Stochastic processes strongly influence HIV-1 evolution during suboptimal protease-inhibitor therapy

A classification algorithm based on dynamic ensemble selection to predict mutational patterns of the envelope protein in HIV-infected patients

BACKGROUND

Therapeutics against the envelope (Env) proteins of human immunodeficiency virus type 1 (HIV-1) effectively reduce viral loads in patients. However, due to mutations, new therapy-resistant Env variants frequently emerge. The sites of mutations on Env that appear in each patient are considered random and unpredictable. Here we developed an algorithm to estimate for each patient the mutational state of each position based on the mutational state of adjacent positions on the three-dimensional structure of the protein.

METHODS

We developed a dynamic ensemble selection algorithm designated k-best classifiers. It identifies the best classifiers within the neighborhood of a new observation and applies them to predict the variability state of each observation. To evaluate the algorithm, we applied amino acid sequences of Envs from 300 HIV-1-infected individuals (at least six sequences per patient). For each patient, amino acid variability values at all Env positions were mapped onto the three-dimensional structure of the protein. Then, the variability state of each position was estimated by the variability at adjacent positions of the protein.

RESULTS

The proposed algorithm showed higher performance than the base learner and a panel of classification algorithms. The mutational state of positions in the high-mannose patch and CD4-binding site of Env, which are targeted by multiple therapeutics, was predicted well. Importantly, the algorithm outperformed other classification techniques for predicting the variability state at multi-position footprints of therapeutics on Env.

CONCLUSIONS

The proposed algorithm applies a dynamic classifier-scoring approach that increases its performance relative to other classification methods. Better understanding of the spatiotemporal patterns of variability across Env may lead to new treatment strategies that are tailored to the unique mutational patterns of each patient. More generally, we propose the algorithm as a new high-performance dynamic ensemble selection technique.

An HIV stochastic model with cell-to-cell infection, B-cell immune response and distributed delay

In this study, a delayed HIV stochastic model with virus-to-cell infection, cell-to-cell transmission and B-cell immune response is proposed. We first transform the stochastic differential equation with distributed delay into a high-dimensional degenerate stochastic differential equation, and then theoretically analyze the dynamic behaviour of the degenerate model. The unique global solution of the model is given by rigorous analysis. By formulating suitable Lyapunov functions, the existence of the stationary Markov process is obtained if the stochastic B-cell-activated reproduction number is greater than one. We also use the law of large numbers theorem and the spectral radius analysis method to deduce that the virus can be cleared if the stochastic B-cell-inactivated reproduction number is less than one. Through uncertainty and sensitivity analysis, we obtain key parameters that determine the value of the stochastic B-cell-activated reproduction number. Numerically, we examine that low level noise can maintain the number of the virus and B-cell populations at a certain range, while high level noise is helpful for the elimination of the virus. Furthermore, the effect of the cell-to-cell infection on model behaviour, and the influence of the key parameters on the size of the stochastic B-cell-activated reproduction number are also investigated.

ANALYSIS OF A STOCHASTIC HBV INFECTION MODEL WITH NONLINEAR INCIDENCE RATE

Considering that environmental factors, diet, subconscious mind and other uncertainties play an important role in the process of delaying and treating diseases, we propose, in this paper, an amended Hepatitis B virus (HBV) model with stochastic perturbation, and investigate the longtime dynamics of this stochastic model. First, if the basic reproductive number of the corresponding deterministic model is less than 1, some sufficient conditions for almost surely exponentially stable in the sense of the infected cells and free virus are established, and the stationary probability density function of the uninfected sell is also obtained. Further, some sufficient conditions for the existence of the stationary distribution are obtained for the basic reproductive number more than 1. In addition, oscillatory behaviors of this model about the equilibrium of the corresponding deterministic model are discussed. Finally, numerical simulations demonstrate the main theoretical results and show stochastic virus model has more dynamic behaviors relative to its corresponding deterministic model. Theoretical results and numerical simulations imply that the intensity and “type (divided into positive and negative)” of white noise play very important roles in the treatment of infectious disease, which can make the disease more and more repetitive and unpredictable. Of course, comfortable environment, reasonable diet, optimistic mood and other positive uncertainty factors have active effects on the treatment and delaying of diseases, but not the converse.

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?

Impact of the HIV-1 genetic background and HIV-1 population size on the evolution of raltegravir resistance

BACKGROUND

Emergence of resistance against integrase inhibitor raltegravir in human immunodeficiency virus type 1 (HIV-1) patients is generally associated with selection of one of three signature mutations: Y143C/R, Q148K/H/R or N155H, representing three distinct resistance pathways. The mechanisms that drive selection of a specific pathway are still poorly understood. We investigated the impact of the HIV-1 genetic background and population dynamics on the emergence of raltegravir resistance. Using deep sequencing we analyzed the integrase coding sequence (CDS) in longitudinal samples from five patients who initiated raltegravir plus optimized background therapy at viral loads > 5000 copies/ml. To investigate the role of the HIV-1 genetic background we created recombinant viruses containing the viral integrase coding region from pre-raltegravir samples from two patients in whom raltegravir resistance developed through different pathways. The in vitro selections performed with these recombinant viruses were designed to mimic natural population bottlenecks.

RESULTS

Deep sequencing analysis of the viral integrase CDS revealed that the virological response to raltegravir containing therapy inversely correlated with the relative amount of unique sequence variants that emerged suggesting diversifying selection during drug pressure. In 4/5 patients multiple signature mutations representing different resistance pathways were observed. Interestingly, the resistant population can consist of a single resistant variant that completely dominates the population but also of multiple variants from different resistance pathways that coexist in the viral population. We also found evidence for increased diversification after stronger bottlenecks. In vitro selections with low viral titers, mimicking population bottlenecks, revealed that both recombinant viruses and HXB2 reference virus were able to select mutations from different resistance pathways, although typically only one resistance pathway emerged in each individual culture.

