Biomechanical Heterogeneity of Living Cells: Comparison between Atomic Force Microscopy and Finite Element Simulation

Biomechanics of Macrophages on Disordered Surface Nanotopography

Macrophages are involved in every stage of the innate/inflammatory immune responses in the body tissues, including the resolution of the reaction, and they do so in close collaboration with the extracellular matrix (ECM). Simplified substrates with nanotopographical features attempt to mimic the structural properties of the ECM to clarify the functional features of the interaction of the ECM with macrophages. We still have a limited understanding of the macrophage behavior upon interaction with disordered nanotopography, especially with features smaller than 10 nm. Here, we combine atomic force microscopy (AFM), finite element modeling (FEM), and quantitative biochemical approaches in order to understand the mechanotransduction from the nanostructured surface into cellular responses. AFM experiments show a decrease of macrophage stiffness, measured with the Young's modulus, as a biomechanical response to a nanostructured (ns-) ZrOx surface. FEM experiments suggest that ZrOx surfaces with increasing roughness represent weaker mechanical boundary conditions. The mechanical cues from the substrate are transduced into the cell through the formation of integrin-regulated focal adhesions and cytoskeletal reorganization, which, in turn, modulate cell biomechanics by downregulating cell stiffness. Surface nanotopography and consequent biomechanical response impact the overall behavior of macrophages by increasing movement and phagocytic ability without significantly influencing their inflammatory behavior. Our study suggests a strong potential of surface nanotopography for the regulation of macrophage functions, which implies a prospective application relative to coating technology for biomedical devices.

Data-Driven and Cell-Specific Determination of Nuclei-Associated Actin Structure

Quantitative and volumetric assessment of filamentous actin fibers (F-actin) remains challenging due to their interconnected nature, leading researchers to utilize threshold based or qualitative measurement methods with poor reproducibility. Here we introduce a novel machine learning based methodology for accurate quantification and reconstruction of nuclei-associated F-actin. Utilizing a Convolutional Neural Network (CNN), we segment actin filaments and nuclei from 3D confocal microscopy images and then reconstruct each fiber by connecting intersecting contours on cross-sectional slices. This allowed measurement of the total number of actin filaments and individual actin filament length and volume in a reproducible fashion. Focusing on the role of F-actin in supporting nucleocytoskeletal connectivity, we quantified apical F-actin, basal F-actin, and nuclear architecture in mesenchymal stem cells (MSCs) following the disruption of the Linker of Nucleoskeleton and Cytoskeleton (LINC) Complexes. Disabling LINC in mesenchymal stem cells (MSCs) generated F-actin disorganization at the nuclear envelope characterized by shorter length and volume of actin fibers contributing a less elongated nuclear shape. Our findings not only present a new tool for mechanobiology but introduce a novel pipeline for developing realistic computational models based on quantitative measures of F-actin.

Atomic force microscopy in disease-related studies: Exploring tissue and cell mechanics

Despite significant progress in human medicine, certain diseases remain challenging to promptly diagnose and treat. Hence, the imperative lies in the development of more exhaustive criteria and tools. Tissue and cellular mechanics exhibit distinctive traits in both normal and pathological states, suggesting that "force" represents a promising and distinctive target for disease diagnosis and treatment. Atomic force microscopy (AFM) holds great promise as a prospective clinical medical device due to its capability to concurrently assess surface morphology and mechanical characteristics of biological specimens within a physiological setting. This review presents a comprehensive examination of the operational principles of AFM and diverse mechanical models, focusing on its applications in investigating tissue and cellular mechanics associated with prevalent diseases. The findings from these studies lay a solid groundwork for potential clinical implementations of AFM. RESEARCH HIGHLIGHTS: By examining the surface morphology and assessing tissue and cellular mechanics of biological specimens in a physiological setting, AFM shows promise as a clinical device to diagnose and treat challenging diseases.

