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A Primer in Bifurcation Theory for Computational Cell Biologists John J. Tyson Virginia Polytechnic Institute & Virginia Bioinformatics Institute [email protected] Click on icon to start audio
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A Primer in Bifurcation Theory for Computational Cell Biologists John J. Tyson Virginia Polytechnic Institute & Virginia Bioinformatics Institute [email protected].

Dec 23, 2015

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Page 1: A Primer in Bifurcation Theory for Computational Cell Biologists John J. Tyson Virginia Polytechnic Institute & Virginia Bioinformatics Institute tyson@vt.edu.

A Primer in Bifurcation Theoryfor Computational Cell Biologists

John J. TysonVirginia Polytechnic Institute

& Virginia Bioinformatics Institute

[email protected]

Click on icon to start audio

Page 2: A Primer in Bifurcation Theory for Computational Cell Biologists John J. Tyson Virginia Polytechnic Institute & Virginia Bioinformatics Institute tyson@vt.edu.

The Dynamical Perspectivein Molecular Cell Biology

Molec Genetics Biochemistry Cell Biology

Kinetic Equations

Molecular Mechanism

Page 3: A Primer in Bifurcation Theory for Computational Cell Biologists John J. Tyson Virginia Polytechnic Institute & Virginia Bioinformatics Institute tyson@vt.edu.

Cdk

C K

I

Cdk

Cyclin

C K

I

Cdk

Cyclin

Cdk

Cyclin

P

Cyclin

Cdk

Wee1

Cdc25

1 2 3 4

3 4 5

6 7

8 9

d[Cyclin][Cyclin] [Cyclin][Cdk] [MPF]

dd[MPF]

[Cyclin][Cdk] [MPF] [MPF]d

[Wee1][MPF] [Cdc25][preMPF]

[MPF][CKI] [MPF:CKI]

k k k kt

k k kt

k k

k k

MPF = Mitosis Promoting Factor

Page 4: A Primer in Bifurcation Theory for Computational Cell Biologists John J. Tyson Virginia Polytechnic Institute & Virginia Bioinformatics Institute tyson@vt.edu.

The Dynamical Perspectivein Molecular Cell Biology

Molec Genetics Biochemistry Cell Biology

Kinetic Equations

Molecular Mechanism

The Curse ofParameter Space

Page 5: A Primer in Bifurcation Theory for Computational Cell Biologists John J. Tyson Virginia Polytechnic Institute & Virginia Bioinformatics Institute tyson@vt.edu.

[Cyclin]

[CKI]

[MPF]

Kinetic Equations

State Space, Vector Field

Molecular Mechanism

Attractors, Transients, RepellorsHenri Poincare (1890)

Page 6: A Primer in Bifurcation Theory for Computational Cell Biologists John J. Tyson Virginia Polytechnic Institute & Virginia Bioinformatics Institute tyson@vt.edu.

The Dynamical Perspectivein Molecular Cell Biology

Molec Genetics Biochemistry Cell Biology

Kinetic Equations

State Space, Vector Field

Attractors, Transients, Repellors

Bifurcation Diagrams

Molecular Mechanism

Signal-Response Curves

Page 7: A Primer in Bifurcation Theory for Computational Cell Biologists John J. Tyson Virginia Polytechnic Institute & Virginia Bioinformatics Institute tyson@vt.edu.

Cdk

C K

I

Cdk

Cyclin

C K

I

Cdk

Cyclin

Cdk

Cyclin

P

Cyclin

Cdk

Wee1

Cdc25

= k1 - (kwee + k2) * MPF + k25 (cyclin - MPF)

= k1 - k2 * cyclin

d MPFdt

d cyclindt

Page 8: A Primer in Bifurcation Theory for Computational Cell Biologists John J. Tyson Virginia Polytechnic Institute & Virginia Bioinformatics Institute tyson@vt.edu.

MPF

Cyclin

d cyclindt

= k1 - k2 * cyclin = 0k1 / k2

d MPFdt

= … = 0

Page 9: A Primer in Bifurcation Theory for Computational Cell Biologists John J. Tyson Virginia Polytechnic Institute & Virginia Bioinformatics Institute tyson@vt.edu.

MPF

Cyclin

d cyclindt

= k1 - k2 * cyclin = 0k1 / k2

d MPFdt

= … = 0

Page 10: A Primer in Bifurcation Theory for Computational Cell Biologists John J. Tyson Virginia Polytechnic Institute & Virginia Bioinformatics Institute tyson@vt.edu.

