Influences of fermentation parameters on lovastatin production by Monascus purpureus using Saccharina japonica as solid fermented substrate

LWT - Food Science and Technology 92 (2018) 1–9

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Influences of fermentation parameters on lovastatin production by Monascus purpureus using Saccharina japonica as solid fermented substrate

T

Sharmin Suraiya, Jang-Ho Kim, Jin Yeong Tak, Mahbubul Pratik Siddique, Cho Ja Young, Joong Kyun Kim, In-Soo Kong∗ Department of Biotechnology, College of Fisheries Science, Pukyong National University, 45 Yongso-ro, Nam-gu, Busan, 48513, Republic of Korea

A R T I C L E I N F O

A B S T R A C T

Keywords: Brown seaweed Lovastatin Fermentation Hypocholestromic Cytotoxic

In this study, Saccharina japonica (brown seaweed) was fermented in solid state by Monascus purpureus to maximize lovastatin production, the response surface methodology (RSM) was applied to optimize four different fermentation parameters: temperature (25−35 °C), time (10−20 days), glucose (0.1–1.5%) and peptone (0.1–0.7%) concentration. The predicted combination of process parameters yielding the highest rate of lovastatin production (13.40 mg gdfs−1) was obtained at a temperature of 25.64 °C, a fermentation time of 14.49 days, glucose concentration of 1.32% and peptone concentration of 0.20%, with 92.85% validity. Among the studied factors, glucose, incubation time and temperature most strongly influenced lovastatin production. Triplicate experiments in which lovastatin was produced under optimal conditions resulted in a mean yield of 13.98 mg gdfs−1 with 207.84 mg gdfs−1 biomass. Liquid chromatography–tandem mass spectrometry (quadrupole time-of-flight) analysis confirmed the ionic molecular weight of lovastatin (405.26). Lovastatin from the M. purpureus fermented S. japonica exhibited thermal stability, superoxide dismutase activity and a cholesterol esterase inhibition activity that was higher than that of unfermented sample and showed no toxic effect on Caco2 cell. Thus, S. japonica was a suitable substrate to maximize lovastatin production from M. purpureus at optimum condition for applying in food and pharmaceutical industry.

1. Introduction Brown seaweed, Saccharina japonica is extensively cultured and consumed in China, Japan and Korea. It is rich in easily degradable carbohydrates in addition to containing large amounts of moisture (70−90% wet weight), polysaccharides (48−61% dry weight), protein 5−21% and lipid (1−4%) (Holdt & Kraan, 2011). The high fermentable carbohydrate and total nitrogen contents of S. japonica (33.4% and 2.2–4.3%, respectively) make it a suitable solid substrate for fermentation (Ra & Kim, 2013). Other substrates that have been used for lovastatin production include rice bran, wheat bran, rice, oil palm frond and corn, but some of these substrates are expensive and/or are needed as food for humans and feed for livestock (Lee, Wang, Kuo, & Pan, 2006). Seaweeds, by contrast, are easily available and inexpensive in coastal countries. Moreover, they lack the hard lingocellulosic materials and are thus readily depolymerized. In this study, the brown seaweed S. japonica was used as a substrate in solid state fermentation (SSF) by the mold Monascus purpureus to obtain lovastatin. Lovastatin (monacolin K) is a natural statin approved by United States Food and Drug Administration (USFDA) as an inhibitor of HMG-

∗

CoA reductase, which prevents the formation of mevalonate from HMGCoA during cholesterol biosynthesis. Both in vitro and in vivo studies have confirmed the ability of lovastatin to reduce plasma cholesterol levels in animals and humans (Chang, Huang, Lee, Shih, & Tzeng, 2002). Since the accumulation of cholesterol in the major arteries is an important mechanism underlying myocardial infarction, lovostatin is a widely prescribed drug (Dikshit & Tallapragada, 2016). Several fungal species produce lovastatin, especially Aspergillus terreus, Doratomyces, Eupenicillium, Monascus pilosus, M. ruber, M. purpureus, Penicillium spp. and Trichoderma are remarkable (Sayyad, Panda, Javed, & Ali, 2007; Seraman, Rajendran, & Thangavelu, 2010). Monascus spp. are nonpathogenic beneficial fungus which produce variety of secondary metabolites such as pigments and anti-cholesterol agent, lovastatin. These metabolites are used in food to increase their nutritional value, improve aroma, appearance, and reducing coronary heart disease. Research study showed that lovastatin production was significantly higher in solid state fermentation (SSF) than submerged culture. In SSF, microorganisms develop on both the surface and the interior of a solid matrix, in absence of free water (Barrios-González & Miranda, 2010). SSF products can be consumed directly after sterilization and can be

