In this study, a genome-scale metabolic model was constructed using published genomic and biochemical data. By employing the flux balance analysis (FBA) framework, the model was able to accurately predict ethanol yields on various carbon substrates, secretion profiles, and key characteristics of central metabolism under various growth conditions. A by-product of the model development was the construction of a pathway genome data-base (PGDB) of the yeast, named PichCyc. The PGDB was constructed using Pathway Tools and the database contains 5,841 genes, 1,457 reactions, 994 gene-associated reactions, and 1,475 metabolites. Pathway Tools also facilitated the annotation of an additional 155 genes through the use of Pathway Hole Filler. Together with the constraint-based model, a platform for model-guided metabolic engineering, high-throughput data contextualization, and a public-access online genomic/biochemical database was created.

In this study, a genome-scale metabolic model was constructed using published genomic and biochemical data. By employing the flux balance analysis (FBA) framework, the model was able to accurately predict ethanol yields on various carbon substrates, secretion profiles, and key characteristics of central metabolism under various growth conditions. A by-product of the model development was the construction of a pathway genome data-base (PGDB) of the yeast, named PichCyc. The PGDB was constructed using Pathway Tools and the database contains 5,841 genes, 1,457 reactions, 994 gene-associated reactions, and 1,475 metabolites. Pathway Tools also facilitated the annotation of an additional 155 genes through the use of Pathway Hole Filler. Together with the constraint-based model, a platform for model-guided metabolic engineering, high-throughput data contextualization, and a public-access online genomic/biochemical database was created.