Different Flavonoids Can Shape Unique Gut Microbiota Profile In Vitro

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1 Different Flavonoids Can Shape Unique Gut Microbiota Profile In Vitro Jiacheng Huang, Long Chen, Bin Xue, Qianyue Liu, Shiyi Ou, Yong Wang, and Xichun Peng Abstract: The impact of flavonoids has been discussed on the relative viability of bacterial groups in human microbiota. This study was aimed to compare the modulation of various flavonoids, including quercetin, catechin and puerarin, on gut microbiota culture in vitro, and analyze the interactions between bacterial species using fructo-oligosaccharide (FOS) as carbon source under the stress of flavonoids. Three plant flavonoids, quercetin, catechin, and puerarin, were added into multispecies culture to ferment for 24 h, respectively. The bacterial 16S rdna amplicons were sequenced, and the composition of microbiota community was analyzed. The results revealed that the tested flavonoids, quercetin, catechin, and puerarin, presented different activities of regulating gut microbiota; flavonoid aglycones, but not glycosides, may inhibit growth of certain species. Quercetin and catechin shaped unique biological webs. Bifidobacterium spp. was the center of the biological web constructed in this study. Keywords: Bifidobacteria, biological web, comparison, gut microbiota, polyphenols Introduction Human intestinal tract harbors a complex bacterial community named microbiota, integrated by more than 800 different bacterial species, which have a significant impact on the nutritional and health status of host. The metabolic activities conducted by gut microbiota contribute to the digestion of dietary compounds, salvage of energy, conversion of nutrients and transformation of xenobiotics. A balanced gut microbiota composition provides benefits to their host, and oppositely microbial imbalances are associated with metabolic and immune-mediated disorders (Inmaculada and others 2007; Santacruz and others 2009; Xu and others 2015). The composition of gut microbiota is regulated by both endogenous and environmental factors (diet, antibiotic intake, xenobiotics, and so on), Of which, the diet is considered a major driver for gut bacterial diversity changes. These changes may impact the relationships of bacteria and their host (Ley and others 2008). Polyphenols are important bioactive components in daily diet (Manach and others 2004; Cardona and others 2013). Polyphenols are usually categorized into 4 classes: hydroxycinnamic acids, flavonoids, hydrolytictannin, and oligomeric proantho cyanidins. Flavonoids play an important role in the prevention and treatment of some diseases (Eghbaliferiz and others 2016). Flavonoids are found in fruit, vegetables, grains, bark, roots, stems, flowers, tea, and wine (Jr 1998). Flavonoids widely exist in diets, supplements and natural products like herbal medicines. Epidemiological studies have shown that a flavonoid-rich diet is obviously associated with the decreased risk of various diseases. Pharmacological evidences also revealed that flavonoids display physiological activities like anti-oxidant, anti-allergic, anti-cancer, anti-inflammatory, anti-microbial and anti-diarrheal functions (Chen and others 2014). MS Submitted 3/14/2016, Accepted 7/2/2016. Authors are with Dept. of Science and Engineering, Jinan Univ., Guangzhou , China. Author Wang is also with Guangdong Engineering Research Center for Oil and Fat Biorefinery, Jinan Univ., Guangzhou , China. Direct inquiries to author Peng ( tpxchun@jnu.edu.cn). Authors Huang and Chen contributed equally to this work. Flavonoids can be classified into various groups on the basis of their molecular structures: flavones, isoflavones, flavanones, catechins and anthocyanins, etc. Many members in each of the groups are well known and abundantly present in food sources. Quercetin, catechin, and puerarin are flavonoids classified as flavones, catechins and isoflavones, respectively (Rice-Evans and others 1996; Nijveldt and others 2001). It is estimated that 90% to 95% of the total polyphenols intake can reach the colonic region without being absorbed (Etxeberria and others 2015). Therefore, flavonoids