Download Systems Biology and multifactorial disease

In silico discovery of principles in multiscale
Systems Biology
Hans V. Westerhoff and friends
Manchester Centre for Integrative Systems Biology
Doctoral Training Centre for Systems Biology from
Molecules to Life
Westerhoff et al., Leiden 20121116
Netherlands Institute for
Systems Biology,
Amsterdam
Lorentz: Principles in multiscale Systems Biology
In silico discovery of principles in
multiscale Systems Biology
• The paradigm of the replica model
• Discovery through replica modelling of reality:
–
–
–
–
–
Time invariance and distributed control
Robust biology
Irreducible complexity
Drug target discovery
Hierarchies in scales: gene expression and time
• We have a problem
• Multiscale ITFoM as a solution
• Out of my comfort zone
Westerhoff et al., Leiden 20121116
Lorentz: Principles in multiscale Systems Biology
The enzymes are like
elementary particles for
biology!
• X=X(time, X0, e1,
e2,.., en, enzyme
parameters, [S])
Constituent equation:
𝑛
𝑑𝑥𝑖 =
𝑁𝑖𝑗 ∙ 𝑒𝑗 ∙ 𝑣𝑗 (𝑥, 𝑝 ) ∙ 𝑑𝑡
𝑗=1
∙ chemical
─ reaction
Westerhoff et al., Leiden 20121116
Lorentz: Principles in multiscale Systems Biology
The paradigm of the replica model
• Model reality using multiscaling that does not
•
•
•
•
•
loose essential complexity
Genes/enzymes as elementary particles
Describe them with rate equations (v(X))
Describe metabolites with node equations
(dX/dt) = N.v)
Integrate
Repeat at higher scales in terms of modules,
keeping relationships with fine-grained levels
Westerhoff et al., Leiden 20121116
Lorentz: Principles in multiscale Systems Biology
Westerhoff et al., Leiden 20121116
Lorentz: Principles in multiscale Systems Biology
Silicon / virtual biochemical organisms
Westerhoff et al., Leiden 20121116
Lorentz: Principles in multiscale Systems Biology
In silico discovery of principles in
multiscale Systems Biology
• The paradigm of the replica model
• Discovery through replica modelling of reality:
–
–
–
–
–
Time invariance and distributed control
Irreducible complexity
Robust biology
Drug target discovery
Hierarchies in scales: gene expression and time
• We have a problem
• Multiscale ITFoM as a solution
• Out of my comfort zone
Westerhoff et al., Leiden 20121116
Lorentz: Principles in multiscale Systems Biology
If the model is a replica, it is
as complex as the real
system, hence offers no
advantages for understanding
Replica models can be used for
computational investigations of
reality
They greatly facilitate discovery of
Principles that govern reality
Westerhoff et al., Leiden 20121116
Lorentz: Principles in multiscale Systems Biology
Westerhoff et al., Leiden 20121116
Lorentz: Principles in multiscale Systems Biology
Hendrik Antoon Lorentz
• 1900: Maxwell equations are
• invariant under the Lorentz
transformation
• Lorentz contraction
Westerhoff et al., Leiden 20121116
Lorentz: Principles in multiscale Systems Biology
Constituent equation:
𝑛
𝑑𝑥𝑖 =
𝑁𝑖𝑗 ∙ 𝑒𝑗 ∙ 𝑣𝑗 (𝑥, 𝑝 ) ∙ 𝑑𝑡
𝑗=1
Our transformation
𝑒𝑖 ′ ≡ 𝜆 ∙ 𝑒𝑖
𝑡 ′ ≡ 𝑡/𝜆
All processes 60 times faster
Seconds instead of minutes as time unit
There should be no effect
∙ chemical
─ reaction
Westerhoff et al., Leiden 20121116
Lorentz: Principles in multiscale Systems Biology
Law/principle of Systems Biology
lnJ
n
C
j 1
x
ej
(t )  C (t )  0
x
t
Westerhoff (2008) J Theor Biol 252, 555 - 567
Steady state or maximum:
𝐶1𝑥 + 𝐶2𝑥 + 𝐶3𝑥 + ⋯ . +𝐶𝑛𝑥 = 0
Westerhoff et al., Leiden 20121116
log of concentration
C=Control of concentration by
enzyme
SS
logarithm of time
Lorentz: Principles in multiscale Systems Biology
Silicon / virtual biochemical
organisms\validated in silico
Westerhoff et al., Leiden 20121116
Lorentz: Principles in multiscale Systems Biology
Growth factor
The principle we discovered
E
EP
F
For the
maximum level
of EP the
phosphatases
are equally
important as
the kinases
FP
G
GP
Transcription of ‘growth’genes
Westerhoff et al., Leiden 20121116
Lorentz: Principles in multiscale Systems Biology
In silico discovery of principles in
multiscale Systems Biology
• The paradigm of the replica model
• Discovery through replica modelling of reality:
–
–
–
–
–
Time invariance and distributed control
Irreducible complexity
Robust biology
Drug target discovery
Hierarchies in scales: gene expression and time
• We have a problem
• Multiscale ITFoM as a solution
• Out of my comfort zone
Westerhoff et al., Leiden 20121116
Lorentz: Principles in multiscale Systems Biology
Simplicity:
Control essentially in one component
(the key gene/enzyme catalyzing the first irreversible step)
Irreducible complexity:
Control is distributed
And not even uniformly
Which is it?
