Difference between revisions of "Team:Fudan-TSI/Composite Part"
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| − | <p style="width: 100%;text-align: center | + | <p class="flow-text" style="width:100%;text-align:center"><span class="white-text">Composite parts</span></p> |
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<ul class="collapsible expandable"> | <ul class="collapsible expandable"> | ||
| − | <li>Team: Fudan-TSI</li> | + | <li class="onThisPageNav"><span>Team: Fudan-TSI</span></li> |
| − | <li><div class="collapsible-header">Project</div> | + | <li><div class="collapsible-header"><span>Project</span></div> |
<div class="collapsible-body"><ul> | <div class="collapsible-body"><ul> | ||
<li><a href="/Team:Fudan-TSI/Description">Background</a></li> | <li><a href="/Team:Fudan-TSI/Description">Background</a></li> | ||
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</li> | </li> | ||
| − | <li><div class="collapsible-header">Results</div> | + | <li><div class="collapsible-header"><span>Results</span></div> |
<div class="collapsible-body"><ul> | <div class="collapsible-body"><ul> | ||
<li><a href="/Team:Fudan-TSI/Results#ReverseTranscription">Reverse Transcription</a></li> | <li><a href="/Team:Fudan-TSI/Results#ReverseTranscription">Reverse Transcription</a></li> | ||
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| − | <li><div class="collapsible-header">Model</div> | + | <li><div class="collapsible-header"><span>Model</span></div> |
<div class="collapsible-body"><ul> | <div class="collapsible-body"><ul> | ||
<li><a href="/Team:Fudan-TSI/Model">Modeling</a></li> | <li><a href="/Team:Fudan-TSI/Model">Modeling</a></li> | ||
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| − | <li><div class="collapsible-header">Parts</div> | + | <li><div class="collapsible-header"><span>Parts</span></div> |
<div class="collapsible-body"><ul> | <div class="collapsible-body"><ul> | ||
<li><a href="/Team:Fudan-TSI/Basic_Part">Basic parts</a></li> | <li><a href="/Team:Fudan-TSI/Basic_Part">Basic parts</a></li> | ||
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<div class="collapsible-body"><ul> | <div class="collapsible-body"><ul> | ||
<li><a href="/Team:Fudan-TSI/Public_Engagement">Education & Public engagement</a></li> | <li><a href="/Team:Fudan-TSI/Public_Engagement">Education & Public engagement</a></li> | ||
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| − | <li><div class="collapsible-header">Team</div> | + | <li><div class="collapsible-header"><span>Team</span></div> |
<div class="collapsible-body"><ul> | <div class="collapsible-body"><ul> | ||
<li><a href="/Team:Fudan-TSI/Team">Members</a></li> | <li><a href="/Team:Fudan-TSI/Team">Members</a></li> | ||
<li><a href="/Team:Fudan-TSI/Attributions">Attributions</a></li> | <li><a href="/Team:Fudan-TSI/Attributions">Attributions</a></li> | ||
<li><a href="https://2018.igem.org/Team:Fudan/Heritage" target=_blank>Heritage</a></li> | <li><a href="https://2018.igem.org/Team:Fudan/Heritage" target=_blank>Heritage</a></li> | ||
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<h1>Composite parts</h1> | <h1>Composite parts</h1> | ||
| − | <p><span>This year, our BioBrick submission includes 7 versions of SynNotch receptors, with our favorite being αCD19-mN1c-tTAA.</span></p> | + | <p class="flow-text"><span>This year, our BioBrick submission includes 7 versions of SynNotch receptors, with our favorite being αCD19-mN1c-tTAA.</span></p> |
</div> | </div> | ||
<div class="hide-on-small-only"> | <div class="hide-on-small-only"> | ||
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<h2>Part:BBa_K2549021 <a href="http://parts.igem.org/Part:BBa_K2549021" target=_blank>αCD19-mN1c-tTAA</a></h2> | <h2>Part:BBa_K2549021 <a href="http://parts.igem.org/Part:BBa_K2549021" target=_blank>αCD19-mN1c-tTAA</a></h2> | ||
<h3>Introduction</h3> | <h3>Introduction</h3> | ||
| − | <p>This year we have provided 7 versions of SynNotch receptors in our BioBrick submission, enabling others to wire their contact-dependent signal transduction in mammalian cells. Multiple combinations of extracellular domains, transmembrane core regions and intracellular domains make it even easier for others to readily assemble their own desirable genetic circuits. </p> | + | <p class="flow-text">This year we have provided 7 versions of SynNotch receptors in our BioBrick submission, enabling others to wire their contact-dependent signal transduction in mammalian cells. Multiple combinations of extracellular domains, transmembrane core regions and intracellular domains make it even easier for others to readily assemble their own desirable genetic circuits. </p> |
| − | <p><b>Among the 7 SynNotch receptors, our favorite one is αCD19-mN1c-tTAA <a href="http://parts.igem.org/Part:BBa_K2549021" target="_blank">(BBa_K2549021)</a></b><br/> | + | <p class="flow-text"><b>Among the 7 SynNotch receptors, our favorite one is αCD19-mN1c-tTAA <a href="http://parts.igem.org/Part:BBa_K2549021" target="_blank">(BBa_K2549021)</a></b><br/> |