Corresponding author. Department of Biotechnology, College of Fisheries Science, Pukyong National University, 45, Yongso-ro, Nam-gu, Busan, 48513, Republic of Korea. E-mail address: [email protected] (I.-S. Kong).

https://doi.org/10.1016/j.lwt.2018.02.013 Received 30 November 2017; Received in revised form 15 January 2018; Accepted 7 February 2018 Available online 10 February 2018 0023-6438/ © 2018 Elsevier Ltd. All rights reserved.

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2.2. Monascus spp. Culture

used as multiple therapeutic agents. Although lovastatin has several different biofunctional activities, its cholestrol-lowering effect in the treatment of hypocholesterolemic is one of the main bioactivity (Chiou, Lai, & Lin, 2006; Wei et al., 2003). Hypercholesterolemia is a metabolic disorder that arises from the ingestion of foods rich in saturated fats and cholesterol, leading to the development of obesity, diabetics and hypertension. An important activity of lovastatin is its inhibition of cholesterol esterase (CE), which is released from the intestinal lumen in response to the ingestion of a fat-containing meal (Chiou et al., 2006). But most of the anti-cholesterol drugs are expensive and/or cause side effects, such as joint pain, muscle pain, dyspepsia, constipation, increase liver enzyme and blood glucose levels. These drawbacks have stimulated the search for novel biological agents that can be used in the prevention and treatment of hyperlipidemia. Thus, the fermentation of S. japonica by Monascus, naturally contains lovastatin, would provide an inexpensive and reliable source of the drug. The fungal production of lovastatin is affected by many factors, including the culture homogeneity, carbon source, fermentation time and speed of agitation (Panda, Javed, & Ali, 2009, 2010). The composition and temperature of the fermentation medium are also important, as they influence the growth and metabolism of the fungus and therefor its production of lovastatin as a secondary metabolite (Chang et al., 2002). During fermentation, the carbon and nitrogen sources are crucial determinants of fungal biomass and metabolite production (Endo, Hasumi, Nakamura, Kunishima, & Masuda, 1985). Given these many variables affecting the yield of lovastatin, we chose the response surface methodology (RSM) as a powerful statistical technique to compare one culture variable at a time, thus reducing the number of experimental trials needed to optimize the process. RSM has been extensively used worldwide to optimize fermentation reactions and has thus found numerous fields of application (Zhou, Wang, Zhu, Liu & Liang, 2009; Getachew & Chun, 2016). To determine the toxicological effects associated with fermentation, in vitro testing methods are simpler, more economical and faster than animal studies and thus provide a convenient screening tool (O'Sullivan et al., 2012). Caco-2 cells have been extensively used in in vitro tests of the toxic effects of several bioactive compounds in the small intestine (Rasmussen, Rasmussen, Larsen, Bladt, & Binderup, 2011) and were therefore used in the present work. As the production of lovastatin using brown seaweeds, a renewable marine biomass, has not yet to be reported, the main purposes of this study was to apply the RSM to optimize the conditions leading to maximum lovastatin production by M. purpureus using S. japonica as solid substrate. The identify and ionic molecular weight of lovastatin were confirmed using liquid chromatograph–tandem mass spectrometry (quadrupole time of flight) LC−MS/ MS (Q-TOF) mass spectrometry. Secondary objectives of this study were to estimate the amount of fermented biomass and to determine the thermal stability of lovastatin, its superoxide dismutase (SOD) and anticholesterol activities and the cytotoxicity of the lovastatin containing fermented.

