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

Background

Mitosis is a highly regulated stage of the cell cycle where multiple subcellular structures take part in a complex chain of events that culminate in chromosome segregation. This involves, among various steps, disassembly of adhesion complexes, reorganization of the cytoskeleton, and migration of duplicated centrosomes along the nuclear envelope so that a bipolar spindle can form. Players involved in this process include microtubule-associated motors kinesin 5, dynein, actin, and myosin II. How the dynamic changes in all these events are coordinated in space and time to ensure efficient centrosome separation and spindle assembly, remains unknown.

Recent advances in live-cell imaging and image analysis techniques made it possible to access the subcellular environment and quantitatively examine its underlying mechanisms. However, available tracking tools are not fine-tuned for the constrains and motion dynamics of centrosome pairs. This limits their tracking performance, and often demands for exhaustive parameter optimization. Moreover, when studying the dynamics of spindle formation, it is often necessary to analyze centrosomes movement in reference to the cellular and nuclear membrane; however, the available computational tools do not directly allow the analysis of the coordinated changes between different structures, in specific subcellular frames of reference. Driven by these computational limitations and the need to better characterize the crosstalk between subcellular structures during mitotic entry, Castro et al developed the open-source software Trackosome [1]. This novel computational tool enables a quantitative analysis of the spatiotemporal dynamics of three cellular components: centrosomes, nuclear envelope and cellular membrane.

Key findings and developments

Tool description

Trackosome is a freely available open-source computational tool to track the centrosomes and reconstruct the nuclear and cellular membranes, based on live imaging datasets, where the structures of interest are independently tagged. The toolbox runs in MATLAB and provides a graphical user interface for easy and efficient access to the tracking and analysis algorithms. The tool has two modules: “centrosome dynamics”, used for tracking centrosomes or other subcellular organelles in 3D and studying their spatiotemporal relations with the nucleus and cell membrane; and “nuclear envelope fluctuations”, used to reconstruct, measure and analyse the dynamic fluctuations of the nuclear membrane (or others) in 2D. Trackosome measures membrane movement in a model-free condition, making it viable for irregularly shaped nuclei. Trackosome can be downloaded from https://github.com/Trackosome

Key findings

Tracking and trajectory analysis of centrosomes is performed in the Trackosome toolbox through the «centrosomes dynamics»module. In a test setup, this module allowed tracking centrosomes with high fidelity even in highly noisy environments.

The authors went on to explore the potential of the tool for following dynamics of cellular organization during early spindle assembly. Trackosome allowed quantification of specific spatiotemporal relations between the centrosome pairs and nuclear and cell membranes, during mitotic entry. Trackosome was able to reconstruct the membranes’ surface, together with the centrosomes’ trajectories in 3D. Moreover it also allowed obtaining quantitative metrics of the intracellular reorganization that occurs in cells as they enter mitosis, namely the distance and angles between centrosomes, the eccentricity of the nuclear and cellular membranes, and the angles between the major axis of the nucleus, cell and centrosomes.

Using Trackosome, the authors were able to study centrosome trajectories, and show that they are not independent. The authors followed cell development in two cell lines, until nuclear breakdown. They found that during this stage, nuclear shape remained approximately constant and correlated with the label of chromatin, while the centrosomes exhibited complex trajectories resembling a search/adaptive path around the nucleus. To infer about the coordination of movement between the centrosomes, their trajectories were analyzed using the nucleus as a reference (which is made possible by Trackosome algorithms). The results indicated a considerable degree of coordination and synchrony among trajectory pairs. The authors discuss the hypothesis of synchronous variation of the forces applied to both centrosomes, probably driven by kinesin-5 or dynein.

The authors then used Trackosome to analyse the dynamic morphology of the nuclear envelope, using Trackosome’s “membrane fluctuations” module. The membrane oscillations are determined by calculating the orthogonal displacement of each point of the membrane with respect to its medial position. The authors were able to quantify and compare the nuclear deformations for cells in interphase and mitosis. They were able to confirm that in interphase, cells present subtle but measurable nuclear membrane movements. This behavior changes in prophase, where there is an increase of the fluctuations amplitude, reflecting the occurrence of nucleus-wide deformations. The authors explored whether Trackosome would be able to detect fluctuations of the nuclear envelope based on pharmacological alterations of the cytoskeleton and the microtubule networks. They found that disruption of the microtubule cytoskeleton significantly reduces the large scale deformations of the nucleus during this stage. The authors conclude that overall, Trackosome is a powerful tool to help unravel new elements in the spatiotemporal dynamics of subcellular structures.

What I like about this preprint

I like this preprint because in it the authors identified a gap in the currently available tools for image analysis of sub-cellular structures during the process of mitosis, and went on to create their own toolbox, and validate it in different settings. I think method development and validation is extremely important in science, and it helps not only the developers, but is useful to the scientific community in general. I also like that the authors made the tool freely available, in the spirit of open science.

References

1. Castro D., et al, Trackosome: a computational toolbox to study the spatiotemporal dynamics of centrosomes, nuclear envelope and cellular membrane, bioRxiv, 2020.
2. https://github.com/Trackosome/

 

 

doi: https://doi.org/10.1242/prelights.22554

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