High Levels of Akkermansia muciniphilia Growth Associated With Spring Water Ingestion Prevents Obesity and Hyperglycemia in a High-fat Diet-Induced Mouse Model

Abstract

Background: Type 2 diabetes may be alleviated by mineral water (MW) ingestion. We investigated whether spring water (SW) (a kind of mixed MW) ingestion influences metabolic parameters via alteration of the gut microbiota in high-fat diet (HFD)-fed mice. Method: We divided 32 C57/BL mice into 4 equal groups: normal diet with tap water (Control), high-fat diet with tap water (HFD), normal diet with SW (SW), and high-fat diet with SW (HFD + SW). During this experiment, we checked the body weight (BW) with fasting blood sugar (FBS) every week and all mice were sacrificed in the 17th week to observe serological markers, internal organs, and composition of gut microbiota. Results: The BW of HFD-fed mice was significantly higher than that of mice fed an HFD + SW diet in the early period of the experiment. Fasting blood glucose (FBG) in the HFD group showed a fluctuating pattern compared to the HFD + SW group, and the area under the curve (AUC) value of the oral glucose tolerance test (OGTT) was significantly greater in the HFD group than in the HFD + SW group. Serologic markers were not significantly different between the HFD and HFD + SW groups. Histologically, the most severe fatty changes in the liver were observed in the HFD group. Lastly, the gut levels of Akkermansia muciniphilia were 100-fold higher in the HFD + SW group than in the HFD mice. Conclusion: These findings indicate that SW ingestion, and the associated high levels of A muciniphilia growth in the gut, may improve the early stage of obesity and ameliorate HFD-induced hyperglycemia.

Keywords

type 2 diabetes obesity mice spring water

Introduction

Type 2 diabetes mellitus (T2DM) and obesity affect a significant proportion of the adult population worldwide. These diseases are caused by excessive caloric intake and insulin resistance, eventually leading to dysfunction of several organs such as the kidneys, heart, blood vessels, and eyes.¹

Recently, many researchers have focused on dysbiosis of the intestinal microbiota and endotoxemia in metabolic diseases.^2-4 The microbiota composition of healthy individuals is different from that of obese and diabetic individuals. Several kinds of foods or drugs may alter the gut microbiota with a positive or negative effect.^5,6 In several clinical investigations, either vitamins or minerals have been used for the management of metabolic syndromes.^7,8 This is because micronutrients including macro elements (like calcium and magnesium), and trace elements (like zinc and fluoride [F]) are essential for glycemic control in diabetes.⁹ The control of blood glucose by minerals might be dependent on the concentrations of the minerals and their relative composition.^10-14 There are a few reports that suggest that the underlying mechanism for the observed improvement in metabolic parameters associated with mineral water (MW) consumption has to do with compositional changes in the intestinal microbiota.¹⁵ They demonstrated improvement of hyperglycemia in diabetic patients drinking bicarbonate-rich spring water (SW), leading to high growth of gut bacteria, specifically those in the family Christensenellaceae, of the Firmicutes phylum. SW possesses many kinds of minerals: not just small amounts of diabetes-alleviating minerals, including potassium, calcium, magnesium, zinc, and magnesium, but also other ones unrelated to diabetes.¹⁵ The composition of SW varies according to regional differences and chemical characteristics of the water.¹⁶

Thus, we investigated whether the ingestion of weak alkaline bicarbonate SW, the most common form of SW, in the Republic of Korea, could affect the metabolic parameters and internal organs in a high-fat diet (HFD)-induced mouse model of obesity, specifically via alteration of the gut microbiota.

Materials and Methods

Reagents

The SW utilized in this study, which is the most common type of SW in Korea with respect to mineral composition (described in Table 1), was obtained from Dukgu Oncheon, located in Gyeongsangbuk-do, Republic of Korea. The mice were provided with freshly supplied SW, which was first filtered through a 0.45 µm filter paper and stored at 4 °C.

Table 1.

Comparative Mineral Compositions of Spring Water (SW) and tap Water.

