In vivo mutation rates and the landscape of fitness costs of HIV-1

A binary trait model reveals the fitness effects of HIV-1 escape from T cell responses

Natural selection often acts on multiple traits simultaneously. For example, the virus HIV-1 faces pressure to evade host immunity while also preserving replicative fitness. While past work has studied selection during HIV-1 evolution, it is challenging to quantitatively separate different contributions to fitness. This task is made more difficult because a single mutation can affect both immune escape and replication. Here, we develop an evolutionary model that disentangles the effects of escaping CD8+ T cell-mediated immunity, which we model as a binary trait, from other contributions to fitness. After validation in simulations, we applied this model to study within-host HIV-1 evolution in a clinical data set. We observed strong selection for immune escape, sometimes greatly exceeding past estimates, especially early in infection. Conservative estimates suggest that roughly half of HIV-1 fitness gains during the first months to years of infection can be attributed to T cell escape. Our approach is not limited to HIV-1 or viruses, and could be adapted to study the evolution of quantitative traits in other contexts.

Prevalence of SARS-CoV-2 variants in Prague wastewater determined by nanopore-based sequencing

The early detection of upcoming disease outbreaks is essential to avoid both health and economic damage. The last four years of COVID-19 pandemic have proven wastewater-based epidemiology is a reliable system for monitoring the spread of SARS-CoV-2, a causative agent of COVID-19, in an urban population. As this monitoring enables the identification of the prevalence of spreading variants of SARS-CoV-2, it could provide a critical tool in the fight against this viral disease. In this study, we evaluated the presence of variants and subvariants of SARS-CoV-2 in Prague wastewater using nanopore-based sequencing. During August 2021, the data clearly showed that the number of identified SARS-CoV-2 RNA copies increased in the wastewater earlier than in clinical samples indicating the upcoming wave of the Delta variant. New SARS-CoV-2 variants consistently prevailed in wastewater samples around a month after they already prevailed in clinical samples. We also analyzed wastewater samples from smaller sub-sewersheds of Prague and detected significant differences in SARS-CoV-2 lineage progression dynamics among individual localities studied, e.g., suggesting faster prevalence of new variants among the sites with highest population density and mobility.

Elevated HIV Viral Load is Associated with Higher Recombination Rate In Vivo

HIV's exceptionally high recombination rate drives its intrahost diversification, enabling immune escape and multidrug resistance within people living with HIV. While we know that HIV's recombination rate varies by genomic position, we have little understanding of how recombination varies throughout infection or between individuals as a function of the rate of cellular coinfection. We hypothesize that denser intrahost populations may have higher rates of coinfection and therefore recombination. To test this hypothesis, we develop a new approach (recombination analysis via time series linkage decay or RATS-LD) to quantify recombination using autocorrelation of linkage between mutations across time points. We validate RATS-LD on simulated data under short read sequencing conditions and then apply it to longitudinal, high-throughput intrahost viral sequencing data, stratifying populations by viral load (a proxy for density). Among sampled viral populations with the lowest viral loads (<26,800 copies/mL), we estimate a recombination rate of 1.5×10-5 events/bp/generation (95% CI: 7×10-6 to 2.9×10-5), similar to existing estimates. However, among samples with the highest viral loads (>82,000 copies/mL), our median estimate is approximately 6 times higher. In addition to co-varying across individuals, we also find that recombination rate and viral load are associated within single individuals across different time points. Our findings suggest that rather than acting as a constant, uniform force, recombination can vary dynamically and drastically across intrahost viral populations and within them over time. More broadly, we hypothesize that this phenomenon may affect other facultatively asexual populations where spatial co-localization varies.

Elevated HIV viral load is associated with higher recombination rate in vivo

HIV's exceptionally high recombination rate drives its intra-host diversification, enabling immune escape and multi-drug resistance within people living with HIV. While we know that HIV's recombination rate varies by genomic position, we have little understanding of how recombination varies throughout infection or between individuals as a function of the rate of cellular coinfection. We hypothesize that denser intra-host populations may have higher rates of coinfection and therefore recombination. To test this hypothesis, we develop a new approach (Recombination Analysis via Time Series Linkage Decay, or RATS-LD) to quantify recombination using autocorrelation of linkage between mutations across time points. We validate RATS-LD on simulated data under short read sequencing conditions and then apply it to longitudinal, high-throughput intra-host viral sequencing data, stratifying populations by viral load (a proxy for density). Among sampled viral populations with the lowest viral loads (< 26,800 copies/mL), we estimate a recombination rate of 1.5 × 10-5 events/bp/generation (95% CI: 7 × 10-6 - 2.9 × 10-5), similar to existing estimates. However, among samples with the highest viral loads (> 82,000 copies/mL), our median estimate is approximately 6 times higher. In addition to co-varying across individuals, we also find that recombination rate and viral load are associated within single individuals across different time points. Our findings suggest that rather than acting as a constant, uniform force, recombination can vary dynamically and drastically across intra-host viral populations and within them over time. More broadly, we hypothesize that this phenomenon may affect other facultatively asexual populations where spatial co-localization varies.

Fitness effects of mutations to SARS-CoV-2 proteins

Knowledge of the fitness effects of mutations to SARS-CoV-2 can inform assessment of new variants, design of therapeutics resistant to escape, and understanding of the functions of viral proteins. However, experimentally measuring effects of mutations is challenging: we lack tractable lab assays for many SARS-CoV-2 proteins, and comprehensive deep mutational scanning has been applied to only two SARS-CoV-2 proteins. Here, we develop an approach that leverages millions of publicly available SARS-CoV-2 sequences to estimate effects of mutations. We first calculate how many independent occurrences of each mutation are expected to be observed along the SARS-CoV-2 phylogeny in the absence of selection. We then compare these expected observations to the actual observations to estimate the effect of each mutation. These estimates correlate well with deep mutational scanning measurements. For most genes, synonymous mutations are nearly neutral, stop-codon mutations are deleterious, and amino acid mutations have a range of effects. However, some viral accessory proteins are under little to no selection. We provide interactive visualizations of effects of mutations to all SARS-CoV-2 proteins (https://jbloomlab.github.io/SARS2-mut-fitness/). The framework we describe is applicable to any virus for which the number of available sequences is sufficiently large that many independent occurrences of each neutral mutation are observed.

Inferring Human Immunodeficiency Virus 1 Proviral Integration Dates With Bayesian Inference

Human immunodeficiency virus 1 (HIV) proviruses archived in the persistent reservoir currently pose the greatest obstacle to HIV cure due to their evasion of combined antiretroviral therapy and ability to reseed HIV infection. Understanding the dynamics of the HIV persistent reservoir is imperative for discovering a durable HIV cure. Here, we explore Bayesian methods using the software BEAST2 to estimate HIV proviral integration dates. We started with within-host longitudinal HIV sequences collected prior to therapy, along with sequences collected from the persistent reservoir during suppressive therapy. We built a BEAST2 model to estimate integration dates of proviral sequences collected during suppressive therapy, implementing a tip date random walker to adjust the sequence tip dates and a latency-specific prior to inform the dates. To validate our method, we implemented it on both simulated and empirical data sets. Consistent with previous studies, we found that proviral integration dates were spread throughout active infection. Path sampling to select an alternative prior for date estimation in place of the latency-specific prior produced unrealistic results in one empirical data set, whereas on another data set, the latency-specific prior was selected as best fitting. Our Bayesian method outperforms current date estimation techniques with a root mean squared error of 0.89 years on simulated data relative to 1.23-1.89 years with previously developed methods. Bayesian methods offer an adaptable framework for inferring proviral integration dates.

Fitness effects of mutations to SARS-CoV-2 proteins

Knowledge of the fitness effects of mutations to SARS-CoV-2 can inform assessment of new variants, design of therapeutics resistant to escape, and understanding of the functions of viral proteins. However, experimentally measuring effects of mutations is challenging: we lack tractable lab assays for many SARS-CoV-2 proteins, and comprehensive deep mutational scanning has been applied to only two SARS-CoV-2 proteins. Here we develop an approach that leverages millions of publicly available SARS-CoV-2 sequences to estimate effects of mutations. We first calculate how many independent occurrences of each mutation are expected to be observed along the SARS-CoV-2 phylogeny in the absence of selection. We then compare these expected observations to the actual observations to estimate the effect of each mutation. These estimates correlate well with deep mutational scanning measurements. For most genes, synonymous mutations are nearly neutral, stop-codon mutations are deleterious, and amino-acid mutations have a range of effects. However, some viral accessory proteins are under little to no selection. We provide interactive visualizations of effects of mutations to all SARS-CoV-2 proteins (https://jbloomlab.github.io/SARS2-mut-fitness/). The framework we describe is applicable to any virus for which the number of available sequences is sufficiently large that many independent occurrences of each neutral mutation are observed.

