J Neurogastroenterol Motil 2024; 30(2): 236-250  https://doi.org/10.5056/jnm23096
The Effect of Clostridium butyricum on Gut Microbial Changes and Functional Profiles of Metabolism in High-fat Diet–fed Rats Depending on Age and Sex
Soo In Choi,1,2 Nayoung Kim,1,2* Yonghoon Choi,1 Ryoung Hee Nam,1 Jae Young Jang,1,3 and Sung-Yup Cho4
1Department of Internal Medicine, Seoul National University Bundang Hospital, Seongnam, Gyeonggi-do, Korea; and Departments of 2Internal Medicine, 3Medical Device Development, and 4Biomedical Sciences, Seoul National University College of Medicine, Seoul, Korea
Correspondence to: *Nayoung Kim, MD, PhD
Department of Internal Medicine, Seoul National University Bundang Hospital, 82 Gumi-ro, 173 beon-gil, Bundang-gu, Seongnam, Gyeonggi-do 13620, Korea
Tel: +82-31-787-7008, E-mail: nakim49@snu.ac.kr, nayoungkim49@empas.com
Received: June 29, 2023; Revised: October 24, 2023; Accepted: November 16, 2023; Published online: April 30, 2024
© The Korean Society of Neurogastroenterology and Motility. All rights reserved.

cc This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract
Background/Aims
A high-fat diet (HFD) causes dysbiosis and promotes inflammatory responses in the colon. This study aims to evaluate the effects of Clostridium butyricum on HFD-induced gut microbial changes in rats.
Methods
Six-week-old Fischer-344 rats with both sexes were given a control or HFD during 8 weeks, and 1-to-100-fold diluted Clostridium butyricum were administered by gavage. Fecal microbiota analyses were conducted using 16S ribosomal RNA metagenomic sequencing and predictive functional profiling of microbial communities in metabolism.
Results
A significant increase in Ruminococcaceae and Lachnospiraceae, which are butyric acid-producing bacterial families, was observed in the probiotics groups depending on sex. In contrast, Akkermansia muciniphila, which increased through a HFD regardless of sex, and decreased in the probiotics groups. A. muciniphila positively correlated with Claudin-1 expression in males (P < 0.001) and negatively correlated with the expression of Claudin-2 (P = 0.042), IL-1β (P = 0.037), and IL-6 (P = 0.044) in females. In terms of functional analyses, a HFD decreased the relative abundances of M00131 (carbohydrate metabolism module), M00579, and M00608 (energy metabolism), and increased those of M00307 (carbohydrate metabolism), regardless of sex. However, these changes recovered especially in male C. butyricum groups. Furthermore, M00131, M00579, and M00608 showed a positive correlation and M00307 showed a negative correlation with the relative abundance of A. muciniphila (P < 0.001).
Conclusion
The beneficial effects of C. butyricum on HFD-induced gut dysbiosis in young male rats originate from the functional profiles of carbohydrate and energy metabolism.
Keywords: Clostridium butyricum; Gastrointestinal microbiome; High-fat diet; Metabolism; Probiotics
Introduction

Notably, dysbiosis in gut microbiota is not only linked with gastrointestinal disorders, such as irritable bowel syndrome (IBS) or inflammatory bowel disease,1 but also involved in systemic metabolism.2,3 The gut microbial composition changes dynamically depending on the age, sex, and diet,4,5 and recent studies have shown that these microbial changes contribute to numerous physiological effects, including the modulation of energy homeostasis, glucose/lipid metabolism, inflammation, immunity, and cancer.6,7 Additionally, recent studies have investigated microbiota metabolites and metabolic pathway changes in microorganisms that affect host metabolism.8-11 Metabolites, such as short-chain fatty acids (SCFAs) not only improve host immunity but also have beneficial effects on pathogenic bacteria, such as Staphylococcus aureus, pathogenic Escherichia coli, and Campylobacter jejuni.8 Naturally, Firmicutes and Clostridium clusters utilize dietary fiber producing butyric acid which is the most important metabolite.12 Probiotics, a mixture of live bacteria, induce taxonomic changes in microbial composition and improve IBS and the immune system.13,14 A previous study found an improvement in high-fat diet (HFD)-induced colonic inflammation by Clostridium butyricum and Biovita through the production of butyric acid in young F344 rats, and the changes were found to be more distinguished in males than in females.15 The commercialized probiotic complex with 3 bacterial species, anaerobic C. butyricum, facultative anaerobe Lactobacillus sporogenes, and aerobic Bacillus subtilis, Biovita (Ildong Pharmaceutical, Co, Ltd, Seoul, Korea) has been widely used to treat constipation, loose stool, abdominal bloating, and functional gastrointestinal disorders from their various proliferative sites depends on oxygen concentration of gastrointestinal tract.16 Moreover, all 3 bacteria could form spore which keeps probiotics easy to store and stable delivery to the intestine.

