Enzymatic synthesis of fructooligosaccharides with high 1-kestose concentrations using response surface methodology Roberto Vega a , M.E. Zúniga-Hansen a,b,⇑ a School of Biochemical Engineering, Pontificia Universidad Católica de Valparaíso, Avenida Brasil 2147, Valparaíso, Chile b Regional Centre for the Study of Healthy Foods (CREAS), Blanco 1623, Oficina 1402, Valparaíso, Chile article info Article history: Received 5 May 2011 Received in revised form 1 September 2011 Accepted 6 September 2011 Available online 13 September 2011 Keywords: Fructooligosaccharide Kestose Short chain fructooligosaccharide synthesis Fructosyltransferase abstract Response surface methodology was used as an optimization tool for the production of short chain fruc- tooligosaccharides (sc-FOS) using the commercial cellulolytic enzyme preparation, Rohapect CM. Three independent variables, temperature, concentrations of sucrose and enzyme were tested in the reaction medium. The responses of the design were, yield (g sc-FOS/100 g initial sucrose), 1-kestose (g/100 g sc- FOS) and volumetric productivity (g sc-FOS/L h). Significant effects on the three responses included a qua- dratic effect (temperature), a linear effect (sucrose and enzyme concentrations) and an interaction between temperature and sucrose concentration. The cost-effective conditions to support the process in a high competitive market were 50 °C, 6.6 TU/mL enzyme, 2.103 M sucrose in 50 mM acetate buffer at pH 5.5, and the synthesis for a 5 h reaction time. Under these conditions, a high Y P/S (63.8%), Q P (91.9 g/L h) and sGF2 (68.2%) was achieved. Ó 2011 Elsevier Ltd. All rights reserved. 1. Introduction Short chain fructooligosaccharides (sc-FOS) of the inulin type constitute one of the most recognized groups of prebiotic oligosac- charides (Ballesteros et al., 2007; Nemukula et al., 2009). Their phys- iological functions are directly related to the indigestibility of sc-FOS in the upper gastrointestinal tract, which promotes the selective growth of bifidobacteria in the large intestine (Hirayama, 2002). This recognition has increased their demand in the food industry; how- ever, the supply of sc-FOS is limited due to the fact that enzymes such as fructosyltransferases (b-fructofuranosidase, EC 3.2.1.26 or b-D-fructosyltransferase, EC 2.4.1.9) are not commercially available. Pectinex Ultra SP-L, a pectinolytic and cellulolytic preparation de- signed for fruit juice processing, has been suggested as a source of food-grade fructosyltransferase because this enzyme has been found in the commercial preparation (Antošová et al., 2008; Ghazi et al., 2006). Reaction conditions to obtain high yields of sc-FOS have been determined using fructosyltransferases of Aspergillus japonicus, Pectinex Ultra SP-L and Aureobasidium pullulans (Cruz et al., 1998; Hang and Woodams, 1996; Madlová et al., 1999). Transfruc- tosylation is favored over hydrolysis at high concentrations of su- crose and by the reaction conditions such as, pH (4.5–6.5), temperature (50–60 °C), reaction time (3–5 h) and high ratios of transferase and hydrolase activities of the enzyme (Ghazi et al., 2006; Nemukula et al., 2009). However, there are no studies on the interactions between the reaction conditions. The optimization of the production of syrups consisting largely of a fructooligosac- charide with a specific degree of polymerization at high yield and volumetric productivity has also not been studied. Transfructosylation is a complex reaction with efficient kinetic controls because sc-FOSs are potential substrates of the reaction (Monsan and Paul, 1995). A higher yield of sc-FOS can be obtained as the duration of the reaction progresses (approximately 55–60%); however, a large amount of 1-kestose is transformed to nystose. 