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

Determinants of HIV-1 transmission clusters and transmitted drug resistance in men who have sex with men: A multicenter study in Portugal (2014-2019)

INTRODUCTION

In the EU/EEA, men who have sex with men (MSM) is a priority group for the prevention and control of HIV-1 infection. In Portugal, the 2023 HIV incidence rate was 8.2 per 100,000 inhabitants, with 876 new infections, 41.7% in MSM. We aim to characterize HIV-1 transmission clusters (TC) and transmitted drug resistance (TDR) and its sociodemographic, behavioral, clinical, and viral genomic determinants in MSM newly diagnosed in Portugal between 2014 and 2019.

METHODS

A total of 340 MSM newly diagnosed with HIV-1 infection at 17 hospitals in Portugal were included. TC was identified with branch support ≥90% and 1.5% genetic distance. Logistic regression models were used to examine factors associated with TC and TDR.

RESULTS

We identified 38 TC with 104 MSM, which includes 81 (26.6%) of the 305 MSM from our sample included in cluster analysis. The overall prevalence of TDR was 8.2%. Only HIV-1 subtype C was significantly associated with TDR. Overall, 10.5% of the clusters had at least 1 surveillance drug resistance mutation. There was no significant difference in the prevalence of TDR or the proportion of Portuguese and migrant MSM inside and outside clusters. Age at diagnosis, district of residence, unprotected sex with a woman, HIV testing, presenter status, and HIV-1 subtype were significantly associated with TC.

CONCLUSION

Specific subgroups of MSM are contributing to HIV-1 clustered transmission in Portugal. However, no association was found between TDR and sociodemographic or behavioral factors. Directed prevention measures should focus on those subgroups.

Quantifying prevalence and risk factors of HIV multiple infection in Uganda from population-based deep-sequence data

People living with HIV can acquire secondary infections through a process called superinfection, giving rise to simultaneous infection with genetically distinct variants (multiple infection). Multiple infection provides the necessary conditions for the generation of novel recombinant forms of HIV and may worsen clinical outcomes and increase the rate of transmission to HIV seronegative sexual partners. To date, studies of HIV multiple infection have relied on insensitive bulk-sequencing, labor intensive single genome amplification protocols, or deep-sequencing of short genome regions. Here, we identified multiple infections in whole-genome or near whole-genome HIV RNA deep-sequence data generated from plasma samples of 2,029 people living with viremic HIV who participated in the population-based Rakai Community Cohort Study (RCCS). We estimated individual- and population-level probabilities of being multiply infected and assessed epidemiological risk factors using the novel Bayesian deep-phylogenetic multiple infection model (deep - phyloMI) which accounts for bias due to partial sequencing success and false-negative and false-positive detection rates. We estimated that between 2010 and 2020, 4.09% (95% highest posterior density interval (HPD) 2.95%-5.45%) of RCCS participants with viremic HIV multiple infection at time of sampling. Participants living in high-HIV prevalence communities along Lake Victoria were 2.33-fold (95% HPD 1.3-3.7) more likely to harbor a multiple infection compared to individuals in lower prevalence neighboring communities. This work introduces a high-throughput surveillance framework for identifying people with multiple HIV infections and quantifying population-level prevalence and risk factors of multiple infection for clinical and epidemiological investigations.

Molecular cluster, transmission characteristics, origin and dynamics analysis of HIV-1 CRF59_01B in China: A molecular epidemiology study

PURPOSE

This study investigated for the HIV-1 CRF59_01B epidemic's spatiotemporal dynamics and its transmission networks in China.

METHODS

Between 2007 and 2020, a total of 250 partial pol gene sequences of HIV-1 CRF59_01B were collected from four regions (10 Chinese provinces). Phylogenetic tree construction and cluster identification were then performed. The Bayesian skyline and birth-death susceptible-infected-removed models were employed for the phylodynamic analyses of subtypes and large clusters, respectively. Phylogenetic analyses and trait diffusion of these sequences were performed using Bayesian phylogenetic methods (beast-classic package). Distance-based molecular network analyses were performed to identify putative relationships.

RESULTS

Using a genetic distance threshold of 1.3 %, We identified 45 clusters that included 62.40 % (156/250) of the sequences. Three clusters (6.67 %, 3/45) had 10 or more sequences, and were considered "large clusters". Six clusters (13.33 %) included sequences from different regions (Southeast, Northeast, Southeast, and Central China). Thirteen clusters (28.89 %) included sequences of men who had sex with men only, three clusters (6.67 %) included sequences of heterosexuals only, and 12 clusters (26.67 %) included sequences of both groups. The substitution rate of CRF59_01B was 1.91 × 10-3 substitutions per site per year [95 % highest posterior density (HPD) interval: 1.39 × 10-3-2.49 × 10-3)], the time to the most recent common ancestor of CRF59_01B was to be 1992.83 (95 % HPD: 1977.97-2002.81). A Bayesian skyline plot revealed that the effective population size of CRF59_01B increased from 2000 to 2015 and remained stable after 2015. The large clusters showed continuous growth from 2013 to 2020. Phylogeographic analysis showed that CRF59_01B B most likely originated in Southeast China, with a posterior probability of 97.44 %, and then spread to other regions.

CONCLUSIONS

Our study revealed the temporal and geographical origins of HIV-1 CRF59_01B as well as the process of transmission among various regions and risk groups in China, which can help develop targeted HIV prevention strategies.

