Computational Systems Biochemistry Group

The verification of metabolic networks of E. coli [1] and yeast [2] basic topological analysis in combination with the prediction of growth rate suffices to show the general validity. But the hepatocyte is one of the cell types with the most multifacted functional spectrum. Thus, a more sophisticated framework to show its function is necessary.

For single-cell organisms, a specialized function "growth" can be estimated from the constituents of the cell [1,2]. This does not make sense for the hepatocyte since its main functions are the supply of substrates for other cells and the catabolism of products of other cells, more specifically, the homeostasis of these substances in the blood. As opposed to the growth function, homeostasis is multi-dimensional.

For the purpose to describe the functional spectrum of the liver cell, we developed a description language describing flux-balance simulations and a computational framework to automatically compute flux distributions and evaluate them. The synthesis and the catabolic functions of the hepatocyte are written in this description language. The computations are performed with flux-minimzation with thermodynamic feasibility [3].

Further methods of verification/refinement are:

The metabolic scope analysis allows to quickly compute the theoretical metabolic capacity of the network [4,5]. Sets of alternative seed compounds are computed and benefit the curation process.
Topological analysis shows whether there are mass leaks showing illegal stoichiometries in the network even if no sum formula is given for all metabolites [6,7].
By pruning non-functional reactions [8], the network can be reduced in its size for a more comprehensive model.

Researchers

Dr. Andreas Hoppe
Prof. Hermann-Georg Holzhütter

This project is part of the HepatoSys Platform Modeling (SP 1.1 Structure and regulation of the hepatocyte metabolism).

References

[1] Feist AM, Henry CS, Reed JL, Krummenacker M, Joyce AR, Karp PD, Broadbelt LJ, Hatzimanikatis V, Palsson BØ. (2007) A genome-scale metabolic reconstruction for Escherichia coli K-12 MG1655 that accounts for 1260 ORFs and thermodynamic information. Mol Syst Biol, 3:121. [PubMed]

[2] Herrgård MJ, Swainston N, Dobson P, Dunn WB, Arga KY, Arvas M, Blüthgen N, Borger S, Costenoble R, Heinemann M, Hucka M, Le Novère N, Li P, Liebermeister W, Mo ML, Oliveira AP, Petranovic D, Pettifer S, Simeonidis E, Smallbone K, Spasic' I, Weichart D, Brent R, Broomhead DS, Westerhoff HV, Kirdar B, Penttilä M, Klipp E, Palsson BØ, Sauer U, Oliver SG, Mendes P, Nielsen J, Kell DB. (2008) A consensus yeast metabolic network reconstruction obtained from a community approach to systems biology. Nat Biotechnol., 26(10):1155-60. [PubMed]

[3] Hoppe A, Hoffmann S, Holzhütter HG. (2007) Including metabolite concentrations into flux-balance analysis: Thermodynamic realizability as a constraint on flux distributions in metabolic networks BMC Syst. Biol., 1(1): 23. [pdf, journal, PubMed]

[4] Handorf T, Christian N, Ebenhöh O, Kahn D. (2008) An environmental perspective on metabolism. J Theor Biol., 252(3):530-7. [PubMed]

[5] Ebenhöh O, Handorf T, Heinrich R. (2004) Structural analysis of expanding metabolic networks. Genome Informatics, 15:35-45. [PubMed]

[6] Gevorgyan A, Poolman MG, Fell DA. (2008) Detection of stoichiometric inconsistencies in biomolecular models. Bioinformatics., 24(19):2245-51. [PubMed]

[7] Klamt S, Saez-Rodriguez J, Gilles ED. (2007) Structural and functional analysis of cellular networks with CellNetAnalyzer. BMC Syst Biol., 8;1:2. [PubMed]

[8] Hoffmann S, Hoppe A and Holzhütter HG. (2007) Pruning genome-scale metabolic models to consistent ad functionem networks. Genome Informatics, 18(1), 308-19. [pdf]

Own Publication

Gille C, Bölling C, Hoppe A, Bulik S, Hoffmann S, Hübner K, Karlstädt A, Ganeshan R, König M, Rother K, Weidlich M, Behre J, Holzhütter HG. (2010) HepatoNet1: a comprehensive metabolic reconstruction of the human hepatocyte for the analysis of liver physiology. Mol Syst Biol., 6:411. [PubMed]

