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Ulrich S Schwarz - One of the best experts on this subject based on the ideXlab platform.

  • Traction Force Microscopy on soft elastic substrates a guide to recent computational advances
    Biochimica et Biophysica Acta, 2015
    Co-Authors: Ulrich S Schwarz, Jerome R D Soine
    Abstract:

    Abstract The measurement of cellular Traction Forces on soft elastic substrates has become a standard tool for many labs working on mechanobiology. Here we review the basic principles and different variants of this approach. In general, the exTraction of the substrate displacement field from image data and the reconstruction procedure for the Forces are closely linked to each other and limited by the presence of experimental noise. We discuss different strategies to reconstruct cellular Forces as they follow from the foundations of elasticity theory, including two- versus three-dimensional, inverse versus direct and linear versus non-linear approaches. We also discuss how biophysical models can improve Force reconstruction and comment on practical issues like substrate preparation, image processing and the availability of software for Traction Force Microscopy. This article is part of a Special Issue entitled: Mechanobiology.

  • model based Traction Force Microscopy reveals differential tension in cellular actin bundles
    PLOS Computational Biology, 2015
    Co-Authors: Jerome R D Soine, Christoph A Brand, Jonathan Stricker, Patrick W Oakes, Margaret L Gardel, Ulrich S Schwarz
    Abstract:

    Adherent cells use Forces at the cell-substrate interface to sense and respond to the physical properties of their environment. These cell Forces can be measured with Traction Force Microscopy which inverts the equations of elasticity theory to calculate them from the deformations of soft polymer substrates. We introduce a new type of Traction Force Microscopy that in contrast to traditional methods uses additional image data for cytoskeleton and adhesion structures and a biophysical model to improve the robustness of the inverse procedure and abolishes the need for regularization. We use this method to demonstrate that ventral stress fibers of U2OS-cells are typically under higher mechanical tension than dorsal stress fibers or transverse arcs.

  • Traction Force Microscopy based on an active cable network model
    Biophysical Journal, 2014
    Co-Authors: Jerome R D Soine, Christoph A Brand, Jonathan Stricker, Patrick W Oakes, Margaret L Gardel, Ulrich S Schwarz
    Abstract:

    Generation of mechanical Force is essential for the function of tissue cells, for example during migration, wound healing or rigidity sensing. The Traction field of adherent cells can be measured on soft elastic substrates using Traction Force Microscopy (TFM). However, mathematical reconstruction of Traction fields effectively requires inversion of the long-ranged elastic equations and therefore is an ill-posed inverse problem. Moreover measurement of the Traction pattern alone does not tell us how Force is distributed inside the cell. To improve the robustness, resolution and scope of conventional TFM, we have developed a new procedure called model-based TFM (MBTFM). We estimate the distribution of intracellular tension from elastic substrate data by minimizing the difference between the experimentally measured displacement field and the predictions of a detailed theoretical model based on active cable networks. Previously this type of model has been successfully used to predict cell shapes on micropatterned substrates. For MBTFM, we consider not only active network conTraction, but also contributions of various types of contractile bundles modeled as contractile one-dimensional line element embedded into the network. Subsequent computer simulations of network conTraction and parameter optimization allow us to estimate the most likely distribution of tension over various contractile structures and adhesion sites.

  • high resolution Traction Force Microscopy
    Methods in Cell Biology, 2014
    Co-Authors: Sergey V Plotnikov, Ulrich S Schwarz, Benedikt Sabass, Clare M Waterman
    Abstract:

