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

Modeling methods for estimating HIV incidence: a mathematical review

Estimating HIV incidence is crucial for monitoring the epidemiology of this infection, planning screening and intervention campaigns, and evaluating the effectiveness of control measures. However, owing to the long and variable period from HIV infection to the development of AIDS and the introduction of highly active antiretroviral therapy, accurate incidence estimation remains a major challenge. Numerous estimation methods have been proposed in epidemiological modeling studies, and here we review commonly-used methods for estimation of HIV incidence. We review the essential data required for estimation along with the advantages and disadvantages, mathematical structures and likelihood derivations of these methods. The methods include the classical back-calculation method, the method based on CD4+ T-cell depletion, the use of HIV case reporting data, the use of cohort study data, the use of serial or cross-sectional prevalence data, and biomarker approach. By outlining the mechanistic features of each method, we provide guidance for planning incidence estimation efforts, which may depend on national or regional factors as well as the availability of epidemiological or laboratory datasets.

Evaluation of High-Resolution Melting for Rapid Differentiation of Phytophthora Hybrids and Their Parental Species

Phytophthora species hybrids have been repeatedly reported as causing damaging diseases to cultivated and wild plants. Two known hybrids, P. andina and P. × pelgrandis, are pathogens of Solanaceae and ornamentals, respectively, although the extent of their host ranges are unknown. P. andina emerged from hybridization of P. infestans and an unidentified related species, whereas P. × pelgrandis emerged from P. nicotianae and P. cactorum. Considering that hybrids and parental species can coexist in the same regions and to distinguish them usually requires cloning or whole genome sequencing, we aimed to develop a rapid tool to distinguish them. Specifically, we used high-resolution melting (HRM) assays to differentiate genotypes based on their amplicon melting profiles. We designed primers for P. × pelgrandis and parental species based on available sequences of P. nicotianae and P. cactorum nuclear genes containing polymorphisms between species. For P. andina, heterozygous sites from Illumina short reads were used for the same purpose. We identified multiple amplicons exhibiting differences in melting curves between parental species and hybrids. We propose HRM as a rapid method for differentiation of P. andina and P. × pelgrandis hybrids from parental species that could be employed to advance research on these pathogens.

Diagnosis of Human Immunodeficiency Virus Infection

HIV diagnostics have played a central role in the remarkable progress in identifying, staging, initiating, and monitoring infected individuals on life-saving antiretroviral therapy. They are also useful in surveillance and outbreak responses, allowing for assessment of disease burden and identification of vulnerable populations and transmission "hot spots," thus enabling planning, appropriate interventions, and allocation of appropriate funding. HIV diagnostics are critical in achieving epidemic control and require a hybrid of conventional laboratory-based diagnostic tests and new technologies, including point-of-care (POC) testing, to expand coverage, increase access, and positively impact patient management. In this review, we provide (i) a historical perspective on the evolution of HIV diagnostics (serologic and molecular) and their interplay with WHO normative guidelines, (ii) a description of the role of conventional and POC testing within the tiered laboratory diagnostic network, (iii) information on the evaluations and selection of appropriate diagnostics, (iv) a description of the quality management systems needed to ensure reliability of testing, and (v) strategies to increase access while reducing the time to return results to patients. Maintaining the central role of HIV diagnostics in programs requires periodic monitoring and optimization with quality assurance in order to inform adjustments or alignment to achieve epidemic control.

HIV-1 envelope sequence-based diversity measures for identifying recent infections

