You have full access to this open access article. However, the usage of positional labeling information for 13 C-MFA faces two challenges: 1 The mass spectrometric acquisition of a large number of potentially interfering mass transitions may hamper accuracy and sensitivity.
For this purpose, we draw on accurate mass spectrometry, selectively labeled standards, and published fragmentation pathways to structurally annotate all dominant mass peaks of a large collection of metabolites, some of which with a complete fragmentation pathway. Our 13 C-data proof that heuristic fragmentation rules often fail to yield correct fragment structures and we expose common pitfalls in the structural annotation of product ions.
We show that the positionally resolved 13 C-label information contained in the product ions that we structurally annotated allows to infer the entire isotopomer distribution of several central metabolism intermediates, which is experimentally demonstrated for malate using quadrupole-time-of-flight MS technology.
Finally, the inclusion of the label information from a subset of these fragments improves flux precision in a Corynebacterium glutamicum model of the central carbon metabolism. On the experimental side, it relies on measuring the 13 C-label distribution in central metabolism intermediates; a task that is most commonly accomplished by mass spectrometry MS [ 1 ].
This distribution is then evaluated by means of a carbon atom transition model to determine in vivo reaction rates [ 2 — 5 ]. The labeling experiment in combination with the model-based data evaluation is known as 13 C-MFA [ 6 ].