MAP kinase signaling: which are the fragile steps?
Healthy tissue
Calculations
based on
0.03
Schöberl model
0.06
At JWS/SiC
-0.43
0.00
-0.18
0.21
0.01
0.43
1.47
-1.47
-1.12
Westerhoff et al., Leiden 20121116
0.44
-0.44
Hornberg et al. Oncogene
Lorentz: Principles in multiscale Systems Biology
In silico discovery of principles in
multiscale Systems Biology
• The paradigm of the replica model
• Discovery through replica modelling of reality:
–
–
–
–
–
Time invariance and distributed control
Irreducible complexity
Robust biology
Drug target discovery
Hierarchies in scales: gene expression and time
• We have a problem
• Multiscale ITFoM as a solution
• Out of my comfort zone
Westerhoff et al., Leiden 20121116
Lorentz: Principles in multiscale Systems Biology
To discover & certify network
principles of robustness
(and disease)
We need a definition of
robustness
Definition of robustness
The percentage by which one
can interfere with a molecular
process without reducing system
function by more than 1 %
Principle 1
Networking enhances robustness
Function
Process in isolation
Enzyme activity
1% decrease in enzyme activity
 
1
1% decrease in function f
f
ei
Robustness is 1 for processes in isolation
Westerhoff et al., Leiden 20121116
Lorentz: Principles in multiscale Systems Biology
robustness of isolated
processes =1
Is the robustness in
networks larger?
Silicon / virtual biochemical organisms
Westerhoff et al., Leiden 20121116
Lorentz: Principles in multiscale Systems Biology
Robustness of vital flux of Trypanosomes vis-àvis perturbation of various glycolytic steps
step
Robustness
Glctr
1.1
GAPdh
42
HK
42
PGI
1546
PFK
234
ALD
38
TPI
482
GDH
66
GPO
-251
PGK
61
PK
ATPase
GlyK
Question:
Is robustness higher (than 1)
in networks of living cells?
691
Answer:
Yes, most robustnesses
in networks in living
organisms are large;
average is 468 here
2744
389
Westerhoff et al., Leiden 20121116
Lorentz: Principles in multiscale Systems Biology
Principle 2???
Trade-off???:
Does making the system more robust
vis-à-vis one perturbation make it
equally less robust for a different
perturbation???
Precise trade-off for robustness?
step
Robustness
Robustness
doubled
glucose
transporter
Glctr
1.1
88
GAPdh
42
4
HK
42
20
PGI
1546
412
PFK
234
56.
ALD
38
3
TPI
482
64
GDH
66
6
GPO
-251
-15
PGK
61
7
691
73
2744
313
389
26
PK
ATPase
GlyK
Westerhoff6085
et al., Leiden
(468)201211161055(81)
Sum (average)
No, robustness is
not conserved
No precise tradeoff for robustness
Lorentz: Principles in multiscale Systems Biology
Principle 2???
Trade-off???:
making the system more robust vis-à-vis
one perturbation makes it less robust for a
different perturbation???
