Eight metal ions (i.e., Na⁺, Ca²⁺, Ag⁺, Co²⁺, Cu²⁺, Al³⁺, Zn²⁺, and Mn⁴⁺) were added in medium on day 3 of culture. The effects of the metal ions on mycelia growth and palmarumycin production in Berkleasmium sp. Dzf12 liquid culture are presented in Table 1. Three metal ions, Ca²⁺, Cu²⁺ and Al³⁺ showed improving effects on the mycelia growth and palmarumycin accumulation. The optimum concentrations to stimulate mycelia growth for Ca²⁺, Cu²⁺ and Al³⁺ were respectively at 20.00, 3.00 and 3.00 mmol/L. However, the optimal concentrations to obviously increase total palmarumycin yield (palmarumycins C₁₂ plus C₁₃) for Ca²⁺, Cu²⁺ and Al³⁺ were respectively at 10.00, 1.50 and 3.00 mmol/L. Correspondingly, total palmarumycin yields at the optimal concentrations of Ca²⁺, Cu²⁺ and Al³⁺ were respectively at 129.24, 112.26 and 112.82 mg/L, which were 4.00-fold, 3.47-fold, and 3.49-fold of control yield (32.32 mg/L), respectively. Zinc ions (Zn²⁺) slightly stimulated mycelia growth, and had no obvious effect on total palmarumycin production. Among the other metal ions (i.e., Na⁺, Ag⁺, Co²⁺ and Mn⁴⁺), both Ag⁺ and Co²⁺ strongly inhibited mycelia growth, and both Na⁺ and Mn⁴⁺ slightly inhibited mycelia growth. Correspondingly, total palmarumycin yield of endophyte Dzf12 liquid cultures was decreased after treatment with the metal ions Na⁺, Ag⁺, Co²⁺ and Mn⁴⁺, respectively. The inhibitory capacity of the metal ions for palmarumycins C₁₂ and C₁₃ production in Dzf12 liquid culture was in order of Co²⁺ > Ag⁺ > Mn⁴⁺ > Na⁺. It was concluded that both Co²⁺ and Ag⁺ exhibited the most toxic to Berkleasmium sp. Dzf12 by inhibiting mycelia growth and palmarumycins C₁₂ and C₁₃ production. Three metal ions, Ca²⁺, Cu²⁺ and Al³⁺ were the most effective at enhancing mycelia growth and palmarumycin production. They were selected for further enhancing experiments for palmarumycin production.

Addition time of the metal ions has been considered as a main factor to affect biosynthesis of fungal or plant secondary metabolites [16,18]. Calcium ion (Ca²⁺) was found to be one of the most effective ions to improve mycelia growth and palmarumycin biosynthesis in liquid culture of Berkleasmium sp. Dzf12, based on the results shown in Table 1. Hence, Ca²⁺ concentrations in medium and addition time were further optimized. As the three-day-old cultures treated with 10 mmol/L of Ca²⁺ reached an ideal palmarumycin production (129.24 mg/L), the highest concentration of Ca²⁺ in subsequent studies was limited at 20 mmol/L. Figure 1 shows the effects of Ca²⁺ on mycelia growth (Figure 1-I) and palmarumycin yield (Figure 1-II) in Berkleasmium sp. Dzf12 liquid cultures, which were dependent on both Ca²⁺ concentrations (1, 5, 10, 15, and 20 mmol/L) and its addition time (added on days 0, 3, 6, 9 and 12). As shown in Figure 1-I, when the cultures were fed with 10 mmol/L of Ca²⁺ on day 6, the mycelia biomass was 1.94-fold of control (13.32 g dw/L versus 6.88 g dw/L). Palmarumycin C₁₃ was distributed in both mycelia and broth, and palmarumycin C₁₂ was only distributed in mycelia. With 10 mmol/L of Ca²⁺ fed on day 3, the highest yields of palmarumycins C₁₂ (23.65 mg/L) and C₁₃ (113.92 mg/L) were obtained. The total palmarumycin yield (palmarumycins C₁₂ plus C₁₃) was improved to reach 137.57 mg/L, which was about 3.94-fold of control yield (34.91 mg/L) (Figure 1-II).

