Analysis of the history and spread of HIV-1 in Uganda using phylodynamics

AUTO-TUNE: selecting the distance threshold for inferring HIV transmission clusters

Molecular surveillance of viral pathogens and inference of transmission networks from genomic data play an increasingly important role in public health efforts, especially for HIV-1. For many methods, the genetic distance threshold used to connect sequences in the transmission network is a key parameter informing the properties of inferred networks. Using a distance threshold that is too high can result in a network with many spurious links, making it difficult to interpret. Conversely, a distance threshold that is too low can result in a network with too few links, which may not capture key insights into clusters of public health concern. Published research using the HIV-TRACE software package frequently uses the default threshold of 0.015 substitutions/site for HIV pol gene sequences, but in many cases, investigators heuristically select other threshold parameters to better capture the underlying dynamics of the epidemic they are studying. Here, we present a general heuristic scoring approach for tuning a distance threshold adaptively, which seeks to prevent the formation of giant clusters. We prioritize the ratio of the sizes of the largest and the second largest cluster, maximizing the number of clusters present in the network. We apply our scoring heuristic to outbreaks with different characteristics, such as regional or temporal variability, and demonstrate the utility of using the scoring mechanism's suggested distance threshold to identify clusters exhibiting risk factors that would have otherwise been more difficult to identify. For example, while we found that a 0.015 substitutions/site distance threshold is typical for US-like epidemics, recent outbreaks like the CRF07_BC subtype among men who have sex with men (MSM) in China have been found to have a lower optimal threshold of 0.005 to better capture the transition from injected drug use (IDU) to MSM as the primary risk factor. Alternatively, in communities surrounding Lake Victoria in Uganda, where there has been sustained heterosexual transmission for many years, we found that a larger distance threshold is necessary to capture a more risk factor-diverse population with sparse sampling over a longer period of time. Such identification may allow for more informed intervention action by respective public health officials.

AUTO-TUNE: SELECTING THE DISTANCE THRESHOLD FOR INFERRING HIV TRANSMISSION CLUSTERS

Molecular surveillance of viral pathogens and inference of transmission networks from genomic data play an increasingly important role in public health efforts, especially for HIV-1. For many methods, the genetic distance threshold used to connect sequences in the transmission network is a key parameter informing the properties of inferred networks. Using a distance threshold that is too high can result in a network with many spurious links, making it difficult to interpret. Conversely, a distance threshold that is too low can result in a network with too few links, which may not capture key insights into clusters of public health concern. Published research using the HIV-TRACE software package frequently uses the default threshold of 0.015 substitutions/site for HIV pol gene sequences, but in many cases, investigators heuristically select other threshold parameters to better capture the underlying dynamics of the epidemic they are studying. Here, we present a general heuristic scoring approach for tuning a distance threshold adaptively, which seeks to prevent the formation of giant clusters. We prioritize the ratio of the sizes of the largest and the second largest cluster, maximizing the number of clusters present in the network. We apply our scoring heuristic to outbreaks with different characteristics, such as regional or temporal variability, and demonstrate the utility of using the scoring mechanism's suggested distance threshold to identify clusters exhibiting risk factors that would have otherwise been more difficult to identify. For example, while we found that a 0.015 substitutions/site distance threshold is typical for US-like epidemics, recent outbreaks like the CRF07_BC subtype among men who have sex with men (MSM) in China have been found to have a lower optimal threshold of 0.005 to better capture the transition from injected drug use (IDU) to MSM as the primary risk factor. Alternatively, in communities surrounding Lake Victoria in Uganda, where there has been sustained hetero-sexual transmission for many years, we found that a larger distance threshold is necessary to capture a more risk factor-diverse population with sparse sampling over a longer period of time. Such identification may allow for more informed intervention action by respective public health officials.

High HIV diversity, recombination, and superinfection revealed in a large outbreak among persons who inject drugs in Kentucky and Ohio, USA

We investigated transmission dynamics of a large human immunodeficiency virus (HIV) outbreak among persons who inject drugs (PWID) in KY and OH during 2017-20 by using detailed phylogenetic, network, recombination, and cluster dating analyses. Using polymerase (pol) sequences from 193 people associated with the investigation, we document high HIV-1 diversity, including Subtype B (44.6 per cent); numerous circulating recombinant forms (CRFs) including CRF02_AG (2.5 per cent) and CRF02_AG-like (21.8 per cent); and many unique recombinant forms composed of CRFs with major subtypes and sub-subtypes [CRF02_AG/B (24.3 per cent), B/CRF02_AG/B (0.5 per cent), and A6/D/B (6.4 per cent)]. Cluster analysis of sequences using a 1.5 per cent genetic distance identified thirteen clusters, including a seventy-five-member cluster composed of CRF02_AG-like and CRF02_AG/B, an eighteen-member CRF02_AG/B cluster, Subtype B clusters of sizes ranging from two to twenty-three, and a nine-member A6/D and A6/D/B cluster. Recombination and phylogenetic analyses identified CRF02_AG/B variants with ten unique breakpoints likely originating from Subtype B and CRF02_AG-like viruses in the largest clusters. The addition of contact tracing results from OH to the genetic networks identified linkage between persons with Subtype B, CRF02_AG, and CRF02_AG/B sequences in the clusters supporting de novo recombinant generation. Superinfection prevalence was 13.3 per cent (8/60) in persons with multiple specimens and included infection with B and CRF02_AG; B and CRF02_AG/B; or B and A6/D/B. In addition to the presence of multiple, distinct molecular clusters associated with this outbreak, cluster dating inferred transmission associated with the largest molecular cluster occurred as early as 2006, with high transmission rates during 2017-8 in certain other molecular clusters. This outbreak among PWID in KY and OH was likely driven by rapid transmission of multiple HIV-1 variants including de novo viral recombinants from circulating viruses within the community. Our findings documenting the high HIV-1 transmission rate and clustering through partner services and molecular clusters emphasize the importance of leveraging multiple different data sources and analyses, including those from disease intervention specialist investigations, to better understand outbreak dynamics and interrupt HIV spread.