As the gut microbiota continuously adapts to the host environment and serves multiple critical functions for their hosts, many researches were focused on discovering association between the gut dysbiosis and metabolic disorders, such as diabetes. However, it is hard to make clear the order of the incidence of these associations. Therefore, current researches attempt to investigate how gut microbes communicate with our body systems through microbiota-derived metabolites and how they are able to modulate host physiology with various omics tools.17 For example, amino acid and carbohydrate metabolic genes, which were enriched in patient groups, decreased with symptomatic improvement by low fermentable oligosaccharides, disaccharides, monosaccharides, and polyols (FODMAPs).10 Metataxonomic sequencing of highly conserved 16S ribosomal RNA (rRNA) is commonly used to identify the composition of the bacterial community of gut microbiota.18 With numerous studies on the taxonomic diversity of microbiota under healthy and diseased conditions, scholars have attempted to not only determine harmful bacterial strains for the host but also the microbial metabolism that influences the host, such as the butyric acid-producing ability. The analysis using phylogenetic investigation of communities by reconstruction of unobserved states (PICRUSt) can help predict the genes present in the microbiota community based on the Kyoto Encyclopedia of Genes and Genomes (KEGG) orthology.19 For instance, a recent study suggested that early-onset colorectal cancer can be distinguished from late-onset colorectal cancer using integrated metagenomic and metabolomic analyses.20

Based on this background, we hypothesized that C. butyricum can improve HFD-induced dysbiosis through the functional profiling of microbial communities, and that its effects would differ regarding sex. The purpose of this study is to assess Biovita, especially C. butyricum, as a possible probiotic on HFD-induced dysbiosis in F344 rats, and to analyze the predictive functional profiling of microbial communities in carbohydrate, energy, and lipid metabolism based on KEGG modules.

Materials and Methods

Study Design

We used 6-week-old specific pathogen-free Fischer-344/NSIc rats of both sexes (Orient, Seoul, Korea).21,22 The rats were bred under specific pathogen-free conditions at 23°C under 12 hour:12 hour light-dark cycles. Two different diets were fed to each group ad libitum: chow diet and a HFD (chow: 3.85 kcal/g; HFD: 5.24 kcal/g, 60% kcal from fat; Research Diets, Inc, New Brunswick, NJ, USA). Probiotics were orally gavaged daily between 10 AM and 11 AM regularly through oral zonde. The concentrations used were decided by referring to prior experiments22,23 conducted to determine dose dependency of these concentrations; the final effective concentrations of C. butyricum were 1.23 × 109 colony-forming units (CFU)/mL. Thus, there were 1 × 107 CFU/mL of C. butyricum in Biovita and low-concentration C. butyricum groups; 1 × 108 CFU/mL of C. butyricum in medium-concentration C. butyricum group; and 1 × 109 CFU/mL of C. butyricum high concentration C. butyricum group, respectively. As Biovita is probiotic complex, Biovita consisted of not only C. butyricum IDCC 1301, but also mixed with L. sporogenes IDCC 1201 and Bacillus subtilis IDCC 1101 (Ildong Pharmaceutical, Co, Ltd). All probiotics were orally gavaged with dissolved form phosphate buffered saline. In the non-probiotics group, pure phosphate buffered saline was orally gavaged as control. The total volume of gavaged solution was 2 mL of each group.

