Shimanami Leaf Intake Affects Bowel Movement and Intestinal Microbiota in Mice

Abstract

The Shimanami Leaf^®, produced at Innoshima Island in Onomichi City, Hiroshima Prefecture, Japan, is a leafy vegetable that does not require pesticide use and has a high nutritional value. Although the leaf has abundant dietary fiber and other nutrients, reports on its biological regulatory functions are lacking. Therefore, this study aimed to elucidate the effects of Shimanami leaf intake on bowel movement and gut microbiota in mice. We examined the effects of Shimanami leaves on fecal weight, fecal water content, and intestinal microbiota composition. On day 10 of administration, the Shimanami leaf-treated group exhibited significantly higher fecal weight and water content than the control group. Next-generation sequencing analysis revealed that the ingestion of Shimanami leaf increased the abundances and diversity of intestinal bacteria, including members from Lactococcus, Streptococcus, and Muribaculaceae. Our findings suggest that Shimanami leaf supplementation improves bowel movement and promotes defecation.

INTRODUCTION

The Shimanami Leaf^® is a hybrid of Brassica juncea var. integrifolia and Azami-na, the hybrid of B. juncea and Brassica campestris var. hakabura, produced at Innoshima Island in Onomichi City, Japan. This leafy vegetable does not require pesticide use and has a high nutritional value. Shimanami leaves have more than twice as many nutrients, especially dietary fiber and folic acid, as do cabbage and kale leaves.

Increasing evidence suggests that the intestinal microbiota plays a major role in maintaining health.^1–3) Moreover, recent epidemiological and clinical data suggest a relationship between intestinal microbiota and the onset of obesity and metabolic syndromes.⁴⁾ The gut microbiota plays a vital role in the gut environment; therefore, the effects of diet on intestinal barrier function and the gut microbiota have been extensively studied.⁵⁾ The composition of the gut microbiota gradually changes based on the host’s diet.⁶⁾ Dietary fiber and some polyphenolic compounds present in fermented foods, such as yogurt, improved gut barrier function and influenced the intestinal microbiota.^7,8) However, the biological effects of Shimanami leaves have not yet been reported. Therefore, this study aimed to investigate the effects of Shimanami leaf consumption on bowel movement and intestinal microbiota in mice.

MATERIALS AND METHODS

Animal Experiments

Animal experiments were approved by and conducted following the guidelines of the Ethical Review Committee of Fukuyama University, Japan (Approval No. 2021-A-23).

Six-week-old female BALB/c mice (Japan SLC, Shizuoka, Japan) were housed individually in plastic cages in a room with controlled temperature (25 ± 2 °C) and humidity (40–60%) under 12 h light/dark cycles, with lights on from 8:00 a.m. to 8:00 p.m. The experimental period lasted for 7 weeks. Mice were allowed ad libitum access to food and water. After one week of acclimatization, they were divided into two groups with similar average body weights (n = 5 and 6 in the control and Shimanami leaf groups, respectively) and fed a control diet (typical 12450H diet [Research Diets Inc., New Brunswick, NJ, U.S.A.]) for 4 weeks, after which the Shimanami leaf-treated group was fed the Shimanami leaf diet (contained 30% Shimanami leaf powder and 70% 12450H diet) for 14 d, whereas the control group was fed the control diet. Shimanami leaves were acquired from Ado Custom Okamoto (Hiroshima, Japan). These mice were allowed ad libitum access to the respective diets and water.

Weight, water consumption, and food intake were measured daily. Fecal weight and water content were measured on the day before and on the 10th day following initiation of Shimanami leaf diet. On day 14 of administration (last day of rearing), feces were collected for DNA extraction.

Sample Collection and DNA Extraction

Fecal samples were collected on day 14 after administration of the respective diets, and next-generation sequencing was performed. Fecal samples (100 mg from each mouse) were mechanically lysed using Micro Smash MS-100 (Tomy Seiko Co., Ltd., Tokyo, Japan). Briefly, total DNA from the lysate was extracted using a phenol/chloroform/isoamyl alcohol mixture, precipitated, and washed with ethanol. Thereafter, the DNA pellets were resuspended in Tris-ethylenediaminetetraacetic acid (EDTA) buffer with ribonuclease (RNase) A (Sigma-Aldrich, St. Louis, MO, U.S.A.), further purified using the High Pure PCR Template Preparation kit (Roche Diagnostics, Mannheim, Germany), and suspended in 200 µL elution buffer according to the manufacturer’s instructions.

