Importance of Viral Sequence Length and Number of Variable and Informative Sites in Analysis of HIV Clustering

Next-Generation Sequencing Methods for Near-Real-Time Molecular Epidemiology of HIV and HCV

The World Health Organisation has set targets of reducing the transmission of new hepatitis C (HCV) infections by 90%, and ending human immunodeficiency virus-1 (HIV) as a public health threat, by 2030. To achieve this, efficient and timely viral surveillance, and effective public health interventions, are required. Traditional epidemiological methods are largely dependent on the recognition of incident cases with symptomatic illness; acute HIV and HCV infections are commonly asymptomatic, which may lead to delays in the recognition of such new infections. Instead, for these viruses, molecular epidemiology may improve the detection of, and response to, clusters of viral transmission. Molecular epidemiology using historical datasets has highlighted key populations that may have benefitted from a timely intervention. Similar analyses performed on contemporary samples are needed to underpin the 2030 targets, but this requires the generation of a cohesive dataset of viral genome sequences in near-real-time. To generate such data, methodologies harnessing next-generation sequencing (NGS) should be utilised. Here we discuss the opportunity presented by NGS for public health surveillance of HIV and HCV, and discuss three methods that can generate sequences for such analysis. These include full-length genome amplification, utilised for analysis of HCV in the research space; tiling PCR, which was the method of choice for many diagnostic laboratories in the SARS-CoV-2 pandemic; and bait-capture hybridisation, which has been utilised in local HIV outbreaks. These techniques could be applied for near-real-time HIV and HCV surveillance, informing public health strategies that will be key to achieving 2030 targets.

Optimized phylogenetic clustering of HIV-1 sequence data for public health applications

Clusters of genetically similar infections suggest rapid transmission and may indicate priorities for public health action or reveal underlying epidemiological processes. However, clusters often require user-defined thresholds and are sensitive to non-epidemiological factors, such as non-random sampling. Consequently the ideal threshold for public health applications varies substantially across settings. Here, we show a method which selects optimal thresholds for phylogenetic (subset tree) clustering based on population. We evaluated this method on HIV-1 pol datasets (n = 14, 221 sequences) from four sites in USA (Tennessee, Washington), Canada (Northern Alberta) and China (Beijing). Clusters were defined by tips descending from an ancestral node (with a minimum bootstrap support of 95%) through a series of branches, each with a length below a given threshold. Next, we used pplacer to graft new cases to the fixed tree by maximum likelihood. We evaluated the effect of varying branch-length thresholds on cluster growth as a count outcome by fitting two Poisson regression models: a null model that predicts growth from cluster size, and an alternative model that includes mean collection date as an additional covariate. The alternative model was favoured by AIC across most thresholds, with optimal (greatest difference in AIC) thresholds ranging 0.007-0.013 across sites. The range of optimal thresholds was more variable when re-sampling 80% of the data by location (IQR 0.008 - 0.016, n = 100 replicates). Our results use prospective phylogenetic cluster growth and suggest that there is more variation in effective thresholds for public health than those typically used in clustering studies.

Incorporating Within-Host Diversity in Phylogenetic Analyses for Detecting Clusters of New HIV Diagnoses

Background

Phylogenetic analyses of HIV sequences are used to detect clusters and inform public health interventions. Conventional approaches summarize within-host HIV diversity with a single consensus sequence per host of the pol gene, obtained from Sanger or next-generation sequencing (NGS). There is growing recognition that this approach discards potentially important information about within-host sequence variation, which can impact phylogenetic inference. However, whether alternative summary methods that incorporate intra-host variation impact phylogenetic inference of transmission network features is unknown.

Methods

We introduce profile sampling, a method to incorporate within-host NGS sequence diversity into phylogenetic HIV cluster inference. We compare this approach to Sanger- and NGS-derived pol and near-whole-genome consensus sequences and evaluate its potential benefits in identifying molecular clusters among all newly-HIV-diagnosed individuals over six months at the largest HIV center in Rhode Island.

Results

Profile sampling cluster inference demonstrated that within-host viral diversity impacts phylogenetic inference across individuals, and that consensus sequence approaches can obscure both magnitude and effect of these impacts. Clustering differed between Sanger- and NGS-derived consensus and profile sampling sequences, and across gene regions.

Discussion

Profile sampling can incorporate within-host HIV diversity captured by NGS into phylogenetic analyses. This additional information can improve robustness of cluster detection.

