Mechanical Properties Of Single Cells Research Articles

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.

Microfluidic high-throughput single-cell mechanotyping: Devices and applications

The mechanical behavior of individual cells plays an important role in regulating various biological activities at the molecular and cellular levels. It can serve as a promising label-free marker of cells’ physiological states. In the past two decades, several techniques have been developed for understanding correlations between cellular mechanical changes and human diseases. However, numerous technical challenges remain with regard to realizing high-throughput, robust, and easy-to-perform measurements of single-cell mechanical properties. In this paper, we review the emerging tools for single-cell mechanical characterization that are provided by microfluidic technology. Different techniques are benchmarked by considering their advantages and limitations. Finally, the potential applications of microfluidic techniques based on cellular mechanical properties are discussed.

Efficient Single-Cell Mechanical Measurement by Integrating a Cell Arraying Microfluidic Device With Magnetic Tweezer

Cell stiffness is an essential label-free biomarker used to diagnose and sort cells at the single-cell level. Here, we integrated magnetic tweezers on an efficient cell arraying microfluidic device to evaluate the mechanical properties of single cells. Two motion modes under pulsed electromagnetic fields have been proposed for magnetic beads. They were magnetically actuated to approach the measuring cells at a distance in rotation mode and move experimentally with the maximal velocity of 23 μm s <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-1</sup> under a rotating magnetic field of 45 Hz and 45 mT. In contrast, the magnetic beads were driven at close range in translation mode to approach and apply extrusion pressure on the target cells under a locally constant magnetic field gradient. The simulation results of the fluid field caused by the moving bead revealed the difference distribution in velocity and pressure under two motion modes, proving the rationality of the motion mode setting. Experimentally, Hela cells and C2C12 cells arrayed in the microfluidic device were physically squeezed by magnetic tweezers, and cell stiffness was measured. Compared to the measurement results with AFM, the proposed method used to measure Young's modulus of the cells was thought to be dependable. We envision the proposed on-chip platform integrated with the magnetic tweezer could show a potential application for the efficient and flexible measurement of biomechanical properties in the future.

A Review of Single-Cell Adhesion Force Kinetics and Applications.

Cells exert, sense, and respond to the different physical forces through diverse mechanisms and translating them into biochemical signals. The adhesion of cells is crucial in various developmental functions, such as to maintain tissue morphogenesis and homeostasis and activate critical signaling pathways regulating survival, migration, gene expression, and differentiation. More importantly, any mutations of adhesion receptors can lead to developmental disorders and diseases. Thus, it is essential to understand the regulation of cell adhesion during development and its contribution to various conditions with the help of quantitative methods. The techniques involved in offering different functionalities such as surface imaging to detect forces present at the cell-matrix and deliver quantitative parameters will help characterize the changes for various diseases. Here, we have briefly reviewed single-cell mechanical properties for mechanotransduction studies using standard and recently developed techniques. This is used to functionalize from the measurement of cellular deformability to the quantification of the interaction forces generated by a cell and exerted on its surroundings at single-cell with attachment and detachment events. The adhesive force measurement for single-cell microorganisms and single-molecules is emphasized as well. This focused review should be useful in laying out experiments which would bring the method to a broader range of research in the future.

Cell properties assessment using optimized dielectrophoresis-based cell stretching and lumped mechanical modeling

Cells mechanical property assessment has been a promising label-free method for cell differentiation. Several methods have been proposed for single-cell mechanical properties analysis. Dielectrophoresis (DEP) is one method used for single-cell mechanical property assessment, cell separation, and sorting. DEP method has overcome weaknesses of other techniques, including compatibility with microfluidics, high throughput assessment, and high accuracy. However, due to the lack of a general and explicit model for this method, it has not been known as an ideal cell mechanical property evaluation method. Here we present an explicit model using the most general electromagnetic equation (Maxwell Stress Tensor) for single-cell mechanical evaluation based on the DEP method. For proof of concept, we used the proposed model for differentiation between three different types of cells, namely erythrocytes, peripheral blood mononuclear cells (PBMC), and an epithelial breast cancer cells line (T-47D). The results show that, by a lumped parameter that depends on cells' mechanical and electrical properties, the proposed model can successfully distinguish between the mentioned cell types that can be in a single blood sample. The proposed model would open up the chance to use a mechanical assessment method for cell searching in parallel with other methods.

