Mechanisms of nonrandom human immunodeficiency virus type 1 infection and double infection: preference in virus entry is important but is not the sole factor

Modeling dynamics of acute HIV infection incorporating density-dependent cell death and multiplicity of infection

Understanding the dynamics of acute HIV infection can offer valuable insights into the early stages of viral behavior, potentially helping uncover various aspects of HIV pathogenesis. The standard viral dynamics model explains HIV viral dynamics during acute infection reasonably well. However, the model makes simplifying assumptions, neglecting some aspects of HIV infection. For instance, in the standard model, target cells are infected by a single HIV virion. Yet, cellular multiplicity of infection (MOI) may have considerable effects in pathogenesis and viral evolution. Further, when using the standard model, we take constant infected cell death rates, simplifying the dynamic immune responses. Here, we use four models-1) the standard viral dynamics model, 2) an alternate model incorporating cellular MOI, 3) a model assuming density-dependent death rate of infected cells and 4) a model combining (2) and (3)-to investigate acute infection dynamics in 43 people living with HIV very early after HIV exposure. We find that all models qualitatively describe the data, but none of the tested models is by itself the best to capture different kinds of heterogeneity. Instead, different models describe differing features of the dynamics more accurately. For example, while the standard viral dynamics model may be the most parsimonious across study participants by the corrected Akaike Information Criterion (AICc), we find that viral peaks are better explained by a model allowing for cellular MOI, using a linear regression analysis as analyzed by R2. These results suggest that heterogeneity in within-host viral dynamics cannot be captured by a single model. Depending on the specific aspect of interest, a corresponding model should be employed.

The role of tunneling nanotubes during early stages of HIV infection and reactivation: implications in HIV cure

Tunneling nanotubes (TNTs), also called cytonemes or tumor microtubes, correspond to cellular processes that enable long-range communication. TNTs are plasma membrane extensions that form tubular processes that connect the cytoplasm of two or more cells. TNTs are mostly expressed during the early stages of development and poorly expressed in adulthood. However, in disease conditions such as stroke, cancer, and viral infections such as HIV, TNTs proliferate, but their role is poorly understood. TNTs function has been associated with signaling coordination, organelle sharing, and the transfer of infectious agents such as HIV. Here, we describe the critical role and function of TNTs during HIV infection and reactivation, as well as the use of TNTs for cure strategies.

[Genetic diversity of the human immunodeficiency virus (HIV-1) in the Kaliningrad region]

INTRODUCTION

As is currently known, the epidemic process in the Kaliningrad Region was mainly associated with the spread of the recombinant form of HIV-1 (CRF03_AB); however, regular HIV importations from other countries and continents has created favorable conditions for emergence and spread of various recombinant forms of the virus.The most complete information on the diversity of recombinant forms in the region is also necessary to understand the structure of drug resistance (DR). The aim of the study was to explore the HIV-1 genetic diversity in the Kaliningrad Region.

MATERIALS AND METHODS

We studied 162 blood plasma samples obtained from patients from the Kaliningrad Region, both with confirmed virological failure of antiretroviral therapy (ART) and with newly diagnosed HIV infection. For reverse transcription and amplification of HIV genome fragments, diagnostic «AmpliSense HIVResist-Seq».

RESULTS AND DISCUSSION

The various recombinants between subtypes A and B (74%) were predominant in study group: recombinant was between CRF03_AB and subtype A (33.95%) and CRF03_AB-like (13.58%) were the most common. Among the "pure" subtypes of the virus, subtype A6 (16.67%). The circulation of subtypes B (3.70%) and G (1.23%) was also noted.Ninety-six patients (59.26%) were identified with at least one mutation associated with antiretroviral (ARV) drug resistance.

CONCLUSION

The observed diversity of subtypes and recombinant forms of the virus implies that the new recombinants are actively emerging in the studied region, both between existing recombinant forms and "pure" subtypes, as well as between "pure" subtypes.

Modeling HIV multiple infection

Multiple infection of target cells by human immunodeficiency virus (HIV) may lead to viral escape from host immune responses and drug resistance to antiretroviral therapy, bringing more challenges to the control of infection. The mechanisms underlying HIV multiple infection and their relative contributions are not fully understood. In this paper, we develop and analyze a mathematical model that includes sequential cell-free virus infection (i.e.one virus is transmitted each time in a sequential infection of target cells by virus) and cell-to-cell transmission (i.e.multiple viral genomes are transmitted simultaneously from infected to uninfected cells). By comparing model prediction with the distribution data of proviral genomes in HIV-infected spleen cells, we find that multiple infection can be well explained when the two modes of viral transmission are both included. Numerical simulation using the parameter estimates from data fitting shows that the majority of T cell infections are attributed to cell-to-cell transmission and this transmission mode also accounts for more than half of cell's multiple infections. These results suggest that cell-to-cell transmission plays a critical role in forming HIV multiple infection and thus has important implications for HIV evolution and pathogenesis.

Dynamics of HIV-1 coinfection in different susceptible target cell populations during cell-free infection

HIV-1 mutations rapidly accumulate through genetic recombination events, which require the infection of a single cell by two virions (coinfection). Accumulation of mutations in the viral population may lead to immune escape and high-level drug resistance. The existence of cell subpopulations characterized by different susceptibility to HIV-1 infection has been proposed as an important parameter driving coinfection (Dang et al., 2004). While the mechanism and the quantification of HIV-1 coinfection have been recently investigated by mathematical models, the detailed dynamics of this process during cell-free infection remains elusive. In this study, we constructed ordinary differential equations considering the heterogeneity of target cell populations during cell-free infection in cell culture, and reproduced the cell culture experimental data. Our mathematical analyses showed that the presence of two differently susceptible target cell subpopulations could explain our experimental datasets, while increasing the number of subpopulations did not improve the fitting. In addition, we quantitatively demonstrated that cells infected by multiple viruses mainly accumulated from one cell subpopulation under cell-free infection conditions. In particular, the frequency of infection events in the more susceptible subpopulation was 6.11-higher than that from the other subpopulation, and 98.3% of coinfected cells emerged from the more susceptible subpopulation. Our mathematical-experimental approach is able to extract such a quantitative information, and can be easily applied to other virus infections.

