Metabolomic analyses of faeces reveals malabsorption in cirrhotic patients

Digestive and Liver Disease 45 (2013) 677–682

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Liver, Pancreas and Biliary Tract

Metabolomic analyses of faeces reveals malabsorption in cirrhotic patients Hai-jun Huang a,b , An-ye Zhang a , Hong-cui Cao a , Hai-feng Lu a , Bao-hong Wang a , Qing Xie a , Wei Xu a , Lan-Juan Li a,∗ a b

State Key Laboratory for Diagnosis and Treatment of Infectious Disease, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou 310003, PR China Department of Infectious Disease, Zhejiang Provincial People’s Hospital, Hangzhou 310014, PR China

a r t i c l e

i n f o

Article history: Received 31 August 2012 Accepted 1 January 2013 Available online 4 February 2013 Keywords: Faecal water extracts Liver cirrhosis Metabolomics UPLC/Q-TOF MS

a b s t r a c t Background: The study of faeces offers a unique opportunity to observe cooperation between the microbiome and the metabolism of mammalian hosts, an essential element in the study of the human metabolome. In the present study, a global metabolomics approach was used to identify metabolites differentially excreted in the faeces of cirrhotic patients compared to controls. Methods: Seventeen cirrhotic patients and 24 healthy individuals were recruited. Faecal metabolites were detected through non-targeted reversed-phase ultra-performance liquid chromatography coupled to electrospray ionization quadrupole time-of-flight mass spectrometry. Results: A total of 9215 peaks were detected. Using unequal variance t-tests, 2393 peaks were observed with P ≤ 0.05, approximately 74.0% of which were due to decreased faecal metabolite concentrations in liver cirrhosis vs. healthy controls. Integrating multivariate data analyses, we identified six major groups of metabolites. Relative levels of identified metabolites were as follows: strong increase in lysophosphatidylcholines, aromatic amino acids, fatty acids, and acylcarnitines, and a dramatic decrease in bile acids and bile pigments. Conclusion: With severe hepatic injury in patients with liver cirrhosis, malabsorption occurs along with disorders of fatty acid metabolism, potentially due to changes in gut microflora. © 2013 Editrice Gastroenterologica Italiana S.r.l. Published by Elsevier Ltd. All rights reserved.

1. Introduction Liver cirrhosis is defined as the histological development of regenerative nodules surrounded by fibrous scar tissue in response to chronic liver injury of various etiologies, leading to progressive loss of liver function, and to altered liver metabolism. Cirrhosis and its associated complications are a major cause of morbidity and mortality worldwide [1]. Furthermore, 1–4% of cirrhotic patients with chronic hepatitis B or chronic hepatitis C develop primary liver cancer yearly [2]. Since liver cirrhosis is associated with serious sequelae, it is important for clinicians to better understand the pathophysiology of liver cirrhosis. Metabolomics, a rapidly evolving tool in systems biology of small molecules, aims to identify untargeted potential biomarkers [3]. This technique offers great promise as an effective and non-invasive diagnostic method [4,5] and is a powerful approach for understanding the pathophysiology of diseases [6,7]. It can be applied to any biofluid, however tissue, blood and urine are the most frequently used specimens for exploring systematic alterations of metabolites in humans. Faecal samples are an

obvious choice since they can be obtained easily and noninvasively, and can reflect the cooperation between microbiome–mammalian metabolism which is an essential element in the study of the human metabolome [8]. Discovering biomarkers of liver cirrhosis through a metabolomics approach is important for basic understanding of the mechanisms of liver damage, drug development, and clinical use (for example, diagnostic, prognostic biomarkers or therapeutic response). Previous metabolomic studies of liver diseases have found several biomarkers which provide new insights into the pathogenesis of hepatic diseases, including hepatic injury, oxidative stress and the abnormal metabolism of lipids and amino acids [5,9,10]. In the present study, we used ultra-performance liquid chromatography coupled with Q-TOF mass spectrometry (UPLC/Q-TOF MS) to analyze faecal samples collected from patients with liver cirrhosis in order to discover potential biomarkers, and gain new insights into the pathophysiology of cirrhosis. 2. Materials and methods 2.1. Study population

∗ Corresponding author. Tel.: +86 571 87236456; fax: +86 571 87236456. E-mail address: [email protected] (L.-J. Li).

