Despite recent breakthroughs in the fight against the HIV/AIDS epidemic within South Africa, the transmission of the virus continues at alarmingly high rates. It is possible, with the use of phylogenetic methods, to uncover transmission events of HIV amongst local communities in order to identify factors that may contribute to the sustained transmission of the virus. The aim of this study was to uncover transmission events of HIV amongst the infected population of Cape Town.
Methods and Results
We analysed gag p24 and RT-pol sequences which were generated from samples spanning over 21-years with advanced phylogenetic techniques. We identified two transmission clusters over a 21-year period amongst randomly sampled patients from Cape Town and the surrounding areas. We also estimated the origin of each of the identified transmission clusters with the oldest cluster dating back, on average, 30 years and the youngest dating back roughly 20 years.
Discussion and Conclusion
These transmission clusters represent the first identified transmission events among the heterosexual population in Cape Town. By increasing the number of randomly sampled specimens within a dataset over time, it is possible to start to uncover transmission events of HIV amongst local communities in generalized epidemics. This information can be used to produce targeted interventions to decrease transmission of HIV in Africa.
HIV-1 drug resistance has the potential to seriously compromise the effectiveness and impact of antiretroviral therapy (ART). As ART programs in sub-Saharan Africa continue to expand, individuals on ART should be closely monitored for the emergence of drug resistance. Surveillance of transmitted drug resistance to track transmission of viral strains already resistant to ART is also critical. Unfortunately, drug resistance testing is still not readily accessible in resource limited settings, because genotyping is expensive and requires sophisticated laboratory and data management infrastructure. An open access genotypic drug resistance monitoring method to manage individuals and assess transmitted drug resistance is described. The method uses free open source software for the interpretation of drug resistance patterns and the generation of individual patient reports. The genotyping protocol has an amplification rate of greater than 95% for plasma samples with a viral load >1,000 HIV-1 RNA copies/ml. The sensitivity decreases significantly for viral loads <1,000 HIV-1 RNA copies/ml. The method described here was validated against a method of HIV-1 drug resistance testing approved by the United States Food and Drug Administration (FDA), the Viroseq genotyping method. Limitations of the method described here include the fact that it is not automated and that it also failed to amplify the circulating recombinant form CRF02_AG from a validation panel of samples, although it amplified subtypes A and B from the same panel.
Medicine; Issue 85; Biomedical Technology; HIV-1; HIV Infections; Viremia; Nucleic Acids; genetics; antiretroviral therapy; drug resistance; genotyping; affordable
The recent HIV-1 vaccine failures highlight the need to better understand virus-host interactions. One key question is why CD8+ T cell responses to two HIV-Gag regions are uniquely associated with delayed disease progression only in patients expressing a few rare HLA class I variants when these regions encode epitopes presented by ∼30 more common HLA variants. By combining epitope processing and computational analyses of the two HIV subtypes responsible for ∼60% of worldwide infections, we identified a hitherto unrecognized adaptation to the antigen-processing machinery through substitutions at subtype-specific motifs. Multiple HLA variants presenting epitopes situated next to a given subtype-specific motif drive selection at this subtype-specific position, and epitope abundances correlate inversely with the HLA frequency distribution in affected populations. This adaptation reflects the sum of intrapatient adaptations, is predictable, facilitates viral subtype diversification, and increases global HIV diversity. Because low epitope abundance is associated with infrequent and weak T cell responses, this most likely results in both population-level immune evasion and inadequate responses in most people vaccinated with natural HIV-1 sequence constructs. Our results suggest that artificial sequence modifications at subtype-specific positions in vitro could refocus and reverse the poor immunogenicity of HIV proteins.
