Article pubs.acs.org/JAFC
Metabolomic Analysis Reveals Cyanidins in Black Raspberry as Candidates for Suppression of Lipopolysaccharide-Induced Inflammation in Murine Macrophages Young-Hee Jo,†,∥ Hyun-Chang Park,†,∥ Seulgi Choi,†,∥ Sugyeong Kim,† Cheng Bao,† Hyung Woo Kim,† Hyung-Kyoon Choi,‡ Hong Jin Lee,*,† and Joong-Hyuck Auh*,† †
Department of Food Science and Technology, Chung-Ang University, Anseong 456-756, South Korea College of Pharmacy, Chung-Ang University, Seoul 156-756, South Korea
‡
S Supporting Information *
ABSTRACT: The extracts produced by multisolvent extraction and subfractionation with preparative liquid chromatography of black raspberry (Rubus coreanus Miquel) cultivated in Gochang, South Korea, were tested for their anti-inflammatory effects. The metabolomic profiling and analysis by orthogonal partial least-squares discriminant analysis (OLPS-DA) suggested that cyanidin, cyanidin-3-glucoside (C3G), and cyanidin-3-rutinoside (C3R) were key components for the anti-inflammatory responses in the most active fraction BF3-1, where they were present at 0.44, 1.26, and 0.56 μg/mg of BF3-1, respectively. Both BF3-1 and mixture of these cyanidins at the same ratio reduced lipopolysaccharide (LPS)-induced protein level of iNOS expression and suppressed mRNA and protein expressions of tumor necrosis factor (TNF)-α, interleukin (IL)-6, and IL-1β through inhibiting the phosphorylation of mitogen-activated protein kinases (MAPKs) and STAT3 in murine macrophage RAW264.7 cells. Overall, the results suggested that co-administration of cyanidin, C3G, and C3R is more effective than that of cyanidin alone and that the coexistence of these anthocyanin components in black raspberry plays a vital role in regulating LPS-induced inflammation even at submicromolar concentrations, making it possible to explain the health beneficial activity of its extracts. KEYWORDS: black raspberry, metabolomic profiling, cyanidin, cyanidin-3-glucoside, cyanidin-3-rutinoside
■
INTRODUCTION There are accumulating studies demonstrating the health beneficial efficacy of black raspberry in chronic diseases such as inflammation, metabolic syndrome, atherosclerosis, and cancer.1−6 Black raspberry supplementation retarded mammary tumorigenesis by inhibiting the expression of estrogen receptor α (ER-α), reducing carcinogen-induced esophageal cancer by regulating pentraxin-3 expression, and suppressing ultraviolet B (UVB)-induced inflammation and skin tumor development.2,5,7 In addition, a diet containing 5 or 10% of freeze-dried black raspberries suppressed DSS-induced colon injury through inhibiting cyclooxygenase 2 (COX-2) expression and reducing the level of tumor necrosis factor-α (TNF-α) and interleukin 1β (IL-1β).4 The potential constituents responsible for the health beneficial efficacy of black raspberries have been identified as anthocyanins, simple phenols such as ellagic acid and quercetin, sterols such as β-sitosterol, vitamins, and minerals.8 Tulio et al. identified five different anthocyanins including cyanidin-3-glucoside and cyanidin-3-rutinoside and demonstrated that cyanidin-3-rutinoside and cyanidin-3-xylosylrutinoside may act as the key components exerting antioxidant activity in black raspberry.9 Ferulic acid and βsitosterol were also reported to show antiproliferative activity in oral cancer cell lines without affecting the normal oral epithelial cells.10 Although the roles of powder or extract of black raspberry in physiological effects and their potent ingredients have been elucidated, there are few studies considering the actual concentrations or interactions of the key phytochemicals in the extracts of black raspberry. To overcome this hurdle, it is © XXXX American Chemical Society