Written informed consent was obtained from all participants prior to initiating the trial and the study protocol conformed

1590-8658/$36.00 © 2013 Editrice Gastroenterologica Italiana S.r.l. Published by Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.dld.2013.01.001

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Table 1 Demographic and clinical characteristics of the study participants. Characteristic

Patient group (n = 17)

Healthy group (n = 24)

p-Value

Age (year) Gender (male/female) ALB, g/L (35–55) ALT, U/L (3–50) AST, U/L (3–40) TB, ␮mol/L (1–22) TBA, ␮mol/L (1–12) PT, s (10.5–14.0) Child–Pugh score

51.71 ± 10.02 11/6 32.80 ± 3.77 48.88 ± 29.40 83.89 ± 63.86 44.94 ± 35.60 66.76 ± 61.11 16.24 ± 3.46 8.06 ± 1.92

47.13 ± 8.08 17/7 46.56 ± 2.97 18.71 ± 7.74 21.46 ± 6.26 12.21 ± 4.10 2.93 ± 1.97 / /

0.113 0.678 <0.001 0.001 0.001 0.002 0.001

Abbreviations: ALB, albumin; ALT, alanine aminotransferase; AST, aspartate aminotransferase; TB, total bilirubin; TBA, total bile acid; PT, prothrombin time. Results are reported as mean ± SD.

to the ethical guidelines of the 1975 Declaration of Helsinki. The study was approved by the Human Ethics Committee of the First Affiliated Hospital, College of Medicine, Zhejiang University, China. Seventeen cirrhotic patients were recruited from patients who were admitted to the Department of Infectious Disease, The First Affiliated Hospital, College of Medicine, Zhejiang University during 2008–2009. These patients included nine patients with HBV-induced cirrhosis, five patients with hepatitis C virus-related cirrhosis, and three patients with alcoholic cirrhosis. A diagnosis of liver cirrhosis was confirmed using clinical signs, imaging findings, or evidence of esophagogastric varices. Patients with HIV co-infection or with hepatocellular carcinoma were excluded. The control group included 24 healthy individuals who came to the First Affiliated Hospital, College of Medicine, Zhejiang University for medical evaluation. They were confirmed to have normal liver function and no viral hepatitis, alcoholic or non-alcoholic fatty liver disease, or other diseases. Patients and volunteers did not undergo any gastrointestinal surgery or receive antibiotic treatment during the two months prior to the study. Subjects were advised to maintain their usual diet during the study period, and to avoid the intake of fermented foods. Demographic and clinical characteristics are shown in Table 1.

2.2. Sample collection and preparation After obtaining informed consent, all stool samples were taken immediately following defecation, aliquoted, and stored at −80 ◦ C until further use. Faecal water was extracted by taking a weighed sample of thawed stool, and mixing with methanol in a ratio of 3 ml/g. The mixture was homogenized using vortexing for 60 s, and then centrifuged at 10,000 rpm for 10 min. Supernatants were transferred to clean tubes, and then filtered through a membrane (0.22 ␮m pore size). The filtered faecal water was placed directly onto the column.

2.3. Chemicals Acetonitrile and formic acid (HPLC grade) were purchased from Sigma–Aldrich (St. Louis, MO). Distilled water was purified “inhouse” using a Milli-Q system (Millipore, Bedford, MA). Methanol, leucine-enkephalin, L-phenylalanine, L-tryptophan, L-tyrosine, chenodeoxycholic acid, lysophosphocholine (16:0), lysophosphocholine (18:2), lysophosphocholine (18:0), lysophosphocholine (18:1), linoleic acid and palmitoleic acid were purchased from Sigma–Aldrich. L-urobilin, L-urobilinogen and L-palmitoylcarnitine were purchased from J&K Chemical Ltd. (Beijing, China). 7Ketolithocholic acid was obtained from Tokyo Chemical Industry Co., Ltd. (Tokyo, Japan).

