<p>We modeled our enzyme reactions in propane pathway with Michaelis-Menten enzyme kinetics. It is widely used in metabolical modeling of enzymes and assumes that the reaction enzyme catalyses is rapid compared to the enzyme and substrate joining together and leaving each other. The archetypical Michaelis-Menten equation for a reaction with one substrate and one product, i.e. \(S \rightarrow P; E \) is \[ \frac{d[P]}{dt} = \frac{V_{max}[S]}{K_{M}+[S]}, \] where \([S]\) is substrate concentration. \( V_{max} \) tells us the maximum speed of the enzyme and \( K_{M} \) is the substrate concentration at which the reaction rate is half of \( V_{max} \), also called the Michaelis constant. Usually we need to calculate \( V_{max} \) by \( K_{cat}\cdot [E] \) where \([E]\) is enzyme concentration and \( K_{cat} \) is the turnover number (unit: \( \tfrac{1}{min} \) ), which describes the speed at which an enzyme processes substrate to product. Only few of our reactions follow this very basic equation, and for the most of them we need to use multisubstrate reaction kinetics. For more information, see for example Enzyme Kinetics: Principals and Methods by Hans Bisswanger (2002).</p>
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<p>We modeled our enzyme reactions in the propane pathway with Michaelis-Menten enzyme kinetics. It is widely used in metabolical modeling of enzymes. Michaelis-Menten kinetics assumes that the reaction an enzyme catalyses is rapid compared to the enzyme and substrate joining together and leaving each other. The archetypical Michaelis-Menten equation for a reaction with one substrate and one product, i.e. \(S \rightarrow P; E \) is \[ \frac{d[P]}{dt} = \frac{V_{max}[S]}{K_{M}+[S]}, \] where \([S]\) is substrate concentration. \( V_{max} \) tells us the maximum speed of the enzyme and \( K_{M} \) is the substrate concentration at which the reaction rate is half of \( V_{max} \), also called the Michaelis constant. Usually we need to calculate \( V_{max} \) by \( K_{cat}\cdot [E] \) where \([E]\) is enzyme concentration and \( K_{cat} \) is the turnover number (unit: \( \tfrac{1}{min} \) ), which describes the speed at which an enzyme processes substrate to product. Only few of our reactions follow this very basic equation, and for the most of them we need to use multisubstrate reaction kinetics. For more information, see for example Enzyme Kinetics: Principals and Methods by Hans Bisswanger (2002).</p>
We modeled our enzyme reactions in the propane pathway with Michaelis-Menten enzyme kinetics. It is widely used in metabolical modeling of enzymes. Michaelis-Menten kinetics assumes that the reaction an enzyme catalyses is rapid compared to the enzyme and substrate joining together and leaving each other. The archetypical Michaelis-Menten equation for a reaction with one substrate and one product, i.e. \(S \rightarrow P; E \) is \[ \frac{d[P]}{dt} = \frac{V_{max}[S]}{K_{M}+[S]}, \] where \([S]\) is substrate concentration. \( V_{max} \) tells us the maximum speed of the enzyme and \( K_{M} \) is the substrate concentration at which the reaction rate is half of \( V_{max} \), also called the Michaelis constant. Usually we need to calculate \( V_{max} \) by \( K_{cat}\cdot [E] \) where \([E]\) is enzyme concentration and \( K_{cat} \) is the turnover number (unit: \( \tfrac{1}{min} \) ), which describes the speed at which an enzyme processes substrate to product. Only few of our reactions follow this very basic equation, and for the most of them we need to use multisubstrate reaction kinetics. For more information, see for example Enzyme Kinetics: Principals and Methods by Hans Bisswanger (2002).
Figure 1: Propane pathway.
AtoB
2\(\cdot\)Acetyl-CoA \(\rightarrow\) Acetoacetyl-CoA + CoA
AtoB is native to Escherichia Coli. The reaction shown above is reversible, but since the ratio of forward and reversible reaction favores strongly the forward one (Vf/Vr: 22.3, Source: Molecular and catalytic properties of the acetoacetyl-coenzyme A thiolase of Escherichia coli; Archives of Biochemistry and Biophysics Volume 176, Issue 1, September 1976, Pages 159–170) we can approximate is as irreversible.
Based on this article, we know that the reaction follows Ping Pong Bi Bi -model and so we get the following rate equation:
Thiolases of Escherichia coli: purification and chain length specificities
Feigenbaum, J.; Schulz, H.; Journal of Bacteriology, Volume 122, Issue 2, May 1975, Pages 407-411
Forward reaction
\( K_{M}^{AtoB:Acetyl\text{-}CoA} \)
0.00047 mol/l
Molecular and catalytic properties of the acetoacetyl-coenzyme A thiolase of Escherichia coli; Archives of Biochemistry and Biophysics Volume 176, Issue 1, September 1976, Pages 159–170
FadB2 is found from Mycobacterium tuberculosis (strain ATCC 25618 / H37Rv). The reaction it catalyzes is reversible and we have assumed it to follow random bi bi reaction model.
