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

Characterization of Cancer Cell Mechanics by Measuring Active Deformation Behavior

Active deformation behavior reflects cell structural dynamics adapting to varying environmental constraints during malignancy progression. In most cases, cell mechanics is characterized by modeling using static equilibrium systems, which fails to comprehend cell deformation behavior leading to inaccuracies in distinguishing cancer cells from normal cells. Here, a method is introduced to measure the active deformation behavior of cancer cells using atomic force microscopy (AFM) and the newly developed deformation behavior cytometry (DBC). During the measurement, cells are deformed and allows a long timescale relaxation (≈5 s). Two parameters are derived to represent deformation behavior: apparent Poisson's ratio for adherent cells, which is measured with AFM and refers to the ratio of the lateral strain to the longitudinal strain of the cell, and shape recovery for suspended cells, which is measured with DBC. Active deformation behavior defines cancer cell mechanics better than traditional mechanical parameters (e.g., stiffness, diffusion, and viscosity). Additionally, aquaporins are essential for promoting the deformation behavior, while the actin cytoskeleton acts as a downstream effector. Therefore, the potential application of the cancer cell active deformation behavior as a biomechanical marker or therapeutic target in cancer treatment should be evaluated.

A review on intelligent impedance cytometry systems: Development, applications and advances

Impedance cytometry is a well-established technique for counting and analyzing single cells, with several advantages, such as convenience, high throughput, and no labeling required. A typical experiment consists of the following steps: single-cell measurement, signal processing, data calibration, and particle subtype identification. At the beginning of this article, we compared commercial and self-developed options extensively and provided references for developing reliable detection systems, which are necessary for cell measurement. Then, a number of typical impedance metrics and their relationships to biophysical properties of cells were analyzed with respect to the impedance signal analysis. Given the rapid advances of intelligent impedance cytometry in the past decade, this article also discussed the development of representative machine learning-based approaches and systems, and their applications in data calibration and particle identification. Finally, the remaining challenges facing the field were summarized, and potential future directions for each step of impedance detection were discussed.

Metal-pad-enhanced resistive pulse sensor reveals complex-valued Braess paradox

A resistive pulse sensor measures the electrical impedance of an electrolyte-filled channel as particles flow through it. Ordinarily, the presence of a nonconductive particle increases the impedance of the channel. Here we report a surprising experimental result in which a microfluidic resistive pulse sensor experiences the opposite effect: The presence of a nonconductive particle decreases the channel impedance. We explain the counterintuitive phenomenon by relating to the Braess paradox from traffic network theory, and we call it the complex-valued Braess paradox (CVBP). We develop theoretical models to study the CVBP and corroborate the experimental data using finite element simulations and lumped-element circuit modeling. We then discuss implications and potential applications of the CVBP in resistive pulse sensing and beyond.

Experimental and numerical responses of fibroblast and epithelial cells to the frequency of electric toothbrush

In the oral environment, fibroblast and gingival epithelial cells undergo distinct forces. Chewing, brushing, or force interactions with dental materials like implants can produce these forces. The behavior and response of these cells to forces are determined by their stiffness. Additionally, this behavior can be crucial in mechanosensory and tissue development. In this study, after being cultured using nanomagnet materials, fibroblast and epithelial cells were subjected to magnetic tweezers cytometry testing, and the viscoelastic model was used to determine their stiffness. The reaction of single gingival cells was modeled by determining the stiffness of cells at Gel Point frequencies and the operating frequency of electric toothbrushes and employing the Finite Element Method (FEM). Epithelial cell and fibroblast gel points took place at frequencies of 5Hz and 3Hz, respectively. At these frequencies, the behavior of cells is both quasi-solid and fluid. In addition, the findings of the finite element analysis demonstrated that the cells undergo a greater degree of deformation at the Gel point frequency compared to the operating frequency of toothbrushes. This quantity was approximately 331 times greater in epithelial cells, which reached a maximum of 7.114 μm. Additionally, the maximal fibroblast cell deformation at 3Hz frequency was determined to be 2.981 μm, which is roughly 117 times that at 150Hz frequency.