2.4. Chromatography A 2 ␮l aliquot was chromatographed on a (2.1 × 100 mm, ACQUITYTM 1.7 ␮m BEHC C18 column) (Waters, Milford, MA) maintained at 40 ◦ C using a ACQUITYTM UPLC system (Waters, Milford, MA). The mobile phase consisted of (A) 0.1% formic acid in water and (B) 0.1% formic acid in acetonitrile. The flow rate was 400 ␮l/min. A linear gradient was optimized as follows: 0–2 min, 3%–20% B; 2–5 min, 20%–30% B; 5–9 min, 30%–100% B; the composition was maintained at 100% B for 1 min, then for 9–12 min at equilibration with 3% B. The column eluent was directed to the mass spectrometer for analyses. 2.5. Mass spectrometry Mass spectrometry was performed on a Waters Micromass QTOF Premier (Waters Micromass Technologies, Manchester, UK) operating in positive electrospray ionization (ESI) modes with “VOptics”. Capillary voltage and a cone voltage were set to 3000 and 35 V, respectively. Source temperature and desolvation temperature were maintained at 100 ◦ C and 350 ◦ C, respectively. Nitrogen was used as both the desolvation gas (600 L/h) and cone gas (50 L/h). The Q-TOF Premier MS acquisition rate was set to 0.3 s with a 0.1 s interscan delay. The scan range was from 50 to 1000 m/z. Data were collected in the centroid mode. All analyses were acquired using lock spray to ensure mass accuracy and reproducibility, and leucine-enkephalin was used as the lock mass (m/z 556.2771) at a concentration of 200 ng/mL and a flow rate of 10 ␮L/min. Argon was used as the collision gas. The structures of faecal water biomarkers were elucidated using MS/MS fragmentation with collision energies ranging from 20 to 40 eV. 3. Data processing and statistical analyses Data were analyzed using the MarkerLynx applications manager Version 4.1 (Waters, Manchester, UK). This application manager integrates peaks in the UPLC-Q-TOF MS data using ApexTrack peak detection. The track peak parameters were set as follows: peak width at 5% height 15 s, peak-to-peak baseline noise calculated automatically, minimum intensity 100, mass window 0.01 (Da), retention time window 0.2 min, noise elimination level 3, mass tolerance 0.01 (Da) with exclusion of de-isotopic data. Data were only used for 0–12 min. The preprocessed data obtained by MarkerLynx were exported and analyzed using principal components analysis (PCA), and partial least squares discriminate analysis (PLS-DA) using SIMCA-P+ software (Umetrics). To globally analyze metabolomic differences between the liver cirrhosis group and the healthy group, unequal variance t-test analyses was performed with SPSS 16.0 for Windows (SPSS, Chicago, IL, USA).

H.-j. Huang et al. / Digestive and Liver Disease 45 (2013) 677–682

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Fig. 1. Comparison of UPLC–MS base peak intensity chromatogram (BPC) profiles of faeces from the patient with liver cirrhosis (A) and healthy controls (B).

To identify potential biomarkers, the peaks of significant differences obtained by unequal variance t-tests or by PLS-DA loading plot were searched against the METLIN [11], HMDB [12], and KEGG [13] databases using accurate mass information; mass accuracy from the TOF was within 5 parts per million for all metabolites. Tandem mass spectroscopy analyses was then performed to identify potential biomarkers, and the results were compared with the available standard compounds.

4. Results Typical base peak intensity chromatograms (BPC) of faecal extracts obtained from a patient with cirrhosis (A) and a healthy control (B) are shown in Fig. 1. A total of 9215 metabolite ion masses were detected using the preprocessing method described above. For statistical calculations, the intensity of each peak was automatically normalized using the MarkerLynx (Waters), making possible a comparison of the relative mass intensities of metabolites between the different data sets. The pre-processed UPLC-Q-TOF-MS data were further investigated.

