Scholarly article on topic 'Application of experimental designs to optimize medium composition for production of thermostable lipase/esterase by Geobacillus thermodenitrificans AZ1'

Application of experimental designs to optimize medium composition for production of thermostable lipase/esterase by Geobacillus thermodenitrificans AZ1 Academic research paper on "Biological sciences"

CC BY-NC-ND
0
0
Share paper
OECD Field of science
Keywords
{Lipase/esterase / "Experimental design" / "Thermostable enzymes" / " Geobacillus thermodenitrificans AZ1"}

Abstract of research paper on Biological sciences, author of scientific article — Yasser R. Abdel-Fattah, Nadia A. Soliman, Samar M. Yousef, Ehab R. El-Helow

Abstract Thirty two morphologically different bacterial were isolated from different soil samples and screened for their ability to produce lipolytic enzymes. Among all isolates, the isolate coded AZ1 was selected due to its high potency to produce lipase at elevated temperature up to 65°C. Phylogenetic analysis based on 16SrDNA sequence revealed its close relationship to Geobacillus thermodenitrificans. The effect of ten culture variable on lipase production was evaluated by implementing Plackett–Burman statistical design. d-sucrose, peptone and soy bean flour were the most significant variables affecting lipase production. A pre-optimized medium based on this experiment yielded an enzyme activity of 260Umin−1 ml−1. For further optimization, a fourteen trials’ multi-factorial Box–Behnken experimental design was applied to find out the optimum level of each of the significant variables. The tested variables, namely: d-sucrose (X1); peptone (X2) and soy bean flour (X3) were examined, each at three different levels coded −1, 0, +1. The optimal levels of the three components were founded to be (g/L): d-sucrose, 6.56; peptone, 6.35; and soy bean flour, 6.92, with a predicted activity of approximately 610Umin−1 ml−1. According to the results of the Plackett–Burman and Box–Behnken designs the following medium composition is expected to be optimum (g/L): d-sucrose 6.56, peptone 6.35, soy bean flour 6.92, CaCl2 0.02, Y.E. 2.5, K2HPO4 1.0, MgSO4.7H2O 0.2 and Fe2 (SO4)3 0.02; pH, 8; cultivation temperature 55°C and incubation time 24h, the enzyme activity measured in the medium was approximately 593Umin−1 ml−1.

Academic research paper on topic "Application of experimental designs to optimize medium composition for production of thermostable lipase/esterase by Geobacillus thermodenitrificans AZ1"

Journal of Genetic Engineering and Biotechnology (2012) 10, 193-200

Academy of Scientific Research & Technology and National Research Center, Egypt

Journal of Genetic Engineering and Biotechnology

www.elsevier.com/locate/jgeb

ARTICLE

Application of experimental designs to optimize medium composition for production of thermostable lipase/esterase by Geobacillus thermodenitrificans AZ1

Yasser R. Abdel-Fattah a *, Nadia A. Soliman a, Samar M. Yousef a, Ehab R. El-Helow b l

a Bioprocess Development Dept., Genetic Engineering and Biotechnology Research Institute, City for Scientific Research and Technology Applications, Alexandria, Egypt

b Botany and Microbiology Dept., Faculty of Science, Alexandria University, Egypt

Received 18 July 2012; revised 9 August 2012; accepted 20 August 2012 Available online 4 October 2012

KEYWORDS

Lipase/esterase; Experimental design; Thermostable enzymes; Geobacillus thermodenitrificans AZ1

Abstract Thirty two morphologically different bacterial were isolated from different soil samples and screened for their ability to produce lipolytic enzymes. Among all isolates, the isolate coded AZ1 was selected due to its high potency to produce lipase at elevated temperature up to 65 °C. Phylogenetic analysis based on 16SrDNA sequence revealed its close relationship to Geobacillus thermodenitrificans. The effect of ten culture variable on lipase production was evaluated by implementing Plackett-Burman statistical design. d-sucrose, peptone and soy bean flour were the most significant variables affecting lipase production. A pre-optimized medium based on this experiment yielded an enzyme activity of 260 U min-1 ml-1. For further optimization, a fourteen trials' multifactorial Box-Behnken experimental design was applied to find out the optimum level of each of the significant variables. The tested variables, namely: d-sucrose (X1); peptone (X2) and soy bean flour (X3) were examined, each at three different levels coded -1,0, +1. The optimal levels of the three components were founded to be (g/L): d-sucrose, 6.56; peptone, 6.35; and soy bean flour, 6.92, with a predicted activity of approximately 610 Umin-1 ml-1. According to the results of the Plackett-Burman and Box-Behnken designs the following medium composition is expected to be optimum (g/L): d-sucrose 6.56, peptone 6.35, soy bean flour 6.92, CaCl2 0.02, Y.E. 2.5, K2HPO4 1.0,

* Corresponding author.

