Improving the quality of biomarker candidates in untargeted metabolomics via peak table-based alignment of comprehensive two-dimensional gas chromatography-mass spectrometry data

Abstract

The potential of high-resolution analytical technologies like GC×GC/TOF MS in untargeted metabolomics and biomarker discovery has been limited by the development of fully automated software that can efficiently align and extract information from multiple chromatographic data sets. In this work we report the first investigation on a peak-by-peak basis of the chromatographic factors that impact GC×GC data alignment. A representative set of 16 compounds of different chromatographic characteristics were followed through the alignment of 63 GC×GC chromatograms. We found that varying the mass spectral match parameter had a significant influence on the alignment for poorly-resolved peaks, especially those at the extremes of the detector linear range, and no influence on well-chromatographed peaks. Therefore, optimized chromatography is required for proper GC×GC data alignment. Based on these observations, a workflow is presented for the conservative selection of biomarker candidates from untargeted metabolomics analyses.

Keywords: Biomarker; Comprehensive two-dimensional gas chromatography; Data alignment; GC×GC–MS; Untargeted metabolomics.

Fig. 1

Two-dimensional gas chromatogram (GC×GC) contour plot of the headspace volatiles of a representative P. aeruginosa clinical isolate. The plot is displayed at 0 – 8 % of the normalized signal intensity to facilitate visualization of trace components, and regions containing only the void volume (¹t_R < 276) or column bleed (²t_R < 1.5) have been excluded for clarity.

Fig. 2

Bubble plot of a representative GC×GC chromatogram, with the 16 peaks of interest displayed in red and the 309 peaks with a S/N > 200 shown in gray.

Fig. 3

Workflow for the identification of high-quality candidate biomarkers from the chromatography of complex samples. The steps on the left, in solid boxes shaded in green, are the recommended steps for the first round of data collection and analysis. The steps on the right, in dotted boxes shaded in blue, are recommended if additional biomarker candidates need to be identified.