Sequential optimizations of Aspergillus awamori EM 66 exochitinase and its application as biopesticide

Article history: Received on: 27/06/2016 Accepted on: 10/09/2016 Available online: 27/02/2017 Sequential optimization strategy was achieved based on statistical experimental designs for enhancement of Aspergillus awamori EM66 exochitinase production. Firstly, 2-level Plackett-Burman design was accomplished for distinguishing between the bioprocess parameters, which improve the exochitinase production. Second optimization step was implemented through central composite design (CCD), for optimization variables amounts which have the highest positive effect on exochitinase production. Maximum activity (5998mU/ml) for exochitinase reported approximately 22 fold increase compared to the basal medium activity. Mortality 92%, 86.67% and 65.67% was recorded when the partial pure fungal exochitinase was applied to the diet of the greater wax moth larvae, Galleria mellonella, the cotton leaf worm, Spodoptera littoralis, and the black cutworm, Agrotis ipsilon, respectively. The results indicated to the importance of Aspergillus awamori EM66 exochitinase as an effective biopesticide.


INTRODUCTION
Hard environments are permanently predictable to accord unrivalled microorganisms have new feature.Honey osmophilic property commended it to be good medium for dominant spores worthy to produce bio-products with unique properties (Esawy et al., 2011;Esawy et al., 2012;Esawy et al., 2013).
Chitin, is a β-1,4-linkedNacetylglucosaminehomopolymer.It is consider the second most copious polysaccharide in nature.Chitin is considered as one of the main component of exoskeletons of some insect, fungus cell walls and crustacean shells (Gooday, 1990;Crosby and Alfred, 2004).It is also exists in several body ingredients of invertebrates and as a bacterial product (Tanaka et al., 1999;Nawani and Kapadnis, 2005).Chitinases (E.C.3.2.1.14)is enzymes have the ability to hydrolyze in soluble chitin to its oligo and monomeric components.Chitinases could be divided into two main enzymes, exochitinases and endochitinases (Graham and Sticklen, 1994).Endochitinases (EC 3.2.1.14)can split chitin at random internal sites yielded a soluble, low-molecular mass multimers of N-Acetylglucosamine (GlcNAc) like chitotetrose, chitotriose, and diacetylchitobiose.Exochitinase consisted of two subcategories: β-1, 4 N-acetyl glucosaminidases and exochitinases (EC 3.2.1.29),the aim of this work which can stimulate the release of diacetylchitobiose starting at the non-reducing end of chitin chains (Chuan, 2006).Many researchers pay attention to chitinases because of their wide range of biotechnological applications, especially in chitooligosaccharides production, glucosamines, and GlcNAc have an massive pharmaceutical potential (Singh et al., 2009) and, Chitinases can be also used as bio-control agents against fungal phytopathogens in agriculture field due to their ability to hydrolyze the chitinous fungal cell wall (Maisuria et al., 2008).Crop pests control by the use of chitinase holds a great promise as an alternative to the use of chemicals (Kramer, 1997).Several years ago, statistical design experimental techniques have been employed for reaching to the most favorable conditions.It was achieved by evaluating the parameters effects and conquer the abuse of factor interactions (Ren et al., 2006, Liu et al., 2013).
Response surface method (RSM) is one of the popular techniques that are used widely in the biotechnology industry (Wejse et al., 2003, Rui et al., 2009).RSM is a combination of mathematic and statistical techniques for experiments design, building models, estimating factors effects, and looking for the optimum conditions.RSM is a convenient road for developing optimum processes with precise conditions that has also minimized production cost of many processes by efficient screening process parameters.The optimal conditions or the region that fits the operation specification can be determined by the RSM via a curvature approach (Elibol and Dursun, 2002).
Egyptian cotton leaf worm, Spodoptera littoralis (Lepidoptera: Noctuidae), an important pest that led to vast loss in vegetables varieties, fodder, and fiber crops (Güz et al., 2013).It is damages wide types of crops, such as cotton, tobacco, and corn in countries located around the Mediterranean Basin and in Southeast Asia (Balachowsky, 1972, Sneh et al., 1981).Number of moth species offensive honey bees, honey polen and wax.Galleria mellonella, causes serious losses to commercial beekeepers every year.Black cutworm causes an economic threat to many agricultural crops.In Pennsylvania field crops, it is most often a pest of corn.It is also cause trouble in wheat and tobacco (Robinson et al., 2001).
The present report is an attempt to improve exochitinase production by honey isolates Aspergillus awamori EM66 through optimization of medium components.The enzyme was partially purified by 30% acetone.Finally, the study focused in the insecticidal activity against three serious insects which destroy valuable and economic crops, the greater wax moth larvae, Galleria mellonella, the Egyptian cotton leaf worm, Spodoptera littoralis and the black cutworms, Agrotis ipsilon.

