Effect of the administration of probiotics on the fecal microbiota of adult individuals

Abstract Probiotics have been used to ameliorate ailments by modulating gut microbiota. However, to date, the effects of probiotic supplementation on the composition of fecal microbiota in healthy adults remain obscure. In this study, nine healthy volunteers were recruited to take probiotics (a mixture of Lactobacillus casei Zhang, L. plantarum P‐8, and Bifidobacterium lactis V9, 2:2:3, 1 × 1010 CFU/day) for 28 days. The fecal samples were collected at 0 and 28 days, and V4 of the 16S rRNA gene sequenced by Illumina MiSeq was used to analyze the fecal microbiota. The enterotype has been used to characterize the composition of gut microbiota. Nine adults were divided into Type P (fecal microbiota dominated by Prevotella, 4 adults) and Type B (fecal microbiota dominated by Bacteroides, 5 adults) based on an enterotype analysis. The responses of variation had been found in two enterotypes. The α‐diversity was not changed significantly after the administration of probiotics in both Type P and B. However, the community structure in Type B was substantially influenced. After the administration of probiotics, Weissella and Leuconostoc were significantly higher in Type P, while Collinsella significantly increased in Type B. The different pathways involving pathogen infections were downregulated at 28 days. The Type VI secretion system and the EHEC/EPEC pathogenicity signature were downregulated in Type B and Type P, respectively.

The composition and structure of gut microbiota are closely related to diet, genes, age, and drug. Although the gut microbiota is immensely separated between individuals, the concept of "enterotypes" has been proposed to improve the understanding of the role that gut microbiome play in health. According to the dominant bacteria in the intestinal tract, the gut microbial community structures of adult human beings are classified into three types, and each type is defined by the high abundance of Bacteroides, Prevotella, and Ruminococcus (Costea et al., 2020). Chung et al. reported that the amount of arabinoxylan-oligosaccharides can significantly increase the abundance of both Bifidobacterium and Prevotella in Prevotellaplus volunteers, while only Bifidobacterium changed in the samples of Prevotella-minus individuals, which indicated the different responses to food based on the characteristics of gut microbiota (Chung et al., 2020).
Probiotics are defined as "live microorganisms which can confer a health benefit on the host when administered in adequate amounts" (McFarland, 2015). Based on the population of specific pathologies, probiotics have been proven to benefit the gut environment and the health of host by regulating the balance of gut microbes and improving the resistance of host to pathogenic bacteria (Xu et al., 2017(Xu et al., , 2019. However, there is limited and less consistent evidence that shows the health-promoting effect of probiotics on healthy participants (Hou et al., 2020;Lee et al., 2020;Wang et al., 2015), which is related to the probiotic strains, ingestion time, viable count, and formulations of probiotic products. Probio-Fit ® , consisting of L. casei Zhang, L. plantarum P-8, and B. lactis V9 (2:2:3), has been shown to have a favorable curative effect in the adjuvant treatment of IBS (Chen et al., 2020) and IBD patients, but its effect on healthy individuals remains unclear. Therefore, this study was designed to investigate changes in the composition and diversity of gut microbiota caused by supplementation with Probio-Fit ® based on enterotypes (Table 1).

| Study participants
Nine participants (five males and four females) were randomly recruited from the same physical examination center of Shanghai, China, when they were examined. All the subjects were between 27 and 38 years old, with a body mass index (BMI) < 30 kg/m 2 . The subjects had no endocrine disorders, diabetes, or gastrointestinal problems and had not taken antibiotics for six months before and during the study period. The participants ceased consuming alcoholic beverages and other probiotic products.

| Experimental design
The probiotic powder Probio-Fit ® containing a 1.0 × 10 10 CFU mix of probiotics was packed in individually sealed sachets and stored at 4℃ before consumption. All the participants were required to take the probiotics for 28 days. Probio-Fit ® was consumed in warm water half an hour after lunch each day and provided by the Beijing Scitop Bio-tech Shareholding Co. Ltd.
The fecal samples of all the subjects were obtained at day 0 (before the supplementation) and day 28 (post supplementation). The sampling process enabled adequate fecal sampling without contamination. All the samples were transported to the laboratory in dry ice and stored at −80°C until further processing.

| DNA extraction and sequencing
The genomic DNA extraction of fecal samples was performed using a QIAGEN DNA Stool Fast Kit (QIAGEN) following the manufacturer's instructions. The quality of the extracted metagenomic DNA was checked using 1.0% agarose gel electrophoresis and a spectrophotometric analysis (optical density at a ratio of 260 nm/280 nm).
The concentration of DNA was required to be >20 ng/μl, and the 260 nm/280 nm ratio was required to be 1.8-2.0.
The extracted DNA was used as the template for amplification of the V4 region of the 16S rRNA gene with a specific barcode primer set. The primers contained Illumina adapters, and the reverse primer contained a barcode sequence unique to each sample. High-throughput sequencing of the PCR products was performed using an Illumina MiSeq platform (MiSeq PE250; Illumina) at PROMEGENE.

