Difference between revisions of "Team:Munich"

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{{Munich}}
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<html>
 
<html>
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<head>
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<link rel="stylesheet" type="text/css"
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href="https://2017.igem.org/Template:Munich/CSS?action=raw&ctype=text/css" />
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<link rel="stylesheet" type="text/css"
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href="https://2017.igem.org/Template:Munich/Header?action=raw&ctype=text/css" />
 
<style>
 
<style>
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body {line-height: initial;}
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h1, h2,h3 {
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body{
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* {margin: 0; padding: 0;}
  
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width: 900px; /*Same as width of the large image*/
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overflow: hidden;
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position: relative;
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margin: 50px auto;
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/*Instead of height we will use padding*/
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padding-top: 600px; /*That helps bring the labels down*/
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/*Lets add a shadow*/
 
}
 
}
  
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h2{
 
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  text-align: center;
 
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}
 
  
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.banner > img{
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/*Last thing remaining is to add transitions*/
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.slider>img{
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position: absolute;
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left: 0; top: 0;
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transition: all 0.5s;
 
}
 
}
  
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.banner {
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.slider input[name='slide_switch'] {
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  width:5000px;
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display: none;
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  overflow: hidden;
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}
 
}
  
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/*keyframe animations*/
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.slider label {
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.first {
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/*Lets add some spacing for the thumbnails*/
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-webkit-animation: bannermove 20s linear infinite;
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margin: 30px 0 0 18px;
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  -moz-animation: bannermove 20s linear infinite;
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    -ms-animation: bannermove 20s linear infinite;
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float: left;
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    -o-animation: bannermove 20s linear infinite;
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cursor: pointer;
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        animation: bannermove 20s linear infinite;
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transition: all 0.5s;
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/*Default style = low opacity*/
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opacity: 0.6;
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        z-index: 99;
 
}
 
}
  
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@keyframes "bannermove" {
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.slider label img{
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0% {
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display: block;
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100% {
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    margin-left: -2000px;
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@-moz-keyframes bannermove {
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/*Time to add the click effects*/
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0% {
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On click the images will be displayed at normal size to complete the effect
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100% {
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/*Clicking on any thumbnail now should activate the image related to it*/
  
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@-o-keyframes "bannermove" {
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/*We are done :)*/
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0% {
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{{Munich/Menu}}
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<table width=100% height=100% cellpadding=0 cellspacing=0 border=0>
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<tr><td width="100%" colspan=3>
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<td id="myContent" width="20%" valign=top align=center>
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<br>
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<!-- Head End -->
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<!-- Content Begin -->
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<video width="980" autoplay="autoplay" controls>
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<source src="https://static.igem.org/mediawiki/2017/4/44/T--Munich--FrontPageVideo.mp4" type="video/mp4">
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<table width="900" border=0 cellspacing=0 cellpadding=10>
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<tr>
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<td width=160></td>
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<td width=160></td>
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<td width=160></td>
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<td width=160></td>
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<td width=160></td>
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<td width=160></td>
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</tr>
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<tr><td colspan=6 align=left valign=center>
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<font size=7 ><b style="color: #51a7f9">Abstract</b></font>
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</td></tr>
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<tr><td align=center valign=center colspan=6>
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<p style="text-align:justify">
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<font size=3 color=#444444>
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The ongoing crisis of increasing antibiotic resistance demands innovative preventive strategies. Recently, the RNA-targeting protein CRISPR-Cas13a has been used for highly sensitive DNA and RNA detection, promising diverse applications in point-of-care diagnostics. We integrated Cas13a in the detection unit of CascAID, our GMO-free diagnostic platform. CascAID combines an automated microfluidic device for rapid lysis and extraction of nucleic acids with a paper-based readout system. We demonstrated the performance of our device by targeting the 16S rRNA from <i>E. coli</i>. We improved the detection limit of our platform, using simulations to optimize our amplification scheme and the final readout.
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</font>
 +
</p>
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<p style="text-align:justify; margin-bottom: 50px">
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<font size=3 color=#444444>
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Conceived as a distributable platform for rapid point-of-care diagnostics, CascAID can be used to distinguish between bacterial and viral infections, thus minimizing the widespread use of antibiotics.
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Furthermore, Cas13a allows the fast design of target sequences, making our system adaptive to the emergence of new viral outbreaks or fast mutating pathogens.
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</font>
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</p>
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</td></tr>
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<tr><td colspan=6 align=middle valign=center>
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<font size=10 ><b style="color: #51a7f9; font-size: 60px; margin-top: 20px">Awards & Achievements</b></font>
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</td></tr>
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<tr>
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<td colspan=6>
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<img src="https://static.igem.org/mediawiki/2017/e/e5/T--Munich--Banner_Awards.jpg" width=900>
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</td>
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</tr>
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<tr>
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<td align=center valign=center colspan=3>
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<div class="captionPicture">
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<h1>First Runner-up</h1>
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</div>
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</td>
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<td align=center valign=center colspan=3>
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<div class="captionPicture">
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<h1>Best Diagnostics Project</h1>
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</div>
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</td>
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</tr>
  
