History and origin of the HIV-1 subtype C epidemic in South Africa and the greater southern African region

The role of migration networks in the development of Botswana's generalized HIV epidemic

The majority of people with HIV live in sub-Saharan Africa, where epidemics are generalized. For these epidemics to develop, populations need to be mobile. However, the role of population-level mobility in the development of generalized HIV epidemics has not been studied. Here we do so by studying historical migration data from Botswana, which has one of the most severe generalized HIV epidemics worldwide; HIV prevalence was 21% in 2021. The country reported its first AIDS case in 1985 when it began to rapidly urbanize. We hypothesize that, during the development of Botswana's epidemic, the population was extremely mobile and the country was highly connected by substantial migratory flows. We test this mobility hypothesis by conducting a network analysis using a historical time series (1981-2011) of micro-census data from Botswana. Our results support our hypothesis. We found complex migration networks with very high rates of rural-to-urban, and urban-to-rural, migration: 10% of the population moved annually. Mining towns (where AIDS cases were first reported, and risk behavior was high) were important in-flow and out-flow migration hubs, suggesting that they functioned as 'core groups' for HIV transmission and dissemination. Migration networks could have dispersed HIV throughout Botswana and generated the current hyperendemic epidemic.

Population mobility and the development of Botswana's generalized HIV epidemic: a network analysis

The majority of people with HIV live in sub-Saharan Africa, where HIV epidemics are generalized. For these epidemics to develop, populations need to be mobile. However, population-level mobility has not yet been studied in the context of the development of generalized HIV epidemics. Here we do so by studying historical migration data from Botswana which has one of the most severe generalized HIV epidemics worldwide; in 2021, HIV prevalence was 21%. The country reported its first AIDS case in 1985 when it began to rapidly urbanize. We hypothesize that, during the development of Botswana's epidemic, the population was highly mobile and there were substantial urban-to-rural and rural-to-urban migratory flows. We test this hypothesis by conducting a network analysis using a historical time series (1981 to 2011) of micro-census data from Botswana. We found 10% of the population moved their residency annually, complex migration networks connected urban with rural areas, and there were very high rates of rural-to-urban migration. Notably, we also found mining towns were both important in-flow and out-flow migration hubs; consequently, there was a very high turnover of residents in towns. Our results support our hypothesis, and together, provide one explanation for the development of Botswana's generalized epidemic.

Evaluating whole HIV-1 genome sequence for estimation of incidence and migration in a rural South African community

Background: South Africa has the largest number of people living with HIV (PLWHIV) in the world, with HIV prevalence and transmission patterns varying greatly between provinces. Transmission between regions is still poorly understood, but phylodynamics of HIV-1 evolution can reveal how many infections are attributable to contacts outside a given community. We analysed whole genome HIV-1 genetic sequences to estimate incidence and the proportion of transmissions between communities in Hlabisa, a rural South African community. Methods: We separately analysed HIV-1 for gag, pol, and env genes sampled from 2,503 PLWHIV. We estimated time-scaled phylogenies by maximum likelihood under a molecular clock model. Phylodynamic models were fitted to time-scaled trees to estimate transmission rates, effective number of infections, incidence through time, and the proportion of infections imported to Hlabisa. We also partitioned time-scaled phylogenies with significantly different distributions of coalescent times. Results: Phylodynamic analyses showed similar trends in epidemic growth rates between 1980 and 1990. Model-based estimates of incidence and effective number of infections were consistent across genes. Parameter estimates with gag were generally smaller than those estimated with pol and env. When estimating the proportions of new infections in Hlabisa from immigration or transmission from external sources, our posterior median estimates were 85% (95% credible interval (CI) = 78%–92%) for gag, 62% (CI = 40%–78%) for pol, and 77% (CI = 58%–90%) for env in 2015. Analysis of phylogenetic partitions by gene showed that most close global reference sequences clustered within a single partition. This suggests local evolving epidemics or potential unmeasured heterogeneity in the population. Conclusions: We estimated consistent epidemic dynamic trends for gag, pol and env genes using phylodynamic models. There was a high probability that new infections were not attributable to endogenous transmission within Hlabisa, suggesting high inter-connectedness between communities in rural South Africa.

