Difference between revisions of "Team:Jiangnan"
| Line 172: | Line 172: | ||
<div style="width: 33.3%;float: left;"> | <div style="width: 33.3%;float: left;"> | ||
<a href="#broad"><img class="animated infinite pulse" src="https://static.igem.org/mediawiki/2018/0/06/T--JiangNan--broad.png" width="50%"></a> | <a href="#broad"><img class="animated infinite pulse" src="https://static.igem.org/mediawiki/2018/0/06/T--JiangNan--broad.png" width="50%"></a> | ||
| − | <div><h4 style="color: white">Broad | + | <div><h4 style="color: white">Broad Spectrum</h4></div> |
</div> | </div> | ||
<div style="width: 33.3%;float: left;"> | <div style="width: 33.3%;float: left;"> | ||
<a href="#sus"><img class="animated infinite swing" src="https://static.igem.org/mediawiki/2018/c/cf/T--Jiangnan--main--sus.png" width="50%"></a> | <a href="#sus"><img class="animated infinite swing" src="https://static.igem.org/mediawiki/2018/c/cf/T--Jiangnan--main--sus.png" width="50%"></a> | ||
| − | <div><h4 style="color: white">Suspension</h4></div> | + | <div><h4 style="color: white">Suspension Culture</h4></div> |
</div> | </div> | ||
<div style="width: 33.3%;float: left;"> | <div style="width: 33.3%;float: left;"> | ||
<a href="#high"><img class="animated infinite rubberBand" src="https://static.igem.org/mediawiki/2018/9/96/T--Jiangnan--main--high.png" width="50%"></a> | <a href="#high"><img class="animated infinite rubberBand" src="https://static.igem.org/mediawiki/2018/9/96/T--Jiangnan--main--high.png" width="50%"></a> | ||
| − | <div><h4 style="color: white">High | + | <div><h4 style="color: white">High Titer</h4></div> |
</div> | </div> | ||
</div> | </div> | ||
| Line 187: | Line 187: | ||
<div id="broad" class="row"> | <div id="broad" class="row"> | ||
<div class="col s7 offset-s1"> | <div class="col s7 offset-s1"> | ||
| − | <h5 style="color: #2e7d32">Broad | + | <h5 style="color: #2e7d32">Broad Spectrum</h5> |
<p>Through text mining, we classified cell receptors according to the Baltimore subtyping of viruses and summarized the primary receptors mediating the entry of different types of viruses. After systematic analysis, we aim to express Nectin 4 and Tfr on our chassis cells to make them possible to a broad spectrum of viruses.</p> | <p>Through text mining, we classified cell receptors according to the Baltimore subtyping of viruses and summarized the primary receptors mediating the entry of different types of viruses. After systematic analysis, we aim to express Nectin 4 and Tfr on our chassis cells to make them possible to a broad spectrum of viruses.</p> | ||
</div> | </div> | ||
| Line 205: | Line 205: | ||
<div id="high" class="row"> | <div id="high" class="row"> | ||
<div class="col s7 offset-s1"> | <div class="col s7 offset-s1"> | ||
| − | <h5 style="color: #03a9f4">High | + | <h5 style="color: #03a9f4">High Titer</h5> |
<p>Through bioinformatics analysis and mathematical modeling, we constructed the network regulating virus titration of cells. The top gene was selected, functionally validated in vitro and used for genomic modulation in the chassis cells to enable them the feature of increased titration. On the other hand, we manufactured a device to generate cold atmospheric plasma, using which cell titration was further increased in response to plasma irradiation.</p> | <p>Through bioinformatics analysis and mathematical modeling, we constructed the network regulating virus titration of cells. The top gene was selected, functionally validated in vitro and used for genomic modulation in the chassis cells to enable them the feature of increased titration. On the other hand, we manufactured a device to generate cold atmospheric plasma, using which cell titration was further increased in response to plasma irradiation.</p> | ||
</div> | </div> | ||
Revision as of 16:20, 17 October 2018
Project Description
The limitingg factors of most vaccine companies, according to our previous invetigation and survey, are
mulitifaceted costs in actual production process and long product lift cycle and other issues due to
to complex application process of new vaccines(call line).
The goal of our project is to enable three features of our chassis cell, i.e.,high titration, suspension cultivation, and
broad spectrum to reduce the production cost increase the yield of viruses for vaccine production. The chassis cell we used here is
MDBK cell.
Broad Spectrum
Suspension Culture
High Titer
Broad Spectrum
Through text mining, we classified cell receptors according to the Baltimore subtyping of viruses and summarized the primary receptors mediating the entry of different types of viruses. After systematic analysis, we aim to express Nectin 4 and Tfr on our chassis cells to make them possible to a broad spectrum of viruses.
Suspension Culture
Through high throughput sequencing of two pairs of cells with and without the suspension feature, we found a panel of genes responsible for the suspension feature of cells following network construction using computational approach. The top gene was functionally validated before applied to the chassis cell for genomic modulation.
High Titer
Through bioinformatics analysis and mathematical modeling, we constructed the network regulating virus titration of cells. The top gene was selected, functionally validated in vitro and used for genomic modulation in the chassis cells to enable them the feature of increased titration. On the other hand, we manufactured a device to generate cold atmospheric plasma, using which cell titration was further increased in response to plasma irradiation.
