Modulating Effects of Dicaffeoylquinic Acids from Ilex kudingcha on

Article Cite This: J. Agric. Food Chem. 2017, 65, 10185-10196

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Modulating Effects of Dicaffeoylquinic Acids from Ilex kudingcha on Intestinal Microecology in Vitro Minhao Xie,† Guijie Chen,† Peng Wan,† Zhuqing Dai,† Bing Hu,† Ligen Chen,‡ Shiyi Ou,§ Xiaoxiong Zeng,*,† and Yi Sun*,† †

College of Food Science and Technology, Nanjing Agricultural University, Nanjing 210095, Jiangsu, China Jiangsu Key Laboratory of Biochemistry and Biotechnology of Marine Wetland, Yancheng Institute of Technology, Yancheng 224051, Jiangsu, China § Department of Food Science and Engineering, Jinan University, Guangzhou 510632, Guangdong, China ‡

ABSTRACT: Dietary polyphenols have been considered as novel prebiotics, and polyphenols could exert their functions through modulating intestinal microbiota. The diverse bioactivities of kudingcha could derive from its phenolic compounds, but the effects of dicaffeoylquinic acids (diCQAs) from Ilex kudingcha on intestinal microbiota have not been investigated. In the present study, high-throughput sequencing and anaerobic fermentation in vitro were utilized to investigate the microecologymodulating function of I. kudingcha diCQAs. As a result, diCQAs raised the diversity and exhibited a more considerable impact than a carbon source on the microbial profile. DiCQAs increased the relative abundances of Alistipes, Bacteroides, Bifidobacterium, Butyricimonas, Clostridium sensu stricto, Escherichia/Shigella, Parasutterella, Romboutsia, Oscillibacter, Veillonella, Phascolarctobacterium, Lachnospiracea incertae sedis, Gemmiger, Streptococcus, and Haemophilus and decreased the relative abundances of Ruminococcus, Anaerostipes, Dialister, Megasphaera, Megamonas, and Prevotella. DiCQAs also affected the generation of short-chain fatty acids through microbiota. The contents of acetic and lactic acids were raised, while the production of propionic and butyric acids was reduced. Conclusively, diCQAs from I. kudingcha had significant modulating effects on intestinal microbiota in vitro, which might be the fundamental of diCQAs exerting their bioactivities. KEYWORDS: Ilex kudingcha, dicaffeoylquinic acid, intestinal microbiota, modulating effect

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in gastric fluid, and part of them could be hydrolyzed by pancreatic enzymes.7 In addition, a small portion of phenolic compounds could be hydrolyzed by intestinal epithelial brush border esterase.9 Besides enzymatic hydrolysis, the factors of pH and the interactions between polyphenols and proteins might exhibit effects on dietary phenolic structures in digestion.10,11 Most polyphenols remain unchanged in the upper digestive tract, and they reach the colon in intact forms and whereby interact with the intestinal microbiota.3 The interactions between polyphenols and gut microbiota consist of two aspects. Polyphenols can modulate gut microbiota (promoting or inhibiting the proliferation of specific communities); reciprocally, bacteria may convert natural polyphenols into metabolites and regulate their bioavailability and activity. In addition, there is a considerable interindividual variability in the functions of polyphenols.12 It is accepted that intestinal microbiota play an important role in the biological activities of polyphenols and could be the main target as well.13 Kudingcha is a traditional herb beverage alternative to Camellia genus tea, and Ilex kudingcha is one of the main plants for kudingcha production in China. It has been reported recently that it exerts diverse biological activities, such as antioxidant, hepatoprotective, anticancer, and anti-inflamma-

INTRODUCTION Phenolic compounds are plant secondary metabolites and are widely distributed in daily vegetables, fruits, and herb beverages.1 Epidemiological investigations, randomized clinical trials, and human and animal intervention studies have demonstrated that dietary polyphenols are beneficial for human health, and long-term dietary consumption of polyphenols is associated with reduction in the risk of chronic diseases such as cancer and neurodegenerative and cardiovascular diseases.2 Mechanism studies have indicated that polyphenols might exert their beneficial effects on the targets of oxidative stress, inflammation, and endothelial function.3 However, dietary polyphenols exhibit low bioaccessibility and bioavailability due to their structural properties, especially multiple hydroxyl groups and large molecular weights. The low bioavailability of polyphenols induces obstacles to explore the biological relevance of their activities.4 The valid concentrations exerting bioactivities of phenolics are usually much higher than their observed values. It has been reported that polyphenols exhibit significant biological functions at the micromolar level, but the concentrations of polyphenols actually reached only the nanomolar level in plasma.5,6 In the upper digestive tract, dietary polyphenols could undergo the modifications of release, hydrolysis, and oxidation. Digestion could liberate polyphenols from the solid food matrix and enhance their antioxidant capacity and bioaccessibility.7 Polyphenols could be partly hydrolyzed in simulated digestions, especially glycosidic bonds.8 Polyphenols could persist as stable © 2017 American Chemical Society