have also been speculated to have impact on the relative viability of gut bacteria (Hui and others 2006; Rastmanesh 2011), implying that dietary modulations with flavonoids may play a role in reshaping the gut microbial community and enhancing host microbial interactions to provide beneficial effects such as weight loss (Rastmanesh 2011). Previous studies showed the supplements of quercetin and catechin greatly impacted gut microbiota composition at different taxonomic levels (Hui and others 2006; John and others 2013; Etxeberria and others 2015). There is no reported study which investigated the effects of puerarin on gut microbiota in details, though the modulation of polyphenols on gut microbiota have been reported frequently reported in literatures (Rastmanesh 2011; Etxeberria and others 2015). Moreover, the effectiveness of various polyphenols on impacting gut microbiota hasn t been fully compared. It is necessary to study the changes of gut microbiota induced by polyphenols as well as the resulted impacts on human health. This study was conducted to compare the capabilities of quercetin, catechin, and puerarin on gut microbiota modulation in vitro. Furthermore, this research work sought to generate the biological web of gut bacteria with fructo-oligosaccharide (FOS) as carbon source under the stress of flavonoids. Materials and Methods Batch-culture fermentation of fecal bacteria Fermentation experiments were conducted using feces from a healthy male adult donor. The donor had not ingested antibiotics for at least 6 months before the study and had no history of gastrointestinal disorder. Samples were diluted by 1:10 (w/v) C 2016 Institute of Technologists R doi: / Further reproduction without permission is prohibited Vol. 00, Nr. 0, 2016 Journal of Science H1

2 Table 1 The detected OTUs at the level of phyla and percentage per total OTUs in each group. Phylum Con Q CAT P Actinobacteria ± ± a ± b ± (7.04%) (25.15%) (22.96%) (9.12%) Bacteroidetes ± ± a ± b ± a (41.74%) (23.09%) (11.59%) (23.51%) Firmicutes ± ± a ± b ± (21.32%) (25.11%) (19.64%) (23.62%) Fusobacteria ± ± ± a ± (0.77%) (0.30%) (0.10%) (1.74%) Proteobacteria ± ± ± a ± a (29.11%) (26.34%) (45.69%) (42.02%) Verrucomicrobia ± ± ± ± 0.84 a (0.02%) (0.01%) (0.01%) Only phyla (OTU%>0.01%) were listed. Means P < 0.05 and means P < 0.01 by comparing to Group Con. The labeled a and b presents the significant difference between the relative groups. Con: Group Con; CAT: Group CAT; P: Group P; Q: Group Q. with an anaerobic phosphate buffer (1 M; ph 7.2) and homogenized in a stomacher for 2 min. The resulting fecal slurry was used to inoculate batch-culture vessels. The protocol described by Tzounis and others (2008) was used for fecal fermentations with minor modification. Briefly, sixteen 50-mL plastic fermenter vessels were equally divided into 4 groups (Con, Q, CAT, and P). Each vessel was filled with 49.5 ml of a prereduced sterile medium (peptone water (2 g/l), yeast extract (2 g/ L), NaCl (0.1 g/l), K 2 HPO 4 (0.04 g/l), KH 2 PO 4 (0.04 g/l), NaHCO 3 (2 g/l), MgSO 4 7H 2 O (0.01 g/l), CaCl 2 6H 2 O (0.01 g/l), Tween 80 (2 ml/l), hemin (50 mg/l), vitamin K (10 μl/l), L- cysteine (0.5 g/l), bile salts (0.5 g/l), resazurin (1 mg/l), fructooligosaccharide (FOS) (10g/L), and distilled water). Quercetin, catechin and puerarin (Sigma-Aldrich Chemical Co., St. Louis, Mo., U.S.A.) were analytical grade, and were individually added into the above liquid media of Group Q, CAT, and P, 0.15g/L in each vessel. The medium was adjusted to ph 7.0. The vessels of Group Con were prepared without any polyphenols (negative control). Batch cultures were run in an anaerobic incubator for a period of 10 h. For this later analysis, samples were stored at 70 C until required. Extraction of DNA from cultures Genomic DNA from the aforementioned fecal bacteria in cultures were extracted from the cultures with a TaKaRa minibest bacterial genomic DNA extraction kit (TaKaRa, Dalian, China), according to the manufacturer s instructions. The final elution volume was 100 μl, and the concentration was determined by spectrophotometer (Beckman Coulter DU 800, Fullerton, Calif., U.S.A.). High-throughput 