"Show me which parasites you carry and I will tell you what you eat", or how to infer the trophic behavior of hematophagous arthropods feeding on wildlife

Most emerging infectious diseases are zoonoses originating from wildlife among which vector-borne diseases constitute a major risk for global human health. Understanding the transmission routes of mosquito-borne pathogens in wildlife crucially depends on recording mosquito blood-feeding patterns. During an extensive longitudinal survey to study sylvatic anophelines in two wildlife reserves in Gabon, we collected 2,415 mosquitoes of which only 0.3% were blood-fed. The molecular analysis of the blood meals contained in guts indicated that all the engorged mosquitoes fed on wild ungulates. This direct approach gave only limited insights into the trophic behavior of the captured mosquitoes. Therefore, we developed a complementary indirect approach that exploits the occurrence of natural infections by host-specific haemosporidian parasites to infer Anopheles trophic behavior. This method showed that 74 infected individuals carried parasites of great apes (58%), ungulates (30%), rodents (11%) and bats (1%). Accordingly, on the basis of haemosporidian host specificity, we could infer different feeding patterns. Some mosquito species had a restricted host range (An.nili only fed on rodents, whereas An.carnevalei, An.coustani, An.obscurus, and An.paludis only fed on wild ungulates). Other species had a wider host range (An.gabonensis could feed on rodents and wild ungulates, whereas An.moucheti and An.vinckei bit rodents, wild ungulates and great apes). An.marshallii was the species with the largest host range (rodents, wild ungulates, great apes, and bats). The indirect method substantially increased the information that could be extracted from the sample by providing details about host-feeding patterns of all the mosquito species collected (both fed and unfed). Molecular sequences of hematophagous arthropods and their parasites will be increasingly available in the future; exploitation of such data with the approach we propose here should provide key insights into the feeding patterns of vectors and the ecology of vector-borne diseases