Guowang Xu

Metabonomics study of liver cancer based on ultra performance liquid chromatography coupled to mass spectrometry with HILIC and RPLC separations

In this study, urinary metabolites from liver cancer patients and healthy volunteers were studied by a metabonomic method based on ultra performance liquid chromatography coupled to mass spectrometry. Both hydrophilic interaction chromatography (HILIC) and reversed-phase liquid chromatography (RPLC) were used to separate the urinary metabolites. Principle component analysis (PCA) and partial least squares to latent structure-discriminant analysis (PLS-DA) models were built to separate the healthy volunteers from the liver cancer patients and to find compounds that are expressed in significantly different amounts between the two populations. 21 metabolite ions were considered as potential biomarkers according to the Variable importance in the Project (VIP) value and S-plot. Compared with RPLC, a more sensitive and stable response can be recorded in HILIC mode due to the high content of organic solvent used. Moreover, the liver cancer group and the healthy volunteers can be better separated based on the data from the HILIC separation, which indicates that HILIC is suitable for urinary metabonomic analysis. In HILIC mode, several polar compounds related to arginine and proline metabolism, alanine and aspartate metabolism, lysine degradation, nicotinate and nicotinamide metabolism were found to be significantly changed in the concentrations of the two different populations: healthy and cancer. In contrast, in RPLC mode, these changed compounds are related to fatty acids oxidation.

Metabolic Characterization of Hepatocellular Carcinoma Using Nontargeted Tissue Metabolomics

Hepatocellular carcinoma has a poor prognosis due to its rapid development and early metastasis. In this report, we characterized the metabolic features of hepatocellular carcinoma using a nontargeted metabolic profiling strategy based on liquid chromatography-mass spectrometry. Fifty pairs of liver cancer samples and matched normal tissues were collected from patients having hepatocellular carcinoma, including tumor tissues, adjacent noncancerous tissues, and distal noncancerous tissues, and 105 metabolites were filtered and identified from the tissue metabolome. The principal metabolic alternations in HCC tumors included elevated glycolysis, gluconeogenesis, and β-oxidation with reduced tricarboxylic acid cycle and Δ-12 desaturase. Furthermore, increased levels of glutathione and other antioxidative molecules, together with decreased levels of inflammatory-related polyunsaturated fatty acids and phospholipase A2, were observed. Differential metabolite levels in tissues were tested in 298 serum specimens from patients with chronic hepatitis, cirrhosis, and hepatocellular carcinoma. Betaine and propionylcarnitine were confirmed to confer good diagnostic potential to distinguish hepatocellular carcinoma from chronic hepatitis and cirrhosis. External validation of cirrhosis and hepatocellular carcinoma serum specimens further showed that this combination biomarker is useful for diagnosis of hepatocellular carcinoma with a supplementary role to α-fetoprotein.

Analytical strategies in lipidomics and applications in disease biomarker discovery

Lipidomics is a lipid-targeted metabolomics approach aiming at comprehensive analysis of lipids in biological systems. Recently, lipid profiling, or so-called lipidomics research, has captured increased attention due to the well-recognized roles of lipids in numerous human diseases to which lipid-associated disorders contribute, such as diabetes, obesity, atherosclerosis and Alzheimers disease. Investigating lipid biochemistry using a lipidomics approach will not only provide insights into the specific roles of lipid molecular species in health and disease, but will also assist in identifying potential biomarkers for establishing preventive or therapeutic approaches for human health. Recent technological advancements in mass spectrometry and rapid improvements in chromatographic techniques have led to the rapid expansion of the lipidomics research field. In this review, emphasis is given to the recent advances in lipidomics technologies and their applications in disease biomarker discovery.

Practical approach for the identification and isomer elucidation of biomarkers detected in a metabonomic study for the discovery of individuals at risk for diabetes by integrating the chromatographic and mass spectrometric information

Sensitive and high-resolution chromatographic-driven metabonomomics studies experienced major growth with the aid of new analytical technologies and bioinformatics software packages. Hence, data collections by LC-MS and data analyses by multivariate statistical methods are by far the most straightforward steps, and the detection of biomarker candidates can easily be achieved. However, the unequivocal identification of the detected metabolite candidates, including isomer elucidation, is still a crux of current metabonomics studies. Here we present a comprehensive analytical strategy for the elucidation of the molecular structure of metabolite biomarkers detected in a metabonomics study, exemplified analyzing spot urine of a cohort of healthy, insulin sensitive subjects and clinically well characterized prediabetic, insulin resistant individuals. An integrated approach of LC-MS fingerprinting, multivariate statistic analysis, LC-MSn experiments, micro preparation, FTICR-MS, GC retention index, database search, and generation of an isotope labeled standard was applied. Overall, we could demonstrate the efficiency of our analytical approach by the unambiguous elucidation of the molecular structure of an isomeric biomarker candidate detected in a complex human biofluid. The proposed strategy is a powerful new analytical tool, which will allow the definite identification of physiologically important molecules in metabonomics studies from basic biochemistry to clinical biomarker discovery.