Sequence Length of HIV-1 Subtype B Increases over Time: Analysis of a Cohort of Patients with Hemophilia over 30 Years

We aimed to investigate whether the sequence length of HIV-1 increases over time. We performed a longitudinal analysis of full-length coding region sequences (FLs) during an HIV-1 outbreak among patients with hemophilia and local controls infected with the Korean subclade B of HIV-1 (KSB). Genes were amplified by overlapping RT-PCR or nested PCR and subjected to direct sequencing. Overall, 141 FLs were sequentially determined over 30 years in 62 KSB-infected patients. Phylogenetic analysis indicated that within KSB, two FLs from plasma donors O and P comprised two clusters, together with 8 and 12 patients with hemophilia, respectively. Signature pattern analysis of the KSB of HIV-1 revealed 91 signature nucleotide residues (1.1%). In total, 48 and 43 signature nucleotides originated from clusters O and P, respectively. Six positions contained 100% specific nucleotide(s) in clusters O and P. In-depth FL analysis for over 30 years indicated that the KSB FL significantly increased over time before combination antiretroviral therapy (cART) and decreased with cART. This increase occurred due to the significant increase in env and nef genes, originating in the variable regions of both genes. The increase in sequence length of HIV-1 over time suggests an evolutionary direction.

Mapping of HIV-1C Transmission Networks Reveals Extensive Spread of Viral Lineages Across Villages in Botswana Treatment-as-Prevention Trial

BACKGROUND

Phylogenetic mapping of HIV-1 lineages circulating across defined geographical locations is promising for better understanding HIV transmission networks to design optimal prevention interventions.

METHODS

We obtained near full-length HIV-1 genome sequences from people living with HIV (PLWH), including participants on antiretroviral treatment in the Botswana Combination Prevention Project, conducted in 30 Botswana communities in 2013-2018. Phylogenetic relationships among viral sequences were estimated by maximum likelihood.

RESULTS

We obtained 6078 near full-length HIV-1C genome sequences from 6075 PLWH. We identified 984 phylogenetically distinct HIV-1 lineages (molecular HIV clusters) circulating in Botswana by mid-2018, with 2-27 members per cluster. Of these, dyads accounted for 62%, approximately 32% (n = 316) were found in single communities, and 68% (n = 668) were spread across multiple communities. Men in clusters were approximately 3 years older than women (median age 42 years, vs 39 years; P < .0001). In 65% of clusters, men were older than women, while in 35% of clusters women were older than men. The majority of identified viral lineages were spread across multiple communities.

CONCLUSIONS

A large number of circulating phylogenetically distinct HIV-1C lineages (molecular HIV clusters) suggests highly diversified HIV transmission networks across Botswana communities by 2018.

Empirical comparison of analytical approaches for identifying molecular HIV-1 clusters

Public health interventions guided by clustering of HIV-1 molecular sequences may be impacted by choices of analytical approaches. We identified commonly-used clustering analytical approaches, applied them to 1886 HIV-1 Rhode Island sequences from 2004-2018, and compared concordance in identifying molecular HIV-1 clusters within and between approaches. We used strict (topological support ≥ 0.95; distance 0.015 substitutions/site) and relaxed (topological support 0.80-0.95; distance 0.030-0.045 substitutions/site) thresholds to reflect different epidemiological scenarios. We found that clustering differed by method and threshold and depended more on distance than topological support thresholds. Clustering concordance analyses demonstrated some differences across analytical approaches, with RAxML having the highest (91%) mean summary percent concordance when strict thresholds were applied, and three (RAxML-, FastTree regular bootstrap- and IQ-Tree regular bootstrap-based) analytical approaches having the highest (86%) mean summary percent concordance when relaxed thresholds were applied. We conclude that different analytical approaches can yield diverse HIV-1 clustering outcomes and may need to be differentially used in diverse public health scenarios. Recognizing the variability and limitations of commonly-used methods in cluster identification is important for guiding clustering-triggered interventions to disrupt new transmissions and end the HIV epidemic.

Factors influencing HIV-1 phylogenetic clustering

PURPOSE OF REVIEW

A major goal of public health in relation to HIV/AIDS is to prevent new transmissions in communities. Phylogenetic techniques have improved our understanding of the structure and dynamics of HIV transmissions. However, there is still no consensus about phylogenetic methodology, sampling coverage, gene target and/or minimum fragment size.

RECENT FINDINGS

Several studies use a combined methodology, which includes both a genetic or patristic distance cut-off and a branching support threshold to identify phylogenetic clusters. However, the choice about these thresholds remains an inherently subjective process, which affects the results of these studies. There is still a lack of consensus about the genomic region and the size of fragments that should be used, although there seems to be emerging a consensus that using longer segments, allied with the use of a realistic model of evolution and a codon alignment, increases the likelihood of inferring true transmission clusters. The pol gene is still the most used genomic region, but recent studies have suggested that whole genomes and/or sequences from nef and gp41 are also good targets for cluster reconstruction.

