Abstract
The increasing availability of various system-level, or so-called ‘omics’, datasets, in concert with existing data from the primary research literature, is facilitating the development of genome-scale metabolic models for many organisms. By incorporating the metabolic reaction stoichiometry as well as other physicochemical properties into systemic network reconstructions, these models account for the constraints that restrict an organism’s phenotypic behavior. Accordingly, unlike many contemporary modeling strategies, this constraint-based modeling approach does not attempt to predict network behavior exactly; rather, it seeks to clearly distinguish those network states that a system can achieve from those that it cannot. A variety of analytical tools have been designed and developed to probe these models, thus enabling studies that investigate the metabolic capabilities of a number of organisms, that generate and test experimental hypotheses, and that predict accurately metabolic phenotypes and evolutionary outcomes. This chapter introduces the concepts that underlie the constraint-based modeling approach, and describes several of its applications with an emphasis on those potentially relevant to the drug development field. In addition, while this chapter focuses on the primary application of the constraint-based approach to date, namely in modeling metabolic networks, the latter sections of the chapter discuss its relatively recent application to modeling other cellular systems. Finally, the chapter concludes with an assessment of future directions focusing on the efforts that will be required to utilize the constraint-based approach in generating a holistic model of a viable organism.
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References
Wheeler DL, Church DM, Edgar R, Federhen S, Helmberg W, Madden TL, Pontius JU, Schuler GD, Schriml LM, Sequeira E et al (2004) Database resources of the National Center for Biotechnology Information: update. Nucleic Acids Res 32 Database issue: D35–40
Joyce AR, Palsson BO (2006) Themodel organism as a system: integrating ‘omics’ data sets. Nat Rev Mol Cell Biol 7(3): 198–210
Arkin AP (2001) Synthetic cell biology. Curr Opin Biotechnol 12(6): 638–644
Tomita M, Hashimoto K, Takahashi K, Shimizu TS, Matsuzaki Y, Miyoshi F, Saito K, Tanida S, Yugi K, Venter JC et al (1999) E-CELL: software environment for whole-cell simulation. Bioinformatics 15(1): 72–84
Hoffmann A, Levchenko A, Scott ML, Baltimore D (2002) The IkappaB-NF-kappaB signaling module: temporal control and selective gene activation. Science 298(5596): 1241–1245
Elowitz MB, Levine AJ, Siggia ED, Swain PS (2002) Stochastic gene expression in a single cell. Science 297(5584): 1183–1186
Arkin A, Ross J, McAdams HH (1998) Stochastic kinetic analysis of developmental pathway bifurcation in phage lambda-infected Escherichia coli cells. Genetics 149(4): 1633–1648
Sarkar A, Franza BR (2004) A logical analysis of the process of T cell activation: different consequences depending on the state of CD28 engagement. J Theor Biol 226(4): 455–466
Reed JL, Famili I, Thiele I, Palsson BO (2006) Towards multidimensional genome annotation. Nat Rev Genet 7(2): 130–141
Price ND, Reed JL, Palsson BO (2004) Genome-scale models of microbial cells: evaluating the consequences of constraints. Nat Rev Microbiol 2(11): 886–897
Edwards JS, Covert M, Palsson B (2002) Metabolic modelling of microbes: the flux-balance approach. Environ Microbiol 4(3): 133–140
Covert MW, Famili I, Palsson BO (2003) Identifying constraints that govern cell behavior: a key to converting conceptual to computational models in biology? Biotechnol Bioeng 84(7): 763–772
Price ND, Papin JA, Schilling CH, Palsson BO (2003) Genome-scale microbial in silico models: the constraints-based approach. Trends Biotechnol 21(4): 162–169
Varma A, Palsson BO (1994) Stoichiometric flux balance models quantitatively predict growth and metabolic by-product secretion in wild-type Escherichia coli W3110. Appl Environ Microbiol 60(10): 3724–3731