E-mail address: yasser1967@yahoo.com (Y.R. Abdel-Fattah).

1 Present address: Faculty of Pharmacy and Drug Manufacturing, Pharos University, Alexandria.

Peer review under responsibility of National Research Center, Egypt.

1687-157X © 2012 Academy of Scientific Research & Technology. Production and hosting by Elsevier B.V. All rights reserved. http://dx.doi.org/10.1016/j.jgeb.2012.08.001

MgSO4.7H2O 0.2 and Fe2 (SO4)3 0.02; pH, 8; cultivation temperature 55 °C and incubation time 24 h, the enzyme activity measured in the medium was approximately 593 U min-1 ml-1.

© 2012 Academy of Scientific Research & Technology. Production and hosting by Elsevier B.V.

All rights reserved.

1. Introduction

Of all known enzymes, lipases are among the enzymes that have attracted scientific attention. In addition to their natural function of hydrolyzing carboxylic ester bonds, lipases can catalyze esterification, interesterification, and transesterification reactions in nonaqueous media. This versatility makes lipases among the enzymes of choice for potential applications in the food, detergent, pharmaceutical, leather, textile, cosmetic, and paper industries.

Lipases (triacylglycerol acylhydrolase, EC. 3.1.1.3) are serine hydrolases which act at the lipid-water interface on the car-boxyl ester bonds present in triacylglycerol to liberate fatty acids and glycerol. The natural substrates of lipases are long-chain triacylglycerols, which have very low solubility in water. The catalytic triad is composed of Ser-Asp/Glu-His and usually also a consensus sequence (Gly -X- Ser-X- Gly) is found around the active site serine. The three-dimensional (3-D) structures of lipases reveal the characteristic a/b-hydrolase fold [1].

A variety of conditions have been described which stimulate or repress the production of lipolytic enzymes including the type and concentration of carbon and nitrogen sources, pH, aeration, metals ions and temperature of the culture medium.

The optimization of fermentation conditions, particularly physical and chemical parameters are of primary importance in the development of any fermentation process owing to their impact on the economy and practicability of the process. The diversity of combinatorial interactions of medium components with the metabolism of cells as well as the large number of medium constituents necessary for cell metabolism and production do not permit satisfactory detailed modeling. The one-dimensional search with successive variation in variables is still employed, even though it is well accepted that it is practically impossible for the one-dimensional search to accomplish an appropriate optimum in a finite number of experiments. Single variable optimization methods are not only tedious, but also can lead to misinterpretation of results, especially because the interaction between different factors is overlooked [2].

Statistical experimental designs have been used for several decades and it can be adopted at various phases of an optimization strategy, such as for screening experiments or for looking for the optimal conditions for targeted response(s) [3]. Lately, the results analyzed by a statistically planned experiment are better acknowledged than those carried out by the traditional one-variable-at-a-time (OVAT). Some of the popular choices in applying statistical designs to bioprocessing include the Plackett-Burman design [4], and response surface methodology with various designs [5-7].

The main objective of the present study was to isolate and identify a thermophilic bacterial strain that efficiently expresses a desirable thermostable lipase. Non-conventional optimization methods were implemented to maximize the enzyme production.

2. Materials and methods

2.1. Sample collection and isolation of thermophilic bacteria

One gram of forest soil collected from Malaysia was suspended in 50 ml sterile water shacked for 3-4 h and one ml of soil suspension was inoculated into a 250 ml Erlenmeyer flask containing 50 ml of LB broth. The flask was incubated at a temperature of 45 0C with constant shaking at 200 rpm for 24 h. Aliquots of one ml of the grown culture was subsequently transferred into a number of 250 ml Erlenmeyer flask containing 50 ml of LB broth and serially incubated at temperatures 50, 55, 60, 65 and 70 0C for isolation of thermophilic bacteria. A suitable volume (100-400 il) of each culture was spread on LB agar plates and incubated overnight at temperatures in the range 45-70 0C.

