Difference between revisions of "Team:Manchester/PromoterModel"

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  <p><b>1.</b> Each sequence was hand-typed into an Excel file and, for ease of comparison, the sequences were aligned and if there was a deletion, it was indicated with “-“. <br> <center><img src="https://static.igem.org/mediawiki/2018/4/4b/T--Manchester--model1.png" width="700px" height="auto"/></p>
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<br><p><b>1.</b> Each sequence was hand-typed into an Excel file and, for ease of comparison, the sequences were aligned and if there was a deletion, it was indicated with “-“. <br> <center><img src="https://static.igem.org/mediawiki/2018/4/4b/T--Manchester--model1.png" width="700px" height="auto"/></p>
 
   <li>Tea</li>
 
   <li>Tea</li>
 
   <li>Milk</li>
 
   <li>Milk</li>
 
</ol>  
 
</ol>  
 
***images***
 
***images***
<center><img src="https://static.igem.org/mediawiki/2018/4/4b/T--Manchester--model1.png" width="700px" height="auto"/>
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<center><img src="https://static.igem.org/mediawiki/2018/7/77/T--Manchester--model2.png" width="700px" height="auto"/>
 
<center><img src="https://static.igem.org/mediawiki/2018/7/77/T--Manchester--model2.png" width="700px" height="auto"/>
 
<center><img src="https://static.igem.org/mediawiki/2018/8/8c/T--Manchester--model3.png" width="700px" height="auto"/>
 
<center><img src="https://static.igem.org/mediawiki/2018/8/8c/T--Manchester--model3.png" width="700px" height="auto"/>

Revision as of 19:52, 17 October 2018




PROMOTER TOOL

Since we wanted to design our Listeria detection system to work both E. coli (for testing) and in Lactococcus lactis (for the industrial application), we wanted to select a promoter that would work well in both species. We came across a paper by Jensen and Hammer, who designed a series of 37 constitutive promoters and characterised their activity in both E. coli and L. lactis using a beta galactosidase assay. They provided an image of aligned sequences juxtaposed with their activity in both species, and this made us wonder whether we could selectively alter certain parts of these sequences to optimise their activity for our purposes. We realised this would mean designing a more active constitutive promoter for our agrC and agrA sensing components, as we want these to be expressed all the time and in large amounts. However, this tool could be used by other iGEM teams who may want a promoter associated with a lower constitutive expression to keep readthrough expression levels at a low level (for more information, see our Collaborations Page)

How does our model work?


1. Each sequence was hand-typed into an Excel file and, for ease of comparison, the sequences were aligned and if there was a deletion, it was indicated with “-“.

  • Tea
  • Milk
  • ***images***