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BMC Bioinformatics. 2000;1:1. Epub 2000 Jul 27.

Metabolic flux balance analysis and the in silico analysis of Escherichia coli K-12 gene deletions.

Author information

  • 1Department of Bioengineering, University of California, San Diego La Jolla, CA 92093-0412, USA. jedwards@arep.med.harvard.edu

Abstract

BACKGROUND:

Genome sequencing and bioinformatics are producing detailed lists of the molecular components contained in many prokaryotic organisms. From this 'parts catalogue' of a microbial cell, in silico representations of integrated metabolic functions can be constructed and analyzed using flux balance analysis (FBA). FBA is particularly well-suited to study metabolic networks based on genomic, biochemical, and strain specific information.

RESULTS:

Herein, we have utilized FBA to interpret and analyze the metabolic capabilities of Escherichia coli. We have computationally mapped the metabolic capabilities of E. coli using FBA and examined the optimal utilization of the E. coli metabolic pathways as a function of environmental variables. We have used an in silico analysis to identify seven gene products of central metabolism (glycolysis, pentose phosphate pathway, TCA cycle, electron transport system) essential for aerobic growth of E. coli on glucose minimal media, and 15 gene products essential for anaerobic growth on glucose minimal media. The in silico tpi-, zwf, and pta- mutant strains were examined in more detail by mapping the capabilities of these in silico isogenic strains.

CONCLUSIONS:

We found that computational models of E. coli metabolism based on physicochemical constraints can be used to interpret mutant behavior. These in silica results lead to a further understanding of the complex genotype-phenotype relation.

PMID:
11001586
[PubMed - indexed for MEDLINE]
PMCID:
PMC29061
Free PMC Article

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