2.2. Qualitative screening of lipolytic activity

Pure isolates were screened for lipolytic activity. A 0.2% tribu-tyrin was added to arabic gum dissolved in hot water, emulsified using a homogenizer for 10 min then LB medium (half strength) and 20 g/l agar were added. The purified colonies were allowed to grow in this medium at 45 0C where the positive results are indicated by the formation of halo zones around colony on the tributyrin plates [8].

2.3. DNA extraction and PCR for sequencing of 16S rDNA

DNA was isolated from the experimental bacterium according to [9]. The 16S rDNA gene was amplified by polymerase chain reaction (PCR) using primers designed to amplify the full length (1500bp) of the 16S rDNA gene according to the Esch-erichia coli genomic DNA sequence. The forward primer was 5' AGAGTTTGATCMTGGCTCAG 3' and the reverse primer was 5' TACGGYACCTTGTTACGACTT 3'. The PCR mixture consisted of final concentration: 1x polymerase buffer (10x), 0.2 mM dNTPs-mix (10 mM), 0.2pM of each primer, 0.1 ig template DNA, 2 U DNA-polymerase (Taq), 2mM MgCl2 (25 mM). PCR amplification was performed in a thermal cycler (eppendorf master cycler personal) programmed for one cycle at 95 0C for 5 min followed by 30 cycles each with 1 min at 94 0C for (denaturation), 1 min at 50 0C for (annealing) and 1 min at 72 0C for (elongation). Reaction mixture was then incubated at 72 0C for 10 min for final extension. After completion the PCR reaction, a fraction of PCR was examined using 1% agarose gel according to the method described by [9] and the remnant mixture was manually purified to remove unincorporated nucleotides and excess primer. PCR reaction volume was completed to 100 il with H2O. 10 il of NaCl (5 M) and 200 il isopropanol were added, then mixed and kept at —20 0C for (20-30 min). The tubes were centri-fuged for 20 min at 13,000 rpm, and then the upper layer was carefully removed without disturbing the pellet. The pellet

washed with 250 il of 70% ethanol, then centrifuged at 10,000 rpm for 10 min, the upper layer was carefully removed without disturbing the pellet. The PCR product was air dried and dissolved in (20-25 il) water. DNA sequences were obtained using 3130x DNA Sequencer (Genetic Analyzer, Applied Biosystems, Hitachi, Japan), based on enzymatic chain terminator technique, developed by Sanger [10]. Similarity analysis of the nucleotides or proteins was carried out by BLAST searches against sequences available in GenBank. For phylogenetic tree construction, graphic view and multiple sequence alignments were performed using BioEdit software [11]. ClustalW, version 1.83 with default parameters. On the basis of the result of multiple sequence alignments a phyloge-netic tree was calculated for each nucleotide or protein by applying the maximum-likelihood method implemented in the Tree-Puzzle software, version 5.2 [12].

2.4. Effect of carbon source on lipolytic activity

A pre-culture from the isolated bacterium was prepared by inoculating 50 ml LB and incubation under shaking (200 rpm) for 24 h at 55 0C. Fermentation media with different carbon sources were inoculated with 500 il pre-culture (55 oc, 200 rpm). Samples were taken at different time intervals (24, 48 and 72 h) and analyzed for enzyme activity at pH 7.4 and a temperature of 65 0C.

2.5. The Plackett-Burman design

For screening purpose, various medium components and culture parameters have been evaluated. Based on the Plack-ett-Burman factorial design [13], each independent factor was examined in two levels: —1 for low level and +1 for high level. This is a fraction of a two-level factorial design and allows the investigation of n—1 variables in at least n experiments. Ten independent variables were screened in 12 combinations according to the design shown in the results and discusssion section. The main effect of each variable was calculated simply as the difference between the average of measurements made at the high setting (+1) and the average of measurements observed at low setting (—1) of that factor. All trials were carried out in 250 ml Erlenmeyer flasks containing 50 ml of the medium. Plackett-Burman design is based on the first order model: Y = bo + Yh biXi, where Y is the response (lipolytic activity), b0 is the model intercept, bi is the variable estimate and xi represents the variable. The significance of variables was determined by calculating the p-value through standard regression analysis.

