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

Achuthanunni Chokkathukalam, Andris Jankevics, Darren John Creek, Fiona Achcar, Michael P Barrett, Rainer Breitling

Research output: Contribution to journalArticleResearchpeer-review

50 Citations (Scopus)

Abstract

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 13C-labelled metabolome dataset from trypanosomal parasites.
Original languageEnglish
Pages (from-to)281 - 283
Number of pages3
JournalBioinformatics
Volume29
Issue number2
DOIs
Publication statusPublished - 2013
Externally publishedYes

Cite this