The role of recombination for the coevolutionary dynamics of HIV and the immune response

The evolutionary implications of recombination in HIV remain not fully understood. A plausible effect could be an enhancement of immune escape from cytotoxic T lymphocytes (CTLs). In order to test this hypothesis, we constructed a population dynamic model of immune escape in HIV and examined the viral-immune dynamics with and without recombination. Our model shows that recombination (i) increases the genetic diversity of the viral population, (ii) accelerates the emergence of escape mutations with and without compensatory mutations, and (iii) accelerates the acquisition of immune escape mutations in the early stage of viral infection. We see a particularly strong impact of recombination in systems with broad, non-immunodominant CTL responses. Overall, our study argues for the importance of recombination in HIV in allowing the virus to adapt to changing selective pressures as imposed by the immune system and shows that the effect of recombination depends on the immunodominance pattern of effector T cell responses.     

A coalescent-based method for detecting and estimating recombination from gene sequences

Determining the amount of recombination in the genealogical history of a sample of genes is important to both evolutionary biology and medical population genetics. However, recurrent mutation can produce patterns of genetic diversity similar to those generated by recombination and can bias estimates of the population recombination rate. Hudson 2001 has suggested an approximate-likelihood method based on coalescent theory to estimate the population recombination rate, 4N(e)r, under an infinite-sites model of sequence evolution. Here we extend the method to the estimation of the recombination rate in genomes, such as those of many viruses and bacteria, where the rate of recurrent mutation is high. In addition, we develop a powerful permutation-based method for detecting recombination that is both more powerful than other permutation-based methods and robust to misspecification of the model of sequence evolution. We apply the method to sequence data from viruses, bacteria, and human mitochondrial DNA. The extremely high level of recombination detected in both HIV1 and HIV2 sequences demonstrates that recombination cannot be ignored in the analysis of viral population genetic data.     

Recombination Rate and Selection Strength in HIV Intra-patient Evolution

The evolutionary dynamics of HIV during the chronic phase of infection is driven by the host immune response and by selective pressures exerted through drug treatment. To understand and model the evolution of HIV quantitatively, the parameters governing genetic diversification and the strength of selection need to be known. While mutation rates can be measured in single replication cycles, the relevant effective recombination rate depends on the probability of coinfection of a cell with more than one virus and can only be inferred from population data. However, most population genetic estimators for recombination rates assume absence of selection and are hence of limited applicability to HIV, since positive and purifying selection are important in HIV evolution. Yet, little is known about the distribution of selection differentials between individual viruses and the impact of single polymorphisms on viral fitness. Here, we estimate the rate of recombination and the distribution of selection coefficients from time series sequence data tracking the evolution of HIV within single patients. By examining temporal changes in the genetic composition of the population, we estimate the effective recombination to be ρ = 1.4±0.6×10⁻⁵ recombinations per site and generation. Furthermore, we provide evidence that the selection coefficients of at least 15% of the observed non-synonymous polymorphisms exceed 0.8% per generation. These results provide a basis for a more detailed understanding of the evolution of HIV. A particularly interesting case is evolution in response to drug treatment, where recombination can facilitate the rapid acquisition of multiple resistance mutations. With the methods developed here, more precise and more detailed studies will be possible as soon as data with higher time resolution and greater sample sizes are available.     

The origin and diversity of the HIV-1 pandemic

This review examines the enormous progress that has been made in the past decade in understanding the origin of HIV, HIV genetic variability, and the impact of global HIV diversity on the pandemic. Multiple zoonotic transmissions of simian immunodeficiency virus (SIV) have resulted in different HIV lineages in humans. In addition, the high mutation and recombination rates during viral replication result in a great genetic variability of HIV within individuals, as well as within populations, upon which evolutionary selection pressures act. The global HIV pandemic is examined in the context of HIV evolution, and the global diversity of HIV subtypes and recombinants is discussed in detail. Finally, the impact of HIV diversity on pathogenesis, transmission, diagnosis, treatment, the immune response, and vaccine development is reviewed.     

Recombination in HIV and the evolution of drug resistance: for better or for worse?

