Polysaccharide from Seeds of Plantago asiatica L. Affects Lipid

Dec 16, 2013 - The obtained DGGE patterns were subsequently normalized and analyzed with Bio-Rad Quantity One 4.4.0 software. During the processing, t...
0 downloads 14 Views 3MB Size
Download PDF
Article pubs.acs.org/JAFC

Polysaccharide from Seeds of Plantago asiatica L. Affects Lipid Metabolism and Colon Microbiota of Mouse Jie-Lun Hu,†,§ Shao-Ping Nie,*,† Qi-Meng Wu,† Chang Li,† Zhi-Hong Fu,† Joshua Gong,†,§ Steve W. Cui,†,§ and Ming-Yong Xie† †

State Key Laboratory of Food Science and Technology, Nanchang University, Nanchang 330047, China Guelph Food Research Center, Agriculture and Agri-Food Canada, 93 Stone Road West, Guelph, Ontario N1G 5C9, Canada

§

S Supporting Information *

ABSTRACT: Polysaccharide from the seeds of Plantago asiatica L. was given via oral administration to mice (0.4 g/kg body weight, 30 days) to observe its effects on mouse nutrient metabolism and colon microbiota. It was found the polysaccharide intake could lower the apparent absorption of lipid. Total triglyceride, cholesterol, and atherogenic index in blood serum with total lipid and cholesterol levels in liver of polysaccharide group mice were all significantly lower than those of the control group (p < 0.05). Furthermore, the effect of the polysaccharide intake on mouse colon bacterial communities was investigated. Mice from the polysaccharide group showed a higher colon bacterial diversity than the control group. Bacteroides sp., Eubacterium sp., butyrate-producing bacteria Butyrivibrio sp., and probiotics Bifidobacterium bifidum, Lactobacillus fermentum, and Lactobacillus reuteri in mouse colon were all increased after polysaccharide intake. These indicated that the intake of polysaccharide from P. asiatica L. could be beneficial for lipid metabolism and colon microbiota. KEYWORDS: Plantago asiatica L., polysaccharide, lipid metabolism, colon microbiota

■

INTRODUCTION In recent years, the influence of polysaccharides on major nutrient (carbohydrate, protein, and lipid) metabolism has been of particular interest because major nutrient metabolism is related to many chronic diseases.1,2 In addition, the effects of polysaccharide on colon microbiota were also paid much attention because of its benefits for the colon health, which is of more and more concern nowadays.3 The gut microbiota in colon contact with its host takes part in a great number of metabolic processes.4 The supply of fermentable carbohydrate is an important factor limiting the growth of bacteria in colon and, as in other environments, bacteria that can transform the available substrates most rapidly will occur in the greatest numbers.5 Polysaccharides can be extracted from many kinds of herbal or plant materials. Some Plantago plants, such as Plantago afra L., Plantago psyllium L., Plantago ovata Forsk. (isabgul), Plantago indica L., and Plantago major L., are often used in traditional medicine throughout the world because the soluble fibers in their seeds are able to improve some intestinal functions.6 Our research group has recently isolated a pure and homogeneous polysaccharide from the seeds of Plantago asiatica L. with a molecular mass of 1894 kDa.7 The polysaccharide was found to be a highly branched heteroxylan, which consisted of a β-1,4-linked Xylp backbone with side chains attached to O-2 or O-3. The side chains consisted of βT-linked Xylp, α-T-linked Araf, α-T-linked GlcAp, β-Xylp-(1→ 3)-α-Araf, and α-Araf-(1→3)-β-Xylp, etc.8 In addition, our recent studies have also shown that this polysaccharide may induce maturation of murine dendrite cells, have antioxidant activity in vitro, promote mouse defecation, increase shortchain fatty acid (SCFA) production in mouse colon and in vitro © XXXX American Chemical Society

fermentation, and have some effects on intestinal function in vitro.9−14 However, the influence of the polysaccharide from P. asiatica L. on nutrient metabolism and colon microbiota in mouse has not been studied. In this study, the effect of the polysaccharide from P. asiatica L. on mouse nutrient metabolism was evaluated by determining the apparent absorption of major nutrients, blood serum ingredients, and liver lipid contents. Additionally, the effect of the polysaccharide on mouse colonic bacterial communities was investigated. Amplicons of the V3 variable regions of bacterial 16S rDNA were analyzed by denaturing gradient gel electrophoresis (DGGE), cloning, and sequencing. Furthermore, the relationship between lipid metabolism difference and bacterial community change of mouse after polysaccharide intake was also discussed.

