Statistical Evaluation of Medium Components by PlackettBurman method for Laccase from Pseudomonas aeruginosa ADN04 using Submerged Fermentation
Arunkumar.T^{1*}, Narendrakumar.G^{2}, Alex Anand.D^{3}
^{1}Department of Bioinformatics, Sathyabama University, Chennai – 600119
^{2}Department of Biotechnology, Sathyabama University, Chennai – 600119
^{3}Department of Biomedical Engineering, Sathyabama University, Chennai – 600119
*Corresponding Author Email: t.arunkumar.t@gmail.com
ABSTRACT:
The effect of medium components on laccase production from using Pseudomonas aeruginosa ADN04 was studied. Placket Burman design was used to evaluate the significant parameters that have large effect on the fermentation and with the experimental design a successful result was obtained. K_{2}HPO_{4}, NaNO_{3, }CaCl_{2, }NH_{4}Cl_{, }CuSO_{4, }NH_{4}H_{2}PO_{4, }ZnSO_{4, }Glucose , Sucrose_{, }Yeast Extract_{,}MgSO_{4, }KH_{2}PO_{4 }was screened for the better media composition. Sucrose, K_{2}HPO_{4}, NH_{4}Cl, Yeast Extract, CaCl_{2}, were standardized according to the F values.
KEYWORDS: PlackettBurman Design (PBD), Laccase, submerged fermentation
INTRODUCTION:
PBD, an efficient way to identify the important factors among a large number of variables, was used in the present study to screen the important variables that significantly influenced laccase production. In this study, a 12run PlackettBurman design was applied to asses eleven factors (including two variables that were kept as dummy)^{ 14}. Each variable was observed at two levels: –1 for the low level and +1 for the high level. It illustrated the variables and their corresponding levels used in the experimental design. The values of two levels were set according to our preceding initial experimental results.
PlackettBurman designs are substitute to fractional factorials for selection. One beneficial characteristic is that the sample size is a multiple of four rather than power of two. There are no twolevel fractional factorial designs with sample sizes between 16 and 32 runs. However, there are twenty run, twentyfourrun, and twentyeightrun PlackettBurman designs^{58}.The main effects are orthogonal and twofactor interactions are puzzled with main effects. This is dissimilar from resolution of three fractional where two factor interactions are indistinguishable from main effects.
MATERIALS AND METHOD:
Bacterial Culture:
Pseudomonas aeruginosa ADN04 (bacterial culture) was isolated, identified biochemically and 16S rRNA sequencing^{9}. The isolated pure culture was preserved in nutrient agar slants at 4°C in Department of Biotechnology, Sathyabama University. All the experimental analysis was executed using these strains.
PlackettBurman design:
Differenet variables were identified to have influence on the production of laccase. But the selection of the variable are perform statisically using PlackettBurman design using JMP 10 –version 17. The difference between the average of H ( high ) and L ( low ) responses for each independent and dummy variable.
Different chemical componets were assessed using this method, K_{2}HPO_{4}, NaNO_{3}, CaCl_{2}, NH_{4}Cl, CuSo_{4, }NH_{4}H_{2}PO_{4, }ZnSO_{4, }Glucose, Sucrose,Yeast Extract, MgSO_{4}, KH_{2}PO_{4 }(Table1).
ZnSO_{4} and CuSO_{4} were used as dummy variable and other components were used to analyse the effect on the enzyme production. The design of experiment was proposed using JMP10 and the analysis was performed accordingly. On the basis of the response (enzyme activity) the Fisher value (Fvalue) was calculated.(Fisher value determines the selection of variables, higher the value more the interaction).
RESULT AND DISCUSSION:
The organism was isolated from the soil sample (Harur forest, Tamilnadu), was preserved as pure culture in the Department of Biotechnology, Sathyabama University, Chennai. The media which was optimized by Arunkumar et al., 2014 was used to as Fermentation media. After incubation, the culture was centrifuged and the supernatant was used for purification.
Table 1:PB Design Screening of media using Plackett Burman (B Design) (Plackett RL, Burman JP, 1946) (JMP10)
K_{2}HPO_{4} 
NaNO_{3} 
CaCl_{2} 
NH_{4}Cl 
CuSo_{4} 
NH_{4}H_{2}PO_{4} 
ZnSO_{4} 
Glucose 
Sucrose 
Yeast Extract 
MgSO_{4} 
KH_{2}PO_{4} 
Response 

