Optimizing targeted/untargeted metabolomics by automating gas chromatography/mass spectrometry workflows

Albert Robbat Jr; Nicole Kfoury; Eugene Baydakov; Yuriy Gankin

doi:10.1016/j.chroma.2017.05.017

Optimizing targeted/untargeted metabolomics by automating gas chromatography/mass spectrometry workflows

J Chromatogr A. 2017 Jul 7:1505:96-105. doi: 10.1016/j.chroma.2017.05.017. Epub 2017 May 8.

Authors

Albert Robbat Jr¹, Nicole Kfoury², Eugene Baydakov³, Yuriy Gankin³

Affiliations

¹ Department of Chemistry, Tufts University, 200 Boston Ave, Suite G700, Medford, MA, 02155, United States. Electronic address: albert.robbat@tufts.edu.
² Department of Chemistry, Tufts University, 200 Boston Ave, Suite G700, Medford, MA, 02155, United States.
³ EPAM Systems, 41 University Drive, Newtown, PA 18940, United States.

PMID: 28533028
DOI: 10.1016/j.chroma.2017.05.017

Abstract

New database building and MS subtraction algorithms have been developed for automated, sequential two-dimensional gas chromatography/mass spectrometry (GC-GC/MS). This paper reports the first use of a database building tool, with full mass spectrum subtraction, that does not rely on high resolution MS data. The software was used to automatically inspect GC-GC/MS data of high elevation tea from Yunnan, China, to build a database of 350 target compounds. The database was then used with spectral deconvolution to identify 285 compounds by GC/MS of the same tea. Targeted analysis of low elevation tea by GC/MS resulted in the detection of 275 compounds. Non-targeted analysis, using MS subtraction, yielded an additional eight metabolites, unique to low elevation tea.

Keywords: Annotated database building; GC/MS; GC–GC/MS; MS subtraction; Spectral deconvolution.

Publication types

Evaluation Study

MeSH terms

Algorithms
China
Databases, Factual
Gas Chromatography-Mass Spectrometry / methods*
Metabolomics / methods*
Software
Workflow