Dual HIV Infection Uncommon in Patients on Antiretroviral Therapy in a Region with High HIV Prevalence

Abstract

Dual HIV infection has been found in regions with high HIV prevalence and in populations infected with diverse strains of HIV. The prevalence of dual infection in KwaZulu-Natal (KZN), where there is a high prevalence of HIV and an influx of immigrants who may be infected with different HIV subtypes, is unknown. The aim of this study was to determine the prevalence of dual infection in KZN. Eighty-three samples were obtained from chronically infected patients on ARV treatment from sites throughout KZN. Subtyping of the samples was performed using the heteroduplex mobility assay (HMA). Twelve samples that had possible dual infection by HMA were cloned and sequenced. Phylogenetic analysis showed that there was no dual infection in these samples. Contrary to a previous study, we did not find dual infection in this region. The patients in our study may be different from those in the previous study in terms of transmission risk factors, treatment, and stage of infection (acute vs. chronic). This study may have important implications for vaccine development and for the pathogenesis and treatment of dual HIV infection.

Introduction

H IV is one of the fastest evolving organisms due to its rapid replication rate, high mutation rate, and frequent recombination. It has a viral generation time of 2.5 days with a production of ∼10¹⁰–10¹² new virions each day.¹ The high mutation rate is due to the unique properties of the reverse transcriptase enzyme, which is largely responsible for the sequence diversity of the retrovirus family of viruses.² The characteristic features of this enzyme are its template switching ability during reverse transcription³ and the lack of an exonucleolytic proofreading mechanism.⁴ The genetic diversity of HIV is evident through the different genetic forms of the virus that exist.

HIV is divided into two species: HIV-1 and HIV-2.⁵ Three HIV-1 groups exist, i.e., groups M, N, and O. Group M subtypes A, B, C, D, F, G, H, J, and K make a large contribution to the number infections caused in the pandemic.⁶ Recombination of different genetic forms of HIV has resulted in circulating recombinant forms (CRFs) of the virus. Unique recombinant forms (URFs) are thought to arise due to secondary recombination of a CRF.⁷ URFs have been reported throughout the world.^7
–9 A high prevalence of URFs has been found in Kenya, Argentina, China, and Nigeria.^8,10,11 The frequent finding of CRFs and URFs reflects the occurrence of dual infections.

Dual HIV infection is the presence of more than one HIV genetic sequence, i.e., groups, subtypes, intrasubtypes, and/or strains within an individual.¹² Dual HIV infection is a prerequisite for circulating recombinant forms of virus.¹³ It suggests that an individual may have had exposure to more than one HIV type at one or more time points.

Dual infection has been found in areas where multiple HIV variants circulate and in regions with high HIV prevalence rates. For instance, coinfections of viruses belonging to distinct HIV-1 subtypes have been found in Tanzania, Kenya, and Brazil.^14
–16 Subtype B intrasubtype and subtype C intrasubtype infections have also been reported, and are of major concern.¹² A study in South Africa using a high-risk cohort of sex workers documented 19% of intrasubtype C dual infection.¹⁷

It is important to document the prevalence of dual infection at the population level since it affects disease progression^12,17 and complicates the management of HIV infection.^18,19 Regular surveillance of dual infections is essential, especially in areas that may have multiple subtypes circulating and in populations that may have a high percentage of individuals who may be resistant to antiretrovirals (ARVs). Monitoring the frequency of dual infections is important since it is an indicator of the appearance of new recombinant viruses (CRFs and URFs).

There are limited data on the epidemiology of dual infection in South Africa. A study on dual infection in a high-risk HIV cohort that had multiple exposures to HIV found 19% of dual infections in the study population.¹⁷ South Africa has a high prevalence of HIV²⁰ and potentially high exposure to diverse HIV variants through immigrants from sub-Saharan Africa.²¹ KwaZulu-Natal (KZN) is at the epicenter of the HIV epidemic, with the highest prevalence of HIV nationally. These factors suggest that the prevalence of dual infection could be high in this region. The present study aims to determine the prevalence of dual infection in the ARV Rollout program in KZN. In this study, we analyzed the env V3 loop of the HIV genome to assess the subtype distribution and prevalence of dual infection in the study population. A Google Scholar and Pubmed search was performed in the English language and did not find any studies documenting the impact of dual infection on treatment outcomes. A further aim of this study was therefore to determine the impact of dual infection on treatment outcomes.

Materials and Methods

This study was given full ethical approval by the University of KwaZulu-Natal, Biomedical Research Ethics Committee, Ref.: H026/05.

