metano

metano analyzes genome-scale metabolic networks using a metabolite-centric approach to interpret flux distributions and refine genome-scale metabolic models (GEMs) with mathematical optimization methods such as flux balance analysis (FBA).

Key Features:

• Metabolite-Centric Framework: Focuses analysis on metabolites to provide an integrated view of flux distributions within metabolic networks.
• Model Refinement via Currency Metabolite Balance Sheets: Compiles balance sheets for currency metabolites to characterize energy metabolism predictions and identify refinement targets such as NADPH metabolism.
• Flux Balance Analysis (FBA) and GEM Support: Uses genome-scale metabolic models and mathematical optimization (FBA) for in-silico prediction of cellular phenotypes.
• Identification of Functional Roles at Branch Points: Enables examination of branch points to identify functional roles and flag enzymatic reactions (e.g., fructose 6-phosphate aldolase and the sedoheptulose bisphosphate bypass) that may carry model-predicted high fluxes unlikely in vivo.
• Metabolite Essentiality Analysis: Performs essentiality analyses to detect problematic assumptions such as unconstrained import/export of ions (e.g., iron) that affect model predictions.
• System-Wide Split Ratio and Branch Point Analysis: Analyzes split ratios and branch points across the network to reveal system-wide insights beyond isolated reaction fluxes.

Scientific Applications:

• Refinement of Genome-Scale Reconstructions: Refines metabolic reconstructions for specific growth scenarios by interpreting integrated flux distributions.
• Characterization of Energy and One-Carbon Metabolism: Supports analysis of energy metabolism and folate-dependent one-carbon pools, including redox cofactors such as NADPH.
• Detection of Unrealistic Model Behaviors: Identifies likely spurious high-flux reactions and unconstrained exchanges (e.g., iron) that compromise model accuracy.
• Application to Model Organisms: Demonstrated utility on the most recent metabolic reconstruction of Escherichia coli to guide model refinements and functional annotation.

Methodology:

Compiling balance sheets for selected currency metabolites and integrating metabolite-centric analyses with flux distributions from genome-scale metabolic models using flux balance analysis (FBA) and mathematical optimization, as demonstrated on an Escherichia coli metabolic reconstruction.