Expectation-Maximization enables Phylogenetic Dating under a Categorical Rate Model

Dating phylogenetic trees to obtain branch lengths in time units is essential for many downstream applications but has remained challenging. Dating requires inferring substitution rates that can change across the tree. While we can assume to have information about a small subset of nodes from the fossil record or sampling times (for fast-evolving organisms), inferring the ages of the other nodes essentially requires extrapolation and interpolation. Assuming a distribution of branch rates, we can formulate dating as a constrained maximum likelihood (ML) estimation problem. While ML dating methods exist, their accuracy degrades in the face of model misspecification, where the assumed parametric statistical distribution of branch rates vastly differs from the true distribution. Notably, most existing methods assume rigid, often unimodal, branch rate distributions. A second challenge is that the likelihood function involves an integral over the continuous domain of the rates, often leading to difficult non-convex optimization problems. To tackle both challenges, we propose a new method called Molecular Dating using Categorical-models (MD-Cat). MD-Cat uses a categorical model of rates inspired by non-parametric statistics and can approximate a large family of models by discretizing the rate distribution into k categories. Under this model, we can use the Expectation-Maximization algorithm to co-estimate rate categories and branch lengths in time units. Our model has fewer assumptions about the true distribution of branch rates than parametric models such as Gamma or LogNormal distribution. Our results on two simulated and real datasets of Angiosperms and HIV and a wide selection of rate distributions show that MD-Cat is often more accurate than the alternatives, especially on datasets with exponential or multimodal rate distributions.

Optimization of genetic distance threshold for inferring the CRF01_AE molecular network based on next-generation sequencing

Introduction

HIV molecular network based on genetic distance (GD) has been extensively utilized. However, the GD threshold for the non-B subtype differs from that of subtype B. This study aimed to optimize the GD threshold for inferring the CRF01_AE molecular network.

Methods

Next-generation sequencing data of partial CRF01_AE pol sequences were obtained for 59 samples from 12 transmission pairs enrolled from a high-risk cohort during 2009 and 2014. The paired GD was calculated using the Tamura-Nei 93 model to infer a GD threshold range for HIV molecular networks.

Results

2,019 CRF01_AE pol sequences and information on recent HIV infection (RHI) from newly diagnosed individuals in Shenyang from 2016 to 2019 were collected to construct molecular networks to assess the ability of the inferred GD thresholds to predict recent transmission events. When HIV transmission occurs within a span of 1-4 years, the mean paired GD between the sequences of the donor and recipient within the same transmission pair were as follow: 0.008, 0.011, 0.013, and 0.023 substitutions/site. Using these four GD thresholds, it was found that 98.9%, 96.0%, 88.2%, and 40.4% of all randomly paired GD values from 12 transmission pairs were correctly identified as originating from the same transmission pairs. In the real world, as the GD threshold increased from 0.001 to 0.02 substitutions/site, the proportion of RHI within the molecular network gradually increased from 16.6% to 92.3%. Meanwhile, the proportion of links with RHI gradually decreased from 87.0% to 48.2%. The two curves intersected at a GD of 0.008 substitutions/site.

Discussion

A suitable range of GD thresholds, 0.008-0.013 substitutions/site, was identified to infer the CRF01_AE molecular transmission network and identify HIV transmission events that occurred within the past three years. This finding provides valuable data for selecting an appropriate GD thresholds in constructing molecular networks for non-B subtypes.

Reconstructing the phylodynamic history and geographic spread of the CRF01_AE-predominant HIV-1 epidemic in the Philippines from PR/RT sequences sampled from 2008 to 2018

The Philippines has had a rapidly growing human immunodeficiency virus (HIV) epidemic with a shift in the prevalent subtype from B to CRF01_AE. However, the phylodynamic history of CRF01_AE in the Philippines has yet to be reconstructed. We conducted a descriptive retrospective study reconstructing the history of HIV-1 CRF01_AE transmissions in the Philippines through molecular epidemiology. Partial polymerase sequences (n = 1144) collected between 2008 and 2018 from three island groups were collated from the Research Institute for Tropical Medicine drug resistance genotyping database. Estimation of the time to the most recent common ancestor (tMRCA), effective reproductive number (Re), effective viral population size (Ne), relative migration rates, and geographic spread of CRF01_AE was performed with BEAST. Re and Ne were compared between CRF01_AE and B. Most CRF01_AE sequences formed a single clade with a tMRCA of June 1996 [95 per cent highest posterior density (HPD): December 1991, October 1999]. An increasing CRF01_AE Ne was observed from the tMRCA to 2013. The CRF01_AE Re reached peaks of 2.46 [95 per cent HPD: 1.76, 3.27] in 2007 and 2.52 [95 per cent HPD: 1.83, 3.34] in 2015. A decrease of CRF01_AE Re occurred in the intervening years of 2007 to 2011, reaching as low as 1.43 [95 per cent HPD: 1.06, 1.90] in 2011, followed by a rebound. The CRF01_AE epidemic most likely started in Luzon and then spread to the other island groups of the country. Both CRF01_AE and Subtype B exhibited similar patterns of Re fluctuation over time. These results characterize the subtype-specific phylodynamic history of the largest CRF01_AE cluster in the Philippines, which contextualizes and may inform past, present, and future public health measures toward controlling the HIV epidemic in the Philippines.

