A roadmap for interpreting 13C metabolite labeling patterns from cells

Joerg M. Buescher, Maciek R. Antoniewicz, Laszlo G. Boros, Shawn C. Burgess, Henri Brunengraber, Clary B. Clish, Ralph J. DeBerardinis, Olivier Feron, Christian Frezza, Bart Ghesquiere, Eyal Gottlieb, Karsten Hiller, Russell G. Jones, Jurre J. Kamphorst, Richard G. Kibbey, Alec C. Kimmelman, Jason W. Locasale, Sophia Y. Lunt, Oliver D.K. Maddocks, Craig MalloyChristian M. Metallo, Emmanuelle J. Meuillet, Joshua Munger, Katharina Nöh, Joshua D. Rabinowitz, Markus Ralser, Uwe Sauer, Gregory Stephanopoulos, Julie St-Pierre, Daniel A. Tennant, Christoph Wittmann, Matthew G. Vander Heiden, Alexei Vazquez, Karen Vousden, Jamey D. Young, Nicola Zamboni, Sarah Maria Fendt

Research output: Contribution to journalReview articlepeer-review

442 Scopus citations


Measuring intracellular metabolism has increasingly led to important insights in biomedical research. 13C tracer analysis, although less information-rich than quantitative 13C flux analysis that requires computational data integration, has been established as a time-efficient method to unravel relative pathway activities, qualitative changes in pathway contributions, and nutrient contributions. Here, we review selected key issues in interpreting 13C metabolite labeling patterns, with the goal of drawing accurate conclusions from steady state and dynamic stable isotopic tracer experiments.

Original languageEnglish (US)
Pages (from-to)189-201
Number of pages13
JournalCurrent Opinion in Biotechnology
StatePublished - Aug 1 2015

All Science Journal Classification (ASJC) codes

  • Bioengineering
  • Biotechnology
  • Biomedical Engineering


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