Use of a high resolution melting (HRM) assay to compare gag, pol, and env diversity in adults with different stages of HIV infection

Abstract

Background: Cross-sectional assessment of HIV incidence relies on laboratory methods to discriminate between recent and non-recent HIV infection. Because HIV diversifies over time in infected individuals, HIV diversity may serve as a biomarker for assessing HIV incidence. We used a high resolution melting (HRM) diversity assay to compare HIV diversity in adults with different stages of HIV infection. This assay provides a single numeric HRM score that reflects the level of genetic diversity of HIV in a sample from an infected individual.

Methods: HIV diversity was measured in 203 adults: 20 with acute HIV infection (RNA positive, antibody negative), 116 with recent HIV infection (tested a median of 189 days after a previous negative HIV test, range 14-540 days), and 67 with non-recent HIV infection (HIV infected >2 years). HRM scores were generated for two regions in gag, one region in pol, and three regions in env.

Results: Median HRM scores were higher in non-recent infection than in recent infection for all six regions tested. In multivariate models, higher HRM scores in three of the six regions were independently associated with non-recent HIV infection.

Conclusions: The HRM diversity assay provides a simple, scalable method for measuring HIV diversity. HRM scores, which reflect the genetic diversity in a viral population, may be useful biomarkers for evaluation of HIV incidence, particularly if multiple regions of the HIV genome are examined.

Figure 1. Regions of the HIV genome analyzed using the HRM diversity assay.

The relevant regions of the HIV genome are shown (adapted from [39]). Numbers at the ends of each genomic segment correspond to coordinates in HXB2 (Genbank accession number: K03455). The amplicons used for HRM diversity analysis (regions analyzed) are indicated by shaded boxes. (A) Gag and pol amplicons: The GAG1 amplicon includes a portion of the coding regions for gag p7 and gag p1. The GAG2 amplicon includes the coding regions for gag p1 and gag p6 and extends into the coding region for HIV protease (PR); this amplicon also corresponds to the transframe (TF) protein. The POL amplicon spans the junction between the coding regions of HIV protease and HIV reverse transcriptase (RT). (B) Env amplicons: The ENV1 amplicon includes the coding region for heptad repeat 1 (HR1) of gp41, as well as portions of the coding regions to either side of HR1. The ENV3 amplicon includes the coding region for heptad repeat 2 (HR2), as well as portions of the coding regions to either side of HR2. The ENV2 amplicon includes the coding region for immunodominant region (IDR) cluster I of gp41, as well as portions of the coding regions for HR1 and HR2 .

Figure 2. HRM scores for plasmid controls and samples from adults with different stages of HIV disease.

The box and whisker plots show the distribution of HRM scores for six regions in the HIV genome in control plasmids (n = 5; Subtype B) and in adults with acute (n = 20), recent (n = 102), and non-recent (n = 67) HIV infection (see text). For each column, the median (closed square), interquartile range (IQR, box), lower inner fence (first quartile [Q1] – [1.5 X IQR]) and upper inner fence (third quartile [Q3] + [1.5 X IQR], whiskers), outliers (greater than [Q3] + [1.5 x IQR], open circle) and extremes (greater than [Q3] + [3 x IQR], asterisk) are shown.

Figure 3. Relationship between HRM scores for the ENV1, ENV2, and GAG2 regions.

Scatter plots are shown for HRM scores for adults with acute, recent, and non-recent infection: (A) ENV1 vs. GAG2, (B) ENV3 vs. GAG2, and (C) ENV1 vs. ENV3.

Figure 4. HRM diversity scores for GAG2, ENV1 and ENV3 plotted in 3 dimensions.

High HRM scores for these regions were determined to be independently associated with non-recent infection. The use of data from multiple regions in tandem demonstrates that HRM scores are generally compact in acute infection (A) with a slight increase in the distribution of data in recent infection (B), and wide dispersion of the data in non-recent infection (C).

Figure 5. Use of the HRM diversity assay as part of a multi-assay algorithm for HIV incidence determination.

Panel A shows one example of a multi-assay algorithm developed for HIV incidence determination. In this algorithm, samples from HIV-infected individuals are first tested using the BED-CEIA assay, using a high assay cutoff to indicate non-recent HIV infection (BED screen). Samples that are below the BED screen cutoff (BED recent samples) are then tested using a second serologic assay, such as one based on antibody avidity (avidity screen). Samples that are below the cutoff for the second serologic assay are considered to be “serologic recent” samples. Samples with low CD4 cell count test results are then excluded as non-recent (note that CD4 cell count test results are usually obtained for all HIV-infected individuals at the time of sample collection). Finally, samples that are not excluded based on CD4 cell count are tested using a viral load assay, and samples with low viral loads are excluded as non-recent. The remaining samples are characterized as recent for the purpose of estimating HIV incidence. Panel B shows an alternative multi-assay algorithm that incorporates the HRM diversity assay. In this algorithm, samples that are characterized as serologic recent based on two assays (BED screen and an avidity screen) are tested with a multi-region HRM diversity assay. Samples that have a high HRM score in at least one of the regions tested are excluded as non-recent. Samples that fail to amplify in all regions tested are also excluded as non-recent, based on the assumption that they have low viral loads; this could be confirmed with a viral load assay. Samples that have low HRM scores in all regions tested are characterized as recent for the purpose of estimating HIV incidence.