Numerical Model of Streaming DEP for Stem Cell Sorting

Neural stem cells are of special interest due to their potential in neurogenesis to treat spinal cord injuries and other nervous disorders. Flow cytometry, a common technique used for cell sorting, is limited due to the lack of antigens and labels that are specific enough to stem cells of interest. Dielectrophoresis (DEP) is a label-free separation technique that has been recently demonstrated for the enrichment of neural stem/progenitor cells. Here we use numerical simulation to investigate the use of streaming DEP for the continuous sorting of neural stem/progenitor cells. Streaming DEP refers to the focusing of cells into streams by equilibrating the dielectrophoresis and drag forces acting on them. The width of the stream should be maximized to increase throughput while the separation between streams must be widened to increase efficiency during retrieval. The aim is to understand how device geometry and experimental variables affect the throughput and efficiency of continuous sorting of SC27 stem cells, a neurogenic progenitor, from SC23 cells, an astrogenic progenitor. We define efficiency as the ratio between the number of SC27 cells over total number of cells retrieved in the streams, and throughput as the number of SC27 cells retrieved in the streams compared to their total number introduced to the device. The use of cylindrical electrodes as tall as the channel yields streams featuring >98% of SC27 cells and width up to 80 μm when using a flow rate of 10 μL/min and sample cell concentration up to 105 cells/mL.