Reevaluation of amino acid variability of the human immunodeficiency virus type 1 gp120 envelope glycoprotein and prediction of new discontinuous epitopes

Prediction of the membrane-spanning beta-strands of the major outer membrane protein of Chlamydia

There is preliminary experimental evidence indicating that the major outer-membrane protein (MOMP) of Chlamydia is a porin. We tested this hypothesis for the MOMP of the mouse pneumonitis serovar of Chlamydia trachomatis using two secondary structure prediction methods. First, an algorithm that calculates the mean hydrophobicity of one side of putative beta-strands predicted the positions of 16 transmembrane segments, a structure common to known porins. Second, outer loops typical of porins were assigned using an artificial neural network trained to predict the topology of bacterial outer-membrane proteins with a predominance of beta-strands. A topology model based on these results locates the four variable domains (VDs) of the MOMP on the outer loops and the five constant domains on beta-strands and the periplasmic turns. This model is consistent with genetic analysis and immunological and biochemical data that indicate the VDs are surface exposed. Furthermore, it shows significant homology with the consensus porin model of the program FORESST, which contrasts a proposed secondary structure against a data set of 349 proteins of known structure. Analysis of the MOMP of other chlamydial species corroborated our predicted model.

Variability in the human immunodeficiency virus type 1 gp120 Env protein linked to phenotype-associated changes in the V3 loop

Isolates of human immunodeficiency virus type 1 (HIV-1) are classified according to the chemokine receptor (coreceptor) used in conjunction with CD4 to target and enter cells: viruses using CCR5 and CXCR4 are classified as R5 and X4, respectively. The major determinant of entry-related HIV-1 phenotypes is known to reside in the third variable region of gp120 (V3). It is clear, however, that positions outside of V3 play some role in influencing phenotype, although marked context dependence and extensive variability among HIV-1 isolates have made the identification of these positions difficult. We used the presence of previously described substitutions in V3 to classify a large set of HIV-1 subtype B gp120 sequences available in public databases as X4-like or R5-like. Using these classifications, we searched for positions outside of V3 where either amino acid composition or variability differed significantly among sequences of different inferred phenotypes. Our approach took the epidemiological relationships among sequences into account. A cluster of positions linked to changes in V3 was identified between amino acids 190 and 204 of gp120, immediately C-terminal of V2; changes at position 440 in C4 were also linked to inferred phenotype. Structural data place these positions at the coreceptor-binding face of gp120 in a surface-exposed location. We also noted a significant increase in net positive charge in a highly variable region of V2. This study both confirms previous observations and predicts specific positions that contribute to a functional relationship between V3, V2, and C4.

Reliabilities of parsimony-based and likelihood-based methods for detecting positive selection at single amino acid sites

The reliabilities of parsimony-based and likelihood-based methods for inferring positive selection at single amino acid sites were studied using the nucleotide sequences of human leukocyte antigen (HLA) genes, in which positive selection is known to be operating at the antigen recognition site. The results indicate that the inference by parsimony-based methods is robust to the use of different evolutionary models and generally more reliable than that by likelihood-based methods. In contrast, the results obtained by likelihood-based methods depend on the models and on the initial parameter values used. It is sometimes difficult to obtain the maximum likelihood estimates of parameters for a given model, and the results obtained may be false negatives or false positives depending on the initial parameter values. It is therefore preferable to use parsimony-based methods as long as the number of sequences is relatively large and the branch lengths of the phylogenetic tree are relatively small.

Human immunodeficiency virus type 1 env sequences from Calcutta in eastern India: identification of features that distinguish subtype C sequences in India from other subtype C sequences

India is experiencing a rapid spread of human immunodeficiency virus type 1 (HIV-1), primarily through heterosexual transmission of subtype C viruses. To delineate the molecular features of HIV-1 circulating in India, we sequenced the V3-V4 region of viral env from 21 individuals attending an HIV clinic in Calcutta, the most populous city in the eastern part of the country, and analyzed these and the other Indian sequences in the HIV database. Twenty individuals were infected with viruses having a subtype C env, and one had viruses with a subtype A env. Analyses of 192 subtype C sequences that included one sequence for each subject from this study and from the HIV database revealed that almost all sequences from India, along with a small number from other countries, form a phylogenetically distinct lineage within subtype C, which we designate C(IN). Overall, C(IN) lineage sequences were more closely related to each other (level of diversity, 10.2%) than to subtype C sequences from Botswana, Burundi, South Africa, Tanzania, and Zimbabwe (range, 15.3 to 20.7%). Of the three positions identified as signature amino acid substitution sites for C(IN) sequences (K340E, K350A, and G429E), 56% of the C(IN) sequences contained all three amino acids while 87% of the sequences contained at least two of these substitutions. Among the non-C(IN) sequences, all three amino acids were present in 2%, while 22% contained two or more of these amino acids. These results suggest that much of the current Indian epidemic is descended from a single introduction into the country. Identification of conserved signature amino acid positions could assist epidemiologic tracking and has implications for the development of a vaccine against subtype C HIV-1 in India.