    Cellular Forces generated by the actomyosin cytoskeleton and transmitted to the extracellular matrix (ECM) through discrete, integrin-based protein assemblies, that is, focal adhesions, are critical to developmental morphogenesis and tissue homeostasis, as well as disease progression in cancer. However, quantitative mapping of these Forces has been difficult since there has been no experimental technique to visualize nanonewton Forces at submicrometer spatial resolution. Here, we provide detailed protocols for measuring cellular Forces exerted on two-dimensional elastic substrates with a high-resolution Traction Force Microscopy (TFM) method. We describe fabrication of polyacrylamide substrates labeled with multiple colors of fiducial markers, functionalization of the substrates with ECM proteins, setting up the experiment, and imaging procedures. In addition, we provide the theoretical background of Traction reconstruction and experimental considerations important to design a high-resolution TFM experiment. We describe the implementation of a new algorithm for processing of images of fiducial markers that are taken below the surface of the substrate, which significantly improves data quality. We demonstrate the application of the algorithm and explain how to choose a regularization parameter for suppression of the measurement error. A brief discussion of different ways to visualize and analyze the results serves to illustrate possible uses of high-resolution TFM in biomedical research.

  • optimization of Traction Force Microscopy for micron sized focal adhesions
    Journal of Physics: Condensed Matter, 2010
    Co-Authors: Jonathan Stricker, Ulrich S Schwarz, Benedikt Sabass, Margaret L Gardel
    Abstract:

    To understand how adherent cells regulate Traction Forces on their surrounding extracellular matrix (ECM), quantitative techniques are needed to measure Forces at the cell‐ECM interface. Microcontact printing is used to create a substrate of 1 μm diameter circles of ECM ligand to experimentally study the reconstruction of Traction stresses at constrained, point-like focal adhesions. Traction reconstruction with point Forces (TRPF) and Fourier transform Traction cytometry (FTTC) are used to calculate the Traction Forces and stress field, respectively, at isolated adhesions. We find that the stress field calculated with FTTC peaks near the center of individual adhesions but propagates several microns beyond the adhesion location. We find the optimal set of FTTC parameters that yield the highest stress magnitude, minimizing information lost from over-smoothing and sampling of the displacement or stress field. A positive correlation between the TRPF and FTTC measurements exists, but integrating the FTTC stress field over the adhesion area yields only a small fraction of the Force calculated by TRPF. An effective area similar to that defined by the width of the stress distribution measured with FTTC is required to reconcile these measurements. These measurements set bounds on the spatial resolution and precision of FTTC measurements on micron-sized adhesions. (Some figures in this article are in colour only in the electronic version)

Benedikt Sabass - One of the best experts on this subject based on the ideXlab platform.

  • a bayesian Traction Force Microscopy method with automated denoising in a user friendly software package
    Computer Physics Communications, 2020
    Co-Authors: Yunfei Huang, Gerhard Gompper, Benedikt Sabass
    Abstract:

    Abstract Adherent biological cells generate Traction Forces on a substrate that play a central role for migration, mechanosensing, differentiation, and collective behavior. The established method for quantifying this cell–substrate interaction is Traction Force Microscopy (TFM). In spite of recent advancements, inference of the Traction Forces from measurements remains very sensitive to noise. However, suppression of the noise reduces the measurement accuracy and the spatial resolution, which makes it crucial to select an optimal level of noise reduction. Here, we present a fully automated method for noise reduction and robust, standardized Traction-Force reconstruction. The method, termed Bayesian Fourier transform Traction cytometry, combines the robustness of Bayesian L2 regularization with the computation speed of Fourier transform Traction cytometry. We validate the performance of the method with synthetic and real data. The method is made freely available as a software package with a graphical user-interface for intuitive usage. Program summary Program Title: Easy-to-use TFM software Program Files doi: http://dx.doi.org/10.17632/229bnpp8rb.1 Licensing provisions: GNU General Public License v3.0 Programming language: Matlab version R2010b or higher Supplementary material: A user manual for the software and a test data set. Nature of problem: Calculation of the Traction Forces on the surface of an elastic material from observed displacements. Solution method: Traction Forces are efficiently calculated by combining L2 regularization in Fourier space with Bayesian inference of the regularization parameter.

