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Predictive understanding of the myriads of signal transduction pathways in acell is an outstanding challenge of systems biology. Such pathways areprimarily mediated by specific but transient protein-protein interactions,which are difficult to study experimentally. In this study, we dissect thespecificity of protein-protein interactions governing two-component signaling(TCS) systems ubiquitously used in bacteria. Exploiting the large number ofsequenced bacterial genomes and an operon structure which packages many pairsof interacting TCS proteins together, we developed a computational approach toextract a molecular interaction code capturing the preferences of a small butcritical number of directly interacting residue pairs. This code is found toreflect physical interaction mechanisms, with the strongest signal coming fromcharged amino acids. It is used to predict the specificity of TCS interaction:Our results compare favorably to most available experimental results, includingthe prediction of 7 (out of 8 known) interaction partners of orphan signalingproteins in Caulobacter crescentus. Surveying among the available bacterialgenomes, our results suggest 15~25% of the TCS proteins could participate inout-of-operon "crosstalks". Additionally, we predict clusters of crosstalkingcandidates, expanding from the anecdotally known examples in model organisms.The tools and results presented here can be used to guide experimental studiestowards a system-level understanding of two-component signaling.

Dissecting the Specificity of Protein-Protein Interaction in Bacterial Two-Component Signaling: Orphans and Crosstalks