The method to quantify cell elasticity based on the precise measurement of pressure inducing cell deformation in microfluidic channels

The cell elasticity has attracted extensive research interests since it not only provides new insights into cell biology but also is an emerging mechanical marker for the diagnosis of some diseases. This paper reports the method for the precise measurement of mechanical properties of single cells deformed to a large extent using a novel microfluidic system integrated with a pressure feedback system and small particle separation unit. The particle separation system was employed to avoid the blockage of the cell deformation channel to enhance the measurement throughput. This system is of remarkable application potential in the precise evaluation of cell mechanical properties. In brief, this paper reports:•The manufacturing of the chip using standard soft lithography;•The methods to deform single cells in a microchannel and measure the relevant pressure drop using a pressure sensor connecting to the microfluidic chip;•Calculation of the mechanical properties including stiffness and fluidity of each cell based on a power-law rheology model describing the viscoelastic behaviors of cells;•Automatic and real-time measurement of the mechanical properties using video processing software.

An Acoustic Platform for Single-Cell, High-Throughput Measurements of the Viscoelastic Properties of Cells.

Cellular processes including adhesion, migration, and differentiation are governed by the distinct mechanical properties of each cell. Importantly, the mechanical properties of individual cells can vary depending on local physical and biochemical cues in a time-dependent manner resulting in significant inter-cell heterogeneity. While several different methods have been developed to interrogate the mechanical properties of single cells, throughput to capture this heterogeneity remains an issue. Here, single-cell, high-throughput characterization of adherent cells is demonstrated using acoustic force spectroscopy (AFS). AFS works by simultaneously, acoustically driving tens to hundreds of silica beads attached to cells away from the cell surface, allowing the user to measure the stiffness of adherent cells under multiple experimental conditions. It is shown that cells undergo marked changes in viscoelasticity as a function of temperature, by altering the temperature within the AFS microfluidic circuit between 21 and 37°C. In addition, quantitative differences in cells exposed to different pharmacological treatments specifically targeting the membrane-cytoskeleton interface are shown. Further, the high-throughput format of the AFS is utilized to rapidly probe, in excess of 1000 cells, three different cell lines expressing different levels of a mechanosensitive protein, Piezo1, demonstrating the ability to differentiate between cells based on protein expression levels.

Selective Anticancer Effect of Phellinus Linteus on Epidermoid Cell Lines Studied by Atomic Force Microscopy: Anticancer Activity on A431 Cancer Cells and Low Toxicity on HaCat Normal Cells

The research on the morphological and mechanical properties of single cells has provided a crucial way of understanding the cellular physiology and metabolism. In this study, the selective anticancer effects of Phellinus linteus on A431 and HaCat cells and their morphological and mechanical properties were systematically investigated by atomic force microscopy (AFM). Notably, the cell morphology on the micronano scale was observed under both the physiological environment and immobilization conditions. The significant morphological changes of A431 cells from the flat to spherical shape, the increase of cell height, and the decrease of the particles on the cell membrane were confirmed to be related to the cell apoptosis under the treatment of the Phellinus linteus water extract (PLWE). Moreover, the small morphology variations of HaCat cells showed that the PLWE presented a high anticancer effect on A431 cells but low toxicity on HaCat cells, which indicated a potential cell selectivity between cancer and normal cells. This work proved that Phellinus linteus could be used as a <;i>potential candidate<;/i> for selective anticancer treatments.

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.

Direct Characterization of Stress-Strain Relationship for Quantifying Single Cell Elasticity

The mechanical properties of live cells are important for maintaining cell physiological functions. Many types of cells such as cancer cells, malaria-infected cells, and cells with progeria have shown altered mechanical properties. Measurement of cell mechanics becomes useful for understanding cell physiology and potentially for diagnosing diseases. A number of techniques have been applied to measuring single cell mechanical properties, among which Atomic Force Microscopy (AFM) is a popular method. However, since this approach has an intrinsic problem of lacking contact area information, the elastic property were commonly extracted by fitting the force-displacement curve acquired from AFM indentation using a Hertzian contact model, which leads to inaccurate measurement as cell-probe contact violates the assumptions of Hertzian model (rigid body contact, no adhesion). An ideal approach to quantify cell's elastic property is direct compression or tensile testing which does not rely on any contact mechanics models with assumptions that cells might not be eligible for. Here, we quantified the elastic property of live cells directly from stress-strain curves by compression test using an integrated system of a confocal microscope and an AFM with a tip-less cantilever. The contact area was measured by confocal microscope and quantified by image processing, then used to convert force to stress. The Young's modulus of T24 cells was determined directly from the slope of stress-strain curves as 0.88±0.12 kPa. In comparison, we also applied previous indentation method and contact mechanics model fitting (Hertz model, Kevin-Voigt model, Standard Linear Solid model, all with Hertzian contact assumptions). The results obtained through each model were 1.54±0.21 kPa, 2.30±0.448 kPa, 1.80±0.32 kPa, respectively (pairwise P<0.05); and the Young's modulus from the three models showed error of 78%±26%, 164%±50%, 105%±21%, compared with our direct stress-strain characterization of the same 10 cells.

