Ecotoxicology and Environmental Safety ∎ (∎∎∎∎) ∎∎∎–∎∎∎

Contents lists available at ScienceDirect

Ecotoxicology and Environmental Safety journal homepage: www.elsevier.com/locate/ecoenv

Lactose hydrolysis by β-galactosidase enzyme: optimization using response surface methodology Bipasha Das a, Ananda Prasad Roy a, Sangita Bhattacharjee b,n, Sudip Chakraborty c, Chiranjib Bhattacharjee a a

Chemical Engineering Department, Jadavpur University, Kolkata 700032, West Bengal, India Chemical Engineering Department, Heritage Institute of Technology, Kolkata 700107, West Bengal, India c Department of Chemical Engineering and Materials, University of Calabria, Cubo-44A, 87036 Rende, CS, Italy b

art ic l e i nf o

a b s t r a c t

Article history: Received 25 November 2014 Received in revised form 13 March 2015 Accepted 23 March 2015

In the present study, it was aimed to optimize the process of lactose hydrolysis using free and immobilized β-galactosidase to produce glucose and galactose. Response surface methodology (RSM) by central composite design (CCD) was employed to optimize the degree of hydrolysis by varying three parameters, temperature (15–45 °C), solution pH (5–9) and β-galactosidase enzyme concentration (2– 8 mg/mL) for free mode of analysis and sodium alginate concentration (2–4%), calcium chloride concentration (3–6%) and enzyme concentration (2–8 mg/mL) for immobilized process. Based on plots and variance analysis, the optimum operational conditions for maximizing lactose hydrolysis were found to be temperature (35.5 °C), pH (6.7) and enzyme concentration (6.7 mg/mL) in free mode and sodium alginate concentration (3%), calcium chloride concentration (5.9%) and enzyme concentration (5.2 mg/mL) in immobilized mode. & 2015 Published by Elsevier Inc.

Keywords: Lactose hydrolysis β-galactosidase Immobilized enzyme Calcium alginate Response surface methodology

1. Introduction The dairy industry is one of the most polluting of various industries, not only in terms of huge volume of effluent that is being produced but also in terms of its characteristics. These dairy effluents having high biological and chemical oxygen demand if discharged without any prior treatment severely pollute receiving water bodies and disturb the whole ecosystem. Whey, the main by-product of dairy industry retains much of the nutrients of the original whole milk including whey proteins and most of the lactose, water soluble vitamins, minerals and fats. There is a gradual increase in cheese production that generates more than 145
106 t of liquid whey per year, with 6
106 t corresponding to lactose (Siso, 1996). Whey has commonly been treated as a waste stream. Therefore, disposal of whey represents severe environmental concern due to its huge volume and high organic matter content that causes high range of BOD and COD values (BOD: 30,000–50,000 ppm, COD: 60,000–80,000 ppm) owing to presence of lactose (Siso, 1996). Whey decomposition is toxic to the natural environment, robbing oxygen from streams and rivers resulting in anaerobic conditions that lead to the destruction of aquatic life over potentially large areas. This dairy effluent n

Corresponding author. Fax: 91 33 2443 0455. E-mail address: [email protected] (S. Bhattacharjee).

promotes the growth algae and bacteria in water system which eventually use up the oxygen causing the fishes to suffocate and die. Due to this, disposal of whey has been a major concern across the globe. Hence, attempts have been made by researchers to recover and reuse the bio-molecules present in whey. Lactose, one of the major components of whey, promotes the sewage fungus growth (Shete and Shinkar, 2013). Hydrolysis of lactose derived from whey is a very useful alternative as the hydrolyzed products are sweeter and can be used for the development of additives for animal and human diet (Ladero et al., 2000). Apart from this, the monosaccharides formed could be subsequently converted to bioethanol following fermentation using suitable microorganism. The bioethanol thus formed could be blended with gasoline, after proper purification. Hence the promising process of lactose hydrolysis has been studied for the last two decades for several reasons (Jurado et al., 2002). Lactose is less fermentable than other sugars and also lactose is one of the major obstacles for whey utilization since it causes crystallization at low temperatures. These problems can be solved if whey lactose is hydrolyzed to glucose and galactose (Matioli et al., 2003). Two methods can be applied for lactose hydrolysis in whey and other dairy products: enzymatic hydrolysis and acidic hydrolysis. Enzymatic hydrolysis is preferable than acidic hydrolysis as the former process allows milder conditions of pH and temperature, and does not cause bad flavors, odors and colors. Furthermore, acidic method can cause protein denaturation which can be

http://dx.doi.org/10.1016/j.ecoenv.2015.03.024 0147-6513/& 2015 Published by Elsevier Inc.

Please cite this article as: Das, B., et al., Lactose hydrolysis by β-galactosidase enzyme: optimization using response surface methodology. Ecotoxicol. Environ. Saf. (2015), http://dx.doi.org/10.1016/j.ecoenv.2015.03.024i