Calcium ion (Ca²⁺) plays an essential role in signal transduction as it is one component of the calcium ion channel. Calcium signaling can result in rapid cellular responses, such as cell motility and contractile events, or more slowly paced responses, such as shifts in gene expression and cell division [34]. Ca²⁺ was reported to obviously accelerate the growth of the fungus Sesarma bidens[35]. It was also reported to cause thickening of the fungal cell walls of Botrytis cinerea[36]. Ca²⁺ uptake is localized in the apex of the tip of fungal hyphae, and Ca²⁺ has been considered to have an important role on fungal tip growth [37–39]. Ca²⁺ was also found to stimulate mycelia growth of Berkleasmium sp. Dzf12 in this study. Its action mechanisms to improve mycelia growth and palmarumycin biosynthesis need further investigation.

Copper ion (Cu²⁺) was also found to be one of the most effective ions to improve mycelia growth and palmarumycin biosynthesis in liquid culture of Berkleasmium sp. Dzf12 based on the results shown in Table 1. Therefore, Cu²⁺ concentration and addition time were further optimized. As the three-day-old cultures treated with 1.50 mmol/L of Cu²⁺ reached an ideal palmarumycin production (112.26 mg/L), the highest concentration of Cu²⁺ in subsequent studies was limited at 3.00 mmol/L. Figure 2 shows the effects of Cu²⁺ on mycelia growth (Figure 2-I) and palmarumycin yield (Figure 2-II) in Berkleasmium sp. Dzf12 liquid cultures, which were dependent on both Cu²⁺ concentrations (0.5, 1.0, 1.5, 2.0, and 3.0 mmol/L) and its addition time (added on days 0, 3, 6, 9 and 12). As shown in Figure 2-I, when the cultures were fed with 0.5–3.0 mmol/L of Cu²⁺ on days 0–12, the mycelia biomass was varied as 6.49–7.84 g dw/L which was higher than that of control (6.88 g dw/L). With 1.0 mmol/L of Cu²⁺ fed on day 3, the highest yields of palmarumycins C₁₂ (6.37 mg/L) and C₁₃ (139.91 mg/L) were obtained. The total palmarumycin yield (palmarumycins C₁₂ plus C₁₃) was improved to reach 146.28 mg/L, which was about 4.19-fold of control yield (34.91 mg/L) (Figure 2-II). Cu²⁺ was previously reported to improve the production of laccase by the white-rot fungus Pleurotus pulmonarius in solid state fermentation [40].

Effects of aluminum ion (Al³⁺) on mycelia growth and palmarumycin production in liquid culture of Berkleasmium sp. Dzf12 are shown in Figure 3. As the three-day-old cultures treated with 1.50 mmol/L of Al³⁺ reached an ideal palmarumycin production (106.21 mg/L), the highest concentration of Al³⁺ in subsequent studies was limited at 2.50 mmol/L. Figure 3 shows the effects of Cu²⁺ on mycelia growth (Figure 3-I) and palmarumycin yield (Figure 3-II) in Berkleasmium sp. Dzf12 liquid cultures, which were dependent on both Al³⁺ concentrations (0.5, 1.0, 1.5, 2.0, and 2.5 mmol/L) and its addition time (added on days 0, 3, 6, 9 and 12). As shown in Figure 3-I, when the cultures were fed with 1.5 mmol/L of Al³⁺ on day 3, the mycelia biomass was 9.69 g dw/L which was higher than that of control (6.88 g dw/L). With 2.0 mmol/L of Al³⁺ fed on day 6, the highest yields of palmarumycins C₁₂ (8.28 mg/L) and C₁₃ (148.49 mg/L) were obtained. The total palmarumycin yield (palmarumycins C₁₂ plus C₁₃) was improved to reach 156.77 mg/L, which was about 4.49-fold of control yield (34.91 mg/L) (Figure 3-II).

