Optimisation of the synthesis of high galacto-oligosaccharides (GOS) from lactose with β-galactosidase from Kluyveromyces lactis

International Dairy Journal 61 (2016) 211e219

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Optimisation of the synthesis of high galacto-oligosaccharides (GOS) from lactose with b-galactosidase from Kluyveromyces lactis
lez-Delgado, María-Jose
Lo
pez-Mun ~ oz*, Gabriel Morales, Yolanda Segura Isabel Gonza Department of Chemical and Energy Technology, Chemical and Environmental Technology, Mechanical Technology and Analytical Chemistry, Universidad
n s/n, E-28933, Mo
stoles, Madrid, Spain Rey Juan Carlos, C/ Tulipa

a r t i c l e i n f o

a b s t r a c t

Article history: Received 11 March 2016 Received in revised form 22 June 2016 Accepted 23 June 2016 Available online 1 July 2016

A rational optimisation for the synthesis of galacto-oligosaccharides (GOS) catalysed by a commercial bgalactosidase from Kluyveromyces lactis, Lactozym Pure 6500 L, is shown. The study of the main reaction parameters e temperature, enzyme concentration, pH, initial lactose concentration and reaction time e using surface response methodology, was demonstrated to be an accurate tool to optimise empirical production of the most desired galacto-oligosaccharides (tri-GOS and tetra-GOS) with a higher presumed prebiotic effect. The optimal value for the yield towards these high-GOS predicted by the model was 12.18% at 40
C, 5 U mL1 enzyme concentration, pH 7.0, 250 g L1 initial lactose concentration and 3 h of reaction. The pH was found to be a critical parameter affecting the transgalactosylation/hydrolysis enzyme activity ratio, and was used to tune the relative production of tri- or tetra-GOS. © 2016 Elsevier Ltd. All rights reserved.

1. Introduction Galacto-oligosaccharides (GOS) are oligosaccharides typically produced from lactose that consist of a variable number of galactose units (usually in the range 1e5) combined with a terminal glucose through glycosidic bonds (Gosling, Stevens, Barber, Kentish, & Gras, 2010; Torres, Gonçalves, Teixeira, & Rodrigues, 2010). GOS are non-digestible by the human gastrointestinal tract and can act as prebiotics by stimulating the proliferation of intestinal lactic acid
ndez Rentería, Noe
Aguilar, bacteria and bifidobacteria (Mele
rez Moorillo
n, & Rodríguez Herrera, 2011; Torres et al., 2010; Neva  e
, St tina, & Drya
k, 2006). GOS intake may thus Curda, Rudolfova imply many health benefits such as immunological stimulation, cholesterol reduction, vitamin synthesis and growth inhibition of pathogens (Gosling et al., 2010; Grizard & Barthomeuf, 1999; Iwasaki, Nakajima, & Nakao, 1996; Mussatto & Mancilha, 2007; 
, Curda,
kov

, 2010; Sangwan, Pocedi cova Misún, Drya a, & Diblíkova Tomar, Ali, Singh, & Singh, 2015; Torres et al., 2010; Wallace et al., 2011). On the other hand, galacto-oligosaccharides display a relative
ndez Rentería et al., sweetness about 35% of that of sucrose (Mele 2011) showing low caloric content, thus being excellent non-

* Corresponding author. Tel.: þ34 91 664 74 64.
pez-Mun ~ oz). E-mail address: [email protected] (M.-J. Lo http://dx.doi.org/10.1016/j.idairyj.2016.06.007 0958-6946/© 2016 Elsevier Ltd. All rights reserved.

cariogenic sugar substitutes (Torres et al., 2010). Furthermore, due to their stability at relatively high temperature and at a wide range of pH, GOS can be used in a variety of industries and processes. For example, they are used in the production of baked goods, beverages (fruit juices and other acid drinks), meal replacers, confectionery products or infant milk formula, wherein they can be supplemented with fructo-oligosaccharides (FOS)
ndez Rentería et al., 2011; Torres et al., 2010). Moreover, since (Mele GOS are also natural minor components in human milk and traditional yoghurts and can be produced from ingested lactose by
ndez Rentería et al., 2011; human intestinal microbiota (Mele Torres et al., 2010), their intake has been recognised as safe by the American Food and Drug Administration (GRAS-FDA). In a further aspect, the production of galacto-oligosaccharides also involves economic and environmental profits because it can take advantage of a residue such as whey lactose from cheese production (Audic, Chaufer, & Daufin, 2003; Torres et al., 2010; Yang & Silva, 1995). All these reasons, combined with the high demand for foods with demonstrable health benefits, provide the industrial production of GOS with a promising future. The preferred method for GOS synthesis is via enzymatic catalysis from lactose-rich substrates using glycosyltransferases (EC 2.4) or glycoside hydrolases (EC 3.2.1) as biocatalysts (Torres et al., 2010). Within the latter group, the enzyme b-galactosidase (EC 3.2.1.23) is able to synthesise galacto-oligosaccharides through a transgalactosylation mechanism. This route occurs when the

