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 two 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.
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