Multiparameter mechanical and morphometric screening of cells

Cellular host response sepsis test for risk stratification of patients in the emergency department: A pooled analysis

OBJECTIVES

Sepsis is one of the most common, costly, and misdiagnosed conditions in U.S. emergency departments (EDs). ED providers often treat on nonspecific signs, subjective suspicion, or presumption of infection, resulting in over- and undertreatment. An increased understanding of host response has opened a new direction for sepsis diagnostics. The IntelliSep test is a U.S. Food and Drug Administration-cleared cellular host response diagnostic that could help distinguish sepsis in ED settings. Our objective was to evaluate the potential of the cellular host response test to expedite appropriate care for patients who present with signs of infection.

METHODS

We performed a pooled analysis of five adult (≥18 years) cohorts enrolled at seven geographically diverse U.S. sites in separate studies. Structured blinded adjudication was used to classify presence or absence of sepsis, and only patients with high confidence in the adjudicated label were included (n = 1002), defined as patients for whom there was consensus in the determination of sepsis per the Sepsis-3 and severe sepsis per the Sepsis-2 definitions between both the independent adjudication panel and the site-level physician.

RESULTS

Among patients with signs or suspicion of infection, the test achieved similar or better performance compared to other indicators in identifying patients at high risk for sepsis (specificity > 83%) and significantly superior performance in identifying those at low risk (sensitivity > 92%; 0% sepsis-associated mortality). The test also stratified severity of illness, as shown by 30-day in-hospital mortality (p < 0.001), hospital length of stay (p < 0.01), and use of hospital resources (p < 0.001).

CONCLUSIONS

Our data suggest that the cellular host response test provides clinically actionable results for patients at both high and low risk for sepsis and provides a rapid, objective means for risk stratification of patients with signs of infection. If integrated into standard of care, the test may help improve outcomes and reduce unnecessary antibiotic use.

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.

A deformability-based biochip for precise label-free stratification of metastatic subtypes using deep learning

Cellular deformability is a promising biomarker for evaluating the physiological state of cells in medical applications. Microfluidics has emerged as a powerful technique for measuring cellular deformability. However, existing microfluidic-based assays for measuring cellular deformability rely heavily on image analysis, which can limit their scalability for high-throughput applications. Here, we develop a parallel constriction-based microfluidic flow cytometry device and an integrated computational framework (ATMQcD). The ATMQcD framework includes automatic training set generation, multiple object tracking, segmentation, and cellular deformability quantification. The system was validated using cancer cell lines of varying metastatic potential, achieving a classification accuracy of 92.4% for invasiveness assessment and stratifying cancer cells before and after hypoxia treatment. The ATMQcD system also demonstrated excellent performance in distinguishing cancer cells from leukocytes (accuracy = 89.5%). We developed a mechanical model based on power-law rheology to quantify stiffness, which was fitted with measured data directly. The model evaluated metastatic potentials for multiple cancer types and mixed cell populations, even under real-world clinical conditions. Our study presents a highly robust and transferable computational framework for multiobject tracking and deformation measurement tasks in microfluidics. We believe that this platform has the potential to pave the way for high-throughput analysis in clinical applications, providing a powerful tool for evaluating cellular deformability and assessing the physiological state of cells.

Label-free microfluidic cell sorting and detection for rapid blood analysis

Blood tests are considered as standard clinical procedures to screen for markers of diseases and health conditions. However, the complex cellular background (>99.9% RBCs) and biomolecular composition often pose significant technical challenges for accurate blood analysis. An emerging approach for point-of-care blood diagnostics is utilizing "label-free" microfluidic technologies that rely on intrinsic cell properties for blood fractionation and disease detection without any antibody binding. A growing body of clinical evidence has also reported that cellular dysfunction and their biophysical phenotypes are complementary to standard hematoanalyzer analysis (complete blood count) and can provide a more comprehensive health profiling. In this review, we will summarize recent advances in microfluidic label-free separation of different blood cell components including circulating tumor cells, leukocytes, platelets and nanoscale extracellular vesicles. Label-free single cell analysis of intrinsic cell morphology, spectrochemical properties, dielectric parameters and biophysical characteristics as novel blood-based biomarkers will also be presented. Next, we will highlight research efforts that combine label-free microfluidics with machine learning approaches to enhance detection sensitivity and specificity in clinical studies, as well as innovative microfluidic solutions which are capable of fully integrated and label-free blood cell sorting and analysis. Lastly, we will envisage the current challenges and future outlook of label-free microfluidics platforms for high throughput multi-dimensional blood cell analysis to identify non-traditional circulating biomarkers for clinical diagnostics.