Received: Revised: Accepted: Published: 10185

August 27, 2017 October 30, 2017 October 31, 2017 October 31, 2017 DOI: 10.1021/acs.jafc.7b03992 J. Agric. Food Chem. 2017, 65, 10185−10196

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Journal of Agricultural and Food Chemistry

old) who did not have any gastrointestinal disorder or take any antibiotics, prebiotics, probiotics, or laxatives over the past 3 months. The fecal samples were mixed together, and the mixture was diluted 10-fold with autoclaved modified physiological saline solution (NaCl, 8.5 g/L; cysteine−HCl, 0.5 g/L) to yield a 10% (w/v) suspension. The suspension was centrifuged at 4 °C (300g, 5 min), and the supernatant was used as the fecal slurry in the following fermentations. The basal nutrient growth medium was prepared with peptone (2.0 g/L), yeast extract (2.0 g/L), NaCl (0.1 g/L), K2HPO4 (0.04 g/L), KH2PO4 (0.04 g/L), MgSO4 (0.01 g/L), CaCl2 (0.01 g/L), NaHCO3 (2.0 g/L), hemin (0.02 g/L), cysteine−HCl (0.5 g/L), bile salts (0.5 g/L), resazurin (1.0 mg/L), Tween 80 (2.0 mL/L), and vitamin K1 (10 μL/ L). Glucose, sucrose, α-GOS, or inulin (10.0 g/L) was added to the basal medium. The microbial fermentation system consisted of 2.0 mL of the fecal slurry and 18.0 mL of medium. The systems containing glucose, sucrose, α-GOS, inulin, and no addition of carbohydrate without diCQAs added were named as GLU, SUC, GOS, INL, and BLK, respectively, and the other parts supplied with diCQAs (1.0 g/L) were recorded as GLUD, SUCD, GOSD, INLD, and BLKD, respectively. Each experiment was carried out in triplicate. The fermentation systems were settled in an MGC Anaero Pack system (Mitsubishi Gas Chemical Co., Inc., Tokyo, Japan) and incubated at 37 °C for 24 h. The oxygen content in the sealed box was lower than 0.1%, which was confirmed by an oxygen indicator. The fermentation systems were made as homogeneous as possible by gentle shaking every 6 h. After incubation and sampling for bacterial DNA extraction, the cultures were frozen at −20 °C until analysis of SCFAs, and the analysis was completed in 1 week. Analysis of the Microbial Composition. The culture media were centrifuged at 4 °C immediately after incubation, and the total genomic DNA was extracted using a TIANamp Stool DNA Kit (TIANGEN Biotech, Beijing, China) according to the instruction manual. The original microbial composition before fermentation was also analyzed and recorded as OR. The DNA samples were sent to the Center for Genetic & Genomic Analysis, Genesky Biotechnologies Inc. (Shanghai, China), for sequencing under the atmosphere of solid carbon dioxide. A high-fidelity polymerase chain reaction (PCR) was utilized to amplify bacterial 16S rDNA hypervariable region 4 (V4) with the primers (primer F, Illumina adapter sequence 1 + AYTGGGYDTAAAGNG; primer R: Illumina adapter sequence 2 + TACNVGGGTATCTAATCC), and specific sequencing labels were added to the library. High-throughput sequencing was performed on the Illumina Miseq platform with the 2 × 250 bp paired-end method after the library was quantified, mixed, and quality checked. The raw data were filtered by several steps to remove low-quality reads. The raw reads were filtered at Q15 and merged, and nonspecific amplicons, reads with an error rate >2, singletons, and chimeras were removed to obtain clean data. Operational taxonomic units (OTUs) were clustered with the similarity of 97% by UPARSE, and the OTUs were subsampled randomly.28 Mothur was utilized for taxonomical assignments at the 80% confidence level based on the Ribosomal Database Project (RDP) database.29,30 R software packages (V2.15.3, http://www.r-project.org/) were employed for calculation of α- and β-diversities. Cluster analysis was performed by using the Bray−Curtis dissimilarity index and the unweighted pair-group method with arithmetic means (UPGMA) linkage method. Canonical correspondence analysis (CCA) was used for analysis of the contributions of diCQAs to the microbial composition. The difference in microbial communities of the groups was revealed by linear discriminative analysis (LDA) effect size (LEfSe, http://huttenhower.sph.harvard.edu/galaxy/) tests.31 Determination of SCFAs and Lactic Acid. The contents of SCFAs produced, including acetic, propionic, n-butyric, isobutyric, nvaleric, and isovaleric acids, were determined by gas chromatography (GC).32 The chromatographic separation was performed on a GC instrument (6890N, Agilent Technologies) equipped with an HPINNOWAX column (30 m × 0.25 mm × 0.25 μm, Agilent) and a flame ionization detector (FID). The carrier gas nitrogen was supplied at a flow rate of 19.0 mL/min. The initial column temperature was

