Comprehensive analysis of metabolic pathways through the combined use of multiple isotopic tracers

Metabolic Flux Analysis (MFA) has emerged as a tool of great significance for metabolic engineering and the analysis of human metabolic diseases. An important limitation of MFA, as carried out via stable isotope labeling and GC/MS measurements, is the large number of isotopomer equations that need to be solved. This restriction reduces the ability of MFA to fully utilize the power of multiple isotopic tracers in elucidating the physiology of complex biological networks. Here, we present a novel framework for modeling isotopic distributions that significantly reduces the number of system variables without any loss of information. The elementary metabolite units (EMU) framework is based on a highly efficient decomposition algorithm identifies the minimum amount of information needed to simulate isotopic labeling within a reaction network using knowledge of atomic transitions occurring in the network reactions. The developed computational and experimental methodologies were applied to two biological systems of major industrial and medical significance. First, we describe the analysis of metabolic fluxes in E. coli in a fed-batch fermentation for overproduction of 1,3-propanediol (PDO).

Department dc:contributor.department

Massachusetts Institute of Technology. Dept. of Chemical Engineering.

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2006

Author dc:creator

• Antoniewicz, Maciek Robert

Advisor dc:contributor.advisor

• Gregory Stephanopoulos.

• Chemical Engineering.

Statement dc:rights

• M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.

Licence dc:rights.uri

• http://dspace.mit.edu/handle/1721.1/7582

Language dc:language.iso

eng

Handle dc:identifier.uri

http://hdl.handle.net/1721.1/37457

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/37457