■

MATERIALS AND METHODS

Materials and Animals. The seeds of P. asiatica L. were purchased from Ji’an, Jiangxi, China, and dried in the sun before use. All reagents used were of analytical grade and purchased from Shanghai Chemicals and Reagents Co. (Shanghai, China). Kunming mice, weighing 20.0 ± 2.0 g [grade II, certificate SCXK (gan) 2006-0001], were purchased from Jiangxi College of Traditional Chinese Medicine, Jiangxi Province, China. All animals used in this study were cared for in accordance with the Guidelines for the Care and Use of Laboratory Animals published by the U.S. National Institutes of Health (NIH Publication 85-23, 1996), and all procedures were

Received: September 12, 2013 Revised: December 4, 2013 Accepted: December 16, 2013

A

dx.doi.org/10.1021/jf4040942 | J. Agric. Food Chem. XXXX, XXX, XXX−XXX

Journal of Agricultural and Food Chemistry

Article

Measurement of the Apparent Absorption of Major Nutrients (Carbohydrate, Protein, and Lipid). The feeds and freeze-dried feces were crushed and measured for their carbohydrate, crude protein, and crude lipid.16 The carbohydrate content was determined colorimetrically: To an aliquot of the feed (200 mg) or feces (200 mg) was added 10 mL of a 0.2 M acetate buffer (pH 4.8) and 5 mL of a 0.12% glucoamylase solution (Biochemical Co., Shanghai, China). After the addition of distilled water to give 50 mL of the solution, a few drops of toluene were added, and the mixture was incubated at 37 °C for 24 h. After hydrolysis, the mixture was filtered, and an aliquot of the solution was used for determining the reducing sugar according to the method of Somoyi-Nelson, 0.9 being adopted as the conversion factor to carbohydrate. The crude protein content was determined by titration: An aliquot of the feed (200 mg) or feces (200 mg) was weighed and degraded by H2SO4. The nitrogen content was determined using the Kjeldahl method with a Kjeltec TM 8400 instrument (Foss, Denmark), 6.25 being adopted as the conversion factor to protein. The crude lipid content was determined gravimetrically according to the Soxhlet method, using an aliquot of the feed (200 mg) or feces (200 mg). The apparent absorption of major nutrients (carbohydrate, protein, and lipid) was calculated by using the following equation:

approved by the Animal Care Review Committee (Animal application approval 0064257), Nanchang University, China. Polysaccharide Preparation. Polysaccharide from P. asiatica L. seeds was prepared using our published method.7 Briefly, the seeds of P. asiatica L. (50 g) were defatted with 1 L of ethanol at room temperature for 24 h under stirring and then extracted with 500 mL of doubly distilled water at 100 °C for 2 h. The residue was re-extracted. The combined aqueous extract (a highly viscous gel) was centrifuged (4800g, 10 min) and prefiltered through a cotton cloth bag. After that, the filtrate was concentrated by a rotary evaporator under reduced pressure at 55 °C to yield P. asiatica L. water extract. The filtrate was mixed with 1.5 g/L papain and heated in water at 60 °C for 2 h. The resulting aqueous solution was extensively dialyzed against doubly distilled water for 72 h and precipitated by adding 4 volumes of anhydrous ethanol at 4 °C for 12 h. After centrifugation, the precipitate was washed with anhydrous ethanol, dissolved in water, and lyophilized to yield the polysaccharide. Animal Experiment Design. Male 6-week-old Kunming mice (20.0 ± 2.0 g) were individually housed in stainless steel cages in a room with controlled temperature (25 ± 0.5 °C), relative humidity (50 ± 5%), and a 12 h/12 h light/dark cycle. All mice were fed the same amount of basal diet (Table 1), which was prepared according to

apparent nutrient absorption (%)

Table 1. Composition of the Basal Diet for Mice component

g/kg dry weight (DW) basis

corn starch soybean meal sucrose corn oil cellulose gelatinized starch vitamin mixturea mineral mixtureb

454 240 100 60 50 10 10 76

= [(intake − excretion)/intake] × 100

(1)

