Response surface modeling and optimization to elucidate and analyze the effects of inoculum age and size on surfactin production
TL;DR: In this article, a computer aided response surface modeling, optimization and analysis of the age and size of the two-stage inocula was carried out in batch reactor studies and the optimal values were obtained including primary inoculum age and density = 56h and 5.5h, respectively.
Abstract: The inoculum age and density markedly influence the productivity and economics of bioprocesses. Some literature reports demonstrated the use of two-stage inocula for the production of surfactin. However, no systematic studies to elucidate the individual, cumulative and interactive effects of the important twin parameters, inoculum age and size on surfactin production, have been reported. Thus, a computer aided response surface modeling, optimization and analysis of the age and size of the two-stage inocula was carried out in batch reactor studies. The optimal values thus, obtained include primary inoculum age and size = 56 h and 5.5% (v/v), secondary inoculum age and size = 4.5 h and 9.5% (v/v), respectively. At the above optimal conditions, the model predicts a maximum relative surfactin concentration of 58–59 CMC −1 , mainly due to a strong interaction between primary inoculum size and secondary inoculum age. The experimental verifications substantiated the model predictions by showing a maximum relative surfactin concentration of 58 CMC −1 , which was found to be equivalent to about 1.3 g L −1 crude surfactin as estimated gravimetrically, thereby resulting in an improved production.
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TL;DR: Practical approaches that have been adopted to make the biosurfactant production process economically attractive include the use of cheaper raw materials, optimized and efficient bioprocesses and overproducing mutant and recombinant strains for obtaining maximum productivity.
Abstract: Biosurfactants or microbial surfactants are surface-active biomolecules that are produced by a variety of microorganisms. Biosurfactants have gained importance in the fields of enhanced oil recovery, environmental bioremediation, food processing and pharmaceuticals owing to their unique properties – higher biodegradability, lower toxicity, and effectiveness at extremes of temperature, pH and salinity. However, large-scale production of these molecules has not been realized because of low yields in production processes and high recovery and purification costs. This article describes some practical approaches that have been adopted to make the biosurfactant production process economically attractive: these include the use of cheaper raw materials, optimized and efficient bioprocesses and overproducing mutant and recombinant strains for obtaining maximum productivity. The application of these strategies in biosurfactant production processes, particularly those using hyper-producing recombinant strains in the optimally controlled environment of a bioreactor, might lead towards the successful commercial production of these valuable and versatile biomolecules in near future.
694 citations
TL;DR: A three factor, three-level Box-Behnken experimental design combining with response surface modeling (RSM) and quadratic programming (QP) was employed for maximizing Pb(II) removal from aqueous solution by Antep pistachio (Pistacia vera L.) shells based on 17 different experimental data obtained in a lab-scale batch study.
Abstract: A three factor, three-level Box-Behnken experimental design combining with response surface modeling (RSM) and quadratic programming (QP) was employed for maximizing Pb(II) removal from aqueous solution by Antep pistachio (Pistacia vera L.) shells based on 17 different experimental data obtained in a lab-scale batch study. Three independent variables (initial pH of solution (pH(0)) ranging from 2.0 to 5.5, initial concentration of Pb(II) ions (C(0)) ranging from 5 to 50 ppm, and contact time (t(C)) ranging from 5 to 120 min) were consecutively coded as x(1), x(2) and x(3) at three levels (-1, 0 and 1), and a second-order polynomial regression equation was then derived to predict responses. The significance of independent variables and their interactions were tested by means of the analysis of variance (ANOVA) with 95% confidence limits (alpha=0.05). The standardized effects of the independent variables and their interactions on the dependent variable were also investigated by preparing a Pareto chart. The optimum values of the selected variables were obtained by solving the quadratic regression model, as well as by analysing the response surface contour plots. The optimum coded values of three test variables were computed as x(1)=0.125, x(2)=0.707, and x(3)=0.107 by using a LOQO/AMPL optimization algorithm. The experimental conditions at this global point were determined to be pH(0)=3.97, C(0)=43.4 ppm, and t(C)=68.7 min, and the corresponding Pb(II) removal efficiency was found to be about 100%.
483 citations
TL;DR: In this article, a review of the operating mechanisms and progress made in enhanced oil recovery through the use of microbes and their metabolic products is presented, and the importance of mathematical models used in predicting the applicability of an MEOR strategy and the microbial growth and transport has been qualitatively discussed.
