HIV-1 Subtype Distribution and Diversity Over 18 Years in Rakai, Uganda.

The Rakai Community Cohort Study in south central Uganda has surveyed people aged 15-49 since 1994. Antiretroviral therapy (ART) was introduced in 2004. HIV p24 and gp41 subtype distribution and viral diversity were studied from blood samples collected at three surveys in 1994-1995, 2002-2003, and 2008-2009, which were compared with a new survey round from 2011 to 2012. These included 1364 HIV+ individuals. For both p24 and gp41 domains, the genetic diversity within subtypes A and D was significantly increasing in the pre-ART era and decreased between the last two survey rounds in the ART era (p < .01). This study suggests that despite ongoing mixing of viral subtypes, an association with the introduction of ART to a reduction of intra-subtype viral genomic diversity may be occurring, which can be explored in ongoing studies.

Quantitation of the latent HIV-1 reservoir from the sequence diversity in viral outgrowth assays.

BACKGROUND: The ability of HIV-1 to integrate into the genomes of quiescent host immune cells, establishing a long-lived latent viral reservoir (LVR), is the primary obstacle to curing these infections. Quantitative viral outgrowth assays (QVOAs) are the gold standard for estimating the size of the replication-competent HIV-1 LVR, measured by the number of infectious units per million (IUPM) cells. QVOAs are time-consuming because they rely on culturing replicate wells to amplify the production of virus antigen or nucleic acid to reproducibly detectable levels. Sequence analysis can reduce the required number of culture wells because the virus genetic diversity within the LVR provides an internal replication and dilution series. Here we develop a Bayesian method to jointly estimate the IUPM and variant frequencies (a measure of clonality) from the sequence diversity of QVOAs. RESULTS: Using simulation experiments, we find our Bayesian approach confers significantly greater accuracy over current methods to estimate the IUPM, particularly for reduced numbers of QVOA replicates and/or increasing actual IUPM. Furthermore, we determine that the improvement in accuracy is greater with increasing genetic diversity in the sample population. We contrast results of these different methods applied to new HIV-1 sequence data derived from QVOAs from two individuals with suppressed viral loads from the Rakai Health Sciences Program in Uganda. CONCLUSIONS: Utilizing sequence variation has the additional benefit of providing information on the contribution of clonality of the LVR, where high clonality (the predominance of a single genetic variant) suggests a role for cell division in the long-term persistence of the reservoir. In addition, our Bayesian approach can be adapted to other limiting dilution assays where positive outcomes can be partitioned by their genetic heterogeneity, such as immune cell populations and other viruses.

Brain-specific HIV Nef identified in multiple patients with neurological disease.

HIV-1 Nef is a flexible, multifunctional protein with several cellular targets that is required for pathogenicity of the virus. This protein maintains a high degree of genetic variation among intra- and inter-host isolates. HIV Nef is relevant to HIV-associated neurological diseases (HAND) in patients treated with combined antiretroviral therapy because of the protein's role in promoting survival and migration of infected brain macrophages. In this study, we analyzed 2020 HIV Nef sequences derived from 22 different tissues and 31 subjects using a novel computational approach. This approach combines statistical regression and evolved neural networks (ENNs) to classify brain sequences based on the physical and chemical characteristics of functional Nef domains. Based on training, testing, and validation data, the method successfully classified brain Nef sequences at 84.5% and provided informative features for further examination. These included physicochemical features associated with the Src-homology-3 binding domain, the Nef loop (including the AP-2 Binding region), and a cytokine-binding domain. Non-brain sequences from patients with HIV-associated neurological disease were frequently classified as brain, suggesting that the approach could indicate neurological risk using blood-derived virus or for the development of biomarkers for use in assay systems aimed at drug efficacy studies for the treatment of HIV-associated neurological diseases.