Palmarumycin C₁₃ production was mainly enhanced when Al³⁺ concentration was lower than 4 mmol/L (Table 2 and Figure 3). When Al³⁺ concentration was higher than 4 mmol/L, palmarumycin C₁₂ production was favored. The ratio of palmarumycin C₁₂ yield to palmarumycin C₁₃ yield was gradually increased (Table 2). Biosynthetically, palmarumycin C₁₂ was considered as the precursor of palmarumycin C₁₃[32,33]. Palmarumycin C₁₂ was converted to palmarumycin C₁₃ by oxidation reaction in mycelia cells. It is possible that the enzyme activity for oxidation was suppressed as the aluminum ion concentration was higher than 4 mmol/L. While aluminum ion concentration was higher than 8 mmol/L, the total yield of palmarumyicns C₁₂ plus C₁₃ gradually decreased. It is possible that high Al³⁺ concentration leads to the suppression of other enzymatic activities in the biosynthetic pathway of palmarumycins besides the oxidation enzyme. The results should be beneficial for us to prepare palmarumycin C₁₂ or palmarumycin C₁₃ by regulating activity of the oxidation enzyme with aluminum ions. Al³⁺ at a high concentration is usually toxic to plants, animals and microorganisms [35]. For example, Al³⁺ completely inhibited the growth of the fungus Sesarma bidens at 100 mg/L AlCl₃ in medium [41]. However, it possesses a variety of biological activities at low concentrations [42]. Al³⁺ enhanced the conversion of (β-isoxazolin-5-on-2-yl)-alanine (BIA) into β-N-oxalyl-L-α,β-diaminopropionic acid (β-ODAP) in the callus tissues derived from leaf explants of Lathyrus sativus[43]. Production of some plant secondary metabolites can be elicited by Al³⁺. For example, resveratrol biosynthesis in grapevine (Vitis vinifera) was stimulated by Al³⁺ at a concentration of 0.05% AlCl₃ in medium [44]. Tropane alkaloid production and antioxidant system activity in micropropagated Datura innoxia plantlets were enhanced by Al³⁺ as an abiotic elicitor [45]. It has not yet been reported how aluminum ions suppress the enzyme-based oxidation. Aluminum ions directly joining the biotransformation step from palmarumycin C₁₂ to palmarumycin C₁₃ needs further clarification.

According to the above single-factor experiments, Ca²⁺, Cu²⁺ and Al³⁺ all showed their obvious effects on palmarumycin C₁₃ production in liquid culture of Berkleasmium sp. Dzf12, and palmarumycin C₁₃ yield was in the majority of palmarumycins C₁₂ plus C₁₃ yield (Figures 1-II, 2-II and 3-II). So the suitable concentrations of Ca²⁺, Cu²⁺ and Al³⁺ in medium for palmarumycin C₁₃ production were further determined by central composite design (CCD) experiments and response surface methodology (RSM). Five levels of each variable were set by the software of Design Expert, which are presented in Table 3. Subsequently, 20 trials of CCD were carried out to optimize palmarumycin C₁₃ yield. The results of CCD experiments were summarized in Table 4. Palmarumycin C₁₃ yield displayed considerable variations from 163.22 to 209.64 mg/L, respectively, depending upon the changes of variables. Based on the results of CCD experiments, a second-order polynomial regression model between palmarumycin C₁₃ yield and the test independent variables by software of Design Expert was shown in Equation 1.

In Equation 1,Y represented palmarumycin C₁₃ yield (mg/L), and x₁, x₂ and x₃ were the coded values of the test variables, the concentrations (mmol/L) of Ca²⁺, Cu²⁺ and Al³⁺, respectively.

In order to determine whether the quadratic regression model was significant or not, the ANOVA analysis was conducted, which was summarized in Table 5. The ANOVA of the quadratic regression model demonstrated that the model was highly significant, evident from Fisher’s test with a very high model F-value (84.65) but a very low p-value (p < 0.0001). The goodness of the model was examined by the determination coefficients (R²) and multiple correlation coefficients (R). For palmarumycin C₁₃ yield, the value (0.9754) of the determination coefficient adj-R² demonstrated that total variation of 97.54% was attributed to the test independent variables and only about 2.46% of the total variation could not be explained by the model. The value of R was closer to 1, the fitness of the model was better [46]. In this study, the multiple correlation coefficient (adj-R) of the model was 0.9876, indicating a good agreement between the experimental and predicted values. The lack-of-fit measured the failure of the model to represent the data in the experimental domain at points which were not included in the regression [47]. The F-value for lack-of-fit was 0.86 and the corresponding p-value was 0.56 (> 0.05), which implied each lack-of-fit was not significant relative to the pure error due to noise. Insignificant lack-of-fit confirmed the validity of the model.

