Introduction

The gut microbiota of humans comprises approximately 1014 microorganisms, including viruses, yeast, and bacteria (Anwar et al., 2021). The gut microbiota population can be influenced by the administration of antibiotics or by diarrhea (Noh et al., 2018), and an imbalance of microbiota (dysbiosis) is associated with obesity, inflammatory bowel disease, and immune responses (Claesson et al., 2011). Therefore, the gut microbiota play a major role in human health and disease.

Probiotics are live microorganisms that are beneficial to the health of the host when administered in adequate amounts (Fuller, 1991). Prebiotics are nondigestible oligosaccharides that benefit the host by stimulating the growth of bacteria. Synbiotics are a combination of probiotics and prebiotics (Roberfroid, 1998). The consumption of probiotics can affect the composition of intestinal microbial communities as the probiotics compete with the microbiota for nutritional substrates. Specifically, altering carbohydrate utilization dynamics via substrate availability through probiotic supplementation affects microbial community structure (O'Toole and Cooney, 2008). Additionally, changes in metabolic profiles, including short-chain fatty acids (SCFAs) concentration, are known to affect the composition of microbiota (Li et al., 2008), and exopolysaccharides produced by probiotics can act as substrates for microbial components. Studies on mice have indicated that probiotics influence the regulation of depressive symptoms (Liu et al., 2020) and obesity (Soundharrajan et al., 2020) as well as altering microbiota composition. For instance, the Firmicutes/Bacteroidetes (F/B) ratio was shown to increase in obese mice but decrease in lean mice (Ley et al., 2005), and an imbalance in this ratio can be restored via the appropriate use of probiotics (Stojanov et al., 2020). The fermentation of prebiotics, e.g., fructooligosaccharide (FOS), galactooligosaccharide, and inulin, causes the proliferation of beneficial microorganisms in the gastrointestinal tract (Hemarajata and Versalovic, 2013), protects the microorganisms from species that have pernicious effects on energy sources, and promotes the production of SCFAs with immunomodulatory properties (Guarino et al., 2020). Moreover, synbiotics have been shown to alleviate disease by improving metabolic profiles (Li et al., 2021) and releasing specific enzyme such as β-fructofuranosidase (Cui et al., 2022).

The effects of probiotics on the structure of the gut microbiota differ according to the probiotic strain. Thus, it is important to select an appropriate strain for a specific therapeutic purpose (Stojanov et al., 2020). In addition, Lactiplantibacillus plantarum has been shown to regulate the gut microbial composition through the hydrolysis of FOS (Chen et al., 2015). In the present study, we investigated the effects of administering L. plantarum FBT215 as a potential probiotic with or without prebiotics (FOS and inulin) on the gut microbiota composition of WT mouse model using the Illumina platform to conduct metagenomic analysis of the 16S rRNA gene. In general, since healthy individual intakes probiotics and prebiotics as food supplements, healthy model was used for study, not a disease model.

Materials and methods

Isolation of L. plantarum FBT215

In previous study, Lactiplantibacillus plantarum FBT215 was isolated from Korean traditional food, kimchi (Kim et al., 2022).

Experimental animals

Six-week-old male C57BL/6J mice (DaeHan Biolink, Eumsung, Korea) weighing 21–23 g were housed under a 12/12 h light/dark cycle with controlled temperature (22 ± 1℃) and relative humidity (55 ± 1%). The mice were acclimated for one week and randomly divided into six groups (n = 5 mice per group) as follows: control (G1), FOS (Sigma-Aldrich, St. Louis, MO, USA; G2), inulin (Sigma-Aldrich; G3), L. plantarum FBT215 (G4), FOS + L. plantarum FBT215 (G5), and inulin + L. plantarum FBT215 (G6) treatment groups.

