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Galectin-9 Induced by Dietary Prebiotics Regulates Immunomodulation to Reduce Atopic Dermatitis Symptoms in 1-Chloro-2,4-Dinitrobenzene (DNCB)-Treated NC/Nga Mice
1Department of Animal Resources Technology, Gyeongnam National University of Science and Technology, Jinju 52725, Republic of Korea 2Department of Animal Science, Chonnam National University, Gwangju 61186, Republic of Korea 3Department of Animal Science and Biotechnology, Gyeongnam National University of Science and Technology, Jinju 52725, Republic of Korea 4Department of Biochemistry, Institute of Cell Differentiation and Aging, College of Medicine, Hallym University, Chuncheon 24252, Republic of Korea 5Department of Nano-Bioengineering, Incheon National University, Incheon 22012, Korea 6Department of Animal Science and Technology, Sunchon National University, Sunchon 57922, Republic of Korea 7Department of Agricultural Biotechnology and Research Institute of Agriculture and Life Sciences, Seoul National University, Seoul 08826, Republic of Korea 8Department of Life Science, Silla University, Busan 46958, Republic of Korea
Correspondence to:J. Microbiol. Biotechnol. 2020; 30(9): 1343-1354
Published September 28, 2020 https://doi.org/10.4014/jmb.2005.05017
Copyright © The Korean Society for Microbiology and Biotechnology.
Abstract
Keywords
Graphical Abstract
Introduction
Atopic dermatitis (AD) is a chronic and inflammatory autoimmune disorder that results in severe itch and eczematous skin lesions [1]. The development of autoimmune disorders is associated with a defective immune system, loss-of-function variants of the epidermal barrier protein filaggrin [2], and disruption of the gut microbial community. In AD, the immunological imbalance between type 1 and type 2 helper T cells (Th1 and Th2 cells, respectively) results in an increase in antigen-specific IgE levels mediated via cytokines such as IL-4, IL-5, and IL- 14 [3-5].
Recent findings suggested that intestinal resident microorganisms play an important role in regulating the gut mucosal immune system and protection against pathogen invasion [6]. Microbial dysbiosis due to diet or antibiotic treatment, infection, and metabolic alteration results in serious health problems including intestinal inflammation [7]. In particular, loss of microbial diversity has a substantial impact on chronic inflammatory skin diseases [4].
Prebiotics are food ingredients selectively metabolized by gut bacteria, and they stimulate the growth of beneficial microorganisms [8], resulting in changes in the composition of intestinal microorganisms [9]. Fructo- oligosaccharides (FOS), inulin, beta-glucan, and galacto-oligosaccharides (GOS) represent sources of prebiotic dietary fiber [10]. Exposure to a mixture of short chain GOS (scGOS) and ling chain FOS (lcFOS) reduces the incidence of AD. In addition, prebiotics improve the symptoms of AD and facilitate the induction of innate responses such as toll-like receptor agonists and cytokines [11, 12]. However, the effects of prebiotic dietary fiber on AD-like skin lesions in mice and alterations in gut microbiota have yet to be investigated.
Thus, in the present study, we investigated whether prebiotics can reduce the symptoms of 1-chloro-2,4- Dinitrobenzene (DNCB)-induced AD-like skin lesions in NC/Nga mice by changing the gut microbiota and elucidated the underlying immune mechanism.
Materials and Methods
Animals
Five-week-old male NC/Nga mice (Central Lab, Animal Inc., Republic of Korea) were maintained at room temperature (22 ± 1°C), with a 12-h light–dark cycle during the experimental period and were provided ad libitum access to food (AIN-76A; Central Lab) and water. Mice were fed with scGOS (Neo Cremar Co., Republic of Korea)/lcFOS (Cell Biotech Co., Republic of Korea) at a ratio of 9:1 to 1% of the diet, and inulin (Vixxol Co., Republic of Korea) and β-glucan (Glucan Co., Republic of Korea) were supplemented at a rate of 1% of the diet. Zyrtec (0.2 mg/kg) (KyungDong Pharm Co., Republic of Korea) was provided in the daily diet as a positive control to alleviate symptoms of atopic dermatitis. After a one-week preliminary experimental period and a four-week AD induction period, the experimental animals were randomly divided into six groups with 6 animals per group: (1) Untreated control group (C: basal diet), (2) AD control group (N: basal diet + DNCB-induced group), (3) Positive control group (P: basal diet + Zyrtec + DNCB-induced group), (4) scGOS/lcFOS group (T1: basal diet + scGOS/lcFOS + DNCB-induced group), (5) inulin group (T2: basal diet + inulin + DNCB-induced group), and (6) β-glucan group (T3: basal diet + β-glucan + DNCB-induced group). The experimental protocol was approved by the Institutional Animal Care Board of Gyeongnam National University of Science and Technology (Approval No. 2017-8).
AD Model
According to the method described by Shin
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Fig. 1.
Effect of prebiotics on DNCB-induced AD-like symptoms in NC/Nga mice. (A ) Experimental design (B ) DNCB-induced AD-like skin lesions and spleen size. (C ) Spleen size-to-body weight ratio was evaluated. (D ) The dermatitis score of AD-like skin lesions was measured to evaluate itch, erythema/hemorrhage, scaling/dryness, edema, and excoriation/ erosion. C: Control, N: Negative control (DNCB-induced), P: Zyrtec positive control (DNCB-induced + Zyrtec), T1: scGOS/ lcFOS (DNCB-induced + scGOS/lcFOS), T2: Inulin (DNCB-induced + Inulin), T3: β-glucan (DNCB-induced + β-glucan); *p < 0.05 versus control group; **p < 0.01 versus control group; #p < 0.05 versus negative control group; ##p < 0.01 versus negative control group. Data represent means ± SD of 5 replicates.
Evaluation of AD
The AD severity score was assessed visually once a week after 4 weeks of DNCB treatment. Scores of 0 (none), 1 (mild), 2 (moderate), and 3 (severe) were measured for each of the four symptoms: erythema/hemorrhage, scarring/dryness, edema, and excoriation/erosion. The sum of the individual scores indicating clinical severity represented the dermatitis score.
Separation and Analysis of RNA from Mouse Mesenteric Lymph Nodes (MLN)
To evaluate the immunomodulatory effects of prebiotics, atopic-induced NC/Nga mice were sacrificed. The mesenteric lymph node (MLN) and spleen were separated. TRIzol was added to the MLN of NC/Nga mice and homogenized using SilentCrusher M (Heidolph, Germany). According to the method presented by Chomczynski and Sacchi [14], RNA was extracted and stored at -20°C until cDNA synthesis. The cDNA was synthesized using reverse transcription-polymerase chain reaction (RT-PCR) kits (TaKaRa Co., Japan) according to the manufacturer’s instructions. The primer sequences are listed in Table 1 [15-19]. Glyceraldehyde-3-phosphate dehydrogenase (GAPDH) was used as the reference gene.
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Table 1 . RT-PCR primer sequences for the analysis of immunomodulatory genes.
Target gene Primer Reference GAPDH Forward 5’ CCACCCAGAAGACTGTGGAT 3’ 15 Reverse 5’ CACATTGGGGGTAGGAACAC 3’ T-bet Forward 5’ TCAACCAGCACCAGACAGAG 3’ 16 Reverse 5’ AAACATCCTGTAATGGCTTGTG 3’ GATA-3 Forward 5’ CATTACCACCTATCCGCCCTATG 3’ 16 Reverse 5’ CACACACTCCCTGCCTTCTGT 3’ RORγT Forward 5’ TTCACCCCACCTCCACTG 3’ 16 Reverse 5’ TGCAAGGGATCACTTCAATTT 3’ Foxp3 Forward 5’ CCCATCCCCAGGAGTCTTG 3’ 17 Reverse 5’ CCATGACTAGGGGCACTGTA 3’ INF-γ Forward 5’ TCAAGTGGCATAGATGTGGAAGAA 3’ 17 Reverse 5’ TGGCTCTGCAGGATTTTCATG 3’ IL-4 Forward 5’ ACAGGAGAAGGGACGCCAT 3’ 17 Reverse 5’ GAAGCCCTACAGACGAGCTCA 3’ IL-17 Forward 5’ TTCATCTGTGTCTCTGATGCT 3’ 17 Reverse 5’ TTGACCTTCACATTCTGGAG 3’ TGF-β Forward 5’ GAAGGCAGAGTTCAGGGTCTT 3’ 17 Reverse 5’ GGTTCCTGTCTTTGTGGTGAA 3’ Galectin-9 Forward 5’ GAGAGGAAGACACACATGCCTTTC 3’ 18 Reverse 5’ GACCACAGCATTCTCATCAAAACG 3’ Filaggrin Forward 5’ CACTGAGCAAAGAAGAGCTGAA 3’ 19 Reverse 5’ CGATGTCTTGGTCATCTGGA 3’ TSLP Forward 5’ AGAGAAGCCCTCAATGACCAT 3’ 19 Reverse 5’ GGACTTCTGTGCCATTTCC 3’
Western Blot Analysis
Whole cell extracts were prepared with RIPA lysis buffer (150 mM NaCl, 1% NP-40, 0.1% SDS, 1% sodium deoxycholate, 50 mM Tris [pH 8.0]) containing 1 mM NaF, 1 mM Na3VO4, and protease inhibitors. Proteins were quantified using the Bradford assay reagent (Bio-Rad) according to the manufacturer’s instructions. Proteins (20– 40 μg) were separated by 10% sodium dodecyl sulfate-polyacrylamide gel electrophoresis and transferred to polyvinylidene fluoride membranes (EMD Millipore, USA). Membranes were blocked with 5% nonfat milk and incubated with the following antibodies: Galectin-9 (ab194338; 1:1000 dilution; Abcam), TLR 9 (ab134368, 1:1000dilution; Abcam), and GAPDH (#2118, 1:10,000; Cell Signaling). Membranes were then incubated with horseradish peroxidase-conjugated secondary antibodies and visualized with Immobilon Western Chemiluminescent HRP Substrate (EMD Millipore).
