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Thermostable alpha-amylase enzyme production from hot spring isolates Alcaligenes faecalis SSB17 – Statistical optimization
Biocatalysis and Agricultural Biotechnology ∎ (∎∎∎∎) ∎∎∎–∎∎∎
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Original Research Paper
Thermostable alpha-amylase enzyme production from hot spring isolates Alcaligenes faecalis SSB17 – Statistical optimization Sudip Kumar Sen a, Tapas Kumar Dora a, Bidyut Bandyopadhyay b, Pradeep Kumar Das Mohapatra c, Sangeeta Raut a,n a
Department of Biotechnology, Gandhi Institute of Engineering Technology, Gunupur, Rayagada, Odisha 765022, India Department of Biotechnology, Vidyasagar University, Midnapore, West Bengal 721102, India c Department of Microbiology, Vidyasagar University, Midnapore, West Bengal 721102, India b
art ic l e i nf o
a b s t r a c t
Article history: Received 16 January 2014 Accepted 14 March 2014
In the present investigation the production and characterization of a thermostable alpha-amylase enzyme from hot spring isolates Alcaligenes faecalis SSB17 has been studied. The individual and combined effect of temperature, pH and time has been investigated on the production of enzyme in four media (Luria Bertani, Nutrient Media, Semi-Synthetic Media l and Semi-Synthetic Media 2) using Box–Behnken design (BBD). Analysis of variance (ANOVA) shows high coefficient values of determination for each medium and satisfactory prediction second order regression models has been derived. Enzyme purification has been carried out by ammonium sulfate precipitation and size exclusion chromatography (SEC). Maximum purification has been obtained by SEC with 60 fold. SDS-PAGE of the purified enzyme has shown the presence of a single band associated with the amylase enzyme, having a molecular weight of 52 kDa & 2014 Elsevier Ltd. All rights reserved.
Keywords: Hot spring Alcaligenes faecalis Amylase Box–Behnken design Optimization
1. Introduction The production of economically important alpha-amylases is essential for the conversion of starch into oligosaccharides (Pedersen and Nielsen, 2000). This enzyme is extensively used in paper, food, pharmaceutical, sugar industries and starch liquefaction (Nigam and Singh, 1995; Ikram-ul-Haq et al., 2003; Roy and Gupta, 2004). Requirement for microbial amylase has increased due to their specificity for reaction, mild condition required for reaction and less energy consumption than the conventional chemical methods. Use of microorganisms for the production of amylase is economical because microbes are easy to manipulate for obtaining enzymes of specific characteristics. Bacillus species are heterogeneous form of organisms and are very versatile in their adaptability to the environment. Bacillus species like Bacillus amyloliquefaciens (Hewitt and Solomons, 1996). Bacillus licheniformis (Morgan and Priest, 1981), Bacillus stearothermophilus (Wind et al., 1994), Bacillus flavothermus (Kelly et al., 1997) and Bacillus megaterium (Jana et al., 1997) have been reported for thermostable alpha-amylase production by fermentation process. The most important characteristic of thermophilic organisms is their ability to produce thermostable enzymes with a higher operational stability and a longer shelf-life n
Corresponding author. Mobile: þ 91 9438450789. E-mail address: [email protected] (S. Raut).
(Thippeswamy et al., 2006). Liquid sugar industry needs thermostable α-amylase that can maintain its activity at high temperature, such as in the gelatinization (100–110 1C) and liquefaction process (80–90 1C). Growth of microorganisms and its metabolite synthesis mainly depend on the medium nutrients and the growth conditions (Prescott et al., 2002). Optimization of medium components and process conditions plays a vital role for maximizing the microbial metabolites production and minimizing the production cost (Bezbaruah et al., 1994). In recent years, the application of statistical experimental design has been reported by many authors for optimization of various microbial metabolites (Tanyildizi et al., 2005). Box–Behnken design (BBD) of RSM is successfully employed to predict the optimal level of the variables within the design space of study (Box and Behnken, 1960) and interaction effect among the variables can also be explained by BBD (Annadurai et al., 1999). Different microorganisms are used for amylase production but limited information is available for production of alpha amylase from hot spring isolates Alcaligenes faecalis. In the present work, it has been reported about the hot spring isolates from Taptapani, Odisha and their ability to produce alpha amylase. Thus, Box– Behnken design has been used to investigate the effect of temperature, pH and time in four different media on the production of alpha amylase. The process parameters has been optimized for the four different media to achieve maximum production of alpha amylase. Simultaneously, the optimum temperature and pH for enzyme activity has been studied.
http://dx.doi.org/10.1016/j.bcab.2014.03.005 1878-8181/& 2014 Elsevier Ltd. All rights reserved.
Please cite this article as: Sen, S.K., et al., Thermostable alpha-amylase enzyme production from hot spring isolates Alcaligenes faecalis SSB17 – Statistical optimization. Biocatal. Agric. Biotechnol. (2014), http://dx.doi.org/10.1016/j.bcab.2014.03.005i
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2. Materials and methods 2.1. Screening of microbes for amylolytic activity using plate assay Out of 170 bacterial isolates from Taptapani Hot Spring, the most efficient amylase producing strain A. faecalis SSB-17 (GenBank accession no. KC923293) has been isolated. Amylolytic activity of all strains on agar plates has been observed by the method (Cowan, 1991) using LB medium supplemented with 1% (w/v) soluble starch. After incubation at 50 1C for 48 h, the plates were flooded with KI/I2 solution, a clear zone around the growth indicated hydrolysis of starch as shown in Fig. 1. A. faecalis SSB17 strain has been maintained in the Department of Biotechnology, GIET, Gunupur, India. All chemicals used in this study were of analytical grade and procured from HiMedia and Sigma chemicals Ltd. 2.2. Composition of medium For testing the growth and optimization of amylase production, the following media has been used: Luria Bertani broth (1.0% tryptone, 0.5% yeast extract, 0.5% NaCl, 1.5% agar, pH 7–7.5), Nutrient media (0.3% beef extract, 0.5% peptone), semi-synthetic medium-1 (2.0% tryptone, 0.05% MgSO4 7H2O, 1.0% KH2PO4, 2.5% Na2HPO4, 1.0% NaCl, 2.0% (NH4)2SO4 and 0.05% CaCl2 2H2O) and semi-synthetic medium-2 (20.0% yeast extract, 5.0% glucose, 1.0% MgSO4 7H2O, 0.05% FeCl3, 1.0% KH2PO4, 2.5% Na2HPO4, 0.5% NaCl, 7.5% (NH4)2SO4, 1.0% CaCl2 2H2O and 0.025% thiamine). 2.3. Amylase assay The amylolytic activity has been assayed by measuring the reducing sugar released when starch is used as substrate. The reaction mixture containing 2.0 ml of the crude enzyme, 2.0 ml of 0.1 M acetate buffer and 1% soluble starch (pH 7.0) has been incubated at 50 1C, 60 1C and 70 1C for 30 min. The amount of reducing sugar released has been determined by the addition of 3,5-dinitrosalicylic acid (DNS) followed by boiling for 10 min according to Bernfield (1955). The absorbance has been measured at 540 nm. One unit of enzyme activity is defined as the amount of enzyme required to release 1 μmol of reducing sugar in one minute under the assay condition. For submerged culture in shake
flasks, samples were taken at different time intervals. Cell growth was monitored by measuring the optical density (OD) of the cell suspensions in a UV–vis spectrophotometer (Perkin Elmer Lambda 25) at 600 nm. A series of dilutions has been performed at ratio of 1:10 and 1:100 for better accuracy. OD of the culture was converted to dry cell mass through a previously prepared linear correlation between OD and Cell Dry Weight. One OD600 nm was almost equal to 0.3 g L 1 for this culture. 2.4. Enzyme partial characterization The alpha-amylase enzyme obtained after size exclusion column chromatography has been characterized by determining its optimum temperature, pH and effects of chelating agents. For all the experiments, enzyme assay has been done by the spectrophotometric method using DNS assay. 2.5. Protein precipitation To find out the highest saturation percentage of ammonium sulfate for precipitation of protein two sets of experiment has been carried out. In the first set, different concentrations of ammonium sulfate (50%, 60%, 70% and 80%) has been prepared. Ammonium sulfate concentration of 60% and 80% showed the highest precipitation yield when the samples were loaded on sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) with coomassie brilliant blue. For the second set of experiment, enzyme precipitation has been carried out using ammonium sulfate of varying concentrations (50%, 55%, 60%, 65%, 70%, 75% and 80%). SDS-PAGE showed 75% saturation as the highest concentration of ammonium sulfate for precipitation of the protein. Sample has been mixed with 3 SDS loading buffer (100 mM Tris–HCl, pH 7.0, 200 mM dithiothreitol, 0.4 g/l of bromophenol blue and 20% (v/v) glycerol at a 1:1 (v/v) ratio) for SDS PAGE. Sample with loading buffer was then boiled for 10 min and centrifuged for 15 min at 10,000g. The resulting supernatant has been used for SDS-PAGE, using a 6% (v/v) stacking gel and 12% (v/v) resolving gel. Proteins has been visualized with coomassie brilliant blue. A SDS-free polyacrylamide gel containing 2% starch has been used for zymogram preparation. After electrophoresis of SSB-17 amylase, the gel has been immersed in Triton X100 (2.5%) for 30 min, washed three times (each 10 min) in PBS buffer (pH 7) and finally stained with Lugol's solution. 2.6. Statistical analysis
Fig. 1. Combined effect of temperature and pH on enzyme production at a time period of 84 h.
