Effect of Enzymatic Ratio on Antioxidant Capacity and Extraction Rate
The antioxidant capacity of the extracted GLTs increased with the increase in the enzymatic ratio (Fig. 1. A), and the antioxidant capacity and extraction rate of GLTs reached a maximum when the enzymatic ratio was 2:1 (cellulase:pectinase). The antioxidant capacity and extraction rate decreased as the composite enzymatic ratio increased, probably due to the content of cellulose and pectin in the body of G. lucidum (Ma et al. 2019). During extraction of plant constiutents, the enzymes degrade plant material to form a sparsely packed structure and sometimes dissolve the plant material completely; this process maximizes the solubilization of the active plant constituents and results in the highest extraction rate (Wen et al. 2020). As the results of our experiments show, as the proportion of pectinase increased, the enzymatic action of the composite enzyme on the pectin substances in the substrate was enhanced. In addition, the enzyme catalyzes the conversion of the active ingredient into a more active form; thus, as the relative amount of pectinase continues to increase compared to that of cellulase, the enzyme complex decreases the enzymatic hydrolysis of cellulose in the substrate. This process leads to a reduction in the extraction rate and antioxidant capacity (Lira et al. 2023). In conjunction with the above trend changes, an enzymatic ratio of 2:1 (cellulase:pectinase) was used in all subsequent experiments.
Effect of Enzyme Concentration on Antioxidant Capacity and Extraction Rate
The relationships among enzyme concentration, antioxidant capacity, and concentration of GLTs are shown in Fig. 1. B. The antioxidant capacity of the GLTs reached a second peak at 1.5% of the complex enzyme concentration, suggesting that the antioxidant capacity of GLTs extracts was stronger at 1% cellulase and 0.5% pectinase but had little effect on the extraction rate. The antioxidant capacity and extraction rate of the GLTs reached a maximum when the amount of the complex was 2.5%, after which they tended to equilibrate. This trend was likely due to the fact that as the concentration of complex enzyme increased, the G. lucidum substrates were fully combined with the enzyme, thus promoting the continuous leaching of triterpenoids (Wu et al. 2020). When the enzyme concentration exceeded 2.5%, it is possible that the complex enzyme was oversaturated with respect to the substrate concentration, and the extraction rate and antioxidant capacity of the GLTs did not improve. Considering the utilization rate of the composite enzyme, antioxidant capacity, and extraction rate of the substance, an optimal enzyme concentration of 2.5% was selected for subsequent experiments.
Effect of Enzymatic pH on Antioxidant Capacity and Extraction Rate
Under acidic conditions, the concentration of hydrogen ions increases, making electron transfer in redox reactions more likely to occur. Therefore, a pH range of 4–6 was chosen for the single-factor experiments. In Fig. 1. C we present the relationship between enzymatic pH, antioxidant capacity, and GLT concentration. A change in enzymatic pH can affect the dissociation of relevant groups on the active site of the enzyme molecule. The dissociation state of the active group on the enzyme molecule was maximized at the optimal pH and substrate binding. When the pH was higher or lower than the optimal pH, the dissociated state of the active group changed, and the binding of the enzyme to the substrate was reduced (Zhao et al. 2018). The antioxidant capacity and extraction rate of GLTs increased with increasing pH in the experimental pH range, reaching a maximum at pH 5.0. A decrease in the antioxidant capacity and extraction rate of GLTs was observed when the pH of the enzyme solution exceeded 5.0. This can be explained by the fact that changing the pH during enzymatic digestion affects the stability of the enzyme, binding status of the enzyme molecule to the substrate, and dissociation status of the moiety. An increase in pH led to a change in the conformation of the enzyme and a decrease in its activity (Shang et al. 2023). Thus pH 5.0 was selected as the optimal condition for the next experiment.
