1,721,293 research outputs found
The within- and among-host evolution of chronically-infecting human RNA viruses
Full text linkThis thesis examines the evolutionary biology of the RNA viruses, a diverse group of pathogens that cause significant diseases. The focus of this work is the relationship between the processes driving the evolution of virus populations within individual hosts and at the epidemic level. First, Chapter One reviews the basic biology of RNA viruses, the current state of knowledge in relevant topics of evolutionary virology, and the principles that underlie the most commonly used methods in this thesis. In Chapter Two, I develop and test a novel framework to estimate the significance of phylogeny-trait association in viral phylogenies. The method incorporates phylogenetic uncertainty through the use of posterior sets of trees (PST) produced in Bayesian MCMC analyses. In Chapter Three, I conduct a comprehensive analysis of the substitution rate of hepatitis C virus (HCV) in within- and between-host data sets using a relaxed molecular clock. I find that within-host substitution rates are more rapid than previously appreciated, that heterotachy is rife in within-host data sets, and that selection is likely to be a primary driver. In Chapter Four I apply the techniques developed in Chapter Two to successfully detect compartmentalization between peripheral blood and cervical tissues in a large data set of human immunodeficiency virus (HIV) patients. I propose that compartmentalization in the cervix is maintained by selection. I extend the framework developed in Chapter Two in Chapter Five and explore the Type II error of the statistics used. In Chapter Six I review the findings of this thesis and conclude with a general discussion of the relationship between within- and among-host evolution in viruses, and some of the limitations of current techniques
Virus evolution and transmission in an ever more connected world
No full textThe frequency and global impact of infectious disease outbreaks, particularly those caused by emerging viruses, demonstrate the need for a better understanding of how spatial ecology and pathogen evolution jointly shape epidemic dynamics. Advances in computational techniques and the increasing availability of genetic and geospatial data are helping to address this problem, particularly when both information sources are combined. Here, we review research at the intersection of evolutionary biology, human geography and epidemiology that is working towards an integrated view of spatial incidence, host mobility and viral genetic diversity. We first discuss how empirical studies have combined viral spatial and genetic data, focusing particularly on the contribution of evolutionary analyses to epidemiology and disease control. Second, we explore the interplay between virus evolution and global dispersal in more depth for two pathogens: human influenza A virus and chikungunya virus. We discuss the opportunities for future research arising from new analyses of human transportation and trade networks, as well as the associated challenges in accessing and sharing relevant spatial and genetic data
Correlating viral phenotypes with phylogeny: accounting for phylogenetic uncertainty.
No full textMany recent studies have sought to quantify the degree to which viral phenotypic characters (such as epidemiological risk group, geographic location, cell tropism, drug resistance state, etc.) are correlated with shared ancestry, as represented by a viral phylogenetic tree. Here, we present a new Bayesian Markov-Chain Monte Carlo approach to the investigation of such phylogeny-trait correlations. This method accounts for uncertainty arising from phylogenetic error and provides a statistical significance test of the null hypothesis that traits are associated randomly with phylogeny tips. We perform extensive simulations to explore and compare the behaviour of three statistics of phylogeny-trait correlation. Finally, we re-analyse two existing published data sets as case studies. Our framework aims to provide an improvement over existing methods for this problem
Are skyline plot-based demographic estimates overly dependent on smoothing prior assumptions?
Full text linkIn Bayesian phylogenetics, the coalescent process provides an informative framework for inferring dynamical changes in the effective size of a population from a sampled phylogeny (or tree) of its sequences. Popular coalescent inference methods such as the Bayesian Skyline Plot, Skyride and Skygrid all model this population size with a discontinuous, piecewise-constant likelihood but apply a smoothing prior to ensure that posterior population size estimates transition gradually with time. These prior distributions implicitly encode extra population size information that is not available from the observed coalescent tree (data). Here we present a novel statistic, Ω, to quantify and disaggregate the relative contributions of the coalescent data and prior assumptions to the resulting posterior estimate precision. Our statistic also measures the additional mutual information introduced by such priors. Using Ω we show that, because it is surprisingly easy to over-parametrise piecewise-constant population models, common smoothing priors can lead to overconfident and potentially misleading conclusions, even under robust experimental designs. We propose Ω as a useful tool for detecting when posterior estimate precision is overly reliant on prior choices
Investigating the endemic transmission of the hepatitis C virus
No full textThe hepatitis C virus (HCV) infects at least 3% of people worldwide and is a leading global cause of liver disease. Although HCV spread epidemically during the 20th century, particularly by blood transfusion, it has clearly been present in human populations for several centuries. Here we attempt to redress the paucity of investigation into how long-term endemic transmission of HCV has been maintained. Such transmission not only represents the 'natural' route of infection but also contributes to new infections today. As a first step, we investigate the hypothesis that HCV can be mechanically transmitted by biting arthropods. Firstly, we use a combined bioinformatic and geographic approach to build a spatial database of endemic HCV infection and demonstrate that this can be used to geographically compare endemic HCV with the range distributions of potential vector species. Second, we use models from mathematical epidemiology to investigate if the parameters that describe the biting behaviour of vectors are consistent with a proposed basic reproduction number (R0) for HCV, and with the sustained transmission of the virus by mechanical transmission. Our analyses indicate that the mechanical transmission of HCV is plausible and that much further research into endemic HCV is neede
The mode and tempo of hepatitis C virus evolution within and among hosts
Full text linkAbstract Background Hepatitis C virus (HCV) is a rapidly-evolving RNA virus that establishes chronic infections in humans. Despite the virus' public health importance and a wealth of sequence data, basic aspects of HCV molecular evolution remain poorly understood. Here we investigate three sets of whole HCV genomes in order to directly compare the evolution of whole HCV genomes at different biological levels: within- and among-hosts. We use a powerful Bayesian inference framework that incorporates both among-lineage rate heterogeneity and phylogenetic uncertainty into estimates of evolutionary parameters. Results Most of the HCV genome evolves at ~0.001 substitutions/site/year, a rate typical of RNA viruses. The antigenically-important E1/E2 genome region evolves particularly quickly, with correspondingly high rates of positive selection, as inferred using two related measures. Crucially, in this region an exceptionally higher rate was observed for within-host evolution compared to among-host evolution. Conversely, higher rates of evolution were seen among-hosts for functionally relevant parts of the NS5A gene. There was also evidence for slightly higher evolutionary rate for HCV subtype 1a compared to subtype 1b. Conclusions Using new statistical methods and comparable whole genome datasets we have quantified, for the first time, the variation in HCV evolutionary dynamics at different scales of organisation. This confirms that differences in molecular evolution between biological scales are not restricted to HIV and may represent a common feature of chronic RNA viral infection. We conclude that the elevated rate observed in the E1/E2 region during within-host evolution more likely results from the reversion of host-specific adaptations (resulting in slower long-term among-host evolution) than from the preferential transmission of slowly-evolving lineages.</p
Estimating the date of origin of an HIV-1 circulating recombinant form.