•HLA class I variants drive selection pressures on Gag to limit epitope production•The strength of the selective pressure is positively correlated to HLA frequencies•HIV adaptation to limit epitope production occurs at subtype-specific HIV motifs•HIV adapts in a predictable way to HLA frequencies in newly infected populations
CD8+ T cell responses against HIV-1 effectively delay disease progression in a minority of patients with relatively rare HLA variants but are ineffective in most. Here, Tenzer et al. identify fundamental HIV-1 adaptation to the conserved human antigen-processing machinery that feeds epitopes to HLA. This adaptation occurs at subtype-specific motifs, facilitates subtype diversification, is predictable, and results in CD8 epitope abundances that correlate inversely with the HLA allele frequencies in affected populations. Thus, HIV vaccine immunogenicity might be increased by unnatural substitutions at subtype-specific motifs.
Few studies have examined immune activation profiles in patients with advanced HIV-1 subtype C infection or assessed their potential to predict responsiveness to HAART. BioPlex, ELISA, and nephelometric procedures were used to measure plasma levels of inflammatory biomarkers in HIV-1 subtype C-infected patients sampled before and after 6 months of successful HAART (n = 20); in patients failing HAART (n = 30); and in uninfected controls (n = 8). Prior to HAART, CXCL9, CXCL10, β2M, sTNF-R1, TGF-β1, IFN-γ, IL-6, TNF, and sCD14 were significantly elevated in HIV-1-infected patients compared to controls (P < 0.01). All of these markers, with the exception of sTNF-R1, were also elevated in patients failing HAART (P < 0.05). The persistently elevated levels of CXCL9, CXCL10, and β2M in patients failing therapy in the setting of a marked reduction in these markers in patients on successful HAART suggest that they may be useful not only to monitor immune activation during HAART, but also to distinguish between good and poor responders. In the case of sCD14 and TGF-β1, the levels of these biomarkers remained persistently elevated despite HAART-induced virological suppression, a finding that is consistent with ongoing monocyte-macrophage activation, underscoring a potential role for adjuvant anti-inflammatory therapy.
Tremendous progress has been made with the scale-up of antiretroviral therapy in Africa, with an estimated seven million people now receiving antiretroviral therapy in the region. The long-term success of antiretroviral therapy programs depends on appropriate strategies to deal with potential threats, one of which is the emergence and spread of antiretroviral drug resistance. Whilst public health surveillance forms the mainstay of the World Health Organization approach to antiretroviral drug resistance, there is likely to be increasing demand for access to drug resistance testing as programs mature and as HIV clinical management becomes more complex. African-owned research initiatives have helped to develop affordable resistance testing appropriate for use in the region, and have developed delivery models for resistance testing at different levels of the public health system. Some upper-middle-income countries such as Botswana and South Africa have introduced drug resistance testing for selected patient groups to guide clinical management. The scale-up of resistance testing will require substantial expansion of clinical and laboratory capacity in the region, but the expertise and resources exist in Africa to support this. The long-term population health impact and cost-effectiveness of resistance testing in the region will also require further investigation.
HIV-1; Drug resistance; Antiretroviral therapy; Treatment failure
South Africa has the largest worldwide HIV/AIDS population with 5.6 million people infected and at least 2 million people on antiretroviral therapy. The majority of these infections are caused by HIV-1 subtype C. Using genotyping methods we characterized HIV-1 subtypes of the gag p24 and pol PR and RT fragments, from a cohort of female participants in the Western Cape Province, South Africa. These participants were recruited as part of a study to assess the combined brain and behavioural effects of HIV and early childhood trauma. The partial HIV-1 gag and pol fragments of 84 participants were amplified by PCR and sequenced. Different online tools and manual phylogenetic analysis were used for HIV-1 subtyping. Online tools included: REGA HIV Subtyping tool version 3; Recombinant Identification Program (RIP); Context-based Modeling for Expeditious Typing (COMET); jumping profile Hidden Markov Models (jpHMM) webserver; and subtype classification using evolutionary algorithms (SCUEAL). HIV-1 subtype C predominates within the cohort with a prevalence of 93.8%. We also show, for the first time, the presence of circulating BC strains in at least 4.6% of our study cohort. In addition, we detected transmitted resistance associated mutations in 4.6% of analysed sequences. With tourism and migration rates to South Africa currently very high, we are detecting more and more HIV-1 URFs within our study populations. It is stil unclear what role these unique strains will play in terms of long term antiretroviral treatment and what challenges they will pose to vaccine development. Nevertheless, it remains vitally important to monitor the HIV-1 diversity in South Africa and worldwide as the face of the epidemic is continually changing.