The diet and administration of probiotics in each group has been described in detail in a previous paper and are shown in Supplementary Figure 1.15 As there is an abbreviation for each group, the name and number of rats in each group are as follows (Supplementary Fig. 1A): males with a control diet (M. CON, n = 8); female rats with a chow diet (F. CON, n = 8); males with a HFD (M. HFD, n = 8); females with a HFD (F. HFD, n = 8); males with a HFD and Biovita (M. Bio, n = 8); females with the HFD and Biovita (F. Bio, n = 8); males with a HFD and low concentrations of C. butyricum (M. LCB, n = 8); females with a HFD and low concentrations of C. butyricum (F. LCB, n = 8); male rats with a HFD and medium concentrations of C. butyricum (M. MCB, n = 8); female rats with a HFD and medium concentrations of C. butyricum (F. MCB, n = 8); male with a HFD and high concentrations of C. butyricum (M. HCB, n = 8); and females with a HFD and high concentrations of C. butyricum (F. HCB, n = 8).

After the feeding period, terminal anesthesia was induced through carbon dioxide inhalation. Feces and colon tissue were obtained and stored at –80℃ immediately for further analysis.

This study was conducted according to the recommendations of the Guide for the Care and Use of Laboratory Animals in South Korea. The protocol was approved by the Institutional Animal Care and Use Committee of Seoul National University Bundang Hospital (Permission No. BA1506-178/027-01).

Fecal Sample Collection and Metagenome Sequencing

Bacterial genomic DNA was extracted from frozen fecal samples using a QIAamp DNA Stool Mini Kit (Qiagen, Valencia, CA, USA) according to the manufacturer’s recommendations. DNA quantity and quality were measured using a NanoDrop 1000 spectrophotometer (Thermo Fisher Scientific, Wilmington, DE, USA) and electrophoresed using 2% agarose gel. To prepare MiSeq library amplicons, the target gene, the 16S ribosomal RNA V3-V4 region, was first amplified using the 341-F (5’-TCG TCG GCA GCG TCA GAT GTG TAT AAG AGA CAG CCT ACG GGN GGC WGC AG-3’) and 805-R (5’-GTC TCG TGG GCT CGG AGA TGT GTA TAA GAG ACA GGA CTA CHV GGG TAT CTA ATC C-3’) primers. Secondly, the V3-V4 PCR amplicons were linked to the Illumina indices and adapters from Nextera XT Index Kit (Illumina, San Diego, CA, USA). Short DNA fragments were eliminated using a PrepTM DNA Purification Kit (Favorgen, Pintung, Taiwan). To quantify the polymerase chain reaction (PCR) amplicons, we used the Quant-iT PicoGreen dsDNA Assay Kit (Thermo Fisher Scientific). Sequencing was conducted at ChunLab, Inc (Seoul, Korea) using a MiSeq system (Illumina).

Non-specific, non-target, and chimeric amplicons were removed from the pre-filter during the quality control process to exclude reads with short lengths and low Q values. Using operational taxonomic unit (OTU) information (number of OTUs and sequences in each OTU), α-diversity, Chao1, and Shannon indices were analyzed using EzBioCloud (Chunlab, Inc). To visualize sample differences, selected taxa were created using GraphPad Prism (version 8.01; GraphPad Software, Inc, San Diego, CA, USA). The unprocessed raw sequence reads datasets about 16S ribosomal RNA gene generated for this study are available in the NCBI Sequence Read Archive (BioProject PRJNA862315, Accession No. SRR20646232~SRR20646353).

Functional Profiling of the Fecal Microbial Community Using Phylogenetic Investigation of Communities by Reconstruction of Unobserved States

To predict the functional profiles of the microbial community, a phylogenetic investigation of the communities was conducted by PICRUSt. This analysis enabled us to infer alterations in the functional markers of the microbiota based on the KEGG database.19,24

Statistical Methods

All statistical calculations, except for those of the pyrosequencing data, were conducted using PASW Statistics for Windows, version 18.0 (Released 2009; IBM Corp, Armonk, NY USA). Groups were compared using the Mann-Whitney U test (also known as the Wilcoxon rank-sum test). Correlations between gene expression and species were determined using Spearman’s correlation. Statistical significance was set at P < 0.05.

