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− | + | <div class="headstyle"> | |
+ | <h1 class="head">CO<sub>2</sub> Utilization Result Analysis</h1> | ||
+ | </div> | ||
+ | <div class="righttitle"> | ||
+ | <h6 class="subtitle">Let Numbers Talk</h6> | ||
+ | </div> | ||
<div class="navbar-example"> | <div class="navbar-example"> | ||
<div class="row"> | <div class="row"> | ||
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<a class="list-group-item list-group-item-action" href="#CO2_uptake">CO<sub>2</sub> uptake</a> | <a class="list-group-item list-group-item-action" href="#CO2_uptake">CO<sub>2</sub> uptake</a> | ||
<a class="list-group-item list-group-item-action" href="#Metabolism_Flux">Metabolism Flux</a> | <a class="list-group-item list-group-item-action" href="#Metabolism_Flux">Metabolism Flux</a> | ||
− | <a class="list-group-item list-group-item-action" href="#Fitting_Experiment_data"> | + | <a class="list-group-item list-group-item-action" href="#Fitting_Experiment_data">Experimental data</a> |
− | <a class="list-group-item list-group-item-action" href="#reference"> | + | <a class="list-group-item list-group-item-action" href="#reference">References</a> |
<a class="list-group-item list-group-item-action" href="#"><i class="fa fa-arrow-up fa-1x" aria-hidden="true"></i></a> | <a class="list-group-item list-group-item-action" href="#"><i class="fa fa-arrow-up fa-1x" aria-hidden="true"></i></a> | ||
</div> | </div> | ||
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<div id="Analysis"> | <div id="Analysis"> | ||
<h3>Analysis</h3> | <h3>Analysis</h3> | ||
− | <p class="pcontent">There are three | + | <p class="pcontent">There are three major questions we have answered in result analysis</p> |
<ol> | <ol> | ||
− | <li class="licontent"><a class="link" href="#CO2_uptake">How | + | <li class="licontent"><a class="link" href="#CO2_uptake">How much CO<sub>2</sub> (air) uptake by engineering <i>E. coli</i>?</a></li> |
− | <li class="licontent"><a class="link" href="#Metabolism_Flux">How | + | <li class="licontent"><a class="link" href="#Metabolism_Flux">How much CO<sub>2</sub> can be fixed in biomass?</a></li> |
<li class="licontent"><a class="link" href="#Fitting_Experiment_data">If the pyruvate trend match biomass trend?</a></li> | <li class="licontent"><a class="link" href="#Fitting_Experiment_data">If the pyruvate trend match biomass trend?</a></li> | ||
</ol> | </ol> | ||
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<div id="centerimg"> | <div id="centerimg"> | ||
<img class="oneimg" src="https://static.igem.org/mediawiki/2018/5/54/T--NCKU_Tainan--analysis_uptake.png"> | <img class="oneimg" src="https://static.igem.org/mediawiki/2018/5/54/T--NCKU_Tainan--analysis_uptake.png"> | ||
− | <p class="pcenter">Fig | + | <p class="pcenter">Fig 1. CO<sub>2</sub> uptake under closed system</p> |
</div> | </div> | ||
<p class="pcontent">However, we cannot set a CO<sub>2</sub> utilization system in a closed system. | <p class="pcontent">However, we cannot set a CO<sub>2</sub> utilization system in a closed system. | ||
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uptake by <i>E. coli</i>. Its CO<sub>2</sub> uptake rate change with time as well. | uptake by <i>E. coli</i>. Its CO<sub>2</sub> uptake rate change with time as well. | ||
As a result, we collect the CO<sub>2</sub> uptake rate and then calculate with the xylose consumed rate and | As a result, we collect the CO<sub>2</sub> uptake rate and then calculate with the xylose consumed rate and | ||
− | pyruvate produced rate. What’s more, the main reaction of CO<sub>2</sub> in engineered <i>E. coli</i> happened between | + | pyruvate produced rate. What’s more, the main reaction of CO<sub>2</sub> in engineered <i>E. coli</i> happened between RuBP to 3PGA, |
which is another part we are going to discuss. | which is another part we are going to discuss. | ||
</p> | </p> | ||