Number of infection events per cell during HIV-1 cell-free infection

HIV-1 accumulates changes in its genome through both recombination and mutation during the course of infection. For recombination to occur, a single cell must be infected by two HIV strains. These coinfection events were experimentally demonstrated to occur more frequently than would be expected for independent infection events and do not follow a random distribution. Previous mathematical modeling approaches demonstrated that differences in target cell susceptibility can explain the non-randomness, both in the context of direct cell-to-cell transmission, and in the context of free virus transmission (Q. Dang et al., Proc. Natl. Acad. Sci. USA 101:632-7, 2004: K. M. Law et al., Cell reports 15:2711-83, 2016). Here, we build on these notions and provide a more detailed and extensive quantitative framework. We developed a novel mathematical model explicitly considering the heterogeneity of target cells and analysed datasets of cell-free HIV-1 single and double infection experiments in cell culture. Particularly, in contrast to the previous studies, we took into account the different susceptibility of the target cells as a continuous distribution. Interestingly, we showed that the number of infection events per cell during cell-free HIV-1 infection follows a negative-binomial distribution, and our model reproduces these datasets.

Cross- and Co-Packaging of Retroviral RNAs and Their Consequences

Retroviruses belong to the family Retroviridae and are ribonucleoprotein (RNP) particles that contain a dimeric RNA genome. Retroviral particle assembly is a complex process, and how the virus is able to recognize and specifically capture the genomic RNA (gRNA) among millions of other cellular and spliced retroviral RNAs has been the subject of extensive investigation over the last two decades. The specificity towards RNA packaging requires higher order interactions of the retroviral gRNA with the structural Gag proteins. Moreover, several retroviruses have been shown to have the ability to cross-/co-package gRNA from other retroviruses, despite little sequence homology. This review will compare the determinants of gRNA encapsidation among different retroviruses, followed by an examination of our current understanding of the interaction between diverse viral genomes and heterologous proteins, leading to their cross-/co-packaging. Retroviruses are well-known serious animal and human pathogens, and such a cross-/co-packaging phenomenon could result in the generation of novel viral variants with unknown pathogenic potential. At the same time, however, an enhanced understanding of the molecular mechanisms involved in these specific interactions makes retroviruses an attractive target for anti-viral drugs, vaccines, and vectors for human gene therapy.

In Vivo HIV-1 Cell-to-Cell Transmission Promotes Multicopy Micro-compartmentalized Infection

HIV-1 infection is enhanced by adhesive structures that form between infected and uninfected T cells called virological synapses (VSs). This mode of transmission results in the frequent co-transmission of multiple copies of HIV-1 across the VS, which can reduce sensitivity to antiretroviral drugs. Studying HIV-1 infection of humanized mice, we measured the frequency of co-transmission and the spatiotemporal organization of infected cells as indicators of cell-to-cell transmission in vivo. When inoculating mice with cells co-infected with two viral genotypes, we observed high levels of co-transmission to target cells. Additionally, micro-anatomical clustering of viral genotypes within lymphoid tissue indicates that viral spread is driven by local processes and not a diffuse viral cloud. Intravital splenic imaging reveals that anchored HIV-infected cells induce arrest of interacting, uninfected CD4(+) T cells to form Env-dependent cell-cell conjugates. These findings suggest that HIV-1 spread between immune cells can be anatomically localized into infectious clusters.

Central memory CD4+ T cells are preferential targets of double infection by HIV-1

Background

Template switching between two distinct HIV-1 RNA genomes during reverse transcription gives rise to recombinant viruses that greatly expand the genetic diversity of HIV-1 and have adverse implications for drug resistance, immune escape, and vaccine design. Virions with two distinct genomes are produced exclusively from cells infected with two or more viruses, or ‘doubly infected’ cells. Previous studies have revealed higher than expected frequencies of doubly infected cells compared to frequencies based on chance alone, suggesting non-random enhancement of double infection.

Methods

We investigated double infection of unstimulated primary CD4+ T cells using reporter viruses carrying genes for different fluorescent proteins, EGFP and mCherry, combined with sophisticated modeling techniques based on Poisson distribution. Additionally, through the use of multiparameter flow cytometry we examined the susceptibility of naïve and memory subsets of CD4+ T cells to double infection by HIV.

Results

Using our double infection system, we confirm non-random enhancement of multiple infection events. Double infection of CD4+ T cells was not found to be a consequence of suboptimal provirus expression rescued by Tat in trans—as has been reported in cell lines—but rather due to a heterogeneous cell population in which only a fraction of primary peripheral blood CD4+ T cells are susceptible to HIV infection regardless of viral titer. Intriguingly, double infection of CD4+ T cells occurred preferentially in memory CD4+ T cells—particularly the central memory (T_CM) subset—but was not a consequence of SAMHD1-mediated restriction of HIV infection in naïve cells.

Conclusions

These findings reveal that double infection in primary CD4+ T cells is primarily a consequences of cellular heterogeneity and not rescue of suboptimal provirus expression by Tat in trans. Additionally, we report a previously unappreciated phenomenon of enhanced double infection within primary T_CM cells and suggest that these long-lived cells may serve as an archive that drive ongoing viral recombination events in vivo.

