Consumption of Black Legumes - ACS Publications - American

Article Cite This: J. Agric. Food Chem. XXXX, XXX, XXX−XXX

pubs.acs.org/JAFC

Consumption of Black Legumes Glycine soja and Glycine max Lowers Serum Lipids and Alters the Gut Microbiome Profile in Mice Fed a High-Fat Diet Changliang Jing,†,‡ Zhiguo Wen,†,§ Ping Zou,‡ Yuan Yuan,‡ Weiran Jing,∥ Yiqiang Li,*,‡ and Chengsheng Zhang*,‡

Downloaded via DURHAM UNIV on July 10, 2018 at 12:55:20 (UTC). See https://pubs.acs.org/sharingguidelines for options on how to legitimately share published articles.

‡

Marine Agriculture Research Center, Tobacco Research Institute of Chinese Academy of Agricultural Sciences, 11 Keyuanjingsi Road, Laoshan, Qingdao, Shandong 266101, People’s Republic of China § Feed Research Institute of Chinese Academy of Agricultural Science, Beijing 10010, People’s Republic of China ∥ Food Science and Engineering College, Qingdao Agricultural University, Qingdao, Shandong 266109, People’s Republic of China S Supporting Information *

ABSTRACT: This study investigated the potential health benefits of two different species of black legume [Glycine soja Sieb. et Zucc. and Glycine max (L.) Merr.] on diet-induced obesity. C57BL/6 mice were fed a high-fat diet (HFD) supplemented with 20% (w/w) black legume for 12 weeks, and the effects on weight gain, serum lipid levels, liver histology, gut fermentation, and microbiome profile were examined. Consumption of black legumes improved the blood lipid profile and increased fecal propionate and butyrate contents; this was accompanied by a reduction in hepatic steatosis and adipocyte size. High-throughput pyrosequencing of 16S rRNA revealed that black legumes prevented the loss of fecal microbiota diversity and richness caused by a HFD and decreased the relative abundance of Verrucomicrobia while increasing that of Bacteroidetes. Collectively, dietary supplementation with black legumes was found to have attenuated many of the adverse health consequences associated with a HFD and modulated gut microbiota in a positive way. KEYWORDS: Glycine soja Sieb. et Zucc., Glycine max (L.) Merr., serum lipids, short-chain fatty acid, fecal microbiota

■

INTRODUCTION Legumes are an important component of a healthy diet owing to their nutritional value (rich in proteins and carbohydrates and low in fat) and functional properties (foaming, emulsification, gelation, and water and oil absorption capacities).1 Consuming legumes has a range of health benefits in relation to chronic diseases, including cardiovascular disease, type 2 diabetes, and obesity.2,3 Different legume varieties have diverse colors, including yellow, green, red, and black seed coats. Black legumes have been widely consumed as food or as material for foods and are a part of the typical diet in Asian countries, such as China and Japan;4 additionally, they are used as a traditional medicine and health food in China for the prevention of diseases, such as atheroma, gastric ulcer, and enteritis.5 Recent studies have attributed the beneficial properties of black legumes to phytochemicals.6,7 Glycine soja Sieb. et Zucc. is a black legume that grows in harsh conditions in China’s Yellow River delta area and accumulates high levels of phytochemicals.8 High dietary intake of phytochemicals from legumes can reduce the risk of heart disease, stroke, and diabetes.9,10 Processing legumes prior to consumption can alter the content of bioactive compounds, thereby enhancing their nutritional quality.11 For instance, heat treatment can increase secondary metabolite conversion and has traditionally been used to improve the nutritional values of legumes.12,13 Roasting increased isoflavone levels in black and yellow soybeans14 as well as antioxidant activity in black soybean;15 © XXXX American Chemical Society

it was also found to reduce trypsin inhibitor activity while enhancing the flavor of the legume.16 Thus, in this study, we evaluated the black legume after roasting. Although the health benefits of many legumes, including chickpea, bean, and pea, have been demonstrated,17,18 the underlying mechanisms and effects of legumes on human microbiota still need to be explained. Legume consumption was shown to improve gut health by altering the gut microbiota profile and activity by means of non-digestible components, such as fiber, which can escape digestion in the upper gut and are fermented by gut microorganisms.19,20 Microbial metabolism of non-digestible legume components produces an array of gut-health-promoting metabolites, such as short-chain fatty acids (SCFAs, namely, acetate, propionate, and butyrate) and phenolic compounds.21 SCFAs have been implicated in the modulation of glucose and lipid metabolism,22,23 and changes in gut microbiota composition were found to be associated with lipid metabolic disorders.24 However, there have been no studies examining the effects of roasted black legumes on the gut microbiome and metabolic diseases. This was investigated in the present study by comparing the effects of dietary supplementation with two species of roasted Received: April 18, 2018 Revised: June 22, 2018 Accepted: June 25, 2018

A

DOI: 10.1021/acs.jafc.8b02016 J. Agric. Food Chem. XXXX, XXX, XXX−XXX

Article

Journal of Agricultural and Food Chemistry black legume on physiological, histological, and biochemical parameters and microbiome profiles of mice fed a high-fat diet (HFD) to evaluate the potential health benefits of consuming black legumes.