Kauffman KJ, Prakash P, Edwards JS (2003) Advances in flux balance analysis. Curr Opin Biotechnol 14(5): 491–496
Price ND, Schellenberger J, Palsson BO (2004) Uniform sampling of steady-state flux spaces: means to design experiments and to interpret enzymopathies. Biophys J 87(4): 2172–2186
Thiele I, Price ND, Vo TD, Palsson BO (2005) Candidate metabolic network states in human mitochondria. Impact of diabetes, ischemia, and diet. J Biol Chem 280(12): 11683–11695
Neidhardt FC, Curtiss R (1996) Escherichia coli and Salmonella: Cellular and molecular biology. 2nd ed. ASM Press, Washington, DC, USA
Scheffler IE (1999) Mitochondria. Wiley-Liss, New York, USA
Liolios K, Tavernarakis N, Hugenholtz P, Kyrpides NC (2006) The Genomes On Line Database (GOLD) v.2: a monitor of genome projects worldwide. Nucleic Acids Res 34(Database issue): D332–334
Consortium CSAA (2005) Initial sequence of the chimpanzee genome and comparison with the human genome. Nature 437(7055): 69–87
Gibbs RA, Weinstock GM, Metzker ML, Muzny DM, Sodergren EJ, Scherer S, Scott G, Steffen D, Worley KC, Burch PE et al (2004) Genome sequence of the Brown Norway rat yields insights into mammalian evolution. Nature 428(6982): 493–521
Istrail S, Sutton GG, Florea L, Halpern AL, Mobarry CM, Lippert R, Walenz B, Shatkay H, Dew I, Miller JR et al (2004) Whole-genome shotgun assembly and comparison of human genome assemblies. Proc Natl Acad Sci USA 101(7): 1916–1921
Kirkness EF, Bafna V, Halpern AL, Levy S, Remington K, Rusch DB, Delcher AL, Pop M, Wang W, Fraser CM et al (2003) The dog genome: survey sequencing and comparative analysis. Science 301(5641): 1898–1903
Stein L (2001) Genome annotation: from sequence to biology. Nat Rev Genet 2(7): 493–503
Brent MR (2005) Genome annotation past, present, and future: how to define an ORF at each locus. Genome Res 15(12): 1777–1786
Mao X, Cai T, Olyarchuk JG, Wei L (2005) Automated genome annotation and pathway identification using the KEGG Orthology (KO) as a controlled vocabulary. Bioinformatics 21(19): 3787–3793
Karp PD, Paley S, Romero P (2002) The Pathway Tools software. Bioinformatics 18Suppl 1: S225–232
Cash P (2003) Proteomics of bacterial pathogens. Adv Biochem Eng Biotechnol 83: 93–115
Taylor SW, Fahy E, Ghosh SS (2003) Global organellar proteomics. Trends Biotechnol 21(2): 82–88
Kanehisa M, Goto S, Kawashima S, Okuno Y, Hattori M (2004) The KEGG resource for deciphering the genome. Nucleic Acids Res 32 Database issue: D277–280
Karp PD, Riley M, Saier M, Paulsen IT, Collado-Vides J, Paley SM, Pellegrini-Toole A, Bonavides C, Gama-Castro S (2002) The EcoCyc Database. Nucleic Acids Res 30(1): 56–58
Mewes HW, Amid C, Arnold R, Frishman D, Guldener U, Mannhaupt G, Munsterkotter M, Pagel P, Strack N, Stumpflen V et al (2004) MIPS: analysis and annotation of proteins from whole genomes. Nucleic Acids Res 32 Database issue: D41–44
Christie KR, Weng S, Balakrishnan R, Costanzo MC, Dolinski K, Dwight SS, Engel SR, Feierbach B, Fisk DG, Hirschman JE et al (2004) Saccharomyces Genome Database (SGD) provides tools to identify and analyze sequences from Saccharomyces cerevisiae and related sequences from other organisms. Nucleic Acids Res 32 Database issue: D311–314
Caspi R, Foerster H, Fulcher CA, Hopkinson R, Ingraham J, Kaipa P, Krummenacker M, Paley S, Pick J, Rhee SY et al (2006) MetaCyc: a multiorganism database of metabolic pathways and enzymes. Nucleic Acids Res 34 (Database issue): D511–516
Karp PD, Ouzounis CA, Moore-Kochlacs C, Goldovsky L, Kaipa P, Ahren D, Tsoka S, Darzentas N, Kunin V, Lopez-Bigas N (2005) Expansion of the BioCyc collection of pathway/genome databases to 160 genomes. Nucleic Acids Res 33(19): 6083–6089
Harris MA, Clark J, Ireland A, Lomax J, Ashburner M, Foulger R, Eilbeck K, Lewis S, Marshall B, Mungall C et al (2004) The Gene Ontology (GO) database and informatics resource. Nucleic Acids Res 32 Database issue: D258–261
