Multi-frequency single cell electrical impedance measurement for label-free cell viability analysis

Cell viability is a physiological status connected to cell membrane integrity and cytoplasmic topography, which is profoundly important for fundamental biological research and practical biomedical applications. A conventional method for assessing cell viability is through cell staining analysis. However, cell staining involves laborious and complicated processing procedures and is normally cytotoxic. Intrinsic cellular phenotypes thus provide new avenues for measuring cell viability in a stain-free and non-toxic manner. In this work, we present a label-free non-destructive impedance-based approach for cell viability assessment by simultaneously characterizing multiple electrical cellular phenotypes in a high-throughput manner (>1000 cells per min). A novel concept called the complex opacity spectrum is introduced for improving the discrimination of live and dead cells. The analysis of the complex opacity spectrum leads to the discovery of two frequency ranges that are optimized for characterizing membranous and cytoplasmic electrical phenotypes. The present impedance-based approach has successfully discriminated between living and dead cells in two different experimental scenarios, including mixed living and dead cells in both homogenous and heterogeneous cell samples. This impedance-based single cell phenotyping technique provides highly accurate and consistent cell viability analysis, which has been validated by commercial fluorescence-based flow cytometry (similar to 1% difference) using heterogeneous cell samples. This label-free high-throughput cell viability analysis strategy will have broad applications in the field of biology and medicine.

Automated summary

This study presents a label-free impedance-based approach for cell viability assessment by characterizing multiple electrical cellular phenotypes in a high-throughput manner, introducing a concept called the complex opacity spectrum for improved discrimination of live and dead cells. The approach successfully discriminated between living and dead cells in different experimental scenarios and provides highly accurate and consistent cell viability analysis, validated by commercial fluorescence-based flow cytometry.