Irene Arnoldi

Complex traits that span multiple tissues and systems often integrate large numbers of genes across development, physiology, and behavior, making it challenging to identify their essential components. Blood feeding in mosquitoes is one such trait. It is ancestral to the mosquito family, maintained in most species for ~200 million years, and was independently lost in three lineages. These convergent losses offer a natural experiment to discover the genetic, physiological, and neural features required for blood feeding. We assembled high-quality, chromosome-level genomes for seven mosquito species, along with whole-brain tomographic reconstructions. Our study spanned the three known non-blood-feeding lineages (Toxorhynchites rutilus, Topomyia yanbarensis, and Malaya genurostris), blood-feeding relatives, and the variable blood feeder Wyeomyia smithii. Comparing orthologous gene clades, we detected convergent gene loss specific to the three lineages that had lost blood feeding. The losses include the salivary platelet-aggregation inhibitor Aegyptin, blood-activated serine proteases such as Chymotrypsin-1 and 2, and a carboxylesterase expressed in the female fat body and brain glia. The loss of blood feeding also extended to chemosensation. Non-blood feeders lack two odorant-binding protein clades, two ionotropic receptor clades associated with blood-component taste detection, and odorant receptor clades expressed in a discrete, strongly female-biased population of antennal neurons. Female-biased head gene expression was reduced in non-blood feeders. Finally, examination of whole-brain tomographic reconstructions across the species revealed smaller antennal lobes in non-blood-feeding females, consistent with reduced olfactory input. Together, these findings identify a compact set of genes, expression patterns, and brain regions associated with blood feeding, offering an evolutionary entry point for functional dissection of how this complex and dangerous trait is built and dismantled.

Mosquitoes are vectors of numerous pathogens that pose significant threats to human and animal health, making their monitoring crucial for effective disease control. Environmental DNA (eDNA)–based approaches enable the detection of multiple organisms in their habitats without the need for morphological identification. However, they require strict and extensive protocol optimization. In this study, we focused on the need for novel monitoring strategies, particularly ones capable of overcoming the limitations of traditional methods. Given the central role of water in the life cycle of mosquitoes, we explored whether eDNA collected from aquatic habitats could provide an effective tool for mosquito detection and taxonomic identification. Specifically, we aimed to evaluate whether an eDNA‐based approach can reliably detect multiple mosquito species and accurately discriminate among them under different community compositions. To this end, we developed and validated a protocol for an eDNA‐based detection and identification method for mosquito monitoring. First, we assessed its performance by conducting laboratory experiments on samples containing nine different combinations of larvae from five mosquito species. eDNA occupancy analysis revealed varying species‐specific detection probabilities, with Aedes albopictus showing the highest detection rate and Aedes koreicus the lowest. Overall detection probability was high at moderate to high larval densities (5 to 50 ind/L), whereas it decreased at 0.5 ind/L, indicating reduced sensitivity at very low larval concentrations. Then, we collected 165 water samples from three types of field locations and assessed the influence of ecological variables, including land use and site type, on mosquito detection probability. Our results indicate that eDNA represents a promising tool for mosquito monitoring, particularly in contexts where larval densities are not extremely low, and may support its future integration into vector surveillance and control program.