Award Abstract #0504168
International Research Fellowship Program: Systems Biology of Glucose Repression in Yeast for Metabolic Engineering

NSF Org:	OISE Office of International Science and Engineering
Initial Amendment Date:	July 1, 2005
Latest Amendment Date:	March 20, 2007
Award Number:	0504168
Award Instrument:	Fellowship
Program Manager:	Susan Parris OISE Office of International Science and Engineering O/D OFFICE OF THE DIRECTOR
Start Date:	June 1, 2005
Expires:	December 31, 2007 (Estimated)
Awarded Amount to Date:	$128416
Investigator(s):	Michael Jewett mcjewett@gmail.com (Principal Investigator)
Sponsor:	Jewett Michael C Stanford, CA 94305 / -
NSF Program(s):	EAPSI
Field Application(s):	0510402 Biomaterials-Short & Long Terms
Program Reference Code(s):	BIOT, 9125, 5980, 5956, 5914
Program Element Code(s):	7316

ABSTRACT

0504168

Jewett

The International Research Fellowship Program enables U.S. scientists and engineers to conduct three to twenty-four months of research abroad. The program's awards provide opportunities for joint research, and the use of unique or complementary facilities, expertise and experimental conditions abroad.

This award will support a twenty-two month research fellowship by Dr. Michael C. Jewett to work with Dr. Jens Nielsen at Technical University of Denmark's Center for Microbial Biotechnology (CMB) in Lyngby, Denmark.

Genetically engineering cells for production of valuable protein therapeutics and secondary metabolites is widely exploited in the pharmaceutical and chemical industries. However, achieving desired phenotypes that are, in general, not the "Darwinian optimum," presents a formidable challenge given the complex nature of the catalytic inventory, metabolic pathways, signaling circuits, and regulatory networks of microorganisms. To rationally design cell factories, we must use system-level methods to gain an understanding of the physiological information necessary to rewire cellular control element. The objective of this project is to identify key components of glucose repression in Saccharomyces cerevisiae using systems biology for design of glucose de-repressed strains. Such strains are industrially attractive for improving baker's yeast production from molasses, bioethanol production from sugar mixtures, and heterologous protein production. To achieve this goal, the PI and host will combine genome-scale metabolic models with DNA array and metabolite profiling data of several glucose repression mutants. Detailed characterization of these mutants by model guided analysis of global cellular function will allow mapping of all pleotrophic effects, identification of co-regulated metabolic patterns, and subsequent engineering of desired strains. In addition to accomplishing this main objective, ther study has several expected deliverables. First, novel algorithms for integration of data from both the transcriptome and the metabolome will be developed. Second, new analytical methods for metabolite profiling based on direct infusion mass spectrometry will be designed. Third, the role of regulatory elements involved in glucose sensing and repression will be clarified.

This study will have a broad impact on the field of systems biology and yeast genetics/physiology. Particularly, the novel algorithms will find wide use in metabolic engineering and directly enhance our capability to design "made to order" organisms. In addition, the development of glucose de-repressed strains of S. cerevisiae will increase their utility as industrial production hosts. Furthermore, since glucose repression in yeast serves as a model for nutrient sensing in eukaryotic cells, the development of efficient algorithms for this system may be applied to mapping of signal transduction pathways in higher eukaryotes - including humans. Progress in this research area will directly enhance and complement many technologies in the scientific community while generating a valuable international partnership. The CMB has a strong international position in metabolic engineering, fermentation, physiology, functional genomics, and systems biology of eukaryotic microorganisms.

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