Difference between revisions of "Team:HUST-China/Comparison between PSB"

 
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                               <li><a class="waves-effect waves-dark" href="https://2018.igem.org/Team:HUST-China/Modeling overview">Modeling overview</a></li>
 
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                               <li><a class="waves-effect waves-dark" href="https://2018.igem.org/Team:HUST-China/Comparison between PSB">Comparison between PSB</a></li>
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                               <li><a class="waves-effect waves-dark" href="https://2018.igem.org/Team:HUST-China/model_of_systems">Model of Systems</a></li>
 
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                               <li><a class="waves-effect waves-dark" href="https://2018.igem.org/Team:HUST-China/Software">Intelligent device software</a></li>  
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                               <li><a class="waves-effect waves-dark" href="https://2018.igem.org/Team:HUST-China/Collaborations">Human Practices</a></li>
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         <h2 class="pageTitle">Comparison_between_PSB</h2>
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                  <p>This page has been moved to <a href="https://2018.igem.org/Team:HUST-China/model_of_systems">"Model of Systems"</a> </p>
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<p>If your browser haven't jumped to that page automatically, please click the link above.</p>
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                   <h3><strong>1. <span class="red-content">Abstract</span></strong></h3>
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                   <h3><strong>Part1: <span class="red-content">Abstract</span></strong></h3>
 
                   <p>Modelling is a powerful tool in synthetic biology that allows us to get a deeper understanding of our system. In order to see whether our system can work and how our system will work, we build this model to simulate our system. This model shows us the details of our system and give our intelligent device software data so that we can change the environment to increase the efficiency and stability of Optopia.</p>
 
                   <p>Modelling is a powerful tool in synthetic biology that allows us to get a deeper understanding of our system. In order to see whether our system can work and how our system will work, we build this model to simulate our system. This model shows us the details of our system and give our intelligent device software data so that we can change the environment to increase the efficiency and stability of Optopia.</p>
 
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                   <h3><strong>2. <span class="red-content">Overview</span></strong></h3>
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                   <h3><strong>Part2: <span class="red-content">Overview</span></strong></h3>
 
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             <h3 style="text-indent: 2em;"><span class="red-content">functions</span></strong></h3>
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                        <h3><b>Parameters</b></h3>
 
 
                             <tr>
 
                             <tr>
 
                               <th>Parameter</th>
 
                               <th>Parameter</th>
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                               <td>k<sub>CO<sub>2</sub>,Rps</sub></td>
 
                               <td>k<sub>CO<sub>2</sub>,Rps</sub></td>
 
                               <td>Yield coefficient of Rps</td>
 
                               <td>Yield coefficient of Rps</td>
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                                 <td>4.124×10-6</td>
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                                 <td>4.124×10<sup>-6</sup></td>
 
                                 <td>g⋅L<sup>-1</sup></td>
 
                                 <td>g⋅L<sup>-1</sup></td>
 
                               <td>Fitting from reference <sup>[5]</sup></td>
 
                               <td>Fitting from reference <sup>[5]</sup></td>
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                               <td>Y<sub>CO<sub>2</sub>,Rps</sub></td>
 
                               <td>Y<sub>CO<sub>2</sub>,Rps</sub></td>
 
                               <td>CO<sub>2</sub> producing coefficient related to lactate consuming.</td>
 
                               <td>CO<sub>2</sub> producing coefficient related to lactate consuming.</td>
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                                 <td>2.340×10<sub>2</sub></td>
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                                 <td>2.340×10<sup>2</sup></td>
 
