385279 Evaluating the Physiological State of Engineered Isobutanol Producing E. coli Strains By Isotopomer Constrained Flux Balance Analysis

Wednesday, November 19, 2014
Galleria Exhibit Hall (Hilton Atlanta)
Gang Wu, Department of Energy, Environmental, and Chemical Engineering, Washington University, St. Louis, MO, Arul Varman, Sandia National Laboratories, Livermore, CA, Lian He, Enery, Environmental and Chemical Engineering Department, Washington University in St. Louis, St Louis, MO and Yinjie J. Tang, Washington University in St. Louis, St. Louis, MO

Metabolic engineering, especially the introduction of exogenous plasmids into the cell, imposes considerable burdens on cell physiology. For example, plasmid replication, protein expression and metabolite accumulation significantly affect the growth rate, expression of native proteins, energetic metabolism, and cell composition of the host cell. Furthermore, biosynthesis of products may result in severe metabolic stresses and cause deleterious impact on both the cell membrane and the energy metabolism. This study aims to understand the metabolic shifts in engineered microbial hosts. Specifically, we have integrated 13C-labeling and genome-scale FBA (flux balance analysis) to investigate the physiologies of engineered E.coli strains for isobutanol production.
      On the experimental side, we performed labeling experiments on several engineered E. coli strains (high performance JCL260 strain from James Liao Lab, low performance strains with only overexpression of EhrlichPathway). Under aerobic growth conditions, we measured both the strain’s growth and isotopomer data of their key proteinogenic amino acids. Then, we used a 13C-MFA (13C-metabolic flux analysis) model to profile the central metabolism based on isotopomer data. Since the precise measurement of volatile extracellular metabolites is difficult, the MFA model did not place tight constraints on overflow metabolite fluxes, and thus 13C-MFA could only determine scratchy ranges of fluxes in central metabolism. To obtain the unique metabolic solution, we built a large-scale flux balance analysis (FBA) model, which is constrained by 13C-MFA results. The integrated FBA model relied on objective functions to evaluate flux distributions. In addition, we tested the sensitivity of the model prediction towards changes in the energy metabolism (ATP maintenance and P/O ratios) and biomass composition equations. By extensively comparing the fluxomics results between the engineered strains, we discovered several metabolic features of the high performance JCL260. First, the JCL260 strain could up-regulate its NADPH production pathways and minimize its overflow metabolism. Second, P/O ratios have relatively a small impact on its optimal isobutanol yield. Third, isobutanol overproduction strongly competes for biomass building blocks and thus addition of nutrients (yeast extract) to support cell growth is essential for high yield of isobutanol.  Finally, model sensitivity analysis also implied that alcohol production by E.coli is more likely to achieve higher yield than biodiesel production since the production pathway is less susceptible to energy limitation.

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