K-124. Experimental Determination and Data Analysis of Protein-Protein Interactions in Rhodopseudomonas palustris

D. A. Pelletier1, G. B. Hurst1, P. K. Lankford1, C. K. McKeown1, T-Y. S. Lu1, E. T. Owens1, D. D. Schmoyer1, J. L. Morrell-Falvey1, W. H. McDonald1, M. Shah1, M. J. Doktycz1, B. S. Hooker2, W. R. Cannon2, D. Daly2, M. Singhal2, R. Taylor2, M. V. Buchanan1;
1Oak Ridge Natl. Lab., Oak Ridge, TN, 2Pacific Northwest Natl. Lab., Richland, WA.

Rhodopseudomonas palustris is a metabolically diverse anoxygenic phototrophic bacterium with potential use in bioremediation and nitrogenase-mediated biohydrogen production. As part of the Genomics:GTL Center for Molecular and Cellular Systems (CMCS) over the past several years we have been mapping protein-protein interactions of the soluble proteome of R. palustris. Toward this goal, we have implemented methodology for systematically identifying the proteins that interact with an affinity-tagged “bait” protein expressed from a plasmid introduced into R. palustris. The steps in this methodology include target or “bait” selection, PCR amplification, cloning, transformation, batch culture, affinity purification, mass spectrometry based identification of protein interactors, and statistical analysis of interaction data. As of January 2008, we have constructed over 1100 clones for expression of dual affinity tag (V5/6xHis) fusion proteins in R. palustris. While these “bait” proteins include homologues of members of well-characterized protein complexes involved in known metabolic networks, approximately 30% of these bait proteins are annotated as conserved or novel proteins of unknown function. Some 467 affinity-tagged bait proteins have been successfully affinity purified from cultures of R. palustris grown under anaerobic photoheterotrophic growth conditions and subjected to mass spectrometry (MS) analysis to identify interacting proteins. The resulting experimental data is then subjected to statistical analysis and confidence scores assigned to bait/prey interactions. Here we will present results on known as well as novel protein-protein interactions identified by this approach. Bioinformatic integration with other data, including comparative genomics, transcriptomics, operon structure, and regulatory networks, that will aid in interpretation and functional annotation of novel interactions is under way. These protein-protein interactions are disseminated through the publicly accessible Microbial Protein-Protein Interaction Database (MiPPI.ornl.gov).