Electrical Property Characterization of Neural Stem Cells in Differentiation

Electrical property characterization of stem cells could be utilized as a potential label-free biophysical approach to evaluate the differentiation process. However, there has been a lack of technology or tools that can quantify the intrinsic cellular electrical markers (e.g., specific membrane capacitance (C-specific membrane) and cytoplasm conductivity (sigma(cytoplasm))) for a large amount of stem cells or differentiated cells. In this paper, a microfluidic platform enabling the high-throughput quantification of C-specific membrane and sigma(cytoplasm) from hundreds of single neural stem cells undergoing differentiation was developed to explore the feasibility to characterize the neural stem cell differentiation process without biochemical staining. Experimental quantification using biochemical markers (e.g., Nestin, Tubulin and GFAP) of neural stem cells confirmed the initiation of the differentiation process featured with gradual loss in cellular stemness and increased cell markers for neurons and glial cells. The recorded electrical properties of neural stem cells undergoing differentiation showed distinctive and unique patterns: 1) in the suspension culture before inducing differentiation, a large distribution and difference in sigma(cytoplasm) among individual neural stem cells was noticed, which indicated heterogeneity that may result from the nature of suspension culture of neurospheres; and 2) during the differentiation in adhering monolayer culture, significant changes and a large difference in C-specific membrane were located indicating different expressions of membrane proteins during the differentiation process, and a small distribution difference in sigma(cytoplasm) was less significant that indicated the relatively consistent properties of cytoplasm during the culture. In summary, significant differences in C-specific membrane and sigma(cytoplasm) were observed during the neural stem cell differentiation process, which may potentially be used as label-free biophysical markers to monitor this process.