Accurate Mass Retention Time Locked Metabolomics EI Library and Workflows for Accurate Mass GC/Q-TOF Metabolomics Data Processing

Importance of the topic

The combination of accurate mass measurement and retention time locking in gas chromatography–quadrupole time-of-flight (GC/Q-TOF) metabolomics significantly improves confidence in compound identification. This approach addresses challenges in deconvolution of complex EI spectra, reduces false positives, and accelerates high-throughput metabolite screening in diverse matrices such as cell extracts.

Objectives and study overview

This work aimed to build a curated, accurate mass retention time locked EI library of approximately 500 primary metabolites and to develop end-to-end workflows for metabolomics data processing. Key goals included generating high-quality EI spectra with precise mass annotation, implementing a novel profile-based feature detection algorithm, and demonstrating the workflow on human breast cancer cell lines (MCF-7 and MDA-MB-468).

Methodology and instrumentation

Sample preparation and derivatization:

• Cell culture: MCF-7 and MDA-MB-468 grown in DMEM with 10% FBS and 5% PenStrep, quenched with methanol, harvested, and flash-frozen.
• Extraction: Polar metabolites extracted in acetonitrile:isopropanol:water (3:3:2), dried, methoximated, and silylated (MSTFA + 1% TMCS).

Chromatography and mass spectrometry:

• System: Agilent 7890B GC with 7200B GC/Q-TOF.
• Column: DB-5 MS UI, 30 m × 0.25 mm × 0.25 µm, retention time locked to d27-myristic acid.
• Carrier gas: Helium at 1 mL/min; oven program 60 °C (1 min) to 325 °C at 10 °C/min, 3.5 min hold.
• Source temperature: 230 °C; transfer line: 290 °C; quadrupole: 150 °C; mass range 50–600 m/z; acquisition rate 5 Hz; EI ionization.

Data processing:

• Peak detection and library search in MassHunter Qualitative Analysis (Unknowns Analysis tool) using a new profile-based feature detection algorithm.
• Library construction and curation in Personal Compound Database and Library (PCDL) with Molecular Formula Generator for fragment annotation.
• Statistical and pathway analyses in Mass Profiler Professional (MPP).

Main results and discussion

The curated EI library provided average molecular ion mass errors below 1 ppm and isotope abundance errors around 1%. Library match scores for 56 test metabolites ranged 89.9–99.1%. The novel profile-based algorithm successfully extracted high-quality spectra from highly saturated chromatogram regions where conventional deconvolution fails. Application to MCF-7 versus MDA-MB-468 extracts revealed significant metabolic differences, exemplified by alterations in the methionine salvage cycle.

Benefits and practical applications

• Enhanced metabolite identification confidence by combining accurate mass, retention time, and EI fragmentation patterns.
• Automated, high-throughput workflows suitable for complex biological matrices.
• Robust feature extraction in regions of spectral overlap and high complexity.

Future trends and opportunities

Expanding library coverage with additional metabolite classes, integrating machine learning for improved deconvolution and annotation, and coupling with complementary separation techniques (e.g. multidimensional GC) are promising directions. Applications may extend to clinical diagnostics, environmental monitoring, and biomarker discovery.

Conclusion

The developed accurate mass, retention time locked EI library and associated workflows deliver a reliable platform for GC/Q-TOF metabolomics. Validated on breast cancer cell lines, this approach offers improved identification accuracy and throughput, paving the way for broader applications in research and quality control.