Spatiotemporal analysis of Guaroa virus diversity, evolution, and spread in South America

Guaroa Virus and Plasmodium vivax Co-Infections, Peruvian Amazon

During April–June 2014 in a malaria-endemic rural community close to the city of Iquitos in Peru, we detected evidence of Guaroa virus (GROV) infection in 14 febrile persons, of whom 6 also had evidence of Plasmodium vivax malaria. Cases were discovered through a long-term febrile illness surveillance network at local participating health facilities. GROV cases were identified by using a combination of seroconversion and virus isolation, and malaria was diagnosed by thick smear and PCR. GROV mono-infections manifested as nonspecific febrile illness and were clinically indistinguishable from GROV and P. vivax co-infections. This cluster of cases highlights the potential for GROV transmission in the rural Peruvian Amazon, particularly in areas where malaria is endemic. Further study of similar areas of the Amazon may provide insights into the extent of GROV transmission in the Amazon basin.

On the importance of negative controls in viral landscape phylogeography

Phylogeographic reconstructions are becoming an established procedure to evaluate the factors that could impact virus spread. While a discrete phylogeographic approach can be used to test predictors of transition rates among discrete locations, alternative continuous phylogeographic reconstructions can also be exploited to investigate the impact of underlying environmental layers on the dispersal velocity of a virus. The two approaches are complementary tools for studying pathogens' spread, but in both cases, care must be taken to avoid misinterpretations. Here, we analyse rice yellow mottle virus (RYMV) sequence data from West and East Africa to illustrate how both approaches can be used to study the impact of environmental factors on the virus’ dispersal frequency and velocity. While it was previously reported that host connectivity was a major determinant of RYMV spread, we show that this was a false positive result due to the lack of appropriate negative controls. We also discuss and compare the phylodynamic tools currently available for investigating the impact of environmental factors on virus spread.

Genetic and Phylogenetic Characterization of Tataguine and Witwatersrand Viruses and Other Orthobunyaviruses of the Anopheles A, Capim, Guamá, Koongol, Mapputta, Tete, and Turlock Serogroups

The family Bunyaviridae has more than 530 members that are distributed among five genera or remain to be classified. The genus Orthobunyavirus is the most diverse bunyaviral genus with more than 220 viruses that have been assigned to more than 18 serogroups based on serological cross-reactions and limited molecular-biological characterization. Sequence information for all three orthobunyaviral genome segments is only available for viruses belonging to the Bunyamwera, Bwamba/Pongola, California encephalitis, Gamboa, Group C, Mapputta, Nyando, and Simbu serogroups. Here we present coding-complete sequences for all three genome segments of 15 orthobunyaviruses belonging to the Anopheles A, Capim, Guamá, Kongool, Tete, and Turlock serogroups, and of two unclassified bunyaviruses previously not known to be orthobunyaviruses (Tataguine and Witwatersrand viruses). Using those sequence data, we established the most comprehensive phylogeny of the Orthobunyavirus genus to date, now covering 15 serogroups. Our results emphasize the high genetic diversity of orthobunyaviruses and reveal that the presence of the small nonstructural protein (NSs)-encoding open reading frame is not as common in orthobunyavirus genomes as previously thought.