Measurement of Blood Serum Ingredients and Liver Lipid Contents. Total serum protein, albumin, albumin/globulin ratio, glucose, urea nitrogen, creatinine, triglyceride, total cholesterol, highdensity lipoprotein (HDL)-cholesterol, low-density lipoprotein (LDL)-cholesterol, atherogenic index, glutamic oxalacetic transaminase activity (GOT), and glutamic pyruvic transaminase activity (GPT) were determined by using an Automatic Biochemical Analyzer (AU2700, Olympus, Hamburg, Germany). Freeze-dried livers were ground, and the lipids were extracted with chloroform/methanol (2:1, v/v).17 The total lipid content was quantified gravimetrically, and the total cholesterol and triglycerides were determined by using the Automatic Biochemical Analyzer, whereas phospholipid contents were determined colorimetrically with a determiner assay kit (Jinghao Medix Co., Beijing, China). Colon Content DNA Extraction and PCR Amplification. To describe bacterial diversity in the mouse colon tract, total DNA was isolated from colon content samples and used as a template for PCR amplification. Amplicons of the V3 regions of bacterial 16S rDNA were analyzed using the DGGE analysis method. Sample DNA extraction (200 mg of frozen colon content for every mouse) was performed by using a QIAamp DNA Stool Mini Kit (QIAGEN, Inc., Shanghai, China), according to the manufacturer’s instruction. For DGGE analysis, PCR amplifications with V3 region primers against the 16S rDNA were performed in a 25 μL (total volume) mixture containing 1.2 μL of forward primer with a GC-clamp [primer F338GC, sequence (5′−3′), CGCCCGCCGCGCGCGGCGGGCGGGGCGGGGGCACGGGGGGACTCCTACGGGAGGCAGCAG] and 1.2 μL pf reverse primer [primer R518, sequence (5′−3′), ATTACCGCGGCTGCTGG], 0.5μL of deoxynucleoside triphosphate at a concentration of 10 mM, 2.5 μL of PCR reaction buffer, 0.2 μL of DNA polymerase (5 U/μL), 1.0 μL of DMSO (4%, v/v), 1 μL of DNA template with an appropriate amount, and 17.4 μL of sterile water.18 PCR amplification was performed with a Biosci PCR system as follows: an initial denaturation of 94 °C for 4 min, followed by 30 cycles of 94 °C for 0.5 min, 56 °C for 0.5 min, and 72 °C for 1 min, and a final elongation at 72 °C for 10 min. Aliquots of 5 μL were analyzed by electrophoresis on an agarose gel (1%) to check the size and amounts of the amplicons. DGGE Profiling. DGGE was performed with the Bio-Rad DCodeTM system (Bio-Rad Ltd., Hercules, CA, USA). PCR products were loaded onto 1 mm thick 8% (w/v) polyacrylamide (acrylamide/ bisacrylamide = 37.5:1) gels containing a 35−65% linear denaturing gradient. TAE buffer (1×, 40 mM Tris-acetate, 1 mM Na-EDTA, pH 8.0) was used as the electrophoresis buffer. The electrophoresis was

a

Containing, in g/kg (DW basis): 0.25 (250000 IU) vitamin A; 0.002 (65000 IU) vitamin D3; 2 (2000 IU) vitamin E; 0.41 menadinoe; 0.07 folic acid; 1.25 niacin; 0.5 calcium pantothenate; 0.2 riboflavin; 0.25 thiamin; 0.5 pyridoxine; 0.003 cyanocobalamine; 0.025 biotin; 70.0 cholin chloride. bContaining, in g/kg (DW basis): 69.6 CaCO3; 313.1 C12H10Ca3·4H2O; 114.6 CaHPO4·2H2O; 222.2 K2HPO4·3H2O; 126.7 KCl; 78.3 NaCl; 38.9 MgCO3; 35.8 MgCO3; 0.204 MnSO4·H2O; 0.042 KI; 0.515NaF; 0.091 AlNH4(SO4)2·12H2O. the published formula,15 and water was provided ad libitum. All mice were randomly divided into two groups: (1, Polysaccharide group) Mice were orally administered polysaccharide at the dose of 0.4 g/kg body weight of mice. The dose for the polysaccharide administration was selected according to our previous research.11,12 (2, Control group) Mice were given distilled water of the same volume as the mean volume of the polysaccharide groups. Each group had 12 mice, and mice were housed individually. All of the mice were given oral administration of polysaccharide or water at about 9:00 a.m. every day for 30 days. In addition, we determined the body weight of each mouse every day before gavage and changed the volume of the polysaccharide to ensure that the mice were given polysaccharide at the dose of 0.4 g/kg body weight by gavage every day. Throughout the experiment, the animals’ general health status and body mass were observed twice daily. At the end of the designated experiment period, feces of the mice were collected individually and used to measure the apparent absorption of major nutrients (carbohydrate, protein, and fat). Blood was drawn from the eyes of the mice, and the serum was isolated by brief centrifugation of the whole blood. After that, the mice were sacrificed, and the liver and colon (with contents) were obtained. Then the colons were aseptically removed immediately and placed on an ice-cold plate and longitudinally opened, and the colon contents were collected. The feces, liver, and colon content were then kept at −20 °C for further analysis. B

dx.doi.org/10.1021/jf4040942 | J. Agric. Food Chem. XXXX, XXX, XXX−XXX

Journal of Agricultural and Food Chemistry

Article

group (87.4 ± 0.3%) for lipid apparent absorption. This observation suggested that the polysaccharide from P. asiatica L. may have had some influence on lowering the absorption of lipid, which was consistent with our previous finding that the polysaccharide from P. asiatica L. could inhibit some pancreatic lipase activity and reduce cholesterol available for absorption.13 The polysaccharide from P. asiatica L., which was found to promote mouse defection in our previous study, might also have some effect on promoting cholesterol and lipid excretion.11 In addition, the polysaccharide was found to increase the propionic acid production in mouse colon, which might influence the lipid metabolism.12 Furthermore, the polysaccharide from P. asiatica L. was found to bind bile acid in vitro,13 which may also affect the excretion and metabolism of cholesterol and lipid. Other studies showed that some other polysaccharides could enhance the excretion of lipids in feces,20 which was similar to our results. Effect of Polysaccharide on the Characteristics of Blood Serum and Liver Lipid Levels. The characteristics of the blood serum and the liver lipid levels in mice of the polysaccharide group or control group are given in Tables 3