2

B. Das et al. / Ecotoxicology and Environmental Safety ∎ (∎∎∎∎) ∎∎∎–∎∎∎

present in lactose solution and yield of undesirable by-products (Demirhan et al., 2010; Sener et al., 2006). The hydrolysis of lactose to glucose and galactose is catalysed by enzymes called β-galactosidases which are found in animals, plants and microorganisms. However, in industry, only the enzymes from microbial sources are used for lactose hydrolysis (Vasiljevic and Jelen, 2002). Basically there are two different methods for using β-galactosidase. The soluble enzyme is used for batch processes, while the immobilized system lends itself for continuous operation. Enzyme immobilization methods are economically advantageous as it allows continuous operation and offer the possibility of reutilizing the enzymes (Singh and Singh, 2012). In addition the immobilized enzyme offers advantages compared to free enzyme; e.g. easy separation from the reaction mixture, no contamination of product by the enzyme (especially useful in food industries), operational and long term stability and multi-enzyme reaction systems (Husain et al., 2011). Immobilization method is highly efficient which is partly due to the mild conditions required and thus minimizes enzyme denaturation. The stabilizing effects of the support matrix increase the thermostability of the immobilized enzyme and prevent the extensive conformational changes typical of thermal denaturation. Several methods have been employed for the immobilization of enzymes. These include adsorption onto insoluble materials, entrapment in polymeric gels, encapsulation in membranes, chemical cross linking by using bifunctional or multifunctional reagents and linking to an insoluble carrier (Ansari and Husain, 2012). Among these, entrapment is the most preferable method since it helps to prevent excess loss of enzyme activity upon immobilization, increases enzyme stability in microenvironment of matrix, protects the enzyme from microbial contamination and easy application (Riaz et al., 2009). Conventional method for optimizing a multifactorial system is to deal with one factor at a time. Optimization of parameters by the conventional method involves changing one independent variable while keeping all others at a constant value. But this type of method is extremely time consuming, expensive for large number of variables, does not describe the combined effect of all the factors involved and may also result in wrong conclusions (Jeya et al., 2009). Response surface methodology (RSM) is a combination of statistical and mathematical techniques useful for designing experiments, building models, analyzing the effect of several independent variables on a system response and for optimizing the system response (Kishore and Kayastha, 2012; Panesar, 2008). In many cases the purpose of an experiment is to optimize the response or to achieve a desirable value of the response. The system response y depends on k input factors such as x1,x2….xk through an unknown function f such that y = f (x1, x2 … . xk ). Response surface methodology (RSM) aims at investigation and approximation of the unknown function f using experimentation, modeling, and data analysis. The common way that researchers address RSM in the literature is to use central composite designs (CCD), suggested by Box and Wilson (1951), or small composite designs (SCD), proposed by Draper and Lin (1990). Because of the presence of three parameters in this study each in batch or immobilized mode, three independent variables and one dependent variable, a substantial number of experiments should have been simultaneously executed, and their possible interactions also should have been studied. In the present study an attempt was made to employ response surface methodology (RSM) by central composite design (CCD) to identify the optimum conditions for hydrolysis of lactose both in free and immobilized mode by analyzing the relationships among different parameters that affect the overall process. In case of free mode, three parameters i,e temperature (15–45 °C), solution pH (5–9), enzyme concentration (2–8 mg/mL) were selected as independent variables, while percent lactose hydrolysis during a

specified time interval was selected as process (dependent parameter) response. As immobilized enzyme can be reused several times and additionally has the benefits of ease of separation from reaction medium, low contamination, better stability etc., entrapment of β-galactosidase enzyme was carried out in freshly prepared calcium alginate beads. In case of immobilized mode, parameters namely enzyme concentration (2–8 mg/mL), sodium alginate concentration (2–4%) and calcium chloride concentration (3–6%) were taken as independent parameters and lactose hydrolysis was the system response. The experimental data were analyzed through Design Expert (version 8.0.7.1, Stat-Ease, Inc, Minneapolis, MN, USA) software and the optimal parameters were determined for maximum lactose hydrolysis both in free and immobilized mode. Thus, the research work in this paper has been carried out with an objective to utilize one of the important biomolecules – lactose, present in dairy effluent to convert it to glucose through enzymatic hydrolysis route using free and immobilized methods so as to further convert the glucose formed to ethanol using Saccharomyces Cerevisae, an industrially popular microorganism (van Maris et al., 2006). In this way the dairy effluent which has been considered to be a very badly polluting stream due to very high BOD and COD values, could be converted to useful products. This technique would lead to a sustainable solution to the environmental problems caused by the disposal of dairy effluent.

2. Materials and methods 2.1. Substrates and chemicals Lactose (Loba Chemie) was used as substrate for hydrolysis study. For preparation of 0.1 M Phosphate buffer, chemicals used were K2HPO4 (obtained from Central Drug House, New Delhi) and KH2PO4 (obtained from SRL, Mumbai) and this buffer was used for preparation of lactose and enzyme solutions; sodium hydroxide (NaOH) and phosphoric acid (H3PO4) used for adjustment of pH were obtained from MERCK, Mumbai; β-galactosidase enzyme (Biolacta FN5, EC 3.2.1.23) isolated from Bacillus circulans was obtained from Burra Foods, Australia. GOD–POD kit (Span Diagnostics Ltd., Surat, India) is a reagent set used for determination of glucose, based on enzymatic method using Glucose oxidase and Peroxidase enzymes. Sodium alginate, obtained from SRL, Mumbai and calcium chloride dehydrate, obtained from MERCK, Mumbai were used for preparation of alginate beads. 2.2. Hydrolysis of lactose by free and immobilized

β-galactosidase

Hydrolysis was performed in both free and immobilized mode keeping the initial lactose concentration constant at 50 g/L. In original whey, the lactose concentration is about 5% (w/v). Hence to get realistic results, a simulated solution of 50 g/L of lactose in water has been used for this study. 2.2.1. Hydrolysis by free enzyme Lactose hydrolysis was performed in a batch mode to study the effect of following parameters: temperature (15–45 °C), pH (5–9) and β-galactosidase enzyme concentration (2–8 mg/mL). As the reaction medium, lactose solution was prepared on a 0.1 M Phosphate buffer (K2HPO4, KH2PO4). The lactose hydrolysis was carried out in a beaker at varying temperature, pH and enzyme concentrations in the following way: 10 mL of lactose solution prepared on the buffer as indicated above was added to 10 mL of enzyme solution prepared on the same buffer. Experiment was performed in a beaker, keeping the beaker over a magnetic stirrer. In order to get the desired temperature and also to obtain

Please cite this article as: Das, B., et al., Lactose hydrolysis by β-galactosidase enzyme: optimization using response surface methodology. Ecotoxicol. Environ. Saf. (2015), http://dx.doi.org/10.1016/j.ecoenv.2015.03.024i

B. Das et al. / Ecotoxicology and Environmental Safety ∎ (∎∎∎∎) ∎∎∎–∎∎∎

3

Fig. 1. (A) Schematic representation of Experimental Setup (free mode) and response surface plots of (B). Effect of interaction between temperature and pH on lactose hydrolysis. (C) Effect of interaction between temperature and enzyme concentration on lactose hydrolysis. (D) Effect of interaction between pH and enzyme concentration on lactose hydrolysis in free mode.

