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

Xiaoli Wei, Biyun Shi, Imhoi Koo, Xinmin Yin, Pawel Lorkiewicz, Hamid Suhail, Ramandeep Rattan, Shailendra Giri, Craig J. McClain, Xiang Zhang

Research output: Contribution to journalArticlepeer-review

17 Scopus citations


Stable isotope assisted metabolomics (SIAM) measures the abundance levels of metabolites in a particular pathway using stable isotope tracers (e.g., 13C, 18O and/or 15N). 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 13C-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 13C-glucose and 13C-glutamine further demonstrated that this method can also be used to analyze the complex data acquired from biological samples.

Original languageEnglish (US)
Pages (from-to)25-32
Number of pages8
JournalAnalytica Chimica Acta
StatePublished - Aug 8 2017

All Science Journal Classification (ASJC) codes

  • Analytical Chemistry
  • Biochemistry
  • Spectroscopy
  • Environmental Chemistry


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