Abstract
BackgroundRhizobium-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.ResultsHere 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.ConclusionOur '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.
Highlights
Rhizobium-Legume symbiosis is an attractive biological process that has been studied for decades because of its importance in agriculture
We present an analysis of the 'Symbiosis Interactome' by first mapping proteins known to be involved in symbiosis on top of the S. meliloti network, and secondly, by extending this resulting network by means of a novel method, referred here as 'phenotypic profiling', which is further extended by incorporating data from the computational prediction of functional modules
The analysis showed that the intersection dataset has a higher accuracy (AUC = 0.75) than the union dataset (AUC = 0.69), and these two networks have bigger accuracies than any of the two independent databases
Summary
Rhizobium-Legume symbiosis is an attractive biological process that has been studied for decades because of its importance in agriculture. Plant-microbe interactions play an important role in agriculture and a lot of effort has been dedicated to analyse these interactions in detail One of these interactions is the Rhizobium-Legume symbiosis, a process that allows the growth of the plant in the absence of externally supplied nitrogen. This is a well studied agronomically important process that is used as a model to study general genetic aspects of plant-microbe interactions [1,2]. Rhizobial bacteria and legumes have evolved complex signal exchange mechanisms in which a lot of genes are involved [3]. S. meliloti is a model bacterium that can engage in a symbiotic interaction by infecting the roots of members of the genera Medicago and Melilotus, being the S. meliloti-Medicago truncatula interaction the model system for indeterminate type nodules [5]
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