The European Physical Journal E

Traction Force Microscopy (TFM) has become a well-established technique to assay the biophysical force produced by cells cultured on soft substrates of controlled stiffness. However, experimental conditions as well as computational implementations can have a large impact on the analysis results accuracy and reproducibility. While this can be alleviated using appropriate controls and a rigorous analytical approach, the comparison of results across studies remains difficult and there is a need for validation and benchmarking tools. To validate the accuracy of and compare various computational TFM analysis algorithms, we developed a virtual in silico model of a cell contracting on a soft substrate of controlled stiffness. The model utilizes user-defined parameters for the cell dimensions as well as for the strength and spatial distribution of a contraction dipole to calculate the deformation that would result on a soft substrate due to the cell contraction. The deformation is computed using the forward analytical stress-strain tensor calculation in the Fourier space. The resulting displacement field is used to apply, using image processing, a deformation on a real or simulated image of fluorescent microspheres embedded into a soft hydrogel, which is normally obtain experimentally by TFM imaging. The deformation field and resulting image then serve as input in the PIV and TFM analysis. The model also enables to create movies of a dynamic cell contraction, such as that of a cardiomyocyte, to validate the time accuracy of the TFM analysis after application of image processing algorithm, such as denoising. Our tool therefore addresses the need for validation and standardization of TFM analytical algorithms and its experimental implementations.

Fluorescence recovery after photobleaching (FRAP) is a common technique to analyze the turnover of molecules in living cells. Numerous physicochemical models have been developed to quantitatively evaluate the rate of turnover driven by chemical reaction and diffusion that occurs in a few seconds to minutes. On the other hand, they have limitations in interpreting long-term FRAP responses where intracellular active movement inevitably provides target molecular architectures with additional effects other than chemical reaction and diffusion, namely directed transport and structural deformation. To overcome the limitations, we develop a continuum mechanics-based model that allows for decoupling FRAP response into the intrinsic turnover rate and subcellular mechanical characteristics such as displacement vector and strain tensor. Our approach was validated using fluorescently-labeled beta-actin in an actomyosin-mediated contractile apparatus called stress fibers, revealing spatially distinct patterns of the multi-physicochemical events, in which the turnover rate of beta-actin was significantly higher at the center of the cell. We also found that the turnover rate is negatively correlated with the strain rate along stress fibers but, interestingly, not with the absolute strain magnitude. Moreover, stress fibers are subjected to centripetal flow as well as both contractile and tensile strains along them. Taken together, this novel framework for long-term FRAP analysis allows for unveiling the contribution of overlooked microscopic mechanics to molecular turnover in living cells.

Hydra vulgaris, long known for its remarkable regenerative capabilities, is also a longstanding source of inspiration for models of spontaneous patterning. Recently, it became clear that early patterning during Hydra regeneration is an integrated mechano-chemical process where morphogen dynamics is influenced by tissue mechanics. One roadblock to understand Hydra self-organization is our lack of knowledge about the mechanical properties of these organisms. In this paper, we combined microfluidic developments to perform parallelized microaspiration rheological experiments and numerical simulations to characterize these mechanical properties. We found three different behaviors depending on the applied stresses: an elastic response, a visco-elastic one and tissue rupture. Using models of deformable shells, we quantify their Youngs modulus, shear viscosity as well as the critical stresses required to switch between behaviors. Based on these experimental results, we propose a description of the tissue mechanics during normal regeneration. Our results provide a first step towards the development of original mechano-chemical models of patterning grounded in quantitative, experimental data. Statement of significanceHydra vulgaris is a remarkable organism thanks to its regenerative abilities. One can cut this animal into several pieces which will reform a full Hydra in a few days. In this process, the pieces have to define a new organizing axis. Recently, researchers have shown that this axis definition is under mechanical control. One roadblock to understand the relationship between tissue mechanics and Hydra biology is our lack of knowledge about the mechanical state of this organism. Here, we perform a mechanical characterization using a combination of microaspiration setups and numerical simulations. We finally propose a description of what happens at the mechanical level during Hydra regeneration, allowing quantitative approaches questioning the role of mechanical cues in axis definition.

