Statistical Optimization of Alkaline Levan Production using Bacillus subtilis

 

J. Niranjan, Fazal Basha, G. Suganya, M. Anil Kumar, M. Seenuvasan, S. Selvanaveen*

Department of Biotechnology, Madha Engineering College, Chennai.

 

ABSTRACT:

The industrially used biopolymer levan as an emulsifying agent was produced in large amounts by optimizing the physical parameters like pH, temperature and incubation time, with the central composite design under the response surface methodology where the maximum yield of levan was found to be 268 µg/ml at a pH of 8.0, a temperature of 20°C and the incubation period of 24^th h. The pH- and thermal stabilities of levan-forming activity were studied and arrived at the maximum activity at pH 7.0 and at 20°C respectively, thereby inferring that the levan is optimally produced by Bacillus subtilis in an alkaline environment. Scanning electron microscope was used to examine the surface morphology levan-producing Bacillus subtilis that showed the levan polymer as white dust-like particles.

 

INTRODUCTION:

Levan is a homopolysaccharide composed of D-fructofuranosyl residues with the molecular weight of about 10⁷ Da, corresponding to approximately 60,000 fructose units and being used as a functional biopolymer in feeds, food, cosmetics, and pharmaceutical and chemical industries¹. Levan production bears a considerable economical interest, and the major applications correspond to the pharmaceutical and food industries².

Levan is commercially used as an emulsifier, formulation aid, stabilizing thickener, surface-finishing agent, encapsulating agent and a carrier for colour or flavours in the food industry ³. Several microorganisms, viz. Bacillus subtilis, Bacillus stearothermophilus, Aerobacter levanicum, Streptococcus salivarius, Pseudomonas aurantiaca, Erwinia herbicola, Rahnella aquatilis, Pseudomonas syringae, Zymomonas mobilis and Bacillus megatrium are capable of producing levan of high molecular weight when grown in sucrose media. The enzymatic production of levan from a recombinant Escherichia coli and over expressing cloned levan sucrase gene of Z. mobilis has been reported ⁴.

 

Levan with varying molecular weights, exhibits antitumor activity against sarcoma-180 cells ^5-7 and acts as a  hypocholesterolemic agent  in blood ^{8, 9} and increases bifidobacteria population in the intestinal tract ¹⁰.

 

Several authors have critically emphasized the importance of biochemical and medium optimization strategies for levan production ^{8, 11}. However, there are some limitations for the industrial applications of levan due to its weak chemical stability in solution and the complex process required to purify levan. Once the limitations are overcome, the market for levan will gradually increase in the various fields. In recent years, microorganisms have been genetically manipulated for the biotechnological production of biopolymers with tailored properties suitable for high-value medical application such as tissue engineering and drug delivery and for use in the food and biotechnology industries ¹².

 

The objective of this study was to culture Bacillus subtilis, purify its metabolic end product ‘levan’ and study its optimization and characterization.

 

MATERIALS AND METHODS:

Microorganisms and Culture Conditions:

A producer organism (bacterial species), was isolated from soil by serial dilution. The sample dilutions were spread-plated in Nutrient agar plates and incubated at room temperature for 24 h. Periodic subculturing of the clear sticky white bacterial colonies identified was done for its enrichment. In addition, the morphological and standard biochemical tests ¹² of gram staining, starch agar plate, catalase test, etc. were carried out for its identification (Results not shown). The identified Bacillus subtilis was grown in RM medium containing (g/l) Glucose, 20; Sucrose, 20; Yeast extract, 10; and KH₂PO₄, 2 at 30°C, pH 6.0 and 150 rpm ¹².

 

Shake Flask Experiment:

2 ml of 24 h aged inoculum was added to 100 ml of specific growth media in a 250ml Erlenmeyer flask at 150 rpm. Periodically, cell count and absorbance were taken to analyze the cell growth, and several experiments were carried out to check the enzyme activity under varying ranges of parameters like pH (5.0, 7.0, 9.0), temperature (10, 20, 30˚C) and incubation time (20, 24, 28 h) ¹³.

