The relation between the genotype and the phenotype of an organism is fundamental to biology. Based on the annotated genome sequence and biochemical information it is possible to reconstruct genome-scale metabolic maps, and in silico methods have been developed to interpret and predict the optimal utilization of the metabolic map under a given growth condition. Using the defined Escherichia coli MG1655 metabolic genotype, experimentally testable hypotheses have been formulated in silico describing the quantitative relation between the uptake rate of a primary carbon source, oxygen uptake rate, and cellular growth. Experiments with E. coli have been performed and experimental data were found to be consistent with the optimal use of the metabolic network to support growth of E. coli under the experimental conditions considered, which were growth on acetate, succinate, and malate. These important results form the basis for the proposed program. It is comprised of three parts, 1) to continue the generation of experimentally testable hypotheses for a broader ranger of carbon sources and to profile the gene expression patterns for these growth conditions, 2) to generate 40 knockout strains and perform both growth experiments and gene expression studies to characterize their metabolic behavior and 3) to perform evolution experiments for wild-type and knockout strains of E. coli that exhibit sub-optimal growth phenotypes. Additionally, gene expression studies will be performed for these evolving strains during and after evolution to identify the molecular events that are elicited during the evolutionary process. Hence the experimental program has the specific aims of determining optimal phase plane behavior for a range of growth conditions, and to determine if metabolic gene expression patterns are consistent with predicted pathway used for both wild-type and knockout strains. If the program is successfully implemented and executed we will have refined and improved our understanding of the metabolic genotype-phenotype relationship for E. coli under the conditions examined, an accomplishment of clear fundamental significance.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Project (R01)
Project #
5R01GM062791-03
Application #
6727600
Study Section
Special Emphasis Panel (ZRG1-MBC-2 (01))
Program Officer
Jones, Warren
Project Start
2002-04-01
Project End
2006-03-31
Budget Start
2004-04-01
Budget End
2006-03-31
Support Year
3
Fiscal Year
2004
Total Cost
$603,687
Indirect Cost
Name
University of California San Diego
Department
Engineering (All Types)
Type
Schools of Arts and Sciences
DUNS #
804355790
City
La Jolla
State
CA
Country
United States
Zip Code
92093
Cho, Byung-Kwan; Kim, Donghyuk; Knight, Eric M et al. (2014) Genome-scale reconstruction of the sigma factor network in Escherichia coli: topology and functional states. BMC Biol 12:4
Federowicz, Stephen; Kim, Donghyuk; Ebrahim, Ali et al. (2014) Determining the control circuitry of redox metabolism at the genome-scale. PLoS Genet 10:e1004264
Cho, Byung-Kwan; Federowicz, Stephen; Park, Young-Seoub et al. (2012) Deciphering the transcriptional regulatory logic of amino acid metabolism. Nat Chem Biol 8:65-71
Charusanti, Pep; Fong, Nicole L; Nagarajan, Harish et al. (2012) Exploiting adaptive laboratory evolution of Streptomyces clavuligerus for antibiotic discovery and overproduction. PLoS One 7:e33727
Schellenberger, Jan; Zielinski, Daniel C; Choi, Wing et al. (2012) Predicting outcomes of steady-state ýýýýC isotope tracing experiments using Monte Carlo sampling. BMC Syst Biol 6:9
Applebee, M Kenyon; Joyce, Andrew R; Conrad, Tom M et al. (2011) Functional and metabolic effects of adaptive glycerol kinase (GLPK) mutants in Escherichia coli. J Biol Chem 286:23150-9
Cho, Byung-Kwan; Federowicz, Stephen A; Embree, Mallory et al. (2011) The PurR regulon in Escherichia coli K-12 MG1655. Nucleic Acids Res 39:6456-64
Lee, Dae-Hee; Feist, Adam M; Barrett, Christian L et al. (2011) Cumulative number of cell divisions as a meaningful timescale for adaptive laboratory evolution of Escherichia coli. PLoS One 6:e26172
Nam, Hojung; Conrad, Tom M; Lewis, Nathan E (2011) The role of cellular objectives and selective pressures in metabolic pathway evolution. Curr Opin Biotechnol 22:595-600
Conrad, Tom M; Lewis, Nathan E; Palsson, Bernhard O (2011) Microbial laboratory evolution in the era of genome-scale science. Mol Syst Biol 7:509

Showing the most recent 10 out of 31 publications