Evolutionary implications of SARS-CoV-2 vaccination for the future design of vaccination strategies

Once the first SARS-CoV-2 vaccine became available, mass vaccination was the main pillar of the public health response to the COVID-19 pandemic. It was very effective in reducing hospitalizations and deaths. Here, we discuss the possibility that mass vaccination might accelerate SARS-CoV-2 evolution in antibody-binding regions compared to natural infection at the population level. Using the evidence of strong genetic variation in antibody-binding regions and taking advantage of the similarity between the envelope proteins of SARS-CoV-2 and influenza, we assume that immune selection pressure acting on these regions of the two viruses is similar. We discuss the consequences of this assumption for SARS-CoV-2 evolution in light of mathematical models developed previously for influenza. We further outline the implications of this phenomenon, if our assumptions are confirmed, for the future design of SARS-CoV-2 vaccination strategies.

Phylodynamics of HIV in the Mexico City Metropolitan Region

Evolutionary analyses of viral sequences can provide insights into transmission dynamics, which in turn can optimize prevention interventions. Here, we characterized the dynamics of HIV transmission within the Mexico City metropolitan area. HIV pol sequences from persons recently diagnosed at the largest HIV clinic in Mexico City (between 2016 and 2021) were annotated with demographic/geographic metadata. A multistep phylogenetic approach was applied to identify putative transmission clades. A data set of publicly available sequences was used to assess international introductions. Clades were analyzed with a discrete phylogeographic model to evaluate the timing and intensity of HIV introductions and transmission dynamics among municipalities in the region. A total of 6,802 sequences across 96 municipalities (5,192 from Mexico City and 1,610 from the neighboring State of Mexico) were included (93.6% cisgender men, 5.0% cisgender women, and 1.3% transgender women); 3,971 of these sequences formed 1,206 clusters, involving 78 municipalities, including 89 clusters of ≥10 sequences. Discrete phylogeographic analysis revealed (i) 1,032 viral introductions into the region, over one-half of which were from the United States, and (ii) 354 migration events between municipalities with high support (adjusted Bayes factor of ≥3). The most frequent viral migrations occurred between northern municipalities within Mexico City, i.e., Cuauhtémoc to Iztapalapa (5.2% of events), Iztapalapa to Gustavo A. Madero (5.4%), and Gustavo A. Madero to Cuauhtémoc (6.5%). Our analysis illustrates the complexity of HIV transmission within the Mexico City metropolitan area but also identifies a spatially active transmission area involving a few municipalities in the north of the city, where targeted interventions could have a more pronounced effect on the entire regional epidemic. IMPORTANCE Phylogeographic investigation of the Mexico City HIV epidemic illustrates the complexity of HIV transmission in the region. An active transmission area involving a few municipalities in the north of the city, with transmission links throughout the region, is identified and could be a location where targeted interventions could have a more pronounced effect on the entire regional epidemic, compared with those dispersed in other manners.

Molecular Biology and Diversification of Human Retroviruses

Studies of retroviruses have led to many extraordinary discoveries that have advanced our understanding of not only human diseases, but also molecular biology as a whole. The most recognizable human retrovirus, human immunodeficiency virus type 1 (HIV-1), is the causative agent of the global AIDS epidemic and has been extensively studied. Other human retroviruses, such as human immunodeficiency virus type 2 (HIV-2) and human T-cell leukemia virus type 1 (HTLV-1), have received less attention, and many of the assumptions about the replication and biology of these viruses are based on knowledge of HIV-1. Existing comparative studies on human retroviruses, however, have revealed that key differences between these viruses exist that affect evolution, diversification, and potentially pathogenicity. In this review, we examine current insights on disparities in the replication of pathogenic human retroviruses, with a particular focus on the determinants of structural and genetic diversity amongst HIVs and HTLV.

Molecular Epidemiology of HIV-1 in Oryol Oblast, Russia

The HIV/AIDS epidemic in Russia is growing, with approximately 100,000 people infected annually. Molecular epidemiology can provide insight into the structure and dynamics of the epidemic. However, its applicability in Russia is limited by the weakness of genetic surveillance, as viral genetic data are only available for <1 per cent of cases. Here, we provide a detailed description of the HIV-1 epidemic for one geographic region of Russia, Oryol Oblast, by collecting and sequencing viral samples from about a third of its known HIV-positive population (768 out of 2,157 patients). We identify multiple introductions of HIV-1 into Oryol Oblast, resulting in eighty-two transmission lineages that together comprise 66 per cent of the samples. Most introductions are of subtype A (315/332), the predominant HIV-1 subtype in Russia, followed by CRF63 and subtype B. Bayesian analysis estimates the effective reproduction number R_e for subtype A at 2.8 [1.7–4.4], in line with a growing epidemic. The frequency of CRF63 has been growing more rapidly, with the median R_e of 11.8 [4.6–28.7], in agreement with recent reports of this variant rising in frequency in some regions of Russia. In contrast to the patterns described previously in European and North American countries, we see no overrepresentation of males in transmission lineages; meanwhile, injecting drug users are overrepresented in transmission lineages. This likely reflects the structure of the HIV-1 epidemic in Russia dominated by heterosexual and, to a smaller extent, people who inject drugs transmission. Samples attributed to men who have sex with men (MSM) transmission are associated with subtype B and are less prevalent than expected from the male-to-female ratio for this subtype, suggesting underreporting of the MSM transmission route. Together, our results provide a high-resolution description of the HIV-1 epidemic in Oryol Oblast, Russia, characterized by frequent interregional transmission, rapid growth of the epidemic, and rapid displacement of subtype A with the recombinant CRF63 variant.