initiated by prerunning for 5 min at a voltage of 220 V and subsequently run at a fixed voltage of 85 V for 16 h at 60 °C. The gel was stained with AgNO3 and developed after completion of electrophoresis. The obtained DGGE patterns were subsequently normalized and analyzed with Bio-Rad Quantity One 4.4.0 software. During the processing, the different lanes were defined, background was subtracted, differences in the intensity of the lanes were compensated during normalization, and the correlation matrix was calculated. Clustering was done with Pearson correlation and the unweighted pair group mean average (UPGMA) method. Identification of DGGE DNA Bands. The bands of interest were excised from the gel using a sterile blade and incubated overnight at 4 °C in Tris−EDTA buffer (pH 8.0) for future sequencing. PCR amplifications of the DNA fragments from the excised gel were carried out according to the same protocols described above with the corresponding primers [forward primer F338, sequence (5′−3′), ACTCCTACGGGAGGCAGCAG; reverse primer R518, sequence (5−3′), ATTACCGCGGCTGCTGG] and 1 μL aliquot of the gel elution.18 PCR products were excised from a 1.0% agarose gel and purified with a DNA Gel Extraction Kit (Tiangen, China). Isolation of DNA bands from the DGGE gel, cloning of excised bands, and sequence analysis were performed as described by Gong et al.19 The sequences were submitted to GenBank and the RDP database to determine their most related bacterium. The DNA sequences are available in the GenBank database with accession numbers. Statistical Analysis. All of the experiments were done in triplicate. Statistical analysis was carried out using SPSS (version 16.0, Chicago, IL, USA). The results were expressed as the mean ± standard deviation and compared using the Tukey test at a 5% confidence level. DGGE banding patterns in each group were digitalized by Quantity One software (Bio-Rad). The intensity and relative position of each DGGE band were determined manually with background subtraction. The intensity of each band was expressed as percentage of the integrated intensity of the entire lane. The matrix of intensity and relative position was analyzed by principal component analysis (PCA) using SPSS software.

Table 3. Effect of Polysaccharide from P. asiatica L. on Characteristic Blood Serum Chemistry of Micea glucose (mmol/L) total protein (g/L) albumin (g/L) albumin/globulin urea nitrogen (mmol/L) creatinine (μmol/L) triglyceride (mmol/L) total cholesterol (mmol/L) HDL-cholesterol (mmol/L) LDL-cholesterol (mmol/L) atherogenic indexb GOT (U/L)c GPT (U/L)d

■

RESULTS AND DISCUSSION General Health Status of Mice. Throughout the experiment period, no noticeable behavioral or activity changes were observed in the mice, and no treatment-related illness or death occurred. The growth of mice appeared normal throughout the experiment period, and no mouse experienced diarrhea or constipation. There was no observable difference in the animals’ body mass and hair luster between the polysaccharide-treated group and control group. Effect of Polysaccharide on Absorption of Major Nutrient of Mice. The apparent absorption of major nutrients (carbohydrate, protein, and lipid) is summarized in Table 2. Although the values for nutrient absorption were all nearly quantitative, there was a significant difference (p < 0.05) between the control group (94.8 ± 0.2%) and polysaccharide

carbohydrate lipid protein

99.9 ± 0.0 a 94.8 ± 0.2 a 99.9 ± 0.1 a

99.6 ± 0.3 a 87.4 ± 0.3 b 99.9 ± 0.1 a

6.56 ± 0.39 a 54.0 ± 1.1 a 31.6 ± 0.5 a 1.4 ± 0.1 a 9.4 ± 0.5 a 35 ± 3 a 1.25 ± 0.12 b 2.65 ± 0.28 b 2.34 ± 0.14 a 0.32 ± 0.09 a 0.17 ± 0.01 b 192 ± 29 a 134 ± 21 a

Each value is the mean ± standard deviation (n = 12); means in the same row not sharing a common letter are significantly different (p < 0.05). bAtherogenic index = (LDL-cholesterol)/(HDL-cholesterol). c GOT, glutamic oxalacetic transaminase activity. dGPT, glutamic pyruvic transaminase activity.