Molecular Epidemiology and Transmission Dynamics of the HIV-1 Epidemic in Ethiopia: Epidemic Decline Coincided With Behavioral Interventions Before ART Scale-Up

Background

Ethiopia is one of the sub-Saharan countries hit hard by the HIV epidemic. Previous studies have shown that subtype C dominates the Ethiopian HIV-1 epidemic, but the evolutionary and temporal dynamics of HIV-1 in Ethiopia have not been closely scrutinized. Understanding the evolutionary and epidemiological pattern of HIV is vital to monitor the spread, evaluate and implement HIV prevention strategies.

Methods

We analyzed 1,276 Ethiopian HIV-1 subtype C polymerase (pol sequences), including 144 newly generated sequences, collected from different parts of the country from 1986 to 2017. We employed state-of-art maximum likelihood and Bayesian phylodynamic analyses to comprehensively describe the evolutionary dynamics of the HIV-1 epidemic in Ethiopia. We used Bayesian phylodynamic models to estimate the dynamics of the effective population size (Ne) and reproductive numbers (Re) through time for the HIV epidemic in Ethiopia.

Results

Our analysis revealed that the Ethiopian HIV-1 epidemic originated from two independent introductions at the beginning of the 1970s and 1980s from eastern and southern African countries, respectively, followed by epidemic growth reaching its maximum in the early 1990s. We identified three large clusters with a majority of Ethiopian sequences. Phylodynamic analyses revealed that all three clusters were characterized by high transmission rates during the early epidemic, followed by a decline in HIV-1 transmissions after 1990. Re was high (4–6) during the earlier time of the epidemic but dropped significantly and remained low (Re < 1) after the mid-1990. Similarly, with an expected shift in time, the effective population size (Ne) steadily increased until the beginning of 2000, followed by a decline and stabilization until recent years. The phylodynamic analyses corroborated the modeled UNAIDS incidence and prevalence estimates.

Conclusion

The rapid decline in the HIV epidemic took place a decade before introducing antiretroviral therapy in Ethiopia and coincided with early behavioral, preventive, and awareness interventions implemented in the country. Our findings highlight the importance of behavioral interventions and antiretroviral therapy scale-up to halt and maintain HIV transmissions at low levels (Re < 1). The phylodynamic analyses provide epidemiological insights not directly available using standard surveillance and may inform the adjustment of public health strategies in HIV prevention in Ethiopia.

Analysis of the Origin and Dissemination of HIV-1 Subtype C in Bulgaria

HIV-1 subtype C is the most abundant strain of HIV-1 infections worldwide and was found in the first known patients diagnosed with HIV/AIDS in Bulgaria in 1986. However, there is limited information on the molecular-epidemiological characteristics of this strain in the epidemic of the country. In this study, we analyze the evolutionary history of the introduction and dissemination of HIV-1 subtype C in Bulgaria using global phylogenetic analysis, Bayesian coalescent-based approach, and molecular clock methods. All available samples with HIV-1 subtype C from individuals diagnosed with HIV/AIDS between 1986 and 2017 were analyzed. Men and women were equally represented, and 24.3% of patients reported being infected abroad. The global phylogenetic analysis indicated multiple introductions of HIV-1 subtype C from various countries of the world. The reconstruction of a Bayesian time-scaled phylogenies showed that several Bulgarian strains segregated together in clusters, while others were intermixed in larger clades containing strains isolated from both European and non-European countries. The time-scale of HIV-1 subtype C introductions in Bulgaria demonstrates the early introduction of these viruses in the country. Our in-depth phylogenetic and phylogeographic analyses are compatible with a scenario of multiple early introductions in the country followed by limited local distribution in the subsequent years. HIV-1 subtype C was introduced in the early years of the epidemic, originating from different countries of the world. Due to the comprehensive measures for prevention and control in the early years of the epidemic in Bulgaria, HIV-1 subtype C was not widely disseminated among the general population of the country.

