Shen-Ling-Bai-Zhu-San alleviates functional dyspepsia in rats and modulates the composition of the gut microbiota

Journal Pre-proof Shen-Ling-Bai-Zhu-San alleviates functional dyspepsia in rats and modulates the composition of the gut microbiota

Shaobao Zhang, Lei Lin, Wen Liu, Baorong Zou, Ying Cai, Deliang Liu, Dan Xiao, Jiahui Chen, Pei Li, Yuping Zhong, Qiongfeng Liao, Zhiyong Xie PII:

S0271-5317(19)30189-7

DOI:

https://doi.org/10.1016/j.nutres.2019.10.001

Reference:

NTR 8051

To appear in:

Nutrition Research

Received date:

19 February 2019

Revised date:

4 October 2019

Accepted date:

10 October 2019

Please cite this article as: S. Zhang, L. Lin, W. Liu, et al., Shen-Ling-Bai-Zhu-San alleviates functional dyspepsia in rats and modulates the composition of the gut microbiota, Nutrition Research(2018), https://doi.org/10.1016/j.nutres.2019.10.001

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© 2018 Published by Elsevier.

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Shen-Ling-Bai-Zhu-San alleviates functional dyspepsia in rats and modulates the composition of the gut microbiota

Shaobao Zhanga, b, Lei Lina, b, Wen Liua, Baorong Zoua, Ying Caia, Deliang Liua, Dan

School of Pharmaceutical Sciences (Shenzhen), Sun Yat-sen University, Guangzhou,

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a

f

Xiaoa, Jiahui Chenc,d, Pei Lic，Yuping Zhongc, Qiongfeng Liao c*, Zhiyong Xiea,b, e*

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School of Pharmaceutical Sciences, Sun Yat-sen University, Guangzhou, 510006, China

c

School of Pharmaceutical Sciences, Guangzhou University of Chinese Medicine,

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Guangzhou, 510006, China

Key Laboratory of State Administration of Traditional Chinese Medicine, Sunshine

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d

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b

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510006, China

e

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Lake Pharma Company Ltd, Dongguan, 523867, China Guangdong Provincial Key Laboratory of New Drug Design and Evaluation, Guangzhou, 510006，China

*Corresponding authors: Zhiyong Xie Tel./Fax: +86 20 84720059 E-mail: [email protected]

1

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Abbreviations: ANOVA, one-way analysis of variance; CPK, creatin phosphokinase; FD, functional dyspepsia;

FLASH,

fast

length

adjustment

of

short

reads;

FDR,

the

Benjamini-Hochberg false discovery rate; GAS, gastrin; KEGG, the Kyoto Encyclopedia of Genes and Genomes; LEfSe, Linear discriminant analysis Effect

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Size; MTL, motilin; OTUs, operational taxonomic units; NCBI, National Center of

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Biotechnology Information; PCR, polymerase chain reaction; PCoA, principal

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coordinates analysis; PICRUSt, Phylogenetic Investigation of Communities by

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Reconstruction of Unobserved States; QIIME, quantitative insight into microbial

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ecology; RDP, Ribosomal Database Project; SCFAs, short-chain fatty acids; SD,

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standard deviation; SLBZS, Shen-Ling-Bai-Zhu-San; SPF, specific pathogen-free.

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Abstract The pathogenesis of functional dyspepsia (FD) is multifactorial, and the gut microbiota may play a significant role. Shen-Ling-Bai-Zhu-San (SLBZS), a traditional Chinese herbal medicine, has been widely used in the treatment of FD, and appears to influence the gut microbiota. Therefore, we hypothesized that SLBZS

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would alleviate dyspeptic symptoms by adjusting the composition of the gut

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microbiota. To test this hypothesis, we aimed to evaluate the effects of SLBZS on

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FD and elucidate the mechanism that underlies the interactions between gut

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microbiota and FD during SLBZS treatment. We employed a rat model of FD

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induced by multiple forms of chronic mild stimulation. 16S rRNA gene sequencing and shotgun metagenomic sequencing were used to analyze the microbial

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communities in fecal samples from the rats. We found that the SLBZS improved

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dyspeptic symptoms in FD rats, such as weight loss, decreased intestinal motility,

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reduced absorptive capacity. Moreover, the SLBZS treatment reversed gut dysbiosis in FD. With SLBZS treatment, FD biomarkers including Prevotella, Mucispirillum and Akkermansia were decreased while SCFA-producing bacteria such as Adlercreutzia and Clostridium, and sulfate-reducing bacteria Desulfovibrio were enriched. Additionally, SLBZS normalized the dysregulated function of the microbiome, upregulating the pathways of energy metabolism and decreasing the oxidative stress as well as bacterial pathogenesis. Our study demonstrated that SLBZS could ameliorate dyspepsia, and amend the dysregulated composition and function of the gut microbial community, providing insight into the mechanism of 3

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SLBZS treatment for FD from the perspective of gut microbiota. Keywords: Shen-Ling-Bai-Zhu-San, gut microbiota, functional dyspepsia, 16S gene

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sequencing, metagenomics

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1. Introduction Functional dyspepsia (FD), one of the most prevalent functional gastrointestinal disorders throughout the world, is defined as discomfort and pain in the upper abdomen, poor appetite, fatigue and emaciation with no underlying organic disease [1, 2]. However, the pathogenesis of FD remains undefined, making treatment and

