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Metabolic Modeling with MetaFlux.

Mario Latendresse1, Wai Kit Ong1, Peter D Karp2

  • 1SRI International, Menlo Park, CA, USA.

Methods in Molecular Biology (Clifton, N.J.)
|October 31, 2021
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Summary
This summary is machine-generated.

MetaFlux software enables creating, executing, and solving metabolic flux models using flux balance analysis (FBA). It offers modes for solving, gene knockout, model development, and variability analysis, supporting dynamic FBA (dFBA) for single organisms and communities.

Keywords:
COBRA methodsCommunity modelingDynamic FBAFBAFlux balance analysisGene knockoutGenome-scale modelMetabolic modelSolverSteady-state

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Area of Science:

  • Systems Biology
  • Metabolic Engineering
  • Computational Biology

Background:

  • Quantitative metabolic flux models are crucial for understanding cellular metabolism.
  • Flux Balance Analysis (FBA) is a widely used computational method for analyzing these models.
  • Dynamic FBA (dFBA) extends FBA to capture temporal changes in metabolic networks.

Purpose of the Study:

  • To introduce MetaFlux, a software tool for creating, executing, and solving metabolic flux models.
  • To demonstrate the capabilities of MetaFlux across its four operational modes: solving, gene knockout, development, and flux variability analysis.
  • To showcase the application of MetaFlux for both individual organisms and microbial communities, including dynamic simulations.

Main Methods:

  • Utilizing MetaFlux software for metabolic flux modeling and analysis.
  • Applying Flux Balance Analysis (FBA) and dynamic FBA (dFBA) techniques.
  • Employing MetaFlux in both local (Pathway Tools required) and web-based environments.
  • Leveraging visualization tools like Cellular Overview and Omics Dashboard for result interpretation.

Main Results:

  • MetaFlux successfully supports the creation and execution of FBA and dFBA models.
  • The software provides distinct modes for model solving, gene knockout analysis, model development, and robustness assessment.
  • Visualization tools effectively represent metabolic reaction fluxes and community dynamics.

Conclusions:

  • MetaFlux is a versatile software tool that facilitates comprehensive analysis of metabolic flux models.
  • The software enhances the study of individual organisms and complex microbial communities through various analytical modes and visualization options.
  • MetaFlux empowers researchers in metabolic engineering and systems biology with robust computational capabilities.