meaningful enough to employ a new approach for profiling the whole metabolites and identifying the set of metabolites exerting the health-promoting effects. Metabolomics is nontargeted identification and quantification of all metabolites within a given set of conditions.11 It objectively measures all or a substantial fraction of all metabolites within a sample, quantifies each relative to an absolute index of the sample (per gram, milliliter, etc.), and analyzes hundreds to thousands of small molecular weight metabolites comprehensively within samples according to their molecular weights.12 Metabolomics is a useful tool for the analysis of the phenotype in food science.13 Currently, metabolite profiling methods have been established including mass spectrometry (MS)-coupled methods, such as LC-MS, ultraperformance LC (UPLC)-MS, and capillary electrophoresis (CE)-MS, which have wide availability in analytical technology.14 LC-MS methods are often used with electrospray ionization (ESI), atmospheric pressure chemical ionization (APCI), or matrix-assisted laser desorption/ionization (MALDI) to porovide the samples as ionized state. The ionized metabolites pass through linear TOF-MS, singlequadrupole MS, or Q-TOF to detect the ion mass and intensity15 commonly by MS-MS or MSn. Following profiling by LC-MS, all data are analyzed by statistical tools to screen out Received: February 2, 2015 Revised: May 17, 2015 Accepted: May 17, 2015
A
DOI: 10.1021/acs.jafc.5b00560 J. Agric. Food Chem. XXXX, XXX, XXX−XXX
Article
Journal of Agricultural and Food Chemistry
gradient mobile phase from 5 to 10% B in 5 min, held at 10% B for 5 min, from 10 to 40% B in 20 min, from 40 to 90% B in 10 min, then returned to the initial conditions (5% B) in 5 min and conditioned at 5% B in 10 min, and finished at 55 min. The flow rate was set at 0.3 mL/min, and UV spectra were measured between 180 and 800 nm. Acquisition was performed in the positive and negative ion mode by electrospray ionization (ESI) source, and the m/z range was 100− 1000 Da. The capillary temperature was 275 °C, and the source voltage was set to 5 kV for ionization. Metabolite Identification. The data acquired by LC-MS/MS were processed for peak detection, alignment, and identification by SIEVE software (Thermo Fisher Scientific, Waltham, MA, USA). The acquired LC-MS/MS spectrum was identified after comparison with those proposed by the MASSBANK database (www.massbank.jp), Human Metabolome Database (www.hmdb.ca), METLIN (http:// masspec.scripps.edu), KEGG database (www.Kegg.co.jp), and related papers. Identifications of cyanidin, cyanidin 3-glucoside, and cyanidin 3-rutinoside were confirmed with authentic standard compounds. HPLC Analysis for Quantification of Metabolites. Quantification of anthocyanins and their metabolites was conducted using a standard curve generated from authentic standards of cyanidin, cyanidin 3-glucoside, and cyanidin 3-rutinoside. Analysis was performed by HPLC (Dionex HPLC-3000, Dionex Corp., Sunnyvale, CA, USA) with a UV detector (Ultimate 3000 diode array detector, Dionex Corp.) using an X-bridge C18 column (3.5 μm, 4.6 × 150 mm, Waters) at 35 °C. The solvents were 10% formic acid in water (phase A) and acetonitrile (phase B) at flow rate of 1 mL/mL. The linear gradient profile was as follows: 5−15% B in 15 min, held at 15% B for 5 min, 15−5% B in 5 min, and finished at 25 min. UV spectra were measured at 520 nm. Cell Culture. RAW264.7 cells were obtained from the Korean Cell Line Bank (Seoul, Korea) and cultured in DMEM supplemented with 10% fetal bovine serum (FBS), 1% penicillin/streptomycin, and 1% HEPES at 37 °C and 5% CO2. Cell Proliferation Assay (MTT Assay). The cells were seeded in a 96-well plate and treated with black raspberry extracts for 24 h. The formazan crystals formed from 3-(4,5-dimethylthiazol-2-yl)-2,5diphenyltetrazolium bromide (MTT, Sigma-Aldrich) were dissolved in DMSO, and the absorbance was measured with an ELISA reader at 570 nm (Molecular Devices, Sunnyvale, CA, USA). Western Blot Analysis. This