Abstract: Biotechnology has played a significant role in enhancing crude oil recovery from the depleted oil reservoirs to solve stagnant petroleum production, after a three-stage recovery process employing mechanical, physical and chemical methods. Biotechnologically enhanced oil recovery processes, known as microbial enhanced oil recovery (MEOR), involve stimulating indigenous reservoir microbes or injecting specially selected consortia of natural bacteria into the reservoir to produce specific metabolic events that lead to improved oil recovery. This also involves flooding with oil recovery agents produced ex situ by industrial or pilot scale fermentation. This paper essentially reviews the operating mechanisms and the progress made in enhanced oil recovery through the use of microbes and their metabolic products. Improvement in oil recovery by injecting solvents and gases or by energizing the reservoir microflora to produce them in situ for carbonate rock dissolution and reservoir re-pressurization has been enunciated. The role of biosurfactants in oil mobilization through emulsification and that of biopolymers for selective plugging of oil-depleted zones and for biofilm formation have been delineated. The spoil sport played by sulfate-reducing bacteria (SRB) in MEOR has also been briefly reviewed. The importance of mathematical models used in predicting the applicability of an MEOR strategy and the microbial growth and transport has been qualitatively discussed. The results of some laboratory studies and worldwide field trials applying ex situ and in situ MEOR technologies were compiled and interpreted. However, the potential of the MEOR technologies has not been fully realized due to poor yield of the useful microbial metabolic products, growth inhibition by accumulated toxic metabolites and longer time of incubation. A complete evaluation and assessment of MEOR from an engineering standpoint based on economics, applicability and performance is required to further improve the process efficiency for writing more success stories. Thus, this review attempts to address almost all the issues concerning the MEOR, its past and recent trends and its future prospect and directions.
461 citations
TL;DR: A four-factor central composite design combined with response surface modeling (RSM) was employed for maximizing CV removal from aqueous solution by the nanocomposite based on 30 different experimental data obtained in a batch study.
Abstract: A magnetic nanocomposite was developed and characterized. Adsorption of crystal violet (CV) dye from water was studied using the nanocomposite. A four-factor central composite design (CCD) combined with response surface modeling (RSM) was employed for maximizing CV removal from aqueous solution by the nanocomposite based on 30 different experimental data obtained in a batch study. Four independent variables, viz. temperature (10-50°C), pH of solution (2-10), dye concentration (240-400 mg/l), and adsorbent dose (1-5 g/l) were transformed to coded values and a second-order quadratic model was built to predict the responses. The significance of independent variables and their interactions were tested by the analysis of variance (ANOVA) and t-test statistics. Adequacy of the model was tested by the correlation between experimental and predicted values of the response and enumeration of prediction errors. Optimization of the process variables for maximum adsorption of CV by nanocomposite was performed using the quadratic model. The Langmuir adsorption capacity of the adsorbent was determined as 81.70 mg/g. The model predicted maximum adsorption of 113.31 mg/g under the optimum conditions of variables (concentration 240 mg/l; temperature 50°C; pH 8.50; dose 1g/l), which was very close to the experimental value (111.80 mg/g) determined in batch experiment.
355 citations
TL;DR: The results are indicative of the potential of the strain for the development of ex situ microbial enhanced oil recovery processes using glucose or date molasses based minimal media and the biosurfactants were stable over wide range of pH, salinity and temperatures.
Abstract: The fermentative production of biosurfactants by Bacillus subtilis strain B30 and the evaluation of biosurfactant based enhanced oil recovery using core-flood were investigated. Different carbon sources (glucose, sucrose, starch, date molasses, cane molasses) were tested to determine the optimal biosurfactant production. The isolate B30 produced a biosurfactant that could reduce the surface tension and interfacial tension to 26.63 ± 0.45 mN/m and 3.79 ± 0.27 mN/m, respectively in less than 12 h in both glucose or date molasses based media. A crude biosurfactant concentration of 0.3–0.5 g/l and critical micelle dilution (CMD) values of 1:8 were observed. The biosurfactants gave stable emulsions with wide range of hydrocarbons including light and heavy crude oil. The biosurfactants were partially purified and identified as a mixture of lipopeptides similar to surfactin, using high performance thin layer chromatography and Fourier transform infrared spectroscopy. The biosurfactants were stable over wide range of pH, salinity and temperatures. The crude biosurfactant preparation enhanced light oil recovery by 17–26% and heavy oil recovery by 31% in core-flood studies. The results are indicative of the potential of the strain for the development of ex situ microbial enhanced oil recovery processes using glucose or date molasses based minimal media.
236 citations
References
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01 Jan 1987
TL;DR: In this paper, the authors present a methodology for estimating response surfaces that rival least squares based on the integrated mean squared error criterion analysis of multiresponse experiments with block effects mixture designs and analyses nonlinear response surface models.
Abstract: Introduction to response surface methodology matrix algebra, least squares, the analysis of variance, and principles of experimental design first-order models and designs second-order models and designs determining optimum conditions methods of estimating response surfaces that rival least squares based on the integrated mean squared error criterion analysis of multiresponse experiments response surface models with block effects mixture designs and analyses nonlinear response surface models Taguchi's robust parameter design additional topics and some directions for future research. Appendix: solutions to selected exercises.