Component	Concentration (mg/L)
Component	SW	Tap water
K	0.6	0.2
Na	41	0.7
Ca	3	0.1
Mg	0.01	0.1
Cl	4.4
SO₄²⁻	5.2
CO₃²⁻	5.8
HCO⁻₃	89.7
SrO	34
F	10.3
Fe	0.02
Mn	-
Li	0.08
Sr	0.03
Zn	0.01
Al	0.016
Pb SiO₂	0.03 32.7

Abbreviations: F, fluoride; Pb, lead.

Animal Studies

All the experimental procedures were approved by the Committee of Animal Ethics of Uijeongbu St. Mary's Hospital (UJA2017-06A). Thirty-two 4-week-old male mice (C57BL/6J) were purchased from The Jackson Laboratory (Seoul, Korea). All the mice were bred freely until the experiment, fed a chow diet, and provided with tap water for 1 week prior to the initiation of the experiment. An HFD containing 45% fat, and a chow diet were both supplied by Research Diets Inc. (NJ, USA) for 17 weeks. The mice were randomly and evenly divided into 4 groups (Control [n = 8], HFD [n = 8], HFD + SW [n = 8], and SW [n = 8] groups), and fed ad libitum with either standard chow or HFD. About 5 mL of either SW or tap water per 20g body weight (BW) was supplied to each group.

Fasting Blood Glucose and Oral Glucose Tolerance Test

After fasting for 8 h, blood samples were collected from the tail vein and the fasting blood glucose (FBG) levels were measured using a Gluco Navii Link 0.3 (SD BIOSENSOR). After oral administration of 2 g/kg of glucose following 8 h of fasting, the oral glucose tolerance test (OGTT) was performed. Briefly, the blood glucose levels were determined in blood samples obtained from the tail vein at 0, 30, 60, 90, and 120 min after glucose administration.

RNA Extraction and PCR Method for Bile Acid-Related Receptor Gene Expression Analysis

To study gene expression of bile acid receptors, total RNA was extracted from the colon using TRIzol reagent (Invitrogen). One µg/µL of the isolated RNA was subjected to reverse transcription using a cDNA synthesis kit (Invitrogen). The mRNA levels of farnesoid X receptor (FXR), vitamin D receptor (VDR), liver X receptor (LXR-α), and glyceraldehyde-3-phosphate dehydrogenase (GAPDH) were quantified using a quantitative real-time polymerase chain reaction (PCR), the iTaqTM Universal SYBR Green Supermix (Bio-Rad Korea), and a CFX96 real-time PCR detection system (Bio-Rad Korea). The primers F (5′-GCCACAGATTTCCTCCTCGT-3′) and R (5′-CAGTCTCTCCCTGGTACCCA-3′) were used to amplify the FXR gene. The primers F (5′-GGTAGAGGGGGCAGGTTAGA-3′) and R (5′-CAGTGTGGCTGCATTCCCTA-3′) were used to amplify the VDR gene. The primers F (5′-AGGAGTGTCGACTTCGCAAA-3′) and R (5′-CTCTTCTTGCCGCTTCAGTTT-3′) were used to amplify the LXR-α gene. The primers F (5′-CCCATGTTTGTGATGGGTGT-3′) and R (5′-GTGATGGCATGGACTGTGGT-3′) were used to amplify the GAPDH gene.

Analysis of gut Microbial Composition

Fecal samples (∼4 mg) were immediately suspended in a solution containing 100 mM Tris HCl (pH 9.0), 40 mM Tris EDTA (pH 8.0), and 4 M guanidine thiocyanate, and kept at −20 °C until DNA extraction. An aliquot of 0.8 mL of the suspension was homogenized with zirconia beads in a 2.0 mL screw cap tube using a Fast Prep 24 Instrument (MP Biomedicals) at 5 m/s for 2 min and placed on ice for 5 min. After centrifugation at 5000 × g for 1 min, DNA was extracted from 200 μL of the suspension using an automatic nucleic acid extractor (Precision System Science). MagDEA DNA 200 (GC) (Precision System Science) was used for automatic nucleic acid extraction, and Illumina MiSeq paired-end sequencing was performed to determine the bacterial composition of the stool samples. We used the forward primer 515F (GTGCCAGCMGCCGCGGTAA) and the reverse primer 806R (GGACTACHVGGGTWTCTAAT) of the hypervariable region V4 of the 16S rRNA gene. Custom scripts were used to remove the primer sequences and align the paired-end reads.

