1. The integrated model of apoptosis EO Kutumova, RN Sharipov, IN Lavrik, FA Kolpakov Design Technological Institute of Digital Techniques SB RAS, Institute of Systems Biology, Institute of Cytology and Genetics SB RAS, German Cancer Research Center (DKFZ) Novosibirsk, Russia

2. Presentation items Apoptosis is the programmed cell death Materials and methods  The integrated model of apoptosis creation  BioUML - the environment for systems biology modeling  Optimization plug-in of BioUML Results  The integrated model details  Parameters fitting

3. Apoptosis or programmed cell death MacFarlane M, Williams AC, EMBO Rep. 2004. 5:674-678 Reactome database: http://www.reactome.org/ TRANSPATH database:http://www.gene-regulation.com/

4. “Can a biologist fix a radio?—Or, what I learned while studying apoptosis“ Y Lazebnik (2002), Cancer Cell, 2(3): 179-182. Biologist view of a radio Engineer’s view of a radio

5. Mathematical models of apoptosis ModelsYearPathways Bentele M, et al2004CD95 induced apoptosis Rangamani P, et al 2007 TNF-alpha induced apoptosis Hua F, et al 2005Fas signaling, type II cells Eissing T, et al2004 Caspases activation Fussenegger M, et al 2000Caspase-function in apoptosis Stucki JW, et al 2005 Caspase-3 activation Legewie S, et al 2006Caspases activation and inhibition Schoeberl B, et al2002 EGF signaling Hoffmann A, et al2002IkB–NF-kB signaling module Hamada H, et al2008 P53 dynamics Bagci EZ, et al2006Mitochondrial level

6. Decomposition of the integrated model 13 modules 5 compartments 286 species 684 reactions 719 parameters

7. TRAIL- signaling CD95-signaling TNF-α-signaling Mitochondrial level Activation of effector caspases by caspase-8 Apoptosis execution phase Cleavage of PARP1 by caspase-3, -7 EGF-signaling p53- module Cytochrome C module NF- κB activation Smac module The integrated model overview Activation of effector caspases by caspase-12

8. BioUML main features Supports access to main biological databases:  catalolgs: Ensembl, UniProt, ChEBI, GO…  pathways: KEGG, Reactome, EHMN, BioModels, SABIO-RK, TRANSPATH, EndoNet, BMOND… Supports main standards used in systems biology: SBML, SBGN, CellML, BioPAX, OBO, PSI-MI… Database search and graph search Visual modeling Data analysis

9. BioUML workbench http://www.biouml.org/

10. BioUML web Availability Web edition:http://www.server.biouml.org/webedition BMOND database:http://www.bmond.biouml.org

11. Notation RNA Active monomer Inactive monomer Phosphorylated protein Heterodimer Homodimer Multimer Binary reaction Complex reaction Entities Reactions

12. Caspase-8 dynamics after TRAIL stimulation

13. Virtual experiments

14. Experimental data ReferencesCell lines Apoptosis inducers Farfan A, et al, 2004JurkatTRAIL Bentele M, et al, 2004SKW 6.4anti-APO-1 Lavrik IN, et al, 2007SKW 6.4anti-APO-1 Janes KA, et al, 2006HT29TNF Hua F, et al, 2005JurkatCD95L Neumann L, et al, 2010HeLaanti-CD95 Sprick MR, et al, 2002T cells CD95L Scaffidi C, et al, 1998CEManti-APO-1

15. Optimization plug-in

19. Main features Diagram parameters estimation Experimental data – time courses or steady states expressed as exact or relative values of substance concentrations Different optimization methods for analysis Multi-experiments optimization Constraint optimization Local/global parameters Parameters optimization using java script

20. Comparison with COPASI (10,000 simulations) MethodBioUML (4 cores) BioUML (1 core) COPASI (1 core) Evolutionary Programming –– 1 min 58,2sec 1 min 31,3 sec 1 min 16,6 sec Particle swarm7,1 sec 7,7 sec 6,9 sec 22,4 sec 15,3 sec 22,5 sec 1 min 32 sec 1 min 26,4 sec 1 min 07,1 sec Stochastic Ranking Evolution Strategy 7,5 sec 7,47 sec 6,9 sec 23,4 sec 23,5 sec 22,2 sec 1 min 25,0 sec 1 min 5,6 sec 1 min 8,8 sec Cellular genetic algorithm 7,7 sec 7,5 sec 7,2 sec 25,5 sec 22,1 sec 20,8 sec –

21. Multi-experiments fitting

23. Analysis diagram Experimental data tables Simulation results for all experiments Optimization document Fitted parameter values for two estimations

24. Java script for the optimization analysis

25. Results

26. Statistics 13 modules 5 compartments 286 species 684 reactions 719 parameters

27. TRAIL module (BMOND ID: Int_TRAIL signaling) Albeck JG, et al: PLoS Biol 2008 Additions: Trimerization of the TRAIL:TRAIL-R complex with subsequent binding by FADD Procaspase-10 activation pathway Reactions of degradation of FLIP long and FLIP short, casp-8 and casp-10

28. CD95 module (BMOND ID: Int_CD95 signaling) Bentele M, et al: The Journal of Cell Biology 2004 Additions: Trimerization of the CD95:CD95L complex Procaspase-10 activation pathway Reactions of degradation of FLIP long and FLIP short, casp-8 and casp-10

29. TNF-α module (BMOND ID: Int_TNF signaling) Rangamani P & Sirovich L: Biotechnology and Bioengineering 2007, Cho K-H, et al: Genome research 2003 Additions: Downregulation of FLIP by FOXO3a* Deactivation of FOXO3a by Akt-PP* Synthesis of procaspase-8 and its processing to the active form under the influence of IFN-gamma** *Kim H-S, et al: The FASEB Journal 2005 **Ossina NK, et al: J Biol Chem 1997

