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Flux-based classification of reactions reveals a functional bow-tie organization of complex metabolic networks

Shalini Singh1,2, Areejit Samal1,3,4, Varun Giri1, Sandeep Krishna5, Nandula Raghuram6, and Sanjay Jain1,7,8,*

  • 1Department of Physics and Astrophysics, University of Delhi, Delhi 110007, India
  • 2Department of Genetics, University of Delhi, South Campus, New Delhi, India
  • 3Max Planck Institute for Mathematics in the Sciences, Inselstrasse 22, D-04103 Leipzig, Germany
  • 4Laboratoire de Physique Théorique et Modèles Statistiques, CNRS and Université Paris-Sud, UMR 8626, F-91405 Orsay, France
  • 5National Centre for Biological Sciences, UAS-GKVK Campus, Bangalore 560065, India
  • 6School of Biotechnology, GGS Indraprastha University, Dwarka, New Delhi 110078, India
  • 7Jawaharlal Nehru Centre for Advanced Scientific Research, Bangalore 560064, India
  • 8Santa Fe Institute, 1399 Hyde Park Road, Santa Fe, New Mexico 87501, USA

  • *jain@physics.du.ac.in
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Phys. Rev. E 87, 052708 – Published 14 May, 2013

DOI: https://doi.org/10.1103/PhysRevE.87.052708

Abstract

Unraveling the structure of complex biological networks and relating it to their functional role is an important task in systems biology. Here we attempt to characterize the functional organization of the large-scale metabolic networks of three microorganisms. We apply flux balance analysis to study the optimal growth states of these organisms in different environments. By investigating the differential usage of reactions across flux patterns for different environments, we observe a striking bimodal distribution in the activity of reactions. Motivated by this, we propose a simple algorithm to decompose the metabolic network into three subnetworks. It turns out that our reaction classifier, which is blind to the biochemical role of pathways, leads to three functionally relevant subnetworks that correspond to input, output, and intermediate parts of the metabolic network with distinct structural characteristics. Our decomposition method unveils a functional bow-tie organization of metabolic networks that is different from the bow-tie structure determined by graph-theoretic methods that do not incorporate functionality.

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References (38)

  1. L. Hartwell, J. Hopfield, S. Leibler, and A. Murray, Nature (London) 402, C47 (1999).
  2. S. Bornholdt, H. Schuster, and J. Wiley, Handbook of Graphs and Networks, Vol. 2 (Wiley, New York, 2003).
  3. A. Barabási and Z. Oltvai, Nat. Rev. Genet. 5, 101 (2004).
  4. A. Wagner, Robustness and Evolvability in Living Systems (Princeton University Press, Princeton, NJ, 2005).
  5. K. Sneppen and G. Zocchi, Physics in Molecular Biology (Cambridge University Press, Cambridge, England, 2005).
  6. U. Alon, An Introduction to Systems Biology: Design Principles of Biological Circuits, Vol. 10 (Chapman & Hall/CRC, Boca Raton, FL, 2006).
  7. K. Kaneko, Life: An Introduction to Complex Systems Biology, Vol. 171 (Springer, Heidelberg, Germany, 2006).
  8. R. Heinrich and S. Schuster, The Regulation of Cellular Systems, Vol. 416 (Chapman & Hall, New York, 1996).
  9. H. Jeong, B. Tombor, R. Albert, Z. Oltvai, and A. Barabási, Nature (London) 407, 651 (2000).
  10. A. Wagner and D. Fell, Proc. R. Soc. London B 268, 1803 (2001).
  11. H. Ma and A. Zeng, Bioinformatics 19, 1423 (2003).
  12. M. Csete and J. Doyle, Trends Biotechnol. 22, 446 (2004).
  13. B. Palsson, Systems Biology: Properties of Reconstructed Networks (Cambridge University Press, Cambirdge, England, 2006).
  14. N. Price, J. Reed, and B. Palsson, Nat. Rev. Microbiol. 2, 886 (2004).
  15. A. Feist and B. Palsson, Nat. Biotechnol. 26, 659 (2008).
  16. M. Oberhardt, B. Palsson, and J. Papin, Mol. Syst. Biol. 5, 320 (2009).
  17. J. Edwards, R. Ibarra, B. Palsson et al., Nat. Biotechnol. 19, 125 (2001).
  18. R. Ibarra, J. Edwards, and B. Palsson, Nature (London) 420, 186 (2002).
  19. D. Segre, D. Vitkup, and G. Church, Proc. Natl. Acad. Sci. 99, 15112 (2002).
  20. J. Reed, T. Vo, C. Schilling, B. Palsson et al., Genome Biol. 4, R54 (2003).
  21. N. Duarte, M. Herrgård, and B. Palsson, Genome Res. 14, 1298 (2004).
  22. S. Becker and B. Palsson, BMC Microbiology 5, 8 (2005).
  23. A. Samal, S. Singh, V. Giri, S. Krishna, N. Raghuram, and S. Jain, BMC bioinformatics 7, 118 (2006).
  24. M. Eisen, P. Spellman, P. Brown, and D. Botstein, Proc. Natl. Acad. Sci. 95, 14863 (1998).
  25. T. Pfeiffer, F. Montero, S. Schuster et al., Bioinformatics 15, 251 (1999).
  26. J. Stelling, S. Klamt, K. Bettenbrock, S. Schuster, E. Gilles et al., Nature (London) 420, 190 (2002).
  27. J. Papin, N. Price, and B. Palsson, Genome Res. 12, 1889 (2002).
  28. J. Reed and B. Palsson, Genome Res. 14, 1797 (2004).
  29. A. Burgard, E. Nikolaev, C. Schilling, and C. Maranas, Genome Res. 14, 301 (2004).
  30. S. Lee, C. Phalakornkule, M. Domach, and I. Grossmann, Comput. & Chem. Eng. 24, 711 (2000).
  31. R. Mahadevan, C. Schilling et al., Metabolic Eng. 5, 264 (2003).
  32. A. Samal, Syst. Synth. Biology 2, 83 (2008).
  33. E. Almaas, B. Kovacs, T. Vicsek, Z. Oltvai, and A. Barabási, Nature (London) 427, 839 (2004).
  34. J. Ellson, E. Gansner, L. Koutsofios, S. North, and G. Woodhull, in Graph Drawing (Springer, New York, 2002), pp. 594–597.
  35. E. Almaas, Z. Oltvai, and A. Barabási, PLoS Comput. Biol. 1, e68 (2005).
  36. H. Ma, X. Zhao, Y. Yuan, and A. Zeng, Bioinformatics 20, 1870 (2004).
  37. A. Broder, R. Kumar, F. Maghoul, P. Raghavan, S. Rajagopalan, R. Stata, A. Tomkins, and J. Wiener, Computer Networks 33, 309 (2000).
  38. S. Schuster and R. Schuster, J. Math. Chem. 6, 17 (1991).

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Phys. Rev. E 87, 052708– Published 14 May, 2013
  • Received 9 December 2012

©2013 American Physical Society

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