<img alt="part BBa_K2549021" src="https://static.igem.org/mediawiki/2018/thumb/0/0c/T--Fudan--BBa_K2549021.png/1339px-T--Fudan--BBa_K2549021.png" /> | <img alt="part BBa_K2549021" src="https://static.igem.org/mediawiki/2018/thumb/0/0c/T--Fudan--BBa_K2549021.png/1339px-T--Fudan--BBa_K2549021.png" /> | ||
</p> | </p> | ||
<h3>How αCD19-mN1c-tTAA works | <h3>How αCD19-mN1c-tTAA works | ||
</h3> | </h3> | ||
| − | <p>It receives ligand-dependent signal via the CD19 scFv and undergoes a cleavage process in which the tTA advance is released, then entering into the nucleus to activate the expression of TRE3GV promotor. Thus it can be served as a signal input module. | + | <p class="flow-text">It receives ligand-dependent signal via the CD19 scFv and undergoes a cleavage process in which the tTA advance is released, then entering into the nucleus to activate the expression of TRE3GV promotor. Thus it can be served as a signal input module. |
</p> | </p> | ||
<h3>Advantages of αCD19-mN1c-tTAA | <h3>Advantages of αCD19-mN1c-tTAA | ||
</h3> | </h3> | ||
| − | <p>We have conducted flow cytometry experiments to test our SynNotch receptors and after testing, αCD19-mN1c-tTAA have stood out for showing the highest signal-to-noise ratio. We have also discovered that it has the highest activation ratio when activated by surface-expressed CD19 antigen. Moreover, it also shows only a few amount of false activation which can be tolerated. As it performs great modularity and has a great potential to be utilized by others to assemble their own CD19-dependent signal transduction module, this especially enables the possibility of the clinical application of SynNotch receptors. | + | <p class="flow-text">We have conducted flow cytometry experiments to test our SynNotch receptors and after testing, αCD19-mN1c-tTAA have stood out for showing the highest signal-to-noise ratio. We have also discovered that it has the highest activation ratio when activated by surface-expressed CD19 antigen. Moreover, it also shows only a few amount of false activation which can be tolerated. As it performs great modularity and has a great potential to be utilized by others to assemble their own CD19-dependent signal transduction module, this especially enables the possibility of the clinical application of SynNotch receptors. |
</p> | </p> | ||
<div class="figureHolder width40" style="margin: 23px auto 0 auto;"> | <div class="figureHolder width40" style="margin: 23px auto 0 auto;"> | ||
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<p style="margin-top:0;text-indent: 0;"><b>Figure 1. Flow cytometry characterization of SynNotch receptors.</b> TRE3GV-EGFP circuit was set to indicate the activation level of SynNotch receptors. It is shown that αCD19-mN1c-tTAA has the highest signal-to-noise ratio.</p> | <p style="margin-top:0;text-indent: 0;"><b>Figure 1. Flow cytometry characterization of SynNotch receptors.</b> TRE3GV-EGFP circuit was set to indicate the activation level of SynNotch receptors. It is shown that αCD19-mN1c-tTAA has the highest signal-to-noise ratio.</p> | ||
| − | <p>For more details, please check <a href="/Team:Fudan-TSI/Part_Collection">our parts collection page</a>. | + | <p class="flow-text">For more details, please check <a href="/Team:Fudan-TSI/Part_Collection">our parts collection page</a>. |
</p> | </p> | ||
</div> | </div> | ||
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<a href="#!"><img alt="project summary" src="https://static.igem.org/mediawiki/2018/9/96/T--Fudan--X.svg"></a> | <a href="#!"><img alt="project summary" src="https://static.igem.org/mediawiki/2018/9/96/T--Fudan--X.svg"></a> | ||
<div class="container"> | <div class="container"> | ||
| − | < | + | <h4 style="margin:0;padding:10px 0;">Project Summary</h4> |
| − | <p style="margin: 0">Mutation library generation is critical for biological and medical research, but current methods cannot mutate a specific sequence continuously without manual intervention. Here we present a toolbox for <i>in vivo</i> continuous mutation library construction. First, the target DNA is transcribed into RNA. Next, our reverse transcriptase reverts RNA into cDNA, during which the target is randomly mutated by enhanced error-prone reverse transcription. Finally, the mutated version replaces the original sequence through recombination. These steps will be carried out iteratively, generating a random mutation library of the target with high efficiency as mutations accumulate along with bacterial growth. Our toolbox is orthogonal and provides a wide range of applications among various species. R-Evolution could mutate coding sequences and regulatory sequences, which enables the <i>in vivo</i> evolution of individual proteins or multiple targets at a time, promotes high-throughput research, and serves as a foundational advance