Mutation rate, selection, and epistasis inferred from RNA virus haplotypes via neural posterior estimation

RNA viruses are particularly notorious for their high levels of genetic diversity, which is generated through the forces of mutation and natural selection. However, disentangling these two forces is a considerable challenge, and this may lead to widely divergent estimates of viral mutation rates, as well as difficulties in inferring the fitness effects of mutations. Here, we develop, test, and apply an approach aimed at inferring the mutation rate and key parameters that govern natural selection, from haplotype sequences covering full-length genomes of an evolving virus population. Our approach employs neural posterior estimation, a computational technique that applies simulation-based inference with neural networks to jointly infer multiple model parameters. We first tested our approach on synthetic data simulated using different mutation rates and selection parameters while accounting for sequencing errors. Reassuringly, the inferred parameter estimates were accurate and unbiased. We then applied our approach to haplotype sequencing data from a serial passaging experiment with the MS2 bacteriophage, a virus that parasites Escherichia coli. We estimated that the mutation rate of this phage is around 0.2 mutations per genome per replication cycle (95% highest density interval: 0.051-0.56). We validated this finding with two different approaches based on single-locus models that gave similar estimates but with much broader posterior distributions. Furthermore, we found evidence for reciprocal sign epistasis between four strongly beneficial mutations that all reside in an RNA stem loop that controls the expression of the viral lysis protein, responsible for lysing host cells and viral egress. We surmise that there is a fine balance between over- and underexpression of lysis that leads to this pattern of epistasis. To recap, we have developed an approach for joint inference of the mutation rate and selection parameters from full haplotype data with sequencing errors and used it to reveal features governing MS2 evolution.

Reversions to consensus are positively selected in HIV-1 and bias substitution rate estimates

Human immunodeficiency virus 1 (HIV-1) is a rapidly evolving virus able to evade host immunity through rapid adaptation during chronic infection. The HIV-1 group M has diversified since its zoonosis into several subtypes at a rate of the order of 10^-3 changes per site per year. This rate varies between different parts of the genome, and its inference is sensitive to the timescale and diversity spanned by the sequence data used. Higher rates are estimated on short timescales and particularly for within-host evolution, while rate estimates spanning decades or the entire HIV-1 pandemic tend to be lower. The underlying causes of this difference are not well understood. We investigate here the role of rapid reversions toward a preferred evolutionary sequence state on multiple timescales. We show that within-host reversion mutations are under positive selection and contribute substantially to sequence turnover, especially at conserved sites. We then use the rates of reversions and non-reversions estimated from longitudinal within-host data to parameterize a phylogenetic sequence evolution model. Sequence simulation of this model on HIV-1 phylogenies reproduces diversity and apparent evolutionary rates of HIV-1 in gag and pol, suggesting that a tendency to rapidly revert to a consensus-like state can explain much of the time dependence of evolutionary rate estimates in HIV-1.

Contributions of adaptation and purifying selection to SARS-CoV-2 evolution

Continued evolution and adaptation of SARS-CoV-2 has led to more transmissible and immune-evasive variants with profound impacts on the course of the pandemic. Here I analyze the evolution of the virus over 2.5 years since its emergence and estimate the rates of evolution for synonymous and non-synonymous changes separately for evolution within clades-well-defined monophyletic groups with gradual evolution-and for the pandemic overall. The rate of synonymous mutation is found to be around 6 changes per year. Synonymous rates within variants vary little from variant to variant and are compatible with the overall rate of 7 changes per year (or [Formula: see text] per year and codon). In contrast, the rate at which variants accumulate amino acid changes (non-synonymous mutations) was initially around 12-16 changes per year, but in 2021 and 2022 it dropped to 6-9 changes per year. The overall rate of non-synonymous evolution, that is across variants, is estimated to be about 26 amino acid changes per year (or [Formula: see text] per year and codon). This strong acceleration of the overall rate compared to within clade evolution indicates that the evolutionary process that gave rise to the different variants is qualitatively different from that in typical transmission chains and likely dominated by adaptive evolution. I further quantify the spectrum of mutations and purifying selection in different SARS-CoV-2 proteins and show that the massive global sampling of SARS-CoV-2 is sufficient to estimate site-specific fitness costs across the entire genome. Many accessory proteins evolve under limited evolutionary constraints with little short-term purifying selection. About half of the mutations in other proteins are strongly deleterious.

Design of an optimal combination therapy with broadly neutralizing antibodies to suppress HIV-1

Infusion of broadly neutralizing antibodies (bNAbs) has shown promise as an alternative to anti-retroviral therapy against HIV. A key challenge is to suppress viral escape, which is more effectively achieved with a combination of bNAbs. Here, we propose a computational approach to predict the efficacy of a bNAb therapy based on the population genetics of HIV escape, which we parametrize using high-throughput HIV sequence data from bNAb-naive patients. By quantifying the mutational target size and the fitness cost of HIV-1 escape from bNAbs, we predict the distribution of rebound times in three clinical trials. We show that a cocktail of three bNAbs is necessary to effectively suppress viral escape, and predict the optimal composition of such bNAb cocktail. Our results offer a rational therapy design for HIV, and show how genetic data can be used to predict treatment outcomes and design new approaches to pathogenic control.

Commonly Elicited Antibodies against the Base of the HIV-1 Env Trimer Guide the Population-Level Evolution of a Structure-Regulating Region in gp41

The antibody response against the HIV-1 envelope glycoproteins (Envs) guides evolution of this protein within each host. Whether antibodies with similar target specificities are elicited in different individuals and affect the population-level evolution of Env is poorly understood. To address this question, we analyzed properties of emerging variants in the gp41 fusion peptide-proximal region (FPPR) that exhibit distinct evolutionary patterns in HIV-1 clade B. For positions 534, 536, and 539 in the FPPR, alanine was the major emerging variant. However, 534A and 536A show a constant frequency in the population between 1979 and 2016, whereas 539A is gradually increasing. To understand the basis for these differences, we introduced alanine substitutions in the FPPR of primary HIV-1 strains and examined their functional and antigenic properties. Evolutionary patterns could not be explained by fusion competence or structural stability of the emerging variants. Instead, 534A and 536A exhibited modest but significant increases in sensitivity to antibodies against the membrane-proximal external region (MPER) and gp120-gp41 interface. These Envs were also more sensitive to poorly neutralizing sera from HIV-1-infected individuals than the clade ancestral form or 539A variant. Competition binding assays confirmed for all sera tested the presence of antibodies against the base of the Env trimer that compete with monoclonal antibodies targeting the MPER and gp120-gp41 interface. Our findings suggest that weakly neutralizing antibodies against the trimer base are commonly elicited; they do not exert catastrophic population size reduction effects on emerging variants but, instead, determine their set point frequencies in the population and historical patterns of change. IMPORTANCE Infection by HIV-1 elicits formation of antibodies that target the viral Env proteins and can inactivate the virus. The specific targets of these antibodies vary among infected individuals. It is unclear whether some target specificities are shared among the antibody responses of different individuals. We observed that antibodies against the base of the Env protein are commonly elicited during infection. The selective pressure applied by such antibodies is weak. As a result, they do not completely eliminate the sensitive forms of the virus from the population, but maintain their frequency at a low level that has not increased since the beginning of the AIDS pandemic. Interestingly, the changes in Env do not occur at the sites targeted by the antibodies, but at a distinct region of Env, the fusion peptide-proximal region, which regulates their exposure.

