Shaw, M;
Zhan, H;
Elmi, M;
Pawar, V;
Essmann, C;
Srinivasan, MA;
(2018)
Three-dimensional behavioural phenotyping of freely moving C. elegans using quantitative light field microscopy.
PLoS One
, 13
(7)
, Article e0200108. 10.1371/journal.pone.0200108.
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Abstract
Behavioural phenotyping of model organisms is widely used to investigate fundamental aspects of organism biology, from the functioning of the nervous system to the effects of genetic mutations, as well as for screening new drug compounds. However, our capacity to observe and quantify the full range and complexity of behavioural responses is limited by the inability of conventional microscopy techniques to capture volumetric image information at sufficient speed. In this article we describe how combining light field microscopy with computational depth estimation provides a new method for fast, quantitative assessment of 3D posture and movement of the model organism Caenorhabditis elegans (C. elegans). We apply this technique to compare the behaviour of cuticle collagen mutants, finding significant differences in 3D posture and locomotion. We demonstrate the ability of quantitative light field microscopy to provide new fundamental insights into C. elegans locomotion by analysing the 3D postural modes of a freely swimming worm. Finally, we consider relative merits of the method and its broader application for phenotypic imaging of other organisms and for other volumetric bioimaging applications.
Type: | Article |
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Title: | Three-dimensional behavioural phenotyping of freely moving C. elegans using quantitative light field microscopy. |
Location: | United States |
Open access status: | An open access version is available from UCL Discovery |
DOI: | 10.1371/journal.pone.0200108 |
Publisher version: | https://doi.org/10.1371/journal.pone.0200108 |
Language: | English |
Additional information: | © 2018 Shaw et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science |
URI: | https://discovery.ucl.ac.uk/id/eprint/10053284 |
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