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      Synonymous Substitution Rates Predict HIV Disease Progression as a Result of Underlying Replication Dynamics

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          Abstract

          Upon HIV transmission, some patients develop AIDS in only a few months, while others remain disease free for 20 or more years. This variation in the rate of disease progression is poorly understood and has been attributed to host genetics, host immune responses, co-infection, viral genetics, and adaptation. Here, we develop a new “relaxed-clock” phylogenetic method to estimate absolute rates of synonymous and nonsynonymous substitution through time. We identify an unexpected association between the synonymous substitution rate of HIV and disease progression parameters. Since immune activation is the major determinant of HIV disease progression, we propose that this process can also determine viral generation times, by creating favourable conditions for HIV replication. These conclusions may apply more generally to HIV evolution, since we also observed an overall low synonymous substitution rate for HIV-2, which is known to be less pathogenic than HIV-1 and capable of tempering the detrimental effects of immune activation. Humoral immune responses, on the other hand, are the major determinant of nonsynonymous rate changes through time in the envelope gene, and our relaxed-clock estimates support a decrease in selective pressure as a consequence of immune system collapse.

          Author Summary

          During the clinical course of HIV infection, an asymptomatic phase always precedes the acquired immunodeficiency syndrome (AIDS). The duration of this asymptomatic phase is highly variable among patients and reflects the rate at which the immune system gradually deteriorates. Although humoral and cell-mediated immune responses are mounted against HIV, continuous replication and adaptation allows the virus to escape host immune responses. To gain a better understanding of the role of viral evolution in disease progression, we developed a new computational technique that can estimate changes in the absolute rates of synonymous and nonsynonymous divergence through time from molecular sequences. Using this type of evolutionary inference, we have identified a previously unknown association between the “silent” evolutionary rate of HIV and the rate of disease progression in infected individuals. This finding demonstrates that cellular immune processes, which are already known to determine HIV pathogenesis, also determine viral replication rates and therefore impose important constraints on HIV evolution.

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          Most cited references55

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          Likelihood models for detecting positively selected amino acid sites and applications to the HIV-1 envelope gene.

          Several codon-based models for the evolution of protein-coding DNA sequences are developed that account for varying selection intensity among amino acid sites. The "neutral model" assumes two categories of sites at which amino acid replacements are either neutral or deleterious. The "positive-selection model" assumes an additional category of positively selected sites at which nonsynonymous substitutions occur at a higher rate than synonymous ones. This model is also used to identify target sites for positive selection. The models are applied to a data set of the V3 region of the HIV-1 envelope gene, sequenced at different years after the infection of one patient. The results provide strong support for variable selection intensity among amino acid sites The neutral model is rejected in favor of the positive-selection model, indicating the operation of positive selection in the region. Positively selected sites are found in both the V3 region and the flanking regions.
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            Temporal association of cellular immune responses with the initial control of viremia in primary human immunodeficiency virus type 1 syndrome.

            Virologic and immunologic studies were performed on five patients presenting with primary human immunodeficiency virus type 1 (HIV-1) infection. CD8+ cytotoxic T lymphocyte (CTL) precursors specific for cells expressing antigens of HIV-1 Gag, Pol, and Env were detected at or within 3 weeks of presentation in four of the five patients and were detected in all five patients by 3 to 6 months after presentation. The one patient with an absent initial CTL response had prolonged symptoms, persistent viremia, and low CD4+ T-cell count. Neutralizing antibody activity was absent at the time of presentation in all five patients. These findings suggest that cellular immunity is involved in the initial control of virus replication in primary HIV-1 infection and indicate a role for CTL in protective immunity to HIV-1 in vivo.
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              Estimating mutation parameters, population history and genealogy simultaneously from temporally spaced sequence data.

              Molecular sequences obtained at different sampling times from populations of rapidly evolving pathogens and from ancient subfossil and fossil sources are increasingly available with modern sequencing technology. Here, we present a Bayesian statistical inference approach to the joint estimation of mutation rate and population size that incorporates the uncertainty in the genealogy of such temporally spaced sequences by using Markov chain Monte Carlo (MCMC) integration. The Kingman coalescent model is used to describe the time structure of the ancestral tree. We recover information about the unknown true ancestral coalescent tree, population size, and the overall mutation rate from temporally spaced data, that is, from nucleotide sequences gathered at different times, from different individuals, in an evolving haploid population. We briefly discuss the methodological implications and show what can be inferred, in various practically relevant states of prior knowledge. We develop extensions for exponentially growing population size and joint estimation of substitution model parameters. We illustrate some of the important features of this approach on a genealogy of HIV-1 envelope (env) partial sequences.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS Comput Biol
                pcbi
                PLoS Computational Biology
                Public Library of Science (San Francisco, USA )
                1553-734X
                1553-7358
                February 2007
                23 February 2007
                2 January 2007
                : 3
                : 2
                : e29
                Affiliations
                [1 ] Department of Zoology, University of Oxford, Oxford, United Kingdom
                [2 ] Department of Pathology, University of California San Diego, La Jolla, United States of America
                [3 ] Department of Computer Science, University of Auckland, Auckland, New Zealand
                [4 ] Centro de Patogénese Molecular, Faculdade de Farmácia de Lisboa, Lisbon, Portugal
                [5 ] Instituto Superior de Ciências da Saúde Egas Moniz, Lisbon, Portugal
                [6 ] Institute of Evolutionary Biology, University of Edinburgh, Edinburgh, United Kingdom
                University of Auckland, Australia
                Author notes
                * To whom correspondence should be addressed. E-mail: philippe.lemey@ 123456zoo.ox.ac.uk
                Article
                06-PLCB-RA-0364R2 plcb-03-02-07
                10.1371/journal.pcbi.0030029
                1797821
                17305421
                6cb34fd5-85e3-468f-a327-288ae4e628dd
                Copyright: © 2007 Lemey et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
                History
                : 5 September 2006
                : 29 December 2006
                Page count
                Pages: 11
                Categories
                Research Article
                Computational Biology
                Computational Biology
                Computational Biology
                Genetics and Genomics
                Genetics and Genomics
                Mathematics
                Nematodes
                Custom metadata
                Lemey P, Kosakovsky Pond SL, Drummond AJ, Pybus OG, Shapiro B, et al. (2007) Synonymous substitution rates predict HIV disease progression as a result of underlying replication dynamics. PLoS Comput Biol 3(2): e29. DOI: 10.1371/journal.pcbi.0030029

                Quantitative & Systems biology
                Quantitative & Systems biology

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