Abstract
Summary: MIA detects and visualizes isotopic enrichment in gas chromatography electron ionization mass spectrometry (GC–EI-MS) datasets in a non-targeted manner. It provides an easy-to-use graphical user interface that allows for visual mass isotopomer distribution analysis across multiple datasets. MIA helps to reveal changes in metabolic fluxes, visualizes metabolic proximity of isotopically enriched compounds and shows the fate of the applied stable isotope labeled tracer.Availability and Implementation: Linux and Windows binaries, documentation, and sample data are freely available for download at http://massisotopolomeanalyzer.lu. MIA is a stand-alone application implemented in C ++ and based on Qt5, NTFD and the MetaboliteDetector framework.Contact: karsten.hiller@uni.lu
Highlights
Stable isotope assisted metabolomics is widely applied to analyze metabolism and to determine reaction mechanisms (Buescher et al, 2015)
We recently demonstrated the potential of non-targeted stable isotope labeling in the analysis of hypoxic cancer cells to detect hypoxia-induced metabolic flux changes in a non-targeted manner (Weindl et al, 2016)
These tools provide the isotopic enrichment of all detected compounds in the form of mass isotopomer distributions (MIDs), which represent the relative abundances of the different isotopic isomers grouped by their masses
Summary
Stable isotope assisted metabolomics is widely applied to analyze metabolism and to determine reaction mechanisms (Buescher et al, 2015). There have been tools available for the non-targeted and quantitative detection of isotopic enrichment in complex samples analyzed by GC-MS (Hiller et al, 2013) or LC-MS (Bueschl et al, 2012; Capellades et al, 2016; Chokkathukalam et al, 2013; Creek et al, 2012; Huang et al, 2014) These tools provide the isotopic enrichment of all detected compounds in the form of mass isotopomer distributions (MIDs), which represent the relative abundances of the different isotopic isomers (isotopologues) grouped by their masses. There was neither free nor commercial software available that sufficiently supported the biological analysis of global stable isotope labeling datasets beyond the mere detection of isotopic enrichment To this end, we developed MIA, an easy-to-use software tool to determine, visualize and analyze mass isotopomer distributions across multiple GC–EI-MS datasets in a non-targeted manner (Fig. 1)
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