Abstract
Stable isotope labeling (SIL) techniques have the potential to enhance different aspects of liquid chromatography–high-resolution mass spectrometry (LC-HRMS)-based untargeted metabolomics methods including metabolite detection, annotation of unknown metabolites, and comparative quantification. In this work, we present MetExtract II, a software toolbox for detection of biologically derived compounds. It exploits SIL-specific isotope patterns and elution profiles in LC-HRMS(/MS) data. The toolbox consists of three complementary modules: M1 (AllExtract) uses mixtures of uniformly highly isotope-enriched and native biological samples for selective detection of the entire accessible metabolome. M2 (TracExtract) is particularly suited to probe the metabolism of endogenous or exogenous secondary metabolites and facilitates the untargeted screening of tracer derivatives from concurrently metabolized native and uniformly labeled tracer substances. With M3 (FragExtract), tandem mass spectrometry (MS/MS) fragments of corresponding native and uniformly labeled ions are evaluated and automatically assigned with putative sum formulas. Generated results can be graphically illustrated and exported as a comprehensive data matrix that contains all detected pairs of native and labeled metabolite ions that can be used for database queries, metabolome-wide internal standardization, and statistical analysis. The software, associated documentation, and sample data sets are freely available for noncommercial use at http://metabolomics-ifa.boku.ac.at/metextractII.
Highlights
Untargeted metabolomics research is the unbiased study of all low molecular weight compounds of a biological system
Reversed-phase (RP) liquid chromatography coupled to high-resolution mass spectrometry (LC-HRMS) is among the most commonly used analytical techniques, as it is well understood, highly customizable, robust, and requires little sample preparation
For gas chromatography coupled with mass spectrometry (GC-MS), Hiller et al.[6] have developed NTFD software for untargeted detection of isotopically labeled primary metabolites and calculation of mass isotopomer distributions
Summary
Untargeted metabolomics research is the unbiased study of all low molecular weight compounds of a biological system. Ion suppression/enhancement in the electrospray ionization source (ESI), which results from coelution of different compounds, can distort relative metabolite abundances. These effects may vary between different samples (e.g., experimental conditions) and complicate statistical analysis and biological interpretation. Stable isotope labeling (SIL) has gained much attention in the past years, reviewed for example by Klein and Heinzle.[4] It utilizes low-abundance naturally occurring stable isotopes (e.g., 13C, 15N) to artificially produce labeled metabolite molecules. Compared to their nonlabeled pendants, labeled metabolites are enriched with naturally occurring low-abundance stable isotopes and possess a higher molecular weight. Kessler et al.[10] developed the ALLocator online platform for mass isotopomer ratio analysis and compound annotation, and Leeming et al.[11] designed the HiTIME algorithm for untargeted detection of drug metabolites by use of isotopic labeling
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