Please use this identifier to cite or link to this item: https://doi.org/10.1186/s12859-017-1684-y
Title: An integrated enhancement and reconstruction strategy for the quantitative extraction of actin stress fibers from fluorescence micrographs
Authors: Zhang, Z 
Xia, S
Kanchanawong, P 
Keywords: Cells
Cytology
Extraction
Fluorescence
Fluorescence microscopy
Image analysis
Image segmentation
Open source software
Open systems
Piecewise linear techniques
Proteins
Sensitivity analysis
Software engineering
Stresses
Tissue culture
Actin cytoskeleton
Fluorescence micrograph
Micro pattern
Morphological analysis
Quantitative extraction
Stress fibers
TIRF
Tissue culture cells
Fibers
actin
algorithm
anisotropy
automation
cell shape
fluorescence microscopy
human
image enhancement
metabolism
procedures
software
stress fiber
tumor cell line
Actins
Algorithms
Anisotropy
Automation
Cell Line, Tumor
Cell Shape
Humans
Image Enhancement
Microscopy, Fluorescence
Software
Stress Fibers
Issue Date: 2017
Citation: Zhang, Z, Xia, S, Kanchanawong, P (2017). An integrated enhancement and reconstruction strategy for the quantitative extraction of actin stress fibers from fluorescence micrographs. BMC Bioinformatics 18 (1) : 268. ScholarBank@NUS Repository. https://doi.org/10.1186/s12859-017-1684-y
Rights: Attribution 4.0 International
Abstract: Background: The stress fibers are prominent organization of actin filaments that perform important functions in cellular processes such as migration, polarization, and traction force generation, and whose collective organization reflects the physiological and mechanical activities of the cells. Easily visualized by fluorescence microscopy, the stress fibers are widely used as qualitative descriptors of cell phenotypes. However, due to the complexity of the stress fibers and the presence of other actin-containing cellular features, images of stress fibers are relatively challenging to quantitatively analyze using previously developed approaches, requiring significant user intervention. This poses a challenge for the automation of their detection, segmentation, and quantitative analysis. Result: Here we describe an open-source software package, SFEX (Stress Fiber Extractor), which is geared for efficient enhancement, segmentation, and analysis of actin stress fibers in adherent tissue culture cells. Our method made use of a carefully chosen image filtering technique to enhance filamentous structures, effectively facilitating the detection and segmentation of stress fibers by binary thresholding. We subdivided the skeletons of stress fiber traces into piecewise-linear fragments, and used a set of geometric criteria to reconstruct the stress fiber networks by pairing appropriate fiber fragments. Our strategy enables the trajectory of a majority of stress fibers within the cells to be comprehensively extracted. We also present a method for quantifying the dimensions of the stress fibers using an image gradient-based approach. We determine the optimal parameter space using sensitivity analysis, and demonstrate the utility of our approach by analyzing actin stress fibers in cells cultured on various micropattern substrates. Conclusion: We present an open-source graphically-interfaced computational tool for the extraction and quantification of stress fibers in adherent cells with minimal user input. This facilitates the automated extraction of actin stress fibers from fluorescence images. We highlight their potential uses by analyzing images of cells with shapes constrained by fibronectin micropatterns. The method we reported here could serve as the first step in the detection and characterization of the spatial properties of actin stress fibers to enable further detailed morphological analysis. © 2017 The Author(s).
Source Title: BMC Bioinformatics
URI: https://scholarbank.nus.edu.sg/handle/10635/181279
ISSN: 14712105
DOI: 10.1186/s12859-017-1684-y
Rights: Attribution 4.0 International
Appears in Collections:Elements
Staff Publications

Show full item record
Files in This Item:
File Description SizeFormatAccess SettingsVersion 
10_1186_s12859-017-1684-y.pdf2.99 MBAdobe PDF

OPEN

NoneView/Download

SCOPUSTM   
Citations

4
checked on Nov 18, 2020

Page view(s)

6
checked on Nov 19, 2020

Google ScholarTM

Check

Altmetric


This item is licensed under a Creative Commons License Creative Commons