HIV-1 Evolutionary Dynamics under Nonsuppressive Antiretroviral Therapy

Prolonged virologic failure on 2nd-line protease inhibitor (PI)-based antiretroviral therapy (ART) without emergence of major protease mutations is well recognized and provides an opportunity to study within-host evolution in long-term viremic individuals. Using next-generation sequencing and in silico haplotype reconstruction, we analyzed whole-genome sequences from longitudinal plasma samples of eight chronically infected HIV-1-positive individuals failing 2nd-line regimens from the French National Agency for AIDS and Viral Hepatitis Research (ANRS) 12249 Treatment as Prevention (TasP) trial. On nonsuppressive ART, there were large fluctuations in synonymous and nonsynonymous variant frequencies despite stable viremia. Reconstructed haplotypes provided evidence for selective sweeps during periods of partial adherence, and viral haplotype competition, during periods of low drug exposure. Drug resistance mutations in reverse transcriptase (RT) were used as markers of viral haplotypes in the reservoir, and their distribution over time indicated recombination. We independently observed linkage disequilibrium decay, indicative of recombination. These data highlight dramatic changes in virus population structure that occur during stable viremia under nonsuppressive ART. IMPORTANCE HIV-1 infections are most commonly initiated with a single founder virus and are characterized by extensive inter- and intraparticipant genetic diversity. However, existing literature on HIV-1 intrahost population dynamics is largely limited to untreated infections, predominantly in subtype B-infected individuals. The manuscript characterizes viral population dynamics in long-term viremic treatment-experienced individuals, which has not been previously characterized. These data are particularly relevant for understanding HIV dynamics but can also be applied to other RNA viruses. With this unique data set we propose that the virus is highly unstable, and we have found compelling evidence of HIV-1 within-host viral diversification, recombination, and haplotype competition during nonsuppressive ART.

Assessing in vivo mutation frequencies and creating a high-resolution genome-wide map of fitness costs of Hepatitis C virus

Like many viruses, Hepatitis C Virus (HCV) has a high mutation rate, which helps the virus adapt quickly, but mutations come with fitness costs. Fitness costs can be studied by different approaches, such as experimental or frequency-based approaches. The frequency-based approach is particularly useful to estimate in vivo fitness costs, but this approach works best with deep sequencing data from many hosts are. In this study, we applied the frequency-based approach to a large dataset of 195 patients and estimated the fitness costs of mutations at 7957 sites along the HCV genome. We used beta regression and random forest models to better understand how different factors influenced fitness costs. Our results revealed that costs of nonsynonymous mutations were three times higher than those of synonymous mutations, and mutations at nucleotides A or T had higher costs than those at C or G. Genome location had a modest effect, with lower costs for mutations in HVR1 and higher costs for mutations in Core and NS5B. Resistance mutations were, on average, costlier than other mutations. Our results show that in vivo fitness costs of mutations can be site and virus specific, reinforcing the utility of constructing in vivo fitness cost maps of viral genomes.

Low Pathogenicity H7N3 Avian Influenza Viruses Have Higher Within-Host Genetic Diversity Than a Closely Related High Pathogenicity H7N3 Virus in Infected Turkeys and Chickens

Within-host viral diversity offers a view into the early stages of viral evolution occurring after a virus infects a host. In recent years, advances in deep sequencing have allowed for routine identification of low-frequency variants, which are important sources of viral genetic diversity and can potentially emerge as a major virus population under certain conditions. We examined within-host viral diversity in turkeys and chickens experimentally infected with closely related H7N3 avian influenza viruses (AIVs), specifically one high pathogenicity AIV (HPAIV) and two low pathogenicity AIV (LPAIVs) with different neuraminidase protein stalk lengths. Consistent with the high mutation rates of AIVs, an abundance of intra-host single nucleotide variants (iSNVs) at low frequencies of 2–10% was observed in all samples collected. Furthermore, a small number of common iSNVs were observed between turkeys and chickens, and between directly inoculated and contact-exposed birds. Notably, the LPAIVs have significantly higher iSNV diversities and frequencies of nonsynonymous changes than the HPAIV in both turkeys and chickens. These findings highlight the dynamics of AIV populations within hosts and the potential impact of genetic changes, including mutations in the hemagglutinin gene that confers the high pathogenicity pathotype, on AIV virus populations and evolution.

Integrase Inhibitor Resistance Mechanisms and Structural Characteristics in Antiretroviral Therapy-Experienced, Integrase Inhibitor-Naive Adults with HIV-1 Infection Treated with Dolutegravir plus Two Nucleoside Reverse Transcriptase Inhibitors in the DAWNING Study

At week 48 in the phase IIIb DAWNING study, the integrase strand transfer inhibitor (INSTI) dolutegravir plus 2 nucleoside reverse transcriptase inhibitors demonstrated superiority to ritonavir-boosted lopinavir in achieving virologic suppression in adults with HIV-1 who failed first-line therapy. Here, we report emergent HIV-1 drug resistance and mechanistic underpinnings among dolutegravir-treated adults in DAWNING. Population viral genotyping, phenotyping, and clonal analyses were performed on participants meeting confirmed virologic withdrawal (CVW) criteria on dolutegravir-containing regimens. Dolutegravir binding to and structural changes in HIV-1 integrase-DNA complexes with INSTI resistance-associated substitutions were evaluated. Of participants who received dolutegravir through week 48 plus an additional 110 weeks for this assessment, 6 met CVW criteria with treatment-emergent INSTI resistance-associated substitutions and 1 had R263R/K at baseline but not at CVW. All 7 achieved HIV-1 RNA levels of <400 copies/mL (5 achieved <50 copies/mL) before CVW. Treatment-emergent G118R was detected in 5 participants, occurring with ≥2 other integrase substitutions, including R263R/K, in 3 participants and without other integrase substitutions in 2 participants. G118R or R263K increased the rate of dolutegravir dissociation from integrase-DNA complexes versus wild-type but retained prolonged binding. Overall, among treatment-experienced adults who received dolutegravir in DAWNING, 6 of 314 participants developed treatment-emergent INSTI resistance-associated substitutions, with a change in in vitro dolutegravir resistance of >10-fold and reduced viral replication capacity versus baseline levels. This study demonstrates that the pathway to dolutegravir resistance is a challenging balance between HIV-1 phenotypic change and associated loss of viral fitness. (This study has been registered at ClinicalTrials.gov under identifier NCT02227238.).

Phylogenetic prioritization of HIV-1 transmission clusters with viral lineage-level diversification rates

Background and objectives

Public health officials faced with a large number of transmission clusters require a rapid, scalable and unbiased way to prioritize distribution of limited resources to maximize benefits. We hypothesize that transmission cluster prioritization based on phylogenetically derived lineage-level diversification rates will perform as well as or better than commonly used growth-based prioritization measures, without need for historical data or subjective interpretation.

Methodology

9822 HIV pol sequences collected during routine drug resistance genotyping were used alongside simulated sequence data to infer sets of phylogenetic transmission clusters via patristic distance threshold. Prioritized clusters inferred from empirical data were compared to those prioritized by the current public health protocols. Prioritization of simulated clusters was evaluated based on correlation of a given prioritization measure with future cluster growth, as well as the number of direct downstream transmissions from cluster members.

Results

Empirical data suggest diversification rate-based measures perform comparably to growth-based measures in recreating public heath prioritization choices. However, unbiased simulated data reveals phylogenetic diversification rate-based measures perform better in predicting future cluster growth relative to growth-based measures, particularly long-term growth. Diversification rate-based measures also display advantages over growth-based measures in highlighting groups with greater future transmission events compared to random groups of the same size. Furthermore, diversification rate measures were notably more robust to effects of decreased sampling proportion.

Conclusions and implications

Our findings indicate diversification rate-based measures frequently outperform growth-based measures in predicting future cluster growth and offer several additional advantages beneficial to optimizing the public health prioritization process.

Predicting in vivo escape dynamics of HIV-1 from a broadly neutralizing antibody

Broadly neutralizing antibodies (bnAbs) show promise for antibody-mediated prevention or treatment of HIV-1 infection. Recent clinical trials, however, indicate that the virus can evolve resistance mutations that escape neutralization by bnAbs. Here, we establish a fitness model for the escape dynamics of HIV in humans. We show that this model can be applied universally across different human hosts, providing a proof of principle that the in vivo response of HIV to bnAb therapies is predictable. Our analysis identifies a fitness trade-off in viral evolution that can inform antibody design and therapy protocols.