Deep learning strategy for small dataset from atomic force microscopy mechano-imaging on macrophages phenotypes

The cytoskeleton is involved during movement, shaping, resilience, and functionality in immune system cells. Biomarkers such as elasticity and adhesion can be promising alternatives to detect the status of cells upon phenotype activation in correlation with functionality. For instance, professional immune cells such as macrophages undergo phenotype functional polarization, and their biomechanical behaviors can be used as indicators for early diagnostics. For this purpose, combining the biomechanical sensitivity of atomic force microscopy (AFM) with the automation and performance of a deep neural network (DNN) is a promising strategy to distinguish and classify different activation states. To resolve the issue of small datasets in AFM-typical experiments, nanomechanical maps were divided into pixels with additional localization data. On such an enlarged dataset, a DNN was trained by multimodal fusion, and the prediction was obtained by voting classification. Without using conventional biomarkers, our algorithm demonstrated high performance in predicting the phenotype of macrophages. Moreover, permutation feature importance was employed to interpret the results and unveil the importance of different biophysical properties and, in turn, correlated this with the local density of the cytoskeleton. While our results were demonstrated on the RAW264.7 model cell line, we expect that our methodology could be opportunely customized and applied to distinguish different cell systems and correlate feature importance with biophysical properties to unveil innovative markers for diagnostics.

The effect of the properties of cell nucleus and underlying substrate on the response of finite element models of astrocytes undergoing mechanical stimulations

Astrocyte cells play a critical role in the mechanical behaviour of the brain tissue; hence understanding the properties of Astrocytes is a big step toward understanding brain diseases and abnormalities. Conventionally, atomic force microscopy (AFM) has been used as one of the most powerful tools to characterize the mechanical properties of cells. However, due to the complexities of experimental work and the complex behaviour of living cells, the finite element method (FEM) is commonly used to estimate the cells' response to mechanical stimulations. In this study, we developed a finite element model of the Astrocyte cells to investigate the effect of two key parameters that could affect the response of the cell to mechanical loading; the properties of the underlying substrate and the nucleus. In this regard, the cells were placed on two different substrates in terms of thickness and stiffness (gel and glass) with varying properties of the nucleus. The main achievement of this study was to develop an insight to investigate the response of the Astrocytes to mechanical loading for future studies, both experimentally and computationally.

A Review of the Development and Challenges of Cell Mechanical Models

Cell models can express a variety of cell information, including mechanical properties, electrical properties, and chemical properties. Through the analysis of these properties, we can fully understand the physiological state of cells. As such, cell modeling has gradually become a topic of great interest, and a number of cell models have been established over the last few decades. In this paper, the development of various cell mechanical models has been systematically reviewed. First, continuum theoretical models, which were established by ignoring cell structures, are summarized, including the cortical membrane droplet model, solid model, power series structure damping model, multiphase model, and finite element model. Next, microstructural models based on the structure and function of cells are summarized, including the tension integration model, porous solid model, hinged cable net model, porous elastic model, energy dissipation model, and muscle model. What's more, from multiple viewpoints, the strengths and weaknesses of each cell mechanical model have been analyzed in detail. Finally, the potential challenges and applications in the development of cell mechanical models are discussed. This paper contributes to the development of different fields, such as biological cytology, drug therapy, and bio-syncretic robots.

Cells-in-Touch: 3D Printing in Reconstruction and Modelling of Microscopic Biological Geometries for Education and Future Research Applications

Additive manufacturing (3D printing) and computer-aided design (CAD) still have limited uptake in biomedical and bioengineering research and education, despite the significant potential of these technologies. The utility of organ-scale 3D-printed models of living structures is widely appreciated, while the workflows for microscopy data translation into tactile accessible replicas are not well developed yet. Here, we demonstrate an accessible and reproducible CAD-based methodology for generating 3D-printed scalable models of human cells cultured in vitro and imaged using conventional scanning confocal microscopy with fused deposition modeling (FDM) 3D printing. We termed this technology CiTo-3DP (Cells-in-Touch for 3D Printing). As a proof-of-concept, we created dismountable CiTo-3DP models of human epithelial, mesenchymal, and neural cells by using selectively stained nuclei and cytoskeletal components. We also provide educational and research context for the presented cellular models. In the future, the CiTo-3DP approach can be adapted to different imaging and 3D printing modalities and comprehensively present various cell types, subcellular structures, and extracellular matrices. The resulting CAD and 3D printed models could be used for a broad spectrum of education and research applications.

