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Quantitative Metabolomics of Saccharomyces Cerevisiae Using Liquid Chromatography Coupled with Tandem Mass Spectrometry07:25

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We present a protocol for the identification and quantitation of major classes of water-soluble metabolites in the yeast Saccharomyces cerevisiae. The described method is versatile, robust, and sensitive. It allows the separation of structural isomers and stereoisomeric forms of water-soluble metabolites from each...
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Untargeted Liquid Chromatography-Mass Spectrometry-Based Metabolomics Analysis of Wheat Grain07:10

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A method for the untargeted analysis of wheat grain metabolites and lipids is presented. The protocol includes an acetonitrile metabolite extraction method and reversed phase liquid chromatography-mass spectrometry methodology, with acquisition in positive and negative electrospray ionization...
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Large Scale Non-targeted Metabolomic Profiling of Serum by Ultra Performance Liquid Chromatography-Mass Spectrometry (UPLC-MS)07:34

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Non-targeted metabolite profiling by ultra performance liquid chromatography coupled with mass spectrometry (UPLC-MS) is a powerful technique to investigate metabolism. This article outlines a typical workflow utilized for non-targeted metabolite profiling of serum including sample organization and preparation, data acquisition, data analysis, quality control, and metabolite...
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Extraction of Aqueous Metabolites from Cultured Adherent Cells for Metabolomic Analysis by Capillary Electrophoresis-Mass Spectrometry11:39

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The purpose of this article is to describe a protocol for extraction of aqueous metabolites from cultured adherent cells for metabolomic analysis, particularly, capillary electrophoresis-mass...
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Gas Chromatography-Mass Spectrometry-Based Targeted Metabolomics of Hard Coral Samples09:01

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Related Experiment Video

Updated: Jan 19, 2026

Quantitative Metabolomics of Saccharomyces Cerevisiae Using Liquid Chromatography Coupled with Tandem Mass Spectrometry
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Mass spectrometry-based forest tree metabolomics.

Ana Margarida Rodrigues1, Célia Miguel2,3, Inês Chaves2,3

  • 1Plant Metabolomics Laboratory, GreenIT-Bioresources for Sustainability, Instituto de Tecnologia Química e Biológica António Xavie, Universidade Nova de Lisboa (ITQB NOVA) Avenida da República, Oeiras, 2780-157, Portugal.

Mass Spectrometry Reviews
|September 10, 2019
PubMed
Summary
This summary is machine-generated.

Mass spectrometry (MS)-based metabolomics advances forest tree research, focusing on Pinus, Quercus, and Eucalyptus species. Data management must adhere to FAIR principles for enhanced knowledge discovery in climate change studies.

Keywords:
FAIR data standardsGC-MSLC-MSclimate changeomics technologiespinewood nematode

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Untargeted Liquid Chromatography-Mass Spectrometry-Based Metabolomics Analysis of Wheat Grain
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Large Scale Non-targeted Metabolomic Profiling of Serum by Ultra Performance Liquid Chromatography-Mass Spectrometry UPLC-MS
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Area of Science:

  • * Forest tree research
  • * Plant metabolomics
  • * Mass spectrometry applications

Background:

  • * Forest tree research lags due to long life cycles, large genomes, and limited genomic tools.
  • * Tree tissues present analytical challenges for mass spectrometry (MS) due to complex matrices and interferents like oleoresins and cellulose.
  • * Understanding metabolite responses to environmental stressors is crucial for economically and ecologically significant tree species.

Purpose of the Study:

  • * To review advances in MS-based metabolomics for forest tree species.
  • * To highlight the application of these techniques in Pinus, Quercus, and Eucalyptus.
  • * To emphasize the importance of data management and FAIR principles in forest tree metabolomics.

Main Methods:

  • * Review of current literature on MS-based metabolomics in forest trees.
  • * Focus on studies analyzing metabolite profiles in response to abiotic and biotic stresses.
  • * Discussion of data processing, analysis, and storage challenges.

Main Results:

  • * MS-based metabolomics offers powerful tools for analyzing forest tree metabolism.
  • * Specific focus on Pinus, Quercus, and Eucalyptus reveals insights into stress responses.
  • * Large datasets generated require robust management and adherence to FAIR principles for reusability.

Conclusions:

  • * MS-based metabolomics is vital for advancing forest tree science, especially under climate change.
  • * Implementing FAIR data principles and metadata standards is essential for maximizing the value of metabolomics data.
  • * Improved data accessibility and interoperability will accelerate discoveries in forest tree biology.