Transcript metabolic pathways - MPG Systems Biology Forum

Elucidating the Roadmap
of Metabolism by Pathway Analysis
Stefan Schuster
Friedrich Schiller University Jena
Dept. of Bioinformatics
Topics of this talk:
Introduction
• Metabolism is bridge between genotype and
phenotype
• Networks of metabolic reactions are complex due
to their size and the presence of bimolecular
reactions
• Many kinetic parameters unknown. Maximal
velocities depend on enzyme concentrations
„Roadmap“ as a metaphor
Roads form
simple graph
Metabolism is
hypergraph
Technologically relevant metabolic
syntheses:
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Antibiotics by fungi
Ethanol by yeast
Amino acids by bacteria
Dyes
Perfumes
etc. etc.
Theoretical Methods
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Dynamic Simulation
Stability and bifurcation analyses
Metabolic Control Analysis (MCA)
Metabolic Pathway Analysis
Metabolic Flux Analysis (MFA)
Optimization, Evolutionary Game
Theory
• and others
Theoretical Methods
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Dynamic Simulation
Stability and bifurcation analyses
Metabolic Control Analysis (MCA)
Metabolic Pathway Analysis
Metabolic Flux Analysis (MFA)
Optimization, Evolutionary Game
Theory
• and others
Metabolic Pathway Analysis (or
Metabolic Network Analysis)
• Decomposition of the network into
the smallest functional entities
(metabolic pathways)
• Does not require knowledge of
kinetic parameters!!
• Uses stoichiometric coefficients
and reversibility/irreversibility of
reactions
History of pathway analysis
• „Direct mechanisms“ in chemistry (Milner 1964,
Happel & Sellers 1982)
• Clarke 1980 „extreme currents“
• Seressiotis & Bailey 1986 „biochemical pathways“
• Leiser & Blum 1987 „fundamental modes“
• Mavrovouniotis et al. 1990 „biochemical pathways“
• Fell (1990) „linearly independent basis vectors“
• Schuster & Hilgetag 1994 „elementary flux modes“
• Liao et al. 1996 „basic reaction modes“
• Schilling, Letscher and Palsson 2000 „extreme
pathways“
Mathematical background
Steady-state condition NV(S) = 0
If the kinetic parameters were known, this could be solved for S.
If not, one can try to solve it for V. The equation system is
linear in V. However, usually there is a manifold of solutions.
Mathematically: kernel (null-space) of N. Spanned by basis
vectors. These are not unique.
non-elementary flux mode
elementary flux modes
S. Schuster et al.: J. Biol. Syst. 2 (1994) 165-182;
Trends Biotechnol. 17 (1999) 53-60;
Nature Biotechnol. 18 (2000) 326-332
An elementary mode is a minimal set of enzymes that
can operate at steady state with all irreversible reactions
used in the appropriate direction
All flux distributions in the living cell are non-negative
linear combinations of elementary modes
Related concept: Extreme pathway (C.H. Schilling,
D. Letscher and B.O. Palsson, J. theor. Biol. 203 (2000) 229)
- distinction between internal and exchange reactions,
all internal reversible reactions are split up into forward
and reverse steps
Mathematical background (2)
Steady-state condition NV = 0
Sign restriction for irreversible fluxes: Virr
0
This represents a linear equation/inequality system.
Solution is a convex region.
All edges correspond to elementary modes.
In addition, there may be elementary modes in the interior.
Geometrical interpretation
Elementary modes correspond to generating vectors
(edges) of a convex polyhedral cone (= pyramid)
in flux space (if all modes are irreversible)
Rate 3
Rate 2
generating vectors
Rate of enzyme 1
Software for computing elementary modes
EMPATH (in SmallTalk) - J. Woods
METATOOL (in C++) - Th. Pfeiffer, F. Moldenhauer,
A. von Kamp
Included in GEPASI - P. Mendes
and JARNAC - H. Sauro
part of METAFLUX (in MAPLE) - K. Mauch
part of FluxAnalyzer (in MATLAB) - S. Klamt
part of ScrumPy (in Python) - M. Poolman
Alternative algorithm in MATLAB – C. Wagner (Bern)
On-line computation:
pHpMetatool - H. Höpfner, M. Lange
http://pgrc-03.ipk-gatersleben.de/tools/phpMetatool/index.php
Biochemical Applications:
1. Can sugars be produced
from lipids?