Data driven and cell specific determination of nuclei-associated actin structure

Quantitative and volumetric assessment of filamentous actin fibers (F-actin) remains challenging due to their interconnected nature, leading researchers to utilize threshold based or qualitative measurement methods with poor reproducibility. Here we introduce a novel machine learning based methodology for accurate quantification and reconstruction of nuclei-associated F-actin. Utilizing a Convolutional Neural Network (CNN), we segment actin filaments and nuclei from 3D confocal microscopy images and then reconstruct each fiber by connecting intersecting contours on cross-sectional slices. This allowed measurement of the total number of actin filaments and individual actin filament length and volume in a reproducible fashion. Focusing on the role of F-actin in supporting nucleocytoskeletal connectivity, we quantified apical F-actin, basal F-actin, and nuclear architecture in mesenchymal stem cells (MSCs) following the disruption of the Linker of Nucleoskeleton and Cytoskeleton (LINC) Complexes. Disabling LINC in mesenchymal stem cells (MSCs) generated F-actin disorganization at the nuclear envelope characterized by shorter length and volume of actin fibers contributing a less elongated nuclear shape. Our findings not only present a new tool for mechanobiology but introduce a novel pipeline for developing realistic computational models based on quantitative measures of F-actin.

A study of macrophage mechanical properties and functional modulation based on the Young's modulus of PLGA-PEG fibers

The immune response of macrophages plays an important role in defending against viral infection, tumor deterioration and repairing of contused tissue. Macrophage functional differentiation induced by nanodrugs is the leading edge of current research, but nanodrugs have toxic side effects, and the influence of their physical properties on macrophages is not clear. Here we create an alternative way to modulate macrophage function through PLGA-PEG fibers' Young's modulus. Previously, we revealed that by controlling the Young's modulus of the fibers from kPa to MPa, all the fibers entered murine macrophage cells (RWA 264.7) in a similar manner, and based on that, we found that macrophages' mechanical properties were affected by the fibers' Young's modulus, that is, hard fibers with a Young's modulus of ∼1 MPa increased the cell average Young's modulus, but did not affect the cell shape, while soft fibers with a Young's modulus of ∼100 kPa decreased the cell average Young's modulus and modulated the cell shape to a more spherical one. On the other hand, only the soft fibers induced proinflammatory cytokine secretion, indicating an M1 macrophage functional modulation by low Young's modulus fibers. This study explored the mechanical properties of the interactions between PLGA-PEG fibers and cells, in particular, when guiding the direction of the modulation of macrophage function, which is of great significance for the applications of material biology in the biomedical field.

Nuclear lamin isoforms differentially contribute to LINC complex-dependent nucleocytoskeletal coupling and whole-cell mechanics

Interactions between the cell nucleus and cytoskeleton regulate cell mechanics and are facilitated by the interplay between the nuclear lamina and linker of nucleoskeleton and cytoskeleton (LINC) complexes. To date, the specific contribution of the four lamin isoforms to nucleocytoskeletal connectivity and whole-cell mechanics remains unknown. We discover that A- and B-type lamins distinctively interact with LINC complexes that bind F-actin and vimentin filaments to differentially modulate cortical stiffness, cytoplasmic stiffness, and contractility of mouse embryonic fibroblasts (MEFs). We propose and experimentally verify an integrated lamin–LINC complex–cytoskeleton model that explains cellular mechanical phenotypes in lamin-deficient MEFs. Our findings uncover potential mechanisms for cellular defects in human laminopathies and many cancers associated with mutations or modifications in lamin isoforms.

