1. Web based simulations of
Murine Lipoprotein Metabolism
With the Tiemann et al
(2011) model

2. References
• Christian A.Tiemann, Joep Vanlier, Peter A.J. Hilbers and Natal A.W. van
Riel. Parameter adaptations during phenotype transitions in progressive
diseases BMC Systems Biology 2011, 5:174 doi:10.1186/1752-0509-5-174
• Christian A.Tiemann, Joep Vanlier, Maaike H. Oosterveer, Albert K. Groen,
Peter A.J. Hilbers, Natal A.W. van Riel. Parameter Trajectory Analysis to
Identify Treatment Effects of Pharmacological Interventions
PLoS Comput Biol 9(8): e1003166. doi:10.1371/journal.pcbi.1003166

3. Lipoprotein metabolism – Tiemann et al (2011)
The model we will use in this tutorial is found in the Biomodels
database – Tiemann2011_PhenotypeTransitions

4. Lipoprotein metabolism – Tiemann et al (2011)
This model describes
lipoprotein production,
remodelling and uptake.
It is an ODE (ordinary
differential equation) model,
based on mass-action kinetics.
(For more information on ODE
models, please see
cbio.bmt.tue.nl/resolve)

5. Lipoprotein metabolism – Tiemann et al (2011)
The model was applied to long-term
data of mice undergoing a
pharmaceutical intervention using the
ADAPT method.
Here, we will look at the basal model,
describing the steady-state of wildtype (B6) mice.
While simulating the model, we must
remeber that in the modelling
approach, uncertainty in the data is
taken into account and the included
parameterset is not unique.
However, we can identify some basal
model features.

6. Lipoprotein metabolism – Tiemann et al (2011)
The model contains 11 states
Plasma
•
TG (Triglycerides) in VLDL/IDL/LDL
•
CE (Cholesteryl ester) in VLDL/IDL/LDL
•
CE (Cholesteryl ester) in HDL
Liver
•
TG (Triglycerides)
– cytoplasm
•
CE (Cholesteryl ester)
– cytoplasm
•
TG (Triglycerides)
– endoplasmatic reticulum
•
CE (cholesteryl ester)
– endoplasmatic reticulum
•
FC (Free cholesterol)

7. Lipoprotein metabolism – Tiemann et al (2011)
• In the GeneXplain platform, select:
Tiemann2011_PhenotypeTransitions
• In the bottom left corner, select “Reactions”

8. Lipoprotein metabolism – Tiemann et al (2011)
Using the “reactions” overview, we can investigate the reactions
included in the model.
The model contains different types of reactions
• Conversion
• Production
• Catabolism
• Transportation

9. Hepatic triglyceride accumulation
As an example of model behaviour, here we will investigate the reactions that
may lead to hepatic hepatic triglyceride (TG) accumulation
First, in the “Variables” tab, select only the following variables to plot:
• TG_ER
- triglcyerides in the hepatocyte endoplasmatic reticulum
• TG_cyt
- triglycerides in the cytosol

10. Hepatic triglyceride accumulation
Simulation of the model (play button in “simulation” tab)
should yield:

11. Hepatic triglyceride accumulation
The following processes in the model could contribute to hepatic TG
accumulation:
Process
Reaction
Parameter
Value
De novo lipogenesis
7, 10
reaction_7_v,
reaction_10_v
1.80635E-5,
1.30725E-5
Lipoprotein uptake
16
reaction_16_k1
0.00132591
Lipoprotein TG lipolysis
22
reaction_22_k1
0.0226027
Hepatic FFA uptake
13
reaction_13_k1,
[FFA]
0.0155327,
0.34 mM
VLDL production
14
reaction_14_k1
0.019342
Hepatic TG hydrolysis
8, 11
reaction_8_k1,
reaction_11_k1
0.701735,
0.340947

12. Hepatic triglyceride accumulation
We simulate hepatic TG accumulation by e.g.
1. Increased concentration of FFA
2. Increased de novo lipogenesis
3. Decreased VLDL production

13. 1. Increased concentration of FFA

14. 2. Increased de novo lipogenesis

15. 3. Decreased VLDL production

16. Hepatic triglyceride accumulation
Note the differences in
• The order of magnitude of change of the parameter to cause
a quantitatively similar effect
• The compartment in which the accumulation is seen

17. cbio.bmt.tue.nl/resolve