The coefficients of the quadratic polynomial model, along with their corresponding p-values, are calculated and presented in Table 6. The p-value was used as a tool to check the significance of each coefficient, which also indicated the interaction strength between each independent parameter [48]. If the p-value was smaller, the significance of the corresponding coefficient should be bigger. It can be seen from Table 6 that most of regression coefficients of the quadratic polynomial models were significant with low p-values.

The three-dimensional (3D) response surface and two-dimensional (2D) contour plots are the graphical representations of the quadratic polynomial regression equation [49]. They provide a method to visualize the relationship between the responses and the experimental levels of each variable, and the interactions between any two test variables from the circular or elliptical nature of contour [50]. A circular contour plot indicates that the interactions between the corresponding variables are negligible. An elliptical nature of the contour plots indicates that the interactions between the corresponding variables are significant [51]. In this study, the 3D response surfaces and 2D contour plots of palmarumycin C₁₃ field (mg/L) versus the metal ion concentrations (mmol/L) are presented in Figure 4, which were generated by employing the software of Design-Expert. Analyses of the 3D response surfaces and their corresponding 2D contour plots allowed us to conveniently investigate the interactions between any two variables, and locate the optimum ranges of the variables efficiently such that the response was maximized. The maximum predicted response was indicated by the surface confined in the smallest ellipse in the contour diagram.

Figure 4A,B graphed the effects of Ca²⁺ and Cu²⁺ on palmarumycin C₁₃ yield and their interactions when Al³⁺ concentration was fixed at zero level (2.0 mmol/L). A full elliptic contour in Figure 4B was observed, indicating a significant interaction between Ca²⁺ and Cu²⁺ for palmarumycin C₁₃ production. When the concentrations of Ca²⁺ and Cu²⁺ in medium were increased from the lowest levels to the highest levels, palmarumycin C₁₃ yield was increased initially and then decreased. Similar results appeared in Figure 4C,D, as well as in Figure 4E,F. Palmarumycin C₁₃ yield was initially augmented and then decreased when the concentrations of two metal ions (either Ca²⁺ and Al³⁺ or Cu²⁺ and Al³⁺) varied from the lowest levels to the highest levels. The interactions either between Ca²⁺ and Al³⁺ or between Cu²⁺ and Al³⁺ were not significant. They were consistent with the analyses of coefficients of the regression equation (Table 6).

By analyzing the 3D response surface and 2D contour plots, the corresponding point to the maximum of palmarumycin C₁₃ yield should locate on the peak of the response surface, which projected in the smallest ellipse in the contour diagram [52]. Hence, the optimal ranges of the concentrations of Ca²⁺, Cu²⁺ and Al³⁺ in medium for realizing the maximization of palmarumycin C₁₃ yield were calculated by the software Design Expert as follows: 5.94 to 9.06 mmol/L for Ca²⁺, 1.24 to 1.63 mmol/L for Cu²⁺, and 1.86 to 2.15 mmol/L for Al³⁺.

By solving the inverse matrix of the regression polynomial equation (Equation 1) employing the software of Design-Expert, the optimum values for palmarumycin C₁₃ yield of the test parameters in uncoded units were obtained as follows: Ca²⁺ as 7.58 mmol/L, Cu²⁺ as 1.36 mmol/L, and Al³⁺ as 2.05 mmol/L. Under the optimum conditions, the predicted palmarumycin C₁₃ yield reached the maximum (208.49 mg/L). Under the determined conditions, a mean value of palmarumycin C₁₃ yield of 203.85 mg/L (n = 5) was obtained from the actual experiments, slightly lower than the predicted maximum value (208.49 mg/L), and about 6.00-fold of the original yield (33.98 mg/L) in the original basal medium. Based on the Student t-test, the above model was satisfactory and adequate for reflecting the expected optimization as no significant difference was observed between the predicted maximum palmarumycin C₁₃ yield and the experimental one.

