Optimization of antioxidant potential of Aspergillus terreus through different statistical approaches

Optimization of antioxidant potential of Aspergillus terreus through different statistical approaches

Daljit Singh Arora* and Priyanka Chandra Microbial Technology Laboratory, Department of Microbiology, Guru Nanak Dev University, Amritsar-143005, India Running title: Antioxidant activity of Aspergillus terreus

*Corresponding author: Prof. Daljit Singh Arora, Department of Microbiology, Guru Nanak Dev University, Amritsar-143005, India Tel. No.: 91-183-2258802-09 Extn: 3316, Fax No. 91-183-2258819-20 E-mail : [email protected]

Biotechnology and Applied Biochemistry Immediate Publication. Published on 08-Oct-2010 as manuscript BA20100202T

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© 2010 Portland Press Limited

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Synopsis A three-step optimization strategy which includes, one-factor-at-a-time classical method and different statistical approaches (Plackett-Burman design and response surface methodology) were applied to optimize the antioxidant potential of Aspergillus terreus. Antioxidant activity was assayed by different procedures and compared with total phenolic content. Primarily, different carbon and nitrogen sources were screened by classical methods, which revealed sucrose and NaNO3 to be the most suitable. Significance of the components of Czapek dox’s

medium with respect to antioxidant activity was evaluated with Plackett-Burman design, which supported sucrose and NaNO3 to be the most significant. In second step, sucrose and NaNO3 along with temperature were further taken as three variables for response surface methodology to study their interaction. Response surface analysis showed 4% sucrose, 0.1% NaNO3 and incubation temperature of 30o C to be the optimal conditions. Under these conditions, the antioxidant potential assayed through different procedures was 88.1%, 74.9% and 70.2% scavenging effect for DPPH radical, ferrous ion and nitric oxide ion, respectively. The reducing power showed an absorbance of 2.0 with 71.5% activity for FRAP assay. Total phenolic content under different physio-chemical conditions and antioxidant potential under various assay procedures correlated positively. Keywords: Antioxidant activity, Aspergillus terreus, Plackett-Burman design, Optimization, Response surface methodology (RSM), Total phenolic content Abbreviations used: ANOVA, analysis of variance; DPPH, 1,1-diphenyl-2-picryl hydrazyl; FC, Folin-Ciocalteau; FRAP, ferric reducing antioxidant power; GAE, gallic acid equivalent; RSM, Response surface methodology; TPC, total phenolic content


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Introduction The biotechnology industry is developing novel products in a wide range of areas such as human and animal health care, agriculture, environment and diagnostics. These products vary from whole cells to extracellular secondary metabolites of various micro-organisms [1]. Fungi are remarkable organisms that readily produce a wide range of natural products as secondary metabolites and some are considered to be beneficial due to their medical, industrial and agricultural importance. These secondary metabolites are antibiotics, phenolic compounds, steroids, terpenes and polyketides which may possess different bioactivities including antioxidant activity [2].

Antioxidants have the capability to neutralize reactive oxygen species (ROS), which include superoxide anion (O-

2), alkoxyl radical (RO.), nitric oxide (NO), hydrogen peroxide (H2O2), peroxyl radical (ROO.) and hypochloride (HOCl) [3]. Such ROS are responsible for many degenerative or pathological processes and antioxidants thus can protect the human body from such situations like aging, cancer, coronary heart disease, Alzheimer’s disease,

neurodegenerative disorders, atherosclerosis, cataracts, and inflammation [4]. Earlier, synthetic antioxidants were commonly used for this purpose but because of their carcinogenic nature, there is a need to find out natural and more effective economic antioxidants [5].

Plants and mushrooms are a large source of such compounds while secondary metabolites of some lower fungi are also reported to possess antioxidant activity. If development of novel drugs is of concern, fungi have an advantage over plants as industrial production and down stream processing of bioactive secondary metabolites is quite easier as compared to plants. Moreover, the production of known bioactive secondary metabolites responsible for antioxidant activity can be enhanced by optimizing the different physio-chemical parameters required for the growth of fungi. As culture conditions have a major impact on the growth of microorganisms and their products, hence their optimization is a critical step for the fermentation process development [6].

Earlier, the classical method of one-factor-at-a-time was most common strategy used, but nowadays a number of statistical techniques are available to perform optimization as it has many advantages. A statistical design enables easy selection of important parameters from a large number of factors and explains the interaction between important variables. Various statistical experimental designs have been used for optimizing fermentation variables. The Plackett-Burman design is a well known and widely used statistical technique for screening and selection of most significant culture variables while response surface methodology (RSM) provides important information regarding the optimum level of each variable along with its interaction and their effect on product yield [7,8].

The present study aims to optimize the conditions for enhancement of antioxidant activity of Aspergillus terreus by various assay procedures [1,1-diphenyl-2-picryl hydrazyl (DPPH) assay, reducing power, ferrous ion and nitric oxide ion scavenging activity, ferric reducing antioxidant power (FRAP) assay] using one-factor-at-a-time classical approach, Plackett-Burman design and response surface methodology. An effort has been made to work out the correlation (if any) between antioxidant activity and the total phenolic content.