Identifying recent HIV-1 infections is crucial for monitoring HIV-1 incidence and optimizing public health prevention efforts. To identify recent HIV-1 infections, we evaluated and compared the performance of 4 sequence-based diversity measures including percent diversity, percent complexity, Shannon entropy and number of haplotypes targeting 13 genetic segments within the env gene of HIV-1. A total of 597 diagnostic samples obtained in 2013 and 2015 from recently and chronically HIV-1 infected individuals were selected. From the selected samples, 249 (134 from recent versus 115 from chronic infections) env coding regions, including V1-C5 of gp120 and the gp41 ectodomain of HIV-1, were successfully amplified and sequenced by next generation sequencing (NGS) using the Illumina MiSeq platform. The ability of the four sequence-based diversity measures to correctly identify recent HIV infections was evaluated using the frequency distribution curves, median and interquartile range and area under the curve (AUC) of the receiver operating characteristic (ROC). Comparing the median and interquartile range and evaluating the frequency distribution curves associated with the 4 sequence-based diversity measures, we observed that the percent diversity, number of haplotypes and Shannon entropy demonstrated significant potential to discriminate recent from chronic infections (p<0.0001). Using the AUC of ROC analysis, only the Shannon entropy measure within three HIV-1 env segments could accurately identify recent infections at a satisfactory level. The env segments were gp120 C2_1 (AUC = 0.806), gp120 C2_3 (AUC = 0.805) and gp120 V3 (AUC = 0.812). Our results clearly indicate that the Shannon entropy measure represents a useful tool for predicting HIV-1 infection recency.

Field-deployable, quantitative, rapid identification of active Ebola virus infection in unprocessed blood

The West African Ebola virus outbreak underlined the importance of delivering mass diagnostic capability outside the clinical or primary care setting in effectively containing public health emergencies caused by infectious disease. Yet, to date, there is no solution for reliably deploying at the point of need the gold standard diagnostic method, real time quantitative reverse transcription polymerase chain reaction (RT-qPCR), in a laboratory infrastructure-free manner. In this proof of principle work, we demonstrate direct performance of RT-qPCR on fresh blood using far-red fluorophores to resolve fluorogenic signal inhibition and controlled, rapid freeze/thawing to achieve viral genome extraction in a single reaction chamber assay. The resulting process is entirely free of manual or automated sample pre-processing, requires no microfluidics or magnetic/mechanical sample handling and thus utilizes low cost consumables. This enables a fast, laboratory infrastructure-free, minimal risk and simple standard operating procedure suited to frontline, field use. Developing this novel approach on recombinant bacteriophage and recombinant human immunodeficiency virus (HIV; Lentivirus), we demonstrate clinical utility in symptomatic EBOV patient screening using live, infectious Filoviruses and surrogate patient samples. Moreover, we evidence assay co-linearity independent of viral particle structure that may enable viral load quantification through pre-calibration, with no loss of specificity across an 8 log-linear maximum dynamic range. The resulting quantitative rapid identification (QuRapID) molecular diagnostic platform, openly accessible for assay development, meets the requirements of resource-limited countries and provides a fast response solution for mass public health screening against emerging biosecurity threats.

Moving towards a reliable HIV incidence test - current status, resources available, future directions and challenges ahead

In 2011 the Incidence Assay Critical Path Working Group reviewed the current state of HIV incidence assays and helped to determine a critical path to the introduction of an HIV incidence assay. At that time the Consortium for Evaluation and Performance of HIV Incidence Assays (CEPHIA) was formed to spur progress and raise standards among assay developers, scientists and laboratories involved in HIV incidence measurement and to structure and conduct a direct independent comparative evaluation of the performance of 10 existing HIV incidence assays, to be considered singly and in combinations as recent infection test algorithms. In this paper we report on a new framework for HIV incidence assay evaluation that has emerged from this effort over the past 5 years, which includes a preliminary target product profile for an incidence assay, a consensus around key performance metrics along with analytical tools and deployment of a standardized approach for incidence assay evaluation. The specimen panels for this evaluation have been collected in large volumes, characterized using a novel approach for infection dating rules and assembled into panels designed to assess the impact of important sources of measurement error with incidence assays such as viral subtype, elite host control of viraemia and antiretroviral treatment. We present the specific rationale for several of these innovations, and discuss important resources for assay developers and researchers that have recently become available. Finally, we summarize the key remaining steps on the path to development and implementation of reliable assays for monitoring HIV incidence at a population level.

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.

