scholarly journals Avoiding tensional equilibrium in cells migrating on a matrix with cell-scale stiffness-heterogeneity

2020 ◽  
Author(s):  
Hiroyuki Ebata ◽  
Satoru Kidoaki
Keyword(s):  
Traction Force ◽  
Model Systems ◽  
Matrix Stiffness ◽  
Force Microscopy ◽  
Force Dynamics ◽  
Cell Functions ◽  
Cell Shaping ◽  
Extracellular Matrix Stiffness ◽  
Living Tissues ◽  
Migration Of Cells

AbstractIntracellular stresses affect various cell functions, including proliferation, differentiation and movement, which are dynamically modulated in migrating cells through continuous cell-shaping and remodeling of the cytoskeletal architecture induced by spatiotemporal interactions with extracellular matrix stiffness. When cells migrate on a matrix with cell-scale stiffness-heterogeneity, which is a common situation in living tissues, what intracellular stress dynamics (ISD) emerge? In this study, to explore this issue, finite element method-based traction force microscopy was applied to cells migrating on microelastically patterned gels. Two model systems of microelastically patterned gels (stiff/soft stripe and stiff triangular patterns) were designed to characterize the effects of a spatial constraint on cell-shaping and of the presence of different types of cues to induce competing cellular taxis (usual and reverse durotaxis) on the ISD, respectively. As the main result, the prolonged fluctuation of traction stress on a whole-cell scale was markedly enhanced on single cell-size triangular stiff patterns compared with homogeneous gels. Such ISD enhancement was found to be derived from the interplay between the nomadic migration of cells to regions with different degrees of stiffness and domain shape-dependent traction force dynamics, which should be an essential factor for keeping cells far from tensional equilibrium.

scholarly journals Both contractile axial and lateral traction force dynamics drive amoeboid cell motility

2014 ◽  
Vol 204 (6) ◽  
pp. 1045-1061 ◽  
Author(s):  
Effie Bastounis ◽  
Ruedi Meili ◽  
Begoña Álvarez-González ◽  
Joshua Francois ◽  
Juan C. del Álamo ◽  
...  
Keyword(s):  
Cell Motility ◽  
Traction Force ◽  
Force Microscopy ◽  
Force Dynamics ◽  
Amoeboid Cell ◽  
Axial Forces ◽  
Extrinsic Cues ◽  
Mutant Strains ◽  
And Migration ◽  
Anterior Posterior

Chemotaxing Dictyostelium discoideum cells adapt their morphology and migration speed in response to intrinsic and extrinsic cues. Using Fourier traction force microscopy, we measured the spatiotemporal evolution of shape and traction stresses and constructed traction tension kymographs to analyze cell motility as a function of the dynamics of the cell’s mechanically active traction adhesions. We show that wild-type cells migrate in a step-wise fashion, mainly forming stationary traction adhesions along their anterior–posterior axes and exerting strong contractile axial forces. We demonstrate that lateral forces are also important for motility, especially for migration on highly adhesive substrates. Analysis of two mutant strains lacking distinct actin cross-linkers (mhcA− and abp120− cells) on normal and highly adhesive substrates supports a key role for lateral contractions in amoeboid cell motility, whereas the differences in their traction adhesion dynamics suggest that these two strains use distinct mechanisms to achieve migration. Finally, we provide evidence that the above patterns of migration may be conserved in mammalian amoeboid cells.

scholarly journals Wrinkle force microscopy: a new machine learning based approach to predict cell mechanics from images

2021 ◽  
Author(s):  
Honghan Li ◽  
Daiki Matsunaga ◽  
Tsubasa S. Matsui ◽  
Hiroki Aosaki ◽  
Koki Inoue ◽  
...  
Keyword(s):  
Machine Learning ◽  
Cell Mechanics ◽  
Traction Force ◽  
Learning System ◽  
Training Data ◽  
Force Microscopy ◽  
Cell Functions ◽  
Microscope Images ◽  
Cellular Forces ◽  
New Machine