Detection of HIV-1 Transmission Clusters from Dried Blood Spots within a Universal Test-and-Treat Trial in East Africa

The Sustainable East Africa Research in Community Health (SEARCH) trial was a universal test-and-treat (UTT) trial in rural Uganda and Kenya, aiming to lower regional HIV-1 incidence. Here, we quantify breakthrough HIV-1 transmissions occurring during the trial from population-based, dried blood spot samples. Between 2013 and 2017, we obtained 549 gag and 488 pol HIV-1 consensus sequences from 745 participants: 469 participants infected prior to trial commencement and 276 SEARCH-incident infections. Putative transmission clusters, with a 1.5% pairwise genetic distance threshold, were inferred from maximum likelihood phylogenies; clusters arising after the start of SEARCH were identified with Bayesian time-calibrated phylogenies. Our phylodynamic approach identified nine clusters arising after the SEARCH start date: eight pairs and one triplet, representing mostly opposite-gender linked (6/9), within-community transmissions (7/9). Two clusters contained individuals with non-nucleoside reverse transcriptase inhibitor (NNRTI) resistance, both linked to intervention communities. The identification of SEARCH-incident, within-community transmissions reveals the role of unsuppressed individuals in sustaining the epidemic in both arms of a UTT trial setting. The presence of transmitted NNRTI resistance, implying treatment failure to the efavirenz-based antiretroviral therapy (ART) used during SEARCH, highlights the need to improve delivery and adherence to up-to-date ART recommendations, to halt HIV-1 transmission.

Short Communication: Validation of the Asante HIV-1 Rapid Recency Assay for Detection of Recent HIV-1 Infections in Uganda

Point of care rapid recency testing for HIV-1 may be a cost-effective tool to identify recently infected individuals for incidence estimation, and focused HIV prevention through intensified contact tracing. We validated the Asante™ HIV-1 rapid recency^® assay for use in Uganda. Archived specimens (serum/plasma), collected from longitudinally observed HIV-1 recently and long-term infected participants, were tested with the Asante HIV-1 rapid recency assay per manufacturer's instructions. Previously identified antiretroviral therapy (ART)-naive samples with known seroconversions within 6 months of follow-up were tested in independent laboratories: the Rakai Health Sciences Program (RHSP) and the Uganda Virus Research Institute HIV Reference Laboratory (UVRI-HRL). In addition, samples from participants who seroconverted within 6-18 months and samples from individuals with chronic HIV-1 infection of at least 18 months duration were classified into three categories: ART naive, ART exposed with suppressed viral loads, and ART exposed with detectable viremia. Of the 85 samples seroconverting in ≤6 months, 27 and 42 samples were identified as "recent" by the Asante HIV-1 rapid recency test at the RHSP laboratory and UVRI-HRL, corresponding to sensitivities of 32% and 49%, respectively. There was 72% agreement between the laboratories (Cohen's kappa = 0.481, 95% CI = 0.317-0.646, p < .0001). Specificity was 100% (200/200) among chronically infected ART-naive samples. The Asante HIV-1 rapid recency assay had low sensitivity for detection of recent HIV-1 infections in Uganda, with substantial interlaboratory variability due to differential interpretation of the test strip bands. Specificity was excellent. Assessment of assay performance in other settings is needed to guide decisions on test utility.

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.

Phylogenetic Networks and Parameters Inferred from HIV Nucleotide Sequences of High-Risk and General Population Groups in Uganda: Implications for Epidemic Control

Phylogenetic inference is useful in characterising HIV transmission networks and assessing where prevention is likely to have the greatest impact. However, estimating parameters that influence the network structure is still scarce, but important in evaluating determinants of HIV spread. We analyzed 2017 HIV pol sequences (728 Lake Victoria fisherfolk communities (FFCs), 592 female sex workers (FSWs) and 697 general population (GP)) to identify transmission networks on Maximum Likelihood (ML) phylogenetic trees and refined them using time-resolved phylogenies. Network generative models were fitted to the observed degree distributions and network parameters, and corrected Akaike Information Criteria and Bayesian Information Criteria values were estimated. 347 (17.2%) HIV sequences were linked on ML trees (maximum genetic distance ≤4.5%, ≥95% bootstrap support) and, of these, 303 (86.7%) that consisted of pure A1 (n = 168) and D (n = 135) subtypes were analyzed in BEAST v1.8.4. The majority of networks (at least 40%) were found at a time depth of ≤5 years. The waring and yule models fitted best networks of FFCs and FSWs respectively while the negative binomial model fitted best networks in the GP. The network structure in the HIV-hyperendemic FFCs is likely to be scale-free and shaped by preferential attachment, in contrast to the GP. The findings support the targeting of interventions for FFCs in a timely manner for effective epidemic control. Interventions ought to be tailored according to the dynamics of the HIV epidemic in the target population and understanding the network structure is critical in ensuring the success of HIV prevention programs.

