Mapping heterogeneity of cellular mechanics by multi-harmonic atomic force microscopy

Advances in microfluidic platforms for tumor cell phenotyping: from bench to bedside

Heterogeneities among tumor cells significantly contribute towards cancer progression and therapeutic inefficiency. Hence, understanding the nature of cancer through liquid biopsies and isolation of circulating tumor cells (CTCs) has gained considerable interest over the years. Microfluidics has emerged as one of the most popular platforms for performing liquid biopsy applications. Various label-free and labeling techniques using microfluidic platforms have been developed, the majority of which focus on CTC isolation from normal blood cells. However, sorting and profiling of various cell phenotypes present amongst those CTCs is equally important for prognostics and development of personalized therapies. In this review, firstly, we discuss the biophysical and biochemical heterogeneities associated with tumor cells and CTCs which contribute to cancer progression. Moreover, we discuss the recently developed microfluidic platforms for sorting and profiling of tumor cells and CTCs. These techniques are broadly classified into biophysical and biochemical phenotyping methods. Biophysical methods are further classified into mechanical and electrical phenotyping. While biochemical techniques have been categorized into surface antigen expressions, metabolism, and chemotaxis-based phenotyping methods. We also shed light on clinical studies performed with these platforms over the years and conclude with an outlook for the future development in this field.

Machine learning and artificial intelligence: Enabling the clinical translation of atomic force microscopy-based biomarkers for cancer diagnosis

The influence of biomechanics on cell function has become increasingly defined over recent years. Biomechanical changes are known to affect oncogenesis; however, these effects are not yet fully understood. Atomic force microscopy (AFM) is the gold standard method for measuring tissue mechanics on the micro- or nano-scale. Due to its complexity, however, AFM has yet to become integrated in routine clinical diagnosis. Artificial intelligence (AI) and machine learning (ML) have the potential to make AFM more accessible, principally through automation of analysis. In this review, AFM and its use for the assessment of cell and tissue mechanics in cancer is described. Research relating to the application of artificial intelligence and machine learning in the analysis of AFM topography and force spectroscopy of cancer tissue and cells are reviewed. The application of machine learning and artificial intelligence to AFM has the potential to enable the widespread use of nanoscale morphologic and biomechanical features as diagnostic and prognostic biomarkers in cancer treatment.

Incongruous Harmonics of Vibrating Solid-Solid Interface

Deconvoluting the vibrations and harmonics in solid-solid interfaces is crucial for designing materials with improved performance, durability, and functionality. The measured vibrating microcantilever signal in the dynamic atomic force microscopy (AFM) encompasses a multitude of distinct signatures reflecting a diverse array of material properties. Nevertheless, uncertainties persist in decoding these signatures, primarily arising from the interplay between attractive and repulsive forces. Consequently, it is challenging to correlate the generated harmonics within the solid-solid interfaces with the imaged phase and topography of materials, as well as the occasional observed contrast reversal. In this study, the vibration harmonics produced at solid-solid interfaces are correlated, linking them to short-range nano-mechanical characteristics through a comprehensive blend of theory, simulation, and experimental methods. These findings shed light on the roots of harmonic generation and contrast reversals, opening avenues for designing innovative materials with customized properties.

Ex vivo SIM-AFM measurements reveal the spatial correlation of stiffness and molecular distributions in 3D living tissue