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recovery a challenge. The possible etiological mechanisms include gastroduodenal

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motor disorders, visceral hypersensitivity, Helicobacter pylori infection and

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emotional disturbances [3]. Recently, several studies have demonstrated that the gut

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microbiota may play a critical role in FD [4-7]. The gut microbiota has effects on

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body weight, digestion, absorption and the ability to resist diseases. It was found that patients with FD presented bacterial overgrowth in the small intestine [4], and small

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intestinal dysbiosis was closely connected with FD [5]. Meanwhile, the symptoms of

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FD patients supplemented with probiotics were alleviated [6], and probiotic therapy

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shifted the composition of the gut microbiota in FD volunteers [7]. Although it was not fully elucidated, the gut microbiota may have beneficial effects on FD, and further studies are needed to elucidate the potential mechanisms of FD.

The common treatments for FD involve antacids, prokinetics, mucosal-protective agents, antidepressants and the eradication of H. pylori [8], which are not entirely effective for all patients. Recently, Chinese herbal medicine, as a complementary and alternative approach to many diseases, has shown beneficial effects in clinical trials [9, 10]. Shen-Ling-Bai-Zhu-San (SLBZS) is a classical herbal formula originating 5

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from traditional Chinese medicine theory (Taiping Huimin Heji Ju Fang, Song Dynasty) and is composed of ten herbs, mainly Panax ginseng, Poria cocos and Atractylodes macrocephala (Table 1). It has been widely used to treat various gastrointestinal diseases in Chinese medicine [11, 12]. At present, SLBZS is a widely used clinical treatment for FD in China because of its significant effect [13, 14].

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Some researches showed that SLBZS exerted antacid effects in an artificial stomach

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model [15], stimulated ghrelin secretion to increase food intake in colon cancer

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patients postoperatively [16] and had a significant anti-inflammatory property in rats

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with nonalcoholic steatohepatitis [17]. Moreover, the SLBZS was reported to

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improve the structure of intestinal flora in rats with diarrhea by restoring the original intestinal balance or enriching the beneficial bacteria [12, 18]. In addition, some

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herbal ingredients of SLBZS, such as Panax ginseng and Atractylodes macrocephala

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have been reported to enhance intestinal absorption, affect gut microbial metabolism

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[19] and mediate disordered intestinal flora [20]. Based on the studies above, it seems that the altered gut microbiota may contribute to the attenuation of FD by SLBZS. However, no study has elucidated the mechanism that underlies the complex interactions between gut microbiota and FD under treatment with SLBZS.

Hence, we hypothesized that SLBZS would exert positive effects on FD by modulating the gut microbiota which contributed to host homeostasis. To test our hypothesis, we adopted a rat model with FD established by multiple forms of stimulations, which was a modified method reported in our previous study [21, 22], 6

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to evaluate the effects of SLBZS on FD. Furthermore, 16S rRNA gene sequencing and shotgun metagenomic sequencing, the high-throughput sequencing techniques, were conducted to explore the composition of and functional change in the gut microbiota, which would provide insight into the possible mechanisms of the

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protective effects against FD by SLBZS from the perspective of gut microbiome.

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2. Methods and materials

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2.1. Preparation of Shen-Ling-Bai-Zhu-San and Rhubarb extract

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SLBZS, composed of ten Chinese medicinal herbs (Table 1), was provided and

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quality controlled by Infinitus Co. Ltd. (Guangzhou, China). The herbs in the table were mixed and extracted three times at 80 °C for two hours using 10 volumes

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distilled water. Then, the SLBZS extract was filtered and concentrated to 1 g/ml (net

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content). The contents of the main active components including ginsenoside Rg1,

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ginsenoside Re, ginsenoside Rb1, pachymic acid, atractylenolide III and platycodin D in SLBZS extract were determined by the reported HPLC method [11]. After comparison with the retention times of the corresponding standards, the ginsenoside Rg1, ginsenoside Re, ginsenoside Rb1, pachymic acid, atractylenolide III and platycodin D were identified in SLBZS, the contents of which were 0.68 mg/g, 0.92 mg/g, 1.86 mg/g, 0.55 mg/g, 0.072 mg/g, and 0.28 mg/g, respectively (Table 2). Rhubarb (Radix et Rhizoma Rhei) was purchased from Zisun Chinese Pharm Co. Ltd. (Guangzhou, China) and then soaked twice for 30 min each using 10 volumes of distilled water. The rhubarb extract was filtered and concentrated to 1 g/ml (net 7

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content). 2.2. Animal experiment All animal experiments were approved and performed in accordance with the guidelines of the Institutional Animal Care and Use Committee of Guangzhou University of Chinese Medicine (Guangzhou, China). Specific pathogen-free (SPF),

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6-week-old male Sprague-Dawley rats (body weight 180-220 g) were purchased

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from Guangdong Medical Laboratory Animal Center (Guangzhou, China) and

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housed in an SPF controlled environment (12 h light/dark cycle, 24 °C ± 2 °C, 50 %

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– 70 % humidity) with free access to water and standard rodent chow (Laboratory

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Rodent Diet 5001; LabDiet, United States) unless special circumstances. The composition of the diets is shown in Table 3.

