Enhanced production of lipase by the thermophilic Geobacillus stearothermophilus strain-5 using statistical experimental designs

New Biotechnology  Volume 27, Number 4  September 2010

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Research Paper

Enhanced production of lipase by the thermophilic Geobacillus stearothermophilus strain-5 using statistical experimental designs Mohamed Sifour1,2, Taha I. Zaghloul2, Hesham M. Saeed2, Mahmoud M. Berekaa3 and Yasser R. Abdel-fattah4 1

Department of Molecular and Cell Biology, Faculty of Science, University of Jijel, Ouled Aissa, Jijel, Algeria Department of Biotechnology, Institute of Graduate Studies and Research, Alexandria University, Egypt 3 Department of Environmental Science, Faculty of Science (Moharam Bay), Alexandria University, Egypt 4 Mubarak City for Scientific Research and Technology Applications, Alexandria, Egypt 2

Statistically based experimental designs were applied to optimize the cultural conditions for the production of a glycerol-inducible lipase from the thermophilic Geobacillus stearothermophilus strain-5. The effect of nineteen culture conditions on enzyme production was evaluated using Plackett–Burman factorial design. Tween 80, K2HPO4, glycerol and glucose were the most significant factors in improving enzyme production. The selected parameters were then further investigated using central composite design to define the optimal process conditions. Maximal enzyme activity (578 U/ml) was reached under the following conditions: glycerol, 2.24% (v/v); Tween 80, 0.76% (v/v); glucose, 0.76% (w/v) and K2HPO4, 0.38% (w/v) which is about five folds the activity in basal medium. A verification experiment was carried out to examine model validation and revealed more than 98% validity.

Introduction Recently, the investigation on enzyme from thermophilic bacteria has gained a considerable attention because many industrial processes operate best at high temperature [1–4]. Lipolytic enzymes (lipases and esterases) are an important group of biocatalysts that found great applications in biotechnological processes, they have been widely used in several industries (food, dairy, detergent, and pharmaceuticals) [5,6]. As most of the industrial processes operate at temperature exceeding 45 8C, lipase should be active and stable at a temperature around 50 8C [1]. Several lipases have been isolated and purified from thermophilic bacteria, mainly from thermophilic Bacillus (Geobacillus) [7–10]. Medium composition significantly affects product concentration, yield and productivity. There is a general practice of determining optimal concentration of media components by varying one factor at a time. However, this method does not depict the net effect of total interactions among the various media components Corresponding author: Sifour, M. ([email protected])

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[5]. Experimental design techniques present a more balanced alternative to the one-factor-at-a time approach to fermentation improvement [11]. The factorial design of a limited set of variables is advantageous in relation to the conventional method of manipulation of a single parameter per trial, as the latter approach frequently fails to locate the optimal conditions for the process, because of its failure to consider the effect of possible interactions between factors [5]. A glycerol-inducible lipase was previously isolated from the thermophilic Geobacillus stearothermophilus strain-5 [12]. The present work aims at evaluating culture conditions affecting lipase secretion from the same isolate by applying factorial experimental design and at determining optimum conditions for its production using central composite design (CCD).

Materials and methods Microorganism The isolate used in this study was isolated from desert soil sample and was purified and identified by 16S rRNA as Geobacillus stearothermophilus (accession number: DQ923400) [12].

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TABLE 1

Lipase assay

Media components and test levels for Plackett–Burman experiment.

Lipase activity was determined colorimetrically [13] using two solutions. Solution 1 contained 90 mg p-nitrophenyl palmitate dissolved in 30 ml 2-propanol. Solution 2 contained 2 g Triton X-100 and 0.5 g gum arabic dissolved in 450 ml buffer (Tris–HCl, 50 mM, pH 8). The assay reagent was prepared by adding 1 ml of solution 1 to 9 ml of solution 2 dropwise to get an emulsion that remained stable for 2 h. The assay mixture contained 900 ml of the emulsion and 100 ml of an appropriately diluted enzyme solution. The liberated p-nitrophenol was measured at 410 nm. One unit of enzyme was defined as the amount of enzyme that releases 1 mmol p-nitrophenol from the substrate per minute. The assay was carried out at 60 8C.