T cell derived HIV-1 is present in the CSF in the face of suppressive antiretroviral therapy

HIV cerebrospinal fluid (CSF) escape, where HIV is suppressed in blood but detectable in CSF, occurs when HIV persists in the CNS despite antiretroviral therapy (ART). To determine the virus producing cell type and whether lowered CSF ART levels are responsible for CSF escape, we collected blood and CSF from 156 neurosymptomatic participants from Durban, South Africa. We observed that 28% of participants with an undetectable HIV blood viral load showed CSF escape. We detected host cell surface markers on the HIV envelope to determine the cellular source of HIV in participants on the first line regimen of efavirenz, emtricitabine, and tenofovir. We confirmed CD26 as a marker which could differentiate between T cells and macrophages and microglia, and quantified CD26 levels on the virion surface, comparing the result to virus from in vitro infected T cells or macrophages. The measured CD26 level was consistent with the presence of T cell produced virus. We found no significant differences in ART concentrations between CSF escape and fully suppressed individuals in CSF or blood, and did not observe a clear association with drug resistance mutations in CSF virus which would allow HIV to replicate. Hence, CSF HIV in the face of ART may at least partly originate in CD4+ T cell populations.

The Role of Phylogenetics in Discerning HIV-1 Mixing among Vulnerable Populations and Geographic Regions in Sub-Saharan Africa: A Systematic Review

To reduce global HIV-1 incidence, there is a need to understand and disentangle HIV-1 transmission dynamics and to determine the geographic areas and populations that act as hubs or drivers of HIV-1 spread. In Sub-Saharan Africa (sSA), the region with the highest HIV-1 burden, information about such transmission dynamics is sparse. Phylogenetic inference is a powerful method for the study of HIV-1 transmission networks and source attribution. In this review, we assessed available phylogenetic data on mixing between HIV-1 hotspots (geographic areas and populations with high HIV-1 incidence and prevalence) and areas or populations with lower HIV-1 burden in sSA. We searched PubMed and identified and reviewed 64 studies on HIV-1 transmission dynamics within and between risk groups and geographic locations in sSA (published 1995-2021). We describe HIV-1 transmission from both a geographic and a risk group perspective in sSA. Finally, we discuss the challenges facing phylogenetic inference in mixed epidemics in sSA and offer our perspectives and potential solutions to the identified challenges.

Gut Microbiome Profiles and Associated Metabolic Pathways in HIV-Infected Treatment-Naïve Patients

The normal composition of the intestinal microbiota is a key factor for maintaining healthy homeostasis, and accordingly, dysbiosis is well known to be present in HIV-1 patients. This article investigates the gut microbiota profile of antiretroviral therapy-naive HIV-1 patients and healthy donors living in Latin America in a cohort of 13 HIV positive patients (six elite controllers, EC, and seven non-controllers, NC) and nine healthy donors (HD). Microbiota compositions in stool samples were determined by sequencing the V3-V4 region of the bacterial 16S rRNA, and functional prediction was inferred using PICRUSt. Several taxa were enriched in EC compared to NC or HD groups, including Acidaminococcus, Clostridium methylpentosum, Barnesiella, Eubacterium coprostanoligenes, and Lachnospiraceae UCG-004. In addition, our data indicate that the route of infection is an important factor associated with changes in gut microbiome composition, and we extend these results by identifying several metabolic pathways associated with each route of infection. Importantly, we observed several bacterial taxa that might be associated with different viral subtypes, such as Succinivibrio, which were more abundant in patients infected by HIV subtype B, and Streptococcus enrichment in patients infected by subtype C. In conclusion, our data brings a significant contribution to the understanding of dysbiosis-associated changes in HIV infection and describes, for the first time, differences in microbiota composition according to HIV subtypes. These results warrant further confirmation in a larger cohort of patients.