uniformity in the reaction mixture, the whole setup that is the beaker along with the magnetic stirrer was placed inside an incubator. The schematic representation of the experimental set-up has been shown in Fig. 1A. Acidic and alkaline pH was maintained by adding requisite amount of phosphoric acid and sodium hydroxide solution respectively. Assuming the enzyme was added at zero time, aliquots of 1 mL were withdrawn after incubation period of 30 min. The sample taken inside the vial was introduced into the boiling water for 10 min to stop the hydrolysis reaction by inactivating the enzyme. This procedure was repeated at selected temperature (15–45 °C), pH (5–9) and enzyme concentrations (2–8 mg/mL). Afterwards the hydrolyzed product glucose was measured using GOD–POD spectrophotometric method (Werner et al., 1970). In order to obtain the time required for maximum lactose hydrolysis under the optimized conditions in free mode, lactose hydrolysis was carried out for a period of 10 h and sample was collected every 30 min to analyze the amount of glucose formed. 2.2.2. Hydrolysis by immobilized enzyme 2.2.2.1. Preparation of enzyme entrapped calcium alginate beads. Lactose hydrolysis was performed in a batch mode with a lactose concentration of 50 g/l (temperature range: 15–45 °C and pH range: 5–9). β-galactosidase enzyme in immobilized form with

varying concentration (2–8 mg/mL) was used as the catalyst for the hydrolysis reaction. The enzyme was mixed with aqueous solution of sodium alginate (2–4% w/v). The enzyme/alginate mixture was drawn into a plastic syringe and then added dropwise into 100 mL aqueous solution of calcium chloride. The concentration of CaCl2 in the solution ranged from 3% w/v to 6% w/v. The enzyme entrapped beads were left in the calcium chloride solution to harden for about 30 min. The alginate will be ionically cross-linked by the calcium ions. The calcium alginate beads were separated from the solution using a strainer and washed thoroughly with distilled water three times to remove excess CaCl2. The beads were dried using tissue paper and then exposed to open air for about 1 h for drying before use. 2.2.2.2. Lactose hydrolysis using immobilized enzyme. The calcium alginate beads with the entrapped enzyme were then placed in lactose solution taken in a beaker and then incubated at 30 °C and pH7. Samples were collected after incubation period of 30 min in sample vials and then introduced into the boiling water for 5– 10 min to stop the hydrolysis reaction by deactivating the catalyst for the reaction. Similar heat treatment had been performed for the other samples. The samples collected contained the hydrolyzed products: glucose and galactose as well as lactose. The amount of glucose formed was measured with the aid of

Please cite this article as: Das, B., et al., Lactose hydrolysis by β-galactosidase enzyme: optimization using response surface methodology. Ecotoxicol. Environ. Saf. (2015), http://dx.doi.org/10.1016/j.ecoenv.2015.03.024i

B. Das et al. / Ecotoxicology and Environmental Safety ∎ (∎∎∎∎) ∎∎∎–∎∎∎

4

GOD–POD method and the UV–vis spectrophotometer (VARIAN, Cary 50 BIO, UV–vis Spectrophotometer).

standard glucose solution (1 mg/mL). Then, these values were used for calculation of remaining lactose in the reaction medium.

2.2.2.3. Optimization of temperature and pH. Important parameters of immobilization such as sodium alginate, calcium chloride and enzyme concentrations were optimized using response surface methodology. At these optimized parameters of immobilization (enzyme, sodium alginate and calcium chloride concentrations), temperature and pH were maximized experimentally. In order to find the optimized temperature for lactose hydrolysis in immobilized mode, the immobilized enzyme with the substrate were incubated at varying temperature ranging from 15 to 45 °C. 0.1 M buffers having different pH (5–9) were used to determine the optimum pH for maximum lactose hydrolysis. Similarly as in free mode, lactose hydrolysis by immobilized enzyme was carried out for 10 h to determine the time required for maximum lactose hydrolysis and the sample was collected after every 30 min for analysis of glucose formed. Lactose hydrolysis % was calculated using the following equation:

2.4. Experimental design

CLi − CLf CLi

× 100%

(1)

where, CLi is the initial lactose concentration and CLf is the final lactose concentration. 2.2.2.4. Reusability and storage stability of immobilized enzyme. The main advantage of enzyme immobilization is that it can be used repeatedly for several batches without much loss of activity during initial stages. Since enzymes are costly, reusability of immobilized enzyme is a key factor for cost-effective industrial applications. An attempt was thereby made to examine the reusability of β-galactosidase immobilized in beads. The obtained beads were washed with distilled water before each cycle and the process was repeated for several batches until the enzyme activity decreased. With a view to determine the storage stability of the immobilized enzyme, the alginate beads with the entrapped enzyme were stored in distilled water at 4 °C for 10 days. Enzyme activity was recorded each day. β-galactosidase activity was detected by measuring the production of glucose using lactose as substrate under the following standard conditions. Activity of β-galactosidase enzyme in immobilized preparations was determined in 100 mg of alginate beads suspended in 100 mM Phosphate buffer at pH 6.5. Hydrolysis was performed in 2 mL reaction mixture containing 100 mM of lactose under the above described assay conditions for 10 min. One unit of β-galactosidase activity was defined as the amount of enzyme catalyzing the formation of 1 mmol glucose per min under the above specified conditions (Rhimi et al., 2010).

The central composite design (CCD) was used to analyze the interaction among different significant factors and determine their optimal values. The most important parameters, which affect the lactose hydrolysis, are found to be temperature, pH and enzyme concentration in case of free mode and enzyme concentration, sodium alginate concentration and calcium chloride concentration in case of immobilized mode. The central composite design was applied using Design Expert (version 8.0.7.1, Stat-Ease, Inc, Minneapolis, MN, USA) statistical software. The total number of experiments with three factors was 20 (¼ 2k þ 2kþ6), where k is the number of factors (¼ 3). Thus response surface methodology (RSM) using central composite design (CCD) resulted in 20 experiments, including six replicates both in free and immobilized modes. In order to study the combined effect of the variables, experiments were performed at different combinations. The experimental plan along with the results is shown in Table 1 (free mode). Since our experiment is a full factorial design, the axial distance α is calculated as follows:

α=2

(No. of variables) = 2(3/4) = 1.682 4

The experimental plan for lactose hydrolysis using immobilized mode is shown in Table 2. Central composite design (CCD) is the most popular of the many classes of RSM designs. In both the cases, in free and immobilized mode, face centered central composite design was used. In face-centered CCD design the star points are at the center of each face of the factorial space. The face-centered CCD requires operating the process at only three level settings of each variable. This makes the face-centered CCD a simpler design to carry out. Thus, face centered central composite design (FCCD) was carried out to determine the model equation to predict the effects of process parameters i,e. temperature, pH and enzyme concentration on maximum degree of hydrolysis of lactose by free β-galactosiadase enzyme. 2.5. Statistical analysis Experimental design and analysis was done using ‘Design Expert’ software (version 8.0.7.1, Stat-Ease Inc., Minneapolis, MN). The mathematical relationship relating the variables to the responses can be calculated by the quadratic polynomial equation: k

Yi = β0 +

∑ βi Xi i=1

2.3. Analysis For determination of residual lactose concentration in the reaction mixture for both free and immobilized mode, samples were collected at regular interval. The samples collected in the vials were introduced into boiling water for 5 min to stop the hydrolysis reaction by deactivating the enzyme. The amount of glucose produced in the hydrolyzed samples was determined by the GOD– POD method, using a commercially available kit (Span Diagnostics Ltd., Surat, India). 10 ml of reaction mixture were added to 1000 ml of glucose reagent. Color was developed for 30 min at room temperature (25–30 °C). After completion of incubation period the absorbance against blank was measured at 505 nm in a spectrophotometer. Glucose concentration was calculated by measuring the absorbance of sample solution with reference to absorbance of

k

+

k−1

k

∑ βii Xi2 + ∑ ∑ i=1

i=1 j=i+1

βij Xi X j

(2)

where Yi is the predicted response, β0 is the constant coefficient, Xi Xj are input variables which influence the response variable Y; βi is the ith linear coefficient; βii the ith quadratic coefficient and βij is the ijth interaction coefficient, k is the number of factors. In this experiment, k ¼3. Data were processed for Eq. (2) using the Design-Expert program including ANOVA (Analysis of Variance) to obtain the interactions between the process variables and the response. The goodness of fit of the quadratic model was expressed by the coefficient of determination R2, and its statistical significance was checked by the Fisher's F-test in the same program. In the present study a total of 20 runs were carried out in each case of free and immobilized mode to estimate the coefficients. Later, the generated mathematical model was validated by conducting experiments at optimal values of variables predicted by response optimization.

Please cite this article as: Das, B., et al., Lactose hydrolysis by β-galactosidase enzyme: optimization using response surface methodology. Ecotoxicol. Environ. Saf. (2015), http://dx.doi.org/10.1016/j.ecoenv.2015.03.024i

B. Das et al. / Ecotoxicology and Environmental Safety ∎ (∎∎∎∎) ∎∎∎–∎∎∎

5

Table 1 Full experimental central composite design with level of variables and the response function (free mode). Experimental no.

Std. order

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20

20 11 6 16 12 13 5 19 14 15 17 10 1 18 3 8 7 9 2 4

Independent factors

Lactose hydrolysis (%)

Temperature (A, °C)

pH (B)

Enzyme concentration (C, mg/mL)

Experimental value

Predicted value

30 30 45 30 30 30 15 30 30 30 30 45 15 30 15 45 15 15 45 45

7 5 5 7 9 7 5 7 7 7 7 7 5 7 9 9 9 7 5 9

5 5 8 5 5 2 8 5 8 5 5 5 2 5 2 8 8 5 2 2

38.3 32.9 32.8 38.3 32.8 33.9 25.6 38.3 42 38.3 38.3 37 24.7 38.3 22.2 28.3 20 35 26.9 23.2

38.98 33.45 33.24 38.98 30.17 35.13 26.00 38.98 38.69 38.98 38.98 37.03 24.54 38.98 22.26 28.96 21.77 32.89 25.63 23.30

The optimum values of selected variables were obtained by solving the regression equation and by evaluating the response surface and contour plots. The response surface and contour plots are used for analysis of different interaction between independent variables while keeping the value of the third variable as constant. Such three dimensional plots give accurate geometrical representation and provide useful information about the behavior of the system.

3. Results and discussion The influences of different parameters such as temperature, pH, and enzyme concentration in case of lactose hydrolysis using free mode and calcium chloride concentration, sodium alginate concentration and enzyme concentration in immobilized mode were

investigated in details and optimized. 3.1. Optimization of lactose hydrolysis in free mode using response surface methodology (RSM) The central composite design (CCD) was employed to evaluate the interaction among the significant variables and also to determine their optimal values. CCD was developed to cut down the number of experimental runs and increase the efficiency. CCD has been applied and considered to be a very efficient statistical experimental design tool in chemical engineering optimization (Gámiz-Gracia et al., 2003). Table 1 shows the experimental conditions for batch runs and the corresponding responses, (for free mode) along with both predicted and experimental values of responses in terms of percent lactose hydrolysis. Similar results were presented in Table 2 for immobilized system.

Table 2 Full experimental central composite design with level of variables and the response function (immobilized mode). Run Std. order Independent factors

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 a

2 17 18 15 12 11 14 6 9 10 3 20 8 16 1 19 7 5 4 13

Experimental value

Predicted value

Enzyme concentration (D, mg/mL)

Sodium alginate concentration (E, %)

Calcium chloride concentration (F, %)

% Lactose hydrolysis

Activity (LHUa)

% Lactose hydrolysis

Activity (LHUa)

8 5 5 5 5 5 5 8 2 8 2 5 8 5 2 5 2 2 8 5

2 3 3 3 4 2 3 2 3 3 4 3 4 3 2 3 4 2 4 3

3 4.5 4.5 4.5 4.5 4.5 6 6 4.5 4.5 3 4.5 6 4.5 3 4.5 6 6 3 3

16.8 17.19 17.19 17.19 14.4 18.8 18.2 14.4 12 16.7 5.33 17.19 16.3 17.19 9.8 17.19 13.2 13.96 15.9 18.3

8.18 8.37 8.37 8.37 7.01 9.16 8.86 7.01 5.84 8.13 2.59 8.37 7.94 8.37 4.77 8.37 6.43 6.8 7.36 8.91

17.5 17.4 17.4 17.4 15.3 17.1 18.8 14.3 11.4 16.5 5.51 17.4 15.8 17.4 10.4 17.4 12.6 14.2 15.7 16.9

8.50 8.49 8.49 8.49 7.44 8.36 9.22 7.04 5.58 8.02 2.64 8.49 7.68 8.49 5.11 8.49 6.19 6.88 7.36 8.18

LHU ¼ lactose hydrolysis unit.