The ability of a cell to regulate its mechanical properties is central to its function. Emerging evidence suggests that interactions between the cell nucleus and cytoskeleton influence cell mechanics through poorly understood mechanisms. Here we conduct quantitative confocal imaging to show that the loss of A-type lamins tends to increase nuclear and cellular volume while the loss of B-type lamins behaves in the opposite manner. We use fluorescence recovery after photobleaching, atomic force microscopy, optical tweezer microrheology, and traction force microscopy to demonstrate that A-type lamins engage with both F-actin and vimentin intermediate filaments (VIFs) through the linker of nucleoskeleton and cytoskeleton (LINC) complexes to modulate cortical and cytoplasmic stiffness as well as cellular contractility in mouse embryonic fibroblasts (MEFs). In contrast, we show that B-type lamins predominantly interact with VIFs through LINC complexes to regulate cytoplasmic stiffness and contractility. We then propose a physical model mediated by the lamin–LINC complex that explains these distinct mechanical phenotypes (mechanophenotypes). To verify this model, we use dominant negative constructs and RNA interference to disrupt the LINC complexes that facilitate the interaction of the nucleus with the F-actin and VIF cytoskeletons and show that the loss of these elements results in mechanophenotypes like those observed in MEFs that lack A- or B-type lamin isoforms. Finally, we demonstrate that the loss of each lamin isoform softens the cell nucleus and enhances constricted cell migration but in turn increases migration-induced DNA damage. Together, our findings uncover distinctive roles for each of the four major lamin isoforms in maintaining nucleocytoskeletal interactions and cellular mechanics.

Force Sensing on Cells and Tissues by Atomic Force Microscopy

Biosensors are aimed at detecting tiny physical and chemical stimuli in biological systems. Physical forces are ubiquitous, being implied in all cellular processes, including cell adhesion, migration, and differentiation. Given the strong interplay between cells and their microenvironment, the extracellular matrix (ECM) and the structural and mechanical properties of the ECM play an important role in the transmission of external stimuli to single cells within the tissue. Vice versa, cells themselves also use self-generated forces to probe the biophysical properties of the ECM. ECM mechanics influence cell fate, regulate tissue development, and show peculiar features in health and disease conditions of living organisms. Force sensing in biological systems is therefore crucial to dissecting and understanding complex biological processes, such as mechanotransduction. Atomic Force Microscopy (AFM), which can both sense and apply forces at the nanoscale, with sub-nanonewton sensitivity, represents an enabling technology and a crucial experimental tool in biophysics and mechanobiology. In this work, we report on the application of AFM to the study of biomechanical fingerprints of different components of biological systems, such as the ECM, the whole cell, and cellular components, such as the nucleus, lamellipodia and the glycocalyx. We show that physical observables such as the (spatially resolved) Young's Modulus (YM) of elasticity of ECMs or cells, and the effective thickness and stiffness of the glycocalyx, can be quantitatively characterized by AFM. Their modification can be correlated to changes in the microenvironment, physio-pathological conditions, or gene regulation.

Modeling stem cell nucleus mechanics using confocal microscopy

Nuclear mechanics is emerging as a key component of stem cell function and differentiation. While changes in nuclear structure can be visually imaged with confocal microscopy, mechanical characterization of the nucleus and its sub-cellular components require specialized testing equipment. A computational model permitting cell-specific mechanical information directly from confocal and atomic force microscopy of cell nuclei would be of great value. Here, we developed a computational framework for generating finite element models of isolated cell nuclei from multiple confocal microscopy scans and simple atomic force microscopy (AFM) tests. Confocal imaging stacks of isolated mesenchymal stem cells were converted into finite element models and siRNA-mediated Lamin A/C depletion isolated chromatin and Lamin A/C structures. Using AFM-measured experimental stiffness values, a set of conversion factors were determined for both chromatin and Lamin A/C to map the voxel intensity of the original images to the element stiffness, allowing the prediction of nuclear stiffness in an additional set of other nuclei. The developed computational framework will identify the contribution of a multitude of sub-nuclear structures and predict global nuclear stiffness of multiple nuclei based on simple nuclear isolation protocols, confocal images and AFM tests.

The viscoelasticity of adherent cells follows a single power-law with distinct local variations within a single cell and across cell lines

AFM-based force-distance curves are commonly used to characterize the nanomechanical properties of live cells. The transformation of these curves into nanomechanical properties requires the development of contact mechanics models. Spatially-resolved force-distance curves involving 1 to 2 μm deformations were obtained on HeLa and NIH 3T3 (fibroblast) cells. An elastic and two viscoelastic models were used to describe the experimental force-distance curves. The best agreement was obtained by applying a contact mechanics model that accounts for the geometry of the contact and the finite-thickness of the cell and assumes a single power-law dependence with time. Our findings show the shortcomings of elastic and semi-infinite viscoelastic models to characterize the mechanical response of a mammalian cell under micrometer-scale deformations. The parameters of the 3D power-law viscoelastic model, compressive modulus and fluidity exponent showed local variations within a single cell and across the two cell lines. The corresponding nanomechanical maps revealed structures that were not visible in the AFM topographic maps.

