Literature DB >> 28121990

Colonic Absorption of Low-Molecular-Weight Metabolites Influenced by the Intestinal Microbiome: A Pilot Study.

Mitsuharu Matsumoto1,2, Takushi Ooga3, Ryoko Kibe2, Yuji Aiba4, Yasuhiro Koga4, Yoshimi Benno2.   

Abstract

Low-molecular-weight metabolites produced by the intestinal microbiome play a direct role in health and disease. However, little is known about the ability of the colon to absorb these metabolites. It is also unclear whether these metabolites are bioavailable. Here, metabolomics techniques (capillary electrophoresis with time-of-flight mass spectrometry, CE-TOFMS), germ-free (GF) mice, and colonized (Ex-GF) mice were used to identify the colonic luminal metabolites transported to colonic tissue and/or blood. We focused on the differences in each metabolite between GF and Ex-GF mice to determine the identities of metabolites that are transported to the colon and/or blood. CE-TOFMS identified 170, 246, 166, and 193 metabolites in the colonic feces, colonic tissue, portal plasma, and cardiac plasma, respectively. We classified the metabolites according to the following influencing factors: (i) the membrane transport system of the colonocytes, (ii) metabolism during transcellular transport, and (iii) hepatic metabolism based on the similarity in the ratio of each metabolite between GF and Ex-GF mice and found 62 and 22 metabolites that appeared to be absorbed from the colonic lumen to colonocytes and blood, respectively. For example, 11 basic amino acids were transported to the systemic circulation from the colonic lumen. Furthermore, many low-molecular-weight metabolites influenced by the intestinal microbiome are bioavailable. The present study is the first to report the transportation of metabolites from the colonic lumen to colonocytes and somatic blood in vivo, and the present findings are critical for clarifying host-intestinal bacterial interactions.

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Mesh:

Year:  2017        PMID: 28121990      PMCID: PMC5266324          DOI: 10.1371/journal.pone.0169207

Source DB:  PubMed          Journal:  PLoS One        ISSN: 1932-6203            Impact factor:   3.240


Introduction

The intestinal microbiome plays an important role in health and disease [1] because it influences pathological and normal homeostatic functions involved in obesity [2, 3], immune disease [4, 5], colon cancer [6], brain function [7], behavior [8], and life-span [9, 10]. We propose that these interactions depend upon direct stimulation of bacterial cell components and the effects of bacterial metabolites. Bacterial cell components influence the physiological and pathological functions of the immune system through the direct stimulation of Toll-like receptors expressed by colonocytes and dendritic cells that reside in the colonic mucosa [11, 12]. In contrast, the relationships between bacterial metabolites and health/disease are not well known, except for specific metabolites such as short-chain fatty acids (SCFA) [13]. It is also unclear what metabolites are transported to the body from the colonic lumen. Although many blood metabolites have been reported to be different between GF and Ex-GF mice [14], no comprehensive data are available to indicate that blood and colonocytes contain bacterial metabolites derived from the colonic lumen because appropriate analytical methods are not available. There is a general concept that the role of the colon is mainly to absorb water, electrolytes, and some vitamins; thus, in the field of gastrointestinal physiology and nutrition, there have been few reports indicating that low-molecular-weight chemicals are absorbed from the large intestine, and physiologists and nutritionists have typically not considered metabolites produced by intestinal bacteria as research targets. In this study, we tried to identify the bioavailable low-molecular-weight metabolites transported to middle colonic tissue and/or blood from the colonic lumen. It is theoretically possible for transportation of specific substances to be detected using stable or radioactive isotopes [15, 16]; however, it is impossible to comprehensively detect a large number of metabolites using these methods. Using capillary electrophoresis combined with time-of-flight mass spectrometry (CE-TOFMS), which analyzes and differentially displays metabolic profiles [17], we previously demonstrated that 125 low-molecular-weight metabolites that showed significant differences in the colonic feces of germ-free (GF) and ex-germ-free (Ex-GF) mice (i.e., mice that were previously GF-free but now harbored specific pathogen-free mouse intestinal microbiota) were influenced by the intestinal microbiome [18]. Here, we focused on these differences between GF and Ex-GF mice to determine the identities of low-molecular-weight metabolites transported to body from colonic lumen. In brief, the blood Ex-GF/GF ratio of metabolites that are transported to the blood from the colonic lumen is similar to the Ex-GF/GF ratio in colonic feces (Fig 1). We determined the Ex-GF/GF ratio for each metabolite derived from the colonic feces, colonic tissue (colonocytes), portal plasma, and cardiac plasma of GF and Ex-GF mice and searched for metabolites with similar Ex-GF/GF ratios in the colonic feces and colonic tissue, portal plasma, and cardiac plasma.
Fig 1

Estimation of metabolites to transport to body from colonic lumen using the difference of concentration between GF and Ex-GF mice (Ex-GF/GF ratio).

(A) Metabolites with similar Ex-GF/GF ratios in colonic feces, colonic tissue, portal plasma, and cardiac plasma were considered to be transported from the colonic lumen to cardiac blood. (B) Metabolites with different Ex-GF/GF ratios between colonic feces and colonic tissue are controlled by (i) membrane transport system (C) Metabolites with different Ex-GF/GF ratios between colonic tissue and portal plasma are controlled by (ii) metabolism during transcellular transport. (D) Metabolites with different Ex-GF/GF ratios between portal plasma and portal.