Living tissues each exhibit a distinct stiffness, which provides cells with key environmental cues that regulate their behaviors. Despite this significance, our understanding of the spatiotemporal dynamics and the biological roles of stiffness in three-dimensional tissues is currently limited due to a lack of appropriate measurement techniques. To address this issue, we propose a new method combining upright structured illumination microscopy (USIM) and atomic force microscopy (AFM) to obtain precisely coordinated stiffness maps and biomolecular fluorescence images of thick living tissue slices. Using mouse embryonic and adult skin as a representative tissue with mechanically heterogeneous structures inside, we validate the measurement principle of USIM-AFM. Live measurement of tissue stiffness distributions revealed the highly heterogeneous mechanical nature of skin, including nucleated/enucleated epithelium, mesenchyme, and hair follicle, as well as the role of collagens in maintaining its integrity. Furthermore, quantitative analysis comparing stiffness distributions in live tissue samples with those in preserved tissues, including formalin-fixed and cryopreserved tissue samples, unveiled the distinct impacts of preservation processes on tissue stiffness patterns. This series of experiments highlights the importance of live mechanical testing of tissue-scale samples to accurately capture the true spatiotemporal variations in mechanical properties. Our USIM-AFM technique provides a new methodology to reveal the dynamic nature of tissue stiffness and its correlation with biomolecular distributions in live tissues and thus could serve as a technical basis for exploring tissue-scale mechanobiology. STATEMENT OF SIGNIFICANCE: Stiffness, a simple mechanical parameter, has drawn attention in understanding the mechanobiological principles underlying the homeostasis and pathology of living tissues. To explore tissue-scale mechanobiology, we propose a technique integrating an upright structured illumination microscope and an atomic force microscope. This technique enables live measurements of stiffness distribution and fluorescent observation of thick living tissue slices. Experiments revealed the highly heterogeneous mechanical nature of mouse embryonic and adult skin in three dimensions and the previously unnoticed influences of preservation techniques on the mechanical properties of tissue at microscopic resolution. This study provides a new technical platform for live stiffness measurement and biomolecular observation of tissue-scale samples with micron-scale resolution, thus contributing to future studies of tissue- and organ-scale mechanobiology.

Multi-Channel Signals in Dynamic Force-Clamp Mode of Microcantilever Sensors for Detecting Cellular Peripheral Brush

The development of numerous diseases, such as renal cyst, cancer, and viral infection, is closely associated with the pathological changes and defects in the cellular peripheral brush. Therefore, it is necessary to develop a potential new method to detect lesions of cellular peripheral brush. Here, a piecewise linear viscoelastic constitutive model of cell is established considering the joint contribution of the peripheral brush and intra-cellular structure. By combining the Laplace transformation and its inverse transformation, and the differential method in the temporal domain and differential quadrature method (DQM) in the spatial domain, the signal interpretation models for quasi-static and dynamic signals of microcantilever are solved. The influence mechanisms of the peripheral brush on the viscoelastic properties of cells and quasi-static/dynamic signals of microcantilever are clarified. The results not only reveal that the peripheral brush has significant effects on the complex modulus of the cell and multi-channel signals of the microcantilever, but also suggest that an alternative mapping method by collecting multi-channel signals including quasi-static and higher frequency signals with more brush indexes could be potentially used to identify cancerous cells.

Soft glassy rheology of single cells with pathogenic protein aggregates

A correlation between the mechanical properties of cells and various diseases has been emerging in recent years. Atomic force microscopy (AFM) has been widely used to measure a single cell's apparent Young's modulus by treating it as a fully elastic object. More recently, quantitative characterization of the complete viscoelasticity of single cells has become possible. We performed AFM-based nano-indentation experiments on hemocytes isolated from third instar larvae to determine their viscoelasticity and found that live hemocytes, like many other cells, follow a scale-free power-law rheology (PLR) akin to soft glasses. Further, we examined the changes in the rheological response of hemocytes in the presence of pathogenic protein aggregates known to cause neurodegenerative diseases such as Huntington's disorder and amyotrophic lateral sclerosis. Our results show that cells lose their fluidity and appear more solid-like in the presence of certain aggregates, in a manner correlated to actin reorganization. More solid-like cells also display reduced intracellular transport through clathrin-mediated endocytosis (CME). However, the cell's rheology remains largely unaffected and is similar to that of wild-type (WT) hemocytes, if aggregates do not perturb the actin organization and CME. Moreover, the fluid-like nature was significantly recovered when actin organization was rescued by overexpressing specific actin interacting proteins or chaperones. Our study, for the first time, underscores a direct correlation between parameters governing glassy dynamics, actin organization and CME.

