Development of systematic and combinatorial approaches for the metabolic engineering of microorganisms

Explorations and optimizations through the genomic space are a daunting undertaking given the complexity and size of the possible search space. To approach this problem, systematic and combinatorial approaches were employed for the engineering of cellular phenotype in Escherichia coli. Initially, a computational method based on global cellular stoichiometry was employed to identify single and multiple gene knockout targets for lycopene production in E. coli. These targets led to substantial increases in lycopene production, but were limited in scope due to the nature of these models. Therefore, these approaches and targets were complemented with combinatorial searches to identify unknown and regulatory targets. When combined, these searches led to further increases of lycopene production and allowed for the visualization of the resulting metabolic landscape. A more exhaustive search was conducted in the background of eight genotypes which resulted in the formulation of the gene knockout search network. This network enables the investigation into how phenotype optimization is biased by search strategy.

Department dc:contributor.department

Massachusetts Institute of Technology. Dept. of Chemical Engineering.

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2006

Author dc:creator

• Alper, Hal (Hal Samuel)

Advisor dc:contributor.advisor

• Gregory Stephanopoulos.

• Chemical Engineering.

Statement dc:rights

• 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.

Licence dc:rights.uri

• http://dspace.mit.edu/handle/1721.1/35134
• http://dspace.mit.edu/handle/1721.1/7582

Language dc:language.iso

eng

Identifier URI

http://dspace.mit.edu/handle/1721.1/35134

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/35134