Global and regional dispersal patterns of hepatitis B virus genotype E from and in Africa: A full-genome molecular analysis

Description of the spatial characteristics of viral dispersal is important in understanding the history of infections. Nine hepatitis B virus (HBV) genotypes (A-I), and a putative 10th genotype (J), with distinct geographical distribution, are recognized. In sub-Saharan Africa (sub)-genotypes A1, D3 and E circulate, with E predominating in western Africa (WA), where HBV is hyperendemic. The low genetic diversity of genotype E (HBV/E) suggests its recent emergence. Our aim was to study the dispersal of HBV/E using full-length, non-redundant and non-recombinant sequences available in public databases. HBV/E was confirmed, and the phylogeny reconstruction performed using maximum likelihood (ML) with bootstrapping. Phylogeographic analysis was conducted by reconstruction of ancestral states using the criterion of parsimony on the estimated ML phylogeny. 46.5% of HBV/E sequences were found within monophyletic clusters. Country-wise analysis revealed the existence of 50 regional clusters. Sequences from WA were located close to the root of the tree, indicating this region as the most probable origin of the HBV/E epidemic and expanded to other geographical regions, within and outside of Africa. A localized dispersal was observed with sequences from Nigeria and Guinea as compared to other WA countries. Based on the sequences available in the databases, the phylogenetic results suggest that European strains originated primarily from WA whereas a majority of American strains originated in Western Central Africa. The differences in regional dispersal patterns of HBV/E suggest limited cross-border transmissions because of restricted population movements.

Reliability of CE-marked NATs for HIV-1 subtype C detection and quantitation

We compared seven CE-marked HIV-1 RNA nucleic acid amplification technology (NAT) based assays for their detection efficiency and quantitation concordance in regard to HIV-1 subtype C. We used 398 plasma samples from South African repeat blood donors identified as HIV positive at occasion of routine screening NAT performed mainly during the years 2010-2013, with most plasma samples reflecting recent HIV-1 infections. All HIV-1 subtype C specimens were detected, independent of mono- or dual-target assay design. In the same time period new variants of HIV-1 subtype B had been identified which were missed by some mono-target assays, a finding which was not corroborated for subtype C in our study. A high level of concordance of HIV-1 subtype C quantitation was determined for the HIV-1 NATs, showing successful standardization in this diagnostic field.

HIV-1 Central Nervous System Compartmentalization and Cytokine Interplay in Non-Subtype B HIV-1 Infections in Nigeria and Malawi

HIV-1 compartmentalization in the central nervous system (CNS) and its contribution to neurological disease have been well documented. Previous studies were conducted among people infected with subtypes B or C where CNS compartmentalization has been observed when comparing viral sequences in the blood to virus in cerebrospinal fluid (CSF). However, little is known about CNS compartmentalization in other HIV-1 subtypes. Using a deep sequencing approach with Primer ID, we conducted a cross-sectional study among Nigerian and Malawian HIV-1 cohorts with or without fungal Cryptococcus infection diagnosed as cryptococcal meningitis (CM) to determine the extent of CSF/CNS compartmentalization with CM. Paired plasma and CSF samples from 45 participants were also analyzed for cytokine/chemokine levels. Viral populations comparing virus in the blood and the CSF ranged from compartmentalized to equilibrated, including minor or partial compartmentalization or clonal amplification of a single viral sequence. The frequency of compartmentalized viral populations in the blood and CSF was similar between the CM- and CM+ participants. We confirmed the potential to see compartmentalization with subtype C infection and have also documented CNS compartmentalization of an HIV-1 subtype G infection. Cytokine profiles indicated a proinflammatory environment, especially within the CSF/CNS. However, sCD163 was suppressed in the CSF in the presence of CM, perhaps due to elevated levels of IL-4, which were also a feature of the cytokine profile, showing a distinct cytokine profile with CM.

Understanding the mechanisms driving the spread of subtype C HIV-1

Human immunodeficiency virus type 1 (HIV-1) subtype C (C-HIV) is the most prevalent form of HIV-1 globally, accounting for approximately 50% of infections worldwide. C-HIV is the predominant and near-exclusive subtype in the low resource regions of India and Southern Africa. Given the vast diversity of HIV-1 subtypes, it is curious as to why C-HIV constitutes such a large proportion of global infections. This enriched prevalence may be due to phenotypic differences between C-HIV isolates and other viral strains that permit enhanced transmission efficiency or, pathogenicity, or might due to the socio-demographics of the regions where C-HIV is endemic. Here, we compare the mechanisms of C-HIV pathogenesis to less prominent HIV-1 subtypes, including viral genetic and phenotypic characteristics, and host genetic variability, to understand whether evolutionary factors drove C-HIV to predominance.