Microorganisms and maintenance
The fungal used throughout this work, was previously identified as Aspergillus awamori EM66 (Kansoh et al., 2015) based on morphological characterization and 18S rRNA sequence analysis.A. awamoriEM66 was routinely grown on Potato dextrose agar (PDA) medium at 30°C and preserved at -80ºC in 50% (v/v) glycerol.

Exochitinase assay
Exochitinase activity was determined according to the method of (Matsumoto et al., 2004) using the chromogenic substrate p-nitro phenyl-β-D-N-acetylglucoseaminide (PNP-β-GlcNAc) as a substrate.One unit of the enzyme activity was acquainting as the enzyme amount releasing 1µmol of Pnitrophenol per minute under the specified assay conditions.
Inoculated flasks were incubated at 30 °C for 6 days in a rotary shaker adjusted at 200 rpm.At the end of incubation period cultures were centrifuged for 15 min using the cooling centrifuge.Culture supernatant was used as the crude enzyme.Results reported are the average values with standard deviations.

Plackett-Burman design
For multivariable processes such as biochemical systems, in which numerous potentially influential factors were involved, it is needful to analyze the process with an initial screening design prior to optimization (Box et al., 1978).Plackett-Burman experimental design (Plackett and Burman,1946) was used to evaluate the relative importance of various nutrients for exochitinase production by A. Awamori EM66 in submerged fermentation.
Fifteen components were selected for the study, each variable represented at two levels, high value (+1) and low value (−1) in 16 trials as shown in (Table 1).
Incubation time, pH, glucose, insect, soya bean, chitin, wheat flour, NaNo 3, CuSO 4, MgSO 4 , K 2 HPO 4 , ZnSO 4, FeSO 4 , MnSO 4 , CaCl 2 , each row represented a trial run and each column represented an independent variable concentrations.Plackett-Burman experimental design was based on the first order linear model: Y= B 0 +ΣB i X i Eq. 1 Where, Y was the response (exochitinase production), B 0 was the model intercept and B i was the variables estimates.The effect of each variable was estimated by following equation, Where, E (X i ) was the effect of the tested variable.M i + and M i − represented exochitinase production from the trials where the variable (X i ) measured was present at high and low concentrations, respectively and N was the number of trials in Eq. 2.
The standard error (SE) of the concentration effect was the square root of the variance of an effect, and the significance level (pvalue) of each concentration effect was determined using student's t-test Where, E (X i ) was the effect of variable X i .

