Computational and experimental insights into the chemosensory navigation of Aedes aegypti mosquito larvae

Mosquitoes are prolific disease vectors that affect public health around
the world. Although many studies have investigated search strategies used
by host-seeking adult mosquitoes, little is known about larval search
behavior. Larval behavior affects adult body size and fecundity, and thus
the capacity of individual mosquitoes to find hosts and transmit disease.
Understanding vector survival at all life stages is crucial for improving
disease control. In this study we use experimental and computational
methods to investigate the chemical ecology and search behavior of Aedes
aegypti mosquito larvae. We first show that larvae do not respond to
several olfactory cues used by adult Ae. aegypti to assess larval habitat
quality, but perceive microbial RNA as a potent foraging attractant.
Second, we demonstrate that Ae. aegypti larvae use chemokinesis, an
unusual search strategy, to navigate chemical gradients. Finally, we use
computational modeling to demonstrate that larvae respond to starvation
pressure by optimizing exploration behavior - possibly critical for
exploiting limited larval habitat types. Our results identify key
characteristics of foraging behavior in an important disease vector
mosquito. In addition to implications for better understanding and control
of disease vectors, this work establishes mosquito larvae as a tractable
model for chemosensory behavior and navigation.