16S rdna gene sequencing of intestinal microbiota Theprimers F515 (59-CACGGTCGKCGGCGCCATT-39) and R806 (59-GGACTACHVGGGTWTCTAAT-39) were used to amplify the V 4 domain of bacterial 16S rdna (Caporaso and others 2011). PCR reactions contained 5 to 100 ng DNA template, 1 GoTaq Green Master Mix (Promega, Madison, Wis., U.S.A.),1mMMgCl 2, and 2 pmol of each primer. Reaction conditions consisted of an initial 94 C for 3 min followed by 35 cycles of 94 C for 45 s, 50 C for60s,and72 C for90s,and a final extension of 72 C for 10 min. All samples were amplified in triplicate and combined prior to purification. Amplicons were purified using the Qiaquick 96 kit (Qiagen) and quantified using PicoGreen dsdna reagent (Invitrogen, Grand Island, N.Y., U.S.A.) according to the manufacturers instructions. Purified libraries were sequenced on the Illumina GAIIx platform. 16S rdna gene analysis Raw Illumina fasta files were demultiplexed, quality-filtered, and analyzed using Quantitative Insights Into Microbial Ecology (QIIME) (Caporaso and others 2010). Sequences that were shorter than 55 bp, contained primer mismatches, ambiguous bases or uncorrectable barcodes, were removed. 16S rdna gene sequences were assigned to operational taxonomic units (OTUs) using UCLUST with a threshold of 97% pair-wise identity (Edgar 2010), and then classified taxonomically using the Ribosomal Database Project (RDP) classifier (Wang and others 2007). Alpha diversity estimates were calculated using Shannon value. Principal Coordinates Analysis (PCoA) was performed and the heat map was constructed to present the differences between the gut microbial communities of the 2 groups. The association of species was analyzed with the order of otu.association in the software of Mothur (Version v ) (Segata and others 2011; Parks and others 2014). Statistical analysis The statistical analysis was performed with SPSS 17.0 software (SPSS Inc., Chicago, Ill., U.S.A.). Results were presented as mean values with standard deviations. Two-tailed t-tests were conducted to compare the bacterial phenotypes in different vessels. Statistical significance was set at a P value of <0.05. All data are presented inthetextasthemeans± S.E.M. Results and Discussion Overall changed structure of gut microbiota by various polyphenols The detected OTUs at the level of phyla are listed in Table 1. Group Q, CAT, and P had different relative amount of OTUs from Group Con. The OTU abundance of Actinobacteria in Group Q and CAT are significantly higher than Group Con (P < 0.01), and that in Group Q significantly higher than that in Group CAT. All tested groups (Q, CAT, and P) presented a significantly lower OTUs amount of Bacteriodetes (P < 0.01), and Group CAT was the lowest. Group CAT also had the lowest OTU abundance of Firmicutes (P < 0.01) and Fusobacteria (P < 0.01), but Group Q had a higher OTU abundance of Firmicutes than the others (P < 0.01). The OTU abundance of Proteobacteria in Group CAT and P was higher than in Group Con and Q (P < 0.01). H2 Journal of Science Vol. 00, Nr. 0, 2016

3 The diversity of gut microbiota in 4 groups is described in Table 2. After 10 h fermentation, the values of Chao and ACE in Group P were significantly higher than that in Group Con, Q and P(P < 0.05); but the values of Simpson and Shannon in Group CAT are significantly lower than that in Group Con, Q and P (P < 0.01). The shared OTUs in different groups are presented in Figure. 1. All 4 groups shared 346 OTUs, 359 OTUS by Group Con and Q, 367 OTUs by Group Con and CAT, 373 OTUs by Group Con and P, 367 OTUs by Group Q and CAT, 372 OTUs by Group Q and P, 363 OTUs by Group CAT and P, 353 OTUs by Group Q, CAT, and P. Figure 1 The shared OTUs between 4 groups. Con: Group Con; CAT: Group CAT; P: Group P; Q: Group Q. Four samples in each group were analyzed. Difference of microbiota in various groups and various samples is further presented by principal components analysis (PCA) (Figure 2). Various samples in each group had similar distribution of bacteria except that of Group Con. The bacterial evolutionary relationships (BER) and changes at level of Genus between various groups are showed in Figure. 