A Generalized Entropy Measure of Within-Host Viral Diversity for Identifying Recent HIV-1 Infections

There is a need for incidence assays that accurately estimate HIV incidence based on cross-sectional specimens. Viral diversity-based assays have shown promises but are not particularly accurate. We hypothesize that certain viral genetic regions are more predictive of recent infection than others and aim to improve assay accuracy by using classification algorithms that focus on highly informative regions (HIRs).We analyzed HIV gag sequences from a cohort in Botswana. Forty-two subjects newly infected by HIV-1 Subtype C were followed through 500 days post-seroconversion. Using sliding window analysis, we screened for genetic regions within gag that best differentiate recent versus chronic infections. We used both nonparametric and parametric approaches to evaluate the discriminatory abilities of sequence regions. Segmented Shannon Entropy measures of HIRs were aggregated to develop generalized entropy measures to improve prediction of recency. Using logistic regression as the basis for our classification algorithm, we evaluated the predictive power of these novel biomarkers and compared them with recently reported viral diversity measures using area under the curve (AUC) analysis.Change of diversity over time varied across different sequence regions within gag. We identified the top 50% of the most informative regions by both nonparametric and parametric approaches. In both cases, HIRs were in more variable regions of gag and less likely in the p24 coding region. Entropy measures based on HIRs outperformed previously reported viral-diversity-based biomarkers. These methods are better suited for population-level estimation of HIV recency.The patterns of diversification of certain regions within the gag gene are more predictive of recency of infection than others. We expect this result to apply in other HIV genetic regions as well. Focusing on these informative regions, our generalized entropy measure of viral diversity demonstrates the potential for improving accuracy when identifying recent HIV-1 infections.

How can we better identify early HIV infections?

PURPOSE OF REVIEW

Detection of early HIV infections (EHIs), including acute HIV infection (AHI), is important for individual health, prevention of HIV transmission, and measurement of HIV incidence. We describe markers of EHI, diagnostic strategies for detecting these markers, and ways to incorporate these strategies into diagnostic and HIV incidence algorithms.

RECENT FINDINGS

For individual diagnosis in the USA and Europe, laboratory-based diagnostic algorithms increasingly incorporate fourth-generation HIV antigen tests, allowing for earlier detection. In some sub-Saharan African settings, symptom-based screening is being explored to identify subsets of persons at high risk for AHI. Point-of-care diagnostics designed for AHI detection are in the pipeline and, if validated, represent an opportunity for real-time AHI diagnosis. At the population level, multiassay algorithms are promising new strategies for estimating HIV incidence on the basis of several assays applied to cross-sectional samples. These algorithms can be developed to optimize performance, in addition to cost and logistical considerations.

SUMMARY

There are important recent advances in detection of EHIs at the individual and population levels. Applying optimal combinations of tests in diagnostic and HIV incidence algorithms is urgently needed to support the multiple goals derived from enhanced detection and discrimination of EHIs.

Rapid and specific detection of porcine parvovirus using real-time PCR and high resolution melting (HRM) analysis

Background

Porcine parvovirus (PPV) is the important causative agent for infectious infertility, which is a fairly tough virus that multiplies normally in the intestine of pigs without causing clinical signs in the world.

Results

We developed an assay integrating real-time PCR and high resolution melting (HRM) analysis for the detection of PPV. Primers targeting the VP gene were highly specific, as evidenced by the negative amplification of closely related viruses, such as porcine circovirus 2 (PCV2), porcine reproductive and respiratory syndrome virus (PRRSV), pseudorabies virus (PRV), classical swine fever virus (CSFV), or Japanese encephalitis virus (JEV). The performance of unlabeled real time PCR was compared to TaqMan real time PCR, and the detection limits of the two methods were nearly equal. Moreover, there was good correlation between Cp and diluted genomic DNA when tested with the two methods. The assay has the accuracy of 100% in reference to labeled real time PCR, when it was tested on 45 clinical samples.

Conclusions

The present study demonstrated that the established assay integrating real-time PCR and HRM is relatively cost-effective and more stable, which provides an alternative tool for rapid, simple, specific and sensitive detection of PPV.

