High-throughput single-cell rheology in complex samples by dynamic real-time deformability cytometry

Deformability of Heterogeneous Red Blood Cells in Aging and Related Pathologies

Aging is interrelated with changes in red blood cell parameters and functionality. In this article, we focus on red blood cells (RBCs) and provide a review of the known changes associated with the characterization of RBC deformability in aging and related pathologies. The biophysical parameters complement the commonly used biochemical parameters and may contribute to a better understanding of the aging process. The power of the deformability measurement approach is well established in clinical settings. Measuring RBCs' deformability has the advantage of relative simplicity, and it reflects the complex effects developing in erythrocytes during aging. However, aging and related pathological conditions also promote heterogeneity of RBC features and have a certain impact on the variance in erythrocyte cell properties. The possible applications of deformability as an early biophysical biomarker of pathological states are discussed, and modulating PIEZO1 as a therapeutic target is suggested. The changes in RBCs' shape can serve as a proxy for deformability evaluation, leveraging single-cell analysis with imaging flow cytometry and artificial intelligence algorithms. The characterization of biophysical parameters of RBCs is in progress in humans and will provide a better understanding of the complex dynamics of aging.

Single-Cell Mechanics: Structural Determinants and Functional Relevance

The mechanical phenotype of a cell determines its ability to deform under force and is therefore relevant to cellular functions that require changes in cell shape, such as migration or circulation through the microvasculature. On the practical level, the mechanical phenotype can be used as a global readout of the cell's functional state, a marker for disease diagnostics, or an input for tissue modeling. We focus our review on the current knowledge of structural components that contribute to the determination of the cellular mechanical properties and highlight the physiological processes in which the mechanical phenotype of the cells is of critical relevance. The ongoing efforts to understand how to efficiently measure and control the mechanical properties of cells will define the progress in the field and drive mechanical phenotyping toward clinical applications.

High-Throughput Sorting and Single-Cell Mechanotyping by Hydrodynamic Sorting-Mechanotyping Cytometry

The existence of many background blood cells hinders the accurate identification of circulating tumor cells (CTCs) in the blood of cancer patients. To unlock this limitation, a hydrodynamic sorting-mechanotyping cytometry (HSMC) integrated with a sorting-concentration chip and a detection chip is proposed for simultaneously achieving the high-throughput cell sorting and the multi-parameter mechanotyping of the sorted tumor cells. The HSMC adopts the spiral inertial microfluidics for label-free sorting of cells in a high-throughput manner, allowing the efficient enrichment of tumor cells from the large background blood cells. Then, the sorted cells are concentrated by the concentration unit and finally passed through the detection unit for hydrodynamic deformation. The HSMC has a high throughput for sorting and detection and can successfully reveal the differences in the cellular mechanical properties. After characterizing and optimizing the single chips, the identification of white blood cells (WBCs) and three types of tumor cells (A549, MCF-7, and MDA-MB-231 cells) is successfully achieved. The identification accuracies for WBCs and different tumor cells are all larger than 94%, while the highest identification accuracy is up to 99.2%. This study envisions that the HSMC will offer an avenue for the analysis of single cell intrinsic mechanics in clinical medicine.

Elasticity of Carrier Fluid: A Key Factor Affecting Mechanical Phenotyping in Deformability Cytometry

Recently, microfluidics deformability cytometry has emerged as a powerful tool for high-throughput mechanical phenotyping of large populations of cells. These methods characterize cells by their mechanical fingerprints by exerting hydrodynamic forces and monitoring the resulting deformation. These devices have shown great promise for label-free cytometry, yet there is a critical need to improve their accuracy and reconcile any discrepancies with other methods, such as atomic force microscopy. In this study, we employ computational fluid dynamics simulations and uncover how the elasticity of frequently used carrier fluids, such as methylcellulose dissolved in phosphate-buffered saline, is significantly influential to the resulting cellular deformation. We conducted CFD simulations conventionally used within the deformability cytometry field, which neglect fluid elasticity. Subsequently, we incorporated a more comprehensive model that simulates the viscoelastic nature of the carrier fluid. A comparison of the predicted stresses between these two approaches underscores the significance of the emerging elastic stresses in addition to the well-recognized viscous stresses along the channel. Furthermore, we utilize a two-phase flow model to predict the deformation of a promyelocyte (i.e., HL-60 cell type) within a hydrodynamic constriction channel. The obtained results highlight a substantial impact of the elasticity of carrier fluid on cellular deformation and raise questions about the accuracy of mechanical property estimates derived by neglecting elastic stresses.

Critical review of single-cell mechanotyping approaches for biomedical applications

Accurate mechanical measurements of cells has the potential to improve diagnostics, therapeutics and advance understanding of disease mechanisms, where high-resolution mechanical information can be measured by deforming individual cells. Here we evaluate recently developed techniques for measuring cell-scale stiffness properties; while many such techniques have been developed, much of the work examining single-cell stiffness is impacted by difficulties in standardization and comparability, giving rise to large variations in reported mechanical moduli. We highlight the role of underlying mechanical theories driving this variability, and note opportunities to develop novel mechanotyping devices and theoretical models that facilitate convenient and accurate mechanical characterisation. Moreover, many high-throughput approaches are confounded by factors including cell size, surface friction, natural population heterogeneity and convolution of elastic and viscous contributions to cell deformability. We nevertheless identify key approaches based on deformability cytometry as a promising direction for further development, where both high-throughput and accurate single-cell resolutions can be realized.

Viscoelasticity of diverse biological samples quantified by Acoustic Force Microrheology (AFMR)

In the context of soft matter and cellular mechanics, microrheology - the use of micron-sized particles to probe the frequency-dependent viscoelastic response of materials - is widely used to shed light onto the mechanics and dynamics of molecular structures. Here we present the implementation of active microrheology in an Acoustic Force Spectroscopy setup (AFMR), which combines multiplexing with the possibility of probing a wide range of forces ( ~ pN to ~nN) and frequencies (0.01-100 Hz). To demonstrate the potential of this approach, we perform active microrheology on biological samples of increasing complexity and stiffness: collagen gels, red blood cells (RBCs), and human fibroblasts, spanning a viscoelastic modulus range of five orders of magnitude. We show that AFMR can successfully quantify viscoelastic properties by probing many beads with high single-particle precision and reproducibility. Finally, we demonstrate that AFMR to map local sample heterogeneities as well as detect cellular responses to drugs.

