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Untargeted Profiling of Tracer-Derived Metabolites Using Stable Isotopic Labeling and Fast Polarity-Switching LC–ESI-HRMS

[Image: see text] An untargeted metabolomics workflow for the detection of metabolites derived from endogenous or exogenous tracer substances is presented. To this end, a recently developed stable isotope-assisted LC–HRMS-based metabolomics workflow for the global annotation of biological samples ha...

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Autores principales: Kluger, Bernhard, Bueschl, Christoph, Neumann, Nora, Stückler, Romana, Doppler, Maria, Chassy, Alexander W., Waterhouse, Andrew L., Rechthaler, Justyna, Kampleitner, Niklas, Thallinger, Gerhard G., Adam, Gerhard, Krska, Rudolf, Schuhmacher, Rainer
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Chemical Society 2014
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4255957/
https://www.ncbi.nlm.nih.gov/pubmed/25372979
http://dx.doi.org/10.1021/ac503290j
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author Kluger, Bernhard
Bueschl, Christoph
Neumann, Nora
Stückler, Romana
Doppler, Maria
Chassy, Alexander W.
Waterhouse, Andrew L.
Rechthaler, Justyna
Kampleitner, Niklas
Thallinger, Gerhard G.
Adam, Gerhard
Krska, Rudolf
Schuhmacher, Rainer
author_facet Kluger, Bernhard
Bueschl, Christoph
Neumann, Nora
Stückler, Romana
Doppler, Maria
Chassy, Alexander W.
Waterhouse, Andrew L.
Rechthaler, Justyna
Kampleitner, Niklas
Thallinger, Gerhard G.
Adam, Gerhard
Krska, Rudolf
Schuhmacher, Rainer
author_sort Kluger, Bernhard
collection PubMed
description [Image: see text] An untargeted metabolomics workflow for the detection of metabolites derived from endogenous or exogenous tracer substances is presented. To this end, a recently developed stable isotope-assisted LC–HRMS-based metabolomics workflow for the global annotation of biological samples has been further developed and extended. For untargeted detection of metabolites arising from labeled tracer substances, isotope pattern recognition has been adjusted to account for nonlabeled moieties conjugated to the native and labeled tracer molecules. Furthermore, the workflow has been extended by (i) an optional ion intensity ratio check, (ii) the automated combination of positive and negative ionization mode mass spectra derived from fast polarity switching, and (iii) metabolic feature annotation. These extensions enable the automated, unbiased, and global detection of tracer-derived metabolites in complex biological samples. The workflow is demonstrated with the metabolism of (13)C(9)-phenylalanine in wheat cell suspension cultures in the presence of the mycotoxin deoxynivalenol (DON). In total, 341 metabolic features (150 in positive and 191 in negative ionization mode) corresponding to 139 metabolites were detected. The benefit of fast polarity switching was evident, with 32 and 58 of these metabolites having exclusively been detected in the positive and negative modes, respectively. Moreover, for 19 of the remaining 49 phenylalanine-derived metabolites, the assignment of ion species and, thus, molecular weight was possible only by the use of complementary features of the two ion polarity modes. Statistical evaluation showed that treatment with DON increased or decreased the abundances of many detected metabolites.
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spelling pubmed-42559572014-12-09 Untargeted Profiling of Tracer-Derived Metabolites Using Stable Isotopic Labeling and Fast Polarity-Switching LC–ESI-HRMS Kluger, Bernhard Bueschl, Christoph Neumann, Nora Stückler, Romana Doppler, Maria Chassy, Alexander W. Waterhouse, Andrew L. Rechthaler, Justyna Kampleitner, Niklas Thallinger, Gerhard G. Adam, Gerhard Krska, Rudolf Schuhmacher, Rainer Anal Chem [Image: see text] An untargeted metabolomics workflow for the detection of metabolites derived from endogenous or exogenous tracer substances is presented. To this end, a recently developed stable isotope-assisted LC–HRMS-based metabolomics workflow for the global annotation of biological samples has been further developed and extended. For untargeted detection of metabolites arising from labeled tracer substances, isotope pattern recognition has been adjusted to account for nonlabeled moieties conjugated to the native and labeled tracer molecules. Furthermore, the workflow has been extended by (i) an optional ion intensity ratio check, (ii) the automated combination of positive and negative ionization mode mass spectra derived from fast polarity switching, and (iii) metabolic feature annotation. These extensions enable the automated, unbiased, and global detection of tracer-derived metabolites in complex biological samples. The workflow is demonstrated with the metabolism of (13)C(9)-phenylalanine in wheat cell suspension cultures in the presence of the mycotoxin deoxynivalenol (DON). In total, 341 metabolic features (150 in positive and 191 in negative ionization mode) corresponding to 139 metabolites were detected. The benefit of fast polarity switching was evident, with 32 and 58 of these metabolites having exclusively been detected in the positive and negative modes, respectively. Moreover, for 19 of the remaining 49 phenylalanine-derived metabolites, the assignment of ion species and, thus, molecular weight was possible only by the use of complementary features of the two ion polarity modes. Statistical evaluation showed that treatment with DON increased or decreased the abundances of many detected metabolites. American Chemical Society 2014-11-05 2014-12-02 /pmc/articles/PMC4255957/ /pubmed/25372979 http://dx.doi.org/10.1021/ac503290j Text en Copyright © 2014 American Chemical Society This is an open access article published under a Creative Commons Attribution (CC-BY) License (http://pubs.acs.org/page/policy/authorchoice_ccby_termsofuse.html) , which permits unrestricted use, distribution and reproduction in any medium, provided the author and source are cited.
spellingShingle Kluger, Bernhard
Bueschl, Christoph
Neumann, Nora
Stückler, Romana
Doppler, Maria
Chassy, Alexander W.
Waterhouse, Andrew L.
Rechthaler, Justyna
Kampleitner, Niklas
Thallinger, Gerhard G.
Adam, Gerhard
Krska, Rudolf
Schuhmacher, Rainer
Untargeted Profiling of Tracer-Derived Metabolites Using Stable Isotopic Labeling and Fast Polarity-Switching LC–ESI-HRMS
title Untargeted Profiling of Tracer-Derived Metabolites Using Stable Isotopic Labeling and Fast Polarity-Switching LC–ESI-HRMS
title_full Untargeted Profiling of Tracer-Derived Metabolites Using Stable Isotopic Labeling and Fast Polarity-Switching LC–ESI-HRMS
title_fullStr Untargeted Profiling of Tracer-Derived Metabolites Using Stable Isotopic Labeling and Fast Polarity-Switching LC–ESI-HRMS
title_full_unstemmed Untargeted Profiling of Tracer-Derived Metabolites Using Stable Isotopic Labeling and Fast Polarity-Switching LC–ESI-HRMS
title_short Untargeted Profiling of Tracer-Derived Metabolites Using Stable Isotopic Labeling and Fast Polarity-Switching LC–ESI-HRMS
title_sort untargeted profiling of tracer-derived metabolites using stable isotopic labeling and fast polarity-switching lc–esi-hrms
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4255957/
https://www.ncbi.nlm.nih.gov/pubmed/25372979
http://dx.doi.org/10.1021/ac503290j
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