SUMMARY

The development and application of standard methodologies for phylogenetic clustering analysis will advance our understanding of factors associated with HIV transmission. This will lead to the design of more precise public health interventions.

A Short-Term Assessment of Nascent HIV-1 Transmission Clusters Among Newly Diagnosed Individuals Using Envelope Sequence-Based Phylogenetic Analyses

The identification of transmission clusters (TCs) of HIV-1 using phylogenetic analyses can provide insights into viral transmission network and help improve prevention strategies. We compared the use of partial HIV-1 envelope fragment of 1,070 bp with its loop 3 (108 bp) to determine its utility in inferring HIV-1 transmission clustering. Serum samples of recently (n = 106) and chronically (n = 156) HIV-1-infected patients with status confirmed were sequenced. HIV-1 envelope nucleotide-based phylogenetic analyses were used to infer HIV-1 TCs. Those were constructed using ClusterPickerGUI_1.2.3 considering a pairwise genetic distance of ≤10% threshold. Logistic regression analyses were used to examine the relationship between the demographic factors that were likely associated with HIV-1 clustering. Ninety-eight distinct consensus envelope sequences were subjected to phylogenetic analyses. Using a partial envelope fragment sequence, 42 sequences were grouped into 15 distinct small TCs while the V3 loop reproduces 10 clusters. The agreement between the partial envelope and the V3 loop fragments was significantly moderate with a Cohen's kappa (κ) coefficient of 0.59, p < .00001. The mean age (<38.8 years) and HIV-1 B subtype are two factors identified that were significantly associated with HIV-1 transmission clustering in the cohort, odds ratio (OR) = 0.25, 95% confidence interval (CI, 0.04-0.66), p = .002 and OR: 0.17, 95% CI (0.10-0.61), p = .011, respectively. The present study confirms that a partial fragment of the HIV-1 envelope sequence is a better predictor of transmission clustering. However, the loop 3 segment may be useful in screening purposes and may be more amenable to integration in surveillance programs.

Surveillance of transmitted HIV-1 antiretroviral drug resistance in the context of decentralized HIV care in Senegal and the Ebola outbreak in Guinea

Objectives

Disruption in HIV care provision may enhance the development and spread of drug resistance due to inadequate antiretroviral therapy. This study thus determined the prevalence of HIV-1 transmitted drug resistance (TDR) in settings of decentralized therapy and care in Senegal and, the Ebola outbreak in Guinea. Antiretroviral-naïve patients were enrolled following a modified WHO TDR Threshold Survey method, implemented in Senegal (January–March 2015) and Guinea (August–September 2015). Plasma and dried blood spots specimens, respectively from Senegalese (n = 69) and Guinean (n = 50) patients, were collected for direct sequencing of HIV-1 pol genes. The Stanford Calibrated Population Resistance program v6.0 was used for Surveillance Drug Resistance Mutations (SDRMs).

Results

Genotyping was successful from 54/69 (78.2%) and 31/50 (62.0%) isolates. In Senegal, TDR prevalence was 0% (mean duration since HIV diagnosis 4.08 ± 3.53 years). In Guinea, two patients exhibited SDRMs M184V (NRTI), T215F (TAM) and, G190A (NNRTI), respectively. TDR prevalence at this second site, however, could not be ascertained because of low sample size. Phylogenetic inference confirmed CRF02_AG predominance in Senegal (62.96%) and Guinea (77.42%). TDR prevalence in Senegal remains extremely low suggesting improved control measures. Continuous surveillance in both settings is mandatory and, should be done closest to diagnosis/transmission time and with larger sample size.

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.

Genetic characterization of human immunodeficiency virus type 1 transmission in the Middle East and North Africa

BACKGROUND

The HIV-1 spread in the Middle East and North Africa (MENA) has not been previously characterised using the phylogenetic approach. The aim of the current study was to investigate the genetic diversity and domestic transmission of HIV-1 in the MENA.

METHODS

A total of 2036 HIV-1 sequences available in Genbank and collected in the MENA during 1988-2016 were used together with 715 HIV-1 reference sequences that were retrieved from Genbank based on genetic similarity with the MENA sequences. The REGA and COMET tools were used to determine HIV-1 subtypes and circulating recombinant forms. Maximum Likelihood and Bayesian phylogenetic analyses were used to identify and date HIV-1 transmission clusters.

