Substitution model of sequence evolution for the human immunodeficiency virus type 1 subtype B gp120 gene over the C2-V5 region

Sources of Variation in Ancestral Sequence Reconstruction for HIV-1 Envelope Genes

We characterized the variation in the reconstructed ancestor of 118 HIV-1 envelope gene sequences arising from the methods used for (a) estimating and (b) rooting the phylogenetic tree, and (c) reconstructing the ancestor on that tree, from (d) the sequence format, and from (e) the number of input sequences. The method of rooting the tree was responsible for most of the sequence variation both among the reconstructed ancestral sequences and between the ancestral and observed sequences. Variation in predicted 3-D structural properties of the ancestors mirrored their sequence variation. The observed sequence consensus and ancestral sequences from center-rooted trees were most similar in all predicted attributes. Only for the predicted number of N-glycosylation sites was there a difference between MP and ML methods of reconstruction. Taxon sampling effects were observed only for outgroup-rooted trees, not center-rooted, reflecting the occurrence of several divergent basal sequences. Thus, for sequences exhibiting a radial phylogenetic tree, as does HIV-1, most of the variation in the estimated ancestor arises from the method of rooting the phylogenetic tree. Those investigating the ancestors of genes exhibiting such a radial tree should pay particular attention to alternate rooting methods in order to obtain a representative sample of ancestors.

Stochastic modelling of genotypic drug-resistance for human immunodeficiency virus towards long-term combination therapy optimization

MOTIVATION

Several mathematical models have been investigated for the description of viral dynamics in the human body: HIV-1 infection is a particular and interesting scenario, because the virus attacks cells of the immune system that have a role in the antibody production and its high mutation rate permits to escape both the immune response and, in some cases, the drug pressure. The viral genetic evolution is intrinsically a stochastic process, eventually driven by the drug pressure, dependent on the drug combinations and concentration: in this article the viral genotypic drug resistance onset is the main focus addressed. The theoretical basis is the modelling of HIV-1 population dynamics as a predator-prey system of differential equations with a time-dependent therapy efficacy term, while the viral genome mutation evolution follows a Poisson distribution. The instant probabilities of drug resistance are estimated by means of functions trained from in vitro phenotypes, with a roulette-wheel-based mechanisms of resistant selection. Simulations have been designed for treatments made of one and two drugs as well as for combination antiretroviral therapies. The effect of limited adherence to therapy was also analyzed. Sequential treatment change episodes were also exploited with the aim to evaluate optimal synoptic treatment scenarios.

RESULTS

The stochastic predator-prey modelling usefully predicted long-term virologic outcomes of evolved HIV-1 strains for selected antiretroviral therapy combinations. For a set of widely used combination therapies, results were consistent with findings reported in literature and with estimates coming from analysis on a large retrospective data base (EuResist).

Characterization and signature pattern analysis of Korean clade HIV-1 using nef gene sequences

Phylogenetic studies of the HIV-1 gene sequences isolated from Korean patients have suggested that most of Korean isolates belong to the subtype B strain. This study aims to characterize the Korean clade by molecular phylogenetic analysis using all of the Korean nef gene sequences registered in the NCBI GenBank (N=422), in addition to 41 reference strains and 94 foreign isolates. Through phylogenetic analyses, we verified that most of the Korean isolates belonged to the subtype B, where 78.8% are clustered exclusively of foreign isolates. This cluster has been named the Korean clade subtype B (KCB) in order to distinguish it from other subtype B clusters. Genetic distance analysis suggested that the KCB cluster was more homogeneous and clearly distinctive from the non-Korean clade subtype B (NKCB). Comparison of consensus amino acid sequences from KCB and NKCB revealed that characteristic KCB signature amino acid patterns composed of 11 amino acid residues, whose frequencies in the KCB were significantly higher than in the NKCB. The KCB signature amino acid residues were critical in identifying KCB from NKCB, since substitution of the NKCB sequences with KCB signature amino acids relocated them to the Koran clade, and vice versa.

The HIV positive selection mutation database

The HIV positive selection mutation database is a large-scale database available at that provides detailed selection pressure maps of HIV protease and reverse transcriptase, both of which are molecular targets of antiretroviral therapy. This database makes available for the first time a very large HIV sequence dataset (sequences from ∼50 000 clinical AIDS samples, generously contributed by Specialty Laboratories, Inc.), which makes possible high-resolution selection pressure mapping. It provides information about not only the selection pressure on individual sites but also how selection pressure at one site is affected by mutations on other sites. It also includes datasets from other public databases, namely the Stanford HIV database [S. Y. Rhee, M. J. Gonzales, R. Kantor, B. J. Betts, J. Ravela and R. W. Shafer (2003) Nucleic Acids Res., 31, 298–303]. Comparison between these datasets in the database enables cross-validation with independent datasets and also specific evaluation of the effect of drug treatment.