Mechanical complexity of living cells can be mapped onto simple homogeneous equivalents

Biological cells are built up from different constituents of varying size and stiffness which all contribute to the cell's mechanical properties. Despite this heterogeneity, in the analysis of experimental measurements one often assumes a strongly simplified homogeneous cell and thus a single elastic modulus is assigned to the entire cell. This ad-hoc simplification has so far mostly been used without proper justification. Here, we use computer simulations to show that indeed a mechanically heterogeneous cell can effectively be replaced by a homogeneous equivalent cell with a volume averaged elastic modulus. To demonstrate the validity of this approach, we investigate a hyperelastic cell with a heterogeneous interior under compression and in shear/channel flow mimicking atomic force and microfluidic measurements, respectively. We find that the homogeneous equivalent cell reproduces quantitatively the behavior of its heterogeneous counterpart, and that this equality is largely independent of the stiffness or spatial distribution of the heterogeneity.

High-throughput viscoelastic characterization of cells in hyperbolic microchannels

Extensive research has demonstrated the potential of cell viscoelastic properties as intrinsic indicators of cell state, functionality, and disease. For this, several microfluidic techniques have been developed to measure cell viscoelasticity with high-throughput. However, current microchannel designs introduce complex stress distributions on cells, leading to inaccuracies in determining the stress-strain relationship and, consequently, the viscoelastic properties. Here, we introduce a novel approach using hyperbolic microchannels that enable precise measurements under a constant extensional stress and offer a straightforward stress-strain relationship, while operating at a measurement rate of up to 100 cells per second. We quantified the stresses acting in the channels using mechanical calibration particles made from polyacrylamide (PAAm) and found that the measurement buffer, a solution of methyl cellulose and phosphate buffered saline, shows strain-thickening following a power law up to 200 s-1. By measuring oil droplets with varying viscosities, we successfully detected changes in the relaxation times of the droplets and our approach could be used to get the interfacial tension and viscosity of liquid-liquid droplet systems from the same measurement. We further applied this methodology to PAAm microgel beads, demonstrating the accurate recovery of Young's moduli and the near-ideal elastic behavior of the beads. To explore the influence of altered cell viscoelasticity, we treated HL60 human leukemia cells with latrunculin B and nocodazole, resulting in clear changes in cell stiffness while relaxation times were only minimally affected. In conclusion, our approach offers a streamlined and time-efficient solution for assessing the viscoelastic properties of large cell populations and other microscale soft particles.

Mechanical properties of human tumour tissues and their implications for cancer development

The mechanical properties of cells and tissues help determine their architecture, composition and function. Alterations to these properties are associated with many diseases, including cancer. Tensional, compressive, adhesive, elastic and viscous properties of individual cells and multicellular tissues are mostly regulated by reorganization of the actomyosin and microtubule cytoskeletons and extracellular glycocalyx, which in turn drive many pathophysiological processes, including cancer progression. This Review provides an in-depth collection of quantitative data on diverse mechanical properties of living human cancer cells and tissues. Additionally, the implications of mechanical property changes for cancer development are discussed. An increased knowledge of the mechanical properties of the tumour microenvironment, as collected using biomechanical approaches capable of multi-timescale and multiparametric analyses, will provide a better understanding of the complex mechanical determinants of cancer organization and progression. This information can lead to a further understanding of resistance mechanisms to chemotherapies and immunotherapies and the metastatic cascade.

Inertial Multi-Force Deformability Cytometry for High-Throughput, High-Accuracy, and High-Applicability Tumor Cell Mechanotyping

Previous on-chip technologies for characterizing the cellular mechanical properties often suffer from a low throughput and limited sensitivity. Herein, an inertial multi-force deformability cytometry (IMFDC) is developed for high-throughput, high-accuracy, and high-applicability tumor cell mechanotyping. Three different deformations, including shear deformations and stretch deformations under different forces, are integrated with the IMFDC. The 3D inertial focusing of cells enables the cells to deform by an identical fluid flow, and 10 parameters, such as cell area, perimeter, deformability, roundness, and rectangle deformability, are obtained in three deformations. The IMFDC is able to evaluate the deformability of different cells that are sensitive to different forces on a single chip, demonstrating the high applicability of the IMFDC in analyzing different cell lines. In identifying cell types, the three deformations exhibit different mechanical responses to cells with different sizes and deformability. A discrimination accuracy of ≈93% for both MDA-MB-231 and MCF-10A cells and a throughput of ≈500 cells s-1 can be achieved using the multiple-parameters-based machine learning model. Finally, the mechanical properties of metastatic tumor cells in pleural and peritoneal effusions are characterized, enabling the practical application of the IMFDC in clinical cancer diagnosis.

High-throughput single-cell assay for precise measurement of the intrinsic mechanical properties and shape characteristics of red blood cells

The intrinsic physical and mechanical properties of red blood cells (RBCs), including their geometric and rheological characteristics, can undergo changes in various circulatory and metabolic diseases. However, clinical diagnosis using RBC biophysical phenotypes remains impractical due to the unique biconcave shape, remarkable deformability, and high heterogeneity within different subpopulations. Here, we combine the hydrodynamic mechanisms of fluid-cell interactions in micro circular tubes with a machine learning method to develop a relatively high-throughput microfluidic technology that can accurately measure the shear modulus of the membrane, viscosity, surface area, and volume of individual RBCs. The present method can detect the subtle changes of mechanical properties in various RBC components at continuum scales in response to different doses of cytoskeletal drugs. We also investigate the correlation between glycosylated hemoglobin and RBC mechanical properties. Our study develops a methodology that combines microfluidic technology and machine learning to explore the material properties of cells based on fluid-cell interactions. This approach holds promise in offering novel label-free single-cell-assay-based biophysical markers for RBCs, thereby enhancing the potential for more robust disease diagnosis.

Photoacoustic micro-viscoelastography for mapping mechanocellular properties

Cellular biomechanical properties provide essential insights into biological functions regarding health and disease. Current measurements of the biomechanical properties of cells require physical contact with cells or pre-loading on the cells. Here, we have developed photoacoustic micro-viscoelastography (PAMVE), which utilizes the phase characteristics of photoacoustic (PA) response, for mapping mechanocellular properties in a load-free manner. PAMVE realizes the local viscoelasticity measurement on the macrophages and red blood cells with micrometer scale. Furthermore, PAMVE can successfully identify the adipose cell and skeletal muscle cell due to the difference in their composition-related biomechanical properties. PAMVE represents an irreplaceable option for interrogating characteristic mechanocellular properties, opening the possibility of studying cellular mechanobiology and pathophysiology.