The measurement of stresses and forces at the tissue level has proven to be an indispensable tool for the understanding of complex biological phenomena such as cancer invasion, embryo development or wound healing. One of the most versatile tools for force inference at the cell and tissue level are elastic force sensors, whose biocompatibility and tunable material properties make them suitable for many different experimental scenarios. The evaluation of those forces, however, is still a bottleneck due to the numerical methods seen in literature until now, which are usually slow and render low experimental yield. Here we present Bead-Buddy, a ready-to-use platform for the evaluation of deformation and stresses from fluorescently labelled sensors within seconds. The strengths of BeadBuddy lie in the pre-computed analytical solutions of the elastic problem, the abstraction of data into Spherical Harmonics, and a simple user interface that creates a smooth workflow for force inference. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=174 SRC="FIGDIR/small/633835v3_ufig1.gif" ALT="Figure 1"> View larger version (54K): org.highwire.dtl.DTLVardef@80c95corg.highwire.dtl.DTLVardef@123d712org.highwire.dtl.DTLVardef@1fd1ce0org.highwire.dtl.DTLVardef@72c688_HPS_FORMAT_FIGEXP M_FIG C_FIG

The reciprocal interplay between cancer cells and their local environment, mediated by mechanical forces, necessitates a deeper experimental understanding. This requires precise quantitative measurements of cellular forces within the intricate three-dimensional context of the extracellular matrix. While methods such as traction-force microscopy and micropillar-array technology have effectively reported on cellular forces in two-dimensional cell culture, extending these techniques to three dimensions has proven exceedingly challenging. In the current study, we introduced a novel approach utilizing soft, elastic hydrogel microparticles, resembling the size of cells, to serve as specific and sensitive traction probes in three-dimensional cell culture of collagen-embedded tumoroids. Our methodology relies on high-resolution detection of microparticle deformations. These deformations are translated into spatially resolved traction fields, reaching a spatial resolution down to 1 {micro}m and thereby detecting traction forces as low as 30 Pa. By integrating this high-resolution traction analysis with three-dimensional cell segmentation, we reconstructed the traction fields originating from individual cells. Our methodology enables us to explore the relationships between cellular characteristics, extracellular traction fields, and cellular responses. We observed that cellular stresses ranged from 10 to 100 Pa, integrating to cellular forces from 0.1 to 100 nN, which correlated with the localization of the cells actin skeleton, and the interaction area that cells developed towards the microparticles. Interestingly, the interaction of cells with inert microparticles appeared to be governed by contact mechanics resembling that of two soft spheres. The methodology presented here not only addresses the challenges of extending traditional stress-probe techniques to three dimensions, but also opens a strategy for the study of specific interactions between cells and the local tumoroid environment in a strive to further understand cell-matrix reciprocity in tissue. Here, we present a novel methodology that permits the measurement of quantitative surface stresses on small, inert, elastic, deformable microparticles. Our approach tackles the involved task of mapping local three-dimensional stress fields within tissue. Our methodology was successfully applied to analyze local stresses within a tumor spheroid. We foresee that our research represents a significant advancement toward comprehending the intricate dynamics of cell-matrix reciprocity within tissue.

In this study we challenge the paradigm of using the Boyle van t Hoff (BvH) relation to relate cell size as a linear function of inverse extracellular osmotic pressure for short time periods (~5 to 30 mins). We present alternative models that account for mechanical resistance (turgor model) and ion-osmolyte leakage (leak model), which is not accounted for by the BvH relation. To test the BvH relation and the alternative models, we conducted a meta-analysis of published BvH datasets, as well as new experiments using a HepG2 cell line. Our meta-analysis showed that the BvH relation may be assumed of the hypertonic region but cannot be assumed a priori over the hyper- and hypotonic region. Both alternative models perform better than the BvH relation but are nearly indistinguishable when plotted. The return to isotonic conditions plot indicated neither alternative model accurate predicts return volumes for HepG2 cells. However, a combined turgor-leak model accurately predicts both the BvH plot and the return to isotonic conditions plot. Moreover, this turgor-leak model provides a facile method to estimate the membrane-cortex Youngs modulus and the cell membrane permeability to intracellular ions/osmolytes during periods of osmotic challenge, and predicts a novel passive method of volume regulation without the need for ion pumps.

