In vitro Modeling for Neurological Diseases using Direct Conversion from Fibroblasts to Neuronal Progenitor Cells and Differentiation into Astrocytes

Abstract

Research on neurological disorders focuses primarily on the impact of neurons on disease mechanisms. Limited availability of animal models severely impacts the study of cell type specific contributions to disease. Moreover, animal models usually do not reflect variability in mutations and disease courses seen in human patients. Reprogramming methods for generation of induced pluripotent stem cells (iPSCs) have revolutionized patient specific research and created valuable tools for studying disease mechanisms. However, iPSC technology has disadvantages such as time, labor commitment, clonal selectivity and loss of epigenetic markers. Recent modifications of these methods allow more direct generation of cell lineages or specific cell types, bypassing clonal isolation or a pluripotent stem cell state. We have developed a rapid direct conversion method to generate induced Neuronal Progenitor Cells (iNPCs) from skin fibroblasts utilizing retroviral vectors in combination with neuralizing media. The iNPCs can be differentiated into neurons (iNs) oligodendrocytes (iOs) and astrocytes (iAs). iAs production facilitates rapid drug and disease mechanism testing as differentiation from iNPCs only takes 5 days. Moreover, iAs are easy to work with and are generated in pure populations at large numbers. We developed a highly reproducible co-culture assay using mouse GFP+ neurons and patient derived iAs to evaluate potential therapeutic strategies for numerous neurological and neurodegenerative disorders. Importantly, the iA assays are scalable to 384-well format facilitating the evaluation of multiple small molecules in one plate. This approach allows simultaneous therapeutic evaluation of multiple patient cell lines with diverse genetic background. Easy production and storage of iAs and capacity to screen multiple compounds in one assay renders this methodology adaptable for personalized medicine.