Addressing variability in cell electrorotation through holographic imaging and correction factors

Abstract

This study addresses the variations observed in electrorotation measurements due to cell positioning and movement. Electrorotation provides a non-disruptive method for inferring the electrical properties of individual cells. However, its widespread adoption is hindered by significant variation in the observed speed. By mitigating the impact of positional dependencies and other influencing factors, our methodology opens avenues for broader applications of electrorotation in single-cell analysis without the need for complex setups to trap and retain the cell in place. Our novel approach combines multi-plane imaging with mathematical treatment of rotation data. This method uses a conventional quadrupole chip and lens-free imaging to track cell movement, resulting in a simpler design and set-up. Through numerical simulations incorporating cell coordinates, chip design, and experimental parameters, we calculate the variation in torque for each position. These values serve as the basis for the correction factors. Validation experiments with T-lymphocytes and fibroblasts show that the correction factors reduce electrorotation speed variation due to cell movement, with an average reduction to 21% and 18%, respectively. These corrections also revealed previously concealed changes in cell properties, in response to external stimuli, thereby enhancing the reliability of measurements and enabling broader applications in single-cell analysis.