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lez-Delgado et al. / International Dairy Journal 61 (2016) 211e219 I. Gonza

galactosyl acceptor is another saccharide (e.g., glucose, galactose, lactose or a lower GOS molecule). If the galactosyl acceptor is water, then a hydrolysis reaction takes place, leading to a nondesired hydrolytic degradation of GOS and lactose alike, which produces the release of galactose and glucose units to the medium
et al., 2010; Rodriguez-Colinas, (Gosling et al., 2010; Pocedi cova Poveda, Jimenez-Barbero, Ballesteros, & Plou, 2012; Torres et al., 2010). The traditional use of b-galactosidases has been related to their hydrolytic activity to produce lactose-free milk and dairy products via lactose hydrolysis in aqueous media (PereiraRodríguez et al., 2012). In the context of GOS production, several b-galactosidases from different microorganisms (bacteria, archaea, yeasts and fungi) with proven transgalactosylation activity have been used. In particular, b-galactosidase from the mesophilic yeast Kluyveromyces lactis, which has been widely studied because of its high lactose hydrolysis activity and its dairy environmental habitat (Park & Oh, 2010; Rodriguez-Colinas et al., 2012), has been shown to mainly produce disaccharides (allolactose and 60 -galactobiose) and trisaccharides (60 galactosyl lactose) (Burvall, Asp, & Dahlqvist, 1979, 1980; Asp, Burvall, Dahlqvist, Hallgren, & Lundblad, 1980; Martínez-Villaluenga, Cardelle-Cobas, Corzo, Olano, & Villamiel, 2008; Rodriguez-Colinas et al., 2011). The composition profile of produced GOS is of crucial importance for determining the health benefits provided. Particularly, in a previous study aimed to test the digestibility of GOS it was found that tri- and tetra-saccharides were not hydrolysed in vitro by human salivary a-amylase, artificial gastric juice, a-amylase of hog pancreas, and rat intestinal acetone powder, whereas disaccharides were partially digested by the intestinal enzymes (Chonan et al., 2004; Torres et al., 2010). Moreover, several researchers have demonstrated that tri- and tetra-GOS are completely metabolised by the intestinal gut flora (Macfarlane, Steed, & Macfarlane, 2008; Makras, Van Acker, & De Vuyst, 2005; Rabiu, Jay, Gibson, & Rastall, 2001; Sako, Matsumoto, & Tanaka, 1999). For this reason, the prebiotic effect of GOS is mainly associated with tri-saccharides (tri-GOS) and tetra-saccharides (tetra-GOS) (Gosling et al., 2010; Torres et al., 2010). In general, even though hydrolysis and transgalactosylation reactions take place simultaneously, the desired transgalactosylation reaction can be favoured by tuning the reaction conditions. Therefore, high initial lactose concentrations, moderately elevated temperatures and low water contents tend to favour transgalactosylation over hydrolysis (Martínez-Villaluenga et al., 2008; Torres et al., 2010). Additionally, both the final GOS composition profile in the reaction mixture and the overall GOS yield, are strongly influenced by a number of factors including initial lactose concentration, enzyme source, pH, temperature and reaction time (Gosling et al., 2010). Some of these factors have been individually investigated previously using different b-galactosidase sources such as K. lactis (Kim, Ji, & Oh, 2004; Martínez-Villaluenga et al., 2008) or Aspergillus aculeatus (Cardelle-Cobas, Villamiel, Olano, & Corzo, 2008). Additionally, the complexity of the overall process for the production of GOS, wherein transgalactosylation and hydrolysis reactions take place simultaneously, is increased because the different reactions have different substrates and rates. This makes the use of different approaches necessary for the analysis and optimisation of the enzymatic process. An example of a valid strategy is the surface response methodology, which has been previously applied to the production of GOS from whey permeate or skim milk using different enzymes (Chen, Hsu, & Chiang, 2002;
pez-Leiva, 1998) and from skim milk or lactose Rustom, Foda, & Lo solutions using Bifidobacterium sp. (Osman, Tzortzis, Rastall, & Charalampopoulos, 2010; Roy, Daoudi, & Azaola, 2002).

In this work, the simultaneous influence of the main reaction parameters, i.e., pH, initial lactose concentration and reaction time, for the production and composition of galacto-oligosaccharides using a commercial b-galactosidase preparation from K. lactis (Lactozym Pure 6500 L), has been studied by means of surface response methodology. This enzyme has been widely used due to its high lactose hydrolysis activity and its dairy environmental habitat. Thus, it was important to obtain an efficient model to reach maximum production of the most prebiotic high-GOS, in this case, tri-GOS and tetra-GOS. 2. Materials and methods 2.1. Materials D-Lactose monohydrate (99%), D-(þ)-galactose (99%), D(þ)-melezitose monohydrate (99%), magnesium chloride (98%), potassium phosphate dibasic trihydrate (99%), potassium phosphate monobasic (98%), 2-nitrophenyl b-D-galactopyranoside (oNPG) (98%) and 2-nitrophenol (oNP) (99%) were purchased from Sigma Aldrich (Steinheim, Germany). Pierce 660 nm Protein Assay was supplied by Thermo Scientific Inc. (Waltham, USA) and bovine serum albumin (BSA), 2 mg mL1 by BioRad (California, USA). Lactozym® Pure 6500 L was obtained from Novozymes A/S (Bagsvaerd, Denmark); this preparation consists of a b-galactosidase purified from K. lactis.