Quantitative characterization of cell physiological state based on dynamical cell mechanics for drug efficacy indication

Cell mechanics is essential to cell development and function, and its dynamics evolution reflects the physiological state of cells. Here, we investigate the dynamical mechanical properties of single cells under various drug conditions, and present two mathematical approaches to quantitatively characterizing the cell physiological state. It is demonstrated that the cellular mechanical properties upon the drug action increase over time and tend to saturate, and can be mathematically characterized by a linear time-invariant dynamical model. It is shown that the transition matrices of dynamical cell systems significantly improve the classification accuracies of the cells under different drug actions. Furthermore, it is revealed that there exists a positive linear correlation between the cytoskeleton density and the cellular mechanical properties, and the physiological state of a cell in terms of its cytoskeleton density can be predicted from its mechanical properties by a linear regression model. This study builds a relationship between the cellular mechanical properties and the cellular physiological state, adding information for evaluating drug efficacy.

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

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

Impedance-Enabled Camera-Free Intrinsic Mechanical Cytometry

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

Node-Pore Sensing for Characterizing Cells and Extracellular Vesicles

Node-Pore Sensing, NPS, is an extremely versatile and powerful technique for the analysis of cells and the detection of extracellular vesicles (EVs). NPS involves measuring the modulated current pulse caused by a cell transiting a microfluidic channel that has been segmented by a series of inserted nodes. As the current pulse reflects the number of nodes and segments of the channel, NPS can achieve exquisite sensitivity. Thus, when used as a Coulter counter, NPS can measure the sub-micron size increase of antibody-coated colloids to which EVs are specifically bound. By simply inserting between two nodes a "contraction" channel through which cells can squeeze, one can mechanically phenotype cells. We discuss the details of performing these two NPS applications.

Assessment of the electrical penetration of cell membranes using four-frequency impedance cytometry

The electrical penetration of the cell membrane is vital for determining the cell interior via impedance cytometry. Herein, we propose a method for determining the conductivity of the cell membrane through the tilting levels of impedance pulses. When electrical penetration occurs, a high-frequency current freely passes through the cell membrane; thus, the intracellular distribution can directly act on the high-frequency impedance pulses. Numerical simulation shows that an uneven intracellular component distribution can affect the tilting levels of impedance pulses, and the tilting levels start increasing when the cell membrane is electrically penetrated. Experimental evidence shows that higher detection frequencies (>7 MHz) lead to a wider distribution of the tilting levels of impedance pulses when measuring cell populations with four-frequency impedance cytometry. This finding allows us to determine that a detection frequency of 7 MHz is able to pass through the membrane of Euglena gracilis (E. gracilis) cells. Additionally, we provide a possible application of four-frequency impedance cytometry in the biomass monitoring of single E. gracilis cells. High-frequency impedance (≥7 MHz) can be applied to monitor these biomass changes, and low-frequency impedance (<7 MHz) can be applied to track the corresponding biovolume changes. Overall, this work demonstrates an easy determination method for the electrical penetration of the cell membrane, and the proposed platform is applicable for the multiparameter assessment of the cell state during cultivation.

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.

Evaluating sources of technical variability in the mechano-node-pore sensing pipeline and their effect on the reproducibility of single-cell mechanical phenotyping

Cellular mechanical properties can reveal physiologically relevant characteristics in many cell types, and several groups have developed microfluidics-based platforms to perform high-throughput single-cell mechanical testing. However, prior work has performed only limited characterization of these platforms' technical variability and reproducibility. Here, we evaluate the repeatability performance of mechano-node-pore sensing, a single-cell mechanical phenotyping platform developed by our research group. We measured the degree to which device-to-device variability and semi-manual data processing affected this platform's measurements of single-cell mechanical properties. We demonstrated high repeatability across the entire technology pipeline even for novice users. We then compared results from identical mechano-node-pore sensing experiments performed by researchers in two different laboratories with different analytical instruments, demonstrating that the mechanical testing results from these two locations are in agreement. Our findings quantify the expectation of technical variability in mechano-node-pore sensing even in minimally experienced hands. Most importantly, we find that the repeatability performance we measured is fully sufficient for interpreting biologically relevant single-cell mechanical measurements with high confidence.

