Next-Generation Genome-Scale Models Incorporating Multilevel 'Omics Data: From Yeast to Human

Area of Science:

• Systems Biology
• Computational Biology
• Eukaryotic Modeling

Background:

• Yeast Saccharomyces cerevisiae pioneered genome-scale modeling.
• Early models focused on metabolic, protein-protein interaction, and gene regulatory networks.
• Network reconstruction utilized genome sequences, literature, and experimental data (e.g., yeast-2-hybrid).

Purpose of the Study:

• To provide a historical perspective on the evolution of genome-scale models.
• To highlight the integration of multi-omics data in next-generation models.
• To demonstrate the translation of yeast modeling insights to human biology.

Main Methods:

• Reconstruction of metabolic networks from genomic and literature data.
• Construction of protein-protein interaction networks using experimental methods.
• Development of gene regulatory networks integrating TF-promoter binding and gene coexpression data.
• Integration of diverse omics data (genomics, metabolomics, transcriptomics, fluxome, phosphoproteome).

Main Results:

• Gradual improvement and integration of various biological networks.
• Development of next-generation genome-scale models incorporating multi-level omics data.
• Successful application of yeast modeling methodologies to human systems.
• Identification of conserved cellular components and regulatory mechanisms between yeast and human.

Conclusions:

• Genome-scale modeling has evolved significantly, driven by yeast research.
• Multi-omics data integration is crucial for advanced eukaryotic models.
• Yeast models provide valuable insights into human physiology and disease states.