| Bioinformatics analysis
The V4 region of the 16S rRNA gene of all the samples was sequenced. All the DNA sequences were spliced and divided into samples according to the nucleotide tag (barcode) information, and the barcode and primers were excised to obtain high-quality sequences. Quantitative Insights into Microbial Ecology (QIIME) package (version 1.7)  was then used to conduct a bioinformatics analysis on the extracted highquality sequences. The main processing flow was as follows: (1) PyNAST (Caporaso, Kuczynski, et al., 2010) was used for sequence calibration and alignment; (2) a single sequence set was constructed according to 100% based on UCLUST (Edgar, 2010); (3) the unique sequence set was classified into operational taxonomic units (OTUs) under the threshold of 97% identity using UCLUST after the selection of the representative sequences; (4) Chimera Slayer (Haas et al., 2011) was adopted to remove the OTUs that contained chimeric sequences; (5) representative sequences of each OTU without a chimera were selected and compared with the sequence homology with RDP (Ribosomal database project, Release 11.5) (Cole et al., 2007), Green Genes (Release 13.8) (DeSantis et al., 2006), and Sliva (Version 132) to assign their taxonomic level of phylum, class, order, family, and genus (Quast et al., 2013); (6) Shannon-Wiener and Simpson diversity were computed on the basis of the de novo taxonomic tree constructed by the representative chimera-checked OTU set using FastTree (Price et al., 2009). Shannon-Wiener and Simpson diversity analyses were performed to evaluate the depth of sequence and biodiversity richness of the samples; (7) Bray-Curtis distances were calculated, and Nonmetric Multi-dimensional scaling (NMDS) based on the Bray-Curtis distances were applied to assess the β-diversity analysis of the microbiota structure of different samples. Linear discriminant analysis effect size (LEfSe) was then performed to find the biomarker before and after the probiotics using the default parameters. The bacterial diversity was predicted from 16S rRNA gene-based microbial compositions, and functional inferences were made from the Kyoto Encyclopedia of Gene and Genomes (KEGG) catalog using the PICRUst algorithm.

| Sequencing data accession numbers
The raw sequence data in our study were deposited in the Metagenome Rapid Annotation using Subsystem Technology (MG-RAST) database (accession number mgp94006, https://www.mgrast.org/linkin.cgi?proje ct=mgp94006).

| Statistical analysis
Statistical analyses were performed using R packages (http:// www.r-proje ct.org/). Based on the genus abundance profile, enterotype analysis was performed as described and visualized by the R "ade4" package. The intragroup differences in the two enterotypes were compared using a Wilcoxon test, and p-values <.05 were considered statistically significant. Linear discriminant analysis (LDA) scores of LEfSe >2 were considered to be significant. The annotated sequences were also assigned to the KEGG orthologue group (KO) according to the highest score, and Z-scores were calculated to express the differences in enriched metabolic pathways before and after the probiotics. Z-scores >1.6 were considered to be statistically enriched. Finally, the analysis results were visualized by R packages, Origin 8.6 (OriginLab) and GraphPad 7.0 (GraphPad Prism).

| Sequencing coverage analysis and enterotypelike clusters
To characterize the effects of probiotics on the intestinal microbiota of healthy adults, V4 of the 16S rRNA genes was sequenced using the Illumina MiSeq platform. A rarefaction model was used to evaluate the species richness of the sampling data ( Figure 1). It was determined that current sequencing had represented most of the microbial diversity. However, more phylotypes could be found by increasing the depth of sequence.
We analyzed the bacterial microbiota composition of all the samples (a total of 18, from two different time points). The fecal microbiota at 0 day were analyzed adopting the method described by Arumugam M (Arumugam et al., 2011), and the results showed that the fecal microbiota fell into two distinct enterotypes described in At the phylum level, more than 99.07% of the sequences belonged to the four most populated bacterial phyla in Type P and  (Figure 3).