  • a bayesian Traction Force Microscopy method with automated denoising in a user friendly software package
    arXiv: Cell Behavior, 2020
    Co-Authors: Yunfei Huang, Gerhard Gompper, Benedikt Sabass
    Abstract:

    Adherent biological cells generate Traction Forces on a substrate that play a central role for migration, mechanosensing, differentiation, and collective behavior. The established method for quantifying this cell-substrate interaction is Traction Force Microscopy (TFM). In spite of recent advancements, inference of the Traction Forces from measurements remains very sensitive to noise. However, suppression of the noise reduces the measurement accuracy and the spatial resolution, which makes it crucial to select an optimal level of noise reduction. Here, we present a fully automated method for noise reduction and robust, standardized Traction-Force reconstruction. The method, termed Bayesian Fourier transform Traction cytometry, combines the robustness of Bayesian L2 regularization with the computation speed of Fourier transform Traction cytometry. We validate the performance of the method with synthetic and real data. The method is made freely available as a software package with a graphical user-interface for intuitive usage.

  • Traction Force Microscopy with optimized regularization and automated bayesian parameter selection for comparing cells
    Scientific Reports, 2019
    Co-Authors: Yunfei Huang, Gerhard Gompper, Christoph Schell, Tobias B Huber, Ahmet Nihat Simsek, Nils Hersch, Rudolf Merkel, Benedikt Sabass
    Abstract:

    Adherent cells exert Traction Forces on to their environment which allows them to migrate, to maintain tissue integrity, and to form complex multicellular structures during developmental morphogenesis. Traction Force Microscopy (TFM) enables the measurement of Traction Forces on an elastic substrate and thereby provides quantitative information on cellular mechanics in a perturbation-free fashion. In TFM, Traction is usually calculated via the solution of a linear system, which is complicated by undersampled input data, acquisition noise, and large condition numbers for some methods. Therefore, standard TFM algorithms either employ data filtering or regularization. However, these approaches require a manual selection of filter- or regularization parameters and consequently exhibit a substantial degree of subjectiveness. This shortcoming is particularly serious when cells in different conditions are to be compared because optimal noise suppression needs to be adapted for every situation, which invariably results in systematic errors. Here, we systematically test the performance of new methods from computer vision and Bayesian inference for solving the inverse problem in TFM. We compare two classical schemes, L1- and L2-regularization, with three previously untested schemes, namely Elastic Net regularization, Proximal Gradient Lasso, and Proximal Gradient Elastic Net. Overall, we find that Elastic Net regularization, which combines L1 and L2 regularization, outperforms all other methods with regard to accuracy of Traction reconstruction. Next, we develop two methods, Bayesian L2 regularization and Advanced Bayesian L2 regularization, for automatic, optimal L2 regularization. Using artificial data and experimental data, we show that these methods enable robust reconstruction of Traction without requiring a difficult selection of regularization parameters specifically for each data set. Thus, Bayesian methods can mitigate the considerable uncertainty inherent in comparing cellular Tractions in different conditions.

  • Traction Force Microscopy with optimized regularization and automated bayesian parameter selection for comparing cells
    arXiv: Biological Physics, 2018
    Co-Authors: Yunfei Huang, Gerhard Gompper, Christoph Schell, Tobias B Huber, Ahmet Nihat Simsek, Nils Hersch, Rudolf Merkel, Benedikt Sabass
    Abstract:

    Adherent cells exert Traction Forces on to their environment, which allows them to migrate, to maintain tissue integrity, and to form complex multicellular structures. This Traction can be measured in a perturbation-free manner with Traction Force Microscopy (TFM). In TFM, Traction is usually calculated via the solution of a linear system, which is complicated by undersampled input data, acquisition noise, and large condition numbers for some methods. Therefore, standard TFM algorithms either employ data filtering or regularization. However, these approaches require a manual selection of filter- or regularization parameters and consequently exhibit a substantial degree of subjectiveness. This shortcoming is particularly serious when cells in different conditions are to be compared because optimal noise suppression needs to be adapted for every situation, which invariably results in systematic errors. Here, we systematically test the performance of new methods from computer vision and Bayesian inference for solving the inverse problem in TFM. We compare two classical schemes, L1- and L2-regularization, with three previously untested schemes, namely Elastic Net regularization, Proximal Gradient Lasso, and Proximal Gradient Elastic Net. Overall, we find that Elastic Net regularization, which combines L1 and L2 regularization, outperforms all other methods with regard to accuracy of Traction reconstruction. Next, we develop two methods, Bayesian L2 regularization and Advanced Bayesian L2 regularization, for automatic, optimal L2 regularization. Using artificial data and experimental data, we show that these methods enable robust reconstruction of Traction without requiring a difficult selection of regularization parameters specifically for each data set. Thus, Bayesian methods can mitigate the considerable uncertainty inherent in comparing cellular Traction Forces.

