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1. Practical Application Scenario: Cell Cycle & Kinetochore 2. From Hash Life to Particle Based Simulation 3. Chemical Organization Theory Jan Huwald Peter Dittrich Bio Systems Analysis Group Institute of Computer Science,

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SLIDE 1
  • 1. Practical Application Scenario:

Cell Cycle & Kinetochore

  • 2. From Hash Life to Particle Based Simulation
  • 3. Chemical Organization Theory

Jan Huwald Peter Dittrich

Bio Systems Analysis Group Institute of Computer Science, Friedrich-Schiller-University Jena

06.12.2012 Birmingham, HIERATIC Jan Huwald / Peter Dittrich - FSU Jena 1

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2

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Practical Application Scenario: Study of Kinetochor Organization and Mitotic Control

3 Jan Huwald / Peter Dittrich - FSU Jena 06.12.2012 Birmingham, HIERATIC

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  • http://nobelprize.org/nobel_prizes/medicine/laureates/2001/illpres/introduction.html
  • B. Ibrahim Diekmann S, Schmitt E, Dittrich P (2008) In-Silico Modeling of the Mitotic Spindle Assembly Checkpoint. PLoS ONE 3(2): e1555. doi:10.1371/journal.pone.0001555
  • B. Ibrahim et al. / Biophysical Chemistry 134 (2008) 93–100
  • B. Ibrahim et al. / BioSystems 95 (2009) 35–50

06.12.2012 Birmingham, HIERATIC 4 Jan Huwald / Peter Dittrich - FSU Jena

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SLIDE 5

Wait until all kinetochores are correctly attached

http://library.thinkquest.org/C004535/mitosis .html

WAIT!

06.12.2012 Birmingham, HIERATIC 5 Jan Huwald / Peter Dittrich - FSU Jena

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SLIDE 6

Wait until all kinetochores are correctly attached

http://library.thinkquest.org/C004535/mitosis .html

GO!

06.12.2012 Birmingham, HIERATIC 6 Jan Huwald / Peter Dittrich - FSU Jena

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SLIDE 7

Wait until all kinetochores are correctly attached

http://library.thinkquest.org/C004535/mitosis .html

GO!

06.12.2012 Birmingham, HIERATIC 7 Jan Huwald / Peter Dittrich - FSU Jena

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SLIDE 8

Systems Biology of Mitosis

  • http://nobelprize.org/nobel_prizes/medicine/laureates/2001/illpres/introduction.html
  • M. Lohel, B. Ibrahim, S. Diekmann, P. Dittrich (2009), The Role of Localization in the Operation of the Mitotic Spindle

Assembly Checkpoint, Cell Cycle, 8(16):2650 - 2660, 2009

  • B. Ibrahim Diekmann S, Schmitt E, Dittrich P (2008) In-Silico Modeling of the Mitotic Spindle Assembly Checkpoint. PLoS

ONE 3(2): e1555. doi:10.1371/journal.pone.0001555

  • B. Ibrahim et al. / Biophysical Chemistry 134 (2008) 93–100
  • B. Ibrahim et al. / BioSystems 95 (2009) 35–50

06.12.2012 Birmingham, HIERATIC 8 Jan Huwald / Peter Dittrich - FSU Jena

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9

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The Human Kinetochor

10 Jan Huwald / Peter Dittrich - FSU Jena 06.12.2012 Birmingham, HIERATIC

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The Human Kinetochore

11

Cell during mitosis

Jan Huwald / Peter Dittrich - FSU Jena 06.12.2012 Birmingham, HIERATIC

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SLIDE 12

The Human Kinetochore

12 Jan Huwald / Peter Dittrich - FSU Jena 06.12.2012 Birmingham, HIERATIC

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SLIDE 13

in vivo, in situ

cell cycle dependent

in vitro

cell cycle dependent

FRAP FRET FCS/FCCS RICS EM/AFM Y2H, M2H Pull-down Western blots in prepation: MassSpec

dynamics neighbourhood structure interaction interaction protein amounts protein modification dynamics dynamics

Experiments performed by the Diekmann Group (FLI Jena)

13 Jan Huwald / Peter Dittrich - FSU Jena 06.12.2012 Birmingham, HIERATIC

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Proximities derived from wet experiments (FRET)

