| Metabonomics or metabolomics is the quantitative measurement of the multiparametric time-related metabolic responses of a complex (multicellular) system to a pathophysiological intervention or genetic modification. Thus metabonomics seeks to assess the global system level homeostatic and pathological responses to interventions or stressors. Metabolome is the result of whole expression of proteome, transcriptome, genome which reflect the biochemical status of tissues directly. It is very important for the illustration of the complicated life systems because of the sensitive response of the changes of the philological and pathological status of the life. The main characteristics of metabonomics are the high-throughput experiment and calculation. Metabonomics has become an important hotspot for the research of disease and healthy in the world now. To research the complicated disease including metabolic diseases (e.g., obesity) with metabonomic study is very significant for the early-stage diagnose and prevention of disease and drug intervention. However, metabonomics need analytical methods with high throughout, sensitivity and precision for supporting. To analysis and identification the whole metabolites in the samples is the most important stage for metabonomic study and the most important feature leading to non-producible result because of which is complicated and difficult to control. Different from the convenient"omics"analytical method, the size, number, group, volatility, electrified property, electrified transfer ratio, polarity and other physiochemical parameter of the objects for metabonomic study are different each other. It's necessary for us to analysis the samples all round. But the convenient analytical method can not satisfy the need because of the following drawbacks of traditional analytical methods: 1. complicated sample pretreatment, 2. too many procedures and undivided method, 3. dissatisfied producibility, 4. low throughput, 5. no coordinated effect. Direct infusion analysis approaches using NMR and FT-CIRMS have been developed for metabolome profiling. Although the infusion techniques enable the instantaneous acquisition of metabolic snapshots, there are still some important drawbacks. In NMR, sufficient amounts of samples must be prepared, and the quantification is difficult. Infusion techniques using MS lack accuracy and precision for quantification due to ion suppression effect and often cannot separate a number of isomers. However, chromatographic method is the most usable and effective separation and analytical tools. The hyphenation of chromatographic method with mass spectrometry can meet requires of separation and analysis for metabonomic study. Therefore, the development of quantitative and high-resolution analytical methods remains one of the most demanding challenges. In this paper, a feasible pretreatment methods and GC/MS, LC/MS, pCEC analytical methods for metabonomic analysis of biological samples were established. Identification of amount of chromatographic peaks and analysis of trend of differential metabolites were dissolved with the metabonomic analysis and the pattern recognition techniques such as PCA, PLS-DA and OPLS-DA. Metabonomic profiling with good reproducibility, stability and remarkable characteristics were obtained with the established method of this dissertation based on the detection of the urine from obesity rats induced with high energy diet.It is essential to pre-treat biological samples e.g. serum, urine, and tissue prior to pCEC analysis because of the capillary column is extremely readily contaminated by matrix materials. A simple, common method is organic solvent precipitation. However, it may cause considerable sample dilution and lose a variety of useful information due to the co-precipitation of proteins. Previous studies indicated that GC/MS analysis with ECF derivatization is able to identify a wide range of in vivo metabolites involving organic acids, amines, amino acids, fatty acids, and amino-alcohols. In addition, ECF derivatization method improved the UV adsorption of such compounds as amino acids, amines etc., and changed their polarity, leading to a higher sensitivity and better separation. Therein, we proposed ECF-derivatized pCEC methodology. In this dissertation, sample pretreatment method was confirmed with some experiments. Analytical conditions for the metabonomic analysis of GC/MS, LC/MS and pCEC were investigated in details. The optimized analytical methods were used for the analysis of urine from obesity rats.The pretreatment method for the biofluid was established successfully. Urine was centrifuged at 14000rpm to separate protein, and was pended for LC/MS analysis. The filtered urine was then derivatized with ethyl chloroformate (ECF) pending GC/MS and pCEC analysis.Analytical methods of GC/MS, LC/MS and pCEC for metabonomic study were established with condition optimization and methodology examination. High energy diet (HED)-induced obesity animal model was utilized to test the potential application of the established method for metabonomic studies. We analyzed urine samples obtained from healthy (n=6) or HED-treated (n=7) rats at pre-dose and the 6th week after administration with HED, individually. Using optimized GC/MS, LC/MS, pCEC analysis protocol, we identified about 200~250, 100 and 100 different urine metabolites, respectively. In GC/MS, more than 80 metabolites are confirmed via spectra database and standard compounds. In LC/MS, more than 20 metabolites are confirmed via spectra database and standard compounds. While in pCEC, 8 compounds were confirmed via standard compounds.Analysis of urine samples from two groups (the healthy control v.s. HED- treated rat) at pre-dose and the 6th week with established method were illustrated. Visual examination of the GC/MS and pCEC displayed a clear difference with each other, while LC/MS could not obtain a clear difference with visual examination. The analytical data were processed via custom scripts in Matlab 7.0 prior to multivariate analysis such as PCA and PLS-DA. PCA scores plot of analytical data describes the general differences between two different groups at the end point of the study whereas little variation is observed at pre-dose. The mechanism of HED-treated pathological changes may be elucidated with the up- or down-regulated metabolic pathways. The dominant metabolites obtained from VIP values of PLS-DA were the differential metabolites between healthy control and HED-induced rats.The application of three established chromatographic methods in the metabonomic analysis was compared also. The metabolites in vivo were complicated. To investigate the metabolites of each sample, tissue or cells were therotically applicable. However, no analytical technique can anlysis the whole metabolites simultaneously till now. To combine the different analytical methods in metabonomic analysis can dissolve the problem in some degree. The determined metabolites were different due to the different method and therefore the obtained information was different also. More information could be obtained from the metabonomic analysis of one disease using different methodology and the in vivo changes could be elucidated better as well.
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