Beyond stiffness: Multiscale viscoelastic features as biomechanical markers for assessing cell types and states

Cell mechanics are pivotal in regulating cellular activities, diseases progression, and cancer development. However, the understanding of how cellular viscoelastic properties vary in physiological and pathological stimuli remains scarce. Here, we develop a hybrid self-similar hierarchical theory-microrheology approach to accurately and efficiently characterize cellular viscoelasticity. Focusing on two key cell types associated with livers fibrosis-the capillarized liver sinusoidal endothelial cells and activated hepatic stellate cells-we uncover a universal two-stage power-law rheology characterized by two distinct exponents, αshort and αlong. The mechanical profiles derived from both exponents exhibit significant potential for discriminating among diverse cells. This finding suggests a potential common dynamic creep characteristic across biological systems, extending our earlier observations in soft tissues. Using a tailored hierarchical model for cellular mechanical structures, we discern significant variations in the viscoelastic properties and their distribution profiles across different cell types and states from the cytoplasm (elastic stiffness E1 and viscosity η), to a single cytoskeleton fiber (elastic stiffness E2), and then to the cell level (transverse expansion stiffness E3). Importantly, we construct a logistic-regression-based machine-learning model using the dynamic parameters that outperforms conventional cell-stiffness-based classifiers in assessing cell states, achieving an area under the curve of 97% vs. 78%. Our findings not only advance a robust framework for monitoring intricate cell dynamics but also highlight the crucial role of cellular viscoelasticity in discerning cell states across a spectrum of liver diseases and prognosis, offering new avenues for developing diagnostic and therapeutic strategies based on cellular viscoelasticity.

Critical review of single-cell mechanotyping approaches for biomedical applications

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

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

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

Cell Surface Parameters for Accessing Neutrophil Activation Level with Atomic Force Microscopy

In this study, we examine the topography and adhesion images of the cell surface of neutrophils during the activation process. Our analysis of cell surface parameters indicates that the most significant changes in neutrophils occur within the first 30 min of activation, suggesting that reactive oxygen species may require approximately this amount of time to activate the cells. Interestingly, we observed surface granular structure as early as 10 min after neutrophil activation when examining atomic force microscopy images. This finding aligns with the reorganization observed within the cells under confocal laser scanning microscopy. By analyzing the cell surface images of adhesion, we identified three spatial surface parameters that correlate with the activation time. This finding enables us to estimate the degree of activation by using atomic force microscopy maps of the cell surface.

Eukaryotic CRFK Cells Motion Characterized with Atomic Force Microscopy

We performed a time-lapse imaging with atomic force microscopy (AFM) of the motion of eukaryotic CRFK (Crandell-Rees Feline Kidney) cells adhered onto a glass surface and anchored to other cells in culture medium at 37 °C. The main finding is a gradient in the spring constant of the actomyosin cortex along the cells axis. The rigidity increases at the rear of the cells during motion. This observation as well as a dramatic decrease of the volume suggests that cells may organize a dissymmetry in the skeleton network to expulse water and drive actively the rear edge.

Viscoelastic parameterization of human skin cells characterize material behavior at multiple timescales

Countless biophysical studies have sought distinct markers in the cellular mechanical response that could be linked to morphogenesis, homeostasis, and disease. Here, an iterative-fitting methodology visualizes the time-dependent viscoelastic behavior of human skin cells under physiologically relevant conditions. Past investigations often involved parameterizing elastic relationships and assuming purely Hertzian contact mechanics, which fails to properly account for the rich temporal information available. We demonstrate the performance superiority of the proposed iterative viscoelastic characterization method over standard open-search approaches. Our viscoelastic measurements revealed that 2D adherent metastatic melanoma cells exhibit reduced elasticity compared to their normal counterparts—melanocytes and fibroblasts, and are significantly less viscous than fibroblasts over timescales spanning three orders of magnitude. The measured loss angle indicates clear differential viscoelastic responses across multiple timescales between the measured cells. This method provides insight into the complex viscoelastic behavior of metastatic melanoma cells relevant to better understanding cancer metastasis and aggression.

