Minimal cut sets and the use of failure modes in metabolic networks

Metabolites

Volumn 2, Issue 3, 2012, Pages 567-595

  Clark, Sangaalofa T ^a   Verwoerd, Wynand S ^a  

^a LINCOLN UNIVERSITY   (New Zealand)

Author keywords

Elementary modes; Metabolic networks; Minimal cut sets

Indexed keywords

ALGORITHM; ANALYTICAL PARAMETERS; ENERGY BALANCE; GENETIC ENGINEERING; KINETICS; METABOLIC REGULATION; METABOLITE; MINIMAL CUT SET; RELIABILITY; REVIEW; SYSTEMS BIOLOGY; THERMODYNAMICS;

EID: 84901312605     PISSN: None     EISSN: 22181989     Source Type: Journal    
DOI: 10.3390/metabo2030567     Document Type: Review

References (65)

1. Gagneur, J.; Klamt, S. Computation of elementary modes: A unifying framework and the new binary approach. BMC Bioinformatics 2004, 5.
2. Schuster, S.; Dandekar, T.; Fell, D.A. Detection of elementary flux modes in biochemical networks: A promising tool for pathway analysis and metabolic engineering. Trends Biotechnol. 1999, 17, 53-60.
3. Schuster, S.; Fell, D.; Dandekar, T. A general definition of metabolic pathways useful for systematic organization and analysis of complex metabolic networks. Nat. Biotechnol. 2000, 18, 326-332.
4. Trinh, C.T.; Wlaschin, A.; Srienc, F. Elementary mode analysis: A useful metabolic pathway analysis tool for characterizing cellular metabolism. Appli. Microbiol. Biotechnol. 2009, 81, 813-826.
5. Fell, D.A.; Wagner, A. The small world of metabolism. Nat. Biotechnol. 2000, 18, 1121-1122.
6. Ma, H.; Zeng, A.-P. Reconstruction of metabolic networks from genome data and analysis of their global structure for various organisms. Bioinformatics 2003, 19, 270-277.
7. Ma, H.-W.; Zeng, A.-P. The connectivity structure, giant strong component and centrality of metabolic networks. Bioinformatics 2003, 19, 1423-1430.
8. Rockafellar, R. Convex Analysis; Princeton University Press: Princeton, NY, USA, 1970.
9. Schilling, C.H.; Schuster, S.; Palsson, B.O.; Heinrich, R. Metabolic pathway analysis: Basic concepts and scientific applications in the post-genomic era. Biotechnol. Prog. 1999, 15, 296-303.
10. Papin, J.A. Comparison of network-based pathway analysis methods. Trends Biotechnol. 2004, 22, 400-405.
11. Klamt, S. Generalized concept of minimal cut sets in biochemical networks. Biosystems 2006, 83, 233-247.
12. Klamt, S.; Gilles, E. Minimal cut sets in biochemical reaction networks. Bioinformatics 2004, 20, 226-234.
13. Klamt, S.; Sae-Rodriguez, J.; Gilles, E.D. Structural and functional analysis of cellular networks with cellnetanalyzer. BMC Syst. Biol. 2007, 1.
14. Haus, U.-U.; Klamt, S.; Stephen, T. Computing knock-out strategies in metabolic networks. J. Comput. Biol. 2008, 15, 259-268.
15. Hädicke, O.; Klamt, S. Computing complex metabolic intervention strategies using constrained minimal cut sets. Metab. Eng. 2011, 13, 204-213.
16. Clark, S.; Verwoerd, W. A systems approach to identifying correlated gene targets for the loss of colour pigmentation in plants. BMC Bioinformatics 2011, 12, 343.
17. Wilhelm, T.; Behre, J.; Schuster, S. Analysis of structural robustness of metabolic networks. Syst. Biol. 2004, 1, 114-120.
18. Fard, N.S. Determination of minimal cut sets of a complex fault tree. Comput. Ind. Eng. 1997, 33, 59-62.
19. Sinnamon, R.M.; Andrews, J.D. Improved accuracy in quantitative fault tree analysis. Qual. Reliab. Eng. Int. 1997, 13, 285-292.
20. Minimal cut sets. Available online: http://www.weibull.com/hotwire/issue63/relbasics63.htm, (accessed on 18 December 2011).
