Untargeted stable isotope-resolved metabolomics to assess the effect of PI3Kβ inhibition on metabolic pathway activities in a PTEN null breast cancer cell line
The combination of high-resolution LC-MS untargeted metabolomics with stable isotope-resolved tracing is a promising approach for the global exploration of metabolic pathway activities. In our established workflow we combine targeted isotopologue feature extraction with the non-targeted X13CMS routi...
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Frontiers Media S.A.
2022-10-01
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author | Marcel Lackner Marcel Lackner Sylvia K. Neef Sylvia K. Neef Stefan Winter Stefan Winter Sandra Beer-Hammer Sandra Beer-Hammer Bernd Nürnberg Matthias Schwab Matthias Schwab Matthias Schwab Matthias Schwab Ute Hofmann Ute Hofmann Mathias Haag Mathias Haag |
author_facet | Marcel Lackner Marcel Lackner Sylvia K. Neef Sylvia K. Neef Stefan Winter Stefan Winter Sandra Beer-Hammer Sandra Beer-Hammer Bernd Nürnberg Matthias Schwab Matthias Schwab Matthias Schwab Matthias Schwab Ute Hofmann Ute Hofmann Mathias Haag Mathias Haag |
author_sort | Marcel Lackner |
collection | DOAJ |
description | The combination of high-resolution LC-MS untargeted metabolomics with stable isotope-resolved tracing is a promising approach for the global exploration of metabolic pathway activities. In our established workflow we combine targeted isotopologue feature extraction with the non-targeted X13CMS routine. Metabolites, detected by X13CMS as differentially labeled between two biological conditions are subsequently integrated into the original targeted library. This strategy enables monitoring of changes in known pathways as well as the discovery of hitherto unknown metabolic alterations. Here, we demonstrate this workflow in a PTEN (phosphatase and tensin homolog) null breast cancer cell line (MDA-MB-468) exploring metabolic pathway activities in the absence and presence of the selective PI3Kβ inhibitor AZD8186. Cells were fed with [U-13C] glucose and treated for 1, 3, 6, and 24 h with 0.5 µM AZD8186 or vehicle, extracted by an optimized sample preparation protocol and analyzed by LC-QTOF-MS. Untargeted differential tracing of labels revealed 286 isotope-enriched features that were significantly altered between control and treatment conditions, of which 19 features could be attributed to known compounds from targeted pathways. Other 11 features were unambiguously identified based on data-dependent MS/MS spectra and reference substances. Notably, only a minority of the significantly altered features (11 and 16, respectively) were identified when preprocessing of the same data set (treatment vs. control in 24 h unlabeled samples) was performed with tools commonly used for label-free (i.e. w/o isotopic tracer) non-targeted metabolomics experiments (Profinder´s batch recursive feature extraction and XCMS). The structurally identified metabolites were integrated into the existing targeted isotopologue feature extraction workflow to enable natural abundance correction, evaluation of assay performance and assessment of drug-induced changes in pathway activities. Label incorporation was highly reproducible for the majority of isotopologues in technical replicates with a RSD below 10%. Furthermore, inter-day repeatability of a second label experiment showed strong correlation (Pearson R2 > 0.99) between tracer incorporation on different days. Finally, we could identify prominent pathway activity alterations upon PI3Kβ inhibition. Besides pathways in central metabolism, known to be changed our workflow revealed additional pathways, like pyrimidine metabolism or hexosamine pathway. All pathways identified represent key metabolic processes associated with cancer metabolism and therapy. |
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spelling | doaj.art-8d61d5899226475b8a84886d04636b102022-12-22T03:31:05ZengFrontiers Media S.A.Frontiers in Molecular Biosciences2296-889X2022-10-01910.3389/fmolb.2022.10046021004602Untargeted stable isotope-resolved metabolomics to assess the effect of PI3Kβ inhibition on metabolic pathway activities in a PTEN null breast cancer cell lineMarcel Lackner0Marcel Lackner1Sylvia K. Neef2Sylvia K. Neef3Stefan Winter4Stefan Winter5Sandra Beer-Hammer6Sandra Beer-Hammer7Bernd Nürnberg8Matthias Schwab9Matthias Schwab10Matthias Schwab11Matthias Schwab12Ute Hofmann13Ute Hofmann14Mathias Haag15Mathias Haag16Dr. Margarete Fischer-Bosch-Institute of Clinical Pharmacology, Stuttgart, GermanyUniversity of Tübingen, Tübingen, GermanyDr. Margarete Fischer-Bosch-Institute of Clinical Pharmacology, Stuttgart, GermanyUniversity of Tübingen, Tübingen, GermanyDr. Margarete Fischer-Bosch-Institute of Clinical Pharmacology, Stuttgart, GermanyUniversity of Tübingen, Tübingen, GermanyDepartment of Pharmacology, Experimental Therapy and Toxicology, Institute for Experimental and Clinical Pharmacology and Pharmacogenomics, Interfaculty Center for Pharmacogenomics and Drug Research (ICePhA), University of Tübingen, Tübingen, GermanyCluster of Excellence iFIT (EXC 2180), Image-Guided and Functionally Instructed Tumor Therapies, University of Tübingen, Tübingen, GermanyDepartment of Pharmacology, Experimental Therapy and Toxicology, Institute for Experimental and