Intelligent image-based deformation-assisted cell sorting with molecular specificity.

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.

Real-time fluorescence and deformability cytometry.

The throughput of cell mechanical characterization has recently approached that of conventional flow cytometers. However, this very sensitive, label-free approach still lacks the specificity of molecular markers. Here we developed an approach that combines real-time 1D-imaging fluorescence and deformability cytometry in one instrument (RT-FDC), thus opening many new research avenues. We demonstrated its utility by using subcellular fluorescence localization to identify mitotic cells and test for mechanical changes in those cells in an RNA interference screen.

Single-cell mechanical phenotype is an intrinsic marker of reprogramming and differentiation along the mouse neural lineage.

Cellular reprogramming is a dedifferentiation process during which cells continuously undergo phenotypical remodeling. Although the genetic and biochemical details of this remodeling are fairly well understood, little is known about the change in cell mechanical properties during the process. In this study, we investigated changes in the mechanical phenotype of murine fetal neural progenitor cells (fNPCs) during reprogramming to induced pluripotent stem cells (iPSCs). We find that fNPCs become progressively stiffer en route to pluripotency, and that this stiffening is mirrored by iPSCs becoming more compliant during differentiation towards the neural lineage. Furthermore, we show that the mechanical phenotype of iPSCs is comparable with that of embryonic stem cells. These results suggest that mechanical properties of cells are inherent to their developmental stage. They also reveal that pluripotent cells can differentiate towards a more compliant phenotype, which challenges the view that pluripotent stem cells are less stiff than any cells more advanced developmentally. Finally, our study indicates that the cell mechanical phenotype might be utilized as an inherent biophysical marker of pluripotent stem cells.

Real-time deformability cytometry: on-the-fly cell mechanical phenotyping.

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.

Extracting Cell Stiffness from Real-Time Deformability Cytometry: Theory and Experiment.

Cell stiffness is a sensitive indicator of physiological and pathological changes in cells, with many potential applications in biology and medicine. A new method, real-time deformability cytometry, probes cell stiffness at high throughput by exposing cells to a shear flow in a microfluidic channel, allowing for mechanical phenotyping based on single-cell deformability. However, observed deformations of cells in the channel not only are determined by cell stiffness, but also depend on cell size relative to channel size. Here, we disentangle mutual contributions of cell size and cell stiffness to cell deformation by a theoretical analysis in terms of hydrodynamics and linear elasticity theory. Performing real-time deformability cytometry experiments on both model spheres of known elasticity and biological cells, we demonstrate that our analytical model not only predicts deformed shapes inside the channel but also allows for quantification of cell mechanical parameters. Thereby, fast and quantitative mechanical sampling of large cell populations becomes feasible.

Changes in Blood Cell Deformability in Chorea-Acanthocytosis and Effects of Treatment With Dasatinib or Lithium.

Misshaped red blood cells (RBCs), characterized by thorn-like protrusions known as acanthocytes, are a key diagnostic feature in Chorea-Acanthocytosis (ChAc), a rare neurodegenerative disorder. The altered RBC morphology likely influences their biomechanical properties which are crucial for the cells to pass the microvasculature. Here, we investigated blood cell deformability of five ChAc patients compared to healthy controls during up to 1-year individual off-label treatment with the tyrosine kinase inhibitor dasatinib or several weeks with lithium. Measurements with two microfluidic techniques allowed us to assess RBC deformability under different shear stresses. Furthermore, we characterized leukocyte stiffness at high shear stresses. The results showed that blood cell deformability-including both RBCs and leukocytes - in general was altered in ChAc patients compared to healthy donors. Therefore, this study shows for the first time an impairment of leukocyte properties in ChAc. During treatment with dasatinib or lithium, we observed alterations in RBC deformability and a stiffness increase for leukocytes. The hematological phenotype of ChAc patients hinted at a reorganization of the cytoskeleton in blood cells which partly explains the altered mechanical properties observed here. These findings highlight the need for a systematic assessment of the contribution of impaired blood cell mechanics to the clinical manifestation of ChAc.

Cell Mechanics Based Computational Classification of Red Blood Cells Via Machine Intelligence Applied to Morpho-Rheological Markers.

