Abstract
AbstractFemale mosquitoes need a blood meal to reproduce, and in obtaining this essential nutrient they transmit deadly pathogens. Although crucial for the spread of mosquito-borne diseases, our understanding of skin exploration, probing, and engorgement, is limited due to a lack of quantitative tools. Indeed, studies often expose human subjects to assess biting behavior. Here, we present the biteOscope, a device that attracts mosquitoes to a host mimic which they bite to obtain an artificial blood meal. The host mimic is transparent, allowing high-resolution imaging of the feeding mosquito. Using machine learning we extract detailed behavioral statistics describing the locomotion, pose, biting, and feeding dynamics ofAedes aegypti, Aedes albopictus, Anopheles stephensi, andAnopheles coluzzii. In addition to characterizing behavioral patterns, we discover that the common insect repellent DEET repelsAnopheles coluzziiupon contact with their legs. The biteOscope provides a new perspective on mosquito blood feeding, enabling high-throughput quantitative characterization of the effects physiological and environmental factors have on this lethal behavior.
Publisher
Cold Spring Harbor Laboratory
Cited by
2 articles.
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