M. purpureus KCCM 60168 and M. kaoliang KCCM 60154 were obtained from the Korean Culture Center of Microorganism (KCCM). The red molds were cultured on potato dextrose agar (PDA) and yeast extract agar (YEA), respectively, at 30 °C for 12 days before they were used to inoculate in S. japonica as the solid substrate. The pure-culture plates were maintained according to the method of Suraiya et al. (2017). 2.3. Solid state fermentation Inocula of M. purpureus were prepared according to the method of Suraiya et al. (2017) with few modifications. Briefly, 10 mL of distilled water was added to an agar plate with a fully-grown culture of M. purpureus. The plate was scraped aseptically and allowed to stand for 5 min to obtain a homogenous spore suspension. Finely ground S. japonica powder (5 g) was placed in a 100-mL conical flask; the moisture content was maintained at 50% (w/w) using distilled water. Then 3 mL of the fungal inoculum wad added to the substrate. Initially, both M. purpureus and M. kaoliang were used for the SSF of S. japonica to obtain lovastatin, with exogenous peptone and glucose added to cultures maintained at 30 °C for 1 month. However, after screening both species only M. purpureus was selected, based on its production of larger amounts of lovastatin. 2.4. Experimental design and statistical analysis The RSM was used to optimize the lovastatin yield obtained from the brown seaweed after its fermentation by M. purpureus under different fermentation conditions, and the Box Behnken design (BBD) was used to optimize those conditions. In the BBD, error was minimized by using 29 randomized runs with five replicates in the central point. The four independent variables used in this experimental design were: fermentation temperature (25−35 °C), time (10−20 days), glucose (0.1–1.5%) and peptone (0.1–0.7%), with three levels used to optimize the fermentation process. Each variable was tested in three coded levels: −1, 0 and + 1 (Table 1). The coded factors are described by Eq. (1):

X=

(Xi − X0) ΔX

(1)

Where, X is the coded value, Xi is the actual value, X0 is the actual value in the center point, and ΔX is the increment of Xi corresponding to a variation of 1 unit. The response variable was fitted to the quadratic polynomial model shown in Eq. (2): k

Y = β0 +  ∑ βi Xi + i= 1

k

k

∑ βii Xi2 + ∑ ∑ i= 1

βij Xi Xj + ε

i
(2)

Where, Y is the response variable, Xi and Xj are the independent variables affecting the response, and β0, βi, βii and βij are the regression coefficients for intercept, linear, quadratic, and interaction term, respectively, and ε is the error. The optimum conditions and the treatment of multiple responses were selected based on the desirability function (Design-Expert v.7, Stat-Ease, Minnesota, USA) and then used for the analysis of BBD experimental design together with multiple regression analysis.

2. Materials and methods 2.1. Materials and reagents D-glucose monohydrate was purchased from Duchefa Biochemie (B.V, Nethaerlands) and Bacto™ Peptone was obtained from BD (Franklin Lakes, NJ, USA). HPLC graded ethyl alcohol, methyl alcohol and ethyl acetate (Samchun Pure Chemical, South Korea), Trifluoroacetic acid (Acros organics, Belgium), Acetonitrile (J. T. Baker, USA), Water (Burdick and Jackson, USA) were used in this study. The lovastatin standard was purchased from Sigma Aldrich (St. Louis, MO, USA).

2.5. Extraction and quantification of lovastatin Fermented dried seaweed (0.25 g) was extracted using 5 mL ethyl acetate, shake-incubating the mixture for 24 h at 180 rpm and 25 °C. The extract was then centrifuged at 10,000 rpm for 10 min and the supernatant filtered through a 0.45 μm filter (Minisart, Sartorius Stedim Biotech GmbH, Goettingen Germany). Lactonization was achieved by 2

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Table 1 Box-Behnken experimental design with natural and coded fermentation conditions and experimentally obtained values of lovastatin. Trials

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29

Investigated response lovastatin (mg gdfs−1)

Independent variables A: Glucose (%)

B: Peptone (%)

C:Time (Day)

D:Temp (°C)

