Abstract
BackgroundThe progress in the "-omic" sciences has allowed a deeper knowledge on many biological systems with industrial interest. This knowledge is still rarely used for advanced bioprocess monitoring and control at the bioreactor level. In this work, a bioprocess control method is presented, which is designed on the basis of the metabolic network of the organism under consideration. The bioprocess dynamics are formulated using hybrid rigorous/data driven systems and its inherent structure is defined by the metabolism elementary modes.ResultsThe metabolic network of the system under study is decomposed into elementary modes (EMs), which are the simplest paths able to operate coherently in steady-state. A reduced reaction mechanism in the form of simplified reactions connecting substrates with end-products is obtained. A dynamical hybrid system integrating material balance equations, EMs reactions stoichiometry and kinetics was formulated. EMs kinetics were defined as the product of two terms: a mechanistic/empirical known term and an unknown term that must be identified from data, in a process optimisation perspective. This approach allows the quantification of fluxes carried by individual elementary modes which is of great help to identify dominant pathways as a function of environmental conditions. The methodology was employed to analyse experimental data of recombinant Baby Hamster Kidney (BHK-21A) cultures producing a recombinant fusion glycoprotein. The identified EMs kinetics demonstrated typical glucose and glutamine metabolic responses during cell growth and IgG1-IL2 synthesis. Finally, an online optimisation study was conducted in which the optimal feeding strategies of glucose and glutamine were calculated after re-estimation of model parameters at each sampling time. An improvement in the final product concentration was obtained as a result of this online optimisation.ConclusionThe main contribution of this work is a novel bioreactor optimal control method that uses detailed information concerning the metabolism of the underlying biological system. Moreover, the method allows the identification of structural modifications in metabolism over batch time.
Highlights
The progress in the "-omic" sciences has allowed a deeper knowledge on many biological systems with industrial interest
The method contemplates the possibility of missing parts of the metabolism and of unknown reaction kinetics and underlying transduction mechanisms
The bioreactor dynamics are described by the material balance equations of each component occurring in the elementary modes (EMs)
Summary
The progress in the "-omic" sciences has allowed a deeper knowledge on many biological systems with industrial interest This knowledge is still rarely used for advanced bioprocess monitoring and control at the bioreactor level. In general the number of reactions exceeds the number of metabolites resulting in undetermined systems of algebraic equations [1]. Such systems can be solved after measurement of the missing fluxes, which are typically uptake rates of substrates and secretion rates of metabolites, and intracellular fluxes when the former are not enough. The determination of metabolic flux distribution in undetermined systems may be obtained by flux-balance analysis (FBA) [2]. Multiple optima are obtained which are a consequence of the existence of redundant pathways in the metabolic network conferring structural robustness to cells [7]
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