Selection and optimization of gene targets for the metabolic engineering of E. coli
Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Chemical Engineering, 2009.
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| Format: | Thesis |
| Language: | eng |
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Massachusetts Institute of Technology
2010
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| Online Access: | http://hdl.handle.net/1721.1/51566 |
| _version_ | 1811076412015116288 |
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| author | Fischer, Curt R., Ph. D. Massachusetts Institute of Technology |
| author2 | Gregory N. Stephanopoulos. |
| author_facet | Gregory N. Stephanopoulos. Fischer, Curt R., Ph. D. Massachusetts Institute of Technology |
| author_sort | Fischer, Curt R., Ph. D. Massachusetts Institute of Technology |
| collection | MIT |
| description | Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Chemical Engineering, 2009. |
| first_indexed | 2024-09-23T10:21:21Z |
| format | Thesis |
| id | mit-1721.1/51566 |
| institution | Massachusetts Institute of Technology |
| language | eng |
| last_indexed | 2024-09-23T10:21:21Z |
| publishDate | 2010 |
| publisher | Massachusetts Institute of Technology |
| record_format | dspace |
| spelling | mit-1721.1/515662019-04-11T14:12:38Z Selection and optimization of gene targets for the metabolic engineering of E. coli Selection and optimization of gene targets for the metabolic engineering of Microorganisms Fischer, Curt R., Ph. D. Massachusetts Institute of Technology Gregory N. Stephanopoulos. Massachusetts Institute of Technology. Dept. of Chemical Engineering. Massachusetts Institute of Technology. Dept. of Chemical Engineering. Chemical Engineering. Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Chemical Engineering, 2009. Includes bibliographical references. This thesis is about identifying genetic interventions that improve the performance of targeted pathways in the metabolism of the bacterium Escherichia coli. Three case studies illustrate three disparate approaches to identifying genetic interventions: (i) combining metabolomic measurements with thermodynamic calculations to identify rate-limiting reaction steps in a target pathway; (ii) use of stoichiometric, optimization-based models of metabolism to predict target genetic interventions in silico; and (iii) the mutagenesis of promoter sequences to fine-tune the expression level of rate-limiting genes. These techniques can be classified by both the number of strain modifications created, and the number of variables measured in each. Taken together, the cases suggest that the best methods for identifying genetic interventions balance the number of strain modifications with the number of measured variables. The first case is butyrate production in recombinant E. coli. A strain of E. coli deleted for the production of lactate, ethanol, and acetate was designed to minimize competing pathways for carbon, and was unexpectedly found to exhibit oxygen auxotrophy. Expression of genes from Clostridium acetobutylicum resulted in production of 3-hydroxybutyric acid, but not butyric acid. (cont.) The clostridial genes ptb and buk were capable of producing S-3-hydroxybutyric acid from the butyrate pathway intermediate metabolite S-3-hydroxybutyryl-CoA. In parallel, the intracellular concentrations of pathway metabolites was measured for a set of strains expressing the clostridial butanol biosynthesis pathway in various configurations. Comparison of measured pool sizes and pool sizes for thermodynamic equilibrium pinpointed the butyryl-CoA dehydrogenase step, encoded by bcd, as a bottleneck enzyme. Thus, points for genetic intervention are ptb, buk, and bcd. The second case is tyrosine overproduction in E. coli. Constraints-based models of E. coli metabolism proved incapable of predicting gene knockout targets. Therefore, to understand factors underlying tyrosine overproduction, the intracellular concentrations of amino acids were measured. In tyrosine overproducers, the intracellular concentrations of most proteinogenic amino acids were vastly perturbed relative to non-producing strains. This fact and thermodynamic considerations suggested that the transamination of p-hydroxyphenylpyruvate to tyrosine was near equilibrium, and thus that nitrogen supply may be limiting tyrosine production. Culture media amended with glutamate or glutamine, but not with a-ketoglutarate or other organic acids, increased tyrosine production in these strains more than 8-fold, showing that interventions which affect nitrogen supply are attractive targets for engineering tyrosine overproduction in E. coli. The last case addresses the question of what types of intervention are best. A series of 22 promoters with well-characterized, variable strengths was created by mutagenesis. This library was used to replace promoters for key genes in the biosynthesis of lycopene or biomass from glucose. These metabolic phenotypes exhibited strain-dependent optima with respect to the expression levels of the key rate-controlling genes genes. Promoter engineering thus shows that subtle genetic interventions can have profound effects on pathway function. by Curt R. Fischer. Ph.D. 2010-02-09T16:45:39Z 2010-02-09T16:45:39Z 2009 2009 Thesis http://hdl.handle.net/1721.1/51566 471480161 eng M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission. http://dspace.mit.edu/handle/1721.1/7582 220 leaves application/pdf Massachusetts Institute of Technology |
| spellingShingle | Chemical Engineering. Fischer, Curt R., Ph. D. Massachusetts Institute of Technology Selection and optimization of gene targets for the metabolic engineering of E. coli |
| title | Selection and optimization of gene targets for the metabolic engineering of E. coli |
| title_full | Selection and optimization of gene targets for the metabolic engineering of E. coli |
| title_fullStr | Selection and optimization of gene targets for the metabolic engineering of E. coli |
| title_full_unstemmed | Selection and optimization of gene targets for the metabolic engineering of E. coli |
| title_short | Selection and optimization of gene targets for the metabolic engineering of E. coli |
| title_sort | selection and optimization of gene targets for the metabolic engineering of e coli |
| topic | Chemical Engineering. |
| url | http://hdl.handle.net/1721.1/51566 |
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