Modeling signal transduction

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Modeling signal transduction
Phototransduction from frogs to flies
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Eye as an evolutionary challenge
To suppose that the eye, with all its inimitable
contrivances , could have been formed by natural
selection, seems, I freely confess, absurd in the
highest possible degree. Yet reason tells me,
C. Darwin, The Origin of Species
Darwin goes on to describe how eye may have
evolved through accumulation of gradual
improvements
A number of different designs exist e.g.
vertebrate, molluskan or jellyfish camera eyes
or insect compound eye
The eye may have evolved independently 20
times!! (read Cells, Embryos and Evolution by
GerhartKirschner)
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Eyes are present in most metazoan phyla how did
they evolve?
See Gerhart and Kirschener, Cells, Embryos and
Evolution
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The grand challenge
To understand the evolutionary processes that
underlie the appearance of a complex organ (an
eye).
To what extent is the similarity between
different eyes (e.g. vertebrate and mollusk) is
due to common ancestry or is the result of
evolutionary convergence due to physical
constraints?
What can we learn from the similarities and
differences in the architecture/anatomy,
development and molecular machinery of eyes (or
light sensitive cells) in different species?
BUT before we can address the question of
evolution we need first to learn how it works
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More broadly

• Molecular pathway(s) of phototransduction are
  similar to many other signaling pathways
• olfaction, taste, etc
• Comparative Systems Biology

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Modeling molecular mechanisms of
photo-transduction
Case studies 1) vertebrate and 2) insect
Phototransduction as a model signaling system
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Vertebrate Rods and Cones
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Vertebrate photoreceptor cell
Rod Outer Segment (2000 Discs)
hv
Rhodopsin
Na
Na, Ca2
Discs
Light reduces the dark current into the cell
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Intracellular Voltage in Rods and Cones
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Measuring currents
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Patch clamp
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Single Photon Response
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Patch clamp recordings
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Electrophysiology of Rods
Na, Ca
cGMP
Na, Ca
cGMP
Ca,K
Ca,K
Na
Na
Na
Na
K
K
K
K
K
K
K
K
K
ATP driven Na/K pump
Na,Ca channels of outer segment need cGMP to stay
open
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Light detector protein Rhodopsin
Rhodopsin undergoes light-induced
conformational change
chromophore, 11-cis retinal

opsin, a membrane protein with 7
transmembrane segments
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cis/trans retinal transition
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Light-induced conformational transition
cytoplasmic side
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Rhodopsin is a G-Protein coupled receptor
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Seven-Helix G-protein- Coupled Receptors form a
large class (5 C. elegans Genome !)
b2 adrenergic receptor
Rhodopsin
cytoplasmic end
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Rhodopsin is a G-Protein coupled receptor
light
Rhodopsin
about 109 rhodopsin molecules and about 108
G-protein molecules per rod outer segment (ROS)
Rh
Tabg
Ta Tbg
GDP
GTP
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G- proteins
a subunit 35-45 kD
g
b subunit 35-40 kD
g subunit 6-12 kD
guanine nucleotide binding site on a
subunit
At least 15 different genes for a subunit and
several different genes for b and g subunits
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Steps in activation
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(No Transcript)
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Effector
PDE
PDE
cGMP
GMP
CNG Channels OPEN CLOSED
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Where did cGMP come from?
Guanylate Cyclase
GTP
cGMP PPi
GMP
Phosphodiesterase
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G Protein Effectors Include
hydrolyzes cyclic nucleotide e.g.
cGMP GMP
Phosphodiesterase (PDE) Adenylyl
cyclase Phospholipase C
synthesizes cAMP from ATP
Enzymes
hydrolyzes PIP2 to produce IP3 and diacylglycerol
(DAG)
Ion channels
e.g. K, Ca and Na channels
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Shut-off
Next question How are the activated
intermediates shut off?
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Rhodopsin inactivation
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Transducin is inactivated by the a intrinsic
GTPase activity which hydrolyzes GTP to
GDP
a
GDP
Pi

Ta and bg re-associate
Accelerated by PDE
Ta-GDP dissociates from PDE which re-inhibits
PDE
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The intrinsic GTPase activity of the a
subunit is regulated by a GAP (GTPase
accelerating protein)
RGS-9
Ta shut off is accelerated by action of
RGS-9
Regulator of G-protein signaling
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Recovery to the resting state requires
resynthesis of the cGMP that had been lost to
hydrolysis.
This is accelerated by low Ca (feedback signal!)
that stimulates Guanylate Cyclase
GTP
cGMP PPi
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Ca- the second 2nd messenger
channel closure shuts off Ca influx, while
efflux by NaCa,K exchange continues and
internal Ca declines. The fall in Ca is the
Ca feedback signal.
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Negative feedback
Ca2 Regulation of Guanylate Cyclase
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Signaling cascade