Cell Lines and Culture Conditions
The human colorectal adenocarcinoma cell line HT29 was purchased from the American Type Culture Collection (ATCC) and maintained in RPMI1640 with stable glutamine (Biowest) enriched with 10% fetal bovine serum (FBS)(Biowest), 1% penicillin/streptomycin (Welgene), and 25 mM HEPES (Shimakyu Co., Ltd., Japan), 25 mM NaHCO3 (Shimakyu Co., Ltd.,) at 37°C with 5% CO2. Isolated MNL lymphocytes were cultured in RPMI 1640 with L-glutamine and sodium bicarbonate (Sigma), 10% FBS (Biowest), 1% penicillin/streptomycin (Welgene), and 0.05 mM 2-β-mercaptoethanol (Sigma) at 37°C in the presence of 5% CO2. For western blot analysis, Gos/Fos, inulin, and β-glucan were treated in the presence of 0, 0.25, 0.5, 1, 2, 5 % w/v, respectively for 12 h.
Analysis of Gut Microbiota
On the last day of the experiment, the NC/Nga mice were sacrificed and fecal samples were collected from them and stored at -80°C until being used for genomic DNA (gDNA) extraction. DNA was extracted using fecal DNA MiniPrep kits (Zymo Research, USA), and the sequences were analyzed using Illumina MiSeq (ChunLab, Inc., Republic of Korea).
Processing of Sequencing Data
The pyrosequencing data for the 16S rRNA gene sequences were processed as we described previously (Kim
Quantitative Real-Time PCR
As mentioned above, DNA was extracted from NC/Nga mice fecal samples. Quantitative PCR (qPCR) was performed using Rotor-Gene SYBR Green PCR Kits (QIAGEN GmbH, Germany). The primer sequences of the microorganisms used for qPCR analysis are listed in Table 2 [20-23]. Universal Reference Gene (URG) method was used.
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Table 2 . qPCR primer sequences for the analysis of beneficial bacteria.
Target microorganism Primer Reference Universal Forward 5’ GTGSTGCAYGGYYGTCGTCA 3’ 20 Reverse 5’ ACGTCRTCCMCNCCTTCCTC 3’ Ruminococcus spp.Forward 5’ GGCGGCYTRCTGGGCTTT 3’ 21 Reverse 5’ CCAGGTGGATWACTTATTGTGTTAA 3’ Roseburia spp.Forward 5’ GCGGTRCGGCAAGTCTGA 3’ 21 Reverse 5’ CCTCCGACACTCTAGTMCGAC 3’ Faecalibacterium prausnitzii Forward 5’ GGAGGAAGAAGGTCTTCGG 3’ 21 Reverse 5’ AATTCCGCCTACCTCTGCACT 3’ Bifidobacterium spp.Forward 5’ TCGCGTCYGGTGTGAAAG 3’ 22 Reverse 5’ GGTGTTCTTCCCGATATCTACA 3’ Lactobacillus sakei Forward 5’ CCATGTGTAGCGGTGAAATG 3’ 23 Reverse 5’ ATCCTGTTTGCTACCCATGC 3’ Leuconostoc mesenteroides Forward 5’ TGATGCATAGCCGAGTTGAG 3’ 23 Reverse 5’ GAAAGCCTTCATCACACACG 3’ Leuconostoc citreum Forward 5’ GGAAACAGATGCTAATACCGAATA 3’ 23 Reverse 5’ TTTACCCCACCAACTAACTAATG 3’ Weissella cibaria Forward 5’ GGGAAACCTACCTCTTAGCA 3’ 23 Reverse 5’ GGACCATCTCTTAGTGATAGCA 3’ Weissella koreensis Forward 5’ GGGCTACACACGTGCTACAA 3’ 23 Reverse 5’ GATTCCGACTTCGTGTAGGC 3’
Statistical Analysis
The variance of the results obtained via repeated experiments was analyzed using SPSS 12.0 (SPSS, Inc., USA). The significance of the results was tested using Duncan’s multiple range test at
Results
Allergic Symptoms in Mice
To investigate the effects of prebiotics on DNCB-induced AD symptoms in mice, the mice were treated with scGOS/lcFOS (T1), inulin (T2), or β-glucan (T3) once a week for six weeks (Fig. 1A). Body weight and body weight gain were decreased in the DNCB-induced AD control (N), scGOS/lcFOS (T1), and inulin (T2) groups compared with the untreated control (C) group. However, positive control (P) and β-glucan (T3) groups showed no significant decrease in body weight and body weight gain (Supplemental File). Furthermore, average daily dietary feed intakes (ADFI) were not different between the treatments (Supplemental File). Feed efficiency decreased with all treatments except in the β-glucan groups (T3) compared with untreated control (C) group (Supplemental File).
DNCB-induced AD control mice (N) showed red spots, edema, and bleeding. Prebiotic (T1-T3) and Zyrtec (P) groups showed a clear decrease in these symptoms (Fig. 1B). Because AD influences the weight of immune organs such as the spleen by modulating various immune responses [24], we next investigated the effect of these prebiotics on spleen weight in the AD mouse model. A decrease in spleen weight was observed in the Zyrtec (P) and inulin (T2) groups compared with the DNCB-induced AD control (N) group (Fig. 1C). Skin lesions were determined according to the SCORAD index to confirm the effect of prebiotics on AD. The index was not clearly different between the DNCB-induced AD control (N) and prebiotic (T1–T3) groups at 3 weeks. However, positive control (P) and prebiotic (T1~T3) groups showed a gradual decrease in the index at 6 weeks compared with that of the DNCB-induced AD control (N) group (Fig. 1D).
T Cell Immune Responses and Skin Barrier-Related Gene Expression
In order to examine the effects of prebiotics on the T cell populations including Th1, Th2, Th17, and Treg, we analyzed the mRNA expression of their specific transcription factors and cytokines such as T-bet, GATA3, RORγt, Foxp3, interferon (IFN)-γ, interleukin(IL)-4, IL-17, and TGF-β, respectively, in the mesenteric lymph nodes (MLN) derived from the DNCB-induced AD mouse model. The AD control (N) group showed a significant decrease in the mRNA expression of IFN-γ and Foxp3, which are transcription factors of Th1 and Treg, respectively, compared with the untreated control (C) group. The prebiotic (T1~T3) and Zyrtec (P) groups clearly showed an increase in mRNA expression of Th1 and Treg-specific transcription factors and cytokines such as T- bet, IFN-γ, Foxp3, and TGF-β compared with the DNCB-induced AD control (N) group (Figs. 2A and 2D). However, treatments with prebiotics (T1~T3) induced a significant decrease in the mRNA expression of Th2- specific transcription factor GATA3 and cytokine IL-4, which were increased in the DNCB-induced AD control (N) (Fig 2B). RORγt, a Th17 transcription factor associated with acute AD [25], was markedly reduced in prebiotic (T1~T3) groups (Fig. 2C). However, no change in IL-17 expression was detected between the different treatments.
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Fig. 2.
Effect of prebiotics on the expression of transcription factors and cytokines. T-cell polarization in mesenteric lymph nodes (MLN) was evaluated by analyzing the expression of T-bet, IFN-γ (Th1, A), GATA-3, IL-4 (Th2, B), RORγT, IL-17 (Th17, C) and Foxp3, TGF-β (Treg, D). C: untreated control, N: AD control (DNCB-induced), P: Zyrtec-positive control (DNCB-induced + Zyrtec), T1: scGOS/lcFOS (DNCB-induced + scGOS/lcFOS), T2: Inulin (DNCB-induced + Inulin), T3: β-glucan (DNCB-induced + β-glucan); *p < 0.05 versus control group, **p < 0.01 versus control group, #p < 0.05 versus negative control group, ##p < 0.01 versus negative control group. Data represent means ± SD of 4 replicates.
The development of allergic symptoms is regulated by a balance between Th1/Treg and Th2 cell populations. It is known that galectin-9 alleviates the allergic symptoms by promoting Th1/Treg cell differentiation, while thymic stromal lymphopoietin (TSLP) aggravates the symptoms via differentiation of naïve cells into Th2 cells [13].
The DNCB-induced AD control (N) group showed a marked decrease in the mRNA expression of galectin-9 compared with the untreated control (C) group, which was significantly increased after prebiotic (T1–T3) treatment. However, the level of TSLP mRNA was dramatically increased in the AD (N) group compared with the untreated control (C) group and decreased in the prebiotic (T1–T3) groups. We next analyzed the expression of the filaggrin gene, which is associated with skin barrier function and decreased AD symptoms [26]. The mRNA level of filaggrin was significantly decreased in the DNCB-induced AD control (N) compared with the untreated control (C) group, and was increased in the inulin (T2) group. These results indicate that prebiotics regulate the immune function by balancing the levels of Th1, Th2, and Treg cells, and decrease Galactin-9, which increases Th1 and Treg cell differentiation, and TSLP, which increases Th2 cell differentiation, indicating amelioration of AD symptoms (Fig. 3).
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Fig. 3.
Effect of prebiotics on the expression of galectin-9, filaggrin, and TSLP in the mesenteric lymph nodes (MLN). C: Untreated control, N: AD control (DNCB-induced), P: Zyrtec-positive control (DNCB-induced + Zyrtec), T1: scGOS/lcFOS (DNCB-induced + scGOS/lcFOS), T2: Inulin (DNCB-induced + Inulin), T3: β-glucan (DNCB-induced + β- glucan); *p < 0.05 versus control group, **p < 0.01 versus control group, #p < 0.05 versus negative control group, ##p < 0.01 versus negative control group. Data represent means ± SD of 4 replicates.
TLR-9 and Galactin-9 Protein Expression Levels in HT29 Cell Lines
TLR9 enhances Th1 and Treg cell populations via IFN-γ, resulting in the prevention and treatment of allergic diseases [27]. Thus, we analyzed the protein expression of TLR-9 and galectin-9 after treatment with prebiotics in intestinal epithelial cells (HT-29 cells) (Fig. 4). Prebiotic treatments resulted in increased protein expression of TLR-9 and galectin-9 in HT-29 cells in a concentration-dependent manner. Thus, scGOS/lcFOS, inulin, and β- glucan are immunomodulated via activation of galectin-9 and TLR-9.