Changes of the plasma metabolome during an oral glucose tolerance test: is there more than glucose to look at?

The oral glucose tolerance test (oGTT) is a common tool to provoke a metabolic challenge for scientific purposes, as well as for diagnostic reasons, to monitor the kinetics of glucose and insulin. Here, we aimed to follow the variety of physiological changes of the whole metabolic pattern in plasma during an oGTT in healthy subjects in a nontargeted reversed-phase ultra performance liquid chromatography coupled to electrospray ionization quadrupole time of flight mass spectrometric metabolomics approach. We detected 11,500 metabolite ion masses/individual. Applying multivariate data analysis, four major groups of metabolites have been detected as the most discriminating oGTT biomarkers: free fatty acids (FFA), acylcarnitines, bile acids, and lysophosphatidylcholines. We found in detail 1) a strong decrease of all saturated and monounsaturated FFA studied during the oGTT; 2) a significant faster decline of palmitoleate (C16:1) and oleate (C18:1) FFA levels than their saturated counterparts; 3) a strong relative increase of polyunsaturated fatty acids in the fatty acid pattern at 120 min; and 4) a clear decrease in plasma C10:0, C12:0, and C14:1 acylcarnitine levels. These data reflect the switch from beta-oxidation to glycolysis and fat storage during the oGTT. Moreover, the bile acids glycocholic acid, glycochenodeoxycholic acid, and glycodeoxycholic acid were highly discriminative, showing a biphasic kinetic with a maximum of a 4.5- to 6-fold increase at 30 min after glucose ingestion, a significant decrease over the next 60 min followed by an increase until the end of the oGTT. Lysophosphatidylcholines were also increased significantly. The findings of our metabolomics study reveal detailed insights in the complex physiological regulation of the metabolism during an oGTT offering novel perspectives of this widely used procedure.

RPLC-ion-trap-FTMS method for lipid profiling of plasma : method validation and application to p53 mutant mouse model

A reversed-phase liquid chromatography-linear ion trap-Fourier transform ion cyclotron resonance-mass spectrometric method was developed for the profiling of lipids in human and mouse plasma. With the use of a fused-core C 8 column and a binary gradient, more than 160 lipids belonging to eight different classes were detected in a single LC-MS run. The method was fully validated and the analytical characteristics such as linearity ( R (2), 0.994-1.000), limit of detection (0.08-1.28 microg/mL plasma), repeatability (RSD, 2.7-7.9%) and intermediate precision (RSD, 2.7-15.6%) were satisfactory. The method was successfully applied to p53 mutant mice plasma for studying some phenotypic effects of p53 expression.

Preanalytical Aspects and Sample Quality Assessment in Metabolomics Studies of Human Blood

BACKGROUND Metabolomics is a powerful tool that is increasingly used in clinical research. Although excellent sample quality is essential, it can easily be compromised by undetected preanalytical errors. We set out to identify critical preanalytical steps and biomarkers that reflect preanalytical inaccuracies. METHODS We systematically investigated the effects of preanalytical variables (blood collection tubes, hemolysis, temperature and time before further processing, and number of freeze-thaw cycles) on metabolomics studies of clinical blood and plasma samples using a nontargeted LC-MS approach. RESULTS Serum and heparinate blood collection tubes led to chemical noise in the mass spectra. Distinct, significant changes of 64 features in the EDTA-plasma metabolome were detected when blood was exposed to room temperature for 2, 4, 8, and 24 h. The resulting pattern was characterized by increases in hypoxanthine and sphingosine 1-phosphate (800% and 380%, respectively, at 2 h). In contrast, the plasma metabolome was stable for up to 4 h when EDTA blood samples were immediately placed in iced water. Hemolysis also caused numerous changes in the metabolic profile. Unexpectedly, up to 4 freeze-thaw cycles only slightly changed the EDTA-plasma metabolome, but increased the individual variability. CONCLUSIONS Nontargeted metabolomics investigations led to the following recommendations for the preanalytical phase: test the blood collection tubes, avoid hemolysis, place whole blood immediately in ice water, use EDTA plasma, and preferably use nonrefrozen biobank samples. To exclude outliers due to preanalytical errors, inspect the biomarker signal intensities reflecting systematic as well as accidental and preanalytical inaccuracies before processing the bioinformatics data.

