Statistical optimization of xylanase production from new isolated Penicillium oxalicum ZH-30 in submerged fermentation

Statistical optimization of xylanase production from new isolated Penicillium oxalicum ZH-30 in submerged fermentation

Biochemical Engineering Journal 34 (2007) 82–86 Short communication Statistical optimization of xylanase production from new isolated Penicillium ox...

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Biochemical Engineering Journal 34 (2007) 82–86

Short communication

Statistical optimization of xylanase production from new isolated Penicillium oxalicum ZH-30 in submerged fermentation Yin Li a,∗ , Zhiqiang Liu b , Hui Zhao a , Yingying Xu c , Fengjie Cui d a

Department of Plant Science, North Dakota State University, Fargo, ND 58105, USA Institute of Bioengineering, Zhejiang University of Technology, Hangzhou 310014, PR China c Department of Cereal and Food Science, North Dakota State University, Fargo, ND 58105, USA d School of Food Engineering and Biotechnology, Jiangsu University, Zhenjiang 2120013, PR China b

Received 19 June 2006; received in revised form 25 September 2006; accepted 13 November 2006

Abstract This research aimed at optimizing fermentation condition (initial pH and temperature) of xylanase production from Penicillium oxalicum ZH-30 by statistical analysis using response surface methodology. Statistical analysis of results showed that the linear, quadric terms and interaction of these two variables had significant effects. The optimal conditions for higher production of xylanase were: initial pH 7.38 and temperature = 31.1 ◦ C. The predicted and verified xylanase activities under optimal condition were 14.33 and 14.50 U/mL, respectively. The temperature range suitable for the industrial application of xylanase from P. oxalicum ZH-30 was 50–60 ◦ C. © 2006 Elsevier B.V. All rights reserved. Keywords: Penicillium oxalicum ZH-30; Optimization; Response surface methodology; Xylanase

1. Introduction Xylanase (1,4-␤-d-xylan-xylanhydrolase, EC 3.2.1.8) catalyzes the hydrolysis of xylan, the major component of hemicellulose in plant cell walls, to xylo-oligosaccharides and xylose. A variety of microorganisms, including bacteria [1,2], yeast [3] and filamentous fungi [4,5], have been reported to produce xylanases. The potential applications of xylanase, with or without concomitant use of cellulase, include biocoversion of ligocellulose to sugar, ethanol and other useful substances, degradation of arabinoxylans in brewing [6], clarification of microflitration membrane [7], and nutritional value improvement of silage and green feed [8]. The xylanase production by microorganisms is strongly influenced by many factors, such as nutritional sources [9–11] and cultivation condition [12–14]. Classical experimental design requires that only one variable be changed at a time to determine its effect. Such work is extremely laborious and time-consuming using the conventional techniques such as ‘one-factor-at-a-time’ method, and moreover, it does not guarantee the determina-



Corresponding author. Tel.: +1 701 231 7737. E-mail address: [email protected] (Y. Li).

1369-703X/$ – see front matter © 2006 Elsevier B.V. All rights reserved. doi:10.1016/j.bej.2006.11.011

tion of optimal conditions, and often fails to consider the combined effects of all involved factors [15]. Response surface methodology (RSM) is a collection of mathematical and statistical technique useful for analyzing the effects of several independent variables. Usually, this process employs a low-order polynomial equation in a pre-determined region of independent variables, which is later analyzed to locate the optimum values of the independent variables for the best response. Recently, different statistical designs for fermentation condition optimization regarding xylanase production have been reported, among which factorial experiments and response surface methodology (RSM) are included [16–18]. These statistical methods have proved to be powerful and useful. The objective of the present work was to apply statistical methods to optimize fermentation parameters for enhancing the xylanase production by Penicillium oxalicum ZH-30. Two variables, initial pH and temperature, were selected as process (independent) variables while xylanase production was the response (dependent variable). An empirical model including the effects of independent variables has also been developed through SAS software to represent the response surface. The thermal stability of xylanase from P. oxalicum ZH-30 was reported in this work as well.

