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High-throughput imaging of Caenorhabditis elegans aging using collective activity monitoring

Anthony D Fouad, Matthew A Churgin, Julia Hayden, Joyce Xu, Jeong-Inn Park, Alice Liu, Christopher Teng, Hongjing Sun, Mateo Parrado, Peter Bowlin, Miguel De La Torre, Timothy A. Crombie, Christine A. Sedore, Anna L. Coleman-Hulbert, Erik Johnson, View ORCID ProfilePatrick Philips, View ORCID ProfileErik C. Andersen, View ORCID ProfileChristopher Fang-Yen
doi: https://doi.org/10.1101/2021.10.18.464905
Anthony D Fouad
1Department of Bioengineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia PA
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Matthew A Churgin
1Department of Bioengineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia PA
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Julia Hayden
1Department of Bioengineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia PA
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Joyce Xu
1Department of Bioengineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia PA
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Jeong-Inn Park
1Department of Bioengineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia PA
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Alice Liu
1Department of Bioengineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia PA
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Christopher Teng
1Department of Bioengineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia PA
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Hongjing Sun
1Department of Bioengineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia PA
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Mateo Parrado
1Department of Bioengineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia PA
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Peter Bowlin
1Department of Bioengineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia PA
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Miguel De La Torre
1Department of Bioengineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia PA
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Timothy A. Crombie
2Department of Molecular Biosciences, Northwestern University, Evanston, IL
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Christine A. Sedore
3Department of Biology, University of Oregon, Eugene, OR
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Anna L. Coleman-Hulbert
3Department of Biology, University of Oregon, Eugene, OR
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Erik Johnson
3Department of Biology, University of Oregon, Eugene, OR
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Patrick Philips
3Department of Biology, University of Oregon, Eugene, OR
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  • ORCID record for Patrick Philips
Erik C. Andersen
2Department of Molecular Biosciences, Northwestern University, Evanston, IL
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Christopher Fang-Yen
1Department of Bioengineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia PA
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  • For correspondence: fangyen@seas.upenn.edu
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ABSTRACT

The genetic manipulability and short lifespan of C. elegans make it an important model for aging research. Widely applied methods for measurements of worm aging based on manual observation are labor intensive and low-throughput. Here, we describe the Worm Collective Activity Monitoring Platform (WormCamp), a system for assaying aging in C. elegans by monitoring activity of populations of worms in standard 24-well plates. We show that metrics based on the rate of decline in collective activity can be used to estimate the average lifespan and locomotor healthspan in the population. Using the WormCamp, we assay a panel of highly divergent natural isolates of C. elegans and show that both lifespan and locomotor healthspan display substantial heritability. To facilitate analysis of large numbers of worms, we developed a robotic imaging system capable of simultaneous automated monitoring of activity, lifespan, and locomotor healthspan in up to 2,304 populations containing a total of ~90,000 animals. We applied the automated system to conduct a large-scale RNA interference screen for genes that affect lifespan and locomotor healthspan. The WormCamp system is complementary to other current automated methods for assessing C. elegans aging and is well suited for efficiently screening large numbers of conditions.

Competing Interest Statement

The authors have declared no competing interest.

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 October 19, 2021.
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High-throughput imaging of Caenorhabditis elegans aging using collective activity monitoring
Anthony D Fouad, Matthew A Churgin, Julia Hayden, Joyce Xu, Jeong-Inn Park, Alice Liu, Christopher Teng, Hongjing Sun, Mateo Parrado, Peter Bowlin, Miguel De La Torre, Timothy A. Crombie, Christine A. Sedore, Anna L. Coleman-Hulbert, Erik Johnson, Patrick Philips, Erik C. Andersen, Christopher Fang-Yen
bioRxiv 2021.10.18.464905; doi: https://doi.org/10.1101/2021.10.18.464905
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High-throughput imaging of Caenorhabditis elegans aging using collective activity monitoring
Anthony D Fouad, Matthew A Churgin, Julia Hayden, Joyce Xu, Jeong-Inn Park, Alice Liu, Christopher Teng, Hongjing Sun, Mateo Parrado, Peter Bowlin, Miguel De La Torre, Timothy A. Crombie, Christine A. Sedore, Anna L. Coleman-Hulbert, Erik Johnson, Patrick Philips, Erik C. Andersen, Christopher Fang-Yen
bioRxiv 2021.10.18.464905; doi: https://doi.org/10.1101/2021.10.18.464905

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