Results

The Body Weight Change During High-fat Diet

The changes in calorie intake and weight gain in each group are shown in Supplementary Figure 1. The average calorie intake was higher in the HFD group than in the control group in males (M. CON vs M. HFD, P = 0.021) (Supplementary Fig. 1B). The total body weight gain also showed a similar pattern to that of the total calorie intake. In particular, the total body weight was higher in the HFD group than in the control group in both male and female rats (F. CON vs F. HFD, P = 0.027) (Supplementary Fig. 1E), and was lower in the Biovita and C. butyricum groups than in the HFD group in both males (M. Bio, P = 0.021; M. LCB, P = 0.002; M. MCB, P = 0.002; M. HCB, P = 0.001; all groups were compared at M. HFD, respectively) (Supplementary Fig. 1D) and females (F. MCB, P = 0.009; F. HCB, P = 0.002; all groups were compared at F. HFD, respectively) (Supplementary Fig. 1E).

Changes in the Composition of Fecal Microbiota

Differences in the relative abundance at the phylum level, α-diversity index Chao1, and Shannon species richness index in each group are shown in Figure 1. Compared with those in control group, the Bacteroidetes and Verrucomicrobia phyla decreased (male, P = 0.001; female, P = 0.001) and increased (male, P = 0.001; female, P = 0.002), respectively, after a HFD was provided to both males and females. After administration of C. butyricum, HFD-induced Verrucomicrobia phylum decreased compared with that in the HFD groups in both males (M. HFD vs M. LCB, P = 0.003; M. HFD vs M. HCB, P = 0.027) (Fig. 1A) and females (F. HFD vs F. HCB, P = 0.030; Fig. 1B).

Figure 1. The characteristics of the stool microbiome. (A, B) The composition of each group at the phylum level. Bacteroidetes were commonly decreased by feeding rats with a high-fat diet (HFD). (C, D) The species richness was estimated by the Chao1 index. The Chao1 index decreased in the HFD group compared with the control group, regardless of sex, which was recovered by probiotic administration. (E, F) The Shannon index decreased in the HFD group compared with the control group, regardless of sex. M, male; F, female; CON, control diet; Bio, HFD with Biovita administration; LCB, HFD with a low concentration of Clostridium butyricum; MCB, HFD with a medium concentration of C. butyricum; and HCB, HFD with a high concentration of C. butyricum.

The α-diversity Chao1 in males, it was significantly decreased α-diversity in the HFD group compared with the control group was increased by administration of Biovita and low concentrations of C. butyricum (M. Bio, P = 0.009; M. LCB, P = 0.012; all groups were compared at M. HFD, respectively) (Fig. 1C). In females, the three concentrations of C. butyricum significantly increased the α-diversity compared with that in the HFD group (F. LCB, P = 0.012; F. MCB, P = 0.021; F. HCB, P = 0.009 compared to F. HFD, respectively) (Fig. 1D).

The other α-diversity Shannon species richness index significantly decreased after HFDs in all groups, regardless of sex (Fig. 1E and 1F). However, Biovita and C. butyricum did not show significant changes in the Shannon species richness index compared with that in the HFD group.

The Changes in Relative Abundances of Ruminococcaceae, Lachnospiraceae, and Akkermansia muciniphila

The changes in relative abundances of Ruminococcaceae, Lachnospiraceae, and Akkermansia muciniphila were analyzed because these families produce butyric acid.25,26 Ruminococcaceae decreased after HFD in both males (M. CON vs M. HFD, P = 0.059; Fig. 2A) and females (F. CON vs F. HFD, P = 0.021; Fig. 2B), which was increased by the administration of a high concentration of C. butyricum in females (F. HCB vs F. HFD, P = 0.036).

Figure 2. The compositional change of high-fat diet (HFD) and probiotic administration at the (A-D) family and (E, F) species levels. (A, B) Ruminococcaceae decreased in the HFD group regardless of sex, and especially increased in the female group administered a high concentration of Clostridium butyricum (P = 0.036) compared with the HFD group. (C, D) Lachnospiraceae family increased in female HFD group. However, C. butyricum administration increased Lachnospiraceae in the male group (low concentration, P = 0.021; high concentration, P = 0.027) compared with the HFD group. (E, F) Compared with the HFD group, Akkermansia muciniphila species increased in the HFD group regardless of sex, and decreased in the male group administered low and high concentrations of C. butyricum (low, P = 0.003; high, P = 0.027) and the female group administered a high concentration of C. butyricum (P = 0.030).

