| Grant number: | 12/22921-8 |
| Support Opportunities: | Research Grants - Young Investigators Grants |
| Start date: | March 01, 2015 |
| End date: | February 29, 2020 |
| Field of knowledge: | Biological Sciences - Biochemistry - Molecular Biology |
| Principal Investigator: | Rafael Silva Rocha |
| Grantee: | Rafael Silva Rocha |
| Host Institution: | Faculdade de Medicina de Ribeirão Preto (FMRP). Universidade de São Paulo (USP). Ribeirão Preto , SP, Brazil |
| City of the host institution: | Ribeirão Preto |
| Associated researchers: | Stephen Busby ; Víctor de Lorenzo |
| Associated scholarship(s): | 19/14883-8 - Reconstruction of the gene regulatory network in Pseudomonas aeruginosa,
BP.IC 19/06672-7 - Genome assembly for identification of antibiotic resistance genes in clinical isolates of the Hospital das Clínicas de Ribeirão Preto, BP.IC 19/04942-7 - Synthetic biology applied to Rhodosporidium toruloides for fine chemical production, BP.DR + associated scholarships - associated scholarships |
Abstract
The ability to coordinate expression of thousands of genes in response to different stimuli is an essential feature of any live organism. However, current knowledge on this matter is largely inferred from data on extant systems involving just a few regulatory components. In this context, this project propose the adoption of a genetically tractable experimental object (Escherichia coli) along with the conceptual and material tools of Synthetic Biology for examining the molecular mechanisms (hardware) and the underlying logic program (software) that account for the regulatory behavior of complex biological systems. The principal approach to this end will involve the generation of synthetic promoter libraries assembled adjacent to combinatorial arrays of upstream binding sequences for five known global regulators (IHF, Fis, Crp, NarL and Fnr). The behavior of the resulting promoter libraries will be thoroughly parameterized in single cells and in populations as a whole for quantification of their transcriptional capacity, kinetics and stochastic noise. The resulting data will be employed to feed computational models for identifying general rules that account for the regulation of the thereby generated promoters and predict the outcome of new ones. We expect that the results of this endeavor will contribute not only a fundamental understanding mechanisms of signal integration in prokaryotic promoters, but will also produce rules and methods for designing and building standardized, integrated biological systems to accomplish many particular tasks of biotechnological interest. (AU)
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