Modeling and optimization of fermentation variables for enhanced production of lactase by isolated Bacillus subtilis strain VUVD001 using artificial neural networking and response surface methodology

Synergistic effects of ternary mixture formulation and process parameters optimization in a sequential approach for enhanced L-asparaginase production using agro-industrial wastes

A novel ternary mixture of inexpensive and nutrient-rich agro-substrates comprising groundnut de-oiled cake, corn gluten meal, and soybean meal has been explored to enhance the L-asparaginase production in solid-state fermentation. To achieve the aim, a hybrid strategy was implemented by utilizing a combination of a mixture design and artificial neural networks. The study initiated with the judicious selection of the agro-substrates based on their low C/N content in comparison to the control using the CHNS elemental analysis. The mixture composition of soybean meal (49.0%), groundnut de-oiled cake (31.5%), and corn gluten meal (19.5%) were found optimum using the simplex lattice mixture design. The agro-industrial substrates mix revealed synergistic effects on the L-asparaginase production than either of the substrates alone. The maximum L-asparaginase activity of 141.45 ± 5.24 IU/gds was observed under the physical process conditions of 70% moisture content, autoclaving period of 30 min and 6.0 pH by adopting the machine learning-derived artificial neural network (ANN) methodology. The ANN modeling showed excellent prediction ability with a low mean squared error of 0.7, a low root mean squared error of 0.84, and a high value of 0.99 for regression coefficient. Moisture content (%) was assessed to be the most sensitive process parameter in the global sensitivity analysis. The net outcome from the two sequential optimization designs is the selection of the ideal mixture composition followed by the optimum physical process parameters. The application of the enzyme demonstrated significant cytotoxicity against leukemia cell line and therefore exhibited an anti-cancer effect. The present study reports a novel mixture combination and methodology that can be used to lower the cost and enhance the production of L-asparaginase using an agro-industrial substrate mixture.

Screening, and Optimization of Fermentation Medium to Produce Secondary Metabolites from Bacillus amyloliquefaciens, for the Biocontrol of Early Leaf Spot Disease, and Growth Promoting Effects on Peanut (Arachis hypogaea L.)

A novel Bacillus amyloliquefaciens BAM strain, with novel fermentation nutrient mediums and compositions, could produce potent antifungal secondary metabolites, as the existing strains face resistance from fungus pathogens. In the current study, we introduced two novel nutrient mediums for the fermentation process, semolina and peanut root extract, as carbon and nitrogen sources in order to maximize the antifungal effects of B. amyloliquefaciens against Cercaspora arachidichola to control early leaf spot disease in peanuts. Based on a single-factor test and the central composite design of response surface methodology, the optimum fermentation medium for Bacillus amyloliquefaciens antagonistic substance was determined, containing 15 gm/L of semolina flour, 12.5 gm/L of beef extract, and 0.5 gm/L of magnesium sulfate, which inhibited the fungal growth by 91%. In vitro, antagonistic activity showed that the fermentation broth of B. amyloliquefaciens BAM with the optimized medium formulation had an inhibition rate of (92.62 ± 2.07)% on the growth of C. arachidichola. Disease control effects in pot experiments show that the pre-infection spray of B. amyloliquefaciens BAM broth had significant efficiency of (92.00 ± 3.79)% in comparison to post-infection spray. B. amyloliquefaciens BAM broth significantly promoted peanut plant growth and physiological parameters and reduced the biotic stress of C. archidechola. Studies revealed that B. amyloliquefaciens BAM with a novel fermentation formulation could be an ideal biocontrol and biofertilizer agent and help in early disease management of early leaf spots in peanuts.