Analysis of the Intestinal Microbiome Composition

The V1–V2 region of the bacterial 16S ribosomal RNA (rRNA) gene was amplified using the Tks Gflex DNA Polymerase (TaKaRa, Shiga, Japan) and the primers 27F-mod (5′-ACACTCTTTCCCTACACGACGCTCTTCCGATCNNNNNN AGRGTTTGATYMTGGCTCAG-3′) and 338R (5′-GTGACTGGAGTTC AGACGTGTGCTCTTCCGATCTNNNNNN TGCTGCCTCCCGTAGGAGT-3′). The PCR products were purified using the AMPure XP purification kit (Beckman Coulter, Brea, CA, U.S.A.) and indexed using the primers 2ndF (5′-AATGATACGGCGACCACCGAGATCTACAC-Index2-ACACTCTTTCCCTACACGACGCTCTTCCGATCT-3′) and 2ndR (5′-CAAGCAGAAGACGGCATACGAGAT-Index1-GTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT-3′).

The indexed library was purified using the AMPure XP purification kit and quantified using the Qubit 4 Fluorometer (Thermo Fisher Scientific, Tokyo, Japan). All samples were added to the multiplex pool at equimolar concentrations and sequenced using the Illumina MiSeq platform (Illumina, San Diego, CA, U.S.A.). The amplified libraries were paired-end sequenced using MiSeq Reagent Kit v3 (600 cycles) and PhiX control v3 (Illumina). Community analysis of the reads was performed using QIIME2 (Ver. 2021.4).⁹⁾ Primer sequences were removed using the Cutadapt plugin in QIIME2.¹⁰⁾ The reads were denoised and clustered based on amplicon sequence variants (ASVs) at a single-nucleotide resolution using the DADA2 plugin in QIIME2.¹¹⁾ The derived ASVs were taxonomically classified using a naïve Bayes classifier trained on reference sequences based on operational taxonomic units clustered using a 99% identity threshold in the SILVA v138 rRNA database.¹²⁾

The ASVs (10000 reads) were used for alpha-diversity estimation of the observed features (observed ASVs), Faith’s phylogenetic diversity (faith-pd), and Shannon index. Beta-diversity metrics were calculated using the ASVs from each sample based on the weighted UniFrac distances. Alpha- and beta-diversity visualizations were carried out using ggplot2, gridExtra, and reshape2 in R (v4.1.2). Linear discriminant analysis (LDA) effect size was performed using the web-based Galaxy platform (http://huttenhower.sph.harvard.edu/galaxy).¹³⁾ The identified features were subjected to the LDA model with a threshold logarithmic LDA score set at 2.0 and ranked. Respective cladograms were generated with genus as the lowest level.

Statistical Analyses

Data are expressed as mean ± standard deviation (S.D.). Student’s t-tests were performed to evaluate the differences in dietary intake, body weight, fecal weight, and fecal water content. Alpha-diversity was analyzed using the non-parametric Kruskal–Wallis test, followed by Mann–Whitney U test. Beta-diversity was visualized using the principal coordinates analysis. Permutational multivariate ANOVA was used to detect statistical differences in microbial community structure among the groups. Statistical significance was set at p < 0.05.

RESULTS AND DISCUSSION

To examine the effects of Shimanami leaf intake on intestinal function, mice were fed a control diet or Shimanami-leaf containing diet. The mean body weight, food intake, and food intake did not differ between the two groups (Table 1).

Table 1. Comparison of Body Weight, Food Intake, and Water Consumption between the Groups with and without Shimanami Leaf Intake over a Two-Week Period Data Are Presented as Mean ± S.D.

	Control	Shimanami leaf
Body weight (g)	24.9 ± 1.20	23.6 ± 0.36
Food intake (g/d)	3.0 ± 0.13	3.1 ± 0.10
Water intake (g/d)	4.4 ± 0.18	4.8 ± 0.31

Fecal weight and fecal water content were examined the day before and 10 d after Shimanami leaf administration. No significant difference was observed between the groups before the administration (Figs. 1A, B). However, on day 10 after administration, fecal weight (Fig. 1A) and fecal water content (Fig. 1B) were significantly higher in the Shimanami leaf group than in the control group. These results indicate that the consumption of Shimanami leaves may improve bowel movement. Dietary fiber intake correlates with an increase in the number of defecations,¹⁴⁾ and the observed increase in fecal volume in the Shimanami leaf intake group in this study may have been influenced by the presence of dietary fiber in Shimanami leaf.

