¹³C MFA

The intra cellular metabolism is an essential system for any living organism, which involves a myriad of different substrates, enzymes and metabolic by products that together form a large extensive metabolic network. The state of this metabolic network will impact every aspect of the cells function and is a key contributor to the differentiation and evolution of the cell. However, the task to accurately quantifying the conversion rates between different metabolites in the network, the metabolic fluxes, remains challenging. The gold standard for estimating metabolic fluxes are isotopically metabolic flux analysis (MFA).

MFA revolves around feeding isotopically labelled substrates to the cell system, allowing the substrate to be metabolised and the isotopic tracer to be distributed throughout the system. This will result in isotopic isomers (isotopomers) of the metabolites in the network, i.e. variants of the same metabolites that have different isotope configurations. The abundance of these of these different isotopmers can be measured via for instance liquid chromatography-mass spectrometry (LC-MS). Such measurements will result in relative distributions of isotopmers with different mass. The combination of these mass isotopomer distributions (MIDs) form different metabolites provide a unique picture of the current metabolic state. As the metabolic fluxes will determine where the isotope tracers end up, once the systems have reached a steady-state the MIDs contain information regarding the metabolic flux state that formed them. This means that if we can construct computational models that estimates the MIDs as a function of the metabolic fluxes, we can get an estimate of what the intracellular metabolic fluxes are.

The model structure for these models is defined by the metabolic network’s stoichiometry, as well as mappings for the specific atom transitions in each reaction. For example, if ¹³C is used as the labelling isotope, the model structure will contain the atom maps for all carbon atoms that might be metabolically replaced by a ¹³C atom. By defining what atom transitions occurs in each reaction and by defining the isotope labelling patterns of the network substrates, the MIDs can be described by a system of equations that is parameterized by the metabolic fluxes.

This means that if we assume that the metabolic system is at steady-state i.e. the net change of isotopically labelled metabolites does not change over time, these equations can be used to calculate the resulting MIDs form a given set of metabolic flux values. Thus, we can estimate which metabolic fluxes produced the MIDs we have measure and as such get an estimate of what the metabolism looked like during our experimental conditions.

This allows us to study metabolic reprogramming associated with disease progression in for example cancer tumour formation such as in liver metastasis, development of metabolic syndrome, and neurodegenerative diseases such as Parkinson’s disease. But it also allows us to map the metabolism for individualized digital twin models.