 

Assay Procedure:

25 ml of harvest sample was centrifuged at 5000 rpm for 10 min. This supernatant was used as the enzyme (levansucrase) source. The reaction mixture [500 µl of enzyme extract and 500 µl of 1M sucrose in acetate buffer (50mM, pH 5)] was incubated at 30°C for 30 min for determining the reducing sugar concentration by Nelson-Somogyi method ¹⁴. One unit of enzyme activity was related to the amount of enzyme required to release 1 µmol of reducing sugar in 1 min under the experimental conditions. Also, the reducing sugar concentration was determined using GOD kit method ¹⁵. The amount of levan produced was estimated by incubating the reaction mixture at 30°C for 2 h. 0.5 ml of reaction mixture was mixed with 1.5 ml of methanol and stirred vigorously. The turbidity was measured immediately at 540 nm. The amount of levan produced was calculated using the standard levan graph. One unit of levan-forming activity was related to the amount of enzyme required to produce 1 µg of levan in 1 min under the experimental conditions ¹².

 

Central Composite Experimental Design to Optimize the Physical Parameters:

The central composite design (CCD) under the response surface methodology (RSM) was employed in order to illustrate the nature of the response surface in the experimental design and elucidate the optimal conditions of the most significant independent variables ¹⁶. In this analysis, the initial pH, temperature and incubation period were chosen as independent variables and the levan product formation was obtained as a dependent output response variable shown in Table I.

 

Table 1 Experimental levels and factors of the independent variables

Independent variables	Design variables	Range and levels
		-1	0	+1
pH	A	6	7	8
Temperature (˚C)	B	10	20	30
Incubation time (h)	C	20	24	28

 

In order to study the combined effects of these variables on the responses, 20 sets of experiments with appropriate combinations of initial pH, temperature and incubation period were conducted using statistical method. The first independent variable (initial pH) was varied over 2 levels (6.0 and 8.0) relative to the central point (pH 7.0), the second independent variable (temperature) was varied over two levels (10 and 30˚C) relative to the central point (20˚C) and the third independent variable (incubation period) was changed over two levels (20 and 28 h) relative to the central point 24 h. The full factorial central composite design matrixes of these three variables with respect to their uncoded and coded values were listed in Table II. The numerical and graphical analysis for the responses of levan product formation was done using the software MINITAB 14.

 

Evaluation of the goodness of fit of the model was done through coefficient determination and analysis of variance (ANOVA). The experimental results were fitted to a second order polynomial equation;

 

where, Y is the dependent variable (levan production); A, B and C are the independent variables; β₀ is the regression coefficient at central point; β₁, β₂ and β₃ are the linear coefficients; β₁₁, β₂₂ and β₃₃ are the quadratic coefficients and β₁₂, β₁₃ and β₂₃  are the second order interaction coefficients. The developed regression model was evaluated by analyzing the values of regression coefficients, ANOVA, and p- and F-values. The quality of fit of the polynomial model equation was expressed by the coefficient of determination, R². The statistical software package was used to identify the experimental design as well as to generate a regression model to predict the optimum combinations considering the effects of linear, quadratic and interaction on levan production. A final experiment was conducted to validate the CCD model developed.

 

Purification of Levan:

A few millilitres of harvested sample were centrifuged at 5000 rpm for 10 min. 1 ml of supernatant was mixed with 4 ml of methanol, to find a white precipitate which is levan. This precipitate was again mixed with methanol at different concentrations to get levan purified and then it was filtered and dried.

 

Characterization of Purified Levan:

The stability of levan was studied under different parameters such as pH and temperature by incubating the purified levan with varying pH values ranging from 5.0 to 9.0 using carbonate buffer (0.1 M). The polymer samples were added to 1 ml of the buffer, incubated at 37°C for 5 min and assayed to check the activity. The thermal stability of levan was analyzed by incubating at 10-20° C for 5 min

 

 

 

Table 2 Central composite design consisting of 20 experimental runs and the study of 3 experimental factors:

 

RESULTS AND DISCUSSION:

Response Surface Estimation:

The need to ensure the effectiveness of enriched production of levan with growing cells of Bacillus subtilis has stimulated the interest to use mathematical models predicting microbial behaviour. The objective of this study was to investigate the combined effects of the initial pH, temperature and incubation time period (independent variables) and to optimize for the maximum yield of levan. Experiments were carried out as per the design matrix of CCD, and the average levan yield (dependent variables) obtained from the culture was used as response. The following second- order quadratic equation was used to fit the experimental values of the activity to estimate the response.

 

Levan Production (µg/mL) = -1955.82-478.51A+20.155B+277.82C+37.64A²-0.364B²-5.273C²-1.05AB-0.625AC-0.063BC               (2)

 

Where; A= pH, B= temperature (˚C) and C= incubation time (h).