Variable

Variable code

Low level (1)

High level (+1)

Tween 80 (%)

X1

0.2

1

Olive oil (%)

X2

1

5

Glycerol (%)

X3

0.2

1

Glucose (%)

X4

0.1

1

Galactose (%)

X5

0

1

Arabinose (%)

X6

0

1

Xylose (%)

X7

0

1

Sucrose (%)

X8

0

1

Inoculum and enzyme preparation

Peptone (%)

X9

0.2

1

Yeast extract (%)

X10

0.2

1

Urea (%)

X11

0.2

1

(NH4)2SO4 (%)

X12

0.2

1

MgSO4 (%)

X13

0.2

1

K2HPO4 (%)

X14

0.1

0.5

KH2PO4 (%)

X15

0.1

0.5

CaCl2 (%)

X16

0.02

0.1%

pH

X17

6

8

Aeration (200 rpm)

X18

No baffles

2 baffles

The production medium was prepared in different formulae according to the experimental design in Tables 1 and 4. At the end of the incubation period, cells were removed by centrifugation at 7000 rpm for 4 min and the supernatant was considered as crude enzyme and used for the measurement of lipase activity. The experiments were carried out in duplicate. The production medium was inoculated with 4% (v/v) of the 16– 18 h bacterial culture (A600 = 2.1 corresponding to 4.2  107 CFU/ ml) grown on PY medium [14] (g/l—peptone: 10; yeast extract: 5; NaCl: 5). Cells were removed by centrifugation at 7000 rpm for 4 min and suspended in normal saline then used as inoculum.

Temperature

X19

55

65

Plackett–Burman design For screening purpose, various medium components as well as environmental factors were evaluated. The different factors were

TABLE 2

Plackett–Burman experimental design for the evaluation of factors affecting lipase production by G. stearothermophilus strain-5; activity was measured after 48 h of incubation. Trials

X1

X2

X3

X4

X5

X6

X7

X8

X9

X10

X11

X12

X13

X14

X15

X16

X17

X18

X19

Activity (U/ml)

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

14.50

2

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

467.00

3

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

187.00

4

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

41.50

5

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

34.60

6

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

45.90

7

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

34.20

8

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

35.70

9

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

46.00

10

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

77.80 129.00

11

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

12

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

38.90

13

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

53.20

14

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

76.90

15

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

226.00

16

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

127.00

17

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

38.50

18

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

263.00

19

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

103.00

20

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

100.00

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New Biotechnology  Volume 27, Number 4  September 2010

prepared in two levels, 1 for low level and +1 for high level, based on a Plackett–Burman statistical design [15]. This design is practical especially when the investigator is faced with large number of factors and is unsure which settings are likely to produce optimal or near optimum responses [16]. Table 1 illustrates the factors under investigation as well as levels of each factor used in the experimental design, whereas Table 2 represents the design matrix. Plackett–Burman experimental design is based on the first order model: X Y ¼ b0 þ bi xi Research Paper

where Y is the response (enzyme activity), b0 is the model intercept and bi is the variables estimates. This model describes no interaction among factors and it is used to screen and evaluate the important factors that influence the response (enzyme activity). The maximum number of variables that can be evaluated in one design is equal to one less than the number of individual experiments. In the present work, 19 assigned variables were screened in 20 experiments that were carried out in Erlenmeyer flasks. Enzyme activity was measured after 48 h of incubation. All experiments were carried out in duplicate and the averages of lipase activity were taken as responses. The variables whose confidence levels were higher than 95% were considered to significantly influence lipase activity.

TABLE 4

CCD matrix representing the effect of different significant variables on lipase production by G. stearothermophilus strain-5. Trials Tween 80 K2HPO4

Glycerol

Glucose

Activity (U/ml)

1

1

1

1

1

450.4

2

1

1

1

1

293.05

3

1

1

1

1

279.86

4

1

1

1

1

281.25

5

1

1

1

1

511.11

1.48258

370.6

6

0

0

0

7

1

1

1

1

328.57 252.77

8

1

1

1

1

9

0

0

0

0

402.77

10

0

0

0

445.4

11

1

1

1

1

313.49

12

0

0

0

0

358.73

13

1

1

1

1

207.64

14

1

1

1

1

339.58

15

1

1

1

1

240.27

16

1

17

1.482579

1.48258

1

1

1

0

0

0 1

299.305 313.94

18

1

1

1

Central composite design (CCD)

19

0

0

0

1.482579 293.46

To describe the nature of the response surface in the experimental region, a central composite design [17] was applied. As presented in Table 3, factors of highest confidence levels elucidated through Plackett–Burman experimental design were prescribed into five levels, coded 1.48, 1, 0, 1.48, and +1. Table 4 represents the design matrix of a 26 trials experiment. For predicting the optimal point, a second-order polynomial function was fitted to correlate relationship between independent variables and response (lipase activity). For the four factors the equation is:

20

0

1.482579

0

0

345.5

Y ¼ b0 þ b1 X1 þ b2 X2 þ b3 X3 þ b4 X4 þ b12 X1 X2 þ b13 X1X3 þ b14 X1 X4 þ b23 X2 X3 þ b24 X2 X4 þ b34 X3 X4 þ b11 X21 þ b22 X22 þ b33 X23 þ b44 X24

TABLE 3

Variables and their settings employed in central composite design for optimization of lipase production by G. stearothermophilus strain-5. Variables

Variable code

1.48

1

0

+1

+1.48

Tween (%)

X1

0.76

1

1.5

2

2.24

K2HPO4 (%)

X2

0.38

0.5

0.75

1

1.12

Glycerol (%)

X3

0.76

1

1.5

2

2.24

Glucose (%)

X4

0.76

1

1.5

2

2.24

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0

1.482579

0

352.08

22

1.48258

0

0

0

0

440

23

1

1

1

1

390.74

24

0

0

0

425.92

25

1

1

1

1

235.94

26

1

1

1

1

353.84

1.48258

nomial model equation was expressed by the coefficient of determination R2.

Statistical analysis of the data

where Y is the predicted response, b0 the model constant; X1, X2, X3 and X4 independent variables; b1, b2, b3 and b4 are linear coefficients; b12, b13, b14, b23, b24 and b34 are cross product coefficients and b12, b22, b33 and b44 are the quadratic coefficients. Microsoft Excel 97 was used for the regression analysis of the experimental data obtained. The quality of fit of the poly-

332

21

395.3

The data on enzyme activity were subjected to multiple linear regression using MICROSOFT EXCEL 97 to estimate t-value, Pvalue and confidence level. The significance level (P-value) was determined using the Student’s t-test. The t-test for any individual effect allows an evaluation of the probability of finding the observed effect purely by chance. If this probability is sufficiently small, the idea that the effect was caused by varying the level of the variable under test is accepted. Confidence level is an expression of the P-value in percent. Optimal value of activity was estimated using the solver function of MICROSOFT EXCEL tools.

Results and discussion The strain used in this study is a thermophilic Geobacillus stearothermophilus that produce a glycerol-inducible lipase [12]. For improvement of the enzyme production, a sequential optimization approaches were applied. The first approach deals with screening for culture as well as nutritional factors affecting growth and lipase production by G. stearothermophilus strain-5. The second

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approach is to optimize the factors that control the enzyme production process.

Nineteen different factors including fermentation conditions and medium constitution were screened for their effect on lipase production using the Plackett–Burman design. The independent variables examined and their settings are shown in Table 1. The design plan and the averages of lipase activity for the different trials are given in U/ml and shown in Table 2. The main effect of each variable was estimated as the difference between both averages of measurements made at the high level (+1) and at the low level (1) of that factor. The data in Table 2 show a wide variation from 14.5 to 467 U/ml of lipase activity. This variation reflects the importance of medium optimization to attain higher productivity. The analysis of the data from the Plackett–Burman experiments involved a first order (main effects) model. The main effects of the examined factors on the enzyme activity were calculated and presented graphically in Fig. 1. On the basis of the analysis of the regression coefficients of the 19 variables after 48 h of incubation, Tween 80, olive oil, glycerol, glucose, arabinose, sucrose, K2HPO4, MgSO4, culture pH and temperature showed positive effect on lipase activity. Xylose, galactose, (NH4)2SO4, peptone, baffles (as an expression of medium aeration factor), KH2PO4, and CaCl2 repressed enzyme production. Urea and yeast extract have a slight effect on enzyme productivity. Fig. 2 shows the ranking of factor estimates in a Pareto chart. The Pareto chart displays the magnitude of each factor estimate and it is a convenient way to view the results of a Plackett–Burman design. The polynomial model describing the correlation between the 19 factors and the lipase activity could be presented as follows: Y activity ¼ 107:01 þ 59:29X1 þ 21:72X2 þ 30:23X3 þ 28:994X4  5:73X5 þ 13:82X6  15:64X7 þ 11:85X8  19:35X9 þ 4:02X10 þ 1:71X11  12:04X12 þ 14:38X13 þ 34:62X14  31:92X15  30:10X16 þ 24:81X17  19:74X18 þ 7:93X19 On the basis of calculated t-values and confidence level (%) (Table 5), Tween 80, K2HPO4, glycerol and glucose, were found to be the most significant variables affecting lipase activity, they were

