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Browsing by Subject "Metabolic shift"

Now showing 1 - 3 of 3
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    Analysis of central metabolic pathways in cultured mammalian cells
    (2014-10) Yongky, Andrew
    Recombinant therapeutic proteins have transformed the field of medicine since their advent more than twenty years ago, providing treatments for various refractory illnesses. Mammalian cells are the preferred hosts for the production of these therapeutics. However, a lack of understanding of the behavior of the cells results in numerous issues that affect the performance of process cultures including inefficient glucose metabolism and improper post-translational modification of the product proteins. With the advances in the knowledge of regulation of metabolism of mammalian cells and the availability of genomics and transcriptomics resources, systems biology approach combining kinetic model and "-omics" tools can now be used to address such issues. The work presented in this thesis employs such systems biology approach to better understand the metabolic behavior of the cells and devise strategies to enhance their performance in culture. Cultured mammalian cells consume huge amount of glucose and convert most of it towards lactate. The accumulation of lactate in culture adversely affects cell growth and productivity. The reliance of these cells on anaerobic glycolysis is also observed in proliferating cells such as cancer cells and embryonic stem cells. In contrast, quiescent cells metabolize glucose at slower rate and glucose is mostly oxidized to carbon dioxide. In the first part of this thesis, we attempt to unravel the regulation of glucose metabolism in proliferating and non-proliferating cells using a mechanistic model of glycolysis. We show that multiple allosteric regulations of glycolysis enzymes can act in synergy to confer bistable behavior to glycolysis activity: at a given glucose concentration, glycolysis can operate at either a high flux state or a low flux state. In proliferating cells, the default state of the cells is to operate at high glycolysis flux. However, it is possible to modulate factors extrinsic and intrinsic to the cells in order to make them switch to low flux state.In the late stages of fed-batch culture, mammalian cells have been observed to shift their metabolism from lactate production to lactate consumption. While it has been correlated with higher productivity, such metabolic shift is not a consistent occurrence as some cultures continue to produce lactate. The metabolic model is used to explain the underlying mechanism behind the metabolic shift to lactate consumption in fed-batch culture. We show that the bistable behavior in glycolysis differs somewhat due to lactate inhibition and growth rate regulation on metabolism. As a result, the cells in culture may or may not shift their metabolism to consume lactate depending on the glucose, lactate and growth rate of the cells. In continuous culture, a similar metabolic behavior has been observed. With the same operating conditions of dilution rate and feed glucose concentration, some continuous cultures reach steady state with high glycolysis flux, while others reach steady state with low glycolysis. The two steady states are marked by distinct steady state cell concentrations. Using a multi-scale reactor model that combines the intracellular metabolism and macroscopic cell growth, we show that multiple steady states exist in continuous culture. At high flux steady state the vast majority of glucose is converted to lactate, whereas at low flux steady state most of the glucose consumed is converted to biomass. The two types of steady states thus have different metabolic efficiency, conferring different cell concentrations.In the final part of the thesis, RNA-seq and microarray are employed to survey the variability in CHO cell lines. We observe a wide range of transcript levels of glycolysis enzymes in CHO cell lines, potentially contributing to distinct metabolic characteristics in different cell lines. The extent of genetic variation in the protein coding regions of the growth signaling pathway genes in CHO cells are discussed.
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    Cell-culture Data Pipeline Python package (CDPpy) for processing and analyzing cell culture datasets
    (2024-08-05) Lu, Yen-An; Fukae, Yudai; Hu, Wei-Shou; Zhang, Qi; qizh@umn.edu; Zhang, Qi; University of Minnesota Decision Discovery and Optimization Lab; University of Minnesota Cellular Engineering Lab
    CDPpy (Cell-culture Data Pipeline Python package) is an open-source library designed for the analysis of fed-batch cell culture data from multiple experiments and cell lines. The package features the functions of a data processing pipeline and visualization toolbox. The processing pipeline reads raw data from Excel files following a fixed template, derives variables such as cumulative substrate consumption and various specific rates, and exports the processed dataset into an Excel file. The specific rates show changing cellular activities over time in culture, providing insights for process optimization. The visualization toolbox enables users to analyze process profiles across experimental runs and cell lines, aiding in future experimental design. In this repository, we include the source code for the package, an instruction for package setup, and a Jupyter notebook that provides step-by-step guidelines for data processing and visualization using an example dataset. The updated version will be announced in the GitHub repository: https://github.com/ddolab/CDPpy in the future.
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    A mechanistic-empirical model of central metabolism, signaling, and the reactor environment for bioprocesses
    (2020-10-07) O'Brien, Conor M; Hu, Wei-Shou; acre@umn.edu; Hu, Wei-Shou
    This model was built and optimized to reproduce the variability inherent to many industrial cell-culture processes. Classically, fed-batch Chinese Hamster Ovary (CHO) cell cultures will initially produce lactate in the early phase of culture before switching to lactate consumption. However, some processes may revert to lactate production in the late stage of culture, driving up osmolarity while reducing viable cell density, and ultimately lowering process performance. This phenomenon may occur in only some runs of a manufacturing processes and even may differ among runs with similar initial conditions and trajectories, leading to longstanding questions about the mechanisms driving this switch. By simulating cultures which were exposed to different amounts of stress before the production bioreactor we show that similar starting conditions in the bioreactor environment can lead to variability in metabolic shift. We provide this model as a tool to demonstrate this metabolic variability and provide a platform for hypothesis testing, in silico bioprocess optimization, and simulation of reactor scale-up and scale-down.