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A Multi-Purpose Worm Tracker Based on FIM

Matthias Kiel, Dimitri Berh, Jens Daniel, Nils Otto, Adrian ter Steege, Xiaoyi Jiang, Eva Liebau, Benjamin Risse
doi: https://doi.org/10.1101/352948
Matthias Kiel
1Departement of Molecular Physiology, Institute for Animal Physiology,University of Muenster, Schlossplatz 8, 48143 Muenster, Germany
2Institute of Hygiene, University of Muenster, Mendelstraße 7, 48149 Münster, Germany
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Dimitri Berh
4Department of Mathematics and Computer Science, University of Muenster, Einsteinstraße 62, 48149 Münster, Germany
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Jens Daniel
1Departement of Molecular Physiology, Institute for Animal Physiology,University of Muenster, Schlossplatz 8, 48143 Muenster, Germany
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Nils Otto
3Centre for Neural Circuits & Behaviour, University of Oxford, Mansfield Road, Oxford, United Kingdom
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Adrian ter Steege
1Departement of Molecular Physiology, Institute for Animal Physiology,University of Muenster, Schlossplatz 8, 48143 Muenster, Germany
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Xiaoyi Jiang
4Department of Mathematics and Computer Science, University of Muenster, Einsteinstraße 62, 48149 Münster, Germany
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Eva Liebau
1Departement of Molecular Physiology, Institute for Animal Physiology,University of Muenster, Schlossplatz 8, 48143 Muenster, Germany
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Benjamin Risse
4Department of Mathematics and Computer Science, University of Muenster, Einsteinstraße 62, 48149 Münster, Germany
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Abstract

The analysis of behavioural traits of Caenorhabditis elegans is an important method for understanding neuromuscular functions and diseases. Since C. elegans is a small and translucent animal which conducts a variety of complex movement patterns many different imaging and tracking protocols are used for different behavioural traits. Thus a unified multi-purpose imaging and tracking system for multiple behavioural assays would be favourable to improve statistical strength and comparability. Here we present a novel worm tracking toolbox based on the FIM (Frustrated total internal reflection (FTIR) based Imaging Method) system incorporating a variety of different behavioural assays into a single imaging and tracking setup.

First, we apply the FTIR-based imaging method to C. elegans, thus we are able to improve the overall image quality compared to state of the art recording techniques. This method is easy to use and can be utilised to image animals during crawling on agar and trashing in water. Second, we extended the existing FIMTrack software to extract skeleton-based posture and motion features of multiple worms with very high accuracy in a comparatively large field-of-view. Third, we integrated a variety of different assays into this system. We carried out chemotaxis assays both with attractant and repellent chemicals. A novel electrotaxis dome compatible with FIM allows locomotion analyses that are not corrupted by random aberrations in unrestricted movement. Additionally, the FIM based worm tracker is able to analyse thrashing behaviour of multiple worms automatically with a high accuracy. Finally we demonstrate the capacity of the FIM based worm tracker to observe GFP signals in C. elegans worms. We tested our new C. elegans tracking suite with mutant strains of the ubiquitin-fold modifier 1 (Ufm1) cascade. We identified intermediate chemosensory phenotypes in Ufm1 cascade mutants which were previously undetected.

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The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
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Posted June 21, 2018.
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A Multi-Purpose Worm Tracker Based on FIM
Matthias Kiel, Dimitri Berh, Jens Daniel, Nils Otto, Adrian ter Steege, Xiaoyi Jiang, Eva Liebau, Benjamin Risse
bioRxiv 352948; doi: https://doi.org/10.1101/352948
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A Multi-Purpose Worm Tracker Based on FIM
Matthias Kiel, Dimitri Berh, Jens Daniel, Nils Otto, Adrian ter Steege, Xiaoyi Jiang, Eva Liebau, Benjamin Risse
bioRxiv 352948; doi: https://doi.org/10.1101/352948

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