• Known in biochemistry for a long time that many bacteria
and plants can produce sugars from lipids (via C2 units)
while animals cannot
Glucose
AcCoA is linked with glucose by a chain
of reactions. However, no elementary
mode realizes this conversion in the
absence of the glyoxylate shunt.
CO2
PEP
Pyr
AcCoA
Cit
Oxac
CO2
IsoCit
Mal
CO2
OG
Fum
Succ
SucCoA
CO2
Glucose
Elementary mode representing
conversion of AcCoA into glucose.
It requires the glyoxylate shunt.
CO2
PEP
AcCoA
Pyr
Cit
Oxac
CO2
Mal
Mas
Gly
Icl
IsoCit
OG
Fum
Succ
SucCoA
CO2
CO2
The glyoxylate shunt is present in green plants
and many bacteria (e.g. E. coli).
This example shows that a description by usual
graphs in the sense of graph theory is insufficient…
S. Schuster, D.A. Fell: Modelling and simulating metabolic networks.
In: Bioinformatics: From Genomes to Therapies (T. Lengauer, ed.)
Wiley-VCH, Weinheim, in press.
A successful theoretical prediction
Glucose
PEP
Pyr
Oxac
Red elementary mode: Usual TCA cycle
Green elementary mode: Catabolic pathway
predicted in Liao et al. (1996) and Schuster
et al. (1999). Experimental hints in Wick et al.
(2001). Experimental proof in:
E. Fischer and U. Sauer:
CO2
A novel metabolic cycle catalyzes
AcCoA glucose oxidation and anaplerosis
in hungry Escherichia coli,
J. Biol. Chem. 278 (2003)
Cit
46446–46451
CO2
Mal
IsoCit
Gly
OG
Fum
Succ
SucCoA
CO2
CO2
2. Crassulacean Acid Metabolism (CAM)
• Variant of photosynthesis employed
by a range of plants (e.g. cacti) as
an adaptation to arid conditions
• To reduce water loss, stomata are
closed during daytime
• At nighttime, PEP + CO2 
oxaloacetate  malate
• At daytime, malate  pyruvate (or
PEP) + CO2  carbohydrates
CAM metabolism during daytime
Pi
hexose
Pi
starch
7
5
RBP
9
TP
TP
Pi
2
Pi
PEP
3
PEP
11
Pi
oxac
CO
2
mal
1
cytosol
8
12
4
CO
CO
Pi
6
Pi
2
pyr
10
pyr
chloroplast
2
Elementary modes
A)
B)
P
hexose
P
CO
RBP
TP
TP
P
P
i
PEP
P
CO
mal
i
i
P
CO
P
i
pyr
chloroplast
Hexose synthesis via
malic enzyme as occurring
in Agavaceae and
Dracaenaceae
Dracaena
starch
i
RBP
2
TP
TP
P
P
i
PEP
P
oxac
i
2
i
CO
2
PEP
pyr
cytosol
P
CO
P
hexose
starch
i
2
oxac
i
CO
mal
i
PEP
i
P
i
P
2
pyr
cytosol
2
i
pyr
chloroplast
Starch synthesis via
malic enzyme as occurring
in Cactaceae and
Crassulacea
Ferocactus
C)
P
hexose
P
CO
i
RBP
TP
TP
P
P
i
PEP
P
CO
mal
i
i
P
CO
P
starch
i
RBP
2
i
pyr
chloroplast
Simultaneous starch and
hexose synthesis via malic
enzyme as occurring in:
Clusia
minor
TP
TP
P
P
i
PEP
P
oxac
i
2
i
2
PEP
pyr
cytosol
CO
P
hexose
starch
P
2
oxac
