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<div class="row"> <!-- honestly idk why this is here - i just copied it from somewhere and then now i'm too scared to remove this class !--> | <div class="row"> <!-- honestly idk why this is here - i just copied it from somewhere and then now i'm too scared to remove this class !--> | ||
− | <div class="titleRegion" style="background-image: url(https://static.igem.org/mediawiki/2018/ | + | <div class="titleRegion" style="background-image: url(https://static.igem.org/mediawiki/2018/d/d0/T--UMaryland--PTNT5.png)"> |
<div class="container" style="height: 200px;"> | <div class="container" style="height: 200px;"> | ||
<div class="titleContainer"> | <div class="titleContainer"> | ||
− | <div class="titleText"> | + | <div class="titleText">TPA vs PCA Detection</div> |
− | <div class="subtitleText"> | + | <div class="subtitleText">a consideration of response time and sensitivity</div> |
</div> | </div> | ||
</div> | </div> | ||
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<div id="Overview"> | <div id="Overview"> | ||
<div class="meatMeat"> | <div class="meatMeat"> | ||
− | + | We found two potential biosensor systems that we could possibly use for detection of the degradation of PET, one which detected protocatechuate (PCA) and the other detecting terephthalate (TPA). To determine which sensor system was better for our needs, we used the MatLab SimBiology package to model the degradation of PET down to PCA and further to the cellular metabolite. The SimBiology files are available at this link: | |
</div> | </div> | ||
<div class="meatMeat"> | <div class="meatMeat"> | ||
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which are the depolymerization of PET into TPA, the degradation of TPA to PCA, the transport of PCA and TPA, and the expression of GFP from the activation of transcription factors. The parameters of the TPA and PCA sensor systems are described below: | which are the depolymerization of PET into TPA, the degradation of TPA to PCA, the transport of PCA and TPA, and the expression of GFP from the activation of transcription factors. The parameters of the TPA and PCA sensor systems are described below: | ||
</div> | </div> | ||
− | <div> | + | <div class="imageBox"> |
− | + | <img src="https://static.igem.org/mediawiki/2018/6/68/T--UMaryland--TPAvPCAtable.png" style="max-width: 100%" alt="Waluigi Time!"> | |
− | + | <div class="imageBoxDescription"></div> | |
− | + | ||
− | + | ||
</div> | </div> | ||
+ | |||
<div class="meatMeat"> | <div class="meatMeat"> | ||
− | + | Using SimBiology we created two sensor systems for our degradation analysis: | |
</div> | </div> | ||
− | + | <div class="imageBox"> | |
− | + | <img src="https://static.igem.org/mediawiki/2018/9/9e/T--UMaryland--Simbiochart.png" style="max-width: 100%" alt="Waluigi Time!"> | |
− | + | <div class="imageBoxDescription"></div> | |
− | + | ||
− | + | ||
</div> | </div> | ||
+ | |||
<div class="meatMeat"> | <div class="meatMeat"> | ||
− | + | Through an extensive literature search, we found the enzyme kinetics parameters and protein concentrations as listed below. We converted all values of Vmax and kcat in units of M product / (s * M protein). We used non-reversible Michaelis-Menten as our enzyme kinetics parameters except the degradation of PETase, which we approximated using our zero order enzyme kinetics equation <a href="https://2018.igem.org/Team:UMaryland/BCmodel"><u>described here</u></a> and the transport of TPA and PCA by TpiAB and PcaK respectively, which followed a law of mass action kinetics. | |
</div> | </div> | ||
− | <div> | + | |
− | + | <div class="imageBox"> | |
+ | <img src="https://static.igem.org/mediawiki/2018/c/c1/T--UMaryland--modeltable.png" style="max-width: 100%" alt="Waluigi Time!"> | ||
+ | <div class="imageBoxDescription"><a href="https://static.igem.org/mediawiki/2018/e/e7/T--UMaryland--simbioparameters.xlsx"><u>Excel file with links</u></a></div> | ||
</div> | </div> | ||
− | <div> | + | <div class="meatMeat"> |
− | + | We ran the simulation with the following parameters: | |
</div> | </div> | ||
− | |||
− | |||
<div class="meatMeat"> | <div class="meatMeat"> | ||
− | + | - “600 uM” of PET added in solution | |
</div> | </div> | ||
<div class="meatMeat"> | <div class="meatMeat"> | ||
− | + | - Constant enzyme concentrations | |
</div> | </div> | ||