Central composite design
After the components identification which affecting the production by Plackett-Burman design three variables (Chitin, MnSO 4 , and CaCl 2 concentrations) for exochitinase were chosen for response surface methodology of central composite design (CCD).CCD proposed by (Adinarayana et al., 2003;Awad et al., 2013) was selected for this study.A 2 3 factorial design with six star points and six replicates at the central points were used to fit the second-order polynomial model.The experimental design consisted of 20 runs and the independent variables were studied at five different levels.The experimental design used for the study was represented in Table 3.All the experiments were done in triplicate and the average of exochitinase production obtained was taken as the dependent variable or response (Y).The second-order polynomial coefficients were calculated and analyzed using the 'SPSS' software (Version 16.0).Second degree polynomials, Eq.( 4), which includes all interaction terms, were used to calculate the predicted response: 4) Where, Y activity was the predicted production of exochitinase (mU/ml), X1, X2 and X3 were the independent variables corresponding to the concentration of Chitin, MnSO 4 , and CaCl 2 respectively.ß0 was the intercept, ß 1 , ß 2 , ß 3 were linear coefficients, ß 11 , ß 22 ,ß 33 were quadratic coefficients, ß 12 , ß 13 , ß 23 were cross product coefficients.Statistical analysis of the model was performed to evaluate the variance analysis (ANOVA).
Statistical significance of the model equation was determined by Fisher's test value, and the proportion of variance explained by the model was given by the multiple coefficient of determination for each variable.The quadratic models were represented as contour plots (3D) and response surface curves were generated by using STATISTICA (0.6).

Partial purification
The optimized culture supernatant (crude exochitinase) of Asperigillus awamori EM66 produced on the previous medium was fractionated using ethanol concentrations (30-80%).The precipitate was obtained by centrifugation (10000 xg, 15 min.at 4°C) and suspended in an appropriate volume of 0.05 M acetate buffer (pH 5.0).The enzyme activity was determined for each fraction as described before.Also, protein content was evaluated for each fraction as described by Lowry et al., (1951).

Insects
Fourth instars larvae of three lepiopteran insect pests were used to test the exochitinase efficiency.These tested insects were the great wax moth larvae, Galleria mellonella, the Egyptian cotton leaf worm, Spodoptera littoralis and the black cutworms, Agrotis ipsilon.Greater wax moth culture G. Mellonella was preserve, on a modified artificial diet according to (Metwally et al., 2012).Cultures of the black cut worm, A. ipsilon (Huf.) and the cotton leaf worm, S. littoralis (Boisd.)larvae were reared on castor leaves Ricinus communis L. according to (Hussein, 2004).

Bioassay
Exochitinase application occurred through mixing with insect media.Two ml of the partial pure enzyme suspension was mixed with 50 g of the artificial diet for the greater wax moth in a 150 CC cups (Metwally et al., 2012).For the other two pests, the leaves of castor were sprayed with 2 ml enzyme suspension and left to dry in a 9 cm Petri dish lined with no.1 Whatman-filter paper.Five insect were added for each cup and Petri dish and 15 replicates for each tested insect.The treatments were kept in 25 ± 1°C and larval mortalities were recorded after 48h.

RESULTS AND DISCUSSION
At the preliminary stage of our study, the honey isolate A. awamori EM66 was tested for exochitinase production.The result indicated that it was exochitinase producer with activity equal (270 mU/ml) and 176.36 mg protein.Consequently, the specific activity was evaluated to be 1.531 U/mg by using the basal medium under submerged fermentation condition.Production of chitinase by Aspergillus spp. was studied in many reports as a potential producer for both endochitinase and exochitinase (Vionis et al., 1996, Xia et al., 2001, Nawani et al., 2002, Rattanakit et al., 2007, Brzezinska and Jankiewicz, 2012).

Exochitinase production optimization by multi-factorial experiments
In this work a sequential optimization approaches were used.The first trail aimed to screen the nutritional factors influencing growth of A. awamori EM66 with respect to exochitinase production.The second step aimed to optimize the influencing factors which controlling enzyme production process.

