The Challenge of HIV-1 Subtype Diversity

Taylor, Barbara S.; Sobieszczyk, Magdalena E.; McCutchan, Francine E.; Hammer, Scott M.

doi:10.1056/nejmra0706737

Cited by 463 publications

(297 citation statements)

References 93 publications

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“…The complexity of HIV strains has increased significantly due to natural evolution and intersubtype recombination; recombinant strains are now prevalent worldwide (57). Thus, it is essential to monitor HIV diversity accurately within populations and to determine phylogenetic classification based on the entire viral genome.…”

Section: Discussionmentioning

confidence: 99%

A Pan-HIV Strategy for Complete Genome Sequencing

et al. 2016

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bMolecular surveillance is essential to monitor HIV diversity and track emerging strains. We have developed a universal library preparation method (HIV-SMART [i.e., switching mechanism at 5= end of RNA transcript]) for next-generation sequencing that harnesses the specificity of HIV-directed priming to enable full genome characterization of all HIV-1 groups (M, N, O, and P) and HIV-2. Broad application of the HIV-SMART approach was demonstrated using a panel of diverse cell-cultured virus isolates. HIV-1 non-subtype B-infected clinical specimens from Cameroon were then used to optimize the protocol to sequence directly from plasma. When multiplexing 8 or more libraries per MiSeq run, full genome coverage at a median ϳ2,000؋ depth was routinely obtained for either sample type. The method reproducibly generated the same consensus sequence, consistently identified viral sequence heterogeneity present in specimens, and at viral loads of <4.5 log copies/ml yielded sufficient coverage to permit strain classification. HIV-SMART provides an unparalleled opportunity to identify diverse HIV strains in patient specimens and to determine phylogenetic classification based on the entire viral genome. Easily adapted to sequence any RNA virus, this technology illustrates the utility of next-generation sequencing (NGS) for viral characterization and surveillance.

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Section: Discussionmentioning

confidence: 99%

A Pan-HIV Strategy for Complete Genome Sequencing

et al. 2016

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“…Despite the perception that current antiretroviral regimens have comparable efficacies across existing diverse HIV-1 subtypes, there is evidence showing that some HIV-1 subtypes may have a transmission advantage, higher replicative efficiency, or even altered drug susceptibility (7)(8)(9)(10)(11), raising awareness on the relevance of investigating HIV-1 diversity. Furthermore, for the effective targeting of preventive measures, it is very relevant to perform persistent monitoring of the HIV-1 pandemic using phylogenetic and epidemiological data analyses as tools in the reconstruction of viral transmission networks (27)(28)(29).…”

Section: Discussionmentioning

confidence: 99%

“…The high prevalences of the B and G subtypes are thought to have promoted the appearance among intravenous drug users (IDU) of different types of B/G recombinant strains, namely, CRF14_BG, which is considered to have emerged in Portugal in the early 1990s and then spread to Spain and other European countries (24)(25)(26). The association between HIV-1 subtype and risk-behavior patterns has been complex to define, mainly due to difficulties in obtaining large numbers of each viral subtype and transmission route within a homogeneous study population (27).…”

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confidence: 99%

Analysis of a Local HIV-1 Epidemic in Portugal Highlights Established Transmission of Non-B and Non-G Subtypes

et al. 2015

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The existing data support Portugal as the western European country with the highest HIV-1 subtype diversity. However, detailed phylogenetic studies of Portuguese HIV-1 epidemics are still scarce. Thus, our main goal was to analyze the phylodynamics of a local HIV-1 infection in the Portuguese region of Minho. Molecular epidemiological analysis was applied to data from 289 HIV-1-infected individuals followed at the reference hospital of the province of Minho, Portugal, at which isolated viruses had been sequenced between 2000 and 2012. Viruses of the G (29.1%) and B (27.0%) subtypes were the most frequent, followed by recombinant forms (17.6%) and the C (14.5%), F1 (7.3%), and A1 (4.2%) subtypes. Multinomial logistic regression revealed that the odds of being infected with the A1 and F1 subtypes increased over the years compared with those with B, G, or C subtypes or recombinant viruses. As expected, polyphyletic patterns suggesting multiple and old introductions of the B and G subtypes were found. However, transmission clusters of non-B and non-G viruses among native individuals were also found, with the dates of the most recent common ancestor estimated to be in the early 2000s. Our study supports that the HIV-1 subtype diversity in the Portuguese region of Minho is high and has been increasing in a manner that is apparently driven by factors other than immigration and international travel. Infections with A1 and F1 viruses in the region of Minho are becoming established and are mainly found in sexually transmitted clusters, reinforcing the need for more efficacious control measures targeting this infection route.

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“…This study included samples from the United States, which were likely to be from individuals with subtype B infection (9). Also, the majority of the samples used to develop the HRM-based MAA were from MSM and persons who inject drugs.…”

Section: Discussionmentioning

confidence: 99%

“…The shadow measures the time period prior to sample collection that is being assessed by a given MAA (6). A 4-assay MAA was developed that provides accurate HIV incidence estimates in cohorts from the United States (4,7,8), where most infections are caused by subtype B HIV (9). This MAA includes CD4 cell count, the BED capture enzyme immunoassay (BED-CEIA) (10), the Bio-Rad Avidity assay (11), and viral load.…”

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confidence: 99%

HIV Diversity as a Biomarker for HIV Incidence Estimation: Including a High-Resolution Melting Diversity Assay in a Multiassay Algorithm

et al. 2014

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pMultiassay algorithms (MAAs) can be used to estimate cross-sectional HIV incidence. We previously identified a robust MAA that includes the BED capture enzyme immunoassay (BED-CEIA), the Bio-Rad Avidity assay, viral load, and CD4 cell count. In this report, we evaluated MAAs that include a high-resolution melting (HRM) diversity assay that does not require sequencing. HRM scores were determined for eight regions of the HIV genome (2 in gag, 1 in pol, and 5 in env). The MAAs that were evaluated included the BED-CEIA, the Bio-Rad Avidity assay, viral load, and the HRM diversity assay, using HRM scores from different regions and a range of region-specific HRM diversity assay cutoffs. The performance characteristics based on the proportion of samples that were classified as MAA positive by duration of infection were determined for each MAA, including the mean window period. The cross-sectional incidence estimates obtained using optimized MAAs were compared to longitudinal incidence estimates for three cohorts in the United States. The performance of the HRM-based MAA was nearly identical to that of the MAA that included CD4 cell count. The HRM-based MAA had a mean window period of 154 days and provided cross-sectional incidence estimates that were similar to those based on cohort follow-up. HIV diversity is a useful biomarker for estimating HIV incidence. MAAs that include the HRM diversity assay can provide accurate HIV incidence estimates using stored blood plasma or serum samples without a requirement for CD4 cell count data.

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The Challenge of HIV-1 Subtype Diversity

Cited by 463 publications

References 93 publications

A Pan-HIV Strategy for Complete Genome Sequencing

A Pan-HIV Strategy for Complete Genome Sequencing

Analysis of a Local HIV-1 Epidemic in Portugal Highlights Established Transmission of Non-B and Non-G Subtypes

HIV Diversity as a Biomarker for HIV Incidence Estimation: Including a High-Resolution Melting Diversity Assay in a Multiassay Algorithm

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