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Complex networks are found throughout biology. 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.

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can we define the basic building blocks of networks
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.

database of direct transcription interactions in e coli

X

Y

Z

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

algorithm that finds n node network motifs
Algorithm that finds n-node network motifs

Examples of 3-node circuits

N

Find all n-node circuits in real graph

X

X

X

Y

Y

Z

Y

Z

U

X

Z

Y

Z

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

slide8

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

slide9

The feed-forward loop is a filter for transient signals allowing fast shutdown

Mangan, PNAS, JMB, 2003

slide10

GFP Reporter plasmid system for promoter activity

Lutz, Bujard 1997

Kalir, Leibler, Surette, Alon, Science 2001

slide11

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.

slide12

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.

slide14

Day-day reproducibility of better than 10%

GFP repeat 2

*2

*1.1

*0.9

*0.5

10%

2-fold

GFP repeat 1

slide15

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

slide16

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).

slide17

OFF pulse

Feedforward loop is a sign-sensitive filter

Vs.

=lacZYA

=araBAD

Mangan Zaslaver, Alon JMB 2003

slide20

Flagella operons are activated in temporal order

Kalir, Leibler, Surette, Alon Science 2001

Laub, McAdams, Shapiro Science 2000

slide22

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

slide23

Turn ON (arg removed)

Turn OFF (arg added)

Time [min]

Time

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

4 node motifs in e coli network overlapping regulation
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

mapping logic gates using gfp reporter arrays lacz
Mapping Logic gates using GFP reporter arrays (LacZ)

IPTG

ANDGATE?

LacZ

cAMP

Setty, Mayo, Surette, Alon, PNAS 2003

e coli and yeast transcriptional networks show the same motifs

X

X

X

Y

Y

Y

Z

Z

W

Z2

Z1

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

slide31

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

slide32

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

food webs represent predatory interactions between species

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

slide34

Foodwebs have“consensus motifs”

  • Consensus motifs – different from transcription networks
  • Feedforward is not motif - omnivores are under-represented
slide35

Links between WWW Pages –a completely different set of motifs is found

  • WebPages are nodes and Links are directed edges
  • 3 node results
slide36

Each node represents a transistor

Each node represents a transistor motif:

Logic gate

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

slide38

ASH

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

networks can be grouped to super families based on the significance profile
Networks can be grouped to super-families based on the significance profile

Normalized

Z-score

Milo et al Science 2004

slide40

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

acknowledgments
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

slide42

Bacteria

Fruit-Flies

Yeast

sH

Ime1

smo

dnaK

dnaJ

Ime2

Ptc

Mammals

HSF1

NFkB

HIF

p53

hsp70

hsp90

IkB

iNOS

Mdm2

Negative feedback loop with one transcription arm and one protein arm is a common network motif across organisms

x

y

negative feedback in engineering uses fast control on slow devices
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

slide44

Negative Feedback can show over-damping, damped

or un-damped oscillations, depending on parameters

slide45

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

slide46

Negative Feedback can show over-damping, damped

or un-damped oscillations, depending on parameters

Engineers usually try to avoid parameters that give Undamped oscillations

slide47

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

digital behavior in the p53 mdm2 feedback loop
‘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

slide50
Dynamics of the p53-mdm2 loop in single living cells, and the design principles of biological feedback

Galit Lahav

Uri Alon

Weizmann Institute

Israel

overview
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

slide52

Bacteria

Fruit-Flies

Yeast

sH

Ime1

smo

dnaK

dnaJ

Ime2

Ptc

Mammals

HSF1

NFkB

HIF

p53

hsp70

hsp90

IkB

iNOS

Mdm2

Negative feedback loop with one transcription arm and one protein arm is a common network motif across organisms

x

y

negative feedback in engineering uses fast control on slow devices1
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

slide54

Negative Feedback can show over-damping, damped

or un-damped oscillations, depending on parameters

slide55

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

slide56

Negative Feedback can show over-damping, damped

or un-damped oscillations, depending on parameters

Engineers usually try to avoid parameters that give Undamped oscillations

what about biological feedback control

P53-CFP

Mdm2-YFP

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

slide58

The p53 Network

Stress signals

Cell cycle arrest

G1/S G2/M

no

yes

Apoptosis

DNA repair

MDM2

p53

One cell death =

Protection of the whole organism

Is the damage

repairable?

slide59

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!

slide60

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

p53 cfp shows damped oscillations in western following dna damage similar to endogenous p53
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+/+

mdm2 yfp kinetics are similar to endogenous mdm2
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

slide64

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 cellsGalitLahavet al.Nature Genetics - Published online: 18 January 2004, doi:10.1038/ng1293

Figure 2: Dynamics of p53-CFP.