Estimation of the factors affecting exochitinase productivity
Firstly, the Plackett-Burman design was done to explain the relations between different medium components.Fifteen factors (X 1 -X 15 ) included culture conditions and medium components were selected for optimization process.Exochitinase average activity for the different attempts were formulated as mU /ml and represented in Table 1.Main effect was estimated as the difference between both the averages of measurements made at the high level (+1) and at the low level (-1) of that factor.Table 1 showed a wide divergence from 876 to 2045 mU /ml on exochitinase activity.Factors effects on the enzyme activity were estimated and showed graphically in Fig. 1.It was introduced the view for factor ranking estimated by Plackett-Burman design.This variation reflected medium optimization significant to reach high productivity.Data analysis from Plackett-Burman tested contained a first order (main effects) model.Regression coefficients analysis for examined variables for the exochitinase were :incubation time, pH, glucose, dried insects, soya bean, chitin, wheat flour, NaNO 3 , CuSO 4 , MgSO 4 , K 2 HPO 4 , ZnSO 4 , FeSO 4 , MnSO 4 , CaCl 2 .Chitin, MnSO 4 , CaCl 2 , FeSO 4 , NaNO 3 , K 2 HPO 4 , CuSO 4 and incubation period showed positive effect on exochitinase activity.Wheat flour, soya bean, glucose, pH, MgSO 4 , ZnSO 4 and dried insect, were contributed negatively.First order model explained the link between the fifteen factors and the exochitinase activity which presented as follows: Yactivity=853.0953+4.532X 1 +38.26265X 2 -987.144X 3 +4152.63X4 -528.983X 5 -9.469752X 6 -373.737X7 -1768.74X8 +26445.02X9 -529.596X 10 + 2311.588X11 + 193353.7X12 +181015.2X13 -10997.6X14 + 4499.06X 15 Eq.( 5) Table 2 revealed the t-test, p effect and confidence level.The variables reported confidence level above 98% in the Plackett-Burman design which were selected for further optimization; they were (Chitin, MnSO 4 and CaCl 2 ).Many reports showed the importance of chitin as a significant factor affecting chitinase production.It was reported that chitin is an essential factor influencing chitinase production by Streptomyces lividans (Vionis et al., 1996).In similar, colloidal chitin was proved to be the best substrate for production of chitinase in Microbispora sp.(Nawani et al., 2002).Chitin also was an important factor for chitinase production by Streptomyces sp.Da11 (Han et al., 2008).Similar to our result, MnSO 4 was found to enhance chitinase production by Aspergillus terreus (Ghanem et al., 2010).It was also mentioned as one of the most important factors affecting chitinase production by Bacillus thuringiensis (Sarrafzadeh and Hussein, 2012).On contrary, (Sharaf 2005) reported that MnSO 4 was an inhibitor for chitinase production by Alternaria alternate.Our results also showed that CaCl 2 activated the production of exochitinase.Similarly, it was found that CaCl 2 activated Pantoea dispersa chitinase production (Gohel et al., 2004).Building on previous results, a medium including (g %), (glucose, 0.2; insect, 0.1; soyabean, 0.2; wheat flour, 0.2; NaNO 3 , 0.02; CuSO 4 , 0.001; MgSO 4 , 0.05; K 2 HPO 4 , 0.2; FeCl 3 , 0.001; CaCl 2 , 0.05 at pH; 8).It was used as a plan medium for further investigations and the cultures were incubated for 6 days.

Optimization of the culture conditions by central composite design
For searching to the proper concentration for the most effected medium components (chitin, MnSO 4 and CaCl 2 ) showed confidence level with about 98% supported the highest chitinase productivity in the Plackett-Burman design.CCD experimental was employed coded and un-coded level of the three independent variables was recorded in Table 3.Also, the results in table.3.referred to the CCD experimental plan, the observed and predicted exochitinase production.Multiple regression analysis of the experimental data reported the following second order polynomial Eq. ( 6): Y activity = -4462.211+4591.092X 1 + 1.160E6 X 2 +62355., 2007).This implies that the variable with the largest effect represented in the linear effect of the CaCl 2 concentration and the squared term of the CaCl 2 concentration.In this finding, it was reported that CaCl 2 , played a role to predict optimum chitinase production (Gohel et al., 2004).
In this finding, it was reported that CaCl 2 , played a role to predict optimum chitinase production (Gohel et al., 2004).Table 5.
showed that F-value obtained by (ANOVA) analysis was (5.622) confirming the model significant.Moreover Prob> F (0.006) was less than 0.05 showed highly significant.(R 2 ) was evaluated as 0.914 for exochitinase activity (a value of R 2 > 0.75 insuring the model aptness).This result indicated that the statistical model recorded 91.4% of variability in the response.Model goodness could be tested by the determination of coefficient (R 2 ) and correlation coefficient (R).The R 2 value is always between 0 and 1.The closer the R 2 to 1, referred to model powerful and better predicted response (Munk et al., 1963).R value (0.8340) concerning (Eq.6) was near 1.This pointed to a close coincide among the experimental results and the theoretical values determined by equation model.