No principle then?
No trade-off?
Yes, there is one!
Sum over all inverse robustnesses
= 1= conserved
step
1/robustness
1/robustness
(doubled glc
transporter)
Glctr
0.887
0.011
GAPdh
0.024
0.249
HK
0.024
0.051
PGI
0.001
0.002
PFK
0.004
0.018
ALD
0.026
0.354
TPI
0.002
0.016
GDH
0.015
0.166
GPO
-0.004
-0.068
PGK
0.016
0.144
PK
0.001
0.014
0
0.003
0.003
0.039
0.999
0.999
ATPase
GlyK
Sum
Westerhoff et al., Leiden 20121116
Lorentz: Principles in multiscale Systems Biology
In silico discovery of principles in
multiscale Systems Biology
• The paradigm of the replica model
• Discovery through replica modelling of reality:
–
–
–
–
–
Time invariance and distributed control
Irreducible complexity
Robust biology
Drug target discovery
Hierarchies in scales: gene expression and time
• We have a problem
• Multiscale ITFoM as a solution
• Out of my comfort zone
Westerhoff et al., Leiden 20121116
Lorentz: Principles in multiscale Systems Biology
Trypanosomiasis
Westerhoff et al., Leiden 20121116
Lorentz: Principles in multiscale Systems Biology
Silicon / virtual biochemical organisms
Westerhoff et al., Leiden 20121116
Lorentz: Principles in multiscale Systems Biology
The most fragile step is…..
Fragility=C=1/rob
ustness
1/robustness
(doubled glc
transporter)
Glucose transport
0.887
0.011
GAPdh
0.024
0.249
?
0.024
0.051
0.001
0.002
0.004
0.018
ALD
0.026
0.354
TPI
0.002
0.016
GDH
0.015
0.166
GPO
-0.004
-0.068
PGK
0.016
0.144
PK
0.001
0.014
0
0.003
0.003
0.039
0.999
0.999
step
HK
PGI
PFK
?
ATPase
GlyK
Sum
Westerhoff et al., Leiden 20121116
Lorentz: Principles in multiscale Systems Biology
Differential network-based drug
design
Target where the difference
between parasite and host is
the largest
Trypanosome in the host
us et al.
T. brucei…..
Red blood cell
Holzhütter et al.
Westerhoff et al., Leiden 20121116
Lorentz: Principles in multiscale Systems Biology
Differential fragility analysis TRYP and ERY
Fragility of
ATP synthesis
flux
0.00
TRYPANOSOME
ERYTHROCYTE
0.68
0.03
BAD
TARGET
0.00 0.001
BAD
TARGET
0.02
0.02
0.005
-0.01
0.05
0.000.01
0.00
0.00
0.00
0
GOOD
TARGET
0.01
0.03
0.06
FAIR
TARGET
0.07
0.94
0.001
(Bakker, Holzhütter, Snoep, Westerhoff)
Westerhoff et al., Leiden 20121116
Lorentz: Principles in multiscale Systems Biology
Haanstra
Westerhoff et al., Leiden 20121116
Lorentz: Principles in multiscale Systems Biology
Westerhoff et al., Leiden 20121116
Lorentz: Principles in multiscale Systems Biology
Fragilities of PGK mRNA and
protein versus perturbations in ..
Fragility of for →:
Targeting the networks: multiple targets at the
same time in hierarchical networks!
Westerhoff et al., Leiden 20121116
Lorentz: Principles in multiscale Systems Biology
The multiscale problem
and transcription activation
• Time:
•
How to bridge the various time scales?
Molecular <1 s versus Cellular >1 h
• The multidimension problem:
•
How to enable regulation by 20
information flows rather than by 1?
The
clock model for mammalian
transcription activation
A B
A B
A
C
A B
D C
B
D C
D
D C
Slow macroscopic dynamics caused
by, rapid, molecular processes!
Metivier, R. et al. Estrogen
receptor-alpha directs ordered,
cyclical, and combinatorial
recruitment of cofactors on a
natural target promoter. Cell
115, 751-763 (2003).
Note!
Transcription
synchrony in
population
of cells!