4.1. Unequal variance t-tests of UPLC-Q-TOF-MS data To investigate metabolomic differences between cirrhotic patients and healthy controls, a total of 9215 peaks (defined by pairs of m/z ratios and retention times) were calculated using unequal variance t-tests. A total of 2393 peaks were found with P ≤ 0.05, which represents 25.8% of the total number of peaks in the data set. When the criteria were further restricted to differences with P ≤ 0.01, there were a total of 1159 peaks, or 12.6% of the total. Of particular interest was the extent to which the intensity data were skewed between disease vs. normal samples. Peaks with P ≤ 0.05, 1771 out of the 2393 (approximately 74.0%), were due to decreased faecal metabolite concentrations in patients with cirrhosis vs. healthy controls. When peaks were selected with P ≤ 0.01, 908 of the 1159, or 78.3% of the peaks were found to be decreased in the cirrhotic patients compared to healthy controls. In summary,

most of the metabolites that changed significantly were decreased in the patients with cirrhosis (Table 2). 4.2. Multivariate data analyses of UPLC-Q-TOF-MS data PCA was also performed to highlight clustering, trends and outliers in the observation direction, and to identify maximum variation in the data set. The PCA scores plot from extracted faecal specimens of healthy volunteers, and patients with liver cirrhosis showed a clear separation (Fig. 2A). We subsequently analyzed the data using PLS-DA to maximize the discrimination between healthy volunteers and patients with cirrhosis. A PLS-DA scores plot (Fig. 2B) showed a similar, but more pronounced discrimination. A PLS-DA loadings plot (Fig. 2C) revealed maximum variations which played important roles in the separation. 4.3. Metabolite identification Sixteen metabolites were identified by comparing their chromatographic retention time and MS/MS fragmentation characteristics with the available standard compounds (shown in Tables 3 and 4). Interestingly, fragmentation of three metabolites with m/z of 400.3406+ , 424.3371+ and 426.3559+ , all resulted in very similar mass spectra in which a carnitine fragment (m/z) 85.03+ was detected. Due to accurate mass measurements and knowledge of possible fragmentation, three metabolites with m/z ratios of 400.3406+ , 424.3371+ and 426.3559+ , corresponding to palmitoylcarnitine, linoleyl carnitine and elaidic carnitine, Table 2 Global characterization of the metabolomic data. Parameter

No. of peaksa

Total observations Observations with P ≤ 0.05 number (%) in total observation Observations with P ≤ 0.01 number (%) in total observation Observations with P ≤ 0.05 number (%) down in liver cirrhosis Observations with P ≤ 0.01 number (%) down in liver cirrhosis

9215 2393 (25.8%) 1159 (12.6%) 1771 (74.0%) 908 (78.3%)

a Defined as an m/z – retention time pair. P values compare liver cirrhosis and healthy control integrated intensities.

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H.-j. Huang et al. / Digestive and Liver Disease 45 (2013) 677–682 Table 3 The most prominent metabolites for discriminating between healthy control and liver cirrhosis patients according to VIP value. m/z

VIP value

Metabolite

Compared with controls

785.5883

27.47

↓

393.3008

1.40

391.2837

10.47

781.5589

8.42

595.3416 597.3590 496.3400 524.3697 522.3531 520.3383

22.05 13.48 9.99 8.93 5.35 4.16

Chenodeoxycholic acid dimeride Chenodeoxycholic acid 7-Ketolithocholic acid 7-Ketolithocholic acid dimeride Urobilin Urobilinogen LPC C16:0 LPC C18:0 LPC C18:1 LPC C18:2

↓ ↓ ↓ ↓ ↓ ↑ ↑ ↑ ↑

LPC, lysophosphatidyl choline; VIP, variable importance in the projection; ↑, upregulated; ↓, down-regulated.

