High-resolution traction force microscopy on small focal adhesions - improved accuracy through optimal marker distribution and optical flow tracking

Claude N Holenstein,Jess G Snedeker,Unai Silvan

doi:10.1038/srep41633

Abstract

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.

Highlights

Contribution of each factor to the overall result (Fig. 1)
We modeled traction as uniform horizontal shear stress at a focal adhesion modeled as a circular area with a diameter ranging from 0.5–5 μm, acting on a cubic substrate large enough to be considered as an elastic half-plane
Among our most important recommendations, we suggest that optical flow algorithms be harnessed to minimize tracking errors

Summary

Introduction

Contribution of each factor to the overall result (Fig. 1). Despite many experimental efforts, very little research has been done to adequately benchmark analytical approaches including all three sub-steps, as a representative simulation and calibration environment has yet to be fully established[5]. If the finite-element mesh is small enough compared to pixel size, the simulation allows us to reproduce the substrate deformation caused by cellular traction force in order to generate synthetic images that closely mimic the movement of beads as would be obtained in TFM Within this framework, we can parametrically explore the effects of any processing step separately and the resulting accuracy of the traction force reconstruction for a known input. We can parametrically explore the effects of any processing step separately and the resulting accuracy of the traction force reconstruction for a known input By using these synthetic images as a ground truth, we propose an alternative approach to track cell-induced deformations making use of the Lucas-Kanade optical flow algorithm[13] with an extension known as Kanade-Lucas-Tomasi (KLT) method to detect locally varying and large deformations using a pyramidal approach[14]. The performance of this approach is compared to the tracking algorithms commonly used in TFM which are based on image correlation calculated either on a regular grid without a priori knowledge of particle locations[7,15,16] or directly on the previously identified beads[6,12]

Methods

Results

Conclusion