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Metabolic Flux Analysis. Metabolic Flux Analysis of Citric Acid Fermentation by Candida lipolytica Presentation by: Miles Beamguard and Wade Mack September 19, 2001. Case Study. - PowerPoint PPT Presentation
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Metabolic Flux Analysis
Metabolic Flux Analysis of Citric Acid Fermentation by Candida lipolytica
Presentation by:
Miles Beamguard and Wade Mack
September 19, 2001
Case Study
Aiba, S. & Matsuoka, M. (1979). Identification of metabolic model: Citrate production from glucose by Candida lipolytica. Biotechnology and Bioengineering. 21, 1373-1386.
Considered the first application of metabolite balancing to fermentation data
Objectives of Presentation
Outline Objectives of Case Study Analyze their reaction equations using
matrix algebra calculations Discuss the relevance of the matrix analysis
approach to metabolite modeling
Objectives of Presentation
Outline Objectives of Case Study Analyze their reaction equations using
matrix algebra calculations Discuss the relevance of the matrix analysis
approach to metabolite modeling
Objectives of Case Study
Analyze the metabolic network Form reaction equations Determine some variables through
experimental data Reduce unknowns by a selected model
Metabolic Network
Glucose
CO2
ICT
Protein
GOX
CO2
OGT
CO2
MAL
SUC
AcCoA
CITOAA
Glucose-6-P
Lipid
CO2Pyruvate
Carbohydrates
CO2
Isocitrate
Citratev6 v17
v14
v16v4
v3
v2
v1
v10
v18
v8
v15v9
v13
v12
v7
v5
v11
Reaction Rate Equations
G6P : v1 - v2/2 – v3 = 0
Pyr : v2 – v4 – v5 = 0
AcCoA : v4 – v6 – v13 – v14 = 0
CIT : v6 – v7 – v17 = 0
ICT : v7 – v8 – v12 – v18 = 0
OGT : v8 – v9 – v15 = 0
SUC : v9 – v10 + v12 = 0
MAL : v10 – v11 + v13 = 0
GOX : v12 - v13 = 0
OOA : v5 + v11 – v6 = 0
CO2 : v4 + v8 + v9 – v16 = 0
Determining Known Variables
Elimination of v13 due to glyoxylate reaction equal to v12
18 reaction rates but only 11 balance equations resulting in 7 degrees of freedom
Measurement within network led to empirical solving for 6 reaction rates.
6 Measured Reaction Rates
Glucose Uptake Rate (rglc) = v1
Carbon Dioxide Production Rate (rc) = v16
Citric Acid Production Rate (rcit) = v17
Isocitrate Production Rate(rict) = v18
Protein Synthesis Rate (rprot) = v15
Carbohydrate Synthesis Rate (rcar) = v3
Select A Model
With 12 unknown reaction rates and 11 balance equations we have 1 degree of freedom, so a model must be assumed.
Model 1 – The glyoxylate shunt is inactive, v12 = 0
Metabolic Network
Glucose
CO2
ICT
Protein
GOX
CO2
OGT
CO2
MAL
SUC
AcCoA
CITOAA
Glucose-6-P
Lipid
CO2Pyruvate
Carbohydrates
CO2
Isocitrate
Citratev6 v17
v14
v16v4
v3
v2
v1
v10
v18
v8
v15v9
v13
v12
v7
v5
v11
Select A Model
With 12 unknown reaction rates and 11 balance equations we have 1 degree of freedom, so a model must be assumed.
Model 1 – The glyoxylate shunt is inactive, v12 = 0
Model 2 – Pyruvate carboxylation is inactive, v5 = 0
Metabolic Network
Glucose
CO2
ICT
Protein
GOX
CO2
OGT
CO2
MAL
SUC
AcCoA
CITOAA
Glucose-6-P
Lipid
CO2Pyruvate
Carbohydrates
CO2
Isocitrate
Citratev6 v17
v14
v16v4
v3
v2
v1
v10
v18
v8
v15v9
v13
v12
v7
v5
v11
Select A Model
With 12 unknown reaction rates and 11 balance equations we have 1 degree of freedom, so a model must be assumed.
Model 1 – The glyoxylate shunt is inactive, v12 = 0
Model 2 – Pyruvate carboxylation is inactive, v5 = 0
Model 3 – The Tricarboxylic Acid cycle was nullified, v9 = 0
Metabolic Network
Glucose
CO2
ICT
Protein
GOX
CO2
OGT
CO2
MAL
SUC
AcCoA
CITOAA
Glucose-6-P
Lipid
CO2Pyruvate
Carbohydrates
CO2
Isocitrate
Citratev6 v17
v14
v16v4
v3
v2
v1
v10
v18
v8
v15v9
v13
v12
v7
v5
v11
Which Model?????