CONCLUSIONS

The generation of a specific raltegravir resistant variant is not predisposed in the genetic background of the viral integrase CDS. Typically, in the early phases of therapy failure the sequence space is explored and multiple resistance pathways emerge and then compete for dominance which frequently results in a switch of the dominant population over time towards the fittest variant or even multiple variants of similar fitness that can coexist in the viral population.

Mutation and recombination in pathogen evolution: Relevance, methods and controversies

Mutation and recombination drive the evolution of most pathogens by generating the genetic variants upon which selection operates. Those variants can, for example, confer resistance to host immune systems and drug therapies or lead to epidemic outbreaks. Given their importance, diverse evolutionary studies have investigated the abundance and consequences of mutation and recombination in pathogen populations. However, some controversies persist regarding the contribution of each evolutionary force to the development of particular phenotypic observations (e.g., drug resistance). In this study, we revise the importance of mutation and recombination in the evolution of pathogens at both intra-host and inter-host levels. We also describe state-of-the-art analytical methodologies to detect and quantify these two evolutionary forces, including biases that are often ignored in evolutionary studies. Finally, we present some of our former studies involving pathogenic taxa where mutation and recombination played crucial roles in the recovery of pathogenic fitness, the generation of interspecific genetic diversity, or the design of centralized vaccines. This review also illustrates several common controversies and pitfalls in the analysis and in the evaluation and interpretation of mutation and recombination outcomes.

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.

Driving HIV-1 into a Vulnerable Corner by Taking Advantage of Viral Adaptation and Evolution

Anti-retroviral therapy (ART) is crucial for controlling human immunodeficiency virus type-1 (HIV-1) infection. Recently, progress in identifying and characterizing highly potent broadly neutralizing antibodies has provided valuable templates for HIV-1 therapy and vaccine design. Nevertheless, HIV-1, like many RNA viruses, exhibits genetically diverse populations known as quasispecies. Evolution of quasispecies can occur rapidly in response to selective pressures, such as that exerted by ART and the immune system. Hence, rapid viral evolution leading to drug resistance and/or immune evasion is a significant barrier to the development of effective HIV-1 treatments and vaccines. Here, we describe our recent investigations into evolutionary pressure exerted by anti-retroviral drugs and monoclonal neutralizing antibodies (NAbs) on HIV-1 envelope sequences. We also discuss sensitivities of HIV-1 escape mutants to maraviroc, a CCR5 inhibitor, and HIV-1 sensitized to NAbs by small-molecule CD4-mimetic compounds. These studies help to develop an understanding of viral evolution and escape from both anti-retroviral drugs and the immune system, and also provide fundamental insights into the combined use of NAbs and entry inhibitors. These findings of the adaptation and evolution of HIV in response to drug and immune pressure will inform the development of more effective antiviral therapeutic strategies.

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.

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.

Influence of mutation and recombination on HIV-1 in vitro fitness recovery

The understanding of the evolutionary processes underlying HIV-1 fitness recovery is fundamental for HIV-1 pathogenesis, antiretroviral treatment and vaccine design. It is known that HIV-1 can present very high mutation and recombination rates, however the specific contribution of these evolutionary forces in the "in vitro" viral fitness recovery has not been simultaneously quantified. To this aim, we analyzed substitution, recombination and molecular adaptation rates in a variety of HIV-1 biological clones derived from a viral isolate after severe population bottlenecks and a number of large population cell culture passages. These clones presented an overall but uneven fitness gain, mean of 3-fold, respect to the initial passage values. We found a significant relationship between the fitness increase and the appearance and fixation of mutations. In addition, these fixed mutations presented molecular signatures of positive selection through the accumulation of non-synonymous substitutions. Interestingly, viral recombination correlated with fitness recovery in most of studied viral quasispecies. The genetic diversity generated by these evolutionary processes was positively correlated with the viral fitness. We conclude that HIV-1 fitness recovery can be derived from the genetic heterogeneity generated through both mutation and recombination, and under diversifying molecular adaptation. The findings also suggest nonrandom evolutionary pathways for in vitro fitness recovery.

Genetic Consequences of Antiviral Therapy on HIV-1

A variety of enzyme inhibitors have been developed in combating HIV-1, however the fast evolutionary rate of this virus commonly leads to the emergence of resistance mutations that finally allows the mutant virus to survive. This review explores the main genetic consequences of HIV-1 molecular evolution during antiviral therapies, including the viral genetic diversity and molecular adaptation. The role of recombination in the generation of drug resistance is also analyzed. Besides the investigation and discussion of published works, an evolutionary analysis of protease-coding genes collected from patients before and after treatment with different protease inhibitors was included to validate previous studies. Finally, the review discusses the importance of considering genetic consequences of antiviral therapies in models of HIV-1 evolution that could improve current genotypic resistance testing and treatments design.

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.

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.

