Dep. de Engenharia Bioquímica Universidade Federal do Rio de Janeiro Ilha do Fundão, Rio de Janeiro RJ, 21949-900, Brasil Tel: 55 21 25627621 Fax: 55 21 25627667 E-mail: fpfranca@eq.ufrj.br
Universidade Federal do Rio de Janeiro Ilha do Fundão, Rio de Janeiro RJ, 21945-970, Brasil Tel: 55 21 25627232 Fax: 55 21 25627232 E-mail: lealopes@ima.ufrj.br
Bacterial exopolysaccharides are extensively used as thickening and gelling agents in a wide range of industrial products and processes due to their structural and physical properties diversity (Copetti et al. 1997; Rinaudo, 2001). The structure, composition and viscosity of the microbial polysaccharides depend on several factors, such as the composition of the culture medium, carbon and nitrogen source, mineral salts, trace elements, type of strain, and fermentation conditions (pH, temperature, oxygen concentration, agitation) (Moreira et al. 1998; Weuster-Botz, 2000; Pinto et al. 2002; Duta et al. 2004). For many microbial species, calcium is essentially required in small amounts: it is essential in maintaining cell wall rigidity, it stabilizes oligomeric proteins and covalently bound protein peptidoglycan complexes in the outer membrane, as well as have a requirement for chemotaxis (Macció et al. 2002). The reach of optimized fermentation conditions, particularly associated to physical and chemical parameters, is of primary and great importance for the development of any process, due to their impact upon its economics and practicability. The diversity of combinatory interactions among medium components, metabolism of cells and the large number of chemical requirements for processing metabolic products, do not allow satisfactory detailed modelling. The one-dimensional search with successive changes on variables conditions is still employed, even trough it is well accepted that it is practically impossible for the one-dimensional search to accomplish an appropriate optimum combination in a finite number of experiments. Single variable optimization methods are not only tedious, but can also lead to misinterpretation of results, especially taking into account that the interaction between different factors is overlooked (Abdel-Fattah et al. 2005). Statistical experimental designs have been used for many decades and can be adopted on several steps of an optimization strategy, such as for screening experiments or searching for the optimal conditions of a targeted response (Kim et al. 2005; Lee and Gilmore, 2005; Nawani and Kapadnis, 2005; Senthilkumar et al. 2005; Wang and Lu, 2005). Recently, the results analyzed by a statistical planned experiment are better acknowledged than those carried out by the traditional one-variable-at-a-time method. Some of the popular choices, applying statistical designs to bioprocessing, include the Plackett-Burman design (Liu et al. 2003; Wang and Lu, 2005) and response surface methodology with various designs (Abdel-Fattah, 2002; Abdel-Fattah and Olama, 2002; Tanyildizi et al. 2005). The response surface methodology is an empirical modelling system that assesses the relationship between a group of variables, which can be controlled experimentally, and the observed response. This methodology is applied mainly both in food science and in the optimization of fermentative processes. It is a 2-level factorial design, where contour plots are generated by linear or quadratic effects of key variables, and a model equation is derived, fitting the experimental data to the calculate system's optimal response (Lakshman et al. 2004; Cazetta et al. 2005; Khanna and Srivastava, 2005). Fast growing rhizobia synthesize different extracellular polysaccharides, like acid exopolysaccharides (EPS) of high molecular weight (Zevenhuizen, 1986). Those microorganisms can also produce neutral glucans, formed by β-1,4 bonds, which are found as cellulosic microfibrils of low molecular weight (Zevenhuizen, 1986; Breedveld et al. 1990; Jain et al. 1990; Breedveld et al. 1993). Many rhizobia stains produced polysaccharides are not found freely dispersed in the medium, but attached upon the microbial cell as an amorphous viscous material. Among these, the curdlana homo-polymer is outstanding, in which the derived sulphated sites show anticoagulant and anti-thrombosisactivities. Besides, they also present an inhibiting effect against the HIV-1 virus The present study investigated the relationship among three variables, that is, calcium carbonate concentration, agitation, and aeration, in exopolysaccharide production by The The microorganism was grown under (30 ± 1)ºC for 48 hrs, using laboratory tubes filled with YMA medium. After growth, the cultures were stored at (5 ± 1)ºC. The microorganism stock culture was maintained in modified yeast mannitol agar extract, which presented the following composition (g/L): mannitol (10.0); K The stock culture was used for preparing the inoculum, using 500 mL Erlenmeyer flasks, containing 100 mL of the YMA medium free from agar. Incubation was carried out in a rotary shaker at 200 rpm and (30 ± 1)ºC, for 48 hrs, with the cells in the final of exponential growth phase. The exopolysaccharides production assays were carried out using a similar culture medium, where the YMA medium was: supplemented with manganese ions (MnCl The inoculation of the production medium was made in order to obtain an average cells concentration of 0.77 ± 0.02 mg/mL.