■

Table 1. Major Composition of Two Different Black Legumesa amount per 100 g G. soja

component protein (g) carbohydrate (g) dietary fiber fat (g) moisture (g)

MATERIALS AND METHODS

Diet Preparation. G. soja and Glycine max (L.) Merr. were harvested in Dongying, Shandong, China. The legumes were roasted and ground in a multidimensional swinging high-energy nanoball mill (YR-30, Yinrun Engineering Co., Jinan, China) to a superfine powder (80 μm) that was sealed in aluminum foil and maintained in a desiccator until use. The composition of the powder was analyzed prior to preparation of experimental diets. The protein, carbohydrate, dietary fiber, fat, and moisture contents were determined according to GB 5009.5-2010, GB/Z 21922-2008, GB/T 22224-2008, GB/T 147722008, and GB 5009.3-2010 methods, respectively. The legumes and experimental diets were sterilized by γ irradiation at 10 kGy. Qualitative and Quantitative Analyses of Polyphenol Compounds. Polyphenol compounds in the legume powder were identified by liquid chromatography electrospray ionization (ESI)− quadrupole time-of-flight tandem mass spectrometry (MS, Bruker Daltonic, Bremen, Germany) and high-performance liquid chromatography (HPLC, 2695, Waters Corp., Milford, MA, U.S.A.) via a dual ESI interface. HPLC separation was carried out on a C8 column (150 × 2.1 mm, 5 μm, Thermo Fisher Scientific, Waltham, MA, U.S.A.). Mobile phases were deionized water with 0.1% formic acid (A) and methanol with 0.1% formic acid (B). Solvent gradient: 0−5 min, 5% B; 5−10 min, 40% B; 10−35 min, 95% B; and 35−40 min, 5% B. The column was thermostatically controlled at 25 °C. The MS conditions have been previously reported,25 and the compounds were identified by a comparison to known standards. For quantitative analysis of daidzin, genistin, and glycitin, the ESI source was operated in the positive ion mode. Mobile phases were the same as above. For analysis of daidzein, genistein, and glycitein, the ESI source was operated in the negative ion multiple reaction monitoring mode. The mobile phase consisted of 0.01% formic acid in 5 mmol ammonium acetate (A) and methanol (B). The solvent gradient was as follows: 0 min, 5% B; 3−5 min, 22% B; 10 min, 42% B; 13 min, 47% B; 15 min, 100% B; 17 min, 100% B; 18 min, 5% B; and 25 min, 5% B. Full-scan mass spectral data: m/z 70−1000, dry gas flow of 6.0 L/min, and dry temperature of 350 °C. External standards were accurately weighed and dissolved in methanol at a concentration of 0.01−100 μg/mL to generate the calibration curves. Animals and Feeding Trial Experiment. Male C57BL/6J mice (7 weeks old, 18−20 g) were purchased from Shandong Experimental Animal Center (Jinan, China). After a 1 week acclimation period, the mice were randomly assigned to four dietary groups (six mice per cage, two cages per group) in a room at 25 ± 2 °C and 55 ± 5% relative humidity with controlled lighting (12:12 h light/dark cycle) and were fed the following diets: (1) normal chow (NCD, D1245B as the control, 10% energy derived from fat), (2) standard HFD (D12492, 60% energy derived from fat), (3) HFD with 20% G. soja powder (HFG), and (4) HFD with 20% G. max powder (HFB). HFG and HFB were isocaloric and isoproteic diets prepared by Biotech Co. (Beijing, China), with corn oil substituted for soybean oil. Diet composition is shown in Table 2. The 20% powder supplementation level was selected on the basis of previous studies26 and mimics the highest intake level of pulse consumers, which is approximately 295 g of pulses/day for an average of 2390 kcal/day diet. The mice had free access to food and water. Food intake and body weight were measured daily and weekly, respectively. Experimental procedures were performed according to the guidelines of the Ethics and Animal Welfare Committee of Shandong Academy of Medical Sciences (SCXK-20140007). Biochemical Analysis. After 11 weeks of dietary intervention, fresh feces were collected from each animal by abdominal massage under sterile conditions in the last week at the same time in the morning. A total of 0.2 g of sample was stored at −20 °C for determination of the SCFA content, and the same weight was set

35.9 19.5 21.9 8.4 9.8

± ± ± ± ±

G. max

0.25 0.02 b 0.01 a 0.09 b 0.02

35.1 23.3 19.0 15.9 9.9

± ± ± ± ±

0.14 0.05 a 0.09 b 0.07 a 0.03

a

Values in the same row with different letters are significantly different (p < 0.05).

Table 2. Composition of Experimental Diets HFDa b

ingredient (g)

NCD

HFD

HFG

HFB

casein, lactic powder L-cysteine DL-methionine corn starch maltodextrin sucrose cellulose corn oil lard mineral mix dicalcium phosphate calcium carbonate potassium citrate vitamix choline bitartrate blue dye total

18.96 0.00 0.28 0.00 29.86 3.32 33.17 4.74 2.37 1.90 0.95 1.23 0.52 1.56 0.95 0.19 0.00 100.00

25.84 0.00 0.40 0.00 0.00 16.15 8.89 6.46 3.23 31.66 1.29 1.68 0.71 2.13 1.29 0.26 0.01 100.00

18.66 20.00 0.40 0.65 0.00 12.25 7.14 0.32 1.55 31.66 1.29 1.68 0.71 2.13 1.29 0.26 0.01 100.00

18.62 20.00 0.40 0.65 0.00 11.49 6.80 2.97 0.05 31.66 1.29 1.68 0.71 2.13 1.29 0.26 0.01 100.00

a

D12492-modified high-fat diet with 60% calories from fat. All highfat diets (HFD, HFG, and HFB) are isocaloric and contained calories, 5.24 kcal/g; protein, 26.2%; fat, 34.9%; and carbohydrate, 26.3% (as g %). bNCD = 10% calories from fat and contained calories, 3.8 kcal/g; protein, 19%; fat, 4%; and carbohydrate, 67% (as g %). aside at −80 °C for DNA extraction. Mice were fasted overnight (12− 14 h), lightly anesthetized with ethyl ether, and then sacrificed by cervical dislocation at the end of 12 weeks. Blood samples were collected by cardiac puncture and separated at 3000 rpm for 10 min at 4 °C to obtain the serum. Serum glucose (Glu), triacylglycerol (TG), total cholesterol (TCHO), high-density lipoprotein cholesterol (HDL-c), and low-density lipoprotein cholesterol (LDL-c) levels were determined using commercially available enzyme assay kits (Nanjing Jiancheng Institute of Bioengineering, Nanjing, China) according to the instructions of the manufacturer. Each assay was performed at least 3 times. Histopathological Analysis. Liver and adipose tissues collected were fixed in 10% formalin to process for paraffin section. Histopathologic changes in the liver were evaluated by hematoxylin and eosin staining.27 Sections were examined under a light microscope (N-MSI-Vectra, PerkinElmer, Waltham, MA, U.S.A.) at 10× and 40× magnifications. Analysis of the Fecal SCFA Content. A 0.2 g portion of samples was mixed with 1000 μL of distilled water and adjusted to pH 2.0 using 50% sulfuric acid. The sample was centrifuged at 5000g for 10 min. A total of 2 mL of ether was added to the supernatant to extract SCFAs and then analyzed by HPLC (model 1100, Agilent Technologies, Santa Clara, CA, U.S.A.) with a diode array detector set at 210 nm.28 Chromatographic separation of each acid was carried B


