Use of a high resolution melting assay to analyze HIV diversity in HIV-infected Ugandan children

A High-Resolution Digital DNA Melting Platform for Robust Sequence Profiling and Enhanced Genotype Discrimination

DNA melting analysis provides a rapid method for genotyping a target amplicon directly after PCR amplification. To transform melt genotyping into a broad-based profiling approach for heterogeneous samples, we previously proposed the integration of universal PCR and melt analysis with digital PCR. Here, we advanced this concept by developing a high-resolution digital melt platform with precise thermal control to accomplish reliable, high-throughput heat ramping of microfluidic chip digital PCR reactions. Using synthetic DNA oligos with defined melting temperatures, we characterized sources of melting variability and minimized run-to-run variations. Within-run comparisons throughout a 20,000-reaction chip revealed that high-melting-temperature sequences were significantly less prone to melt variation. Further optimization using bacterial 16S amplicons revealed a strong dependence of the number of melting transitions on the heating rate during curve generation. These studies show that reliable high-resolution melt curve genotyping can be achieved in digital, picoliter-scale reactions and demonstrate that rate-dependent melt signatures may be useful for enhancing automated melt genotyping.

Association of HIV diversity and virologic outcomes in early antiretroviral treatment: HPTN 052

Higher HIV diversity has been associated with virologic outcomes in children on antiretroviral treatment (ART). We examined the association of HIV diversity with virologic outcomes in adults from the HPTN 052 trial who initiated ART at CD4 cell counts of 350-550 cells/mm3. A high resolution melting (HRM) assay was used to analyze baseline (pre-treatment) HIV diversity in six regions in the HIV genome (two in gag, one in pol, and three in env) from 95 participants who failed ART. We analyzed the association of HIV diversity in each genomic region with baseline (pre-treatment) factors and three clinical outcomes: time to virologic suppression after ART initiation, time to ART failure, and emergence of HIV drug resistance at ART failure. After correcting for multiple comparisons, we did not find any association of baseline HIV diversity with demographic, laboratory, or clinical characteristics. For the 18 analyses performed for clinical outcomes evaluated, there was only one significant association: higher baseline HIV diversity in one of the three HIV env regions was associated with longer time to ART failure (p = 0.008). The HRM diversity assay may be useful in future studies exploring the relationship between HIV diversity and clinical outcomes in individuals with HIV infection.

Analysis of HIV Diversity in HIV-Infected Black Men Who Have Sex with Men (HPTN 061)

Background

HIV populations often diversify in response to selective pressures, such as the immune response and antiretroviral drug use. We analyzed HIV diversity in Black men who have sex with men who were enrolled in the HIV Prevention Trials Network 061 study.

Methods

A high resolution melting (HRM) diversity assay was used to measure diversity in six regions of the HIV genome: two in gag, one in pol, and three in env. HIV diversity was analyzed for 146 men who were HIV infected at study enrollment, including three with acute infection and 13 with recent infection (identified using a multi-assay algorithm), and for 21 men who seroconverted during the study. HIV diversification was analyzed in a paired analysis for 62 HIV-infected men using plasma samples from the enrollment and 12-month (end of study) visits.

Results

Men with acute or recent infection at enrollment and seroconverters had lower median HRM scores (lower HIV diversity) than men with non-recent infection in all six regions analyzed. In univariate analyses, younger age, higher CD4 cell count, and HIV drug resistance were associated with lower median HRM scores in multiple regions; ARV drug detection was marginally associated with lower diversity in the pol region. In multivariate analysis, acute or recent infection (all six regions) and HIV drug resistance (both gag regions) were associated with lower median HRM scores. Diversification in the pol region over 12 months was greater for men with acute or recent infection, higher CD4 cell count, and lower HIV viral load at study enrollment.

Conclusions

HIV diversity was significantly associated with duration of HIV infection, and lower gag diversity was observed in men who had HIV drug resistance. HIV pol diversification was more pronounced in men with acute or recent infection, higher CD4 cell count, and lower HIV viral load.

