computational investigation of intracellular networks centre for medical systems biology...
TRANSCRIPT
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Computational Investigation of
Intracellular Networks
Centre for Medical Systems Biology
C E N T R F O R I N T E G R A T I V E
B I O I N F O R M A T I C S V U
E
Thomas Binsl
Kate Mullen
Olav Kongas
Mark NobleFrits Prinzen
Joli Bussemaker David Alders
Johan Groeneveld
Lori Gustafson
Koert Zuurbier
Jan Bart Hak
Glenn Harrison
Marcel Eijgelshoven
Bas de Groot
Jaap Heringa
Ivo van Stokkum
Hans van BeekThomas Binsl
Kate Mullen
Olav Kongas
Mark NobleFrits Prinzen
Joli Bussemaker David Alders
Johan Groeneveld
Lori Gustafson
Koert Zuurbier
Jan Bart Hak
Glenn Harrison
Marcel Eijgelshoven
Bas de Groot
Jaap Heringa
Ivo van Stokkum
Hans van Beek
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C E N T R F O R I N T E G R A T I V EB I O I N F O R M A T I C S V U
E
Agenda• Systems Approach
(components and interactions)
• Bioinformatic and Statistical Analysis
(top-down)
• Metabolomics and Fluxomics
(metabolic flux measurements)
• Mechanistic Modeling : modular and multiscale
(bottom-up)
• Summary
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C E N T R F O R I N T E G R A T I V EB I O I N F O R M A T I C S V U
E
Agenda• Systems Approach
(components and interactions)
• Bioinformatic and Statistical Analysis
(top-down)
• Metabolomics and Fluxomics
(metabolic flux measurements)
• Mechanistic Modeling : modular and multiscale
(bottom-up)
• Summary
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Gene 1
Gene 2
Phenotype 1
Gene 3
Gene 4 Phenotype 1a
Phenotype 2
Gene 1
Gene 3
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Interfaces of Components May Be Damaged during Isolation
Intact System Isolation of Components
Interfaces Damaged during Isolation
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Study System at Multiple Scales
Molecules Form Pathways
Pathways Form Cells
Cell Types Form Organs or
Ecosystems
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Widespread RNA transcription found in ENCODE project :
Nature, June 2007
"Instead of running errands, RNA appears to be running the whole show," said Isidore Rigoutsos, a lead scientist at IBM's Thomas
J. Watson Research Center
RN
A
tran
scri
pti
on
Do Not Forget the RNA Level
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C E N T R F O R I N T E G R A T I V EB I O I N F O R M A T I C S V U
E
Agenda• Systems Approach
(components and interactions)
• Bioinformatic and Statistical Analysis
(top-down)
• Metabolomics and Fluxomics
(metabolic flux measurements)
• Mechanistic Modeling : modular and multiscale
(bottom-up)
• Summary
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C E N T R F O R I N T E G R A T I V EB I O I N F O R M A T I C S V U
E
Results Rat Boneload vs control
C. Reijnders, N. Bravenboer, J van Beek, P. Lips et al.
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Bone : Differentially expressed genes 6 hours after mechanical loading
Gene name Fold change
P adj value Biological connection
mepeosteoregulin
OF451.83 0.054
skeletal development; regulation of bone remodeling;
negative regulation of bone mineralizationgarnl1tulip 1
1.42 0.054 regulation of transcription
creatine kinase, muscle form -2.62 0.065 phosphocreatine biosynthesis and metabolism
fibrinogen B beta chain -2.27 0.074blood coagulation; wound healing;
regulation of blood pressure; positive regulation of cell proliferation
putative pheromone receptor V2R2B 1.60 0.094 related to Ca2+-sensing receptor and metabotropic
glutamate receptors
monoamine oxidase A - 4.00 0.094behavior; catecholamine catabolism and metabolism;
dopamine metabolism; electron transport; neurotransmitter catabolism
troponin-c -3.90 0.094 Ca2+-bindingsubunit of the troponin complex
QFG-TN1 olfactory receptor 1.46 0.145
G-protein coupled receptor protein signaling pathway;perception of smell, sensory transduction of chemical
stimulus kinesin light chain C -2.06 0.160 unknown
3 significantly down-regulated genes: p21 (c‑Ki‑ras), amino acid transporter system A (ATA2), andphosphate regulating neutral endopeptidase on the X chromosome (PHEX)
Du
al C
han
nel
S
ingl
e C
han
nel
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C E N T R F O R I N T E G R A T I V EB I O I N F O R M A T I C S V U
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PHEX proteases(cathepsin B)
MEPE-ASARM
ASARM
+
MEPE
Enhances mineralization
Inhibits mineralization
Role creatine kinase and troponin-C yet unknown
Changes after loading a bone
Local change in loaded bone
Change in all bones
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Signaling Pathway Map: Epidermal Growth Factor
(Kitano)
Signaling Pathway Map: Concept Map: MAPK
(Van Kampen)
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C E N T R F O R I N T E G R A T I V EB I O I N F O R M A T I C S V U
E
Agenda• Systems Approach
(components and interactions)
• Bioinformatic and Statistical Analysis
(top-down)
• Metabolomics and Fluxomics
(metabolic flux measurements)
• Mechanistic Modeling : modular and multiscale
(bottom-up)
• Summary
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The Airport ExampleWhat do we need to know to determine throughput?
