Article Search
닫기

Microbiology and Biotechnology Letters

보문(Article)

View PDF

Fermentation Microbiology  |  Applied Microbiology

Microbiol. Biotechnol. Lett. 2022; 50(4): 522-532

https://doi.org/10.48022/mbl.2208.08003

Received: August 7, 2022; Revised: November 14, 2022; Accepted: November 15, 2022

Cheonggukjang Fermented with Bacillus subtilis SCGB574 Ameliorates High Fat Diet-Deteriorated Large Intestinal Health in Rat Model

Jae Ho Choi1, Jiyon Kim2, Taekyun Shin3, Myeong Seon Ryu4, Hee-Jong Yang4, Do-Youn Jeong4, Hong-Seok Son5*, and Tatsuya Unno1,2*

1Subtropical/Tropical Organism Gene Bank, Jeju National University, Jeju 63243, Republic of Korea
2Faculty of Biotechnology, College of Applied Life Sciences, SARI, Jeju National University, Jeju 63243, Republic of Korea
3Department of Veterinary Anatomy, College of Veterinary Medicine and Veterinary Medical Research Institute, Jeju National University, Jeju 63243, Republic of Korea
4Department of Research and Development, Microbial Institute for Fermentation Industry (MIFI), Sunchang 56048, Republic of Korea
5Department of Food Biosciences and Technology, College of Life Sciences and Biotechnology, Korea University, Seoul 02841, Republic of Korea

Correspondence to :
Hong-Seok Son,      sonhs@korea.ac.kr
Tatsuya Unno,        tatsu@jejunu.ac.kr

Cheonggukjang is a traditional fermented food in Korea, which is known to exert beneficial effects on health. In this study, we evaluated the effects of cheonggukjang fermented by Bacillus subtilis SCGB 574 (B574) on high fat diet (HFD)-deteriorated large intestinal health. Rats were fed with HFD or HFD supplemented with 10.1% cheonggukjang (B574). Fecal microbiota was analyzed based on 16S rRNA gene sequences, and the fecal and serum metabolome were measured using GC-MS. Our results showed that SCGB574 intake significantly reduced body weight, restored tight junction components, and ameliorated inflammatory cell infiltration. SCGB574 also shifted gut microbiota by increasing the abundance of short chain fatty acid producers such as Alistipes and Flintibacter, although it decreased the abundance of Lactobacillus. Serum and fecal metabolome analyses showed significantly different metabolic profiles between the groups. The top five metabolites increased by SCGB574 were i) arginine biosynthesis, ii) alanine, aspartate, and glutamate metabolism; iii) starch and sucrose metabolism; iv) neomycin, kanamycin, and gentamicin biosynthesis; and v) galactose metabolism. These results showed that cheonggukjang fermented by SCGB574 ameliorates adverse effects of HFD through improving intestinal health.

Keywords: Bacillus subtilis SCGB574, Cheonggukjang, gut microbiota, short chain fatty acids, tight junction

Graphical Abstract


Soybean is a plant that contains various physiologically active substances, such as proteins, oligosaccharides, dietary fibers, isoflavones, saponins, lecithin, and protease inhibitors. It is known for its beneficial effects in various diseases and health aspects, such as weight control, anti-inflammation, and digestive diseases [1]. Soybeans produce short-chain fatty acids (SCFA), such as acetic acid, propionic acid, and butyric acid, which are the main energy sources for gut microbiota, and beneficial bacteria in the intestine [2, 3]. Insoluble dietary fiber, such as cellulose and lignin, promotes digestion and absorption and enhances intestinal peristalsis to improve constipation [4, 5].

Changes in the intestinal environment due to modifications in dietary habits cause changes in the gut microbiota colonies, resulting in the occurrence of inflammatory bowel disease and metabolic diseases such as autoimmune diseases, obesity, and diabetes, which have recently emerged as social problems. In particular, a high-fat diet reduces the binding force of the intestinal epithelial barrier due to imbalances in induction, change, and chronicization of gut microbiota present in the body, and intestinal leaky syndrome (leaky gut) caused by increased infection by harmful gut microbiota, as shown in an animal model. Despite the clinical significance associated with obesity-induced intestinal disease, the role of the intestinal cell binding force (tight junctions) in obese patients is still unclear.