The Molecular Epidemiology and Transmission Dynamics of HIV Type 1 in a General Population Cohort in Uganda

The General Population Cohort (GPC) in south-western Uganda has a low HIV-1 incidence rate (<1%). However, new infections continue to emerge. In this research, 3796 HIV-1 pol sequences (GPC: n = 1418, non-GPC sites: n = 1223, Central Uganda: n = 1010 and Eastern Uganda: n = 145) generated between 2003–2015 were analysed using phylogenetic methods with demographic data to understand HIV-1 transmission in this cohort and inform the epidemic response. HIV-1 subtype A1 was the most prevalent strain in the GPC area (GPC and non-GPC sites) (39.8%), central (45.9%) and eastern (52.4%) Uganda. However, in the GPC alone, subtype D was the predominant subtype (39.1%). Of the 524 transmission clusters identified by Cluster Picker, all large clusters (≥5 individuals, n = 8) involved individuals from the GPC. In a multivariate analysis, clustering was strongly associated with being female (adjusted Odds Ratio, aOR = 1.28; 95% CI, 1.06–1.54), being >25 years (aOR = 1.52; 95% CI, 1.16–2.0) and being a resident in the GPC (aOR = 6.90; 95% CI, 5.22–9.21). Phylogeographic analysis showed significant viral dissemination (Bayes Factor test, BF > 3) from the GPC without significant viral introductions (BF < 3) into the GPC. The findings suggest localized HIV-1 transmission in the GPC. Intensifying geographically focused combination interventions in the GPC would contribute towards controlling HIV-1 infections.

Influences on Adherence to Antiretroviral Therapy (ART) in Early-Stage HIV Disease: Qualitative Study from Uganda and South Africa

Realization of optimal treatment and prevention benefits in the era of universal antiretroviral therapy (ART) and "U=U" (undetectable = untransmittable) requires high adherence at all stages of HIV disease. This article draws upon qualitative interview data to characterize two types of influences on ART adherence for 100 Ugandans and South Africans initiating ART during early-stage HIV infection. Positive influences are: (a) behavioral strategies supporting adherence; (b) preserving health through adherence; (c) support from others; and (d) motivating effect of adherence monitoring. "De-stabilizing experiences" (mobility, loss, pregnancy) as barriers are posited to impact adherence indirectly through intervening consequences (e.g. exacerbation of poverty). Positive influences overlap substantially with adherence facilitators described for later-stage adherers in previous research. Adherence support strategies and interventions effective for persons initiating ART later in HIV disease are likely also to be helpful to individuals beginning treatment immediately upon confirmation of infection. De-stabilizing experiences merit additional investigation across varying populations.

Phylogenetic and Demographic Characterization of Directed HIV-1 Transmission Using Deep Sequences from High-Risk and General Population Cohorts/Groups in Uganda

Across sub-Saharan Africa, key populations with elevated HIV-1 incidence and/or prevalence have been identified, but their contribution to disease spread remains unclear. We performed viral deep-sequence phylogenetic analyses to quantify transmission dynamics between the general population (GP), fisherfolk communities (FF), and women at high risk of infection and their clients (WHR) in central and southwestern Uganda. Between August 2014 and August 2017, 6185 HIV-1 positive individuals were enrolled in 3 GP and 10 FF communities, 3 WHR enrollment sites. A total of 2531 antiretroviral therapy (ART) naïve participants with plasma viral load >1000 copies/mL were deep-sequenced. One hundred and twenty-three transmission networks were reconstructed, including 105 phylogenetically highly supported source–recipient pairs. Only one pair involved a WHR and male participant, suggesting that improved population sampling is needed to assess empirically the role of WHR to the transmission dynamics. More transmissions were observed from the GP communities to FF communities than vice versa, with an estimated flow ratio of 1.56 (95% CrI 0.68–3.72), indicating that fishing communities on Lake Victoria are not a net source of transmission flow to neighboring communities further inland. Men contributed disproportionally to HIV-1 transmission flow regardless of age, suggesting that prevention efforts need to better aid men to engage with and stay in care.

Molecular Surveillance of HIV-1 Infection in Krasnoyarsk Region, Russia: Epidemiology, Phylodynamics and Phylogeography

BACKGROUND

The information about the dynamics of the viral population and migration events that affect the epidemic in different parts of the Russia is insufficient. Possibly, the huge size of the country and limited transport accessibility to certain territories may determine unique traits of the HIV-1 evolutionary history in different regions.

OBJECTIVE

The aim of this study was to explore the genetic diversity of HIV-1 in the Krasnoyarsk region and reconstruct spatial-temporal dynamics of the infection in the region.

METHODS

The demographic and virologic data from 281 HIV-infected individuals in Krasnoyarsk region collected during 2011-2016 were analyzed. The time to the most recent common ancestor, evolutionary rates, population growth, and ancestral geographic movements was estimated using Bayesian coalescent-based methods.

