Optimization Of Extra Cellular Peroxidase Production Biology Essay

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A response surface methodology was used for the optimization of extra cellular laccase production using Pleurotus sp. Central composite experimental design was applied in the analysis of results and this procedure required limited number of experiments performed while providing possible interactions of selected components. Optimum values of tested variables for the maximum laccase production were; mannitol 4.8gm/l, beef extract 3gm/l and pH 6.2 and copper sulphate 4 mg/l, the maximum laccase production was 90.861U/ml. Only 27 experiments were attained this optimum conditions for enzyme production and the coefficient of determination was 89.0%. In the present study, we have demonstrated that the use of central composite factorial design for high yield of enzymes.

Key words ABTS, Pleurotus sp., Laccase, Response surface methodology

Introduction:

Lignin and cellulose are both rather rigid organic polymers (Tuor et al., 1995), which have developed during evolution for construction and preservation purposes (Call & Mücke, 1997). The degradation of lignin in the pulping and bleaching processes is essential for the manufacturing of paper products. These compounds have to be exposed to harsh physiochemical conditions to modify or degrade their structure for utilization in the pulp and paper industry (Coll et al., 1993). The problems caused by chemicals used in bleaching forced industry to consider alternative, more environmental friendly methods (Yang & Eriksson, 1992). Such a biological alternative to traditional bleaching was provided through the discovery of oxidative enzymes (Poppius-Levlin et al., 1997). Laccase is a polyphenol oxidase that contains four coppers, and is able to oxidize its substrates by using molecular oxygen as an electron acceptor. Laccase can be found in plants, insects and bacteria, but its major sources from fungi. Fungi associated with many biological functions such as lignin degradation, removal of potentially toxic phenols in addition to paper industry (Argyero Poulos, D.S., 2001.). The oxidative enzymes can be used for biodecolorization and detoxification of industrial effluent waste water (Feng Xu, 2005). Laccase and peroxidase enxymes are generally produced by submerged fermentation in commercial practice; the medium composition play a significant role in the enzyme production. Research efforts have been pointed towards evaluating the effect of various organic and inorganic nutrients, metal ions, pH, temperature, aeration, and agitation on the yield of enzymes. From the conventional method the following parameters were selected for the Response Surface Methodological optimization. Mannitol, beef extract, pH and ferrous sulphate were found to be important factors in enhancing the laccase production. The conventional method of optimization involves varying one parameter at a time and keeping the others are invariant.

Response surface methodology (RSM) is a simple model to analyze the effect of various factors influencing the responses by varying them simultaneously. Carbon and nitrogen sources have been promised to play a significant role in enhancing the production of fungal laccase. The central composite design used to analyze the interaction effects of variables on production of laccase enzymes (Fannin et al., 1981;Deshayes 1980; Matthews et al., 1981) (Box and Wilson 1951; Cochran and Cox, 1957; Box et al., 1978; Akhnazarova and Kafarov, 1982; Khuri and Cornell, 1987; Yee and Blanch, 1993; Mak et al., 1995). Conventional method of optimization involves changing one independent variable at a time (vanillin, glycerol and mineral salt solution) and maintaining all the others at a constant.

Materials and methods

Isolation and identification

Laccase-producing fungi were screened from Dry Evergreen forest of Guindy National Park and IIT Madras, Chennai. Fungi were isolated by placing pieces of unexposed tissue of fruit body on MEA (Malt Extract Agar) and PDB (Potato dextrose Broth) plates containing different indicator compounds. The plates were incubated at 27oC for at least a week and strains were sub cultured when clear positive reactions were visible. Production of laccase was carried out in production medium and these medium were sterilized by autoclaving at 121°C for 15 min. The above medium (50ml in 250ml Erlenmeyer flasks) was inoculated with two mycelial discs (8mm) and maintained at 27°C in a static condition. Fermented broth was filtered in filter paper at 4°C and the supernatant was recovered and used as enzyme source. The range of test variables are given in table 1. The concentration of mannitol, beef extract, pH and ferrous sulphate were varied according to the experimental design (table 2). The pH value of the medium was adjusted before sterilization.

Enzymatic assay

Extra cellular laccase activity of cell free filtrate was assayed spectrophotometrically on 9th day, 10 mM of ABTS as substrates with 100 mM sodium acetate buffer (pH 5.0), 0.1 ml of the culture filtrate (assay for 1ml of reaction mixture) and absorbance was measured at 436 nm. (Mansur et al., 1997). 0.1 ml of distilled water, 0.9 ml of sodium acetate buffer was kept as blank.

