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Updated: Apr 7, 2026

A Strategy for Sensitive, Large Scale Quantitative Metabolomics
Published on: May 27, 2014
Development of a Quantitative Serial LC-MS/MS Method for Gut Microbiota Metabolomics
Takanobu Yoshida1, Tomoya Shintani2, Daisuke Sasaki2
1Engineering Biology Research Center, Kobe University, 1-1 Rokkodai-cho, Nada-ku, Kobe 657-8501, Japan.
None:
The significance of gut microbiota in human health has gained increasing attention. Accordingly, metabolomics has been used to elucidate host-microbiota interactions. Liquid chromatography-tandem mass spectrometry (LC-MS/MS) is an ideal choice for metabolome analysis of gut microbiota due to its quantitative capabilities. However, conventional LC-MS/MS requires multiple columns, multiple mobile phases, and complex procedures to optimize conditions for each target metabolite. To address these limitations, we developed a quantitative serial LC-MS/MS method, termed the Kobe University Serial LC-MS/MS Analysis using Multiple columns with a Single mobile phase (KUSLAMS). This platform integrates two columns (PFPP and C18) and a derivatization method for seamless, high-throughput quantification of 215 metabolites, including amino acids, nucleotides, carboxylic acids, amines, and fatty acids. Reproducibility for repeated analysis was assessed using 82 intracellular gut microbiota metabolites, for which new analytical methods were developed. Among these, 64 metabolites were detected with coefficients of variation (CV) below 15%. The application of KUSLAMS to an in vitro gut microbiota culture system with and without inulin revealed differences in the concentrations of 21 intracellular and 14 extracellular metabolites. Notably, several metabolites exhibited increased intracellular and decreased extracellular concentrations, suggesting a possible link between intracellular accumulation and extracellular depletion, although this interpretation is exploratory. These results indicate that KUSLAMS allows for the simultaneous monitoring of intra- and extracellular metabolite dynamics. Together, these findings demonstrate that KUSLAMS is a robust and versatile platform for the exploration of microbiota-derived metabolites relevant to human health.
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