Parvini, Cartagena and Solares introduce an iterative viscoelastic approach based on the generalized Maxwell and Kelvin-Voigt models. The results showed that metastatic melanoma cells had lower elasticity than normal fibroblasts and melanoma cells were less viscous than the fibroblasts over a large frequency range, enhancing the understanding of cellular responses at different frequencies.

3D nanomechanical mapping of subcellular and sub-nuclear structures of living cells by multi-harmonic AFM with long-tip microcantilevers

Recent developments such as multi-harmonic Atomic Force Microscopy (AFM) techniques have enabled fast, quantitative mapping of nanomechanical properties of living cells. Due to their high spatiotemporal resolution, these methods provide new insights into changes of mechanical properties of subcellular structures due to disease or drug response. Here, we propose three new improvements to significantly improve the resolution, identification, and mechanical property quantification of sub-cellular and sub-nuclear structures using multi-harmonic AFM on living cells. First, microcantilever tips are streamlined using long-carbon tips to minimize long-range hydrodynamic interactions with the cell surface, to enhance the spatial resolution of nanomechanical maps and minimize hydrodynamic artifacts. Second, simultaneous Spinning Disk Confocal Microscopy (SDC) with live-cell fluorescent markers enables the unambiguous correlation between observed heterogeneities in nanomechanical maps with subcellular structures. Third, computational approaches are then used to estimate the mechanical properties of sub-nuclear structures. Results are demonstrated on living NIH 3T3 fibroblasts and breast cancer MDA-MB-231 cells, where properties of nucleoli, a deep intracellular structure, were assessed. The integrated approach opens the door to study the mechanobiology of sub-cellular structures during disease or drug response.

In Vitro Magnetic Techniques for Investigating Cancer Progression

Worldwide, there are currently around 18.1 million new cancer cases and 9.6 million cancer deaths yearly. Although cancer diagnosis and treatment has improved greatly in the past several decades, a complete understanding of the complex interactions between cancer cells and the tumor microenvironment during primary tumor growth and metastatic expansion is still lacking. Several aspects of the metastatic cascade require in vitro investigation. This is because in vitro work allows for a reduced number of variables and an ability to gather real-time data of cell responses to precise stimuli, decoupling the complex environment surrounding in vivo experimentation. Breakthroughs in our understanding of cancer biology and mechanics through in vitro assays can lead to better-designed ex vivo precision medicine platforms and clinical therapeutics. Multiple techniques have been developed to imitate cancer cells in their primary or metastatic environments, such as spheroids in suspension, microfluidic systems, 3D bioprinting, and hydrogel embedding. Recently, magnetic-based in vitro platforms have been developed to improve the reproducibility of the cell geometries created, precisely move magnetized cell aggregates or fabricated scaffolding, and incorporate static or dynamic loading into the cell or its culture environment. Here, we will review the latest magnetic techniques utilized in these in vitro environments to improve our understanding of cancer cell interactions throughout the various stages of the metastatic cascade.

Enabling autonomous scanning probe microscopy imaging of single molecules with deep learning

Scanning probe microscopies allow investigating surfaces at the nanoscale, in real space and with unparalleled signal-to-noise ratio. However, these microscopies are not used as much as it would be expected considering their potential. The main limitations preventing a broader use are the need of experienced users, the difficulty in data analysis and the time-consuming nature of experiments that require continuous user supervision. In this work, we addressed the latter and developed an algorithm that controlled the operation of an Atomic Force Microscope (AFM) that, without the need of user intervention, allowed acquiring multiple high-resolution images of different molecules. We used DNA on mica as a model sample to test our control algorithm, which made use of two deep learning techniques that so far have not been used for real time SPM automation. One was an object detector, YOLOv3, which provided the location of molecules in the captured images. The second was a Siamese network that could identify the same molecule in different images. This allowed both performing a series of images on selected molecules while incrementing the resolution, as well as keeping track of molecules already imaged at high resolution, avoiding loops where the same molecule would be imaged an unlimited number of times. Overall, our implementation of deep learning techniques brings SPM a step closer to full autonomous operation.

