(590c) Constraint-Based Modeling of Cyanobacterial Metabolism
The U.S. currently needs alternative renewable sources of energy to reduce our dependence on fossil-fuels, which are becoming increasingly limited and expensive. Research investments and efforts focused on developing clean and efficient processes for sustainable fuel production, of which hydrogen is considered as one of the promising future fuels . Among bio-based hydrogen-producing processes, oxygenic photosynthesis receives great interest, since light energy is converted to chemical energy using water as electron donor for reduction of electron carriers (ferredoxin and NADPH), which can subsequently be used to generate hydrogen. Oxygenic photosynthetic microorganisms display varying levels of light conversion efficiencies, which ultimately translate into different rates of electron transfer, growth, and hydrogen production. Developing a model for such organisms will offer solutions to fundamental science questions of how different factors are interconnected at a system level, and affect cellular phenotypes. In addition, the model will have the ability to serve as an in silico tool for manipulating photosynthetic microorganisms to act as catalysts for solar energy conversion and will potentially allow development of a highly efficient biofuel production process.
We have built a genome-scale constraint-based metabolic model for Cyanothece sp. ATCC 51142, a unicellular diazotrophic cyanobacterium that can temporally separate the process of light-dependent autotrophic growth and glycogen accumulation from N2 fixation. The resulting model currently includes 806 genes, 585 metabolites, and 664 reactions accounting for common pathways such as central metabolism, respiration, nucleotide and amino acid biosynthesis, and those that are more unique to cyanobacteria such as photosynthesis, carbon fixation, and cyanophycin production. Photosynthesis was modeled as a set of three sequential reactions that involve photosystem II, cytochrome b6f complex, and photosystem I. This was done in order to study how light intensities of different wavelengths of light and separate photosystem activities affect electron flow through photosynthesis and respiration, nitrogen source utilization, cellular growth and hydrogen production.
Data on glycogen requirement for nitrogen fixation in the dark  and amino acid utilization as sole nitrogen sources have been used to test and refine the model. Additionally, we have used the model to estimate energy requirements for Cyanothece sp. ATCC 51142 using experimental batch data collected with different light wavelengths of various intensities. We have subsequently used the model to investigate how flux through different photosystems affects cellular growth and fluxes through linear and cyclic photosynthesis pathways, cytochrome oxidases, NADH dehydrogenases, Mehler reactions, and ferredoxin-NADP reductase.
Using a custom-built photobioreactor, which allows for the control and monitoring of incident and transmitted light, we have measured biomass composition, gene expression and protein expression of Cyanothece sp. ATCC 51142 under nitrogen- and light-limited chemostat conditions. These experimental datasets have been incorporated into the model to improve flux predictions for both chemostat conditions. In the future, the model will be used to simulate hydrogen production rates, and to suggest metabolic engineering strategies for improving hydrogen and chemical production.
1. Dunn S: Hydrogen futures: toward a sustainable energy system. International Journal of Hydrogen Energy 2002, 27(3):235-264.
2. Schneegurt MA, Sherman DM, Sherman LA: Growth, physiology and ultrastructure of a diazotrophic cyanobacterium, Cyanothece sp. strain ATCC 51142 in mixotrophic and chemoheterotrophic cultures. Journal of Phycology 1997, 33:632-642.