Optimization of compactin production in chemically defined production medium by Penicillium citrinum using statistical methods

Optimization of Baker's Yeast Production on Date Extract Using Response Surface Methodology (RSM)

This work aims to study the production of the biomass of S. cerevisiae on an optimized medium using date extract as the only carbon source in order to obtain a good yield of the biomass. The biomass production was carried out according to the central composite experimental design (CCD) as a response surface methodology using Minitab 16 software. Indeed, under optimal biomass production conditions, temperature (32.9 °C), pH (5.35) and the total reducing sugar extracted from dates (70.93 g/L), S. cerevisiae produced 40 g/L of their biomass in an Erlenmeyer after only 16 h of fermentation. The kinetic performance of the S. cerevisiae strain was investigated with three unstructured models i.e., Monod, Verhulst, and Tessier. The conformity of the experimental data fitted showed a good consistency with Monod and Tessier models with R² = 0.945 and 0.979, respectively. An excellent adequacy was noted in the case of the Verhulst model (R² = 0.981). The values of kinetic parameters (Ks, X_m, μ_m, p and q) calculated by the Excel software, confirmed that Monod and Verhulst were suitable models, in contrast, the Tessier model was inappropriately fitted with the experimental data due to the illogical value of Ks (−9.434). The profiles prediction of the biomass production with the Verhulst model, and that of the substrate consumption using Leudeking Piret model over time, demonstrated a good agreement between the simulation models and the experimental data.

Isolation, characterization, optimization, immobilization and batch fermentation of bioflocculant produced by Bacillus aryabhattai strain PSK1

Among others, isolate PSK1 was selected and identified by 16 S rDNA sequencing as Bacillus aryabhattai. Growth optimization of PSK1 and physicochemical parameters affected bioflocculant production was carried out by Plackett-Burman design and resulted in increasing in the activity by 4.5%. Bioflocculant production by entrapped and adsorbed immobilized microbial cells was performed using different techniques and revealed enhancement in the activity in particular with pumice adsorption. HPLC analysis of sugars and amino acids composition, FTIR and the effect of different factors on the purified PSK1 biopolymer such as presence of cations, thermal stability, pH range and clay concentration was carried out. Scanning electron microscopy (SEM) of free, immobilized cells, PSK1 bioflocculant and formed flocs were performed. The results revealed that bioflocculant PSK1 is mainly glycoprotein consists of glucose and rhamnose with a large number of amino acids in which arginine and phenylalanine were the major. SEM analysis demonstrated that PSK1 have a clear crystalline rod shaped structure. FTIR spectrum reported the presence of hydroxyl and amino groups which are preferred in flocculation process. PSK1 was soluble in water and insoluble in all other tested organic solvents, while it was thermally stable from 40 to 80 °C. Among examined cations, CaCl₂ was the best coagulant. The maximum flocculation activity of the PSK1 recorded at 50 °C (92.8%), pH 2.0 (94.56%) with clay concentration range 5-9 g/l. To obtain a large amount of PSK1 bioflocculant with high flocculating activity, batch fermentation was employed. The results recorded ∼6 g/l yield after 24 h of fermentation.

Strategies for Fermentation Medium Optimization: An In-Depth Review

Optimization of production medium is required to maximize the metabolite yield. This can be achieved by using a wide range of techniques from classical “one-factor-at-a-time” to modern statistical and mathematical techniques, viz. artificial neural network (ANN), genetic algorithm (GA) etc. Every technique comes with its own advantages and disadvantages, and despite drawbacks some techniques are applied to obtain best results. Use of various optimization techniques in combination also provides the desirable results. In this article an attempt has been made to review the currently used media optimization techniques applied during fermentation process of metabolite production. Comparative analysis of the merits and demerits of various conventional as well as modern optimization techniques have been done and logical selection basis for the designing of fermentation medium has been given in the present review. Overall, this review will provide the rationale for the selection of suitable optimization technique for media designing employed during the fermentation process of metabolite production.

