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Humboldt- Universität zu Berlin Edda Klipp Systembiologie 9 – Signal Transduction Sommersemester 2010 Humboldt-Universität zu Berlin Institut für Biologie Theoretische Biophysik

Humboldt- Universität zu Berlin Edda Klipp Systembiologie 9 – Signal Transduction Sommersemester 2010 Humboldt-Universität zu Berlin Institut für Biologie

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Page 1: Humboldt- Universität zu Berlin Edda Klipp Systembiologie 9 – Signal Transduction Sommersemester 2010 Humboldt-Universität zu Berlin Institut für Biologie

Humboldt-Universität

zu Berlin

Edda Klipp

Systembiologie 9 – Signal Transduction

Sommersemester 2010

Humboldt-Universität zu BerlinInstitut für BiologieTheoretische Biophysik

Page 2: Humboldt- Universität zu Berlin Edda Klipp Systembiologie 9 – Signal Transduction Sommersemester 2010 Humboldt-Universität zu Berlin Institut für Biologie

Humboldt-Universität

zu Berlin

Modeling of Signal Transduction

Before: Metabolismus - Mass transferNow: Signal transduction - Information transfer

Typical Signals:• Hormones, pheromones• Heat, cold, osmotic pressure• concentration of certain substances (K, Ca, cAMP,..)• nutrient availability

http://www.bio.davidson.edu/courses/Immunology/Flash/MAPK.html

Interactive Animation of MAP Kinase Signal Transduction

http://www.idp.mdh.se/personal/bfg02/forskning/quasi/quasi12.htmlwww.apple.com/quicktime

Page 3: Humboldt- Universität zu Berlin Edda Klipp Systembiologie 9 – Signal Transduction Sommersemester 2010 Humboldt-Universität zu Berlin Institut für Biologie

Humboldt-Universität

zu Berlin

Typical Mechanism“Signal”

Activation of receptor at membran

Internalization of signalsG-Protein, Phosphorelay

Signal transmission

Activation of transcription factors

Transcription,Translation,Protein function biochemical response

Gen

mRNA Protein

Downregulation of signal

Page 4: Humboldt- Universität zu Berlin Edda Klipp Systembiologie 9 – Signal Transduction Sommersemester 2010 Humboldt-Universität zu Berlin Institut für Biologie

Humboldt-Universität

zu Berlin

Yeast Signaling Pathways

Page 5: Humboldt- Universität zu Berlin Edda Klipp Systembiologie 9 – Signal Transduction Sommersemester 2010 Humboldt-Universität zu Berlin Institut für Biologie

Humboldt-Universität

zu Berlin

Signaling Pathway Components

Page 6: Humboldt- Universität zu Berlin Edda Klipp Systembiologie 9 – Signal Transduction Sommersemester 2010 Humboldt-Universität zu Berlin Institut für Biologie

Humboldt-Universität

zu Berlin

Rezeptors

• transmembrane • receive signal and transmit it• conformation change• active or inactive form

Simple concept:

H + R HR

KD = H R HR

.

H - HormoneR - ReceptorHR - Hormone-receptor-complex

Typical values :KD = 10-12 M ….10-6 M

Ligand

Extrazellular space

Intrazellular space

Membrane

Receptor,Binding site

Rezeptor,zytosolische Domaine

inactive active

Page 7: Humboldt- Universität zu Berlin Edda Klipp Systembiologie 9 – Signal Transduction Sommersemester 2010 Humboldt-Universität zu Berlin Institut für Biologie

Humboldt-Universität

zu Berlin

Receptor, Extended Model

Ri Rs Ra

L

vis

vsi

vsa

vas

vpi

vdivai

vps

vds vda

aisiisdipii vvvvvRdt

d

assasiisdspss vvvvvvRdt

d

aiassadaa vvvvRdt

d

xxyxy Rkv

LRkv ssasa

nb

nb

ssasaLK

LKRkv

1

Differential equationsRate expressions ??

Mass action

Hill kinetics

Page 8: Humboldt- Universität zu Berlin Edda Klipp Systembiologie 9 – Signal Transduction Sommersemester 2010 Humboldt-Universität zu Berlin Institut für Biologie

Humboldt-Universität

zu Berlin

Receptor, Model of Yi et al.

Ri Rs Ra

L

vis

vsi

vsa

vas

vpi

vdi vai

vps

vds vda

0 10 20 30

0

2000

4000

6000

8000

10000

Time

Rs

Ra

Num

ber

of

Mol

ecul

es

0iR

0 ** ii vv

-1s cellper molecules 4pskpsps kv

sdsds Rkv

adada Rkv

LRkv ssasa

aasas Rkv

14 s104 dsk

13 s104 dak

116 sM102 sak

12 s101 ask

+L

Page 9: Humboldt- Universität zu Berlin Edda Klipp Systembiologie 9 – Signal Transduction Sommersemester 2010 Humboldt-Universität zu Berlin Institut für Biologie

Humboldt-Universität

zu Berlin

G-Proteine: „small G-proteins“

21

21

vvRasdt

d

vvRasdt

d

GTP

GDP

RasRasRas GTPGDPtotal

Differential equationsConservation relations

GDP GTP

GTPGDP+ +

z.B. Ras-Protein

GDPRas GTPRas

GDPGTPGEF

GAPPi

v1

v2

GEF – Guanine nucleotide exchange factorGAP – GTPase-activating protein

Page 10: Humboldt- Universität zu Berlin Edda Klipp Systembiologie 9 – Signal Transduction Sommersemester 2010 Humboldt-Universität zu Berlin Institut für Biologie

