We present a genome-scale metabolic reconstruction for the extreme halophile Halobacterium salinarum. The reconstruction represents a summary of the knowledge regarding the organism's metabolism, and has already led to new research directions and improved the existing annotation. We used the network for computational analysis and studied the aerobic growth of the organism using dynamic simulations in media with 15 available carbon and energy sources. Simulations resulted in predictions for the internal fluxes, which describe at the molecular level how the organism lives and grows. We found numerous indications that cells maximized energy production even at the cost of longer term concerns such as growth prospects. Simulations showed a very low carbon incorporation rate of only ≈15%. All of the supplied nutrients were simultaneously degraded, unexpectedly including five which are essential. These initially surprising behaviors are likely adaptations of the organism to its natural environment where growth occurs in blooms. In addition, we also examined specific aspects of metabolism, including how each of the supplied carbon and energy sources is utilized. Finally, we investigated the consequences of the model assumptions and the network structure on the quality of the flux predictions.
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