In the present work, the Box–Behnken experimental design has been chosen to find the relationship between the response functions and variables. The Box–Behnken design is a rotable second-order design based on three-level incomplete-factorial designs. The special arrangement of the Box–Behnken design levels allows the number of design points to increase at the same rate as the number of polynomial coefficients. Each design can be perceived as a combination of a two-level (full or fractional) factorial design with an incomplete block design. In each block, a certain number of factors are put through all combinations for the factorial design, while the other factors are kept at the central values. Most of the designs can be split into groups (blocks), for each of which the model will have a different constant term, in such a way that the block constants will be uncorrelated with the other coefficients. In conventional experimentation, the experiment has been conducted keeping all the variables constant except the parameters whose influence was being studied. This type of experiment reveals the effect of the chosen parameters under set conditions, assuming that variables are independent and that effect will be same at other values of the remaining variables.
Please cite this article as: Sen, S.K., et al., Thermostable alpha-amylase enzyme production from hot spring isolates Alcaligenes faecalis SSB17 – Statistical optimization. Biocatal. Agric. Biotechnol. (2014), http://dx.doi.org/10.1016/j.bcab.2014.03.005i
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Y 4 ¼ 1:896 þ 0:173A 0:562B þ 0:217C 0:253AB þ 0:267AC
3. Results and discussion
0:268BC 0:855A2 0:255B2 0:543C 2
3.1. Statistical modeling using Box–Behnken method To estimate the enzyme activity, empirical models has been developed by using statistical software package design expert. From the analysis of experimental data, it is found that the above response has been influenced by temperature (A); pH (B); and time (C). The complete experimental range and levels of independent variables are given in Table 1 whereas Table 2 shows the design of experiment together with the experimental values for enzyme activity. Runs 13–17 at the center point have been used to determine the experimental error. According to the sequential model sum of squares, the models have been selected on the basis of the highest order polynomials where the additional terms are significant and the models are not aliased. The quadratic model has been selected as suggested by the software. Experiments have been planned to obtain a quadratic model consisting of 23 trials plus a star configuration (α¼ 7 2) and their replicates at the center point. The following equation (in coded factor) has been obtained for enzyme activity using LB medium neglecting the insignificant terms 2
Table 3 shows the ANOVA for enzyme activity in LB medium. The values of R2 and R2adj have been found to be 0.9955 and 0.9899 respectively. The predicted R2 of 0.9295 is in reasonable agreement with the R2adj of 0.9899. Adequate precision measures the signal to noise ratio. A ratio greater than 4 is desirable. The ratio of 46.219 obtained in the present study indicates an adequate signal. Thus, the model evaluated can be used to navigate the design space. The fair correlation coefficients might have resulted by the insignificant terms in Table 3 and is most likely due to three different variables selected in wide ranges with a limited number of experiments as well as the nonlinear influence of the investigated parameters on process response. The F-value for the model was found to be 175.907, which implies that the model is significant. There is only 0.01% chance that a “Model F-value” this large could occur due to noise. Value of “Prob4F” less than 0.0500 indicates Table 3 ANOVA for enzyme production in LB medium. Source
2
Y 1 ¼ 2:485 0:828B þ 0:324C þ 0:118AC 0:77BC 1:02A 0:22B 0:424C 2
ð1Þ
Similarly, the quadratic models developed for enzyme activity using nutrient, SM1 and SM2 media are represented in Eqs. (2)–(4). Y 2 ¼ 0:4125 1:01B þ 0:43C þ 0:28AC 0:63BC 1:6A2 0:97B2 1:22C 2
ð2Þ
Y 3 ¼ 2:112 þ 0:172A 0:55B þ0:116C 0:226AB þ 0:283AC 0:3BC 0:96A2 0:344B2 0:55C 2
ð3Þ
Table 1 Level of independent variables. Variables
Symbol
1
0
þ1
Temperature (1C) pH Time (h)
A B C
60 6.5 72
70 7.75 84
80 9 96
Run
Temp
pH
Time
LB
Nutrient
SM1
SM2
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17
60 80 60 80 60 80 60 80 70 70 70 70 70 70 70 70 70
6.5 6.5 9 9 7.75 7.75 7.75 7.75 6.5 9 6.5 9 7.75 7.75 7.75 7.75 7.75
84 84 84 84 72 72 96 96 72 72 96 96 84 84 84 84 84
2.048 1.985 0.542 0.348 0.857 0.689 1.145 1.45 1.548 1.345 3.858 0.578 2.485 2.485 2.485 2.485 2.485
2.457 2.745 0.415 0.578 1.012 0.548 1.475 2.145 1.921 1.245 3.875 0.678 4.125 4.125 4.125 4.125 4.125
0.947 1.754 0.312 0.213 0.545 0.312 0.312 1.214 1.413 0.878 2.145 0.412 2.112 2.112 2.112 2.112 2.112
0.941 1.745 0.333 0.124 0.385 0.245 0.215 1.145 1.145 0.545 2.187 0.514 1.896 1.896 1.896 1.896 1.896
Sum of squares
Model 14.555 A 0.001 B 5.487 C 0.839 AB 0.004 AC 0.055 BC 2.366 A2 4.429 2 B 0.220 C2 0.757 Residual 0.064 Lack of 0.064 fit Pure 0 error Cor 14.620 total 2 R R2adj R2pred
Degree of freedom
Mean square
F value
Prob4F
Remarks
9 1 1 1 1 1 1 1 1 1 7 3
1.617 0.001 5.487 0.839 0.004 0.055 2.366 4.429 0.220 0.757 0.009 0.021
175.907 0.195 596.900 91.341 0.466 6.083 257.444 481.728 23.937 82.378
o0.0001 0.6715 o0.0001 o0.0001 0.5165 0.0431 o0.0001 o0.0001 0.0018 o0.0001
Significant
4
0
Significant Significant Significant Significant Significant Significant Significant
16 0.995598 0.989938 0.929567
Table 4 ANOVA for enzyme production in nutrient medium. Source
Table 2 Design matrix for enzyme production.