Exploring the Evolutionary History and Phylodynamics of Human Immunodeficiency Virus Type 1 Outbreak From Unnao, India Using Phylogenetic Approach

Certain rural and semiurban settings in the Unnao district, Uttar Pradesh, India observed an unprecedented increase in the detection of HIV cases during July 2017. Subsequent investigations through health camps and a follow-up case-control study attributed the outbreak to the unsafe injection exposures during treatment. In this study, we have undertaken a secondary analysis to understand the phylogenetic aspects of the outbreak-associated HIV-1 sequences along with the origin and phylodynamics of these sequences. The initial phylogenetic analysis indicated separate monophyletic grouping and there was no mixing of outbreak-associated sequences with sequences from other parts of India. Transmission network analysis using distance-based and non-distance-based methods revealed the existence of transmission clusters within the monophyletic Unnao clade. The median time to the most recent common ancestor (tMRCA) for sequences from Unnao using the pol gene region was observed to be 2011.87 [95% highest posterior density (HPD): 2010.09–2013.53], while the estimates using envelope (env) gene region sequences traced the tMRCA to 2010.33 (95% HPD: 2007.76–2012.99). Phylodynamics estimates demonstrated that the pace of this local epidemic has slowed down in recent times before the time of sampling, but was certainly on an upward track since its inception till 2014.

Large Evolutionary Rate Heterogeneity among and within HIV-1 Subtypes and CRFs

HIV-1 is a fast-evolving, genetically diverse virus presently classified into several groups and subtypes. The virus evolves rapidly because of an error-prone polymerase, high rates of recombination, and selection in response to the host immune system and clinical management of the infection. The rate of evolution is also influenced by the rate of virus spread in a population and nature of the outbreak, among other factors. HIV-1 evolution is thus driven by a range of complex genetic, social, and epidemiological factors that complicates disease management and prevention. Here, we quantify the evolutionary (substitution) rate heterogeneity among major HIV-1 subtypes and recombinants by analyzing the largest collection of HIV-1 genetic data spanning the widest possible geographical (100 countries) and temporal (1981–2019) spread. We show that HIV-1 substitution rates vary substantially, sometimes by several folds, both across the virus genome and between major subtypes and recombinants, but also within a subtype. Across subtypes, rates ranged 3.5-fold from 1.34 × 10⁻³ to 4.72 × 10⁻³ in env and 2.3-fold from 0.95 × 10⁻³ to 2.18 × 10⁻³ substitutions site⁻¹ year⁻¹ in pol. Within the subtype, 3-fold rate variation was observed in env in different human populations. It is possible that HIV-1 lineages in different parts of the world are operating under different selection pressures leading to substantial rate heterogeneity within and between subtypes. We further highlight how such rate heterogeneity can complicate HIV-1 phylodynamic studies, specifically, inferences on epidemiological linkage of transmission clusters based on genetic distance or phylogenetic data, and can mislead estimates about the timing of HIV-1 lineages.

Global Patterns of Recombination across Human Viruses

Viral recombination is a major evolutionary mechanism driving adaptation processes, such as the ability of host-switching. Understanding global patterns of recombination could help to identify underlying mechanisms and to evaluate the potential risks of rapid adaptation. Conventional approaches (e.g., those based on linkage disequilibrium) are computationally demanding or even intractable when sequence alignments include hundreds of sequences, common in viral data sets. We present a comprehensive analysis of recombination across 30 genomic alignments from viruses infecting humans. In order to scale the analysis and avoid the computational limitations of conventional approaches, we apply newly developed topological data analysis methods able to infer recombination rates for large data sets. We show that viruses, such as ZEBOV and MARV, consistently displayed low levels of recombination, whereas high levels of recombination were observed in Sarbecoviruses, HBV, HEV, Rhinovirus A, and HIV. We observe that recombination is more common in positive single-stranded RNA viruses than in negatively single-stranded RNA ones. Interestingly, the comparison across multiple viruses suggests an inverse correlation between genome length and recombination rate. Positional analyses of recombination breakpoints along viral genomes, combined with our approach, detected at least 39 nonuniform patterns of recombination (i.e., cold or hotspots) in 18 viral groups. Among these, noteworthy hotspots are found in MERS-CoV and Sarbecoviruses (at spike, Nucleocapsid and ORF8). In summary, we have developed a fast pipeline to measure recombination that, combined with other approaches, has allowed us to find both common and lineage-specific patterns of recombination among viruses with potential relevance in viral adaptation.

Priority Intervention Targets Identified Using an In-Depth Sampling HIV Molecular Network in a Non-Subtype B Epidemics Area

