UC Irvine

Human mesenchymal stem cells (hMSCs) are adult stem cells that possess great therapeutic potential in the field of regenerative medicine. These stem cells have the potential to differentiate into various types of human tissue upon the addition of differentiation-inducing cytokines, making them one of the prime candidates used for tissue engineering. In addition, upon hMSC transplantation or infusion, the cells secrete a broad array of growth factors and cytokines to reduce inflammation and expedite wound healing. However, hMSC-based therapies are also known for their clinical outcome variability, which could be accounted for by the complex and dynamic population heterogeneity of hMSCs that we have not yet fully understood as a scientific community. The primary goal of this dissertation is to develop additional biomarkers for hMSCs using dielectrophoresis (DEP) in hope of gaining a deeper understanding of its population dynamics and paving a way to enhance the consistency of clinical outcomes. DEP, a label-free cell polarization technique, allows us to rapidly characterize the biophysical properties (capacitance, conductivity, and permittivity) of a large population of hMSCs. A comparison of the collected DEP spectra collected as part of this dissertation and the corresponding panel of biophysical properties shows that DEP can detect the unique electrical properties of hMSCs and pick up minute differences between hMSCs harvested from different human tissues. In addition, the results from a subsequent large-scale characterization study shows that membrane capacitance and cytoplasm conductivity are positively correlated with the level of in vitro expansion. Further comparing the DEP characterization results to differentiation data shows that membrane capacitance and conductivity correlate with osteogenic capacity while cytoplasm conductivity correlates with adipogenic capacity. Stemming from these results, sorting biologically relevant and electrically distinct hMSCs subpopulations using DEP was explored. To better quantify the DEP response in a microfluidic sorting channel, an image processing and analysis scheme was developed to allow for single-cell level cell trajectory analysis under the influence of DEP and hydrodynamic drag force, which confirm the extent of hMSCs’ intrapopulation heterogeneity. A comparison of quantitative sorting data obtained with earlier characterization data reveals similar behavior, indicating that the knowledge gained from DEP characterization can be directly translated toward sorting.