SIMULTANEOUS PRODUCTION OF BIOSURFACTANTS AND LIPASES FROM Aspergillus niger AND OPTIMIZATION BY RESPONSE SURFACE METHODOLOGY AND DESIRABILITY FUNCTIONS

Adsorption of extracellular lipase in a packed-bed reactor: an alternative immobilization approach

In light of the growing demand for novel biocatalysts and enzyme production methods, this study aimed to evaluate the potential of Aspergillus tubingensis for producing lipase under submerged culture investigating the influence of culture time and inducer treatment. Moreover, this study also investigated conditions for the immobilization of A. tubingensis lipase by physical adsorption on styrene-divinylbenzene beads (Diaion HP-20), for these conditions to be applied to an alternative immobilization system with a packed-bed reactor. Furthermore, A. tubingensis lipase and its immobilized derivative were characterized in terms of their optimal ranges of pH and temperature. A. tubingensis was shown to be a good producer of lipase, obviating the need for inducer addition. The enzyme extract had a hydrolytic activity of 23 U mL-1 and achieved better performance in the pH range of 7.5 to 9.0 and in the temperature range of 20 to 50 °C. The proposed immobilization system was effective, yielding an immobilized derivative with enhanced hydrolytic activity (35 U g-1), optimum activity over a broader pH range (5.6 to 8.4), and increased tolerance to high temperatures (40 to 60 ℃). This research represents a first step toward lipase production from A. tubingensis under a submerged culture and the development of an alternative immobilization system with a packed-bed reactor. The proposed system holds promise for saving time and resources in future industrial applications.

Recent advances in Emulsan production, purification, and application: Exploring bioemulsifiers unique potentials

Bioemulsifiers are compounds produced by microorganisms that reduce the interfacial forces between hydrophobic substances and water. Due to their potential in the pharmaceutical and food industries and their efficiency in oil spill remediation, they have been the subject of study in the scientific community while being safe, biodegradable, and sustainable compared to synthetic options. These biomolecules have high molecular weight and polymeric structures, distinguishing them from traditional biosurfactants. Emulsan, a bioemulsifier exopolysaccharide, is produced by Acinetobacter strains and is highly efficient in forming stable emulsions. Its low toxicity and high potential as an emulsifying agent promote its application in pharmaceutical and food industries as a drug-delivery vehicle and emulsion stabilizer. Due to the high environmental impact of oil spills, bioemulsifiers have great potential for environmental applications, such as bioremediation. This unique feature gives them a distinct mechanism of action in forming emulsions, resulting in minimal environmental impact. A better understanding of these aspects can improve the use of bioemulsifiers and environmental remediation in various industries. This review will discuss the production and characterization of Emulsan, focusing on recent advancements in cultivation conditions, purification techniques, compound identification, and ecotoxicity.

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.

Statistical Optimization of Biosurfactant Production from Aspergillus niger SA1 Fermentation Process and Mathematical Modeling

In this study, we sought to investigate the production and optimization of biosurfactants by soil fungi isolated from petroleum oil-contaminated soil in Saudi Arabia. Forty-four fungal isolates were isolated from ten petroleum oil-contaminated soil samples. All isolates were identified using the internal transcribed spacer (ITS) region, and biosurfactant screening showed that thirty-nine of the isolates were positive. Aspergillus niger SA1 was the highest biosurfactant producer, demonstrating surface tension, drop collapsing, oil displacement, and an emulsification index (E24) of 35.8 mN/m, 0.55 cm, 6.7 cm, and 70%, respectively. This isolate was therefore selected for biosurfactant optimization using the Fit Group model. The biosurfactant yield was increased 1.22 times higher than in the nonoptimized medium (8.02 g/l) under conditions of pH 6, temperature 35°C, waste frying oil (5.5 g), agitation rate of 200 rpm, and an incubation period of 7 days. Model significance and fitness analysis had an RMSE score of 0.852 and a p-value of 0.0016. The biosurfactant activities were surface tension (35.8 mN/m), drop collapsing (0.7 cm), oil displacement (4.5 cm), and E24 (65.0%). The time course of biosurfactant production was a growth-associated phase. The main outputs of the mathematical model for biomass yield were Yx/s (1.18), and μmax (0.0306) for biosurfactant yield was Yp/s (1.87) and Yp/x (2.51); for waste frying oil consumption the So was 55 g/l, and Ke was 2.56. To verify the model's accuracy, percentage errors between biomass and biosurfactant yields were determined by experimental work and calculated using model equations. The average error of biomass yield was 2.68%, and the average error percentage of biosurfactant yield was 3.39%.

Bioprocess Optimization of Nutritional Parameters for Enhanced Anti-leukemic L-Asparaginase Production by Aspergillus candidus UCCM 00117: A Sequential Statistical Approach

Sequential optimization of bioprocess nutritional conditions for production of glutaminase-near-free L-asparaginase by Aspergillus candidus UCCM 00117 was conducted under shake flask laboratory conditions. Catalytic and anti-cancer activities of the poly-peptide were evaluated using standard in vitro biochemical methods. Medium nutrients were selected by one-factor-at-a-time (OFAT) approach while Plackett-Burman design (PBD) screened potential factors for optimization. Path of steepest ascent (PSA) and response surface methodology (RSM) of a Min-Run-Res V fractional factorial of a central composite rotatable design (CCRD) were employed to optimize factor levels towards improved enzyme activity. A multi-objective approach using desirability function generated through predictor importance and weighted coefficient methodology was adopted for optimization. The approach set optimum bioprocess conditions as 49.55 g/L molasses, 64.98% corn steep liquor, 44.23 g/L asparagine, 1.73 g/L potassium, 0.055 g/L manganese and 0.043 g/L chromium (III) ions, at a composite desirability of 0.943 and an L-asparaginase activity of 5216.95U. The Sephadex-200 partially-purified polypeptide had a specific activity of 476.84 U/mg; 0.087U glutaminase activity, 36.46% yield and 20-fold protein purification. Anti-cancer activity potentials of the catalytic poly-peptide were dose-dependent with IC₅₀ (µg/mL): 4.063 (HL-60), 13.75 (HCT-116), 15.83 (HeLa), 11.68 (MCF-7), 7.61 (HepG-2). The therapeutic enzyme exhibited 15-fold more cytotoxicity to myeloid leukemia cell line than to normal (HEK 238 T) cell. Optimum temperature and pH for activity were within physiological range. However, significant interactions between exposure time and levels of each of temperature and pH made interpretations of residual enzyme activities difficult. The manganese-dependent L-asparaginase from Aspergillu s candidus UCCM 00117 is recommended for further anticancer drug investigations.