		Verification of the Stoichiometric Model of the Hepatocyte with Flux-Balance Optimization
Home Research VirtualLiver People Publications Software Positions Events Contact		The verification of metabolic networks of E. coli [1] and yeast [2] basic topological analysis in combination with the prediction of growth rate suffices to show the general validity. But the hepatocyte is one of the cell types with the most multifacted functional spectrum. Thus, a more sophisticated framework to show its function is necessary. For single-cell organisms, a specialized function "growth" can be estimated from the constituents of the cell [1,2]. This does not make sense for the hepatocyte since its main functions are the supply of substrates for other cells and the catabolism of products of other cells, more specifically, the homeostasis of these substances in the blood. As opposed to the growth function, homeostasis is multi-dimensional. For the purpose to describe the functional spectrum of the liver cell, we developed a description language describing flux-balance simulations and a computational framework to automatically compute flux distributions and evaluate them. The synthesis and the catabolic functions of the hepatocyte are written in this description language. The computations are performed with flux-minimzation with thermodynamic feasibility [3]. Further methods of verification/refinement are: The metabolic scope analysis allows to quickly compute the theoretical metabolic capacity of the network [4,5]. Sets of alternative seed compounds are computed and benefit the curation process. Topological analysis shows whether there are mass leaks showing illegal stoichiometries in the network even if no sum formula is given for all metabolites [6,7]. By pruning non-functional reactions [8], the network can be reduced in its size for a more comprehensive model. Researchers Dr. Andreas Hoppe Prof. Hermann-Georg Holzhütter This project is part of the HepatoSys Platform Modeling (SP 1.1 Structure and regulation of the hepatocyte metabolism). References [1] Feist AM, Henry CS, Reed JL, Krummenacker M, Joyce AR, Karp PD, Broadbelt LJ, Hatzimanikatis V, Palsson BØ. (2007) A genome-scale metabolic reconstruction for Escherichia coli K-12 MG1655 that accounts for 1260 ORFs and thermodynamic information. Mol Syst Biol, 3:121. [PubMed] [2] Herrgård MJ, Swainston N, Dobson P, Dunn WB, Arga KY, Arvas M, Blüthgen N, Borger S, Costenoble R, Heinemann M, Hucka M, Le Novère N, Li P, Liebermeister W, Mo ML, Oliveira AP, Petranovic D, Pettifer S, Simeonidis E, Smallbone K, Spasic' I, Weichart D, Brent R, Broomhead DS, Westerhoff HV, Kirdar B, Penttilä M, Klipp E, Palsson BØ, Sauer U, Oliver SG, Mendes P, Nielsen J, Kell DB. (2008) A consensus yeast metabolic network reconstruction obtained from a community approach to systems biology. Nat Biotechnol., 26(10):1155-60. [PubMed] [3] Hoppe A, Hoffmann S, Holzhütter HG. (2007) Including metabolite concentrations into flux-balance analysis: Thermodynamic realizability as a constraint on flux distributions in metabolic networks BMC Syst. Biol., 1(1): 23. [pdf, journal, PubMed] [4] Handorf T, Christian N, Ebenhöh O, Kahn D. (2008) An environmental perspective on metabolism. J Theor Biol., 252(3):530-7. [PubMed] [5] Ebenhöh O, Handorf T, Heinrich R. (2004) Structural analysis of expanding metabolic networks. Genome Informatics, 15:35-45. [PubMed] [6] Gevorgyan A, Poolman MG, Fell DA. (2008) Detection of stoichiometric inconsistencies in biomolecular models. Bioinformatics., 24(19):2245-51. [PubMed] [7] Klamt S, Saez-Rodriguez J, Gilles ED. (2007) Structural and functional analysis of cellular networks with CellNetAnalyzer. BMC Syst Biol., 8;1:2. [PubMed] [8] Hoffmann S, Hoppe A and Holzhütter HG. (2007) Pruning genome-scale metabolic models to consistent ad functionem networks. Genome Informatics, 18(1), 308-19. [pdf] Own Publication Gille C, Bölling C, Hoppe A, Bulik S, Hoffmann S, Hübner K, Karlstädt A, Ganeshan R, König M, Rother K, Weidlich M, Behre J, Holzhütter HG. (2010) HepatoNet1: a comprehensive metabolic reconstruction of the human hepatocyte for the analysis of liver physiology. Mol Syst Biol., 6:411. [PubMed]