Optimizing Oil Production in Oleaginous Yeast by Cell-Wide Measurements and Genome-Based Models (Final Report) (2021)

The work funded under this DOE genomics grant focused on characterizing, modifying and developing genetic engineering tools for the then very promising but under-characterized oleaginous yeast Yarrowia lipolytica. To-date, all biodiesel production facilities rely on vegetable oils and animal fats as feedstocks, which are very limited. Nature, on the other hand, is very well equipped for making carbohydrates, which are very plentiful throughout the world and rather well distributed in various forms. While numerous (biochemical and thermochemical) technologies exist presently for carbohydrate conversion to alcohols, there is none available for the cost-efficient production of lipids from carbohydrate feedstocks. Such a technology would have wide-ranging implications in land use, renewable resource utilization and production of transportation fuels with minimal carbon footprint. The global research objectives of this award were to develop tools for cell-wide measurement of metabolites and lipids that, along with transcriptional data, will allow the construction of genome-scale metabolic models, as well as models of transcriptional regulation, that will guide the further metabolic engineering of Yarrowia lipolytica. To achieve these goals, a very strong international and diverse team consisting of research groups at MIT, UCLA, PNNL and Chalmers University was put together, whose specific goals, achievements and breakthroughs are summarized below: MIT, the lead institution for this award, focused on the characterization and further engineering of the two over-producing Yarrowia strains that had already been engineered on which future yield, title and productivity enhancements were based. These were the overproducing Hr3/D9 strain expressing delta-9 stearoyl-CoA desaturase (SCD), and the ACC-DGA strain, which expressed the genes Acetyl-CoA carboxylase (ACC1), and Diacylglyceride acyl-transferase (DGA1). Once majority of lipogenic improvements were achieved by these prior efforts, the focus turned on several genetic engineering, fermentation and modeling strategies to achieve further gains in figures of merit of yield, productivity and titer, including: Assuring the lipogenesis pathway has no limitations in its requirement of reducing equivalents (NADPH); systematically identifying and investigating the lipogenic effect of a promising panel of 44 different lipogenesis-related genes of Yarrowia in 7 different categories; exploring the possibility of loss of lipids via catabolic processes; investigating how to mitigate the effects of the unique nitrogen starvation conditions required, which leave the cells in an unfavorable physiological state; establishing a mathematical model to guide identification and rewire of the central carbon metabolism towards optimization of process yield of lipids; and, observing the behavior of our strains when fed with acetate, a dilute mixture of organic volatile fatty acids (VFAs) and dilute biomass hydrolysates (which include xylose) With starting Yarrowia Hr3/D9 and ACC1/DGA1 strains already having a maximum productivity of 0.253g/L/h (during the lipid accumulation phase of the fermentation), yield of about 0.2 grams of oil per gram of glucose consumed, titer of 55-75 g/Lt in 72 hrs, and lipid content of 62% dry cell weight, our best strain grown in 3 liter bioreactor was able to reach a titer of 98 g/L, productivity of 1.2 g/L/h and a process yield of 0.269 g/g from a single fed-batch fermentation. UCLA worked to construct dynamic models of Yarrowia lipolytica and use them to identify gene targets for improving lipid production. No such models were available at the genome scale when this project started. The particularly attractive approach of Ensemble Modeling (EM), starts with a cell-wide metabolic reconstruction of the target species, and generates an ensemble of dynamic models reaching the same steady state characterized by 13C flux measurements, provided by the MIT team. The availability of such dynamic models is invaluable in identifying targets for speeding up the lipid production process, as suggested by numerous test cases using EM for productivity improvement. The following was achieved: Reconstruction of a cell-wide description of Yarrowia metabolism using literature information (in collaboration with the Chalmers team). Building of an ensemble of dynamic, kinetic models following the EM protocol, given a cell-wide reconstruction of the ACC1+DGA1Yarrowia strain metabolism using 13C flux measurements. In-silico overexpression (up to 2-fold) and knockdown (down to 50%) of every single enzyme using the ensemble of dynamic models (Ensemble Modeling for Robustness Analysis) and identified potential gene targets for productivity improvement. Discovery of reference fluxes for acetic acid metabolism in Yarrowia and predicted potential gene targets to optimize lipid yield with Ensemble Modeling (EM). The efforts from the research group at Chalmers University of Technology primarily focused on the following topics: Genome-scale model reconstruction and method development; elucidation of the regulation underlying lipid accumulation in Y. lipolytica; establishing a Y. lipolytica amenable and suitable for further genetic engineering, and to investigate the effects of increased lipid production in yeast S. cerevisiae as a base model as well analyze transcriptional changes on strains accumulating increased levels of triacylglycerides (TAG). PNNL’s initial work was focused on generating a multi-omic and microscopy datasets for the characterization of lipogenesis in Y. lipolytica. Concurrent with the multi-omic studies, PNNL developed a number of molecular genetic research tools for Yarrowia that were disseminated to the other participants in the project. These included: A NHEJ deficient mutant that greatly increased the efficiency of targeted transformation; the “Yarrowia Cell Atlas”, consisting of various strains with GFP proteins that were localized to a variety of organelles; and, understanding the yeast-to-hyphal transition, a collaboration with Chalmers. PNNL generated non-hyphal or “smooth” mutants of Y. lipolytica, which led to a number of interesting studies aimed at understanding the control of growth morphology in Yarrowia. Over the course of this project PNNL developed a molecular genetic toolbox for the oleaginous yeast, Yarrowia lipolytica and generated and analyzed multiple datasets aimed at understanding the regulatory circuits underlying lipid accumulation and morphology. Control of cell morphology is a critical component of industrial bioprocesses and the work conducted under this project is applicable beyond Yarrowia, to other fungal production organisms. Moreover, expansion Yarrowia Cell Atlas is ongoing as part of a BER funded Bioimaging project in collaboration with University of Idaho (PI – A. Vasdekis). Yarrowia lipolytica has solidified itself as a powerful research and development organism for the field of industrial microbiology and biotechnology.