Identifying Recent HIV Infections: From Serological Assays to Genomics

In this paper, we review serological and molecular based methods to identify HIV infection recency. The accurate identification of recent HIV infection continues to be an important research area and has implications for HIV prevention and treatment interventions. Longitudinal cohorts that follow HIV negative individuals over time are the current gold standard approach, but they are logistically challenging, time consuming and an expensive enterprise. Methods that utilize cross-sectional testing and biomarker information have become an affordable alternative to the longitudinal approach. These methods use well-characterized biological makers to differentiate between recent and established HIV infections. However, recent results have identified a number of limitations in serological based assays that are sensitive to the variability in immune responses modulated by HIV subtypes, viral load and antiretroviral therapy. Molecular methods that explore the dynamics between the timing of infection and viral evolution are now emerging as a promising approach. The combination of serological and molecular methods may provide a good solution to identify recent HIV infection in cross-sectional data. As part of this review, we present the advantages and limitations of serological and molecular based methods and their potential complementary role for the identification of HIV infection recency.

A comparison of two measures of HIV diversity in multi-assay algorithms for HIV incidence estimation

BACKGROUND

Multi-assay algorithms (MAAs) can be used to estimate HIV incidence in cross-sectional surveys. We compared the performance of two MAAs that use HIV diversity as one of four biomarkers for analysis of HIV incidence.

METHODS

Both MAAs included two serologic assays (LAg-Avidity assay and BioRad-Avidity assay), HIV viral load, and an HIV diversity assay. HIV diversity was quantified using either a high resolution melting (HRM) diversity assay that does not require HIV sequencing (HRM score for a 239 base pair env region) or sequence ambiguity (the percentage of ambiguous bases in a 1,302 base pair pol region). Samples were classified as MAA positive (likely from individuals with recent HIV infection) if they met the criteria for all of the assays in the MAA. The following performance characteristics were assessed: (1) the proportion of samples classified as MAA positive as a function of duration of infection, (2) the mean window period, (3) the shadow (the time period before sample collection that is being assessed by the MAA), and (4) the accuracy of cross-sectional incidence estimates for three cohort studies.

RESULTS

The proportion of samples classified as MAA positive as a function of duration of infection was nearly identical for the two MAAs. The mean window period was 141 days for the HRM-based MAA and 131 days for the sequence ambiguity-based MAA. The shadows for both MAAs were <1 year. Both MAAs provided cross-sectional HIV incidence estimates that were very similar to longitudinal incidence estimates based on HIV seroconversion.

CONCLUSIONS

MAAs that include the LAg-Avidity assay, the BioRad-Avidity assay, HIV viral load, and HIV diversity can provide accurate HIV incidence estimates. Sequence ambiguity measures obtained using a commercially-available HIV genotyping system can be used as an alternative to HRM scores in MAAs for cross-sectional HIV incidence estimation.

Association of pol diversity with antiretroviral treatment outcomes among HIV-infected African children

Background

In HIV-infected children, viral diversity tends to increase with age in the absence of antiretroviral treatment (ART). We measured HIV diversity in African children (ages 6–36 months) enrolled in a randomized clinical trial comparing two ART regimens (Cohort I of the P1060 trial). Children in this cohort were exposed to single dose nevirapine (sdNVP) at birth.

Methods

HIV diversity was measured retrospectively using a high resolution melting (HRM) diversity assay. Samples were obtained from 139 children at the enrollment visit prior to ART initiation. Six regions of the HIV genome were analyzed: two in gag, one in pol, and three in env. A single numeric HRM score that reflects HIV diversity was generated for each region; composite HRM scores were also calculated (mean and median for all six regions).

Results

In multivariable median regression models using backwards selection that started with demographic and clinical variables, older age was associated with higher HRM scores (higher HIV diversity) in pol (P = 0.005) and with higher mean (P = 0.014) and median (P<0.001) HRM scores. In multivariable models adjusted for age, pre-treatment HIV viral load, pre-treatment CD4%, and randomized treatment regimen, higher HRM scores in pol were associated with shorter time to virologic suppression (P = 0.016) and longer time to study endpoints (virologic failure [VF], VF/death, and VF/off study treatment; P<0.001 for all measures).

Conclusions

In this cohort of sdNVP-exposed, ART-naïve African children, higher levels of HIV diversity in the HIV pol region prior to ART initiation were associated with better treatment outcomes.

HIV diversity as a biomarker for HIV incidence estimation: including a high-resolution melting diversity assay in a multiassay algorithm

Multiassay 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.