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<p class="pcontent">Time A was about 10 min (or 700 s) with [CO<sub>2</sub> uptake] reach 1 mM, causing 25% CO<sub>2</sub> uptake in total.</p> | <p class="pcontent">Time A was about 10 min (or 700 s) with [CO<sub>2</sub> uptake] reach 1 mM, causing 25% CO<sub>2</sub> uptake in total.</p> | ||
<p class="pcontent">Time B was about 1 hour (or 3500 s) with [CO<sub>2</sub> uptake] equals to [air CO<sub>2</sub>], causing 75% CO<sub>2</sub> uptake in an hour.</p> | <p class="pcontent">Time B was about 1 hour (or 3500 s) with [CO<sub>2</sub> uptake] equals to [air CO<sub>2</sub>], causing 75% CO<sub>2</sub> uptake in an hour.</p> | ||
− | <p class="pcontent">Time C was about 1.5 hour (or 8000 s) for [CO<sub>2</sub> uptake] reach balance with the highest CO<sub>2</sub> uptake percentage, | + | <p class="pcontent">Time C was about 1.5 hour (or 8000 s) for [CO<sub>2</sub> uptake] reach balance with the highest CO<sub>2</sub> uptake percentage, 88%.</p> |
</div> | </div> | ||
<div class="card card-body"> | <div class="card card-body"> | ||
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<p class="pcenter">Table 2 </p> | <p class="pcenter">Table 2 </p> | ||
<p class="pcenter">xylose consumed rate and pyruvate produced rate under different CO<sub>2</sub> uptake time interval without CA</p> | <p class="pcenter">xylose consumed rate and pyruvate produced rate under different CO<sub>2</sub> uptake time interval without CA</p> | ||
+ | <p class="pcontent">From table 1 and table 2, we knew that the highest pyruvate produced rate happened under the lowest CO<sub>2</sub> uptake percentage. | ||
+ | Besides, pyruvate produced rate of engineered <i>E. coli</i> with CA is higher than that of engineered <i>E. coli</i> without CA. | ||
+ | Although our working space was open system that we cannot sense precise data of the change of CO<sub>2</sub> concentration. | ||
+ | Through pyruvate produced rate, we can easily recognize which phase of CO<sub>2</sub> uptake and then figure out the percentage of total CO<sub>2</sub> uptake. | ||
+ | It is the method we calculate how much CO<sub>2</sub> uptake by our engineered <i>E. coli</i>. | ||
+ | </p> | ||
</div> | </div> | ||
<div class="row"> | <div class="row"> | ||
<div class="col-4" id="centerimg"> | <div class="col-4" id="centerimg"> | ||
− | <img class="smallimg" src="https://static.igem.org/mediawiki/2018/0/00/T--NCKU_Tainan--analysis_fig3_A.png"> | + | <img class="smallimg" style="position:relative;" src="https://static.igem.org/mediawiki/2018/0/00/T--NCKU_Tainan--analysis_fig3_A.png"> |
<p class="pcenter">A</p> | <p class="pcenter">A</p> | ||
</div> | </div> | ||
<div class="col-4" id="centerimg"> | <div class="col-4" id="centerimg"> | ||
− | <img class="smallimg" src="https://static.igem.org/mediawiki/2018/1/18/T--NCKU_Tainan--analysis_fig3_B.png"> | + | <img class="smallimg" style="position:relative;" src="https://static.igem.org/mediawiki/2018/1/18/T--NCKU_Tainan--analysis_fig3_B.png"> |
<p class="pcenter">B</p> | <p class="pcenter">B</p> | ||
</div> | </div> | ||
<div class="col-4" id="centerimg"> | <div class="col-4" id="centerimg"> | ||
− | <img class="smallimg" src="https://static.igem.org/mediawiki/2018/3/32/T--NCKU_Tainan--analysis_fig3_C.png"> | + | <img class="smallimg" style="position:relative;" src="https://static.igem.org/mediawiki/2018/3/32/T--NCKU_Tainan--analysis_fig3_C.png"> |
<p class="pcenter">C</p> | <p class="pcenter">C</p> | ||
</div> | </div> | ||
<div class="col-12"> | <div class="col-12"> | ||
− | <p class="pcenter">Fig. | + | <p class="pcenter">Fig 2. Result of xylose and pyruvate under A, B, C, time interval</p> |
</div> | </div> | ||
</div> | </div> | ||
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What we can analysis is that the pyruvate produced rate being correlation with CO<sub>2</sub> uptake rate, | What we can analysis is that the pyruvate produced rate being correlation with CO<sub>2</sub> uptake rate, | ||