Molecular network analysis based on the genetic similarity of HIV-1 is increasingly used to guide targeted interventions. Nevertheless, there is a lack of experience regarding molecular network inferences and targeted interventions in combination with epidemiological information in areas with diverse epidemic strains of HIV-1.We collected 2,173 pol sequences covering 84% of the total newly diagnosed HIV-1 infections in Shenyang city, Northeast China, between 2016 and 2018. Molecular networks were constructed using the optimized genetic distance threshold for main subtypes obtained using sensitivity analysis of plausible threshold ranges. The transmission rates (TR) of each large cluster were assessed using Bayesian analyses. Molecular clusters with the characteristics of ≥5 newly diagnosed cases in 2018, high TR, injection drug users (IDUs), and transmitted drug resistance (TDR) were defined as priority clusters. Several HIV-1 subtypes were identified, with a predominance of CRF01_AE (71.0%, 1,542/2,173), followed by CRF07_BC (18.1%, 393/2,173), subtype B (4.5%, 97/2,173), other subtypes (2.6%, 56/2,173), and unique recombinant forms (3.9%, 85/2,173). The overall optimal genetic distance thresholds for CRF01_AE and CRF07_BC were both 0.007 subs/site. For subtype B, it was 0.013 subs/site. 861 (42.4%) sequences of the top three subtypes formed 239 clusters (size: 2-77 sequences), including eight large clusters (size ≥10 sequences). All the eight large clusters had higher TR (median TR = 52.4/100 person-years) than that of the general HIV infections in Shenyang (10.9/100 person-years). A total of ten clusters including 231 individuals were determined as priority clusters for targeted intervention, including eight large clusters (five clusters with≥5 newly diagnosed cases in 2018, one cluster with IDUs, and two clusters with TDR (K103N, Q58E/V179D), one cluster with≥5 newly diagnosed cases in 2018, and one IDUs cluster. In conclusion, a comprehensive analysis combining in-depth sampling HIV-1 molecular networks construction using subtype-specific optimal genetic distance thresholds, and baseline epidemiological information can help to identify the targets of priority intervention in an area epidemic for non-subtype B.

Deep Profiling Identifies Selection of Nonsynonymous Amino Acid Substitutions in HIV-1 Envelope During Early Infection

Understanding the evolutionary dynamics of the viruses within an individual at or near the moment of transmission can provide critical inputs for the design of an effective vaccine for HIV infection. In this study, high-throughput sequencing technology was employed to analyze the evolutionary rate in viruses obtained at a single time point from drug-naive recently infected infants and adults in the chronic stage of disease. Gene-wise nonsynonymous (pN) and synonymous (pS) mutation rates were estimated and compared between the two groups. Significant differences were observed in the evolutionary rates between viruses in the early and late stages of infection. Higher rates of adaptive mutations in the HIV-1 envelope gene (env) were found in the chronic viruses as compared with those in the early stages of HIV infection. Conversely, percentage of nonsynonymous substitutions in env was found to be higher in recently transmitted viruses. In addition, a positive correlation was found between mutation and the evolutionary rate, and infectivity titer in recent infection. Despite the small sample size, the study identified useful information about viral evolution on transmission-associated bottlenecks. The effect of intraindividual HIV-1 evolution at the population level was highly contemporary, and the higher percentage of nonsynonymous substitutions seen in env during recent HIV-1 infection has suggested a pattern of convergent evolution leading to a positive selection for survival fitness and disease progression.

Dynamics of HIV-1 Molecular Networks Reveal Effective Control of Large Transmission Clusters in an Area Affected by an Epidemic of Multiple HIV Subtypes

This study reconstructed molecular networks of human immunodeficiency virus (HIV) transmission history in an area affected by an epidemic of multiple HIV-1 subtypes and assessed the efficacy of strengthened early antiretroviral therapy (ART) and regular interventions in preventing HIV spread. We collected demographic and clinical data of 2221 treatment-naïve HIV-1–infected patients in a long-term cohort in Shenyang, Northeast China, between 2008 and 2016. HIV pol gene sequencing was performed and molecular networks of CRF01_AE, CRF07_BC, and subtype B were inferred using HIV-TRACE with separate optimized genetic distance threshold. We identified 168 clusters containing ≥ 2 cases among CRF01_AE-, CRF07_BC-, and subtype B-infected cases, including 13 large clusters (≥ 10 cases). Individuals in large clusters were characterized by younger age, homosexual behavior, more recent infection, higher CD4 counts, and delayed/no ART (P < 0.001). The dynamics of large clusters were estimated by proportional detection rate (PDR), cluster growth predictor, and effective reproductive number (R_e). Most large clusters showed decreased or stable during the study period, indicating that expansion was slowing. The proportion of newly diagnosed cases in large clusters declined from 30 to 8% between 2008 and 2016, coinciding with an increase in early ART within 6 months after diagnosis from 24 to 79%, supporting the effectiveness of strengthened early ART and continuous regular interventions. In conclusion, molecular network analyses can thus be useful for evaluating the efficacy of interventions in epidemics with a complex HIV profile.

Comparative Circulation Dynamics of the Five Main HIV Types in China

The HIV epidemic in China accounts for 3% of the global HIV incidence. We compared the patterns and determinants of interprovincial spread of the five most prevalent circulating types. HIV pol sequences sampled across China were used to identify relevant transmission networks of the five most relevant HIV-1 types (B and circulating recombinant forms [CRFs] CRF01_AE, CRF07_BC, CRF08_BC, and CRF55_01B) in China. From these, the dispersal history across provinces was inferred. A generalized linear model (GLM) was used to test the association between migration rates among provinces and several measures of human mobility. A total of 10,707 sequences were collected between 2004 and 2017 across 26 provinces, among which 1,962 are newly reported here. A mean of 18 (minimum and maximum, 1 and 54) independent transmission networks involving up to 17 provinces were identified. Discrete phylogeographic analysis largely recapitulates the documented spread of the HIV types, which in turn, mirrors within-China population migration flows to a large extent. In line with the different spatiotemporal spread dynamics, the identified drivers thereof were also heterogeneous but are consistent with a central role of human mobility. The comparative analysis of the dispersal dynamics of the five main HIV types circulating in China suggests a key role of large population centers and developed transportation infrastructures as hubs of HIV dispersal. This advocates for coordinated public health efforts in addition to local targeted interventions.IMPORTANCE While traditional epidemiological studies are of great interest in describing the dynamics of epidemics, they struggle to fully capture the geospatial dynamics and factors driving the dispersal of pathogens like HIV as they have difficulties capturing linkages between infections. To overcome this, we used a discrete phylogeographic approach coupled to a generalized linear model extension to characterize the dynamics and drivers of the across-province spread of the five main HIV types circulating in China. Our results indicate that large urbanized areas with dense populations and developed transportation infrastructures are facilitators of HIV dispersal throughout China and highlight the need to consider harmonized country-wide public policies to control local HIV epidemics.