A Progress Report and Roadmap for Microphysiological Systems and Organ-On-A-Chip Technologies to Be More Predictive Models in Human (Knee) Osteoarthritis

Osteoarthritis (OA), a chronic debilitating joint disease affecting hundreds of million people globally, is associated with significant pain and socioeconomic costs. Current treatment modalities are palliative and unable to stop the progressive degeneration of articular cartilage in OA. Scientific attention has shifted from the historical view of OA as a wear-and-tear cartilage disorder to its recognition as a whole-joint disease, highlighting the contribution of other knee joint tissues in OA pathogenesis. Despite much progress in the field of microfluidic systems/organs-on-a-chip in other research fields, current in vitro models in use do not yet accurately reflect the complexity of the OA pathophenotype. In this review, we provide: 1) a detailed overview of the most significant recent developments in the field of microsystems approaches for OA modeling, and 2) an OA-pathophysiology-based bioengineering roadmap for the requirements of the next generation of more predictive and authentic microscale systems fit for the purpose of not only disease modeling but also of drug screening to potentially allow OA animal model reduction and replacement in the near future.

Microfluidic Impedance-Deformability Cytometry for Label-Free Single Neutrophil Mechanophenotyping

The intrinsic biophysical states of neutrophils are associated with immune dysfunctions in diseases. While advanced image-based biophysical flow cytometers can probe cell deformability at high throughput, it is nontrivial to couple different sensing modalities (e.g., electrical) to measure other critical cell attributes including cell viability and membrane integrity. Herein, an "optics-free" impedance-deformability cytometer for multiparametric single cell mechanophenotyping is reported. The microfluidic platform integrates hydrodynamic cell pinching, and multifrequency impedance quantification of cell size, deformability, and membrane impedance (indicative of cell viability and activation). A newly-defined "electrical deformability index" is validated by numerical simulations, and shows strong correlations with the optical cell deformability index of HL-60 experimentally. Human neutrophils treated with various biochemical stimul are further profiled, and distinct differences in multimodal impedance signatures and UMAP analysis are observed. Overall, the integrated cytometer enables label-free cell profiling at throughput of >1000 cells min^-1 without any antibodies labeling to facilitate clinical diagnostics.

A survey of physical methods for studying nuclear mechanics and mechanobiology

It is increasingly appreciated that the cell nucleus is not only a home for DNA but also a complex material that resists physical deformations and dynamically responds to external mechanical cues. The molecules that confer mechanical properties to nuclei certainly contribute to laminopathies and possibly contribute to cellular mechanotransduction and physical processes in cancer such as metastasis. Studying nuclear mechanics and the downstream biochemical consequences or their modulation requires a suite of complex assays for applying, measuring, and visualizing mechanical forces across diverse length, time, and force scales. Here, we review the current methods in nuclear mechanics and mechanobiology, placing specific emphasis on each of their unique advantages and limitations. Furthermore, we explore important considerations in selecting a new methodology as are demonstrated by recent examples from the literature. We conclude by providing an outlook on the development of new methods and the judicious use of the current techniques for continued exploration into the role of nuclear mechanobiology.

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.

Development and validation of a cellular host response test as an early diagnostic for sepsis

Sepsis must be diagnosed quickly to avoid morbidity and mortality. However, the clinical manifestations of sepsis are highly variable and emergency department (ED) clinicians often must make rapid, impactful decisions before laboratory results are known. We previously developed a technique that allows the measurement of the biophysical properties of white blood cells as they are stretched through a microfluidic channel. In this study we describe and validate the resultant output as a model and score—the IntelliSep Index (ISI)—that aids in the diagnosis of sepsis in patients with suspected or confirmed infection from a single blood draw performed at the time of ED presentation. By applying this technique to a high acuity cohort with a 23.5% sepsis incidence (n = 307), we defined specific metrics—the aspect ratio and visco-elastic inertial response—that are more sensitive than cell size or cell count in predicting disease severity. The final model was trained and cross-validated on the high acuity cohort, and the performance and generalizability of the model was evaluated on a separate low acuity cohort with a 6.4% sepsis incidence (n = 94) and healthy donors (n = 72). For easier clinical interpretation, the ISI is divided into three interpretation bands of Green, Yellow, and Red that correspond to increasing disease severity. The ISI agreed with the diagnosis established by retrospective physician adjudication, and accurately identified subjects with severe illness as measured by SOFA, APACHE-II, hospital-free days, and intensive care unit admission. Measured using routinely collected blood samples, with a short run-time and no requirement for patient or laboratory information, the ISI is well suited to aid ED clinicians in rapidly diagnosing sepsis.

