Applied Microbiology and Biotechnology

, Volume 80, Issue 5, pp 849–862

Genome-scale reconstruction and in silico analysis of the Clostridium acetobutylicum ATCC 824 metabolic network

  • Joungmin Lee
  • Hongseok Yun
  • Adam M. Feist
  • Bernhard Ø. Palsson
  • Sang Yup Lee
Genomics and Proteomics

DOI: 10.1007/s00253-008-1654-4

Cite this article as:
Lee, J., Yun, H., Feist, A.M. et al. Appl Microbiol Biotechnol (2008) 80: 849. doi:10.1007/s00253-008-1654-4

Abstract

To understand the metabolic characteristics of Clostridium acetobutylicum and to examine the potential for enhanced butanol production, we reconstructed the genome-scale metabolic network from its annotated genomic sequence and analyzed strategies to improve its butanol production. The generated reconstructed network consists of 502 reactions and 479 metabolites and was used as the basis for an in silico model that could compute metabolic and growth performance for comparison with fermentation data. The in silico model successfully predicted metabolic fluxes during the acidogenic phase using classical flux balance analysis. Nonlinear programming was used to predict metabolic fluxes during the solventogenic phase. In addition, essential genes were predicted via single gene deletion studies. This genome-scale in silico metabolic model of C. acetobutylicum should be useful for genome-wide metabolic analysis as well as strain development for improving production of biochemicals, including butanol.

Keywords

Genome-scale metabolic network In silico Metabolic flux analysis Clostridium acetobutylicum Butanol 

Supplementary material

253_2008_1654_MOESM1_ESM.pdf (925 kb)
Supplementary Data 1Gene–protein–reaction relationship, metabolite abbreviation, and whole reaction set used in the model. (PDF 548 KB)
253_2008_1654_MOESM2_ESM.pdf (86 kb)
Supplementary Data 2Biomass composition of C. acetobutylicum, ATCC 824 used in the model. (PDF 79.6 KB)
253_2008_1654_MOESM3_ESM.pdf (61 kb)
Supplementary Data 3The list of essential and partially essential genes in synthetic medium from in silico gene deletion analysis. (PDF 60.8 KB)

Copyright information

© Springer-Verlag 2008

Authors and Affiliations

  • Joungmin Lee
    • 1
  • Hongseok Yun
    • 1
  • Adam M. Feist
    • 2
  • Bernhard Ø. Palsson
    • 2
  • Sang Yup Lee
    • 1
    • 3
  1. 1.Metabolic and Biomolecular Engineering National Research Laboratory, Department of Chemical & Biomolecular Engineering (BK21 Program), BioProcess Engineering Research Center, Center for Systems and Synthetic Biotechnology and Institute for the BioCenturyKAISTDaejeonRepublic of Korea
  2. 2.Department of BioengineeringUniversity of CaliforniaSan Diego, La JollaUSA
  3. 3.Department of Bio and Brain Engineering, Department of Biological Sciences and Bioinformatics Research CenterKAISTDaejeonRepublic of Korea

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