This manuscript presents a thorough investigation and description of metabolic control
dynamics in vivo and in silico using as a model de novo pyrimidine biosynthesis.
Metabolic networks have been studied intensely for decades, helping develop a detailed
understanding of the way cells carry out their biosynthetic and catabolic functions.
Biochemical reactions have been defined, pathway structures have been proposed,
networks of genetic control have been examined, and mechanisms of enzymatic activity
and regulation have been elucidated. In parallel with these types of traditional
biochemical analysis, there has been increasing interest in engineering cellular
metabolism for commercial and medical applications. Several different mathematical
approaches have been developed to model biochemical pathways by combining
stoichiometric and/or kinetic information with probabilistic analysis, or deciphering the
comparative logic of metabolic networks using genomic-derived data. However, most of
the research performed to date has relied on theoretical analyses and non-dynamic
physiological states. The studies described in this dissertation provide a unique effort
toward combining mathematical analysis with dynamic transition experimental data.
Most importantly these studies emphasize the significance of providing a quantitative framework for understanding metabolic control. The pathway of de novo biosynthesis of
pyrimidines in Escherichia coli provides an ideal model for the study of metabolic
control, as there is extensive documentation available on each gene and enzyme involved
as well as on their corresponding mechanisms of regulation. Biochemical flux through
the pathway was analyzed under dynamic conditions using middle-exponential growth
and steady state cultures. The fluctuations of the biochemical pathway intermediates and
end products transitions were quantified in response to physiological perturbation.
Different growth rates allowed the comparison of rapid versus long-term equilibrium
shifts in metabolic adaptation. Finally, monitoring enzymatic activity levels during
metabolic transitions provided insight into the interaction of genetic and biochemical
mechanisms of regulation. Thus, it was possible to construct a robust mathematical
model that faithfully represented, with a remarkable predictability, the nature of the
metabolic response to specific environmental perturbations. These studies constitute a
significant contribution to the fields of quantitative biochemistry and metabolic control,
which can be extended to other cellular processes as well as different organisms.
| Identifer | oai:union.ndltd.org:tamu.edu/oai:repository.tamu.edu:1969.1/4425 |
| Date | 30 October 2006 |
| Creators | Rodriguez Rodriguez, Mauricio |
| Contributors | Wild, James R. |
| Publisher | Texas A&M University |
| Source Sets | Texas A and M University |
| Language | en_US |
| Detected Language | English |
| Type | Book, Thesis, Electronic Dissertation, text |
| Format | 3591499 bytes, electronic, application/pdf, born digital |
Page generated in 0.0201 seconds