  • high resolution Traction Force Microscopy
    Methods in Cell Biology, 2014
    Co-Authors: Sergey V Plotnikov, Ulrich S Schwarz, Benedikt Sabass, Clare M Waterman
    Abstract:

    Cellular Forces generated by the actomyosin cytoskeleton and transmitted to the extracellular matrix (ECM) through discrete, integrin-based protein assemblies, that is, focal adhesions, are critical to developmental morphogenesis and tissue homeostasis, as well as disease progression in cancer. However, quantitative mapping of these Forces has been difficult since there has been no experimental technique to visualize nanonewton Forces at submicrometer spatial resolution. Here, we provide detailed protocols for measuring cellular Forces exerted on two-dimensional elastic substrates with a high-resolution Traction Force Microscopy (TFM) method. We describe fabrication of polyacrylamide substrates labeled with multiple colors of fiducial markers, functionalization of the substrates with ECM proteins, setting up the experiment, and imaging procedures. In addition, we provide the theoretical background of Traction reconstruction and experimental considerations important to design a high-resolution TFM experiment. We describe the implementation of a new algorithm for processing of images of fiducial markers that are taken below the surface of the substrate, which significantly improves data quality. We demonstrate the application of the algorithm and explain how to choose a regularization parameter for suppression of the measurement error. A brief discussion of different ways to visualize and analyze the results serves to illustrate possible uses of high-resolution TFM in biomedical research.

Marco Fritzsche - One of the best experts on this subject based on the ideXlab platform.

  • Single cell Force profiling of human myofibroblasts reveals a biophysical spectrum of cell states.
    Biology Open, 2020
    Co-Authors: Thomas B. Layton, Marco Fritzsche, Lynn M. Williams, H Colin-york, Fiona E. Mccann, Marisa Cabrita, Marc Feldmann, Cameron Brown, Dominic Furniss
    Abstract:

    Mechanical Force is a fundamental regulator of cell phenotype. Myofibroblasts are central mediators of fibrosis, a major unmet clinical need characterized by the deposition of excessive matrix proteins. Traction Forces of myofibroblasts play a key role in remodelling the matrix and modulates the activities of embedded stromal cells. Here, we employ a combination of unsupervised computational analysis, cytoskeletal profiling and single cell Traction Force Microscopy as functional readout to uncover how the complex spatiotemporal dynamics and mechanics of living human myofibroblast shape sub-cellular profiling of Traction Forces in fibrosis. We resolve distinct biophysical communities of myofibroblasts, and our results provide a new paradigm for studying functional heterogeneity in human stromal cells.

  • the future of Traction Force Microscopy
    Current Opinion in Biomedical Engineering, 2018
    Co-Authors: Huw Colinyork, Marco Fritzsche
    Abstract:

    Abstract Animal cells continuously sense and respond to mechanical Force. Quantifying these Forces remains a major challenge in bioengineering; yet such measurements are essential for the understanding of cellular function. Traction Force Microscopy is one of the most successful and broadly-used Force probing technologies, chosen for the simplicity of its implementation, flexibility to mimic cellular conditions, and well-established analysis pipe-line. Here, we review the accomplishments, and discuss the applicability and limitations of Traction Force Microscopy. We explain fundamental shortcomings of the method, summarise latest improvements, and outline future pathways towards the impact of the method, especially considering latest developments in state-of-the-art super-resolution fluorescence imaging. In light of the increasing discovery of the importance of mechanobiology in cell physiology, we envisage Traction Force Microscopy to remain a major player for quantifying mechanical Forces in living cells.