Viscoelastic-Sorting Integrated Deformability Cytometer for High-Throughput Sorting and High-Precision Mechanical Phenotyping of Tumor Cells

The counts and phenotypes of circulating tumor cells (CTCs) in whole blood are useful for disease monitoring and prognostic assessment of cancer. However, phenotyping CTCs in the blood is difficult due to the presence of a large number of background blood cells, especially some blood cells with features similar to those of tumor cells. Herein, we presented a viscoelastic-sorting integrated deformability cytometer (VSDC) for high-throughput label-free sorting and high-precision mechanical phenotyping of tumor cells. A sorting chip for removing large background blood cells and a detection chip for detecting multiple cellular mechanical properties were integrated into our VSDC. Our VSDC has a sorting efficiency and a purity of over 95% and over 81% for tumor cells, respectively. Furthermore, multiple mechanical parameters were used to distinguish tumor cells from white blood cells using machine learning. An accuracy of over 97% for identifying tumor cells was successfully achieved with the highest identification accuracy of 99.4% for MCF-7 cells. It is envisioned that our VSDC will open up new avenues for high-throughput and label-free single-cell analysis in various biomedical applications.

Mathematical model for force and energy of virion-cell interactions during full engulfment in HIV: Impact of virion maturation and host cell morphology

Viral endocytosis involves elastic cell deformation, driven by chemical adhesion energy, and depends on physical interactions between the virion and cell membrane. These interactions are not easy to quantify experimentally. Hence, this study aimed to develop a mathematical model of the interactions of HIV particles with host cells and explore the effects of mechanical and morphological parameters during full virion engulfment. The invagination force and engulfment energy were described as viscoelastic and linear-elastic functions of radius and elastic modulus of virion and cell, ligand-receptor energy density and engulfment depth. The influence of changes in the virion-cell contact geometry representing different immune cells and ultrastructural membrane features and the decrease in virion radius and shedding of gp120 proteins during maturation on invagination force and engulfment energy was investigated. A low invagination force and high ligand-receptor energy are associated with high virion entry ability. The required invagination force was the same for immune cells of different sizes but lower for a local convex geometry of the cell membrane at the virion length scale. This suggests that localized membrane features of immune cells play a role in viral entry ability. The available engulfment energy decreased during virion maturation, indicating the involvement of additional biological or biochemical changes in viral entry. The developed mathematical model offers potential for the mechanobiological assessment of the invagination of enveloped viruses towards improving the prevention and treatment of viral infections.

Recent advances in deformation-assisted microfluidic cell sorting technologies

Cell sorting is an essential prerequisite for cell research and has great value in life science and clinical studies. Among the many microfluidic cell sorting technologies, label-free methods based on the size of different cell types have been widely studied. However, the heterogeneity in size for cells of the same type and the inevitable size overlap between different types of cells would result in performance degradation in size-based sorting. To tackle such challenges, deformation-assisted technologies are receiving more attention recently. Cell deformability is an inherent biophysical marker of cells that reflects the changes in their internal structures and physiological states. It provides additional dimensional information for cell sorting besides size. Therefore, in this review, we summarize the recent advances in deformation-assisted microfluidic cell sorting technologies. According to how the deformability is characterized and the form in which the force acts, the technologies can be divided into two categories: (1) the indirect category including transit-time-based and image-based methods, and (2) the direct category including microstructure-based and hydrodynamics-based methods. Finally, the separation performance and the application scenarios of each method, the existing challenges and future outlook are discussed. Deformation-assisted microfluidic cell sorting technologies are expected to realize greater potential in the label-free analysis of cells.

Computer vision meets microfluidics: a label-free method for high-throughput cell analysis

In this paper, we review the integration of microfluidic chips and computer vision, which has great potential to advance research in the life sciences and biology, particularly in the analysis of cell imaging data. Microfluidic chips enable the generation of large amounts of visual data at the single-cell level, while computer vision techniques can rapidly process and analyze these data to extract valuable information about cellular health and function. One of the key advantages of this integrative approach is that it allows for noninvasive and low-damage cellular characterization, which is important for studying delicate or fragile microbial cells. The use of microfluidic chips provides a highly controlled environment for cell growth and manipulation, minimizes experimental variability and improves the accuracy of data analysis. Computer vision can be used to recognize and analyze target species within heterogeneous microbial populations, which is important for understanding the physiological status of cells in complex biological systems. As hardware and artificial intelligence algorithms continue to improve, computer vision is expected to become an increasingly powerful tool for in situ cell analysis. The use of microelectromechanical devices in combination with microfluidic chips and computer vision could enable the development of label-free, automatic, low-cost, and fast cellular information recognition and the high-throughput analysis of cellular responses to different compounds, for broad applications in fields such as drug discovery, diagnostics, and personalized medicine.

Non-contact microfluidic analysis of the stiffness of single large extracellular vesicles from IDH1-mutated glioblastoma cells

In preparation for leveraging extracellular vesicles (EVs) for disease diagnostics and therapeutics, fundamental research is being done to understand EV biological, chemical, and physical properties. Most published studies have investigated nanoscale EVs and focused on EV biochemical content. There is much less understanding of large microscale EV characteristics and EV mechanical properties. We recently introduced a non-contact microfluidic technique that measures the stiffness of large EVs (>1 μm diameter). This pilot study probes the robustness of the microfluidic technique to distinguish between EV populations by comparing stiffness distributions of large EVs derived from glioblastoma cell lines. EVs derived from cells expressing the IDH1 mutation, a common glioblastoma mutation known to disrupt lipid metabolism, were stiffer than those expressed from wild-type cells in a statistical comparison of sample medians. A supporting lipidomics analysis showed that the IDH1 mutation increased the amount of saturated lipids in EVs. Taken together, these data encourage further investigation into the potential of high-throughput microfluidics to distinguish between large EV populations that differ in biomolecular composition. These findings contribute to the understanding of EV biomechanics, in particular for the less studied microscale EVs.

Highly efficient mRNA delivery with nonlinear microfluidic cell stretching for cellular engineering

In the past few years, messenger RNA (mRNA) has emerged as a promising therapeutic agent for the treatment and prevention of various diseases. Clinically, mRNA-based drugs have been used for cancer immunotherapy, infectious diseases, and genomic disorders. To maximize the therapeutic efficacy of mRNA, the exact amount of mRNAs must be delivered to the target locations without degradation; however, traditional delivery modalities, such as lipid carriers and electroporation, are suboptimal because of their high cost, cell-type sensitivity, low scalability, transfection/delivery inconsistency, and/or loss of cell functionality. Therefore, new effective and stable delivery methods are required. Accordingly, we present a novel nonlinear microfluidic cell stretching (μ-cell stretcher) platform that leverages viscoelastic fluids, i.e., methylcellulose (MC) solutions, and cell mechanoporation for highly efficient and robust intracellular mRNA delivery. In the proposed platform, cells suspended in MC solutions with mRNAs were injected into a microchannel where they rapidly passed through a single constriction. Owing to the use of viscoelastic MC solutions, a high shear force was applied to the cells, effectively creating transient nanopores. This feature allows mRNAs to be effectively internalized through generated membrane discontinuities. Using this platform, high delivery efficiency (∼97%), high throughput (∼3.5 × 10⁵ cells per min), cell-type-/cargo-size-insensitive delivery, simple operation (single-step), low analyte consumption, low-cost operation (<$1), and nearly clogging-free operation were demonstrated, demonstrating the high potential of the proposed platform for application in mRNA-based cellular engineering research.

