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<h2> <center> 2. How do we generate a colorometric signal upon protein detection </center> </h2>  
 
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<br>To generate the signal upon the human thrombin detection, we used toehold switches and the aptamer trigger that recognizes the human thrombin. </br>
 
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To generate the signal upon the human thrombin detection, we used toehold switches and the aptamer trigger that recognizes the human thrombin.  
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<figcaption><b>Figure 2</b>: Shaded error graph resuming the results</figcaption>               
 
<figcaption><b>Figure 2</b>: Shaded error graph resuming the results</figcaption>               
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Revision as of 23:41, 1 November 2017

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Building a cell-free biosensor for protein detection based on aptamers for target recognition and toeholds for signal generation




How does our biosensor work

Our system relays on three major building blocks:


  • Aptamer pair detects the presence of a protein in a sample


  • Aptamer can trigger the toehold


  • Translation of the downstream reporter for signal generation in our home-made cell-free lysate

  • 1. How do we detect the presence of a target protein


    To demonstrate the ability of our aptamer pair to bind to their target protein Thrombin we used microfluidics, and measured the fluorescence of the Cy3 probe which is attached to the second aptamer. If high levels of fluorescence are measured, this indicates that Thrombin was bound between the two aptamers.

    Our experimental set up was as follows: the biotinylated Thrombin Aptamer 1 was first flown, then human thrombin in the top half of the chip and finally the Cy3-labeled Thrombin Aptamer 2 trigger extension in the whole chip.

    Figure 1: Sandwich immunoassay with Thrombin Aptamers 1 and 2 trigger extension in buffer

    2. How do we generate a colorometric signal upon protein detection


    To generate the signal upon the human thrombin detection, we used toehold switches and the aptamer trigger that recognizes the human thrombin.

    Figure 2: Shaded error graph resuming the results
    Figure 3a: Shaded error graph resuming the results
    Figure 3b: End points measurements were taken after 6 hours of incubation

    3. Streamline toehold design by writing a software

    Generating new toehold sensors requires in-silico processing. It is a quick step (~5 min) if a tool that pipelines the required processes is available. In the scope of our project we generated our own switches targeting Hepatitis C viral RNA and sucessfully proven that the toeholds are functional, i.e they unfolded only in the prescence of a complementary sequence to allow the translation of the downstream reporter lacZ.

    Figure 4: Toehold A in the iGEM backbone psB1C3

    We tested the ToeholdDesigner's output, and chosen the best 4 toeholds for a unique sequence of the Hepatitis C virus we have found using different online resources such as BLAST, in our home-made lysates.


    As shown below, we demonstrate that we can design functional toeholds using ToeholdDesigner
    Figure 5a: Kinetic measurements of the 4 generated toeholds in a usual lysate reaction
    Shaded error graphs
    Figure 5b: End point measurements of the 4 generated toeholds in a usual lysate reaction