Mathematical Analysis of the Biophysical Response of EGCG‐treated yperglycemic HMEC‐1 and UMR Cells in vitro using Electric Cell‐Substrate Impedance Sensing Technology
Authors: CHOI JEANNIE , LAI NOK HANG (TONY) , SATO SHANE (TONY) , HERNANDEZ BRYAN , VANDERWERFF JON , JOSEPH EUGENE 
Published: June 2021

Hyperglycemia, the hallmark of diabetes mellitus, is a major risk factor for endothelial dysfunction and compromised bone cell metabolism. Not many studies have measured the biophysical response of hyperglycemic human microvascular endothelial cells (HMEC‐1) and bone‐like rat osteosarcoma cells, UMR 106‐01 BSP (UMR cells), treated with (−)‐Epigallocatechin‐3‐gallate (EGCG), a natural antioxidant and the active ingredient in green tea, using electric cell‐substrate impedance sensing (ECIS) technology. The aim of this study was to determine the biophysical response of HMEC‐1 and UMR cells under hyperglycemic conditions when treated with EGCG. Moreover, the derivation of predictive mathematical formulas was sought to analyze the ECIS‐generated biophysical data. We hypothesized that ECIS technology can be used as a tool to evaluate the effects of glucose and EGCG on cell membrane resistance, spreading and attachment in HMEC‐1 and UMR cell cultures by mathematical analysis. HMEC‐1 and UMR cells were separately cultured and plated at 4.0×104 and 2.5×105 cells/mL, respectively, in eight‐well (8W) ECIS array plates. Designated plate wells were treated with glucose with or without EGCG. The cell cultures were incubated in a humidified chamber at 37° C with infusion of 5% CO2. Membrane resistance, time of complete cell attachment, and rate of spreading of the cells were monitored and measured in vitro, using the ECIS machine. The one‐tailed correlation analysis was employed to statistically study the relationships between glucose concentration and the following parameters: maximum resistance, spreading rate, and complete attachment time in both HMEC‐1 and UMR cells. To verify statistical significance of the results, p‐values were obtained for each set of experiments. The experimental data showed that the higher concentrations of glucose lowered the maximum cell membrane resistance, cell spreading rate, and time of cell attachment. The following mathematical formulas were derived based on the ECIS data: 1) dR/dt=kR(1−R/L), 2) R(t)=L/(1+be−kt), and 3) ln(π/1−π) = kt−ln(b), (where dR/dt=rate of spreading, R(t)=cell membrane resistance at any time point, L=maximum resistance, k=rate constant, b=(L−R0)/R0, t=time in hours, and π=r(R(t)−R0/L). The formulas were found to be of predictive value. The p‐values obtained from the correlation test of glucose concentration and two of the parameters tested indicated statistical significance (L for HMEC‐1 cells: 0.061; dR/dt for HMEC‐1 cells: 0.027; L for UMR cells: p=0.041; dR/dt for UMR cells: p=0.047). The results suggest that the ECIS technology is a useful tool in the mathematical analysis of biophysical phenomena in HMEC‐1 and UMR 106 cells in vitro.Support or Funding InformationFunding for this study was provided by the Ryckman Student Research Endowment Fund of the Biology Department of La Sierra University in Riverside, CA.This abstract is from the Experimental Biology 2019 Meeting. There is no full text article associated with this abstract published in The FASEB Journal.