Journal of Chemistry

Journal of Chemistry / 2019 / Article

Research Article | Open Access

Volume 2019 |Article ID 5204534 | 11 pages | https://doi.org/10.1155/2019/5204534

Optimization of Microwave-Assisted Extraction Saponins from Sapindus mukorossi Pericarps and an Evaluation of Their Inhibitory Activity on Xanthine Oxidase

Academic Editor: Gabriel Navarrete-Vazquez
Received15 Oct 2018
Revised18 Dec 2018
Accepted27 Dec 2018
Published23 Jan 2019

Abstract

A microwave-assisted extraction (MAE) method was applied to separate saponins from Sapindus mukorossi pericarps. The most important factors of the six extraction parameters were selected using Plackett–Burman designs; therefore, the further extraction procedure was optimized using the Box–Behnken designs; meanwhile, the optimum processing parameters and well-pleasing saponins extraction rate were inferred. The final operation conditions were the ethanol concentration of 40%, soaking time of 3 h, particle size of 80–100 meshes, extraction time of 13 min, solvent-solid ratio of 19 mL/g, and microwave power of 425 W. Based on the optimal extraction parameters, the extraction rate of the saponins by means of MAE technique reached 280.55 ± 6.81 mg/g, which exceeds yields acquired using conventional manners. Saponins from S. mukorossi have obvious xanthine oxidase inhibitory properties in vitro compared with allopurinol. The saponins displayed a type of competitive inhibition of xanthine oxidase. In conclusion, a MAE technique in association with a response surface design provides an efficient extraction tactics, which could sufficiently isolate saponins from S. mukorossi pericarps; further, this technique could be applied to the dissociation of other bioactive substances from plant sources. In addition, the saponins may be a promising alternative to conventional medicine to treat gout and other inflammation-associated disorders to mitigate the side effects of traditional drugs.

1. Introduction

Sapindus mukorossi of Sapindaceae family, commonly famous for soapnut, washnut, reetha, or ritha, is a well-known, handsome, deciduous, and valuable tree species. It is indigenous to the hilly areas of China and Japan below an altitude of 1000 m and is widely cultivated in North India [1, 2]. As it is rich in valuable saponins (possessing the property of outstanding surface activity), S. mukorossi is an ecofriendly and promising alternative material of biosurfactant for producing shampoos, cosmetic cleansers, and detergents in sanitary and cosmetic products [3]. S. mukorossi saponins can be applied to remove heavy metals or hydrocarbons from polluted soil and waste water and for enhancing oil recovery, dye solubilization, and nanoparticle synthesis [47]. Moreover, S. mukorossi saponins are widely applied to pharmaceutical industry, due to its manifold pharmacological effects, including antimicrobial activity [811], antitumor functions [1214], anti-inflammatory effects [15, 16], and insecticidal activity [17, 18]. S. mukorossi pericarps are a main source of saponins, which make up 7% to 27% of the whole fruit [19]. Therefore, it is of our great interest to optimize the extraction process of saponins from S. mukorossi pericarps.

Inflammation is the susceptive condition of blood vessel hyperemia. The vascular reaction is the major part of the inflammation process, which results from corporal or biochemical injury factors in living tissue accompanied by redness, swelling, pyrexia, pain, and dysfunction [19, 20]. Xanthine oxidase (XO) is the key enzyme of uricogenesis resulting in a painful inflammation: gout. Moreover, chronic inflammation can cause hyperuricemia or other chronic diseases. Clinically, inflammatory disorders are generally controlled by steroidal or nonsteroidal drugs. Nevertheless, long-term use of these drugs e.g., betamethasone and acetylsalicylic acid can lead to gastrointestinal, renal, and cardiovascular disorders or other side effects [21]. It is important to find a low or even nontoxic anti-inflammatory substitute; therefore, plant products are an ideal potential natural treatment. Previous studies have investigated the anti-inflammatory activity of the S. mukorossi saponins. Nonetheless, in the current investigation, their inhibition activity on XO was still at an exploratory stage. Therefore, it is necessary to evaluate the inhibition model of XO in vitro to provide scientific evidence for further research on S. mukorossi saponins.

Traditional methods, including maceration extraction (ME) [22] and Soxhlet and reflux extraction (SE and RE) [23], and nontraditional techniques, supercritical fluid extraction (SCFE), and ultrasonic-assisted extraction (UAE) [24], are generally used for saponins extraction. Nonetheless, some disadvantages are associated with these methods (e.g., long-time consumption, tedious extraction processes, massive organic solvent usage, high energy input, low yield, high apparatus requirements, complex operations, and environmental issues) [25]. Consequently, it is vitally important to select a novel, efficient, and green technique for saponins extraction, which could overcome the drawbacks of traditional techniques. Microwave-assisted extraction (MAE) has attracted much attention for its shorter extraction duration [26], decreased solvent usage, higher extraction efficiency [27], lower operating costs, and environmental friendliness in comparison with traditional and other advanced extraction methods [28, 29]. Specially, microwave energy enables heat to instantaneously and simultaneously transfer to the solvent and the entire material in the extraction process by the special heating mechanism with electromagnetic radiation. In recent years, MAE has been used to separate various bioactive components including saponins, essential oil, flavonoids, and terpenoids from plant materials [17, 26, 28, 29].

Plackett–Burman designs (PBDs) and Box–Behnken designs (BBDs) are generally applied to RSM based on the requirements and experimental conditions. PBD is a first order polynomial design, which is a practical RSM for preliminary studies to screen principal element from packs of associated parameters for the requested response variables [29, 30]. In this study, these variables are either fixed or eliminated in the subsequent investigation. Moreover, as a favorable type of design for supporting a response surface, BBD is further employed to assess second-order multivariate technique in terms of three-level synsemantic factorial design [31]. BBD has been generally performed to optimize the extraction process of bioactive components from natural raw materials since it offers sufficient information about the main and interaction effects, which cannot be easily evaluated by univariate techniques [32, 33]. Additionally, the model outcomes can be clearly exhibited on the response surface plot. As far as we know, there is no study involved on using statistical optimization methodology for the maximum extraction of S. mukorossi saponins. Herein, this paper is mainly concentrated on the optimization of the microwave-assisted extraction procedure by both BBD and PBD. SE, RE, and ME were carried out to compare performance characteristics with MAE. Additionally, the inhibitory activity of saponins on XO in vitro was preliminary studied.

