Abstract
Marine cyanobacteria are promising microbes to capture and convert atmospheric CO2 and light into biomass and valuable industrial bio-products. Yet, reports on metabolic characteristics of non-model cyanobacteria are scarce. In this report, we show that an Indian euryhaline Synechococcus sp. BDU 130192 has biomass accumulation comparable to a model marine cyanobacterium and contains approximately double the amount of total carbohydrates, but significantly lower protein levels compared to Synechococcus sp. PCC 7002 cells. Based on its annotated chromosomal genome sequence, we present a genome scale metabolic model (GSMM) of this cyanobacterium, which we have named as iSyn706. The model includes 706 genes, 908 reactions, and 900 metabolites. The difference in the flux balance analysis (FBA) predicted flux distributions between Synechococcus sp. PCC 7002 and Synechococcus sp. BDU130192 strains mimicked the differences in their biomass compositions. Model-predicted oxygen evolution rate for Synechococcus sp. BDU130192 was found to be close to the experimentally-measured value. The model was analyzed to determine the potential of the strain for the production of various industrially-useful products without affecting growth significantly. This model will be helpful to researchers interested in understanding the metabolism as well as to design metabolic engineering strategies for the production of industrially-relevant compounds.
Highlights
Photosynthesis captures solar energy and converts atmospheric carbon dioxide into organic compounds [1]
We have measured the macromolecular composition of biomass of this organism and created a genome scale metabolic model (GSMM) for this cyanobacterium to help in understanding its metabolic capabilities
Our results suggest that mainly the photon intake and oxygen evolution change slightly, while the underlying flux distribution, which is a function of biomass equation and metabolic network, isn’t altered significantly
Summary
Photosynthesis captures solar energy and converts atmospheric carbon dioxide into organic compounds [1]. Genome-scale metabolic models (GSMMs) are large-scale stoichiometric models based on the annotated genome sequence that contain metabolic reactions present in the majority of pathways of the organism These models allow qualitative predictions such as testing of gene essentiality and the metabolic responses to environmental perturbations, as well as quantitative predictions such as ratios of nutrient utilization, central carbon metabolism fluxes, cell growth and nutrient exchanges under different growth conditions [12]. The model was employed to determine the biotechnological potential of the native cyanobacterium for various bioproducts and to determine engineering targets for the production of heterologous compounds
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