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Identification of Potential Target Pathways of Recombinant Yeast for Increasing Bioethanol Productivity: In Silico Analysis Using Cybernetic Models

Hyun-Seob Song, John A Morgan, Nancy W. Y. Ho, Arvind Varma, and Doraiswami Ramkrishna. School of Chemical Engineering, Purdue University, Forney Hall of Chemical Engineering, 480 Stadium Mall Drive, West Lafayette, IN 47907

Continuing efforts are in progress to design effective recombinant yeasts converting pentose sugars as well as hexose sugars to ethanol for the development of an economically viable B2B (biomass-to-biofuel) process. While significant advances have been made in the past in the metabolic engineering of fermenting yeasts, further increase of bioethanol productivity is desirable. In this regard, mathematical models are needed for a more systematic approach to genetic modification.

A hybrid cybernetic model has been developed for the Ho-Purdue strain 1400 (pLNH33) by combining cybernetic modeling concept with elementary mode analysis based on the steady-state postulate on intracelluar metabolites. The hybrid cybernetic model is characterized by the dynamical description of metabolic processes as a combination of elementary mode fluxes. The selection of the modes is modulated by cybernetic control laws towards maximizing a predetermined metabolic fitness function (e.g., biomass growth rate or carbon uptake rate). Using this model, we have investigated the effect of various pathway modifications on ethanol productivity of yeast and fermenters. Comprehensive dynamic simulations have been conducted together with metabolic control analysis to identify the metabolic pathway which can lead to the substantial increase of ethanol productivity. While as such, the hybrid model provides critical information on the pathway modification for increasing ethanol productivity, an advanced model based on detailed metabolic description might be required to narrow down the range of genetic modification to a few specific target genes. For this purpose, a more detailed cybernetic model based on Young's modeling framework (Young 2005; Young et al. 2008) is being formulated and will be applied for the development of an improved yeast strain.


Young JD. 2005. A system-level mathematical description of metabolic regulation combining aspects of elementary mode analysis with cybernetic control laws. PhD Dissertation, Purdue University

Young JD, Henne KL, Morgan JA., Konopka AE, Ramkrishna D. 2008. Integrating cybernetic modeling with pathway analysis provides a dynamic, systems-level description of metabolic control. Biotechnology and Bioengineering 100(3):542-559