Sengupta, S., Chen, Z., Efromson, J., Bègue, A., Harfouche, M., Adegbesan, A.S., Urquhart, A.E., Chan, Y.B., Yang, S., Henry, S.A., Palavicino-Maggio, C.B. (2025). High-throughput tracking of freely moving Drosophila reveals variations in aggression and courtship behaviors.  Sci. Rep. 16(1): 217.

FBrf0264333

Research paper

Aggression is a nearly universal behavior used to secure food, territory, and mates across species, including the fruit fly Drosophila melanogaster. In fruit flies, both sexes display aggression through stereotypical motor patterns. This, along with their sophisticated genetic and molecular toolkit, makes Drosophila melanogaster an excellent model for studying aggression. While male- and female-specific aggressive motor programs have been qualitatively described, automated systems for quantifying these behaviors in freely moving flies remain limited in their ability to combine high-resolution analysis with high throughput. Here, we pair a high-resolution, high-throughput imaging system (Kestrel) with DeepLabCut pose estimation to create a pipeline that tracks multiple freely moving fly pairs and quantifies social dynamics with high fidelity. We validated the system’s high-throughput performance and body-part tracking accuracy through manual scoring and established Drosophila behavioral phenotypes. The platform reliably reproduced a known phenotype: heightened female aggression following activation of cholinergic pC1 neurons. It also revealed a previously uncharacterized neuronal population labeled by R72A10-GAL4 that promotes courtship in males without affecting aggression. Pose-based analysis further detected locomotive differences between experimental and control groups, and subtle genotype-specific variations in aggression and courtship. By providing a high-fidelity readout of circuit-specific manipulations, this workflow enables mechanistic dissection of social behaviors. The online version contains supplementary material available at 10.1038/s41598-025-29213-w.

PMC12770420 (PMC) (EuropePMC)