Nanopin - a Mems Based Sensor for the Analysis of Single-Cell Mechanical Properties

We describe a new MEMS based sensor for mechanical characterization, such as stiffness, of individual adherent cells. Here, we evaluated its feasibility using human lung carcinoma A549 cells. Previously, MEMS based force sensors have been reported, but most of them applied large stress to a cell and demonstrated insufficient sensitivity. Our prototype demonstrated limits of 4 nN for force, 300 μN/m for stiffness, and 0.05 μN/m·s for viscoelasticity measurements, respectively, providing the required sensitivity for measuring single cell mechanical changes. Nanopin was fabricated with SOI wafer by conventional cleanroom processes, and consisted of a sensing probe, comb drive actuator and a displacement sensor. Briefly, a sensing tip is oscillated by the actuator with nanometer accuracy and its displacement is measured by the sensor. Phase-lock-loop control allows to track resonance frequency over time. Several probe tips were designed, and UnipicK+™ single cell collection system was used for accurate z-axes positioning and placement of Nanopin tip over a single cell (NeuroInDx, USA). We conducted measurements of adherent human lung carcinoma A549 cells grown on noncoated and Poly-L-lysine (PLL) coated dishes. All measurements were performed at 1.5 µm depth after initial point of contact. Cells on PLL coated dishes demonstrated approximately 8 Hz shift in frequency with stable resonance frequency and amplitude. Using a mass-spring-damper model, the stiffness was estimated to be approximately 0.02 N/m. Contrary to these results, cells grown on noncoated dishes showed increasing resonance frequency and amplitude over time. After measurements, cells were placed back in incubator and their normal growth was confirmed. Our studies demonstrate the feasibility of the proposed Nanopin sensor for single cell stiffness measurements and its integration in continuous mechanical analysis and cell acquisition workflow.

Quantitative characterization of mechano-biological interrelationships of single cells

This paper presented a quantitative investigation on the alteration of cell biological functions in relation to the change of mechanical properties of single cells. Leukemia NB4 cells were used as cell line. The dielectrophoresis (DEP) method was utilized to verify the mechanical properties variation of NB4 cells under the electric field treatment. A quantitative study of cell mechanical properties was then carried out using optical tweezers (OT), and cell biological properties using gene expression measurement. The result shows cell stiffness decreased after electric treatment. Biological properties related to cell motility, structure, apoptosis, migration, invasion, and metastases changed with cell mechanical properties variation.

Measurement and analysis of cellular viscoelastic properties using atomic force microscopy

Cell mechanics plays an important role in cellular physiological and pathological processes. During the formation and progression of tumors, the alterations in the mechanics of cancerous cells and tumor micro-environment promote the growth and migration of cancerous cells. Hence, investigating cell mechanics is of crucial significance in understanding the underlying mechanisms regulating life activities and diseases. The advent of atomic force microscopy (AFM) provides a powerful tool for detecting the mechanical properties of single cells. Compared with other single-cell mechanical analysis techniques, the advantage of AFM is that AFM is able to simultaneously obtain the topography and mechanics of cells, which is particularly useful for investigating the correlation between cell structures and cell mechanics. The biomedical applications of AFM in single-cell mechanics provide considerable novel insights into how cell and tissue mechanics affect tumor development and metastasis, contributing much to the communities of biomechanics and biophysics. However, current AFM single-cell mechanical experiments are commonly performed on measuring the elastic properties of cells and studies about the viscoelastic properties of cells are still scarce. In this work, AFM was utilized to measure and analyze the viscoelastic properties of cells. First, the detailed procedure of detecting the viscoelasticity of cells based on AFM indentation technique was established. AFM probe was controlled to perform approach-dwell-retract movement on cells in the vertical direction. During the approach-dwell-retract process, the deflection of AFM cantilever versus time was recorded, which yielded the force-time (F-T) curves. The original F-T curves were then normalized and fitted by two-order Maxwell model, which gave two cellular relaxation times (the first relaxation time τ 1 and the second relaxation time τ 2). The fitting results showed that the theoretical curve matched the experimental relaxation curve well, indicating that the two-order Maxwell model was suited for characterizing the relaxation behaviors of cells. Second, the established procedure was used to measure the relaxation time of six different types of cells, including mammalian adherent cells, mammalian suspended cells, normal cells, cancerous cells, cell lines cultured in vitro and primary cells prepared from bone marrow and peripheral blood of healthy volunteers. The fitting curves were consistent with the experimental relaxation curves for all of the six types of cells used here, indicating the effectiveness of the presented method for detecting the viscoelastic properties of cells. Besides, the results showed the various cellular relaxation times for the different types of cells. The statistical results showed that the first cellular relaxation times were in the range 0.01−0.03 s, which might correspond to the behaviors of cytoplasm. The second cellular relaxation time was in the range 0.2−0.4 s, which might correspond to the behaviors of the cytoskeleton. Finally, regression analysis was performed on the measured cellular relaxation times, showing the linear relationship between the first cellular relaxation time τ 1 and the second cellular relaxation time τ 2, and the regression coefficients were variable for different types of cells. The research improves our understanding of cellular viscoelasticity and also provides a novel idea to measure the viscoelastic properties of cells, which will have potential impacts on cell mechanics and biomedicine.

