Modelling - iGEM Bordeaux 2012

iGEM - Bordeaux - Conception

We choosed to create 4 operons:

  • the top three permit cellular communication and to see phenotypes of the cells.
  • the last one containes genes to allow signal transduction (to other neighbor cells).

  • Each of the top three operons can respond specificly to a quorum sensing (QSS) and respond by another QSS giving rise to a chain reaction , to all near bacteria.

    The next figure represents the different genetic constructions that we will try to make.

    Principle and rules

    Each cell of the grid can be in 4 differents states: state1, state2, state3, state4 (state4 being state 1 and 2 at the same time). On the following steps the state of the cell is determined by the action of other close cells.

    The next rules are applied on each cells of the grid for each turn:

  • if a bacteria is in a “virgin” state and have close neighbor(s), she is candidate to be activated.
  • if a bacteria is in a “virgin” state and haven't close neighbor(s), she will remain into her “virgin” state.
  • if a bacteria is in an “activated” state and have close neighbor(s), she has an opportunity to change neighbor state's.
  • Definition of a “state”

    A “virgin” cell has a state at 0 at the begining. Each cells have severals caracteristics wich are non activated when the simulation begin (excepted for their coordinate x and y).
    Here is an exemple of a grid with x cells in beige:

  • At t = 0, cells are randomly placed on the grid.
  • At t = 0', some cells can randomly change state at the begining, you can see A in blue, B in red, C in green.
  • At t = 1, cells located in the area stimulated (black circle) by the first stimulus (light) are going to evolve in state 1 and these cells are colored in blue.
  • At t = 1', you can see a zoom in area. Three cells are visible two in state 1 (cell number 1 and 2) and one in state 0 (cell number 3). The third cell beeing close to cells in state 1 might be able to become in state 2. If her genes are all fonctionals (operons, genes, receptors ...) she will be in state 2.
  • At t = 2, cell number 3 has passed in state 2, she will now be able to transform her neighbor to state 3.
  • Characteristics of the algorithm

    Size of the grid : infinite, the size is choosed by the user (file
    Step of time (t) : new step of time correspond to the addition of the function stimulus_factor().
    State of the cell :

  • state 0 : beige
  • state 1 : blue
  • state 2 : red
  • state 3 : green
  • state 4 : black

  • Initialisation : cells are placed on the grid depending on the information the user has choosed (file
    First simulation : cells become in state 1.
    Next simulations : cells are changing their state depending on their characteristics, neighborhood, metabolites, etc.