The Dynamics of Intracellular Ca2+

Signals

Jianwei Shuai (帅建伟 )

Department of PhysicsXiamen University

Outline

• Introduction

• IP3R Ca2+ channel model

• Ca2+ blips with single IP3R Ca2+ channel

• Ca2+ puffs with clustered Ca2+ channels

• Ca2+ waves at the global cell level

• Summary

Fixed Ca2+ via Moving Ca2+

Moving Calcium Ions

In-between:• Brain memory• Ca2+-related diseases: Cancer, Alzheimer’s • Communication between cells,• Communication among different organelles within a cell

Life beginning

Life ending

A life and death signal in cells

SpermCa2+

OscillationCell

DivisionEgg

CellDeath

HighCalcium

Concentration

protein-digesting enzymes

Cell Structure

Ca2+ Release Dynamics

Cell Membrane

Pump ER

IP3 Cytosol

IP3RPump

M 1.0]Ca[ Rest

[Ca]Local>10M

ChannelJ

ER

CytosolCaD

Membrane

Ca2+-induced Ca2+ release propagates Ca2+ waves

Low [Ca] opens the IP3R channels: fast binding;

High [Ca] inhibits the IP3R channels: slow binding.

How does Ca2+ act as a cellular signal?

Cellular information is encoded by the spatiotemporal Ca2+ patterns

(e.g. frequency and amplitude of oscillation).

Ca2+ Concentration

Ca2+ Oscillation

SpatiotemporalCa2+ wave

Ca2+ Signal

Ca2+ concepts

Technique to Visualize Cytosolic Ca2+

Green light

Blue light Blue light

Blue light

CalciumFluorescence

dye

Ca2+ spreading wave

Ian Parker, UC Irvine

Ca2+ spiral wave

Lechleiter, Girard, Peralta and Clapham, Science, 1991

Fine structure underlying Ca2+ waves

Marchant & Parker, EMBO J. 1999

Ca2+ waves consist of puffs

puff

Ca2+ waves at higher [IP3] Local Ca2+ puffs at low [IP3]

Marchant & Parker, EMBO J. 1999

Puff is triggered by blip

Temporal Profile

Heather, Dargan, Shuai and Parker, Biophys J. 2006

Blip

Puff

Multi-scale Ca2+ Signals

Single IP3R Channel Model

The IP3R channel model

Three independent and equivalent subunits.

DeYoung & Keizer, PNAS 1992

The open subunit is

101

111

100

010

000

011

001

Activa

tion C

a2+

IP3

Inhibitory Ca2+

b61

b62

b52

b41

b32

b21

b11

b51

b42

b31

b22

b12

a61

c

a52

c

a51

c

a42

c

a41

c

a31

p

a32

p

a21

c

a12

p

a62

c

a22

c

a11

p

110

has 8 states: Each subunit IP3 +Ca

-Ca

IP3 +Ca

110122

2251

010312111221002

51110

)]Ca[(

]IP[]Ca[

xbab

xaxbxadt

dx

Channel is open when 3 subunits are open

3110

Total

Open )(xN

N

Tetrameric Structure of IP3R

Hamada, et al, JBC 2003

IP3R model with 4 Subunits

Open Channel

Each channel has four independent and equivalent subunits.

3 activesubunits

4 activesubunits

IP3

0.01 0.1 1 10 100 10000.0

0.2

0.4

0.6

0.8

1.0

Mak Experiment IP3 = 0.01 M (2003) IP3 = 0.02 M (2003) IP3 = 0.033 M (2003) IP3 = 0.033 M (1998) IP3 = 10.0 M (2003)

[IP3]=10.0 M

0.033

0.02

0.01

Op

en

pro

ba

bili

ty

Ca2+ (M)

