1.0 INTRODUCTION:

A vast number of microbial EPSs were reported over the last decades, and their composition, structure, biosynthesis and functional properties have been extensively studied. In recent years the increased demand for natural polymers for potential commercial importance as fructose sweetener, thickening agent in food industry, antitumor agent ^{1, 2}and pharmaceutical applications led to a remarkable interest in polysaccharides produced by microorganisms. The amount of the levan produced is not equal to the other biopolymers such as dextran and xanthan³. This is mainly due to the inefficiency of the producer organism. Among many levan producing organisms, Takahashi strain is the most efficient levan-producing strain among all of the B. subtilis strains tested; it produced the highest yield of levan in the least time (21 h) under the common cultivation condition⁴.

The best conversion yield of the saccharose into levan using the Bacillus subtilis DSM 347 strain were achieved using a 15% (w/v) addition of saccharose and culturing temperature of 37°C ⁵. Six Bacillus strains were isolated from different honey sources showed antiviral activity against highly pathogenic avian influenza HPAI, H5N1and adenovirus type 40⁶.

Surfactants have been used in biotechnological processes to improve the production of number of biomolecules produced by fermentation^7. Proposed mechanisms for increased production of biomolecules in presence of surfactants are increased cell membrane permeability, change in lipid metabolism and stimulation of the release of bio molecules⁸. Response surface methodology (RSM) is a versatile method applied in the optimization of medium constituents and other critical variables responsible for the production of bio molecules⁹. Statistical optimization has the advantage of less time consuming and avoid the erroneous interpretation occurred in one factor at a time optimization^10,11.

The objective of the present study was to produce the levan by bacillus subtilis and to optimize the variables like surfactant concentration, pH and temperature for levan production using response surface methodology.

2.0 MATERIALS AND METHODS:

Organism and culture conditions: The B.subtilis strain obtained from M K University. The culture organism was grown on the agar plates with the defined medium containing (g/l): glucose -100, beef extract -1, yeast extract -2, peptone -5, sodium chloride -5, citric acid -11.7, sodium sulfate-4, yeast extract-4.2, ammonium chloride-5, potassium chloride- 4.62, magnesium chloride-4.1, manganese chloride-5.43, ferric chloride- 4.19, zinc chloride- 0.21.The strain was routinely grown at 28 degree for 48 hours. In batch fermentation, the glucose was replaced with saccharose (100g/l).

Batch fermentation:

Batch fermentation was carried out at 37⁰C with 50ml fermentation medium in 250 ml Erlenmeyer flask, inoculated with 10% v/v of seed culture. The culturing process was carried out in aerobic conditions for 96 h. Samples were collected at every 12h of fermentation process (a 96 hour period) to determine the following parameters ¹², The biomass was determined in a spectrophotometer based on 660 nm a calibration curve ¹³. The produced levan was extracted from the fermented medium and its dry weight determined ¹⁴. Cell growth yield (Y_X/S) and Levan yield (Y_P/S) and specific growth rate was determined from the specific growth data curve. Sucrose determination was performed through dosage of total reducing sugars in each sample using the 3, 5-dinitrosalicilic acid colorimetric method after acid hydrolysis ¹⁵. Levan production was the same composition of pre fermentation medium was taken. To that 0.5g/l of the surfactants namely Tween 40, Tween 80 and Triton X-100 were used for this study. The surfactants at measured concentration of 0.5g/l were added to the medium during 0 ^th and 24 ^th hr and the process was carried out for 60 hrs. . After the fermentation period, the broth was analyzed for biomass determination and isolation of levan as given above. Control process without surfactant was also carried out to compare the results

Optimization using design for levan production:

The levan production medium was the same composition of the pre-fermentation medium, differing in concentration of surfactants, pH of the medium and the incubation temperature values. Three components were selected (Table 1) showed the design matrix for the factorial experiment, including the central point, used to study the influence of 3 factors on levan production by B. subtilis. The batch fermentations were carried out batch wise in 250 mL Erlenmeyer flasks containing 50 mL of fermentation medium, placed on orbital shaker at10000 rpm under room temperature, during 24 h period.

