Viral metagenomics to track, explain and predict the transmission and spatiotemporal spread of Dengue and Chikungunya viruses in Brazil

Abstract

Brazil is hyper-endemic for dengue, with over 8 million cases reported between 2000-2015. The transmission and dissemination of the four serotypes of dengue virus (DENV) is reported in the country through the mosquito vector (Aedes aegypti). Besides DENV, other two virus Chikungunya (CHIKV) and Zika (ZIKV) ) have already been introduced in Brazil and has caused severe epidemics, but the situation can be complicated even more as these have not yet started the period of rain. This project is a collaboration between researchers from the Institute of Tropical Medicine (IMT/USP), Oxford University (OU) and the Blood Systems Research Institute (BSRI) in an effort to reconstruct in detail the transmission dynamics of circulating viral strains in Brazil, using epidemiological data and the human host to better understand the pathogenesis of these viruses. The infrastructure already established by the Brazilian team has allowed the collection of individual blood samples from different cities in Brazil that will be included in the project and this project will be recruited other cities, which will allow the collection of isolates from current outbreaks of DENV, CHIKV and ZIKV. The aim of this study is to perform the viral metagenomics of samples collected in several Brazilian cities using next-generation sequencing to elucidate and predict the spatial dynamics and transmission of DENV, CHIKV and ZIKV in Brazil. At least 400 DENV, 200 CHIKV and 200 ZIKV from individuals that total nucleic acids are sequenced, the sequencing order of one or more viruses. The virus that through this approach are not completely sequenced will then be amplified and sequenced the missing parts. The obtained sequences are then subjected to mount "de novo" through a "pipeline" of BSRI for reconstruction of viral genomes, the consensus sequences generated will be submitted to genetic characterization focusing on the identification of transmission networks and viral spread. Then maximum likelihood and Bayesian phylogenetics will be reconstructed to determine the evolutionary relationships of the circulating strains in the national and global contexts. Best fitting nucleotide substitution, molecular clock, and coalescent models will be chosen using harmonic mean estimators, path sampling and stepping stone approaches. Rates of viral lineage movement among populations will be quantified using discrete phylogeographic approaches. Given the latitude and longitude coordinates of each isolate, we will also apply continuous diffusion models and summarize key epidemiological statistics such as dispersal velocity. Coalescent and birth-death skyline models will be used to estimate the rate of epidemic growth through time of different circulating lineages. Rates of synonymous and nonsynonymous changes will be quantified using renaissance counting and more recent algorithms for quantifying molecular adaptation being developed by the Oxford team. Viruses of dengue cases with the worst clinical outcomes will also be sequenced and analysed to see if there is any DENV sequence motif or mutational combination associated with severity. The association between disease severity and mutations will be tested using an association test that takes into account phylogenetic uncertainty. In summary, the study will combine genetic, ecological, clinical, and surveillance data to understand DENV, CHIKV and ZIKV epidemiology as well as DENV-host interactions that underlie disease severity. Ultimately, the research proposed here aims to reduce the burden caused by important arbovirus outbreaks in Brazil, with potential benefits for both public health and vaccine development. (AU)