D)
i
CO
mal
2
i
PEP
i
P
i
P
2
pyr
cytosol
CO
pyr
i
chloroplast
Hexose synthesis via PEPCK
as occurring in Clusia rosea
and in:
Ananus comosus =
pineapple
F)
E)
P
hexose
P
RBP
P
oxac
CO
mal
P
CO
i
P
pyr
Pi
chloroplast
Starch synthesis via
PEPCK as occurring
in Asclepadiaceae
Caralluma
hexagona
i
PEP
2
oxac
i
2
starch
RBP
TP
PEP
pyr
cytosol
CO 2
Pi
i
PEP
Pi
Pi
TP
P
2
hexose
starch
i
TP
CO
i
CO
mal
Pi
cytosol
TP
Pi
PEP
P
i
2
pyr
CO 2
pyr
Pi
chloroplast
Simultaneous starch and
hexose synthesis via PEPCK
as occurring in:
Aloe vera
„Pure“ pathways
• In a review by Christopher and Holtum (1996), only
cases A), B), D), and E) were given as “pure”
functionalities. F) was considered as a superposition,
and C) was not mentioned.
• However, F) is an elementary mode as well, although it
produces two products. It does not use the triose
phosphate transporter
• The systematic overview provided by elementary modes
enables one to look for missing examples. Case C) is
indeed realized in Clusia minor (Borland et al, 1994).
• Interestingly, (almost) pure elementary modes are
realized here, although this should reduce robustness
S. Schuster, D.A. Fell: Modelling and simulating metabolic networks.
In: Bioinformatics: From Genomes to Therapies (T. Lengauer, ed.)
Wiley-VCH, Weinheim, in press.
3. Adenine and adenosine
salvage pathways
• Human erythrocytes cannot synthesize nucleotide
phosphates de novo
• They can recycle nucleotides to give nucleotide
phosphates
• In particular, they can recycle adenine and adenosine,
but not hypoxanthine
S. Schuster, D. Kenanov: Adenine and adenosine salvage
pathways in erythrocytes and the role of S-adenosylhomocysteine
hydrolase – A theoretical study using elementary flux modes.
FEBS J. 272 (2005) 5278-5290.
membrane
DPGM
GLCim
GLCext
GLC
HK
PGI
G6P
G6PDH
GL6PDH
ADP
2GSH
GSSGR
RU5P
R5P
NADH
ADP
GSSG
TKI
S7P
TA
F6P
X5P
GA3P
PYRext
LACtrans
LAC
LACext
PRM
ATP
HGPRT
ADPRT
ADENINE
AMP
AMPDA
SAHH2
ApK
S-AdoHcy
MetAcc
Acc
MT
SAM
SAMext
ATP
AMP
ADP
SAHH1
HCY
AK
ADP
NUC
ADA
NUC
ADO
+
AMP
R1P
PRPP
HYPX
IMP
PRPP
3'KetoRibose
HCY
K
PYRtrans
E4P
R5P
ATP
leak
PYR
NAD
GA3P
ADP
+
ATP
NADH
LDH
Na
K
ADP
EN
PEP
PK
PRPPsyn
NaK ATPase
K
PGM
2PG
GSHox
+
+
3PG
ATP
DHAP
leak
+
NAD
PGK
1,3 DPG
TKII
Xu5PE
Na
GAPDH
GA3P
TPI
NADPH
R5PI
CO2
ALD
FDP
NADP
GL6P
PGLase
GO6P
+
PFK
ATP
ATP ADP
Na
F6P
2,3DPG
DPGase
INO
HXtrans
PNPase
HYPXext
Question
• As salvage pathways use enzymes
consuming ATP as well as enzymes
producing ATP, it is not easy to see
whether a net synthesis of ATP is possible.