2.2. Enzyme activity The b-galactosidase activity of Lactozym Pure 6500 L was determined by means of the oNPG method (Cardelle-Cobas et al., 2008; Martínez-Villaluenga et al., 2008). The reaction mechanism for oNPG hydrolysis is similar to that of lactose hydrolysis, with the substrate oNPG hydrolysed into galactose and oNP. The production of oNP was quantified spectrophotometrically using a Varian Cary 500 Scan UVeVis NIR Spectrophotometer. Different temperatures and pH values were assayed to determine the stability of the enzyme. In a typical experiment, a solution of oNPG (3.48 g L1) in a phosphate buffer (0.05 M potassium phosphate containing 1 mM MgCl2) with 0.002 g L1 enzyme was prepared and the reaction was allowed to proceed at a fixed selected temperature and pH. Samples were withdrawn (200 mL aliquot) at different time periods and the reaction stopped with the addition of 1 M H2SO4 (1200 mL). Then, 1 M Na2CO3 (1800 mL) was added to each sample to neutralise the acid and favour the development of a yellow colour. Thereafter, the absorbance of the sample at 420 nm was measured. Enzyme activity was calculated as enzyme units (U mL1), defined as the amount of enzyme that produces 1 mmol oNP mL1 min1. Moreover, a specific activity (U mg1), taking into account the protein concentration in the commercial enzyme solution Lactozym Pure 6500 L (mg mL1), was calculated. In this regard, protein concentration was assessed at 660 nm using the Protein assay according to the manufacturer's instructions (Thermo Scientific Inc., Waltham, USA) with BSA as standard. 2.3. GOS synthesis In a typical experiment corresponding to the synthesis of GOS, a lactose solution was prepared in 0.05 M potassium phosphate buffer containing 1 mM MgCl2 at the given pH. Reactions runs were performed in a 100 mL round-bottomed flask with magnetic stirring at 600 rpm. Temperature was controlled using a water bath placed over a heating plate equipped with a thermocouple sensor probe for temperature control. Samples were withdrawn at specific time intervals and immediately placed in a thermoblock at 90
C for


lez-Delgado et al. / International Dairy Journal 61 (2016) 211e219 I. Gonza

5 min to stop the reaction by thermal inactivation of the enzyme. Thereafter, samples were diluted appropriately in water depending on the initial lactose concentration and analysed by highperformance liquid chromatography (HPLC). 2.4. Chromatographic analysis and quantification of products Carbohydrate composition was determined using a Varian ProStar 500 HPLC chromatograph equipped with a Varian 356-LC Refractive Index detector. Analysis of standards, carbohydrates, as well as GOS, was performed using a method adapted from literature (Sen et al., 2011). A diluted sample (6 mL) was injected onto a 300  7.8 mm Rezex RCM-Monosaccharide Ca2þ (8%) column (Phenomenex). The mobile phase consisted of Milli-Q water with a flow rate of 0.5 mL min1. Column and detector cell temperatures was were maintained at 80
C and 35
C, respectively. Solutions of pure standards of glucose, galactose, and melezitose (as a reference for tri-galacto-oligosaccharides, tri-GOS) of known concentrations were used for quantitative analysis. R-squared value for each standard was greater than 0.999 in all cases. Response factor for tetra-GOS was extrapolated considering an additional monosaccharide unit from tri-GOS. Data acquisition and processing were performed with the Galaxie Chromatography Data System 1.9.3.2 software (Varian, Inc.). Carbohydrate yield was defined as weight percent of the starting lactose content in the reaction media Eq. (1).

Yi ¼


 i produced g L1  100
 Laco g L1

(1)

3. Results and discussion 3.1. Enzyme activity determination in oNPG hydrolysis To determine both the stability and the maximum activity of the b-galactosidase under different reaction conditions, a number of preliminary oNPG hydrolysis experiments were carried out. This hydrolysis reaction is biochemically similar to the hydrolysis of lactose to galactose and glucose, and therefore it can be used as a rapid prospective assay for the activity and stability of the enzyme. The effect of critical parameters such as temperature and pH has been explored in this system using 1 U mL1 of enzyme equivalent to 0.002 g L1. The results are depicted both graphically in Fig. 1 (in terms of yield to oNP), and numerically in Table 1 (in terms of specific activity, U mg1). The effect of pH in the range 5.0e7.5 was assayed at 40
C, whereas the effect of temperature was analysed at pH 6.5 in the range 30e60
C.

