A major challenge in post-genomic biology is the understanding of the complex molecular internal machinery of the cell. A fundamental component in the machinery to take decisions is the regulatory network of transcription initiation. The purpose of this application is to enhance the major annotation project on transcriptional regulation and operon organization of the model organism Escherichia coil K-12. This project is a conceptual continuation and expansion of a previous grant supporting the annotation work enriching RegulonDB. In addition to continuing literature curation, we propose to perform an exhaustive mapping of all possible missing promoter sites in the genome, as well as to perform several theoretical analyses of the regulatory network, together with simulations and comparisons with microarray data performed in other laboratories. We plan to complement literature knowledge with computational predictions, and to actively search for the missing links that will permit us to put together transcription, transport, signal transduction and metabolism, taking advantage of several existing databases. We will determine how much this cellular knowledge is consistent with the large amounts of microarray experiments performed in several laboratories. These comparisons require building several computational and chemical models of regulatory simple and complex interactions determining gene expression, as well as their consequences in the overall cellular network (transport, signal transduction and metabolism). We will analyze the network in modules, motifs, and maps, using different mathematical criteria based on the statistical properties of the network connectivity, as well as on biological knowledge of conditions and microarray experiments. Finally, we intend to perform low-resolution discrete simulations of the dynamics of the network, as well as detailed stochastic modeling of selected maps and subcomponents of the network. Modeling and its comparison with experiments shall enhance the overall quality and depth of the classical and active annotation of the regulatory network of the best known and studied single cell organism. Having a better understanding of a whole cell, shall provide an important contribution to basic biology and thus to the foundations to understand health and disease.
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| Salgado, Heladia; Peralta-Gil, Martin; Gama-Castro, Socorro et al. (2013) RegulonDB v8.0: omics data sets, evolutionary conservation, regulatory phrases, cross-validated gold standards and more. Nucleic Acids Res 41:D203-13 |
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| Pauling, Josch; Rottger, Richard; Neuner, Andreas et al. (2012) On the trail of EHEC/EAEC--unraveling the gene regulatory networks of human pathogenic Escherichia coli bacteria. Integr Biol (Camb) 4:728-33 |
| Salgado, Heladia; Martinez-Flores, Irma; Lopez-Fuentes, Alejandra et al. (2012) Extracting regulatory networks of Escherichia coli from RegulonDB. Methods Mol Biol 804:179-95 |
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