  • Dissection of mechanical Force in living cells by super-resolved Traction Force Microscopy
    Nature Protocols, 2017
    Co-Authors: Huw Colin-york, Christian Eggeling, Marco Fritzsche
    Abstract:

    Cells continuously exert or respond to mechanical Force. Measurement of these nanoscale Forces is a major challenge in cell biology; yet such measurement is essential to the understanding of cell regulation and function. Current methods for examining mechanical Force generation either necessitate dedicated equipment or limit themselves to coarse-grained Force measurements on the micron scale. In this protocol, we describe stimulated emission depletion Traction Force Microscopy—STED-TFM (STFM), which allows higher sampling of the Forces generated by the cell than conventional TFM, leading to a twofold increase in spatial resolution (of up to 500 nm). The procedure involves the preparation of functionalized polyacrylamide gels loaded with fluorescent beads, as well as the acquisition of STED images and their analysis. We illustrate the approach using the example of HeLa cells expressing paxillin-EGFP to visualize focal adhesions. Our protocol uses widely available laser-scanning confocal microscopes equipped with a conventional STED laser, open-source software and common molecular biology techniques. The entire STFM experiment preparation, data acquisition and analysis require 2–3 d and could be completed by someone with minimal experience in molecular biology or biophysics. Many cellular processes rely on cells generating or responding to nanoscale mechanical Forces. This protocol describes STED–Traction Force Microscopy (STFM), which allows these Forces to be measured with higher resolution and accuracy than standard TFM.

  • super resolved Traction Force Microscopy stfm
    Nano Letters, 2016
    Co-Authors: Huw Colinyork, Dilip Shrestha, James H Felce, Dominic Waithe, Emad Moeendarbary, Simon J Davis, Christian Eggeling, Marco Fritzsche
    Abstract:

    Measuring small Forces is a major challenge in cell biology. Here we improve the spatial resolution and accuracy of Force reconstruction of the well-established technique of Traction Force Microscopy (TFM) using STED Microscopy. The increased spatial resolution of STED-TFM (STFM) allows a greater than 5-fold higher sampling of the Forces generated by the cell than conventional TFM, accessing the nano instead of the micron scale. This improvement is highlighted by computer simulations and an activating RBL cell model system.

Julie A Theriot - One of the best experts on this subject based on the ideXlab platform.

  • microparticle Traction Force Microscopy reveals subcellular Force exertion patterns in immune cell target interactions
    Nature Communications, 2020
    Co-Authors: Daan Vorselen, Yifan Wang, Miguel M De Jesus, Pavak K Shah, Matthew J Footer, Morgan Huse, Julie A Theriot
    Abstract:

    Force exertion is an integral part of cellular behavior. Traction Force Microscopy (TFM) has been instrumental for studying such Forces, providing spatial Force measurements at subcellular resolution. However, the applications of classical TFM are restricted by the typical planar geometry. Here, we develop a particle-based Force sensing strategy for studying cellular interactions. We establish a straightforward batch approach for synthesizing uniform, deformable and tuneable hydrogel particles, which can also be easily derivatized. The 3D shape of such particles can be resolved with superresolution (<50 nm) accuracy using conventional confocal Microscopy. We introduce a reference-free computational method allowing inference of Traction Forces with high sensitivity directly from the particle shape. We illustrate the potential of this approach by revealing subcellular Force patterns throughout phagocytic engulfment and Force dynamics in the cytotoxic T-cell immunological synapse. This strategy can readily be adapted for studying cellular Forces in a wide range of applications. Traction Force Microscopy is an effective method for measuring cellular Forces but it is limited by planar geometry. Here the authors develop a facile method to produce deformable hydrogel particles and a reference-free computational method to resolve surface Traction Forces from particle shape deformation.