213

Table 1 Specific activity (U mg1) of b-galactosidase for the hydrolysis of oNPG; effect of pH and temperature. Effect of pH (at 40
C)

Effect of temperature (at pH 6.5)

pH

Specific activity (U mg1)

Temp. (
C)

Specific activity (U mg1)

5.0 6.5 7.5

1 524 299

30 40 50 60

476 524 46 17

Fig. 1A and Table 1 demonstrate that the enzyme provides maximum activity at pH 6.5 (524 U mg1, 77% yield of oNP in 12 min) followed by pH 7.5 (299 U mg1, 54%). Remarkably, at pH 5.0 no production of oNP could be detected. Therefore, pH value has a significant effect of which can be attributed to the high sensitivity of the enzyme to pH (Martínez-Villaluenga et al., 2008). On the other hand, Fig. 1B and Table 1 show that this enzyme is highly active up to moderate temperatures, in the range 30e40
C, providing a maximum performance in the experiment carried out at 40
C. An increase of reaction temperature to 50e60
C, however, resulted in a sharp decrease of oNP production. This can be related to the lack of thermal stability of the b-galactosidase from K. lactis, for which such inactivation at this temperature has been described previously (Martínez-Villaluenga et al., 2008). Therefore, the best hydrolytic conditions for this enzyme within the studied range were 40
C and pH 6.5. 3.2. Study of temperature and enzyme concentration in synthesis of GOS To establish the appropriate range of temperatures and enzyme concentrations for the optimisation analysis, a preliminary set of experiments on the production of GOS from lactose was carried out with focus on desired-GOS (tri- and tetra-GOS). Thus, temperature was analysed in the range of 40e60
C using an initial lactose concentration of 250 mg mL1, 2 U mL1 enzyme concentration and pH 6.5. The temperature is a key factor, since higher temperatures allow higher lactose concentrations, leading to an improvement of the transgalactosylation activity and consequently higher GOS yields (Martínez-Villaluenga et al., 2008; Torres et al., 2010). Fig. 2A depicts the kinetic curves for the three temperatures evaluated. The maximum desired-GOS yield (12.3%) was achieved after 5 h at 40
C whereas, an increase of the temperature up to 50
C leads to a considerably lower yield (about 4%). Furthermore, the curve corresponding to this temperature clearly shows saturation after very short reaction times (0.5 h) that can be ascribed to an inactivation of the enzyme. Similarly, at the highest temperature, 60
C, the enzymatic activity is negligible.

Fig. 1. Effect of (A) pH (C, pH 5; -, pH 6.5; :, pH) and (B) temperature (:, 30
C; -, 40
C; C, 50
C; A, 60
C) on the activity of the enzyme in the oNPG hydrolysis reaction to oNP.

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Fig. 2. Effect of (A) temperature (-, 40
C; :, 50
C; C, 60
C) using 2 U mL1 of enzyme, and (B) enzyme concentration (C, 2 U mL1; -, 5 U mL1; :, 10 U mL1; A, 20 U mL1) at 40
C, on tri and tetra-galacto-oligosaccharides (Ydesired-GOS) production. Experimental conditions: initial lactose concentration 250 g L1, pH 6.5.

Despite the above-mentioned benefits of high temperatures for the production of GOS from lactose, these results suggest that the enzyme suffers from thermal denaturation over 40
C, which was also observed in the previous oNPG hydrolysis experiments (Fig. 1B). Thus, the enzyme activity for the hydrolysis and transgalactosylation appear to be similarly affected by thermal protein denaturation. These results slightly contrast with those previously reported (Martínez-Villaluenga et al., 2008), in which a slightly better stability of the enzyme at high temperatures was observed, leading to a maximum GOS production (including also di-GOS) at 50
C and the appearance of deactivation only when increasing the temperature up to 60
C. Fig. 2B displays the kinetic curves of desired-GOS (tri and tetragalacto-oligosaccharides) yield at 40
C using different enzyme concentrations (2, 5, 10 and 20 U mL1). The evolution of desiredGOS over the reaction time is strongly affected by the concentration of the b-galactosidase. For 2 U mL1, the reaction was slow, needing long reaction times to achieve adequate yields. For enzyme concentration 5 U mL1, the presence of a maximum in desiredGOS yield becomes clear in the kinetic curves, appearing at progressively shorter reaction times as the enzyme loading increases. The maximum yield towards desired-GOS (12.5%) was achieved with 5 U mL1 of enzyme after 2 h. These results indicate that, at 40
C, the increase of enzyme concentration enhances its hydrolytic activity over the transgalactosylation activity, thus leading to a progressive reduction of the yield to desired-GOS at long reaction times, once the substrate lactose has been depleted. A similar trend was reported by (Martínez-Villaluenga et al., 2008). On the basis of these results, for the following optimisation experiments 5 U mL1 was considered as the most appropriate enzyme concentration because it provides maximum GOS yields with limited hydrolysis activity.