Improvement of HIV-1 and Human T Cell Lymphotropic Virus Type 1 Replication-Dependent Vectors via Optimization of Reporter Gene Reconstitution and Modification with Intronic Short Hairpin RNA

Cell-to-cell transmission is an efficient mechanism to disseminate human immunodeficiency virus type 1 (HIV-1) and human T cell lymphotropic virus type 1 (HTLV-1). However, it has been challenging to quantify the level of cell-to-cell transmission because the virus-producing cells cannot be easily distinguished from infected target cells. We have previously described replication-dependent vectors that can quantify infection events in cocultured cells. These vectors contain an antisense-oriented promoter and reporter gene interrupted by a sense-oriented intron from the human gamma-globin gene. This strategy prevents expression of the reporter gene in the transfected cells but permits its expression in target cells after infection. However, the gamma-globin intron is not efficiently removed by splicing in the aforementioned vectors, thereby reducing the level of reporter gene expression after transduction into target cells. Here, we used two approaches to improve the replication-dependent vectors. First, we improved the splicing events that remove the gamma-globin intron by optimizing the intron insertion site within the reporter gene. Second, we improved the packaging of the spliced RNA without the gamma-globin intron by targeting the intron-containing RNA via microRNA 30 (miR30)-based short hairpin RNAs. Using two optimized fluorescent reporter vectors and flow cytometry, we determined that multiply HIV-1-infected cells were generated at a higher frequency in coculture than in cell-free infection; furthermore, this increase was dependent upon viruses bearing HIV-1 Env. Compared with previously described vectors, these improved vectors can quantify the infection in lymphocytes and in primary cells with a higher sensitivity and allow the detection and quantitation of multiply infected cells, providing better tools to study retroviral cell-mediated infection.

IMPORTANCE

The human-pathogenic retroviruses HTLV-1 and HIV-1 can be transmitted more efficiently in vivo via direct contact of infected cells with healthy target cells than through cell-free virion-mediated infection. Despite its importance, cell-to-cell transmission has been difficult to quantify because the previously infected cells and the newly infected cells are mixed together in the same culture. In the current study, we generated vectors that are significantly improved over the previously described replication-dependent vectors. As a result, these improved vectors can efficiently detect and quantify cell-to-cell transmission or new infection events in cells in mixed culture. These luciferase- or fluorescence protein-based reporter vectors can be used to quantify and study HIV-1 or HTLV-1 cell-mediated infection in a simple one-step transfection/infection assay.

Modeling multiple infection of cells by viruses: Challenges and insights

The multiple infection of cells with several copies of a given virus has been demonstrated in experimental systems, and has been subject to previous mathematical modeling approaches. Such models, especially those based on ordinary differential equations, can be characterized by difficulties and pitfalls. One such difficulty arises from what we refer to as multiple infection cascades. That is, such models subdivide the infected cell population into sub-populations that are carry i viruses, and each sub-population can in principle always be further infected to contain i + 1 viruses. In order to study the model with numerical simulations, the infection cascade needs to be cut artificially, and this can influence the results. This is shown here in the context of the simplest setting that involves a single, homogeneous virus population. If the viral replication rate is sufficiently fast, then most infected cells will accumulate in the last member of the infection cascade, leading to incorrect numerical results. This can be observed even with relatively long infection cascades, and in this case computational costs associated with a sufficiently long infection cascade can render this approach impractical. We subsequently examine a more complex scenario where two virus types/strains with different fitness are allowed to compete. Again, we find that the length of the infection cascade can have a crucial influence on the results. Competitive exclusion can be observed for shorter infection cascades, while coexistence can be observed for longer infection cascades. More subtly, the length of the infection cascade can influence the equilibrium level of the populations in numerical simulations. Studying the model in a parameter regime where an increase in the infection cascade length does not influence the results, we examine the effect of multiple infection on the outcome of competition. We find that multiple infection can promote coexistence of virus types if there is a degree of intracellular niche separation. If this is not the case, the only outcome is competitive exclusion, similar to equivalent models that do not take into account multiple infection of cells. We further find that multiple infection has a reduced ability to allow coexistence if virus spread is spatially restricted compared to a well-mixed system. These results provide important insights when analyzing and interpreting multiple infection models.

Contribution of HIV-1 genomes that do not integrate to the basic reproductive ratio of the virus

Recent experimental data indicate that HIV-1 DNA that fails to integrate (from now on called uDNA) can by itself successfully produce infectious offspring virions in resting T cells that become activated after infection. This scenario is likely important at the initial stages of the infection. We use mathematical models to calculate the relative contribution of unintegrated and integrated viral DNA to the basic reproductive ratio of the virus, R0, and the models are parameterized with preliminary data. This is done in the context of both free virus spread and transmission of the virus through virological synapses. For free virus transmission, we find that under preliminary parameter estimates, uDNA might contribute about 20% to the total R0. This requires that a single copy of uDNA can successfully replicate. If the presence of more than one uDNA copy is required for replication, uDNA does not contribute to R0. For synaptic transmission, uDNA can contribute to R0 regardless of the number of uDNA copies required for replication. The larger the number of viruses that are successfully transmitted per synapse, however, the lower the contribution of uDNA to R0 because this increases the chances that at least one virus integrates. Using available parameter values, uDNA can maximally contribute 20% to R0 in this case. We argue that the contribution of uDNA to virus reproduction might also be important for continued low level replication of HIV-1 in the presence of integrase inhibitor therapy. Assuming a 20% contribution of uDNA to the overall R0, our calculations suggest that R0=1.6 in the absence of virus integration. While these are rough estimates based on preliminary data that are currently available, this analysis provides a framework for future experimental work which should directly measure key parameters.