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Following the rules of animal experimental ethics, we determined the number of rats

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in each group based on our previous animal experiment [21, 22] combined with

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power analysis for t-test by R program (Salvatore Mangiafico's Companion). After one week of acclimatization, 18 healthy rats were randomly assigned into the control group (n=6) and model group (n=12). Every three rats in the same group were kept in a cage. The FD rat model was established by the modified multiple forms of stimulations.

Multiple

stimulations

including

diarrhea,

fasting

and

swimming-induced fatigue were used once a day for 14 days. While the model group rats were administered daily by oral gavage with rhubarb extract inducing diarrhea at a dose of 10 g/kg, the control group was given the same volume of sterile saline. Meanwhile, the model rats accepted loading swimming every day to exhaust and 8

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fasting every other day while the control group lived without starvation and exhaustion. After modeling, the model rats were randomly divided into two groups (n=6 each group) supplemented daily with sterile saline (FD group) or SLBZS (SLBZS group). The rats in the SLBZS group were given SLBZS suspended in sterile water at a dose of 1.323 g/kg in the next 28 days. The others in the control

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2.3. Sample collection and biomedical analyses

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experiment lasted for 42 days from modeling to the end.

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group and FD group were given an equal volume of sterile saline. The entire

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Body weight, food and water consumption of rats were measured weekly. Fresh

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feces and urine samples were collected on day 42 using metabolic cages and stored at -80 °C immediately for further analyses. After the termination of experimental

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duration, all rats were anesthetized with pentobarbital sodium after overnight fast.

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Blood samples were collected from the abdominal aorta and then serum samples

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were isolated from the blood samples through centrifugation at 5000 rpm at 4 °C for 10 min. Serum gastrin (GAS), motilin (MTL) and creatine phosphokinase (CPK) activity were determined according to the manufacturer’s instructions of enzyme-linked immunosorbent assay kits. The excretion rate of urine D-xylose was evaluated by a commercial kit. The above kits were all purchased from Nanjing Jiancheng Bioengineering Institute (Nanjing, China). 2.4. 16S rRNA gene V4 region sequencing of gut microbiota DNA extraction, 16S rRNA gene amplification and sequencing were all conducted in the laboratory of Beijing Genomic Institute-WuHan Huada Gene Institute (Shenzhen, 9

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China). DNA was extracted from the fecal samples and was amplified using a method previously described [23]. The V4 variable region of the 16S rRNA gene was

amplified

with

the

universal

primer

(5’-GTGCCAGCMGCCGCGGTAA-3’)

and

pair

515F 806R

(5’-GGACTACHVGGGTWTCTAAT-3’). The sequencing libraries were prepared with a one-step polymerase chain reaction in a 50 μl reaction mixture that contained

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30 ng of DNA template, 4 μl each of forward and reverse primers (515F-806R) and

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25 μl NEB Phusion High-Fidelity PCR master mix (New England Biolabs Inc.,

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United Kingdom). The PCR program was as follows: initial denaturation at 95 °C for

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3 min, followed by 30 cycles of denaturation at 98 °C, annealing at 55 °C, and extension at 72 °C for 45 seconds each, and a final extension at 72 °C for 7 min.

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After amplification and validation of the library, the sequencing of qualified libraries

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was performed on Illumina MiSeq platform with sequencing strategy PE250

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following the manufacturer’s instructions. 2.5. Bioinformatics analyses High-quality reads were acquired in subsequent bioinformatics analyses by in-house pipeline (Huada Gene). In short, the high-quality paired-end reads were merged to tags using FLASH v1.2.11 [24]. Chimeric sequences were purged identified by the UCHIME algorithm. The remaining reads were clustered into operational taxonomic units (OTUs) at 97 % sequence similarity using an open-reference OTU picking strategy with QIIME v1.9.1 [25], and then the representative sequences for each OTU were aligned against the GreenGenes core set [26]. The taxonomy was 10

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assigned using the Ribosomal Database Project (RDP) classifier method. Alpha and beta diversity analyses were performed in QIIME. Linear discriminant analysis Effect Size [27] (LEfSe) was utilized to explain differences among groups and identify the potential microbial biomarkers. The putative functions of microbial communities based on the 16S rDNA sequences were predicted by Phylogenetic

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Investigation of Communities by Reconstruction of Unobserved States [28]

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(PICRUSt). The information on the result of PICRUSt is listed in Table 4. STAMP

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[29] was used for functional profiling.

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2.6. Whole-metagenome shotgun sequence analyses

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The extracted DNA samples (n=6, average 2 per group) from the control, FD and SLBZS group were sequenced on the Illumina HiSeq 4000 Sequencer with the read

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lengths 150 bp and insert size of the DNA fragments 350 bp by Huada Gene Institute.

