George W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332, United States.
The Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology & Emory University, Atlanta, Georgia 30332, United States.
ACS Sens. 2021 Oct 22;6(10):3789-3799. doi: 10.1021/acssensors.1c01770. Epub 2021 Sep 21.
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.
细胞的力学特性,如刚性,可以作为生物标志物来对细胞的功能特性(如活力)进行分选或检测。在本研究中,我们报告了使用微流控装置作为高灵敏度传感器的方法,该传感器将细胞生物力学转换为细胞分离,从而准确地检测细胞活力。细胞群体在多个倾斜脊处流动和偏转,使得每个脊的偏转角、细胞脊相互作用时间和细胞大小都可以作为传感器输入,以准确地确定细胞状态。评估了脊的角度,以优化存活和非存活细胞之间在允许连续流动的情况下的细胞迁移差异。在第一种操作模式下,我们将存活和非存活细胞流经装置,并通过记录细胞的总偏转作为二进制分类器,将存活细胞与非存活细胞区分开来,进行了灵敏度分析。通过使用曲线下面积 (AUC) 分析评估传感器的性能,结果为 0.97。通过在第二种操作模式下包含附加传感器输入,我们进行了主成分分析 (PCA),通过对存活细胞和非存活细胞之间几乎没有重叠的细胞群体进行聚类,进一步提高了细胞状态的识别能力。因此,我们发现微流控分离装置可用于以无标记的方式有效地分选细胞并准确地感知细胞活力。