多批次肝衰竭患者呼出气体的电喷雾萃取电离质谱检测及代谢组学数据分析

采用高分辨电喷雾萃取电离质谱(EESI-MS)技术对肝衰竭患者和健康志愿者呼出气体样本进行快速检测, 结合多块偏最小二乘分析(MB-PLS)方法, 对多批次获取的呼出气体代谢数据进行统计建模分析, 并与传统的PLS方法进行比较. 结果表明, MB-PLS方法能有效消除批次差异对统计建模的影响. 此外, 利用MB-PLS模型变量VIP值对变量进行筛选, 可降低数据的冗余, 消除无关变量对模型的影响, 从而有效提高了模型的性能.     

Liquid chromatography–mass spectrometry based global metabolite profiling: A review

Untargeted, global metabolite profiling (often described as metabonomics or metabolomics) represents an expanding research topic and is, potentially, a major pillar for systems biology studies. To obtain holistic metabolic profiles from complex samples, such as biological fluids or tissue extracts, requires powerful, high resolution and information-rich analytical methods and for this spectroscopic technologies are generally used. Mass spectrometry, coupled to liquid chromatography (LC–MS), is increasingly being used for such investigations as a result of the significant advances in both technologies over the past decade. Here we try to critically review the topic of LC–MS-based global metabolic profiling and describe and compare the results offered by different analytical strategies and technologies. This review highlights the current challenges, limitations and opportunities of the current methodology.     

NMR and pattern recognition methods in metabolomics: From data acquisition to biomarker discovery: A review

Metabolomics is the discipline where endogenous and exogenous metabolites are assessed, identified and quantified in different biological samples. Metabolites are crucial components of biological system and highly informative about its functional state, due to their closeness to functional endpoints and to the organism's phenotypes. Nuclear Magnetic Resonance (NMR) spectroscopy, next to Mass Spectrometry (MS), is one of the main metabolomics analytical platforms. The technological developments in the field of NMR spectroscopy have enabled the identification and quantitative measurement of the many metabolites in a single sample of biofluids in a non-targeted and non-destructive manner. Combination of NMR spectra of biofluids and pattern recognition methods has driven forward the application of metabolomics in the field of biomarker discovery. The importance of metabolomics in diagnostics, e.g. in identifying biomarkers or defining pathological status, has been growing exponentially as evidenced by the number of published papers. In this review, we describe the developments in data acquisition and multivariate analysis of NMR-based metabolomics data, with particular emphasis on the metabolomics of Cerebrospinal Fluid (CSF) and biomarker discovery in Multiple Sclerosis (MScl).     

Nuclear magnetic resonance-based metabolomics for prediction of gastric damage induced by indomethacin in rats

Non-steroidal anti-inflammatory drugs (NSAIDs) have side effects including gastric erosions, ulceration and bleeding. In this study, pattern recognition analysis of the ¹H-nuclear magnetic resonance (NMR) spectra of urine was performed to develop surrogate biomarkers related to the gastrointestinal (GI) damage induced by indomethacin in rats. Urine was collected for 5 h after oral administration of indomethacin (25 mg kg⁻¹) or co-administration with cimetidine (100 mg kg⁻¹), which protects against GI damage. The ¹H-NMR urine spectra were divided into spectral bins (0.04 ppm) for global profiling, and 36 endogenous metabolites were assigned for targeted profiling. The level of gastric damage in each animal was also determined. Indomethacin caused severe gastric damage; however, indomethacin administered with cimetidine did not. Simultaneously, the patterns of changes in their endogenous metabolites were different. Multivariate data analyses were carried out to recognize the spectral pattern of endogenous metabolites related to indomethacin using partial least square-discrimination analysis. In targeted profiling, a few endogenous metabolites, 2-oxoglutarate, acetate, taurine and hippurate, were selected as putative biomarkers for the gastric damage induced by indomethacin. These metabolites changed depending on the degree of GI damage, although the same dose of indomethacin (10 mg kg⁻¹) was administered to rats. The results of global and targeted profiling suggest that the gastric damage induced by NSAIDs can be screened in the preclinical stage of drug development using a NMR based metabolomics approach.     

De novo analysis of electron impact mass spectra using fragmentation trees

The automated fragmentation analysis of high resolution EI mass spectra based on a fragmentation tree algorithm is introduced. Fragmentation trees are constructed from EI spectra by automated signal extraction and evaluation. These trees explain relevant fragmentation reactions and assign molecular formulas to fragments. The method enables the identification of the molecular ion and the molecular formula of a metabolite if the molecular ion is present in the spectrum. These identifications are independent of existing library knowledge and, thus, support assignment and structural elucidation of unknown compounds. The method works even if the molecular ion is of very low abundance or hidden under contaminants with higher masses. We apply the algorithm to a selection of 50 derivatized and underivatized metabolites and demonstrate that in 78% of cases the molecular ion can be correctly assigned. The automatically constructed fragmentation trees correspond very well to published mechanisms and allow the assignment of specific relevant fragments and fragmentation pathways even in the most complex EI-spectra in our dataset. This method will be very helpful in the automated analysis of metabolites that are not included in common libraries and it thus has the potential to support the explorative character of metabolomics studies.     