which help us to define the question that how much CO<sub>2</sub> uptake by engineered <i>E. coli</i>. | which help us to define the question that how much CO<sub>2</sub> uptake by engineered <i>E. coli</i>. | ||
− | It can also fit with | + | It can also fit with experimental data easily. Next, we discuss about the true CO<sub>2</sub> reaction in <i>E. coli</i> |
CO<sub>2</sub> utilization bypass pathway. Every single mole of CO<sub>2</sub> uptake will react | CO<sub>2</sub> utilization bypass pathway. Every single mole of CO<sub>2</sub> uptake will react | ||
− | with one mole of | + | with one mole of RuBP and then produce 2 mole of 3PGA. |
</p> | </p> | ||
<div id="centerimg"> | <div id="centerimg"> | ||
<img class="oneimg" src="https://static.igem.org/mediawiki/2018/0/08/T--NCKU_Tainan--analysis_fig4.png"> | <img class="oneimg" src="https://static.igem.org/mediawiki/2018/0/08/T--NCKU_Tainan--analysis_fig4.png"> | ||
− | <p class="pcenter">Fig. | + | <p class="pcenter">Fig 3. result of RuBP and 3PGA during CO<sub>2</sub> uptake</p> |
</div> | </div> | ||
− | <p class="pcontent">Since that | + | <p class="pcontent">Since that RuBP and 3PGA are just intermediate products in metabolism, |
their concentration is quite low. Besides, results of three CO<sub>2</sub> uptake time interval showed similar. | their concentration is quite low. Besides, results of three CO<sub>2</sub> uptake time interval showed similar. | ||
− | We still can see that 3PGA produced is 2 times larger | + | We still can see that 3PGA produced is 2 times larger than RuBP produced. |
We then calculate their produced rate in three CO<sub>2</sub> uptake time interval. | We then calculate their produced rate in three CO<sub>2</sub> uptake time interval. | ||
</p> | </p> | ||
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<tr> | <tr> | ||
<th colspan="1">Time interval</th> | <th colspan="1">Time interval</th> | ||
− | <th colspan="1"> | + | <th colspan="1">RuBp produced rate (mM/s)</th> |
<th colspan="1">3PGA produced rate (mM/s)</th> | <th colspan="1">3PGA produced rate (mM/s)</th> | ||
</tr> | </tr> | ||
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<div id="Metabolism_Flux"> | <div id="Metabolism_Flux"> | ||
<h3>Carbon metabolism flux</h3> | <h3>Carbon metabolism flux</h3> | ||
− | <p class="pcontent">The main | + | <p class="pcontent">The main metabolic pathway of xylose in <i>E. coli</i> is PP pathway and glycolysis. As for recombinant <i>E. coli</i>, |
it has multiple xylose metabolic pathways, and we can simplify them into original pathway and CO<sub>2</sub> Bypass pathway. | it has multiple xylose metabolic pathways, and we can simplify them into original pathway and CO<sub>2</sub> Bypass pathway. | ||
Therefore, we need to define the percentage of xylose, which is consumed by engineered <i>E. coli</i>, | Therefore, we need to define the percentage of xylose, which is consumed by engineered <i>E. coli</i>, | ||
entering CO<sub>2</sub> bypass pathway and utilize CO<sub>2</sub>. | entering CO<sub>2</sub> bypass pathway and utilize CO<sub>2</sub>. | ||
</p> | </p> | ||
− | <p class="pcontent">It | + | <p class="pcontent">It takes a lot of time to get absolute metabolic flux of CO<sub>2</sub> in engineered <i>E. coli</i> and require feed of <sup>13</sup>CO<sub>2</sub> during cultivation. |
Since the metabolic flux of the original metabolic pathway is quite stable, | Since the metabolic flux of the original metabolic pathway is quite stable, | ||
the relative metabolic flux of CO<sub>2</sub>-utilization over that of the original metabolic pathway could | the relative metabolic flux of CO<sub>2</sub>-utilization over that of the original metabolic pathway could | ||
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<div id="centerimg" class="col-5"> | <div id="centerimg" class="col-5"> | ||
<img id="fluximg" src="https://static.igem.org/mediawiki/2018/9/93/T--NCKU_Tainan--analysis_flux.png"> | <img id="fluximg" src="https://static.igem.org/mediawiki/2018/9/93/T--NCKU_Tainan--analysis_flux.png"> | ||