Laser tweezers as a biophotonic tool to investigate the efficacy of living sickle red blood cells in response to optical deformation

A laser tweezer technique based on single and/or dual-laser beams is proposed as a biophotonic tool to trap single cells and investigate their biophysical and biomechanical characteristics. Optical deformability and changes in size and cellular morphology of living and nonliving cells can be measured using the proposed technique. Representative results of red blood cell (RBC) optical deformability of 20 homozygous patients with sickle cell disease, including follow-up patients after treating with hydroxyurea (HU) for at least 3 months and 20 healthy control groups, are presented and compared. Shape recovery of deformed RBCs and relaxation time are recorded for each RBC. Results showed that healthy blood and patients treated with HU demonstrate significantly higher optical deformability and degree of optical elongation with morphological change of RBCs than untreated patients. Moreover, the healthy control group and patients treated with HU exhibited faster relaxation time for RBCs than untreated patients. A trapping power that reaches 180 mW caused no observable photo-damage at a wavelength 1064 nm.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s12551-021-00790-0.

Microfluidic label-free bioprocessing of human reticulocytes from erythroid culture

In vitro erythroid cultures from human hematopoietic stem cells produce immature red blood cells (RBCs) called reticulocytes, which are important for RBCs production, and are widely used in scientific studies of malaria pathology, hematological diseases and protein translation. However, in vitro reticulocyte cultures contain expelled cell nuclei and erythroblasts as undesirable by-products and current purification methods such as density gradient centrifugation and fluorescence-activated cell sorting (FACS) are not optimal for integrated bioprocessing and downstream therapeutic applications. Developments in Dean flow fractionation (DFF) and deterministic lateral displacement (DLD) microfluidic sorting methods are ideal alternatives due to label-free size sorting, throughput scalability and low manufacturing cost. DFF sorting of reticulocytes from whole erythroid culture showed a 2.4-fold increase in cell recovery compared to FACS albeit with a lower purity; DLD sorting showed comparable cell recovery and purity with FACS using an inverse-L pillar structure to emphasize size and deformability sorting of reticulocytes. The viability and functional assurance of purified reticulocytes showed conserved cell deformability and supported the propagation of malaria parasites. Collectively, our study on label-free RBCs isolation represents a significant technical advancement towards developing in vitro generated viable human RBCs, opening opportunities for close-loop cell manufacturing, downstream therapeutic and research purposes.

Deformation of leukaemia cell lines in hyperbolic microchannels: investigating the role of shear and extensional components

The mechanical properties of cells are of enormous interest in a diverse range of physio and pathological situations of clinical relevance. Unsurprisingly, a variety of microfluidic platforms have been developed in recent years to study the deformability of cells, most commonly employing pure shear or extensional flows, with and without direct contact of the cells with channel walls. Herein, we investigate the effects of shear and extensional flow components on fluid-induced cell deformation by means of three microchannel geometries. In the case of hyperbolic microchannels, cell deformation takes place in a flow with constant extensional rate, under non-zero shear conditions. A sudden expansion at the microchannel terminus allows one to evaluate shape recovery subsequent to deformation. Comparison with other microchannel shapes, that induce either pure shear (straight channel) or pure extensional (cross channel) flows, reveals different deformation modes. Such an analysis is used to confirm the softening and stiffening effects of common treatments, such as cytochalasin D and formalin on cell deformability. In addition to an experimental analysis of leukaemia cell deformability, computational fluid dynamic simulations are used to deconvolve the role of the aforementioned flow components in the cell deformation dynamics. In general terms, the current study can be used as a guide for extracting deformation/recovery dynamics of leukaemia cell lines when exposed to various fluid dynamic conditions.

Elongation Index as a Sensitive Measure of Cell Deformation in High-Throughput Microfluidic Systems

One of the promising approaches for high-throughput screening of cell mechanotype is microfluidic deformability cytometry (mDC), in which the apparent deformation index (DI) of the cells stretched by extensional flow at the stagnation point of a cross-slot microchannel is measured. The DI is subject to substantial measurement errors due to cell offset from the flow centerline and velocity fluctuations in inlet channels, leading to artificial widening of DI versus cell size plots. Here, we simulated an mDC experiment using a custom computational algorithm for viscoelastic cell migration. Cell motion and deformation in a cross-slot channel was modeled for fixed or randomized values of cellular mechanical properties (diameter, shear elasticity, cortical tension) and initial cell placement, with or without sinusoidal fluctuations between the inlet velocities. Our numerical simulation indicates that mDC loses sensitivity to changes in shear elasticity when the offset distance exceeds 5 μm, and just 1% velocity fluctuation causes an 11.7% drop in the DI. The obtained relationships between the cell diameter, shear elasticity, and offset distance were used to establish a new measure of cell deformation, referred to as the "elongation index" (EI). In the randomized study, the EI scatter plots were visibly separated for the low- and high-elasticity populations of cells, with a mean of 300 and 3500 Pa, whereas the standard DI output was unable to distinguish between these two groups of cells. The successful suppression of the offset artifacts with a narrower data distribution was shown for the EI output of MCF-7 cells.

