Spring 2013
BsysE 595
Biosystems Engineering for Fuels and Chemicals
Metabolic pathway alteration,
regulation and control (1)
Xi Wang
01/22/2013
Outline (Topics)
1. Introduction of Cellular Metabolism (Lec 5)
2. Constraint-based Metabolic Network Reconstruction (Lec 5)
3. Flux Balance Analysis of Metabolic Network (Lec 6)
4. COBRA Toolbox (Lec 6)
5. Regulation of Metabolic Pathway (Lec 7)
6. Examples of Metabolic Pathway Modification (Metabolic
Engineering) (Lec 7)
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Topic 1
Topic 2
Topic 3
Topic 4
Topic 5
Topic 6
Topic 1 Introduction of Cellular Metabolism
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What does Metabolic Engineering do?
Altering metabolic pathways to improve cell properties and
produce or overproduction of certain target metabolites
which is interested.
Specifically:
• Improving the production of chemicals already produced by the host
organism,
• Extending the range of substrate for growth and product formation
• Adding new catabolic activities for degradation of toxic chemicals
• Producing chemicals new to the host organism were produced
• Creating situations that contributed to a drastic modification of the
overall cellular properties
(Stephanopoulos GN, 1998)
4
Metabolic Engineering
• Definition of Metabolic Engineering
“Metabolic engineering is the science that combines
systematic analysis of metabolic and other pathways with
molecular biological techniques to improve cellular
properties by designing and implementing rational genetic
modifications.” (Koffas M, et al., 1999)
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Metabolic Engineering Schematic
Flux Quantification
ANALYSIS
MODIFICATION
recombinant
DNA technology
(Koffas M)
Analysis of Flux
Control
Metabolic
Networks
Cell improvement
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The cell as a factory
• The cell is treated as a living chemical factory,
with an input and an output.
D
S
A
B
E
C
P1
(Koffas M)
P
7
Metabolic engineering is an inter-disciplinary
field of study
Metabolic engineering is based on lots of science and technologies:
• Biochemistry
• Genetics
• Cell biology
• Molecular biology
• Chemical engineering
• Bioinformatics
.
.
.
A comprehensive understanding of cellular metabolism is necessary
before engineering a specific pathway.
8
Biochemical reactions
• Assembly reactions carry out chemical modifications of
macromolecules, their transport to prespecified locations in the cell,
and, finally, their association to form cellular structures such as
cell wall, membranes, nucleus, etc.
• Polymerization reactions represent directed, sequential linkage of
activated molecules into long (branched or unbranched) polymeric
chains. These reactions form macromolecules from a moderately
large number of building blocks.
• Biosynthetic reactions produce the building blocks used in the
polymerization reactions. They also produce coenzymes and related
metabolic factors, including signal molecules.
• Fueling reactions produce the 12 precursor metabolites needed
for biosynthesis. Additionally, they generate Gibbs free energy in the
form of ATP, which is used for biosynthesis, polymerization, and
assembling reactions. Finally, the fueling reactions produce reducing
power needed for biosynthesis. The fueling reactions include all
biochemical pathways referred to as catabolic pathways (degrading
and oxidizing substrates).
(Stephanopoulos GN, 1998)
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Overall structure of cell synthesis from sugars
Overall structure of cell synthesis from sugars
(Stephanopoulos GN, 1998)
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Relaxation times
Reaction relevance within a given time frame is usually assessed by
comparing the relaxation times of the various reactions, which are
defined as the characteristic times of the reactions approximated as a
first-order process.
Relaxation times of different cellular processes in comparison with
the relaxation time of bioreactor operation
(Stephanopoulos GN, 1998)
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Pseudo-steady state
• Processes with much larger relaxation times than that of the system
of interest can generally be considered as frozen, e.g., mutations
are normally slow compared to cell growth and therefor they can be
neglected in studies of cellular growth
• Processes that have relaxation times much smaller than that of the
system can normally be considered as being in pseudoequilibrium.
• Enzymatic reactions therefore generally respond rapidly to new
environmental conditions, and a pseudo-steady state in their
reaction rates and related metabolites is obtained.
• Standard: A process can normally be considered at pseudo-steady
state if its relaxation time one-third of the relaxation time of the
system.
(Stephanopoulos GN, 1998)
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Central Carbohydrate Metabolic Network
(Noor E., et al., 2010)
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The 12 Precursor Metabolites
(Noor E., et al., 2010)
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Biochemical reactions direction
• Most of biochemical reactions are reversible. The reaction direction
depends on the thermodynamic favorability (ΔG < 0).
(Last slide of Topic 1)
Metabolic pathway of Glycolysis
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Topic 1
Topic 2
Topic 3
Topic 4
Topic 5
Topic 6
Topic 2 Constraint-based Metabolic Network
Reconstruction
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Metabolic Reconstruction Belongs to
Systems Biology
Systems Biology is the study of the interactions between the
components of biological systems, and how these interactions lead to
the function and behavior of that system (for example, the enzymes
and metabolites in a metabolic pathway)
Systems Biology is based on “Omics” and “Network”:
• Genomics
• Metabolomics & Metabolic network
• Proteomics & Signal transduction network
• Transcriptomics & Transcriptional regulation network
Construction and modeling network models is important in Systems
Biology. The availability of genomic data (genomic sequences and
annotation) enabled the reconstruction of metabolic network for
certain species (Genome-scale model)
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Advances of reconstructed genome-scale model
Legend
Red- Number of organisms;
Blue- Number of reconstructed models
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Genome-scale Metabolic Network
• Genome-scale network contains all of the known metabolic
reactions in an organism and the genes that encode each enzyme
• Metabolic models for more than 30 organisms are available
(http://systemsbiology.ucsd.edu
In_Silico_Organisms/Other_Organisms)
• High-throughput technologies enable the construction of many more
each year
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Application of metabolic network model
• Analysis of high-throughput data
• Metabolic engineering
• Reference for the new hypothesis
• Analysis of difference among species
• In-depth study of metabolic network properties
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The procedure of metabolic network
reconstruction
1.