Reciprocal regulation of cellular mechanics and metabolism

Metabolism and mechanics are intrinsically intertwined. External forces, sensed through the cytoskeleton or distortion of the cell and organelles, induce metabolic changes in the cell. The resulting changes in metabolism, in turn, feed back to regulate every level of cell biology, including the mechanical properties of cells and tissues. Here we examine the links between metabolism and mechanics, highlighting signalling pathways involved in the regulation and response to cellular mechanosensing. We consider how forces and metabolism regulate one another through nanoscale molecular sensors, micrometre-scale cytoskeletal networks, organelles and dynamic biomolecular condensates. Understanding this cross-talk will create diagnostic and therapeutic opportunities for metabolic disorders such as cancer, cardiovascular pathologies and obesity.

Mechanomics Biomarker for Cancer Cells Unidentifiable through Morphology and Elastic Modulus

Cellular mechanical properties are potential cancer biomarkers used for objective cytology to replace the current subjective method relying on cytomorphology. However, heterogeneity among intra/intercellular mechanics and the interplay between cytoskeletal prestress and elastic modulus obscured the difference detectable between malignant and benign cells. In this work, we collected high density nanoscale prestress and elastic modulus data from a single cell by AFM indentation to generate a cellular mechanome. Such high dimensional mechanome data was used to train a malignancy classifier through machine learning. The classifier was tested on 340 single cells of various origins, malignancy, and degrees of similarity in morphology and elastic modulus. The classifier showed instrument-independent robustness and classification accuracy of 89% with an AUC-ROC value of 93%. A signal-to-noise ratio 8 times that of the human-cytologist-based morphological method was also demonstrated, in differentiating precancerous hyperplasia cells from normal cells derived from the same lung cancer patient.

Mapping mechanical properties of biological materials via an add-on Brillouin module to confocal microscopes

Several techniques have been developed over the past few decades to assess the mechanical properties of biological samples, which has fueled a rapid growth in the fields of biophysics, bioengineering, and mechanobiology. In this context, Brillouin optical spectroscopy has long been known as an intriguing modality for noncontact material characterization. However, limited by speed and sample damage, it had not translated into a viable imaging modality for biomedically relevant materials. Recently, based on a novel spectroscopy strategy that substantially improves the speed of Brillouin measurement, confocal Brillouin microscopy has emerged as a unique complementary tool to traditional methods as it allows noncontact, nonperturbative, label-free measurements of material mechanical properties. The feasibility and potential of this innovative technique at both the cell and tissue level have been extensively demonstrated over the past decade. As Brillouin technology is rapidly recognized, a standard approach for building and operating Brillouin microscopes is required to facilitate the widespread adoption of this technology. In this protocol, we aim to establish a robust approach for instrumentation, and data acquisition and analysis. By carefully following this protocol, we expect that a Brillouin instrument can be built in 5-9 days by a person with basic optics knowledge and alignment experience; the data acquisition as well as postprocessing can be accomplished within 2-8 h.

