Setup

Kill Switch (Figure 5)

We manually reviewed the wiki pages for the 110 Gold Medal iGEM teams from the 2017 competition. We flagged those teams who indicated that they contemplated or actually implemented a kill switch in their projects. 15 of them mentioned a kill switch, but only 12 were picked as having actually attempted an implementation. All teams can be found in this spreadsheet. We then reviewed their descriptions of their kill switches to determine which BioBricks they used for implementation, some of which were novel parts submitted for addition to the registry. Based on their descriptions of the triggering conditions and the specific mechanisms causing cellular death, we manually built the feature model. We calculated the number of products using FeatureIDE (882 products).

Cell to Cell Signalling (Figures 6 & 7)

To create the cell-to-cell signalling model we manually analyzed all basic parts within the Cell-cell signaling and quorum sensing function category on the Registry of Standard Parts. Two categories of required parts were found in separate webpages: Ribosome Binding Sites and Terminators. The developed feature model can be seen below (click on the image to view the full model).

Due to the scale of this model we had to use FaMa Version 1.1.2 [1] to calculate the number of products. The input files for each model can be found in our artifacts can be found here (the FaMa tool downloads can be found here). Due to the scale we split the model into the three top level features (sender, receiver, reporter) and ran them separately. The total number of products was found by multiplying them. The cell-to-cell signalling model was run on an HPC cluster with 35GB and java was given 32GB (java -jar ./lib/FaMaSDK-1.1.1.jar -xmx 32). The sender and receiver each have 11,448,000 products and the reporter has 5,724,000 products. Multiplying 11,448,000 * 11,448,000 * 5,724,000 = 7.50169 × 10²⁰ products for the whole model.