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EXTENSIVE GENETIC DIVERSITY OF PLASMODIUM VIVAX DBP-II IN RIO DE JANEIRO ATLANTIC FOREST AND BRAZILIAN AMAZON BASIN: EVIDENCE OF POSITIVE SELECTION
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Background: Plasmodium vivax is the most widespread human malaria parasite outside Africa and is the predominant parasite in the Americas. Increasing reports of P. vivax disease severity, together with the emergence of drugresistant strains, underscore the urgency of the development of vaccines against P. vivax. Polymorphisms on DBP-IIgene could act as an immune evasion mechanism and, consequently, limited the vaccine efcacy. This study aimed to investigate the pvdbp-II genetic diversity in two Brazilian regions with diferent epidemiological patterns: the unstable transmission area in the Atlantic Forest (AF) of Rio de Janeiro and; the fxed malaria-endemic area in Brazilian Amazon (BA). Methods: 216 Brazilian P. vivax infected blood samples, diagnosed by microscopic examination and PCR, were investigated. The region fanking pvdbp-II was amplifed by PCR and sequenced. Genetic polymorphisms of pvdbp-II were estimated based on the number of segregating sites and nucleotide and haplotype diversities; the degree of diferentiation between-regions was evaluated applying Wright’s statistics. Natural selection was calculated using the rate of nonsynonymous per synonymous substitutions with the Z-test, and the evolutionary distance was estimated based on the reconstructed tree.
Results: 79 samples from AF and 137 from BA were successfully sequenced. The analyses showed 28 polymorphic sites distributed in 21 codons, with only 5% of the samples Salvador 1 type. The highest rates of polymorphic sites were found in B- and T cell epitopes. Unexpectedly, the nucleotide diversity in pvdbp-II was higher in AF (0.01) than in BA (0.008). Among the 28 SNPs detected, 18 are shared between P. vivax isolates from AF and BA regions, but 8 SNPs were exclusively detected in AF—I322S, K371N, E385Q, E385T, K386T, K411N, I419L and I419R—and 2 (N375D and I419M) arose exclusively in BA. These fndings could suggest the potential of these geographical clusters as population-specifc-signatures that may be useful to track the origin of infections. The sample size should be increased in order to confrm this possibility.
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