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Fig. 4.
Prebiotics increase TLR-9 and Gal-9 protein expression in HT29 cell lines (A, B, C). Western blot analysis showed a dose-dependent increase in TLR-9 and Gal-9 protein levels in HT29 cells following treatment with scGOS/lcFOS (9:1 w/v mixture), inulin, and β-glucan for 12 h, respectively.
Diversity Analysis of Gut Microbiota
In the early stages of life, dysbiosis in the intestinal microbiome is the main cause of allergic diseases [28, 29]. Therefore, we analyzed the diversity of fecal microbiota in mice via 16S rRNA gene sequencing (Table 3 and Figs. 5A and 5B). The prebiotics (T1-T3) increased the intestinal microbial diversity compared with AD (N) and Zyrtec (P) groups (Table 3). In addition, intestinal microbial diversity was significantly increased in the scGOS/ lcFOS (T1) and inulin (T2) groups at the species level compared with the untreated control (C) group (Table 3). The Chao1 index indicated that the richness of intestinal microbiota in the group treated with prebiotics (T1-T3) was significantly increased compared with negative (N) and positive control (P) groups (Fig. 5A). The Shannon index showed that the inulin (T2) group had higher microbial diversity than the other groups (Fig. 5B).
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Table 3 . Effects of dietary prebiotic supplementation on diversity of fecal microbiota in mice.
Items Treatments C N P T1 T2 T3 Genus 237 (2) 189 (12)** 187 (4)** 256 (23)## 250 (13)## 242 (9)## Species 660 (20) 553 (10)** 554 (16)** 765 (51)**## 772 (22)**## 748 (73)## C: Untreated control, N: AD control (DNCB-induced), P: Zyrtec-positive control (DNCB-induced + Zyrtec), T1: scGOS/lcFOS (DNCB-induced + scGOS/lcFOS), T2: Inulin (DNCB-induced + Inulin), T3: β-glucan (DNCB-induced + β-glucan); *
p < 0.05 versus control group; **p < 0.01 versus control group; #p < 0.05 versus negative control group; ##p < 0.01 versus negative control group. Data represent means ± SD of 4 replicates.
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Fig. 5.
Intestinal microbiota richness and diversity was increased with prebiotic treatment. (A ) Richness, (B ) Diversity, and (C) Principal coordinate analysis (PcoA) of community structures using a Fast UniFrac distance matrix. C: Untreated control, N: AD control (DNCB-induced), P: Zyrtec-positive control (DNCB-induced + Zyrtec), T1: scGOS/lcFOS (DNCB-induced + scGOS/lcFOS), T2: Inulin (DNCB-induced + Inulin), T3: β-glucan (DNCB-induced + β-glucan). Percentage of variation explained by principal component 1 (PC1): 46.726%; percentage of variation explained by principal component 2 (PC2): 14.962%; percentage of variation explained by principal component 3 (PC3): 6.865%. *p < 0.05 versus control group, **p < 0.01 versus control group, #p < 0.05 versus negative control group, ##p < 0.01 versus negative control group. Data represent means ± SD of 4 replicates.
Principal Coordinate Analysis (PCoA) Analysis of Gut Microbiota
The overall structural changes of the intestinal microbiota were then analyzed using principal coordinate analysis (PCoA). The PcoA plots showed that microbial communities from untreated control (C) and inulin (T2) groups, scGOS/lcFOS (T1) and β-glucan (T3) groups, AD control (N) and Zyrtec (P) groups were similar to each other (Fig. 5C), which indicates that prebiotics alleviate AD via changes in the intestinal microbial community. The Zyrtec (P) group showed a microbial community structure similar to that of AD control (N) group, suggesting that Zyrtec has no attenuating effect on AD symptoms due to intestinal microbial changes. These results suggest that changes in intestinal microbial communities may affect the induction and mitigation of AD.
Analysis of Intestinal Microbial Changes in Mice
Intestinal microorganisms constitute the immune system, and affect the incidence of various diseases, including AD [30]. Therefore, the effects of prebiotics on changes in gut microbiota were analyzed (Table 4). In general, an increase in
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Table 4 . Pyrosequencing analysis of fecal microbiota composition in mice fed with prebiotics.
Items Treatments C N P T1 T2 T3 mean % (SD) mean % (SD) mean % (SD) mean % (SD) mean % (SD) mean % (SD) Firmicutes (p) 81.38 (3.34) 87.82 (1.29)* 79.52 (2.22)## 63.59 (5.68)**## 76.12 (7.89)# 63.58 (6.21)**## Clostridia (c) 65.67 (8.08) 83.05 (3.59)** 78.24 (0.83)*# 55.26 (7.32)## 74.33 (7.48) 56.45 (3.06)## Lachnospiraceae (F) 42.76 (7.83) 70.47 (2.96)** 69.38 (2.08) 39.89 (3.06)## 47.37 (4.82)## 30.39 (6.62)## Eisenbergiella (G) 7.89 (1.37) 7.53 (0.54) 7.98 (1.38) 8.91 (2.65) 14.14 (1.74)**## 5.45 (1.18)*# Ruminococcaceae (F) 21.78 (4.98) 9.12 (0.59)* 8.93 (0.77)** 18.46 (3.91)# 20.54 (3.47)## 21.77 (3.72)## Ruminococcus (G) 1.91 (0.67) 0.00 (0.00)* 0.00 (0.00)* 2.98 (0.66)## 3.02 (0.72)## 2.57 (1.30)# Bacilli (c) 14.82 (8.22) 4.66 (4.80) 1.11 (1.73)* 4.26 (3.84) 5.02 (4.11) 2.94 (1.47) Lactobacillaceae (F) 20.63 (7.96) 2.00 (1.52)** 0.32 (0.26)* 5.77 (3.35)* 4.32 (1.43)* 2.78 (1.42)** Lactobacillus (G) 19.86 (7.69) 1.97 (1.49)** 0.31 (0.26)*# 5.53 (3.17)* 4.11 (1.37)* 2.66 (1.32)* Bacteroidetes (p) 16.81 (3.77) 9.22 (1.79)* 16.41 (2.42)## 33.47 (5.26)**## 21.56 (7.96)# 31.89 (9.12)*## Bacteroidia (c) 16.80 (3.78) 9.22 (1.79)* 16.40 (2.42)## 33.47 (5.27)**## 16.22 (4.89)# 31.88 (9.11)*## Prevotellaceae (F) 0.71 (0.09) 0.52 (0.20) 0.85 (0.11)# 26.02 (6.74)**## 2.52 (2.00) 26.09 (8.54)*## Prevotella (G) 0.67 (0.08) 0.15 (0.01)** 0.40 (0.16)*# 24.47 (6.26)**## 2.28 (1.76) 24.41 (8.23)*# S24-7_f(F) 8.59 (1.89) 4.82 (1.59)* 6.97 (0.83) 7.08 (1.56) 7.64 (0.59)# 4.51 (1.59)* C: Untreated control, N: AD control (DNCB-induced), P: Zyrtec-positive control (DNCB-induced + Zyrtec), T1: scGOS/lcFOS (DNCB-induced + scGOS/lcFOS), T2: Inulin (DNCB-induced + Inulin), T3: β-glucan (DNCB-induced + β-glucan); *
p < 0.05 versus control group; **p < 0.01 versus control group; #p < 0.05 versus negative control group; ##p < 0.01 versus negative control group. Data represent means ± SD of 4 replicates.
Immunomodulatory Effects by Intestinal Microbial
Groups of intestinal microorganisms such as
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Table 5 . Clostridia cluster analysis of fecal microbiota in mice fed with prebiotics.
Items Treatments C N P T1 T2 T3 mean % (SD) mean % (SD) mean % (SD) mean % (SD) mean % (SD) mean % (SD) Clostridia cluster XIVa Genus Ruminococcus 0.969 (0.526) 0.000 (0.000)* 0.000 (0.000)* 2.985 (0.661)**## 3.021 (0.718)**## 2.570 (1.300)# Roseburia 0.569 (0.238) 0.507 (0.325) 0.172 (0.060)* 0.249 (0.108) 0.648 (0.251) 0.221 (0.093)* Species Roseburia 0.010 (0.008) 0.000 (0.000) 0.000 (0.000) 0.029 (0.032) 0.174 (0.172) 0.009 (0.011) intestinalis Lachnospira 0.002 (0.003) 0.000 (0.000) 0.000 (0.000) 0.036 (0.033) 0.182 (0.206) 0.309 (0.217) pectinoschiza Ruminococcus 0.005 (0.001) 0.000 (0.000)** 0.001 (0.002)* 0.033 (0.044) 0.018 (0.019) 0.006 (0.010)*## lactaris Coprococcus 0.004 (0.003) 0.002 (0.003) 0.000 (0.000) 0.009 (0.003)# 0.006 (0.002) 0.014 (0.013) comes Clostridium 0.008 (0.006) 0.002 (0.001) 0.007 (0.002)## 0.004 (0.002) 0.002 (0.003) 0.002 (0.002) symbiosum Clostridia cluster IV Genus Anaerofilum 0.009 (0.004) 0.000 (0.000)* 0.003 (0.001)*## 0.393 (0.381) 0.029 (0.017)# 0.054 (0.071) C: Untreated control, N: AD control (DNCB-induced), P: Zyrtec-positive control (DNCB-induced + Zyrtec), T1: scGOS/lcFOS (DNCB-induced + scGOS/lcFOS), T2: Inulin (DNCB-induced + Inulin), T3: β-glucan (DNCB-induced + β-glucan); *
p < 0.05 versus control group; **p < 0.01 versus control group; #p < 0.05 versus negative control group; ##p < 0.01 versus negative control group. Data represent means ± SD of 4 replicates.