Fig. 1. Variations in the Fecal Weight and Water Content

(A) Fecal weight (g) before and after the administration of Shimanami leaf. (B) Fecal water content (%) before and after administration. Values represent mean ± S.D. (n = 5 and 6 in the control and Shimanami leaf groups, respectively). Data were analyzed using Student’s t-test (* p < 0.05, ** p < 0.01) for the control and Shimanami leaf groups.

To identify the changes in the gut microbiota after Shimanami leaf consumption, 16S rRNA gene sequencing was performed to analyze the fecal microbiome collected from the mice in each group. In total, 580640 quality reads, with an average of 52785 reads, were obtained. The changes in alpha diversity between the groups were evaluated using the observed features and Faith’s phylogenetic diversity (species richness estimation) and Shannon index (species richness and evenness estimation). Approximately 60 species of intestinal bacteria were identified in the control group, and approximately 210 species were identified in the Shimanami leaf group (Fig. 2A). The Faith’s phylogenetic diversity was significantly higher in the Shimanami leaf group than in the control group (Fig. 2B). These results indicate that the diversity of intestinal bacteria significantly increased with the intake of Shimanami leaves. Uniformity estimated using the Shannon index revealed that the alpha diversity significantly increased with the consumption of Shimanami leaves (Fig. 2C). The number and diversity of bacterial species were significantly higher in the Shimanami leaf group than in the control group. Although the phylum Firmicutes had a higher abundance ratio in the control group (Figs. 3A, B), the Shimanami leaf group showed an increased abundance of members of the phyla Bacteroidota (synonym Bacteroidetes), Actinobacteria, and Desulfobacterota. The abundance of Bacteroidota was significantly reduced in patients with constipation,¹⁵⁾ whereas that of Firmicutes was increased in obese mice.¹⁶⁾ Moreover, the absence of various genera of Bacteroidota may be associated with obesity, with lower numbers indicating a high risk of obesity. An increase in the Firmicutes to Bacteroidota (F/B) ratio is a potential indicator of obesity. Administration of Shimanami leaves significantly lowered the F/B ratio (Fig. 3C). The relative abundances of Firmicutes and Bacteroidota have been suggested as highly variable among individuals from the same population.¹⁷⁾ Therefore, comparing the F/B ratio may not necessarily be an effective method. However, selected probiotics can improve F/B dysbiosis and help reduce obesity.¹⁸⁾ Thus, our results suggest that the intake of Shimanami leaves may prevent obesity by modulating the F/B ratio.

Fig. 2. Alpha Diversity of the Intestinal Microbiome in the Control and Shimanami Leaf Groups Was Analyzed Using (A) Observed Features, (B) Faith’s Phylogenetic Diversity, and (C) Shannon Index

Values represent mean ± S.D. (n = 5 and 6 in the control and Shimanami leaf groups, respectively). Upon detection of significant differences using non-parametric Kruskal–Wallis test, comparison between the groups was performed using Mann–Whitney U test (** p < 0.01).

Fig. 3. Composition of the Intestinal Microbiome at the Phylum Level

(A) Linear discriminant analysis effect size (LEfSe) comparison of gut microbiota between the groups. Taxonomic cladogram derived from LEfSe analysis of the 16S rRNA gene sequence. The microorganisms with a high abundance in the control group are shown in red, and those with a high abundance in the Shimanami leaf group are in green. The darker the color, the higher the abundance. (B) Distribution of intestinal microflora at the phylum level. (C) Firmicutes to Bacteroidota (F/B) ratios.

The Shimanami leaf group was dominated by members of Lactobacillaceae and Muribaculaceae at the family level, which are associated with unsaturated fatty acid metabolism and intestinal barrier function, respectively (Fig. 4A). Oscillospiraceae species were also commonly observed, which were depleted in children with obesity.¹⁹⁾ In contrast, Peptostreptococcaceae members were abundant in the control group. An increase in the abundance of Peptostreptococcaceae members has been reported in patients with colon cancer. These results indicate that Shimanami leaves may help alleviate colitis and obesity.