Y. Li et al. / Biochemical Engineering Journal 34 (2007) 82–86

2. Materials and methods 2.1. Microorganism The P. oxalicum ZH-30 strain was isolated from soil and identified according to the morphology and comparison of ITS rDNA gene sequence (DQ473437). It was maintained at 4 ◦ C on potato dextrose agar (PDA) in our laboratory. Spores suspensions were prepared from 6-day-old cultures that had been grown on PDA slopes at 30 ◦ C. Sterile distilled water was aseptically added to each slope and a suspension of the spores was made by lightly brushing the mycelium with a sterile wire loop. The suspension was diluted with sterile distilled water to give a final spore count of 1 × 107 spores/mL. 2.2. Media and cultivation The medium used for xylanase production was composed of (g/L): NH4 Cl 9; KH2 PO4 1; NaNO3 1; MgSO4 ·7H2 O 1; CaCl2 ·2H2 O 0.3; yeast extract 1. The agricultural waste wheat bran (10 g/L) was added to the medium. The pH was adjusted according to the experimental design. The media was then autoclaved for 20 min at 121 ◦ C. Erlenmeyer flasks (250 mL) containing 75 mL of medium were inoculated with 1 mL of diluted spore suspension and then were maintained at 30 ◦ C on a rotary shaker under 150 rpm for 15.4, 48, 96, 144 or 176.6 h, according to the experimental design. At the end of fermentation, the mycelium was separated from the enzyme-containing broth by centrifugation at 10,000 × g for 15 min to obtain the crude enzyme. 2.3. Experimental design Response surface methodology (RSM) was used to optimize the fermentation conditions for enhanced xylanase production. Central composite design (CCD) with two factors and five levels, including five replicates at the center point, was used for fitting a second-order response surface. The CCD contained an imbedded factorial or fractional factorial matrix with center points and “star points” around the center point that allow estimation of the

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curvature [19]. One unit was designated to the distance from the center of the design space to a factional point, while α unit was designated to the distance from the center of the design space to a star point. The star points represent new extreme values (low and high) for each factor in this design. If the factorial is a full factorial then 1/4

α = [2k ]

(1)

In this study k = 2 factors (pH and temperature), so α = 1.414. Table 1 gives the factors and their values, and the experimental design, respectively. This methodology allows the modeling of a second-order equation that describes the process. Xylanase production was analyzed by multiple regressions through the least squares method to fit the following equation:    β i xi + βij xi xj + βij xi2 (2) Y = β0 + where Y is the measured response variable; β0 , βi , βij , βii are constant and regression coefficients of the model, and xi , xj represent the independent variables in coded values. Data from the central composite design for the optimization of xylanase production was subjected to a second-order multiple regression analysis using the least squares regression methodology to obtain the parameter estimators of the mathematical model. The regression analysis and analysis of variance (ANOVA) were carried out using the RSREG procedure of the SAS statistical package (Version 8.1, SAS Institute, Cary, NC, USA) to fit second-order polynomial equations for all response variables. Canonical analysis, which was used to predict the shape of the curve generated by the model, was carried out as well. Response surface was made by the fitted quadratic polynomial equation obtained from RSREG analysis. 2.4. Analytical method The xylanase activity was determined by measuring the release of reducing sugars from oat spelt xylan (1%, w/v) using the dinitrosalicylic acid method [20]. The reaction mixture containing 1 mL of a solution of 1% oat spelt xylan in a citrate buffer 50 mM, pH 5.0 plus 1 mL of the diluted crude enzyme, was incu-

Table 1 Box-Behnken experiments design matrix with experimental and predicted values of xylanase production by Penicillium oxalicum ZH-30 Runs

1 2 3 4 5 6 7 8 9 10 11 12 13

Coded setting levels

Actual levels

Xylanase production (U/mL)

X1 (pH)

X2 (temperature)

X1 (pH)

X2 (temperature)

Experimental

Predicted

−1 −1 1 1 −1.414 1.414 0 0 0 0 0 0 0

−1 1 −1 1 0 0 −1.414 1.414 0 0 0 0 0

7 7 9 9 6.6 9.4 8 8 8 8 8 8 8

25 35 25 35 30 30 23 37 30 30 30 30 30

7.76 11.82 1.94 1.25 13.11 1.68 1.72 7.20 11.64 13.10 12.48 11.58 12.86

7.30 12.46 1.54 1.94 13.03 1.51 2.38 6.32 12.33 12.33 12.33 12.33 12.33

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bate for 30 min at 50 ◦ C. One unit of xylanase was defined as the amount of enzyme required to released 1 ␮mol of xylose from xylan in 1 min under the assay condition. 2.5. Partial purification of xylanases by ammonium sulphate fractionation A calculated amount of solid ammonium sulphate was added to the culture supernatant with constant stirring at 10 ◦ C to achieve 40% saturation. After centrifugation at 8000 × g at 4 ◦ C for 20 min the precipitate was discarded and the supernatant was subsequently adjusted to 40–70% saturation by addition of calculated amounts of ammonium sulphate. The precipitate was dissolved in a small volume of citrate buffer (50 mM, pH 5.0). The enzyme solution was subjected to dialysis for about 18–24 h at 10 ◦ C against 50 mM citrate buffer (pH 5.0) fortified with 100 ppm sodium azide, with three intermittent changes of the buffer. Xylanase activity and protein estimation were carried out as well. 2.6. Protein assay Protein quantitative analysis was determined by the Bradford method [21] with bovine serum albumin as a standard. 2.7. Determination of themostability of partially purified xylanase The thermal stability was determined at the temperatures 50, 55, 60, 65 and 70 ◦ C after incubation of suitably diluted enzyme samples in absence of substrate for 0, 15, 30, 45 and 60 min. 3. Results and discussion 3.1. Xylanase activity optimization For response surface methodology (RSM) based on the central composite design, which was used to optimize the cultivation conditions for xylanase production, 13 experimental runs with the combination of two factors were carried out (Table 1). The

