Amino acid metabolism in Chinese hamster ovary cell culture

Abstract

The present thesis focuses on amino acids (a.a.) and their metabolism by Chinese hamster ovary cells, the workhorse of the multibillion dollar biopharmaceutical industry. The aim of the research was to explore a.a. transport and metabolism and define optimal operating conditions during fed-batch culture, which is the most common process mode used industrially. A fast and reliable way to calculate a.a. concentration ranges in media and feeds is of vital importance, as a.a. are the monomers of proteins, which account for 70% of dry cell weight. The desired recombinant product of bioprocesses is typically also a protein. The transport of a.a. into the cells was studied at the mRNA level of a.a. transporters for the first time in a bioprocessing context. The presented results demonstrate that a.a. transport is not the limiting step for recombinant protein formation. Also, the study allowed for a staged feeding strategy to be designed, where a.a. were not fed altogether. Following linear projection of an integral of viable cell concentration target and using the specific a.a. consumption rates during batch culture, six feeds were formulated containing a.a. and glucose. Three designs were based on the results of the a.a. transport study; however, they underperformed in comparison to the other feeds. In the latter, all nutrients were fed at the same time, resulting in cell culture performance comparable to that obtained with a commercial feed that was tested in parallel. This renders the presented method the first to define a traceable quantitative way to calculate amount of nutrients in the feeds. Flux balance analysis, a powerful technique that allows for investigation of intracellular dynamics, was used to analyse the metabolic data. An enhanced intracellular network was created by coupling two pre-existing in the literature that also for the first time included the glycosylation of the host proteins in the biomass equation. Finally, a novel methodology was developed and coded in R to calculate specific rates of consumption/production of various metabolites in cell culture. The methodology couples mass balances for fed-batch culture operation with constructed vectors of the sampling and feeding schemes. This can be further developed to a bioprocess relevant software platform for analysing cell culture data.