Supplementary material

Optimization of media for maximum urease production

Various nutritional factors in the basic media (composition: 20g/l sucrose, 3.4g/l yeast extract, 0.85 g/l Urea, 0.05g/l

MgSO4.7H2O, 0.03g/l NiSO4.6H2O, 0.04g/l CaCl2, 5.5g/l KH2PO4, 0.35g/l K2HPO4) influencing urease production by

B. pasteurii NCIM 2477 were studied. The fermentation studies for optimizing urease production were investigated in two steps using submerged fermentation at 30±2ᵒC and 180rpm for 24hrs. One factor-at-a-time method was used primarily, to select parameters (Initial pH condition (7.0), Inoculation size (2%), urea concentration (2%) and carbon-nitrogen source (2% glucose; 1% yeast extract)) for optimization of media for urease production.

Considerable amount of urease (33.50 U/ml) was produced from B. pasteurii with optimization by one-factor-at-a- time method. Two experimental designs, the Plackett-Burman design and the central composite design (CCD) were carried out for further optimization of fermentation medium. Experimental designs were generated by using the statistical software package ‘Design-Expert 6.0.10 Stat-Ease,’ Minneapolis, MN. Statistical analysis of experimental data was also performed using this software. The significance of each nutritional component with respect to urease production was identified by Plackett-Burman design (seven (n) variables including six nutritional viz. yeast extract,

glucose, urea, MgSO4, NiSO4, NaCl, and one dummy or unassigned variable were studied with eight (n+1) experiments (Table. 1). Each variable were represented at two levels, high and low, denoted by (+) and (-) signs, respectively. The difference between the two values was taken large enough in order ensure that the peak area for

highest enzyme production is well included. The F test value for glucose (206.88), urea (363.54) and NiSO4 (408.26) implied them to be the most significant terms in the Plackett-Burman design. In the second step, the concentration of most significant factors and their interaction were studied using response surface methodology (central composite design). Each variable in the design was studied at five different levels (glucose: 0.32%, 1%, 2%, 3%, 3.68%., urea:

0.32%, 1%, 2%, 3%, 3.68%., NiSO4: 0, 0.01, 0.03, 0.05, 0.06) with all variables taken at a central coded value of

1 zero (-1.68, -1, 0, 1, 1.68). Accordingly, a factorial experimental design, with an axial point (α = 1.68) and six replicates at the center point, with a total number of 20 experiments, was employed which increased yield of urease activity of B. pasteurii from 33.50 to 42.57 Uml-1. (Table 2). The relationship of the independent variables and the response was calculated by the second order polynomial equation:

(1)

Y is the predicted response; β0 a constant; βi the linear coefficient; βii the squared coefficient; and βij the cross- product coefficient, k is number of factors. The second order polynomial coefficients were calculated using the software package Design Expert Version 6.0.10 to estimate the responses of the dependent variable. Response surface plots were also obtained using Design Expert Version 6.0.10. Validation of the model proposed by the software was done by running the experiments at the predicted levels of parameters for optimal urease production.

The results were analyzed by using ANOVA i.e. analysis of variance suitable for the experimental design used. The

Model F-value of 76.40 implies the model is significant. Values of P less than 0.0001 indicate model terms are significant. The coefficient estimates and the corresponding P values suggests that, among the test variables used in

2 2 2 the study, A, B, C, A , B and C , (where A = Glucose, B = Urea, C =NiSO4,) are significant model terms. The interactions between A, B and C were found to be insignificant.

The corresponding second-order response model for Equation (1) that was found after analysis for the regression.

Final Equation in Terms of Actual Factors:

Urease (U/ml) =

2 42.62892026 + 1.960988671 * Glucose + 2.999323452* Urea + 1.829020998 * NiSO4 - 4.142394155 * Glucose -

2 2 3.266642406 * Urea -3.443419101 * NiSO4 + 0.9875 * Glucose * Urea - 1.0375 * Glucose * NiSO4 + 0.7875

* Urea * NiSO4

(2)

The "Pred R-Squared" of 0.9033 is in reasonable agreement with the "Adj R-Squared" of 0.9728."Adeq Precision" measures the signal to noise ratio. A ratio greater than 4 is desirable. Ratio of 23.34 indicates an adequate signal.

2 The fit of the model was also expressed by the coefficient of regression R 2, which was found to be 0.9857, indicating that 98.57 % of the variability in the response could be explained by the model.

The maximum production of urease obtained using the optimized medium for urease production (OptU) was

42.57±0.54 U/ml which was in close agreement with the predicted value (43.82 U/ml) by the RSM regression study.

Hence 2.43 fold increase in urease activity was observed after media optimization by combination of one-factor-at- a-time, Plackett Burman and Response surface method using Central Composite Design.

Table 1 Plackett Burman design for seven variables and its impact on urease activity

Ex. Yeast a Glucose Urea MgSO4 NiSO4 Dummy NaCl Yield No. Extract 36.11±0. 1 - + + - + + - 0002 30.92±0. 2 - - + + + - + 003 33.58±0. 3 + - + + - + - 004 28.00±0. 4 - + - + - + + 003 32.50±0. 5 + - - - + + + 001 29.00±0. 6 + + + - - - + 0007 27.70±0. 7 + + - + + - - 005 22.00±0. 8 ------002 Yeast extract high level (+)=1.5%, low level (-)=0.5%; Glucose high level (+) =3, low level (+) =1%; urea high level (+)=3%, low level (+) =1%; MgSO4 high level (+)=0.008%, low level (+) =0.002%; NiSO4 high level (+)=0.05%, low level (+) =0.01%; NaCl high level (+)=1%, low level (-)=0.1%

*Yield- Enzyme Activity (U/ml) and a Values are means of three replications ±SD

3 Table 2 Experimental design and results of CCD of response surface methodology (RSM) for the optimization of urease production

Enzyme activity (U/ml) Urea NiSO4 Run Glucose (%) (%) (g/l) Experimentala predicted 1 -1 -1 -1 25.75 ± 0.02 25.72 2 1 -1 -1 30.65 ± 0.04 29.75 3 -1 1 -1 28.97 ± 0.05 28.17 4 1 1 -1 34.98 ± 0.08 36.15 5 -1 -1 1 31.36 ± 0.01 29.88 6 1 -1 1 29.27 ± 0.03 29.75 7 -1 1 1 34.89 ± 0.05 35.48 8 1 1 1 39.59 ± 0.02 39.30 9 -1.68 0 0 26.75 ± 0.03 27.61 10 1.68 0 0 34.64 ± 0.07 34.21 11 0 -1.68 0 27.35 ± 0.04 28.35 12 0 1.68 0 38.99 ± 0.03 38.43 13 0 0 -1.68 29.63 ± 0.06 29.81 14 0 0 1.68 35.71 ± 0.02 35.97 15 0 0 0 42.67 ± 0.01 42.63 16 0 0 0 43.67 ± 0.03 42.63 17 0 0 0 41.73 ± 0.05 42.63 18 0 0 0 42.72 ± 0.02 42.63 19 0 0 0 43.06 ± 0.02 42.63 20 0 0 0 42.00 ± 0.04 42.63 a Values are means of three replications ±SD

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