to synthetic biology. | + | <p class="flow-text" style="margin:0">Mutation library generation is critical for biological and medical research, but current methods cannot mutate a specific sequence continuously without manual intervention. Here we present a toolbox for <i>in vivo</i> continuous mutation library construction. First, the target DNA is transcribed into RNA. Next, our reverse transcriptase reverts RNA into cDNA, during which the target is randomly mutated by enhanced error-prone reverse transcription. Finally, the mutated version replaces the original sequence through recombination. These steps will be carried out iteratively, generating a random mutation library of the target with high efficiency as mutations accumulate along with bacterial growth. Our toolbox is orthogonal and provides a wide range of applications among various species. R-Evolution could mutate coding sequences and regulatory sequences, which enables the <i>in vivo</i> evolution of individual proteins or multiple targets at a time, promotes high-throughput research, and serves as a foundational advance to synthetic biology. |
</p> | </p> | ||
</div> | </div> | ||
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</a><a href="http://www.yfc.cn/en/" target="_blank"><img class="col s3 m6 l3" style="padding: 0.15rem 0.9rem;" alt="Yunfeng Capital" src="https://static.igem.org/mediawiki/2018/e/e2/T--Fudan--yunfengLogo.png"> | </a><a href="http://www.yfc.cn/en/" target="_blank"><img class="col s3 m6 l3" style="padding: 0.15rem 0.9rem;" alt="Yunfeng Capital" src="https://static.igem.org/mediawiki/2018/e/e2/T--Fudan--yunfengLogo.png"> | ||
</a> | </a> | ||
| − | <h3 class="col s12" style="text-align: left; color: rgba(255, 255, 255, 0.8); font-size: | + | <h3 class="col s12" style="text-align: left; color: rgba(255, 255, 255, 0.8); font-size:12.5px">R-Evolution: an <i>in vivo</i> sequence-specific toolbox for continuous mutagenesis</h3> |
</div> | </div> | ||
<div id="usefulLinks" class="col m9 s12 row"> | <div id="usefulLinks" class="col m9 s12 row"> | ||
Revision as of 07:05, 17 September 2019
<script src="https://code.jquery.com/jquery-1.11.3.min.js"></script>
Composite parts
Part:BBa_K2549021 αCD19-mN1c-tTAA
Introduction
This year we have provided 7 versions of SynNotch receptors in our BioBrick submission, enabling others to wire their contact-dependent signal transduction in mammalian cells. Multiple combinations of extracellular domains, transmembrane core regions and intracellular domains make it even easier for others to readily assemble their own desirable genetic circuits.
Among the 7 SynNotch receptors, our favorite one is αCD19-mN1c-tTAA (BBa_K2549021)
How αCD19-mN1c-tTAA works
It receives ligand-dependent signal via the CD19 scFv and undergoes a cleavage process in which the tTA advance is released, then entering into the nucleus to activate the expression of TRE3GV promotor. Thus it can be served as a signal input module.
Advantages of αCD19-mN1c-tTAA
We have conducted flow cytometry experiments to test our SynNotch receptors and after testing, αCD19-mN1c-tTAA have stood out for showing the highest signal-to-noise ratio. We have also discovered that it has the highest activation ratio when activated by surface-expressed CD19 antigen. Moreover, it also shows only a few amount of false activation which can be tolerated. As it performs great modularity and has a great potential to be utilized by others to assemble their own CD19-dependent signal transduction module, this especially enables the possibility of the clinical application of SynNotch receptors.
Figure 1. Flow cytometry characterization of SynNotch receptors. TRE3GV-EGFP circuit was set to indicate the activation level of SynNotch receptors. It is shown that αCD19-mN1c-tTAA has the highest signal-to-noise ratio.
For more details, please check our parts collection page.
Project Summary
Mutation library generation is critical for biological and medical research, but current methods cannot mutate a specific sequence continuously without manual intervention. Here we present a toolbox for in vivo continuous mutation library construction. First, the target DNA is transcribed into RNA. Next, our reverse transcriptase reverts RNA into cDNA, during which the target is randomly mutated by enhanced error-prone reverse transcription. Finally, the mutated version replaces the original sequence through recombination. These steps will be carried out iteratively, generating a random mutation library of the target with high efficiency as mutations accumulate along with bacterial growth. Our toolbox is orthogonal and provides a wide range of applications among various species. R-Evolution could mutate coding sequences and regulatory sequences, which enables the in vivo evolution of individual proteins or multiple targets at a time, promotes high-throughput research, and serves as a foundational advance to synthetic biology.