UCL Discovery
UCL home » Library Services » Electronic resources » UCL Discovery

Functional genomics, analysis of adaptation in and applications of models to the metabolism of engineered Escherichia coli

Bryant, W.A.; (2010) Functional genomics, analysis of adaptation in and applications of models to the metabolism of engineered Escherichia coli. Doctoral thesis , UCL (University College London). Green open access

[thumbnail of 19628.pdf]

Download (1MB)
[thumbnail of Supplementary Table 1] Excel Spreadsheet (Supplementary Table 1)

Download (3MB)
[thumbnail of Supplementary Table 2] Excel Spreadsheet (Supplementary Table 2)

Download (1MB)
[thumbnail of Supplementary Table 3] Excel Spreadsheet (Supplementary Table 3)

Download (341kB)
[thumbnail of Supplementary Table 4] Excel Spreadsheet (Supplementary Table 4)

Download (5MB)
[thumbnail of qry file  - combined presence ] Text (qry file - combined presence )

Download (2kB)
[thumbnail of sql file - iaf1260] Text (sql file - iaf1260)

Download (945kB)


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.

Type: Thesis (Doctoral)
Title: Functional genomics, analysis of adaptation in and applications of models to the metabolism of engineered Escherichia coli
Open access status: An open access version is available from UCL Discovery
Language: English
UCL classification: UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Biochemical Engineering
URI: https://discovery.ucl.ac.uk/id/eprint/19628
Downloads since deposit
Download activity - last month
Download activity - last 12 months
Downloads by country - last 12 months

Archive Staff Only

View Item View Item