2. Experimental

2.1. Reagents and Materials

Xanthine oxidase (XO) was of biochemical reagent (BR) grade, allopurinol (purity ≥ 98%) and oleanolic acid (purity ≥ 98%) were of analytical standard, and xanthine was of pure grade. All of them were purchased from Yuanye Bio-Technology Co., Ltd. (Shanghai, China). Ethanol and dimethyl sulfoxide (DMSO) were of analytical reagent (AR) grade and were purchased from Xilong Scientific Co., Ltd. (Guangdong, China).

S. mukorossi fruits were collected in October 2017 from Jiangxi Normal University (Nanchang, China) and authenticated by Prof. Yisheng Tu (College of Life Sciences, Jiangxi Normal University). A voucher specimen (00049836) had been deposited at Lushan Botanical Garden Herbarium (The Chinese Academy of Sciences, Jiangxi, China). The pericarps were separated from fresh fruits, shade-dried for 15 days at room temperature, and then ground using a 2500Y-grinder (swing-type high-speed traditional Chinese medicine pulverizer, Yongkang Boou Hardware Products Co., Ltd., China) and sieved with different sizes. These homogeneous powder samples were preserved in a sealed desiccator at 4°C before future experiments.

2.2. MAE Apparatus

The apparatus for the MAE process was equipped with a WP800SL23 microwave oven (Guangdong Galanz Enterprise Co., Ltd., China) operating at a frequency of 2.45 GHz, a multimode reactor, and a thermometer IR sensor, by which both time and power can be adjusted through its control panel as described in a previous study of our research group [26]. Microwave energy could be constantly transmitted to the reactor, and during operation, microwave power could be dynamically regulated by the control panel in accordance with the actual demands. A Clevenger condenser was added on the top of the domestic microwave oven to make it suitable for laboratory use, and the condenser was connected to a round-bottom flask (500 mL) through a hole that was wrapped with polytetrafluoroethylene around the external upper part of the round-bottom flask to avoid microwave leakage [34]. The inside dimension of microwave oven chamber was 215 mm × 350 mm × 330 mm. The whole system worked at atmospheric pressure.

2.3. Extraction and Determination Procedures of S. mukorossi Saponins

The initial single-factor experiments were carried out to ascertain the appropriate ranges of the six parameters for subsequent experimental operation. 1 g of pericarps sample was mixed with a definite volume of solvent and then subjected to MAE. After extraction, the mixtures were cooled and the supernatant was collected by centrifugation at 1000 × g for 10 min at 25°C, followed by filtration using a 0.45 µm nylon membrane. The results of HPLC-MS have shown that oleanolic type is the main compounds of total saponins from pericarps of S. mukorossi [35], and the oleanolic acid was always regarded as the standard to determine the content of S. mukorossi saponins in previous studies [19, 36]. Herein, we also employed oleanolic-type as the main compounds for the determination the content of saponins from pericarps of S. mukorossi. The result of determination showed that the oleanolic-type triterpenoid saponins took a proportion of 76.05% ± 1.52 in the obtained saponins in our study. The content of S. mukorossi saponins was determined by HPLC analysis as described by Upadhyay et al. [37].

2.4. Optimizing Processes for S. mukorossi Saponins Extraction

The processes to optimize S. mukorossi saponins extraction conditions were performed as follows: (1) screen the most significant factors from the six parameters by PBD and (2) optimize the chosen factors to obtain the optimum operational parameters and forecast an acceptable saponins extraction yield by BBD.

2.4.1. Screening the Most Significant Factors by PBD

PBD determined the most significant variables influencing the extraction of saponins from S. mukorossi pericarps. The design standards assumed that no interplay effects existed between each parameter, and they were built on the following polynomial equation:where denotes the predicted value, and refer to the invariable describing the equation intercept and the regression coefficient, respectively, and Xi represents the coded factors (AF). These six parameters included microwave power (A), irradiation time (B), solvent-solid ratio (C), ethanol concentration (D), soaking time (E), and particle size (F) and were screened at two different levels (–1 and +1) with 12-run experiments by PBD, as presented in Table 1. The levels of independent factors were ascertained in terms of the single-factor experimental results.


RunABCDEFYield (mg/g)
ActualPredicted

1540 (+1)15 (+1)10 (−1)80 (+1)3 (+1)80–100 (+1)241.17226.38
2230 (−1)5 (−1)10 (−1)40 (−1)1 (−1)40–60 (−1)160.00151.90
3540 (+1)5 (−1)10 (−1)40 (−1)3 (+1)40–60 (−1)190.50195.29
4540 (+1)5 (−1)20 (+1)80 (+1)3 (+1)40–60 (−1)218.50218.68
5230 (−1)5 (−1)10 (−1)80 (+1)1 (−1)80–100 (+1)143.17145.96
6540 (+1)15 (+1)20 (+1)40 (−1)1 (−1)40–60 (−1)261.17258.99
7230 (−1)15 (+1)10 (−1)80 (+1)3 (+1)40–60 (−1)175.83185.65
8540 (+1)5 (−1)20 (+1)80 (+1)1 (−1)80–100 (+1)209.50216.01
9540 (+1)15 (+1)10 (−1)40 (−1)1 (−1)80–100 (+1)224.17229.65
10230 (−1)5 (−1)20 (+1)40 (−1)3 (+1)80–100 (+1)197.17190.99
11230 (−1)15 (+1)20 (+1)80 (+1)1 (−1)40–60 (−1)216.83212.32
12230 (−1)15 (+1)20 (+1)40 (−1)3 (+1)80–100 (+1)221.83228.01

ANOVA
SourceSum of squaresDegree of freedomMean squareF valueP ValueInference
Model11841.0261973.5016.850.0035
Residual517585.645117.13
Cor. totalb12426.6611

