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      Determination of Cell Membrane Capacitance and Conductance via Optically Induced Electrokinetics

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          Abstract

          Cell membrane capacitance and conductance are key pieces of intrinsic information correlated with the cellular dielectric parameters and morphology of the plasma membrane; these parameters have been used as electrophysiological biomarkers to characterize cellular phenotype and state, and they have many associated clinical applications. Here, we present our work on the non-invasive determination of cell membrane capacitance and conductance by an optically activated microfluidics chip. The model for determining the cell membrane capacitance and conductance was established by a single layer of the shell-core polarization model. Three-dimensional finite-element analyses of the positive and negative optically induced dielectrophoresis forces generated by the projected light arrays of spots were performed, thus providing a theoretical validation of the feasibility of this approach. Then, the crossover frequency spectra for four typical types of cells (Raji cells, MCF-7 cells, HEK293 cells, and K562 cells) were experimentally investigated by using a micro-vision based motion-tracking technique. The different responses of these cells to the positive and negative ODEP forces were studied under four different liquid conductivities by automatic observation and tracking of the cellular trajectory and texture during the cells’ translation. The cell membrane capacitance and conductance were determined from the curve-fitted spectra, which were 11.1 ± 0.9 mF/m 2 and 782 ± 32 S/m 2, respectively, for Raji cells, 11.5 ± 0.8 mF/m 2 and 114 ± 28 S/m 2 for MCF-7 cells, 9.0 ± 0.9 mF/m 2 and 187 ± 22 S/m 2 for HEK293 cells, and 10.2 ± 0.7 mF/m 2 and 879 ± 24 S/m 2 for K562 cells. Furthermore, as an application of this technique, the membrane capacitances of MCF-7 cells treated with four different concentrations of drugs were acquired. This technique introduces a determination of cell membrane capacitance and conductance that yields statistically significant data while allowing information from individual cells to be obtained in a non-invasive manner.

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          Author and article information

          Contributors
          Journal
          Biophys J
          Biophys. J
          Biophysical Journal
          The Biophysical Society
          0006-3495
          1542-0086
          03 October 2017
          03 October 2017
          : 113
          : 7
          : 1531-1539
          Affiliations
          [1 ]State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, China
          [2 ]School of Mechanical Engineering, Shenyang Jianzhu University, Shenyang, China
          [3 ]Department of Mechanical and Biomedical Engineering, City University of Hong Kong, Hong Kong
          [4 ]School of Control Engineering, Northeastern University at Qinhuangdao, Qinhuangdao, China
          [5 ]Department of Power Mechanical Engineering, National Tsing Hua University, Hsinchu, Taiwan
          Author notes
          Article
          PMC5627184 PMC5627184 5627184 S0006-3495(17)30863-9
          10.1016/j.bpj.2017.08.006
          5627184
          28978446
          881c0ca7-96b8-48ae-8711-d7e2169a30b3
          © 2017 Biophysical Society.
          History
          : 24 February 2017
          : 7 August 2017
          Categories
          Membranes

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