Difference between revisions of "Team:NCKU Tainan/Kinetic Law"
| Line 68: | Line 68: | ||
Michaelis and Menten considered a quasi equilibrium between E and the ES-Complex to simplify the system. | Michaelis and Menten considered a quasi equilibrium between E and the ES-Complex to simplify the system. | ||
</p> | </p> | ||
| − | <p class="pcontent">$${{d[S] \over dt} = -k_1[E] \cdot S + k_{-1}[ES]}$$</p> | + | <p class="pcontent">$${{d[S] \over dt} = -k_1[E] \cdot [S]+ k_{-1}[ES]}$$</p> |
| − | <p class="pcontent">$${{d[ES]\over dt} = k_1[E] \cdot S - (k_{-1} + k_2)[ES]}$$</p> | + | <p class="pcontent">$${{d[ES]\over dt} = k_1[E] \cdot [S] - (k_{-1} + k_2)[ES]}$$</p> |
| − | <p class="pcontent">$${{d[E] \over dt} = k_1[E] \cdot S - (k_{-1} + k_2)[ES]}$$</p> | + | <p class="pcontent">$${{d[E] \over dt} = k_1[E] \cdot [S] - (k_{-1} + k_2)[ES]}$$</p> |
<p class="pcontent">$${{d[P] \over dt} = k_2[ES]}$$</p> | <p class="pcontent">$${{d[P] \over dt} = k_2[ES]}$$</p> | ||
| − | <p class="pcontent">After derivation $${v = {-ds \over dt} = { | + | <p class="pcontent">After derivation $${v = {-ds \over dt} = {d[P] \over dt}}$$</p> |
<p class="pcontent">where V<sub>m</sub> represents the maximum rate achieved by the system, | <p class="pcontent">where V<sub>m</sub> represents the maximum rate achieved by the system, | ||
and the Km is the substrate concentration at which the reaction rate is half of V<sub>m</sub>. | and the Km is the substrate concentration at which the reaction rate is half of V<sub>m</sub>. | ||
| Line 90: | Line 90: | ||
</p> | </p> | ||
<p class="pcontent">$${{d[S] \over dt} = -k_1[E] \cdot [S] + k_{-1}[ES]}$$</p> | <p class="pcontent">$${{d[S] \over dt} = -k_1[E] \cdot [S] + k_{-1}[ES]}$$</p> | ||
| − | <p class="pcontent">$${{d[ES] \over dt} = k_1[E] \cdot [S] + k_{-2}[E] \cdot P - (k_{-1} + k_2)[ES]}$$</p> | + | <p class="pcontent">$${{d[ES] \over dt} = k_1[E] \cdot [S] + k_{-2}[E] \cdot [P] - (k_{-1} + k_2)[ES]}$$</p> |
| − | <p class="pcontent">$${{d[E] \over dt} = k_1[E] \cdot [S] - k_{-2}[E] \cdot P - (k_{-1} + k_2)[ES]}$$</p> | + | <p class="pcontent">$${{d[E] \over dt} = k_1[E] \cdot [S] - k_{-2}[E] \cdot [P] - (k_{-1} + k_2)[ES]}$$</p> |
| − | <p class="pcontent">$${v = { | + | <p class="pcontent">$${v = {d[P] \over dt} = k_2[ES] - k_{-2}E \cdot [P] = v_f - v_b}$$</p> |
| − | <p class="pcontent">After derivation $${v = {-ds \over dt} = { | + | <p class="pcontent">After derivation $${v = {-ds \over dt} = {d[P] \over dt}}$$</p> |
<p class="pcontent">Finally we use V<sub>fmax</sub> = k2⋅Etotal and V<sub>bmax</sub> = k<sub>−1</sub>⋅Etotal to get the common form for the reversible Michaelis Menten equation</p> | <p class="pcontent">Finally we use V<sub>fmax</sub> = k2⋅Etotal and V<sub>bmax</sub> = k<sub>−1</sub>⋅Etotal to get the common form for the reversible Michaelis Menten equation</p> | ||
<p class="pcontent">$${v = {v^{max}_f S/K_{m,1} - v^{max}_b P/K_{m,2} \over (1 + S/K_{m,1} + P/K_{m,1})}}$$</p> | <p class="pcontent">$${v = {v^{max}_f S/K_{m,1} - v^{max}_b P/K_{m,2} \over (1 + S/K_{m,1} + P/K_{m,1})}}$$</p> | ||
Revision as of 19:49, 17 October 2018
Kinetic law
Ideas Come True
Kinetic law of Modeling
Mathematic model helps us to predict the reaction result before experiment. First of all, we have to define which kinetic law can be applied into which metabolic pathway and chemical equation. There are three kinds of kinetic we chose in this model, mass action, Henri-Michaelis-Menten, and Ping-Pong-Bi-Bi.
