International Journal of Biological Macromolecules 61 (2013) 63–68
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International Journal of Biological Macromolecules journal homepage: www.elsevier.com/locate/ijbiomac
Response surface optimization of enzyme-assisted extraction polysaccharides from Dictyophora indusiata Songhai Wu a , Guili Gong a , Yanyan Wang a , Feng Li a , Shaoyi Jia a , Fengxiang Qin a , Haitao Ren a , Yong Liu a,b,∗ a b
School of Chemical Engineering and Technology, Tianjin University, Tianjin, PR China School of Chemistry and Chemical Engineering, Tianjin University of Technology, Tianjin, PR China
a r t i c l e
i n f o
Article history: Received 20 April 2013 Received in revised form 31 May 2013 Accepted 23 June 2013 Available online xxx Keywords: Dictyophora indusiata polysaccharides Enzyme-assisted extraction Response surface methodology Optimization
a b s t r a c t An enzyme-assisted procedure for the extraction of the water-soluble polysaccharides from the stipe of Dictyophora indusiata was investigated using response surface methodology. The orthogonal array design was employed to optimize the concentration of three kinds of enzyme (cellulase, papain and pectolyase) and the optimal cellulose, papain and pectolyase concentration were 2.0% (wt.% of D. indusiata powder), 2.0% and 1.5%, respectively. And then the effect such as temperature, time and pH was studied based on a three-level three-factor Box–Behnken design. The optimized conditions were as follows: extraction temperature 52.5 ◦ C, extraction time 105 min and pH 5.25. Under these conditions, the experimental yield of polysaccharides was 9.77 ± 0.18%, which was well matched with the predictive yield of 9.87%. As it turned out, enzyme-assisted procedure was an effective method. © 2013 Elsevier B.V. All rights reserved.
1. Introduction Dictyophora indusiata (Chinese name Zhu-Sun, the bamboo fungi) is an edible mushroom well-accepted by consumers in China and other Asian countries [1]. It is called “veiled lady mushroom” or “queen of the mushrooms” due to its beautiful appearance, delicious taste and health benefit [2–4]. D. indusiata polysaccharides (DIPs) are the main bioactive ingredient of D. indusiata, which exhibited several potent bioactivities, such as anticancer, mental tranquilization, antitumor, and tonics, and so forth [5,6]. In order to discover its promising functions, Li & Wang [3] studied the antioxidant properties of DIPs in vitro. Hua et al. [1] analyzed the structure of DIPs and their antioxidant activities in vivo. However, up to now, little attention was devoted to the extraction of DIPs. Conventional techniques to obtain polysaccharides, such as heating, boiling, or refluxing, have been widely investigated [7–9]. Nonetheless, they usually require long extraction time and high extraction temperature, but achieve low extraction efficiency relatively. Recently, compound enzymes assisted extraction, which is considered as a mild, efficient and environmentally friendly method, has been shown to have immense research potential to
improve the yield of the target component used in the extraction of constituents from different plants [10–12]. Response surface methodology (RSM) is a strategy involving statistical approach, which applies in the optimization of conditions in food and pharmaceutical research frequently. It is an empirical statistical technique for multiple regression analysis by using quantitative data obtained from properly designed experiments to optimize extraction processes [13–16]. As one type of RSM, Box–Behnken design (BBD) used to optimize technical parameters is quite convenient and prevalent to other approaches required in optimizing a process, such as saving materials, decreasing expenses, reducing time, and so on [17]. The present work was aimed to investigate the extraction process of water-soluble DIPs with compound enzymes (cellulase, papain and pectolyase) based on the results of three different single enzymes extraction, and further to optimize other extraction conditions for obtaining higher yield of DIPs by RSM based on BBD. As far as we known, there were no reports available in the literature regarding the optimization of enzyme-assist extraction of DIPs with compound enzymes by RSM.