06.12.2012 Birmingham, HIERATIC Jan Huwald / Peter Dittrich - FSU Jena 14

See: paper: D. Hellwig, S. Emmerth, T: Ulbricht, V: Döring, C. Hoischen, R. Martin, C. P. Samora, A. D. McAinsh, C. W. Carroll, A. F. Straight, P. Meraldi, S. Dekmann, Dynamic binding of CENP- N to the kinetochore through the cell cycle, J. Cell. Sci., 2011, 15;124, pp 3871-83. paper: L. Prendergast, C. v. Vuuren, A. Kaczmarczyk, V. Doering, D. Hellwig, N. uinn, C. Hoischen, S. Diekmann, K. F. Sullivan, Pre-mitotic assembly of CENPs -T and -W switches centromeric chromatin to a mitotic state, PLoS Biology, 2011; 9(6):e1001082, 2011. paper: A. Eskat, W. Deng, A. Hofmeister, S. Rudolphi, S. Emmerth, D. Hellwig,T. Ulbricht, V. Döring, J. M. Bancroft, A. D. McAinsh, M. C.Cardoso, P. Meraldi, C. Hoischen, H. Leonhardt, S. Diekmann, Step-Wise Assembly, Maturation and Dynamic Behavior of the Human CENP-P/O/R/Q/U Kinetochore Sub-Complex, PLoS ONE 7(9): e44717, 2012. paper: S. Dambacher, W Deng, Mahn,, D. Sadic, J.J. Fröhlich, A. Nuber, C. Hoischen, S. Diekmann, Heinrich Leonhardt and Gunnar Schotta, CENP-C facilitates the recruitment of M18BP1 to centromeric chromatin, Nucleus 3:1, 101–110; 2012. paper: M. Bui, E. K. Dimitriadis, C. Hoischen, E. An, D. Quénet, S. Giebe A. Nita-Lazar, S. Diekmann, Y. Dalal, Cell-Cycle-Dependent Structural Transitions in the Human CENP-A Nucleosome In Vivo, Cell 150, 317–326, 2012.

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3-D Rule-Based Model

  • 1. Set of reaction rules like
  • 2. Geometry information:
  • size of a molecule
  • angle of bond

15 Jan Huwald / Peter Dittrich - FSU Jena 06.12.2012 Birmingham, HIERATIC

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Rule-Based Modeling in Space

06.12.2012 Birmingham, HIERATIC Jan Huwald / Peter Dittrich - FSU Jena 16

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06.12.2012 Birmingham, HIERATIC Jan Huwald / Peter Dittrich - FSU Jena 17 # use the 'kill' modification to delete bonds (used by the next four rules) A(a!1).Pa(a!1~kill) -> A(a) + Pa(a~kill) Pa(a~kill) -> Pa(a~n) B(a!1).Pb(a!1~kill) -> B(a) + Pb(a~kill) Pb(a~kill) -> Pb(a~n) # transform the bonds A(a!2,x!1).B(x!1,a!4).Pa(a!2~n,x!3).Pb(x!3,a!4)

  • > A(a!2,x!1).B(x!1,a!4).Pa(a!2~kill,x!3).Pb(x!3,a!4)

A(a,x!1).B(x!1,a!2).Pb(a!2,x!3).Pa(x!3,a) + A(a,x!1).B(x!1,a)

  • > A(a,x!1).B(x!1,a!2).Pb(a!2,x!3).Pa(x!3,a!4).A(a!4,x!5).B(x!5,a)

A(x!1).B(x!1,a!2).Pb(a!2~n,x!3).Pa(x!3,a!4).A(a!4,x!5).B(x!5)

  • > A(x!1).B(x!1,a!2).Pb(a!2~kill,x!3).Pa(x!3,a!4).A(a!4,x!5).B(x!5)

A(a!+,x!1).B(x!1,a) + Pa(a!+,x!3).Pb(x!3,a)

  • > A(a!+,x!1).B(x!1,a!2).Pa(a!+,x!3).Pb(x!3,a!2)

# attach new motor-proteins to the filaments A(a,x!1).B(x!1,a,o!+) + Pa(a,x!3).Pb(x!3,a)

  • > A(a!2,x!1).B(x!1,a,o!+).Pa(a!2,x!3).Pb(x!3,a)