RESULTS

The study revealed moderate diversity of the HIV-1 subtypes found in the region, which included A6 (92.3%), CRF063_02A (4.3%), B (1.1%), and unique recombinants (2.5%). Phylogenetic reconstruction revealed that the A6 subtype was introduced into Krasnoyarsk region by one viral lineage, which arose around 1996.9 (1994.5-1999.5). The phylogeography analysis pointed to Krasnoyarsk city as the geographical center of the epidemic, which further spread to central neighboring districts of the region. At least two epidemic growth phases of subtype A6 were identified which included exponential growth in early-2000s followed by the decline in the mid/late 2010s.

CONCLUSION

This study demonstrates a change in the genetic diversity of HIV-1 in the Krasnoyarsk region. At the beginning of the epidemic, subtype A6 prevailed, subtypes B and CRF063_02A appeared in the region later.

Computational MHC-I epitope predictor identifies 95% of experimentally mapped HIV-1 clade A and D epitopes in a Ugandan cohort

Background

Identifying immunogens that induce HIV-1-specific immune responses is a lengthy process that can benefit from computational methods, which predict T-cell epitopes for various HLA types.

Methods

We tested the performance of the NetMHCpan4.0 computational neural network in re-identifying 93 T-cell epitopes that had been previously independently mapped using the whole proteome IFN-γ ELISPOT assays in 6 HLA class I typed Ugandan individuals infected with HIV-1 subtypes A1 and D. To provide a benchmark we compared the predictions for NetMHCpan4.0 to MHCflurry1.2.0 and NetCTL1.2.

Results

NetMHCpan4.0 performed best correctly predicting 88 of the 93 experimentally mapped epitopes for a set length of 9-mer and matched HLA class I alleles. Receiver Operator Characteristic (ROC) analysis gave an area under the curve (AUC) of 0.928. Setting NetMHCpan4.0 to predict 11-14mer length did not improve the prediction (37–79 of 93 peptides) with an inverse correlation between the number of predictions and length set. Late time point peptides were significantly stronger binders than early peptides (Wilcoxon signed rank test: p = 0.0000005). MHCflurry1.2.0 similarly predicted all but 2 of the peptides that NetMHCpan4.0 predicted and NetCTL1.2 predicted only 14 of the 93 experimental peptides.

Conclusion

NetMHCpan4.0 class I epitope predictions covered 95% of the epitope responses identified in six HIV-1 infected individuals, and would have reduced the number of experimental confirmatory tests by > 80%. Algorithmic epitope prediction in conjunction with HLA allele frequency information can cost-effectively assist immunogen design through minimizing the experimental effort.

Pervasive and non-random recombination in near full-length HIV genomes from Uganda

Recombination is an important feature of HIV evolution, occurring both within and between the major branches of diversity (subtypes). The Ugandan epidemic is primarily composed of two subtypes, A1 and D, that have been co-circulating for 50 years, frequently recombining in dually infected patients. Here, we investigate the frequency of recombinants in this population and the location of breakpoints along the genome. As part of the PANGEA-HIV consortium, 1,472 consensus genome sequences over 5 kb have been obtained from 1,857 samples collected by the MRC/UVRI & LSHTM Research unit in Uganda, 465 (31.6 per cent) of which were near full-length sequences (>8 kb). Using the subtyping tool SCUEAL, we find that of the near full-length dataset, 233 (50.1 per cent) genomes contained only one subtype, 30.8 per cent A1 (n = 143), 17.6 per cent D (n = 82), and 1.7 per cent C (n = 8), while 49.9 per cent (n = 232) contained more than one subtype (including A1/D (n = 164), A1/C (n = 13), C/D (n = 9); A1/C/D (n = 13), and 33 complex types). K-means clustering of the recombinant A1/D genomes revealed a section of envelope (C2gp120-TMgp41) is often inherited intact, whilst a generalized linear model was used to demonstrate significantly fewer breakpoints in the gag-pol and envelope C2-TM regions compared with accessory gene regions. Despite similar recombination patterns in many recombinants, no clearly supported circulating recombinant form (CRF) was found, there was limited evidence of the transmission of breakpoints, and the vast majority (153/164; 93 per cent) of the A1/D recombinants appear to be unique recombinant forms. Thus, recombination is pervasive with clear biases in breakpoint location, but CRFs are not a significant feature, characteristic of a complex, and diverse epidemic.

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.

SNAPPy: A snakemake pipeline for scalable HIV-1 subtyping by phylogenetic pairing

Human immunodeficiency virus 1 (HIV-1) genome sequencing is routinely done for drug resistance monitoring in hospitals worldwide. Subtyping these extensive datasets of HIV-1 sequences is a critical first step in molecular epidemiology and evolution studies. The clinical relevance of HIV-1 subtypes is increasingly recognized. Several studies suggest subtype-related differences in disease progression, transmission route efficiency, immune evasion, and even therapeutic outcomes. HIV-1 subtyping is mainly done using web-servers. These tools have limitations in scalability and potential noncompliance with data protection legislation. Thus, the aim of this work was to develop an efficient method for large-scale local HIV-1 subtyping. We designed SNAPPy: a snakemake pipeline for scalable HIV-1 subtyping by phylogenetic pairing. It contains several tasks of phylogenetic inference and BLAST queries, which can be executed sequentially or in parallel, taking advantage of multiple-core processing units. Although it was built for subtyping, SNAPPy is also useful to perform extensive HIV-1 alignments. This tool facilitates large-scale sequence-based HIV-1 research by providing a local, resource efficient and scalable alternative for HIV-1 subtyping. It is capable of analyzing full-length genomes or partial HIV-1 genomic regions (GAG, POL, and ENV) and recognizes more than ninety circulating recombinant forms. SNAPPy is freely available at: https://github.com/PMMAraujo/snappy/releases.

