Difference between revisions of "Team:HUST-China/Modeling overview"

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                               <li><a class="waves-effect waves-dark" href="https://2018.igem.org/Team:HUST-China/Results">Results</a></li>
 
                               <li><a class="waves-effect waves-dark" href="https://2018.igem.org/Team:HUST-China/Results">Results</a></li>
 
                               <li><a class="waves-effect waves-dark" href="https://2018.igem.org/Team:HUST-China/wetlab/protocols">Protocols</a></li>
 
                               <li><a class="waves-effect waves-dark" href="https://2018.igem.org/Team:HUST-China/wetlab/protocols">Protocols</a></li>
                               <li><a class="waves-effect waves-dark" href="https://2018.igem.org/Team:HUST-China/InterLab">Interlab</a></li>
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                               <li><a class="waves-effect waves-dark" href="https://2018.igem.org/Team:HUST-China/InterLab">Interlab</a></li>  
                               <li><a class="waves-effect waves-dark" href="https://2018.igem.org/Team:HUST-China/Improve">Improve</a></li>  
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                               <li><a class="waves-effect waves-dark" href="https://2018.igem.org/Team:HUST-China/Improve">Improve</a></li>
 
                               <li><a class="waves-effect waves-dark" href="https://2018.igem.org/Team:HUST-China/Notebook">Notebook</a></li>
 
                               <li><a class="waves-effect waves-dark" href="https://2018.igem.org/Team:HUST-China/Notebook">Notebook</a></li>
 
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                           <ul class="dropdown-menu">
 
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                               <li><a class="waves-effect waves-dark" href="https://2018.igem.org/Team:HUST-China/Human Practices">Human Practices</a></li>
 
                               <li><a class="waves-effect waves-dark" href="https://2018.igem.org/Team:HUST-China/Human Practices">Human Practices</a></li>
                               <li><a class="waves-effect waves-dark" href="https://2018.igem.org/Team:HUST-China/Education Engagement">Education&Engagement</a></li>  
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                               <li><a class="waves-effect waves-dark" href="https://2018.igem.org/Team:HUST-China/Education&Engagement">Education&Engagement</a></li>  
 