Antiretroviral drug resistance is becoming increasingly common with the expansion of human immunodeficiency virus (HIV) treatment programmes in high prevalence settings. Genotypic resistance testing could have benefit in guiding individual-level treatment decisions but successful models for delivering resistance testing in low- and middle-income countries have not been reported.
An HIV Treatment Failure Clinic model was implemented within a large primary health care HIV treatment programme in northern KwaZulu-Natal, South Africa. Genotypic resistance testing was offered to adults (≥16 years) with virological failure on first-line antiretroviral therapy (one viral load >1000 copies/ml after at least 12 months on a standard first-line regimen). A genotypic resistance test report was generated with treatment recommendations from a specialist HIV clinician and sent to medical officers at the clinics who were responsible for patient management. A quantitative process evaluation was conducted to determine how the model was implemented and to provide feedback regarding barriers and challenges to delivery.
A total of 508 specimens were submitted for genotyping between 8 April 2011 and 31 January 2013; in 438 cases (86.2%) a complete genotype report with recommendations from the specialist clinician was sent to the medical officer. The median turnaround time from specimen collection to receipt of final report was 18 days (interquartile range (IQR) 13–29). In 114 (26.0%) cases the recommended treatment differed from what would be given in the absence of drug resistance testing. In the majority of cases (n = 315, 71.9%), the subsequent treatment prescribed was in line with the recommendations of the report.
Genotypic resistance testing was successfully implemented in this large primary health care HIV programme and the system functioned well enough for the results to influence clinical management decisions in real time. Further research will explore the impact and cost-effectiveness of different implementation models in different settings.
HIV-1; Drug resistance; Anti-retroviral agents; Primary health care; Treatment failure; Process assessment (health care); Capacity building
Better understanding of drug resistance patterns in HIV-infected children on antiretroviral therapy (ART) is required to inform public health policies in high prevalence settings. The aim of this study was to characterise the acquired drug resistance in HIV-infected children failing first-line ART in a decentralised rural HIV programme.
Plasma samples were collected from 101 paediatric patients (≤15 yrs of age) identified as failing ART. RNA was extracted from the plasma, reverse transcribed and a 1.3 kb region of the pol gene was amplified and sequenced using Sanger sequencing protocols. Sequences were edited in Geneious and drug resistance mutations were identified using the RegaDB and the Stanford resistance algorithms. The prevalence and frequency of mutations were analysed together with selected clinical and demographic data in STATA v11.
A total of 101 children were enrolled and 89 (88%) were successfully genotyped; 73 on a non-nucleoside reverse-transcriptase inhibitor (NNRTI)-based regimen and 16 on a protease inhibitor (PI)-based regimen at the time of genotyping. The majority of patients on an NNRTI regimen (80%) had both nucleoside reverse-transcriptase inhibitor (NRTI) and NNRTI resistance mutations. M184V and K103N were the most common mutations amongst children on NNRTI-based and M184V among children on PI-based regimens. 30.1% had one or more thymidine analogue mutation (TAM) and 6% had ≥3 TAMs. Only one child on a PI-based regimen harboured a major PI resistance mutation.
Whilst the patterns of resistance were largely predictable, the few complex resistance patterns seen with NNRTI-based regimens and the absence of major PI mutations in children failing PI-based regimens suggest the need for wider access to genotypic resistance testing in this setting.
