Identification of metabolites in human plasma using GC-Orbitrap-MS after online derivatization

Importance of Topic

Gas chromatography–mass spectrometry (GC‐MS) is a cornerstone technique in metabolomics, offering high separation power and access to extensive spectral libraries. Many biologically relevant metabolites are polar and nonvolatile, requiring chemical derivatization to enable gas‐phase analysis. Implementing automated online derivatization immediately before injection reduces variability associated with sample aging and enhances throughput, which is critical for reliable profiling of complex matrices such as human plasma.

Objectives and Study Overview

This work evaluated the combination of automated online derivatization with a high‐resolution GC‐Orbitrap‐MS system for the identification of metabolites in human plasma. By leveraging a comprehensive HRAM metabolomics library (>850 compounds), the study assessed identification confidence, mass accuracy, and reproducibility across replicate injections.

Methodology and Instrumentation

• Sample Preparation: 20 µL human plasma was protein‐precipitated in methanol, dried under nitrogen, then derivatized sequentially with methoxyamine in pyridine and MSTFA using an online Gerstel MPS autosampler.
• Gas Chromatography: Thermo Scientific TRACE 1310 GC with a TraceGOLD TG-5SilMS 30 m × 0.25 mm × 0.25 µm column; split injection (5:1), He carrier at 1.0 mL/min; oven program 70 °C (4 min) to 320 °C at 20 °C/min (8 min hold).
• Mass Spectrometry: Thermo Scientific Q Exactive GC Orbitrap, EI 70 eV, transfer line 250 °C, source 230 °C; full-scan m/z 50–650 at 60 000 FWHM, lockmass correction (m/z 207.03235).

Results and Discussion

Spectral deconvolution and library matching enabled confident identification of key metabolites, exemplified by pyroglutamic acid 2TMS (search index 903, HRF 99.4%, combined score 97.8%). Over 200 features exceeding 1×10^6 peak area were detected in plasma extracts. Selected compounds (e.g., ribose 4TMS, palmitic acid ester, cholesterol TMS) exhibited sub‐1 ppm mass accuracy. Reproducibility across eight replicates yielded %RSD values between 5–12%, demonstrating the stability of the online derivatization workflow compared to traditional offline protocols.

Benefits and Practical Applications

• High‐confidence metabolite identification using combined spectral indexing and high‐resolution filtering.
• Automated online derivatization minimizes variability from sample waiting time and accelerates sample throughput.
• Robust quantitative profiling suitable for clinical, forensic, and pharmaceutical metabolomics studies.

Future Trends and Potential Applications

• Adoption of data‐independent acquisition strategies to expand metabolome coverage.
• Real‐time monitoring of bioprocesses and clinical diagnostics with automated sample derivatization.
• Growth of high‐resolution spectral libraries to include novel biomarkers and transformation products.

Conclusion

The integration of GC‐Orbitrap‐MS with automated online derivatization offers a robust, high‐throughput solution for human plasma metabolite profiling. The approach delivers reproducible, sub‐ppm mass accuracy and high identification confidence, paving the way for advanced metabolomics applications.

Reference

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• Thermo Fisher Scientific. Q Exactive GC Orbitrap GC-MS HRAM Metabolomics Library. 2017.
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