PT  - JOURNAL ARTICLE
AU  - Keles, Mehmet F.
AU  - Sapci, Ali
AU  - Brody, Casey
AU  - Palmer, Isabelle
AU  - Le, Christin
AU  - Tastan, Oznur
AU  - Keles, Sunduz
AU  - Wu, Mark N.
TI  - Deep Phenotyping of Sleep in <em>Drosophila</em>
AID  - 10.1101/2023.10.30.564733
DP  - 2023 Jan 01
TA  - bioRxiv
PG  - 2023.10.30.564733
4099  - http://biorxiv.org/content/early/2023/11/02/2023.10.30.564733.short
4100  - http://biorxiv.org/content/early/2023/11/02/2023.10.30.564733.full
AB  - Sleep is an evolutionarily conserved behavior, whose function is unknown. Here, we present a method for deep phenotyping of sleep in Drosophila, consisting of a high-resolution video imaging system, coupled with closed-loop laser perturbation to measure arousal threshold. To quantify sleep-associated microbehaviors, we trained a deep-learning network to annotate body parts in freely moving flies and developed a semi-supervised computational pipeline to classify behaviors. Quiescent flies exhibit a rich repertoire of microbehaviors, including proboscis pumping (PP) and haltere switches, which vary dynamically across the night. Using this system, we characterized the effects of optogenetically activating two putative sleep circuits. These data reveal that activating dFB neurons produces micromovements, inconsistent with sleep, while activating R5 neurons triggers PP followed by behavioral quiescence. Our findings suggest that sleep in Drosophila is polyphasic with different stages and set the stage for a rigorous analysis of sleep and other behaviors in this species.Competing Interest StatementThe authors have declared no competing interest.