Analysis of stable isotope assisted metabolomics data acquired by GC-MS

作者：Wei Xiaoli^*; Shi Biyun; Koo Imhoi; Yin Xinmin; Lorkiewicz Pawel; Suhail Hamid; Rattan Ramandeep; Giri Shailendra; McClain Craig J; Zhang Xiang

来源：Analytica Chimica Acta, 2017, 980: 25-32.

DOI：10.1016/j.aca.2017.05.002

• IsoGC
• Stable isotope assisted metabolomics
• GC-MS
• Signature ion
• Isotopologues

Stable isotope assisted metabolomics (SIAM) measures the abundance levels of metabolites in a particular pathway using stable isotope tracers (e.g., C-13, O-18 and/or N-15). We report a method termed signature ion approach for analysis of SIAM data acquired on a GC-MS system equipped with an electron ionization (EI) ion source. The signature ion is a fragment ion in EI mass spectrum of a derivatized metabolite that contains all atoms of the underivatized metabolite, except the hydrogen atoms lost during derivatization. In this approach, GC-MS data of metabolite standards were used to recognize the signature ion from the EI mass spectra acquired from stable isotope labeled samples, and a linear regression model was used to deconvolute the intensity of overlapping isotopologues. A mixture score function was also employed for cross-sample chromatographic peak list alignment to recognize the chromatographic peaks generated by the same metabolite in different samples, by simultaneously evaluating the similarity of retention time and EI mass spectrum of two chromatographic peaks. Analysis of a mixture of 16 C-13-labeled and 16 unlabeled amino acids showed that the signature ion approach accurately identified and quantified all isotopologues. Analysis of polar metabolite extracts from cells respectively fed with uniform C-13-glucose and C-13-glutamine further demonstrated that this method can also be used to analyze the complex data acquired from biological samples.

• 出版日期2017-8-8