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The preprocess of whole-metagenome shotgun sequence data was similar to the 16S

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rRNA gene sequencing. High-quality sequences were assembled by SOAPdenovo2 [30] and aligned against the gene catalog by SOAP2 [31] to determine the abundance of genes. Only genes with ≥2 mapped remained in samples [32]. The protein sequences of predicted genes within the Kyoto Encyclopedia of Genes and Genomes (KEGG) database [33] with E ≤ 1e-5 were searched using BLASTP [34]. The genes were annotated using KEGG homologs and each protein was assigned to the KEGG Orthology group (KO) [35]. 2.7. Sequence accession numbers The genome sequences generated during the current study have been uploaded to the 11

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NCBI as Bioproject #PRJNA469977. Raw files of the bacterial V4 16S rRNA data and metagenomic data are available in the NCBI Sequence Read Archive (SRA) under Bioproject accession #SRP145166. 2.8. Statistical analyses All data are expressed as the means ± SD. Difference in body weight and other biochemical analyses were assessed using one-way analysis of variance (ANOVA)

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with Tukey’s post hoc test. Significant p values linked with microbial clades

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identified by LEfSe were corrected for multiple hypotheses testing using the

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Benjamini-Hochberg false discovery rate (FDR) method. Significant p values of

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microbial functions were performed by STAMP using one-way ANOVA followed by Tukey–Kramer post hoc test. Other statistical analyses were performed using

3. Results

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significant when p ＜0.05.

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GraphPad Prism version 7.00 for windows. All results were considered statistically

3.1. SLBZS reduces dyspeptic symptoms in rats with FD To explore the effects of SLBZS on FD, we recorded the body weight and biochemical indicators of rats in all groups. Compared with the control group, the rats in the FD and SLBZS groups exhibited a significant decrease in body weight (Fig. 1A) and food and water intake (Fig. 1F, G) on day 14. On day 42, the rats in the SLBZS group gained more weight than those in the FD group and there was no significant difference between the SLBZS group and the control group (Fig. 1A). 12

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The food and water consumption of rats in the SLBZS group were increased as well (Fig. 1F, G), implying that the appetite of FD rats was promoted. Lower serum levels of MTL and GAS in the FD group, which are gut hormones regulating the movements and secretions of the digestive tract, indicated that the ability of the gastrointestinal motility and gastric emptying decreased [36, 37], while SLBZS

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significantly improved these hormones levels (Fig. 1B, C). The excretion rate of

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urine D-xylose, an indicator of intestinal absorptive capacity [38], was significantly

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higher in the SLBZS group than in the FD group (Fig. 1D), suggesting that SLBZS

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improved the intestinal absorption function. Additionally, the activity of serum CPK

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was significantly decreased in FD rats in contrast with the normal rats and was slightly increased by the SLBZS intervention (Fig. 1E), which indicated there was a

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disequilibrium of energy metabolism [39] in FD rats and SLBZS might have an

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impact on it. All results revealed that the rat model with FD was established

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successfully and that SLBZS alleviated the disorder state in rats caused by FD. 3.2. SLBZS modulates the overall structure of gut microbiota in FD rats To examine how the gut microbiota was influenced, the overall structure of gut microbiota in all groups was profiled by 16S rRNA gene sequencing. After quality filtering of raw data, a total of 621,873 reads (34,548 ± 462 reads per samples) were obtained, the average length of which was 250 bp. Following identifying chimeric sequences, there were 566,340 effective reads (31,463 ± 726 reads per sample) for diversity analyses and data mining. Alpha diversity was used to evaluate species richness and diversity. As shown in the rarefaction curve (Fig. 2A), the observed 13

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OTU number in all groups reached stable values with a certain depth of sequencing, indicating that the sequencing effort was sufficient for representing and capturing rare new phylotypes and most diversity. The Chao1 index of the FD group and the SLBZS group (Fig. 2B) were both lower than the control group, but it was slightly elevated by SLBZS. The line slopes of the rank abundance curve (Fig. 2C)

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suggested that species diversity in the FD and SLBZS groups was lower than in the

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control group.

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Beta diversity analysis was performed to compare the similarity of bacterial floras

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among three groups based on their composition structures. Unweighted

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UniFrac-based principal coordinate analysis (PCoA) revealed that the community of each group was well clustered and clearly separated (Fig. 2D; R = 0.8683, p = 0.001

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with ANOSIM). The UniFrac distance between the control and the FD group is

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farther than the distance between the control and the SLBZS group, implying that

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FD altered the original microbiota while SLBZS led a positive change in modulating the gut microbiota. There was also a significant clustering displayed by hierarchical clustering among the three groups (Fig. 2E). Relative taxonomic abundance at the family level (Fig. 2F, Table 5) showed that SLBZS increased the abundance of S24-7 and decreased the abundance of Prevotellaceae and Lactobacillaceae back to normal. Taken together, the evidence suggests that the SLBZS intervention adjusted the structure of the microbial community closer to normal based on beta diversity, although it had no obvious effect on alpha diversity. 3.3. SLBZS alters key phylotypes in FD rats 14

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To further determine the correlation among gut microbiota, FD and SLBZS, we employed LEfSe to identify the key phylotypes based on taxon analysis. The key phylotypes representative of distinguishing biomarkers in each group are shown in the cladogram (Fig. 3A). The differences in the microbial community were also verified with the Mann-Whitney U test at phylum, family and genus taxon levels

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(Fig. 3B-D). Compared with the other two groups, the FD group exhibited increased

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two phyla Verrucomicrobia and Deferribacteres, which included Akkermansia and