A new hyperelastic lookup table for RT-DC

Real-time deformability cytometry (RT-DC) is an established method that quantifies features like size, shape, and stiffness for whole cell populations on a single-cell level in real-time. A lookup table (LUT) disentangles the experimentally derived steady-state cell deformation and the projected area to extract the cell stiffness in the form of the Young's modulus. So far, two lookup tables exist but are limited to simple linear material models and cylindrical channel geometries. Here, we present two new lookup tables for RT-DC based on a neo-Hookean hyperelastic material numerically derived by simulations based on the finite element method in square and cylindrical channel geometries. At the same time, we quantify the influence of the shear-thinning behavior of the surrounding medium on the stationary deformation of cells in RT-DC and discuss the applicability and impact of the proposed LUTs regarding past and future RT-DC data analysis. Additionally, we provide insights about the cell strain and stresses, as well as the influence resulting from the rotational symmetric assumption on the cell deformation and volume estimation. The new lookup tables and the numerical cell shapes are made freely available.

Acousto-dielectric tweezers for size-insensitive manipulation and biophysical characterization of single cells

The intrinsic biophysical properties of cells, such as mechanical, acoustic, and electrical properties, are valuable indicators of a cell's function and state. However, traditional single-cell biophysical characterization methods are hindered by limited measurable properties, time-consuming procedures, and complex system setups. This study presents acousto-dielectric tweezers that leverage the balance between controllable acoustophoretic and dielectrophoretic forces applied on cells through surface acoustic waves and alternating current electric fields, respectively. Particularly, the balanced acoustophoretic and dielectrophoretic forces can trap cells at equilibrium positions independent of the cell size to differentiate between various cell-intrinsic mechanical, acoustic, and electrical properties. Experimental results show our mechanism has the potential for applications in single-cell analysis, size-insensitive cell separation, and cell phenotyping, which are all primarily based on cells' intrinsic biophysical properties. Our results also show the measured equilibrium position of a cell can inversely determine multiple biophysical properties, including membrane capacitance, cytoplasm conductivity, and acoustic contrast factor. With these features, our acousto-dielectric tweezing mechanism is a valuable addition to the resources available for biophysical property-based biological and medical research.

Shear rheology of methyl cellulose based solutions for cell mechanical measurements at high shear rates

Methyl cellulose (MC) is a widely used material in various microfluidic applications in biology. Due to its biocompatibility, it has become a popular crowding agent for microfluidic cell deformability measurements, which usually operate at high shear rates (>10 000 s^-1). However, a full rheological characterization of methyl cellulose solutions under these conditions has not yet been reported. With this study, we provide a full shear-rheological description for solutions of up to 1% MC dissolved in phosphate-buffered saline (PBS) that are commonly used in real-time deformability cytometry (RT-DC). We characterized three different MC-PBS solutions used for cell mechanical measurements in RT-DC with three different shear rheometer setups to cover a range of shear rates from 0.1-150 000 s^-1. We report viscosities and normal stress differences in this regime. Viscosity functions can be well described using a Carreau-Yasuda model. Furthermore, we present the temperature dependency of shear viscosity and first normal stress difference of these solutions. Our results show that methyl cellulose solutions behave like power-law liquids in viscosity and exhibit first normal stress difference at shear rates between 5000-150 000 s^-1. We construct a general viscosity equation for each MC solution at a certain shear rate and temperature. Furthermore, we investigated how MC concentration influences the rheology of the solutions and found the entanglement concentration at around 0.64 w/w%. Our results help to better understand the viscoelastic behavior of MC solutions, which can now be considered when modelling stresses in microfluidic channels.

Microfluidic techniques for mechanical measurements of biological samples

The use of microfluidics to make mechanical property measurements is increasingly common. Fabrication of microfluidic devices has enabled various types of flow control and sensor integration at micrometer length scales to interrogate biological materials. For rheological measurements of biofluids, the small length scales are well suited to reach high rates, and measurements can be made on droplet-sized samples. The control of flow fields, constrictions, and external fields can be used in microfluidics to make mechanical measurements of individual bioparticle properties, often at high sampling rates for high-throughput measurements. Microfluidics also enables the measurement of bio-surfaces, such as the elasticity and permeability properties of layers of cells cultured in microfluidic devices. Recent progress on these topics is reviewed, and future directions are discussed.

A computational model for the transit of a cancer cell through a constricted microchannel

We propose a three-dimensional computational model to simulate the transient deformation of suspended cancer cells flowing through a constricted microchannel. We model the cell as a liquid droplet enclosed by a viscoelastic membrane, and its nucleus as a smaller stiffer capsule. The cell deformation and its interaction with the suspending fluid are solved through a well-tested immersed boundary lattice Boltzmann method. To identify a minimal mechanical model that can quantitatively predict the transient cell deformation in a constricted channel, we conduct extensive parametric studies of the effects of the rheology of the cell membrane, cytoplasm and nucleus and compare the results with a recent experiment conducted on human leukaemia cells. We find that excellent agreement with the experiment can be achieved by employing a viscoelastic cell membrane model with the membrane viscosity depending on its mode of deformation (shear versus elongation). The cell nucleus limits the overall deformation of the whole cell, and its effect increases with the nucleus size. The present computational model may be used to guide the design of microfluidic devices to sort cancer cells, or to inversely infer cell mechanical properties from their flow-induced deformation.

Biosensing of Haemorheological Properties Using Microblood Flow Manipulation and Quantification

The biomechanical properties of blood have been used to detect haematological diseases and disorders. The simultaneous measurement of multiple haemorheological properties has been considered an important aspect for separating the individual contributions of red blood cells (RBCs) and plasma. In this study, three haemorheological properties (viscosity, time constant, and RBC aggregation) were obtained by analysing blood flow, which was set to a square-wave profile (steady and transient flow). Based on a simplified differential equation derived using a discrete circuit model, the time constant for viscoelasticity was obtained by solving the governing equation rather than using the curve-fitting technique. The time constant (λ) varies linearly with respect to the interface in the coflowing channel (β). Two parameters (i.e., average value: <λ>, linear slope: dλdβ) were newly suggested to effectively represent linearly varying time constant. <λ> exhibited more consistent results than dλdβ. To detect variations in the haematocrit in blood, we observed that the blood viscosity (i.e., steady flow) is better than the time constant (i.e., transient flow). The blood viscosity and time constant exhibited significant differences for the hardened RBCs. The present method was then successfully employed to detect continuously varying haematocrit resulting from RBC sedimentation in a driving syringe. The present method can consistently detect variations in blood in terms of the three haemorheological properties.