<div class="meatMeat"> | <div class="meatMeat"> | ||
− | + | - Reversibility of reactions not considered | |
</div> | </div> | ||
− | <div class=" | + | <div class="meatMeat"> |
− | + | - Simulated rich oxygenated media with excess NADPH | |
− | + | ||
</div> | </div> | ||
<div class="meatMeat"> | <div class="meatMeat"> | ||
− | + | - Fixed 50 uM of transcription factor concentrations (a gross exaggeration) | |
</div> | </div> | ||
<div class="meatMeat"> | <div class="meatMeat"> | ||
− | + | - 30 Day simulation | |
</div> | </div> | ||
− | <div class=" | + | <div class="meatSubtitle"> |
− | + | Simulation Results | |
− | + | </div> | |
+ | <div class="center"> | ||
+ | <div class="imageBox"> | ||
+ | <img src="https://static.igem.org/mediawiki/2018/4/46/T--UMaryland--simresult1.png" style="max-width: 100%" alt="Waluigi Time!"> | ||
+ | <div class="imageBoxDescription"></div> | ||
+ | </div> | ||
</div> | </div> | ||
− | <div class=" | + | <div class="meatMeat"> |
− | + | In the PCA detection system, we predict that there are high levels of PCA in the media, but the rate limiting reaction in the degradation pathway is the conversion of DCD to PCA. Transport of PCA limits the activation of the PcaU. The model predicts that concentrations of PCA will exceed the solubility limit (120 uM in water), but we see that there is full activation of PcaU prior to the solubility limit being reached. There is rapid activation of PcaU at about 1.5 days. | |
− | + | ||
</div> | </div> | ||
− | + | <div class="center"> | |
− | + | <div class="imageBox"> | |
+ | <img src="https://static.igem.org/mediawiki/2018/2/2f/T--UMaryland--simresult2.png" style="max-width: 100%" alt="Waluigi Time!"> | ||
+ | <div class="imageBoxDescription"></div> | ||
+ | </div> | ||
</div> | </div> | ||
<div class="meatMeat"> | <div class="meatMeat"> | ||
− | + | In the TPA detection system we see an immediate increase in the concentration of TPA in the media, with a similar problem of the rate of transport limiting the activation of TphC. In this simulation, we see an increase in the time to full response to about 7 days, which is about 4x longer than the PCA based system. However, in this simulation we exceed the solubility limit of TPA (90 uM) rapidly, therefore we tweaked the model to a fixed concentration 90 uM concentration of TPA in the media. | |
</div> | </div> | ||
− | + | <div class="center"> | |
− | + | <div class="imageBox"> | |
− | + | <img src="https://static.igem.org/mediawiki/2018/b/bb/T--UMaryland--simresult3.png" style="max-width: 100%" alt="Waluigi Time!"> | |
− | + | <div class="imageBoxDescription"></div> | |
− | <img src="https://static.igem.org/mediawiki/2018/ | + | </div> |
</div> | </div> | ||
<div class="meatMeat"> | <div class="meatMeat"> | ||
− | + | In the fixed TPA concentration model, we see an even longer increase in the time to full response to almost 30 days, which is now 20x slower compared to the PCA based system. Therefore we concluded that for fastest response time to degradation of PET, a PCA based sensor system would be much better than a TPA based sensor system. | |
</div> | </div> | ||
<div class="meatMeat"> | <div class="meatMeat"> | ||
− | + | With regards to sensitivity, we were unable to get a clear picture from our literature search. We searched for lacZ activity which is downstream of the PCA or TPA activated promoter system. There are conflicting units of specific activity (U) and Miller Units, which cannot be converted between each other. However, we found that the detection limit of PCA is close to 1 uM while the detection of TPA is close to 10 uM [8,10]. Therefore we concluded that the sensitivity of the PCA sensor is also better than the TPA based sensor. </div> | |
</div> | </div> | ||
+ | <div class="meatSubtitle"> | ||
+ | Simulation Conclusions | ||
+ | </div> | ||
<div class="meatMeat"> | <div class="meatMeat"> | ||
− | - | + | - The biochemistry literature is of limited help when trying to acquire values |
+ | </div> | ||
+ | <div class="meatMeat"> | ||
+ | - PCA Detection System provides better response time and sensitivity vs.the TPA Detection System | ||
+ | </div> | ||
+ | <div class="meatMeat"> | ||
+ | - Transport across the membrane the limiting factor in both scenarios | ||
+ | </div> | ||
+ | <div class="meatMeat"> | ||
+ | - Increasing the expression of transport proteins the biggest challenge | ||
