Extracting Microtubule Networks from Superresolution Single-Molecule Localization Microscopy Data. Molecular Biology of the Cell, November 2016

By Zhen Zhang1, Yukako Nishimura1, and Pakorn Kanchanawong2,3

Molecular Biology of the Cell. November 2016. 28(2). 333-345. doi: 10.1091/mbc.E16-06-0421.

Abstract

Microtubule filaments form ubiquitous networks that specify spatial organization in cells. However, quantitative analysis of the microtubule networks is hampered by their complex architecture, limiting insights into the interplay between their organization and cellular functions. Although superresolution microscopy has greatly facilitated high-resolution imaging of microtubule filaments, the extraction of the complete filament networks from such dataset remains challenging. Here, we describe a computational tool for the automated retrieval of microtubule filaments from single-molecule-localization-based superresolution microscopy images. We present a user-friendly graphically-interfaced implementation and demonstrate a quantitative analysis of microtubule network architecture phenotypes in fibroblasts.

 

1Mechanobiology Institute, Singapore.
2Mechanobiology Institute, Singapore.
3Department of Biomedical Engineering, National University of Singapore.