Virological failure (VF) has been identified as the earliest, most predictive determinant of HIV-1 antiretroviral treatment (ART) failure. Due to the high cost and complexity of virological monitoring, VF assays are rarely performed in resource-limited settings (RLS). Rather, ART failure is determined by clinical monitoring and to a large extent immunological monitoring. This paper describes the development and evaluation of a low-cost, dried blood spot (DBS)-compatible qualitative assay to determine VF, in accordance with current WHO guideline recommendations for therapy switching in RLS. The assay described here is an internally controlled qualitative real-time PCR targeting the conserved long terminal repeat domain of HIV-1. This assay was applied to HIV-1 subtypes A to H and further evaluated on HIV-1 clinical plasma samples from South Africa (n = 191) and Tanzania (n = 42). Field evaluation was performed in Uganda using local clinical plasma samples (n = 176). Furthermore, assay performance was evaluated for DBS. This assay is able to identify VF for all major HIV-1 group M subtypes with equal specificity and has a lower detection limit of 1.00E+03 copies/ml for plasma samples and 5.00E+03 copies/ml for DBS. Comparative testing yielded accurate VF determination for therapy switching in 89% to 96% of samples compared to gold standards. The assay is robust and flexible, allowing for “open platform” applications and producing results comparable to those of commercial assays. Assay design enables application in laboratories that can accommodate real-time PCR equipment, allowing decentralization of testing to some extent. Compatibility with DBS extends access of sampling and thus access to this test to remote settings.
The purpose of this study was to investigate the balance between transfer ribonucleic acid (tRNA) supply and demand in retrovirus-infected cells, seeking the best targets for antiretroviral therapy based on the hypothetical tRNA Inhibition Therapy (TRIT). Codon usage and tRNA gene data were retrieved from public databases. Based on logistic principles, a therapeutic score (T-score) was calculated for all sense codons, in each retrovirus-host system. Codons that are critical for viral protein translation, but not as critical for the host, have the highest T-score values. Theoretically, inactivating the cognate tRNA species should imply a severe reduction of the elongation rate during viral mRNA translation. We developed a method to predict tRNA species critical for retroviral protein synthesis. Four of the best TRIT targets in HIV-1 and HIV-2 encode Large Hydrophobic Residues (LHR), which have a central role in protein folding. One of them, codon CUA, is also a TRIT target in both HTLV-1 and HTLV-2. Therefore, a drug designed for inactivating or reducing the cytoplasmatic concentration of tRNA species with anticodon TAG could attenuate significantly both HIV and HTLV protein synthesis rates. Inversely, replacing codons ending in UA by synonymous codons should increase the expression, which is relevant for DNA vaccine design.
codon usage; tRNA; HIV; HTLV; therapy
To determine the frequency and patterns of acquired antiretroviral drug resistance in a rural primary health care programme in South Africa.
Cross-sectional study nested within HIV treatment programme.
Adult (≥18 years) HIV-infected individuals initially treated with a first-line stavudine- or zidovudine-based antiretroviral therapy (ART) regimen and with evidence of virological failure (one viral load >1000 copies/ml) were enrolled from 17 rural primary health care clinics. Genotypic resistance testing was performed using the in-house SATuRN/Life Technologies system. Sequences were analysed and genotypic susceptibility scores (GSS) for standard second-line regimens were calculated using the Stanford HIVDB 6.0.5 algorithms.
A total of 222 adults were successfully genotyped for HIV drug resistance between December 2010 and March 2012. The most common regimens at time of genotype were stavudine, lamivudine and efavirenz (51%); and stavudine, lamivudine and nevirapine (24%). Median duration of ART was 42 months (interquartile range (IQR) 32–53) and median duration of antiretroviral failure was 27 months (IQR 17–40). One hundred and ninety one (86%) had at least one drug resistance mutation. For 34 individuals (15%), the GSS for the standard second-line regimen was <2, suggesting a significantly compromised regimen. In univariate analysis, individuals with a prior nucleoside reverse-transcriptase inhibitor (NRTI) substitution were more likely to have a GSS <2 than those on the same NRTIs throughout (odds ratio (OR) 5.70, 95% confidence interval (CI) 2.60–12.49).