Broadly neutralizing antibodies are promising candidates for treatment and prevention of HIV-1 infections. Such antibodies can temporarily suppress viral load in infected individuals; however, the virus often rebounds by escape mutants that have evolved resistance. In this paper, we map a fitness model of HIV-1 interacting with broadly neutralizing antibodies using in vivo data from a recent clinical trial. We identify two fitness factors, antibody dosage and viral load, that determine viral reproduction rates reproducibly across different hosts. The model successfully predicts the escape dynamics of HIV-1 in the course of an antibody treatment, including a characteristic frequency turnover between sensitive and resistant strains. This turnover is governed by a dosage-dependent fitness ranking, resulting from an evolutionary trade-off between antibody resistance and its collateral cost in drug-free growth. Our analysis suggests resistance–cost trade-off curves as a measure of antibody performance in the presence of resistance evolution.

Human immunotypes impose selection on viral genotypes through viral epitope specificity

BACKGROUND

Understanding the genetic interplay between human hosts and infectious pathogens is crucial for how we interpret virulence factors. Here, we tested for associations between HIV and host genetics, and interactive genetic effects on viral load (VL) in HIV+ ART-naive clinical trial participants.

METHODS

HIV genomes were sequenced and the encoded amino acid (AA) variants were associated with VL, human single nucleotide polymorphisms (SNPs) and imputed HLA alleles, using generalized linear models with Bonferroni correction.

RESULTS

Human (388,501 SNPs) and HIV (3,010 variants) genetic data was available for 2,122 persons. Four HIV variants were associated with VL (p-values<1.66×10 -5). Twelve HIV variants were associated with a range of 1-512 human SNPs (p-value<4.28×10 -11). We found 46 associations between HLA alleles and HIV variants (p-values<1.29×10 -7). We found HIV variants and immunotypes when analyzed separately, were associated with lower VL, whereas the opposite was true when analyzed in concert. Epitope binding prediction showed HLA alleles to be weaker binders of associated HIV AA variants relative to alternative variants on the same position.

CONCLUSIONS

Our results show the importance of immunotype specificity on viral antigenic determinants, and the identified genetic interplay puts emphasis that viral and human genetics should be studied in the context of each other.

MPL resolves genetic linkage in fitness inference from complex evolutionary histories

Genetic linkage causes the fate of new mutations in a population to be contingent on the genetic background on which they appear. This makes it challenging to identify how individual mutations affect fitness. To overcome this challenge, we developed marginal path likelihood (MPL), a method to infer selection from evolutionary histories that resolves genetic linkage. Validation on real and simulated data sets shows that MPL is fast and accurate, outperforming existing inference approaches. We found that resolving linkage is crucial for accurately quantifying selection in complex evolving populations, which we demonstrate through a quantitative analysis of intrahost HIV-1 evolution using multiple patient data sets. Linkage effects generated by variants that sweep rapidly through the population are particularly strong, extending far across the genome. Taken together, our results argue for the importance of resolving linkage in studies of natural selection.

Validation of multiplex PCR sequencing assay of SIV

Background

The generation of accurate and reproducible viral sequence data is necessary to understand the diversity present in populations of RNA viruses isolated from clinical samples. While various sequencing methods are available, they often require high quality templates and high viral titer to ensure reliable data.

Methods

We modified a multiplex PCR and sequencing approach to characterize populations of simian immunodeficiency virus (SIV) isolated from nonhuman primates. We chose this approach with the aim of reducing the number of required input templates while maintaining fidelity and sensitivity. We conducted replicate sequencing experiments using different numbers of quantified viral RNA (vRNA) or viral cDNA as input material. We performed assays with clonal SIVmac239 to detect false positives, and we mixed SIVmac239 and a variant with 24 point mutations (SIVmac239-24X) to measure variant detection sensitivity.

Results

We found that utilizing a starting material of quantified viral cDNA templates had a lower rate of false positives and increased reproducibility when compared to that of quantified vRNA templates. This study identifies the importance of rigorously validating deep sequencing methods and including replicate samples when using a new method to characterize low frequency variants in a population with a small number of templates.

Conclusions

Because the need to generate reproducible and accurate sequencing data from diverse viruses from low titer samples, we modified a multiplex PCR and sequencing approach to characterize SIV from populations from non-human primates. We found that increasing starting template numbers increased the reproducibility and decreased the number of false positives identified, and this was further seen when cDNA was used as a starting material. Ultimately, we highlight the importance of vigorously validating methods to prevent overinterpretation of low frequency variants in a sample.

Efficient inference, potential, and limitations of site-specific substitution models

Natural selection imposes a complex filter on which variants persist in a population resulting in evolutionary patterns that vary greatly along the genome. Some sites evolve close to neutrally, while others are highly conserved, allow only specific states, or only change in concert with other sites. On one hand, such constraints on sequence evolution can be to infer biological function, one the other hand they need to be accounted for in phylogenetic reconstruction. Phylogenetic models often account for this complexity by partitioning sites into a small number of discrete classes with different rates and/or state preferences. Appropriate model complexity is typically determined by model selection procedures. Here, we present an efficient algorithm to estimate more complex models that allow for different preferences at every site and explore the accuracy at which such models can be estimated from simulated data. Our iterative approximate maximum likelihood scheme uses information in the data efficiently and accurately estimates site-specific preferences from large data sets with moderately diverged sequences and known topology. However, the joint estimation of site-specific rates, and site-specific preferences, and phylogenetic branch length can suffer from identifiability problems, while ignoring variation in preferences across sites results in branch length underestimates. Site-specific preferences estimated from large HIV pol alignments show qualitative concordance with intra-host estimates of fitness costs. Analysis of these substitution models suggests near saturation of divergence after a few hundred years. Such saturation can explain the inability to infer deep divergence times of HIV and SIVs using molecular clock approaches and time-dependent rate estimates.

Longitudinal characterization of HIV-1 pol-gene in treatment-naïve men-who-have-sex-with-men from acute to chronic infection stages

HIV-1 is characterized by its ability to mutate and recombine even at polymerase (pol) gene. However, pol-gene diversity is limited due to functional constraints. The aim of this study was to characterize longitudinally, by next-generation sequencing (NGS), HIV-1 variants based on pol-gene sequences, at intra- and inter-host level, from acute/early to chronic stages of infection, in the absence of antiretroviral therapy. Ten men who have sex with men (MSM) were recruited during primary infection and yearly followed for five years. Even after a maximum of a five-year follow-up period, the phylogenetic analysis of HIV-1 pol-gene sequences showed a host-defined structured pattern, with a predominance of purifying selection forces during the follow-up. MSM had been acutely infected by different HIV-1 variants mainly ascribed to pure subtype B, or BF recombinant variants and showed different genetic mosaicism patterns that last until the chronic stage, representing a major challenge for prevention strategies.

The Role of APOBECs in Viral Replication

Apolipoprotein B mRNA-editing enzyme catalytic polypeptide-like (APOBEC) proteins are a diverse and evolutionarily conserved family of cytidine deaminases that provide a variety of functions from tissue-specific gene expression and immunoglobulin diversity to control of viruses and retrotransposons. APOBEC family expansion has been documented among mammalian species, suggesting a powerful selection for their activity. Enzymes with a duplicated zinc-binding domain often have catalytically active and inactive domains, yet both have antiviral function. Although APOBEC antiviral function was discovered through hypermutation of HIV-1 genomes lacking an active Vif protein, much evidence indicates that APOBECs also inhibit virus replication through mechanisms other than mutagenesis. Multiple steps of the viral replication cycle may be affected, although nucleic acid replication is a primary target. Packaging of APOBECs into virions was first noted with HIV-1, yet is not a prerequisite for viral inhibition. APOBEC antagonism may occur in viral producer and recipient cells. Signatures of APOBEC activity include G-to-A and C-to-T mutations in a particular sequence context. The importance of APOBEC activity for viral inhibition is reflected in the identification of numerous viral factors, including HIV-1 Vif, which are dedicated to antagonism of these deaminases. Such viral antagonists often are only partially successful, leading to APOBEC selection for viral variants that enhance replication or avoid immune elimination.