Optimization by RSM

Box-Behnken design consists of a group of controlled experimental factors and measured responses, according to one or more selected criteria. A prior knowledge to understanding the process and process variables under investigation are necessary for achieving a more realistic model. Among the different components of the media, carbon, nitrogen, pH and metal ion were the major variables were selected to find optimal conditions for higher enzyme production using Response Surface Methodology. The range of experimental variables was investigated in this study (Table 1). Several experimental design have been selected the Box-Behnken design proposed by Box et al., (1978). For this study, 4 factorial design were employed to fit the second order polynomial model which indicates 27 experiments were required for this procedure. The mid values (zero level) chosen for experimental design comprised mannitol, beef extract, pH and ferrous sulphate. The three significant independent variables X1, X2, X3 and X4 and the mathematical relationship of response Y on these variables can be approximated by quadratic / (Second degree) polynomial equation as shown below:

Y=bo+b1X1+b2X2+b3X3+b4X4+b11X12+b22X22+b33X32+b44X4²+b12X1X2+b13X1X3+b14X1X4+b23X2X3+b34X3X4

Where

Y is the predicted response,

bo is the constant,

b1, b2, b 3 &b4 are the linear co-efficients,

b11, b22, b33 & b44 are the quadratic co-efficients and

b12, b13 , b23,b24& b34 are the cross-product co-efficients. The optimum values of the selected variables were obtained by solving the regression equation (Cornell 1987). In that, the 27 fermentation experiments were conducted in triplicate.

Results and discussion

Pleurous sp. was grown in CDB at different temperatures ranging from 20 and 40˚C at 5°c interval. Maximum production of 44 U/ml was recorded at 25˚C. The temperature above and below 25˚C did not enhance the Laccase production (fig.2). Saravanakumar and Kaviyarasan (2010) studied the optimal parameter of maximum laccase enzyme production was found to be pH 8.0, temperature 25°C, glycerol, vanillin and CuSo4, but the laccase production was decreased at 30°C (Thurston, 1994). In general, the fungi were cultivated at temperatures between 25°C and 30°C for optimal laccase production (Arora & Gill, 2000; Fahreus & Reinhammar, 1967; Pointing et al., 2000; Vasconcelos et al., 2000). When the temperatures higher than 30°C the activity of ligninolytic enzymes was reduced (Zadrazil et al., 1999).

The pH showed a significant influence on the production of extra cellular Laccase, the test fungus produced Laccase between the pH of 5.0 to 9.0. Maximum Laccase production of 94.3 and 94.0 U/ml was recorded at pH 5.5 and 7.5 respectively, and the moderate activity was observed in pH 9.0 and declined (fig.1). The optimal pH for laccase production was found to be at pH 6.5 in submerged culture of Chaetomium globosum (El-Zayat, 2008). The laccase production was 25-fold higher in Botryosphaeria rhodina showed a significant effect with increased pH of 3.5 - 7.5 for both induced and noninduced cultures (Dekker et al., 2007). Among the different carbon sources tested namely Glucose, Sucrose, Mannitol, Maltose, Glycerol and Fructose at 1% concentration, the level of Laccase production was maximum at 161.1 U/ml, in mannitol amended medium. The enzyme production of 149 U/ml and 90.9 U/ml was recorded with Fructose and Glycerol on 15th day of incubation. The carbon sources like glucose and maltose showed decreased effect on Laccase production from pleurotus sp., (fig.3). (Dekker et al., 2007)

Fig.1

Fig.2

Fig. 3

Churapa Teerapatsakul et al., (2007) showed that Ganoderma sp. produced maximum laccase activity in the presence of glycerol as a carbon source in liquid medium. In addition, Rodriguez Couto et al.,(2006) reported glycerol as a sole carbon source in Trametes hirsuta, which showed a maximum laccase activity of 19,400 U/L, which was reported the highest from the fungus. Pleurotus sp. produced maximum laccase activity when beef extract was sole nitrogen source (114 U/ml) as shown in fig.4. However, most of the fungal laccases were stimulated by organic nitrogen than inorganic nitrogen source. Kirk and Farrell 1987, Higuchi 1990, Cullen 1997) reported Laccase and other ligninolytic enzyme activity was increased due to carbon and organic nitrogen. Saravanakumar and Kaviyarasan (2010) reported maximum laccase production (84 U/ml) by using vanillin. Monteiro and De Carvalho (1998) reported high laccase activity with semi-continuous production in shake-flasks using a low carbon to nitrogen ratio (7: 8 g.g). Buswell et al., (1995) found that laccases were produced at high nitrogen concentrations, although it is generally accepted that a high carbon to nitrogen ratio is required for laccase production. Laccase was also produced earlier when the fungus was cultivated in a substrate with a high nitrogen concentration and these changes did not reflect differences in biomass. Heinzkill et al., (1998) also reported a higher yield of laccase using nitrogen rich media rather than nitrogen limited media usually employed for production of oxido reductase.