MPF

Cyclin

d cyclindt

= k1 - k2 * cyclin = 0k1 / k2

d MPFdt

= … = 0

saddle-node

Page 11: A Primer in Bifurcation Theory for Computational Cell Biologists John J. Tyson Virginia Polytechnic Institute & Virginia Bioinformatics Institute tyson@vt.edu.

MPF

Cyclin

d cyclindt

= k1 - k2 * cyclin = 0k1 / k2

d MPFdt

= … = 0

Page 12: A Primer in Bifurcation Theory for Computational Cell Biologists John J. Tyson Virginia Polytechnic Institute & Virginia Bioinformatics Institute tyson@vt.edu.

One-parameter bifurcation diagram

Parameter, k1

Variable, MPF

stable steady state

unstable steady state

saddle-nodesaddle-node

Signal Response

t t

p x

OFF

ON

(signal)

(response)

x

y

Page 13: A Primer in Bifurcation Theory for Computational Cell Biologists John J. Tyson Virginia Polytechnic Institute & Virginia Bioinformatics Institute tyson@vt.edu.

Frog egg

MPF

Cdc25- PCdc25

MPF- P

0

0.5

1

0 1 2

resp

on

se (

MP

F)

signal (cyclin)

interphase

met

apha

se

(inactive)CycBMPF =

M-phase Promoting Factor

Page 14: A Primer in Bifurcation Theory for Computational Cell Biologists John J. Tyson Virginia Polytechnic Institute & Virginia Bioinformatics Institute tyson@vt.edu.

02468

101214

0 6 12 18 24 30 60

MPF activity depends on total cyclin concentration

and on the history of the extract

Cyclin concentration increasing

inactivation threshold at 90 min

MP

F a

ctiv

ity

nM cyclin B

M

IIIIII

02468

101214

0 6 12 18 24 30 60

MP

F a

ctiv

ity

nM cyclin B

M

M

MI/MIII

Cyclin concentration decreasing

I M

bistabilityWei Sha & Jill Sible (2003)

zero

zero

Page 15: A Primer in Bifurcation Theory for Computational Cell Biologists John J. Tyson Virginia Polytechnic Institute & Virginia Bioinformatics Institute tyson@vt.edu.

Oscillations

0

0.5

1

0 1 2

MP

F

cyclin

MPF

Cdc25- PCdc25

MPF- P(inactive)

cyclin synthesis

cyclin degradationAPC

negative feedback loop

Page 16: A Primer in Bifurcation Theory for Computational Cell Biologists John J. Tyson Virginia Polytechnic Institute & Virginia Bioinformatics Institute tyson@vt.edu.

Pomerening, Kim & FerrellCell (2005)

MP

F a

cti

vit

y

MPF activity

Total Cyclin

Total Cyclin

stable limit cycle

Page 17: A Primer in Bifurcation Theory for Computational Cell Biologists John J. Tyson Virginia Polytechnic Institute & Virginia Bioinformatics Institute tyson@vt.edu.

Variable,MPF

Parameter, k1

sss

uss

slc max

min

One-parameter bifurcation diagram

Hopf Bifurcation

stable limit cycle

Page 18: A Primer in Bifurcation Theory for Computational Cell Biologists John J. Tyson Virginia Polytechnic Institute & Virginia Bioinformatics Institute tyson@vt.edu.

The Dynamical Perspectivein Molecular Cell Biology

Molec Genetics Biochemistry Cell Biology

Kinetic Equations

State Space, Vector Field

Attractors, Transients, Repellors

Bifurcation Diagrams

Molecular Mechanism

Signal-Response Curves

Page 19: A Primer in Bifurcation Theory for Computational Cell Biologists John J. Tyson Virginia Polytechnic Institute & Virginia Bioinformatics Institute tyson@vt.edu.

•Saddle-Node (bistability, hysteresis)•Hopf Bifurcation (oscillations)•Subcritical Hopf•Cyclic Fold•Saddle-Loop•Saddle-Node Invariant Circle

Signal-Response Curve = One-parameter Bifurcation Diagram

Rene Thom

Page 20: A Primer in Bifurcation Theory for Computational Cell Biologists John J. Tyson Virginia Polytechnic Institute & Virginia Bioinformatics Institute tyson@vt.edu.

References

• Strogatz, Nonlinear Dynamics and Chaos (Addison Wesley)

• Kuznetsov, Elements of Applied Bifurcation Theory (Springer)

• XPP-AUT www.math.pitt.edu/~bard/xpp

• Oscill8 http://oscill8.sourceforge.net