Quantifying selection against synonymous mutations in HIV-1 env evolution

Intrapatient evolution of human immunodeficiency virus type 1 (HIV-1) is driven by the adaptive immune system resulting in rapid change of HIV-1 proteins. When cytotoxic CD8(+) T cells or neutralizing antibodies target a new epitope, the virus often escapes via nonsynonymous mutations that impair recognition. Synonymous mutations do not affect this interplay and are often assumed to be neutral. We test this assumption by tracking synonymous mutations in longitudinal intrapatient data from the C2-V5 part of the env gene. We find that most synonymous variants are lost even though they often reach high frequencies in the viral population, suggesting a cost to the virus. Using published data from SHAPE (selective 2'-hydroxyl acylation analyzed by primer extension) assays, we find that synonymous mutations that disrupt base pairs in RNA stems flanking the variable loops of gp120 are more likely to be lost than other synonymous changes: these RNA hairpins might be important for HIV-1. Computational modeling indicates that, to be consistent with the data, a large fraction of synonymous mutations in this genomic region need to be deleterious with a cost on the order of 0.002 per day. This weak selection against synonymous substitutions does not result in a strong pattern of conservation in cross-sectional data but slows down the rate of evolution considerably. Our findings are consistent with the notion that large-scale patterns of RNA structure are functionally relevant, whereas the precise base pairing pattern is not.

A finite population model of molecular evolution: theory and computation

This article is concerned with the evolution of haploid organisms that reproduce asexually. In a seminal piece of work, Eigen and coauthors proposed the quasispecies model in an attempt to understand such an evolutionary process. Their work has impacted antiviral treatment and vaccine design strategies. Yet, predictions of the quasispecies model are at best viewed as a guideline, primarily because it assumes an infinite population size, whereas realistic population sizes can be quite small. In this paper we consider a population genetics-based model aimed at understanding the evolution of such organisms with finite population sizes and present a rigorous study of the convergence and computational issues that arise therein. Our first result is structural and shows that, at any time during the evolution, as the population size tends to infinity, the distribution of genomes predicted by our model converges to that predicted by the quasispecies model. This justifies the continued use of the quasispecies model to derive guidelines for intervention. While the stationary state in the quasispecies model is readily obtained, due to the explosion of the state space in our model, exact computations are prohibitive. Our second set of results are computational in nature and address this issue. We derive conditions on the parameters of evolution under which our stochastic model mixes rapidly. Further, for a class of widely used fitness landscapes we give a fast deterministic algorithm which computes the stationary distribution of our model. These computational tools are expected to serve as a framework for the modeling of strategies for the deployment of mutagenic drugs.

Impact of antiretroviral pressure on selection of primary human immunodeficiency virus type 1 envelope sequences in vitro

The initiation of drug therapy results in a reduction in the human immunodeficiency virus type 1 (HIV-1) population, which represents a potential genetic bottleneck. The effect of this drug-induced genetic bottleneck on the population dynamics of the envelope (Env) regions has been addressed in several in vivo studies. However, it is difficult to investigate the effect on the env gene of the genetic bottleneck induced not only by entry inhibitors but also by non-entry inhibitors, particularly in vivo. Therefore, this study used an in vitro selection system using unique bulk primary isolates established in the laboratory to observe the effects of the antiretroviral drug-induced bottleneck on the integrase and env genes. Env diversity was decreased significantly in one primary isolate [KP-1, harbouring both CXCR4 (X4)- and CCR5 (R5)-tropic variants] when passaged in the presence or absence of raltegravir (RAL) during in vitro selection. Furthermore, the RAL-selected KP-1 variant had a completely different Env sequence from that in the passage control (particularly evident in the gp120, V1/V2 and V4-loop regions), and a different number of potential N-glycosylation sites. A similar pattern was also observed in other primary isolates when using different classes of drugs. This is the first study to explore the influence of anti-HIV drugs on bottlenecks in bulk primary HIV isolates with highly diverse Env sequences using in vitro selection.

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.

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.

Development and evaluation of an assay for HIV-1 protease and reverse transcriptase drug resistance genotyping of all major group-M subtypes

BACKGROUND

High cost and varying sensitivity for non-B HIV-1 subtypes limits application of current commercial kits for HIV-1 drug resistance genotyping of all major HIV-1 group-M subtypes.

OBJECTIVES

Our research aimed to develop and validate an assay specific for all major HIV-1 group-M subtypes for use as an alternative to commercial assays for HIV-1 protease (PR) and reverse transcriptase (RT) drug resistance genotyping.

STUDY DESIGN

A nested RT-PCR encompassing the entire PR and RT up to amino acid 321 of HIV-1 was designed to detect HIV-1 group-M subtypes. Primers compatible with group-M subtypes were defined and analytical sensitivity of the assay evaluated using a panel of reference viruses for subtypes A-H and CRF01_AE. The assay was subsequently evaluated on 246 plasma samples from HIV-1 infected individuals harboring various group-M subtypes and viral loads (VLs).

RESULTS

All major group-M HIV-1 subtypes were detected with an overall analytical sensitivity of 1.00E+03 RNA copies/ml. Application of the genotyping assay on 246 primarily African clinical samples comprising subtypes A (n=52; 21.7%), B (n=12; 5.0%), C (n=127; 52.9%), D (n=25; 10.4%), CRF01_AE (n=10; 4.2%), and CRF02_AG (n=10; 4.2%), and unassigned variants (n=10; 4.2%), VL range 4.32E+02-8.63E+06 (median 2.66E+04) RNA copies/ml, was ∼98% successful.

CONCLUSIONS

A group-M subtype-independent genotyping assay for detection of HIV-1 drug resistance was developed. The described assay can serve as an alternative to commercial assays for HIV-1 drug resistance genotyping in routine diagnostics, and for surveillance and monitoring of drug resistance in resource-limited settings (RLS).

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.