Experiments were designed by using Minitab statistical software package. The effect of three variables (surfactant concentration, pH and temperature) on the production of levan was studied using a central composite design at five experimental levels: –a, –1, 0, +1, +a where a = 2^n/4, n is the number of variables and 0 corresponds to the central point. The experimental levels for these variables were selected from our preliminary work, which indicated that an optimum could be found within the level of parameters studied. The levels of factors used for experimental design are given in (Table 1). The actual level of each factor was calculated by the following equation ^16:

Actual level – (high level + low level)/2

Coded value = --------------------------------------------------

(high level – low level)/2

Twenty experiments were carried out each at five levels (Table 2). levan concentration was analyzed by using a second order polynomial equation and the data were fitted in to the equation by multiple regression procedure. The model equation for analysis is given below:

Y = β₀ + β₁X₁ + β₂X₂ + β₃X₃ + β₁₁X₁² + β₂₂X₂² + β₃₃X₃² + β₁₂X₁X₂ +

β₁₃X₁X₃ + β₂₃X₂X₃

Where X₁, X₂ and X₃ are the levels of the factors and β₁, β₂, β₃ - linear coefficients, β_11,β_22,β₃₃– quadratic coefficients, β₁₂, β₁₃, β₂₃ are interactive coefficient estimates with β₀ having a role of a scaling constant.Analysis of Variance (ANOVA), regression analysis was done and contour plots were drawn by using Minitab package.

Table1. Level of factors used in the experimental design for optimization of levan production by B. subtilis with Tween 80

Factor	Name	Levels
Factor	Name	-a	-1	0	+1	+a
X₁	Tween 80	0.25	0.50	0.875	1.50	1.925
X₂	pH	4.40	5.50	7.00	8.50	9.520
X₃	Temperature	18.18	25.00	35.00	45.00	51.00

3.0 RESULTS:

Batch kinetics:

The time course data on biomass, levan production and saccharose consumption by Bacillus subtilis during levan fermentation by B.subtilis is shown in Fig 1. Levan was produced during growth as well as stationary phase and was found to be both growth as well as non-growth associated. Levan production has increased from 1.5g/l to 60 33.5 g/l and biomass 1.45 to 13.2 g/l from 0 to 60 hrs (Fig 1).

A plot of the natural logarithm of biomass concentration against time yielded a straight line and the slope of which was equal to maximum specific growth rate (µ_max). Maximum specific growth rate of 0.459h^-1 was obtained from the batch fermentation in shake flask culture .Cell growth yield (Y_X/S) and Levan yield (Y_P/S) was determined from the growth data at the exponential phase. Cell growth yield and Levan yield of 0.13g biomass/g of saccharose and 0.335g Levan/g of saccharose were obtained respectively from shake flask culture.

Fig1. Batch kinetics of levan fermentation by B.subtilis in shake flask culture

Effect of non-ionic surfactants on biomass, levan production:

Among the three non-ionic surfactants tested, Tween 80 gave the highest yield at 48.8g/l followed by Tween 40 and Triton X-100 at 39.8g/land 42.2g/l respectively compared to control fermentation without surfactant at 33.5g/l . Biomass was also found to increase by addition of surfactants. Fermentation with Tween 80 produced higher cell biomass at 25.18g/l and that with Tween 40 and Triton X-100 was 15.54g/l and 17.96g/l respectively is shown in Fig2.

Fig 2: Effect of various non-ionic surfactants on levan production by Bacillus subtilis

Experimental design and statistical analysis:

Optimization of process variables using central composite design:

Response surface methodology using central composite design was applied to optimize the concentration of significant variables for design experiments. Twenty experiments were carried out from the design and the experimental values are given in (Table 2), along with predicted values of the model. By applying multiple regression analysis on the experimental data, the following second order polynomial equation was found to explain levan production by B.subtilis.

