Computational Investigation of Intracellular Networks

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

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

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

Gene 1

Gene 2

Phenotype 1

Gene 3

Gene 4 Phenotype 1a

Phenotype 2

Gene 1

Gene 3

Interfaces of Components May Be Damaged during Isolation

Intact System Isolation of Components

Interfaces Damaged during Isolation

Study System at Multiple Scales

Molecules Form Pathways

Pathways Form Cells

Cell Types Form Organs or

Ecosystems

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

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

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.

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

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

Signaling Pathway Map: Epidermal Growth Factor

(Kitano)

Signaling Pathway Map: Concept Map: MAPK

(Van Kampen)

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

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

... but the “radar flux” is

informative

The Airport ExampleWhat do we need to know to determine throughput?

Carbon Transition Networks (CTNs)

Thomas Binsl

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

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

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

Switching from Google Earth,

To “Google Human”

To “Google Heart”

Computational Model of Essential Parts of Molecular System

• 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

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

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

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

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

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?

Effect of creatine kinase expression

level on metabolic

oscillations and on average

concentrations

Pictorial Summary

Modular Modeling, Using Information from Multiple Scales, makes Systems Accessible to Deep and Wide Analysis

Using stable isotopes to trace networks

Networks of Correlation

Clish, Van der Greef, Naylor OMICS Vol. 8, 2004

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

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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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%

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

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

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

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

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

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)

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

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 )

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

Metabolites in the Same Biochemical Reaction Often Correlate Poorly

ATP Level

(mM)

Phosphocreatine (mM)

AttackStay in Pack

J. van der Greef (CMSB)

False discovery rate of edges potentially VERY high

Centre for Medical Systems Biology

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

Systems Consist of Components

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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Results for Bone :load vs control

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 !

File 3

FluxSimulator (Network Specification)

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