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

DNA microbeads for spatio-temporally controlled morphogen release within organoids

Organoids are transformative in vitro model systems that mimic features of the corresponding tissue in vivo. However, across tissue types and species, organoids still often fail to reach full maturity and function because biochemical cues cannot be provided from within the organoid to guide their development. Here we introduce nanoengineered DNA microbeads with tissue mimetic tunable stiffness for implementing spatio-temporally controlled morphogen gradients inside of organoids at any point in their development. Using medaka retinal organoids and early embryos, we show that DNA microbeads can be integrated into embryos and organoids by microinjection and erased in a non-invasive manner with light. Coupling a recombinant surrogate Wnt to the DNA microbeads, we demonstrate the spatio-temporally controlled morphogen release from the microinjection site, which leads to morphogen gradients resulting in the formation of retinal pigmented epithelium while maintaining neuroretinal cell types. Thus, we bioengineered retinal organoids to more closely mirror the cell type diversity of in vivo retinae. Owing to the facile, one-pot fabrication process, the DNA microbead technology can be adapted to other organoid systems for improved tissue mimicry.

Endothelin-1 influences mechanical properties and contractility of hiPSC derived cardiomyocytes resulting in diastolic dysfunction

A better understanding of the underlying pathomechanisms of diastolic dysfunction is crucial for the development of targeted therapeutic options with the aim to increase the patients' quality of life. In order to shed light on the processes involved, suitable models are required. Here, effects of endothelin-1 (ET-1) treatment on cardiomyocytes derived from human induced pluripotent stem cells (hiPSCs) were investigated. While it is well established, that ET-1 treatment induces hypertrophy in cardiomyocytes, resulting changes in cell mechanics and contractile behavior with focus on relaxation have not been examined before. Cardiomyocytes were treated with 10 nM of ET-1 for 24 h and 48 h, respectively. Hypertrophy was confirmed by real-time deformability cytometry (RT-DC) which was also used to assess the mechanical properties of cardiomyocytes. For investigation of the contractile behavior, 24 h phase contrast video microscopy was applied. To get a deeper insight into changes on the molecular biological level, gene expression analysis was performed using the NanoString nCounter® cardiovascular disease panel. Besides an increased cell size, ET-1 treated cardiomyocytes are stiffer and show an impaired relaxation. Gene expression patterns in ET-1 treated hiPSC derived cardiomyocytes showed that pathways associated with cardiovascular diseases, cardiac hypertrophy and extracellular matrix were upregulated while those associated with fatty acid metabolism were downregulated. We conclude that alterations in cardiomyocytes after ET-1 treatment go far beyond hypertrophy and represent a useful model for diastolic dysfunction.

Detecting normal and cancer skin cells via glycosylation and adhesion signatures: A path to enhanced microfluidic phenotyping

Recruiting circulating cells based on interactions between surface receptors and corresponding ligands holds promise for capturing cells with specific adhesive properties. Our study investigates the adhesion of skin cells to specific lectins, particularly focusing on advancements in lectin-based biosensors with diagnostic potential. We explore whether we can successfully capture normal skin (melanocytes and keratinocytes) and melanoma (WM35, WM115, WM266-4) cells in a low-shear flow environment by coating surfaces with lectins. Specifically, we coated surfaces with Dolichos biflorus (DBA) and Maackia Amurensis (MAL) lectins, which were used to detect and capture specific skin cells from the flow of cell mixture. Alterations in glycan expression (confirmed by fluorescent microscopy) demonstrated that DBA binds predominantly to normal skin cells, while MAL interacts strongly with melanoma cells. Assessing adhesion under static and dynamic low-shear stress conditions (up to 30 mPa) underscores the reliability of DBA and MAL as markers for discriminating specific cell type. Melanocytes and keratinocytes adhere to DBA-coated surfaces, while melanoma cells prefer MAL-coated surfaces. A comprehensive analysis encompassing cell shape, cytoskeleton, and focal adhesions shows the independence of our approach from the inherent characteristics of cells, thus demonstrating its robustness. Our results carry practical implications for lectin-biosensor designs, emphasizing the significance of glycan-based discrimination of pathologically altered cells. Combined with microfluidics, it demonstrates the value of cell adhesion as a discriminant of cancer-related changes, with potential applications spanning diagnostics, therapeutic interventions, and advanced biomedical technologies.

Advances in single-cell transcriptomics in animal research

Understanding biological mechanisms is fundamental for improving animal production and health to meet the growing demand for high-quality protein. As an emerging biotechnology, single-cell transcriptomics has been gradually applied in diverse aspects of animal research, offering an effective method to study the gene expression of high-throughput single cells of different tissues/organs in animals. In an unprecedented manner, researchers have identified cell types/subtypes and their marker genes, inferred cellular fate trajectories, and revealed cell‒cell interactions in animals using single-cell transcriptomics. In this paper, we introduce the development of single-cell technology and review the processes, advancements, and applications of single-cell transcriptomics in animal research. We summarize recent efforts using single-cell transcriptomics to obtain a more profound understanding of animal nutrition and health, reproductive performance, genetics, and disease models in different livestock species. Moreover, the practical experience accumulated based on a large number of cases is highlighted to provide a reference for determining key factors (e.g., sample size, cell clustering, and cell type annotation) in single-cell transcriptomics analysis. We also discuss the limitations and outlook of single-cell transcriptomics in the current stage. This paper describes the comprehensive progress of single-cell transcriptomics in animal research, offering novel insights and sustainable advancements in agricultural productivity and animal health.