These experiments were conducted in a fermenter (Model BioFlow IV, New Brunswick Scientific), with 20 L capacity, equipped with disc impeller, oxygen and pH electrodes. The equipment also monitored temperature, agitation speed, gas purging flow rate, pumping rates, antifoam addition and the vessel level. All processing parameters were online monitored, with the aid of AFS 3.0 software (Advanced Fermentation Software, New Brunswick Scientific). The temperature (30 ± 1ºC) and pH value (7.0 ± 0.1) were kept constant during the experiments. Other parameters, like substrate concentration, aeration and agitation, were chosen as the most significant ones, considering the experimental design. After selecting those parameters, experiments were done in duplicate, for superior (+) and lower (-) levels of the experimental design, and in triplicate, for the central point (0). For each experiment, 1000 mL of the inoculum was used, that is, 10% (v/v) of the initial working volume (10 L). The process was conducted throughout 48 hrs. During the process, microscopic examinations, using Gram method, were performed in order to detect possible microbial contaminations in the medium. Prior for the quantitative determination of mannitol, the fermented broth was filtered through 0.2 µm Millipore membranes, in order to remove microbial cells. In the filtered fluid, the substrate was analyzed by high performance liquid chromatography (HPLC), in a Waters chromatograph, equipped with SHODEX SC1011 ion-exchange columns, at 75ºC. Reagent water type I (ASTM, 2001) was used as eluent, and the elution rate applied was 0.8 mL/min. The amount of fermented exopolysaccharide was determined by dry-weight measurements. The fermented broth was heated at (80 ± 1)ºC, for 10 min, to ensure microbial inactivation. Afterwards, the microbial cells were removed by a filtration step. In order to precipitate the exopolysaccharides, a solution of ethanol P.A. and reagent water type I (ASTM, 2001) (3:1) was added to the fermented broth. After the exopolysaccharides total precipitation, the suspended material was filtered through 0.2 µm Millipore membrane, using Gouche crucible previously weighed. The obtained product was dried at (80 ± 1)ºC until constant weight. All determinations were done in triplicate. The exopolysaccharides extracted from the fermented broth was purified through successive washings with solutions of ethanol P.A. and reagent water type I (ASTM, 2001) at 70, 80 and 90% (v/v), respectively. The product was finally dried by a nitrogen gas purging flow, under controlled heating.