Because of the various effects of soybeans, multiple studies have been conducted on various functional materials such as food, cosmetics, and pharmaceuticals, but there are not many studies on the tight junction function in intestinal health. Fermented soybean is a functional food that exhibits excellent biological activities, such as anti-inflammatory and immunomodulatory functions, and is a rich source of nutrients, phytochemicals, bioactive compounds, and probiotics [6]. Recent research data showed that natto and miso contain large amounts of physiologically active compounds such as nattokinase, bacilopeptidase F, vitamin K2, dipicolinic acid, γ-polyglutamic acid, isoflavones, vanillic acid and syric acid, which suggested health-promoting effects of these fermented bean products [7]. Cheonggukjang contains compounds such as isoflavones, peptides, aglycones, and dietary fiber and is a food rich in polygamma-glutamic acid. The consumption of cheonggukjang improves type 2 diabetes by lowering insulin sensitivity and enhancing insulin secretion in animal models [8]. Cheonggukjang along with doenjang is one of the important fermented foods consumed in Korea and exhibits strong antimutagenic activities against several carcinogens/mutagens such as aflatoxin B1 [9]. In addition, several reports have shown that increased intake of cheonggukjang has anti-obesity and anti-diabetic effects [10, 11], cardiovascular disease prevention and anti-aging effects [1216].

A previous study showed that treatment with Cheonggukjang fermented by Bacillus subtilis SCGB574 restored intestinal integrity in a pancreatectomized model. Therefore, in the present study, we evaluated Cheonggukjang fermented by B. subtilis SCGB574 as a functional food source in a rat model. The rats exhibited the effects of chronically ingesting high-fat feed, including large intestinal imbalance due to obesity induction, with the results of the study showing improved intestinal health.

Reagents

Ethanol were obtained from Sigma-Aldrich (USA). Nuclease-free water was obtained from Invitrogen (USA). RNAiso Plus reagent was obtained from Takara Korea Biomedical Inc. (Korea). RT kit and oligo dT were obtained from BioFACT Inc., Korea.

Fermentation of soybean and preparation of Cheonggukjang

Soybeans used in the production of Cheonggukjang were purchased from Sunchang, Jeollabuk-do, and fermented using B. subtilis SCGB574 (KCCM11965P). Briefly, Cheonggukjang was immersed in 3.5 kg of soybeans for 24 h, filtered through a sieve to remove moisture, boiled for 30 min at 121℃, and then cooled to 40℃. Enriched B574 in tryptone soya broth (Thermo Fisher Scientific Inc., UK) medium was inoculated into boiled soybeans with 0.5% (v/w) at 30℃ for 24 h. Cheonggukjang was fermented for 36 h at 37℃ and 80% humidity using a constant temperature and humidity chamber at the Microbial Institute for Fermentation Industry (Sunchang, Korea). The fermented Cheonggukjang was dried at 60℃ for 24 h and ground into powder [17, 18].

Animal experiment

SPF 6-week-old male Sprague Dawley (SD) rats were purchased from DBL Co., Ltd. (Korea). The rats were allowed free access to a rodent chow diet (Orientbio, Korea) and tap water. Rats were grown in a conditioned environment at 22 ± 2℃ and 50 ± 5% relative humidity with a 12-h dark/light cycle. The composition and formulation of the 60% high-fat diet (HFD; DooYeol Biotech, Korea) are detailed in Table 1. Cheonggukjang powder comprised approximately 10.1% of the diet, which is an average portion of the previous studies using this cheonggukjang high-fat diet [8, 19]. Rats were randomly divided into the following three groups (n = 8 rats/group): (1) normal diet group (ND), (2) HFD group (HFD), and (3) HFD + B. subtilis SCGB574 group (B574). The rats were acclimatized for at least 1 week before experimentation. Following acclimation, rats were randomized to either remain on a chow diet or change to HFD (Fig. 1). Blood was collected from the vena cava, and the large intestine was removed and stored at -70℃ until used for histopathological analysis. Animal Ethics Committee of Jeju National University (The IACUC of Jeju National University; Approval number 2020-0027) was used as a strict guideline to perform all experimental protocols.

Table 1 . The compositions and formulas of high fat diet.

