Design and 3D modeling investigation of a microfluidic electrode array for electrical impedance measurement of single yeast cells.
Yangye GengZhen ZhuZhao ZhangFeng XuMario A MarchisioZixin WangDejing PanXiangwei ZhaoQing-An HuangPublished in: Electrophoresis (2021)
High-resolution microscopic imaging may cause intensive image processing and potential impact of light irradiation on yeast replicative lifespan (RLS). Electrical impedance spectroscopy (EIS) could be alternatively used to perform high-throughput and label-free yeast RLS assays. Prior to fabricating EIS-integrated microfluidic devices for yeast RLS determination, systematic modeling and theoretical investigation are crucial for device design and optimization. Here, we report three-dimensional (3D) finite-element modeling and simulations of EIS measurement in a microfluidic single yeast in situ impedance array (SYIIA), which is designed by patterning an electrode matrix underneath a cell-trapping array. SYIIA was instantiated and modeled as a 5 × 5 sensing array comprising 25 units for cell immobilization, culturing, and time-lapse EIS recording. Simulations of yeast growing and budding in a sensing unit demonstrated that EIS signals enable the characterization of cell growth and daughter-cell dissections. In the 5 × 5 sensing array, simulation results indicated that when monitoring a target cell, daughter dissections in its surrounding traps may induce variations of the recorded EIS signals, which could cause mistakes in identifying target daughter-cell dissections. To eliminate the mis-identifications, electrode array pitch was optimized. Therefore, the results could conduct the design and optimization of microfluidic electrode-array-integrated devices for high-throughput and accurate yeast RLS assays.
Keyphrases
- high throughput
- single cell
- high resolution
- cell therapy
- label free
- saccharomyces cerevisiae
- stem cells
- oxidative stress
- mass spectrometry
- molecular dynamics
- magnetic resonance imaging
- circulating tumor cells
- computed tomography
- radiation therapy
- machine learning
- cell death
- induced apoptosis
- bone marrow
- solid state
- high density
- cell cycle arrest
- cell proliferation