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Biomedical research relies on identification and isolation of specific cell types using molecular biomarkers and sorting methods such as fluorescence or magnetic activated cell sorting. Labelling processes potentially alter the cells' properties and should be avoided, especially when purifying cells for clinical applications. A promising alternative is the label-free identification of cells based on physical properties. Sorting real-time deformability cytometry (soRT-DC) is a microfluidic technique for label-free analysis and sorting of single cells. In soRT-FDC, bright-field images of cells are analyzed by a deep neural net (DNN) to obtain a sorting decision, but sorting was so far only demonstrated for blood cells which show clear morphological differences and are naturally in suspension. Most cells, however, grow in tissues, requiring dissociation before cell sorting which is associated with challenges including changes in morphology, or presence of aggregates. Here, we introduce methods to improve robustness of analysis and sorting of single cells from nervous tissue and provide DNNs which can distinguish visually similar cells. We employ the DNN for image-based sorting to enrich photoreceptor cells from dissociated retina for transplantation into the mouse eye., (© 2022. The Author(s).)

Diagnosis of myelodysplastic syndrome (MDS) mainly relies on a manual assessment of the peripheral blood and bone marrow cell morphology. The WHO guidelines suggest a visual screening of 200 to 500 cells which inevitably turns the assessor blind to rare cell populations and leads to low reproducibility. Moreover, the human eye is not suited to detect shifts of cellular properties of entire populations. Hence, quantitative image analysis could improve the accuracy and reproducibility of MDS diagnosis. We used real-time deformability cytometry (RT-DC) to measure bone marrow biopsy samples of MDS patients and age-matched healthy individuals. RT-DC is a high-throughput (1000 cells/s) imaging flow cytometer capable of recording morphological and mechanical properties of single cells. Properties of single cells were quantified using automated image analysis, and machine learning was employed to discover morpho-mechanical patterns in thousands of individual cells that allow to distinguish healthy vs. MDS samples. We found that distribution properties of cell sizes differ between healthy and MDS, with MDS showing a narrower distribution of cell sizes. Furthermore, we found a strong correlation between the mechanical properties of cells and the number of disease-determining mutations, inaccessible with current diagnostic approaches. Hence, machine-learning assisted RT-DC could be a promising tool to automate sample analysis to assist experts during diagnosis or provide a scalable solution for MDS diagnosis to regions lacking sufficient medical experts., (© 2022. The Author(s).)

The mechanical phenotype of a cell is an inherent biophysical marker of its state and function, with many applications in basic and applied biological research. Microfluidics-based methods have enabled single-cell mechanophenotyping at throughputs comparable to those of flow cytometry. Here, we present a standardized cross-laboratory study comparing three microfluidics-based approaches for measuring cell mechanical phenotype: constriction-based deformability cytometry (cDC), shear flow deformability cytometry (sDC) and extensional flow deformability cytometry (xDC). All three methods detect cell deformability changes induced by exposure to altered osmolarity. However, a dose-dependent deformability increase upon latrunculin B-induced actin disassembly was detected only with cDC and sDC, which suggests that when exposing cells to the higher strain rate imposed by xDC, cellular components other than the actin cytoskeleton dominate the response. The direct comparison presented here furthers our understanding of the applicability of the different deformability cytometry methods and provides context for the interpretation of deformability measurements performed using different platforms.

Although label-free cell sorting is desirable for providing pristine cells for further analysis or use, current approaches lack molecular specificity and speed. Here, we combine real-time fluorescence and deformability cytometry with sorting based on standing surface acoustic waves and transfer molecular specificity to image-based sorting using an efficient deep neural network. In addition to general performance, we demonstrate the utility of this method by sorting neutrophils from whole blood without labels.

