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

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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, which 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 mostly 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 impossible.
 
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           <h2>The Solution</h2>
 
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<div><p>We solved this problem with a smartphone app combined with a novel fluorescence detection approach based on 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. It determines the median of the greenvalue of some pixels in the sensorspot and compares it to these of the negative control. If the ratio of real sample and negative control is above a certain theshold, 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 heavymetals and date rape drugs.
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 positive 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 a real sample and the 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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Revision as of 20:07, 14 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 mostly 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 impossible.

The Solution

We solved this problem with a smartphone App. It determines the median of the greenvalue of some pixels in the sensorspot and compares it to these of the negative control. If the ratio of real sample and negative control is above a certain theshold, 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 heavymetals and date rape drugs.