Effect of Enzymatic Temperature on Antioxidant Capacity and Extraction Rate
The relationship between the enzymatic temperature, antioxidant capacity, and extraction rate of GLTs is illustrated in Fig. 1. D. The antioxidant capacity of the extract was strongest at the enzymatic temperature of 30 ℃, and the antioxidant capacity decreased with the increase of enzymatic temperature. The yield of GLTs yield increased with increasing temperature up to 30 ℃, possibly due to the acceleration of intermolecular motion with increasing temperature and the enhancement of intermolecular permeability and diffusion, which increases the solubilization of substances (Chang et al. 2023). When GLTs are extracted over a considerable period of time and under prolonged heating conditions, the optimal reaction temperature of the enzyme is surpassed and enzymatic activity is inhibited (Selvamuthukumaran et al. 2017). Second, given that the enzyme is essentially a protein its optimal hydrolysis temperature is related to the mechanism of its catalytic action. However, the conformation of the enzyme will also change if the temperature is too low (Zhai et al. 2017). Only at the appropriate temperature is the enzymatic activity optimized and the GLTs extraction rate maximized. The results of our experiments show that the optimal enzyme-induced hydrolysis temperature is 45 ℃ under conditions that target the extraction rate. In this experiment, the antioxidant capacity was the main evaluation index; accordingly, 30 ℃ was selected as the optimal enzymatic temperature for extracting GLTs for the next experiment.
Effect of Enzymatic Time on Antioxidant Capacity and Extraction Rate
The duration of the complex enzymatic reaction affected the antioxidant capacity of the GLTs extract. As illustrated in Fig. 1. E, a trend of initial increase of antioxidant capacity, followed by a decrease was observed with as reaction time progressed. The antioxidant value reached a maximum at 30 min, although the extraction rate stabilized after 40 min. This may be because, when the substrate mass concentration was low, the actions of cellulase and pectinase gradually increased with increasing substrate mass concentration. When the enzymatic time is prolonged, an excess of substrate molecules accumulate at the center of activity of the enzyme and this affects the speed of the enzyme-catalyzed reaction. Because the concentration of the substrate no longer changes, the antioxidant capacity and the extraction rate over a given reaction time rises, and begins to stabilize after the substrate molecules accumulate (Guo et al. 2021). Prolonged enzymatic digestion causes destruction of the active parts of some substrate proteins, leading to a decrease in the enzymatic reaction rate and antioxidant capacity (Ren et al. 2019). Therefore, 30 min was selected as optimal digestion time.
RSM Results of GLTs Extraction
The results of the RSM are shown in Table 1. The analytical factorization part was tested 24 times, and the center point was repeated twice. The optimal process conditions for enzyme-assisted extraction of wild-cultivated G. lucidum (with the goal of maximizing antioxidant capacity of the active ingredients) were as follows: enzyme concentration 2.5%, pH 5.0, temperature 30℃, and reaction duration 30 min. Under these conditions, the antioxidant capacity of the extracted GLTs was determined to be 0.115234 µmol/mL.
Table 1
Box-Behnken experimental design and results
Experiment number
|
A
|
B
|
C
|
D
|
Antioxidant capacity(μmol/mL)
|
Extraction rate
(%)
|
1
|
0
|
-1
|
0
|
1
|
0.0636529
|
3.415
|
2
|
-1
|
1
|
0
|
0
|
0.0781407
|
4.188
|
3
|
0
|
1
|
1
|
0
|
0.0885283
|
4.668
|
4
|
0
|
1
|
0
|
-1
|
0.077865
|
4.110
|
5
|
0
|
-1
|
-1
|
0
|
0.0688038
|
3.954
|
6
|
0
|
0
|
0
|
0
|
0.115591
|
4.230
|
7
|
-1
|
0
|
0
|
-1
|
0.0870124
|
3.607
|
8
|
1
|
-1
|
0
|
0
|
0.0708364
|
3.383
|
9
|
1
|
0
|
-1
|
0
|
0.0920562
|
3.649
|
10
|
0
|
0
|
1
|
1
|
0.0713188
|
3.895
|
11
|
0
|
-1
|
1
|
0
|
0.076039
|
4.057
|
12
|
0
|
0
|
-1
|
1
|
0.083033
|
3.448
|
13
|
1
|
0
|
0
|
-1
|
0.0700613
|
3.425
|
14
|
-1
|
0
|
0
|
1
|
0.0726108
|
3.201
|
15
|
0
|
0
|
0
|
0
|
0.114877
|
4.136
|
16
|
0
|
1
|
-1
|
0
|
0.0829304
|
4.049
|
17
|
1
|
1
|
0
|
0
|
0.102715
|
3.935
|
18
|
0
|
-1
|
0
|
-1
|
0.0626193
|
3.396
|
19
|
-1
|
-1
|
0
|
0
|
0.100854
|
3.772
|
20
|
-1
|
0
|
1
|
0
|
0.110854
|
4.103
|
21
|
1
|
0
|
0
|
1
|
0.0896309
|
4.032
|
22
|
1
|
0
|
1
|
0
|
0.0730491
|
4.022
|
23
|
0
|
0
|
-1
|
-1
|
0.0510257
|
3.457
|
24
|
0
|
1
|
0
|
1
|
0.0730056
|
3.502
|
25
|
-1
|
0
|
-1
|
0
|
0.0634461
|
3.496
|
26
|
0
|
0
|
1
|
-1
|
0.100882
|
4.094
|
* : Differences are significant(p < 0.05).