One is enough: in vivo effective population size is dose-dependent for a plant RNA virus

Effective population size (N(e)) determines the strength of genetic drift and the frequency of co-infection by multiple genotypes, making it a key factor in viral evolution. Experimental estimates of N(e) for different plant viruses have, however, rendered diverging results. The independent action hypothesis (IAH) states that each virion has a probability of infection, and that virions act independent of one another during the infection process. A corollary of IAH is that N(e) must be dose dependent. A test of IAH for a plant virus has not been reported yet. Here we perform a test of an IAH infection model using a plant RNA virus, Tobacco etch virus (TEV) variants carrying GFP or mCherry fluorescent markers, in Nicotiana tabacum and Capsicum annuum plants. The number of primary infection foci increased linearly with dose, and was similar to a Poisson distribution. At high doses, primary infection foci containing both genotypes were found at a low frequency (<2%). The probability that a genotype that infected the inoculated leaf would systemically infect that plant was near 1, although in a few rare cases genotypes could be trapped in the inoculated leaf by being physically surrounded by the other genotype. The frequency of mixed-genotype infection could be predicted from the mean number of primary infection foci using the independent-action model. Independent action appears to hold for TEV, and N(e) is therefore dose-dependent for this plant RNA virus. The mean number of virions causing systemic infection can be very small, and approaches 1 at low doses. Dose-dependency in TEV suggests that comparison of N(e) estimates for different viruses are not very meaningful unless dose effects are taken into consideration.

Taking multiple infections of cells and recombination into account leads to small within-host effective-population-size estimates of HIV-1

Whether HIV-1 evolution in infected individuals is dominated by deterministic or stochastic effects remains unclear because current estimates of the effective population size of HIV-1 in vivo, N(e), are widely varying. Models assuming HIV-1 evolution to be neutral estimate N(e)~10²-10⁴, smaller than the inverse mutation rate of HIV-1 (~10⁵), implying the predominance of stochastic forces. In contrast, a model that includes selection estimates N(e)>10⁵, suggesting that deterministic forces would hold sway. The consequent uncertainty in the nature of HIV-1 evolution compromises our ability to describe disease progression and outcomes of therapy. We perform detailed bit-string simulations of viral evolution that consider large genome lengths and incorporate the key evolutionary processes underlying the genomic diversification of HIV-1 in infected individuals, namely, mutation, multiple infections of cells, recombination, selection, and epistatic interactions between multiple loci. Our simulations describe quantitatively the evolution of HIV-1 diversity and divergence in patients. From comparisons of our simulations with patient data, we estimate N(e)~10³-10⁴, implying predominantly stochastic evolution. Interestingly, we find that N(e) and the viral generation time are correlated with the disease progression time, presenting a route to a priori prediction of disease progression in patients. Further, we show that the previous estimate of N(e)>10⁵ reduces as the frequencies of multiple infections of cells and recombination assumed increase. Our simulations with N(e)~10³-10⁴ may be employed to estimate markers of disease progression and outcomes of therapy that depend on the evolution of viral diversity and divergence.

Phylogeny and resistance profiles of HIV-1 POL sequences from rectal biopsies and blood

The phylogeny and resistance profiles of human immunodeficiency virus type 1 (HIV-1) protease (PR) and reverse transcriptase (RT) sequences were compared among six patients with HIV-1 who had received numerous treatments. RNA and DNA fractions were obtained from concurrent blood and rectal biopsy samples. Phylogenetic trees and resistance profiles showed that the rectal mucosa and the peripheral blood mononuclear cells (PBMCs) harbored different HIV-1 strains. The resistance-associated mutations found in each strain corresponded to the treatment history of the patients. The resistance mutations acquired during earlier treatment regimens were detected in the sequences obtained from the rectal samples and in the PBMCs in several of the patients. Also, differences in the resistance profiles were observed between anatomical sites and between RNA and DNA fractions. Thus, a single sample probably will not be representative of the HIV-1 archived in different sites. Both the resistance profile and phylogeny of HIV-1 often differed in sequences obtained from RNA and DNA from the same site. These findings suggest that additional information regarding the antiviral resistance profile of the patient might be obtained by testing different anatomical sites.

Estimating frequencies of minority nevirapine-resistant strains in chronically HIV-1-infected individuals naive to nevirapine by using stochastic simulations and a mathematical model

Nevirapine forms the mainstay of our efforts to curtail the pediatric AIDS epidemic through prevention of mother-to-child transmission of HIV-1. A key limitation, however, is the rapid selection of HIV-1 strains resistant to nevirapine following the administration of a single dose. This rapid selection of resistance suggests that nevirapine-resistant strains preexist in HIV-1 patients and may adversely affect outcomes of treatment. The frequencies of nevirapine-resistant strains in vivo, however, remain poorly estimated, possibly because they exist as a minority below current assay detection limits. Here, we employ stochastic simulations and a mathematical model to estimate the frequencies of strains carrying different combinations of the common nevirapine resistance mutations K103N, V106A, Y181C, Y188C, and G190A in chronically infected HIV-1 patients naïve to nevirapine. We estimate the relative fitness of mutant strains from an independent analysis of previous competitive growth assays. We predict that single mutants are likely to preexist in patients at frequencies ( approximately 0.01% to 0.001%) near or below current assay detection limits (>0.01%), emphasizing the need for more-sensitive assays. The existence of double mutants is subject to large stochastic variations. Triple and higher mutants are predicted not to exist. Our estimates are robust to variations in the recombination rate, cellular superinfection frequency, and the effective population size. Thus, with 10(7) to 10(8) infected cells in HIV-1 patients, even when undetected, nevirapine-resistant genomes may exist in substantial numbers and compromise efforts to prevent mother-to-child transmission of HIV-1, accelerate the failure of subsequent antiretroviral treatments, and facilitate the transmission of drug resistance.