- Mass action
- Henri-Michaelis-Menten
- Ping-Pong-Bi-Bi
In chemistry, the law of mass action is the proposition that the rate of a chemical reaction is directly proportional to the product of the activities or concentrations of the reactants. Mass action kinetics describes this behavior as an equation where the velocity or rate of a chemical reaction is directly proportional to the concentration of the reactants.
$${aA + bB \xrightarrow{Kf} cC + dD}$$
$${aA + bB \xrightarrow{Kr} cC + dD}$$
$${Kf = {[C]^c[D]^d \over [A]^a[B]^b}}$$
$${Kr = {[A]^a[B]^b \over [C]^c[D]^d}}$$
Where Kf is forward rate of equilibrium, Kr is reverse rate of equilibrium
In 1913, Michaelis and Menten studied the invertase system and found some behavioral patterns of enzyme-matrix reaction. When the enzyme is catalyzed, the matrix will be combined with the enzyme to generate the product. However, the binding of the enzyme to the matrix is reversible. The concentration of ES will be constant when the reaction is steady state. They also proposed the mathematical description of the behavior of the enzyme. They can express the relationship between the reaction rate and the enzyme mathematically. Hence, the reaction rate is in a hyperbolic relationship with the concentration of substrate at a fixed amount of enzyme. That is the Michaelis-Menten kinetic law.
A. The Henri-Michaelis-Menten kinetic law is expressed as follows:
$${E + S \underset{k_{-1}}{\stackrel{k_1}{\rightleftharpoons}} ES \xrightarrow{k_2} E + P}$$
The Enzyme (E) forms a Complex (ES) with the Substrate (S) and modifies it to the Product (P). The Product is then released and the Enzyme is free to perform another modification. This process is described by the ODE system.
The system cannot be solved analytically. Michaelis and Menten considered a quasi equilibrium between E and the ES-Complex to simplify the system.
$${{d[S] \over dt} = -k_1[E] \cdot [S]+ k_{-1}[ES]}$$
$${{d[ES]\over dt} = k_1[E] \cdot [S] - (k_{-1} + k_2)[ES]}$$
$${{d[E] \over dt} = k_1[E] \cdot [S] - (k_{-1} + k_2)[ES]}$$
$${{d[P] \over dt} = k_2[ES]}$$
After derivation $${v = {-ds \over dt} = {d[P] \over dt}}$$
where Vm represents the maximum rate achieved by the system, and the Km is the substrate concentration at which the reaction rate is half of Vm.
The constants vmax and Km can be looked up at the public data base BRENDA. The rate konstant k2 describes how many substrate molecules are transformed into product molecules per second and active site, it is thus called turnover number.
$${Vmax = k_2 \cdot [E_{total}] = k_{cat} \cdot [E_{total}]}$$
B. A more realistic description of a enzymatic reactions than pure Michaelis Menten Kinetics is given by considering the product forming reaction step as reversible.
$${E + S \underset{k_{-1}}{\stackrel{k_1}{\rightleftharpoons}} ES \xrightarrow{k_2} E + P}$$
The Enzyme (E) forms a Complex (ES) with the Substrate (S) and modifies it to the Product (P). In the reversible Michaelis-Menten reaction the Product can bind the enzyme again and react back to the substrate. This process is described by the ODE system.
$${{d[S] \over dt} = -k_1[E] \cdot [S] + k_{-1}[ES]}$$
$${{d[ES] \over dt} = k_1[E] \cdot [S] + k_{-2}[E] \cdot [P] - (k_{-1} + k_2)[ES]}$$
$${{d[E] \over dt} = k_1[E] \cdot [S] - k_{-2}[E] \cdot [P] - (k_{-1} + k_2)[ES]}$$
$${v = {d[P] \over dt} = k_2[ES] - k_{-2}E \cdot [P] = v_f - v_b}$$
After derivation $${v = {-ds \over dt} = {d[P] \over dt}}$$
Finally we use Vfmax = k2⋅Etotal and Vbmax = k−1⋅Etotal to get the common form for the reversible Michaelis Menten equation
$${v = {v^{max}_f S/K_{m,1} - v^{max}_b P/K_{m,2} \over (1 + S/K_{m,1} + P/K_{m,1})}}$$
Where Vf is the forward rate and the Vb is backwared rate while $${K_{m,1} = {K_{-1} + K_2 \over K_1}}$$ or represents as KS, and $${K_{m,2} = {K_{-1} + K_2 \over K_{-2}}}$$ or represent as KP.