Fig. 4. Composition and Distribution of the Intestinal Microbiome at the Family (A) and Genus (B) Levels

At the genus level, members of Ruminococcus and Turicibacter from the phylum Firmicutes were abundant in the control group, whereas those of Bacteroidota were abundant in the Shimanami leaf group (Fig. 4B). In the Shimanami leaf group, the abundance of lactic acid-producing bacteria, such as Lactococcus spp. and Streptococcus spp., increased, indicating improvement in the intestinal environment.²⁰⁾ In the control group, Turicibacter abundance increased. An increase in Turicibacter abundance was associated with upregulated purine metabolic pathway in obese mice.²¹⁾

Blautia spp. was more abundant in individuals with less visceral fat.²²⁾ Herein, Blautia spp. was more abundant in the Shimanami leaf group than in the control group, and Blautia coccoides was present only in the Shimanami leaf group. The abundance of B. coccoides was decreased in the intestines of older people and patients with diseases, such as diabetes and colorectal cancer.²³⁾ Barley consumption is suggested to increase Blautia spp. abundance²⁴⁾; thus, the potential probiotic role of barley in improving host health has received attention. The increase in Blautia spp. abundance with the intake of Shimanami leaves suggests that Shimanami leaf consumption may improve host health.

Other species belonging to the family Muribaculaceae have been reported to improve intestinal inflammation, neoplastic colitis,²⁵⁾ and glucose metabolism.²⁶⁾ The abundance of genus Prevotellaceae_UCG-001 was decreased in mice with ulcerative colitis and was associated with improved glucose metabolism.²⁷⁾ Herein, the abundance of members from Muribaculaceae and Prevotellaceae_UCG-001 was increased in mice fed Shimanami leaves, suggesting that Shimanami leaf intake may improve intestinal inflammation and glucose metabolism.

The overall composition of the gut microbiome of the control and Shimanami leaf groups was compared using beta diversity indices for the weighted UniFrac distance. The beta diversity of the Shimanami leaf group changed significantly compared with that of the control group (Fig. 5). In our previous study, the beta diversity of the group fed a dietary fiber diet containing inulin was significantly different from that of the group fed the control diet.²⁸⁾ Therefore, the changes observed in both alpha and beta diversities in this study may have been due to the dietary fiber content of Shimanami leaf. Although their fiber components have not yet been studied extensively, Shimanami leaves contain a considerable amount of dietary fiber. In particular, Shimanami leaf contains 4.2 g dietary fiber per 100 g, which is much higher than that in supposedly high dietary fiber-containing leafy vegetables, such as kale (3.7/100 g), cabbage (1.8/100 g), and lettuce (1.1/100 g). Dietary fiber-rich diets and changes in the intestinal microflora have been reported not only at the mouse level, but also at the human level.²⁹⁾ Therefore, dietary fiber influences the changes in the intestinal microflora caused by the intake of Shimanami leaves. In contrast, the same high dietary fiber-containing diet resulted in different changes in bacteria in the body owing to the production of metabolites and other factors.³⁰⁾ Shimanami leaf is a cruciferous vegetable, and cruciferous vegetables contain many sulfur compounds, such as glucosinolates, which may also be present in Shimanami leaf. Therefore, these metabolites and others may also alter the intestinal microflora; accordingly, these should be investigated in the future.

Fig. 5. Principal Coordinates Analysis (PCoA) Plot of the Intestinal Microbiome in the Control (n = 5) and Shimanami Leaf Groups (n = 6)

p-Values were determined using the pairwise permutational multivariate analysis of variance (PERMANOVA).

This study had some limitations. Further studies are required to identify the constituents of Shimanami leaves that contribute to improving bowel movement and the gut microbiota. Dietary fiber may not affect fecal water content.³¹⁾ In addition, a meta-analysis of studies on the effects of dietary fiber on constipation showed that fiber intake can increase the frequency of defecation but may not improve stool firmness or fecal volume and water content.¹⁴⁾ Furthermore, changes in the intestinal microbiota with the intake of Shimanami leaves may occur because of dietary fiber components not contributed by Shimanami leaves. Lastly, because we only used laboratory mice, our results should be verified in humans in clinical trials. Mouse and human gut microbiota are different, and although the abundance of each bacterium differs between the mouse and human gut microbiota, the types of bacteria present in the gut are qualitatively similar.³²⁾

In conclusion, our results showed that Shimanami leaves can improve bowel movement and gut microbiota in mice. We believe that the intake of Shimanami leaves may also improve intestinal bowel movement, thereby protecting the body from harmful bacteria and toxins.

