Development and application of analytical methods for metabolic cell analysis under patho-physiological conditions

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The aim of the core project is the development and application of novel analytical and statistical methods for the comprehensive characterization of the tumor and immune cell metabolome and proteome and their interactions. The core unit provides the other projects with quantitative metabolic and proteomic profiling and fingerprinting methods based on multidimensional NMR, hyphenated mass spectrometry (MS), and state-of-the-art statistical bioinformatics.In the last funding period we performed more than 3800 analyses to support the projects in the KFO. With respect to method development an analytical method for accurate quantification of tryptophan metabolites by LC-MS and an assay to determine MTAP activity was developed. Furthermore, a LC-QTOFMS platform was established and used in a comparative study on metabolic differences between various human cancer and primary cells. With KFO partners we studied the immune modulation by Diclofenac in a murine glioma model and the effect of Diclofenac on Myc-expression and glucose metabolism. For the analysis of NMR data the newly developed MetaboQuant approach allows accurate metabolite quantification from complex biological matrices. One important aspect in context of subsequent data evaluation is the use of optimal statistical data analysis methods, employing both unsupervised and supervised techniques, several of which were implemented and applied, including among others Affinity Propagation and Random Forests. Furthermore, state-of-the-art methods for NMR and comprehensive two-dimensional gas chromatography based metabolomics were summarized in two recent reviews and three book chapters.Established methods include the quantitative analysis of intermediates of glycolysis and TCA cycle, amino acids, tryptophan metabolites, and intermediates of the methionine and polyamine metabolism as well as metabolic fingerprinting by NMR and MS. Recently established proteomic techniques involve label-free quantification of thousands of proteins in parallel (SWATH-MS). Novel methods to be developed in the second funding period regard the study of alterations in cancer lipid metabolism, including the determination of arachidonic acid metabolites and the analysis of carbon flux from glucose and glutamine into fatty acids and other metabolites. To that end, current NMR and MS methods will be further developed including among others the adaptation of high-resolution non-uniform sampling of NMR spectra (NUS) for carbon flux analysis. Further, we will establish a method for the enantioselective separation and mass spectrometric determination of D- and L-2-hydroxyglutaric acid. The former is found in cancers such as gliomas and hematologic malignancies that harbor mutations in isocitrate dehydrogenase 1 and 2. With respect to the analysis of NMR-based fingerprinting data we will concentrate on the systematic assessment of existing and the development of novel spectra alignment techniques.