There are high levels of drug resistance in adults with failure of first-line antiretroviral therapy in this rural primary health care programme. Standard second-line regimens could potentially have had reduced efficacy in about one in seven adults involved.
South Africa’s national antiretroviral (ARV) treatment program expanded in 2010 to include the nucleoside reverse transcriptase (RT) inhibitors (NRTI) tenofovir (TDF) for adults and abacavir (ABC) for children. We investigated the associated changes in genotypic drug resistance patterns in patients with first-line ARV treatment failure since the introduction of these drugs, and protease inhibitor (PI) resistance patterns in patients who received ritonavir-boosted lopinavir (LPV/r)-containing therapy.
We analysed ARV treatment histories and HIV-1 RT and protease mutations in plasma samples submitted to the Tygerberg Academic Hospital National Health Service Laboratory.
Between 2006 and 2012, 1,667 plasma samples from 1,416 ARV-treated patients, including 588 children and infants, were submitted for genotypic resistance testing. Compared with 720 recipients of a d4T or AZT-containing first-line regimen, the 153 recipients of a TDF-containing first-line regimen were more likely to have the RT mutations K65R (46% vs 4.0%; p<0.001), Y115F (10% vs. 0.6%; p<0.001), L74VI (8.5% vs. 1.8%; p<0.001), and K70EGQ (7.8% vs. 0.4%) and recipients of an ABC-containing first-line regimen were more likely to have K65R (17% vs 4.0%; p<0.001), Y115F (30% vs 0.6%; p<0.001), and L74VI (56% vs 1.8%; p<0.001). Among the 490 LPV/r recipients, 55 (11%) had ≥1 LPV-resistance mutations including 45 (9.6%) with intermediate or high-level LPV resistance. Low (20 patients) and intermediate (3 patients) darunavir (DRV) cross resistance was present in 23 (4.6%) patients.
Among patients experiencing virological failure on a first-line regimen containing two NRTI plus one NNRTI, the use of TDF in adults and ABC in children was associated with an increase in four major non- thymidine analogue mutations. In a minority of patients, LPV/r-use was associated with intermediate or high-level LPV resistance with predominantly low-level DRV cross-resistance.
Summary: RegaDB is a free and open source data management and analysis environment for infectious diseases. RegaDB allows clinicians to store, manage and analyse patient data, including viral genetic sequences. Moreover, RegaDB provides researchers with a mechanism to collect data in a uniform format and offers them a canvas to make newly developed bioinformatics tools available to clinicians and virologists through a user friendly interface.
Availability and implementation: Source code, binaries and documentation are available on http://rega.kuleuven.be/cev/regadb. RegaDB is written in the Java programming language, using a web-service-oriented architecture.
Motivation: Large phylogenies are being built today to study virus evolution, trace the origin of epidemics, establish the mode of transmission and survey the appearance of drug resistance. However, no tool is available to quickly inspect these phylogenies and combine them with extrinsic traits (e.g. geographic location, risk group, presence of a given resistance mutation), seeking to extract strain groups of specific interest or requiring surveillance.
Results: We propose a new method for obtaining such groups, which we call phylotypes, from a phylogeny having taxa (strains) annotated with extrinsic traits. Phylotypes are subsets of taxa with close phylogenetic relationships and common trait values. The method combines ancestral trait reconstruction using parsimony, with combinatorial and numerical criteria measuring tree shape characteristics and the diversity and separation of the potential phylotypes. A shuffling procedure is used to assess the statistical significance of phylotypes. All algorithms have linear time complexity. This results in low computing times, typically a few minutes for the larger data sets with a number of shuffling steps. Two HIV-1 data sets are analyzed, one of which is large, containing >3000 strains of HIV-1 subtype C collected worldwide, where the method shows its ability to recover known clusters and transmission routes, and to detect new ones.
Availability: This method and companion tools are implemented in an interactive Web interface (www.phylotype.org), which provides a wide choice of graphical views and output formats, and allows for exploratory analyses of large data sets.