ð4Þ
Sum of Squares
Model 35.095 A 0.054 B 8.165 C 1.485 AB 0.004 AC 0.321 BC 1.589 A2 10.853 B2 3.968 C2 6.313 Residual 0.078 Lack of 0.078 fit Pure 0.000 error Cor 35.173 total 2 R R2adj R2pred
Degree of freedom 9 1 1 1 1 1 1 1 1 1 7 3 4
Mean square
F value
Prob4F
Remarks
3.899 0.054 8.165 1.485 0.004 0.321 1.589 10.853 3.968 6.313 0.011 0.026
348.914 4.828 730.576 132.896 0.350 28.766 142.169 971.124 355.033 564.900
o0.0001 0.0640 o0.0001 o0.0001 0.5730 0.0010 o0.0001 o0.0001 o0.0001 o0.0001
Significant Significant Significant Significant Significant Significant Significant Significant
0
16 0.997776 0.994916 0.964413
Please cite this article as: Sen, S.K., et al., Thermostable alpha-amylase enzyme production from hot spring isolates Alcaligenes faecalis SSB17 – Statistical optimization. Biocatal. Agric. Biotechnol. (2014), http://dx.doi.org/10.1016/j.bcab.2014.03.005i
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model terms are significant. In this case B, C, AC, BC, A2, B2 and C2 are significant model terms. The ANOVA for nutrient, SM1 and SM2 media have been represented in Tables 4–6. The coefficients of correlations obtained are 0.9977, 0.9978 and 0.9983 for nutrient medium, SM1 and SM2 respectively. On the basis of ANOVA results obtained, pH and time has been found to have significant effects on enzyme activity in LB and nutrient media, whereas in SM1 and SM2 media, temperature, pH and time play significant role on enzyme activity. 3.2. Combined effect of temperature, pH and time on enzyme production 3.2.1. Using LB medium Fig. 2 shows the combined effect of temperature and pH on enzyme activity at a time period of 84 h in LB medium. It has been observed that with increase in temperature up to 75 1C, the enzyme activity increases and then decreases. The increase in Table 5 ANOVA for enzyme production in SM1 medium. Source
Sum of squares
Model A B C AB AC BC A2 B2 C2 Residual Lack of fit Pure error Cor total R2 2 Radj R2pred
9.918 0.237 2.469 0.109 0.205 0.322 0.359 3.887 0.500 1.299 0.022 0.022 0 9.939
Mean square
F value
Prob4 F
Remarks
9 1 1 1 1 1 1 1 1 1 7 3
1.102 0.237 2.469 0.109 0.205 0.322 0.359 3.887 0.500 1.299 0.003 0.007
357.962 76.992 801.907 35.498 66.660 104.616 116.552 1262.804 162.441 421.866
o 0.0001 o 0.0001 o 0.0001 0.0006 o 0.0001 o 0.0001 o 0.0001 o 0.0001 o 0.0001 o 0.0001
Significant Significant Significant Significant Significant Significant Significant Significant Significant Significant
4
0
Degree of freedom
Fig. 2. Combined effect of time and temperature on enzyme production at a pH of 7.75.
16 0.997832 0.995044 0.965311
Table 6 ANOVA for enzyme production in SM2 medium. Source
Sum of squares
Model A B C AB AC BC A2 B2 C2 Residual Lack of fit Pure error Cor total R2 2 Radj R2pred
8.992 0.240 2.534 0.379 0.257 0.286 0.288 3.080 0.274 1.243 0.015 0.015 0 9.007
Mean square
F value
Prob4 F
Remarks
9 1 1 1 1 1 1 1 1 1 7 3
0.999 0.240 2.534 0.379 0.257 0.286 0.288 3.080 0.274 1.243 0.002 0.005
470.503 112.911 1193.018 178.416 120.805 134.782 135.539 1450.268 128.927 585.143
o 0.0001 o 0.0001 o 0.0001 o 0.0001 o 0.0001 o 0.0001 o 0.0001 o 0.0001 o 0.0001 o 0.0001
Significant Significant Significant Significant Significant Significant Significant Significant Significant Significant
4
0
Degree of freedom
16 0.99835 0.996228 0.973594
Fig. 3. Combined effect of time and pH on enzyme production at a temperature of 70 1C.
enzyme activity may be due to the metabolic process adopted in hot spring environment. Beyond 75 1C, the enzyme activity decreases due to the changes in cell envelope. Also modification in the surface protein layer can be induced by different levels of oxygen. Therefore, incubation temperature might affect the cell membrane of A. faecalis SSB-17 by changing the dissolved oxygen. Simultaneously, with increase in pH the enzyme activity decreases. The decline in enzyme activity may be due to reversible reaction that involves ionization or deionization of acidic or basic groups in the active center of the enzyme protein. Irreversible inactivation of the enzyme was particularly at the lower and higher ranges of acidic and alkaline condition. Fig. 3 shows the combined effect of time and temperature on enzyme activity at a pH 7.75 in LB medium. It has been observed that with increase in time up to 93 h the enzyme activity increases and then decreases. The increase in enzyme activity is due to the log phase in growth kinetics of the microorganisms. The decrease in enzyme activity beyond 99 h is due to the decline phase of the microorganisms and
Please cite this article as: Sen, S.K., et al., Thermostable alpha-amylase enzyme production from hot spring isolates Alcaligenes faecalis SSB17 – Statistical optimization. Biocatal. Agric. Biotechnol. (2014), http://dx.doi.org/10.1016/j.bcab.2014.03.005i
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unavailability of the substrate. Similarly, Fig. 4 (the three dimensional response surface), represents the combined effect of time and pH on the enzyme activity at a temperature of 70 1C in LB medium. The reasons for the effect of time and pH on the enzyme activity has been described above. A maximum enzyme activity of 3.858 U/ml was found in LB medium.
3.2.2. Using nutrient medium Fig. 5 shows the combined effect of temperature and pH on enzyme activity at a time period of 84 h in nutrient medium. It has been observed that with increase in temperature up to 75 1C, the enzyme activity increases and then decreases. The reason for increase and decrease in enzyme activity with respect to the temperature is similar to LB medium. Fig. 6 depicts the combined effect of time and temperature on enzyme activity at a pH 7.75 in
Fig. 6. Combined effect of time and pH on enzyme production in nutrient medium at a temperature of 70 1C.
Fig. 4. Combined effect of temperature and pH on enzyme production at a time period of 84 h.
Fig. 7. Combined effect of temperature and pH on enzyme production using SM1 medium at a time period of 84 h.
Fig. 5. Combined effect of time and temperature on enzyme production at a pH of 7.75.
nutrient medium. It has been observed that with increase in time up to 92 h the enzyme activity increases and then decreases. The increase in enzyme activity is due to the log phase in growth kinetics of the microorganisms. The decrease in enzyme activity beyond 92 h is due to decline phase of the microorganisms and unavailability of substrate. It has been observed that the microorganisms can sustain up to 99 h in LB medium whereas in nutrient medium it can sustain up to 92 h. This may be due to the presence of different carbon and nitrogen sources. Similarly, Fig. 7 (the three dimensional response surface), represents the combined effect of time and pH on the enzyme activity at a temperature of 70 1C in nutrient medium. It has been observed that the enzyme activity increases up to pH 8, which may be due to the binding of enzyme with the substrate or ionization of the substrate. The decline in enzyme activity beyond pH 8 may be due to reversible reaction that involves ionization or deionization of
Please cite this article as: Sen, S.K., et al., Thermostable alpha-amylase enzyme production from hot spring isolates Alcaligenes faecalis SSB17 – Statistical optimization. Biocatal. Agric. Biotechnol. (2014), http://dx.doi.org/10.1016/j.bcab.2014.03.005i
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3.2.3. Using SM1 medium Fig. 8 (the three dimensional response plot), shows the combined effect of temperature and pH on enzyme activity at a time period of 84 h in SM1 medium. It has been observed that with increase in temperature up to 75 1C, the enzyme activity increases and then decreases. The reason for increase and decrease in enzyme activity with respect to temperature is similar to LB and
nutrient medium. Fig. 9 (the three dimensionless response plot), shows the combined effect of time and temperature on enzyme activity at a pH 7.75 in SM1 medium. It has been observed that with increase in time up to 84 h the enzyme activity increases and then decreases. The increase in enzyme activity is due to the log phase in growth kinetics of the microorganisms. The decrease in enzyme activity beyond 84 h is due to the decline phase of microorganisms and unavailability of substrate. It has been observed that the microorganisms can sustain up to 84 h in SM1 medium i.e. less than the LB and nutrient media. Similarly, Fig. 10 (the three dimensional response surface), represents the combined effect of time and pH on enzyme activity at a temperature of 70 1C in SM1 medium. It has been observed that the enzyme activity increases up to pH of 7.7 and then decreases. The tolerance pH level of A. faecalis SSB-17 lies between nutrient and LB media.
Fig. 8. Combined effect of time and temperature on enzyme production in SM1 medium at a pH of 7.75.
Fig. 10. Combined effect of temperature and pH on enzyme production in SM2 medium at a time period of 84 h.
Fig. 9. Combined effect of time and pH on enzyme production in SM1 medium at a temperature of 70 1C.
Fig. 11. Combined effect of time and temperature on enzyme production in SM2 medium at a pH of 7.75.
acidic or basic groups in the active center of the enzyme protein. Irreversible inactivation of the enzyme was particularly at the lower and higher ranges of acidic and alkaline condition. The tolerance pH level of A. faecalis SSB-17 is more in nutrient medium as compared to LB medium, which may be due to more ionization and deionization in nutrient medium. A maximum enzyme activity of 4.125 U/ml was found in nutrient medium.