Microfluidic-Based Approaches in Targeted Cell/Particle Separation Based on Physical Properties: Fundamentals and Applications

Cell separation is a key step in many biomedical research areas including biotechnology, cancer research, regenerative medicine, and drug discovery. While conventional cell sorting approaches have led to high-efficiency sorting by exploiting the cell's specific properties, microfluidics has shown great promise in cell separation by exploiting different physical principles and using different properties of the cells. In particular, label-free cell separation techniques are highly recommended to minimize cell damage and avoid costly and labor-intensive steps of labeling molecular signatures of cells. In general, microfluidic-based cell sorting approaches can separate cells using "intrinsic" (e.g., fluid dynamic forces) versus "extrinsic" external forces (e.g., magnetic, electric field, etc.) and by using different properties of cells including size, density, deformability, shape, as well as electrical, magnetic, and compressibility/acoustic properties to select target cells from a heterogeneous cell population. In this work, principles and applications of the most commonly used label-free microfluidic-based cell separation methods are described. In particular, applications of microfluidic methods for the separation of circulating tumor cells, blood cells, immune cells, stem cells, and other biological cells are summarized. Computational approaches complementing such microfluidic methods are also explained. Finally, challenges and perspectives to further develop microfluidic-based cell separation methods are discussed.

Effect of Nuclear Stiffness on Cell Mechanics and Migration of Human Breast Cancer Cells

The migration and invasion of cancer cells through 3D confined extracellular matrices is coupled to cell mechanics and the mechanics of the extracellular matrix. Cell mechanics is mainly determined by both the mechanics of the largest organelle in the cell, the nucleus, and the cytoskeletal architecture of the cell. Hence, cytoskeletal and nuclear mechanics are the major contributors to cell mechanics. Among other factors, steric hindrances of the extracellular matrix confinement are supposed to affect nuclear mechanics and thus also influence cell mechanics. Therefore, we propose that the percentage of invasive cells and their invasion depths into loose and dense 3D extracellular matrices is regulated by both nuclear and cytoskeletal mechanics. In order to investigate the effect of both nuclear and cytoskeletal mechanics on the overall cell mechanics, we firstly altered nuclear mechanics by the chromatin de-condensing reagent Trichostatin A (TSA) and secondly altered cytoskeletal mechanics by addition of actin polymerization inhibitor Latrunculin A and the myosin inhibitor Blebbistatin. In fact, we found that TSA-treated MDA-MB-231 human breast cancer cells increased their invasion depth in dense 3D extracellular matrices, whereas the invasion depths in loose matrices were decreased. Similarly, the invasion depths of TSA-treated MCF-7 human breast cancer cells in dense matrices were significantly increased compared to loose matrices, where the invasion depths were decreased. These results are also valid in the presence of a matrix-metalloproteinase inhibitor GM6001. Using atomic force microscopy (AFM), we found that the nuclear stiffnesses of both MDA-MB-231 and MCF-7 breast cancer cells were pronouncedly higher than their cytoskeletal stiffness, whereas the stiffness of the nucleus of human mammary epithelial cells was decreased compared to their cytoskeleton. TSA treatment reduced cytoskeletal and nuclear stiffness of MCF-7 cells, as expected. However, a softening of the nucleus by TSA treatment may induce a stiffening of the cytoskeleton of MDA-MB-231 cells and subsequently an apparent stiffening of the nucleus. Inhibiting actin polymerization using Latrunculin A revealed a softer nucleus of MDA-MB-231 cells under TSA treatment. This indicates that the actin-dependent cytoskeletal stiffness seems to be influenced by the TSA-induced nuclear stiffness changes. Finally, the combined treatment with TSA and Latrunculin A further justifies the hypothesis of apparent nuclear stiffening, indicating that cytoskeletal mechanics seem to be regulated by nuclear mechanics.

Physical Biomarkers of Disease Progression: On-Chip Monitoring of Changes in Mechanobiology of Colorectal Cancer Cells

Disease can induce changes to subcellular components, altering cell phenotype and leading to measurable bulk-material mechanical properties. The mechanical phenotyping of single cells therefore offers many potential diagnostic applications. Cells are viscoelastic and their response to an applied stress is highly dependent on the magnitude and timescale of the actuation. Microfluidics can be used to measure cell deformability over a wide range of flow conditions, operating two distinct flow regimes (shear and inertial) which can expose subtle mechanical properties arising from subcellular components. Here, we investigate the deformability of three colorectal cancer (CRC) cell lines using a range of flow conditions. These cell lines offer a model for CRC metastatic progression; SW480 derived from primary adenocarcinoma, HT29 from a more advanced primary tumor and SW620 from lymph-node metastasis. HL60 (leukemia cells) were also studied as a model circulatory cell, offering a non-epithelial comparison. We demonstrate that microfluidic induced flow deformation can be used to robustly detect mechanical changes associated with CRC progression. We also show that single-cell multivariate analysis, utilising deformation and relaxation dynamics, offers potential to distinguish these different cell types. These results point to the benefit of multiparameter determination for improving detection and accuracy of disease stage diagnosis.