RESULTS

At least 21 HIV-1 subtypes and recombinant forms were prevalent in the MENA. Subtype B was the most common variant (39%), followed by CRF35_AD (19%) and CRF02_AG (14%). The most common genetic region was pol, and 675 partial pol sequences (average of 1005 bp) were eligible for detailed phylogenetic analysis. Fifty-four percent of the MENA sequences formed HIV-1 transmission clusters. Whereas numerous clusters were country-specific, some clusters indicated transmission links between countries for subtypes B, C and CRF02_AG. This was more common in North Africa compared with the Middle East (p < 0.001). Recombinant forms had a larger proportion of clustering compared to pure subtypes (p < 0.001). The largest MENA clusters dated back to 1991 (an Algerian CRF06_cpx cluster of 43 sequences) and 2002 (a Tunisian CRF02_AG cluster of 48 sequences).

CONCLUSIONS

We found an extensive HIV-1 diversity in the MENA and a high proportion of sequences in transmission clusters. This study highlights the need for preventive measures in the MENA to limit HIV-1 spread in this region.

Recent advances in understanding HIV evolution

The human immunodeficiency virus (HIV) evolves rapidly owing to the combined activity of error-prone reverse transcriptase, recombination, and short generation times, leading to extensive viral diversity both within and between hosts. This diversity is a major contributing factor in the failure of the immune system to eradicate the virus and has important implications for the development of suitable drugs and vaccines to combat infection. This review will discuss the recent technological advances that have shed light on HIV evolution and will summarise emerging concepts in this field.

Using nearly full-genome HIV sequence data improves phylogeny reconstruction in a simulated epidemic

HIV molecular epidemiology studies analyse viral pol gene sequences due to their availability, but whole genome sequencing allows to use other genes. We aimed to determine what gene(s) provide(s) the best approximation to the real phylogeny by analysing a simulated epidemic (created as part of the PANGEA_HIV project) with a known transmission tree. We sub-sampled a simulated dataset of 4662 sequences into different combinations of genes (gag-pol-env, gag-pol, gag, pol, env and partial pol) and sampling depths (100%, 60%, 20% and 5%), generating 100 replicates for each case. We built maximum-likelihood trees for each combination using RAxML (GTR + Γ), and compared their topologies to the corresponding true tree’s using CompareTree. The accuracy of the trees was significantly proportional to the length of the sequences used, with the gag-pol-env datasets showing the best performance and gag and partial pol sequences showing the worst. The lowest sampling depths (20% and 5%) greatly reduced the accuracy of tree reconstruction and showed high variability among replicates, especially when using the shortest gene datasets. In conclusion, using longer sequences derived from nearly whole genomes will improve the reliability of phylogenetic reconstruction. With low sample coverage, results can be highly variable, particularly when based on short sequences.

Multiplexed next-generation sequencing and de novo assembly to obtain near full-length HIV-1 genome from plasma virus

Analysing the HIV-1 near full-length genome (HIV-NFLG) facilitates new understanding into the diversity of virus population dynamics at individual or population level. In this study we developed a simple but high-throughput next generation sequencing (NGS) protocol for HIV-NFLG using clinical specimens and validated the method against an external quality control (EQC) panel. Clinical specimens (n=105) were obtained from three cohorts from two highly conserved HIV-1C epidemics (India and Ethiopia) and one diverse epidemic (Sweden). Additionally an EQC panel (n=10) was used to validate the protocol. HIV-NFLG was performed amplifying the HIV-genome (Gag-to-nef) in two fragments. NGS was performed using the Illumina HiSeq2500 after multiplexing 24 samples, followed by de novo assembly in Iterative Virus Assembler or VICUNA. Subtyping was carried out using several bioinformatics tools. Amplification of HIV-NFLG has 90% (95/105) success-rate in clinical specimens. NGS was successful in all clinical specimens (n=45) and EQA samples (n=10) attempted. The mean error for mutations for the EQC panel viruses were <1%. Subtyping identified two as A1C recombinant. Our results demonstrate the feasibility of a simple NGS-based HIV-NFLG that can potentially be used in the molecular surveillance for effective identification of subtypes and transmission clusters for operational public health intervention.