Genetic Cluster Analysis for HIV Prevention

PURPOSE OF REVIEW

This review summarizes the use of genetic similarity clusters to understand HIV transmission and inform prevention efforts.

RECENT FINDINGS

Recent emphases include the development of real-time cluster identification in order to interrupt transmission chains, the use of clusters to estimate rates of transmission along the HIV care cascade, and the extension of cluster analyses to understand transmission in the generalized epidemics of sub-Saharan Africa. Importantly, this recent empirical work has been accompanied by theoretical work that elucidates the processes that underlie HIV genetic similarity clusters; multiple studies suggest that clusters are not necessarily enriched with individuals with high transmission rates, but rather can reflect variation in sampling times within a population, with individuals sampled early in infection more likely to cluster. Analyses of genetic similarity clusters have great promise to inform HIV epidemiology and prevention. Future emphases should include the collection of additional sequence data from underrepresented populations, such as those in sub-Saharan Africa, and further development and evaluation of clustering methods.

Characterization of a large cluster of HIV-1 A1 infections detected in Portugal and connected to several Western European countries

HIV-1 subtypes associate with differences in transmission and disease progression. Thus, the existence of geographic hotspots of subtype diversity deepens the complexity of HIV-1/AIDS control. The already high subtype diversity in Portugal seems to be increasing due to infections with sub-subtype A1 virus. We performed phylogenetic analysis of 65 A1 sequences newly obtained from 14 Portuguese hospitals and 425 closely related database sequences. 80% of the A1 Portuguese isolates gathered in a main phylogenetic clade (MA1). Six transmission clusters were identified in MA1, encompassing isolates from Portugal, Spain, France, and United Kingdom. The most common transmission route identified was men who have sex with men. The origin of the MA1 was linked to Greece, with the first introduction to Portugal dating back to 1996 (95% HPD: 1993.6–1999.2). Individuals infected with MA1 virus revealed lower viral loads and higher CD4⁺ T-cell counts in comparison with those infected by subtype B. The expanding A1 clusters in Portugal are connected to other European countries and share a recent common ancestor with the Greek A1 outbreak. The recent expansion of this HIV-1 subtype might be related to a slower disease progression leading to a population level delay in its diagnostic.

Using Contact Patterns to Inform HIV Interventions in Persons Who Inject Drugs in Northern Vietnam

OBJECTIVES

Population mixing patterns can greatly inform allocation of HIV prevention interventions such as treatment as prevention or preexposure prophylaxis. Characterizing contact patterns among subgroups can help identify the specific combinations of contact expected to result in the greatest number of new infections.

SETTING

Baseline data from an intervention to reduce HIV-related risk behaviors in male persons who inject drugs (PWID) in the Northern Vietnamese province of Thai Nguyen were used for the analysis.

METHODS

Egocentric network data were provided by PWID who reported any drug-injection equipment sharing in the previous 3 months. Age-dependent mixing was assessed to explore its epidemiological implications on risk of HIV transmission risk (among those HIV-infected) and HIV acquisition risk (among those not infected) in PWID.

RESULTS

A total of 1139 PWID collectively reported 2070 equipment-sharing partnerships in the previous 3 months. Mixing by age identified the 30-34 and 35-39 years age groups as the groups from whom the largest number of new infections was transmitted, making them primary targets for treatment as prevention. Among the uninfected, 25-29, 30-35, and 35-39 years age groups had the highest HIV acquisition rate, making them the primary targets for preexposure prophylaxis.

CONCLUSIONS

Collection and analysis of contact patterns in PWID is feasible and can greatly inform infectious disease dynamics and targeting of appropriate interventions. Results presented also provide much needed empirical data on mixing to improve mathematical models of disease transmission in this population.

Phylogeography of HIV-1 suggests that Ugandan fishing communities are a sink for, not a source of, virus from general populations

Although fishing communities (FCs) in Uganda are disproportionately affected by HIV-1 relative to the general population (GP), the transmission dynamics are not completely understood. We earlier found most HIV-1 transmissions to occur within FCs of Lake Victoria. Here, we test the hypothesis that HIV-1 transmission in FCs is isolated from networks in the GP. We used phylogeography to reconstruct the geospatial viral migration patterns in 8 FCs and 2 GP cohorts and a Bayesian phylogenetic inference in BEAST v1.8.4 to analyse the temporal dynamics of HIV-1 transmission. Subtype A1 (pol region) was most prevalent in the FCs (115, 45.1%) and GP (177, 50.4%). More recent HIV transmission pairs from FCs were found at a genetic distance (GD) <1.5% than in the GP (Fisher’s exact test, p = 0.001). The mean time depth for pairs was shorter in FCs (5 months) than in the GP (4 years). Phylogeographic analysis showed strong support for viral migration from the GP to FCs without evidence of substantial viral dissemination to the GP. This suggests that FCs are a sink for, not a source of, virus strains from the GP. Targeted interventions in FCs should be extended to include the neighbouring GP for effective epidemic control.

