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Complex networks are found throughout biology
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Can we define the basic building blocks of networks?
Generalize the notion of MOTIFS, widely used in sequence analysis, to the level of networks.
Sequence motif: a sequence that appears much more frequently than in randomized sequences.
‘Network motif’: a pattern that appear much more frequently than in randomized networks.
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Database of direct transcription interactions in E. coli
X Y Z
Transcription factors
operons
X
Y
Z
Directed graph
424 nodes, 519 interactionsBased on selected data from RegulonDB + 100 interactions from literature search
Shen-Orr 2002, Thieffry Collado-Vides 1998
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Algorithm that finds n-node network motifs
Find all n-node circuits in real graphN
T
Y
U
X
Z
W M
X
ZY
X
ZY
X
ZY
Examples of 3-node circuits
And in a set of randomized graphs with the same distribution
of incoming and outgoing arrows.
Assign P-value probability of occurring more at random than
in the real graphRandomization: Newman, 2000, Sneppen& Malsov 2002
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The thirteen 3-node connected subgraphs
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Two main types of feed-forward loops are found
X
Y
Z
X
Y
Z
Coherent Incoherent
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Dynamics of the feed-forward loop system
Mangan, PNAS, JMB, 2003
X(t) = time varying input
dY / dt = F(X) – a Y
dZ / dt = F(X) F(Y) – b Z
F
Threshold
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The feed-forward loop is a filter for transient signals allowing fast
shutdown
Mangan, PNAS, JMB, 2003
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GFP Reporter plasmid system for promoter activity
Lutz, Bujard 1997Zaslaver et al, Nat. Meth. 2006
Low copy plasmidFast folding GFPNontoxic
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Plasmid with promoter for gene Xcontrolling a reporter
Construct strains, each reporting for a different promoter
High throughput cloning:Promoter PCR, restriction, ligation, preps all in 96-well format.
Gene X intact on chromosome
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Construct strains, each reporting for a different promoter
Grow strains under same conditions andmeasure reporter fluorescence or luminescence
Commercial fluorimeter/luminometershakes, temperature control, injectors.Measure at the same time cell optical density.
Each well reportsfor a different promoter
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0 100 200 300 400 500 600 700
104
105
106
minimal + aa LB minimal - aa arabinose 0.5mM
Activity of 96 promoters across 20 h growth in 20 conditionsG
FP
/OD
0 500 1000 1500 2000 2500 3000 3500 4000 4500
104
105
106
7 min resolution
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*2
*1.1
*0.9
*0.5
GFP repeat 1
GF
P r
epea
t 2Day-day reproducibility of better than 10%
10%2-fold
2000 strainsavailable
Open BioSystems
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Maximal response to a pulse of X is filtered by FFL
Simulation
X
ZX
Y
Z
Input pulse to X of duration T T
Response
Pulse duration T
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Sign-sensitive filtering by arabinose feed-forward loop
Max response
crp
lacZ
crp
araC
araB
cAMP Pulse duration [min]Experiments: Mangan et al , JMB (2003).
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OFF pulse
Feed-forward loop is a sign-sensitive filterFeed-forward loop is a sign-sensitive filter
Mangan et al JMB 2003
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Shen-Orr, et al Nature genetics 2002
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The single-input module can generate a temporal program of gene expression
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Flagella operons are activated in temporal order
Kalir, Leibler, Surette, Alon Science 2001Laub, McAdams, Shapiro Science 2000
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Temporal order matches position of proteinsalong the flagella motor
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Turn ON (arg removed) Turn OFF (arg added)
Time [min] Time
Temporal order in Arginine biosynthesis system with minutes between genes
Zaslaver, Surette, Alon,
Nature Genetics 2004
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Turn ON (arg removed) Turn OFF (arg added)
Time [min] Time
Glutamate
N-Ac-Glutamate
N-Ac-glutamyl-p
N-Ac-Ornithine
N-Ac-glutamyl-SA
Citrulline
Arginine
Temporal order matches enzyme position in the pathway
Klipp, Heinrich
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199 4-node directed connected subgraphs199 4-node directed connected subgraphs
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4-node motifs in E. coli network: overlapping regulation
X
Z
X
Y
Z1
Y
W Z2
Overlapping regulation Feed-forward loop
with two output genes
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Hengge-Aronis
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Mapping Logic gates using GFP reporter arrays (LacZ)
LacZIPTG
cAMP
ANDGATE?
Setty, Mayo, Surette, Alon, PNAS 2003
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Can we draw complex networks in an understandable way?
