FRED

FRED stands for the Functional, Robust, Electrochemical Detector, and he is one of our mascots for the 2012 iGEM Calgary project. FRED is involved in creating a biosensor that will work in environments where traditional biosensors will not, such as turbid or anaerobic environments. This is important for oil sands applications as in the tailings ponds where detection of toxins is needed the environments are usually murky and any samples taken below a few meters are low in oxygen. While there are traditional methods for detection of toxins such as gas chromatography-mass spectrometry (GC-MS) or fourier transform infrared spectroscopy (FTIR), these techniques involve expensive machinery, skilled technicians, transport offsite and pre-processing before any data can be obtained. FRED will be able to do onsite testing in a matter of minutes with no advanced training required for users.

What is FRED made of?

Detecting

The first part of any biosensor is to be able to detect that a compound is present. This traditionally relies on promoters that are responsive to a certain compound. We have created a transposon library that will determine genetic elements that will activate in the presence of toxins. Various toxins such as carbazole, naphthenic acids, and DBT were used as model compounds for finding these toxin-sensitive elements.

Reporting

After being able to detect the compounds we need FRED to tell us about them. With the challenges imposed by the tailings ponds we decided to improve upon last year's single output electrochemical system to create a triple output system. This novel approach to electrochemical reporting has provided us with a fast and accurate measurement approach that can function in environments where fluorescence or luminescence would fail.

Modelling

Due to the novel nature of our electrochemical system there were a lot of questions that were raised in the design phase of this system. One big concern was whether the response would be fast enough. Rather than wasting reagents testing a multitude of timecourses a mathematical model was made to predict how the system would behave. The results from the modelling helped guide the wetlab experiments which in turn gave new data for the model to run on.

Prototyping

Having the biological systems working was only one part of the system though, as there still needs to be a physical device to use and software to interpret the raw data. With this in mind we also designed and built a prototype and accompanying software platform that works with FRED to detect toxins. This builds upon the rudimentary prototype of last year by adding in electrical filters, variable detection settings, diagnostic LEDs and miniaturizing it all at the same time.