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Poly-pathway model, a novel approach to simulate multiple metabolic states by reaction network-based model - Application to amino acid depletion in CHO cell culture
KTH, School of Biotechnology (BIO), Industrial Biotechnology. (Cell Technology Group)
KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Optimization and Systems Theory.
KTH, School of Biotechnology (BIO), Industrial Biotechnology.ORCID iD: Cell Technology Group
KTH, School of Electrical Engineering (EES), Automatic Control.
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2016 (English)In: Journal of Biotechnology, ISSN 0168-1656, E-ISSN 1873-4863, Vol. 228, 37-49 p.Article in journal (Refereed) PublishedText
Abstract [en]

Mammalian cell lines are characterized by a complex and flexible metabolism. A single model that could describe the variations in metabolic behavior triggered by variations in the culture conditions would be a precious tool in bioprocess development. In this paper, we introduce an approach to generate a poly-pathway model and use it to simulate diverse metabolic states triggered in response to removal, reduction or doubling of amino acids in the culture medium of an antibody-producing CHO cell line. Macro-reactions were obtained from a metabolic network via elementary flux mode enumeration and the fluxes were modeled by kinetic equations with saturation and inhibition effects from external medium components. Importantly, one set of kinetic parameters was estimated using experimental data of the multiple metabolic states. A good fit between the model and the data was obtained for the majority of the metabolites and the experimentally observed flux variations. We find that the poly-pathway modeling approach is promising for the simulation of multiple metabolic states.

Place, publisher, year, edition, pages
Elsevier, 2016. Vol. 228, 37-49 p.
Keyword [en]
Modeling, Metabolic flux analysis, Elementary flux modes, Chinese hamster ovary cells, Amino acid metabolism, Poly-pathway model
National Category
Biological Sciences
Identifiers
URN: urn:nbn:se:kth:diva-189659DOI: 10.1016/j.jbiotec.2016.03.015ISI: 000377786500008PubMedID: 27060554ScopusID: 2-s2.0-84973333168OAI: oai:DiVA.org:kth-189659DiVA: diva2:949262
Funder
VINNOVA
Note

QC 20160718

Available from: 2016-07-18 Created: 2016-07-11 Last updated: 2016-07-18Bibliographically approved

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Hagrot, ErikaOddsdóttir, Hildur AesaHosta, Joan GonzalezJacobsen, Elling W.Chotteau, Veronique
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