In males, Lachnospiraceae decreased by HFD but significantly increased after treatment with high concentrations C. butyricum (M. HFD vs M. LCB, P = 0.021; M. HFD vs M. HCB, P = 0.027) (Fig. 2C). These changes were not observed in females (Fig. 2D).

A. muciniphila increased after a HFD in both male rats and female rats (M. CON vs M. HFD, P = 0.001; F. CON vs F. HFD, P = 0.002) but decreased after the administration of C. butyricum (M. HFD vs M.LCB, P = 0.003; M. HFD vs M. HCB, P = 0.027; F. HFD vs F. HCB, P = 0.030) (Fig. 2E and 2F).

The Correlation Between Akkermansia muciniphila and Colonic Mucosal Environment

To assess the influence of gut microbial changes on colonic epithelial cell status, we determined mRNA expression in the colonic mucosa in a previous study.15 The results of mRNA expression levels in colonic mucosa were compared with those of the relative abundance of A. muciniphila, which could be the key microbial member influence to colonic mucosal environment comprising stool microbiota with an average of 20% in all groups (Fig. 3). First, we compared the correlation between A. muciniphila and tight junction protein gene expression. In males, cldn1 showed positive correlations with A. muciniphila abundance (Spearman ρ = 0.512, P < 0.001; Fig. 3A), whereas in females, a negative correlation was observed between cldn2 and A. muciniphila (Spearman ρ = –0.297, P = 0.042; Fig. 3B). In contrast, in the case of inflammatory cytokines, both IL-1β gene (Spearman ρ = –0.302, P = 0.037; Fig. 3C) and IL-6 gene (Spearman ρ = –0.295, P = 0.044; Fig. 3D) negatively correlated with A. muciniphila in females. Moreover, we compared the concentration of SCFAs in the feces with the relative abundance of A. muciniphila (Supplementary Fig. 3). Notably, A. muciniphila, which produces SCFAs,27 negatively correlated with fecal acetic acid (Supplementary Fig. 3A) and butyric acid (Supplementary Fig. 3B).

Figure 3. Correlation between Akkermansia muciniphila and the gene expression of colonic epithelial tight junction protein and inflammatory cytokines. A. muciniphila positively correlated with claudin-1 (cldn1) gene expression in males rats (A, P < 0.001), and negatively correlated with claudin-2 (cldn2) gene expression in females rats (B, P = 0.042). Conversely, in females, the relative abundance of A. muciniphila negatively correlated with inflammatory cytokines, IL-1β (C, P = 0.037), and IL-6 (D, P = 0.044). The statistical significance was determined by Spearman’s correlation. CON, control diet; HFD, high-fat diet; Bio, HFD with Biovita administration; LCB, HFD with a low concentration of Clostridium butyricum; MCB, HFD with a medium concentration of C. butyricum; HCB, HFD with a high concentration of C. butyricum.

Predictive Functional Profiling of Microbial Communities in Carbohydrate and Energy Metabolism

We conducted the predictive functional profiling of microbial communities in carbohydrate and energy metabolism based on the KEGG modules, and the representative modules in each group are indicated as heatmaps and scatter graphs (carbohydrate metabolism, Fig. 4A; energy metabolism, Fig. 5A). As shown in the figures, the functional profiles showed different responses to diet and probiotics according to the age and sex.

Figure 4. Predictive functional profiling of microbial communities through the Kyoto Encyclopedia of Genes and Genomes (KEGG) database regarding carbohydrate metabolism based on KEGG modules. (A) The modules that showed significant difference between groups are represented as a heatmap, depending on the sex. The significantly different modules are shown in the scatter graph. (B) M00131, inositol phosphate metabolism, Ins(1,3,4,5)P4 → Ins(1,3,4)P3 → myo-inositol; (C) M00307, Pyruvate oxidation, pyruvate → acetyl-CoA. Akkermansia muciniphila showed negative correlation with M00131 (D, P < 0.001) and positive correlation with M00307 (E, P < 0.001). CON, control diet; HFD, high-fat diet; Bio, HFD with Biovita administration; LCB, HFD with a low concentration of Clostridium butyricum; MCB, HFD with a medium concentration of C. butyricum; HCB, HFD with a high concentration of C. butyricum.

