Genome-Scale Metabolic\nModel Reconstruction and Investigation\ninto the Fluxome of the Fast-Growing Cyanobacterium <i>Synechococcus</i> sp. PCC 11901

The ability to convert atmospheric CO<sub>2</sub> and\nlight into\nbiomass and value-added chemicals makes cyanobacteria a promising\nresource microbial host for biotechnological applications. A newly\ndiscovered fastest-growing cyanobacterial strain, <i>Synechococcus</i> sp. PCC 11901, has been reported to have the highest biomass accumulation\nrate, making it a preferred target host for producing renewable fuels,\nvalue-added biochemicals, and natural products. System-level knowledge\nof an organism is imperative to understand the metabolic potential\nof the strain, which can be attained by developing genome-scale metabolic\nmodels (GEMs). We present the first genome-scale metabolic model of <i>Synechococcus</i> sp. PCC 11901 (iRS840), which contains 840\ngenes, 1001 reactions, and 944 metabolites. The model has been optimized\nand validated under different trophic modes, i.e., autotrophic and\nmixotrophic, by conducting an <i>in vivo</i> growth experiment.\nThe robustness of the metabolic network was evaluated by changing\nthe biomass coefficient of the model, which showed a higher sensitivity\ntoward pigments under the photoautotrophic condition, whereas under\nthe heterotrophic condition, amino acids were found to be more influential.\nFurthermore, it was discovered that PCC 11901 synthesizes succinyl-CoA\nvia succinic semialdehyde due to its imperfect TCA cycle. Subsequent\nflux balance analysis (FBA) revealed a quantum yield of 0.16 in silico,\nwhich is higher compared to that of PCC 6803. Under mixotrophic conditions\n(with glycerol and carbon dioxide), the flux through the Calvin cycle\nincreased compared to autotrophic conditions. This model will be useful\nfor gaining insights into the metabolic potential of PCC 11901 and\ndeveloping effective metabolic engineering strategies for product\ndevelopment.