Ventral Telencephalic Patterning Protocols for Induced Pluripotent Stem Cells

The differentiation of human induced pluripotent stem cells (hiPSCs) into specific cell types for disease modeling and restorative therapies is a key research agenda and offers the possibility to obtain patient-specific cells of interest for a wide range of diseases. Basal forebrain cholinergic neurons (BFCNs) play a particular role in the pathophysiology of Alzheimer's dementia and isolated dystonias. In this work, various directed differentiation protocols based on monolayer neural induction were tested for their effectiveness in promoting a ventral telencephalic phenotype and generating BFCN. Ventralizing factors [i.e., purmorphamine and Sonic hedgehog (SHH)] were applied at different time points, time intervals, and concentrations. In addition, caudal identity was prevented by the use of a small molecule XAV-939 that inhibits the Wnt-pathway. After patterning, gene expression profiles were analyzed by quantitative PCR (qPCR). Rostro-ventral patterning is most effective when initiated simultaneously with neural induction. The most promising combination of patterning factors was 0.5 mu M of purmorphamine and 1 mu M of XAV-939, which induces the highest expression of transcription factors specific for the medial ganglionic eminence, the source of GABAergic inter- and cholinergic neurons in the telencephalon. Upon maturation of cells, the immune phenotype, as well as electrophysiological properties were investigated showing the presence of marker proteins specific for BFCN (choline acetyltransferase, ISL1, p75, and NKX2.1) and GABAergic neurons. Moreover, a considerable fraction of measured cells displayed mature electrophysiological properties. Synaptic boutons containing the vesicular acetylcholine transporter (VACHT) could be observed in the vicinity of the cells. This work will help to generate basal forebrain interneurons from hiPSCs, providing a promising platform for modeling neurological diseases, such as Alzheimer's disease or Dystonia.

Automated summary

Differentiating hiPSCs into BFCNs using specific protocols resulted in cells displaying mature immune phenotype and electrophysiological properties, showing potential for modeling neurological diseases such as Alzheimer's and Dystonia.