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E. coli and yeast transcriptional networks show the same motifs
X
Z
Y
W
X
Y
Z1 Z2
The same network motifs characterize transcriptional regulation in a eukaryote and a prokaryote
The same 4-node motifs
Also SIMS and DORs
X
Y
Z
Feed-forward loop: coli 40, yeast 74, over 10 STDs from random networks! Same two types of FFLs.
Milo et al 2002, Lee at al 2002
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The incoherent FFL can act as a pulse generator
X
Y
Z
IncoherentType 1FFL
Z
t
Mangan et al, 2006Basu et al, 2004
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X1
Y1
Z1
AND
AND
X2
Y2
Z2
AND
AND
Z3
R. Losick et al. , PLOS 2004
Developmental transcription network made of feed-forward loops: B. subtilis sporulation
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X1
Y1
Z1
AND
AND
X2
Y2
Z2
AND
AND
Z3
0 1 2 3 4 5 6 7 8 9 100
0.2
0.4
0.6
0.8
1 Z1 Z2 Z3
time
Z
Feed-forward loops drive temporal patternof pulses of expression
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Negative feedback loop with one transcription arm and one protein arm is a common
network motif across organisms
x
y
HSF1 HIF
iNOShsp70hsp90
NFB
IB
p53
Mdm2
Mammals
dnaKdnaJ
H Ime1
Ime2
smo
Ptc
Bacteria Yeast Fruit-Flies
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Negative feedback in engineering uses fast control on
slow devices.
Heater
Thermostat
Powersupply
Temperature
slow
fastEngineers tune the feedback parameters to obtain rapid
and stable temperature control
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Negative Feedback can show over-damping, damped or un-damped oscillations, depending on parameters
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Negative Feedback can show over-damping, damped or un-damped oscillations, depending on parameters
Engineers usually prefer damped oscillations-fast response, not too much overshoot
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Negative Feedback can show over-damping, damped or un-damped oscillations, depending on parameters
Engineers usually try to avoid parameters that give Undamped oscillations
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real-time proteomics in single living cells for p53-mdm2 dynamics
pMT-I p53 CFP 0.2Kb 1.2Kb 0.7Kb
Hygro
pMdm2 Mdm2 YFP 3.5Kb 15Kb 0.7Kb
Neo
P53-CFP
Mdm2-YFP
p53-CFP and Mdm2-YFP fusion protein allow imaging of p53 and MDM2 protein in living cells G. Lahav
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Food webs represent predatory interactions between species
Skipwith pond (25 nodes), primarily invertebratesLittle Rock Lake (92 nodes), pelagic and benthic species Bridge Brook Lake (25 nodes), pelagic lake species Chesapeake Bay (31 nodes), emphasizing larger fishesYthan Estuary (78 nodes) birds, fishes, invertebratesCoachella Valley (29 nodes), diverse desert taxa St. Martin Island (42 nodes), lizards Source: Williams & Martinez, 2000
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Foodwebs have“consensus motifs”
• Consensus motifs – different from transcription networks
• Feedforward is not motif - omnivores are under-represented
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Links between WWW Pages – a completely different set of motifs is found
• WebPages are nodes and Links are directed edges
• 3 node results
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Full reverse engineering of electronic circuit from transistor to module level
Each node represents a transistor
Each node represents a transistor motif:Logic gate
Each node represents a gate motif:D-flipflop
Each node represents a gate-flipflop motif:counter
Itzkovitz 2004
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Map of synaptic connections between C. elegans neurons
White, Brenner, 1986
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FLP
AVD
AVA
Nose touch
Backward movement
Feedforward loops in C. elegans avoidance reflex circuit
ASH Sensory neurons
Interneurons
Thomas & Lockery 1999
Noxious chemicals, nose touch
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Networks can be grouped to super-families based on the significance profile
Milo et al Science 2004
NormalizedZ-score
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Summary –network motifs
Network motifs, significant patterns in networks
Three motifs in transcription networksand their functions
High-accuracy promoter activity measurements from living cells
algorithms at www.weizmann.ac.il/mcb/UriAlonReview: Nat. Rev. Gen. 2007
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Acknowledgments
Alex SigalNaama GevaGalit LahavNitzan RosenfeldShiraz Kalir
Weizmann Institute, Israel
M. Elowitz, CaltechS. Leibler, RockefellerM.G. Surette, CalgaryH. Margalit, Jerusalem
Ron MiloAdi NatanShmoolik MangamShalev ItzkovitzNadav Kashtan
Alon ZaslaverErez DekelAvi MayoYaki Setty
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Dynamics of the p53-mdm2 loop in single living
cells, and the design principles
of biological feedback
Galit Lahav Uri Alon
Weizmann InstituteIsrael
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overview• Introduction- negative feedback loop
motif
•System for real time proteomics of p53-mdm2 in living human cells
•Dynamics of p53-mdm2 at the single cell level
•Design principles of biological feedback
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Negative feedback loop with one transcription arm and one protein arm is a common
network motif across organisms
x
y
HSF1 HIF
iNOShsp70hsp90
NFB
IB
p53
Mdm2
Mammals
dnaKdnaJ
H Ime1
Ime2
smo
Ptc
Bacteria Yeast Fruit-Flies
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Negative feedback in engineering uses fast control on
slow devices.