Estimation of metabolites to transport to body from colonic lumen using the difference of concentration between GF and Ex-GF mice (Ex-GF/GF ratio).

(A) Metabolites with similar Ex-GF/GF ratios in colonic feces, colonic tissue, portal plasma, and cardiac plasma were considered to be transported from the colonic lumen to cardiac blood. (B) Metabolites with different Ex-GF/GF ratios between colonic feces and colonic tissue are controlled by (i) membrane transport system (C) Metabolites with different Ex-GF/GF ratios between colonic tissue and portal plasma are controlled by (ii) metabolism during transcellular transport. (D) Metabolites with different Ex-GF/GF ratios between portal plasma and portal.

Materials and Methods

Mice and diets

Germ-free (GF) BALB/c mice were purchased from Japan Clea Inc. (Tokyo, Japan) and bred at the Department of Infectious Diseases, Tokai University School of Medicine, Kanagawa, Japan. Six male litters were divided into GF and Ex-GF (see below) groups to remove effects caused by inherited individual distinctions. Mice were housed in Trexler-type flexible film plastic isolators with sterilized tips (CLEA Japan, Inc., Tokyo, Japan) as bedding. The mice were provided with water and commercial CL-2 pellets (CLEA Japan, Inc.) that were sterilized using an autoclave (121°C, 30 min). Bacteriological contamination of feces was analyzed throughout the cultivation procedure using Gifu Anaerobe Medium (GAM) agar (Nissui, Tokyo, Japan). Using a gastric gavage tube, we inoculated the stomachs of Ex-GF mice (4 weeks of age) with 0.5 mL of a 1:10 dilution of feces obtained from specific-pathogen-free BALB/c mice and housed them mice of various for 3 weeks until collecting specimens at 7 weeks of age. This study was carried out in strict accordance with the recommendations in the guidelines of the Animal Care Committee of Tokai University. The protocol was approved by the Kyodo Milk Animal Use Committee (Permit Number: 2009–03).

Specimen preparation

Cardiac and portal blood samples were collected from mice anesthetized with inhalation of isoflurane using small animal anesthetizer MK-A110 (Muromachi Kikai Co. Ltd., Tokyo, Japan) (7 weeks of age) into tubes containing sodium ethylenediamine tetraacetate (final concentration, 0.13%). Portal blood (50–100 μl) and cardiac blood (50–100 μl) were collected using a needle. The blood samples were centrifuged for 20 min at 2,300 × g at 4°C. The samples were stored at −80°C. The mice were sacrificed by cervical dislocation, and the middle colonic tissues and content (colonic feces) were collected. Middle colonic tissues were removed from a region containing feces and were frozen immediately in liquid nitrogen and stored at –80°C. Colonic feces and blood were prepared according to a published procedure [19]. Colons were suspended in methanol (500 μl) with 50 μM internal standard and vortexed vigorously five times for 60 s using a MicroSmash MS-100R (Tomy Digital Biology Co., Ltd., Tokyo, Japan) at 4,000 rpm at 4°C. The resulting colon sample served as the crude metabolome.

Capillary electrophoresis–time-of-flight mass spectrometry (CE-TOFMS)

Metabolomic measurements were performed using an Agilent Capillary Electrophoresis System, and data were processed by Huma Metabolome Technologies Inc. (Tsuruoka, Japan) according to a published method [20]. All pretreated metablome samples were centrifugally filtered through a 5-kDa cutoff filter Ultrafree-MC (Millipore). The values of the peaks were normalized to those of the internal standards methionine sulfone (cationic) and D-camphor-10-sulfonic acid (anionic), respectively.

Ratio of values in GF mice to those in Ex-GF mice (Ex-GF/GF ratio)

In this study, we calculated the ratio of values in GF mice to those in Ex-GF mice (Ex-GF/GF ratio) and classified the metabolites. We defined the threshold Ex-GF/GF ratio to determine whether metabolites were present at higher or lower concentrations in Ex-GF mice than in GF mice. The metabolites were measured in the metabolome of the cardiac plasma, which was influenced by all gateways: (i) the membrane transport system of colonocytes, (ii) metabolism during transcellular transport, and (iii) hepatic metabolism (Fig 1). The highest Ex-GF/GF ratio for metabolites present at higher concentrations in Ex-GF than in GF mice (where the difference was still significantly different) was 1.259 (S1 Table). The lowest Ex-GF/GF ratio for metabolites present at lower concentrations in Ex-GF than in GF mice was 0.866 (S1 Table). Therefore, in this study, the Ex-GF/GF ratio of metabolites present at higher concentrations in Ex-GF mice than in GF mice was defined as ≥1.25, and the Ex-GF/GF ratio of metabolites present at lower concentrations in Ex-GF mice than in GF mice was defined as < 0.8.

Statistical analysis

IBM SPSS Statistics (Japan IBM, Tokyo) software was used to conduct statistical analyses. Metabolome data were analyzed using PCA and clustering analysis. Differences in relative quantities between GF and Ex-GF mice were evaluated for each metabolite using Welch’s t test. The levels of individual metabolites in GF and Ex-GF mice were compared using Fisher’s exact test.

