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用于基于气相色谱-质谱联用(GC-MS)的代谢物谱分析实验定量分析的TagFinder

TagFinder for the quantitative analysis of gas chromatography--mass spectrometry (GC-MS)-based metabolite profiling experiments.

作者信息

Luedemann Alexander, Strassburg Katrin, Erban Alexander, Kopka Joachim

机构信息

Department Prof. L. Willmitzer, Max Planck Institute of Molecular Plant Physiology, Am Muehlenberg 1, D-14476 Potsdam-Golm, Germany.

出版信息

Bioinformatics. 2008 Mar 1;24(5):732-7. doi: 10.1093/bioinformatics/btn023. Epub 2008 Jan 19.

Abstract

MOTIVATION

Typical GC-MS-based metabolite profiling experiments may comprise hundreds of chromatogram files, which each contain up to 1000 mass spectral tags (MSTs). MSTs are the characteristic patterns of approximately 25-250 fragment ions and respective isotopomers, which are generated after gas chromatography (GC) by electron impact ionization (EI) of the separated chemical molecules. These fragment ions are subsequently detected by time-of-flight (TOF) mass spectrometry (MS). MSTs of profiling experiments are typically reported as a list of ions, which are characterized by mass, chromatographic retention index (RI) or retention time (RT), and arbitrary abundance. The first two parameters allow the identification, the later the quantification of the represented chemical compounds. Many software tools have been reported for the pre-processing, the so-called curve resolution and deconvolution, of GC-(EI-TOF)-MS files. Pre-processing tools generate numerical data matrices, which contain all aligned MSTs and samples of an experiment. This process, however, is error prone mainly due to (i) the imprecise RI or RT alignment of MSTs and (ii) the high complexity of biological samples. This complexity causes co-elution of compounds and as a consequence non-selective, in other words impure MSTs. The selection and validation of optimal fragment ions for the specific and selective quantification of simultaneously eluting compounds is, therefore, mandatory. Currently validation is performed in most laboratories under human supervision. So far no software tool supports the non-targeted and user-independent quality assessment of the data matrices prior to statistical analysis. TagFinder may fill this gap.

STRATEGY

TagFinder facilitates the analysis of all fragment ions, which are observed in GC-(EI-TOF)-MS profiling experiments. The non-targeted approach allows the discovery of novel and unexpected compounds. In addition, mass isotopomer resolution is maintained by TagFinder processing. This feature is essential for metabolic flux analyses and highly useful, but not required for metabolite profiling. Whenever possible, TagFinder gives precedence to chemical means of standardization, for example, the use of internal reference compounds for retention time calibration or quantitative standardization. In addition, external standardization is supported for both compound identification and calibration. The workflow of TagFinder comprises, (i) the import of fragment ion data, namely mass, time and arbitrary abundance (intensity), from a chromatography file interchange format or from peak lists provided by other chromatogram pre-processing software, (ii) the annotation of sample information and grouping of samples into classes, (iii) the RI calculation, (iv) the binning of observed fragment ions of equal mass from different chromatograms into RI windows, (v) the combination of these bins, so-called mass tags, into time groups of co-eluting fragment ions, (vi) the test of time groups for intensity correlated mass tags, (vii) the data matrix generation and (viii) the extraction of selective mass tags supported by compound identification. Thus, TagFinder supports both non-targeted fingerprinting analyses and metabolite targeted profiling.

AVAILABILITY

Exemplary TagFinder workspaces and test data sets are made available upon request to the contact authors. TagFinder is made freely available for academic use from http://www-en.mpimp-golm.mpg.de/03-research/researchGroups/01-dept1/Root_Metabolism/smp/TagFinder/index.html.

摘要

动机

基于气相色谱 - 质谱联用(GC - MS)的典型代谢物谱分析实验可能包含数百个色谱图文件,每个文件包含多达1000个质谱标签(MST)。质谱标签是大约25 - 250个碎片离子及各自同位素异构体的特征模式,这些是在气相色谱(GC)之后通过对分离出的化学分子进行电子轰击电离(EI)产生的。随后这些碎片离子通过飞行时间(TOF)质谱(MS)进行检测。谱分析实验的质谱标签通常报告为离子列表,其特征在于质量、色谱保留指数(RI)或保留时间(RT)以及任意丰度。前两个参数用于化合物的鉴定,后者用于所代表化合物的定量。已经报道了许多用于气相色谱 - (电子轰击电离 - 飞行时间) - 质谱(GC - (EI - TOF) - MS)文件预处理(即所谓的曲线分辨率和去卷积)的软件工具。预处理工具生成数值数据矩阵,其中包含实验中所有对齐的质谱标签和样本。然而,这个过程容易出错,主要原因是(i)质谱标签的保留指数或保留时间对齐不准确,以及(ii)生物样品的高度复杂性。这种复杂性导致化合物共洗脱,结果产生非选择性的,换句话说不纯的质谱标签。因此,对于同时洗脱的化合物进行特异性和选择性定量时,选择和验证最佳碎片离子是必不可少的。目前,大多数实验室在人工监督下进行验证。到目前为止,尚无软件工具支持在统计分析之前对数据矩阵进行非靶向且用户独立的质量评估。TagFinder可能填补这一空白。

策略

TagFinder有助于分析在气相色谱 - (电子轰击电离 - 飞行时间) - 质谱(GC - (EI - TOF) - MS)谱分析实验中观察到的所有碎片离子。非靶向方法允许发现新的和意想不到的化合物。此外,可以通过TagFinder处理保持质量同位素异构体分辨率。此功能对于代谢通量分析至关重要且非常有用,但对于代谢物谱分析并非必需。只要有可能,TagFinder优先采用化学标准化方法,例如,使用内标化合物进行保留时间校准或定量标准化。此外,支持外部标准化用于化合物鉴定和校准。TagFinder的工作流程包括:(i)从色谱文件交换格式或其他色谱图预处理软件提供的峰列表中导入碎片离子数据,即质量、时间和任意丰度(强度);(ii)注释样品信息并将样品分组为类别;(iii)计算保留指数;(iv)将来自不同色谱图的等质量观察到的碎片离子归入保留指数窗口;(v)将这些箱(所谓的质量标签)组合成共洗脱碎片离子的时间组;(vi)测试时间组中强度相关的质量标签;(vii)生成数据矩阵;(viii)提取由化合物鉴定支持的选择性质量标签。因此,TagFinder支持非靶向指纹分析和代谢物靶向谱分析。

可用性

可根据要求向联系作者提供示例性的TagFinder工作区和测试数据集。TagFinder可从http://www-en.mpimp-golm.mpg.de/03-research/researchGroups/01-dept1/Root_Metabolism/smp/TagFinder/index.html免费获取用于学术用途。

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