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High-throughput behavioral analysis in C. elegans

Nature Methods volume 8, pages 592598 (2011) | Download Citation

Abstract

We designed a real-time computer vision system, the Multi-Worm Tracker (MWT), which can simultaneously quantify the behavior of dozens of Caenorhabditis elegans on a Petri plate at video rates. We examined three traditional behavioral paradigms using this system: spontaneous movement on food, where the behavior changes over tens of minutes; chemotaxis, where turning events must be detected accurately to determine strategy; and habituation of response to tap, where the response is stochastic and changes over time. In each case, manual analysis or automated single-worm tracking would be tedious and time-consuming, but the MWT system allowed rapid quantification of behavior with minimal human effort. Thus, this system will enable large-scale forward and reverse genetic screens for complex behaviors.

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Acknowledgements

We appreciate the assistance of P. Liu in collecting data for the tap habituation screen as part of a directed studies course at the University of British Columbia, and of D. Hoffmann in the design of the multiworm tracker illumination platform and solenoid for tap habituation. M. Zlatic provided valuable bug reports, suggestions for features and feedback on the usability of the MWT outside of the authors' laboratories. We appreciate advice from and discussions with members of our labs and our colleagues at the Janelia Farm Research Campus (JFRC). Strains used in this study were acquired with speed and ease from the Caenorhabditis Genetics Center, for whose services we are grateful; many of these strains were generated by the C. elegans Gene Knockout Consortium. This work was supported by the Howard Hughes Medical Institute's JFRC (N.A.S. and R.A.K.) and the JFRC visitor program (A.C.G. and C.H.R.), and by a National Science and Engineering Research Council of Canada operating grant (to C.H.R.) and post-graduate scholarship (to A.C.G.). Preliminary investigations into multi-worm tracking were supported by the Peter Wall Institute for Advanced Studies′ Visiting Junior Scholars Program and by the lab of W. Schafer.

Author information

Author notes

    • Nicholas A Swierczek
    •  & Andrew C Giles

    These authors contributed equally to this work.

Affiliations

  1. Howard Hughes Medical Institute, Janelia Farm Research Campus, Ashburn, Virginia, USA.

    • Nicholas A Swierczek
    •  & Rex A Kerr
  2. Graduate Program in Neuroscience, University of British Columbia, Vancouver, British Columbia, Canada.

    • Andrew C Giles
  3. Brain Research Center, University of British Columbia, Vancouver, British Columbia, Canada.

    • Andrew C Giles
    •  & Catharine H Rankin
  4. Department of Psychology, University of British Columbia, Vancouver, British Columbia, Canada.

    • Catharine H Rankin

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Contributions

N.A.S. and R.A.K. designed the MWT system, built the hardware and wrote the software. A.C.G., C.H.R. and R.A.K. designed the experiments. A.C.G. and R.A.K. conducted the experiments and analyzed data. R.A.K. wrote the manuscript.

Competing interests

The authors declare no competing financial interests.

Corresponding author

Correspondence to Rex A Kerr.

Supplementary information

Zip files

  1. 1.

    Supplementary Software 1

    The MultiWorm Tracker (MWT) consists of real-time image-processing software, MWT, and offline analysis software, Choreography.

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DOI

https://doi.org/10.1038/nmeth.1625

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