Global insights into energetic and metabolic networks in Rhodobacter sphaeroides

BACKGROUND: Improving our understanding of processes at the core of cellular lifestyles can be aided by combining information from genetic analyses, high-throughput experiments and computational predictions. RESULTS: We combined data and predictions derived from phenotypic, physiological, genetic and computational analyses to dissect the metabolic and energetic networks of the facultative photosynthetic bacterium Rhodobacter sphaeroides. We focused our analysis on pathways crucial to the production and recycling of pyridine nucleotides during aerobic respiratory and anaerobic photosynthetic growth in the presence of an organic electron donor. In particular, we assessed the requirement for NADH/NADPH transhydrogenase enzyme, PntAB during respiratory and photosynthetic growth. Using high-throughput phenotype microarrays (PMs), we found that PntAB is essential for photosynthetic growth in the presence of many organic electron donors, particularly those predicted to require its activity to produce NADPH. Utilizing the genome-scale metabolic model iRsp1095, we predicted alternative routes of NADPH synthesis and used gene expression analyses to show that transcripts from a subset of the corresponding genes were conditionally increased in a ΔpntAB mutant. We then used a combination of metabolic flux predictions and mutational analysis to identify flux redistribution patterns utilized in the ΔpntAB mutant to compensate for the loss of this enzyme. Data generated from metabolic and phenotypic analyses of wild type and mutant cells were used to develop iRsp1140, an expanded genome-scale metabolic reconstruction for R. sphaeroides with improved ability to analyze and predict pathways associated with photosynthesis and other metabolic processes. CONCLUSIONS: These analyses increased our understanding of key aspects of the photosynthetic lifestyle, highlighting the added importance of NADPH production under these conditions. It also led to a significant improvement in the predictive capabilities of a metabolic model for the different energetic lifestyles of a facultative organism.