Binary protein interactions form the basic building blocks of molecular networks and dynamic assemblies that control all cellular functions of bacteria. Although these protein interactions are a potential source of targets for the development of new antibiotics， few high-confidence data sets are available for the large proteomes of most pathogenic bacteria. We used a library of recombinant proteins from the plague bacterium Yersinia pestis to probe planar microarrays of immobilized proteins that represented ∼85% (3552 proteins) of the bacterial proteome， resulting in >77，000 experimentally determined binary interactions. Moderate (K ∼μm) to high-affinity (K ∼nm) interactions were characterized for ... More
Binary protein interactions form the basic building blocks of molecular networks and dynamic assemblies that control all cellular functions of bacteria. Although these protein interactions are a potential source of targets for the development of new antibiotics， few high-confidence data sets are available for the large proteomes of most pathogenic bacteria. We used a library of recombinant proteins from the plague bacterium Yersinia pestis to probe planar microarrays of immobilized proteins that represented ∼85% (3552 proteins) of the bacterial proteome， resulting in >77，000 experimentally determined binary interactions. Moderate (K ∼μm) to high-affinity (K ∼nm) interactions were characterized for >1600 binary complexes by surface plasmon resonance imaging of microarrayed proteins. Core binary interactions that were in common with other gram-negative bacteria were identified from the results of both microarray methods. Clustering of proteins within the interaction network by function revealed statistically enriched complexes and pathways involved in replication， biosynthesis， virulence， metabolism， and other diverse biological processes. The interaction pathways included many proteins with no previously known function. Further， a large assembly of proteins linked to transcription and translation were contained within highly interconnected subregions of the network. The two-tiered microarray approach used here is an innovative method for detecting binary interactions， and the resulting data will serve as a critical resource for the analysis of protein interaction networks that function within an important human pathogen.