Information-Distilled Generative Label-Free Morphological Profiling Encodes Cellular Heterogeneity

Image-based cytometry faces challenges due to technical variations arising from different experimental batches and conditions, such as differences in instrument configurations or image acquisition protocols, impeding genuine biological interpretation of cell morphology. Existing solutions, often necessitating extensive pre-existing data knowledge or control samples across batches, have proved limited, especially with complex cell image data. To overcome this, "Cyto-Morphology Adversarial Distillation" (CytoMAD), a self-supervised multi-task learning strategy that distills biologically relevant cellular morphological information from batch variations, is introduced to enable integrated analysis across multiple data batches without complex data assumptions or extensive manual annotation. Unique to CytoMAD is its "morphology distillation", symbiotically paired with deep-learning image-contrast translation-offering additional interpretable insights into label-free cell morphology. The versatile efficacy of CytoMAD is demonstrated in augmenting the power of biophysical imaging cytometry. It allows integrated label-free classification of human lung cancer cell types and accurately recapitulates their progressive drug responses, even when trained without the drug concentration information. CytoMAD  also allows joint analysis of tumor biophysical cellular heterogeneity, linked to epithelial-mesenchymal plasticity, that standard fluorescence markers overlook. CytoMAD can substantiate the wide adoption of biophysical cytometry for cost-effective diagnosis and screening.

The F-actin bundler SWAP-70 promotes tumor metastasis

Dynamic rearrangements of the F-actin cytoskeleton are a hallmark of tumor metastasis. Thus, proteins that govern F-actin rearrangements are of major interest for understanding metastasis and potential therapies. We hypothesized that the unique F-actin binding and bundling protein SWAP-70 contributes importantly to metastasis. Orthotopic, ectopic, and short-term tail vein injection mouse breast and lung cancer models revealed a strong positive dependence of lung and bone metastasis on SWAP-70. Breast cancer cell growth, migration, adhesion, and invasion assays revealed SWAP-70's key role in these metastasis-related cell features and the requirement for SWAP-70 to bind F-actin. Biophysical experiments showed that tumor cell stiffness and deformability are negatively modulated by SWAP-70. Together, we present a hitherto undescribed, unique F-actin modulator as an important contributor to tumor metastasis.

Microfluidic characterization of single-cell biophysical properties and the applications in cancer diagnosis

Single-cell biophysical properties play a crucial role in regulating cellular physiological states and functions, demonstrating significant potential in the fields of life sciences and clinical diagnostics. Therefore, over the last few decades, researchers have developed various detection tools to explore the relationship between the biophysical changes of biological cells and human diseases. With the rapid advancement of modern microfabrication technology, microfluidic devices have quickly emerged as a promising platform for single-cell analysis offering advantages including high-throughput, exceptional precision, and ease of manipulation. Consequently, this paper provides an overview of the recent advances in microfluidic analysis and detection systems for single-cell biophysical properties and their applications in the field of cancer. The working principles and latest research progress of single-cell biophysical property detection are first analyzed, highlighting the significance of electrical and mechanical properties. The development of data acquisition and processing methods for real-time, high-throughput, and practical applications are then discussed. Furthermore, the differences in biophysical properties between tumor and normal cells are outlined, illustrating the potential for utilizing single-cell biophysical properties for tumor cell identification, classification, and drug response assessment. Lastly, we summarize the limitations of existing microfluidic analysis and detection systems in single-cell biophysical properties, while also pointing out the prospects and future directions of their applications in cancer diagnosis and treatment.

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.

Computational Hyperspectral Microflow Cytometry

Miniaturized flow cytometry has significant potential for portable applications, such as cell-based diagnostics and the monitoring of therapeutic cell manufacturing, however, the performance of current techniques is often limited by the inability to resolve spectrally-overlapping fluorescence labels. Here, the study presents a computational hyperspectral microflow cytometer (CHC) that enables accurate discrimination of spectrally-overlapping fluorophores labeling single cells. CHC employs a dispersive optical element and an optimization algorithm to detect the full fluorescence emission spectrum from flowing cells, with a high spectral resolution of ≈3 nm in the range from 450 to 650 nm. CHC also includes a dedicated microfluidic device that ensures in-focus imaging through viscoelastic sheathless focusing, thereby enhancing the accuracy and reliability of microflow cytometry analysis. The potential of CHC for analyzing T lymphocyte subpopulations and monitoring changes in cell composition during T cell expansion is demonstrated. Overall, CHC represents a major breakthrough in microflow cytometry and can facilitate its use for immune cell monitoring.

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.

Size Matters: Rethinking Hertz Model Interpretation for Cell Mechanics Using AFM

Cell mechanics are a biophysical indicator of cell state, such as cancer metastasis, leukocyte activation, and cell cycle progression. Atomic force microscopy (AFM) is a widely used technique to measure cell mechanics, where the Young modulus of a cell is usually derived from the Hertz contact model. However, the Hertz model assumes that the cell is an elastic, isotropic, and homogeneous material and that the indentation is small compared to the cell size. These assumptions neglect the effects of the cytoskeleton, cell size and shape, and cell environment on cell deformation. In this study, we investigated the influence of cell size on the estimated Young's modulus using liposomes as cell models. Liposomes were prepared with different sizes and filled with phosphate buffered saline (PBS) or hyaluronic acid (HA) to mimic the cytoplasm. AFM was used to obtain the force indentation curves and fit them to the Hertz model. We found that the larger the liposome, the lower the estimated Young's modulus for both PBS-filled and HA-filled liposomes. This suggests that the Young modulus obtained from the Hertz model is not only a property of the cell material but also depends on the cell dimensions. Therefore, when comparing or interpreting cell mechanics using the Hertz model, it is essential to account for cell size.

