Chih-Chieh Jay Yu1, David M Raizen2, Christopher Fang-Yen3. 1. Department of Bioengineering, School of Engineering and Applied Science, University of Pennsylvania, 210 South 33rd Street, Suite 240, Skirkanich Hall, Philadelphia, PA 19104, USA. Electronic address: jayyu0528@gmail.com. 2. Department of Neurology, Perelman School of Medicine, University of Pennsylvania, 462 Stemmler Hall, 415 Curie Boulevard, Philadelphia, PA 19104, USA. Electronic address: raizen@mail.med.upenn.edu. 3. Department of Bioengineering, School of Engineering and Applied Science, University of Pennsylvania, 210 South 33rd Street, Suite 240, Skirkanich Hall, Philadelphia, PA 19104, USA; Department of Physics, Korea University, Anam-dong, Seongbuk-gu, Seoul 136-701, South Korea. Electronic address: fangyen@seas.upenn.edu.
Abstract
BACKGROUND: The nematode Caenorhabditis elegans is widely used as a model for understanding the neuronal and genetic bases of behavior. Recent studies have required longitudinal assessment of individual animal's behavior over extended periods. NEW METHOD: Here we present a technique for automated monitoring of multiple worms for several days. Our method uses an array of plano-concave glass wells containing standard agar media. The concave well geometry allows worms to be imaged even at the edge of the agar surface and prevents them from burrowing under the agar. We transfer one worm or embryo into each well, and perform imaging of the array of wells using a single camera. Machine vision software is used to quantify size, activity, and/or fluorescence of each worm over time. RESULTS: We demonstrate the utility of our method in two applications: (1) quantifying behavioral quiescence and developmental rate in wild-type and mutant animals, and (2) characterizing differences in mating behavior between two C. elegans strains. COMPARISON WITH EXISTING METHOD(S): Current techniques for tracking behavior in identified worms are generally restricted to imaging either single animals or have not been shown to work with arbitrary developmental stages; many are also technically complex. Our system works with up to 24 animals of any stages and is technically simple. CONCLUSIONS: Our multi-well imaging method is a powerful tool for quantification of long-term behavioral phenotypes in C. elegans.
BACKGROUND: The nematode Caenorhabditis elegans is widely used as a model for understanding the neuronal and genetic bases of behavior. Recent studies have required longitudinal assessment of individual animal's behavior over extended periods. NEW METHOD: Here we present a technique for automated monitoring of multiple worms for several days. Our method uses an array of plano-concave glass wells containing standard agar media. The concave well geometry allows worms to be imaged even at the edge of the agar surface and prevents them from burrowing under the agar. We transfer one worm or embryo into each well, and perform imaging of the array of wells using a single camera. Machine vision software is used to quantify size, activity, and/or fluorescence of each worm over time. RESULTS: We demonstrate the utility of our method in two applications: (1) quantifying behavioral quiescence and developmental rate in wild-type and mutant animals, and (2) characterizing differences in mating behavior between two C. elegans strains. COMPARISON WITH EXISTING METHOD(S): Current techniques for tracking behavior in identified worms are generally restricted to imaging either single animals or have not been shown to work with arbitrary developmental stages; many are also technically complex. Our system works with up to 24 animals of any stages and is technically simple. CONCLUSIONS: Our multi-well imaging method is a powerful tool for quantification of long-term behavioral phenotypes in C. elegans.
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