Conserved epitopes with high HLA-I population coverage are targets of CD8+ T cells associated with high IFN-γ responses against all dengue virus serotypes

Cytotoxic CD8⁺ T cells are key for immune protection against viral infections. The breadth and cross-reactivity of these responses are important against rapidly mutating RNA viruses, such as dengue (DENV), yet how viral diversity affect T cell responses and their cross-reactivity against multiple variants of the virus remains poorly defined. In this study, an integrated analysis was performed to map experimentally validated CD8⁺ T cell epitopes onto the distribution of DENV genome sequences across the 4 serotypes worldwide. Despite the higher viral diversity observed within HLA-I restricted epitopes, mapping of 609 experimentally validated epitopes sequences on 3985 full-length viral genomes revealed 19 highly conserved epitopes across the four serotypes within the immunogenic regions of NS3, NS4B and NS5. These conserved epitopes were associated with a higher magnitude of IFN-γ response when compared to non-conserved epitopes and were restricted to 13 HLA class I genotypes, hence providing high coverage among human populations. Phylogeographic analyses showed that these epitopes are largely conserved in most of the endemic regions of the world, and with only some of these epitopes presenting distinct mutated variants circulating in South America and Asia.This study provides evidence for the existence of highly immunogenic and conserved epitopes across serotypes, which may impact design of new universal T-cell-inducing vaccine candidates that minimise detrimental effects of viral diversification and at the same time induce responses to a broad human population.

Drivers of within-host genetic diversity in acute infections of viruses

Genetic diversity is the fuel of evolution and facilitates adaptation to novel environments. However, our understanding of what drives differences in the genetic diversity during the early stages of viral infection is somewhat limited. Here, we use ultra-deep sequencing to interrogate 43 clinical samples taken from early infections of the human-infecting viruses HIV, RSV and CMV. Hundreds to thousands of virus templates were sequenced per sample, allowing us to reveal dramatic differences in within-host genetic diversity among virus populations. We found that increased diversity was mostly driven by presence of multiple divergent genotypes in HIV and CMV samples, which we suggest reflect multiple transmitted/founder viruses. Conversely, we detected an abundance of low frequency hyper-edited genomes in RSV samples, presumably reflecting defective virus genomes (DVGs). We suggest that RSV is characterized by higher levels of cellular co-infection, which allow for complementation and hence elevated levels of DVGs.

The few days or weeks following infection with a virus, termed acute infection, are critical for virus establishment. Here we sought to characterize what leads to differences in the genetic diversity of different viruses sampled during acute infection. We performed ultra-deep sequencing of hundreds to thousands viral genomes from forty-three samples spanning three pathogenic human viruses: HIV, RSV and CMV. We found major differences in the genetic diversity of these different viruses, and in different patients infected with the same virus. We investigated the factors responsible for these differences. We found that the DNA virus CMV was less diverse, most likely since it has a lower mutation rate than the RNA viruses HIV and RSV. We also found that the samples with the highest genetic diversity, which included one CMV sample and two HIV samples, bore evidence for multiple genotype infection. In other words, patients from whom these samples were taken were infected with two different “strains” of the virus. Finally, we also found evidence that viral genomes of HIV, and in particular RSV, are edited by the innate immune system of the host, leading to the presence of defective virus genomes.

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.

In vivo drug resistance mutation dynamics from the early to chronic stage of infection in antiretroviral-therapy-naïve HIV-infected men who have sex with men

Human immunodeficiency virus type 1 (HIV) primary drug resistance mutations (DRMs) influence the long-term therapeutic effects of antiretroviral treatment (ART). Drug-resistance genotyping based on polymerase gene sequences obtained by next-generation sequencing (NGS) was performed using samples from 10 ART-naïve HIV-infected men who have sex with men (MSM; P1-P10) from the acute/early to chronic stage of infection. Three of the 10 subjects exhibited the presence of major (abundance, ≥ 20%) viral populations carrying DRM at early/acute stage that later, at the chronic stage, dropped drastically (V106M) or remained highly abundant (E138A). Four individuals exhibited additional DRMs (M46I/L; I47A; I54M, L100V) as HIV minority populations (abundance, 2-20%) that emerged during the chronic stage but ephemerally.

Key Positions of HIV-1 Env and Signatures of Vaccine Efficacy Show Gradual Reduction of Population Founder Effects at the Clade and Regional Levels

HIV-1 group M was transmitted to humans nearly one century ago. The virus has since evolved to form distinct clades, which spread to different regions of the world. The envelope glycoproteins (Envs) of HIV-1 have rapidly diversified in all infected populations. We examined whether key antigenic sites of Env and signatures of vaccine efficacy are evolving toward similar or distinct structural forms in different populations worldwide. Patterns of amino acid variants that emerged at each position of Env were compared between diverse HIV-1 clades and isolates from different geographic regions. Interestingly, at each Env position, the amino acid in the clade ancestral or regional-founder virus was replaced by a unique frequency distribution (FD) of amino acids. FDs are highly conserved in populations from different regions worldwide and in paraphyletic and monophyletic subclade groups. Remarkably, founder effects of Env mutations at the clade and regional levels have gradually decreased during the pandemic by evolution of each site toward the unique combination of variants. Therefore, HIV-1 Env is evolving at a population level toward well-defined "target" states; these states are not specific amino acids but rather specific distributions of amino acid frequencies. Our findings reveal the powerful nature of the forces that guide evolution of Env and their conservation across different populations. Such forces have caused a gradual decrease in the interpopulation diversity of Env despite an increasing intrapopulation diversity.IMPORTANCE The Env protein of HIV-1 is the primary target in AIDS vaccine design. Frequent mutations in the virus increase the number of Env forms in each population, limiting the efficacy of AIDS vaccines. Comparison of newly emerging forms in different populations showed that each position of Env is evolving toward a specific combination of amino acids. Similar changes are occurring in different HIV-1 subtypes and geographic regions toward the same position-specific combinations of amino acids, often from distinct ancestral sequences. The predictable nature of HIV-1 Env evolution, as shown here, provides a new framework for designing vaccines that are tailored to the unique combination of variants expected to emerge in each virus subtype and geographic region.

A de novo approach to inferring within-host fitness effects during untreated HIV-1 infection

In the absence of effective antiviral therapy, HIV-1 evolves in response to the within-host environment, of which the immune system is an important aspect. During the earliest stages of infection, this process of evolution is very rapid, driven by a small number of CTL escape mutations. As the infection progresses, immune escape variants evolve under reduced magnitudes of selection, while competition between an increasing number of polymorphic alleles (i.e., clonal interference) makes it difficult to quantify the magnitude of selection acting upon specific variant alleles. To tackle this complex problem, we developed a novel multi-locus inference method to evaluate the role of selection during the chronic stage of within-host infection. We applied this method to targeted sequence data from the p24 and gp41 regions of HIV-1 collected from 34 patients with long-term untreated HIV-1 infection. We identify a broad distribution of beneficial fitness effects during infection, with a small number of variants evolving under strong selection and very many variants evolving under weaker selection. The uniquely large number of infections analysed granted a previously unparalleled statistical power to identify loci at which selection could be inferred to act with statistical confidence. Our model makes no prior assumptions about the nature of alleles under selection, such that any synonymous or non-synonymous variant may be inferred to evolve under selection. However, the majority of variants inferred with confidence to be under selection were non-synonymous in nature, and in most cases were have previously been associated with either CTL escape in p24 or neutralising antibody escape in gp41. We also identified a putative new CTL escape site (residue 286 in gag), and a region of gp41 (including residues 644, 648, 655 in env) likely to be associated with immune escape. Sites inferred to be under selection in multiple hosts have high within-host and between-host diversity although not all sites with high between-host diversity were inferred to be under selection at the within-host level. Our identification of selection at sites associated with resistance to broadly neutralising antibodies (bNAbs) highlights the need to fully understand the role of selection in untreated individuals when designing bNAb based therapies.