Results

Analysis of the metabolomes of the colonic feces, colon, portal plasma, and cardiac plasma of GF and Ex-GF mice

CE-TOFMS identified 170, 246, 166, and 193 metabolites from the colonic feces, colonic tissue, portal plasma, and cardiac plasma, respectively. Significant differences (p < 0.05) were observed between GF and Ex-GF mice in each specimen; the number of metabolites with differences in the Ex-GF/GF ratio was as follows: colonic feces, 111 (65.7%); colonic tissue, 56 (22.8%); portal plasma, 33 (19.9%); and cardiac plasma, 39 (20.2%) (Fig 2A). Principal component analysis (PCA) showed patterns for metabolites in all samples (Fig 2B). The metabolomic profiles of colonic feces showed the greatest difference between the two groups of mice. However, the metabolome difference for colonic tissue, portal and cardiac plasma was not significant. Based on the PCA results of each specimen, it was possibles to assign all metabolomic profiles into two clusters corresponding to GF mice and Ex-GF mice (Fig 2C).
Fig 2

Differences in the metabolomes of GF and Ex-GF mice.

(A) Number of metabolites that were significantly (p < 0.05) or not significantly different between GF and Ex-GF mice.(B) PCA of metabolome profiles. Fec-Ex, colonic feces of Ex-GF mice; Fec-GF, colonic feces of GF mice; Col-Ex, colon of Ex-GF mice; Col-GF, colon of GF mice; PP-Ex, portal plasma of Ex-GF mice; PP-GF, portal plasma of GF mice; CP-Ex, cardiac plasma of Ex-GF mice; CP-GF, cardiac plasma of GF mice.(C) PCA of metabolome profiles in each specimen.

Differences in the metabolomes of GF and Ex-GF mice.

(A) Number of metabolites that were significantly (p < 0.05) or not significantly different between GF and Ex-GF mice.(B) PCA of metabolome profiles. Fec-Ex, colonic feces of Ex-GF mice; Fec-GF, colonic feces of GF mice; Col-Ex, colon of Ex-GF mice; Col-GF, colon of GF mice; PP-Ex, portal plasma of Ex-GF mice; PP-GF, portal plasma of GF mice; CP-Ex, cardiac plasma of Ex-GF mice; CP-GF, cardiac plasma of GF mice.(C) PCA of metabolome profiles in each specimen.

Classification of metabolites according to the Ex-GF/GF ratio

In the present study, 146 colonic fecal metabolites detected in all mice were selected for analysis (122 metabolites that were detected in colonic feces and colonic tissue are shown in Table 1, and 24 metabolites that were detected in colonic feces but not in colonic tissue are shown in Table 2). The table shows that the levels of most of the selected metabolites were influenced by the intestinal microbiome in the colonic lumen because they showed significant differences between GF and Ex-GF mice. Transport of low-molecular-weight metabolites to the cardiac blood from the colonic lumen appeared to be influenced by 3 gateways: (i) the membrane transport system of colonocytes, (ii) metabolism during transcellular transport, and (iii) hepatic metabolism (Fig 1). Therefore, we estimated the effect of these gateways for each metabolite using the Ex-GF/GF ratio (Table 1). In total, 62 metabolites (No. 1 to No. 62) had Ex-GF/GF ratios that were similar between the colonic feces and colonic tissue, indicating that their levels are not influenced by the membrane transport system of colonocytes. Twenty-two metabolites (No. 1 to No. 22) had similar Ex-GF/GF ratios for colonic feces, colonic tissue, portal plasma, and cardiac plasma, and were thus probably transported from the colonic lumen to the systemic blood supply independently of factors (i), (ii), and (iii) defined above. The other 40 metabolites (No. 23 to No. 62), which had Ex-GF/GF ratios that were similar between the colonic feces and colonic tissue but not portal blood, were transported to colonic tissue, although their levels were controlled by (ii) metabolism during transcellular transport and/or (iii) hepatic metabolism. In contrast, 60 metabolites (No. 63 to No. 122) with different Ex-GF/GF ratios between the colonic feces and colonic tissue were also detected (Table 1). Because these metabolites are influenced by (i) the membrane transport system of colonocytes, their concentrations in the colonic tissue were independent of their concentrations in the colonic lumen. Twenty-four metabolites were not detected in the colonic tissue (Table 2). Therefore, these metabolites are not transported to the body from the colonic lumen. Eight of 11 peptides detected were in this group.
Table 1

The ExGF/GF ratio and the influence of 3 gateways on each metabolite detected in the colonic feces, colon, portal plasma, and cardiac plasma.

