Team:US AFRL CarrollHS/Model
Overview
The focus of modeling was to determine and implement a way to have a good signal on our paper-based chromium sensor. We used previous models to look into the effects that different ribosomal binding sites would have on gene expression, as our goal was to have the maximum reporter expression to yield a strong, visual sensor. More experimental testing of varying the ribosome binding site can be performed in the future, but we used the results of the models to determine the optimal RBS to implement into our ChrP-bFMO and ChrP-GFPa1 constructs.
Research
We implemented the modeling of two previous iGEM teams: the 2018 US_AFRL_CarrollHS team [1] and the 2016 William_and_Mary team [2]. Both models explored the result of varying the RBS on gene expression.
US_AFRL_CarrollHS used two different sets of RBSs, shown in Tables 1 and 2 to model relative gene expression. The results are displayed in Figures 1 and 2, corresponding to Tables 1 and 2, respectively. We saw that RBS34 resulted in the greatest expression.
We also looked into the findings of team William and Mary. Figure 3 from their 2016 model demonstrated that RBS 34 had the second greatest expression, but that RBS 34 has a quicker expression.
William and Mary also collaborated with two other teams, the University of Pittsburgh and Alverno, who both characterized the ribosomal binding sites in cell free systems. Their results are in Figures 4 and 5, respectively. RBS 34 was again shown to result in the top three highest gene expression.
Results and Discussion
The modeling created by 2018 team US_AFRL_CarrollHS and 2016 team William and Mary led us to implement RBS 34 in the design of our ChrP-RBS34-bFMO and ChrP-RBS34-GFPa1 constructs. Despite the addition of RBS34, there was no apparent expression of either reporter. For further experimental results, please see our Results page.
Modeling Attributions:
[1] https://2018.igem.org/Team:US_AFRL_CarrollHS/Model
[2] https://2016.igem.org/Team:William_and_Mary/RBS