Difference between revisions of "Team:NCKU Tainan/Model"

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                                                     <tr>
 
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                                                         <th colspan="4">CO<sub>2</sub> uptake</th>
 
                                                         <th colspan="4">CO<sub>2</sub> uptake</th>
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                                                         <th colspan="2">Kf (mM)</th>
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                                                         <th colspan="2">K<sub>f</sub> (mM)</th>
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                                                         <th colspan="2">Kr (mM)</th>                                                         
+
                                                         <th colspan="2">K<sub>r</sub> (mM)</th>                                                         
 
                                                     </tr>
 
                                                     </tr>
 
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                                                             <th colspan="8">CO<sub>2</sub> bypass pathway</th>
 
                                                             <th colspan="8">CO<sub>2</sub> bypass pathway</th>
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                                                             <th colspan="3">Vmax (1/S)</th>
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                                                             <th colspan="3">V<sub>max</sub> (1/S)</th>
 
                                                             <th colspan="3">K<sub>M</sub> (mM)</th>                                                         
 
                                                             <th colspan="3">K<sub>M</sub> (mM)</th>                                                         
 
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                                                             <td rowspan="2" colspan="6">$${RuBP + CO_2 \xrightarrow{RuBisCO} 3PG}$$</td>
 
                                                             <td rowspan="2" colspan="6">$${RuBP + CO_2 \xrightarrow{RuBisCO} 3PG}$$</td>
 
                                                             <td colspan="2">Vmax</td>
 
                                                             <td colspan="2">Vmax</td>
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                                                             <td colspan="2">Krubp</td>
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                                                             <td colspan="2">K<sub>rubp</sub></td>
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                                                             <td colspan="2">KCO<sub>2</sub></td>
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                                                             <td colspan="2">K<sub>CO</sub><sub>2</sub></td>
 
                                                         </tr>
 
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                                                             <th colspan="13">TCA cycle</th>
 
                                                             <th colspan="13">TCA cycle</th>
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                                                             <th colspan="3">Vmf (mM/min)</th>
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                                                             <th colspan="3">V<sub>mf</sub> (mM/min)</th>
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                                                             <th colspan="3">Vmr (mM/min)</th>
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                                                             <th colspan="3">Ks (mM)</th>  
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                                                             <th colspan="3">K<sub>s</sub> (mM)</th>  
−
                                                             <th colspan="3">Kp (mM)</th>                                                       
+
                                                             <th colspan="3">K<sub>p</sub> (mM)</th>                                                       
 
                                                         </tr>
 
                                                         </tr>
 
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                                                             <td rowspan="2" colspan="1">C14</td>
 
                                                             <td rowspan="2" colspan="1">C14</td>
 
                                                             <td rowspan="2" colspan="12">$${ICIT \rightarrow SUCC + GOX}$$</td>
 
                                                             <td rowspan="2" colspan="12">$${ICIT \rightarrow SUCC + GOX}$$</td>
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                                                             <td colspan="3">Vmf (mM/min)</td>
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                                                             <td colspan="3">V<sub>mf</sub> (mM/min)</td>
−
                                                             <td colspan="3">Vmr (mM/min)</td>
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                                                             <td colspan="3">V<sub>mr</sub> (mM/min)</td>
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                                                             <td colspan="2">Kicit (mM)</td>
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                                                             <td colspan="2">K<sub>icit</sub> (mM)</td>
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                                                             <td colspan="2">Ksucc (mM)</td>
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                                                             <td colspan="2">K<sub>succ</sub> (mM)</td>
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                                                             <td colspan="2">Kgox (mM)</td>
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                                                             <td colspan="2">K<sub>gox</sub> (mM)</td>
 
                                                         </tr>
 
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Revision as of 12:31, 14 October 2018

Model

Achievement


  1. Figure out how much CO2 uptake into the E.coli to make our project more effective.

  2. We will realize how much carbon we can fix in our project.

Model

In order to achieve these two goals, we try to figure out three main questions：

  1. Amount of CO2 uptake by E. coli
  2. CO2 flux in E. coli metabolism
  3. Amount of Carbon fixed in biomass

Purpose

We aim to develop the biological model to make our experimental data more useful, even more effective to achieve the optimization parameters in the model. Therefore, we can save time to try and error on doing experiment. After that, we analyze the rate of production and consumption. In this way, we can calculate the amount of carbon dioxide uptake into the Escherichia coli (E. coli) and calculate how much CO2 will be used in our system. In addition, we also want to realize how much carbon fix in our system. We have to understand the process in E. coli after uptaking CO2. Since we integrated non-native carbon fixation pathway into E. coli to let E. coli utilize CO2, we can simplify the CO2 utilization pathway in engineered E. coli into two parts, CO2 uptake and CO2 metabolism.

Method of model

Follow our model progress diagram with a better sense of how we achieve our goal.

