Diego Giraldo

Anopheles gambiaeis a highly anthropophilic (human-preferring) malaria vector that prefers to blood feed frequently and selectively on humans. This mosquito species exhibits a strong innate olfactory preference to seek out human scent over other animals, and certain humans over others—key behavioral traits with the potential to drive heterogeneity in biting risk and malaria transmission. Here, we describe the application of a large-scale, semi-field system in Zambia for the quantification ofAn. gambiaeolfactory preferences toward whole body odor sourced from individual humans. We detail steps for modifying one-person canvas tents to duct odor from sleeping humans into a central, semi-field flight cage arena that is securely screened. Using this system, we describe a protocol to perform two-choice olfactory preference assays with two human volunteers using laboratory-rearedAn. gambiaeand odor-guided thermotaxis assays that leverage infrared video tracking to quantify mosquito landings on heated targets baited with each body odor sample. This multichoice olfactory preference assay has the potential to be applied with expanded cohorts of humans to define the chemosensory basis ofAn. gambiaehost preference and interindividual differences in human attractiveness to mosquitoes and to be used to quantify the effects of protective measures such as personal and spatial repellents on mosquito landing behavior.

The African malaria mosquitoAnopheles gambiaeis strongly attracted to human body odor and skin temperature. Quantitative behavioral assays suitable for use in semi-field environments with this nocturnal mosquito species are essential to gain improved insights intoAn. gambiaesensory biology, the mechanistic basis of mosquito attraction to humans, and host preference. In this protocol, we describe steps for engineering equipment for a novel behavioral assay forAn. gambiae, which we have termed the odor-guided thermotaxis assay (OGTA). The OGTA uses infrared videography to quantify landings of femaleAn. gambiaeon an aluminum platform heated to human skin temperature that can be baited with volatile odorants such as carbon dioxide or human whole body odor. The OGTA facilitates high-content recordings ofAn. gambiaelanding behavior during odor-guided thermotaxis under naturalistic semi-field conditions without the requirement for domestic power.

The most dangerous mosquito species for human health are those that blood feed preferentially and frequently on humans (anthropophilic mosquitoes). These include prolific disease vectors such as the African malaria mosquitoAnopheles gambiaeand yellow fever mosquitoAedes aegypti. The chemosensory basis for anthropophilic behavior exhibited by these disease vectors, as well as the factors that drive interindividual differences in human attractiveness to mosquitoes, remain largely uncharacterized. Here, we concisely review established methods to quantify mosquito interspecific and intraspecific host preference in the laboratory, as well as semi-field and field environments. Experimental variables for investigator consideration during assays of mosquito host preference across these settings are highlighted.

Summary: The African malaria mosquito Anopheles gambiae exhibits a strong innate sensory drive to seek out human scent. To detect human odorants, An. gambiae uses olfactory sensory neurons (OSNs) that can be divided into different classes by unique repertoires of chemoreceptor gene expression. We applied CRISPR-Cas9-mediated T2A-In Frame Fusions and the QF2/QUAS system to gain genetic access to specific OSN subsets in An. gambiae expressing the chemoreceptor genes Ir25a , Ir76b , Gr22 and orco . We first optimized methods to generate cell-type specific QF2 driver and QUAS responder lines to map expression patterns of these chemoreceptors across mosquito sensory appendages. We next applied transcuticular calcium imaging to record neurophysiological responses to select human-related odorants for each OSN class. This neurogenetic toolkit tiling OSN subsets in An. gambiae , including those responsive to CO ₂ , stands to support systematic efforts to decode olfaction in this prolific disease vector at high-resolution to combat malaria.

Variability in the chemical composition of human scent has the potential to modulate mosquito attraction to certain humans. We have engineered a large-scale, semi-field system in Zambia for quantifying mosquito olfactory preferences towards whole body odor sourced from different humans under naturalistic conditions. In a flight cage arena with infrared tracking, we document that the African malaria mosquito Anopheles gambiae hierarchically prefers to land on heated targets mimicking human skin temperature when they are baited with carbon dioxide (CO ₂ ) over background air, human body odor over CO ₂ , and the scent of one individual over another. In a six-choice assay configuration, we further identify humans at both ends of the attractiveness spectrum whose scent is differentially attractive to An. gambiae relative to other individuals. We demonstrate integrative use of this multi-choice olfactory assay with whole body volatilomics, establishing a powerful method for discovery of human odorants modulating heterogeneity in biting risk at enhanced throughput.

The yellow fever mosquito Aedes aegypti employs olfaction to locate humans. We applied neural activity mapping to define the molecular and cellular logic of how the mosquito brain is wired to detect two human odorants that are attractive when blended together. We determined that the human breath volatile carbon dioxide (CO ₂ ) is detected by the largest unit of olfactory coding in the antennal lobe of the mosquito brain. Synergistically, CO ₂ detection gates pre-synaptic calcium signaling in olfactory sensory neuron axon terminals that innervate unique antennal lobe regions tuned to the human sweat odorant L-(+)-lactic acid. We propose that simultaneous detection of the signature human volatiles CO ₂ and L-(+)-lactic acid disinhibits a multimodal olfactory network for hunting humans in the mosquito brain.

Sensing environmental temperatures is essential for the survival of ectothermic organisms. InDrosophila, two of the most used methodologies to study temperature preferences (T_P) and the genes involved in thermosensation are two-choice assays and temperature gradients. Whereas two-choice assays reveal a relative T_P, temperature gradients can identify the absolute T_p. One drawback of gradients is that small ectothermic animals are susceptible to cold-trapping: a physiological inability to move at the cold area of the gradient. Often cold-trapping cannot be avoided, biasing the resulting T_Pto lower temperatures. Two mathematical models were previously developed to correct for cold-trapping. These models, however, focus on group behaviour which can lead to overestimation of cold-trapping due to group aggregation. Here we present a mathematical model that simulates the behaviour of individualDrosophilain temperature gradients. The model takes the spatial dimension and temperature difference of the gradient into account, as well as the rearing temperature of the flies. Furthermore, it allows the quantification of cold-trapping and reveals unbiased T_P.Additionally, our model reveals that flies have a range of tolerable temperatures, and this measure is more informative about the behaviour than commonly used T_P. Online simulation is hosted athttp://igloo.uni-goettingen.de. The code can be accessed athttps://github.com/zerotonin/igloo.

Sensing environmental temperatures is essential for the survival of ectothermic organisms. In Drosophila, two methodologies are used to study temperature preferences (T _P ) and the genes involved in thermosensation: two-choice assays and temperature gradients. Whereas two-choice assays reveal a relative T _P , temperature gradients can identify the absolute T _p . One drawback of gradients is that small ectothermic animals are susceptible to cold-trapping: a physiological inability to move at the cold area of the gradient. Often cold-trapping cannot be avoided, biasing the resulting T _P to lower temperatures. Two mathematical models were previously developed to correct for cold-trapping. These models, however, focus on group behaviour which can lead to overestimation of cold-trapping due to group aggregation. Here we present a mathematical model that estimates the behaviour of individual Drosophila in temperature gradients. The model takes the spatial dimension and temperature difference of the gradient into account, as well as the rearing temperature of the flies. Furthermore, it allows quantifying cold-trapping, reveals true T _P , and differentiates between temperature preference and tolerance. Online simulation is hosted at http://igloo.uni-goettingen.de . The code can be accessed at https://github.com/zerotonin/igloo .