Please cite this article as: Das, B., et al., Lactose hydrolysis by β-galactosidase enzyme: optimization using response surface methodology. Ecotoxicol. Environ. Saf. (2015), http://dx.doi.org/10.1016/j.ecoenv.2015.03.024i

B. Das et al. / Ecotoxicology and Environmental Safety ∎ (∎∎∎∎) ∎∎∎–∎∎∎

6

Table 3 Analysis of variance (ANOVA) for the quadratic polynomial model for level optimization of lactose hydrolysis using β-galactosidase enzyme in free mode. Source

Sum of square

dF

Mean square

F value

p Value

Model A-temp B-pH C-conc. AB AC BC A2 B2 C2 Residual Lack of fit Pure error Cor total

794.23 42.85 26.90 31.68 1.25E  003 18.91 1.90 44.50 141.48 11.81 32.52 32.52 0.000 826.75

9 1 1 1 1 1 1 1 1 1 10 5 5 19

88.25 42.85 26.90 31.68 1.25E  003 18.91 1.90 44.50 141.48 11.81 3.25 6.5 0.000

27.14 13.18 8.27 9.74 3.8E  004 5.82 0.58 13.68 43.51 3.63

o 0.0001 0.0046 0.0165 0.0108 0.9847 0.0366 0.4622 0.0041 o 0.0001 0.0858

R2 ¼ 0.9607, R2adj ¼ 0.9253, adequate precision¼ 13.497.

Using polynomial multivariate regression technique, Eq. (3) has been obtained after the analysis of variance (ANOVA), which provides an estimation of the level of lactose hydrolysis as a function of temperature, solution pH and enzyme concentration in case of enzymatic hydrolysis using free mode.

Y1 = + 38.99 + 2.07 × A − 1.64 × B + 1.78 × C − 0.012 × A × B + 1.54 × A × C − 0.49 × B × C − 4.02 × A2 − 7.17 × B2 − 2.07 × C 2

(3)

where Y1 ¼lactose hydrolysis (%), A ¼temperature (°C), B ¼ pH and C ¼enzyme concentration (mg/mL) (Table 3). The ‘Prob4F ’ value for the model was o0.0001, which indicated that the model was statistically significant with a confidence interval of 99.99%. The Model F-value of 27.14 implies the model was significant. Values of p (Prob 4F) less than 0.0500 indicate that the model terms are significant. ANOVA reveals that that the most significant factor effecting the lactose hydrolysis process is A-Temperature (p ¼0.0046) followed by C-Enzyme Concentration (p ¼0.0108) and B-pH (p ¼0.0165). The interactions between Temperature and Enzyme concentration gave the most significant effect where the p-value was found to be 0.0366. Regression analysis revealed a coefficient of determination (Rsquared) value of 0.9607, indicating that the model fails to explain only 3.93% of total variations. Relatively high value of R2 indicated that the full quadratic model equation was capable of representing the system under the given experimental domain. The adjusted coefficient of determination (Adj R-squared) was found to be 0.9253 indicating a good agreement between the experimental and predicted values (Table 1). The coefficient of variation (CV) indicated the degree of precision with which the experiment is compared. The reliability of the experiment is low if the CV value is high. In the present study low CV % (5.57) denoted that the experiment performed is reliable. “Adeq Precision” measures the signal to noise ratio. A ratio greater than 4 is desirable. In the present study the ratio of 13.497 indicated an adequate signal. The response surface plots or contour plots generated by response surface methodology can be used to study the effect of interaction of variables on lactose hydrolysis and also to predict the optimal values of those variables. The 3D surface plots were generated by plotting the response (lactose hydrolysis) on Z-axis against any two independent variables while keeping the third independent variable at its constant level. Fig. 1B shows the effect of temperature and pH on lactose hydrolysis. Temperature affects enzyme activity and the reaction process because it changes the conformation of the enzyme.

Initially, an increase in temperature first caused an increase in lactose hydrolysis as can be seen in Fig. 1B. However, protein conformations are very sensitive to temperature changes. Once the optimal temperature was reached, any further increase in temperature altered the enzyme conformation. The substrate that is lactose may not be able to fit properly onto the changed enzyme surface, so hydrolysis was found to decrease. Similarly, change in pH of the reaction solution affects the enzyme conformation. With increase in pH, lactose hydrolysis was found to increase initially in the range from 5 to 7. After that the percent lactose hydrolysis was found to decline substantially. This could be due to the fact that β-galactosidase is most stable in the pH range of 6.5–7. Beyond that the activity of the enzyme gets reduced which resulted in decline in lactose hydrolysis. From Fig. 1B it is further clear that lactose hydrolysis was maximum at pH around 7 and temperature around 30 °C. The effect of temperature and enzyme concentration at a fixed value of pH (pH ¼ 7) is shown in Fig. 1C. From the figure it can be seen that with increase in β-galactosidase concentration from lower values, lactose hydrolysis increased significantly at a particular temperature. However the rate of increase of lactose hydrolysis flattened as enzyme concentration was changed from moderate to higher values. This could be due to the fact that at moderate to higher enzyme concentration, almost all the lactose got biochemically bound to form enzyme–substrate complex, thus showing no further increase in percent lactose hydrolysis. With simultaneous increase in both enzyme concentration and temperature (in the range: 15–35 °C), lactose hydrolysis was observed to increase. However, at higher temperatures (range: 35–45 °C), lactose hydrolysis was found to decrease which could have been due to reduced activity of the enzyme at higher temperature. Fig. 1D shows the effect of enzyme concentration and pH on lactose hydrolysis. An increase in enzyme concentration with increase in pH (5–7), a substantial increase in lactose hydrolysis was observed but at higher pH i.e. beyond pH 7, lactose hydrolysis was found to decrease. This could be attributed due to higher activity of the enzyme in the acidic to neutral pH (pH: 5–7) range. 3.1.1. Validation of the model According to the response surface analysis, optimum lactose hydrolysis was estimated to be 40% at a temperature of 35.5 °C, pH of 6.7 and enzyme concentration of 6.7 mg/mL. To validate the optimum conditions, an experiment for lactose hydrolysis was performed with the specified conditions. Under these conditions lactose hydrolysis was found to be 38.1% which was slightly different from the predicted value of 40%. Thus, the model developed was accurate and reliable for predicting the optimized conditions, as well as for maximum lactose hydrolysis. 3.2. Optimization of lactose hydrolysis in immobilized mode using response surface methodology (RSM) The enzyme concentration, sodium alginate concentration, calcium chloride concentration, temperature and pH are important factors to be considered which highly influence the lactose hydrolysis process in immobilized mode. Enzyme, sodium alginate and calcium chloride concentrations were optimized using RSM. Then temperature and pH were maximized by the conventional experimental method at optimized values of enzyme, sodium alginate and calcium chloride concentrations as determined by RSM. Using face centered central composite design (FCCD) method, a total of 20 experiments with different combinations of enzyme concentrations (2–8 mg/mL), sodium alginate concentrations (2–4 w/v%) and calcium chloride concentrations (3–6 w/v%) were performed. Lactose hydrolysis (Y2, %) and enzyme activity (Y3, LHU) were used as responses (Table 2).

