Complex networks are found throughout biology

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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
Transcription factors
Directed graph
X
Y
Z
operons
424 nodes, 519 interactions Based 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 graph

Examples of 3-node circuits
N
X
X
X
Y
Z
Y
Z
Y
U
X
Z
Z
Y
T
M
W
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 graph
Randomization Newman, 2000, Sneppen Malsov 2002
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The thirteen 3-node connected subgraphs
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Two types of feed-forward loops are significant
X
X
Y
Y
Z
Z
Incoherent
Coherent
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Dynamics of the feed-forward loop system
X(t) time varying input dY / dt F(X) a Y dZ
/ dt F(X) F(Y) b Z
F
Mangan, PNAS, JMB, 2003
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 1997 Kalir, Leibler, Surette, Alon,
Science 2001
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Construct strains, each reporting for a different
promoter
Plasmid with promoter for gene X controlling a
reporter
Gene X intact on chromosome
High throughput cloning Promoter PCR,
restriction, ligation, preps all in 96-well
format.
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Construct strains, each reporting for a different
promoter
Grow strains under same conditions and measure
reporter fluorescence or luminescence
Each well reports for a different promoter
Commercial fluorimeter/luminometer shakes,
temperature control, imjectors. Measure at the
same time cell optical density.
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Activity of 96 promoters across 20 h growth in 20
conditions
7 min resolution
GFP/OD
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Day-day reproducibility of better than 10
GFP repeat 2
2 1.1 0.9 0.5
10
2-fold
GFP repeat 1
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Maximal response to a pulse of X is filtered by
FFL
Input pulse to X of duration T
T
Response
X
Z
X
Y
Z
Simulation
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, Zaslaver, Alon, JMB (2003).
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Feedforward loop is a sign-sensitive filter
Vs.
lacZYA
araBAD
Mangan Zaslaver, Alon JMB 2003
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Shen-Orr, Milo, Mangan, Alon 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 2001 Laub,
McAdams, Shapiro Science 2000
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Temporal order matches position of proteins along
the flagella motor
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Temporal order in Arginine biosynthesis system
with minutes between genes
Zaslaver, Surette, Alon, Nature Genetics 2004
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Temporal order matches enzyme position in the
pathway
Glutamate
N-Ac-Glutamate
N-Ac-glutamyl-p
N-Ac-glutamyl-SA
N-Ac-Ornithine
Citrulline
Arginine
Klipp, Heinrich
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199 4-node directed connected subgraphs
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4-node motifs in E. coli network overlapping
regulation
X
X
Y
Y
Z
W
Z2
Z1
Overlapping regulation
Generalization of Feedforward loop to two
controlled genes
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Hengge-Aronis
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Mapping Logic gates using GFP reporter arrays
(LacZ)
IPTG
ANDGATE?
LacZ
cAMP
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
Feed-forward loop coli 40, yeast 74, over 10
STDs from random networks! Same two types out of
eight, coherent and incoherent FFL
The same 4-node motifs Also SIMS and DORs
The same network motifs characterize
transcriptional regulation in a eukaryote and a
prokaryote
Milo et al 2002, Lee at al 2002
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Developmental transcription network made of
feed-forward loops B. subtilis sporulation
X1
Y1
AND
AND
Z1
X2
Y2
AND
R. Losick et al. , PLOS 2004
AND
Z2
Z3
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Feed-forward loops drive temporal pattern of
pulses of expression
X1
Z
Z3
Z1
Z2
Y1
AND
AND
Z1
X2
time
Y2
AND
AND
Z2
Z3
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Food webs represent predatory interactions
between species

• Skipwith pond (25 nodes), primarily invertebrates
• Little Rock Lake (92 nodes), pelagic and benthic
  species
• Bridge Brook Lake (25 nodes), pelagic lake
  species
• Chesapeake Bay (31 nodes), emphasizing larger
  fishes
• Ythan Estuary (78 nodes) birds, fishes,
  invertebrates
• Coachella Valley (29 nodes), diverse desert taxa
• St. Martin Island (42 nodes), lizards