Humboldt-Universität

zu Berlin

G-Proteine: „small G-proteins“

e.g. Ras-Protein

GDPRas GTPRas

GDPGTP

GEF

GAPPi

v1

v2

GAPRaskv

GEFRaskv

GTP

GDP

22

11

GAPkGEFk

GEFkRasRas total

GTP

21

1

2 4 6 8 10

0.2

0.4

0.6

0.8

1

0.5 1 1.5 2

0.2

0.4

0.6

0.8

1

RasK

RasGAPkv

RasK

RasGEFkv

GTPm

GTP

GDPm

GDP

2

22

1

11

GT

PR

asG

TPR

as

GAP

GEF

GAP

GEF

21

21

vvRasdt

d

vvRasdt

d

GTP

GDP

RasRasRas GTPGDPtotal

Differential equations

1121 totalRaskk ;

111 2121 mmtotal KKRaskk ;;

Mass action

Michaelis Menten

GEF or GAP =1 (const.), other varying from 0 to 10

Enzyme concentration

Enzyme concentration

Page 11: Humboldt- Universität zu Berlin Edda Klipp Systembiologie 9 – Signal Transduction Sommersemester 2010 Humboldt-Universität zu Berlin Institut für Biologie

Humboldt-Universität

zu Berlin

G-Proteins: „small G-proteins“

21

21

vvRasdt

d

vvRasdt

d

GTP

GDP

RasRasRas GTPGDPtotal

Differential equations

e.g. Ras-Protein

GDPRas GTPRas

GDPGTP

GEF

GAPPi

v1

v2

0.5 1 1.5 2

0.2

0.4

0.6

0.8

1

RasK

RasGAPkv

RasK

RasGEFkv

GTPm

GTP

GDPm

GDP

2

22

1

11

GT

PR

as

GEF

GAP

„sigmoidal dependence“

„Ultrasensitivity“

„Switch-like regulation“

0.5 1 1.5 2

0.2

0.4

0.6

0.8

1

01021 . mm KK

1021 mm KK

GT

PR

as

Enzyme: GEF

Enzyme concentration111 2121 mmtotal KKRaskk ;;

Page 12: Humboldt- Universität zu Berlin Edda Klipp Systembiologie 9 – Signal Transduction Sommersemester 2010 Humboldt-Universität zu Berlin Institut für Biologie

Humboldt-Universität

zu Berlin

G-Proteins: „small G-proteins“

e.g. Ras-Protein

GDPRas GTPRas

GDPGTP

GEF

GAPPi

v1

v2

RasK

RasGAPkv

RasK

RasGEFkv

GTPm

GTP

GDPm

GDP

2

22

1

11

0.5 1 1.5 2

0.2

0.4

0.6

0.8

1

01021 . mm KK

1021 mm KK

GT

PR

as

Enzym: GEF

010

11

21

21

.

;;

mm

total

KK

Raskk

GT

PR

as

Zeit

GEF: 0 x

2 4 6 8 10

0.2

0.4

0.6

0.8

1

x=0.5

x=1.0

x=1.5

x=2.5x=2.0

Page 13: Humboldt- Universität zu Berlin Edda Klipp Systembiologie 9 – Signal Transduction Sommersemester 2010 Humboldt-Universität zu Berlin Institut für Biologie

Humboldt-Universität

zu Berlin

G-Protein

GDPG

GTPG

GDPG

GDP

activereceptor

Pi

signalG

Pi

slow fast

RGS

GTP

vga

vh1vh0

vsr

srga vvGdt

d

10 hhga vvvGTPGdt

d GDPGGTPGGGt

GGGtotal

0 10 20 30

0

2000

4000

6000

8000

10000

Time

G

Num

ber

of

Mol

ecul

es

G

GDPG

GTPG

Differential equationsConservation relations

GDP

GTP

+

GDP

+

Page 14: Humboldt- Universität zu Berlin Edda Klipp Systembiologie 9 – Signal Transduction Sommersemester 2010 Humboldt-Universität zu Berlin Institut für Biologie

Humboldt-Universität

zu Berlin

Phosphorelay-System

AspHis

Sln1 ATP

ADP

Pii

Ypd1

Ssk1-P

Pi

Pi

Pi

high osmolarity

?

Ypd1-P

Ssk1

Asp

12

3

4

5

Example: Sln1 pathway, Phosphorelay system

His

Asp

1111 31 YpdPASlnkSlnkSlndt

d

PHSlnkSlnkPHSlndt

d 111 21

1111 32 YpdPASlnkPHSlnkPASlndt

d

11111 34 YpdPASlnkSskPYpdkYpddt

d

11111 34 YpdPASlnkSskPYpdkPYpddt

d

1111 45 SskPYpdkPSskkSskdt

d

1111 45 SskPYpdkPSskkPSskdt

d

PASlnPHSlnSlnSln total 1111

PYpdYpdYpd total 111

PskSSskSsk total 111

- Transmits individual phosphate groups

Page 15: Humboldt- Universität zu Berlin Edda Klipp Systembiologie 9 – Signal Transduction Sommersemester 2010 Humboldt-Universität zu Berlin Institut für Biologie

Humboldt-Universität

zu Berlin

Phosphorelay-System

total

total

total

CCPC

BBPB

AAPA

CPkBPCkCdt

d

CBPkAPBkBdt

d

BAPkATPAkAdt

d

43

32

21

0 1 2 3 4 5

k1

0.2

0.4

0.6

0.8

1

A, B

, C

A-P A

ADP ATP

B B-P

C-P CP

k1

k2

k3

k4

Three component system

Two components

One component

0 50 100

0.02

0.04

0.06

0.08

0.1

Time

Dependence ofsteady state valuesOf stress strength

Temporal behavior,Stress – no Stress

A, B

, C

Page 16: Humboldt- Universität zu Berlin Edda Klipp Systembiologie 9 – Signal Transduction Sommersemester 2010 Humboldt-Universität zu Berlin Institut für Biologie

Humboldt-Universität

zu Berlin

Phosphorelay-System

B

C-P

B-P

C

v3

v4

A-P Av2

v1

0 100 200 300 400 500 600

0

0.2

0.4

0.6

0.8

1.