Functional Bacteria Analysis by qPCR
Next, we used qPCR to investigate the changes in intestinal populations of functional microorganisms (Fig. 6). We found that the levels of butyrate-producing microorganisms
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Fig. 6.
Measurement of the abundance of functional bacteria in the feces of prebiotic-treated groups by quantitative PCR. (A ,B ) Butyrate-producing bacteria; (C -F ) lactic-acid bacteria; C: Untreated control, N: AD control (DNCB-induced), P: Zyrtec-positive control (DNCB-induced + Zyrtec), T1: scGOS/lcFOS (DNCB-induced + scGOS/lcFOS), T2: Inulin (DNCB-induced + Inulin), T3: β-glucan (DNCB-induced + β-glucan); *p < 0.05 versus control group, **p < 0.01 versus control group, #p < 0.05 versus negative control group, ##p < 0.01 versus negative control group. Data represent means ± SD of 4 replicates.
Discussion
In this study, we investigated the effects of prebiotics on the development of AD. In order to establish an AD mouse model, we treated the dorsal skin of NC/Nga mice with DNCB and detected the generation of AD-like skin lesions, such as red spots, edema, and bleeding. We found that prebiotic supplementation resulted in suppression of AD symptoms via reduction in spleen weight and SCORAD index. Increased spleen weight is associated with AD symptoms [36]. Recent studies suggested that AD is triggered by an imbalance between Th1, Th2, and Treg cell-related immune responses [37]. Abnormal expression of IFN-γ, IL-4, and IL-5 by T lymphocytes affects AD symptoms [38]. Mutations in the filaggrin gene increase the incidence of various allergic diseases, including epidermal barrier defects and increased skin infections [39]. In addition, high levels of TSLP are expressed in AD, and T cells switch from Th1 to Th2 pattern [38, 39]. However, galectin-9 reduces mast cell degranulation and acute allergic skin reactions by promoting the differentiation of Th1 and Treg cells [40]. In this study, prebiotic treatment increased the population of Th1, Treg cells, and mRNA expression of galectin-9 in the MLNs isolated from DNCB-treated mice.
TLRs are expressed in intestinal epithelial cells and contribute to intestinal homeostasis [41], and especially, TLR-9 activation mediates innate and adaptive immunity [42]. TLR-9 has immunomodulatory effects via increased Th1 and Treg cells, resulting in alleviation of allergic diseases [27]. Using intestinal epithelial cell lines, we confirmed that prebiotic treatment increased the expression of TLR-9 and galectin-9 proteins.
Intestinal symbiotic microorganisms affect intestinal immunity via interaction between microbial antigens and pattern recognition receptors expressed by host cells [43]. Intestinal dysbiosis is a chronic inflammatory condition, similar to AD, and is associated with the onset of disease [44]. Thus, prebiotics modulate chronic inflammatory diseases such as AD by altering the composition of intestinal symbiotic microorganisms via immunomodulation. The intestinal microbial diversity is influenced by dietary behavior and has great influence on host physiology and immune function [45]. Westernized dietary habits associated with a reduction in dietary fiber intake result in reduced intestinal microbial diversity [46]. In the present study, we found that prebiotic treatment increased the intestinal microbial diversity. Consistent with our finding, previous studies have shown that bacterial species belonging to
It was reported that
Previous studies have shown that reduced levels of
In conclusion, prebiotic supplementation inhibits AD-like skin lesions in mice. Our results show that the inhibitory effect of prebiotics on AD is mediated via modulation of intestinal homeostasis as well as Th1/Th2 cytokine balance. These results suggest that prebiotics may have potential applications in the treatment of AD via attenuation of the allergic responses.
Supplemental Material
Acknowledgments
This research was conducted with the aid of the Industry Core Technology Development Project (Nos. 10049026 and 10063302), Ministry of Trade, Industry, and Energy, Korea.
Conflict of Interest
The authors have no financial conflicts of interest to declare.
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Related articles in JMB
Article
Research article
J. Microbiol. Biotechnol. 2020; 30(9): 1343-1354
Published online September 28, 2020 https://doi.org/10.4014/jmb.2005.05017
Copyright © The Korean Society for Microbiology and Biotechnology.
Galectin-9 Induced by Dietary Prebiotics Regulates Immunomodulation to Reduce Atopic Dermatitis Symptoms in 1-Chloro-2,4-Dinitrobenzene (DNCB)-Treated NC/Nga Mice
Jeong A Kim1+, Sung Hak Kim2+, In Sung Kim1+, Da Yoon Yu1, Gwang Il Kim1, Yang Soo Moon3, Sung Chan Kim4, Seung Ho Lee5, Sang Suk Lee6, Cheol Heui Yun7, In Soon Choi8, and Kwang Keun Cho1*
1Department of Animal Resources Technology, Gyeongnam National University of Science and Technology, Jinju 52725, Republic of Korea 2Department of Animal Science, Chonnam National University, Gwangju 61186, Republic of Korea 3Department of Animal Science and Biotechnology, Gyeongnam National University of Science and Technology, Jinju 52725, Republic of Korea 4Department of Biochemistry, Institute of Cell Differentiation and Aging, College of Medicine, Hallym University, Chuncheon 24252, Republic of Korea 5Department of Nano-Bioengineering, Incheon National University, Incheon 22012, Korea 6Department of Animal Science and Technology, Sunchon National University, Sunchon 57922, Republic of Korea 7Department of Agricultural Biotechnology and Research Institute of Agriculture and Life Sciences, Seoul National University, Seoul 08826, Republic of Korea 8Department of Life Science, Silla University, Busan 46958, Republic of Korea
Correspondence to:Kwang Keun Cho
chotwo2@gntech.ac.kr
Abstract
Atopic dermatitis (AD) is a skin disorder that causes chronic itch. We investigated the inhibitory effects of a mixture of prebiotic short-chain galacto-oligosaccharides and long-chain fructooligosaccharides (scGOS/lcFOS), inulin, or β-glucan on AD development in 1-chloro-2,4- dinitrobenzene (DNCB)-treated NC/Nga mice. Mice were randomly assigned to six groups: untreated mice, AD control, positive control (DNCB-treated NC/Nga mice fed a dietary supplement of Zyrtec), and DNCB-treated NC/Nga mice fed a dietary supplement of prebiotics such as scGOS/lcFOS (T1), inulin (T2), or β-glucan (T3). The prebiotic treatment groups (T1, T2, and T3) showed suppression of AD symptoms, Th2 cell differentiation, and AD-like skin lesions induced by DNCB. In addition, prebiotic treatment also reduced the number of microorganisms such as Firmicutes, which is associated with AD symptoms, and increased the levels of Bacteroidetes and Ruminococcaceae, which are associated with alleviation of AD symptoms. Our findings demonstrate the inhibitory effects of prebiotics on AD development by improving the Th1/Th2 cytokine balance and beneficial symbiotic microorganisms in in vitro and in vivo models.
Keywords: Gut microbiota, immunomodulation, prebiotics, Th1 cells, Th2 cells, Treg cells
Introduction
Atopic dermatitis (AD) is a chronic and inflammatory autoimmune disorder that results in severe itch and eczematous skin lesions [1]. The development of autoimmune disorders is associated with a defective immune system, loss-of-function variants of the epidermal barrier protein filaggrin [2], and disruption of the gut microbial community. In AD, the immunological imbalance between type 1 and type 2 helper T cells (Th1 and Th2 cells, respectively) results in an increase in antigen-specific IgE levels mediated via cytokines such as IL-4, IL-5, and IL- 14 [3-5].
Recent findings suggested that intestinal resident microorganisms play an important role in regulating the gut mucosal immune system and protection against pathogen invasion [6]. Microbial dysbiosis due to diet or antibiotic treatment, infection, and metabolic alteration results in serious health problems including intestinal inflammation [7]. In particular, loss of microbial diversity has a substantial impact on chronic inflammatory skin diseases [4].
Prebiotics are food ingredients selectively metabolized by gut bacteria, and they stimulate the growth of beneficial microorganisms [8], resulting in changes in the composition of intestinal microorganisms [9]. Fructo- oligosaccharides (FOS), inulin, beta-glucan, and galacto-oligosaccharides (GOS) represent sources of prebiotic dietary fiber [10]. Exposure to a mixture of short chain GOS (scGOS) and ling chain FOS (lcFOS) reduces the incidence of AD. In addition, prebiotics improve the symptoms of AD and facilitate the induction of innate responses such as toll-like receptor agonists and cytokines [11, 12]. However, the effects of prebiotic dietary fiber on AD-like skin lesions in mice and alterations in gut microbiota have yet to be investigated.
Thus, in the present study, we investigated whether prebiotics can reduce the symptoms of 1-chloro-2,4- Dinitrobenzene (DNCB)-induced AD-like skin lesions in NC/Nga mice by changing the gut microbiota and elucidated the underlying immune mechanism.
Materials and Methods
Animals
Five-week-old male NC/Nga mice (Central Lab, Animal Inc., Republic of Korea) were maintained at room temperature (22 ± 1°C), with a 12-h light–dark cycle during the experimental period and were provided ad libitum access to food (AIN-76A; Central Lab) and water. Mice were fed with scGOS (Neo Cremar Co., Republic of Korea)/lcFOS (Cell Biotech Co., Republic of Korea) at a ratio of 9:1 to 1% of the diet, and inulin (Vixxol Co., Republic of Korea) and β-glucan (Glucan Co., Republic of Korea) were supplemented at a rate of 1% of the diet. Zyrtec (0.2 mg/kg) (KyungDong Pharm Co., Republic of Korea) was provided in the daily diet as a positive control to alleviate symptoms of atopic dermatitis. After a one-week preliminary experimental period and a four-week AD induction period, the experimental animals were randomly divided into six groups with 6 animals per group: (1) Untreated control group (C: basal diet), (2) AD control group (N: basal diet + DNCB-induced group), (3) Positive control group (P: basal diet + Zyrtec + DNCB-induced group), (4) scGOS/lcFOS group (T1: basal diet + scGOS/lcFOS + DNCB-induced group), (5) inulin group (T2: basal diet + inulin + DNCB-induced group), and (6) β-glucan group (T3: basal diet + β-glucan + DNCB-induced group). The experimental protocol was approved by the Institutional Animal Care Board of Gyeongnam National University of Science and Technology (Approval No. 2017-8).