 MetbolitesCategory ExGF/GF ratioMembrane transport system of colonocytesExGF/GF ratioMetabolism during transcellular transportExGF/GF ratioHepatic metabolismExGF/GF ratio 
 KEGG IDColonic fecesColonPortal plasmaCardiac plasma 
 (HMDB ID) 
1CytosineBase/nucleotideC00380 1.43 unclearNA 
2Cholic acid C00695   1.71 
3Pipecolic acid C00408 2.451.611.66 
4Stachydrine C101721.140.940.840.90 
5Phe*Amino acidC000790.760.640.760.83 
6ValAmino acidC001830.660.660.610.64 
7LysAmino acidC000470.660.410.700.74 
8IleAmino acidC004070.640.560.570.60 
95-Hydroxylysine C167410.600.500.590.72 
10LeuAmino acidC001230.580.600.630.65Ex-GF/GF
11N8-Acetylspermidine* C010290.510.370.67→/→0.823
12SerAmino acidC000650.500.360.560.592.5
13N-Acetylhistidine C029970.440.780.870.692
14GlyAmino acidC000370.440.750.560.551.5
15HisAmino acidC001350.390.430.760.871
16ThrAmino acidC001880.180.300.500.540.67
17ArgAmino acidC000620.150.280.37→/→0.890.5
18ProAmino acidC001480.140.380.570.630.4
19HydroxyprolineAmino acidC010150.050.220.470.540
20Creatinine C007910.010.340.660.77 
21N-Acetyl-β-alanineAlkylamino acidC01073 0.400.73→/→1.52 
221-MethylnicotinamideAlkylamino acidC02918 0.510.500.45 
23Glutaric acid C00489  unclearNAXND 
24Valeric acidFatty acidC00803 39.53→/→1.22XND 
252-Aminobutyric acidAmino acidC02261 1.89→/→0.730.78 
26SarcosineCholineC00213 2.43unclearNAunclear0.42 
271-Methyl-4-imidazoleacetic acidAlkylamino acidC0582819.207.02→/→1.271.19 
28Lactic acidEnergyC001861.040.93→/→1.291.19 
29ThiamineCo-enzyme/its derivativesC003780.981.18→/→1.731.75 
305-Oxoproline C018790.880.75→/→1.432.11 
31TrpAmino acidC000780.830.89→/→0.75→/→0.88 
32GluAmino acidC000250.780.89→/→1.941.29 
33Carnitine C003180.260.69→/→0.991.02 
34Glucosamine C003290.050.09unclearNAunclearNA 
35Gluconic acid C002570.010.20→/→1.52→/→1.10 
364-Guanidinobutyric acid C01035 0.19→/→0.860.86 
37Urea C00086 0.71→/→0.960.99 
38Ophthalmic acidPeptide(05765) 0.21unclearNAunclear0.47 
39AspAmino acidC000491.241.10→/→2.041.35 
402'-Deoxycytidine C008810.180.56→/→1.231.16 
415-Methoxyindoleacetic acidAlkylamino acidC05660 0.67→/→1.31XND 
42S-AdenosylmethionineCo-enzyme/its derivativesC00019 0.74unclearNAunclear1.18 
43Nicotinic acidCo-enzyme/its derivativesC0025333.97 XNDunclearND 
445-Aminovaleric acidAmino acidC00431 32.55XNDunclearND 
452,6-Diaminopimelic acidAmino acidC00666  XNDunclearND 
46p-Hydroxyphenylacetic acid C00642  XNDunclearND 
471H-Imidazole-4-propionic acid -  XNDunclearND 
48Piperidine C01746  XNDunclearND 
49Adenine C00147 1.72XNDunclearND 
50Prostaglandin E2NeurotransmitterC00584 1.66XNDunclearND 
51N-Acetylglutamic acidAlkylamino acidC00624 1.62XNDunclear0.99 
524-Pyridoxic acid C008474.46 XNDunclearND 
53N-AcetylornithineAlkylamino acidC004372.171.62XNDunclearND 
54N-Acetylputrescine C027141.511.28XNDunclearND 
55Methionine sulfoxide C029891.011.18XNDunclear0.49 
56Thr-AspPeptide-0.760.48XNDunclearND 
57Ser-GluPeptide-0.730.47XNDunclearND 
58SDMA (03334)0.570.59XNDunclear1.07 
59N6,N6,N6-TrimethyllysineAlkylamino acidC037930.240.11XNDunclearND 
60Guanosine C003870.120.69XNDunclearNA 
61N-AcetylmethionineAlkylamino acidC02712 0.57XNDunclearND 
62Gly-AspPeptide- 0.47XNDunclearND 
63β-AlaAmino acidC00099 →/→1.111.181.24 
64Pantothenic acidCo-enzyme/its derivativesC00864 →/→0.851.07→/→1.45 
65TaurineAmino acidC0024516.86→/→1.191.081.09 
66CitrullineAmino acidC003279.98→/→0.680.680.73 
67OrnithineAmino acidC000777.38→/→0.941.18→/→0.69 
683-MethylhistidineAlkylamino acidC011522.52→/→1.040.900.94 
69Pyridoxal C002501.82→/→1.050.920.97 
70N6-AcetyllysineAlkylamino acidC027271.39→/→0.460.510.68 
71MetAmino acidC000731.02→/→0.410.520.57 
72Isethionic acid C051231.00→/→0.690.650.45 
73TyrAmino acidC000820.98→/→0.660.700.75 
74AlaAmino acidC000410.90→/→0.790.660.57 
75Gly-LeuPeptideC021550.86→/→0.250.660.47 
76CholineCholineC001140.26→/→1.240.94→/→1.46 
77Taurocholic acid C051220.26→/→1.011.19→/→0.18 
78BetaineCholineC007190.49→/→0.990.820.84 
79Trimethylamine N-oxide C01104 →/→2.542.232.99 
80O-Acetylcarnitine C025710.14→/→0.881.201.19 
811-Methyladenosine C02494 →/→0.820.891.06 
82NicotinamideCo-enzyme/its derivativesC00153 →/→0.890.98→/→0.62 
83N-Acetylaspartic acidNeurotransmitterC01042 →/→1.21unclearNAXND 
84N,N-DimethylglycineCholineC01026 →/→0.93→/→0.650.70 
85Succinic acidEnergyC00042 →/→1.00→/→2.18→/→0.88 
863-Phenylpropionic acid C05629 →/→0.67→/→1.13XND 
87Cytidine C00475 →/→0.72→/→1.651.32 
88Ribulose 5-phosphateEnergyC00199 →/→0.81→/→1.29→/→1.17 
89HomoserineAmino acidC00263 →/→0.91unclearNAunclear0.82 
90Putrescine C0013417.15→/→1.06unclearNAunclear1.02 
91γ-Butyrobetaine C011818.97→/→1.08→/→0.530.57 
92Glyceric acid C002587.33→/→0.49→/→1.10XND 
93Hypoxanthine C002625.01→/→0.94→/→   
94GABANeurotransmitterC003343.66→/→1.11→/→1.264.20 
95Urocanic acid C007853.52→/→1.02→/→1.30→/→0.57 
96Spermidine C003152.85→/→0.96unclearNAunclear0.57 
97Glycerol 3-phosphate C000930.53→/→1.08→/→1.92→/→0.98 
98Uric acid C003660.44→/→1.00→/→1.54→/→0.80 
99GlnAmino acidC000640.27→/→1.01→/→2.091.80 
100Creatine C003000.22→/→1.07→/→1.42→/→1.14 
101Inosine C002940.16→/→0.82→/→   
102Uridine C00299 →/→1.03unclearNAunclear1.55 
103CystinePeptideC00491 →/→NA→/→0.470.59 
104N-MethylprolineAlkylamino acid- →/→NAXNDunclearND 
105Guanine C00242 →/→0.85XNDunclearND 
106Arg-GluPeptide- →/→0.48XNDunclearND 
107β-Ala-LysPeptideC05341 →/→0.37XNDunclearND 
108TyramineCo-enzyme/its derivativesC00483 →/→1.19XNDunclearNA 
109Uracil C00106 →/→1.04XNDunclearNA 
110CMP C00055 →/→1.09XNDunclear1.07 
111Propionic acidFatty acidC00163 →/→NAXNDunclear1.03 
112Adenosine C00212 →/→0.53XNDunclearNA 
113N-AcetylglucosamineAlkylamino acidC001407.41→/→1.01XNDunclear1.14 
114N-Acetylneuraminic acidAlkylamino acidC002702.95→/→1.25XNDunclear0.57 
1153-Aminoisobutyric acidAmino acidC051452.26→/→0.81XNDunclear  
116Glu-GluPeptideC014250.83→/→NAXNDunclearND 
117His-GluPeptide-0.55→/→NAXNDunclearND 
118Betaine aldehyde_+H2OCholineC005760.41→/→1.74XNDunclearND 
119Spermine C007500.28→/→0.95XNDunclearND 
120S-LactoylglutathionePeptideC03451 →/→3.11XNDunclearND 
121Thymidine C00214 →/→1.04XNDunclearNA 
122Glucuronic acid C00191 →/→NAXNDunclear0.70 

