Baseline Proteome Analysis of the Anoxygenic Phototrophic Bacterium
Rhodopseudomonas palustris under Major Metabolic States

Rhodopseudomonas palustris is a purple nonsulfur anoxygenic phototrophic bacterium that is ubiquitous in soil and water samples. R. palustris is of great interest due to its high metabolic diversity, ability to fix carbon dioxide, potential for hydrogen production, and ability to biodegrade organic pollutants under both aerobic and anaerobic conditions.

R. palustris is currently the focus of an interdisciplinary study through DOE's Genomes to Life program. The long-range objective of this interdisciplinary study is to examine how processes of global carbon sequestration (CO₂ fixation), nitrogen fixation, sulfur oxidation, energy generation from light, biofuel (hydrogen) production, organic carbon catabolism and metal reduction operate in a single microbial cell through traditional and systems biology approaches. The annotated genome of this microbe (Larimer et al, Nature Biotech, 2004) reveals ~4836 potential protein encoding genes in a 5.459Mb genome. The genome sequencing effort has paved the way for detailed system biology studies such as transcriptomics, proteomics, protein-protein interactions studies and metabolomics. By coupling information from global experimentation with more traditional approaches such as gene knockouts we hope to gain insight into the complex metabolism of this diverse microbe.

This study's focus is the detailed mapping of the R. palustris proteome under all its known major metabolic modes. This baseline proteome map under major metabolic states provides a starting point for more detailed proteome and protein-protein interactions studies. Because these results are openly available, the information can easily be integrated with other studies within the microbial cell project. Rapidly advancing LC-MS/MS technologies have now allowed for the reproducible and rapid analysis of protein complexes and proteomes from microbial species. These technologies can now be directly tied to genomic tools to allow for a detailed analysis of a microbial species at the systems level. Our goal is to use multi-level proteomics technologies to obtain a greater understanding of the diverse metabolic states of this microbe and the proteins important to the individual growth states. For the initial foundation of this project, we have analyzed the baseline proteome of R. palustris wild-type strain grown under numerous conditions including photoheterotrophic, chemoheterotrophic, nitrogen fixation, photoautotrophic, stationary phase, as well as benzoate as an alternate carbon source. Specifically, we are studying the expression of redundant genes, identifying changes unique to each growth state, and developing protein targets for large-scale analysis of protein machines from this microbe