AD Model
According to the method described by Shin
-
Figure 1.
Effect of prebiotics on DNCB-induced AD-like symptoms in NC/Nga mice. (A ) Experimental design (B ) DNCB-induced AD-like skin lesions and spleen size. (C ) Spleen size-to-body weight ratio was evaluated. (D ) The dermatitis score of AD-like skin lesions was measured to evaluate itch, erythema/hemorrhage, scaling/dryness, edema, and excoriation/ erosion. C: Control, N: Negative control (DNCB-induced), P: Zyrtec positive control (DNCB-induced + Zyrtec), T1: scGOS/ lcFOS (DNCB-induced + scGOS/lcFOS), T2: Inulin (DNCB-induced + Inulin), T3: β-glucan (DNCB-induced + β-glucan); *p < 0.05 versus control group; **p < 0.01 versus control group; #p < 0.05 versus negative control group; ##p < 0.01 versus negative control group. Data represent means ± SD of 5 replicates.
Evaluation of AD
The AD severity score was assessed visually once a week after 4 weeks of DNCB treatment. Scores of 0 (none), 1 (mild), 2 (moderate), and 3 (severe) were measured for each of the four symptoms: erythema/hemorrhage, scarring/dryness, edema, and excoriation/erosion. The sum of the individual scores indicating clinical severity represented the dermatitis score.
Separation and Analysis of RNA from Mouse Mesenteric Lymph Nodes (MLN)
To evaluate the immunomodulatory effects of prebiotics, atopic-induced NC/Nga mice were sacrificed. The mesenteric lymph node (MLN) and spleen were separated. TRIzol was added to the MLN of NC/Nga mice and homogenized using SilentCrusher M (Heidolph, Germany). According to the method presented by Chomczynski and Sacchi [14], RNA was extracted and stored at -20°C until cDNA synthesis. The cDNA was synthesized using reverse transcription-polymerase chain reaction (RT-PCR) kits (TaKaRa Co., Japan) according to the manufacturer’s instructions. The primer sequences are listed in Table 1 [15-19]. Glyceraldehyde-3-phosphate dehydrogenase (GAPDH) was used as the reference gene.
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Table 1 . RT-PCR primer sequences for the analysis of immunomodulatory genes..
Target gene Primer Reference GAPDH Forward 5’ CCACCCAGAAGACTGTGGAT 3’ 15 Reverse 5’ CACATTGGGGGTAGGAACAC 3’ T-bet Forward 5’ TCAACCAGCACCAGACAGAG 3’ 16 Reverse 5’ AAACATCCTGTAATGGCTTGTG 3’ GATA-3 Forward 5’ CATTACCACCTATCCGCCCTATG 3’ 16 Reverse 5’ CACACACTCCCTGCCTTCTGT 3’ RORγT Forward 5’ TTCACCCCACCTCCACTG 3’ 16 Reverse 5’ TGCAAGGGATCACTTCAATTT 3’ Foxp3 Forward 5’ CCCATCCCCAGGAGTCTTG 3’ 17 Reverse 5’ CCATGACTAGGGGCACTGTA 3’ INF-γ Forward 5’ TCAAGTGGCATAGATGTGGAAGAA 3’ 17 Reverse 5’ TGGCTCTGCAGGATTTTCATG 3’ IL-4 Forward 5’ ACAGGAGAAGGGACGCCAT 3’ 17 Reverse 5’ GAAGCCCTACAGACGAGCTCA 3’ IL-17 Forward 5’ TTCATCTGTGTCTCTGATGCT 3’ 17 Reverse 5’ TTGACCTTCACATTCTGGAG 3’ TGF-β Forward 5’ GAAGGCAGAGTTCAGGGTCTT 3’ 17 Reverse 5’ GGTTCCTGTCTTTGTGGTGAA 3’ Galectin-9 Forward 5’ GAGAGGAAGACACACATGCCTTTC 3’ 18 Reverse 5’ GACCACAGCATTCTCATCAAAACG 3’ Filaggrin Forward 5’ CACTGAGCAAAGAAGAGCTGAA 3’ 19 Reverse 5’ CGATGTCTTGGTCATCTGGA 3’ TSLP Forward 5’ AGAGAAGCCCTCAATGACCAT 3’ 19 Reverse 5’ GGACTTCTGTGCCATTTCC 3’
Western Blot Analysis
Whole cell extracts were prepared with RIPA lysis buffer (150 mM NaCl, 1% NP-40, 0.1% SDS, 1% sodium deoxycholate, 50 mM Tris [pH 8.0]) containing 1 mM NaF, 1 mM Na3VO4, and protease inhibitors. Proteins were quantified using the Bradford assay reagent (Bio-Rad) according to the manufacturer’s instructions. Proteins (20– 40 μg) were separated by 10% sodium dodecyl sulfate-polyacrylamide gel electrophoresis and transferred to polyvinylidene fluoride membranes (EMD Millipore, USA). Membranes were blocked with 5% nonfat milk and incubated with the following antibodies: Galectin-9 (ab194338; 1:1000 dilution; Abcam), TLR 9 (ab134368, 1:1000dilution; Abcam), and GAPDH (#2118, 1:10,000; Cell Signaling). Membranes were then incubated with horseradish peroxidase-conjugated secondary antibodies and visualized with Immobilon Western Chemiluminescent HRP Substrate (EMD Millipore).
Cell Lines and Culture Conditions
The human colorectal adenocarcinoma cell line HT29 was purchased from the American Type Culture Collection (ATCC) and maintained in RPMI1640 with stable glutamine (Biowest) enriched with 10% fetal bovine serum (FBS)(Biowest), 1% penicillin/streptomycin (Welgene), and 25 mM HEPES (Shimakyu Co., Ltd., Japan), 25 mM NaHCO3 (Shimakyu Co., Ltd.,) at 37°C with 5% CO2. Isolated MNL lymphocytes were cultured in RPMI 1640 with L-glutamine and sodium bicarbonate (Sigma), 10% FBS (Biowest), 1% penicillin/streptomycin (Welgene), and 0.05 mM 2-β-mercaptoethanol (Sigma) at 37°C in the presence of 5% CO2. For western blot analysis, Gos/Fos, inulin, and β-glucan were treated in the presence of 0, 0.25, 0.5, 1, 2, 5 % w/v, respectively for 12 h.
Analysis of Gut Microbiota
On the last day of the experiment, the NC/Nga mice were sacrificed and fecal samples were collected from them and stored at -80°C until being used for genomic DNA (gDNA) extraction. DNA was extracted using fecal DNA MiniPrep kits (Zymo Research, USA), and the sequences were analyzed using Illumina MiSeq (ChunLab, Inc., Republic of Korea).
Processing of Sequencing Data
The pyrosequencing data for the 16S rRNA gene sequences were processed as we described previously (Kim
Quantitative Real-Time PCR
As mentioned above, DNA was extracted from NC/Nga mice fecal samples. Quantitative PCR (qPCR) was performed using Rotor-Gene SYBR Green PCR Kits (QIAGEN GmbH, Germany). The primer sequences of the microorganisms used for qPCR analysis are listed in Table 2 [20-23]. Universal Reference Gene (URG) method was used.
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Table 2 . qPCR primer sequences for the analysis of beneficial bacteria..
Target microorganism Primer Reference Universal Forward 5’ GTGSTGCAYGGYYGTCGTCA 3’ 20 Reverse 5’ ACGTCRTCCMCNCCTTCCTC 3’ Ruminococcus spp.Forward 5’ GGCGGCYTRCTGGGCTTT 3’ 21 Reverse 5’ CCAGGTGGATWACTTATTGTGTTAA 3’ Roseburia spp.Forward 5’ GCGGTRCGGCAAGTCTGA 3’ 21 Reverse 5’ CCTCCGACACTCTAGTMCGAC 3’ Faecalibacterium prausnitzii Forward 5’ GGAGGAAGAAGGTCTTCGG 3’ 21 Reverse 5’ AATTCCGCCTACCTCTGCACT 3’ Bifidobacterium spp.Forward 5’ TCGCGTCYGGTGTGAAAG 3’ 22 Reverse 5’ GGTGTTCTTCCCGATATCTACA 3’ Lactobacillus sakei Forward 5’ CCATGTGTAGCGGTGAAATG 3’ 23 Reverse 5’ ATCCTGTTTGCTACCCATGC 3’ Leuconostoc mesenteroides Forward 5’ TGATGCATAGCCGAGTTGAG 3’ 23 Reverse 5’ GAAAGCCTTCATCACACACG 3’ Leuconostoc citreum Forward 5’ GGAAACAGATGCTAATACCGAATA 3’ 23 Reverse 5’ TTTACCCCACCAACTAACTAATG 3’ Weissella cibaria Forward 5’ GGGAAACCTACCTCTTAGCA 3’ 23 Reverse 5’ GGACCATCTCTTAGTGATAGCA 3’ Weissella koreensis Forward 5’ GGGCTACACACGTGCTACAA 3’ 23 Reverse 5’ GATTCCGACTTCGTGTAGGC 3’
Statistical Analysis
The variance of the results obtained via repeated experiments was analyzed using SPSS 12.0 (SPSS, Inc., USA). The significance of the results was tested using Duncan’s multiple range test at
Results
Allergic Symptoms in Mice
To investigate the effects of prebiotics on DNCB-induced AD symptoms in mice, the mice were treated with scGOS/lcFOS (T1), inulin (T2), or β-glucan (T3) once a week for six weeks (Fig. 1A). Body weight and body weight gain were decreased in the DNCB-induced AD control (N), scGOS/lcFOS (T1), and inulin (T2) groups compared with the untreated control (C) group. However, positive control (P) and β-glucan (T3) groups showed no significant decrease in body weight and body weight gain (Supplemental File). Furthermore, average daily dietary feed intakes (ADFI) were not different between the treatments (Supplemental File). Feed efficiency decreased with all treatments except in the β-glucan groups (T3) compared with untreated control (C) group (Supplemental File).