Please cite this article as: Sen, S.K., et al., Thermostable alpha-amylase enzyme production from hot spring isolates Alcaligenes faecalis SSB17 – Statistical optimization. Biocatal. Agric. Biotechnol. (2014), http://dx.doi.org/10.1016/j.bcab.2014.03.005i
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A maximum enzyme activity of 2.145 U/ml was found in SM1 medium. 3.2.4. Using SM2 medium Fig. 11 shows the combined effect of temperature and pH on enzyme activity at a time period of 84 h in SM2 medium. It has been observed that with increase in temperature up to 75 1C, the enzyme activity increases and then decreases. The reason for increase and decrease in enzyme activity with respect to temperature is similar to other media, which has been explained in earlier sections. Fig. 12 depicts the combined effect of time and temperature on enzyme activity at pH 7.75 in SM2 medium. It has been observed that with increase in time up to 89h the enzyme activity increases and then decreases. The increase in enzyme activity was due to the log phase in growth kinetics of the microorganisms. The decrease in enzyme activity beyond 89h was due to the decline phase of the microorganisms and unavailability of substrate. It has been observed that the time period up to
7
which the microorganism can sustain is more than SM1 medium but less than that of LB and nutrient media. Similarly, Fig. 13 (the three dimensional response surface), represents the combined effect of time and pH on the enzyme activity at a temperature of 70 1C in SM2 medium. It has been found that the enzyme activity increases up to pH 7.7 and then decreases. The tolerant pH level of A. faecalis SSB-17 is similar to SM1 medium, whereas it is less than that of LB and nutrient media. A maximum enzyme activity of 2.187 U/ml was found in SM2 medium. 3.3. Optimization by response surface modeling One of the main aims of this study was to find the optimum process parameters to maximize the enzyme activity from the mathematical model equations developed in this study. The quadratic model equations have been optimized using quadratic programming (QP) to maximize enzyme activity within the experimental range studied. The optimum regions on the temperature,
Fig. 12. Combined effect of time and pH on enzyme production in SM2 medium at a temperature of 70 1C.
Fig. 14. Optimization region of pH and temperature for enzyme production using nutrient medium at 84 h.
Fig. 13. Optimization region of pH and temperature for enzyme production using LB medium at 84 h.
Fig. 15. Optimization region of pH and temperature for enzyme production using SM1 medium at 84 h.
Please cite this article as: Sen, S.K., et al., Thermostable alpha-amylase enzyme production from hot spring isolates Alcaligenes faecalis SSB17 – Statistical optimization. Biocatal. Agric. Biotechnol. (2014), http://dx.doi.org/10.1016/j.bcab.2014.03.005i
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time and pH for enzyme activity are shown in Figs. 14–17 for LB, nutrient, SM1 and SM2 media respectively. The optimum production factors for enzyme activity by using different media has been
presented in Table 7. It has been observed from Table 7 that nutrient medium is suitable for enzyme activity from A. faecalis SSB-17. The optimized conditions (Table 7 and Fig. 15) are temperature, 70 1C; pH, 7.57; and time, 84 h with a maximum enzyme activity of 4.125 U/ml in nutrient medium.
3.4. Partial purification of alpha amylase The highest enzyme yield has been obtained by precipitating the protein at 80% saturation of ammonium sulfate (Fig. 17A). The saturated protein has been first purified by ion exchange chromatography followed by gel filtration using a Sephadex-G75 column to gain 38.89 mg total protein. Gel filtration led to 59.73% recovery of the purified amylase protein with a specific activity of 5.33 U/mg. SDS-PAGE of the purified enzyme has shown
Table 7 Optimized conditions for enzyme production in different medium.
Fig. 16. Optimization region of pH and temperature for enzyme production using SM2 medium at 84 h.
Medium
Temperature (1C)
pH
Time (h)
Predicted
Observed
LB Nutrient SM1 SM2
70 70 70 74.39
6.5 7.57 6.56 6.75
96 84 96 90.42
3.753 4.125 2.183 2.322
3.858 4.125 2.145 2.187
Fig. 17. (A) SDS-PAGE of partially purified protein following precipitation at different percentage saturations of ammonium sulfate. Lane 1: Standard protein markers; Lane 2: 60% ammonium sulfate; Lane 3: 70% ammonium sulfate; Lane 4: 80% ammonium sulfate. (B) SDS-PAGE of the purified amylase from Alcaligenes faecalis SSB17. Lane 1: ladder marker; Lane 2: crude enzyme extract; Lane 3: enzyme isolation after chromatography by DEAE-Sepharose; Lane 4: enzyme isolation after chromatography by sephadexG75. (C) Native-PAGE of purified enzyme. Lane 1: ladder marker; Lane 2: purified enzyme. Protein Marker cat. no. H-623110475001730.
Please cite this article as: Sen, S.K., et al., Thermostable alpha-amylase enzyme production from hot spring isolates Alcaligenes faecalis SSB17 – Statistical optimization. Biocatal. Agric. Biotechnol. (2014), http://dx.doi.org/10.1016/j.bcab.2014.03.005i
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the presence of a single band associated with amylase enzyme, having a molecular weight of 52 kDa (Fig. 17).
4. Conclusion In this study, four different media have been used for enzyme activity from A. faecalis SSB-17. Response surface methodology (RSM) based BBD and QP has been used to model and optimize the influence of three process parameters on enzyme activity in the four different media. These three process parameters are temperature, pH and time. Mathematical model equations have been derived for enzyme activity by using sets of experimental data and ANOVA. Three-dimensional response surface plots, which are simulated from the models, are presented to describe the effect of the process variables on enzyme activity. Predicted values obtained using the model equations have been in very good agreement with the observed values. Taking advantage of the QP, temperature as 70 1C, pH as 7.75 and time as 84 h has been determined as optimum levels in nutrient medium of the process parameters to achieve the maximum enzyme activity of 4.125 U/ml, similar to maximum enzyme activity in the tests conducted. The results in this paper indicate that optimization by using RSM, BBD and QP can be useful in improving the enzyme activity from A. faecalis SSB-17. Simultaneously, SDS-PAGE of the purified enzyme has shown the presence of a single band associated with the amylase enzyme, having molecular weight of 52 kDa.
Acknowledgment The authors show deep gratitude to the management of GIET, Gunupur-765022, for their constant motivation along with all facilities and requisite support for completion of this work.
9
References Annadurai, G., Mathalai Balan, S., Murugesan, T., 1999. Box–Behnken design in the development of optimized complex medium for phenol degradation using Pseudomonas putida (NICM 2174). Bioprocess Eng. 21, 415–421. Bezbaruah, R.L., Gogoi, B.K., Pillai, K.R., 1994. Optimization of alkaline amylase production bythermophilic Bacillus stearothermophilus AN 002. J. Basic Microbiol. 34, 139–144. Box, G.E.P., Behnken, D.W., 1960. Three level design for the study of quantitative variables. Technometrics 2, 455–475. Bernfield, P., 1955. Methods in Enzymology. vol. 1. Academic Press, New York, USA, pp. 149–158 Cowan, D.A., 1991. Industrial enzymes. In: Moses, V., Capes, R.E. (Eds.), Biotechnology: The Science and the Business. Harwood Academic Publishers, London, pp. 311–340 Hewitt, C.J., Solomons, G.L., 1996. Theproduction of a-amylase (E.C.3.2.1.1.) by Bacillus amyloliquefaciens, in a complex and a totally defined synthetic culture medium. J. Ind. Microbiol. 17, 96–99. Ikram-ul-Haq, Ashraf, Hamad, Iqbal, Javed, Qadeer, M.A., 2003. Production of alpha amylase by Bacillus licheniformis using an economical medium. Bioresour. Technol. 87, 57–61. Jana, M., Chattopadhyay, D.J., Pati, B.R., 1997. Thermostable, highsalt-tolerant amylase from Bacillus megaterium VUMB-109. Acta Microbiol. Immunol. Hung. 44, 281–289. Kelly, C.T., Bolton, D.J., Fogarty, W.M., 1997. Biphasic production of alpha-amylase of Bacillus flavor thermus in batch fermentation. Biotechnol. Lett. 19, 75–77. Morgan, F.J., Priest, F.G., 1981. Characterization of thermo stable alpha-amylase from Bacillus licheniformis NCTB 6346. J. Appl. Bacteriol. 50, 104–114. Nigam, P., Singh, D., 1995. Enzyme and microbial system involved in starch processing. Enzyme Microb. Technol. 17, 770–778. Pedersen, H., Nielsen, J., 2000. The influence of nitrogen sources on the alpha amylase productivity of Aspergillus oryzae in continuous cultures. Appl. Microbiol. Biotechnol. 53, 278–281. Prescott, M.I., Harley, P.S., Klein, A.D., 2002. Microbiology, 5th ed. McGraw Hill Inc., New York. Roy, I., Gupta, M.N., 2004. Hydrolysis of starch by a mixture of glycoamylase and pullulanase entrapped. individually in calcium alginate beads. Enzyme Microb. Technol. 34, 26–32. Tanyildizi, M.S., Ozer, D., Elibol, M., 2005. Optimization of alpha-amylase production by Bacillus sp. Using response surface methodology. Process Biochem. 40, 2291–2296. Thippeswamy, S., Girigowda, K., Mulimani, V.H., 2006. Isolation and identification of a-amylase producing Bacillus sp. from dhal industry waste. Ind. J. Biochem. Biophys. 43, 295–298. Wind, R.D., Buitelaar, R.M., Egglink, G., Huizing, H.J., DijKhuized, L., 1994. Characterization of a new Bacillus stearothermophilus isolate: a highly thermostable alpha-amylase producing strain. Appl. Microbiol. Biotechnol. 41, 155–162.
