Thermodynamic analysis of computed pathways integrated into the metabolic networks of E. coli and Synechocystis reveals contrasting expansion potential

摘要: Introducing biosynthetic pathways into an organism is both reliant on and challenged by endogenous biochemistry. Here we compared the expansion potential of metabolic network in photoautotroph Synechocystis with that heterotroph E. coli using novel workflow POPPY (Prospecting Optimal Pathways PYthon). First, metabolomic fluxomic data were combined models to identify thermodynamic constraints metabolite concentrations (NET analysis). Then, thousands automatically constructed placed within each subjected a network-embedded variant max-min driving force analysis (NEM). We found networks had different capabilities for imparting forces toward certain compounds. Key metabolites constrained differently due opposing flux directions glycolysis carbon fixation, forked tri-carboxylic acid cycle, photorespiration. Furthermore, lysine biosynthesis pathway was identified as thermodynamically constrained, impacting heterologous reactions through low 2-oxoglutarate levels. Our study also important yet poorly covered areas existing metabolomics provides reference future thermodynamics-based engineering beyond. The methodology represents step making optimal pathway-host matches, which likely become practical range host organisms diversified.