Regression data
TermEffectCoefficientStandard errorF ValueT ValueP ValueInference
A38.3619.183.1237.696.150.0017
B37.0318.513.1235.125.930.0020
C31.6915.853.1225.735.080.0039
D−8.31−4.153.121.77−1.330.2412
E5.032.513.120.650.800.4576
F2.361.183.120.140.380.7210
T-value limit2.57Value of Bonferroni limit4.88

aThe results were obtained with Design Expert 8.0 software. A is the microwave power, B is the microwave time, C is the solvent-solid ratio, D is the ethanol concentration, E is the soaking time and F is the particle size. bTotals of all information corrected for the mean; , significant; , highly significant; , extremely significant.
2.4.2. Optimization of the Saponins Extraction Conditions by BBD

After determining the most influential independent variables using PBD, the three most significant parameters regarding the extraction yield of saponins were evaluated by BBD at three levels. The ranges and levels of influencing variables are displayed in Table 2 based on the results from pre-experimental runs. The independent parameters were combined with the extraction yields of saponins. Experimental runs were implemented stochastically to decline the effects of uncontrolled factors in the actual experiments introduced by exterior factors (operative and instrumental errors). The following quadratic polynomial equation was used to fit the correlations between the saponins extraction yield and the three selected extraction factors. The complete quadratic equation for the developed model iswhere is the predicted response; , , , and represent the regression coefficients for the intercept, linearity, square, and interaction, separately; and Xi refers to the variable.


Saponins
No.ABCYield (mg/g)ANOVA
ActualPredictedSourceSum of squaresDegree of freedomMean squareF valueP value

1230 (−1)10 (0)9 (−1)165.86166.49Modelb2797493108.27146.4729<0.0001∗∗∗
2385 (0)5 (−1)15 (+1)247.71245.48A845118451.30398.s2554<0.0001∗∗∗
3540 (+1)15 (+1)12 (0)239.83243.095B261012610.03122.994<0.0001∗∗∗
4540 (+1)5 (−1)12 (0)220.57223.43C6801679.7032.029820.0008∗∗∗
5230 (−1)15 (+1)12 (0)197.41194.55AB2711270.9312.767260.0091∗∗
6385 (0)5 (−1)9 (−1)225.45228.085AC110.760.0356680.8556
7385 (0)10 (0)12 (0)272.13272.282BC111.080.0509690.8278
8385 (0)15 (+1)9 (−1)260.94263.17A214588114587.86687.4321<0.0001∗∗∗
9385 (0)10 (0)12 (0)269.05272.282B26751674.9531.806110.0008∗∗∗
10540 (+1)10 (0)15 (+1)250.56249.93C296196.044.5258820.0709
11385 (0)10 (0)12 (0)274.63272.282Residual149721.22
12540 (+1)10 (0)9 (−1)237.86232.365Lack of fit123340.906.328630.0534
13230 (−1)5 (-1)12 (0)145.23141.965Pure error2646.46
14385 (0)15 (+1)15 (+1)285.28282.645Cor. totalc2812316
15230 (−1)10 (0)15 (+1)180.3185.795Credibility analysis of the regression equations
16385 (0)10 (0)12 (0)270.64272.282Std. Dev.dMeanC.V.e %PressR2Adjust. R2Predicted R2Adequacy precision
17385 (0)10 (0)12 (0)274.96272.2824.61236.381.952003.520.99470.98790.928839.8177

aThe results were obtained using Design Expert 8.0 software; bA is the microwave power, B is the microwave time, C is the solvent-solid ratio; , significant; , highly significant; , extremely significant. cTotals of all information corrected for the mean; dstandard deviation; ecoefficient of variation.
2.5. Comparison of MAE with Traditional Techniques

The conventional techniques including ME, RE, and SE approaches were employed for saponins extraction to compare with the MAE technique. The ME was implemented at 25°C for 48 h while the RE and SE procedures were implemented in a heating mantle with a maximum operating power of 1 kW for the extraction of 4 h. The other operation parameters were identical to the optimized conditions.

2.6. Evaluation of the Inhibitory Activity of Saponins on XO In Vitro

A XO inhibition assay using xanthine as a substrate was performed as reported by Filha et al. [38] with minor modulations. To be brief, 0.48 mL of saponins extracts with a series of concentrations (5, 25, 50, 75, and 100 μg/mL) were blended with 1.5 mL of XO solution (0.28 units/mL in phosphate buffer) and 2.4 mL of phosphate buffer (0.07 mM, pH 7.5), and the mixed solution was preincubated at 25°C for 15 min. After incubation, the reaction was initiated by adding 1.6 mL of xanthine (0.15 mM), and the absorbance was recorded at 295 nm every 2 seconds for 2 min using a UV spectrophotometer. The extractions were replaced with dimethyl sulfoxide solution/phosphate buffer without extract solution as a negative control, and allopurinol (5–100 μg/mL in phosphate buffer) served as a positive control. The trials were repeated three times, and the XO inhibitory rate was calculated as the percent inhibition of XO expressed by the following equation:where is the slope of linear change in absorbance per second without saponins extract and is the slope of the linear change with saponins. Lineweaver–Burk plot was employed to illustrate the enzymatic inhibitory mode of saponins on XO.

2.7. Statistical Analysis

The data from PBD and BBD during the experimental processes were implemented using Design Expert 8.0 software. All the experimental runs were performed in triplicate, and all the values are expressed as the average value ± standard deviation.

3. Results and Discussion

3.1. Screening the Most Significant Factors by PBD

Six parameters were analyzed by PBD for their influence on the extraction rate of saponins. The design matrix was employed to select the most pronounced variables for saponins extraction process, and the corresponding responses are shown in Table 1. The experimental results are formulated using the following second-order polynomial equation:

Depending on the results from PBD, the absolute T values of each variable are presented in Table 1. The parameters were deemed to be statistically significant, as the T values of parameters are higher than both the T-value limit (2.57) and the Bonferroni limit (4.88). A supporting plot for variable analysis is shown in the Pareto chart of effects (Figure 1), which is composed of several bars reflecting a length proportional to the absolute value. The parameters’ main effects were rank-ordered by significance. The variables, arranged in sequence, were A > B > C > D > E > F. Consequently, three parameters (A, B, and C) of six independent variables had highly pronounced influences on the saponins extraction efficiency as demonstrated in the Pareto chart by their T values, which showed much higher value than the T value of the Bonferroni limit. Similar results were also found in reports by Wei et al. and Gao [39, 40]. Besides, these favorable influences on the saponins extraction rate were exhibited by the three screened crucial variables, meanwhile raising their values contributed to saponins extraction yield. The statistical analysis results were a good fit to the P values acquired from the regression analysis (Table 1) as well. Meanwhile, the influences of other parameters such as the ethanol concentration (negative effect), the soaking time (positive effect), and the particle size (positive effect) were determined to have a relatively insignificant influence on this response value over the range of factors investigated; these abovementioned extraction parameters had a relatively little influence on the saponins extraction efficiency. Consequently, according to the results from Table 1, the ethanol concentration, soaking time, and particle size were fixed at 40%, 3 h, and 80–100 meshes, respectively. The other three variables (A, B, and C) were screened for further optimization studies.

