16s rRNA phylogenetic analysis and sequence comparison
16s rRNA sequence (1681bp) analysis of strain R16C1 was determined using BLAST search engine which showed sequence similarity to many species of genus Enterobacter. A phylogenetic tree (Fig. 1) was constructed using RelTime method. Maximum Likelihood Method was used to calculate divergence times for all branching points in the topology which was based on the Tamura-Nei model. The approximate log likelihood value of the topology given is -7630.0822. The branch lengths were measured in the relative number of substitutions per site and the tree is constructed to scale. 10 nucleotide sequences were used for the analysis. 1st + 2nd + 3rd + noncoding positions were included. All the positions containing missing data and gaps were removed. A total of 1374 positions were there in the final dataset. MEGA6 software was used to conduct evolutionary analysis .The tree generated shows close phylogenetic relation of R16C1 strain with certain other Enterobacter species showing highest sequence homology (93%) to Enterobacter aesburiae. The strain was therefore identified as Enterobacter aesburiae and sequence product was submitted in Genbank database (Accession number MT93543).
Effect of incubation time on asparagnase production
An important criterion for the potency assessment is the time course of L-asparaginase production. The highest peak activity of the enzyme production 9.15 U / ml was attained after 72 hrs of incubation and then decreased (Fig. 2).
Effect of pH on production of L-asparaginase
Growth and production of enzyme are dependent on initial pH of the medium which reduces the lag phase as well as increases the production. Czapekdox media with a pH range of 4, 5, 6, 7, 8, 8.6, 9 and 10 was used. pH 8.6 gave highest enzyme activity of 9.81 U/ml after 72 hrs of incubation. Figure 3 shows enzyme activity studied under different pH conditions.
Effect of incubation temperature
Temperature used for incubation directly effects growth of the bacteria thus affecting enzyme production. A varied range of temperature from 10 to 90 0C was used for the study. Maximum enzyme activity was recorded at 30 0C temperature after an incubation of 72 hrs. Enzyme activity recorded at optimum temperature was 10.22 U/ml represented in Fig. 4
Effect of inoculum size and rpm
Different sizes of inoculum and rpm were used for the study using one variable at a time giving a maximum enzyme activity of 9.72 U/ml at a rpm of 180 and 10.5 U /ml using an inoculum size of 10% (Figs. 5 & 6).
Screening of optimum medium for enzyme production
To optimize suitable media for enzyme production isolated culture was inoculated in 11 different media. Experimental results for the study are shown graphically in Fig. 7. Of all the media used, M9 medium containing maltose showed maximum enzyme activity of 30.62 U/ml.
Effect of asparagine concentration of enzyme production
Media containing different concentrations (0.1–2.5%) of L-asparagine was used in the study. At a concentration of 1.0% of L-asparagine in the culture media, the isolate Enterobacter aesburiae showed maximum L-asparaginase activity and it was found to be 31.22 U/ml (Fig. 8). A pareto chart showing effect of different variables studied on the production of enzyme depicts highest enzyme activity being absorbed using 10% inoculums size and M9 media (Fig. 9).
Analysis of Varaiance
Based on experimental design, 15 combinations were developed (Tables 2 & 3) to obtain asparaginase activity. Obtained experimental data was used for analysis of variance. P-value less than 0.05 indicates the significance of model terms. In this case t, rpm, in (inoculum %), t*t, rpm*rpm, in*in, t*rpm, t*in, rpm*in are significant model. The adequacy of results was analyzed using ANOVA and R2, the determination coefficient. Therefore, a good fit between predicted and observed responses implying the reliability of model can be reflected from the obtained R2value. In case of values ˃0.1 (non-significant model terms), model reduction can be used to improve the model.