Fig.4

Response surface methodology (RSM)

A response surface methodology allowed calculation of maximum production based on a few sets of experiments in which all the factors were varied within chosen ranges. This method has been successfully applied in the optimization of medium compositions (Lee, S.L. and W.C. Chen, 1997) conditions of enzymatic hydrolysis (A.Y.M. Ma and B. Ooraikul, 1986) and fermentation processes (Rosi et al., (1987) and Sonia (2005). In optimizing the effect of carbon and nitrogen sources on laccase production from Pleurotus sp., 4 factorial designs were applied using mannitol, peptone, pH and metal ion. Box-Behnken design aims to select most important variables in the system that influence over all enzyme productivity. Each variable varies for a desired response represented at high and low levels. Generally calculated F values should be several times more than tabulated value, if the model is a good prediction of experimental results and estimated factors effects are real. Also high F value and a very low probability (P> F = 0.0001) indicate that present model is in a good prediction of experimental results. The F value of model implies that model is significant. (Akhnazarova and Kafarov, 1982; Cornell, 1987). The goodness of fit was checked by determination coefficient (R2), and value of the determination coefficient (R2 = 89.5%) indicates that only 10.5% was not explained by the model. The adjusted coefficient (Adj. R2 = 75 %) was also very high, which indicates a high significance of the experiment (Box and Wilson 1951; Cochran and Cox 1957; Akhnazarova and Kafarov 1982; Khuri and Cornell 1987; Yee and Blanch 1993; Mak et al., 1995). Box et al., 1978 reported a higher value of the correlation coefficient (R = 98.1%) signifies an excellent correlation between the independent variables (Box and Wilson 1951; Cochran and Cox 1957; khnazarova and Kafarov 1982; Yee and Blanch 1993; Mak et al., 1995). The application of Response Surface Methodology (Box and Wilson 1951; Khuri and Cornell 1987; Mak et al., 1995) was yielded higher enzyme production. The logarithmic values of enzyme yields and test variables in uncoded unit as follows:

Y=50.33+b1(-3.44)+b2(1.22)+b3(16.29)+b4(-3.44)+b11(-0.95)+b22(-14.23)+b33(-12.27)+b12 (-3.44)(1.24)+b13(-3.44)(16.29)+b23(1.24)(16.29)+b14(-3.44)(-3.44)+b24(16.29)+(-3.44)

The enzyme concentrations expressed in logarithmic values, and X1, X2, X3 and X4 were the coded values of test variables (mannitol, beef extract, pH and copper sulphate respectively). The significance of each coefficient was determined by t- value and p values (Table 2). The larger t- value and smaller the p- value indicates the significance of the model. This implies the quadratic main effects of vanillin, glycerol and mineral salt solution of the medium are more significant (Akhnazarova and Kafarov 1982; Khuri and Cornell 1987). The carbon and nitrogen source support the maximum enzyme activity and their respective P-values were P X1 2 > 0.021, P X2 2 < 0.166 and P X3 2 <0.022. The mannitol and beef extract have a direct relationship on the production of the enzyme. From the model each observed values (Y f (0) was compared with the predicted values (Y f (P) (table 2). Perturbation plot is an important diagrammatic representation to compare effect of all variable at a particular point in design space; real benefits from this plot were selecting axes and constants in wire frame. Response surface plots showed two variables at a time and maintaining others were fixed level, it was more helpful to understanding the interaction effects of these two factors. A circle in the square shows that response is sensitive to that factor (fig.5,8,9,10). A relatively other showed insensitiveness to the enzyme yields (fig.6,7). If there are more than two factors,

Table.1 Observed responses and predicted values

S.No

Mannitol

Beef extract

pH

Ferous sulphate

Peroxidase Yield (U/ml)