Supplementary data are available at Bioinformatics online.
HIV-1 transmitted drug resistance (TDR) could reverse the gains of antiretroviral rollout. To ensure that current first-line therapies remain effective, TDR levels in recently infected treatment-naive patients need to be monitored. A literature review and data mining exercise was carried out to determine the temporal trends in TDR in South Africa. In addition, 72 sequences from seroconvertors identified from Africa Centre's 2010 HIV surveillance round were also examined for TDR. Publicly available data on TDR were retrieved from GenBank, curated in RegaDB, and analyzed using the Calibrated Population Resistance Program. There was no evidence of TDR from the 2010 rural KwaZulu Natal samples. Ten datasets with a total of 1618 sequences collected between 2000 and 2010 were pooled to provide a temporal analysis of TDR. The year with the highest TDR rate was 2002 [6.67%, 95% confidence interval (CI): 3.09–13.79%; n=6/90]. After 2002, TDR levels returned to <5% (WHO low-level threshold) and showed no statistically significant increase in the interval between 2002 and 2010. The most common mutations were associated with NNRTI resistance, K103N, followed by Y181C and Y188C/L. Five sequences had multiple resistance mutations associated with NNRTI resistance. There is no evidence of TDR in rural KwaZulu-Natal. TDR levels in South Africa have remained low following a downward trend since 2003. Continuous vigilance in monitoring of TDR is needed as more patients are initiated and maintained onto antiretroviral therapy.
The evolution of substitutions conferring drug resistance to HIV-1 is both episodic, occurring when patients are on antiretroviral therapy, and strongly directional, with site-specific resistant residues increasing in frequency over time. While methods exist to detect episodic diversifying selection and continuous directional selection, no evolutionary model combining these two properties has been proposed. We present two models of episodic directional selection (MEDS and EDEPS) which allow the a priori specification of lineages expected to have undergone directional selection. The models infer the sites and target residues that were likely subject to directional selection, using either codon or protein sequences. Compared to its null model of episodic diversifying selection, MEDS provides a superior fit to most sites known to be involved in drug resistance, and neither one test for episodic diversifying selection nor another for constant directional selection are able to detect as many true positives as MEDS and EDEPS while maintaining acceptable levels of false positives. This suggests that episodic directional selection is a better description of the process driving the evolution of drug resistance.
When exposed to treatment, HIV-1 and other rapidly evolving viruses have the capacity to acquire drug resistance mutations (DRAMs), which limit the efficacy of antivirals. There are a number of experimentally well characterized HIV-1 DRAMs, but many mutations whose roles are not fully understood have also been reported. In this manuscript we construct evolutionary models that identify the locations and targets of mutations conferring resistance to antiretrovirals from viral sequences sampled from treated and untreated individuals. While the evolution of drug resistance is a classic example of natural selection, existing analyses fail to detect the majority of DRAMs. We show that, in order to identify resistance mutations from sequence data, it is necessary to recognize that in this case natural selection is both episodic (it only operates when the virus is exposed to the drugs) and directional (only mutations to a particular amino-acid confer resistance while allowing the virus to continue replicating). The new class of models that allow for the episodic and directional nature of adaptive evolution performs very well at recovering known DRAMs, can be useful at identifying unknown resistance-associated mutations, and is generally applicable to a variety of biological scenarios where similar selective forces are at play.