The equilibrium constant \(K_{eq}\) in reversible random bi bi model is from Haldane relationship \[ K_{eq} = \frac{V_1\cdot K_{M}^{FadB2:3\text{-}Hydroxybutyryl\text{-}CoA}\cdot K_{M}^{FadB2:NADP^+}}{V_2\cdot K_{M}^{FadB2:Acetoacetyl\text{-}CoA}\cdot K_{M}^{FadB2:NADPH}}.\] See Enzyme Kinetics: Principals and Methods by Hans Bisswanger (2002) for reference. We have not taken H\(^+\) concentration into account in this calculation which is justified because it needs to be fairly constant in the cell or otherwise the cell will die off. This yields us the following as our reaction rate equation.
The enzyme is from Clostridium acetobutylicum, but only values to be found were for Clostridium Kluyveri. However, we do not see this as a problem since the species are very close relatives and so the values ought to be close enough for comparison.
The reaction is reversible, but according to Purification and Properties of NADP-Dependent L(+)-3-Hydroxybutyryl -CoA Dehydrogenase from Clostridium kluyveri; Eur. J. Biochem. 32,51-56 (1973), the specific activity of the 3-hydroxybutyryl-CoA dehydrogenase (forward) as measured in the direction of acetoacetyl-CoA reduction is 478.6 U/mg protein and the rate of the oxidation reaction (reverse) proceeded with 36.6 U / mg protein. Because of the disparity between these rates we approximate the reaction as irreversible.
We don’t consider how \(H^+\) affects the reaction which is justified by knowing that its concentration in the cell should always be quite constant; otherwise the cell will die. Based on these pieces of information we can assume that the reaction is either random or ordered Bi Bi -reaction so the rate equation is as follows.
Crt is found from Clostridium acetobutylicum. Since there is only one substrate in the reaction, we can form the rate equation from basic Michaelis-Menten kinetic model. We assumed the reaction to be irreversible since the enzyme is quite efficient.
Purification and Characterization of Crotonase from Clostridium acetobutylicum; The journal of Biological Chemistry, Volume 247, Number 16, August 1972, Pages 5266-5271
Purification and Characterization of Crotonase from Clostridium acetobutylicum; The journal of Biological Chemistry, Volume 247, Number 16, August 1972, Pages 5266-5271
Ter is from Treponema denticola. Its reaction without H\( ^+\) is an ordered bi-bi reaction mechanism with NADH binding first (source: Biochemical and Structural Characterization of the trans-Enoyl-CoA Reductase from Treponema denticola; Biochemistry 2012, 51, 6827−6837). Since we found no references for the reaction to be reversible, we modeled it as irreversible.
Biochemical and Structural Characterization of the trans-Enoyl-CoA Reductase from Treponema denticola; Biochemistry 2012, 51, 6827−6837
Forward reaction
\( K_{M}^{Ter:Crotonyl\text{-}CoA} \)
70 µmol/l
Biochemical and Structural Characterization of the trans-Enoyl-CoA Reductase from Treponema denticola; Biochemistry 2012, 51, 6827−6837
\( K_{M}^{Ter:NADH} \)
5.2e-06 mol/l
Biochemical and Structural Characterization of the trans-Enoyl-CoA Reductase from Treponema denticola; Biochemistry 2012, 51, 6827−6837
\( K_{I}^{Ter:Butyryl\text{-}CoA} \)
1.98e-07 mol/l
Biochemical and Structural Characterization of the trans-Enoyl-CoA Reductase from Treponema denticola; Biochemistry 2012, 51, 6827−6837
YciA
Butyryl-CoA + H\( _2\)O \(\rightarrow\) Butyrate + CoA
YciA is found in Haemophilus influenzae. When searching for information about this enzyme no references for it being reversible were found. Because of this we modeled it as irreversible. We know that there is abundance of water in the cell, so when considering rate equation we can safely assume that it doesn't have much effect to it. This is why we can again use the basic Michaelis-Menten rate equation.
Car-enzyme is originally from Mycobacterium marinum. We assumed that this reaction is irreversible, which is justified because we have ATP in the reactants so we know that the possible reverse reaction can’t be very efficient.
For the same reasons as mentioned before, we didn’t consider \(H^+\) in equations. We know that the reaction can be modeled using Bi Uni Uni Bi Ping Pong mechanism. Thus, the rate equation will be
Carboxylic acid reductase is a versatile enzyme for the conversion of fatty acids into fuels and chemical commodities; PNAS | January 2, 2013 | vol. 110 | no. 1 | 87–92
Forward reaction, calculated from a plot
\( K_{M}^{Car:Butyrate} \)
0.013 mol/l
Carboxylic acid reductase is a versatile enzyme for the conversion of fatty acids into fuels and chemical commodities; PNAS | January 2, 2013 | vol. 110 | no. 1 | 87–92
Calculated from a plot
\( K_{M}^{Car:NADPH} \)
4.8e-05 mol/l
Carboxylic acid reductase is a versatile enzyme for the conversion of fatty acids into fuels and chemical commodities; PNAS | January 2, 2013 | vol. 110 | no. 1 | 87–92
\( K_{M}^{Car:ATP} \)
0.000115 mol/l
Carboxylic acid reductase is a versatile enzyme for the conversion of fatty acids into fuels and chemical commodities; PNAS | January 2, 2013 | vol. 110 | no. 1 | 87–92
Sfp
Sfp does not directly affect to the intermediates in our pathway, but instead acts as an activating enzyme for Car. We have modeled the reactions concerning Sfp here.
