Sophorolipids (SLs) are regarded as one of the most promising biosurfactants. They have a low toxicity and are easily degradable without polluting the environment. However, high production costs are the main obstacle to extended SLs application. Semi-continuous fermentation is a promising technology for achieving high SLs productivity, which is based on in-situ separation. In this study, the sedimentation mechanism of SLs was analyzed. The formation of a hydrophobic mixture of SLs and oil was a key factor in sedimentation. The hydrophobicity and density of the mixture determined SLs sedimentation rate. According to the mechanism, ultrasonic enhanced sedimentation technology (UEST) was introduced, by which the sedimentation rates were increased by 46.9% to 485.4% with different Oil/SLs ratios. UEST-assisted real-time rational in-situ separation and semi-continuous fermentation were performed. We observed that SLs productivity and yield were 2.15 g/L and 0.58 g/g, whereas the loss ratio of cells, glucose, and oil was reduced by 68.2%, 16.2%, and 65.5%, respectively. In-situ SLs separation efficiency and rate were increased by 34.5% and 26.4%, respectively. This study provides the foundation and new horizon for the optimization of the SLs fermentation process.

In this study, we developed a mechanism-assisted data-driven model to regulate substrate feedback to improve the production efficiency of sophorolipids (SLs). First, we used a variety of on-line biosensors to establish a multi-scale parameter detection system. We found that the production of SLs by fed-batch fermentation could be divided into three stages: a stage that was limited by cell production capacity, a stage that was inhibited by high product concentration, and a stage that was limited by oxygen supply. Subsequently, we used process parameters to develop a data-driven model, and this was then combined with the analysis of cell metabolic mechanisms. The optimal production of SLs was achieved in the first and second stages by the precise feedback regulation of substrate feeding, which increased the titer of SLs by 4.9%. The control error of the substrate was reduced from more than 15% to less than 5%. The mechanism-assisted data-driven model was then applied for semi-continuous fermentation during the production of SLs. This effectively alleviated the oxygen limitation during the third stage, and further increased the productivity of SLs to 2.30 g/L/h, 40.2% higher than the fed-batch fermentation method.

Sophorolipids (SLs) are regarded as one of the most promising biosurfactants. However, high production costs are the main obstacle to extended SLs application. Semi-continuous fermentation, which is based on in-situ separation, is a promising technology for achieving high SLs productivity. In this study, the sedimentation mechanism of SLs was analyzed. The formation of a hydrophobic mixture of SLs and rapeseed oil was a key factor in sedimentation. And the hydrophobicity and density of the mixture determined SLs sedimentation rate. On this basis, ultrasonic enhanced sedimentation technology (UEST) was introduced, by which the sedimentation rates were increased by 46.9% to 485.4% with different ratio of rapeseed oil to SLs. UEST-assisted real-time in-situ separation and semi-continuous fermentation were performed. SLs productivity and yield were 2.15 g/L/h and 0.58 g/g, respectively, simultaneously the loss ratio of cells, glucose, and rapeseed oil were significantly reduced. This study provides the new horizon for optimization of the SLs fermentation process.