Retroviral vectors for analysis of viral mutagenesis and recombination

Retrovirus population diversity within infected hosts is commonly high due in part to elevated rates of replication, mutation, and recombination. This high genetic diversity often complicates the development of effective diagnostics, vaccines, and antiviral drugs. This review highlights the diverse vectors and approaches that have been used to examine mutation and recombination in retroviruses. Retroviral vectors for these purposes can broadly be divided into two categories: those that utilize reporter genes as mutation or recombination targets and those that utilize viral genes as targets of mutation or recombination. Reporter gene vectors greatly facilitate the detection, quantification, and characterization of mutants and/or recombinants, but may not fully recapitulate the patterns of mutagenesis or recombination observed in native viral gene sequences. In contrast, the detection of mutations or recombination events directly in viral genes is more biologically relevant but also typically more challenging and inefficient. We will highlight the advantages and disadvantages of the various vectors and approaches used as well as propose ways in which they could be improved.

Fifteen to twenty percent of HIV substitution mutations are associated with recombination

HIV undergoes high rates of mutation and recombination during reverse transcription, but it is not known whether these events occur independently or are linked mechanistically. Here we used a system of silent marker mutations in HIV and a single round of infection in primary T lymphocytes combined with a high-throughput sequencing and mathematical modeling approach to directly estimate the viral recombination and mutation rates. From >7 million nucleotides (nt) of sequences from HIV infection, we observed 4,801 recombination events and 859 substitution mutations (≈1.51 and 0.12 events per 1,000 nt, respectively). We used experimental controls to account for PCR-induced and transfection-induced recombination and sequencing error. We found that the single-cycle virus-induced mutation rate is 4.6 × 10(-5) mutations per nt after correction. By sorting of our data into recombined and nonrecombined sequences, we found a significantly higher mutation rate in recombined regions (P = 0.003 by Fisher's exact test). We used a permutation approach to eliminate a number of potential confounding factors and confirm that mutation occurs around the site of recombination and is not simply colocated in the genome. By comparing mutation rates in recombined and nonrecombined regions, we found that recombination-associated mutations account for 15 to 20% of all mutations occurring during reverse transcription.

Mathematical models of HIV replication and pathogenesis

This review outlines how mathematical models have been helpful, and continue to be so, for obtaining insights into the in vivo dynamics of HIV infection. The review starts with a discussion of a basic mathematical model that has been frequently used to study HIV dynamics. Some crucial results are described, including the estimation of key parameters that characterize the infection, and the generation of influential theories which argued that in vivo virus evolution is a key player in HIV pathogenesis. Subsequently, more recent concepts are reviewed that have relevance for disease progression, including the multiple infection of cells and the direct cell-to-cell transmission of the virus through the formation of virological synapses. These are important mechanisms that can influence the rate at which HIV spreads through its target cell population, which is tightly linked to the rate at which the disease progresses towards AIDS.

Modeling sequence evolution in HIV-1 infection with recombination

Previously we proposed two simplified models of early HIV-1 evolution. Both showed that under a model of neutral evolution and exponential growth, the mean Hamming distance (HD) between genetic sequences grows linearly with time. In this paper we describe a more realistic continuous-time, age-dependent mathematical model of infection and viral replication, and show through simulations that even in this more complex description, the mean Hamming distance grows linearly with time. This remains unchanged when we introduce recombination, though the confidence intervals of the mean HD obtained ignoring recombination are overly conservative.

HIV-1 reverse transcription

Reverse transcription and integration are the defining features of the Retroviridae; the common name "retrovirus" derives from the fact that these viruses use a virally encoded enzyme, reverse transcriptase (RT), to convert their RNA genomes into DNA. Reverse transcription is an essential step in retroviral replication. This article presents an overview of reverse transcription, briefly describes the structure and function of RT, provides an introduction to some of the cellular and viral factors that can affect reverse transcription, and discusses fidelity and recombination, two processes in which reverse transcription plays an important role. In keeping with the theme of the collection, the emphasis is on HIV-1 and HIV-1 RT.

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.

Increased burst size in multiply infected cells can alter basic virus dynamics

BACKGROUND

The dynamics of viral infections have been studied extensively in a variety of settings, both experimentally and with mathematical models. The majority of mathematical models assumes that only one virus can infect a given cell at a time. It is, however, clear that especially in the context of high viral load, cells can become infected with multiple copies of a virus, a process called coinfection. This has been best demonstrated experimentally for human immunodeficiency virus (HIV), although it is thought to be equally relevant for a number of other viral infections. In a previously explored mathematical model, the viral output from an infected cell does not depend on the number of viruses that reside in the cell, i.e. viral replication is limited by cellular rather than viral factors. In this case, basic virus dynamics properties are not altered by coinfection.

RESULTS

Here, we explore the alternative assumption that multiply infected cells are characterized by an increased burst size and find that this can fundamentally alter model predictions. Under this scenario, establishment of infection may not be solely determined by the basic reproductive ratio of the virus, but can depend on the initial virus load. Upon infection, the virus population need not follow straight exponential growth. Instead, the exponential rate of growth can increase over time as virus load becomes larger. Moreover, the model suggests that the ability of anti-viral drugs to suppress the virus population can depend on the virus load upon initiation of therapy. This is because more coinfected cells, which produce more virus, are present at higher virus loads. Hence, the degree of drug resistance is not only determined by the viral genotype, but also by the prevalence of coinfected cells.

CONCLUSIONS

Our work shows how an increased burst size in multiply infected cells can alter basic infection dynamics. This forms the basis for future experimental testing of model assumptions and predictions that can distinguish between the different scenarios.

