molecular underpinnings of MNDs. © 2023. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.
| Authors | Wu J, Tang Y |
|---|---|
| Journal | Methods in molecular biology (Clifton, N.J.) |
| Publication Date | 2023;2593:245-258 |
| PubMed | 36513936 |
| DOI | 10.1007/978-1-0716-2811-9_16 |