An optofluidic "tweeze-and-drag" cell stretcher in a microfluidic channel

The mechanical properties of biological cells are utilized as an inherent, label-free biomarker to indicate physiological and pathological changes of cells. Although various optical and microfluidic techniques have been developed for cell mechanical characterization, there is still a strong demand for non-contact and continuous methods. Here, by combining optical and microfluidic techniques in a single desktop platform, we demonstrate an optofluidic cell stretcher based on a "tweeze-and-drag" mechanism using a periodically chopped, tightly focused laser beam as an optical tweezer to trap a cell temporarily and a flow-induced drag force to stretch the cell in a microfluidic channel transverse to the tweezer. Our method leverages the advantages of non-contact optical forces and a microfluidic flow for both cell stretching and continuous cell delivery. We demonstrate the stretcher for mechanical characterization of rabbit red blood cells (RBCs), with a throughput of ∼1 cell per s at a flow rate of 2.5 μl h^-1 at a continuous-wave laser power of ∼25 mW at a wavelength of 1064 nm (chopped at 2 Hz). We estimate the spring constant of RBCs to be ∼14.9 μN m^-1. Using the stretcher, we distinguish healthy RBCs and RBCs treated with glutaraldehyde at concentrations of 5 × 10^-4% to 2.5 × 10^-3%, with a strain-to-concentration sensitivity of ∼-1529. By increasing the optical power to ∼45 mW, we demonstrate cell-stretching under a higher flow rate of 4 μl h^-1, with a higher throughput of ∼1.5 cells per s and a higher sensitivity of ∼-2457. Our technique shows promise for applications in the fields of healthcare monitoring and biomechanical studies.

Mapping inertial migration in the cross section of a microfluidic channel with high-speed imaging

The wide adoption of inertial microfluidics in biomedical research and clinical settings, such as rare cell isolation, has prompted the inquiry of its underlying mechanism. Although tremendous improvement has been made, the mechanism of inertial migration remains to be further elucidated. Contradicting observations are not fully reconciled by the existing theory, and details of the inertial migration within channel cross sections are missing in the literature. In this work, for the first time, we mapped the inertial migration pathways within channel cross section using high-speed imaging at the single-particle level. This is in contrast to the conventional method of particle streak velocimetry (PSV), which provides collective information. We also applied smoothed particle hydrodynamics (SPH) to simulate the transient motion of particles in 3D and obtained cross-sectional migration trajectories that are in agreement with the high-speed imaging results. We found two opposing pathways that explain the contradicting observations in rectangular microchannels, and the force analysis of these pathways revealed two metastable positions near the short walls that can transition into stable positions depending on the flow condition and particle size. These new findings significantly improve our understanding of the inertial migration physics, and enhance our ability to precisely control particle and cell behaviors within microchannels for a broad range of applications.

Mechano-Optical Analysis of Single Cells with Transparent Microcapillary Resonators

The study of biophysical properties of single cells is becoming increasingly relevant in cell biology and pathology. The measurement and tracking of magnitudes such as cell stiffness, morphology, and mass or refractive index have brought otherwise inaccessible knowledge about cell physiology, as well as innovative methods for high-throughput label-free cell classification. In this work, we present hollow resonator devices based on suspended glass microcapillaries for the simultaneous measurement of single-cell buoyant mass and reflectivity with a throughput of 300 cells/minute. In the experimental methodology presented here, both magnitudes are extracted from the devices' response to a single probe, a focused laser beam that enables simultaneous readout of changes in resonance frequency and reflected optical power of the devices as cells flow within them. Through its application to MCF-7 human breast adenocarcinoma cells and MCF-10A nontumorigenic cells, we demonstrate that this mechano-optical technique can successfully discriminate pathological from healthy cells of the same tissue type.

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

Cellular biophysical properties are the effective label-free phenotypes indicative of differences in cell types, states, and functions. However, current biophysical phenotyping methods largely lack the throughput and specificity required in the majority of cell-based assays that involve large-scale single-cell characterization for inquiring the inherently complex heterogeneity in many biological systems. Further confounded by the lack of reported robust reproducibility and quality control, widespread adoption of single-cell biophysical phenotyping in mainstream cytometry remains elusive. To address this challenge, here we present a label-free imaging flow cytometer built upon a recently developed ultrafast quantitative phase imaging (QPI) technique, coined multi-ATOM, that enables label-free single-cell QPI, from which a multitude of subcellularly resolvable biophysical phenotypes can be parametrized, at an experimentally recorded throughput of >10,000 cells/s-a capability that is otherwise inaccessible in current QPI. With the aim to translate multi-ATOM into mainstream cytometry, we report robust system calibration and validation (from image acquisition to phenotyping reproducibility) and thus demonstrate its ability to establish high-dimensional single-cell biophysical phenotypic profiles at ultra-large-scale (>1,000,000 cells). Such a combination of throughput and content offers sufficiently high label-free statistical power to classify multiple human leukemic cell types at high accuracy (~92-97%). This system could substantiate the significance of high-throughput QPI flow cytometry in enabling next frontier in large-scale image-derived single-cell analysis applied in biological discovery and cost-effective clinical diagnostics. © 2019 International Society for Advancement of Cytometry.

