2024/04/18 by Dhruv Khatri, Khatri, Dhruv, Shivani A. Yadav +3
Engineering · #Advanced Materials and Mechanics #Biological Physics (physics.bio-ph) #Biomolecules (q-bio.BM) #FOS: Biological sciences #FOS: Physical sciences #Nanofabrication and Lithography Techniques #Quantitative Methods (q-bio.QM)
paper · pdf · doi:10.48550/arxiv.2404.12029
openalex publication_date 2024/04/18 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Quantification of microscopy time-series of in vitro reconstituted motor driven microtubule (MT) transport in 'gliding assays' is typically performed using computational object tracking tools. However, these are limited to non-intersecting and rod-like filaments. Here, 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. We demonstrate the utility of the tool by segmentation and tracking MTs from experiments with dynein-driven wave like filament looping. The accuracy of contour detection is sub-pixel accuracy, and Dice scores indicate a robustness to noise, better than currently used tools. Thus KnotResolver overcomes multiple limitations of widely used tools in microscopy of cytoskeletal filament-like structures.