Source
|
DF
|
Adj SS
|
Adj MS
|
F-Value
|
P-Value
|
Table 3
ANOVA for response surface cubic model Analysis of Variance
Model
|
9
|
1176.58
|
130.731
|
109.99
|
0.000
|
Linear
|
3
|
49.30
|
16.432
|
13.83
|
0.007
|
rpm
|
1
|
34.94
|
34.945
|
29.40
|
0.003
|
t
|
1
|
14.02
|
14.019
|
11.79
|
0.019
|
in
|
1
|
0.33
|
0.332
|
0.28
|
0.020
|
Square
|
3
|
1024.49
|
341.496
|
287.33
|
0.000
|
rpm*rpm
|
1
|
380.33
|
380.328
|
320.00
|
0.000
|
t*t
|
1
|
417.74
|
417.743
|
351.48
|
0.000
|
in*in
|
1
|
383.90
|
383.897
|
323.00
|
0.000
|
2-Way Interaction
|
3
|
102.80
|
34.265
|
28.83
|
0.001
|
rpm*t
|
1
|
12.50
|
12.496
|
10.51
|
0.023
|
rpm*in
|
1
|
89.40
|
89.397
|
75.22
|
0.000
|
t*in
|
1
|
0.90
|
0.902
|
0.76
|
0.023
|
Error
|
5
|
5.94
|
1.189
|
|
|
Lack-of-Fit
|
3
|
5.85
|
1.950
|
42.65
|
0.023
|
Pure Error
|
2
|
0.09
|
0.046
|
|
|
Total
|
14
|
1182.52
|
|
|
|
Model Summary: R-sq-99.5%, R-sq adj-98.59%, R-sq (Pred)- 92.7% |
Response plots to analyse process variables
Response surface plots enable an excellent understanding of interaction effects as well as main effects of the factors under study. It is easy to obtain plots by calculating the model data predicting response (Y) values against different concentration of the variables. Figure 11a, b & c shows contour plots and response surface plots obtained as a function of rpm, temperature and inoculums against asparaginase activity keeping one variable constant at a time. Final equation obtained in terms of uncoded units is
Regression Equation.
Optimum values
The enzyme activity was predominantly influenced by % inoculum used, rpm and temperature. The contour plots designed showed the region of eligibility for maximum enzyme activity. The point prediction obtained from ANOVA for response surface cubic model for asparaginase activity (40.17 U/ml) is 30 0C, 180 rpm and 10% inoculum size.
Plate assay method was used to detect L-asparaginase activity of isolated culture. A pink colored zone formed around the culture growth in nutrient plate containing phenol red indicator and 1% asparagine indicated the production of enzyme. A quantitative estimation of enzyme activity was performed using nesselerization method. L-asparaginase positive culture was identified morphologically as well as with 16s rRNA sequencing as Enterobacter aesburiae strain R16C1/MT93543. To study the effect of different parameters on enzyme activity optimization studies were performed using one variable at a time. After screening suitable medium for enzyme production where maximum activity was observed in M9 medium containing maltose 10 g/l, K2HPO4 3.0 g/l, Yeast Extract 5.0 g/l, Tryptone 5.0 g/l and L-asparagine 1%. Three parameters- temperature, rpm and inoculum size were chosen to study their effect on enzyme production in M9 medium using RSM. As, it was difficult to analyze all the optimized values of studied factors using generated contour plots, point prediction of the software was used for determining the optimum values. To optimize, Box Benhken statistical design was used to study the effect of selected variables interaction on asparaginase production. A close similarity between the experimental and predicted values reflected the applicability and accuracy of RSM in optimization of process parameters to maximize L asparaginase production. Unstructured mathematical modelling of L-asparaginase revealed that the data obtained from model was best fit for the experimental data. The three dimensional response surface plot representing combined effect of pH and temperature (Fig. 9a) shows that the highest enzyme activity was observed at middle value of rpm and temperature. Similarly, the interaction between inoculum and temperature is studied which shows that central values of inoculum and temperature continued to give highest enzyme activity. A strong interaction between the three parameters studied, existed for the production of enzyme as the contour plots obtained for the variables under study were elliptical in nature (Fig. 10). The results obtained showed a considerable increase in enzyme activity after optimization than the initial value. The minimum L-asparaginase activity (12.38 U/mL) was observed in run number 11 and a highest activity of (40.17 U/mL) was obtained in run 1, 2 and 5. Optimum combination of rpm 180, temperature 30 0C and inoculum size 10% was determined. Enzyme activity predicted using this combination is 40.17 U/ml which is very close to experimental results of 40.36 U/ml.