DNCB-induced AD control mice (N) showed red spots, edema, and bleeding. Prebiotic (T1-T3) and Zyrtec (P) groups showed a clear decrease in these symptoms (Fig. 1B). Because AD influences the weight of immune organs such as the spleen by modulating various immune responses [24], we next investigated the effect of these prebiotics on spleen weight in the AD mouse model. A decrease in spleen weight was observed in the Zyrtec (P) and inulin (T2) groups compared with the DNCB-induced AD control (N) group (Fig. 1C). Skin lesions were determined according to the SCORAD index to confirm the effect of prebiotics on AD. The index was not clearly different between the DNCB-induced AD control (N) and prebiotic (T1–T3) groups at 3 weeks. However, positive control (P) and prebiotic (T1~T3) groups showed a gradual decrease in the index at 6 weeks compared with that of the DNCB-induced AD control (N) group (Fig. 1D).
T Cell Immune Responses and Skin Barrier-Related Gene Expression
In order to examine the effects of prebiotics on the T cell populations including Th1, Th2, Th17, and Treg, we analyzed the mRNA expression of their specific transcription factors and cytokines such as T-bet, GATA3, RORγt, Foxp3, interferon (IFN)-γ, interleukin(IL)-4, IL-17, and TGF-β, respectively, in the mesenteric lymph nodes (MLN) derived from the DNCB-induced AD mouse model. The AD control (N) group showed a significant decrease in the mRNA expression of IFN-γ and Foxp3, which are transcription factors of Th1 and Treg, respectively, compared with the untreated control (C) group. The prebiotic (T1~T3) and Zyrtec (P) groups clearly showed an increase in mRNA expression of Th1 and Treg-specific transcription factors and cytokines such as T- bet, IFN-γ, Foxp3, and TGF-β compared with the DNCB-induced AD control (N) group (Figs. 2A and 2D). However, treatments with prebiotics (T1~T3) induced a significant decrease in the mRNA expression of Th2- specific transcription factor GATA3 and cytokine IL-4, which were increased in the DNCB-induced AD control (N) (Fig 2B). RORγt, a Th17 transcription factor associated with acute AD [25], was markedly reduced in prebiotic (T1~T3) groups (Fig. 2C). However, no change in IL-17 expression was detected between the different treatments.
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Figure 2.
Effect of prebiotics on the expression of transcription factors and cytokines. T-cell polarization in mesenteric lymph nodes (MLN) was evaluated by analyzing the expression of T-bet, IFN-γ (Th1, A), GATA-3, IL-4 (Th2, B), RORγT, IL-17 (Th17, C) and Foxp3, TGF-β (Treg, D). C: untreated control, N: AD control (DNCB-induced), P: Zyrtec-positive control (DNCB-induced + Zyrtec), T1: scGOS/lcFOS (DNCB-induced + scGOS/lcFOS), T2: Inulin (DNCB-induced + Inulin), T3: β-glucan (DNCB-induced + β-glucan); *p < 0.05 versus control group, **p < 0.01 versus control group, #p < 0.05 versus negative control group, ##p < 0.01 versus negative control group. Data represent means ± SD of 4 replicates.
The development of allergic symptoms is regulated by a balance between Th1/Treg and Th2 cell populations. It is known that galectin-9 alleviates the allergic symptoms by promoting Th1/Treg cell differentiation, while thymic stromal lymphopoietin (TSLP) aggravates the symptoms via differentiation of naïve cells into Th2 cells [13].
The DNCB-induced AD control (N) group showed a marked decrease in the mRNA expression of galectin-9 compared with the untreated control (C) group, which was significantly increased after prebiotic (T1–T3) treatment. However, the level of TSLP mRNA was dramatically increased in the AD (N) group compared with the untreated control (C) group and decreased in the prebiotic (T1–T3) groups. We next analyzed the expression of the filaggrin gene, which is associated with skin barrier function and decreased AD symptoms [26]. The mRNA level of filaggrin was significantly decreased in the DNCB-induced AD control (N) compared with the untreated control (C) group, and was increased in the inulin (T2) group. These results indicate that prebiotics regulate the immune function by balancing the levels of Th1, Th2, and Treg cells, and decrease Galactin-9, which increases Th1 and Treg cell differentiation, and TSLP, which increases Th2 cell differentiation, indicating amelioration of AD symptoms (Fig. 3).
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Figure 3.
Effect of prebiotics on the expression of galectin-9, filaggrin, and TSLP in the mesenteric lymph nodes (MLN). C: Untreated control, N: AD control (DNCB-induced), P: Zyrtec-positive control (DNCB-induced + Zyrtec), T1: scGOS/lcFOS (DNCB-induced + scGOS/lcFOS), T2: Inulin (DNCB-induced + Inulin), T3: β-glucan (DNCB-induced + β- glucan); *p < 0.05 versus control group, **p < 0.01 versus control group, #p < 0.05 versus negative control group, ##p < 0.01 versus negative control group. Data represent means ± SD of 4 replicates.
TLR-9 and Galactin-9 Protein Expression Levels in HT29 Cell Lines
TLR9 enhances Th1 and Treg cell populations via IFN-γ, resulting in the prevention and treatment of allergic diseases [27]. Thus, we analyzed the protein expression of TLR-9 and galectin-9 after treatment with prebiotics in intestinal epithelial cells (HT-29 cells) (Fig. 4). Prebiotic treatments resulted in increased protein expression of TLR-9 and galectin-9 in HT-29 cells in a concentration-dependent manner. Thus, scGOS/lcFOS, inulin, and β- glucan are immunomodulated via activation of galectin-9 and TLR-9.
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Figure 4.
Prebiotics increase TLR-9 and Gal-9 protein expression in HT29 cell lines (A, B, C). Western blot analysis showed a dose-dependent increase in TLR-9 and Gal-9 protein levels in HT29 cells following treatment with scGOS/lcFOS (9:1 w/v mixture), inulin, and β-glucan for 12 h, respectively.
Diversity Analysis of Gut Microbiota
In the early stages of life, dysbiosis in the intestinal microbiome is the main cause of allergic diseases [28, 29]. Therefore, we analyzed the diversity of fecal microbiota in mice via 16S rRNA gene sequencing (Table 3 and Figs. 5A and 5B). The prebiotics (T1-T3) increased the intestinal microbial diversity compared with AD (N) and Zyrtec (P) groups (Table 3). In addition, intestinal microbial diversity was significantly increased in the scGOS/ lcFOS (T1) and inulin (T2) groups at the species level compared with the untreated control (C) group (Table 3). The Chao1 index indicated that the richness of intestinal microbiota in the group treated with prebiotics (T1-T3) was significantly increased compared with negative (N) and positive control (P) groups (Fig. 5A). The Shannon index showed that the inulin (T2) group had higher microbial diversity than the other groups (Fig. 5B).
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Table 3 . Effects of dietary prebiotic supplementation on diversity of fecal microbiota in mice..
Items Treatments C N P T1 T2 T3 Genus 237 (2) 189 (12)** 187 (4)** 256 (23)## 250 (13)## 242 (9)## Species 660 (20) 553 (10)** 554 (16)** 765 (51)**## 772 (22)**## 748 (73)## C: Untreated control, N: AD control (DNCB-induced), P: Zyrtec-positive control (DNCB-induced + Zyrtec), T1: scGOS/lcFOS (DNCB-induced + scGOS/lcFOS), T2: Inulin (DNCB-induced + Inulin), T3: β-glucan (DNCB-induced + β-glucan); *
p < 0.05 versus control group; **p < 0.01 versus control group; #p < 0.05 versus negative control group; ##p < 0.01 versus negative control group. Data represent means ± SD of 4 replicates..
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Figure 5.
Intestinal microbiota richness and diversity was increased with prebiotic treatment. (A ) Richness, (B ) Diversity, and (C) Principal coordinate analysis (PcoA) of community structures using a Fast UniFrac distance matrix. C: Untreated control, N: AD control (DNCB-induced), P: Zyrtec-positive control (DNCB-induced + Zyrtec), T1: scGOS/lcFOS (DNCB-induced + scGOS/lcFOS), T2: Inulin (DNCB-induced + Inulin), T3: β-glucan (DNCB-induced + β-glucan). Percentage of variation explained by principal component 1 (PC1): 46.726%; percentage of variation explained by principal component 2 (PC2): 14.962%; percentage of variation explained by principal component 3 (PC3): 6.865%. *p < 0.05 versus control group, **p < 0.01 versus control group, #p < 0.05 versus negative control group, ##p < 0.01 versus negative control group. Data represent means ± SD of 4 replicates.
Principal Coordinate Analysis (PCoA) Analysis of Gut Microbiota
The overall structural changes of the intestinal microbiota were then analyzed using principal coordinate analysis (PCoA). The PcoA plots showed that microbial communities from untreated control (C) and inulin (T2) groups, scGOS/lcFOS (T1) and β-glucan (T3) groups, AD control (N) and Zyrtec (P) groups were similar to each other (Fig. 5C), which indicates that prebiotics alleviate AD via changes in the intestinal microbial community. The Zyrtec (P) group showed a microbial community structure similar to that of AD control (N) group, suggesting that Zyrtec has no attenuating effect on AD symptoms due to intestinal microbial changes. These results suggest that changes in intestinal microbial communities may affect the induction and mitigation of AD.
Analysis of Intestinal Microbial Changes in Mice
Intestinal microorganisms constitute the immune system, and affect the incidence of various diseases, including AD [30]. Therefore, the effects of prebiotics on changes in gut microbiota were analyzed (Table 4). In general, an increase in
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Table 4 . Pyrosequencing analysis of fecal microbiota composition in mice fed with prebiotics..