→: metabolites are transported without selection by the gateway. →/→: metabolites are influenced by selection by the gateway. X: metabolites are blocked by the gateway. Metabolites detected in only Ex-GF or GF mice are indicated in red or green without the number, respectively.

*Although the Ex-GF/GF ratio was >0.8 in cardiac plasma, the ratio was judged as similar, because there was no significant difference between portal and cardiac plasma.

Table 2

Metabolites detected in colonic feces but not in colonic tissue.

Metbolites  ExGF/GF ratio 
CategoryKEGG IDColonic fecesColonPortal plasmaCardiac plasma 
   
4-Methylbenzoic acid -20.00NDNDND 
Hydroxyindole C0376620.00NDNDNDEx-GF/GF
3'-CMP; Cytidine 2'-monophosphateBase/nucleotideC0310420.00NDNDND3
Pyridoxamine C1371020.00NDNDND2.5
1,3-Diaminopropane -20.00NDNDND2
Cadaverine C0167220.00NDNDND1.5
3-Methylbenzoic acid C0145420.00NDNDND1
3-(4-Hydroxyphenyl)propionic acid C0145620.00NDNDND0.67
Saccharopine C004491.70NDNDND0.5
Indole-3-acetamide -1.25NDNDND0.4
Oxypurinol C075991.21NDNDND0
Allantoin -0.12NDNDND 
Galactosamine C166750.09NDNDND 
3-Nitrotyrosine -0.00NDNDND 
O-Succinylhomoserine C037760.00NDNDND 
γ-Glu-2-aminobutanoic acid  0.00NDNDND 
3-Hydroxy-3-methylglutaric acid C037610.00NDNDND 
Glucaric acid C007670.00NDNDND 
Quinic acid C002960.00NDNDND 
2'-DeoxyguanosineBase/nucleotideC085070.41NDNDND 
2-Oxoglutaric acid C0002620.00ND1.03ND 
4-Methyl-2-oxovaleric acid/ 3-Methyl-2-oxovaleric acidAlkylamino acidC0023320.00ND0.70ND 
XanthineBase/nucleotideC003851.42NDND1.18 
Butyric acidFatty acidC0024620.00ND1.26ND 

Metabolites detected in only Ex-GF or GF mice are indicated red or green without number, respectively.

