Analysis of HIV-1 env gene sequences reveals evidence for a low effective number in the viral population

Predator-Prey Dynamics of Intra-Host Simian Immunodeficiency Virus Evolution Within the Untreated Host

The dynamic nature of the SIV population during disease progression in the SIV/macaque model of AIDS and the factors responsible for its behavior have not been documented, largely owing to the lack of sufficient spatial and temporal sampling of both viral and host data from SIV-infected animals. In this study, we detail Bayesian coalescent inference of the changing collective intra-host viral effective population size (N_e ) from various tissues over the course of infection and its relationship with what we demonstrate is a continuously changing immune cell repertoire within the blood. Although the relative contribution of these factors varied among hosts and time points, the adaptive immune response best explained the overall periodic dynamic behavior of the effective virus population. Data exposing the nature of the relationship between the virus and immune cell populations revealed the plausibility of an eco-evolutionary mathematical model, which was able to mimic the large-scale oscillations in N_e through virus escape from relatively few, early immunodominant responses, followed by slower escape from several subdominant and weakened immune populations. The results of this study suggest that SIV diversity within the untreated host is governed by a predator-prey relationship, wherein differing phases of infection are the result of adaptation in response to varying immune responses. Previous investigations into viral population dynamics using sequence data have focused on single estimates of the effective viral population size (N_e ) or point estimates over sparse sampling data to provide insight into the precise impact of immune selection on virus adaptive behavior. Herein, we describe the use of the coalescent phylogenetic frame- work to estimate the relative changes in N_e over time in order to quantify the relationship with empirical data on the dynamic immune composition of the host. This relationship has allowed us to expand on earlier simulations to build a predator-prey model that explains the deterministic behavior of the virus over the course of disease progression. We show that sequential viral adaptation can occur in response to phases of varying immune pressure, providing a broader picture of the viral response throughout the entire course of progression to AIDS.

Evolution of Protease Inhibitor Resistance in Human Immunodeficiency Virus Type 1 Infected Patients Failing Protease Inhibitor Monotherapy as Second-line Therapy in Low-income Countries: An Observational Analysis Within the EARNEST Randomized Trial

BACKGROUND

Limited viral load (VL) testing in human immunodeficiency virus (HIV) treatment programs in low-income countries often delays detection of treatment failure. The impact of remaining on failing protease inhibitor (PI)-containing regimens is unclear.

METHODS

We retrospectively tested VL in 2164 stored plasma samples from 386 patients randomized to receive lopinavir monotherapy (after initial raltegravir induction) in the Europe-Africa Research Network for Evaluation of Second-line Therapy (EARNEST) trial. Protease genotypic resistance testing was performed when VL >1000 copies/mL. We assessed evolution of PI resistance mutations from virological failure (confirmed VL >1000 copies/mL) until PI monotherapy discontinuation and examined associations using mixed-effects models.

RESULTS

Median post-failure follow-up (in 118 patients) was 68 (interquartile range, 48-88) weeks. At failure, 20% had intermediate/high-level resistance to lopinavir. At 40-48 weeks post-failure, 68% and 51% had intermediate/high-level resistance to lopinavir and atazanavir; 17% had intermediate-level resistance (none high) to darunavir. Common PI mutations were M46I, I54V, and V82A. On average, 1.7 (95% confidence interval 1.5-2.0) PI mutations developed per year; increasing after the first mutation; decreasing with subsequent mutations (P < .0001). VL changes were modest, mainly driven by nonadherence (P = .006) and PI mutation development (P = .0002); I47A was associated with a larger increase in VL than other mutations (P = .05).

CONCLUSIONS

Most patients develop intermediate/high-level lopinavir resistance within 1 year of ongoing viral replication on monotherapy but retain susceptibility to darunavir. Viral load increased slowly after failure, driven by non-adherence and PI mutation development.

CLINICAL TRIALS REGISTRATION

NCT00988039.

The Puzzle of HIV Neutral and Selective Evolution

HIV is one of the fastest evolving organisms known. It evolves about 1 million times faster than its host, humans. Because HIV establishes chronic infections, with continuous evolution, its divergence within a single infected human surpasses the divergence of the entire humanoid history. Yet, it is still the same virus, infecting the same cell types and using the same replication machinery year after year. Hence, one would think that most mutations that HIV accumulates are neutral. But the picture is more complicated than that. HIV evolution is also a clear example of strong positive selection, that is, mutants have a survival advantage. How do these facts come together?

Effects of life history and ecology on virus evolutionary potential

The life history traits of viruses pose many consequences for viral population structure. In turn, population structure may influence the evolutionary trajectory of a virus. Here we review factors that affect the evolutionary potential of viruses, including rates of mutation and recombination, bottlenecks, selection pressure, and ecological factors such as the requirement for hosts and vectors. Mutation, while supplying a pool of raw genetic material, also results in the generation of numerous unfit mutants. The infection of multiple host species may expand a virus' ecological niche, although it may come at a cost to genetic diversity. Vector-borne viruses often experience a diminished frequency of positive selection and exhibit little diversity, and resistance against vector-borne viruses may thus be more durable than against non-vectored viruses. Evidence indicates that adaptation to a vector is more evolutionarily difficult than adaptation to a host. Overall, a better understanding of how various factors influence viral dynamics in both plant and animal pathosystems will lead to more effective anti-viral treatments and countermeasures.

Neutral Theory and Rapidly Evolving Viral Pathogens

The evolution of viral pathogens is shaped by strong selective forces that are exerted during jumps to new hosts, confrontations with host immune responses and antiviral drugs, and numerous other processes. However, while undeniably strong and frequent, adaptive evolution is largely confined to small parts of information-packed viral genomes, and the majority of observed variation is effectively neutral. The predictions and implications of the neutral theory have proven immensely useful in this context, with applications spanning understanding within-host population structure, tracing the origins and spread of viral pathogens, predicting evolutionary dynamics, and modeling the emergence of drug resistance. We highlight the multiple ways in which the neutral theory has had an impact, which has been accelerated in the age of high-throughput, high-resolution genomics.

Phylodynamic Inference across Epidemic Scales

Within-host genetic diversity and large transmission bottlenecks confound phylodynamic inference of epidemiological dynamics. Conventional phylodynamic approaches assume that nodes in a time-scaled pathogen phylogeny correspond closely to the time of transmission between hosts that are ancestral to the sample. However, when hosts harbor diverse pathogen populations, node times can substantially pre-date infection times. Imperfect bottlenecks can cause lineages sampled in different individuals to coalesce in unexpected patterns. To address realistic violations of standard phylodynamic assumptions we developed a new inference approach based on a multi-scale coalescent model, accounting for nonlinear epidemiological dynamics, heterogeneous sampling through time, non-negligible genetic diversity of pathogens within hosts, and imperfect transmission bottlenecks. We apply this method to HIV-1 and Ebola virus (EBOV) outbreak sequence data, illustrating how and when conventional phylodynamic inference may give misleading results. Within-host diversity of HIV-1 causes substantial upwards bias in the number of infected hosts using conventional coalescent models, but estimates using the multi-scale model have greater consistency with reported number of diagnoses through time. In contrast, we find that within-host diversity of EBOV has little influence on estimated numbers of infected hosts or reproduction numbers, and estimates are highly consistent with the reported number of diagnoses through time. The multi-scale coalescent also enables estimation of within-host effective population size using single sequences from a random sample of patients. We find within-host population genetic diversity of HIV-1 p17 to be 2Nμ=0.012 (95% CI 0.0066-0.023), which is lower than estimates based on HIV envelope serial sequencing of individual patients.