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Mucispirillum respectively. Mucispirillum was reported to be related to inflammation,

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and Akkermansia showed an inverse correlation with body weight [40, 41]. Notably,

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Helicobacteriaceae and Prevotellaceae (including Prevotella) increased in the FD rats as well. The pathogenic bacterium Helicobacter pylori belongs to

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Helicobacteriaceae, which is a possible etiological mechanism of FD [3]. Prevotella,

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an opportunistic bacterium, was identified as an FD biomarker as the reported result

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[42]. Moreover, Lactobacillaceae including Lactobacillus, a type of lactic-producing bacteria, exhibited excessive reproduction in FD rats. In contrast, the levels of short-chain fatty acids (SCFAs)-producing bacteria (including Allobaculum, Clostridium

and

Adlercreutzia)

and

the

sulfate-reducing

bacteria

Desulfovibrionaceae (including Desulfovibrio), which were decreased in the FD group,

were

significantly

increased

in

the

SLBZS

group.

Meanwhile,

Helicobacteriaceae and Prevotella were markedly reduced by SLBZS. In addition, the difference between the control and the SLBZS group was less expected for a few bacteria, such as Elusimicrobiaceae and Desulfovibrio. Collectively, the above 15

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changes demonstrated that the intestinal flora of FD was disordered, while SLBZS could restore the majority of gut microbiota. 3.4. SLBZS ameliorates microbial metabolic functions in FD rats We utilized PICRUSt to predict potential metagenome functions based on 16S rRNA gene sequencing data. A summary of the PICRUSt analysis is presented in Table 4.

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Several decreased pathways of basic metabolism were revealed in the FD group

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compared with the control group and the SLBZS group (Fig. 4). The energy

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metabolism including inositol phosphate metabolism, phosphonate and phosphinate

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metabolism, and phosphatidylinositol signaling system significantly declined in the

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FD group compared with the control group (Fig. 4A-C). Energy metabolism is crucial for maintaining homeostasis, and its disruption may impact normal

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physiological conditions, such as balanced ATP concentration and signal

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transduction [43]. There were also differences in lipid metabolism among the three

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groups (Fig. 4D-F). Particularly, the primary and secondary bile acid biosynthesis, which are important pathways of microbial metabolism and contribute to gastric emptying and appetite [44], were reduced obviously in the FD group, while they were enhanced by the SLBZS treatment (Fig. 4E, F). In addition, the pathways of bacterial pathogenesis process, covering cell motility and secretion, bacterial invasion of epithelial cells, and bacterial secretion system, were significantly increased in the FD group (Fig. 4G-I), suggesting that the bacterial pathogenicity might be increased in the FD rats. An increased capacity for oxidative stress, a feature of the inflammatory environment, was observed in the FD 16

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group, as indicated by the increased sulfur metabolism and cysteine and methionine metabolism, which led to a rise in the level of pyruvate (Fig. 4J-L). Conversely, the SLBZS supplement could reverse the undesirable changes in the above metabolism. Overall, the results suggested that the metabolism of gut microbiota in the FD rats was disordered and that SLBZS treatment modulated the microbial functions to a

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similar level as the control group.

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Furthermore, shotgun metagenomic sequencing was used to validate the predicted

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functions, followed by a subset of six stool samples from three groups. A total of

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239,112,440 qualified reads were harvested with an average of 39,852,073 ± 283,059

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reads. The changing trends of 11 metabolic pathways from shotgun sequencing were consistent with the results from 16S rRNA gene sequencing (Fig. 5). Despite the fact

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that the alteration of the bacterial secretion system was unlike the predicted method,

4. Discussion

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most of the metabolic pathways predicted by PICRUSt were reliable.

In the current study, aiming to investigate the correlation among the FD, intestinal microbiota and SLBZS, we adopted multiple chronic mild stimulation to establish FD rat model, which has been verified in our previous study [21, 22]. All model rats exhibited dyspeptic symptoms, such as poor appetite, decreased body weight, and dysfunction of gastrointestinal motility and absorption, which was in accordance with the symptoms of FD. As shown by the results of the biochemical indicators, the dyspeptic symptoms were ameliorated significantly in the SLBZS group, 17

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demonstrating that SLBZS was effective in FD rats.

To observe whether the improvement of SLBZS in FD was related to the change in gut microbiota, we utilized 16S rRNA gene sequencing and shotgun metagenomic sequencing. Correspondingly, the analysis of microbial diversity and structure

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revealed that the SLBZS treatment could effectively modulate the gut microbiota

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closer to a normal conditional, while FD resulted in microbial disordered.

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Nevertheless, there was a lower alpha diversity in the SLBZS group compared with

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the control group, which might be relevant to the herbal ingredients of SLBZS –

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Atractylodes macrocephala and Glycyrrhiza uralensis which have antibacterial

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properties [45, 46].

