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Studying the Cytoskeleton

Studying the Cytoskeleton

The cytoskeletal architecture can be studied using different microscopic and biochemical techniques. Electron microscopy was instrumental in discovering the cytoskeletal architecture around the 1960s, which allowed obtaining structural information at a high-resolution level. However, the sample preparation procedure often limits this ability in biological samples. Several protocols have been developed over the years to optimize sample preparation. In one of the protocols known as rotary...

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Related Experiment Video

Updated: Jun 14, 2025

Using Microfluidics and Fluorescence Microscopy to Study the Assembly Dynamics of Single Actin Filaments and Bundles

Using Microfluidics and Fluorescence Microscopy to Study the Assembly Dynamics of Single Actin Filaments and Bundles

Published on: May 5, 2022

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

Dhruv Khatri¹, Shivani A Yadav¹, Chaitanya A Athale¹

¹Division of Biology, Indian Institute of Science Education and Research Pune (IISER Pune), Pashan, Pune, Maharashtra 411008, India.

Bioinformatics (Oxford, England)

|September 3, 2024

Summary

This summary is machine-generated.

KnotResolver is a new computational tool that tracks complex, self-intersecting microtubule filaments in gliding assays. This method overcomes limitations of existing tools for analyzing dynamic biological structures.

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Area of Science:

Biophysics
Computational Biology
Cell Biology

Background:

Traditional computational tools struggle to quantify microtubule dynamics in gliding assays when filaments are highly curved or self-intersecting.
Existing methods are limited to analyzing non-intersecting, rod-like filaments, hindering the study of complex biological structures.

Purpose of the Study:

To develop and present KnotResolver, a novel computational image-analysis pipeline for tracking highly curved, self-intersecting looped filaments (knots) in microscopy time series.
To overcome the limitations of current tracking tools in analyzing complex microtubule dynamics.

Main Methods:

The pipeline integrates filament segmentation and cross-over identification using a directed graph representation.
Nodes in the graph represent cross-overs, and edges represent the connecting paths, allowing for complex filament reconstruction.
Graphs are mapped back to contours, minimizing distance to a reference for sub-pixel accuracy and noise robustness.

Main Results:

KnotResolver successfully tracks image time series of highly curved, self-intersecting looped filaments by resolving cross-overs.
The method achieves sub-pixel accuracy in contour detection and demonstrates robustness to noise.
Demonstrated utility in quantifying flagella-like curvature dynamics and wave-like oscillations of clamped microtubules in gliding assays.

Conclusions:

KnotResolver provides a robust solution for analyzing complex microtubule dynamics in gliding assays, particularly for self-intersecting and highly curved filaments.
The open-source availability of the MATLAB-based code facilitates broader application in biophysical and cell biology research.
This tool enhances the quantification of dynamic biological structures, opening new avenues for research in motor-driven transport and cytoskeletal dynamics.