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Materials and methods Experimental Aspergillus terreus was isolated from soil of Navakot area, Amritsar, Punjab, India (31° 37' 59" North, 74° 51' 56" East) and identified on the basis of standard protocol and the identity was confirmed by National Fungal Culture Collection of India, Agharkar Research Institute, Pune, India. To study the antioxidant potential, the fungus was grown on 50 ml Czapek dox’s broth (sucrose 3%, NaNO3 0.2%, K2HPO4 0.1%, MgSO4 0.05%, KCl 0.05%, FeSO4 0.001%,pH 7.0). The medium was inoculated with two discs (8mm) of fungal mycelia obtained from 6-7 days grown culture on Yeast extract glucose agar plates. The growth was carried out under stationary conditions at 25o C. After incubation of 10 days, the culture broth was filtered through Whatman filter paper no.1 and the filtrate so obtained was analyzed for antioxidant potential by different assay procedures and total phenolic content was estimated with Folin-Ciocalteau (FC) method. The optimized pH of the medium and incubation period values were used based on previous studies [9]. Assay procedures for antioxidant activity DPPH free radicals scavenging activity The scavenging activity for DPPH free radicals was measured according to Zhao et al. 2006 [10] with slight modifications. To 2 ml of distilled water, 1 ml of 0.1 mM DPPH solution in ethanol and 0.5 ml of extract was added. The mixture was shaken vigorously and allowed to reach a steady state for 30 min at room temperature. Decolourization of DPPH was determined by measuring the decrease in absorbance at 517 nm, and the DPPH radical scavenging effect was calculated according to the following equation:

% scavenging rate = [1-(A1 -A2)/ A0] x 100 Where A0 represents the absorbance of the control (DPPH without extract) and A1 represents the absorbance of the reaction mixture, A2 represents the absorbance without DPPH (DPPH was replaced by same volume of distilled water). Determination of antioxidant activity by reducing power measurement The reducing power of the extracts was determined according to Chang et al. 2002 [11] with slight modifications. An aliquot of 0.5 ml extract was added to 0.1 ml of 1% potassium ferricyanide. After incubating the mixture at 50 oC for 30 min, during which ferricyanide was reduced to ferrocyanide, it was supplemented with 0.1 ml of 1% trichloroacetic acid and 0.1% FeCl3, and left for 20 min. Absorbance was read at 700 nm to determine the amount of ferric ferrocyanide (Prussian blue) formed. Higher absorbance of the reaction mixture indicates higher reducing power of the sample. Determination of antioxidant activity by ferric reducing antioxidant power (FRAP) assay FRAP assay was carried out according to Othman et al.2007 [12] by monitoring the reduction of Fe3+- tripyridyl triazine (TPTZ) to blue colored Fe2+-TPTZ. The FRAP reagent was prepared by mixing 300 mM acetate buffer (pH 3.6), 10 mM TPTZ and 20 mM ferric chloride in a ratio of 10:1:1. The reaction mixture containing 2 ml of FRAP reagent, 0.5 ml of extract and 1 ml of distilled water was incubated for 10 min and the absorbance measured at 593 nm. Antioxidant potential of the sample was compared with the activity of 0.5 ml stock solution of 1mg/ml FeSO4.


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Determination of ferrous ion scavenging (metal chelating) activity The chelating activity of the extracts for ferrous ions was measured according to Zhao et al. 2006 [10]. The reaction mixture containing 0.5 ml of extract, 1.6 ml of deionized water, 0.05 ml of FeCl2 (2mM) and 0.1 ml of ferrozine (5mM) was incubated at 40 oC for 10 min and the absorbance measured at 562 nm. The chelating activity was calculated as

Chelating rate = [1-(A1 -A2)/ A0] x 100 Where A0 represents the absorbance of the control (without extract) and A1 represents the absorbance of reaction mixture, A2 represents the absorbance without FeCl2. Determination of nitric oxide (NO) scavenging activity Nitric oxide production from sodium nitroprusside was measured according to Kang et al. 2006 [13]. An equal amount (6 ml) of sodium nitroprusside (5mM) solution was mixed with 6 ml of extract and incubated at 25 oC for 180 min. After every 30 min, 0.5 ml of the reaction mixture was mixed with an equal amount of Griess reagent (1% sulphanilamide, 2% phosphoric acid, and 0.1% napthylethylene diamine dihydrochloride) and absorbance was taken at 546 nm and compared with absorbance of 1mg/ml of standard solution (sodium nitrite) treated in the same way with Griess reagent. Determination of total phenolic content (TPC) The total phenolic content was determined colorimetrically using the Folin-Ciocalteau (FC) method according to Singleton et al. 1999 [14] with some modifications. Test sample (0.5 ml) was mixed with 0.2ml of FC reagent and allowed to stand for 10 min to which 0.6 ml of 20% sodium carbonate was added and mixed completely. The reaction mixture was incubated at 40o C for 30 min. Absorbance of the reaction mixture was measured at 765 nm. Gallic acid was taken as standard. Medium optimization using one-factor-at-a-time classical method Screening of different carbon and nitrogen sources To find out the best carbon source, sucrose in the Czapek dox’s medium was replaced with same concentration of one of the sugars (glucose, maltose, lactose, starch and glycerol) and to work out the best nitrogen source, NaNO3 in Czapek dox’s medium was substituted with one or the other inorganic nitrogen source (KNO3, NH4NO3, (NH4)2Cl , (NH4)2 SO4 , (NH4)H2 SO4) or nitrogen rich organic supplement (yeast extract, peptone, malt extract, urea, casein, soyabean meal). Statistical optimization of the medium Plackett-Burman experimental design The Plackett-Burman experimental design is a valuable tool for the rapid evaluation of the effects of various medium components. Because this design is a preliminary optimization technique, which tests only two levels of each medium component, it cannot provide the optimal quantity of each component required in the medium. This technique, however, provides indications of how each component tends to affect the activity. The screening of most significant parameters affecting antioxidant potential was studied by the Plackett–Burman design. The 5 factors, which are components of Czapek dox’s medium (sucrose, NaNO3, K2HPO4, KCl, and


