Comparative development of volatile-oriented multi-SPME and derivatisation-based GC×GC-TOFMS workflows for non-targeted faecal metabolomics

Abstract

Gas chromatography-mass spectrometry (GC-MS) remains a key technique in metabolomics, yet most workflows rely on chemical derivatisation to enable the analysis of non-volatile metabolites. Although derivatisation broadens metabolite coverage, it increases sample preparation time and may introduce additional analytical variabilities. In contrast, solid-phase microextraction (SPME) enables rapid, solvent-free sampling of volatile and semi-volatile compounds, representing an attractive alternative for non-targeted studies. However, methodological developments integrating SPME with comprehensive two-dimensional gas chromatography (GC × GC-MS) remain limited. In this study, a simultaneous multi-SPME GC × GC-TOFMS workflow was developed for the non-targeted screening of faecal samples. Three identical fibres were used simultaneously to generate technical replicates from a single biological sample resulting strong performances in terms of relative standard deviation (10%). Dedicated fibre storage containers and optimised storage conditions were also developed to preserve analyte stability between sampling and injection. In parallel, commonly used GC × GC column configurations were evaluated. The optimised workflow was applied to stool reference materials generated within an interlaboratory metabolomics study coordinated by the National Institute of Standards and Technology (NIST), investigating the effects of diet (vegan vs. omnivore) and sample preservation (aqueous vs. lyophilised) to develop the more adequate stool reference material. SPME results were compared with derivatisation-based metabolomic and lipidomic workflows. Multivariate analysis revealed clear discrimination between diets and storage conditions, while data-fusion analysis highlighted the complementary nature of volatile, metabolomic, and lipidomic profiles. This work provides practical guidance for developing robust GC × GC-MS workflows for complex biological matrices, highlighting the need of multi-extraction approaches for comprehensive analytical coverage.

Keywords: Data fusion; GC×GC-TOFMS; Microbiome; Multi-SPME; Non-target screening.