2. Materials and methods ∗ Corresponding author at: School of Chemistry and Chemical Engineering, Tianjin University of Technology, Tianjin, PR China. Tel.: +86 2287401961; fax: +86 2287401961. E-mail address:
[email protected] (Y. Liu). 0141-8130/$ – see front matter © 2013 Elsevier B.V. All rights reserved. http://dx.doi.org/10.1016/j.ijbiomac.2013.06.036
2.1. Materials D. indusiata (dried product) was purchased from a local commercial market in Tianjin, China.
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Table 1 Results of orthogonal experiment. Number
(A)
(B) a
1 (1.0% ) 1 1 2 (1.5%a ) 2 2 3 (2.0%a ) 3 3 4.91 7.21 8.23 3.32
1 2 3 4 5 6 7 8 9 R1 R2 R3 R
Table 2 Independent variables and their levels used in the response surface design. The yield of DIPsb
(C) a
1 (1.0% ) 2 (1.5%a ) 3 (2.0%a ) 1 2 3 1 2 3 6.47 7.13 6.74 0.66
a
1 (1.5% ) 2 (2.0%a ) 3 (2.5%a ) 2 3 1 3 1 2 6.78 7.22 6.35 0.44
4.59 4.67 5.46 8.36 7.12 6.14 6.46 9.30 8.62
−1
0
1
90 40 4
120 50 5
150 60 6
X1 : extraction time (min); X2 : temperature (◦ C); X3 : pH.
Papain from papaya latex (P3250, 0.5–2 /mg) was supplied by Sigma Chemical Company. Cellulase (0.3 /mg), Pectolyase (≥5 /mg) and d-glucose was obtained from Tianjin Zhi En Biotechnological Co., Ltd. and all other reagents were purchased from Tianjin Guangfu Fine Chemical Research Institute. All other reagents used in this study were of analytical grade. 2.2. Methods 2.2.1. Extraction procedure The stipe of D. indusiata were ground into powder and passed through 80 mesh screen. Then, in a designed temperature, extraction time and pH, the powder (1 g) was extracted with 30 mL of compound enzymes solution at the given concentration. Watersoluble crude polysaccharides were isolated by precipitation of the concentrated supernatant with 4 volumes of dehydrated alcohol and recovered by centrifugation. The polysaccharides content was measured by phenol–sulfuric acid method with d-glucose as a standard at 490 nm [18]. The yield of polysaccharides in the stipe of D. indusiata was calculated by the following equation: polysaccharides yield% (w/w) polysaccharides weigh × 100 Dictyophora indusiata powder weight(1 g)
Factor levels
X1 X2 X3
A: papain concentration; B: pectolyase concentration; C: cellulose concentration. a On weight of dry D. indusiata powder basis. b Determined using the phenol–sulfuric acid method.
=
Independent variables
(1)
2.2.2. Orthogonal array design (OAD) of compound enzymes concentrations To investigate the optimal concentrations of cellulase, papain and pectolyase, an orthogonal array design was employed with the extraction conditions as follows: pH 5, temperature 50 ◦ C, and extraction time 120 min. In Table 1, the extraction experiments were carried out with 3 factors and 3 levels, and the range of each factor was according to the results of fundamental single-factor experiments. The yield (%) of DIPs was the dependent variable and was acquired according to the method in Section 2.2.1. 2.2.3. Box–Behnken design and statistical analysis A Box–Behnken experimental design was used to further determine the optimum enzyme-assisted extraction conditions of DIPs on the basis of orthogonal results of compound enzymes concentrations. A three-factor (X1 , extraction time; X2 , temperature; X3 , pH) BBD at three levels was chosen to evaluate their combined effect. For each factor, the experimental range was selected based on the results of single factor experiments. As seen from Table 2, the coded and uncoded (actual) levels of the independent variables were presented based on preliminary experimental results. And Table 3
shows the whole design consisted of 15 experimental points, and all the experiments were carried out in random order to minimize any effect on the observed responses. All trials were conducted in triplicate. SAS (Version9.2, USA) software package was used for the experimental design, variance and regression analysis of the experimental data. The data from BBD was explained multiple regressions to fit the following second-degree polynomial equation: yk = bk0 +
3
bki xi +
i=1
3
bkii xi2 +
i=1
3
bkij xi xj
(2)
i RB ≈ RC . The optimal combination parameters were pectolyase concentration of 1.5%, cellulase and papain concentration of 2.0%. In these conditions, the 9.42% extraction yield could be reached.