Article

Journal of Agricultural and Food Chemistry

Table 3. Effect of Black Legume Supplementation on Body Weight, Weight Gain, Feeding, and Serum Parameters in Mice on a High-Fat Dieta parameter

NCD

initial BW (g) final BW (g) weight gain (g) feed intake (g/day) energy intake (kcal/day) serum parameters Glu (mmol/L) TG (mmol/L) TCHO (mmol/L) HDL-c (mmol/L) LDL-c (mmol/L)

HFD

HFG

19.85 ± 0.21 27.25 ± 0.35 a 7.4 ± 0.14 a 2.45 ± 0.04 10.14 ± 0.04 a

19.81 33.75 13.94 2.38 12.87

± ± ± ± ±

0.87 0.43 b 0.24 b 0.04 0.17 b

± ± ± ± ±

4.84 1.55 5.29 2.85 0.78

± ± ± ± ±

0.18 0.07 0.54 0.07 0.08

2.25 0.92 3.16 1.45 0.43

0.95 0.24 0.13 0.29 0.04

a a a a a

HFB

19.82 32.48 12.66 2.63 12.41

± ± ± ± ±

0.81 0.11 c 0.27 c 0.02 0.28 b

4.27 1.27 4.19 3.47 0.56

± ± ± ± ±

0.41 0.18 0.18 0.21 0.07

b b b b b

c a c c c

19.82 32.15 12.28 2.46 12.31

± ± ± ± ±

0.52 0.38 c 0.18 c 0.04 0.47 b

3.14 1.44 4.41 3.23 0.61

± ± ± ± ±

0.30 0.07 0.44 0.14 0.08

d b c c c

Values represent the mean ± SD (n = 10). Values in the same row with different letters are significantly different (p < 0.05).

a

Table 4. Analysis of SCFA Concentrations in Feces of Mice under Different Treatmentsa production of SCFAs (mM) treatment NCD HFD HFG HFB

acetic acid 99.6 84.2 113.3 103.5

± ± ± ±

8.5 3.7 6.1 2.1

propionic acid b a c d

68.7 45.7 98.3 81.5

± ± ± ±

5.8 6.7 3.5 4.3

b a d c

butyric acid 59.3 48.6 68.9 65.8

± ± ± ±

6.7 3.9 5.8 5.4

b a c c

total SCFAs 229.6 184.8 285.2 258.7

± ± ± ±

15.8 14.9 13.9 14.5

b a d c

Values represent the mean ± SD (n = 10). Letters represent significant differences between groups.

a

■

out on a C18 column (4.6 × 250 mm, 5 μm) at 30 °C. The mobile phase consisting of phosphate buffer solution (A) and acetonitrile solution (B) was as follows: 0−2 min, 100% A; 2−5 min, 90% A; 5− 20 min, 50% A; and 20−25 min, 0% A. Acetic, propionic, and butyric acid standards were obtained from Solarbio Science Technology Co. (Beijing, China). Polymerase Chain Reaction (PCR) Amplification and Illumina Sequencing. Three fecal samples in each group were randomly selected for microbiome analyses. Bacterial genomic DNA was extracted from feces using the QIAamp DNA Stool Mini Kit (Qiagen, Hilden, Germany). The DNA concentration was quantified using a Nanodrop 8000 spectrophotometer (Thermo Fisher Scientific), and DNA purity and quality were analyzed by 1% agarose gel electrophoresis. DNA samples were diluted to 30 ng/μL and stored at −20 °C until use. The V3 and V4 regions of the bacterial 16S rRNA gene were amplified by PCR (Bio-Rad, Hercules, CA, U.S.A.) using the primers 338F (ACTCCTACGGGAGGCAGCAG) and 806R (GGACTACHVGGGTWTCTAAT). The cycling and reaction conditions were described by Fu et al.29 Sequencing was carried out on the Illumina MiSeq PE300 sequencing platform (Illumina, San Diego, CA, U.S.A.) at Beijing Allwegene Technology Co. (Beijing, China). The detailed information about Illumina sequencing was as described by Fu et al.29 and Liu et al.30 A unique sequence set was classified into operational taxonomic units (OTUs) below a threshold of 97% identity using UCLUST (https://drive5.com/usearch/manual/uclust_algo.html). Chimeric sequences were identified and removed using USEARCH, version 8.0.1623 (https://www.hpc.science.unsw.edu.au/software/usearch/ 801623). The taxonomy of each 16S rRNA gene sequence was analyzed with UCLUST against the Silva119 16S rRNA database (https://www.arb-silva.de/) using a confidence threshold of 90%. Statistical Analysis. Statistical analysis was performed using Statistical Analysis System version 9.2 software (SAS Institute, Cary, NC, U.S.A.). Data are presented as the mean ± standard deviation (SD), and differences between groups were evaluated by one-way analysis of variance followed by Tukey’s test. p < 0.05 was considered statistically significant. Heatmap images, Venn diagrams, and linear discriminant analysis effect size (LEfSe) were created according to the method described by Tian et al.31

