In silico co-factor balance estimation using constraint-based modelling informs metabolic engineering in Escherichia coli
Fig 8
Components of Cofactor Balance Assessment (CBA) pipeline and summarised workflow.
A stoichiometric model, flux distribution and a list of target reactions are required to call the CBA function in the python environment. Stoichiometric models contain reaction information, such as whether they consume or produce ATP and NAD(P). We used the E.coli Core stoichiometric model and the COBRApy package, and selected reactions were implemented to build the path to novel products. CBA classifies reactions in the model according to whether they are involved in the consumption or production of NAD(P)/ATP, assigns them a cofactor balance score, and groups them into categories as represented above. Finally, the total balance per category is calculated the total sum of flux and adjusted to provide a final value for each category. The result is a profile displaying the fraction of the total cofactor produced involved in maintenance, biomass, target and waste production.