Liver Histology

Liver steatosis was classified into 4 grades according to the percentage of liver cells with steatotic vacuoles: grade 0 <5%, grade 1 <33%, 2≥33%, and 3≥66%.¹⁷

Data Analysis

Data were presented as mean ± standard deviation (SD). For two-group comparisons, statistical analysis was performed using Student's t-test, whereas one-way analysis of variance (ANOVA) was used when more than 2 groups were compared. Fisher's exact test was performed for analyzing categorical variables. All statistical analyses were performed using SPSS 13.0 (SPSS Inc.). A P value of < 0.05 was considered statistically significant.

Results

BW, FBG, and Other Serologic Markers Associated With Metabolic Diseases

There was little difference in the initial BW of the 4 groups. While the BW of the mice in the Control and SW groups increased gradually from 28 to 32 g during the study period, the BW of the mice in the HFD and HFD + SW groups increased rapidly from the 1st week to the 10th week to 40 g, and then reached 45 g by the end of the experiment (Figure 1). The BW of the mice in the HFD group was significantly higher than that of the mice in the HFD + SW group in the early stage of the experiment (P < 0.05): the BW of the mice in the HFD /HFD + SW groups was 34.02 ± 1.12/31.95 ± 1.74 g, 36.87 ± 1.55/34.29 ± 2.01 g, 38.36 ± 1.91/ 35.64 ± 2.52 g, 39.96 ± 1.85 / 37.00 ± 3.08 g, and 42.90 ± 1.18/40.02 ± 3.11 g on the second, third, fourth, fifth, and seventh weeks, respectively. The BW was not significantly different between the HFD and HFD + SW groups on the sixth week, and in the very early (beginning to second week) and late periods (8th week to 17th week) of the experiment (Figure 1). These data suggest that ingestion of SW while consuming a HFD may prevent BW gain in the early period.

Figure 1.

Effects of spring water (SW) ingestion in high-fat diet (HFD)-induced obesity model of mice. Change in body weight (BW) of normal diet and tap water (Control), HFD-induced type 2 diabetes, ingestion of high-fat diet and spring water (HFD + SW), and normal diet and SW for 17 weeks.

The FBG levels, which were also measured every week, showed a fluctuating pattern (100-300 mg/dL) in the HFD group compared to the other 3 groups (100-200 mg/dL) (Figure 2a). The OGTT was performed by checking blood glucose levels every 30 min for 2 h on the last day. The area under the curve (AUC) values were 22775 ± 153, 35220 ± 867, 25785 ± 1322, and 23240 ± 90 in the Control, HFD, HFD + SW, and SW groups, respectively, (P < 0.001). Thus, the AUC value was significantly higher in the HFD group than in the other 3 groups (Figure 2b). It might be presumed that HFD-induced hyperglycemia would decline substantially after ingestion of SW, but it still did not reach the control levels. The plasma levels of insulin, leptin, and monocyte chemoattractant protein 1 (MCP-1) were significantly higher in the HFD and HFD + SW groups than in the Control and SW groups (P < 0.05); however, there was little difference between the HFD and HFD + SW groups. The serum levels of insulin, leptin, and MCP-1 were 1004 ± 711.6, 3515 ± 1843, 2439 ± 1119 and 2438 ± 1438, 7910 ± 5993, 6895 ± 5226.7, and 57.5 ± 8.1, 114.9 ± 46.3, 92.1 ± 30.2 pg/mL in the Control, HFD, and HFD + SW groups, respectively (Table 2). Other blood markers, including interleukin 6 (IL-6), resistin, and tumor necrosis factor-alpha (TNF-α), were not significantly different among the 4 groups (Table 2).

Figure 2.