Source Williams Martinez, 2000
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Foodwebs haveconsensus 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 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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Feedforward loops in C. elegans avoidance reflex
circuit
Nose touch
Noxious chemicals, nose touch
Sensory neurons
FLP
AVD
Interneurons
AVA
Backward movement
Thomas Lockery 1999
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Networks can be grouped to super-families based
on the significance profile
Normalized Z-score
Milo et al Science 2004
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Summary network motifs
Network motifs, significant patterns in networks
Three motifs in transcription networks and
their functions High-accuracy promoter activity
measurements from living cells
Milo Science 2002, Shen-Orr Nat. Gen. 2002,
Itzkovitz PRE 2003, algorithms at
www.weizmann.ac.il/mcb/UriAlon
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Acknowledgments
Weizmann Institute, Israel
Alex Sigal Naama Geva Galit Lahav Nitzan
Rosenfeld Shiraz Kalir
Alon Zaslaver Erez Dekel Avi Mayo Yaki Setty
Ron Milo Adi Natan Shmoolik Mangam Shalev
Itzkovitz Nadav Kashtan
M. Elowitz, Caltech S. Leibler, Rockefeller M.G.
Surette, Calgary H. Margalit, Jerusalem
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Negative feedback loop with one transcription arm
and one protein arm is a common network motif
across organisms
x
y
43
Negative feedback in engineering uses fast
control on slow devices.
Heater
Power supply
Temperature
slow
Thermostat
fast
Engineers tune the feedback parameters to obtain
rapid and stable temperature control
44

Negative Feedback can show over-damping, damped
or un-damped oscillations, depending on
parameters
45

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
46

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
0.2Kb 1.2Kb
0.7Kb
pMT-I p53 CFP
Hygro
3.5Kb
15Kb 0.7Kb
pMdm2 Mdm2
YFP
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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Undamped p53 pulses in individual cells following
DNA damage
Lahav Nat. genetics 2004
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Digital behavior in the p53-mdm2 feedback loop
Number of cells with multiple pulses increases
with damage, but not the size/shape of pulse.
Analog design
Digital design
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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 Institute Israel
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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
53
Negative feedback in engineering uses fast
control on slow devices.
Heater
Power supply
Temperature
slow
Thermostat
fast
Engineers tune the feedback parameters to obtain
rapid and stable temperature control
54

Negative Feedback can show over-damping, damped
or un-damped oscillations, depending on
parameters
55

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
56

Negative Feedback can show over-damping, damped
or un-damped oscillations, depending on
parameters
Engineers usually try to avoid parameters that
give Undamped oscillations
57
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
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The p53 Network
MDM2
p53
One cell death Protection of the whole organism
Is the damage repairable?
59

Damped oscillations in p53-mdm2 and NFkB-IkB
negative feedback loops
western
p53-mdm2
Hrs after g 0 1 2 3 4 5 6 7
8
p53
MDM2
western
p53
mdm2
Lev Bar-Or et al, PNAS, 2000
Damped oscillations
NFkB-IkB
Electro Mobility Gel-Shift Assay
Hoffman et al, Science, 2002
Measurements on populations!
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System for real-time proteomics in single living
cells for p53-mdm2 kinetics.
0.2Kb 1.2Kb
0.7Kb
pMT-I p53 CFP
Hygro
3.5Kb
15Kb 0.7Kb
pMdm2 Mdm2
YFP
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.
Hours after g
0 ½ 1 2 3 4 5 6 7 8 9
p53-CFP
p53
p53
p53-CFP
Mcf7 p53/
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Mdm2-YFP kinetics are similar to endogenous Mdm2.
Hours after g Irradiation
0 ½ 1 2 3 4 5 6 7 8 9
Mdm2-YFP
Mdm2
Mdm2-YFP
Mdm2
Mcf7 p53/ Mdm2 /
Mdm2-YFP appears to undergo the same decrease as
endogenous mdm2 at early times
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p53-CFP and Mdm2-YFP expression after DNA damage
in living human cells.
64