                                 <td>1</sup></td>
 
                                 <td>1</sup></td>
 
                               <td>Fitting from reference <sup>[5]</sup></td>
 
                               <td>Fitting from reference <sup>[5]</sup></td>
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                            <tr>
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                              <th>Parameter</th>
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                              <th>Description</th>
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                              <th>Value</th>
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                              <th>Unit</th>
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                              <th>Source</th>
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                            </tr>
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                              <td>μ<sub>Shewa,max</sub></td>
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                              <td>maximum specific growth rate of biomass</td>
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                                <td>1.192×10<sup>-1</sup></td>
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                                <td>g/(L·h)</td>
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                              <td>Fitting from reference <sup>[8]</sup></td>
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                            </tr>
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                          <tr>
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                              <td>c<sub>Shewa,max</sub></td>
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                              <td>maximum biomass (dry weight) of Shewanella <sup>[8]</sup>  ——Li F et al. 2018, 7</td>
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                                <td>1.531×10<sup>-3</sup></td>
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                                <td>g/L</td>
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                              <td>Fitting from reference <sup>[4]</sup></td>
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                            </tr>
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                            <tr>
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                              <td>k<sub>Shewa,O<sub>2</sub></sub> </td>
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                              <td>a parameter influencing the relationship between substances and biomass</td>
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                                <td>1.332×10<sup>-5</sup></td>
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                                <td>g/L</td>
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                              <td>Fitting from reference <sup>[9]</sup></td>
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                            </tr>
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                            <tr>
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                              <td>k<sub>Shewa,Lac</sub></td>
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                              <td>a parameter influencing the relationship between substances and biomass</td>
 +
                                <td>4.869×10<sup>-1</sup></td>
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                                <td>1</sup></td>
 +
                              <td>Fitting from reference <sup>[5]</sup></td>
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                            </tr>
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                            <tr>
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                              <td>k<sub>Shewa,1</sub></</td>
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                              <td>correction term regarding the rate of consumption of lactate</td>
 +
                                <td>7.325×10<sup>1</sup></td>
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                                <td>-</td>
 +
                              <td>Fitting from reference <sup>[9]</sup></td>
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                            </tr>
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                            <tr>
 +
                              <td>k<sup>'</sup><sub>Shewa,2</sub></td>
 +
                              <td>simplified coefficient about the Nernst equation</td>
 +
                                <td>1.235×10<sup>-1</sup></td>
 +
                                <td>-</td>
 +
                              <td>Fitting from reference <sup>[9]</sup></td>
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                            </tr>
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                            <tr>
 +
                              <td>T</td>
 +
                              <td>current temperature</td>
 +
                                <td>298</td>
 +
                                <td>K</td>
 +
                              <td>Experiment data</td>
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                            </tr>
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                            <tr>
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                              <td>v<sub>Shewa,max</sub></td>
 +
                              <td>maximum lactate consumption rate per unit biomass</td>
 +
                                <td>7.012×10<sup>-1</sup></td>
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                                <td>g/(L·h)</td>
 +
                              <td>Fitting from reference <sup>[9]</sup></td>
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                            </tr>
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                            <tr>
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                              <td>k<sub>Shewa,3</sub></td>
 +
                              <td>constant value about lactate consuming</td>
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                                <td>3.056×10<sup>-1</sup></td>
 +
                                <td>g/L</td>
 +
                              <td>Fitting from reference <sup>[9]</sup></td>
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                            </tr>
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 +
                      </table>
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                     <h3><strong>Part3: <span class="red-content">Whole design</span></strong></h3>
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                     <h3><strong>Part3: <span class="red-content">Result</span></strong></h3>
 
