Due to its availability, low-price, and higher degree of reduction than lignocellulosic sugars, glycerol has become an attractive carbon source for the production of fuels and reduced chemicals. However, this high degree of reduction of carbon atoms in glycerol also results in significant challenges in regard to its utilization under fermentative conditions. Therefore, in order to unlock the full potential of microorganisms for the fermentative conversion of glycerol into fuels and chemicals, a detailed understanding of the anaerobic fermentation of glycerol is required. The work presented here highlights a comprehensive experimental investigation into fermentative glycerol metabolism in Escherichia coli, which has elucidated several key pathways and mechanisms. The activity of both the fermentative and respiratory glycerol dissimilation pathways was found to be important for maximum glycerol utilization, a consequence of the metabolic cycle and downstream effects created by the essential involvement of PEP-dependent dihydroxyacetone kinase (DHAK) in the fermentative glycerol dissimilation pathway. The decoupling of this cycle is of central importance during fermentative glycerol metabolism, and while multiple decoupling mechanisms were identified, their relative inefficiencies dictated not only their level of involvement, but also implicated the activity of other pathways/enzymes, including fumarate reductase and pyruvate kinase. The central role of the PEP-dependent DHAK, an enzyme whose transcription was found to be regulated by the cyclic adenosine monophosphate (cAMP) receptor protein (CRP)-cAMP complex, was also tied to the importance of multiple fructose 1,6-bisphosphotases (FBPases) encoded by fbp, glpX, and yggF. The activity of these FBPases, and as a result the levels of fructose 1,6-bisphosphate, a key regulatory compound, appear to also play a role in the involvement of several other enzymes during fermentative glycerol metabolism including PEP carboxykinase. Using this improved understanding of fermentative glycerol metabolism as a platform, E. coli has been engineered to produce high yields and titers of ethanol (19.8 g/L, 0.46 g/g), co-produced along with hydrogen, and 1,2-propanediol (5.6 g/L, 0.21 g/g) from glycerol, demonstrating its potential as a carbon source for the production of fuels and reduced chemicals.

This thesis presents the mathematical modeling of two new Escherichia coli platforms with economical potential for the production of biofuels and chemicals, namely glycerol fermentation and the reversal of the β-oxidation cycle. With the increase in traditional fuel prices, alternative renewable energy sources are needed, and the efficient production of biofuels becomes imperative. So far studies have focused on using glucose as feedstock for the production of ethanol and other fuels, but a recent increase in glycerol availability and its consequent decrease in price make it an attractive feedstock. Furthermore, the reversed β-oxidation cycle is a highly efficient mechanism for the synthesis of long-chain products. These two platforms have been reported experimentally in E. coli but their mathematical modeling is presented for the first time here. Because mathematical models have proved to be useful in the optimization of microbial metabolism, two complementary models were used in this study: kinetic and stoichiometric. Kinetic models can identify the control structure within a specific pathway, but they require highly detailed information, making them applicable to small sets of reactions. In contrast, stoichiometric models require only mass balance information, making them suitable for genome-scale modeling to study the effect of adding or removing reactions for the optimization of the synthesis of desired products. To study glycerol fermentation, a kinetic model was implemented, allowing prediction of the limiting enzymes of this process: glycerol dehydrogenase and di-hydroxyacetone kinase. This prediction was experimentally validated by increasing their enzymatic activities, resulting in a two-fold increase in the rate of ethanol production. Additionally, a stoichiometric genome-scale model (GEM) was modified to represent the fermentative metabolism of glycerol, identifying key metabolic pathways for glycerol fermentation (including a new glycerol dissimilation pathway). The GEM was used to identify genetic modifications that would increase the synthesis of desired products, such as succinate and butanol. Finally, glucose metabolism using the reversal β-oxidation cycle was modeled using a GEM to simulate the synthesis of a variety of medium and long chain products (including advanced biofuels). The model was used to design strategies that can lead to increase the productivity of target products.