(173a) 13C-Metaboloic Flux Analysis of Microbial Cell Factories: A Touch of Revelation

Metabolic engineering facilitates the construction of microbial cell factories that can convert renewable carbon sources into advanced biofuels and value-added chemicals. However, it is challenging to move most of the engineered microbes beyond laboratory settings, as low product yield and titer in large reactors prevent the scale-up of these microbial factories, particularly for products having low profit margins. To understand the bottlenecks in microbial cell factories, we can use flux analysis models to reveal that: 1) carbon flux dissipation into a complex metabolic network, leading to a diverse array of metabolites besides the desired product; 2) ATP and NAD(P)H generation and consumption for biofuel synthesis.

This presentation will discuss our recent work (collaborating with Dr. Antoniewicz group and Dr. Peng group) on the metabolic flux response to genetic modifications on E. coli fatty acid pathways. We engineered a fatty acid overproducing E. coli strain through overexpressing tesA (“pull”) and fadR (“push”) and knocking out fadE (“block”). This “pull-push-block” strategy resulted in a yield of 0.17 gram of fatty acids per gram of glucose (which is equivalent to 48% of the maximum theoretical yield) in batch cultures. ¹³C-metabolic flux analysis revealed several significant flux responses to fatty acid overproduction, including reduction of waste acetate secretion and up-regulations of NADPH production pathways (such as transhydrogenase reactions and oxidative pentose phosphate reactions). This study also shows that the engineered strain has much higher energy loss than its parent strain.

To reveal the impact of energy metabolisms on fatty acid yields, we built a mini flux balance analysis (FBA) model to predict the maximum fatty acid yield in response to varying P/O ratios (Phosphate/Oxygen Ratio) and ATP maintenance for diverse cellular processes (e.g., energy spilling, cell motility, membrane repair, re-synthesis of macromolecules, etc.). The results indicate that fatty acid yield is extremely sensitive to cell maintenance and P/O ratio. Under sup-optimal conditions (e.g., P/O ratio < 2), yields of high energy content molecules (such as biodiesel) can be severely limited by poor efficiency of energy metabolism. In this case, traditional pathway engineering strategies, aimed to avoid carbon loss and redirect fluxes towards the products, may not be effective to improve cell productivity.   

Extensive genetic modifications of microbial cell factories may cost high cell maintenance, giving rise to metabolic burdens and imbalances. This will reduce the energy molecules available to the biosynthesis pathway, posing a dilemma between satisfying the energy requirement by ‘burning’ carbon sources and attaining high product yield by avoiding carbon loss. Besides, mass transfer limitations in large bioreactors may cause micro-environmental fluctuations (such as O₂ level, pH and temperatures, etc.), which induce metabolic shifts and stress responses in host cells, and cause poor respiration efficiency (e.g., reduced proton gradient to power ATP synthase during oxidative phosphorylation). Therefore, ¹³C-MFA is important and useful to characterize both carbon and energy metabolisms in microbial hosts under complex genetic and sup-optimal growth conditions. It not only identifies metabolic nodes for rational genetic modifications of microbial hosts, but also discourages those microbial cell factories showing poor energy metabolism.