Please cite this article as: Das, B., et al., Lactose hydrolysis by β-galactosidase enzyme: optimization using response surface methodology. Ecotoxicol. Environ. Saf. (2015), http://dx.doi.org/10.1016/j.ecoenv.2015.03.024i

B. Das et al. / Ecotoxicology and Environmental Safety ∎ (∎∎∎∎) ∎∎∎–∎∎∎

To estimate the optimal lactose hydrolysis and enzyme activity in immobilized mode, the following full quadratic second-order polynomial equations (Eqs. (4) and (5)) using coded units was fitted to the results.

Y2 = 17.42 + 2.58 × D − 0.86 × E + 0.99 × F + 0.78 × D × E − 1.75 × D × F + 0.81 × E × F − 3.42 × D2 − 1.17 × E 2 + 0.47 × F 2

(4)

where Y2 ¼lactose hydrolysis (%); D¼ enzyme concentrations (2–8 mg/mL); E¼sodium alginate concentrations (%); F¼ calcium chloride concentrations (%).

Y3 = 8.49 + 1.22 × D − 0.46 × E + 0.52 × F + 0.33 × D × E − 0.81 × D × F + 0.45 × E × F − 1.69 × D2 − 0.59 × E 2 + 0.21 × F 2

(5)

where Y3 ¼enzyme activity (LHU); D, E, F are having the same meaning as in Eq. (4). ANOVA results of the quadratic models indicated that the model equations derived by RSM could adequately be used to describe the lactose hydrolysis and enzyme activity under a wide range of operating conditions. The ANOVA results indicated that all the quadratic models obtained were significant, since the probability values (Prob4Fo0.0001) were low. Values of Prob4 F less than 0.05 indicate that the model terms are significant, while values greater than 0.10 indicate that the model terms are not significant. The “adequate precision” ratios of the models for lactose hydrolysis and enzyme activity were 20.452 and 23.743, respectively. Ratios greater than 4 indicate an adequate signal for the models. A high R2 value, close to 1, ensures a satisfactory adjustment of the quadratic model to the experimental data. The values of the determination coefficient R2 were 0.9583 and 0.9586 respectively,

7

indicates that only 4.14–4.17% of the total variation could not be explained by the model. The values of the adjusted R2 of 0.9207 and 0.9213, for lactose hydrolysis and enzyme activity respectively, were also high, indicating the strong significance of the model. The plots of the quadratic model with one variable kept at constant level and the other two varying within the experimental ranges are shown in Fig. 2A–C. The effect of enzyme concentration in immobilization process on lactose hydrolysis can be seen from Fig. 2A and B. Increasing the enzyme concentration increases the activity and lactose hydrolysis reaching its maximum value using 5.2 mg/mL enzyme. Beyond this concentration, lactose hydrolysis (Fig. 2A and B) and enzyme activity were decreased. Increasing the enzyme concentration at constant substrate concentration, both lactose hydrolysis and enzyme activity were increased at the initial stage, more enzyme is available to strike with substrate molecules and form enzyme substrate complex and thus more product in a given time. While increasing the concentration a point will appear when the rate becomes constant. This is because now the substrate molecules become the limiting factor. All the substrate molecules were combined with an enzyme and all the active sites in the enzyme were occupied with the substrate molecules. It has been reported that the immobilization of enzyme depends on concentration of sodium alginate and the degree of cross linking of the gelling agent affects the pore size of the beads (Dey et al., 2003; Longo et al., 1992). Various concentrations of sodium alginate were used for preparation of calcium alginate beads in order to vary the relative degree of cross linking which would create different pore size. As the concentration of alginate increased, lactose hydrolysis and β-galactosidase activity also increased. Lactose hydrolysis was found to be highest for a final sodium alginate concentration of 3.0% (w/v) (Fig. 2A). Above sodium alginate concentration of 3.0%, lactose hydrolysis and enzyme activity were found to decrease. This could be due to

Fig. 2. Response surface plots showing interaction between different variables in immobilized mode. (A) effect of interaction between enzyme and sodium alginate concentrations on lactose hydrolysis. (B) effect of interaction between enzyme and calcium chloride concentrations on lactose hydrolysis. (C) effect of interaction between sodium alginate and calcium chloride concentrations on lactose hydrolysis.

