Advanced process monitoring and feedback control to enhance cell culture process production and robustness

The metabolism of Chinese Hamster Ovary (CHO) cells in a production environment has been extensively investigated. However, a key metabolic transition, the switch from lactate production to lactate consumption, remains enigmatic. Though commonly observed in CHO cultures, the mechanism(s) by which this metabolic shift is triggered is unknown. Despite this, efforts to control the switch have emerged due to the association of lactate consumption with improved cell growth and productivity. This review aims to consolidate current theories surrounding the lactate switch. The influence of pH, NAD /NADH, pyruvate availability and mitochondrial function on lactate consumption are explored. A hypothesis based on the cellular redox state is put forward to explain the onset of lactate consumption. Various techniques implemented to control the lactate switch, including manipulation of the culture environment, genetic engineering, and cell line selection are also discussed.

Section: Media and Process Controlmentioning

confidence: 99%

Mechanisms driving the lactate switch in Chinese hamster ovary cells

Hartley

Walker

Chung

et al. 2018

“…Even novel measurement concepts in the process analytical technology initiative mostly measure bulk compositions and relate this information to cellular regulations and effects. Exemplary, online glucose measurements (Zhang et al, ) or RAMAN spectroscopy (Berry et al, ; Matthews et al, ) are discussed in the literature. These measurement concepts are very useful to understand processes in a holistic way, but only partially useful to gain an understanding of population heterogeneity with changing cell metabolism.…”

Section: Resultsmentioning

confidence: 99%

Process‐induced cell cycle oscillations in CHO cultures: Online monitoring and model‐based investigation

Möller

Bhat

Riecken

et al. 2019

The influence of process strategies on the dynamics of cell population heterogeneities in mammalian cell culture is still not well understood. We recently found that the progression of cells through the cell cycle causes metabolic regulations with variable productivities in antibody‐producing Chimese hamster ovary (CHO) cells. On the other hand, it is so far unknown how bulk cultivation conditions, for example, variable nutrient concentrations depending on process strategies, can influence cell cycle‐derived population dynamics. In this study, process‐induced cell cycle synchronization was assessed in repeated‐batch and fed‐batch cultures. An automated flow cytometry set‐up was developed to measure the cell cycle distribution online, using antibody‐producing CHO DP‐12 cells transduced with the cell cycle‐specific fluorescent ubiquitination‐based cell cycle indicator (FUCCI) system. On the basis of the population‐resolved model, feeding‐induced partial self‐synchronization was predicted and the results were evaluated experimentally. In the repeated‐batch culture, stable cell cycle oscillations were confirmed with an oscillating G1 phase distribution between 41% and 72%. Furthermore, oscillations of the cell cycle distribution were simulated and determined in a (bolus) fed‐batch process with up to 25×106 cells/ml. The cell cycle synchronization arose with pulse feeding only and ceased with continuous feeding. Both simulated and observed oscillations occurred at higher frequencies than those observable based on regular (e.g., daily) sample analysis, thus demonstrating the need for high‐frequency online cell cycle analysis. In summary, we showed how experimental methods combined with simulations enable the improved assessment of the effects of process strategies on the dynamics of cell cycle‐dependent population heterogeneities. This provides a novel approach to understand cell cycle regulations, control cell population dynamics, avoid inadvertently induced oscillations of cell cycle distributions and thus to improve process stability and efficiency.

“…Bolus glucose additions were fed to maintain the glucose concentration above 2 g/L at designated time points. This is described in more detail elsewhere (Gilbert et al, ; Huang et al, ; Zhang et al, ).…”

Section: Methodsmentioning

confidence: 99%

Identifying the differences in mechanisms of mycophenolic acid controlling fucose content of glycoproteins expressed in different CHO cell lines

Zhang

Tsang

Markely

et al. 2016

Self Cite

In the biopharmaceutical industry, glycosylation is a critical quality attribute that can modulate the efficacy of a therapeutic glycoprotein. Obtaining a consistent glycoform profile is desired because molecular function can be defined by its carbohydrate structures. Specifically, the fucose content of oligosaccharides in glycoproteins is one of the most important attributes that can significantly affect antibody-dependent cellular cytotoxicity (ADCC) activity. It is therefore important to understand the fucosylation pathway and be able to control fucosylation at the desired level to match predecessor materials in late stage and biosimilar programs. Several strategies were explored in this study and mycophenolic acid (MPA) was able to finely modulate the fucose content with the least undesired side effects. However, the response was significantly different between CHO cell lines of different lineages. Further experiments were then performed for a deeper understanding of the mechanism of fucosylation in different CHO cell lines. Results indicated that changes in the intracellular nucleotide involved in fucosylation pathway after MPA treatment are the main cause of the differences in fucosylation level response in different CHO cell lines. Differences in MPA metabolism in the various CHO cell lines directly resulted in different levels of afucosylation measured in antibodies produced by the CHO cell lines. Biotechnol. Bioeng. 2016;113: 2367-2376. © 2016 Wiley Periodicals, Inc.