0.001 0.01 0.1 1. 10.

0

0.2

0.4

0.6

0.8

1.

Co

nce

ntr

atio

n C

Co

nce

ntr

atio

n,

a.u

.

Rate constant k4

Time a.u.

k1=10

k1=10.10.010.001

C

BA

Dynamics

Steady State

total

total

total

CCPC

BBPB

AAPA

CPkBPCkCdt

d

CBPkAPBkBdt

d

BAPkATPAkAdt

d

43

32

21

Page 17: Humboldt- Universität zu Berlin Edda Klipp Systembiologie 9 – Signal Transduction Sommersemester 2010 Humboldt-Universität zu Berlin Institut für Biologie

Humboldt-Universität

zu Berlin

MAP Kinase Cascade= Mitogen activated protein kinase cascade

MAPKKKK

MAPKKKinactive

MAPKKKactive

MAPKKinactive

MAPKKactive

MAPKinactive

MAPKactive

Signal

Page 18: Humboldt- Universität zu Berlin Edda Klipp Systembiologie 9 – Signal Transduction Sommersemester 2010 Humboldt-Universität zu Berlin Institut für Biologie

Humboldt-Universität

zu Berlin

MAP Kinase Cascade - Equations

ATPMAPKKKPkATPMAPKKKKMAPKKKkMAPKKKPdt

d

MAPKKKPkATPMAPKKKKMAPKKKkMAPKKKdt

d

21

41

MAPKKPPkATPMAPKKKPMAPKKPkMAPKKPPdt

d

MAPKKPkMAPKKPPkATPMAPKKKPMAPKKPkATPMAPKKKPMAPKKkMAPKKPdt

d

MAPKKPkATPMAPKKKPMAPKKkMAPKKdt

d

86

8765

85

MAPKPPkATPMAPKKPPMAPKPkMAPKPPdt

d

MAPKPkMAPKPPkATPMAPKKPPMAPKPkATPMAPKKPPMAPKkMAPKPdt

d

MAPKPkATPMAPKKPPMAPKkMAPKdt

d

1110

1211109

109

Page 19: Humboldt- Universität zu Berlin Edda Klipp Systembiologie 9 – Signal Transduction Sommersemester 2010 Humboldt-Universität zu Berlin Institut für Biologie

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MAP Kinase Cascade - Equations

totaltotal

totaltotal

totaltotal

MAPKKKCCPPCPC

MAPKKKBBPPBPB

MAPKKKAAPPAPA

CPPpBPPCPkCPPdt

d

CPpBPPCkCdt

d

BPPpAPBPkBPPdt

d

BPpAPBkBdt

d

APPpAPkAPPdt

d

APpSAkAdt

d

k – Kinase, p - Phosphatase Steady state

101234

10244

pSSSSS

kCBASCPP totaltotaltotal

...............

Sigmoidale dependence of concentrationof activated MAP kinase on concentration of input signal.

0 0.5 1 1.5 2kp0

0.05

0.1

0.15

0.2

PP

C

Page 20: Humboldt- Universität zu Berlin Edda Klipp Systembiologie 9 – Signal Transduction Sommersemester 2010 Humboldt-Universität zu Berlin Institut für Biologie

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MAPK Cascade: Impact of Kinases and Phosphatase

0 10 20 30 40 500

0.005

0.01

0.015

0.02

0.025

0 10 20 30 40 500

0.2

0.4

0.6

0.8

0 10 20 30 40 500

0.0025

0.005

0.0075

0.01

0.0125

0.015

0.0175

0 10 20 30 40 500

0.1

0.2

0.3

0.4

0.5

0.6

0.7

k=1

k=2

k=3k=4 k=5

k=1

0.9

0.8

0.7

0.6

p=1

p=1

p=1

1.1

1.2

1.3

1.4

k=1

p=0.5

p=0.3

p=0.4

p=0.1

p=0.2

Time, a.u. Time, a.u.

MA

PK

-PP

, a

.u.

MA

PK

-PP

, a

.u.

Time, a.u. Time, a.u.

A

B

C

D

MA

PK

-PP

, a

.u.

MA

PK

-PP

, a

.u.

k – Kinase, p - Phosphatase

Page 21: Humboldt- Universität zu Berlin Edda Klipp Systembiologie 9 – Signal Transduction Sommersemester 2010 Humboldt-Universität zu Berlin Institut für Biologie

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zu Berlin

71 vvMAPKKKdt

d

8271 vvvvPMAPKKKdt

d

822 vvPMAPKKKdt

d

....

0 20 40 60 80 1000

0.05

0.1

0.15

0.2

0.25

0 2 4 6 8 10

0.02

0.04

0.06

0.08

MA

PK

P2

MA

PK

P2(t

)

Time

MAPKKKK=0.1

k = 0.04

k = 0.36

k = 0.16

k = 0.64k = 1

k/p

MAPKKKK=0.01

1262 vvPMAPKdt

d

- Sigmoide input/output dependence

- Signal amplification

Time courses Steady states

MAP Kinase Cascade – Parameter Dependence

k – Kinase, p - Phosphatase

Page 22: Humboldt- Universität zu Berlin Edda Klipp Systembiologie 9 – Signal Transduction Sommersemester 2010 Humboldt-Universität zu Berlin Institut für Biologie

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MAPK Cascade: Control

P1,0 P1

1

2

P0

P2,0 P2

3

4

P3,0 P3

5

6

1 2 3 4 5 6

Rates

P1,0

P1

P2,0

P2

P3,0

P3

1

2

3

4

5

6

positive

none

negative

k

j

j

kJv v

J

J

vC j

k

k

i

i

kSv v

S

S

vC i

k

Page 23: Humboldt- Universität zu Berlin Edda Klipp Systembiologie 9 – Signal Transduction Sommersemester 2010 Humboldt-Universität zu Berlin Institut für Biologie

