Part:BBa_K2066039:Experience
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Applications of BBa_K2066039
In order to apply the concept of modulating a transfer function by having the ability to create a multimodal dose-response regulatory output function, we first wanted to reproduce the results from the Amit et al. paper. We managed to get plasmids with different number of TetO binding sites within the looping region and transformed them into the special 3.300LG strain (gift from Orna Atar). Our main plasmid had three TetR binding sites and was transformed with a pACT Tet helper plasmid, which allows the constitutive expression of LacI, TetR, and NRII2302. After inducing our system with different concentrations of aTc, we were able to replicate Amit’s step-like graph with four discrete states of expression as shown in Figure 1.
Figure 1. Reproduction of Amit et. al. work by WM iGEM 2016. The 3.300LG strain was transformed with the helper plasmid as well as the genetic circuit (52S) with three TetO binding sites affecting the looping propensity between the enhancer and promoter region, allowing for the modulation of discrete states of output. The data was plotted on the y-axis as the ratio of the fluorescence level measured in the presence of a given aTc concentration divided by the maximum fluorescence level. The shading represents the standard error of the mean.
However, Amit et. al. included a lacO site in front of their reporter, allowing them to turn “on” the synthetic enhancer suite with IPTG. In order the make the synthetic enhancer more useful for integration into a genetic circuit, we wanted it to be reliant on as few inducers as possible. Thus, we removed the LacI expression dependent feature from the synthetic enhancer by extracting only the functional coding region and promoter for NRII from the pACT Tet helper plasmid from Amit et al. Because NRII was part of an operon and thus only had the translational stop codon, but not a transcriptional terminator, we cloned in a B0015 double terminator at the end of the sequence. We then used Gibson Assembly to put the NRII insert into the UNS flanked Biobrick standard backbone and submitted it into the registry as Bba_K2066112. Subsequently, we cloned the functional NRII unit onto the same plasmid as our 52S construct (which has the three TetR binding sites) in an attempt to reduce number of plasmids required for transformations and thus keep the metabolic strain on the cell low.
In summary, the three modifications WM iGEM 2016 did to the Synthetic Enhancer constructs gifted by Amit et. al. were: 1.We moved the 52S construct with three TetR binding sites onto the BioBrick backbone flanked by the UNS regions for ease of cloning (BBa_ K2066120). 2. We then removed the synthetic enhancers system’s reliance on LacI/IPTG induction to make it more compatible with use in genetic circuits. 3. Finally, we put the helper NRII expression and the synthetic enhancer suite onto the same plasmid backbone to make it more compatible with the existing genetic circuitry in the cell.
After doing these modifications, we cotransformed 3.300LG strain with the novel 52S and NRII plasmid along with a plasmid that could constitutively express TetR (BBa_I739001). We induced the plasmid with varying concentrations of aTc and got results that reconfirmed the multimodal transfer functions seen in Amit et. al.
Figure 2. 3.300LG cells were transformed with an iGEM BioBrick standard part containing 52S (the synthetic enhancer suite with three tetO binding sites) and a plasmid constitutively expressing tetR. Data shows four discrete steps, representing the four different binding states of TetR modulated by the inducer concentration, which affects the looping propensity and thus, the overall quantitative expression of the output. The data was plotted on the y-axis as the ratio of the fluorescence level measured in the presence of a given aTc concentration divided by the maximum fluorescence level. The shading represents the standard error of the mean.
This is the first ever construction and characterization of a synthetic enhancer construct in iGEM. We have observed discrete levels of the regulatory output. Because we now have to the tool to regulate transfer functions to have more than just a binary “off” and “on” state, we can apply this concept to better understand biological systems, create biosensors that can detect distinct levels of concentration present and give an output accordingly, etc.
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