A genetic-algorithm approach to simulating human immunodeficiency virus evolution reveals the strong impact of multiply infected cells and recombination

A Trait-Based Approach to Predicting Viral Host-Range Evolvability

Predicting the evolution of virus host range has proven to be extremely difficult, in part because of the sheer diversity of viruses, each with unique biology and ecological interactions. We have not solved this problem, but to make the problem more tractable, we narrowed our focus to three traits intrinsic to all viruses that may play a role in host-range evolvability: mutation rate, recombination rate, and phenotypic heterogeneity. Although each trait should increase evolvability, they cannot do so unbounded because fitness trade-offs limit the ability of all three traits to maximize evolvability. By examining these constraints, we can begin to identify groups of viruses with suites of traits that make them especially concerning, as well as ecological and environmental conditions that might push evolution toward accelerating host-range expansion.

Space and Genotype-Dependent Virus Distribution during Infection Progression

The paper is devoted to a nonlocal reaction-diffusion equation describing the development of viral infection in tissue, taking into account virus distribution in the space of genotypes, the antiviral immune response, and natural genotype-dependent virus death. It is shown that infection propagates as a reaction-diffusion wave. In some particular cases, the 2D problem can be reduced to a 1D problem by separation of variables, allowing for proof of wave existence and stability. In general, this reduction provides an approximation of the 2D problem by a 1D problem. The analysis of the reduced problem allows us to determine how viral load and virulence depend on genotype distribution, the strength of the immune response, and the level of immunity.

An Evolutionary Computing Model for the Study of Within-Host Evolution

Evolution of an individual within another individual is known as within-host dynamics (WHD). The most common modeling technique to study WHD involves ordinary differential equations (ODEs). In the field of biology, models of this kind assume, for example, that both the number of viruses and the number of mouse cells susceptible to being infected change according to their interaction as stated in the ODE model. However, viruses can undergo mutations and, consequently, evolve inside the mouse, whereas the mouse, in turn, displays evolutionary mechanisms through its immune system (e.g., clonal selection), defending against the invading virus. In this work, as the main novelty, we propose an evolutionary WHD model simulating the coexistence of an evolving invader within a host. In addition, instead of using ODEs we developed an alternative methodology consisting of the hybridization of a genetic algorithm with an artificial immune system. Aside from the model, interest in biology, and its potential clinical use, the proposed WHD model may be useful in those cases where the invader exhibits evolutionary changes, for instance, in the design of anti-virus software, intrusion detection algorithms in a corporation’s computer systems, etc. The model successfully simulates two intruder detection paradigms (i.e., humoral detection, danger detection) in which the intruder represents an evolving invader or guest (e.g., virus, computer program,) that infects a host (e.g., mouse, computer memory). The obtained results open up the possibility of simulating environments in which two entities (guest versus host) compete evolutionarily with each other when occupying the same space (e.g., organ cells, computer memory, network).

Approximate perturbative solutions of quasispecies model with recombination

Despite the major roles played by genetic recombination in ecoevolutionary processes, limited progress has been made in analyzing realistic recombination models to date, due largely to the complexity of the associated mechanisms and the strongly nonlinear nature of the dynamical differential systems. In this paper, we consider a many-loci genomic model with fitness dependent on the Hamming distance from a reference genome, and adopt a Hamilton-Jacobi formulation to derive perturbative solutions for general linear fitness landscapes. The horizontal gene transfer model is used to describe recombination processes. Cases of weak selection and weak recombination with simultaneous mutation and selection are examined, yielding semianalytical solutions for the distribution surplus of O(1/N) accuracy, where N is the number of nucleotides in the genome.