Application of Response Surface Methodology for Optimization of Urea Grafted Multiwalled Carbon Nanotubes in Enhancing Nitrogen Use Efficiency and Nitrogen Uptake by Paddy Plants

Efficient use of urea fertilizer (UF) as important nitrogen (N) source in the world’s rice production has been a concern. Carbon-based materials developed to improve UF performance still represent a great challenge to be formulated for plant nutrition. Advanced N nanocarrier is developed based on functionalized multiwall carbon nanotubes (f-MWCNTs) grafted with UF to produce urea-multiwall carbon nanotubes (UF-MWCNTs) for enhancing the nitrogen uptake (NU) and use efficiency (NUE). The grafted N can be absorbed and utilized by rice efficiently to overcome the N loss from soil-plant systems. The individual and interaction effect between the specified factors of f-MWCNTs amount (0.10–0.60 wt%) and functionalization reflux time (12–24 hrs) with the corresponding responses (NUE, NU) were structured via the Response Surface Methodology (RSM) based on five-level CCD. The UF-MWCNTs with optimized 0.5 wt% f-MWCNTs treated at 21 hrs reflux time achieve tremendous NUE up to 96% and NU at 1180 mg/pot. Significant model terms (pvalue < 0.05) for NUE and NU responses were confirmed by the ANOVA. Homogeneous dispersion of UF-MWCNTs was observed via FESEM and TEM. The chemical changes were monitored by FT-IR and Raman spectroscopy. Hence, this UF-MWCNTs’ approach provides a promising strategy in enhancing plant nutrition for rice.

Fermentative production and optimization of mevastatin in submerged fermentation using Aspergillus terreus

The main objective of the study is to enhance the mevastatin production using Plackett–Burman (PB) and central composite design (CCD) by Aspergillus terreus in submerged fermentation (SmF). Eight nutrients were chosen for a PB design with 12 experimental runs. A maximum mevastatin production of 170.4 mg L⁻¹ was obtained in PB design. Response surface methodology (RSM) is a sequential procedure with an initial objective to lead the experimenter rapidly and efficiently along a path of improvement toward the general vicinity of the optimum. The individual and interactive effects of these variables were studied by conducting the fermentation run at randomly selected and different levels of all five factors. Experiments were conducted to optimize the medium constituents like glycerol, CuCl₂·2H₂O, FeSO₄·7H₂O, KH₂PO₄ and MgSO₄·7H₂O. At the optimum condition, a maximum mevastatin production of 701 mg L⁻¹ was obtained.

Use of experimental design for the optimization of the production of new secondary metabolites by two Penicillium species

A fractional factorial design approach has been used to enhance secondary metabolite production by two Penicillium strains. The method was initially used to improve the production of bioactive extracts as a whole and subsequently to optimize the production of particular bioactive metabolites. Enhancements of over 500% in secondary metabolite production were observed for both P. oxalicum and P. citrinum. Two new alkaloids, citrinalins A (5) and B (6), were isolated and identified from P. citrinum cultures optimized for production of minor metabolites.

Optimizing protease production from an isolate of the nematophagous fungusDuddingtonia flagransusing response surface methodology and its larvicidal activity on horse cyathostomins

Protease production fromDuddingtonia flagrans(isolate AC001) was optimized and the larvicidal activity of the enzymatic extract was evaluated on infective horse cyathostomin larvae (L3).Duddingtonia flagranswas grown in liquid medium with eight different variables: glucose, casein, bibasic potassium phosphate (K2HPO4), magnesium sulphate (MgSO4), zinc sulphate (ZnSO4), ferrous sulphate (FeSO4), copper sulphate (CuSO4) and temperature. The Plackett–Burman analysis showed a significant influence of MgSO4, CuSO4and casein (P < 0.05) on protease production byD. flagransin liquid medium. Central composite design indicated that the highest proteolytic activity was 39.56 U/ml as a function of the concentrations of casein (18.409 g/l), MgSO4(0.10 g/l) and CuSO4(0.50 mg/l). A significant difference (P < 0.01) was found for the larval number between the treated and control groups at the end of the experiment. A reduction of 95.46% in the number of free-living larvae was found in the treated group compared with the control. The results of this study suggest that protease production byD. flagrans(AC001) in liquid medium was optimized by MgSO4, CuSO4and casein, showing that the optimized enzymatic extract exerted larvicidal activity on cyathostomins and therefore may contribute to large-scale industrial production.

