Electrical and Computer Engineering, University of Virginia, Charlottesville, Virginia 22904, United States.
Chemistry, University of Virginia, Charlottesville, Virginia 22904, United States.
Anal Chem. 2022 Feb 15;94(6):2865-2872. doi: 10.1021/acs.analchem.1c04739. Epub 2022 Feb 2.
Biophysical cellular information at single-cell sensitivity is becoming increasingly important within analytical and separation platforms that associate the cell phenotype with markers of disease, infection, and immunity. Frequency-modulated electrically driven microfluidic measurement and separation systems offer the ability to sensitively identify single cells based on biophysical information, such as their size and shape, as well as their subcellular membrane morphology and cytoplasmic organization. However, there is a lack of reliable and reproducible model particles with well-tuned subcellular electrical phenotypes that can be used as standards to benchmark the electrical physiology of unknown cell types or to benchmark dielectrophoretic separation metrics of novel device strategies. Herein, the application of red blood cells (RBCs) as multimodal standard particles with systematically modulated subcellular electrophysiology and associated fluorescence level is presented. Using glutaraldehyde fixation to vary membrane capacitance and by membrane resealing after electrolyte penetration to vary interior cytoplasmic conductivity and fluorescence in a correlated manner, each modified RBC type can be identified at single-cell sensitivity based on phenomenological impedance metrics and fitted to dielectric models to compute biophysical information. In this manner, single-cell impedance data from unknown RBC types can be mapped versus these model RBC types for facile determination of subcellular biophysical information and their dielectrophoretic separation conditions, without the need for time-consuming algorithms that often require unknown fitting parameters. Such internal standards for biophysical cytometry can advance in-line phenotypic recognition strategies.
在将细胞表型与疾病、感染和免疫标志物相关联的分析和分离平台中,单细胞灵敏度的生物物理细胞信息变得越来越重要。基于频变的电驱动微流控测量和分离系统能够基于生物物理信息(例如细胞大小和形状、亚细胞膜形态和细胞质组织)灵敏地识别单细胞。然而,缺乏具有良好调谐的亚细胞电生理特性的可靠且可重复的模型颗粒,这些颗粒可用作标准来基准未知细胞类型的电生理或基准新型器件策略的介电泳分离度量。在此,提出了将红细胞 (RBC) 用作具有系统调制的亚细胞电生理和相关荧光水平的多模态标准颗粒。通过戊二醛固定来改变膜电容,并在电解质渗透后通过膜再封闭来改变内部细胞质电导率和荧光,以相关的方式,每种经过修饰的 RBC 类型都可以基于现象学阻抗指标在单细胞灵敏度下进行识别,并拟合介电模型以计算生物物理信息。通过这种方式,可以将未知 RBC 类型的单细胞阻抗数据与这些模型 RBC 类型进行映射,以便轻松确定亚细胞生物物理信息及其介电泳分离条件,而无需使用通常需要未知拟合参数的耗时算法。这种生物物理细胞计量学的内部标准可以推进在线表型识别策略。