tory activities, and also prevention of gastric injury, neuronal damage, and metabolic disorders.14−21 The activities derive from the active components in I. kudingcha, including triterpenoids, polysaccharides, and polyphenols.15,22 The main phonolics in I. kudinghca are caffeoylquinic acids (CQAs), including monocaffeoylquinic acids (mono-CQAs) and dicaffeoylquinic acids (diCQAs). In our previous study,23 it was found that diCQAs were seldomly hydrolyzed in simulated saliva and gastric and pancreatic fluids or by Caco-2 cells. It has been reported that consumption of coffee, a worldwide popular CQA-rich beverage, increased the population of Bifidobacterium spp. without a major influence on the dominant microbiota.24 CQAs could increase the proportion of Akkermansia in mice with colitis and the abundance of Bifidobacterium spp. in vitro.25,26 DiCQAs have caught less attention than monoCQAs. The intestinal microbiota may play a crucial role in catalyzing the breakage of diCQAs, but the effects of diCQAs on intestinal microbiota have seldomly been studied. In the present study, therefore, anaerobic fermentation in vitro and high-throughput sequencing were utilized to investigate the impact of diCQAs on microbial compositions under different kinds of carbohydrate conditions. Furthermore, the influences of diCQAs on the production of short-chain fatty acids (SCFAs) were investigated.

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MATERIALS AND METHODS

Materials and Reagents. Kudingcha made from the leaves of I. kudingcha C.J. Tseng was purchased from Hainan Yexian Bio-Science Co. (Haikou, China). Glucose and sucrose were obtained from Sinopharm Chemical Reagent Co., Ltd. (Shanghai, China). Inulin was purchased from Nanjing Oddfoni Biological Technology Co., Ltd. (Nanjing, China). Soybean oligosaccharide (α-galactooligosaccharide, α-GOS) was obtained from Nanjing Duolong Biotech Co., Ltd. (Nanjing, China). Standards of acetic, propionic, n-butyric, isobutyric, n-valeric, isovaleric, and 2-ethylbutyric acids, methanol, and formic acid of high-performance liquid chromatography (HPLC) grade were purchased from Sigma Co. (St. Louis, MO). All the other reagents were of analytical grade. Preparation of DiCQAs. DiCQAs were prepared from kudingcha according to the reported method with some modifications.23 Briefly, kudingcha was extracted with hot water, and the resulting infusion was filtered, cooled to room temperature, and loaded onto a column of macroporous resin HP-20 (Mitsubishi Chemical, Tokyo, Japan). The column was eluted with pure water until the effluent had no absorption at 325 nm by monitoring online with a UV photometer (BUCHI, Switzerland). The target fraction was eluted with ethanol solution (70%, v/v), and the collected effluent was vacuum concentrated and freeze-dried to afford diCQAs. Determination of DiCQAs. The phenolic content of prepared diCQAs was determined by the Folin−Ciocalteu method with 3,5diCQA as the standard. A mixture of a 0.5 mL sample solution with an approximate concentration and 1.0 mL of 10% Folin−Ciocalteu reagent was kept for 5 min in the dark, and 2.0 mL of Na2CO3 (200 g/ L) was then added. After incubation and gentle shaking for 1 h at room temperature, the absorbance at 747 nm was recorded. The composition of the prepared diCQAs was analyzed by a highperformance liquid chromatograph equipped with a TSK gel ODS80TsQA column (2.0 × 250 mm, 5 μm, Tosoh Corp., Tokyo, Japan). The elution was performed with an effluent consisting of 45% ethanol and 0.2% formic acid for 23 min. The elution rate was set at 0.5 mL/ min, and the temperature of the column oven and wavelength of the detector were set at 40 °C and 280 nm, respectively. Anaerobic Fermentation in Vitro. The model of anaerobic fermentation in vitro with a fecal microbe was utilized to investigate the effects of diCQAs on intestinal microbiota as previously reported23,27 with some modifications. Fecal samples were obtained from four healthy volunteers (two males and two females, 22−28 years 10186

DOI: 10.1021/acs.jafc.7b03992 J. Agric. Food Chem. 2017, 65, 10185−10196

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Figure 1. Rarefaction (A) and Shannon (B) index curves of all the samples.