• Invest ATP to gain ATP - Bootstrapping like
Baron Münchhausen?
Goal:
• Analyse theoretically how many salvage
pathways exist
• Which enzymes involves each of these
and in what flux proportions (i.e. relative
fluxes)
• Compute the net overall stoichiometry of
ATP anabolism
• Medical impact of enzyme deficiencies
External metabolites
• Adenine or adenosine depending on which
salvage is analysed
• glucose, lactate, CO2, ATP
• hypoxanthine, sodium and potassium
outside the cell
Adenine as a source
•
•
•
•
153 elementary modes
4 of these produce ATP
ATP per adenine yield: 1:1
ATP per glucose yields: 3:10, 2:7, 1:4, 1:6
membrane
DPGM
GLCim
GLCext
GLC
HK
PGI
G6P
G6PDH
GL6PDH
ADP
2GSH
GSSGR
RU5P
R5P
NADH
ADP
GSSG
TKI
S7P
TA
F6P
X5P
GA3P
PYRext
LACtrans
LAC
LACext
PRM
ATP
HGPRT
ADPRT
ADENINE
AMP
AMPDA
SAHH2
ApK
S-AdoHcy
MetAcc
Acc
MT
SAM
ATP
AMP
ADP
INO
HXtrans
PNPase
HCY
AK
ADP
NUC
ADA
NUC
ADO
+
R1P
PRPP
HYPX
IMP
PRPP
3'KetoRibose
HCY
K
PYRtrans
E4P
R5P
ATP
leak
PYR
NAD
GA3P
ADP
+
ATP
NADH
LDH
Na
K
ADP
EN
PEP
PK
PRPPsyn
NaK ATPase
K
PGM
2PG
GSHox
+
+
3PG
ATP
DHAP
leak
+
NAD
PGK
1,3 DPG
TKII
Xu5PE
Na
GAPDH
GA3P
TPI
NADPH
R5PI
CO2
ALD
FDP
NADP
GL6P
PGLase
GO6P
+
PFK
ATP
ATP ADP
Na
F6P
2,3DPG
DPGase
AMP
SAHH1
SAMext
Elementary mode with highest ATP:glucose yield (3:10)
HYPXext
membrane
DPGM
GLCim
GLCext
GLC
HK
PGI
G6P
G6PDH
GL6PDH
ADP
2GSH
GSSGR
RU5P
R5P
NADH
ADP
GSSG
TKI
S7P
TA
F6P
X5P
GA3P
PYRext
LACtrans
LAC
LACext
PRM
ATP
HGPRT
ADPRT
ADENINE
AMP
AMPDA
SAHH2
ApK
S-AdoHcy
MetAcc
Acc
MT
SAM
ATP
AMP
ADP
INO
HCY
AK
ADP
NUC
ADA
NUC
ADO
+
R1P
PRPP
HYPX
IMP
PRPP
3'KetoRibose
HCY
K
PYRtrans
E4P
R5P
ATP
leak
PYR
NAD
GA3P
ADP
+
ATP
NADH
LDH
Na
K
ADP
EN
PEP
PK
PRPPsyn
NaK ATPase
K
PGM
2PG
GSHox
+
+
3PG
ATP
DHAP
leak
+
NAD
PGK
1,3 DPG
TKII
Xu5PE
Na
GAPDH
GA3P
TPI
NADPH
R5PI
CO2
ALD
FDP
NADP
GL6P
PGLase
GO6P
+
PFK
ATP
ATP ADP
Na
F6P
2,3DPG
DPGase
AMP
SAHH1
SAMext
Elementary mode with lowest ATP:glucose yield (1:6)
HXtrans
PNPase
HYPXext
Adenosine as a source
• 97 elementary modes
• 12 of these produce ATP
• ATP per adenosine yield: 1:1, 2:3, 5:8,
8:17, 2:5, 5:14, and 1:4.
• ATP per glucose yields: 1:1, 5:6, 2:3, 5:9,
1:3, 1:6, and: 1:0!!
