Work

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

Year: 2024

Type: article

Abstract: MOTIVATION: Quantification 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. RESULTS: 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. 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." AVAILABILITY AND IMPLEMENTATION: The MATLAB-based source code is released as OpenSource and is available at https://github.com/CyCelsLab/MTKnotResolver.

Source: Bioinformatics

DOI: 10.1093/bioinformatics/btae538

Authors: Dhruv Khatri, Shivani A Yadav, Chaitanya A Athale

Institution: Indian Institute of Science Education and Research Pune

Language: English

Topic: Cell Image Analysis Techniques

Subfield: Biophysics

Field: Biochemistry, Genetics and Molecular Biology

Domain: Life Sciences

Open Access status: gold

Estimated APC paid: $4,188

Funders: Department of Biotechnology, Ministry of Science and Technology, India, Council of Scientific and Industrial Research, India, Indo-French Centre for the Promotion of Advanced Research, Indian Institute of Science Education and Research Mohali