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Title: High-throughput analysis of the intestinal microbiota in Clostridium difficile-associated disease
Author: Berg, Adam Lewis
ISNI:       0000 0004 2744 3573
Awarding Body: University of Leicester
Current Institution: University of Leicester
Date of Award: 2013
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The nosocomial pathogen Clostridium difficile is normally unable to thrive in the human gut due to colonisation resistance. The presence of the normal intestinal bacteria prevents its proliferation through competition for nutrients, or via other mechanisms as yet unknown. Disruption of the standard flora of an individual as a result of antibiotic administration attenuates this resistance such that colonisation can occur. The resultant infection, Clostridium difficile-associated disease (CDAD), is potentially life-threatening, and represents a considerable financial and logistical burden for healthcare institutions. While exposure to the microbe is an absolute pre-requisite for development of the disease, other aspects of the epidemiology and pathogenesis of CDAD are as yet incompetely defined. However, the hypothesis at the core of the current research is that the composition of the microbiota may contribute to the multifactorial nature of the infection: certain individuals may have a microbiotic fingerprint which confers protection against the pathogen, while the flora of others means they are more susceptible to colonisation by Clostridium difficile. The aim of the current research was to investigate the microbiota of a number of individuals treated with antibiotics and subsequently falling into 3 distinct groups; those who contracted CDAD; those who developed diarrhoea not caused by Clostridium difficile; and those who displayed no evidence of intestinal disruption. To identify substantive differences between the groups it was essential to characterise the intestinal bacteria in a comprehensive manner, beyond the potential of existing techniques. Achievement of the research objective thus necessitated the development of novel array and sequencing approaches, along with complementary bioinformatic pipelines for analysis.
Supervisor: Ketley, Julian; Barer, Mike Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available