Regulation of Metabolic Homeostasis in Cell Culture Bioprocesses

O'Brien, Conor M.; Mulukutla, Bhanu Chandra; Mashek, Douglas G.; Hu, Wei Shou

doi:10.1016/j.tibtech.2020.02.005

Cited by 31 publications

(17 citation statements)

References 96 publications

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“…Despite the counterintuitive results (at least in terms of cell growth), we hypothesize that cells may have triggered an oxygen-dependent response after reaching specific VCD levels that resulted in metabolic changes that favor either cell growth or r-protein production. survival and increase the glycolytic flux by enhancing catalytic efficiency of glycolytic enzymes (phophofructokinase 1 and pyruvate kinase [PK), 33 and increase glucose uptake by upregulation of the GLUT1 glucose transporter activity. 34 In high volume culture conditions, cells showed higher consumption of glucose and lower production/secretion of glycolysis-derived metabolites (e.g., lactate, sorbitol, threitol, and fructose), thereby indicating that more of the glucose that has entered cells is being utilized more efficiently in glycolysis (Figures 4 and S3).…”

Section: Discussionmentioning

confidence: 99%

Metabolic profiling of Chinese hamster ovary cell cultures at different working volumes and agitation speeds using spin tube reactors

Torres

Elvin

Betts

et al. 2020

Biotechnology Progress

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Culture systems based on spin tube reactors have been consolidated in the development of manufacturing processes based on Chinese hamster ovary (CHO) cells.Despite their widespread use, there is little information about the consequences of varying operational setting parameters on the culture performance of recombinant CHO cell lines. Here, we investigated the effect of varying working volumes and agitation speeds on cell growth, protein production, and cell metabolism of two clonally

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Section: Discussionmentioning

confidence: 99%

Metabolic profiling of Chinese hamster ovary cell cultures at different working volumes and agitation speeds using spin tube reactors

Torres

Elvin

Betts

et al. 2020

Biotechnology Progress

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show abstract

“…This implies that cell metabolism based on feeding regime has a notable impact on SMR and marker expression I addition to seeding density. It is well understood and recognized that metabolic rates are a function of nutrient availability [ 61 , 62 ]; it is therefore unsurprising that conditions with a higher cell load exhibit a lower metabolic rate measured by SMR as nutrient depletion will result in decreased nutrient availability overall. Thus, if these parameters are not adequately controlled the resultant cell output quality would be highly variable and incomparable between different process runs and undoubtedly between different sites, which would compromise the use of the cells be it as a reference standard, or therapeutic product.…”

Section: Discussionmentioning

confidence: 99%

The importance of cell culture parameter standardization: an assessment of the robustness of the 2102Ep reference cell line

et al. 2021

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Work undertaken using the embryonic carcinoma 2102Ep line, highlighted the requirement for robust, well-characterized and standardized protocols. A systematic approach utilizing ‘quick hit’ experiments demonstrated variability introduced into culture systems resulting from slight changes to culture conditions (route A). This formed the basis for longitudinal experiments investigating long-term effects of culture parameters including seeding density and feeding regime (route B).Results demonstrated that specific growth rates (SGR) of passage 59 (P59) cells seeded at 20,000 cells/cm 2 and subjected to medium exchange after 48h prior to reseeding at 72h (route B2) on average was marginally higher than, P55 cells cultured under equivalent conditions (route A1); whereby SGR values were (0.021±0.004) and (0.019±0.004). Viability was higher in route B2 over 10 passages with average viability reported as (86.3%±8.1) compared to route A1 (83.3±8.8). The metabolite data demonstrated both culture route B1 (P57 cells seeded at 66,667 cells/cm 2 ) and B2 had consistent-specific metabolite rates (SMR) for glucose, but SMR values of route B1 was consistently lower than route B2 (0.00001 mmol, cell-1.d-1 and 0.000025).Results revealed interactions between phenotype, SMR and feeding regime that may not be accurately reflected by growth rate or observed morphology. This implies that current schemes of protocol control do not adequately account for variability, since key cell characteristics, including phenotype and SMR, change regardless of standardized seeding densities. This highlights the need to control culture parameters through defined protocols, for processes that involve culture for therapeutic use, biologics production, and reference lines.

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“…Lastly, the minimize ROS synthesis objective function hypothesized negligible activities in glycolysis and citric acid cycle, deviating from known CHO biology 83 . Instead, most consumed glucose was diverted to the folate cycle via phosphoserine transamination to produce energy and byproduct formic acid (Fig.…”

Section: Selection Of Objective Function Has Greatest Influence On Model Predictionmentioning

confidence: 97%

Systematic evaluation of parameters for genome-scale metabolic models of cultured mammalian cells

Schinn

Morrison

Wei

et al. 2021

Metabolic Engineering

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Genome-scale metabolic models describe cellular metabolism with mechanistic detail.Given their high complexity, such models need to be parameterized correctly to yield accurate predictions and avoid overfitting. Effective parameterization has been wellstudied for microbial models, but it remains unclear for higher eukaryotes, including mammalian cells. To address this, we enumerated model parameters that describe key features of cultured mammalian cells -including cellular composition, bioprocess performance metrics, mammalian-specific pathways, and biological assumptions behind model formulation approaches. We tested these parameters by building thousands of metabolic models and evaluating their ability to predict the growth rates of a panel of phenotypically diverse Chinese Hamster Ovary cell clones. We found the following considerations to be most critical for accurate parameterization: (1) cells limit metabolic activity to maintain homeostasis, (2) cell morphology and viability change dynamically during a growth curve, and (3) cellular biomass has a particular macromolecular composition. Depending on parameterization, models predicted different metabolic phenotypes, including contrasting mechanisms of nutrient utilization and energy generation, leading to varying accuracies of growth rate predictions. Notably, accurate parameter values broadly agreed with experimental measurements. These insights will guide future investigations of mammalian metabolism.

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Regulation of Metabolic Homeostasis in Cell Culture Bioprocesses

Cited by 31 publications

References 96 publications

Metabolic profiling of Chinese hamster ovary cell cultures at different working volumes and agitation speeds using spin tube reactors

Metabolic profiling of Chinese hamster ovary cell cultures at different working volumes and agitation speeds using spin tube reactors

The importance of cell culture parameter standardization: an assessment of the robustness of the 2102Ep reference cell line

Systematic evaluation of parameters for genome-scale metabolic models of cultured mammalian cells

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