3.2. Optimization of Extraction Conditions by BBD
3.2.1. Experimental Design and Statistical Analysis

The effects of three individual target factors (A, B, and C) were evaluated using a BBD, followed by an optimization of the operating process. The levels of different variables and the relevant responses are displayed in Table 2. Seventeen experimental runs were conducted on the basis of the design. Using multiple-regression analysis on the test results, the estimated responses on the yield of saponins, the experimental results could be evaluated by the following quadratic polynomial equation:

The model adequacy was verified by the F test, determination coefficient (R2), and analysis of variance (ANOVA) for regression as presented in Table 2. The F value, ratio of the regression mean square and residual, indicated the effect of the individually tested variables on the model. The shown P value reflected the significance of every coefficient, which may conversely reveal the model of the interaction effects between the factors [41]. The model was extremely statistically pronounced, as proven by the F test (146.4729). This combined with the low value (<0.0001) confirmed that the regression equation could be appropriately and adequately applied to elucidate a large proportion of the data variances in the response. The variance of the data round the fitted pattern was defined by lack of fit [42]. The lack of fit of the F value (6.3286) and value (0.0534) indicated that each of the variables was an insignificant disparity compared with the pure error and the developed models could be well fitted to predict the responses. The value of the R2 (0.9947) showed that at least 99.47% of the variability in the response suited the model [42]. The significant correlation between the experimental and predicted response values was denoted by the value of the adjusted determination coefficient (R2Adj = 0.9879). Thus, the high value of R2 (0.9947), adjusted R2 (0.9879), and pre-R2 (0.9288) ensured that the developed model illuminated the practical interactive influences between the responses and the operational factors were satisfactorily associated [43]. A low value of coefficient of variance (C.V., 1.95) expressly displayed a high accuracy and great reliability in the experiments performed. The adequacy accuracy measured the signal-to-noise ratio, whose ratio higher than 4 was satisfying. Therefore, the value of 31.81 indicated a competent signal and indisputably supported the fitness of the developed model [44].

3.2.2. Effect of Process Variables on Saponins Extraction

The plotted response surfaces were used to investigate both the effects of the screened variables and the interrelations of the tested variables on the saponins yield by 3D response surface curves with underlying 2D contour plots [45], which showed the optimum extraction conditions as illustrated in Figures 2(a)2(c). Namely, the response surface plot demonstrated the correlation between responses and test levels of each factor and the pattern of interaction effect between each pair of experimental factors. Every figure displayed how the two parameters affected the saponins yield, while the third parameter was unchanged. These plots (circular or elliptical) statistically showed the significance of the interrelations between parameters. The insignificance of the interaction effects between the relevant parameters was reflected in the circular contour plot, whereas the significance was displayed in the elliptical contour plot [41].

Figure 2(a) shows the interaction effect between A and B on the saponins yield at an invariable value of the parameter C with 15 mL/g. The response curve along with the elliptical contour plot demonstrated that the mutual effects between these two factors were significant. When microwave time was held at a lower level (under 13 min), the extraction yields markedly improved with rising irradiation time for a range of microwave power. The yield reached the maximum value in about 13 min and then declined from 420 to 540 W. There was a quadratic effect which exhibited for the influence of microwave power on saponins yield. An acceptable extraction rate was acquired at approximately 420 W, but the yield was reduced at a higher output power. Saponins yield improved with the enhancement of extraction time at an invariable microwave power. This might be explained by the fact that microwave power played a vital role in saponins extraction before a threshold level. After passing the threshold, no increase was observed on the rate of extraction due to saturation [41]. The microwave irradiation sped up cell rupture by instantaneous heating and internal pressure enhancement inside the cells of target samples, which facilitated sample surface breakdown and in turn promoted the diffusion of saponins from the plant cells into the extracting solution, thus increasing the extraction yield. However, after microwave power reached the threshold level (approximately 420 W), increasing microwave time did not significantly affect the extraction yield. In contrast, overexposure of plant sample to the microwave field and/or mass saturation impeded the mass transfer rate of saponins into the extracting solution. This may have caused the degradation of saponins, resulting in a decreased yield of saponins [46]. A similar phenomenon was also observed in microwave-assisted extraction of anthraquinones from R. emodi [47].

Figure 2(b) shows the relationship between the extraction parameters A and C on saponins yield at a defined value of the independent variable B of 10 min. A linear response on the saponins yield was presented for the variable A; additionally, a marked quadratic effect on the saponins yield was presented for variable C. Saponins extraction yield improved with the extraction parameter C and a set extraction power from 230 to 427 W. When extraction power was fixed at 427 W, the yield decreased gradually and demonstrated an unfavorable influence on saponins yield. This phenomenon was similar to the previous study [48].

Figure 2(c) displayed the interaction effects between the independent variables B and C on saponins yield with a constant value of the extraction variable A at 385 W. The saponins extraction yield improved with an increased value of the independent variables B and C. The peak of the extraction yield was achieved when the values of the variables B and C slightly exceeded 14 min and 20 mL/g, separately. Nevertheless, saponins extraction yield plateaued when extraction time reached 14 min. This result may be due to the fact that a suitable microwave radiation time could cause sufficient microwave energy accumulation to enhance the saponins dissolution process, resulting in an increased yield. Excessive exposure time under microwave radiation could induce degradation of saponins, resulting in a reduction in saponins extraction yield. A similar phenomenon was found in the process of polysaccharides extraction from Moringa oleifera Lam. leaves [49].