Positively selected amino acid sites in the entire coding region of hepatitis C virus subtype 1b

To predict the amino acid sites important for the clearance of hepatitis C virus (HCV) subtype 1b in vivo, positively selected amino acid sites were detected by analyzing the sequence data collected from the international DNA databank. The rate of nonsynonymous substitutions per nonsynonymous site was compared with that of synonymous substitutions per synonymous site for each codon site in the entire coding region. As a result, 13 out of 3010 amino acid sites were found to be positively selected. Among the 13 positively selected amino acid sites, eight were located in the structural proteins and five were in the nonstructural proteins. Moreover, eight were located in B-cell epitopes and two were in T-cell epitopes. These observations suggest that both the antibody and the cytotoxic T lymphocyte are involved in the clearance of HCV subtype 1b in vivo. These positively selected amino acid sites represent candidate vaccination targets for HCV subtype 1b.

Improved success of phenotype prediction of the human immunodeficiency virus type 1 from envelope variable loop 3 sequence using neural networks

We have assembled two sets of HIV-1 V3 sequences with defined epidemiologic relationships associated with experimentally determined coreceptor usage or MT-2 cell tropism. These data sets were used for three purposes. First, they were employed to test existing methods for predicting coreceptor usage and MT-2 cell tropism. Of these methods, the presence of one basic amino acid at position 11 or 25 proved to be most reliable for both phenotypic classifications, although its predictive power for the X4 phenotype was less than 50%. Second, we used the sequence sets to train neural networks to infer coreceptor usage from V3 genotype with better success than the best available motif-based method, and with a predictive power equal to that of the best motif-based method for MT-2 cell tropism. Third, we used the sequence sets to reexamine patterns of variability associated with the different phenotypes, and we showed that the phenotype-associated sequence patterns could be reproduced from large sets of V3 sequences using phenotypes predicted by the trained neural network.

Phylogenetic reconstruction of intrapatient evolution of human immunodeficiency virus type 1: predominance of drift and purifying selection

The intra-host evolution of 73 human immunodeficiency virus type 1 quasispecies was analysed by split decomposition analysis. Non-synonymous and synonymous nucleotide substitutions were counted along the shortest path connecting all sequences and compared with the numbers expected under the assumption of a random model of mutation. For the majority of substitutions, drift and negative selection seemed to prevail.

Genetic drift and within-host metapopulation dynamics of HIV-1 infection

Most HIV replication occurs in solid lymphoid tissue, which has prominent architecture at the histological level, which separates groups of productively infected CD4(+) cells. Nevertheless, current population models of HIV assume panmixis within lymphoid tissue. We present a simple "metapopulation" model of HIV replication, where the population of infected cells is comprised of a large number of small populations, each of which is established by a few founder viruses and undergoes turnover. To test this model, we analyzed viral genetic variation of infected cell subpopulations within the spleen and demonstrated the action of founder effects as well as significant variation in the extent of genetic differentiation between subpopulations among patients. The combination of founder effects and subpopulation turnover can result in an effective population size much lower than the actual population size and may contribute to the importance of genetic drift in HIV evolution despite a large number of infected cells.

Evidence for positive selection driving the evolution of HIV-1 env under potent antiviral therapy

In HIV-infected individuals treated with potent antiretroviral therapy, viable virus can be isolated from latently infected cells several years into therapy, due to the long life of these cells, ongoing replication replenishing this population, or both. We have analysed the V3 region of the HIV-1 env gene isolated from six patients who have undergone 2 years of potent antiretroviral therapy without frank failure of viral suppression. We show that in two (and possibly three) patients, the sequence changes between baseline virus and virus isolated from infected cells persisting 2 years into infection result from positive selection driving adaptive evolution, occurring either prior to or during therapy. Our analyses suggest low-level replication despite absence of drug resistance due to drug sanctuary sites, or to low-level ongoing replication in the presence of alterations in the selective environment during therapy, perhaps due to a decline in HIV-specific immune responsiveness or changes in target cell pools. In one patient, genetic divergence between baseline plasma and infected cells isolated during therapy may reflect the long half-life of some of these persistent cell populations and the divergence of viral subpopulations that occurred prior to therapy.