Noise-induced bistability in the fate of cancer phenotypic quasispecies: a bit-strings approach

Tumor cell populations are highly heterogeneous. Such heterogeneity, both at genotypic and phenotypic levels, is a key feature during tumorigenesis. How to investigate the impact of this heterogeneity in the dynamics of tumors cells becomes an important issue. Here we explore a stochastic model describing the competition dynamics between a pool of heterogeneous cancer cells with distinct phenotypes and healthy cells. This model is used to explore the role of demographic fluctuations on the transitions involving tumor clearance. Our results show that for large population sizes, when demographic fluctuations are negligible, there exists a sharp transition responsible for tumor cells extinction at increasing tumor cells' mutation rates. This result is consistent with a mean field model developed for the same system. The mean field model reveals only monostability scenarios, in which either the dominance of the tumor cells or the dominance of the healthy cells is found. Interestingly, the stochastic model shows that for small population sizes the monostability behavior disappears, involving the presence of noise-induced bistability. The impact of the initial populations of cells in the fate of the cell populations is investigated, as well as the transient times towards the healthy and the cancer states.

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.

Retrospective on the all-in-one retroviral nucleocapsid protein

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This retrospective reviews 30 years of research on the retroviral nucleocapsid protein (NC) focusing on HIV-1 NC.

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Originally considered as a non-specific nucleic-acid binding protein, NC has seminal functions in virus replication.

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Indeed NC turns out to be a all-in-one viral protein that chaperones viral DNA synthesis and integration, and virus formation.

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As a chaperone NC provides assistance to genetic recombination thus allowing the virus to escape the immune response and antiretroviral therapies against HIV-1.

This review aims at briefly presenting a retrospect on the retroviral nucleocapsid protein (NC), from an unspecific nucleic acid binding protein (NABP) to an all-in-one viral protein with multiple key functions in the early and late phases of the retrovirus replication cycle, notably reverse transcription of the genomic RNA and viral DNA integration into the host genome, and selection of the genomic RNA together with the initial steps of virus morphogenesis. In this context we will discuss the notion that NC protein has a flexible conformation and is thus a member of the growing family of intrinsically disordered proteins (IDPs) where disorder may account, at least in part, for its function as a nucleic acid (NA) chaperone and possibly as a protein chaperone vis-à-vis the viral DNA polymerase during reverse transcription. Lastly, we will briefly review the development of new anti-retroviral/AIDS compounds targeting HIV-1 NC because it represents an ideal target due to its multiple roles in the early and late phases of virus replication and its high degree of conservation.

HIV-1 reverse transcription

Reverse transcription is an obligatory step in retrovirus replication in the course of which the retroviral RNA/DNA-dependent DNA polymerase (RT) copies the single-stranded positive sense RNA genome to synthesize the double-stranded viral DNA. At the same time the RT-associated RNaseH activity degrades the genomic RNA template, which has just been copied. The viral nucleocapsid protein NCp7 is an obligatory partner of RT, chaperoning synthesis of the complete viral DNA flanked by the two long-terminal repeats (LTR), required for viral DNA integration into the host genome and its expression. Here we describe assays for in vitro and ex vivo monitoring of reverse transcription and the chaperoning role of the nucleocapsid protein (NC).

Evolutionary advantage via common action of recombination and neutrality

We investigate evolution models with recombination and neutrality. We consider the Crow-Kimura (parallel) mutation-selection model with the neutral fitness landscape, in which there is a central peak with high fitness A, and some of 1-point mutants have the same high fitness A, while the fitness of other sequences is 0. We find that the effect of recombination and neutrality depends on the concrete version of both neutrality and recombination. We consider three versions of neutrality: (a) all the nearest neighbor sequences of the peak sequence have the same high fitness A; (b) all the l-point mutations in a piece of genome of length l≥1 are neutral; (c) the neutral sequences are randomly distributed among the nearest neighbors of the peak sequences. We also consider three versions of recombination: (I) the simple horizontal gene transfer (HGT) of one nucleotide; (II) the exchange of a piece of genome of length l, HGT-l; (III) two-point crossover recombination (2CR). For the case of (a), the 2CR gives a rather strong contribution to the mean fitness, much stronger than that of HGT for a large genome length L. For the random distribution of neutral sequences there is a critical degree of neutrality ν(c), and for μ<μ(c) and (μ(c)-μ) is not large, the 2CR suppresses the mean fitness while HGT increases it; for ν much larger than ν(c), the 2CR and HGT-l increase the mean fitness larger than that of the HGT. We also consider the recombination in the case of smooth fitness landscapes. The recombination gives some advantage in the evolutionary dynamics, where recombination distinguishes clearly the mean-field-like evolutionary factors from the fluctuation-like ones. By contrast, mutations affect the mean-field-like and fluctuation-like factors similarly. Consequently, recombination can accelerate the non-mean-field (fluctuation) type dynamics without considerably affecting the mean-field-like factors.

