IDEAS home Printed from https://ideas.repec.org/a/plo/pcbi00/1003702.html
   My bibliography  Save this article

CeleST: Computer Vision Software for Quantitative Analysis of C. elegans Swim Behavior Reveals Novel Features of Locomotion

Author

Listed:
  • Christophe Restif
  • Carolina Ibáñez-Ventoso
  • Mehul M Vora
  • Suzhen Guo
  • Dimitris Metaxas
  • Monica Driscoll

Abstract

In the effort to define genes and specific neuronal circuits that control behavior and plasticity, the capacity for high-precision automated analysis of behavior is essential. We report on comprehensive computer vision software for analysis of swimming locomotion of C. elegans, a simple animal model initially developed to facilitate elaboration of genetic influences on behavior. C. elegans swim test software CeleST tracks swimming of multiple animals, measures 10 novel parameters of swim behavior that can fully report dynamic changes in posture and speed, and generates data in several analysis formats, complete with statistics. Our measures of swim locomotion utilize a deformable model approach and a novel mathematical analysis of curvature maps that enable even irregular patterns and dynamic changes to be scored without need for thresholding or dropping outlier swimmers from study. Operation of CeleST is mostly automated and only requires minimal investigator interventions, such as the selection of videotaped swim trials and choice of data output format. Data can be analyzed from the level of the single animal to populations of thousands. We document how the CeleST program reveals unexpected preferences for specific swim “gaits” in wild-type C. elegans, uncovers previously unknown mutant phenotypes, efficiently tracks changes in aging populations, and distinguishes “graceful” from poor aging. The sensitivity, dynamic range, and comprehensive nature of CeleST measures elevate swim locomotion analysis to a new level of ease, economy, and detail that enables behavioral plasticity resulting from genetic, cellular, or experience manipulation to be analyzed in ways not previously possible.

Suggested Citation

  • Christophe Restif & Carolina Ibáñez-Ventoso & Mehul M Vora & Suzhen Guo & Dimitris Metaxas & Monica Driscoll, 2014. "CeleST: Computer Vision Software for Quantitative Analysis of C. elegans Swim Behavior Reveals Novel Features of Locomotion," PLOS Computational Biology, Public Library of Science, vol. 10(7), pages 1-12, July.
    • Handle: RePEc:plo:pcbi00:1003702
    DOI: 10.1371/journal.pcbi.1003702
    as