  • Microparticle Traction Force Microscopy reveals subcellular Force exertion patterns in immune cell–target interactions
    Nature Communications, 2020
    Co-Authors: Daan Vorselen, Yifan Wang, Miguel M De Jesus, Pavak K Shah, Matthew J Footer, Morgan Huse, Julie A Theriot
    Abstract:

    Force exertion is an integral part of cellular behavior. Traction Force Microscopy (TFM) has been instrumental for studying such Forces, providing spatial Force measurements at subcellular resolution. However, the applications of classical TFM are restricted by the typical planar geometry. Here, we develop a particle-based Force sensing strategy for studying cellular interactions. We establish a straightforward batch approach for synthesizing uniform, deformable and tuneable hydrogel particles, which can also be easily derivatized. The 3D shape of such particles can be resolved with superresolution (

  • superresolved and reference free microparticle Traction Force Microscopy mp tfm reveals the complexity of the mechanical interaction in phagocytosis
    bioRxiv, 2018
    Co-Authors: Daan Vorselen, Yifan Wang, Matthew J Footer, Julie A Theriot
    Abstract:

    Force exertion is an integral part of cellular behavior. Traction Force Microscopy (TFM) has been instrumental for studying such Forces, providing both spatial and directional Force measurements at subcellular resolution. However, the applications of classical TFM are restricted by the typical planar geometry. Here, we develop a particle-based Force sensing strategy, specifically designed for studying ligand-dependent cellular interactions. We establish an accessible batch approach for synthesizing highly uniform, deformable and tunable hydrogel particles. In addition, they can be easily derivatized to trigger specific cellular behavior. The 3D shape of such particles can be resolved with superresolution (

Christian Franck - One of the best experts on this subject based on the ideXlab platform.

  • epifluorescence based three dimensional Traction Force Microscopy
    2020
    Co-Authors: Lauren Hazlett, Jonathan S Reichner, Alexander K Landauer, Mohak Patel, Hadley Witt, Jin Yang, Christian Franck
    Abstract:

    The datasets presented here are intended to be used with the Single-Layer-3D-TFM Matlab and FEniCS code package on the Franck Lab Github page (https://github.com/FranckLab). The datasets include: an example dataset for new users to practice using the code along with the experimental rigid displacement data, synthetic Traction validation cases, and experimental cell Traction data which can be used to reproduce the figures in the publication.

  • high resolution large deformation 3d Traction Force Microscopy
    Biophysical Journal, 2015
    Co-Authors: Jennet Toyjanova, Eyal Barkochba, Cristina Lopezfagundo, Jonathan S Reichner, Diane Hoffmankim, Christian Franck
    Abstract:

    Traction Force Microscopy (TFM) is a powerful approach of quantifying cell-material interactions, which over the last two decades has contributed significantly to our understanding of cellular mechanosensing and mechanotransduction. In addition, recent advances in three-dimensional (3D) imaging and Traction Force analysis (3D TFM) have highlighted the significance of the third dimension in influencing various cellular processes. Yet irrespective of dimensionality almost all TFM approaches have relied on a linear elastic theory framework to calculate cell surface Tractions.This talk presents a new high-resolution 3D TFM algorithm, which utilizes a large deformation formulation to quantify cellular displacement fields with unprecedented resolution. The results feature some of the first experimental evidence that cells are indeed capable of exerting large material deformations, which require the formulation of a new theoretical TFM framework to accurately calculate Traction Forces. Based on our previous 3D TFM technique we reformulate our approach to accurately account for large material deformation and quantitatively contrast and compare both linear and large deformation frameworks as a function of the applied cell deformation. Particular attention is paid in estimating the accuracy penalty associated with utilizing a traditional linear elastic approach in the presence of large deformation gradients.