Purpose of model

How many CO2 can be used by E. coli

CO2 uptake

CO2 exists in the phase of gas. Therefore, E. coli uptake CO2 by diffusion. However, the native diffusion rate is really low, not to mention the dissolved rate. We clone CA (carbonic anhydrase) gene to speed up the diffusion rate. The higher diffusion rate, the higher CO2 concentration maintained in engineered E. coli. Higher CO2 concentration in engineered E. coli provides more steady CO2 condition for downstream pathway.

CO2 uptake Kf (mM) Kr (mM)
R1 $${[CO_2]_{air} \rightarrow [CO_2]_{uptake}}$$ 9.23E-04 4.78E-04
R2 $${[CO_2]_{uptake} + [H_2O] \rightarrow [H_2CO_3]}$$ 0.062 23.7
R3 $${[H_2CO_3] \rightarrow [H^+] + [HCO_3^-]}$$ 8000000 4.7E10
R4 $${[HCO_3^-] \rightarrow [H^+] + [CO_3^{2-}]}$$ 3 5E10
R5 $${[H^+] + [HCO_3^-] \longleftrightarrow [H_2O] + [CO_2]_{uptake}}$$ Vmax Km
0.47333 0.0062

Result

Enzyme, CA, strongly catalyzes the hydration of CO2 and its interaction appears to follow a Michaelis-Menten mechanism with a Hill constant of 0.0062 in our research. The result of Engineered E. coli cloned with or without CA gene showed below. A quite different diffusion time explains the function of CA.

Fig. 2 CO2 uptake amount change with time in engineered E. coli without CA gene.

Fig. 3 CO2 uptake amount change with time in engineered E. coli with CA gene.

CO2 Metabolism

Xylose is the main source of our engineered E. coli to uptake CO2. However, there is another pathway for xylose metabolism, which means that there is only a part of xylose that E. coli consumed will react with CO2. We build a model to predict the different carbon flux between original xylose metabolism, PP pathway (Pentose Phosphate pathway), and our CO2 bypass pathway.

Both of two pathways will end up at pyruvate, which is a key intersection in the network of metabolic pathways. We built a model of TCA cycle to explain how pyruvate play an energy precursor role and then is converted into biomass of E. coli.

Pathway

Fig. 4 Metabolic pathway of CO2-utilization E. coli.

The introduced CO2-utilization bypass pathway composed of PRK and Rubisco is drawn in green line and noted by ” A” reaction and the double line was the pathway that composed by genetically modified, while the central carbon metabolic pathway including PP pathway and TCA cycle is drawn in blue line and yellow line and noted by “B” reaction and “C” reaction, respectively. See more detail in Kinetic law.

