Synthesis of Short Chain Fructooligosaccharides with �-fructofuranosidase

ZENG Jie , YU Xiao-ling ,ZHAO Xiu-hong , LI Guang-lei , LIANG Xin-hong 1 1 2 1 1 1. School of Food Science, Henan Institute of Science and Technology, Xinxiang 453003, China; 2. College of Chemistry and Life Science,Shenyang Normal University, Shenyang, 110034 China

zengjie623@163.com; yuxiaoling73@163.com; zhaoxiuhong1976@163.com; liguanglei73@163.com; liangxinhong2005@163.com

Abstract

The influence of temperature, pH, reaction time, and�-fructofuranosidase concentration on the formation of short-chain fructooligosaccharides (FOS) was examined by statistical response surface methodology (RSM). The result showed that enzyme concentration (2.15U g-1 sucrose), temperature (53.97 °C), and pH (5.90) and time (3.68min) favoured the synthesis of high levels of fructooligosaccharide(FOS). 1. Introduction

Fructo-oligosaccharides (FOS) such as kestose (GF2), nystose (GF3) and lF-fructofuranosylnystose (GF4), in which one to three fructose units are bound to the �-2,1 position of sucrose, are mainly made up of 1-kestose, nystose, and �-fructofuranosyl nystose [1].

FOS can be produced by transferring one to three molecules of fructose to the fructose residue in sucrose through the action of �-D-fructosyltransferase (FTase, EC 2.4.1.9) or �-fructofuranosidase (FFase, EC 3.2.1.26) with high transfructosylating activities obtained from plants[2] and microorganisms [3-6].

Response surface methodology (RSM) uses an experimental design such as the central composite design (CCD) to fit a model by least squares technique. If the proposed model is adequate, as revealed by the diagnostic checking provide by an analysis of variance (ANOVA) and residual plots, contour plots can be usefully employed to study the response surface and located the optimum.

The objective of this investigation was to use �-fructofuranosidase to produced FOS and optimize the production conditions by Response Surface Methodology (RSM).

2. Materials and methods

2.1. Materials

�-fructofuranosidase was produced by Aspergillus japonicus 3.3556 strain which was from college of food science, Shenyang Agricultrual University and propagated on potato dextrose agar medium (PDA) at 30°C and maintained at 4°C.

Suctose and other chemicals were analytical grades and obtained from readily available commercial sources.

2.2. Experiment Design

One response was measured: FOS content (Y),

defined as the ratio of total fructo-oligosaccharide produced by �-fructofuranosidase from sucrose. Each of variables to be optimized was coded at 5 levels: -2,-1, 0, 1and 2. Table 1 shows the variables, their symbols and levels. The selection of variable levels was based on our preliminary study.

Table 1 Variables and their levels for central composite design

Coded-variable level Variable Sym

bol -2 -1 0 1 2Temperature( ) X1 40 45 50 55 60

pH X2 5.0 5.5 6.0 6.5 7.0

Time (min) X3 2.5 3.0 3.5 4.0 4.5Enzyme addition

U/g sucrose X4 0.7 1.3 1.9 2.5 3.1

_____________________________ 978-1-4244-3930-0/09/$25.00 ©2009 IEEE

added to the factorial design to provide for estimation of curvature of the model. Twelve replicates (run 25-36) at the center of the design were used to allow for estimation of “pure error” sum of squares. Experiments were randomized in order to minimize the effects of unexplained variability in the observed response due to extraneous factors. 2.3. Analysis of FOS by -fructofuranosidase reaction from sucrose

The products fructo-oligosaccharides by FFase were

separated from the reaction mixture by HPLC. 2.4. Statistic analysis

A software package (Design Expert7.0) was used to fit the second-order models and generate response surface plots. The model proposed for the response (Y) was:

4 4 42

01 1 1

n n nn n tm n mn n n m

Y b b x b x b x x= = ≠ −

= + + +� � �

Where b0 is the value of the fitted response at the center point of the design, which is point (0, 0, 0, 0). Bn, bnn and bnm are the linear, quadratic and cross-product regression terms, respectively.

3. Results and discussion 3.1. Diagnostic checking of the fitted model

ANOVA for the regression was performed to assess the “goodness of fit”. The model for Y was:

Y=-35.24779+8.82805X1+32.15857X2+32.36561X3+

12.75916X

4–2.03750X1 X2+0.16584 X1 X3+ 0.35030 X1 X4–2.01367 X2 X3–2.72769 X2 X4– 2.02777 X3 X4–0.10391 X1

2 –1.63212 X22 –

3.39622 X32–1.86095 X4

2 The result of ANOVA was shown on Table 3. The

Model F-value of 4.50 implies the model was significant. There was only a 0.10% chance that a “Model F-Value” this large could occur due to noise. Values of “Prob > F” less than 0.05 indicated model terms were significant. The “Lack of Fit F-value” of 1.31 implies the Lack of Fit was not significant.