Molecular Characterization of HIV-1 Minority Subtypes in Hong Kong: A Recent Epidemic of CRF07_BC among the Men who have Sex with Men Population

BACKGROUND

Over the past years, an increasing trend was noticed for non-B and non- CRF01_AE HIV-1 strains prevalence in Hong Kong.

OBJECTIVE

In this study, we aimed at using the available HIV-1 pol sequences collected from 1994 to 2013 through our local antiretroviral resistance surveillance program to investigate the molecular epidemiology and evolution of HIV-1 minority subtypes in Hong Kong. We also aimed at investigating their potential association and impact of those transmission risk groups.

METHODS

A total of 2,315 HIV-1 partial pol sequences were included. HIV-1 genotypes were determined by REGA Genotyping Tool and phylogenetic analysis with reference sequences. The viral evolutionary rates and time of the most common ancestor (tMRCA) were estimated by Bayesian Markov Chain Monte Carlo (MCMC) interference.

RESULTS

Apart from the two prevalent HIV-1 genotypes in Hong Kong (subtype B,41.6%, CRF01_AE,40.5%), phylogenetic analysis revealed a broad viral diversity including CRF07_BC(5.1%), subtype C(4.5%), CRF02_AG(1.1%), CRF08_BC(0.8%), subtype A1(0.8%), subtype G(0.4%), subtype D(0.4%), CRF06_cpx(0.4%), subtype F(0.1%), CRF12_BF(0·04%) and other recombinants(4.5%). The top five minority subtypes were further analyzed which demonstrated distinct epidemiological and phylogenetic patterns. Over 70% of subtypes A1, C and CRF02_AG infections were circulated among non-Chinese Asians or African community in Hong Kong and were mainly transmitted between heterosexual regular partners. Instead, over 90% of CRF07_BC and CRF08_BC patients were Chinese. An epidemic cluster was identified in CRF07_BC and estimated to expand from 2002 onwards based on skyline plot and molecular clock analysis.

CONCLUSION

Our results highlighted the emergence of CRF07_BC epidemic in local MSM community, public health interventions targeting the community should be further enhanced to tackle the epidemic.

HIV-1 subtype C predicted co-receptor tropism in Africa: an individual sequence level meta-analysis

Background

Entry inhibitors, such as Maraviroc, hold promise as components of HIV treatment and/or pre-exposure prophylaxis in Africa. Maraviroc inhibits the interaction between HIV Envelope gp120 V3-loop and CCR5 coreceptor. HIV-1 subtype C (HIV-1-C) is predominant in Southern Africa and preferably uses CCR5 co-receptor. Therefore, a significant proportion of HIV-1-C CXCR4 utilizing viruses (X4) may compromise the effectiveness of Maraviroc. This analysis examined coreceptor preferences in early and chronic HIV-1-C infections across Africa.

Methods

African HIV-1-C Envelope gp120 V3-loop sequences sampled from 1988 to 2014 were retrieved from Los Alamos HIV Sequence Database. Sequences from early infections (< 186 days post infection) and chronic infections (> 186 days post infection) were analysed for predicted co-receptor preferences using Geno2Pheno [Coreceptor] 10% FPR, Phenoseq-C, and PSSMsinsi web tools. V3-loop diversity was determined, and viral subtype was confirmed by phylogenetic analysis. National treatment guidelines across Africa were reviewed for Maraviroc recommendation.