3.2.3. Optimization of MAE by RSM and Validation of the Optimized Conditions

Based on the results of the RSM, the optimized extraction parameters for S. mukorossi saponins are the extraction factors A, B, and C are 425 W, 13 min, and 13 mL/g, separately. Under the abovementioned processing parameters, the maximum saponins extraction rate was forecasted to be 286.31 mg/g by BBD. A validation of the MAE procedure was applied to verify the precision and suitability of the extraction process. The tests were conducted thrice under the optimized processing parameters, and the practical extraction rate of saponins was 280.55 ± 6.81 mg/g. The actual result was very approximate to the predicted values, showing that the obtained extraction conditions are credible.

3.3. Comparison with Reference Methods

In the present study, classical extraction techniques including ME, RE, and SE were conducted to make a comparison with the MAE extraction process. The saponins extraction rate for ME, RE, and SE were 123.41 ± 3.34 mg/g, 204.16 ± 5.89 mg/g, and 212.58 ± 5.59 mg/g, respectively. Hence, MAE was superior to traditional extraction methods in saponins extraction rate. With respect to environmental effect, the MAE was carried out at 425 W with 13 min, and the traditional techniques (RE and SE) were performed at 1 KW with 4 h, respectively. The power consumption of MAE was only 0.092 kWh but 4 kWh for RE and SE. The quantity of CO2 rejected into the atmosphere can be calculated according to the literature: to generate 1 kWh by combustion of fossil fuel (coal or fuel) will release 800 g of CO2 into the atmosphere [50]. According to the result from calculation, it showed that the quantity of CO2 rejected into the atmosphere is much lesser in the process of MAE (73.67 g CO2) than that of RE or SE (3200.00 g CO2). In summary, it drew a conclusion that MAE can be suggested as a green method as which can provide a shorter extraction time, higher extraction efficiency, less energy consumption, and a smaller quantity of CO2 release. Therefore, MAE could be applied as a green technique for the isolation of saponins from S. mukorossi.

At the same time, the RSM in this research confirmed the advantages of identifying the optimal operation conditions and predicting acceptable responses. Therefore, the combination of MAE with RSM has attractive development foreground for industrialized separation and purification of natural compounds from different plant resources in the future.

We deduced that the special heating mechanism produced by microwave radiation power ensured a high saponins extraction rate. In the MAE procedure, the microwaves led to a rapid temperature rise resulting in cytoarchitecture interior changes and internal pressure enhancement, while the saponins diffused in the same direction. This may have ruptured the cell structures to facilitate the quick release of saponins. Moreover, the effect of the molecules’ ionic conduction and dipole rotation caused by microwaves can promote both heat and mass transfer rates [5153]. In the MAE method, the direct mutual influence of the microwave on the ethanol aqueous solution and the water inside the materials exist in the biomaterial cells to rupture the cells and effuse endocellular components into the solvent, quickly increasing the saponins extraction yield. A similar phenomenon was also observed in the literature [54, 55]. Hence, MAE was more effective than the traditional techniques for saponins extraction.

3.4. Evaluation of XO Inhibitory Activity In Vitro

XO directly regulates the level of uric acid. The effect of S. mukorossi saponins on XO activity was demonstrated using spectrophotometry as shown in Figure 3. S. mukorossi saponins showed an inhibitory effect on XO. There was a concentration-dependent effect on XO. The lowest inhibitory rate (28.21 ± 0.80%) was at a saponins concentration of 25 μg/mL, and the highest inhibitory rate (89.87 ± 2.25%) was at a saponins concentration of 100 μg/ml. The inhibitory rate of S. mukorossi saponins at 100 μg/mL was very close to the rate observed in the positive control, allopurinol, which displayed a rate of 92.25 ± 3.07% at the same concentration. An inhibitory mechanism assay was performed by kinetic analysis using Lineweaver–Burk plots (Figure 4), which indicated that S. mukorossi saponins exhibited high XO inhibition. The mode of inhibition for saponins was competitive as determined by the Vmax and Km from Lineweaver–Burk plots. The value of Km increased as the saponins concentration increased, while the Vmax values were constant relative to xanthine as the substrate. Therefore, saponins may compete with the substrate for the active site of XO, preventing the substrate from binding. Similar phenomena have been reported in early studies [56]. S. mukorossi saponins may be regarded as triterpene glycosides consisting of the oligosaccharide chain and sapogenins, which shows strong surface activity properties as amphiphilic products. Their inhibition on XO might be attributable to their surface activity. S. mukorossi saponins might be specific surfactants that bind to an enzyme with special affinity [57].

The excess of uric acid produced by XO results in hyperuricemia in human, gout, or other chronic inflammatory disorders [58, 59]. The effective inhibition of XO by S. mukorossi saponins may inhibit the production of uric acid to reduce the symptoms caused by uric acid. Thus, S. mukorossi saponins have great potential as a natural alternative agent for the prevention of, and therapy for, gout and other inflammatory disorders.

4. Conclusion

In conclusion, we investigated the utility of the microwave-assisted method to extract saponins from S. mukorossi pericarps. The MAE method was applied to extract the saponins using both PBD and BBD to optimize the operating process. The optimized operation procedure obtained a yield of 280.55 ± 6.81 mg/g with the following extraction parameters: the ethanol concentration of 40%, soaking time of 3 h, particle size of 80–100 meshes, extraction time of 13 min, solvent-solid ratio of 19 mL/g, and microwave power of 425 W. In comparison with conventional methods, MAE demonstrated a higher extraction efficiency in a shorter extraction time along with decreased energy consumption for saponin extraction. The inhibition activity of XO performed in vitro revealed that saponins from S. mukorossi pericarps demonstrate a type of competitive inhibition on XO compared with the standard drug, allopurinol. It can be inferred that S. mukorossi saponins may be a potential and natural therapeutic for hyperuricemia and other inflammatory disorders. In summary, the results of this study not only provide a green, efficient, and reliable technique for the maximum extraction yield of saponins from S. mukorossi pericarps but also offer the basis for using S. mukorossi saponins to treat gout and other inflammatory disorders.

Data Availability

The data used to support the findings of this study are available from the corresponding author upon request.

Conflicts of Interest

The authors declare that there are no conflicts of interest regarding the publication of this paper.

Acknowledgments

The authors thank the Fundamental Research Funds by the National Natural Science Foundation of China (31860189 and 31760099) for financial support.