HIV-1 CRF02_AG and subtype G (HIV-1G) account for most HIV infections in Nigeria, but their evolutionary trends have not been well documented. To better elucidate the dynamics of the epidemic in Nigeria we characterised the gag and env genes of North-Central Nigerian HIV-1 isolates from pregnant women. Of 28 samples sequenced in both genes, the predominant clades were CRF02_AG (39%) and HIV-1G (32%). Higher predicted proportion of CXCR4-tropic (X4) HIV-1G isolates was noted compared to CRF02_AG (p = 0.007, Fisher's exact test). Phylogenetic and Bayesian analysis conducted on our sequences and all the dated available Nigerian sequences on the Los Alamos data base showed that CRF02_AG and HIV-1G entered into Nigeria through multiple entries, with presence of HIV-1G dating back to early 1980s. This study underlines the genetic complexity of the HIV-1 epidemic in Nigeria, possible subtype-specific differences in co-receptor usage, and the evolutionary trends of the predominant HIV-1 strains in Nigeria, which may have implications for the design of biomedical interventions and better understanding of the epidemic.
To investigate the origins and evolutionary history of subtype C HIV-1 in Zimbabwe in a context of regional conflict and migration.
HIV-1C pol sequence datasets were generated from four sequential cohorts of antenatal women in Harare, Zimbabwe sampled over 15 years (1991–2006).
One hundred and seventy-seven HIV-1C pol sequences were obtained from four successive cohorts in Zimbabwe. Maximum-likelihood methods were used to explore phylogenetic relationships between Zimbabwean HIV-1C sequences and subtype C strains from other regions. A Bayesian coalescent-based framework was used to estimate evolutionary parameters for HIV-1C in Zimbabwe, including origin and demographic growth patterns.
Zimbabwe HIV-1C pol demonstrated increasing sequence divergence over the 15-year period. Nearly all Zimbabwe sequences clustered phylogenetically with subtype C strains from neighboring countries. Bayesian evolutionary analysis indicated a most recent common ancestor date of 1973 with three epidemic growth phases: an initial slow phase (1970s) followed by exponential growth (1980s), and a linearly expanding epidemic to the present. Bayesian trees provided evidence for multiple HIV-1C introductions into Zimbabwe during 1979–1981, corresponding with Zimbabwean national independence following a period of socio-political instability.
The Zimbabwean HIV-1C epidemic likely originated from multiple introductions in the late 1970s and grew exponentially during the 1980s, corresponding to changing political boundaries and rapid population influx from neighboring countries. The timing and phylogenetic clustering of the Zimbabwean sequences is consistent with an origin in southern Africa and subsequent expansion. HIV-1 sequence data contain important epidemiological information, which can help focus treatment and prevention strategies in light of more recent political volatility in Zimbabwe.
epidemiology; evolutionary history; HIV-1; origin; subtype C; Zimbabwe
Despite the existence of over 50 subtypes and circulating recombinant forms of human immunodeficiency virus type-1 (HIV-1), subtype-C dominates the heterosexual pandemic causing 56% of all infections.
To evaluate whether viral genetic factors may contribute to the observed subtype-C predominance.
Chimeric viruses were generated using V1-V3 envelope fragments from a subtype-A/C dually-infected woman with preferential genital replication of subtype-C. Viral adaptation, spread and cell fusion ability were evaluated in vitro using peripheral blood mononuclear cells (PBMC) and HeLa-CD4-CCR5 cell lines, sequencing and cloning. Structural modeling was performed using a crystal structure of gp120-CD4-X5. Phylogenetic analysis was done using subtype-A, -B and -C sequences from blood and cervix of 37 infected women and database sequences.
We identified two envelope motifs, compact V1-V2 loops and V3-316T, which are found at high frequency throughout subtype-C evolution, and affect gp120 interactions with CD4 and CCR5, respectively. When a V1-Δ5 deletion or V3-A316T was incorporated into subtype-A, each increased viral fusion and spread in PBMC and cell-lines with low CCR5-expression several fold. Structural modeling suggested the formation of an additional hydrogen bond between V3 and CCR5. Moreover, we found preferential selection of HIV with 316T and/or extremely short V1-V2 loops in cervices of three women infected with subtype-A/C, -B or −C.
As CD4+-CCR5+-T-cells are key targets for genital HIV infection, and cervical selection can favor compact V1-V2 loops and 316T, which increase viral infectivity, we propose that these conserved subtype-C motifs may contribute to transmission and spread of this subtype.