Conflict of Interest

The Shimanami leaf was provided by Ado Custom Okamoto, Japan, who also funded the research. The other authors have no other conflicts of interest to declare.

REFERENCES

• 1) Mitsuoka T. The effect of nutrition on intestinal flora. Nahrung, 28, 619–625 (1984).
• 2) Gibson GR, Roberfroid MB. Dietary modulation of the human colonic microbiota: introducing the concept of prebiotics. J. Nutr., 125, 1401–1412 (1995).
• 3) Membrez M, Blancher F, Jaquet M, Bibiloni R, Cani PD, Burcelin RG, Corthesy I, Macé K, Chou CJ. Gut microbiota modulation with norfloxacin and ampicillin enhances glucose tolerance in mice. FASEB J., 22, 2416–2426 (2008).
• 4) Tilg H, Kaser A. Gut microbiome, obesity, and metabolic dysfunction. J. Clin. Invest., 121, 2126–2132 (2011).
• 5) Bagheri S, Zolghadri S, Stanek A. Beneficial effects of anti-inflammatory diet in modulating gut microbiota and controlling obesity. Nutrients, 14, 3985 (2022).
• 6) Claus SP, Guillou H, Ellero-Simatos S. The gut microbiota: a major player in the toxicity of environmental pollutants? NPJ Biofilms Microbiomes, 2, 16003 (2016).
• 7) Ito H, Wada T, Ohguchi M, Sugiyama K, Kiriyama S, Morita T. The degree of polymerization of inulin-like fructans affects cecal mucin and immunoglobulin A in rats. J. Food Sci., 73, H36–H41 (2008).
• 8) Taira T, Yamaguchi S, Takahashi A, Okazaki Y, Yamaguchi A, Sakaguchi H, Chiji H. Dietary polyphenols increase fecal mucin and immunoglobulin A and ameliorate the disturbance in gut microbiota caused by a high fat diet. J. Clin. Biochem. Nutr., 57, 212–216 (2015).
• 9) Bolyen E, Rideout JR, Dillon MR, et al. Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2. Nat. Biotechnol., 37, 852–857 (2019).
• 10) Martin M. Cutadapt removes adapter sequences from high-throughput sequencing reads. EMBnet J., 17, 10–12 (2011).
• 11) Callahan BJ, McMurdie PJ, Rosen MJ, Han AW, Johnson AJA, Holmes SP. DADA2: high-resolution sample inference from Illumina amplicon data. Nat. Methods, 13, 581–583 (2016).
• 12) Quast C, Pruesse E, Yilmaz P, Gerken J, Schweer T, Yarza P, Peplies J, Glöckner FO. The SILVA ribosomal RNA gene database project: improved data processing and web-based tools. Nucleic Acids Res., 41 (D1), D590–D596 (2013).
• 13) Segata N, Izard J, Waldron L, Gevers D, Miropolsky L, Garrett WS, Huttenhower C. Metagenomic biomarker discovery and explanation. Genome Biol., 12, R60 (2011).
• 14) Yang J, Wang HP, Zhou L, Xu CF. Effect of dietary fiber on constipation: a meta analysis. World J. Gastroenterol., 18, 7378–7383 (2012).
• 15) Zhu L, Liu W, Alkhouri R, Baker RD, Bard JE, Quigley EM, Baker SS. Structural changes in the gut microbiome of constipated patients. Physiol. Genomics, 46, 679–686 (2014).
• 16) Ley RE, Bäckhed F, Turnbaugh P, Lozupone CA, Knight RD, Gordon JI. Obesity alters gut microbial ecology. Proc. Natl. Acad. Sci. U.S.A., 102, 11070–11075 (2005).
• 17) Magne F, Gotteland M, Gauthier L, Zazueta A, Pesoa S, Navarrete P, Balamurugan R. The firmicutes/bacteroidetes ratio: a relevant marker of gut dysbiosis in obese patients? Nutrients, 12, 1474 (2020).
• 18) Stojanov S, Berlec A, Štrukelj B. The influence of probiotics on the Firmicutes/Bacteroidetes ratio in the treatment of obesity and inflammatory bowel disease. Microorganisms, 8, 1715 (2020).
• 19) Maya-Lucas O, Murugesan S, Nirmalkar K, Alcaraz LD, Hoyo-Vadillo C, Pizano-Zárate ML, García-Mena J. The gut microbiome of Mexican children affected by obesity. Anaerobe, 55, 11–23 (2019).
