Application of GC Orbitrap mass spectrometry for untargeted metabolomics of pathogenic microorganisms

Importance of the Topic

The rise of antibiotic resistance and the complex interactions between pathogenic microorganisms such as Candida albicans and Staphylococcus aureus pose significant challenges for healthcare. Untargeted metabolomics using high-resolution GC–MS provides detailed insights into the small-molecule metabolites driving synergistic virulence, biofilm formation, and host–pathogen interactions.

Objectives and Study Overview

This study aimed to apply a Thermo Scientific Q Exactive GC Orbitrap mass spectrometer for untargeted metabolomic profiling of C. albicans and S. aureus in mono- and co-culture. Both spent media and intracellular extracts were analyzed to identify statistically significant metabolites involved in microbial interactions and to elucidate biochemical pathways underlying enhanced virulence.

Methodology and Instrumentation

Derivatization and Sample Preparation:

• Methoximation with methoxyamine HCl in pyridine at 60 °C for 120 min.
• Silylation with MSTFA + 1% TMCS at 80 °C for 120 min.
• Internal standards: 13C6-glucose, D27-myristic acid, scyllo-inositol.

GC–MS Analysis:

• Thermo Scientific TRACE 1310 GC with TraceGOLD TG-5Sil MS column (30 m × 0.25 mm × 0.25 µm).
• Injection: 1 µL, split 1:100, inlet 250 °C, He carrier at 1.0 mL/min.
• Oven program: 70 °C (4 min) to 320 °C at 20 °C/min (8 min hold).
• Q Exactive GC Orbitrap MS: full-scan EI 50–650 Da, 60 000 FWHM at m/z 200, internal lock mass (m/z 207.03235).

Data Processing:

• Compound Discoverer: chromatographic alignment, peak detection, PCA, volcano plots for group comparisons.
• TraceFinder: peak deconvolution, NIST 2014 spectral library matching (SI > 700), high-resolution filtering, semi-quantitation.

Main Findings and Discussion

PCA demonstrated clear separation between media-only samples, mono-culture media, co-culture media, and intracellular extracts with high reproducibility in QC runs (<20% RSD). Key observations included:

• Glycine depletion in S. aureus media compared to other groups.
• Elevated sedoheptulose-7-phosphate in co-culture media, suggesting altered pentose phosphate pathway activity and potential fungal modulation of bacterial growth.
• Accumulation of scyllo-inositol derivatives in S. aureus cell extracts, confirmed by pure standard comparison with sub-ppm mass accuracy.

Benefits and Practical Applications

The high mass resolution, dynamic range, and full-scan capability of the Q Exactive GC Orbitrap enable confident, untargeted detection of metabolites at varying concentrations. Automated workflows streamline data processing, reduce time to result, and support customized and commercial library searches, facilitating applications in microbial interaction studies, clinical diagnostics, and QA/QC in biomanufacturing.

Future Trends and Opportunities

Advances likely include the expansion of high-resolution spectral libraries, integration with LC–MS and other omics platforms for multi-layered pathway analysis, real-time GC–MS monitoring of biofilm development, and miniaturized instrumentation for point-of-care metabolomics. Machine-learning algorithms will further enhance feature extraction, compound identification, and predictive modeling of pathogen behavior.

Conclusion

This work demonstrates the power of untargeted GC-Orbitrap metabolomics for elucidating complex microbial interactions. The Q Exactive GC platform delivers high-confidence compound identification, robust quantitation, and efficient data workflows, providing unprecedented insight into metabolite-driven pathogen synergy.

References

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