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What happened to computing 1930-80 is now happening to biology
Friden mechanical calculator: 1930-1966
Friden electronic calculator: 1965
Intel 4004
mproc:
1971
Sharp single chip calculator:
1977
What happened to computing 1930-80 is now happening to biology
% cells damaged by transfection
Pre-2000
Proportion of cells transfected
- Example: electroporation
The complete protocol
Today
Tomorrow
Another example: automated parallel mini-preps
The geek shall inherit (systems) biology
Pathway/
interaction
DBs / literature
cell-specific,
comprehensive,
kinetic and
quantitative data
Computation
Biology
Technology
data
analysis
experiments to
test hypotheses
experimental
planning
model
construction
model
analysis
hypothesis
formulation
2 complementary approaches in systems biology:
Top-down, global, systematic
Bottom-up, local dynamics
•
•
Focus on nonlinear interactions
•
Study irreducible systems
•
Analyzing emergent (difficult-topredict, nonlinear) properties
•
Hypothesis and model-driven
•
Discovery science via high
throughput ‘omic technologies
Screening
- multi-target/multi-component drugs
- multi-parameter disease signatures
•
Observation & data-driven
global climate
local weather
The yeast galactose utilization pathway – bottom up view
Galactose
Gal2p
(transporter)
+ feedback
Gal3p
Gal1p
(kinase)
Galactose
Galactose
1-phosphate
+ feedback
Gal3p*
UDP-galactose
Gal7p
(transferase)
Gal10p
(epimerase)
Gal80p
- feedback
Gal4p
UDP- glucose
Gal80
de Atauri et al Biochem J. 2005
Glucose
1-phosphate
Gal4p
UGP1
PGM1
PGM2
GPH1
GSY1
GSY2
TPS1
TSL1
TPS3
GSC2
FKS1
FKS3
Gal3
Gal4p
Gal2
1,3-â-Glucan
Gal4p
Threhalose synthesis
Glucose
6-phosphate
Glycogen synthesis
Gal 1,7,10
The yeast galactose utilization pathway – top down view
How do we make sense of this?
A network graph viewed in Cytoscape; what does it do?
An Exclusive OR gate
out = XOR
•
in1
in2
1
•
4
out
3
2
in1
in2
NOR 1
NAND 2
NOT 3
NOR 4
0
0
1
1
0
0
0
1
0
1
0
1
1
0
0
1
0
1
1
1
0
0
1
0
1
T1
2
•
in1
in2
Vdd
•
T5
•
.
T2
3
T3
T4
•
T11
T6
4
•
• •
T7
5
T8
T9
T10
6
•
•
7
T12
8
•
out = XOR
T13
T14
Gnd
0
NOR (1)
NAND (2)
NOT (3)
NOR (4)
“Guilt by association” network analysis
Phagocytosis
Fas
Cell adhesion
Translation
Actin polymerization
mRNA stability
p38
pathway
Red nodes: down-regulated
Green nodes: up-regulated
Transfac/HPRD/in-house
documented P-P interaction
Transfac documented
P-DNA interaction
Network motifs & functional building blocks
Ecoli
sea urchin functional building blocks
Nonlinear switch
Unidirectional switch
Bolouri & Davidson
BioEssays 2002
Community effect
yeast
Uri Alon & colleagues
Rick Young & colleagues
Regulated &/or
rapid response
Cannot guess function from topology alone
Network topology:
1
•
in1
in2
T1
2
•
.
T5
•
T2
T3
T4
•
T11
T6
• •
•
7
T12
T9
•
•
T10
5
T8
• •
T13
T14
0
equivalent network motifs/modules
select1
select2
•
•
T13
7
T12
A
T11
Possible (mis)interpretation:
B
 A if (select1=on & select2=on)
Network motifs have many additional inputs and interactions
A topological motif may implement different functions
The feed forward motif:
Alon & colleagues, Nature Genetics, 2002. 31(1): p. 64-8
see also:
A coherent feedforward motif acting as a gradient sensor
Need a functional abstraction hierarchy
Potential genetic regulatory functional building blocks
(D)
(A)
(E)
(F)
(B)
(C)
(g)
BioTapestry.org
At steady state:
PSS
Otx
= (ks/kdp).mRNA
mRNASS= (kt/kdm).Y
GataE
mRNA
Kdiss
mRNAss
Pss
P
kt.ks/2.kdm.kdp
GCM
Potential genetic regulatory functional building blocks
(D)
(A)
(E)
(F)
(B)
(C)
(g)
(1)
(2)
positive
driver
(3)
positive
intercellular
feedback
blue gene activity level
b-catenin/Wnt8 ‘Community Effect’ filters out expression variability
_ cell 1
_ cell 2
_ cell 3
cell 1 driver gene
cell type
specific
gene battery
Simulated time
cb
c
Cells in a reinforcing loop
- all cells in group adopt same fate
- sharp boundary between cell types
- insensitive to level of “driver”
GSK-3
Nb-TCF
frizzled
Krox
Wnt8
Intercellular positive feedback: The community effect