Gp41-targeted antibodies restore infectivity of a fusion-deficient HIV-1 envelope glycoprotein

The HIV-1 envelope glycoprotein (Env) mediates viral entry via conformational changes associated with binding the cell surface receptor (CD4) and coreceptor (CCR5/CXCR4), resulting in subsequent fusion of the viral and cellular membranes. While the gp120 Env surface subunit has been extensively studied for its role in viral entry and evasion of the host immune response, the gp41 transmembrane glycoprotein and its role in natural infection are less well characterized. Here, we identified a primary HIV-1 Env variant that consistently supports >300% increased viral infectivity in the presence of autologous or heterologous HIV-positive plasma. However, in the absence of HIV-positive plasma, viruses with this Env exhibited reduced infectivity that was not due to decreased CD4 binding. Using Env chimeras and sequence analysis, we mapped this phenotype to a change Q563R, in the gp41 heptad repeat 1 (HR1) region. We demonstrate that Q563R reduces viral infection by disrupting formation of the gp41 six-helix bundle required for virus-cell membrane fusion. Intriguingly, antibodies that bind cluster I epitopes on gp41 overcome this inhibitory effect, restoring infectivity to wild-type levels. We further demonstrate that the Q563R change increases HIV-1 sensitivity to broadly neutralizing antibodies (bNAbs) targeting the gp41 membrane-proximal external region (MPER). In summary, we identify an HIV-1 Env variant with impaired infectivity whose Env functionality is restored through the binding of host antibodies. These data contribute to our understanding of gp41 residues involved in membrane fusion and identify a mechanism by which host factors can alleviate a viral defect.

CpG-creating mutations are costly in many human viruses

Mutations can occur throughout the virus genome and may be beneficial, neutral or deleterious. We are interested in mutations that yield a C next to a G, producing CpG sites. CpG sites are rare in eukaryotic and viral genomes. For the eukaryotes, it is thought that CpG sites are rare because they are prone to mutation when methylated. In viruses, we know less about why CpG sites are rare. A previous study in HIV suggested that CpG-creating transition mutations are more costly than similar non-CpG-creating mutations. To determine if this is the case in other viruses, we analyzed the allele frequencies of CpG-creating and non-CpG-creating mutations across various strains, subtypes, and genes of viruses using existing data obtained from Genbank, HIV Databases, and Virus Pathogen Resource. Our results suggest that CpG sites are indeed costly for most viruses. By understanding the cost of CpG sites, we can obtain further insights into the evolution and adaptation of viruses.

Drug Resistance Evolution in HIV in the Late 1990s: Hard Sweeps, Soft Sweeps, Clonal Interference and the Accumulation of Drug Resistance Mutations

The evolution of drug resistance in pathogens such as HIV is an important and widely known example in the field of evolutionary medicine. Here, we focus on a unique data set from the late 1990s with multiple viral sequences from multiple time points in 118 patients. We study patterns of evolutionary dynamics in the viral populations in these patients who were treated with Reverse Transcriptase Inhibitors and Protease Inhibitors in the late 1990s. Specifically, we aim to visualize and analyze examples of population genetic processes such as selective sweeps and clonal interference. The figures and descriptions in this paper can be used in evolution and population genetics classes. We show and analyze a wide variety of patterns, specifically: soft sweeps, hard sweeps, softening sweeps and hardening sweeps, simultaneous sweeps, accumulation of mutations and clonal interference.

Analysis of unusual and signature APOBEC-mutations in HIV-1 pol next-generation sequences

Introduction

At low mutation-detection thresholds, next generation sequencing (NGS) for HIV-1 genotypic resistance testing is susceptible to artifactual detection of mutations arising from PCR error and APOBEC-mediated G-to-A hypermutation.

Methods

We analyzed published HIV-1 pol Illumina NGS data to characterize the distribution of mutations at eight NGS mutation detection thresholds: 20%, 10%, 5%, 2%, 1%, 0.5%, 0.2%, and 0.1%. At each threshold, we determined proportions of amino acid mutations that were unusual (defined as having a prevalence <0.01% in HIV-1 group M sequences) or signature APOBEC mutations.

Results

Eight studies, containing 855 samples, in the NCBI Sequence Read Archive were analyzed. As detection thresholds were lowered, there was a progressive increase in the proportion of positions with usual and unusual mutations and in the proportion of all mutations that were unusual. The median proportion of positions with an unusual mutation increased gradually from 0% at the 20% threshold to 0.3% at the 1% threshold and then exponentially to 1.3% (0.5% threshold), 6.9% (0.2% threshold), and 23.2% (0.1% threshold). In two of three studies with available plasma HIV-1 RNA levels, the proportion of positions with unusual mutations was negatively associated with virus levels. Although the complete set of signature APOBEC mutations was much smaller than that of unusual mutations, the former outnumbered the latter in one-sixth of samples at the 0.5%, 1%, and 2% thresholds.

Conclusions

The marked increase in the proportion of positions with unusual mutations at thresholds below 1% and in samples with lower virus loads suggests that, at low thresholds, many unusual mutations are artifactual, reflecting PCR error or G-to-A hypermutation. Profiling the numbers of unusual and signature APOBEC pol mutations at different NGS mutation detection thresholds may be useful to avoid selecting a threshold that is too low and poses an unacceptable risk of identifying artifactual mutations.

Molecular dating and viral load growth rates suggested that the eclipse phase lasted about a week in HIV-1 infected adults in East Africa and Thailand

Most HIV-1 infected individuals do not know their infection dates. Precise infection timing is crucial information for studies that document transmission networks or drug levels at infection. To improve infection timing, we used the prospective RV217 cohort where the window when plasma viremia becomes detectable is narrow: the last negative visit occurred a median of four days before the first detectable HIV-1 viremia with an RNA test, referred below as diagnosis. We sequenced 1,280 HIV-1 genomes from 39 participants at a median of 4, 32 and 170 days post-diagnosis. HIV-1 infections were dated by using sequence-based methods and a viral load regression method. Bayesian coalescent and viral load regression estimated that infections occurred a median of 6 days prior to diagnosis (IQR: 9–3 and 11–4 days prior, respectively). Poisson-Fitter, which analyzes the distribution of hamming distances among sequences, estimated a median of 7 days prior to diagnosis (IQR: 15–4 days) based on sequences sampled 4 days post-diagnosis, but it did not yield plausible results using sequences sampled at 32 days. Fourteen participants reported a high-risk exposure event at a median of 8 days prior to diagnosis (IQR: 12 to 6 days prior). These different methods concurred that HIV-1 infection occurred about a week before detectable viremia, corresponding to 20 days (IQR: 34–15 days) before peak viral load. Together, our methods comparison helps define a framework for future dating studies in early HIV-1 infection.

HIV-1 infected individuals rarely know when they became infected but knowing when an infection occurred provides critical information regarding HIV-1 pathogenesis and epidemiology. Using a unique cohort in which infection was known to have occurred in a narrow interval, we investigated methods to estimate the timing of infections. Several methods suggested that HIV-1 infection typically occurs a median of one week before the infection can be detected by HIV-1 RNA testing. Going forward, we provide a strategy that can be used to elucidate the origin of an acute/early infection.

Impact of Antiretroviral Therapy Duration on HIV-1 Infection of T Cells within Anatomic Sites

Understanding the impact of antiretroviral therapy (ART) duration on HIV-infected cells is critical for developing successful curative strategies. To address this issue, we conducted a cross-sectional/inter-participant genetic characterization of HIV-1 RNA from pre- and on-therapy plasmas and HIV-1 DNA from CD4⁺ T cell subsets derived from peripheral blood (PB), lymph node (LN), and gut tissues of 26 participants after 3 to 17.8 years of ART. Our studies revealed in four acute/early participants who had paired PB and LN samples a substantial reduction in the proportion of HIV-infected cells per year on therapy within the LN. Extrapolation to all 12 acute/early participants estimated a much smaller reduction in the proportion of HIV-1-infected cells within LNs per year on therapy that was similar to that in the participants treated during chronic infection. LN-derived effector memory T (T_EM) cells contained HIV-1 DNA that was genetically identical to viral sequences derived from pre- and on-therapy plasma samples. The proportion of identical HIV-1 DNA sequences increased within PB-derived T_EM cells. However, the infection frequency of T_EM cells in PB was stable, indicating that cellular proliferation that compensates for T cell loss over time contributes to HIV-1 persistence. This study suggests that ART reduces HIV-infected T cells and that clonal expansion of HIV-infected cells maintains viral persistence. Importantly, LN-derived T_EM cells are a probable source of HIV-1 genomes capable of producing infectious HIV-1 and should be targeted by future curative strategies.IMPORTANCE HIV-1 persists as an integrated genome in CD4⁺ memory T cells during effective therapy, and cessation of current treatments results in resumption of viral replication. To date, the impact of antiretroviral therapy duration on HIV-infected CD4⁺ T cells and the mechanisms of viral persistence in different anatomic sites is not clearly elucidated. In the current study, we found that treatment duration was associated with a reduction in HIV-infected T cells. Our genetic analyses revealed that CD4⁺ effector memory T (T_EM) cells derived from the lymph node appeared to contain provirus that was genetically identical to plasma-derived virions. Moreover, we found that cellular proliferation counterbalanced the decay of HIV-infected cells throughout therapy. The contribution of cellular proliferation to viral persistence is particularly significant in T_EM cells. Our study emphasizes the importance of HIV-1 intervention and provides new insights into the location of memory T cells infected with HIV-1 DNA, which is capable of contributing to viremia.