Experimental result

Predicted result

0.1 0.1 0.8 0.1 1.5 0.8 0.8 0.1 0.8 0.8 1.5 0.8 0.8 0.8 1.5 0.8 0.8 0.8 0.8 0.8 0.1 0.8 1.5 0.1 0.8 0.8 0.8 1.5 1.5

0.7 0.1 0.4 0.4 0.4 0.1 0.7 0.4 0.4 0.4 0.1 0.4 0.1 0.4 0.4 0.4 0.1 0.7 0.7 0.7 0.4 0.4 0.4 0.4 0.1 0.4 0.4 0.4 0.7

15 15 15 10 10 15 15 20 15 10 15 20 20 10 15 15 15 10 20 15 15 15 20 15 10 15 20 15 15

30 30 30 30 30 25 25 30 30 35 30 35 30 25 35 30 35 30 30 35 25 30 30 35 30 30 25 25 30

12.19 10.16 11.86 4.42 6.99 11.68 10.53 5.56 10.91 6.54 10.94 4.06 5.01 6.78 9.74 12.11 6.40 3.98 5.82 11.81 10.07 12.56 5.61 12.22 7.28 11.11 9.23 12.22 11.72

11.15 9.76 11.71 5.35 7.05 12.67 10.16 6.50 11.71 6.55 10.82 3.97 4.14 5.71 9.39 11.71 7.77 5.01 6.95 11.81 10.58 11.71 5.67 11.27 6.31 11.71 8.06 13.33 10.96

(−1) (−1) (0) (−1) (+1) (0) (0) (−1) (0) (0) (+1) (0) (0) (0) (+1) (0) (0) (0) (0) (0) (−1) (0) (+1) (−1) (0) (0) (0) (+1) (+1)

(+1) (−1) (0) (0) (0) (−1) (+1) (0) (0) (0) (−1) (0) (−1) (0) (0) (0) (−1) (+1) (+1) (+1) (0) (0) (0) (0) (−1) (0) (0) (0) (+1)

(0) (0) (0) (−1) (−1) (0) (0) (+1) (0) (−1) (0) (+1) (+1) (−1) (0) (0) (0) (−1) (+1) (0) (0) (0) (+1) (0) (−1) (0) (+1) (0) (0)

(0) (0) (0) (0) (0) (−1) (−1) (0) (0) (+1) (0) (+1) (0) (−1) (+1) (0) (+1) (0) (0) (+1) (−1) (0) (0) (+1) (0) (0) (−1) (−1) (0)

2.7. Biomass estimation and thermal stability of lovastatin

incubating 0.5 mL of the supernatant in 0.5 mL of trifluroacetic acid (1%) for 1 h. The lovastatin yield was estimated using a high-performance liquid chromatography (HPLC, Agilent 1200, Agilent Technologies, Santa Clara, CA, USA) system equipped with an isocratic pump with a UV/VIS detector. A YMC-pack ODS-A column (5 μm, 4.6 × 150 mm) was used for lovastatin quantification. The mobile phase was consisted of acetonitrile and water (65:35, v/v) delivered at flow rate of 1 mL min−1. Lovastatin was detected at a wavelength of 238 nm.

The total biomass of Monascus spp. was determined using the method of Babitha, Soccol, and Pandey (2007). The absorbance was measured at 530 nm against the reagent blank. For biomass estimation, N-acetyl-D-glucosamine (Sigma-Aldrich) served as the standard. The thermal stability of lovastatin was estimated by using one set of corning tubes each containing 1 mL of lovastatin sample. These tubes were incubated for 1 h at −80, −20 °C temperature and another set was incubated at 0, 20, 40, 60, 80, and 100 °C for 1 h. The amount of lovastatin was then estimated using HPLC.

