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Title: Functional genomics, analysis of adaptation in, and applications of models to, the metabolism of engineered Escherichia coli
Author: Bryant, W. A.
ISNI:       0000 0004 2727 3287
Awarding Body: University College London (University of London)
Current Institution: University College London (University of London)
Date of Award: 2010
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In order to examine the metabolism of bacteria in the genus Enterobacteriaceae tools for gene complement comparison and stoichiometric model building have been developed to take advantage of both the number of complete bacterial genome sequences currently available and the relationship between genes and metabolism. A functional genomic approach to improving knowledge of the metabolism of Escherichia coli CFT073 (a uropathogen) has been undertaken taking into account not only its genome sequence, but its close relationship to E. coli MG1655. A fresh comparison of E. coli CFT073 has been done with E. coli MG1655 to identify all those genes in CFT073 that are not present in MG1655 and may have metabolic characteristics. These genes have further been bioinformatically assessed to determine whether they might encode enzymes for the metabolism of chemicals commonly found in human urine, and one set of such genes has been experimentally confirmed to encode an L-sorbose utilisation pathway. Little experimental work has been done as yet to elucidate how bacteria adaptively respond to the introduction of heterologous metabolic genes. To investigate how bacteria respond to such DNA, genes encoding the L-sorbose utilisation and uptake operon from CFT073 have been cloned and transformed into DH5 and a selective pressure (minimal medium with L-sorbose as sole carbon source) has been applied over 100 generations of growth of this strain in serial passage to investigate the change in its behaviour. The availability of large numbers of completely sequenced genomes, along with the development of a stoichiometric metabolic model with very high coverage of E. coli metabolism (iAF1260 [1]) have made possible the analysis of the core metabolism of large numbers of bacteria to investigate gene essentiality in these bacteria. A novel way of assessing gene complement has been developed using BLAST and DiagHunter to improve reliability of gene synteny comparisons with contextual information about the genes and to extend work by others to cover all E. coli and Shigella genome sequences with available sequences on GanBank (as of 1st June 2009) in order to bioinformatically investigate essential genes in these bacteria and the heterogeneity of their metabolic networks. Further to this a metabolic model has been constructed for DH5 with an added L-sorbose pathway and for CFT073 and these models have been used to investigate behavioural changes during adaptation of bacteria to novel heterologous genes.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available