Class descriptionIngredientsHFDB574


g/Kg%Kcalg/Kg%Kcal
ProteinCasein265.028.41,060.0224.223.7896.9
ProteinL-Cystine4.00.416.04.00.416.0
CarbohydrateMaltodextrin160.017.1640.0142.815.1571.2
CarbohydrateSucrose90.09.6360.080.38.5321.3
FatLard310.033.22,790.0291.430.82,623.0
FatSoybean Oil30.03.2270.028.23.0253.8
FiberCellulose0.00.00.00.00.00.0
MineralMineral Mix48.05.10.048.05.10.0
VitaminVitamin Mix21.02.284.021.02.284.0
VitaminCholine Bitartrate3.00.30.03.00.30.0
Food additiveCalcium Phosphate3.40.40.03.40.40.0
Food additiveB5740.00.00.010010.6453.8

Total934.4100.05,220.0946.4100.05,220.0


Figure 1.Animal experiment. Rats fed a normal chow diet (ND) were changed to a high fat diet (HFD) for 4 weeks for acclimatization. After acclimatization to HFD, rats were fed the HFD or HFD contained in 10.1% Cheonggukjang fermented by Bacillus subtilis SCGB574 (B574) for 6 weeks. On the last day, the large intestine was removed for histopathological analysis and stored in a freezer at -80℃ until required for analysis.

Histopathological examination

The tissues of the large intestine were dissected and fixated in 10% neutral buffered formalin, prepared with paraffin, and stained with hematoxylin and eosin (H&E) (Histoire, Korea). Histopathological observation of each section was observed at 100 × magnification under a microscope at the College of Veterinary Medicine, Jeju National University.

RNA extraction and qPCR

The large intestinal total RNA was extracted using RNAiso Plus reagent (Takara Korea Biomedical Inc., Korea) and a spectrophotometer DS-11 plus (Denovix Inc., USA) was used to measure its concentration. Complementary DNA (cDNA) was synthesized from 1 μg of RNA using the BioFACT™ RT Kit (BioFACT Inc., Korea) with oligo dT primers for reverse transcription. Zonula occludens-1 (ZO-1), Claudin-1, Occludin-1, and β-actin genes were targeted for quantitative realtime polymerase chain reaction (q-PCR) using TB Green™ Premix Ex Taq™ (Takara Korea Biomedical Inc.) to measure quantitative gene expression related to cellular tight junctions. The primer sequences used in this study are listed in Table 2. PCR reactions were performed in triplicate with the Thermal Cycler Dice® Real Time System Lite (Takara Bio Inc., Japan).

Table 2 . Primer sequences for qPCR.

GeneSequencesNCBI Number
ZO-1F CTGCCTCGAACCTCTACTCNM_001106266.1
R TAACTTCGTGGGTACTGGTCAA
Claudin-1F TGCAGCTTCTGGGTTTCANM_031699.3
R AAACGCAGGACATCCACA
Occludin-1F ATCCTGTCTATGCTCGTCANM_031329.3
R GTAACCTCCGAAGCCACC
β-actinF TGGCACCACCATGTACCNM_031144.3
R CCACCAATCCACACAGAGT


Gut microbiota analysis

The cecal DNA was extracted from approximately 200 mg of ceca using a PowerFecal DNA extraction kit (Qiagen, Germany). MiSeq library was constructed using the Two-step PCR according to the manufacturers’ instruction. The V3 and V4 regions of the 16S rRNA gene was amplified using the 341F (5'-TCGTCGGCAGCGTCAGATGTGTATAAGAGACAGCCTACGGGNGGCWGCAG-3) and 806R (5-GTCTCGTGGGCTCGGAGA TGTGTATAAGAGACAGGACTACHVGGGTATCTAATCC-3) primer sets. PCR amplicons were sent to Macrogen Inc. (Korea) to perform Illumina sequencing using MiSeq. MOTHUR software was used as described (https://mothur.org/wiki/miseq_sop/). Sequences were aligned against Silva.nr_v138, and the taxonomic classification was performed using RDP trainset version 18. Opti. clust algorithm was applied to assign operational taxonomic units (OTUs) at a sequence dissimilarity of 97%. PICRUSt2 was used to predict metabolic activities. Alpha diversity (Chao and Shannon) was calculated using the MOTHUR software. Non-metric multidimensional scaling (NMDS) was also performed using the MOTHUR software. Taxonomic compositions were visualized in a heatmap using the pheatmap function in R.

