Lucrative pectinase production by novel strain Pseudozyma sp. SPJ with statistical optimization techniques using agro-industrial residues

Abstract

Production of high titers of an alkaline, extracellular and thermo-tolerant pectinase by a newly isolated yeast Pseudozyma sp. SPJ was carried out under solid state fermentation. Citrus peel, the inexpensive agro-industrial residue used as substrate, was experienced to be unsurpassed. Response surface methodology was conducted to optimize the culture conditions for Pseudozyma sp. SPJ for hyper production of pectinase. Plackett Burman design was applied to identify the most effective culture variables. Out of nine variables studied, incubation time, moisture content and ammonium sulfate were detected as most important. A full factorial Central Composite Design was used to optimize the levels of these variables, which resulted in 17-fold increase (71.19 IU/g to 1215.66 IU/g dry substrate) in the enzyme yield. The results of analysis of variance and multiple regression analysis implies that the effect of incubation time (p<0.000) and moisture content (p<0.018) is more than ammonium sulfate. And also the interaction of moisture content with ammonium sulfate (p<0.002) is more significant.

Keywords

pectinase / Pseudozyma sp. SPJ / response surface methodology / solid state fermentation

Introduction

Pectinases are the enzymes that breakdown the glycosidic bonds of the long chain of galacturonic acid residues of pectic substances (the structural polysaccharides of plant cell wall). Microbial pectinases contribute to almost 25% of the global food enzyme sales and are estimated to increase further. Pectinases are meant for extraction, liquefaction and clarification of fruit juices (Kashyap et al., 2001). In fabric industry, they are employed to ret plant fibers such as flax, hemp and jute (Hoondal et al., 2002; Sharma et al., 2011a). They are also applied to mechanical pulp to solve the retention problems in the paper industry (Reid and Ricard, 2000).

Sub-merged fermentation (SmF) is extensively used for the production of enzymes and for understanding the physiological aspects of enzyme synthesis while solid-state fermentation (SSF) is mainly advocated for the improvement in production level of enzymes (Patil and Dayanand, 2006). In SSF microbes grow and make products while sticking on the surface of solid substrates in near absence of free flowing water. Such system proves more efficient in production of several enzymes and metabolites by microbes as being closer to the microbes’ natural habitat. This cultivation technique has acquired a special relevance in the field of biotechnology because it gives higher productivity per reactor volume, has lower operating costs, produces less wastewater, demands less energy and space, requires simpler equipments, gives higher product concentration, avoids foaming and lowers the risks of contamination (Pandey et al., 2000; Suryanarayan, 2003).

The cost of enzyme production is one of the main factors which determine the use of enzyme at industrial scale. To meet industrial demands, high yielding, extracellular pectinase producing organisms are suitable that can use agro-residues as substrate to produce the enzyme cost effectively. The citrus processing residues are attractive and potential feed stock for their biological conversion to value added products as they are rich in both soluble and insoluble carbohydrates. Citrus peel contains 30% (approx.) of pectin in its fresh weight. Citrus peel is also reported earlier (Garzon and Hours, 1991; Ismail, 1996; Nabi et al., 2003; Dhillon et al., 2004; Sharma et al., 2012) as a good substrate for pectinase production as it consists of pectin with proteins (Dhillon et al., 2004).Use of these residues can help in solving the problem of pollution (Cauto and Sanroman, 2005), as they can increase the Biological Oxygen Demand (BOD) of water.

Optimization of culture conditions is very important as it improves the productivity, economy and practicability of the process (Souza and Roberto 1999; Chen et al., 2002). One variable at a time strategy is the conventional method used for this purpose. This method is not only time consuming, but being one dimensional it can also result in misinterpretation of optimum conditions (Box et al., 1978; Cochran and Cox, 1957). Response surface methodology (RSM) has recently attracted attention as an optimization technique in the field of numerical analysis. It is a powerful statistical technique (Box and Wilson, 1951), consuming less time and labor as fewer experiments are required to give even better results. Its most attractive feature is that it takes all the interactions between the independent variables into consideration and quantifies them (Haaland, 1989; Bogar et al., 2003; Vaidya et al., 2003; Wejse et al., 2003). A 3.5 fold increase in keratinase production using RSM has been reported (Tatineni et al., 2007). Sharma et al. (2011b) have reported 4.2 fold increase in pectinase production under submerged culture conditions using RSM. The aim of study was to achieve maximum pectinase yield from newly isolated yeast Pseudozyma sp. SPJ using an economic substrate by statistically optimizing its culture conditions under solid state fermentation.

Materials and methods

Microorganism and its cultivation

An alkaline pectinase producing yeast was isolated from fruit waste disposal site and identified as Pseudozyma sp. SPJ by Microbial Type Culture Collection and Gene Bank (MTCC), Institute of Microbial Technology (IMTECH), Chandigarh, and given accession No. 9842. The microorganism was identified on the basis of its phenotypic characterization and results were further confirmed by 26S rRNA sequencing method. The culture was maintained on yeast extract peptone dextrose (YEPD) medium slants and stored at 4°C (sub-cultured every 3 months).