Viruses as indicators of contemporary host dispersal and phylogeography: an example of feline immunodeficiency virus (FIVP le ) in free-ranging African lion (Panthera leo)

Measuring contemporary dispersal in highly mobile terrestrial species is challenging, especially when species are characterized by low levels of population differentiation. Directly transmitted viruses can be used as a surrogate for traditional methods of tracking host movement. Feline immunodeficiency virus (FIV) is a species-specific lentivirus, which has an exceptionally high mutation rate and circulates naturally in wild felids. Using samples derived from 35 lion (Panthera leo) prides, we tested the prediction that FIV in lions (FIV_{P le} ) can be used to track the dispersal of individuals between prides. As FIV_{P le} subtypes are geographically structured throughout Africa, we predicted that this marker could be used to detect phylogeographic structure of lions at smaller spatial scales. Phylogenetic analyses of FIV_{P le} pol-RT sequences showed that core pride members (females and subadults) shared evolutionary close viral lineages which differed from neighbouring core prides, whereas sequences from sexually mature males associated with the same pride were always the most divergent. In six instances, natal pride associations of divergent male lions could be inferred, on the assumption that FIV_{P le} infections are acquired during early life stages. Congruence between the genetic pattern of FIV and pride structure suggests that vertical transmission plays an important role in lion FIV dynamics. At a fine spatial scale, significant viral geographic structuring was also detected between lions occurring north of the Olifants River within the Kruger National Park (KNP) and those occupying the southern and central regions. This pattern was further supported by phylogenetic analyses and the confinement of FIV_{P le} subtype E to the northern region of KNP. The study provides new insights into the use of retroviral sequences to predict host dispersal and fine-scale contemporary geographic structure in a social felid species.

Genotypic and Phylogenetic Insights on Prevention of the Spread of HIV-1 and Drug Resistance in "Real-World" Settings

HIV continues to spread among vulnerable heterosexual (HET), Men-having-Sex with Men (MSM) and intravenous drug user (IDU) populations, influenced by a complex array of biological, behavioral and societal factors. Phylogenetics analyses of large sequence datasets from national drug resistance testing programs reveal the evolutionary interrelationships of viral strains implicated in the dynamic spread of HIV in different regional settings. Viral phylogenetics can be combined with demographic and behavioral information to gain insights on epidemiological processes shaping transmission networks at the population-level. Drug resistance testing programs also reveal emergent mutational pathways leading to resistance to the 23 antiretroviral drugs used in HIV-1 management in low-, middle- and high-income settings. This article describes how genotypic and phylogenetic information from Quebec and elsewhere provide critical information on HIV transmission and resistance, Cumulative findings can be used to optimize public health strategies to tackle the challenges of HIV in “real-world” settings.

Prevalence and clinical impacts of HIV-1 intersubtype recombinants in Uganda revealed by near-full-genome population and deep sequencing approaches

OBJECTIVES

HIV-1 subtypes A1 and D cocirculate in a rural community in Mbarara, Uganda. This study examines HIV-1 intersubtype recombination in this community under a full-genome sequencing context. We aim to estimate prevalence, examine time trends, and test for clinical correlates and outcomes associated with intersubtype recombinants.

METHODS

Near-full-genome HIV-1 Sanger sequence data were collected from plasma samples of 504 treatment-naïve individuals, who then received protease inhibitor or nonnucleoside reverse transcriptase inhibitor-containing regimens and were monitored for up to 7.5 years. Subtypes were inferred by Los Alamos Recombinant Identification Program (RIP) 3.0 and compared with Sanger/REGA and MiSeq/RIP. 'Nonrecombinants' and 'recombinants' infections were compared in terms of pretherapy viral load, CD4 cell count, posttherapy time to virologic suppression, virologic rebound, first CD4 rise above baseline and sustained CD4 recovery.

RESULTS

Prevalence of intersubtype recombinants varied depending on the genomic region examined: gag (15%), prrt (11%), int (8%), vif (10%), vpr (2%), vpu (9%), GP120 (8%), GP41 (18%), and nef (4%). Of the 200 patients with near-full-genome data, prevalence of intersubtype recombination was 46%; the most frequently observed recombinant was A1-D (25%). Sanger/REGA and MiSeq/RIP yielded generally consistent results. Phylogenetic tree revealed most recombinants did not share common ancestors. No temporal trend was observed (all P > 0.1). Subsequent subtype switches were detected in 27 of 143 (19%) study participants with follow-up sequences. Nonrecombinant versus recombinants infections were not significantly different in any pre nor posttherapy clinical correlates examined (all P > 0.2).

CONCLUSION

Intersubtype recombination was highly prevalent (46%) in Uganda if the entire HIV genome was considered, but was neither associated with clinical correlates nor therapy outcomes.