Figure 5. Predictive functional profiling of microbial communities through the Kyoto Encyclopedia of Genes and Genomes (KEGG) database regarding energy metabolism based on KEGG modules. (A) The modules that showed significant differences between groups are represented as a heatmap, depending on the sex. The significantly different modules are shown in the scatter graph. (B) M00579, phosphate acetyltransferase-acetate kinase pathway, acetyl-CoA → acetate; (C) M00608, 2-oxocarboxylic acid chain extension, 2-oxoglutarate → 2-oxoadipate → 2-oxopimelate → 2-oxosuberate. Akkermansia muciniphila showed negative correlations with M00131 (D, P < 0.001) and M00307 (E, P < 0.001). CON, control diet; HFD, high-fat diet; Bio, HFD with Biovita administration; LCB, HFD with a low concentration of Clostridium butyricum; MCB, HFD with a medium concentration of C. butyricum; HCB, HFD with a high concentration of C. butyricum.

In carbohydrate metabolism, the relative abundance of M00131 (inositol phosphate metabolism, Ins(1,3,4,5)P4 to Ins(1,3,4)P3 to myo-inositol; Fig. 4B) decreased after HFD, whereas that of M00307 (pyruvate oxidation, pyruvate to acetyl-CoA; Fig. 4E) increased. However, C. butyricum increased the relative abundance of M00131 (MHF vs MLCB, P = 0.009; MHF vs MMCB, P = 0.009) (Fig. 4B) and decreased that of M00307 (MHF vs MLCB, P = 0.012; MHF vs MMCB, P = 0.036; MHF vs MHCB, P = 0.027) (Fig. 4C) among males.

Subsequently, we compared the relative abundances of the metabolic modules and A. muciniphila as a metabolic regulator under HFD condition in the colonic mucosa. M00131, which was decreased by HFD, showed a negative correlation with A. muciniphila (Spearman ρ = –0.609, P < 0.001; Fig. 4D), whereas M00307, which was increased by a HFD, positively correlated with A. muciniphila (Spearman ρ = 0.756, P < 0.001; Fig. 4E).

Considering energy metabolism, the relative abundance of all modules significantly decreased after HFD (M00579: phosphate acetyltransferase-acetate kinase pathway, acetyl-CoA to acetate; M00608: 2-Oxocarboxylic acid chain extension, 2-oxoglutarate to 2-oxoadipate to 2-oxopimelate to 2-oxosuberate) in both male rats and female rats (Fig. 5B and 5C). However, differences were observed in the response to probiotics between males and females; the relative abundances of M00579 (Fig. 5B) and M00608 (Fig. 5C) increased after the administration of Biovita or C. butyricum to males but not females. Especially, C. butyricum increased the relative abundance of M00579 (MHF vs MLCB, P = 0.012; MHF vs MMCB, P = 0.036; MHF vs MHCB, P = 0.046) (Fig. 5B) in males.

The comparison of the relative abundances of the modules and A. muciniphila indicated that the module showed decreased relative abundance in the HFD group, and both M00579 (Spearman ρ = –0.702, P < 0.001; Fig. 5D) and M00608 (Spearman ρ = –0.329, P = 0.001; Fig. 5E) showed significant negative correlations with A. muciniphila.

Discussion

HFD and obesity have been associated with intestinal inflammation28,29 and one of its known mechanisms was profound alterations in gut microbiota composition, resulting in immunological dysregulation and inflammation.30,31 For instance, HFD induces a decrease in Bacteroidetes and an increase in Firmicutes in both animals and humans.32 Additionally, HFD is known to significantly affect the gut bacterial ecosystem at the functional level, altering the hormonal and immune systems and bile acid metabolism.33 As butyric acid is known to reduce inflammatory responses and modulates immune intervention experiments regarding butyric acid producing probiotic is needed.