(2006) The Gene Ontology (GO) project in 2006. Nucleic Acids Res 34 (Database issue): D322–326
Serres MH, Goswami S, Riley M (2004) GenProtEC: an updated and improved analysis of functions of Escherichia coli K-12 proteins. Nucleic Acids Res 32 Database issue: D300–302
Coulton G (2004) Are histochemistry and cytochemistry ‘Omics’? J Mol Histol 35(6): 603–613
Arita M, Robert M, Tomita M (2005) All systems go: launching cell simulation fueled by integrated experimental biology data. Curr Opin Biotechnol 16(3): 344–349
Huh WK, Falvo JV, Gerke LC, Carroll AS, Howson RW, Weissman JS, O’Shea EK (2003) Global analysis of protein localization in budding yeast. Nature 425(6959): 686–691
Guda C, Subramaniam S (2005) pTARGET: a new method for predicting protein subcellular localization in eukaryotes. Bioinformatics 21(21): 3963–3969
Fields S (2005) High-throughput two-hybrid analysis. The promise and the peril. Febs J 272(21): 5391–5399
Deeds EJ, Ashenberg O, Shakhnovich EI (2006) A simple physical model for scaling in protein-protein interaction networks. Proc Natl Acad Sci USA 103(2): 311–316
Sprinzak E, Sattath S, Margalit H (2003) How reliable are experimental protein-protein interaction data? J Mol Biol 327(5): 919–923
Palsson B (2004) Two-dimensional annotation of genomes. Nat Biotechnol 22(10): 1218–1219
Beard DA, Liang SD, Qian H (2002) Energy balance for analysis of complex metabolic networks. Biophys J 83(1): 79–86
Covert MW, Knight EM, Reed JL, Herrgard MJ, Palsson BO (2004) Integrating high-throughput and computational data elucidates bacterial networks. Nature 429(6987): 92–96
Covert MW, Palsson BO (2003) Constraints-based models: regulation of gene expression reduces the steady-state solution space. J Theor Biol 221(3): 309–325
Covert MW, Schilling CH, Palsson B (2001) Regulation of gene expression in flux balance models of metabolism. J Theor Biol 213(1): 73–88
Covert MW, Palsson BO (2002) Transcriptional regulation in constraints-based metabolic models of Escherichia coli. J Biol Chem 277(31): 28058–28064
Chvatal V (1983) Linear Programming. WH Freeman and Company, New York, USA
Reed JL, Palsson BO (2004) Genome-scale in silico models of E. coli have multiple equivalent phenotypic states: assessment of correlated reaction subsets that comprise network states. Genome Res 14(9): 1797–1805
Vo TD, Greenberg HJ, Palsson BO (2004) Reconstruction and functional characterization of the human mitochondrial metabolic network based on proteomic and biochemical data. J Biol Chem 279(38): 39532–39540
Barrett CL, Herring CD, Reed JL, Palsson BO (2005) The global transcriptional regulatory network for metabolism in Escherichia coli exhibits few dominant functional states. Proc Natl Acad Sci USA 102(52): 19103–19108
Neidhardt FC, Ingraham JL, Schaechter M (1990) Physiology of the bacterial cell. Sinauer Associates, Inc., Sunderland, MA, USA
Reed JL, Vo TD, Schilling CH, Palsson BO (2003) An expanded genome-scale model of Escherichia coli K-12 (iJR904 GSM/GPR). Genome Biol 4(9): R54
Reed JL, Palsson BO (2003) Thirteen years of building constraint-based in silico models of Escherichia coli. J Bacteriol 185(9): 2692–2699
Edwards JS, Palsson BO (2000) The Escherichia coli MG1655 in silico metabolic genotype: its definition, characteristics, and capabilities. Proc Natl Acad Sci USA 97(10): 5528–5533
Schilling CH, Covert MW, Famili I, Church GM, Edwards JS, Palsson BO (2002) Genome-scale metabolic model of Helicobacter pylori 26695. J Bacteriol 184(16): 4582–4593
Thiele I, Vo TD, Price ND, Palsson B (2005) An expanded metabolic reconstruction of Helicobacter pylori (iIT341 GSM/GPR): An in silico genome-scale characterization of single and double deletion mutants. J Bacteriol 187(16): 5818–5830
Becker SA, Palsson BO (2005) Genome-scale reconstruction of the metabolic network in Staphylococcus aureus N315: an initial draft to the two-dimensional annotation. BMC Microbiol 5(1): 8
