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Related Experiment Video

Updated: May 29, 2025

Identification and Quantification of Deranged Metabolites in Critically Ill Patients Using NMR-Based Metabolomics
11:02

Identification and Quantification of Deranged Metabolites in Critically Ill Patients Using NMR-Based Metabolomics

Published on: November 29, 2024

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Ion suppression correction and normalization for non-targeted metabolomics.

Iqbal Mahmud1, Bo Wei1, Lucas Veillon1

  • 1Metabolomics Core Facility, Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center (MDACC), Houston, TX, USA.

Nature Communications
|February 5, 2025
PubMed
Summary
This summary is machine-generated.

The IROA TruQuant Workflow effectively corrects ion suppression in mass spectrometry metabolomics. This method enhances measurement accuracy and precision across various analytical conditions, revealing new insights into cellular metabolism.

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Area of Science:

  • Analytical Chemistry
  • Biochemistry
  • Metabolomics

Background:

  • Ion suppression significantly impacts mass spectrometry (MS)-based metabolomics, reducing accuracy, precision, and sensitivity.
  • Accurate quantification of metabolites is crucial for understanding biological processes and disease mechanisms.

Purpose of the Study:

  • To introduce and evaluate the IROA TruQuant Workflow for measuring and correcting ion suppression in MS metabolomics.
  • To perform robust normalization of metabolomic data using Dual MSTUS normalization.

Main Methods:

  • Utilized a stable isotope-labeled internal standard (IROA-IS) library and companion algorithms.
  • Evaluated the workflow across ion chromatography (IC), hydrophilic interaction liquid chromatography (HILIC), and reversed-phase liquid chromatography (RPLC)-MS.
  • Tested in positive and negative ionization modes, with clean and unclean ion sources, and diverse biological matrices.

Main Results:

  • Observed ion suppression ranging from 1% to over 90% across all tested conditions.
  • The workflow effectively corrected ion suppression and reduced coefficients of variation from 1% to 20%.
  • Demonstrated application in studying ovarian cancer cell response to L-asparaginase (ASNase), revealing novel peptide metabolism alterations.

Conclusions:

  • The IROA TruQuant Workflow provides robust correction for ion suppression in non-targeted metabolomic data.
  • This method enhances data reliability across diverse analytical setups and biological samples.
  • The workflow facilitates the discovery of previously unreported metabolic changes, as shown in the ovarian cancer study.