Please cite this article as: Sen, S.K., et al., Thermostable alpha-amylase enzyme production from hot spring isolates Alcaligenes faecalis SSB17 – Statistical optimization. Biocatal. Agric. Biotechnol. (2014), http://dx.doi.org/10.1016/j.bcab.2014.03.005i
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Original Research Paper
Thermostable alpha-amylase enzyme production from hot spring isolates Alcaligenes faecalis SSB17 – Statistical optimization Sudip Kumar Sen a, Tapas Kumar Dora a, Bidyut Bandyopadhyay b, Pradeep Kumar Das Mohapatra c, Sangeeta Raut a,n a
Department of Biotechnology, Gandhi Institute of Engineering Technology, Gunupur, Rayagada, Odisha 765022, India Department of Biotechnology, Vidyasagar University, Midnapore, West Bengal 721102, India c Department of Microbiology, Vidyasagar University, Midnapore, West Bengal 721102, India b
art ic l e i nf o
a b s t r a c t
Article history: Received 16 January 2014 Accepted 14 March 2014
In the present investigation the production and characterization of a thermostable alpha-amylase enzyme from hot spring isolates Alcaligenes faecalis SSB17 has been studied. The individual and combined effect of temperature, pH and time has been investigated on the production of enzyme in four media (Luria Bertani, Nutrient Media, Semi-Synthetic Media l and Semi-Synthetic Media 2) using Box–Behnken design (BBD). Analysis of variance (ANOVA) shows high coefficient values of determination for each medium and satisfactory prediction second order regression models has been derived. Enzyme purification has been carried out by ammonium sulfate precipitation and size exclusion chromatography (SEC). Maximum purification has been obtained by SEC with 60 fold. SDS-PAGE of the purified enzyme has shown the presence of a single band associated with the amylase enzyme, having a molecular weight of 52 kDa & 2014 Elsevier Ltd. All rights reserved.
Keywords: Hot spring Alcaligenes faecalis Amylase Box–Behnken design Optimization
1. Introduction The production of economically important alpha-amylases is essential for the conversion of starch into oligosaccharides (Pedersen and Nielsen, 2000). This enzyme is extensively used in paper, food, pharmaceutical, sugar industries and starch liquefaction (Nigam and Singh, 1995; Ikram-ul-Haq et al., 2003; Roy and Gupta, 2004). Requirement for microbial amylase has increased due to their specificity for reaction, mild condition required for reaction and less energy consumption than the conventional chemical methods. Use of microorganisms for the production of amylase is economical because microbes are easy to manipulate for obtaining enzymes of specific characteristics. Bacillus species are heterogeneous form of organisms and are very versatile in their adaptability to the environment. Bacillus species like Bacillus amyloliquefaciens (Hewitt and Solomons, 1996). Bacillus licheniformis (Morgan and Priest, 1981), Bacillus stearothermophilus (Wind et al., 1994), Bacillus flavothermus (Kelly et al., 1997) and Bacillus megaterium (Jana et al., 1997) have been reported for thermostable alpha-amylase production by fermentation process. The most important characteristic of thermophilic organisms is their ability to produce thermostable enzymes with a higher operational stability and a longer shelf-life n
Corresponding author. Mobile: þ 91 9438450789. E-mail address: [email protected] (S. Raut).
(Thippeswamy et al., 2006). Liquid sugar industry needs thermostable α-amylase that can maintain its activity at high temperature, such as in the gelatinization (100–110 1C) and liquefaction process (80–90 1C). Growth of microorganisms and its metabolite synthesis mainly depend on the medium nutrients and the growth conditions (Prescott et al., 2002). Optimization of medium components and process conditions plays a vital role for maximizing the microbial metabolites production and minimizing the production cost (Bezbaruah et al., 1994). In recent years, the application of statistical experimental design has been reported by many authors for optimization of various microbial metabolites (Tanyildizi et al., 2005). Box–Behnken design (BBD) of RSM is successfully employed to predict the optimal level of the variables within the design space of study (Box and Behnken, 1960) and interaction effect among the variables can also be explained by BBD (Annadurai et al., 1999). Different microorganisms are used for amylase production but limited information is available for production of alpha amylase from hot spring isolates Alcaligenes faecalis. In the present work, it has been reported about the hot spring isolates from Taptapani, Odisha and their ability to produce alpha amylase. Thus, Box– Behnken design has been used to investigate the effect of temperature, pH and time in four different media on the production of alpha amylase. The process parameters has been optimized for the four different media to achieve maximum production of alpha amylase. Simultaneously, the optimum temperature and pH for enzyme activity has been studied.
http://dx.doi.org/10.1016/j.bcab.2014.03.005 1878-8181/& 2014 Elsevier Ltd. All rights reserved.
