FilamentSensor 2.0: An open-source modular toolbox for 2D/3D cytoskeletal filament tracking

Cytoskeletal pattern formation and structural dynamics are key to a variety of biological functions and a detailed and quantitative analysis yields insight into finely tuned and well-balanced homeostasis and potential pathological alterations. High content life cell imaging of fluorescently labeled...

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Bibliographic Details
Published in:PloS one 2023-02, Vol.18 (2), p.e0279336-e0279336
Main Authors: Hauke, Lara, Primeßnig, Andreas, Eltzner, Benjamin, Radwitz, Jennifer, Huckemann, Stefan F, Rehfeldt, Florian
Format: Article
Language:English
Subjects:
Algorithms
Biology and Life Sciences
Biosensors
Cell cycle
Computer and Information Sciences
Cytoskeleton
Dynamic structural analysis
Engineering and Technology
Health aspects
Homeostasis
Image segmentation
Mechanical properties
Open source software
Pattern formation
Physical Sciences
Quantitative analysis
Research and Analysis Methods
Segmentation
Tracking
User interface
Workflow
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Summary:Cytoskeletal pattern formation and structural dynamics are key to a variety of biological functions and a detailed and quantitative analysis yields insight into finely tuned and well-balanced homeostasis and potential pathological alterations. High content life cell imaging of fluorescently labeled cytoskeletal elements under physiological conditions is nowadays state-of-the-art and can record time lapse data for detailed experimental studies. However, systematic quantification of structures and in particular the dynamics (i.e. frame-to-frame tracking) are essential. Here, an unbiased, quantitative, and robust analysis workflow that can be highly automatized is needed. For this purpose we upgraded and expanded our fiber detection algorithm FilamentSensor (FS) to the FilamentSensor 2.0 (FS2.0) toolbox, allowing for automatic detection and segmentation of fibrous structures and the extraction of relevant data (center of mass, length, width, orientation, curvature) in real-time as well as tracking of these objects over time and cell event monitoring.
ISSN:1932-6203
1932-6203
DOI:10.1371/journal.pone.0279336