Mapping genome variation of SARS-CoV-2 worldwide highlights the impact of COVID-19 super-spreaders

The human pathogen severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is responsible for the major pandemic of the twenty-first century. We analyzed more than 4700 SARS-CoV-2 genomes and associated metadata retrieved from public repositories. SARS-CoV-2 sequences have a high sequence identity (>99.9%), which drops to >96% when compared to bat coronavirus genome. We built a mutation-annotated reference SARS-CoV-2 phylogeny with two main macro-haplogroups, A and B, both of Asian origin, and more than 160 sub-branches representing virus strains of variable geographical origins worldwide, revealing a rather uniform mutation occurrence along branches that could have implications for diagnostics and the design of future vaccines. Identification of the root of SARS-CoV-2 genomes is not without problems, owing to conflicting interpretations derived from either using the bat coronavirus genomes as an outgroup or relying on the sampling chronology of the SARS-CoV-2 genomes and TMRCA estimates; however, the overall scenario favors haplogroup A as the ancestral node. Phylogenetic analysis indicates a TMRCA for SARS-CoV-2 genomes dating to November 12, 2019, thus matching epidemiological records. Sub-haplogroup A2 most likely originated in Europe from an Asian ancestor and gave rise to subclade A2a, which represents the major non-Asian outbreak, especially in Africa and Europe. Multiple founder effect episodes, most likely associated with super-spreader hosts, might explain COVID-19 pandemic to a large extent.

Phylodynamics Helps to Evaluate the Impact of an HIV Prevention Intervention

Assessment of the long-term population-level effects of HIV interventions is an ongoing public health challenge. Following the implementation of a Transmission Reduction Intervention Project (TRIP) in Odessa, Ukraine, in 2013-2016, we obtained HIV pol gene sequences and used phylogenetics to identify HIV transmission clusters. We further applied the birth-death skyline model to the sequences from Odessa (n = 275) and Kyiv (n = 92) in order to estimate changes in the epidemic's effective reproductive number (Re) and rate of becoming uninfectious (δ). We identified 12 transmission clusters in Odessa; phylogenetic clustering was correlated with younger age and higher average viral load at the time of sampling. Estimated Re were similar in Odessa and Kyiv before the initiation of TRIP; Re started to decline in 2013 and is now below Re = 1 in Odessa (Re = 0.4, 95%HPD 0.06-0.75), but not in Kyiv (Re = 2.3, 95%HPD 0.2-5.4). Similarly, estimates of δ increased in Odessa after the initiation of TRIP. Given that both cities shared the same HIV prevention programs in 2013-2019, apart from TRIP, the observed changes in transmission parameters are likely attributable to the TRIP intervention. We propose that molecular epidemiology analysis can be used as a post-intervention effectiveness assessment tool.

Genetic characterization of HIV-1 epidemic in Anhui Province, China

Background

Anhui Province in China is facing a severe HIV epidemic with an increasing number of newly diagnosed cases.

Methods

In this study, HIV genetic characteristics in the province were investigated. Newly reported HIV-positive individuals from 15 districts of Anhui Province were enrolled and interviewed. Total viral RNA was extracted from plasma isolated from blood samples. We amplified and sequenced an HIV pol fragment of the 1062 bp. The sequences were used for determination of HIV subtypes and the presence of drug resistance mutations. Transmission networks were constructed to explore possible relationships. And all of assembled partial pol genes were submitted to the Stanford HIV Drug Resistance Database website to find the transmitted drug resistance.

Results

Partial pol gene sequences were obtained from 486 cases. The results showed that MSM was the most dominant transmission route (253, 52.06%), followed by heterosexual transmission (210, 43.21%) and blood-borne transmission (1, 0.21%). Many subtypes were identified, including CRF01_AE (226, 46.50%), CRF07_BC (151, 31.07%), subtype B (28, 5.76%), CRF08_BC (20, 4.12%), CRF55_01B (15, 3.09%), CRF68_01B (7, 1.44%), CRF67_01B (3, 0.62%), CRF57_BC (2, 0.41%), CRF59_01B (2, 0.41%), CRF79_0107 (2, 0.41%), subtype C (2, 0.41%), CRF64_BC (1, 0.21%), and circulating recombinant forms (URFs) (27, 5.55%). Four transmission subnetworks containing high transmission risk individuals (with degree ≥4) were identified based on CRF01_AE and CRF07_BC sequences, including two CRF01_AE transmission subnetworks constituted by elderly people with average ages of 67.9 and 61.5 years. Infection occurred most likely through heterosexual transmission, while the other two CRF07_BC transmission subnetworks consist mainly of MSMs with average ages of 31.73 and 34.15. The level of HIV-transmitted drug resistance is 3.09%.

