Abstract
BackgroundHIV 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.MethodsDivMelt 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.ResultsHRM 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.ConclusionDivMelt provides a rapid, accurate method of determining HRM scores from melting curve data, facilitating use of the HRM diversity assay for large-scale studies.
Highlights
Accurate methods to estimate HIV incidence from crosssectional surveys are needed for surveillance of the HIV/AIDS epidemic [1]
Distinct patterns of high resolution melting (HRM) scores are associated with different stages of HIV disease, suggesting that the HRM diversity assay may be useful for analysis of HIV incidence [5]
Source of HRM Data Used in the Analysis Plasmids (n = 5) and plasma samples from individuals with acute (n = 20), recent (n = 102), and non-recent (n = 67) HIV infection were analyzed with the HRM diversity assay as part of a previous study [5]
Summary
Accurate methods to estimate HIV incidence from crosssectional surveys are needed for surveillance of the HIV/AIDS epidemic [1]. HIV diversity may be a useful biomarker for analysis of HIV incidence because levels of HIV diversity change during the course of HIV infection [5,6]. We developed a rapid assay to quantify HIV diversity that does not require sequencing This assay is based on high resolution melting (HRM) analysis [5,7]. 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. A software package, the HRM Diversity Assay Analysis Tool (DivMelt), was developed to automate calculation of HRM scores from melting curve data
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