Latent HIV-1 can be reactivated by cellular superinfection in a Tat-dependent manner, which can lead to the emergence of multidrug-resistant recombinant viruses

The HIV-1 latent reservoir represents an important source of genetic diversity that could contribute to viral evolution and multidrug resistance following latent virus reactivation. This could occur by superinfection of a latently infected cell. We asked whether latent viruses might be reactivated when their host cells are superinfected, and if so, whether they could contribute to the generation of recombinant viruses. Using populations of latently infected Jurkat cells, we found that latent viruses were efficiently reactivated upon superinfection. Pathways leading to latent virus reactivation via superinfection might include gp120-CD4/CXCR4-induced signaling, modulation of the cellular environment by Nef, and/or the activity of Tat produced upon superinfection. Using a range of antiviral compounds and genetic approaches, we show that gp120 and Nef are not required for latent virus reactivation by superinfection, but this process depends on production of functional Tat by the superinfecting virus. In a primary cell model of latency in unstimulated CD4 T cells, superinfection also led to latent virus reactivation. Drug-resistant latent viruses were also reactivated following superinfection in Jurkat cells and were able to undergo recombination with the superinfecting virus. Under drug-selective pressure, this generated multidrug-resistant recombinants that were identified by unique restriction digestion band patterns and by population-level sequencing. During conditions of poor drug adherence, treatment interruption or treatment failure, or in drug-impermeable sanctuary sites, reactivation of latent viruses by superinfection or other means could provide for the emergence or spread of replicatively fit viruses in the face of strong selective pressures.

Pathogenesis and treatment of HIV infection: the cellular, the immune system and the neuroendocrine systems perspective

Infections with HIV represent a great challenge for the development of strategies for an effective cure. The spectrum of diseases associated with HIV ranges from opportunistic infections and cancers to systemic physiological disorders like encephalopathy and neurocognitive impairment. A major progress in controlling HIV infection has been achieved by highly active antiretroviral therapy (HAART). However, HAART does neither eliminate the virus reservoirs in form of latently infected cells nor does it completely reconstitute immune reactivity and physiological status. Furthermore, the failure of the STEP vaccine trial and the only marginal efficacies of the RV144 trial together suggest that the causal relationships between the complex sets of viral and immunological processes that contribute to protection or disease pathogenesis are still poorly understood. Here, we provide an up-to-date overview of HIV-host interactions at the cellular, the immune system and the neuroendocrine systems level. Only by integrating this multi-level knowledge one will be able to handle the systems complexity and develop new methodologies of analysis and prediction for a functional restoration of the immune system and the health of the infected host.

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.

Biological evolution in a multidimensional fitness landscape

We considered a multiblock molecular model of biological evolution, in which fitness is a function of the mean types of alleles located at different parts (blocks) of the genome. We formulated an infinite population model with selection and mutation, and calculated the mean fitness. For the case of recombination, we formulated a model with a multidimensional fitness landscape (the dimension of the space is equal to the number of blocks) and derived a theorem about the dynamics of initially narrow distribution. We also considered the case of lethal mutations. We also formulated the finite population version of the model in the case of lethal mutations. Our models, derived for the virus evolution, are interesting also for the statistical mechanics and the Hamilton-Jacobi equation as well.

Suboptimal provirus expression explains apparent nonrandom cell coinfection with HIV-1

