Inclusion of maintenance energy improves the intracellular flux predictions of CHO.

Diana Széliová,David E Ruckerbauer,Marcus Weinguny,Isabel Rocha,Jerneja Štor,Gabriele Lhota,Michael Hanscho,Jürgen Zanghellini,Isabella Thiel,Nicole Borth

doi:10.1371/journal.pcbi.1009022

Abstract

Chinese hamster ovary (CHO) cells are the leading platform for the production of biopharmaceuticals with human-like glycosylation. The standard practice for cell line generation relies on trial and error approaches such as adaptive evolution and high-throughput screening, which typically take several months. Metabolic modeling could aid in designing better producer cell lines and thus shorten development times. The genome-scale metabolic model (GSMM) of CHO can accurately predict growth rates. However, in order to predict rational engineering strategies it also needs to accurately predict intracellular fluxes. In this work we evaluated the agreement between the fluxes predicted by parsimonious flux balance analysis (pFBA) using the CHO GSMM and a wide range of 13C metabolic flux data from literature. While glycolytic fluxes were predicted relatively well, the fluxes of tricarboxylic acid (TCA) cycle were vastly underestimated due to too low energy demand. Inclusion of computationally estimated maintenance energy significantly improved the overall accuracy of intracellular flux predictions. Maintenance energy was therefore determined experimentally by running continuous cultures at different growth rates and evaluating their respective energy consumption. The experimentally and computationally determined maintenance energy were in good agreement. Additionally, we compared alternative objective functions (minimization of uptake rates of seven nonessential metabolites) to the biomass objective. While the predictions of the uptake rates were quite inaccurate for most objectives, the predictions of the intracellular fluxes were comparable to the biomass objective function.

Highlights

Chinese hamster ovary (CHO) cells are currently the leading production host for the synthesis of complex biopharmaceuticals with human-like post-translational modifications [1]
Flux data were mapped onto the genomescale metabolic model iCHO1766 [8] and compared to parsimonious flux balance analysis (pFBA) predictions based on biomass maximization
The iCHO1766 model takes into account energy demands for the synthesis of biomass and recombinant proteins, it currently lacks a value for nongrowth associated maintenance energy—the energy needed for processes such as turnover and repair of macromolecules or maintenance of concentration gradients (e.g. Na+/K+ and Ca2+ ATPases) [35]

Summary

Introduction

Chinese hamster ovary (CHO) cells are currently the leading production host for the synthesis of complex biopharmaceuticals with human-like post-translational modifications [1]. The increasing demand for CHO-derived products requires advances in cell line and process development. Significant improvements in productivity, product yield and growth rate of the cells have been achieved by media optimization and high-throughput screening for good producers [3, 4]. The development of high producer cell lines is laborious, expensive and takes several months for each new product [5]. Systems biology approaches such as metabolic modeling might push the productivity even further, shorten the development times for new products and improve the product quality by elucidating potential bottlenecks in metabolism and suggesting genetic engineering or feed/media optimization strategies [6, 7]

Methods

Results

Discussion

Conclusion