Sample pre-processing and derivatization

Serum and fecal metabolites were extracted by adding 1 ml of protein precipitant (cold methanol, 70% v/v) to 30 μl of serum in 250 μl Eppendorf tubes. The tubes were vortexed and incubated at 37℃ for 30 min, followed by centrifugation at 13,572 g for 5 min at 4℃ to remove the precipitated protein. Quality control (QC) samples were prepared by pooling equal volumes (approximately 10 μl) of each sample prior to derivatization. Ten microliters of ribitol (0.5 mg/l) was added as an internal standard (IS). Finally, the collected supernatant of each sample was concentrated to dryness using an Eppendorf vacuum centrifuge for 3 h at 45℃. After drying, 100 μl of O-methoxyamine hydrochloride in pyridine solution (20mg/ml) was added to each sample. After vortex-mixing each sample for 30 s, all samples were incubated at 30℃ for 90 min in the dark. Silylation was performed by adding 50 μl of N-methyl-N-trimethylsilyl-trifluoroacetamide containing 1% trimethylchlorosilane. Following vortexing each sample for 30 s, the samples were incubated at 37℃ for 30 min. The samples were then centrifuged at 15,928 g for 10 min, and the supernatant was subjected to GC-MS analysis. To measure the performance and stability of the system together with the reproducibility of the sample treatment procedure, QC samples were analyzed every 30 samples throughout the run.

GC-MS analysis and data processing

GC-MS (QP2020, Shimadzu, Japan) was used to analyze the derivatized samples. Metabolites were separated using Rtx-5MS with a fused silica capillary column (30 m × 0.25 mm ID, J&W Scientific, USA). The front inlet temperature was set at 230℃. The column temperature was isothermally maintained at 80℃ for 2 min and then raised by 15℃/min to 330℃ then maintained for 6 min. The transfer line was 250℃ and ion source temperature was 200℃. A 70 eV electron beam was used to achieve ionization. The helium gas flow rate was set to 1 ml/min. A mass range of 85−500 m/z was recorded in 20 scans per second. A Shimadzu GC solution (Shimadzu) was used to obtain chromatograms and mass spectra. GC-MS data were extracted from Shimadzu GC-MS Postrun Analysis to netCDF format file and then processed with MetAlign software to detect peaks and alignments [20]. The resulting CSV-format file was imported into AIoutput software to identify and predict peaks [21]. SIMCA-P 15.0 (Umetrics, Sweden) was used to visualize the results of principal component analysis (PCA) and OPLS-DA of GC-MS data. Permutation test was repeated 200 times to cross-validate. Metabolites with VIP > 1.0, and significance set at p < 0.05, were used to discriminate groups. Metabolites were identified by comparing their mass spectra with the AIoutput software, NIST 14.0 library, and the human metabolome database (HMDB, http://www.hmdb.ca). MSEA of potential metabolites was performed using MetaboAnalyst 5.0, web software (www.metaboanalyst.ca).

Statistical analysis

Statistical significance was evaluated using the Tukey-Kramer test through one-way analysis of variance (ANOVA), with significance set at p < 0.05, p < 0.01, and p < 0.001. Differentially abundant bacteria were identified using the linear discriminant analysis effect size (LEfSe); effect size > 3 and p < 0.05 were considered significant. Analysis of molecular variance (AMOVA) was performed using the MOTHUR software.

Anti-obesity effects of SCGB574 supplement on HFDinduced weights gain and fat deposition in rats

The beneficial effects of soybeans and their modified products have been scientifically shown through studies using various animal models. In previous studies, fermented soybean products attenuated diet-induced body and fat weight in an obese model.

At baseline, no significant differences in body weights were observed. After 10 weeks of HFD intake, the HFD significantly increased body weight. Our results showed that Cheonggukjang supplementation significantly reduced the enhanced body weight gain and decreased fat accumulation compared to the control group (Tables 3 and 4). A recent study reported that Cheonggukjang, 4.5% soybean products fermented by B. subtilis SCGB574, alleviated body weight gain and fat mass in a pancreatectomized model. These results indicate the anti-obesity effects of Cheonggukjang fermented by B. subtilis SCGB574 in HFD-induced obese animals.

Table 3 . Effects of Cheonggukjang on the HFD-induced body weight gain in rat.

GroupInitial Body Weight (g)Final Body Weight (g)Body Weight Change (g)
ND205.3 ± 5.13256.6 ± 10.2751.3 ± 11.26
HFD204.1 ± 4.27429.9 ± 12.45 ###225.8 ± 13.95 ###
B574209.9 ± 9.82381.1 ± 7.51 ***171.3 ± 16.58 ***

1Results were indicated as mean ± standard deviation (N = 8). Compared with ND, ###p < 0.001, compared with HFD, ***p < 0.001. ND, HFD, B574, and BSC represented the normal diet group, the 60% high fat diet group, and the Bacillus subtilis SCGB574 group, respectively.



Table 4 . Effects of Cheonggukjang on the HFD-induced fat weight in rat.