Result of serological parameters related to diabetes. (A) Level of fasting blood glucose (FBG) during experiment in the control animal model. (B) Oral glucose tolerance test (OGTT) and area under the curve (AUC) at the 17th week: the value of AUC was significantly highest in the AUC of the high-fat diet (HFD) among the 4 groups.

Table 2.

Serological Parameters in Blood of Experimental Mice.

Group		Control	HFD	HFD + SW	SW	P value
LFT	AST	23.5 ± 0.7	111.0 ± 29.3	97.4 ± 33.3	37.0 ± 6.4	<.05*
	ALT	12.5 ± 0.7	99.3 ± 27.6	81.9 ± 45.1	15.8 ± 2.8	<.05*
	ALP	92.0 ± 0.0	96.4 ± 16.1	95.6 ± 27.2	106.3 ± 8.3	ns
	LDH	163.5 ± 171.8	517.1 ± 266.6	438.9 ± 114.2	116.0 ± 57.5	<.05**
Lipid	TC	94.0 ± 4.2	234.1 ± 24.9	207.4 ± 44.9	85.5 ± 13.1	<.05**
	TG	34.0 ± 5.7	43.8 ± 19.4	34.1 ± 6.1	32.0 ± 12.0	ns
	HDL-C	60.0 ± 2.8	81.4 ± 5.5	77.1 ± 7.5	53.5 ± 4.8	<.05***
	LDL-C	4.5 ± 0.7	16.6 ± 2.9	15.0 ± 5.5	2.8 ± 0.5	<.05***
DM markers (pg/mL)	Resistin	5382.2 ± 2911.9	11375.6 ± 9745.3	7635.8 ± 5459.5	4074.9 ± 4751.8	ns
	Insulin	1004 ± 712	3515 ± 1843.	2440 ± 1119	552. ± 223	<.05***
	Leptin	2438 ± 1438	7910 ± 5993	6895 ± 5227	199 ± 109	<.05***
	TNF-α	14.3 ± 6.1	17.5 ± 6.9	12.4 ± 4.4	20.9 ± 0.0	ns
	MCP-1	57.5 ± 18.1	114.9 ± 46.3	92.1 ± 30.2	49.6 ± 33.9	<.05***
Electrolytes	Mg	25.4 ± .3.1	24.8 ± 2.1	23.2 ± 4.1	16.5 ± 3.8	ns
	Fe	182.0 ± 7.1	162.1 ± 35.3	147.0 ± 40.1	116.5 ± 30.4	<.05****
	Na	154.0 ± 1.4	153.1 ± 1.5	153.4 ± 1.8	151.8 ± 1.0	ns
	K	9.2 ± 0.3	8.7 ± 0.6	9.0 ± 0.9	11.2 ± 1.4	ns
	Cl	106.5 ± 0.7	107.6 ± 1.2	107.8 ± 1.0	109.3 ± 2.2	ns
	CA	11.3 ± 0.6	11.5 ± 0.4	11.5 ± 0.2	10.9 ± 0.4	ns

Abbreviations: ALT, alanine aminotransferase; ALP, alkaline phosphatase; AST, aspartate aminotransferase; DM, diabetes mellitus; HFD, high-fat diet; HFD + SW, high-fat diet + spring water; HDL-C, high-density lipoprotein cholesterol; LFT, liver function test; LDL-C, low-density lipoprotein cholesterol; LDH, lactate dehydrogenase; MCP-1, monocyte chemoattractant factor protein-1; ns, nonspecific; SW, spring water; TC, total cholesterol; TG, triglyceride; TNF-α, tumor necrosis factor-α.

*P < 0.05: HFD + SW versus SW, **P < 0.05: HFD versus HFD + SW, ***P < 0.05: C versus HFD, + SW, ****P < 0.05: C versus SW.