+ | </div> | ||
+ | <div class="meatMeat"> | ||
+ | - PcaK transport system is much faster and smaller than the TpiBA system | ||
+ | </div> | ||
+ | <div class="meatMeat"> | ||
+ | - Metabolism of PCA negligible in limiting response of PcaU system | ||
</div> | </div> | ||
− | + | <div> | |
− | + | 1. Sabathé, F. & Soucaille, P. Characterization of the CipA scaffolding protein and in vivo production of a minicellulosome in Clostridium acetobutylicum. J. Bacteriol. 185, 1092–1096 (2003). | |
</div> | </div> | ||
− | + | <div> | |
− | + | 2. Yoshida, S. et al. A bacterium that degrades and assimilates poly(ethylene terephthalate). Science 351, 1196–1199 (2016). | |
</div> | </div> | ||
− | + | <div> | |
− | + | 3. Fukuhara, Y., Kasai, D., Katayama, Y., Fukuda, M. & Masai, E. Enzymatic properties of terephthalate 1,2-dioxygenase of Comamonas sp. strain E6. Biosci. Biotechnol. Biochem. 72, 2335–2341 (2008). </div> | |
+ | <div> | ||
+ | 4. Salier, E., Laue, H., Schläfli Oppenberg, H. R. & Cook, A. M. Purification and some properties of (1R,2S)-1,2-dihydroxy-3,5-cyclohexadiene-1,4-dicarboxylate dehydrogenase from Comamonas testosteroni T-2. FEMS Microbiol. Lett. 130, 97–102 (1995). | ||
</div> | </div> | ||
− | + | <div> | |
− | + | 5. Fujisawa, H. & Hayaishi, O. Protocatechuate 3,4-dioxygenase. I. Crystallization and characterization. J. Biol. Chem. 243, 2673–2681 (1968). | |
− | + | ||
</div> | </div> | ||
− | <div | + | <div> |
− | + | 6. Nichols, N. N. & Harwood, C. S. PcaK, a high-affinity permease for the aromatic compounds 4-hydroxybenzoate and protocatechuate from Pseudomonas putida. J. Bacteriol. 179, 5056–5061 (1997). | |
</div> | </div> | ||
+ | <div> | ||
+ | 6. Nichols, N. N. & Harwood, C. S. PcaK, a high-affinity permease for the aromatic compounds 4-hydroxybenzoate and protocatechuate from Pseudomonas putida. J. Bacteriol. 179, 5056–5061 (1997). | ||
+ | </div> | ||
+ | <div> | ||
+ | 7. Hosaka, M. et al. Novel tripartite aromatic acid transporter essential for terephthalate uptake in Comamonas sp. strain E6. Appl. Environ. Microbiol. 79, 6148–6155 (2013). | ||
+ | </div> | ||
+ | <div> | ||
+ | 8. Siehler, S. Y., Dal, S., Fischer, R., Patz, P. & Gerischer, U. Multiple-level regulation of genes for protocatechuate degradation in Acinetobacter baylyi includes cross-regulation. Appl. Environ. Microbiol. 73, 232–242 (2007). | ||
+ | </div> | ||
+ | <div> | ||
+ | 9. Trautwein, G. & Gerischer, U. Effects exerted by transcriptional regulator PcaU from Acinetobacter sp. strain ADP1. J. Bacteriol. 183, 873–881 (2001). | ||
+ | </div> | ||
+ | <div> | ||
+ | 10. Kasai, D., Kitajima, M., Fukuda, M. & Masai, E. Transcriptional regulation of the terephthalate catabolism operon in Comamonas sp. strain E6. Appl. Environ. Microbiol. 76, 6047–6055 (2010). | ||
+ | </div> | ||
+ | </div> | ||
</div> | </div> | ||
</div> | </div> |
Latest revision as of 02:04, 18 October 2018
TPA vs PCA Detection
a consideration of response time and sensitivity
We found two potential biosensor systems that we could possibly use for detection of the degradation of PET, one which detected protocatechuate (PCA) and the other detecting terephthalate (TPA). To determine which sensor system was better for our needs, we used the MatLab SimBiology package to model the degradation of PET down to PCA and further to the cellular metabolite. The SimBiology files are available at this link:
Simulation Setup
There are four major processes that occur in our sensor setup as shown below:
which are the depolymerization of PET into TPA, the degradation of TPA to PCA, the transport of PCA and TPA, and the expression of GFP from the activation of transcription factors. The parameters of the TPA and PCA sensor systems are described below:
Using SimBiology we created two sensor systems for our degradation analysis:
Through an extensive literature search, we found the enzyme kinetics parameters and protein concentrations as listed below. We converted all values of Vmax and kcat in units of M product / (s * M protein). We used non-reversible Michaelis-Menten as our enzyme kinetics parameters except the degradation of PETase, which we approximated using our zero order enzyme kinetics equation described here and the transport of TPA and PCA by TpiAB and PcaK respectively, which followed a law of mass action kinetics.