− | <p class="pcontent">Fig. | + | <p class="pcontent">Fig 4. carbon flux in engineered <i>E. coli</i></p> |
</div> | </div> | ||
<div class="col-7" id="part"> | <div class="col-7" id="part"> | ||
<p class="pcontent">X:Actual 3PGA detected from the original pathway = 3PGA<sub>0</sub></p> | <p class="pcontent">X:Actual 3PGA detected from the original pathway = 3PGA<sub>0</sub></p> | ||
− | <p class="pcontent">Y:Actual 3PAG detected from | + | <p class="pcontent">Y:Actual 3PAG detected from CO<sub>2</sub> bypass pathway = 3PGA’</p> |
<p class="pcontent">a:3PGA generated from the central pathway</p> | <p class="pcontent">a:3PGA generated from the central pathway</p> | ||
− | <p class="pcontent"> | + | <p class="pcontent">b:CO<sub>2</sub> fixed by the CO<sub>2</sub> bypass pathway</p> |
− | <p class="pcontent"> | + | <p class="pcontent">c:mole of 3PGA<sub>0</sub> into downstream</p> |
− | <p class="pcontent">d : | + | <p class="pcontent">d : mole of 3PGA’ into downstream</p> |
</div> | </div> | ||
</div> | </div> | ||
<p class="pcontent">To define the MFI<sub>CO<sub>2</sub></sub>, we use CO<sub>2</sub> fixed by the CO<sub>2</sub> bypass pathway, | <p class="pcontent">To define the MFI<sub>CO<sub>2</sub></sub>, we use CO<sub>2</sub> fixed by the CO<sub>2</sub> bypass pathway, | ||
noted as b, divided by the 3PGA generated from the central pathway, | noted as b, divided by the 3PGA generated from the central pathway, | ||
− | noted as a. We also assume c is | + | noted as a. We also assume c is mole of 3PGA¬0 and d is mole of 3PGA’ that channels into downsteam metabolism. |
− | After metabolism, (a+b) | + | After metabolism, (a+b) mole of 3PGA<sub>0</sub> and b mole of 3PGA’ are generated. |
</p> | </p> | ||
<p class="pcontent">Besides, X and Y represent the actual 3PGA detected from the original pathway and CO<sub>2</sub> bypass pathway, | <p class="pcontent">Besides, X and Y represent the actual 3PGA detected from the original pathway and CO<sub>2</sub> bypass pathway, | ||
− | which show in 3PGA<sub>0</sub> and 3PGA’ in the | + | which show in 3PGA<sub>0</sub> and 3PGA’ in the Fig 1., respectively. |
− | In the experiment, we use | + | In the experiment, we use <sup>13</sup>C-labeled CO<sub>2</sub> and unlabeled sugar to get the amount of 3PGA<sub>0</sub> and 3PGA’. |
However, it was reported that 3.45% of unlabeled 3PGA, which is noted as 3PGA’, | However, it was reported that 3.45% of unlabeled 3PGA, which is noted as 3PGA’, | ||
will convert to its isotopic during the culturing <i>E. coli</i> strains in medium. | will convert to its isotopic during the culturing <i>E. coli</i> strains in medium. | ||
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we derive equation (1) and (2) into a final relationship between a, b, x, and y. | we derive equation (1) and (2) into a final relationship between a, b, x, and y. | ||
</p> | </p> | ||
− | <p class="pcontent">$${MFI(Metabolic flux index) = {b \over a} = {{0.97y-0.03x} \over {1.03x-0.97y}}}$$</p> | + | <p class="pcontent">$${MFI(Metabolic \ flux \ index) = {b \over a} = {{0.97y-0.03x} \over {1.03x-0.97y}}}$$</p> |
<p class="pcontent">As a result, we only need the amount of 3PGA<sub>0</sub> and 3PGA’ to calculate MFI<sub>CO<sub>2</sub></sub>. | <p class="pcontent">As a result, we only need the amount of 3PGA<sub>0</sub> and 3PGA’ to calculate MFI<sub>CO<sub>2</sub></sub>. | ||
− | Through modelling, we supply | + | Through modelling, we supply 4 (g/l) xylose and 5% CO<sub>2</sub> to get the data of 3PGA<sub>0</sub> and 3PGA’, |
which helps us to adjust the rate between xylose and CO<sub>2</sub> sources. | which helps us to adjust the rate between xylose and CO<sub>2</sub> sources. | ||
</p> | </p> | ||
<div id="centerimg"> | <div id="centerimg"> | ||
<img class="oneimg" src="https://static.igem.org/mediawiki/2018/c/cd/T--NCKU_Tainan--analysis_3PGA.png"> | <img class="oneimg" src="https://static.igem.org/mediawiki/2018/c/cd/T--NCKU_Tainan--analysis_3PGA.png"> | ||