Auxeticity in biosystems: an exemplification of its effects on the mechanobiology of heterogeneous living cells

Auxeticity (negative Poisson's ratio) is the unique mechanical property found in an extensive variety of materials, such as metals, graphene, composites, polymers, foams, fibers, ceramics, zeolites, silicates and biological tissues. The enhanced mechanical features of the auxetic materials have motivated scientists to design, engineer and manufacture man-made auxetic materials to fully leverage their capabilities in different fields of research applications, including aeronautics, medical, protective equipments, smart sensors, filter cleaning, and so on. Atomic force microscopy (AFM) indentation is one of the most widely used methods for characterizing the mechanical properties and response of the living cells. In this contribution, we highlight main consequences of auxeticity for biosystems and provide a representative example to quantify the effect of nucleus auxeticity on the force response of the embryonic stem cells. A parametric study has been conducted on a heterogeneous stem cell to evaluate the effect of nucleus diameter, nucleus elasticity, indenter's shape and location on the force-indentation curve. The developed model has also been validated with the recently reported experimental studies available in the literature. Our results suggest that the nucleus auxeticity plays a profound role in cell mechanics especially for large size nucleus. We also report the mechanical stresses induced within the hyperelastic cell model under different loading conditions that would be quite useful in decoding the interrelations between mechanical stimuli and cellular behavior of auxetic biosystems. Finally, current and potential areas of applications of our findings for regenerative therapies, tissue engineering, 3 D/4D bioprinting, and the development of meta-biomaterials are discussed.

Unveiling a Hidden Event in Fluorescence Correlative Microscopy by AFM Nanomechanical Analysis

Fluorescent imaging combined with atomic force microscopy (AFM), namely AFM-fluorescence correlative microscopy, is a popular technology in life science. However, the influence of involved fluorophores on obtained mechanical information is normally underestimated, and such subtle changes are still challenging to detect. Herein, we combined AFM with laser light excitation to perform a mechanical quantitative analysis of a model membrane system labeled with a commonly used fluorophore. Mechanical quantification was additionally validated by finite element simulations. Upon staining, we noticed fluorophores forming a diffuse weakly organized overlayer on phospholipid supported membrane, easily detected by AFM mechanics. The laser was found to cause a degradation of mechanical stability of the membrane synergically with presence of fluorophore. In particular, a 30 min laser irradiation, with intensity similar to that in typical confocal scanning microscopy experiment, was found to result in a ∼40% decrease in the breakthrough force of the stained phospholipid bilayer along with a ∼30% reduction in its apparent elastic modulus. The findings highlight the significance of analytical power provided by AFM, which will allow us to “see” the “unseen” in correlative microscopy, as well as the necessity to consider photothermal effects when using fluorescent dyes to investigate, for example, the deformability and permeability of phospholipid membranes.

Tools for computational analysis of moving boundary problems in cellular mechanobiology

A cell's ability to change shape is one of the most fundamental biological processes and is essential for maintaining healthy organisms. When the ability to control shape goes awry, it often results in a diseased system. As such, it is important to understand the mechanisms that allow a cell to sense and respond to its environment so as to maintain cellular shape homeostasis. Because of the inherent complexity of the system, computational models that are based on sound theoretical understanding of the biochemistry and biomechanics and that use experimentally measured parameters are an essential tool. These models involve an inherent feedback, whereby shape is determined by the action of regulatory signals whose spatial distribution depends on the shape. To carry out computational simulations of these moving boundary problems requires special computational techniques. A variety of alternative approaches, depending on the type and scale of question being asked, have been used to simulate various biological processes, including cell motility, division, mechanosensation, and cell engulfment. In general, these models consider the forces that act on the system (both internally generated, or externally imposed) and the mechanical properties of the cell that resist these forces. Moving forward, making these techniques more accessible to the non-expert will help improve interdisciplinary research thereby providing new insight into important biological processes that affect human health. This article is categorized under: Cancer > Cancer>Computational Models Cancer > Cancer>Molecular and Cellular Physiology.