Visco-Node-Pore Sensing: A Microfluidic Rheology Platform to Characterize Viscoelastic Properties of Epithelial Cells

Viscoelastic properties of cells provide valuable information regarding biological or clinically relevant cellular characteristics. Here, we introduce a new, electronic-based, microfluidic platform-visco-node-pore sensing (visco-NPS)-which quantifies cellular viscoelastic properties under periodic deformation. We measure the storage (G') and loss (G″) moduli (i.e., elasticity and viscosity, respectively) of cells. By applying a wide range of deformation frequencies, our platform quantifies the frequency dependence of viscoelastic properties. G' and G″ measurements show that the viscoelastic properties of malignant breast epithelial cells (MCF-7) are distinctly different from those of non-malignant breast epithelial cells (MCF-10A). With its sensitivity, visco-NPS can dissect the individual contributions of different cytoskeletal components to whole-cell mechanical properties. Moreover, visco-NPS can quantify the mechanical transitions of cells as they traverse the cell cycle or are initiated into an epithelial-mesenchymal transition. Visco-NPS identifies viscoelastic characteristics of cell populations, providing a biophysical understanding of cellular behavior and a potential for clinical applications.

Technologies for the Directed Evolution of Cell Therapies

The next generation of therapies is moving beyond the use of small molecules and proteins to using whole cells. Compared with the interactions of small-molecule drugs with biomolecules, which can largely be understood through chemistry, cell therapies act in a chemical and physical world and can actively adapt to that world, amplifying complexity but also the potential for truly breakthrough impact. Although there has been success in introducing targeting proteins into cells to achieve a therapeutic effect, for example, chimeric antigen receptor (CAR) T cells, our ability to engineer cells is generally limited to introducing proteins, but not modulating large-scale traits or structures of cellular "machines," which play critical roles in disease. Example traits include the ability to secrete compounds, deform through tissue, adhere to surrounding cells, apply force to phagocytose targets, or move through extracellular matrix. There is an opportunity to increase the efficacy of cell therapies through the use of quantitative automation tools, to analyze, sort, and select rare cells with beneficial traits. Combined with methods of genetic or epigenetic mutagenesis to create diversity, such approaches can enable the directed cellular evolution of new therapeutically optimal populations of cells and uncover genetic underpinnings of these optimal traits.

Cells Under Stress: An Inertial-Shear Microfluidic Determination of Cell Behavior

The deformability of a cell is the direct result of a complex interplay between the different constituent elements at the subcellular level, coupling a wide range of mechanical responses at different length scales. Changes to the structure of these components can also alter cell phenotype, which points to the critical importance of cell mechanoresponse for diagnostic applications. The response to mechanical stress depends strongly on the forces experienced by the cell. Here, we use cell deformability in both shear-dominant and inertia-dominant microfluidic flow regimes to probe different aspects of the cell structure. In the inertial regime, we follow cellular response from (visco-)elastic through plastic deformation to cell structural failure and show a significant drop in cell viability for shear stresses >11.8 kN/m2. Comparatively, a shear-dominant regime requires lower applied stresses to achieve higher cell strains. From this regime, deformation traces as a function of time contain a rich source of information including maximal strain, elastic modulus, and cell relaxation times and thus provide a number of markers for distinguishing cell types and potential disease progression. These results emphasize the benefit of multiple parameter determination for improving detection and will ultimately lead to improved accuracy for diagnosis. We present results for leukemia cells (HL60) as a model circulatory cell as well as for a colorectal cancer cell line, SW480, derived from primary adenocarcinoma (Dukes stage B). SW480 were also treated with the actin-disrupting drug latrunculin A to test the sensitivity of flow regimes to the cytoskeleton. We show that the shear regime is more sensitive to cytoskeletal changes and that large strains in the inertial regime cannot resolve changes to the actin cytoskeleton.

On-chip refractive index cytometry for whole-cell deformability discrimination

On-chip high-throughput phenotyping of single cells has gained a lot of interest recently due to the discrimination capability of label-free biomarkers such as whole-cell deformability and refractive index. Here we present on-chip refractive index cytometry (RIC) for whole-cell deformability at a high measurement rate. We have further exploited a previously published on-chip optical characterization method which enhances cellular discrimination through the refractive index measurement of single cells. The proposed on-chip RIC can simultaneously probe the cellular refractive index, effective volume and whole-cell deformability while reaching a measurement rate up to 5000 cells per second. Additionally, the relative position of the nucleus inside the cell is reflected by the asymmetry of the measured curve. This particular finding is confirmed by our numerical simulation model and emphasized by a modified cytoskeleton HL-60 cells model. Furthermore, the proposed device discriminated HL-60 derived myeloid cells such as neutrophils, basophils and promyelocytes, which are indistinguishable using flow cytometry. To our knowledge, this is the first integrated device to simultaneously characterize the cellular refractive index and whole-cell deformability, yielding enhanced discrimination of large myeloid cell populations.