RESULTS Characterization of Black Legume Powders and Experimental Diet Compositions. The detailed characteristics of the two black legumes are shown in Table 1. G. soja had lower carbohydrate and fat contents than G. max. However, the dietary fiber content of G. soja was higher than that of G. max. HFDs supplemented with the two black legumes were prepared that were equivalent in terms of energy, with corn oil substituted for soybean oil to eliminate the effects of isoflavones in the latter. The linoleic and linolenic acid contents of G. max (49.19 and 8.41 g/100 g, respectively) were higher than those of G. soja (2.82 and 0.87 g/100 g, respectively). Different amounts of cellulose were added to each diet to equalize total dietary fiber. Additionally, 0.65% DLmethionine was added to the HFG and HFB groups to achieve the same amount of nitrogen as in the HFD. Qualitative and quantitative analyses of phenolic compounds in the diets are shown in Tables S1 and S2 of the Supporting Information. The isoflavone content in G. soja was 788.77 μg/g, while the isoflavone content in G. max was 139.72 μg/g. Effect of Black Legume Supplementation on Body Weight and Lipid Profiles. There were no differences in the initial body weight among groups. However, all three HFD groups had higher energy intake than the NCD group (p < 0.05) and higher final body weights (p < 0.05). At the end of the experiment, body weights in NCD, HFD, HFG, and HFB had increased by 27.2, 41.3, 38.9, and 38.3%, respectively. Thus, mice that consumed a HFD supplemented with black legumes gained less weight and had lower final body weights than those on a non-supplemented HFD (Table 3). Serum levels of Glu, TG, TCHO, HDL-c, and LDL-c were significantly higher (p < 0.05) in the HFD, HFG, and HFB groups than in the NCD group. On the other hand, the HFB and HFG groups had lower Glu, TCHO, and LDL-c (p < 0.05) but higher HDL-c (p < 0.05) levels than the HFD group. C


Article


Figure 1. Representative images of liver and white adipose tissue sections stained with hematoxylin and eosin and observed at 40× magnification.

the richness and diversity of fecal microbiota. A total of 447 OTUs were detected, with 131 common to all samples (Figure 2B). Numbers of OUTs exclusive to the HFB and HFG groups at the phylum level were 88 and 4, respectively. The exclusive OTUs belonged to Firmicutes (n = 33), Bacteroidetes (n = 33), Proteobacteria (n = 9), Tenericutes (n = 2), Spirochaetae (n = 2), Fusobacteria (n = 2), Actinobacteria (n = 2), Tenericutes (n = 2), Saccharibacteria (n = 2), Elusimicrobia (n = 1), and Cyanobacteria (n = 1) in the HFB group and Firmicutes (n = 3) and Cyanobacteria (n = 1) in the HFG group. Principal coordinate analysis (PCoA) revealed that the four diet groups formed distinct clusters in the ordination plot, suggesting that black legume supplementation caused major changes in gut microbiome profiles (Figure 2C). To examine these changes in greater detail, we compared the relative abundance of the predominant taxa in the four groups that were identified by sequencing (Figure 3). Gut microbiota composition differed significantly among the groups. At the phylum level, the HFD group showed a marked decrease relative to the NCD group in the relative abundance of Firmicutes (3.63 versus 19.32%) and an increase in the relative abundance of Verrucomicrobia (31.61 versus 0.01%). In comparison to the HFD group, mice in the HFB and HFG groups had greater abundance of Bacteroidetes (1.34- and 1.07-fold higher, respectively) and Proteobacteria (1.26- and 2.41-fold higher, respectively) and a much lower abundance of Verrucomicrobia. These results demonstrate that black legume supplementation reverses some of the change in gut microbiota composition induced by a HFD. Microbiome profiling was carried out at the genus level to further analyze the differences among diet groups. Clustering of the 20 most abundant genera (>0.2%) is shown in Figure 4. The classified genera belonged to four phyla, i.e., Bacteroidetes (n = 8), Firmicutes (n = 7), Proteobacteria (n = 3), and Verrucomicrobia (n = 1). However, genus distributions differed markedly across groups: a HFD resulted in a sharp increase in Akkermansia but a decrease in Ruminococcus and Escherichia/Shigella. On the other hand, consumption of HFG and HGB decreased Akkermansia by 81.91 and 98.04%, respectively, while increasing the relative abundance of Allobaculum, Parasutterella, Anaerotruncus, Helicobacter, and Alistipes.

Moreover, the serum Glu level was higher whereas the TG level was lower in the HFG group than the HFB group (p < 0.05). Effect of Black Legume Supplementation on the SCFA Content. The fecal SCFA content was examined by measuring acetic, propionic, and butyric acid and total SCFA concentrations. Total SCFA and acid concentrations were reduced in the HFD group compared to the NCD group (p < 0.05; Table 4) but were elevated in HFG and HFB groups (p < 0.05). Moreover, acetic and propionic acid and total SCFA concentrations were higher in the HFG group than the HFB group (p < 0.05). Effect of Black Legume Supplementation on HFDInduced Hepatosteatosis and Changes in Adipose Tissue. Mice on a HFD showed increased lipid deposition and microvesicular steatosis in the liver, with small lipid droplets in cells (Figure 1). However, black legume supplementation had a lipid-lowering effect, as evidenced by the reduction in hepatic steatosis. Moreover, a HFD increased the mean size of adipocytes in abdominal adipose tissue compared to the NCD group, an effect that was partly reversed in mice that consumed a diet supplemented with black legumes, indicating that lipid storage was inhibited. Effect of Black Legume Supplementation on Microbial Community Richness and Diversity. To evaluate whether black legume consumption induces changes in the gut microbiome, we evaluated fecal bacterial composition by sequencing the bacterial 16S rRNA V3−V4 region. A total of 12 samples from each of the four groups were analyzed by high-throughput pyrosequencing, which generated 840 906 raw reads. After low-quality sequences were removed, 806 091 clean tags were subjected to analysis. The number of clean tags per sample ranged from 41 571 to 88 436. Effective reads were clustered into OTUs based on a 97% similarity level. Rarefaction and Shannon−Wiener curves suggested that the libraries were sufficiently large to cover most of the bacterial diversity in different samples (panels A and B of Figure S1 of the Supporting Information). Interestingly, Chao and Shannon indices, which were higher in the HFB group (324.76 and 4.85) than the HFG group (236.60 and 4.72), were higher in the black-legume-supplemented HFD group compared to the non-supplemented HFD group (155.63 and 3.73) (p < 0.05; Figure 2A). These results indicate that black legumes enhanced D


