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<p>The parameters the user can define are linked to experimental conditions but also to the mechanics of the simulation itself. These parameters are explained below. | <p>The parameters the user can define are linked to experimental conditions but also to the mechanics of the simulation itself. These parameters are explained below. | ||
<ul> | <ul> | ||
− | < | + | <li>The simulation time is the real life time that will be simulated</li> |
− | < | + | <li>The simulation step is the interval of time at which the system will be updated. It can be changed if users find it necessary to add more precision or make the simulation faster. </li> |
− | < | + | <li>The initial number of bacteria is the total number of transformed (donors) and not transformed (recipient) bacteria.</li> |
− | < | + | <li>The percentage of donor bacteria is the number of bacteria possessing a plasmid and can conjugate with other bacteria.</li> |
− | < | + | <li>The height and length of the grid (the simulation environment) are the number of squares that occupy the grid's height and length. By default it is 1000x1000 but in case of a very large number of bacteria it can be extented.</li> |
− | < | + | <li>The conjugation rate is the probability by which a donor will give a copy of its plasmid to a bacterium close to it (in the distance of one square</li> |
− | < | + | <li>The segregation loss is the probability that a donor cell will not pass its plasmid to its daughter cell during division</li> |
− | < | + | <li>The plasmid cost id the probability of death of a transformed bacterium because of the absence of selection pressure. By default it's 0 but it could be bigger in case, for example, of a bacterium with an antibiotic-resistance plasmid in an antibiotic-free environment.</li> |
</ul> | </ul> | ||
</p> | </p> |
Revision as of 16:46, 19 October 2016
As iGEMers we are responsible of using safe practices during our lab work in order to reduce the risks linked to harmful substances or organisms. A big number of iGEM teams use engineered E. coli or other bacteria in their projects and their release in the environment is a risk that should be prevented. However, there are always limits to prevention and the use of a tool to predict the risk of an eventual release of bacteria in the laboratory could help reinforce the biosafety in an alternative way. This is why we created a software that can allow users to simulate the growth of transformed bacteria for a given set of parameters defined by the user. The user can input an initial number of bacteria that would be released on a surface, the percentage that are transformed, parameters linked to the are of the simulated surface and parameters linked to plasmid loss and plasmid transfer.
Our tool runs an agent-based simulation. The agents are bacteria which can be transformed or not and the environment is a grid of squares that represent each 1µm² of a solid surface. Each square can contain one bacterial cell diractly in contact with the surface or piled up on another bacterium in contact with the surface. The piling up is limited by the user. A certain concentration of an energy source for the bacteria can be present on the grid. Time is concrete so bacteria repeat a schedule of actions at each time step. These actions are consuming nutrients, metabolizing them, dividing or dying if certain conditions are met. To simulate the growth of bacteria we used two different approaches that are explaind in the section model. In this section we will concentrate on the parameters that the user can define and how that can change the result they obtain. We opted for a simple user interface (figure 1) in gtkmm as the language we used for the simulation is C++. It was one of our principal goals to make an interface so that non-programmers could run our application without problems. The parameters the user can define are linked to experimental conditions but also to the mechanics of the simulation itself. These parameters are explained below.
Overview
The simulation
The user interface