Two Decades of Genome-Scale Metabolic Modeling for Saccharomyces cerevisiae

Saccharomyces cerevisiae (baker’s yeast) is both a highly valuable industrial microorganism and a central model system in biological and medical research. Its importance is strengthened by being the first eukaryote to have its genome fully sequenced and publicly released, providing the basis for systematic studies of cellular function, regulation, and metabolism. Using this genomic foundation, researchers have developed at least 16 genome-scale metabolic models over the past two decades. These reconstructions integrate extensive biochemical, genetic, and physiological data to map the yeast metabolic network and its gene–reaction relationships. Genome scale metabolic models are commonly analyzed using flux balance analysis, a constraint-based computational framework that represents metabolism through stoichiometric matrices and applies mass-balance. By optimizing biological objectives such as biomass production, flux balance analysis predicts feasible flux distributions without requiring detailed kinetic parameters. Together, genome scale metabolic models and flux balance analysis form a powerful platform for studying yeast metabolism, enabling large-scale predictions of growth, gene essentiality, metabolic bottlenecks, theoretical yields, and responses to genetic or environmental changes. This review summarizes key advances in genome-scale metabolic modeling of Saccharomyces cerevisiae over the past twenty three years.