Metabolic Syndrome workshop
Genome-Scale Metabolic Models and Systems Medicine of Metabolic SyndromeDec. 13, 2013Eindhoven University of Technology, Eindhoven
Natal van Riel Dept. of Biomedical Engineering, TU/e, [email protected] Systems Biology and Metabolic Diseases
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Can we link understanding of metabolism and
biochemistry (incl. modeling)
to the multi-omics data that are collected in
in research projects
and in the clinic of the (near) future
and tendencies towards stratified
and personalized health and healthcare
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Is the time right for application of GSMM’s
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…for a Systems Medicine approach of Metabolic Syndrome?
2007 Recon1(Duarte 2007 PNAS 104(6): 1777)
2010 Hepatonet(Gille 2010 Mol Syst Biol 6:411)
2013 Recon2(Thiele et al. 2013, Nat Biotech.)
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Recon 2
• Genome-Scale Metabolic Model• Total number of reactions 7,440• Total number of metabolites 5,063• Number of unique metabolites 2,626
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http://humanmetabolism.org/
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Genome-scale metabolic reconstructions
Advantages:• Especially good coverage of small, monomeric molecules and
central metabolism• Comprehensive network topology (wiring)
Limitations:• Manual curration needed of many pathways outside central
metabolism• Weak in polymeric metabolites with large heterogeneity, e.g.,
lipids, lipoproteins
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Applications of the global human metabolic network
“Genome-scale metabolic network reconstructions provide a platform to interpret omics data in a biochemically meaningful manner.”• Four classes of application:
1. Integration of ‘omics’ data for tissue and cell specific network reconstruction,
2. Mapping homologous genes for global mammalian network reconstruction,
3. Contextualization of ‘omics’ data from pathological and drug-treated states,
4. Simulation of pathological and drug-treated states
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Example: a metabolic perspective on ADHD, autism• Neurotransmission is disrupted in most psychiatric disorders• Serotonergic system malfunctioning• An underlying metabolic cause
PAGE 7Yap,et al 2010, J Proteome Res 9(6): 2996
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Metabolomics of 24 hour urine
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• Metabolomics(N=362)
• Analysis and interpretation with network model
• Recon2, curated for tryptophan metabolism
Dermois et al
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HUMETICS HUman METabolic diagnostICS
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Network-based analysisAPeT in collaboration with TU/eDermois, van den Eijnde et al
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Integration of multi-omics data
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(A) Gene expression pattern (4 clusters)
(B) Metabolic network expression overlay
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Zelezniak et al, 2010, PLoS Comput Biol 6(4): e1000729.
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Simulation
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COnstraints Based Reconstruction and Analysis (COBRA) methods• So far, just the topology• What about fluxes
• Flux Balance Analysis (FBA)• Flux Variability Analysis (FVA)• …
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Network stoichiometry and Stoichiometric Matrix• A hypothetical network
• Stoichiometry matrix
• Stoichiometric model
with the species concentrations collated in a vector and the reaction rates in a vector
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( ) ( ( ))d t tdt
s Nv s
1 4[ ,..., ]Ts ss1 5[ ,..., ]Tv vv
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Steady-state (‘homeostasis’)
metabolite balancing equation• Set of differential equations set of algebraic equations with
the rates in v unknown
• Here 4 equations (4 species) and 5 unknowns• an under-determined set of equations• not a single solution
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( ) ( ( )) ˆd t tdt
s Nv s 0 Nv 0
1
2
3
4
5
1 0 1 1 0 01 1 0 0 0 01 1 0 0 0 00 0 0 1 1 0
vvvvv
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• Mass balances (Differential Equations)• Steady-state (concentrations constant over time), (Nv = 0)• A metabolic fingerprint / snapshot
• Measurements to constrain the underdetermined system• Isotopic tracers, e.g. 13C
• Solve / simulate with Flux Balance Analysis
Metabolic Balancing Analysis
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0v 1v
0v1v
2v
0v1v
2v
3v
1v
2v
3v1v
2v
System of algebraic equations
An underdetermined system
Flux space
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Analyzing pathway diagrams
• Can be linked to an objective function to be minimized or maximized in FBA
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Two equivalent routes for converting an input substrate into an output metabolite
If we know/assume that the system aims for minimization of total (number of) intracellular fluxes (efficiency), both routes are not equivalent
If the objective is to maximize ATP yield then also only one route will be utilized
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The conceptual basis of Flux Balance Analysis
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N
With no constraints, the flux distribution of a biological network may lie at any point in a solution space
Through optimization of an objective function, FBA can identify a single
optimal flux distribution that lies on the edge of the allowable solution space
mass balance constraints imposed by the stoichiometric matrix N + capacity constraints imposed by the lower and upper bounds (ai and bi) are applied to a
network an allowable solution spaceThe network may acquire any flux distribution within this space, but points
outside this space are denied by the constraintsOrth et al. Nat Biotechnol. 2010; 28(3): 245-248
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A multi-tissue type genome-scale metabolic network
• Implications for blood-based metabolic biomarkers
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Bordbar, et al., I. (2011) BMC Syst. Biol., 5, 180
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Systems medicine and metabolic modelling
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Mardinoglu & Nielsen. J Intern Med 2012; 271:142–154
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Systems medicine and metabolic modelling
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