Statistical optimization of medium for the production of pyruvate oxidase by the recombinant Escherichia coli

Pyruvate oxidase (PyOD) is a very useful enzyme for clinical diagnostic applications and environmental monitor. Optimization of the fermentation medium for maximization of PyOD constitutively, production by Escherichia coli DH5alpha/pSMLPyOD was carried out. Response surface methodology (RSM) was used to optimize the medium constituents. A 2(6-2) fractional factorial design (first order model) was carried out to identify the significant effect of medium components towards PyOD production. Statistical analysis of results shows that yeast extract, ammonium sulfate and composite phosphate were significant factors on PyOD production. The optimized values of these three factors were obtained by RSM based on the result of a 2(3) central composite rotatable design. Under these proposed optimized medium, the model predicted a PyOD activity of 610 U/L and via experimental rechecking the model, an activity of 670 U/L was attained.

Optimization of medium composition for lipase production byCandida rugosaNCIM 3462 using response surface methodology

A sequential optimization approach using statistical design of experiments was employed to enhance the lipase production by Candida rugosa in submerged batch fermentation. Twelve medium components were evaluated initially using the Plackett–Burman 2-level factorial design. The significant variables affecting lipase production were found to be glucose, olive oil, peptone, (NH4)2SO4, and FeCl3·6H2O. Various vegetable oils were tested in the second step, and among them, groundnut oil was found to be the best inducer for lipase production by C. rugosa. The third step was to identify the optimal values of the significant medium components with groundnut oil as the inducer using response surface methodology. The regression equation obtained from the experimental data designed using a central composite design was solved, and analyzing the response surface contour plots, the optimal concentrations of the significant variables were determined. A maximum lipase activity of 5.95 U·mL–1, which is 1.64 times the maximum activity obtained in the Plackett–Burman experimental trials, was observed. The optimum combination of medium constituents contained 19.604 g·L–1glucose, 13.065 mL·L–1groundnut oil, 7.473 g·L–1peptone, 0.962 g·L–1(NH4)2SO4, 0.0019 g·L–1FeCl3·6H2O, and other insignificant components at the fixed level. A predictive model of the combined effects of the independent variables using response surface methodology and an artificial neural network was proposed. The unstructured kinetic models, logistic model, and Luedeking–Piret model were used to describe cell mass and lipase production. The parameters of the models were evaluated and the lipase production by C. rugosa was found to be growth associated.

Application of response surface methodology in medium optimization for pyruvic acid production of Torulopsis glabrata TP19 in batch fermentation

Response surface methodology (RSM) was used to optimize the fermentation medium for enhancing pyruvic acid production by Torulopsis glabrata TP19. In the first step of optimization, with Plackett-Burman design, ammonium sulfate, glucose and nicotinic acid were found to be the important factors affecting pyruvic acid production significantly. In the second step, a 2(3) full factorial central composite design and RSM were applied to determine the optimal concentration of each significant variable. A second-order polynomial was determined by the multiple regression analysis of the experimental data. The optimum values for the critical components were obtained as follows: ammonium sulfate 0.7498 (10.75 g/L), glucose 0.9383 (109.38 g/L) and nicotinic acid 0.3633 (7.86 mg/L) with a predicted value of maximum pyruvic acid production of 42.2 g/L. Under the optimal conditions, the practical pyruvic acid production was 42.4 g/L. The determination coefficient (R(2)) was 0.9483, which ensures adequate credibility of the model. By scaling up fermentation from flask to jar fermentor, we obtained promising results.

Optimization of nutrient parameters for lovastatin production by Monascus purpureus MTCC 369 under submerged fermentation using response surface methodology

Lovastatin, an inhibitor of HMG-CoA reductase, was produced by submerged fermentation using Monascus purpureus MTCC 369. Five nutritional parameters screened using Plackett-Burman experimental design were optimized by Box-Behnken factorial design of response surface methodology for lovastatin production in shake flask cultures. Maximum lovastatin production of 351 mg/l were predicted in medium containing 29.59 g/l dextrose, 3.86 g/l NH4Cl, 1.73 g/l KH2PO4, 0.86 g/l MgSO4 x 7H2O, and 0.19 g/l MnSO4 x H2O using response surface plots and point prediction tool of DESIGN EXPERT 7.0 (Statease, USA) software.