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<tr>
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<td align=center valign=center colspan=3>
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<div class="captionPicture">
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<h2>Best Model</h2>
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</div>
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</td>
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<td align=center valign=center colspan=3>
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<div class="captionPicture">
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<h2>Best Applied Design</h2>
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</div>
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</td>
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</tr>
  
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<tr>
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<td align=center valign=center colspan=3>
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<div class="captionPicture">
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<h2>Best Hardware</h2>
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</div>
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</td>
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<td align=center valign=center colspan=3>
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<div class="captionPicture">
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<h2>Best Software</h2>
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</div>
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</td>
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</tr>
  
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h1{
 
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  margin: 20px;
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<tr>
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}
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<td align=center valign=center colspan=2>
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<h3>Nominated for Best Wiki</h3>
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</td>
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<td align=center valign=center colspan=2>
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<h3>Nominated for Best Presentation</h3>
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</td>
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<td align=center valign=center colspan=2>
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<h3>Nominated for Best Poster</h3>
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</td>
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</tr>
  
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h2{
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<td align=center valign=center colspan=2>
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<h3>Nominated for Best Integrated Human Practices</h3>
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}
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</td>
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<td align=center valign=center colspan=2>
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<h3>Nominated for Best Education & Public Engagement</h3>
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</td>
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<td align=center valign=center colspan=2>
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<h3>Nominated for Best Measurement</h3>
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<h3 style="margin-bottom: 50px">Nominated for Best Composite Part</h3>
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</td>
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<td align=center valign=center colspan=2>
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<h3 style="margin-bottom: 50px">Nominated for Best Part Collection</h3>
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</td>
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<td align=center valign=center colspan=1></td>
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h3{
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<font size=10 ><b style="color: #51a7f9; font-size: 60px; margin-top: 20px">Gallery</b></font>
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The markup is very simple:
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Radio Inputs
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Labels with thumbnails to detect click event
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Main Image
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<div class="slider">
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<input type="radio" name="slide_switch" id="id3" checked="checked"/>
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<label for="id3">
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<img src="https://static.igem.org/mediawiki/2017/9/99/T--Munich--Review2017_77.jpeg" width="100"/>
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<img src="https://static.igem.org/mediawiki/2017/9/99/T--Munich--Review2017_77.jpeg" width=900/>
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<input type="radio" name="slide_switch" id="id2" />
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<label for="id2">
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<img src="https://static.igem.org/mediawiki/2017/d/dd/T--Munich--Review2017_14.jpeg" width="100"/>
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<img src="https://static.igem.org/mediawiki/2017/d/dd/T--Munich--Review2017_14.jpeg" width=900/>
  
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<input type="radio" name="slide_switch" id="id1"/>
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<label for="id1">
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<img src="https://static.igem.org/mediawiki/2017/b/b8/T--Munich--Review2017_5.jpeg" width="100"/>
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<img src="https://static.igem.org/mediawiki/2017/b/b8/T--Munich--Review2017_5.jpeg" width= 900/>
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<img src="https://static.igem.org/mediawiki/2017/f/f0/T--Munich--Review2017_21.jpeg" width="100"/>
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<img src="https://static.igem.org/mediawiki/2017/f/f0/T--Munich--Review2017_21.jpeg" width=900/>
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table{
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  <div class="banner first"><img id="picture" src="https://static.igem.org/mediawiki/2017/9/92/T--Munich--logo.png" alt="" style="width:350px;height:233px;"/><img src="https://static.igem.org/mediawiki/2017/3/36/T--Munich--scientist.jpg" alt="" style="width:350px;height:233px" /><img src="https://static.igem.org/mediawiki/2017/f/fa/T--Munich--Explaning_MakeMunich.jpg" alt="" style="width:350px;height:233px;"/><img src="https://static.igem.org/mediawiki/2017/4/40/T--Munich--Wetlab_work.jpg" alt="" style="width:350px;height:233px;"/><img src="https://static.igem.org/mediawiki/2017/c/cd/Groupphoto_170504.jpeg" alt="" style="width:350px;height:233px;"/><img class="hola" src="https://static.igem.org/mediawiki/2017/9/92/T--Munich--logo.png" alt="" style="width:350px;height:233px;"/><img class ="hola" src="https://static.igem.org/mediawiki/2017/3/36/T--Munich--scientist.jpg" alt="" style="width:350px;height:233px" /><img src="https://static.igem.org/mediawiki/2017/f/fa/T--Munich--Explaning_MakeMunich.jpg" alt="" style="width:350px;height:233px;"/><img src="https://static.igem.org/mediawiki/2017/4/40/T--Munich--Wetlab_work.jpg" alt="" style="width:350px;height:233px;"/><img src="https://static.igem.org/mediawiki/2017/c/cd/Groupphoto_170504.jpeg" alt="" style="width:350px;height:233px;"/>
 