In our study, we observed a decrease in species richness and relative abundance of beneficial bacteria and an increased Firmicutes/Bacteroidetes ratio after a HFD, regardless of sex, suggesting that HFD caused intestinal inflammation. In previous studies, HFD-induced inflammatory responses showed age and sex differences, and the gut microbiota composition and butyrate levels changed with age in rats.34,35 In addition, intestinal inflammation induced by the water avoidance stress test was more prominent in female rats, and the responses to the administration of the probiotic Lactobacillus farciminis were also more prominent in females.36 In contrast, the effect of C. butyricum on HFD-induced intestinal inflammation was more prominent in males than in females.15 In the present study, the effect of Biovita and C. butyricum was different depending on sex. The Firmicutes/Bacteroidetes ratio, which is known to increase with obesity and a HFD, was not evident in our present study. In contrast, α-diversity indices, such as species richness (Chao1) and the relative abundance of beneficial bacteria, Ruminococcaceae and Lachnospiraceae, and butyric acid-producing bacterial families were more prominent. This effect was supported by the increased concentration of fecal butyric acid by administration of C. butyricum groups.15

The composition of the microbiota community along the gastrointestinal tract is highly versatile not only by the location, but by the age, host diet, and disease status.37,38 Generally, the normal gut microbiota forms a stable bacterial composition that is resistant to foreign bacteria, including pathogens, known as “colonization resistance.”39 We assume this colonization resistance as a reason why probiotics that were orally gavaged daily, namely, Biovita and C. butyricum, were not detected in any of the administered rats. Several studies have reported that expected therapeutic bacteria already affect the existing gut microbiota but are not significantly detected even after long-term administration.40-42 Additionally, evidence shows that some dead strains still show natural advantages as probiotic.43-45 Although C. butyricum was not detected in our fecal samples, it altered the ability to change the gut microbiome. As shown in Supplementary Figure 2, the butyric acid concentrations in feces were lower in whole HF diet groups, while those in C. butyricum administration groups showed recovery in males (MHF vs MLCB, P = 0.012; MHF vs MHCB, P = 0.003) (Supplementary Fig. 2A). Fecal microbiota transplantation (FMT), the administration of a fecal suspension containing the normal gut microbiota from a healthy donor to the gut of patients with gastrointestinal diseases directly, is another known therapeutic agent for gut dysbiosis.46 Recently, 3 years follow up from FMT of 125 patients with IBS showed about 77.8% in response to FMT and greater quality of life with safe FMT protocol.47 However, the way of FMT is invasive to patients more than probiotics usage, and the cost problem is also an obstracle to patients.

When we conducted additional functional analyses to evaluate the effect of probiotics on host metabolism, the HFD induced the deterioration of carbohydrate and energy metabolism, and the administration of C. butyricum reversed this effect. Moreover, the small intestine, where digested nutrients such as carbohydrates are absorbed, is also residence of gut microbiota. For instance, there are approximately 107-8 CFU/mL including C. butyricum in the distal ileum, which might modulate metabolism depending on host diet.48 However, the activity of each metabolic module showed different responses to the HFD and probiotic administration according to sex. Notably, the gut microbiota plays a role in controlling host metabolism, and intestinal inflammation deteriorates host metabolism. The gut microbiome in patients with atherosclerotic cardiovascular disease, a typical systemic metabolic disease, differed from the healthy gut microbiome in terms of higher possibility for the transport of simple sugars (phosphotransferase systems) and amino acids, while the possibility for the biosynthesis of most vitamins was lower.49 In a study on humans, stress-induced intestinal inflammation caused changes in the intestinal microbial composition (decrease in Bacteroidetes and increase in Firmicutes and several other phyla), changes in stool and plasma metabolites, and increased intestinal permeability.50 Furthermore, a study of patients with inflammatory bowel disease found a functional shift from carbohydrate and nucleotide metabolism toward increased amino acid and lipid metabolism during active inflammation.51 The decrease in energy metabolism observed in our study was consistent with these results.

Additionally, our study implies a difference in these changes between the sexes which might be related to sex differences in the gut microbiota.5 Moreover, gut microbiota regulates estrogens through the secretion of β-glucuronidase, an enzyme that deconjugates estrogens into their active forms, which is so called the “estrogen-gut microbiome axis.”52 Sex differences mainly originate from the expression of genes related to sex chromosomes or physiologic factors, such as body fat percentage; however, the gut microbiota, which are involved in the excretion, circulation, and metabolic processes of steroid sex hormones, could play a role in these differences, especially in males and postmenopausal women.53,54 As our study showed changes in the species richness and relative abundance of beneficial bacteria in the manner of sex differences, there may be a possible interaction between intestinal microorganisms and sex hormones. However, as we did not measure the activity of β-glucuronidase or analyze the microbiota that produce the β-glucuronidase in detail, this should be evaluated in future studies.