Stable multi-infection of splenocytes during SIV infection--the basis for continuous recombination

Background

Recombination is an important mechanism in the generation of genetic diversity of the human (HIV) and simian (SIV) immunodeficiency viruses. It requires the co-packaging of divergent RNA genomes into the same retroviral capsid and subsequent template switching during the reverse transcription reaction. By HIV-specific fluorescence in situ hybridization (FISH), we have previously shown that the splenocytes from 2 chronically infected patients with Castelman's disease were multi-infected and thus fulfill the in vivo requirements to generate genetic diversity by recombination. In order to analyze when multi-infection first occurs during a lentivirus infection and how the distribution of multi-infection evolves during the disease course, we now determined the SIV copy numbers from splenocytes of 11 SIVmac251-infected rhesus macaques cross-sectionally covering the time span of primary infection throughout to end-stage immunodeficiency.

Results

SIV multi-infection of single splenocytes was readily detected in all monkeys and all stages of the infection. Single-infected cells were more frequent than double- or triple- infected cells. There was no strong trend linking the copy number distribution to plasma viral load, disease stage, or CD4 cell counts.

Conclusions

SIV multi-infection of single cells is already established during the primary infection phase thus enabling recombination to affect viral evolution in vivo throughout the disease course.

Mechanisms and factors that influence high frequency retroviral recombination

With constantly changing environmental selection pressures, retroviruses rely upon recombination to reassort polymorphisms in their genomes and increase genetic diversity, which improves the chances for the survival of their population. Recombination occurs during DNA synthesis, whereby reverse transcriptase undergoes template switching events between the two copackaged RNAs, resulting in a viral recombinant with portions of the genetic information from each parental RNA. This review summarizes our current understanding of the factors and mechanisms influencing retroviral recombination, fidelity of the recombination process, and evaluates the subsequent viral diversity and fitness of the progeny recombinant. Specifically, the high mutation rates and high recombination frequencies of HIV-1 will be analyzed for their roles in influencing HIV-1 global diversity, as well as HIV-1 diagnosis, drug treatment, and vaccine development.

Effect of multiple infection of cells on the evolutionary dynamics of HIV in vivo: implications for host adaptation mechanisms

The dynamics between human immunodeficiency virus type 1 and the immune system have been studied both experimentally and mathematically, exploring aspects of host adaptation and viral mechanisms to escape host control. The majority of this work, however, has been performed assuming that any cell can only be infected by one copy of the virus. In recent years, it has become clear that multiple copies of the virus can infect the same cell, a process we refer to as co-infection. Here, we review this topic and discuss how immune control of the infection and the ability of the virus to escape immune control is affected by co-infection.

Majority of CD4+ T cells from peripheral blood of HIV-1-infected individuals contain only one HIV DNA molecule

Neither the number of HIV-1 proviruses within individual infected cells in HIV-1-infected patients nor their genetic relatedness within individual infected cells and between cells and plasma virus are well defined. To address these issues we developed a technique to quantify and genetically characterize HIV-1 DNA from single infected cells in vivo. Analysis of peripheral blood CD4(+) T cells from nine patients revealed that the majority of infected cells contain only one copy of HIV-1 DNA, implying a limited potential for recombination in virus produced by these cells. The genetic similarity between HIV populations in CD4(+) T cells and plasma implies ongoing exchange between these compartments both early and late after infection.

Multiploid inheritance of HIV-1 during cell-to-cell infection

During cell-to-cell transmission of human immunodeficiency virus type 1 (HIV-1), many viral particles can be simultaneously transferred from infected to uninfected CD4 T cells through structures called virological synapses (VS). Here we directly examine how cell-free and cell-to-cell infections differ from infections initiated with cell-free virus in the number of genetic copies that are transmitted from one generation to the next, i.e., the genetic inheritance. Following exposure to HIV-1-expressing cells, we show that target cells with high viral uptake are much more likely to become infected. Using T cells that coexpress distinct fluorescent HIV-1 variants, we show that multiple copies of HIV-1 can be cotransmitted across a single VS. In contrast to cell-free HIV-1 infection, which titrates with Poisson statistics, the titration of cell-associated HIV-1 to low rates of overall infection generates a constant fraction of the newly infected cells that are cofluorescent. Triple infection was also readily detected when cells expressing three fluorescent viruses were used as donor cells. A computational model and a statistical model are presented to estimate the degree to which cofluorescence underestimates coinfection frequency. Lastly, direct detection of HIV-1 proviruses using fluorescence in situ hybridization confirmed that significantly more HIV-1 DNA copies are found in primary T cells infected with cell-associated virus than in those infected with cell-free virus. Together, the data suggest that multiploid inheritance is common during cell-to-cell HIV-1 infection. From this study, we suggest that cell-to-cell infection may explain the high copy numbers of proviruses found in infected cells in vivo and may provide a mechanism through which HIV preserves sequence heterogeneity in viral quasispecies through genetic complementation.

Evolutionary game theoretic strategy for optimal drug delivery to influence selection pressure in treatment of HIV-1

Cytotoxic T-lymphocyte (CTL) escape mutation is associated with long-term behaviors of human immunodeficiency virus type 1 (HIV-1). Recent studies indicate heterogeneous behaviors of reversible and conservative mutants while the selection pressure changes. The purpose of this study is to optimize the selection pressure to minimize the long-term virus load. The results can be used to assist in delivery of highly loaded cognate peptide-pulsed dendritic cells (DC) into lymph nodes that could change the selection pressure. This mechanism may be employed for controlled drug delivery. A mathematical model is proposed in this paper to describe the evolutionary dynamics involving viruses and T cells. We formulate the optimization problem into the framework of evolutionary game theory, and solve for the optimal control of the selection pressure as a neighborhood invader strategy. The strategy dynamics can be obtained to evolve the immune system to the best controlled state. The study may shed light on optimal design of HIV-1 therapy based on optimization of adaptive CTL immune response.