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Although there is no definitive evidence to prove which microorganisms are the

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cause of FD, some studies have presented that structural dysbiosis of gut microbiota occurs in FD. Based on LEfSe, we identified the microbiota with striking differences among the control group, the FD group and the SLBZS group. Among the key phylotypes in the FD group, the abundance of Prevotella was extremely high, which has been reported to be a biomarker of FD [42]. Lactobacillaceae, including Lactobacillus, were also excessively propagated with the accumulation of lactic acid in the intestine, leading to decreased luminal pH and increased intestinal osmotic pressure [47, 48], which was a potential cause for diarrhea. Meanwhile, the relative abundance of Mucispirillum increased markedly. Previous studies demonstrated that 18

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Mucispirillum was evaluated in the condition of inflammatory stress [41] when low-grade inflammation occurred in the duodenum of FD [49], indicating that inflammation might occur in FD rats. Moreover, the high abundance of Akkermansia in the FD group agrees with the result reported before that Akkermansia was elevated in undernourished rodents [50] and had an inverse correlation with body weight in

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rodents and humans [40]. Claire Chevalier et al. also found that the absence of

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Akkermansia in cold exposure enabled the intestinal absorptive surface to increase

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[51].

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Therefore, the high abundance of Akkermansia may enable decreased uptake of energy and act as a biomarker of energy scarcity. As mentioned above, the gut

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microbiota was tightly related to FD and the dysregulated bacteria might take part in

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the development of FD jointly.

We also found that gut microbiota disorders were ameliorated with the SLBZS intervention. The abundance of Prevotella, Lactobacillus, Mucispirillum and Akkermansia, which were higher in the FD group, were decreased in the SLBZS group. Correspondingly, Desulfovibrio, a type of sulfate-reducing bacteria, increased markedly and was able to grow on lactic and sulfate [52], contributing to consumption of the excessive lactic acid produced by Lactobacillus. Furthermore, the levels of SCFA-producing bacteria including Adlercreutzia, Clostridium and Allobaculum [53] were enriched with SLBZS treatment. It is well established that 19

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SCFAs, vital substrates for maintaining the colonic epithelium, can regulate the integrity of the epithelial barrier and suppress the pathogen [53, 54]. The lower abundance of SCFA-producing bacteria in the FD group might result in epithelial barrier injury and host inflammation. Taking the above into consideration, SLBZS treatment could increase the SCFA-producing bacteria and Desulfovibrio and reduce

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the disadvantageous gut microbiota in FD including Prevotella, Mucispirillum and

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Akkermansia.

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We employed PICRUSt to predict the potential functions of the microbiota and

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found several metabolic pathways which varied obviously in the present study. It is noteworthy that the energy metabolisms involving inositol phosphate metabolism,

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phosphonate and phosphinate metabolism, and phosphatidylinositol signaling system

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were suppressed in the FD rats. The decreased CPK activity also suggested that the

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FD rats had disturbed energy metabolism. The members of the inositol phosphate metabolism pathway involved inositol phosphate, phosphonate and phosphinate. The inositol phosphate metabolism, phosphonate and phosphinate metabolism play important roles in many signal transduction pathways such as PI3K/Akt signaling [55]. These dysregulated energy metabolisms leading to PI3K/Akt signaling disorder were associated with gastric cancer predisposition. Furthermore, inositol phosphate controlled the activity of the glycolytic transcription factor GCR1 to regulate ATP concentration [43]. Inositol phosphates are generally distributed in the class Actinobacteria [56], which was also consistent with the lowest abundance of 20

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Actinobacteria in the FD group. Additionally, we inferred that the enhanced oxidative stress in the FD rats made the gut microbiota react to inflammation based on upregulated oxidative stress pathways. Increased sulfur metabolism is related to intestinal disorders and inflammation [57]. Prevotella and Akkermansia, which were highly abundant in the FD rats, were involved in pathways of colonic sulfur

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metabolism. The increased sulfur metabolism together with the high abundance of

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Mucispirillum suggested that the FD rats were in the condition of inflammation with

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microbiota were turned over by SLBZS.

pr

high probability. The disturbed metabolisms in FD that matched up the disordered

More recently, emerging evidence has demonstrated that bile acids are critical in

al

maintaining gut microbiota homeostasis, balanced lipid and energy metabolism [58].

rn

Bile acids could also inhibit the growth of harmful bacteria [42]. There was a lower

Jo u

abundance of Prevotella in the SLBZS group because Prevotella was vulnerable to bile acids. Thus, the upregulated pathways of primary and secondary bile acid biosynthesis in the SLBZS group were beneficial for the recovery of FD. Furthermore, our shotgun metagenomic sequencing results further validated the inferred functions of the microbial communities from 16S data. Taken together, the functional variation of gut microbiota among groups revealed that SLBZS treatment could regulate the disturbed metabolism in FD rats and modulate the disordered microbiota function to a normal condition.

21

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There are several limitations in the current study. First, the actual concentration of SLBZS reaching the colon, which was not determined, might be important for us to clearly illuminate the effect of SLBZS on the host and gut microbiota. Second, there might be other potential effective components, such as polysaccharides, in the SLBZS extract, while the HPLC method for the chemical analysis was mainly used

f

to determine the several reported active components. Some studies have found that

oo

the polysaccharides isolated from Panax ginseng and Atractylodes macrocephala

pr

could enhance intestinal absorption and improve the disordered microbiota [19, 20].

e-

Third, further molecular mechanisms of how host homeostasis was impacted by the

Pr

improved gut microbiota were not explored in this study. Although there are limitations, our study still has strengths. The present study was the first to elucidate

al

the complex interactions between gut microbiota and FD treated with SLBZS, laying

rn

the basis for further study. Moreover, the gut microbiota of humans and rats has a

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high similarity, although there are some important differences [59], which provides a good alternative to explore the relationship between gut microbiota and FD based on a rat model. Thus, taking advantage of the high-throughput sequencing techniques, we identified some potential FD biomarkers such as Prevotella and Mucispirillum and some beneficial bacteria such as Desulfovibrio and Adlercreutzia upregulation by SLBZS which would provide us with a new idea in therapeutic strategy for FD.