Items Treatments C N P T1 T2 T3 mean % (SD) mean % (SD) mean % (SD) mean % (SD) mean % (SD) mean % (SD) Firmicutes (p) 81.38 (3.34) 87.82 (1.29)* 79.52 (2.22)## 63.59 (5.68)**## 76.12 (7.89)# 63.58 (6.21)**## Clostridia (c) 65.67 (8.08) 83.05 (3.59)** 78.24 (0.83)*# 55.26 (7.32)## 74.33 (7.48) 56.45 (3.06)## Lachnospiraceae (F) 42.76 (7.83) 70.47 (2.96)** 69.38 (2.08) 39.89 (3.06)## 47.37 (4.82)## 30.39 (6.62)## Eisenbergiella (G) 7.89 (1.37) 7.53 (0.54) 7.98 (1.38) 8.91 (2.65) 14.14 (1.74)**## 5.45 (1.18)*# Ruminococcaceae (F) 21.78 (4.98) 9.12 (0.59)* 8.93 (0.77)** 18.46 (3.91)# 20.54 (3.47)## 21.77 (3.72)## Ruminococcus (G) 1.91 (0.67) 0.00 (0.00)* 0.00 (0.00)* 2.98 (0.66)## 3.02 (0.72)## 2.57 (1.30)# Bacilli (c) 14.82 (8.22) 4.66 (4.80) 1.11 (1.73)* 4.26 (3.84) 5.02 (4.11) 2.94 (1.47) Lactobacillaceae (F) 20.63 (7.96) 2.00 (1.52)** 0.32 (0.26)* 5.77 (3.35)* 4.32 (1.43)* 2.78 (1.42)** Lactobacillus (G) 19.86 (7.69) 1.97 (1.49)** 0.31 (0.26)*# 5.53 (3.17)* 4.11 (1.37)* 2.66 (1.32)* Bacteroidetes (p) 16.81 (3.77) 9.22 (1.79)* 16.41 (2.42)## 33.47 (5.26)**## 21.56 (7.96)# 31.89 (9.12)*## Bacteroidia (c) 16.80 (3.78) 9.22 (1.79)* 16.40 (2.42)## 33.47 (5.27)**## 16.22 (4.89)# 31.88 (9.11)*## Prevotellaceae (F) 0.71 (0.09) 0.52 (0.20) 0.85 (0.11)# 26.02 (6.74)**## 2.52 (2.00) 26.09 (8.54)*## Prevotella (G) 0.67 (0.08) 0.15 (0.01)** 0.40 (0.16)*# 24.47 (6.26)**## 2.28 (1.76) 24.41 (8.23)*# S24-7_f(F) 8.59 (1.89) 4.82 (1.59)* 6.97 (0.83) 7.08 (1.56) 7.64 (0.59)# 4.51 (1.59)* C: Untreated control, N: AD control (DNCB-induced), P: Zyrtec-positive control (DNCB-induced + Zyrtec), T1: scGOS/lcFOS (DNCB-induced + scGOS/lcFOS), T2: Inulin (DNCB-induced + Inulin), T3: β-glucan (DNCB-induced + β-glucan); *
p < 0.05 versus control group; **p < 0.01 versus control group; #p < 0.05 versus negative control group; ##p < 0.01 versus negative control group. Data represent means ± SD of 4 replicates..
Immunomodulatory Effects by Intestinal Microbial
Groups of intestinal microorganisms such as
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Table 5 . Clostridia cluster analysis of fecal microbiota in mice fed with prebiotics..
Items Treatments C N P T1 T2 T3 mean % (SD) mean % (SD) mean % (SD) mean % (SD) mean % (SD) mean % (SD) Clostridia cluster XIVa Genus Ruminococcus 0.969 (0.526) 0.000 (0.000)* 0.000 (0.000)* 2.985 (0.661)**## 3.021 (0.718)**## 2.570 (1.300)# Roseburia 0.569 (0.238) 0.507 (0.325) 0.172 (0.060)* 0.249 (0.108) 0.648 (0.251) 0.221 (0.093)* Species Roseburia 0.010 (0.008) 0.000 (0.000) 0.000 (0.000) 0.029 (0.032) 0.174 (0.172) 0.009 (0.011) intestinalis Lachnospira 0.002 (0.003) 0.000 (0.000) 0.000 (0.000) 0.036 (0.033) 0.182 (0.206) 0.309 (0.217) pectinoschiza Ruminococcus 0.005 (0.001) 0.000 (0.000)** 0.001 (0.002)* 0.033 (0.044) 0.018 (0.019) 0.006 (0.010)*## lactaris Coprococcus 0.004 (0.003) 0.002 (0.003) 0.000 (0.000) 0.009 (0.003)# 0.006 (0.002) 0.014 (0.013) comes Clostridium 0.008 (0.006) 0.002 (0.001) 0.007 (0.002)## 0.004 (0.002) 0.002 (0.003) 0.002 (0.002) symbiosum Clostridia cluster IV Genus Anaerofilum 0.009 (0.004) 0.000 (0.000)* 0.003 (0.001)*## 0.393 (0.381) 0.029 (0.017)# 0.054 (0.071) C: Untreated control, N: AD control (DNCB-induced), P: Zyrtec-positive control (DNCB-induced + Zyrtec), T1: scGOS/lcFOS (DNCB-induced + scGOS/lcFOS), T2: Inulin (DNCB-induced + Inulin), T3: β-glucan (DNCB-induced + β-glucan); *
p < 0.05 versus control group; **p < 0.01 versus control group; #p < 0.05 versus negative control group; ##p < 0.01 versus negative control group. Data represent means ± SD of 4 replicates..
Functional Bacteria Analysis by qPCR
Next, we used qPCR to investigate the changes in intestinal populations of functional microorganisms (Fig. 6). We found that the levels of butyrate-producing microorganisms
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Figure 6.
Measurement of the abundance of functional bacteria in the feces of prebiotic-treated groups by quantitative PCR. (A ,B ) Butyrate-producing bacteria; (C -F ) lactic-acid bacteria; C: Untreated control, N: AD control (DNCB-induced), P: Zyrtec-positive control (DNCB-induced + Zyrtec), T1: scGOS/lcFOS (DNCB-induced + scGOS/lcFOS), T2: Inulin (DNCB-induced + Inulin), T3: β-glucan (DNCB-induced + β-glucan); *p < 0.05 versus control group, **p < 0.01 versus control group, #p < 0.05 versus negative control group, ##p < 0.01 versus negative control group. Data represent means ± SD of 4 replicates.
Discussion
In this study, we investigated the effects of prebiotics on the development of AD. In order to establish an AD mouse model, we treated the dorsal skin of NC/Nga mice with DNCB and detected the generation of AD-like skin lesions, such as red spots, edema, and bleeding. We found that prebiotic supplementation resulted in suppression of AD symptoms via reduction in spleen weight and SCORAD index. Increased spleen weight is associated with AD symptoms [36]. Recent studies suggested that AD is triggered by an imbalance between Th1, Th2, and Treg cell-related immune responses [37]. Abnormal expression of IFN-γ, IL-4, and IL-5 by T lymphocytes affects AD symptoms [38]. Mutations in the filaggrin gene increase the incidence of various allergic diseases, including epidermal barrier defects and increased skin infections [39]. In addition, high levels of TSLP are expressed in AD, and T cells switch from Th1 to Th2 pattern [38, 39]. However, galectin-9 reduces mast cell degranulation and acute allergic skin reactions by promoting the differentiation of Th1 and Treg cells [40]. In this study, prebiotic treatment increased the population of Th1, Treg cells, and mRNA expression of galectin-9 in the MLNs isolated from DNCB-treated mice.
TLRs are expressed in intestinal epithelial cells and contribute to intestinal homeostasis [41], and especially, TLR-9 activation mediates innate and adaptive immunity [42]. TLR-9 has immunomodulatory effects via increased Th1 and Treg cells, resulting in alleviation of allergic diseases [27]. Using intestinal epithelial cell lines, we confirmed that prebiotic treatment increased the expression of TLR-9 and galectin-9 proteins.
Intestinal symbiotic microorganisms affect intestinal immunity via interaction between microbial antigens and pattern recognition receptors expressed by host cells [43]. Intestinal dysbiosis is a chronic inflammatory condition, similar to AD, and is associated with the onset of disease [44]. Thus, prebiotics modulate chronic inflammatory diseases such as AD by altering the composition of intestinal symbiotic microorganisms via immunomodulation. The intestinal microbial diversity is influenced by dietary behavior and has great influence on host physiology and immune function [45]. Westernized dietary habits associated with a reduction in dietary fiber intake result in reduced intestinal microbial diversity [46]. In the present study, we found that prebiotic treatment increased the intestinal microbial diversity. Consistent with our finding, previous studies have shown that bacterial species belonging to
It was reported that
Previous studies have shown that reduced levels of
In conclusion, prebiotic supplementation inhibits AD-like skin lesions in mice. Our results show that the inhibitory effect of prebiotics on AD is mediated via modulation of intestinal homeostasis as well as Th1/Th2 cytokine balance. These results suggest that prebiotics may have potential applications in the treatment of AD via attenuation of the allergic responses.
Supplemental Material
Acknowledgments
This research was conducted with the aid of the Industry Core Technology Development Project (Nos. 10049026 and 10063302), Ministry of Trade, Industry, and Energy, Korea.
Conflict of Interest
The authors have no financial conflicts of interest to declare.
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Table 1 . RT-PCR primer sequences for the analysis of immunomodulatory genes..