Response Surface Methodology (RSM) Mediated Optimization of Medium Components for Mycelial Growth and Metabolites Production of Streptomyces alfalfae XN-04

Streptomyces alfalfae XN-04 has been reported for the production of antifungal metabolites effectively to control Fusarium wilt of cotton, caused by Fusarium oxysporum f. sp. vasinfectum (Fov). In this study, we used integrated statistical experimental design methods to investigate the optimized liquid fermentation medium components of XN-04, which can significantly increase the antifungal activity and biomass of XN-04. Seven variables, including soluble starch, KNO₃, soybean cake powder, K₂HPO₄, MgSO₄·7H₂O, CaCO₃ and FeSO₄·7H₂O, were identified as the best ingredients based on one-factor-at-a-time (OFAT) method. The results of Plackett–Burman Design (PBD) showed that soluble starch, soybean cake powder and K₂HPO₄ were the most significant variables among the seven variables. The steepest climbing experiment and response surface methodology (RSM) were performed to determine the interactions among these three variables and fine-tune the concentrations. The optimal compositions of medium were as follows: soluble starch (26.26 g/L), KNO₃ (1.00 g/L), soybean cake powder (23.54 g/L), K₂HPO₄ (0.27 g/L), MgSO₄·7H₂O (0.50 g/L), CaCO₃ (1.00 g/L) and FeSO₄·7H₂O (0.10 g/L). A verification experiment was then carried out under the optimized conditions, and the results revealed the mycelial dry weight of S. alfalfae XN-04 reaching 6.61 g/L. Compared with the initial medium, a 7.47-fold increase in the biomass was achieved using the optimized medium. Moreover, the active ingredient was purified from the methanol extract of S. alfalfae XN-04 mycelium and then identified as roflamycoin (a polyene macrolide antibiotic). The results may provide new insights into the development of S. alfalfae XN-04 fermentation process and the control of the Fusarium wilt of cotton and other plant diseases.

Fusarium graminearum as a producer of xylanases with low cellulases when grown on wheat bran

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Endophytic fungi of cacao had important xylanase activity when grown on wheat bran.

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F. graminearum strain Ec220 produced xylanases with low cellulolytic activity.

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Xylanase production was optimized using response surface methodology.

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Proteomic analysis revealed similarities with previously reported xylanases.

The xylanolytic potential of endophytic fungi isolated from leaves of Theobroma cacao was explored for the first time. Four fungal strains showed significant amounts of xylanase activity and low cellulase levels when grown on wheat bran as the sole carbon source. Strain Ec220 of Fusarium graminearum had the highest xylanase production (1.79 U/ml), whereas its cellulase activity was minimal (0.24 U/ml). Optimal conditions for xylanase production were: 154 h of incubation time, pH 5.79 and 29.8 °C. Furthermore, two protein spots detected by two-dimensional gel electrophoresis showed molecular weights (26.05 and 27.70 kDa) and isoelectric points (6.18 and 9.20) corresponding to previously reported F. graminearum xylanases, Xyl A and Xyl B, respectively. Therefore, endophytic fungi of T. cacao can be an important source of xylanolytic activities when cultured on wheat bran, and xylanases with low cellulases found in strain Ec220 require further characterization as they show promise for possible industrial applications.

L-asparaginase production in solid-state fermentation using Aspergillus niger: process modeling by artificial neural network approach

L-asparaginase has proven itself as a potential anti-cancer drug and in the mitigation of acrylamide formation in the food industry. In the present investigation, a novel utilization of niger (Guizotia abyssinica) de-oiled cake as the sole source for the cost-effective production of L-asparaginase was evaluated and compared with different agro-substrates in solid-state fermentation. The substrate provided a favorable C/N content for the L-asparaginase production as evident from the chemical composition (CHNS analysis) of the substrate. The influential process parameters viz; autoclaving time, moisture content, temperature and pH were optimized and modeled using machine-learning based artificial neural network (ANN) and statistical-based response surface methodology (RSM). The maximum enzyme activity of 34.65 ± 2.18 IU/gds was observed at 30.3 min of autoclaving time, 62% moisture content, 30 °C temperature and 6.2 pH in 96 h. A 1.36 fold improvement in enzyme activity was observed on utilizing optimized parameters. In comparison with RSM, the ANN model showed superior prediction with a low mean squared error of 0.072, low root mean squared error of 0.268 and 0.99 value of regression coefficient. The present study demonstrates the novel utilization of inexpensive and readily available agro-industrial waste for the development of cost-effective L-asparaginase production process.

