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

病理生理条件下代谢细胞分析方法的开发和应用

基本信息

批准号：
201483576
负责人：
Privatdozentin Dr. Katja Dettmer-Wilde
金额：
--
依托单位：
Institut für Funktionelle Genomik
依托单位国家：
德国
项目类别：
Clinical Research Units
财政年份：
2011
资助国家：
德国
起止时间：
2010-12-31 至 2019-12-31
项目状态：
已结题

来源：
https://gepris.dfg.de/gepris/projekt/201483576?language=en
关键词：
Development application analytical methods metabolic

项目摘要

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.

核心项目的目的是开发和应用新颖的分析和统计方法，用于肿瘤和免疫细胞代谢组和蛋白质组及其相互作用的全面表征。核心单元为其他项目提供了定量的代谢和蛋白质组学分析以及基于多维NMR，连字符质谱法（MS）和最先进的统计生物信息信息学的指纹识别方法。在上一个融资期间，我们进行了3800多个分析，以支持KFO中的项目超过3800个项目。对于方法开发，开发了一种分析方法，用于通过LC-MS准确定量色氨酸代谢产物和确定MTAP活性的测定法。此外，建立了LC-QTOFMS平台，并用于对各种人类癌和原代细胞之间代谢差异的比较研究。通过KFO伴侣，我们研究了双氯芬酸在鼠神经胶质瘤模型中的免疫调节，以及双氯芬酸对MYC表达和葡萄糖代谢的影响。为了分析NMR数据，新开发的代谢方法可从复杂的生物学基质中进行准确的代谢物定量。随后的数据评估背景下的一个重要方面是使用最佳统计数据分析方法，该方法采用了无监督和监督技术，其中几种已实施和应用，包括亲和力传播和随机森林。 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 NMR和MS的指纹识别。最近确定的蛋白质组学技术涉及并联（Swath-Ms）的数千种蛋白质的无标记定量。在第二个资金期间要开发的新方法研究了癌症脂质代谢改变的研究，包括测定金己烯酸代谢产物以及将碳通量从葡萄糖和谷氨酰胺分析为脂肪酸和其他代谢产物的分析。为此，当前的NMR和MS方法将进一步开发，包括对NMR光谱（NUS）高分辨率非均匀采样的适应进行碳通量分析。此外，我们将建立一种对对映选择性分离和质谱测定D-和L-2-羟基谷物酸的方法。前者在诸如神经胶质瘤和血液学恶性肿瘤等癌症中发现，这些疾病含有异位酸盐脱氢酶1和2的突变。对于基于NMR的指纹数据的分析，我们将集中于对现有的系统评估和新型光谱一致性技术的系统评估。