State Key Laboratory of Transducer Technology (SKLTT), Aerospace Information Research Institute (AIR), Chinese Academy of Sciences (CAS), Beijing, China.
School of Electronic, Electrical and Communication Engineering (EECE), University of Chinese Academy of Sciences (UCAS), Beijing, China.
Cytometry A. 2022 May;101(5):434-447. doi: 10.1002/cyto.a.24517. Epub 2021 Nov 25.
This paper reported a microfluidic platform which realized the characterization of inherent single-cell biomechanical and bioelectrical parameters simultaneously. Individual cells traveled through a constriction channel with deformation images and impedance variations captured and processed into cortical tension T , specific membrane capacitance C , and cytoplasmic conductivity σ based on an equivalent biophysical model. These properties of thousands of individual cells of K562, Jurkat, HL-60, HL-60 treated with paraformaldehyde (PA)/cytochalasin D (CD)/concanavalin A (ConA), granulocytes of Donor 1, Donor 2, and Donor 3 were quantified for the first time. Leveraging T , C , and σ , (1) high accuracies of classifying wild-type and processed HL-60 cells (e.g., 93.5% of PA treated vs. CD treated HL-60 cells) were realized, revealing the effectiveness of using these three biophysical parameters in cell-type classification; (2) low accuracies of classifying normal granulocytes from three donors (e.g., 56.4% of Donor 1 vs. 2), indicating comparable parameters for normal granulocytes. In conclusion, this platform can characterize single-cell T , C , and σ concurrently and quantify multiple parameters in single-cell analysis.
本文报道了一种微流控平台,该平台实现了同时对固有单细胞生物力学和生物电学参数进行特征描述。通过对变形图像和阻抗变化的捕获和处理,将单个细胞输送通过收缩通道,基于等效生物物理模型将其转化为皮质张力 T 、特定膜电容 C 和细胞质电导率σ。首次对 K562、Jurkat、HL-60、经多聚甲醛(PA)/细胞松弛素 D(CD)/刀豆球蛋白 A(ConA)处理的 HL-60 细胞、供体 1、供体 2 和供体 3 的数千个单个细胞的这些特性进行了量化。利用 T 、 C 和σ ,(1)实现了对野生型和处理后的 HL-60 细胞的高分类准确率(例如,PA 处理的 HL-60 细胞与 CD 处理的 HL-60 细胞的准确率为 93.5%),表明使用这三个生物物理参数进行细胞类型分类是有效的;(2)对来自三个供体的正常粒细胞的分类准确率较低(例如,供体 1 与供体 2 的准确率为 56.4%),表明正常粒细胞的参数相似。总之,该平台可以同时对单个细胞的 T 、 C 和σ 进行特征描述,并在单细胞分析中量化多个参数。