Constraint-Based Metabolic Modeling of Synechococcus elongatus PCC 11801 and PCC 11802 for Photosynthetic...

Constraint-based reconstruction and analysis (COBRA) is a powerful systems biology approach for computational bioengineering. Synechococcus elongatus PCC 11801 and PCC 11802 are fast-growing, stress-tolerant cyanobacteria that are promising platforms for photosynthetic biomanufacturing. Here, we present constraint-based models (CBMs) iLV1052 and iLV1087 of PCC 11801 and PCC 11802, respectively, to facilitate and streamline strain engineering efforts. Following draft reconstruction using a template model, the models underwent extensive manual curation to reduce redundancy, and verification using BiGG, KEGG, and BRENDA databases. We added 281 and 69 new reactions for PCC 11801 and PCC 11802, respectively, associated with stress tolerance, growth stability, antioxidant defense, energy regulation, and sulfur acquisition. The models were refined through iterative debugging and validation using flux balance analysis, flux variability analysis, and single gene/reaction deletion analysis. Gene essentiality predictions gave 69% accuracy for PCC 11801 and 83% for PCC 11802. The flux maps captured key features of cyanobacterial metabolism, including an incomplete TCA cycle. The final PCC 11801 CBM contained 1130 reactions, 1052 genes, and 930 metabolites, while the PCC 11802 CBM included 1199 reactions, 1087 genes, and 951 metabolites. The simulations predicted that succinic acid exhibited the highest theoretical yield among the tested target products in both strains. Using the Optknock framework, phosphoenolpyruvate carboxylase was identified as a metabolic hotspot for future bioengineering efforts aimed at the production of valuable products like ethanol, butanol, and butanediol.