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MAPK Cascade: Control

P1,0

P0P1,0

P1X

P0

P1

P2,0

P1P2,0

P2X

P2

P3,0

P2P3,0

P3X

P3

with complex formation

1 2 3 4 5 6 7 8 9 10 11 12

Rates

P1,0

P0 P1,0

P1

P1X

P2,0

P1 P2,0

P2

P2X

P3,0

P2 P3,0

P3

P3X

1

2

3

4

5

6

7

8

9

10

11

12

1 2

4 3

5 6

8 7

9 10

12 11X – phosphatase

positive

none

negative

Page 24: Humboldt- Universität zu Berlin Edda Klipp Systembiologie 9 – Signal Transduction Sommersemester 2010 Humboldt-Universität zu Berlin Institut für Biologie

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zu Berlin

MAPK-Cascade with Feedbackand Michaelis-Menten Kinetics: Oscillations

Page 25: Humboldt- Universität zu Berlin Edda Klipp Systembiologie 9 – Signal Transduction Sommersemester 2010 Humboldt-Universität zu Berlin Institut für Biologie

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zu Berlin

MAP Kinase Cascade – Scaffolding

MAPKKK

MAPKK

MAPK

Ste5Ste11

Ste7Fus3

Sca

ffol

d

Page 26: Humboldt- Universität zu Berlin Edda Klipp Systembiologie 9 – Signal Transduction Sommersemester 2010 Humboldt-Universität zu Berlin Institut für Biologie

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MAP Kinase Cascade – Scaffolding

Ste5Ste11

Ste7Fus3

Double Phosphorylation of each protein

000 001 002

010 011 012

020 021 022100 101 102

110 111 112

120 121 122200 201 202

210 211 212

220 221 222

Page 27: Humboldt- Universität zu Berlin Edda Klipp Systembiologie 9 – Signal Transduction Sommersemester 2010 Humboldt-Universität zu Berlin Institut für Biologie

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Quantitative Measures for Signaling

0 1 2 3 4 50

0.1

0.2

0.3P1,0 P1

v1f

v1r

P2,0 P2

P3,0 P3

v2r

P0

v2f

v3f

v3r

Time, a.u.C

on

cen

tra

tion

, a

.u.

A11

1

P1

P1maxt1max

(a) (b)

Transition time

0

0

dttX

dttXt

i

i

i

2

0

0

2

i

i

i

i

dttX

dttXt

i

i

i

dttX

S

20

Signal duration Amplitude

Heinrich et al., T.A. Mol.Cell, 2002

Page 28: Humboldt- Universität zu Berlin Edda Klipp Systembiologie 9 – Signal Transduction Sommersemester 2010 Humboldt-Universität zu Berlin Institut für Biologie

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Crosstalk & Signal Integration

Schaber, Kofahl, Kowald & Klipp, 2006, FEBS J.

Signal Signal

Receptor A Receptor B

Target A Target BX – function of amplitude, timing or integral of response

AX

BXC

BAX

AXSi ,

Measures of crosstalk

BAX

BXSe ,

Se > 1 Se < 1

Si > 1

Si < 1

Mutual signalinhibition

Mutual signalamplification

Dominance ofextrinsic signal

Dominance ofintrinsic signal

PheromonePathway

FilamentousGrowth Pathway

Crossactivation

Mutual signalamplification

Crossinhibition

Dominance of intrinsic signal

Page 29: Humboldt- Universität zu Berlin Edda Klipp Systembiologie 9 – Signal Transduction Sommersemester 2010 Humboldt-Universität zu Berlin Institut für Biologie

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Crosstalk

0 1 2 3 4 50

0.1

0.2

0.3

0 1 2 3 4 50

0.1

0.2

0.3

0 1 2 3 4 50

0.1

0.2

0.3

0 1 2 3 4 50

0.1

0.2

0.3

P1A,0 P1A

v1Af

v1Ar

P2A,0 P2A

P3A,0 P3A

v2Ar

= P0A

v2Af

v3Af

v3Ar

P1B,0P1B

v1Bf

v1Br

P2B,0P2B

P3B,0P3B

= P0B

v2Bf

v3Bf

v3Br

(a)

v2Br

P1A

P2A

P3A

P1B

P2B

P3BP1A P2A

P3A

P1A

P2A

P3A

Time a.u

Co

nce

ntr

atio

n a

.u.

Time a.u

Co

nce

ntr

atio

n a

.u.

0 1 2 3 4 50

0.1

0.2

0.3

P1B

P2B

P3B

ki = 1 ki = 10

0 1 2 3 4 50

0.1

0.2

0.3

Co

nce

ntr

atio

n a

.u.

Page 30: Humboldt- Universität zu Berlin Edda Klipp Systembiologie 9 – Signal Transduction Sommersemester 2010 Humboldt-Universität zu Berlin Institut für Biologie

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Crosstalk

0 1 2 3 4 50

0.1

0.2

0.3

0 1 2 3 4 50

0.1

0.2

0.3

0 1 2 3 4 50

0.1

0.2

0.3

P1A,0 P1A

v1Af

v1Ar

P2A,0 P2A

P3A,0 P3A

v2Ar

= P0A

v2Af

v3Af

v3Ar

P1B,0P1B

v1Bf

v1Br

P2B,0P2B

P3B,0P3B

= P0B

v2Bf

v3Bf

v3Br

v2Br

P1A

P2A

P3A

P1A P2AP3A

P1A

P2A

P3A

Co

nce

ntr

atio

n a

.u.

Time a.u

Co

nce

ntr

atio

n a

.u.

ki = 1 ki = 10

Co

nce

ntr

atio

n a

.u.