(a) p53-CFP (green) in clonal MCF7+pU265+pU293 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.

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.

p53 pulses in the nucleus

slide65

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 cellsGalitLahavet al.Nature Genetics - Published online: 18 January 2004, doi:10.1038/ng1293

Figure 2: Dynamics of p53-CFP.

(a) p53-CFP (green) in clonal MCF7+pU265+pU293 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

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.

two groups of behavior one peak and two peaks with small variations inside each group

Ymax1

Ymax2

Peak Width=350±60min (SD)

2nd Peak Width=340±40min (SD)

Ymax2/Ymax1=1.1±0.2 (SD)

T(Ymax2)-T(Ymax1)=370±50min (SD)

Two groups of behavior: one peak and two peaks, with small variations inside each group

1st Peak Width=360±50min (SD)

slide72
Average of single cell data is similar to Western: damped oscillations are an artifact of mixing two behavior classes
the irradiation level determines the distribution of cells undergoing 0 1 or 2 oscillations
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

the irradiation level determines the distribution of cells undergoing 0 1 or 2 oscillations1
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

the irradiation level determines the distribution of cells undergoing 0 1 or 2 oscillations2
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

the irradiation level determines the distribution of cells undergoing 0 1 or 2 oscillations3
The irradiation level determines the distribution of cells undergoing 0,1 or 2 oscillations

100

80

10Gy

60

% of cells

40

2.5Gy

5Gy

20

0.3Gy

0Gy

0

0 1 2+

Numbers of pulses

mean pulse widths do not depend on dna damage level

Second pulse width

First pulse width

2.5Gy 5Gy 10Gy

0.3Gy 2.5Gy 5Gy 10Gy

Mean pulse widths do not depend on DNA damage level
mean pulse height does not depend on dna damage level

First pulse height

Second pulse height

0.3Gy 2.5Gy 5Gy 10Gy

2.5Gy 5Gy 10Gy

Mean pulse height does not depend on DNA damage level
digital behavior in the p53 mdm2 feedback loop1
‘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

what s next
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 loops…do they also display ‘digital behavior’?
the goal dynamic proteomics in individual living human cells
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
slide84

Annotated library of cells each of which

Expressed a chromosomally YFP-tagged protein

+automated microscopy and image-analysis

slide85

SASD

YFP

puro

transcription

SASD

SASD

SASD

SASD

RNA

exon1

exon2

YFP

puro

exon3

splicing

mRNA

exon1

exon2

YFP

exon3

exon4

translation

Protein

N

C

YFP

Exon tagging a gene with a fluorescent protein

intron3

DNA

intron1

intron2

exon1

exon2

exon3

exon4

slide86

YFP

Exon n+1

AAAAAAAAAA

Added seq

Exon n

472

YFP

Exon n+1

AAAAAAAAAA

Added seq

546

clone

RACE stage

1

2

1

2

1

2

1

2

1

2

1

2

4c18

4d8

1d13

1d22

1e18

1f21

Clone 1e18

YFP

Clone 1e18

Tagged protein identified using RACE

A

B

C

Ribosomal protein L5

slide88

0 min

10 min

20 min

30 min

Dynamic proteomics in individual cells

summary
Summary
  • Network motifs and their biological function
  • Digital pulses of p53
  • Dynamic proteomics in individual living cells
acknowledgments1
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

the heat shock single input module

b1

k1

1

b2

k2

2

b3

k3

3

bn

kn

n

d

dnaKJ

groEL

htpG

lon

The heat-shock single-input-module

32

SINGLE INPUT MODULE NETWORK MOTIF

heat shock promoters are activated after ethanol step and then adapt
Heat shock promoters are activated after ethanol step, and then adapt

4% ethanol

Added at t=0,

Natan et al 2004

heat shock promoters are turned off in temporal order
Heat-shock promoters are turned OFF in temporal order

Temporal turn-off order ~3 minutes difference

Natan et al 2004

slide97

Turn-off order matches severity of repair

Same principle found in SOS DNA repair [Ronen, Shraiman, Alon PNAS 2002]