1-Kestose has more sweetening power than other sc-FOS, and 1-kestose-rich sc-FOS syrups can be used as sugar for diabetics (Yun, 1996). The chain length is an important factor influencing the physiological effect of the oligomer in the host (Biedrzycka and Bielecka, 2004; Yoshida et al., 2006) and fermentation by bif- idobacteria and lactobacilli species (Kaplan and Hutkins, 2000; Sannohe et al., 2008). Working with mice and in vitro experiments, Suzuki et al. (2006) have observed the superiority of 1-kestose over syrups consisting largely of nystose in the selective growth of bif- idobacteria, but the relevance of these studies to the human gut microflora remains unknown. Yoshida et al. (2006) reported that 1-kestose and nystose can modulate the intestinal microflora and immune system in mice with different degrees of effectiveness. The authors suggested that the ratios of 1-kestose and nystose in the sc-FOS mixture can be changed to improve their biological activity in the host. In a study with infants, Shibata et al. (2009) administered 1-kestose for the treatment of atopic dermatitis (AD) and found a significant improvement in the SCORAD (Clinical 0960-8524/$ - see front matter Ó 2011 Elsevier Ltd. All rights reserved. doi:10.1016/j.biortech.2011.09.025 ⇑ Corresponding author at: School of Biochemical Engineering, Pontificia Universidad Católica de Valparaíso, Avenida Brasil 2147, Valparaíso, Chile. Tel.: +56 32 2273650; fax: +56 32 2273803. E-mail address: [email protected](M.E. Zúniga-Hansen). Bioresource Technology 102 (2011) 10180–10186 Contents lists available at SciVerse ScienceDirect Bioresource Technology journal homepage: www.elsevier.com/locate/biortech
Transcript
Bioresource Technology 102 (2011) 10180–10186
Contents lists available at SciVerse ScienceDirect
Enzymatic synthesis of fructooligosaccharides with high 1-kestoseconcentrations using response surface methodology
Roberto Vega a, M.E. Zúniga-Hansen a,b,⇑a School of Biochemical Engineering, Pontificia Universidad Católica de Valparaíso, Avenida Brasil 2147, Valparaíso, Chileb Regional Centre for the Study of Healthy Foods (CREAS), Blanco 1623, Oficina 1402, Valparaíso, Chile
a r t i c l e i n f o a b s t r a c t
Article history:Received 5 May 2011Received in revised form 1 September 2011Accepted 6 September 2011Available online 13 September 2011
Response surface methodology was used as an optimization tool for the production of short chain fruc-tooligosaccharides (sc-FOS) using the commercial cellulolytic enzyme preparation, Rohapect CM. Threeindependent variables, temperature, concentrations of sucrose and enzyme were tested in the reactionmedium. The responses of the design were, yield (g sc-FOS/100 g initial sucrose), 1-kestose (g/100 g sc-FOS) and volumetric productivity (g sc-FOS/L h). Significant effects on the three responses included a qua-dratic effect (temperature), a linear effect (sucrose and enzyme concentrations) and an interactionbetween temperature and sucrose concentration. The cost-effective conditions to support the processin a high competitive market were 50 �C, 6.6 TU/mL enzyme, 2.103 M sucrose in 50 mM acetate bufferat pH 5.5, and the synthesis for a 5 h reaction time. Under these conditions, a high YP/S (63.8%), QP
(91.9 g/L h) and sGF2 (68.2%) was achieved.� 2011 Elsevier Ltd. All rights reserved.
1. Introduction transferase and hydrolase activities of the enzyme (Ghazi et al.,
Short chain fructooligosaccharides (sc-FOS) of the inulin typeconstitute one of the most recognized groups of prebiotic oligosac-charides (Ballesteros et al., 2007; Nemukula et al., 2009). Their phys-iological functions are directly related to the indigestibility of sc-FOSin the upper gastrointestinal tract, which promotes the selectivegrowth of bifidobacteria in the large intestine (Hirayama, 2002). Thisrecognition has increased their demand in the food industry; how-ever, the supply of sc-FOS is limited due to the fact that enzymessuch as fructosyltransferases (b-fructofuranosidase, EC 3.2.1.26 orb-D-fructosyltransferase, EC 2.4.1.9) are not commercially available.Pectinex Ultra SP-L, a pectinolytic and cellulolytic preparation de-signed for fruit juice processing, has been suggested as a source offood-grade fructosyltransferase because this enzyme has beenfound in the commercial preparation (Antošová et al., 2008; Ghaziet al., 2006).