I = 0.628748Pmax = 0.132872tmax = 2.85456

I = 0.067494Pmax = 0.0459428tmax = 0.538455

I = 0.688995Pmax = 0.136802tmax = 2.73227

Integrated Response

Timing of Response

,A

Ai X

XAS

,A

Ae X

XAS

Si(Pmax) = 0.97

Se(I) = 0.097

Si(I) = 0.91

Se(Pmax) = 0.34

Se(tmax) = 0.197

Si(tmax) = 1.04

Mutual amplification

Mutual amplification

Dominance ofintrinsic signal

Maximal Response

Page 31: Humboldt- Universität zu Berlin Edda Klipp Systembiologie 9 – Signal Transduction Sommersemester 2010 Humboldt-Universität zu Berlin Institut für Biologie

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Integration of Signaling Pathways

m24; FRE, medium Responses: 9,10,11

0 10 20 30 40 500

0.0005

0.001

0.0015

0.002

0.0025

m20; PRE, large Responses: 5,17,19,20

0 10 20 30 40 500

0.2

0.4

0.6

0.8

m20; PRE, medium negative Responses: 7,9,12,18,21

0 10 20 30 40 500.2

0.15

0.1

0.05

0

5

79

11

12

17

18

1920

21

5

9

10

11

4 -Fus3 phosphorylation in MAPKcascade6 -repeated Fus3 phosphorylation10-Kss1 phosphorylation in MAPKcascade21-Kss1 release from Ste12Tec1 complex

Response coefficients of

m24; FRE, large negative Responses: 6,16,30,31,39

0 10 20 30 40 50

0.01

0.008

0.006

0.004

0.002

0

6

Time/min Time/min

m24; FRE, plus minus Responses: 2,4,5,21,22

0 10 20 30 40 500.006

0.004

0.002

0

0.002

0.004

0.006

2

4

21

22

m20; PRE, medium Responses: 3,4,6,10,11,40

0 10 20 30 40 500

0.025

0.05

0.075

0.1

0.125

0.15

0.175

46

10

PREs FREs

l

i

i

lSp p

tS

tS

pR i

l

Page 32: Humboldt- Universität zu Berlin Edda Klipp Systembiologie 9 – Signal Transduction Sommersemester 2010 Humboldt-Universität zu Berlin Institut für Biologie

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Putting all together : the Pheromone pathway

a

a

a

a

MATa-cells MAT-cells

Page 33: Humboldt- Universität zu Berlin Edda Klipp Systembiologie 9 – Signal Transduction Sommersemester 2010 Humboldt-Universität zu Berlin Institut für Biologie

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MATa-cells MAT-cells

Putting all together: the Pheromone pathway

a

a

a

a

Page 34: Humboldt- Universität zu Berlin Edda Klipp Systembiologie 9 – Signal Transduction Sommersemester 2010 Humboldt-Universität zu Berlin Institut für Biologie

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Pheromone pathway

Ste50

Cdc

42

Ste5

G

G

PP

NucleusCytoplasm

Bem1

Cdc24

Plasma membrane

Extracellular space

Ste20

Ste2G

G

G

G Ste11

Ste7

Fus3

Fus3Fus3

Far1Cdc24 P

P

ClnCdc28

Far1Cdc24

Far1

Actin

GSte20

Cdc

42

G

Cdc24

Bem1

Bar1

active

GTP

GDP

GGDP

Sst2

Ste12

Dig1Dig2

Kss1

Ste12

Dig1Dig2

Kss1

Ste12

Ste12

Ste2

Page 35: Humboldt- Universität zu Berlin Edda Klipp Systembiologie 9 – Signal Transduction Sommersemester 2010 Humboldt-Universität zu Berlin Institut für Biologie

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Pheromone pathway

Cdc

42

Ste5

GG

Bem1

Cdc24

Extracellular space

Ste20

Ste2G

G

G

G

GTP

GDP

GGDP

Sst2

Ste2

NucleusCytoplasm

Far1Cdc24 P

P

ClnCdc28

Far1Cdc24

Bar1

active

Ste12

Dig1Dig2

Kss1

Ste12

Dig1Dig2

Kss1

Ste12

Ste12

PPFus3

Fus3

Plasma membrane

Far1

Actin

GSte20

Cdc

42

G

Cdc24

Bem1

Ste50 Ste11

Ste7

Fus3

Page 36: Humboldt- Universität zu Berlin Edda Klipp Systembiologie 9 – Signal Transduction Sommersemester 2010 Humboldt-Universität zu Berlin Institut für Biologie

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Pheromone pathway

Ste50

Cdc

42

Ste5

GG

PP

Bem1

Cdc24

Plasma membrane

Extracellular space

Ste20

Ste2G

G

G

G Ste11

Ste7

Fus3

Fus3Fus3

Far1

Actin

GSte20

Cdc

42

G

Cdc24Bem1GTP

GDP

GGDP

Sst2

Ste2

NucleusCytoplasm

Far1Cdc24 P

P

ClnCdc28

Far1Cdc24

Bar1

active

Ste12

Dig1Dig2

Kss1

Ste12

Dig1Dig2

Kss1

Ste12

Ste12

Page 37: Humboldt- Universität zu Berlin Edda Klipp Systembiologie 9 – Signal Transduction Sommersemester 2010 Humboldt-Universität zu Berlin Institut für Biologie

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Pheromone pathway

Ste50

Cdc

42

Ste5

GG

PP

NucleusCytoplasm

Bem1

Cdc24

Plasma membrane

Extracellular space

Ste20

Ste2G

G

G

G Ste11

Ste7

Fus3

Fus3Fus3

Far1Cdc24 P

P

ClnCdc28

Far1Cdc24

Far1

Actin

GSte20

Cdc

42

G

Cdc24Bem1

Bar1active

GTP

GDP

GGDP

Sst2

Ste12

Dig1Dig2

Kss1

Ste12

Dig1Dig2

Kss1

Ste12

Ste12

Ste2

Page 38: Humboldt- Universität zu Berlin Edda Klipp Systembiologie 9 – Signal Transduction Sommersemester 2010 Humboldt-Universität zu Berlin Institut für Biologie