Synthetic cationic fluorophores are used widely as probes to measure the membrane potentials of bacterial cells, eukaryotic cells and organelles, such as mitochondria. An external oscillating electric field was applied to Escherichia coli cells using microelectrodes and AC electro-osmosis was observed for the fluorophores, independent of the electrophysiology of the bacteria, giving rise to phantom action potentials. The fluorophores migrate around the microfluidic device in vortices modulating their concentration having decreases or dips in fluorescence. We show that the fluorescent dips are universally present when using cationic fluorophores, such as thioflavin-T, propidium iodide, Syto9 and Sytox Green, with or without E. coli cells in the inoculum, when stimulated with AC voltages. This is in contrast to the study of Stratford et al (PNAS, 2019) who claim the existence of action potentials. Furthermore, E. coli biofilms also demonstrated similar phenomena with dips in the fluorescence. We measured the relaxation times of the fluorophores experiencing AC electro-osmosis, which depended on the biofilm, the cells and the fluorophores used. PI had the smallest relaxation time and Syto9 the highest. Removing the cells resulted in longer relaxation times and introducing biofilm did not significantly change the relaxation times compared with the single cell experiments. Furthermore, fluorescently labelled DNA and fluorescent colloidal beads also demonstrate fluorescent dips through AC electro-osmosis, showing that these particles can be driven through biofilms. This is the first study of AC electro-osmosis in bacterial biofilms, indicating a surprisingly high mobility of charged molecules within the extracellular polymeric substance, which could be used to treat biofilms i.e. to increase the kinetics of delivery of antibiotics.

Cells sense and respond to fluid shear stress. Cell surfaces are exposed to flow, yet the influence of shear stress on the behavior of plasma membrane proteins remains unclear. Here we show that extracellular flow induces the gradient distribution of cell membrane proteins with increasing concentration toward the downstream direction of the flow. Shear stress at 10-30 dynes/cm2 caused formation of concentration gradients of both GPI-anchored proteins and transmembrane proteins, including integrin{beta}1, E-cadherin and the insulin receptor in Xenopus XTC cells. Using single-molecule live-cell imaging, we found that GPI-anchored T-cadherin molecules are dragged along the direction of flow under shear stress. In addition, shear stress induced concentration gradients of membrane proteins in COS-7 cells and human umbilical vein endothelial cells (HUVECs). Our findings suggest that external flow directly transports membrane proteins, establishing concentration gradients that may contribute to the cellular flow-sensing mechanism.

Three-dimensional (3D) cell spheroids are widely used in biomedical research as in vitro tissue models, yet quantitative understanding of their morphogenesis remains limited. Here, we present an integrated experimental and computational approach to analyze and model the compaction of cell aggregates in agarose microwells with defined cross-sectional geometries. Custom 3D-printed stamps were designed to produce circular, square, and triangular microwells with equal cross-sectional area. Time-lapse imaging and AI-based segmentation were employed to track the evolution of spheroid morphology, with circularity and projected area used as quantitative indicators of compaction dynamics. We show that the compaction process follows predictable exponential trends in both parameters, with mesenchymal spheroids (from human dermal fibroblasts line HDF) compacting faster than epithelial spheroids (from ARPE-19 cells). Spheroid rounding was simulated as a visco-capillary-driven process with a computational fluid dynamics (CFD) model using the Volume of Fluid (VoF) method in OpenFOAM. The visco-capillary velocity extracted from both experimental and simulation data served as a unifying parameter that explained differences in compaction kinetics. Using additional mechanical measurements (AFM and compression), we estimated surface tension and effective viscosity, confirming that surface tension differences predominantly drive the observed kinetics. Pharmacological treatments modulating cytoskeletal tension revealed that contractility inhibition significantly modified spheroid formation dynamics, allowing acquisition of non-spherical cell aggregates. Taken together, our study establishes a robust, geometry-controlled platform for analyzing spheroid formation and quantifying their mechanical properties, as well as provides a framework for creating cellular aggregates of defined shapes. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=74 SRC="FIGDIR/small/676122v1_ufig1.gif" ALT="Figure 1"> View larger version (32K): org.highwire.dtl.DTLVardef@18a8355org.highwire.dtl.DTLVardef@b46d52org.highwire.dtl.DTLVardef@1756067org.highwire.dtl.DTLVardef@10c1118_HPS_FORMAT_FIGEXP M_FIG C_FIG

Micro Particle Image Velocimetry (Micro-PIV), an advanced imaging technique, enables high-resolution velocity field measurements by tracking fluorescent tracers in microscopic environments. Here, we adapt conventional micro-PIV to study the rapidly contractile dynamics of active poroelastic gels. We demonstrate how frame-to-frame correlation improves signal-to-noise ratios and how the elastic nature of the solid phase of the gel can be included in the analysis. To do this, we average the gel displacement data under an axisymmetric assumption to extract radial strain profiles that reliably reveal local deformations of the gel. By analyzing gels of varying shapes, we further show that our method extends robustly to gels that are not completely circular or that do not displace symmetrically towards their geometric center. The analysis reveals common underlying features in the radial profiles of gel deformation. These strain profiles will allow the inference of the spatial and orientational distribution of motor-generated active stresses with appropriate constitutive models for the gel mechanics. Our findings emphasize the importance of tailored micro-PIV methodologies for analyzing complex fluids, particularly autonomously contracting poroelastic materials. This approach significantly enhances understanding of cytoskeletal dynamics and self-organization processes, with broad implications for cell motility, morphogenesis, and active matter physics.