Microfluidic Systems for Blood and Blood Cell Characterization

A laboratory blood test is vital for assessing a patient's health and disease status. Advances in microfluidic technology have opened the door for on-chip blood analysis. Currently, microfluidic devices can reproduce myriad routine laboratory blood tests. Considerable progress has been made in microfluidic cytometry, blood cell separation, and characterization. Along with the usual clinical parameters, microfluidics makes it possible to determine the physical properties of blood and blood cells. We review recent advances in microfluidic systems for measuring the physical properties and biophysical characteristics of blood and blood cells. Added emphasis is placed on multifunctional platforms that combine several microfluidic technologies for effective cell characterization. The combination of hydrodynamic, optical, electromagnetic, and/or acoustic methods in a microfluidic device facilitates the precise determination of various physical properties of blood and blood cells. We analyzed the physical quantities that are measured by microfluidic devices and the parameters that are determined through these measurements. We discuss unexplored problems and present our perspectives on the long-term challenges and trends associated with the application of microfluidics in clinical laboratories. We expect the characterization of the physical properties of blood and blood cells in a microfluidic environment to be considered a standard blood test in the future.

Cell deformability heterogeneity recognition by unsupervised machine learning from in-flow motion parameters

Cell deformability is a well-established marker of cell states for diagnostic purposes. However, the measurement of a wide range of different deformability levels is still challenging, especially in cancer, where a large heterogeneity of rheological/mechanical properties is present. Therefore, a simple, versatile and cost-effective recognition method for variable rheological/mechanical properties of cells is needed. Here, we introduce a new set of in-flow motion parameters capable of identifying heterogeneity among cell deformability, properly modified by the administration of drugs for cytoskeleton destabilization. Firstly, we measured cell deformability by identification of in-flow motions, rolling (R), tumbling (T), swinging (S) and tank-treading (TT), distinctively associated with cell rheological/mechanical properties. Secondly, from a pool of motion and structural cell parameters, an unsupervised machine learning approach based on principal component analysis (PCA) revealed dominant features: the local cell velocity (V_Cell/V_Avg), the equilibrium position (Y_Eq) and the orientation angle variation (Δφ). These motion parameters clearly defined cell clusters in terms of motion regimes corresponding to specific deformability. Such correlation is verified in a wide range of rheological/mechanical properties from the elastic cells moving like R until the almost viscous cells moving as TT. Thus, our approach shows how simple motion parameters allow cell deformability heterogeneity recognition, directly measuring rheological/mechanical properties.

Multiple-Streams Focusing-Based Cell Separation in High Viscoelasticity Flow

Viscoelastic flow has been widely used in microfluidic particle separation processes, in which particles get focused on the channel center in diluted viscoelastic flow. In this paper, the transition from single-stream focusing to multiple-streams focusing (MSF) in high viscoelastic flow is observed, which is applied for cell separation processes. Particle focusing stream bifurcation is caused by the balance between elastic force and viscoelastic secondary flow drag force. The influence of cell physical properties, such as cell dimension, shape, and deformability, on the formation of multiple-streams focusing is studied in detail. Particle separation is realized utilizing different separation criteria. The size-based separation of red (RBC) and white (WBC) blood cells is demonstrated in which cells get focused in different streams based on their dimension difference. Cells with different deformabilities get stretched in the viscoelastic flow, leading to the change of focusing streams, and this property is harnessed to separate red blood cells infected with the malaria parasite, Plasmodium falciparum. The achieved results promote our understanding of particle movement in the high viscoelastic flow and enable new particle manipulation and separation processes for sample treatment in biofluids.

Simple Assessment of Red Blood Cell Deformability Using Blood Pressure in Capillary Channels for Effective Detection of Subpopulations in Red Blood Cells

Assessment of red blood cell (RBC) deformability as a biomarker requires expensive equipment to induce and monitor deformation. In this study, we present a simple method for quantifying RBC deformability. We designed a microfluidic channel consisting of a micropillar channel and a coflowing channel connected in series. When blood (loading volume = 100 μL) was injected continuously into the device under constant pressure (1 bar), we monitored the boundary position of the blood and the reference flow in the coflowing channel. A decrease in the deformability of RBCs results in a growing pressure drop in the micropillar channel, which is mirrored by a decrease in blood pressure in the coflowing channel. Analysis of this temporal variation in blood pressure allowed us to define the clogging index (CI) as a new marker of RBC deformability. As a result of the analytical study and numerical simulation, we have demonstrated that the coflowing channel may serve as a pressure sensor that allows the measurement of blood pressure with accuracy. We have shown experimentally that a higher hematocrit level (i.e., more than 40%) does not have a substantial influence on CI. The CI tended to increase to a higher degree in glutaraldehyde-treated hardened RBCs. Furthermore, we were able to resolve the difference in deformability of RBCs between two different RBC density subfractions in human blood. In summary, our approach using CI provides reliable information on the deformability of RBCs, which is comparable to the readouts obtained by ektacytometry. We believe that our microfluidic device would be a useful tool for evaluating the deformability of RBCs, which does not require expensive instruments (e.g., high-speed camera) or time-consuming micro-PIV analysis.

A Systematic Study of Size Correlation and Young's Modulus Sensitivity for Cellular Mechanical Phenotyping by Microfluidic Approaches

Cellular mechanical properties are a class of intrinsic biophysical markers for cell state and health. Microfluidic mechanical phenotyping methods have emerged as promising tools to overcome the challenges of low throughput and high demand for manual skills in conventional approaches. In this work, two types of microfluidic cellular mechanical phenotyping methods, contactless hydro-stretching deformability cytometry (lh-DC) and contact constriction deformability cytometry (cc-DC) are comprehensively studied and compared. Polymerized hydrogel beads with defined sizes are used to characterize a strong negative correlation between size and deformability in cc-DC (r = -0.95), while lh-DC presents a weak positive correlation (r = 0.13). Young's modulus sensitivity in cc-DC is size-dependent while it is a constant in lh-DC. Moreover, the deformability assessment for human breast cell line mixture suggests the lh-DC exhibits better differentiation capability of cells with different size distributions, while cc-DC provides higher sensitivity to identify cellular mechanical changes within a single cell line. This work is the first to present a quantitative study and comparison of size correlation and Young's modulus sensitivity of contactless and contact microfluidic mechanical phenotyping methods, which provides guidance to choose the most suitable cellular mechanical phenotyping platform for specific cell analysis applications.

