Broadfield Precision Distortion and Displacement Analysis (BPDDA): An Automated Distortion Correction and Stitching Method for Traction Force Microscopy

Abstract

During tissue development and wound healing processes, cells generate and transmit mechanical forces to the surrounding matrix. Traction force microscopy (TFM) is widely used to measure these forces on soft gels, but conventional TFM is usually limited to a single field of view. This small area makes it difficult to study how local forces are organized across large cell monolayers. This thesis develops a large field TFM method and uses it to analyze collective mechanics in wound healing. Compared to previous studies limited to a single imaging field, this approach enables traction force measurements over image sizes exceeding 2 mm. Wound closure relies on coordinated force generation across large cell assemblies rather than isolated single cell mechanics. By enabling direct measurement of traction forces over tissue scale areas, the large field TFM approach provides new insight into how local cellular forces are organized and integrated to drive collective closure dynamics. A distortion correction and stitching workflow, termed Broadfield Precision Distortion and Displacement Analysis (BPDDA), was first established. A micropillar calibration board was used to measure the distortion field of the microscope, and a fourth order polynomial fit was used to correct it. After distortion correction, position errors were reduced to below one pixel. This level of geometric control is necessary when bead displacements are only a few tenths of a micrometer. To improve displacement detection, a hybrid method called MPIV+Track was then designed. It combines windowed particle image velocimetry with single-particle tracking. Tests on simulated displacement fields that mimic cell experiments showed that MPIV+Track detects small displacements better than MPIV or Track alone. It produced more detailed vectors than MPIV 4 and fewer false vectors than Track, especially in noisy images or images with dense bead distribution. BPDDA was applied to MEC1 cell monolayers that were closing circular wounds on soft gels. At early times after stencil removal, a thin ring of inward traction at the wound edge was detected in the traction maps. At later times, this ring was replaced by a wider traction band around the wound, which was found to support collective migration. TGF-β treatment increased traction magnitude and directional order near the edge, whereas ROCK inhibition reduced traction and altered the balance between edge forces and forces in the interior of the monolayer. Unlike small wounds dominated by a purse string mechanism, closure of the large wounds studied here involves traction forces generated by cells far from the wound edge. Finally, the method was used to compare control HeLa cells with HeLa cells in which IQGAP1 level was reduced. These changes indicate that IQGAP1 mediates mechanosensation and force transmission at the cell–matrix interface. Earlier work has suggested roles for IQGAP1 in cytoskeletal organization and migration (1), whereas this study directly measures how IQGAP1 depletion alters traction force magnitude and stiffness dependent force responses. Overall, these results demonstrate that combining BPDDA with MPIV+Track enables TFM measurements with sub-pixel geometric accuracy over millimeter-scale areas. This method provides a practical basis for future studies of cell monolayer mechanics. Quantitative measurements of monolayer mechanics enable direct study of how local cellular forces are coordinated across cell collectives to drive tissue level behaviors such as wound healing and tissue morphogenesis