Developments in label-free microfluidic methods for single-cell analysis and sorting

Advancements in microfluidic technologies have led to the development of many new tools for both the characterization and sorting of single cells without the need for exogenous labels. Label-free microfluidics reduce the preparation time, reagents needed, and cost of conventional methods based on fluorescent or magnetic labels. Furthermore, these devices enable analysis of cell properties such as mechanical phenotype and dielectric parameters that cannot be characterized with traditional labels. Some of the most promising technologies for current and future development toward label-free, single-cell analysis and sorting include electronic sensors such as Coulter counters and electrical impedance cytometry; deformation analysis using optical traps and deformation cytometry; hydrodynamic sorting such as deterministic lateral displacement, inertial focusing, and microvortex trapping; and acoustic sorting using traveling or standing surface acoustic waves. These label-free microfluidic methods have been used to screen, sort, and analyze cells for a wide range of biomedical and clinical applications, including cell cycle monitoring, rapid complete blood counts, cancer diagnosis, metastatic progression monitoring, HIV and parasite detection, circulating tumor cell isolation, and point-of-care diagnostics. Because of the versatility of label-free methods for characterization and sorting, the low-cost nature of microfluidics, and the rapid prototyping capabilities of modern microfabrication, we expect this class of technology to continue to be an area of high research interest going forward. New developments in this field will contribute to the ongoing paradigm shift in cell analysis and sorting technologies toward label-free microfluidic devices, enabling new capabilities in biomedical research tools as well as clinical diagnostics. This article is categorized under: Diagnostic Tools > Biosensing Diagnostic Tools > Diagnostic Nanodevices.

Perspectives and applications of machine learning for evolutionary developmental biology

Evolutionary Developmental Biology (Evo-Devo) is an ever-expanding field that aims to understand how development was modulated by the evolutionary process. In this sense, "omic" studies emerged as a powerful ally to unravel the molecular mechanisms underlying development. In this scenario, bioinformatics tools become necessary to analyze the growing amount of information. Among computational approaches, machine learning stands out as a promising field to generate knowledge and trace new research perspectives for bioinformatics. In this review, we aim to expose the current advances of machine learning applied to evolution and development. We draw clear perspectives and argue how evolution impacted machine learning techniques.

Biophysical investigation of living monocytes in flow by collaborative coherent imaging techniques

We implemented a completely label-free biophysical (morphometric and optical) property characterization of living monocytes in flow, using measurements obtained from two coherent imaging techniques: a pure light scattering approach to obtain an optical signature (OS) of cells, and a digital holography (DH) approach to achieve optical cell reconstructions in flow. A precise 3D cell alignment platform, taking advantage of viscoelastic fluid properties and microfluidic channel geometry, was used to investigate the OS of cells to achieve their refractive index, ratio of the nucleus over cytoplasm, and overall cell dimension. Further quantitative phase-contrast reconstructions by DH were employed to calculate surface area, dry mass, and biovolume of monocytes by using the OS outcomes as input parameters. The results show significantly different biophysical cell properties, confirming the possibility to differentiate monocytes from other cell classes in flow, thus avoiding chemical cell staining or labeling, which are nowadays used.

Multi-sample deformability cytometry of cancer cells

There is growing recognition that cell deformability can play an important role in cancer metastasis and diagnostics. Advancement of methods to characterize cell deformability in a high throughput manner and the capacity to process numerous samples can impact cancer-related applications ranging from analysis of patient samples to discovery of anti-cancer compounds to screening of oncogenes. In this study, we report a microfluidic technique called multi-sample deformability cytometry (MS-DC) that allows simultaneous measurement of flow-induced deformation of cells in multiple samples at single-cell resolution using a combination of on-chip reservoirs, distributed pressure control, and data analysis system. Cells are introduced at rates of O(100) cells per second with a data processing speed of 10 min per sample. To validate MS-DC, we tested more than 50 cell-samples that include cancer cell lines with different metastatic potential and cells treated with several cytoskeletal-intervention drugs. Results from MS-DC show that (i) the cell deformability correlates with metastatic potential for both breast and prostate cancer cells but not with their molecular histotype, (ii) the strongly metastatic breast cancer cells have higher deformability than the weakly metastatic ones; however, the strongly metastatic prostate cancer cells have lower deformability than the weakly metastatic counterparts, and (iii) drug-induced disruption of the actin network, microtubule network, and actomyosin contractility increased cancer cell deformability, but stabilization of the cytoskeletal proteins does not alter deformability significantly. Our study demonstrates the capacity of MS-DC to mechanically phenotype tumor cells simultaneously in many samples for cancer research.