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MgSO4) were examined. Total 14 tests were designed including 12 combinations and 2 repetitions at central point which contain different concentration of each factor and the effect of each factor was determined by the difference between the average of the + and – responses. The significance level of effect of each factor was determined by student’s t test .The most common

mean of assessing significant value is the p value which was also evaluated for each factor. Response surface methodology through Box-Behnken design On the basis of results from screening of different carbon and nitrogen sources through one-factor-at-a-time classical method and different components by Plackett-Burman design, sucrose and NaNO3 were found to be the best for antioxidant activity. Sucrose as carbon source, NaNO3 as nitrogen source and temperature were taken independent variables for the optimization by RSM using Box-Behnken design of experiments. Each variable was studied at three levels (-1, 0, +1); for sucrose these were 5%, 3% and1%; NaNO3: 0.05%, 0.2% and 0.35 %; temperature: 15oC, 25oC and 35oC

The experimental design included 17 flasks with five replicates having all the three variables at their central coded values. The DPPH assay, reducing power, ferrous ion and nitric oxide ion scavenging activity, FRAP assay and their total phenolic contents were taken as responses G (1-6). The mathematical relationship of response G (for each parameter) and independent variable X (X1, Sucrose; X2, NaNO3; and X3, temperature) was calculated by the following quadratic model equation.

G (1-6) = β0 + β1X1 + β2X2 + β3X3 + β11X21 + β22X2

2 + β33X23 + β12X1X2 + β13X1X3 + β23X2X3 (1)

Where, G is the predicted response; β0, intercept; β1, β2, and β3, linear coefficients; β11, β22 and β33, squared coefficients and β12, β13 and β23 interaction coefficients. MINITAΒ version 11

statistical software was used to obtain optimal working conditions and generate response surface graphs. Statistical analysis of experimental data was also performed using this software. Results Effect of different carbon and nitrogen sources on antioxidant potential studied by various assay procedures Initially, to assess the antioxidant potential by various assay procedures all the experimentation was done by growing Aspergillus terreus on Czapek dox’s broth medium. In order to find the optimal carbon source, sucrose was replaced with different sugars. Carbohydrates are the structural and storage compounds in the cells of fungi and thereby play a key role in the growth as well as in the production of various useful secondary metabolites. Of the various carbon sources tested, sucrose proved to support the maximum antioxidant activity (Table 1) and the order followed was sucrose>dextrose>maltose> lactose>starch>glycerol. Sucrose was thus selected as carbon source for further experimentation.

Similarly, NaNO3 turned out to be the best nitrogen source to support maximum antioxidant potential. Peptone and yeast extract were also good sources of nitrogen while, urea gave the poorest activity. The antioxidant profile of Aspergillus terreus for different nitrogen sources remained the same irrespective of assay procedures adopted. NO ion scavenging activity was monitored for 180 min (data not shown) which increased gradually with respect to time, data pertaining to 180 min is only shown (Table 2).

The TPC of Aspergillus terreus extracts have been expressed as gallic acid equivalent (GAE) i.e. mg gallic acid /100 ml culture. TPC are known to be responsible for antioxidant


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activity and the Aspergillus terreus possessed high TPC, which is positively correlated with its antioxidant potential. The highest TPC yield was 16.74 mg/ml in the presence of sucrose and NaNO3 in the medium. On the basis of above results, Czapek dox’s broth medium was chosen for remaining experimentations. Plackett-Burman design for selection of significant components A Plackett-Burman design experiment was employed to evaluate the influence of five factors (sucrose, NaNO3, K2HPO4, KCl, and MgSO4) and their importance in culture medium to obtain better antioxidant activity. Antioxidant potential of Aspergillus terreus assayed by different procedures and extra-cellularly produced total phenolic content varied significantly with the 14 run of different combinations of the media components (Table 3). The maximum antioxidant potential along with high TPC was observed in run order 13 and run order 14 which was followed by run order 5. The results were subjected to regression analysis and the analysis of variance (ANOVA) which revealed sucrose and NaNO3 to have statistically significant effect on antioxidant potential with p value ≤ 0.05 and ≤ 0.5, respectively which showed that of the five variables only sucrose and NaNO3 played a critical role for antioxidant activity. Based on these results, sucrose and NaNO3 were selected as two variables and applied to optimize the medium composition by RSM. To know the optimum temperature and its interaction with other variables (sucrose and NaNO3), it was chosen as a third variable as it is the important physical parameter that affects the activity as well as fungal growth. Box-Behnken design Fitting the model The data obtained from quadratic model equation was found to be significant. It was verified by F value and the analysis of variance (ANOVA) by fitting the data of all independent observations in response surface quadratic model. The Table 5 showed the results of ANOVA demonstrating the model F-value and lack of fit value of all the responses. The results for model F-value implies the model is significant which indicates it to be suitable to represent adequately the real relationship among the parameter used. R2 value for all the responses ranged between 88-93%, which showed suitable fitting of the model in the designed experiments (Table 4, 5). The final predictive equations for each response : DPPH assay (G1), reducing power (G 2), ferrous ion scavenging activity (G3), FRAP assay (G4) and nitric oxide ion scavenging activity (G 5) and their total phenolic contents (G 6) obtained are as follow:

G (1) = – 4.26 + 25.07 X1 + 113.62 X2 + 2.17 X3 – 2.79 X21 + 33.44 X2

2 – 0.03 X23 –

41.50 X1X2 + 0.01 X1X3 – 0.32 X2X3 (2) G (2) = – 2.416 + 0.505 X1 + 6.644 X2 + 0.149 X3 – 0.061 X2

1 – 0.244 X22 – 0.003 X2

3 – 1.705 X1X2 + 0.010 X1X3 – 0.078 X2X3 (3)

G (3) = – 9.65 + 9.96 X1 + 83.59 X2 + 3.73 X3 – 1.31 X21 – 18.13 X2

2 – 0.06 X23 – 23.67

X1X2 + 0.11 X1X3 – 0.58 X2X3 (4) G (4) = – 13.52 + 9.09 X1 + 102.16 X2 + 3.80 X3 – 1.09 X2

1 – 29.56 X22 – 0.07 X2

3 – 25.83 X1X2 + 0.10 X1X3 – 0.93 X2X3 (5)

G (5) = – 12.45 + 9.70 X1 + 95.57 X2 + 3.68 X3 – 1.22 X21 – 57.67 X2

2 – 0.06 X23 – 21.25

X1X2 + 0.08 X1X3 – 0.70 X2X3 (6) G (6) = – 17.11 + 6.96 X1 + 32.59 X2 + 0.99 X3 – 1.13 X2

1 + 31.44 X22 – 0.02 X2

3 – 16.17 X1X2 + 0.15 X1X3 + 0.10 X2X3 (7)


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The optimized values of factors were validated by repeating the experiment in triplicate flasks. Effect of different variables on DPPH assay Sucrose significantly affected the DPPH activity. The Linear effect (X1), squared effect (X1

2) as well as interactive effect (X1X2) was highly significant ( p value < 0.005). The response surface graphs showed the highest activity at concentration of sucrose in between 3-5 % but with least amount of NaNO3 while the activity decreased with decrease in sucrose concentration and with increase in the concentration of NaNO3 at a constant temperature of 25o C. Maximum DPPH scavenging effect (90 %) was obtained at 3 % of sucrose, 0.05 % of NaNO3 and at 30o C (Fig.1). Effect of variables on reducing power Linear effects (X1, X2, X3), squared effects (X1

2, X 22) and interactive effect between sucrose-

temperature (X1X3) was significant with p value <0.5. Interactive effect (X1X2) was most significant at p value ≤ 0.005. The response surface graphs showed the highest reducing potential with an absorbance of 2.1, when the concentration of sucrose is 5 % with 0.05 % of NaNO3 and at a temperature of 30o C (Fig. 2). Effect of variables on FRAP assay, ferrous ion and nitric oxide ion scavenging activity Effect of variables was similar on FRAP assay, ferrous ion and nitric oxide ion scavenging activity. Linear effect (X3) and interactive effect (X1X2) was significant with p value ≤ 0.005. While linear (X1) and its squared effect (X3

2) showed significance at p ≤ 0.05. At 30o C, with medium composition of 4 % of sucrose with 0.05 % of NaNO3, ferric reducing antioxidant power was 72 % which was highest as compared to other medium conditions (Fig. 3). Similarly, highest scavenging effect of 70 % for nitric oxide ion was observed at 30o C with 4 % and 0.05 % of sucrose and NaNO3 respectively (Fig. 4). The chelating effect (75 %) was highest at 30o C in the medium containing 4.5 % of sucrose with 0.05 % of NaNO3. Antioxidant potential as assayed by different procedures demonstrated decrease in activity with the further increase of NaNO3

concentration and decrease in the temperature and sucrose concentration (Fig. 5). Effect of variables on total phenolic content The interactive effect (X1X2) was highly significant with p value ≤ 0.005 while linear (X1) and squared effect of sucrose (X1

2) and interactive between sucrose-temperature (X1X3) is significant with p value ≤ 0.05. The highest amount of TPC was obtained at 4.5 % of sucrose and with 0.05 % of NaNO3 concentration at 32o C (Fig. 6) and yield decreased with the decrease in temperature and sucrose concentration and with the increase in NaNO3 concentration.