2.6. Confirmation of lovastatin by LC−MS/MS (Q-TOF) 2.8. SOD activity of lovastatin sample M. purpureus fermented seaweed of 0.5 g was dissolved in three different solvents (ethanol, methanol, and acetonitrile) instead of ethyl acetate, which because of its volatility was difficult to detect by LC−MS/MS (Q-TOF) (Bruker, Germany). After incubation for 24 h at 180 rpm and 25 °C, the mixture was filtered through a 0.45 μm filter and the filtrate was used for LC−MS/MS (Q-TOF) analysis. The LC−MS/MS (Q-TOF) system was prepared by separating the mixed substances using an ultra performance liquid chromatography (UPLC) system consisting of a C18 column (1.7 μm, 10 mm × 2.1 mm) equipped with an isocratic pump and using acetonitrile and water (65:35, v/v) containing 0.1% formic acid. Ionizing was carried with ion spray and separation was achieved according to a mass to charge ratio 20,000–40,000 (m/z). Q-TOF can be measured with high sensitivity by selecting a specific substance present in the mixture and detectable at high resolution. All analyses were performed using the ESI interface with the following settings: positive ionization mode; nebulizer 1.0 bar; active focus; capillary voltage 4500 V; dry heater set at 200 °C; scan 50–200 m/z; end-plate offset −500V; dry gas flow 8.0 L min−1; charging voltage 2000 V; corona 0 nA and APCI heater set at 0 °C.

The SOD activity of the lovastatin sample was determined using a SOD assay Kit (Bio Vision, Milpitas, CA, USA) and the method described by Dudonné, Vitrac, Coutière, Woillez, & Mèrillon (2009). In this method O2·‾ reduces WST-1 to produce yellow formazan, which is measured spectrophotometrically at 450 nm. Antioxidants are able to inhibit yellow WST formation; thus, the percentage of inhibition of superoxide radical formation was calculated as:

SOD activity (% of inhibition) (Abs of sample − Abs of control) ⎤ ×100 = ⎡1− Abs blank ⎦ ⎣ Where, Abs of sample = sample with SOD reagent, Abs of control = sample without SOD reagent and Abs blank = SOD reagent without sample. 2.9. Anti-cholesterol activity of the lovastatin sample A modified version of the method of Pietsch & Gutschow (2002) was used to determine pancreatic cholesterol esterase (CE) inhibition. The 1-mL reaction contained 100 μL of different concentrations of various 3

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inhibitors pre-incubated with 400 μL of Triton X-100 (5% w/w), 100 μL of p-nitrophenyl butyrate (p-NPB; 0.05 M in acetonitrile), 20 μL of acetonitrile (2%) and 280 μL of assay buffer (100 mM sodium phosphate, 100 mM NaCl, pH 7.0). The sample was mixed thoroughly and incubate for 5 min at 25 °C before the reaction was initiated by the addition of 100 μL of CE (5 μg mL-1in 100 mM sodium phosphate buffer pH 7.0). The samples were mixed again and after 1 min the amount of liberated p-nitrophenoxide was determined by measuring the absorbance at 405 nm.

lovastatin production were < 0.05 and therefore positively significant. The results of the analysis of variance (ANOVA) of the model are shown in Supplementary Table 1. Therefore, the mathematical model of the response was statistically acceptable at the 5% significance level (Supplementary Table 1). The experimental values were fitted to a polynomial quadratic model [Eq. (3)] and multiple regression coefficients were generated for all responses using the least square method, a multiple regression technique generating the lowest residual possible. A lack of fit test confirmed the suitability of experimental data to the quadratic model as the p value < 0.05 (Supplementary Table 1). Lack of fit F-value 3.29 implies that it is not significant, consequently model is fit for this assay (Supplementary Table 1). There is only 13.11% chance of ‘lack of fit’ due to noise. The correlation coefficient of the multiple regression (R2) for lovastatin production was 0.9285, reflecting the good representation of the experimental values by the model equation. The adjusted R2 in this study was 0.8569 which is close to R2 value indicate better prediction of the model (Supplementary Table 1). Lovastatin production from M. purpureus using S. japonica as solid substrate under the optimized conditions specified by the RSM was therefore determined to be a potent production method. Seraman et al. (2010) used CCD experimental design to optimize lovastatin production; the correlation coefficient in the multiple regression (R2) was 0.901.