3. Samples of Group Q had approximate BER at level of Genus; samples of Group CAT also had close BER. But various samples of Group Q and Group Con had distant BER. The BER of Group Q was also distant from that of Group CAT. The relative contents (%) of detected bacteria in total bacteria from each group were listed in Table 3. The genera, Bacteroides, Parabacteroides, and Butyricimonas of Bacteroidetes phyla, had significantly lower relative abundances in Group Q (individually 18.4%, 3.6%, and 0.2%, P < 0.01), CAT (individually 8.8%, 2.1%, and 0.2%, P < 0.01) and P (individually 18.1%, 4.2%, 0.4%, P < 0.01 or 0.05) than that in Group Con, and especially in Group CAT its relative abundance was significantly lower than the others (3.9%, P < 0.01); the genus, Megasphaera of Firmicutes phyla, also presented the lowest relative abundance in Group CAT (P < 0.01). The relative abundance of many genera in various phyla were increased, including Bifidobacterium of Actinobacteria in Group Q (24.0%, P < 0.01) and CAT (21.7%, P < 0.01), Streptococcus and Faecalibacterium of Firmicutes in Group Q (4.2% and 0.6%, P < 0.01) and CAT (7.1% and 0.7, P < 0.01), an unknown genus of Firmicutes in Group Q (0.7%, P < 0.01) and P (0.6%, P < 0.05), an unknown genus of Proteobacteria phyla in Group CAT (44.4%, P < 0.01) and P (38.3%, P < 0.01). All bacteria survived in the intervention of flavonoids interacted and the network of interaction is presented in Figure 4. Some core genera can be read in Figure 4. Bifidobacterium spp. is the core and surrounded by Sulcia, Prevotella, Alistipes, Butyricimonas, Bacteroides, Parabacteroides, Odoribacter, Flavobacterium, Delftia, andlactobacillus based on the amount of joints. Figure 2 Difference of microbiota in various groups (Con, Q, CAT, and P) by principal components analysis (PCA). Con: Group Con; CAT: Group CAT; P: Group P; Q: Group Q. Four samples in each group were analyzed. Vol. 00, Nr. 0, 2016 Journal of Science H3

4 Table 2 Diversity index of gut microbiota. Groups Chao ACE Simpson Shannon Con ± ± ± ± 0.24 Q ± ± ± ± 0.24 CAT ± ± ± ± 0.20 P ± ± ± ± 0.27 Means P < 0.05; means P < The values of Ace and Chao index reflect the total OTUs in samples with different calculations; the value of Coverage index indicates the detected rate of bacteria; the values of Shannon and Simpson index present the diversity of microbiota, the high diversity with a higher value of Shannon and a lower value of Simpson. Regulation of 3 flavonoids on gut microbiota was compared by in vitro fermentation in this study. The 3 flavonoids presented different capabilities of shaping gut microbiota. Both quercetin and catechin had significantly stimulated the growth of Actinobacteria, and catechin posed a stronger effect; all 3 polyphenols inhibited the growth of Bacteroidetes, and catechin was also the most effective one. Catechin also suppressed the growth of Firmicutes and Fusobacteria. On the contrary, quercetin enhanced the growth of Firmicutes and Proteobacteria. Puerarin had promoted the growth of Fusobacteria and Proteobacteria, and it had significantly increased the community richness of microbiota. But after all, all 3 tested flavonoids decreased the diversity of microbiota, especially Catechin. All samples shared 346 OTUs and each flavonoid had its own impacted bacterial groups that were distinctive from the control and other samples. Both catechin and quercetin altered the composition of microbiota and generated distinct patterns, but puerarin did not. Some bacteria were considerably suppressed, such as Bacteriodetes, especially by catechin, but some others were significantly promoted, including Actinobacteria by quercetin and catechin, Proteobacteria by catechin and prerarin. Furthermore, Bifidobacterium spp. became the core of microbiota in fermenting Figure 3 Heatmap of microbiota at the level of Genus in different samples. (A) Group Con including A1-4; (B) Group Q including B1-4; (C) Group CAT including C1-4; and (D) Group P including D1-4. H4 Journal of Science Vol. 00, Nr. 0, 2016