Westerhoff et al., Leiden 20121116
Karpova, T. S. et al. Concurrent
fast and slow cycling of a
transcriptional activator at an
endogenous promoter. Science
(New York, N.Y 319, 466-469
(2008).
Saramaki, A. et al. Cyclical
chromatin looping and
transcription factor association
on the regulatory regions of
the p21 (CDKN1A) gene in
response to 1alpha,25dihydroxyvitamin D3. J Biol
Chem 284, 8073-8082,
doi:M808090200 [pii]
Lorentz: Principles in multiscale Systems Biology
In silico discovery of principles in
multiscale Systems Biology
• The paradigm of the replica model
• Discovery through replica modelling of reality:
–
–
–
–
–
Time invariance and distributed control
Irreducible complexity
Robust biology
Drug target discovery
Hierarchies in scales: gene expression and time
• We have a problem
• Multiscale ITFoM as a solution
• Out of my comfort zone
Westerhoff et al., Leiden 20121116
Lorentz: Principles in multiscale Systems Biology
Well,
Why?
we have ‘a’ problem
• Definitive cures are lacking for most diseases
• The health care budget will cripple the economy
• The life sciences are tremendously successful
but ….. not in empowering medicine
• ………….
Increased spending has not
improved cancer mortality
50
45
40
cumulative NCI funding
(G$)
35
+2000
cancer mortality (/1000)
30
25
20
-10 %
15
10
5
0
1970
1975
1980
1985
1990
Westerhoff et al., Leiden 20121116
1995
2000
2005
2010
Lorentz: Principles in multiscale Systems Biology
Global prevalence
of diabetes and
impaired glucose
tolerance (IGT) in
2010 and 2030
Boyle, 2011
Westerhoff et al., Leiden 20121116
Lorentz: Principles in multiscale Systems Biology
transcriptomics
genomics
proteomics
Yet…
We can measure almost
everything now
metabolomics
structural biology
biochemistry
biophysics
Westerhoff et al., Leiden 20121116
biology
physiology
Lorentz: Principles in multiscale Systems Biology
>1 trillion €/year spent on biomedical research:
Tower of Babel?
health
Brueghel
disease
Westerhoff et al., Leiden 20121116
Lorentz: Principles in multiscale Systems Biology
In silico discovery of principles in
multiscale Systems Biology
• The paradigm of the replica model
• Discovery through replica modelling of reality:
–
–
–
–
–
Time invariance and distributed control
Irreducible complexity
Robust biology
Drug target discovery
Hierarchies in scales: gene expression and time
• We have a problem
• Multiscale ITFoM as a solution
• Out of my comfort zone
Westerhoff et al., Leiden 20121116
Lorentz: Principles in multiscale Systems Biology
IT Future of Medicine
a FET Flagship project
A CERN-like project:
1.3 G€
Idea 1: Use computable replica model to organize and integrate the data
Westerhoff et al., Leiden 20121116
Lorentz: Principles in multiscale Systems Biology
transcriptomics
genomics
proteomics
project all information into a
computer replica
metabolomics
structural biology
biochemistry
biophysics
Westerhoff et al., Leiden 20121116
biology
physiology
Lorentz: Principles in multiscale Systems Biology
Integration of all information through the ITFoM
flagship into computable human models!
health
An ICT model of the
human
Brueghel
disease
Westerhoff et al., Leiden 20121116
Lorentz: Principles in multiscale Systems Biology
Idea 2: to deal with
otherwise impossible
complexity
The human body is a computer
using simple principles
We should borrow its
computation strategy
New ICT for medicine
The virtual patient – a “person
simulator”
New ICT for medicine
The virtual patient – a “person
simulator”
And 7 billion of these…..:
Silicon / virtual biochemical human
Westerhoff et al., Leiden 20121116
Lorentz: Principles in multiscale Systems Biology
Integrating
Models
Models from Molecular
Systems Biology
Physiological models from
VPH
Statistical models
T.
bruc
ei
Red
blood
cell
Virtual
heart
HepatoMiccyte
rob
iom
e
Melanoma
Epidemiological models
Clinical models
Patients’ concepts
…….
Westerhoff et al., Leiden 20121116
Lorentz: Principles in multiscale Systems Biology
Final WP numbering and organization: blue is ICT, red is
medical and green is analytical expertise. The end product
is ICT models of individual humans for individualized
medicine.