analysis was described previously.16 Briefly, the cells were harvested with radioimmunoprecipitation assay (RIPA) lysis buffer, and the protein extract was separated and transferred to a polyvinylidene difluoride (PVDF) membrane (Millipore, Billerica, MA, USA). The primary antibodies against iNOS (Abcam, Cambridge, MA, USA), COX2, IκBα (Santa Cruz Biotech, Santa Cruz, CA, USA), phospho-ERK, phospho-p38, phospho-JNK, phospho-STAT3 (Cell Signaling Technology, Boston, MA, USA), β-actin (Sigma-Aldrich), and secondary antibodies (Santa Cruz) were used. The expression levels of proteins were visualized with EZ capture MG (ATTO, Tokyo, Japan) and quantified with CS Analyzer (ver. 3.0, ATTO). RNA Extraction and Quantitative RT-PCR Analysis. The cellular RNA was isolated and reverse-transcribed to cDNA using Trizol reagent (Sigma) and a RevertAid First Strand cDNA Synthesis Kit (Theromo Scientific, Lafayette, CO, USA) in Atlas Thermal Cycler (Astec, Fukuoka, Japan), respectively. The cDNA was amplified using TaqMan primers (iNOS, COX-2, TNF-α, IL-1β, interleukin-6 (IL-6), glyceraldehyde-3-phosphate dehydrogenase (GAPDH); Applied Biosystems, Foster City, CA, USA) in ABI Prism 7500 real-time PCR system (Applied Biosystems) and relatively quantified as described in the previous study.16 Enzyme-Linked Immunosorbent Assay (ELISA). Following the instructions from the company, the expression of cytokines (TNF-α, IL-6, IL-1β) in culture supernatants was analyzed using an ELISA kit (Koma Biotech Inc., Seoul, Korea). Data Processing and Statistical Analysis. SIEVE software (Thermo Fisher Scientific) was used for peak/feature picking and deconvolution of raw data. The SIEVE parameters were as follows: mass range, 100−1000 Da; retention time, 1.5−35 min; frame m/z
critical contributors on the significant variations in the target samples. In our previous study, metabolomic investigation using MScoupled method was performed between the fractions separated by multistep solvent extraction, and ellagic acid was successfully identified as a key metabolite in the fraction exerting anti-inflammatory activity in strawberry (‘Seolhyang’).16 Recently, it was also reported that 1H nuclear magnetic resonance (NMR)-based metabolomic analyses were developed, by which the bioactive contributors in black raspberry against oxidative stress and proliferation of HT-29 colon cancer cells were identified.17,18 These results suggested that the metabolomic process could be one of the significant approaches to ascertain the constituents responsible for the physiological efficacy of the active food resources. However, comparative demonstration of active components screening with metabolomic approach along with mechanistic evaluation has been tried to date. In this study, black raspberry cultivated in South Korea was separated into several fractions with organic solvents, and then the most active extract in suppressing lipopolysaccharide (LPS)-induced inflammation was further fractionated. The key contributors were discriminated and identified through multivariate statistical analysis, and their antiinflammatory activity was validated with the underlying mechanism.
■
MATERIALS AND METHODS
Materials. Black raspberry (Rubus coreanus Miquel) cultivated in Gochang, South Korea, was used for the multistep solvent extraction. Fresh black raspberries were freeze-dried and kept in a deep freezer (−80 °C) before use. LPS, cyanidin, cyanidin 3-glucoside chloride, and cyanidin 3-rutinoside chloride were obtained from Sigma-Aldrich Corp. (St. Louis, MO, USA). Ethyl acetate was purchased from DUKSAN (Ansan, South Korea), methanol from SAMCHUN (Pyung-Taek, South Korea), acetonitrile from J. T. Baker (Phillipsburg, NJ, USA), and formic acid from Sigma-Aldrich Corp. Extraction of Polyphenol Compounds from Black Raspberry. Polyphenols from black raspberry were extracted by multistep solvent