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采用(13)C、(15)N 和(34)S 同位素标记以及高分辨质谱技术,对极性和亲脂性代谢物进行元素式注释。

Elemental formula annotation of polar and lipophilic metabolites using (13) C, (15) N and (34) S isotope labelling, in combination with high-resolution mass spectrometry.

机构信息

Max Planck Institute of Molecular Plant Physiology, Am Mühlenberg 1, 14476 Potsdam, Germany.

出版信息

Plant J. 2011 Oct;68(2):364-76. doi: 10.1111/j.1365-313X.2011.04682.x. Epub 2011 Jul 26.

Abstract

The unbiased and comprehensive analysis of metabolites in any organism presents a major challenge if proper peak annotation and unambiguous assignment of the biological origin of the peaks are required. Here we provide a comprehensive multi-isotope labelling-based strategy using fully labelled (13) C, (15) N and (34) S plant tissues, in combination with a fractionated metabolite extraction protocol. The extraction procedure allows for the simultaneous extraction of polar, semi-polar and hydrophobic metabolites, as well as for the extraction of proteins and starch. After labelling and extraction, the metabolites and lipids were analysed using a high-resolution mass spectrometer providing accurate MS and all-ion fragmentation data, providing an unambiguous readout for every detectable isotope-labelled peak. The isotope labelling assisted peak annotation process employed can be applied in either an automated database-dependent or a database-independent analysis of the plant polar metabolome and lipidome. As a proof of concept, the developed methods and technologies were applied and validated using Arabidopsis thaliana leaf and root extracts. Along with a large repository of assigned elemental compositions, which is provided, we show, using selected examples, the accuracy and reliability of the developed workflow.

摘要

如果需要对代谢物进行适当的峰注释,并明确分配峰的生物学来源,那么对任何生物体中的代谢物进行无偏且全面的分析都是一项重大挑战。在这里,我们提供了一种全面的基于多同位素标记的策略,该策略使用完全标记的(13)C、(15)N 和(34)S 植物组织,并结合了分级代谢物提取方案。该提取程序允许同时提取极性、半极性和疏水性代谢物,以及蛋白质和淀粉。标记和提取后,使用高分辨率质谱仪分析代谢物和脂质,提供准确的 MS 和全离子碎片化数据,为每个可检测的同位素标记峰提供明确的读数。所采用的同位素标记辅助峰注释过程可应用于基于数据库的或独立于数据库的植物极性代谢组学和脂质组学分析。作为概念验证,该方法和技术已应用于拟南芥叶片和根提取物,并进行了验证。随着提供的元素组成的大型存储库,我们使用选定的示例展示了所开发工作流程的准确性和可靠性。

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