Rapid detection and differentiation of Clonorchis sinensis and Opisthorchis viverrini using real-time PCR and high resolution melting analysis

Clonorchis sinensis and Opisthorchis viverrini are both important fish-borne pathogens, causing serious public health problem in Asia. The present study developed an assay integrating real-time PCR and high resolution melting (HRM) analysis for the specific detection and rapid identification of C. sinensis and O. viverrini. Primers targeting COX1 gene were highly specific for these liver flukes, as evidenced by the negative amplification of closely related trematodes. Assays using genomic DNA extracted from the two flukes yielded specific amplification and their identity was confirmed by sequencing, having the accuracy of 100% in reference to conventional methods. The assay was proved to be highly sensitive with a detection limit below 1 pg of purified genomic DNA, 5 EPG, or 1 metacercaria of C. sinensis. Moreover, C. sinensis and O. viverrini were able to be differentiated by their HRM profiles. The method can reduce labor of microscopic examination and the contamination of agarose electrophoresis. Moreover, it can differentiate these two flukes which are difficult to be distinguished using other methods. The established method provides an alternative tool for rapid, simple, and duplex detection of C. sinensis and O. viverrini.

In silico single strand melting curve: a new approach to identify nucleic acid polymorphisms in Totiviridae

Background

The PCR technique and its variations have been increasingly used in the clinical laboratory and recent advances in this field generated new higher resolution techniques based on nucleic acid denaturation dynamics. The principle of these new molecular tools is based on the comparison of melting profiles, after denaturation of a DNA double strand. Until now, the secondary structure of single-stranded nucleic acids has not been exploited to develop identification systems based on PCR. To test the potential of single-strand RNA denaturation as a new alternative to detect specific nucleic acid variations, sequences from viruses of the Totiviridae family were compared using a new in silico melting curve approach. This family comprises double-stranded RNA virus, with a genome constituted by two ORFs, ORF1 and ORF2, which encodes the capsid/RNA binding proteins and an RNA-dependent RNA polymerase (RdRp), respectively.

Results

A phylogenetic tree based on RdRp amino acid sequences was constructed, and eight monophyletic groups were defined. Alignments of RdRp RNA sequences from each group were screened to identify RNA regions with conserved secondary structure. One region in the second half of ORF2 was identified and individually modeled using the RNAfold tool. Afterwards, each DNA or RNA sequence was denatured in silico using the softwares MELTSIM and RNAheat that generate melting curves considering the denaturation of a double stranded DNA and single stranded RNA, respectively. The same groups identified in the RdRp phylogenetic tree were retrieved by a clustering analysis of the melting curves data obtained from RNAheat. Moreover, the same approach was used to successfully discriminate different variants of Trichomonas vaginalis virus, which was not possible by the visual comparison of the double stranded melting curves generated by MELTSIM.

Conclusion

In silico analysis indicate that ssRNA melting curves are more informative than dsDNA melting curves. Furthermore, conserved RNA structures may be determined from analysis of individuals that are phylogenetically related, and these regions may be used to support the reconstitution of their phylogenetic groups. These findings are a robust basis for the development of in vitro systems to ssRNA melting curves detection.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2105-15-243) contains supplementary material, which is available to authorized users.

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.

Rapid detection and simultaneous genotyping of Cronobacter spp. (formerly Enterobacter sakazakii) in powdered infant formula using real-time PCR and high resolution melting (HRM) analysis

Cronobacter spp. is an emerging pathogen that causes meningitis, sepsis, bacteremia, and necrotizing enterocolitis in neonates and children. The present study developed an assay integrating real-time PCR and high resolution melting (HRM) analysis targeting the OmpA gene for the specific detection and rapid identification of Cronobacter spp. (formerly Enterobacter sakazakii) in powdered infant formula. Eleven Cronobacter field isolates and 25 reference strains were examined using one pair of primers, having the accuracy of 100% in reference to conventional methods. The assay was proved to be highly sensitive with a detection limit of 10² CFU/ml without pre-enrichment, and highly concordant (100%) when compared with ISO-IDF 22964 in 89 actual samples. The method performed for Cronobacter spp. detection was less than 24 h, drastically shortened, compared to several days using standard culturing method, it is probe-free and reduces a risk of PCR carryover. Moreover, all Cronobacter strains examined in this study were genotyped into two species according to their HRM profiles. The established method should provide a molecular tool for direct detection and simultaneous genotyping of Cronobacter spp. in powdered infant formula.

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.