Results

Sequences from early (n = 6316) and chronic (n = 7338) HIV-1-C infected individuals from 10 and 15 African countries respectively were available for analyses. Overall, 518/6316 (8.2%; 95% CI 0.7–9.3) of early sequences were X4, with Ethiopia and Malawi having more than 10% each. For chronic infections, 8.3% (95% CI 2.4–16.2) sequences were X4 viruses, with Ethiopia, Tanzania, and Zimbabwe having more than 10% each. For sequences from early chronic infections (< 1 year post infection), the prevalence of X4 viruses was 8.5% (95% CI 2.6–11.2). In late chronic infections (≥ 5 years post infection), X4 viruses were observed in 36% (95% CI − 16.3 to 49.9), with two countries having relatively high X4 viruses: South Africa (43%) and Malawi (24%). The V3-loop amino acid sequence were more variable in X4 viruses in chronic infections compared to acute infections, with South Africa, Ethiopia and Zimbabwe showing the highest levels of V3-loop diversity. All sequences were phylogenetically confirmed as HIV-1-C and clustered according to their co-receptor tropism. In Africa, Maraviroc is registered only in South Africa and Uganda.

Conclusions

Our analyses illustrate that X4 viruses are present in significantly similar proportions in early and early chronic HIV-1 subtype C infected individuals across Africa. In contrast, in late chronic infections, X4 viruses increase 3–5 folds. We can draw two inferences from our observations: (1) to enhance the utility of Maraviroc in chronic HIV subtype C infections in Africa, prior virus co-receptor determination is needed; (2) on the flip side, research on the efficacy of CXCR4 antagonists for HIV-1-C infections is encouraged. Currently, the use of Maraviroc is very limited in Africa.

Distinct rates and patterns of spread of the major HIV-1 subtypes in Central and East Africa

Since the ignition of the HIV-1 group M pandemic in the beginning of the 20th century, group M lineages have spread heterogeneously throughout the world. Subtype C spread rapidly through sub-Saharan Africa and is currently the dominant HIV lineage worldwide. Yet the epidemiological and evolutionary circumstances that contributed to its epidemiological expansion remain poorly understood. Here, we analyse 346 novel pol sequences from the DRC to compare the evolutionary dynamics of the main HIV-1 lineages, subtypes A1, C and D. Our results place the origins of subtype C in the 1950s in Mbuji-Mayi, the mining city of southern DRC, while subtypes A1 and D emerged in the capital city of Kinshasa, and subtypes H and J in the less accessible port city of Matadi. Following a 15-year period of local transmission in southern DRC, we find that subtype C spread at least three-fold faster than other subtypes circulating in Central and East Africa. In conclusion, our results shed light on the origins of HIV-1 main lineages and suggest that socio-historical rather than evolutionary factors may have determined the epidemiological fate of subtype C in sub-Saharan Africa.

Population Structure and Implications on the Genetic Architecture of HIV-1 Phenotypes Within Southern Africa

The interesting history of Southern Africa has put the region in the spotlight for population medical genetics. Major events including the Bantu expansion and European colonialism have imprinted unique genetic signatures within autochthonous populations of Southern Africa, this resulting in differential allele frequencies across the region. This genetic structure has potential implications on susceptibility and resistance to infectious diseases such as human immunodeficiency virus (HIV) infection. Southern Africa is the region affected worst by HIV. Here, we discuss advances made in genome-wide association studies (GWAS) of HIV-1 in the past 12 years and dissect population diversity within Southern Africa. Our findings accentuate that a plethora of factors such as migration, language and culture, admixture, and natural selection have profiled the genetics of the people of Southern Africa. Genetic structure has been observed among the Khoe-San, among Bantu speakers, and between the Khoe-San, Coloureds, and Bantu speakers. Moreover, Southern African populations have complex admixture scenarios. Few GWAS of HIV-1 have been conducted in Southern Africa, with only one of these identifying two novel variants (HCG22rs2535307 and CCNG1kgp22385164) significantly associated with HIV-1 acquisition and progression. High genetic diversity, multi-wave genetic mixture and low linkage disequilibrium of Southern African populations constitute a challenge in identifying genetic variants with modest risk or protective effect against HIV-1. We therefore posit that it is compelling to assess genome-wide contribution of ancestry to HIV-1 infection. We further suggest robust methods that can pin-point population-specific variants that may contribute to the control of HIV-1 in Southern Africa.