Sample population

The sample size required for this study was calculated to be 83 (STATA™ 9 StataCorp, College Station, TX). This sample size calculation was based on the population size and prevalence of HIV in KZN (28%) and the prevalence of dual infection reported by Gottlieb et al. (7.8%).^12,20 The samples were randomly selected using random numbers provided by a statistician. Samples were collected over a 4 month period.

To investigate the impact of dual infection on treatment outcome, samples were from patients on the ARV Rollout program. All patients had HIV infection for at least 6 months and were not in the acute phase of HIV infection. These samples were sent from various ARV sites in KZN to the Department of Virology, Inkosi Albert Luthuli Central Hospital, Durban for routine 6 monthly CD4⁺ T cell testing. The sample population consisted of male and female patients, aged 2–55 years (8.4% children and 91.6% adults). All patients had a CD4⁺ T cell count below 200 cells/mm³ and/or were WHO stage IV.²² The mean viral load of the population group was 70,350 copies/ml. Sixty-three percent of patients had undetectable viral loads.

Sample collection

Eighty-three whole blood samples submitted for routine CD4⁺ T cell testing from the KZN ARV Rollout program were identified for use in this study. Samples were collected from March to June 2005. Routine testing was performed and residual whole blood, which would otherwise have been discarded, was used anonymously for this study. A minimum of 500 μl whole blood was required. Samples with less than the minimum volume were excluded from the study. The following information was obtained from the laboratory database: viral load and CD4⁺ T cell results, the patient's age and gender, and the name of the ARV site attended. The data were recorded anonymously and no patient identifiers were used.

Polymerase chain reaction

White blood cells were isolated from whole blood using Blood Wash (Roche). DNA was extracted using the Biomerieux HIV-1 extraction method.²³ A nested polymerase chain reaction (PCR) was conducted using first round primers ED5 and ED12, followed by second round primers ED31 and ED33. Amplification conditions were as follows: 3 cycles of 94°C for 1 min, 55°C for 1 min, 72°C for 1 min; 32 cycles of 94°C for 15 s, 55°C for 45 s, 72°C for 1 min; final extension at 72°C for 5 min. The PCR product of 460 bp was detected on a 1% agarose gel using ultraviolet transillumination (Whatman Biometra, Goettingen). PCR products were purified using the QIAquick PCR Purification Kit (Qiagen, Hilden). Amplicons were either used for the heteroduplex mobility assay or stored at −20°C for later use.

Heteroduplex mobility assay

The heteroduplex mobility assay HIV-1 env kit was provided by the NIH. Reference strains A, B, C, D, E, F, G, H, and J were amplified using second round primers ED31 and ED33. The envelope region of the genome has been used in previous studies of dual infection in this region and was therefore chosen for subtype analysis in this study.^12,17 Heteroduplexes were formed by mixing 5 μl of reference strain, with 5 μl of sample and 1.1 μl annealing buffer in 0.2-ml tubes. The tubes were heated at 94°C for 2 min and immediately cooled on ice: rapid cooling facilitates the formation of stable heteroduplexes between divergent strains. The heteroduplex reaction was mixed with 3 μl of loading dye and carefully loaded onto the 5% nondenaturing polyacrylamide gel while the sandwich was on the caster. A molecular weight marker (Roche, Basel, Switzerland) was loaded simultaneously to serve as a reference marker. The gel was electrophoresed at a constant voltage of 250 V for 3 h for the env products. The gel tank was placed in a water bath with ice packs to prevent the tank from heating and thus melting the gel. The gel was removed from the apparatus and placed in an ethidium bromide (Merck, Germany) solution for 10 min and destained with distilled water. It was then viewed under ultraviolet light using the Biometra GelDocAnalyse version 1.0 (Whatman Biometra, Goettingen). The electrophoretic conditions were extremely important for heteroduplex stability. Therefore optimization of the gel units, plates, acrylamide concentration, buffer, and standard voltage/current conditions was carefully adjusted for this experiment.

Clonal sequencing

All samples analyzed by heteroduplex mobility assay (HMA) that showed more than one heteroduplex migrating to the furthest position on the gel, or had distinct slow migrating heteroduplexes or smears, were cloned and then sequenced. Taq polymerase-amplified PCR products were used with a TOPO TA Cloning Kit (Invitrogen, Carlsbad, CA). Clones were screened by PCR. PCR-positive clones were sequenced.

PCR products were purified using the QIAquick PCR Purification Kit (Qiagen, Hilden). The concentrations of the PCR products were determined by comparison of the PCR products to a mass ladder (Invitrogen, Carlsbad, CA). Sequencing was performed using the ABI Prism BigDye Terminator v3.1 ready reaction Cycle Sequencing Kit (ABl, United Kingdom).