Effect of cell sample size in atomic force microscopy nanoindentation

Single-cell technologies are powerful tools to evaluate cell characteristics. In particular, Atomic Force Microscopy (AFM) nanoindentation experiments have been widely used to study single cell mechanical properties. One important aspect related to single cell techniques is the need for sufficient statistical power to obtain reliable results. This aspect is often overlooked in AFM experiments were sample sizes are arbitrarily set.The aim of the present work was to propose a tool for sample size estimation in the context of AFM nanoindentation experiments of single cell. To this aim, a retrospective approach was used by acquiring a large dataset of experimental measurements on four bone cell types and by building saturation curves for increasing sample sizes with a bootstrap resampling method.It was observed that the coefficient of variation (CV%) decayed with a function of the form y = axb with similar parameters for all samples tested and that sample sizes of 21 and 83 cells were needed for the specific cells and protocol employed if setting a maximum threshold on CV% of 10% or 5%, respectively. The developed tool is made available as an open-source repository and guidelines are provided for its use for AFM nanoindentation experimental design.

Experimental Characterization of MCF-10A Normal Cells Using AFM: Comparison with MCF-7 Cancer Cells

The mechanical properties of single cells have been recently identified as the basis of an emerging approach in medical applications since they are closely related to the biological processes of cells and human health conditions. The problem in hand is how to measure mechanical properties in order to obtain them more accurately and applicably. Some of the cell’s properties such as elasticity module and adhesion have been measured before using various methods; nevertheless, comprehensive tests for two healthy and cancerous cells have not been performed simultaneously. As a Nanoscale device, AFM has been used for some biological cells, however for breast cells, it has been utilized just to measure elasticity module. To provide a more accurate comparison for the healthy and the malignant cancer cells of breast, mechanical properties of MCF-10A cells such as topography, elasticity module, adhesion force, viscoelastic characteristics, bending and axial rigidity were determined and compared to the MCF-7 cells results obtained in previous works. Results revealed that the healthy breast cells are stiffer and less adhesive in comparison with the cancerous ones. Topography images revealed that cancerous cells have bigger radii. These results can help with the diagnosis of malignant cancer cells and even the level of the disease.

Cell quake elastography

The ability to measure the elasticity of a cell provides information about its anatomy, function, and pathological state. Many techniques have been proposed to measure mechanical properties of single cells but most need a model of the cell characteristics and the fixation of the cell on a substrate. Moreover, current measurements take seconds to hours to perform, during which biological processes can modify the cell elasticity. Here, we have developed an alternative technique by applying shear wave elastography to the micrometer scale. Elastic waves were mechanically induced in live mammalian oocytes using a vibrating actuator. These audible frequency waves were observed optically at 205,000 frames per second and tracked with an optical flow algorithm previously developed in the context of ultrasound elastography. Whole-cell elasticity was then reconstructed using an elastography method inspired by the seismology field. Using this approach we showed that the elasticity of mouse oocytes is decreased when the oocyte cytoskeleton is disrupted with cytochalasin B. The technique is fast (less than 1 ms for data acquisition), precise (spatial resolution of a few micrometers), and able to map internal cell structures. The proposed method may represent a tractable option for interrogating biomechanical properties of diverse cell types.