For Ping-Pong-Bi-Bi, it is a double displacement reactions. Hence, there is more than one matrix in the reaction, and there may be several products for multi-matrix reactions in most of enzyme reactions. For example, S1 + S2 → P1 + P2. Binding of A and B are the different enzyme forms, E and F respectively. The double matrix reaction can still be applied to the Henri-Michaelis-Menten formula, but the Km of the two matrices should be determined separately. In addition, the concentration of S2 in the reaction should be saturated when S1 is measured.
Method of our Modeling
We choose the simbiology in matlab to develop our model. SimBiology provides an app and programmatic tools to model, simulate, and analyze dynamic systems which can easily applied on systems biology.
Pathway of our project
Part A : (CO2 uptake model)
CO2 diffuse into cell can use Fick’s law.
$${[CO_2]_{air} \rightarrow [CO_2]_{uptake}}$$
Assume E. coli was a sphere with 10-6 radius while the depth of membrane was 4*10-9
$${J = {-D{dφ \over dx}}}$$
J is the "diffusion flux," of which the dimension is amount of substance per unit area per unit time. D is the diffusion coefficient or diffusivity
After CO2 diffused into cell, it will have a reversible reaction.
$${CO_2 + H_2O \underset{k_{-1}}{\stackrel{k_1}{\rightleftharpoons}} H^+ + HCO_3^-}$$
That’s what CA catalyze the reversible interconversion of CO2 and HCO3-. Although some CAs prefer the direction of CO2 hydration, the carboxysomal CAs in cyanobacteria and some chemoautotrophic bacteria favor the direction of HCO3- dehydration. The result of model and our experiments showed that CA improve amount of CO2 uptake and CO2 utilization.
Fig 1. CO2 uptake model diagram of simbiology
Part B : (Xylose – PRK – Rubisco model)
We clone our genes into E. coli to make it fix the carbon dioxide. The genes include PRK, Rubisco. On the other hand, we also want to produce the higher value product in our project.
| Equation | Enzyme | Kinetic law |
|---|---|---|
| $${Xylose \rightarrow Xylulose}$$ $${Xylulose + ATP \rightarrow X5P}$$ $${X5P \rightarrow Ru5P}$$ | xylose isomerase | Henri-Michaelis-Menten |
| $${Ru5P \xrightarrow{PRK} + RuBP}$$ | Phosphoribulokinase | Henri-Michaelis-Menten |
| $${RuBP + CO_2 \xrightarrow{RuBisCo} + 3PG}$$ | Ribulose-1,5-bisphosphate carboxylase/ oxygenase | Ping-Pong-Bi-Bi |
Fig 2. CO2-utilization bypass model diagram of simbiology
Part C : (Original metabolism model)
It’s a original pathway which xylose is consumed by E. coli. Basically, E. coli will comsume the xylose and then produce the temporary production, pyruvate.
| Equation | Enzyme | Kinetic law |
|---|---|---|
| $${X5P + R5P \rightarrow S7P + GAP}$$ | transketolase | Henri-Michaelis-Menten |
| $${S7P + GAP \rightarrow F6P + E4P}$$ | transaldolase | Henri-Michaelis-Menten |
| $${E4P + X5P \rightarrow F6P + GAP}$$ | transaldolase | Henri-Michaelis-Menten |
| $${FBP \rightarrow GAP}$$ | fructose-bisphosphate aldolase | Henri-Michaelis-Menten |
| $${DHAP \rightarrow GAP}$$ | triose-phosphate isomerase | Reversible Henri-Michaelis-Menten |
| $${F6P + ATP \rightarrow FBP + ADP}$$ | 6-phosphofructokinase | Henri-Michaelis-Menten |
| $${F6P \rightarrow GAP}$$ | glucose-6-phosphate isomerase | Henri-Michaelis-Menten |
| $${G6P + NADP^+ \rightarrow 6PG + NAPDH}$$ | 6-phosphogluconolactonase | Ping-Pong-Bi-Bi |
| $${6PG + NADP^+ \rightarrow Ru5P + NAPDH}$$ | phosphogluconate dehydrogenase (NADP+-dependent, decarboxylating) | Henri-Michaelis-Menten |
| $${GAP + NADP^+ + ADP \rightarrow 3PGA + NAPDH + ATP}$$ | glyceraldehyde-3-phosphate dehydrogenase (NADP+) | Henri-Michaelis-Menten |
| phosphoglycerate kinase | ||
| $${3PGA \rightarrow PEP}$$ | phosphoglycerate mutase | Henri-Michaelis-Menten |
| phosphopyruvate hydratase | ||
| $${PEP \rightarrow PYR}$$ | pyruvate kinase | Henri-Michaelis-Menten |
Fig 3. Original metabolism model diagram of simbiology
Fig 4. Xylose and pyruvate result of original pathway
Fig 5. X5P result of original pathway
Fig 6. Ru5P result of original pathway
Fig 7. 3PGA result of original pathway
Fig 8. R5P result of original pathway
Fig 9. GAP result of original pathway
Fig 10. S7P result of original pathway
Fig 11. F6P result of original pathway
Fig 12. E4P result of original pathway
Fig 13. FBP result of original pathway
Fig 14. DHAP result of original pathway
Fig 15. G6P result of original pathway
Fig 16. 6PG result of original pathway
Fig 17. PEP result of original pathway
Part D : (TCA cycle model)
In Tricarboxylic acid cycle (TCA cycle), we can get final production in this cycle. The two carbons of Acetyl CoA are decomposed into carbon dioxide to produce energy, form ATP or GTP, and reduce NADH and FADH2, and then provide the energy needed for the reaction in the organism.