Table 1. Richness and α-Diversity of Each Groupa Chao1 OR BLK GLU SUC GOS INL BLKD GLUD SUCD GOSD INLD a

224.9 180.5 170.1 167.1 188.5 162.8 189.3 194.5 187.4 202.7 228.0

± ± ± ± ± ± ± ± ± ± ±

6.6 cd 17.2 ab 13.0 ab 11.9 ab 29.6 abc 5.4 a 18.4 abc 2.0 abcd 27.9 abc 13.1 bcd 39.0 d

ACE 225.8 177.7 167.6 168.0 177.6 160.5 185.2 202.4 187.8 202.5 203.0

± ± ± ± ± ± ± ± ± ± ±

Shannon

9.0 d 15.3 abc 3.7 ab 10.8 ab 15.4 abc 7.9 a 20.6 abc 9.7 cd 28.2 bc 11.8 cd 4.2 cd

2.90 3.28 2.32 2.24 2.35 2.14 2.78 2.86 2.82 2.67 2.85

± ± ± ± ± ± ± ± ± ± ±

0.04 0.06 0.01 0.05 0.03 0.05 0.08 0.02 0.01 0.03 0.02

Simpson f g c b c a e ef e d ef

0.139 0.066 0.240 0.267 0.209 0.275 0.106 0.131 0.109 0.140 0.123

± ± ± ± ± ± ± ± ± ± ±

0.006 0.006 0.008 0.016 0.009 0.024 0.005 0.003 0.006 0.005 0.005

c a e f d f b c b c bc

The same letter means no statistical significance was observed in the richness or α-diversity index between different groups (P > 0.05).

maintained at 100 °C for 1 min, increased to 180 °C in 16 min, and maintained at 180 °C for 4 min. The sample was acidified with hydrochloric acid before injection. 2-Ethylbutyric acid was employed as the internal standard for quantification. The content of lactic acid was determined by a commercial kit (Lactic Acid Assay Kit, Nanjing Jiancheng Bioengineering Institute, Nanjing, China) according to the manual instruction. Statistical Analysis. The data are expressed as the mean ± standard deviation (SD). The least significant difference (LSD), Duncan’s multiple range test, and one-way analysis of variance (ANOVA) were used for multiple comparisons by SPSS 16. P < 0.05 was considered to be of statistical significance.

was performed in triplicate. The average sequencing depth (clean data) of the 33 samples was 43029 ± 6733 reads. There were 316 different OTUs detected in total, and each sample consisted of 160 ± 21 OTUs. The refraction and Shannon index curves are shown in Figure 1. Although the refraction curve kept increasing with the increase of the sequencing depth, the Shannon index already reached a plateau and was stable for all the samples. The results besides the coverage index (99.91 ± 0.01%) suggested that most species were captured, though new OTUs would be expected if additional sequencing was performed. The results were valid as derived from the data. The α-diversity indexes are summarized as shown in Table 1. INL exhibited the lowest diversity, and BLK had the highest. With the addition of carbohydrates, kudingcha diCQAs increased the α-diversity, especially the Shannon and Simpson indexes, compared to the corresponding culture condition without diCQAs (P < 0.05). When cultured without any sugar, the diversity of the micobiota was slightly decreased by diCQAs (BLKD compared to BLK) because BLKD had a lower Shannon index (P < 0.05), higher Simpson index (P < 0.05), and higher mean values of Chao1 and ACE (P > 0.05). It has been reported that the diversity of gut microbiota is closely associated with host health. The gut microbial diversities of obese individuals are less than those of lean ones,33 and the Shannon index is significantly negatively related to fat tissue.34 The results of the present study showed that diCQAs could increase the diversity of intestinal microbiota, indicating that diCQAs from I. kudingcha have the potential in antiobesity by modulating the intestinal microflora. Effects of DiCQAs on the Overall Microbial Structure. Multivariate analyses were performed to compare the overall

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RESULTS AND DISCUSSION CQA derivatives are the main phenolics in I. kudingcha, and 3CQA, 4-CQA, 5-CQA, 3,4-diCQA, 3,5-diCQA, and 4,5-diCQA account for >90% of the total kudingcha polyphenols.23 For HP-20 macroporous resin chromatography, diCQAs were absorbed to the resin, and mono-CQAs were eluted by pure water with other components, such as carbohydrates and proteins. After complete washing with deionized water, diCQAs were eluted by ethanol solution. The Folin−Ciocalteu method and HPLC analysis revealed that diCQAs were the dominant compounds, and the proportions of 3,4-, 3,5-, and 4,5-diCQAs were 26.9 ± 1.7%, 42.3 ± 2.0%, and 30.8 ± 3.4%, respectively. Richness and Diversity of Microbiota after Anaerobic Fermentation. The experiment consisted of eleven groups in total, including four groups containing different carbohydrates (GLU, SUC, GOS, and INL), one group without carbohydrate added (BLK), five treatments with addition of kudingcha diCQAs corresponding to the five groups mentioned above, and the original status (OR). Each fermentation experiment 10187