Probiotic, prebiotic, and probiotic + prebiotic treatments

L. plantarum FBT215 was administered orally as a potential probiotic strain at a concentration of 1 × 1010 CFU/mice/day for 4 weeks. Probiotic, prebiotic, and probiotic + prebiotic combination treatments were each dissolved in 0.15 mL of water. The mice in G1 were treated with 0.15 mL of water only; those in G2 and G3 were treated with 0.15 g of FOS and inulin, respectively; those in G4 were treated with 1 × 1010 CFU/mice/day of L. plantarum FBT215; and those in G5 and G6 were each treated with 1 × 1010 CFU/mice/day of L. plantarum FBT215 combined with 0.15 g of either FOS or inulin, respectively. Over a 4-week period, the mice were gavaged orally for the first 2 weeks and probiotic and/or prebiotic were provided ad libitum for the last 2 weeks by mixing with Labdiet 5053 (Orientbio, Sungnam, Korea). After the 4-week experimental period, the mice were sacrificed using CO2 inhalation and their cecal tissues were collected. Tissue samples were immediately frozen at – 80℃.

Sampling, 16S rRNA gene sequencing, and bioinformatic analysis

The cecal samples were used for analysis of the intestinal microbiota composition. Libraries were constructed using a Herculase II Fusion DNA Polymerase Nextra XT Index Kit V2 (Macrogen, Daejeon, Korea) according to 16S Metagenomic Sequencing Library Preparation Part #15044223 Rev. B. The V3–V4 region was amplified to construct the libraries using the Bakt_341F (5′-CCTACGGGNGGCWGCAG-3′) and 805R (5′-GACTACHVGGGTATCTAATCC-3′) primer set. These libraries were sequenced via the MiSeq Illumina platform. To produce amplicon sequence variants (ASVs), the Divisive Amplicon Denoising Algorithm 2 (DADA2) was used for denoising. Prior to this analysis, both the adapters and primers were removed via Cutadapt. Quality filtering, merging, and chimera removal were then performed using DADA2.

γ-Aminobutyric acid measurement via an enzyme-linked immunosorbent assay

γ-Aminobutyric acid (GABA) concentrations in the cecal tissues were measured using a GABA enzyme-linked immunosorbent assay (ELISA; LDN Immunoassays, Nordhorn, Germany). Samples were diluted 1:10 (w/v) in lysis solution (0.1 N of HCl, 1 mM of EDTA, and 4 mM of sodium metabisulphite) and homogenized. After centrifugation at 5000 × g for 5 min, the resultant aqueous solution was used to quantify GABA according to the ELISA manufacturer’s instructions. All reactions were performed in duplicate and measured at 450 nm.

Statistical analysis

A t-test was used to determine the differences between two groups, e.g., the control group and an experimental group. Statistical analyses were performed via IBM SPSS statistics 26 (IBM Corp., Armonk, NY, USA), and p < 0.05 was considered statistically significant.

Results and discussion

The 16S rRNA gene sequencing conducted for each sample generated > 140,000 reads. The number of ASVs produced using denoising methods was 39,401–86,598 after filtering, denoising, and chimera removal. The average GC content was 55.04%, and the rarefaction curve reached a plateau depending on the sequencing depth (data not shown). As > 100,000 reads per sample is generally regarded as a sufficient number for the analysis of gut microbiota (Illumina, 2013), the number of reads obtained via our methods was sufficient for the present analysis.

Relative abundance of bacterial composition

The intestinal microbiota structure can be altered by various factors, including drugs, toxins, and pathogens, but particularly by diet (Carding et al., 2015). FOS and inulin are generally regarded as prebiotics that selectively stimulate the growth of gut microorganisms (Ballan et al., 2020). Previous study found that FOS improves intestinal conditions and regulates the immune system (Fukasawa et al., 2010). In the present study, the effects of L. plantarum FBT215, prebiotics, and combinations of these treatments on the gut microbiota composition were examined, and the relative abundance of phyla and genera is shown in Figs. 1 and 2, respectively.

