Team:UNILausanne/Contribution
Contributions
Repressilator
In order to test the repressilator, we have adapted a protocol that can be reused by the next teams. It makes use of more accessible lab equipment, making this system more attainable in the iGEM universe. It allows the measurement of oscillations produced by the repressilator over an extended time period by keeping the cells in an exponential phase, therefore allowing the oscillation to remain active.
Parts
In regards with the kill switch, we have characterized already existing parts such as ccdA – Antitoxin in ccdA/ccdB system (BBa_K1075032), Colicin E2 immunity protein (BBa_K1976027) and Colicin E2 DNase domain “miniColicin” (BBa_K1976048) . We demonstrated that the toxin-antitoxin systems enable us to efficiently control cell viability. By doing so, we performed extensive measurements on the ccdB/ccdA (pKA1 plasmid) and miniColicin E2/IM2 (pKC1 plasmid) parts, which were previously uncharacterized in the iGEM Part Registry.
By doing so, we laid the foundations and facilitated the implementation of a kill switch system within the biosafety context of future iGEM projects.
Modelling
For our contribution we made our Python scripts on the ODE repressilator, IBM repressilator and kill switch readily available for other teams to use on github. The first model uses ordinary differential equations to model the oscillations caused by the repressilator. The individual-based model (IBM) simulates individual bacteria as python dictionaries including a list of the three proteins of the repressilator and a counter to track the divisions that a bacterium has undergone. Then, we set how bacteria update their proteins, divide, or die. We have two different configurations of the model depending on whether we store our simulated bacteria in a list (one dimension) or in a grid (two dimensions). The IBM has been characterized by reproducing findings of prior deterministic models and experiments. We propose it as a modelling framework to understand the effect of single cells on the population signal of the repressilator system, but could be easily adapted to other applications. And finally, we began exploring the kill switch dynamics with a model that still needs to be perfected, but that could bring insights into the design of a kill switch. You can see each model in more detail here.
