Humans have evolved intimate symbiotic relationships with a consortium of gut microbes (microbiome) and individual variations in the microbiome influence host health, may be implicated in disease etiology, and affect drug metabolism, toxicity, and efficacy. However, the molecular basis of these microbe-host interactions and the roles of individual bacterial species are obscure. We now demonstrate a''transgenomic'' approach to link gut microbiome and metabolic phenotype (metabotype) variation. We have used a combination of spectroscopic, microbiomic, and multivariate statistical tools to analyze fecal and urinary samples from seven Chinese individuals (sampled twice) and to model the microbialhost metabolic connectivities. At the species level, we found structural differences in the Chinese family gut microbiomes and those reported for American volunteers, which is consistent with population microbial cometabolic differences reported in epidemiological studies. We also introduce the concept of functional metagenomics, defined as ''the characterization of key functional members of the microbiome that most influence host metabolism and hence health.'' For example, Faecalibacterium prausnitzii population variation is associated with modulation of eight urinary metabolites of diverse structure, indicating that this species is a highly functionally active member of the microbiome, influencing numerous host pathways. Other species were identified showing different and varied metabolic interactions. Our approach for understanding the dynamic basis of host-microbiome symbiosis provides a foundation for the development of functional metagenomics as a probe of systemic effects of drugs and diet that are of relevance to personal and public health care solutions. covariation analysis ͉ gut microbiota ͉ metabonomics ͉ metabotype ͉ metagenomics

Colorectal carcinogenesis involves the overexpression of many immediate-early response genes associated with growth and inflammation, which significantly alters downstream protein synthesis and small-molecule metabolite production. We have performed a serum metabolic analysis to test the hypothesis that the distinct metabolite profiles of malignant tumors are reflected in biofluids. In this study, we have analyzed the serum metabolites from 64 colorectal cancer (CRC) patients and 65 healthy controls using gas chromatography time-of-flight mass spectrometry (GC-TOFMS) and Acquity ultraperformance liquid chromatography-quadrupole time-of-flight mass spectrometry (Acquity UPLC-QTOFMS). Orthogonal partial least-squares discriminate analysis (OPLS-DA) models generated from GC-TOFMS and UPLC-QTOFMS metabolic profile data showed robust discrimination from CRC patients and healthy controls. A total of 33 differential metabolites were identified using these two analytical platforms, five of which were detected in both instruments. These metabolites potentially reveal perturbation of glycolysis, arginine and proline metabolism, fatty acid metabolism and oleamide metabolism, associated with CRC morbidity. These results suggest that serum metabolic profiling has great potential in detecting CRC and helping to understand its underlying mechanisms.

Missing values exist widely in mass-spectrometry (MS) based metabolomics data. Various methods have been applied for handling missing values, but the selection can significantly affect following data analyses. Typically, there are three types of missing values, missing not at random (MNAR), missing at random (MAR), and missing completely at random (MCAR). Our study comprehensively compared eight imputation methods (zero, half minimum (HM), mean, median, random forest (RF), singular value decomposition (SVD), k-nearest neighbors (kNN), and quantile regression imputation of left-censored data (QRILC)) for different types of missing values using four metabolomics datasets. Normalized root mean squared error (NRMSE) and NRMSE-based sum of ranks (SOR) were applied to evaluate imputation accuracy. Principal component analysis (PCA)/partial least squares (PLS)-Procrustes analysis were used to evaluate the overall sample distribution. Student’s t-test followed by correlation analysis was conducted to evaluate the effects on univariate statistics. Our findings demonstrated that RF performed the best for MCAR/MAR and QRILC was the favored one for left-censored MNAR. Finally, we proposed a comprehensive strategy and developed a public-accessible web-tool for the application of missing value imputation in metabolomics (https://metabolomics.cc.hawaii.edu/software/MetImp/).

Legends for figures 2 and 3 have been revised along with abbreviation for HCC; hepatocellular carcinoma. The online version of this article reflects these changes.

Background & Aims The prevalence of non-alcoholic fatty liver disease (NAFLD) and steatohepatitis (NASH) is increasing at an alarming rate. The role of bile acids in the development and progression of NAFLD to NASH and cirrhosis is poorly understood. This study aimed to quantify the bile acid metabolome in healthy subjects and patients with non-cirrhotic NASH under fasting conditions and after a standardized meal. Methods Liquid chromatography tandem mass spectroscopy was used to quantify 30 serum and 16 urinary bile acids from 15 healthy volunteers and 7 patients with biopsy-confirmed NASH. Bile acid concentrations were measured at two fasting and four post-prandial timepoints following a high-fat meal to induce gallbladder contraction and bile acid reabsorption from the intestine. Results Patients with NASH had significantly higher total serum bile acid concentrations than healthy subjects under fasting conditions (2.2- to 2.4-fold increase in NASH; NASH: 2595–3549 μM and healthy: 1171–1458 μM) and at all post-prandial time points (1.7- to 2.2-fold increase in NASH; NASH: 4444–5898 μM and healthy: 2634–2829 μM). These changes were driven by increased taurine- and glycine-conjugated primary and secondary bile acids. Patients with NASH exhibited greater variability in their fasting and post-prandial bile acid profile. Conclusions Results indicate that patients with NASH have higher fasting and post-prandial exposure to bile acids, including the more hydrophobic and cytotoxic secondary species. Increased bile acid exposure may be involved in liver injury and the pathogenesis of NAFLD and NASH.

