Supporting Information

Biochemical and Biotechnological Studies on a Novel

Purified Bacillus Cholesterol Oxidase Tolerant to Solvent

and Thermal Stress

Fathy N. ElBaz 1 · Rawia F. Gamal 2 · Ashraf F. ElBaz 1 · Nasser E. Ibrahim 3 · Ahmed

ElMekawy 1,4

1 Department of Industrial Biotechnology, Genetic Engineering and Biotechnology Research

Institute, University of Sadat City (USC), Sadat City, Egypt.2 Department of Agricultural Microbiology, Faculty of Agriculture, Ain Shams University,

Cairo, Egypt.3 Department of Bioinformatics, Genetic Engineering and Biotechnology Research Institute,

University of Sadat City (USC), Sadat City, Egypt. 4 School of Chemical Engineering, University of Adelaide, Adelaide, Australia.

Correspondence: Ahmed ElMekawy, Tel.: +61 470235043; fax: +61 8 8303 4373

E-mail addresses: ahmed.elmekawy@adelaide.edu.au, ahmed.elmekawy@gebri.usc.edu.eg

S1

Statistical optimization of ChO production

The individual effects of the examined variables on ChO production are displayed as a

Pareto chart (Figure S2A), which exemplifies the extent of each effect along with the ranking of

different variables (El-Baz et al. 2011). After analyzing the regression coefficients, it was

observed that all variables had a positive effect on ChO activity, except harvesting time, Tween

80 concentration, cholesterol concentration and cholesterol addition time. Nevertheless, a non-

significant effect was observed on ChO activity, among low and high levels, for different

experimental variables, with the exception of harvesting time, NH4NO3, yeast extract and Tween

80 concentrations.

The lower probability value along with the higher F-value, compared to the tabulated

one, confirmed the model’s significance at a high confidence level. Additionally, the actual

values were highly correlated to the predicted ones, with R2 and adjusted R2 values of 0.92 and

0.82, respectively, illustrating that the variables were precisely compared and confirming the

model’s significance. A second-order polynomial model was created (Equation S1) in order to

predict the optimum point, throughout the tested variables.

Y = 1.79 + 0.09 X3 – 0.09 X4 – 0.09 X5 + 0.11 X8 + 0.32 X3X5 + 0.30 X5X8 – 0.20 X42 – 0.24 X5

2

+ 0.02 X82 (S1)

Where Y is the response variable of ChO activity, while X3, X4, X5 and X8 are harvesting time,

NH4NO3, yeast extract and Tween 80 concentrations, respectively. Equation (2) was solved, and

the highest ChO activity was predicted to be 93.3 U/mL in the 8th run.

The individual and interactive effects of the four independent variables on the ChO

activity were expressed by a Pareto chart (Figure S2B). The X4, X3X5, X42, X3X4, X4X8, X3X8,

X4X5 and X32 bars resided within the significance line, which showed that these terms had

insignificant effects on ChO activity. On the other side, the bars which crossed the significance

line (X8, X82, X5, X5, X5X8, X3 and X5

2) were significant at 95% confidence level. The positive

values of the coefficients (X82, X5, X3 and X5

2) exhibited a synergistic effect on the ChO activity,

while negative values showed an antagonistic effect on the ChO activity. The contour plots of

Correspondence: Ahmed ElMekawy, Tel.: +61 470235043; fax: +61 8 8303 4373

E-mail addresses: ahmed.elmekawy@adelaide.edu.au, ahmed.elmekawy@gebri.usc.edu.eg

S2

ChO activity for each pair of variables, by fixing the other factors constant at their high level, are

shown in Figure S3. The maximum amount of ChO was produced at a harvesting time between

5 and 6.5 days with a simultaneous negative effect of NH4NO3 and Tween 80 upon increasing

their concentrations (Figure S3A and C), while yeast extract had a positive effect on ChO

activity when its concentration was increased within the maximum range of the harvesting time

(Figure S3B). On the other side, increasing the concentration of Tween 80 reduced the enzyme

activity with maximum value (˃ 64 U/mL) obtained at lower concentrations irrespective of the

interacted factor (Figure S3C, D and E). Moreover, the interaction between yeast extract

concentration and all the other factors resulted in increased enzyme activity to more than 48

U/mL (Figure S3B, E and F).

