Contribution

Wet Lab

Adding to Reporter Promoter Documentation

We documented our attempted clone BBa_R0051 fused with mCherry in order to characterize its expression profile. We were unsuccessful in attempting to clone it properly and documented why we think the process failed on the parts page.

New Parts

For our new parts, our iGEM team is adding new parts for the iGEM registry: BBa_4341001, BBa_K4341000, BBa_K4341003, and BBa_K4341004. These parts were created in order to create a fusion promoter with the rrnB-P1 promoter to have very high expression. Unfortunately because of time and resource constraints we were unable to successfully clone these into a pET-based plasmid, but we hope that future teams may be able to use these designs for high expression use cases. We were able to isolate these four inserts via PCR and digestion successfully as shown in our results page.

2D Phage Puzzle

Our team made a 2D phage puzzle which we displayed at Boonshoft and COSI. We were able to explain to our audience why selecting the correct receptors to bind to bacteria was vital to our fight against sepsis using phage. We found that giving our audience a physical representation of what we were explaining helped their understanding, especially the younger audiences we interacted with. The pdf that can be downloaded here displays the assembly drawings for our 3D printed phage puzzle pieces. We went through two iterations to find the ideal scaling for the puzzle. Initially, our puzzle pieces were larger; however, we found that it was a danger to the younger audiences since they had sharp edges and were heavy. The larger pieces were also harder for younger audiences to connect the phage to bacteria. Therefore, for the second iteration, we halved the size of the puzzle. The pieces were lighter/safer, the cost was greatly reduced (~$300 to ~$100), and younger audiences were more responsive to the puzzles. Hopefully, if other teams do something similar they're able to apply some of the things we learned to their displays.

Figure 1. Bacteria (left) and Phage (right) Model Visualizations




Population, Bioreactor, and Cocktail Models

The bioreactor model contains the very beginning aspects of developing a control system. Teams can take the thinking we used to develop the dynamic model for concentration and use it to create other dynamic models. For example, teams can use energy balances to create a dynamic model for temperature. Building a schematic as a reference and deciding on assumptions, similar to how we did it, will help direct model development. To see more, check out the modeling page here.

The phage and bacteria population model can be used by other teams that are trying to determine how population changes for a specific organism and bacteria at unsteady state. If the team's project does not deal with phage and bacteria, our model can be used a starting point. The validity of the results when using the exact same code would be questionable, so they would need to reassess the differential equations used; however, if the organism and bacteria interaction mimic phage and bacteria's relationship, then the model can be used as a rough estimate of how population changes. You can download the code here and to see more, check out the modeling page here.

The phage cocktail model can be used by other teams as a starting point for other cellular automata projects. Cellular automata is a diverse modeling method that can also be quite complicated. Using our well commented code as a skeleton, teams can add their own assumptions, states, rules, and parameters to fit whatever they want to show. Designing and implementing a cellular automata of their own can help teams show complicated concepts in simple terms or visually show something that is hard to picture. You can download the code here and to see more, check out the modeling page here.

Phage Database

We have also worked on finding more bacteriophages that are associated with sepsis-related bacteria. All of the information we have researched has been compiled and added to a database of potential phages that we began with our project last year. Organizing this information allows physicians to save time finding the right phage for different patients and other teams to easily access phage that infect sepsis-related bacteria.