# release motor-proteins Fin(o!1).B(a!2,o!1).Pa(a,x!3).Pb(x!3,a!2)

  • > Fin(o!1).B(a,o!1) + Pa(a,x!3).Pb(x!3,a)

Example of an infinite reaction network

  • G. Grünert, B. Ibrahim, T. Lenser, M. Lohel, T. Hinze, P. Dittrich, BMC Bioinformatics, 11:307,

2010

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Interactions derived from wet experiments (FRET)

06.12.2012 Birmingham, HIERATIC Jan Huwald / Peter Dittrich - FSU Jena 18

See: paper: D. Hellwig, S. Emmerth, T: Ulbricht, V: Döring, C. Hoischen, R. Martin, C. P. Samora, A. D. McAinsh, C. W. Carroll, A. F. Straight, P. Meraldi, S. Dekmann, Dynamic binding of CENP- N to the kinetochore through the cell cycle, J. Cell. Sci., 2011, 15;124, pp 3871-83. paper: L. Prendergast, C. v. Vuuren, A. Kaczmarczyk, V. Doering, D. Hellwig, N. uinn, C. Hoischen, S. Diekmann, K. F. Sullivan, Pre-mitotic assembly of CENPs -T and -W switches centromeric chromatin to a mitotic state, PLoS Biology, 2011; 9(6):e1001082, 2011. paper: A. Eskat, W. Deng, A. Hofmeister, S. Rudolphi, S. Emmerth, D. Hellwig,T. Ulbricht, V. Döring, J. M. Bancroft, A. D. McAinsh, M. C.Cardoso, P. Meraldi, C. Hoischen, H. Leonhardt, S. Diekmann, Step-Wise Assembly, Maturation and Dynamic Behavior of the Human CENP-P/O/R/Q/U Kinetochore Sub-Complex, PLoS ONE 7(9): e44717, 2012. paper: S. Dambacher, W Deng, Mahn,, D. Sadic, J.J. Fröhlich, A. Nuber, C. Hoischen, S. Diekmann, Heinrich Leonhardt and Gunnar Schotta, CENP-C facilitates the recruitment of M18BP1 to centromeric chromatin, Nucleus 3:1, 101–110; 2012. paper: M. Bui, E. K. Dimitriadis, C. Hoischen, E. An, D. Quénet, S. Giebe A. Nita-Lazar, S. Diekmann, Y. Dalal, Cell-Cycle-Dependent Structural Transitions in the Human CENP-A Nucleosome In Vivo, Cell 150, 317–326, 2012.

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3-D Rule-Based Model

19 Jan Huwald / Peter Dittrich - FSU Jena 06.12.2012 Birmingham, HIERATIC

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What we can learn …

  • Bridge can form
  • Kinetochore has

different structures

  • Bridge depends on

nucleosome distances and molecule concentration

06.12.2012 Birmingham, HIERATIC Jan Huwald / Peter Dittrich - FSU Jena 20

Source: R. Henze et al.

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Clustering 600 Simulations

06.12.2012 Birmingham, HIERATIC Jan Huwald / Peter Dittrich - FSU Jena 21

Source: R. Henze et al.

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M-Phase Full Kinetochore (Inner and Outer Kinetochore)

06.12.2012 Birmingham, HIERATIC Jan Huwald / Peter Dittrich - FSU Jena 22

Source: R. Henze et al.

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3-D Rule-Based Model

23 Jan Huwald / Peter Dittrich - FSU Jena 06.12.2012 Birmingham, HIERATIC

Source: R. Henze et al.

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06.12.2012 Birmingham, HIERATIC Jan Huwald / Peter Dittrich - FSU Jena 24 # use the 'kill' modification to delete bonds (used by the next four rules) A(a!1).Pa(a!1~kill) -> A(a) + Pa(a~kill) Pa(a~kill) -> Pa(a~n) B(a!1).Pb(a!1~kill) -> B(a) + Pb(a~kill) Pb(a~kill) -> Pb(a~n) # transform the bonds A(a!2,x!1).B(x!1,a!4).Pa(a!2~n,x!3).Pb(x!3,a!4)

  • > A(a!2,x!1).B(x!1,a!4).Pa(a!2~kill,x!3).Pb(x!3,a!4)

A(a,x!1).B(x!1,a!2).Pb(a!2,x!3).Pa(x!3,a) + A(a,x!1).B(x!1,a)