Natural selection favoring more transmissible HIV detected in United States molecular transmission network

HIV molecular epidemiology can identify clusters of individuals with elevated rates of HIV transmission. These variable transmission rates are primarily driven by host risk behavior; however, the effect of viral traits on variable transmission rates is poorly understood. Viral load, the concentration of HIV in blood, is a heritable viral trait that influences HIV infectiousness and disease progression. Here, we reconstruct HIV genetic transmission clusters using data from the United States National HIV Surveillance System and report that viruses in clusters, inferred to be frequently transmitted, have higher viral loads at diagnosis. Further, viral load is higher in people in larger clusters and with increased network connectivity, suggesting that HIV in the United States is experiencing natural selection to be more infectious and virulent. We also observe a concurrent increase in viral load at diagnosis over the last decade. This evolutionary trajectory may be slowed by prevention strategies prioritized toward rapidly growing transmission clusters.

Evolutionary Dynamics in Structured Populations Under Strong Population Genetic Forces

In the long-term neutral equilibrium, high rates of migration between subpopulations result in little population differentiation. However, in the short-term, even very abundant migration may not be enough for subpopulations to equilibrate immediately. In this study, we investigate dynamical patterns of short-term population differentiation in adapting populations via stochastic and analytical modeling through time. We characterize a regime in which selection and migration interact to create non-monotonic patterns of population differentiation over time when migration is weaker than selection, but stronger than drift. We demonstrate how these patterns can be leveraged to estimate high migration rates using approximate Bayesian computation. We apply this approach to estimate fast migration in a rapidly adapting intra-host Simian-HIV population sampled from different anatomical locations. We find differences in estimated migration rates between different compartments, even though all are above [Formula: see text] = 1. This work demonstrates how studying demographic processes on the timescale of selective sweeps illuminates processes too fast to leave signatures on neutral timescales.

A CRISPR/Cas9 library to map the HIV-1 provirus genetic fitness

The integrated proviral genome is the major barrier to a cure for HIV-1 infection. Genome editing technologies, such as CRISPR/Cas9, may disable or remove the HIV-1 provirus by introducing DNA double strand breaks at sequence specific sites in the viral genome. Host DNA repair by the error-prone non-homologous end joining pathway generates mutagenic insertions or deletions at the break. CRISPR/Cas9 editing has been shown to reduce replication competent viral genomes in cell culture, but only a minority of possible genome editing targets have been assayed. Currently there is no map of double strand break genetic fitness for HIV-1 to inform the choice of editing targets. However, CRISPR/Cas9 genome editing makes it possible to target double strand breaks along the length of the provirus to generate a double strand break genetic fitness map. We identified all possible HIV-1 targets with different bacterial species of CRISPR/Cas9. This library of guide RNAs was evaluated for GC content and potential off-target sites in the human genome. Complexity of the library was reduced by eliminating duplicate guide RNA targets in the HIV-1 long terminal repeats and targets in the env gene. Although the HIV-1 genome is AT-rich, the S. pyogenes CRISPR/Cas9 with the proto-spacer adjacent motif NGG offers the most HIV-1 guide RNAs. This library of HIV-1 guide RNAs may be used to generate a double strand break genetic fragility map to be further applied to any genome editing technology designed for the HIV-1 provirus. Keywords: HIV-1; genome editing; CRISPR; genetic fitness; guide RNAs.

An Evolutionary Model-Based Approach To Quantify the Genetic Barrier to Drug Resistance in Fast-Evolving Viruses and Its Application to HIV-1 Subtypes and Integrase Inhibitors

Viral pathogens causing global disease burdens are often characterized by high rates of evolutionary changes. The extensive viral diversity at baseline can shorten the time to escape from therapeutic or immune selective pressure and alter mutational pathways. The impact of genotypic background on the barrier to resistance can be difficult to capture, particularly for agents in experimental stages or that are recently approved or expanded into new patient populations. We developed an evolutionary model-based counting method to quickly quantify the population genetic potential to resistance and assess population differences. We demonstrate its applicability to HIV-1 integrase inhibitors, as their increasing use globally contrasts with limited availability of non-B subtype resistant sequence data and corresponding knowledge gap. A large sequence data set encompassing most prevailing HIV-1 subtypes and resistance-associated mutations of currently approved integrase inhibitors was investigated. A complex interplay between codon predominance, polymorphisms, and associated evolutionary costs resulted in a subtype-dependent varied genetic potential for 15 resistance mutations against integrase inhibitors. While we confirm the lower genetic barrier of subtype B for G140S, we convincingly discard a similar effect previously suggested for G140C. A supplementary analysis for HIV-1 reverse transcriptase inhibitors identified a lower genetic barrier for K65R in subtype C through differential codon usage not reported before. To aid evolutionary interpretations of genomic differences for antiviral strategies, we advanced existing counting methods with increased sensitivity to identify subtype dependencies of resistance emergence. Future applications include novel HIV-1 drug classes or vaccines, as well as other viral pathogens.

Constrained Mutational Sampling of Amino Acids in HIV-1 Protease Evolution

The evolution of HIV-1 protein sequences should be governed by a combination of factors including nucleotide mutational probabilities, the genetic code, and fitness. The impact of these factors on protein sequence evolution is interdependent, making it challenging to infer the individual contribution of each factor from phylogenetic analyses alone. We investigated the protein sequence evolution of HIV-1 by determining an experimental fitness landscape of all individual amino acid changes in protease. We compared our experimental results to the frequency of protease variants in a publicly available data set of 32,163 sequenced isolates from drug-naïve individuals. The most common amino acids in sequenced isolates supported robust experimental fitness, indicating that the experimental fitness landscape captured key features of selection acting on protease during viral infections of hosts. Amino acid changes requiring multiple mutations from the likely ancestor were slightly less likely to support robust experimental fitness than single mutations, consistent with the genetic code favoring chemically conservative amino acid changes. Amino acids that were common in sequenced isolates were predominantly accessible by single mutations from the likely protease ancestor. Multiple mutations commonly observed in isolates were accessible by mutational walks with highly fit single mutation intermediates. Our results indicate that the prevalence of multiple-base mutations in HIV-1 protease is strongly influenced by mutational sampling.

An Antigenic Atlas of HIV-1 Escape from Broadly Neutralizing Antibodies Distinguishes Functional and Structural Epitopes

Anti-HIV broadly neutralizing antibodies (bnAbs) have revealed vaccine targets on the virus's envelope (Env) protein and are themselves promising immunotherapies. The efficacy of bnAb-based therapies and vaccines depends in part on how readily the virus can escape neutralization. Although structural studies can define contacts between bnAbs and Env, only functional studies can define mutations that confer escape. Here, we mapped how all possible single amino acid mutations in Env affect neutralization of HIV by nine bnAbs targeting five epitopes. For most bnAbs, mutations at only a small fraction of structurally defined contact sites mediated escape, and most escape occurred at sites near, but not in direct contact with, the antibody. The Env mutations selected by two pooled bnAbs were similar to those expected from the combination of the bnAbs's independent action. Overall, our mutation-level antigenic atlas provides a comprehensive dataset for understanding viral immune escape and refining therapies and vaccines.