Reaction conditions to obtain high yields of sc-FOS have beendetermined using fructosyltransferases of Aspergillus japonicus,Pectinex Ultra SP-L and Aureobasidium pullulans (Cruz et al.,1998; Hang and Woodams, 1996; Madlová et al., 1999). Transfruc-tosylation is favored over hydrolysis at high concentrations of su-crose and by the reaction conditions such as, pH (4.5–6.5),temperature (50–60 �C), reaction time (3–5 h) and high ratios of
2006; Nemukula et al., 2009). However, there are no studies onthe interactions between the reaction conditions. The optimizationof the production of syrups consisting largely of a fructooligosac-charide with a specific degree of polymerization at high yieldand volumetric productivity has also not been studied.
Transfructosylation is a complex reaction with efficient kineticcontrols because sc-FOSs are potential substrates of the reaction(Monsan and Paul, 1995). A higher yield of sc-FOS can be obtainedas the duration of the reaction progresses (approximately 55–60%);however, a large amount of 1-kestose is transformed to nystose.
1-Kestose has more sweetening power than other sc-FOS, and1-kestose-rich sc-FOS syrups can be used as sugar for diabetics(Yun, 1996). The chain length is an important factor influencingthe physiological effect of the oligomer in the host (Biedrzyckaand Bielecka, 2004; Yoshida et al., 2006) and fermentation by bif-idobacteria and lactobacilli species (Kaplan and Hutkins, 2000;Sannohe et al., 2008). Working with mice and in vitro experiments,Suzuki et al. (2006) have observed the superiority of 1-kestose oversyrups consisting largely of nystose in the selective growth of bif-idobacteria, but the relevance of these studies to the human gutmicroflora remains unknown. Yoshida et al. (2006) reported that1-kestose and nystose can modulate the intestinal microflora andimmune system in mice with different degrees of effectiveness.The authors suggested that the ratios of 1-kestose and nystose inthe sc-FOS mixture can be changed to improve their biologicalactivity in the host. In a study with infants, Shibata et al. (2009)administered 1-kestose for the treatment of atopic dermatitis(AD) and found a significant improvement in the SCORAD (Clinical
evaluations of AD using Severity Scoring of Atopic Dermatitis)score in kestose-treated subjects.
It is well-known that high temperatures and high enzyme con-centrations in the reaction medium accelerate the transfructosyla-tion rate, which improves volumetric productivity; however,1-kestose is converted more quickly to nystose under these condi-tions. Therefore, the factors affecting the process can be optimizedaccording to the required final product specifications. Responsesurface methodology can be applied to this process as an optimiza-tion tool (Montgomery, 2004).
Screening of commercial food-grade enzyme preparations forfructosyltransferases suitable for the production of sc-FOS (Vegaand Zuniga-Hansen, 2010), revealed high levels of transfructosyla-tion activity in Rohapect CM. This enzyme preparation, obtainedfrom Trichoderma reesei, is employed in cleaning of UF-membranesused in the fruit juice and wine industries. In the current study,conditions were determined for producing sc-FOS from sucrosewhile obtaining a high percentage of 1-kestose using Rohapect CM.
2. Methods
2.1. Materials
Rohapect CM was obtained from AB Enzymes GmbH (DimercoComercial Ltda., Chile). Wako Chemicals (Richmond, VA, USA) pro-vided 1-kestose, nystose and 1F-fructofuranosylnystose standards.A glucose–oxidase–peroxidase enzymatic kit was obtained fromSpinreact (San Esteve de Bas, Spain). Other reagents were pur-chased from Sigma Chemical (St. Louis, MO, USA) or Merck (Darms-tadt, Germany).