Fig. 1
figure 1

Composition of bacterial taxa at the phylum level. A Stacked bar graph showing the relative abundance of phyla in G1–G6. Bar graphs showing the relative abundance of B Bacteroidetes, C Firmicutes, and D Proteobacteria. *p < 0.05 and **p < 0.01 represent significant differences compared with the control group

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Fig. 2
figure 2

Composition of bacterial taxa at the genus level. A Stacked bar graph showing the relative abundance of genera in G1–G6 (at least one sample > 1%). Bar graphs showing the relative abundance of B Muribaculum, C Duncaniella, D Kineothrix, and E Bacteroides. *p < 0.05 and **p < 0.01 represent significant differences compared with the control group

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Bacteroidetes (55.68–81.52%) was the most abundant phylum in all groups, followed by Firmicutes (10.40–38.25%) and Proteobacteria (0.65–6.60%) (Fig. 1). The abundance of Bacteroidetes was significantly increased in all groups except G4 (Fig. 1B), whereas the abundance of Firmicutes was significantly decreased in all groups (Fig. 1C). The abundance of Proteobacteria increased in G4 like previous study that administered the L. plantarum ZDY2013 for 3 weeks (Xie et al., 2016) but decreased in the combined treatment groups (Fig. 1D). Proteobacteria decreased in existing study using synbiotics composed of Bifidobacterium longum and inulin-based prebiotics (MacFarlane et al., 2013). However, further study will be needed to identify the association between probiotic L. plantarum and/or prebiotics in Proteobacteria abundance. Similarly, previous research showed that the abundance of Bacteroidetes and Firmicutes increased and decreased, respectively, when FOS and inulin were administered (Zhu et al., 2017). In the present study, treatment with L. plantarum FBT215 significantly reduced the F/B ratio. Several dysbiosis-related diseases, such as obesity or inflammatory bowel disease, are associated with an increase or decrease in the F/B ratio, and effects of this ratio are known to differ according to probiotic administration (Stojanov et al., 2020). Indeed, balancing the F/B ratio is important for improving dysbiosis and maintaining health (Stojanov et al., 2020); thus, L. plantarum FBT215 could potentially be used in supplements for improving, for example, obesity. However, further studies on the efficacy of L. plantarum FBT215 supplementation are needed in obese mice.

The most abundant genus was Muribaculum (49.18–68.79%), followed by Duncaniella (2.56–6.99%) (Fig. 2), and these two genera were significantly more abundant in the experimental groups than in the control group, which explains the increase in the abundance of Bacteroidetes (Fig. 2B and C). Previous studies have indicated that Muribaculum is depleted under inflamed conditions (Dobranowski et al., 2019; Zhou et al., 2022), and the abundance of Muribaculum intestinale is reduced in mice with Crohn’s disease (Dobranowski et al., 2019). Duncaniella is known to help protect the host from dextran sulfate sodium-induced colonic injury (Chang et al., 2021). In contrast, the abundance of Kineothrix (0.58–6.82%), a butyrate-producing bacteria (Haas and Blanchard, 2017), significantly decreased in G4–G6 (Fig. 2D), and the abundance of Bacteroides, i.e., acetate-, propionate-, and lactate-producing bacteria, increased in G3 and G5–G6 (Fig. 2E). SCFAs, including acetate and butyrate, are synthesized by intestinal microbiota via indigestible carbohydrate fermentation, and the concentration of SCFAs is influenced by external factors, including probiotic usage, which regulate the gut microbiota structure (Cui et al., 2022). Although the abundance of certain SCFAs-producing bacteria decreased in several experimental groups, it remains necessary to determine how the concentration of SCFAs changes with the administration of probiotics and/or prebiotics. At the species level, L. plantarum increased markedly, as expected, in G4–G6 following treatment with L. plantarum FBT215 (data not shown).

