ArticleJournal of food and drug analysis2025
Development of an untargeted metabolomics analytical protocol for fecal samples by liquid chromatography-mass spectrometry.
Article in Journal of food and drug analysis, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Gut microbiota has recently gained attention for its role in regulating multiple host pathways and contributing to disease developments. Fecal metabolomics using liquid chromatography-mass spectrometry (LC-MS) offers a promising approach to study gut microbial metabolites; however, it remains technically challenging due to the complex, heterogeneous nature of fecal samples and the lack of standardized protocols. This study aimed to establish a robust and reproducible untargeted fecal metabolomics workflow. We systematically evaluated sample preparation parameters-including sample amount, extraction solvent, numbers of extraction, and sample-to-solvent ratio-and assessed method reproducibility. Additionally, we compared three LC-MS data acquisition workflows using 10 samples from inflammatory bowel disease (IBD) patients and healthy controls (HC) to improve the identification of biologically relevant metabolites. In sample preparation, our results showed that 50 mg of lyophilized feces was sufficient to capture inter-individual metabolic variation. Additionally, methanol outperformed acetonitrile and showed comparable results to three binary solvent mixtures. A single extraction with methanol was sufficient, and a 1:20 (w/v) sample-to-solvent ratio maximized feature detection. Among the acquisition methods, data-dependent acquisition (DDA) with simultaneous MS1 and MS2 scans provided the highest metabolite coverage with acceptable annotation reliability. In summary, we recommend a single extraction of 50 mg lyophilized feces with 1 mL methanol and the use of DDA for sample acquisition to ensure comprehensive and reproducible untargeted analysis. This optimized protocol improves metabolite detection in human feces and offers a practical strategy to support future studies exploring gut microbial contributions to human health and disease.
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