Metabolic Models @Feb 10, 2011 5:12:42 PM

Genome-scale metabolic network reconstruction is important for understanding cellular behaviors in a systems view.

Converting the reconstruction into a mathematical model enables researchers to analyze cell behaviors in response to changing environments by using constraint-based flux balance analysis (FBA) tools, such as COBRA [1].

With the growing availability of complete microbial genomes, the number of genome-scale metabolic networks is expected to increase rapidly.

However, the number of genome-scale metabolic models follows in single-digit percentage of the number of sequenced genomes due to the difficulties in network reconstruction [2].

Availabe genome-scale metabolic network reconstructions were collected and listed in Palsson's Systems Biology Research Group.

Here, we took the adavantage of these reconstructed metabolic networks to demonstrate the availablitity of Model Editor.

Once the reconstructed models imported into the Model Editor, users can start to add, refine and build their own models and run FBA as well in the Model Editor.

Because two kinds of data formats, spreadsheet and xml, are commonly used for metabolic reconstruction models, the Model Editor allows importing both formats.


Reconstruction Models (GPR)

Two layers of relations between "gene and protein" and "protein and reaction" can be summarized in a three-sheet spreadsheet.

Gene Index (A basic description of gene)

5'Coordinate, Locus Tag, Gene, Product, EC Number

Protein Index (Protein information and the association between protein and gene)

Abbreviation, Name, Gene

Reaction Index (Reaction information and the association between reaction and protein)

Abbreviation, Name, Equation, Protein, Subsystem

Available models: iAF1260 GPR.xls, iYL1228


Reconstruction Models

Most published metabolic models, assembly of biochemical reactions, are available in either spreedsheet or SBML format.

Available models in Excel: (Please note that the excel files provided here were modified according to Format of database.)

Bacillus subtilis, iYO844 (BiGG), original release, iYO844.xls

Buchnera aphidicola, iGT196 (BiGG), original release, iGT196.xls

Saccharomyces cerevisiae, iMM904 (BiGG), original release, iMM904.xls

Salmonella typhimurium,iRR1083 (BiGG), original release, iRR1083.xls

Shewanella oneidensis, iSO783 (BiGG), original Release, iSO783.xls

Available models in SBML:

Models exported from BiGG can be modified by TextReplacer with the replacing rules (RulesforBiGG.TXT) and then imported to Model Editor.


Model Name Original Modified
E. coli iAF1260 iAF1260.xml Out iAF1260.xml
E. coli textbook textbook.xml Out textbook.xml
H. sapiens Recon 1 Recon1.xml Out Recon1.xml
S. cerevisiae iND750 iND750.xml Out iND750.xml
M. barkeri iAF692 iAF692.xml Out iAF692.xml
H. pylori iIT341 iIT341.xml Out iIT341.xml
S. aureus iSB619 iSB619.xml Out iSB619.xml
M. tuberculosis iNJ661 iNJ661.xml Out iNJ661.xml


Models downloaded from Model SEED can be modified by TextReplacer with the replacing rules (RulesforSEED.TXT) and then imported to Model Editor. Because the Model SEED provides more than one hundred of draft models, several of them were listed here as examples.

Model Name Original Modified
Acinetobacter sp. ADP1 ( Opt62977.3 ) Opt62977.3.xml Out Opt62977.3.xml
Bacillus subtilis subsp. subtilis str. 168 ( Seed224308.1 ) Seed224308.1.xml Out Seed224308.1.xml
Staphylococcus aureus subsp. aureus N315 ( Opt158879.1 ) Opt158879.1.xml Out Opt158879.1.xml


In addition to the BiGG- and SEED-based models, several published models were made by using the resource of BioCyc and KEGG. These models can be modified and imported into the Model Editor. For example, the SBML file of Haloalkaliphile Natronomonas pharaonis original release can be modified by TextReplacer with the replacing rules (RulesforKEGG.TXT).






[1] Becker SA, Feist AM, Mo ML, Hannum G, Palsson BO, Herrgard MJ: Quantitative prediction of cellular metabolism with constraint-based models: the COBRA Toolbox. Nat Protoc 2007, 2(3):727-738.

[2] Palsson B: Metabolic systems biology. FEBS Lett 2009, 583(24):3900-3904.