Mahadevan R, Bond DR, Butler JE, Esteve-Nunez A, Coppi MV, Palsson BO, Schilling CH, Lovley DR (2006) Characterization of metabolism in the Fe(III)-reducing organism Geobacter sulfurreducens by constraint-based modeling. Appl Environ Microbiol 72(2): 1558–1568
Borodina I, Krabben P, Nielsen J (2005) Genome-scale analysis of Streptomyces coelicolor A3(2) metabolism. Genome Res 15(6): 820–829
Feist AM, Scholten JCM, Palsson BO, Brockman FJ, Ideker T (2006) Modeling methanogenesis with a genome-scale metabolic reconstruction of Methanosarcina barkeri. Mol Syst Biol 2(1): msb4100046-E1-msb4100046-E14
Forster J, Famili I, Fu P, Palsson BO, Nielsen J (2003) Genome-scale reconstruction of the Saccharomyces cerevisiae metabolic network. Genome Res 13(2): 244–253
Duarte NC, Herrgard MJ, Palsson BO (2004) Reconstruction and validation of Saccharomyces cerevisiae iND750, a fully compartmentalized genome-scale metabolic model. Genome Res 14(7): 1298–1309
Kuepfer L, Sauer U, Blank LM (2005) Metabolic functions of duplicate genes in Saccharomyces cerevisiae. Genome Res 15(10): 1421–1430
Almaas E, Oltvai ZN, Barabasi AL (2005) The activity reaction core and plasticity of metabolic networks. PLoS Comput Biol 1(7): e68
Segre D, DeLuna A, Church GM, Kishnoy R (2005) Modular epistasis in yeast metabolism. Nat Genet 37(1): 77–83
Sheikh K, Forster J, Nielsen LK (2005) Modeling hybridomacell metabolism using a generic genome-scale metabolic model of Mus musculus. Biotechnol Prog 21(1): 112–121
Wiback SJ, Palsson BO (2002) Extreme pathway analysis of human red blood cell metabolism. Biophys J 83(2): 808–818
Hucka M, Finney A, Sauro HM, Bolouri H, Doyle JC, Kitano H, Arkin AP, Bornstein BJ, Bray D, Cornish-Bowden A et al (2003) The systems biology markup language (SBML): a medium for representation and exchange of biochemical network models. Bioinformatics 19(4): 524–531
Novere NL, Finney A, Hucka M, Bhalla US, Campagne F, Collado-Vides J, Crampin EJ, Halstead M, Klipp E, Mendes P et al (2005) Minimum information requested in the annotation of biochemical models (MIRIAM). Nat Biotechnol 23(12): 1509–1515
Schilling CH, Palsson BO (2000) Assessment of the metabolic capabilities of Haemophilus influenzae Rd through a genome-scale pathway analysis. J Theor Biol 203(3): 249–283
Forster J, Famili I, Palsson BO, Nielsen J (2003) Large-scale evaluation of in silico gene deletions in Saccharomyces cerevisiae. Omics 7(2): 193–202
Hartwell L (2004) Genetics. Robust interactions. Science 303(5659): 774–775
Tong AH, Lesage G, Bader GD, Ding H, Xu H, Xin X, Young J, Berriz GF, Brost RL, Chang M et al (2004) Global mapping of the yeast genetic interaction network. Science 303(5659): 808–813
Heinemann M, Kummel A, Ruinatscha R, Panke S (2005) In silico genome-scale reconstruction and validation of the Staphylococcus aureus metabolic network. Biotechnol Bioeng 92(7): 850–864
Baba T, Ara T, Hasegawa M, Takai Y, Okumura Y, Baba M, Datsenko KA, Tomita M, Wanner BL, Mori H (2006) Construction of Escherichia coli K-12 in-frame, single-gene knockout mutants: the Keio collection. 2(1): pmsb4100050-E1-msb4100050-E11
Glasner JD, Liss P, Plunkett G 3rd, Darling A, Prasad T, Rusch M, Byrnes A, Gilson M, Biehl B, Blattner FR et al (2003) ASAP, a systematic annotation package for community analysis of genomes. Nucleic Acids Res 31(1): 147–151
Salgado H, Gama-Castro S, Martinez-Antonio A, Diaz-Peredo E, Sanchez-Solano F, Peralta-Gil M, Garcia-Alonso D, Jimenez-Jacinto V, Santos-Zavaleta A, Bonavides-Martinez C et al (2004) RegulonDB (version 4.0): transcriptional regulation, operon organization and growth conditions in Escherichia coli K-12. Nucleic Acids Res 32 Database issue: D303–306
Palsson BO (2006) Systems Biology: Properties of Reconstructed Networks. Cambridge University Press, UK
Price ND, Thiele I, Palsson BO (2006) Candidate states of Helicobacter pylori’s genome-scale metabolic network upon application of loop law thermodynamic constraints. Biophys J 90(11): 3919–3928