extraction method with ethyl acetate and methanol as described previously.16,19 Black raspberry (2.5 g) was extracted with ethyl acetate (10 mL) for 30 min at room temperature, and the supernatant was evaporated and resuspended with methanol (BF1). The residue was acidified with HCl (2 M, 1 mL) and then extracted with methanol (BF2), and another supernatant portion was hydrolyzed with HCl in MeOH (0.6 M, 5 mL) for 20 h at 60 °C (BF3) and analyzed by LC-MS/MS. Subfractionation of BF3 Using Preparative LC. BF3 was further fractionated using preparative liquid chromatography (LCforte/R, YMC, Kyoto, Japan). Separation was carried out using YMCDispoPack AT ODS (40 g, 25 μm) (YMC). The solvent system was consisted of a gradient mobile phase from 100% B in 3 min, from 100 to 0% in 24 min, held at 0% over 3 min, and finished at 30 min, where solvent A was 0.1% formic acid in water and solvent B was 0.1% formic acid in methanol. The flow rate was set at 25 mL/min, and UV spectra were measured at 280, 360, and 400 nm. The BF3 was separated into three subfractions according to peak shape, which was detected at 280 nm (Figure 2A). Metabolite Profiling Using LC-MS/MS Analysis. Profiling of the metabolites in each fraction or the extracts was conducted using a LC-MS/MS system consisting of an Accela HPLC system with a PDA detector (Accela 80 Hz PDA detector, Thermo Fisher Scientific, San Jose, CA, USA) and an LTQ-Velos ion trap mass spectrometer fitted with a heat electrospray ionization interface (Thermo Fisher Scientific).16 Separation was carried out using a UPLC BEH C18 column (1.7 um, 100 × 2.1 mm i.d., Acquity, Waters, Milford, MA, USA) at 35 °C. Solvent A was 0.1% formic acid in water, and solvent B was 0.1% formic acid in acetonitrile. The solvent system consisted of a B
DOI: 10.1021/acs.jafc.5b00560 J. Agric. Food Chem. XXXX, XXX, XXX−XXX
Article
Journal of Agricultural and Food Chemistry
Figure 1. Anti-inflammatory effect of Korean black raspberry fractions in LPS-induced RAW264.7 cells. (A) PCA score plot for the metabolites in each fraction. Fractionation of extract was performed by using multistep solvent extraction and PCA score plot for classifying the distinctive metabolites in extract fractions (1, BF1; 2, BF2; 3, BF3) analyzed by LC-ESI-ion trap MS/MS in positive and negative ion mode. (B) Comparison of anti-inflammatory effects of each fraction. The cells (8 × 105 cells/well in 60 mm dish) were treated with black raspberry fractions (300 μg/mL) together with LPS (100 ng/mL) for 15 h. The protein expression levels of iNOS and COX2 were determined by Western blotting and normalized with β-actin. (C) Anti-inflammatory effect of BF3. The cells (8 × 105 cells/well in 60 mm dish) were treated with BF3 (30, 50, 100, 300 μg/mL) together with LPS (100 ng/mL) for 15 h. iNOS and COX2 protein expression were determined by Western blotting and normalized with β-actin. (D) Effect of BF3 on cell viability. The cells (1 × 104 cells/well in a 96-well plate) were treated with BF3 at the indicated concentrations for 24 h, and cell viability was assessed by MTT assay. Statistical significance was determined by one-way ANOVA with the Duncan test, and differences are indicated with different letters (p < 0.05). width, 0.02 Da; frame time width, 2.5 min. Noise filtering, peak detection, isotope peak removal, alignment of retention time and mass, and peak normalization were conducted. Multivariate statistical analyses, including principal component analysis (PCA) and orthogonal partial least-squares discriminant analysis (OPLS-DA), were performed using SIMCA software (Umetrics, Umea, Sweden). The data sets were mean-centered and pareto-scaled before analysis. For analyzing the data from MTT, Western blot, quantitative RT-PCR, and ELISA assays, one-way ANOVA with Duncan’s test was used, and differences were considered statistically significant at p < 0.05.
