4.7 Article

mzMatch-ISO: an R tool for the annotation and relative quantification of isotope-labelled mass spectrometry data

Journal

BIOINFORMATICS
Volume 29, Issue 2, Pages 281-283

Publisher

OXFORD UNIV PRESS
DOI: 10.1093/bioinformatics/bts674

Keywords

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Funding

  1. Scottish Universities Life Sciences Alliance (SULSA)
  2. Netherlands Organisation for Scientific Research NWO-Vidi grant
  3. Australian National Health and Medical Research Council
  4. SysMO
  5. NWO-Vidi
  6. SULSA
  7. Wellcome Trust through The Wellcome Trust Centre for Molecular Parasitology
  8. Wellcome Trust [085349]
  9. BBSRC [BB/I004599/1] Funding Source: UKRI
  10. Biotechnology and Biological Sciences Research Council [BB/I004599/1] Funding Source: researchfish

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Motivation: Stable isotope-labelling experiments have recently gained increasing popularity in metabolomics studies, providing unique insights into the dynamics of metabolic fluxes, beyond the steady-state information gathered by routine mass spectrometry. However, most liquid chromatography-mass spectrometry data analysis software lacks features that enable automated annotation and relative quantification of labelled metabolite peaks. Here, we describe mzMatch-ISO, a new extension to the metabolomics analysis pipeline mzMatch.R. Results: Targeted and untargeted isotope profiling using mzMatch-ISO provides a convenient visual summary of the quality and quantity of labelling for every metabolite through four types of diagnostic plots that show (i) the chromatograms of the isotope peaks of each compound in each sample group; (ii) the ratio of mono-isotopic and labelled peaks indicating the fraction of labelling; (iii) the average peak area of mono-isotopic and labelled peaks in each sample group; and (iv) the trend in the relative amount of labelling in a predetermined isotopomer. To aid further statistical analyses, the values used for generating these plots are also provided as a tab-delimited file. We demonstrate the power and versatility of mzMatch-ISO by analysing a C-13-labelled metabolome dataset from trypanosomal parasites.

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