In conclusion, the hypothesis that SLBZS exerted positive effects on FD by improving the gut microbiota, thus contributing to homeostasis for the host, was 22

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supported. Our study showed that SLBZS could improve dyspepsia, remediate dysregulated microbiota and repair unbalanced metabolic pathways within the gut microbiota. Specifically, the SLBZS treatment increased the abundance of Desulfovibrio and SCFA-producing bacteria such as Adlercreutzia and Clostridium and decreased the abundance of Prevotella, Mucispirillum and Akkermansia which

f

might be taken as biomarkers to diagnose FD. Our findings shed light on the

oo

complex interactions between gut microbiota and FD under SLBZS treatment;

pr

however, further research and clinical data are needed to enhance our comprehension

e-

of FD treatment with SLBZS and develop novel effective therapeutic methods for its

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rn

al

Pr

application.

23

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Acknowledgments This work was supported by the National Natural Science Foundation of China [No. U1803123], Key projects of Guangdong Natural Science Foundation [No. 2017A030311022], and the Zhongshan Science and Technology Program [No. 2016C1015], the Science Program for Overseas Scholar of Guangzhou University of

f

Chinese Medicine (Torch Program) [No. XH20170111], Guangdong Provincial Key

oo

Laboratory of Construction Foundation [No. 2017B030314030]. The authors declare

Jo u

rn

al

Pr

e-

pr

no conflict of interest.

24

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Figure legends Fig. 1 SLBZS reduces dyspeptic symptoms in FD rats. The effects of SLBZS on (A) body weight, (B) the level of MTL, (C) GAS and (E) CPK activity in serum together with the excretion rate of urine (D) D-xylose. Data are presented as means ± SD (n=6). The differences among groups were assessed by one-way ANOVA followed

f

by Tukey–Kramer post hoc test (*p < 0.05, **p < 0.01). The food and water intake

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of rats were recorded during the experiment. (F) The food intake and (G) the water

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intake of rats every day. There were six rats in each group and every three rats in the

Pr

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same group were kept in a cage.

Fig. 2 The overall structure of microbiome was assessed by alpha diversity and beta

al

diversity among all groups. (A) The rarefaction curve. (Red, blue and orange

rn

indicate Control group, FD group and SLBZS group, respectively.) (B) Chao1 index.

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Statistical analysis was performed using Tukey–Kramer post hoc test (** p < 0.01). Values are means ± SD (n=6). (C) Rank abundance curve. (D) Unweighted PCoA. (E) The hierarchical clustering. Scale bar = 0.02. (F) Bacterial taxonomic profiling at the family level in each group.

Fig. 3 Taxonomic difference of gut microbiota was compared among three groups by LEfSe. The threshold of the logarithmic LDA score for discriminative feature is > 2.0. (A) The cladogram presented the significantly different bacterial taxa in the control group (red area), the FD group (green area) and the SLBZS group (blue area). 35

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The relative abundance (%) at the phylum (B), the family (C), and the genus level (D) was represented on a bar graph. Significance between groups was calculated with Mann-Whitney U test: Control group vs. FD group (∗ p < 0.05, ∗∗ p < 0.01); SLBZS group vs. FD group (# p < 0.05, ## p < 0.01); Control group vs. SLBZS group ( & p <

f

0.05, && p < 0.01). Values are presented as means ± SD (n=6).

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Fig. 4 Inferred gut microbiome functions was predicted among all groups. Energy

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metabolism: (A) Inositol phosphate metabolism, (B) Phosphonate and phosphinate

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metabolism, (C) Phosphatidylinositol signaling system. Lipid metabolism: (D)

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Sphingolipid metabolism, (E) Primary bile acid biosynthesis, (F) Secondary bile acid biosynthesis. Bacterial pathogenesis process: (G) Cell motility and secretion, (H)

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Bacterial invasion of epithelial cells, (I) Bacterial secretion system. Pathways of

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oxidative stress: (J) Sulfur metabolism, (K) Cysteine and methionine metabolism, (L)

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Pyruvate metabolism. Significance between every two groups was calculated with one-way ANOVA followed by Tukey-Kramer post hoc test (*p < 0.05, **p < 0.01). Values are expressed as means ± SD (n=6).

Fig. 5 Shotgun metagenomic sequencing was performed to validate the inferred microbial metabolic functions with a small subset of fecal samples from the control group, the FD group and the SLBZS group (n=2).