GroupFat Weight (g)
ND5.2 ± 0.42
HFD27.9 ± 1.57 ###
B57420.2 ± 1.55 ***

1Results were indicated as mean ± standard deviation (N = 8). Compared with ND, ###p < 0.001, compared with HFD, ***p < 0.001. ND, HFD, B574, and BSC represented the normal diet group, the 60% high fat diet group, the Bacillus subtilis SCGB574 group, respectively.



Consumption of HFD in rodents leads to weight gain, increases adipose tissue weight, and promotes hyperlipidemia and hyperglycemia [22, 23]. In this study, we showed that the weight gain increase was significantly higher in the HFD group than in the ND group. Interestingly, B574 group showed no difference in feed intake compared with the other groups but showed lower weight increase compared to the HFD group. These results are consistent with previous findings, which were known to prevent weight gain from HFD in animals fed fermented soy food.

Effects of SCGB574 supplement on HFD-induced disruption of the large intestinal epithelial barrier in rats

The intestine not only absorbs essential nutrients, but also protects the host from various ingested toxins and gut microbes [24]. The intestinal barrier system consists of a mucous layer, intestinal epithelial cells, and tight junctions, all of which are susceptible to external factors such as dietary fat intake [25]. When the components of the intestinal barrier system are destroyed, intestinal permeability increases, leading to intestinal diseases such as inflammatory bowel disease, necrotizing enteritis, and celiac disease [26]. Several studies have reported that excessive intake of fat destroys the intestinal epithelial barrier and reduces the tightness of tight junctions. To functionally assess the degree of avidity of the intestinal epithelial barrier associated with obesity, we explored the messenger RNA (mRNA) expression of tight junction markers in the large intestine tissue. The mRNA expression of tight junctional components, including ZO-1, Claudin-1, and Occludin-1, was decreased in the HFD group, while SCGB574 supplementation restored these mRNA expression levels in the treatment groups (Fig. 2).

Figure 2.Inhibitory effect of Cheonggukjang fermented by Bacillus subtilis SCGB574 (B574) on HFD-induced disruption of the large intestine epithelial barrier in rats. The mRNA expression of ZO-1 (A), Claudin-1 (B), and Occludin-1 (C) was determined by qPCR analysis. Results are indicated as means ± SD (N = 8). ## means significant difference between ND and HFD. * and ** mean significant different between HFD and B574. ###p < 0.001, significantly different from the ND. *p < 0.05, significantly different from the HFD. **p < 0.01, significantly different from the HFD.

Mucus is secreted by goblet cells to provide the mucus layer in the normal colon tissue. MUC2 is a gel-forming mucus and a major structural component of the protective mucus layer in the colon tissue [27]. It has been reported that MUC2 expression decreases with the progression of colitis in various animal models [28]. In models of IBD, it often causes loss of the colonic mucus layer and goblet cells. Moreover, it impairs epithelial barrier function by reducing tight junction proteins, including transmembrane barrier protein (occludin) and cytoplasmic scaffolding protein (ZO-1) in the IBD model [29]. These histological changes were improved by ingestion of cheonggukjang.

We also performed histopathological analysis to evaluate HFD-induced destruction of the large intestinal epithelial tissue. We found that HFD intake caused infiltration of inflammatory cells and loss of epithelial cells in the large intestine epithelial tissue. These histopathological changes were improved by supplementation with Chunggukjang (Fig. 3). Our results are consistent with those of previous studies showing that consumption of fermented soybean products improves the integrity of the large intestinal epithelial barrier and infiltration of inflammatory cells. Colonic tissue under normal conditions consists of epithelial layer, mucosal layer, and mucosal matrix. However, inflammatory responses of colonic tissue induce histological changes such as epithelial cell disruption, goblet cell reduction, and inflammatory cell infiltration [30]. Ingestion of DSS depletes goblet cells and increases inflammatory cell infiltration in colon tissues. These histological changes were significantly improved by cheonggukjang treatments. Taken together, we suggest that the consumption of fermented soybean product, cheonggukjang, may confer beneficial effects on large intestinal health.

Figure 3.Inhibitory effect of Cheonggukjang fermented by Bacillus subtilis SCGB574 (B574) on HFD-induced histopathological changes in large intestine. Large intestine tissue was stained by H&E stain and representative H&E-stained large intestine tissues were photographed at 100× magnification under the microscope for histopathological analysis.

