4.5 Article

Error propagation in constraint-based modeling of Chinese hamster ovary cells

Journal

BIOTECHNOLOGY JOURNAL
Volume 16, Issue 4, Pages -

Publisher

WILEY-V C H VERLAG GMBH
DOI: 10.1002/biot.202000320

Keywords

Chinese hamster ovary cells; error propagation; exchange rates; genome‐ scale metabolic modeling; flux balance analysis

Funding

  1. PhD program BioToP of the Austrian Science Fund (FWF Project) [W1224]
  2. COMET center acib - BMK
  3. BMDW
  4. SFG
  5. Standortagentur Tirol
  6. Government of Lower Austria
  7. Vienna Business Agency

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This study investigated the impact of sampling frequency and measurement errors of metabolite concentrations during batch culture on the accuracy of calculated exchange rates, as well as how this error propagates into FBA predictions of growth rates. The results showed that accurate measurements of essential amino acids with low uptake rates are crucial for FBA predictions, followed by a sufficient number of analyzed time points. High measurement accuracy and sampling frequency are essential for reliably predicting growth rate differences of cell lines.
Chinese hamster ovary (CHO) cells are the most popular mammalian cell factories for the production of glycosylated biopharmaceuticals. To further increase titer and productivity and ensure product quality, rational system-level engineering strategies based on constraint-based metabolic modeling, such as flux balance analysis (FBA), have gained strong interest. However, the quality of FBA predictions depends on the accuracy of the experimental input data, especially on the exchange rates of extracellular metabolites. Yet, it is not standard practice to devote sufficient attention to the accurate determination of these rates. In this work, we investigated to what degree the sampling frequency during a batch culture and the measurement errors of metabolite concentrations influence the accuracy of the calculated exchange rates and further, how this error then propagates into FBA predictions of growth rates. We determined that accurate measurements of essential amino acids with low uptake rates are crucial for the accuracy of FBA predictions, followed by a sufficient number of analyzed time points. We observed that the measured difference in growth rates of two cell lines can only be reliably predicted when both high measurement accuracy and sampling frequency are ensured.

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