3.3. Optimisation of the experimental design methodology A factorial experimental design was carried out to assess the simultaneous combined effect of the main reaction parameters affecting high-GOS production. Such parameters include temperature, enzyme concentration, pH, lactose concentration and reaction time. Temperature and enzyme concentration, from the above discussion, were fixed at 40
C and 5 U mL1, respectively, leaving the other three parameters (time, pH and lactose concentration) as the factors to be optimised. An experimental design methodology (Montgomery, 2012) was used to simultaneously analyse the effect of these three important reaction variables. A 33 factorial experimental design (three factors at three levels) was carried out. The central point was repeated three times to determine the variability of the results and to assess the experimental error. The selected responses for the analysis were as follows: yield to desired-GOS

(trisaccharides, tri-GOS, plus tetrasaccharides, tetra-GOS) (Ydesiredyield to trisaccharides (Ytri-GOS), yield to tetrasaccharides (Ytetra-GOS) and glucose/galactose ratio (Glu/Gal). Specifically, the optimisation of the reaction variables aimed to increase the yield to desired-GOS, as the product with the most prebiotic effect. The combination of all these parameters gives accurate information about the enzymatic reaction for high-GOS production. Thus, the different GOS yields reveal the amount and profile of produced high-GOS; and glucose/galactose ratio reveals the predominant transformation (hydrolysis versus transgalactosylation), which would be equal to one if only hydrolysis takes place. On the other hand, when the transgalactosylation becomes predominant over the hydrolysis reaction, the concentration of free galactose in the media will be lower than free glucose as they become part of new produced GOS. The selection of the levels for each factor was based on either preliminary experimental results or previously reported data, taking into account the following considerations. In the case of the initial lactose concentration, this is limited by the maximum lactose solubility in water at 40
C, which is 250 g L1 (Machado, Coutinho, & Macedo, 2000). Regarding the pH, the maximum enzyme hydrolysis activity was reached at pH 6.5 (Fig. 1A), coinciding with the optimal pH range of 6.5e7.5 for GOS production activity reported in literature (Martínez-Villaluenga et al., 2008). Finally, based on the previous kinetic results at 40
C and 5 U mL1, showing a maximum of desired-GOS yield at 1e2 h (Fig. 2B), the effect of reaction time was analysed up to 3 h. Consequently, selected levels for each factor in the design were: pH (6, 6.5, and 7); initial lactose concentration (50, 150, and 250 g L1), reaction time (1, 2, and 3 h) (Table 2). All the experiments were carried out in a randomised order to minimise the effect of unexplained variability in the observed response. An empirical multiple quadratic model was assumed to fit the experimental results. Multiple regression analysis was performed by using the Statgraphics software to fit a second order polynomial equation for each response: GOS),

YA ¼ b0 þ

3 X i¼1

bi Xi þ

3 X i¼1

bii Xi2 þ

3 XX

bij Xi Xj

(2)

i
where Y is each response (yield to tri-GOS, tetra-GOS, and desired GOS, wt%; and glucose/galactose ratio). b0, bi, bii and bij are the regression coefficients of the intercept, linear, quadratic and binary interactions, respectively. Xi and Xj are the independent factors, initial lactose concentration, pH and reaction time. To validate the parameters and for the sake of model fitting, an estimation of the statistical error was performed. The analysis of statistical significance was based on the total error criteria with a confidence level of 95.0%. Thus, Eqs. (3)e(6) were obtained by multiple regression


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215

Table 2 Experiment matrix and experimental results for the production of GOS from lactose by b-galactosidase from Kluyveromyces lactis.a Run

IpH

IL

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 Mean

1 1 1 1 1 1 1 0 1 0 1 0 1 1 1 1 1 1 0 1 0 1 0 1 0 0 0 0 0 0 0 1 0 1 0 1 1 1 1 1 1 1 1 0 1 0 1 0 1 1 1 1 1 1 0 0 0 0 0 0 ± s.d.

It

pH

[L]o (g L1)

t (h)

Ydesired-GOS (%)

[Desired-GOS] (g L1)

Ytri-GOS (%)

[Tri-GOS] (g L1)

Ytetra-GOS (%)

[Tetra-GOS] (g L1)

Glu/Gal

1 0 1 1 0 1 1 0 1 1 0 1 1 0 1 1 0 1 1 0 1 1 0 1 1 0 1 0 0 0

6 6 6 6 6 6 6 6 6 6.5 6.5 6.5 6.5 6.5 6.5 6.5 6.5 6.5 7 7 7 7 7 7 7 7 7 6.5 6.5 6.5

50 50 50 150 150 150 250 250 250 50 50 50 150 150 150 250 250 250 50 50 50 150 150 150 250 250 250 150 150 150

1 2 3 1 2 3 1 2 3 1 2 3 1 2 3 1 2 3 1 2 3 1 2 3 1 2 3 2 2 2

3.6 3.4 3.2 7.5 8.4 8.4 9.4 11.3 11.9 3.7 1.5 1.0 9.7 9.6 9.0 11.8 12.3 11.0 4.5 3.3 2.2 10.2 9.7 8.3 9.5 12.0 12.8 8.7 9.6 9.6 9.4 ± 0.5