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.

Effect of different modes of viral spread on the dynamics of multiply infected cells in human immunodeficiency virus infection

Infection of individual cells with more than one HIV particle is an important feature of HIV replication, which may contribute to HIV pathogenesis via the occurrence of recombination, viral complementation and other outcomes that influence HIV replication and evolutionary dynamics. A previous mathematical model of co-infection has shown that the number of cells infected with i viruses correlates with the ith power of the singly infected cell population, and this has partly been observed in experiments. This model, however, assumed that virus spread from cell to cell occurs only via free virus particles, and that viruses and cells mix perfectly. Here, we introduce a cellular automaton model that takes into account different modes of virus spread among cells, including cell to cell transmission via the virological synapse, and spatially constrained virus spread. In these scenarios, it is found that the number of multiply infected cells correlates linearly with the number of singly infected cells, meaning that co-infection plays a greater role at lower virus loads. The model further indicates that current experimental systems that are used to study co-infection dynamics fail to reflect the true dynamics of multiply infected cells under these specific assumptions, and that new experimental techniques need to be designed to distinguish between the different assumptions.

Accurately measuring recombination between closely related HIV-1 genomes

Retroviral recombination is thought to play an important role in the generation of immune escape and multiple drug resistance by shuffling pre-existing mutations in the viral population. Current estimates of HIV-1 recombination rates are derived from measurements within reporter gene sequences or genetically divergent HIV sequences. These measurements do not mimic the recombination occurring in vivo, between closely related genomes. Additionally, the methods used to measure recombination make a variety of assumptions about the underlying process, and often fail to account adequately for issues such as co-infection of cells or the possibility of multiple template switches between recombination sites. We have developed a HIV-1 marker system by making a small number of codon modifications in gag which allow recombination to be measured over various lengths between closely related viral genomes. We have developed statistical tools to measure recombination rates that can compensate for the possibility of multiple template switches. Our results show that when multiple template switches are ignored the error is substantial, particularly when recombination rates are high, or the genomic distance is large. We demonstrate that this system is applicable to other studies to accurately measure the recombination rate and show that recombination does not occur randomly within the HIV genome.

Monitoring of drug resistance in therapy-naïve HIV infected patients and detection of African HIV subtypes in Hungary

Mutations in the HIV-1 pol gene associated with resistance to antiretroviral drugs in therapy-naïve Hungarian individuals transmitted as primary infection by their foreign sexual partners originated from African, Asian and other European countries had been analyzed. Drug resistance genotyping of HIV RT and PR genes were performed where mutations of 72 codons - among them 64 specific resistance codons representing 6 nucleoside reverse transcriptase inhibitor (NRTIs), 2 non-nucleoside reverse transcriptase inhibitor (NNRTIs) and 6 proteinase inhibitor (PRIs) drugs - had been analyzed by Truegene HIV-1 Genotyping kit and OpenGene Sequencing System. Viral variants harboring resistance mutations in the po l gene were detected in 14% of the subjects. The highest rate of resistance to a single class of inhibitors was detected towards PR inhibitors (12%), followed by NRTI (8%) and NNRTI (5%). On the contrary, 25% of viruses transmitted by homosexual activity contained mutations led to resistance to NNRT. Viruses from 11 percent of cases were resistant to 2 classes of inhibitors, and 7 percent to three classes of inhibitors. Based upon sequence data non-B subtypes and CRFs were detected in more than 71% of cases. HIV-1 C (10.7%), HIV-F1 (7.2%) and HIV-1 G (3.6%) were detected as the more frequent subtypes. Among the HIV-1 recombinant viruses CRF02_AG variants were found more frequently (28.5%) followed by CRF06_cpx (17.8%) indicating penetration of non-B subtypes and recombinant African variants into Hungary, which raises serious clinical and public health consequences.

The remarkable frequency of human immunodeficiency virus type 1 genetic recombination

The genetic diversity of human immunodeficiency virus type 1 (HIV-1) results from a combination of point mutations and genetic recombination, and rates of both processes are unusually high. This review focuses on the mechanisms and outcomes of HIV-1 genetic recombination and on the parameters that make recombination so remarkably frequent. Experimental work has demonstrated that the process that leads to recombination--a copy choice mechanism involving the migration of reverse transcriptase between viral RNA templates--occurs several times on average during every round of HIV-1 DNA synthesis. Key biological factors that lead to high recombination rates for all retroviruses are the recombination-prone nature of their reverse transcription machinery and their pseudodiploid RNA genomes. However, HIV-1 genes recombine even more frequently than do those of many other retroviruses. This reflects the way in which HIV-1 selects genomic RNAs for coencapsidation as well as cell-to-cell transmission properties that lead to unusually frequent associations between distinct viral genotypes. HIV-1 faces strong and changeable selective conditions during replication within patients. The mode of HIV-1 persistence as integrated proviruses and strong selection for defective proviruses in vivo provide conditions for archiving alleles, which can be resuscitated years after initial provirus establishment. Recombination can facilitate drug resistance and may allow superinfecting HIV-1 strains to evade preexisting immune responses, thus adding to challenges in vaccine development. These properties converge to provide HIV-1 with the means, motive, and opportunity to recombine its genetic material at an unprecedented high rate and to allow genetic recombination to serve as one of the highest barriers to HIV-1 eradication.