The IP3R model with conformational change

Active01100Active Xbxadt

dX

1100Active0

110152

21002

5111201031110 )]Ca[(]Ca[]IP[

xaXb

xbbaxaxbxadt

dx

)1(4 Active3Active

4ActiveOpen XXXP

Shuai, et al, Biophys J. 2007

Ca2+ Blips

with Single IP3R Channel

Model Design

6m

6m

6m

Free Ca2+

Immobile Buffer

Mobile Buffer

])MobCa[[Mob](]Ca[]MobCa[

])ImmCa[[Imm](]Ca[]ImmCa[ )0,,( ]Ca[]Ca[

T2

MM

T2

SSCh22

Ca

2

JzyxDt

]MobCa[])MobCa[[Mob](]Ca[

]MobCa[]MobCa[

MT2

M

2MobCa

Dt ]ImmCa[])ImmCa[[Imm](]Ca[

]ImmCa[ST

2S

t

Markovian simulation of channel dynamics

Stochastic binding/unbinding dynamics:

101

111

100

010

000

011

001

IP3

Inhibitory Ca2+

a2[Ca]dta5[Ca]dt

b1dt

110

b1dta2[Ca]dt a5[Ca]dt

IP3

100

IP3 -Ca

101

IP3 +Ca

110 000

0 1

RandomNumber?

Shuai & Jung, Biophys J 2002

[Ca2+] distribution around the channel mouth

15nm

[Ca2+]~400M [Ca2+]~20M

ER

Cytosol

1

10

100

500

5 5 15 100015100

20M

400M

[Ca2

+] M

Effects of Ca2+ Buffers

0.1 1 10 100 1000 100000.0

0.2

0.4

0.6

PO

[Ca2+ Buffer] (M)

C0

3

6

9

O

(ms)

1

10

100

C (

ms)

A

B

BAPTA EGTA Immobile

Shuai, et al, Biophys J. 2008

Slower Decay of [Ca2+]due to Immobile Buffer

0.1

110

[Immobile] = 800 M

100

[Ca2

+] M

Time (ms)

[EGTA] = 0 M

100010000100

0 10 20 30 40 50

0.1

110

[Immobile] = 800 M

1

100

Time (ms)

[BAPTA] = 0 M

1001000

10

0 10 20 30 40 50

Faster Decay of [Ca2+]with Mobile Buffer

Ca2+ Puffs

with Clustered IP3R channels

Puff Model

6m

6m

6m

L : Cluster widthN : Total number of open channels during a puff

L

Free Ca2+

Immobile Buffer

EGTA

Fluo4 Dextran

])CaEG[[EG](]Ca[]CaEG[])FlCa[[Fl](]Ca[]FlCa[

])ImCa[[Im](]Ca[]ImCa[ )0,,( ]Ca[]Ca[

T2

EET2

FF

T2

ImImCh22

Ca

2

JzyxDt

]FluoCa[])FluoCa[[Fluo](]Ca[

]FluoCa[]FluoCa[

FT2

F

2FluoCa

Dt ]StatCa[])StatCa[[Stat](]FreeCa[

]StatCa[STS

t

A Cluster of 9 IP3Rs

Effects of Immobile Buffers

Effects of Fast Mobile Buffer

[BAPTA] M

[Ca2+] in the Cluster

Time (ms)

Modified [Ca2+] by BAPTA

[BAPTA] M

0.01 0.1 1 10 100 10000.0

0.2

0.4

0.6

0.8

1.0

Mak Experiment IP3 = 0.01 M (2003) IP3 = 0.02 M (2003) IP3 = 0.033 M (2003) IP3 = 0.033 M (1998) IP3 = 10.0 M (2003)

[IP3]=10.0 M

0.033

0.02

0.01

Ope

n pr

obab

ility

Ca2+ (M)

Ruediger, Shuai, et al, Submitted

Conclusion 1Ca2+ Buffers function differently at single and clustered channel levels.