Effects of Cheonggukjang on gut microbiota

In this study, we obtained a total of 1,623,405 reads that were rarefied to 10,000 reads per sample for downstream analysis. Among the ND groups, two samples were removed due to sequencing error. Results from Fig. 4 and Table S1 show that the distribution of gut microbiota in all treatment groups were significantly different from each other (p < 0.05). Dietary difference (HFD vs. ND) showed a far greater difference than that of Cheonggukjang (B574 vs. HFD). Although Cheonggukjang significantly shifted the gut microbiota (p < 0.05), it did not affect alpha-diversity (Fig. S1).

Figure 4.Beta-diversity analysis of gut microbiota based on non-metric multidimensional scaling.

Bacterial composition analysis showed that the effects of diet were clear at the family level, while the effects of Cheonggukjang appeared to be clear at the genus level (Fig. S2). Therefore, a differential abundance test was performed to identify the biomarkers at the genus level. The results in Fig. 5 show 35 genera (17 increased and 18 decreased) and nine genera (four decreased and five increased) by HFD and Cheonggukjang, respectively. Abundance of genera decreased by HFD includes probiotics such as Bifidobacterium, Lactobacillus, and other SCFA producers such as Alloprevotella and Oscillibacter. However, HFD increased other SCFA producers, such as Allobaculum and Roseburia. Feeding Cheonggukjang increased SCFA producers, such as Flintibacter and Alistipes, but decreased Lactobacillus. Since Cheonggukjang is a bean-based food fermented by Bacillus spp., we observed a significant increase in Bacillus spp., Bacillus used for Cheonggukjang fermentation may have competed against Lactobacillus over nutrients since both are dietary fiber fermenters.

Figure 5.Differentially abundant genera between ND and HFD groups (A) and B574 and HFD groups (B).

It should be noted that Streptococcus was increased by HFD, but decreased by Cheonggukjang. The roles of Streptococcus vary depending on the species; thus, further studies (i.e., isolation of the genus) are needed to determine their roles in the gut. It has been reported that Bilophila, which was decreased by Cheonggukjang, aggravated high-fat diet-induced metabolic dysfunctions; thus, Cheonggukjang may provide beneficial effects in ameliorating the adverse effects caused by a high-fat diet.

SCGB574treatment changes metabolites of serum and feces

PCA was used to determine the intrinsic similarity of the spectral profiles of the GC-MS (Fig. 6). A clear separation among the groups was observed in the score plot from the serum and feces samples, suggesting that metabolites of the serum and feces were altered by HFD and SCGB574treatments. In particular, the clear discrimination between HFD and B574 groups in fecal samples suggests that SCGB574treatment may affect the growth of gut microflora in a high-fat diet. Among the 111 metabolites that were detected in this study, those that significantly contributed to clustering between ND and HFD groups or HFD and B574 groups were identified according to a threshold of variable importance in projection (VIP) > 1.0 from supervised orthogonal partial least squares discriminant analysis (OPLS-DA) and p < 0.05 (Figs. S3 and S4). To visualize metabolites significantly altered by HFD but recovered by SCGB574treatment, heat map analysis was performed (Fig. 7).

Figure 6.PCA score plot for ND, HFD, and B574 groups derived from GC-MS data of serum (A, R2X = 0.380, Q2 = 0.175) and feces (B, R2X = 0.597, Q2 = 0.534) samples of mice.

Figure 7.Summary plot of meaningful metabolic pathways in serum from the metabolite sets enrichment analysis (MSEA) that are ranked by Holm p value on HFD vs. B574. The metabolites that were significantly different between groups were used for MSEA. Pathways are shown in order of decreasing significance from top to bottom (increasing nominal p values, colored from red to yellow) with bars indicating their estimated fold enrichment.

Metabolic pathway analysis

Metabolite set enrichment analysis (MSEA) was performed to identify the metabolic pathways affected by SCGB574treatment in HFD-induced rats. Table S1 presents each perturbed biochemical pathway with the number of metabolite hits, p-values, holm-adjusted p-values, and false discovery rates. The top five most significant pathways included arginine biosynthesis, alanine, aspartate and glutamate metabolism, starch and sucrose metabolism, neomycin, kanamycin, gentamicin biosynthesis, and galactose metabolism.

From the present study, we conclude that Cheonggukjang fermented by B. subtilis SCGB574 (B574) increases SCFA production and enhances the firmness of tight junctions, as well as the ability to modulate the gut microbiota to ameliorate HFD-induced obesity.

This research was supported, in part, by the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (2016R1A6A1A03012862) and the Traditional Culture Convergence Research Program through the NRF funded by the Ministry of Science and Information and Communications Technology (ICT) (NRF-2016M3C1B5907152), Republic of Korea. We are grateful to Sustainable Agriculture Research Institute (SARI) in Jeju National University for providing the experimental facilities.