Heater
Thermostat
Powersupply
Temperature
slow
fastEngineers tune the feedback parameters to obtain rapid
and stable temperature control
![Page 54: Complex networks are found throughout biology. Can we define the basic building blocks of networks? Generalize the notion of MOTIFS, widely used in sequence](https://reader035.vdocuments.site/reader035/viewer/2022070401/56649f185503460f94c2f48e/html5/thumbnails/54.jpg)
Negative Feedback can show over-damping, damped or un-damped oscillations, depending on parameters
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Negative Feedback can show over-damping, damped or un-damped oscillations, depending on parameters
Engineers usually prefer damped oscillations-fast response, not too much overshoot
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Negative Feedback can show over-damping, damped or un-damped oscillations, depending on parameters
Engineers usually try to avoid parameters that give Undamped oscillations
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What about biological feedback control?
Kohn, Mol Biol Cell, 1999 Our model system- perhaps the best studied example in mammals, p53-mdm2 negative feedback loop
P53-CFP
Mdm2-YFP
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Is the damage repairable?
Apoptosis
no
Cell cycle arrestG1/S G2/M
One cell death =
Protection of the whole organism
yes
DNA repair
Stress signals p53 MDM2
The p53 Network
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Damped oscillations in p53-mdm2 and
NFB-IB negative feedback loops
Hoffman et al, Science, 2002
Measurements on populations!
Lev Bar-Or et al, PNAS, 2000
western
p53-mdm2
NFB-IB Damped oscillations
Electro Mobility Gel-Shift Assay
p53
MDM2
westernHrs after 0 1 2 3 4 5 6 7 8
p53 mdm2
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System for real-time proteomics in single living cells for p53-mdm2 kinetics.
pMT-I p53 CFP 0.2Kb 1.2Kb 0.7Kb
Hygro
pMdm2 Mdm2 YFP 3.5Kb 15Kb 0.7Kb
Neo
P53-CFP
Mdm2-YFP
p53-CFP and Mdm2-YFP fusion protein allow imaging of p53 and MDM2 protein in living cells
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p53-CFP shows damped oscillations in western following DNA damage
similar to endogenous p53.
p53-CFP
p53
0 ½1 2 3 4 5 6 7 8 9 Hours after
0
10
20
30
40
50
60
70
80
90
100
0 2 4 6 8 10
p53
p53-CFP
Mcf7 p53+/+
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Mdm2-YFP kinetics are similar to endogenous
Mdm2.
Mdm2-YFPMdm2
0 ½1 2 3 4 5 6 7 8 9 Hours after Irradiation
0
20
40
60
80
100
120
0 2 4 6 8 10
Mdm2
Mdm2-YFP
Mcf7 p53+/+ Mdm2+/+
Mdm2-YFP appears to undergo the same decreaseas endogenous mdm2 at early times
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p53-CFP and Mdm2-YFP expression after DNA damage in living human cells.