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Figure 2. Clustering analysis (A), heat map of Bray−Curtis dissimilarity (B), NMDS (C), and CCA (D) of microflora at the OTU level.

compositions of all the anaerobic fermentation samples at the OTU level, and the results are displayed in Figure 2. The results of clustering analysis indicated that all the samples could be divided into two main groups, the group with diCQA addition and the group without diCQAs (Figure 2A). The fermentations without carbohydrate addition (BLK and BLKD) were nearer to that of the group with addition of diCQAs; that of OR was closer to those of the samples without diCQAs. The samples cultured with different sugars were clustered into different subgroups, but the distance between them was less than that caused by diCQAs (Figure 2B). In the results of nonmetric multidimensional scaling (NMDS) analysis, the samples with (GLUD, SUCD, GOSD, and INLD, green cycle) and without (GLU, SUC, GOS, and INL, blue cycle) diCQAs were separated completely on axis 1 (Figure 2C), suggesting the significant difference among them. The contributions of diCQAs and sugars to the shift in the microbial composition were determined by CCA, and the results are shown in Figure 2D. DiCQAs exhibited much more impact on the fermentation in vitro on both CCA1 and CCA2 than the sugars (glucose, sucrose, α-GOS, and inulin), indicating that diCQAs dominated the modulation on intestinal microbiota. The multiple analyses showed similar tendencies. Composition of the Microbial Community at the Phylum and Genus Levels. All the fermented samples mainly consisted of Firmicutes, Bacteroidetes, Proteobacteria, Actinobacteria, and Fusobacteria (Figure 3A). The addition of

diCQAs reduced the relative abundance of Firmicutes in respective carbohydrate conditions (P < 0.05, Figure 3B). DiCQAs had little effect on the relative abundance of Bacteroidetes (P > 0.05) except in the case of GOS, and diCQAs significantly decreased its abundance when α-GOS was utilized as the carbon source (P < 0.05, Figure 3C). In the conditions of all the carbohydrates and even without sugar, diCQAs reduced the ratio of Firmicutes to Bacteroidetes (F/B) compared to the corresponding group without diCQAs (P < 0.05, Figure 3D) and significantly increased the relative abundance of Proteobacteria (P < 0.05) except the GOS group (P > 0.05). In addition, diCQAs increased the abundance of Actinobacteria, especially the culture with α-GOS (P < 0.05, Figure 3E). The value of F/B is closely related to the ability of the harvesting energy of gut microflora, and it has been considered as an important indicator to evaluate the microbial composition.35,36 The reduction of F/B attributed to diCQAs indicated their antiobesity potential. Similar to diCQAs, quercetin and catechin have also been reported to increase the abundance of Actinobacteria, but puerarin did not have such potential.37 The microbial compositions of the anaerobic cultures at the genus level are shown in Figure 4. Bacteroides, Prevotella, Megamonas, Bifidobaterium, Escherichia/Shigella, Faecalibacterium, Parabacterium, Parasutterella, Blautia, Clostridium XIVa, Fusobacterium, and Dialister were the main genera. It was obvious that diCQAs increased the relative abundances of 10188


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Figure 3. Microbial composition at the phylum level (A, stack column; B, relative abundance of Firmicutes; C, relative abundance of Bacteroidetes; D, ratio of Firmicutes to Bacteroidetes (F/B); E, relative abundance of Actinobacteria).

Bacteroides, Bifidobacterium, and Escherichia/Shigella in the cultures with sugars, and the abundances of Prevotella, Megamonas, Dialister, and Anaerostipes were reduced. Notably, the abundance of Bifidobacterium for GOSD was higher than those for α-GOS and the other groups with diCQAs. α-GOS and diCQAs could synergistically promote the proliferation of Bifidobacterium. The results at the genus level are consistent with the data at the phylum level, and GOSD also exhibited the highest abundance of Actinobacteria. Difference in the Microbial Composition Derived from diCQAs. LDA and LEfSe were performed to identify the distinction of the microbial profile between groups treated with diCQAs or not. The LDA scores of the genera with a significant difference induced by diCQAs in the conditions of

different carbohydrates are shown in Figure 5. Under the addition of glucose, sucrose, α-GOS, and inulin, diCQAs increased the abundances of 20, 17, 20, and 22 genera, respectively, and the abundances of 10, 10, 11, and 8 genera were reduced, respectively. There were 14 genera increased in all the groups, including Bacteroides, Escherichia/Shigella, Bifidobacterium, Parasutterella, Alistipes, Romboutsia, Oscillibacter, Veillonella, Butyricimonas, Phascolarctobacterium, Lachnospiracea incertae sedis, Gemmiger, Streptococcus, Clostridium sensu stricto, and Haemophilus. On the other hand, the genera of Ruminococcus 2, Anaerostipes, Dialister, Megasphaera, Megamonas, and Prevotella were reduced by diCQAs. In addition, Clostridium XlVa and Odoribacter were increased and Blautia and Collinsella were decreased in at least three 10189