Combining experiments with artificial intelligence algorithms, we propose a new machine learning based approach to extract the cellular force distributions from the microscope images. The full process can be divided into three steps. First, we culture the cells on a special substrate allowing to measure both the cellular traction force on the substrate and the corresponding substrate wrinkles simultaneously. The cellular forces are obtained using the traction force microscopy (TFM), at the same time that cell-generated contractile forces wrinkle their underlying substrate. Second, the wrinkle positions are extracted from the microscope images. Third, we train the machine learning system with GAN (generative adversarial network) by using sets of corresponding two images, the traction field and the input images (raw microscope images or extracted wrinkle images), as the training data. The network understands the way to convert the input images of the substrate wrinkles to the traction distribution from the training. After sufficient training, the network is utilized to predict the cellular forces just from the input images. Our system provides a powerful tool to evaluate the cellular forces efficiently because the forces can be predicted just by observing the cells under the microscope, which is a way simpler method compared to the TFM experiment. Additionally, the machine learning based approach presented here has the profound potential for being applied to diverse cellular assays for studying mechanobiology of cells.Significance StatementCell-generated forces are indispensable determinants of fundamental cell functions such as motility and cell division. As such, quantifying how the forces change upon perturbations to the cells such as gene mutations and drug administration is of profound importance. Here we present a novel machine learning based system that allows for efficient estimations of the forces that are determined only by “observing” microscope images. Given that the cellular traction forces are regulated downstream of diverse signaling pathways, our system – that helps significantly improve the throughput of the measurements – presents a new, high throughput platform for real time analysis of the effects of a massive number of genetic and molecular perturbations on the forces and resulting cell mechanics.

scholarly journals Modulating Tumor Cell Functions by Tunable Nanopatterned Ligand Presentation

Nanomaterials ◽  
2020 ◽  
Vol 10 (2) ◽  
pp. 212
Author(s):  
Katharina Amschler ◽  
Michael P. Schön
Keyword(s):  
Extracellular Matrix ◽  
Tumor Cell ◽  
Cell Fate ◽  
Epithelial Mesenchymal Transition ◽  
Model Systems ◽  
Cellular Functions ◽  
Biophysical Parameters ◽  
Ligand Density ◽  
Mesenchymal Transition ◽  
Cell Functions

Cancer comprises a large group of complex diseases which arise from the misrouted interplay of mutated cells with other cells and the extracellular matrix. The extracellular matrix is a highly dynamic structure providing biochemical and biophysical cues that regulate tumor cell behavior. While the relevance of biochemical signals has been appreciated, the complex input of biophysical properties like the variation of ligand density and distribution is a relatively new field in cancer research. Nanotechnology has become a very promising tool to mimic the physiological dimension of biophysical signals and their positive (i.e., growth-promoting) and negative (i.e., anti-tumoral or cytotoxic) effects on cellular functions. Here, we review tumor-associated cellular functions such as proliferation, epithelial-mesenchymal transition (EMT), invasion, and phenotype switch that are regulated by biophysical parameters such as ligand density or substrate elasticity. We also address the question of how such factors exert inhibitory or even toxic effects upon tumor cells. We describe three principles of nanostructured model systems based on block copolymer nanolithography, electron beam lithography, and DNA origami that have contributed to our understanding of how biophysical signals direct cancer cell fate.

scholarly journals Two-dimensional TIRF-SIM–traction force microscopy (2D TIRF-SIM-TFM)

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Liliana Barbieri ◽  
Huw Colin-York ◽  
Kseniya Korobchevskaya ◽  
Di Li ◽  
Deanna L. Wolfson ◽  
...  
Keyword(s):  
Resolution Enhancement ◽  
Traction Force ◽  
Super Resolution ◽  
Traction Force Microscopy ◽  
Two Dimensional ◽  
Structured Illumination ◽  
Structured Illumination Microscopy ◽  
Force Microscopy ◽  
Health And Disease ◽  
Spatio Temporal

AbstractQuantifying small, rapidly evolving forces generated by cells is a major challenge for the understanding of biomechanics and mechanobiology in health and disease. Traction force microscopy remains one of the most broadly applied force probing technologies but typically restricts itself to slow events over seconds and micron-scale displacements. Here, we improve >2-fold spatially and >10-fold temporally the resolution of planar cellular force probing compared to its related conventional modalities by combining fast two-dimensional total internal reflection fluorescence super-resolution structured illumination microscopy and traction force microscopy. This live-cell 2D TIRF-SIM-TFM methodology offers a combination of spatio-temporal resolution enhancement relevant to forces on the nano- and sub-second scales, opening up new aspects of mechanobiology to analysis.

