Metabolomics is a powerful technique for the discovery of novel biomarkers and elucidation of biochemical pathways to improve diagnosis, prognosis and therapy. An advantage of this approach is its ability to assess global metabolic profiles to enhance pathologic characterization. Urine is an ideal bio-medium for disease study because it is readily available, easily obtained and less complex than other body fluids. Ease of collection allows for serial sampling to monitor disease and therapeutic response. Because of this potential, this paper will review urine metabolomic analysis, discuss its significance in the post-genomic era and highlight the specific roles of endogenous small molecule metabolites in this emerging field.

To enhance the therapeutic efficacy and reduce the adverse effects of traditional Chinese medicine, practitioners often prescribe combinations of plant species and/or minerals, called formulae. Unfortunately, the working mechanisms of most of these compounds are difficult to determine and thus remain unknown. In an attempt to address the benefits of formulae based on current biomedical approaches, we analyzed the components of Yinchenhao Tang, a classical formula that has been shown to be clinically effective for treating hepatic injury syndrome. The three principal components of Yinchenhao Tang are Artemisia annua L., Gardenia jasminoids Ellis, and Rheum Palmatum L., whose major active ingredients are 6,7-dimethylesculetin (D), geniposide (G), and rhein (R), respectively. To determine the mechanisms underlying the efficacy of this formula, we conducted a systematic analysis of the therapeutic effects of the DGR compound using immunohistochemistry, biochemistry, metabolomics, and proteomics. Here, we report that the DGR combination exerts a more robust therapeutic effect than any one or two of the three individual compounds by hitting multiple targets in a rat model of hepatic injury. Thus, DGR synergistically causes intensified dynamic changes in metabolic biomarkers, regulates molecular networks through target proteins, has a synergistic/ additive effect, and activates both intrinsic and extrinsic pathways. Molecular & Cellular

Shaoyao-Gancao decoction (SGD), a traditional Chinese formulae containing Paeoniae Radix and Glycyrrhizae Radix, is commonly used to relieve abdominal pain. It has attracted increasingly much attention as one of the most popular and valuable herbal medicine in clinic. However, the systematic analysis of chemical constituents of SGD are difficult to determine and thus remain unclear. In this paper, a rapid, sensitive, and reliable ultra-performance LC-ESI/quadrupole-TOF high-definition MS (UPLC-ESI-Q-TOF-MS) with automated MetaboLynx analysis in negative ion mode were established to characterize the chemical constituents of SGD. The analysis was performed on a Waters UPLC(TM) HSS T3 (2.1 × 100 mm, 1.8 μm) using gradient elution system. MS/MS fragmentation behavior was proposed for aiding the structural identification of the components. With the optimized conditions, a total of 58 peaks were tentatively characterized by comparing the retention time and mass spectrometry data and retrieving the reference literatures. Of note, 44 ingredients were identified from Glycyrrhizae Radix, and 14 were from Paeoniae Radix. It is concluded that a rapid and robust platform based on UPLC-ESI-Q-TOF-MS was successfully developed for globally identifying multiple-constituent of traditional Chinese medicine prescriptions. This is the first report on systematic analysis of chemical constituents and in vivo metabolites of SGD.

Metabolomics is a powerful new technology that allows the assessment of global low-molecular-weight metabolites in a biological system and which shows great potential in biomarker discovery. Analysis of the key metabolites in body fluids has become an important part of improving the diagnosis, prognosis, and therapy of diseases. Hepatitis C virus (HCV) is a major leading cause of liver disease worldwide and a serious burden on public health. However, the lack of a small-animal model has hampered the analysis of HCV pathogenesis. We hypothesize that an animal model (Tupaia belangeri chinensis) of HCV would produce a unique characterization of metabolic phenotypes. Ultra-performance liquid-chromatography/electrospray ionization-SYNAPT-high-definition mass spectrometry (UPLC/ESI-SYNAPT-HDMS) coupled with pattern recognition methods and system analysis was carried out to obtain comprehensive metabolomics profiling and pathways of large biological data sets. Taurine, hypotaurine, ether lipid, glycerophospholipid, arachidonic acid, tryptophan, and primary bile acid metabolism pathways were acutely perturbed, and 38 differential metabolites were identified. More important, five metabolite markers were selected via the "significance analysis for microarrays" method as the most discriminant and interesting biomarkers that were effective for the diagnosis of HCV. Network construction has led to the integration of metabolites associated with the multiple perturbation pathways. Integrated network analysis of the key metabolites yields highly related signaling pathways associated with the differentially expressed proteins, which suggests that the creation of new treatment paradigms targeting and activating these networks in their entirety, rather than single proteins, might be necessary for controlling and treating HCV efficiently.

To discover and screen the constituents or metabolites absorbed into blood after oral administration of herbal medicines tends to be more and more difficult. In this work, an integrative pattern recognition approach of principal component analysis (PCA) and orthogonal partial least squared discriminant analysis (OPLS-DA) was successfully applied for rapid discovery of natural compounds from herbal medicines. A rapid, sensitive, and reliable ultra performance liquid chromatography coupled with electrospray ionization/quadrupole-time-of-flight mass spectrometry (UPLC-ESI-Q-TOF-MS) method with Masslynx™ software was established to characterize the chemical constituents and rats metabolites of Phellodendri amurensis cortex (Guan Huangbai, GHB). The analysis was performed on a Waters UPLC HSS T3 column (2.1 × 100 mm, 1.8 μm) using gradient elution system. A hyphenated electrospray ionization and quadrupole-time-of-flight analyzer was used for the determination of accurate mass of the protonated or deprotonated molecule and fragment ion in both negative and positive modes. A total of 46 peaks were obtained, 41 of which were tentatively characterized from GHB. In the S-plot of OPLS-DA, 24 interested ions (17 ions in positive mode and 6 ions in negative mode) were extracted, among them, 12 absorbed prototype components of GHB and 12 metabolites were identified in vivo. Major metabolic reactions of GHB were demethylation, methylation and glucuronidation. This is the first report on systematic analysis of chemical constituents and in vivo metabolites of GHB. It is concluded that UPLC-MS coupled with pattern recognition approach for the identification of herbal constituents in biological samples has been successfully developed. The method can also be applied to rapid discovery and global characterization of the constituents in rat serum after oral administration of other herbal medicines.