Abstract
BACKGROUND: Erythritol is a natural sweetener that is used in the food industry. It is produced as an osmoprotectant by bacteria and yeast. Due to its chemical properties, it does not change the insulin level in the blood, and therefore it can be safely used by diabetics. Previously, it has been shown that erythrose reductase (ER), which catalyzes the final step, plays a crucial role in erythritol synthesis. ER reduces erythrose to erythritol with NAD(P)H as a cofactor. Despite many studies on erythritol synthesis by Yarrowia lipolytica, the enzymes involved in this metabolic pathway have ever been described. RESULTS: The gene YALI0F18590g encoding the predicted erythrose reductase from Y. lipolytica was overexpressed, and its influence on erythritol synthesis was studied. The amino acid sequence of the Y. lipolytica ER showed a high degree of similarity to the previously described erythrose reductases from known erythritol producers, such as Candida magnoliae and Moniliella megachiliensis. Here, we found that the gene overexpression results in an enhanced titer of erythritol of 44.44 g/L (20% over the control), a yield of 0.44 g/g and productivity of 0.77 g/L/h. Moreover, on purification and characterization of the enzyme we found that it displays the highest activity at 37 °C and pH 3.0. The effects of various metal ions (Zn(2+), Cu(2+), Mn(2+), Fe(2+)) on erythrose reductase were investigated. The addition of Zn(2+) ions at 0.25 mM had a positive effect on the activity of erythrose reductase from Y. lipolytica, as well as on the erythritol production. CONCLUSIONS: In this study we identified, overexpressed and characterized a native erythrose reductase in Y. lipolytica. Further optimizations of this strain via metabolic pathway engineering and media optimization strategies enabled 54 g/L to be produced in a shake-flask experiment. To date, this is the first reported study employing metabolic engineering of the native gene involved in the erythritol pathway to result in a high titer of the polyol. Moreover, it indicates the importance of environmental conditions for genetic targets in metabolic engineering.