title: A chemometric-assisted method based on gas chromatography-mass spectrometry for metabolic profiling analysis.
abstract: An automatic and efficient data analysis method for comprehensive metabolic profiling analysis is urgently required. In this study, a new chemometric-assisted method for metabolic profiling analysis (CAMMPA) was developed to discover potentially valuable metabolites automatically and efficiently. The proposed method mainly consists of three stages. First, automatic chromatographic peak detection is performed based on the total ion chromatograms of samples to extract chromatographic peaks that can be accurately quantified. Second, a novel peak-shift alignment technique based on peak detection results is implemented to resolve time-shift problems across samples. Consequently, aligned results, including aligned chromatograms, and peak area tables, among others, can be successfully obtained. Third, statistical analysis using results from unsupervised and supervised classification results, together with ANOVA and partial least square-discriminate analysis, is performed to extract potential metabolites. To demonstrate the proposed technique, a complex GC-MS metabolic profiling dataset was measured to identify potential metabolites in tobacco plants of different growth stages as well as different plant tissues after maturation. Results indicated that the efficiency of the routine metabolic profiling analysis procedure can be significantly improved and potential metabolites can be accurately identified with the aid of CAMMPA.
authors.affiliation: Zhengzhou Tobacco Research Institute of CNTC, Zhengzhou 450001, China. Electronic address: yongjie.yu@163.com.
authors.forename: Yong-Jie
authors.initials: YJ
authors.lastname: Yu
authors.affiliation: College of Pharmacy, South-Central University for Nationalities, Wuhan 430074, China.
authors.forename: Hai-Yan
authors.initials: HY
authors.lastname: Fu
authors.affiliation: Technology Center of China Tobacco Guizhou Industrial Co. Ltd., Guiyang 550009, China.
authors.forename: Li
authors.initials: L
authors.lastname: Zhang
authors.affiliation: Zhengzhou Tobacco Research Institute of CNTC, Zhengzhou 450001, China.
authors.forename: Xiao-Yu
authors.initials: XY
authors.lastname: Wang
authors.affiliation: Zhengzhou Tobacco Research Institute of CNTC, Zhengzhou 450001, China.
authors.forename: Pei-Jian
authors.initials: PJ
authors.lastname: Sun
authors.affiliation: Zhengzhou Tobacco Research Institute of CNTC, Zhengzhou 450001, China.
authors.forename: Xiao-Bing
authors.initials: XB
authors.lastname: Zhang
authors.affiliation: Zhengzhou Tobacco Research Institute of CNTC, Zhengzhou 450001, China. Electronic address: xiefuwei@sina.com.
authors.forename: Fu-Wei
authors.initials: FW
authors.lastname: Xie
mesh_terms: D008401:Gas Chromatography-Mass Spectrometry; D055432:Metabolomics / Q000295:instrumentation* / Q000379:methods*; D014026:Nicotiana / Q000737:chemistry
keywords: Automatic chromatographic peak detection; Metabolic profiling analysis; Peak-shift alignment; Plant sample