The endophytic fungus Berkleasmium sp. Dzf12 (GenBank accession number EU543255) was isolated from the healthy rhizomes of the medicinal plant Dioscorea zingiberensis C. H. Wright (Dioscoreaceae) in our previous study [8,9]. The living culture has been deposited in China General Microbiological Culture Collection Center (CGMCC) under the number of CGMCC 2476. It was also maintained on potato dextrose agar (PDA) slants at 4 °C. For preparation of the inoculum, four disks (about 5 mm) of the mycelia of Dzf12 were transferred into each Erlenmeyer flask (300 mL) containing 100 mL of potato dextrose broth. After 4 days’ cultivation on a rotary shaker in darkness at 150 rpm and 25 °C, the seed suspension cultures in three percent (v/v) were inoculated in Erlenmeyer flasks (150 mL) containing 30 mL of fermentation medium, which composed of glucose 40 g/L, peptone 10 g/L, KH₂PO₄ 1.0 g/L, MgSO₄·7H₂O 0.5 g/L and FeSO₄·7H₂O 0.05 g/L, pH 6.5. The Erlenmeyer flasks were incubated on a rotary shaker in darkness at 150 rpm and 25 °C for 13 days.

Stock metal ion solutions were prepared by dissolving each inorganic salt (i.e., NaCl, CaCl₂·2H₂O, AgNO₃, CoCl₂·6H₂O, CuCl₂·2H₂O, AlCl₃·6H₂O, ZnCl₂, and MnCl₄·4H₂O) in distilled water. The solutions were sterilized by filtrating through a microfilter (pore size, 0.22 μm), diluted with sterile water into different concentrations, and then stored at 4 °C before use. Based on our preliminary experiments (data not shown), the metal ion solutions were added to three-day-old cultures. 100 μL of the stock solution was used as inoculum in 30 mL medium in the experiments with varying amounts of NaCl (final concentrations of Na⁺ in medium as 5, 10, 20 mmol/L), CaCl₂·2H₂O (final concentrations of Ca²⁺ in medium as 5, 10, 20 mmol/L), AgNO₃ (final concentrations of Ag⁺ in medium as 0.05, 0.10 and 0.50 mmol/L), CoCl₂·6H₂O (final concentrations of Co²⁺ in medium as 0.05, 0.10 and 0.50 mmol/L), CuCl₂·2H₂O (final concentrations of Cu²⁺ in medium as 0.50, 1.50 and 3.00 mmol/L), AlCl₃·6H₂O (final concentrations of Al³⁺ in medium as 0.50, 1.50 and 3.00 mmol/L), ZnCl₂ (final concentrations of Zn²⁺ in medium as 2.00, 4.00 and 8.00 mmol/L), MnCl₄·4H₂O (final concentrations of Mn⁴⁺ in medium as 2.00, 4.00 and 8.00 mmol/L), respectively. As Ca²⁺, Cu²⁺ and Al³⁺ were found to be the most effective metal ions (data shown in Table 1), they were applied in the next experiments at five concentrations (1, 5, 10, 15 and 20 mmol/L for Ca²⁺; 0.5, 1.0, 1.5, 2.0 and 3.0 mmol/L for Cu²⁺; 0.5, 1.0, 1.5, 2.0 and 2.5 mmol/L for Al³⁺) on days 0, 3, 6, 9 and 12 of culture, respectively. Furthermore, Al³⁺ was added on day 3 of culture at six concentrations (2, 4, 6, 8, 10 and 12 mmol/L) to investigate its effect on palmarumycins C₁₂ and C₁₃ production. For investigating the combination effects of Ca²⁺, Cu²⁺ and Al³⁺ on palmarumycin C₁₃ production, the final concentrations of the metal ions were set by the software of Design Expert and presented in Table 3.

The mycelia of Berkleasmium sp. Dzf12 were separated from the liquid medium by filtration under vacuum and rinsed thoroughly with distilled water, and then dried at 50–55 °C in an oven to a constant dry weight (dw).