2.6. Response surface methodology (Box-Behnken design)

After estimating the relative significance of independent variables, the most significant three variables were selected for further determination of their optimal level with respect to enzyme activity (U min—:ml—as a response. For this reason Box-Behnken design [14] was applied. This optimization process involves three main steps: performing the statistically designed experiments, estimating the coefficients of the structured mathematical model and predicting the response and checking the adequacy of the model. The effects of sucrose, peptone and soy bean flour on lipase activity were evaluated. Levels of these factors were optimized for maximum lipase

production (the response). In the results and discussion section a 14-trial experimental design, where each variable was tested in three different levels: low (—1), middle (0) and high (+1). These levels (—1,0, +1) correspond to 4, 6.5 and 9 g/L for d-sucrose; 4, 6.5 and 9 g/L for peptone and 4, 6.5 and 9 g/L for soy bean flour, respectively. Once the lipase activity was measured, a second-order polynomial model was fitted to the response data obtained from the design. The polynomial equation is in the following form: Y = P0 + p1Xi + P2X2+ P3X3 + P12X1X2+ P13X1X3 + P23X2X3 + P11X? + P22X^+ P33X^, where Y is the predicted response, P0 is the model constant; X1, X2 and X3 are independent variables; P1, P2 and P3 are linear coefficients; P12, P13 and P23 are cross product coefficients and P11, P22 and P33 are the quadratic coefficients.

2.7. Statistical analysis of data

The data of enzyme activity was subjected to multiple linear regressions using Microsoft Excel 97 to estimate t-value, P-value and confidence levels. The significance level (P-value) is determined using the Students t-test. 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. The simultaneous effects of the three most significant independent factors on each response were visualized using three-dimensional graphs generated by STATISTICA 5.0. All experiments were carried out in triplicates and data represented are their mean values.

2.8. Quantitative estimation of lipolytic activity

The enzyme activity was determined spectrophotometrically (Visible spectrophotometer Novaspec plus/Amersham Biosciences) using p-nitrophenyl laurate from Sigma-Aldrich Chemie GmbH, Germany (0.00814 g dissolved in 1 ml absolute ethanol) as a substrate. All activity measurements were performed in triplicates and expressed as the arithmetic mean of estimations. A 25 il volume of appropriately diluted sample was dissolved in 725 il phosphate buffer (50 mM, pH 7.2). The enzymatic reaction was carried out at 65 0C after addition of 100 il substrate solution (25 mM p-nitrophenyl laurate in absolute ethanol). After 10 min of incubation, a volume of 250 il 100 mM Na2CO3 was added as a stopping reagent and the mixture was centrifuged at 4 oc (10 min 13,000 rpm). The absorbance of liberated p-Nitrophenol was measured at 420 nm. One unit (U) of esterase activity is defined as the amount of enzyme that causes the release of 1 imol of p-Nitro-phenol/min under test conditions [15].

3. Results and discussion

3.1. Sample collection and isolation of thermophilic bacteria

Thirty two bacterial colonies with different morphotypes were observed, selected and purified into separate colonies by streaking method.

3.2. Qualitative screening of lipolytic activity

Thirty two purified colonies of different morphotypes were allowed to grow at 45 0C in screening medium where, the

Figure 1 Phenotypic characterization of investigated bacterium coded AZ1. A: Cell size under scanning electron microscope (7500x), B: Terminal spore and vegetative form of cells (20.000x), C: Section in spore form (50.000x).

Isolate AZ1

■ EU484356 Geobacillus thermodenitrificans strain BCRC 11733

EU477773 Geobacillus sp. F84b - FJ823098 Geobacillus thermodenitrificans strain C24 EF077218 Geobacillus sp. SY-9

— GQ079518 Uncultured bacterium clone nbwl 181c12c1

- AY466707 Geobacillus sp. NS3-1 FN562414 Geobacillus thermodenitrificans isolate G4 I— AB546234 Geobacillus thermodenitrificans JF086490 Uncultured bacterium clone ncd977c04c1

-AB116103 Geobacillus thermodenitrificans strain T1620

AY608974 Bacillus sp. BGSC W9A74 j AY608977 Bacillus sp. BGSC W9A86 ' AY608979 Bacillus sp. BGSC W9A91

AB116102 Geobacillus thermodenitrificans strain T1611 AB116105 Geobacillus thermodenitrificans strain T1630

GQ180110 Bacillus clausii strain DF1 GQ293455 Geobacillus themiodenitrificans strain CMB-A3 JF176900 Uncultured bacterium clone ncd2051g12c2

AJ005760 Bacillus stearothermophilus K1041 GU903484 Geobacillus thermodenitrificans strain HP

1 rïl I

Figure 2 Phylogenetic tree of the selected and identified strain with respect to reference strains based on the 16S rDNA sequences.

positive results are indicated by the formation of halo zones around colony on the tributyrin agar plates. Based on this screening, the isolate coded AZ1 could be classified as a true thermophile as its growth temperature profile ranges between 40 and 65 0C. This isolate was selected among the tested isolates due to its ability to produce lipase at high temperature.