Predicting adaptive evolution

Phylogenetic trees reconstruct past evolution and can provide evidence of past evolutionary pressure on genes and on individual codons. In addition to tracing past evolutionary events, molecular phylogenetics might also be used to predict future evolution. Our ability to verify adaptive hypotheses using phylogenetics has broad implications for vaccine design, genomics and structural biology.

On the origin and evolution of the human immunodeficiency virus (HIV)

The human AIDS viruses--HIV-1 and HIV-2--impose major burdens on the health and economic status of many developing countries. Surveys of other animal species have revealed that related viruses--the SIVs are widespread in a large number of African simian primates where they do not appear to cause disease. Phylogenetic analyses indicate that these SIVs are the reservoirs for the human viruses, with SIVsm from the sooty mangabey monkey the most likely source of HIV-2, and SIVcpz from the common chimpanzee the progenitor population for HIV-1. Although it is clear that AIDS has a zoonotic origin, it is less certain when HIV-1 and HIV-2 first entered human populations and whether cross-species viral transmission is common among primates. Within infected individuals the process of HIV evolution takes the form of an arms race, with the virus continually fixing mutations by natural selection which allow it to escape from host immune responses. The arms race is less intense in SIV-infected monkeys, where a weaker immune response generates less selective pressure on the virus. Such a difference in virus-host interaction, along with a broadening of co-receptor usage such that HIV strains are able to infect cells with both CCR5 and CXCR4 chemokine receptors, may explain the increased virulence of HIV in humans compared to SIV in other primates.

Dating the common ancestor of SIVcpz and HIV-1 group M and the origin of HIV-1 subtypes using a new method to uncover clock-like molecular evolution

Attempts to estimate the time of origin of human immunodeficiency virus (HIV)-1 by using phylogenetic analysis are seriously flawed because of the unequal evolutionary rates among different viral lineages. Here, we report a new method of molecular clock analysis, called Site Stripping for Clock Detection (SSCD), which allows selection of nucleotide sites evolving at an equal rate in different lineages. The method was validated on a dataset of patients all infected with hepatitis C virus in 1977 by the same donor, and it was able to date exactly the known origin of the infection. Using the same method, we calculated that the origin of HIV-1 group M radiation was in the 1930s. In addition, we show that the coalescence time of the simian ancestor of HIV-1 group M and its closest related cpz strains occurred around the end of the XVII century, a date that could be considered the upper limit to the time of simian-to-human transmission of HIV-1 group M. The results show also that SSCD is an easy-to-use method of general applicability in molecular evolution to calibrate clock-like phylogenetic trees.

Evolutionary and immunological implications of contemporary HIV-1 variation

Evolutionary modelling studies indicate less than a century has passed since the most recent common ancestor of the HIV-1 pandemic strains and, in that time frame, an extraordinarily diverse viral population has developed. HIV-1 employs a multitude of schemes to generate variants: accumulation of base substitutions, insertions and deletions, addition and loss of glycosylation sites in the envelope protein, and recombination. A comparison between HIV and influenza virus illustrates the extraordinary scale of HIV variation, and underscores the importance of exploring innovative HIV vaccine strategies. Deeper understanding of the implications of variation for both antibody and T-cell responses may help in the effort to rationally design vaccines that stimulate broad cross-reactivity. The impact of HIV-1 variation on host immune response is reviewed in this context.

Statistical methods for detecting molecular adaptation

The past few years have seen the development of powerful statistical methods for detecting adaptive molecular evolution. These methods compare synonymous and nonsynonymous substitution rates in protein-coding genes, and regard a nonsynonymous rate elevated above the synonymous rate as evidence for darwinian selection. Numerous cases of molecular adaptation are being identified in various systems from viruses to humans. Although previous analyses averaging rates over sites and time have little power, recent methods designed to detect positive selection at individual sites and lineages have been successful. Here, we summarize recent statistical methods for detecting molecular adaptation, and discuss their limitations and possible improvements.