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Direct reprogramming of adult human fibroblasts: Generation of dopaminergic neurons for cell-based replacement therapy

Authors: Shrigley, Shelby; Pereira, Maria; Drouin-Ouellet, Janelle; Parmar, Malin;

Direct reprogramming of adult human fibroblasts: Generation of dopaminergic neurons for cell-based replacement therapy

Abstract

Cell-based replacement therapy has great potential to address the motor symptoms of Parkinson’s disease (PD), a neurodegenerative disease resulting from the progressive loss of dopaminergic cells within the nigrostriatal system. Direct neural reprogramming is a technology where a somatic cell is directly converted into an induced neuron without going through a pluripotent intermediate stage. Induced neurons (iNs) are a unique resource obviating safety concerns associated with pluripotency, as well as ethical concerns with embryonic derived cells, whilst allowing for patient specific cells or matched donors. We have previously shown that dopaminergic (DA) neuronal fate could be generated from human fetal fibroblasts using forced expression of Ascl1 and specific DA fate determinants. However, this early protocol showed low efficiency when converting adult human fibroblasts. Here we build on our reprogramming method to convert human adult fibroblasts into induced dopaminergic neurons (iDANs) with a new combination of transcription factors combined with a RE1-silencing transcription factor (REST) knock-down. High content screening analysis shows that approximately 20% of converted cells express tyrosine hydroxylase (TH) using our new reprogramming cocktail. Furthermore, there is a progressive morphological maturation from day 6 and our iDANs express both mature neuronal and dopaminergic markers. Results provide a more robust and efficient protocol for the generation of iDANs and will help to pave the way for future research assessing their potential for brain repair.

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This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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