was sufficient for further fragmentation into MS2 and MS3 analysis for the tentative identification of each metabolite. Black Raspberry Fraction 1 (BF1). BF1, as ethyl acetate extract, contained p-coumaroyl hexose, (epi)catechin-(epi)catechin, quercetin 3-O-rutinoside, quercetin 3-O-glucuronide, ellagic acid hexose, kaempferol-deoxyhexose, luteolin 7-glucoside, vanilloyl hexose, myricetin hexose, and hibiscetin tetramethyl ether in positive ion mode. Catechin, ellagic acid, methyl ellagic acid pentose, ellagitannin derivatives, pcoumaroylhexose, quercetin, quercetin, quercetin 3-glucoside, quercetin 3-O-glucuronide, proanthocyanidin B2 (EC-4,8-C), HHDP-galloyl-glucose, dihydroxybenzoic acid, and hydroxybenzoyl hexose were identified in negative ion mode. Black Raspberry Fraction 2 (BF2). BF2, as a simple methanol extract, cyanidin 3-glucoside, cyanidin 3-rutinoside, cyanidin 3-sambubioside, cyanidin 3-xylosylrutinoside, (+)catechin, p-coumaroyl hexose, quercetin 3-O-glucuronide, quercetin, and pelargonidin 3-rutinoside were identified in positive ion mode. Ellagic acid, ellagic acid-pentose conjugate, quercetin, quercetin glucoside, quercetin 3-O-glucuronide, quercetin 3-rutinoside, cyanidin 3-glucoside, malvidin 3-Oglucoside, pelargonidin 3-O-rutinoside, peonidin glucoside,
■
RESULTS Metabolite Profiling in Fractionated Black Raspberry by LC-ESI-Ion Trap-MS/MS. Black raspberry metabolites were fractionated into three groups (BF1, BF2, BF3) through ethyl acetate and methanol extraction as described under Materials and Methods. PCA clearly indicated that the metabolites in different fractions were separated into different groups as shown in Figure 1A. Differences were mainly contributed by principal component 1 in both negative and positive ion modes. The metabolites in each fraction were analyzed using LC-ESI-MS/MS and summarized (see Supporting Information Table 1). The abundance of all molecular ions C
DOI: 10.1021/acs.jafc.5b00560 J. Agric. Food Chem. XXXX, XXX, XXX−XXX
Article
Journal of Agricultural and Food Chemistry
Figure 2. PCA for the metabolites in subfractions of Korean black raspberry extract 3 (BF3). (A) HPLC chromatogram of BF3 by preparative HPLC. BF3 was fractionated into three subfractions (at 280 nm): BF3-1, 2.00−6.84 min; BF3-2, 6.84−10.67 min; BF3-3, 10.67−15.45 min. (B) PCA score plot of Korean black raspberry subfractions analyzed by LC-ESI-ion trap MS/MS in positive (left) and negative ion mode (right).
not affect the cell viability up to 1000 μg/mL, indicating that iNOS inhibition is not derived from the cellular cytotoxicity in the macrophage cells (Figure 1D). On the basis of these results, we chose BF3 for further studies of subfractionation and identification of active metabolites. Metabolite Phenotyping of Black Raspberry Subfractions. Through prep-LC, BF3 metabolites were fractionated into three subfractions, and then their metabolites were analyzed by LC-ESI-ion trap-MS/MS. PCA indicated that metabolites in subfractions were classified into different groups. In positive ion mode, principal component 1 (explaining 52.1% of the total variance) discriminated the metabolite profiles of subfractions, whereas principal component 2 explained 25.3% of total variance (Figure 2B). In negative ion mode, metabolites in subfractions were discriminated by principal component 1 (explaining 62.2% of total variance), and principal component 2 explained 18.6% of total variance (Figure 2B). The PCA score plots demonstrated the distinctive metabolite phenotypes of subfractions. The metabolites in each subfractions were analyzed using LC-ESI-ion trap-MS/MS and are summarized in the Supporting Information (Table 2). By comparison of retention time and MSn spectra in positive mode, cyanidin 3glucoside, cyanidin 3-rutinoside, and cyanidin were identified in BF3-1. Cyanidin 3-glucoside, cyanidin 3-rutioside, pelargonidin 3-rutinoside, quercetin-3-rutinoside, and cyanidin 3-xylosylrutinoside were identified in BF3-3. Cyanidin 3-glucoside, cyanidin 3-rutinoside, cyanidin, and ellagic acid were also identified in BF3-1 in negative mode, and ellagic acid and quercetin were
