pyTFM: A tool for traction force and monolayer stress microscopy.
Journal
PLoS computational biology
ISSN: 1553-7358
Titre abrégé: PLoS Comput Biol
Pays: United States
ID NLM: 101238922
Informations de publication
Date de publication:
06 2021
06 2021
Historique:
received:
23
09
2020
accepted:
02
05
2021
revised:
01
07
2021
pubmed:
22
6
2021
medline:
14
10
2021
entrez:
21
6
2021
Statut:
epublish
Résumé
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.
Identifiants
pubmed: 34153027
doi: 10.1371/journal.pcbi.1008364
pii: PCOMPBIOL-D-20-01714
pmc: PMC8248623
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
e1008364Déclaration de conflit d'intérêts
The authors have declared that no competing interests exist.
Références
J Cell Biol. 2018 Sep 3;217(9):3031-3044
pubmed: 29980627
Biophys J. 2008 Jan 1;94(1):207-20
pubmed: 17827246
Proc Natl Acad Sci U S A. 2009 Dec 29;106(52):22108-13
pubmed: 20018765
Methods Cell Biol. 2015;125:269-87
pubmed: 25640434
Soft Matter. 2014 Apr 14;10(14):2414-23
pubmed: 24622969
PeerJ. 2014 Jun 19;2:e453
pubmed: 25024921
Nature. 2020 Sep;585(7825):357-362
pubmed: 32939066
Development. 2010 May;137(9):1407-20
pubmed: 20388652
Elife. 2014 Dec 05;3:e03282
pubmed: 25479385
Proc Natl Acad Sci U S A. 1997 Dec 9;94(25):13661-5
pubmed: 9391082
Biophys J. 1999 Apr;76(4):2307-16
pubmed: 10096925
Am J Physiol Cell Physiol. 2002 Mar;282(3):C595-605
pubmed: 11832345
Nat Methods. 2015 Jul;12(7):653-6
pubmed: 26030446
Soft Matter. 2014 Oct 21;10(39):7681-2
pubmed: 25186230
Nat Mater. 2011 Jun;10(6):469-75
pubmed: 21602808
J Theor Biol. 2006 Oct 7;242(3):607-16
pubmed: 16782134
Proc Natl Acad Sci U S A. 2001 Jul 3;98(14):7765-70
pubmed: 11438729
Nat Methods. 2016 Feb;13(2):171-6
pubmed: 26641311
Elife. 2020 Apr 30;9:
pubmed: 32352379
PLoS One. 2013;8(2):e55172
pubmed: 23468843
Cytoskeleton (Hoboken). 2013 Apr;70(4):201-14
pubmed: 23444002
Nat Methods. 2020 Mar;17(3):261-272
pubmed: 32015543
Cell. 2006 Aug 25;126(4):677-89
pubmed: 16923388
Sci Rep. 2019 Jan 24;9(1):539
pubmed: 30679578
Adv Drug Deliv Rev. 2007 Nov 10;59(13):1329-39
pubmed: 17900747
J Biomech Eng. 2013 Jul 1;135(7):71009
pubmed: 23720059
Biorheology. 2006;43(6):721-8
pubmed: 17148855
Biorheology. 2009;46(3):191-205
pubmed: 19581727