Validation of results Thus, from the overall assessment (Fig 1-6), the optimized conditions for different assay procedures, it may be concluded as 4% sucrose, 0.05 % NaNO3 and incubation temperature of 30o C while other media components were retained as standard concentration in Czapek Dox’s

medium. The F value and R2 value showed that the model correlated well with measured data and was statistically significant. To confirm the model adequacy for predicting maximum scavenging activity, the verification experiment using the optimum medium composition (mentioned above) was performed. The experiments under optimized conditions were carried out


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in triplicates which showed 88.1%, 74.9% and 70.2% scavenging effect for DPPH radical, ferrous ion and nitric oxide ion, respectively. The yield for TPC was 22.3 mg/ml and reducing power showed 2.0 absorbance with 71.5% activity for FRAP Assay. A good agreement between the predicted and experimental results verified the validity of the model and the improvement of antioxidant activity indicated that RSM is a powerful tool for determining the exact optimal values of the individual factors and the maximum response value. Discussion Mushrooms and plants have been known for production of antioxidant compounds but more recently fungi have attracted the attention of scientific community because of their ability to produce wide range of secondary metabolites many of which are known to possess antioxidant activity. The fungi have an edge over mushrooms and plants because of their amenability to easy manipulations. Optimization of fermentation medium and conditions is very important for maximizing the yield and minimizing the production cost of many secondary metabolites. Most of the recent optimization efforts have relied on statistical experimental design and response surface analysis [15]. Statistical design is a powerful tool that can be used to account for the main as well as interactive influences of fermentation parameters on the process performance; thus the present study is based on this. It is an efficient way to generate useful information with limited experimentation, thereby cutting the process development time and cost [16].

The testing of different carbon and nitrogen sources revealed sucrose and sodium nitrate to be the most promising for obtaining the best antioxidant activity by Aspergillus terreus which is in consonance with earlier studies carried out on Aspergillus candidus. However, it contravenes the general perception that glucose and starch are known to be the best carbon source for the fungal growth [17]. The results thus explain that a fungal species may have the ability to utilize a particular carbon source for vegetative growth but may not be able to use it for production of specialized structural molecules. This signifies that availability of easily utilizable carbon and nitrogen sources promote primary metabolism and feeding with more slowly metabolizable compounds (sucrose and NaNO3) may lead to the formation of secondary metabolites. All carbon and nitrogen sources are divided into quickly metabolizable sources and sustainable sources. Quickly metabolizable sources are beneficial for faster growth of microorganisms and relieving their need for long-term accumulation of products. Sucrose and NaNO3 are regarded as sustainable sources, which favors the production of secondary metabolites as these are the results of later growth [18]. The study thus demonstrated the basic composition of Czapek dox’s medium to be the best for effective production of antioxidant activity. In fact, culture media designing has a major impact on the growth of microbes and the production of microbial products [6].

Biomass did not significantly affect the activity, as dextrose supported maximum biomass followed by starch but maximum antioxidant potential as assayed by different procedures was demonstrated by sucrose. Similarly, yeast extract followed by peptone supported maximum biomass but sodium nitrate showed highest activity. However, urea gave minimum biomass accompanied by minimum activity. These observations are in agreement with earlier study on Lentinula edodes which also showed no correlation between mycelial biomass and antibacterial activity [19].

Further analysis of the effect of the medium constituents through Plackett Burman design showed sucrose and NaNO3 to be significant but the significance was less than 50%. The results got further support from the RSM observations where low concentration of NaNO3 in the


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medium favors the antioxidant activity. This demonstrates the important role of nitrogen source to regulate secondary metabolite production [20]. Sucrose is beneficial for the growth of fungi as well as for production of secondary metabolites which are responsible for their antioxidant activity.

Though KCl, MgSO4 and K2HPO4 did not significantly affect the antioxidant activity but are retained at standard concentration in Czapek Dox’s medium because magnesium and

potassium are required by all the fungi for a variety of regulatory functions and control the biosynthesis of various secondary metabolites. This shows that the medium most suitable for growth may or may not be equally effective for secondary metabolites and thus enhancement of secondary metabolites can only be achieved through systematic manipulation of different parameters [21].

It is commonly known that the antioxidative effects are mainly due to redox properties of phenolic compounds which can play an important role in absorbing and neutralizing free radicals by acting as reducing agents and hydrogen donor or quenching singlet and triplet oxygen or decomposing peroxides [22]. The importance of phenolic contents has been endorsed by their high content in Aspergillus terreus and their antioxidant activity is quite comparable to that of many mushrooms as well as medicinal plants. Further, the better production of phenolics under optimized conditions also enhanced the antioxidant activity.

The results obtained indicate Aspergillus terreus to be a potent antioxidant producer having broad spectrum against various free radicals. Previous studies have shown the linear correlation between total phenolic content and antioxidant activity, in this study too, total phenolic content of Aspergillus terreus correlated well with the antioxidant activity. The extract obtained from Aspergillus terreus showed good activity against DPPH radical by neutralizing the free radical character of purple color DPPH, either by transfer of electron or hydrogen atom, to yellow colored diamagnetic molecule revealing hydrogen donating property of phenolic compounds present in the extract which can be supported by the positive correlation(r =0.856) between the results of DPPH assay and TPC [23]. Similarly, positive correlation(r =0.835) was found between reducing power assay and TPC. Reducing power assay proves the potential of the phenolic compounds in the extracts to act as reductones that inhibit lipid peroxidation by donating a hydrogen atom thereby terminating the free radical chain reaction. Moreover, this reducing potential may be due to the di or monohydroxy substitution in the aromatic rings that possess potent hydrogen donating ability [10]. Results of FRAP assay are also positively correlated(r =0.828) with TPC and good activity of the fungal extract for FRAP assay denotes its reducing potential. Generally the reducing properties are associated to the breaking of free radical chain by donating a hydrogen atom [12]. The extracts also showed appreciable chelating activity of metals, as the transition metals such as ferrous ion can stimulate lipid peroxidation by generating hydroxyl radicals through Fenton reaction. The chelating activity for ferrous ion was assayed by the inhibition of formation of red colored ferrozine and ferrous complex. There was positive correlation (r =0.820) between chelating activity and TPC [10]. As evident from studies, the extracts are able to scavenge nitric oxide ion and correlation between TPC was found to be positive (r =0.849). NO. is an effective reactive radical that acts as an important oxidative biological signaling molecule in a large variety of diverse physiological processes, including neurotransmission, blood pressure regulation, defense mechanisms, smooth muscle relaxation and immune regulation. Overproduction of reactive nitrogen species is called nitrosative stress. Nitrosative stress may lead to nitrosylation reactions that can alter the structure of proteins and