2.2. Enzyme assay
Rohapect CM had 12,000 TU/mL of transfructosylation activity.One unit of TU was defined as the amount of enzyme required totransfer 1 lmole of fructose per min under the following condi-tions: 1.169 M sucrose in sodium acetate buffer (50 mM, pH 5.5),50 �C and stirring at 150 rpm. At various time points over 5 min,4 mL aliquots were withdrawn from the reaction mixture. Thereaction was stopped by heat-inactivating the enzyme in boilingwater for 10 min. Glucose concentration (G) and reducing sugars(R) were estimated by an enzymatic kit and the Somogy–Nelsonmethod, respectively. The concentrations of both fructose (F) andtransferred fructose (FT) in the reaction medium were computedusing Eq. (1) (Chen and Liu, 1996)
F ¼ R� G and FT ¼ G� F ð1Þ
Table 1Values of independent variables at different levels of the experimental design.
Sucrose and reaction products (sc-FOS, glucose and fructose)were analyzed with high-performance liquid chromatography(HPLC) using Perkin–Elmer Series 200 equipment with a refractiveindex detector, an autosampler and TotalChrom software (version6.3.1). The column type was BP-100 Ag+ (300 mm � 7.8 mm, Ben-son Polymeric, Reno, NV, USA). The column temperature was main-tained at 50 �C, and the detector temperature was kept at 45 �C.The samples (10 lL) were eluted with 0.4 mL/min of Milli-Q water.A chromatogram of the reaction mixture is illustrated in theSupplementary data.
2.4. Experimental design
The experiments were performed in 20 mL sucrose solution inan acetate buffer (50 mM, pH 5.5) at 150 rpm. The pH of the
reaction medium was 5.5, which did not significantly affect sc-FOS production, when it was studied as a factor over time (pH:5.0–6.5). Other experimental conditions were the same as in Sec-tion 2.2, except for the 0.4 mL aliquot that was removed from thereaction mixture. Temperature and the concentration of sucroseand the enzyme were studied. A rotational central composite de-sign of the three variables with three central points was appliedto determine the optimal conditions of temperature and the con-centration of sucrose and the enzyme. The levels of the indepen-dent variables are presented in Table 1 and are coded as shownin Eq. (2).
xi ¼ 2ðXi � XicpÞ=DXi ð2Þ
where xi is the coded level of the ith variable, Xi is the level of the ithnatural variable, Xicp is the ith natural variable at the center point,and DXi is the step change value of the ith natural variable. Table2 presents the way that experiments are to be conducted for theplanning of the 17 trials.
The responses were yield (YP/S), 1-kestose in sc-FOS (sGF2) andvolumetric productivity (QP), which were reported after 3 or 5 hreaction time. YP/S was defined as sc-FOS grams per 100 g of initialsucrose. sGF2 was defined as 1-kestose grams per 100 g of sc-FOS.QP was defined as sc-FOS grams per reactor volume and reactiontime (g/L h).
2.5. Statistical analysis
The results were analyzed using STATISTICA for Windows Ver-sion 8.0 (StatSoft. Inc. 2007, USA). Differences were considered sig-nificant at p-values 6 0.05.
3. Results and discussion
3.1. Fitting model, adequacy and model adequacy checking
The results of the experimental design after 3 or 5 h reactiontime are shown in Tables 3 and 4, respectively. The second tofourth column are the results obtained for YP/S, sGF2 and QP, whichwere the responses of the experimental design. sGF2 and QP in allof the experiments presented in Table 3 were greater than those inTable 4, in contrast, the YP/S was lower. This low yield represented alarge amount of remaining sucrose, which is not sustainable in ahighly competitive market. A higher YP/S, such as 60%, can be a goodcompromise between sc-FOS production, 1-kestose concentrationand sucrose remaining. We focus on the results on the experimen-tal design after a 5 h reaction time (Table 4). sGF2 varied accordingto the reaction conditions from 53.9% to 81.9%. Higher sGF2s wereachieved in Trials 2, 3, 9, 14 and 16 under different experimentalconditions, but YP/Ss were lower than in other trials.
