Transplantation of human embryonic stem cell (hESC)-derived neural progenitors is a potential treatment for neurological disorders, but relatively little is known about the time course for human neuron maturation after transplantation and the emergence of morphological and electrophysiological properties. To address this gap, we transplanted hESC-derived human GABAergic interneuron progenitors into the mouse hippocampus, and then characterized their electrophysiological properties and dendritic arborizations after transplantation by means of ex vivo whole-cell patch clamp recording, followed by biocytin staining, confocal imaging and neuron reconstruction software. We asked whether particular electrophysiological and morphological properties showed maturation-dependent changes after transplantation. We also investigated whether the emergence of particular electrophysiological properties were linked to increased complexity of the dendritic arbors. Human neurons were classified into five distinct neuronal types (Type I-V), ranging from immature to mature fast-spiking interneurons. Hierarchical clustering of the dendritic morphology and Sholl analyses suggested four morphologically distinct classes (Class A-D), ranging from simple/immature to highly complex. Incorporating all of our data regardless of neuronal classification, we investigated whether any electrophysiological and morphological features correlated with time post-transplantation. This analysis demonstrated that both dendritic arbors and electrophysiological properties matured after transplantation.
Pubmed ID: 32813731 RIS Download
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Imaris provides range of capabilities for working with three dimensional images. Uses flexible editing and processing functions, such as interactive surface rendering and object slicing capabilities. And output to standard TIFF, Quicktime and AVI formats. Imaris accepts virtually all image formats that are used in confocal microscopy and many of those used in wide-field image acquisition.
View all literature mentionsDatabase of neuronal cell types based on multimodal characterization of single cells to enable data-driven approaches to classification. It includes data such as electrophysiology recordings, imaging data, morphological reconstructions, and RNA and DNA sequencing data.
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