Developing High-Throughput HIV Incidence Assay with Pyrosequencing Platform

Abstract

Human immunodeficiency virus (HIV) incidence is an important measure for monitoring the epidemic and evaluating the efficacy of intervention and prevention trials. This study developed a high-throughput, single-measure incidence assay by implementing a pyrosequencing platform. We devised a signal-masking bioinformatics pipeline, which yielded a process error rate of 5.8 ؋ 10 ؊4 per base. The pipeline was then applied to analyze 18,434 envelope gene segments (HXB2 7212 to 7601) obtained from 12 incident and 24 chronic patients who had documented HIV-negative and/or -positive tests. The pyrosequencing data were cross-checked by using the single-genome-amplification (SGA) method to independently obtain 302 sequences from 13 patients. Using two genomic biomarkers that probe for the presence of similar sequences, the pyrosequencing platform correctly classified all 12 incident subjects (100% sensitivity) and 23 of 24 chronic subjects (96% specificity). One misclassified subject's chronic infection was correctly classified by conducting the same analysis with SGA data. The biomarkers were statistically associated across the two platforms, suggesting the assay's reproducibility and robustness. Sampling simulations showed that the biomarkers were tolerant of sequencing errors and template resampling, two factors most likely to affect the accuracy of pyrosequencing results. We observed comparable biomarker scores between AIDS and non-AIDS chronic patients (multivariate analysis of variance [MANOVA], P ‫؍‬ 0.12), indicating that the stage of HIV disease itself does not affect the classification scheme. The highthroughput genomic HIV incidence marks a significant step toward determining incidence from a single measure in cross-sectional surveys. IMPORTANCEAnnual HIV incidence, the number of newly infected individuals within a year, is the key measure of monitoring the epidemic's rise and decline. Developing reliable assays differentiating recent from chronic infections has been a long-standing quest in the HIV community. Over the past 15 years, these assays have traditionally measured various HIV-specific antibodies, but recent technological advancements have expanded the diversity of proposed accurate, user-friendly, and financially viable tools. Here we designed a high-throughput genomic HIV incidence assay based on the signature imprinted in the HIV gene sequence population. By combining next-generation sequencing techniques with bioinformatics analysis, we demonstrated that genomic fingerprints are capable of distinguishing recently infected patients from chronically infected patients with high precision. Our high-throughput platform is expected to allow us to process many patients' samples from a single experiment, permitting the assay to be cost-effective for routine surveillance.

Deep sequencing: Becoming a critical tool in clinical virology

“…Accordingly, HIV has been classified into types, groups, subtypes or clades, circulating recombinant forms (CRF) and unique recombinant forms (URF) mainly based on the diversity of the viral env and pol genes [65–67]. Although to date most of the deep sequencing studies of HIV have focused on drug resistance and tropism, the methodology has been used to characterize novel HIV recombinants [69] and to determine HIV incidence [70]. Interestingly, deep sequencing has been particularly useful in the detection and characterization of HIV superinfection events, which seem to occur at higher rates than previously identified [71].…”

Differentiation of acute from chronic hepatitis C virus infection by nonstructural 5B deep sequencing: A population‐level tool for incidence estimation

“…To date, most longitudinal investigations of HCV diversity have utilized population or clonal sequencing of samples from a limited number of individuals. Deep sequencing studies have demonstrated improved sensitivity for detection of minor sequence variants, compared to clonal sequencing, enabling highly sensitive, specific differentiation of acute and chronic HIV infections, but similar differentiation analyses have heretofore not been applied to HCV. In this study, amplicons from the HCV nonstructural 5B (NS5B) region from 77 individuals with documented seroconversion time frames were deep sequenced to assess its potential to differentiate acute from chronic infection.…”

Assessment of Ambiguous Base Calls in HIV-1 pol Population Sequences as a Biomarker for Identification of Recent Infections in HIV-1 Incidence Studies

“…Unfortunately, samples from individuals infected with HIV-1 non-B subtypes (6,7), from elite controllers (8), from individuals treated with antiretroviral drugs (8,9), and from individuals with advanced stages of disease (7,9) can be misclassified on the basis of serological criteria because of delayed or reduced production of HIV-specific antibodies. Nonserological HIV-1 incidence assays (10,11) and algorithms combining serological and nonserological biomarkers have therefore been developed (12,13). HIV-1 diversity is considered to be a candidate nonserological biomarker, as it increases during the course of infection in antiretroviral treatment (ART)-naive individuals.…”

“…HIV-1 diversity is considered to be a candidate nonserological biomarker, as it increases during the course of infection in antiretroviral treatment (ART)-naive individuals. Viral diversity can be determined by single-genome sequencing (11), next-generation sequencing (10), and high-resolution melting assays (12), but direct Sanger population sequencing can also reflect HIV-1 polymorphisms via ambiguous base calls (14)(15)(16).…”