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Systems-level analysis of isotopic labeling in untargeted metabolomic data by X13CMS

Nature Protocols volume 14, pages 1970–1990 (2019)Cite this article

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Abstract

Identification of previously unreported metabolites (so-called ‘unknowns’) in untargeted metabolomic data has become an increasingly active area of research. Considerably less attention, however, has been dedicated to identifying unknown metabolic pathways. Yet, for each unknown metabolite structure, there is potentially a yet-to-be-discovered chemical transformation. Elucidating these biochemical connections is essential to advancing our knowledge of cellular metabolism and can be achieved by tracking an isotopically labeled precursor to an unexpected product. In addition to their role in mapping metabolic fates, isotopic labels also provide critical insight into pathway dynamics (i.e., metabolic fluxes) that cannot be obtained from conventional label-free metabolomic analyses. When labeling is compared quantitatively between conditions, for example, isotopic tracers can enable relative pathway activities to be inferred. To discover unexpected chemical transformations or unanticipated differences in metabolic pathway activities, we have developed X13CMS, a platform for analyzing liquid chromatography/mass spectrometry (LC/MS) data at the systems level. After providing cells, animals, or patients with an isotopically enriched metabolite (e.g., 13C, 15N, or 2H), X13CMS identifies compounds that have incorporated the isotopic tracer and reports the extent of labeling for each. The analysis can be performed with a single condition, or isotopic fates can be compared between multiple conditions. The choice of which metabolite to enrich and which isotopic label to use is highly context dependent, but 13C-glucose and 13C-glutamine are often applied because they feed a large number of metabolic pathways. X13CMS is freely available.

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Fig. 1: Tracking of glucose labels through central carbon metabolism.
Fig. 2: Tracking multiple isotopic labels in the same experiment requires high-resolution mass spectrometry.
Fig. 3: General workflow for global tracking of isotopic labels from an enriched nutrient with untargeted metabolomics.
Fig. 4: Schematic illustrating the relationship between steps in the overall X13CMS workflow.
Fig. 5: Representative data for citrate.
Fig. 6: Comprehensive tracking of isotopic labels from uniformly 13C-labeled lactate with untargeted metabolomics revealed that lactate carbon fuels the TCA cycle and lipid synthesis in some cancer cells.
Fig. 7: Comprehensive tracking of isotopic labels from uniformly 13C-labeled 2HG with untargeted metabolomics revealed that 2HG is not readily metabolized in colorectal carcinoma cells harboring mutations in isocitrate dehydrogenase 1.
Fig. 8: After 6 h of labeling with uniformly 13C-labeled glucose, X13CMS identified differences in the enrichment of palmitate between proliferating and quiescent fibroblasts.
Fig. 9: Graphical user interface of MSConvert.
Fig. 10: Representative plots created by X13CMS.

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Data availability

A zip file with example data can be downloaded from http://pattilab.wustl.edu/software/x13cms/x13cms.php or http://pattilab.wustl.edu/download/Example.zip.

Code availability

X13CMS is freely available at http://pattilab.wustl.edu/software/x13cms/x13cms.php.

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Acknowledgements

G.J.P. received financial support for this work from National Institutes of Health grants R35ES028365, U01CA235482, and R24OD024624, as well as the Alfred P. Sloan Foundation, the Pew Scholars Program in the Biomedical Sciences, and the Edward Mallinckrodt, Jr., Foundation. We thank N.G. Mahieu for his contributions to Figure 2.

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Authors and Affiliations

  1. Department of Chemistry, Washington University in St. Louis, St. Louis, MO, USA

    Elizabeth M. Llufrio, Kevin Cho & Gary J. Patti

  2. Department of Medicine, Washington University in St. Louis, St. Louis, MO, USA

    Kevin Cho & Gary J. Patti

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All authors equally developed and tested the protocol based on ref. 24. All authors drafted the manuscript and contributed to manuscript editing and revision.

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Correspondence to Gary J. Patti.

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G.J.P. is a scientific advisory board member for Cambridge Isotope Laboratories and a recipient of the 2017 Agilent Early Career Professor Award. The remaining authors declare no competing interests.

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Huang, X. et al. Anal. Chem. 86, 1632–1639 (2014): https://pubs.acs.org/doi/10.1021/ac403384n

Key data used in this protocol

A zip file with example data can be downloaded from http://pattilab.wustl.edu/software/x13cms/x13cms.php or http://pattilab.wustl.edu/download/Example.zip

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Supplementary Methods

Representative example of preparing labeled samples for untargeted metabolomics.

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Llufrio, E.M., Cho, K. & Patti, G.J. Systems-level analysis of isotopic labeling in untargeted metabolomic data by X13CMS. Nat Protoc 14, 1970–1990 (2019). https://doi.org/10.1038/s41596-019-0167-1

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