Automated detection, tracking and motion analysis of cytoskeletal keratin filaments in microscopic time-lapse fluorescence recordings
|D. Kotsur, R. Yakobenchuk, J. Mattes, R. Leube, R. Windoffer. Automated detection, tracking and motion analysis of cytoskeletal keratin filaments in microscopic time-lapse fluorescence recordings. pages Poster No. 135, 1, 2018.|
|Seiten||Poster No. 135|
Keratin networks impact mechanical properties of epithelial cells. Keratin network topology is remarkably variable between different tissues and cell types. The most obvious differences are due to filament bundling and branching.
We developed image analysis tools to identify and quantify different categories of keratin filament organization. These tools allow the automatic detection and tracking of individual filaments in living cells producing fluorescent keratins. They further facilitate monitoring filament deformations.
An active-contour-based algorithm was developed to track individual keratin filament segments within their respective networks using microscopic fluorescence recordings of fluorescently labelled keratins. First, noise, speckles and other artefacts are removed to improve the fidelity of keratin filament detection as structures of interest. The tracking algorithm takes the resulting filaments as starting points and follows their displacement over time. Each filament position in a given time-frame is represented by a parametric curve. The application allows accurate quantification of motion parameters such as movement and curvature dynamics in the defined keratin filament segments.
The new workflow enables us to classify and analyze different filament subgroups within living cells and link their occurrence to specific cellular conditions.