Carbon dioxide and blood-feeding shift visual cue tracking during navigation in Aedes aegypti mosquitoes
Cite this dataset
Barredo, Elina et al. (2022). Carbon dioxide and blood-feeding shift visual cue tracking during navigation in Aedes aegypti mosquitoes [Dataset]. Dryad. https://doi.org/10.5061/dryad.z8w9ghxfv
Hematophagous mosquitoes need a blood meal to complete their reproductive cycle. To accomplish this, female mosquitoes seek vertebrate hosts, land on them, and bite. As their eggs mature, they shift attention away from hosts and towards finding sites to lay eggs. We asked whether females were more tuned to visual cues when a host-related signal, carbon dioxide, was present, and further examined the effect of a blood meal, which shifts behavior to ovipositing. Using a custom, tethered-flight arena that records wing stroke changes while displaying visual cues, we found the presence of CO2 enhances visual attention towards discrete stimuli and improves contrast sensitivity for host-seeking Aedes aegypti mosquitoes. Conversely, intake of a blood meal reverses vertical bar tracking, a stimulus that non-fed females readily follow. This switch in behavior suggests that physiological status modulates visual attention in mosquitoes, a phenomenon that has been described before in olfaction but not in visually-driven behaviors.
We collected the steering responses of rigidly tethered flying insects by measuring their wingstroke dynamics in a virtual reality arena. Our system records the wing beat amplitude (V) and frequency (Hz) using two photodiode receivers under an infrared beam that illuminates flying subjects. The receivers record WBA changes in the shadow cast by the IR beam, which are saved as a binary file per experiment per insect. Voltage signal changes (WBA) represent insect steering efforts, where positive WBA values indicate right turns and negative ones suggest left turns.
The Python code we provided can be used for analyzing our data and generating the plots that we have submitted with our article.
The analysis is written in Python3 and can be called from any interpreter such as Sypder or using a terminal command line. Feel free to contact Elina Barredo for further information about these files or the script.
National Science Foundation, Award: IOS-1750833
Centers for Disease Control and Prevention, Award: U01CK000510