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.

High throughput cell mechanotyping of cell response to cytoskeletal modulations using a microfluidic cell deformation system

Cellular mechanical properties influence cellular functions across pathological and physiological systems. The observation of these mechanical properties is limited in part by methods with a low throughput of acquisition or with low accessibility. To overcome these limitations, we have designed, developed, validated, and optimized a microfluidic cellular deformation system (MCDS) capable of mechanotyping suspended cells on a population level at a high throughput rate of ∼300 cells pers second. The MCDS provides researchers with a viable method for efficiently quantifying cellular mechanical properties towards defining prognostic implications of mechanical changes in pathology or screening drugs to modulate cytoskeletal integrity.

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.

Tumor Biomechanics Alters Metastatic Dissemination of Triple Negative Breast Cancer via Rewiring Fatty Acid Metabolism

In recent decades, the role of tumor biomechanics on cancer cell behavior at the primary site has been increasingly appreciated. However, the effect of primary tumor biomechanics on the latter stages of the metastatic cascade, such as metastatic seeding of secondary sites and outgrowth remains underappreciated. This work sought to address this in the context of triple negative breast cancer (TNBC), a cancer type known to aggressively disseminate at all stages of disease progression. Using mechanically tuneable model systems, mimicking the range of stiffness's typically found within breast tumors, it is found that, contrary to expectations, cancer cells exposed to softer microenvironments are more able to colonize secondary tissues. It is shown that heightened cell survival is driven by enhanced metabolism of fatty acids within TNBC cells exposed to softer microenvironments. It is demonstrated that uncoupling cellular mechanosensing through integrin β1 blocking antibody effectively causes stiff primed TNBC cells to behave like their soft counterparts, both in vitro and in vivo. This work is the first to show that softer tumor microenvironments may be contributing to changes in disease outcome by imprinting on TNBC cells a greater metabolic flexibility and conferring discrete cell survival advantages.

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.

Membrane localization of actin filaments stabilizes giant unilamellar vesicles against external deforming forces

Actin organization is crucial for establishing cell polarity, which influences processes such as directed cell motility and division. Despite its critical role in living organisms, achieving similar polarity in synthetic cells remains challenging. In this study, we employ a bottom-up approach to investigate how molecular crowders facilitate the formation of cortex-like actin networks and how these networks localize and organize based on membrane shape. Using giant unilamellar vesicles (GUVs) as models for cell membranes, we show that actin filaments can arrange along the membrane to form cortex-like structures. Notably, this organization is achieved using only actin and crowders as a minimal set of components. We utilize surface micropatterning to examine actin filament organization in deformed GUVs adhered to various pattern shapes. Our findings indicate that at the periphery of spherical GUVs, actin bundles align along the membrane. However, in highly curved regions of adhered GUVs, actin bundles avoid crossing the highly curved edges perpendicular to the adhesion site and instead remain in the lower curved regions by aligning parallel to the micropatterned surface. Furthermore, the actin bundles increase the stiffness of the GUVs, effectively counteracting strong deformations when GUVs adhere to micropatterns. This finding is corroborated by real-time deformability cytometry on GUVs with synthetic actin cortices. By precisely manipulating the shape of GUVs, our study provides a minimal system to investigate the interplay between actin structures and the membrane. Our findings provide insights into the spatial organization of actin structures within crowded environments, specifically inside GUVs that resemble the size and shape of cells. This study advances our understanding of actin network organization and functionality within cell-sized compartments.

High-throughput mechanical phenotyping and transcriptomics of single cells

The molecular system regulating cellular mechanical properties remains unexplored at single-cell resolution mainly due to a limited ability to combine mechanophenotyping with unbiased transcriptional screening. Here, we describe an electroporation-based lipid-bilayer assay for cell surface tension and transcriptomics (ELASTomics), a method in which oligonucleotide-labelled macromolecules are imported into cells via nanopore electroporation to assess the mechanical state of the cell surface and are enumerated by sequencing. ELASTomics can be readily integrated with existing single-cell sequencing approaches and enables the joint study of cell surface mechanics and underlying transcriptional regulation at an unprecedented resolution. We validate ELASTomics via analysis of cancer cell lines from various malignancies and show that the method can accurately identify cell types and assess cell surface tension. ELASTomics enables exploration of the relationships between cell surface tension, surface proteins, and transcripts along cell lineages differentiating from the haematopoietic progenitor cells of mice. We study the surface mechanics of cellular senescence and demonstrate that RRAD regulates cell surface tension in senescent TIG-1 cells. ELASTomics provides a unique opportunity to profile the mechanical and molecular phenotypes of single cells and can dissect the interplay among these in a range of biological contexts.

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.

Membrane to cortex attachment determines different mechanical phenotypes in LGR5+ and LGR5- colorectal cancer cells

Colorectal cancer (CRC) tumors are composed of heterogeneous and plastic cell populations, including a pool of cancer stem cells that express LGR5. Whether these distinct cell populations display different mechanical properties, and how these properties might contribute to metastasis is poorly understood. Using CRC patient derived organoids (PDOs), we find that compared to LGR5- cells, LGR5+ cancer stem cells are stiffer, adhere better to the extracellular matrix (ECM), move slower both as single cells and clusters, display higher nuclear YAP, show a higher survival rate in response to mechanical confinement, and form larger transendothelial gaps. These differences are largely explained by the downregulation of the membrane to cortex attachment proteins Ezrin/Radixin/Moesin (ERMs) in the LGR5+ cells. By analyzing single cell RNA-sequencing (scRNA-seq) expression patterns from a patient cohort, we show that this downregulation is a robust signature of colorectal tumors. Our results show that LGR5- cells display a mechanically dynamic phenotype suitable for dissemination from the primary tumor whereas LGR5+ cells display a mechanically stable and resilient phenotype suitable for extravasation and metastatic growth.

