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MicrobesFlux: a web platform for drafting metabolic models from the KEGG database.

Xueyang Feng1, You Xu, Yixin Chen

  • 1Department of Energy, Environmental and Chemical Engineering, Washington University, Saint Louis, MO 63130, USA. xfeng@illinois.edu

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|August 4, 2012
PubMed
Summary

MicrobesFlux is a new web platform that helps biologists build microbial metabolic models. This tool simplifies the process of reconstructing metabolic networks and predicting cellular metabolism using flux balance analysis.

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Area of Science:

  • Systems Biology
  • Metabolic Engineering
  • Bioinformatics

Background:

  • High-throughput sequencing enables microbial genome mapping.
  • Systems biologists construct metabolic models to predict cellular metabolism.
  • Developing metabolic models requires integrating genome annotations and network architecture from multiple databases.

Purpose of the Study:

  • To develop a user-friendly platform for constructing microbial metabolic networks.
  • To enable constraint-based flux balance analysis using genome databases and experimental data.
  • To accelerate metabolic model development for a wide range of microorganisms.

Main Methods:

  • Developed MicrobesFlux, a semi-automatic, web-based platform.
  • Automated downloading of metabolic networks for ~1,200 species from KEGG.
  • Provided tools for model reconstruction, including gene knockouts and heterologous pathway integration.
  • Formulated reconstructed networks into constraint-based flux models for analysis.
  • Exported simulation results in Systems Biology Markup Language (SBML) format.

Main Results:

  • MicrobesFlux successfully generated metabolic model drafts for ~1,200 microbial species.
  • Demonstrated platform functionality by creating a flux balance analysis (FBA) model for *Thermoanaerobacter* sp. strain X514.
  • Predicted biomass growth and ethanol production for the engineered microorganism.

Conclusions:

  • MicrobesFlux is an installation-free, open-source platform for biologists to develop metabolic models.
  • Facilitates reconstruction of metabolic networks and predictions of microbial metabolism via FBA.
  • Serves as a foundation for advanced biological system modeling by integrating 'omics' data.