3.3. Phenotypic characterization

Morphological examination of the selected AZ1 isolate revealed the following characteristics: Cells were Gram-positive rods with size ranged from 0.5-0.7 im width and 1.9-2.4 im

length (Fig. 1A). Spore forming microorganism able to form spores terminally, investigation of vegetative and spore forms was performed using electron microscope as represented in Fig. 1 B & C.

3.4. Molecular identification and phylogeny of the selected isolate

The selected isolate was identified by sequencing of the PCR amplified 16S rDNA gene. The product of the PCR was analyzed on 1% agarose gel, purified from the gel and sent for sequencing. The obtained sequence was submitted to the

BLAST in order to find homologies with other relevant 16S rDNA sequences, where it showed 99% similarity to Geobacil-lus thermodenitrificans strain BCRC 11733 (ac: EU484356). The phylogeny of the selected isolate and closely related species was analyzed using the multisequence alignment program and the results are presented in a phylogenetic tree (Fig. 2).

3.5. Evaluation of culture conditions affecting lipolytic enzyme formation by G. thermodenitrificans AZ1

3.5.1. Effect of carbon source on total lipolytic enzyme production by G. thermodenitrificans AZ1

The major factor for the expression of lipase activity has always been carbon source, since many lipases are inducible enzymes [16] and are thus generally produced in the presence of a lipid source such as an oil or other inducers, such as triacylgly-cerols, fatty acids, hydrolyzable esters, tweens, bile salts and glycerol [17-21]. However, their production is significantly influenced by other carbon sources, such as sugars, sugar alcohol, polysaccharides, whey, casamino acids and other complex sources [22,23,18,24,25]. In this experiment the fermentation medium with the following composition (g/L): peptone, 5; yeast extract 2.5; K2HPO4, 1; MgSO4.7H2O, 0.2; pH 8 was separately amended with different carbon sources in a concentration of 5 g/L. The fermentation process was carried out after culturing the tested bacterium in each medium and incubated under shaking conditions 200 rpm at 55 0C where ali-quots were withdrawn for analysis at different time intervals (24-72 h). Among fourteen tested carbon sources, the soluble starch was the best carbon source followed by d-sucrose in terms of lipase activity (Table 1). The maximum lipolytic activities (222.2 and 110 U min-1 ml-1) were attained after 24 h in case of using soluble starch and d-sucrose as carbon source, respectively.

3.5.2. Application of the Plackett-Burman design

Ten independent culture variables were examined. The used basal medium has the following composition (g/L): yeast

Table 3 Randomized Plackett-Burman experimental design for evaluating factors influencing lipase production from G.

thermodenitrificans AZ1.

Trials Independent variables® Lipase activity

A B C D E F G H I J (Umin-1ml-1)b

1 +1 -1 +1 -1 -1 -1 +1 + 1 +1 -1 68.17

2 -1 -1 +1 +1 +1 -1 +1 + 1 -1 +1 55.67

3 -1 +1 -1 -1 -1 +1 +1 + 1 -1 +1 0.00

4 +1 +1 +1 -1 +1 +1 -1 + 1 -1 -1 48.11

5 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 27.52

6 +1 -1 -1 -1 +1 +1 +1 -1 +1 +1 34.56

7 -1 +1 +1 -1 +1 -1 -1 -1 +1 +1 73.58

8 +1 +1 -1 +1 -1 -1 -1 +1 +1 +1 260.49

9 +1 -1 +1 +1 -1 +1 -1 -1 -1 +1 298.40

10 -1 +1 +1 +1 -1 +1 +1 -1 +1 -1 32.85

11 -1 -1 -1 +1 +1 +1 -1 + 1 +1 -1 32.03

12 +1 +1 -1 +1 +1 -1 +1 -1 -1 -1 0.00

-1 = low level and +1 = high level.

a Variables are coded the same as given in Table 6.

b Enzyme activity (Umin-1 ml-1) was determined after 24 h of inoculation.

Table 1 Effect of carbon source on lipolytic enzyme production by G. thermodenitrifican AZ1.