Donor-Recipient Identification in Para- and Poly-phyletic Trees Under Alternative HIV-1 Transmission Hypotheses Using Approximate Bayesian Computation

Diversity of the founding population of Human Immunodeficiency Virus Type 1 (HIV-1) transmissions raises many important biological, clinical, and epidemiological issues. In up to 40% of sexual infections, there is clear evidence for multiple founding variants, which can influence the efficacy of putative prevention methods, and the reconstruction of epidemiologic histories. To infer who-infected-whom, and to compute the probability of alternative transmission scenarios while explicitly taking phylogenetic uncertainty into account, we created an approximate Bayesian computation (ABC) method based on a set of statistics measuring phylogenetic topology, branch lengths, and genetic diversity. We applied our method to a suspected heterosexual transmission case involving three individuals, showing a complex monophyletic-paraphyletic-polyphyletic phylogenetic topology. We detected that seven phylogenetic lineages had been transmitted between two of the individuals based on the available samples, implying that many more unsampled lineages had also been transmitted. Testing whether the lineages had been transmitted at one time or over some length of time suggested that an ongoing superinfection process over several years was most likely. While one individual was found unlinked to the other two, surprisingly, when evaluating two competing epidemiological priors, the donor of the two that did infect each other was not identified by the host root-label, and was also not the primary suspect in that transmission. This highlights that it is important to take epidemiological information into account when analyzing support for one transmission hypothesis over another, as results may be nonintuitive and sensitive to details about sampling dates relative to possible infection dates. Our study provides a formal inference framework to include information on infection and sampling times, and to investigate ancestral node-label states, transmission direction, transmitted genetic diversity, and frequency of transmission.

HIV Progression Depends on Codon and Amino Acid Usage Profile of Envelope Protein and Associated Host-Genetic Influence

Acquired immune deficiency syndrome (AIDS) is a spectrum of conditions caused by infection with the human immunodeficiency virus (HIV). Two types of HIV have been characterized: HIV-1 and HIV-2. The present study investigated whether evolutionary selection pressure differs between rapid progressor (RP), slow progressor (SP), and long-term non-progressor (LTNP) of HIV-I infected individuals. An unexpected association between the evolutionary rate of substitution in envelope (env) gene and disease progression is observed. Our present study suggests that env genes of LTNP are subject to unusually strong functional constraint with respect to RP. We also observed that the three categories of env genes i.e., RP, SP, and LTNP, had their own characteristic pattern of amino acid usage and SP and LTNP sequences shared similar patterns of amino acid usage different from RP sequences and evolutionary rate significantly influenced the amino acid usage pattern of the three different types of env gene sequences. It was also noted that the evolutionary rate for the glycosylation sites of LTNP and SP sequences were even significantly less than the RP sequences. Comparative analysis on the influence of human host on the three categories of env genes are well correlated with the rates of disease progression suggesting the adaptive strategies of the viruses for successful residence and infection. Host associated selective constraints appeared most relaxed on the RP sequences and strongest in LTNP sequences. The present study clearly portrays how evolutionary selection pressure differs between three categories of env genes i.e., RP, SP, and LTNP. The env genes, coding for the env glycoproteins, experience severe selection constraints from the host due to their constant exposure to the host immune system. In this perspective it might be suggested that env gene evolution occurs mainly by negative selection with the occurrence of mutation that might not reach fixation in the viral population. This work also confers a deeper insight into the crucial effects of host factors that govern the overall progression of HIV infection.

A spatio-temporal assessment of simian/human immunodeficiency virus (SHIV) evolution reveals a highly dynamic process within the host

The process by which drug-resistant HIV-1 arises and spreads spatially within an infected individual is poorly understood. Studies have found variable results relating how HIV-1 in the blood differs from virus sampled in tissues, offering conflicting findings about whether HIV-1 throughout the body is homogeneously distributed. However, most of these studies sample only two compartments and few have data from multiple time points. To directly measure how drug resistance spreads within a host and to assess how spatial structure impacts its emergence, we examined serial sequences from four macaques infected with RT-SHIVmne027, a simian immunodeficiency virus encoding HIV-1 reverse transcriptase (RT), and treated with RT inhibitors. Both viral DNA and RNA (vDNA and vRNA) were isolated from the blood (including plasma and peripheral blood mononuclear cells), lymph nodes, gut, and vagina at a median of four time points and RT was characterized via single-genome sequencing. The resulting sequences reveal a dynamic system in which vRNA rapidly acquires drug resistance concomitantly across compartments through multiple independent mutations. Fast migration results in the same viral genotypes present across compartments, but not so fast as to equilibrate their frequencies immediately. The blood and lymph nodes were found to be compartmentalized rarely, while both the blood and lymph node were more frequently different from mucosal tissues. This study suggests that even oft-sampled blood does not fully capture the viral dynamics in other parts of the body, especially the gut where vRNA turnover was faster than the plasma and vDNA retained fewer wild-type viruses than other sampled compartments. Our findings of transient compartmentalization across multiple tissues may help explain the varied results of previous compartmentalization studies in HIV-1.

Quantifying the Sensitivity of HIV-1 Viral Entry to Receptor and Coreceptor Expression

Infection by many viruses begins with fusion of viral and cellular lipid membranes, followed by entry of viral contents into the target cell and ultimately, after many biochemical steps, integration of viral DNA into that of the host cell. The early steps of membrane fusion and viral capsid entry are mediated by adsorption to the cell surface, and receptor and coreceptor binding. HIV-1 specifically targets CD4+ helper T-cells of the human immune system and binds to the receptor CD4 and coreceptor CCR5 before fusion is initiated. Previous experiments have been performed using a cell line (293-Affinofile) in which the expressions of CD4 and CCR5 concentration were independently controlled. After exposure to HIV-1 of various strains, the resulting infectivity was measured through the fraction of infected cells. To design and evaluate the effectiveness of drug therapies that target the inhibition of the entry processes, an accurate functional relationship between the CD4/CCR5 concentrations and infectivity is desired in order to more quantitatively analyze experimental data. We propose three kinetic models describing the possible mechanistic processes involved in HIV entry and fit their predictions to infectivity measurements, contrasting and comparing different outcomes. Our approach allows interpretation of the clustering of infectivity of different strains of HIV-1 in the space of mechanistic kinetic parameters. Our model fitting also allows inference of nontrivial stoichiometries of receptor and coreceptor binding and provides a framework through which to quantitatively investigate the effectiveness of fusion inhibitors and neutralizing antibodies.

Models of Viral Population Dynamics

Models of viral population dynamics have contributed enormously to our understanding of the pathogenesis and transmission of several infectious diseases, the coevolutionary dynamics of viruses and their hosts, the mechanisms of action of drugs, and the effectiveness of interventions. In this chapter, we review major advances in the modeling of the population dynamics of the human immunodeficiency virus (HIV) and briefly discuss adaptations to other viruses.