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Pheromone pathway: structural parts

Ste2

G

Fus3 Sst2

Ste12Bar1

MAPKscaffold

Far1Cdc28

Plasma membrane

Gene expression Complex formation

Signalingcascade

G proteincycle

Receptor activation

Pheromone

Page 39: Humboldt- Universität zu Berlin Edda Klipp Systembiologie 9 – Signal Transduction Sommersemester 2010 Humboldt-Universität zu Berlin Institut für Biologie

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Ste2

G

Fus3 Sst2

Ste12Bar1

MAPKscaffold

Far1Cdc28

Plasma membrane

Gene expression Complex formation

Signalingcascade

G proteincycle

Receptor activation

Pheromone

Yu et al., Nature, 2008

Page 40: Humboldt- Universität zu Berlin Edda Klipp Systembiologie 9 – Signal Transduction Sommersemester 2010 Humboldt-Universität zu Berlin Institut für Biologie

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Pheromone pathway: time courses

In comprehensive model: regulatory feedback loops are consideredmutant phenotypes can be investigated

10-3 10-2 10-1 100 101 102 103 104

0

0.2

0.4

0.6

0.8

1

Ste12active

Fus3PP

G-Far1

Rel

ativ

e C

once

ntra

tion

-factor / nM

Far1-Cdc28

Graded response depending on concentration of -factor

Polarized growth

CellCyclearrest

Kofahl & Klipp, Yeast, 2004

Page 41: Humboldt- Universität zu Berlin Edda Klipp Systembiologie 9 – Signal Transduction Sommersemester 2010 Humboldt-Universität zu Berlin Institut für Biologie

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Pheromone pathway: time coursesF

us3

-PP

G

0 10 20 300

1.2

0.025

0.05

1.17

0 10 20 300

0.20.4

0.60.8

1.

1.2

0 10 20 300

0.2

0.4

0.6

0.8

1.

1.2

0 10 20 300

0.2

0.4

0.6

0 10 20 30

0.01

0.02

0.03

0.04

0 10 20 300

0.01

0.02

0.03

0.04

0 10 20 300

0.01

0.02

0.03

0 10 20 300

0.02

0.04

0.06

0 10 20 30

0.1

0.2

0.3

0.4

0 10 20 30

0.1

0.2

0.3

0.4

0 10 20 30

0.1

0.2

0.3

0 10 20 30

0.1

0.2

0.3

0.4

Overexpression G

G defect in binding G

Overexpression G

sst2

Sst2 mutant

Sst2 gain of function

Page 42: Humboldt- Universität zu Berlin Edda Klipp Systembiologie 9 – Signal Transduction Sommersemester 2010 Humboldt-Universität zu Berlin Institut für Biologie

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Yu & Brent et al.: Experimental Data

Page 43: Humboldt- Universität zu Berlin Edda Klipp Systembiologie 9 – Signal Transduction Sommersemester 2010 Humboldt-Universität zu Berlin Institut für Biologie

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Yu & Brent et al.: Experimental Data

DoRA – Dose Response Alignment

Page 44: Humboldt- Universität zu Berlin Edda Klipp Systembiologie 9 – Signal Transduction Sommersemester 2010 Humboldt-Universität zu Berlin Institut für Biologie

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Yeast Cell as an Osmometer

Eriksson, Lab on Chip, 2006

Serge Pelet, ETH, Zürich

Yeast cells shrink upon osmoshock

Stress adaptation requires glycerol accumulation.

MAPK Hog1 is considered a key player.

Page 45: Humboldt- Universität zu Berlin Edda Klipp Systembiologie 9 – Signal Transduction Sommersemester 2010 Humboldt-Universität zu Berlin Institut für Biologie

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Osmotic Stress Response

Ypd1

High osmolarity

Ssk1

Sln1

Ssk2

Pbs2

Hog1 mRNA

Protein

Glycerol

Turgor Fps1

Construct network from literature data and experts‘ knowledge

Study properties of small modules, e.g. MAPK cascade, G protein cycles, …

MKKK-P

MKK-PPMKK

MK-PPMK

k

p

MKKKK

MKKK

0 10 20 30 40 500

0.005

0.01

0.015

0.02

0.025

0 10 20 30 40 500

0.1

0.2

0.3

0.4

0.5

0.6

0.7

k/p=1

k/p=2

k/p=3

k/p=4k/p=5

k/p=1

0.9

0.8

0.70.6

Time, a.u.

MA

PK

-PP

, a

.u.

MA

PK

-PP

, a

.u.

Parameter change

Amplitude

Duration

Collect experimental data (time series!!!)Estimate model parametersSimulate: Agreement of model/experiment?Sensitivity analysis

Prediction of hitherto untested scenarios- Deletion mutants- Compound overexpression- New experimental scenarios

Transcriptome data – mRNA levelsProteome data – phosphorylation, concentration changesMetabolome data – concentration changes

MA

PK

casc

adeP

hosp

hore

lay

Gene regulation

Metabolism

Systems equations (Set of ODEs)

r – number of reactionsSi – metabolite concentrationsvj – reaction ratesnij – stoichiometric coefficients

Network properties

Individual reaction properties

r

jjij

i vndt

dS

1

Page 46: Humboldt- Universität zu Berlin Edda Klipp Systembiologie 9 – Signal Transduction Sommersemester 2010 Humboldt-Universität zu Berlin Institut für Biologie

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Osmostress Response – Full Model

Klipp, Nordlander, Krüger, Gennemark & Hohmann, Nature Biotechn, 2005

Page 47: Humboldt- Universität zu Berlin Edda Klipp Systembiologie 9 – Signal Transduction Sommersemester 2010 Humboldt-Universität zu Berlin Institut für Biologie

Humboldt-Universität

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Ypd1

High osmolarity

Ssk1

Sln1

Ssk2

Pbs2

Hog1 mRNA

Protein

Glycerol

Turgor Fps1

0 30 60 90 120

0

0.2

0.4

0.6

0.8

1.