30. p53 module (BMOND ID: Int_p53 pathway) Hamada H, et al: PLoS One 2008 Additions: Upregulation of mdm- 2 by Akt-PP * * Gottlieb TM, et al: Oncogene 2002

31. NF-κB module (BMOND ID: Int_NF-κB module) Hoffmann A, et al: Science 2002 Werner SL, et al: Science 2005 Cheong R, et al: J Biol Chem 2006 Kearns JD, et al: J Cell Biol 2006 O’Dea EL, et al:Mol Syst Biol 2007 Additions: Regulation of cIAP by NF- κ B* Upregulation of NF- κ B by Akt-PP and ERK-PP** * Salvesen GS, Duckett CS: Nat Rev Mol Cell Biol 2002 ** Meng F, et al: J Biol Chem 2002

32. EGF module ( BMOND ID: Int_EGF signaling) Schoeberl B, et al: Nature Biotechnology 2002 Borisov N, et al: Molecular Systems Biology 2009 Additions: Reactions of protein syntheses and degradations

33. Mitochondria module (BMOND ID: Int_mitochondria) Bagci EZ, et al, Biophysical J 2006 Albeck JG, et al, PLoS Biol 2008 Additions: Activation of CREB and deactivation of BAD by Akt-PP and ERK-PP Upregulation of Bcl-2 by CREB Bcl-2 suppression by p53

34. Cytochrome C module (BMOND ID: Int_Cyt C response) Bagci EZ, et al, Biophysical Journal 2006 Legewie S, et al, PLoS Computational Biology 2006

35. SMAC module ( BMOND ID: Int_Smac response) Salvesen GS, Duckett CS: Nat Rev Mol Cell Biol 2002

36. Type I cells module ( BMOND ID: Int_type I cells) Bentele M, et al: The Journal of Cell Biology 2004

37. Caspase-12 module (BMOND ID: Int_casp-12 response) Fan T-Y, et al: Acta Biochimica et Biophysica Sinica 2005

38. PARP module ( BMOND ID: Int_PARP cleavage ) Bentele M, et al: The Journal of Cell Biology 2004 Albeck JG, et al: PLoS Biol 2008

39. Apoptosis execution phase module ( BMOND ID : Int_execution phase ) Fan T-Y, et al: Acta Biochimica et Biophysica Sinica 2005

40. Fitting results

41. Experimental data for the CD95 module was found in the papers: Neumann L, et al: Molecular Systems Biology, 2010 Bentele M, et al: The Journal of Cell Biology, 2004 Hua F, et al: The Journal of Immunology, 2005 Scaffidi C, et al: The EMBO Journal, 1998

42. Fitting results for the CD95L module Bentele M, 2004 Neumann L, 2010Scaffidi C, 1998 Hua F, 2005

43. Fitting of the TNF module parameters was based on the experimental data of Janes KA et al Janes KA, et al: Cell 2006

44. Fitting results for the TNF-α module Untreated cells 5 ng/ml of TNF-α 100 ng/ml of TNF-α

45. TRAIL module fitting Farfan A, et al: Cell Notes, 2004 Vilimanovich U and Bumbasirevic V: Cell. Mol. Life Sci., 2008

46. Fitting results for the TRAIL module Farfan, et al, Jurkat cellsVilimanovich, et al, LN-71 cells Vilimanovich, et al, U343MG cells

47. TRAIL- signaling CD95-signaling TNF-α-signaling Mitochondrial level Activation of effector caspases by caspase-8 Activation of effector caspases by caspase-12 Apoptosis execution phase Cleavage of PARP1 by caspase-3, -7 EGF-signaling p53- module Cytochrome C module NF- κB activation Smac module Conclusions

48. The integrated model of apoptosis is one of the most complex models existing at the moment. Modular representation for apoptosis models have never seen before. Effective optimization plug-in allowing to parallelize calculations was developed for the model parameters estimation. Availability: BioUML Home page:http://www.biouml.org Web edition:http://www.server.biouml.org/webedition BMOND database:http://www.bmond.biouml.org

49. Acknowledgements Part of this work was partially supported by the grant: European Committee grant №037590 “Net2Drug” European Committee grant №202272 “LipidomicNet” BioUML author: Fedor Kolpakov Useful comments, discussions and technical support: Alexander Kel and Sergey Zhatchenko Software developers Annotator Nikita TolstyhAlexey Shadrin Ruslan Sharipov Elena KutumovaTatyana Leonova Ilya KiselevMikhail Puzanov

50. Experimental data of Bentele M et al (CD95L concentration – 79.6 nM) Time (min) p43 (p43/p41)p55 (pro-8)p18 (casp-8) BLU% % % 011440510000 5161843129800 10192131237100 20343834407873 30384335808142 6055622930675021 120206231234053387163 180151170146533471198 2408910092721238100

51. Experimental data of Hua F et al (CD95L concentration – 2 nM) Time (h)procaspase-8 ( S.E.) 0.51 10,768717209793586 1.50,773312261257627 20,508999000649146 30,337764699869925 40,285381219211975 50,18596448144249 60,177879408426172 70,189180280994578 80,239456408757187

52. Experimental data of Janes KA, et al Time (h) Untreated cells TNF (100 ng/ml) TNF (5 ng/ml) pro-8 casp-8 pro-8casp-8pro-8casp-8 01002 0 7 0.08389231590927 0.251103317409813 0.51011184010513 11037173211819 1.511738151113020 210236200712714 410844145137512 812763135728923 1214346131908442 1614060132928558 2012892123988976 241511009910091100