Phylogenetic Analysis of Ethiopian HIV-1 Subtype C Near Full-Length Genomes Reveals High Intrasubtype Diversity and a Strong Geographical Cluster

In this study, we characterize HIV-1 subtype C (HIV-1C) strains at the near full-length genome (NFLG) level and perform genotypic drug resistance testing (GRT) and genotypic tropism testing (GTT) from Ethiopia (HIV-1CET). Plasma samples (n = 150) were obtained from therapy-naive individuals residing in Addis Ababa, Ethiopia in 2008. HIV-NFLG was performed in a subset of patients (n = 30). GRT (pol) and GTT (V3 env) were performed using in-house methods. GTT was analyzed by PhenoSeq-C. The phylogenetic analysis of the NLFG identified two separate clusters of HIV-1CET, although all strains formed one large overarching cluster together. At NFLG, greater diversity was found among HIV-1CET strains compared to HIV-1C strains from other geographical locations. The geographic clustering was weak in the small subgenomic (pol and env) regions. The primary drug-resistant mutations were identified at a low level (<5%). GTT identified that 12% (12/102) of the patients were predicted to be harboring X4-tropic or both R5/X4-tropic viruses.

Phylodynamic analysis of HIV sub-epidemics in Mochudi, Botswana

Southern Africa continues to be the epicenter of the HIV/AIDS epidemic. This HIV-1 subtype C epidemic has a predominantly heterosexual mode of virus transmission and high (>15%) HIV prevalence among adults. The epidemiological dynamics of the HIV-1C epidemic in southern Africa are still poorly understood. Here, we aim at a better understanding of HIV transmission dynamics by analyzing HIV-1 subtype C sequences from Mochudi, a peri-urban village in Botswana. HIV-1C env gene sequences (gp120 V1C5) were obtained through enhanced household-based HIV testing and counseling in Mochudi. More than 1200 sequences were generated and phylogenetically distinct sub-epidemics within Mochudi identified. The Bayesian birth-death skyline plot was used to estimate the effective reproductive number, R, and the timing of virus transmission, to classify sub-epidemics as "acute" (those with recent viral transmissions) or "historic" (those without recent viral transmissions). We identified two of the 15 sub-epidemics as "acute." The median estimates of R among the clusters ranged from 0.72 to 1.77. The majority of HIV lineages, 11 out of 15 clusters with 5+ members, appear to have been introduced to Mochudi between 1996 and 2002. The median peak duration of viral transmissions was 7.1 years (range 2.9-9.7 years). The median life span of identified HIV sub-epidemics, i.e., the time between the inferred epidemic origin and its most recent sample, was 13.1 years (range 10.2-22.1 years). Most viral transmissions within the sub-epidemics occurred between 1997 and 2007. The time period during which infected people are infectious appears to have decreased since the introduction of the national ART program in Botswana. Real-time HIV genotyping and breaking down local HIV epidemics into phylogenetically distinct sub-epidemics may help to reveal the structure and dynamics of HIV transmission networks in communities, and aid in the design of targeted interventions for members of the acute sub-epidemics that likely fuel local HIV/AIDS epidemics.

Long-Range HIV Genotyping Using Viral RNA and Proviral DNA for Analysis of HIV Drug Resistance and HIV Clustering

The goal of the study was to improve the methodology of HIV genotyping for analysis of HIV drug resistance and HIV clustering. Using the protocol of Gall et al. (A. Gall, B. Ferns, C. Morris, S. Watson, M. Cotten, M. Robinson, N. Berry, D. Pillay, and P. Kellam, J Clin Microbiol 50:3838-3844, 2012, doi:10.1128/JCM.01516-12), we developed a robust methodology for amplification of two large fragments of viral genome covering about 80% of the unique HIV-1 genome sequence. Importantly, this method can be applied to both viral RNA and proviral DNA amplification templates, allowing genotyping in HIV-infected subjects with suppressed viral loads (e.g., subjects on antiretroviral therapy [ART]). The two amplicons cover critical regions across the HIV-1 genome (including pol and env), allowing analysis of mutations associated with resistance to protease inhibitors, reverse transcriptase inhibitors (nucleoside reverse transcriptase inhibitors [NRTIs] and nonnucleoside reverse transcriptase inhibitors [NNRTIs]), integrase strand transfer inhibitors, and virus entry inhibitors. The two amplicons generated span 7,124 bp, providing substantial sequence length and numbers of informative sites for comprehensive phylogenic analysis and greater refinement of viral linkage analyses in HIV prevention studies. The long-range HIV genotyping from proviral DNA was successful in about 90% of 212 targeted blood specimens collected in a cohort where the majority of patients had suppressed viral loads, including 65% of patients with undetectable levels of HIV-1 RNA loads. The generated amplicons could be sequenced by different methods, such as population Sanger sequencing, single-genome sequencing, or next-generation ultradeep sequencing. The developed method is cost-effective-the cost of the long-range HIV genotyping is under $140 per subject (by Sanger sequencing)-and has the potential to enable the scale up of public health HIV prevention interventions.