** : Differences are highly significant(p < 0.01).;
Model Equation Development and Significance test
Based on the test results in Table 1, multiple regression analysis was performed on Y and the factors using Design-Expert 8.0.6 software, and the final regression equation for triterpenoids was obtained, as shown in Eq. (4).
R(Antioxidant capacity) = 0.12-1.214E-003A + 5.032E-003B + 6.615E-003C + 3.155E-004D + 0.014AB-0.017AC + 8.493E -003AD-4.093E-004BC-1.473E -003BD-0.015CD -0.011A2 -0.019B2 -0.017C2 -0.024D2 (4)
As shown in Table 2, the model reaches a highly significant level of (Model P < 0.0001). The misfit term P = 0.0768 > 0.05 is not significant, indicating that no misfit factor exists in the test and the regression equation is a satisfactory simulation. The coefficient of determination, R2, is 0.9643, meaning that the model can explain 96.43% of the variation in response values, indicating that the predicted results are in good agreement with the actual results. The composite correlation coefficient RAdj of the model is 0.9188, indicating that 91.88% of the test results are influenced by the test factors. The above data can reflect that the regression equation fits well and the test error is small, which can well predict and analyze the extraction process of enzymatic triterpenoid components, and this model can be used to analyze the changes in the response value and speculate the test results.
Table 2
Analysis of variance of regression models for the antioxidant capacity of GLTs
Source of variance | square sum | degrees of freedom | mean square | F-value | P-value |
mould | 7.036×10− 3 | 14 | 5.026×10− 4 | 21.20 | < 0.0001** |
A-enzyme concentrations | 1.769×10− 5 | 1 | 1.769×10− 5 | 0.75 | 0.4061 |
B-enzymatic pH | 3.038×10− 4 | 1 | 3.038×10− 4 | 12.82 | 0.0043* |
C-enzyme temperature | 5.250×10− 4 | 1 | 4.011×10− 4 | 22.15 | 0.0006** |
D-enzyme time | 1.195×10− 6 | 1 | 1.195×10− 6 | 0.050 | 0.8265 |
AB | 7.451×10− 4 | 1 | 7.451×10− 4 | 31.43 | 0.0002** |
AC | 1.103×10− 3 | 1 | 1.103×10− 3 | 46.52 | < 0.0001** |
AD | 2.885×10− 4 | 1 | 2.885×10− 4 | 12.17 | 0.0051** |
BC | 6.702×10− 7 | 1 | 6.702×10− 7 | 0.028 | 0.8695 |
BD | 8.682×10− 6 | 1 | 8.682×10− 6 | 0.37 | 0.5573 |
CD | 9.477×10− 4 | 1 | 9.477×10− 4 | 39.98 | < 0.0001** |
A2 | 5.120×10− 4 | 1 | 5.120×10− 4 | 21.60 | 0.0007** |
B2 | 1.574×10− 3 | 1 | 1.574×10− 3 | 66.40 | < 0.0001** |
C2 | 1.260×10− 3 | 1 | 1.260×10− 3 | 53.17 | < 0.0001** |
D2 | 2.598×10− 3 | 1 | 2.598×10− 3 | 109.60 | < 0.0001** |
residual | 2.608×10− 4 | 11 | 2.608×10− 4 | 102.20 | 0.0768 |
Lack of fit | 2.605×10− 4 | 10 | 2.605×10− 4 |
Pure error | 2.549×10− 7 | 1 | 2.549×10− 7 |
aggregate | 7.296×10− 3 | 25 | | | |
R2 = 0.9643 | RAdj=0.9188 | | |
* : Differences are significant(p < 0.05). |
** : Differences are highly significant(p < 0.01). |
The value of F can intuitively reflect the magnitude of influence of each factor on the antioxidant capacity of GLTs; the larger the value of F, the greater the influence on the response value. Among the four factors affecting the antioxidant capacity of the enzymatically digested GLTs, the order of precedence was as follows: enzymatic temperature (C) > enzymatic pH (B) > enzyme concentration (A) > enzymatic time (D). The effects of the primary term C-enzyme temperature, secondary terms A2, B2, C2, and D2, and the interaction terms AB, AC, and CD on the rate of antioxidant capacity of GLTs were highly significant. There was a significant effect of item B (enzymatic pH) and the interaction term AD on the antioxidant capacity of GLTs, and the other factors were not significant. Furthermore, high temperatures caused structural changes in G. lucidum and weakened its antioxidant capacity.
