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Computational Modeling of Hepatic Lipid and Lipoprotein Metabolism
NCSB / NBIC Modelers-Bioinformatics Meeting
26-02-2010
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Overall aim:
Development of mathematical models describing lipid and carbohydrate metabolism at whole body and organ specific level in mice
Leiden University Medical Center BioModeling & bioInformatics Biomedical NMR
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triglyceridecholesterol ester
VLDL
IDLLDL
FFA
HDL
chylomicronremnants
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Véniant et al.
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TGTG
Liang et al.Zhang et al.Boogaerts et al.
TG
TG
Grefhorst et al.Davis et al.Dixon et al.
TG
Millar et al.Wong et al.Horton et al.
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FA metabolism
Lipogenesis
Lipolysis
Ketogenesis
apoB metabolism
Remnant catabolism
NEFA
Part I Part II
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GPAT / AGPAT
G3P
LPA
PA
DAG
FA
Glycerol
DGAT1
TG
PPAP2
FA
FA FA
GPAT / AGPAT
MG
TGH
HSL:FABP4
HSL:FABP4
FA
MGL
FA
GK
HSL:FABP4
C
CE
FAFA
ACAT
TG CE
Apo B
Apo B
FFA
FAFA
TG / CE / Glycerol
MTP
DGAT2
FAFAS
MGK
G3P
DGK
MGAT
Liver
Peripheral
Lipoprotein Type Matrix
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GPAT / AGPAT
G3P
LPA
PA
DAG
FA
Glycerol
DGAT1
TG
PPAP2
FA
FA FA
GPAT / AGPAT
MG
TGH
HSL:FABP4
HSL:FABP4
FA
MGL
FA
GK
HSL:FABP4
C
CE
FAFA
ACAT
TG CE
Apo B
Apo B
FFA
FAFA
TG / CE / Glycerol
MTP
DGAT2
FAFAS
MGK
G3P
DGK
MGAT
Liver
Peripheral
Lipoprotein Type Matrix
, , , ,
, , , , , , , ,
[ ][ ] [ ] [ ] [ ][ ]
[ ][ ] [ ] [ ] [ ]DAG MG MG GLC MG LPA MG DAG
m DAG MG m MG GLC m MG LPA m MG DAG
V MG FA V MG V MG V MGd MG
dt K MG FA K MG K MG K MG
, , ,
, , , , , ,
[ ] [ ][ ] [ ][ ]
[ ] [ ][ ] [ ]C C CE CE C
Cm C m C CE m CE C
V C V C FA V CEd CV
dt K C K C FA K CE
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GPAT / AGPAT
G3P
LPA
PA
DAG
FA
Glycerol
DGAT1
TG
PPAP2
FA
FA FA
GPAT / AGPAT
MG
TGH
HSL:FABP4
HSL:FABP4
FA
MGL
FA
GK
HSL:FABP4
C
CE
FAFA
ACAT
TG CE
Apo B
Apo B
FFA
FAFA
TG / CE / Glycerol
MTP
DGAT2
FAFAS
MGK
G3P
DGK
MGAT
Liver
Peripheral
Lipoprotein Type Matrix
, , , ,
, , , , , , , ,
[ ][ ] [ ] [ ] [ ][ ]
[ ][ ] [ ] [ ] [ ]DAG MG MG GLC MG LPA MG DAG
m DAG MG m MG GLC m MG LPA m MG DAG
V MG FA V MG V MG V MGd MG
dt K MG FA K MG K MG K MG
, , ,
, , , , , ,
[ ] [ ][ ] [ ][ ]
[ ] [ ][ ] [ ]C C CE CE C
Cm C m C CE m CE C
V C V C FA V CEd CV
dt K C K C FA K CE
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LiteratureQuantitative data generation
Bijland et al.
Exhaustingly searching for
kinetic parameters and specie
concentrations
parameter estimation
• Text mining techniques to infer quantitative information (PHASAR / BioMeta)
• Inferring pathway topologies in a more structured way
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GPAT / AGPAT
G3P
LPA
PA
DAG
FA
Glycerol
DGAT1
TG
PPAP2
FA
FA FA
GPAT / AGPAT
MG
TGH
HSL:FABP4
HSL:FABP4
FA
MGL
FA
GK
HSL:FABP4
C
CE
FAFA
ACAT
TG CE
Apo B
Apo B
FFA
FAFA
TG / CE / Glycerol
MTP
DGAT2
FAFAS
MGK
G3P
DGK
MGAT
Liver
Peripheral
Lipoprotein Type Matrix
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cholesterol
trig
lyce
ride
0 1000 2000
0
500
0
100
00
Cholesterol: 1000Triglyceride: 5000
particle uptake
hydrolysis
Different lipoprotein types− Based on triglyceride and cholesterol content− Color represents concentration of lipoprotein type
content transfer
VLDL production
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cholesterol
trig
lyce
ride
• VLDL production
• Particle uptake
• Hydrolysis
• CETP
910
• Apo B
• TG• CE
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cholesterol
trig
lyce
ride
• VLDL production
• Particle uptake
• Hydrolysis
• CETP
109
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cholesterol
trig
lyce
ride
109
1
• VLDL production
• Particle uptake
• Hydrolysis
• CETP
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cholesterol
trig
lyce
ride
10 10
1
9 9
1
• VLDL production
• Particle uptake
• Hydrolysis
• CETP
CETP
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Acknowledgements
Peter Hilbers Natal van Riel Jeroen Jeneson Joep VanlierJoep SchmitzÇeylan Cölmekçi
Ko Willems van DijkJan Bert van Klinken Sjoerd van den Berg Silvia Bijland