All iGEM projects involve modified organisms. When we work with those organisms, the question of confinement is essential to prevent their spreading out of the lab. Even if each team thinks about the best tool to answer this question, our team has decided to think about the worst situations.

What happens when a bacterial population escapes from our test tubes ?

To answer this question, we decided to create a computational simulation model in order to see :

• the number of bacteria that could proliferate on a lab bench
• what percentage of these bacteria would able to maintain their plasmid

The presentation of our work will be done in different sections. First, we are going to explain our approach in choosing a simulation model and our reasons for our choices. In the next section, we will describe how we have created our model and explain its initialization. After this, we will explain our mathematical choices to modelize bacterial growth and plasmid loss. Finally, we will make an assessment of our model, explain how we have validated it and give our perspectives for this project.

1. Multi-agent modelling

The definition

In informatics, a multi-agent system aims to represent intelligent agents which interact with one another and with a specific environment. In our case, our agents are bacteria, dispersed randomly on a grid (our environment). The bacteria are submitted to successive actions such as growth or division, and have specific attributes such as a an individual cell mass, or more importantly a plasmid. Our model helps us to know if our bacteria is able to survive on this specific environment and if they can maintain their plasmid in specific conditions.
This model is interesting to use because it modelizes how act the agents in the environment and how interact the environment with the agents.