HHDP-galloyl-glucose, ellagitannin derivatives, galloyl bisHHDP-glucoside, p-coumaroyl hexose, and citric acid were found in negative mode. Black Raspberry Fraction 3 (BF3). BF3, as the acidic hydrolysate of BF2, cyanidin, cyanidin 3-glucoside, cyanidin 3rutinoside, cyanidin 3-sambubioside, pelargonidin 3-malonylglucoside, pelargonidin 3-rutinoside, and quercetin were found in positive ion mode, whereas cyanidin, cyanidin 3-glucoside, cyanidin 3-rutinoside, isorhamnetin 3-glucuronide, pelargonidin 3-rutinoside, ellagic acid, HHDP-galloyl-glucose, ellagitannin derivatives, kaempferol, and quercetin were identified in negative ion mode. Black Raspberry Fractions Inhibited LPS-Induced Inflammation in Murine Macrophage Cells. To investigate the effect of black raspberry fractions on regulating inflammation, murine macrophage RAW264.7 cells were treated with extracted fractions (BF1-BF3) at 300 μg/mL concentration, and the protein expression of well-known inflammatory markers iNOS and COX-2 was determined. As shown in Figure 1B, BF3 exerted the most significant inhibition on iNOS expression, followed by BF1, and BF2 did not show suppressive activity. BF3 also reduced the expression of COX-2, but the effect was marginal (Figure 1B). To evaluate the dose dependency of the most potent fraction, RAW264.7 cells were treated with BF3 at different concentrations (30, 50, 100, 300 μg/mL), and we found that BF3 significantly suppressed iNOS expression from 100 μg/mL concentration, with a slight inhibition on COX-2 (Figure 1C). In the MTT assay, BF3 did D
DOI: 10.1021/acs.jafc.5b00560 J. Agric. Food Chem. XXXX, XXX, XXX−XXX
Article
Journal of Agricultural and Food Chemistry
Figure 3. Anti-inflammatory effect of subfractions of BF3 in LPS-induced RAW264.7 cells. (A) Comparison of anti-inflammatory effects of each subfraction. The cells (8 × 105 cells/well in 60 mm dish) were treated with black raspberry subfractions (BF3-1, BF3-2, BF3-3; 100 μg/mL) together with LPS (100 ng/mL) for 15 h. The levels of iNOS and COX2 protein expression were determined by Western blotting and normalized with βactin. (B) Anti-inflammatory effect of BF3-1. The cells (8 × 105 cells/well in 60 mm dish) were treated with BF3-1 (30, 50, 100, 300, 500 μg/mL) with LPS (100 ng/mL) for 15 h, and iNOS and COX2 protein expressions were determined by Western blotting and normalized with β-actin. (C) Effect of BF3-1 on cell viability. The cells (1× 104 cells/well in a 96-well plate) were treated with BF3-1 at the indicated concentrations for 24 h, and cell viability was determined by MTT assay. Statistical significance was determined by one-way ANOVA with Duncan’s test, and differences are indicated with different letters (p < 0.05).
Figure 4. Analysis for the key compounds in BF3-1. (A) S-plot generated by OPLS-DA for the metabolite in BF3-1 and BF3-2 in positive (left) and negative ion mode (right). (B) Quantification of cyanidin, cyanidin 3-glucoside, and cyanidin 3-rutinoside in BF3-1 by HPLC.
phage Cells. Here, we evaluated the regulatory effects of BF3 subfractions on inflammatory markers iNOS and COX-2 in LPS-induced RAW264.7 macrophage cells. As shown in Figure 3A, BF3-1 (100 μg/mL) strongly inhibited the expression of iNOS induced by LPS treatment, but BF3-2 and BF3-3 exerted
identified in BF3-2 in negative ion mode. Cyanidin 3-glucoside, cyanidin-3-rutinoside, and quercetin-3-rutinoside were found in BF3-3 under negative ion mode of analysis. Subfractions of BF3 Exerted More Active Efficacy in Regulating Inflammatory Markers in Murine MacroE
DOI: 10.1021/acs.jafc.5b00560 J. Agric. Food Chem. XXXX, XXX, XXX−XXX
Article
Journal of Agricultural and Food Chemistry
Figure 5. Anti-inflammatory mechanisms of BF3-1 and corresponding key constituents in LPS-induced RAW264.7 cells. (A) The cells (8 × 105 cells/well in 60 mm dish) were treated with the key compounds (cyanidin, C3G, C3R) or BF3-1 (100, 300, 500 μg/mL) with LPS (100 ng/mL) for 15 h. X1 represents 0.15 μM cyanidin, 0.26 μM C3G, and 0.09 μM C3R, respectively, and X3 and X5 represent levels 3 and 5 times higher than X1. The protein expression levels of iNOS and COX2 were determined by Western blotting and normalized with β-actin. (B) The cells (8 × 105 cells/ well in 60 mm dish) were treated with cyanidin alone (X1 and X5) and cyanidin mixture (X1, X3, X5) for 15 h. The expression level of iNOS was determined by Western blotting and normalized with β-actin. (C) The cells (8 × 105 cells/well in 60 mm dish) were treated with the key compounds (cyanidin, C3G, C3R) and BF3-1 (100, 300, 500 μg/mL) with LPS (100 ng/mL) for 15 min. The levels of LPS-induced phosphorylation of MAPKs and STAT3 and IκBα degradation were assessed by Western blotting and normalized with β-actin. Statistical significance was determined by one-way ANOVA with Duncan’s test, and differences are indicated with different letters (p < 0.05).