Tested carbon source Total lipolytic activity (U min-1 ml-1)

24 h 48 h 72 h

d-Fructose 83.8 83.5 82.5

d-Glucose 98.6 97.1 83.7

d-Lactose 94.4 92.9 68.1

d-Sucrose 110.0 102.5 90.3

Starch-soluble 222.2 221.4 218.1

Olive-oil 54.2 46.6 48.1

Tween 80 64.4 62.5 64.0

0live/Tween80 59.2 59.1 61.0

Oleic acid 29.6 31.4 18.2

Glycerol 34.8 32.8 34.2

Peanut oil 16.4 12.0 23.1

Nigella oil 19.7 20.0 21.9

Linseed oil 34.3 28.8 31.2

Tributyrin 62.3 61.0 59.2

* Note: the used ratio of mixed carbon source 0.5:0.5%.

Table 2 Media components and test levels for Plackett-

Burman experiment.

Variable code Variable Low level High level

(-1) (+1)

A d-sucrose (g/L) 0 5

B Soluble starch (g/L) 0 5

C Peptone (g/L) 0 5

D Soy bean flour (g/L) 0 5

E Ammonium sulfate (g/L) 0 5

F CaCl2 (g/L) 0.02 0.2

G NaCl (g/L) 0.02 0.2

H Fe2(S04)3 (g/L) 0.02 0.2

I pH 7 8

J Temperature (OC) 45 55

Figure 3 Effect of environmental factors on the lipolytic enzyme activity produced by Geobacillus thermodenitrificans AZ1 after 24 h incubation based on Plackett-Burman design results.

Table 4 Statistical analysis of Plackett-Burman design showing coefficient values, main effect, lipase activity. t- and p-values for each variable on

Variables Coefficients Main effect t Statistics P-value Confidence level (%)

Intercept 77.618 - - - -

d-sucrose 40.672 81.345 37.615 0.016 98.3

Soluble starch -8.443 -16.886 7.808 0.081 91.9

peptone 18.517 37.034 17.125 0.037 96.3

Soy bean flour 35.623 71.246 32.945 0.019 98.1

Ammonium sulfate -36.956 -73.913 34.178 0.018 98.1

CaCl2 -3.290 -6.580 3.0428 0.202 79.8

NaCl -45.739 -91.479 42.301 0.015 98.5

Fe2(SO4)3 -0.203 -0.407 0.188 0.881 11.9

pH 5.998 11.997 5.548 0.113 88.7

Temperature 42.833 85.666 39.613 0.016 98.4

extract, 2.5; K2HPO4, 1.0 and MgSO4.7H2O, 0.2. The independent variables examined and their settings are shown in Table 2. The design matrix along with the corresponding response (lipolytic activity) is given in Table 3.

A wide variation was shown for productivity throughout different trials of the experiment. The variation ranged from 0 to 298.4 Umin-1 ml-1. This reflects the significant effect of medium composition and other environmental conditions on lipase production.

The main effect of examined variables on lipolytic enzyme production was calculated and illustrated graphically in Fig. 3. The sign of a factor estimate indicates, on average, which factor setting results in higher titers. A large estimate, either positive or negative close to zero means that a factor has little or no effect. On the basis of these results; it is conceivable that the lipolytic activity is directly related to d-sucrose, peptone, soy-bean flour, temperature and pH. On the other hand, sodium chloride and ammonium sulfate repressed enzyme activity during the bioprocess. Soluble starch, CaCl2 and Fe2 (SO4)3 slightly repressed lipase/esterase activity.

The regression coefficients, ¿-values, p-values and confidence level percentages for the ten experimental variables are shown in Table 4. The significance level (P-value) was determined using the Students ¿-test. The t test for any individual effect allows an evaluation of the probability of finding the observed effect purely by chance of this probability is sufficiently small, the idea that the effect was caused by varying the level of the variable under test is accepted.

Table 6 Box-Behnken factorial experimental design, repre-

senting the response of lipolytic activity as influenced by

d-sucrose, peptone and Soy bean flour.

Trials d -sucrose Peptone Soy bean flour Total lipolytic

activity (U min ml )

1- 1 -1 0 303.79

2 1 -1 0 277.12

3- 1 1 0 162.96

4 1 1 0 270.37

5 - 1 0 -1 238.70

6 1 0 -1 265.18

7- 1 0 1 252.77

8 1 0 1 253.42

9 0 -1 -1 271.57

10 0 1 -1 176.38

11 0 -1 1 393.70

12 0 1 1 452.22

13 0 0 0 610.37

14 0 0 0 599.25

Table 5 The levels of variables chosen for the Box-Behnken optimization experiment.

