High-resolution deep sequencing reveals biodiversity, population structure, and persistence of HIV-1 quasispecies within host ecosystems.

BACKGROUND: Deep sequencing provides the basis for analysis of biodiversity of taxonomically similar organisms in an environment. While extensively applied to microbiome studies, population genetics studies of viruses are limited. To define the scope of HIV-1 population biodiversity within infected individuals, a suite of phylogenetic and population genetic algorithms was applied to HIV-1 envelope hypervariable domain 3 (Env V3) within peripheral blood mononuclear cells from a group of perinatally HIV-1 subtype B infected, therapy-naïve children. RESULTS: Biodiversity of HIV-1 Env V3 quasispecies ranged from about 70 to 270 unique sequence clusters across individuals. Viral population structure was organized into a limited number of clusters that included the dominant variants combined with multiple clusters of low frequency variants. Next generation viral quasispecies evolved from low frequency variants at earlier time points through multiple non-synonymous changes in lineages within the evolutionary landscape. Minor V3 variants detected as long as four years after infection co-localized in phylogenetic reconstructions with early transmitting viruses or with subsequent plasma virus circulating two years later. CONCLUSIONS: Deep sequencing defines HIV-1 population complexity and structure, reveals the ebb and flow of dominant and rare viral variants in the host ecosystem, and identifies an evolutionary record of low-frequency cell-associated viral V3 variants that persist for years. Bioinformatics pipeline developed for HIV-1 can be applied for biodiversity studies of virome populations in human, animal, or plant ecosystems.

Genetic determinants in HIV-1 Gag and Env V3 are related to viral response to combination antiretroviral therapy with a protease inhibitor.

OBJECTIVE: To identify novel viral determinants in HIV-1 protease, Gag, and envelope V3 that relate to outcomes to initial protease inhibitor-based antiretroviral therapy. DESIGN: A longitudinal cohort study of protease inhibitor-naive, HIV-infected individuals was designed to identify genetic variables in viral Gag and envelope sequences associated with response to antiretroviral therapy. METHODS: Genetic and statistical models, including amino acid profiles, phylogenetic analyses, receiver operating characteristic analyses, and covariation analyses, were used to evaluate viral sequences and clinical variables from individuals who developed immune reconstitution with or without suppression of viral replication. RESULTS: Pretherapy chemokine (C-X-C motif) receptor 4-using V3 regions had significant associations with viral failure (P = 0.04). Amino acid residues in protease covaried with Gag residues, particularly in p7(NC), independent of cleavage sites. Pretherapy V3 charge combined with p6(Pol) and p2/p7(NC) cleavage site genotypes produced the best three-variable model to predict viral suppression in 88% of individuals. Combinations of baseline CD4 cell percentage with genetic determinants in Gag-protease predicted viral fitness in 100% of individuals who failed to suppress viral replication. CONCLUSION: Baseline genetic determinants in Gag p6(Pol) and p2/p7(NC), as well as envelope, provide novel combinations of biomarkers for predicting emergence of viral resistance to initial therapy regimens.