使用稳定同位素模式进行非靶向质量同位素组分析以识别代谢变化。

Non-Targeted Mass Isotopolome Analysis Using Stable Isotope Patterns to Identify Metabolic Changes.

作者信息

Dudek Christian-Alexander, Schlicker Lisa, Hiller Karsten

机构信息

Department of Bioinformatics and Biochemistry, Braunschweig Integrated Centre of Systems Biology (BRICS), Technische Universität Braunschweig, Braunschweig, Germany.

Computational Biology of Infection Research, Helmholtz Centre for Infection Research, Braunschweig, Germany.

出版信息

Methods Mol Biol. 2020;2088:17-32. doi: 10.1007/978-1-0716-0159-4_2.

DOI:10.1007/978-1-0716-0159-4_2

PMID:31893368

Abstract

Gas chromatography coupled with mass spectrometry can provide an extensive overview of the metabolic state of a biological system. Analysis of raw mass spectrometry data requires powerful data processing software to generate interpretable results. Here we describe a data processing workflow to generate metabolite levels, mass isotopomer distribution, similarity and variability analysis of metabolites in a nontargeted manner, using stable isotope labeling. Using our data analysis software, no bioinformatic or programming background is needed to generate results from raw mass spectrometry data.

摘要

气相色谱-质谱联用技术能够全面概述生物系统的代谢状态。对原始质谱数据进行分析需要功能强大的数据处理软件才能生成可解读的结果。在此，我们描述了一种数据处理流程，该流程使用稳定同位素标记，以非靶向方式生成代谢物水平、质量同位素异构体分布、代谢物相似性和变异性分析结果。使用我们的数据分析软件，无需生物信息学或编程背景知识，就能从原始质谱数据中生成结果。