This statistical technique is widely used as a tool to verify the efficacy of several processes. In the present work, it has been used for obtaining pieces of information about the exopolysaccharides production process; thus, a reduction in operational costs can be expected. A 2 X aeration (vvm), _{2}X agitation (rpm). The manipulation responses of the input variables were evaluated as a function of the substrate conversion into exopolysaccharide, coded by Y_{3}_{p/s} (g/g). A mathematical model, describing the relationships among the process dependent variable, Yp/s, and the independent variables in a second-order equation, was developed. Design-based experimental data were matched according to the following second-order polynomial equation: where, β = linear terms coefficients,_{i} = quadratic terms coefficients,β _{ii} = interaction coefficients.β _{ij}All the calculations involved as well as the drawing of all three-dimensional surface (3D) have been obtained using the Statistica Three-dimensional surface (3D) plots were drawn to illustrate the main and interactive effects of the independent variables on exopolysaccharides production. The optimum values of the selected variables were obtained both by solving the regression equation and also by analyzing the response surface contour plots (Myers and Montgomery, 2002). The statistical technique is widely used as a tool for checking the efficiency of several processes. In the present work it has been used with the purpose of obtaining information about the exopolysaccharides production process; consequently, a reduction in the operational variability and a cut down in operational costs can be expected. The experimental results (Y Y ) + (-0.081844 X) + (-0.000081 _{2}X) + (0.205141 _{3}X) + (0.000153 _{1}X_{2}X) + (0.000052 _{1}X_{3}X)_{2}X_{3}Besides the linear effect of the substrate/ exopolysaccharides factor, Y The regression coefficient, The statistical significance of the ratio, between the of mean square variation, due to regression, and the mean square residual error, was tested using analysis of variance (ANOVA). ANOVA is a statistical technique that subdivides the total variation of a set of data into component associated to specific sources of variation for the purpose of testing hypotheses for the modelled parameters. According to the ANOVA (Table 5), the F-values for all regressions were high, what indicates that most of the variations on the response variable can be explained by the regression equation. The associated p-value is used to estimate whether F is large enough to indicate statistical significance. A p-value lower than 0.01 indicates that the model is considered to be statistically significant (Kim et al. 2003). The p values of all of the regression were lower than 0.01. This means that at least one of the terms in the regression equation has a significant correlation with the response variable. The ANOVA table also shows a term for residual error, which measures the amount of variation in the response data left unexplained by the model. The type of the model, chosen to explain the relationship between the factors and response, is correct. The analysis of variance (ANOVA), indicates that the second-order polynomial model (Equation 1) was highly significant and adequate to represent the actual relationship between the response and input variables, with very small p values (p = 0.0000). Pareto chart (Figure 1) corroborates the data shown in Table 5, and also enhances the understanding of this table. Figure 1 shows that all the linear terms of the model were significant for the set confidence level, as well as the quadratic term of X), was not statistically significant (Figure 1 and Table 5). Statistical data analysis shows that calcium carbonateconcentration is the most important variable for the production process._{1}X_{2}X_{3}The matching quality, of the data obtained by the model proposed in Equation 1, was evaluated considering the correlation coefficient, R Figure 2 shows the regression plot of the Y The 3D response surface plots described by the regression model were drawn to illustrate the effects of the independent variables, and combined