Sequence analysis

The sequences were aligned with CLUSTAL W²⁴ and manually edited with the Genetic Data Environment (GDE 2.2) program.²⁵ Subtype reference strains were obtained from the Los Alamos subtype database (http://www.hiv.lanl.gov/content/sequence/NEWALIGN/align.html) and consensus sequences for each patient were generated using VESPA (viral epidemiology signature pattern analysis). Phylogenetic trees were generated in PAUP*4.0²⁶ using the TVM + G model of substitution as determined by MODELTEST 3.7.²⁷ Trees were rooted with a homologous region of HIV-1 group O (AY489739). All trees were bootstrapped with 1000 sampling replicates. Trees were viewed with FigTree.²⁸

Results

Population demographics

Samples were received from ARV sites throughout KZN, i.e., Christ the King Hospital, G.J. Crookes Hospital, King Edward Hospital, Mahatma Ghandi Memorial Hospital, Prince Mshiyeni Memorial Hospital, and the R.K. Khan Hospital. All patients were on the ARV Rollout program. The mean age of the population group was 32 years, ranging from 2 to 55 years. There were 54 females, 26 males, and 3 patients with unknown gender. The mean age in males was 33 years while the mean age in females was 31 years. There were 91.6% (76/83) adults in this study.

CD4⁺ T cell and viral load results

The Biomerieux HIV-1 Viral Load kit was used to quantify the samples for diagnostic purposes. The viral loads in the sample population measured at 6 months posttreatment ranged from undetectable to 590,000 IU/ml. The median viral load was 5900 IU/ml and the average viral load was 70,350 IU/ml. Fifty-two samples had undetectable viral loads while 31 samples had detectable viral loads. The difference in the proportion of inconclusive HMA between patients with detectable viral loads [2/31 (6.5%) inconclusive HMAs] and undetectable viral loads [10/52 (19%) inconclusive HMAs] was not significant (p = 0.195, Fisher's exact test).

HIV-1 genotyping

Subtypes were determined on HMA by the heteroduplex that migrates to the furthest position in the gel. Samples in which a single subtype could not be unequivocally determined required clonal sequencing to determine the subtype or the presence of dual infection or recombination. Such indeterminate results occurred when there were distinct slow migrating heteroduplexes or smears^12,17 or when two heteroduplexes migrated to the furthest equivalent position on a polyacrylamide gel. In this study 12 samples had inconclusive HMA results and were therefore cloned and sequenced. For each of the 12 samples, 20–40 clones were screened by PCR. Those that were positive were sequenced. The phylogenetic tree in Fig. 1 is representative of the consensus sequences of these samples.

FIG. 1.

Maximum likelihood subtype tree of consensus sequences for each patient. The tree was generated in PAUP*4.0 using the TVM + G substitution model. Only bootstrap values (1000 replicates) > 75 are shown. The scale bar is shown at the bottom of the figure. Consensus sequences of all samples clustered with the subtype C reference sequences.

The phylogenetic criteria from Gottlieb et al. ¹² were used to define dual HIV-1 infection: “(1) HIV sequences from a patient were required to cluster into two distinct monophyletic clades (excluding recombinants) without known epidemiologic linkage; (2) these clades were required to be no closer to each other, in a phylogenetic tree, than multiple random unlinked sequences from the HIV-1 database; and (3) the mean pairwise nucleotide distance between the two distinct clades was required to be within the range of pairwise nucleotide distances generated from randomly selected unlinked sequences in the HIV-1 database.”¹² None of the 12 samples matched these criteria.

Discussion

The aim of this study was to determine the prevalence of dual infection in KZN province of South Africa. The prevalence of dual infection in this population was expected to be high based on the high prevalence of HIV in this region, the high levels of immigrants from sub-Saharan Africa into this province, and a previous study that demonstrated a high prevalence of dual infection in a selected cohort within KZN.^12,17 This study, however, did not find a high prevalence of dual infection in the study population. The factors that may have led to this unexpected finding have important implications.

According to the inclusion criteria in this study, all patients have been HIV infected for at least 6 months and were not in the acute phase of HIV infection. Dual infection found during acute infection, as described in previous studies,^12,17 may subsequently be cleared by the immune system during chronic infection in patients in this study.²⁹ Alternatively, the immune system may be able to prevent infection by a second subtype following infection by one subtype.²⁹

This has important implications for vaccine design. Dual infection implies that infection with one particular subtype of HIV is insufficient to prevent infection by viruses belonging to another subtype. A high prevalence of dual infection would pose a significant challenge to vaccine development since it raises the possibility that a subtype-specific vaccine may not necessarily prevent infections by subtypes not included in the vaccine. Conversely, the absence of dual infection, as this study has shown, indicates that the immune system may either clear or prevent infection with a second subtype and hence subtype-specific vaccines may still provide protection against all subtypes.

