431424 Optimizing Neural Stem Cell Sorting with Dielectrophoresis

Monday, November 9, 2015: 1:45 PM
Ballroom E (Salt Palace Convention Center)
Nicolo S. Mendoza1, Stephen T. Flynn2, Clarissa C. Ro1, Jamison L. Nourse1 and Lisa A. Flanagan1, (1)Neurology, University of California, Irvine, Irvine, CA, (2)Biology, California State University, Fullerton, Irvine, CA

Human neural stem cells have enormous potential as therapeutics for central nervous system injuries and diseases. However, cultures of these cells are heterogenous, containing a mix of stem cells and progenitors linked to specific fates. Distinct progenitors in the neural lineage are detected in dielectrophoresis (DEP) without the use of labels, creating a rapid and convenient method for analyzing and separating these cells.

We demonstrated previously that astrocyte and neuron progenitors could be isolated from mouse neural stem and progenitor cells (NSPCs) at specific frequencies in DEP.  Furthermore, the specific membrane capacitance values of both mouse and human cells reflect their fate potential and distinguish astrocyte and neuron progenitors. In our previous DEP-based sorts, we utilized a set frequency range to isolate a specific progenitor population. However, we found that the cells’ responses to the frequencies were not always the same, potentially due to minor variations in the batches of cells, devices used for sorting, or media conductivity across different sorts.

To address this issue, we compared predicting the appropriate sorting frequency by two approaches - generating a pre-sorting analysis of cell trapping at escalating frequencies in the sorting device (mini trapping curve) or analyzing the cells in a 3DEP Reader.  Data obtained from the 3DEP Reader analysis provided a good prediction of the mini trapping curve data and rapidly identified frequencies for sorting. Human NSPCs sorted by frequencies identified in the 3DEP analysis were enriched as confirmed by post-sorting DEP analysis indicating shifts in the DEP frequency response and membrane capacitance of sorted cells compared to controls. Progenitor cells sorted using this approach were analyzed for fate potential by assessing differentiation into neurons or astrocytes. Further analysis focused on quantitative assessment of N-glycosylation in sorted progenitors since we previously found clear links among cell surface glycosylation, membrane capacitance, and cell fate in the neural lineage. Efficient sorting of human neural stem cells into distinct pools of progenitors enables further study and optimization of these cells to treat human injuries and disease.

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