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         <h2 class="pageTitle">Sort of three genes</h2>
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         <h2 class="pageTitle">Modeling overview
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                   <h3><strong>1. <span class="red-content">Overview</span></strong></h3>
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                   <h3><strong>1. <span class="red-content">Overview </span></strong></h3>
                   <p>In Rhodopseudomonas, the sequence of genes in plasmid influences them expression ability. (Shou-Chen.2012) We have three genes to transfer. So we should find out which gene is the most important, and we sort three genes by their importance.</p>
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                   <p style="font-size:16px; line-height: 25px;letter-spacing:1px; text-indent:0px;">
<p>But then we meet a problem that there are not enough references about Rhodopseudomonas for us to obtain enough parameters for our simulation, so we run the simulation in a large range of parameters for many times and use the statistical result to decide how to sort the three genes
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This year, our job can mainly divided into three parts: Comparison of Rhodopseudomonas and Cyanobacteria, sort of three genes pathway in Rhodopseudomonas, and intelligent device software.
</p>
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                   <h3><strong>2. <span class="red-content">Function</span></strong></h3>
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                   <h3><strong>2. <span class="red-content">Comparison between PSB</span></strong></h3>
                   <img src="https://static.igem.org/mediawiki/2018/c/cf/T--HUST-China--2018-sort-pic1.png" class="img-responsive" >
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                   <p style="font-size:16px; line-height: 25px;letter-spacing:1px; text-indent:0px;">
                  <p>(We skip some reactions in tricarboxylic acid cycle, and let Isocitrate come to Malate in one reaction.)</p>
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In the past, people use Cyanobacteria to provide energy for electricity producing bacteria. Because it’s efficient and easier to control. But Shewanella species are heterotrophic facultative anaerobes, and produce electricity only in anaerobic environment (Justin et al.2009). So we think Rhodopseudomonas may be better because it’s cycle photophosphorylation doesn’t produce oxygen. But Rhodopseudomonas is not as efficient as Cyanobacteria. So we use computer simulation to find which is better.
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                   <h3><strong>3. <span class="red-content">Parameters</span></strong></h3>
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                   <h3><strong>3. <span class="red-content">Sort of three genes</span></strong></h3>
                   <p>There are not enough references for us to get exact parameters. So we assort parameters into several groups and change one group’s value each time. At the same time, we change the expression abilities of three genes to find which is the most important in this parameter situation.
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                   <p style="font-size:16px; line-height: 25px;letter-spacing:1px; text-indent:0px;">
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In Rhodopseudomonas, the sequence of genes in plasmid influence them expression ability. (Shou-Chen.2012) We have three gene to transfer. So we should find out which gene is most important, and we sort three genes by their importance.
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                            <tr>
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                              <th>Income parameters</th>
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                              <th>Metabolism parameters</th>
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                              <th>Cross membrane parameters </th>
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                              <th>Ks parameters</th>
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                              <th>Gene expression</th>
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                            </tr>
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                            <tr>
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                              <td>g<sub>Pyruvate</sub></td>
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                              <td>k<sub>2LdhA</sub></td>
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                              <td>V<sub>max2</sub></td>
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                              <td>K<sub>s1</sub></td>
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                              <td>K<sub>s2</sub></td>
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                            </tr>
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                              <tr>
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                              <td>g<sub>Acetyl-CoA</sub></td>
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                              <td>k<sub>1LdhA</sub></td>
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                              <td></td>
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                              <td>Ks<sub>3A</sub></td>
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                              <td>[LdhA]</td>
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                            </tr>
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                            <tr>
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                              <td></td>
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                                <td>V<sub>max1</sub></td>
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                              <td></td>
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                              <td>Ks<sub>3M</sub></td>
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                              <td>Ks<sub>5</sub></td>
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                            </tr>
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                            <tr>
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                              <td></td>
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                              <td>V<sub>max3</sub></td>
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                              <td></td>
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                              <td>K<sub>s4</sub></td>
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                              <td></td>
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                            </tr>
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                            <tr>
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                              <td></td>
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                              <td>V<sub>max4</sub></td>
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                              <td></td>
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                              <td></td>
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                              <td></td>
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                            </tr>
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                            <tr>
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                              <td></td>
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                              <td>V<sub>max5</sub></td>
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                              <td></td>
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                              <td></td>
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                              <td></td>
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                            </tr>
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                   <h3><strong>4. <span class="red-content">Result</span></strong></h3>
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                   <h3><strong>3. <span class="red-content">Intelligent device software</span></strong></h3>
                  <p>We generate each group ’s value from 〖10〗^(-5) to 〖10〗^5,and run the simulation. At the beginning, we simply sum the concentration of Lactate outside. But it is not fair for each parameter situation because in some cases the value of final result is much lower than others. So we use the SOFTMAX function to turn the concentration result into scores from 0 to 1. The function is shown below:</p>
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                    <div align="center">
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                      <img src="https://static.igem.org/mediawiki/2018/archive/c/cf/20181014074349%21T--HUST-China--2018-sort-pic1.png" class="img-responsive" ></div>
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                      <p>If the gene expression parameter is lower than 1,we take the negative value of score. Then we sum all scores together, and get the final result.</p>
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                        <img src="https://static.igem.org/mediawiki/2018/archive/c/cf/20181014074548%21T--HUST-China--2018-sort-pic1.png" class="img-responsive" >
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                      <p>(the curve: score(x,y) means the sum of the first x parameter conditions’ scores when the model runs for y units of times)</p>
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                      <p>The result shows that in more than 10,000 parameter conditions, mles is the most important gene. So we sort three genes by their final scores: mles, lldp, ldhA.</p>
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                  <h3><strong>5. <span class="red-content">Reference</span></strong></h3>
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                   <p style="font-size:16px; line-height: 25px;letter-spacing:1px; text-indent:0px;">
 
                   <p style="font-size:16px; line-height: 25px;letter-spacing:1px; text-indent:0px;">
<span>[1] 1.Shou-Chen Lo. 2012. Enhancement of Hydrogen Production and Carbon Fixation in Purple Nonsulfur Bacterium by Synthetic Biology. Ph.D. Dissertation</span></p>
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Using a new multi-culture bacteria system means we should use a new fermentation strategy. So we use algorithm to know the system’s situation and decide how to control the device, letting system working more efficiently and steadily.  
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            <h4><strong>Reference </strong></h4>
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          <p style="font-size:16px; line-height: 25px;letter-spacing:1px; text-indent:0px;">
 +
<span>[1] Justin L. Burns, Thomas J. DiChristina. 2009. Anaerobic Respiration of Elemental Sulfur and Thiosulfate by Shewanella oneidensis MR-1 Requires psrA, a Homolog of the phsA Gene of Salmonella enterica Serovar Typhimurium LT2. American Society for Microbiology Journals</span></p>
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          <p style="font-size:16px; line-height: 25px;letter-spacing:1px; text-indent:0px;">
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<span>[2] 2.Shou-Chen Lo. 2012. Enhancement of Hydrogen Production and Carbon Fixation in Purple Nonsulfur Bacterium by Synthetic Biology. Ph.D. Dissertation</span></p>
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Revision as of 11:49, 17 October 2018

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Modeling overview

Reference

[1] Justin L. Burns, Thomas J. DiChristina. 2009. Anaerobic Respiration of Elemental Sulfur and Thiosulfate by Shewanella oneidensis MR-1 Requires psrA, a Homolog of the phsA Gene of Salmonella enterica Serovar Typhimurium LT2. American Society for Microbiology Journals

[2] 2.Shou-Chen Lo. 2012. Enhancement of Hydrogen Production and Carbon Fixation in Purple Nonsulfur Bacterium by Synthetic Biology. Ph.D. Dissertation