Despite the ability of primate lentiviruses to prevent infected cells from being reinfected, cell coinfection has occurred in the past and has shaped virus evolution by promoting the biogenesis of heterozygous virions and recombination during reverse transcription. In vitro experiments have shown that cell coinfection with HIV is more frequent than would be expected if coinfection were a random process. A possible explanation for this bias is the heterogeneity of target cells and the preferred infection of a subpopulation. To address this question, we compared the frequency of double-positive cells measured following coincubation with green fluorescent protein (GFP) and DsRed HIV reporter viruses with that of stochastic coinfection calculated as the product of the frequencies of GFP- and DsRed-positive cells upon incubation with either reporter virus. Coinfection was more frequent than would be expected on the grounds of stochastic infection, due to the underestimation of single-infection frequencies, which mathematically decreased the calculated frequency. Indeed, when cells were incubated with either reporter virus, a fraction of the cells were scored as uninfected yet harbored a silent provirus that was reactivated upon coinfection through cross talk between viral elements. When such cross talk was avoided, experimental and calculated coinfection frequencies matched, indicating random coinfection. The proportion of infected cells harboring a silent provirus was estimated from coinfection experiments and was shown to be cell type dependent but independent of the virus entry route.

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.

Genetic architecture of HIV-1 genes circulating in north India & their functional implications

This review presents data on genetic and functional analysis of some of the HIV-1 genes derived from HIV-1 infected individuals from north India (Delhi, Punjab and Chandigarh). We found evidence of novel B/C recombinants in HIV-1 LTR region showing relatedness to China/Myanmar with 3 copies of Nfκb sites; B/C/D mosaic genomes for HIV-1 Vpr and novel B/C Tat. We reported appearance of a complex recombinant form CRF_02AG of HIV-1 envelope sequences which is predominantly found in Central/Western Africa. Also one Indian HIV-1 envelope subtype C sequence suggested exclusive CXCR4 co-receptor usage. This extensive recombination, which is observed in about 10 per cent HIV-1 infected individuals in the Vpr genes, resulted in remarkably altered functions when compared with prototype subtype B Vpr. The Vpu C was found to be more potent in causing apoptosis when compared with Vpu B when analyzed for subG1 DNA content. The functional implications of these changes as well as in other genes of HIV-1 are discussed in detail with possible implications for subtype-specific pathogenesis highlighted.

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.

Selection via flatness as a dynamical effect in evolution models with finite population

We investigate the phenomenon of selection via flatness. In the static case, the finiteness of the population does not seriously influence the increase of mean fitness of population due to flatness around a peak. The effect is proportional to 1/square root(L), where L is the genome length. We investigated the two peak model (high peak and a flat peak). We find that the selection of flatness for long genome lengths occurs as a dynamic phenomenon in the case of evolution with small populations. We found that two factors are crucial to define the role of flatness: special initial distribution (the population is located at centers of peaks) allows flat peak to attract more population, and the large value of mutations per population per virus life cycle sometimes also increases the role of flatness. We suggested simple criteria to identify the phenomenon of dynamical arresting of population around flat peak by experiment. We infer that selection via robustness is possible in evolution as a nonequilibrium phenomenon.

The human immunodeficiency virus type 1 Rev protein: ménage à trois during the early phase of the lentiviral replication cycle

The Rev protein of human immunodeficiency viruses (HIV) has long been recognized to be essential for the late phase of the virus replication cycle, due to its strong enhancement of expression of viral structural proteins. Surprisingly, a number of recent papers have demonstrated that Rev can also interfere with integration of the reverse-transcribed cDNA into the host-cell genome. This seems to be due to Rev's binding to integrase and LEDGF/p75, an important cellular cofactor of HIV-1 integration. As Rev is presumably expressed at sufficiently high levels only after the encoding genome has already integrated, the main function of Rev during the early phase might be to reduce genotoxicity due to excessive integration events after superinfection of the same cell by subsequent viruses. Other potential consequences for HIV-1 replication and evolution after co-infection of the same cell with two viruses are discussed.

Different fitnesses for in vivo and in vitro evolutions due to the finite generation-time effect

We consider the finite generation-time effect in virus evolution models, introducing differential equations with delay. The suggested approach more adequately describes the evolution in case of growing populations than the popular models of population genetics, especially for the viruses with large number of offspring during one life cycle. Now the mean fitness, as a coefficient for exponential population growth, could not be defined via instant characteristics of the model. For the constant population size the finite generation-time does not affect mean fitness in the steady state. The growing virus population is characterized by different fitness than the population with a constant size.