CO2 bypass pathway Vmax (1/S) KM (mM)
A1 $${Xylose \rightarrow Xylulose}$$ $${Xylulose + ATP \rightarrow X5P}$$ 0.02456 124.55879
A2 $${X5P \rightarrow Ru5P}$$ 0.08 12.5
A3 $${Ru5P \xrightarrow{PRK} RuBP}$$ 225.81858 0.27
A4 $${RuBP + CO_2 \xrightarrow{RuBisCO} 3PG}$$ Vmax Krubp KCO2
333.33 53 2.7
Pentose Phosphate Pathway Vmax (1/S) KM (mM)
B1 $${Ru5P \rightarrow R5P}$$ 0.13672 12.5
B2 $${X5P + R5P \rightarrow S7P + GAP}$$
$${X5P \rightarrow S7P}$$ 58.27 4.96E-09
$${X5P \rightarrow GAP}$$ 58.27 48
$${R5P \rightarrow S7P}$$ 58.27 0.008
$${R5P \rightarrow GAP}$$ 58.27 3.05E-07
B3 $${S7P + GAP \rightarrow F6P + E4P}$$
$${S7P \rightarrow E4P}$$ 58.27 2.524
$${S7P \rightarrow F6P}$$ 58.27 6.10E-09
$${GAP \rightarrow E4P}$$ 58.27 1.73E-07
$${GAP \rightarrow F6P}$$ 58.27 8.23E-09
B4 $${E4P + X5P \rightarrow F6P + GAP}$$
$${E4P \rightarrow F6P}$$ 1 1
$${E4P \rightarrow GAP}$$ 5.827E-4 1.733E-7
$${X5P \rightarrow F6P}$$ 0.05827 1.733E-7
$${X5P \rightarrow GAP}$$ 0.005827 48.8
B5 $${FBP \rightarrow GAP}$$ 135.425 4
B6 $${DHAP \longleftrightarrow GAP}$$ Vmf Vmr KmDHAP KmGAP
0.2394 0.24 0.812 0.245
B7 $${FBP \rightarrow DHAP}$$ 0.0001247 0.04
B8 $${F6P + ATP \rightarrow FBP + ADP}$$ 88.2533 0.017
B9 $${F6P \rightarrow G6P}$$ 88.2353 0.017
B10 $${G6P + NADP^+ \rightarrow 6PG + NADPH}$$ Vmax KmG6P KmNADP
11.736 0.12 0.0123
B11 $${6PG + NADP^+ \rightarrow Ru5P + NADPH}$$ 1.0 0.044
B12 $${GAP + NADP^+ + ADP \rightarrow 3PGA + NADPH + ATP}$$ 0.4 0.013
B13 $${3PGA \rightarrow PEP}$$ 0.43478 0.23
B14 $${PEP \rightarrow PYR}$$ 0.23148 0.45
TCA cycle Vmf (mM/min) Vmr (mM/min) Ks (mM) Kp (mM)
C1 $${PEP + HCO_3^- + NAD^+ \rightarrow OAA + NADH}$$ 1 1 1 1
C2 $${AcCoA \rightarrow CIT}$$ 64.8 0.648 0.05 0.12
C3 $${CIT \rightarrow ICIT}$$ 31.2 0.312 1.7 0.7
C4 $${ICIT + NADP^+ \rightarrow AKG + NADPH + CO_2}$$ 10.2 0.102 0.03 0.3
C5 $${AKG + NAD^+ \rightarrow AKG + NADPH + CO_2}$$ 57.344 0.57344 0.1 1.0
C6 $${SUCCoA + ADP \rightarrow SUCC + ATP}$$ 6.54 0.0651 0.015 0.15
C7 $${SUCC + FAD \rightarrow FUM + FADH_2}$$ 1.02 1.02 0.12 0.15
C8 $${FUM \rightarrow MAL}$$ 887.7 87.7 0.25 2.38
C9 $${MAL + NAD^+ \rightarrow OAA + NADH}$$ 184 184 0.833 0.0443
C10 $${OAA \rightarrow CIT}$$ 64.8 0.648 0.012 0.12
C11 $${PYR \rightarrow NADH + AcCoA + CO_2}$$ Vmax (1/s) Km (mM)
0.00518 1.5
C12 $${ICIT \rightarrow GOX}$$ 1.172 0.01172 0.145 0.13
C13 $${GOX \rightarrow MAL}$$ 20 0.2 0.057 1.0
C14 $${ICIT \rightarrow SUCC + GOX}$$ Vmf (mM/min) Vmr (mM/min) Kicit (mM) Ksucc (mM) Kgox (mM)
1.172 0.012 0.145 0.59 0.13
E4P erythrose-4-phosphate
F6P fructose-6-phosphate
FBP fructose-1,6-bisphosphate
G6P glucose-6-phosphate
GAP glyceraldehyde-3-phosphate
PEP phosphoenol pyruvate
PYR pyruvate
R5P ribose-5-phosphate
Ru5P ribulose-5-phosphate
S7P sedoheptulose-7-phosphate
X5P xylulose-5-phosphate
6PG 6-phosphogluconate
DHAP Dihydroxyacetone phosphate
3PG 3-Phosphoglyceric acid
RuBP ribulose-1,5-bisphosphate
PRK Phosphoribulokinase
Rubisco Ribulose-1,5-bisphosphate carboxylase/ oxygenase
AcCoA Acetyl-CoA
CIT Citrate
ICIT Isocitrate
AKG Alpha-ketoglutarate
SUCCoA Succinyl-CoA
SUCC Succinate
FUM Fumarate
MAL Malate
OAA Oxaloacetic acid
GOX Glyoxylate

Xylose v.s. CO2 analysis in CO2 utilization efficiency

Two main sources of CO2 metabolism in engineered E. coli are xylose and CO2. CO2 utilization rate varies under different condition. We use 5% CO2 (about 2.6 mM) and 0.4% (about 26 mM) xylose in experiment as an optimization CO2 utilization rate. Constant CO2 condition and limited CO2 condition also effects metabolism performance. In other words, open system and close system showed different results. Therefore, adjust initial concentration of CO2 and Xylose and choose open or close system to see the change of pyruvate production.

References

  1. Jacqueline E. G, Christopher P. L, Maciek R. A. Comprehensive analysis of glucose and xylose metabolism in Escherichia coli under aerobic and anaerobic conditions by 13C metabolic flux analysis. Metab Eng. 2017 Jan; 39: 9–18.
  2. Uwe Sauer, Bernhard J. E. 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.
  3. Fuyu G, Guoxia L, Xiaoyun Z, Jie Z, Zhen C and Yin L. Quantitative analysis of an engineered CO2-fixing Escherichia colireveals great potential of heterotrophic CO2 fixation. Gong et al. Biotechnology for Biofuels, 2015, 8:86.
  4. Y. Pocker, and Joan S. Y. Ng. Plant carbonic anhydrase. Properties and carbon dioxide hydration kinetics. Biochemistry, 1973, 12 (25), pp 5127–5134.

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