389058 Metabolic Modeling of an Escherichia coli Cell-Free Glycoprotein Synthesis System

Monday, November 17, 2014: 4:51 PM
205 (Hilton Atlanta)
Joseph A. Wayman1, Michael C. Jewett2, Matthew P. DeLisa3 and Jeffery D. Varner3, (1)Applied and Engineering Physics, Cornell University, Ithaca, NY, (2)Chemical and Biological Engineering, Northwestern University, Evanston, IL, (3)School of Chemical and Biomolecular Engineering, Cornell University, Ithaca, NY

Cell-free systems, derived from crude cell extracts, contain the cellular components required for transcription, translation, and energy metabolism (e.g., ribosomes, metabolic enzymes). These systems are capable of synthesizing desired proteins, offering precise control of the chemical environment and reduce diversion of substrate toward unnecessary cellular processes. Cell-free systems offer an attractive platform for the controlled production of therapeutic proteins. Recently, cell-free production of glycosylated proteins was achieved from E. coli extracts. The reduced complexity and well-defined composition of cell-free systems make them an ideal system for model-based interrogation and engineering. In this study, we construct a structural network of an E. coli cell-free system from which an ensemble of kinetic models is developed. Our parameter identification approach combines two elements. First, component concentrations and reaction rates are estimated based on solutions to a quadratic program called a state regulator problem (SRP). The SRP objective penalizes accumulation of species while minimizing reaction flux through the network. This objective does not require a steady-state solution, allowing this method to capture potential dynamic behavior of metabolic systems. Second, SRP estimates are combined with metaheuristic optimization against experimental data in order to identify an ensemble of kinetic models. This approach accommodates metabolomic and fluxomic measurements. Sensitivity analysis on resulting candidate models can reveal mechanisms controlling protein production and, thus, identify strategies for strain improvement. Specifically, we discuss the model's application toward glycan synthesis along with glycosylation efficiency and glycoprotein production.

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See more of this Session: Modeling Approaches for Biological Phenomena
See more of this Group/Topical: Food, Pharmaceutical & Bioengineering Division