Spatially Resolved Correlation between Stiffness Increase and Actin Aggregation around Nanofibers Internalized in Living Macrophages

Plasticity and functional diversity of macrophages play an important role in resisting pathogens invasion, tumor progression and tissue repair. At present, nanodrug formulations are becoming increasingly important to induce and control the functional diversity of macrophages. In this framework, the internalization process of nanodrugs is co-regulated by a complex interplay of biochemistry, cell physiology and cell mechanics. From a biophysical perspective, little is known about cellular mechanics’ modulation induced by the nanodrug carrier’s internalization. In this study, we used the polylactic-co-glycolic acid (PLGA)–polyethylene glycol (PEG) nanofibers as a model drug carrier, and we investigated their influence on macrophage mechanics. Interestingly, the nanofibers internalized in macrophages induced a local increase of stiffness detected by atomic force microscopy (AFM) nanomechanical investigation. Confocal laser scanning microscopy revealed a thickening of actin filaments around nanofibers during the internalization process. Following geometry and mechanical properties by AFM, indentation experiments are virtualized in a finite element model simulation. It turned out that it is necessary to include an additional actin wrapping layer around nanofiber in order to achieve similar reaction force of AFM experiments, consistent with confocal observation. The quantitative investigation of actin reconfiguration around internalized nanofibers can be exploited to develop novel strategies for drug delivery.

Altered mechanics of vaginal smooth muscle cells due to the lysyl oxidase-like1 knockout

The remodeling mechanisms that cause connective tissue of the vaginal wall, consisting mostly of smooth muscle, to weaken after vaginal delivery are not fully understood. Abnormal remodeling after delivery can contribute to development of pelvic organ prolapse and other pelvic floor disorders. The present study used vaginal smooth muscle cells (vSMCs) isolated from knockout mice lacking the expression of the lysyl oxidase-like1 (LOXL1) enzyme, a well-characterized animal model for pelvic organ prolapse. We tested if vaginal smooth muscle cells from LOXL1 knockout mice have altered mechanics including stiffness and surface adhesion. Using atomic force microscopy, we performed nanoindentations on both isolated and confluent cells to evaluate the effect of LOXL1 knockout on in vitro cultures of vSMCs cells from nulliparous mice. The results show that LOXL1 knockout vSMCs have increased stiffness in pre-confluent but decreased stiffness in confluent cultures (p* < 0.05) and significant decreased surface adhesion in pre-confluent cultures (p* < 0.05). This study provides evidence that the weakening of vaginal connective tissue in the absense of LOXL1 changes the mechanical properties of the vSMCs. STATEMENT OF SIGNIFICANCE: Pelvic organ prolapse is a common condition affecting millions of women worldwide, which significantly impacts their quality of life. Alterations in vaginal and pelvic floor mechanical properties can change their ability to support the pelvic organs. This study provides evidence of altered stiffness of vaginal smooth muscle cells from mice resembling pelvic organ prolapse. The results from this study set a foundation to develop pathophysiology-driven therapies focused on the interplay between smooth muscle mechanics and extracellular matrix remodeling.

Dynamic indentation reveals differential viscoelastic properties of white matter versus gray matter-derived astrocytes upon treatment with lipopolysaccharide

Astrocytes in white matter (WM) and gray matter (GM) brain regions have been reported to have different morphology and function. Previous single cell biomechanical studies have not differentiated between WM- and GM-derived samples. In this study, we explored the local viscoelastic properties of isolated astrocytes and show that astrocytes from rat brain WM-enriched areas are ~1.8 times softer than astrocytes from GM-enriched areas. Upon treatment with pro-inflammatory lipopolysaccharide, GM-derived astrocytes become significantly softer in the nuclear and the cytoplasmic regions, where the F-actin network appears rearranged, whereas WM-derived astrocytes preserve their initial mechanical features and show no alteration in the F-actin cytoskeletal network. We hypothesize that the flexibility in biomechanical properties of GM-derived astrocytes may contribute to promote regeneration of the brain under neuroinflammatory conditions.