Rhodotorula toruloides is a non-conventional, oleaginous yeast able to naturally accumulate high amounts of microbial lipids when grown on various carbon substrates, including from a lignocellulosic origin. Its unique metabolic characteristics, which make lipid synthesis possible, are not fully understood. With genome-scale models (GEMs) it is possible to systematically study cellular metabolism using metabolic flux predictions in silico. Enzyme-constrained genome-scale modelling approach has been demonstrated to improve cell phenotype predictions in model organisms, including yeasts. In this work, enzyme-constrained genome-scale metabolic model of R. toruloides was developed, incorporating cell physiology and absolute proteomics data on three different carbon substrates (xylose, glucose, acetic acid) under exponential growth and lipid accumulation phases. The generated model could predict experimental rates measured in all conditions, except for the gases on glucose. Further, predicted intracellular flux patterns demonstrated the differences in R. toruloides metabolism under different carbon substrates and the importance of cofactor balance (NADPH) during the lipid accumulation. These results and the developed genome-scale model can be further used for the design of efficient microbial cell factories and various metabolic studie