Changes in the Weight of the Internal Organs and Liver

Ingestion of HFD + SW might affect the internal organs by altering the accumulation of fat and various minerals. The weight of the liver in the HFD group was the highest among the 4 groups (P < 0.05) (Figure 3a): 1.32 ± 0.14, 2.14 ± 0.24, 1.79 ± 0.44, and 1.20 ± 0.11 g in the Control, HFD, HFD + SW, and SW groups, respectively. The weight of white fat in the SW group was the lowest among the 4 groups (P < 0.05) and there was no significant difference between the HFD and HFD + SW groups: 1.22 ± 0.24, 1.64 ± 0.39, 1.51 ± 0.25, and 0.68 ± 0.28 g in the Control, HFD, HFD + SW, and SW groups. There was also no significant difference in the weight of other organs between the HFD and HFD + SW groups (Figure 3a). The liver function test revealed that all parameters, including aspartate aminotransferase (AST), alanine aminotransferase (ALT), alkaline phosphatase (ALK-P), and lactate dehydrogenase (LDH), were not significantly different between the HFD and HFD + SW groups (Table 2). However, there was a significant difference in AST, ALT, and LDH levels between the HFD (with or without SW) and the non-HFD groups (Table 2). Histologically, the HFD group showed more severe fat infiltration into the liver than the other 3 groups, but there was no significant difference between the HFD and HFD + SW groups: the grade of steatosis of the liver was grades 2 (5/8, 62.5%) and 3 (3/8, 37.5%) in the HFD group, and grades 1 (3/8, 37.5%), 2 (3/8, 37.5%), and 3 (2/8, 25.0%) in the HFD + SW group (Figure 3b, 3c).

Figure 3.

Effect of spring water (SW) ingestion on fatty liver in high-fat diet (HFD)-induced diabetes model mice. (A) Weight of internal organs. (B) Microscopical findings of fatty liver (liver H&E staining) mice. (C) Degree of fatty liver in normal diet and tap water mice (Control), high-fat diet (HFD), high fat diet and spring water (HFD + SW), and normal diet and SW mice (SW).

Blood Lipid Profiles, Inflammatory Markers, and Mineral Toxicity

In the serologic lipid profiles, the levels of total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), and low-density lipoprotein cholesterol (LDL-C) were significantly higher in the HFD groups, irrespective of SW ingestion, than in the non-HFD groups (Control and SW), but were not different between the HFD and HFD + SW groups, or between the Ctrol and SW groups (Table 2). The triglyceride (TG) levels were also not significantly different between the 4 groups (Table 2). All serum electrolytes were not significantly different between the 4 groups, except iron, which was significantly higher in the Control group than in the SW group (Table 2).

Expression of Bile Acid-Related Receptors in the Large Intestine

In the large intestine, the gene expression levels of bile acid-related receptors, including FXR, VDR, LXR-α, and GAPDH were not significantly different between the 4 groups.

Changes in gut Microbiota Associated With the Ingestion of SW in the Mice-Fed HFD

Using next-generation sequencing (NGS) of the gut microbiota, the levels of A muciniphila, a species in the phylum Verrucomicrobia, were 100-fold higher in the HFD + SW group than in the HFD group (Figure 4). According to the gut microbiota analysis, the ratio of Bacteroides to Firmicutes was not different among the 4 groups as follows: Control (49.5/51.5, 0.96), HFD (42.5/60.0, 0.70), HFD + SW (39.0/56.0, 0.69), and SW (45.5/62.5, 0.72).

Figure 4.

Next-generation sequencing (NGS) analysis of gut microbiota at 17th week: normal diet and tap water (Control), high-fat diet (HFD), high-fat diet and spring water (HFD + SW), and normal diet and SW.