Cultivation under SSF

In a 250 mL Erlenmeyer flask, 10 g of solid substrate (citrus peel) and 25 mL mineral salt solution (in g/L: MgSO₄·7H₂O, 0.2; KH₂PO₄, 0.4; pH 8.0) were taken; sterilized by autoclaving at 1.05 kg/cm² for 30 min; inoculated with 10% (v/w) inoculum of 16 h old yeast culture and incubated in a humidified incubator at 32°C for 72 h. The flasks were tapped at regular intervals in order to mix the contents.

Enzyme extraction

The enzyme was extracted twice using100 mL glycine-NaOH buffer (0.01 M, pH 9.0) for each flask of the cultured solid substrate. The contents were squeezed through a wet muslin cloth. The enzyme extract as centrifuged (10000 r/min, 30 min, 4°C) and the clear supernatant obtained was used as crude enzyme for enzymatic measurements.

Pectinase assay

Suitable dilution of crude enzyme (10 μL) was added to 490 μL of pectin (0.1%) and incubated at 65°C for 5 min. Then, 1.5 mL of dinitrosalicylic acid (DNSA) was added to the reaction mixture and heated in boiling water bath for 15 min. Absorbance was measured at 540 nm (Miller 1959). Three controls have been used in the enzyme assay; blank (500 μL buffer), substrate blank (10 μL buffer+ 490 μL substrate) and enzyme blank (10 μL enzyme+ 490 μL buffer).The absorbance values for the blanks are subtracted from the absorbance of the test reaction mixture. One unit of enzyme activity was defined as the amount of enzyme that released 1μmol galacturonic acid per min under assay conditions, using galacturonic acid as standard.

Identification of effective culture conditions

The Plackett Burman design (PBD) was used to find out the critical culture conditions (physical and chemical) for the pectinase production by Pseudozyma sp. SPJ. The software package Minitab 16 was used to design and analyze the experiments. It designed 12 experiments for 9 variables (Table 1) out of which the inoculum size was taken as dummy variable. After performing the experiments, the pectinase activity was determined in each case by taking cell free supernatant as crude enzyme. The experiments were conducted in triplicates and the mean value of three responses (pectinase activity) was taken as result.The variables showing maximal effect were identified by performing F-test.

F value for each variable is calculated with Eq. (1):

(1)F\mathrm{v}\mathrm{a}\mathrm{l}\mathrm{u}\mathrm{e}=\frac{\mathrm{F}\mathrm{a}\mathrm{c}\mathrm{t}\mathrm{o}\mathrm{r}\mathrm{m}\mathrm{e}\mathrm{a}\mathrm{n}\mathrm{s}\mathrm{q}\mathrm{u}\mathrm{a}\mathrm{r}\mathrm{e}}{\mathrm{E}\mathrm{r}\mathrm{r}\mathrm{o}\mathrm{r}\mathrm{m}\mathrm{e}\mathrm{a}\mathrm{n}\mathrm{s}\mathrm{q}\mathrm{u}\mathrm{a}\mathrm{r}\mathrm{e}}

The factor mean square for variable A was calculated with Eq. (2):

(2)\mathrm{F}\mathrm{a}\mathrm{c}\mathrm{t}\mathrm{o}\mathrm{r}\mathrm{m}\mathrm{e}\mathrm{a}\mathrm{n}\mathrm{s}\mathrm{q}\mathrm{u}\mathrm{a}\mathrm{r}\mathrm{e}={\displaystyle \frac{{(\sum A(H)-{\displaystyle \sum A(L)})}^{\mathrm{2}}}{\mathrm{12}}}

Here, H is the value of response of the experiments having higher values of the variable and L is the value of response of the experiments having lower values of the variable. The error mean square was the factor mean square for the dummy variable used in the design.

Optimization of most effective variables using Central Composite Design (CCD)

A full factorial CCD was designed, studying each variable at 5 levels i.e. incubation time (24–120 h), moisture content (1–5 mL/g dry substrate)and concentration of ammonium sulfate (0.1%–0.5%), with total 20 runs (8 cube points, 6 axial points and 6 central points) as shown in Table 2. Pectinase activity was measured for all the runs designed and multiple regression analysis and Analysis of Variance (ANOVA) were performed with the resulting data. The quadratic model for predicting the optimal response i.e. pectinase activity is given as Eq. (3):

(3)Y={\beta }_{\mathrm{0}}+{\beta }_{\mathrm{1}}{x}_{\mathrm{1}}+{\beta }_{\mathrm{2}}{x}_{\mathrm{2}}+{\beta }_{\mathrm{3}}{x}_{\mathrm{3}}+{\beta }_{\mathrm{11}}{x}_{\mathrm{1}}^{\mathrm{2}}+{\beta }_{\mathrm{22}}{x}_{\mathrm{2}}^{\mathrm{2}}+{\beta }_{\mathrm{33}}{x}_{\mathrm{3}}^{\mathrm{2}}+{\beta }_{\mathrm{12}}{x}_{\mathrm{1}}{x}_{\mathrm{2}}+{\beta }_{\mathrm{13}}{x}_{\mathrm{1}}{x}_{\mathrm{3}}+{\beta }_{\mathrm{23}}{x}_{\mathrm{2}}{x}_{\mathrm{3}}

where Y is the pectinase activity, β₀ is the intercept, β_1,β₂ and β₃ are linear coefficients; β_11,β₂₂ and β₃₃ are squared coefficients; and β₁₂, β₁₃ and β₂₃ are interaction coefficients.

