Using insect-derived DNA and RNA to describe vector, host, and pathogen communities across a gradient of anthropogenic impact and deforestation in the Brazilian Amazon

Strong data informing whether there is a generalizable effect of land-use change on species communities and consequently zoonotic disease risk is sparse because ecological and sampling complexities make it challenging to establish direct links between vectors and hosts. However, emerging molecular methods using invertebrate-derived DNA (iDNA) or RNA (iRNA) can now measure species diversity and interactions from vector bloodmeals. Here, we used iDNA metabarcoding of sandflies and their bloodmeals from forested sites across the southern Amazon to disentangle the relationships between Leishmania parasites, sandfly vectors, and wildlife hosts. We found that the vector community was significantly influenced by pasture cover, and that sandflies fed on a diversity of vertebrates, but domestic dogs and the nine-banded armadillo were overwhelmingly the most prevalent hosts. The probability of a host being detected in sandfly bloodmeals had a significant hump-shaped relationship to the amount of forest cover, with the highest probability found at sites with both forest and agriculture. Subsequent work has focused on iDNA and iRNA sequencing methods using mosquito vectors captured from intact tropical forest in the northwest Amazon. Results revealed that as human disturbance increased, there’s evidence of decreasing alpha diversity of mosquito and vertebrate species but an increasing viral prevalence. These results also revealed mosquito feeding preferences for birds, monkeys, humans, and dogs and a particularly high prevalence of pox viruses and flaviviruses. Both of these research projects show that landscape-level field sampling with powerful molecular methods can measure the important relationships between vectors and hosts in disease hotspots.