A comprehensive genomics solution for HIV surveillance and clinical monitoring in a global health setting

Abstract

High-throughput viral genetic sequencing is needed to monitor the spread of drug resistance, direct optimal antiretroviral regimes, and to identify transmission dynamics in generalised HIV epidemics. Public health efforts to sequence HIV genomes at scale face three major technical challenges: (i) minimising assay cost and protocol complexity, (ii) maximising sensitivity, and (iii) recovering accurate and unbiased sequences of both the genome consensus and the within-host viral diversity. Here we present a novel, high-throughput, virus-enriched sequencing method and computational pipeline tailored specifically to HIV (veSEQ-HIV), which addresses all three technical challenges, and can be used directly on leftover blood drawn for routine CD4 testing. We demonstrate its performance on 1,620 plasma samples collected from consenting individuals attending 10 large urban clinics in Zambia, partners of HPTN 071 (PopART). We show that veSEQ-HIV consistently recovers complete HIV genomes from the majority of samples of different subtypes, and is also quantitative: the number of HIV reads per sample obtained by veSEQ-HIV estimates viral load without the need for additional testing. Both quantitativity and sensitivity were assessed on a subset of 126 samples with clinically measured viral loads, and with standardized quantification controls (VL 100 -5,000,000 RNA copies/ml). Complete HIV genomes were recovered from 93% (85/91) of samples when viral load was over 1,000 copies per ml. The quantitative nature of the assay implies that variant frequencies estimated with veSEQ-HIV are representative of true variant frequencies in the sample. Detection of minority variants can be exploited for epidemiological analysis of transmission and drug resistance, and we show how the information contained in individual reads of a veSEQ-HIV sample can be used to detect linkage between multiple mutations associated with resistance to antiretroviral therapy. Less than 2% of reads obtained by veSEQ-HIV were identified as in silico contamination events using updates to the phyloscanner software (phyloscanner clean) that we show to be 95% sensitive and 99% specific at 'decontaminating' NGS data. The cost of the assay -approximately 45 USD per sample -compares favourably with existing VL and HIV genotyping tests, and provides the additional value of viral load quantification and inference of drug resistance with a single test. veSEQ-HIV is well suited to large public health efforts and is being applied to all ~9000 samples collected for the HPTN 071-2 (PopART Phylogenetics) study. Figure 1: Information included in the veSEQ-HIV method. The veSEQ-HIV method was developed to provide multiple measurements from a single assay, including viral load, genotype, inference of the transmission events and drug resistance levels.

Are We Ready for NGS HIV Drug Resistance Testing? The Second “Winnipeg Consensus” Symposium

“…Most NGS HIVDR protocols involve rounds of PCR amplification in NGS library preparation. Probe-capture-based NGS methods, such as veSEQ-HIV, require minimal PCR steps and may help to reduce PCR-introduced sampling bias [ 49 ].…”

Emerging PCR-Based Techniques to Study HIV-1 Reservoir Persistence

“…This gives rise to the need for good universal criteria on what defines replication competence, which factors should be taken into account while subjecting these sequences for analysis, and an open disclosure of the used strategy when presenting data. Examples of such pipelines offering a standardized method using Illumina sequencing data have been published, yet they focus on different aspects [33][34][35]. For instance, hivmmer is a variant-caller for the pol subgenomic region whereas shiver and veSEQ-HIV are both aimed at the reconstruction of HIV-1 quasispecies to study epidemiology and viral drug resistance [33][34][35].…”

Pangea-Hiv 2

“…(1) Sequence your samples with PANGEA: We offer subsidized state-of-the-art NGS sequencing [60] to collaborators who are willing to contribute their sequence data and associated epidemiological data to the PANGEA database 12 months after they have received the data. (2) Contribute sequence data: If your project is at a stage where you are ready to reach out to a wider range of collaborators or if you are looking for a secure storing place for your data, consider contributing your sequence data to the PANGEA database.…”

“…Currently the PANGEA database holds over 18 000 NGS sequence files from sub-Saharan Africa ( protocol [60], we currently obtain full genomes from close to 90% of high-quality samples, with many of the less-complete sequences originating from participants who are likely already virally suppressed.…”