References

  1. V. Attri, K. S. Pant, N. Singh, and V. Negi, “Influence of seed size and pre-sowing treatments on germination parameters of Sapindus mukorossi Gaertn under laboratory condition,” International Journal of Current Microbiology and Applied Sciences, vol. 6, no. 9, pp. 2788–2799, 2017. View at: Publisher Site | Google Scholar
  2. S. Goyal, “Medicinal plants of the genus sapindus (sapindaceae)-a review of their botany, phytochemisty, biological activity and traditional uses,” Journal of Drug Delivery and Therapeutics, vol. 4, no. 5, pp. 7–20, 2014. View at: Publisher Site | Google Scholar
  3. S. M. Sonawane and H. Sonawane, “A review of recent and current research studies on the biological and pharmalogical activities of Sapindus Mukorossi,” International Journal of Interdisciplinary Research and Innovations, vol. 3, no. 4, pp. 85–95, 2015. View at: Google Scholar
  4. K. Samal, C. Das, and K. Mohanty, “Application of saponin biosurfactant and its recovery in the MEUF process for removal of methyl violet from wastewater,” Journal of Environmental Management, vol. 203, pp. 8–16, 2017. View at: Publisher Site | Google Scholar
  5. K. Samal, C. Das, and K. Mohanty, “Eco-friendly biosurfactant saponin for the solubilization of cationic and anionic dyes in aqueous system,” Dyes and Pigments, vol. 140, pp. 100–108, 2017. View at: Publisher Site | Google Scholar
  6. A. Pradhan and A. Bhattacharyya, “Quest for an eco-friendly alternative surfactant: surface and foam characteristics of natural surfactants,” Journal of Cleaner Production, vol. 150, pp. 127–134, 2017. View at: Publisher Site | Google Scholar
  7. S. Mukhopadhyay, S. Mukherjee, M. A. Hashim, and B. Sen Gupta, “Application of colloidal gas aphron suspensions produced from Sapindus mukorossi for arsenic removal from contaminated soil,” Chemosphere, vol. 119, no. 4-5, pp. 355–362, 2015. View at: Publisher Site | Google Scholar
  8. Q. Hu, Y.-Y. Chen, Q.-Y. Jiao et al., “Triterpenoid saponins from the pulp of Sapindus mukorossi and their antifungal activities,” Phytochemistry, vol. 147, pp. 1–8, 2018. View at: Publisher Site | Google Scholar
  9. F. M. Porsche, D. Molitor, M. Beyer, S. Charton, C. André, and A. Kollar, “Antifungal activity of saponins from the fruit pericarp of Sapindus mukorossi against Venturia inaequalis and Botrytis cinerea,” Plant Disease, vol. 102, no. 5, pp. 991–1000, 2017. View at: Publisher Site | Google Scholar
  10. R. Singh, “Free radicals scavenging activity and antimicrobial potential of leaf and fruit extracts of Sapindus mukorossi Gaertn. against clinical pathogen,” International Journal of Phytomedicine, vol. 8, pp. 22–28, 2016. View at: Google Scholar
  11. R. Singh, N. Kumari, and G. Nath, “Antimicrobial efficacy of callus and in vitro leaf extracts of Sapindus Mukorossi Gaertn. against pathogenic microbes,” Mathews Journal of Pharmaceutical Science, vol. 1, no. 2, pp. 9–13, 2016. View at: Google Scholar
  12. M. Liu, Y. Chen, Y. Kuo, M. Lu, and C. Liao, “Aqueous extract of Sapindus mukorossi induced cell death of A549 cells and exhibited antitumor property in vivo,” Scientific Reports, vol. 8, no. 1, pp. 4831–4846, 2018. View at: Publisher Site | Google Scholar
  13. M. S. Rao, A. B. Syed, M. A. Fazil et al., “Evaluation of protective effect of Sapindus mukorossi saponin fraction on CCl4-induced acute hepatotoxicity in rats,” Clinical and Experimental Gastroenterology, vol. 5, pp. 129–137, 2012. View at: Publisher Site | Google Scholar
  14. X.-W. Zhu, M.-P. Wei, D.-P. Xu, Y.-H. Guo, Y.-F. Xie, and W.-R. Yao, “In vitro and in vivo antitumor effects of the extract of Sapindus spp,” Journal of the Taiwan Institute of Chemical Engineers, vol. 66, pp. 27–32, 2016. View at: Publisher Site | Google Scholar
  15. M. Shah, Z. Parveen, and M. R. Khan, “Evaluation of antioxidant, anti-inflammatory, analgesic and antipyretic activities of the stem bark of Sapindus mukorossi,” BMC Complementary and Alternative Medicine, vol. 17, no. 1, pp. 526–532, 2017. View at: Publisher Site | Google Scholar
  16. H. Wang, J. Gao, J. Kou, D. Zhu, and B. Yu, “Anti-inflammatory activities of triterpenoid saponins from Polygala japonica,” Phytomedicine, vol. 15, no. 5, pp. 321–326, 2008. View at: Publisher Site | Google Scholar
  17. T. Eddaya, A. Boughdad, E. Sibille, P. Chaimbault, A. Zaid, and A. Amechrouq, “Biological activity of Sapindus mukorossi gaerten (sapindaceae) aqueous extract against Thysanoplusia orichalcea (Lepidoptera: noctuidae),” Industrial Crops and Products, vol. 50, pp. 325–332, 2013. View at: Publisher Site | Google Scholar
  18. S. Saha, S. Walia, J. Kumar, S. Dhingra, and B. S. Parmar, “Screening for feeding deterrent and insect growth regulatory activity of triterpenic saponins fromDiploknema butyraceaandSapindus mukorossi,” Journal of Agricultural and Food Chemistry, vol. 58, no. 1, pp. 434–440, 2010. View at: Publisher Site | Google Scholar
  19. C. Sun, J. Wang, J. Duan, G. Zhao, X. Weng, and L. Jia, “Association of fruit and seed traits of Sapindus mukorossi Germplasm with environmental factors in southern China,” Forests, vol. 8, no. 12, pp. 491–506, 2017. View at: Publisher Site | Google Scholar
  20. S. Jan and M. R. Khan, “Antipyretic, analgesic and anti-inflammatory effects of Kickxia ramosissima,” Journal of Ethnopharmacology, vol. 182, pp. 90–100, 2016. View at: Publisher Site | Google Scholar