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  <h1> CascAID </h1>
 
 
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<h3> <a style="color: #51a7f9 !important" href="/Team:Munich/Gallery">See the rest of our gallery...</a></h3>
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</td>
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</tr>
  
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<div class="part2">
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<tr><td class="no-padding" colspan=6 align=right valign=center height=10>
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  <table style="width:100%; text-align:justify" >
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    <td bgcolor="white" class = "problem"> <h3 id="hola">Problem</h3>
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      <p> Although there are many diagnose tests available that can detect even the smallest traces of a pathogen, they usually require expensive lab-equipment or skilled labor. Usually, places most prone to diseases are also the ones most lacking such equipment or personal, and thus, where tests are least asequible.
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Many different diseases can present similar symptoms. But because the treatment for each of them can vary greatly (e.g. bacterial vs viral infetion), a quick and reliable diagnose is important to start as soon as possible with the right treatment. On the other hand, wrongly recognizing the cause of a disease not only leads to prescription of the wrong medicine, but also can contribute to the spread of resistances. <br><br>
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New diagnose tool must take these points into consideration and be designed with affordability, availability, simplicity and reliability in mind, and, where possible, be flexible enough to cover a wide array of diseases in order to present the user with a single, powerful product.
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      </p> </td>
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    <td bgcolor="white" class ="solution"><h3>Solution</h3>
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    <p> We are working at a diagnose tool that combines the power of high sensible methods with the affordability needed for a wide application field. Our project, named CascAID, utilizes the CRISPR/Cas effector Cas13a to quickly and reliably test for different pathogens based on their RNA. By cleaverly designing a short RNA sequence, it is possible to guide Cas13a to only cleave RNA molecules belonging to a pathogen. Once the target has been digested, Cas13a becomes active and cleaves indiscriminately other RNA molecules. If the sample contained pathogen, then digested RNA will be found, where as a negative sample won't produce digestion fragments. <br><br>
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To provide an affordable product, CascAID will be implemented on paper-strips, using deep-freeze technologie that allows proteins and other organic molecules to remain active over long periods of time, even at room temperature. Thanks to the cheapness of paper as a material, CascAID-strips can be single use, thus reducing the risk of cross-contamination without increasing the costs of manufacture.
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      </p>
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    </td>
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  </tr>
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</table>
 
</table>
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<!-- Content End -->
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</div>
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  <br>
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<div class="footer">
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    <h5>Follow our progress or contact us on:</h5>
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<div class="logos"> <a href="https://www.facebook.com/Munich.iGEM/">
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<img border="0" src="https://image.flaticon.com/icons/svg/33/33702.svg" width="30px" height="30px" align="center"> </a>
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  <a  href="https://www.instagram.com/igem.munich.2017/">
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<img border="0" src="https://image.flaticon.com/icons/svg/87/87390.svg" width="30px" height="30px" align="center"> </a>
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<a  href="mailto:igem.munich@gmail.com"> <img  src= "https://static.igem.org/mediawiki/2017/9/97/T--Munich--mail_symbol.svg" width="30px" height="30px" align="center"> </a> </div>
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{{Munich/Footer}}

Latest revision as of 20:49, 15 December 2017

Description

Design

Demonstrate

Measurement

Applied Design

Final Results

Achievements

Protocols

Notebook

Safety

Parts

Improved Part

Part Collection

InterLab

Model

Software

Collaboration

Detector

Quake Valve

Paperstrips

Sample Processing

Silver

Gold

Engagement

Collaborations

Team members

Sponsors

Attributions

Gallery

Abstract

The ongoing crisis of increasing antibiotic resistance demands innovative preventive strategies. Recently, the RNA-targeting protein CRISPR-Cas13a has been used for highly sensitive DNA and RNA detection, promising diverse applications in point-of-care diagnostics. We integrated Cas13a in the detection unit of CascAID, our GMO-free diagnostic platform. CascAID combines an automated microfluidic device for rapid lysis and extraction of nucleic acids with a paper-based readout system. We demonstrated the performance of our device by targeting the 16S rRNA from E. coli. We improved the detection limit of our platform, using simulations to optimize our amplification scheme and the final readout.

Conceived as a distributable platform for rapid point-of-care diagnostics, CascAID can be used to distinguish between bacterial and viral infections, thus minimizing the widespread use of antibiotics. Furthermore, Cas13a allows the fast design of target sequences, making our system adaptive to the emergence of new viral outbreaks or fast mutating pathogens.

Awards & Achievements

First Runner-up

Best Diagnostics Project

Best Model

Best Applied Design

Best Hardware

Best Software

Nominated for Best Wiki

Nominated for Best Presentation

Nominated for Best Poster

Nominated for Best Integrated Human Practices

Nominated for Best Education & Public Engagement

Nominated for Best Measurement

Nominated for Best Composite Part

Nominated for Best Part Collection
Gallery

See the rest of our gallery...