HIV protease resistance and viral fitness

PURPOSE OF REVIEW

This review focuses on the evolution of protease inhibitor resistance and replication capacity in the presence and absence of protease inhibitor pressure.

RECENT FINDINGS

Classically, HIV escapes through mutations in the protease itself causing a decrease in affinity to the inhibitor, leading to resistance. These changes also affect the binding of the enzyme to the natural substrate, and as a consequence cause a decrease in replication capacity of the virus. Continuous replication of these viruses may result in the acquisition of compensatory changes, which will fixate the drug-resistant variant in the viral population. Furthermore, novel treatment strategies have been developed to combat the development of classic protease inhibitor resistance. Using these strategies, the development of resistance in the viral protease is blocked because single or double mutations do not confer significant resistance. Alternative protease inhibitor resistance pathways are described, which enable the virus to escape these novel strategies.

SUMMARY

Suboptimal protease inhibitor pressure clearly results in the selection of mutations conferring resistance and in the acquisition of mutations compensating the initial reduction in viral replicative capacity. The major implications of the selection of these compensatory changes on evolution in the absence of protease inhibitor pressure are discussed.

The evolutionary rate dynamically tracks changes in HIV-1 epidemics: application of a simple method for optimizing the evolutionary rate in phylogenetic trees with longitudinal data

Large-sequence datasets provide an opportunity to investigate the dynamics of pathogen epidemics. Thus, a fast method to estimate the evolutionary rate from large and numerous phylogenetic trees becomes necessary. Based on minimizing tip height variances, we optimize the root in a given phylogenetic tree to estimate the most homogenous evolutionary rate between samples from at least two different time points. Simulations showed that the method had no bias in the estimation of evolutionary rates and that it was robust to tree rooting and topological errors. We show that the evolutionary rates of HIV-1 subtype B and C epidemics have changed over time, with the rate of evolution inversely correlated to the rate of virus spread. For subtype B, the evolutionary rate slowed down and tracked the start of the HAART era in 1996. Subtype C in Ethiopia showed an increase in the evolutionary rate when the prevalence increase markedly slowed down in 1995. Thus, we show that the evolutionary rate of HIV-1 on the population level dynamically tracks epidemic events.

The effect of intrinsic stochasticity on transmitted HIV drug resistance patterns

Estimates of transmitted HIV drug-resistance prevalence vary widely among and within epidemiological surveys. Interpretation of trends from available survey data is therefore difficult. Because the emergence of drug-resistance involves small populations of infected drug-resistant individuals, the role of stochasticity (chance events) is likely to be important. The question addressed here is: how much variability in transmitted HIV drug-resistance prevalence patterns arises due to intrinsic stochasticity alone, i.e., if all starting conditions in the different epidemics surveyed were identical? This 'thought experiment' gives insight into the minimum expected variabilities within and among epidemics. A simple stochastic mathematical model was implemented. Our results show that stochasticity alone can generate a significant degree of variability and that this depends on the size and variation of the pool of new infections when drug treatment is first introduced. The variability in transmitted drug-resistance prevalence within an epidemic (i.e., the temporal variability) is large when the annual pool of all new infections is small (fewer than 200, typical of the HIV epidemics in Central European and Scandinavian countries) but diminishes rapidly as that pool grows. Epidemiological surveys involving hundreds of new infections annually are therefore needed to allow meaningful interpretation of temporal trends in transmitted drug-resistance prevalence within individual epidemics. The stochastic variability among epidemics shows a similar dependence on the pool of new infections if treatment is introduced after endemic equilibrium is established, but can persist even when there are more than 10,000 new infections annually if drug therapy is introduced earlier. Stochastic models may therefore have an important role to play in interpreting differences in transmitted drug-resistance prevalence trends among epidemiological surveys.

High HIV Type 1 prevalence and wide genetic diversity with dominance of recombinant strains but low level of antiretroviral drug-resistance mutations in untreated patients in northeast Gabon, Central Africa

The northeast of Gabon, central Africa is characterized by high population density and a high rate of immigration from the surrounding countries. To determine the prevalence, circulating subtypes, and antiretroviral resistance mutations of HIV-1, 810 blood samples were collected from the general population of the two main cities (Oyem and Makokou) of this region. Of these, 61 (7.5%) were found to be positive for HIV-1. Analysis of the env (gp120), pol, and gag (p24) sequences as well as phylogenetic analyses showed at least eight different viral lineages. The most prevalent strains were CRF02 recombinants, followed by subtypes A, D, and C. The remaining strains were found to be F, J, G, and also, for the first time in Gabon, the recombinant form CRF11cpx. Analysis of antiretroviral drug-resistance mutations in protease and reverse transcriptase from this untreated population showed a low level of specific mutations. These mutations were associated with subtype polymorphism rather than with resistance to antiretroviral drugs. The wide diversity and the emergence of recombinant strains are in accordance with the rapid spread of new HIV strains in the population and, thus, the dynamic evolution of the epidemic.

Immunological responses during a virologically failing antiretroviral regimen are associated with in vivo synonymous mutation rates of HIV type-1 env

Background

Little is known about the underlying causes of differences in immunological response to antiretroviral therapy during multidrug-resistant (MDR) HIV type-1 (HIV-1) infection. This study aimed to identify virological factors associated with immunological response during therapy failure.

Methods

Individuals with MDR HIV-1 receiving therapy for ≥3 months were included. CD4+ T-cell count slopes and pol and clonal env sequences were determined. Genetic analyses were performed using distance-based and maximum likelihood methods. Synonymous mutations rates of env were used to estimate viral replication.

