Hamideh Fouladiha1, Sayed-Amir Marashi2,3, Shangzhong Li4,5, Zerong Li5,6, Helen O Masson4,5, Behrouz Vaziri7, Nathan E Lewis4,5,6. 1. Department of Biotechnology, College of Science, University of Tehran, Tehran, Iran. 2. Department of Biotechnology, College of Science, University of Tehran, Tehran, Iran. marashi@ut.ac.ir. 3. Department of Biotechnology, University of Tehran, Enghelab Avenue, 1417614411, Tehran, Iran. marashi@ut.ac.ir. 4. Department of Bioengineering, University of California, San Diego, USA. 5. Novo Nordisk Foundation Center for Biosustainability, University of California, San Diego, USA. 6. Department of Pediatrics, University of California, San Diego, USA. 7. Protein Chemistry and Proteomics Laboratory, Biotechnology Research Center, Pasteur Institute of Iran, Tehran, Iran.
Abstract
OBJECTIVE: Chinese hamster ovary (CHO) cells are the leading cell factories for producing recombinant proteins in the biopharmaceutical industry. In this regard, constraint-based metabolic models are useful platforms to perform computational analysis of cell metabolism. These models need to be regularly updated in order to include the latest biochemical data of the cells, and to increase their predictive power. Here, we provide an update to iCHO1766, the metabolic model of CHO cells. RESULTS: We expanded the existing model of Chinese hamster metabolism 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 iCHO2101. In this updated model, the number of reactions and pathways capable of carrying flux is substantially increased. CONCLUSIONS: The present CHO model is an important step towards more complete metabolic models of CHO cells.
OBJECTIVE:Chinese hamsterovary (CHO) cells are the leading cell factories for producing recombinant proteins in the biopharmaceutical industry. In this regard, constraint-based metabolic models are useful platforms to perform computational analysis of cell metabolism. These models need to be regularly updated in order to include the latest biochemical data of the cells, and to increase their predictive power. Here, we provide an update to iCHO1766, the metabolic model of CHO cells. RESULTS: We expanded the existing model of Chinese hamster metabolism 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 iCHO2101. In this updated model, the number of reactions and pathways capable of carrying flux is substantially increased. CONCLUSIONS: The present CHO model is an important step towards more complete metabolic models of CHO cells.
Entities:
Keywords:
CHO cells; Constraint-based modeling; Gap-filling; Metabolic network models; Systems biology
Authors: Nuno Carinhas; Rui Oliveira; Paula Marques Alves; Manuel J T Carrondo; Ana P Teixeira Journal: Trends Biotechnol Date: 2012-04-26 Impact factor: 19.536
Authors: Scott A Becker; Adam M Feist; Monica L Mo; Gregory Hannum; Bernhard Ø Palsson; Markus J Herrgard Journal: Nat Protoc Date: 2007 Impact factor: 13.491
Authors: Alexander Dobin; Carrie A Davis; Felix Schlesinger; Jorg Drenkow; Chris Zaleski; Sonali Jha; Philippe Batut; Mark Chaisson; Thomas R Gingeras Journal: Bioinformatics Date: 2012-10-25 Impact factor: 6.937
Authors: Nuno Carinhas; Tiago M Duarte; Laura C Barreiro; Manuel J T Carrondo; Paula M Alves; Ana P Teixeira Journal: Biotechnol Bioeng Date: 2013-07-07 Impact factor: 4.530
Authors: Matthew N Benedict; Michael B Mundy; Christopher S Henry; Nicholas Chia; Nathan D Price Journal: PLoS Comput Biol Date: 2014-10-16 Impact factor: 4.475