Microfluidics-Based Technologies for the Assessment of Castration-Resistant Prostate Cancer

Castration-resistant prostate cancer remains a significant clinical challenge, wherein patients display no response to existing hormone therapies. The standard of care often includes aggressive treatment options using chemotherapy, radiation therapy and various drugs to curb the growth of additional metastases. As such, there is a dire need for the development of innovative technologies for both its diagnosis and its management. Traditionally, scientific exploration of prostate cancer and its treatment options has been heavily reliant on animal models and two-dimensional (2D) in vitro technologies. However, both laboratory tools often fail to recapitulate the dynamic tumor microenvironment, which can lead to discrepancies in drug efficacy and side effects in a clinical setting. In light of the limitations of traditional animal models and 2D in vitro technologies, the emergence of microfluidics as a tool for prostate cancer research shows tremendous promise. Namely, microfluidics-based technologies have emerged as powerful tools for assessing prostate cancer cells, isolating circulating tumor cells, and examining their behaviour using tumor-on-a-chip models. As such, this review aims to highlight recent advancements in microfluidics-based technologies for the assessment of castration-resistant prostate cancer and its potential to advance current understanding and to improve therapeutic outcomes.

Photocell-Based Optofluidic Device for Clogging-Free Cell Transit Time Measurements

Measuring the transit time of a cell forced through a bottleneck is one of the most widely used techniques for the study of cell deformability in flow. It in turn provides an accessible and rapid way of obtaining crucial information regarding cell physiology. Many techniques are currently being investigated to reliably retrieve this time, but their translation to diagnostic-oriented devices is often hampered by their complexity, lack of robustness, and the bulky external equipment required. Herein, we demonstrate the benefits of coupling microfluidics with an optical method, like photocells, to measure the transit time. We exploit the femtosecond laser irradiation followed by chemical etching (FLICE) fabrication technique to build a monolithic 3D device capable of detecting cells flowing through a 3D non-deformable constriction which is fully buried in a fused silica substrate. We validated our chip by measuring the transit times of pristine breast cancer cells (MCF-7) and MCF-7 cells treated with Latrunculin A, a drug typically used to increase their deformability. A difference in transit times can be assessed without the need for complex external instrumentation and/or demanding computational efforts. The high throughput (4000-10,000 cells/min), ease of use, and clogging-free operation of our device bring this approach much closer to real scenarios.

"Patchiness" in mechanical stiffness across a tumor as an early-stage marker for malignancy

Mechanical phenotyping of tumors, either at an individual cell level or tumor cell population level is gaining traction as a diagnostic tool. However, the extent of diagnostic and prognostic information that can be gained through these measurements is still unclear. In this work, we focus on the heterogeneity in mechanical properties of cells obtained from a single source such as a tissue or tumor as a potential novel biomarker. We believe that this heterogeneity is a conventionally overlooked source of information in mechanical phenotyping data. We use mechanics-based in-silico models of cell-cell interactions and cell population dynamics within 3D environments to probe how heterogeneity in cell mechanics drives tissue and tumor dynamics. Our simulations show that the initial heterogeneity in the mechanical properties of individual cells and the arrangement of these heterogenous sub-populations within the environment can dictate overall cell population dynamics and cause a shift towards the growth of malignant cell phenotypes within healthy tissue environments. The overall heterogeneity in the cellular mechanotype and their spatial distributions is quantified by a "patchiness" index, which is the ratio of the global to local heterogeneity in cell populations. We observe that there exists a threshold value of the patchiness index beyond which an overall healthy population of cells will show a steady shift towards a more malignant phenotype. Based on these results, we propose that the "patchiness" of a tumor or tissue sample, can be an early indicator for malignant transformation and cancer occurrence in benign tumors or healthy tissues. Additionally, we suggest that tissue patchiness, measured either by biochemical or biophysical markers, can become an important metric in predicting tissue health and disease likelihood just as landscape patchiness is an important metric in ecology.

Evidence and therapeutic implications of biomechanically regulated immunosurveillance in cancer and other diseases

Disease progression is usually accompanied by changes in the biochemical composition of cells and tissues and their biophysical properties. For instance, hallmarks of cancer include the stiffening of tissues caused by extracellular matrix remodelling and the softening of individual cancer cells. In this context, accumulating evidence has shown that immune cells sense and respond to mechanical signals from the environment. However, the mechanisms regulating these mechanical aspects of immune surveillance remain partially understood. The growing appreciation for the 'mechano-immunology' field has urged researchers to investigate how immune cells sense and respond to mechanical cues in various disease settings, paving the way for the development of novel engineering strategies that aim at mechanically modulating and potentiating immune cells for enhanced immunotherapies. Recent pioneer developments in this direction have laid the foundations for leveraging 'mechanical immunoengineering' strategies to treat various diseases. This Review first outlines the mechanical changes occurring during pathological progression in several diseases, including cancer, fibrosis and infection. We next highlight the mechanosensitive nature of immune cells and how mechanical forces govern the immune responses in different diseases. Finally, we discuss how targeting the biomechanical features of the disease milieu and immune cells is a promising strategy for manipulating therapeutic outcomes.

