Microfluidic Platform to Transduce Cell Viability to Distinct Flow Pathways for High-Accuracy Sensing

Mechanical properties of cells such as stiffness can act as biomarkers to sort or detect cell functional properties such as viability. In this study, we report the use of a microfluidic device as a high-sensitivity sensor that transduces cell biomechanics to cell separation to accurately detect viability. Cell populations are flowed and deflected at a number of skew ridges such that deflection per ridge, cell-ridge interaction time, and cell size can all be used as sensor inputs to accurately determine the cell state. The angle of the ridges was evaluated to optimize the differences in cell translation between viable and nonviable cells while allowing continuous flow. In the first mode of operation, we flowed viable and nonviable cells through the device and conducted a sensitivity analysis by recording the cell's total deflection as a binary classifier that differentiates viable from nonviable cells. The performance of the sensor was assessed using an area under the curve (AUC) analysis to be 0.97. By including additional sensor inputs in the second mode of operation, we conducted a principal component analysis (PCA) to further improve the identification of the cell state by clustering populations with little overlap between viable and nonviable cells. We therefore found that microfluidic separation devices can be used to efficiently sort cells and accurately sense viability in a label-free manner.

Automated summary

The study utilized a microfluidic device as a high-sensitivity sensor to accurately detect cell viability by transducing cell biomechanics to separation. Different angles of the ridges were evaluated to optimize cell separation and identification. Furthermore, the use of principal component analysis improved the accuracy of cell state identification by clustering populations with little overlap between viable and nonviable cells, enabling efficient cell sorting and label-free viability sensing.