Schizophrenia is a severe mental disorder that affects 0.5–1% of the population worldwide. Current diagnostic methods are based on psychiatric interviews, which are subjective in nature. The lack of disease biomarkers to support objective laboratory tests has been a long-standing bottleneck in the clinical diagnosis and evaluation of schizophrenia. Here we report a global metabolic profiling study involving 112 schizophrenic patients and 110 healthy subjects, who were divided into a training set and a test set, designed to identify metabolite markers. A panel of serum markers consisting of glycerate, eicosenoic acid, β-hydroxybutyrate, pyruvate and cystine was identified as an effective diagnostic tool, achieving an area under the receiver operating characteristic curve (AUC) of 0.945 in the training samples (62 patients and 62 controls) and 0.895 in the test samples (50 patients and 48 controls). Furthermore, a composite panel by the addition of urine β-hydroxybutyrate to the serum panel achieved a more satisfactory accuracy, which reached an AUC of 1 in both the training set and the test set. Multiple fatty acids and ketone bodies were found significantly (P<0.01) elevated in both the serum and urine of patients, suggesting an upregulated fatty acid catabolism, presumably resulting from an insufficiency of glucose supply in the brains of schizophrenia patients.

After our serum metabonomic study of colorectal cancer (CRC) patients recently published in J. Proteome Res., we profiled urine metabolites from the same group of CRC patients (before and after surgical operation) and 63 age-matched healthy volunteers using gas chromatography-mass spectrometry (GC-MS) in conjunction with a multivariate statistics technique. A parallel metabonomic study on a 1,2-dimethylhydrazine (DMH)-treated Sprague-Dawley rat model was also performed to identify significantly altered metabolites associated with chemically induced precancerous colorectal lesion. The orthogonal partial least-squares-discriminant analysis (OPLS-DA) models of metabonomic results demonstrated good separations between CRC patients or DMH-induced model rats and their healthy counterparts. The significantly increased tryptophan metabolism, and disturbed tricarboxylic acid (TCA) cycle and the gut microflora metabolism were observed in both the CRC patients and the rat model. The urinary metabolite profile of postoperative CRC subjects altered significantly from that of the preoperative stage. The significantly down-regulated gut microflora metabolism and TCA cycle were observed in postoperative CRC subjects, presumably due to the colon flush involved in the surgical procedure and weakened physical conditions of the patients. The expression of 5-hydroxytryptophan significantly decreased in postsurgery samples, suggesting a recovered tryptophan metabolism toward healthy state. Abnormal histamine metabolism and glutamate metabolism were found only in the urine samples of CRC patients, and the abnormal polyamine metabolism was found only in the rat urine. This study assessed the important metabonomic variations in urine associated with CRC and, therefore, provided baseline information complementary to serum/plasma and tissue metabonomics for the complete elucidation of the underlying metabolic mechanisms of CRC.

Dysregulated bile acids (BAs) are closely associated with liver diseases and attributed to altered gut microbiota. Here, we show that the intrahepatic retention of hydrophobic BAs including deoxycholate (DCA), taurocholate (TCA), taurochenodeoxycholate (TCDCA), and taurolithocholate (TLCA) were substantially increased in a streptozotocin and high fat diet (HFD) induced nonalcoholic steatohepatitis-hepatocellular carcinoma (NASH-HCC) mouse model. Additionally chronic HFD-fed mice spontaneously developed liver tumors with significantly increased hepatic BA levels. Enhancing intestinal excretion of hydrophobic BAs in the NASH-HCC model mice by a 2% cholestyramine feeding significantly prevented HCC development. The gut microbiota alterations were closely correlated with altered BA levels in liver and feces. HFD-induced inflammation inhibited key BA transporters, resulting in sustained increases in intrahepatic BA concentrations. Our study also showed a significantly increased cell proliferation in BA treated normal human hepatic cell lines and a down-regulated expression of tumor suppressor gene CEBPα in TCDCA treated HepG2 cell line, suggesting that several hydrophobic BAs may collaboratively promote liver carcinogenesis.