Dynamic regulation of bacterial metabolic pathways using autonomous, pathway-independent control strategies
Massachusetts Institute of Technology. Department of Biological Engineering.
Kristala L. Jones Prather.
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Metabolic engineering efforts have so far focused on strain optimization through careful metabolic modeling and tinkering with host genomes, through gene knockouts or knockins, to direct flux in desired channels. These efforts have borne fruit with the development of large manufacturing processes for numerous chemicals. The next challenge for metabolic engineering, however, lies in tackling issues associated with construction of more complex pathways, such as those that directly interfere with host metabolism, have branchpoints with promiscuous enzymes, or synthesize toxic intermediates or products. Dynamic metabolic engineering has emerged as a new frontier for tool development to allow regulation and control of native and cellular pathways during the course of a production run. Advantages in dynamic strategies are especially apparent in the aforementioned examples where traditional static strategies of gene knockouts or knockins are not an option. Instead, it is necessary to be able to control when certain genes are expressed, such as to build biomass before switching on growth-limiting production pathways, or accumulating intermediates to drive the reaction of a promiscuous enzyme along a certain branch. In this thesis, we propose enzyme control strategies that are independent of any biosynthetic pathway of interest. Therefore, they can theoretically be applied to a wide variety of contexts in a "plug-and-play" fashion to control pathway enzyme expression. After initial work to understand the limitations of nutrient starvation strategies to induce genetic circuits, we decided to use quorum sensing circuitry to create circuits that can be autonomously induced. We used parts of the Esa QS system (derived from Pantoea stewartii) to create circuit variants in the Lscherichia cohi genome, which switch off expression of the targeted gene at various times and cell densities. Switching times were varied by modulating the expression of the AHL synthase, and therefore the production rate of AHL, the quorum sensing molecule. Switching dynamics were characterized and ranked for the entire library of circuit variants using fluorescent reporters. The characterized device was used to identify optimal switching times for redirection of glycolytic fluxes into heterologous pathways, resulting in a 5.5-fold boost in myo-inositol (MI) and increasing glucaric acid titers from unmeasurable quantities up to >0.8 g/L. With a focus on industrial application, consistency of device performance was verified in benchtop bioreactors, achieving nearly 10-fold and 5-fold boosts in specific titers of myoinositol and glucaric acid, respectively. To demonstrate broad utility and "off-the-shelf" applicability, the control module was applied to dynamic downregulation of flux into aromatic amino acid biosynthesis to accumulate the industrially-relevant intermediate, shikimate, resulting in an increase in titers from unmeasurable quantities to >100 mg/L. Finally, this QS device was coupled with a MI-biosensor circuit to institute two layers of dynamic regulation and further improve glucaric acid titers. Production trials in these composite strains resulted in the highest glucaric titers (-2 g/L) reported to date from E. coli K-strains. This work reports the first completely autonomous dynamic regulation module and its application in bioproduction of multiple products from different metabolic pathways. We envision that the strategy presented here may be adapted to any pathway context and gene of interest. With increased prevalence of dynamic regulation, the relevant strategies may become standardized for general use.
Thesis: Ph. D., Massachusetts Institute of Technology, Department of Biological Engineering, 2017.Cataloged from PDF version of thesis.Includes bibliographical references (pages 86-91).
DepartmentMassachusetts Institute of Technology. Department of Biological Engineering.
Massachusetts Institute of Technology