Omega-3 supplementation changes the physical properties of leukocytes but not erythrocytes in healthy individuals: An exploratory trial

n3-PUFA impact health in several ways, including cardiovascular protection and anti-inflammatory effects, but the underlying mechanisms are not fully understood. In this exploratory study involving 31 healthy subjects, we aimed to investigate the effects of 12 weeks of fish-oil supplementation (1500 mg EPA+DHA/day) on the physical properties of multiple blood cell types. We used deformability cytometry (DC) for all cell types and Laser-assisted Optical Rotational Red Cell Analysis (Lorrca) to assess red blood cell (RBC) deformability. We also investigated the correlation between changes in the physical properties of blood cells and changes in the Omega-3 Index (O3I), defined as the relative content of EPA+DHA in RBCs. Following supplementation, the mean±SD O3I increased from 5.3 %±1.5 % to 8.3 %±1.4 % (p < 0.001). No significant changes in RBC properties were found by both techniques. However, by DC we observed a consistent pattern of physical changes in lymphocytes, neutrophils and monocytes. Among these were significant increases in metrics correlated with the cells' deformability resulting in less stiff cells. The results suggest that leukocytes become softer and have an increased ability to deform under induced short-term physical stress such as hydrodynamic force in the circulation. These changes could impact immune function since softer leukocytes can potentially circulate more easily and could facilitate a more rapid response to systemic inflammation or infection. In conclusion, fish-oil supplementation modulates some physical properties of leukocyte-subfractions, potentially enhancing their biological function. Further studies are warranted to explore the impact of n3-PUFA on blood cell biology, particularly in disease states associated with leukocyte dysregulation.

PIEZO1-mediated mechanosensing governs NK-cell killing efficiency and infiltration in three-dimensional matrices

Natural killer (NK) cells play a vital role in eliminating tumorigenic cells. Efficient locating and killing of target cells in complex three-dimensional (3D) environments are critical for their functions under physiological conditions. However, the role of mechanosensing in regulating NK-cell killing efficiency in physiologically relevant scenarios is poorly understood. Here, we report that the responsiveness of NK cells is regulated by tumor cell stiffness. NK-cell killing efficiency in 3D is impaired against softened tumor cells, whereas it is enhanced against stiffened tumor cells. Notably, the durations required for NK-cell killing and detachment are significantly shortened for stiffened tumor cells. Furthermore, we have identified PIEZO1 as the predominantly expressed mechanosensitive ion channel among the examined candidates in NK cells. Perturbation of PIEZO1 abolishes stiffness-dependent NK-cell responsiveness, significantly impairs the killing efficiency of NK cells in 3D, and substantially reduces NK-cell infiltration into 3D collagen matrices. Conversely, PIEZO1 activation enhances NK killing efficiency as well as infiltration. In conclusion, our findings demonstrate that PIEZO1-mediated mechanosensing is crucial for NK killing functions, highlighting the role of mechanosensing in NK-cell killing efficiency under 3D physiological conditions and the influence of environmental physical cues on NK-cell functions.

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.

Classification of fetal and adult red blood cells based on hydrodynamic deformation and deep video recognition

Flow based deformation cytometry has shown potential for cell classification. We demonstrate the principle with an injection moulded microfluidic chip from which we capture videos of adult and fetal red blood cells, as they are being deformed in a microfluidic chip. Using a deep neural network - SlowFast - that takes the temporal behavior into account, we are able to discriminate between the cells with high accuracy. The accuracy was larger for adult blood cells than for fetal blood cells. However, no significant difference was observed between donors of the two types.

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.

Scaling up stem cell production: harnessing the potential of microfluidic devices

Stem cells are specialised cells characterised by their unique ability to both self-renew and transform into a wide array of specialised cell types. The widespread interest in stem cells for regenerative medicine and cultivated meat has led to a significant demand for these cells in both research and practical applications. Despite the growing need for stem cell manufacturing, the industry faces significant obstacles, including high costs for equipment and maintenance, complicated operation, and low product quality and yield. Microfluidic technology presents a promising solution to the abovementioned challenges. As an innovative approach for manipulating liquids and cells within microchannels, microfluidics offers a plethora of advantages at an industrial scale. These benefits encompass low setup costs, ease of operation and multiplexing, minimal energy consumption, and the added advantage of being labour-free. This review presents a thorough examination of the prominent microfluidic technologies employed in stem cell research and explores their promising applications in the burgeoning stem cell industry. It thoroughly examines how microfluidics can enhance cell harvesting from tissue samples, facilitate mixing and cryopreservation, streamline microcarrier production, and efficiently conduct cell separation, purification, washing, and final cell formulation post-culture.

High-throughput quantification of red blood cell deformability and oxygen saturation to probe mechanisms of sickle cell disease

The complex, systemic pathology of sickle cell disease is driven by multiple mechanisms including red blood cells (RBCs) stiffened by polymerized fibers of deoxygenated sickle hemoglobin. A critical step toward understanding the pathologic role of polymer-containing RBCs is quantifying the biophysical changes in these cells in physiologically relevant oxygen environments. We have developed a microfluidic platform capable of simultaneously measuring single RBC deformability and oxygen saturation under controlled oxygen and shear stress. We found that RBCs with detectable amounts of polymer have decreased oxygen affinity and decreased deformability. Surprisingly, the deformability of the polymer-containing cells is oxygen-independent, while the fraction of these cells increases as oxygen decreases. We also find that some fraction of these cells is present at most physiologic oxygen tensions, suggesting a role for these cells in the systemic pathologies. Additionally, the ability to measure these pathological cells should provide clearer targets for evaluating therapies.

