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pyTFM: A tool for traction force and monolayer stress microscopy
- Source :
- PLoS Computational Biology, Vol 17, Iss 6, p e1008364 (2021), PLoS Computational Biology
- Publication Year :
- 2021
- Publisher :
- Public Library of Science (PLoS), 2021.
-
Abstract
- Cellular force generation and force transmission are of fundamental importance for numerous biological processes and can be studied with the methods of Traction Force Microscopy (TFM) and Monolayer Stress Microscopy. Traction Force Microscopy and Monolayer Stress Microscopy solve the inverse problem of reconstructing cell-matrix tractions and inter- and intra-cellular stresses from the measured cell force-induced deformations of an adhesive substrate with known elasticity. Although several laboratories have developed software for Traction Force Microscopy and Monolayer Stress Microscopy computations, there is currently no software package available that allows non-expert users to perform a full evaluation of such experiments. Here we present pyTFM, a tool to perform Traction Force Microscopy and Monolayer Stress Microscopy on cell patches and cell layers grown in a 2-dimensional environment. pyTFM was optimized for ease-of-use; it is open-source and well documented (hosted at https://pytfm.readthedocs.io/) including usage examples and explanations of the theoretical background. pyTFM can be used as a standalone Python package or as an add-on to the image annotation tool ClickPoints. In combination with the ClickPoints environment, pyTFM allows the user to set all necessary analysis parameters, select regions of interest, examine the input data and intermediary results, and calculate a wide range of parameters describing forces, stresses, and their distribution. In this work, we also thoroughly analyze the accuracy and performance of the Traction Force Microscopy and Monolayer Stress Microscopy algorithms of pyTFM using synthetic and experimental data from epithelial cell patches.<br />Author summary The analysis of cellular force generation and transmission is an increasingly important aspect in the field of biological research. However, most methods for studying cellular force generation or transmission require complex calculations and have not yet been implemented in comprehensive, easy-to-use software. This is a major hurdle preventing a wider application in the field. Here we present pyTFM, an open-source Python package with a graphical user interface that can be used to evaluate cellular force generation in cells and cell colonies and force transfer within small cell patches and larger cell layers grown on the surface of an elastic substrate. In combination with the image annotation and tool ClickPoints, pyTFM allows the user to set all necessary analysis parameters, select regions of interest, examine the input data and intermediary results, and calculate a wide range of parameters describing cellular forces, stresses, and their distribution. Additionally, pyTFM can be used as standalone python library. pyTFM comes with an extensive documentation (hosted at https://pytfm.readthedocs.io/) including usage examples and explanations of the theoretical background.
- Subjects :
- 0301 basic medicine
Fluorescence-lifetime imaging microscopy
02 engineering and technology
Traction force microscopy
Physical Phenomena
Mathematical and Statistical Techniques
Microscopy
Biology (General)
Shear Stresses
Tractive force
Fourier Analysis
Ecology
Physics
Applied Mathematics
Simulation and Modeling
Classical Mechanics
021001 nanoscience & nanotechnology
Deformation
Computational Theory and Mathematics
Modeling and Simulation
Physical Sciences
Mechanical Stress
0210 nano-technology
Biological system
Algorithms
Research Article
Materials science
Imaging Techniques
QH301-705.5
Materials Science
Material Properties
Finite Element Analysis
Research and Analysis Methods
Stress (mechanics)
03 medical and health sciences
Cellular and Molecular Neuroscience
Fluorescence Imaging
Monolayer
Genetics
ddc:530
Molecular Biology
Ecology, Evolution, Behavior and Systematics
Damage Mechanics
Work (physics)
Biology and Life Sciences
Cell Biology
Elasticity (physics)
Elasticity
030104 developmental biology
Mathematics
Subjects
Details
- Language :
- English
- ISSN :
- 15537358
- Volume :
- 17
- Issue :
- 6
- Database :
- OpenAIRE
- Journal :
- PLoS Computational Biology
- Accession number :
- edsair.doi.dedup.....e288f48a1e54ab016d7f2495d5c86195