Superinfection with a heterologous HIV strain per se does not lead to faster progression

BACKGROUND

It has been suggested that superinfection of HIV positive individuals with heterologous HIV strains could lead to faster progression to AIDS, generating concern over the risks of exposure to new infections in those already infected.

METHODS

A mathematical model of the within-host dynamics of two sequential infections with strains of HIV describing activation and infection of immune cells was developed. Multiple stochastic realizations describing progression to AIDS in the individual were generated, comparing the situation with and without superinfection.

RESULTS

It was found that the susceptibility of immune cells to dual infection is crucial to the outcome of HIV superinfection. A low susceptibility leads to competitive exclusion between the strains and a high susceptibility may lead to co-existence if the superinfecting strain is sufficiently fit. It was also found that only superinfection with a fitter strain leads to faster progression to AIDS, rather than superinfection per se.

CONCLUSION

In theory, a superinfection event with a heterologous strain of HIV does not lead to faster progression to AIDS. Unless superinfection allows the spread of fitter virus, it should not be of concern for public health.

Serial evolutionary networks of within-patient HIV-1 sequences reveal patterns of evolution of X4 strains

Background

The HIV virus is known for its ability to exploit numerous genetic and evolutionary mechanisms to ensure its proliferation, among them, high replication, mutation and recombination rates. Sliding MinPD, a recently introduced computational method [1], was used to investigate the patterns of evolution of serially-sampled HIV-1 sequence data from eight patients with a special focus on the emergence of X4 strains. Unlike other phylogenetic methods, Sliding MinPD combines distance-based inference with a nonparametric bootstrap procedure and automated recombination detection to reconstruct the evolutionary history of longitudinal sequence data. We present serial evolutionary networks as a longitudinal representation of the mutational pathways of a viral population in a within-host environment. The longitudinal representation of the evolutionary networks was complemented with charts of clinical markers to facilitate correlation analysis between pertinent clinical information and the evolutionary relationships.

Results

Analysis based on the predicted networks suggests the following:: significantly stronger recombination signals (p = 0.003) for the inferred ancestors of the X4 strains, recombination events between different lineages and recombination events between putative reservoir virus and those from a later population, an early star-like topology observed for four of the patients who died of AIDS. A significantly higher number of recombinants were predicted at sampling points that corresponded to peaks in the viral load levels (p = 0.0042).

Conclusion

Our results indicate that serial evolutionary networks of HIV sequences enable systematic statistical analysis of the implicit relations embedded in the topology of the structure and can greatly facilitate identification of patterns of evolution that can lead to specific hypotheses and new insights. The conclusions of applying our method to empirical HIV data support the conventional wisdom of the new generation HIV treatments, that in order to keep the virus in check, viral loads need to be suppressed to almost undetectable levels.

Multiple HIV-1 infection of cells and the evolutionary dynamics of cytotoxic T lymphocyte escape mutants

Cytotoxic T lymphocytes (CTL) are an important branch of the immune system, killing virus-infected cells. Many viruses can mutate so that infected cells are not killed by CTL anymore. This escape can contribute to virus persistence and disease. A prominent example is HIV-1. The evolutionary dynamics of CTL escape mutants in vivo have been studied experimentally and mathematically, assuming that a cell can only be infected with one HIV particle at a time. However, according to data, multiple virus particles frequently infect the same cell, a process called coinfection. Here, we study the evolutionary dynamics of CTL escape mutants in the context of coinfection. A mathematical model suggests that an intermediate strength of the CTL response against the wild-type is most detrimental for an escape mutant, minimizing overall virus load and even leading to its extinction. A weaker or, paradoxically, stronger CTL response against the wild-type both lead to the persistence of the escape mutant and higher virus load. It is hypothesized that an intermediate strength of the CTL response, and thus the suboptimal virus suppression observed in HIV-1 infection, might be adaptive to minimize the impact of existing CTL escape mutants on overall virus load.

Coinfection rates in Φ6 bacteriophage are enhanced by virus-induced changes in host cells

Two or more viruses infecting the same host cell can interact in ways that profoundly affect disease dynamics and control, yet the factors determining coinfection rates are incompletely understood. Previous studies have focused on the mechanisms that viruses use to suppress coinfection, but recently the phenomenon of enhanced coinfection has also been documented. In the experiments described here, we explore the hypothesis that enhanced coinfection rates in the bacteriophage Φ6 are achieved by virus-induced upregulation of the Φ6 receptor, which is the bacterial pilus. First, we confirmed that coinfection enhancement in Φ6 is virus-mediated by showing that Φ6 attaches significantly faster to infected cells than to uninfected cells. Second, we explored the hypothesis that coinfection enhancement in Φ6 depends upon changes in the expression of an inducible receptor. Consistent with this hypothesis, the closely related phage, Φ12, that uses constitutively expressed lipopolysaccharide as its receptor, attaches to infected and uninfected cells at the same rate. Our results, along with the previous finding that coinfection in Φ6 is limited to two virions, suggest that viruses may closely regulate rates of coinfection through mechanisms for both coinfection enhancement and exclusion.

Emergence of antiretroviral drug resistance in therapy-naive HIV infected patients in Hungary

Mutations in the HIV-1 genes associated with resistance to antiretroviral drugs were detected also in primary HIV infected individuals who did not receive antiretroviral treatment. Drug resistance genotyping of HIV pol gene was done by in situ DNA hybridization using a Line Probe Assay and by direct sequencing. Viral variants harbouring resistance mutations such as: M41, T69R, K70R, M184V, T215Y in the pol gene were detected in 14% of the subjects. HIV mutants resistant to NRT inhibitors were found in 10 and 20% of patients infected before and after the year 2000, respectively. Multiple drug resistant viruses (2-3 drug classes) were present in 3.5% of the mainly recently infected patients. In protease gene only minor resistant mutations were found such as L101 and A71V. These findings indicate the evolution of drug resistance showing a correlation with the time of introduction of combination therapy in our country, where more than 70% of HIV infections were by homo/bisexual transmission. This confirms the transmission of drug-resistant HIV shown by genotype testing during primary infection in therapy-naive patients and initiates serious clinical and public health consequences.