1.8 1.7 1.6 11.4 13.0 12.9 21.4 26.3 28.0 2.1 0.8 0.5 15.3 15.0 13.4 28.8 29.6 27.7 2.3 1.7 1.1 14.7 14.2 11.9 21.3 27.4 28.5 13.9 15.0 14.9 14.7 ± 0.6

3.6 3.4 3.2 7.5 8.4 8.3 8.6 10.4 10.9 3.7 1.5 1.0 9.2 9.2 8.5 10.7 11.1 9.8 4.5 3.3 2.2 9.2 8.6 7.3 8.8 11.0 11.7 8.3 9.2 9.2 8.9 ± 0.4

1.8 1.7 1.6 11.4 12.9 12.8 19.7 24.2 25.6 2.1 0.8 0.5 14.5 14.3 12.7 26.1 26.8 24.5 2.3 1.7 1.1 13.3 12.6 10.4 19.5 25.0 26.0 13.2 14.3 14.3 14.0 ± 0.5

0.0 0.0 0.0 0.0 0.1 0.1 0.8 0.9 1.0 0.0 0.0 0.0 0.5 0.5 0.5 1.1 1.2 1.3 0.0 0.0 0.0 1.0 1.1 1.0 0.8 1.1 1.1 0.4 0.5 0.4 0.4 ± 0.04

0.0 0.0 0.0 0.0 0.1 0.1 1.8 2.1 2.4 0.0 0.0 0.0 0.7 0.7 0.7 2.7 2.9 3.2 0.0 0.0 0.0 1.4 1.6 1.5 1.8 2.4 2.5 0.6 0.7 0.6 0.7 ± 0.06

1.2 1.2 1.2 1.4 1.3 1.3 1.5 1.6 1.5 1.1 1.0 1.0 1.4 1.4 1.4 1.5 1.5 1.4 1.2 1.1 1.1 1.4 1.4 1.3 1.6 1.6 1.6 1.3 1.4 1.4 1.4 ± 0.03

a Experimental conditions were 40
C, 5 U mL1 enzyme concentration. Columns 2 to 4 represent the 0 and ±1 encoded factor levels on a dimensionless scale whereas columns 5 to 7 represent the factor levels on a natural scale. Abbreviations are: [L]o, initial concentration of lactose; t, reaction time; I, coded value; Ydesired-GOS, yield to desiredGOS; Ytri-GOS, yield to tri-GOS; Ytetra-GOS, yield to tetra-GOS; [desired-GOS], concentration of desired-GOS; [tri-GOS], concentration of tri-GOS; [tetra-GOS], concentration of tetra-GOS; Glu/Gal, molar ratio free glucose/free galactose.

analysis using the software Statgraphics from the matrix generated by the experimental data.

Glu=Gal ¼ 6:24255  1:59778  pH þ 5:63194  104  ½Lo þ 0:133194  t þ 0:120833  pH2 þ 4:83333

YdesiredGOS ¼ 8:88712 þ 1:43861  pH þ 5:84792  102

 104  pH  ½Lo  2:33333  102  pH  t

 ½Lo þ 4:005  t  5  103  pH2 þ 3:45

 5:64583  106  ½L2o þ 9:16667  105  ½Lo  t

 103  pH  ½Lo  0:64  pH  t  1:87125  104  ½L2o þ 8:7  103  ½Lo  t  0:31625  t2 (3)

 6:45833  103  t2 (6) The R2 values for Eqs (3)e(6) were 95.9%, 95.5%, 83.9%, and 95.6%, respectively.

YtriGOS ¼ 1:35175  0:611944  pH þ 5:86493  102  ½Lo þ 4:22889  t þ 0:134167  pH2 þ 2:93333  103  pH  ½Lo  0:661667  pH  t  1:89313  104  ½L2o þ 8:06667  103  ½Lo  t  0:326458  t2 (4) YtetraGOS ¼ 7:81703 þ 2:13528  pH  1:0625  104  ½Lo  0:215278  t  0:145833  pH2 þ 5  104  pH  ½Lo þ 2:33333  102  pH  t þ 2:35417  106  ½L2o þ 6:33333  104  ½Lo  t þ 5:20833  103  t2 (5)

3.3.1. Model validity An evaluation of the regression error was performed on these models, aiming to validate their use for making predictions. The first indication of the performance of the fit is that the regression coefficients are high [over 95% for Eqs. (3), (4) and (6); and 84% for Eq. (5)]. Fig. 3 depicts the correlation between experimental results (Table 2, runs 1e30) and the respective predicted values obtained using the mathematical models, showing good agreement between experimental and predicted values for each of the responses. Additionally, the arithmetical mean and the standard deviation of each response were calculated from the central point replicas (Table 2, runs 28e30, and 14): desired-GOS yield (9.37 ± 0.5); tri-GOS yield (8.94 ± 0.4); tetra-GOS yield (0.44 ± 0.04), and Glu/Gal ratio (1.4 ± 0.03). Consequently, the obtained standard deviations are low enough to consider that experimental error is not very significant.

