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Phylogenetic analysis of rabies surveillance samples from north and northeast Brazil
Phylogenetic analysis of rabies surveillance samples from north and northeast Brazil
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Phylogenetic analysis of rabies surveillance samples from north and northeast Brazil
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Phylogenetic analysis of rabies surveillance samples from north and northeast Brazil
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Phylogenetic analysis of rabies surveillance samples from north and northeast Brazil
Phylogenetic analysis of rabies surveillance samples from north and northeast Brazil
Journal Article

Phylogenetic analysis of rabies surveillance samples from north and northeast Brazil

2023
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Overview
Viruses of the Lyssavirus genus are classified into several genotypes (GT1 to GT7), of which only GT1 (classic rabies virus—RABV) has a cosmopolitan distribution and circulates in Brazil. GT1 is subdivided into several antigenic variants (AgV) maintained in independent cycles with a narrow host range and distinct geographic distributions, namely, AgV1 and AgV2 found in dogs, AgV3 in the vampire bats Desmodus rotundus , and AgV4 and AgV6 in bats non-hematophagous Tadarida brasiliensis and Lasiurus cinereus , a common variant of marmoset ( Callithrix jacchus ), and crab-eating fox ( Cerdocyon thous ). In this study, we performed phylogenetic analysis to identify at the antigenic variant level; six RABV genomes derived from the Rabies Surveillance in the north and northeast regions of Brazil. The analysis resulted in the formation of 11 monophyletic clusters, each corresponding to a particular variant, with high bootstrap support values. The samples were positioned inside the AgV3, AgV6, and Callithrix variant clades. This is the first report of the AgV6 variant found in northern Brazil, which provides valuable information for rabies surveillance in the country. The possibility of viral spillover has been much debated, as it deals with the risk of shifting transmission from a primary to a secondary host. However, more genomic surveillance studies should be performed, with a greater number and diversity of samples to better understand the transmission dynamics of each variant to detect changes in its geographic distribution and spillover events.