and 4, respectively. There was in general no marked difference in serum chemistry, apart from total triglyceride, total cholesterol, and atherogenic index (Table 3). Total triglyceride, total cholesterol, and atherogenic index in blood serum tended to be lower in the group of mice given oral administration of polysaccharide, with the difference between the control group Table 4. Effect of Polysaccharide from P. asiatica L. on Liver Lipid Levels in Micea

apparent absorption (%) polysaccharide group

polysaccharide group

a

Table 2. Effect of Polysaccharide from P. asiatica L. on Apparent Absorption of Carbohydrate, Protein, and Lipid in Micea control group

control group 6.72 ± 0.51 a 55.3 ± 1.1 a 31.3 ± 0.9 a 1.3 ± 0.1 a 9.5 ± 0.6 a 33 ± 2 a 1.90 ± 0.11 a 3.27 ± 0.26 a 2.62 ± 0.11 a 0.58 ± 0.14 a 0.22 ± 0.01 a 193 ± 21 a 132 ± 19 a

cholesterol (μmol/g of liver) triglyceride (μmol/g of liver) phospholipid (μmol/g of liver) total lipid (mg/g liver)

Each value is the mean ± standard deviation (n = 12); means in the same row not sharing a common letter are significantly different (p < 0.05).

control group

polysaccharide group

6.4 ± 0.4 a 33.5 ± 1.2 a 35.4 ± 2.2 a 49.6 ± 2.2 a

5.5 ± 0.2 b 32.9 ± 0.9 a 35.9 ± 1.8 a 44.6 ± 2.2 b

Each value is the mean ± standard deviation (n = 12); means in the same row not sharing a common letter are significantly different (p < 0.05).

a

a

C

dx.doi.org/10.1021/jf4040942 | J. Agric. Food Chem. XXXX, XXX, XXX−XXX

Journal of Agricultural and Food Chemistry

Article

Figure 1. Microbiota analysis for the colon content in mice from polysaccharide group and control group: (A) denaturing gradient gel electrophoresis (DGGE) of V3 regions of bacterial 16S rDNA amplifications; (B) UPGMA cluster analysis of DGGE bacterial profiles; (C) PCA scores plot of DGGE bacterial profiles. PC1, PC2, and PC3 represent principal factors and their probability (%) of influence on the bacterial profiles. C1−C5, colon content samples individually from five mice randomly chosen from the control group after 30 days of administration; P1−P5, colon content samples individually from five mice randomly chosen from the polysaccharide group after 30 days of administration.

Table 5. Diversity Indices Calculated from the DGGE Banding Profiles Generated from the V3 Region of Bacterial 16S rDNA treatment

richness (S)

control group polysaccharide group

24.60 ± 3.05 a 30.80 ± 3.96 b

c

H′a

H′maxb

evenness (E)

3.02 ± 0.13 a 3.34 ± 0.14 b

3.10 ± 0.12 a 3.42 ± 0.13 b

0.97 ± 0.01 a 0.98 ± 0.01 a

a H′, Shannon−Wiener index. bH′max, maximum Shannon−Wiener index. cValues are mean of three determinations ± standard deviation. Different letters indicate significant difference (p < 0.05) from each other in the same column.

the serum and liver cholesterol levels (Tables 3 and 4, p < 0.05). Although cholesterol was also accumulated in the liver, the liver cholesterol level was significantly reduced by the polysaccharide intake. This may be because except for the polysaccharide itself, the organic acids, particularly propionate, that are produced by colonic fermentation could also influence the liver cholesterol metabolism.23 The polysaccharide from P. asiatica L. was found to increase the propionic acid production of mouse colon in our previous study.12 Thus, the effect of the polysaccharide on lowering the liver cholesterol level may be stronger than its effect on lowering the liver triglyceride level. Effect of Polysaccharide on Mice Colon Microbiota. Diversity indices for the DGGE bacterial profiles (Figure 1A) generated from the 16S rDNA V3 region are shown in Table 5. The richness of the DGGE banding profiles for the polysaccharide group (30.80 ± 3.96) was significantly higher than for the control group (24.60 ± 3.05, p < 0.05) after 30 days of administration. In addition, a significant increase was also observed in the Shannon−Wiener index and maximum Shannon−Wiener index for the polysaccharide group relative to the control group (p < 0.05). There was no significant difference for the evenness between the polysaccharide group and control group (p > 0.05). The effect of polysaccharide on the bacterial communities after 30 days of oral administration was investigated by PCR-

and the polysaccharide group being significant (p < 0.05). Studies have shown that an elevation of serum lipids, especially cholesterol, is one of the most important risk factors leading to coronary heart disease.21 Thus, the cholesterol-lowering effect of the polysaccharide from P. asiatica L. was beneficial for health. A difference in liver lipid levels was apparent for cholesterol and total lipid (Table 4). The liver cholesterol and total lipid level in mice given oral administration of polysaccharide were both significantly lower (p < 0.05) than that of the control group. Thus, the polysaccharide from P. asiatica L. appears to play a role in lowering the liver cholesterol level. Some other studies also indicated that polysaccharides present in some food materials could reduce the cholesterol in serum and lipid in liver,22 which was similar to our results. In contrast to liver cholesterol level, the liver triglyceride level in mice was not significantly decreased after polysaccharide administration for 30 days (Table 4, p > 0.05). We have observed that the polysaccharide intake could significantly lower the serum triglyceride level of mice (Table 3, p < 0.05). The influence of the polysaccharide on serum triglyceride level may be faster than its effect on liver triglyceride level because the triglyceride was accumulated in liver and the reducing effect by polysaccharide intake may need more time. However, for cholesterol, the polysaccharide could significantly reduce both D

