6 resultados para DISEASE VIRUS

em Glasgow Theses Service


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The under-reporting of cases of infectious diseases is a substantial impediment to the control and management of infectious diseases in both epidemic and endemic contexts. Information about infectious disease dynamics can be recovered from sequence data using time-varying coalescent approaches, and phylodynamic models have been developed in order to reconstruct demographic changes of the numbers of infected hosts through time. In this study I have demonstrated the general concordance between empirically observed epidemiological incidence data and viral demography inferred through analysis of foot-and-mouth disease virus VP1 coding sequences belonging to the CATHAY topotype over large temporal and spatial scales. However a more precise and robust relationship between the effective population size (

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Understanding how virus strains offer protection against closely related emerging strains is vital for creating effective vaccines. For many viruses, including Foot-and-Mouth Disease Virus (FMDV) and the Influenza virus where multiple serotypes often co-circulate, in vitro testing of large numbers of vaccines can be infeasible. Therefore the development of an in silico predictor of cross-protection between strains is important to help optimise vaccine choice. Vaccines will offer cross-protection against closely related strains, but not against those that are antigenically distinct. To be able to predict cross-protection we must understand the antigenic variability within a virus serotype, distinct lineages of a virus, and identify the antigenic residues and evolutionary changes that cause the variability. In this thesis we present a family of sparse hierarchical Bayesian models for detecting relevant antigenic sites in virus evolution (SABRE), as well as an extended version of the method, the extended SABRE (eSABRE) method, which better takes into account the data collection process. The SABRE methods are a family of sparse Bayesian hierarchical models that use spike and slab priors to identify sites in the viral protein which are important for the neutralisation of the virus. In this thesis we demonstrate how the SABRE methods can be used to identify antigenic residues within different serotypes and show how the SABRE method outperforms established methods, mixed-effects models based on forward variable selection or l1 regularisation, on both synthetic and viral datasets. In addition we also test a number of different versions of the SABRE method, compare conjugate and semi-conjugate prior specifications and an alternative to the spike and slab prior; the binary mask model. We also propose novel proposal mechanisms for the Markov chain Monte Carlo (MCMC) simulations, which improve mixing and convergence over that of the established component-wise Gibbs sampler. The SABRE method is then applied to datasets from FMDV and the Influenza virus in order to identify a number of known antigenic residue and to provide hypotheses of other potentially antigenic residues. We also demonstrate how the SABRE methods can be used to create accurate predictions of the important evolutionary changes of the FMDV serotypes. In this thesis we provide an extended version of the SABRE method, the eSABRE method, based on a latent variable model. The eSABRE method takes further into account the structure of the datasets for FMDV and the Influenza virus through the latent variable model and gives an improvement in the modelling of the error. We show how the eSABRE method outperforms the SABRE methods in simulation studies and propose a new information criterion for selecting the random effects factors that should be included in the eSABRE method; block integrated Widely Applicable Information Criterion (biWAIC). We demonstrate how biWAIC performs equally to two other methods for selecting the random effects factors and combine it with the eSABRE method to apply it to two large Influenza datasets. Inference in these large datasets is computationally infeasible with the SABRE methods, but as a result of the improved structure of the likelihood, we are able to show how the eSABRE method offers a computational improvement, leading it to be used on these datasets. The results of the eSABRE method show that we can use the method in a fully automatic manner to identify a large number of antigenic residues on a variety of the antigenic sites of two Influenza serotypes, as well as making predictions of a number of nearby sites that may also be antigenic and are worthy of further experiment investigation.

