Mechanotransduction encompasses the role of mechanical forces in controlling cell behavior by activating signal transduction pathways. Most forces at a cellular level are caused by myosin II, which contracts and cross-links actin. Myosin II-dependent forces are transmitted through the actin cytoskeleton to molecular endpoints that promote specific cellular outcomes, e.g., cell proliferation, adhesion, or migration. For example, most adhesive and migratory phenomena are mechanically linked by a molecular clutch comprised of mechanosensitive scaffolds. Myosin II activation and mechanosensitive molecular mechanisms are finely tuned and spatiotemporally integrated to coordinate morphogenetic events during development. Mechanical events dependent on myosin II also participate in tumor cell proliferation, invasion, and metastatic dissemination. Specifically, tumor cells alter the mechanical properties of the microenvironment to create favorable conditions for proliferation and/or dissemination. These observations position myosin II-dependent force generation and mechanotransduction at the crossroads between normal development and cancer.

A group of phosphorylatable serine residues within the nonhelical domain of NMII-B controls the ability of NMII-B to generate stable migratory front–rear polarity.

Traction Force Microscopy (TFM) is a widespread method used to recover cellular tractions from the deformation that they cause in their surrounding substrate. Particle Image Velocimetry (PIV) is commonly used to quantify the substrate’s deformations, due to its simplicity and efficiency. However, PIV relies on a block-matching scheme that easily underestimates the deformations. This is especially relevant in the case of large, locally non-uniform deformations as those usually found in the vicinity of a cell’s adhesions to the substrate. To overcome these limitations, we formulate the calculation of the deformation of the substrate in TFM as a non-rigid image registration process that warps the image of the unstressed material to match the image of the stressed one. In particular, we propose to use a B-spline -based Free Form Deformation (FFD) algorithm that uses a connected deformable mesh to model a wide range of flexible deformations caused by cellular tractions. Our FFD approach is validated in 3D fields using synthetic (simulated) data as well as with experimental data obtained using isolated endothelial cells lying on a deformable, polyacrylamide substrate. Our results show that FFD outperforms PIV providing a deformation field that allows a better recovery of the magnitude and orientation of tractions. Together, these results demonstrate the added value of the FFD algorithm for improving the accuracy of traction recovery.