title: Computational design of genomic transcriptional networks with adaptation to varying environments.
abstract: Transcriptional profiling has been widely used as a tool for unveiling the coregulations of genes in response to genetic and environmental perturbations. These coregulations have been used, in a few instances, to infer global transcriptional regulatory models. Here, using the large amount of transcriptomic information available for the bacterium Escherichia coli, we seek to understand the design principles determining the regulation of its transcriptome. Combining transcriptomic and signaling data, we develop an evolutionary computational procedure that allows obtaining alternative genomic transcriptional regulatory network (GTRN) that still maintains its adaptability to dynamic environments. We apply our methodology to an E. coli GTRN and show that it could be rewired to simpler transcriptional regulatory structures. These rewired GTRNs still maintain the global physiological response to fluctuating environments. Rewired GTRNs contain 73% fewer regulated operons. Genes with similar functions and coordinated patterns of expression across environments are clustered into longer regulated operons. These synthetic GTRNs are more sensitive and show a more robust response to challenging environments. This result illustrates that the natural configuration of E. coli GTRN does not necessarily result from selection for robustness to environmental perturbations, but that evolutionary contingencies may have been important as well. We also discuss the limitations of our methodology in the context of the demand theory. Our procedure will be useful as a novel way to analyze global transcription regulation networks and in synthetic biology for the de novo design of genomes.
authors.affiliation: Institute of Systems and Synthetic Biology, Universite d'Evry Val d'Essonne, Genopole®, Centre National de la Recherche Scientifique (CNRS UPS3509), 91030 Evry Cedex, France.
authors.forename: Javier
authors.initials: J
authors.lastname: Carrera
authors.forename: Santiago F
authors.initials: SF
authors.lastname: Elena
authors.forename: Alfonso
authors.initials: A
authors.lastname: Jaramillo
mesh_terms: D001331:Automation; D001671:Biochemistry / Q000379:methods; D019295:Computational Biology / Q000379:methods*; D003198:Computer Simulation; D004926:Escherichia coli / Q000235:genetics / Q000378:metabolism; D029968:Escherichia coli Proteins / Q000235:genetics; D019143:Evolution, Molecular; D015964:Gene Expression Regulation, Bacterial; D053263:Gene Regulatory Networks; D016680:Genome, Bacterial; D023281:Genomics; D008954:Models, Biological; D008957:Models, Genetic; D008962:Models, Theoretical; D015398:Signal Transduction; D014158:Transcription, Genetic
chemical_list: D029968:Escherichia coli Proteins