The causes and consequences of HIV evolution

HIV dynamics with multiple infections of target cells

The high incidence of multiple infections of cells by HIV sets the stage for rapid HIV evolution by means of recombination. Yet how HIV dynamics proceeds with multiple infections remains poorly understood. Here, we present a mathematical model that describes the dynamics of viral, target cell, and multiply infected cell subpopulations during HIV infection. Model calculations reproduce several experimental observations and provide key insights into the influence of multiple infections on HIV dynamics. We find that the experimentally observed scaling law, that the number of cells coinfected with two distinctly labeled viruses is proportional to the square of the total number of infected cells, can be generalized so that the number of triply infected cells is proportional to the cube of the number of infected cells, etc. Despite the expectation from Poisson statistics, we find that this scaling relationship only holds under certain conditions, which we predict. We also find that multiple infections do not influence viral dynamics when the rate of viral production from infected cells is independent of the number of times the cells are infected, a regime expected when viral production is limited by cellular rather than viral factors. This result may explain why extant models, which ignore multiple infections, successfully describe viral dynamics in HIV patients. Inhibiting CD4 down-modulation increases the average number of infections per cell. Consequently, altering CD4 down-modulation may allow for an experimental determination of whether viral or cellular factors limit viral production.

Lethal mutagenesis of HIV

HIV-1 and other retroviruses exhibit mutation rates that are 1,000,000-fold greater than their host organisms. Error-prone viral replication may place retroviruses and other RNA viruses near the threshold of "error catastrophe" or extinction due to an intolerable load of deleterious mutations. Strategies designed to drive viruses to error catastrophe have been applied to HIV-1 and a number of RNA viruses. Here, we review the concept of extinguishing HIV infection by "lethal mutagenesis" and consider the utility of this new approach in combination with conventional antiretroviral strategies.

Antiretroviral resistance and genetic diversity of human immunodeficiency virus type 1 isolates from the Federal District, Central Brazil

In the context of universal access to antiretroviral therapy, the surveillance of human immunodeficiency virus type 1 (HIV-1) genetic diversity and resistance becomes pivotal. In this work our purpose was to describe the genetic variability; prevalence of drug-resistance mutations; and genotypic resistance profiles in HIV-1 infected individuals under antiretroviral treatment, from the Federal District, Brasilia, Central Brazil. The entire viral protease and codons 19 to 234 of the reverse transcriptase gene from 45 HIV-1 isolates were amplified and sequenced for subtyping and genotyping. By phylogenetic analysis, 96% of the samples clustered with subtype B and the remaining 4% with HIV-1 subtype F sequences. One major protease inhibitor resistance-associated mutation, I50V, was detected in 38% of the samples. Minor mutations were also found at the protease gene: L10I/V (7%), K20M (2%), M36I (11%), L63P (20%), A71T (2%), and V77I (7%). Many mutations associated with reduced susceptibility to nucleoside or non-nucleoside reverse transcriptase inhibitors were detected: M41L (11%), E44D (4%), D67N (11%), T69D (2%), K70R (11%), L74V (2%), L100I (4%), K103N (18%), V118I (9%), Y181C (11%), M184V (18%), G190A (4%), T215Y (4%), and K219E (4%). This study has shown that 84% of the studied population from the Federal District, showing evidences of therapy failure, presented viral genomic mutations associated with drug resistance. The main antiretrovirals to which this population showed resistance were the PI amprenavir (38%), the NNRTIs delavirdine, nevirapine (31%), and efavirenz (24%), and the NRTIs lamivudine (18%), abacavir, and zidovudine (13%).

Mapping sites of positive selection and amino acid diversification in the HIV genome: an alternative approach to vaccine design?

A safe and effective HIV-1 vaccine is urgently needed to control the worldwide AIDS epidemic. Traditional methods of vaccine development have been frustratingly slow, and it is becoming increasingly apparent that radical new approaches may be required. Computational and mathematical approaches, combined with evolutionary reasoning, may provide new insights for the design of an efficacious AIDS vaccine. Here, we used codon-based substitution models and maximum-likelihood (ML) methods to identify positively selected sites that are likely to be involved in the immune control of HIV-1. Analysis of subtypes B and C revealed widespread adaptive evolution. Positively selected amino acids were detected in all nine HIV-1 proteins, including Env. Of particular interest was the high level of positive selection within the C-terminal regions of the immediate-early regulatory proteins, Tat and Rev. Many of the amino acid replacements were associated with the emergence of novel (or alternative) myristylation and casein kinase II (CKII) phosphorylation sites. The impact of these changes on the conformation and antigenicity of Tat and Rev remains to be established. In rhesus macaques, a single CTL-associated amino substitution in Tat has been linked to escape from acute SIV infection. Understanding the relationship between host-driven positive selection and antigenic variation may lead to the development of novel vaccine strategies that preempt the escape process.