Palmarumycin extraction and determination were carried out as previously described [10,29–31]. Briefly, 50 mg of dry mycelia powder was added into a tube with 5 mL of methanol-chloroform (9:1, v/v), and then subjected to ultrasonic treatment (three times, 60 min each). After removal of the solid by filtration, the filtrate was evaporated to dryness and re-dissolved in 1 mL of methanol. For quantitative analysis of palmarumycins C₁₂ and C₁₃ in broth, 3 mL of the culture broth without mycelia was evaporated to dryness and extracted with 5 mL of methanol-chloroform (9:1, v/v) in an ultrasonic bath (three times, 60 min each), and the liquid extract was then evaporated to dryness and re-dissolved in 1 mL of methanol.

Palmarumycin content was analyzed by the high performance liquid chromatography (HPLC) system (Shimadzu, Japan), which consisted of two LC-20AT solvent delivery units, an SIL-20A autosampler, an SPD-M20A photodiode array detector, and CBM-20Alite system controller. The reversed-phase Agilent TC-C₁₈ column (250 mm × 4.6 mm i.d., particle size 5 μm) was used for separation by using a mobile phase of methanol-H₂O (50:50, v/v) at a flow rate of 1.0 mL/min. The temperature was maintained at 40 °C, and UV detection at 226 nm. The sample injection volume was 10 μL. The LCsolution multi-PDA workstation was employed to acquire and process chromatographic data. Palmarumycins C₁₂ and C₁₃ were detected and quantified with the standards prepared according to the method of Cai et al.[8] and Li et al.[10].

Central composite design (CCD) experiments and response surface methodology (RSM) were employed to optimize the concentrations of Ca²⁺, Cu²⁺ and Al³⁺ in the fermentation medium for realizing the maximization of palmarumycin C₁₃ yield by the software of Design-Expert. The metal ion solutions were added to 3-day-old cultures. 100 μL of the stock solution was used as inoculum in 30 mL medium in the experiments with varying amounts of CaCl₂·2H₂O, CuCl₂·2H₂O, and AlCl₃·6H₂O, respectively. Each independent variable (final metal ion concentration) in the CCD experiments was studied at five coded levels (−1.682, −1, 0, +1, +1.682), which is represented in Table 3. The independent variable was expressed as X_i, which was coded as x_i, according to the following equation (Equation 2):

where x_i is the coded value of the variable X_i, while X₀ is the value of X_i at the center point, and ΔX is the step change of an independent variable.

CCD in this experimental design consisted of 20 trials which were carried out in a random order in triplicate that was necessary to estimate the variability of measurements, which are presented in Table 4. Five replicates at the center point of the design were carried out to allow for estimation of a pure error sum of squares. Palmarumycin C₁₃ yield was recorded as the mean of triplicates, which was taken as the response value.

Based on the CCD experimental data, a second-order polynomial model was established, which correlated the relationship between palmarumycin C₁₃ and the test independent variables. The relationship could be expressed by the following equation (Equation 3):

where Y is the predicted response value; a₀ is the intercept term; x₁, x₂ and x₃ are test independent variables; a₁, a₂ and a₃ are linear coefficients; a₁₂, a₁₃ and a₂₃ are cross-product coefficients; and a₁₁, a₂₂ and a₃₃ are the quadratic term coefficients. All of the coefficients of the second polynomial model and the responses obtained from the experimental design were subjected to multiple nonlinear regression analyses.

The fitness of the second-order polynomial model equation was evaluated by the coefficient (R²) of determination. The analysis of variance (ANOVA) and test of significance for regression coefficients were conducted by F-test. In order to visualize the relationship between the response values and test independent variables, the fitted polynomial equation was separately expressed as 3D response surfaces and 2D contour plots by the software of Design Expert [53,54].

All experiments were carried out in triplicate, and the results were represented by their mean values and the standard deviations (SD). The data were submitted to analysis of variance (one-way ANOVA) to detect significant differences by PROC ANOVA of SAS version 8.2. The term significant has been used to denote the differences for which p ≤ 0.05.