High-resolution traction force microscopy on small focal adhesions - improved accuracy through optimal marker distribution and optical flow tracking.
The accurate determination of cellular forces using Traction Force Microscopy at increasingly small focal attachments to the extracellular environment presents an important yet substantial technical challenge. In these measurements, uncertainty regarding accuracy is prominent since experimental calibration frameworks at this size scale are fraught with errors - denying a gold standard against which accuracy of TFM methods can be judged. Therefore, we have developed a simulation platform for generating synthetic traction images that can be used as a benchmark to quantify the influence of critical experimental parameters and the associated errors. Using this approach, we show that TFM accuracy can be improved >35% compared to the standard approach by placing fluorescent beads as densely and closely as possible to the site of applied traction. Moreover, we use the platform to test tracking algorithms based on optical flow that measure deformation directly at the beads and show that these can dramatically outperform classical particle image velocimetry algorithms in terms of noise sensitivity and error. We then report how optimized experimental and numerical strategy can improve traction map accuracy, and further provide the best available benchmark to date for defining practical limits to TFM accuracy as a function of focal adhesion size.
Biomechanics Laboratory, University Hospital Balgrist, University of Zurich, 8008 Zürich, Switzerland.|Institute for Biomechanics, ETH Zurich, 8008 Zürich, Switzerland.
Claude N
CN
Holenstein
Biomechanics Laboratory, University Hospital Balgrist, University of Zurich, 8008 Zürich, Switzerland.|Institute for Biomechanics, ETH Zurich, 8008 Zürich, Switzerland.
Unai
U
Silvan
Biomechanics Laboratory, University Hospital Balgrist, University of Zurich, 8008 Zürich, Switzerland.|Institute for Biomechanics, ETH Zurich, 8008 Zürich, Switzerland.
Jess G
JG
Snedeker
D000465:Algorithms; D002448:Cell Adhesion; D022001:Focal Adhesions; D007091:Image Processing, Computer-Assisted; D008853:Microscopy / Q000379:methods*