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Different behavior of individual cells following DNA damage
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Different behavior of individual cells following DNA damage
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Different behavior of individual cells following DNA damage
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Different behavior of individual cells following DNA damage
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Different behavior of individual cells following DNA damage
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Two groups of behavior: one peak and two peaks, with small
variations inside each group
Peak Width=350±60min (SD)1st Peak Width=360±50min (SD)
Ym
ax1
Ym
ax2
Ymax2/Ymax1=1.1±0.2 (SD)
T(Ymax2)-T(Ymax1)=370±50min (SD)
2nd Peak Width=340±40min (SD)
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Average of single cell data is similar to Western: damped oscillations are an artifact of mixing two behavior
classes
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The irradiation level determines the distribution of
cells undergoing 0,1 or 2 oscillations
2.5Gy
Numbers of pulses0 1 2+
%of
cells
100
80
60
40
20
0
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The irradiation level determines the distribution of
cells undergoing 0,1 or 2 oscillations
2.5Gy
10Gy
Numbers of pulses0 1 2+
%of
cells
100
80
60
40
20
0
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The irradiation level determines the distribution of
cells undergoing 0,1 or 2 oscillations
2.5Gy
0.3Gy
Numbers of pulses0 1 2+
%of
cells
100
80
60
40
20
0
10Gy
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The irradiation level determines the distribution of
cells undergoing 0,1 or 2 oscillations
5Gy
10Gy
2.5Gy
0.3Gy
0Gy
Numbers of pulses0 1 2+
%of
cells
100
80
60
40
20
0
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Mean pulse widths do not depend on DNA damage level
0.3Gy 2.5Gy 5Gy 10Gy
First pulse width
2.5Gy 5Gy 10Gy
Second pulse width
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Mean pulse height does not depend on DNA damage level
0.3Gy 2.5Gy 5Gy 10Gy
First pulse height
2.5Gy 5Gy 10Gy
Second pulse height
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‘Digital behavior’ in the p53-mdm2 feedback loop
Number of cells with multiple pulses, not the size/shape of the pulse, increases with damage.
Analog design
Digital design
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tStyaDDdt
tdS
tyαtydt
tdy
txβtydt
tdy
txtyαtxSSdt
tdx
βtxtyαtxSSdt
tdx
ss
yy
yy
x
20
0
00
20
10
*
**
Show limit cycle figure
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Individual cells show large amplitude variation
But peak timing is more precise
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What's next?
• What is the mechanism for the ‘digital behavior’ in the p53-Mdm2 loop?
• What about other negative feedback loops…do they also display ‘digital behavior’?
• Could different numbers of pulses convey different 'meanings' to the cell in terms of expression of downstream genes?
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The goal: dynamic proteomics in individual living human cells
• Protein concentration and location at high temporal-resolution and accuracy
• In individual living human cells
• For most of the expressed proteins
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Annotated library of cells each of whichExpressed a chromosomally YFP-tagged protein
+automated microscopy and image-analysis
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Exon tagging a gene with a fluorescent protein
exon1 exon2 exon3 exon4intron1 intron2
intron3
DNA
transcription
exon1 exon2 exon3RNASA SD SA SD SA SD SA SD
YFP puro
splicing
mRNA exon1exon2 YFP exon3 exon4
Proteintranslation
YFPN C
SA SDYFP puro
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clone
RACE stage
4c18 1d13 1d224d8 1e18 1f21
1 11111 2 22 2 22
Clone 1e18YFP
Clone 1e18
YFP
546
Added seqYFP AAAAAAAAAAExon n Exon n+1
472
Added seqAAAAAAAAAAExon n+1
A
C
B
Ribosomal protein L5
Tagged protein identified using RACE
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A wide variety of localization patterns
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0 min 10 min
20 min 30 min
Dynamic proteomics in individual cells
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Summary
• Network motifs and their biological function
• Digital pulses of p53
• Dynamic proteomics in individual living cells
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Acknowledgments
Galit Lahav
Alex SigalNaama GevaLior Ben-ArziNitzan RosenfeldShiraz KalirInbal Alaluf
Weizmann Institute, Israel
Zvi KamBenjamin GeigerMoshe OrenVarda Rotter
Stan Leibler, Rockefeller -coliMike Surette, Calgary -coliArnold Levine, IAS Princeton –p53Michael Elowitz, Caltech –p53
Ron MiloAdi NatanShmoolik MangamShalev ItzkovitzNadav KashtanIdo Zelman
Alon ZaslaverShai Shen-OrrErez DekelAvi MayoYaki Setty
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The heat-shock single-input-module
k1
1
k2
2
k3
3
n
kn
n
dnaKJ groEL htpG lond
32
SINGLE INPUT MODULE NETWORK MOTIF
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Heat shock promoters are activated after ethanol step, and then adapt
4% ethanolAdded at t=0 , Natan et al 2004
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Heat shock promoters are turned ON together and OFF in a temporal
order
Natan et al 2004
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Heat-shock promoters are turned OFF in temporal order
Normalized Promoter Activity
Time from ethanol shock [minutes]54 60 66 72 78 84 90 96
groEL
ftsJ
htpG
hslUV
htpX
Lon
clpB
clpP
dnaK 0
0.1
0.2
0.3
0.4
0.5
Temporal turn-off order ~3 minutes difference
Natan et al 2004
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Turn-off order matches severity of repair
Same principle found in SOS DNA repair [Ronen, Shraiman, Alon PNAS 2002]