To return to the article, close this browser
window. To toggle between the article and the
figure, click on the browser window containing
the article. Dynamics of the p53-Mdm2 feedback
loop in individual cellsGalit Lahav et
al.Nature Genetics - Published online 18
January 2004, doi10.1038/ng1293   
 Figure 2 Dynamics of p53-CFP. (a)
p53-CFP (green) in clonal MCF7pU265pU293 cells
after 5-Gy   -irradiation. Time (in min) after
irradiation is shown below images. (b,c) p53-CFP
levels (total CFP fluorescence in nuclei) from
cells 1 and 2 (indicated by arrows in a). (d)
Dynamics of p53-CFP (green) and Mdm2-YFP (red) in
a cell that shows two pulses. Time (in min) after
irradiation is shown below images. (e) p53-CFP
(green) and Mdm2-YFP (red) levels in the nucleus
of the cell in d. AU, arbitrary units.
p53 pulses in the nucleus
65

To return to the article, close this browser
window. To toggle between the article and the
figure, click on the browser window containing
the article. Dynamics of the p53-Mdm2 feedback
loop in individual cellsGalit Lahav et
al.Nature Genetics - Published online 18
January 2004, doi10.1038/ng1293   
 Figure 2 Dynamics of p53-CFP. (a)
p53-CFP (green) in clonal MCF7pU265pU293 cells
after 5-Gy   -irradiation. Time (in min) after
irradiation is shown below images. (b,c) p53-CFP
levels (total CFP fluorescence in nuclei) from
cells 1 and 2 (indicated by arrows in a). (d)
Dynamics of p53-CFP (green) and Mdm2-YFP (red) in
a cell that shows two pulses. Time (in min) after
irradiation is shown below images. (e) p53-CFP
(green) and Mdm2-YFP (red) levels in the nucleus
of the cell in d. AU, arbitrary units.
Mdm2 pulses follow p53 pulses in the nucleus
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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
1st Peak Width36050min (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
100
80
60
of cells
40
2.5Gy
20
0
0 1
2
Numbers of pulses
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The irradiation level determines the distribution
of cells undergoing 0,1 or 2 oscillations
100
80
10Gy
60
of cells
40
2.5Gy
20
0
0 1
2
Numbers of pulses
75
The irradiation level determines the distribution
of cells undergoing 0,1 or 2 oscillations
100
80
10Gy
60
of cells
40
2.5Gy
20
0.3Gy
0
0 1
2
Numbers of pulses
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The irradiation level determines the distribution
of cells undergoing 0,1 or 2 oscillations
100
80
10Gy
60
of cells
40
5Gy
2.5Gy
20
0.3Gy
0Gy
0
0 1
2
Numbers of pulses
77
Mean pulse widths do not depend on DNA damage
level
78
Mean pulse height does not depend on DNA damage
level
79
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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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?

• Could different numbers of pulses convey
  different 'meanings' to the cell in terms of
  expression of downstream genes?

• What about other negative feedback loopsdo
  they also display digital behavior?

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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
which Expressed a chromosomally YFP-tagged
protein automated microscopy and image-analysis
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Exon tagging a gene with a fluorescent protein
intron3
DNA
intron1
intron2
exon1
exon2
exon3
exon4
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Tagged protein identified using RACE
A
B
C
Ribosomal protein L5
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A wide variety of localization patterns
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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
Weizmann Institute, Israel
Galit Lahav Alex Sigal Naama Geva Lior
Ben-Arzi Nitzan Rosenfeld Shiraz Kalir Inbal
Alaluf
Alon Zaslaver Shai Shen-Orr Erez Dekel Avi
Mayo Yaki Setty
Ron Milo Adi Natan Shmoolik Mangam Shalev
Itzkovitz Nadav Kashtan Ido Zelman
Zvi Kam Benjamin Geiger Moshe Oren Varda Rotter
Stan Leibler, Rockefeller -coli Mike Surette,
Calgary -coli Arnold Levine, IAS Princeton
p53 Michael Elowitz, Caltech p53
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The heat-shock single-input-module
?32
SINGLE INPUT MODULE NETWORK MOTIF
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Heat shock promoters are activated after ethanol
step, and then adapt
4 ethanol Added at t0,
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
96
Heat-shock promoters are turned OFF in temporal
order
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