effects of each independent variable upon the response variable. Figure 3 illustrates 3D response surface based on the Y X) independent variables upon Y_{2}_{p/s}, while the third independent variable, agitation (X), was kept constant level (800 rpm). It can be observed that the maximum estimated Y_{3}_{p/s} 0.3431 (g/g) was obtained using calcium carbonate concentration of 1.0 g/L and aeration of 1.3 vvm.The data obtained by varying calcium carbonate concentration ( X), fixing aeration at 1.3 vvm, can be observed in Figure 4. The analysis of Figure 4 reveals that the maximum substrate conversion into exopolysaccharides was also obtained under the following condition: at calcium carbonate concentration of 1.0 g/L and agitation of 800 rpm._{3}Figure 3 and Figure 4 also show that an increase on agitation and aeration parameters promotes an increase on Y The application of the regression model (Equation 1) for the substrate/exopolysaccharides factor, Y The process for exopolysaccharides production is carried out under aeration and agitation. The control of such parameters is of great importance for adequately conducting the fermentation process. According to Brock and Madigan (1991), for a rise in biomass from aerobic microorganisms, a vigorous aeration is required, what should be reached by forced aeration. This induced aeration is essential for getting high performance responses form the process, since oxygen is slightly soluble in water, not being quickly replaced by air diffusion, and worthwhile for microbial growth. Zevenhuizen (1986), using a mannitol-rich culture medium, has directed the polysaccharide synthesis towards exopolysaccharides by applying forced aeration. The efficiency in conducing forced aeration is linked to agitation, which favours oxygen diffusion in the medium and its transfer to cells. Agitation also promotes a reduction in nutrient particles, favouring the nutrient homogenization in the culture medium, providing additionally a rise in mass transfer rates, this favouring microbial growth. In the production medium used for obtaining biopolymers, several ions are added to propitiate the exopolysaccharides, and these shall be in appropriate amounts. The metallic ions perform catalytic and essential structural functions in proteins, being accumulated inside the cell by active transport (Macció et al. 2002). The literature tells about the use of calcium carbonate to prevent the acidification of the bacterial broth (Macció et al. 2002). Jordan (1984) suggested the use of 4.0 g/L of calcium carbonate in the culture media, for controlling pH in the In agreement with the data presented in this study the yield income values of the product (Y
Most researches developed using The analysis of the response surfaces obtained by the experimental design, with central and having Y The introduction of calcium carbonate, in the composition of the culture media, associated with high agitation and aeration, promoted a significant rise in the substrate/product yield (Y Based on the present study, it is evident that the use of statistical optimization tools, response surface methodology, has helped to locate the optimum levels of the most significant parameters for exopolysaccharides production, with minimum effort and time.
ABDEL-FATTAH, Yasser Refaat. Optimization of thermostable lipase production from a thermophilic ABDEL-FATTAH, Yasser Refaat and OLAMA, Zakia A. L-asparaginase production by ABDEL-FATTAH, Yasser Refaat; SAEED, Hesham M.; GOHAR, Yousry M. and EL-BAZ, Mohamed A. Improved production of AMERICAN SOCIETY FOR TESTING MATERIAL (ASTM). Standard specification for reagent water. ASTM D-1193, October 2001, p. 1-3. BOHN, John A. and BEMILLER, James N. (1→3)-β-D-glucans as biological response modifiers: a review of strutucture-funcional activity relationships. BOX, G.E.P.; HUNTER, W.G. and HUNTER, J.S. Statistics for experimenters. An introduction to design, data analysis and model building. NY, USA. 1978. 