Effect of traditional Chinese medicine berberine on type 2 diabetes based on comprehensive metabonomics

A comprehensive metabonomic method, in combination with fingerprint analysis and target analysis, was performed to reveal potential mechanisms of berberine action in the treatment of patients with type 2 diabetes and dyslipidemia. Serum samples of 60 patients before and after treatment with either berberine or placebo were collected. Ultra-performance liquid chromatography and quadrupole time-of-flight tandem mass spectrometry (UPLC Q-TOF MS) coupled with pattern recognition analysis were used to identify changes in global serum metabolites. Compared with placebo, patients before and after berberine treatment could be separated into distinct clusters as displayed by the orthogonal signal correction filtered partial least-squares discriminant analysis (OSC-PLS-DA) score plot, which indicated changes in circulating metabolites after berberine treatment. Among them, free fatty acids changed markedly. These were further quantified by UPLC combined with single quadrupole mass spectrometry (UPLC SQ MS). There was a highly significant decrease in the concentrations of 13 fatty acids following berberine administration. 10 fatty acids also differed statistically from placebo. These results suggest that berberine might play a pivotal role in the treatment of type 2 diabetes through down-regulating the high level of free fatty acids and that comprehensive metabonomic measurements are potentially very useful for studying the mechanisms of action of traditional Chinese medicines.

Quality and safety of Chinese herbal medicines guided by a systems biology perspective

Chinese herbal medicines, often referred as Chinese materia medica (CMM), are comprised of a complex multicomponent nature. The activities are aimed at the system level via interactions with a multitude of targets in the human body. This review aims at the toxicity aspects of CMM and its preparations at the different steps of production; harvesting, processing and the final formulation. The historic perspective and todays issues of the safety of CMM are introduced briefly, followed by the descriptions of the toxic CMM in the current Chinese Pharmacopoeia (2005). Subsequently, several aspects of safety are illustrated using a typical example of a toxic CMM, Aconitum roots, and some recent findings of our own research are included to illustrate that proper processing and multi-herbs formulation can reduce the level of toxic components. This also explains that in CMM, some herbs, such as Aconitum, Ephedra species are never used as single herb for intervention and that aconite is only used when it is processed and in combination with specific matched other herbs. The formulation principle of multi-herbs intervention strategy is a systems approach for the treatment and prevention of disease. In this light, the role of systems toxicology in the safety and quality of Chinese herbal medicine is proposed as a promising method. Moreover the principles of practiced-based and evidence-based research are discussed from a symbiotic perspective.

Simultaneous extraction of metabolome and lipidome with methyl tert-butyl ether from a single small tissue sample for ultra-high performance liquid chromatography/mass spectrometry

A common challenge for scientists working with animal tissue or human biopsy samples is the limitation of material and consequently, the difficulty to perform comprehensive metabolic profiling within one experiment. Here, we present a novel approach to simultaneously perform targeted and non-targeted metabolomics as well as lipidomics from one small piece of liver or muscle tissue by ultra-high performance liquid chromatography/mass spectrometry (UHPLC/MS) following a methyl tert-butyl ether (MTBE)-based extraction. Equal relative amounts of the resulting polar and non-polar fractions were pooled, evaporated and reconstituted in the appropriate solvent for UHPLC/MS analysis. This mix was comparable or superior in yield and reproducibility to a standard 80% methanol extraction for the profiling of polar and lipophilic metabolites (free carnitine, acylcarnitines and FFA). The mix was also suitable for non-targeted metabolomics, an easy measure to increase the metabolite coverage by 30% relative to using the polar fraction alone. Lipidomics was performed from an aliquot of the non-polar fraction. This novel strategy could successfully be applied to one mouse soleus muscle with a dry weight of merely 2.5 mg. By enabling a simultaneous profiling of lipids and metabolites with mixed polarity while saving material for molecular, biochemical or histological analyses, our approach may open up new perspectives toward a comprehensive investigation of small, valuable tissue samples.