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Title: Molecular biology of antibiotic resistance elements in human Haemophilus spp.
Author: Zain, Zaini Mohd
ISNI:       0000 0001 3413 8831
Awarding Body: University of Oxford
Current Institution: University of Oxford
Date of Award: 2004
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Antibiotic resistance in Haemophilus influenzae emerged in the 1970s and rapidly rose in prevalence worldwide. The principal source of resistance was a large conjugative resistance element often referred to as a plasmid. The origins of this resistance element that integrates and conjugates have not been determined. The main aim of this thesis was to investigate the origin of this integrative and conjugative element (ICE) through comparative analysis of whole sequenced elements. Two Haemophilus resistance ICEs, ICEHin1056, from the UK, and ICEHin299, from Greece, were completely sequenced. Two further ICEs, ICEHin2866 from the USA and ICEHpa8F from a UK Haemophilus parainfluenzae were compared. These ICEs consisted of highly homologous sequences that were predicted to form functional modules. The properties of these predicted modules accounted for replication, conjugation and integrative and excisive recombination with tRNAleu. As the sequence diversity of resistance associated genes common to these ICEs were highly conserved compared to core ICE sequences they probably have been recently acquired by these ICEs suggesting a relatively recent origin. Further comparative analysis of these ICEs revealed a common evolutionary origin with genomic islands (GIs) found among bacteria belonging to β- and γ-Proteobacteria. These GIs share coherently organised core genes indicating that they have originated from a distant common ancestor. This finding contradicts the hypothesis that GIs were derived from independently evolving modules. Furthermore, the preservation of a coherent core gene structure between distantly related GIs suggests these core genes acting together confer a particular fitness advantage, which has contributed to the dissemination of adaptive genes such as antibiotic resistance genes. The methods used to compare these genomic islands could in the future be used to classify all genomic islands.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available