→: metabolites are transported without selection by the gateway. →/→: metabolites are influenced by selection by the gateway. X: metabolites are blocked by the gateway. Metabolites detected in only Ex-GF or GF mice are indicated in red or green without the number, respectively. *Although the Ex-GF/GF ratio was >0.8 in cardiac plasma, the ratio was judged as similar, because there was no significant difference between portal and cardiac plasma. Metabolites detected in only Ex-GF or GF mice are indicated red or green without number, respectively.

Discussion

This is the first study to clarify the effect of both the absorption system and intestinal microbiome on the bioavailability of colonic luminal low-molecular-weight metabolites. First, we explain why we believe this method was able to accurately detect the transport of metabolites from colonic lumen. If the colon does not contribute to the absorption of colonic luminal metabolites, as required by the notion that the colon absorbs only water, minerals, and some vitamins, the difference in the metabolite concentration in colonic tissue, portal plasma, and cardiac plasma between GF mice and Ex-GF mice would not be apparent. However, in the present study, we detected differences in the concentration of each metabolite between GF and Ex-GF mice in all specimens, and these Ex-GF/GF ratios were similar among the colonic feces, colonic tissue, portal plasma, and cardiac plasma. Thus, it is evident that this method is able to accurately detect low-molecular-weight metabolites transported to the body from the colonic lumen. In fact, the similarity of the Ex-GF/GF ratio of Arg, which is known to be absorbed by colonic epithelial cells [21], between colonic feces and colonic tissue supports this method. The Ex-GF/GF ratio of 62 metabolites (No. 1 to No. 62) was similar between the colonic feces and colonic tissue, indicating that many metabolites are bioavailable and revising the general concept that the role of the colon is mainly to absorb water [22], electrolytes [22], and some vitamins [23]. In fact, some metabolites belonging to this group have been known as substances specifically absorbed from the colon, for example, amino acids [21, 24]. Furthermore, 56 metabolites (all of the metabolites except for stachydrine, lactic acid, thiamine, 5-oxoproline, Trp, and methionine sulfoxide) showed differences between GF and Ex-GF in colonic feces, indicating that many low-molecular-weight metabolites influenced by the intestinal microbiome are bioavailable. From the classification of metabolites based on the Ex-GF/GF ratio of each specimen, we estimated the influence of these metabolites in health and disease. Twenty-two metabolites (No. 1 to No. 22) (Table 1), including 11 basic amino acids, that had similar Ex-GF/GF ratios for all specimens were transported to the systemic circulation from the colonic lumen. Therefore, these metabolites are probably directly involved in health and disease. Forty metabolites (No. 23 to No. 62) with similar Ex-GF/GF ratios between the colonic feces and colonic tissue but not portal blood are proposed to be key factors that influence colonic barrier function and the intestinal mucosal immune system. In contrast, 60 metabolites (No. 63 to No. 122) with different Ex-GF/GF ratios between the colonic feces and colonic tissue are stringently regulated by cellular homeostasis. For example, significant differences were observed in the Ex-GF/GF ratio of GABA (No. 94) between colonic feces and colonic tissue, and between portal plasma and cardiac plasma. Therefore, GABA must be regulated by the membrane transport system of colonocytes and by the hepatic metabolism because it functions as a neurotransmitter. Significant differences were also observed in the Ex-GF/GF ratios of Glu (No. 32), Asp (No. 39), and Tyr (No. 73), which function as neurotransmitters or precursors of neurotransmitters, in colonic feces and other specimens, although many basic amino acids are transported from the colonic lumen to the systemic blood with the same Ex-GF/GF ratio. Twenty-four metabolites that were not detected in the colonic tissue (Table 2) are not transported to the body from the colonic lumen. Eight of 11 peptides detected were in this group, indicating that nearly all peptides are not absorbed by colonocytes, although previous studies suggested that peptides are absorbed through peptide transporter 1 (PEPT1) [25, 26]. However, it was reported that PEPT1 is present in the distal part of the colon but not in the proximal colon [26]. Unfortunately, since the middle colon was analyzed in this study, the presence of PEPT1 is unclear. Surprisingly, butyrate, which is involved in the metabolism and normal development of colonic epithelial cells [27, 28], also belongs to this group, indicating that butyrate absorbed from the lumen is immediately metabolized in colonocytes because in vivo studies demonstrated that butyrate in the colonic lumen is absorbed and is metabolized to CO2, 3-hydroxybutyrate, and lactate [29, 30]. Colonic gene expression of butyrate transporter SLC5A8 is markedly lower in GF mice than in conventional mice [31], indicating that the stimulation of intestinal bacteria is an important factor in the expression of transporter. On the other hand, Jakobsdottir et al. [32] reported that the concentrations of acetate, propionate, and butyrate in the cecal content correlated significantly with those in portal serum after the oral administration of dietary fiber. Based on these reports, parts of the colon (distal, middle, and proximal) and effects of bacterial stimulation are also important factors to understand the colonic transport system of low-molecular-weight metabolites. Further study is required to clarify the bioavailability of peptides and SCFA in colonic tissue considering these points and using analytical instruments such as liquid chromatography for SCFA. Regarding polyamines, Ex-GF/GF ratios of fecal putrescine, spermidine, and spermine were 17.15, 2.85, and 0.28, respectively (Table 1), demonstrating that the colonic luminal putrescine and spermidine are produced by the colonic microbiome. In contrast, colonic luminal spermine is probably derived from live or exfoliated epithelial cells and is absorbed by the colonic microbiome. On the other hand, since polyamines have to be strictly controlled because of physiological function and toxicity in the body, Ex-GF/GF ratios of all polyamines in colon tissue were around 1 (putrescine: 1.06, spermidine: 0.96, and spermine: 0.95). To the best of our knowledge, little is known about the colonic transporter that absorbs metabolites. Although it is known that lipophiles are delivered by passive diffusion across the enterocyte membrane [33],water-soluble substances detected using CE-TOFMS are probably absorbed through transporters using energy produced by Na+/K+ATPase. For example, amino acids are absorbed through the Na+ pump transporter [34]. Here, we show that 14 basic amino acids were absorbed into colonocytes (colonic tissue) with an Ex-GF/GF ratio similar to that of colonic feces, indicating that the transporters mediate the uptake of amino acids by colonocytes. The present study indicates that known/unknown transporters are used to absorb water-soluble metabolites. We confirmed the validity of this study using snapshots of the metabolome corresponding to the known relationship among the intestinal microbiome, intestinal bacterial metabolites, and health/disease using bacterial metabolism of trimethylamine N-oxide (TMAO) from choline, which is associated with cardiovascular disease risk [35]. Here, we showed that the colonic fecal concentrations of choline (No. 76) and carnitine (No. 33) in Ex-GF mice were lower than those in GF mice because they are metabolized by the intestinal microbiota (Fig 3). Furthermore, the TMAO (No. 79) concentrations in the cardiac plasma were higher in Ex-GF mice because TMAO was produced through liver metabolism of trimethylamine (TMA) produced by the intestinal microbiota in Ex-GF mice (the TMA concentration was below the limit of detection). Therefore, we consider that the metabolome data obtained from the present study are useful for understanding the mechanism of diseases caused by intestinal microbiome.
Fig 3