A Pareto chart for each response with all of the possible stan-dardized effects is illustrated in Fig. 1 at a 0.05 level of significance.It was observed that temperature (quadratic effect) had the great-est influence, followed by enzyme concentration (linear effect) onYP/S; whereas for sGF2, enzyme concentration (linear effect), tem-perature (quadratic effect), interaction between temperature andsucrose concentration and then the sucrose concentration (lineareffect) had a significant effect. The strongest effect on QP was
Table 3Experimental design of three variables and the observed responses after a 3 h reaction tim
sucrose concentration (linear effect), followed by temperature(quadratic effect) and, finally, the enzyme concentration (linear ef-fect). For further analysis, the other effects were pooled into the er-ror since they were negligible at a 0.05 level of significance. Thesame results were observed in a normal probability plot versus astandardized effect estimate (figure not shown).
As can be seen in Fig. 1a, the effect of sucrose concentration onYP/S was not significant for the levels of study, even at sucrose con-centrations less than 0.292 M because the fructosyltransferase ofRohapect CM possesses the ability to bind the acceptor, fructosylmoiety, and to exclude H2O (Ballesteros et al., 2007); however,the sucrose concentration had a strong positive influence on QP
and less on sGF2 (Fig. 1b and c).An analysis of the variance (ANOVA) of the reduced model was
required to confirm both results obtained by graphical methodsand the model’s adequacy. The results of response surface modelof the second order, fitting in the form of ANOVA (Table 5), indi-cated that the quadratic effect of temperature, the linear effect ofboth the sucrose and enzyme concentrations, and the interactionbetween temperature and sucrose concentration were significantto the sGF2 response. The highest p-value (267.8 � 10�4) of
Fig. 1. Pareto chart of the magnitudes of the standardized effects at a 5 h reactiontime for a yield of sc-FOS (a), 1-kestose in sc-FOS (b), and the volumetricproductivity of sc-FOS (c). The independent variables (coded) were temperature(x1), sucrose concentration (x2) and enzyme concentration (x3).
significant effects was found for the sucrose concentration. Thelack of fit of the quadratic model was not significant(p = 998.9 � 10�4). Non-significant lack of fit is a good indicationthat the model fits the actual relationship of the reaction parame-ters within the selected levels.
ANOVA of the reduced model for the YP/S and QP responses con-firmed the significant factors obtained by the Pareto chart; how-ever, the lack of fit of the quadratic model was significantrelative to the pure error for both responses. In this case it wasnot possible to fit the data to a second order polynomial; therefore,
the optimization was not performed. YP/S and QP responses for theexperimental run 9, Table 4, were far from the bell-shaped regionthat described the responses of other experimental runs. Thisexperimental run was atypical describing a region as a non-symmetrical curve, which was caused largely by the effect of tem-perature (Bas and Boyaci, 2007). The catalytic activity wasgradually lost when the reaction was incubated at a temperatureof 63.4 �C because YP/S and QP did not reach the typical valuesshown in Table 4. This phenomenon was due to thermal inactiva-tion of the enzyme (data not shown). In contrast, the threeresponses of the experimental design shown in Table 3 fitted verywell to a second order polynomial.
The goodness-of-fit of the reduced model was verified by thecoefficient of determination R2, which was 0.929 for sGF2. Approx-imately 100R2 = 92.9%, of the variability of the observed responsecan be explained by the fitted model in the coded form of Eq. (3).According to Haaland (1989), values above 0.90 are considered tobe very good. In addition, the adjusted determination coefficient(Adj. R2) was 0.905 for the model of Eq. (3). This value ensuredthe satisfactory adjustment of the polynomial model to the exper-imental data. The adjusted R2 corrects the R2 value for sample sizeand number of terms in the model. If there are many terms in themodel and if the sample size is not very large, the adjusted R2 maybe noticeably smaller than R2 (Haaland, 1989). In our case, the ad-justed R2 was close to the R2 value.
The coefficients of Eq. (3) were obtained by a multiple regres-sion analysis on the experimental data using the least squaresmethod.