    Download full text from publisher

    File URL: https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1003702
    Download Restriction: no
    File URL: https://journals.plos.org/ploscompbiol/article/file?id=10.1371/journal.pcbi.1003702&type=printable
    Download Restriction: no
    File URL: https://libkey.io/10.1371/journal.pcbi.1003702?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Scott Ogg & Suzanne Paradis & Shoshanna Gottlieb & Garth I. Patterson & Linda Lee & Heidi A. Tissenbaum & Gary Ruvkun, 1997. "The Fork head transcription factor DAF-16 transduces insulin-like metabolic and longevity signals in C. elegans," Nature, Nature, vol. 389(6654), pages 994-999, October.
    2. Laura A. Herndon & Peter J. Schmeissner & Justyna M. Dudaronek & Paula A. Brown & Kristin M. Listner & Yuko Sakano & Marie C. Paupard & David H. Hall & Monica Driscoll, 2002. "Stochastic and genetic factors influence tissue-specific decline in ageing C. elegans," Nature, Nature, vol. 419(6909), pages 808-814, October.
    3. Greg J Stephens & Bethany Johnson-Kerner & William Bialek & William S Ryu, 2008. "Dimensionality and Dynamics in the Behavior of C. elegans," PLOS Computational Biology, Public Library of Science, vol. 4(4), pages 1-10, April.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Li-Chun Lin & Han-Sheng Chuang, 2017. "Analyzing the locomotory gaitprint of Caenorhabditis elegans on the basis of empirical mode decomposition," PLOS ONE, Public Library of Science, vol. 12(7), pages 1-14, July.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Elke Braun & Bart Geurten & Martin Egelhaaf, 2010. "Identifying Prototypical Components in Behaviour Using Clustering Algorithms," PLOS ONE, Public Library of Science, vol. 5(2), pages 1-15, February.
    2. Spencer Farrell & Arnold Mitnitski & Kenneth Rockwood & Andrew D Rutenberg, 2022. "Interpretable machine learning for high-dimensional trajectories of aging health," PLOS Computational Biology, Public Library of Science, vol. 18(1), pages 1-30, January.
    3. Drew Benjamin Sinha & Zachary Scott Pincus, 2022. "High temporal resolution measurements of movement reveal novel early-life physiological decline in C. elegans," PLOS ONE, Public Library of Science, vol. 17(2), pages 1-17, February.
    4. Stanislav Nagy & Marc Goessling & Yali Amit & David Biron, 2015. "A Generative Statistical Algorithm for Automatic Detection of Complex Postures," PLOS Computational Biology, Public Library of Science, vol. 11(10), pages 1-23, October.
    5. Minjie Hong & Xiaotian Zhou & Chenming Zeng & Demin Xu & Ting Xu & Shimiao Liao & Ke Wang & Chengming Zhu & Ge Shan & Xinya Huang & Xiangyang Chen & Xuezhu Feng & Shouhong Guang, 2024. "Nucleolar stress induces nucleolar stress body formation via the NOSR-1/NUMR-1 axis in Caenorhabditis elegans," Nature Communications, Nature, vol. 15(1), pages 1-19, December.
    6. Katharina Jovic & Mark G Sterken & Jacopo Grilli & Roel P J Bevers & Miriam Rodriguez & Joost A G Riksen & Stefano Allesina & Jan E Kammenga & L Basten Snoek, 2017. "Temporal dynamics of gene expression in heat-stressed Caenorhabditis elegans," PLOS ONE, Public Library of Science, vol. 12(12), pages 1-16, December.
    7. Chang Woo Ji & Young-Seuk Park & Yongde Cui & Hongzhu Wang & Ihn-Sil Kwak & Tae-Soo Chon, 2020. "Analyzing the Response Behavior of Lumbriculus variegatus (Oligochaeta: Lumbriculidae) to Different Concentrations of Copper Sulfate Based on Line Body Shape Detection and a Recurrent Self-Organizing ," IJERPH, MDPI, vol. 17(8), pages 1-15, April.
    8. Markus Reischl & Mazin Jouda & Neil MacKinnon & Erwin Fuhrer & Natalia Bakhtina & Andreas Bartschat & Ralf Mikut & Jan G Korvink, 2019. "Motion prediction enables simulated MR-imaging of freely moving model organisms," PLOS Computational Biology, Public Library of Science, vol. 15(12), pages 1-16, December.
    9. Sepideh Bazazi & Frederic Bartumeus & Joseph J Hale & Iain D Couzin, 2012. "Intermittent Motion in Desert Locusts: Behavioural Complexity in Simple Environments," PLOS Computational Biology, Public Library of Science, vol. 8(5), pages 1-10, May.
    10. Steffen Werner & Jochen C Rink & Ingmar H Riedel-Kruse & Benjamin M Friedrich, 2014. "Shape Mode Analysis Exposes Movement Patterns in Biology: Flagella and Flatworms as Case Studies," PLOS ONE, Public Library of Science, vol. 9(11), pages 1-21, November.
    11. Maria Gabriella Melchiorre & Marco Socci & Sabrina Quattrini & Giovanni Lamura & Barbara D’Amen, 2022. "Frail Older People Ageing in Place in Italy: Use of Health Services and Relationship with General Practitioner," IJERPH, MDPI, vol. 19(15), pages 1-26, July.
    12. Chongbin Zheng & Evelyn Tang, 2024. "A topological mechanism for robust and efficient global oscillations in biological networks," Nature Communications, Nature, vol. 15(1), pages 1-11, December.
    13. Jeffrey P Nguyen & Ashley N Linder & George S Plummer & Joshua W Shaevitz & Andrew M Leifer, 2017. "Automatically tracking neurons in a moving and deforming brain," PLOS Computational Biology, Public Library of Science, vol. 13(5), pages 1-19, May.
    14. Laetitia Hebert & Tosif Ahamed & Antonio C Costa & Liam O’Shaughnessy & Greg J Stephens, 2021. "WormPose: Image synthesis and convolutional networks for pose estimation in C. elegans," PLOS Computational Biology, Public Library of Science, vol. 17(4), pages 1-20, April.
    15. Li-Chun Lin & Han-Sheng Chuang, 2017. "Analyzing the locomotory gaitprint of Caenorhabditis elegans on the basis of empirical mode decomposition," PLOS ONE, Public Library of Science, vol. 12(7), pages 1-14, July.
    16. Céline N Martineau & André E X Brown & Patrick Laurent, 2020. "Multidimensional phenotyping predicts lifespan and quantifies health in Caenorhabditis elegans," PLOS Computational Biology, Public Library of Science, vol. 16(7), pages 1-14, July.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:plo:pcbi00:1003702. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: ploscompbiol (email available below). General contact details of provider: https://journals.plos.org/ploscompbiol/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.