A Modular Model of the Apoptosis Machinery

  • E. O. KutumovaEmail author
  • I. N. Kiselev
  • R. N. Sharipov
  • I. N. Lavrik
  • Fedor A. Kolpakov
Conference paper
Part of the Advances in Experimental Medicine and Biology book series (AEMB, volume 736)


Using a modular principle of computer hardware as a metaphor, we defined and implemented in the BioUML platform a module concept for biological pathways. BioUML provides a user interface to create modular models and convert them automatically into plain models for further simulations. Using this approach, we created the apoptosis model including 13 modules: death stimuli (TRAIL, CD95L, and TNF-α)-induced activation of caspase-8; survival stimuli (p53, EGF, and NFB) regulation; the mitochondria level; cytochrome C- and Smac-induced activation of caspase-3; direct activation of effector caspases by caspase-8 and − 12; PARP and apoptosis execution phase modules. Each module is based on earlier published models and extended by data from the Reactome and TRANSPATH databases. The model ability to simulate the apoptosis-related processes was checked; the modules were validated using experimental data. Availability:


Output Port Type Rule Diagram Type Substitution Rule Modular Model 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


  1. 1.
    Bentele M, Lavrik I, Ulrich M, Stößer S, Heermann DW, Kalthoff H, Krammer PH, Eils R (2004) Mathematical modeling reveals threshold mechanism in CD95-induced apoptosis. J Cell Biol 166(6):839–851PubMedCrossRefGoogle Scholar
  2. 2.
    Hoffmann A, Levchenko A, Scott ML, Baltimore D (2002) The IkB–NF-kB signaling module: temporal control and selective gene activation. Science 298:1241–1245PubMedCrossRefGoogle Scholar
  3. 3.
    Hamada H, Tashima Y, Kisaka Y, Iwamoto K, Hanai T, Eguchi Y, Okamoto M (2008) Sophisticated framework between cell cycle arrest and apoptosis induction based on p53 dynamics. PLoS One 4(3):e4795:1–7Google Scholar
  4. 4.
    Bagci EZ, Vodovotz Y, Billiar TR, Ermentrout GB, Bahar I (2006) Bistability in apoptosis: roles of Bax, Bcl-2 and mitochondrial permeability transition pores. Biophys J 90:1546–1559PubMedCrossRefGoogle Scholar
  5. 5.
    Legewie S, Bluthgen N, Herzel H (2006) Mathematical modeling identifies inhibitors of apoptosis as mediators of positive feedback and bistability. PLoS Comput Biol 2(9):e120:1061–1073Google Scholar
  6. 6.
    Rangamani P, Sirovich L (2007) Survival and apoptotic pathways initiated by TNF-alpha: modeling and predictions. Biotechnol Bioeng 97(5):1216–1229PubMedCrossRefGoogle Scholar
  7. 7.
    Cho K-H, Shin S-Y, Lee H-W, Wolkenhauer O (2003) Investigations into the analysis and modeling of the TNFα-mediated NF-κ B-signaling pathway. Genome Res 13:2413–2422PubMedCrossRefGoogle Scholar
  8. 8.
    Albeck JG, Burke JM, Spencer SL, Lauffenburger DA, Sorger PK (2008) Modeling a snap-action, variable-delay switch controlling extrinsic cell death. PLoS Biol 6(12):e299CrossRefGoogle Scholar
  9. 9.
    Hua F, Cornejo MG, Cardone MH, Stokes CL, Lauffenburger DA (2005) Effects of Bcl-2 levels on Fas signaling-induced caspase-3 activation: molecular genetic tests of computational model predictions. J Immunol 175:985–995PubMedGoogle Scholar
  10. 10.
    Schoeberl B, Eichler-Jonsson C, Gilles ED, Muller G (2002) Computational modeling of the dynamics of the MAP kinase cascade activated by surface and internalized EGF receptors. Nat Biotechnol 20:370–375PubMedCrossRefGoogle Scholar
  11. 11.
    Randhawa R, Shaffer CA, Tyson JJ (2009) Model aggregation: a building-block approach to creating large macromolecular regulatory networks. Bioinformatics 25(24):3289–3295PubMedCrossRefGoogle Scholar
  12. 12.
    Randhawa R, Shaffer CA, Tyson JJ (2010) Model composition for macromolecular regulatory networks. IEEE/ACM Trans Comput Biol Bioinform 7(2):278–287PubMedCrossRefGoogle Scholar
  13. 13.
    Joshi-Tope G, Gillespie M, Vastrik I, D’Eustachio P, Schmidt E, de Bono B, Jassal B, Gopinath GR, Wu GR, Matthews L, Lewis S, Birney E, Stein L (2005) Reactome: a knowledgebase of biological pathways. Nucleic Acids Res 33:D428–D432PubMedCrossRefGoogle Scholar
  14. 14.
    Krull M, Voss N, Choi C, Pistor S, Potapov A, Wingender E (2003) TRANSPATH: an integrated database on signal transduction and a tool for array analysis. Nucleic Acids Res 31(1):97–100PubMedCrossRefGoogle Scholar
  15. 15.
    Neumann L, Pforr C, Beaudouin J, Pappa A, Fricker N, Krammer PH, Lavrik IN, Eils R (2010) Dynamics within the CD95 death-inducing signaling complex decide life and death of cells. Mol Syst Biol 6:352PubMedCrossRefGoogle Scholar
  16. 16.
    Scaffidi C, Fulda S, Srinivasan A, Friesen C, Li F, Tomaselli KJ, Debatin K-M, Krammer PH, Peter ME (1998) Two CD95 (APO-1/Fas) signaling pathways. EMBO J 17(6):1675–1687PubMedCrossRefGoogle Scholar
  17. 17.
    Vilimanovich U, Bumbasirevic V (2008) TRAIL induces proliferation of human glioma cells by c-FLIPL-mediated activation of ERK1/2. Cell Mol Life Sci 65:814–826PubMedCrossRefGoogle Scholar
  18. 18.
    Farfan A, Yeager T, Moravec R, Niles A (2004) Multiplexing homogeneous cell-based assays. Cell Notes 10:15–18Google Scholar
  19. 19.
    Janes KA, Gaudet S, Albeck JG, Nielsen UB, Lauffenburger DA, Sorger PK (2006) The response of human epithelial cells to TNF involves an inducible autocrine cascade. Cell 124:1225–1239PubMedCrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC 2012

Authors and Affiliations

  • E. O. Kutumova
    • 1
    • 2
    Email author
  • I. N. Kiselev
    • 1
    • 2
  • R. N. Sharipov
    • 3
    • 1
  • I. N. Lavrik
    • 4
  • Fedor A. Kolpakov
    • 1
    • 2
  1. 1.Institute of Systems Biology, LtdNovosibirskRussia
  2. 2.Design Technological Institute of Digital Techniques SB RASNovosibirskRussia
  3. 3.Institute of Cytology and Genetics SB RASNovosibirskRussia
  4. 4.German Cancer Research Center (DKFZ)HeidelbergGermany

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