Phylogenetically resolving epidemiologic linkage

Although the use of phylogenetic trees in epidemiological investigations has become commonplace, their epidemiological interpretation has not been systematically evaluated. Here, we use an HIV-1 within-host coalescent model to probabilistically evaluate transmission histories of two epidemiologically linked hosts. Previous critique of phylogenetic reconstruction has claimed that direction of transmission is difficult to infer, and that the existence of unsampled intermediary links or common sources can never be excluded. The phylogenetic relationship between the HIV populations of epidemiologically linked hosts can be classified into six types of trees, based on cladistic relationships and whether the reconstruction is consistent with the true transmission history or not. We show that the direction of transmission and whether unsampled intermediary links or common sources existed make very different predictions about expected phylogenetic relationships: (i) Direction of transmission can often be established when paraphyly exists, (ii) intermediary links can be excluded when multiple lineages were transmitted, and (iii) when the sampled individuals' HIV populations both are monophyletic a common source was likely the origin. Inconsistent results, suggesting the wrong transmission direction, were generally rare. In addition, the expected tree topology also depends on the number of transmitted lineages, the sample size, the time of the sample relative to transmission, and how fast the diversity increases after infection. Typically, 20 or more sequences per subject give robust results. We confirm our theoretical evaluations with analyses of real transmission histories and discuss how our findings should aid in interpreting phylogenetic results.

Coalescent Inference Using Serially Sampled, High-Throughput Sequencing Data from Intrahost HIV Infection

Human immunodeficiency virus (HIV) is a rapidly evolving pathogen that causes chronic infections, so genetic diversity within a single infection can be very high. High-throughput "deep" sequencing can now measure this diversity in unprecedented detail, particularly since it can be performed at different time points during an infection, and this offers a potentially powerful way to infer the evolutionary dynamics of the intrahost viral population. However, population genomic inference from HIV sequence data is challenging because of high rates of mutation and recombination, rapid demographic changes, and ongoing selective pressures. In this article we develop a new method for inference using HIV deep sequencing data, using an approach based on importance sampling of ancestral recombination graphs under a multilocus coalescent model. The approach further extends recent progress in the approximation of so-called conditional sampling distributions, a quantity of key interest when approximating coalescent likelihoods. The chief novelties of our method are that it is able to infer rates of recombination and mutation, as well as the effective population size, while handling sampling over different time points and missing data without extra computational difficulty. We apply our method to a data set of HIV-1, in which several hundred sequences were obtained from an infected individual at seven time points over 2 years. We find mutation rate and effective population size estimates to be comparable to those produced by the software BEAST. Additionally, our method is able to produce local recombination rate estimates. The software underlying our method, Coalescenator, is freely available.

Investigating the Consequences of Interference between Multiple CD8+ T Cell Escape Mutations in Early HIV Infection

During early human immunodeficiency virus (HIV) infection multiple CD8⁺ T cell responses are elicited almost simultaneously. These responses exert strong selective pressures on different parts of HIV’s genome, and select for mutations that escape recognition and are thus beneficial to the virus. Some studies reveal that the later these escape mutations emerge, the more slowly they go to fixation. This pattern of escape rate decrease(ERD) can arise by distinct mechanisms. In particular, in large populations with high beneficial mutation rates interference among different escape strains –an effect that can emerge in evolution with asexual reproduction and results in delayed fixation times of beneficial mutations compared to sexual reproduction– could significantly impact the escape rates of mutations. In this paper, we investigated how interference between these concurrent escape mutations affects their escape rates in systems with multiple epitopes, and whether it could be a source of the ERD pattern. To address these issues, we developed a multilocus Wright-Fisher model of HIV dynamics with selection, mutation and recombination, serving as a null-model for interference. We also derived an interference-free null model assuming initial neutral evolution before immune response elicitation. We found that interference between several equally selectively advantageous mutations can generate the observed ERD pattern. We also found that the number of loci, as well as recombination rates substantially affect ERD. These effects can be explained by the underexponential decline of escape rates over time. Lastly, we found that the observed ERD pattern in HIV infected individuals is consistent with both independent, interference-free mutations as well as interference effects. Our results confirm that interference effects should be considered when analyzing HIV escape mutations. The challenge in estimating escape rates and mutation-associated selective coefficients posed by interference effects cannot simply be overcome by improved sampling frequencies or sizes. This problem is a consequence of the fundamental shortcomings of current estimation techniques under interference regimes. Hence, accounting for the stochastic nature of competition between mutations demands novel estimation methodologies based on the analysis of HIV strains, rather than mutation frequencies.

Within-host evolution of human immunodeficiency virus (HIV) is shaped by strong immune responses mounted against the virus. Multiple CD8⁺ T cell populations, each recognizing a specific part of an HIV protein, simultaneously suppress HIV growth. Escape mutations that arise in HIV genome regions coding for these virion protein parts, impair CD8⁺ T cell recognition and are consequently strongly selected. The emergence and rise of these escape mutations exhibits an intriguing temporal pattern: the earlier an escape mutation arises, the faster it goes to fixation. This pattern is termed escape rate decrease (ERD). In this paper, we tested computationally whether interference, i.e. the coexistence of multiple genetically distinct HIV strains engaged in competitive interaction within the host, could be a possible source of ERD. As an alternative, we also mathematically derived the temporal pattern of escapes under interference-free conditions, and compared this with data. We found that interference between multiple beneficial mutations could generate ERD. However, ERD does not imply the presence of interference. Thus, more detailed data is required to unambiguously determine whether interference effects influence ERD generation. Nevertheless, interference should be considered when studying the within-host evolution of HIV. Ignoring its effects on population dynamics can severely underestimate the protective capacity of CD8⁺ T cells.

Population genomics of intrapatient HIV-1 evolution

Many microbial populations rapidly adapt to changing environments with multiple variants competing for survival. To quantify such complex evolutionary dynamics in vivo, time resolved and genome wide data including rare variants are essential. We performed whole-genome deep sequencing of HIV-1 populations in 9 untreated patients, with 6-12 longitudinal samples per patient spanning 5-8 years of infection. The data can be accessed and explored via an interactive web application. We show that patterns of minor diversity are reproducible between patients and mirror global HIV-1 diversity, suggesting a universal landscape of fitness costs that control diversity. Reversions towards the ancestral HIV-1 sequence are observed throughout infection and account for almost one third of all sequence changes. Reversion rates depend strongly on conservation. Frequent recombination limits linkage disequilibrium to about 100 bp in most of the genome, but strong hitch-hiking due to short range linkage limits diversity.

Short communication: phylodynamics analysis of the human immunodeficiency virus type 1 envelope gene in mother and child pairs

Characterizing the impact of HIV transmission routes on viral genetic diversity can improve the understanding of the mechanisms of virus evolution and adaptation. HIV vertical transmission can occur in utero, during delivery, or while breastfeeding. The present study investigated the phylodynamics of the HIV-1 env gene in mother-to-child transmission by analyzing one chronically infected pair from Brazil and three acutely infected pairs from Zambia, with three to five time points. Sequences from 25 clones from each sample were obtained and aligned using Clustal X. ML trees were constructed in PhyML using the best evolutionary model. Bayesian analyses testing the relaxed and strict molecular clock were performed using BEAST and a Bayesian Skyline Plot (BSP) was construed. The genetic variability of previously described epitopes was investigated and compared between each individual time point and between mother and child sequences. The relaxed molecular clock was the best-fitted model for all datasets. The tree topologies did not show differentiation in the evolutionary dynamics of the virus circulating in the mother from the viral population in the child. In the BSP, the effective population size was more constant in time in the chronically infected patients while in the acute patients it was possible to detect bottlenecks. The genetic variability within viral epitopes recognized by the human immune system was considerably higher among the chronically infected pair in comparison with acutely infected pairs. These results contribute to a better understanding of HIV-1 evolutionary dynamics in mother-to-child transmission.