Time / min

mRNA

Ssk1

Co

nce

ntr

atio

n,

rela

tive

Hog1P2

Gpd1

A

WT

Hog

1P2

Time / min0 30 60 90 120

00.20.40.60.8

1.1.2

wild type

Fps1 open

Ptp2 over

Fps open+Ptp2 over

0 30 60 90 120

0

0.5

1.

1.5

Time / min

mRNA

GlycinC

on

cen

tra

tion

, re

lativ

e

Hog1P2

Protein

A

Gpd1Fps1 mutant

Osmotic stress

Klipp et al.,Nature Biotechn, 2005

Page 48: Humboldt- Universität zu Berlin Edda Klipp Systembiologie 9 – Signal Transduction Sommersemester 2010 Humboldt-Universität zu Berlin Institut für Biologie

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Osmotic stress model: Test cases

Ypd1

High osmolarity

Ssk1

Sln1

Ssk2

Pbs2

Hog1 mRNA

Protein

Glycerol

Turgor Fps1

0 30 60 90 120

0

0.5

1.

1.5

ŸŸ

Ÿ

Ÿ

Ÿ Ÿ Ÿ

Ÿ Ÿ

ŸŸ Ÿ Ÿ

Cells are competent to respond to a second shock.

0 30 60 90 120

0

0.5

1.

1.5

mR

NA

, rel

ativ

e

60 min

30 min15 minSingle

Time/min

Time/min

mR

NA

, rel

ativ

e

Repeated osmostress

60 min

30 min15 minSingle

x

x

x

x

Klipp et al.,Nature Biotechn, 2005

Page 49: Humboldt- Universität zu Berlin Edda Klipp Systembiologie 9 – Signal Transduction Sommersemester 2010 Humboldt-Universität zu Berlin Institut für Biologie

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0 20 40 60 80 100 1200

0.1

0.2

0.3

0.4

0.5

Osmotic stress response: What is the impact of specific components over time ?

Ypd1

High osmolarity

Ssk1

Sln1

Ssk2

Pbs2

Hog1 mRNA

Protein

Glycerol

Turgor Fps1

l

i

i

lSp p

tS

tS

pR i

l

Responsecoefficients

0 20 40 60 80 100 1200

2

4

6

8

0 20 40 60 80 100 120

0.4

0.3

0.2

0.1

0

Time-dependent Response CoefficientsRelated to Glycerol Concentration

Closure of Fps1

Inhibition of Sln1

Strength of osmoshockHog1 nuclear import

Ssk1 dephosphorylation

Glycerol export

mRNA degradation

Hog1 dephosphorylation

Hog1 nuclear export

Sln1 phosphorylation

Hog1 phosphorylation

Glycerol influx

mRNA and protein production

Time / min

Time / minTime / min

0 20 40 60 80 100 1200

100

200

300

400

500

600

Time / min

Glycerolconcentration

Ingalls & Sauro, JTB, 2003

Page 50: Humboldt- Universität zu Berlin Edda Klipp Systembiologie 9 – Signal Transduction Sommersemester 2010 Humboldt-Universität zu Berlin Institut für Biologie

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Signaling Pathways in Yeast

Page 51: Humboldt- Universität zu Berlin Edda Klipp Systembiologie 9 – Signal Transduction Sommersemester 2010 Humboldt-Universität zu Berlin Institut für Biologie

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Model Selection: Sho branch I

Page 52: Humboldt- Universität zu Berlin Edda Klipp Systembiologie 9 – Signal Transduction Sommersemester 2010 Humboldt-Universität zu Berlin Institut für Biologie

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Model Selection: Sho branch II

Different architectures – which one explains data best?

Page 53: Humboldt- Universität zu Berlin Edda Klipp Systembiologie 9 – Signal Transduction Sommersemester 2010 Humboldt-Universität zu Berlin Institut für Biologie

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Model Selection: Sho branch III

Page 54: Humboldt- Universität zu Berlin Edda Klipp Systembiologie 9 – Signal Transduction Sommersemester 2010 Humboldt-Universität zu Berlin Institut für Biologie

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Model Size – Skeleton Model

Ypd1

High osmolarity

Ssk1

Sln1

Ssk2

Pbs2

Hog1 mRNA

Protein

Glycerol

Turgor Fps1

MA

PK

casc

adeP

hosp

hore

lay

Gene regulation

Metabolism

Hog1P2

Osmolarityex

mRNA

Turgor Glycerol

Fps1

Page 55: Humboldt- Universität zu Berlin Edda Klipp Systembiologie 9 – Signal Transduction Sommersemester 2010 Humboldt-Universität zu Berlin Institut für Biologie

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Oscillatory Input – Oscillatory Output

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Oscillatory Input – oscillatory output

x – intracellular osmotic pressurey – nuclear Hog1

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Oscillatory Input – oscillatory output

x – intracellular osmotic pressurey – nuclear Hog1

3 0 3 5 4 0 4 5 5 0

1 .3

1 .4

1 .5

1 .6

1 .7

Page 58: Humboldt- Universität zu Berlin Edda Klipp Systembiologie 9 – Signal Transduction Sommersemester 2010 Humboldt-Universität zu Berlin Institut für Biologie

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Simplified, yet Comprehensive Model of Osmotic Stress Response

Zi et al., PLoS ONE, 2010

Data from Mettetal et al., Science, 2008

Page 59: Humboldt- Universität zu Berlin Edda Klipp Systembiologie 9 – Signal Transduction Sommersemester 2010 Humboldt-Universität zu Berlin Institut für Biologie