plot. The variables on the top indicated metabolites in BF3-2, and the ones on the bottom indicated metabolites in BF3-1 in positive and negative ion modes as described in Figure 4A. Cyanidin, cyanidin 3-glucoside (C3G), and cyanidin 3-rutinoside (C3R) were identified as significant variables (p < 0.05) specifically found in BF3-1 compared to BF3-2 with regulatory activity on iNOS and COX-2 expression as denoted in Figure 4A. Quantitative analysis on these key molecules revealed that cyanidin, C3G, and C3R were contained in BF3-1 at 0.44, 1.26, and 0.56 μg/mg, respectively (Figure 4B). The critical difference of these compounds in BF3-1 may influence the
only slight suppression of iNOS and COX-2. In a concentration dependency test, BF3-1 showed inhibitory efficacy of iNOS from 50 μg/mL and of COX-2 from 300 μg/mL without affecting the cellular viability (Figure 3B,C), suggesting that BF3-1 black raspberry fraction may contain the key components responsible for anti-inflammatory activity. Screening of Anti-inflammatory Metabolites in BF3-1 and BF3-2 by LC-ESI-Ion Trap MS/MS. All data sets of metabolite profiles of BF3-1 and BF3-2 were analyzed by OLPS-DA. The S-plot visualized the variables that differentiated most in uncoordinated way at the top or bottom in the F
DOI: 10.1021/acs.jafc.5b00560 J. Agric. Food Chem. XXXX, XXX, XXX−XXX
Article
Journal of Agricultural and Food Chemistry
Figure 6. Effect of BF3-1 and key constituents on mRNA and protein expression of cytokines in LPS-induced RAW264.7 cells. The cells (8 × 105 cells/well in 60 mm dish) were treated with the key compounds (cyanidin, C3G, C3R) and BF3-1 (100, 300, 500 μg/mL) with LPS (100 ng/mL) for 15 h. (A) The mRNA levels of cytokines were measured by quantitative RT-PCR. (B) The released cytokine levels in media were measured by ELISA. Statistical significance was determined by one-way ANOVA with Duncan’s test, and differences are indicated with different letters (p < 0.05).
different anti-inflammatory patterns of BF3-1 and BF3-2 as indicated in Figure 3A. BF3-1 and Cyanidin Mixture Commonly Suppressed the Inflammatory Markers and Regulated the Same Intracellular Signaling Mediators in Murine Macrophage Cells. Here, we compared the anti-inflammatory activity between the BF3-1 fraction and the cyanidin mixture of the key components, cyanidin, C3G, and C3R, in LPS-induced RAW264.7 cells. On the basis of the quantifications of key components in BF3-1, the actual amounts of cyanidin, C3G, and C3R in BF3-1 at 100 μg/mL were determined as 0.044 μg/ mL (∼0.15 μM), 0.126 μg/mL (∼0.26 μM), and 0.056 μg/mL (∼0.09 μM), respectively, which was described as X1 (Figure 5). X3 and X5 represent 3 and 5 times higher amounts of each constituent relative to X1, which are the same amounts present in 300 and 500 μg/mL of BF3-1, respectively. As shown in Figure 5A, the BF3-1 fraction exerted dose-dependent suppression of iNOS expression, and the cyanidin mixture also showed similar activity, although COX-2 inhibition is more significant in BF3-1. In addition, single treatment of cyanidin at the concentrations of X1 (0.044 μg/mL) and X5 (0.22 μg/mL) suppressed LPS-induced iNOS expression only up to 12.8 and 34.7%, respectively, but the treatment of cyanidin mixture exerted iNOS inhibitory activity up to 16.6% and 98.3% (Figure 5B). These results suggest that the regulatory efficacy on iNOS expression by BF3-1 fraction might be derived from the coexistence of cyanidin, C3G, and C3R. To determine whether BF3-1 and the cyanidin mixture share the upstream inflammatory signaling molecules, we tested the expression of inhibitory κB (IκB) and phosphorylation of mitogen-activated protein kinases (MAPKs) and found that the phosphorylations of extracellular signal-related kinase (ERK), c-Jun N-terminal kinase (JNK), and p38 induced by LPS treatment were