Minimization of genetic distances by the consensus, ancestral, and center-of-tree (COT) sequences for HIV-1 variants within an infected individual and the design of reagents to test immune reactivity

Eliciting maximal immune responses to highly divergent viruses is a challenge and a focus in AIDS vaccine development. Another challenge is to identify the immune correlates of protective immunity. Recent AIDS vaccine design approaches attempt to use reconstructed centralized viral sequences that minimize genetic differences to circulating viruses. Using these approaches, we derive and analyze consensus (CON), ancestral (ANC), and center-of-tree (COT) sequences to represent intra-individual HIV-1 env variants encoding a range of diversities and phylogenetic structures. Each reconstructed sequence significantly minimized genetic distances to extant sequences throughout the first 5 years of infection of an individual. Interestingly, ANC sequences diverged and were not significantly better than extant sequences in minimizing genetic distances at later stages of infection and disease, likely due to the development of a substantially asymmetric phylogeny. COT or CON sequences derived from autologous virus samplings may be useful for increasing the sensitivity of assessments of immune reactivity against HIV.

Human immunodeficiency virus type 1 env evolves toward ancestral states upon transmission to a new host

Selecting human immunodeficiency virus (HIV) sequences for inclusion within vaccines has been a difficult problem, as circulating HIV strains evolve relentlessly and become increasingly divergent over time. We report an assessment of this divergence from three perspectives: (i) across different hosts as a function of time of infection, (ii) between donors and recipients in known transmission pairs, and (iii) within individual hosts over time in relation to the initially replicating virus and to the deduced ancestral sequence of the intrahost viral population. Surprisingly, we consistently found less divergence between viruses from different individuals sampled in primary infection than in individuals sampled at more advanced stages of illness. Furthermore, longitudinal analysis of intrahost divergence revealed a 2- to 3-year period of evolution toward a common ancestral sequence at the start of infection, indicating that HIV recovers certain ancestral features when infecting a new host. These results have important implications for the study of HIV population genetics and rational vaccine design, including favoring the inclusion of viral gene sequences taken early in infection.

Recombination estimation under complex evolutionary models with the coalescent composite-likelihood method

The composite-likelihood estimator (CLE) of the population recombination rate considers only sites with exactly two alleles under a finite-sites mutation model (McVean, G. A. T., P. Awadalla, and P. Fearnhead. 2002. A coalescent-based method for detecting and estimating recombination from gene sequences. Genetics 160:1231-1241). While in such a model the identity of alleles is not considered, the CLE has been shown to be robust to minor misspecification of the underlying mutational model. However, there are many situations where the putative mutation and demographic history can be quite complex. One good example is rapidly evolving pathogens, like HIV-1. First we evaluated the performance of the CLE and the likelihood permutation test (LPT) under more complex, realistic models, including a general time reversible (GTR) substitution model, rate heterogeneity among sites (Gamma), positive selection, population growth, population structure, and noncontemporaneous sampling. Second, we relaxed some of the assumptions of the CLE allowing for a four-allele, GTR + Gamma model in an attempt to use the data more efficiently. Through simulations and the analysis of real data, we concluded that the CLE is robust to severe misspecifications of the substitution model, but underestimates the recombination rate in the presence of exponential growth, population mixture, selection, or noncontemporaneous sampling. In such cases, the use of more complex models slightly increases performance in some occasions, especially in the case of the LPT. Thus, our results provide for a more robust application of the estimation of recombination rates.

