Label-free enrichment of fate-biased human neural stem and progenitor cells.

Human neural stem and progenitor cells (hNSPCs) have therapeutic potential to treat neural diseases and injuries since they protect brain tissue and can mature into the three main cell types found in the brain and spinal cord: astrocytes, neurons, and oligodendrocytes. However, challenges remain for using these cells therapeutically since hNSPC batches expanded for patient treatment contain heterogeneous cells linked to different mature cell fates. This means that it can be quite difficult to control how the cells behave in therapeutic applications. HNSPCs that mature into astrocytes are of interest for specific neurological diseases, creating a need for approaches that can detect and isolate these cells. HNSPCs that will form astrocytes have distinct cell surface properties, and we surmised these properties could be used to sort heterogeneous hNSPCs to generate enriched populations of cells that will make astrocytes. We used a novel cell sorting platform that does not require labeling of cells. We implemented a two-step cell sorting scheme, consisting of analysis to define the optimal sorting parameters followed by separation of cells using the best settings. We developed a novel cell sorting device that increased sorting reproducibility and provided both enriched and depleted cell populations in a single sort. We found hNSPCs that will form astrocytes could be separated from the other cell types present in hNSPC cultures, providing the first demonstration that these cells could be enriched without the use of labels. Enriched human stem cells capable of making astrocytes enable future experiments to determine the specific properties of these important cells and test their therapeutic efficacy in models of neurological diseases.