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Related Experiment Video

Updated: May 18, 2026

Quantitative Metabolomics of Saccharomyces Cerevisiae Using Liquid Chromatography Coupled with Tandem Mass Spectrometry
07:25

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

Published on: January 5, 2021

A yeast metabolite extraction protocol optimised for time-series analyses.

Kalesh Sasidharan1, Tomoyoshi Soga, Masaru Tomita

  • 1Institute for Advanced Biosciences, Keio University, Nipponkoku 403-1, Daihouji, Tsuruoka City, Yamagata, Japan.

Plos One
|September 7, 2012
PubMed
Summary

This study presents a novel method for precise time-resolved metabolite quantification in microbial systems, stabilizing thiols and minimizing degradation for accurate attomole-level measurements.

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Last Updated: May 18, 2026

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Area of Science:

  • Metabolomics
  • Microbial Physiology
  • Analytical Chemistry

Background:

  • Accurate quantification of time-resolved metabolite data is crucial but hindered by metabolite degradation during extraction.
  • Capillary electrophoresis mass spectrometry (CE-MS) is sensitive to high salt concentrations common in extraction protocols.
  • Metabolite yield in microbial systems is affected by extraction efficiency and cell disruption methods.

Purpose of the Study:

  • To develop a robust method for absolute quantification of time-resolved metabolite data in microbial systems.
  • To overcome technical challenges including metabolite degradation and CE-MS incompatibility with high salt concentrations.
  • To enable precise attomole-level metabolite measurements in microbial samples.

Main Methods:

  • Rapidly quenching metabolism using a dry-ice ethanol bath and methanol N-ethylmaleimide solution to stabilize thiols.
  • Efficiently disrupting microbial cells using bead-beating to improve metabolite release.
  • Minimizing metabolite leaching and artifacts from live-cell pelleting through rapid sample processing.
  • Calculating metabolite levels to an attomole/cell level using cell weight, number, and size distribution.

Main Results:

  • The developed method successfully stabilizes labile metabolites, particularly thiols.
  • Rapid processing and efficient cell disruption minimized metabolite degradation and leaching.
  • Absolute quantification of metabolites was achieved at the attomole/cell level.
  • The method was successfully applied to study yeast respiratory oscillations during continuous growth.

Conclusions:

  • This method provides a reliable approach for absolute quantification of time-resolved metabolite data in microbial studies.
  • It addresses key technical limitations in current metabolomic workflows, enhancing data accuracy.
  • The attomole-level quantification capability opens new avenues for understanding microbial metabolism and dynamics.