Difference between revisions of "Team:Bielefeld-CeBiTec/Software"

 
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<h1 style="margin-bottom: 0px">Our App</h1>
 
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<p>Fluorescence Quantification via smartphone</p>
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<p>Fluorescence Quantification via Smartphone</p>
 
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           <h2>The Problem</h2>
 
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<div><p>Fluorescence is a widely used output signal in many microbiological and biotechnological applications. Green fluorescent protein (GFP) is among the most frequently used reporter proteins and has been worked with in numerous iGEM projects. Nevertheless fluorescence can hardly be detected by the bare eye and quantification turns out to be impossible. Since our test strip determines the quality of drinking water and other beverages, it is utterly important to detect even small signals. Furthermore, we noticed that many heavy metals decrease the functionality of the cell-free protein synthesis, thereby artificially lowering the fluorescence output and potentially leading to false-negative test results, that could cause the uptake of toxic substances.
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<div><p>Fluorescence is a widely used output signal in many microbiological and biotechnological applications. Green fluorescent protein (GFP) is among the most used reporter proteins and has been used in numerous iGEM projects. Nevertheless fluorescence can barely be detected by the eye and quantification turns out to be nearly impossible.
 
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           <h2>Our Solution</h2>
 
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<div><p>We solved this problem with a smartphone app combined with a novel fluorescence detection approach based two filters placed in front of the camera and the flash of the smartphone. <br>
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<div><p>We solved this problem with a smartphone App. The App determines the median of the greenvalue of a area of pixels in the sensorspot and compares it to the pixels of the negative control (the not induced sensor). If the ratio of a sample and the negative control is above a certain theshold (10%), valid biosensor signal is detected. Additionally it is checked whether the value for the positive control (drop of sfGFP) is above a certain value, thereby confirming the functionality of the biosensor. Furthermore the App displays specific information regarding the different heavymetals and date rape drugs to inform the user.
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Two test strips will be required for each test, one that is wetted with clean water and a second one incubated with the sample. Since both strips contain a positve control, that should always generate a sfGFP signal, effects of heavy metals and other contaminants on the CFPS can be measured by comparison of the two positive controls. The generated correction factor is applied to the values of the other spots. <br>
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The fluorescence quantification algorithm determines the median of the green value of some pixels in the sensorspot and compares it to those of the negative control. If the ratio of real sample and negative control is above a certain threshold, the app detects a contamination. It also checks whether the value for the positive control is above a certain value, thereby confirming the functionality of the test. Furthermore it contains specific information regarding the different heavy metals and date rape drugs.
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For easy handling a correct positioning of the smartphone and the biosensor test strip, we designed and printed a measurement case.
 
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<img src="https://static.igem.org/mediawiki/2015/b/b2/Bielefeld-CeBiTec_app1small.png">
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<figcaption>A photo of our test strip generated by a typical smartphone using an ideal filter combination to detect fluorescence of sfGFP.</figcaption></center>
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<img src="https://static.igem.org/mediawiki/2015/8/80/Bielefeld-CeBiTec_app2small.png">
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<figcaption>Screenshot of the app. It shows the pixels it took into account for the calculation in red, so the user can check, whether the pixels chosen are correct. Furthermore, it provides the values it calculated for the greeness of the spot.</figcaption></center>
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<img src="https://static.igem.org/mediawiki/2015/e/e0/Bielefeld-CeBiTec_app3small.png">
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<figcaption>The application is adapted to the box shown in the picture. The box provides the ideal environment for capturing pictures under reproducible conditions. The application will calculate whether a contamination is present and give out an list of the contaminants in the water sample.</figcaption></center>
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<a type="button" class="btn btn-default btn-next" href="https://2015.igem.org/Team:Bielefeld-CeBiTec/Software/SourceCode"><img src="https://static.igem.org/mediawiki/2015/5/51/Bielefeld-CeBiTec_iGEM_logo.png"><p>See the source code!</p></a>
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<a type="button" class="btn btn-default btn-next" href="https://2015.igem.org/Team:Bielefeld-CeBiTec/Software/SourceCode"><img src="https://static.igem.org/mediawiki/2015/c/cb/Bielefeld-CeBiTec_App_transparent.png"><p>See the source code!</p></a>
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<a type="button" class="btn btn-default btn-next" href="https://2015.igem.org/Team:Bielefeld-CeBiTec/Project/Biosafety"><img src="https://static.igem.org/mediawiki/2015/5/51/Bielefeld-CeBiTec_iGEM_logo.png"><p>Ok, so my GMOs are in a box and everything is safe?</p></a>
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<h2>Software</h2>
 
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<h4>Note</h4>
 
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<p>In order to be considered for the <a href="https://2015.igem.org/Judging/Awards#SpecialPrizes">Best Software Tool award</a>, you must fill out this page.</p>
 
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<p>Regardless of the topic, iGEM projects often create or adapt computational tools to move the project forward. Because they are born out of a direct practical need, these software tools (or new computational methods) can be surprisingly useful for other teams. Without necessarily being big or complex, they can make the crucial difference to a project's success. This award tries to find and honour such "nuggets" of computational work.</p>
 
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If you are working on software as your main project, please join the software track. If you are creating software as an addition to your main project, please apply for this award.
 
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Here are a few examples from previous teams:
 
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<li><a href="https://2013.igem.org/Team:TU-Munich/Results/Software">TU Munich 2013</a></li>
 
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<li><a href="https://2014.igem.org/Team:Heidelberg/Software">Heidelberg 2014</a></li>
 
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<li><a href="https://2014.igem.org/Team:Aachen/Project/Measurement_Device#Software">Aachen 2014</a></li>
 
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Latest revision as of 13:08, 16 September 2015

iGEM Bielefeld 2015


Our App

Fluorescence Quantification via Smartphone

The Problem

Fluorescence is a widely used output signal in many microbiological and biotechnological applications. Green fluorescent protein (GFP) is among the most used reporter proteins and has been used in numerous iGEM projects. Nevertheless fluorescence can barely be detected by the eye and quantification turns out to be nearly impossible.

Our Solution

We solved this problem with a smartphone App. The App determines the median of the greenvalue of a area of pixels in the sensorspot and compares it to the pixels of the negative control (the not induced sensor). If the ratio of a sample and the negative control is above a certain theshold (10%), valid biosensor signal is detected. Additionally it is checked whether the value for the positive control (drop of sfGFP) is above a certain value, thereby confirming the functionality of the biosensor. Furthermore the App displays specific information regarding the different heavymetals and date rape drugs to inform the user. For easy handling a correct positioning of the smartphone and the biosensor test strip, we designed and printed a measurement case.

A photo of our test strip generated by a typical smartphone using an ideal filter combination to detect fluorescence of sfGFP.
Screenshot of the app. It shows the pixels it took into account for the calculation in red, so the user can check, whether the pixels chosen are correct. Furthermore, it provides the values it calculated for the greeness of the spot.
The application is adapted to the box shown in the picture. The box provides the ideal environment for capturing pictures under reproducible conditions. The application will calculate whether a contamination is present and give out an list of the contaminants in the water sample.

Download it!

See the source code!