Results

Of 1,000 patients treated between 1995 and 2003, 72 individuals fulfilled the definition for triple-class failure, but 25 were non-compliant, 21 were successfully resuppressed and 3 had died or quit therapy. Of the 23 that fulfilled study criteria, 16 had samples available for analysis. In a longitudinal mixed-effects model, plasma HIV-1 RNA only tended to predict immunological response ( P=0.06), whereas minor protease inhibitor (PI) and nucleoside reverse transcriptase (NRTI) mutations at baseline correlated significantly with CD4+ T-cell count slopes ( r=-0.56, P=0.04 and r=-0.64, P=0.008, respectively). Interestingly, synonymous mutations of env correlated inversely with CD4+ T-cell count slopes ( r=-0.60; P=0.01) and individuals with codons under positive selection had significantly better CD4+ T-cell responses than individuals without (0.42 versus -5.34; P=0.02).

Conclusions

Our results suggest that minor PI mutations and NRTI mutations present early during therapy failure are predictive of the CD4+ T-cell count slopes. Synonymous mutation rates of the env gene suggested that underlying differences in fitness could cause this association.

Genetic drift of HIV populations in culture

Populations of Human Immunodeficiency Virus type 1 (HIV-1) undergo a surprisingly large amount of genetic drift in infected patients despite very large population sizes, which are predicted to be mostly deterministic. Several models have been proposed to explain this phenomenon, but all of them implicitly assume that the process of virus replication itself does not contribute to genetic drift. We developed an assay to measure the amount of genetic drift for HIV populations replicating in cell culture. The assay relies on creation of HIV populations of known size and measurements of variation in frequency of a neutral allele. Using this assay, we show that HIV undergoes approximately ten times more genetic drift than would be expected from its population size, which we defined as the number of infected cells in the culture. We showed that a large portion of the increase in genetic drift is due to non-synchronous infection of target cells. When infections are synchronized, genetic drift for the virus is only 3-fold higher than expected from its population size. Thus, the stochastic nature of biological processes involved in viral replication contributes to increased genetic drift in HIV populations. We propose that appreciation of these effects will allow better understanding of the evolutionary forces acting on HIV in infected patients.

Genetic drift can be a strong evolutionary force, especially in small populations. Studies of HIV evolution within a single infected patient suggest that genetic drift plays an important role in the evolution of the virus, despite the large size of the viral population. The factors responsible for the high genetic drift are not known, but several models have been proposed to explain the phenomenon; all of them assume that the viral population is ideal. We measured the amount of genetic drift in HIV populations, replicating in the controlled environment of cell culture. We found that HIV populations exhibit approximately 10-fold more genetic drift than would be expected for an ideal population of similar size. Non-synchronous timing of infection is partially responsible for the increase, but other unidentified factors also contribute. While the increase in genetic drift observed for HIV in culture is not sufficient to explain the several orders of magnitude increase in intra-patient genetic drift, it provides strong experimental evidence for the intrinsic stochasticity of the HIV replication cycle. Understanding the sources of genetic drift is necessary to better understand the evolutionary forces that act upon HIV in vivo.

Antiviral resistance and impact on viral replication capacity: evolution of viruses under antiviral pressure occurs in three phases

Resistance development is a major obstacle to antiviral therapy, and all active antiviral agents have shown to select for resistance mutations. Aspects of antiviral resistance development are discussed for specific compounds or drug classes in the previous chapters, while this chapter provides an overview regarding the evolution of different viruses (HIV, HBV, HCV, and Influenza) under pressure of antiviral therapy. Virus replication is an error prone process resulting in a large number of variants (quasispecies) in patients. Resistance evolution under suboptimal therapy can be schematically distinguished into three phases. (1) preexisting variants less sensitive to the respective drug are selected from the quasispecies population, (2) outgrowing variants acquire additional mutations increasing their resistance, and (3) compensatory mutations accumulate to overcome the generally reduced replicative capacity of resistant variants. Successful therapy should be aimed at suppression of all existing viral variants, thus preventing selection of minority species and their subsequent evolution. This implies that the amount of mutations required for first escape to the viral regimen (genetic barrier) should be larger than the expected number of mutations present in viruses in the quasispecies. Accordingly, combination therapy can achieve complete inhibition of replication for most HIV, HBV, and Influenza infected patients without resistance development. However, resistant viruses can become selected under circumstances of suboptimal antiviral therapy and these resistant viruses can be transmitted. Proper use of drugs and worldwide monitoring for the presence and spread of drug resistant viruses are therefore of utmost importance.

The changing trend of HIV type 1 subtypes in Nairobi

Monitoring the distribution of HIV-1 subtypes and recombinants among infected individuals has become a priority in HIV therapy. A laboratory analysis of samples collected from HIV-positive patients attending an STI clinic in Nairobi was done between March and May 2004. PCR was carried out on pol (intergrase) and env (C2V3) regions and resulting data on the 54 samples successfully analyzed revealed the following as circulating subtypes: 35/54(65%) were A1/A1, 5/54(9%) were A/C, 4/54 (7%) were A1/D, 1/54 (2%) was C/D, 1/54 (2%) was D/D, 1/54 (2%) was A1/A2, 1/54 (2%)was G/G, 1/54 (2%) was A2/D, 1/54 (2%) was C/C, and 4/54 (7%) were CRF02_ AG. The results show an increase in HIV-1 recombinants with the emergence of A1/A2 and an increase in CRF02_AG recombinants. Subtype diversity in the advent of ARV use will impact negatively on treatment outcomes. As such, increased viral evolution and recombination will call for continuous evaluation of available anti-HIV regimens for better management of those infected with HIV-1.