  • 3d viscoelastic Traction Force Microscopy
    Soft Matter, 2014
    Co-Authors: Jennet Toyjanova, Erin Hannen, Eyal Barkochba, Eric M Darling, David L Henann, Christian Franck
    Abstract:

    Native cell–material interactions occur on materials differing in their structural composition, chemistry, and physical compliance. While the last two decades have shown the importance of Traction Forces during cell–material interactions, they have been almost exclusively presented on purely elastic in vitro materials. Yet, most bodily tissue materials exhibit some level of viscoelasticity, which could play an important role in how cells sense and transduce Tractions. To expand the realm of cell Traction measurements and to encompass all materials from elastic to viscoelastic, this paper presents a general, and comprehensive approach for quantifying 3D cell Tractions in viscoelastic materials. This methodology includes the experimental characterization of the time-dependent material properties for any viscoelastic material with the subsequent mathematical implementation of the determined material model into a 3D Traction Force Microscopy (3D TFM) framework. Utilizing this new 3D viscoelastic TFM (3D VTFM) approach, we quantify the influence of viscosity on the overall material Traction calculations and quantify the error associated with omitting time-dependent material effects, as is the case for all other TFM formulations. We anticipate that the 3D VTFM technique will open up new avenues of cell–material investigations on even more physiologically relevant time-dependent materials including collagen and fibrin gels.

  • high resolution large deformation 3d Traction Force Microscopy
    PLOS ONE, 2014
    Co-Authors: Jennet Toyjanova, Eyal Barkochba, Cristina Lopezfagundo, Jonathan S Reichner, Diane Hoffmankim, Christian Franck
    Abstract:

    Traction Force Microscopy (TFM) is a powerful approach for quantifying cell-material interactions that over the last two decades has contributed significantly to our understanding of cellular mechanosensing and mechanotransduction. In addition, recent advances in three-dimensional (3D) imaging and Traction Force analysis (3D TFM) have highlighted the significance of the third dimension in influencing various cellular processes. Yet irrespective of dimensionality, almost all TFM approaches have relied on a linear elastic theory framework to calculate cell surface Tractions. Here we present a new high resolution 3D TFM algorithm which utilizes a large deformation formulation to quantify cellular displacement fields with unprecedented resolution. The results feature some of the first experimental evidence that cells are indeed capable of exerting large material deformations, which require the formulation of a new theoretical TFM framework to accurately calculate the Traction Forces. Based on our previous 3D TFM technique, we reformulate our approach to accurately account for large material deformation and quantitatively contrast and compare both linear and large deformation frameworks as a function of the applied cell deformation. Particular attention is paid in estimating the accuracy penalty associated with utilizing a traditional linear elastic approach in the presence of large deformation gradients.

  • three dimensional Traction Force Microscopy for studying cellular interactions with biomaterials
    Procedia IUTAM, 2012
    Co-Authors: Jacob Notbohm, Anand R Asthagiri, Christian Franck, Stacey A Maskarinec, David A Tirrell, G Ravichandran
    Abstract:

    The interactions between biochemical and mechanical signals during cell adhesion, migration, spreading and other processes influence cellular behavior. Three-dimensional measurement techniques are needed to investigate the effect of mechanical properties of the substrate on cellular behavior. This paper discusses a three-dimensional full-field measurement technique that has been developed for measuring large deformations in soft materials. The technique utilizes a digital volume correlation (DVC) algorithm to track motions of sub-volumes within 3-D images obtained using laser scanning confocal Microscopy. The technique is well-suited for investigating 3-D mechanical interactions between cells and the extracellular matrix and for obtaining local constitutive properties of soft biomaterials. Results from the migration of single fibroblast cells on polyacrylamide gels and their implications for cell motility models are discussed. The implications that the Traction distributions of epithelial cell clusters have on the inhibition of proliferation due to cell contact and scattering of cells in a cluster are discussed. These results provide insights on Force fields generated by cells and the role of the mechanical properties of the substrate on cellular interactions and mechanotransduction. Analytical solutions and finite element simulations are used to elucidate the mechanics of cellular Forces exerted on the extracellular matrix.