We ran the simulation with the following parameters:
- “600 uM” of PET added in solution
- Constant enzyme concentrations
- Reversibility of reactions not considered
- Simulated rich oxygenated media with excess NADPH
- Fixed 50 uM of transcription factor concentrations (a gross exaggeration)
- 30 Day simulation
Simulation Results
In the PCA detection system, we predict that there are high levels of PCA in the media, but the rate limiting reaction in the degradation pathway is the conversion of DCD to PCA. Transport of PCA limits the activation of the PcaU. The model predicts that concentrations of PCA will exceed the solubility limit (120 uM in water), but we see that there is full activation of PcaU prior to the solubility limit being reached. There is rapid activation of PcaU at about 1.5 days.
In the TPA detection system we see an immediate increase in the concentration of TPA in the media, with a similar problem of the rate of transport limiting the activation of TphC. In this simulation, we see an increase in the time to full response to about 7 days, which is about 4x longer than the PCA based system. However, in this simulation we exceed the solubility limit of TPA (90 uM) rapidly, therefore we tweaked the model to a fixed concentration 90 uM concentration of TPA in the media.
In the fixed TPA concentration model, we see an even longer increase in the time to full response to almost 30 days, which is now 20x slower compared to the PCA based system. Therefore we concluded that for fastest response time to degradation of PET, a PCA based sensor system would be much better than a TPA based sensor system.
With regards to sensitivity, we were unable to get a clear picture from our literature search. We searched for lacZ activity which is downstream of the PCA or TPA activated promoter system. There are conflicting units of specific activity (U) and Miller Units, which cannot be converted between each other. However, we found that the detection limit of PCA is close to 1 uM while the detection of TPA is close to 10 uM [8,10]. Therefore we concluded that the sensitivity of the PCA sensor is also better than the TPA based sensor.
Simulation Conclusions
- The biochemistry literature is of limited help when trying to acquire values
- PCA Detection System provides better response time and sensitivity vs.the TPA Detection System
- Transport across the membrane the limiting factor in both scenarios
- Increasing the expression of transport proteins the biggest challenge
- PcaK transport system is much faster and smaller than the TpiBA system
- Metabolism of PCA negligible in limiting response of PcaU system
1. Sabathé, F. & Soucaille, P. Characterization of the CipA scaffolding protein and in vivo production of a minicellulosome in Clostridium acetobutylicum. J. Bacteriol. 185, 1092–1096 (2003).
2. Yoshida, S. et al. A bacterium that degrades and assimilates poly(ethylene terephthalate). Science 351, 1196–1199 (2016).
3. Fukuhara, Y., Kasai, D., Katayama, Y., Fukuda, M. & Masai, E. Enzymatic properties of terephthalate 1,2-dioxygenase of Comamonas sp. strain E6. Biosci. Biotechnol. Biochem. 72, 2335–2341 (2008).
4. Salier, E., Laue, H., Schläfli Oppenberg, H. R. & Cook, A. M. Purification and some properties of (1R,2S)-1,2-dihydroxy-3,5-cyclohexadiene-1,4-dicarboxylate dehydrogenase from Comamonas testosteroni T-2. FEMS Microbiol. Lett. 130, 97–102 (1995).
5. Fujisawa, H. & Hayaishi, O. Protocatechuate 3,4-dioxygenase. I. Crystallization and characterization. J. Biol. Chem. 243, 2673–2681 (1968).
6. Nichols, N. N. & Harwood, C. S. PcaK, a high-affinity permease for the aromatic compounds 4-hydroxybenzoate and protocatechuate from Pseudomonas putida. J. Bacteriol. 179, 5056–5061 (1997).
6. Nichols, N. N. & Harwood, C. S. PcaK, a high-affinity permease for the aromatic compounds 4-hydroxybenzoate and protocatechuate from Pseudomonas putida. J. Bacteriol. 179, 5056–5061 (1997).
7. Hosaka, M. et al. Novel tripartite aromatic acid transporter essential for terephthalate uptake in Comamonas sp. strain E6. Appl. Environ. Microbiol. 79, 6148–6155 (2013).
8. Siehler, S. Y., Dal, S., Fischer, R., Patz, P. & Gerischer, U. Multiple-level regulation of genes for protocatechuate degradation in Acinetobacter baylyi includes cross-regulation. Appl. Environ. Microbiol. 73, 232–242 (2007).
9. Trautwein, G. & Gerischer, U. Effects exerted by transcriptional regulator PcaU from Acinetobacter sp. strain ADP1. J. Bacteriol. 183, 873–881 (2001).
10. Kasai, D., Kitajima, M., Fukuda, M. & Masai, E. Transcriptional regulation of the terephthalate catabolism operon in Comamonas sp. strain E6. Appl. Environ. Microbiol. 76, 6047–6055 (2010).
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