Fig. 2. Multivariate data analyses of patients with liver cirrhosis and healthy controls. Filled black triangle: patients with liver cirrhosis, filled red box: healthy control. A: Scores scatter plots of the principal components analyses (PCA) of faeces samples from patients with liver cirrhosis and healthy controls. The t[1] and t[2] values represent the scores of the samples in principal components 1 and 2, which account for 51% of the total variations (R2 X = 0.51).B: Scores scatter plots of partial a least square discriminant analyses (PLS-DA) model of faeces from patients with liver cirrhosis and healthy controls. The fitness (R2 Y) and prediction power (Q2 Y) of this two-component model are 0.95 and 0.79, respectively. C: A loadings scatter plots representing the correlation between individual faecal ions (w*) and the sample groups (c) in the first and second components of the PLS-DA model. The ions most responsible for the variance in the scores plot are indicated on the loadings plot by their distance from the origin. The variables marked with ([1][1]) are the metabolites selected as potential biomarkers.

respectively were identified. Identities of the palmitoylcarnitine were further confirmed by comparison to authentic standards.

5. Discussion We found a decrease in concentration of a large number of metabolites in the faeces of patients with liver cirrhosis. From a holistic point of view, 2393 peaks with P ≤ 0.05, approximately 74.0% of which represent decreased faecal metabolite concentrations in liver cirrhosis, were significantly altered in samples from cirrhotic vs. normal participants. This indicated an apparent downregulation of many metabolites associated with cirrhosis. Among these peaks, we identified six major groups of metabolites: bile acids, bile pigments, lysophosphatidylcholines, aromatic amino acids, fatty acids and acylcarnitines.

According to the variable importance in the projection (VIP) value, the most pronounced change among the cirrhotic patient samples was that faecal bile acids (chenodeoxycholic acid and 7ketolithocholic acid) diminished dramatically. Chenodeoxycholic acid is a primary bile acid. 7-Ketolithocholic acid is thought to be the major intermediate in the intestinal bacterial conversion of chenodeoxycholic to ursodeoxycholic acid [14]. Bile acids are synthesized in hepatocytes from cholesterol by hepatic enzymes, and excreted into the bile duct in the predominantly conjugated form, [15] and returned to the liver by an efficient enterohepatic circulation. For excretion from the body, bile acids can undergo complex bacterial deconjugation. The main forms of bile acids in faeces, therefore, are primary bile acids and secondary bile acids [16]. Bile acids serve many important physiological functions, including stimulation of bile flow, secretion of biliary lipid, mediation of the absorption of dietary lipids, and suppression of bacterial growth in the small intestine [17,18]. Fat malabsorption and intestinal bacterial overgrowth have been associated with a deficiency in intraluminal bile acids in patients with cirrhosis [19]. The levels of faecal bile acids are determined by bile release from the gallbladder, hepatic synthesis and intestinal absorption. Bile acid secretion is markedly decreased in cirrhotic patients [20]. Moreover, hepatic synthesis of bile acids is impaired. Finally, small intestinal bacterial overgrowth may accelerate bacterial deconjugation, which may worsen intraluminal bile acid deficiency because unconjugated bile acids are rapidly absorbed by non-ionic diffusion [21,22]. Another important change in patients with cirrhosis is that levels of faecal urobilin and urobilinogen decrease dramatically. Urobilinogen is formed by bacterial action on bilirubin, which mostly occurs in the distal ileum and colon [23]. Urobilin is an oxidized form of urobilinogen. The main forms of bile pigments in faeces, therefore, are urobilinoids. In cirrhotic patients, markedly Table 4 Potential differential metabolites selected and identified according to t-test. m/z

t-Test value

Metabolite

Compared with controls

205.0848 166.0865 182.0748 400.3420 424.3362 426.3556 281.2349 255.2180

<0.001 0.003 0.007 0.01 0.014 0.041 <0.001 0.048

Tryptophan Phenylalanine Tyrosine Palmitoylcarnitine Linoleyl carnitine Elaidic carnitine Linoleic acid Palmitoleic acid

↑ ↑ ↑ ↑ ↑ ↑ ↑ ↑

↑, Up-regulated.

