Isotopic Ratio Outlier Analysis of the S. cerevisiae Metabolome Using Accurate Mass Gas Chromatography/Time-of-Flight Mass Spectrometry: A New Method for Discovery

Yunping Qiu, Robyn D. Moir, Ian M. Willis, Chris Beecher, Yu Hsuan Tsai, Timothy J. Garrett, Richard A. Yost, Irwin J. Kurland

Research output: Contribution to journalArticle

12 Citations (Scopus)

Abstract

Isotopic ratio outlier analysis (IROA) is a 13C metabolomics profiling method that eliminates sample to sample variance, discriminates against noise and artifacts, and improves identification of compounds, previously done with accurate mass liquid chromatography/mass spectrometry (LC/MS). This is the first report using IROA technology in combination with accurate mass gas chromatography/time-of-flight mass spectrometry (GC/TOF-MS), here used to examine the S. cerevisiae metabolome. S. cerevisiae was grown in YNB media, containing randomized 95% 13C, or 5%13C glucose as the single carbon source, in order that the isotopomer pattern of all metabolites would mirror the labeled glucose. When these IROA experiments are combined, the abundance of the heavy isotopologues in the 5%13C extracts, or light isotopologues in the 95%13C extracts, follows the binomial distribution, showing mirrored peak pairs for the molecular ion. The mass difference between the 12C monoisotopic and the 13C monoisotopic equals the number of carbons in the molecules. The IROA-GC/MS protocol developed, using both chemical and electron ionization, extends the information acquired from the isotopic peak patterns for formulas generation. The process that can be formulated as an algorithm, in which the number of carbons, as well as the number of methoximations and silylations are used as search constraints. In electron impact (EI/IROA) spectra, the artifactual peaks are identified and easily removed, which has the potential to generate "clean" EI libraries. The combination of chemical ionization (CI) IROA and EI/IROA affords a metabolite identification procedure that enables the identification of coeluting metabolites, and allowed us to characterize 126 metabolites in the current study.

Original languageEnglish (US)
Pages (from-to)2747-2754
Number of pages8
JournalAnalytical Chemistry
Volume88
Issue number5
DOIs
StatePublished - Mar 1 2016

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Metabolites
Gas chromatography
Mass spectrometry
Carbon
Ionization
Glucose
Electrons
Liquid chromatography
Spectrum analysis
Mirrors
Ions
Molecules
Experiments

ASJC Scopus subject areas

  • Analytical Chemistry

Cite this

Isotopic Ratio Outlier Analysis of the S. cerevisiae Metabolome Using Accurate Mass Gas Chromatography/Time-of-Flight Mass Spectrometry : A New Method for Discovery. / Qiu, Yunping; Moir, Robyn D.; Willis, Ian M.; Beecher, Chris; Tsai, Yu Hsuan; Garrett, Timothy J.; Yost, Richard A.; Kurland, Irwin J.

In: Analytical Chemistry, Vol. 88, No. 5, 01.03.2016, p. 2747-2754.

Research output: Contribution to journalArticle

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abstract = "Isotopic ratio outlier analysis (IROA) is a 13C metabolomics profiling method that eliminates sample to sample variance, discriminates against noise and artifacts, and improves identification of compounds, previously done with accurate mass liquid chromatography/mass spectrometry (LC/MS). This is the first report using IROA technology in combination with accurate mass gas chromatography/time-of-flight mass spectrometry (GC/TOF-MS), here used to examine the S. cerevisiae metabolome. S. cerevisiae was grown in YNB media, containing randomized 95{\%} 13C, or 5{\%}13C glucose as the single carbon source, in order that the isotopomer pattern of all metabolites would mirror the labeled glucose. When these IROA experiments are combined, the abundance of the heavy isotopologues in the 5{\%}13C extracts, or light isotopologues in the 95{\%}13C extracts, follows the binomial distribution, showing mirrored peak pairs for the molecular ion. The mass difference between the 12C monoisotopic and the 13C monoisotopic equals the number of carbons in the molecules. The IROA-GC/MS protocol developed, using both chemical and electron ionization, extends the information acquired from the isotopic peak patterns for formulas generation. The process that can be formulated as an algorithm, in which the number of carbons, as well as the number of methoximations and silylations are used as search constraints. In electron impact (EI/IROA) spectra, the artifactual peaks are identified and easily removed, which has the potential to generate {"}clean{"} EI libraries. The combination of chemical ionization (CI) IROA and EI/IROA affords a metabolite identification procedure that enables the identification of coeluting metabolites, and allowed us to characterize 126 metabolites in the current study.",
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