Statistical Methodologies for the Optimization of Lipase and Biosurfactant by Ochrobactrum intermedium Strain MZV101 in an Identical Medium for Detergent Applications

Advances in the co-production of biosurfactant and other biomolecules: statistical approaches for process optimization

An efficient microbial conversion for simultaneous synthesis of multiple high-value compounds, such as biosurfactants and enzymes, is one of the most promising aspects for an economical bioprocess leading to a marked reduction in production cost. Although biosurfactant and enzyme production separately have been much explored, there are limited reports on the predictions and optimization studies on simultaneous production of biosurfactants and other industrially important enzymes, including lipase, protease, and amylase. Enzymes are suited for an integrated production process with biosurfactants as multiple common industrial processes and applications are catalysed by these molecules. However, the complexity in microbial metabolism complicates the production process. This study details the work done on biosurfactant and enzyme co-production and explores the application and scope of various statistical tools and methodologies in this area of research. The use of advanced computational tools is yet to be explored for the optimization of downstream strategies in the co-production process. Given the complexity of the co-production process and with various new methodologies based on artificial intelligence (AI) being invented, the scope of AI in shaping the biosurfactant-enzyme co-production process is immense and would lead to not only efficient and rapid optimization, but economical extraction of multiple biomolecules as well.

Kinetic modeling and quasi-economic analysis of fermentative glycolipopeptide biosurfactant production in a medium co-optimized by statistical and neural network approaches

This study presents the kinetics of production of a glycolipopeptide biosurfactant in a medium previously co-optimized by response surface and neural network methods to gain some insight into its volumetric and specific productivities for possible scale-up towards industrial production. Significant kinetic parameters including maximum specific growth rate, µmax, specific substrate consumption rate, qs and specific biosurfactant yield, Yp/x were determined from logistic model parameters after comparison with other kinetic models. Results showed that bio-catalytic rates of lipase and urease reached exponential values within the first 12 h of fermentation leading to high specific rates of substrate consumption and bacterial growth. Volumetric biosurfactant production reached significantly high levels during prolonged stationary growth and specific urease activity. This suggests that glycolipopeptide biosynthesis may proceed through stationary phase transpeptidation of the glycolipid base. A high cross-correlation coefficient of 0.950 confirmed that substrate consumption and glycolipopeptide production occurred contemporaneously during the 66-h fermentation. The maximum biosurfactant concentration of 132.52 g/L, µmax of 0.292 h^-1, qp of 1.674 g/gDCW/h, rp of 2.008 g/(Lh) and Yp/x of 4.413 g/g predicted by the selected logistic model and a unit cost of €0.57/g glycolipopeptide in the optimized medium may lead to technical and economic benefits.

Medium optimization based on comparative metabolomic analysis of chicken embryo fibroblast DF-1 cells

Chicken embryo fibroblast DF-1 cells are increasingly being used in the production of avian virus vaccines. However, the relatively low proliferative capacity does not meet the requirements of industrial production. In this study, we attempted to improve the proliferative capacity of DF-1 cells. The results of intracellular metabolomics showed that 28 types of metabolites could play roles in DF-1 cell growth based on the variance and timing analysis of intracellular metabolites from DF-1 cells grown in two media with distinct growth difference, DMEM/F12 (1 : 1) and DMEM. By examining the differences in the components in the two media, DOE was used to screen and optimize the growth medium for DF-1 cells. The maximum cell density was 40.72% higher, and the infectious bursal disease virus (IBDV) titer was 2.68 times higher, in the optimized medium than in the control. This study proposes a complete solution from metabolomics to media optimization.

Production of Cold-Active Lipase by Free and Immobilized Marine Bacillus cereus HSS: Application in Wastewater Treatment

Lipases are enzymes that have the potential to hydrolyze triacylglycerol to free fatty acids and glycerol and have various applications. The aim of the present study was to isolate and screen marine bacteria for lipase production, optimize the production, and treat wastewater. A total of 20 marine bacterial isolates were obtained from the Mediterranean Sea and were screened for lipase production. All isolates were found to have lipolytic ability. The differences between the isolates were studied using RAPD-PCR. The most promising lipase producer (isolate 3) that exhibited the highest lipolytic hydrolysis (20 mm) was identified as Bacillus cereus HSS using 16S rDNA analysis and had the accession number MF581790. Optimization of lipase production was carried out using the Plackett-Burman experimental design with cotton seed oil as the inducer under shaking conditions at 10°C. The most significant factors that affected lipase production were FeSO4, KCl, and oil concentrations. By using the optimized culture conditions, the lipase activity increased by 1.8-fold compared with basal conditions. Immobilization by adsorption of cells on sponge and recycling raised lipase activity by 2.8-fold compared with free cells. The repeated reuse of the immobilized B. cereus HSS maintained reasonable lipase activity. A trial for the economic treatment of oily wastewater was carried out. Removal efficiencies of biological oxygen demand, total suspended solids, and oil and grease were 87.63, 90, and 94.7%, respectively, which is promising for future applications.

Statistical Design, a Powerful Tool for Optimizing Biosurfactant Production: A Review

Biosurfactants (Bs) have been studied for decades and applied in different industrial sectors because of their competitive biochemical characteristics, and the fact that they are environmentally friendly. Current scientific investigations mainly involve the search for novel Bs producing organisms with attractive characteristics. Bs are expected to replace synthetic surfactants in the near future, but low production yields and inefficient downstream processes have prevented their widespread use. Although there are numerous reports on Bs optimization, to date there has been no critical compilation or revision of the statistical designs and strategies employed for improved production. The purpose of this mini review is to briefly discuss the factors that affect Bs production and the importance of statistical design as an essential tool for increasing production.