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decreased bilirubin excretion [24], and conversion to urobilinogen, have been shown to result in diminished faecal urobilinogen. Moreover, intestinal bacterial action on deconjugation of conjugated bilirubin and reduction of unconjugated bilirubin [20] has been shown to be impaired due to an imbalance of gut microflora in cirrhosis, which may cause a further decrease in faecal urobilinoids. This may play a role in elevated bilirubin concentrations in plasma [25]. An intriguing result of our study is the significant increase in faecal lysophosphatidylcholine concentration in patients with cirrhosis, which has not been previously reported. Faecal lysophosphatidylcholines mainly originate from phospholipase A2 or possibly gut microflora hydrolysis of dietary and biliary phosphatidylcholine, which is a major component of dietary and biliary phospholipid. Biliary phospholipid secretion is diminished in cirrhotic patients [26]. The increased excretion of lysophosphatidylcholines, therefore, may indicate malabsorption. Elevated concentrations of faecal lysophosphatidylcholines may be due to several reasons. First, pancreatic insufficiency is considered to be a cause of increased excretion of lysophosphatidylcholine in patients with cystic fibrosis [27]. It has been shown that pancreatic exocrine function is impaired in patients with cirrhosis [28]. This may induce decreased secretion of phospholipase A2, and reduced digestion and absorption of phosphatidylcholine. We believe that impaired phospholipase A2 secretion is responsible for the elevated faecal lysophosphatidylcholine excretion in patients with cirrhosis. However, the effects of dietary phosphatidylcholine on faecal excretion of lysophosphatidylcholines was not determined due to a lack of data on the phospholipid content of foods. Secondly, there are considerable amounts of lecithinase-positive bacteria in gut microflora, which may be considered to be sensitive to dietary variables [29,30]. We therefore presume that the imbalance of gut microflora in cirrhosis may play a role in the elevated faecal lysophosphatidylcholine. In the current study, the amounts of phenylalanine, tryptophan and tyrosine were increased in the aqueous faecal extracts of patients with cirrhosis compared with healthy subjects. Phenylalanine and tryptophan, two essential amino acids, can be obtained only from the diet, and cannot be synthesized by humans; tyrosine can be produced from phenylalanine. Increased concentrations of these aromatic amino acids may suggest malabsorption. Amino acids absorbed by digestion can undergo protein synthesis, deamination, and transamination in the liver. Elevated aromatic amino acids may be due to several causes. First, disposal of these amino acids is impaired in cirrhosis [31,32]. This can be due to reduced first-pass splanchnic (likely hepatic) uptake of amino acids [33] which may reduce the absorption of amino acids. Second, production of amino acids is increased in patients with cirrhosis [31]. Third, gut microflora has been demonstrated to have a large effect on the disposal of these aromatic amino acids [34]. Since gut microflora imbalance in liver cirrhosis has been described previously, it is possible that altered gut microflora may play a role. We found increased levels of faecal fatty acids (linoleic acid and palmitoleic acid) which may indicate malabsorption and/or low intake. Our results are in agreement with a previous study [19]. In the intestinal lumen, long-chain fatty acids are hydrolyzed from triacylglycerols by pancreatic lipase. The mechanism of this defect in fat absorption remains unclear. Pancreatic disorders and inadequate bile excretion may be responsible for elevated fat acid excretion [19], and imbalance of gut microflora secondary to cirrhosis, and may also contribute to the low absorption of fatty acids [35]. An increased concentration of long-chain acylcarnitines in the aqueous faecal extracts was observed in patients with cirrhosis. This may be due to disorders of fatty acid or organic acid metabolism [36]. Although the majority of carnitines are obtained

