Download pathway_cell_models_2011

Biological pathway and
systems analysis
An introduction
Biomedicine ‘after the human genome’
Patient
Molecular basis of
disease
Current disease
models
Molecular building
blocks
genes
proteins
very data-rich about genes, genome
organisation, proteins, biochemical
function of individual biomolecules
Patient
Physiology
Clinical data
Molecular basis of
disease
Current disease
models
Molecular building
blocks
genes
proteins
Disease
manifestation in
organs, tissues,
cells
?
Molecular
organisation
Patient
physiology, clinical
data
Complex
disease models
Disease
manifestation in
organs, tissues,
cells
tissues
organs
Computational
modelling
Molecular building
blocks
genes
proteins
Molecular
organisation
Global approaches: Systems Biology
Perturbation
Living cell
Dynamic response
Bioinformatics
Mathematical
modelling
cell network
modelling
Simulation
“Virtual cell”
•Basic principles
•Applied uses, e.g.
drug design
Dynamic biochemistry
• Biomolecular interactions
• Protein-ligand interactions
• Metabolism and signal transduction
• Databases and analysis tools
• Metabolic and signalling simulation
• Metabolic databases and simulation
• Dynamic models of cell signalling
Dynamic Pathway Models
• Forefront of the field of systems biology
• Main types
Metabolic networks
Gene networks
Signal transduction networks
• Two types of formalism appearing in the
literature:
– data mining
 e.g. genome expression at gene or protein level
 contribute to conceptualisations of pathways
– simulations of established conceptualisations
Signalling Pathways Models
Charasunti et al. (2004)
– model of the action of
Gleevec on the Crk-1
pathway in Chronic
Myeloid Leukaemia
(shown in Biocarta)
Dynamic models of cell
signalling
…from pathway interaction
and molecular data
Erk1/Erk2 Mapk
Signaling pathway
…to dynamic models of pathway
function
Schoeberl
et al., 2002
Simulations: Dynamic Pathway Models
Epidermal growth factor (EGF) pathway
•
These have recently come to the
forefront due to emergence of
high-throughput technologies.
•
Composed of theorised/
validated pathways with kinetic
data attached to every
biochemical reaction
- this enables one to simulate the
change in concentrations of the
components of the pathway over
time given initial parameters.
•
Schoeberl et al (2002) Nat. Biotech 20: 370
These concentrations underlie cell
behaviour.
Pathway simulation and analysis software
http://sbml.org
The Systems Biology Markup Language (SBML)
• open interchange format for computer models of biological processes
• useful for models of metabolism, cell signaling, and more
Over 200 software packages today support SBML.
The SBML Software Guide lists different software systems and their
features.
http://bml.org/SBML_Software_Guide
Hunter and Borg (2003)
Hunter and Borg (2003)
•Computer models integrate experimental findings into a comprehensive, quantitative
and mechanistic description of biological behaviour
• When experimental techniques cannot provide data
Hunter and Borg (2003)
Hunter and Borg (2003)
Virtual Physiological Human Project
www.vph-noe.eu/
Virtual Physiological Human
Simulation of complex models of cells, tissues and organs
www.vph-noe.eu
•Heart modelling: 40+ years of mathematical modeling of
electrophysiology and tissue mechanics
•New models integrate molecular mechanisms and large-scale gene
expression profiles
patient
integration across scales through
computational modelling
organ
Anatomy and integrative
function, electrical dynamics
Vessels, circulatory flow,
exchanges, energy metabolism
cell
Cell models, ion fluxes,
action potential, molecules,
functional genomics
Computer modelling of the heart
• Pacemaker rhythm in the heart is integrated at the level of the cell
• No oscillator at the biochemical level of subcellular protein networks
(Noble 2006)
• No ‘gene for’ pacemaker rhythm
• A set of proteins together with the cellular architecture
• Computer programs can mimic pacemaker rhythm
• Computer programs are representations of the processes involved
at all the relevant biological levels
• Long-term aim: Investigate cardiac function of a specific person
Computer modelling of the heart
• Mathematical reconstruction of the nerve impulse (Alan Hodgkin &
Andrew Huxley 1952)
• Denis Noble applied their ideas to reconstructing the electrical
functioning of the heart at UCL (Noble 1960,1962)
– long-lasting action potential and pacemaker potential of cardiac muscle
• Computer models for studying bioelectrical activity at the tissue level
(Spach 1983; Barr & Plonsey 1984; Spach &Kootsey 1985)
Linking a genetic defect to its cellular
phenotype in a cardiac arrhythmia
• Genetic defects in ion-channels are typically studied in isolated
expression systems
– away from the cellular environment where they function physiologically
• A connection between molecular findings and the physiology of the
cell is difficult to establish
Clancy and Rudy (1999)
Linking a genetic defect to its cellular
phenotype in a cardiac arrhythmia
• Genetic mutations in the SCN5A gene give rise to a congenital form
of the ‘long-QTsyndrome’
• http://www.mykentuckyheart.com/information/LongQTSyndrome.htm
– substantial prolongation of the QT interval on the
electrocardiogram, which may precede sudden
cardiac death
• Mapped to the alpha-subunit of the cardiac sodium channel (LQT3)
• DKPQ mutation most severe: deletion of Lys 1505, Pro 1506 and
Gln 1507 in the highly conserved portion responsible for fast
inactivation
Markovian model represents discrete structural states and their interactions
A mutation affecting the structural integrity of a particular state will affect adjacent states
Integration of single channels (wild-type or mutant) into the whole cell where effects on cell
behaviour can be studied
Clancy and Rudy (1999) Nature 400: 566–569
Spatial distribution of key proteins
• Transmural expression differences of an ion channel protein leads to
different action potential profiles at the epicardium, midwall and
endocardium
• Arrhythmias
Hunter et al (2005) Mechanisms of Ageing and Development
126:187–192.
The hallmarks of systems biology
• a careful series of observations and calculations
• an iterative process of modelling and experimental
validation
• from pathways to cells to organs…
The hallmarks of systems biology
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formulate a general or specific question
define the components of a biological system
collect previous relevant datasets
integrate them to formulate an initial model of the system
generate testable predictions and hypotheses
systematically perturb the components of the system
experimentally or through simulation
study the results
compare the responses observed to those predicted by the
model
refine the model so that its predictions fit best to the
experimental observations
conceive and test new experimental perturbations to
distinguish between the multiple competing hypotheses
iterate the process until a suitable response to the initial
question is obtained