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Characterization of Electron Ionization and Chemical Ionization on a Novel High Resolution Gas Chromatography Time-of-Flight Mass Spectrometer—Tools for the Identification of Unknown Metabolites

Posters |  | LECOInstrumentation
GC/MSD, GC/HRMS, GC/TOF
Industries
Metabolomics
Manufacturer
Agilent Technologies, GERSTEL, LECO

Summary

Importance of the topic


Comprehensive two-dimensional gas chromatography coupled with time-of-flight mass spectrometry (GCxGC-TOFMS) offers unprecedented resolution and peak capacity for complex biological samples. In metabolomics, distinguishing subtle variations in small-molecule profiles between healthy and disease states is critical for biomarker discovery and understanding metabolic regulation. GCxGC-TOFMS addresses limitations of conventional one-dimensional GC by resolving coeluting compounds and capturing low-abundance metabolites in blood plasma.

Objectives and Study Overview


This study compared pooled, trimethylsilyl-derivatized plasma samples from three phenotypes of Zucker rats: lean, fatty, and diabetic obese. The primary aims were to demonstrate the enhanced analyte detection and separation afforded by GCxGC-TOFMS, to overlay chromatographic and spectral data across sample pools, and to evaluate this approach as a rapid screening tool for metabolite differences potentially linked to metabolic health.

Methodology and Instrumentation


Sample Preparation
  • Proteins removed by 5000 MWCO ultrafiltration.
  • Dried residues derivatized overnight at 60 °C with BSTFA.
GCxGC-TOFMS Analysis
  • Gas chromatograph: Agilent 7890 with LECO dual-stage quad-jet thermal modulator.
  • Primary column: 30 m × 0.25 mm id × 0.25 µm Rxi-5Sil MS.
  • Secondary column: 1.24 m × 0.15 mm id × 0.15 µm Rxi-17Sil MS.
  • Carrier gas: Helium at 1.5 mL/min; injection: 1 µL splitless at 260 °C.
  • Temperature program: primary ramp 6 °C/min from 70 °C to 305 °C; secondary ramp offset +5 °C.
  • Mass spectrometer: LECO Pegasus 4D TOFMS at 150 spectra/s; mass range 45–750 m/z; ion source 240 °C; electron energy –70 eV.

Main Results and Discussion


Overlaid linear ion chromatograms and two-dimensional contour plots revealed clear metabolite variations across the three rat phenotypes. Key findings included:
  • Leucine (N,O-TMS derivative) was absent in lean plasma but upregulated in fatty and obese diabetic pools.
  • TMS-ester-oxobutyl glycine appeared only in fatty and obese samples, indicating phenotype-specific expression.
  • Proline (N,O-TMS) and tris-TMS-L-threonine were detected in all pools with differing abundance trends.
  • Penta-TMS-glucopyranose exhibited a progressive increase from lean to fatty to obese diabetic samples.
The enhanced peak capacity of GCxGC resolved analytes buried under high-concentration coelutants in one-dimensional GC, and TOFMS provided rich, non-skewed spectra to support deconvolution and library matching.

Benefits and Practical Applications


GCxGC-TOFMS enables rapid, high-throughput screening of large sample cohorts for metabolomic differences. The method reduces analysis time while increasing sensitivity to low-level compounds. It is especially valuable for QA/QC in pharmaceutical and clinical research, environmental monitoring, and discovery of diagnostic biomarkers in complex matrices such as blood plasma.

Future Trends and Opportunities


Advances in data processing and machine learning are expected to enhance automated deconvolution and pattern recognition in GCxGC-TOFMS datasets. Integration with high-resolution accurate-mass instruments may expand metabolome coverage. Miniaturized GCxGC systems, faster modulation technologies, and targeted quantitation workflows will broaden applications in clinical diagnostics, nutrigenomics, and personalized medicine.

Conclusion


This proof-of-concept study demonstrates that GCxGC-TOFMS is a powerful, efficient screening tool for distinguishing metabolic phenotypes in pooled rat plasma samples. The combination of comprehensive chromatographic separation and high-speed mass spectral acquisition uncovers unique and differential metabolite signatures, supporting its adoption for rapid biomarker discovery and comparative metabolomics.

References


  • Max Planck spectral library
  • Fiehn Rtx5 library
  • NIST mass spectral library
  • Wiley7 library

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