Gurdon ‘88, Nature, 336, 772-4
Data from Davidson lab
Potential genetic regulatory functional building blocks
(D)
(A)
(E)
(F)
(B)
(C)
(g)
Intracellular negative feedback
x
See also Ashburner et al 1973-1981 (see Cell, 1990. 61(1):1-3)
(A) tuned for regulated level
(B) single transcriptional pulse
(C) tuned for rapid response
FoxA
(D) tuned for long lasting oscillation
Potential genetic regulatory functional building blocks
(D)
(A)
(E)
(F)
(B)
(C)
(g)
Cell 2 (anterior)
Cell 1 (posterior)
Su(Fu)
Fu
Smo::Cos2
Wnt
Ci::Su(Fu)
Smo
CiA
CiR
Cos2::GSK3b
Smo_I
Ptc
Nkd
Dlp
Ptc: :Hh
Hh pathway
6000
5000
4000
3000
DshA
2000
DshA2
En
1000
En2
0
1
9
17 25 33
41 49 57 65 73
81 89 97 105 113 121 129 137 145 153 161 169 177 185 193 201
u
Hh
Slp
En
Ci
TCF
TCF
Wnt pathway
Mutual exclusion in a mammalian adult cell specification process
Mutual exclusion operator
cooperativity factor = 2
gene 1
production _ rate
K Diss * decay _ rate
cooperativity factor = 3
cooperativity factor = 4
production _ rate
gene 2 K * decay _ rate
Diss
after Cherry & Adler, JTB 2000
Multi-cellular mutual exclusion
Potential genetic regulatory functional building blocks
(D)
(A)
(E)
(F)
(B)
(C)
(g)
The feed forward motif:
Alon & colleagues, Nature Genetics, 2002. 31(1): p. 64-8
see also:
10000
protein_A
protein_AA
protein_B
8000
100 molecules
6000
4000
yeast
2000
0
0
2001.334
~ 2 days
45000
40000
protein_A
protein_AA
35000
protein_B
30000
25000
MF
20000
15000
10000
5000
0
9000
6000
7000
8000
9000
Potential genetic regulatory functional building blocks
(D)
(A)
(E)
(F)
(B)
(C)
(g)
Regulatory circuit elements: boundary detection switches
Repression cascade
activator level
steady state gene 2
steady state gene 2
Direct activation
activator level
U
activator
activator
gene3
U
gene1
gene2
gene1
gene2
cell type 1
cell type 2
gene2, cell2
gene2
gene1
gene2
gene1
time
gene2, cell1
time
time
Potential genetic regulatory functional building blocks
(D)
(A)
(E)
(F)
(B)
(C)
(g)
Potential genetic regulatory functional building blocks
(D)
(A)
(E)
(F)
(B)
(C)
(g)
A feedforward motif functioning as a reset (homeostasis) mechanism
TLR4
NFkB
ATF3
IL6, IL12b…
NFkB
NFkB
ATF3
ATF3
TLR4 genes
Gilchrist et al, Nature, 2006
Robust behavior in parameter space
P2
P2
quantitative
measure of
behavior
P1
P1
Concave:
Convex:
• Poor stability margins
• Large stability margins
• Parameter interdependence
• Parameter independence
Note also rate of change of ‘desired’ behavior away from operating point
The same genes take part in different processes and functional blocks
Different genes implement the same functional building blocks
Data from Davidson lab
Heart specification functional module:
conserved from flies to humans?
fly
vertebrate
maveric, multi-talented enthusiasts
diverse, specialized suppliers of
modular, standardized parts
early adopters standardize,
develop “Killer Apps”
performance, reliability, usability
and manufacturability
http://www.septicshock.org/
http://magnet.systemsbiology.net/software/Pointillist/
Hwang et al, PNAS 2005a, b
Orrell et al, Physica D, 2006
Ramsey et al, Nat. Gen. 2006
Gilchrist et al, Nature 2006
http://sugp.caltech.edu/endomes/
Davidson et al, Science 2002
Davidson Lab & Eric Davidson
Bill Longabaugh
Jennifer Smith, Deena Leslie, Andrea
Weston, Marcello Marelli, Tim Petersen
Steve Ramsey
Daehee Hwang
Andy Siegel, John Aitchison, Lee Hood
Ben Buelow, Mark Gilchrist, Katy Kennedy, Adrian Ozinsky,
Jared Roach, Carrie Baldwin, Natalya Yudkovsly
David Orrell
Alan Aderem
Alistair Rust
Martin Korb
Vesteinn Thorsson
Pedro de Atauri
Mark Robinson
Christophe Battail
Bin Li
Department of Cellular & Physiological Sciences
University of British Columbia
Life Sciences Centre
2350 Health Sciences Mall
Vancouver, BC Canada V6T 1Z3
Recruiting:
- Graduate students
- Post docs
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Subjects:
- molecular & cell biology
- transcriptional regulation
- single cell assays
- math, stats
- physics, engineering
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- software engineering