Viral evolutionary analyses as magnifying glass on parasite population dynamics

Rapidly evolving pathogens may be used to study the contemporary population structure and recent demographic history of their genetically uniform hosts. Because viral evolution can manifest itself over months or years, viruses may provide insights into host evolution that were not apparent from host genetic data, and that would be impossible to obtain by other means. Here, we want to apply the concept of “viruses as genetic tags of their host” and use - for the first time - evolutionary timescales of a virus, here the Leishmaniavirus, to gain insights into the population dynamics of a vector-borne pathogen, here the Leishmania parasite (here considered as the host of the virus).
Leishmania (Trypanosomatidae) is a genus of widespread protozoan parasites causing leishmaniasis, a neglected tropical disease transmitted through a sandfly vector (Phlebotominae). Leishmania braziliensis is one of the major causes of cutaneous leishmaniasis in South America and is also associated with mucocutaneous leishmaniasis. Being zoonotic, L. braziliensis is mainly associated with rodents and some other wild mammals; human infection does not appear to be important for transmission. It is established that L. braziliensis and its sister species L. guyanensis are associated with a double stranded RNA virus called Leishmaniavirus 1 (LRV1; Totiviridae), forming a tripartite symbiosis with their mammalian host and sandfly vector.
Here, we hypothesize that LRV1 will reveal unprecedented details on the population dynamics of the Leishmania parasite. Specifically, we will focus on the following scientific objectives: i) uncover the geographic distribution of LRV1 in South-America, ii) reconcile the co-evolutionary history between LRV1 and the L. braziliensis parasite and iii) model Leishmania population dynamics through evolutionary analyses of LRV1. We start our project by screening 506 Leishmania isolates for the presence of LRV1 and model its distribution in South-America based on bioclimatic and environmental predictor variables (work package 1). LRV-positive samples will be sequenced using a customized total RNA sequencing protocol and bio-informatically processed to recover both the viral RNA genome and the parasite transcriptome. The generated data will be used to study patterns of cospeciation and host-switching within a co-phylogenetic framework (work package 2), and unravel the phylogeographic history of the parasite and its virus through population genomic and Bayesian phylogenetic analyses (work package 3). By aligning the evolutionary histories of these two symbiotic species, our unique approach will provide major insights into the specific bioclimatic, spatial and environmental factors that influenced the spread of a zoonotic disease.