1,480 citations
TL;DR: In this paper, the authors present a methodology for estimating response surfaces that rival least squares based on the integrated mean squared error criterion analysis of multiresponse experiments with block effects mixture designs and analyses nonlinear response surface models.
Abstract: Introduction to response surface methodology matrix algebra, least squares, the analysis of variance, and principles of experimental design first-order models and designs second-order models and designs determining optimum conditions methods of estimating response surfaces that rival least squares based on the integrated mean squared error criterion analysis of multiresponse experiments response surface models with block effects mixture designs and analyses nonlinear response surface models Taguchi's robust parameter design additional topics and some directions for future research. Appendix: solutions to selected exercises.
1,384 citations
TL;DR: A fine study of the structure/function relationships associated with the three-dimensional structure has led to the recognition of the specific residues required for activity in surfactin biosynthesis and will assist researchers in the selection of molecules with improved and/or refined properties useful in oil and biomedical industries.
Abstract: The name surfactin refers to a bacterial cyclic lipopeptide, primarily renowned for its exceptional surfactant power since it lowers the surface tension of water from 72 mN m-1 to 27 mN m-1 at a concentration as low as 20 microM. Although surfactin was discovered about 30 years ago, there has been a revival of interest in this compound over the past decade, triggered by an increasing demand for effective biosurfactants for difficult contemporary ecological problems. This simple molecule also looks very promising as an antitumoral, antiviral and anti-Mycoplasma agent. Structural characteristics show the presence of a heptapeptide with an LLDLLDL chiral sequence linked, via a lactone bond, to a beta-hydroxy fatty acid with 13-15 C atoms. In solution, the molecule exhibits a characteristic "horse saddle" conformation that accounts for its large spectrum of biological activity, making it very attractive for both industrial applications and academic studies. Surfactin biosynthesis is catalysed non-ribosomally by the action of a large multienzyme complex consisting of four modular building blocks, called the surfactin synthetase. The biosynthetic activity involves the multicarrier thiotemplate mechanism and the enzyme is organized in structural domains that place it in the family of peptide synthetases, a class of enzymes involved in peptidic secondary-metabolite synthesis. The srfA operon, the sfp gene encoding a 4'-phosphopantetheinyltransferase and the comA regulatory gene work together for surfactin biosynthesis, while the gene encoding the acyltransferase remains to be isolated. Concerning surfactin production, there is no indication whether the genetic regulation, involving a quorum-sensing mechanism, overrides other regulation factors promoted by the fermentation conditions. Knowledge of the modular arrangement of the peptide synthetases is of the utmost relevance to combinatorial biosynthetic approaches and has been successfully used at the gene level to modify the surfactin template. Biosynthetic and genetic rationales have been described for building variants. A fine study of the structure/function relationships associated with the three-dimensional structure has led to the recognition of the specific residues required for activity. These studies will assist researchers in the selection of molecules with improved and/or refined properties useful in oil and biomedical industries.
738 citations
TL;DR: In terms of surface activity, heat and pH stability, many biosurfactants are comparable to synthetic surfactants as mentioned in this paper, and as such, they find applications in a wide variety of industrial processes.
Abstract: Surfactants find applications in a wide variety of industrial processes. Biomolecules that are amphiphilic and partition preferentially at interfaces are classified as biosurfactants. In terms of surface activity, heat and pH stability, many biosurfactants are comparable to synthetic surfactants. Therefore, as the environmental compatibility is becoming an increasingly important factor in selecting industrial chemicals, the commercialization of biosurfactant is gaining much attention. In this paper, the general properties and functions of biosurfactants are introduced. Strategies for development of biosurfactant assay, enhanced biosurfactant production, large scale fermentation, and product recovery are discussed. Also discussed are recent advances in the genetic engineering of biosurfactant production. The potential applications of biosurfactants in industrial processes and bioremediation are presented. Finally, comments on the application of enzymes for the production of surfactants are also made.
224 citations
TL;DR: In this paper, the effect of fermentation process conditions, namely pH, temperature, rates of agitation and aeration, on surfactin production was extensively studied to optimize the process conditions for the maximum production of surfactins.
Abstract: Response-surface methodology was applied to determine the effect of the fermentation process conditions, namely pH, temperature, rates of agitation and aeration, on surfactin production. The effects of the mutual interactions between these parameters were extensively studied to optimize the process conditions for the maximum production of surfactin. With a view to simultaneously reducing the number of experiments and obtaining the mutual interactions between the variables required for achieving the optimal experimental conditions, a 24 full-factorial central composite design followed by multi-stage Monte-Carlo optimization was employed for experimental design and analysis of the results. The optimum process conditions for the enhanced production of surfactin were as follows: pH = 6.755, temperature = 37.4 °C, agitation = 140 rpm and aeration = 0.75 vvm. Relative surfactin concentrations were denoted by the reciprocal of the critical micelle concentrations.
169 citations