HIV-1 full-genome phylogenetics of generalized epidemics in sub-Saharan Africa: impact of missing nucleotide characters in next-generation sequences

To characterize HIV-1 transmission dynamics in regions where the burden of HIV-1 is greatest, the “Phylogenetics and Networks for Generalised HIV Epidemics in Africa” consortium (PANGEA-HIV) is sequencing full-genome viral isolates from across sub-Saharan Africa. We report the first 3,985 PANGEA-HIV consensus sequences from four cohort sites (Rakai Community Cohort Study, n = 2,833; MRC/UVRI Uganda, n = 701; Mochudi Prevention Project, n = 359; Africa Health Research Institute Resistance Cohort, n = 92). Next-generation sequencing success rates varied: more than 80% of the viral genome from the gag to the nef genes could be determined for all sequences from South Africa, 75% of sequences from Mochudi, 60% of sequences from MRC/UVRI Uganda, and 22% of sequences from Rakai. Partial sequencing failure was primarily associated with low viral load, increased for amplicons closer to the 3′ end of the genome, was not associated with subtype diversity except HIV-1 subtype D, and remained significantly associated with sampling location after controlling for other factors. We assessed the impact of the missing data patterns in PANGEA-HIV sequences on phylogeny reconstruction in simulations. We found a threshold in terms of taxon sampling below which the patchy distribution of missing characters in next-generation sequences (NGS) has an excess negative impact on the accuracy of HIV-1 phylogeny reconstruction, which is attributable to tree reconstruction artifacts that accumulate when branches in viral trees are long. The large number of PANGEA-HIV sequences provides unprecedented opportunities for evaluating HIV-1 transmission dynamics across sub-Saharan Africa and identifying prevention opportunities. Molecular epidemiological analyses of these data must proceed cautiously because sequence sampling remains below the identified threshold and a considerable negative impact of missing characters on phylogeny reconstruction is expected.

Defining HIV-1 transmission clusters based on sequence data

Understanding HIV-1 transmission dynamics is relevant to both screening and intervention strategies of HIV-1 infection. Commonly, HIV-1 transmission chains are determined based on sequence similarity assessed either directly from a sequence alignment or by inferring a phylogenetic tree. This review is aimed at both nonexperts interested in understanding and interpreting studies of HIV-1 transmission, and experts interested in finding the most appropriate cluster definition for a specific dataset and research question. We start by introducing the concepts and methodologies of how HIV-1 transmission clusters usually have been defined. We then present the results of a systematic review of 105 HIV-1 molecular epidemiology studies summarizing the most common methods and definitions in the literature. Finally, we offer our perspectives on how HIV-1 transmission clusters can be defined and provide some guidance based on examples from real life datasets.

Geolocalization of HIV-1 subtypes and resistance mutations of patients failing antiretroviral therapy in Salvador - Brazil

Background

Geographical distribution of HIV variants is an important way to understand the circulation and spread of such viral strains.

Objectives

To evaluate the spatial distribution of HIV-1 variants in patients failing antiretroviral therapy, in Salvador, Brazil.

Methods

We performed a cross-sectional evaluation of HIV resistance test reports of patients who underwent genotyping tests in a referral center in Salvador, Brazil, for the years 2008–2014. The laboratory database contains around 2500 resistance reports of patients failing antiretroviral therapy. Genotypic tests were performed by sequencing of HIV-1 POL region (TrueGene, Siemens). We assessed HIV-1 resistance mutations and subtype, as well as residential address, age, and gender of patients.

Results

We evaluated 1300 reports, 772 (59.4%) of them from male patients. As expected, subtype B predominated (79%) followed by subtypes F1 (6.7%) and BF (6.5%). The most frequent mutations in HIV-1 reverse transcriptase were 184V (79.1%), 41L (33.5%), 67N (30.4%), 103N (42.4%), and 108I (11.1%). Most frequent mutations in HIV-1 protease were 63P (52.4%), 36I (47.9%), 15 V (33.0%), 62 V (28.1%) and 13 V (25.8%). Some mutations (41L, 215Y, 210W) were significantly more frequent among men. We detected a significantly higher accumulation of 103N mutation in specific areas of Salvador. We identified a more restricted circulation pattern for subtype FB (more frequent in some regions), and F1 (almost absent in a specific region).

Conclusion

Our results suggest that specific subtypes/resistance mutations present a distinct frequency rate in specific areas of Salvador, probably due to a restricted circulation pattern. This trend to clustering was observed in regions covered by AIDS referral centers, suggesting that pattern of care for such patients can interfere in virological outcomes.

A transmission-virulence evolutionary trade-off explains attenuation of HIV-1 in Uganda

Evolutionary theory hypothesizes that intermediate virulence maximizes pathogen fitness as a result of a trade-off between virulence and transmission, but empirical evidence remains scarce. We bridge this gap using data from a large and long-standing HIV-1 prospective cohort, in Uganda. We use an epidemiological-evolutionary model parameterised with this data to derive evolutionary predictions based on analysis and detailed individual-based simulations. We robustly predict stabilising selection towards a low level of virulence, and rapid attenuation of the virus. Accordingly, set-point viral load, the most common measure of virulence, has declined in the last 20 years. Our model also predicts that subtype A is slowly outcompeting subtype D, with both subtypes becoming less virulent, as observed in the data. Reduction of set-point viral loads should have resulted in a 20% reduction in incidence, and a three years extension of untreated asymptomatic infection, increasing opportunities for timely treatment of infected individuals.