Within-host stochastic emergence dynamics of immune-escape mutants

Predicting the emergence of new pathogenic strains is a key goal of evolutionary epidemiology. However, the majority of existing studies have focussed on emergence at the population level, and not within a host. In particular, the coexistence of pre-existing and mutated strains triggers a heightened immune response due to the larger total pathogen population; this feedback can smother mutated strains before they reach an ample size and establish. Here, we extend previous work for measuring emergence probabilities in non-equilibrium populations, to within-host models of acute infections. We create a mathematical model to investigate the emergence probability of a fitter strain if it mutates from a self-limiting strain that is guaranteed to go extinct in the long-term. We show that ongoing immune cell proliferation during the initial stages of infection causes a drastic reduction in the probability of emergence of mutated strains; we further outline how this effect can be accurately measured. Further analysis of the model shows that, in the short-term, mutant strains that enlarge their replication rate due to evolving an increased growth rate are more favoured than strains that suffer a lower immune-mediated death rate (‘immune tolerance’), as the latter does not completely evade ongoing immune proliferation due to inter-parasitic competition. We end by discussing the model in relation to within-host evolution of human pathogens (including HIV, hepatitis C virus, and cancer), and how ongoing immune growth can affect their evolutionary dynamics.

The ongoing evolution of infectious diseases provides a constant health threat. This evolution can either result in the production of new pathogens, or new strains of existing pathogens that escape prevailing drug treatments or immune responses. The latter process, also known as immune escape, is a predominant reason for the persistence of several viruses, including HIV and hepatitis C virus (HCV), in their human host. As a consequence, the within-host emergence of new strains has been the intense focus of modelling studies. However, existing models have neglected important feedbacks that affects this emergence probability. Specifically, once a mutated pathogen arises that spreads more quickly than the initial (resident) strain, it potentially triggers a heightened immune response that can eliminate the mutated strain before it spreads. Our study outlines novel mathematical modelling techniques that accurately quantify how ongoing immune growth reduces the emergence probability of mutated pathogenic strains over the course of an infection. Analysis of this model suggests that, in order to enlarge its emergence probability, it is evolutionary beneficial for a mutated strain to increase its growth rate rather than tolerate immunity by having a lower immune-mediated death-rate. Our model can be readily applied to existing within-host data, as demonstrated with application to HIV, HCV, and cancer dynamics.

The Effect of Interference on the CD8(+) T Cell Escape Rates in HIV

In early human immunodeficiency virus (HIV) infection, the virus population escapes from multiple CD8⁺ cell responses. The later an escape mutation emerges, the slower it outgrows its competition, i.e., the escape rate is lower. This pattern could indicate that the strength of the CD8⁺ cell responses is waning, or that later viral escape mutants carry a larger fitness cost. In this paper, we investigate whether the pattern of decreasing escape rates could also be caused by genetic interference among different escape strains. To this end, we developed a mathematical multi-epitope model of HIV dynamics, which incorporates stochastic effects, recombination, and mutation. We used cumulative linkage disequilibrium measures to quantify the amount of interference. We found that nearly synchronous, similarly strong immune responses in two-locus systems enhance the generation of genetic interference. This effect, combined with a scheme of densely spaced sampling times at the beginning of infection and sparse sampling times later, leads to decreasing successive escape rate estimates, even when there were no selection differences among alleles. These predictions are supported by empirical data from one HIV-infected patient. Thus, interference could explain why later escapes are slower. Considering escape mutations in isolation, neglecting their genetic linkage, conceals the underlying haplotype dynamics and can affect the estimation of the selective pressure exerted by CD8⁺ cells. In systems in which multiple escape mutations appear, the occurrence of interference dynamics should be assessed by measuring the linkage between different escape mutations.

Compositional Constraint Is the Key Force in Shaping Codon Usage Bias in Hemagglutinin Gene in H1N1 Subtype of Influenza A Virus

It is vital to unravel the codon usage bias in order to gain insights into the evolutionary forces dictating the viral evolution process. Influenza A virus has attracted attention of many investigators over the years due to high mutation rate and being cross-specific shift operational in the viral genome. Several authors have reported that the codon usage bias is low in influenza A viruses, citing mutational pressure as the decisive force shaping up the codon usage in these viruses. In this study, complete coding sequences of hemagglutinin genes for H1N1 subtype of influenza A virus have been explored for the possible codon usage bias acting upon these genes. The results indicate overall low bias with peaking ENC values. The GC content is found to be substantially low as against AT content in the silent codon sites. Significant correlations were observed in between the compositional parameters versus AT₃, implying the possible role of the latter in shaping codon usage profile in the viral hemagglutinin. The data showed conspicuously that the sequences were A redundant with most codons preferring nucleotide A over others in the third synonymous codon site. The results indicated the pivotal role of compositional pressure affecting codon usage in this virus.

Timing and order of transmission events is not directly reflected in a pathogen phylogeny

Pathogen phylogenies are often used to infer spread among hosts. There is, however, not an exact match between the pathogen phylogeny and the host transmission history. Here, we examine in detail the limitations of this relationship. First, all splits in a pathogen phylogeny of more than 1 host occur within hosts, not at the moment of transmission, predating the transmission events as described by the pretransmission interval. Second, the order in which nodes in a phylogeny occur may be reflective of the within-host dynamics rather than epidemiologic relationships. To investigate these phenomena, motivated by within-host diversity patterns, we developed a two-phase coalescent model that includes a transmission bottleneck followed by linear outgrowth to a maximum population size followed by either stabilization or decline of the population. The model predicts that the pretransmission interval shrinks compared with predictions based on constant population size or a simple transmission bottleneck. Because lineages coalesce faster in a small population, the probability of a pathogen phylogeny to resemble the transmission history depends on when after infection a donor transmits to a new host. We also show that the probability of inferring the incorrect order of multiple transmissions from the same host is high. Finally, we compare time of HIV-1 infection informed by genetic distances in phylogenies to independent biomarker data, and show that, indeed, the pretransmission interval biases phylogeny-based estimates of when transmissions occurred. We describe situations where caution is needed not to misinterpret which parts of a phylogeny that may indicate outbreaks and tight transmission clusters.

Constructing lower-bounds for CTL escape rates in early SIV infection

Intrahost human and simian immunodeficiency virus (HIV and SIV) evolution is marked by repeated viral escape from cytotoxic T-lymphocyte (CTL) response. Typically, the first such CTL escape starts around the time of peak viral load and completes within one or two weeks. Many authors have developed methods to quantify CTL escape rates, but existing methods depend on sampling at two or more timepoints. Since many datasets capture the dynamics of the first CTL escape at a single timepoint, we develop inference methods applicable to single timepoint datasets. To account for model uncertainty, we construct estimators which serve as lower bounds for the escape rate. These lower-bound estimators allow for statistically meaningful comparison of escape rates across different times and different compartments. We apply our methods to two SIV datasets, showing that escape rates are relatively high during the initial days of the first CTL escape and drop to lower levels as the escape proceeds.

