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Updated: Apr 26, 2026

Preparation of Drosophila Larval Samples for Gas Chromatography-Mass Spectrometry GC-MS-based Metabolomics
Published on: June 6, 2018
Best Practices in GC-MS and GC × GC-MS-Based Metabolomics and Volatile Analyses: An International Survey
Ryland T Giebelhaus1, Michael Herold2, James J Harynuk3,4
1Department of Chemistry, University of Victoria, Elliott Building Room 313, 3800 Finnerty Road, Victoria, BCV8P 5C2, Canada.
Abstract:
Standardized quality assurance and quality control (QA/QC) practices are essential for reproducible GC-MS metabolomics, yet systematic documentation of current laboratory practices has been lacking. Here, as part of the Metabolomic Quality Assurance and Quality Control Consortium (mQACC), we surveyed 85 laboratories from 27 countries to characterize QA/QC implementation and establish evidence-based recommendations. Respondents represented diverse applications, with 79% performing untargeted analysis, 60% conducting targeted analyses, and 44% conducting both. While single column chromatography is clearly the norm, 24% of the participants used multidimensional chromatography to improve the separation of complex mixtures. Electron ionization with autotuning dominated >95% of the respondents, but more than 30% of the laboratories at least occasionally also used chemical ionization. While most laboratories used low-resolution mass spectrometers, almost half of the laboratories also performed GC-MS analyses on high-resolution QTOF or Orbitrap instruments. A strong consensus emerged on critical QA/QC practices: >90% of laboratories use internal standards for quality control, perform regular leak checks, and maintain injector systems through routine component replacement, spanning column (exchange/cuts), liners, syringes, and septa. Routine monitoring (>50%) involves method blanks, peak shape assessments, and systematic evaluation of intensity drifts, carryovers, and contamination. Retention indices coupled with mass spectral library matching served as the primary annotation approach (60%). Overall, a consensus of best practices in QA/QC and reporting emerged, providing evidence-based recommendations for high-quality GC-MS metabolomics.
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