Data acquisition and imaging using wavelet transform: a new path for high speed transient force microscopy

The unique ability of Atomic Force Microscopy (AFM) to image, manipulate and characterize materials at the nanoscale has made it a remarkable tool in nanotechnology. In dynamic AFM, acquisition and processing of the photodetector signal originating from probe-sample interaction is a critical step in data analysis and measurements. However, details of such interaction including its nonlinearity and dynamics of the sample surface are limited due to the ultimately bounded bandwidth and limited time scales of data processing electronics of standard AFM. Similarly, transient details of the AFM probe's cantilever signal are lost due to averaging of data by techniques which correlate the frequency spectrum of the captured data with a temporally invariant physical system. Here, we introduce a fundamentally new approach for dynamic AFM data acquisition and imaging based on applying the wavelet transform on the data stream from the photodetector. This approach provides the opportunity for exploration of the transient response of the cantilever, analysis and imaging of the dynamics of amplitude and phase of the signals captured from the photodetector. Furthermore, it can be used for the control of AFM which would yield increased imaging speed. Hence the proposed method opens a pathway for high-speed transient force microscopy.

Viscoelasticity and Volume of Cortical Neurons under Glutamate Excitotoxicity and Osmotic Challenges

Neural activity depends on the maintenance of ionic and osmotic homeostasis. Under these conditions, the cell volume must be regulated to maintain optimal neural function. A disturbance in the neuronal volume regulation often occurs in pathological conditions such as glutamate excitotoxicity. The cell volume, mechanical properties, and actin cytoskeleton structure are tightly connected to achieve the cell homeostasis. Here, we studied the effects of glutamate-induced excitotoxicity, external osmotic pressure, and inhibition of actin polymerization on the viscoelastic properties and volume of neurons. Atomic force microscopy was used to map the viscoelastic properties of neurons in time-series experiments to observe the dynamical changes and a possible recovery. The data obtained on cultured rat cortical neurons were compared with the data obtained on rat fibroblasts. The neurons were found to be more responsive to the osmotic challenges but less sensitive to the inhibition of actin polymerization than fibroblasts. The alterations of the viscoelastic properties caused by glutamate excitotoxicity were similar to those induced by the hypoosmotic stress, but, in contrast to the latter, they did not recover after the glutamate removal. These data were consistent with the dynamic volume changes estimated using ratiometric fluorescent dyes. The recovery after the glutamate-induced excitotoxicity was slow or absent because of a steady increase in intracellular calcium and sodium concentrations. The viscoelastic parameters and their changes were related to such parameters as the actin cortex stiffness, tension, and cytoplasmic viscosity.

Viscoelasticity in simple indentation-cycle experiments: a computational study

Instrumented indentation has become an indispensable tool for quantitative analysis of the mechanical properties of soft polymers and biological samples at different length scales. These types of samples are known for their prominent viscoelastic behavior, and attempts to calculate such properties from the indentation data are constantly made. The simplest indentation experiment presents a cycle of approach (deepening into the sample) and retraction of the indenter, with the output of the force and indentation depth as functions of time and a force versus indentation dependency (force curve). The linear viscoelastic theory based on the elastic–viscoelastic correspondence principle might predict the shape of force curves based on the experimental conditions and underlying relaxation function of the sample. Here, we conducted a computational analysis based on this theory and studied how the force curves were affected by the indenter geometry, type of indentation (triangular or sinusoidal ramp), and the relaxation functions. The relaxation functions of both traditional and fractional viscoelastic models were considered. The curves obtained from the analytical solutions, numerical algorithm and finite element simulations matched each other well. Common trends for the curve-related parameters (apparent Young’s modulus, normalized hysteresis area, and curve exponent) were revealed. Importantly, the apparent Young’s modulus, obtained by fitting the approach curve to the elastic model, demonstrated a direct relation to the relaxation function for all the tested cases. The study will help researchers to verify which model is more appropriate for the sample description without extensive calculations from the basic curve parameters and their dependency on the indentation rate.

Nanomechanical mapping of soft materials with the atomic force microscope: methods, theory and applications

Fast, high-resolution, non-destructive and quantitative characterization methods are needed to develop materials with tailored properties at the nanoscale or to understand the relationship between mechanical properties and cell physiology. This review introduces the state-of-the-art force microscope-based methods to map at high-spatial resolution the elastic and viscoelastic properties of soft materials. The experimental methods are explained in terms of the theories that enable the transformation of observables into material properties. Several applications in materials science, molecular biology and mechanobiology illustrate the scope, impact and potential of nanomechanical mapping methods.

