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Title: Identification of biomarkers in protection against bovine tuberculosis through global gene expression analysis in vaccinated and infected mice and cattle
Author: Aranday-Cortes, Elihu
ISNI:       0000 0004 2724 5761
Awarding Body: Imperial College London
Current Institution: Imperial College London
Date of Award: 2012
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Bovine tuberculosis (bTB) is a chronic disease of cattle caused by Mycobacterium bovis, a member of the Mycobacterium tuberculosis complex group of bacteria. bTB infection in cattle is not uniformly distributed throughout Great Britain but concentrated in the southwest of England and Wales. Vaccination of cattle might offer a long-term solution for controlling the disease and priority has been given to the development of a cattle vaccine against bTB. Identification of biomarkers in tuberculosis research remains elusive and the goal of this project is to identify host correlates of protection and biomarkers of progressive bTB in cattle. Previous work in cattle has revealed three distinct stages following vaccination and challenge with bTB: immune responses following vaccination; early protective anamnestic responses after M. bovis infection in protected cattle; and late responses indicative of progressive disease in unprotected animals. These three stages can be replicated in our mouse model of M. bovis infection. Therefore, we hypothesized that by studying global gene expression during these stages we will identify, respectively, predictors of protection, correlates of protective immunity, and biomarkers of pathology. Because both cattle and mice present these three stages, mice were used for genome-wide expression profiling of systemic responses after BCG vaccination and M. bovis infection to identify candidate biomarkers of protective immunity. RNA was prepared from spleen cells of vaccinated and control mice prior and post-M. bovis challenge. Global gene expression was determined using murine microarrays, and candidate genes identified were validated in cattle by RT-QPCR. After BCG vaccination, we defined a specific pulmonary gene expression signature related to the connective tissue development and function network that predicted vaccine success before M. bovis challenge. In addition, a Th17-related cytokine profile was found that correlated with vaccine-induced protective immunity following infection with virulent M. bovis in the lung as well as additional genes that were up-regulated in the spleens of vaccinated animals post-infection related to neutrophil biology and inflammation. In antigen-stimulated splenocytes we found statistically significant modulation of 1109 genes early after infection and 1134 at later time-point post-infection. 618 of these genes were modulated at both time points. In the lung 282 genes were significantly modulated in animals post-infection. Amongst the most strongly up-regulated genes were GzmA in spleen, and Cxcl9 and IL-22 in lungs. The expression of the most up-regulated genes identified in the murine studies were evaluated using PBMC from BCG vaccinated and unvaccinated calves prior and post experimental infection; and uninfected and naturally infected cattle. Thus, we confirmed that the expression of IFN-γ IL-17, IL-22, Cxcl10 and Ido1 predicted vaccine success and correlated with protection. Cxcl9, GzmA and IL-22 following in vitro stimulation with PPD was significantly increased in infected cows compared to naïve animals. Thus, we have demonstrated that murine transcriptome analysis can be used to predict the responses in cattle. This study has therefore prioritized both biomarkers predicting vaccination success before challenge, biosignatures that are potentially associated with protective immune responses after challenge and biomarkers of pathology that will be useful to evaluate future vaccine candidates. Key words: Bovine tuberculosis, host responses, vaccination, diagnosis, host transcriptome, microarrays
Supervisor: Vordermeier, Martin ; Lalvani, Ajit ; Hingley-Wilson, Suzie Sponsor: Department for Environment, Food & Rural Affairs ; Consejo Nacional de Ciencia y Tecnologia (Mexico)
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral