454 sequencing technology is a promising approach for characterizing HIV-1 populations and for identifying low frequency mutations. The utility of 454 technology for determining allele frequencies and linkage associations in HIV infected individuals has not been extensively investigated. We evaluated the performance of 454 sequencing for characterizing HIV populations with defined allele frequencies.

Although next generation sequencing (NGS) offers the potential for studying virus populations in unprecedented depth, PCR error, amplification bias and recombination during library construction have limited its use to population sequencing and measurements of unlinked allele frequencies. Here we report a method, termed ultrasensitive Single-Genome Sequencing (uSGS), for NGS library construction and analysis that eliminates PCR errors and recombinants, and generates single-genome sequences of the same quality as the “gold-standard” of HIV-1 single-genome sequencing assay but with more than 100-fold greater depth. Primer ID tagged cDNA was synthesized from mixtures of cloned BH10 wild-type and mutant HIV-1 transcripts containing ten drug resistance mutations. First, the resultant cDNA was divided and NGS libraries were generated in parallel using two methods: uSGS and a method applying long PCR primers to attach the NGS adaptors (LP-PCR-1). Second, cDNA was divided and NGS libraries were generated in parallel comparing 3 methods: uSGS and 2 methods adapted from more recent reports using variations of the long PCR primers to attach the adaptors (LP-PCR-2 and LP-PCR-3). Consistently, the uSGS method amplified a greater proportion of cDNAs, averaging 30% compared to 13% for LP-PCR-1, 21% for LP-PCR-2 and 14% for LP-PCR-3. Most importantly, when the uSGS sequences were binned according to their primer IDs, 94% of the bins did not contain PCR recombinant sequences versus only 55, 75 and 65% for LP-PCR-1, 2 and 3, respectively. Finally, when uSGS was applied to plasma samples from HIV-1 infected donors, both frequent and rare variants were detected in each sample and neighbor-joining trees revealed clusters of genomes driven by the linkage of these mutations, showing the lack of PCR recombinants in the datasets. The uSGS assay can be used for accurate detection of rare variants and for identifying linkage of rare alleles associated with HIV-1 drug resistance. In addition, the method allows accurate in-depth analyses of the complex genetic relationships of viral populations in vivo.

It has been proposed that most drug-resistant mutants, resulting from a single-nucleotide change, exist at low frequency in human immunodeficiency virus type 1 (HIV-1) and simian immunodeficiency virus (SIV) populations in vivo prior to the initiation of antiretroviral therapy (ART). To test this hypothesis and to investigate the emergence of resistant mutants with drug selection, we developed a new ultrasensitive allele-specific PCR (UsASP) assay, which can detect drug resistance mutations at a frequency of ≥0.001% of the virus population. We applied this assay to plasma samples obtained from macaques infected with an SIV variant containing HIV-1 reverse transcriptase (RT) (RT-simian-human immunodeficiency [SHIV] _mne ), before and after they were exposed to a short course of efavirenz (EFV) monotherapy. We detected RT inhibitor (RTI) resistance mutations K65R and M184I but not K103N in 2 of 2 RT-SHIV-infected macaques prior to EFV exposure. After three doses over 4 days of EFV monotherapy, 103N mutations (AAC and AAT) rapidly emerged and increased in the population to levels of ∼20%, indicating that they were present prior to EFV exposure. The rapid increase of 103N mutations from <0.001% to 20% of the viral population indicates that the replicating virus population size in RT-SHIV-infected macaques must be 10 ⁶ or more infected cells per replication cycle.

The latent HIV-1 reservoir is comprised of stably integrated and intact proviruses with limited to no viral transcription. It has been proposed that latent infection may be maintained by methylation of pro-viral DNA. Here, for the first time, we investigate the cytosine methylation of a replication competent provirus (AMBI-1) found in a T cell clone in a donor on antiretroviral therapy (ART). Methylation profiles of the AMBI-1 provirus were compared to other proviruses in the same donor and in samples from three other individuals on ART, including proviruses isolated from lymph node mononuclear cells (LNMCs) and peripheral blood mononuclear cells (PBMCs). We also evaluated the apparent methylation of cytosines outside of CpG (i.e., CpH) motifs. We found no evidence for methylation in AMBI-1 or any other provirus tested within the 5′ LTR promoter. In contrast, CpG methylation was observed in the env-tat-rev overlapping reading frame. In addition, we found evidence for differential provirus methylation in cells isolated from LNMCs vs. PBMCs in some individuals, possibly from the expansion of infected cell clones. Finally, we determined that apparent low-level methylation of CpH cytosines is consistent with occasional bisulfite reaction failures. In conclusion, our data do not support the proposition that latent HIV infection is associated with methylation of the HIV 5′ LTR promoter.

The prevalence of HIV-1 drug resistance is increasing worldwide and monitoring its emergence is important for the successful management of populations receiving combination antiretroviral therapy. It is likely that pre-existing drug resistance mutations linked on the same viral genomes are predictive of treatment failure. Because of the large number of sequences generated by ultrasensitive single-genome sequencing (uSGS) and other similar next-generation sequencing methods, it is difficult to assess each sequence individually for linked drug resistance mutations. Several software/programs exist to report the frequencies of individual mutations in large data sets, but they provide no information on linkage of resistance mutations. In this study, we report the HIV-DRLink program, a research tool that provides resistance mutation frequencies as well as their genetic linkage by parsing and summarizing the Sierra output from the Stanford HIV Database. The HIV-DRLink program should only be used on data sets generated by methods that eliminate artifacts due to polymerase chain reaction recombination, for example, standard single-genome sequencing or uSGS. HIV-DRLink is exclusively a research tool and is not intended to inform clinical decisions.

The prevalence of HIV-1 drug resistance is increasing worldwide and monitoring its emergence is important for the successful management of populations receiving combination antiretroviral therapy (cART). Using Ultrasensitive Single-Genome Sequencing (uSGS), a next-generation method that avoids PCR bias and PCR recombination, a recent report showed that pre-existing dual-class drug resistance mutations linked on the same viral genomes were predictive of treatment failure while unlinked mutations were not. Because of the large numbers of sequences generated by uSGS and other next-generation sequencing methods, it is difficult to assess each sequence individually for linked resistance mutations. Several software/programs exist to report the frequencies of individual mutations in large datasets but they provide no information on their linkage. Here, we report the HIV-DRLink program, a research tool that provides mutation frequencies in the total dataset as well as their linkage to other mutations conferring resistance to the same or different drug classes. The HIV-DRLink program should only be used on datasets generated by methods that eliminate artifacts due to PCR recombination, for example, standard Single-Genome Sequencing (SGS) or Ultrasensitive Single-Genome Sequencing (uSGS). HIV-DRLink is exclusively a research tool and is not intended to inform clinical decisions.