Journal
METABOLIC ENGINEERING
Volume 61, Issue -, Pages 288-300Publisher
ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.ymben.2020.06.002
Keywords
Chinese hamster ovary; Biomass composition; Metabolic modeling; Flux balance analysis; Uptake rates; Secretion rates
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Funding
- Federal Ministry for Digital and Economic Affairs (bmwd)
- Federal Ministry for Transport, Innovation and Technology (bmvit)
- Styrian Business Promotion Agency SFG
- Standortagentur Tirol, Government of Lower Austria
- ZIT Technology Agency of the City of Vienna through the COMET-Funding Program
- PhD program BioToP (Biomolecular Technology of Proteins) of the Austrian Science Fund (FWF Project) [W1224]
- Novo Nordisk Foundation [NNF10CC1016517, NNF14OC0009473]
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Background: Cell line-specific, genome-scale metabolic models enable rigorous and systematic in silico investigation of cellular metabolism. Such models have recently become available for Chinese hamster ovary (CHO) cells. However, a key ingredient, namely an experimentally validated biomass function that summarizes the cellular composition, was so far missing. Here, we close this gap by providing extensive experimental data on the biomass composition of 13 parental and producer CHO cell lines under various conditions. Results: We report total protein, lipid, DNA, RNA and carbohydrate content, cell dry mass, and detailed protein and lipid composition. Furthermore, we present meticulous data on exchange rates between cells and environment and provide detailed experimental protocols on how to determine all of the above. The biomass composition is converted into cell lineand condition-specific biomass functions for use in cell line-specific, genomescale metabolic models of CHO. Finally, flux balance analysis (FBA) is used to demonstrate consistency between in silico predictions and experimental analysis. Conclusions: Our study reveals a strong variability of the total protein content and cell dry mass across cell lines. However, the relative amino acid composition is independent of the cell line and condition and thus needs not be explicitly measured for each new cell line. In contrast, the lipid composition is strongly influenced by the growth media and thus will have to be determined in each case. These cell line-specific variations in biomass composition have a small impact on growth rate predictions with FBA, as inaccuracies in the predictions are rather dominated by inaccuracies in the exchange rate spectra. Cell-specific biomass variations only become important if the experimental errors in the exchange rate spectra drop below twenty percent.
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