Loss and recovery of genetic diversity in adapting populations of HIV

The evolution of drug resistance in HIV occurs by the fixation of specific, well-known, drug-resistance mutations, but the underlying population genetic processes are not well understood. By analyzing within-patient longitudinal sequence data, we make four observations that shed a light on the underlying processes and allow us to infer the short-term effective population size of the viral population in a patient. Our first observation is that the evolution of drug resistance usually occurs by the fixation of one drug-resistance mutation at a time, as opposed to several changes simultaneously. Second, we find that these fixation events are accompanied by a reduction in genetic diversity in the region surrounding the fixed drug-resistance mutation, due to the hitchhiking effect. Third, we observe that the fixation of drug-resistance mutations involves both hard and soft selective sweeps. In a hard sweep, a resistance mutation arises in a single viral particle and drives all linked mutations with it when it spreads in the viral population, which dramatically reduces genetic diversity. On the other hand, in a soft sweep, a resistance mutation occurs multiple times on different genetic backgrounds, and the reduction of diversity is weak. Using the frequency of occurrence of hard and soft sweeps we estimate the effective population size of HIV to be 1.5 x 10(5) (95% confidence interval [0.8 x 10(5),4.8 x 10(5)]). This number is much lower than the actual number of infected cells, but much larger than previous population size estimates based on synonymous diversity. We propose several explanations for the observed discrepancies. Finally, our fourth observation is that genetic diversity at non-synonymous sites recovers to its pre-fixation value within 18 months, whereas diversity at synonymous sites remains depressed after this time period. These results improve our understanding of HIV evolution and have potential implications for treatment strategies.

Reconstructing the timing and dispersion routes of HIV-1 subtype B epidemics in the Caribbean and Central America: a phylogenetic story

The Caribbean and Central America are among the regions with highest HIV-1B prevalence worldwide. Despite of this high virus burden, little is known about the timing and the migration patterns of HIV-1B in these regions. Migration is one of the major processes shaping the genetic structure of virus populations. Thus, reconstruction of epidemiological network may contribute to understand HIV-1B evolution and reduce virus prevalence. We have investigated the spatio-temporal dynamics of the HIV-1B epidemic in The Caribbean and Central America using 1,610 HIV-1B partial pol sequences from 13 Caribbean and 5 Central American countries. Timing of HIV-1B introduction and virus evolutionary rates, as well as the spatial genetic structure of the HIV-1B populations and the virus migration patterns were inferred. Results revealed that in The Caribbean and Central America most of the HIV-1B variability was generated since the 80 s. At odds with previous data suggesting that Haiti was the origin of the epidemic in The Caribbean, our reconstruction indicated that the virus could have been disseminated from Puerto Rico and Antigua. These two countries connected two distinguishable migration areas corresponding to the (mainly Spanish-colonized) Easter and (mainly British-colonized) Western islands, which indicates that virus migration patterns are determined by geographical barriers and by the movement of human populations among culturally related countries. Similar factors shaped the migration of HIV-1B in Central America. The HIV-1B population was significantly structured according to the country of origin, and the genetic diversity in each country was associated with the virus prevalence in both regions, which suggests that virus populations evolve mainly through genetic drift. Thus, our work contributes to the understanding of HIV-1B evolution and dispersion pattern in the Americas, and its relationship with the geography of the area and the movements of human populations.

The intra-host evolutionary and population dynamics of human immunodeficiency virus type 1: a phylogenetic perspective

The intra-host evolutionary and population dynamics of the human immunodeficiency virus type 1 (HIV-1), the cause of the acquired immunodeficiency syndrome, have been the focus of one of the most extensive study efforts in the field of molecular evolution over the past three decades. As HIV-1 is among the fastest mutating organisms known, viral sequence data sampled over time from infected patients can provide, through phylogenetic analysis, significant insights about the tempo and mode of evolutionary processes shaped by complex interaction with the host milieu. Five main aspects are discussed: the patterns of HIV-1 intra-host diversity and divergence over time in relation to different phases of disease progression; the impact of selection on the temporal structure of HIV-1 intra-host genealogies inferred from longitudinally sampled viral sequences; HIV-1 intra-host sub-population structure; the potential relationship between viral evolutionary rate and disease progression and the central evolutionary role played by recombination occurring in super-infected cells.

HIV populations are large and accumulate high genetic diversity in a nonlinear fashion

HIV infection is characterized by rapid and error-prone viral replication resulting in genetically diverse virus populations. The rate of accumulation of diversity and the mechanisms involved are under intense study to provide useful information to understand immune evasion and the development of drug resistance. To characterize the development of viral diversity after infection, we carried out an in-depth analysis of single genome sequences of HIV pro-pol to assess diversity and divergence and to estimate replicating population sizes in a group of treatment-naive HIV-infected individuals sampled at single (n = 22) or multiple, longitudinal (n = 11) time points. Analysis of single genome sequences revealed nonlinear accumulation of sequence diversity during the course of infection. Diversity accumulated in recently infected individuals at rates 30-fold higher than in patients with chronic infection. Accumulation of synonymous changes accounted for most of the diversity during chronic infection. Accumulation of diversity resulted in population shifts, but the rates of change were low relative to estimated replication cycle times, consistent with relatively large population sizes. Analysis of changes in allele frequencies revealed effective population sizes that are substantially higher than previous estimates of approximately 1,000 infectious particles/infected individual. Taken together, these observations indicate that HIV populations are large, diverse, and slow to change in chronic infection and that the emergence of new mutations, including drug resistance mutations, is governed by both selection forces and drift.

Design requirements for interfering particles to maintain coadaptive stability with HIV-1

Defective interfering particles (DIPs) are viral deletion mutants lacking essential transacting or packaging elements and must be complemented by wild-type virus to propagate. DIPs transmit through human populations, replicating at the expense of the wild-type virus and acting as molecular parasites of viruses. Consequently, engineered DIPs have been proposed as therapies for a number of diseases, including human immunodeficiency virus (HIV). However, it is not clear if DIP-based therapies would face evolutionary blocks given the high mutation rates and high within-host diversity of lentiviruses. Divergent evolution of HIV and DIPs appears likely since natural DIPs have not been detected for lentiviruses, despite extensive sequencing of HIVs and simian immunodeficiency viruses (SIVs). Here, we tested if the apparent lack of lentiviral DIPs is due to natural selection and analyzed which molecular characteristics a DIP or DIP-based therapy would need to maintain coadaptive stability with HIV-1. Using a well-established mathematical model of HIV-1 in a host extended to include its replication in a single cell and interference from DIP, we calculated evolutionary selection coefficients. The analysis predicts that interference by codimerization between DIPs and HIV-1 genomes is evolutionarily unstable, indicating that recombination between DIPs and HIV-1 would be selected against. In contrast, DIPs that interfere via competition for capsids have the potential to be evolutionarily stable if the capsid-to-genome production ratio of HIV-1 is >1. Thus, HIV-1 variants that attempt to "starve" DIPs to escape interference would be selected against. In summary, the analysis suggests specific experimental measurements that could address the apparent lack of naturally occurring lentiviral DIPs and specifies how therapeutic approaches based on engineered DIPs could be evolutionarily robust and avoid recombination.

Stochastic effects are important in intrahost HIV evolution even when viral loads are high

Blood plasma viral loads and the time to progress to AIDS differ widely among untreated HIV-infected humans. Although people with certain HLA (HLA-I) alleles are more likely to control HIV infections without therapy, the majority of such untreated individuals exhibit high viral loads and progress to AIDS. Stochastic effects are considered unimportant for evolutionary dynamics in HIV-infected people when viral load is high or when selective forces strongly drive mutation. We describe a computational study of host-pathogen interaction demonstrating that stochastic effects can have a profound influence on disease dynamics, even in cases of high viral load and strong selective pressure. These stochastic effects are pronounced when the virus must traverse a fitness "barrier" in sequence space to escape the host's cytotoxic T-lymphocyte (CTL) response, as often occurs when a fitness defect imposed by a CTL-driven mutation must be compensated for by other mutations. These "barrier-crossing" events are infrequent and stochastic, resulting in divergent disease outcomes in genetically identical individuals infected by the same viral strain. Our results reveal how genetic determinants of the CTL response control the probability with which an individual is able to control HIV infection indefinitely, and thus provide clues for vaccine design.