Antioxidant potential and optimization of production of extracellular polysaccharide by Acinetobacter indicus M6

Background

Extracellular polysaccharides (ECPs) produced by biofilm-producing marine bacterium have great applications in biotechnology, pharmaceutical, food engineering, bioremediation, and bio-hydrometallurgy industries. The ECP-producing strain was identified as Acinetobacter indicus M6 species by 16S rDNA analysis. The polymer produced by the isolate was quantified and purified and chemically analyzed, and antioxidant activities have been studied. The face-centered central composite design (FCCCD) was used to design the model.

Results

The results have clearly shown that the ECP was found to be endowed with significant antioxidative activities. The ECP showed 59% of hydroxyl radical scavenging activity at a concentration of 500 μg/mL, superoxide radical scavenging activity (72.4%) at a concentration of 300 μg/mL, and DPPH˙ radical scavenging activity (72.2%) at a concentration of 500 μg/mL, respectively. Further, HPLC and GC-MS results showed that the isolated ECP was a heteropolymer composed of glucose as a major monomer, and mannose and glucosamine were minor monomers. Furthermore, the production of ECP by Acinetobacter indicus M6 was increased through optimization of nutritional variables, namely, glucose, yeast extract, and MgSO₄ by “Response Surface Methodology”. Moreover the production of ECP reached to 2.21 g/L after the optimization of nutritional variables. The designed model is statistically significant and is indicated by the R² value of 0.99. The optimized medium improved the production of ECP and is two folds higher in comparison with the basal medium.

Conclusions

Acinetobacter indicus M6 bacterium produces a novel and unique extracellular heteropolysaccharide with highly efficient antioxidant activity. GC-MS analyses elucidated the presence of quite uncommon (1→4)-linked glucose, (1→4)-linked mannose, and (→4)-GlcN-(1→) glycosidic linkages in the backbone. The optimized medium improved the production of ECP and is two folds higher in comparison with the basal medium. The newly optimized medium could be used as a promising alternative for the overproduction of ECP.

Utilization of oil palm decanter cake for valuable laccase and manganese peroxidase enzyme production from a novel white-rot fungus, Pseudolagarobasidium sp. PP17-33

Oil palm decanter cake (OPDC) in the current study was converted to valuable products as laccase and manganese peroxidase (MnP) by an undescribed strain of the white-rot fungus, Pseudolagarobasidium sp. PP17-33. The optimization to enhance the production of enzymes through solid-state fermentation was performed using Plackett-Burman design and response surface methodology. The highest observed laccase was 5.841 U/gds and observed MnP was 5.156 U/gds, which enhanced yield by 2.59-fold and 1.94-fold from the non-optimization. The optimized medium (mg/g of OPDC) consisted of 0.852 mg CuSO₄·5H₂O, 13.512 mg glucose, 2 mg yeast extract, 0.2 mg KH₂PO₄, 1.5 mg MgSO₄·7H₂O, 0.01 mg FeSO₄·7H₂O, 0.15 mg MnSO₄·H₂O, 0.01 mg ZnSO₄·7H₂O and 0.3 mg Tween 80 (pH 5.0) when incubated at 30 °C for 7 days. The most significant variables of laccase and MnP productions were CuSO₄·5H₂O and glucose concentrations. This study is the first to report on the production of ligninolytic enzymes from OPDC waste using white-rot fungi. In addition, five different white-rot fungi, Coriolopsis aspera, C. retropicta, Dentipellis parmastoi, Nigroporus vinosus and Tyromyces xuchilensis, are newly observed producers of ligninolytic enzymes in Thailand. The results obtained from this study are significant not only for agro-industrial waste management but also for value-added enzyme production.