Computational design of antiviral RNA interference strategies that resist human immunodeficiency virus escape

Recently developed antiviral strategies based upon RNA interference (RNAi), which harnesses an innate cellular system for the targeted down-regulation of gene expression, appear highly promising and offer alternative approaches to conventional highly active antiretroviral therapy or efforts to develop an AIDS vaccine. However, RNAi is faced with several challenges that must be overcome to fully realize its promise. Specifically, it degrades target RNA in a highly sequence-specific manner and is thus susceptible to viral mutational escape, and there are also challenges in delivery systems to induce RNAi. To aid in the development of anti-human immunodeficiency virus (anti-HIV) RNAi therapies, we have developed a novel stochastic computational model that simulates in molecular-level detail the propagation of an HIV infection in cells expressing RNAi. The model provides quantitative predictions on how targeting multiple locations in the HIV genome, while keeping the overall RNAi strength constant, significantly improves efficacy. Furthermore, it demonstrates that delivery systems must be highly efficient to preclude leaving reservoirs of unprotected cells where the virus can propagate, mutate, and eventually overwhelm the entire system. It also predicts how therapeutic success depends upon a relationship between RNAi strength and delivery efficiency and uniformity. Finally, targeting an essential viral element, in this case the HIV TAR region, can be highly successful if the RNAi target sequence is correctly selected. In addition to providing specific predictions for how to optimize a clinical therapy, this system may also serve as a future tool for investigating more fundamental questions of viral evolution.

Human immunodeficiency virus type 1 genetic diversity in the nervous system: Evolutionary epiphenomenon or disease determinant?

Over the past decade there has been a revolution in the understanding and care of human immunodeficiency virus/acquired immunodeficiency syndrome (HIV/AIDS)-associated disease. Much of this progress stems from a broader recognition of the importance of differences in viral types, including receptor preference(s), replication properties, and reservoirs, as contributing factors to immunosuppresion and disease progression. In contrast, there is limited conceptualizatin of viral diversity and turnover in the brain and circulation in relation to neurocognitive impairments. Herein, the authors review current concepts regarding viral molecular diversity and phenotypes together with features of HIV-1 neuroinvasion, neurotropism, neurovirulence and neurosusceptiblity. Viral genetic and antigenic diversity is reduced within the brain compared to blood or other systemic organs within individuals. Conversely, viral molecular heterogeneity is greater in patients with HIV-associated dementia compared to nondemented patients, depending on the viral gene examined. Individual viral proteins exert multiple neuropathogenic effects, although the neurological consequences of different viral polymorphisms remain uncertain. Nonetheless, host genetic polymorphisms clearly influence neurological disease outcomes and likely dictate both acquired and innate immune responses, which in turn shape viral evolution within the host. Emerging issues include widespread antiretroviral therapy resistance and increasing awareness of viral superinfections together with viral recombination, all of which are likely to impact on both HIV genetic variation and neuropathogenesis. With the persisting prevalence of HIV-induced neurocognitive disabilities, despite marked improvements in managing immunosuppression, it remains imperative to fully define and understand the mechanisms by which viral dynamics and diversity contribute to neurological disease, permitting the development of new therapeutic strategies.

Distinct patterns of natural selection in the reverse transcriptase gene of HIV-1 in the presence and absence of antiretroviral therapy

The emergence of human immunodeficiency virus (HIV) drug-resistant mutations during antiretroviral therapy is explained by either the preexistence of low-frequency-resistant strains before the start of therapy or by the selection of unsuppressed resistant strains during therapy. We used pairwise and maximum likelihood analyses of the ratio of nonsynonymous to synonymous substitutions per site (d(N)/d(S)) to study the extent of positive selection in the reverse transcriptase (RT) gene of HIV-1 from multiple data sets of drug-treated (117 sequences) and drug-naive patients (270 sequences). In the pairwise analysis, evidence for positive selection (d(N)/d(S) > 1) was only found in drug-treated individuals and in codons conferring drug resistance. By the maximum likelihood method, a positive selection at codons conferring drug resistance was only observed in patients receiving therapy, and although positive selection was detected in drug-naive patients, this was always at codons unrelated to drug resistance. We therefore document a striking difference in the process of allele fixation in drug resistance codons (RC) between populations of HIV-1-infected individuals naive to treatment and those receiving therapy. Furthermore, although mutations associated with drug resistance are sometimes found in drug-naive patients, we suggest that these are fixed because of linkage to sites experiencing immune escape. Finally, we show that compensatory changes are likely to be important in the development of HIV drug resistance by counter-acting the deleterious effects normally associated with drug resistance mutations.

The structure of HIV-1 genomic RNA in the gp120 gene determines a recombination hot spot in vivo

By frequently rearranging large regions of the genome, genetic recombination is a major determinant in the plasticity of the human immunodeficiency virus type I (HIV-1) population. In retroviruses, recombination mostly occurs by template switching during reverse transcription. The generation of retroviral vectors provides a means to study this process after a single cycle of infection of cells in culture. Using HIV-1-derived vectors, we present here the first characterization and estimate of the strength of a recombination hot spot in HIV-1 in vivo. In the hot spot region, located within the C2 portion of the gp120 envelope gene, the rate of recombination is up to ten times higher than in the surrounding regions. The hot region corresponds to a previously identified RNA hairpin structure. Although recombination breakpoints in vivo cluster in the top portion of the hairpin, the bias for template switching in this same region appears less marked in a cell-free system. By modulating the stability of this hairpin we were able to affect the local recombination rate both in vitro and in infected cells, indicating that the local folding of the genomic RNA is a major parameter in the recombination process. This characterization of reverse transcription products generated after a single cycle of infection provides insights in the understanding of the mechanism of recombination in vivo and suggests that specific regions of the genome might be prompted to yield different rates of evolution due to the presence of circumscribed recombination hot spots.