dx.doi.org/10.1021/jf4040942 | J. Agric. Food Chem. XXXX, XXX, XXX−XXX

Journal of Agricultural and Food Chemistry

Article

bacteria (bands 9−12) were Bacteroides sp. Bacteroidetes can degrade polysaccharides and metabolic intermediates. They were also able to produce SCFAs such as acetate, lactate, propionate, and others.24 Band 1 was closest to butyrateproducing bacteria and affiliated with the family of Butyrivibrio. A few species-related bands, 5, 6, and 8, had a closer relationship with probiotics Bif idobacterium bif idum, Lactobacillus fermentum, and Lactobacillus reuteri, respectively. These putative butyrate-producing bacteria or probiotics were observed to increase after polysaccharide intake in this study, similar to these bacteria reported to utilize fibers previously.25 Bands 3 and 4 were sequenced and identified as belonging to Eubacterium sp., which were reported to be very active fermentation bacteria for fiber.26 Bands 2, 7, 13, and 14 were sequenced as well (Figure 1A), which had higher peak density in the control group than in the polysaccharide-treated groups. The sequencing results showed that their most related bacteria were Clostridiales sp. and Helicobacter sp., which are the common commensal bacteria in the colon and not good for health in a large amount.18 These sequencing results indicated that polysaccharide treatment could decrease Clostridiales sp. and Helicobacter sp. in the mouse colon microbiota. On the basis of the banding patterns (Figure 1A) and sequencing results (Table 6), it can be inferred that orally administered polysaccharide could substantially affect the mouse colon microbiota. In addition, some other papers have indicated that the predominant increased species in colon microbiota belong to the genera Bacteroides, Eubacterium, and Bif idobacterium after the supply of fermentable carbohydrates. Many other bacteria also occur in high numbers, including Lactobacilli and various anaerobic Gram-positive cocci.27 Their results were similar to ours. It was reported that there were some relationships between lipid metabolism difference and bacterial community change. The intestinal microbiota develops an important biochemical activity within the host body by providing additional metabolic functions. Specific components of the commensal microbiota also regulate serum lipids and cholesterol by taking part in metabolism.28 Some intestinal bacteria could influence lipid metabolism. Butyrivibrio proteoclasticus, a butyrate-producing ruminal bacterium, could have some effects on cholesterol and lipid utilization.29 Lactic acid bacteria and Bif idobacteria could remove cholesterol or carry out cholesterol assimilation. For example, Lactobacillus fermentum was reported to reduce serum lipids and cholesterol in subjects.30 Low lipid level was associated with higher Bifidobacterium numbers in cecal content in mice.31 Furthermore, Eubacterium rectale, Bacteroides thetaiotaomicrometer, and Bacteroides vulgatus were also found to be cholesterol-reducing bacteria.32 Thus, the Bacteroides sp., Eubacterium sp., Butyrivibrio proteoclasticus, Bifidobacterium bifidum, Lactobacillus fermentum, and Lactobacillus reuteri, which were found increased in mouse colon after the intake of polysaccharide P. asiatica L., may have some effect on the mouse lipid metabolism in this study. In addition, some probiotics-related metabolites might also exert beneficial effects on cholesterol and lipid metabolism. Propionic acid was reported to affect the liver cholesterol metabolism.23 The polysaccharide from P. asiatica L. was found to increase the propionic acid production in mice colon in a previous study,12 which might influence the lipid metabolism. Bile acid was found to be closely related to cholesterol and lipid metabolism; thus, the polysaccharide from P. asiatica L., which