Conceptualization, J.H.C. and T.U.; methodology, J.H.C., J.Y.K., T.S., H.S., and T.U.; software, H.S. and T.U.; validation, J.H.C., H.S., and T.U.; formal analysis, J.H.C., H.S., and T.U.; investigation, J.H.C., J.Y.K., H.S., and T.U.; resources, M.R.S., H.Y., and D.J.; data curation, J.H.C., H.S., and T.U.; writing-original draft preparation, J.H.C., H.S., and T.U.; writing-review and editing, J.H.C., H.S., and T.U.; visualization, J.H.C., H.S., and T.U.; supervision, T.U.; project administration, T.U.; funding acquisition, T.U. All authors have read and agreed to the published version of the manuscript.

  1. Kim IS, Kim CH, Yang WS. 2021. Physiologically active molecules and functional properties of soybeans in human health-A current perspective. Int. J. Mol. Sci. 22: 4054.
    Pubmed KoreaMed CrossRef
  2. Ashaolu TJ, Ashaolu JO, Adeyeye SAO. 2021. Fermentation of prebiotics by human colonic microbiota in vitro and short-chain fatty acids production: a critical review. J. Appl. Microbiol. 130: 677-687.
    Pubmed CrossRef
  3. Markowiak-Kopec P, Slizewska K. 2020. The effect of probiotics on the production of short-chain fatty acids by human intestinal microbiome. Nutrients 12: 1107.
    Pubmed KoreaMed CrossRef
  4. Lattimer JM, Haub MD. Effects of dietary fiber and its components on metabolic health. Nutrients 2: 1266-1289.
    Pubmed KoreaMed CrossRef
  5. Muller M, Canfora EE, Blaak EE. 2018. Gastrointestinal transit time, glucose homeostasis and metabolic health: Modulation by dietary fibers. Nutrients 10: 275.
    Pubmed KoreaMed CrossRef
  6. Shahbazi R, Sharifzad F, Bagheri R, Alsadi N, Yasavoli-Sharahi H, Matar C. 2021. Anti-inflammatory and immunomodulatory properties of fermented plant foods. Nutrients 13: 1516.
    Pubmed KoreaMed CrossRef
  7. Cao ZH, Green-Johnson JM, Buckley ND, Lin QY. 2019. Bioactivity of soy-based fermented foods: A review. Biotechnol. Adv. 37: 223-238.
    Pubmed CrossRef
  8. Jeong DY, Daily JW, Lee GH, Ryu MS, Yang HJ, Jeong SY, et al. 2020. Short-term fermented soybeans with Bacillus amyloliquefaciens potentiated insulin secretion capacity and improved gut microbiome diversity and intestinal integrity to alleviate Asian type 2 diabetic symptoms. J. Agric. Food Chem. 68: 13168-13178.
    Pubmed CrossRef
  9. do Prado FG, Pagnoncelli MGB, de Melo Pereira GV, Karp SG, Soccol CR. 2022. Fermented soy products and their potential health benefits: A review. Microorganisms 10: 1606.
    Pubmed KoreaMed CrossRef
  10. Huang C, Pang D, Luo Q, Chen X, Gao Q, Shi L, et al. 2016. Soy isoflavones regulate lipid metabolism through an AKT/mTORC1 pathway in Diet-Induced Obesity (DIO) male rats. Molecules 21: 586.
    Pubmed KoreaMed CrossRef
  11. Squadrito F, Marini H, Bitto A, Altavilla D, Polito F, Adamo EB, et al. 2013. Genistein in the metabolic syndrome: results of a randomized clinical trial. J. Clin. Endocrinol. Metab. 98: 3366-3374.
    Pubmed CrossRef
  12. Nagata C, Wada K, Tamura T, Konishi K, Goto Y, Koda S, et al. 2017. Dietary soy and natto intake and cardiovascular disease mortality in Japanese adults: the Takayama study. Am. J. Clin. Nutr. 105: 426-431.
    Pubmed CrossRef
  13. Kurosawa Y, Nirengi S, Homma T, Esaki K, Ohta M, Clark JF, et al. 2015. A single-dose of oral nattokinase potentiates thrombolysis and anti-coagulation profiles. Sci. Rep. 5: 11601.
    Pubmed KoreaMed CrossRef
  14. Gaman L, Stoian I, Atanasiu V. 2011. Can ageing be slowed? Hormetic and redox perspectives. J. Med. Life 4: 346-351.