Wideband Magnetic Excitation System for Atomic Force Microscopy Cantilevers with Megahertz-Order Resonance Frequency

Small cantilevers with a megahertz-order resonance frequency provide excellent sensitivity and speed in liquid-environment atomic force microscopy (AFM). However, stable and accurate oscillation control of a small cantilever requires the photothermal excitation, which has hindered their applications to the studies on photo-sensitive materials. Here, we develop a magnetic excitation system with a bandwidth wider than 4 MHz, enabling a light-free excitation of small cantilevers. In the system, a cantilever with a magnetic bead is driven by a magnetic field generated by a coil. In the coil driver, a differentiation circuit is used for compensating the frequency dependence of the coil impedance and keeping the current constant. By implementing several differentiation circuits with different frequency ranges, we enable to drive various cantilevers having different resonance frequencies with sufficient excitation efficiency. In contrast to the conventional coil driver with a closed-loop circuit, the developed one consists of an open-loop circuit and hence can be stably operated regardless of the coil design. With the developed system, atomic-resolution imaging of mica in liquid using a small cantilever with a megahertz-order resonance frequency is demonstrated. This development should lead to the future applications of AFM with small cantilevers to the studies on various photo-sensitive materials and phenomena.

Nanorheology of living cells measured by AFM-based force-distance curves

Mechanobiology aims to establish functional relationships between the mechanical state of a living a cell and its physiology. The acquisition of force-distance curves with an AFM is by far the dominant method to characterize the nanomechanical properties of living cells. However, theoretical simulations have shown that the contact mechanics models used to determine the Young's modulus from a force-distance curve could be off by a factor 5 from its expected value. The semi-quantitative character arises from the lack of a theory that integrates the AFM data, a realistic viscoelastic model of a cell and its finite-thickness. Here, we develop a method to determine the mechanical response of a cell from a force-distance curve. The method incorporates bottom-effect corrections, a power-law rheology model and the deformation history of the cell. It transforms the experimental data into viscoelastic parameters of the cell as a function of the indentation frequency. The quantitative agreement obtained between the experiments performed on living fibroblast cells and the analytical theory supports the use of force-distance curves to measure the nanorheological properties of cells.

Digging deeper: structural background of PEGylated fibrin gels in cell migration and lumenogenesis

Fibrin is a well-known tool in tissue engineering, but the structure of its modifications created to improve its properties remains undiscussed despite its importance, e.g. in designing biomaterials that ensure cell migration and lumenogenesis. We sought to uncover the structural aspects of PEGylated fibrin hydrogels shown to contribute to angiogenesis. The analysis of the small-angle X-ray scattering (SAXS) data and ab initio modeling revealed that the PEGylation of fibrinogen led to the formation of oligomeric species, which are larger at a higher PEG : fibrinogen molar ratio. The improvement of optical properties was provided by the decrease in aggregates' sizes and also by retaining the bound water. Compared to the native fibrin, the structure of the 5 : 1 PEGylated fibrin gel consisted of homogenously distributed flexible fibrils with a smaller space between them. Moreover, as arginylglycylaspartic acid (RGD) sites may be partly bound to PEG-NHS or masked because of the oligomerization, the number of adhesion sites may be slightly reduced that may provide the better cell migration and formation of continuous capillary-like structures.

Global mapping of live cell mechanical features using PeakForce QNM AFM

Atomic force microscopy (AFM) has been widely used to acquire surface topography upon different scanning modes and to quantify mechanical properties of a cell using single-point ramp force mode. However, these traditional measurements need massive force curves originating from multiple points of a cell to exclude the potential errors resulted from limited and factitious selections of testing points, making the measurements time-consuming and highly localized. PeakForce Quantitative NanoMechanics (PF QNM) is a high-speed (faster by 3–4 order of magnitude) and global surface mechanical property mapping method with high spatial resolution, overcoming the drawbacks of traditional ramp mode especially used for a live cell with high heterogeneity. In this protocol, we elaborated how to run PF QNM measurements for live cells and relevant modification may be needed when extending this method to other cell-like soft materials.