| Effect of probiotics on the gut microbial α-diversity and β-diversity
The Shannon and Simpson indices were used to evaluate the change of α-diversity before and after the probiotics were consumed. The The NMDS analysis based on the Bray-Curtis distances revealed bacterial structural differences between the two different enterotypes in both Type P and Type B, but no clear clusters were observed before and after the intervention of probiotics ( Figure 4c). However, it is noteworthy that the samples that belonged to the same individual mostly clustered together (connected by lines on the plot), suggesting that the individual difference might be greater than that of the probiotic effects on the fecal microbiota structure. Therefore, the variable difference in the Bray-Curtis distances based on individuals before and after ingestion was calculated to decrease the difference between participants. The results showed the variation of Type B was higher than that of Type P (Figure 4d), which indicates that the structure of Type B could be more disturbed than that of Type P. However, no statistically significant difference was observed.

| Probiotics-directed changes in the composition of gut microbiota
To determine the change of microbiota composition after the probiotics, the LEfSe analysis was used to identify differences in the taxa before and after the administration in the two enterotypes.
Varied responses were found between the two types. In Type P, 20 taxa of different taxonomic levels were found before and after the administration of probiotics (Figure 5a, LDA Score >2).

| Changes in microbial metabolic pathways and functional features
To investigate the effects of administration of probiotics on the functional profiles, high-quality reads from two different enterotype Relative abundance (%) samples were assembled and annotated for their protein-coding genes and generated for the KEGG database orthologues (Figure 5b and Figure 6b).
Varied responses were observed again. After the administration of probiotics, the function of two enterotypes clustered closer, which indicates that the same metabolic modules of individuals changed in the opposite direction after the administration of probiotics. For example, phosphate and amino acid transport systems decreased in Type P, but they increased in Type B after the probiotics. Some modules in carbohydrate and lipid metabolism and energy metabolism were higher in the subjects of Type B after the administration of probiotics, which were higher in the subjects of Type P before the administration of probiotics.
In addition, we also found some similarities in the two enterotypes, such as the significant downregulation of pathogenic bacteriarelated metabolic pathways after the administration of probiotics. In the Type P group, the KOs of Type III secretion system, polyamine biosynthesis, and EHEC/EPEC pathogenicity signature were significantly decreased, while the KOs of Type VI secretion system were significantly dropped in Type B.

| D ISCUSS I ON
In this study, the effects of the probiotic's administration on fecal microbiota in healthy individuals were investigated. The concept of "en- database (Koren et al., 2013). The enterotype stratifications were not specific to a nation or continent, which could reflect different responses toward diet intake (Wu et al., 2011). Enterotype P, driven by Prevotella, has been shown to be rich in individuals with fiberrich diets. Conversely, enterotype B represented by Bacteroides has been related to diets enriched in saturated fats and animal proteins (Costea et al., 2018). These variations among enterotypes reflect different combinations of microbial trophic chains with a probable impact on energy balance in the hosts (Christensen et al., 2018).
Therefore, the different responses of the two enterotypes to drugs were analyzed in some studies. A study on the effects of Acarbose on type-2 diabetic patients showed that patients with different enterotypes (B-type and P-type) showed different responses in metabolic parameters (Gu et al., 2017).
Such interesting results also occurred in this study, which showed various responses to probiotic administrations in different F I G U R E 4 α-diversity and β-diversity analyses on fecal microbiota before and after the intervention of probiotics.    enterotypes. The α-diversity did not change significantly in two enterotypes after the administration of probiotics, which is consistent with previous findings that the α-diversity of intestinal flora was not significantly affected by the administration of probiotics . Examinations of the β-diversity indicated that the samples that belonged to the same individual mostly clustered together regardless of the probiotic interventions. However, after removing individual differences, it appeared that Type B was more vulnerable than Type P when the probiotics were administered. The same observation has been obtained in a previous study (Haddad et al., 2020;Kang et al., 2016), which indicates that the ability of pro- The changes in bacterial diversity and population may lead to the regulation of metabolic pathways. Therefore, it is paramount to analyze the regulation of pathways and their functional features.

F I G U R E 5 Identification of bacterial biomarkers (a) by LEfSe analysis and KOs change (b) of volunteers in
Alterations in the microbial metabolic pathways were also observed in two enterotypes. The same metabolic modules of individuals were found to cluster in one enterotype after the administration of probiotics but dispersed in another, which could be related to the

| CON CLUS IONS
Our study demonstrated various responses owing to the administration of probiotics in different enterotypes, suggesting that probiotics are likely to colonize in the intestinal microbiota of an individual depending on its characteristics. However, the administration of probiotics is likely to promote the health of the individual in both Type P and Type B by enhancing the growth of beneficial bacteria and inhibiting the pathways related to pathogenesis.

ACK N OWLED G EM ENTS
This project was supported by the National Natural Science

CO N FLI C T S O F I NTE R E S T
There are no conflicts of interest to declare.

E TH I C S A PPROVA L
All the study procedures were approved by the Ethical Committee