The significance of each coded coefficient was determined byStudent’s t-test and p-values as listed in Table 6. Small p-valueswere associated with large t-values, which imply that coefficientsare much greater than the standard error (Haaland, 1989).
The verification of the adequacy of the sGF2 model was basedon an analysis of the residuals. The error must be normally distrib-uted, be independent with a zero mean and have homogeneousvariance (Montgomery, 2004). The normal probability plot of thestudentized deleted residuals (data not shown) did not indicateany violations of the fundamental assumptions of the analysis orany atypical points.
3.2. Characterization of the response surface
When regression coefficients were obtained, the stationarypoint of the response surface for sGF2 could be computed(x1s = 0.413, Ts = 57.1 �C; x2s = 0.867, Ss = 2.076 M; x3s = Non-existence). The characterization of the system around thestationary point was performed by a canonical analysis. The modelof Eq. (3) was displaced to a new center, which was the stationarypoint, whose associated axes are called the principal axes ofresponse system. Thus, we obtain
SGF2 ¼ SsGF2þX3
i¼1
kiW2i ð4Þ
where SsGF2 is the response at the stationary point, Wi are thetransformed independent variables, and ki are the polynomial equa-tion eigenvalues in matrix notation, which were k1 = 5.11,k2 = �0.82 and k3 = 0. Given that k1 and k2 have different signs,the stationary point is a saddle point for any value that is assignedto x3 because it linearly affects each response.
Fig. 2a illustrates the effect of both sucrose concentration andtemperature on sGF2 with 5.4 TU/mL of enzyme concentration.The W2 canonical variable plays a lesser role than the W1 canonicalvariable because the k2 magnitude is relatively smaller than the k1
Table 5Analysis of variance (ANOVA) for the second-order model of the sGF2 response after a 5 h reaction time.
Factor Sum of squares d.f. Mean square F-value Probability p (>F)a
magnitude for the sGF2 response. This figure indicates that theheight of the fitted surface changes faster as it moves along the W1
axis (where it increases in value) than when it moves along the W2
axis. The interaction between temperature and sucrose concentra-tion is represented by contour lines of elliptical shapes in Fig. 2a(Box et al., 2005). Strictly speaking, the response surface for sGF2is a sloping ridge (the k1 eigenvalue is positive; Montgomery,2004), but it can be approximated as a stationary ridge becausethe stationary point is not very remote from the design origin (Boxet al., 2005).
sGF2 began to decrease when the sucrose concentration andtemperature were lower than 1.694 M and 55 �C, respectively.Therefore, the lower value for this response within the experimen-tal matrix can be obtained with 1.555 M sucrose and at 50 �C whenthe enzyme concentration is 5.4 TU/mL. In addition, there was anincrease in the sGF2 response as the sucrose concentration wasincreased, reaching a maximum response on the sucrose axis(Ss = 2.076 M). Thus, there was also an increase in the sGF2response as the temperature was increased or decreased with aminimal response on the temperature axis (Ts = 57.1 �C). The inter-action between temperature and sucrose concentration can beexplained by the theory that attributes decrease at the rate ofthe enzymatic reactions to the effect of the thermodynamic non-ideality at high concentrations of saccharides (Antošová et al.,2008), which is modulated by temperature. In addition, thermalinactivation of the enzyme was another factor that affected theinteraction; it had a high impact when the experimental conditionswere 1.694 M sucrose and 60 �C or 1.899 M sucrose and 63.4 �C.This result can be explained by the protective effect of a high con-centration of sucrose and possibly of sc-FOS (Lee and Timasheff,1981; Madlová et al., 2000).