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Dengue fever is one of the most important mosquito-borne diseases worldwide and is caused by infection with dengue virus (DENV). The disease is endemic in tropical and sub-tropical regions and has increased remarkably in the last few decades. At present, there is no antiviral or approved vaccine against the virus. Treatment of dengue patients is usually supportive, through oral or intravenous rehydration, or by blood transfusion for more severe dengue cases. Infection of DENV in humans and mosquitoes involves a complex interplay between the virus and host factors. This results in regulation of numerous intracellular processes, such as signal transduction and gene transcription which leads to progression of disease. To understand the mechanisms underlying the disease, the study of virus and host factors is therefore essential and could lead to the identification of human proteins modulating an essential step in the virus life cycle. Knowledge of these human proteins could lead to the discovery of potential new drug targets and disease control strategies in the future. Recent advances of high throughput screening technologies have provided researchers with molecular tools to carry out investigations on a large scale. Several studies have focused on determination of the host factors during DENV infection in human and mosquito cells. For instance, a genome-wide RNA interference (RNAi) screen has identified host factors that potentially play an important role in both DENV and West Nile virus replication (Krishnan et al. 2008). In the present study, a high-throughput yeast two-hybrid screen has been utilised in order to identify human factors interacting with DENV non-structural proteins. From the screen, 94 potential human interactors were identified. These include proteins involved in immune signalling regulation, potassium voltage-gated channels, transcriptional regulators, protein transporters and endoplasmic reticulum-associated proteins. Validation of fifteen of these human interactions revealed twelve of them strongly interacted with DENV proteins. Two proteins of particular interest were selected for further investigations of functional biological systems at the molecular level. These proteins, including a nuclear-associated protein BANP and a voltage-gated potassium channel Kv1.3, both have been identified through interaction with the DENV NS2A. BANP is known to be involved in NF-kB immune signalling pathway, whereas, Kv1.3 is known to play an important role in regulating passive flow of potassium ions upon changes in the cell transmembrane potential. This study also initiated a construction of an Aedes aegypti cDNA library for use with DENV proteins in Y2H screen. However, several issues were encountered during the study which made the library unsuitable for protein interaction analysis. In parallel, innate immune signalling was also optimised for downstream analysis. Overall, the work presented in this thesis, in particular the Y2H screen provides a number of human factors potentially targeted by DENV during infection. Nonetheless, more work is required to be done in order to validate these proteins and determine their functional properties, as well as testing them with infectious DENV to establish a biological significance. In the long term, data from this study will be useful for investigating potential human factors for development of antiviral strategies against dengue.

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Serosurveillance is a powerful tool fundamental to understanding infectious disease dynamics. The presence of virus neutralising antibody (VNAb) in sera is considered the best evidence of infection, or indeed vaccination, and the gold standard serological assay for their detection is the virus neutralisation test (VNT). However, VNTs are labour intensive, costly and time consuming. In addition, VNTs for the detection of antibodies to highly pathogenic viruses require the use of high containment facilities, restricting the application of these assays to the few laboratories with adequate facilities. As a result, robust serological data on such viruses are limited. In this thesis I develop novel VNTs for the detection of VNAb to two important, highly pathogenic, zoonotic viruses; rabies and Rift Valley fever virus (RVFV). The pseudotype-based neutralisation test developed in this study allows for the detection of rabies VNAb without the requirement for high containment facilities. This assay was utilised to investigate the presence of rabies VNAb in animals from a variety of ecological settings. In this thesis I present evidence of natural rabies infection in both domestic dogs and lions from rabies endemic settings. The assay was further used to investigate the kinetics of VNAb response to rabies vaccination in a cohort of free-roaming dogs. The RVFV neutralisation assay developed herein utilises a recombinant luciferase expressing RVFV, which allows for rapid, high-throughput serosurveillance of this important neglected pathogen. In this thesis I present evidence of RVFV infection in a variety of domestic and wildlife species from Northern Tanzania, in addition to the detection of low-level transmission of RVFV during interepidemic periods. Additionally, the investigation of a longitudinal cohort of domestic livestock also provided evidence of rapid waning of RVF VNAb following natural infection. Collectively, the serological data presented in this thesis are consistent with existing data in the literature generated using the gold standard VNTs. Increasing the availability of serological assays will allow the generation of robust serological data, which are imperative to enhancing our understanding of the complex, multi-host ecology of these two viruses.

