Dynamic estimations of metabolic fluxes with constraint-based models and possibility theory
Living cells can be modelled by successively imposing known constraints that limit their behaviour, such as mass balances, thermodynamic laws or enzyme capacities. The resulting constraint-based models enclose all the functional states that the modelled cells may exhibit. Then, predictions can be obtained from the models in two main ways: adding experimental data to determine the state of cells at given conditions (MFA) or invoking an assumption of evolved optimal behaviour (FBA). Both MFA and FBA predictions are typically performed at steady state. However, it is easy to take extracellular dynamics into account. This work explores the benefits of using possibility theory to get these dynamic predictions. It will be shown that the possibilistic methods (a) provide rich estimates for time-varying fluxes and metabolite concentrations, (b) account for uncertainty and data scarcity, and (c) give predictions relaxing the optimality assumption of FBA. On the other hand, these methods could serve as basis for monitoring and fault detection systems in industrial bioprocesses. ; This research has been partially supported by the Spanish Government MINECO (1st and 3rd authors are grateful to grant CICYT DPI2011-28112-C04-01, and A. Sala is grateful to grant DPI2011-27845-C02-01). ; Llaneras Estrada, F.; Sala, A.; Picó Marco, JA. (2012). Dynamic estimations of metabolic fluxes with constraint-based models and possibility theory. Journal of Process Control. 22(10):1946-1955. https://doi.org/10.1016/j.jprocont.2012.09.001 ; S ; 1946 ; 1955 ; 22 ; 10