Cellular force generation and transmission are fundamental processes driving cell migration, division, tissue morphogenesis, and disease progression. Traction Force Microscopy (TFM) and Monolayer Stress Microscopy (MSM) have emerged as essential techniques for quantifying these mechanical processes, but current software solutions are fragmented across multiple platforms with varying degrees of usability and accessibility. Here, we present napariTFM, a comprehensive open-source plugin for the napari image viewer that integrates state-of-the-art algorithms for both TFM and MSM analysis within an intuitive graphical user interface. The software implements TV-L1 optical flow for displacement analysis, Fourier Transform Traction Cytometry (FTTC) for force reconstruction, and finite element methods for stress calculation, supporting both single-frame and time-series analysis of 2D microscopy data. Systematic validation using synthetic datasets with known ground truth values demonstrated excellent accuracy, with correlation coefficients above 0.9 for most situations. Real-time parameter adjustment and immediate visualization capabilities enable interactive optimization of analysis parameters and quality assessment during processing. Finally, we demonstrate the softwares capabilities through analysis of optogenetic contractility experiments in cell doublets. napariTFM addresses critical gaps in the cellular mechanics software ecosystem by combining algorithmic rigor with practical usability, providing the research community with an accessible platform for quantitative studies of cellular force generation and transmission.

Mechanobiology has shown great success in revealing complex cellular dynamics in various pathologies and physiologies. Most methods for assessing a cells mechanical properties, however, generally extract only a few physical constants such as Youngs modulus. This can limit the potential for accurate classification given the wide variety of rheological properties of cells, there are many ways for cells to differ. While it was recently shown that deep learning can classify cells more accurately than traditional approaches, it is not clear how this may be extended to unsupervised classification. In this work, we showcase the potential for a deep learning model to classify cells in an unsupervised fashion using a blend of physical properties. We introduce the combination of a variational autoencoder and a previously described clustering loss for classifying cells in an unsupervised fashion.

Cell motility represents one of the most fundamental function in mechanobiology. Cell motility is directly implicated in development, cancer or tissue regeneration, but it also plays a key role in the future of tissue and biomedical engineering. Here, we derived a computational model of cell motility that incorporates the most important mechanisms toward cell motility: cell protrusion, polarization and retrograde flow. We first validate our model to explain two important types of cell migration, i.e. confined and ameboid cell migration, as well as all phases of the latter cell migration type, i.e. symmetric cell spreading, cell polarization and latter migration. Then, we use our model to investigate durotaxis and chemotaxis. The model predicts that chemotaxis alone induces larger migration velocities than durotaxis and that durotaxis is activated in soft matrices but not in stiff ones. More importantly, we analyze the competition between chemical and mechanical signals. We show that chemotaxis rules over durotaxis in most situations although durotaxis diminishes chemotaxis. Moreover, we show that inhibiting the effect of GTPases in actin polymerization at the cell front may allow durotaxis to take control over chemotaxis in soft substrates. Understanding how the main forces in cell motility cooperate, and how a precise manipulation of external cues may control directed cell migration is not only key for a fundamental comprehension of cell biology but also to engineer better biomimetic tissues. To this end, we provide a freely-available platform to predict all phases and modes of cell motility analyzed in this work.

Investigations of the response of curved epithelia derived from MDCK-II cells to external deformation involved indentation-relaxation experiments using colloidal probe microscopy. Notably, hemicysts exhibited lower tissue tension, greater compliance, and increased fluidity compared to cysts. The primary response to deformation turned out to be the in-plane expansion of the basal cortex/membrane of cells. Additionally, drug treatments applied to curved tissue, along with deformation of tailored mutants (such as E-cadherin knockout), revealed that tissue compliance over short time scales is influenced by an interplay of viscoelastic properties in individual cells, their apical-basal polarity, superelasticity of the shell, and excess interfacial area. Meanwhile, tissue resilience predominantly depends on the integrity of cell-cell contacts.