  21. S. Harirforoosh, W. Asghar, and F. Jamali, “Adverse effects of nonsteroidal antiinflammatory drugs: an update of gastrointestinal, cardiovascular and renal complications,” Journal of Pharmacy and Pharmaceutical Sciences, vol. 16, no. 5, pp. 821–847, 2013. View at: Publisher Site | Google Scholar
  22. M. Masullo, L. Calabria, D. Gallotta, C. Pizza, and S. Piacente, “Saponins with highly hydroxylated oleanane-type aglycones from Silphium asteriscus L,” Phytochemistry, vol. 97, no. 1, pp. 70–80, 2014. View at: Publisher Site | Google Scholar
  23. Y. Ming, S. N. Tan, J. W. H. Yong, and E. S. Ong, “Emerging green technologies for the chemical standardization of botanicals and herbal preparations,” TrAC Trends in Analytical Chemistry, vol. 50, pp. 1–10, 2013. View at: Publisher Site | Google Scholar
  24. R. G. Bitencourt, C. L. Queiroga, Í. Montanari Junior, and F. A. Cabral, “Fractionated extraction of saponins from Brazilian ginseng by sequential process using supercritical CO2, ethanol and water,” Journal of Supercritical Fluids, vol. 92, no. 8, pp. 272–281, 2014. View at: Publisher Site | Google Scholar
  25. F. Chen, X. Du, Y. Zu, L. Yang, and F. Wang, “Microwave-assisted method for distillation and dual extraction in obtaining essential oil, proanthocyanidins and polysaccharides by one-pot process from Cinnamomi Cortex,” Separation and Purification Technology, vol. 164, pp. 1–11, 2016. View at: Publisher Site | Google Scholar
  26. Z. Liu, B. Deng, S. Li, and Z. Zou, “Optimization of solvent-free microwave assisted extraction of essential oil from Cinnamomum camphora leaves,” Industrial Crops and Products, vol. 124, pp. 353–362, 2018. View at: Publisher Site | Google Scholar
  27. H.-j. Xu, X.-w. Shi, X. Ji, Y.-f. Du, H. Zhu, and L.-t. Zhang, “A rapid method for simultaneous determination of triterpenoid saponins in Pulsatilla turczaninovii using microwave-assisted extraction and high performance liquid chromatography-tandem mass spectrometry,” Food Chemistry, vol. 135, no. 1, pp. 251–258, 2012. View at: Publisher Site | Google Scholar
  28. R. Y. Krishnan and K. S. Rajan, “Microwave assisted extraction of flavonoids from Terminalia bellerica: study of kinetics and thermodynamics,” Separation and Purification Technology, vol. 157, pp. 169–178, 2016. View at: Publisher Site | Google Scholar
  29. H. Zhang, X. Yang, and Y. Wang, “Microwave assisted extraction of secondary metabolites from plants: current status and future directions,” International Journal of Food Engineering, vol. 22, no. 12, pp. 672–688, 2015. View at: Publisher Site | Google Scholar
  30. S. S Mohanty and H. M Mohan, “Process optimization of butachlor bioremediation by Enterobacter cloacae using Plackett-Burman design and response surface methodology,” Process Safety and Environmental Protection, vol. 119, pp. 98–206, 2018. View at: Publisher Site | Google Scholar
  31. S. L. C. Ferreira, V. A. Lemos, V. S. de Carvalho et al., “Multivariate optimization techniques in analytical chemistry - an overview,” Microchemical Journal, vol. 140, pp. 176–182, 2018. View at: Publisher Site | Google Scholar
  32. S. V. F. Gomes, L. A. Portugal, J. P. dos Anjos et al., “Accelerated solvent extraction of phenolic compounds exploiting a Box-Behnken design and quantification of five flavonoids by HPLC-DAD in Passiflora species,” Microchemical Journal, vol. 132, pp. 28–35, 2017. View at: Publisher Site | Google Scholar
  33. M. R. Jalali and M. A. Sobati, “Intensification of oxidative desulfurization of gas oil by ultrasound irradiation: optimization using Box-Behnken design (BBD),” Applied Thermal Engineering, vol. 111, pp. 1158–1170, 2017. View at: Publisher Site | Google Scholar
  34. M. Gavahian, A. Farahnaky, R. Farhoosh, K. Javidnia, and F. Shahidi, “Extraction of essential oils from Mentha piperita using advanced techniques: microwave versus ohmic assisted hydrodistillation,” Food and Bioproducts Processing, vol. 94, pp. 50–58, 2015. View at: Publisher Site | Google Scholar
  35. H. Wu, C. Zhang, Z. Weng et al., “Preparation of total sapindus-saponins for quality control,” Science and Technology of Food Industry, vol. 34, no. 8, pp. 91–96, 2013. View at: Google Scholar
  36. R. Li, Z. L. Wu, Y. J. Wang, and L. L. Li, “Separation of total saponins from the pericarp of Sapindus mukorossi Gaerten by foam fractionation,” Industrial Crops and Products, vol. 51, pp. 163–170, 2013. View at: Publisher Site | Google Scholar
  37. A. Upadhyay and D. K. Singh, “Molluscicidal activity of Sapindus mukorossi and Terminalia chebula against the freshwater snail Lymnaea acuminata,” Chemosphere, vol. 83, no. 4, pp. 468–474, 2011. View at: Publisher Site | Google Scholar
  38. Z. S. Filha, I. F. Vitolo, L. G. Fietto, J. A. Lombardi, and D. A. Saúdeguimarães, “Xanthine oxidase inhibitory activity of Lychnophora species from Brazil (Arnica),” Journal of Ethnopharmacology, vol. 107, no. 1, pp. 79–82, 2006. View at: Publisher Site | Google Scholar
  39. F. Gao, Y. Zhao, and J. Luo, “Extraction and characterization of saponins from Sapindus,” Forestry Chemistry and Industry, vol. 32, no. 6, pp. 89–93, 2012. View at: Google Scholar
  40. F. Wei, J. Yu, and H. Xie, “Extraction and separation of natural sapindus saponin,” AnHui Chemical Industry, vol. 33, no. 3, pp. 15–18, 2007. View at: Google Scholar
