GENERAL: Bacteria are important in human disease, bioterrorism, and dealing with the environment. We now have full DMA sequences for the genomes for key bacteria. We now need to understand the mechanism that govern whole genome functions. Elucidating these mechanisms will have a broad scientific influence, and how we understand the generation of antibiotic resistance in pathogenic bacteria. SPECIFIC: This R01 program has used genome-scale experimental methods to study the transcriptional regulatory network in Escherichia coli and its optimal growth phenotypes during adaptive evolution. The program has to date achieved several important milestones; 1) it has used phenotypic phase plane analysis to predict and measure optimal growth states; 2) it has shown that in about 70% of the >100 cases examined to date, that the endpoint of laboratory adaptive evolution is consistent with the a priori computations of the genome-scale in silico model for wild-type and knock-out (KO) strains; 3) it has led to expression profiling before, during and after adaptive evolutions characterizing the extensive change in the E. coli transcriptome and shown that there are multiple uses of the genome to produce a particular growth phenotype; 4) it has studied the oxygen shift in wild-type and transcription factor (TF) KO strains, and by using expression profiling determined a large number of new regulatory interactions in E. coli; and 5) it has put myc-tags on these TFs to begin the process of determining the genome location of their binding sites. Based on these results, this R01 program is in a position to answer broad and fundamental questions about the use and regulation of the E. coli genome and its evolutionary plasticity on a genome-scale. We thus put forth the following 2 specific aims that focus on determining the transcriptional regulatory network in E. coli I) a broad and systematic elucidation of the structure of the network in the sequenced K-12 MG1655 strain through the use of established environmental and genetic shift experiments and II) after adaptive evolution to optimal growth on glycerol and lactate, and after adaptive evolution of selected transcription factor knock- outs.
These specific aims lie at the heart of understanding how prokaryotic genomes respond to their environments and how such responses are modified during adaptive evolution to better fitness in a given environment. ? ? ?

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Project (R01)
Project #
2R01GM062791-04A2
Application #
7145128
Study Section
Genomics, Computational Biology and Technology Study Section (GCAT)
Program Officer
Jones, Warren
Project Start
2001-04-01
Project End
2010-05-31
Budget Start
2006-06-01
Budget End
2007-05-31
Support Year
4
Fiscal Year
2006
Total Cost
$627,131
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
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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

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