Please cite this article as: Sen, S.K., et al., Thermostable alpha-amylase enzyme production from hot spring isolates Alcaligenes faecalis SSB17 – Statistical optimization. Biocatal. Agric. Biotechnol. (2014), http://dx.doi.org/10.1016/j.bcab.2014.03.005i
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2. Materials and methods 2.1. Screening of microbes for amylolytic activity using plate assay Out of 170 bacterial isolates from Taptapani Hot Spring, the most efficient amylase producing strain A. faecalis SSB-17 (GenBank accession no. KC923293) has been isolated. Amylolytic activity of all strains on agar plates has been observed by the method (Cowan, 1991) using LB medium supplemented with 1% (w/v) soluble starch. After incubation at 50 1C for 48 h, the plates were flooded with KI/I2 solution, a clear zone around the growth indicated hydrolysis of starch as shown in Fig. 1. A. faecalis SSB17 strain has been maintained in the Department of Biotechnology, GIET, Gunupur, India. All chemicals used in this study were of analytical grade and procured from HiMedia and Sigma chemicals Ltd. 2.2. Composition of medium For testing the growth and optimization of amylase production, the following media has been used: Luria Bertani broth (1.0% tryptone, 0.5% yeast extract, 0.5% NaCl, 1.5% agar, pH 7–7.5), Nutrient media (0.3% beef extract, 0.5% peptone), semi-synthetic medium-1 (2.0% tryptone, 0.05% MgSO4 7H2O, 1.0% KH2PO4, 2.5% Na2HPO4, 1.0% NaCl, 2.0% (NH4)2SO4 and 0.05% CaCl2 2H2O) and semi-synthetic medium-2 (20.0% yeast extract, 5.0% glucose, 1.0% MgSO4 7H2O, 0.05% FeCl3, 1.0% KH2PO4, 2.5% Na2HPO4, 0.5% NaCl, 7.5% (NH4)2SO4, 1.0% CaCl2 2H2O and 0.025% thiamine). 2.3. Amylase assay The amylolytic activity has been assayed by measuring the reducing sugar released when starch is used as substrate. The reaction mixture containing 2.0 ml of the crude enzyme, 2.0 ml of 0.1 M acetate buffer and 1% soluble starch (pH 7.0) has been incubated at 50 1C, 60 1C and 70 1C for 30 min. The amount of reducing sugar released has been determined by the addition of 3,5-dinitrosalicylic acid (DNS) followed by boiling for 10 min according to Bernfield (1955). The absorbance has been measured at 540 nm. One unit of enzyme activity is defined as the amount of enzyme required to release 1 μmol of reducing sugar in one minute under the assay condition. For submerged culture in shake
flasks, samples were taken at different time intervals. Cell growth was monitored by measuring the optical density (OD) of the cell suspensions in a UV–vis spectrophotometer (Perkin Elmer Lambda 25) at 600 nm. A series of dilutions has been performed at ratio of 1:10 and 1:100 for better accuracy. OD of the culture was converted to dry cell mass through a previously prepared linear correlation between OD and Cell Dry Weight. One OD600 nm was almost equal to 0.3 g L 1 for this culture. 2.4. Enzyme partial characterization The alpha-amylase enzyme obtained after size exclusion column chromatography has been characterized by determining its optimum temperature, pH and effects of chelating agents. For all the experiments, enzyme assay has been done by the spectrophotometric method using DNS assay. 2.5. Protein precipitation To find out the highest saturation percentage of ammonium sulfate for precipitation of protein two sets of experiment has been carried out. In the first set, different concentrations of ammonium sulfate (50%, 60%, 70% and 80%) has been prepared. Ammonium sulfate concentration of 60% and 80% showed the highest precipitation yield when the samples were loaded on sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) with coomassie brilliant blue. For the second set of experiment, enzyme precipitation has been carried out using ammonium sulfate of varying concentrations (50%, 55%, 60%, 65%, 70%, 75% and 80%). SDS-PAGE showed 75% saturation as the highest concentration of ammonium sulfate for precipitation of the protein. Sample has been mixed with 3 SDS loading buffer (100 mM Tris–HCl, pH 7.0, 200 mM dithiothreitol, 0.4 g/l of bromophenol blue and 20% (v/v) glycerol at a 1:1 (v/v) ratio) for SDS PAGE. Sample with loading buffer was then boiled for 10 min and centrifuged for 15 min at 10,000g. The resulting supernatant has been used for SDS-PAGE, using a 6% (v/v) stacking gel and 12% (v/v) resolving gel. Proteins has been visualized with coomassie brilliant blue. A SDS-free polyacrylamide gel containing 2% starch has been used for zymogram preparation. After electrophoresis of SSB-17 amylase, the gel has been immersed in Triton X100 (2.5%) for 30 min, washed three times (each 10 min) in PBS buffer (pH 7) and finally stained with Lugol's solution. 2.6. Statistical analysis
Fig. 1. Combined effect of temperature and pH on enzyme production at a time period of 84 h.
In the present work, the Box–Behnken experimental design has been chosen to find the relationship between the response functions and variables. The Box–Behnken design is a rotable second-order design based on three-level incomplete-factorial designs. The special arrangement of the Box–Behnken design levels allows the number of design points to increase at the same rate as the number of polynomial coefficients. Each design can be perceived as a combination of a two-level (full or fractional) factorial design with an incomplete block design. In each block, a certain number of factors are put through all combinations for the factorial design, while the other factors are kept at the central values. Most of the designs can be split into groups (blocks), for each of which the model will have a different constant term, in such a way that the block constants will be uncorrelated with the other coefficients. In conventional experimentation, the experiment has been conducted keeping all the variables constant except the parameters whose influence was being studied. This type of experiment reveals the effect of the chosen parameters under set conditions, assuming that variables are independent and that effect will be same at other values of the remaining variables.
Please cite this article as: Sen, S.K., et al., Thermostable alpha-amylase enzyme production from hot spring isolates Alcaligenes faecalis SSB17 – Statistical optimization. Biocatal. Agric. Biotechnol. (2014), http://dx.doi.org/10.1016/j.bcab.2014.03.005i
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Y 4 ¼ 1:896 þ 0:173A 0:562B þ 0:217C 0:253AB þ 0:267AC
3. Results and discussion
0:268BC 0:855A2 0:255B2 0:543C 2
3.1. Statistical modeling using Box–Behnken method To estimate the enzyme activity, empirical models has been developed by using statistical software package design expert. From the analysis of experimental data, it is found that the above response has been influenced by temperature (A); pH (B); and time (C). The complete experimental range and levels of independent variables are given in Table 1 whereas Table 2 shows the design of experiment together with the experimental values for enzyme activity. Runs 13–17 at the center point have been used to determine the experimental error. According to the sequential model sum of squares, the models have been selected on the basis of the highest order polynomials where the additional terms are significant and the models are not aliased. The quadratic model has been selected as suggested by the software. Experiments have been planned to obtain a quadratic model consisting of 23 trials plus a star configuration (α¼ 7 2) and their replicates at the center point. The following equation (in coded factor) has been obtained for enzyme activity using LB medium neglecting the insignificant terms 2
Table 3 shows the ANOVA for enzyme activity in LB medium. The values of R2 and R2adj have been found to be 0.9955 and 0.9899 respectively. The predicted R2 of 0.9295 is in reasonable agreement with the R2adj of 0.9899. Adequate precision measures the signal to noise ratio. A ratio greater than 4 is desirable. The ratio of 46.219 obtained in the present study indicates an adequate signal. Thus, the model evaluated can be used to navigate the design space. The fair correlation coefficients might have resulted by the insignificant terms in Table 3 and is most likely due to three different variables selected in wide ranges with a limited number of experiments as well as the nonlinear influence of the investigated parameters on process response. The F-value for the model was found to be 175.907, which implies that the model is significant. There is only 0.01% chance that a “Model F-value” this large could occur due to noise. Value of “Prob4F” less than 0.0500 indicates Table 3 ANOVA for enzyme production in LB medium. Source
2
Y 1 ¼ 2:485 0:828B þ 0:324C þ 0:118AC 0:77BC 1:02A 0:22B 0:424C 2
ð1Þ
Similarly, the quadratic models developed for enzyme activity using nutrient, SM1 and SM2 media are represented in Eqs. (2)–(4). Y 2 ¼ 0:4125 1:01B þ 0:43C þ 0:28AC 0:63BC 1:6A2 0:97B2 1:22C 2
ð2Þ
Y 3 ¼ 2:112 þ 0:172A 0:55B þ0:116C 0:226AB þ 0:283AC 0:3BC 0:96A2 0:344B2 0:55C 2
ð3Þ
Table 1 Level of independent variables. Variables
Symbol
1
0
þ1
Temperature (1C) pH Time (h)
A B C
60 6.5 72
70 7.75 84
80 9 96
Run
Temp
pH
Time
LB
Nutrient
SM1
SM2
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17
60 80 60 80 60 80 60 80 70 70 70 70 70 70 70 70 70
6.5 6.5 9 9 7.75 7.75 7.75 7.75 6.5 9 6.5 9 7.75 7.75 7.75 7.75 7.75
84 84 84 84 72 72 96 96 72 72 96 96 84 84 84 84 84
2.048 1.985 0.542 0.348 0.857 0.689 1.145 1.45 1.548 1.345 3.858 0.578 2.485 2.485 2.485 2.485 2.485
2.457 2.745 0.415 0.578 1.012 0.548 1.475 2.145 1.921 1.245 3.875 0.678 4.125 4.125 4.125 4.125 4.125
0.947 1.754 0.312 0.213 0.545 0.312 0.312 1.214 1.413 0.878 2.145 0.412 2.112 2.112 2.112 2.112 2.112
0.941 1.745 0.333 0.124 0.385 0.245 0.215 1.145 1.145 0.545 2.187 0.514 1.896 1.896 1.896 1.896 1.896
Sum of squares
Model 14.555 A 0.001 B 5.487 C 0.839 AB 0.004 AC 0.055 BC 2.366 A2 4.429 2 B 0.220 C2 0.757 Residual 0.064 Lack of 0.064 fit Pure 0 error Cor 14.620 total 2 R R2adj R2pred
Degree of freedom
Mean square
F value
Prob4F
Remarks
9 1 1 1 1 1 1 1 1 1 7 3
1.617 0.001 5.487 0.839 0.004 0.055 2.366 4.429 0.220 0.757 0.009 0.021
175.907 0.195 596.900 91.341 0.466 6.083 257.444 481.728 23.937 82.378
o0.0001 0.6715 o0.0001 o0.0001 0.5165 0.0431 o0.0001 o0.0001 0.0018 o0.0001
Significant
4
0
Significant Significant Significant Significant Significant Significant Significant
16 0.995598 0.989938 0.929567
Table 4 ANOVA for enzyme production in nutrient medium. Source
Table 2 Design matrix for enzyme production.
