Yeast Genome-Scale Metabolic Models for Simulating Genotype-Phenotype Relations.

Area of Science:

• Systems Biology
• Metabolic Engineering
• Yeast Genetics

Background:

• Understanding genotype-phenotype relationships is crucial across life sciences.
• Metabolic phenotypes are increasingly accessible via genome-scale metabolic model (GSMM) simulations.
• GSMMs are available for key yeast species and can be reconstructed for others.

Purpose of the Study:

• To provide an overview of yeast GSMMs and simulation approaches.
• To explore how GSMMs can interrogate genotype-phenotype relations.
• To inspire novel research questions and applications using GSMMs.

Main Methods:

• Utilizing GSMM simulations to analyze metabolic phenotypes.
• Integrating omics data within GSMM frameworks.
• Reviewing methodological approaches based on biological reasoning.

Main Results:

• GSMM simulations allow simultaneous consideration of nutrient availability, redox, and energy homeostasis.
• GSMMs provide a framework for omics data integration to understand genotype-phenotype regulation.
• Methodological review highlights potential applications for GSMMs in yeast research.

Conclusions:

• Yeast GSMMs are powerful tools for dissecting genotype-phenotype dependencies.
• Simulation approaches offer insights into metabolic regulation and cellular homeostasis.
• Continued development and application of GSMMs hold significant promise for future biological discoveries.