A roadmap for interpreting 13C metabolite labeling patterns from cells
Measuring intracellular metabolism has increasingly led to important insights in biomedical research. [superscript 13]C tracer analysis, although less information-rich than quantitative [superscript 13]C flux analysis that requires computational data integration, has been established as a time-effic...
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| Format: | Article |
| Language: | en_US |
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Elsevier
2017
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| Online Access: | http://hdl.handle.net/1721.1/107921 https://orcid.org/0000-0001-6909-4568 |
| Summary: | Measuring intracellular metabolism has increasingly led to important insights in biomedical research. [superscript 13]C tracer analysis, although less information-rich than quantitative [superscript 13]C 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 nutrientcontributions. Here, we review selected key issues in interpreting [superscript 13]C metabolite labeling patterns, with the goal of drawing accurate conclusions from steady state and dynamic stable isotopic tracer experiments |
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