Developing an understanding of sophorolipid synthesis through application of a central composite design model

Abstract

A key barrier to market penetration for sophorolipid biosurfactants is the ability to improve productivity and utilize alternative feedstocks to reduce the cost of production. To do this, a suitable screening tool is required that is able to model the interactions between media components and alter conditions to maximize productivity. In the following work, a central composite design is applied to analyse the effects of altering glucose, rapeseed oil, corn steep liquor and ammonium sulphate concentrations on sophorolipid production with Starmerella bombicola ATCC 222144 after 168 h. Sophorolipid production was analysed using standard least squares regression and the findings related to the growth (OD₆₀₀) and broth conditions (glucose, glycerol and oil concentration). An optimum media composition was found that was capable of producing 39.5 g l^–1 sophorolipid. Nitrogen and rapeseed oil sources were found to be significant, linked to their role in growth and substrate supply respectively. Glucose did not demonstrate a significant effect on production despite its importance to biosynthesis and its depletion in the broth within 96 h, instead being replaced by glycerol (via triglyceride breakdown) as the hydrophilic carbon source at the point of glucose depletion. A large dataset was obtained, and a regression model with applications towards substrate screening and process optimisation developed.