Antibody selection and amino acid reversions

Pathogens adapt to antibody surveillance through amino acid replacements in targeted protein regions, or epitopes, that interfere with antibody binding. However, such escape mutations may exact a fitness cost due to impaired protein function. Here, it is hypothesized that the recurring generation of specific neutralizing antibodies to an epitope region as it evolves in response to antibody selection will cause amino acid reversions by releasing early escape mutations from immune selection. The plausibility of this hypothesis was tested with stochastic simulation of adaptation at the molecular sequence level in finite populations. Under the conditions of strong selection and weak mutation, the rates of allele fixation and amino acid reversion increased with population size and selection coefficients. These rates decreased with population size, however, if mutation became strong, because clonal interference reduced the rate of adaptation. The model successfully predicts the rate of reversion per allele fixation for an important human immunodeficiency virus type 1 (HIV-1) antibody epitope region. Therefore, antibody selection may generate complex adaptive dynamics.

Stochastic simulations suggest that HIV-1 survives close to its error threshold

The use of mutagenic drugs to drive HIV-1 past its error threshold presents a novel intervention strategy, as suggested by the quasispecies theory, that may be less susceptible to failure via viral mutation-induced emergence of drug resistance than current strategies. The error threshold of HIV-1, , however, is not known. Application of the quasispecies theory to determine poses significant challenges: Whereas the quasispecies theory considers the asexual reproduction of an infinitely large population of haploid individuals, HIV-1 is diploid, undergoes recombination, and is estimated to have a small effective population size in vivo. We performed population genetics-based stochastic simulations of the within-host evolution of HIV-1 and estimated the structure of the HIV-1 quasispecies and . We found that with small mutation rates, the quasispecies was dominated by genomes with few mutations. Upon increasing the mutation rate, a sharp error catastrophe occurred where the quasispecies became delocalized in sequence space. Using parameter values that quantitatively captured data of viral diversification in HIV-1 patients, we estimated to be substitutions/site/replication, ∼2–6 fold higher than the natural mutation rate of HIV-1, suggesting that HIV-1 survives close to its error threshold and may be readily susceptible to mutagenic drugs. The latter estimate was weakly dependent on the within-host effective population size of HIV-1. With large population sizes and in the absence of recombination, our simulations converged to the quasispecies theory, bridging the gap between quasispecies theory and population genetics-based approaches to describing HIV-1 evolution. Further, increased with the recombination rate, rendering HIV-1 less susceptible to error catastrophe, thus elucidating an added benefit of recombination to HIV-1. Our estimate of may serve as a quantitative guideline for the use of mutagenic drugs against HIV-1.

Currently available antiretroviral drugs curtail HIV infection but fail to eradicate the virus. A strategy of intervention radically different from that employed by current drugs has been proposed by the molecular quasispecies theory. The theory predicts that increasing the viral mutation rate beyond a critical value, called the error threshold, would cause a severe loss of genetic information, potentially leading to viral clearance. Several chemical mutagens are now being developed that can increase the mutation rate of HIV-1. Their success depends on reliable estimates of the error threshold of HIV-1, which are currently lacking. The quasispecies theory cannot be applied directly to HIV-1: the theory considers an infinitely large population of asexually reproducing haploid individuals, whereas HIV-1 is diploid, undergoes recombination, and is estimated to have a small effective population size in vivo. We employed detailed stochastic simulations that overcome the limitations of the quasispecies theory and accurately mimic HIV-1 evolution in vivo. With these simulations, we estimated the error threshold of HIV-1 to be ∼2–6-fold higher than its natural mutation rate, suggesting that HIV-1 survives close to its error threshold and may be readily susceptible to mutagenic drugs.

Ultrasensitive allele-specific PCR reveals rare preexisting drug-resistant variants and a large replicating virus population in macaques infected with a simian immunodeficiency virus containing human immunodeficiency virus reverse transcriptase

It has been proposed that most drug-resistant mutants, resulting from a single-nucleotide change, exist at low frequency in human immunodeficiency virus type 1 (HIV-1) and simian immunodeficiency virus (SIV) populations in vivo prior to the initiation of antiretroviral therapy (ART). To test this hypothesis and to investigate the emergence of resistant mutants with drug selection, we developed a new ultrasensitive allele-specific PCR (UsASP) assay, which can detect drug resistance mutations at a frequency of ≥0.001% of the virus population. We applied this assay to plasma samples obtained from macaques infected with an SIV variant containing HIV-1 reverse transcriptase (RT) (RT-simian-human immunodeficiency [SHIV](mne)), before and after they were exposed to a short course of efavirenz (EFV) monotherapy. We detected RT inhibitor (RTI) resistance mutations K65R and M184I but not K103N in 2 of 2 RT-SHIV-infected macaques prior to EFV exposure. After three doses over 4 days of EFV monotherapy, 103N mutations (AAC and AAT) rapidly emerged and increased in the population to levels of ∼20%, indicating that they were present prior to EFV exposure. The rapid increase of 103N mutations from <0.001% to 20% of the viral population indicates that the replicating virus population size in RT-SHIV-infected macaques must be 10(6) or more infected cells per replication cycle.

The origin of genetic diversity in HIV-1

One of the hallmarks of HIV infection is the rapid development of a genetically complex population (quasispecies) from an initially limited number of infectious particles. Genetic diversity remains one of the major obstacles to eradication of HIV. The viral quasispecies can respond rapidly to selective pressures, such as that imposed by the immune system and antiretroviral therapy, and frustrates vaccine design efforts. Two unique features of retroviral replication are responsible for the unprecedented variation generated during infection. First, mutations are frequently introduced into the viral genome by the error prone viral reverse transcriptase and through the actions of host cellular factors, such as the APOBEC family of nucleic acid editing enzymes. Second, the HIV reverse transcriptase can utilize both copies of the co-packaged viral genome in a process termed retroviral recombination. When the co-packaged viral genomes are genetically different, retroviral recombination can lead to the shuffling of mutations between viral genomes in the quasispecies. This review outlines the stages of the retroviral life cycle where genetic variation is introduced, focusing on the principal mechanisms of mutation and recombination. Understanding the mechanistic origin of genetic diversity is essential to combating HIV.

Standing genetic variation and the evolution of drug resistance in HIV

Drug resistance remains a major problem for the treatment of HIV. Resistance can occur due to mutations that were present before treatment starts or due to mutations that occur during treatment. The relative importance of these two sources is unknown. Resistance can also be transmitted between patients, but this process is not considered in the current study. We study three different situations in which HIV drug resistance may evolve: starting triple-drug therapy, treatment with a single dose of nevirapine and interruption of treatment. For each of these three cases good data are available from literature, which allows us to estimate the probability that resistance evolves from standing genetic variation. Depending on the treatment we find probabilities of the evolution of drug resistance due to standing genetic variation between and . For patients who start triple-drug combination therapy, we find that drug resistance evolves from standing genetic variation in approximately 6% of the patients. We use a population-dynamic and population-genetic model to understand the observations and to estimate important evolutionary parameters under the assumption that treatment failure is caused by the fixation of a single drug resistance mutation. We find that both the effective population size of the virus before treatment, and the fitness of the resistant mutant during treatment, are key-parameters which determine the probability that resistance evolves from standing genetic variation. Importantly, clinical data indicate that both of these parameters can be manipulated by the kind of treatment that is used.