Estimation of the effective number of founders that initiate an infection after aphid transmission of a multipartite plant virus

The fecundity of RNA viruses can be very high. Thus, it is often assumed that viruses have large populations, and RNA virus evolution has been mostly explained using purely deterministic models. However, population bottlenecks during the virus life cycle could result in effective population numbers being much smaller than reported censuses, and random genetic drift could be important in virus evolution. A step at which population bottlenecks may be severe is host-to-host transmission. We report here an estimate of the size of the population that starts a new infection when Cucumber mosaic virus (CMV) is transmitted by the aphid Aphis gossypii, based on the segregation of two CMV genotypes in plants infected by aphids that acquired the virus from plants infected by both genotypes. Results show very small effective numbers of founders, between one and two, both in experiments in which the three-partite genome of CMV was aphid transmitted and in experiments in which a fourth RNA, CMV satellite RNA, was also transmitted. These numbers are very similar to those published for Potato virus Y, which has a monopartite genome and is transmitted by aphids according to a different mechanism than CMV. Thus, the number of genomic segments seems not to be a major determinant of the effective number of founders. Also, our results suggest that the occurrence of severe bottlenecks during horizontal transmission is general for viruses nonpersistently transmitted by aphids, indicating that random genetic drift should be considered when modeling virus evolution.

Interplay of reverse transcriptase inhibitor therapy and gag p6 diversity in HIV type 1 subtype G and CRF02_AG

Abstract The gag p6 region of HIV-1 has various nonsubstitutionary mutations, including insertions, duplications, deletions, and premature stop codons. Studies have linked gag p6 mutations to reduced susceptibility to antiretroviral therapy in HIV-1 subtype B. This study examined the relationship between antiretroviral therapy and gag p6 diversity in HIV-1 CRF02_AG and subtype G. p6 data were generated for secondary analyses following Viroseq genotyping of pol gene sequences in plasma samples from HIV-1-infected Nigerians on reverse transcriptase inhibitor therapy, with virologic failure (repeat VL > 2000 copies/ml). p6 sequence chromatograms were available for 40 CRF02_AG and 43 subtype G-infected individuals. Subjects who had not received their supply of antiretroviral drugs for at least 2 months prior to the plasma sampling were classified as nonadherent. p6 sequences from therapy-adherent individuals had more nonsubstitutionary mutations than sequences from drug-naive individuals (p = 0.0005). The P5L/T mutation was inversely correlated with the presence of K27Q/N in p6, with each mutation being more prominent in subtype G and CRF02_AG, respectively. The data also suggested that P5L/T may be a compensatory mutation for the loss of an essential phosphorylation site in p6. In addition, there was an inverse association between P5L/T mutations in p6 and thymidine analog mutations in reverse transcriptase (p = 0.0001), and drug nonadherence was associated with an 8-fold lower risk of having a nonsubstitutionary mutation in p6 (95% CI = 1.27-52.57). Our data suggest that antiretroviral therapy influences gag p6 diversity, but further studies are needed to clarify these observations.

Human immunodeficiency virus type 1 seroprevalence and antiretroviral drug resistance-associated mutations in miners in Gabon, central Africa

Miners in sub-Saharan African are known to have an extremely high prevalence of HIV-1 infection. We therefore evaluated the prevalence of HIV-1 infection among manganese miners in Gabon, central Africa and examined the diversity of HIV-1 strains by characterizing the polymorphism of the pol gene in order to observe drug resistance-associated mutations. In 857 samples tested, the HIV-1 prevalence was 2.9%. By pol sequence analysis, we showed that all the HIV-1 strains belonged to group M, with a majority of CRF02_AG (57%) followed by subtype A (9%) and CRF01_AE or subtype B (4%). The remaining HIV-1 strains demonstrated discordant genomic results and exhibited a mosaic pol genome (30%). Most of the mutations detected in pol coding regions corresponded to the subtype polymorphism, with no specific antiretroviral drug resistance. To avoid the rapid emergence of resistant viruses in this part of central Africa, continuous surveillance of the circulation of drug-resistant viruses must be maintained to guide treatment strategies.

Reappearance of an 11-year-old sequence in an HIV-1 infected patient during treatment interruption

HIV-1 from a patient with multi-drug resistant virus was identified as wild type during treatment interruption. The aim of the study was to describe how the viral population is affected by treatment interruptions and use phylogeny to reconstruct the evolutionary pattern. 15 samples covering 13 y and 2 treatment interruptions were analysed in both pol and env. The wild type virus found in the sample from the second treatment interruption in 2002 had not been present as a dominant population since 1994. Phylogeny showed that the 2002 sample was more closely related to wild type sequences than to other sequences sampled in 2002. This indicated that the wild type virus was caused by recruitment from the viral archives rather than reversion of previously circulating resistant strains. A few weeks after re-initiated treatment, virus showed full resistance, indicating that resistant virus was present as a subpopulation and reselected due to higher fitness in the presence of drugs. Phylogeny of env showed that CCR5 and CXCR4 viruses coexist in the patient. In conclusion, the study showed that at all times during infection, virus is archived in the cells and can be recruited when the surrounding environment changes and the archived virus is more fit.

Modeling HIV infection dynamics: the role of recombination in the development of drug resistance

The benefit of recombination to HIV remains unclear because just as recombination can induce the association of favorable mutations and accelerate the development of multidrug resistance, it can also dissociate favorable combinations of mutations. The confounding influences of mutation, random genetic drift, selection and epistatic interactions between multiple resistance loci render the role of recombination difficult to unravel experimentally. Mathematical models provide valuable insights into the influence of recombination on the genomic diversification of HIV and the development of drug resistance in patients undergoing therapy, capture several recent experimental observations of HIV recombination quantitatively, and set the stage for the establishment of a robust framework for the identification of improved treatment protocols and guidelines for drug development.