| Equation | Enzyme | Kinetic law |
|---|---|---|
| $${PEP + HCO_3^- + NAD^+ \rightarrow OAA + NADH}$$ | PEP carboxylase | Reversible Henri-Michaelis-Menten |
| $${AcCoA \rightarrow CIT}$$ | citrate synthase | Reversible Henri-Michaelis-Menten |
| $${cIT \rightarrow ICIT}$$ | aconitate hydratase | Reversible Henri-Michaelis-Menten |
| $${ICIT + NADP^+ \rightarrow AKG + NADPH + CO_2}$$ | isocitrate dehydrogenase | Reversible Henri-Michaelis-Menten |
| $${AKG + NAD^+ \rightarrow SUCCoA + NADH + CO_2}$$ | dihydrolipoyllysine-residue succinyltransferase | Reversible Henri-Michaelis-Menten |
| $${SUCCoA + ADP \rightarrow SUCC + ATP}$$ | succinate-CoA ligase (ADP-forming) | Reversible Henri-Michaelis-Menten |
| $${SUCC + FAD \rightarrow FUM + FADH_2}$$ | succinate dehydrogenase | Reversible Henri-Michaelis-Menten |
| $${FUM \rightarrow MAL}$$ | fumarate hydratase | Reversible Henri-Michaelis-Menten |
| $${MAL + NAD^+ \rightarrow OAA + NADH}$$ | malate dehydrogenase | Reversible Henri-Michaelis-Menten |
| $${OAA \rightarrow CIT}$$ | citrate synthase | Reversible Henri-Michaelis-Menten |
| $${PYR \rightarrow NADH + AcCoA + CO_2}$$ | pyruvate dehydrogenase complex | Henri-Michaelis-Menten |
| $${ICIT \rightarrow GOX}$$ | isocitrate lyase | Reversible Henri-Michaelis-Menten |
| $${GOX \rightarrow MAL}$$ | malate synthase | Reversible Henri-Michaelis-Menten |
| $${ICIT \rightarrow SUCC + GOX}$$ | isocitrate lyase | Reversible Henri-Michaelis-Menten |
Fig 18. TCA cycle model diagram of simbiology
Result analysis
We built the whole xylose metabolism in our engineered E. coli, which help us calculate the rate of xylose will go into CO2 utilization bypass. The result of this model shows that CO2 uptake affect the production of pyruvate. We can confirm that our engineered E. coli successfully uptake CO2 while the increase rate of pyruvate production followed the experiment data. To see more analysis of CO2 utilization on analysis page.
Fig 19. TCA cycle model diagram of simbiology
Fig 20. whole xylose metabolisml diagram of simbiology
References
- Michaelis Menten Kinetics in bio – physic wiki, web : http://www.bio-physics.at/wiki/index.php?title=Michaelis_Menten_Kinetics
- citric acid cycle from Brenda, web : https://www.brenda-enzymes.org/pathway_index.php?ecno=&brenda_ligand_id=Alpha-ketoglutarate&organism=Escherichia+coli&pathway=citric_acid_cycle&site=pathway
- U. Sauer, J. E. Bernhard, The PEP—pyruvate—oxaloacetate node as the switch point for carbon flux distribution in bacteria. FEMS Microbiology Reviews, Volume 29, Issue 4, 1 September 2005, Pages 765–794.