Mechanical Properties and Differentiation Assessments of Neural Stem Cells with Pneumatic Micropipette Aspiration

The change in chemical and biological properties of neural stem cells (NSCs) before and after differentiating into neurons and glial cells has been well studied. However, there is lack of knowledge on the relationship between cell differentiation and alteration of cell mechanical features. Mechanical properties can reflect specific changes that occur with biochemical and cytological changes. Here, we present a robotic micromanipulation system for measuring the mechanical properties of single cells. This system consists of a suction micropipette, a robotic micromanipulator and an inverted microscope. A pneumatic micropipette aspiration method is utilized to measure the elastic properties of the cells. We found that the mechanical properties of NSCs belong to the solid state, however, neurons and glial cells are close to the liquid state. Further, NSCs are harder than neurons and glial cells.

Machine Learning for Nuclear Mechano-Morphometric Biomarkers in Cancer Diagnosis

Current cancer diagnosis employs various nuclear morphometric measures. While these have allowed accurate late-stage prognosis, early diagnosis is still a major challenge. Recent evidence highlights the importance of alterations in mechanical properties of single cells and their nuclei as critical drivers for the onset of cancer. We here present a method to detect subtle changes in nuclear morphometrics at single-cell resolution by combining fluorescence imaging and deep learning. This assay includes a convolutional neural net pipeline and allows us to discriminate between normal and human breast cancer cell lines (fibrocystic and metastatic states) as well as normal and cancer cells in tissue slices with high accuracy. Further, we establish the sensitivity of our pipeline by detecting subtle alterations in normal cells when subjected to small mechano-chemical perturbations that mimic tumor microenvironments. In addition, our assay provides interpretable features that could aid pathological inspections. This pipeline opens new avenues for early disease diagnostics and drug discovery.

Micromechanical and surface adhesive properties of single saccharomyces cerevisiae cells

The adhesion and mechanical properties of a biological cell (e.g. cell membrane elasticity and adhesiveness) are often strong indicators for the state of its health. Many existing techniques for determining mechanical properties of cells require direct physical contact with a single cell or a group of cells. Physical contact with the cell can trigger complex mechanotransduction mechanisms, leading to cellular responses, and consequently interfering with measurement accuracy. In the current work, based on ultrasonic excitation and interferometric (optical) motion detection, a non-contact method for characterizing the adhesion and mechanical properties of single cells is presented. It is experimentally demonstrated that the rocking (rigid body) motion and internal vibrational resonance frequencies of a single saccharomyces cerevisiae (SC) (baker’s yeast) cell can be acquired with the current approach, and the Young’s modulus and surface tension of the cell membrane as well as surface adhesion energy can be extracted from the values of these acquired resonance frequencies. The detected resonance frequency ranges for single SC cells include a rocking (rigid body) frequency of 330 ± 70 kHz and two breathing resonance frequencies of 1.53 ± 0.12 and 2.02 ± 0.31 MHz. Based on these values, the average work-of-adhesion of SC cells on a silicon substrate in aqueous medium is extracted, for the first time, as . Similarly, the surface tension and the Young’s modulus of the SC cell wall are predicted as and 9.20 ± 2.80 MPa, respectively. These results are compared to those reported in the literature by utilizing various methods, and good agreements are found. The current approach eliminates the measurement inaccuracies associated with the physical contact. Exciting and detecting cell dynamics at micro-second time-scales is significantly faster than the currently known metabolistic response times of cells (milliseconds to seconds), thus, it has the potential to decouple metabolistic and mechanotransduction effects from external stimuli and to operate at high throughput rates.

Dynamical Modeling and Analysis of Viscoelastic Properties of Single Cells

A single cell can be regarded as a complex network that contains thousands of overlapping signaling pathways. The traditional methods for describing the dynamics of this network are extremely complicated. The mechanical properties of a cell reflect the cytoskeletal structure and composition and are closely related to the cellular biological functions and physiological activities. Therefore, modeling the mechanical properties of single cells provides the basis for analyzing and controlling the cellular state. In this study, we developed a dynamical model with cellular viscoelasticity properties as the system parameters to describe the stress-relaxation phenomenon of a single cell indented by an atomic force microscope (AFM). The system order and parameters were identified and analyzed. Our results demonstrated that the parameters identified using this model represent the cellular mechanical elasticity and viscosity and can be used to classify cell types.