The effect of interventions on the transmission and spread of HIV in South Africa: a phylodynamic analysis

The epidemic in South Africa is characterized by high genetic diversity driven by multiple independent introductions. The bulk of these introductions occurred between 1985-2000 during which time HIV prevalence increased exponentially. Epidemic growth has stabilized in recent years with the implementation of several interventions. Here we identified distinct HIV clades from a large sequence dataset of southern African HIV sequences (n = 15,332). Each clade was characterized using phylodynamic and phylogeographic methods to infer their growth through time and space. The estimated date of origin for the 18 clades that were found, fell between 1979-1992 with strong growth during the 1990's. Phylogeographic reconstruction revealed wide dispersal of clades throughout the country with the city of Johannesburg as the focal point of viral dispersal. We found clear signs of decreasing growth rate in four of the clades since the advent of interventions, while other clades have continued to growth and expand. Our results demonstrate that interventions do not affect the HIV epidemic universally with major difference between different clades over time and space. Here we demonstrate the utility and flexibility of molecular epidemiological methods and demonstrate how they can potentially be a powerful tool in HIV epidemic monitoring in South Africa.

Early Presence of HIV-1 Subtype C in Washington, D.C

The presence of non-B HIV subtypes in the USA has been documented during the epidemic, although the timing of early introductions of different subtypes remains uncertain. Subtype C, the most common HIV variant worldwide, was first reported in the USA in 1996-97, after subtype C had expanded greatly in sub-Saharan Africa. In this study, we report a patient with subtype C infection acquired by mother-to-child transmission, born in the USA in 1990 to a Washington, D.C. resident who never traveled outside the USA, demonstrating that subtype C was present in the USA much earlier. Comparative analysis of the sequence from this patient and subtype C sequences in the USA and elsewhere suggest multiple independent introductions of this subtype into the USA have taken place, many of which are traced to sub-Saharan or East Africa. These data indicate subtype C HIV was already present in the USA years earlier than previously reported, and during the early period of subtype C expansion.

HIV-1 diversity among young women in rural South Africa: HPTN 068

Background

South Africa has one of the highest rates of HIV-1 (HIV) infection world-wide, with the highest rates among young women. We analyzed the molecular epidemiology and evolutionary history of HIV in young women attending high school in rural South Africa.

Methods

Samples were obtained from the HPTN 068 randomized controlled trial, which evaluated the effect of cash transfers for school attendance on HIV incidence in women aged 13–20 years (Mpumalanga province, 2011–2015). Plasma samples from HIV-infected participants were analyzed using the ViroSeq HIV-1 Genotyping assay. Phylogenetic analysis was performed using 200 pol gene study sequences and 2,294 subtype C reference sequences from South Africa. Transmission clusters were identified using Cluster Picker and HIV-TRACE, and were characterized using demographic and other epidemiological data. Phylodynamic analyses were performed using the BEAST software.

Results

The study enrolled 2,533 young women who were followed through their expected high school graduation date (main study); some participants had a post-study assessment (follow-up study). Two-hundred-twelve of 2,533 enrolled young women had HIV infection. HIV pol sequences were obtained for 94% (n = 201/212) of the HIV-infected participants. All but one of the sequences were HIV-1 subtype C; the non-C subtype sequence was excluded from further analysis. Median pairwise genetic distance between the subtype C sequences was 6.4% (IQR: 5.6–7.2). Overall, 26% of study sequences fell into 21 phylogenetic clusters with 2–6 women per cluster. Thirteen (62%) clusters included women who were HIV-infected at enrollment. Clustering was not associated with study arm, demographic or other epidemiological factors. The estimated date of origin of HIV subtype C in the study population was 1958 (95% highest posterior density [HPD]: 1931–1980), and the median estimated substitution rate among study pol sequences was 1.98x10^-3 (95% HPD: 1.15x10^-3–2.81x10^-3) per site per year.

Conclusions

Phylogenetic analysis suggests that multiple HIV subtype C sublineages circulate among school age girls in South Africa. There were no substantive differences in the molecular epidemiology of HIV between control and intervention arms in the HPTN 068 trial.