2.
3.
4.
Draft reconstruction
Refinement of reconstruction
Conversion of reconstruction into computable format
Network evaluation
(Thiele I., et
al., 2010)
Overview of the procedure to iteratively reconstruct metabolic networks
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1. Draft reconstruction
List of Reactions, Metabolites
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2. Refinement of reconstruction content
The draft reconstruction is converted into a integrated reconstruction by
re-evaluation of the content
(Thiele I., et al., 2010)
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3. Conversion of reconstruction into a
condition-specific model
[1] Mathematical representation the network reaction list (stoichiometric matrix)
[2] Define the systems boundaries
[3] Adding constraints
(Thiele I.,
et al.,
2010)
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4. Gap analysis
(Thiele I., et al., 2010)
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Gene-protein-reaction (GPR) associations
Examples of GPR associations and their representation in Boolean
format are shown for Escherichia coli.
(Thiele I., et al., 2010)
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Example: Reconstruction of the metabolic
network of S. cerevisiae
(Forster J et al., 2003)
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Principles of metabolic network model
computation
Algorithm (Constraint based Model)
1. Flux balance analysis (FBA)
2. Minimization of metabolic adjustment (MOMA)
3. Regulatory on/off minimization (ROOM)
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1. Flux balance analysis (FBA)
• FBA uses Linear Programming (LP) to maximize an objective
function under different constraints. In the model, a steadystate flux distribution (v) is looking for maximizing growth rate
under mass balance, thermodynamical, and flux capacity
constraints.
(Shlomi T et al., 2005)
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2. Minimization of metabolic adjustment (MOMA)
• MOMA finds a solution that satisfies the same constraints as
FBA, while minimizing the Euclidean distance from a wild-type
flux distribution (usually obtained previously by FBA).
w is the wild-type flux distribution;
A is a set of reactions associated with the deleted genes
(Shlomi T et al., 2005)
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3. Regulatory on/off minimization (ROOM)
• ROOM finds a flux distribution that satisfies the same
constraints as FBA while minimizing the number of significant
(large enough) flux changes.
(Shlomi T et al., 2005)
For each flux i, 1 i m, yi 1 for a significant flux change in vi and yi 0
otherwise, and wu and wl are thresholds determining significance of the
flux change, with and specifying the relative and absolute ranges of
tolerance, respectively (w and A are as in MOMA).
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Difference between MOMA and ROOM
(Shlomi T et al., 2005)
(a) A given flux distribution for the wild-type intact network that can be
obtained by FBA and experimental flux data. The flux through b2 represents
growth rate. (b) MOMA’s prediction for the knocked-out network following the
knockout of reaction v6. (c) ROOM’s prediction for the knocked-out network
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Definition of metabolic pathway and flux
• Metabolic pathway
Definition: Any sequence of feasible and observable biochemical
reaction steps connecting a specified set of input and output
metabolites.
• Pathway flux
Definition: The rate at which input metabolites are processed to form
output metabolites
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Summary
Topic 1. Introduction of cellular metabolism
• Concept of metabolic engineering
• Biochemical reactions
• Relaxation time, pseudo-steady state
• Central carbon metabolic pathway
Topic 2 Constraint based metabolic network reconstruction
• The procedure of metabolic network reconstruction
• GPR associations
• Algorithm (FBA, MOMA, ROOM)
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Reference
• Textbook
Metabolic Engineering,
Principles and
Methodologies
G.N. Stephanopoulos, A.A.
Aristidou, J. Nielsen
Academic Press, 1998
ISBN: 0-12-666260-6
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Reference
• Forster J, Famili I, Fu P, Palsson B, Nielsen J. Genome-scale
reconstruction of the Saccharomyces cerevisiae metabolic network.
Genome Research. 2003, 13: 244–253.
• Koffas M, Roberge C, Lee K, Stephanopoulos G. Metabolic
engineering. Annu. Rev. Biomed. Eng. 1999, 01: 535–557.
• Noor E, Eden E, Milo R, Alon U. Central carbon metabolism as a
minimal biochemical walk between precursors for biomass and
energy. Molecular Cell. 2010, 39: 809–820.
• Shlomi T, Berkman O, Ruppin E. Regulatory onoff minimization of
metabolic flux changes after genetic perturbations. PNAS. 2005,
102(21): 7695–7700.
• Thiele I, Palsson B. A protocol for generating a high-quality genomescale metabolic reconstruction. Nature Protocols. 2010, 5(1): 93–
121.
• Stephanopoulos GN, Aristidou AA, Nielsen J. Metabolic
Engineering, Principles and Methodologies. Academic Press, 1998.
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Thank you for your attention!
Questions?
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