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from the diet, long-chain acylcarnitines are formed in the liver, and mainly excreted by biliary transport [37]. Faecal acylcarnitines, therefore, originate from biliary acylcarnitine and may reflect plasma concentrations. In a previous study, the concentration of long-chain acylcarnitines in the plasma of cirrhosis patients, due to viral hepatitis, showed a significant increase in comparison to agematched control subjects [38]. Our finding of increased long-chain acylcarnitine concentrations in the gut are most likely a result of elevated biliary excretion from increased plasma long-chain acylcarnitine concentrations. Moreover, long-chain acylcarnitine in the gut can be used as a nitrogen or carbon source by intestinal bacteria [39]. Therefore, it is possible that the differences in gut microflora between patients with liver cirrhosis and healthy controls may play an important role in the development of elevated long-chain acylcarnitine levels in the gut. In conclusion, a metabolomics approach based on the UPLC–MS technique was used to characterize perturbations of the faecal metabolome in healthy subjects and patients with cirrhosis. Our findings suggest that with severe hepatic injury in patients with cirrhosis, malabsorption occurs along with disorders of fatty acid metabolism, which may be due to changes in gut microflora. Conflict of interest statement None declared. Acknowledgements This work was supported by the National Science and Technology Major Project (2012ZX10002004), and the Technology Group Project for Infectious Disease Control of Zhejiang Province (2009R50041). References [1] Schuppan D, Afdhal NH. Liver cirrhosis. Lancet 2008;8(371(9615)):838–51. [2] Befeler AS, Di Bisceglie AM. Hepatocellular carcinoma: diagnosis and treatment. Gastroenterology 2002;122(6):1609–19. [3] Want EJ, Nordstrom A, Morita H, et al. From exogenous to endogenous: the inevitable imprint of mass spectrometry in metabolomics. Journal of Proteome Research 2007;6:459–68. [4] Marchesi JR, Holmes E, Khan F, et al. Rapid and noninvasive metabonomic characterization of inflammatory bowel disease. Journal of Proteome Research 2007;6:546–51. [5] Yu K, Sheng G, Sheng J, et al. A metabonomic investigation on the biochemical perturbation in liver failure patients caused by hepatitis B virus. Journal of Proteome Research 2007;6:2413–9. [6] Li M, Wang B, Zhang M, et al. Symbiotic gut microbes modulate human metabolic phenotypes. Proceedings of the National Academy of Sciences of the United States of America 2008;105:2117–22. [7] Dumas ME, Barton RH, Toye A, et al. Metabolic profiling reveals a contribution of gut microbiota to fatty liver phenotype in insulin-resistant mice. Proceedings of the National Academy of Sciences of the United States of America 2006;103:12511–6. [8] Nicholson JK, Holmes E, Wilson ID. Gut microorganisms, mammalian metabolism and personalized health care. Nature Reviews Microbiology 2005;3:431–8. [9] Yang J, Zhao X, Liu X, et al. High performance liquid chromatography-mass spectrometry for metabonomics: potential biomarkers for acute deterioration of liver function in chronic hepatitis B. Journal of Proteome Research 2006;5:554–61. [10] Yin P, Wan D, Zhao C, et al. A metabonomic study of hepatitis B-induced liver cirrhosis and hepatocellular carcinoma by using RP-LC and HILIC coupled with mass spectrometry. Molecular BioSystems 2009;5:868–76. [11] Smith CA, O’Maille G, Want EJ, et al. METLIN: a metabolite mass spectral database. Therapeutic Drug Monitoring 2005;27:747–51. [12] Wishart DS, Tzur D, Knox C, et al. HMDB: the human metabolome database. Nucleic Acids Research 2007;35:D521–6. [13] Kanehisa M, Goto S. KEGG: kyoto encyclopedia of genes and genomes. Nucleic Acids Research 2000;28:27–30. [14] Fukiya S, Arata M, Kawashima H, et al. Conversion of cholic acid and chenodeoxycholic acid into their 7-oxo derivatives by bacteroides intestinalis AM-1 isolated from human feces. FEMS Microbiology Letters 2009;293:263–70. [15] Matoba N, Une M, Hoshita T. Identification of unconjugated bile acids in human bile. Journal of Lipid Research 1986;27:1154–62.

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