Protocol Optimization for Direct Reprogramming of Primary Human Fibroblast into Induced Striatal Neurons

Abstract

The modeling of neuropathology on induced neurons obtained by cell reprogramming technologies can fill a gap between clinical trials and studies on model organisms for the development of treatment strategies for neurodegenerative diseases. Patient-specific models based on patients’ cells play an important role in such studies. There are two ways to obtain induced neuronal cells. One is based on induced pluripotent stem cells. The other is based on direct reprogramming, which allows us to obtain mature neuronal cells from adult somatic cells, such as dermal fibroblasts. Moreover, the latter method makes it possible to better preserve the age-related aspects of neuropathology, which is valuable for diseases that occur with age. However, direct methods of reprogramming have a significant drawback associated with low cell viability during procedures. Furthermore, the number of reprogrammable neurons available for morphological and functional studies is limited by the initial number of somatic cells. In this article, we propose modifications of a previously developed direct reprogramming method, based on the combination of microRNA and transcription factors, which allowed us to obtain a population of functionally active induced striatal neurons (iSNs) with a high efficiency. We also overcame the problem of the presence of multinucleated neurons associated with the cellular division of starting fibroblasts. Synchronization cells in the G1 phase increased the homogeneity of the fibroblast population, increased the survival rate of induced neurons, and eliminated the presence of multinucleated cells at the end of the reprogramming procedure. We have demonstrated that iSNs are functionally active and able to form synaptic connections in co-cultures with mouse cortical neurons. The proposed modifications can also be used to obtain a population of other induced neuronal types, such as motor and dopaminergic ones, by selecting transcription factors that determine differentiation into a region-specific neuron.