Despite fluorescent cell-labelling being widely employed in biomedical studies, some of its drawbacks are inevitable, with unsuitable fluorescent probes or probes inducing a functional change being the main limitations. Consequently, the demand for and development of label-free methodologies to classify cells is strong and its impact on precision medicine is relevant. Towards this end, high-throughput techniques for cell mechanical phenotyping have been proposed to get a multidimensional biophysical characterization of single cells. With this motivation, our goal here is to investigate the extent to which an unsupervised machine learning methodology, which is applied exclusively on morpho-rheological markers obtained by real-time deformability and fluorescence cytometry (RT-FDC), can address the difficult task of providing label-free discrimination of reticulocytes from mature red blood cells. We focused on this problem, since the characterization of reticulocytes (their percentage and cellular features) in the blood is vital in multiple human disease conditions, especially bone-marrow disorders such as anemia and leukemia. Our approach reports promising label-free results in the classification of reticulocytes from mature red blood cells, and it represents a step forward in the development of high-throughput morpho-rheological-based methodologies for the computational categorization of single cells. Besides, our methodology can be an alternative but also a complementary method to integrate with existing cell-labelling techniques.

Analysis of Biomechanical Properties of Hematopoietic Stem and Progenitor Cells Using Real-Time Fluorescence and Deformability Cytometry.

Stem cell mechanics, determined predominantly by the cell's cytoskeleton, plays an important role in different biological processes such as stem cell differentiation or migration. Several methods to measure mechanical properties of cells are currently available, but most of them are limited in the ability to screen large heterogeneous populations in a robust and efficient manner-a feature required for successful translational applications. With real-time fluorescence and deformability cytometry (RT-FDC), mechanical properties of cells in suspension can be screened continuously at rates of up to 1,000 cells/s-similar to conventional flow cytometers-which makes it a suitable method not only for basic research but also for a clinical setting. In parallel to mechanical characterization, RT-FDC allows to measure specific molecular markers using standard fluorescence labeling. In this chapter, we provide a detailed protocol for the characterization of hematopoietic stem and progenitor cells (HSPCs) in heterogeneous mobilized peripheral blood using RT-FDC and present a specific morpho-rheological fingerprint of HSPCs that allows to distinguish them from all other blood cell types.

High-throughput single-cell mechanical phenotyping with real-time deformability 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.

Detection of human disease conditions by single-cell morpho-rheological phenotyping of blood.

Blood is arguably the most important bodily fluid and its analysis provides crucial health status information. A first routine measure to narrow down diagnosis in clinical practice is the differential blood count, determining the frequency of all major blood cells. What is lacking to advance initial blood diagnostics is an unbiased and quick functional assessment of blood that can narrow down the diagnosis and generate specific hypotheses. To address this need, we introduce the continuous, cell-by-cell morpho-rheological (MORE) analysis of diluted whole blood, without labeling, enrichment or separation, at rates of 1000 cells/sec. In a drop of blood we can identify all major blood cells and characterize their pathological changes in several disease conditions in vitro and in patient samples. This approach takes previous results of mechanical studies on specifically isolated blood cells to the level of application directly in blood and adds a functional dimension to conventional blood analysis.

High-throughput cell mechanical phenotyping for label-free titration assays of cytoskeletal modifications.

The mechanical fingerprint of cells is inherently linked to the structure of the cytoskeleton and can serve as a label-free marker for cell homeostasis or pathologic states. How cytoskeletal composition affects the physical response of cells to external loads has been intensively studied with a spectrum of techniques, yet quantitative and statistically powerful investigations in the form of titration assays are hampered by the low throughput of most available methods. In this study, we employ real-time deformability cytometry (RT-DC), a novel microfluidic tool to examine the effects of biochemically modified F-actin and microtubule stability and nuclear chromatin structure on cell deformation in a human leukemia cell line (HL60). The high throughput of our method facilitates extensive titration assays that allow for significance assessment of the observed effects and extraction of half-maximal concentrations for most of the applied reagents. We quantitatively show that integrity of the F-actin cortex and microtubule network dominate cell deformation on millisecond timescales probed with RT-DC. Drug-induced alterations in the nuclear chromatin structure were not found to consistently affect cell deformation. The sensitivity of the high-throughput cell mechanical measurements to the cytoskeletal modifications we present in this study opens up new possibilities for label-free dose-response assays of cytoskeletal modifications.

Mechanical phenotyping of primary human skeletal stem cells in heterogeneous populations by real-time deformability cytometry.

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.