2.10. Cytotoxicity assay (cell proliferation) of lovastatin by MTS assay Caco-2 cells (KCLB 30037) were purchased from the Korean Cell Line Bank (KCBL) and grown at 37 °C in an atmosphere of 95% air and 5% CO2 in Dulbecco's modified Eagle medium (Gibco, Grand Island, NY) supplemented with 10% fetal bovine serum and 1% streptomycinpenicillin (100 μg mL-1 and 100 IU mL−1, respectively). The cells were seeded in clear 96 well flat bottom plates at a concentrations of 6.2 × 103 cells well−1 were, incubated for 24 h, after which adherent cells were treated with various concentrations of sample and incubated again for 24 h. Caco-2 cells viability was measured using a cell proliferation assay Kit (Celltiter 96® AQueous non-radioactive cell proliferation assay, Promega, Germany). The number of living cells in culture was determined at 490 nm using microplate spectrophotometer (Infinite M200 nanoquant, Tecan, Zurich, Switzerland). Here, M. purpureus fermented S. japonica, unfermented S. japonica and standard lovastatin was expressed as SjMp (L), SjU and L, respectively.

3.2. Effect of fermentation conditions on lovastatin production The effect of each fermentation parameter and their interactions effect on lovastatin production by M. purpureus using S. japonica was examined. Based on the experimental data, six response surface threedimensional (3D) graphs were obtained using the multiple nonlinear quadratic regression model. The results showed the positive linear and negative quadratic effect of glucose on lovastatin production. Fig. 1b, c, and f showed that lower amount of glucose was not suitable for higher lovastatin production and with the glucose concentration increment, the lovastatin production was increased. So, it can be concluded that higher glucose concentration was suitable for lovastatin production. Sayyad et al. (2007) also found that the glucose concentration was a positive, significant factor for lovastatin production using M. purpureus MTCC 369. As S. japonica contains high amount of moisture, polysaccharides, protein and mineral (Holdt & Kraan, 2011), it is suitable for fungal fermentation and production of secondary metabolite, lovastatin. Although in S. japonica fermentable sugar is not readily available but plenty of carbohydrases available in M. purpureus convert polysaccharides to utilizable mono-sugar for growth and produce metabolite (Pandey, 2003; General, Prasad, Kim, Vadakedath, & Cho, 2014). This characteristic accounts for the suitability of S. japonica as a solid substrate for fermentation and subsequent lovastatin production by M. purpureus. The negative linear and negative quadratic effect of peptone on lovastatin production (Fig. 1a, b, and e) showed that a medium amount of external peptone supplement was suitable for SSF. Chang et al. (2002) found a positive effect of peptone on lovastatin production by M. ruber. Fig. 1a, c, and d show the positive significant effect of incubation time on lovastatin production. The figures showed that both shorter and longer fermentation times reducing lovastatin production. In the SSF of rice by M. purpureus, the fermentation period was also shown to be a positive significant factor for lovastatin production (Panda et al., 2009). Our analysis of the effect of fermentation temperature showed that a higher temperature was not suitable for lovastatin production (Fig. 1d–f). Panda, Javed, and Ali (2010) determined an optimum fermentation temperature 29.46 °C in the production of lovastatin by the SSF of rice by a co-culture of M. purpureus and M. ruber.

2.11. Data analysis The data were analyzed using IBM SPSS software ver. 20. A p value (< 0.05) was considered to indicate statistical significance. The data are expressed as the mean ± standard deviations (SD) for triplicate samples. 3. Results and discussions 3.1. Model fitting and response surface analysis RSM was used to optimize lovastatin production by M. purpureus in SSF in which S. japonica was the substrate. The four examined variables were temperature, fermentation time, glucose concentration and peptone concentration. Their response/influence was measured as the lovastatin yield (mg g−1 of dried fermented S. japonica). The actual and predicted values are shown in Table 1. Equation (3) is the multiple nonlinear quadratic regression model used in this work: Lovastatin = − 60.56 + 14.33A − 33.60B + 7.71C + 1.16D −1.47AB − 0.18AC − 0.33AD + 0.68BCE + 1.09BD −0.05CD −0.50A2 − 8.76B2 − 0.21C2 − 0.012D2 (3) Where A, B, C and D represent glucose (%), peptone (%), incubation period (days), incubation temperature (°C), respectively. State-ease Design expert 7 software was used for point prediction to measure the optimum values of the four variables for maximum lovastatin production. The lovastatin yield obtained from the different experimental conditions defined in the RSM varied from 3.98 to 12.56 mg gdfs−1 (Table 1). Thus, in this study, lovastatin production from M. purpureus using S. japonica as the solid substrate was higher than that reported by Su, Wang, Lin, & Pan, 2003. These results were also higher than the reports of Chang et al., 2002; Lee et al., 2006, used monoculture of M. ruber, M. pilosus, and M. purpureus on rice for optimization of maximum lovastatin production. Lovastatin production from M. purpureus using S. japonica as solid substrate, the BBD of the RSM runs was designed according to three randomly selected levels. The p-value of the four variables influencing