Evolution of the equine infectious anemia virus long terminal repeat during the alteration of cell tropism

Equine infectious anemia virus (EIAV) is a lentivirus with in vivo cell tropism primarily for tissue macrophages; however, in vitro the virus can be adapted to fibroblasts and other cell types. Tropism adaptation is associated with both envelope and long terminal repeat (LTR) changes, and findings strongly suggest that these regions of the genome influence cell tropism and virulence. Furthermore, high levels of genetic variation have been well documented in both of these genomic regions. However, specific EIAV nucleotide or amino acid changes that are responsible for cell tropism changes have not been identified. A study was undertaken with the highly virulent, macrophage-tropic strain of virus EIAV(wyo) to identify LTR changes associated with alterations in cell tropism. We found the stepwise generation of a new transcription factor binding motif within the enhancer that was associated with adaptation of EIAV to endothelial cells and fibroblasts. An LTR that contained the new motif had enhanced transcriptional activity in fibroblasts, whereas the new site did not alter LTR activity in a macrophage cell line. This finding supports a previous prediction that selection for new LTR genetic variants may be a consequence of cell-specific selective pressures. Additional investigations of the EIAV(wyo) LTR were performed in vivo to determine if LTR evolution could be detected over the course of a 3-year infection. Consistent with previous in vivo findings, we observed no changes in the enhancer region of the LTR over that time period, indicating that the EIAV(wyo) LTR was evolutionarily stable in vivo.

Immunogen sequence: the fourth tier of AIDS vaccine design

While worldwide efforts to develop an effective HIV-1 vaccine are underway, the virus continues to spread, particularly in developing countries where the delivery of antiviral therapies presents formidable challenges. Vaccine research has largely focused on three general aspects: vectors, adjuvants, and immunization schedules. Our group favor the use of computational methods to design potential immunogens that capture the genetic and biological features of circulating viruses. These methods allow researchers to predict, in silico, the presence of potential glycosylation sites, humoral immune responses, and epitope coverage. This review shall compare three computational approaches for immunogen design: the consensus sequence, which has at each site the modal nucleotide or amino acid residue across a sequence alignment; the most recent common ancestor, the sequence estimated at the basal node of the clades seen in the HIV-1 phylogeny; and the center of tree method, which minimizes the evolutionary distance to all sequences in the data set.

A statistical characterization of consistent patterns of human immunodeficiency virus evolution within infected patients

Within-patient HIV populations evolve rapidly because of a high mutation rate, short generation time, and strong positive selection pressures. Previous studies have identified "consistent patterns" of viral sequence evolution. Just before HIV infection progresses to AIDS, evolution seems to slow markedly, and the genetic diversity of the viral population drops. This evolutionary slowdown could be caused either by a reduction in the average viral replication rate or because selection pressures weaken with the collapse of the immune system. The former hypothesis (which we denote "cellular exhaustion") predicts a simultaneous reduction in both synonymous and nonsynonymous evolution, whereas the latter hypothesis (denoted "immune relaxation") predicts that only nonsynonymous evolution will slow. In this paper, we present a set of statistical procedures for distinguishing between these alternative hypotheses using DNA sequences sampled over the course of infection. The first component is a new method for estimating evolutionary rates that takes advantage of the temporal information in longitudinal DNA sequence samples. Second, we develop a set of probability models for the analysis of evolutionary rates in HIV populations in vivo. Application of these models to both synonymous and nonsynonymous evolution affords a comparison of the cellular-exhaustion and immune-relaxation hypotheses. We apply the procedures to longitudinal data sets in which sequences of the env gene were sampled over the entire course of infection. Our analyses (1) statistically confirm that an evolutionary slowdown occurs late in infection, (2) strongly support the immune-relaxation hypothesis, and (3) indicate that the cessation of nonsynonymous evolution is associated with disease progression.

The solitary wave of asexual evolution

Using a previously undescribed approach, we develop an analytic model that predicts whether an asexual population accumulates advantageous or deleterious mutations over time and the rate at which either process occurs. The model considers a large number of linked identical loci, or nucleotide sites; assumes that the selection coefficient per site is much less than the mutation rate per genome; and includes back and compensating mutations. Using analysis and Monte Carlo simulations, we demonstrate the accuracy of our results over almost the entire range of population sizes. Two limiting cases of our results, when either deleterious or advantageous mutations can be neglected, correspond to the Fisher-Muller effect and Muller's ratchet, respectively. By comparing predictions of our model (no recombination) to those of simple single-locus models (strong recombination), we show that the accumulation of advantageous mutations is slowed by linkage over a broad, finite range of population size. This supports the view of Fisher and Muller, who argued in the 1930s that progressive evolution of organisms is slowed because loci at which beneficial mutations can occur are often linked together on the same chromosome. These results follow from our main finding, that distribution of sequences over the mutation number evolves as a traveling wave whose speed and width depend on population size and other parameters. The model explains a logarithmic dependence of steady-state fitness on the population size reported recently for an RNA virus.