• When ATP/glucose = 1:0, then all
adenosine is used as exclusive energy
source
membrane
DPGM
GLCim
GLCext
GLC
HK
PGI
G6P
G6PDH
GL6PDH
ADP
2GSH
GSSGR
RU5P
R5P
NADH
ADP
GSSG
TKI
S7P
TA
F6P
X5P
GA3P
PYRext
LACtrans
LAC
LACext
PRM
ATP
HGPRT
ADPRT
ADENINE
AMP
AMPDA
SAHH2
ApK
S-AdoHcy
MetAcc
Acc
MT
SAM
ATP
AMP
ADP
INO
HXtrans
HYPXext
PNPase
HCY
AK
ADP
NUC
ADA
NUC
ADO
+
R1P
PRPP
HYPX
IMP
PRPP
3'KetoRibose
HCY
K
PYRtrans
E4P
R5P
ATP
leak
PYR
NAD
GA3P
ADP
+
ATP
NADH
LDH
Na
K
ADP
EN
PEP
PK
PRPPsyn
NaK ATPase
K
PGM
2PG
GSHox
+
+
3PG
ATP
DHAP
leak
+
NAD
PGK
1,3 DPG
TKII
Xu5PE
Na
GAPDH
GA3P
TPI
NADPH
R5PI
CO2
ALD
FDP
NADP
GL6P
PGLase
GO6P
+
PFK
ATP
ATP ADP
Na
F6P
2,3DPG
DPGase
AMP
SAHH1
SAMext
One elementary mode using adenosine as energy and nucleotide source
2.3-Diphosphoglycerate bypass
• Neither for adenine nor adenosine
salvage, any elementary mode involves
the 2.3DPG bypass
• ATP balance would not be positive
anymore
Molar investment ratio
moles of ATP consumed
moles of ATP produced - moles of ATP consumed
In glycolysis:
2
=1
4-2
In elementary mode 1 of adenine salvage, this ratio is
18:(20-18) = 9:1.
S. Schuster, D. Kenanov: FEBS J. 272 (2005) 5278-5290.
Maximization of tryptophan:glucose yield
Model of 65 reactions in the central metabolism of E. coli.
26 elementary modes. 2 modes with highest tryptophan:
glucose yield: 0.451.
PEP
Pyr
S. Schuster, T. Dandekar, D.A. Fell,
Trends Biotechnol. 17 (1999) 53
Glc
233
G6P
Anthr
3PG
PrpP
GAP
105
Trp
Conclusions
• Elementary modes are an appropriate concept
to describe biochemical pathways
• Information about network structure can be
used to derive far-reaching conclusions about
performance of metabolism
• Elementary modes reflect specific
characteristics of metabolic networks such as
steady-state mass flow, thermodynamic
constraints and and the systemic interactions
(Systems Biology)
Conclusions (2)
• It can be tested whether connected routes can
function at steady state
• A complete list of potential pathways can be
generated. Thereafter, experimental search for
realized pathways.
• Pathway analysis is well-suited for computing
maximal and submaximal molar yields
Cooperations
•Steffen Klamt, Jörg Stelling, Ernst Dieter Gilles
(MPI Magdeburg)
•Thomas Dandekar (U Würzburg)
•David Fell (Brookes U Oxford)
•Thomas Pfeiffer, Sebastian Bonhoeffer (ETH Zürich)
•Thomas Wilhelm (IMB Jena)
•Reinhart Heinrich, Thomas Höfer (HU Berlin)
•Marko Marhl (U Maribor, Slovenia)
•Hans Westerhoff (VU Amsterdam)
• and others
•Acknowledgement to DFG and BMBF for financial
support
Current group members
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•
•
•
•
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•
Dr. Axel von Kamp
Dr. Ina Weiß
Dimitar Kenanov
Jörn Behre
Beate Knoke
Ralf Bortfeldt
Gunter Neumann