1 
H 
H 
H 
H 
L 
H 
L 
H 
H 
L 
L 
H 
43.2 
2 
H 
H 
H 
L 
H 
L 
H 
H 
L 
L 
H 
L 
38.1 
3 
H 
H 
L 
H 
L 
H 
H 
L 
L 
H 
L 
L 
41.2 
4 
H 
L 
H 
L 
H 
H 
L 
L 
H 
L 
L 
L 
28.6 
5 
L 
H 
L 
H 
H 
L 
L 
H 
L 
L 
L 
H 
53.1 
6 
H 
L 
H 
H 
L 
L 
H 
L 
L 
L 
H 
H 
40.2 
7 
L 
H 
H 
L 
L 
H 
L 
L 
L 
H 
H 
H 
23.5 
8 
H 
H 
L 
L 
H 
L 
L 
L 
H 
H 
H 
H 
41.2 
9 
H 
L 
L 
H 
L 
L 
L 
H 
H 
H 
H 
L 
31.25 
10 
L 
L 
H 
L 
L 
L 
H 
H 
H 
H 
L 
H 
40.95 
11 
L 
H 
L 
L 
L 
H 
H 
H 
H 
L 
H 
L 
21.5 
12 
H 
L 
L 
L 
H 
H 
H 
H 
L 
H 
L 
H 
38.74 
13 
L 
L 
L 
H 
H 
H 
H 
L 
H 
L 
H 
H 
37.2 
14 
L 
L 
H 
H 
H 
H 
L 
H 
L 
H 
H 
L 
25.4 
15 
L 
H 
H 
H 
H 
L 
H 
L 
H 
H 
L 
L 
39.4 
16 
L 
L 
L 
L 
L 
L 
L 
L 
L 
L 
L 
L 
15.2 
L – Low , H High
Table 2: Statistical analysis of Plackett Burman design for the production of laccase using Ps.aeruginosa ADN04
Component 
Lower Level 
Higher Level 
Main Effect 
F Value 
K_{2}HPO_{4} 
1 
5 
267.2672 
1.3012933 
NaNO_{3} 
2 
10 
238.27445 
1.1601309 
CaCl_{2} 
1 
5 
0.0002 
9.738E07 
NH_{4}Cl 
1 
4 
498.6482 
2.4278608 
CuSO_{4} 
0.001 
0.001 
250.20845 
1.2182362 
NH_{4}H_{2}PO_{4} 
0.1 
0.9 
20.60045 
0.09767006 
ZnSO_{4} 
0.01 
0.01 
160.5632 
0.7817638 
Glucose 
1 
3 
82.81845 
0.4032335 
Sucrose 
5 
10 
7.72245 
0.0375997 
Yeast Extract 
5 
10 
2.57645 
0.0125444 
MgSO4 
0.2 
1 
220.9202 
1.0756351 
KH_{2}PO_{4} 
1 
5 
149.6192 
0.6498098 
Table2 express the interaction of variables represented by Fvalue. Higher the value more the influence. Sucrose, K_{2}HPO_{4}, NH_{4}Cl, Yeast Extract, CaCl_{2}On the basis of PB design, the high influencing components were selected for further analysis.
Fig. 1: Curve fitting between the actual and predicted value
The curve fitting between the Actual and the predicted values shows the R2 value to be 97.283 that shows the significance of the reaction performed (Figure 1).
Table 3:Summary of Fit
R^{2} 
0.972833 
R^{2} Adj 
0.949632 
Root Mean Square Error 
7.023172 
Mean of Response 
34.667 
Observations (or Sum Wgts) 
20 
Table3 and Table4express the fit of the model as R2 value is 97.2% corresponding to the Adj. R2 value of 94.9%. The values justify that the results given by the experimental analysis and the report generated by the software was relevant.
Table 4: Analysis of Variance
Source 
DF 
Sum of Squares 
Mean Square 
F Ratio 
Model 
12 
1357.5402 
113.128 
2.2935 
Error 
7 
345.2747 
49.325 
Prob > F 
C. Total 
19 
1702.8148 

0.1386 
Table 5: Parameter Estimates
Term 
Estimate 
Std Error 
t Ratio 
Prob>t 
Intercept 
34.667 
1.570429 
22.07 
<.0001* 
K_{2}HPO_{4}[1] 
4.843 
1.570429 
3.08 
0.0177* 
NaNO_{3}[2] 
1.138 
1.570429 
0.72 
0.4922 
CaCl_{2}[1] 
1.482 
1.570429 
0.94 
0.3768 
NH_{4}Cl[1] 
2.192 
1.570429 
1.40 
0.2054 
CuSO_{4}[0.001] 
0.428 
1.570429 
0.27 
0.7931 
NH_{4}H_{2}PO_{4}[0.1] 
1.317 
1.570429 
0.84 
0.4294 
ZnSO_{4}[0.01] 
0.057 
1.570429 
0.04 
0.9721 
Glucose [5] 
1.352 
1.570429 
0.86 
0.4178 
Sucrose[5] 
5.178 
1.570429 
3.30 
0.0132* 
Yeast extract[1] 
2.157 
1.570429 
1.37 
0.2120 
MgSO_{4}[0.2] 
0.938 
1.570429 
0.60 
0.5691 
KH_{2}PO_{4}[1] 
0.182 
1.570429 
0.12 
0.9110 
Table:6 Sorted Parameter Estimates
Term 
Estimate 
Std Error 
t Ratio 
t Ratio 
Prob>t 
Sucrose [5] 
5.178 
1.570429 
3.30 