Structural evolution and acoustic phonon behavior in crystalline PTFE latex films

2003 ◽  
Vol 779 ◽  
Author(s):  
M. Pierno ◽  
C.S. Casari ◽  
A. Li Bassi ◽  
M.G. Beghi ◽  
R. Piazza ◽  
...  
Keyword(s):  
Structural Evolution ◽  
Crystalline Polymer ◽  
Model Systems ◽  
Fibrillar Structure ◽  
Sintering Process ◽  
Latex Films ◽  
Force Microscopy ◽  
Crystalline Polymers ◽  
Atomic Force ◽  
Acoustic Excitations

AbstractThe structural evolution of polytetrafluoroethylene (PTFE) crystalline polymer latex films is studied at hundreds nanometer length scale by atomic force microscopy and Brillouin light scattering. In a controlled sintering process the transition is observed from the original particle distribution towards a ‘fibrillar’ structure of crystalline regions embedded in a disordered matrix. This transition is accompanied by a cross-over from localized acoustic excitations to propagating acoustic phonons, related to mesoscopic elastic properties. After sintering, a ‘mark’ of the original particulate structure persists, suggesting that filming of crystalline polymers may be analogous to sintering of ceramic powders. Films of crystalline polymers can thus be exploited as model systems to study the elasto-optical properties of granular and disordered media.

scholarly journals Different Cell Migration Modes: Insights from Traction Force Microscopy and Modeling

2021 ◽  
Vol 120 (3) ◽  
pp. 113a
Author(s):  
Wouter-Jan Rappel ◽  
Elisabeth Ghabache ◽  
Yuansheng Cao ◽  
Yuchuan Miao ◽  
Alexander Groisman ◽  
...  
Keyword(s):  
Cell Migration ◽  
Traction Force ◽  
Traction Force Microscopy ◽  
Force Microscopy

scholarly journals Epifluorescence-based three-dimensional traction force microscopy

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Lauren Hazlett ◽  
Alexander K. Landauer ◽  
Mohak Patel ◽  
Hadley A. Witt ◽  
Jin Yang ◽  
...  
Keyword(s):  
Spatial Frequency ◽  
Open Source ◽  
Single Particle ◽  
Three Dimensional ◽  
Traction Force ◽  
High Spatial Frequency ◽  
Epifluorescence Microscopy ◽  
Traction Force Microscopy ◽  
Force Microscopy ◽  
Out Of Plane

Abstract We introduce a novel method to compute three-dimensional (3D) displacements and both in-plane and out-of-plane tractions on nominally planar transparent materials using standard epifluorescence microscopy. Despite the importance of out-of-plane components to fully understanding cell behavior, epifluorescence images are generally not used for 3D traction force microscopy (TFM) experiments due to limitations in spatial resolution and measuring out-of-plane motion. To extend an epifluorescence-based technique to 3D, we employ a topology-based single particle tracking algorithm to reconstruct high spatial-frequency 3D motion fields from densely seeded single-particle layer images. Using an open-source finite element (FE) based solver, we then compute the 3D full-field stress and strain and surface traction fields. We demonstrate this technique by measuring tractions generated by both single human neutrophils and multicellular monolayers of Madin–Darby canine kidney cells, highlighting its acuity in reconstructing both individual and collective cellular tractions. In summary, this represents a new, easily accessible method for calculating fully three-dimensional displacement and 3D surface tractions at high spatial frequency from epifluorescence images. We released and support the complete technique as a free and open-source code package.

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