Designing pathways for bioproducing complex chemicals by combining tools for pathway extraction and ranking

The synthesis of many important biochemicals involves complex molecules and numerous reactions. The design and optimization of whole-cell biocatalysts for the production of these molecules requires metabolic modeling to extract production pathways from biochemical databases and integrate them into genome-scale models of the host. However, the synthesis of such complex molecules often requires reactions from multiple pathways operating in balanced subnetworks that are not assembled in existing databases. Here, we present SubNetX, a computational algorithm that extracts reactions from a database and assembles balanced subnetworks to produce a target biochemical from selected precursor metabolites, energy currencies, and cofactors. These subnetworks can be integrated into whole-cell models, allowing the reconstruction and ranking of alternative biosynthetic pathways based on yield, length, and other design goals. We apply SubNetX to 70 industrially relevant natural and synthetic chemicals to demonstrate the application of this pipeline.