Almaas E, Kovacs B, Vicsek T, Oltvai ZN, Barabasi AL (2004) Global organization of metabolic fluxes in the bacterium Escherichia coli. Nature 427(6977): 839–843
Allen TE, Palsson BO (2003) Sequence-based analysis of metabolic demands for protein synthesis in prokaryotes. J Theor Biol 220(1): 1–18
Papin JA, Hunter T, Palsson BO, Subramaniam S (2005) Reconstruction of cellular signalling networks and analysis of their properties. Nat Rev Mol Cell Biol 6(2): 99–111
Varma A, Palsson BO (1993) Metabolic capabilities of Escherichia coli: II. Optimal growth patterns. J Theor Biol 165(4): 503–522
Papin JA, Palsson BO (2004) Topological analysis of mass-balanced signaling networks: a framework to obtain network properties including crosstalk. J Theor Biol 227(2): 283–297
Papin JA, Palsson BO (2004) The JAK-STAT signaling network in the human Bcell: an extreme signaling pathway analysis. Biophys J 87(1): 37–46
Schilling CH, Palsson BO (2000) Assessment of the metabolic capabilities of Haemophilus influenzae Rd through a genome-scale pathway Analysis. J Theor Biol 203(3): 249–283
Bell SL, Palsson BO (2005) Expa: a program for calculating extreme pathways in biochemical reaction networks. Bioinformatics 21(8): 1739–1740
Herrgard MJ, Lee BS, Portnoy V, Palsson BO (2006) Integrated analysis of regulatory and metabolic networks reveals novel regulatory mechanisms in Saccharomyces cerevisiae. Genome Res 16(5): 627–635
Gianchandani EP, Papin JA, Price ND, Joyce AR, Palsson BO (2006) Matrix formalism to describe functional states of transcriptional regulatory systems. PLoS Comput Biol 2(8): e101
Papin JA, Price ND, Palsson BO (2002) Extreme pathway lengths and reaction participation in genome-scale metabolic networks. Genome Res 12(12): 1889–1900
Price ND, Reed JL, Papin JA, Famili I, Palsson BO (2003) Analysis of metabolic capabilities using singular value decomposition of extreme pathway matrices. Biophys J 84(2 Pt 1): 794–804
Price ND, Papin JA, Palsson BO (2002) Determination of redundancy and systems properties of the metabolic network of Helicobacter pylori using genome-scale extreme pathway analysis. Genome Res 12(5): 760–769
Fong SS, Burgard AP, Herring CD, Knight EM, Blattner FR, Maranas CD, Palsson BO (2005) In silico design and adaptive evolution of Escherichia coli for production of lactic acid. Biotechnol Bioeng 91(5): 643–648
Burgard AP, Pharkya P, Maranas CD (2003) Optknock: a bilevel programming framework for identifying gene knockout strategies for microbial strain optimization. Biotechnol Bioeng 84(6): 647–657
Wheeler DL, Barrett T, Benson DA, Bryant SH, Canese K, Chetvernin V, Church DM, DiCuccio M, Edgar R, Federhen S et al (2006) Database resources of the National Center for Biotechnology Information. Nucleic Acids Res 34 (Database issue): D173–180
Park SM, Schilling CH, Palsson BO (2003) Compositions and methods for modeling Bacillus subtilis metabolism. US Patent and Trademark Office, USA
Edwards JS, Palsson BO (1999) Systems properties of the Haemophilus influenzae Rd metabolic genotype. J Biol Chem 274(25): 17410–17416
Oliveira AP, Nielsen J, Forster J (2005) Modeling Lactococcus lactis using a genomescale flux model. BMC Microbiol 5: 39
Hong SH, Kim JS, Lee SY, In YH, Choi SS, Rih JK, Kim CH, Jeong H, Hur CG, Kim JJ (2004) The genome sequence of the capnophilic rumen bacterium Mannheimia succiniciproducens. Nat Biotechnol 22(10): 1275–1281
Taylor SW, Fahy E, Zhang B, Glenn GM, Warnock DE, Wiley S, Murphy AN, Gaucher SP, Capaldi RA, Gibson BW et al (2003) Characterization of the human heart mitochondrial proteome. Nat Biotechnol 21(3): 281–286
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Joyce, A.R., Palsson, B.Ø. (2007). Toward whole cell modeling and simulation: Comprehensive functional genomics through the constraint-based approach. In: Boshoff, H.I., Barry, C.E. (eds) Systems Biological Approaches in Infectious Diseases. Progress in Drug Research, vol 64. Birkhäuser Basel. https://doi.org/10.1007/978-3-7643-7567-6_11
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