The Symbiosis Interactome: a computational approach reveals novel components, functional interactions and modules in Sinorhizobium meliloti.
| Autor: | Rodriguez-Llorente I; Dpt, of Molecular Biology and Biochemistry, University of Malaga, Malaga, Spain. irodri@us.es, Caviedes MA, Dary M, Palomares AJ, Cánovas FM, Peregrín-Alvarez JM |
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| Jazyk: | angličtina |
| Zdroj: | BMC systems biology [BMC Syst Biol] 2009 Jun 16; Vol. 3, pp. 63. Date of Electronic Publication: 2009 Jun 16. |
| DOI: | 10.1186/1752-0509-3-63 |
| Abstrakt: | Background: Rhizobium-Legume symbiosis is an attractive biological process that has been studied for decades because of its importance in agriculture. However, this system has undergone extensive study and although many of the major factors underpinning the process have been discovered using traditional methods, much remains to be discovered. Results: Here we present an analysis of the 'Symbiosis Interactome' using novel computational methods in order to address the complex dynamic interactions between proteins involved in the symbiosis of the model bacteria Sinorhizobium meliloti with its plant hosts. Our study constitutes the first large-scale analysis attempting to reconstruct this complex biological process, and to identify novel proteins involved in establishing symbiosis. We identified 263 novel proteins potentially associated with the Symbiosis Interactome. The topology of the Symbiosis Interactome was used to guide experimental techniques attempting to validate novel proteins involved in different stages of symbiosis. The contribution of a set of novel proteins was tested analyzing the symbiotic properties of several S. meliloti mutants. We found mutants with altered symbiotic phenotypes suggesting novel proteins that provide key complementary roles for symbiosis. Conclusion: Our 'systems-based model' represents a novel framework for studying host-microbe interactions, provides a theoretical basis for further experimental validations, and can also be applied to the study of other complex processes such as diseases. |
| Databáze: | MEDLINE |
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