Article


Figure 2. Diversity, richness, and population structure of fecal microbiota under different treatments (n = 3): (A) OTU richness and diversity indices, (B) Venn diagram showing the OTUs shared among different samples, and (C) principal coordinate analysis score plot of gut microbiota based on the relative abundance of OTUs at the genus level.

reduces the risk of cardiometabolic disease, diabetes mellitus, and obesity.32−34 In this study, we compared two black legumes of different species in terms of their impact on various aspects of metabolic syndrome in mice. In agreement with a previous study,35 we showed that dietary supplementation with these legumes reduced weight gain and restored serum levels of glucose and cholesterol that were increased by consumption of a HFD. This was supported by our histological analysis, which showed that the number of lipid droplets and hepatic steatosis induced by a HFD were also reduced, with mice in the HFG group showing greater improvement in adipocyte size. These effects can be attributed to the high polyphenol content of black legumes.36,37 Numerous studies have demonstrated that SCFAs exhibits a variety of biological activities in various organs and tissues.38,39 Our results showed that a HFD significantly reduced each acid

We compared the fecal microbiota of different treatment using LEfSe to identify the specific bacterial taxa associated with the black legume supplementation. Consistent with the above results, significantly different taxa abundances were observed among the four groups (Figure S2 of the Supporting Information). At the family level, Verrucomicrobiaceae, Verrucomicrobia, Akkermansia, and Verrucomicrobiae were enriched in the HFD group, while Proteobacteria, Helicobacteracear, Desulfovibrionaceae, and Campylobacterales were more abundant in the HFB group and Rikenellaceae and Alistipes was more abundant in the HFG group. These data indicated the biomarkers of four groups (Figure 5).

■

DISCUSSION Increased consumption of legume-derived foods is inversely correlated with symptoms of metabolic syndrome and, thus, E


Article


Figure 3. Relative abundance of bacteria at the phylum level under different treatments (n = 3).

Figure 4. Heatmap of relative abundances of predominant genera (top 20) under each treatment. The color intensity in each treatment is normalized to represent its relative ratio in the four groups (n = 3).

propionate are produced via amino acid fermentation.40,41 Accordingly, the amino acids may be higher in the HFG group, resulting from G. soja supplementation.42,43 With regard to the roles of propionate and butyrate, it has been reported that propionate and butyrate are predominantly antiobesogenic and

and total SCFA concentrations in feces, while dietary supplementation of black legumes restored the levels of each acid and total SCFA induced by high fat diet. SCFAs are mainly produced through fermentation of carbohydrates and amino acids that escape digestion, whereas acetate and F


Article


Figure 5. Identified biomarkers ranked by the effect size in different samples (n = 3).

observation also reported that the relative abundance of Verrucomicrobia was suppressed by consumption of bamboo shoot fiber.52 Thus, this inhibitory effect of black legume supplementation may be attributable to the fiber. At the genus level, HFG and HFB groups showed enrichment of Allobaculum, whose members are known to be SCFA producers.53 Thus, the high content of dietary fiber and phytochemicals, including phenolic compounds, may account for the beneficial effects of black legumes. In summary, the results of this study demonstrate that dietary supplementation with black legumes improved the lipid profiles of mice fed a HFD, an effect that was associated with modulation of gut microbiota composition. Additional studies are needed to clarify whether polyphenols or dietary fiber (or both) in black legumes are directly responsible for these beneficial effects on metabolism.

considered as providing health benefits by reducing visceral and liver fat.44,45 Consistent with these observations, a propionate and butyrate increase was observed and a lower weight gain with a lower amount of abdominal fat was observed as well in HFB and HFG. Furthermore, acetate and propionate are mainly produced by members of the Bacteroidetes phylum, while butyrate is predominantly produced by the Firmicute phylum.46 This could be the plausible explanation for the higher abundance of Bacteroidetes and higher production of acetic and propionate acids in HFG under high-fat diet conditions. Given that gut microbiota composition reflects metabolic health,47,48 we investigated the impact of black legume supplementation on gut microbiome profiles in the different diet groups. The OTU analysis and Chao 1, abundance-based coverage estimator (ACE), and Shannon’s diversity indices indicated that species diversity and richness were decreased in HFD-fed mice, which was reversed by black legume supplementation. PCoA revealed that black legume consumption also altered gut microbiota composition compared to mice that consumed a HFD or NCD. The relative abundance of Bacteroidetes is thought to reflect the degree of weight loss.49 Indeed, we observed that the relative abundance of Bacteroidetes was higher in the HFG and HFB groups than the HFD group and much higher than the NCD group, suggesting that black legumes promote the proliferation of Bacteroidetes and inhibit weight gain. Verrucomicrobia is associated with nutrient metabolism and has beneficial effects on metabolism.50,51 However, we found that the relative abundance of Verrucomicrobia was significantly increased in HFD-fed mice compared to NCD and was reduced by black legume supplementation. The inhibitory effect of black legume supplementation may be attributed to the fiber. A similar

■

ASSOCIATED CONTENT

S Supporting Information *

The Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/acs.jafc.8b02016. Information about the identified phenolic compounds (Table S1) and their content (Table S2) in two black legume powders, rarefaction and Shannon curves of fecal microbiota (Figure S1), and taxonomic hierarchical structure of the identified habitat biomarkers generated using LEfSe (Figure S2) (PDF)

■

AUTHOR INFORMATION

Corresponding Authors

*Telephone: +86-532-88702115. Fax: +86-532-88701012. Email: [email protected]. G


Article

Journal of Agricultural and Food Chemistry *E-mail: [email protected].