The patients in this study were on therapy, while patients in previous studies were not.^12,14,17 It is possible that ARV therapy may suppress the viral load in a dually infected patient so that the “second” virus subtype is below the level of detection or amplification by PCR. However, the difference in the proportion of inconclusive HMA between patients with detectable and undetectable viral loads in this study was not significant (p = 0.1).

The impact of dual infection on treatment outcomes could not be determined in this study. This may be an area of further research in patients on ARVs in areas where dual infection is highly prevalent. A prospective study is also necessary to study the effect of HAART in dually infected patients, specifically to determine whether the less dominant subtype in dual infection is “cleared” with treatment. If this is the case, then HAART would be indicated in dually infected patients independent of CD4⁺ T cell count and viral load since treatment may prevent the origin and spread of recombinant viruses.

The lack of dual infection in this study could also be attributed to several technical factors. HMA may not detect dual infections if the second virus is present in low copy numbers.¹⁷ The techniques in this study were performed according to the methods used in previous studies.^12,17 However, these techniques may have certain limitations. A positive control for dual infection is not included in the HMA kit and other subtyping assays. All techniques used to detect dual infection provide qualitative results. These tests do not quantify the subtypes and subsubtypes that may exist in an individual. The use of subtyping kits targeting the gag and/or pol regions of the genome in conjunction with env HMA would have improved the detection of recombinant strains of virus in this study.

Several studies have reported high levels of dual infections in cohorts of high-risk individuals who had multiple exposures to HIV (437 exposures per year).^14,17 The lack of dual infection in our study population could be due to risk behavior that differs from such “high-risk” cohorts, although the nature of our study did not allow risk behavior to be specifically documented.

This study also determined the molecular epidemiology of HIV in KZN. All samples were typed as subtype C virus. These results are in accordance with previous data that demonstrate that subtype C has dominated the pandemic in South Africa.⁶ Globally, subtype C is the greatest contributor to the epidemic, causing 50% of infections.³⁰ The circulation of subtypes in South Africa is due to two separate epidemics. Initially the homosexual population presented with infections by subtypes B and D, which was followed by a subtype C epidemic in the heterosexual population.³¹

Subtype C infections have spread rapidly throughout the world. Viral, host, and socioeconomic factors may be related to the increase in C-type infections. Viral differences have been noted in HIV-1 group M subtypes. Subtype C is the only variant to have an extra NF-κB binding site.³² Studies have shown that the triple (NF)-κB motif confers higher promoter activity.³³ The response to the proinflammatory cytokine tumor necrosis factor-α is increased with the triple (NF)-κB configuration. This implies that subtype C may have a replication advantage in those with chronic immune activation.³⁴ Other differences between subtype C and the other HIV group M subtypes have been identified. Protease genes in subtype C viruses may have increased catalytic activity in comparison to other subtypes.³⁵ The regulatory proteins Tat and Rev are prematurely truncated and the vpu reading frame has a 15-bp insertion at the 5′ end in HIV subtype C.³⁶ The rapid spread of subtype C may be due to the use of the coreceptor CCR-5.³⁷ Further studies are required to validate these queries.

The present study was the first performed to determine the prevalence of dual infection in a population on ARV therapy. Dual infection was not detected in the study population. There are at least two explanations for this: the immune system is able to clear or prevent infection by a “second” virus or HAART suppresses the second subtype to below levels of detection by PCR. This has implications for vaccine development and antiviral dynamics, respectively.

Sequence Data

The sequence data were as follows: FJ905848, FJ905849, FJ905850, FJ905851, FJ905852, FJ905853, FJ905854, FJ905855, FJ905856, FJ905857, FJ905858, FJ905859, FJ905860, FJ905861, FJ905862, FJ905863, FJ905864, FJ905865, FJ905866, FJ905867, FJ905868, FJ905869, FJ905870, FJ905871, FJ905872, FJ905873, FJ905874, FJ905875, FJ905876, FJ905877, FJ905878, FJ905879, FJ905880, FJ905881, FJ905882, FJ905883, FJ905884, FJ905885, FJ905886, FJ905887, FJ905888, FJ905889, FJ905890, FJ905891, FJ905892, FJ905893, FJ905894, and FJ905895.

Footnotes

Acknowledgments

We thank the Medical Research Council South Africa and the National Health Laboratory Services Research Trust for funding this project.

The following reagent was obtained through the NIH AIDS Research and Reference Reagent Program, Division of AIDS, NIAID, NIH: Heteroduplex Mobility Analysis HIV-1 env Subtyping Kit from Dr. James Mullins.

Disclosure Statement

No competing financial interests exist.

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