5 Table 3 Bacterial relative content (%) in total bacteria of each group. Bacteria and its classification Phyla Class Order Family Genus Con Q CAT P Actinobacteria Actinobacteria Bifidobacteriales Bifidobacteriaceae Bifidobacterium Coriobacteriia Coriobacteriales Coriobacteriaceae Collinsella Bacteroidaceae Bacteroides a 8.8 b 18.1 a Porphyromonadaceae Parabacteroides a 2.1 b 4.2 a Bacteroidetes Bacteroidia Bacteroidales Prevotellaceae Prevotela Ordoibacteraceae Butyricimonas Odoribacdter Enterococcaceae Enterococcus Bacilli Lactobacillales Lactobacillaceae Lactobacillus Streptococcaceae Streptococcus Clostridiaceae Unknown Clostridium Unknown Lachnospiraceae Blautia Coprococcus Ruminococcus Firmicutes Clostridia Clostridiales Peptostreptococcaceae Unknown Unknown Ruminococcaceae Faecalibacterium Oscillospira Ruminococcus Veillonellaceae Megasphaera Phascolarctobacterium Erysipelotrichi Erysipelotrichales Erysipelotrichaceae Unknown Eubacterium Fusobacteria Fusobacteriia Fusobacteriales Fusobacteriaceae Fusobacterium Alphaproteobacteria Rhizobiales Brucellaceae Ochrobactrum Betaproteobacteria Burkholderiales Alcaligenaceae Sutterella Unknown Proteobacteria Gammaproteobacteria Enterobacteriales Enterobacteriaceae Klebsiella Halomonas Only the bacteria whose relative content were more than 0.1% were listed. FOS. Bifidobacterium genus covers many species and subspecies that can produce a diversity of enzymes hydrolyzing complex and nondigestible carbohydrate in gut, including some oligosaccharides and even plant fibers (Brandt and Barrangou 2016). Our results supported this opinion. The representative flavonoids with different structures (Byung- Hwan and others 2011; Lingyuan and others 2013; Song and others 2014) were compared since their abundant existence in plant originated food. The structures of quercetin and catechin are very similar, but they present distinguishable activities of regulating microbiota, and they shaped their unique composition of bacterial communities (Figure. 3). The structure of puerarin is a kind of isoflavone with a glucosyl group different from the other 2. Puerarin did not alter bacterial community significantly after 10 h fermentation. Our results are consistant with the viewpoint that flavonoid aglycones, but not their glycosides, may inhibit the growth of some intestinal bacteria (Duda-Chodak2012). Among 3 flavonoids, only catechin significantly lowered the community diversity of bacteria, but puerarin increased the community richness. The addition of quercetin neither significantly altered community diversity nor richness. The modulation effects of catechin and quercetin on gut microbiota were reported in many literatures (Alvarez and others 2006; Hui and others 2006;Duda-Chodak 2012; John and others 2013; Etxeberria and others 2015). But the relative mechanism was still lack of information. Puerarin did not reshape the bacterial community comparing to the control, even though it enhanced bacterial richness, which might be resulted by its glucosyl group (Duda-Chodak 2012). Specific phylotypes modulated by various polyphenols All samples shared 346 OTUs which may be generated by bacteria that could utilize FOS as energy and could survive the flavonoids stress. Three groups of tested flavonoids may also share a few species that might be contributed to the breaking down of flavonoids to carbon dioxide in the end (Bremner and others 2002). Anyone of flavonoids did not shape a microbiota community with exclusive bacterial species, but any 2 of them shared some common species. Therefore, if continuous ingestion of some special flavonoids by human, some unique bacteria will be trained out in gut and their function must be concerned. FOS can benefit the growth of Bifidobacterium spp. as prebiotics. But our results showed that the addition of quercetin and catechin can significantly stimulate the growth of Bifidobacterium spp., which is supported by previous studies (Yamakoshi and others 2001; Mar and others 2009; Gwiazdowska and others 2015). All flavonoids, especially catechin, in this study presented the strong inhibitory effect on Bacteriodes spp., which is consistent with other reports. Instead, catechin and puerarin also stimulated the growth of unknown genus in Proteobacteria phyla. The Proteobacteria are a major group (phylum) of gram-negative bacteria. They include a wide variety of pathogens, such as Escherichia, Salmonella, Vibrio, Helicobacter,andYersinia, and many other notable genera (Madigan and Martinko 2006). Since the stimulated genus is kept unknown, it still cannot conclude that the ingestion of catechin and puerarin will result in infection by pathogens. The enhanced growth of Bifidobacterium spp. and unknown genus of Proteobacteria phyla might reshape new constant communities with different bacteria. Vol. 00, Nr. 0, 2016 Journal of Science H5