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so inhibit their normal function and act as a potent oxidizing agent that can cause DNA fragmentation and lipid peroxidation [24]. Most of the literature is available on antioxidant activity of plants and mushrooms though some of the fungi are known to produce antioxidant activity. To the best of our knowledge apparently this is the first systematic report on antioxidant activity of Aspergillus terreus demonstrated by different assay procedures and its optimization by statistical methods. Under optimal condition, Aspergillus terreus showed 88.1%, 74.9% and 70.2% scavenging effect for DPPH radical, ferrous ion and nitric oxide ion, respectively. The yield for TPC was 22.3 mg/ml and reducing power showed absorbance of 2.0 with 71.5% activity for FRAP Assay. The results showed the scavenging effect for DPPH radical, ferrous ion and nitric oxide ion was enhanced by 1.07, 1.1 and 1.1 folds, respectively while reducing potential and ferric reduction rate was enhanced by 1.5 and 1.1 folds. The production of TPC was enhanced by 1.4 folds.

These results are comparable with the antioxidant activity of various other fungi, Aspergillus candidus, Chaetomium sp., Cladosporium sp, Colletotrichum gloeosporioides [25] and many mushrooms such as Lentinus edodes, Volvariella volvacea, [26] and many medicinal plants like Amaranthus paniculatus, Aerva lanata, Coccinia indica, Coriandrum sativum [27].

The study thus suggests that not only mushrooms and plants but some other fungi may also be a good source of antioxidant compounds and Aspergillus terreus is one such potential candidate offering a better scope for production and easier down streaming of such bioactive compounds. These findings will facilitate the further studies to gain better understanding of production of bioactive metabolites in fungi, which will be helpful in their biotechnological mass production in near future. Acknowledgements Priyanka Chandra is thankful to UGC for Rajiv Gandhi National Fellowship vide no.F.42 (SC)/2008 (SA-III). References

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2. Fox, E.M. and Howlett, J.B. (2008) Curr. Opin. Microbiol. 11, 1-7 3. Valentao, P., Fernandes, E., Carvalho, F., Andrade, P.B., Seabra, R.M. and Bastos, M.L.

(2002) Biol. Pharm. Bull. 25, 1320-1323 4. Tiwari, O.P. and Tripathi, Y. (2007) Food Chem. 100, 1170-1176 5. Mathew, S. and Abraham, T.E. (2006) Food Chem. 94, 520-528 6. Miao, L., Kwong, T.F.N. and Qian, P.Y. (2006) Appl. Microbiol. Biotechnol. 72, 1063-

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9. Arora, D.S., Chandra P. (2010) Braz. J. Microbiol. 41, 465-477 10. Zhao, R., Xiang, Z.J., Ye, T.X., Yaun, J.Y. and Guo, X.Z. (2006) Food Chem. 99, 767-

774 11. Chang, L.W., Yen, W.J., Huang, S.C. and Duh, P.D. (2002) Food Chem.78, 347-354.


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12. Othman, A., Ismail, A., Ghani, N.A. and Adenan, I. (2007) Food Chem. 100, 1523-1530 13. Kang, K.S., Yokozawa, T., Kim, H.Y. and Park, J.H. (2006) J. Agri. Food Chem. 54,

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0717-3458 17. Yen, G.C. and Chang, Y.C. (1999) J. Food Prot. 62, 657–661 18. Tandon, R.N. and Singh, G.J. (1956) Proceedings: Plant Sciences 44, 61-67 19. Hassegawa, R.H., Kasuya, M.C.M. and Vanetti, M.C.D. (2005) Electronic J.

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M.M., Figueiredo, A.C., Barroso, J.G. and Pedro, L.G. (2007) Food Chem. 105, 146-155 24. Abas, F., Lajs, N.H., Israf, D.A., Khoziroh, S. and Kalsom, Y.U. (2006) Food Chem. 95,

566-573 25. Rios, M.F., Pajan, C.M.G., Galan, R.H., Sanchez, A.J.M. and Callado, I.G. (2006) Bio.

Med. Chem. Lett. 16, 5836-5839 26. Cheung, L.M. and Cheung, P.C.K. (2005) Food Chem. 89, 403-409 27. Ali, S.S., Kasoju, N., Luthra, A., Singh, A., Sharanabasava, H., Sahu, A. and Bora, U.