Recombination in one- and two-dimensional fitness landscapes

We consider many-site mutation-recombination models of molecular evolution, where fitness is a function of a Hamming distance from one (one-dimensional case) or two (two-dimensional case) sequences. For the one-dimensional case, we calculate the population distribution dynamics for a model with zero fitness and an arbitrary symmetric initial distribution and find an error threshold transition point in the single-peak fitness model for a given initial symmetric distribution. We calculate the recombination period in the case of a single-peak fitness function, when the original population is located at one sequence, at some Hamming distance from the peak configuration. Steady-state fitness is calculated with finite genome length corrections. We derive analytical equations for the two-dimensional mutation-recombination model.

Implications of the nucleocapsid and the microenvironment in retroviral reverse transcription

This mini-review summarizes the process of reverse-transcription, an obligatory step in retrovirus replication during which the retroviral RNA/DNA-dependent DNA polymerase (RT) copies the single-stranded genomic RNA to generate the double-stranded viral DNA while degrading the genomic RNA via its associated RNase H activity. The hybridization of complementary viral sequences by the nucleocapsid protein (NC) receives a special focus, since it acts to chaperone the strand transfers obligatory for synthesis of the complete viral DNA and flanking long terminal repeats (LTR). Since the physiological microenvironment can impact on reverse-transcription, this mini-review also focuses on factors present in the intra-cellular or extra-cellular milieu that can drastically influence both the timing and the activity of reverse-transcription and hence virus infectivity.

Timing the emergence of resistance to anti-HIV drugs with large genetic barriers

New antiretroviral drugs that offer large genetic barriers to resistance, such as the recently approved inhibitors of HIV-1 protease, tipranavir and darunavir, present promising weapons to avert the failure of current therapies for HIV infection. Optimal treatment strategies with the new drugs, however, are yet to be established. A key limitation is the poor understanding of the process by which HIV surmounts large genetic barriers to resistance. Extant models of HIV dynamics are predicated on the predominance of deterministic forces underlying the emergence of resistant genomes. In contrast, stochastic forces may dominate, especially when the genetic barrier is large, and delay the emergence of resistant genomes. We develop a mathematical model of HIV dynamics under the influence of an antiretroviral drug to predict the waiting time for the emergence of genomes that carry the requisite mutations to overcome the genetic barrier of the drug. We apply our model to describe the development of resistance to tipranavir in in vitro serial passage experiments. Model predictions of the times of emergence of different mutant genomes with increasing resistance to tipranavir are in quantitative agreement with experiments, indicating that our model captures the dynamics of the development of resistance to antiretroviral drugs accurately. Further, model predictions provide insights into the influence of underlying evolutionary processes such as recombination on the development of resistance, and suggest guidelines for drug design: drugs that offer large genetic barriers to resistance with resistance sites tightly localized on the viral genome and exhibiting positive epistatic interactions maximally inhibit the emergence of resistant genomes.

