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 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.

Automated summary

The formation and dynamics of cytoskeletal patterns are important for biological functions and can provide insights into homeostasis and pathological alterations. A quantitative analysis is needed for systematic quantification of structures and dynamics, and an upgraded algorithm, FilamentSensor 2.0, allows for automatic detection and tracking of fibrous structures for real-time data extraction and cell event monitoring.