(2008) Food Res. Int. 41, 1–15


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http://apt.allenpress.com/perlserv/?request=get-toc&issn=0362-028X&volume=62&issue=6

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Figure Captions Fig. 1 Contour plot showing effect of different variables on DPPH assay (hold value: 0.05g/L of sodium nitrate) Fig. 2 Contour plot showing effect of different variables on reducing power (hold value: 0.05g/L of sodium nitrate) Fig. 3 Contour plot showing effect of different variables on FRAP assay (hold value: 0.05g/L of sodium nitrate) Fig. 4 Contour plot showing effect of different variables on nitric oxide ion scavenging activity (hold value: 0.05g/L of sodium nitrate) Fig. 5 Contour plot showing effect of different variables on ferrous ion scavenging activity (hold value: 0.05g/L of sodium nitrate); Fig. 6 Contour plot showing effect of different variables on total phenolic content (mg/ml) (hold value: 0.05g/L of sodium nitrate)


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Table 1 Effect of various carbon sources on antioxidant potential of Aspergillus terreus*

1DPPH-1.1-diphenyl -2-picryl hydrazyl; 2FRAP- Ferric reducing antioxidant power; 3NO-nitric oxide; 4TPC-total phenolic content

*(Arora and Chandra 2010)

% activity Dextrose Maltose Lactose Starch Sucrose

Glycerol

DPPH1 Assay 62.48±0.14 60.39±0.34 54.58±0.8 50.30±0.05 82.77±0.05 32.87±0.23

Reducing power 1.2± 0.32 1.06±0.13 0.911±0.29 0.932±0.34 1.36±0.20 0.871±0.09

Fe2+ scavenging activity

59.3± 0.30 57.2±0.11 49.3±0.31 50.3±0.72 68.23±0.13 43.4±0.1

FRAP2 assay 54.2±0.18 52.4±0.17 43.4±0.09 45.4±0.60 64.2±0.25 40.4±0.34

NO3 scavenging

activity

30min 60min 90min 120min 180min

20.9±0.02 32.4±0.01 40.3±0.03 48.6±0.01 54.4±0.07

19.2±0.03 31.8±0.13 39.2±0.23 45.3±0.45 50.3±0.56

15.3±0.21 22.9±0.07 30.4±0.41 36.3±0.08 40.2±0.25

10.3±0.03 262±0.22 334±0.42 38.2±0.30 40.3±0.39

33.4±0.54 42.3±0.07 50.4±0.19 58.3±0.26 64.4±0.17

10.2±0.67 25.3±0.01 32.6±0.3 36.3±0.22 38.6±0.45

TPC4 (mg/ml) 11.06±0.21 8.59±0.30 3.34±0.45 5.78±0.087 16.74±0.02 2.9±0.11

Biomass (mg) 465±0.9 293±0.55 265±0.7 407±0.6 315±0.4 105±0.67


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Table 2 Effect of various nitrogen sources on antioxidant potential of Aspergillus terreus*

1DPPH-1.1-diphenyl -2-picryl hydrazyl; 2FRAP- Ferric reducing antioxidant power; 3NO-nitric oxide; 4TPC-total phenolic content *(Arora and Chandra 2010)

Antioxidant activity (%)

Nitrogen sources DPPH1 Assay

Reducing power

Fe2+

scavenging activity

FRAP2 assay

NO3

scavenging activity

TPC4 (mg/ml)

Biomass (mg)

Nitrogen rich organic supplements

Yeast extract 73.39±0.05 1.26±0.32 64.5±0.4 62.3±0.55 60.4±0.11 10.11±0.4 460±0.21

Peptone 69.73±0.04 1.13±0.65 65.3±0.8 63.6±0.43 59.2±0.21 13.83±0.45 455±0.54

Malt extract 69.0±0.3 0.792±0.45 47.7±0.05 41.3±0.5 30.3±0.43 8.7±0.5 310±0.4

Casein 70.1±0.01 1.1±0.09 40.2±0.4 38.3±0.7 32.4±0.5 7.28±0.05 312±0.66

Soyabean meal 61.99±0.22 0.916±0.9 46.2±0.6 42.3±0.7 38.3±0.6 8.2±0.67 280±0.67

Urea 21.7±0.7 0.11±0.2 - - - 0.7±0.01 98±0.6

Inorganic nitrogen sources

KNO3 52.02±0.04 0.427±0.08 32.8±0.02 30.4±0.08 24.3±0.1 2.2±0.05 220±0.01 (NH4)2 SO4 62.11±0.56 0.920±0.03 60.2±0.56 58.2±0.51 42.4±0.11 7.1±0.5 245±0.1

(NH4)H2 SO4 50.55±0.5 0.432±0.3 28.2±0.1 25.3±0.02 18.4±0.05 2.2±0.05 206±0.001

NH4NO3 46.12±0.1 0.84±0.06 43.4±0.05 40.2±0.5 36.4±0.6 6.3±0.1 198±0.02

NaNO3 82.77±0.05 1.36±0.20 68.23±0.13 64.2±0.25 64.4±0.17 16.74±0.02 315±0.7

(NH4)2Cl 54.73±0.7 0.72±0.66 42.8±0.5 40.3±0.01 42.4±0.11 5.24±0.4 223±0.05


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Table 3 Plackett-Burman design variables with different antioxidant potential as response

Variables (g/L) Antioxidant activity (% activity) Run Sucrose NaNO3 K2HPO4 MgSO4 KCl DPPH1

