An improved texture correlation algorithm to measure substrate–cytoskeletal network strain transfer under large compressive strain

Abstract

Force-induced deformation of tissues is transduced to the cytoskeletal (CSK) network within cells via focal adhesions. Previous studies have characterized transfer of strains of less than 15% from the substrate to the cell, using mitochondria as surrogate markers for CSK deformation. However, it is unclear if intracellular strains determined from mitochondrial displacement accurately reflect CSK network deformation. Furthermore, previous studies have not characterized substrate–CSK network strain transfer for strain magnitudes exceeding 15%, as can occur in vivo and in cell culture studies. Here, we developed and characterized a texture correlation algorithm to address the image distortion problem caused by large strain. We then used this algorithm to characterize large compressive strain (−40%) transfer from the substrate to the CSK in living cells, using fluorescently tagged actin to perform the tracking and both fluorescently tagged actin and talin to make validation measurements. With this approach, we were able to demonstrate explicitly that substrate strain transfers directly to CSK deformation in living cells undergoing large compressive deformation, and that the strain transfer ratios are independent of cell alignment. The tools and approaches developed here enable improved characterization of cell–matrix interactions under large deformation and in doing so, may reveal new insights into mechanotransduction mechanisms in such circumstances.