Description:

William Bothfeld, Tyo Lab:

Title
A glucose-sensing toggle switch for autonomous, high productivity genetic control

Abstract
Great progress has been made in expanding the number and types of chemicals made biologically. Many of the strategies to biosynthesize these chemicals involve production during cell growth. This scheme is inherently limited because feedstock (e.g., sugar) is converted to excess biomass instead of product, essential genes must be maintained for cell growth, and a high titer of product can be toxic to growth and may limit yields. A two-stage growth and production phase strategy could avoid these issues. At bench scale, chemical additions turn on production pathways in cells to implement two-phase strategies. However, these chemicals are expensive and not practical for large scale production. We have developed a genetic toggle switch that uses glucose sensing to enable this two-phase strategy. Temporary glucose starvation precisely and autonomously activates product expression in rich or minimal media, obviating the requirement for inducing chemicals. The switch remains stably in the new state even after reintroduction of glucose. In the context of polyhydroxybutyrate biosynthesis (a bio-polymer), our system enables shorter growth phases and comparable titers to cells that are steadily expressing PHB at near maximal tolerance levels. This two-phase production strategy, and specifically the glucose toggle switch, should be broadly useful to initiate many types of genetic program for metabolic engineering applications.

Robert Brydon, Broadbelt Lab:

Title
Microkinetic modeling of homogeneous and catalyzed oxidation systems

Abstract
Epoxidation, a specific form of partial oxidation, is an especially valuable process for the production of resins, plasticizers, curing agents, and more products. Traditional mechanisms used to explain partial oxidation systems are often insufficient when applied to cases where there is a high selectivity to epoxide products. This work sought to create a comprehensive microkinetic model that could be applied to a variety of partial oxidation systems with varying intrinsic selectivities to epoxide products. A challenge in modeling is the ability to sufficiently capture the behavior of complex chemistry without the scale of the model becoming unreasonable. By employing automatic network generation with a reaction family approach, a set of reactions and parameters of manageable size was created for partial oxidation and validated against experimental data. The resultant net flux analysis provided insights that shape a new understanding of epoxidation through radical intermediates. With the contribution of homogeneous oxidation well-defined, the developed microkinetic model was adapted to account for various catalysts. The resultant models were then used to investigate the effect of catalysts, including gold nanoparticles and transition metal oxides, on oxidation activity and selectivity.