Unbiased retrieval of frequency-dependent mechanical properties from noisy time-dependent signals

The mechanical response of materials to dynamic loading is often quantified by the frequency-dependent complex modulus. Probing materials directly in the frequency domain faces technical challenges such as a limited range of frequencies, long measurement times, or small sample sizes. Furthermore, many biological samples, such as cells or tissues, can change their properties upon repetitive probing at different frequencies. Therefore, it is common practice to extract the material properties by fitting predefined mechanical models to measurements performed in the time domain. This practice, however, precludes the probing of unique and yet unexplored material properties. In this report, we demonstrate that the frequency-dependent complex modulus can be robustly retrieved in a model-independent manner directly from time-dependent stress-strain measurements. While applying a rolling average eliminates random noise and leads to a reliable complex modulus in the lower frequency range, a Fourier transform with a complex frequency helps to recover the material properties at high frequencies. Finally, by properly designing the probing procedure, the recovery of reliable mechanical properties can be extended to an even wider frequency range. Our approach can be used with many state-of-the-art experimental methods to interrogate the mechanical properties of biological and other complex materials.

Impedance-Enabled Camera-Free Intrinsic Mechanical Cytometry

Mechanical properties of single cells are important label-free biomarkers normally measured by expensive and complex imaging systems. To unlock this limit and allow mechanical properties comparable across different measurement platforms, camera-free intrinsic mechanical cytometry (CFIMC) is proposed for on-the-fly measurement of two major intrinsic mechanical parameters, that is, Young's modulus E and fluidity β, of single cells. CFIMC adopts a framework that couples the impedance electrodes with the constriction channel spatially, so that the impedance signals contain the dynamic deformability information of the cell squeezing through the constriction channel. Deformation of the cell is thus extracted from the impedance signals and used to derive the intrinsic mechanical parameters. With reasonably high throughput (>500 cells min^-1 ), CFIMC can successfully reveal the mechanical difference in cancer and normal cells (i.e., human breast cell lines MCF-10A, MCF-7, and MDA-MB-231), living and fixed cells, and pharmacological perturbations of the cytoskeleton. It is further found that 1 µM level concentration of Cytochalasin B may be the threshold for the treated cells to induce a significant cytoskeleton effect reflected by the mechanical parameters. It is envisioned that CFIMC provides an alternative avenue for high-throughput and real-time single-cell intrinsic mechanical analysis.

Wide-range viscoelastic compression forces in microfluidics to probe cell-dependent nuclear structural and mechanobiological responses

The cell nucleus plays a critical role in mechanosensing and mechanotransduction processes, by adaptive changes of its envelope composition to external biophysical stimuli such as substrate rigidity and tensile forces. Current measurement approaches lack precise control in stress application on nuclei, thus significantly impairing a complete mechanobiological study of cells. Here, we present a contactless microfluidic approach capable to exert a wide range of viscoelastic compression forces (10–10³ µN)—as an alternative to adhesion-related techniques—to induce cell-specific mechano-structural and biomolecular changes. We succeed in monitoring substantial nuclear modifications in Lamin A/C expression and coverage, diffusion processes of probing molecules, YAP shuttling, chromatin re-organization and cGAS pathway activation. As a result, high compression forces lead to a nuclear reinforcement (e.g. up to +20% in Lamin A/C coverage) or deconstruction (e.g. down to −45% in Lamin A/C coverage with a 30% reduction of chromatin condensation state parameter) up to cell death. We demonstrate how wide-range compression on suspended cells can be used as a tool to investigate nuclear mechanobiology and to define specific nuclear signatures for cell mechanical phenotyping.

Interpretation of cell mechanical experiments in microfluidic systems depend on the choice of cellular shape descriptors

The capability to parameterize shapes is of essential importance in biomechanics to identify cells, to track their motion, and to quantify deformation. While various shape descriptors have already been investigated to study the morphology and migration of adherent cells, little is known of how the mathematical definition of a contour impacts the outcome of rheological experiments on cells in suspension. In microfluidic systems, hydrodynamic stress distributions induce time-dependent cell deformation that needs to be quantified to determine viscoelastic properties. Here, we compared nine different shape descriptors to characterize the deformation of suspended cells in an extensional as well as shear flow using dynamic real-time deformability cytometry. While stress relaxation depends on the amplitude and duration of stress, our results demonstrate that steady-state deformation can be predicted from single cell traces even for translocation times shorter than their characteristic time. Implementing an analytical simulation, performing experiments, and testing various data analysis strategies, we compared single cell and ensemble studies to address the question of computational costs vs experimental accuracy. Results indicate that high-throughput viscoelastic measurements of cells in suspension can be performed on an ensemble scale as long as the characteristic time matches the dimensions of the microfluidic system. Finally, we introduced a score to evaluate the shape descriptor-dependent effect size for cell deformation after cytoskeletal modifications. We provide evidence that single cell analysis in an extensional flow provides the highest sensitivity independent of shape parametrization, while inverse Haralick's circularity is mostly applicable to study cells in shear flow.

Cell and Tissue Nanomechanics: From Early Development to Carcinogenesis

Cell and tissue nanomechanics, being inspired by progress in high-resolution physical mapping, has recently burst into biomedical research, discovering not only new characteristics of normal and diseased tissues, but also unveiling previously unknown mechanisms of pathological processes. Some parallels can be drawn between early development and carcinogenesis. Early embryogenesis, up to the blastocyst stage, requires a soft microenvironment and internal mechanical signals induced by the contractility of the cortical actomyosin cytoskeleton, stimulating quick cell divisions. During further development from the blastocyst implantation to placenta formation, decidua stiffness is increased ten-fold when compared to non-pregnant endometrium. Organogenesis is mediated by mechanosignaling inspired by intercellular junction formation with the involvement of mechanotransduction from the extracellular matrix (ECM). Carcinogenesis dramatically changes the mechanical properties of cells and their microenvironment, generally reproducing the structural properties and molecular organization of embryonic tissues, but with a higher stiffness of the ECM and higher cellular softness and fluidity. These changes are associated with the complete rearrangement of the entire tissue skeleton involving the ECM, cytoskeleton, and the nuclear scaffold, all integrated with each other in a joint network. The important changes occur in the cancer stem-cell niche responsible for tumor promotion and metastatic growth. We expect that the promising concept based on the natural selection of cancer cells fixing the most invasive phenotypes and genotypes by reciprocal regulation through ECM-mediated nanomechanical feedback loop can be exploited to create new therapeutic strategies for cancer treatment.