21. Fault tree analysis. Available online: http://www.weibull.com/basics/fault-tree/index.htm, (accessed on 18 December 2011).
22. Empowering the reliability professional. Available online: http://www.reliasoft.com/, (accessed on 18 December 2011)
23. Bollabas, B. Modern Graph Theory; Springer-Verlag: New York, NY, 1998.
24. Schuster, S.; Hilgetag, C.; Woods, J.H.; Fell, D.A. Reaction routes in biochemical reaction systems: Algebraic properties, validated calculation procedure and example from nucleotide metabolism. J. Math. Biol. 2002, 45, 153-181.
25. Trinh, C.T.; Carlson, R.; Wlaschin, A.; Srienc, F. Design, construction and performance of the most efficient biomass producing e. Coli bacterium. Metab. Eng. 2006, 8, 628-638.
26. Unrean, P.; Trinh, C.T.; Srienc, F. Rational design and construction of an efficient e. Coli for production of diapolycopendioic acid. Metab. Eng. 2010, 12, 112-122.
27. Burgard, A.P.; Pharkya, P.; Maranas, C.D. Optknock: A bilevel programming framework for identifying gene knockout strategies for microbial strain optimization. Biotechnol. Bioeng. 2003, 84, 647-657.
28. Tepper, N.; Shlomi, T. Predicting metabolic engineering knockout strategies for chemical production: Accounting for competing pathways. Bioinformatics 2010, 26, 536-543.
29. Ballerstein, K.; von Kamp, A.; Klamt, S.; Haus, U.-U. Minimal cut sets in a metabolic network are elementary modes in a dual network. Bioinformatics 2012, 28, 381-387.
30. Acuña, V.; Chierichetti, F.; Lacroix, V.; Marchetti-Spaccamela, A.; Sagot, M.-F.; Stougie, L. Modes and cuts in metabolic networks: Complexity and algorithms. Biosystems 2009, 95, 51-60.
31. Acuña, V.; Marchetti-Spaccamela, A.; Sagot, M.-F.; Stougie, L. A note on the complexity of finding and enumerating elementary modes. Biosystems 2010, 99, 210-214.
32. Garey, M.R.; Johnson, D.S. Computers and Intractability. A Guide to the Theory of NP-Completeness; W. H. Freeman and Co.: San Francisco, CA, USA,1979.
33. Alsuwaiyel, M.H. Algorithms: Design Techniques and Analysis, 3rd ed.; World Scientific Publishing Co., Pte., Ltd.: Singapore, 2003; Vol. 7.
34. Kozen, D.C. Theory of Computation. Springer: New York, NY, USA, 2006.
35. Imielinski, M.; Belta, C. On the computation of minimal cut sets in genome scale metabolic networks. Amer. Contr. Conf. 2007, 1329-1334
36. Famili, I.; Palsson, B.O. Systemic metabolic reactions are obtained by singular value decomposition of genome-scale stoichiometric matrices. J. Theor. Biol. 2003, 224, 87-96.
37. Berge, C. Hypergraphs. Combinatorics of Finite Sets; North-Holland Mathematical Library: Amsterdam, North-Holland, 1989; Volume 43
38. Fredman, M.L.; Khachiyan, L. On the complexity of dualization of monotone disjunctive normal forms. J. Algorithm 1996, 21, 618-628.
39. Csete, M.E.; Doyle, J.C. Reverse engineering of biological complexity. Science 2002, 295, 1664-1669.
40. Kitano, H. Biological robustness. Nat. Publ. Group 2004, 5.
41. Papin, J.A.; Price, N.D.; Palsson, B.O. Extreme pathway lengths and reaction participation in genome-scale metabolic networks. Genome Res. 2002, 12, 1889-1900.
42. Stelling, J.; Klamt, S.; Bettenbrock, K.; Schuster, S.; Gilles, E.D. Metabolic network structure determines key aspects of functionality and regulation. Nature 2002, 420, 190-193.
43. Min, Y.; Jin, X.; Chen, M.; Pan, Z.; Ge, Y.; Chang, J. Pathway knockout and redundancy in metabolic networks. J. Theor. Biol. 2011, 270, 63-69.
