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CiliaQ – a simple, open-source software for automated quantification of ciliary morphology and fluorescence in 2D, 3D, and 4D images

View ORCID ProfileJan Niklas Hansen, Sebastian Rassmann, Birthe Stüven, View ORCID ProfileNathalie Jurisch-Yaksi, View ORCID ProfileDagmar Wachten
doi: https://doi.org/10.1101/2020.09.28.317065
Jan Niklas Hansen
1Institute of Innate Immunity, Biophysical Imaging, Medical Faculty, University of Bonn, 53127 Bonn, Germany
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  • For correspondence: jan.hansen@uni-bonn.de dwachten@uni-bonn.de
Sebastian Rassmann
1Institute of Innate Immunity, Biophysical Imaging, Medical Faculty, University of Bonn, 53127 Bonn, Germany
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Birthe Stüven
1Institute of Innate Immunity, Biophysical Imaging, Medical Faculty, University of Bonn, 53127 Bonn, Germany
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Nathalie Jurisch-Yaksi
2Department of Clinical and Molecular Medicine, The Faculty of Medicine, Norwegian University of Science and Technology, Trondheim, Norway
3Kavli Institute for Systems Neuroscience and Centre for Neural Computation, The Faculty of Medicine, Norwegian University of Science and Technology, Trondheim, Norway
4Department of Neurology and Clinical Neurophysiology, St. Olavs University Hospital, Trondheim, Norway
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Dagmar Wachten
1Institute of Innate Immunity, Biophysical Imaging, Medical Faculty, University of Bonn, 53127 Bonn, Germany
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  • For correspondence: jan.hansen@uni-bonn.de dwachten@uni-bonn.de
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Abstract

Cilia are hair-like membrane protrusions that emanate from the surface of most vertebrate cells and are classified into motile and primary cilia. Motile cilia move fluid flow or propel cells, while also fulfilling sensory functions. Primary cilia are immotile and act as a cellular antenna, translating environmental cues into cellular responses. Ciliary dysfunction leads to severe diseases, commonly termed ciliopathies. The molecular details underlying ciliopathies and ciliary function are, however, not well understood. Since cilia are small subcellular compartments, imaging-based approaches have been used to study them. However, tools to comprehensively analyze images are lacking. Automatic analysis approaches require commercial software and are limited to 2D analysis and only a few parameters. The widely used manual analysis approaches are time consuming, user-biased, and difficult to compare. Here, we present CiliaQ, a package of open-source, freely-available, and easy-to-use ImageJ plugins. CiliaQ allows high throughput analysis of 2D and 3D, static or time-lapse images from fluorescence microscopy of cilia in cell culture or tissues, and outputs a comprehensive list of parameters for ciliary morphology, length, bending, orientation, and fluorescence intensity, making it broadly applicable. We envision CiliaQ as a resource and platform for reproducible and comprehensive analysis of ciliary function in health and disease.

Competing Interest Statement

The authors have declared no competing interest.

Footnotes

  • Introduction and Discussion revised; Figure 7 and Section 2.5 added.

  • https://github.com/hansenjn/CiliaQ

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. All rights reserved. No reuse allowed without permission.
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Posted January 19, 2021.
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CiliaQ – a simple, open-source software for automated quantification of ciliary morphology and fluorescence in 2D, 3D, and 4D images
Jan Niklas Hansen, Sebastian Rassmann, Birthe Stüven, Nathalie Jurisch-Yaksi, Dagmar Wachten
bioRxiv 2020.09.28.317065; doi: https://doi.org/10.1101/2020.09.28.317065
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CiliaQ – a simple, open-source software for automated quantification of ciliary morphology and fluorescence in 2D, 3D, and 4D images
Jan Niklas Hansen, Sebastian Rassmann, Birthe Stüven, Nathalie Jurisch-Yaksi, Dagmar Wachten
bioRxiv 2020.09.28.317065; doi: https://doi.org/10.1101/2020.09.28.317065

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