3.3. Model adequacy and verification Model adequacy was determined using the diagnostics plots shown 4

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Fig. 1. Three dimensional response surface plots representing interaction effects: (a) peptone concentration with incubation period (time) (b) peptone concentration with glucose concentration (c) glucose concentration with incubation time (d) incubation temperature with incubation period (time) (f) peptone concentration with incubation period (time) (g) incubation temperature with glucose concentration.

5

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Fig. 2. Diagnostic plots for the adequacy of proposed model. (a) Normal % probability verses internally studentized residuals (b) predicted verses actual (c) internally studentized residuals verses run number.

conditions, lovastatin production was predicted to be 13.40 mg gdfs−1 (desirability 1.00), with 92.85% validity. An analysis of the optimized conditions in triplicate experiments resulted in a mean lovastatin production of 13.98 mg gdfs−1. Lovastatin production in the study of Sayyad et al. (2007), using a BBD, was 326 mg L-1 on average, with 93% validity. In the co-culture of M. purpureus and M. ruber on rice, Panda et al. (2010) reported an average lovastatin yield of 2.80 mg g-1, with 98.93% validity.

in Fig. 2. The normal % probability for internally studentized residuals was normally distributed; the values remained close to the straight line without deviation (Fig. 2a) and all the points were within the limits ( ± 3) of run number (Fig. 2b). Predicted vs. actual plots showed that the predicted and actual values for lovastatin production were close to the straight line, indicating adequate agreement between them (Fig. 2c). In a study of lovastatin production from Aspergillus terreus, Lai, Pan, and Tzeng (2003) also found a normal probability (%) distribution for internally studentized residuals. Using RSM to optimize lovastatin production from M. purpureus, the predicted and actual values obtained by Seraman et al. (2010) in a quadratic polynomial model were close to the straight line. The residual data above and below the X-axis indicated that the variance was independent and appropriate for the model. In our model, the predicted combination of process variables resulting in the highest lovastatin production was a temperature of 25.64 °C, a fermentation time of 14.49 days, and glucose and peptone concentrations of 0.20% and 1.32%, respectively. Under these

3.4. LC−MS/MS (Q-TOF) analysis for lovastatin Protonated [M+H+] lovastatin was monitored in electrospray positive ionization mode. In the UPLC chromatogram of LC−MS/MS (QTOF) for the standard, UV chromatogram and base peak chromatogram (BPC) + all MS peak occurred at 4.4 min (Fig. 3a). The ion mass spectrum of the lovastatin standard is shown in Fig. 3b. The UPLC chromatogram of LC−MS/MS (Q-TOF) for S. japonica fermented by M. 6

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Fig. 3. Confirmation of lovastatin using UPLC and LC−MS/MS (Q-TOF). (a) UPLC chromatogram of standard lovastatin showed that UV chromatogram and Base Peak Chromatogram (BPC) peak + All MS was observed in 4.4 min (b) LC−MS/MS (Q-TOF) showed the ion mass (positive ionization mode) spectra of standard lovastatin protonated molecule [M+H+] was 405.26. (c) UPLC chromatogram of fermented seaweed showed that UV chromatogram and Base Peak Chromatogram (BPC) + All Mass peak of lovastatin was observed in 4.3 min (d) LC−MS/MS (Q-TOF) showed the ion mass (positive ionization mode) spectra of fermented sample lovastatin protonated molecule [M+H+] was 405.20 (ethanol extracted). (e) acetonitrile extracted fermented sample lovastatin protonated molecule [M+H+] was 405.26. (f) methanol extracted fermented sample lovastatin protonated molecule [M+H+] was 405.24.