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Table 1. The plant composition of Shen-Ling-Bai-Zhu-San Botanical name

Part used

Amounts (g)

Ren Shen

Panax ginseng

Root and Rhizoma

100

Fu Ling

Poria cocos

Sclerotium

100

Bai Zhu

Atractylodes macrocephala

Rhizoma

100

Gan Cao

Glycyrrhiza uralensis

Root and Rhizoma

100

Shan Yao

Dioscorea opposite

Rhizoma

100

Bai Bian Dou

Dolichos lablab

Seed

75

Lian Zi

Nelumbinis semen

Seed

50

Yi Yi Ren

Coicis semen

Kernal

50

Sha Ren

Amomi fructus

Fruit

50

Jie Geng

Platycodon grandiflorum

Root

50

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pr

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f

Chinese name

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Journal Pre-proof Table 2. The contents of main active components in Shen-Ling-Bai-Zhu-San Source

Content (mg/g)

Ginsenoside Rg1

Ren Shen

0.68

Ginsenoside Re

Ren Shen

0.92

Ginsenoside Rb1

Ren Shen

1.86

Pachymic acid

Fu Ling

0.55

Atractylenolide III

Bai Zhu

Platycodin D

Jie Geng

0.072 0.28

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Pr

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pr

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f

Active component

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Table 3. Ingredient composition (g/kg) of Laboratory Rodent Diet 5001 Laboratory Rodent Diet 5001 (g/kg)

Casein

232.0

DL-Methionine

7.0

Corn Starch

460.6

Soybean oil

107.0

oo

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Ingredient

Omega-3 Fatty Acids

1.9

51.0

pr

Cellulose

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Glucose

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Sucrose Lactose

40.0 20.1 2.3

Mineral Mix 1

52.7

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al

Choline Chloride

Vitamin Mix 2

23.2

Total

1000.0

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1

2.2

Mineral Mix (per kg of diet): Calcium, 10 g; Phosphorus, 12 g; Potassium, 12 g; Magnesium, 2.1 g; Sulfur, 4.1 g; Sodium, 4 g; Chlorine, 7 g; Fluorine, 16 mg; Iron, 270 mg; Zinc, 79 mg; Manganese, 70 mg; Copper, 13 mg; Cobalt, 0.9 mg; Iodine, 1mg; Chromium, 1.2 mg; Selenium, 0.3 mg. 2 Vitamin Mix (per kg of diet): Carotene, 2.3 mg; Vitamin K (as menadione), 1.3 mg; Thiamin Hydrochloride, 16 mg; Riboflavin, 4.5 mg; Niacin, 120 mg; Pantothenic Acid, 24 mg; Folic Acid. 7.1 mg; Pyridoxine, 6 mg; Biotin, 0.3 mg; Vitamin B12, 0.05 mg; Vitamin E, 42 IU; Vitamin D3, 4500 IU; Vitamin A 15000 IU.

39

Journal Pre-proof Table 4. Summary of PICRUST analysis 1

Control

FD

SLBZS

22,213 ± 1,662 （81.3 ± 4.7）

22,219 ± 784（83.8 ± 1.9）

20,274 ± 1,421 （72.8 ± 7.3）

428 ± 22

404 ± 19

370 ± 41

Weighted NSTI 3

0.175 ± 0.012

0.157 ± 0.008

0.192 ± 0.012

KOs 4

13,726,114 ±

12,686,987 ±

13,400,476 ±

Mapped sequences (% total) 2 Reference-based

pr

oo

f

OTUs

2,447,229

1,389,483

e-

1,039,463 Values are expressed as means ± SD (n=6).

2

Mapped sequences (% total) were based on the number and percentage of the 16S

Pr

1

The weighted NSTI (Nearest Sequenced Taxon Index) value representing the

rn

3

al

rRNA gene sequences mapping to GreenGenes database with 97% similarity.

prediction) 4

Jo u

accuracy of metagenome prediction (Lower values indicates the more accurate

The number of inferred KOs (KEGG Orthology groups) for stool samples.

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Table 5. Relative abundance of four major differential bacterial families among

Relative abundance (%)

15.77 ±

28.44 ±

7.66

2.72

6.86

15.65 ±

8.82 ±

4.75 ±

7.82

4.41

3.31

3.90 ±

11.57 ±

1.43 ±

FD vs.

Control vs.

vs. FD

SLBZS

SLBZS

0.026

0.007

0.805

0.115

＜0.001

0.430

0.01

＜0.001

0.266

Jo u

the groups of rats 1

rn

al

Pr

Prevotellaceae

26.20 ±

Control

pr

Bacteroidaceae

SLBZS

e-

S24-7

FD

f

Control

p-value

oo

Major Family

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Lactobacillaceae

1

2.37

3.64

1.40

0.83 ±

5.48 ±

1.18 ±

0.25

2.25

1.10

0.003

0.012

0.915

Data are expressed as means ± SD (n = 6). p-values were calculated using Tukey’s

Jo u

rn

al

Pr

e-

pr

oo

f

honest significant difference test.

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Highlight 1. Shen-Ling-Bai-Zhu-San ameliorated the symptoms of functional dyspepsia in rats. 2. It modulated the composition of gut microbiota and restored dysregulated microbiota. 3. It improved the energy metabolism and the oxidative stress of gut microbiota.

f

4. The high abundance of Prevotella and Mucispirillum might be taken as

Jo u

rn

al

Pr

e-

pr

oo

biomarkers.

43

Figure 1

Figure 2

Figure 3

Figure 4

Figure 5