Simian immunodeficiency virus (SIV) envelope quasispecies transmission and evolution in infant rhesus macaques after oral challenge with uncloned SIVmac251: increased diversity is associated with neutralizing antibodies and improved survival in previously immunized animals.
BACKGROUND: Oral infection of infant macaques with simian immunodeficiency virus (SIV) is a useful animal model to test interventions to reduce postnatal HIV transmission via breast-feeding. We previously demonstrated that immunization of infant rhesus macaques with either modified vaccinia virus Ankara (MVA) expressing SIV Gag, Pol and Env, or live-attenuated SIVmac1A11 resulted in lower viremia and longer survival compared to unimmunized controls after oral challenge with virulent SIVmac251 (Van Rompay et al., J. Virology 77:179-190, 2003). Here we evaluate the impact of these vaccines on oral transmission and evolution of SIV envelope variants. RESULTS: Limiting dilution analysis of SIV RNA followed by heteroduplex mobility assays of the V1-V2 envelope (env) region revealed two major env variants in the uncloned SIVmac251 inoculum. Plasma sampled from all infants 1 week after challenge contained heterogeneous SIV env populations including one or both of the most common env variants in the virus inoculum; no consistent differences in patterns of env variants were found between vaccinated and unvaccinated infants. However, SIV env variant populations diverged in most vaccinated monkeys 3 to 5 months after challenge, in association with the development of neutralizing antibodies. CONCLUSIONS: These patterns of viral envelope diversity, immune responses and disease course in SIV-infected infant macaques are similar to observations in HIV-infected children, and underscore the relevance of this pediatric animal model. The results also support the concept that neonatal immunization with HIV vaccines might modulate disease progression in infants infected with HIV by breast-feeding.
Greenier, JL; Van Rompay, KKA; Montefiori, D; Earl, P; Moss, B; Marthas, ML
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