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Figure 4. Stack column (A) and heat map (B) of microbial composition at the genus level.

cases. It was found that the abundances of genera affected by diCQAs were similar in the fermentations with different sugars. Considering the results of β-diversities and LDA, it could be deduced that diCQAs played a primary role in modulation of the microbial composition, and the difference in carbohydrate functioned as a secondary effect. In the LEfSe analysis, the samples from cultures with different carbohydrates but without diCQAs (GLU, SUC, GOS, and INL) were regarded as a whole group (named as C), and the corresponding diCQA-treated samples were counted as another group (recorded as CD). The different types of sugar were regarded as the subclasses of LEfSe, and the results and the greatest differences in taxa caused by diCQAs are shown in Figure 6. The difference between the C and CD groups exhibited a tendency identical with those of the results obtained from the comparison of

respective carbohydrate conditions. At the phylum level, the CD groups showed a higher abundance of Actinobacteria and Proteobacteria than the C groups, while Firmicutes were more prevalent in the C groups. At the class level, diCQAs decreased the relative abundance of Negativicutes, and increased Bacilli, Actinobacteria, Gammaproteobacteria, and Alphaproteobacteria. At the order level, the abundances of Bifidobacteriales, Lactobacillales, Enterobacteriales, Pasteurellales, Rhodobacterales, and Bdellovibrionales were enriched while Selenomonadales was reduced by diCQAs. DiCQAs enhanced the abundances of 12 families, including Bifidobacteriaceae, Bacteroidacea, Porphyromonadaceae, and Rikenellaceae, while they inhibited Sreptococcaceae, Prevotellaceae, and Veillonellaceae. In addition , the LDA comparison at the OTU level is exhibited in Figure 7. The supplement of diCQAs altered the 10190


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Figure 5. LDA of microbial composition at the genus level (A, GLU vs GLUD; B, SUC vs SUCD; C, GOS vs GOSD; D, INL vs INLD).

relative abundances of 72 OTUs, including 59 OTUs that were raised and the other 13 lowered. The enhanced OTUs belonged to Bacteroides (OTU006, OTU002, OTU012, OTU021, OTU178, OTU023, OTU107, and OTU020), Alistipes (OTU085, OTU058, and OTU240), Bifidobacterium (OTU108 and OTU189), Oscillibacter (OTU069 and OTU050), Lachnospiracea incertae sedis (OTU017 and OTU052), Gemmiger (OTU032 and OTU035), Streptococcus (OTU059 and OTU040), and Clostridium sensu stricto (OTU114 and OTU090), and some other enriched genera included Escherichia/Shigella (OTU082), Romboutsia (OTU026), Veillonella (OTU127), Butyricimonas (OTU041), Phascolarctobacterium (OTU025), and Haemophilus

(OTU018). The OTUs with shortened abundance were derived from Prevotella (OTU007, OTU106, OTU015, and OTU005), Megamonas (OTU146 and OTU016), Faecalibacterium (OTU003 and OTU051), Anaerostipes (OTU065), Dialister (OTU013), Megasphaera (OTU109), Flavonifractor (OTU083), and Holdemanella (OTU132). The results are almost consistent at all the levels. Polyphenols are an important class of dietary bioactive compounds, and their impacts on intestinal microbiota both in vitro and in vivo have been reported in many cases. In the updated concept, phenolics have been considered as one kind of prebiotics that could be selectively utilized by host microorganisms and affect the microbiome.38 Prebiotics derived 10191


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Figure 6. LEfSe comparison of microbiota between diCQA-treated (CD) and nontreated (C) groups.

from Gemmiger, Alistipes and Bifidobacterium are beneficial to the proliferation of lean individuals, indicating their contributions to leanness.39 Notabaly, diCQAs exhibited a significant positive effect on the proliferation of Bifidobacteria. Bifidobacterium is a widely studied probiotic genus, and it plays an effective role in restoring intestinal homeostasis. It is able to reduce the risk and occurrence of obesity,40 and its abundance is negatively associated with the level of endotoxins in obese individuals.41 Its health-promoting mechanisms involve several actions, such as adhesion to the gut epithelium, production of beneficial metabolites, enhancement of the intestinal barrier, modulation of the immune response, and competitive exclusion of pathogens.42 Butyricimonas could convert glucose to isobutyrate and n-butyrate.43 Prevotella is related to individual high intake of dietary fibers due to its ability to degrade dietary fiber, but it is also associated with the metabolism level and proinflammation.44−46 In addition, a low concentration of phenolics could inhibit the growth of pathogens and promote the abundance of probiotics, while their high concentrations could contribute to the opposite effects.47 In previous studies, different kinds of culture conditions were utilized to investigate the effects of phenolics on microflora, especially by using the in vitro anaerobic fermentation model. In some cases, no carbohydrate was added,27,48 and solo carbohydrate conditions (only one carbon source or a mixture of several sugars) were employed in some other research.37,49 Carbohydrates have a huge impact on intestinal microbial communities and composition, but seldom has a study been done to account for their contributions during the investigations of the effects of other dietary components including polyphenols. In the perspective of our present data, the difference in carbohydrates (glucose, sucrose, α-GOS, and inulin) exerted much less influence than diCQAs on micro-

