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Novel column generation-based optimization approach for poly-pathway kinetic model applied to CHO cell culture

Hagrot, Erika, Oddsdóttir, Hildur Æsa, Mäkinen, Meeri, Forsgren, Anders, Chotteau, Véronique
Metabolic Engineering Communications 2019 v.8 pp. e00083
Chinese hamsters, algorithms, amino acids, animal ovaries, biochemical pathways, bioprocessing, cell culture, kinetics, mathematical models, metabolism, metabolites, prediction, secretion
Mathematical modelling can provide precious tools for bioprocess simulation, prediction, control and optimization of mammalian cell-based cultures. In this paper we present a novel method to generate kinetic models of such cultures, rendering complex metabolic networks in a poly-pathway kinetic model. The model is based on subsets of elementary flux modes (EFMs) to generate macro-reactions. Thanks to our column generation-based optimization algorithm, the experimental data are used to identify the EFMs, which are relevant to the data. Here the systematic enumeration of all the EFMs is eliminated and a network including a large number of reactions can be considered. In particular, the poly-pathway model can simulate multiple metabolic behaviors in response to changes in the culture conditions.We apply the method to a network of 126 metabolic reactions describing cultures of antibody-producing Chinese hamster ovary cells, and generate a poly-pathway model that simulates multiple experimental conditions obtained in response to variations in amino acid availability. A good fit between simulated and experimental data is obtained, rendering the variations in the growth, product, and metabolite uptake/secretion rates. The intracellular reaction fluxes simulated by the model are explored, linking variations in metabolic behavior to adaptations of the intracellular metabolism.