Antibody detection by agglutination-PCR (ADAP) enables early diagnosis of HIV infection by oral fluid analysis

Oral fluid (OF) is a highly effective substrate for population-based HIV screening efforts, as it is noninfectious and significantly easier to collect than blood. However, anti-HIV antibodies are found at far lower concentrations in OF compared with blood, leading to poor sensitivity and a longer period of time from infection to detection threshold. Thus, despite its inherent advantages in sample collection, OF is not widely used for population screening. Here we report the development of an HIV OF assay based on Antibody Detection by Agglutination-PCR (ADAP) technology. This assay is 1,000-10,000 times more analytically sensitive than clinical enzyme-linked immunoassays (EIAs), displaying both 100% clinical sensitivity and 100% specificity for detecting HIV antibodies within OF samples. We show that the enhanced analytical sensitivity enables this assay to correctly identify HIV-infected individuals otherwise missed by current OF assays. We envision that the attributes of this improved HIV OF assay can increase testing rates of at-risk individuals while enabling diagnosis and treatment at an earlier time point.

Divergent HIV-1 strains (CRF92_C2U and CRF93_cpx) co-circulating in the Democratic Republic of the Congo: Phylogenetic insights on the early evolutionary history of subtype C

Molecular epidemiological studies revealed that the epicenter of the HIV pandemic was Kinshasa, the capital city of the Democratic Republic of the Congo (DRC) in Central Africa. All known subtypes and numerous complex recombinant strains co-circulate in the DRC. Moreover, high intra-subtype diversity has been also documented. During two previous surveys on HIV-1 antiretroviral drug resistance in the DRC, we identified two divergent subtype C lineages in the protease and partial reverse transcriptase gene regions. We sequenced eight near full-length genomes and classified them using bootscanning and likelihood-based phylogenetic analyses. Four strains are more closely related to subtype C although within the range of inter sub-subtype distances. However, these strains also have small unclassified fragments and thus were named CRF92_C2U. Another strain is a unique recombinant of CRF92_C2U with an additional small unclassified fragment and a small divergent subtype A fragment. The three remaining strains represent a complex mosaic named CRF93_cpx. CRF93_cpx have two fragments of divergent subtype C sequences, which are not conventional subtype C nor the above described C2, and multiple divergent subtype A-like fragments. We then inferred the time-scaled evolutionary history of subtype C following a Bayesian approach and a partitioned analysis using major genomic regions. CRF92_C2U and CRF93_cpx had the most recent common ancestor with conventional subtype C around 1932 and 1928, respectively. A Bayesian demographic reconstruction corroborated that the subtype C transition to a faster phase of exponential growth occurred during the 1950s. Our analysis showed considerable differences between the newly discovered early-divergent strains and the conventional subtype C and therefore suggested that this virus has been diverging in humans for several decades before the HIV/M diversity boom in the 1950s.

The substitution rate of HIV-1 subtypes: a genomic approach

HIV-1M causes most infections in the AIDS pandemic. Its genetic diversity is defined by nine pure subtypes and more than sixty recombinant forms. We have performed a comparative analysis of the evolutionary rate of five pure subtypes (A1, B, C, D, and G) and two circulating recombinant forms (CRF01_AE and CRF02 AG) using data obtained from nearly complete genome coding sequences. Times to the most recent common ancestor (tMRCA) and substitution rates of these HIV genomes, and their genomic partitions, were estimated by Bayesian coalescent analyses. Genomic substitution rate estimates were compared between the HIV-1 datasets analyzed by means of randomization tests. Significant differences in the rate of evolution were found between subtypes, with subtypes C and A1 and CRF01_AE displaying the highest rates. On the other hand, CRF02_AG and subtype D were the slowest evolving types. Using a different molecular clock model for each genomic partition led to more precise tMRCA estimates than when linking the same clock along the HIV genome. Overall, the earliest tMRCA corresponded to subtype A1 (median = 1941, 95% HPD = 1943-55), whereas the most recent tMRCA corresponded to subtype G and CRF01_AE subset 3 (median = 1971, 95% HPD = 1967-75 and median = 1972, 95% HPD = 1970-75, respectively). These results suggest that both biological and epidemiological differences among HIV-1M subtypes are reflected in their evolutionary dynamics. The estimates obtained for tMRCAs and substitution rates provide information that can be used as prior distributions in future Bayesian coalescent analyses of specific HIV-1 subtypes/CRFs and genes.