DGGE bacterial profiling and identification of putative bacterial species through sequence analysis of recovered DGGE DNA bands. To compare the predominant bacterial communities between different treatments, PCR amplification of the V3 region of the 16S rRNA gene was carried out with corresponding primers. DGGE banding patterns of the V3 region of colon content of each group are shown in Figure 1A. The influence of polysaccharide intake on bacterial community structure was investigated. DGGE image analysis showed that the bacterial community structure from the colon content samples of the polysaccharide group was similar (Figure 1A) and also grouped together in the UPGMA cluster analysis (Figure 1B). In addition, it could also be seen that the bacterial community structure of colon content from polysaccharide group mice was low in similarity with the control group, which means the influence of polysaccharide intake appeared to be a major factor affecting the community. Furthermore, the PCA scores plot (Figure 1C) was also used to compare the differences between banding patterns of different treatments. In the PCA scores plot, “sit together” demonstrates similarity between samples. As shown in Figure 1C, the banding pattern of the control group was different from that of the polysaccharide group. Because banding patterns were related to the bacterial communities, the above results suggest that the predominant bacterial communities in the colon content of polysaccharide group mice were different from those of the control group mice. Several numerically dominant bacterial species in the colon content for the polysaccharide group corresponding to the presence of some intense DGGE DNA bands, which were different from the control group, were observed (Figure 1A). To further clarify the differences, bands that showed different percentages of density among groups were sequenced for determining their putative identity of bacteria. The putative identity of bacteria is presented in Table 6, which may suggest their possible role in the utilization of the polysaccharide. As shown in Figure 1A and Table 6, 14 interesting excised bands were identified. Although bands 1, 3−6, and 8−12 have the same migration in different lanes, higher peak density of bands can be observed in the polysaccharide-treated group than in the control group (Figure 1A). Sequencing results showed that their most related Table 6. Band Identification for Searching the Bacterial Identity in Denaturing Gradient Gel Electrophoresis (DGGE) Using Bacterial V3 Primers strain

closest relative

similarity (%)

GenBank no.

1 2 3 4 5 6 7 8 9 10 11 12 13 14

Butyrivibrio proteoclasticus Clostridiales sp. Eubacterium rectale Eubacterium sp. Bifidobacterium bifidum Lactobacillus fermentum Helicobacter pylori Lactobacillus reuteri Bacteroides salanitronis Ruminococcus torques Bacteroides thetaiotaomicrometer Bacteroides vulgatus Clostridium clarif lavum Clostridium caenicola

96 97 100 98 95 98 96 100 100 99 99 95 98 99

U37378.1 AB781636.1 AB626630.1 AY169428.1 GU936674.1 JQ669802.1 JX455160.1 HQ615667.1 AB253731.1 NR_036777.1 NR_074277.1 HQ012024.1 NR_041235.1 NR_041311.1 E

dx.doi.org/10.1021/jf4040942 | J. Agric. Food Chem. XXXX, XXX, XXX−XXX

Journal of Agricultural and Food Chemistry

Article

was found to bind bile acid in vitro,13 might also affect cholesterol and lipid metabolism. Our results showed the effect of polysaccharide from P. asiatica L. on mouse lipid metabolism and colon microbiota for the first time. The intake of polysaccharide from P. asiatica L. could lower the apparent absorption of lipid and decrease the serum and liver lipid level in mice. Mice from the polysaccharide group showed a higher colon bacterial diversity than the control group. Bacteroides sp., Eubacterium sp., butyrate-producing bacteria Butyrivibrio sp., and probiotics Bifidobacterium bifidum, Lactobacillus fermentum, and Lactobacillus reuteri in mouse colon were all increased after mice were given oral administration of the polysaccharide. These suggested that the intake of polysaccharide from P. asiatica L. may be beneficial for lipid metabolism and colon microbiota. The changed colon bacteria may play a role in utilization of the polysaccharide and mouse lipid metabolism, which was also affected by polysaccharide intake.