From cellular mechanotransduction to the formation of embryonic tissues and organs, mechanics has been shown to play an important role in the control of cell behavior and embryonic development. Most of our existing knowledge of how mechanics affects cell behavior comes from in vitro studies, mainly because measuring cell and tissue mechanics in 3D multicellular systems, and especially in vivo, remains challenging. Oil microdroplet sensors, and more recently gel microbeads, use surface deformations to directly quantify mechanical stresses within developing tissues, in vivo and in situ, as well as in 3D in vitro systems like organoids or multicellular spheroids. However, an automated analysis software able to quantify the spatiotemporal evolution of stresses and their characteristics from particle deformations is lacking. Here we develop STRESS (Surface Topography Reconstruction for Evaluation of Spatiotemporal Stresses), an analysis software to quantify the geometry of deformable particles of spherical topology, such as microdroplets or gel microbeads, that enables the automatic quantification of the temporal evolution of stresses in the system and the spatiotemporal features of stress inhomogeneities in the tissue. As a test case, we apply these new code to measure the temporal evolution of mechanical stresses using oil microdroplets in developing zebrafish tissues. Starting from a 3D timelapse of a droplet, the software automatically calculates the statistics of local anisotropic stresses, decouples the deformation modes associated with tissue- and cell-scale stresses, obtains their spatial features on the droplet surface and analyzes their spatiotemporal variations using spatial and temporal stress autocorrelations. The automated nature of the analysis will help users obtain quantitative information about mechanical stresses in a wide range of 3D multicellular systems, from developing embryos or tissue explants to organoids. Author summaryThe measurement of mechanical stresses in 3D multicellular systems, such as living tissues, has been very challenging because of a lack in technologies for this purpose. Novel microdroplet techniques enable direct, quantitative in situ measurements of mechanical stresses in these systems. However, computational tools to obtain mechanical stresses from 3D images of microdroplets in an automated and accurate manner are lacking. Here we develop STRESS, an automated analysis software to analyze the spatiotemporal characteristics of mechanical stresses from microdroplet deformations in a wide range of systems, from living embryonic tissues and tissue explants to organoids and multicellular spheroids.

Imposed deformations play an important role in morphogenesis and tissue homeostasis, both in normal and pathological conditions. To perceive mechanical perturbations of different types and magnitudes, tissues need appropriate detectors, with a compliance that matches the perturbation amplitude. By comparing results of selective osmotic compressions of cells within multicellular aggregates with small osmolites and global aggregate compressions with big osmolites, we show that global compressions have a strong impact on the aggregates growth and internal cell motility, while selective compressions of same magnitude have almost no effect. Both compressions alter the volume of individual cells in the same way but, by draining the water out of the extracellular matrix, the global one imposes a residual compressive mechanical stress on the cells while the selective one does not. We conclude that, in aggregates, the extracellular matrix is as a sensor which mechanically regulates cell proliferation and migration in a 3D environment.

The cellular cytoskeleton provides the cell with mechanical rigidity and mediates mechanical interaction between cells and with the extracellular environment. The actin structure plays a key role in regulating cellular behaviors like motility, cell sorting, or cell polarity. From the earliest stages of development, in naive stem cells, the critical mechanical role of the actin structure is becoming recognized as a vital cue for correct segregation and lineage control of cells and as a regulatory structure that controls several transcription factors. The ultrastructure of the earliest embryonic stem cells has not been investigated in living cells despite the fact that it is well-known that cells undergo morphological shape changes during the earliest stages of development. Here, we provide 3D investigations of the actin cytoskeleton of naive mouse embryonic stem cells (ESCs) in clusters of sizes relevant for early stage development using super resolution optical reconstruction microscopy (STORM). We quantitatively describe the morphological, cytoskeletal and mechanical changes appearing between cells in small clusters at the earliest stages of inner cell mass differentiation, as recapitulated by cells cultured under two media conditions, 2i and Serum/LIF, thus promoting the naive and first primed state, respectively. High resolution images of living stem cells showed that the peripheral actin structure undergoes a dramatic change between the two media conditions. The actin organization changed from being predominantly oriented parallel to the cell surface in 2i medium to a more radial orientation in Serum/LIF. Finally, using an optical trapping based technique, we detected micro-rheological differences in the cell periphery between the cells cultured in these two media, with results correlating well with the observed nano-architecture of the ESCs in the two different differentiation stages. These results pave the way for linking physical properties and cytoskeletal architecture to the development from naive stem cells to specialized cells. Statement of SignificanceCells receive mechanical signals and must provide mechanical feedback, therefore, physical properties are instrumental for cell-cell interactions. Mechanical signals mediated through the cell surface can significantly affect transport of signaling molecules and can influence biological processes like transcriptional regulation. To achieve a deeper insight into how the cytoskeletal structure is responsible for cell shape and material properties at the earliest stages of development, we employ super-resolution microscopy to image actin fibers in clusters of embryonic stem cells mimicking early development. By modification of the culturing conditions, we investigate how the actin cytoskeleton and micro-rheological properties of ESCs change between the naive ground state and the stage primed towards epiblast, thus revealing a correlation between differentiation stage and cytoskeletal structure.

