Team:Aachen

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<div style="font-size:300%;color:#0069b8;margin-left:40px;">Cellock Holmes - A Case of Identity</div ><br/>
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<div style="font-size:175%;margin-top:12px;">Welcome to the iGEM Aachen 2014 Wiki!</div >
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<p style="margin-left:0px;margin-right:0px;">Until now, an ideal method to detect pathogenic bacteria is still elusive. The existing techniques require expensive equipment, trained personnel or labourious routines. </p>
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<p style="margin-left:0px;margin-right:0px;">We, the iGEM team Aachen, have developed a '''novel biosensor system''' called ''Cellock Holmes'' that '''detects bacteria on solid surfaces''' using a low-cost, rapid and portable technique.</p>
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<p style="margin-left:0px;margin-right:0px;">In this project, we demonstrate a unique way of combining '''Open Source biology, software and hardware'''.</p>
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Welcome to the Teamwiki of the iGEM Aachen in 2014!
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<h2>Cellock Holmes - a case of identity </h2>
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Pathogens on solid surfaces in places where good hygiene is crucial pose a serious threat, since – even after cleaning – these can still be present in dangerous amounts. This is demonstrated by the high number of 3.2 million patients each year that have to be treated due to in the health sector acquired infections. And 37000 of those infections end deadly. The EU estimates that at least 20-30% of those cases would be preventable with an intensive hygiene program. However, for a more effective control these respective pathogens have to be identified.
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We are developing a system that makes this possible. We are constructing a device with which pathogens can be detected easily, efficiently, effectively and less expensively by utilising genetically modified cells. We focus on a fast response time coupled with an automated analysis.
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Our project is not only applicable to the detection of pathogens but we are looking to develop it further into a platform for a general 2D detection of nearly any cell or substance.    
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Current techniques vs. Cellock Holmes
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<td><p style="margin-left:0px;margin-right:20px;overflow:auto;"> To watch our <b>final presentation</b> just click <a href="https://www.youtube.com/watch?v=-pKLyq3BD0k" target="_blank"> here </a>.</p></td>
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<td><p style="margin-left:0px;margin-right:20px;overflow:auto;">The whole project was awarded <b>Best Measurement Project</b> and won the track.</p></td>
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Our biological approach
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In order to detect the pathogens fast, specifically and inexpensively we are building sensor cells to detect these pathogens. These sensor cells can identify pathogens in very low concentration by responsing to specific extracellular molecules either secreted by or displayed on the pathogens. These molecules trigger a fast fluorescence response by our immobilized sensor cells  which will be measured by our device.
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You can follow our molecular approach in more detail by checking out our
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<td><p style="margin-left:0px;margin-right:20px;overflow:auto;">Our image analysis software <i>Measurarty</i> was awarded <b>Best Supporting Software</b> in the overgrad section.</p></td>
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<td><p style="margin-left:0px;margin-right:20px;overflow:auto;">Our work on biosafety was rewarded with the <b>Safety Commendation</b> special award.</p></td>
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<td><p style="margin-left:0px;margin-right:20px;overflow:auto;">We fulfilled all Bronze and Silver criteria and won a <b>Gold Medal</b>.</p></td>
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The device
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Our device Cellock Holmes is designed to be an automated 2D fluorescence analyser. We aim to be able to quickly measure the fluorescence emitted by our sensor cells and automatically analyze the emitted images with our software Measurarty. This will enabel us to reliably detect the amount of CFU (colony forming units) of the pathogens present on the sample. The device will have different Filters for different wavelenghts included to be able to analyze different fluorescent proteins at the same time.
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To learn more about our device check out
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The software Measurarty
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The third part of our project is our software Measurarty. The software will allow us to analyze the fluorescence emitted by our sensor cells in a more advanced and better way than just using a simple Treshold. We will utilize a modern segmentation algorithm in combination with further, detailed image processing algorythms.
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For more information check out our
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Latest revision as of 14:01, 5 May 2015


Cellock Holmes - A Case of Identity

Welcome to the iGEM Aachen 2014 Wiki!

Until now, an ideal method to detect pathogenic bacteria is still elusive. The existing techniques require expensive equipment, trained personnel or labourious routines.

We, the iGEM team Aachen, have developed a '''novel biosensor system''' called ''Cellock Holmes'' that '''detects bacteria on solid surfaces''' using a low-cost, rapid and portable technique.

In this project, we demonstrate a unique way of combining '''Open Source biology, software and hardware'''.

Achievements

To watch our final presentation just click here .

The whole project was awarded Best Measurement Project and won the track.

Our image analysis software Measurarty was awarded Best Supporting Software in the overgrad section.

Our work on biosafety was rewarded with the Safety Commendation special award.

We fulfilled all Bronze and Silver criteria and won a Gold Medal.




Bürgerstiftung Aachen
Niersverband Genscript Eurofins Genomics Labomedic
BMBF IDT m2p labs Carl Roth pro RWTH
Institute of Applied Microbiology - iAMB Institute for Molecular Biotechnology Helmholtz Association - Initiative on Synthetic Biology Aachen Biology and Biotechnology - ABBt Forschungszentrum Jülich Fab Lab Aachen Schwaneberg Group