ComMet

ComMet compares metabolic states using genome-scale metabolic models (GEMs) to analyze and contrast achievable metabolic flux spaces and identify metabolically distinct network modules.

Key Features:

• Genome-scale metabolic model analysis: Operates on genome-scale metabolic models (GEMs) to represent and analyze cellular metabolism.
• In-depth flux characterization: Enables detailed characterization of achievable metabolic flux states within a metabolic network.
• Comparative flux-space analysis: Compares flux spaces across multiple conditions to identify biochemical differences and similarities.
• Objective selection and reaction flux constraints: Implements structured objective selection and reaction flux constraints for condition-specific analyses.
• Module identification and visualization: Identifies and visualizes metabolically distinct network modules to reveal network modularity.
• Scalability to large models: Handles large-scale GEMs, including human models such as iAdipocytes1809.

Scientific Applications:

• Human adipocyte metabolism: Applied to iAdipocytes1809 to compare metabolic states with unlimited versus blocked branched-chain amino acid uptake.
• Cross-condition metabolic comparison: Used to explore metabolic variations across microbial and human models under different environmental or genetic conditions.

Methodology:

Leverages genome-scale metabolic models (GEMs) to systematically analyze large-scale metabolic flux spaces, applies structured objective selection and reaction flux constraints, compares flux spaces across conditions, and identifies and visualizes metabolically distinct network modules.