Diversity of gut microbiota

To identify the diversity of bacterial communities within (α) and between (β) groups, various parameters were used. For α diversity, the Shannon, Inverse Simpson, and Chao1 indices (Fig. 3A–C, respectively) were measured. All experimental groups except G4 showed significantly decreased Shannon index values, which provides more weight to the value of species richness than evenness in measurement (Kim et al., 2017), and Inverse Simpson index values (Fig. 3A and B). These findings are consistent with a previous study in which the Shannon index decreased after FOS, L. plantarum, and L. plantarum + FOS supplementations (Cui et al., 2022). However, according to the Chao1 index, species richness increased in the probiotic treatment group (Fig. 3C), whereas it decreased in a previous study using L. plantarum ST-III (Cui et al., 2022). Therefore, L. plantarum FBT215-fed mice had more rare microbial species and a higher abundance of microbial species than the control mice. Good’s coverage index (Fig. 3D) of all groups was > 0.99, indicating that only 1% of reads were not covered during sequencing, i.e., > 99% of the total species were represented in the analysis and the degree of sequencing coverage was high.

Fig. 3
figure 3

Boxplots of α diversity parameters. Boxes represent the interquartile range between 25 and 75th percentiles. Horizontal line in the box is the median value. A Shannon, B Inverse Simpson, C Chao1, and D Good’s coverage indice in G1–G6. *p < 0.05, **p < 0.01, and ***p < 0.001 represent significant differences compared with the control group

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To assess β diversity, principal coordinate analysis (PCoA) was performed (Fig. 4). According to weighted UniFrac, which considers species abundance (Chen et al., 2012), the distribution of the control group was clustered far from the experimental groups, and the two clusters were statistically different (Fig. 4A and C). However, a plot based on the unweighted UniFrac distance, which calculates only the presence or absence of species (Chen et al., 2012), showed an ambiguous dispersion among the G1–G4 groups. The distribution of G5 and G6 groups were different with other groups. However, there were no statistically significant differences (Fig. 4B and D). These results suggest that the experimental treatments may not affect the growth of new microorganisms in mice but may affect the growth of existing microorganisms.

Fig. 4
figure 4

PCoA plots based on microbial ASVs of samples. A, C Weighted UniFrac distance and B, D unweighted UniFrac distance are represented by two-dimensional plots and boxplots. ***p < 0.001 represents significant difference compared with the control group

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GABA concentrations in cecal content

L. plantarum FBT215 is a GABA-producing bacterium (Kim et al., 2022). Thus, GABA concentrations were measured after dietary treatments. GABA levels were significantly higher in L. plantarum FBT215-fed groups than in the control group (Fig. 5). However, there were no significant differences between the G4 and G5–G6 groups. Previous study showed that GABA concentrations significantly different according to the type of prebiotics in vitro (Kim et al., 2022), but further research about the effects of probiotics and/or prebiotics on GABA production will be needed in vivo. Thus, these results provide some evidence of a relationship between GABA-producing bacteria and health benefits.

Fig. 5
figure 5

GABA concentrations in cecal content using ELISA. *p < 0.05 and **p < 0.01 represent significant differences compared with the control group

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In general, the diversity of intestinal microbiota increases with health status (Larsen and Claassen, 2018). Our data show that the administration of probiotics and/or prebiotics alters the intestinal microbiota structure and the indices of microbial diversity in mice. The F/B ratio decreased significantly in the L. plantarum FBT215 supplement group, indicating that L. plantarum FBT215 has the potential to increase and decrease Bacteroidetes and Firmicutes levels, respectively, and thereby help prevent obesity. One limitation of the current study that affects the interpretation of the results is the use of normal mice rather than a specific disease-induced mouse model. In addition, commonly used amounts of probiotics and prebiotics were tested without determining the probiotic concentration that produce the maximum effect and the prebiotic concentration expected to produce synergetic effects with the probiotic. Therefore, concentration of treatment that produce the synergetic effects should be tested for identifying maximum effect in future studies. Nevertheless, we found that L. plantarum FBT215 dietary supplementation with or without prebiotics can alter the abundance of bacteria in the intestine of mice.