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Fig. 3. Correlation between model-predicted values versus experimental values of (A) Ydesired-GOS, (B) Ytri-GOS, (C) Ytetra-GOS and (D) Glu/Gal.

3.3.2. Influence of reaction conditions: initial lactose concentration, pH and reaction time The analysis of the mathematical models allows the identification of the most influential factors of each response. To facilitate the interpretation of the equations, Fig. 4 and Supplementary

Fig. S1 plot the response surfaces for the yields of desired-GOS and yield to tetra-GOS. Additionally, the use of Pareto charts helps to identify the significance of the different factors (pH, time and initial lactose concentration) on the diverse responses analysed herein (Fig. 5), whereas for the analysis of the combined

Fig. 4. Three-dimensional surface plots for (A) desired-GOS (tri-GOS þ tetra-GOS) production, (B) tetra-GOS production and (C) Glu/Gal ratio as a function of pH and initial lactose concentration, [L]0, at 3 h of reaction time. Representation of Eqs. (2), (4), and (5), respectively.


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Fig. 5. Pareto charts corresponding to initial lactose concentration (Lac), pH and time (t) for the responses (A) Ydesired-GOS, (B) Ytri-GOS, (C) Ytetra-GOS and (D) Glu/Gal, showing the significance line (vertical line), positive (striped) or negative (checked) effects of each factor or interaction for each variable.

effect of the different factors, interaction charts are provided in Fig. 6. Analysing the influence of starting lactose concentration, Pareto charts indicate that the initial lactose concentration positively and significantly affects the yields to desired-GOS, tri-GOS and tetraGOS and Glu/Gal ratio (Fig. 5). However, its quadratic effect LaceLac has a significant negative effect in the yield to tri-GOS and desired-GOS. Three-dimensional surface plots of Ydesired-GOS, YtetraGOS (Fig. 4) and Ytri-GOS (data not shown) at 3 h reaction time, demonstrated that an increase of initial lactose concentration results in a considerable increase of GOS production, leading to a maximum at the highest initial lactose concentration studied of 250 g L1. These results are in agreement with previous studies using the same enzyme (Martínez-Villaluenga et al., 2008) and others b-galactosidases (Gosling et al., 2010; Torres et al., 2010) where the influence of this parameter was studied separately. On the other hand, Pareto charts indicate that pH (in the analysed range of 6.0e7.0) does not significantly affect Ydesired-GOS and Ytri-GOS, only presenting a positive significant effect on Ytetra-GOS (Fig. 5). Three-dimensional surface plots for Ydesired-GOS and Ytetra-GOS

(Fig. 4) corroborate the above-mentioned effect of pH. Regarding the influence of reaction time, Pareto charts discard a significant effect of time on the yields, only being observed a small effect on the ratio Glu/Gal (Fig. 5). On the contrary, the interaction term of time-initial lactose concentration appears to have a significant impact on Ydesired-GOS and Ytri-GOS. The three-dimensional surface plots of Ydesired-GOS and Ytri-GOS at 1 h and 2 h (Supplementary Fig. S1) indicate a slight increment in GOS production over time, which is more pronounced in the range of pH 6.5e7. Nevertheless, the statistical analysis has demonstrated this trend is not significant. These results can be confirmed in agreement with the interaction graphs shown in Fig. 6, in which it can be observed that initial lactose concentration and reaction time, as well as pH and reaction time, interact to affect Ydesired-GOS and Ytri-GOS, whereas no interaction takes place between pH and initial lactose concentration. 3.3.3. Optimum conditions The models obtained may be used to predict the optimum reaction conditions to reach the maximum value of any one of the

Fig. 6. Interaction charts of the independent variables: initial lactose concentration (Lac), pH and time (t) for the responses (A) Ydesired-GOS, (B) Ytri-GOS, (C) Ytetra-GOS and (D) Glu/Gal.

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lez-Delgado et al. / International Dairy Journal 61 (2016) 211e219 I. Gonza

Fig. 7. Evolution of desired-GOS production (Ydesired-GOS; line with square symbols) and Glu/Gal ratio (Glu/Gal; hatched bars) with reaction time: (A) reaction carried out under the experimental design optimum conditions (pH 7, 250 g L1 initial lactose concentration, 40
C and 5 U mL1 enzyme); (B), reaction carried out at a higher pH value (pH 7.5, 250 g L1 initial lactose concentration, 40
C and 5 U mL1 enzyme).