significantly blocked by both the BF3-1 fraction and cyanidin mixture in a dose-dependent manner (Figure 5B). Interestingly, however, BF3-1 and the cyanidin mixture did not recover the degraded IκB by LPS treatment, indicating that they regulated the LPS-induced inflammation independent of the nuclear factor κB (NF-κB) signaling pathway. BF3-1 and Cyanidin Mixture Inhibited Expression Level of the Same Cytokines in Murine Macrophage Cells Induced by LPS. Due to critical roles of cytokines during the inflammatory processes,20 we further investigated the roles of BF3-1 and cyanidin mixture in regulating the expression of well-known cytokines tumor necrosis factor-α (TNF-α), interleukin 1β (IL-1β), and interleukin 6 (IL-6) in RAW264.7 cells. In mRNA expression of cytokines determined by quantitative RT-PCR, both cyanidin mixture and BF3-1 reduced the level of those cytokines most significantly at X5 and 500 μg/mL (Figure 6A). In addition, the amount of the secreted cytokines at protein level was confirmed by ELISA, and it was found to be reduced by cyanidin mixture and BF3-1 treatment, where IL-1β was most strikingly suppressed (Figure 6B). Recently, it was reported that LPS increased the production of cytokines IL-6 and IL-1β through STAT3 activation in murine macrophage cells.21 Here, we also confirmed that BF3-1 and cyanidin mixture blocked the phosphorylation of STAT3 (Figure 5B), which may lead to reduced LPS-induced expression of IL-6 and IL-1β (Figure 6).
■
DISCUSSION Metabolomics is the useful analysis appropriate for profiling a whole set of metabolites and phenotyping the unique metabolome from complicated food and natural resources. This approach has been recently applied to elucidate the relationship between dietary sources and human chronic G
DOI: 10.1021/acs.jafc.5b00560 J. Agric. Food Chem. XXXX, XXX, XXX−XXX
Article
Journal of Agricultural and Food Chemistry
ERK, JNK, p38, and STAT3, resulting in reduction of both mRNA and protein expression of cytokines, TNF-α, IL-6, and IL-1β, in addition to iNOS suppression without cytotoxicity (Figures 5 and 6). The cyanidin mixture containing cyanidin, C3G, and C3R, identified by metabolomic screening and quantified by HPLC analsysis from BF3-1, was validated to have similar efficacy in regulating the inflammatory mediators at submicromolar concentrations (Figures 5 and 6), ascertaining that cyanidin, C3G, and C3R are the critical constituents in black raspberry fraction BF3-1. The NF-κB, activated by LPS, cytokines (IL-1β or TNF-α), or oxidative stress, is a well-known transcription factor regulating iNOS expression.37 Berry anthocyanins including cyanidin 3-glucoside have been reported to block the NF-κB activation induced by cytokines and UVB in different models.27,38,39 In this study, however, neither black raspberry extract (BF3-1) nor corresponding cyanidin mixture induced the recovery of IκB degradation (Figure 5B), which is one of the key events happening during activation of the NF-κB signaling pathway by LSP. This inconsistent result in regulating NF-κB signaling might be from the lower concentration of treated anthocyanins than in other studies. The concentration of the X3 mixture containing cyanidin, cyanidin-3-glucoside, and cyanidin-3-rutinoside in the present study was only 0.678 ug/mL (1.51 μM), whereas other studies used from 8.99 μg/ mL (20 μM) to 112.34 μg/mL (250 μM) of cyanidin-3glucoside.27,38,39 Instead, BF3-1 and the cyanidin mixture significantly suppressed LPS-induced MAPKs phosphorylation, which can lead to inhibition of the binding of activating protein-1 (AP-1) complex and iNOS expression.40 These findings suggest that coexistence of anthocyanins even at low concentrations (