Variables Variable code -1 0 + 1

d-sucrose (g/L) X1 4 6.5 9

Peptone (g/L) X2 4 6.5 9

Soy bean flour (g/L) X3 4 6.5 9

Figure 4 Three dimensional graphs showing the surface response as affected by culture variables during production of lipolytic enzymes by Geobacillus thermodenitrificans AZ1.

From the confidence level of the variables, it was apparent that d-sucrose, peptone and soy bean flour were the most significant variables increasing lipase production. On the contrary, sodium chloride and ammonium sulfate showed high significant negative effect. According to these results, a medium of the following composition is expected to be near optimum (g/L): d-sucrose, 5; peptone, 5; soy bean flour, 5; Fe2 (SO4)3, 0.02; CaCl2, 0.02; yeast extract, 2.5; K2HPO4, 1; MgSO4.7H2O, 0.2; pH 8; temperature, 55 0C and incubation time 24 h. The enzyme activity measured in the medium was 261.481 Umin^mP1.

3.5.3. Optimization of the culture conditions by Box-Behnken experimental design

A second multi-factorial experiment was applied according to the Box-Behnken design (a response surface methodology) to find out the optimum level of each of the most significant independent variables to bring out maximum production of lipo-lytic enzyme. Each of the three factors of highest influences as elucidated through the Plackett-Burman experimental design including d-sucrose (X1), Peptone (X2) and Soy bean flour (X3) was examined at three different levels coded —1,0, +1 (Table 5). The 14 different examined combinations are shown in (Table 6), where all cultures were performed in triplicate and the average of the observations was used. The experimental results were introduced in the form of surface plots (Fig. 4), where it showed that 0.025, —0.056 and 0.168 levels of peptone, d-sucrose and soy bean flour support high lipase activity. For predicting the optimal point, within experimental constrains, a second-order polynomial function was fitted to the experimental results (non-linear optimization algorithm) of lipase activity: Y = 604.8 + 13.5X: + 23X2 + 50X3 + 33.5 XiX2 — 6.5XiX3 — 38.4X2X3 + 211.1X1 — 140.2X2 — 41.2X2, where X!, X2, and X3 are the levels of d-sucrose, peptone and soy bean flour, respectively. At the model level, the correlation measures for the estimation of the regression equation are the multiple correlation coefficients R and the determination coefficient R2. The closer the value of R is to 1; the better is the correlation between the measured and the predicted values. In this experiment, the value of R was 0.957 for 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: d-sucrose 6.562 g/L, peptone 6.359 g/L and soy bean flour 6.922 g/L, with a predicted activity of 609.855 U min—1 ml—1. The formula of the optimized medium in (g/L) is as follows: d-sucrose, 6.562; peptone, 6.359; soy bean flour, 6.922; CaCl2, 0.02; yeast extract, 2.5; K2HPO4, 1.0; MgSO4.7H2O, 0.2; Fe2(SO4)3, 0.02; pH 8; cultivation temperature 55 0C and incubation time 24 h. The enzyme activity measured in a verification experiment using this medium was 592.59 U min—1 ml—1.

Acknowledgement

Authors would like to acknowledge the Science and Technology Development Funds (STDF) for their funding the present work which located within the frame of grant number 247.

References

[1] M. Nardini, B.W. Dijkstra, a/p Hydrolase fold enzymes: the family keeps growing, Curr. Opin. Struct. Biol. 9 (1999) 732-737.

[2] G.Q. He, Q.H. Chen, X.J. Ju, N.D. Shi, Improved elastase production by Bacillus sp. EL31410—further optimization and kinetics studies of culture medium for batch fermentation, J. Zhejiang Univ. Sci. 5 (2) (2004) 149-156.

[3] G.E.P. Box, D.W. Behnken, Some new three level designs for the study of quantitative variables, Technometrics 2 (1960) 455475.

[4] C. Liu, Y. Liu, W. Liao, Z. Wen, S. Chen, Application of statistically based experimental designs for the optimization of nisin production from whey, Biotechnol. Lett. 25 (2003) 877882.