The rapid evolution of drug resistance remains a major obstacle for HIV therapy. The capacity of the virus for recombination is widely believed to facilitate the evolution of drug resistance. Here, we challenge this intuitive view. We develop a population genetic model of HIV replication that incorporates the processes of mutation, cellular superinfection, and recombination. We show that cellular superinfection increases the abundance of low fitness viruses at the expense of the fittest strains due to the mixing of viral proteins during virion assembly. Moreover, we argue that whether recombination facilitates the evolution of drug resistance depends critically on how resistance mutations interact to determine viral fitness. Contrary to the commonly held belief, we find that, under the most plausible biological assumptions, recombination is expected to slow down the rate of evolution of multi-drug-resistant virus during therapy.     

Homologous recombination between human immunodeficiency viral DNAs in cultured human cells: analysis of the factors influencing recombination

Recombination between HIV DNAs was analyzed using DNA transfection in cell cultures and the optimal conditions for efficient recombination were determined. Recombinant plasmid DNA substrates were constructed from HIV proviral DNAs and the success of recombination was measured by the production of viable hybrid virus. The process of recombination between HIV DNAs was shown to be i) dependent on homology between the truncated HIV DNAs and ii) maximum with concentrations of the truncated DNAs 3ug and above. HIV isolates with heterogeneity in their primary sequence, thus offer an ideal system for the analysis of the requirement of homologous recombination. In addition, recombination methodology would be useful for generating hybrid HIVs for the analysis of specific viral gene functions.     

Stochastic interplay between mutation and recombination during the acquisition of drug resistance mutations in human immunodeficiency virus type 1

The emergence of drug resistance mutations in human immunodeficiency virus (HIV) has been a major setback in the treatment of infected patients. Besides the high mutation rate, recombination has been conjectured to have an important impact on the emergence of drug resistance. Population genetic theory suggests that in populations limited in size recombination may facilitate the acquisition of beneficial mutations. The viral population in an infected patient may indeed represent such a population limited in size, since current estimates of the effective population size range from 500 to 10(5). To address the effects of limited population size, we therefore expand a previously described deterministic population genetic model of HIV replication by incorporating the stochastic processes that occur in finite populations of infected cells. Using parameter estimates from the literature, we simulate the evolution of drug-resistant viral strains. The simulations show that recombination has only a minor effect on the rate of acquisition of drug resistance mutations in populations with effective population sizes as small as 1,000, since in these populations, viral strains typically fix beneficial mutations sequentially. However, for intermediate effective population sizes (10(4) to 10(5)), recombination can accelerate the evolution of drug resistance by up to 25%. Furthermore, a reduction in population size caused by drug therapy can be overcome by a higher viral mutation rate, leading to a faster evolution of drug resistance.     

Molecular Mechanisms of Recombination Restriction in the Envelope Gene of the Human Immunodeficiency Virus

The ability of pathogens to escape the host''s immune response is crucial for the establishment of persistent infections and can influence virulence. Recombination has been observed to contribute to this process by generating novel genetic variants. Although distinctive recombination patterns have been described in many viral pathogens, little is known about the influence of biases in the recombination process itself relative to selective forces acting on newly formed recombinants. Understanding these influences is important for determining how recombination contributes to pathogen genome and proteome evolution. Most previous research on recombination-driven protein evolution has focused on relatively simple proteins, usually in the context of directed evolution experiments. Here, we study recombination in the envelope gene of HIV-1 between primary isolates belonging to subtypes that recombine naturally in the HIV/AIDS pandemic. By characterizing the early steps in the generation of recombinants, we provide novel insights into the evolutionary forces that shape recombination patterns within viral populations. Specifically, we show that the combined effects of mechanistic processes that determine the locations of recombination breakpoints across the HIV-1 envelope gene, and purifying selection acting against dysfunctional recombinants, can explain almost the entire distribution of breakpoints found within this gene in nature. These constraints account for the surprising paucity of recombination breakpoints found in infected individuals within this highly variable gene. Thus, the apparent randomness of HIV evolution via recombination may in fact be relatively more predictable than anticipated. In addition, the dominance of purifying selection in localized areas of the HIV genome defines regions where functional constraints on recombinants appear particularly strong, pointing to vulnerable aspects of HIV biology.     

