Engineering lipid overproduction in the oleaginous yeast Yarrowia lipolytica.

Conversion of carbohydrates to lipids at high yield and productivity is essential for cost-effective production of renewable biodiesel. Although some microorganisms can convert sugars to oils, conversion yields and rates are typically low due primarily to allosteric inhibition of the lipid biosynthetic pathway by saturated fatty acids. By reverse engineering the mammalian cellular obese phenotypes, we identified the delta-9 stearoyl-CoA desaturase (SCD) as a rate limiting step and target for the metabolic engineering of the lipid synthesis pathway in Yarrowia lipolytica. Simultaneous overexpression of SCD, Acetyl-CoA carboxylase (ACC1), and Diacylglyceride acyl-transferase (DGA1) in Y. lipolytica yielded an engineered strain exhibiting highly desirable phenotypes of fast cell growth and lipid overproduction including high carbon to lipid conversion yield (84.7% of theoretical maximal yield), high lipid titers (~55g/L), enhanced tolerance to glucose and cellulose-derived sugars. Moreover, the engineered strain featured a three-fold growth advantage over the wild type strain. As a result, a maximal lipid productivity of ~1g/L/h is obtained during the stationary phase. Furthermore, we showed that the engineered yeast required cytoskeleton remodeling in eliciting the obesity phenotype. Altogether, our work describes the development of a microbial catalyst with the highest reported lipid yield, titer and productivity to date. This is an important step towards the development of an efficient and cost-effective process for biodiesel production from renewable resources.

Multivariate modular metabolic engineering for pathway and strain optimization.

Despite the potential in utilizing microbial fermentation for chemical production, the field of industrial biotechnology still lacks a standard, universally applicable principle for strain optimization. A key challenge has been in finding and applying effective ways to address metabolic flux imbalances. Strategies based on rational design require significant a priori knowledge and often fail to take a holistic view of cellular metabolism. Combinatorial approaches enable more global searches but require a high-throughput screen. Here, we present the recent advances and promises of a novel approach to metabolic pathway and strain optimization called multivariate modular metabolic engineering (MMME). In this technique, key enzymes are organized into distinct modules and simultaneously varied based on expression to balance flux through a pathway. Because of its simplicity and broad applicability, MMME has the potential to systematize and revolutionize the field of metabolic engineering and industrial biotechnology.