  • > A(a,x!1).B(x!1,a!2).Pb(a!2,x!3).Pa(x!3,a!4).A(a!4,x!5).B(x!5,a)

A(x!1).B(x!1,a!2).Pb(a!2~n,x!3).Pa(x!3,a!4).A(a!4,x!5).B(x!5)

  • > A(x!1).B(x!1,a!2).Pb(a!2~kill,x!3).Pa(x!3,a!4).A(a!4,x!5).B(x!5)

A(a!+,x!1).B(x!1,a) + Pa(a!+,x!3).Pb(x!3,a)

  • > A(a!+,x!1).B(x!1,a!2).Pa(a!+,x!3).Pb(x!3,a!2)

# attach new motor-proteins to the filaments A(a,x!1).B(x!1,a,o!+) + Pa(a,x!3).Pb(x!3,a)

  • > A(a!2,x!1).B(x!1,a,o!+).Pa(a!2,x!3).Pb(x!3,a)

# release motor-proteins Fin(o!1).B(a!2,o!1).Pa(a,x!3).Pb(x!3,a!2)

  • > Fin(o!1).B(a,o!1) + Pa(a,x!3).Pb(x!3,a)

Example of an infinite reaction network

  • G. Grünert, B. Ibrahim, T. Lenser, M. Lohel, T. Hinze, P. Dittrich, BMC Bioinformatics, 11:307,

2010

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25

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From Hash Life to Particle Based Simulation

26 06.12.2012 Birmingham, HIERATIC Jan Huwald / Peter Dittrich - FSU Jena

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Chemical Organization Theory

27 Jan Huwald / Peter Dittrich - FSU Jena 06.12.2012 Birmingham, HIERATIC

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06.12.2012 Birmingham, HIERATIC Jan Huwald / Peter Dittrich - FSU Jena 28

Starting Point

<M, R> : reaction network M : set of (molecular) species Example: M = { a, b, c, d, e} R : set of reaction rules Example: R = { a + b  2 b,  a, a , … }

d c a b e

2 2

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06.12.2012 Birmingham, HIERATIC Jan Huwald / Peter Dittrich - FSU Jena 29

„Chemical Organization“

Organization := a set of molecular species that is (algebraically) closed and self-maintaining

Reaction inside the organization produce only species of that

  • rganization.

Within a self-maintaining set, all species consumed by a reaction can be produced by a reaction within the self-maintzaining set while no species concentration in the set decreases.

[Speroni di Fenizio/Dittrich (2005/7, Bull. Math. Biol. 2007) inspired by Fontana, Buss, Rössler, Eigen, Kauffman, Maturana, Varela, Uribe]

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06.12.2012 Birmingham, HIERATIC Jan Huwald / Peter Dittrich - FSU Jena 30

„Chemical Organization“

Organization := a set of molecular species that is (algebraically) closed and self-maintaining

In a self-maintaining set, it is possible to run all reactions at a strictily positive rate and no molecular species decreases.

[Speroni di Fenizio/Dittrich (2005/7, Bull. Math. Biol. 2007) inspired by Fontana, Buss, Rössler, Eigen, Kauffman, Maturana, Varela, Uribe]

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06.12.2012 Birmingham, HIERATIC Jan Huwald / Peter Dittrich - FSU Jena 31

Example 1

d c a b e

  • > a

2

a + b -> 2 b

2

a + c -> 2 c b -> d c -> d b + c -> e

a -> b -> c -> d -> e ->

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06.12.2012 Birmingham, HIERATIC Jan Huwald / Peter Dittrich - FSU Jena 32

Example 1

d c a b e

2 2

Organization {a, b, d}

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06.12.2012 Birmingham, HIERATIC Jan Huwald / Peter Dittrich - FSU Jena 33

Checking for Closure

d c a b e

2 2

Organization {a, b, d}

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06.12.2012 Birmingham, HIERATIC Jan Huwald / Peter Dittrich - FSU Jena 34

Checking for Self-Maintenance

d c a b e

2 2

Organization {a, b, d}

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06.12.2012 Birmingham, HIERATIC Jan Huwald / Peter Dittrich - FSU Jena 35

