Modeling
For our two-dimensional biosensor, we thought of different methods to generate a faster and stronger fluorescent response from weak promoters. In our molecular approach (left) to detect P. aeruginosa, a fusion protein of GFP and the dark quencher is cleaved by the very specific TEV protease which is introduced behind the weak quorum sensing promoter.
To validate our hypothesis, we developed a model of our molecular approach using the CAD tool TinkerCell, see figure below (Chandran, Bergmann and Sauro, 2009).
In the above figure, we compare the response time of the fluorescence signal between our theoretical system and a traditional biosensor, we included a direct expression of GFP in the same plot. In the results shown above, the strength of the promoter used for the direct GFP expression (traditional approach) is twice as high as the strength of the promoter upstream of the TEV coding sequence in our new approach. Despite a weaker promoter, a higher GFP concentration is generated in the model of the novel biosensor, predicting a quicker response time of our system.
The model predicted that our approach should be an improvement over the commonly used direct expression, so we proceeded with the clonings and assembled plasmids to test the system.
Due to the complexity of the quorum sensing circuit, we assembled an IPTG-inducible TEV protease instead of the 3-oxo-C12-HSL-inducible version.
Although the modeled system and the existing double plasmid system differ regarding the induction mechanism, the correlation was high. However, since the final 3-oxo-C12-HSL inducible construct could not be built in time, a new model was designed according to the existing and functional IPTG-inducible system.
The model was fitted to the data gathered from the characterization experiment conducted in shake flasks. Additionally, the data from the characterization experiment of the double plasmid construct K1319014 + K1319008 in the chip system was included in the plot. The data was derived from the plate reader output of the four central spots of the chip. The background from the non-induced chip was substracted from the fluorescent response to correct the data and avoid effects from cell growth leading to wrong signal strengths. The development of the fluorescence is presented here.
It is shown that the fluorescent response in chips occurs later than in the characterization experiment in shake flasks. This is explainable as the solid agar chip poses a greater diffusion barrier than liquid medium as used in the shake flasks. Further, the rate of fluorescence increase over time is smaller than in the characterization experiments in shake flasks. The reason is that the sensor cells need oxygen to produce GFP. However, they are embedded in solid agar in which the amount of available oxygen is lower compared to a shaking liquid system.
The right prediction of the outcome of the characteization experiments by the model shows that our molecular approach is valid. A faster and stronger fluorescent signal could be proven both theoretically and empirically.
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