Intakes of selected nutrients, foods, and phytochemicals and prostate cancer risk in western New York. Nutr. Nutr. Cancer 2005, 53, 33−41. (10) Papandreou, C.; Becerra-Tomás, N.; Bulló, M.; MartínezGonzález, M. Á .; Corella, D.; Estruch, R.; Ros, E.; Arós, F.; Schroder, H.; Fitó, M.; Serra-Majem, L.; Lapetra, J.; Fiol, M.; Ruiz-Canela, M.; Sorli, J. V.; Salas-Salvadó, J. Legume consumption and risk of allcause, cardiovascular, and cancer mortality in the PREDIMED study. Clin. Nutr. 2018, DOI: 10.1016/j.clnu.2017.12.019. (11) Ö zcan, M. M.; Al Juhaimi, F. Effect of sprouting and roasting processes on some physico-chemical properties and mineral contents of soybean seed and oils. Food Chem. 2014, 154, 337−342. (12) Alajaji, S. A.; Eladawy, T. A. Nutritional composition of chickpea (Cicer arietinum L.) as affected by microwave cooking and other traditional cooking methods. J. Food Compos. Anal. 2006, 19, 806−812. (13) Oliviero, T.; Capuano, E.; Cämmerer, B.; Fogliano, V. Influence of roasting on the antioxidant activity and HMF formation of a cocoa bean model systems. J. Agric. Food Chem. 2009, 57, 147−52. (14) Zhou, R.; Cai, W.; Xu, B. Phytochemical profiles of black and yellow soybeans as affected by roasting. Int. J. Food Prop. 2017, 20, 3179−3190. (15) Kim, H. G.; Kim, G. W.; Oh, H.; Yoo, S. Y.; Kim, Y. O.; Oh, M. S. Influence of roasting on the antioxidant activity of small black soybean (Glycine max L. Merrill). LWTFood Sci. Technol. 2011, 44, 992−998. (16) Lee, S.; Lee, J. Effects of oven-drying, roasting, and explosive puffing process on isoflavone distributions in soybeans. Food Chem. 2009, 112, 316−320. (17) Monk, J. M.; Lepp, D.; Wu, W.; Graf, D.; McGillis, L. H.; Hussain, A.; Carey, C.; Robinson, L. E.; Liu, R.; Tsao, R.; Brummer, Y.; Tosh, S. M.; Power, K. A. Chickpea-supplemented diet alters the gut microbiome and enhances gut barrier integrity in C57Bl/6 male mice. J. Funct. Foods 2017, 38, 663−674. (18) Kim, S. J.; de Souza, R. J.; Choo, V. L.; Ha, V.; Cozma, A. I.; Chiavaroli, L.; Mirrahimi, A.; Blanco Mejia, S.; Di Buono, M.; Bernstein, A. M.; Leiter, L. A.; Kris-Etherton, P. M.; Vuksan, V.; Beyene, J.; Kendall, C. W. C.; Jenkins, D. J. A.; Sievenpiper, J. L. Effects of dietary pulse consumption on body weight: A systematic review and meta-analysis of randomized controlled trials. Am. J. Clin. Nutr. 2016, 103, 1213−1223. (19) Monk, J. M.; Lepp, D.; Zhang, C. P.; Wu, W.; Zarepoor, L.; Lu, J. T.; Pauls, K. P.; Tsao, R.; Wood, G. A.; Robinson, L. E.; Power, K. A. Diets enriched with cranberry beans alter the microbiota and mitigate colitis severity and associated inflammation. J. Nutr. Biochem. 2016, 28, 129−139. (20) Monk, J. M.; Lepp, D.; Wu, W.; Pauls, K. P.; Robinson, L. E.; Power, K. A. Navy and black bean supplementation primes the colonic mucosal microenvironment to improve gut health. J. Nutr. Biochem. 2017, 49, 89−100. (21) Chen, P. X.; Dupuis, J. H.; Marcone, M. F.; Pauls, P. K.; Liu, R.; Liu, Q.; Tang, Y.; Zhang, B.; Tsao, R. Physicochemical properties and in vitro digestibility of cooked regular and nondarkening cranberry beans (Phaseolus vulgaris L.) and their effects on bioaccessibility, phenolic composition, and antioxidant activity. J. Agric. Food Chem. 2015, 63, 10448−10458. (22) den Besten, G.; van Eunen, K.; Groen, A. K.; Venema, K.; Reijngoud, D.-J.; Bakker, B. M. The role of short-chain fatty acids in the interplay between diet, gut microbiota, and host energy metabolism. J. Lipid Res. 2013, 54, 2325−2340. (23) Mora, S.; Fullerton, R. Effects of short chain fatty acids on glucose and lipid metabolism in adipocytes. FASEB J. 2015, 29 (Supplement), 672.5. (24) Sanz, Y.; Santacruz, A.; Gauffin, P. Gut microbiota in obesity and metabolic disorders. Proc. Nutr. Soc. 2010, 69, 434−41. (25) Peng, H.; Li, W.; Li, H.; Deng, Z.; Zhang, B. Extractable and non-extractable bound phenolic compositions and their antioxidant properties in seed coat and cotyledon of black soybean (Glycinemax (L.) merr). J. Funct. Foods 2017, 32, 296−312.

ORCID

Changliang Jing: 0000-0003-3830-5099 Ping Zou: 0000-0002-6893-2571 Author Contributions †

Changliang Jing and Zhiguo Wen contributed equally to this work. Funding

This work was supported by the China Postdoctoral Science Foundation (2017M622305), the Application Research Project of Qingdao Postdoctoral Personnel, the Open Project Program of Key Laboratory of Feed Biotechnology (Ministry of Agriculture, China), and the Agricultural Science and Technology Innovation Program (ASTIP-TRIC07). Notes

The authors declare no competing financial interest.

