UC San Diego

Metabolic engineering of microorganisms will be necessary to advance mankind over the coming centuries. Systems biology has the potential to significantly aide in this effort through design, interpretation, and expansion of experimental implementation. This dissertation outlines work towards advancing the field of systems biology, in general, and specifically focuses on applying this technology to metabolically engineer the bacterium Escherichia coli. The first part of this thesis dissertation focuses on the impact of systems biology in science and engineering through an introduction of the topic and demonstration of systems biology case studies centered on the reconstruction of E. coli metabolism. The history of reconstruction of E. coli metabolism prior to and since the genomic era is presented and provides the scope of the fundamental biological platform, the metabolic reconstruction, for which later computations are based. The process and product of network reconstruction and the developed methods necessary for validation and use are outlined. The second part of the thesis dissertation describes the generation, properties, and biological characterization of two organism-specific genome-scale metabolic reconstructions. These reconstructions are for an environmentally important archaea, Methanosarcina barkeri, and the aforementioned bacteria and model organism, E. coli. The transformation of these reconstructions to computational models is presented along with validation of modeling results through comparison with experimental data. Demonstrations of the utility of metabolic reconstructions as platforms for systems analyses to answer biological questions are presented in application specific examples. The third part of this thesis dissertation describes how the generated metabolic reconstruction of E. coli was used for model-driven metabolic engineering. A computation evaluation of the production potential for native products of E. coli from different feedstocks is presented. This study characterizes the range and number of products that can be coupled to growth in E. coli. Lastly, the in vivo construction, evolution, and characterization of strains computationally designed from this analysis are presented for validation of approach. The generated strains possess production capabilities suitable for further development at a larger scale. Taken in whole, this thesis dissertation describes the process developed, outcomes, and future potential of performing systems metabolic engineering of microorganisms.