Department of Mechanical Engineering, Johns Hopkins University, Baltimore, Maryland 21287, USA.
Microsystems and Nanotechnology Division, National Institute of Standards and Technology, Gaithersburg, Maryland 20899, USA.
Lab Chip. 2022 Aug 23;22(17):3217-3228. doi: 10.1039/d1lc01169c.
Flow cytometry is an invaluable technology in biomedical research, but confidence in single-cell measurements remains limited due to a lack of appropriate techniques for uncertainty quantification (UQ). It is particularly challenging to evaluate the potential for different instrumentation designs or operating parameters to influence the measurement physics in ways that change measurement repeatability. Here, we report a direct experimental approach to UQ using a serial flow cytometer that measured each particle more than once along a flow path. The instrument was automated for real-time characterization of measurement precision and operated with particle velocities exceeding 1 m s, throughputs above 100 s, and analysis yields better than 99.9%. These achievements were enabled by a novel hybrid inertial and hydrodynamic particle focuser to tightly control particle positions and velocities. The cytometer identified ideal flow conditions with fluorescence area measurement precision on the order of 1% and characterized tradeoffs between precision, throughput, and analysis yield. The serial cytometer is anticipated to improve single-cell measurements through estimation (and subsequent control) of uncertainty contributions from various other instrument parameters leading to overall improvements in the ability to better classify sample composition and to find rare events.
流式细胞术是生物医学研究中一种非常有价值的技术，但由于缺乏适当的不确定性量化 (UQ) 技术，人们对单细胞测量的置信度仍然有限。评估不同仪器设计或操作参数是否有可能以改变测量可重复性的方式影响测量物理性质尤其具有挑战性。在这里，我们报告了一种使用串联流式细胞仪进行 UQ 的直接实验方法，该方法沿着流道多次测量每个颗粒。该仪器经过自动化处理，可实时表征测量精度，并以超过 1 m s 的颗粒速度、超过 100 s 的吞吐量和超过 99.9%的分析产量运行。通过一种新颖的混合惯性和流体动力颗粒聚焦器来紧密控制颗粒位置和速度，实现了这些成就。该流式细胞仪通过对荧光面积测量精度进行排序，确定了理想的流动条件，精度约为 1%，并对精度、吞吐量和分析产量之间的权衡进行了特征描述。串联流式细胞仪有望通过估计（并随后控制）来自各种其他仪器参数的不确定性贡献来提高单细胞测量水平，从而整体提高更好地分类样本组成和发现稀有事件的能力。