■

ABBREVIATIONS USED BW, body weight; Glu, blood glucose; HDL-c, high-density lipoprotein cholesterol; HFB, high-fat diet supplemented with 20% Glycine max powder; HFD, high-fat diet (60% kcal from fat); HFG, high-fat diet supplemented with 20% Glycine soja seed powder; LDL-c, low-density lipoprotein cholesterol; NCD, normal diet; T-CHO, total cholesterol; TG, total triglyceride; SCFA, short-chain fatty acid; OTU, operational taxonomic unit

■

REFERENCES

(1) Adebowale, K. O.; Lawal, O. S. Comparative study of the functional properties of bambarra groundnut (Voandzeia subterranean), jack bean (Canavalia ensiformis) and mucuna bean (Mucuna pruriens) flours. Food Res. Int. 2004, 37, 355−365. (2) Dhillon, P. K.; Bowen, L.; Kinra, S.; Bharathi, A. V.; Agrawal, S.; Prabhakaran, D.; Reddy, K. S.; Ebrahim, S. Legume consumption and its association with fasting glucose, insulin resistance and type 2 diabetes in the Indian Migration Study. Public Health Nutr 2016, 19, 3017−3026. (3) Nouri, F.; Sarrafzadegan, N.; Mohammadifard, N.; Sadeghi, M.; Mansourian, M. Intake of legumes and the risk of cardiovascular disease: Frailty modeling of a prospective cohort study in the Iranian middle-aged and older population. Eur. J. Clin. Nutr. 2016, 70, 217− 221. (4) Lee, M.; Sorn, S. R.; Park, Y.; Park, H. K. Anthocyanin rich-black soybean testa improved visceral fat and plasma lipid profiles in overweight/obese Korean adults: A randomized controlled trial. J. Med. Food 2016, 19, 995−1003. (5) Qin, Q.; Zhang, Y. L.; Zhang, S. W. The nutritional value and research progress of black soybean. China Food Addit. 2015, 7, 145− 150. (6) Kanamoto, Y.; Yamashita, Y.; Nanba, F.; Yoshida, T.; Tsuda, T.; Fukuda, I.; Nakamuratsuruta, S.; Ashida, H. A black soybean seed coat extract prevents obesity and glucose intolerance by up-regulating uncoupling proteins and down-regulating inflammatory cytokines in high-fat diet-fed mice. J. Agric. Food Chem. 2011, 59, 8985−8993. (7) Kurimoto, Y.; Shibayama, Y.; Inoue, S.; Soga, M.; Takikawa, M.; Ito, C.; Nanba, F.; Yoshida, T.; Yamashita, Y.; Ashida, H.; Tsuda, T. Black soybean seed coat extract ameliorates hyperglycemia and insulin sensitivity via the activation of AMP-activated protein kinase in diabetic mice. J. Agric. Food Chem. 2013, 61, 5558−5564. (8) Zhou, S.; Haruo, S.; Yue, W.; Satoko, S.; Yang, Z. H. Comparison of isoflavones among wild, black and yellow soybeans. Soybean Sci. 2008, 27, 315−319. (9) Mccann, S. E.; Ambrosone, C. B.; Moysich, K. B.; Brasure, J.; Marshall, J. R.; Freudenheim, J. L.; Wilkinson, G. S.; Graham, S. H