- O. Mugihito, S. Hideaki, T. Yukihiro , M Noriko, S. Tatsuya, O. Masahiro, I. Ayaaki, S. Kenji, Kinetic modeling and sensitivity analysis of xylose metabolism in Lactococcus lactis IO-1. Journal of Bioscience and Bioengineering VOL. 108 No. 5, 376–384, 2009.
- W. Akira, N. Keisuke, H. Tomohiro, S. Ryohei, Reaction mechanism of phosphoribulokinase from a cyanobacterium, Synechococcus PCC7942. Photosynthesis Research 56: 27–33, 1998
- G. B. Guillaume, D. F. Graham, T. J. Andrews, Despite slow catalysis and confused substrate specificity, all ribulose bisphosphate carboxylases may be nearly perfectly optimized Proc Natl Acad Sci U S A. 2006 May 9; 103(19): 7246–7251.
- L. Yun, A. M. Keith, Determination of Apparent Km Values for Ribulose 1,5- Bisphosphate Carboxylase/Oxygenase (Rubisco) Activase Using the Spectrophotometric Assay of Rubisco Activity. Plant Physiol. (1991) 95, 604-609
- Rong-guang Z, C. Evalena A., Alexei S., Tatiana S., Elena E., Steven B., Cheryl H. A., Aled M. E., Andrzej J., and Sherry L. M. Structure of Escherichia Coli Ribose-5-Phosphate Isomerase: A Ubiquitous Enzyme of the Pentose Phosphate Pathway and the Calvin Cycle Structure, Vol. 11, 31–42, January, 200
- Inês L., Joana F., Christine C., Sandra M., Nuno S., Nilanjan R., Anabela C., and Joana T. Ribose 5-Phosphate Isomerase B Knockdown Compromises Trypanosoma brucei Bloodstream Form Infectivity PLoS Negl Trop Dis. 2015 Jan; 9(1): e3430.
- Singh2006 TCA mtu model1. SBML2LATEX. Web : http: //www.ra.cs.uni-tuebingen.de/software/SBML2LaTeX
- J. Shen, Modeling the glutamate–glutamine neurotransmitter cycle, Front. Neuroenergetics, 28 January 2013
- X. Feng, H. Zhao, Investigating xylose metabolism in recombinant Saccharomyces cerevisiae via 13C metabolic flux analysis, Microb Cell Fact. 2013; 12: 114.
- D. Runquist, M. Bettiga, Increased expression of the oxidative pentose phosphate pathway and gluconeogenesis in anaerobically growing xylose-utilizing Saccharomyces cerevisiae, Microbial Cell Factories 2009, 8:49
- Kalle Hult rev 2005, 2007 Linda Fransson Department of Biotechnology KTH, Stockholm, Enzyme kinetics, An investigation of the enzyme glucose-6- phosphate isomerase
- Model name: “Mosca2012 - Central Carbon Metabolism Regulated by AKT”, SBML2LATEX. Web : http: //www.ra.cs.uni-tuebingen.de/software/SBML2LaTeX
- M. Ettore, A. Roberta, M. Carlo, B. Annamaria, C. Gianfranco, M. Luciano, Computational modeling of the metabolic states regulated by the kinase Akt, Front. Physiol., 21 November 2012
- E. G. Jacqueline, P. L. Christopher, R. A. Maciek, Comprehensive analysis of glucose and xylose metabolism in Escherichia Coli under aerobic and anaerobic conditions by 13C metabolic flux analysis, Metabolic Engineering Volume 39, January 2017, Pages 9-18
- N. N. Ulusu, C. Şengezer, Kinetic mechanism and some properties of glucose-6- phosphate dehydrogenase from sheep brain cortex, Türk Biyokimya Dergisi [Turkish Journal of Biochemistry–Turk J Biochem] 2012; 37 (4) ; 340–347
- H. Stefania, M. Katy, C. Carlo, M. Morena, D. Franco, 6-Phosphogluconate Dehydrogenase Mechanism EVIDENCE FOR ALLOSTERIC MODULATION BY SUBSTRATE, J Biol Chem. 2010 Jul 9; 285(28): 21366–21371.
- K. Nielsen, P.G. Sørensen, F. Hynne, H. G. Busse, Sustained oscillations in glycolysis: an experimental and theoretical study of chaotic and complex periodic behavior and of quenching of simple oscillations, Biophysical Chemistry 72 (1998) 49–62
- UniProtKB - A0RV30 from web : https://www.uniprot.org/uniprot/A0RV30