3.4. Effect of pH on extraction yield of polysaccharides To investigate the influence of pH on the yield of DIPs, different pH was set at 3–7 when the other extraction conditions were as
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Fig. 2. The 3D plots (A, C, and E) and 2D contour plots (B, D and F) showing the effects of variables (X1 : extraction time, min; X2 : temperature, ◦ C; X3 : pH) on extraction yield of DIPs.
3.6. Optimization of the procedure by RSM 3.6.1. Statistical analysis and the model fitting A total of 15 experimental points for optimizing the three individual parameters in the BBD, including extraction time (x1 ), temperature (x2 ) and pH (x3 ), was shown in Table 3. Three replicates (exp. Nos. 13–15) at the center of the design were adopted to estimate a pure error sum of squares. By applying multiple regression analysis on the experimental data, the mathematical model describing the relationship of response variable and the test variables was given by the following second-order polynomial equation: y = 9.62 − 0.17x1 + 0.66375x2 + 0.96875x3 − 0.30875x12 − 0.72x1 x2 − 2.39625x22 + 0.16x1 x3 + 0.6975x2 x3 − 2.09125x32 (3)
A summary of the analysis of fit statistics of extraction yield (y) for the selected quadratic predictive model and the coefficient values of Eq. (3) calculated for their significance using SAS version 9.2 was listed in Table 4. The model fits well with the experimental data, as the determination coefficient R2 and the adjusted determination coefficient Adj. R2 had values of 98.76% and 96.52%, respectively. This indicated that the fitted model was highly significant, which could achieve a high degree of correlation (98.76%) between the observed and predicted values for the production of DIPs and only 1.24% of the total variations were not explained by the model. At the same time, a quite low coefficient value of the variation (C.V.) (5.03%) clearly indicated a rather high degree of precision and a good deal of reliability of the experimental values [20]. This meant that polysaccharides extraction results could be analyzed and predicted by the model. The P-value was used as a tool to check the significance of each coefficient that may in turn reveal the pattern of the interactions between the variables. The smaller the P-value, the more significant the corresponding coefficient was
S. Wu et al. / International Journal of Biological Macromolecules 61 (2013) 63–68 Table 4 Test of significance for regression coefficients.
Table 5 Predicted and experimental extraction yield of DIPs at optimal conditions.
Effect
Estimate
Stand error
t-ratio
P-value
x1 x2 x3 x1 × x1 x1 × x2 x1 × x3 x2 × x2 x2 × x3 x3 × x3
−0.17 0.66375 0.96875 −0.30875 −0.72 0.16 −2.39625 0.6975 −2.09125
0.125601 0.125601 0.125601 0.18488 0.177627 0.177627 0.18488 0.177627 0.18488
−1.35349 5.284589 7.712913 −1.67 −4.05344 0.900765 −12.9611 3.926774 −11.3114
0.2339 0.0032a 0.0006a 0.1558 0.0098a 0.4090 0.05) from the predicted value of 9.87%. These data proved that the model designed in this study was valid (Table 5).
