A Large-Scale Behavioral Screen to Identify Neurons Controlling Motor Programs in the Drosophila Brain
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Author(s)
Flood, Thomas F.
Gorczyca, Michael
White, Benjamin H.
Ito, Kei
Yoshihara, Motojiro
Date Issued
August 2013
Journal
G3: Genes-Genomes-Genetics
Publisher
Genetics Society of America
Citation
Flood, T. F., M. Gorczyca, B. H. White, K. Ito, and M. Yoshihara. “A Large-Scale Behavioral Screen to Identify Neurons Controlling Motor Programs in the Drosophila Brain.” G3: Genes|Genomes|Genetics 3, no. 10 (October 3, 2013): 1629–1637.
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Final published version
Abstract
Drosophila is increasingly used for understanding the neural basis of behavior through genetically targeted manipulation of specific neurons. The primary approach in this regard has relied on the suppression of neuronal activity. Here, we report the results of a novel approach to find and characterize neural circuits by expressing neuronal activators to stimulate subsets of neurons to induce behavior. Classical electrophysiological studies demonstrated that stimulation of command neurons could activate neural circuits to trigger fixed action patterns. Our method was designed to find such command neurons for diverse behaviors by screening flies in which random subsets of brain cells were activated. We took advantage of the large collection of Gal4 lines from the NP project and crossed 835 Gal4 strains with relatively limited Gal4 expression in the brain to flies carrying a UAS transgene encoding TRPM8, a cold-sensitive ion channel. Low temperatures opened the TRPM8 channel in Gal4-expressing cells, leading to their excitation, and in many cases induced overt behavioral changes in adult flies. Paralysis was reproducibly observed in the progeny of crosses with 84 lines, whereas more specific behaviors were induced with 24 other lines. Stimulation performed using the heat-activated channel, TrpA1, resulted in clearer and more robust behaviors, including flight, feeding, and egg-laying. Through follow-up studies starting from this screen, we expect to find key components of the neural circuits underlying specific behaviors, thus providing a new avenue for their functional analysis.
MIT Department
Picower Institute for Learning and Memory
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DOI of Published Version
https://doi.org/10.1534/g3.113.006205