ð4Þ
Sum of Squares
Model 35.095 A 0.054 B 8.165 C 1.485 AB 0.004 AC 0.321 BC 1.589 A2 10.853 B2 3.968 C2 6.313 Residual 0.078 Lack of 0.078 fit Pure 0.000 error Cor 35.173 total 2 R R2adj R2pred
Degree of freedom 9 1 1 1 1 1 1 1 1 1 7 3 4
Mean square
F value
Prob4F
Remarks
3.899 0.054 8.165 1.485 0.004 0.321 1.589 10.853 3.968 6.313 0.011 0.026
348.914 4.828 730.576 132.896 0.350 28.766 142.169 971.124 355.033 564.900
o0.0001 0.0640 o0.0001 o0.0001 0.5730 0.0010 o0.0001 o0.0001 o0.0001 o0.0001
Significant Significant Significant Significant Significant Significant Significant Significant
0
16 0.997776 0.994916 0.964413
Please cite this article as: Sen, S.K., et al., Thermostable alpha-amylase enzyme production from hot spring isolates Alcaligenes faecalis SSB17 – Statistical optimization. Biocatal. Agric. Biotechnol. (2014), http://dx.doi.org/10.1016/j.bcab.2014.03.005i
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model terms are significant. In this case B, C, AC, BC, A2, B2 and C2 are significant model terms. The ANOVA for nutrient, SM1 and SM2 media have been represented in Tables 4–6. The coefficients of correlations obtained are 0.9977, 0.9978 and 0.9983 for nutrient medium, SM1 and SM2 respectively. On the basis of ANOVA results obtained, pH and time has been found to have significant effects on enzyme activity in LB and nutrient media, whereas in SM1 and SM2 media, temperature, pH and time play significant role on enzyme activity. 3.2. Combined effect of temperature, pH and time on enzyme production 3.2.1. Using LB medium Fig. 2 shows the combined effect of temperature and pH on enzyme activity at a time period of 84 h in LB medium. It has been observed that with increase in temperature up to 75 1C, the enzyme activity increases and then decreases. The increase in Table 5 ANOVA for enzyme production in SM1 medium. Source
Sum of squares
Model A B C AB AC BC A2 B2 C2 Residual Lack of fit Pure error Cor total R2 2 Radj R2pred
9.918 0.237 2.469 0.109 0.205 0.322 0.359 3.887 0.500 1.299 0.022 0.022 0 9.939
Mean square
F value
Prob4 F
Remarks
9 1 1 1 1 1 1 1 1 1 7 3
1.102 0.237 2.469 0.109 0.205 0.322 0.359 3.887 0.500 1.299 0.003 0.007
357.962 76.992 801.907 35.498 66.660 104.616 116.552 1262.804 162.441 421.866
o 0.0001 o 0.0001 o 0.0001 0.0006 o 0.0001 o 0.0001 o 0.0001 o 0.0001 o 0.0001 o 0.0001
Significant Significant Significant Significant Significant Significant Significant Significant Significant Significant
4
0
Degree of freedom
Fig. 2. Combined effect of time and temperature on enzyme production at a pH of 7.75.
16 0.997832 0.995044 0.965311
Table 6 ANOVA for enzyme production in SM2 medium. Source
Sum of squares
Model A B C AB AC BC A2 B2 C2 Residual Lack of fit Pure error Cor total R2 2 Radj R2pred
8.992 0.240 2.534 0.379 0.257 0.286 0.288 3.080 0.274 1.243 0.015 0.015 0 9.007
Mean square
F value
Prob4 F
Remarks
9 1 1 1 1 1 1 1 1 1 7 3
0.999 0.240 2.534 0.379 0.257 0.286 0.288 3.080 0.274 1.243 0.002 0.005
470.503 112.911 1193.018 178.416 120.805 134.782 135.539 1450.268 128.927 585.143
o 0.0001 o 0.0001 o 0.0001 o 0.0001 o 0.0001 o 0.0001 o 0.0001 o 0.0001 o 0.0001 o 0.0001
Significant Significant Significant Significant Significant Significant Significant Significant Significant Significant
4
0
Degree of freedom
16 0.99835 0.996228 0.973594
Fig. 3. Combined effect of time and pH on enzyme production at a temperature of 70 1C.
enzyme activity may be due to the metabolic process adopted in hot spring environment. Beyond 75 1C, the enzyme activity decreases due to the changes in cell envelope. Also modification in the surface protein layer can be induced by different levels of oxygen. Therefore, incubation temperature might affect the cell membrane of A. faecalis SSB-17 by changing the dissolved oxygen. Simultaneously, with increase in pH the enzyme activity decreases. The decline in enzyme activity may be due to reversible reaction that involves ionization or deionization of acidic or basic groups in the active center of the enzyme protein. Irreversible inactivation of the enzyme was particularly at the lower and higher ranges of acidic and alkaline condition. Fig. 3 shows the combined effect of time and temperature on enzyme activity at a pH 7.75 in LB medium. It has been observed that with increase in time up to 93 h the enzyme activity increases and then decreases. The increase in enzyme activity is due to the log phase in growth kinetics of the microorganisms. The decrease in enzyme activity beyond 99 h is due to the decline phase of the microorganisms and
Please cite this article as: Sen, S.K., et al., Thermostable alpha-amylase enzyme production from hot spring isolates Alcaligenes faecalis SSB17 – Statistical optimization. Biocatal. Agric. Biotechnol. (2014), http://dx.doi.org/10.1016/j.bcab.2014.03.005i
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unavailability of the substrate. Similarly, Fig. 4 (the three dimensional response surface), represents the combined effect of time and pH on the enzyme activity at a temperature of 70 1C in LB medium. The reasons for the effect of time and pH on the enzyme activity has been described above. A maximum enzyme activity of 3.858 U/ml was found in LB medium.
3.2.2. Using nutrient medium Fig. 5 shows the combined effect of temperature and pH on enzyme activity at a time period of 84 h in nutrient medium. It has been observed that with increase in temperature up to 75 1C, the enzyme activity increases and then decreases. The reason for increase and decrease in enzyme activity with respect to the temperature is similar to LB medium. Fig. 6 depicts the combined effect of time and temperature on enzyme activity at a pH 7.75 in
Fig. 6. Combined effect of time and pH on enzyme production in nutrient medium at a temperature of 70 1C.
Fig. 4. Combined effect of temperature and pH on enzyme production at a time period of 84 h.
Fig. 7. Combined effect of temperature and pH on enzyme production using SM1 medium at a time period of 84 h.
Fig. 5. Combined effect of time and temperature on enzyme production at a pH of 7.75.
nutrient medium. It has been observed that with increase in time up to 92 h the enzyme activity increases and then decreases. The increase in enzyme activity is due to the log phase in growth kinetics of the microorganisms. The decrease in enzyme activity beyond 92 h is due to decline phase of the microorganisms and unavailability of substrate. It has been observed that the microorganisms can sustain up to 99 h in LB medium whereas in nutrient medium it can sustain up to 92 h. This may be due to the presence of different carbon and nitrogen sources. Similarly, Fig. 7 (the three dimensional response surface), represents the combined effect of time and pH on the enzyme activity at a temperature of 70 1C in nutrient medium. It has been observed that the enzyme activity increases up to pH 8, which may be due to the binding of enzyme with the substrate or ionization of the substrate. The decline in enzyme activity beyond pH 8 may be due to reversible reaction that involves ionization or deionization of
Please cite this article as: Sen, S.K., et al., Thermostable alpha-amylase enzyme production from hot spring isolates Alcaligenes faecalis SSB17 – Statistical optimization. Biocatal. Agric. Biotechnol. (2014), http://dx.doi.org/10.1016/j.bcab.2014.03.005i
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3.2.3. Using SM1 medium Fig. 8 (the three dimensional response plot), shows the combined effect of temperature and pH on enzyme activity at a time period of 84 h in SM1 medium. It has been observed that with increase in temperature up to 75 1C, the enzyme activity increases and then decreases. The reason for increase and decrease in enzyme activity with respect to temperature is similar to LB and
nutrient medium. Fig. 9 (the three dimensionless response plot), shows the combined effect of time and temperature on enzyme activity at a pH 7.75 in SM1 medium. It has been observed that with increase in time up to 84 h the enzyme activity increases and then decreases. The increase in enzyme activity is due to the log phase in growth kinetics of the microorganisms. The decrease in enzyme activity beyond 84 h is due to the decline phase of microorganisms and unavailability of substrate. It has been observed that the microorganisms can sustain up to 84 h in SM1 medium i.e. less than the LB and nutrient media. Similarly, Fig. 10 (the three dimensional response surface), represents the combined effect of time and pH on enzyme activity at a temperature of 70 1C in SM1 medium. It has been observed that the enzyme activity increases up to pH of 7.7 and then decreases. The tolerance pH level of A. faecalis SSB-17 lies between nutrient and LB media.