44. Holzhütter, S.; Holzhütter, H.-G. Computational design of reduced metabolic networks. Chem. Bio. Chem. 2004, 5, 1401-1422.
45. Papp, B.; Pal, C.; Hurst, L.D. Metabolic network analysis of the causes and evolution of enzyme dispensability in yeast. Nature 2004, 429, 661-664.
46. Edwards, J.S.; Palsson, B.O. Metabolic flux balance analysis and the in silico analysis of escherichia coli k-12 gene deletions. BMC Bioinformatics 2000, 1, 1-10.
47. Wiechert, W.; Möllney, M.; Petersen, S.; de Graaf, A.A. A universal framework for 13c metabolic flux analysis. Metab. Eng. 2001, 3, 265-283.
48. Klamt, S.; Schuster, S.; Gilles, E.D. Calculability analysis in underdetermined metabolic networks illustrated by a model of the central metabolism in purple nonsulfur bacteria. Biotechnol. Bioeng. 2002, 77, 734-751.
49. Edwards, J.S.; Covert, M.; Palsson, B. Metabolic modelling of microbes: The flux-balance approach. Environ. Microbiol. 2002, 4, 133-140.
50. Schwender, J. Metabolic flux analysis as a tool in metabolic engineering of plants. Curr. Opin. Biotechnol. 2008, 19, 131-137.
51. Nolan, R.P.; Fenley, A.P.; Lee, K. Identification of distributed metabolic objectives in the hypermetabolic liver by flux and energy balance analysis. Metab. Eng. 2006, 8, 30-45.
52. Schilling, C.H.; Edwards, J.S.; Letscher, D.; Palsson, B.O. Combining pathway analysis with flux balance analysis for the comprehensive study of metabolic systems. Biotechnol. Bioeng. 2000, 71, 286-306.
53. Cherkassky, B.; Goldberg, A.; Radzik, T. Shortest paths algorithms: Theory and experimental evaluation. Math. Program. 1996, 73, 129-174.
54. Wu, X.; Qi, X. Genes encoding hub and bottleneck enzymes of the arabidopsis metabolic network preferentially retain homeologs through whole genome duplication. BMC Evol. Biol. 2010, 10.
55. Yu, H.; Kim, P.M.; Sprecher, E.; Trifonov, V.; Gerstein, M. The importance of bottlenecks in protein networks: Correlation with gene essentiality and expression dynamics. PLoS Comput. Biol. 2007, 3, e59.
56. Homeolog-cogepedia. Available online: http://genomevolution.org/wiki/index.php/Homeolog, accessed on 10 September 2012.
57. Bordel, S.; Nielsen, J. Identification of flux control in metabolic networks using non-equilibrium thermodynamics. Metab. Eng. 2010, 12, 369-377.
58. Ma, H.; Zhao, X.; Yuan, Y.; Zeng, A. Decomposition of metabolic network into functional modules based on the global connectivity structure of reaction graph. Bioinformatics 2004, 20, 1870-1876.
59. Csete, M.; Doyle, J. Bow ties, metabolism and disease. Trends Biotechnol. 2004, 22, 446-450.
60. Zhao, J.; Tao, L.; Yu, H.; Luo, J.-H.; Cao, Z.-W.; Li, Y.-X. Bow-tie topological features of metabolic networks and the functional significance. Chin. Sci. Bull. 2007, 52, 1036-1045.
61. Zhao, J.; Yu, H.; Luo, J.-H.; Cao, Z.-W.; Li, Y.-X. Hierarchical modularity of nested bow-ties in metabolic networks. BMC Bioinformatics 2006, 7, 386.
62. White, D.R.; Batagelj, V.; Mrvar, A. Anthropology-Analyzing large kinship and marriage networks with pgraph and pajek. Soc. Sci. Comput. Rev. 1999, 17, 245-274.
63. Imielinski, M.; Belta, C.; Rubin, H.; Halasz, A. Systematic analysis of conservation relations in escherichia coli genome-scale metabolic network reveals novel growth media. Biophys. J. 2006, 90, 2659-2672.
64. Kauffman, K.J.; Prakash, P.; Edwards, J.S. Advances in flux balance analysis. Curr. Opin. Biotechnol. 2003, 14, 491-496.
65. Lee, J.M.; Gianchandani, E.P.; Papin, J.A. Flux balance analysis in the era of metabolomics. Brief. Bioinform. 2006, 7, 140-150.