Model Validation
Validation was carried out under optimized medium conditions.It was predicted by the polynomial model.The experimental exochitinase production of 5886mU/ml was recorded.This result was close to its predicted value (5200mU/ml) after 6 days of fermentation validating the proposed model.An overall 22.2fold increased in exochitinase production was being achieved after RSM application.This reflected the success and value of optimization process.Many reports were mentioned in optimization of exochitinase productivity by response surface methodology.Exochitinase produced by marine isolate Pantoea dispersa increased about 3.9% after optimization by RSM (Gohel et al., 2004).Aeromonass chubertii chitinase increased about 1.6 % more than primary medium (Liu et al., 2013).On the other hand, chitinase produced by Streptomyces sp.Da11 associated with the South China Sea sponge Craniella australiensis increased about 39% with (RSM) optimization (Han et al., 2008).
The optimization strategy led to an increased in chitinase production in the strains Streptomyces sp.NK1057, NK528 and NK951 by 29, 9.3 and 28%, respectively (Sarrafzadeh and Hussein, 2012).
Exochitinase productivity by Aspergillusa wamori EM66 under submerged fermentation was effective and worthy optimized by using Plackett-Burman design and central composite design for selecting the statistically important factors and evaluation their optimal concentrations and illustrated graphically by second order polynomial model prepared by central composite design.For determination the relationship between the three factors and the exochitinase yield.Final components concentrations optimized with RSM medium were g%: (Glucose, 0.2; insect,0.1;Soyabean,0.2;Chitin,1.0;Wheat flour,0.2;NaNO 3 ,0.02;CuSO 4 , 0.001; MgSO 4 , 0.05; K 2 HPO 4 ,0.2;FeCl 3 ,0.001;MnSO 4 , 0.004; CaCl 2 , 0.1).The initial pH was limited to 8 and the cultures were incubated for 6 days.

Enzyme partial purification
The crude enzyme was fractionated by using absolute ethanol (30-80%) W/V.The most promising fraction was obtained at 30% this result suggested that the exochitinase had low molecular weight.Its total activity and protein content recorded 23.34 U and 0.837 mg, respectively.This result referred to about 18 times purification fold compared to the preliminary crude culture filtrate.Accordingly, the specific activity was calculated to be 27.89U/mg.The high specific activity of this enzyme gave it tremendous interest; since it referred that it approaches to purity.

Efficiency of the exochitinase against some lepidopteran pests
The partial pure enzyme was tested against three serious lepidopteran pests, larvae of the black cutworm, A. ipsilon, larvae of the Egyptian cotton leaf worm, S. littoralis and larvae of the greater wax moth, G. mellonella.The results in table 5.showed that exochitinase had a great effect on the larvae of the three tested pests.The maximum effect of the enzyme was noticed with exochitinase addition to the artificial diet of G. mellonella with a mortality percentage of 84% for the larvae and 8% for pupae and the total percentage reached to 92%.The treated larvae stopped feeding and suffered from recognizable blacking and severe rot which leads to their death (Fig. 3, 4).When the exochitinase sprayed on castor leaves and fed to the cotton leaf worms, 86.67% total mortality of S. littoralis was recorded.Meanwhile, less effect of the enzyme (the total mortality reach to 65.67%) was noticed with the treatment of larvae of A. ipsilon with the enzyme.Great attention to the chitinolytic enzymes has been progress due to their possible involvement as defensive agents against chitin-including pestiferous and pathogenic organisms, like insects, nematodes, and fungi (Munk et al., 1963, Carr and Klessig, 1989, Linthorst, 1991, Sahai and Manocha, 1993).The peritrophic membrane and exoskeleton of insects act as physicochemical barriers to environmental hazards and predators.Both are composite materials made up primarily of chitin and protein, Chitinase of family 18 and 19 have a catalytic reaction and can be described as being similar to lysozyme and chitosanase in its mode of action (Sahai and Manocha, 1993).Another effect of chitinase could be revealed to that the microbial chitinases could be partially digesting the peritrophic membrane.This helping the microbes and their toxins in peritrophic membrane penetration (Smirnoff and Valero, 1983, Sneh et al., 1983, Shahabuddin and Kaslow, 1993, Wiwat et al.1996, Chandrasekaran et al., 2012).