[5] Y.R. Abdel-Fattah, Optimization of thermostable lipase from a thermophilic Geobacillus sp. Using Box-Behnken experimental design, Biotechnol. Lett. 24 (2002) 1217-1222.

[6] Y.R. Abdel-Fattah, Z.A. Olama, L-Asparaginase production by Pseudomonas aeruginosa in solid-state culture: evaluation and optimization of culture conditions using factorial designs, Proc. Biochem. 38 (2002) 115-122.

[7] Y.R. Abdel-Fattah, H.A. El-Enshasy, N.A. Soliman, H. El-Gendi, Bioprocess development for production of alkaline protease by bacillus pseudofirmus Mn6 through statistical experimental designs, J. Microbiol. Biotechnol. 19 (4) (2008) 378-386.

[8] R.C. Lawrence, T.F. Fryer, B. Reiter, Rapid method for the quantitative estimation of microbial lipases, Nature, London 213 (1967) 1264-1265.

[9] J. Sambrook, E.F. Fritsch, T. Maniatis, Molecular cloning, A Laboratory Manual Cold Spring Harbor Laboratory, NY, 1989.

[10] F. Sanger, S. Nicklen, A.R. Coulson, DNA sequencing with chain terminating inhibitors, Proc. Natl. Acad. Sci. USA 74 (1977) 5463-5467.

[11] Hall TA (1999). BioEdit:a user-friendly biological sequence alignment editor and analysis program for windows 95/98/ NT.Nucl.Acids.Symp.Ser., 41:95-98.

[12] R D M. Page, TREEVIEW: An application to display phylogenitic trees on personal computers, Comput. Appl. Biosci. 12 (1996) 357-358.

[13] R.L. Plackett, J.P. Burman, The design of optimum multi-factorial experiments, Biometrika 33 (1946) 305-325.

[14] G. Box, D. Behnken, Some new three-level designs for the study of quantitative variables, Technometrics 2 (1960) 455-475.

[15] P. Becker, I. Abu-Reesh, S. Markossian, G. Antranikian, H. Markl, Determination of kinetic parameters during continuous cultivation of the lipase-producing thermophile Bacillus sp. IHI-91 on olive oil, Appl. Microbiol. Biotechnol. 48 (1997) 184-190.

[16] M. Lotti, S. Monticelli, J.L. Montesinos, S. Brocca, F. Valero, J. Lafuente, Physiological control on the expression and secretion of Candida rugosa lipase, Chem. Phys. Lipids 93 (1998) 143148.

[17] P.K. Ghosh, R.K. Saxena, R. Gupta, R.P. Yadav, W.S. Davidson, Microbial lipases: production and applications, Sci. Prog. 79 (1996) 119-157.

[18] S. Dharmsthiti, J. Pratuangdejkul, G.T. Theeragool, S. Luchai, Lipase activity and gene cloning of Acinetobacter calcoaceticus LP009, J Gen. Appl. Microbiol. 44 (1998) 139-145.

[19] S.H. Shirazi, S R. Rehman, M.M. Rehman, Short communication:production of extracellular lipases by Saccharomyces cerevisiae, Microbiol. Biotechnol. 14 (1998) 595-597.

[20] S. Bradoo, R.K. Saxena, R. Gupta, Two acidothermotolerant lipases from new variants of Bacillus spp, Microbiol. Biotechnol. 15 (1999) 87-91.

[21] P. Rathi, R.K. Saxena, R. Gupta, A novel alkaline lipase from Burkholderia cepacia for detergent formulation, Process Biochem. 37 (2001) 187-192.

[22] E.J. Gilbert, J.W. Drozd, C.W. Jones, Physiological regulation and optimization of lipase activity in Pseudomonas aeruginosa EF2, J. Gen. Microbiol. 137 (1991) 2215-2221.

[23] P. Lotrakul, S. Dharmsthiti, Lipase production by Aeromonas sobria LP004 in a medium containing whey and soybean meal, World J. Microbiol. Biotechnol. 13 (1997) 163-166.

[24] E.H. Ghanem, H.A. Al-Sayeed, K.M. Saleh, An alkalophilic thermostable lipase produced by a new isolate of Bacillus alcalophilus, J. Microbiol. Biotechnol. 16 (5) (2000) 459464.

[25] N. Rashid, Y. Shimada, S. Ezaki, H. Atomi, T. Imanaka, Low temperature lipase from psychrotrophic Pseudomonas sp. Strain KB700A, Appl. Environ. Microbiol. 67 (2001) 40644069.