Distinguishing cells using electro-acoustic spinning

Many diseases, including cancer and covid, result in altered mechanical and electric properties of the affected cells. These changes were proposed as disease markers. Current methods to characterize such changes either provide very limited information on many cells or have extremely low throughput. We introduce electro-acoustic spinning (EAS). Cells were found to spin in combined non-rotating AC electric and acoustic fields. The rotation velocity in EAS depends critically on a cell's electrical and mechanical properties. In contrast to existing methods, the rotation is uniform in the field of view and hundreds of cells can be characterized simultaneously. We demonstrate that EAS can distinguish cells with only minor differences in electric and mechanical properties, including differences in age or the number of passages.

YAP localization mediates mechanical adaptation of human cancer cells during extravasation in vivo

Biophysical profiling of primary tumors has revealed that individual tumor cells fall along a highly heterogeneous continuum of mechanical phenotypes. One idea is that a subset of tumor cells is "softer" to facilitate detachment and escape from the primary site, a step required to initiate metastasis. However, it has also been postulated that cells must be able to deform and generate sufficient force to exit into distant sites. Here, we aimed to dissect the mechanical changes that occur during extravasation and organ colonization. Using multiplexed methods of intravital microscopy and optical tweezer based active microrheology, we obtained longitudinal images and mechanical profiles of cells during organ colonization in vivo. We determined that cells were softer, more liquid like upon exit of the vasculature but stiffened and became more solid like once in the new organ microenvironment. We also determined that a YAP mediated mechanogenotype influenced the global dissemination in our in vivo and in vitro models and that reducing mechanical heterogeneity could reduce extravasation. Moreover, our high throughput analysis of mechanical phenotypes of patient samples revealed that this mechanics was in part regulated by the external hydrodynamic forces that the cancer cells experienced within capillary mimetics. Our findings indicate that disseminated cancer cells can keep mutating with a continuum landscape of mechano-phenotypes, governed by the YAP-mediated mechanosensing of hydrodynamic flow.

IL-3 receptor signalling suppresses chronic intestinal inflammation by controlling mechanobiology and tissue egress of regulatory T cells

IL-3 has been reported to be involved in various inflammatory disorders, but its role in inflammatory bowel disease (IBD) has not been addressed so far. Here, we determined IL-3 expression in samples from patients with IBD and studied the impact of Il3 or Il3r deficiency on T cell-dependent experimental colitis. We explored the mechanical, cytoskeletal and migratory properties of Il3r -/- and Il3r +/+ T cells using real-time deformability cytometry, atomic force microscopy, scanning electron microscopy, fluorescence recovery after photobleaching and in vitro and in vivo cell trafficking assays. We observed that, in patients with IBD, the levels of IL-3 in the inflamed mucosa were increased. In vivo, experimental chronic colitis on T cell transfer was exacerbated in the absence of Il-3 or Il-3r signalling. This was attributable to Il-3r signalling-induced changes in kinase phosphorylation and actin cytoskeleton structure, resulting in increased mechanical deformability and enhanced egress of Tregs from the inflamed colon mucosa. Similarly, IL-3 controlled mechanobiology in human Tregs and was associated with increased mucosal Treg abundance in patients with IBD. Collectively, our data reveal that IL-3 signaling exerts an important regulatory role at the interface of biophysical and migratory T cell features in intestinal inflammation and suggest that this might be an interesting target for future intervention.

Rapid single-cell physical phenotyping of mechanically dissociated tissue biopsies

During surgery, rapid and accurate histopathological diagnosis is essential for clinical decision making. Yet the prevalent method of intra-operative consultation pathology is intensive in time, labour and costs, and requires the expertise of trained pathologists. Here we show that biopsy samples can be analysed within 30 min by sequentially assessing the physical phenotypes of singularized suspended cells dissociated from the tissues. The diagnostic method combines the enzyme-free mechanical dissociation of tissues, real-time deformability cytometry at rates of 100-1,000 cells s-1 and data analysis by unsupervised dimensionality reduction and logistic regression. Physical phenotype parameters extracted from brightfield images of single cells distinguished cell subpopulations in various tissues, enhancing or even substituting measurements of molecular markers. We used the method to quantify the degree of colon inflammation and to accurately discriminate healthy and tumorous tissue in biopsy samples of mouse and human colons. This fast and label-free approach may aid the intra-operative detection of pathological changes in solid biopsies.

Impedance-Based Multimodal Electrical-Mechanical Intrinsic Flow Cytometry

Reflecting various physiological states and phenotypes of single cells, intrinsic biophysical characteristics (e.g., mechanical and electrical properties) are reliable and important, label-free biomarkers for characterizing single cells. However, single-modal mechanical or electrical properties alone are not specific enough to characterize single cells accurately, and it has been long and challenging to couple the conventionally image-based mechanical characterization and impedance-based electrical characterization. In this work, the spatial-temporal characteristics of impedance sensing signal are leveraged, and an impedance-based multimodal electrical-mechanical flow cytometry framework for on-the-fly high-dimensional intrinsic measurement is proposed, that is, Young's modulus E, fluidity β, radius r, cytoplasm conductivity σi , and specific membrane capacitance Csm , of single cells. With multimodal high-dimensional characterization, the electrical-mechanical flow cytometry can better reveal the difference in cell types, demonstrated by the experimental results with three types of cancer cells (HepG2, MCF-7, and MDA-MB-468) with 93.4% classification accuracy and pharmacological perturbations of the cytoskeleton (fixed and Cytochalasin B treated cells) with 95.1% classification accuracy. It is envisioned that multimodal electrical-mechanical flow cytometry provides a new perspective for accurate label-free single-cell intrinsic characterization.