Medical user and
expertise
Instrumentation
and assays
Analytical
WP2
Hard
ware
/Soft
ware
indu
stry
Hard- & Software
WP#3
Medical
WP1
Integration
WP#6
Data Pipelines
WP#4
Computational
WP#5
Databases and
repositories
Coordination
WP#7
Programing
industry &
academia
ICT-integration challenges
molecules – tissues - patients
4.9(I) Tools
4.8(I) Models
4.7(I) Data
4.6(I) Maps
ICT-modelling Strategies
4.1 (S) Watchmaker’s models (SiC)
4.3 (S) Mechanic’s models (VPH)
4.8(I) Tools
4.7(I) Models
4.6(I) Data
4.5(I) Maps
4.2 (S) Engineer’s models
4.4 (S) Learner’s models
4.5 (S) Combinations
In silico discovery of principles in
multiscale Systems Biology
• The paradigm of the replica model
• Discovery through replica modelling of reality:
–
–
–
–
–
Time invariance and distributed control
Irreducible complexity
Robust biology
Drug target discovery
Hierarchies in scales: gene expression and time
• We have a problem
• Multiscale ITFoM as a solution
• Out of my comfort zone
Westerhoff et al., Leiden 20121116
Lorentz: Principles in multiscale Systems Biology
Out of my comfort zone
• How to link down (enzyme MD)
Antreas Kalli
Use essential dynamics
Reduce to essential states
Compute affinities
Validate experimentally
Insert into enzyme kinetics
Westerhoff et al., Leiden 20121116
Lorentz: Principles in multiscale Systems Biology
Out of my comfort zone
• Pathway complexity
Eytan Rubin, Mattias Reuss, and us and others
Use exometabolomics, FBA and objective functions to find where
most of the flux is
Project SNPs into those pathways
Westerhoff et al., Leiden 20121116
Lorentz: Principles in multiscale Systems Biology
Out of my comfort zone
• Parameter finding intracellular networks
Martine Smits
Bob van de Water
Rich data sets
Multiple RNAi
7 billion humans
Westerhoff et al., Leiden 20121116
Lorentz: Principles in multiscale Systems Biology
Out of my comfort zone
• Cell heterogeneity
Single cell analyses
Westerhoff et al., Leiden 20121116
Lorentz: Principles in multiscale Systems Biology
Out of my comfort zone
• Towards tissue
•
•
•
•
Katarina Wolf
David Basanta
Chris Adami
Andreas Deutsch
Transparent black box approach
Focus on dominant behavior first
Agent based models
Evolutionary games, but extended to continuous variables
And connect parameters between levels!
Westerhoff et al., Leiden 20121116
Lorentz: Principles in multiscale Systems Biology
Out of my comfort zone
• True tissue dynamics and anatomy
• Bernard Corfe
Transparent black box approach
Focus on dominant behavior first
Agent based models
Evolutionary games, but extended to continuous variables
And connect parameters between levels!
Westerhoff et al., Leiden 20121116
Lorentz: Principles in multiscale Systems Biology
Out of my comfort zone
• Lifestyle and ethics
• Angela Brand, Bernard Corfe
Insert substrates= food into pathways
Insert movement as muscle activity
Insert brain through measured hormone levels
Westerhoff et al., Leiden 20121116
Lorentz: Principles in multiscale Systems Biology
In silico discovery of principles in
multiscale Systems Biology
• The paradigm of the replica model
• Discovery through replica modelling of reality:
–
–
–
–
–
Time invariance and distributed control
Irreducible complexity
Robust biology
Drug target discovery
Hierarchies in scales: gene expression and time
• We have a problem
• Multiscale ITFoM as a solution
• Out of my comfort zone
Westerhoff et al., Leiden 20121116
Lorentz: Principles in multiscale Systems Biology
In silico discovery of principles in multiscale
Systems Biology
friends
Manchester Centre for Integrative Systems Biology
Doctoral Training Centre for Systems Biology from
Molecules to Life
Westerhoff et al., Leiden 20121116
Netherlands Institute for
Systems Biology,
Amsterdam
Lorentz: Principles in multiscale Systems Biology