(712g) Resolving the Central Metabolism of Oleaginous Yeast Yarrowia Lipolytica By 13C-Metabolic Flux Analysis
AIChE Annual Meeting
2014 AIChE Annual Meeting
Food, Pharmaceutical & Bioengineering Division
Advances in Metabolic Engineering and Bioinformatics for Biofuels II: Next-Generation Method Development
Thursday, November 20, 2014 - 5:09pm to 5:27pm
The oleaginous yeast Yarrowia lipolytica can accumulate large quantities of lipids in the form of triacylglycerol (TAG) in its lipid body, making it an attractive host for biodiesel production. To develop engineered strains producing high lipid yield, we need to identify metabolic bottleneck pathways for genetic manipulation, e.g. gene knockout and over-expression. Thus, the determination of in vivo metabolic fluxes can provide critical information for the identification of target genes and the evaluation of engineered strains. Here, we constructed a Yarrowia lipolytica metabolic model containing glycolysis, oxidative and non-oxidative pentose phosphate pathway (PPP), TCA cycle, amino acid metabolism, glyoxylate shunt, lipid metabolism and biomass synthesis. The model enables us to estimate NADPH formation via malic enzyme (ME) and the oxidative PPP, de novo synthesis of lipid via the TCA cycle and anabolic pathways of pyruvate carboxylase (PC) and the glyoxylate shunt. Based on this model, we quantified metabolic flux values in Yarrowia with [1-13C]glucose, [1,2-13C]glucose and [U-13C]glucose tracers, in which the tracer experiments were performed in parallel labeling experiments with wild type Yarrowia strain. Overall, [1,2-13C]glucose and [U-13C]glucose tracers showed good flux resolution. Furthermore, we introduced a combined analysis of two data sets from [1,2-13C]glucose and [U-13C]glucose experiments. We acquired a flux map of high resolution and accuracy by the combined analysis which generated narrow confidence intervals at key pathways, e.g. oxidative PPP, ME, PC, pyruvate dehydrogenase (PDH), citrate synthase, ATP citrate lyase and glyoxylate shunt. Based on the metabolic model and the combined flux analysis, we acquired dynamic in vivo flux maps of an acetyl-CoA carboxylase- and diacylglycerol acyltransferase-overexpressing strain at exponential, linear growth and lipid accumulation phases. The production rates of non-lipid biomass decreased from the exponential to lipid accumulation phase. In opposite, the lipid production rates increased according to the progress of the cell culture. This result indicates the dynamic rewiring of in vivo metabolic activities for lipid synthesis: First, the engineered strain maintained high oxidative PPP fluxes during culture compared to normal yeast cells. Second, PK, PDH and ME fluxes were linearly correlated with lipid production flux. The dynamic information allows us to reveal bottleneck enzymes for lipid production and to develop engineered cells for biofuel production.