Systematically gap-filling the genome-scale model of CHO cells

Chinese hamster ovary (CHO) cells are the leading cell factories for producing recombinant proteins in the biopharmaceutical industry. In comparison to other mammalian cell types, handling of CHO cells is relatively easy. For example, CHO cells can grow in suspension and reach high cellular densities in bioreactors. Therefore, studying the metabolism of CHO cells to improve the bio-production of these cells is an important subject of research. In this regard, constraintbased metabolic models are useful platforms to perform computational analysis of cell metabolism. Here, we expanded the existing model of Chinese hamster metabolism (CHO1766) with the help of four gap-filling approaches, leading to the addition of 773 new reactions and 335 new genes. We incorporated these into an updated genome-scale metabolic network model of CHO cells, named CHO2101. This updated model substantially increased the number of reactions capable of carrying flux. The addition of these new data provides an important step towards more complete metabolic models of CHO cells.