Engineered cellular systems are a promising avenue for production of a wide range of useful products including renewable fuels, commodity and specialty chemicals, industrial enzymes, and pharmaceuticals. Achieving this breadth of biological products is facilitated by the diversity of organisms found in nature. Using biological and engineering principles, this diversity can be harnessed to make efficient and renewable bio-based products. Such advancements rely upon our ability to modify host genetics and metabolism. This work focuses on the development of new biotechnological tools which enable cellular engineering, and the implementation of these tools in eukaryotic systems.
Mammalian cell engineering has important implications in protein therapeutics and gene therapy. One major limitation, however, is the ability to predictably control gene expression. We address this challenge by examining critical aspects of gene expression in human cells. First, we evaluate the impact of selection markers, a common mammalian expression element, on cell line development. In doing so, we determine that Zeocin is the best selection agent for human cells. Next, we identify loci across the genome that support high level expression of recombinant DNA and demonstrate their advantage for stable integration. Finally, we optimize a Cre recombinase based methodology that enables efficient retargeting of genomic loci. Collectively, this work augments the current genetic toolbox for human cell lines.
Beyond basic gene expression, there is interest in understanding global interactions within the cell and how they relate to phenomena including gene regulation, expression and disease states. Although our tools are not yet sufficient to study these phenomena in many hosts, methods can be developed in lower eukaryotes and then adapted for more complex hosts later. We demonstrated two methods in S. cerevisiae that utilize a systems-level approach to understand complex phenotypes. First, we developed condition-specific codon optimization that utilizes systems biology information to optimize gene sequence in a condition-specific manner. Additionally, we developed a Graded Dominant Mutant Approach which can be used to dissect multifunctional proteins, understand epigenetic factors, and quantitatively determine protein-DNA interactions. Both can be implemented in many cellular hosts and expand our ability to engineer complex phenotypes in eukaryotic cell systems.
| Identifer | oai:union.ndltd.org:UTEXAS/oai:repositories.lib.utexas.edu:2152/30449 |
| Date | 25 August 2015 |
| Creators | Lanza, Amanda Morgan |
| Contributors | Alper, Hal S. |
| Source Sets | University of Texas |
| Detected Language | English |
| Type | Thesis |
| Format | application/pdf |
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