Fig. 2b depicts the effects of both enzyme concentration andtemperature on sGF2 with 1.899 M sucrose. The k1 eigenvaluemeasures the quadratic curve along the W1 axis. An increase inthe amount of enzyme causes a linear decrease for sGF2. The sur-face of Fig. 2b shows a sloping ridge predicting a lower sGF2 whenthe enzyme concentration increased and temperature increased ordecreased with a minimum value of the response at 57.1 �C. Thehigher values for the YP/S and QP responses were observed at highenzyme concentrations (Table 4, Fig. 1a and c), but lower values
of sGF2 response were found under this condition, indicating acompromise among these responses. The main effect of tempera-ture on the three responses was quadratic. On one side of the par-abolic curve, the temperature increased the transfructosylationrate which reached a minimum in the sGF2 response at 57.1 �C.Under these conditions, a higher conversion of 1-kestose to nystosewas performed. On the other side of the parabolic curve (T = 60 �C)the effect of the temperature was on the catalytic activity of thebiocatalyst. The transfructosylation rate was high at the start ofthe reaction, but as the reaction progressed, the enzyme was ther-mally inactivated and the conversion rate of 1-kestose to nystosebecame slower. Moreover, Fig. 2b shows that the contour linesare parabolas given that there is no interaction between tempera-ture and enzyme concentration (Box et al., 2005). The effect of theinteraction between temperature and sucrose concentration isapparent when the minimum points of the parabolas are displacedto positive levels of temperature due to an increase in sucroseconcentration.
Fig. 2c illustrates the linear effects (k2 � 0 and k3 = 0) of differ-ent enzyme and sucrose concentrations on sGF2 at 55 �C. This sur-face is more sensitive to changes in enzyme concentration thansucrose concentration. The fitted surface depicts an increase insGF2 when there is a decrease in enzyme concentration and an in-crease in sucrose concentration. Therefore, when the reaction med-ium is 3.4 TU/mL of enzyme concentration and 2.243 M sucrose atthe temperature of 55 �C, sGF2 can be between 75% and 80%; thisresult can be explained by the amount of biocatalyst in the reactionmedium. The reaction rate is slow with a low concentration of theenzyme, which decreases the rate of conversion of 1-kestose tonystose at a 5 h reaction time. In addition, sucrose concentrationhas been accepted as one of the key factors influencing the maxi-mum yield of 1-kestose because it increases the availability offructosyl moiety acceptors and decreases the availability of water(Gosling et al., 2010).
A ridge analysis was used to find optimal values for the sGF2 re-sponse on spheres centered at some point in the predictive vari-ables (a selected ‘‘focus’’, T = 55 �C, S = 2.103 M and E = 5.4 TU/mL) because the canonical analysis indicated that the stationarypoint was a saddle point, which is typically useless. This focus,which we denote here by f was selected based on the results
Fig. 3. The maximum predicted response sGF2 and its corresponding positionalcoordinates (T, S, E) are plotted against R, the distance the point lies from the focusf = (55 �C, 2.103 M, 5.4 TU/mL). d Kestose percentage (sGF2), j temperature (�C), Nsucrose (M), � enzyme (TU/mL).
Fig. 2. Response surfaces and contour plots at a 5 h reaction time for 1-kestose insc-FOS as a function of sucrose and temperature, enzyme = 5.4 TU/mL (a), enzymeand temperature, sucrose = 1.899 M (b), enzyme and sucrose, temperature = 55 �C(c).
shown in Fig. 2 because the high concentration of sucrose favoredthe sGF2 response. The ridge analysis can be used as a tool to help
interpret an existing response surface or in our case mark out alocus or path of highest response when moving from the focus.
A solution x for the maximum sGF2 response on a sphere of ra-dius R is by solving Eq. (5) (Box and Draper, 2007).
x ¼ �12ðB� lIÞ�1ðbþ 2lfÞ ð5Þ
Subject to the constraints:
R ¼ ðx� fÞ0ðx� fÞ
And any value l > k = 5.11 (highest eigenvalue for Eq. (3)). Where Bis a symmetric matrix containing all second-order coefficients and bis a matrix containing all first-order coefficients for Eq. (3).