Molecular mechanocytometry using tension-activated cell tagging

Flow cytometry is used routinely to measure single-cell gene expression by staining cells with fluorescent antibodies and nucleic acids. Here, we present tension-activated cell tagging (TaCT) to label cells fluorescently based on the magnitude of molecular force transmitted through cell adhesion receptors. As a proof-of-concept, we analyzed fibroblasts and mouse platelets after TaCT using conventional flow cytometry.

Engineering DNA-based cytoskeletons for synthetic cells

The development and bottom-up assembly of synthetic cells with a functional cytoskeleton sets a major milestone to understand cell mechanics and to develop man-made machines on the nano- and microscale. However, natural cytoskeletal components can be difficult to purify, deliberately engineer and reconstitute within synthetic cells which therefore limits the realization of multifaceted functions of modern cytoskeletons in synthetic cells. Here, we review recent progress in the development of synthetic cytoskeletons made from deoxyribonucleic acid (DNA) as a complementary strategy. In particular, we explore the capabilities and limitations of DNA cytoskeletons to mimic functions of natural cystoskeletons like reversible assembly, cargo transport, force generation, mechanical support and guided polymerization. With recent examples, we showcase the power of rationally designed DNA cytoskeletons for bottom-up assembled synthetic cells as fully engineerable entities. Nevertheless, the realization of dynamic instability, self-replication and genetic encoding as well as contractile force generating motors remains a fruitful challenge for the complete integration of multifunctional DNA-based cytoskeletons into synthetic cells.

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.

Unknown cell class distinction via neural network based scattering snapshot recognition

Neural network-based image classification is widely used in life science applications. However, it is essential to extrapolate a correct classification method for unknown images, where no prior knowledge can be utilised. Under a closed set assumption, unknown images will be inevitably misclassified, but this can be genuinely overcome choosing an open-set classification approach, which first generates an in-distribution of identified images to successively discriminate out-of-distribution images. The testing of such image classification for single cell applications in life science scenarios has yet to be done but could broaden our expertise in quantifying the influence of prediction uncertainty in deep learning. In this framework, we implemented the open-set concept on scattering snapshots of living cells to distinguish between unknown and known cell classes, targeting four different known monoblast cell classes and a single tumoral unknown monoblast cell line. We also investigated the influence on experimental sample errors and optimised neural network hyperparameters to obtain a high unknown cell class detection accuracy. We discovered that our open-set approach exhibits robustness against sample noise, a crucial aspect for its application in life science. Moreover, the presented open-set based neural network reveals measurement uncertainty out of the cell prediction, which can be applied to a wide range of single cell classifications.

The chemorepellent, SLIT2, bolsters innate immunity against Staphylococcus aureus

Neutrophils are essential for host defense against Staphylococcus aureus (S. aureus). The neuro-repellent, SLIT2, potently inhibits neutrophil chemotaxis, and might, therefore, be expected to impair antibacterial responses. We report here that, unexpectedly, neutrophils exposed to the N-terminal SLIT2 (N-SLIT2) fragment kill extracellular S. aureus more efficiently. N-SLIT2 amplifies reactive oxygen species production in response to the bacteria by activating p38 mitogen-activated protein kinase that in turn phosphorylates NCF1, an essential subunit of the NADPH oxidase complex. N-SLIT2 also enhances the exocytosis of neutrophil secondary granules. In a murine model of S. aureus skin and soft tissue infection (SSTI), local SLIT2 levels fall initially but increase subsequently, peaking at 3 days after infection. Of note, the neutralization of endogenous SLIT2 worsens SSTI. Temporal fluctuations in local SLIT2 levels may promote neutrophil recruitment and retention at the infection site and hasten bacterial clearance by augmenting neutrophil oxidative burst and degranulation. Collectively, these actions of SLIT2 coordinate innate immune responses to limit susceptibility to S. aureus.

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.

Using Adhesive Micropatterns and AFM to Assess Cancer Cell Morphology and Mechanics

The mechanical properties of living cells reflect their physiological and pathological state. In particular, cancer cells undergo cytoskeletal modifications that typically make them softer than healthy cells, a property that could be used as a diagnostic tool. However, this is challenging because cells are complex structures displaying a broad range of morphologies when cultured in standard 2D culture dishes. Here, we use adhesive micropatterns to impose the cell geometry and thus standardize the mechanics and morphologies of cancer cells, which we measure by atomic force microscopy (AFM), mechanical nanomapping, and membrane nanotube pulling. We show that micropatterning cancer cells leads to distinct morphological and mechanical changes for different cell lines. Micropatterns did not systematically lower the variability in cell elastic modulus distribution. These effects emerge from a variable cell spreading rate associated with differences in the organization of the cytoskeleton, thus providing detailed insights into the structure-mechanics relationship of cancer cells cultured on micropatterns. Combining AFM with micropatterns reveals new mechanical and morphological observables applicable to cancer cells and possibly other cell types.

EMT induces characteristic changes of Rho GTPases and downstream effectors with a mitosis-specific twist

Epithelial-mesenchymal transition (EMT) is a key cellular transformation for many physiological and pathological processes ranging from cancer over wound healing to embryogenesis. Changes in cell migration, cell morphology and cellular contractility were identified as hallmarks of EMT. These cellular properties are known to be tightly regulated by the actin cytoskeleton. EMT-induced changes of actin-cytoskeletal regulation were demonstrated by previous reports of changes of actin cortex mechanics in conjunction with modifications of cortex-associated f-actin and myosin. However, at the current state, the changes of upstream actomyosin signaling that lead to corresponding mechanical and compositional changes of the cortex are not well understood. In this work, we show in breast epithelial cancer cells MCF-7 that EMT results in characteristic changes of the cortical association of Rho-GTPases Rac1, RhoA and RhoC and downstream actin regulators cofilin, mDia1 and Arp2/3. In the light of our findings, we propose that EMT-induced changes in cortical mechanics rely on two hitherto unappreciated signaling paths-i) an interaction between Rac1 and RhoC and ii) an inhibitory effect of Arp2/3 activity on cortical association of myosin II.