No full textHIV is capable of frequent genetic exchange through recombination. Despite the pandemic spread of HIV-1 recombinants, their times of origin are not well understood. We investigate the epidemic history of a HIV-1 circulating recombinant form (CRF) by estimating the time of the recombination event that lead to the emergence of CRF33_01B, a recently described recombinant descended from CRF01_AE and subtype B. The gag, pol and env genes were analyzed using a combined coalescent and relaxed molecular clock model, implemented in a Bayesian Markov chain Monte Carlo framework. Using linked genealogical trees we calculated the time interval between the common ancestor of CRF33_01B and the ancestors it shares with closely related parental lineages. The recombination event that generated CRF33_01B (t(rec)) occurred sometime between 1991 and 1993, suggesting that recombination is common in the early evolutionary history of HIV-1. The proof-of-concept approach provides a new tool for the investigation of HIV molecular epidemiology and evolution
The molecular epidemiology of HCV and related viruses in Africa
Full text linkHepatitis C virus (HCV) causes severe illness in millions of people worldwide, but the epidemic strains responsible for most infections arose within the past hundred years and represent only a small part of total HCV diversity. In this thesis I combine laboratory and computational methods to study HCV in Africa. I aim to characterize its current genetic diversity and its historical transmission prior to the global HCV epidemic. In Chapter 2 I begin by screening samples from the Democratic Republic of the Congo (DRC) for HCV and the related human pegivirus. I find high HCV sequence diversity, including a putative new subtype, and find significantly higher HCV prevalence in those born before 1950. Chapter 3 continues this screening, and combines the sequences obtained with those from online databases. Using molcular clock methods I estimate that genotype 4 originated in central Africa around 1733, and that multiple lineages, including subtype 4a which dominates the HCV epidemic in Egypt, have moved to north Africa since ~1850. In Chapter 4 I analyse sequences sampled from an elderly population in Kinshasa to estimate HCV’s transmission history there during the 20th century. The results indicate a rapid increase in HCV transmission between 1950 and 1970 in multiple independent lineages. Possible causes of this increase are discussed. This study population also exhibits high HCV genetic diversity, including the second genotype 7 sample discovered to date. Finally, Chapter 5 uses a range of sequencing techniques, including RNAseq, to characterise two putative HCV recombinants from Cameroon. I confirm that both sequences are recombinants, and generate a full genome sequence for one. I also develop new tools to distinguish between dual infection and recombination in next-generation sequencing data, and discuss how recombination might affect HCV diversity and treatment
The evolution of viral diversity
Full text linkThis thesis focuses on the population dynamics of three antigenically diverse RNA viruses: dengue, influenza and HIV-1. It comprises a set of studies highlighting the roles of structural constraints on critical antigenic determinants, interactions between immune responses to different antigenic types, host lifespan, and the degree of mixing between different host populations in determining the epidemiology and within-host dynamics of these pathogen systems.Dengue exists in humans as a collection of four antigenically related serotypes. Although infection by one serotype appears to convey life-long protection to homologous infection, it is believed to be a risk factor for severe disease manifestations upon secondary, heterologous infection due to the phenomenon of Antibody-Dependent Enhancement (ADE). It is not clear if third or fourth infections are possible, and if so, how they contribute to dengue epidemiology. In this thesis, I investigate the effect of third and fourth infections on the transmission dynamics of dengue.By contrast with dengue, human influenza viruses are known to be in rapid antigenic flux, manifesting in the sequential replacement of antigenic types. This pattern of evolution does not appear to be the same in shorter-lived hosts such as swine and birds. In this thesis, I have used a simple multi-locus model to explore the relationship between host lifespan and viral evolution, as well as to elucidate the effects of transmission between hosts of different lifespan in effort to capture the cross-species element of influenza transmission.My final chapter concerns the within-host evolution of HIV-1. I propose a new model for the pathogenesis of HIV-1 where the transition to AIDS is primarily linked to the gradual loss of the ability to make new antibody responses as the CD4+ population declines.Together these studies emphasise that it is the changing profile of immune responses – either at the population level or within the host – that is the principal determinant of the dynamics of the pathogen, rather than the mode and tempo of antigenic innovation
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