Distinct cell-types within the retina are mainly specified by morphological and molecular parameters, however, physical properties are increasingly recognized as a valuable tool to characterize and distinguish cells in diverse tissues. High-throughput analysis of morpho-rheological features has recently been introduced using real-time deformability cytometry (RT-DC) providing new insights into the properties of different cell-types. Rod photoreceptors represent the main light sensing cells in the mouse retina that during development forms apically the densely packed outer nuclear layer. Currently, enrichment and isolation of photoreceptors from retinal primary tissue or pluripotent stem cell-derived organoids for analysis, molecular profiling, or transplantation is achieved using flow cytometry or magnetic activated cell sorting approaches. However, such purification methods require genetic modification or identification of cell surface binding antibody panels. Using primary retina and embryonic stem cell-derived retinal organoids, we characterized the inherent morpho-mechanical properties of mouse rod photoreceptors during development based on RT-DC. We demonstrate that rods become smaller and more compliant throughout development and that these features are suitable to distinguish rods within heterogenous retinal tissues. Hence, physical properties should be considered as additional factors that might affect photoreceptor differentiation and retinal development besides representing potential parameters for label-free sorting of photoreceptors. © 2019 The Authors. Cytometry Part A published by Wiley Periodicals, Inc. on behalf of International Society for Advancement of Cytometry., (© 2019 The Authors. Cytometry Part A published by Wiley Periodicals, Inc. on behalf of International Society for Advancement of Cytometry.)

Mechanical properties of cells can serve as a label-free marker of cell state and function and their alterations have been implicated in processes such as cancer metastasis, leukocyte activation, or stem cell differentiation. Over recent years, new techniques for single-cell mechanical characterization at high throughput have been developed to accelerate discovery in the field of mechanical phenotyping. One such technique is real-time deformability cytometry (RT-DC), a robust technology based on microfluidics that performs continuous mechanical characterization of cells in a contactless manner at rates of up to 1000 cells per second. This tremendous throughput allows for comparison of large sample numbers and precise characterization of heterogeneous cell populations. Additionally, parameters acquired in RT-DC measurements can be used to determine the apparent Young's modulus of individual cells. In this chapter, we present practical aspects important for the implementation of the RT-DC methodology, including a description of the setup, operation principles, and experimental protocols. In the latter, we describe a variety of preparation procedures for samples originating from different sources including 2D and 3D cell cultures as well as blood and tissue-derived primary cells, and discuss obstacles that may arise during their measurements. Finally, we provide insights into standard data analysis procedures and discuss the method's performance in light of other available techniques., (© 2018 Elsevier Inc. All rights reserved.)

Real-time deformability cytometry (RT-DC) is a microfluidic technique that allows to capture and evaluate morphology and rheology of up to 1000 cells/s in a constricted channel. The cells are deformed without mechanical contact by hydrodynamic forces and are quantified in real-time without the need of additional handling or staining procedures. Segmented pictures of the cells are stored and can be used for further analysis. RT-DC is sensitive to alterations of the cytoskeleton, which allows, e.g., to show differences in cell cycle phases, identify different subpopulations in whole blood and to study mechanical stiffening of cells entering a dormant state. The abundance of the obtainable parameters and the interpretation as mechanical readout is an analytical challenge that needs standardization. Here, we will provide guidelines for measuring and post-processing of RT-DC data.

Skeletal stem cells (SSCs) are a sub-population of mesenchymal stromal cells (MSCs) present in bone marrow with multipotent differentiation potential. A current unmet challenge hampering their clinical translation remains the isolation of homogeneous populations of SSCs, in vitro, with consistent regeneration and differentiation capacities. Cell stiffness has been shown to play an important role in cell separation using microfluidic techniques such as inertial focusing or deterministic lateral displacement. Here we report that the mechanical properties of SSCs, and of a surrogate human osteosarcoma cell line (MG-63), differ significantly from other cell populations found in the bone marrow. Using real-time deformability cytometry, a recently introduced method for cell mechanical characterization, we demonstrate that both MG-63 and SSCs are stiffer than the three primary leukocyte lineages (lymphocytes, monocytes and granulocytes) and also stiffer than HL-60, a human leukemic progenitor cell line. In addition, we show that SSCs form a mechanically distinct sub-population of MSCs. These results represent an important step towards finding the bio-physical fingerprint of human SSCs that will allow their label-free separation from bone marrow with significant physiological and therapeutic implications.

