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

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

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/

“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

Mathematical models of apoptosisModels Year Pathways

Bentele M, et al 2004 CD95 induced apoptosisRangamani P, et al 2007 TNF-alpha induced apoptosisHua F, et al 2005 Fas signaling, type II cellsEissing T, et al 2004 Caspases activationFussenegger M, et al

2000 Caspase-function in apoptosis

Stucki JW, et al 2005 Caspase-3 activationLegewie S, et al 2006 Caspases activation and inhibitionSchoeberl B, et al 2002 EGF signalingHoffmann A, et al 2002 IkB–NF-kB signaling module Hamada H, et al 2008 P53 dynamicsBagci EZ, et al 2006 Mitochondrial level

Decomposition of the integrated model

• 13 modules• 5 compartments• 286 species• 684 reactions• 719 parameters

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

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

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

BioUML web

AvailabilityWeb edition: http://www.server.biouml.org/webeditionBMOND database: http://www.bmond.biouml.org

Notation

RNA

Active monomer

Inactive monomer

Phosphorylated protein

Heterodimer

Homodimer

Multimer

Binary reaction Complex reaction

Entities

Reactions

Caspase-8 dynamics after TRAIL stimulation

Virtual experiments

Experimental data

References Cell lines Apoptosis inducers

Farfan A, et al, 2004 Jurkat TRAIL

Bentele M, et al, 2004 SKW 6.4 anti-APO-1

Lavrik IN, et al, 2007 SKW 6.4 anti-APO-1

Janes KA, et al, 2006 HT29 TNF

Hua F, et al, 2005 Jurkat CD95L

Neumann L, et al, 2010 HeLa anti-CD95Sprick MR, et al, 2002 T cells CD95L

Scaffidi C, et al, 1998 CEM anti-APO-1

Optimization plug-in

Optimization plug-in

Optimization plug-in

Optimization plug-in

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

Comparison with COPASI (10,000 simulations)

Method BioUML

(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 swarm 7,1 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

–

Multi-experiments fitting

Multi-experiments fitting

Analysis diagram

Experimental data tables

Simulation results for all experiments

Optimization document

Fitted parameter valuesfor two estimations

Java script for the optimization analysis

Results

Statistics

• 13 modules• 5 compartments• 286 species• 684 reactions• 719 parameters

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 FADDProcaspase-10 activation pathway Reactions of degradation of FLIP long and FLIP short, casp-8 and casp-10

CD95 module(BMOND ID: Int_CD95 signaling)

Bentele M, et al: The Journalof Cell Biology 2004Additions:Trimerization of the CD95:CD95L complexProcaspase-10 activation pathway Reactions of degradation of FLIP long and FLIP short, casp-8 and casp-10

TNF-α module (BMOND ID: Int_TNF signaling)

Rangamani P & Sirovich L: Biotechnology and Bioengineering 2007, Cho K-H, et al: Genome research 2003Additions: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

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

NF-κB module(BMOND ID: Int_NF-κB module)

Hoffmann A, et al: Science 2002Werner SL, et al: Science 2005Cheong R, et al: J Biol Chem 2006Kearns JD, et al: J Cell Biol 2006O’Dea EL, et al:Mol Syst Biol 2007

Additions:Regulation of cIAP by NF-κB*Upregulation of NF-κB by Akt-PP and ERK-PP**

* Salvesen GS, Duckett CS: Nat Rev Mol Cell Biol 2002** Meng F, et al: J Biol Chem 2002

EGF module(BMOND ID: Int_EGF signaling)

Schoeberl B, et al: Nature Biotechnology 2002

Borisov N, et al: Molecular Systems Biology 2009Additions:Reactions of protein syntheses and degradations

Mitochondriamodule(BMOND ID: Int_mitochondria)

Bagci EZ, et al, Biophysical J 2006Albeck JG, et al, PLoS Biol 2008Additions:Activation of CREB and deactivation of BAD by Akt-PP and ERK-PPUpregulation of Bcl-2 by CREBBcl-2 suppression by p53

Cytochrome Cmodule(BMOND ID:Int_Cyt C response)

Bagci EZ, et al,Biophysical Journal 2006

Legewie S, et al,PLoS Computational Biology 2006

SMAC module (BMOND ID: Int_Smac response)

Salvesen GS, Duckett CS: Nat Rev Mol Cell Biol 2002

Type I cells module (BMOND ID: Int_type I cells)

Bentele M, et al: The Journal of Cell Biology 2004

Caspase-12 module (BMOND ID: Int_casp-12 response)

Fan T-Y, et al: Acta Biochimica et Biophysica Sinica 2005

PARP module (BMOND ID: Int_PARP cleavage )

Bentele M, et al: The Journal of Cell Biology 2004Albeck JG, et al: PLoS Biol 2008

Apoptosis execution phase module(BMOND ID: Int_execution phase )

Fan T-Y, et al: Acta Biochimica et Biophysica Sinica 2005

Fitting results

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

Fitting results for the CD95L module

Bentele M, 2004

Neumann L, 2010 Scaffidi C, 1998

Hua F, 2005

Fitting of the TNF module parameters was based on the experimental data

of Janes KA et al

Janes KA, et al: Cell 2006

Fitting results for the TNF-α moduleUntreated cells 5 ng/ml of TNF-α

100 ng/ml of TNF-α

TRAIL modulefitting

• Farfan A, et al:Cell Notes, 2004 • Vilimanovich U and Bumbasirevic V:Cell. Mol. Life Sci., 2008

Fitting results for the TRAIL moduleFarfan, et al, Jurkat cellsVilimanovich, et al, LN-71 cells

Vilimanovich, et al, U343MG cells

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

p53-module

Cytochrome C module

NF- κB activation

Smac module

Conclusions

Conclusions

• 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.orgWeb edition: http://www.server.biouml.org/webeditionBMOND database: http://www.bmond.biouml.org

AcknowledgementsPart 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 AnnotatorNikita Tolstyh Alexey Shadrin Ruslan Sharipov Elena Kutumova Tatyana Leonova Ilya Kiselev Mikhail Puzanov

Experimental data of Bentele M et al(CD95L concentration – 79.6 nM)

Time (min)

p43 (p43/p41) p55 (pro-8) p18 (casp-8)

BLU % BLU % BLU %

0 1 1 4405 100 0 0

5 16 18 4312 98 0 0

10 19 21 3123 71 0 0

20 34 38 3440 78 7 3

30 38 43 3580 81 4 2

60 55 62 2930 67 50 21

120 206 231 2340 53 387 163

180 151 170 1465 33 471 198

240 89 100 927 21 238 100

Experimental data of Hua F et al(CD95L concentration – 2 nM)

Time (h) procaspase-8 ( S.E.)

0.5 1

1 0,768717209793586

1.5 0,773312261257627

2 0,508999000649146

3 0,337764699869925

4 0,285381219211975

5 0,18596448144249

6 0,177879408426172

7 0,189180280994578

8 0,239456408757187

Experimental data of Janes KA, et al

Time (h)

Untreated cells TNF (100 ng/ml) TNF (5 ng/ml)pro-8 casp-8 pro-8 casp-8 pro-8 casp-8

0 100 2 100 0 100 70.083 89 23 159 0 92 70.25 110 33 174 0 98 130.5 101 1 184 0 105 131 103 7 173 2 118 19

1.5 117 38 151 1 130 202 102 36 200 7 127 144 108 44 145 13 75 128 127 63 135 72 89 23

12 143 46 131 90 84 4216 140 60 132 92 85 5820 128 92 123 98 89 7624 151 100 99 100 91 100