Assay Reducing

power Fe2+

scavenging activity

FRAP2 assay

NO3 scavenging

activity

TPC4 (mg/ml)

1 5.0 0.000 0.18 0.000 0.000 70.3 0.70 53.2 52.60 55.30 6.2 2 5.0 0.350 0.00 0.090 0.000 78.4 1.01 62.7 60.30 60.32 12.3 3 0.0 0.350 0.18 0.000 0.090 35.7 0.32 25.3 22.60 26.20 3.2 4 5.0 0.000 0.18 0.090 0.000 60.2 0.56 50.2 50.44 52.30 4.8 5 5.0 0.350 0.00 0.090 0.090 82.4 1.36 68.4 64.12 64.40 16.2 6 5.0 0.350 0.18 0.000 0.090 75.1 0.91 60.1 58.20 59.30 10.1 7 0.0 0.350 0.18 0.090 0.000 32.6 0.26 20.4 18.80 22.34 3.0 8 0.0 0.000 0.18 0.090 0.090 58.2 0.53 51.8 50.60 50.80 5.8 9 0.0 0.000 0.00 0.090 0.090 30.1 0.22 15.2 15.90 18.40 2.6 10 5.0 0.000 0.00 0.000 0.090 72.1 0.72 56.8 55.34 56.40 7.3 11 0.0 0.350 0.00 0.000 0.000 66.7 0.63 51.8 50.40 50.22 5.3 12 0.0 0.000 0.00 0.000 0.000 0.0 0.00 0.0 0.00 0.00 0.0 13 2.5 0.175 0.09 0.045 0.045 83.3 1.32 67.3 64.80 66.40 15.3 14 2.5 0.175 0.09 0.045 0.045 83.8 1.35 68.2 65.42 66.70 16.7



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Table 4 Box-Behnken design of different variables with their responses


Variables (g/L) Antioxidant activity (% activity) Run Sucrose NaNO3 Temperature DPPH1

Assay Reducing

power Fe2+

scavenging activity

FRAP2 assay

NO3 scavenging

activity

TPC4(mg/ml)

1 1 0.05 25 62.3 0.686 60.8 58.3 58.6 8.6 2 5 0.05 25 84.3 1.6 69.2 67.3 65.2 17.2 3 1 0.35 25 84 1.6 70.2 68.3 66.2 16.4 4 5 0.35 25 56.2 0.468 50.2 46.3 47.3 5.6 5 1 0.2 15 52.8 0.381 48.2 46.3 45.2 4.3 6 5 0.2 15 57.8 0.46 50.1 48.6 48.6 5.2 7 1 0.2 35 78.3 0.815 58.6 55.6 57.2 7.2 8 5 0.2 35 84.3 1.7 69.2 66.3 66.8 20.2 9 3 0.05 15 76.3 0.756 54.2 50.3 50.8 9.2 10 3 0.35 15 77.2 0.792 55.2 52.3 52.8 10.3 11 3 0.05 35 84.2 1.6 69.3 66.3 65.4 18.3 12 3 0.35 35 83.2 1.17 66.8 62.7 63.2 20 13 3 0.2 25 82.6 1.3 67.4 63.2 65.8 16.2 14 3 0.2 25 80.2 1.29 68.9 64.8 65.2 15.2 15 3 0.2 25 82.8 1.4 67.6 67.6 65.4 16.3 16 3 0.2 25 81.3 1.3 69.2 65.6 66.8 16.8 17 3 0.2 25 83.7 1.41 68.23 64.2 64.4 14.3


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Table 5 Regression coefficients for different antioxidant potential as responses

Term DPPH1 Assay Reducing

power Fe2+ scavenging activity

FRAP2 assay NO3 scavenging activity

TPC4

Constant -4.26 -2.416 ** -9.65 -13.52 * -12.45 * -17.11 * Sucrose 25.07 *** 0.505 ** 9.96 ** 9.09 ** 9.70** 6.96 **

NaNO3 113.62 * 6.644 ** 83.59 * 102.16 95.57 * 32.59 *

Temperature 2.17 * 0.149 ** 3.73 *** 3.80 ** 3.68 ** 0.99 *

Sucrose × Sucrose -2.79 *** -0.061 ** -1.31 ** -1.09 ** -1.22 ** -1.13***

NaNO3× NaNO3 33.44 -0.244 -18.13 -29.56 -57.67 ** 31.44

Temperature×Temperature -0.03* -0.003 ** -0.06 *** -0.07 ** -0.06 ** -0.02 *

Sucrose × NaNO3 -41.50*** -1.705 *** -23.67 *** -25.83 *** -21.25 ** -16.17 ***

Sucrose×Temperature 0.01 0.010 ** 0.11 1 0.10 * 0.08 * 0.15

NaNO3×Temperature -0.32 -0.078** -0.58 -0.93 -0.70 0.10

R2 88.4% 93.2% 91.8% 89.6% 89.7% 91.0%

Model F-Value 5.91 * 10.66 *** 8.75 *** 6.72 ** 6.76 * 7.86 **

Lack of fit value 39.16 19.16 44.16 11.58 41.51 12.61 * p≤0.5;

** p ≤ 0.05;

*** p≤0.005



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Figure 1

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Figure 3

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Optimization of antioxidant potential of Aspergillus terreus through different statistical approaches

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