FIGURE 2

Pareto chart rationalizing the effect of each variable on the enzyme activity (U/ml) produced by G. stearothermophilus strain-5.

chosen for further optimization. Some variables of negative significant effect were not included in the next optimization experiment, but instead were used in all trials at their (1) level. Most of the reports state that lipases are generally induced by oils [18,19]. Tween 80 was one of the most important factors that affect the production of lipase from Geobacillus thermoleovorans [19]; Tween 80 was also found to be the best carbon source inducing production of lipase from a thermophilic Bacillus sp. [20]. In our study, lipase production was induced by glycerol and glucose and it was poorly induced by olive oil. This observation is in accordance with the report of Gupta et al. [21], where glycerol and mannitol were applied for lipase induction in a thermophilic Bacillus sp. instead

TABLE 5

Statistical analysis of Plackett–Burman design showing coefficient values, t- and P-values for each variable. Variables

P-value

59.291

7.47

0.0847

Olive oil (%)

21.721

2.74

0.2230

Glycerol (%)

30.239

3.81

0.1634

Glucose (%)

28.664

3.61

0.1791

Galactose (%)

5.735

0.72

0.6016

Xylose (%)

13.82 15.645

1.74

0.3318

1.97

0.2989 0.3756

Sucrose (%)

11.851

1.49

Peptone (%)

19.355

2.44

0.2477

4.024

0.51

0.7012

1.714

0.22

0.8646

12.047

1.52

0.3708

Yeast extract (%) Urea (%) (NH4)2SO4 (%) MgSO4 (%)

14.381

1.81

0.3210

K2HPO4 (%)

34.625

4.36

0.1434

KH2PO4 (%)

31.928

4.02

0.1551

CaCl2 (%)

30.102

3.79

0.1641

24.812

3.13

0.1971

19.742

2.49

0.2433

7.936

4.63

0.1354

pH FIGURE 1

t-Statistics

Tween 80 (%)

Arabinose (%)

Effect of different factors on lipase production (U/ml) by G. stearothermophilus strain-5 as screened with Plackett–Burman design.

Coefficients

Aeration Temperature

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Evaluation of the factors affecting lipase productivity

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of lipid sources. On the other hand, supplementation of the medium with 0.1% glucose enhanced the production of lipase from the thermophilic Bacillus sp. THL027 [22].

Application of CCD and data analysis Further experiments were carried out to obtain a quadratic model consisting of 26 trials. As presented in Table 3, factors of highest confidence levels were prescribed into five levels, coded 1.48, 1, 0, +1 and +1.48. The design of this experiment is given in Table 4 together with the experimental results. Regression analysis was

New Biotechnology  Volume 27, Number 4  September 2010

performed to fit the response function (lipase activity) with the experimental data. The analysis of variance for the four variables (Tween 80, glycerol, glucose and K2HPO4) indicated that enzyme activity can be well described by a polynomial model with a relatively high coefficient of determination (R2 = 0.85). The statistical analysis of the full model in Table 6 shows that Tween 80, K2HPO4, glucose and glycerol each had a significant effect on lipase synthesis. When presenting experimental results in the form of surface plot (Fig. 3) it can be seen that near to moderate levels of Tween 80, K2HPO4 and glucose and high level of glycerol

Research Paper FIGURE 3

Three dimensional response surface graphs showing the behavior of lipase response as affected by different culture conditions in CCD (A, B, C, D, E, and F). 334

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Regression coefficient of the full polynomial model representing relationships between lipase activity and independent variables (Tween 80, K2HPO4, glycerol and glucose). Coefficient symbol

Estimatea

P-value

b0

402.94

<1  104

b1

28.21

1.3  102

b2

24.24

2.8  102

able role in the lipase production. In addition to its role as an important constituent of cellular biomolecules such as nucleic acids and phospholipids, phosphate is known to play a regulatory role in the synthesis of primary and secondary metabolites in microorganisms [23]. The final production conditions were as follows (%): glycerol: 2.24; glucose: 0.76; Tween 80: 0.76; K2HPO4: 0.38; yeast extract: 1; peptone: 0.2; (NH4)2SO4: 0.2; MgSO4:1; KH2PO4: 0.1; CaCl2: 0.02, pH adjusted to 7.0–7.5 and incubated at 60 8C.

