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dc.contributor.advisorGregory Stephanopoulos.en_US
dc.contributor.authorSantos, Christine Nicole S. (Christine Nicole San Diego)en_US
dc.contributor.otherMassachusetts Institute of Technology. Dept. of Chemical Engineering.en_US
dc.date.accessioned2010-11-08T17:40:49Z
dc.date.available2010-11-08T17:40:49Z
dc.date.copyright2010en_US
dc.date.issued2010en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/59885
dc.descriptionThesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Chemical Engineering, 2010.en_US
dc.descriptionCataloged from student submitted PDF version of thesis.en_US
dc.descriptionIncludes bibliographical references (p. 231-246).en_US
dc.description.abstractAlthough the field of microbial metabolic engineering has traditionally been dominated by rational and knowledge-driven approaches, recent advances in genetic engineering have led to the emergence of a new methodology based on phenotypic diversification and screening. Unlike "classical strain improvement," which requires the use of general mutagens to introduce nonspecific chromosomal substitutions, these novel combinatorial methods enable sampling of a wider range of phenotypic space and, additionally, offer the important feature of genetic traceability. As an example, the use of transposon mutagenesis allows for the random integration of a genetic cassette within the chromosome for the generation of gene knockout libraries. More recently, the mutagenesis of cellular transcriptional components (global transcription machinery engineering, gTME) has enabled a complete reprogramming of the transcriptome, a useful feature for eliciting a broad array of phenotypes. Despite these advances in library generation, however, the application of these combinatorial approaches has surprisingly been limited to the engineering of only a handful of cellular properties. Thus, there remains a pressing need for a full evaluation of these techniques and, more specifically, an objective comparison of their relative strengths and weaknesses when applied towards strain improvement endeavors. We decided to explore these specific issues using the metabolic engineering framework of L-tyrosine overproduction in Escherichia coli. Although this particular strain optimization problem merely represents a "model system" for these studies, such endeavors do have important industrial implications, as L-tyrosine serves both as a dietary supplement and a valuable precursor for a myriad of polymers, adhesives and coatings, pharmaceuticals, biocosmetics, and flavonoid products. To establish the early foundations for a combinatorial approach, we began with the construction of a "parental" or starting strain for the generation of these genetic libraries. This was achieved by utilizing several common rational engineering strategies to both deregulate and increase the flux through the aromatic amino acid biosynthetic pathway. The resulting strains, P1 and P2, exhibited L-tyrosine production levels of 358 mg/l and 418 mg/l, respectively, thus establishing an already high base line for this study. In a parallel investigation, we also worked on developing a simple high-throughput screen for Ltyrosine production in E. coli, another prerequisite for the use of these combinatorial approaches. This was accomplished through the heterologous expression of a bacterial tyrosinase which provided a visual link between L-tyrosine production and the synthesis of the colored pigment, melanin. When implemented on a solid agar format, this assay allowed for the identification and isolation of high L-tyrosine producers from combinatorial libraries of more than 106 mutants. Having established the basis for a combinatorial study, these strains and tools were subsequently applied for the generation and screening of three separate libraries - a random knockout library constructed through transposon integration and two plasmid-encoded gTME libraries based on the mutagenesis of the a subunit and the s70 sigma factor of RNA polymerase (rpoA and rpoD, respectively). Several strains were isolated, with some gTME mutants exhibiting impressive titers of up to ~900 mg/l L-tyrosine, a 114% increase over the parental. Upon further examination, however, we discovered that phenotypic transferability was somewhat hampered in these strains due to an unusual requirement for both the plasmidencoded rpoA/rpoD and a mutated chromosomal background to achieve the desired phenotype. Furthermore, the biochemical mechanisms triggered by these factors appeared to be nonspecific, as several plasmid-background combinations were found to lead to the same cellular behaviors. To elucidate the biochemical underpinnings for these phenomena, we decided to conduct a full characterization of three isolated gTME strains through both microarray analysis and whole genome sequencing. Interestingly, whole genome sequencing revealed the presence of a separate unique mutation within each strain in two biochemically-related loci (hisH, purF). Although microarray experiments generally yield intractable results, we were also fortunate to find patterns of expression linking this phenotype to two different cellular responses -- the acid stress resistance pathway and the stringent response. Indeed, the overexpression of two transcriptional regulators for these pathways (evgA, relA) was able to supplant the need for the mutant rpoA or rpoD plasmids, thus validating the contributions of these specific mechanisms towards determining cellular phenotype. The successful identification of these critical genetic factors led us to the construction of a novel, genetically-defined strain (rpoA14R) exhibiting a titer of 902 mg/l L-tyrosine and a yield of 0.18 g L-tyrosine/g glucose in 50 ml cultures. To put these numbers into perspective, this yield on glucose is more than 150% greater than a classically-improved strain (DPD4195) currently used for the industrial production of L-tyrosine and, when excluding biomass-related glucose utilization, represents 85% of the maximum theoretical yield. As an added feature, further engineering of this strain has established its capacity to produce the flavonoid precursor naringenin at competitive levels, thus providing a route for the synthesis of other important Ltyrosine derivatives. During this study, we have successfully applied a combinatorial engineering approach for both eliciting a complex phenotype and identifying novel biochemical and genetic avenues by which to engineer future strains. As such, these combinatorial techniques have certainly proven to be valuable tools within the metabolic engineer's ever-expanding arsenal.en_US
dc.description.statementofresponsibilityby Christine Nicole S. Santos.en_US
dc.format.extent253 p.en_US
dc.language.isoengen_US
dc.publisherMassachusetts Institute of Technologyen_US
dc.rightsM.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.en_US
dc.rights.urihttp://dspace.mit.edu/handle/1721.1/7582en_US
dc.subjectChemical Engineering.en_US
dc.titleCombinatorial search strategies for the metabolic engineering of microorganismsen_US
dc.typeThesisen_US
dc.description.degreePh.D.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Chemical Engineering
dc.identifier.oclc673712813en_US


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