Spatio-Temporal History of HIV-1 CRF35_AD in Afghanistan and Iran

HIV-1 Circulating Recombinant Form 35_AD (CRF35_AD) has an important position in the epidemiological profile of Afghanistan and Iran. Despite the presence of this clade in Afghanistan and Iran for over a decade, our understanding of its origin and dissemination patterns is limited. In this study, we performed a Bayesian phylogeographic analysis to reconstruct the spatio-temporal dispersion pattern of this clade using eligible CRF35_AD gag and pol sequences available in the Los Alamos HIV database (432 sequences available from Iran, 16 sequences available from Afghanistan, and a single CRF35_AD-like pol sequence available from USA). Bayesian Markov Chain Monte Carlo algorithm was implemented in BEAST v1.8.1. Between-country dispersion rates were tested with Bayesian stochastic search variable selection method and were considered significant where Bayes factor values were greater than three. The findings suggested that CRF35_AD sequences were genetically similar to parental sequences from Kenya and Uganda, and to a set of subtype A1 sequences available from Afghan refugees living in Pakistan. Our results also showed that across all phylogenies, Afghan and Iranian CRF35_AD sequences formed a monophyletic cluster (posterior clade credibility> 0.7). The divergence date of this cluster was estimated to be between 1990 and 1992. Within this cluster, a bidirectional dispersion of the virus was observed across Afghanistan and Iran. We could not clearly identify if Afghanistan or Iran first established or received this epidemic, as the root location of this cluster could not be robustly estimated. Three CRF35_AD sequences from Afghan refugees living in Pakistan nested among Afghan and Iranian CRF35_AD branches. However, the CRF35_AD-like sequence available from USA diverged independently from Kenyan subtype A1 sequences, suggesting it not to be a true CRF35_AD lineage. Potential factors contributing to viral exchange between Afghanistan and Iran could be injection drug networks and mass migration of Afghan refugees and labours to Iran, which calls for extensive preventive efforts.

Integrating molecular epidemiology and social network analysis to study infectious diseases: Towards a socio-molecular era for public health

The number of public health applications for molecular epidemiology and social network analysis has increased rapidly since the improvement in computational capacities and the development of new sequencing techniques. Currently, molecular epidemiology methods are used in a variety of settings: from infectious disease surveillance systems to the description of disease transmission pathways. The latter are of great epidemiological importance as they let us describe how a virus spreads in a community, make predictions for the further epidemic developments, and plan preventive interventions. Social network methods are used to understand how infections spread through communities and what the risk factors for this are, as well as in improved contact tracing and message-dissemination interventions. Research is needed on how to combine molecular and social network data as both include essential, but not fully sufficient information on infection transmission pathways. The main differences between the two data sources are that, firstly, social network data include uninfected individuals unlike the molecular data sampled only from infected network members. Thus, social network data include more detailed picture of a network and can improve inferences made from molecular data. Secondly, network data refer to the current state and interactions within the social network, while molecular data refer to the time points when transmissions happened, which might have happened years before the sampling date. As of today, there have been attempts to combine and compare the data obtained from the two sources. Even though there is no consensus on whether and how social and genetic data complement each other, this research might significantly improve our understanding of how viruses spread through communities.

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We summarise and analyse the roles of molecular evolution studies in molecular epidemiology of infectious diseases.

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We review how social network and molecular sequence data have been integrated in the past.

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We show how integrating social network and molecular evolution approaches may change the study of infectious diseases.

Reconstructing the HIV-1 CRF02_AG and CRF06_cpx epidemics in Burkina Faso and West Africa using early samples

BACKGROUND

HIV-1 circulating recombinant forms (CRFs) represent viral recombinant lineages that play a significant role in the global epidemic. Two of them dominate the epidemic in Burkina Faso: CRF06_cpx (first described in this country) and CRF02_AG. We reconstructed the phylodynamics of both recombinant viruses in Burkina Faso and throughout West Africa.

METHODS

We analysed CRF06_cpx and CRF02_AG sequences (protease/gp41) from early samples collected in Burkina Faso in 1986 together with other GenBank sequences (1984-2013) in 4 datasets: African CRF06_cpx (210/60); down-sampled CRF06_cpx (146/45); Burkina Faso CRF02_AG (130/39) and West/Central African CRF02_AG (691/298). For each dataset, we analysed both protease and gp41 jointly using the BEAST multilocus analysis and conducted phylogeographic analysis to reconstruct the early migration routes between countries.

RESULTS

The time to the most recent common ancestor (tMRCA) of CRF06_cpx was 1979 (1973-1983) for protease and 1981 (1978-1983) for gp41. The gp41 analysis inferred the origin of CRF06_cpx (or at least its parental subtype G lineage) in the Democratic Republic of Congo but migrated to Burkina Faso soon after (1982). Both genes showed that CRF06_cpx radiated to the rest of West Africa predominantly after around 1990. These results were robust to the oversampling of Burkina Faso sequences as they were confirmed in the down-sampled dataset. The tMRCA of the Burkina Faso CRF02_AG lineage was 1979 (1977-1983) for protease and 1980 (1978-1981) for gp41. However, we reconstructed its presence in West Africa much earlier (mid-1960s), with an initial origin in Cameroon and/or Nigeria, and its phylogeographic analysis revealed much interconnection within the region with a lack of country-specific phylogenetic patterns, which prevents tracking its exact migration routes.

CONCLUSIONS

Burkina Faso presents a relatively young HIV epidemic, with the diversification of the current in-country CRF02_AG and CRF06_cpx lineages taking place around 1980. This country represents the main source of CRF06_cpx in West Africa. The CRF02_AG epidemic started at least a decade earlier and showed much interchange between West African countries (especially involving coastal countries) suggesting great population mobility and an extensive viral spread in the region.