Metabolomic snapshots of the known phenomenon of intestinal microbiome-dependent production of pro-atherogenic trimethylamine N-oxide by degradation of carnitine/choline in the intestinal tract.

FMO: flavin-containing monooxygenase.

Metabolomic snapshots of the known phenomenon of intestinal microbiome-dependent production of pro-atherogenic trimethylamine N-oxide by degradation of carnitine/choline in the intestinal tract.

FMO: flavin-containing monooxygenase. In the present study, we succeeded in the estimation of low-molecular-weight metabolites transported to the rest of the body from the colonic lumen by focusing on differences in the Ex-GF/GF ratio between GF and Ex-GF mice and have thus revised the general concept of the role of the colon. We also found that many low-molecular-weight metabolites influenced by the intestinal microbiome appeared to be absorbed from the colonic lumen. In the field of gastrointestinal physiology, it is very important to note that many low-molecular-weight chemicals influenced by intestinal microbiome in the large intestine appeared to be absorbed from the colonic lumen. Although this study does not provide direct evidence that low-molecular-weight metabolites influenced by intestinal microbiome are absorbed into the body from the large intestine, it contributes to the field of nutrition by providing a list of low-molecular-weight metabolites that are transported to the body from the colonic lumen. In other fields such as medicine, immunology, physiology, pharmacology, bacteriology, and nutrition, these findings may also contribute new insight into the function of the colon and its interactions with the intestinal microbiome and provide candidate chemicals whose roles in the body can be elucidated in future studies. In addition, further studies are required to investigate the colonic absorption of low-molecular-metabolites in mice of various strains and ages and in female mice.

All metabolites and their Ex-GF/GF ratio detected from cardiac plasma.

(DOCX) Click here for additional data file.
  34 in total

1.  Physico-chemical state of lipids in intestinal content during their digestion and absorption.

Authors:  A F HOFMANN; B BORGSTROM
Journal:  Fed Proc       Date:  1962 Jan-Feb

Review 2.  Molecular analysis of the intestinal microflora in IBD.

Authors:  G W Tannock
Journal:  Mucosal Immunol       Date:  2008-11       Impact factor: 7.313

Review 3.  Short-chain fatty acids in the human colon: relation to gastrointestinal health and disease.

Authors:  P B Mortensen; M R Clausen
Journal:  Scand J Gastroenterol Suppl       Date:  1996

4.  L-arginine uptake by cationic amino acid transporter 2 is essential for colonic epithelial cell restitution.

Authors:  Kshipra Singh; Lori A Coburn; Daniel P Barry; Jean-Luc Boucher; Rupesh Chaturvedi; Keith T Wilson
Journal:  Am J Physiol Gastrointest Liver Physiol       Date:  2012-02-23       Impact factor: 4.052

5.  An obesity-associated gut microbiome with increased capacity for energy harvest.

Authors:  Peter J Turnbaugh; Ruth E Ley; Michael A Mahowald; Vincent Magrini; Elaine R Mardis; Jeffrey I Gordon
Journal:  Nature       Date:  2006-12-21       Impact factor: 49.962

6.  In vivo absorption of medium-chain fatty acids by the rat colon exceeds that of short-chain fatty acids.

Authors:  J R Jørgensen; M D Fitch; P B Mortensen; S E Fleming
Journal:  Gastroenterology       Date:  2001-04       Impact factor: 22.682

7.  Metabolism of short-chain fatty acids by rat colonic mucosa in vivo.

Authors:  M D Fitch; S E Fleming
Journal:  Am J Physiol       Date:  1999-07

Review 8.  Intestinal absorption of water-soluble vitamins: an update.