■

(8) Yin, J.; Lin, H.; Li, J.; Wang, Y.; Cui, S. W.; Nie, S.; Xie, M. Carbohydr. Polym. 2012, 87, 2416−2424. (9) Huang, D. H.; Xie, M. Y.; Yin, J. Y.; Nie, S. P.; Tang, Y. F.; Zhou, C. J. Ethnopharmacol. 2009, 124, 493−498. (10) Tang, Y.; Huang, D.; Yin, J.; Zhou, C.; Xie, X.; Xie, M. Food Sci. 2007, 28, 517−520. (11) Wu, G.; Tian, Y.; Xie, M.; Li, C. Food Sci. 2007, 28, 514−516. (12) Hu, J. L.; Nie, S. P.; Min, F. F.; Xie, M. Y. J. Agric. Food Chem. 2012, 60, 11525−11532. (13) Hu, J. L.; Nie, S. P.; Li, C.; Xie, M. Y. Int. J. Biol. Macromol. 2013, 54, 264−269. (14) Hu, J. L.; Nie, S. P.; Li, C.; Fu, Z. H.; Xie, M. Y. J. Agric. Food Chem. 2013, 61, 6092−6101. (15) Adachi, T.; Ono, Y.; Koh, K. B.; Takashima, K.; Tainaka, H.; Matsuno, Y.; Nakagawa, S.; Todaka, E.; Sakurai, K.; Fukata, H. Food Chem. Toxicol. 2004, 42, 445−452. (16) Takahashi, T.; Maeda, H. Biosci., Biotechnol., Biochem. 1999, 63, 1340−1345. (17) Folch, J.; Lees, M.; Sloane-Stanley, G. J. Biol. Chem. 1957, 226, 497−509. (18) Muyzer, G.; De Waal, E. C.; Uitterlinden, A. G. Appl. Environ. Microbiol. 1993, 59, 695−700. (19) Gong, J.; Yu, H.; Liu, T.; Gill, J.; Chambers, J.; Wheatcroft, R.; Sabour, P. J. Appl. Microbiol. 2008, 104, 1372−1382. (20) Dall’Agnol, R.; Lino von Poser, G. J. Ethnopharmacol. 2000, 71, 337−341. (21) Kannel, W. B.; Castelli, W. P.; Gordon, T. Ann. Intern. Med. 1979, 90, 969−975. (22) Gallaher, C. M.; Munion, J.; Hesslink, J. R.; Wise, J.; Gallaher, D. D. J. Nutr. 2000, 130, 2753−2759. (23) Nishimura, N.; Nishikawa, H.; Kiriyama, S. J. Nutr. 1993, 123, 1260−1269. (24) Duncan, S.; Louis, P.; Flint, H. Lett. Appl. Microbiol. 2007, 44, 343−350. (25) Crittenden, R.; Karppinen, S. J. Sci. Food Agric. 2002, 82, 781− 789. (26) Varel, V. H.; Yen, J. T. J. Anim. Sci. 1997, 75, 2715−2722. (27) Finegold, S. M.; Attebery, H. R.; Sutter, V. L. Am. J. Clin. Nutr. 1974, 27, 1456−1469. (28) Gill, S. R.; Pop, M.; DeBoy, R. T.; Eckburg, P. B.; Turnbaugh, P. J.; Samuel, B. S.; Gordon, J. I.; Relman, D. A.; Fraser-Liggett, C. M.; Nelson, K. E. Science 2006, 312, 1355−1359. (29) Moon, C. D.; Pacheco, D. M. Int. J. Syst. Evol. Microbiol. 2008, 58, 2041−2045. (30) Simons, L. A.; Amansec, S. G. Nutr. Metab. Cardiovasc. 2006, 16, 531−535. (31) Cani, P. D.; Amar, J.; Iglesias, M. A.; Poggi, M.; Knauf, C.; Bastelica, D.; Neyrinck, A. M.; Fava, F.; Tuohy, K. M.; Chabo, C. Diabetes 2007, 56, 1761−1772. (32) Sadzikowski, M.; Sperry, J.; Wilkins, T. Appl. Environ. Microbiol. 1977, 34, 355−362.

ASSOCIATED CONTENT

S Supporting Information *

Structure of the polysaccharide from the seeds of P. asiatica L. This material is available free of charge via the Internet at http://pubs.acs.org.

■

AUTHOR INFORMATION

Corresponding Author

*(S.-P.N.) Phone/fax: +86-791-88304452. E-mail: spnie@ncu. edu.cn. Funding

This study is financially supported by the Key Program of the National Natural Science Foundation of China (31130041), the National Key Technology R&D Program of China (2012BAD33B06), the National Natural Science Foundation of China (20802032 and 21062012), the Program for New Century Excellent Talents in University (NCET-12-0749), and Research Projects of the State Key Laboratory of Food Science and Technology (SKLF-ZZA-201301 and SKLF-KF-201202), which are gratefully acknowledged. Notes

The authors declare no competing financial interest.

■

ABBREVIATIONS USED HDL, high-density lipoprotein; LDL, low-density lipoprotein; DGGE, denaturing gradient gel electrophoresis; PCA, principal component analysis; UPGMA, unweighted pair group mean average; SCFA, short-chain fatty acid

■

REFERENCES

(1) Neyrinck, A. M.; Possemiers, S.; Verstraete, W.; De Backer, F.; Cani, P. D.; Delzenne, N. M. J. Nutr. Biochem. 2012, 23, 51−59. (2) Gropper, S. S.; Smith, J. L. In Advanced Nutrition and Human Metabolism, 1st ed.; Wadsworth Publishing: New York, 2012. (3) Xu, X.; Xu, P.; Ma, C.; Tang, J.; Zhang, X. Biotechnol. Adv. 2012, 31, 318−337. (4) Topping, D. L.; Clifton, P. M. Physiol. Rev. 2001, 81, 1031−1064. (5) Cummings, J. H.; Macfarlane, G. T. J. Appl. Microbiol. 1991, 70, 443−459. (6) Mahady, G. B.; Fong, H. S.; Farnsworth, N. R. In WHO Monographs on Selected Medicinal Plants, 1st ed.; World Health Organisation: Geneva, Switzerland, 1999. (7) Yin, J. Y.; Nie, S. P.; Zhou, C.; Wan, Y.; Xie, M. Y. J. Sci. Food Agric. 2010, 90, 210−217. F

dx.doi.org/10.1021/jf4040942 | J. Agric. Food Chem. XXXX, XXX, XXX−XXX