0.0132* 
K_{2}HPO_{4}[1] 
4.843 
1.570429 
3.08 

0.0177* 
NH_{4}Cl[1] 
2.192 
1.570429 
1.40 

0.0054* 
Yeast Extract [1] 
2.157 
1.570429 
1.37 

0.0120* 
CaCl2[1] 
1.482 
1.570429 
0.94 

0.0037* 
Glucose[5] 
1.352 
1.570429 
0.86 

0.4178 
NH_{4}H_{2}PO_{4}[0.1] 
1.317 
1.570429 
0.84 

0.4294 
NaNO_{3}[2] 
1.138 
1.570429 
0.72 

0.4922 
MgSO_{4}[0.2] 
0.938 
1.570429 
0.60 

0.5691 
CuSO_{4}[0.001] 
0.428 
1.570429 
0.27 

0.7931 
KH_{2}PO_{4}[1] 
0.182 
1.570429 
0.12 

0.9110 
ZnSO_{4}[0.01] 
0.057 
1.570429 
0.04 

0.9721 
Fig.2: Prediction Profiler
Figure 2 summaries the structural prediction of the compound in various composition.
Table 7: Screening for YContrasts
Term 
Contrast 
Plot of tRatio 
Length tRatio 
Individual pValue 
Simultaneous pValue 
Sucrose 
5.17800 

2.62 
0.0257* 
0.2620 
K_{2}HPO_{4} 
4.84300 

2.45 
0.0307* 
0.2967 
NH_{4}Cl 
2.19200 

1.11 
0.2524 
0.9926 
YE 
2.15700 

1.09 
0.2599 
0.9937 
CaCl_{2} 
1.48200 

0.75 
0.4317 
1.0000 
Glucose 
1.35200 

0.68 
0.4720 
1.0000 
NH_{4}H_{2}PO_{4} 
1.31700 

0.67 
0.5299 
1.0000 
NaNO_{3} 
1.13800 

0.58 
0.5899 
1.0000 
MgSO_{4} 
0.93800 

0.47 
0.6543 
1.0000 
CuSO_{4} 
0.42800 

0.22 
0.8337 
1.0000 
KH_{2}PO_{4} 
0.18200 

0.09 
0.9291 
1.0000 
ZnSO_{4} 
0.05700 

0.03 
0.9775 
1.0000 
Sucrose*K_{2}HPO_{4} 
2.75952 

1.40 
0.1622 
0.9207 
Sucrose*NH_{4}Cl 
0.04048 

0.02 
0.9841 
1.0000 
K_{2}HPO_{4}*NH_{4}Cl 
1.10475 

0.56 
0.6003 
1.0000 
Sucrose*YE 
1.90019 

0.96 
0.3160 
0.9993 
K_{2}HPO_{4}*YE 
1.61220 

0.82 
0.3932 
1.0000 
NH_{4}Cl*YE 
1.32031 

0.67 
0.4830 
1.0000 
Sucrose*CaCl_{2} 
0.68814 

0.35 
0.7368 
1.0000 
Fig.3: Half Normal Plot
Length PSE=1.97798Asterisked terms were forced orthogonal. Analysis is order dependent.pValues derived from a simulation of 10000 Lenth t ratios.
Figure 2 and Figure 3 shows the use a normal and half normal probability plot of the effects to evaluate the significance and statistical importance of main and interaction effects from a 2factorial design. The fitted line indicates where you would expect the points to fall if the effects were zero. Significant effects have a label and fall toward the left or right side of the graph.
Table 5, table 6, table 7 states the effective prediction of the interaction of compounds present in the medium by statistical approach. Identifying appropriate components for the medium was a timeconsuming and arduous process involving large number of experiments. The PBD is the basic groundwork technique for fast screening of the effects of different medium constituents. Initial various carbon, nitrogen and salts have been analysed to choose best for the maximum laccase production. PBD was used to assess theimportance of various medium components and to enhance the laccase production in submergefermentation. The variables represent the nutrient components, the independent variables andtheir respective high and low concentration was used in PB optimization study. The maximum laccaseproduction was 232.11 mg/L was obtained in PB optimization study using Pseudomonas aeruginosa. This technique evidenced tobe appreciated in screening enormous number of constituents in production media effectively.
CONCLUSION:
K_{2}HPO_{4}, NaNO_{3}, CaCl_{2}, NH_{4}Cl, CuSO_{4}, NH_{4}H_{2}PO_{4}, ZnSO_{4}, Glucose, Sucrose, Yeast Extract, MgSO_{4}, KH_{2}PO_{4} were selected as the variables and by using Plackett Burman method Sucrose, K_{2}HPO_{4, }KH_{2}PO_{4}, NH_{4}Cl, , CuSO_{4}, NaNO_{3}, MgSO_{4} found to have maximum impact on the production of laccase enzyme.
CONFLICT OF INTEREST:
The authors declare no conflict of interest.
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Received on 20.02.2017 Modified on 11.03.2017
Accepted on 21.03.2017 © RJPT All right reserved
Research J. Pharm. and Tech. 2017; 10(4): 11151119.
DOI: 10.5958/0974360X.2017.00201.3