Metabolic fingerprinting of high-fat plasma samples processed by centrifugation- and filtration-based protein precipitation delineates significant differences in metabolite information coverage

Metabolomics and metabolic fingerprinting are being extensively employed for improved understanding of biological changes induced by endogenous or exogenous factors. Blood serum or plasma samples are often employed for metabolomics studies. Plasma protein precipitation (PPP) is currently performed in most laboratories before LC–MS analysis. However, the impact of fat content in plasma samples on metabolite coverage has not previously been investigated. Here, we have studied whether PPP procedures influence coverage of plasma metabolites from high-fat plasma samples. An optimized UPLC-QTOF/MS metabolic fingerprinting approach and multivariate modeling (PCA and OPLS-DA) were utilized for finding characteristic metabolite changes induced by two PPP procedures; centrifugation and filtration. We used 12-h fasting samples and postprandial samples collected at 2 h after a standardized high-fat protein-rich meal in obese non-diabetic subjects recruited in a dietary intervention. The two PPP procedures as well as external and internal standards (ISs) were used to track errors in response normalization and quantification. Remarkably and sometimes uniquely, the fPPP, but not the cPPP approach, recovered not only high molecular weight (HMW) lipophilic metabolites, but also small molecular weight (SMW) relatively polar metabolites. Characteristic SMW markers of postprandial samples were aromatic and branched-chain amino acids that were elevated (p < 0.001) as a consequence of the protein challenge. In contrast, some HMW lipophilic species, e.g. acylcarnitines, were moderately lower (p < 0.001) in postprandial samples. LysoPCs were largely unaffected. In conclusion, the fPPP procedure is recommended for processing high-fat plasma samples in metabolomics studies. While method improvements presented here were clear, use of several ISs revealed substantial challenges to untargeted metabolomics due to large and variable matrix effects.     

MS-IAS:集成的质谱代谢组学数据分析系统

针对代谢组学研究中的数据处理问题,本研究建立了基于质谱的数据分析系统MS-IAS(Mass spectrometry based integrated analysis system).此系统集成了特征选择、聚类、分类等多种方法,用以处理质谱数据,具有多种统计分析方法能对所选的特征变量进行比较,以发现与所研究问题相关的潜在生物标志物.MS-IAS支持数据与多种算法结果可图形化显示,有助于对数据的解释与分析.以肝病患者的质谱代谢组数据为例,展示MS-IAS的功能,两种特征选择算法从数据集中筛选出了40个对肝病具有区分能力的特征变量,展示了MS-IAS成为代谢组学研究中的通用质谱数据分析系统的潜力.     

Dynamic Metabolic Profiling of Urine From Type 2 Diabetic KK-Ay Mice Treated with Repaglinide by GC-MS

Repaglinide is a short-acting insulin secretagogue, commonly used for the treatment of type 2 diabetes. In this paper, metabolomics were first applied to research of dynamic urine metabolic profiling and biomarkers of type 2 diabetic KK-A^y mice treated with repaglinide based on GC-MS. Twenty diabetic KK-A^y mice were randomly assigned to four groups and fed with repaglinide for 6, 9, 12, and 14 weeks, respectively. Five C57BL/6 J mice were used as the healthy control group and fed with water as contrast. The PCA scores plot of the identified 41 metabolites showed that as treating time went on, the diabetic groups got closer to the healthy group. Furthermore, five marker metabolites, d-Glucose, d-Galactose, 1,5-Anhydro-d-glucitol, myo-inositol and tartaric acid were screened out, which have similar change footprints of the whole metabolic profiles. The results demonstrated that repaglinide not only regulates the sugars and polyalcohol but also the organic acid in the organism. This work has illustrated the potential of metabolomics to disease diagnosis, pharmacology, and pharmacodynamics research.     

Targeted Metabolomics Based on LC-MS/MS Revealing Alteration of Bile Acids in Male Migraine Patients

Migraine is an episodic neurological disorder and the second most disabling disease with unclear pathogenesis. Since dietary adjustment and probiotics supplement can improve the symptoms of migraine, the intestinal flora metabolites of bile acids(BAs) attract attentions in this work. 21 BAs, including cholic acid(CA), chenodeoxycholic acid(CDCA), deoxycholic acid (DCA), lithocholic acid(LCA), ursodeoxycholic acid(UDCA), hyocholic acid(HCA), hyodeoxycholic acid(HDCA) and their glycine- and taurine-conjugated species, were compared in serum of migraine patients and healthy controls using liquid chromatography-tandem mass spectrometry(LC-MS/MS), which is the first study about the correlation between BAs and migraine. Two secondary BAs, DCA and LCA as well as their glycine- and taurine-conjugated forms, were demonstrated with significant difference between male patients and male controls, while no obvious difference was found in the two female groups. The result indicated that the variation of BAs might be gender-related when referred to migraine, which would emphasize the importance of gender-stratified analysis for the disease with varying morbidity in male and female. Five differential metabolites may serve as potential serum biomarkers for the male migraine patients, providing a new sight for the understanding and biomarker exploring of the migraine in male.     

GC/MS-based metabolomics reveals fatty acid biosynthesis and cholesterol metabolism in cell lines infected with influenza A virus

Metabolomics is the downstream of systems biology and has drawn significant interest for studying the metabolic networks from cells to organisms. To profile the metabolites in two different cell lines (A549 and AGS) infected with influenza A virus, gas chromatography coupled with mass spectrometry (GC/MS) was employed. Some differentiating metabolites in the cell lines were tentatively identified using reference library, interpreted and visualized by applying principal components analysis (PCA) and cluster heat map. Consequently, metabolic flux profiling allowed the differentiation of fatty acid biosynthesis and cholesterol metabolism during viral replication in the cell lines. The change in fatty acid turnover was also observed. Metabolomics investigation also revealed the different responses between A549 and AGS cell lines to the virus infection. From the pattern recognition results, AGS cell line might be more susceptible to influenza A virus. Regarding the fact that AGS is a poorly differentiated gastric adenocarcinoma cell line whereas A549 is a relatively differentiated lung tumor one, it is speculated that viral replication might be associated with the cell differentiations.