purpureus showed that the UV chromatogram and BPC + all MS peak was occurred at 4.3 min (Fig. 3c). The ionic formula of lovastatin from M. purpureus fermented S. japonica was C24H37O5 (Fig. 3d–f). The ionic molecular weight of lovastatin was consistent with that reported by Silva, Rezende, & Boralli (2014).

produced lovastatin was estimated by HPLC, by measuring the lovastatin concentration. At −80, −20, 0, 20, 40, 60, 80, 100 °C, the lovastatin concentration was 13.07, 13.74, 13.67, 13.97, 12.89, 12.02 and 11.32 mg gdfs−1, respectively. Yoshida et al. (2011) also determined the thermal stability of lovastatin at different temperatures.

3.5. Biomass estimation and thermal stability of lovastatin

3.6. SOD activity

The estimated biomass of M. purpureus feeding on S. japonica was 207.84 mg gdfs−1, based on the glucosamine concentration, and agreed with the result of Babitha et al. (2007). The thermal stability of the

The SOD activity of both the fermented sample containing lovastatin and the standard was higher than that of unfermented sample (Fig. 4a). Lovastatin increased SOD activity both in vitro and in vivo 7

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2011). In normal to mildly hyperlipidemic individuals, the ingestion of M. pilosus-fermented garlic extract reduces triglyceride and cholesterol levels in serum, with no noticeable adverse effects (Higashikawa, Noda, Awaya, Ushijima, & Sugiyama, 2012). 3.8. Cytotoxicity by MTS assay The data clearly demonstrated that neither the fermented nor the unfermented sample exhibited cytotoxicity and that cell viability was maintained (Fig. 4c). Tobert (2003) reported the low cytotoxicity of a lovastatin-containing extract. Rasmussen et al. (2011) also reported that monacolin K (lovastatin) was not cytotoxic, whereas in an MTS assay Lin, Song, and Pan (2006) demonstrated moderate cytotoxicity to Caco-2 cells (IC50 = 30 μg mL−1). 4. Conclusions S. japonica is rich in carbohydrates, including alginate, fucoidan, laminarin, glucan and mannitol, and therefore a suitable substrate for lovastatin production by M. purpureus via fermentation. The fermentation conditions to produce lovastatin were optimized using quadratic polynomial. Under the optimized conditions, the yield and biomass were 13.98 mg gdfs−1 and 207.84 mg gdfs−1, respectively. The ionic molecular weight of lovastatin was confirmed by LC−MS/MS (Q-TOF). In addition, the produced lovastatin exhibited thermal stability over a wide temperature range. The fermented sample containing lovastatin had high SOD and cholesterol inhibition activities and was not cytotoxic to Caco-2 cells. To the best of our knowledge, this is the first report on the optimization of lovastatin production from M. purpureus fermented S. japonica. This work could be considered as a model approach for lovastatin production and hopefully will draw attention to the researchers as well functional foods and pharmaceutical industries. Conflicts of interest The authors declare no conflicts of interest. Appendix A. Supplementary data

Fig. 4. Bio-functional activity and cytotoxic effect of lovastatin containing M. purpureus fermented S. japonica. (a) SOD activity of lovastatin sample. (b) Cholesterol esterase inhibition activity of M. purpureus fermented lovastatin sample (c) Cytotoxicity of fermented, unfermented and standard lovastatin on Caco-2 cell. Values are Mean ± SD (SD: Standard deviation where, n = 3). Values with the same small letter are not significantly different (p < 0.05) according to Duncan's test. SjU: S. japonica unfermented, SjMp (L): S. japonica fermented by M. purpureus containing lovastatin, L: lovastatin standard.

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