653 p. ISBN 0-471-09315-7. BREEDVELD, M.W.; ZEVENHUIZEN, L.P.T.M. and ZEHNDER, A.J.B. Excessive excretion of cyclic β-(1,2)-glucan by BREEDVELD, M.W.; ZEVENHUIZEN, L.P.T.M.; CANTER CREMERS, H.C.J. and ZEHNDER, A.J.B. Influence of growth conditions on production of capsular and extracellular polysaccharides by BROCK, T.D. and MADIGAN, M.T. CAZETTA, M.L.; CELLIGOI, M.A.P.C.; BUZATO, J.B.; SCARMINO, I.S. and DA SILVA, R.S.F. Optimization study for sorbitol production by COPETTI, Giuliano; GRASSI, Mario; LAPASIN, Romano and PRICL, Sabrina. Synergic gelation of xanthan gum with locust bean gum: a rheological investigation. DUTA, Flávia Pereira; DA COSTA, Antonio Carlos Augusto; LOPES, Léa Maria De Almeida; BARROS, Ana; SÉRVULO, Eliana Flávia Camporese and de FRANÇA, Francisca Pessôa. Effect of Process Parameters on Production of a Biopolymer by GORE, R.S. and MILLER, K.J. Cell surface carbohydrates of microaerobic, nitrogenase-active, continuous culture of JAGODZINSKI, Paul P.; WIADERKIEWICZ, Richard; KURZAWSKI, Grzegorz; KLOCZEWIAK, Marek; NAKASHIMA, Hideki; HYJEK, Elizabeth; YAMAMOTO, Naoki; URYU, Toshiyuki; KANEKO, Yutaro; POSNER, Marshall R. and KOZBOR, Danuta. Mechanism of the inhibitory effect of curdlan sulfate on HIV-1 infection JAIN, D.K.; PREVOST, D. and BORDELEAU, L.M. Role of bacterial polysaccharides in the derepression of ex-planta nitrogenase activity with rhizobia. JORDAN, D.C. Family III. KHANNA, Shilpi and SRIVASTAVA, Ashok K. Statistical media optimization studies for growth and PHB production by KIM, H.O.; LIM, J.M.; JOO, J.H.; KIM, S.W.; HWANG, H.J.; CHOI, J.W. and YUN, J.W. Optimization of submerged culture condition for the production of mycelial biomass and exopolysaccharides by KIM, H.M.; KIM, J.G.; CHO, J.D. and HONG, J.W. Optimization and characterization of UV-curable adhesives for optical communications by response surface methodology. LAKSHMAN, Kshama; RASTOGI, N.K. and SHAMALA, T.R. Simultaneous and comparative assessment of parent and mutant strain of LEE, Kwang-Min and GILMORE, David F. Formulation and process modeling of biopolymer (polyhydroxyalkanoates: PHAs) production from industrial wastes by novel crossed experimental design. LIU, Chuanbin; LIU, Yan; LIAO, Wei; WEN, Zhiyou and CHEN, Shulin. Application of statistically-based experimental designs for the optimization of nisin production from whey. MACCIÓ, Daniela; FABRA, Adriana and CASTRO, Stella. Acidity and calcium interaction affect the growth of MOREIRA, A. da S.; SOUZA, A. da S. and VENDRUSCOLO, Claire T. Determinação da composição de biopolímero por cromatografia em camada delgada: metodologia. MYERS, R.H. and MONTGOMERY, D.C. Response surface methodology: process and product optimization using designed experiments. New York: Wiley, 2002. 824 p. ISBN 0-471-41255-4. NAWANI, N.N. and KAPADNIS, B.P. Optimization of chitinase production using statistics based experimental designs. NETO, B.B.; SCARMÍNIO, I. and BRUNS, R.E. Planejamento e otimização de experimentos, Editora UNICAMP, Campinas, Brasil, 1995. 299 p. ISBN 8-526-80336-0. O' HARA, Graham W.; GOSS, Thomas J.; DILWORTH, Michael J. and GLENN, Andrew R. Maintenance of intracellular pH and acid tolerance in PINTO, Ellen; MOREIRA, Angelita and VENDRUSCOLO, Claire T. Influence of pH, addition of salts and temperature in the viscosity of biopolimers produced by RINAUDO, Marguerite. Relation between the molecular structure of some polysaccharides and original properties in sol and gel states. SENTHILKUMAR, S.R.; ASHOKKUMAR, B.; RAJ, K. Chandra and GUNASEKARAN, P. Optimization of medium composition for alkali-stable xylanase production by SOTO, María José; VAN DILLEWIJIN, Pieter; MARTÍNEZ-ABARCA, Francisco; JIMÉNEZ-ZURDO, José I. and TORO, Nicolás. Attachment to plant roots and TANYILDIZI, M. Saban; OZER, Dursun and ELIBOL, Murat. Optimization of α-amylase production by WANG, Yun-Xiang and LU, Zhao-Xin. Optimization of processing parameters for the mycelial growth and extracellular polysaccharide production by WEUSTER-BOTZ, Dirk. Experimental design for fermentation media development: statistical design or global random search? ZEVENHUIZEN, L.P.T.M. Selective synthesis of polysaccharides by Note: Electronic Journal of Biotechnology is not responsible if on-line references cited on manuscripts are not available any more after the date of publication. |

Home | Mail to Editor | Search | Archive |