Department of Electrical and Electronic Engineering, Faculty of Engineering, The University of Hong Kong, Pokfulam, Hong Kong.
School of Biomedical Sciences, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong.
Cytometry A. 2019 May;95(5):510-520. doi: 10.1002/cyto.a.23765. Epub 2019 Apr 22.
Cellular biophysical properties are the effective label-free phenotypes indicative of differences in cell types, states, and functions. However, current biophysical phenotyping methods largely lack the throughput and specificity required in the majority of cell-based assays that involve large-scale single-cell characterization for inquiring the inherently complex heterogeneity in many biological systems. Further confounded by the lack of reported robust reproducibility and quality control, widespread adoption of single-cell biophysical phenotyping in mainstream cytometry remains elusive. To address this challenge, here we present a label-free imaging flow cytometer built upon a recently developed ultrafast quantitative phase imaging (QPI) technique, coined multi-ATOM, that enables label-free single-cell QPI, from which a multitude of subcellularly resolvable biophysical phenotypes can be parametrized, at an experimentally recorded throughput of >10,000 cells/s-a capability that is otherwise inaccessible in current QPI. With the aim to translate multi-ATOM into mainstream cytometry, we report robust system calibration and validation (from image acquisition to phenotyping reproducibility) and thus demonstrate its ability to establish high-dimensional single-cell biophysical phenotypic profiles at ultra-large-scale (>1,000,000 cells). Such a combination of throughput and content offers sufficiently high label-free statistical power to classify multiple human leukemic cell types at high accuracy (~92-97%). This system could substantiate the significance of high-throughput QPI flow cytometry in enabling next frontier in large-scale image-derived single-cell analysis applied in biological discovery and cost-effective clinical diagnostics. © 2019 International Society for Advancement of Cytometry.
细胞生物物理特性是细胞类型、状态和功能差异的有效无标记表型。然而，当前的生物物理表型方法在大多数基于细胞的测定中缺乏所需的通量和特异性，这些测定涉及大规模单细胞特征化，以探究许多生物系统中固有的复杂异质性。由于缺乏报告的稳健可重复性和质量控制，单细胞生物物理表型在主流细胞计数中的广泛采用仍然难以实现。为了解决这一挑战，我们在这里展示了一种基于最近开发的超快速定量相位成像（QPI）技术的无标记成像流式细胞仪，该技术被称为多原子（multi-ATOM），能够对无标记单细胞进行 QPI，从中可以参数化多种亚细胞分辨率的生物物理表型，其实验记录的通量>10,000 个细胞/s-这是当前 QPI 无法实现的功能。为了将 multi-ATOM 转化为主流细胞计数，我们报告了稳健的系统校准和验证（从图像采集到表型可重复性），从而证明了其能够在超大规模（>1,000,000 个细胞）上建立高维单细胞生物物理表型谱的能力。这种通量和内容的结合提供了足够高的无标记统计能力，可以以高精度（约 92-97%）对多种人类白血病细胞类型进行分类。该系统可以证明高通量 QPI 流式细胞术在实现大规模图像衍生单细胞分析的下一个前沿技术中的重要性，这些技术可应用于生物发现和具有成本效益的临床诊断。 © 2019 国际细胞分析学会。