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Signal Response Gain

Page 60: Humboldt- Universität zu Berlin Edda Klipp Systembiologie 9 – Signal Transduction Sommersemester 2010 Humboldt-Universität zu Berlin Institut für Biologie

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Glycerol Accumulation Depends on Stress and Nutritional Conditions

Glycerolt 21

2 0 4 0 6 0 8 0 1 0 0 1 2 0 1 4 0

8 0 0 0 0 0

1 . 0 1 0 6

1 . 2 1 0 6

1 . 4 1 0 6

1 . 6 1 0 6

2 0 4 0 6 0 8 0 1 0 0

1 . 0 1 0 6

1 . 5 1 0 6

2 . 0 1 0 6

2 . 5 1 0 6

5 0 0 0 1 0 0 0 0 1 5 0 0 0

4 0

5 0

6 0

0 . 1 0 . 2 0 . 3 0 . 4

2 5

3 0

3 5

4 0

4 5

5 0

Gly

cero

l

Gly

cero

l

Time Time

stress Glucose

Glycerolt 21

stress Glucose

More stress, stronger response

More stress, slower response

More glucose, stronger response

More glucose, faster response

Page 61: Humboldt- Universität zu Berlin Edda Klipp Systembiologie 9 – Signal Transduction Sommersemester 2010 Humboldt-Universität zu Berlin Institut für Biologie

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Flows Influencing Glycerol

2 0 4 0 6 0 8 0 1 0 0 1 2 0 1 4 0

5 0 0 0

1 0 0 0 0

1 5 0 0 0

Gly

cero

lflux

Time

Total Production

Transcriptionally regulated

Export

Volume-regulated

Net Production

Page 62: Humboldt- Universität zu Berlin Edda Klipp Systembiologie 9 – Signal Transduction Sommersemester 2010 Humboldt-Universität zu Berlin Institut für Biologie

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Systembiologie

Systemische Betrachtung von biologischen Sachverhalten und Prozessen

Zusammenspiel von Experiment und Theorie – „iterative cycle“

Häufig: Erzeugung, Analyse und Interpretation großer Datenmengen

Immer öfter: gezielte Erhebung von Daten zur Modellierung

Modellierung: - verschiedene Modellierungsansätze haben ihre

Stärken undSchwächen- ein Sachverhalt kann mit unterschiedlichen

Modellen beschrieben werden- kein sinnvolles Modell ohne sinnvolle Fragestellung

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Signal-Motive

RSfdt

dR, S – Signal, R – Response

S

R RkSkkdt

dR210

Kinetik

linear

RK

RV

SK

SV

dt

dR

mm

2

2

1

1

Michaelis-Menten

Steady State

2

10

k

SkkR ss

1212

21

VVSKV

SKVR

m

mss

Response

linear

hyperbolic

1 2 3 4 5

1

2

3

4

5

Signal S (arbitrary units)

Re

spo

nse

R (

arb

itra

ry u

nits

)

sigmoid

hyperbolic

linear

Vgl.: Tyson, Chen & Novak, Current Op. Cell Biology, 2003

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Signal-Motive

RSfdt

dR, S – Signal, R – Response

Kinetik

linear

Michaelis-Menten

Steady State Response

hyperbolic

1 2 3 4 5

1

2

3

4

5

Signal S (arbitrary units)

Re

spo

nse

R (

arb

itra

ry u

nits

)

sigmoid

hyperbolic

linear

S

RR0

RkRRSkdt

dRtotal 21

totalRRR 0

Skk

SkRR totalss

12

1

RK

Rk

RRK

RRSk

dt

dR

mtm

t

2

2

1

1

totalRRR 0

total

m

total

m

totalss

R

K

R

KkSkG

RR

2121 ,,,

sigmoid

One loop

uKuvuKvJuvuKvJuv

uKKJvuG

4

22

,,,

Goldbeter-Koshland-Funktion

Vgl.: Tyson, Chen & Novak, Current Op. Cell Biology, 2003

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Signal-Motive

RSfdt

dR, S – Signal, R – Response

Kinetik

linear

Steady State Response

1 2 3 4 5

1

2

3

4

5

Signal S (arbitrary units)

Re

spo

nse

R (

arb

itra

ry u

nits

)

sigmoid

hyperbolic

linear

sigmoid

S

R1R0 R

Two loops

RkSRkdt

dR413

RkRSkkSRkdt

dR413201

1

totalRRRR 10

2314142

231

SkkSkkkk

SkkRR totalss

Vgl.: Tyson, Chen & Novak, Current Op. Cell Biology, 2003

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Signal-Motive

RSfdt

dR, S – Signal, R – Response

Perfect adaptation

Vgl.: Tyson, Chen & Novak, Current Op. Cell Biology, 2003

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Signal-Motive

RSfdt

dR, S – Signal, R – Response

Mutual activation

Vgl.: Tyson, Chen & Novak, Current Op. Cell Biology, 2003

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Signal-Motive

RSfdt

dR, S – Signal, R – Response

Mutual inhibition

Vgl.: Tyson, Chen & Novak, Current Op. Cell Biology, 2003

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Signal-Motive

RSfdt

dR, S – Signal, R – Response

Negative feedback: homeostasis

Vgl.: Tyson, Chen & Novak, Current Op. Cell Biology, 2003

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Signal-Motive

RSfdt

dR, S – Signal, R – Response

Negative feedback: oscillations

Vgl.: Tyson, Chen & Novak, Current Op. Cell Biology, 2003

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Signal-Motive

RSfdt

dR, S – Signal, R – Response

Activator – Inhibitor

Vgl.: Tyson, Chen & Novak, Current Op. Cell Biology, 2003

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Signal-Motive

RSfdt

dR, S – Signal, R – Response

Substrate-depletion oscillator

Vgl.: Tyson, Chen & Novak, Current Op. Cell Biology, 2003