3.6.2. Response surface plot and contour plot showing effects of extraction variables on yield of polysaccharides The graphical representations of the regression Eq. (3), termed as the response surfaces and the contour plots were obtained using SAS v9.2 and presented in Fig. 2. These three-dimensional (3D) plots and two-dimensional (2D) contour plots provided a visual interpretation of the interactions between two variables and ease the location of optimum experimental conditions while the third variable is fixed at the 0 level. Different shapes of contour plots could reflect different strength of the interaction effects between the variables. Elliptical contours were obtained when there was a perfect interaction between the independent variables while circular contour plots indicated otherwise [22]. As seen from Fig. 2(A) and (B), where the extraction yield of DIPs was given as a function of extraction time and temperature at fixed pH (0 level), the extraction yield of DIPs increased with increase of temperature from 40 to 52.5 ◦ C, while the extraction yield of DIPs decreased above 52.5 ◦ C due to the lower enzyme activity at higher temperatures [19]. When temperature was set, extraction yield of DIPs also increased with extraction time increasing from 90 to 105 min. However, a continued increase of the extraction time produces a decrease in response. The 2D contour plot indicated that the mutual interaction between temperature and extraction time was significant (P = 0.0098). Fig. 2(C) and (D) showed the 3D response surface plot and the contour plot at varying extraction time and pH when temperature was fixed (0 level). They indicated that extraction yield of DIPs increased rapidly when the pH increased from 4 to 5.25, and then began to decrease when the pH continued to increase. At a fixed pH, the variety of extraction yield of DIPs was slight when the extraction time increased. In Fig. 2(E) and (F), when the 3D plot and the 2D contour plot were developed for the extraction yield of DIPs with varying extraction temperature and pH at fixed extraction time (0 level), maximum extraction yield of DIPs was achieved when extraction temperature and pH were 52.5 ◦ C and 5.25, respectively. According to Fig. 2, the optimal extraction conditions of DIPs with the optimal compound enzymes concentrations (pectolyase concentration of 1.5%, cellulase and papain concentration of 2.0%) were obtained from response surface analysis as follows: extraction time 104.94 min, extraction temperature 52.51 ◦ C, pH 5.25, and the model predicted a maximum response of 9.87%. Based on the significance of regression coefficients in the quadratic polynomial model (Table 4) and gradient of slope in the 2D plot (Fig. 2), pH was the
4. Conclusion Enzyme-assisted extraction, which was an efficient and environmentally friendly extraction technique, could be used to improve the extraction yield of DIPs. Firstly, we acquired the optimal compound enzymes concentrations (pectolyase concentration of 1.5%, cellulase and papain concentration of 2.0%) by an orthogonal test design. Then to further optimize DIPs extraction, extraction time, temperature and pH were studied by RSM. The second-order polynomial model gave a satisfactory description of the experimental data. In order to obtain the desired level of DIPs extraction, the optimum point of extraction time 105 min, extraction temperature 52.5 ◦ C and pH 5.25was achieved vividly. Under the optimal conditions, the experiment extraction yield of DIPs was 9.77 ± 0.18%, which was in accord with the predicted value of 9.87% closely. Acknowledgments We greatly acknowledge the financial support from the National Natural Science Foundation of China (XH, No. 41003040; YL, No. 41201487), the Natural Science Foundation of Tianjin (XH, No. 10JCYBJC06000). We are also grateful for the Construction of Technical Platform 160 for Pharmaceutical Separation and Refinement (No. 2009ZX09301-008). References [1] Y. Hua, B. Yang, J. Tang, Z. Ma, Q. Gao, M. Zhao, Carbohydrate Polymers 87 (2012) 343–347. [2] M. Zhang, S.W. Cui, P.C.K. Cheung, Q. Wang, Trends in Food Science & Technology 18 (2007) 4–19. [3] X. Li, Z. Wang, L. Wang, E. Walid, H. Zhang, International Journal of Molecular Sciences 13 (2012) 5801–5817. [4] J. Wang, X. Xu, H. Zheng, J. Li, C. Deng, Z. Xu, J. Chen, Journal of Agricultural and Food Chemistry 57 (2009) 5918–5924. [5] Y.B. Ker, K.C. Chen, C.C. Peng, C.L. Hsieh, R.Y. Peng, Evidence-Based Complementary and Alternative Medicine 2011 (2011) 1–9, 396013. [6] C.K. Hara, Carbohydrate Research 110 (1982) 77–87. [7] W. Yang, Y. Fang, J. Liang, Q. Hu, Food Research International 44 (2011) 1269–1275. [8] B. Yang, J. Wang, M. Zhao, Y. Liu, W. Wang, Y. Jiang, Carbohydrate Research 341 (2006) 634–638. [9] Y.F.A. Luo, A. Luo, Journal of Medicinal Plants Research 5 (2011) 966–972. [10] A. Niu, J. Wu, D. Yu, R. Wang, International Journal of Biological Macromolecules 42 (2008) 447–449.
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