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                        <h3>Design of MFC</h3>
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                         <p>We have designed a bipolar chamber MFC this year. Proton exchange membrane divided it into anode chamber and cathode chamber. Anode chamber containing S.oneidensis, nutrient substance(LB、lactate ) or other electrical producing microbes were sealed to prevent the entry of external oxygen. Considering safety and oxidation-reduction potential, we put ferric chloride solution in cathode chamber so that S.oneidensis can transfer electrons outside of their membranes by electron transport chain. Then electrons will reduce ferric ion into ferrous through carbon cloth and produce electricity.We recorded open circuit voltage curve and load voltage curve of MFCs in each different systems. Also, we have measured the biomass of each system in order to ensure whether the improved electricity could be attributed to more attached <i>Shewanella</i> cells on the anodes or the higher electroactivity of single cell.[11] </p>
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                          The voltage output of the three systems (Rhodopseudomonas palustris- Shewanella, Synechocystis - Shewanella and Shewanella only) are shown in the following figure:
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                        <img class="img-responsive" src="https://static.igem.org/mediawiki/2018/archive/9/92/20181017203446%21T--HUST-China--2018-psb-pic10086.png">
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                        <p>
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                              <p class="red-content"><strong>Co-culture</strong></p>
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                          The figure shows that because Rhodopseudomonas palustris  and Synechocystis can produce lactate, these two systems can produce electricity more efficiently and steadily, which demonstrates the value and feasibility of our project. In the beginning of the Synechocystis-Shewanella system, oxygen produced by Synechocystis inhibited the electricity production of Shewanella, so this system doesn’t have peak value.
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                                <p>Obviously, the ecological relationship between microorganisms is very complex. There is not only the competition between them for the nutrient, but also the regulation of metabolites among them including induction, transgenosis and synergistic metabolism. Besides, it has been found that the co-culture of microorganisms can improve the electric efficiency of Microbial Fuel Cell under certain conditions.  </p>
+
                        </p>
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                                <p>Metabolites exchange is a common relationship in co-culturing. Therefore, we have designed a clear microbial metabolic pathway to achieve the conversion from light to electricity as well as used more potential symbiotic relationships between the flora to help improve the electricity production efficiency of MFC.</p>
+
                        After molecular engineering, we get experiment data. It can fit our model result well. This demonstrates our model is right, so we can design a software based on model to tell us a better application experiment protocol which can get better result.
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                                  <p>By consulting literature, we found two kinds of microorganisms——Cyanobacteria and <i>Rhodopseudomonas palustris</i>, both of which can utilize light energy and provide lactate to S.oneidensis after doing molecular construction.  </p>
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                        <p>
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                                    <p>In order to provide a basic growth environment, we mix the culture medium of different strains.（Please refer to our protocol section for the composition of the mediums.）</p>
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                                <p class="red-content"><strong><i>Synechocystis</i> PCC6803</strong></p>
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                                <p>Lactate produced by <i>Synechocystis</i> PCC6803 can be used as the optimal carbon source for <i>Shewanella</i>. At the same time, acetate produced by <i>Shewanella</i> can be used as the organic carbon source of <i>Synechocystis</i> PCC6803 to increase the lactate production. And the metabolite exchange of <i>Synechocystis</i> PCC6803 and <i>Shewanella</i> is the basis for our photoautotrophic MFC.[12]. </p>
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                                  <p class="red-content"><strong><i>Rhodopseudomonas palustris</i></strong></p>
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                                    <p>We attempted to engineer <i>Rhodopseudomonas palustris</i> by synthetic biology to achieve the same or a better function of Synechococcus elongatus.</p>
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                                    <p>In the preliminary experiment, we found that there may be more potential interactions in the co-culture of <i>Rhodopseudomonas palustris</i> and <i>Shewanella</i>, which can greatly improve the coulombic efficiency of our MFC (please refer our results section for more detials). This is an unexpected surprise for us, which improve to our confidence in the success of the project.</p>
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                    <h3><strong>Part4: <span class="red-content">Disscussion</span></strong></h3>
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                        Based the insight we have gained from modeling, we find that concentration of carbon dioxide is the major limitation of Synechocystis-Shewanella system. Because low concentration of carbon dioxide will limit photosynthesis of Synechocystis, producing less lactate. Finally it leads to low electricity production. (Rhodopseudomonas can utilize the metabolic waste of Shewanella, so it need less carbon dioxide) Therefore, we add carbon dioxide to system and find that it can improve the electricity production. However, if we add too much carbon dioxide, the production will decrease, because excess carbon dioxide will inhibit the photosynthesis. (David et al. 2015)[1]1Finally, we find that the system has the highest voltage output when we add carbon dioxide 2.103*〖10〗^(-4)  g⁄*h.
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