HIV-1; subtype-C; subtype-A; evolution; CCR5; cervix; transmission; phylogeny
The global spread of HIV-1 has been accompanied by the emergence of genetically distinct viral strains. Over the past two decades subtype C viruses, which predominate in Southern and Eastern Africa, have spread rapidly throughout parts of South America. Phylogenetic studies indicate that subtype C viruses were introduced to South America through a single founder event that occurred in Southern Brazil. However, the external route via which subtype C viruses spread to the South American continent has remained unclear.
We used automated genotyping to screen 8,309 HIV-1 subtype C pol gene sequences sampled within the UK for isolates genetically linked to the subtype C epidemic in South America. Maximum likelihood and Bayesian approaches were used to explore the phylogenetic relationships between 54 sequences identified in this screen, and a set of globally sampled subtype C reference sequences. Phylogenetic trees disclosed a robustly supported relationship between sequences from Brazil, the UK and East Africa. A monophyletic cluster comprised exclusively of sequences from the UK and Brazil was identified and dated to approximately the early 1980s using a Bayesian coalescent-based method. A sub-cluster of 27 sequences isolated from homosexual men of UK origin was also identified and dated to the early 1990s.
Phylogenetic, demographic and temporal data support the conclusion that the UK was a crucial staging post in the spread of subtype C from East Africa to South America. This unexpected finding demonstrates the role of diffuse international networks in the global spread of HIV-1 infection, and the utility of globally sampled viral sequence data in revealing these networks. Additionally, we show that subtype C viruses are spreading within the UK amongst men who have sex with men.
Human immunodeficiency virus type-1 (HIV-1), hepatitis B and C and other rapidly evolving viruses are characterized by extremely high levels of genetic diversity. To facilitate diagnosis and the development of prevention and treatment strategies that efficiently target the diversity of these viruses, and other pathogens such as human T-lymphotropic virus type-1 (HTLV-1), human herpes virus type-8 (HHV8) and human papillomavirus (HPV), we developed a rapid high-throughput-genotyping system. The method involves the alignment of a query sequence with a carefully selected set of pre-defined reference strains, followed by phylogenetic analysis of multiple overlapping segments of the alignment using a sliding window. Each segment of the query sequence is assigned the genotype and sub-genotype of the reference strain with the highest bootstrap (>70%) and bootscanning (>90%) scores. Results from all windows are combined and displayed graphically using color-coded genotypes. The new Virus-Genotyping Tools provide accurate classification of recombinant and non-recombinant viruses and are currently being assessed for their diagnostic utility. They have incorporated into several HIV drug resistance algorithms including the Stanford (http://hivdb.stanford.edu) and two European databases (http://www.umcutrecht.nl/subsite/spread-programme/ and http://www.hivrdb.org.uk/) and have been successfully used to genotype a large number of sequences in these and other databases. The tools are a PHP/JAVA web application and are freely accessible on a number of servers including:
Little is known about the HIV-1 epidemic in Balkan countries. To fill the gap, we investigated the viral genetic diversity in Bulgaria, by sequencing and phylogenetic characterization of 86 plasma samples collected between 2002 and 2006 from seropositive individuals diagnosed within 1986–2006. Analysis of pol gene sequences assigned 51% of the samples to HIV-1 subtype B and 27% to subtype A1. HIV-1 subtype C, F, G, H, and a few putative recombinant forms were also found. Phylogenetic and molecular clock analysis showed a continuous exchange of subtype A and B between Bulgaria and Western as well as other Eastern European countries. At least three separate introductions of HIV-1 subtype A and four of HIV-1 subtype B have occurred within the past 25 years in Bulgaria. The central geographic location of Bulgaria, the substantial genetic heterogeneity of the epidemic with multiple subtypes, and the significant viral flow observed to and from the Balkan countries have the potential to modify the current HIV-1 epidemiological structure in Europe and highlight the importance of more extensive and continuous monitoring of the epidemic in the Balkans.