Advance of microfluidic constriction channel system of measuring single-cell cortical tension/specific capacitance of membrane and conductivity of cytoplasm

This paper reported a microfluidic platform which realized the characterization of inherent single-cell biomechanical and bioelectrical parameters simultaneously. Individual cells traveled through a constriction channel with deformation images and impedance variations captured and processed into cortical tension T_c , specific membrane capacitance C_sm , and cytoplasmic conductivity σ_cy based on an equivalent biophysical model. These properties of thousands of individual cells of K562, Jurkat, HL-60, HL-60 treated with paraformaldehyde (PA)/cytochalasin D (CD)/concanavalin A (ConA), granulocytes of Donor 1, Donor 2, and Donor 3 were quantified for the first time. Leveraging T_c , C_sm , and σ_cy , (1) high accuracies of classifying wild-type and processed HL-60 cells (e.g., 93.5% of PA treated vs. CD treated HL-60 cells) were realized, revealing the effectiveness of using these three biophysical parameters in cell-type classification; (2) low accuracies of classifying normal granulocytes from three donors (e.g., 56.4% of Donor 1 vs. 2), indicating comparable parameters for normal granulocytes. In conclusion, this platform can characterize single-cell T_c , C_sm , and σ_cy concurrently and quantify multiple parameters in single-cell analysis.

Axial and Nonaxial Migration of Red Blood Cells in a Microtube

Human red blood cells (RBCs) are subjected to high viscous shear stress, especially during microcirculation, resulting in stable deformed shapes such as parachute or slipper shape. Those unique deformed RBC shapes, accompanied with axial or nonaxial migration, cannot be fully described according to traditional knowledge about lateral movement of deformable spherical particles. Although several experimental and numerical studies have investigated RBC behavior in microchannels with similar diameters as RBCs, the detailed mechanical characteristics of RBC lateral movement—in particular, regarding the relationship between stable deformed shapes, equilibrium radial RBC position, and membrane load—has not yet been fully described. Thus, we numerically investigated the behavior of single RBCs with radii of 4 μm in a circular microchannel with diameters of 15 μm. Flow was assumed to be almost inertialess. The problem was characterized by the capillary number, which is the ratio between fluid viscous force and membrane elastic force. The power (or energy dissipation) associated with membrane deformations was introduced to quantify the state of membrane loads. Simulations were performed with different capillary numbers, viscosity ratios of the internal to external fluids of RBCs, and initial RBC centroid positions. Our numerical results demonstrated that axial or nonaxial migration of RBC depended on the stable deformed RBC shapes, and the equilibrium radial position of the RBC centroid correlated well with energy expenditure associated with membrane deformations.

T cell stiffness is enhanced upon formation of immunological synapse

T cells are activated by target cells via an intimate contact, termed immunological synapse (IS). Cellular mechanical properties, especially stiffness, are essential to regulate cell functions. However, T cell stiffness at a subcellular level at the IS still remains largely elusive. In this work, we established an atomic force microscopy (AFM)-based elasticity mapping method on whole T cells to obtain an overview of the stiffness with a resolution of ~60 nm. Using primary human CD4⁺ T cells, we show that when T cells form IS with stimulating antibody-coated surfaces, the lamellipodia are stiffer than the cell body. Upon IS formation, T cell stiffness is enhanced both at the lamellipodia and on the cell body. Chelation of intracellular Ca²⁺ abolishes IS-induced stiffening at the lamellipodia but has no influence on cell-body-stiffening, suggesting different regulatory mechanisms of IS-induced stiffening at the lamellipodia and the cell body.

On the Determination of Mechanical Properties of Aqueous Microgels-Towards High-Throughput Characterization

Aqueous microgels are distinct entities of soft matter with mechanical signatures that can be different from their macroscopic counterparts due to confinement effects in the preparation, inherently made to consist of more than one domain (Janus particles) or further processing by coating and change in the extent of crosslinking of the core. Motivated by the importance of the mechanical properties of such microgels from a fundamental point, but also related to numerous applications, we provide a perspective on the experimental strategies currently available and emerging tools being explored. Albeit all techniques in principle exploit enforcing stress and observing strain, the realization differs from directly, as, e.g., by atomic force microscope, to less evident in a fluid field combined with imaging by a high-speed camera in high-throughput strategies. Moreover, the accompanying analysis strategies also reflect such differences, and the level of detail that would be preferred for a comprehensive understanding of the microgel mechanical properties are not always implemented. Overall, the perspective is that current technologies have the capacity to provide detailed, nanoscopic mechanical characterization of microgels over an extended size range, to the high-throughput approaches providing distributions over the mechanical signatures, a feature not readily accessible by atomic force microscopy and micropipette aspiration.

In vitro analysis of multiple blood flow determinants using red blood cell dynamics under oscillatory flow

The flow behavior of blood is determined mainly by red blood cell (RBC) deformation and aggregation as well as blood viscoelasticity. These intricately interdependent parameters should be monitored by healthcare providers to understand all aspects of circulatory flow dynamics under numerous cases including cardiovascular and infectious diseases. Current medical instruments and microfluidic systems lack the ability to quantify these parameters all at once and in physiologically relevant flow conditions. This work presents a handheld platform and a measurement method for quantitative analysis of multiple of these parameters from 50 μl undiluted blood inside a miniaturized channel. The assay is based on an optical transmission analysis of collective RBC deformation and aggregation under near-infrared illumination during a 1 s damped oscillatory flow and at stasis, respectively. Measurements with blood of different hemo-rheological properties demonstrate that the presented approach holds a potential for initiating simultaneous and routine on-chip blood flow analysis even in resource-poor settings.

A neural network-based algorithm for high-throughput characterisation of viscoelastic properties of flowing microcapsules

Microcapsules, consisting of a liquid droplet enclosed by a viscoelastic membrane, have a wide range of biomedical and pharmaceutical applications and also serve as a popular mechanical model for biological cells. In this study, we develop a novel high throughput approach, by combining a machine learning method with a high-fidelity mechanistic capsule model, to accurately predict the membrane elasticity and viscosity of microcapsules from their dynamic deformation when flowing in a branched microchannel. The machine learning method consists of a deep convolutional neural network (DCNN) connected by a long short-term memory (LSTM) network. We demonstrate that with a superior prediction accuracy the present hybrid DCNN-LSTM network can still be faster than a conventional inverse method by five orders of magnitude, and can process thousands of capsules per second. We also show that the hybrid network has fewer restrictions compared with a simple DCNN.

