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Journal of Biomedicine and Biotechnology
Volume 2010, Article ID 415148, 10 pages
http://dx.doi.org/10.1155/2010/415148
Research Article

Optimal Fluxes, Reaction Replaceability, and Response to Enzymopathies in the Human Red Blood Cell

1CNR Institute for Physico-Chemical Processes (IPCF), Rome Sapienza Unit, Roma, Italy
2Dipartimento di Fisica, Sapienza Università di Roma, Piazzale Aldo Moro 2, 00185 Roma, Italy
3Department of Molecular, Cellular, and Developmental Biology, Yale University, New Haven, CT 06520, USA

Received 30 November 2009; Accepted 14 May 2010

Academic Editor: Jamey Young

Copyright © 2010 A. De Martino et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. K. Kobayashi, S. D. Ehrlich, A. Albertini et al., “Essential Bacillus subtilis genes,” Proceedings of the National Academy of Sciences of the United States of America, vol. 100, no. 8, pp. 4678–4683, 2003. View at Publisher · View at Google Scholar · View at Scopus
  2. C. M. Sassetti, D. H. Boyd, and E. J. Rubin, “Comprehensive identification of conditionally essential genes in mycobacteria,” Proceedings of the National Academy of Sciences of the United States of America, vol. 98, no. 22, pp. 12712–12717, 2001. View at Publisher · View at Google Scholar · View at Scopus
  3. B. J. Akerley, E. J. Rubin, V. L. Novick, K. Amaya, N. Judson, and J. J. Mekalanos, “A genome-scale analysis for identification of genes required for growth or survival of Haemophilus influenzae,” Proceedings of the National Academy of Sciences of the United States of America, vol. 99, no. 2, pp. 966–971, 2002. View at Publisher · View at Google Scholar · View at Scopus
  4. S. Y. Gerdes, M. D. Scholle, J. W. Campbell et al., “Experimental determination and system level analysis of essential genes in Escherichia coli MG1655,” Journal of Bacteriology, vol. 185, no. 19, pp. 5673–5684, 2003. View at Publisher · View at Google Scholar · View at Scopus
  5. R. S. Kamath, A. G. Fraser, Y. Dong et al., “Systematic functional analysis of the Caenorhabditis elegans genome using RNAi,” Nature, vol. 421, no. 6920, pp. 231–237, 2003. View at Publisher · View at Google Scholar · View at Scopus
  6. R. Mahadevan and B. Ø. Palsson, “Properties of metabolic networks: structure versus function,” Biophysical Journal, vol. 88, no. 1, pp. L07–L09, 2005. View at Publisher · View at Google Scholar · View at Scopus
  7. A. Samal, S. Singh, V. Giri, S. Krishna, N. Raghuram, and S. Jain, “Low degree metabolites explain essential reactions and enhance modularity in biological netwoks,” BMC Bioinformatics, vol. 7, article 118, 2006. View at Publisher · View at Google Scholar · View at Scopus
  8. C. Martelli, A. De Martino, E. Marinari, M. Marsili, and I. P. Castillo, “Identifying essential genes in Escherichia coli from a metabolic. optimization principle,” Proceedings of the National Academy of Sciences of the United States of America, vol. 106, no. 8, pp. 2607–2611, 2009. View at Publisher · View at Google Scholar · View at Scopus
  9. T. A. Rapoport, R. Heinrich, and S. M. Rapoport, “The regulatory principles of glycolysis in erythrocytes in vivo and in vitro. A minimal comprehensive model describing steady states, quasi-steady states and time-dependent processes,” Biochemical Journal, vol. 154, no. 2, pp. 449–469, 1976. View at Google Scholar · View at Scopus
  10. H.-G. Holzhutter, G. Jacobasch, and A. Bisdorff, “Mathematical modelling of metabolic pathways affected by an enzyme deficiency. A mathematical model of glycolysis in normal and pyruvate-kinase-deficient red blood cells,” European Journal of Biochemistry, vol. 149, no. 1, pp. 101–111, 1985. View at Google Scholar · View at Scopus
  11. N. Jamshidi and B. Ø. Palsson, “Systems biology of the human red blood cell,” Blood Cells, Molecules, and Diseases, vol. 36, no. 2, pp. 239–247, 2006. View at Publisher · View at Google Scholar · View at Scopus
  12. D. B. Johnson, “Finding all the elemtary circuits of a directed graph,” SIAM Journal on Computing, vol. 4, p. 77, 1975. View at Google Scholar
  13. S. J. Wiback, I. Famili, H. J. Greenberg, and B. Ø. Palsson, “Monte Carlo sampling can be used to determine the size and shape of the steady-state flux space,” Journal of Theoretical Biology, vol. 228, no. 4, pp. 437–447, 2004. View at Publisher · View at Google Scholar · View at Scopus
  14. R. U. Ibarra, J. S. Edwards, and B. Ø. Palsson, “Escherichia coli K-12 undergoes adaptive evolution to achieve in silico predicted optimal growth,” Nature, vol. 420, no. 6912, pp. 186–189, 2002. View at Publisher · View at Google Scholar · View at Scopus