Clinical Pharmacology and Pharmacogenomics, Interfaculty Center for Pharmacogenomics and Drug Research (ICePhA), University of Tübingen, Tübingen, GermanyDr. Margarete Fischer-Bosch-Institute of Clinical Pharmacology, Stuttgart, GermanyUniversity of Tübingen, Tübingen, GermanyCluster of Excellence iFIT (EXC 2180), Image-Guided and Functionally Instructed Tumor Therapies, University of Tübingen, Tübingen, GermanyDepartments of Clinical Pharmacology and of Pharmacy and Biochemistry, University of Tübingen, Tübingen, GermanyDr. Margarete Fischer-Bosch-Institute of Clinical Pharmacology, Stuttgart, GermanyUniversity of Tübingen, Tübingen, GermanyDr. Margarete Fischer-Bosch-Institute of Clinical Pharmacology, Stuttgart, GermanyUniversity of Tübingen, Tübingen, GermanyThe combination of high-resolution LC-MS untargeted metabolomics with stable isotope-resolved tracing is a promising approach for the global exploration of metabolic pathway activities. In our established workflow we combine targeted isotopologue feature extraction with the non-targeted X13CMS routine. Metabolites, detected by X13CMS as differentially labeled between two biological conditions are subsequently integrated into the original targeted library. This strategy enables monitoring of changes in known pathways as well as the discovery of hitherto unknown metabolic alterations. Here, we demonstrate this workflow in a PTEN (phosphatase and tensin homolog) null breast cancer cell line (MDA-MB-468) exploring metabolic pathway activities in the absence and presence of the selective PI3Kβ inhibitor AZD8186. Cells were fed with [U-13C] glucose and treated for 1, 3, 6, and 24 h with 0.5 µM AZD8186 or vehicle, extracted by an optimized sample preparation protocol and analyzed by LC-QTOF-MS. Untargeted differential tracing of labels revealed 286 isotope-enriched features that were significantly altered between control and treatment conditions, of which 19 features could be attributed to known compounds from targeted pathways. Other 11 features were unambiguously identified based on data-dependent MS/MS spectra and reference substances. Notably, only a minority of the significantly altered features (11 and 16, respectively) were identified when preprocessing of the same data set (treatment vs. control in 24 h unlabeled samples) was performed with tools commonly used for label-free (i.e. w/o isotopic tracer) non-targeted metabolomics experiments (Profinder´s batch recursive feature extraction and XCMS). The structurally identified metabolites were integrated into the existing targeted isotopologue feature extraction workflow to enable natural abundance correction, evaluation of assay performance and assessment of drug-induced changes in pathway activities. Label incorporation was highly reproducible for the majority of isotopologues in technical replicates with a RSD below 10%. Furthermore, inter-day repeatability of a second label experiment showed strong correlation (Pearson R2 > 0.99) between tracer incorporation on different days. Finally, we could identify prominent pathway activity alterations upon PI3Kβ inhibition. Besides pathways in central metabolism, known to be changed our workflow revealed additional pathways, like pyrimidine metabolism or hexosamine pathway. All pathways identified represent key metabolic processes associated with cancer metabolism and therapy.https://www.frontiersin.org/articles/10.3389/fmolb.2022.1004602/fullnon-targeted analysis13C labelingLC-QTOF-MSglycolysisTCA cyclePI3K |
spellingShingle | Marcel Lackner Marcel Lackner Sylvia K. Neef Sylvia K. Neef Stefan Winter Stefan Winter Sandra Beer-Hammer Sandra Beer-Hammer Bernd Nürnberg Matthias Schwab Matthias Schwab Matthias Schwab Matthias Schwab Ute Hofmann Ute Hofmann Mathias Haag Mathias Haag Untargeted stable isotope-resolved metabolomics to assess the effect of PI3Kβ inhibition on metabolic pathway activities in a PTEN null breast cancer cell line Frontiers in Molecular Biosciences non-targeted analysis 13C labeling LC-QTOF-MS glycolysis TCA cycle PI3K |
title | Untargeted stable isotope-resolved metabolomics to assess the effect of PI3Kβ inhibition on metabolic pathway activities in a PTEN null breast cancer cell line |
title_full | Untargeted stable isotope-resolved metabolomics to assess the effect of PI3Kβ inhibition on metabolic pathway activities in a PTEN null breast cancer cell line |
title_fullStr | Untargeted stable isotope-resolved metabolomics to assess the effect of PI3Kβ inhibition on metabolic pathway activities in a PTEN null breast cancer cell line |
title_full_unstemmed | Untargeted stable isotope-resolved metabolomics to assess the effect of PI3Kβ inhibition on metabolic pathway activities in a PTEN null breast cancer cell line |
title_short | Untargeted stable isotope-resolved metabolomics to assess the effect of PI3Kβ inhibition on metabolic pathway activities in a PTEN null breast cancer cell line |
title_sort | untargeted stable isotope resolved metabolomics to assess the effect of pi3kβ inhibition on metabolic pathway activities in a pten null breast cancer cell line |
topic | non-targeted analysis 13C labeling LC-QTOF-MS glycolysis TCA cycle PI3K |
url | https://www.frontiersin.org/articles/10.3389/fmolb.2022.1004602/full |
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