Discussion

T2DM is regarded as a disorder closely associated with obesity, hypertension, and hypercholesterolemia. In the present study, we propose that the ingestion of SW, a mixed MW, might prevent HFD-induced hyperglycemia and obesity in the HFD-induced mouse model, by altering the composition of gut microbiota. Although several clinical and animal studies have investigated the improvement of metabolic parameters associated with MW consumption, few studies have examined the effects of MW consumption on gut microbiota.¹⁵ One study found heavy growth of Christensenellaceae (phylum Firmiticus) in the stool of diabetic patients consuming SW,¹⁵ whereas, in our experiment, high levels of A muciniphila were discovered in the stool of HFD-fed mice having ingested SW. In the present study, we used SW, a type of MW obtained from the hot spring of Dukgu, Gyeongsangbuk-do, Republic of Korea. It is the most common type of SW in Korea, with a weakly alkaline character and some silicate.¹⁶ However, it also contains high amounts of minerals, such as lead (Pb), and F, making it inappropriate for a drinking beverage due to its toxicity (Table 1). For usage as a daily beverage, it would be necessary to make it suitable for drinking to reduce toxicity. Although we could not check for Pb and F in the mice having ingested SW, no deaths of experimental mice occurred in this study, and the tested serological mineral levels were little different between the 4 groups, except for the elevation of serum iron observed in the Control group (Table 2). This result requires further investigation in the future.

In this study, the reduction in BW gain was significant in the HFD + SW group during the first 6 weeks (second to seventh weeks) of the experiment in comparison to the HFD group (Figure 1). However, this weight loss effect was not maintained for an extended period; a gradual decrease in the BW gap between the HFD and HFD + SW groups was observed toward the late stage. These data suggest that SW ingestion may prevent obesity in the early stage of a long-term intake of a HFD. Therefore, to maintain the BW loss effect for an extended period, intervention by changing the mineral composition of the original SW by manipulating its composition would be necessary. Hence, SW ingestion may be regarded as a useful supplement in addition to the conventional management of obesity. Hitherto, there have been 3 different opinions regarding the influence of MW on the control of BW, where its consumption has been associated with weight gain,¹⁸ weight loss,¹⁹ and no change in weight.²⁰ These conflicting results may result from the difference in mineral composition of the SW consumed. Further, these studies did not investigate the relationship between the change in weight and gut microbiota alteration.

In the Control, SW, and HFD + SW groups, the FBG levels showed a relatively narrow fluctuating pattern during the experimental period. The levels were maintained at ∼100 to 200 mg/dL, whereas the FBG of the HFD + SW group showed a highly fluctuating value between 100 and 300 mg/dL. The OGTT performed on the last day of this experiment also revealed a higher AUC value in the HFD group than in the other 3 groups (P < 0.001) (Figure 2). These findings are consistent with previous reports, which demonstrated MW-associated weight loss and better homeostatic model assessment of insulin resistance (HOMA-IR) and OGTT.^8,9,14,20 These results suggest the possibility that SW could be utilized as a tool for the stabilization of blood glucose by SW ingestion during the management of diabetes. Furthermore, these outcomes suggest that long-term intake of SW may prevent glucose intolerance or hyperglycemia in an HFD mouse model. The mechanism of lowering blood glucose may be associated with changes in the gut microbiota, and with the function of minerals, acting in a way similar to the way insulin transports glucose to cells.^21,22 Other serological parameters related to diabetes such as insulin, leptin, and MCP-1, were significantly more elevated in the HFD group, regardless of SW ingestion. However, there was no significant difference between the HFD and HFD + SW groups. Furthermore, other serological parameters, including resistin, TNF-α, and IL-6, were not different between the 4 groups, either. These results are in disagreement with previous studies, which showed elevated serologic markers associated with diabetes.^4,18

Among the 4 groups, the weight of the liver was significantly highest in the HFD group (Figure 3a), which was then decreased by SW intake. Microscopically, the proportion of occupied foamy hepatocytes in the liver was higher in the HFD group, although there was no statistical difference (Figure 3b, 3c). The liver function tests showed a similar pattern: the relevant parameters were elevated, as expected in the HFD group with or without SW than in the non-HFD groups. Among the 4 groups, the weight of white fat was the lowest in the SW group (Figure 3a). SW ingestion may reduce the weight of white fat (a marker of obesity), although there was little difference between the HFD and HFD + SW groups. These findings might be related to hyperglycemia and gut microbiota changes. We also observed that the longer the duration of the experiment, the higher the fatty infiltration in the liver (unpublished data). To date, there have been only a few reports on MW ingestion and improvement of carbohydrate, lipid metabolism, and liver function.^13,18,23