Target gene Primer Reference GAPDH Forward 5’ CCACCCAGAAGACTGTGGAT 3’ 15 Reverse 5’ CACATTGGGGGTAGGAACAC 3’ T-bet Forward 5’ TCAACCAGCACCAGACAGAG 3’ 16 Reverse 5’ AAACATCCTGTAATGGCTTGTG 3’ GATA-3 Forward 5’ CATTACCACCTATCCGCCCTATG 3’ 16 Reverse 5’ CACACACTCCCTGCCTTCTGT 3’ RORγT Forward 5’ TTCACCCCACCTCCACTG 3’ 16 Reverse 5’ TGCAAGGGATCACTTCAATTT 3’ Foxp3 Forward 5’ CCCATCCCCAGGAGTCTTG 3’ 17 Reverse 5’ CCATGACTAGGGGCACTGTA 3’ INF-γ Forward 5’ TCAAGTGGCATAGATGTGGAAGAA 3’ 17 Reverse 5’ TGGCTCTGCAGGATTTTCATG 3’ IL-4 Forward 5’ ACAGGAGAAGGGACGCCAT 3’ 17 Reverse 5’ GAAGCCCTACAGACGAGCTCA 3’ IL-17 Forward 5’ TTCATCTGTGTCTCTGATGCT 3’ 17 Reverse 5’ TTGACCTTCACATTCTGGAG 3’ TGF-β Forward 5’ GAAGGCAGAGTTCAGGGTCTT 3’ 17 Reverse 5’ GGTTCCTGTCTTTGTGGTGAA 3’ Galectin-9 Forward 5’ GAGAGGAAGACACACATGCCTTTC 3’ 18 Reverse 5’ GACCACAGCATTCTCATCAAAACG 3’ Filaggrin Forward 5’ CACTGAGCAAAGAAGAGCTGAA 3’ 19 Reverse 5’ CGATGTCTTGGTCATCTGGA 3’ TSLP Forward 5’ AGAGAAGCCCTCAATGACCAT 3’ 19 Reverse 5’ GGACTTCTGTGCCATTTCC 3’
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Table 2 . qPCR primer sequences for the analysis of beneficial bacteria..
Target microorganism Primer Reference Universal Forward 5’ GTGSTGCAYGGYYGTCGTCA 3’ 20 Reverse 5’ ACGTCRTCCMCNCCTTCCTC 3’ Ruminococcus spp.Forward 5’ GGCGGCYTRCTGGGCTTT 3’ 21 Reverse 5’ CCAGGTGGATWACTTATTGTGTTAA 3’ Roseburia spp.Forward 5’ GCGGTRCGGCAAGTCTGA 3’ 21 Reverse 5’ CCTCCGACACTCTAGTMCGAC 3’ Faecalibacterium prausnitzii Forward 5’ GGAGGAAGAAGGTCTTCGG 3’ 21 Reverse 5’ AATTCCGCCTACCTCTGCACT 3’ Bifidobacterium spp.Forward 5’ TCGCGTCYGGTGTGAAAG 3’ 22 Reverse 5’ GGTGTTCTTCCCGATATCTACA 3’ Lactobacillus sakei Forward 5’ CCATGTGTAGCGGTGAAATG 3’ 23 Reverse 5’ ATCCTGTTTGCTACCCATGC 3’ Leuconostoc mesenteroides Forward 5’ TGATGCATAGCCGAGTTGAG 3’ 23 Reverse 5’ GAAAGCCTTCATCACACACG 3’ Leuconostoc citreum Forward 5’ GGAAACAGATGCTAATACCGAATA 3’ 23 Reverse 5’ TTTACCCCACCAACTAACTAATG 3’ Weissella cibaria Forward 5’ GGGAAACCTACCTCTTAGCA 3’ 23 Reverse 5’ GGACCATCTCTTAGTGATAGCA 3’ Weissella koreensis Forward 5’ GGGCTACACACGTGCTACAA 3’ 23 Reverse 5’ GATTCCGACTTCGTGTAGGC 3’
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Table 3 . Effects of dietary prebiotic supplementation on diversity of fecal microbiota in mice..
Items Treatments C N P T1 T2 T3 Genus 237 (2) 189 (12)** 187 (4)** 256 (23)## 250 (13)## 242 (9)## Species 660 (20) 553 (10)** 554 (16)** 765 (51)**## 772 (22)**## 748 (73)## C: Untreated control, N: AD control (DNCB-induced), P: Zyrtec-positive control (DNCB-induced + Zyrtec), T1: scGOS/lcFOS (DNCB-induced + scGOS/lcFOS), T2: Inulin (DNCB-induced + Inulin), T3: β-glucan (DNCB-induced + β-glucan); *
p < 0.05 versus control group; **p < 0.01 versus control group; #p < 0.05 versus negative control group; ##p < 0.01 versus negative control group. Data represent means ± SD of 4 replicates..
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Table 4 . Pyrosequencing analysis of fecal microbiota composition in mice fed with prebiotics..
Items Treatments C N P T1 T2 T3 mean % (SD) mean % (SD) mean % (SD) mean % (SD) mean % (SD) mean % (SD) Firmicutes (p) 81.38 (3.34) 87.82 (1.29)* 79.52 (2.22)## 63.59 (5.68)**## 76.12 (7.89)# 63.58 (6.21)**## Clostridia (c) 65.67 (8.08) 83.05 (3.59)** 78.24 (0.83)*# 55.26 (7.32)## 74.33 (7.48) 56.45 (3.06)## Lachnospiraceae (F) 42.76 (7.83) 70.47 (2.96)** 69.38 (2.08) 39.89 (3.06)## 47.37 (4.82)## 30.39 (6.62)## Eisenbergiella (G) 7.89 (1.37) 7.53 (0.54) 7.98 (1.38) 8.91 (2.65) 14.14 (1.74)**## 5.45 (1.18)*# Ruminococcaceae (F) 21.78 (4.98) 9.12 (0.59)* 8.93 (0.77)** 18.46 (3.91)# 20.54 (3.47)## 21.77 (3.72)## Ruminococcus (G) 1.91 (0.67) 0.00 (0.00)* 0.00 (0.00)* 2.98 (0.66)## 3.02 (0.72)## 2.57 (1.30)# Bacilli (c) 14.82 (8.22) 4.66 (4.80) 1.11 (1.73)* 4.26 (3.84) 5.02 (4.11) 2.94 (1.47) Lactobacillaceae (F) 20.63 (7.96) 2.00 (1.52)** 0.32 (0.26)* 5.77 (3.35)* 4.32 (1.43)* 2.78 (1.42)** Lactobacillus (G) 19.86 (7.69) 1.97 (1.49)** 0.31 (0.26)*# 5.53 (3.17)* 4.11 (1.37)* 2.66 (1.32)* Bacteroidetes (p) 16.81 (3.77) 9.22 (1.79)* 16.41 (2.42)## 33.47 (5.26)**## 21.56 (7.96)# 31.89 (9.12)*## Bacteroidia (c) 16.80 (3.78) 9.22 (1.79)* 16.40 (2.42)## 33.47 (5.27)**## 16.22 (4.89)# 31.88 (9.11)*## Prevotellaceae (F) 0.71 (0.09) 0.52 (0.20) 0.85 (0.11)# 26.02 (6.74)**## 2.52 (2.00) 26.09 (8.54)*## Prevotella (G) 0.67 (0.08) 0.15 (0.01)** 0.40 (0.16)*# 24.47 (6.26)**## 2.28 (1.76) 24.41 (8.23)*# S24-7_f(F) 8.59 (1.89) 4.82 (1.59)* 6.97 (0.83) 7.08 (1.56) 7.64 (0.59)# 4.51 (1.59)* C: Untreated control, N: AD control (DNCB-induced), P: Zyrtec-positive control (DNCB-induced + Zyrtec), T1: scGOS/lcFOS (DNCB-induced + scGOS/lcFOS), T2: Inulin (DNCB-induced + Inulin), T3: β-glucan (DNCB-induced + β-glucan); *
p < 0.05 versus control group; **p < 0.01 versus control group; #p < 0.05 versus negative control group; ##p < 0.01 versus negative control group. Data represent means ± SD of 4 replicates..
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Table 5 . Clostridia cluster analysis of fecal microbiota in mice fed with prebiotics..
Items Treatments C N P T1 T2 T3 mean % (SD) mean % (SD) mean % (SD) mean % (SD) mean % (SD) mean % (SD) Clostridia cluster XIVa Genus Ruminococcus 0.969 (0.526) 0.000 (0.000)* 0.000 (0.000)* 2.985 (0.661)**## 3.021 (0.718)**## 2.570 (1.300)# Roseburia 0.569 (0.238) 0.507 (0.325) 0.172 (0.060)* 0.249 (0.108) 0.648 (0.251) 0.221 (0.093)* Species Roseburia 0.010 (0.008) 0.000 (0.000) 0.000 (0.000) 0.029 (0.032) 0.174 (0.172) 0.009 (0.011) intestinalis Lachnospira 0.002 (0.003) 0.000 (0.000) 0.000 (0.000) 0.036 (0.033) 0.182 (0.206) 0.309 (0.217) pectinoschiza Ruminococcus 0.005 (0.001) 0.000 (0.000)** 0.001 (0.002)* 0.033 (0.044) 0.018 (0.019) 0.006 (0.010)*## lactaris Coprococcus 0.004 (0.003) 0.002 (0.003) 0.000 (0.000) 0.009 (0.003)# 0.006 (0.002) 0.014 (0.013) comes Clostridium 0.008 (0.006) 0.002 (0.001) 0.007 (0.002)## 0.004 (0.002) 0.002 (0.003) 0.002 (0.002) symbiosum Clostridia cluster IV Genus Anaerofilum 0.009 (0.004) 0.000 (0.000)* 0.003 (0.001)*## 0.393 (0.381) 0.029 (0.017)# 0.054 (0.071) C: Untreated control, N: AD control (DNCB-induced), P: Zyrtec-positive control (DNCB-induced + Zyrtec), T1: scGOS/lcFOS (DNCB-induced + scGOS/lcFOS), T2: Inulin (DNCB-induced + Inulin), T3: β-glucan (DNCB-induced + β-glucan); *
p < 0.05 versus control group; **p < 0.01 versus control group; #p < 0.05 versus negative control group; ##p < 0.01 versus negative control group. Data represent means ± SD of 4 replicates..
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