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Foot-and-mouth disease (FMD), a disease of cloven hooved animals caused by FMD virus (FMDV), is one of the most economically devastating diseases of livestock worldwide. The global burden of disease is borne largely by livestock-keepers in areas of Africa and Asia where the disease is endemic and where many people rely on livestock for their livelihoods and food-security. Yet, there are many gaps in our knowledge of the drivers of FMDV circulation in these settings. In East Africa, FMD epidemiology is complicated by the circulation of multiple FMDV serotypes (distinct antigenic variants) and by the presence of large populations of susceptible wildlife and domestic livestock. The African buffalo (Syncerus caffer) is the only wildlife species with consistent evidence of high levels of FMDV infection, and East Africa contains the largest population of this species globally. To inform FMD control in this region, key questions relate to heterogeneities in FMD prevalence and impacts in different livestock management systems and to the role of wildlife as a potential source of FMDV for livestock. To develop FMD control strategies and make best use of vaccine control options, serotype-specific patterns of circulation need to be characterised. In this study, the impacts and epidemiology of FMD were investigated across a range of traditional livestock-keeping systems in northern Tanzania, including pastoralist, agro-pastoralist and rural smallholder systems. Data were generated through field studies and laboratory analyses between 2010 and 2015. The study involved analysis of existing household survey data and generated serological data from cross-sectional livestock and buffalo samples and longitudinal cattle samples. Serological analyses included non-structural protein ELISAs, serotype-specific solid-phase competitive ELISAs, with optimisation to detect East African FMDV variants, and virus neutralisation testing. Risk factors for FMDV infection and outbreaks were investigated through analysis of cross-sectional serological data in conjunction with a case-control outbreak analysis. A novel Bayesian modeling approach was developed to infer serotype-specific infection history from serological data, and combined with virus isolation data from FMD outbreaks to characterise temporal and spatial patterns of serotype-specific infection. A high seroprevalence of FMD was detected in both northern Tanzanian livestock (69%, [66.5 - 71.4%] in cattle and 48.5%, [45.7-51.3%] in small ruminants) and in buffalo (80.9%, [74.7-86.1%]). Four different serotypes of FMDV (A, O, SAT1 and SAT2) were isolated from livestock. Up to three outbreaks per year were reported by households and active surveillance highlighted up to four serial outbreaks in the same herds within three years. Agro-pastoral and pastoral livestock keepers reported more frequent FMD outbreaks compared to smallholders. Households in all three management systems reported that FMD outbreaks caused significant impacts on milk production and sales, and on animals’ draught power, hence on crop production, with implications for food security and livelihoods. Risk factor analyses showed that older livestock were more likely to be seropositive for FMD (Odds Ratio [OR] 1.4 [1.4-1.5] per extra year) and that cattle (OR 3.3 [2.7-4.0]) were more likely than sheep and goats to be seropositive. Livestock managed by agro-pastoralists (OR 8.1 [2.8-23.6]) or pastoralists (OR 7.1 [2.9-17.6]) were more likely to be seropositive compared to those managed by smallholders. Larger herds (OR: 1.02 [1.01-1.03] per extra bovine) and those that recently acquired new livestock (OR: 5.57 [1.01 – 30.91]) had increased odds of suffering an FMD outbreak. Measures of potential contact with buffalo or with other FMD susceptible wildlife did not increase the likelihood of FMD in livestock in either the cross-sectional serological analysis or case-control outbreak analysis. The Bayesian model was validated to correctly infer from ELISA data the most recent serotype to infect cattle. Consistent with the lack of risk factors related to wildlife contact, temporal and spatial patterns of exposure to specific FMDV serotypes were not tightly linked in cattle and buffalo. In cattle, four serial waves of different FMDV serotypes that swept through southern Kenyan and northern Tanzanian livestock populations over a four-year period dominated infection patterns. In contrast, only two serotypes (SAT1 and SAT2) dominated in buffalo populations. Key conclusions are that FMD has a substantial impact in traditional livestock systems in East Africa. Wildlife does not currently appear to act as an important source of FMDV for East African livestock, and control efforts in the region should initially focus on livestock management and vaccination strategies. A novel modeling approach greatly facilitated the interpretation of serological data and may be a potent epidemiological tool in the African setting. There was a clear temporal pattern of FMDV antigenic dominance across northern Tanzania and southern Kenya. Longer-term research to investigate whether serotype-specific FMDV sweeps are truly predictable, and to shed light on FMD post-infection immunity in animals exposed to serial FMD infections is warranted.

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Arboviruses (Arthropod-borne viruses) cause acute diseases that are increasingly affecting both human and animal health. Currently, there is a critical lack of understanding about the nature of arbovirus-host interactions in the lymph nodes (LNs), the place where the adaptive immune response is initiated and shaped. In this study, we used bluetongue virus (BTV) and its natural sheep host, to characterise the early events of an arbovirus infection with particular focus on the LNs. Our findings reveal a previously uncharacterized mechanism used by an arbovirus to manipulate host immunity. This study shows that BTV, similarly to other antigens delivered through the skin, is transported rapidly via the lymph to the peripheral lymph nodes. Here, BTV infects and disrupts the stromal network of marginal reticular cells and follicular dendritic cells composing the scaffolding of the follicular area. These cells contribute to antigen presentation and affinity maturation of B-cells for the production of antibodies. Consequently, we observed a loss of germinal centre structure, which hinders B-cell proliferation. This process results in a delayed production of high affinity and virus neutralizing antibodies that is directly related to the virulence of the BTV strain used and the severity of disease. Moreover the humoral immune response to a different antigen is also hampered in BTV-infected animals. Our data show that an arbovirus can evade the host antiviral responses by inducing an acute immunosuppression. Although transient, this immunosuppression occurs at the critical early stages of infection when a delayed host humoral immune response likely affects virus systemic dissemination and the clinical outcome of disease.