For HIV patients who are treated with antiretroviral drugs, treatment usually works well. However, the virus can, and sometimes does, become resistant against one or more drugs. HIV drug resistance results from the acquisition of specific and well known mutations. It is currently unknown whether drug resistance mutations usually stem from standing genetic variation, i.e., they were already present at low frequency before treatment started, or whether they tend to occur during treatment. In the current manuscript, I make use of several large datasets and evolutionary modeling to estimate the probability that drug resistance mutations are present before treatment starts and lead to viral failure. I find that for the most common type of treatment with a combination of three drugs, drug resistance evolves from pre-existing mutations in 6% of the patients. With other types of treatment, this probability varies from 0 to 39%. I conclude that there is room for improvement in preventing the evolution of drug resistance from pre-existing mutations.

The coalescence of intrahost HIV lineages under symmetric CTL attack

Cytotoxic T lymphocytes (CTLs) are immune system cells that are thought to play an important role in controlling HIV infection. We develop a stochastic ODE model of HIV-CTL interaction that extends current deterministic ODE models. Based on this stochastic model, we consider the effect of CTL attack on intrahost HIV lineages assuming that CTLs attack several epitopes with equal strength. In this setting, we introduce a limiting version of our stochastic ODE under which we show that the coalescence of HIV lineages can be described through Poisson-Dirichlet distributions. Through numerical experiments, we show that our results under the limiting stochastic ODE accurately reflect HIV lineages under CTL attack when the HIV population size is on the low end of its hypothesized range. Current techniques of HIV lineage construction depend on the Kingman coalescent. Our results give an explicit connection between CTL attack and HIV lineages.

The HIV Epidemic: High-Income Countries

The HIV epidemic in higher-income nations is driven by receptive anal intercourse, injection drug use through needle/syringe sharing, and, less efficiently, vaginal intercourse. Alcohol and noninjecting drug use increase sexual HIV vulnerability. Appropriate diagnostic screening has nearly eliminated blood/blood product-related transmissions and, with antiretroviral therapy, has reduced mother-to-child transmission radically. Affected subgroups have changed over time (e.g., increasing numbers of Black and minority ethnic men who have sex with men). Molecular phylogenetic approaches have established historical links between HIV strains from central Africa to those in the United States and thence to Europe. However, Europe did not just receive virus from the United States, as it was also imported from Africa directly. Initial introductions led to epidemics in different risk groups in Western Europe distinguished by viral clades/sequences, and likewise, more recent explosive epidemics linked to injection drug use in Eastern Europe are associated with specific strains. Recent developments in phylodynamic approaches have made it possible to obtain estimates of sequence evolution rates and network parameters for epidemics.

Evolutionary dynamics of HIV at multiple spatial and temporal scales

Infectious diseases remain a formidable challenge to human health, and understanding pathogen evolution is crucial to designing effective therapeutics and control strategies. Here, we review important evolutionary aspects of HIV infection, highlighting the concept of selection at multiple spatial and temporal scales. At the smallest scale, a single cell may be infected by multiple virions competing for intracellular resources. Recombination and phenotypic mixing introduce novel evolutionary dynamics. As the virus spreads between cells in an infected individual, it continually evolves to circumvent the immune system. We discuss evolutionary mechanisms of HIV pathogenesis and progression to AIDS. Viral spread throughout the human population can lead to changes in virulence and the transmission of immune-evading variation. HIV emerged as a human pathogen due to selection occurring between different species, adapting from related viruses of primates. HIV also evolves resistance to antiretroviral drugs within a single infected host, and we explore the possibility for the spread of these strains between hosts, leading to a drug-resistant epidemic. We investigate the role of latency, drug-protected compartments, and direct cell-to-cell transmission on viral evolution. The introduction of an HIV vaccine may select for viral variants that escape vaccine control, both within an individual and throughout the population. Due to the strong selective pressure exerted by HIV-induced morbidity and mortality in many parts of the world, the human population itself may be co-evolving in response to the HIV pandemic. Throughout the paper, we focus on trade-offs between costs and benefits that constrain viral evolution and accentuate how selection pressures differ at different levels of selection.

Genetic diversity and molecular epidemiology of HIV transmission

The high genetic diversity of HIV is one of its most significant features, as it has consequences in global distribution, vaccine design, therapy success, disease progression, transmissibility and viral load testing. Studying HIV diversity helps to understand its origins, migration patterns, current distribution and transmission events. New advances in sequencing technologies based on the parallel acquisition of data are now used to characterize within-host and population processes in depth. Additionally, we have seen similar advances in statistical methods designed to model the past history of lineages (the phylodynamic framework) to ultimately gain better insights into the evolutionary history of HIV. We can, for example, estimate population size changes, lineage dispersion over geographic areas and epidemiological parameters solely from sequence data. In this article, we review some of the evolutionary approaches used to study transmission patterns and processes in HIV and the insights gained from such studies.

The dynamics of HIV-1 adaptation in early infection

Human immunodeficiency virus type 1 (HIV-1) undergoes a severe population bottleneck during sexual transmission and yet adapts extremely rapidly to the earliest immune responses. The bottleneck has been inferred to typically consist of a single genome, and typically eight amino acid mutations in viral proteins spread to fixation by the end of the early chronic phase of infection in response to selection by CD8(+) T cells. Stochastic simulation was used to examine the effects of the transmission bottleneck and of potential interference among spreading immune-escape mutations on the adaptive dynamics of the virus in early infection. If major viral population genetic parameters are assigned realistic values that permit rapid adaptive evolution, then a bottleneck of a single genome is not inconsistent with the observed pattern of adaptive fixations. One requirement is strong selection by CD8(+) T cells that decreases over time. Such selection may reduce effective population sizes at linked loci through genetic hitchhiking. However, this effect is predicted to be minor in early infection because the transmission bottleneck reduces the effective population size to such an extent that the resulting strong selection and weak mutation cause beneficial mutations to fix sequentially and thus avoid interference.

Enhancing protein backbone binding--a fruitful concept for combating drug-resistant HIV

The evolution of drug resistance is one of the most fundamental problems in medicine. In HIV/AIDS, the rapid emergence of drug-resistant HIV-1 variants is a major obstacle to current treatments. HIV-1 protease inhibitors are essential components of present antiretroviral therapies. However, with these protease inhibitors, resistance occurs through viral mutations that alter inhibitor binding, resulting in a loss of efficacy. This loss of potency has raised serious questions with regard to effective long-term antiretroviral therapy for HIV/AIDS. In this context, our research has focused on designing inhibitors that form extensive hydrogen-bonding interactions with the enzyme's backbone in the active site. In doing so, we limit the protease's ability to acquire drug resistance as the geometry of the catalytic site must be conserved to maintain functionality. In this Review, we examine the underlying principles of enzyme structure that support our backbone-binding concept as an effective means to combat drug resistance and highlight their application in our recent work on antiviral HIV-1 protease inhibitors.

The evolution of HIV: inferences using phylogenetics

Molecular phylogenetics has revolutionized the study of not only evolution but also disparate fields such as genomics, bioinformatics, epidemiology, ecology, microbiology, molecular biology and biochemistry. Particularly significant are its achievements in population genetics as a result of the development of coalescent theory, which have contributed to more accurate model-based parameter estimation and explicit hypothesis testing. The study of the evolution of many microorganisms, and HIV in particular, have benefited from these new methodologies. HIV is well suited for such sophisticated population analyses because of its large population sizes, short generation times, high substitution rates and relatively small genomes. All these factors make HIV an ideal and fascinating model to study molecular evolution in real time. Here we review the significant advances made in HIV evolution through the application of phylogenetic approaches. We first examine the relative roles of mutation and recombination on the molecular evolution of HIV and its adaptive response to drug therapy and tissue allocation. We then review some of the fundamental questions in HIV evolution in relation to its origin and diversification and describe some of the insights gained using phylogenies. Finally, we show how phylogenetic analysis has advanced our knowledge of HIV dynamics (i.e., phylodynamics).

