Team:Aachen

From 2014.igem.org

(Difference between revisions)
Line 16: Line 16:
<tr>
<tr>
<td></td>
<td></td>
-
<td width="975px" align="center">
+
<td class="contentWidth" align="center">
-
<table class="transbg" width="1100px"  cellspacing="0">
+
<table class="transbg" width="100%"  cellspacing="0">
<tr>
<tr>
-
<td class="contentcell" width="95%" height="400px" align="center">  
+
<td class="contentcell" width="95%" align="center">  
<!--====================================================================-->
<!--====================================================================-->
<!--====================================================================-->
<!--====================================================================-->
Line 60: Line 60:
</p>
</p>
<p>
<p>
-
<figure>
+
In parallel, the team also aims to develop a more flexible novel molecular detection system for the biosensor based on binding proteins and genetic probes.
-
<img style="float: left; margin: 0px 15px 15px 0px;" src="http://2014.igem.org/wiki/images/e/ec/Aachen_Infografik_sampling_biosensor.png" width="700" />
+
 
 +
<figure style="float: left; margin: 0px 15px 15px 0px;" >
 +
<img src="http://2014.igem.org/wiki/images/e/ec/Aachen_Infografik_sampling_biosensor.png" width="700" />
<figcaption>
<figcaption>
<i>Figure 1: Sampling of microorganisms (left) for the detection with a 2D biosensor (right)</i></figcaption>
<i>Figure 1: Sampling of microorganisms (left) for the detection with a 2D biosensor (right)</i></figcaption>
</figure>
</figure>
-
In parallel, the team also aims to develop a more flexible novel molecular detection system for the biosensor based on binding proteins and genetic probes.
 
</p>
</p>
<p>
<p>
Line 101: Line 102:
<tr>
<tr>
<td></td>
<td></td>
-
<td width="975px" align="center">
+
<td class="contentWidth" align="center">
-
<table class="transbg" width="975px"  cellspacing="0">
+
<table class="transbg" width="100%"  cellspacing="0">
<tr>
<tr>
-
<td class="contentcell" width="95%" height="400px" align="center">  
+
<td class="contentcell" width="95%" align="center">  
<!--====================================================================-->
<!--====================================================================-->
<!--====================================================================-->
<!--====================================================================-->
Line 145: Line 146:
<tr>
<tr>
<td></td>
<td></td>
 +
<td class="contentWidth" align="center">
-
<td align="center">
+
<table class="transbg" width="100%"  cellspacing="0">
-
 
+
-
<table class="transbg" width="975px"  cellspacing="0">
+
<tr>
<tr>
-
<td class="contentcell" width="95%" height="400px" align="center">  
+
<td class="contentcell" width="95%" align="center">  
<!--====================================================================-->
<!--====================================================================-->
<!--====================================================================-->
<!--====================================================================-->
Line 188: Line 188:
<tr>
<tr>
<td></td>
<td></td>
 +
<td class="contentWidth" align="center">
-
<td align="center">
+
<table class="transbg" width="100%"  cellspacing="0">
-
 
+
-
<table class="transbg" width="975px"  cellspacing="0">
+
<tr>
<tr>
-
<td class="contentcell" width="95%" height="400px" align="center">  
+
<td class="contentcell" width="95%" align="center">  
<!--====================================================================-->
<!--====================================================================-->
<!--====================================================================-->
<!--====================================================================-->

Revision as of 10:44, 3 June 2014

Welcome to the Teamwiki of the iGEM Aachen in 2014!


We are the first ever iGEM team in Aachen taking part in iGEM!



Cellock Holmes - a case of identity

Nosocomial infections - solving a real-world problem

Existing sterilizing methods fail to completely eradicate harmful pathogens on solid surfaces, resulting in a high number of patients (~3.2 million in Europe1) to be treated annually due to such infections. The European Union estimated that at least 800,000 of these cases would be preventable by implementing an intensive hygiene program, raising the necessity for a real-time detection technique. Current techniques fail since they are not effective, economical and rapid2.

Our iGEM Aachen team, consisting of life science, engineering as well as computer science students, aims to tackle these difficulties by developing a real-time pathogen detection technique, called ‘Cellock Holmes’, using SynBio and open hardware.

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.




Strategy and focus

While detection is the first step, characterization and quantification are equally important to reliably assess the danger of an infection.

Cellock Holmes is devised based upon a SynBio approach comprising of a two-dimensional biosensor and a measurement device . The two-dimensional biosensor (Figure 1) is designed to recognize quorum sensing molecules secreted by the pathogen cells and generate a distinct fluorescence signal.

In parallel, the team also aims to develop a more flexible novel molecular detection system for the biosensor based on binding proteins and genetic probes.

Figure 1: Sampling of microorganisms (left) for the detection with a 2D biosensor (right)

In parallel, the team also aims to develop a more flexible novel molecular detection system for the biosensor based on binding proteins and genetic probes.

These molecular approaches were selected as a reasonable spectrum from the established to novel and high-potential modules.

The Aachen team is committed to consider all aspects of the entire project, including biosafety. The living cells inside the measurement device are ensured to be killed by irradiation with strong UV light. In this way neither the sampled pathogens nor the genetically modified sensor cells can escape our biosensor unit.




Our biological approach

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.

You can follow our molecular approach in more detail by checking out our Biological Part/Labbook

The Device

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.

To learn more about our device check out Cellock Holmes.

The software Measurarty

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.

For more information check out our Computational Part.