Conclusions

The simultaneous spread of multiple HIV subtypes in Anhui province underscores that close surveillance of the local HIV epidemic is necessary. Furthermore, the elderly people were frequently involved, arguing for behaviour intervention in this specific population besides the MSM risk group.

The ability of single genes vs full genomes to resolve time and space in outbreak analysis

Background

Inexpensive pathogen genome sequencing has had a transformative effect on the field of phylodynamics, where ever increasing volumes of data have promised real-time insight into outbreaks of infectious disease. As well as the sheer volume of pathogen isolates being sequenced, the sequencing of whole pathogen genomes, rather than select loci, has allowed phylogenetic analyses to be carried out at finer time scales, often approaching serial intervals for infections caused by rapidly evolving RNA viruses. Despite its utility, whole genome sequencing of pathogens has not been adopted universally and targeted sequencing of loci is common in some pathogen-specific fields.

Results

In this study we highlighted the utility of sequencing whole genomes of pathogens by re-analysing a well-characterised collection of Ebola virus sequences in the form of complete viral genomes (≈19 kb long) or the rapidly evolving glycoprotein (GP, ≈2 kb long) gene. We have quantified changes in phylogenetic, temporal, and spatial inference resolution as a result of this reduction in data and compared these to theoretical expectations.

Conclusions

We propose a simple intuitive metric for quantifying temporal resolution, i.e. the time scale over which sequence data might be informative of various processes as a quick back-of-the-envelope calculation of statistical power available to molecular clock analyses.

Prevalence of Non-B HIV-1 Subtypes in North Italy and Analysis of Transmission Clusters Based on Sequence Data Analysis

HIV-1 diversity is increasing in European countries due to immigration flows, as well as travels and human mobility, leading to the circulation of both new viral subtypes and new recombinant forms, with important implications for public health. We analyzed 710 HIV-1 sequences comprising protease and reverse-transcriptase (PR/RT) coding regions, sampled from 2011 to 2017, from naive patients in Spedali Civili Hospital, Brescia, Italy. Subtyping was performed by using a combination of different tools; the phylogenetic analysis with a structured coalescence model and Makarov Chain Monte Carlo was used on the datasets, to determine clusters and evolution. We detected 304 (43%) patients infected with HIV-1 non-B variants, of which only 293 sequences were available, with four pure subtypes and five recombinant forms; subtype F1 (17%) and CRF02_AG (51.1%) were most common. Twenty-five transmission clusters were identified, three of which included >10 patients, belonging to subtype CRF02_AG and subtype F. Most cases of alleged transmission were between heterosexual couples. Probably due to strong migratory flows, we have identified different subtypes with particular patterns of recombination or, as in the case of the subtype G (18/293, 6.1%), to a complete lack of relationship between the sequenced strains, revealing that they are all singletons. Continued HIV molecular surveillance is most important to analyze the dynamics of the boost of transmission clusters in order to implement public health interventions aimed at controlling the HIV epidemic.

SimpactCyan 1.0: An Open-source Simulator for Individual-Based Models in HIV Epidemiology with R and Python Interfaces

SimpactCyan is an open-source simulator for individual-based models in HIV epidemiology. Its core algorithm is written in C++ for computational efficiency, while the R and Python interfaces aim to make the tool accessible to the fast-growing community of R and Python users. Transmission, treatment and prevention of HIV infections in dynamic sexual networks are simulated by discrete events. A generic “intervention” event allows model parameters to be changed over time, and can be used to model medical and behavioural HIV prevention programmes. First, we describe a more efficient variant of the modified Next Reaction Method that drives our continuous-time simulator. Next, we outline key built-in features and assumptions of individual-based models formulated in SimpactCyan, and provide code snippets for how to formulate, execute and analyse models in SimpactCyan through its R and Python interfaces. Lastly, we give two examples of applications in HIV epidemiology: the first demonstrates how the software can be used to estimate the impact of progressive changes to the eligibility criteria for HIV treatment on HIV incidence. The second example illustrates the use of SimpactCyan as a data-generating tool for assessing the performance of a phylodynamic inference framework.

A Protective Monoclonal Antibody Targets a Site of Vulnerability on the Surface of Rift Valley Fever Virus

The Gn subcomponent of the Gn-Gc assembly that envelopes the human and animal pathogen, Rift Valley fever virus (RVFV), is a primary target of the neutralizing antibody response. To better understand the molecular basis for immune recognition, we raised a class of neutralizing monoclonal antibodies (nAbs) against RVFV Gn, which exhibited protective efficacy in a mouse infection model. Structural characterization revealed that these nAbs were directed to the membrane-distal domain of RVFV Gn and likely prevented virus entry into a host cell by blocking fusogenic rearrangements of the Gn-Gc lattice. Genome sequence analysis confirmed that this region of the RVFV Gn-Gc assembly was under selective pressure and constituted a site of vulnerability on the virion surface. These data provide a blueprint for the rational design of immunotherapeutics and vaccines capable of preventing RVFV infection and a model for understanding Ab-mediated neutralization of bunyaviruses more generally.

