Label-Free Sorting of Human Mesenchymal Stem Cells Using Insulating Dielectrophoresis

Abstract

Human mesenchymal stem cells (hMSCs) are a multipotent yet heterogeneous cell population with immunosuppressive and regenerative properties, making them highly promising for stem cell therapies targeting metabolic diseases. However, the inherent heterogeneity of hMSCs presents challenges for producing consistent therapeutic outcomes, emphasizing the need to isolate functionally distinct subpopulations. In this study, we employed insulating dielectrophoresis (DEP) via a trap-and-release sorting strategy to generate and characterize subpopulations of adipose tissue (AT)-derived hMSCs. Voltage and frequency parameters were systematically tuned, revealing that higher voltages increased the percentage of trapped cells, while higher frequencies had less impact. Sorted cells underwent a 14-day adipogenic differentiation process, assessed by Oil Red O staining. Our results demonstrated that untrapped cell populations generated at lower voltage and frequency thresholds exhibited enhanced adipogenic differentiation compared to unsorted controls. These findings suggest that DEP can be leveraged to isolate progenitor cells within hMSC populations, enabling the production of homogeneous cell subsets with targeted functional potential. This work highlights the utility of insulating DEP for addressing hMSC heterogeneity and advancing the development of stem cell therapies.

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CytoRecovery’s Role in the Research

CytoRecovery supported this study by providing its specialized device, the CytoChip, which was used to sort stem cells without the need for labels or chemical tags. This technology enabled researchers to separate stem cells into distinct groups based on their natural electrical properties, while maintaining the cells' health and functionality. The CytoChip made it possible to identify a group of cells with a stronger ability to turn into fat cells, which could be important for future stem cell therapies. CytoRecovery’s tools played a key part in showing how this label-free approach can create more consistent and effective cell treatments.