Modeling and estimation of kinetic parameters and replicative fitness of HIV-1 from flow-cytometry-based growth competition experiments

Growth competition assays have been developed to quantify the relative fitness of HIV-1 mutants. In this article, we develop mathematical models to describe viral/cellular dynamic interactions in the assay system from which the competitive fitness indices or parameters are defined. In our previous HIV-viral fitness experiments, the concentration of uninfected target cells was assumed to be constant (Wu et al. 2006). But this may not be true in some experiments. In addition, dual infection may frequently occur in viral fitness experiments and may not be ignorable. Here, we relax these two assumptions and extend our earlier viral fitness model (Wu et al. 2006). The resulting models then become nonlinear ODE systems for which closed-form solutions are not achievable. In the new model, the viral relative fitness is a function of time since it depends on the target cell concentration. First, we studied the structure identifiability of the nonlinear ODE models. The identifiability analysis showed that all parameters in the proposed models are identifiable from the flow-cytometry-based experimental data that we collected. We then employed a global optimization approach (the differential evolution algorithm) to directly estimate the kinetic parameters as well as the relative fitness index in the nonlinear ODE models using nonlinear least square regression based on the experimental data. Practical identifiability was investigated via Monte Carlo simulations.

Viral complementation allows HIV-1 replication without integration

BACKGROUND

The integration of HIV-1 DNA into cellular chromatin is required for high levels of viral gene expression and for the production of new virions. However, the majority of HIV-1 DNA remains unintegrated and is generally considered a replicative dead-end. A limited amount of early gene expression from unintegrated DNA has been reported, but viral replication does not proceed further in cells which contain only unintegrated DNA. Multiple infection of cells is common, and cells that are productively infected with an integrated provirus frequently also contain unintegrated HIV-1 DNA. Here we examine the influence of an integrated provirus on unintegrated HIV-1 DNA (uDNA).

RESULTS

We employed reporter viruses and quantitative real time PCR to examine gene expression and virus replication during coinfection with integrating and non-integrating HIV-1. Most cells which contained only uDNA displayed no detected expression from fluorescent reporter genes inserted into early (Rev-independent) and late (Rev-dependent) locations in the HIV-1 genome. Coinfection with an integrated provirus resulted in a several fold increase in the number of cells displaying uDNA early gene expression and efficiently drove uDNA into late gene expression. We found that coinfection generates virions which package and deliver uDNA-derived genomes into cells; in this way uDNA completes its replication cycle by viral complementation. uDNA-derived genomes undergo recombination with the integrated provirus-derived genomes during second round infection.

CONCLUSION

This novel mode of retroviral replication allows survival of viruses which would otherwise be lost because of a failure to integrate, amplifies the effective amount of cellular coinfection, increases the replicating HIV-1 gene pool, and enhances the opportunity for diversification through errors of polymerization and recombination.

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.

Immunity and protection by live attenuated HIV/SIV vaccines

Live attenuated virus vaccines have shown the greatest potential to protect against simian immunodeficiency virus (SIV) infection, a model for human immunodeficiency virus (HIV). Immunity against the vaccine virus is thought to mediate protection. However, it is shown computationally that the opposite might be true. According to the model, the initial growth of the challenge strain, its peak load, and its potential to be pathogenic is higher if immunity against the vaccine virus is stronger. This is because the initial growth of the challenge strain is mainly determined by virus competition rather than immune suppression. The stronger the immunity against the vaccine strain, the weaker its competitive ability relative to the challenge strain, and the lower the level of protection. If the vaccine virus does protect the host against a challenge, it is because the competitive interactions between the viruses inhibit the initial growth of the challenge strain. According to these arguments, an inverse correlation between the level of attenuation and the level of protection is expected, and this has indeed been observed in experimental data.

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.

Human immunodeficiency virus evolution towards reduced replicative fitness in vivo and the development of AIDS

Human immunodeficiency virus (HIV) infection progresses to AIDS following an asymptomatic period during which the virus is thought to evolve towards increased fitness and pathogenicity. We show mathematically that progression to the strongest HIV-induced pathology requires evolution of the virus towards reduced replicative fitness in vivo. This counter-intuitive outcome can happen if multiple viruses co-infect the same cell frequently, which has been shown to occur in recent experiments. According to our model, in the absence of frequent co-infection, the less fit AIDS-inducing strains might never emerge. The frequency of co-infection can correlate with virus load, which in turn is determined by immune responses. Thus, at the beginning of infection when immunity is strong and virus load is low, co-infection is rare and pathogenic virus variants with reduced replicative fitness go extinct. At later stages of infection when immunity is less efficient and virus load is higher, co-infection occurs more frequently and pathogenic virus variants with reduced replicative fitness can emerge, resulting in T-cell depletion. In support of these notions, recent data indicate that pathogenic simian immunodeficiency virus (SIV) strains occurring late in the infection are less fit in specific in vitro experiments than those isolated at earlier stages. If co-infection is blocked, the model predicts the absence of any disease even if virus loads are high. We hypothesize that non-pathogenic SIV infection within its natural hosts, which is characterized by the absence of disease even in the presence of high virus loads, could be explained by a reduced occurrence of co-infection in this system.

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.