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Title: A systems biology approach to investigating host-pathogen interactions in infection with Burkholderia pseudomallei
Author: Cizmeci, Deniz
ISNI:       0000 0004 7653 2062
Awarding Body: University of Exeter
Current Institution: University of Exeter
Date of Award: 2017
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This thesis applies systems approaches in order better to understand host-pathogen interactions in infectious diseases; it focuses on the intracellular bacterium Burkholderia pseudomallei, the causative agent of the human disease melioidosis. Little is known about the epigenetic changes in host cells during infection. This study assesses genome-wide patterns of the epigenetic marker DNA methylation in host cells following infection with B. pseudomallei. The studies of this thesis concern the infection of human macrophage-like U937 cells with B. pseudomallei and the DNA methylation levels were measured during the early stages of infection. Analyses reveal significant changes in infected cells (compared to uninfected controls) at multiple locations in the host DNA. Most of the methylation changes in infected cells are losses rather than gains in methylation. Five different differential methylation patterns (constant, early, late, transient, and oscillatory) are identified. Differentially methylated sites mapped to genes that may affect virulence, e.g. genes involved in actin regulation, immune response, inflammatory response, and nitric oxide generation. The thesis also measures whole blood DNA methylation profiles of patients diagnosed with melioidosis in order to test the potential role of host DNA methylation in melioidosis. The results demonstrate that patients with melioidosis are separated from healthy subjects by their distinct methylation profiles. The differentially methylated regions reported here can potentially be used as biomarkers for classification and prognostication of infectious diseases. In addition to exploring the changes to the host, a comprehensive understanding of the pathogen interference and the search for countermeasures requires a framework that assesses how the host changes the pathogen metabolically. In this thesis, to understand the role of trehalose pathway in virulence, computational models were constructed by integrating kinetic information, genomics data and literature surveys. Existing kinetic models of the trehalose pathway were implemented and extended allowing for the in silico investigation of the trehalose mutant. Further, metabolic networks of B. pseudomallei were analysed at the genome scale to identify molecular links between trehalose and metabolic pathways such as glycolysis. The genome- scale reconstruction of the B. pseudomallei metabolic network was used to simulate growth under different conditions and predict the effects of gene knockouts. This thesis not only expands the existing knowledge about B. pseudomallei infection, the novel approaches employed here will stimulate a wider understanding of the applications of systems biology to host-pathogen research and defence needs.
Supervisor: Akman, Ozgur Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available