biota. In was roughly deduced that sugars with simple chemical structures could have a limited influence on the investigations of the impacts of phenolics on intestinal microbial profiles. However, it is still believed that polysaccharides with complicated structures and some complex carbohydrates have significant impacts on gut microbiota, especially some specific communities. For example, Akkermansia muciniphila, a bacterial species receiving extensive attention recently, could merely multiply with mucin polysaccharides as the carbon source.50 Effects of DiCQAs on the Production of SCFAs. The contents of SCFAs were analyzed, and the results are displayed in Table 2. Among all the SCFAs, acetic, propionic, and lactic acids were the most abundant organic acids, and the most noticed acid, butyric acid, also accounted for a certain proportion. In the conditions without any carbohydrate, diCQAs inhibited the production of all the detected organic acids and the amount of total acids (P < 0.05) except lactic acid, whose concentration was higher in BLKD than that in the BLK group (P < 0.05). In the conditions of respective carbohydrates added, diCQAs promoted the production of acetic and lactic acids (P < 0.05), and the difference was not significant (P > 0.05) between the groups with inulin as the carbon source (INL and INLD). The addition of diCQAs decreased the content of propionic acid in folds (P < 0.05), and the production of n-butyric acid was also reduced in all the carbohydrate conditions (P < 0.05). In addition, the BLK group showed the highest concentrations of isobutyric, n-butyric, and isovaleric acids (P < 0.05). The large intestine is the main site of humans to generate SCFAs, and the gut microbiota inhabiting the large intestine play a crucial role. The organic acids, including lactic, pyruvic, and acetic acids, derive from the fermentation of carbohydrates, and they could also be further converted to propionic and 10192


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Figure 7. LDA of microbiota between diCQA-treated (CD) and nontreated (C) groups at the OTU level.

longing to Firmicutes), and Bacteroides (Bacteroidetes), and the nine genus bacteria all have SCFA-producing potentials.55 In the previous literature, the reported butyrate-generating bacteria include Roseburia spp., Eubacterium spp., Anaerotipes spp., Coprococcus spp. (Lachnospiraceae), Clostridium spp. and Faecalibacterium prausnitzii (Clostridaceae); Bifidobacterium spp., Lactobacillus spp., and Bacteroides thetaiotaomicron, which have the capability to produce actate, and Roseburia sp., Veillonella spp., Ruminococcus spp., Bacteroides spp., Dialister spp., Phascolarctobacterium spp., Clostridium histolyticum, and Prevotella spp., which can generate propionate in the colon.56−59 In addition, acetate and lactate also could be further metabolized to butyric acid by intestinal microbiota.60,61 In the present study, it was found that diCQAs increased the abundances of the acetate-producing bacteria Bifidobacterium,

butyric acids by the microorganisms. The SCFAs have multiple functions in maintaining human health, and they could protect the intestinal mucosal barrier, decrease the inflammatory level, stimulate gastrointestinal motility, and function as epithelial nutrients and energy components. Butyrate is one of the most important microbial metabolites, and it is the main energy resource of colon epithelia and has the functions of regulating host gene expressions, cell differentiation, and apoptosis.51 Butyrate could also promote the differentiation of Treg cells in mice and attenuate the development of colitis.52 Acetic acid could promote the secretion of intestinal mucin,53 and propionic acid might play a crucial role in the regulation of appetite.54 The Chinese human gut “core microbiome” consists of Phascolarctobacterium, Roseburia, Blautia, Faecalibacterium, Clostridium, Subdoligranulum, Ruminococcus, Coprococcus (be10193


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Journal of Agricultural and Food Chemistry Table 2. Concentrations of Short-Chain Fatty Acids, Lactic Acid, and Total Acids (mM)a acetate OR BLK GLU SUC GOS INL BLKD GLUD SUCD GOSD INLD a