Que la lumière soit. Et si ce n’était plus seulement vrai !

Ces dernières années ont vu une progression importante des capacités des nouveaux appareils de cytométrie. Deux sauts technologiques ont été récemment franchis avec la cytométrie couplée à la spectrométrie de masse, dans laquelle les fluorochromes ont été remplacés par des métaux rares non radioactifs de la famille des lanthanides et la cytométrie spectrale qui collecte les photons sur le spectre visible. Dans cette revue, nous décrivons schématiquement la cytométrie en flux conventionnelle et ces deux technologies ainsi que leurs avantages et adaptabilités et leurs inconvénients.

Characterizing cellular mechanical phenotypes with mechano-node-pore sensing

The mechanical properties of cells change with their differentiation, chronological age, and malignant progression. Consequently, these properties may be useful label-free biomarkers of various functional or clinically relevant cell states. Here, we demonstrate mechano-node-pore sensing (mechano-NPS), a multi-parametric single-cell-analysis method that utilizes a four-terminal measurement of the current across a microfluidic channel to quantify simultaneously cell diameter, resistance to compressive deformation, transverse deformation under constant strain, and recovery time after deformation. We define a new parameter, the whole-cell deformability index (wCDI), which provides a quantitative mechanical metric of the resistance to compressive deformation that can be used to discriminate among different cell types. The wCDI and the transverse deformation under constant strain show malignant MCF-7 and A549 cell lines are mechanically distinct from non-malignant, MCF-10A and BEAS-2B cell lines, and distinguishes between cells treated or untreated with cytoskeleton-perturbing small molecules. We categorize cell recovery time, ΔT_r, as instantaneous (ΔT_r ~ 0 ms), transient (ΔT_r ≤ 40ms), or prolonged (ΔT_r > 40ms), and show that the composition of recovery types, which is a consequence of changes in cytoskeletal organization, correlates with cellular transformation. Through the wCDI and cell-recovery time, mechano-NPS discriminates between sub-lineages of normal primary human mammary epithelial cells with accuracy comparable to flow cytometry, but without antibody labeling. Mechano-NPS identifies mechanical phenotypes that distinguishes lineage, chronological age, and stage of malignant progression in human epithelial cells.

Functional and Biomimetic Materials for Engineering of the Three-Dimensional Cell Microenvironment

The cell microenvironment has emerged as a key determinant of cell behavior and function in development, physiology, and pathophysiology. The extracellular matrix (ECM) within the cell microenvironment serves not only as a structural foundation for cells but also as a source of three-dimensional (3D) biochemical and biophysical cues that trigger and regulate cell behaviors. Increasing evidence suggests that the 3D character of the microenvironment is required for development of many critical cell responses observed in vivo, fueling a surge in the development of functional and biomimetic materials for engineering the 3D cell microenvironment. Progress in the design of such materials has improved control of cell behaviors in 3D and advanced the fields of tissue regeneration, in vitro tissue models, large-scale cell differentiation, immunotherapy, and gene therapy. However, the field is still in its infancy, and discoveries about the nature of cell-microenvironment interactions continue to overturn much early progress in the field. Key challenges continue to be dissecting the roles of chemistry, structure, mechanics, and electrophysiology in the cell microenvironment, and understanding and harnessing the roles of periodicity and drift in these factors. This review encapsulates where recent advances appear to leave the ever-shifting state of the art, and it highlights areas in which substantial potential and uncertainty remain.

Single-cell screening of multiple biophysical properties in leukemia diagnosis from peripheral blood by pure light scattering

Histology and histopathology are based on the morphometric observations of quiescent cells. Their diagnostic potential could largely benefit from a simultaneous screening of intrinsic biophysical properties at single-cell level. For such a purpose, we analyzed light scattering signatures of individual mononuclear blood cells in microfluidic flow. In particular, we extracted a set of biophysical properties including morphometric (dimension, shape and nucleus-to-cytosol ratio) and optical (optical density) ones to clearly discriminate different cell types and stages. By considering distinctive ranges of biophysical properties along with the obtained relative cell frequencies, we can identify unique cell classes corresponding to specific clinical conditions (p < 0.01). Based on such a straightforward approach, we are able to discriminate T-, B-lymphocytes, monocytes and beyond that first results on different stages of lymphoid and myeloid leukemia cells are presented. This work shows that the simultaneous screening of only three biophysical properties enables a clear distinction between pathological and physiological mononuclear blood stream cells. We believe our approach could represent a useful tool for a label-free analysis of biophysical single-cell signatures.