Fig. 3 shows how the estimated maximum response values varyfrom 67% to 90% kestose on spheres of different radii R. This figuredepicts the maximum expected response when the operating con-ditions are moved away from the focus and shows the correspond-ing positional coordinates of the maximum responses. It is inagreement with Fig. 2, so in order to maximize the sGF2 responseshould increase the sucrose concentration and decrease the en-zyme concentration, as well as decreasing the temperature withreference to this focus. This analysis has provided useful informa-tion regarding the roles of design variables within the experimen-tal region. Ridge analysis can provide some guidelines regardingwhere future experiments should be made in order to achievethe conditions that are more desirable; however, this analysis didnot consider the YP/S and QP responses. Therefore, the independentvariables that predict some point in the locus of maximumresponse may be an experimental condition where the yield andvolumetric productivity do not fulfill the specifications for a com-petitive process. With this in mind, it is possible to select theexperimental run 10 and 11 as the most appropriate conditionsto achieve high yield, high volumetric productivity and high per-centage of 1-kestose, but we select the experimental run 11(50 �C, 2.103 M, 6.6 TU/mL, Fig. 4) because the remaining concen-tration of sucrose was lower than in the experimental run 10.
Sc-FOS production on an industrial scale is made from a 60% to70% (w/v) sucrose solution and achieves a 55% to 60% sc-FOS yield.Our results are consistent with the results for the scaling processthat were reported by other authors (Yun, 1996; Sangeetha et al.,2005), although in this study the application of the responsesurface methodology has led to a high volumetric productivity anda high 1-kestose percentage catalyzed by a commercial enzymepreparation. These results and the low cost of this enzyme prepara-tion support its use for the scaling of the sc-FOS production. In our
Fig. 4. Time course of the synthesis of sc-FOS catalyzed by Rohapect CM.Experimental conditions were 2.103 M sucrose in 50 mM acetate buffer (pH 5.5),6.6 TU/mL enzyme and 50 �C (experimental run 11, Table 4). In the reaction wasdetected trace amounts of fructose when we compare with a control experiment. NKestose, j nystose, d fructofuranosylnystose, � sucrose, . glucose, s total sc-FOS.
case, volumetric productivity achieved values higher than those re-ported in the literature by batch operation (3.25, 6.61 g/L h; Prataet al., 2010; Mussatto et al., 2009), solid-state fermentation(10.76 g/L h; Mussatto and Teixeira, 2010) even with semi-continuous operation (45 g/L h; Yun and Song, 1996). In addition,the kestose composition in the syrup was approximately doubledwith respect to the composition of the commercial preparationMeioligo� (Meiji Seika Kaisha, Ltd, Tokyo, Japan; Suzuki et al., 2006).
The fructosyltransferase of Rohapect CM exhibited a high abilityto transfer fructosyl moieties to an acceptor other than H2O, as nodecline in total sc-FOS profile was observed after an 8 h reactiontime (Fig. 4). This reaction is independent of the global kinetic con-trol mechanisms and can be stopped according to defined objec-tives, such as the peak of a fructooligosaccharide, kestose/nystoseratio and sucrose conversion. The reaction time is a very importantparameter with which to control these processes.
4. Conclusions
Rohapect CM catalyzed the sc-FOS synthesis under all of theexperimental conditions, which is remarkable for its potentialuse as biocatalyst for the industrial processing of sucrose into sc-FOS syrup. Using response surface methodology, it was possibleto determine the cost-effective conditions of temperature (50 �C),sucrose concentration (2.103 M) and enzyme concentration(6.6 TU/mL) to support the process in a high competitive market.Under these conditions, a high YP/S (63.8%), QP (91.9 g/L h) andsGF2 (68.2%) was achieved. The results showed that the processis inexpensive, simple and can be used on an industrial scale.
Acknowledgements
This research was financially supported by the Project FONDEFDO7I1045 of Chile and the CREAS. In addition, we acknowledge thefinancial support (scholarship) of CONICYT for our PhD student,R.Vega. We are grateful to Matias Berndt (Dimerco Comercial Ltda.,Chile) for the enzyme sample.
Appendix A. Supplementary data
Supplementary data associated with this article can be found, inthe online version, at doi:10.1016/j.biortech.2011.09.025.
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