Use this URL to cite or link to this record in EThOS: https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.501199
Title: Metabonomic characterisation of host-parasite interactions in vivo
Author: Li, Jia
ISNI:       0000 0004 2670 9923
Awarding Body: Imperial College London
Current Institution: Imperial College London
Date of Award: 2009
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Abstract:
Parasitic diseases, particularly prevalent in tropics, impact severely on public health. This thesis presents a metabolism-driven top-down systems biology approach to characterise metabolic changes in mice resulting from parasitic infections, specifically Plasmodium berghei and Schistosoma mansoni. A metabolic profiling approach has been applied to characterise dynamic metabolic changes induced by parasitic infections and to examine changes associated with therapeutic intervention for the infection. The strategy consists of 3 steps: (1) development of animal models: where biofluid samples were collected at different experimental time points and tissues were obtained at the end point of experiments. Randomised housing of mice, consistent environmental conditions and strict sampling time were adhered to in order to minimise the environment, stress and diurnal variation which can cause bias in metabolic profiles; (2) sample acquisition: where all biofluid samples were analysed by high-resolution 1H nuclear magnetic resonance (NMR) spectroscopy and tissue samples were analysed by 1H magic angle spinning NMR spectroscopy. Two-dimensional NMR experiments such as correlation spectroscopy and total correlation spectroscopy were carried out on selected samples to aid the identification of metabolites; (3) multivariate data analyses including both unsupervised (principal component analysis) and supervised (orthogonal-projection to latent structures-discriminant analysis) methods. Various multivariate statistical strategies were used to characterise infection-related changes in metabolism at the system level across multiple biofluids and tissues. For both S. mansoni and P. berghei infections the metabolic response included changes in energy metabolism, inflammatory responses and gut microbiota metabolites. The effect of treatment with vancomycin was also assessed in order to further explore the gut microbiota changes. Time-course changes in mouse gut microbial community after vancomycin treatment were monitored using 16S rRNA gene polymerase chain reaction-denaturing gradient gel electrophoresis (PCR-DGGE) analysis of the faeces. The integration of the microbial and DGGE data helped to promote understanding of the microbial-mammalian metabolic axis.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.501199  DOI: Not available
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