Y = -207.263 + 46.3921X₁ + 47.4545X₂ –- 4.46380X3 –- 25.6162X₁² –- 3.36132X₂² –- 0.0637010X₃² + 0.443333X₁X₂

Regression analysis of the experimental data showed surfactant concentration, temperature and pH had positive linear effect on levan production (P<0.05). Tween 80, pH and temperature had a strong positive linear effect on the production of levan (P< 0.05) as evidenced from positive linear coefficients. These parameters also exhibited significant negative quadratic effects indicating that levan production increased the level of these factors increased and decreased as the level of these parameters increased above certain levels. Interaction between these parameters was also significant.

ANOVA (Table 3) gives the value of the model and can explain whether a more complex model is required for a better fit. If the F- test for the model is significant at the 5% level (P < 0.05), then the model is fit and can adequately account for the variation observed. If the F- test for lack of fit is significant (P < 0.05), then a more complicated model is required to fit the data. The closure the value of ‘R’ (multiple correlation coefficient) to 1, the better the correlation between the observed and predicted values. In this study, the value of R (0.9997) and P value for lack of fit (0.617) indicate that the experimental data obtained fit well with the model and explains the effect of Tween 80 concentration, pH and temperature on levan production.

The T-value (Table 4) indicates how large the coefficient is in relationship to its standard error and was calculated by dividing each coefficient by its standard error. As given in Table 4, Tween 80, pH and temperature had a strong positive linear effect on the production of levan (P< 0.05) as evidenced from positive linear coefficients. These parameters also exhibited significant negative quadratic effects indicating that levan production increased the level of these factors increased and decreased as the level of these parameters increased above certain levels. Interaction between these parameters was also significant.

Figures 3.0 4.0, 5.0 show the contour plots ,surface and optimized plot of levan production for each pair of parameters by keeping the third factor constant at its middle level. Maximum levan was produced at middle level of each pair of factors at a constant middle level of the third factor. Further increase in these factors above the middle level showed decrease in levan production. In order to determine the optimum levels of Tween 80 concentration, pH and temperature for levan production the experimental data were fitted in to equation and the optimum values were: Tween 80 - 0.875g/l, pH-7.0 and temperature 35 °C. Maximum levan production of 59g/l was obtained (Predicted- 62.139 g/l).

Table 2: Experimental design of process variables (Surfactant concentration, pH, Temperature) for the production of levan with Tween 80

Run order	Tween 80(g/l)	pH	Temperature	Levan(g/l)
Run order	Tween 80(g/l)	pH	Temperature	Theoretical	predicted
1	0.875	7.0	35.0	58.860	62.139
2	1.500	5.5	25.0	37.480	42.739
3	0.250	7.0	45.0	31.250	62.139
4	0.875	5.5	35.0	58.840	62.139
5	1.500	8.5	45.0	37.622	42.739
6	0.875	7.0	35.0	58.690	62.139
7	0.875	7.0	35.0	59.000	62.139
8	0.875	7.0	51.8	39.150	44.210
9	0.250	8.5	25.0	33.054	35.968
10	0.875	9.5	35.0	38.560	42.750
11	0.875	7.0	35.0	58.385	62.139
12	1.500	8.5	25.0	39.700	42.631
13	0.250	8.5.0	45.0	31.020	36.068
14	0.050	7.0	35.0	37.800	40.824
15	0.875	7.0	35.0	58.890	62.139
16	0.875	7.0	18.5	43.120	44.690
17	0.875	4.5	35.0	37.036	39.148
18	1.900	7.0	35.0	36.445	39.982
19	1.500	5.5	45.0	36.150	39.536
20	0.250	5.5	25.0	32.457	34.437

Table 3: Analysis of Variance (ANOVA) for levan production with Tween 80

Source	DF	Seq SS	Adj SS	Adj MS	F	P
regression	9	2241.78	2241.78	249.086	6047.65_a	0.000
linear	3	46.06	111.84	37.281	905.16	0.000
square	3	2194.02	2194.02	731.340	177756.44	0.000
interaction	3	1.70	1.70	0.565	13.72	0.001
Residual Error	10	0.41	0.41	0.041
Lack-of-Fit	5	0.18	0.18	0.035	0.76_b	0.617
Pure Error	5	0.23	0.23	0.047
Total	19	2242.19