The antioxidant capacity of GLTs was affected to a great degree by pH and temperature (as previously reported (Sui et al. 2014)) and to a much lesser degree by enzyme concentration and time. The rate and direction of the redox reaction change at different pH values, and a change in the pH can easily cause a change in the redox reaction. In addition, temperature changes the structure of the substance and causes a change in the antioxidant capacity; the longer the high temperature lasts, the greater the loss of the antioxidant capacity of the substance.
Response Surface Analysis of Factor Interactions
To further explore the effects of enzyme concentration (A), enzymatic pH (B), enzymatic temperature (C), and enzymatic time (D) on the response values, and to visualize and analyze the interactions among the four factors and the effects of antioxidant capacity, surface and contour plot analyses of the relationship between the factors and the response values were performed using Design-Expert 8.0.6 software. When interaction between the factors occurs, the surface map shows a response value (Yang et al. 2019). As shown in Fig. 2, as the enzyme concentration, pH, temperature, and time increased, the antioxidant capacity of the extracts first increased and then decreased.
The contour density and shape of the contour map can determine whether the effect of the two factors on the response value is significant (Guo et al. 2021); if the contour lines are dense and close to elliptical, the interaction between the two factors has a significant effect on the response value (Ibrahim et al. 2021). By analyzing the shape of the contour plots in Fig. 2. A–D, it can be seen that the interaction of the three groups of factors, namely, enzyme concentration and pH, enzyme concentration and temperature, and enzyme concentration and time, had a significant effect on the response value, which is in accordance with the ANOVA results of the regression equation.
As shown in Fig. 2. E–F, the response surface plots were relatively flat and the contour lines were almost circular, indicating that the interactions between cellulase addition and enzymatic temperature, pH, and time were not significant, and there was good agreement with the data in Table 2. Considering the regression coefficients obtained for the independent and dependent variables, enzymatic pH and temperature were perhaps the most important factors significantly influencing the antioxidant capacity of GLTs.
Validation Experiments
To verify the accuracy of the model predictions, the process conditions of the highest antioxidant capacity group in the four-factor, three-level test group were used as validation conditions three times. The obtained mean value of triterpenoid antioxidant capacity was 0.117 ± 0.011 µmol/mL, and the value of GLTs antioxidant capacity under the optimal extraction conditions obtained from the model regression equation was 0.12 µmol/mL, and the two data were almost equal, which indicated that the model was reliable.
Identification of GLTs
The structural characterization of GLTs is very important for studying their physiological activity (Pratap et al. 2022). Pure triterpenoids were identified by MALDI-TOF MS. The imitation wild cultivated G. lucidum fruiting bodies contained 19 ganoderic acid monomers (Table S3). In a recent study conducted in Poland, 13 triterpenoid compounds were found in G. lucidum fruiting bodies, including ganoderic acid A, ganoderic enoic acid B, and lucidenic acid A (Joanna et al. 2022). In another study, 10 triterpene fractions could be detected in cultivated Ganoderma leucocontextum from Sichuan and Tibet, including ganoderma lucidum enoic acid E, ganoderma lucidum acid A, ganoderma lucidum alcohol F, and other compounds (Liu et al. 2021). The differences in GLTs may be attributed to the different sample sources, purification methods, and quantification methods. Moreover, the present study revealed that wild-cultivated G. lucidum contained more than six bioactive components, including ganoderic acid C, which has strong antioxidant and anti-inflammatory capacity, and ganoderic acid T, which is antitumor and has the effect of inducing apoptosis and necrosis of cancer cells(Liu et al. 2017, Du et al. 2018). This may be related to the strong antioxidant properties of wild G. lucidum. The identification of wild-cultivated GLTs and our interpretation of their potential biological functions serves as the foundation for further studies; the next step is to quantify each active ingredient to further determine the relationship between antioxidant capacity and triterpene content.