Toward deep biophysical cytometry: prospects and challenges

The biophysical properties of cells reflect their identities, underpin their homeostatic state in health, and define the pathogenesis of disease. Recent leapfrogging advances in biophysical cytometry now give access to this information, which is obscured in molecular assays, with a discriminative power that was once inconceivable. However, biophysical cytometry should go 'deeper' in terms of exploiting the information-rich cellular biophysical content, generating a molecular knowledge base of cellular biophysical properties, and standardizing the protocols for wider dissemination. Overcoming these barriers, which requires concurrent innovations in microfluidics, optical imaging, and computer vision, could unleash the enormous potential of biophysical cytometry not only for gaining a new mechanistic understanding of biological systems but also for identifying new cost-effective biomarkers of disease.

Cell nucleus as a microrheological probe to study the rheology of the cytoskeleton

Mechanical properties of the cell are important biomarkers for probing its architectural changes caused by cellular processes and/or pathologies. The development of microfluidic technologies has enabled measuring the cell's mechanical properties at high throughput so that mechanical phenotyping can be applied to large samples in reasonable timescales. These studies typically measure the stiffness of the cell as the only mechanical biomarker and do not disentangle the rheological contributions of different structural components of the cell, including the cell cortex, the interior cytoplasm and its immersed cytoskeletal structures, and the nucleus. Recent advancements in high-speed fluorescent imaging have enabled probing the deformations of the cell cortex while also tracking different intracellular components in rates applicable to microfluidic platforms. We present a, to our knowledge, novel method to decouple the mechanics of the cell cortex and the cytoplasm by analyzing the correlation between the cortical deformations that are induced by external microfluidic flows and the nucleus displacements, induced by those cortical deformations, i.e., we use the nucleus as a high-throughput microrheological probe to study the rheology of the cytoplasm, independent of the cell cortex mechanics. To demonstrate the applicability of this method, we consider a proof-of-concept model consisting of a rigid spherical nucleus centered in a spherical cell. We obtain analytical expressions for the time-dependent nucleus velocity as a function of the cell deformations when the interior cytoplasm is modeled as a viscous, viscoelastic, porous, and poroelastic material and demonstrate how the nucleus velocity can be used to characterize the linear rheology of the cytoplasm over a wide range of forces and timescales/frequencies.

Mechanical properties of cell- and microgel bead-laden oxidized alginate-gelatin hydrogels

3D-printing technologies, such as biofabrication, capitalize on the homogeneous distribution and growth of cells inside biomaterial hydrogels, ultimately aiming to allow for cell differentiation, matrix remodeling, and functional tissue analogues. However, commonly, only the mechanical properties of the bioinks or matrix materials are assessed, while the detailed influence of cells on the resulting mechanical properties of hydrogels remains insufficiently understood. Here, we investigate the properties of hydrogels containing cells and spherical PAAm microgel beads through multi-modal complex mechanical analyses in the small- and large-strain regimes. We evaluate the individual contributions of different filler concentrations and a non-fibrous oxidized alginate-gelatin hydrogel matrix on the overall mechanical behavior in compression, tension, and shear. Through material modeling, we quantify parameters that describe the highly nonlinear mechanical response of soft composite materials. Our results show that the stiffness significantly drops for cell- and bead concentrations exceeding four million per milliliter hydrogel. In addition, hydrogels with high cell concentrations (≥6 mio ml^-1) show more pronounced material nonlinearity for larger strains and faster stress relaxation. Our findings highlight cell concentration as a crucial parameter influencing the final hydrogel mechanics, with implications for microgel bead drug carrier-laden hydrogels, biofabrication, and tissue engineering.

Label-Free Isolation and Single Cell Biophysical Phenotyping Analysis of Primary Cardiomyocytes Using Inertial Microfluidics

To advance the understanding of cardiomyocyte (CM) identity and function, appropriate tools to isolate pure primary CMs are needed. A label-free method to purify viable CMs from mouse neonatal hearts is developed using a simple particle size-based inertial microfluidics biochip achieving purities of over 90%. Purified CMs are viable and retained their identity and function as depicted by the expression of cardiac-specific markers and contractility. The physico-mechanical properties of sorted cells are evaluated using downstream real-time deformability cytometry. CMs exhibited different physico-mechanical properties when compared with non-CMs. Taken together, this CM isolation and phenotyping method could serve as a valuable tool to progress the understanding of CM identity and function, and ultimately benefit cell therapy and diagnostic applications.

Characterization of Single-Cell Osmotic Swelling Dynamics for New Physical Biomarkers

Characterization of cell physical biomarkers is vital to understand cell properties and applicable for disease diagnostics. Current methods used to analyze physical phenotypes involve external forces to deform the cells. Alternatively, internal tension forces via osmotic swelling can also deform the cells. However, an established assumption contends that the forces generated during hypotonic swelling concentrated on the plasma membrane are incapable of assessing the physical properties of nucleated cells. Here, we utilized an osmotic swelling approach to characterize different types of nucleated cells. Using a microfluidic device for cell trapping arrays with truncated hanging micropillars (CellHangars), we isolated single cells and evaluated the swelling dynamics during the hypotonic challenge at 1 s time resolution. We demonstrated that cells with different mechanical phenotypes showed unique swelling dynamics signature. Different types of cells can be classified with an accuracy of up to ∼99%. We also showed that swelling dynamics can detect cellular mechanical property changes due to cytoskeleton disruption. Considering its simplicity, swelling dynamics offers an invaluable label-free physical biomarker for cells with potential applications in both biological studies and clinical practice.

Mechanical phenotyping of breast cell lines by in-flow deformation-dependent dynamics under tuneable compressive forces

Cell mechanical properties are powerful biomarkers for label-free phenotyping. To date, microfluidic approaches assay mechanical properties by measuring changes in cellular shape, applying extensional or shear flows or forcing cells to pass through constrictions. In general, such approaches use high-speed imaging or transit time measurements to evaluate cell deformation, while cell dynamics in-flow after stress imposition have not yet been considered. Here, we present a microfluidic approach to apply, over a wide range, tuneable compressive forces on suspended cells, which result in well distinct signatures of deformation-dependent dynamic motions. By properly conceiving microfluidic chip geometry and rheological fluid properties, we modulate applied single-cell forces, which result in different motion regimes (rolling, tumbling or tank-treating) depending on the investigated cell line. We decided to prove our approach by testing breast cell lines, with well-known mechanical properties. We measured a set of in-flow parameters (orientation angle, aspect ratio, cell deformation and cell diameter) as a backward analysis of cell mechanical response. By such an approach, we report that the highly invasive tumour cells (MDA-MB-231) are much more deformable (6-times higher) than healthy (MCF-10A) and low invasive ones (MCF-7). Thus, we demonstrate that a microfluidic design with tuneable rheological fluid properties and direct analysis of bright-field images can be suitable for the label-free mechanical phenotyping of various cell lines.