As our results demonstrated, cholesterol levels with the exception of TG levels, were significantly lower in the non-HFD group than in the HFD group (Table 2). However, SW ingestion in the HFD group did not significantly decrease serum cholesterol levels. Previously, there have been conflicting positive or negative correlations between MW intake and cholesterol levels.^5,7,8,14,24 Bile acid metabolism is strongly associated with metabolic disorders since bile acid is necessary for the synthesis of cholesterol.²⁵ The SW used in our study had some amount of silicate (32.7 mg/L). Even if there are few reports about the relation of silicate directly with glycemic control, silicate has the characteristic of a bile acid-binding property to decrease serum cholesterol as a primary precursor of bile acid.^10,25-28 Thus, we quantified the amount of bile acid in the stool of mice ingesting SW, but there was no significant difference among the 4 groups (unpublished data). Further studies will be required to elucidate the mechanism for controlling blood glucose between silicate and bile acids and to elucidate the mechanism of SW for metabolic effects. Previous reports, with either vitamins or minerals, used in the management of metabolic syndromes, did not evaluate bile acid and gut microbiota of the stool.⁸ It was known that the gene expression associated with bile acid-related receptors in the intestine is related to bile acid circulation, cholesterol metabolism, and obesity.^25,29 Thus, we examined the gene expression of bile acid-related receptors in the large intestine: FXR, VDR, and LXR-α. However, there was little difference in the expression of all the bile acid-related genes between the 4 groups.

We analyzed the gut microbiota composition to clarify the influence of SW ingestion on the population. Interestingly, we found heavy residence (approximately 100-fold higher) of A muciniphila in the HFD + SW group compared with the HFD group (Figure 4). A muciniphila is a Gram-negative, anaerobic bacterium that colonizes the mucus layer of the human gastrointestinal tract.^30-33 Mucin is a mandatory factor for the growth of A muciniphila, which was recently discovered in various studies to possess anti-obesity and anti-diabetic functions through the tightening of the mucosal barrier, making the barrier impermeable to commensal bacteria. It is presumed that large numbers of resident A muciniphila might increase the factors acting against the metabolic syndrome indicated in this study. There have been few reports in association with MW ingestion, leading to the overgrowth of gut microbiota, specifically of Christensenellaceae species, which is related to lowering hyperglycemia.¹⁵ In this study the SW contained highly confluent minerals like Na, K, Ca, Mg, Cl, SO₄, HCO₃, Fe, Mn, and Zn,¹⁵ while Dukgu Oncheon SW possessed a high amount of F, Zn, and SiO₂ (Table 1). The difference in mineral composition between the 2 SWs might have had an impact on the growth of a different type of microbiome. Purified tap water contains a scanty amount of Na, K, Ca, and some amount of Mg relative to SW, which did not make the serum level more elevated than that in the tap water groups (Table 2). Further studies are necessary to elucidate the mechanism of microbiota change in association with mineral components. Lastly, the proportion of Bacteroides to Firmicutes was not different between the HFD and HFD + SW groups.

In conclusion, our study reports that long-term consumption of SW may have the potential to improve obesity and hyperglycemia as a result of the associated changes in the intestinal microbiome.

Footnotes

Author’s Contribution

E.J.K., T.S.S., H.H.C, H.Y.O., and S.H.P. performed the investigation. J.O.J., J.S.S., and S.S.C. performed analysis of gut microbial composition. Y.C.C provided resources. E.J.K and H.S.C analyzed the data and wrote the first draft of the manuscript. T.S.S and H.S.C reviewed and edited the manuscript. H.K.L. and H.S.C. conceptualized and supervised the study and acquired funding. H.S.C. is the guarantor of this work and, as such, had full access to all the data in the study and takes responsibility for its integrity and the accuracy of the data analysis.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Ethical Approval

This study was approved by the Committee of Animal Ethics of Uijeongbu St. Mary's Hospital (UJA2017-06A).

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

Informed Consent

Not applicable, because this article does not contain any studies with human or animal subjects.

Trial Registration

Not applicable, because this article does not contain any clinical trials.

ORCID iD

Hiun Suk Chae

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