− | <p class="pcenter">Fig | + | <p class="pcenter">Fig 5. The result of 3PGA produced form PP pathway (original metabolism) and from CO<sub>2</sub> bypass pathway.</p> |
</div> | </div> | ||
<div class="card card-body"> | <div class="card card-body"> | ||
− | + | <p class="pcenter">Table 3 MFI<sub>CO<sub>2</sub></sub> at different time</p> | |
+ | <table> | ||
<tr> | <tr> | ||
<th colspan="1">Time</th> | <th colspan="1">Time</th> | ||
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</tr> | </tr> | ||
</table> | </table> | ||
− | + | ||
</div> | </div> | ||
<div id="Fitting_Experiment_data"> | <div id="Fitting_Experiment_data"> | ||
− | <h4>Fitting | + | <h4>Fitting Experimental data</h4> |
− | <p class="pcontent">The purpose of modelling is to predict the result before doing | + | <p class="pcontent">The purpose of modelling is to predict the result before doing experimental data. |
Our model focus on the metabolism pathway in engineered <i>E. coli</i>, | Our model focus on the metabolism pathway in engineered <i>E. coli</i>, | ||
trying to understand how <i>E. coli</i> utilize CO<sub>2</sub>. | trying to understand how <i>E. coli</i> utilize CO<sub>2</sub>. | ||
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<div id="centerimg"> | <div id="centerimg"> | ||
<img class="oneimg" src="https://static.igem.org/mediawiki/2018/e/e6/T--NCKU_Tainan--kinetic_law_fig6.png"> | <img class="oneimg" src="https://static.igem.org/mediawiki/2018/e/e6/T--NCKU_Tainan--kinetic_law_fig6.png"> | ||
− | <p class="pcenter">Fig. | + | <p class="pcenter">Fig 6. pyruvate produced under different CO<sub>2</sub> uptake condition (model result)</p> |
</div> | </div> | ||
<div id="centerimg"> | <div id="centerimg"> | ||
<img class="oneimg" src="https://static.igem.org/mediawiki/2018/1/12/T--NCKU_Tainan--analysis_p3_cell_growth.png"> | <img class="oneimg" src="https://static.igem.org/mediawiki/2018/1/12/T--NCKU_Tainan--analysis_p3_cell_growth.png"> | ||
− | <p class="pcenter">Fig. | + | <p class="pcenter">Fig 7. cell growth under different CO<sub>2</sub> conditions (experimental data)</p> |
+ | <p class="pcenter" style="font-size: 15px;">* LXSPC = Engineered <i>E. coli</i> contains PRK, Rubisco, and CA</p> | ||
+ | |||
</div> | </div> | ||
<p class="pcontent">The final goal of our project is to prove that our engineered <i>E. coli</i> could | <p class="pcontent">The final goal of our project is to prove that our engineered <i>E. coli</i> could | ||
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CO<sub>2</sub> convert into pyruvate through <i>E. coli</i> and then express on its cell growth. | CO<sub>2</sub> convert into pyruvate through <i>E. coli</i> and then express on its cell growth. | ||
Therefore, we can conclude that pyruvate production will have correlation with biomass, | Therefore, we can conclude that pyruvate production will have correlation with biomass, | ||
− | which | + | which confirms that our model is reasonable to show the result with pyruvate production. |
</p> | </p> | ||
</div> | </div> | ||
Line 311: | Line 325: | ||
<div id="reference"> | <div id="reference"> | ||
− | <h3> | + | <h3>References</h3> |
<ol> | <ol> | ||
− | + | <li class="smallp">Michaelis Menten Kinetics in bio – physic wiki, web : http://www.bio-physics.at/wiki/index.php?title=Michaelis_Menten_Kinetics</li> | |
<li class="smallp">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</li> | <li class="smallp">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</li> | ||
− | <li class="smallp"> | + | <li class="smallp">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.</li> |
− | <li class="smallp"> | + | <li class="smallp">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.</li> |
− | <li class="smallp"> | + | <li class="smallp"> W. Akira, N. Keisuke, H. Tomohiro, S. Ryohei, Reaction mechanism of phosphoribulokinase from a cyanobacterium, Synechococcus PCC7942. Photosynthesis Research 56: 27–33, 1998</li> |
− | <li class="smallp"> | + | <li class="smallp">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.</li> |