Checking for Self-Maintenance

d c a b e

2 2

Organization {a, b, d}

  • 1. Find flux vector
  • utside of org. = 0
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06.12.2012 Birmingham, HIERATIC Jan Huwald / Peter Dittrich - FSU Jena 36

Checking for Self-Maintenance

d c a b e

2 2

Organization {a, b, d}

  • 1. Find flux vector
  • utside of org. = 0

inside of org. > 0 1 1 1 10 9 8

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06.12.2012 Birmingham, HIERATIC Jan Huwald / Peter Dittrich - FSU Jena 37

Checking for Self-Maintenance

d c a b e

2 2

Organization {a, b, d}

  • 1. Find flux vector
  • utside of org. = 0

inside of org. > 0 1 1 1 10 9 8

  • 2. Check production rates
  • utside of org. = 0 (closure)
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06.12.2012 Birmingham, HIERATIC Jan Huwald / Peter Dittrich - FSU Jena 38

Checking for Self-Maintenance

d c a b e

2 2

Organization {a, b, d}

  • 1. Find flux vector
  • utside of org. = 0

inside of org. > 0 1 1 1 10 9 8

  • 2. Check production rates
  • utside of org. = 0 (closure)

7

inside of org. 0 (self-maint.)

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06.12.2012 Birmingham, HIERATIC Jan Huwald / Peter Dittrich - FSU Jena 39

All Organizations

d c a b e

2 2

All Organizations

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06.12.2012 Birmingham, HIERATIC Jan Huwald / Peter Dittrich - FSU Jena 40

All Organizations

d c a b e

2 2

All Organizationen a

a

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06.12.2012 Birmingham, HIERATIC Jan Huwald / Peter Dittrich - FSU Jena 41

All Organizations

All Organizations

d c a b e

2 2

a b d a

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06.12.2012 Birmingham, HIERATIC Jan Huwald / Peter Dittrich - FSU Jena 42

All Organizations

All Organizations a b d

d c a b e

2 2

a c d a

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06.12.2012 Birmingham, HIERATIC Jan Huwald / Peter Dittrich - FSU Jena 43

All Organizations

a b d a c d

d c a b e

2 2

a b c d e a Hasse diagram of

  • rganizations
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06.12.2012 Birmingham, HIERATIC Jan Huwald / Peter Dittrich - FSU Jena 44

„Overlapping Hierachy“

a b d a c d

d c a b e

2 2

a b c d e a Hasse diagram of

  • rganizations
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06.12.2012 Birmingham, HIERATIC Jan Huwald / Peter Dittrich - FSU Jena 45

„Overlapping Hierachy“

a b d a c d

d c a b e

2 2

a b c d e a Hasse diagram of

  • rganizations
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06.12.2012 Birmingham, HIERATIC Jan Huwald / Peter Dittrich - FSU Jena 46

Theorem: Fixed points are instances of

  • rganizations

a b d a c d a b c d e a

) (x x f  

                 ] [ ] [ ] [ ] [ ] [ e d c b a x

) ( x f 

                 11 7 4 x

differential equation fixed point / (stationary solution)

Hasse diagram of

  • rganizations

{ a, b, d } a b d

Dittrich/Speroni d.F., Bull. Math. Biol., 2007

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06.12.2012 Birmingham, HIERATIC Jan Huwald / Peter Dittrich - FSU Jena 47

Limit Set Theorem

[S. Peter, P. Dittrich, Adv. Compl. Sys. 14(1): 77-96, 2011]

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Transient Dynamics

Movement in state space Now: movement in the „space“ of organizations.

06.12.2012 Birmingham, HIERATIC Jan Huwald / Peter Dittrich - FSU Jena 48

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06.12.2012 Birmingham, HIERATIC Jan Huwald / Peter Dittrich - FSU Jena 49

Upward and Downward Movement in the “Space” of Organization

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50

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06.12.2012 Birmingham, HIERATIC Jan Huwald / Peter Dittrich - FSU Jena 51 # use the 'kill' modification to delete bonds (used by the next four rules) A(a!1).Pa(a!1~kill) -> A(a) + Pa(a~kill) Pa(a~kill) -> Pa(a~n) B(a!1).Pb(a!1~kill) -> B(a) + Pb(a~kill) Pb(a~kill) -> Pb(a~n) # transform the bonds A(a!2,x!1).B(x!1,a!4).Pa(a!2~n,x!3).Pb(x!3,a!4)