Expanding hematopoietic stem cell ex vivo: recent advances and technical considerations

Hematopoietic stem cells (HSCs) are the most primitive cell type in the hematopoietic hierarchy, which are responsible for sustaining the lifelong production of mature blood and immune cells. Due to their superior long-term regenerative capacity, HSC therapies such as stem cell transplantation have been used in a broad range of hematologic disorders. However, the rarity of this population in vivo considerably limits its clinical applications and large-scale analyses such as screening and safety studies. Therefore, ex vivo culture methods that allow long-term expansion and maintenance of functional HSCs are instrumental in overcoming the difficulties in studying HSC biology and improving HSC therapies. In this perspective, we discuss recent advances and technical considerations for three ex vivo HSC expansion methods including 1) polyvinyl alcohol-based HSC expansion, 2) mesenchymal stromal cell-HSC co-culture, and 3) two-/three-dimensional hydrogel HSC culture. This review summarizes the presentations and discussions from the 2022 International Society for Experimental Hematology (ISEH) Annual Meeting New Investigator Technology Session.

Microfluidic Microcirculation Mimetic for Exploring Biophysical Mechanisms of Chemotherapy-Induced Metastasis

There is rapidly emerging evidence from pre-clinical studies, patient samples and patient subpopulations that certain chemotherapeutics inadvertently produce prometastatic effects. Prior to this, we showed that doxorubicin and daunorubicin stiffen cells before causing cell death, predisposing the cells to clogging and extravasation, the latter being a step in metastasis. Here, we investigate which other anti-cancer drugs might have similar prometastatic effects by altering the biophysical properties of cells. We treated myelogenous (K562) leukemic cancer cells with the drugs nocodazole and hydroxyurea and then measured their mechanical properties using a microfluidic microcirculation mimetic (MMM) device, which mimics aspects of blood circulation and enables the measurement of cell mechanical properties via transit times through the device. We also quantified the morphological properties of cells to explore biophysical mechanisms underlying the MMM results. Results from MMM measurements show that nocodazole- and hydroxyurea-treated K562 cells exhibit significantly altered transit times. Nocodazole caused a significant (p < 0.01) increase in transit times, implying a stiffening of cells. This work shows the feasibility of using an MMM to explore possible biophysical mechanisms that might contribute to chemotherapy-induced metastasis. Our work also suggests cell mechanics as a therapeutic target for much needed antimetastatic strategies in general.

Human T cells loaded with superparamagnetic iron oxide nanoparticles retain antigen-specific TCR functionality

Background

Immunotherapy of cancer is an emerging field with the potential to improve long-term survival. Thus far, adoptive transfer of tumor-specific T cells represents an effective treatment option for tumors of the hematological system such as lymphoma, leukemia or myeloma. However, in solid tumors, treatment efficacy is low owing to the immunosuppressive microenvironment, on-target/off-tumor toxicity, limited extravasation out of the blood vessel, or ineffective trafficking of T cells into the tumor region. Superparamagnetic iron oxide nanoparticles (SPIONs) can make cells magnetically controllable for the site-specific enrichment.

Methods

In this study, we investigated the influence of SPION-loading on primary human T cells for the magnetically targeted adoptive T cell therapy. For this, we analyzed cellular mechanics and the T cell response after stimulation via an exogenous T cell receptor (TCR) specific for the melanoma antigen MelanA or the endogenous TCR specific for the cytomegalovirus antigen pp65 and compared them to T cells that had not received SPIONs.

Results

SPION-loading of human T cells showed no influence on cellular mechanics, therefore retaining their ability to deform to external pressure. Additionally, SPION-loading did not impair the T cell proliferation, expression of activation markers, cytokine secretion, and tumor cell killing after antigen-specific activation mediated by the TCR.

Conclusion

In summary, we demonstrated that SPION-loading of T cells did not affect cellular mechanics or the functionality of the endogenous or an exogenous TCR, which allows future approaches using SPIONs for the magnetically enrichment of T cells in solid tumors.

Micropipette-assisted atomic force microscopy for single-cell 3D manipulations and nanomechanical measurements

Mechanical cues play a crucial role in regulating physiological and pathological processes, and atomic force microscopy (AFM) has become an important and standard tool for measuring the mechanical properties of single cells. In particular, providing a capability to manipulate cells in a three-dimensional (3D) space benefits enhancing the applications of AFM measurements in cell biology. Here, we present the complementary integration of AFM and micropipette micromanipulation, which allows precise 3D manipulations and nanomechanical measurements of single living cells. A micropipette micromanipulation system under the guidance of optical microscopy was established to isolate single living cells, and polydimethylsiloxane (PDMS) micropillar substrates were used to physically immobilize the isolated living cells for downstream AFM detection. The viscoelastic properties (Young's modulus, relaxation time, viscosity) of cells were quantitatively measured by AFM-based indentation assay. The effectiveness of micropipette-assisted AFM in single-cell analysis was confirmed on both living animal suspended cells and living animal adherent cells, showing dramatic changes in cell mechanics in different states and revealing the dynamics of single cells grown on micropillar arrays. The study demonstrates the great potential of a micropipette to aid AFM in single-cell manipulations for better accessing the mechanical cues involved in cellular processes, which will allow additional studies of single-cell mechanics and will benefit the field of mechanobiology.