− | <li class="smallp"> | + | <li class="smallp"> 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</li> |
− | <li class="smallp">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 | + | <li class="smallp">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 <i>Escherichia Coli</i> Ribose-5-Phosphate Isomerase: A Ubiquitous Enzyme of the Pentose Phosphate Pathway and the Calvin Cycle Structure, Vol. 11, 31–42, January, 200</li> |
<li class="smallp">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.</li> | <li class="smallp">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.</li> | ||
<li class="smallp">Singh2006 TCA mtu model1. SBML2LATEX. Web : http: //www.ra.cs.uni-tuebingen.de/software/SBML2LaTeX</li> | <li class="smallp">Singh2006 TCA mtu model1. SBML2LATEX. Web : http: //www.ra.cs.uni-tuebingen.de/software/SBML2LaTeX</li> | ||
− | <li class="smallp"> | + | <li class="smallp">J. Shen, Modeling the glutamate–glutamine neurotransmitter cycle, Front. Neuroenergetics, 28 January 2013</li> |
− | <li class="smallp"> | + | <li class="smallp">X. Feng, H. Zhao, Investigating xylose metabolism in recombinant Saccharomyces cerevisiae via 13C metabolic flux analysis, Microb Cell Fact. 2013; 12: 114.</li> |
− | <li class="smallp"> | + | <li class="smallp">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</li> |
<li class="smallp">Kalle Hult rev 2005, 2007 Linda Fransson Department of Biotechnology KTH, Stockholm, Enzyme kinetics, An investigation of the enzyme glucose-6- phosphate isomerase</li> | <li class="smallp">Kalle Hult rev 2005, 2007 Linda Fransson Department of Biotechnology KTH, Stockholm, Enzyme kinetics, An investigation of the enzyme glucose-6- phosphate isomerase</li> | ||
<li class="smallp">Model name: “Mosca2012 - Central Carbon Metabolism Regulated by AKT”, SBML2LATEX. Web : http: //www.ra.cs.uni-tuebingen.de/software/SBML2LaTeX</li> | <li class="smallp">Model name: “Mosca2012 - Central Carbon Metabolism Regulated by AKT”, SBML2LATEX. Web : http: //www.ra.cs.uni-tuebingen.de/software/SBML2LaTeX</li> | ||
− | <li class="smallp"> | + | <li class="smallp">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</li> |
− | <li class="smallp"> | + | <li class="smallp">E. G. Jacqueline, P. L. Christopher, R. A. Maciek, Comprehensive analysis of glucose and xylose metabolism in <i>Escherichia Coli</i> under aerobic and anaerobic conditions by 13C metabolic flux analysis, Metabolic Engineering Volume 39, January 2017, Pages 9-18</li> |
− | <li class="smallp">N. | + | <li class="smallp">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</li> |
− | <li class="smallp"> | + | <li class="smallp">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.</li> |
− | <li class="smallp">K. Nielsen, P.G. Sørensen, F. Hynne, H. | + | <li class="smallp">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</li> |
<li class="smallp">UniProtKB - A0RV30 from web : https://www.uniprot.org/uniprot/A0RV30</li> | <li class="smallp">UniProtKB - A0RV30 from web : https://www.uniprot.org/uniprot/A0RV30</li> | ||
</ol> | </ol> | ||
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} | } | ||
} else { | } else { | ||
− | if ($(this).scrollTop() >= | + | if ($(this).scrollTop() >= 500) { |
var position = $("#sidelist").position(); | var position = $("#sidelist").position(); | ||
if(position == undefined){} | if(position == undefined){} | ||
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}); | }); | ||
}); | }); | ||
− | $(". | + | $(".oneimg").click(function(){ |
+ | if (this.classList.contains('clicked')) { | ||
+ | $('img').removeClass("clicked"); | ||
+ | this.classList.remove('clicked'); | ||
+ | } else { | ||
+ | $('img').removeClass("clicked"); | ||
+ | this.classList.add('clicked'); | ||
+ | } | ||
+ | }); | ||
+ | $(".smallimg").click(function(){ | ||
if (this.classList.contains('clicked')) { | if (this.classList.contains('clicked')) { | ||
$('img').removeClass("clicked"); | $('img').removeClass("clicked"); |
Latest revision as of 02:16, 18 October 2018