Analysis of a stochastic predator-prey model with applications to intrahost HIV genetic diversity

During an infection, HIV experiences strong selection by immune system T cells. Recent experimental work has shown that MHC escape mutations form an important pathway for HIV to avoid such selection. In this paper, we study a model of MHC escape mutation. The model is a predator-prey model with two prey, composed of two HIV variants, and one predator, the immune system CD8 cells. We assume that one HIV variant is visible to CD8 cells and one is not. The model takes the form of a system of stochastic differential equations. Motivated by well-known results concerning the short life-cycle of HIV intrahost, we assume that HIV population dynamics occur on a faster time scale then CD8 population dynamics. This separation of time scales allows us to analyze our model using an asymptotic approach. Using this model we study the impact of an MHC escape mutation on the population dynamics and genetic evolution of the intrahost HIV population. From the perspective of population dynamics, we show that the competition between the visible and invisible HIV variants can reach steady states in which either a single variant exists or in which coexistence occurs depending on the parameter regime. We show that in some parameter regimes the end state of the system is stochastic. From a genetics perspective, we study the impact of the population dynamics on the lineages of an HIV sample taken after an escape mutation occurs. We show that the lineages go through severe bottlenecks and that in certain parameter regimes the lineage distribution can be characterized by a Kingman coalescent. Our results depend on methods from diffusion theory and coalescent theory.

Daily sampling of an HIV-1 patient with slowly progressing disease displays persistence of multiple env subpopulations consistent with neutrality

The molecular evolution of HIV-1 is characterized by frequent substitutions, indels and recombination events. In addition, a HIV-1 population may adapt through frequency changes of its variants. To reveal such population dynamics we analyzed HIV-1 subpopulation frequencies in an untreated patient with stable, low plasma HIV-1 RNA levels and close to normal CD4+ T-cell levels. The patient was intensively sampled during a 32-day period as well as approximately 1.5 years before and after this period (days −664, 1, 2, 3, 11, 18, 25, 32 and 522). 77 sequences of HIV-1 env (approximately 3100 nucleotides) were obtained from plasma by limiting dilution with 7–11 sequences per time point, except day −664. Phylogenetic analysis using maximum likelihood methods showed that the sequences clustered in six distinct subpopulations. We devised a method that took into account the relatively coarse sampling of the population. Data from days 1 through 32 were consistent with constant within-patient subpopulation frequencies. However, over longer time periods, i.e. between days 1…32 and 522, there were significant changes in subpopulation frequencies, which were consistent with evolutionarily neutral fluctuations. We found no clear signal of natural selection within the subpopulations over the study period, but positive selection was evident on the long branches that connected the subpopulations, which corresponds to >3 years as the subpopulations already were established when we started the study. Thus, selective forces may have been involved when the subpopulations were established. Genetic drift within subpopulations caused by de novo substitutions could be resolved after approximately one month. Overall, we conclude that subpopulation frequencies within this patient changed significantly over a time period of 1.5 years, but that this does not imply directional or balancing selection. We show that the short-term evolution we study here is likely representative for many patients of slow and normal disease progression.

Sampling HIV intrahost genealogies based on a model of acute stage CTL response

Cytotoxic T lymphocytes (CTLs) play an important role in the immune response to HIV during the acute stage of infection, but the effect of CTLs on HIV intrahost genetic diversity is poorly understood. We introduce a model of CTL attack during the acute stage. Assuming this model, we develop a method to sample HIV intrahost genealogies. Using our sampling approach, we characterize the evolutionary forces that shape HIV genealogies. In particular, we show that early mutation events can have significant impact on HIV genealogies and that certain types of CTL attack are best at controlling HIV genetic diversity. Our sampler represents a first step toward using HIV genetic data to infer properties of CTL attack.

Differential persistence of transmitted HIV-1 drug resistance mutation classes

BACKGROUND

Transmitted human immunodeficiency virus type 1 (HIV-1) drug resistance (TDR) mutations can become replaced over time by emerging wild-type viral variants with improved fitness. The impact of class-specific mutations on this rate of mutation replacement is uncertain.

METHODS

We studied participants with acute and/or early HIV infection and TDR in 2 cohorts (San Francisco, California, and São Paulo, Brazil). We followed baseline mutations longitudinally and compared replacement rates between mutation classes with use of a parametric proportional hazards model.

RESULTS

Among 75 individuals with 195 TDR mutations, M184V/I became undetectable markedly faster than did nonnucleoside reverse-transcriptase inhibitor (NNRTI) mutations (hazard ratio, 77.5; 95% confidence interval [CI], 14.7-408.2; P<.0001), while protease inhibitor and NNRTI replacement rates were similar. Higher plasma HIV-1 RNA level predicted faster mutation replacement, but this was not statistically significant (hazard ratio, 1.71 log(10) copies/mL; 95% CI, .90-3.25 log(10) copies/mL; P=.11). We found substantial person-to-person variability in mutation replacement rates not accounted for by viral load or mutation class (P<.0001).

CONCLUSIONS

The rapid replacement of M184V/I mutations is consistent with known fitness costs. The long-term persistence of NNRTI and protease inhibitor mutations suggests a risk for person-to-person propagation. Host and/or viral factors not accounted for by viral load or mutation class are likely influencing mutation replacement and warrant further study.

Estimate of effective recombination rate and average selection coefficient for HIV in chronic infection

HIV adaptation to a host in chronic infection is simulated by means of a Monte-Carlo algorithm that includes the evolutionary factors of mutation, positive selection with varying strength among sites, random genetic drift, linkage, and recombination. By comparing two sensitive measures of linkage disequilibrium (LD) and the number of diverse sites measured in simulation to patient data from one-time samples of pol gene obtained by single-genome sequencing from representative untreated patients, we estimate the effective recombination rate and the average selection coefficient to be on the order of 1% per genome per generation (10(-5) per base per generation) and 0.5%, respectively. The adaptation rate is twofold higher and fourfold lower than predicted in the absence of recombination and in the limit of very frequent recombination, respectively. The level of LD and the number of diverse sites observed in data also range between the values predicted in simulation for these two limiting cases. These results demonstrate the critical importance of finite population size, linkage, and recombination in HIV evolution.

HIV-1 infected monozygotic twins: a tale of two outcomes

BACKGROUND

Replicate experiments are often difficult to find in evolutionary biology, as this field is inherently an historical science. However, viruses, bacteria and phages provide opportunities to study evolution in both natural and experimental contexts, due to their accelerated rates of evolution and short generation times. Here we investigate HIV-1 evolution by using a natural model represented by monozygotic twins infected synchronically at birth with an HIV-1 population from a shared blood transfusion source. We explore the evolutionary processes and population dynamics that shape viral diversity of HIV in these monozygotic twins.

RESULTS

Despite the identical host genetic backdrop of monozygotic twins and the identical source and timing of the HIV-1 inoculation, the resulting HIV populations differed in genetic diversity, growth rate, recombination rate, and selection pressure between the two infected twins.

CONCLUSIONS

Our study shows that the outcome of evolution is strikingly different between these two "replicates" of viral evolution. Given the identical starting points at infection, our results support the impact of random epigenetic selection in early infection dynamics. Our data also emphasize the need for a better understanding of the impact of host-virus interactions in viral evolution.