An Open-source Python Tool for Traction Force Microscopy on Micropatterned Substrates.

Abstract

Cell-generated forces play a critical role in driving and regulating complex biological processes, such as cell migration and division and cell and tissue morphogenesis in development and disease. Traction force microscopy (TFM) is an established technique developed in the field of mechanobiology used to quantify cellular forces exerted on soft substrates and internal mechanical tissue stresses. TFM measures cell-generated traction forces in 2D or 3D environments with varying mechanical and biochemical properties. This technique involves embedding fiducial markers in the substrate, imaging substrate deformations caused by the cells, and using mathematical models to infer forces. This protocol compiles procedures from various previously published studies and software packages and describes how to perform TFM on 2D micropatterned substrates. Although not the focus of this protocol, the methods and software packages shown here also allow to perform monolayer stress microscopy (MSM), a method to calculate internal mechanical stress within the cells by modeling them as a thin plate with linear and homogeneous material properties. TFM and MSM are non-invasive methods capable of yielding spatially and temporally resolved force and stress maps with high throughput. As such, they enable the generation of rich datasets, which can provide valuable insights into the roles of cell-generated forces in various physiological and pathological processes. Key features • TFM and MSM protocol for 2D micropatterned polyacrylamide substrates, from sample preparation over imaging to data analysis with provided code. • Sample preparation method is based on Tseng et al. [1]. • TFM analysis is done with Python custom code and is optimized for batch analysis of movies. • MSM analysis is done with pyTFM from Bauer et al. [2].