 

The experimental and predicted values of levan product formed were agreed very well when analyzed in MINITAB 14 (Table 3) where levan-forming activity was the response i.e. the levan concentration expressed in logarithmic values and A, B and C were the coded values of the variables (pH, temperature and incubation time).

 

Table 3 Experimental and predicted values of levan-forming activity

ANOVA was carried out for the results of quadratic model for the levan production as shown in the Table 4. The associated probability > F value for the model (0.000 for levan production) was lower than 0.05.

 

At the model level, the correlation measure for the estimation of the regression equation was the determination coefficient R². The correlation between the experimental and predicted values was better when the value of R² was closer to 1.0. In this experiment, the value of R² for levan production was 0.976. These values indicate a high degree

 

of correlation between the experimental and predicted values. The value of R² indicates that 97.6% of the variables: pH, temperature and incubation time period contribute very positively to the responses. The value of R² was also a measure of fit of the model and it could be mentioned that only about 2.4% of the total variations was not explained by the levan production ¹⁷. Linear and quadratic effects of parameters were significant, meaning that they could act as limiting factors and little variation in their concentration would alter either the growth rate or the product formation rate or both to a considerable extent ¹⁹.

 

 

Table 4 Analysis of Variance (Anova) for Quadratic Model for Levan Production:

The 3D response surface plots (Fig.1-3) are the graphical representations of the regression equation used to determine the optimum values of the variables within the ranges considered. The main target of response surface is to hunt efficiently for the optimum values of the variables such that the response is maximized ²⁰. An elliptical response surface in the entire region was found from the second order quadratic equation for the higher levan production with the interaction of the independent variables. Further, these three dimensional plots were easier as convenient means for optimizing the variables.

 

Fig.1Response surface plot showing the effect of temperature and time on the levan yield

 

Fig.2Response surface plot showing the effect of pH and incubation time on the levan yield

The maximum amount of levan produced through the experiment was found to be 268 µg/ml. This value is nearly equal to the predicted value (254.982 µg/mL) of levan yield. Thus, the maximum yield of levan was found to be 268 µg/ml at a pH of 8.0, a temperature of 20°C and incubation time period of 24 h. As a result, it could be said that RSM was used successfully as a fast and error-free approach for the optimization of parameters for production of levan with respect to the parameters of the variants of pH, temperature and incubation time. Besides, the interaction study between these components provided an additional advantage of employing RSM.

 

pH Stability of Levan- Forming Activity:

It has been noted that the important characteristic of most microorganisms is their strong dependence on the extracellular pH for cellular growth and enzyme production. The results on the effect of pH on levan-forming activity are presented in Fig. 4. The pH kinetics of the levan-forming activity revealed that the activity increased from pH 7.0 to pH 9.0 and below which it decreased. The optimum pH recorded was 7.0 for maximum activity. It was determined that the levan formation was active at a broad pH range of 7.0-9.0.

 

Fig. 4  Effect of pH on levan-forming activity.

 

Thermal Stability of Levan-Forming Activity:

The results of the studies on the effect of the temperature on levan-forming activity are presented in Fig. 5. Its activity was ascending up to 20ºC and increased sharply at 20ºC and descended thereafter. Thus the temperature kinetics of the enzyme produced by the isolated Bacillus subtilis suggests that the enzyme activity was defined at 20ºC.

Fig. 5  Effect of temperature on levan-forming activity.

 

SEM Imaging:

Scanning electron microscopy (SEM) (JEOL JSM-6360) is an important method, which has been increasingly used to examine the morphology of the biological specimens. The surface morphology of Bacillus subtilis was exemplified by SEM. As shown in Fig. 6, the levan sample was observed as white dust-like particles.

 

Fig. 6  SEM image at 2500 times the normal

 

CONCLUSION:

Successful purification of alkaline levan produced by Bacillus subtilis using methylation was done after which the product was purified with several folds with an increase in levan-forming activity. In conjecture to this, the central composite factorial design also proved to be a useful factor in determining the optimal conditions for maximum levan productivity.

 

ACKNOWLEDGMENT:

The authors are indebted to all the colleagues, especially those from the Department of Biotechnology, Madha Engineering College for their valuable suggestions on the manuscript and laboratory work.

 

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Received on 25.08.2013                                  Accepted on 01.09.2013        

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