• The open probability for a single IP3R:– increases with increasing immobile buffer– has little change with the mobile buffer

• The open probability for a clustered IP3Rs:– has little change with the immobile buffer– shows a biphasic mode with the increase of

fast mobile buffer (BAPTA).

Ca2+ Waves

at Global Cell Level

ClusterJ

ER

Cytosol

PumpJ

CaD

Ca2+ wave model

])MobC[[Mob](]Ca[]MobCa[

])StatCa[[Stat](]Ca[]StatCa[ )0,,( ]Ca[]Ca[

T2

MM

T2

SSCluster22

Ca

2

JzyxDt

]StatCa[])StatCa[[Stat](]FreeCa[]StatCa[

STS

t

]MobCa[])MobCa[[Mob](]Ca[]MobCa[]MobCa[

MT2

M2

MobCa

Dt

Free Ca2+Stationary Buffer

Mobile Buffer Channel cluster

m 60

y

x

A stochastic Ca2+ model with clustered channels

Cluster distance 3 mEach cluster 36 channels

With low [IP3] stimulus

?

[IP3]

[Ca2+]

Total channels: 14,400

m 60m 60 Cell size:

What will happen if we change cluster distributions?

Cluster distance 0.5 m Each cluster 1 channel

Cluster distance 3 m Each cluster 36 channels

Cluster distance 5 mEach cluster 100 channels

Fixed !!!

No wave with low [IP3]at small cluster distance

0 500 1000 1500 20000.0

0.1

0.2

0.3

Ca2+

(M)

Time (sec)

0.0

0.1

0.2

0.3

Averaged calcium

Calcium at center cluster

M25.0[IP3]

Cluster distance 0.5 m Each cluster 1 channel

No wave with low [IP3]at large cluster distance

0 500 1000 1500 20000.0

0.1

0.2

0.3

Ca2+

(M)

Time (sec)

0.0

0.1

0.2

0.3

Averaged calcium

Calcium at center cluster

M25.0[IP3]

Cluster distance 5 mEach cluster 100 channels

At middle cluster distance Ca2+ waves generated with low [IP3]

M25.0[IP3] 0 500 1000 1500 20000.0

0.1

0.2

0.3

Ca2+

(M)

Time (sec)

0.0

0.1

0.2

0.3

Averaged calcium

Calcium at center cluster

Cluster distance 3 m Each cluster 36 channels

Noise-induced Ca2+ waves

From Stochasticity To Periodicity at biologically realistic cluster distribution

Shuai and Jung, PNAS 2003

0

2 )( dtT

Characteristic time of self-correlation

211

2

11

1111

)()(

)()()(

xtxxtx

xtxxtx

Channel number per Cluster1 4 9 16 25 36 64 100

1 2 3 4 50

5

10

15

2.51.50.5

DCa

=20 m2/secIP

3=0.21 M

Cluster Distance (m)

T

With high [IP3] stimulus

?

[IP3]

[Ca2+]

Puff-induced Ca2+ waves

Bifurcation of calcium signal

Channel noise only

Channel noise only

Channel noise

+IP3 noise

Interaction of channel noise and IP3 noise

Liao, Jung, Shuai, PRE (2009)

Restoration of Periodicity by Noise Suppressing Noise

Conclusion 2The novel roles of molecular noise in Ca2+ system

• At resting state with low [IP3] concentration:– The channel noise with clustered IP3Rs can

generate the periodic Ca2+ waves

• At oscillatory state with high [IP3]:– The channel noise will destroy the periodic Ca2+

oscillation– The additional IP3 noise with certain strength

can partly restore the periodicity of Ca2+ signals.

Summary

University of California, Irvine Prof. Ian Parker

Ohio University Prof. Peter Jung

Thanks

Los Alamos National Lab John E. Pearson

University of Pennsylvania

Prof. J. Kevin Foskett

Dr. Don-On Daniel Mak

Humboldt-Univeristy at Berlin Dr. Sten Ruediger

NSF China (2008-2010)NIH USA (2009-2012)