Residual value

Observed Value

Predictedvalue

1

1

1

6.0

0.00275

33.3

28.1333

5.1667

2

3

1

6.0

0.00275

10.7

23.1500

-12.4500

3

1

3

6.0

0.00275

37.5

32.5167

4.9833

4

3

3

6.0

0.00275

11.1

23.7333

-12.6333

5

2

2

3.5

0.00050

10.7

14.3333

-3.6333

6

2

2

8.5

0.00050

25.1

36.4667

-11.3667

7

2

2

3.5

0.00500

0.9

-3.0000

3.9000

8

2

2

8.5

0.00500

36.2

40.0333

-3.8333

9

1

2

3.5

0.00275

1.7

16.0833

-14.3833

10

3

2

3.5

0.00275

1.4

-0.5500

1.9500

11

1

2

8.5

0.00275

36.5

38.9167

-2.4167

12

3

2

8.5

0.00275

55.7

41.7833

13.9167

13

2

1

6.0

0.00050

21.6

14.9333

6.6667

14

2

3

6.0

0.00050

60.7

41.5167

19.1833

15

2

1

6.0

0.00500

12.5

32.1500

-19.6500

16

2

3

6.0

0.00500

3.4

10.5333

-7.1333

17

1

2

6.0

0.00050

34.9

40.9667

-6.0667

18

3

2

6.0

0.00050

20.7

25.4833

-4.7833

19

1

2

6.0

0.00500

38.2

25.4833

12.7167

20

3

2

6.0

0.00500

41.2

27.2000

14.0000

21

2

1

3.5

0.00275

1.5

-10.7500

12.2500

22

2

3

3.5

0.00275

16.2

16.2833

-0.0833

23

2

1

8.5

0.00275

54.4

46.3833

8.0167

24

2

3

8.5

0.00275

20.0

24.3167

-4.3167

25

2

2

6.0

0.00275

24.6

50.3333

-25.7333

26

2

2

6.0

0.00275

56.5

50.3333

6.1667

27

2

2

6.0

0.00275

69.9

50.3333

19.5667

Table.2 Model coefficients estimated by multiples linear regression

Coefficient

t- value

p- value

Constant

50.33

5.082

0.000

X1 (C)

-3.44

-0.695

0.500

X2 (N)

1.24

0.251

0.806

X3(pH)

16.29

3.290

0.006

X4(M)

-3.44

-0.695

0.500

X11(C+C)

-9.22

-1.242

0.238

X22(N+N)

-14.23

-1.915

0.080

X33 (pH+pH)

-17.05

-2.295

0.041

X44(M+M)

-11.32

-1.525

0.153

X12 (C+N

-0.95

-0.111

0.914

X13 (C+pH)

4.88

0.568

0.580

X14 (C+M

4.30

0.501

0.625

X23 (B+pH)

-12.27

-1.431

0.178

X24 (B+M)

-12.05

-1.405

0.185

X34 (pH+M)

5.23

0.609

0.554

Table.3 Analysis of variance (ANOVA) for the factorial design

Source of variation

Sum of squares

Degree of freedom

Mean square

F- value

Probe (P)

>F

Regression

7023

14

501.7

1.70

0.180

Residual error

1465

12

3532

Total

10555

26

R= 89%; Adjusted R2= 75%

Fig.5

Fig.6

Fig.7

Fig.8

Fig.9

Fig.10

perturbation plot could be used to find effect of variables on enzyme production. These influential factors are good choices for axes on counter plots and can be easily obtained by calculating from model. The yield values of different variables can also predicated from the respective response surface plots (fig. 5 to 10). The laccase production was predominantly influenced by mannitol and peptone. Mannitol and peptone are therefore the key factors which control the biosynthesis of laccase enzyme. At lower concentration of beef extract as well as higher metal ion may not cause inhibition of enzyme synthesis. (Ikehata et al., 2004; Sakurai et al., 2002; Ragalski et al., 2006; Stajic et al., 2006). The regression equation solve the optimal values of test variables in uncoded units and the values were beef extract 4.8 gm/l, mannitol 3gm/l, pH 6.2 and copper sulphate 4mg/l. Monteiro and De Carvalho (1998) reported high laccase activity with semi-continuous production in shake-flasks using a low carbon to nitrogen ratio (7: 8 g.g). Buswell et al., (1995) found that laccases were produced at high nitrogen concentrations, although it is generally accepted that a high carbon to nitrogen ratio is required for laccase production. This model predicts maximum production of enzyme that can be obtained by using the above RSM and the production was increased up to 2-3 folds.

Conclusion

Box- Behnken experimental design for process optimization involves a study of specific region of individual factors. Yield of laccase increased by supplementation of medium. In this study, response surface analysis and central composite design were used for optimizing culture media for maximizing laccase production by using Pleurotus sp. in submerged fermentation. The optimized fermentation medium composition increased 2 to 3 fold of enzyme production.

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