Article

Journal of Agricultural and Food Chemistry (26) Mudryj, A. N.; Yu, N.; Hartman, T. J.; Mitchell, D. C.; Lawrence, F. R.; Aukema, H. M. Pulse consumption in Canadian adults influences nutrient intakes. Br. J. Nutr. 2012, 108, S27−S36. (27) Fischer, A. H.; Jacobson, K. A.; Rose, J.; Zeller, R. Hematoxylin and eosin staining of tissue and cell sections. Cold Spring Harb Protoc. 2008, 2008, pdb.prot4986. (28) Dai, Z.; Lyu, W.; Xie, M.; Yuan, Q. Y.; Ye, H.; Hu, B.; Zhou, L.; Zeng, X. Effects of a-galactooligosaccharides from chickpeas on high fat diet induced metabolic syndrome in mice. J. Agric. Food Chem. 2017, 65, 3160−3166. (29) Fu, S. F.; Chen, K. Q.; Sun, W. X.; Zhu, R.; Zheng, Y.; Zou, H. Improved methane production of corn straw by the stimulation of calcium peroxide. Energy Convers. Manage. 2018, 164, 36−41. (30) Liu, L.; Wang, S.; Guo, X.; Zhao, T.; Zhang, B. Succession and diversity of microorganisms and their association with physicochemical properties during green waste thermophilic composting. Waste Manage. 2018, 73, 101−112. (31) Tian, X.-Y.; Zhang, C.-S. Illumina-Based Analysis of Endophytic and Rhizosphere Bacterial Diversity of the Coastal Halophyte Messerschmidia sibirica. Front. Microbiol. 2017, 8, 2288−2298. (32) Bouchenak, M.; Lamrisenhadji, M. Nutritional quality of legumes, and their role in cardiometabolic risk prevention: A review. J. Med. Food 2013, 16, 185−198. (33) Afshin, A.; Micha, R.; Khatibzadeh, S.; Mozaffarian, D. Consumption of nuts and legumes and risk of incident ischemic heart disease, stroke, and diabetes: A systematic review and metaanalysis. Am. J. Clin. Nutr. 2014, 100, 278−288. (34) Rebello, C. J.; Greenway, F. L.; Finley, J. W. A review of the nutritional value of legumes and their effects on obesity and its related co-morbidities. Obes. Rev. 2014, 15, 392−407. (35) Jung, J. H.; Kim, H. S. The inhibitory effect of black soybean on hepatic cholesterol accumulation in high cholesterol and high fat dietinduced non-alcoholic fatty liver disease. Food Chem. Toxicol. 2013, 60, 404−412. (36) Ting, Y.; Chang, W. T.; Shiau, D. K.; Chou, P. H.; Wu, M. F.; Hsu, C. L. Antiobesity efficacy of quercetin-rich supplement on dietinduced obese rats: Effects on body composition, serum lipid profile, and gene expression. J. Agric. Food Chem. 2018, 66, 70−80. (37) Zhao, L.; Zhang, Q.; Ma, W.; Tian, F.; Shen, H.; Zhou, M. A combination of quercetin and resveratrol reduces obesity in high-fat diet-fed rats by modulation of gut microbiota. Food Funct. 2017, 8, 4644−4656. (38) Tan, J.; Mckenzie, C.; Vuillermin, P. J.; Goverse, G.; Vinuesa, C. G.; Mebius, R. E.; Macia, L.; Mackay, C. R. Dietary fiber and bacterial SCFA enhance oral tolerance and protect against food allergy through diverse cellular pathways. Cell Rep. 2016, 15, 2809− 2824. (39) Astakhova, L.; Ngara, M.; Babich, O.; Prosekov, A.; Asyakina, L.; Dyshlyuk, L.; Midtvedt, T.; Zhou, X.; Ernberg, I.; Matskova, L. Short chain fatty acids (SCFA) reprogram gene expression in human malignant epithelial and lymphoid cells. PLoS One 2016, 11, e0154102. (40) Morrison, D. J.; Preston, T. Formation of short chain fatty acids by the gut microbiota and their impact on human metabolism. Gut Microbes 2016, 7, 189−200. (41) Russell, W. R.; Gratz, S. W.; Duncan, S. H.; Holtrop, G.; Ince, J.; Scobbie, L.; Duncan, G.; Johnstone, A. M.; Lobley, G. E.; Wallace, R. J.; Duthie, G. G.; Flint, H. J. High-protein, reduced-carbohydrate weight-loss diets promote metabolite profiles likely to be detrimental to colonic health. Am. J. Clin. Nutr. 2011, 93, 1062−1072. (42) Wang, M. Study on the nutritional evaluation and trypsin inhibitor of wild soybean (Glycine soja Sieb. et Zucc.) in Jimo. Master’s Degree Thesis, Ocean University of China, Qingdao, China, 2013; pp 23. (43) Russell, W. R.; Gratz, S. W.; Duncan, S. H.; Holtrop, G.; Ince, J.; Scobbie, L.; Duncan, G.; Johnstone, A. M.; Lobley, G. E.; Wallace, R. J.; Duthie, G. G.; Flint, H. J. High-protein, reduced-carbohydrate weight-loss diets promote metabolite profiles likely to be detrimental to colonic health. Am. J. Clin. Nutr. 2011, 93, 1062−1072.

(44) Lu, Y.; Fan, C.; Li, P.; Lu, Y.; Chang, X.; Qi, K. Short chain fatty acids prevent high-fat-diet-induced obesity in mice by regulating G protein-coupled receptors and gut microbiota. Sci. Rep. 2016, 6, 37589. (45) Kosmala, M.; Jurgonski, A.; Juskiewicz, J.; Karlińska, E.; Macierzyński, J.; Roj, E.; Zduńczyk, Z. The chemical composition of blackberry press cake, polyphenolic extract, and defatted seeds, and their effects on cecal fermentation, bacterial metabolites, and blood lipid profile in rats. J. Agric. Food Chem. 2017, 65, 5470−5497. (46) Chakraborti, C. K. New-found link between microbiota and obesity. World J. Gastroentero. 2015, 6, 110−119. (47) Chang, C.-J.; Lin, C.-S.; Lu, C.-C.; Martel, J.; Ko, Y.-F.; Ojcius, D. M.; Tseng, S.-F.; Wu, T.-R.; Chen, Y.-Y. M.; Young, J. D.; Lai, H.C. Ganoderma lucidum reduces obesity in mice by modulating the composition of the gut microbiota. Nat. Commun. 2015, 6, 7489. (48) Liu, F.; Wang, X.; Shi, H.; Wang, Y.; Xue, C.; Tang, Q. J. Polymannuronic acid ameliorated obesity and inflammation associated with a high-fat and high-sucrose diet by modulating the gut microbiome in a murine model. Br. J. Nutr. 2017, 117, 1332−1342. (49) Ley, R.; Turnbaugh, P.; Klein, S.; Gordon, J. Human gut microbes associated with obesity. Nature 2006, 444, 1022−1023. (50) Anhê, F. F.; Roy, D.; Pilon, G.; Dudonné, S.; Matamoros, S.; Varin, T. V.; Garofalo, C.; Moine, Q.; Desjardins, Y.; Levy, E.; Marette, A. A polyphenol-rich cranberry extract protects from dietinduced obesity, insulin resistance and intestinal inflammation in association with increased Akkermansia spp. population in the gut microbiota of mice. Gut 2015, 64, 872−873. (51) Shen, W.; Shen, M.; Zhao, X.; Zhu, H.; Yang, Y.; Lu, S.; Tan, Y.; Li, G.; Li, M.; Wang, J.; Hu, F.; Le, S. Anti-obesity effect of capsaicin in mice fed with high-fat diet is associated with an increase in population of the gut bacterium Akkermansia muciniphila. Front. Microbiol. 2017, 8, 1−10. (52) Li, X.; Guo, J.; Ji, K.; Zhang, P. Bamboo shoot fiber prevents obesity in mice by modulating the gut microbiota. Sci. Rep. 2016, 6, 32953. (53) Bai, J.; Zhu, Y.; Dong, Y. Modulation of gut microbiota and gutgenerated metabolites by bitter melon results in improvement in the metabolic status in high fat diet-induced obese rats. J. Funct. Foods 2018, 41, 127−134.

I


Consumption of Black Legumes - ACS Publications - American

Recommend Documents