KnotResolver: tracking self-intersecting filaments in microscopy using directed graphs

Abstract

AbstractMotivationQuantification of microscopy time series of in vitro reconstituted motor-driven microtubule transport in “gliding assays” is typically performed using computational object tracking tools. However, these are limited to non-intersecting and rod-like filaments.ResultsHere, we describe a novel computational image-analysis pipeline, KnotResolver, to track image time series of highly curved self-intersecting looped filaments (knots) by resolving cross-overs. The code integrates filament segmentation and cross-over or “knot” identification based on directed graph representation, where nodes represent cross-overs and edges represent the path connecting them. The graphs are mapped back to contours and the distance to a reference minimized. The accuracy of contour detection is sub-pixel with a robustness to noise. We demonstrate the utility of KnotResolver by automatically quantifying “flagella-like” curvature dynamics and wave-like oscillations of clamped microtubules in a “gliding assay.”