Neither the number of airplanes on the ground ...
… nor the map of the runways ...
is very helpful
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... but the “radar flux” is
informative
The Airport ExampleWhat do we need to know to determine throughput?
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Carbon Transition Networks (CTNs)
Thomas Binsl
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Simulation of glutamate NMR multiplets due to carbon-13 isotope enrichment during infusion of labeled acetate
4-carbon singlet
4-carbon doublet
NMR Spectrum 4-carbon glutamate
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acetyl-CoA
acetate
5 C
tra ns po rt
6 C
4 C
g lu tam a teasp a rta te
une n rich ed su bs tra te s
In Vivo Metabolic Rates Estimated from 13C NMR Spectrum
TCA cycle flux =7.7 µmol/g/min(n = 60)
glutamate content24.6 µmol/g
Transport time29.8 sec (n=7)
58 % acetyl CoAfrom infused acetate (n=36)
Anaplerosis 16 % of TCA cycle flux(n=19)
Transamination 17.4 µmol/g/min(n=9)
TCAcycle
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C E N T R F O R I N T E G R A T I V EB I O I N F O R M A T I C S V U
E
Agenda• Systems Approach
(components and interactions)
• Bioinformatic and Statistical Analysis
(top-down)
• Metabolomics and Fluxomics
(metabolic flux measurements)
• Mechanistic Modeling : modular and multiscale
(bottom-up)
• Summary
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Switching from Google Earth,
To “Google Human”
To “Google Heart”
Computational Model of Essential Parts of Molecular System
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• Big Model Many Trees, Forest Visible?
• Small is Beautiful Well Maintained Garden
The K.I.S.S. Principle
("Keep It Simple, Stupid") or ("Keep It Short and Simple")
Boehringer Pathways
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ATPasePi
ATPADP
MM-CKPCr Cr
Cyt
osol
MOM
MIM
PCrMi-CK
Cr
ATPADP
Inte
rmem
bran
eS
pace
Pi
Pi
ADP ATPOxPhos
Model of High Energy Phosphate Group Handling in Energy Metabolism
Mitochondrial MatrixADP and inorganic phosphate (Pi) enter intermembrane space and stimulate oxidative phosphorylation (OxPhos).
Model Elements :
• two creatine kinase (CK) isoforms
• diffusion & membrane permeation
Communicating Modules:
• ATP consumption (ATPase) as forcing function
• ATP production by mitochondria
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ADP and inorganic phosphate (Pi) enter intermembrane space and stimulate oxidative phosphorylation (OxPhos).
Model Elements :
• two creatine kinase (CK) isoforms
• diffusion & membrane permeation
Communicating Modules:
• ATP consumption (ATPase) as forcing function
• ATP production by mitochondria
ATPasePi
ATPADP
MM-CKPCr Cr
Cyt
osol
MOM
MIM
PCrMi-CK
Cr
ATPADP
Inte
rmem
bran
eS
pace
Pi
Pi
ADP ATPOxPhos
Model of High Energy Phosphate Group Handling in Energy Metabolism
Mitochondrial Matrix
Border of the module
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ATPasePi
ATPADP
MM-CKPCr Cr
Cyt
osol
MOM
MIM
PCrMi-CK
Cr
ATPADP
Inte
rmem
bran
eS
pace
Pi
Pi
ADP ATPOxPhos
Mitochondrial Matrix
? ?
Border of the module
ADP and inorganic phosphate (Pi) enter intermembrane space and stimulate oxidative phosphorylation (OxPhos).
Model Elements :
• two creatine kinase (CK) isoforms
• diffusion & membrane permeation
Communicating Modules:
• ATP consumption (ATPase) as forcing function
• ATP production by mitochondria
Model of High Energy Phosphate Group Handling in Energy Metabolism
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Ingredients for this Simulation
Dynamics of response O2 uptake at whole heart level
Transport time blood vessels and diffusion
Decrease total O2 amount in whole heart Increase O2 uptake heart
NMR determined diffusion coefficients
Mitochondrial Membrane Permeability
Steady state responses isolated mitochondria
Enzyme kinetics of two enzymes
=
Outer Membrane Permeability for ADP = 21 m/s
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Our model analysis implies that in rabbit heart at 487 μM/sec ATP hydrolysis, the diffusion flux carried by PCr
is 154 μM/sec.
This suggests that the PCr shuttle is of minor importance.But what is the function of the two creatine kinase isoforms?