6 Figure 4 The growth network of gut bacteria with FOS as carbon source under the stress of polyphenols. The association of species was analyzed with the order of otu.association in the software of Mothur (Version v ). The lines between species indicate their significant association, red lines for positive association and green lines for negative one. The linked points are different species differentiated with colored ovals. Development of new biological web of gut microbiota Our previous study reported that FOS cannot maintain the growth of Bifidobacterium spp. at a high level (Li and others 2015) in long term. We deduced when commensal or mutual bacteria of Bifidobacteriumspp. are regulated, the growth of Bifidobacterium spp. will also be affected (Li and others 2015). Emmanuel and others (2009) posed a mesocosm of Lactobacillus johnsonii, Bifidobacterium longum, and Escherichia coli in the mouse gut; Trosvik and others (2010) believed that ecological interactions happened in the web of an experimental gut microbiota including Bacteriodes thetaiotaomicron, Clostridium perfingens, E. coli, andb. logum. Inthisstudy, the biological web of microbiota was centered with Bifidobacterium spp. when fecal bacteria fermented FOS in vitro combined with the stress of 3 polyphenols, which will be attributed to further probe the pattern of Bifidobacterium spp. growth. Conclusion The 3 flavonoids, quercetin, catechin, and puerarin presented different activities of regulating gut microbiota; flavonoid aglycones, but not including their glycosides, may inhibit growth of some intestinal bacteria. Quercetin and catechin shaped their own biological web. Hence, if some special flavonoid aglycones are continuously ingested by human, some unique bacteria will be trained out in gut. In this study, the biological web of microbiota was centered with Bifidobacterium spp. Acknowledgments The program was supported by the funds of the National Natural Science Funds (No ) and the funds of the Fundamental Research Funds for the Central Universities (No ). We thank Ruixia Qiu from the Dept. of Science and Engineering, Jinan Univ., for their contribution to the experiments of this study. All authors report no conflicts of interest. Author Contributions J. Huang contributed to the conception of the study and interpreted the results. L. Chen performed the data analyses and wrote the manuscript. QY. Liu revised the manuscript. XC. Peng approved the final version. References Alvarez ML, Debattista NB, Pappano NB Synergism of flavonoids with bacteriostatic action against Staphylococcus aureus ATCC and Escherichia coli ATCC Biocell 30(1): Brandt K, Barrangou R Phylogenetic analysis of the bifidobacterium genus using glycolysis enzyme sequences. Front Microbiol 7:657. doi: /fmicb Bremner P, Bourne LC, Kuhnle G, Rechner AR, Hubbard GP, Moore KP, Riceevans CA The metabolic fate of dietary polyphenols in humans. Free Radical Bio Med 33(2): Byung-Hwan L, Tae-Joon S, Sung-Hee H, Sun-Hye C, Jiyeon K, Hyeon-Joong K, Chan- Woo P, Soo-Han L, Seung-Yeol N Quercetin inhibits α3β4 nicotinic acetylcholine receptor-mediated ion currents expressed in Xenopus oocytes. Korean J Physiol Pha 15(1): Caporaso JG, Kuczynski J, Stombaugh J, Bittinger K, Bushman FD, Costello EK, Fierer N, Peña AG, Goodrich JK, Gordon JI QIIME allows analysis of high-throughput community sequencing data. Nat Methods 7(5): Caporaso JG, Lauber CL, Walters WA, Berglyons D, Lozupone CA, Turnbaugh PJ, Fierer N, Knight R Global patterns of 16s rrna diversity at a depth of millions of sequences per sample. Proc Natl Acad Sci USA 108(25): H6 Journal of Science Vol. 00, Nr. 0, 2016

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