CONCLUSIONS
This study is aiming to improve the exochitinase productivity for honey isolate Aspergillus awamori EM66.Statistical experimental design was used for optimization process.Estimation the constituents optimal concentrations have clear influencing on enzyme productivity can be obtained by a highly significant quadratic polynomial equation obtained by the central composite design.A high similarity between the predicted and experimental results was noticed.This reflected RSM accuracy and applicability to optimize the exochitinase production process.Mortality (92%) was recorded when partial pure enzyme was applied to the diet of both larva and pupal of Galleria mellonella wax, followed 86.67% and 65.67% mortality when fungal exochitinase was applied for larva of Spodoptera littoralisn and Agrotis ipsilon respectively.Aspergillus awamori EM66 exochitinase could be serving as an effective biopesticide to control harmful pests which destroy importantly economic crops instead of hazardous chemical pesticide.
Financial support and sponsorship: Nil.

Conflict of Interests:
There are no conflicts of interest.

Fig. 1 :
Fig. 1: Effect of culture conditions and medium composition on exochitinase (mU/ml) produced by Aspergillus awamori EM66 051X 1 X 2 -16412.830X 1 X 3 -3.522E6X 2 X 3 Eq.6WhereY activity was the response (exochitinase production) and X 1 , X 2 and X 3 were the coded values of the test variables (chitin, MnSO 4 and CaCl 2 ) respectively.The graphical representations of the regression equation was represented in the three-dimensional response surface and the two-dimensional contour plots graphs.They were fundamentally important for showing the relations between the interaction effects of the estimated factors and the response value.Fig.2.A-C showed the response surface and contour plots of chitin and MnSO 4 , MnSO 4 and CaCl 2 , also chitin and CaCl 2 on exochitinase production respectively, the other component was fixed at zero level.Regression analysis results are shown in Table4.analyzing the results of central composite designed experiments data.It is recognized the increase in t-value magnitude, the decrease in pvalue, resulting more consideration of the corresponding coefficient (Aravindan and Viruthagiri

Fig 2 .
Fig 2. A. Response surface plot of exochitinase production by Aspergillus awamori EM66 showing the interactive effects of different concentrations of chitin and MnSO4 at X3= 0

Fig 3 :
Fig 3: Effect of partial purified exichitinase on larvae of the great wax moth, Galleria mellonella,A.larva after treatment, B. larva without treatment.

Fig 4 :
Fig 4: Effect of partial purified exichitinase on different stages of larvae of the great wax moth, Galleria mellonella

Table 2 .
Statistical analysis of Plackett-Burman design showing coefficient values, effect, t-and P-values for each variable on

Table 3 :
Central composite design (CCD) consisting of 20 experiments for three experimental factors in coded and actual values for the production of exochitinase by Aspergillus awamori EM66.

Table 4 :
Model coefficients and Analysis of variance (ANOVA) test estimated by multiples linear regression for exochitinase.

Table 5 :
Summary of the mortality percentages of the three lepidopteran pests after treatment with crude exochitinase.