Ado
Aldehyde deformylating oxygenase is the final enzyme in the propane pathway, turning butyraldehyde into propane. We are using and ADO mutant (A134F) that has an increased activity towards short-chained aldehydes, such as butyraldehyde. Furthermore, we are enhancing the electron supply to ADO by overexpressing its presumed natural electron acceptor/donor ferredoxin. To reduce ferredoxin under aerobic conditions, we co-express NADPH/ferredoxin/flawodoxin-oxidoreductase(Fpr).
Using A134F mutant and a ferredoxin reducing system including Fpr improve propane production. Combining all these improvements is challenging from the modeling point of view, as there are no kinetic parameters available for the reaction where both the ADO A134F mutant and a ferredoxin reducing system are used. As no sufficient data is available, we cannot model the ADO reaction like we have modeled the other reactions in the propane pathway.
We know that the wild-type ADO together with PMS/NADH reducing system has kcat value 0.0031±0.0001 min−1 and Km value 10.1±0.9 mM for the reaction from butyraldehyde to propane. A134F mutant has been shown to be more efficient than wild-type ADO and ferredoxin reducing system more efficient for ADO than a PMS/NADH reducing system. Therefore we can rather safely assume 10.1±0.9 mM to be the maximum Km possible and 0.0031±0.0001 min−1 to be the minimum kcat possible for estimating ADO reaction kinetics in our system.
Since we could not model the reactions that govern ADO's function, we approximated these reactions by simplifying the enzyme kinetics that govern ADO to the simplest case of Miclaelis-Menten kinetics. While this is not ideal, with current data and within these time limitations we can't make better assumptions.
Production of Propane and Other Short-Chain Alkanes by Structure-Based Engineering of Ligand Specificity in Aldehyde-Deformylating Oxygenase, Khara et al (2013)
Forward reaction
\( K_{M}^{Ado:Butyraldehyde} \)
0.0101 mol/l
Production of Propane and Other Short-Chain Alkanes by Structure-Based Engineering of Ligand Specificity in Aldehyde-Deformylating Oxygenase, Khara et al (2013)
Other Constants
The following table provides information about typical concentrations in a cell that we use in our model.
Constant
Value
Source
To note
[Acetyl-CoA]
0.00061 mol/l
Absolute Metabolite Concentrations and Implied Enzyme Active Site Occupancy in Escherichia coli, Bennett et al, 2009
glucose-fed, exponentially growing E. coli
[Acetoacetyl-CoA]
2.2e-05 mol/l
Absolute Metabolite Concentrations and Implied Enzyme Active Site Occupancy in Escherichia coli, Bennett et al, 2009
glucose-fed, exponentially growing E. coli
[CoA]
0.00014 mol/l
Absolute Metabolite Concentrations and Implied Enzyme Active Site Occupancy in Escherichia coli, Bennett et al, 2009
glucose-fed, exponentially growing E. coli
[NADPH]
0.00012 mol/l
Absolute Metabolite Concentrations and Implied Enzyme Active Site Occupancy in Escherichia coli, Bennett et al, 2009
glucose-fed, exponentially growing E. coli
[NADP\( ^+\)]
2.1e-06 mol/l
Absolute Metabolite Concentrations and Implied Enzyme Active Site Occupancy in Escherichia coli, Bennett et al, 2009
glucose-fed, exponentially growing E. coli
[NADH]
8.3e-05 mol/l
Absolute Metabolite Concentrations and Implied Enzyme Active Site Occupancy in Escherichia coli, Bennett et al, 2009
glucose-fed, exponentially growing E. coli
[NAD\( ^+\)]
0.0026 mol/l
Absolute Metabolite Concentrations and Implied Enzyme Active Site Occupancy in Escherichia coli, Bennett et al, 2009
glucose-fed, exponentially growing E. coli
[ATP]
0.0096 mol/l
Absolute Metabolite Concentrations and Implied Enzyme Active Site Occupancy in Escherichia coli, Bennett et al, 2009
glucose-fed, exponentially growing E. coli
[AMP]
0.00028 mol/l
Absolute Metabolite Concentrations and Implied Enzyme Active Site Occupancy in Escherichia coli, Bennett et al, 2009
glucose-fed, exponentially growing E. coli
[H\( _2\)O]
38.85 mol/l
Concentration of water in water is \(\frac{\frac{m}{V}}{M}\). E.coli is about 70% water. Thus, the water concentration in E.coli is \( 70\% \cdot \frac{1000 \frac{g}{l}}{18.01 g/mol} = 38.85 \frac{mol}{l} \)