Correspondence: Ahmed ElMekawy, Tel.: +61 470235043; fax: +61 8 8303 4373

E-mail addresses: ahmed.elmekawy@adelaide.edu.au, ahmed.elmekawy@gebri.usc.edu.eg

S3

S4

Table S1. The ChO activity of Bacillus pumilus produced under

various experimental factors randomized by Plackett-Burman design.Trial X1 X2 X3 X4 X5 X6 X7 X8 ChO activity (U/mL)

1 1 1 -1 -1 -1 1 -1 -1 9 ± 0.71

2 -1 1 -1 -1 1 -1 1 1 1.8 ± 0.12

3 -1 -1 1 -1 1 1 1 -1 4.5 ± 0.4

4 1 -1 -1 -1 1 -1 -1 1 0.08 ± 0.01

5 1 -1 -1 1 -1 1 1 1 0.06 ± 0.01

6 -1 -1 -1 1 -1 -1 1 -1 0.09 ± 0.02

7 1 -1 1 1 1 -1 -1 -1 6.75 ± 0.45

8 -1 1 1 1 -1 -1 -1 1 1.65 ± 0.11

9 -1 -1 1 -1 -1 1 -1 1 7.5 ± 0.5

10 -1 1 -1 1 1 1 -1 -1 57 ± 3.4

11 1 1 1 -1 -1 -1 1 -1 2.55 ± 0.17

12 1 1 1 1 1 1 1 1 1.65 ± 0.11

Table S2. Experimental and theoretical values of ChO activity under four variables

through Box-Behnken experimental design.Tria

l Pattern X3 X4 X5 X8 ChO activity (U/mL) Predicted ChO activity (U/mL)

1 0−−0 6 0.2 0.6 0.4 34.5 ± 2.51 27.2

2 0−0+ 6 0.2 0.8 0.6 6 ± 0.46 10.7

3 0+0− 6 0.4 0.8 0.2 67.5 ± 5.22 60.2

4 +0−0 7 0.3 0.6 0.4 3 ± 0.23 38.3

5 0000 6 0.3 0.8 0.4 14.3 ± 1.09 15.2

6 −−00 5 0.2 0.8 0.4 52.5 ± 4.03 18.4

7 0000 6 0.3 0.8 0.4 16.5 ± 1.25 15.2

8 00+− 6 0.3 1 0.2 90 ± 6.81 93.3

9 00−− 6 0.3 0.6 0.2 52.5 ± 3.97 46.7

10 0+−0 6 0.4 0.6 0.4 7.5 ± 0.56 17.8

11 −00+ 5 0.3 0.8 0.6 6.5 ± 0.48 1.3

12 −+00 5 0.4 0.8 0.4 11.3 ± 0.83 16.5

13 00−+ 6 0.3 0.6 0.6 22.5 ± 1.65 18.8

14 0000 6 0.3 0.8 0.4 15 ± 1.12 15.2

15 −0−0 5 0.3 0.6 0.4 12 ± 0.89 10.8

16 00++ 6 0.3 1 0.6 2.9 ± 0.21 7.8

17 0+0+ 6 0.4 0.8 0.6 2.9 ± 0.28 2.1

18 +0+0 7 0.3 1 0.4 45 ± 4.31 43.7

19 +00− 7 0.3 0.8 0.2 64.5 ± 6.16 73.1

20 −0+0 5 0.3 1 0.4 52.4 ± 5.04 41.6

21 ++00 7 0.4 0.8 0.4 39.8 ± 3.82 25.7

22 0++0 6 0.4 1 0.4 27 ± 2.59 37.7

23 0−0− 6 0.2 0.8 0.2 60 ± 5.75 62.4

24 +00+ 7 0.3 0.8 0.6 67.5 ± 6.46 11.4

25 0−+0 6 0.2 1 0.4 50.3 ± 4.81 43.4

26 −00− 5 0.3 0.8 0.2 54.8 ± 5.24 53.5

27 +−00 7 0.2 0.8 0.4 45 ± 4.31 38.8

S5

Figure S1. Phylogenetic tree showing position of the isolated Bacillus pumilus strain based on 16S

rRNA gene sequence.

S6

Figure S2. Pareto chart streamlining the effect of each variable on ChO

production by Bacillus pumilus applying Plackett-Burman design (A) and Box-

Behnken design (B). The vertical line defines the 95% confidence interval.

S7

Figure S3. Contour plots for ChO production as a function of harvesting time

and NH4NO3 concentration (A), harvesting time and yeast extract concentration

(B), harvesting time and Tween 80 concentration (C), NH4NO3 and Tween 80

concentrations (D), yeast extract and Tween 80 concentrations (E) and

NH4NO3 and yeast extract concentrations (F).