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Trackosome: a computational toolbox to study the spatiotemporal dynamics of centrosomes, nuclear envelope and cellular membrane.

Domingos CastroVanessa NunesJoana T LimaJorge G FerreiraPaulo de Castro Aguiar
Published in: Journal of cell science (2020)
During the initial stages of mitosis, multiple mechanisms drive centrosome separation and positioning. How they are coordinated to promote centrosome migration to opposite sides of the nucleus remains unclear. Here, we present Trackosome, an open-source image analysis software for tracking centrosomes and reconstructing nuclear and cellular membranes, based on volumetric live-imaging data. The toolbox runs in MATLAB and provides a graphical user interface for easy access to the tracking and analysis algorithms. It provides detailed quantification of the spatiotemporal relationships between centrosomes, nuclear envelope and cellular membrane, and can also be used to measure the dynamic fluctuations of the nuclear envelope. These fluctuations are important because they are related to the mechanical forces exerted on the nucleus by its adjacent cytoskeletal structures. Unlike previous algorithms based on circular or elliptical approximations, Trackosome measures membrane movement in a model-free condition, making it viable for irregularly shaped nuclei. Using Trackosome, we demonstrate significant correlations between the movements of the centrosomes, and identify specific oscillation modes of the nuclear envelope. Overall, Trackosome is a powerful tool that can be used to help unravel new elements in the spatiotemporal dynamics of subcellular structures.
Keyphrases
  • machine learning
  • deep learning
  • high frequency
  • big data
  • mass spectrometry