Use this URL to cite or link to this record in EThOS:
Title: Microbial and metabolic interactions in the Zucker rat
Author: Lees, Hannah
ISNI:       0000 0004 2736 9385
Awarding Body: Imperial College London
Current Institution: Imperial College London
Date of Award: 2013
Availability of Full Text:
Access from EThOS:
Access from Institution:
The metabolic syndrome is known to have a direct and indirect impact on endogenous metabolism. Additionally, there is emerging evidence of an obesity-associated microbiome with the potential to influence caloric extraction from the diet and host energy metabolism. However, the nature of the shift in relative contributions of bacterial phyla in obesity, and the question of whether the observed shift in microbiome is more associated with a high-fat diet than genetically induced obesity per se, are still yet to be fully elucidated. This thesis seeks to explore the relationship between obesity progression and the co-evolution of the intestinal microbiota, via profiling of host fluid and tissue metabolites, and faecal bacteria. The obese Zucker rat is characterised predominantly by obesity, insulin resistance and dyslipidaemia, and serves as an animal model of metabolic syndrome. The effect of mixed- strain housing of obese (fa/fa) and lean, (+/+) and (fa/+), Zucker rats on the evolution and development of the microbiome and metabolic phenotype of the animals over the course of ten weeks was investigated via 1H NMR spectroscopy of biofluids, faeces and tissue extracts, and metagenomic profiling of the intestinal microbiota via pyrosequencing of faecal samples. The collected data sets were evaluated and interrogated using a combination of multivariate and univariate statistical analyses to gain a comprehensive understanding of how age, genotype and cage environment affect endogenous metabolism and metabolic cross-talk between the host and intestinal microbiota. The nature of the interaction between host and microbiome remains poorly understood, particularly with respect to the development of obesity and metabolic syndrome. Here for the first time I have adopted a complex systems biology approach using multivariate statistical methods (principal components analysis (PCA) and orthogonal projections to latent structures discriminant analysis (OPLS-DA), for example) to identify correlations between host metabolism and faecal microbial composition during the development of obesity. Urinary and faecal metabolite changes were assessed over a period of ten weeks, with end point tissue and plasma composition assessed at 14 weeks of age. Urinary metabolic differences were apparent at week five and trajectory plots illustrated further divergence with age between the obese and lean strains. The two lean strains were found to be comparable metabolically, with both strains exhibiting a similar urinary metabolite trajectory over the ten-week sampling period. The analysis of faecal extracts demonstrated clear age-related variation across the ten-week period, however, only subtle variation relating to genotype and cage-environment were observed. Bacterial profiling showed clear age-related variation in the relative abundance of certain phyla and bacterial families dominated by an age-related three-fold increase in Bacteroidetes, with a concomitant decrease in Firmicutes. Differences relating to genotype were not evident at either the phylum or family level, whereas cage-environment-based clustering of samples was clearly apparent, with the most marked differences at weeks five and seven. With evidence of differences in urinary metabolites of host-microbiome co-metabolic origin found between the obese and lean animals, and no perceptible difference in the intestinal bacteria of the two phenotypes based on compositional profiling, these results suggest that the contribution of the microbiota to host metabolism is not straightforward but merits further investigation.
Supervisor: Holmes, Elaine ; Nicholson, Jeremy Sponsor: Biotechnology and Biological Sciences Research Council ; AstraZeneca (Firm)
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral