期刊
CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS
卷 86, 期 2, 页码 189-197出版社
ELSEVIER SCIENCE BV
DOI: 10.1016/j.chemolab.2006.06.004
关键词
metabolic fingerprinting; Arabidopsis thaliana; LC-MS; data treatment; ANOVA; PCA; HCA
A metabolomic strategy based on a rapid high performance liquid chromatography (LC) method coupled with a high resolution time-of-flight (TOF) mass spectrometer (MS) has been developed to detect metabolomic modifications occurring in Arabidopsis thaliana upon stress induction. The method was evaluated for its potential of fast discrimination between stressed (wounding by forceps) versus control Arabidopsis specimens, based on a metabolomic fingerprinting survey. Multivariate analysis was applied to handle the large amount of data generated and extract relevant information. Signal variations were filtered with an ANOVA test to select discriminant detected analytes between plant sets. Selected ions were then processed through a data reduction procedure applied to the chromatographic information generating Total Mass Spectra (TMS) and further investigated by multivariate analysis. Principal Components Analysis (PCA) and Hierarchical Cluster Analysis (HCA) on principal coordinates were combined for data treatment. PCA and HCA demonstrate a clear clusterisation of plant specimens selecting the highest discriminating ions given by the complete data analysis and leading to the specific identification of discrete induced metabolites or spiked compounds. Putative stress induced compounds issued from this screening procedure were analysed using a conventional chromatographic gradient. This sequential strategy (screening-confirmation) was developed for the investigation of new low molecular mass regulators involved in plant defence signalling. (c) 2006 Elsevier B.V. All rights reserved.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据