  15. D. Segrè, D. Vitkup, and G. M. Church, “Analysis of optimality in natural and perturbed metabolic networks,” Proceedings of the National Academy of Sciences of the United States of America, vol. 99, no. 23, pp. 15112–15117, 2002. View at Publisher · View at Google Scholar · View at Scopus
  16. N. D. Price, J. Schellenberger, and B. Ø. Palsson, “Uniform sampling of steady-state flux spaces: means to design experiments and to interpret enzymopathies,” Biophysical Journal, vol. 87, no. 4, pp. 2172–2186, 2004. View at Publisher · View at Google Scholar · View at Scopus
  17. A. Braunstein, R. Mulet, and A. Pagnani, “Estimating the size of the solution space of metabolic networks,” BMC Bioinformatics, vol. 9, article 240, 2008. View at Publisher · View at Google Scholar · View at Scopus
  18. S. J. Wiback and B. Ø. Palsson, “Extreme pathway analysis of human red blood cell metabolism,” Biophysical Journal, vol. 83, no. 2, pp. 808–818, 2002. View at Google Scholar · View at Scopus
  19. N. D. Price, J. L. Reed, J. A. Papin, S. J. Wiback, and B. Ø. Palsson, “Network-based analysis of metabolic regulation in the human red blood cell,” Journal of Theoretical Biology, vol. 225, no. 2, pp. 185–194, 2003. View at Publisher · View at Google Scholar · View at Scopus
  20. C. L. Barrett, N. D. Price, and B. Ø. Palsson, “Network-level analysis of metabolic regulation in the human red blood cell using random sampling and singular value decomposition,” BMC Bioinformatics, vol. 7, article 132, 2006. View at Publisher · View at Google Scholar · View at Scopus
  21. K. J. Kauffman, J. D. Pajerowski, N. Jamshidi, B. Ø. Palsson, and J. S. Edwards, “Description and analysis of metabolic connectivity and dynamics in the human red blood cell,” Biophysical Journal, vol. 83, no. 2, pp. 646–662, 2002. View at Google Scholar · View at Scopus
  22. K. J. Kauffman, P. Prakash, and J. S. Edwards, “Advances in flux balance analysis,” Current Opinion in Biotechnology, vol. 14, no. 5, pp. 491–496, 2003. View at Publisher · View at Google Scholar · View at Scopus
  23. A. De Martino and M. Marsili, “Typical properties of optimal growth in the von Neumann expanding model for large random economies,” Journal of Statistical Mechanics, no. 9, pp. 19–27, 2005. View at Publisher · View at Google Scholar · View at Scopus
  24. A. De Martino, C. Martelli, R. Monasson, and I. Pérez Castillo, “Von Neumann's expanding model on random graphs,” Journal of Statistical Mechanics, no. 5, Article ID P05012, 2007. View at Publisher · View at Google Scholar · View at Scopus
  25. I. Famili and B. Ø. Palsson, “The convex basis of the left null space of the stoichiometric matrix leads to the definition of metabolically meaningful pools,” Biophysical Journal, vol. 85, no. 1, pp. 16–26, 2003. View at Google Scholar · View at Scopus
  26. A. De Martino, C. Martelli, and F. A. Massucci, “On the role of conserved moieties in shaping the robustness and production capabilities of reaction networks,” Europhysics Letters, vol. 85, no. 3, Article ID 38007, 2009. View at Publisher · View at Google Scholar · View at Scopus
  27. R. Tarjan, “Depth-first search and linear graph algorithms,” SIAM Journal on Computing, vol. 1, no. 2, pp. 146–160, 1972. View at Google Scholar · View at Scopus
  28. W. Krauth and M. Mezard, “Learning algorithms with optimal stability in neural networks,” Journal of Physics, vol. 20, no. 11, pp. L745–L752, 1987. View at Publisher · View at Google Scholar · View at Scopus
  29. K. B. Storey, Ed., Functional Metabolism, Wiley-Liss, Nashville, Tenn, USA, 2004.
  30. S. Durmuş Tekir, T. Çakir, and K. Ö. Ülgen, “Analysis of enzymopathies in the human red blood cells by constraint-based stoichiometric modeling approaches,” Computational Biology and Chemistry, vol. 30, no. 5, pp. 327–338, 2006. View at Publisher · View at Google Scholar · View at Scopus
  31. G. Jacobasch, “Biochemical and genetic basis of red cell enzyme deficiencies,” Baillière's Clinical Haematologyy, vol. 13, no. 1, pp. 1–20, 2000. View at Publisher · View at Google Scholar · View at Scopus
  32. D. Vitkup, P. Kharchenko, and A. Wagner, “Influence of metabolic network structure and function on enzyme evolution,” Genome Biology, vol. 7, no. 5, article R39, 2006. View at Publisher · View at Google Scholar · View at Scopus
  33. R. P. Alexander, P. M. Kim, T. Emonet, and M. B. Gerstein, “Understanding modularity in molecular networks requires dynamics,” Science signaling, vol. 2, no. 81, p. pe44, 2009. View at Google Scholar · View at Scopus
  34. V. Van Kerrebroeck and E. Marinari, “Ranking vertices or edges of a network by loops: a new approach,” Physical Review Letters, vol. 101, no. 9, Article ID 098701, 2008. View at Publisher · View at Google Scholar · View at Scopus