APOBEC3G Regulation of the Evolutionary Race Between Adaptive Immunity and Viral Immune Escape Is Deeply Imprinted in the HIV Genome

APOBEC3G (A3G) is a host enzyme that mutates the genomes of retroviruses like HIV. Since A3G is expressed pre-infection, it has classically been considered an agent of innate immunity. We and others previously showed that the impact of A3G-induced mutations on the HIV genome extends to adaptive immunity also, by generating cytotoxic T cell (CTL) escape mutations. Accordingly, HIV genomic sequences encoding CTL epitopes often contain A3G-mutable “hotspot” sequence motifs, presumably to channel A3G action toward CTL escape. Here, we studied the depths and consequences of this apparent viral genome co-evolution with A3G. We identified all potential CTL epitopes in Gag, Pol, Env, and Nef restricted to several HLA class I alleles. We simulated A3G-induced mutations within CTL epitope-encoding sequences, and flanking regions. From the immune recognition perspective, we analyzed how A3G-driven mutations are predicted to impact CTL-epitope generation through modulating proteasomal processing and HLA class I binding. We found that A3G mutations were most often predicted to result in diminishing/abolishing HLA-binding affinity of peptide epitopes. From the viral genome evolution perspective, we evaluated enrichment of A3G hotspots at sequences encoding CTL epitopes and included control sequences in which the HIV genome was randomly shuffled. We found that sequences encoding immunogenic epitopes exhibited a selective enrichment of A3G hotspots, which were strongly biased to translate to non-synonymous amino acid substitutions. When superimposed on the known mutational gradient across the entire length of the HIV genome, we observed a gradient of A3G hotspot enrichment, and an HLA-specific pattern of the potential of A3G hotspots to lead to CTL escape mutations. These data illuminate the depths and extent of the co-evolution of the viral genome to subvert the host mutator A3G.

Inferring population genetics parameters of evolving viruses using time-series data

With the advent of deep sequencing techniques, it is now possible to track the evolution of viruses with ever-increasing detail. Here, we present Flexible Inference from Time-Series (FITS)-a computational tool that allows inference of one of three parameters: the fitness of a specific mutation, the mutation rate or the population size from genomic time-series sequencing data. FITS was designed first and foremost for analysis of either short-term Evolve & Resequence (E&R) experiments or rapidly recombining populations of viruses. We thoroughly explore the performance of FITS on simulated data and highlight its ability to infer the fitness/mutation rate/population size. We further show that FITS can infer meaningful information even when the input parameters are inexact. In particular, FITS is able to successfully categorize a mutation as advantageous or deleterious. We next apply FITS to empirical data from an E&R experiment on poliovirus where parameters were determined experimentally and demonstrate high accuracy in inference.

Virus-inclusive single-cell RNA sequencing reveals the molecular signature of progression to severe dengue

A fraction of the 400 million people infected with dengue annually progresses to severe dengue (SD). Yet, there are currently no biomarkers to predict disease progression. We profiled the landscape of host transcripts and viral RNA in thousands of single blood cells from dengue patients prior to progressing to SD. We discovered cell type-specific immune activation and candidate predictive biomarkers. We also determined preferential virus association with specific cell populations, particularly naive B cells and monocytes. We explored immune activation of bystander cells, clonality and somatic evolution of adaptive immune repertoires, as well as viral genomics. This multifaceted approach could advance understanding of pathogenesis of any viral infection, map an atlas of infected cells, and promote the development of prognostics.

Dengue virus (DENV) infection can result in severe complications. However, the understanding of the molecular correlates of severity is limited, partly due to difficulties in defining the peripheral blood mononuclear cells (PBMCs) that contain DENV RNA in vivo. Accordingly, there are currently no biomarkers predictive of progression to severe dengue (SD). Bulk transcriptomics data are difficult to interpret because blood consists of multiple cell types that may react differently to infection. Here, we applied virus-inclusive single-cell RNA-seq approach (viscRNA-Seq) to profile transcriptomes of thousands of single PBMCs derived early in the course of disease from six dengue patients and four healthy controls and to characterize distinct leukocyte subtypes that harbor viral RNA (vRNA). Multiple IFN response genes, particularly MX2 in naive B cells and CD163 in CD14⁺ CD16⁺ monocytes, were up-regulated in a cell-specific manner before progression to SD. The majority of vRNA-containing cells in the blood of two patients who progressed to SD were naive IgM B cells expressing the CD69 and CXCR4 receptors and various antiviral genes, followed by monocytes. Bystander, non-vRNA–containing B cells also demonstrated immune activation, and IgG1 plasmablasts from two patients exhibited clonal expansions. Lastly, assembly of the DENV genome sequence revealed diversity at unexpected sites. This study presents a multifaceted molecular elucidation of natural dengue infection in humans with implications for any tissue and viral infection and proposes candidate biomarkers for prediction of SD.

Estimating the mutational fitness effects distribution during early HIV infection

The evolution of HIV during acute infection is often considered a neutral process. Recent analysis of sequencing data from this stage of infection, however, showed high levels of shared mutations between independent viral populations. This suggests that selection might play a role in the early stages of HIV infection. We adapted an existing model for random evolution during acute HIV-infection to include selection. Simulations of this model were used to fit a global mutational fitness effects distribution to previously published sequencing data of the env gene of individuals with acute HIV infection. Measures of sharing between viral populations were used as summary statistics to compare the data to the simulations. We confirm that evolution during acute infection is significantly different from neutral. The distribution of mutational fitness effects is best fit by a distribution with a low, but significant fraction of beneficial mutations and a high fraction of deleterious mutations. While most mutations are neutral or deleterious in this model, about 5% of mutations are beneficial. These beneficial mutations will, on average, result in a small but significant increase in fitness. When assuming no epistasis, this indicates that, at the moment of transmission, HIV is near, but not on the fitness peak for early infection.

Relationship between latent and rebound viruses in a clinical trial of anti-HIV-1 antibody 3BNC117

A clinical trial was performed to evaluate 3BNC117, a potent anti-HIV-1 antibody, in infected individuals during suppressive antiretroviral therapy and subsequent analytical treatment interruption (ATI). The circulating reservoir was evaluated by quantitative and qualitative viral outgrowth assay (Q²VOA) at entry and after 6 mo. There were no significant quantitative changes in the size of the reservoir before ATI, and the composition of circulating reservoir clones varied in a manner that did not correlate with 3BNC117 sensitivity. 3BNC117 binding site amino acid variants found in rebound viruses preexisted in the latent reservoir. However, only 3 of 217 rebound viruses were identical to 868 latent viruses isolated by Q²VOA and near full-length sequencing. Instead, 63% of the rebound viruses appeared to be recombinants, even in individuals with 3BNC117-resistant reservoir viruses. In conclusion, viruses emerging during ATI in individuals treated with 3BNC117 are not the dominant species found in the circulating latent reservoir, but frequently appear to represent recombinants of latent viruses.

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.

Within-patient mutation frequencies reveal fitness costs of CpG dinucleotides and drastic amino acid changes in HIV

HIV has a high mutation rate, which contributes to its ability to evolve quickly. However, we know little about the fitness costs of individual HIV mutations in vivo, their distribution and the different factors shaping the viral fitness landscape. We calculated the mean frequency of transition mutations at 870 sites of the pol gene in 160 patients, allowing us to determine the cost of these mutations. As expected, we found high costs for non-synonymous and nonsense mutations as compared to synonymous mutations. In addition, we found that non-synonymous mutations that lead to drastic amino acid changes are twice as costly as those that do not and mutations that create new CpG dinucleotides are also twice as costly as those that do not. We also found that G→A and C→T mutations are more costly than A→G mutations. We anticipate that our new in vivo frequency-based approach will provide insights into the fitness landscape and evolvability of not only HIV, but a variety of microbes.

A probabilistic view on the deterministic mutation-selection equation: dynamics, equilibria, and ancestry via individual lines of descent

We reconsider the deterministic haploid mutation-selection equation with two types. This is an ordinary differential equation that describes the type distribution (forward in time) in a population of infinite size. This paper establishes ancestral (random) structures inherent in this deterministic model. In a first step, we obtain a representation of the deterministic equation's solution (and, in particular, of its equilibria) in terms of an ancestral process called the killed ancestral selection graph. This representation allows one to understand the bifurcations related to the error threshold phenomenon from a genealogical point of view. Next, we characterise the ancestral type distribution by means of the pruned lookdown ancestral selection graph and study its properties at equilibrium. We also provide an alternative characterisation in terms of a piecewise-deterministic Markov process. Throughout, emphasis is on the underlying dualities as well as on explicit results.