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Effect of creatine kinase expression
level on metabolic
oscillations and on average
concentrations
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Pictorial Summary
Modular Modeling, Using Information from Multiple Scales, makes Systems Accessible to Deep and Wide Analysis
Using stable isotopes to trace networks
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Networks of Correlation
Clish, Van der Greef, Naylor OMICS Vol. 8, 2004
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AcknowledgmentsThomas Binsl
Kate Mullen
Olav Kongas
Mark NobleFrits Prinzen
Joli Bussemaker David Alders
Johan Groeneveld
Lori Gustafson
Koert Zuurbier
Jan Bart Hak
Glenn Harrison
Marcel Eijgelshoven
Bas de Groot
Jaap Heringa
Ivo van Stokkum
Hans van Beek
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C E N T R F O R I N T E G R A T I V EB I O I N F O R M A T I C S V U
E
Threshold False Discovery Rate(Benjamini-Hochberg Linear Stepup)
Rank Order
P v
alue
5 10 15 20 25
0.0
00
00
.00
10
0.0
02
00
.00
30
indexSort[1:25]
ind
exS
ort
[1:2
5]/2
37
5 *
0.2
Linear Stepup Threshold
FDR = 20%
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Time [min]
FluxSimulator (Simulation Results)Is
oto
pom
er
Fra
cti
on
Time (sec)0 100 200
0
1
0
1
Metabolite B
Metabolite D
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Oxygen Consumption by Blood Gas (μmol / g dry /min)
Oxy
gen
Con
sum
pti
on b
y N
MR
Met
hod
(μ
mol
/ g
dry
/min
)
COMPARING THE NEW NMR METHOD WITH OXYGEN
CONSUMPTION MEASURED BY ‘GOLD STANDARD’ (BLOOD GAS)
n = 42 pigs
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ATP ATP
ADP ADP
PCr
Mitochondria Myofibrilcreatine kinase
Module : set of molecular processes performing a cellular function
Functions of the adenine nucleotide-creatine-phosphate module:
1. transfer high-energy phosphate bonds from mitochondria to cytosolic ATPases
2. dynamic adaptation of ATP synthesis to time-varying hydrolysis
3. emergency buffer system
Adenine Nucleotide – Creatine - Phosphate Module
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Predicted oscillation of ADP in cytosol for low permeability of mitochondrial
outer membrane
Membrane Permeability
0.16 m/s(Vendelin, Saks et al. 2000)
ADP levels much too high
Response much too slow
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Isolating the Module under Study Experimentally
Response measured of
venous oxygen in mouse heart
Activation time of oxidative phosporylation
3.7 s
… and Measuring the Response of the System as a Whole
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The response is simplified by removing
pulsatility from the ATP hydrolysis forcing function
5
1
34
2
Membrane Permeability1 = m/s (for sake argument)
2 = 85 m/s (Beard 2006)
3 = 21 m/s (optimised tmito = 3.7 s)
4 = 3.5 m/s (Saks 2003)
5 = 0.16 m/s (Saks 2000)
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Partitioning the Contributions of Mitochondrial and Muscle CK Isoforms
experiment: normal CK
experiment: both CK isoforms inhibited
MM-CK changes
Mi-CK changes
Both CKs change
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59.2 59.4 59.6 59.8 60.0
02
00
04
00
0
Time (s)
AT
P h
ydro
lysi
s (u
M/s
)
59.2 59.4 59.6 59.8 60.0
50
06
50
80
0
Time (s)
AT
P s
ynth
esi
s (u
M/s
)
Time varying load on the mitochondria at
two levels:
First level:
ATP hydrolysis in beating heart muscle pulsates during each
heartbeat
AT
P H
ydro
lysi
s (μ
M/s
)A
TP
Syn
thes
is (
μM
/s)
Time ( s )AT
P H
ydro
lysi
s (μ
M/s
)
Time ( s )
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At t=0 paced heart rate is stepped from 135 to 220 beats/min
Time varying load on the mitochondria at
two levels:
Second level:
Heart rate is variable
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Metabolites in the Same Biochemical Reaction Often Correlate Poorly
ATP Level
(mM)
Phosphocreatine (mM)
AttackStay in Pack
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J. van der Greef (CMSB)
False discovery rate of edges potentially VERY high
Centre for Medical Systems Biology
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Simulation of glutamate NMR multiplets due to carbon-13 isotope enrichment during infusion of labeled acetate
4-carbon singlet
4-carbon doublet
time am
pli
tud
e
TCA cycle
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Systems Consist of Components
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C E N T R F O R I N T E G R A T I V EB I O I N F O R M A T I C S V U
E
Results for Bone :load vs control
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ATPasePi
ATPADP
MM-CKPCr Cr
Cyt
osol
MOM
MIM
PCrMi-CK
Cr
ATPADP
Inte
rmem
bran
eS
pace
Pi
Pi
ADP ATPOxPhos
Mitochondrial Matrix
Outer Membrane Permeability for ADP
21 m/s(tmito optimised to 3.7 s)
Diffusion in Cytosolcharacteristic diffusion time about 0.35 millisec
Outer Membrane Permeability Determined from Functional Response
In Vivo Estimation !
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File 3
FluxSimulator (Network Specification)
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C E N T R F O R I N T E G R A T I V EB I O I N F O R M A T I C S V U
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Organism 1
Organism 2
Environmental State 1Organism 4
Environmental State 1a
Environmental State 2
Organism 1
Organism 3
Ecological System