Fig3: Counter plots

Fig 4: Surface plots

Fig5: Optimized plot

Table 4: Estimated Regression Coefficients for levan production with Tween 80

Term	Coeff	SE coeff	T	P
Constant	58.7914	0.08195	717.394	0.000
Surfactant concentration	2.8438	0.05840	48.697	0.000
pH	0.4868	0.05840	48.697	0.000
Temperature	-0.9007	0.05515	-16.331	0.000
Tween80*Tween80	-10.0063	0.06347	-157.659	0.000
pH*pH	-7.5630	0.05400	-140.053	0.000
Temperature*temperature	-6.3701	0.0540	-117.785	0.00
Tween80*pH	0.4156	0.07175	5.792	0.00
Tween80*Temperature	-0.0209	0.07175	-0.291	0.777
pH*Temperature	-0.1969	0.07175	-2.744	0.021

4.0 DISCUSSION:

During levan production, there was initial lag phase of 6 hr after which exponential phase started and continued till 48^th hr after which growth ceased. Cell growth showed distinct exponential phase followed by stationary phase but levan was produced throughout the fermentation. Maximum levan production of 33.5g/l was achieved using 10% (w/v) addition of saccharose and culturing temperature of 37°C. Experiments performed with Bacillus subtilis DSM 347 strain showed the best conversion yield of saccharose into levan were using a 15% (w/v) addition of saccharose and culturing temperature of 37°C ¹⁷. Takahashi strain is the most efficient levan-producing strain among all of the B. subtilis strains tested; it produced the highest yield of levan in the least time (21 h) under the common cultivation condition. After cultivation for 21 h, 40-50 mg of levan was produced in medium containing 20% (w/w) sucrose, which was approximately 50% yield on available fructose¹⁸.

The mechanism by which the surfactants improve the levan production may be that they affect mass transfer either by changing the surface film resistance or the hydrodynamics. The action of the surfactant could be by interacting with the bacterial cell membrane in a way that would enhance the polymerization process of the levan molecule and/or by the facilitation of the release of the polymer from the membrane ¹⁹. It can be inferred from the results that Tween 80 showed higher impact on exerting these mechanisms than the other two non-ionic surfactants tested. Similar kind of results were obtained for xanthan production by Xanthamonas campestris where Triton X-100 showed maximum production of about 1.45 fold at 0.5g/l than fermentations carried out by the addition of non-ionic surfactants Tween 40, Tween 80 and CHAPS. Increased production of glutathione with ionic and non-ionic surfactants where about 50% increase in production was observed than the control fermentation without surfactants²⁰, increased production of glutathione by Saccharomyces cervisiae.

Response surface methodology was applied in screening the process parameters that influence the exopolymer production. About 20 experiments was created involve three variables factors which are temperature, pH, surfactant concentration. Based on the results obtained in the form of analysis of variance (ANOVA) of 2-level factorial design model, the significant values of pH, Temperature and surfactant concentration were found.

5.0 CONCLUSION:

Kinetic studies of Levan fermentation in shake flask resulted maximum biomass of 13.23g/l. Maximum levan production of 33.5g/l was observed. Maximum specific growth rate of 0.459 h^-1was obtained in shake flask fermentation. Higher cell growth, Levan production and growth and Levan yield were obtained from the shake flask fermentation due to pH control. Non-ionic surfactants when added to the fermentation medium in the shake flask improved the levan production at 0.5g/l. Tween 80 increased the levan production by 48.8% more than the control fermentation followed by Tween 40 and Triton x 100 at 26% and 19% increase respectively. Central Composite Design was successfully applied to determine the optimum concentration of Tween 80, pH and temperature of the process. Optimum level of factors were: Tween 80 – 0.875 g/l, pH- 7.0and temperature 37°C and at these optimum levels levan production of 59g/l was obtained. (Predicted- 62.139 g/l).Thus the strategies have been applied successfully in this work to enhance the levan production under specified conditions.

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Received on 19.09.2013 Accepted on 29.09.2013

Asian J. Pharm. Tech. 2013; Vol. 3: Issue 4, Pg 149-154