  15. Silva S, Michniak-Kohn B, Leonardi GR. 2017. An overview about oxidation in clinical practice of skin aging. An. Bras. Dermatol. 92: 367-374.
    Pubmed KoreaMed CrossRef
  16. Carmona JJ, Michan S. 2016. Biology of healthy aging and longevity. Rev. Invest. Clin. 68: 7-16.
  17. Hong S, Hwang SW, Yang HJ, Jeong DY, Kim O. 2019. Anti-atopic dermatitis effect of the soybean fermented by B. amyloliquefaciens via inhibiting IL-31. J. Biomed. Transl. Res. 20: 30-36.
    CrossRef
  18. Kim SY, Lee KB, Cho YH, Yang HJ, Ryu MS, Yoo YC. 2020. Inhibitory effect of the extract of Cheonggukjang fermented with Bacillus amyloliquefaciens SCGB1 on LPS-Induced inflammation and inflammatory diseases. J. Korean. Soc. Food. Sci. Nutr. 49: 8.
    CrossRef
  19. Monk JM, Wu W, Lepp D, Wellings HR, Hutchinson AL, Liddle DM, et al. 2019. Navy bean supplemented high-fat diet improves intestinal health, epithelial barrier integrity and critical aspects of the obese inflammatory phenotype. J. Nutr. Biochem. 70: 91-104.
    Pubmed CrossRef
  20. Lommen A. 2009. MetAlign: interface-driven, versatile metabolomics tool for hyphenated full-scan mass spectrometry data preprocessing. Anal. Chem. 81: 3079-3086.
    Pubmed CrossRef
  21. Tsugawa H, Bamba T, Shinohara M, Nishiumi S, Yoshida M, Fukusaki E. 2011. Practical non-targeted gas chromatography/mass spectrometry-based metabolomics platform for metabolic phenotype analysis. J. Biosci. Bioeng. 112: 292-298.
    Pubmed CrossRef
  22. Kim JH, Hahm DH, Yang DC, Kim JH, Lee HJ, Shim I. 2005. Effect of crude saponin of Korean red ginseng on high-fat diet-induced obesity in the rat. J. Pharmacol. Sci. 97: 124-131.
    Pubmed CrossRef
  23. Winzell MS, Ahren B. 2004. The high-fat diet-fed mouse: a model for studying mechanisms and treatment of impaired glucose tolerance and type 2 diabetes. Diabetes 53 Suppl 3: S215-219.
    Pubmed CrossRef
  24. de Vos WM, Tilg H, Van Hul M, Cani PD. 2022. Gut microbiome and health: mechanistic insights. Gut 71: 1020-1032.
    Pubmed KoreaMed CrossRef
  25. Untersmayr E, Brandt A, Koidl L, Bergheim I. 2022. The intestinal barrier dysfunction as driving factor of inflammaging. Nutrients 14: 949.
    Pubmed KoreaMed CrossRef
  26. Khoshbin K, Camilleri M. 2020. Effects of dietary components on intestinal permeability in health and disease. Am. J. Physiol. Gastrointest Liver Physiol. 319: G589-G608.
    Pubmed KoreaMed CrossRef
  27. Van Klinken BJ, Van der Wal JW, Einerhand AW, Büller HA, Dekker J. 1999. Sulphation and secretion of the predominant secretory human colonic mucin MUC2 in ulcerative colitis. Gut 44: 387-393.
    Pubmed KoreaMed CrossRef
  28. Grondin JA, Kwon YH, Far PM, Haq S, Khan WI. 2020. Mucins in intestinal mucosal defense and inflammation: learning from clinical and experimental studies. Front. Immunol. 11: 2054.
    Pubmed KoreaMed CrossRef
  29. Forster C. 2008. Tight junctions and the modulation of barrier function in disease. Histochem. Cell Biol. 130: 55-70.
    Pubmed KoreaMed CrossRef
  30. Kanwal S, Joseph TP, Aliya S, Song S, Saleem MZ, Nisar MA, et al. 2020. Attenuation of DSS induced colitis by Dictyophora indusiata polysaccharide (DIP) via modulation of gut microbiota and inflammatory related signaling pathways. J. Funct. Foods 64: 103641.
    CrossRef

Starts of Metrics

Share this article on :

Related articles in MBL

Most Searched Keywords ?

What is Most Searched Keywords?

  • It is most registrated keyword in articles at this journal during for 2 years.