Multi-parametric functional imaging of cell cultures and tissues with a CMOS microelectrode array

Electrode-based impedance and electrochemical measurements can provide cell-biology information that is difficult to obtain using optical-microscopy techniques. Such electrical methods are non-invasive, label-free, and continuous, eliminating the need for fluorescence reporters and overcoming optical imaging's throughput/temporal resolution limitations. Nonetheless, electrode-based techniques have not been heavily employed because devices typically contain few electrodes per well, resulting in noisy aggregate readouts. Complementary metal-oxide-semiconductor (CMOS) microelectrode arrays (MEAs) have sometimes been used for electrophysiological measurements with thousands of electrodes per well at sub-cellular pitches, but only basic impedance mappings of cell attachment have been performed outside of electrophysiology. Here, we report on new field-based impedance mapping and electrochemical mapping/patterning techniques to expand CMOS-MEA cell-biology applications. The methods enable accurate measurement of cell attachment, growth/wound healing, cell-cell adhesion, metabolic state, and redox properties with single-cell spatial resolution (20 mu m electrode pitch). These measurements allow the quantification of adhesion and metabolic differences of cells expressing oncogenes versus wild-type controls. The multi-parametric, cell-population statistics captured by the chip-scale integrated device opens up new avenues for fully electronic high-throughput live-cell assays for phenotypic screening and drug discovery applications.

Automated summary

Electrode-based impedance and electrochemical measurements can provide non-invasive, label-free cell-biology information, overcoming limitations of optical imaging. However, existing electrode-based techniques have noisy results due to the limited number of electrodes per well. New field-based impedance mapping and electrochemical mapping/patterning techniques using CMOS-MEA expand the possibilities of cell-biology applications, with single-cell spatial resolution.