• 20) Walter J. Ecological role of lactobacilli in the gastrointestinal tract: implications for fundamental and biomedical research. Appl. Environ. Microbiol., 74, 4985–4996 (2008).
• 21) Sato K, Yamazaki K, Kato T, Nakanishi Y, Tsuzuno T, Yokoji-Takeuchi M, Yamada-Hara M, Miura N, Okuda S, Ohno H, Yamazaki K. Obesity-related gut microbiota aggravates alveolar bone destruction in experimental periodontitis through elevation of uric acid. MBio, 12, e0077121 (2021).
• 22) Ozato N, Saito S, Yamaguchi T, Katashima M, Tokuda I, Sawada K, Katsuragi Y, Kakuta M, Imoto S, Ihara K, Nakaji S. Blautia genus associated with visceral fat accumulation in adults 20–76 years of age. NPJ Biofilms Microbiomes, 5, 28 (2019).
• 23) Liu X, Mao B, Gu J, Wu J, Cui S, Wang G, Zhao J, Zhang H, Chen W. Blautia-a new functional genus with potential probiotic properties? Gut Microbes, 13, 1875796 (2021).
• 24) Matsuoka T, Hosomi K, Park J, Goto Y, Nishimura M, Maruyama S, Murakami H, Konishi K, Miyachi M, Kawashima H, Mizuguchi K, Kobayashi T, Yokomichi H, Kunisawa J, Yamagata Z. Relationships between barley consumption and gut microbiome characteristics in a healthy Japanese population: a cross-sectional study. BMC Nutr., 8, 23 (2022).
• 25) Hu L, Jin L, Xia D, Zhang Q, Ma L, Zheng H, Xu T, Chang S, Li X, Xun Z, Xu Y, Zhang C, Chen F, Wang S. Nitrate ameliorates dextran sodium sulfate-induced colitis by regulating the homeostasis of the intestinal microbiota. Free Radic. Biol. Med., 152, 609–621 (2020).
• 26) Xiao S, Liu C, Chen M, Zou J, Zhang Z, Cui X, Jiang S, Shang E, Qian D, Duan J. Scutellariae radix and coptidis rhizoma ameliorate glycolipid metabolism of type 2 diabetic rats by modulating gut microbiota and its metabolites. Appl. Microbiol. Biotechnol., 104, 303–317 (2020).
• 27) Sacks D, Baxter B, Campbell BCV, et al. Multisociety consensus quality improvement revised consensus statement for endovascular therapy of acute ischemic stroke. Int. J. Stroke, 13, 612–632 (2018). https://pubmed.ncbi.nlm.nih.gov/29786478/
• 28) Takayama K, Takahara C, Tabuchi N, Okamura N. Daiokanzoto (Da-Huang-Gan-Cao-Tang) is an effective laxative in gut microbiota associated with constipation. Sci. Rep., 9, 3833 (2019).
• 29) Lyu B, Wang Y, Fu H, Li J, Yang X, Shen Y, Swallah MS, Yu Z, Li Y, Wang H, Yu H, Jiang L. Intake of high-purity insoluble dietary fiber from Okara for the amelioration of colonic environment disturbance caused by acute ulcerative colitis. Food Funct., 13, 213–226 (2022).
• 30) Bouranis JA, Beaver LM, Jiang D, Choi J, Wong CP, Davis EW, Williams DE, Sharpton TJ, Stevens JF, Ho E. Interplay between cruciferous vegetables and the gut microbiome: A multi-omic approach. Nutrients, 15, 42 (2022).
• 31) Oshiro T, Harada Y, Kubota K, Sadatomi D, Sekine H, Nishiyama M, Fujitsuka N. Associations between intestinal microbiota, fecal properties, and dietary fiber conditions: the Japanese traditional medicine Junchoto ameliorates dietary fiber deficit-induced constipation with F/B ratio alteration in rats. Biomed. Pharmacother., 152, 113263 (2022).
• 32) Ishida T, Jobu K, Kawada K, Morisawa S, Kawazoe T, Shiraishi H, Fujita H, Nishimura S, Kanno H, Nishiyama M, Ogawa K, Morita Y, Hanazaki K, Miyamura M. Impact of gut microbiota on the pharmacokinetics of glycyrrhizic acid in Yokukansan, a Kampo medicine. Biol. Pharm. Bull., 45, 104–113 (2022).