Metabolomics 2017: Back to the Future with Thermo Scientific™ Q Exactive™ GC Orbitrap™ GC-MS/MS

Significance of the Topic

Analytical coverage of the metabolome is essential for biomarker discovery and systems biology. GC/MS provides a well-established workflow for volatiles and derivatized metabolites. Incorporating high-resolution accurate mass enhances identification fidelity and alleviates the key challenge of unknown assignment in metabolomics.

Objectives and Study Overview

This whitepaper evaluates the Thermo Scientific Q Exactive GC Orbitrap GC-MS/MS system, demonstrating improved chromatographic resolution, mass accuracy, and streamlined workflows. It reviews automated online derivatization, data deconvolution, spectral library matching, and software-assisted unknown identification.

Methodology

• Automated two-step derivatization of samples using methoxyamine hydrochloride followed by MSTFA, executed on the TriPlus RSH autosampler with dual incubators (37 °C for 90 min, 45 °C for 30 min).
• Gas chromatography parameters: initial oven hold at 70 °C, temperature ramp to 325 °C at 10 °C/min, total runtime ~30 min with injected volume of 1 µL.
• Mass spectrometry: Q Exactive GC Orbitrap operated in electron ionization (EI) at resolving powers of 60 000 to 120 000 FWHM (m/z 200), optional chemical ionization (CI) for molecular ion detection.
• Peak detection and deconvolution via TraceFinder plugin; library matching against the Thermo GC-Orbitrap EI Metabolomics Library (~900 compounds) with high-resolution filtering (±5 ppm).
• Automated formula confirmation and isotopic pattern scoring using Compound Discoverer software; supplementary structure suggestions via ChemSpider.
• Batch and sequential derivatization strategies supporting up to 24 samples in 24 h with reproducibility around 5 % RSD.

Used Instrumentation

• Thermo Scientific Q Exactive GC Orbitrap GC-MS/MS system.
• Thermo Scientific TriPlus RSH autosampler featuring dual incubators, vortex mixer, and syringe module.
• Thermo TraceFinder Deconvolution plugin and GC-Orbitrap EI Metabolomics Library.
• Thermo Scientific Compound Discoverer software.

Main Results and Discussion

• HRAM data enabled clear deconvolution of complex peaks, such as hexadecanoic acid methyl ester, surpassing unit resolution performance by mass extraction clarity.
• Mass accuracy improved with resolution: from 9.4 ppm at 15 000 to 0.1 ppm at 120 000, reducing candidate formulas for m/z 324.13541 from over 100 to a single top hit.
• Automated derivatization maintained stability with average RSD of 5 % over 24 h for amino acid targets.
• Workflow integration significantly shortened time to identify unknowns using HRF scoring and retention index matching.

Benefits and Practical Applications

• Broad metabolome coverage including volatiles, organic acids, amino acids, lipids, steroids, and sugars.
• High reproducibility and robust matrix-independent ionization.
• Automated sample preparation and data analysis increase throughput for clinical, environmental, and QA/QC labs.
• Enhanced confidence in biomarker discovery and metabolic profiling due to precise mass measurement.

Future Trends and Opportunities

• Development of additional ionization modes and library expansions to capture a wider range of metabolites.
• Integration of machine learning algorithms for more efficient unknown annotation and pathway analysis.
• Advances in miniaturized chromatography and faster gradients to boost throughput.
• Cloud-based data sharing and collaborative platforms for large-scale metabolomics studies.

Conclusion

Thermo Scientific Q Exactive GC Orbitrap GC-MS/MS, combined with automated derivatization and advanced software workflows, addresses critical challenges in metabolomics by delivering superior mass accuracy, robust quantitation, and efficient unknown identification, paving the way for deeper biological insights.

References

• Bouatra S. et al., 2013. The Human Urine Metabolome, PLOS ONE.