responses. Thus, the maximum production of the combined highGOS (Ydesired-GOS) is predicted to be 12.18% at pH 7.0, 250 g L1 of initial lactose concentration and 3 h of reaction. Similarly, the maximum production of tetra-GOS (Ytetra-GOS) is predicted to be 1.35% at pH 7.0 and 3 h of reaction, whereas the maximum production of tri-GOS (Ytri-GOS) is predicted to be 10.93%, but at a lower pH value (6.0), while at similar initial lactose concentration and time. These results thus show that pH is a critical parameter tuning the profile of the high-GOS produced. The increased production of tetra-GOS at the higher pH (close to 7) is attributed to an increased transgalactosylation activity over the hydrolysis activity, as evidenced by a Glu/Gal ratio of 1.6 at pH 7 versus 1.2 at pH 6.0 (Fig. 4 and Table 2). Indeed, the glucose/galactose ratio has a maximum value at pH 7. Regarding the production of desired-GOS as the main response to optimise, the optimum reaction conditions coincide with the upper limits of the three factors analysed: pH 7.0, 250 g L1 initial lactose concentration, and reaction time of 3 h. As was mentioned previously, the initial lactose concentration is limited by its solubility at the reaction temperature (previously fixed at 40
C). On the other hand, to analyse the benefits of increasing reaction time and pH, additional experiments were carried out up to 5 h and pH 7.5 (the optimum pH range for GOS production activity reported in literature is 6.5e7.5; Martínez-Villaluenga et al., 2008). Thus, Fig. 7A depicts the evolution over time of the yield to desired-GOS, and Glu/Gal ratio under the optimum pH (7.0) and lactose concentration (250 g L1). It shows that the maximum yield to the most desired GOS is already achieved at 3 h of reaction time, remaining unchanged at 5 h. Therefore, 3 h of reaction time can be confirmed as the optimum reaction time for the tri-GOS production. On the other hand, to test a pH higher than 7.0, Fig. 7B shows the reaction results at pH 7.5, keeping the other variables constant. The curve corresponding to desired-GOS yield shows a dramatic reduction in comparison with the results at pH 7.0. These results are in agreement with our previous results of specific activity (Fig. 1 and Table 1) which indicated a loss of enzymatic activity at pH 7.5. 4. Conclusions In the present work, the study by surface response methodology of the main reaction parameters e pH, initial lactose concentration and reaction time e for the synthesis of high galactooligosaccharides (tri- and tetra-GOS) catalysed by b-galactosidase from K. lactis, was demonstrated to be a suitable tool to optimise empirical GOS production. In particular, the optimal value for the GOS yield with the presumed most prebiotic effect (desired galacto-oligosaccharides, tri- and tetra-GOS) in our experimental conditions was 12.18% at 40
C, 5 U mL1 enzyme concentration, pH 7, 250 g L1 initial lactose concentration and 3 h of reaction time. In

addition, the model allows also the prediction of the conditions required to maximise separately the yield to tri-GOS or tetra-GOS, achieving a value of 10.93% or 1.35%, respectively, though at different pH (6.0 for tri-GOS and 7.0 for tetra-GOS). Therefore, pH appears as an efficient parameter for determining the transgalactosylation/hydrolysis ratio of enzyme activity. The analysis of the obtained mathematical models explains the influence of the different variables and their interaction to maximise the yield to the most desired GOS. Acknowledgements Lactozym® Pure 6500 L was a generous gift from Novozymes. Appendix A. Supplementary data Supplementary data related to this article can be found at http:// dx.doi.org/10.1016/j.idairyj.2016.06.007. References Asp, N.-G., Burvall, A., Dahlqvist, A., Hallgren, P., & Lundblad, P. (1980). Oligosaccharide formation during hydrolysis of lactose with Saccharomyces lactis lactase (Maxilact®): Part 2 e Oligosaccharide structure. Food Chemistry, 5, 147e153. Audic, J.-L., Chaufer, B., & Daufin, G. (2003). Non-food applications of milk components and dairy co-products: A review. Lait, 83, 417e438. Burvall, A., Asp, N.-G., & Dahlqvist, A. (1979). Oligosaccharide formation during hydrolysis of lactose with Saccharomyces lactis lactase (Maxilact®): Part 1 e Quantitative aspects. Food Chemistry, 4, 243e250. Burvall, A., Asp, N.-G., & Dahlqvist, A. (1980). Oligosaccharide formation during hydrolysis of lactose with Saccharomyces lactis lactase (Maxilact®): Part 3 e Digestibility by human intestinal enzymes in vitro. Food Chemistry, 5, 189e194. Cardelle-Cobas, A., Villamiel, M., Olano, A., & Corzo, N. (2008). Study of galactooligosaccharide formation from lactose using Pectinex Ultra SP-L. Journal of the Science of Food and Agriculture, 88, 954e961. Chen, C. S., Hsu, C. K., & Chiang, B. H. (2002). Optimization of the enzymic process for manufacturing low-lactose milk containing oligosaccharides. Process Biochemistry, 38, 801e808. Chonan, O., Shibahara-Sone, H., Takahashi, R., Ikeda, M., Kikuchi-Hayakawa, H., Ishikawa, F., et al. (2004). Undigestibility of galactooligosaccharides. Nippon Shokuhin Kagaku Kogaku Kaishi, 51, 28e33.  e
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