variables used in the factorial analysis were initial pH and temperature named X1 , X2 in this design, respectively. The maximum xylanase production was 13.11 U/mL in run 5, while the minimum xylanase production was 1.25 U/mL in run 4. This result suggested that the xylanase from P. oxalicum ZH-30 had a higher enzyme activity at neutral pH. Statistical testing of the model was done by the Fisher’s statistical test for analysis of variance (ANOVA) and the results are shown in Table 2. The computed F-value (91.91) was much higher than the F-value in statistic tables [19]. Usually, the higher the value of CV, the lower the reliability of experiment is. Here, a lower value of CV (9.60) indicated a greater reliability of the experiments performed. The goodness of a model can be checked by the determination coefficient (R2 ) and correlation coefficient (R). The determination coefficient (R2 ) implies that the sample variation of 98.5% for xylanase production is attributed to the independent variables, and only about 1.5% of the total variation cannot be explained by the model. The closer the value of R (correlation coefficient) to 1, the better the correlation between the experimental and predicted values. Here the value of R (0.992) for Eq. (3) being close to 1 indicated a close agreement between the experimental results and the theoretical values predicted by the model equation. Linear, crossproduct and quadratic terms were significant at the 5% level. Therefore, the quadratic model was selected in this optimization study. The Student’s t-distribution and the corresponding values of the variable estimation are also shown in Table 2. Significance of coefficients has been reported to be directly proportional to t-value and inversely to P-value [22]. The parameter estimates and the corresponding P-values suggest that the independent variables X1 (pH) and X2 (temperature) have a significant effect on xylanase production. Positive coefficient for X2 indicated a linear effect to increase xylanase production, while negative coefficient for X1 was observed to decrease xylanase production in a linear effect. The quadric term of these two variables also had a significant effect. The model clearly revealed a significant interaction between pH and temperature (P < 0.0207). In this case, X1 , X2 , X12 X22 , X1 X2 are significant model terms. By applying multiple regression analysis on the experimental data, the following second-order polynomial equation was found

Table 2 Analysis of variance for the response of xylanase production Model term

Degree of freedom

Estimate

Standard error

Sum of squares

F-value

P-value

X1 X2 X1 2 X1 X2 X2 2 Linear Quadratic Crossproduct

1 1 1 1 1 2 2 1

−4.07 1.39 −2.53 −1.19 −3.99

0.28 0.28 0.30 0.40 0.30

132.47 15.46 44.42 5.64 111.01 147.93 139.58 5.64

208.45 24.32 69.90 8.88 174.67 115.96 109.41 8.84

<0.0001* 0.0017* <0.0001* 0.0207* <0.0001* <0.0001 <0.0001 0.0207

Total model Total error

5 7

293.15 4.47

91.91

<0.0001

Coefficient of variation (CV) = 9.60; coefficient determination (R2 ) = 0.985; correlation coefficient (R) = 0.992. * Significant at 5% level (P < 0.05).

Y. Li et al. / Biochemical Engineering Journal 34 (2007) 82–86

Fig. 1. Response surface plot of the combined effects of pH and temperature on the xylanase activity by Penicillium oxalicum ZH-30.

to explain the xylanase production: Y = 12.33 − 4.07pH + 1.39T − 2.53pH2 − 1.19pH × T −3.99T 2

(3)

where Y is the predicted response (xylanase production). The fitted response surface plot and their corresponding counter plot for the xylanase production from P. oxalicum ZH30 by the above model were given in Figs. 1 and 2, respectively. The contour plots affirmed that the objective function is unimodal in nature showing an optimum in the boundaries. The

Fig. 2. Contour plot of the combined effects of pH and temperature on the xylanase activity by P. oxalicum ZH-30.