  • > A(a!2,x!1).B(x!1,a!4).Pa(a!2~kill,x!3).Pb(x!3,a!4)

A(a,x!1).B(x!1,a!2).Pb(a!2,x!3).Pa(x!3,a) + A(a,x!1).B(x!1,a)

  • > A(a,x!1).B(x!1,a!2).Pb(a!2,x!3).Pa(x!3,a!4).A(a!4,x!5).B(x!5,a)

A(x!1).B(x!1,a!2).Pb(a!2~n,x!3).Pa(x!3,a!4).A(a!4,x!5).B(x!5)

  • > A(x!1).B(x!1,a!2).Pb(a!2~kill,x!3).Pa(x!3,a!4).A(a!4,x!5).B(x!5)

A(a!+,x!1).B(x!1,a) + Pa(a!+,x!3).Pb(x!3,a)

  • > A(a!+,x!1).B(x!1,a!2).Pa(a!+,x!3).Pb(x!3,a!2)

# attach new motor-proteins to the filaments A(a,x!1).B(x!1,a,o!+) + Pa(a,x!3).Pb(x!3,a)

  • > A(a!2,x!1).B(x!1,a,o!+).Pa(a!2,x!3).Pb(x!3,a)

# release motor-proteins Fin(o!1).B(a!2,o!1).Pa(a,x!3).Pb(x!3,a!2)

  • > Fin(o!1).B(a,o!1) + Pa(a,x!3).Pb(x!3,a)

Organizations in rule-based (spatial) systems?

  • G. Grünert, B. Ibrahim, T. Lenser, M. Lohel, T. Hinze, P. Dittrich, BMC Bioinformatics, 11:307,

2010

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Our role in HIERATIC

53 Jan Huwald / Peter Dittrich - FSU Jena 06.12.2012 Birmingham, HIERATIC

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Role in HIERATIC

Responsible for: WP4 and WP7

D4.1) Multi-scale simulation library featuring spatial compartmentalisation and fast/slow time dynamics.: [month 12] D4.2) Integration of coarse-graining algorithms.: [month 24] D4.3) Implementation of algorithms to factor out less significant aspects of the system: [month 30] Take algorithms from WP3 and implement it (in MASON).

06.12.2012 Birmingham, HIERATIC Jan Huwald / Peter Dittrich - FSU Jena 54

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55

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WP7 Multi-scale biochemical reactions demonstrator

  • 1. Implement Artificial Chemistry simulation tool for biochemical reaction modelling with first version of

multi-scale simulation library.

  • 2. Compare theoretical analysis applied to biochemical reaction networks and empirical results with existing

Chemical Organisation Theory.

  • 3. Implement efficient multi-scale simulation tool for cell cycle control systems, making use of hierarchical

decomposition algorithms. This WP will be led by Jena, contributing to the development of the software library and theoretical analysis of reaction networks in terms of Chemical Organisation Theory. They will be assisted by USFD who bring expertise in network models of biochemical processes in and between cells. Person-Months per Participant

D7.1) Artificial Chemistry simulation library.: [month 24] D7.2) Efficient Cell Cycle control simulation library.: [month 36]

06.12.2012 Birmingham, HIERATIC Jan Huwald / Peter Dittrich - FSU Jena 56

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Whereas linear coarse-graining maps can be directly interpreted as a change of variables, non-linear coarse-grainings identify points in the original space as equivalent if they map onto the same connected level set of the new space. Finding a way to operationalise this representation is an important step on the way to finding constructions of nonlinear coarse- grainings.

06.12.2012 Birmingham, HIERATIC Jan Huwald / Peter Dittrich - FSU Jena 57

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06.12.2012 Birmingham, HIERATIC Jan Huwald / Peter Dittrich - FSU Jena 58

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06.12.2012 Birmingham, HIERATIC Jan Huwald / Peter Dittrich - FSU Jena 59

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06.12.2012 Birmingham, HIERATIC Jan Huwald / Peter Dittrich - FSU Jena 60

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06.12.2012 Birmingham, HIERATIC Jan Huwald / Peter Dittrich - FSU Jena 61

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Stochastic coarse graining

06.12.2012 Birmingham, HIERATIC Jan Huwald / Peter Dittrich - FSU Jena 62