HIV drug resistance tendencies in Latvia

The treatment of HIV infection in Latvia by using highly active antiretroviral therapy (HAART) was started in 1996. The prevalence and tendencies of HIV drug resistance among treated and treatment-naive patients in Latvia in the years 2006-2007 were evaluated in this study. Data of HIV genotyping, performed in 132 HIV-1 infected during years 2006-2007 by TRUGENE HIV-1 genotyping assay (BayerHealthCare-diagnostics) are included in the study. Analysis of data showed that in the group of treatment-naive individuals majority carried wild type virus. Prevalence of resistance-associated mutations (RAMs) in the treatment-naive group according to IAS list was 28%. In most cases it was NRTI mutation A62V that is associated with multinucleoside resistance caused by Q151M, its effect in the absence of Q151M is not known. By many authors A62V is supposed to be a result of polymorphism in RT gene and is excluded from the list of resistance mutations. High prevalence of A62V is typical for HIV-1 subtype A. As majority of treatment-naive cases (89%) in this study were with HIV-1 subtypes A or AE, we excluded A62V mutation and estimated RAMs prevalence in group of treatment-naive HIV-infected individuals as 7%. Minor PI mutations were not included in analyses. In Europe published rates generally very between 5% and 15%. In the group of treatment-experienced HIV infected people 25/75 were with HIV-1 subtype B, the rest part--with non-B subtypes: A/AE (35/75), CRF-01AE (7/75), B/AE (4/75) and others. In treatment-experienced patients RAMs prevalence was estimated as 58.6%. Most frequently RAMs were found for nucleoside reverse transcriptase inhibitors (NRTI) (49.3%) followed by non-nucleoside reverse transcriptase inhibitors (NNRTI) (22.6%) and protease inhibitors (PI) (16%). In the group of NRTI mutations M184V (26/75; 34.6%), A62V (12/75; 16.0%) and T215Y (8/75; 10.6%), in NNRTI mutations K103N (10/75; 13.3%), G190S (6/75; 8.0%), in PI group mutations L90M (6/75; 8.0%) and M461/L (6/75; 8.0%) occurred most frequently. The following drug susceptibility was predicted according to the Trugen expert interpretations: in 33/75 (44%) patients no evidence of resistance, in 21/75 (28%) patients resistance to 1 drug class (NRTI--16/75, NNRTI--4/75, PI--1/75), in 17 patients (22.6%) resistance to 2 drug classes (NRTI+NNRTI--9/75, NRTI+PI--7/75, NNRTI+PI--1/75) and in 3/75 (4%) patients resistance to all 3 classes of drugs (NRTI+NNRTI+PI). We conclude, that prevalence of RAMs in treatment-naive HIV infected persons in Latvia is comparable with prevalence in Europe. The origin of predominated mutation A62V associated with NRTI at present is not clear. In more than half of treated HIV infected patients HIV resistance to at least one HAART class was predicted.

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.

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.

Emergence of recombinant forms of HIV: dynamics and scaling

The ability to accelerate the accumulation of favorable combinations of mutations renders recombination a potent force underlying the emergence of forms of HIV that escape multi-drug therapy and specific host immune responses. We present a mathematical model that describes the dynamics of the emergence of recombinant forms of HIV following infection with diverse viral genomes. Mimicking recent in vitro experiments, we consider target cells simultaneously exposed to two distinct, homozygous viral populations and construct dynamical equations that predict the time evolution of populations of uninfected, singly infected, and doubly infected cells, and homozygous, heterozygous, and recombinant viruses. Model predictions capture several recent experimental observations quantitatively and provide insights into the role of recombination in HIV dynamics. From analyses of data from single-round infection experiments with our description of the probability with which recombination accumulates distinct mutations present on the two genomic strands in a virion, we estimate that approximately 8 recombinational strand transfer events occur on average (95% confidence interval: 6-10) during reverse transcription of HIV in T cells. Model predictions of virus and cell dynamics describe the time evolution and the relative prevalence of various infected cell subpopulations following the onset of infection observed experimentally. Remarkably, model predictions are in quantitative agreement with the experimental scaling relationship that the percentage of cells infected with recombinant genomes is proportional to the percentage of cells coinfected with the two genomes employed at the onset of infection. Our model thus presents an accurate description of the influence of recombination on HIV dynamics in vitro. When distinctions between different viral genomes are ignored, our model reduces to the standard model of viral dynamics, which successfully predicts viral load changes in HIV patients undergoing therapy. Our model may thus serve as a useful framework to predict the emergence of multi-drug-resistant forms of HIV in infected individuals.

Modeling Within-Host Evolution of HIV: Mutation, Competition and Strain Replacement

Virus evolution during infection of a single individual is a well-known feature of disease progression in chronic viral diseases. However, the simplest models of virus competition for host resources show the existence of a single dominant strain that grows most rapidly during the initial period of infection and competitively excludes all other virus strains. Here, we examine the dynamics of strain replacement in a simple model that includes a convex trade-off between rapid virus reproduction and long-term host cell survival. Strains are structured according to their within-cell replication rate. Over the course of infection, we find a progression in the dominant strain from fast- to moderately-replicating virus strains featuring distinct jumps in the replication rate of the dominant strain over time. We completely analyze the model and provide estimates for the replication rate of the initial dominant strain and its successors. Our model lays the groundwork for more detailed models of HIV selection and mutation. We outline future directions and application of related models to other biological situations.