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boundary optimum point was evaluated using gradient method in the direction of steepest ascent. The contour plots clearly revealed that there were no saddle points within the experimental region. Fig. 2 depicts the contour plot showing the effect of pH and temperature on the xylanase production. As shown in Fig. 2, decreasing the pH within the tested range was beneficial to improvement of xylanase production under submerged fermentation. The study of Fig. 2 indicates that the maximum xylanase production could be obtained in the range of pH 7–7.5 and temperature 30–32.5 ◦ C. The statistical optimal values of variables are obtained when moving along the major and minor axis of the contour and the response at the center point yields maximum xylanase production. These observations were also verified from canonical analysis of response surface. Canonical analysis revealed a minimum region for the model. The stationary point presenting a maximum xylanase had the following critical values: initial pH 7.38, temperature = 31.1 ◦ C. The predicted xylanase activity for these conditions was 14.33 U/mL. A repeat fermentation of xylanase by P. oxalicum ZH-30 under optimal conditions was carried out for the verification of optimization. The maximal xylanase level obtained was 14.50 U/mL. This value was found to be 2.7% less than the predicted value. This discrepancy might be due to the slight variation in experimental conditions. The optimization resulted in 10.6-fold increase of xylanase production, compared with the lowest xylanase production of 1.25 U/mL at run 4 in central composite design. 3.2. Thermal stability of xylanase from P. oxalicum ZH-30 Ammonium sulphate fractionation (40–70% saturation) of crude xylanase yielded 80.3% of the enzyme with 3.54-fold purification. Thermal stability is a very important aspect of enzymatic bioreactors. Utilization of enzymes in industrial processes often encounters the problem of thermal inactivation of the enzyme. In fact, enzymes containing a number of extremophilic characteristics may be of the most use in industry. Thermal stability assessment of partially purified xylanase from P. oxalicum ZH-30 were carried out by preincubating the enzyme up to 60 min at 50, 55, 60, 65, 70 ◦ C, respectively (Fig. 3). The xylanase retained 86.1 and 82.4% activity at 50 and 55 ◦ C, respectively, after 60 min preincubating. The enzyme was sensitive at 65 ◦ C, retaining 45.1% activity after 15 min and only 15.5% activity left after 60 min. At 70 ◦ C, the enzyme activity was completely inactivated (0.9%) within 15 min. These results clearly indicated that the suitable temperature range for industrial application for xylanase from P. oxalicum ZH-30 was 50–60 ◦ C. Belancic et al. [23] reported that xylanases from Penicillium purpurogenum lost about 40% of their activities when kept for 3 h at 60 ◦ C. Sinitsyna et al. [24] also reported the similar properties of xylanase from Penicillium canescens. The properties of partially purified xylanase from P. oxalicum ZH-30 indicated its possible use in processed at moderate temperature which may include preparation of baked cereal food products and degradation of arabinoxylans in brewing. At the beginning of mashing, the mashing-in temperature was around 50 ◦ C, which

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Y. Li et al. / Biochemical Engineering Journal 34 (2007) 82–86

Fig. 3. Themostability of partially purified xylanase from P. oxalicum ZH-30.

was a favorable temperature for xylanase to degrade arabinoxylans polymers into xylo-oligosaccharides [6]. The enzymatic degradation of these polymers would increase wort filterability and reduce haze in the final product. The applications of xylanase from P. oxalicum ZH-30 in brewing science are now in progressing. 4. Conclusion To the best of our knowledge, there are no reports of optimization of xylanase production by P. oxalicum ZH-30 using statistical experimental design. Statistical optimization of cultivation conditions using central composite design appears to be a valuable tool for the production of xylanase by P. oxalicum ZH-30. The predicted and verifiable xylanase activities under optimal conditions were 14.33 and 14.50 U/mL, respectively. The suitable temperature range for industrial application of xylanase from P. oxalicum ZH-30 was 50–0 ◦ C. References [1] V.B. Damiano, D.A. Bocchini, E. Gomes, R.D. Silva, Application of crude xylanase from Bacillus licheniformis 77-2 to the bleaching of eucalyptus Kraft pulp, World J. Microbiol. Biotechnol. 19 (2003) 139–144. [2] A. Dhillon, S. Khanna, Production of a thermostable alkali-tolerant xylanase from Bacillus circulans AB 16 grown on wheat straw, World J. Microbiol. Biotechnol. 16 (2000) 325–327. [3] J. Gomes, I. Gomes, W. Steiner, Thermolabile xylanase of the Antarctic yeast Cryptococcus adeliae: production and properties, Extremophiles 4 (2000) 227–235. [4] Y. Li, J. Lin, D. Meng, J. Lu, G. Gu, Z. Mao, Effect of pH, cultivation time and substrate concentration on the xylanase production by Aspergillus awamori ZH-26 under submerged fermentation using central composite rotary design, Food Technol. Biotechnol. 44 (2006) 473–477. [5] B.C. Saha, Production, purification and properties of xylanase from a newly isolated Fusarium proliferatum, Process Biochem. 37 (2002) 1279–1284.

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