Verification of Carbon Fluxes Examination of the free-energy change at the
biochemical standard state After review, both models 2 and 3 resulted in
a negative carbon flux and free energy change and thus were discarded.
Objectives of Presentation
Outline Objectives of Case Study Analyze their reaction equations using
matrix algebra calculations Discuss the relevance of the matrix analysis
approach to metabolite modeling
Reaction Rate Equations
G6P : v1 - v2/2 – v3 = 0
Pyr : v2 – v4 – v5 = 0
AcCoA : v4 – v6 – v13 – v14 = 0
CIT : v6 – v7 – v17 = 0
ICT : v7 – v8 – v12 – v18 = 0
OGT : v8 – v9 – v15 = 0
SUC : v9 – v10 + v12 = 0
MAL : v10 – v11 + v13 = 0
GOX : v12 - v13 = 0
OOA : v5 + v11 – v6 = 0
CO2 : v4 + v8 + v9 – v16 = 0
Reaction Rates in Matrix Form
1 -0.5 -1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 1 0 -1 -1 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 1 0 -1 0 0 0 0 0 0 -1 -1 0 0 0 0 0
0 0 0 0 0 1 -1 0 0 0 0 0 0 0 0 0 -1 0 0
0 0 0 0 0 0 1 -1 0 0 0 -1 0 0 0 0 0 -1 0
0 0 0 0 0 0 0 1 -1 0 0 0 0 0 -1 0 0 0 v = 0
0 0 0 0 0 0 0 0 1 -1 0 1 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 1 -1 0 1 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 1 -1 0 0 0 0 0 0
0 0 0 0 1 -1 0 0 0 0 1 0 0 0 0 0 0 0 0
0 0 0 1 -1 0 0 1 1 0 0 0 0 0 0 -1 0 0 0
Matrix Solution for Intracellular Fluxes
-1
V2
-0.5 0 0 0 0 0 0 0 0 0 0
1 -1 0 0 0 0 0
V4
1 -1 -1 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0
V5
0 1 0 -1 0 0 0 0 0 -1 -1
0 0 0 0 0 0 0 rglc
V6
0 0 0 1 1 0 0 0 0 0 0
0 0 0 0 0 -1 0 rcar
V7
0 0 0 0 1 1 0 0 0 0 0
0 0 -1 0 0 0 -1 0
V8 = - 0 0 0 0 0 1 -1 0 0 0 0 X 0 0 0 -1 0 0 0 rprot
V9
0 0 0 0 0 0 1 -1 0 0 0
0 0 1 0 0 0 0 rc
V10
0 0 0 0 0 0 0 1 1 1 0
0 0 0 0 0 0 0 rcit
V11
0 0 0 0 0 0 0 0 0 1 0
0 0 1 0 0 0 0 rict
V13
0 0 1 -1 0 0 0 0 1 0 0
0 0 0 0 0 0 0
V14
0 1 -1 0 0 1 1 0 0 0 0
0 0 0 0 -1 0 0
Simplified Intracellular Flux Matrix
V2 2 -2 0 0 0 0 0
V4 2 -2 1 -1 0 -1 -1
V5 0 0 -1 1 0 1 1 rglc
V6 -1 1 0 1.5 0.5 2 2 rcar
V7 -1 1 0 1.5 0.5 1 2 0
V8 = -1 1 -1 1.5 0.5 1 1 rprot
V9 -1 1 -1 0.5 0.5 1 1 rc
V10 -1 1 0 0.5 0.5 1 1 rcit
V11 -1 1 1 0.5 0.5 1 1 rict
V13 0 0 1 0 0 0 0
V14 3 -3 0 -2.5 -0.5 -3 -3
Objectives of Presentation
Outline Objectives of Case Study Analyze their reaction equations using
matrix algebra calculations Discuss the relevance of the matrix analysis
approach to metabolite modeling
Relevance of Matrix Approach
Allows a simplified analysis of a complex metabolic network
Succinctly demonstrates 11 different reaction equations in relation to one another
References
Aiba, S. & Matsuoka, M. (1979). Identification of metabolic model: Citrate production from glucose by Candida lipolytica. Biotechnology and Bioengineering. 21, 1373-1386.
Mathews, C. & Van Holde, K. E. (1996). Biochemistry, 2nd edition. Benjamin/Cummings Inc., Menlo Park, CA. 415-516.
Stephanopoulus, G., Aristidou, A., Nielson, J. (1998). Metabolic Engineering. Academic Press, San Diego, CA. 320-326.
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