Evolution of genetic diversity and drug resistance mutations in HIV-1 among untreated patients from Mali between 2005 and 2006

OBJECTIVES

To describe HIV-1 variants circulating in Mali and to estimate the rate of transmission of HIV-1 drug resistance in 2006.

PATIENTS AND METHODS

Viral reverse transcriptase (RT) and protease (PR) genes from 198 antiretroviral (ARV)-naive patients diagnosed HIV-1 positive in May 2006 in Bamako and Segou were sequenced.

RESULTS

Although CRF02_AG was always the predominant HIV-1 subtype observed (72%), a higher genetic diversity than that in 2005 was observed. The overall prevalence of primary resistance is 11.5% in Mali in 2006, according to the 2007 IAS-USA list of mutations [nucleoside RT inhibitor (NRTI): 1.5%, non-NRTI (NNRTI): 9% and PI: 1%], and 2.5% (NRTI: 1%, NNRTI: 1.5% and PI: 0%), according to the Stanford list of mutations. There was no significant difference between 2005 and 2006 in the overall primary resistance prevalence or in the prevalence of mutations in the different ARV classes. Resistance mutations found in RT and PR genes are in agreement with the highly active antiretroviral therapy regimen available in Mali, except for V90I, V106I and A98G mutations which are associated with etravirine resistance, but polymorphic in non-B subtypes.

CONCLUSIONS

HIV-1 genetic diversity seems increased in Mali, but the overall HIV-1 primary resistance prevalence remains low. This is consistent with the findings from other West African countries where prevalence rates are lower than 5%. However, considering the large scaling up of ARV use in this country, it is necessary to regularly monitor the development of primary resistance in Mali.

Recombination increases human immunodeficiency virus fitness, but not necessarily diversity

Recombination can facilitate the accumulation of mutations and accelerate the emergence of resistance to current antiretroviral therapies for human immunodeficiency virus (HIV) infection. Yet, since recombination can also dissociate favourable combinations of mutations, the benefit of recombination to HIV remains in question. The confounding effects of mutation, multiple infections of cells, random genetic drift and fitness selection that underlie HIV evolution render the influence of recombination difficult to unravel. We developed computer simulations that mimic the genomic diversification of HIV within an infected individual and elucidate the influence of recombination. We find, interestingly, that when the effective population size of HIV is small, recombination increases both the diversity and the mean fitness of the viral population. When the effective population size is large, recombination increases viral fitness but decreases diversity. In effect, recombination enhances (lowers) the likelihood of the existence of multi-drug resistant strains of HIV in infected individuals prior to the onset of therapy when the effective population size is small (large). Our simulations are consistent with several recent experimental observations, including the evolution of HIV diversity and divergencein vivo. The intriguing dependencies on the effective population size appear due to the subtle interplay of drift, selection and epistasis, which we discuss in the light of modern population genetics theories. Current estimates of the effective population size of HIV have large discrepancies. Our simulations present an avenue for accurate determination of the effective population size of HIVin vivoand facilitate establishment of the benefit of recombination to HIV.

Multiple independent origins of a protease inhibitor resistance mutation in salvage therapy patients

BACKGROUND

Combination anti-viral therapies have reduced treatment failure rates by requiring multiple specific mutations to be selected on the same viral genome to impart high-level drug resistance. To determine if the common protease inhibitor resistance mutation L90M is only selected once or repeatedly on different HIV genetic backbones during the course of failed anti-viral therapies we analyzed a linked region of the viral genome during the evolution of multi-drug resistance.

RESULTS

Using L90M allele specific PCR we amplified and sequenced gag-pro regions linked to very early L90M containing HIV variants prior to their emergence and detection as dominant viruses in 15 failed salvage therapy patients. The early minority L90M linked sequences were then compared to those of the later L90M viruses that came to dominate the plasma quasispecies. Using Bayesian evolutionary analysis sampling trees the emergence of L90M containing viruses was seen to take place on multiple occasion in 5 patients, only once for 2 patients and an undetermined number of time for the remaining 8 patients.

CONCLUSION

These results indicate that early L90M mutants can frequently be displaced by viruses carrying independently selected L90M mutations rather than by descendents of the earlier mutants.

Characterization of HIV type 1 reverse transcriptase mutations in infants infected by mothers who received peripartum nevirapine prophylaxis in Jos, Nigeria

This study was carried out to characterize HIV-1 reverse transcriptase (RT) mutations in vertically infected infants in Jos, Nigeria. DNA was extracted from peripheral blood mononuclear cells of 102 infants, aged 0 to 6 months, born to HIV-1-infected mothers who had received peripartum single-dose nevirapine prophylaxis. PCR-based diagnosis revealed that 14 infants (13.7%) were infected with HIV-1. Phylogenetic analyses of RT revealed wide viral diversity, with CRF02_AG, subtype G, subsubtype A3, CRF06_cpx, and a subtype D recombinant present in the population. Four of 13 (31%) infants had NNRTI resistance mutations--V179I (2 infants), Y181C, and V179E. Intriguingly, subtype G sequences did not have NNRTI mutations but rather carried a Q207N mutation, which may undergo negative selection under drug pressure. Our data suggest wide diversity for vertically transmitted HIV-1 viruses in Nigeria and highlight the potential significance of transmitting rare mutations in subtype G.