Divergence dating using mixed effects clock modelling: An application to HIV-1

The need to estimate divergence times in evolutionary histories in the presence of various sources of substitution rate variation has stimulated a rich development of relaxed molecular clock models. Viral evolutionary studies frequently adopt an uncorrelated clock model as a generic relaxed molecular clock process, but this may impose considerable estimation bias if discrete rate variation exists among clades or lineages. For HIV-1 group M, rate variation among subtypes has been shown to result in inconsistencies in time to the most recent common ancestor estimation. Although this calls into question the adequacy of available molecular dating methods, no solution to this problem has been offered so far. Here, we investigate the use of mixed effects molecular clock models, which combine both fixed and random effects in the evolutionary rate, to estimate divergence times. Using simulation, we demonstrate that this model outperforms existing molecular clock models in a Bayesian framework for estimating time-measured phylogenies in the presence of mixed sources of rate variation, while also maintaining good performance in simpler scenarios. By analysing a comprehensive HIV-1 group M complete genome data set we confirm considerable rate variation among subtypes that is not adequately modelled by uncorrelated relaxed clock models. The mixed effects clock model can accommodate this rate variation and results in a time to the most recent common ancestor of HIV-1 group M of 1920 (1915-25), which is only slightly earlier than the uncorrelated relaxed clock estimate for the same data set. The use of complete genome data appears to have a more profound impact than the molecular clock model because it reduces the credible intervals by 50 per cent relative to similar estimates based on short envelope gene sequences.

The N-Terminus of the HIV-1 p6 Gag Protein Regulates Susceptibility to Degradation by IDE

As part of the Pr55^Gag polyprotein, p6 fulfills an essential role in the late steps of the replication cycle. However, almost nothing is known about the functions of the mature HIV-1 p6 protein. Recently, we showed that p6 is a bona fide substrate of the insulin-degrading enzyme (IDE), a ubiquitously expressed zinc metalloprotease. This phenomenon appears to be specific for HIV-1, since p6 homologs of HIV-2, SIV and EIAV were IDE-insensitive. Furthermore, abrogation of the IDE-mediated degradation of p6 reduces the replication capacity of HIV-1 in an Env-dependent manner. However, it remained unclear to which extent the IDE mediated degradation is phylogenetically conserved among HIV-1. Here, we describe two HIV-1 isolates with IDE resistant p6 proteins. Sequence comparison allowed deducing one single amino acid regulating IDE sensitivity of p6. Exchanging the N-terminal leucine residue of p6 derived from the IDE sensitive isolate HIV-1_NL4-3 with proline enhances its stability, while replacing Pro-1 of p6 from the IDE insensitive isolate SG3 with leucine restores susceptibility towards IDE. Phylogenetic analyses of this natural polymorphism revealed that the N-terminal leucine is characteristic for p6 derived from HIV-1 group M except for subtype A, which predominantly expresses p6 with an N-terminal proline. Consequently, p6 peptides derived from subtype A are not degraded by IDE. Thus, IDE mediated degradation of p6 is specific for HIV-1 group M isolates and not occasionally distributed among HIV-1.

Genome-scale analysis of evolutionary rate and selection in a fast-expanding Spanish cluster of HIV-1 subtype F1

This work is aimed at assessing the presence of positive selection and/or shifts of the evolutionary rate in a fast-expanding HIV-1 subtype F1 transmission cluster affecting men who have sex with men in Spain. We applied Bayesian coalescent phylogenetics and selection analyses to 23 full-coding region sequences from patients belonging to that cluster, along with other 19 F1 epidemiologically-unrelated sequences. A shift in the overall evolutionary rate of the virus, explained by positively selected sites in the cluster, was detected. We also found one substitution in Nef (H89F) that was specific to the cluster and experienced positive selection. These results suggest that fast transmission could have been facilitated by some inherent genetic properties of this HIV-1 variant.

Evolution of HIV-1 within untreated individuals and at the population scale in Uganda

HIV-1 undergoes multiple rounds of error-prone replication between transmission events, resulting in diverse viral populations within and among individuals. In addition, the virus experiences different selective pressures at multiple levels: during the course of infection, at transmission, and among individuals. Disentangling how these evolutionary forces shape the evolution of the virus at the population scale is important for understanding pathogenesis, how drug- and immune-escape variants are likely to spread in populations, and the development of preventive vaccines. To address this, we deep-sequenced two regions of the HIV-1 genome (p24 and gp41) from 34 longitudinally-sampled untreated individuals from Rakai District in Uganda, infected with subtypes A, D, and inter-subtype recombinants. This dataset substantially increases the availability of HIV-1 sequence data that spans multiple years of untreated infection, in particular for different geographical regions and viral subtypes. In line with previous studies, we estimated an approximately five-fold faster rate of evolution at the within-host compared to the population scale for both synonymous and nonsynonymous substitutions, and for all subtypes. We determined the extent to which this mismatch in evolutionary rates can be explained by the evolution of the virus towards population-level consensus, or the transmission of viruses similar to those that establish infection within individuals. Our findings indicate that both processes are likely to be important.

Molecular evolution methods to study HIV-1 epidemics

Nucleotide sequences of HIV isolates are obtained routinely to evaluate the presence of resistance mutations to antiretroviral drugs. But, beyond their clinical use, these and other viral sequences include a wealth of information that can be used to better understand and characterize the epidemiology of HIV in relevant populations. In this review, we provide a brief overview of the main methods used to analyze HIV sequences, the data bases where reference sequences can be obtained, and some caveats about the possible applications for public health of these analyses, along with some considerations about their limitations and correct usage to derive robust and reliable conclusions.