Variables giving quadratic and interaction terms with the largest absolute coefficients in the fitted models were chosen for the axes of contour plots to account for curvature of the surfaces. In Fig. 1a, pH

and enzyme addition were selected for the vertical and horizontal axes respectively for the contour plot and 3D-surface of FOS content, while temperature and time were measured at different levels.

3.2. Response Surface Plotting

Table 2. Central composite design arrangement and response

Variable level Run X1 X2 X3 X4

FOS (%)

1 1 1 1 1 38.7982 1 1 1 -1 35.48523 1 1 -1 1 41.78234 1 1 -1 -1 36.84435 1 -1 1 1 40.48596 1 -1 1 -1 37.23677 1 -1 -1 1 44.87648 1 -1 -1 -1 38.89379 -1 1 1 1 39.7341

10 -1 1 1 -1 37.375811 -1 1 -1 1 41.210812 -1 1 -1 -1 39.427513 -1 -1 1 1 40.764314 -1 -1 1 -1 40.649815 -1 -1 -1 1 35.79816 -1 -1 -1 -1 39.385717 2 0 0 0 41.083318 -2 0 0 0 30.395719 0 2 0 0 45.698520 0 -2 0 0 43.298721 0 0 2 0 41.744522 0 0 -2 0 43.724523 0 0 0 2 44.37624 0 0 0 -2 42.525925 0 0 0 0 42.462526 0 0 0 0 43.756327 0 0 0 0 46.329428 0 0 0 0 46.724329 0 0 0 0 48.726830 0 0 0 0 46.310531 0 0 0 0 40.475632 0 0 0 0 45.747333 0 0 0 0 44.179334 0 0 0 0 43.596735 0 0 0 0 44.200136 0 0 0 0 42.587

In Fig. 1b, Time and enzyme addition were selected

for the vertical and horizontal axes respectively for the contour plot and 3D-surface of FOS content, while temperature and pH were measured at different levels.

Response surface contour plots of the response surface methodology as a function of two factors at a time, holding all other factors at fixed levels (zero, for instance), are more helpful in understanding both the main and the interaction effects of these two factors. These plots can be easily obtained by calculating from the model, the values taken by one factor while the second varies (from -2 to +2, step 1 for instance) with constraint of a given Y value. The yield values for different concentrations of the variables can also be predicted from the respective response surface contour plots .

Table 3. ANOVA for the fitted model Source Sum of

squares df Mean

square F

valueP

valueModel 371.27 14 26.52 4.50 0.001*

Residual 123.73 21 5.89 Lack of Fit 67.27 10 6.73 1.31 0.3309Pure error 56.46 11 5.13 Cor total 494.89 35

* means significant (p 0.05) 3.3. Optimization Based on FOS production

The model is useful in indicating the direction in which to change variables in order to FOS content. The model for Y indicated that temperature, pH and Time were the major variables affecting FOS production. By using Design Expert 7.0 software, the optimum condition were The temperature = 53.97 °C, pH = 5.90, time = 3.68 min and Enzyme addition = 2.15 U/g sucrose could be recommended as a practical optimum. The estimated values for FOS 41.9662 % was obtained at those conditions. A verification experiment at the optimum condition, consisting of 3 runs, was performed and the practical yield of 42.325

% (n=3) was obtained. 4. Conclusion

Optimum production conditions of FOS by FFase could be achieved at temperature 53.97 °C, pH 5.90, time 3.68 min and Enzyme addition 2.15 U/g sucrose. Such conditions resulted in FOS yield of 41.9662 %.

Acknowledgements

The financial support provided by the Science and Technology Plan of Henan institute of science technology (No.7039) was greatly appreciated.

a (Temperature= 50 °C; Time=3min)

b (Temperature= 50 °C; pH=6.0)

Figure 1. Contour plot and 3D surface for FOS production

References [1] H.Hidaka, T.Eida, T.Adachi, and Y.Saitoh, Industrial production of fructooligosaccharides and its application for

human and animals . Nippon Nogeikagaku Kaishi 1987, 61, pp 915-923.

[2] W.C.Chen. “Medium improvement for �-fructofuranosidase production by Aspergillus japonicus”. Process Biochemistry. 1998. 33(3), pp 267-271

[3] K.Fujita, K. Hara, H.Hashimoto, and S.Kitahata, “Purification and some properties of �-fructo furanosidase I from Arthrobacter sp. K-1”. Agricultural and Biological Chemistry ,1990, 54, pp 913-919.

[4] S.Hayashi, K.Matsuzaki, Y.Takasaki, H.Ueno and K.Imada, “Production of �-fructofuranosidase by Aspergillus japonicus”. World Journal of Microbiologyand Biotechnology, 1992, 8, pp 155-159.

[5] Y. C.Su, C. S.Sheu, J. Y.Chien and T. R.Tzan, “Production of �-fructofuranosidase with transfructosylating activity for fructooligosaccharides synthesis by Aspergillus japonicus NTU-1249”. Proceedings of the National Science Council (R.O.C.), PartB 1991, 15, pp 131-139.

[6] J. A.Smith, D.Grove, S. J.Luenser and L. G.Park, “Process for the production of fructose transferase enzyme”. US Patent 4, 1982,309, pp 505,.