CHARACTERIZING THE PHYSICAL PROPERTIES OF LIVING CELLS THROUGH MICROFLUIDIC IMPEDANCE SENSING

The purpose of this research is to explore and investigate the biophysical properties of living cells using microfluidics based electrical impedance sensing (EIS) technique. It provides a non-invasive approach to detect label-free biological markers in the regulation of cellular activities even at a molecular level. We specifically focus on the development, testing, and theoretical modeling of electrical impedance spectroscopy for neuroblastoma cells and endothelial cells. First, we demonstrate that the EIS technique can be used to monitor the progressive mitochondrial fission/fusion modification in genetically modified human neuroblastoma cell lines. Our results characterize quantitatively the abnormal mitochondrial dynamics through the variations in cytoplasm conductivity. Secondly, we employ a real time EIS method to determine the biophysical properties of the junctions which join one endothelial cell with one another in a monolayer of endothelial cells. In particular, we examine the role of the protein, c-MYC oncogene, in the barrier function. Our results show that the downregulation of c-MYC oncogene enhances the endothelial barrier dysfunction associated with inflammation. Finally, we measure and find that the electrical admittance (the reciprocal of the impedance) of the monolayer of endothelial cellular networks exhibits an anomalous power law of the form, Y ∝ ωα, over a wide range of frequency, with the value of the exponent, α, depending on the severity of the inflammation. We attribute the power law to the changes of the intercellular electric permeability between neighboring endothelial cells. Thus, the inflammation gives rise to relatively smaller values of α compared to that of the no-inflammation group. Furthermore, we propose a simple percolation model of a large R-C network to confirm the emergent of power law scaling behavior of the complex admittance, suggesting that the endothelial network behaves as a complex microstructural network and its electrical properties may be simulated by a large R-C network.