Results and discussion

Nine variables were taken to identify the most important ones by using PBD for the production of pectinase and the results were measured in terms of pectinase activity (Table 1). The three variables: incubation time, moisture content and ammonium sulfate were found to be most effective by observing the results of F-test performed (Table 1). The three most effective variables were subjected to CCD (Chen et al., 2002) for their level optimization. The measured and predicted values for the pectinase activity are given in the Table 2. The results were further analyzed using actual (uncoded) values of the independent variables used for RSM. The estimated regression coefficients for pectinase activity were given in Table 3. By applying multiple regression analysis, the Eq. (4) is explaining the pectinase production.

(4)$$\begin{gathered} Y=\mathrm{1}\mathrm{114.51}+\mathrm{5.53}{x}_{\mathrm{1}}-\mathrm{66.71}{x}_{\mathrm{2}}-\mathrm{220.37}{x}_{\mathrm{3}}-\mathrm{0.03}{x}_{\mathrm{1}}^{\mathrm{2}}-\mathrm{3.55}{x}_{\mathrm{2}}^{\mathrm{2}} \\ -\mathrm{91.19}{x}_{\mathrm{3}}^{\mathrm{2}}-\mathrm{0.06}{x}_{\mathrm{1}}{x}_{\mathrm{2}}-\mathrm{2.73}{x}_{\mathrm{1}}{x}_{\mathrm{3}}+\mathrm{180.33}{x}_{\mathrm{2}}{x}_{\mathrm{3}} \end{gathered}$$

The value of R² (95.86%), adjusted R² (92.14%) and insignificant (p<0.130) Lack of Fit concluded the model as fit, suitable and significant (Box et al., 1978; Cochran and Cox, 1957; Akhnazarova and Kafarov, 1982). ANOVA was conducted and the significance of each coefficient was determined by student’s t-test and p value (Table 4). The larger the magnitude of the t value and smaller the p value (p<0.05 at 5% significance level), the more significant is the corresponding coefficient (Akhnazarova and Kafarov, 1982). This implies that the effect of incubation time (p<0.001) and moisture content (p<0.018) is more than other variables and also the interaction of moisture content with ammonium sulfate (p<0.002) is more significant at 5% significance level. p values for linear (0.000), square (0.000) and interaction (0.010) coefficients found to be significant. The model F value 25.73 indicated model terms as significant. The results of statistical analysis were represented in the form of contour plots (Fig. 1). Each plot represents an infinite number of combinations of two test variables while keeping the third one at its respective constant value. A 3.5 fold increase in the exo-polygalacturonase production was attained using RSM (Gupta et al., 2008).

The p value had shown that the most important factor for pectinase production is the time of incubation.The maximum activity of enzyme was observed in the culture filtrate harvested after 72 h (1215.66 IU/g dry substrate). The enzyme yield increased with the time of incubation up to 72 h and decreased thereafter (Fig. 1A, 1B). This might be a result of variation in pH of the medium during fermentation. Microorganisms start hydrolyzing the enzymes for synthesis of biomass proteins after a certain time period (Nabi et al., 2003). Maximum pectinase was harvested after 96 h (Hours et al., 1998; Bayoumi et al., 2008) and after 65 h (Piccoli-Valle et al., 2001).

Moisture content is also found crucial for growth of the organism and enzyme production.The importance of moisture level in SSF medium and its influence on microbial growth and product biosynthesis may be attributed to the impact of moisture on the physical properties of the solid substrate. Pseudozyma sp. SPJ produced maximum titer of pectinase when citrus peel was moistened with MA (g/L: MgSO₄·7H₂O, 0.5; KH₂PO₄, 1.0) in a ratio of 1:1 to 1:2.5 (Fig. 1A) and decreased with any increase or decrease in the moisture level. The porosity and gas volume may reduce with increase in moisture level and when lower it is known to decrease nutrient solubility and swelling of solid substrate. It also increases water tension (Raimbault and Alazard, 1980; Narahara et al., 1982). Maximum pectinase yield at substrate to moisture ratio of 1:5 has been reported for Streptomyces sp. RCK-SC (Kuhad et al., 2004).

The concentration of ammonium sulfate was not found as a significant variable individually; however its interaction with moisture content (Fig. 1C) had shown that requirement of ammonium sulfate increases with increase in the moisture level. Ammonium sulfate is a good inorganic source of nitrogen for growth of microbes.It has been optimized as 0.3% experimentally and up to 0.2% with graphical evaluation.

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