b3

5.33

0.59

b4

33.78

5  103

Verification of model

b12

9.82

0.38

b13

15.17

0.19

b14

29.36

2  102

The adequacy of the model was examined by an additional experiment using the derived optimal conditions. The predicted value was 589.1 U/ml and in the experimental value was 578  5 U/ml. This is approximately 98% of the predicted value, which indicates that the generated model gave an adequate prediction of the enzyme activity. Optimization through statistical experimental design has been applied in the production of many lipolytic enzymes [24,25]. Plackett–Burman design was used to evaluate cultural conditions affecting lipase production by a thermophilic G. thermoleovorans YN [11], followed by determining the optimum conditions by implementing Box–Behnken experimental design. The optimized medium resulted in about 4-fold increase in enzyme production, compared with that obtained in the basal medium [19]. Moreover, the production of thermostable lipase from a thermophilic Bacillus sp. was improved tremendously (around 193-fold) following medium optimization involving both one-at-a-time and statistical designing approaches [21].

b23

10.54

0.35

b24

31.57

1.4  102

b34

28.20

2.5  102

b11

17.41

0.24

b22

9.01

0.53

b33

11.94

0.41

b44

37.86

2  102

a

Estimates are the polynomial model coefficients.

supported high lipase activity. For predicting the optimal point, within experimental constrains, a second-order polynomial function was fitted to the experimental results of lipase activity: Y ¼ 402:94  28:21X1  24:24X2  5:33X3  33:78X4  9:82X1 X2  15:17X1 X3 þ 29:36X1 X4  10:54X2 X3 þ 31:57X2 X4  28:2X3 X4  17:41X21  9:01X22  11:94X23  37:86X24 where X1, X2, X3 and X4 represent codified values for Tween 80, K2HPO4, glycerol and glucose, respectively. At the model level, the correlation measures for the estimation of the regression equation are the multiple correlation coefficient R and the determination coefficient R2. The closer the value of R is to 1, the better is the correlation between the observed and the predicted values. In this experiment, the value of R was 0.92 for activity. This value indicates a high degree of correlation between the experimental and the predicted values. The value of determination coefficient R2 = 0.85 being a measure of fit of the model, indicates that about 15% of the total variations are not explained by the activity model. From statistical analysis, it can be concluded that among the test variables, glycerol had the most significant effect on lipase activity. The optimal levels of the three components as obtained from the maximum point of the polynomial model were estimated using the Solver function of MICROSOFT EXCEL tools, and found to be (%): glycerol: 2.24, Tween 80: 0.76, glucose: 0.76 and K2HPO4: 0.38. with a predicted activity of 589.1 U/ml. The optimal value of enzyme activity was about five times that in the basal conditions, which reflects the necessity and the value of optimization process. Results obtained in this study are in accordance with other findings, where it was reported that glycerol is one of the most important factors that affect lipase production from a thermophilic Bacillus sp. [18,21]. The importance of Tween 80 as carbon source for the production of lipase was also reported [19,20]. In addition, the presence of inorganic phosphate showed a remark-

Monitoring production of lipase in basal and optimized media The bacterial growth and the extracellular lipolytic activity of the G. stearothermophilus strain-5 grown on the basal (PY) medium [14] and optimized medium were monitored. Bacterial growth was determined by measuring the absorbance of the culture suspension at 420 nm. Lipolytic activity was measured using p-nitophenyl palmitate as mentioned before. Data of Fig. 4 illustrated the

FIGURE 4

Monitoring bacterial growth and extracellular lipolytic activity of G. stearothermophilus strain-5 grown on (&) PY medium and (~) optimized medium. Open symbols represent bacterial growth and the closed ones represent corresponding lipolytic activity. www.elsevier.com/locate/nbt

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TABLE 6

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growth and the level of lipolytic activity through 48 h of incubation. Data showed that the level of extracellular enzyme production started at late log phase of the bacterial growth and increased gradually with bacterial growth till it reached its maximal level after 24 and 48 h of incubation on the basal and on the optimized medium, respectively. The level of the enzyme produced in opti-

New Biotechnology  Volume 27, Number 4  September 2010

mized medium was about five folds the activity in basal medium, which confirms the necessity of the optimization process.

Acknowledgment M. Sifour is very grateful to the ‘Ministry of Higher Education and Scientific Research of Algeria’ for their financial support.