Antibody maturation and viral diversification in HIV-infected women

INTRODUCTION

The Post-exposure Prophylaxis in Infants (PEPI)-Malawi trial evaluated infant antiretroviral regimens for prevention of post-natal HIV transmission. A multi-assay algorithm (MAA) that includes the BED capture immunoassay, an avidity assay, CD4 cell count, and viral load was used to identify women who were vs. were not recently infected at the time of enrollment (MAA recent, N = 73; MAA non-recent, N = 2,488); a subset of the women in the MAA non-recent group known to have been HIV infected for at least 2 years before enrollment (known non-recent, N = 54). Antibody maturation and viral diversification were examined in these women.

METHODS

Samples collected at enrollment (N = 2,561) and 12-24 months later (N = 1,306) were available for serologic analysis using the BED and avidity assays. A subset of those samples was used for analysis of viral diversity, which was performed using a high resolution melting (HRM) diversity assay. Viral diversity analysis was performed using all available samples from women in the MAA recent group (61 enrollment samples, 38 follow-up samples) and the known non-recent group (43 enrollment samples, 22 follow-up samples). Diversity data from PEPI-Malawi were also compared to similar data from 169 adults in the United States (US) with known recent infection (N = 102) and known non-recent infection (N = 67).

RESULTS

In PEPI-Malawi, results from the BED and avidity assays increased over time in the MAA recent group, but did not change significantly in the MAA non-recent group. At enrollment, HIV diversity was lower in the MAA recent group than in the known non-recent group. HRM diversity assay results from women in PEPI-Malawi were similar to those from adults in the US with known duration of HIV infection.

CONCLUSIONS

Antibody maturation and HIV diversification patterns in African women provide additional support for use of the MAA to identify populations with recent HIV infection.

Analysis of HIV using a high resolution melting (HRM) diversity assay: automation of HRM data analysis enhances the utility of the assay for analysis of HIV incidence

BACKGROUND

HIV diversity may be a useful biomarker for discriminating between recent and non-recent HIV infection. The high resolution melting (HRM) diversity assay was developed to quantify HIV diversity in viral populations without sequencing. In this assay, HIV diversity is expressed as a single numeric HRM score that represents the width of a melting peak. HRM scores are highly associated with diversity measures obtained with next generation sequencing. In this report, a software package, the HRM Diversity Assay Analysis Tool (DivMelt), was developed to automate calculation of HRM scores from melting curve data.

METHODS

DivMelt uses computational algorithms to calculate HRM scores by identifying the start (T1) and end (T2) melting temperatures for a DNA sample and subtracting them (T2 - T1 =  HRM score). DivMelt contains many user-supplied analysis parameters to allow analyses to be tailored to different contexts. DivMelt analysis options were optimized to discriminate between recent and non-recent HIV infection and to maximize HRM score reproducibility. HRM scores calculated using DivMelt were compared to HRM scores obtained using a manual method that is based on visual inspection of DNA melting curves.

RESULTS

HRM scores generated with DivMelt agreed with manually generated HRM scores obtained from the same DNA melting data. Optimal parameters for discriminating between recent and non-recent HIV infection were identified. DivMelt provided greater discrimination between recent and non-recent HIV infection than the manual method.

CONCLUSION

DivMelt provides a rapid, accurate method of determining HRM scores from melting curve data, facilitating use of the HRM diversity assay for large-scale studies.

Impact of mutation type and amplicon characteristics on genetic diversity measures generated using a high-resolution melting diversity assay

We adapted high-resolution melting (HRM) technology to measure genetic diversity without sequencing. Diversity is measured as a single numeric HRM score. Herein, we determined the impact of mutation types and amplicon characteristics on HRM diversity scores. Plasmids were generated with single-base changes, insertions, and deletions. Different primer sets were used to vary the position of mutations within amplicons. Plasmids and plasmid mixtures were analyzed to determine the impact of mutation type, position, and concentration on HRM scores. The impact of amplicon length and G/C content on HRM scores was also evaluated. Different mutation types affected HRM scores to varying degrees (1-bp deletion < 1-bp change < 3-bp insertion < 9-bp insertion). The impact of mutations on HRM scores was influenced by amplicon length and the position of the mutation within the amplicon. Mutations were detected at concentrations of 5% to 95%, with the greatest impact at 50%. The G/C content altered melting temperature values of amplicons but had no impact on HRM scores. These data are relevant to the design of assays that measure genetic diversity using HRM technology.