Fig. 8. Combined effect of time and temperature on enzyme production in SM1 medium at a pH of 7.75.
Fig. 10. Combined effect of temperature and pH on enzyme production in SM2 medium at a time period of 84 h.
Fig. 9. Combined effect of time and pH on enzyme production in SM1 medium at a temperature of 70 1C.
Fig. 11. Combined effect of time and temperature on enzyme production in SM2 medium at a pH of 7.75.
acidic or basic groups in the active center of the enzyme protein. Irreversible inactivation of the enzyme was particularly at the lower and higher ranges of acidic and alkaline condition. The tolerance pH level of A. faecalis SSB-17 is more in nutrient medium as compared to LB medium, which may be due to more ionization and deionization in nutrient medium. A maximum enzyme activity of 4.125 U/ml was found in nutrient medium.
Please cite this article as: Sen, S.K., et al., Thermostable alpha-amylase enzyme production from hot spring isolates Alcaligenes faecalis SSB17 – Statistical optimization. Biocatal. Agric. Biotechnol. (2014), http://dx.doi.org/10.1016/j.bcab.2014.03.005i
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A maximum enzyme activity of 2.145 U/ml was found in SM1 medium. 3.2.4. Using SM2 medium Fig. 11 shows the combined effect of temperature and pH on enzyme activity at a time period of 84 h in SM2 medium. It has been observed that with increase in temperature up to 75 1C, the enzyme activity increases and then decreases. The reason for increase and decrease in enzyme activity with respect to temperature is similar to other media, which has been explained in earlier sections. Fig. 12 depicts the combined effect of time and temperature on enzyme activity at pH 7.75 in SM2 medium. It has been observed that with increase in time up to 89h the enzyme activity increases and then decreases. The increase in enzyme activity was due to the log phase in growth kinetics of the microorganisms. The decrease in enzyme activity beyond 89h was due to the decline phase of the microorganisms and unavailability of substrate. It has been observed that the time period up to
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which the microorganism can sustain is more than SM1 medium but less than that of LB and nutrient media. Similarly, Fig. 13 (the three dimensional response surface), represents the combined effect of time and pH on the enzyme activity at a temperature of 70 1C in SM2 medium. It has been found that the enzyme activity increases up to pH 7.7 and then decreases. The tolerant pH level of A. faecalis SSB-17 is similar to SM1 medium, whereas it is less than that of LB and nutrient media. A maximum enzyme activity of 2.187 U/ml was found in SM2 medium. 3.3. Optimization by response surface modeling One of the main aims of this study was to find the optimum process parameters to maximize the enzyme activity from the mathematical model equations developed in this study. The quadratic model equations have been optimized using quadratic programming (QP) to maximize enzyme activity within the experimental range studied. The optimum regions on the temperature,
Fig. 12. Combined effect of time and pH on enzyme production in SM2 medium at a temperature of 70 1C.
Fig. 14. Optimization region of pH and temperature for enzyme production using nutrient medium at 84 h.
Fig. 13. Optimization region of pH and temperature for enzyme production using LB medium at 84 h.
Fig. 15. Optimization region of pH and temperature for enzyme production using SM1 medium at 84 h.
Please cite this article as: Sen, S.K., et al., Thermostable alpha-amylase enzyme production from hot spring isolates Alcaligenes faecalis SSB17 – Statistical optimization. Biocatal. Agric. Biotechnol. (2014), http://dx.doi.org/10.1016/j.bcab.2014.03.005i
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time and pH for enzyme activity are shown in Figs. 14–17 for LB, nutrient, SM1 and SM2 media respectively. The optimum production factors for enzyme activity by using different media has been
presented in Table 7. It has been observed from Table 7 that nutrient medium is suitable for enzyme activity from A. faecalis SSB-17. The optimized conditions (Table 7 and Fig. 15) are temperature, 70 1C; pH, 7.57; and time, 84 h with a maximum enzyme activity of 4.125 U/ml in nutrient medium.
3.4. Partial purification of alpha amylase The highest enzyme yield has been obtained by precipitating the protein at 80% saturation of ammonium sulfate (Fig. 17A). The saturated protein has been first purified by ion exchange chromatography followed by gel filtration using a Sephadex-G75 column to gain 38.89 mg total protein. Gel filtration led to 59.73% recovery of the purified amylase protein with a specific activity of 5.33 U/mg. SDS-PAGE of the purified enzyme has shown
Table 7 Optimized conditions for enzyme production in different medium.
Fig. 16. Optimization region of pH and temperature for enzyme production using SM2 medium at 84 h.
Medium
Temperature (1C)
pH
Time (h)
Predicted
Observed
LB Nutrient SM1 SM2
70 70 70 74.39
6.5 7.57 6.56 6.75
96 84 96 90.42
3.753 4.125 2.183 2.322
3.858 4.125 2.145 2.187
Fig. 17. (A) SDS-PAGE of partially purified protein following precipitation at different percentage saturations of ammonium sulfate. Lane 1: Standard protein markers; Lane 2: 60% ammonium sulfate; Lane 3: 70% ammonium sulfate; Lane 4: 80% ammonium sulfate. (B) SDS-PAGE of the purified amylase from Alcaligenes faecalis SSB17. Lane 1: ladder marker; Lane 2: crude enzyme extract; Lane 3: enzyme isolation after chromatography by DEAE-Sepharose; Lane 4: enzyme isolation after chromatography by sephadexG75. (C) Native-PAGE of purified enzyme. Lane 1: ladder marker; Lane 2: purified enzyme. Protein Marker cat. no. H-623110475001730.
Please cite this article as: Sen, S.K., et al., Thermostable alpha-amylase enzyme production from hot spring isolates Alcaligenes faecalis SSB17 – Statistical optimization. Biocatal. Agric. Biotechnol. (2014), http://dx.doi.org/10.1016/j.bcab.2014.03.005i
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the presence of a single band associated with amylase enzyme, having a molecular weight of 52 kDa (Fig. 17).
4. Conclusion In this study, four different media have been used for enzyme activity from A. faecalis SSB-17. Response surface methodology (RSM) based BBD and QP has been used to model and optimize the influence of three process parameters on enzyme activity in the four different media. These three process parameters are temperature, pH and time. Mathematical model equations have been derived for enzyme activity by using sets of experimental data and ANOVA. Three-dimensional response surface plots, which are simulated from the models, are presented to describe the effect of the process variables on enzyme activity. Predicted values obtained using the model equations have been in very good agreement with the observed values. Taking advantage of the QP, temperature as 70 1C, pH as 7.75 and time as 84 h has been determined as optimum levels in nutrient medium of the process parameters to achieve the maximum enzyme activity of 4.125 U/ml, similar to maximum enzyme activity in the tests conducted. The results in this paper indicate that optimization by using RSM, BBD and QP can be useful in improving the enzyme activity from A. faecalis SSB-17. Simultaneously, SDS-PAGE of the purified enzyme has shown the presence of a single band associated with the amylase enzyme, having molecular weight of 52 kDa.
Acknowledgment The authors show deep gratitude to the management of GIET, Gunupur-765022, for their constant motivation along with all facilities and requisite support for completion of this work.
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Please cite this article as: Sen, S.K., et al., Thermostable alpha-amylase enzyme production from hot spring isolates Alcaligenes faecalis SSB17 – Statistical optimization. Biocatal. Agric. Biotechnol. (2014), http://dx.doi.org/10.1016/j.bcab.2014.03.005i