Automated analysis of long-term grooming behavior in Drosophila using a k-nearest neighbors classifier
- University of Miami, United States
- Columbia University, United States
Abstract
Despite being pervasive, the control of programmed grooming is poorly understood. We addressed this gap by developing a high-throughput platform that allows long-term detection of grooming in Drosophila melanogaster. In our method, a k-nearest neighbors algorithm automatically classifies fly behavior and finds grooming events with over 90% accuracy in diverse genotypes. Our data show that flies spend ~13% of their waking time grooming, driven largely by two major internal programs. One of these programs regulates the timing of grooming and involves the core circadian clock components cycle, clock, and period. The second program regulates the duration of grooming and, while dependent on cycle and clock, appears to be independent of period. This emerging dual control model in which one program controls timing and another controls duration, resembles the two-process regulatory model of sleep. Together, our quantitative approach presents the opportunity for further dissection of mechanisms controlling long-term grooming in Drosophila.
Data availability
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Automated analysis of internally programmed grooming behavior inAvailable at Dryad Digital Repository under a CC0 Public Domain Dedication.
Article and author information
Author details
Funding
National Science Foundation (IOS-1656603)
- Sheyum Syed
National Institutes of Health (R01GM105775)
- Mimi M Shirasu-Hiza
National Institutes of Health (R01AG045842)
- Mimi M Shirasu-Hiza
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Copyright
© 2018, Qiao et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
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Automated analysis of long-term grooming behavior in Drosophila using a k-nearest neighbors classifier
eLife 7:e34497.
https://doi.org/10.7554/eLife.34497
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