Summary Carbon fluxes throughout metabolic networks can be investigated experimentally through 13 C‐isotope labelling experiments ( 13 C‐ILE) and 13 C‐metabolic flux analysis ( 13 C‐MFA). 13 C‐ILE involves the application of isotopically labelled substrates to a biological system to detect label distribution throughout the metabolic network, while 13 C‐MFA is a computational approach that quantitatively estimates fluxes by fitting isotope‐labelling data to metabolic network models. 13 C‐MFA can encompass more metabolic reactions and provide subcellular flux estimates that remain difficult to validate directly using current 13 C‐ILE approaches. Overcoming major bottlenecks of 13 C‐ILE is thus needed to improve and validate 13 C‐MFA. Mass spectrometry (MS)‐based 13 C‐ILE has been carried out mostly at isotopologue rather than isotopomer level. Isotopologues differ in their isotopic composition, while isotopomers have the same isotopic composition but at different positions within the molecule. Thus, 13 C‐isotopomer approaches discriminate which atoms of a metabolite have received 13 C, enabling better comprehension of the regulation of metabolic pathways. Here, we highlight the major challenges to improve MS‐based positional 13 C analysis and discuss the advantages of this approach over MS‐based methods with low or no carbon‐positional resolution. We further demonstrate how positional 13 C analysis has been used to estimate enzyme activity in vivo and to study plant metabolism.
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Lima et al. (2026) studied this question.
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