Epithelial cell collectives migrate through tissue interfaces and crevices to orchestrate processes of development, tumor invasion, and wound healing. Naturally, traversal of cell collective through confining environments involves crowding due to the narrowing space, which seems tenuous given the conventional inverse relationship between cell density and migration. However, physical transitions required to overcome such epithelial densification for migration across confinements remain unclear. Here, in contiguous microchannels, we show that epithelial (MCF10A) monolayers accumulate higher cell density before entering narrower channels; however, overexpression of breast cancer oncogene +ErbB2 reduced this need for density accumulation across confinement. While wildtype MCF10A cells migrated faster in narrow channels, this confinement sensitivity reduced after +ErbB2 mutation or with constitutively-active RhoA. The migrating collective developed pressure differentials upon encountering microchannels, like fluid flow into narrowing spaces, and this pressure dropped with their continued migration. These transitions of pressure and density altered cell shapes and increased effective temperature, estimated by treating cells as granular thermodynamic system. While +RhoA cells and those in confined regions were effectively warmer, cancer-like +ErbB2 cells remained cooler. Epithelial reinforcement by metformin treatment increased density and temperature differentials across confinement, indicating that higher cell cohesion could reduce unjamming. Our results provide experimental evidence for previously proposed theories of inverse relationship between density and motility-related effective temperature. Indeed, we show across cell lines that confinement increases pressure and effective temperature, which enable migration by reducing density. This physical interpretation of collective cell migration as granular matter could advance our understanding of complex living systems.

Over the past few years, atomic force microscopy (AFM) has developed as a mature research tool for measuring the nanomechanical properties of tissue, cells and biological structures. The force spectroscopy mode of AFM allows the local elasticity of biological samples to be measured. The mechanical properties of cells are highly affected by homeostatic changes observed during disease. In the case of the intestine, the aetiology for some conditions is still unclear. To improve the clinical translation of pre-clinical models, a new and different approach could be to study cellular behaviour in health and disease from a mechanical point of view. Specifically, knowledge of changes in epithelial membranes in response to drugs is useful for interpreting both drug action and disease development. Here, we used human intestinal Caco-2 cells as a first step to record epithelial membrane elasticity measurements at the nanoscale using AFM. Three different drugs were selected to influence intestinal epithelium integrity by specifically targeting different functional aspects of the membrane, such as permeability and support. Results indicate a relationship between measured cell elasticity and cell viability markers, such as cellular toxicity and membrane barrier functions. Our work represents a proof-of-concept that cells suffer a particular change in elastic properties depending upon the mechanism of action of an applied drug. The following may provide an efficient approach for diagnosing intestinal pathologies and testing drugs for clinical use.\n\nSTATEMENT OF SIGNIFICANCEWe present evidence that epithelial membrane suffers a particular change in elastic properties depending upon the mechanism of action of an applied drug. These changes can be monitored over time using AFM technology and may provide an alternative and efficient approach for diagnosing intestinal pathologies and testing drugs for clinical use.

Computational modeling has emerged as a powerful approach to studying cytoskeletal dynamics. The simulation software Cytosim provides intuitive yet flexible simulations of filament polymerization, cross-linking, and motor activity. Here, we present Cytocalc, a lightweight Python toolkit designed to streamline and standardize the analysis of Cytosim simulation output, supporting studies of biological functionality and physical properties of cytoskeletal systems. After introducing Cytocalc and validating it, we use it to establish a new workflow for quantifying network viscoelasticity from Cytosim simulations. Specifically, we determine the complex shear modulus of cross-linked networks and quantify how the storage modulus increases with cross-linker density. The cross-linker dependence of the networks elasticity exhibits two regimes, a scaling regime consistent with elasticity arising from the suppression of thermal bending fluctuations of filaments as well as a much weaker dependence at high cross-linker concentration.