Please cite this article as: Das, B., et al., Lactose hydrolysis by β-galactosidase enzyme: optimization using response surface methodology. Ecotoxicol. Environ. Saf. (2015), http://dx.doi.org/10.1016/j.ecoenv.2015.03.024i

8

B. Das et al. / Ecotoxicology and Environmental Safety ∎ (∎∎∎∎) ∎∎∎–∎∎∎

decrease in pore size of the beads which in turn caused more diffusional resistance to the transport of substrate molecules to and product molecules from the alginate gel matrix. Lower alginate concentrations (below 3%) caused formation of softer beads with larger pore sizes which in turn might be responsible for disintegration and higher leakage of enzyme from the gel matrix, thus adversely affecting the enzyme activity and the lactose hydrolysis process. From Fig. 2B, it was observed that lactose hydrolysis was increased with increase in calcium chloride concentration. Ca þ 2 ion is the most frequently employed ion for immobilization purposes because of its low toxicity. Concentrations of the cationic solutions significantly affect the stability and pore size of the beads (Jobanputra et al., 2011). The interaction effect between sodium alginate and calcium chloride concentrations had a positive effect on both lactose hydrolysis (Fig. 2C) and enzyme activity. One or two experimental data might be somewhat less than or more than those of predicted value. This can happen as the model equation has been formed by the software itself after considering all experimental data points. So for a particular set of data points, there may be deviation. 3.2.1. Validation of the model According to the response surface analysis, optimum lactose hydrolysis in immobilized mode was estimated to be 18.8% at enzyme concentration of 5.2 mg/mL, sodium alginate concentration of 3.0% and calcium chloride concentration of 6%. To validate the optimum conditions, an experiment for lactose hydrolysis and enzyme activity was performed with the specified conditions. Under these conditions lactose hydrolysis was found to be 17.9% and enzyme activity to be 8.7 LHU which were slightly different from the predicted values of 18.8% and 9.1 LHU for lactose hydrolysis and enzyme activity respectively. Thus, the model developed was accurate and reliable for predicting the optimized conditions for maximum lactose hydrolysis. 3.2.2. Optimization of temperature and pH After getting the optimal process conditions for calcium alginate beads preparation using the response surface methodology, pH and temperature for the immobilized β-galactosidase enzymatic hydrolysis were optimized by the conventional experimental method. Temperature and pH were not considered as input parameters during RSM study so as to avoid complexity of the optimization process. After RSM study, enzyme entrapped calcium alginate beads were prepared using optimized values of sodium alginate, calcium

chloride and enzyme concentration and using these beads lactose hydrolysis study was carried out with the objective to optimize temperature and pH effect by conventional method i.e. by varying one parameter at a time while keeping other parameter constant. Temperature was varied between 15–45 °C and pH was varied between 5–9. From Fig. 3A, it was clear that maximum lactose hydrolysis by immobilized enzyme was achieved at 30 °C. For lactose hydrolysis in immobilized mode, optimum pH was observed to be at 5. Solution pH has considerable effect on the activity and stability of enzymes. Enzymes are charged molecules. With change in pH, there has been a change in the charged microenvironment around the surface of the beads entrapping the enzymes which caused a change in enzyme activity. 3.2.3. Reusability and storage stability of immobilized enzyme The alginate beads with the enzyme were repeatedly used for 8 cycles, 1 h each, with the beads being washed with distilled water in between the cycle (Fig. 3B). The activity was found to be almost constant for the first four cycles. Then a sharp decrease in activity was observed. The beads lost 40% of its original activity after 8 cycles. This gradual decrease in enzyme activity with each cycle at later stages may be due to leakage of enzyme in the surrounding solution and also may be due to the fact that the beads lost their tensile strength due to repeated washings at the end of each cycle. Immobilized enzyme was stored at 4 °C temperature in distilled water. The activity was noted up to 10 days. It was found that beads which were stored at 4 °C showed 25% loss of activity after 48 h and 64% loss of activity after 10 days. Immobilized enzymes can be stored for quite some time in refrigerator at 4 °C.

4. Conclusions In this study, response surface methodology was found effective in optimizing and determining the interactions among process variables for lactose hydrolysis in free and immobilized mode. Temperature and enzyme concentration were found to be critical factors affecting the lactose hydrolysis process in free mode followed by pH. Temperature of 35.5 °C, pH of 6.7 and enzyme concentration of 6.7 mg/mL were found to be the optimum values to achieve maximum lactose hydrolysis in free mode. In immobilized mode, lactose hydrolysis and enzyme activity were found to be significantly influenced by enzyme concentration, sodium alginate concentration and calcium chloride concentration and were optimized at 5.2 mg/mL, 3.0% and 6% respectively. Temperature and pH are also important parameters influencing the activity and

Fig. 3. (A) Optimization of temperature and pH in immobilized mode. (B) Reusability of immobilized enzyme.

Please cite this article as: Das, B., et al., Lactose hydrolysis by β-galactosidase enzyme: optimization using response surface methodology. Ecotoxicol. Environ. Saf. (2015), http://dx.doi.org/10.1016/j.ecoenv.2015.03.024i

B. Das et al. / Ecotoxicology and Environmental Safety ∎ (∎∎∎∎) ∎∎∎–∎∎∎

hydrolysis reaction by immobilized enzyme and were maximized at values of 30 °C and 5 respectively. Temperature higher than 30 °C and pH higher than 5 may have affected the activity of the immobilized enzyme which ultimately resulted in decreased lactose hydrolysis. Upon immobilization of the enzyme, a shift of optimum pH was found from 6.7 to 5. This shift in pH could be resulted from the change in acidic and basic amino acid side chain ionization in the microenvironment around the active sites due to which the nature of the entrapped enzyme changed. This behavior could be advantageous for use of this immobilized form in the degradation of lactose recovered from whey waste which normally has an acidic pH. Lactose hydrolysis by free enzyme was 40% whereas by immobilized enzyme it was 18.82% for a period of 30 min. However a maximum lactose hydrolysis of 88% in 6 h for free mode and 72% in 8 h in immobilized mode were achieved. The hydrolysis was less in immobilized form than in free form which may be due to the fact that the conformation of enzyme was changed upon entrapment in alginate beads that affected the enzyme activity and the hydrolysis process. Enzyme in solution form can be used only for batch study but the immobilized mode of enzyme can be used both for batch and continuous operation. Immobilized enzyme helps to provide better enzyme thermostability, pH tolerance, can be reused for several cycles and prevent the loss of enzyme activity (Panesar et al., 2010). The reusability property of the immobilized enzyme would ultimately help in reducing the cost of the process.

