Quantitative Phase Imaging Flow Cytometry for Ultra‐Large‐Scale Single‐Cell Biophysical Phenotyping

Abstract

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

Label‐Free Leukemia Monitoring by Computer Vision

“…Also on a microfluidic flow platform, Dannhauser et al used light scattering properties to discriminate peripheral blood mononuclear blood cell types, including T‐, B‐lymphocytes, and monocytes in different stages of lymphoid and myeloid leukemia. Lee et al used an ultrafast quantitative phase imaging (QPI) flow cytometer to classify multiple human leukemic cell types at ~92–97% accuracy based on subcellular biophysical profiles. Similarly, Mugnano et al used QPI to detect characteristic morphologies of red blood cells in several inherited anemias, such as iron‐deficiency anemia, thalassemia, hereditary spherocytosis, and congenital dyserythropoietic anemia.…”

In Flow Cytometry, Image Is Everything

“…Hui et al describe their development of a method, which they refer to as immuno‐flowFISH, for conducting FISH on immunophenotyped whole cells in suspension to detect chromosomal abnormalities in chronic lymphocytic leukemia. Lee et al report their development of a quantitative phase IFC system to conduct large‐scale biophysical phenotyping of numerous single cells (>1,000,000 cells) in a label‐free manner. Yaakov et al report their quantitative characterization of the kinetics of Mimivirus infection stages by IFC.…”

Elasticity Spectra as a Tool to Investigate Actin Cortex Mechanics

“…There is a growing interest for the identification of assays and methods able to assess the mechanotransduction state of single cells, and exploit it with higher throughput, towards the identification and screening of new drugs [17]. In this view, a simple and reliable method to characterize the physical state of the AC would be a valuable tool to identify innovative label-free biophysical markers of the cellular phenotype [18,19,20]. The study of AC structure and mechanics is particularly challenging from the technical point of view.…”