Cyanobacteria have flexible metabolic capability that enables them to adapt to various environments. To investigate their underlying metabolic regulation mechanisms, we performed an integrated analysis of metabolic flux using transcriptomic and metabolomic data of a cyanobacterium Synechocystis sp. PCC 6803, under mixotrophic and photoheterotrophic conditions. The integrated analysis indicated drastic metabolic flux changes, with much smaller changes in gene expression levels and metabolite concentrations between the conditions, suggesting that the flux change was not caused mainly by the expression levels of the corresponding genes. Under photoheterotrophic conditions, created by the addition of the photosynthesis inhibitor atrazine in mixotrophic conditions, the result of metabolic flux analysis indicated the significant repression of carbon fixation and the activation of the oxidative pentose phosphate pathway (PPP). Moreover, we observed gluconeogenic activity of upstream of glycolysis, which enhanced the flux of the oxidative PPP to compensate for NADPH depletion due to the inhibition of the light reaction of photosynthesis. 'Omics' data suggested that these changes were probably caused by the repression of the gap1 gene, which functions as a control valve in the metabolic network. Since metabolic flux is the outcome of a complicated interplay of cellular components, integrating metabolic flux with other 'omics' layers can identify metabolic changes and narrow down these regulatory mechanisms more effectively.

Cyanobacteria have received considerable attention as a sustainable energy resource because of their organic material production capacity using light energy and CO2 as a carbon source. Therefore, it is important to understand the cellular metabolism of cyanobacteria for metabolic engineering. In this study, to shed light on the central metabolism of cyanobacteria, we performed transcriptomic and metabolomic analyses of a glucose-tolerant strain of the cyanobacterium Synechocystis sp. PCC 6803, which was cultured under auto- and mixotrophic conditions. Our results indicate that the oxidative pentose phosphate pathway and glycolysis are activated under mixotrophic conditions rather than autotrophic conditions. Moreover, we examined the effect of atrazine, a photosynthesis inhibitor, on the metabolism of PCC 6803 under mixotrophic conditions, which was defined as photoheterotrophic conditions, by transcriptomics and metabolomics. We demonstrated that the activity of the glycolytic pathway decreased due to the indirect effect of atrazine. In addition, the difference in transcriptional and metabolic changes between auto- and photoheterotrophic conditions could also be captured. The omics dataset reported herein provides clues for understanding the metabolism of cyanobacteria.

In terms of generating sustainable energy resources, the prospect of producing energy and other useful materials using cyanobacteria has been attracting increasing attention since these processes require only carbon dioxide and solar energy. To establish production processes with a high productivity, in silico models to predict the metabolic activity of cyanobacteria are highly desired. In this study, we reconstructed a genome-scale metabolic model of the cyanobacterium Synechocystis sp. PCC6803, which included 465 metabolites and 493 metabolic reactions. Using this model, we performed constraint-based metabolic simulations to obtain metabolic flux profiles under various environmental conditions. We evaluated the simulated results by comparing these with experimental results from (13)C-tracer metabolic flux analyses, which were obtained under heterotrophic and mixotrophic conditions. There was a good agreement of simulation and experimental results under both conditions. Furthermore, using our model, we evaluated the production of ethanol by Synechocystis sp. PCC6803, which enabled us to estimate quantitatively how its productivity depends on the environmental conditions. The genome-scale metabolic model provides useful information for the evaluation of the metabolic capabilities, and prediction of the metabolic characteristics, of Synechocystis sp. PCC6803.