Measuring viscoelasticity of soft biological samples using atomic force microscopy

Mechanical properties play important roles at different scales in biology. At the level of a single cell, the mechanical properties mediate mechanosensing and mechanotransduction, while at the tissue and organ levels, changes in mechanical properties are closely connected to disease and physiological processes. Over the past three decades, atomic force microscopy (AFM) has become one of the most widely used tools in the mechanical characterization of soft samples, ranging from molecules, cell organoids and cells to whole tissue. AFM methods can be used to quantify both elastic and viscoelastic properties, and significant recent developments in the latter have been enabled by the introduction of new techniques and models for data analysis. Here, we review AFM techniques developed in recent years for examining the viscoelastic properties of cells and soft gels, describe the main steps in typical data acquisition and analysis protocols, and discuss relevant viscoelastic models and how these have been used to characterize the specific features of cellular and other biological samples. We also discuss recent trends and potential directions for this field.

Viscoelastic mapping of cells based on fast force volume and PeakForce Tapping

Development of fast force volume (FFV), PeakForce Tapping (PFT), and related AFM techniques allow fast acquisition and mapping of a sample's mechanical properties. The methods are well-suited for studying soft biological samples like living cells in a liquid environment. However, the question remains how the measured mechanical properties are related to those acquired with the classical force volume (FV) technique conducted at low indentation rates. The difference is coming mostly from the pronounced viscoelastic behavior of cells, making apparent elastic parameters depending on the probing rate. Here, the viscoelastic analysis was applied directly to the force curves acquired with force volume or PeakForce Tapping by their post-processing based on the Ting's model. Maps from classical force volume, FFV and PFT obtained using special PFT cantilevers and cantilevers modified with microspheres were compared here. With the correct viscoelastic model, which was found to be the power-law rheology model, all the techniques have provided self-consistent results. The techniques were further modified for the mapping of the viscoelastic model-independent complex Young's modulus.

Resveratrol-Induced Temporal Variation in the Mechanical Properties of MCF-7 Breast Cancer Cells Investigated by Atomic Force Microscopy

Atomic force microscopy (AFM) combined with fluorescence microscopy has been used to quantify cytomechanical modifications induced by resveratrol (at a fixed concentration of 50 µM) in a breast cancer cell line (MCF-7) upon temporal variation. Cell indentation methodology has been utilized to determine simultaneous variations of Young's modulus, the maximum adhesion force, and tether formation, thereby determining cell motility and adhesiveness. Effects of treatment were measured at several time-points (0-6 h, 24 h, and 48 h); longer exposures resulted in cell death. Our results demonstrated that AFM can be efficiently used as a diagnostic tool to monitor irreversible morpho/nano-mechanical changes in cancer cells during the early steps of drug treatment.

Application of atomic force microscopy in cancer research

Atomic force microscopy (AFM) allows for nanometer-scale investigation of cells and molecules. Recent advances have enabled its application in cancer research and diagnosis. The physicochemical properties of live cells undergo changes when their physiological conditions are altered. These physicochemical properties can therefore reflect complex physiological processes occurring in cells. When cells are in the process of carcinogenesis and stimulated by external stimuli, their morphology, elasticity, and adhesion properties may change. AFM can perform surface imaging and ultrastructural observation of live cells with atomic resolution under near-physiological conditions, collecting force spectroscopy information which allows for the study of the mechanical properties of cells. For this reason, AFM has potential to be used as a tool for high resolution research into the ultrastructure and mechanical properties of tumor cells. This review describes the working principle, working mode, and technical points of atomic force microscopy, and reviews the applications and prospects of atomic force microscopy in cancer research.