  41. Q. Zhao, J. F. Kennedy, X. Wang et al., “Optimization of ultrasonic circulating extraction of polysaccharides from Asparagus officinalis using response surface methodology,” International Journal of Biological Macromolecules, vol. 49, no. 2, pp. 181–187, 2011. View at: Publisher Site | Google Scholar
  42. W. Yang, Y. Fang, J. Liang, and Q. Hu, “Optimization of ultrasonic extraction of flammulina velutipes polysaccharides and evaluation of its acetylcholinesterase inhibitory activity,” Food Research International, vol. 44, no. 5, pp. 1269–1275, 2011. View at: Publisher Site | Google Scholar
  43. T. Belwal, I. D. Bhatt, R. S. Rawal, and V. Pande, “Microwave-assisted extraction (MAE) conditions using polynomial design for improving antioxidant phytochemicals in Berberis asiatica Roxb. ex DC. leaves,” Industrial Crops and Products, vol. 95, pp. 393–403, 2017. View at: Publisher Site | Google Scholar
  44. X. Lu, Z. Zheng, H. Li et al., “Optimization of ultrasonic-microwave assisted extraction of oligosaccharides from lotus (Nelumbo nucifera Gaertn.) seeds,” Industrial Crops and Products, vol. 107, pp. 546–557, 2017. View at: Publisher Site | Google Scholar
  45. K. Ameer, S.-W. Bae, Y. Jo, H.-G. Lee, A. Ameer, and J.-H. Kwon, “Optimization of microwave-assisted extraction of total extract, stevioside and rebaudioside-a from Stevia rebaudiana (Bertoni) leaves, using response surface methodology (RSM) and artificial neural network (ANN) modelling,” Food Chemistry, vol. 229, pp. 198–207, 2017. View at: Publisher Site | Google Scholar
  46. J. P. Maran, V. Sivakumar, K. Thirugnanasambandham, and R. Sridhar, “Microwave assisted extraction of pectin from waste Citrullus lanatus fruit rinds,” Carbohydrate Polymers, vol. 101, pp. 786–791, 2014. View at: Publisher Site | Google Scholar
  47. A. U. Arvindekar and K. S. Laddha, “An efficient microwave-assisted extraction of anthraquinones from Rheum emodi: optimisation using RSM, UV and HPLC analysis and antioxidant studies,” Industrial Crops and Products, vol. 83, pp. 587–595, 2016. View at: Publisher Site | Google Scholar
  48. B. Ren, C. Chen, C. Li, X. Fu, L. You, and R. H. Liu, “Optimization of microwave-assisted extraction of Sargassum thunbergii polysaccharides and its antioxidant and hypoglycemic activities,” Carbohydrate Polymers, vol. 173, pp. 192–201, 2017. View at: Publisher Site | Google Scholar
  49. C. Chen, B. Zhang, Q. Huang, X. Fu, and R. H. Liu, “Microwave-assisted extraction of polysaccharides from Moringa oleifera Lam. leaves: characterization and hypoglycemic activity,” Industrial Crops and Products, vol. 100, pp. 1–11, 2017. View at: Publisher Site | Google Scholar
  50. C.-h. Ma, L. Yang, Y.-g. Zu, and T.-t. Liu, “Optimization of conditions of solvent-free microwave extraction and study on antioxidant capacity of essential oil from Schisandra chinensis (Turcz.) Baill,” Food Chemistry, vol. 134, no. 4, pp. 2532–2539, 2012. View at: Publisher Site | Google Scholar
  51. Y. Chen, M.-Y. Xie, and X.-F. Gong, “Microwave-assisted extraction used for the isolation of total triterpenoid saponins from Ganoderma atrum,” Journal of Food Engineering, vol. 81, no. 1, pp. 162–170, 2007. View at: Publisher Site | Google Scholar
  52. C. Y. Cheok, H. A. K. Salman, and R. Sulaiman, “Extraction and quantification of saponins: a review,” Food Research International, vol. 59, pp. 16–40, 2014. View at: Publisher Site | Google Scholar
  53. V. Mandal, S. Dewanjee, and S. C. Mandal, “Microwave-assisted extraction of total bioactive saponin fraction from Gymnema sylvestre with reference to gymnemagenin: a potential biomarker,” Phytochemical Analysis, vol. 20, no. 6, pp. 491–497, 2010. View at: Publisher Site | Google Scholar
  54. A. K. Das, V. Mandal, and S. C. Mandal, “Design of experiment approach for the process optimisation of microwave assisted extraction of lupeol fromFicus racemosaLeaves using response surface methodology,” Phytochemical Analysis, vol. 24, no. 3, pp. 230–247, 2012. View at: Publisher Site | Google Scholar
  55. B. Hu, C. Li, Z. Zhang et al., “Microwave-assisted extraction of silkworm pupal oil and evaluation of its fatty acid composition, physicochemical properties and antioxidant activities,” Food Chemistry, vol. 231, pp. 348–355, 2017. View at: Publisher Site | Google Scholar
  56. F. Xu, X. Zhao, L. Yang, X. Wang, and J. Zhao, “A new cycloartane-type triterpenoid saponin xanthine oxidase inhibitor from Homonoia riparia Lour,” Molecules, vol. 19, no. 9, pp. 13422–13431, 2014. View at: Publisher Site | Google Scholar
  57. A. Nagao, M. Seki, and H. Kobayashi, “Inhibition of xanthine oxidase by flavonoids,” Bioscience, Biotechnology, and Biochemistry, vol. 63, no. 10, pp. 1787–1790, 2014. View at: Publisher Site | Google Scholar
  58. M. Akram, K. Usmanghani, I. Ahmed, I. Azhar, and A. Hamid, “Comprehensive review on therapeutic strategies of gouty arthritis,” Pakistan Journal of Pharmaceutical Sciences, vol. 27, no. 5, pp. 1575–1582, 2014. View at: Google Scholar
  59. S. M. N. Azmi, P. Jamal, and A. Amid, “Xanthine oxidase inhibitory activity from potential Malaysian medicinal plant as remedies for gout,” International Food Research Journal, vol. 19, pp. 159–165, 2012. View at: Google Scholar

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