RNA structures facilitate recombination-mediated gene swapping in HIV-1

Many viruses, including retroviruses, undergo frequent recombination, a process which can increase their rate of adaptive evolution. In the case of HIV, recombination has been responsible for the generation of numerous intersubtype recombinant variants with epidemiological importance in the AIDS pandemic. Although it is known that fragments of genetic material do not combine randomly during the generation of recombinant viruses, the mechanisms that lead to preferential recombination at specific sites are not fully understood. Here we reanalyze recent independent data defining (i) the structure of a complete HIV-1 RNA genome and (ii) favorable sites for recombination. We show that in the absence of selection acting on recombinant genomes, regions harboring RNA structures in the NL4-3 model strain are strongly predictive of recombination breakpoints in the HIV-1 env genes of primary isolates. In addition, we found that breakpoints within recombinant HIV-1 genomes sampled from human populations, which have been acted upon extensively by natural selection, also colocalize with RNA structures. Critically, junctions between genes are enriched in structured RNA elements and are also preferred sites for generating functional recombinant forms. These data suggest that RNA structure-mediated recombination allows the virus to exchange intact genes rather than arbitrary subgene fragments, which is likely to increase the overall viability and replication success of the recombinant HIV progeny.     

The clarifying role of time series data in the population genetics of HIV

HIV can evolve remarkably quickly in response to antiretroviral therapies and the immune system. This evolution stymies treatment effectiveness and prevents the development of an HIV vaccine. Consequently, there has been a great interest in using population genetics to disentangle the forces that govern the HIV adaptive landscape (selection, drift, mutation, and recombination). Traditional population genetics approaches look at the current state of genetic variation and infer the processes that can generate it. However, because HIV evolves rapidly, we can also sample populations repeatedly over time and watch evolution in action. In this paper, we demonstrate how time series data can bound evolutionary parameters in a way that complements and informs traditional population genetic approaches. Specifically, we focus on our recent paper (Feder et al., 2016, eLife), in which we show that, as improved HIV drugs have led to fewer patients failing therapy due to resistance evolution, less genetic diversity has been maintained following the fixation of drug resistance mutations. Because soft sweeps of multiple drug resistance mutations spreading simultaneously have been previously documented in response to the less effective HIV therapies used early in the epidemic, we interpret the maintenance of post-sweep diversity in response to poor therapies as further evidence of soft sweeps and therefore a high population mutation rate (θ) in these intra-patient HIV populations. Because improved drugs resulted in rarer resistance evolution accompanied by lower post-sweep diversity, we suggest that both observations can be explained by decreased population mutation rates and a resultant transition to hard selective sweeps. A recent paper (Harris et al., 2018, PLOS Genetics) proposed an alternative interpretation: Diversity maintenance following drug resistance evolution in response to poor therapies may have been driven by recombination during slow, hard selective sweeps of single mutations. Then, if better drugs have led to faster hard selective sweeps of resistance, recombination will have less time to rescue diversity during the sweep, recapitulating the decrease in post-sweep diversity as drugs have improved. In this paper, we use time series data to show that drug resistance evolution during ineffective treatment is very fast, providing new evidence that soft sweeps drove early HIV treatment failure.     

Recombination in AIDS viruses

Recombination contributes to the generation of genetic diversity in human immunodeficiency viruses (HIV) but can only occur between viruses replicating within the same cell. Since individuals have not been found to be simultaneously coinfected with multiple divergent strains of HIV-1 or HIV-2, recombination events have been thought to be restricted to the rather closely related members of the quasispecies that evolves during the course of HIV infection. Here we describe examples of both HIV-1 and HIV-2 genomes that appear to be hybrids of genetically quite divergent viruses. Phylogenetic analyses were used to examine the evolutionary relationships among multiple HIV strains. Evolutionary trees derived from different genomic regions were consistent with respect to most of the viruses investigated. However, some strains of HIV-1 and HIV-2 exhibited significantly discordant branching orders indicative of genetic exchanges during their evolutionary histories. The crossover points of these putative recombination events were mapped by examining the distribution of phylogenetically informative sites supporting alternative tree topologies. A similar example of a recombinant simian immunodeficiency virus identified in West African green monkeys has also been described recently. These results indicate that coinfection with highly divergent viral strains can occur in HIV-infected humans and SIV-infected primates and could lead to the generation of hybrid genomes with significantly altered biological properties. Thus, future characterization of primate lentiviruses should include careful phylogenetic investigation of possible genomic mosaicism.Correspondence to: P.M. Sharp     

Mortality among Human Immunodeficiency Virus Type 2-Positive Villagers in Rural Guinea-Bissau Is Correlated with Viral Genotype