Authors:  Hamid M Said; Zainab M Mohammed
Journal:  Curr Opin Gastroenterol       Date:  2006-03       Impact factor: 3.287

9.  Obesity alters gut microbial ecology.

Authors:  Ruth E Ley; Fredrik Bäckhed; Peter Turnbaugh; Catherine A Lozupone; Robin D Knight; Jeffrey I Gordon
Journal:  Proc Natl Acad Sci U S A       Date:  2005-07-20       Impact factor: 11.205

Review 10.  Gut microbiota-derived short-chain Fatty acids, T cells, and inflammation.

Authors:  Chang H Kim; Jeongho Park; Myunghoo Kim
Journal:  Immune Netw       Date:  2014-12-22       Impact factor: 6.303

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1.  Microbial Metabolite Signaling Is Required for Systemic Iron Homeostasis.

Authors:  Nupur K Das; Andrew J Schwartz; Gabrielle Barthel; Naohiro Inohara; Qing Liu; Amanda Sankar; David R Hill; Xiaoya Ma; Olivia Lamberg; Matthew K Schnizlein; Juan L Arqués; Jason R Spence; Gabriel Nunez; Andrew D Patterson; Duxin Sun; Vincent B Young; Yatrik M Shah
Journal:  Cell Metab       Date:  2019-11-07       Impact factor: 27.287

2.  Absorptive transport of amino acids by the rat colon.

Authors:  Yuxin Chen; Meredith M Dinges; Andrew Green; Scott E Cramer; Cynthia K Larive; Christian Lytle
Journal:  Am J Physiol Gastrointest Liver Physiol       Date:  2019-11-25       Impact factor: 4.052

3.  Gut microbiota drives macrophage-dependent self-renewal of intestinal stem cells via niche enteric serotonergic neurons.

Authors:  Pingping Zhu; Tiankun Lu; Jiayi Wu; Dongdong Fan; Benyu Liu; Xiaoxiao Zhu; Hui Guo; Ying Du; Feng Liu; Yong Tian; Zusen Fan
Journal:  Cell Res       Date:  2022-04-04       Impact factor: 46.297

Review 4.  Hypermetabolism and Nutritional Support in Sepsis.

Authors:  John C Alverdy
Journal:  Surg Infect (Larchmt)       Date:  2018-02-02       Impact factor: 2.150

5.  Gut microbiota and serum metabolite differences in African Americans and White Americans with high blood pressure.

Authors:  Jacquelyn M Walejko; Seungbum Kim; Ruby Goel; Eileen M Handberg; Elaine M Richards; Carl J Pepine; Mohan K Raizada
Journal:  Int J Cardiol       Date:  2018-07-23       Impact factor: 4.164

6.  Human Gut Microbiota from Autism Spectrum Disorder Promote Behavioral Symptoms in Mice.

Authors:  Gil Sharon; Nikki Jamie Cruz; Dae-Wook Kang; Michael J Gandal; Bo Wang; Young-Mo Kim; Erika M Zink; Cameron P Casey; Bryn C Taylor; Christianne J Lane; Lisa M Bramer; Nancy G Isern; David W Hoyt; Cecilia Noecker; Michael J Sweredoski; Annie Moradian; Elhanan Borenstein; Janet K Jansson; Rob Knight; Thomas O Metz; Carlos Lois; Daniel H Geschwind; Rosa Krajmalnik-Brown; Sarkis K Mazmanian
Journal:  Cell       Date:  2019-05-30       Impact factor: 66.850

Review 7.  Bioengineered Systems and Designer Matrices That Recapitulate the Intestinal Stem Cell Niche.

Authors:  Yuli Wang; Raehyun Kim; Samuel S Hinman; Bailey Zwarycz; Scott T Magness; Nancy L Allbritton
Journal:  Cell Mol Gastroenterol Hepatol       Date:  2018-01-17

Review 8.  From gut microbiota to host appetite: gut microbiota-derived metabolites as key regulators.

Authors:  Hui Han; Bao Yi; Ruqing Zhong; Mengyu Wang; Shunfen Zhang; Jie Ma; Yulong Yin; Jie Yin; Liang Chen; Hongfu Zhang
Journal:  Microbiome       Date:  2021-07-20       Impact factor: 14.650

Review 9.  What We Know So Far about the Metabolite-Mediated Microbiota-Intestinal Immunity Dialogue and How to Hear the Sound of This Crosstalk.

Authors:  Clément Caffaratti; Caroline Plazy; Geoffroy Mery; Abdoul-Razak Tidjani; Federica Fiorini; Sarah Thiroux; Bertrand Toussaint; Dalil Hannani; Audrey Le Gouellec
Journal:  Metabolites       Date:  2021-06-21

Review 10.  Regulation of Neurotransmitters by the Gut Microbiota and Effects on Cognition in Neurological Disorders.

Authors:  Yijing Chen; Jinying Xu; Yu Chen
Journal:  Nutrients       Date:  2021-06-19       Impact factor: 5.717

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