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Updated: Apr 7, 2026

A Strategy for Sensitive, Large Scale Quantitative Metabolomics

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.

|April 6, 2026

Summary

This summary is machine-generated.

A new method, Kobe University Serial LC-MS/MS Analysis using Multiple columns with a Single mobile phase (KUSLAMS), enables high-throughput gut microbiota metabolome analysis. This platform accurately quantifies numerous metabolites, aiding human health research.

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Last Updated: Apr 7, 2026

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Quantitative Metabolomics of Saccharomyces Cerevisiae Using Liquid Chromatography Coupled with Tandem Mass Spectrometry

Quantitative Metabolomics of Saccharomyces Cerevisiae Using Liquid Chromatography Coupled with Tandem Mass Spectrometry

Published on: January 5, 2021

Area of Science:

Microbiology
Metabolomics
Analytical Chemistry

Background:

The gut microbiota plays a crucial role in human health.
Metabolomics is essential for understanding host-microbiota interactions.
Conventional liquid chromatography-tandem mass spectrometry (LC-MS/MS) methods for metabolome analysis are complex and inefficient.

Purpose of the Study:

To develop a streamlined, high-throughput quantitative method for analyzing gut microbiota metabolites.
To overcome the limitations of conventional LC-MS/MS techniques.

Main Methods:

Developed the Kobe University Serial LC-MS/MS Analysis using Multiple columns with a Single mobile phase (KUSLAMS) platform.
Integrated two columns (PFPP and C18) and a derivatization method.
Quantified 215 metabolites, including amino acids, nucleotides, carboxylic acids, amines, and fatty acids.

Main Results:

Achieved high-throughput quantification of 215 metabolites.
Demonstrated reproducibility with 64 out of 82 intracellular metabolites detected with coefficients of variation below 15%.
Identified significant differences in intra- and extracellular metabolite concentrations in response to inulin in an in vitro gut microbiota culture.

Conclusions:

KUSLAMS is a robust and versatile platform for simultaneous monitoring of intra- and extracellular metabolite dynamics.
This method facilitates the exploration of microbiota-derived metabolites relevant to human health.
KUSLAMS simplifies and enhances the efficiency of metabolome analysis for gut microbiota research.