We present the results of a 6-year study of 131 human immunodeficiency virus (HIV) type 2 (HIV-2)-infected individuals from a rural population in Guinea-Bissau. Proviral DNA sequences 1.3 kb in length were obtained from each individual and, together with clinical data, including proviral load and CD4 and CD8 levels, were used to assess whether viral genotype influences clinical outcome. With a phylogenetic model, a correlation was found between viral genotype and mortality; this correlation was not due to confounding factors, such as age-specific viral strains or cohabitation of patients. The data provide strong evidence for the involvement of viral genetic factors in determining HIV disease progression in vivo. The pattern of association found suggests that virulence factors are multiple and scattered throughout the HIV-2 genome and can be rapidly gained or lost by the virus through a combination of mutation and recombination. These findings may lead to the identification of viral determinants of HIV disease progression.     

Evidence of recombination in intrapatient populations of hepatitis C virus

Hepatitis C virus (HCV) is a major cause of liver disease worldwide and a potential cause of substantial morbidity and mortality in the future. HCV is characterized by a high level of genetic heterogeneity. Although homologous recombination has been demonstrated in many members of the family Flaviviridae, to which HCV belongs, there are only a few studies reporting recombination on natural populations of HCV, suggesting that these events are rare in vivo. Furthermore, these few studies have focused on recombination between different HCV genotypes/subtypes but there are no reports on the extent of intra-genotype or intra-subtype recombination between viral strains infecting the same patient. Given the important implications of recombination for RNA virus evolution, our aim in this study has been to assess the existence and eventually the frequency of intragenic recombination on HCV. For this, we retrospectively have analyzed two regions of the HCV genome (NS5A and E1-E2) in samples from two different groups: (i) patients infected only with HCV (either treated with interferon plus ribavirin or treatment naïve), and (ii) HCV-HIV co-infected patients (with and without treatment against HIV). The complete data set comprised 17712 sequences from 136 serum samples derived from 111 patients. Recombination analyses were performed using 6 different methods implemented in the program RDP3. Recombination events were considered when detected by at least 3 of the 6 methods used and were identified in 10.7% of the amplified samples, distributed throughout all the groups described and the two genomic regions studied. The resulting recombination events were further verified by detailed phylogenetic analyses. The complete experimental procedure was applied to an artificial mixture of relatively closely viral populations and the ensuing analyses failed to reveal artifactual recombination. From these results we conclude that recombination should be considered as a potentially relevant mechanism generating genetic variation in HCV and with important implications for the treatment of this infection.     

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.     

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.     

表达HIV-1 gag重组鸡痘病毒的构建与筛选

构建并筛选表达HIV-1 gag蛋白的重组鸡痘病毒,并对其进行鉴定。首先设计引物通过PCR技术扩增HIV-1 gag基因,将其连接到pMD18-T载体上,测序正确后将其克隆入本实验室自行构建的鸡痘病毒穿梭载体pTKET中,获得重组质粒pTKET-HIV gag。然后将其与鸡痘病毒FPV282E4株共转染原代鸡胚成纤维细胞(CEF)进行同源重组,以增强型绿色荧光蛋白(EGFP)为筛选标记,通过噬斑筛选获得重组病毒,应用PCR,RT-PCR,Western blot方法对重组病毒进行鉴定和遗传稳定性分析。结果:通过10次噬斑筛选,PCR检测表明目的基因已整合到重组鸡痘病毒基因组中,RT-PCR,Western blot结果表明HIV-1 gag在感染细胞内成功表达且具有抗原性。连续传代20次,PCR,RT-PCR,Western blot均能检测到外源基因的整合、转录和表达,且未能扩增出FPV-TK基因,表明重组病毒遗传稳定性良好,而且病毒已经纯化。结论:成功获得表达HIV-1gag的重组鸡痘病毒,为进一步免疫试验研究奠定基础。     

Minimally selected p and other tests for a single abrupt changepoint in a binary sequence

A novel changepoint statistic based on the minimum value, over possible changepoint locations, of Fisher's Exact Test, is introduced. Specific points in the exact distribution of the minimally selected Fisher's value may be rapidly calculated as a lattice-path counting problem via known recurrence methods. The test is compared to the Kolmogorov-Smirnov two-sample test, the maximally selected chi-square, and a likelihood ratio test. The tests are applied to assessing recombination in genetic sequences of HIV.