• Converts a microscopic stimulus
• activation of a single molecule
• into a macroscopic response

Alberts et al, Mol Bio of the Cell
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Phototransduction Cascadeas an enzymatic
amplifier
light
Rhodopsin
Rh
1st Stage of amplification 200 - 1000 G
per Rh
Gabg - GDP
Ga- GTP Gbg
2nd Stage amplification each PDE hydrolyzes
100 cGMP molecules.
Phosphodiesterase (PDE)
PDE
GC
cGMP
GMP
GTP
channel closure generates electrical signal
CNG Channels OPEN CLOSED
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Olfaction
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Olfactory receptorcascade
Odor ligand
Olfactory receptor
R
R
Gabg - GDP
Ga- GTP Gbg
AC Adenylate cyclase
AC
cAMP
AMP
ATP
PDE
DEPOLARIZATION OF THE CELL
CNG Channels OPEN
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Invertebrate Phototransduction Cascade
Rhodopsin
light
Rh
Gqa- GTP Gqbg
Gq - GDP
Phospholipase C
PLC
PIP2
IP3 DAG
( phosphoinositol 3,4 bisphosphate )
?
Trp Channels CLOSED OPEN
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Enzymatic amplifier modules
GDP
G
1st stage G-protein (Transducin) activation and
deactivation
GTP
PDE
Rh
G
Pi
GDP
GTP
2nd stage cGMP hydrolysis and synthesis
Note GTP / GDP GMP acts a metabolic
power supply
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More examples of amp modules
GDP
ADP
G
SP
GTP
GAP
GEF
Phosphotase
Kinase
G
S
Pi
Pi
GDP
GTP
ATP
Small GTPases Ras, Rho, Rab, Rap, Reb,
Vasodilation
Receptor Guanylate Cyclase
Nitric Oxide
PDE5
Viagra
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General push-pull amplifier circuit
Xc
a
Power supply
Eact
Ede-act
ab
c
maintains high c/a
Xa
c
b
Steady state
Note X/X e-bDE because the system is
held out of equilibrium by fixed c/a
maintained by metabolism
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Amplifier gain and time constant
Small change in X induced by a small change in
Eact
Linear response (in the Fourier domain)
Static gain
Time constant
Note g t the gain-bandwidth theorem !!
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Linear analysis of vertebrate phototransduction
Rh deactivation 2 amplifier modules with
negative feedback via Ca
Good approximation to weak flash (single photon)
response
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Linear analysis of the cascade
Assuming stoichiometric processes of PDE and Ch
activation are fast
d PDE d G
d Ch d cGMP
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Hard and Soft parameters
Kinetic constants/affinities -- hard
parameters
change on evolutionary
time
scale Enzyme concentrations -- soft
parameters that
can be regulated by
the cell.
e.g.
Golden rule of biological networks anything
worth regulating is regulated
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General behavior

at short times
at times times
For
With n3 - good fit to single-photon response
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Case of feedback
gFdCa
feedback
via dCh
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Consequences of negative feedback
Reduction of static gain
Accelerated recovery
Ringing
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Signal and Noise How much gain is enough?
Single photon signal

dI 2 pA
dI /I Dark 3
I Dark 60 pA
Whats the dominant source of background noise?
Thermal fluctuations?
ROS capacitance C 20pF
Negligible !
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Reaction shot noise
Langevin noise (i.e. Gaussian, White)
of molecules
E.g. if G- 0 consider DX produced over
time Dt
Poisson process
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Channel opening noise
ChD lt Chgt tChg (cGMPD)ChTot
Channel flicker noise
Note this Poisson law holds generally for mass
action
lt 3 signal
Plus fluctuations of dcGMP
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cGMP fluctuations
Note voltage response is coherent over the
whole rod outer segment, hence must
consider the whole volume Vros 104mm3
cGMP cGMP Vros 10mM 104mm3 107
Negligible fluctuations
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Locality of single photon response
hv
cGMP depletion
Na, Ca2
100mm
G and PDE activity
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Single photon response variability
Baylor-Riecke coefficient of variation
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What is the largest source of response
variability?
Spontaneous activation G -gt G ?? lt 10-7
s-1 Negligible even with 108 G
molecules !
Variability of Rh on- time Dt ??
DG kDt
ltDtgt tRh 1st order Poisson process
Baylor Reicke measured
Poisson process of order 20 !!!
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Multistep deactivation of Rh
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Meta-Rhodopsin shut-off
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Summary

• What we have learned
• GPCR / cyclic nucleotide cascade
• Enzymatic amplifier module
• and linear response
• Noise analysis
• Tomorrow
• from frog to fly and from linear to
  non-linear

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Acknowledgements
Anirvan Sengupta, (Rutgers) Peter Detwiler (U.
Washington) Sharad Ramanathan (CGR/Lucent)