Acknowledgments The work reported in the article was funded by UGC-BSR.

References Ansari, S.A., Husain, Q., 2012. Lactose hydrolysis from milk/whey in batch and continuous processes by concanavalin A-Celite 545 immobilized Aspergillus oryzae β galactosidase. Food Bioprod. Process. 90, 351–359. Box, G.E.P., Wilson, K.B., 1951. On the experimental attainment of optimum conditions. J. R. Stat. Soc. Ser. B 13, 1–45. Demirhan, E., Apar, D.K., Özbek, B., 2010. A modelling study on hydrolysis of whey lactose and stability of β-galactosidase. Korean J. Chem. Eng. 27, 536–545. Dey, G., Singh, B., Banerjee, R., 2003. Immobilization of 2- amylase produced by Bacillus circulans GRS 313. Braz. Arch. Biol.Technol. 46, 167–176. Draper, N.R., Lin, D.K.J., 1990. Small response surface designs. Technometrics 32, 195–202. Gámiz-Gracia, L., Cuadros-Rodríguez, L., Almansa-López, E.J., Soto-Chinchilla, J.M., García-Campaña, A., 2003. Use of highly efficient Draper–Lin small composite designs in the formal optimisation of both operational and chemical crucial

9

variables affecting a FIA-chemiluminescence detection system. Talanta 60, 523–534. Husain, Q., Ansari, S.A., Alam, F., Azam, A., 2011. Immobilization of Aspergillus oryzae β galactosidase on zinc oxide nanoparticles via simple adsorption mechanism. Int. J. Biol. Macromol. 49, 37–43. Jeya, M., Zhang, Y.-W., Kim, I.-W., Lee, J.-K., 2009. Enhanced saccharification of alkali treated rice straw by cellulase from Trametes hirsuta and statistical optimization of hydrolysis conditions by RSM. Bioresour. Technol. 100, 5155–5161. Jobanputra, A.H., Karode, B.A., Chincholkar, S.B., 2011. Calcium alginate as supporting material for the immobilization of rifamycin oxidase from Chryseobacterium species. Biotechnol. Bioinf. Bioeng. 1, 529–535. Jurado, E., Camacho, F., Luzón, G., Vicaria, J.M., 2002. A new kinetic model proposed for enzymatic hydrolysis of lactose by a β-galactosidase from Kluyveromyces fragilis. Enzyme Microb. Technol. 31, 300–309. Kishore, D., Kayastha, A.M., 2012. Optimisation of immobilisation conditions for chick pea b-galactosidase (CpGAL) to alkylamine glass using response surface methodology and its applications in lactose hydrolysis. Food Chem. 134, 1650–1657. Ladero, M., Santos, A., Garcia, J.L., Garcia-Ochoa, F., 2000. Kinetic modelling of lactose hydrolysis with a b-galactosidase from Kluyveromyces fragilis. Enzyme Microb. Technol. 27, 583–592. Longo, M.A., Novella, I.S., García, L.A., Díaz, M., 1992. Diffusion of proteases in calcium alginate beads. Enzyme Microb. Technol. 14, 586–590. Matioli, G., Moraes, F.F., Zanin, G.M., 2003. Operational stability and kinetics of lactose hydrolysis by β-galactosidase from Kluyveromyces fragilis. Acta Sci. Health Sci. 25, 7–12. Panesar, P.S., 2008. Application of response surface methodology in the permeabilization of yeast cells for lactose hydrolysis. Biochem. Eng. J. 39, 91–96. Panesar, P.S., Kumari, S., Panesar, R., 2010. Potential applications of immobilized βgalactosidase in food processing industries. Enzyme Res., 1–16. Rhimi, M., Boisson, A., Dejob, M., Boudebouze, S., Maguin, E., Haser, R., Aghajari, N., 2010. Efficient bioconversion of lactose in milk and whey: immobilization and biochemical characterization of a β-galactosidase from the dairy Streptococcus thermophilus LMD9 strain. Res. Microbiol. 161, 515–525. Riaz, A., Qader, S.A.U., Anwar, A., Iqbal, S., 2009. Immobilization of a thermostable áamylase on calcium alginate beads from Bacillus Subtilis KIBGE-HAR. Aust. J. Basic Appl. Sci. 3, 2883–2887. Sener, N., Apar, D.K., Ö zbek, B., 2006. A modelling study on milk lactose hydrolysis and b-galactosidase stability under sonication. Process Biochem. 41, 1493–1500. Shete, B.S., Shinkar, N.P., 2013. Dairy industry wastewater sources, characteristics & its effects on environment. Int. J. Curr. Eng. Technol. 3, 1611–1615. Singh, A.K., Singh, K., 2012. Study on hydrolysis of lactose in whey by use of immobilized enzyme technology for production of instant energy drink. Adv. J. Food Sci. Technol. 4, 84–90. Siso, M.I.G., 1996. The biotechnological utilization of cheese whey: a review. Bioresour. Technol. 57, 1–11. van Maris, A.J.A., Abbott, D.A., Bellissimi, E., Brink, Jv, Kuyper, M., Luttik, M.A.H., Wisselink, H.W., Scheffers, W.A., Dijken, J.P., Pronk, J.T., 2006. Alcoholic fermentation of carbon sources in biomass hydrolysates by Saccharomyces cerevisiae: current status. Antonie van Leeuwenhoek 90, 391–418. Vasiljevic, T., Jelen, P., 2002. Lactose hydrolysis in milk as affected by neutralizers used for the preparation of crude b-galactosidase extracts from Lactobacillus bulgaricus 11842. Innov. Food Sci. Emerg. Technol. 3, 175–184. Werner, W., Rey, H.G., Wielinger, H., 1970. Properties of a new chromogen for the estimation of glucose in blood sugar according to the GOD/POD method. Anal. Chem. 252, 224–228.

Please cite this article as: Das, B., et al., Lactose hydrolysis by β-galactosidase enzyme: optimization using response surface methodology. Ecotoxicol. Environ. Saf. (2015), http://dx.doi.org/10.1016/j.ecoenv.2015.03.024i