Adaptation of HIV-1 depends on the host-cell environment

Many viruses have the ability to rapidly develop resistance against antiviral drugs and escape from the host immune system. To which extent the host environment affects this adaptive potential of viruses is largely unknown. Here we show that for HIV-1, the host-cell environment is key to the adaptive potential of the virus. We performed a large-scale selection experiment with two HIV-1 strains in two different T-cell lines (MT4 and C8166). Over 110 days of culture, both virus strains adapted rapidly to the MT4 T-cell line. In contrast, when cultured on the C8166 T-cell line, the same strains did not show any increase in fitness. By sequence analyses and infections with viruses expressing either yellow or cyan fluorescent protein, we were able to show that the absence of adaptation was linked to a lower recombination rate in the C8166 T-cell line. Our findings suggest that if we can manipulate the host-cellular factors that mediate viral evolution, we may be able to significantly retard viral adaptability.

Influence of sequence identity and unique breakpoints on the frequency of intersubtype HIV-1 recombination

Background

HIV-1 recombination between different subtypes has a major impact on the global epidemic. The generation of these intersubtype recombinants follows a defined set of events starting with dual infection of a host cell, heterodiploid virus production, strand transfers during reverse transcription, and then selection. In this study, recombination frequencies were measured in the C1-C4 regions of the envelope gene in the presence (using a multiple cycle infection system) and absence (in vitro reverse transcription and single cycle infection systems) of selection for replication-competent virus. Ugandan subtypes A and D HIV-1 env sequences (115-A, 120-A, 89-D, 122-D, 126-D) were employed in all three assay systems. These subtypes co-circulate in East Africa and frequently recombine in this human population.

Results

Increased sequence identity between viruses or RNA templates resulted in increased recombination frequencies, with the exception of the 115-A virus or RNA template. Analyses of the recombination breakpoints and mechanistic studies revealed that the presence of a recombination hotspot in the C3/V4 env region, unique to 115-A as donor RNA, could account for the higher recombination frequencies with the 115-A virus/template. Single-cycle infections supported proportionally less recombination than the in vitro reverse transcription assay but both systems still had significantly higher recombination frequencies than observed in the multiple-cycle virus replication system. In the multiple cycle assay, increased replicative fitness of one HIV-1 over the other in a dual infection dramatically decreased recombination frequencies.

Conclusion

Sequence variation at specific sites between HIV-1 isolates can introduce unique recombination hotspots, which increase recombination frequencies and skew the general observation that decreased HIV-1 sequence identity reduces recombination rates. These findings also suggest that the majority of intra- or intersubtype A/D HIV-1 recombinants, generated with each round of infection, are not replication-competent and do not survive in the multiple-cycle system. Ability of one HIV-1 isolate to outgrow the other leads to reduced co-infections, heterozygous virus production, and recombination frequencies.

Stochastic or deterministic: what is the effective population size of HIV-1?

Various studies have attempted to estimate the effective population size of HIV-1 to determine the strength of stochastic effects in within-host evolution. The largely discrepant estimates, the complexity of the concept of the effective population size and the resulting uncertainty about the underlying assumptions make the interpretation of these estimates difficult. Here, we explain the concept and critically assess the current estimates. We discuss the biologically relevant factors that affect the estimate and use of the effective population size. We argue that these factors lead to an underestimation of the effective population size and, thus, to an overestimation of the strength of stochastic effects in HIV-1 evolution.

Lack of correlation between SIV-Nef evolution and rapid disease progression in morphine-dependent nonhuman primate model of AIDS

Six morphine-dependent and two control macaques were infected in an SIV/SHIV nonhuman primate model of AIDS. Three animals in the morphine group rapidly developed clinical disease and died within the timeframe of this study. The sequence evolution of nef in plasma virus was assessed at 4, 12, and 20 weeks postinfection. Cloned sequences were compared phylogenetically against each other as well as against the inoculum virus clones to determine the effect of morphine and rate of disease progression on diversity and divergence, respectively. Unlike our earlier studies of tat and env, nef evolution was not affected by morphine abuse or by rapid disease progression. The results suggest that although the evolution of other loci is inversely correlated to the onset and rate of clinical disease, differential evolution of nef is related neither to drug abuse nor to rapid progression within the first 20 weeks of infection.