3.13 15.58 19.48 22.39 21.11 28.97 10.48 27.37 25.95 24.70 30.14

± ± ± ± ± ± ± ± ± ± ±

0.37 0.92 0.42 0.53 1.55 2.36 0.61 1.64 1.82 0.99 1.48

propionate a c d e de hi b gh fg f I

0.65 6.27 10.97 11.11 10.32 13.40 3.02 1.96 1.78 1.99 1.59

± ± ± ± ± ± ± ± ± ± ±

0.40 0.43 0.94 0.91 0.15 0.91 0.43 0.51 0.51 0.67 0.19

n-butyrate

isobutyrate a d e e e f c bc b bc ab

0.00 0.53 0.00 0.00 0.00 0.00 0.39 0.00 0.00 0.06 0.01

± ± ± ± ± ± ± ± ± ± ±

0.00 0.07 0.00 0.00 0.00 0.00 0.15 0.00 0.00 0.11 0.02

a c a a a a b a a a a

0.12 2.49 0.37 0.24 0.62 0.40 0.62 0.13 0.15 0.36 0.17

± ± ± ± ± ± ± ± ± ± ±

0.04 0.08 0.03 0.02 0.15 0.06 0.08 0.03 0.01 0.02 0.05

n-valerate

isovalerate a d b a c b c a a b a

0.00 1.80 0.07 0.04 0.06 0.07 1.33 0.07 0.04 0.01 0.08

± ± ± ± ± ± ± ± ± ± ±

0.00 0.10 0.01 0.05 0.02 0.05 0.37 0.11 0.07 0.01 0.07

a c a a a a b a a a a

0.00 0.53 0.81 0.02 0.04 0.14 0.00 0.01 0.00 0.00 0.00

± ± ± ± ± ± ± ± ± ± ±

0.00 0.09 0.12 0.03 0.02 0.02 0.00 0.02 0.00 0.00 0.00

lactate a c d a a b a a a a a

0.16 0.01 4.98 5.28 5.91 6.30 0.84 8.06 6.64 7.43 8.71

± ± ± ± ± ± ± ± ± ± ±

0.03 0.01 0.09 0.11 0.22 0.07 0.14 0.75 0.38 0.38 0.13

total acids a a c c d de b g e f h

4.06 27.21 36.69 39.07 38.06 49.28 16.69 37.60 34.56 34.56 40.70

± ± ± ± ± ± ± ± ± ± ±

0.78 1.42 0.97 1.29 1.60 3.33 1.24 1.90 2.70 1.83 1.18

a c de ef ef g b def d d f

The same letter means no statistical significance was observed in acid content between different groups (P > 0.05).

ORCID

propionate-producing Bacteroides, Veillonella, and Phascolarctobacterium, butyrate-producing Butyricimonas, and other SCFAgenerating communities, such as Lachnospiracea, Streptococcus, and Clostridium. Simultaneously, diCQAs reduced the abundances of propionate-producing Ruminococcus and Dialister, butyrate-producing Anaerostipes, and other SCFA-synthesis-related Megamonas and Prevotella. In terms of the SCFA contents and composition, diCQAs decreased the levels of propionate and butyrate and raised the concentrations of acetate and lactate; in the perspective of the microbial profile, the abundance of a certain organic acid-producing bacterium was not merely raised or decreased. Some of the specific acidgenerating communities were promoted by diCQAs, and some of the others were inhibited. The changes in the contents of the small molecular organic acids were attributed to diverse factors, and they were the converging results of multiple aspects. Besides the related abundances of SCFA-generating species, they were also associated with the absolute quantities and their contributions to the production to each acid. In addition, diCQAs not only altered the abundances of microbial communities, but also exhibited an impact on their metabolic pathways, though diCQAs could affect the synthesis, the conversion, and further the amounts of SCFAs. Altogether the effects of diCQAs on the production of SCFAs comprehensively resulted from multiple strategies and levels of contributing factors. Conclusively, diCQAs from I. kudingcha raised the intestinal microbial diversity in vitro and showed a more considerable impact than a carbon source on the microbial profile. DiCQAs increased the abundances of several genera, such as Bacteroides, Escherichia/Shigella, Bifidobacterium, Alistipes, and Butyricimonas, and decreased the abundances of Ruminococcus, Anaerostipes, Dialister, Megasphaera, Megamonas, and Prevotella. DiCQAs also affected the generation of SCFAs through gut microbiota. They raised the contents of acetic and lactic acids and reduced the production of propionic and butyric acids. In a word, diCQAs from I. kudingcha had significant modulating effects on intestinal microbiota, which suggested that diCQA had the potential to be developed as functional foods to improve human health and prevent disease through promoting gut health.

■

Shiyi Ou: 0000-0002-6779-0858 Xiaoxiong Zeng: 0000-0003-2954-3896 Funding

This work was supported by Grants-in-Aid for Scientific Research from the National Natural Science Foundation of China (31171666) and a project funded by the Priority Academic Program Development of Jiangsu Higher Education Institutions (PAPD). Notes

The authors declare no competing financial interest.

■

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Modulating Effects of Dicaffeoylquinic Acids from Ilex kudingcha on

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