Automated Cell Mechanical Characterization by On-Chip Sequential Squeezing: From Static to Dynamic

The mechanical properties of cells are harmless biomarkers for cell identification and disease diagnosis. Although many systems have been developed to evaluate the static mechanical properties of cells for biomedical research, their robustness, effectiveness, and cost do not meet clinical requirements or the experiments with a large number of cell samples. In this paper, we propose an approach for on-chip cell mechanical characterization by analyzing the dynamic behavior of cells as they pass through multiple constrictions. The proposed serpentine microfluidic channel consisted of 20 constrictions connected in series and divided into five rows for tracking cell dynamic behavior. Assisted by computer vision, the squeezing time of each cell through five rows of constrictions was automatically collected and filtered to evaluate the cell's mechanical deformability. We observed a decreasing passage time and increasing dynamic deformability of the cells as they passed through the multiple constrictions. The deformability increase rate of the HeLa cells was eight times greater than that of MEF cells. Moreover, the weak correlation between the deformability increase rate and the cell size indicated that cell recognition based on measuring the deformability increase rate could hardly be affected by the cell size variation. These findings showed that the deformability increase rate of the cell under on-chip sequential squeezing as a new index has great potential in cancer cell recognition.

Recent Advances on the Model, Measurement Technique, and Application of Single Cell Mechanics

Since the cell was discovered by humans, it has been an important research subject for researchers. The mechanical response of cells to external stimuli and the biomechanical response inside cells are of great significance for maintaining the life activities of cells. These biomechanical behaviors have wide applications in the fields of disease research and micromanipulation. In order to study the mechanical behavior of single cells, various cell mechanics models have been proposed. In addition, the measurement technologies of single cells have been greatly developed. These models, combined with experimental techniques, can effectively explain the biomechanical behavior and reaction mechanism of cells. In this review, we first introduce the basic concept and biomechanical background of cells, then summarize the research progress of internal force models and experimental techniques in the field of cell mechanics and discuss the latest mechanical models and experimental methods. We summarize the application directions of cell mechanics and put forward the future perspectives of a cell mechanics model.

The promise of single-cell mechanophenotyping for clinical applications

Cancer is the second leading cause of death worldwide. Despite the immense research focused in this area, one is still not able to predict disease trajectory. To overcome shortcomings in cancer disease study and monitoring, we describe an exciting research direction: cellular mechanophenotyping. Cancer cells must overcome many challenges involving external forces from neighboring cells, the extracellular matrix, and the vasculature to survive and thrive. Identifying and understanding their mechanical behavior in response to these forces would advance our understanding of cancer. Moreover, used alongside traditional methods of immunostaining and genetic analysis, mechanophenotyping could provide a comprehensive view of a heterogeneous tumor. In this perspective, we focus on new technologies that enable single-cell mechanophenotyping. Single-cell analysis is vitally important, as mechanical stimuli from the environment may obscure the inherent mechanical properties of a cell that can change over time. Moreover, bulk studies mask the heterogeneity in mechanical properties of single cells, especially those rare subpopulations that aggressively lead to cancer progression or therapeutic resistance. The technologies on which we focus include atomic force microscopy, suspended microchannel resonators, hydrodynamic and optical stretching, and mechano-node pore sensing. These technologies are poised to contribute to our understanding of disease progression as well as present clinical opportunities.

Mechanical Low-Pass Filtering of Cells for Detection of Circulating Tumor Cells in Whole Blood

The detection of circulating tumor cells (CTCs) from liquid biopsies using microfluidic devices is attracting a considerable amount of attention as a new, less-invasive cancer diagnostic and prognostic method. One of the drawbacks of the existing antibody-based detection systems is the false negatives for epithelial cell adhesion molecule detection of CTCs. Here we report a mechanical low-pass filtering technique based on a microfluidic constriction and electrical current sensing system for the novel CTC detection in whole blood without any specific antigen-antibody interaction or biochemical modification of the cell surface. The mechanical response of model cells of CTCs, such as HeLa, A549, and MDA-MB-231 cells, clearly demonstrated different behaviors from that of Jurkat cells, a human T-lymphocyte cell line, when they passed through the 6-μm wide constriction channel. A 6-μm wide constriction channel was determined as the optimum size to identify CTCs in whole blood with an accuracy greater than 95% in tens of milliseconds. The mechanical filtering of cells at a single cell level was achieved from whole blood without any pretreatment (e.g., dilution of lysing) and prelabeling (e.g., fluorophores or antibodies).