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A systems biology approach to modelling the heart
Denis NobleUniversity of Oxford
WUN Lecture
14th December 2005
NOBLE, D (2002) Science 295, 1678-1682.
The problem
There are around 25,000 genes in the Human Genome Coding for over 100,000 proteins We know the function of only a very small proportion – genes or proteins
Yet most biological functions depend on many genes & proteins interacting
Illustrative calculation
Assume each function depends on 2 genes(absurd, but still instructive)
Total number of possible ‘functions’ would be0.5 x 25,000 x 24,999
= 312,487,500 With more realistic assumptions about # of genes in each
function, the figures are huge : at 100/function (~ 1.5 e302); for all combinations (~ 2 e166713)
10289
1072403 !
We will only read the “Book of Life” by understanding how genes interact in co-operative ways in complex systems
This means we must unravel & understand biological complexity – i.e. complement reduction with integration
Experimentally and in simulation
The solution
The reductionist causal chain
organism organtissue
cellular sub-
cellularpathwaysprotein
gene
I know one approach that will fail, which is to start with genes, make proteins from them and to try to build things bottom-up
Sydney Brenner, 2001
NOBLE, D (2002) Nature Reviews Molecular Cell Biology 3, 460-463.
Unravelling complexityNeed to work in an integrative way at all levels:
organism organtissue
cellular sub-cellularpathwaysprotein
gene
There are feed-downs as well as upward between all these levels
Systems leveltriggers ofcell signalling
Systems levelcontrols ofgene expression
Protein machineryreads genes
Physiological systems & function
Top-down
Middle-out
Bottom-up
Molecular data & mechanisms
systems organs
tissues cells
pathways organelles
Sydney BrennerNobel Prize2001Middle-out!!
Modeling the heart
Working to connect many levels:
Genetic mutationsProtein function
Cellular machineryTissue function
Whole organ : the Virtual Heart
Modeling the heart
Cell models
1960 : analysis of K+ channels in the heart
-25-50-75-100mV
1
2
-1
-2
current
IK1
IK
Replotted from Hall, Hutter & Noble, 1963Journal of Physiology, 166, 225-240
Model Construction 1960
INa
IK1IK
ICl
Purkinje fibre Channels
Noble, 1960Nature 188, 495-497
Nature’s pact with the devil:
1. The good news
The inward rectifier potassium currentiK1 (Kir2.x)
guarantees energy conservation
Nature’s pact with the devil:
2. The bad news
The delayed potassium currentiKr (HERG + MinK)
is highly promiscuous
Model Construction 2000
INa
IClIK1 IK Ito
ICaChannels
I Na/K
I NaCaNa/H Na/HCO3 Cl/OH
Cl/HCO3
Carriers
Ca
pH
ATP
Glucose
Fatty Acids
Amino Acids
H/Lactate
SubstratesAng II1
2
NO
ßM
Receptors
Example of protein interaction in a cell model Reconstructing the heart’s pacemaker
Sinus rhythm generated by ion channel interaction
ICaL
IKr
Em
If is example of fail-safe ‘redundancy’
Rhythm abolished when interaction prevented
Acceleration of sinus rhythm by adrenaline
If
All 3 protein levels up-regulated
SA node model – ibNa & if
Example of ‘gene knock-out’
Em
If
IbNa
20% 40% 60% 80% 100%
Noble, D., J. C. Denyer, H.F. Brown. & D DiFrancesco (1992). Proc Royal Society B 250: 199-207.
Disease insightModelling arrhythmias
Mutations in various ionic channels can predispose to repolarization failure
This simulation is of a sodium channelmis-sense mutation responsible foridiopathic ventricular fibrillation
Sodium channel molecular structureFour transmembrane domains each with six subunits
Heart sodium channel mutationsgreen : IVF mutations red : long QT mutations
(Chen et al, Nature, 19 March 1998)
Expressed sodium channel kinetics(Chen et al, Nature, 19 March 1998)
Computer model prediction
• Sodium channel missense mutation
• 12 and 18 mV voltage shifts
• Using digital cell ventricular model
12 mVshift18 mVshift
This approach has now been used for a substantial number of gene manipulations in heart cells and can account for genetic susceptibility to fatal cardiac arrhythmia
Including interactions with drugs causing long QT and arrhythmia in clinical trials
Genetic typing to screen out those susceptible to drugs causingQT problems is therefore a foreseeable possibility
Noble D (2002) Unravelling the genetics and mechanisms of cardiac arrhythmia. Proc Natl Acad Sci USA 99, 5755-6
Unravelling genetics of arrhythmia
This example shows
effect of 90% block of IK alone (pure class III)
effect of additional 20% block of Ica,L
Multiple site drugs:QT prolongation without arrhythmia?
• Normal action potential
• Block of IK alone
• Partial block of ICaL
Connecting levels
Incorporation of cellular models into organ models
Multi-level simulations use engineering principles: select lower-level models
using higher-level insights
Noble D (2002) Modelling the heart: from genes to cells to the whole organ. Science 295, 1678-1682
Physiome Sciences
Peter Hunter – the Aucklandmodel ventricle
Launch of ThePhysiome ProjectOf IUPShttp://www.physiome.org.nz
movies
Spread of excitation wave in whole ventricle model
Model – Smith et al Experiment – Nash et al
Spread of excitation wave in whole ventricle model
Model – Smith et al Experiment – Nash et al
Simulation of heart failure EADs leading toTorsades de Pointes arrhythmia
Rai Winslow
Impact-induced arrhythmia Li, Kohl & Trayanova, 2004
Bi-domain modelling with full ionic cell modelsincluding stretch-activated channels
Breakdown of re-entrant arrhythmia into fibrillationSimulation – Panfilov,
Experiment – Witkowsky
Ischaemia ProjectNic Smith – coronary circulation model
INaCa
0 100 200 300
Time (seconds)
20
10
0
[Na+]i
(mM)
Voltage
[Na+ ]i
[Ca2+]i( M)
0
-20
-40
0
-100
1.0
0
INaCa
(nA)
Voltage(mV)
[Ca2+ ]i
Ca oscillator activated as Ca oscillator activated as [Na][Na]ii rises rises
Human cell model
TEN TUSSCHER, NOBLE, D., NOBLE, P. J. & PANFILOV (2004).
A model of the human ventricular myocyte. American Journal of Physiology
286, H1573-1589.
Detailed channel, transporter and SR equations,but computationally very efficient
Human ventricular cell modelClass III induced EAD
[K]o reduced from 5.4 mM to 2.7 mMThen iKr blocked by 90%
mV
seconds
[K]o reduced
iKr blocked by 90%
Re-entrant arrhythmia inhuman model
TEN TUSSCHER & PANFILOV (2004).