Since its isolation from human feces in 2004,55 A. muciniphila has been shown to reduce the risk of metabolic disorders by producing SCFAs from host intestinal mucin.56-58 However, in our study, we consistently confirmed an increase in A. muciniphila after long-term administration of a HFD.28,59 Furthermore, we found a negative correlation between the relative fecal abundance of A. muciniphila and fecal concentrations of acetic acid and butyric acid (Supplementary Fig. 3). One possible explanation for this unexpected negative correlation might be the environmental differences caused by the HFD. The production of SCFAs varies among A. muciniphila in different environments.60 Alternatively, the produced SCFAs may have been absorbed by colonocytes.61 However, we assumed that A. muciniphila changed the gut microbiota indirectly and that A. muciniphila affected the gut microbial composition. When we analyzed the correlation between A. muciniphila and other gut microbiota at the genus level (Supplementary Fig. 4), we identified 2 representative genera, Acetatifactor and A. muciniphila (Supplementary Fig. 4A), whereas Bacteroides showed a positive correlation with A. muciniphila. Notably, the Acetatifactor genus is not a well-known strain, and we expect that its beneficial role in the gut microbiota is attributed to its positive correlation with fecal acetic and butyric acid concentrations. However, based on the positive correlation of A. muciniphila with Bacteroides, which includes various opportunistic pathogens,62 we propose that A. muciniphila had a negative effect under HFD conditions. A few studies have reported that A. muciniphila is associated with colitis and colon cancer.63,64 The ability of A. muciniphila to degrade the intestinal mucin layer necessitates careful concern about its use as a probiotic.

This study had some limitations. As we approached fecal microbiome through “metataxonomics,” which refers the sequencing of the certain marker region, in our case, 16s ribosomal RNA gene, we could analyze our data based on the reported bacterial genome. However, the way used for metataxonomics, sequencing limited region, we could analyze the data faster but not accurate. For instance, when we tried to compare the taxonomic composition between experimental groups, lower taxonomic level, such as genus, showed about 70% of not characterized genus. Moreover, the functional profiling analysis that we conducted was predictive result based on KEGG database. In this aspect, “metagenomics,” which refers that the whole-genome shotgun sequencing might be the proper method to compare the metabolism change between the HFD and probiotics group. However, it was difficult to conduct the whole-genome sequencing to a large experimental group because of the limited resources.

In conclusion, feeding a HFD to F344 rats decreased the α-diversity, beneficial butyric acid-producing bacterial family, and carbohydrate/energy metabolism by the gut microbiome; the administration of C. butyricum showed different effects depending on their sex, and the recovery of HFD-induced changes were more prominent in male groups. These suggest that beneficial effects of C. butyricum on HFD-induced gut dysbiosis in male rats originate from the functional profiles of carbohydrate and energy metabolism (Fig. 6).

Figure 6. Graphical summary of the change of gut microbiota by a high-fat diet and Clostridium butyricum used as a probiotic. SCFAs, short-chain fatty acids.
Supplementary Materials

Note: To access the supplementary figures mentioned in this article, visit the online version of Journal of Neurogastroenterology and Motility at http://www.jnmjournal.org/, and at https://doi.org/10.5056/jnm23096.

Financial support:

This work was supported by the Seoul National University Bundang Hospital Research fund (Grant No. 06-2020-0317). In addition, this work was supported by Ildong Pharmaceutical, Co, Ltd.

Conflicts of interest

None.

Author contributions

Soo In Choi performed the animal experiment, analyzed the data, and wrote the draft; Nayoung Kim provided the key concept, designed the experiments, critically revised the manuscript; Yonghoon Choi critically revised the manuscript; Ryoung Hee Nam and Jae Young Jang performed the animal experiment prepared the stool DNA for metagenomics; and Sung-Yup Cho provided concept.

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