References Research Paper

1 Sharma, R. et al. (2002) Purification and characterisation of a thermostable alkaline lipase from a new thermophilic Bacillus sp, RSJ-1. Process Biochem. 37, 1075–1084 2 Haki, G.D. and Rakshit, S.K. (2003) Developments in industrially important thermostable enzymes: a review. Bioresour. Technol. 89, 17–34 3 Dominguez, A. et al. (2005) Lipolytic enzyme production by Thermus thermophilus HB27 in a stirred tank bioreactor. Biochem. Eng. J. 26, 95–99 4 Soliman, N.A. et al. (2007) Molecular cloning and characterization of thermostable esterase and lipase from Geobacillus thermoleovorans YN isolated from desert soil in Egypt. Process Biochem. 42, 1090–1100 5 Gupta, R. et al. (2004) Bacterial lipases: an overview of production, purification and biochemical properties. Appl. Microbiol. Biotechnol. 64, 763–781 6 Hasan, F. et al. (2006) Industrial applications of microbial lipases. Enzyme Microb. Technol. 39, 235–251 7 Schmidt-Dannert, C. et al. (1996) Screening purification and properties of a thermophilic lipase of Bacillus thermocatenulatus. Biochim. Biophys. Acta 1301, 105– 114 8 Sinchaikul, S. et al. (2001) Optimization of a thermostable lipase from Bacillus stearothermophilus P1: overexpression, purification and characterization. Protein Expr. Purif. 22, 388–398 9 Li, H. and Zhang, X. (2005) Characterization of thermostable lipase thermophilic Geobacillus sp. TW1. Protein Expr. Purif. 42, 153–159 10 Abdel-Fattah, Y.R. and Gaballa, A.A. (2008) Identification and over-expression of a thermostable lipase from Geobacillus thermoleovorans Toshki in Escherichia coli. Microbiol. Res. 163, 13–20 11 Abdel-Fattah, Y.R. et al. (2002) Lipase production from a thermophilic Bacillus sp.: application of Plackett–Burman design for evaluating culture conditions affecting enzyme formation. Acta Microbiol. Pol. 51, 353–366 12 Berekaa, M. et al. (2009) Production of a novel glycerol-inducible lipase from thermophilic Geobacillus stearothermophilus strain-5. World J. Microbiol. Biotechnol. 25, 287–294 13 Vorderwuelbecke, T. et al. (1992) Comparison of lipases by different assays. Enzyme Microb. Technol. 14, 631–639

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14 Bernhard, K. et al. (1978) Bacteriocin and antibiotic resistance plasmids in Bacillus cereus and Bacillus subtilis. J. Bacteriol. 133, 897–903 15 Plackett, R.L. and Burman, J.P. (1946) The design of optimum multifactorial experiments. Biometrika 33, 305–325 16 Strobel, R.J. and Sullivan, G.R. (1999) Experimental design for improvement of fermentations. In Manual of Industrial Microbiology and Biotechnology (Demain, A.L. and Davies, J.E., eds), pp. 80–93, ASM Press 17 Box, G. and Behnken, D. (1960) Some new three-level designs for the study of quantitative variables. Technometrics 2, 455–475 18 Becker, P. et al. (1997) Determination of the kinetic parameters during continuous cultivation of the lipase-producing thermophile Bacillus sp. IHI-91 on olive oil. Appl. Microbiol. Biotechnol. 48, 184–190 19 Abdel-Fattah, Y.R. (2002) Optimization of thermostable lipase production from a thermophilic Geobacillus sp. using Box–Behnken experimental design. Biotechnol. Lett. 24, 1217–1222 20 Sidhu, P. et al. (1998) Production of extracellular alkaline lipase by anew thermophilic Bacillus sp.. Folia Microbiol. 43, 51–54 21 Gupta, N. et al. (2004) Glycerol-inducible thermostable lipase from Bacillus sp.: medium optimization by a Plackett–Burman design and by response surface methodology. Can. J. Microbiol. 50, 361–368 22 Dharmasthiti, S. and Luchai, S. (1999) Production, purification and characterization of thermophilic lipase from Bacillus sp. THL027. Microbiol. Lett. 179, 241–246 23 Malhotra, R. et al. (2000) Production and characterization of thermostable and calcium-independent a-amylase of an extreme thermophile Bacillus thermoleovorans NP54. Lett. Appl. Microbiol. 31, 378–384 24 Kulkarni, N. and Gadre, R.V. (2002) Production and properties of an alkaline, thermophilic lipase from Pseudomonas fluorescens NS2W. J. Indus. Microbiol. Biotechnol. 28, 344–348 25 Rathi, P. et al. (2002) Statistical medium optimization and production of a hyperthermostable lipase from Burkholderia cepacia in a bioreactor. J. Appl. Microbiol. 93, 930–936