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      Phylodynamics of HIV-1 Subtype B among the Men-Having-Sex-with-Men (MSM) Population in Hong Kong

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          Abstract

          The men-having-sex-with-men (MSM) population has become one of the major risk groups for HIV-1 infection in the Asia Pacific countries. Hong Kong is located in the centre of Asia and the transmission history of HIV-1 subtype B transmission among MSM remained unclear. The aim of this study was to investigate the transmission dynamics of HIV-1 subtype B virus in the Hong Kong MSM population. Samples of 125 HIV-1 subtype B infected MSM patients were recruited in this study. Through this study, the subtype B epidemic in the Hong Kong MSM population was identified spreading mainly among local Chinese who caught infection locally. On the other hand, HIV-1 subtype B infected Caucasian MSM caught infection mainly outside Hong Kong. The Bayesian phylogenetic analysis also indicated that 3 separate subtype B epidemics with divergence dates in the 1990s had occurred. The first and latest epidemics were comparatively small-scaled; spreading among the local Chinese MSM while sauna-visiting was found to be the major sex partner sourcing reservoir for the first subtype B epidemic. However, the second epidemic was spread in a large-scale among local Chinese MSM with a number of them having sourced their sex partners through the internet. The epidemic virus was estimated to have a divergence date in 1987 and the infected population in Hong Kong had a logistic growth throughout the past 20 years. Our study elucidated the evolutionary and demographic history of HIV-1 subtype B virus in Hong Kong MSM population. The understanding of transmission and growth model of the subtype B epidemic provides more information on the HIV-1 transmission among MSM population in other Asia Pacific high-income countries.

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          MRBAYES: Bayesian inference of phylogenetic trees.

          J P Huelsenbeck, F Ronquist (2001)
          The program MRBAYES performs Bayesian inference of phylogeny using a variant of Markov chain Monte Carlo. MRBAYES, including the source code, documentation, sample data files, and an executable, is available at http://brahms.biology.rochester.edu/software.html.
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            Bayesian phylogenetic analysis of combined data.

            Johan Nylander, Fredrik Ronquist, John P. Huelsenbeck … (2004)
            The recent development of Bayesian phylogenetic inference using Markov chain Monte Carlo (MCMC) techniques has facilitated the exploration of parameter-rich evolutionary models. At the same time, stochastic models have become more realistic (and complex) and have been extended to new types of data, such as morphology. Based on this foundation, we developed a Bayesian MCMC approach to the analysis of combined data sets and explored its utility in inferring relationships among gall wasps based on data from morphology and four genes (nuclear and mitochondrial, ribosomal and protein coding). Examined models range in complexity from those recognizing only a morphological and a molecular partition to those having complex substitution models with independent parameters for each gene. Bayesian MCMC analysis deals efficiently with complex models: convergence occurs faster and more predictably for complex models, mixing is adequate for all parameters even under very complex models, and the parameter update cycle is virtually unaffected by model partitioning across sites. Morphology contributed only 5% of the characters in the data set but nevertheless influenced the combined-data tree, supporting the utility of morphological data in multigene analyses. We used Bayesian criteria (Bayes factors) to show that process heterogeneity across data partitions is a significant model component, although not as important as among-site rate variation. More complex evolutionary models are associated with more topological uncertainty and less conflict between morphology and molecules. Bayes factors sometimes favor simpler models over considerably more parameter-rich models, but the best model overall is also the most complex and Bayes factors do not support exclusion of apparently weak parameters from this model. Thus, Bayes factors appear to be useful for selecting among complex models, but it is still unclear whether their use strikes a reasonable balance between model complexity and error in parameter estimates.
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              Bayesian selection of continuous-time Markov chain evolutionary models.

              M. Suchard, R Weiss, J Sinsheimer (2001)
              We develop a reversible jump Markov chain Monte Carlo approach to estimating the posterior distribution of phylogenies based on aligned DNA/RNA sequences under several hierarchical evolutionary models. Using a proper, yet nontruncated and uninformative prior, we demonstrate the advantages of the Bayesian approach to hypothesis testing and estimation in phylogenetics by comparing different models for the infinitesimal rates of change among nucleotides, for the number of rate classes, and for the relationships among branch lengths. We compare the relative probabilities of these models and the appropriateness of a molecular clock using Bayes factors. Our most general model, first proposed by Tamura and Nei, parameterizes the infinitesimal change probabilities among nucleotides (A, G, C, T/U) into six parameters, consisting of three parameters for the nucleotide stationary distribution, two rate parameters for nucleotide transitions, and another parameter for nucleotide transversions. Nested models include the Hasegawa, Kishino, and Yano model with equal transition rates and the Kimura model with a uniform stationary distribution and equal transition rates. To illustrate our methods, we examine simulated data, 16S rRNA sequences from 15 contemporary eubacteria, halobacteria, eocytes, and eukaryotes, 9 primates, and the entire HIV genome of 11 isolates. We find that the Kimura model is too restrictive, that the Hasegawa, Kishino, and Yano model can be rejected for some data sets, that there is evidence for more than one rate class and a molecular clock among similar taxa, and that a molecular clock can be rejected for more distantly related taxa.
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                Author and article information

                Contributors
                : Role: Editor
                Journal
                Journal ID (nlm-ta): PLoS One
                Journal ID (publisher-id): plos
                Journal ID (pmc): plosone
                Title: PLoS ONE
                Publisher: Public Library of Science (San Francisco, USA )
                ISSN (Electronic): 1932-6203
                Publication date Collection: 2011
                Publication date (Electronic): 22 September 2011
                Volume: 6
                Issue: 9
                Electronic Location Identifier: e25286
                Affiliations
                [1 ]Department of Microbiology, Queen Mary Hospital, the University of Hong Kong, Hong Kong Special Administrative Region, China
                [2 ]Integrated Treatment Centre, Special Preventive Programme, Centre of Health Protection, Department of Health, Hong Kong Special Administrative Region, China
                [3 ]AIDS Institute, the University of Hong Kong, Hong Kong Special Administrative Region, China
                McGill University, Canada
                Author notes

                Conceived and designed the experiments: JC W-CY. Performed the experiments: JC ST W-CY. Analyzed the data: JC K-HW KC ZC W-CY. Contributed reagents/materials/analysis tools: W-CY K-HW KC. Wrote the paper: JC ST WC.

                Article
                Publisher ID: PONE-D-11-09060
                DOI: 10.1371/journal.pone.0025286
                PMC ID: 3178636
                PubMed ID: 21966483
                SO-VID: 55a235b2-3c77-4f9c-bffa-5ddd5de3d440
                Copyright © Chen 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
                Date received : 23 May 2011
                Date accepted : 31 August 2011
                Page count
                Pages: 7
                Categories
                Subject: Research Article
                Subject: Biology
                Subject: Population Biology
                Subject: Epidemiology
                Subject: Infectious Disease Epidemiology
                Subject: Medicine
                Subject: Epidemiology
                Subject: Infectious Disease Epidemiology
                Subject: Infectious Diseases
                Subject: Sexually Transmitted Diseases
                Subject: AIDS
                Subject: Viral Diseases
                Subject: HIV
                Subject: HIV epidemiology
                Subject: Obstetrics and Gynecology
                Subject: Genitourinary Infections
                Subject: HIV
                Subject: Urology
                Subject: Genitourinary Infections
                Subject: HIV

                ScienceOpen disciplines: Uncategorized
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                ScienceOpen disciplines: Uncategorized

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