Abstract

Due to its vital importance in the supply of cellular pathways with energy and precursors, glycolysis has been studied for several decades regarding its capacity and regulation. For a systems-level understanding of the Madin-Darby canine kidney (MDCK) cell metabolism, we couple a segregated cell growth model published earlier with a structured model of glycolysis, which is based on relatively simple kinetics for enzymatic reactions of glycolysis, to explain the pathway dynamics under various cultivation conditions. The structured model takes into account in vitro enzyme activities, and links glycolysis with pentose phosphate pathway and glycogenesis. Using a single parameterization, metabolite pool dynamics during cell cultivation, glucose limitation and glucose pulse experiments can be consistently reproduced by considering the cultivation history of the cells. Growth phase-dependent glucose uptake together with cell-specific volume changes generate high intracellular metabolite pools and flux rates to satisfy the cellular demand during growth. Under glucose limitation, the coordinated control of glycolytic enzymes re-adjusts the glycolytic flux to prevent the depletion of glycolytic intermediates. Finally, the model's predictive power supports the design of more efficient bioprocesses.

Highlights

  • The primary metabolism of cells is essential for cell growth and maintenance

  • The detailed in vitro characterization of glycolytic enzymes, such as hexokinase (HK), phosphofructokinase (PFK) and pyruvate kinase (PK), with respect to their catalytic properties in the presence of substrates, products and allosteric effectors represents an initial step towards a kinetic description of metabolic phenomena of cells [1,2,3]

  • We argue that the many different dynamics in glycolysis result from an interplay between a growth-dependent sugar uptake together with simple intrinsic enzyme regulation

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Summary

Introduction

The primary metabolism of cells is essential for cell growth and maintenance. Glycolysis is a central element of the primary metabolic activity and supplies anabolic pathways with precursors and cellular energy in form of ATP. Dynamic mathematical models of glycolysis have been developed for many different organisms such as Escherichia coli, yeast, or mammalian cells. Such models range from simple to full kinetic descriptions with the intention to study specific observations, e.g., metabolic steady states [4,5,6] perturbation of substrates [7,8,9] or enzymes [10], flux sensors [11], oscillations in glycolysis [12], the glucose uptake system [13], or the link of liver cell glycolysis with blood glucose homeostasis [14,15]. Based on the additional quantification of extracellular metabolite changes and cell number measurements a systematic analysis of basic dynamics of glycolysis for various cultivation conditions is possible

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