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+ | <li>Team: Fudan-TSI</li> | ||
+ | <li><div class="collapsible-header">Project</div> | ||
+ | <div class="collapsible-body"><ul> | ||
+ | <li><a href="/Team:Fudan-TSI/Description">Background</a></li> | ||
+ | <li><a href="/Team:Fudan-TSI/Design">Design</a></li> | ||
+ | <li><a href="/Team:Fudan-TSI/Applied_Design">Applied Design</a></li> | ||
+ | <li><a href="/Team:Fudan-TSI/Experiments">Experiments</a></li> | ||
+ | <li><a href="/Team:Fudan-TSI/Judging">Judging</a></li> | ||
+ | </ul></div> | ||
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+ | <li><div class="collapsible-header">Results</div> | ||
+ | <div class="collapsible-body"><ul> | ||
+ | <li><a href="/Team:Fudan-TSI/Results#ReverseTranscription">Reverse Transcription</a></li> | ||
+ | <li><a href="/Team:Fudan-TSI/Results#Recombination">Recombination</a></li> | ||
+ | <li><a href="/Team:Fudan-TSI/Demonstrate">Demonstration</a></li> | ||
+ | <li><a href="/Team:Fudan-TSI/Measurement">Measurement</a></li> | ||
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+ | <li><a href="/Team:Fudan-TSI/Hardware">Hardware</a></li> | ||
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+ | <li><div class="collapsible-header">Parts</div> | ||
+ | <div class="collapsible-body"><ul> | ||
+ | <li><a href="/Team:Fudan-TSI/Basic_Part">Basic parts</a></li> | ||
+ | <li><a href="/Team:Fudan-TSI/Composite_Part">Composite parts</a></li> | ||
+ | <li><a href="/Team:Fudan-TSI/Improve">Improved parts</a></li> | ||
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+ | <li><a href="/Team:Fudan-TSI/Integrated_Human_Practice">Integrated human practice</a></li> | ||
+ | <li><a href="/Team:Fudan-TSI/Collaborations">Collaborations</a></li> | ||
+ | <li><a href="/Team:Fudan-TSI/Safety">Safety</a></li> | ||
+ | </ul></div> | ||
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+ | <li><div class="collapsible-header">Team</div> | ||
+ | <div class="collapsible-body"><ul> | ||
+ | <li><a href="/Team:Fudan-TSI/Team">Members</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="/Team:Fudan-TSI">© 2019</a></li> | ||
+ | </ul></div> | ||
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+ | </ul><!-- .expandable --> | ||
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+ | <li><a href="/Team:Fudan-TSI/Basic_Part">Basic parts</a></li> | ||
+ | <li><a href="/Team:Fudan-TSI/Composite_Part">Composite parts</a></li> | ||
+ | <li><a href="/Team:Fudan-TSI/Optimization">Optimization</a></li> | ||
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+ | <li>Parts improvement</li> | ||
+ | <li class="onThisPageNav"><a href="#section1">Introduction</a></li> | ||
+ | <li class="onThisPageNav"><a href="#section2">Responsive elements</a></li> | ||
+ | <li class="onThisPageNav"><a href="#section3">pSV40 vs pCMV</a></li> | ||
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− | <p style="margin: 0"> | + | <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. |
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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"> | ||
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− | <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:12px">R-Evolution: an <i>in vivo</i> sequence-specific toolbox for continuous mutagenesis</h3> |
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Revision as of 04:59, 15 September 2019
Improved parts
Introduction
Last year our team has proposed a SynTF-SynPro approach which enables others to construct a customized and orthogonal transcriptional network in mammalian cells. The structures of the corresponding silencing- or activating-form of SynPros were pSV40-N*RE and N*RE-minCMV, in which N*RE is short for responsive elements of N repeats.
This year we took it a step further to create our engineered transmembrane binary logic gates in eukaryotic cells based on the foundational concepts we have constructed upon last year. We made use of the SynTF-SynPro system to function as our Combiner, which executes the final computation of our genetic circuits. To improve the signal-to-noise ratio of our Combiner and to allow others to more easily use our toolbox, we attempted to optimize the structure of the SynPros and constructed N*RE-CMV, which replaces the pSV40-N*RE to respond to transcriptional repressors. Furthermore, we also conducted experiments to characterize our N*RE-CMV, ensuring that it performs exceedingly better than the previous pSV40-N*RE. We have substituted all the pSV40-N*RE with N*RE-CMV when wiring our genetic circuits and picked 8*ZF21.16-CMV for specific demonstration of our parts improvement. For more details, refer to the existing BioBrick page or the improved BioBrick page.
Place of responsive elements
We have experimentally discovered that the place of N*RE can have an impact on basal expression of SynPros. Thus, when designing transcription repressing circuit, we hope that the addition of the N*RE will not bother the original expression of the promotor. Unfortunately, we realized that when the N*RE is placed downstream the promotor, the basal expression of the promotor is effected without the transcriptional repressor. Therefore, we made an attempt to adjust the position of N*RE to upstream of the promotor. Interestingly, the basal expression of the promotor is less affected as compared to the previous design. Actually, similar phenomenon have been reported previously that reporter activity was highly variable among the four different TALE binding sites introduced between the promoter and the reporter coding sequence while the introduction of multiple copies of each of the four different operators upstream from the promoter caused only minimal variability in reporter expression as suggested by Gaber R, et al, 2014 (PMID: 24413461).
pSV40 vs pCMV
To better verify that the transcription repressor can effectively repress the expression of its responsive circuit, we attempted to increase the basal expression for a more precise comparison. As a result, we designed a simple genetic circuit in which a EGFP-P2A was put downstream the promotor to test and compare the basal expression of pSV40 and pCMV. We used fluorescence microscopy to detect the expression of the reporter gene 24 hours after transient transfecting 293T cells with the two mentioned circuits, respectively. We found that pCMV has a significantly higher basal expression than that of pSV40, providing us a more ideal alternation to construct our transcriptional repressor-based Combiner circuit.
Figure 1. Flow cytometry data of previously designed SynPros based on pSV40. It can be clearly identified that the basal expression of pSV40 is easily effected by the adding of responsive elements. (sTF is short for silencing-form transcriptional factors.)
Figure 2. Flow cytometry data of the improved design of SynPros based on pCMV. It is shown that the basal expression of pCMV is barely effected by the adding of responsive elements. (sTF is short for silencing-form transcriptional factors.)
Figure 3. Fluorescence intensity comparison of pCMV-EGFP-P2A and pSV40-EGFP-P2A 24 hours after transfection. The expression level of pCMV is significantly higher than pSV40.
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.