We introduce real-time deformability cytometry (RT-DC) for continuous cell mechanical characterization of large populations (>100,000 cells) with analysis rates greater than 100 cells/s. RT-DC is sensitive to cytoskeletal alterations and can distinguish cell-cycle phases, track stem cell differentiation into distinct lineages and identify cell populations in whole blood by their mechanical fingerprints. This technique adds a new marker-free dimension to flow cytometry with diverse applications in biology, biotechnology and medicine.

Background: Elasticity of cells is determined by their cytoskeleton. Changes in cellular function are reflected in the amount of cytoskeletal proteins and their associated networks. Drastic examples are diseases such as cancer, in which the altered cytoskeleton is even diagnostic. This connection between cellular function and cytoskeletal mechanical properties suggests using the deformability of cells as a novel inherent cell marker., Methods: The optical stretcher is a new laser tool capable of measuring cellular deformability. A unique feature of this deformation technique is its potential for high throughput, with the incorporation of a microfluidic delivery of cells., Results: Rudimentary implementation of the microfluidic optical stretcher has been used to measure optical deformability of several normal and cancerous cell types. A drastic difference has been seen between the response of red blood cells and polymorphonuclear cells for a given optically induced stress. MCF-10, MCF-7, and modMCF-7 cells were also measured, showing that while cancer cells stretched significantly more (five times) than normal cells, optical deformability could even be used to distinguish metastatic cancer cells from nonmetastatic cancer cells. This trimodal distribution was apparent after measuring a mere 83 cells, which shows optical deformability to be a highly regulated cell marker., Conclusions: Preliminary work suggests a deformability-based cell sorter similar to current fluorescence-based flow cytometry without the need for specific labeling. This could be used for the diagnosis of all diseases, and the investigation of all cellular processes, that affect the cytoskeleton., (Copyright 2004 Wiley-Liss, Inc.)

Cells alter the path of light, a fact that leads to well‐known aberrations in single cell or tissue imaging. Optical diffraction tomography (ODT) measures the biophysical property that causes these aberrations, the refractive index (RI). ODT is complementary to fluorescence imaging and does not require any markers. The present study introduces RI and fluorescence tomography with optofluidic rotation (RAFTOR) of suspended cells, facilitating the segmentation of the 3D‐correlated RI and fluorescence data for a quantitative interpretation of the nuclear RI. The technique is validated with cell phantoms and used to confirm a lower nuclear RI for HL60 cells. Furthermore, the nuclear inversion of adult mouse photoreceptor cells is observed in the RI distribution. The applications shown confirm predictions of previous studies and illustrate the potential of RAFTOR to improve our understanding of cells and tissues. [ABSTRACT FROM AUTHOR]

Numerous cell functions are accompanied by phenotypic changes in viscoelastic properties, and measuring them can help elucidate higher level cellular functions in health and disease. We present a high-throughput, simple and low-cost microfluidic method for quantitatively measuring the elastic (storage) and viscous (loss) modulus of individual cells. Cells are suspended in a highviscosity fluid and are pumped with high pressure through a 5.8 cm long and 200 µm wide microfluidic channel. The fluid shear stress induces large, ear ellipsoidal cell deformations. In addition, the flow profile in the channel causes the cells to rotate in a tank-treading manner. From the cell deformation and tank treading frequency, we extract the frequency-dependent viscoelastic cell properties based on a theoretical framework developed by R. Roscoe [1] that describes the deformation of a viscoelastic sphere in a viscous fluid under steady laminar flow. We confirm the accuracy of the method using atomic force microscopy-calibrated polyacrylamide beads and cells. Our measurements demonstrate that suspended cells exhibit power-law, soft glassy rheological behavior that is cell-cycle-dependent and mediated by the physical interplay between the actin filament and intermediate filament networks. [ABSTRACT FROM AUTHOR]