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Research Abstracts Online
January 2009 - March 2010

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University of Minnesota Twin Cities
College of Biological Sciences
BioTechnology Institute

PI: Friedrich Srienc, Associate Fellow

Elementary Mode Analysis for Biochemical Networks

Evolution has developed the metabolism of organisms with a highly coupled network of hundreds of enzyme-catalyzed reactions. Advances in molecular biological techniques, such as PCR, have provided means of rapidly altering the topography of these reaction networks. Analysis of native and recombinant metabolic networks has been simplified by a number of theoretical tools. One such method is elementary mode analysis. An elementary mode is the simplest balanced combination of substrates, products, and intracellular reactions operating at steady state.

Projects this group has worked on during this period include: developing an efficient algorithm to compute elementary modes of genome-scale metabolic networks by applying parallel programming; developing and analyzing an Escherichia coli metabolic model that optimizes the production of biomass under different oxygen stresses, the production of poly-(R)-3-hydroxybutyric acid (PHB) under anaerobic growth, and the production of biofuels and the production of carotenoids from various substrates; developing and analyzing a Saccharomyces cerevisiae metabolic model for biofuel production; developing and analyzing a Shewanella oneidensis metabolic model for biofuel production from glycerol using external electrodes as electron acceptors; developing and analyzing a Thermoanaerobacterium saccharolyticum metabolic model for production of biofuel from renewable resources; developing an algorithm based on stoichiometric and thermodynamic constraints for counting and/or finding elementary modes containing a specified set of reactions for rational strain design; and constructing a relational database of an E. coli metabolic network that is employed to map the function of gene products on their corresponding metabolic network to identify the regulation bottlenecks of the metabolic network.

Group Members

Christopher M. Flynn, Graduate Student
Johnathan Gorke, Graduate Student
Pedro Pena, Research Associate
Tyler P. Price, Graduate Student
Daniel P. Rouse, Graduate Student
Greg W. Sitton, Graduate Student
Pornkamol (Apple) Unrean, Graduate Student